https://wiki.aardrock.com/api.php?action=feedcontributions&user=Just&feedformat=atomAardRock Wiki - User contributions [en]2024-03-28T15:00:12ZUser contributionsMediaWiki 1.37.1https://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=2112LogboekJustBoerlage2006-05-30T13:10:51Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
<br />
<br />
{| <br />
|Datum || Van || Tot || Duur || Cumulatief || Activiteit <br />
|-<br />
|08-02-06 || 13:00 || 16:00 || 03:00 || 03:00 || Vergadering INFOSP en AardRock<br />
|- <br />
|13-02-06 || 15:00 || 16:30 || 01:30 || 04:30 || Vergadering INFOSP <br />
|- <br />
|14-02-06 || 15:00 || 18:00 || 03:00 || 07:30 || XP game <br />
|-<br />
|20-02-06 || 15:00 || 16:30 || 01:30 || 09:00 || Vergadering INFOSP <br />
|- <br />
|21-02-06 || 15:00 || 17:00 || 02:00 || 11:00 || Vergadering AardRock <br />
|- <br />
|27-02-06 || 15:00 || 17:00 || 02:00 || 13:00 || Vergadering INFOSP <br />
|- <br />
|28-02-06 || 15:00 || 17:30 || 02:30 || 15:30 || Vergadering AardRock <br />
|- <br />
|05-03-06 || 19:00 || 22:30 || 03:30 || 19:00 || Gezocht naar medische bronnen <br />
|- <br />
|06-03-06 || 12:00 || 15:00 || 03:00 || 22:00 || Emails gelezen; medische bronnen verwerkt <br />
|-<br />
|06-03-06 || 15:00 || 17:00 || 02:00 || 24:00 || Vergadering INFOSP <br />
|-<br />
|07-03-06 || 15:00 || 17:30 || 02:30 || 26:30 || Vergadering AardRock <br />
|-<br />
|12-03-06 || 18:00 || 21:00 || 03:00 || 29:30 || Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
|-<br />
|14-03-06 || 12:00 || 15:30 || 03:30 || 33:00 || Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
|-<br />
|20-03-06 || 12:30 || 16:30 || 04:00 || 37:00 || Voedingtabel info verwerken; vergadering INFOSP <br />
|-<br />
|21-03-06 || 10:30 || 17:00 || 06:30 || 43:30 || Story 23, Notulen maken; <br />
|-<br />
|22-03-06 || 13:00 || 15:30 || 02:30 || 46:00 || Story 21, praatje met hans <br />
|-<br />
|27-03-06 || 11:30 || 16:30 || 05:00 || 51:00 || Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
|-<br />
|28-03-06 || 12:30 || 17:00 || 04:30 || 55:30 || Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
|- <br />
|03-04-06 || 15:00 || 16:00 || 01:00 || 56:30 || Mail lezen en vergadering <br />
|-<br />
|03-04-06 || 23:00 || 24:00 || 01:00 || 57:30 || Notulen maken <br />
|-<br />
|04-04-06 || 13:30 || 16:30 || 03:30 || 61:00 || Verwerken gegevens van GI<br />
|-<br />
|29-04-06 || 12:00 || 14:00 || 02:00 ||63:00||Lezen van dieet relateerde info<br />
|-<br />
|30-04-06 || 12:00 || 15:00 || 03:00 ||66:00||Lezen van dieet relateerde info<br />
|-<br />
|02-05-06 || 10:00 || 19:30 || 09:30 || 75:30||ontwikkeling advieserend model<br />
|-<br />
|09-05-06 || 9:30 || 17:00 || 07:30 || 83:00 || ontwikkeling advieserend model, lezen maven hfd 1& 2<br />
|-<br />
|11-05-06 || 14:00 || 16:00 || 02:00 || 85:00||gelezen maven hrd 1& 2<br />
|-<br />
|21-05-06 || 20:00 || 22:00 || 02:00 || 87:00|| ruwe schets gemaakt van nieuwe ideeen<br />
|-<br />
|23-05-06 ||10:00 ||16:00 ||06:00 || 93:00 ||Uitwerken nieuwe ideeën voor het advieserend model, offerte nevo-tabel aanvragen<br />
|-<br />
|24-05-06 ||13:00||15:00||02:00||95:00 || Bellen naar AMC en VU<br />
|-<br />
|25-05-06 ||11:00||14:00||03:00||98:00 || Inlezen k-NNA<br />
|-<br />
|26-05-06 ||14:00||14:30||00:30||98:30 || Bellen naar AMC<br />
|-<br />
|26-05-06 ||18:00||20:00||02:00||100:30 || Uitwerken bevindingen k-NNA<br />
|-<br />
|27-05-06 ||20:00||21:00||01:00||101:30 || Inlezen k-NNA<br />
|- <br />
|29-05-06 ||11:30||14:30||3:00||104:30 || Bellen naar ACM, VU en voedingscentrum <br />
|-<br />
|30-05-06 ||09:00||11:00||2:00||106:30 || Inlezen andere instance based algoritmen<br />
|-<br />
|30-05-06 ||12:00|| || || ||Uitwerken bevindingen k-NNA<br />
|-}</div>Justhttps://wiki.aardrock.com/index.php?title=Agenda20060530&diff=2109Agenda200605302006-05-30T12:28:11Z<p>Just: </p>
<hr />
<div>* Opening<br />
* Vaststelling agenda<br />
* Goedkeuring notulen<br />
* W.H.J.G.E.W.G.J.D (Wat heb je gedaan en wat ga je doen?)<br />
* Testdata<br />
* W.V.T.T.K.<br />
* Rondvraag<br />
* Volgende vergaderingen<br />
* Sluiting</div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2108Neural network2006-05-30T12:21:09Z<p>Just: extra comment</p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm (lazy learning, local)<br />
* Locally weigthed regression (lazy learning, global)<br />
* Radial basis funcions (eager learning, local)<br />
<br />
<br />
== k-nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the preferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
For using k-nearest neighbor algorithm (k-NNA) you need a n-dimensional space. The space is build up from the instances used as trainingsdata. N is the number of attributes were the instances are composed of. When a new instance x (test-data) with attributes <math>(a_1 (x),a_2(x) \ldots a_n(x))</math> is put into the system, the system form a query that looks for the near instances in the n-dimensional space. For each instance the distance <math> d(x_i,x_j) </math>is measured by:<br />
<br />
<math>d(x_i,x_j) \equiv \sqrt{\sum_{r=1}^n (a_r(x_i)-a_r(x_j))^2}</math><br />
<br />
This is the Euclidean distance. This will be done for <math> x_1 \mathrm{ till }x_k </math>. The k-nearest instances are then add up and divided by k to calculate the mean.<br />
<br />
<math>\hat{f}(x_q) \leftarrow \frac{\sum _{i=1}^k f(x_i)}{k}</math><br />
<br />
Er is een formule die berekent hoe groot k mag zijn in verband met de grootte van de buurt waarin men zoekt, maar die heb ik nu niet bij me. Die volgt later.</div>Justhttps://wiki.aardrock.com/index.php?title=Make_combinations&diff=2107Make combinations2006-05-30T12:15:56Z<p>Just: extra baddy</p>
<hr />
<div>There are 2 ways for searching in de basebase for possible entrees that add to the advise the system can give.<br />
* direct search<br />
* fussy search<br />
<br />
I show the meanings with an example.<br />
<br />
my entries at 8:40 are<br />
<br />
* 8:30 2 slice of cheese<br />
* 8:30 2 slice of white bread<br />
* 8:30 1 glass of milk<br />
* 8:35 1 apple (30 g)<br />
* health status: normal<br />
<br />
question to the system. how much insulin do i have to inject if i want that my concentration glucose in blood is around 5 mmol/l at 11:00.<br />
<br />
In the system happens a few things:<br />
* First a new entry is set in the database.<br />
* second it calculates the amount of carbonate of the foodintake<br />
* Third it makes a query of the question to search with in the database<br />
<br />
This query is not a straightforward thing. First it will search directly at entries in the past. If it find a match then this is the most trustfull advise the system can give. This in relation to the definition of reproduction. If you do an experiment in the past and you know the results and you do the experiment again. You can expect to get the same result. To give the query a fair change to find entrees, the query have to losen up. How much has to be done experimented empericaly.<br />
for the example this means:<br />
<br />
look for: 8:15 - 8:45 350-400 gr carbonate(with white bread, cheese, milk and apple as food-intake)<br />
10:30 - 11:30 4,5 - 5,5 mmol/l glucose units insuline<br />
<br />
Lets say it finds entries from previous entries in past. with amounts of units insuline. We can present the mean to the user, if the difference is not signifide, and the entries where the advise is build from is presented to the user. If the user is not satisfied it can say that to the system and it will [[narrow it searchparameters]]. The problem is which one so thats still a design thought.<br />
<br />
But what if it cannot find a match? It will search fussy. With this search it broads it search window (see the figure what i mean). it starts with broading 1 parameter of the query, untill it finds a entry that match. then it start anew and broads another parameter. when all the paramaters are done it starts broading 2 parameters, untill it finds a match. Last round will be that all the parameters will losen up untill it finds an entry that match. The broadingsteps are fixed and has to be emperical assessed.<br />
<br />
What do we have? a collection of entrees with different kinds of answers. But which one is the most rightnest or is a couple of entries from different searchround together beter then just from 1 searchround? A learning system as a [[neural network]] could profide that answer. The advise is of less value than a direct search. The user could have the abbility to see which enties the strongest influens had on the advise. Thats simply showing the entries of a searchround with the highest weights.<br />
<br />
At the end the system could ask the user to check it's glucose level in blood at some point in time. This to reference that the advise was a good or bad one so it can ajust it weights.<br />
<br />
The reason to calculate the carbonate load is: <br />
* in direct search measures of intake can differ, but the carbonate load not. In the example the apple can weight 50 g. but de carbonate load is allmost the same.<br />
* in fussy search if we losen the foodintake it goes like this:<br />
*2 slice of cheese 2 slice of cheese<br />
*2 slice of bread 2 slice of bread<br />
*1 glass of milk<br />
*350-400 gr carbonate 350-400 gr carbonate<br />
<br />
The amount of carbonates is important to [[find alternatives]]. In other words you eat different products, but the carbonate stays the same.<br />
<br />
[[Image:puntenwolk1.jpg]]<br />
* red dots: entries found by direct search<br />
* blue dots: entries found when broading the searchparameters, food intake and time of foodintake<br />
* clear square: searchwindow by direct search<br />
* unclear square: searchwindow broadend after one fussy searchround.<br />
<br />
<br />
== The goods and the bad's ==<br />
<br />
'''The good things about this approtess are:'''<br />
<br />
* It can handle inconsequent users. If a day is forgotten it can still give advise.<br />
* Close to what the user allready does. Fill in his logbook en looks up when things went wrong.<br />
* Easy to implement.<br />
* can start from the beginning and the more entries it has the better it starts to function.<br />
* advise is local/personal.<br />
<br />
'''The bad things:'''<br />
<br />
* Instance based learning is a very simple way of learning. with large databases it is better to use basian learning.<br />
* There is no involvement from the outside world.<br />
* Extra knowledge from other users are not shared.<br />
* The k-nearest neighbor algorithm is slow, because it is a lazy learning algorithm, it calulate for every new instance the hypothese space.</div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2106Neural network2006-05-30T11:59:03Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm (lazy learning, local)<br />
* Locally weigthed regression (lazy learning, global)<br />
* Radial basis funcions (eager learning, local)<br />
<br />
<br />
== k-nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the preferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
For using k-nearest neighbor algorithm (k-NNA) you need a n-dimensional space. The space is build up from the instances used as trainingsdata. N is the number of attributes were the instances are composed of. When a new instance x (test-data) with attributes <math>(a_1 (x),a_2(x) \ldots a_n(x))</math> is put into the system, the system form a query that looks for the near instances in the n-dimensional space. For each instance the distance <math> d(x_i,x_j) </math>is measured by:<br />
<br />
<math>d(x_i,x_j) \equiv \sqrt{\sum_{r=1}^n (a_r(x_i)-a_r(x_j))^2}</math><br />
<br />
This is the Euclidean distance. This will be done for <math> x_1 \mathrm{ till }x_k </math>. The k-nearest instances are then add up and divided by k to calculate the mean.<br />
<br />
<math>\hat{f}(x_q) \leftarrow \frac{\sum _{i=1}^k f(x_i)}{k}</math></div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2105Neural network2006-05-30T11:38:46Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm.<br />
* Locally weigthed regression<br />
* Radial basis funcions<br />
<br />
<br />
== k-nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the preferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
For using k-nearest neighbor algorithm (k-NNA) you need a n-dimensional space. The space is build up from the instances used as trainingsdata. N is the number of attributes were the instances are composed of. When a new instance x (test-data) with attributes (a1 (x) ... an(x)) is put into the system, the system form a query that looks for the near instances in the n-dimensional space. For each instance the distance d(x_i,x_j)is measured by:<br />
<br />
<math>d(x_i,x_j) \equiv \sqrt{\sum_{r=1}^n (a_r(x_i)-a_r(x_j))^2}</math><br />
<br />
This is the Euclidean distance.<br />
<br />
<math>\hat{f}(x_q) \leftarrow \frac{\sum _{i=1}^k f(x_i)}{k}</math></div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2104Neural network2006-05-30T11:18:56Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm.<br />
* Locally weigthed regression<br />
* Radial basis funcions<br />
<br />
<br />
== k-nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the preferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
k-nearest neighbor algorithm<br />
<br />
<math>d(x_i,x_j)= \sqrt{\sum_{r=1}^n (a_r(x_i)-a_r(x_j))^2}</math><br />
<br />
<math>\hat{f}(x_q) \leftarrow \frac{\sum _{i=1}^k f(x_i)}{k}</math></div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2103Neural network2006-05-30T11:13:31Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm.<br />
* Locally weigthed regression<br />
* Radial basis funcions<br />
<br />
<br />
== k-nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the preferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
k-nearest neighbor algorithm<br />
<br />
<math>d(x_i,x_j)= \sum_{r=1}^n (a_r(x_i)-a_r(x_j))^2</math><br />
<math>f(x_q) \leftarrow \frac{\sum _{i=1}^k f(x_i)}{k}</math></div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2102Neural network2006-05-30T11:12:29Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm.<br />
* Locally weigthed regression<br />
* Radial basis funcions<br />
<br />
<br />
== k-nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the preferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
k-nearest neighbor algorithm<br />
<br />
<math>d(x_i,x_j)= \sum_{r=1}^n (a_r(x_i)-a_r(x_j))^2</math><br />
<math>f(x_q) \leftarrow \fract{\sum _{i=1}^k f(x_i)}{k}</math></div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2101Neural network2006-05-30T11:09:18Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm.<br />
* Locally weigthed regression<br />
* Radial basis funcions<br />
<br />
<br />
== k-nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the preferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
k-nearest neighbor algorithm<br />
<br />
<math>d(x_i,x_j)= \sum_{r=1}^n (a_r(x_i)-a_r(x_j))^2</math></div>Justhttps://wiki.aardrock.com/index.php?title=Advise&diff=2100Advise2006-05-30T10:53:04Z<p>Just: </p>
<hr />
<div>Types of advise generated by the system with the query underneath:<br />
<br />
1. What amount of insuline I have to use to be between safety levels after 3 hours.<br />
<br />
2. What is an alternative foodproduct for the one I selected. <br />
<br />
3. What is the amount of food I can eat when I use this amount of units insuline.<br />
<br />
4. What is the amount of exercise (amount of kiloJoules) I can perform during 3 hours.</div>Justhttps://wiki.aardrock.com/index.php?title=Databased_advisory_System&diff=2097Databased advisory System2006-05-30T10:37:58Z<p>Just: add new page</p>
<hr />
<div>== Advise without teaching==<br />
<br />
<br />
The user periodicaly enters their personal information into the system.<br />
<br />
Less frequent entries are:<br />
* weight/muscle mass<br />
* maximal kilojoules intake<br />
* health status<br />
<br />
Frequent entries are:<br />
* Food intake (product + volumn)<br />
* Insulin intake (volumn + type)<br />
* Glucose values<br />
* Activities/stress <br />
<br />
These entries has to be marked with a timestamp(default present time, else the time that the activity occured).<br />
<br />
The user fills the database just like he is accustomed with his own personal logboek. This is an advantage, because people gladly work with things which they already known. After time the database will be filled with entries who shows resemblance with each other.<br />
<br />
Example:<br /><br />
02-03-2006 11:50 apple 40 gram<br /><br />
02-03-2006 11:53 sandwich cheese/ham<br /><br />
02-03-2006 11:57 sandwich salad<br /><br />
02-03-2006 15:00 6,6 mmol/l glucose<br /><br />
<br />
14-03-2006 12:00 apple 30 gram<br /><br />
14-03-2006 12:05 sandwich cheese/ham<br /><br />
14-03-2006 12:12 sandwich salad<br /><br />
14-03-2006 15:00 6,5 mmol/l glucose<br /><br />
<br />
The system forms relations by the input taken for the past.<br />
<br />
Absolute weights are acquired by manual weighting and inserted into the system. In normal life, people use the same amount of food. they use the same plate and cups. The system could be provided with a function that relates the absolute weights with the relative weigths. This could be done with three manual measurements. On the background the absolute values are still being used. Periodically the system has to ask the user to revalidate the weigths the system uses. This protects the system from natural changes.<br />
<br />
The system must be able to [[make combinations]] of entries inserted in the past, to generate [[advise]] in the present.<br />
Next idea is based on the MetisII project, a translation machine that translate dutch noun phrases into english ones. When time progresses the database will be filled with entries. When a new entr<br />
Advise can be stated in the form:<br />
* Het foodintake today is justifide, because in de past at day ... has the glucoselevel in blood between 4 and 8 mmmol/l after ... hours.<br />
* Het entries of today are compared from those of the past. The result shows to take a different course of action than that of the past. On ... day were your glucose level not in the safety area of 4-8 mmol/l.<br />
<br />
The results have to been shown in a userfriendly format. In that way the user can decide if the recommendations are usefull or that the system made an error. Maybe it is posible to validate the recommendations the system generates by the user.<br />
<br />
Because more than one user is entering input to the system, other kinds of advise can be generated. It is extremly usefull with entries of new foodintake. Input of others can generate upper and downvalues wich indicates how much insulin can be used.<br />
<br />
Example of advise is:<br />
* This is new inputdata. Several persons have inserted the same input. The range of insulin intakevalues which were used lays between ... and ... units<br />
<br />
Collecting multiple glucose measurements of persons who ate the same thing, produces a cloud of points. This can be transformed to an area of prediction, which indicates the chances a person gets a hypo or a hyper.<br />
<br />
[[Image:puntenwolk.jpg]]</div>Justhttps://wiki.aardrock.com/index.php?title=Make_combinations&diff=2095Make combinations2006-05-30T10:35:51Z<p>Just: delete a sentence</p>
<hr />
<div>There are 2 ways for searching in de basebase for possible entrees that add to the advise the system can give.<br />
* direct search<br />
* fussy search<br />
<br />
I show the meanings with an example.<br />
<br />
my entries at 8:40 are<br />
<br />
* 8:30 2 slice of cheese<br />
* 8:30 2 slice of white bread<br />
* 8:30 1 glass of milk<br />
* 8:35 1 apple (30 g)<br />
* health status: normal<br />
<br />
question to the system. how much insulin do i have to inject if i want that my concentration glucose in blood is around 5 mmol/l at 11:00.<br />
<br />
In the system happens a few things:<br />
* First a new entry is set in the database.<br />
* second it calculates the amount of carbonate of the foodintake<br />
* Third it makes a query of the question to search with in the database<br />
<br />
This query is not a straightforward thing. First it will search directly at entries in the past. If it find a match then this is the most trustfull advise the system can give. This in relation to the definition of reproduction. If you do an experiment in the past and you know the results and you do the experiment again. You can expect to get the same result. To give the query a fair change to find entrees, the query have to losen up. How much has to be done experimented empericaly.<br />
for the example this means:<br />
<br />
look for: 8:15 - 8:45 350-400 gr carbonate(with white bread, cheese, milk and apple as food-intake)<br />
10:30 - 11:30 4,5 - 5,5 mmol/l glucose units insuline<br />
<br />
Lets say it finds entries from previous entries in past. with amounts of units insuline. We can present the mean to the user, if the difference is not signifide, and the entries where the advise is build from is presented to the user. If the user is not satisfied it can say that to the system and it will [[narrow it searchparameters]]. The problem is which one so thats still a design thought.<br />
<br />
But what if it cannot find a match? It will search fussy. With this search it broads it search window (see the figure what i mean). it starts with broading 1 parameter of the query, untill it finds a entry that match. then it start anew and broads another parameter. when all the paramaters are done it starts broading 2 parameters, untill it finds a match. Last round will be that all the parameters will losen up untill it finds an entry that match. The broadingsteps are fixed and has to be emperical assessed.<br />
<br />
What do we have? a collection of entrees with different kinds of answers. But which one is the most rightnest or is a couple of entries from different searchround together beter then just from 1 searchround? A learning system as a [[neural network]] could profide that answer. The advise is of less value than a direct search. The user could have the abbility to see which enties the strongest influens had on the advise. Thats simply showing the entries of a searchround with the highest weights.<br />
<br />
At the end the system could ask the user to check it's glucose level in blood at some point in time. This to reference that the advise was a good or bad one so it can ajust it weights.<br />
<br />
The reason to calculate the carbonate load is: <br />
* in direct search measures of intake can differ, but the carbonate load not. In the example the apple can weight 50 g. but de carbonate load is allmost the same.<br />
* in fussy search if we losen the foodintake it goes like this:<br />
*2 slice of cheese 2 slice of cheese<br />
*2 slice of bread 2 slice of bread<br />
*1 glass of milk<br />
*350-400 gr carbonate 350-400 gr carbonate<br />
<br />
The amount of carbonates is important to [[find alternatives]]. In other words you eat different products, but the carbonate stays the same.<br />
<br />
[[Image:puntenwolk1.jpg]]<br />
* red dots: entries found by direct search<br />
* blue dots: entries found when broading the searchparameters, food intake and time of foodintake<br />
* clear square: searchwindow by direct search<br />
* unclear square: searchwindow broadend after one fussy searchround.<br />
<br />
<br />
== The goods and the bad's ==<br />
<br />
'''The good things about this approtess are:'''<br />
<br />
* It can handle inconsequent users. If a day is forgotten it can still give advise.<br />
* Close to what the user allready does. Fill in his logbook en looks up when things went wrong.<br />
* Easy to implement.<br />
* can start from the beginning and the more entries it has the better it starts to function.<br />
* advise is local/personal.<br />
<br />
'''The bad things:'''<br />
<br />
* Instance based learning is a very simple way of learning. with large databases it is better to use basian learning.<br />
* There is no involvement from the outside world.<br />
* Extra knowledge from other users are not shared.</div>Justhttps://wiki.aardrock.com/index.php?title=Make_combinations&diff=2063Make combinations2006-05-26T20:54:32Z<p>Just: </p>
<hr />
<div>There are 2 ways for searching in de basebase for possible entrees that add to the advise the system can give.<br />
* direct search<br />
* fussy search<br />
<br />
I show the meanings with an example.<br />
<br />
my entries at 8:40 are<br />
<br />
* 8:30 2 slice of cheese<br />
* 8:30 2 slice of white bread<br />
* 8:30 1 glass of milk<br />
* 8:35 1 apple (30 g)<br />
* health status: normal<br />
<br />
question to the system. how much insulin do i have to inject if i want that my concentration glucose in blood is around 5 mmol/l at 11:00.<br />
<br />
In the system happens a few things:<br />
* First a new entry is set in the database.<br />
* second it calculates the amount of carbonate of the foodintake<br />
* Third it makes a query of the question to search with in the database<br />
<br />
This query is not a straightforward thing. First it will search directly at entries in the past. If it find a match then this is the most trustfull advise the system can give. This in relation to the definition of reproduction. If you do an experiment in the past and you know the results and you do the experiment again. You can expect to get the same result. To give the query a fair change to find entrees, the query have to losen up. How much has to be done experimented empericaly.<br />
for the example this means:<br />
<br />
look for: 8:15 - 8:45 350-400 gr carbonate(with white bread, cheese, milk and apple as food-intake)<br />
10:30 - 11:30 4,5 - 5,5 mmol/l glucose units insuline<br />
<br />
Lets say it finds entries from previous entries in past. with amounts of units insuline. We can present the mean to the user, if the difference is not signifide, and the entries where the advise is build from is presented to the user. If the user is not satisfied it can say that to the system and it will [[narrow it searchparameters]]. The problem is which one so thats still a design thought.<br />
<br />
But what if it cannot find a match? It will search fussy. With this search it broads it search window (see the figure what i mean). it starts with broading 1 parameter of the query, untill it finds a entry that match. then it start anew and broads another parameter. when all the paramaters are done it starts broading 2 parameters, untill it finds a match. Last round will be that all the parameters will losen up untill it finds an entry that match. The broadingsteps are fixed and has to be emperical assessed.<br />
<br />
What do we have? a collection of entrees with different kinds of answers. But which one is the most rightnest or is a couple of entries from different searchround together beter then just from 1 searchround? A learning system as a [[neural network]] could profide that answer. but that part i have to discus with Durk, because maybe he has the answer on that question. Het advise is of less value than a direct search. The user could have the abbility to see which enties the strongest influens had on the advise. Thats simply showing the entries of a searchround with the highest weights.<br />
<br />
At the end the system could ask the user to check it's glucose level in blood at some point in time. This to reference that the advise was a good or bad one so it can ajust it weights.<br />
<br />
The reason to calculate the carbonate load is: <br />
* in direct search measures of intake can differ, but the carbonate load not. In the example the apple can weight 50 g. but de carbonate load is allmost the same.<br />
* in fussy search if we losen the foodintake it goes like this:<br />
*2 slice of cheese 2 slice of cheese<br />
*2 slice of bread 2 slice of bread<br />
*1 glass of milk<br />
*350-400 gr carbonate 350-400 gr carbonate<br />
<br />
the amount of carbonates is important to [[find alternatives]]. In other words you eat different products, but the carbonate stays the same.<br />
<br />
[[Image:puntenwolk1.jpg]]<br />
* red dots: entries found by direct search<br />
* blue dots: entries found when broading the searchparameters, food intake and time of foodintake<br />
* clear square: searchwindow by direct search<br />
* unclear square: searchwindow broadend after one fussy searchround.<br />
<br />
<br />
== The goods and the bad's ==<br />
<br />
'''The good things about this approtess are:'''<br />
<br />
* It can handle inconsequent users. If a day is forgotten it can still give advise.<br />
* Close to what the user allready does. Fill in his logbook en looks up when things went wrong.<br />
* Easy to implement.<br />
* can start from the beginning and the more entries it has the better it starts to function.<br />
* advise is local/personal.<br />
<br />
'''The bad things:'''<br />
<br />
* Instance based learning is a very simple way of learning. with large databases it is better to use basian learning.<br />
* There is no involvement from the outside world.<br />
* Extra knowledge from other users are not shared.</div>Justhttps://wiki.aardrock.com/index.php?title=Make_combinations&diff=2062Make combinations2006-05-26T20:41:00Z<p>Just: </p>
<hr />
<div>There are 2 ways for searching in de basebase for possible entrees that add to the advise the system can give.<br />
* direct search<br />
* fussy search<br />
<br />
I show the meanings with an example.<br />
<br />
my entries at 8:40 are<br />
<br />
* 8:30 2 slice of cheese<br />
* 8:30 2 slice of white bread<br />
* 8:30 1 glass of milk<br />
* 8:35 1 apple (30 g)<br />
* health status: normal<br />
<br />
question to the system. how much insulin do i have to inject if i want that my concentration glucose in blood is around 5 mmol/l at 11:00.<br />
<br />
In the system happens a few things:<br />
* First a new entry is set in the database.<br />
* second it calculates the amount of carbonate of the foodintake<br />
* Third it makes a query of the question to search with in the database<br />
<br />
This query is not a straightforward thing. First it will search directly at entries in the past. If it find a match then this is the most trustfull advise the system can give. This in relation to the definition of reproduction. If you do an experiment in the past and you know the results and you do the experiment again. You can expect to get the same result. To give the query a fair change to find entrees, the query have to losen up. How much has to be done experimented empericaly.<br />
for the example this means:<br />
<br />
look for: 8:15 - 8:45 350-400 gr carbonate(with white bread, cheese, milk and apple as food-intake)<br />
10:30 - 11:30 4,5 - 5,5 mmol/l glucose units insuline<br />
<br />
Lets say it finds entries from previous entries in past. with amounts of units insuline. We can present the mean to the user, if the difference is not signifide, and the entries where the advise is build from is presented to the user. If the user is not satisfied it can say that to the system and it will [[narrow it searchparameters]]. The problem is which one so thats still a design thought.<br />
<br />
But what if it cannot find a match? It will search fussy. With this search it broads it search window (see the figure what i mean). it starts with broading 1 parameter of the query, untill it finds a entry that match. then it start anew and broads another parameter. when all the paramaters are done it starts broading 2 parameters, untill it finds a match. Last round will be that all the parameters will losen up untill it finds an entry that match. The broadingsteps are fixed and has to be emperical assessed.<br />
<br />
What do we have? a collection of entrees with different kinds of answers. But which one is the most rightnest or is a couple of entries from different searchround together beter then just from 1 searchround? A learning system as a [[neural network]] could profide that answer. but that part i have to discus with Durk, because maybe he has the answer on that question. Het advise is of less value than a direct search. The user could have the abbility to see which enties the strongest influens had on the advise. Thats simply showing the entries of a searchround with the highest weights.<br />
<br />
At the end the system could ask the user to check it's glucose level in blood at some point in time. This to reference that the advise was a good or bad one so it can ajust it weights.<br />
<br />
The reason to calculate the carbonate load is: <br />
* in direct search measures of intake can differ, but the carbonate load not. In the example the apple can weight 50 g. but de carbonate load is allmost the same.<br />
* in fussy search if we losen the foodintake it goes like this:<br />
*2 slice of cheese 2 slice of cheese<br />
*2 slice of bread 2 slice of bread<br />
*1 glass of milk<br />
*350-400 gr carbonate 350-400 gr carbonate<br />
<br />
the amount of carbonates is important to [[find alternatives]]. In other words you eat different products, but the carbonate stays the same.<br />
<br />
[[Image:puntenwolk1.jpg]]<br />
* red dots: entries found by direct search<br />
* blue dots: entries found when broading the searchparameters, food intake and time of foodintake<br />
* clear square: searchwindow by direct search<br />
* unclear square: searchwindow broadend after one fussy searchround.</div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2061Neural network2006-05-26T20:35:12Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm.<br />
* Locally weigthed regression<br />
* Radial basis funcions<br />
<br />
<br />
== k - nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the prefferences of the users better. how many entry are usefull for users and how many entries can they compriand.<br />
<br />
Van het algorithme snap ik niet zoveel. heb nu drie verschillende boeken nageslagen over het onderwerp maar kom er niet verder mee. Zal durk vragen mij hierbij te helpen.</div>Justhttps://wiki.aardrock.com/index.php?title=Find_alternatives&diff=2060Find alternatives2006-05-26T20:33:07Z<p>Just: </p>
<hr />
<div>Giel discovered during the interviews with dietists, that many users of our application will ask the system that: what kind of variation can i make while staying on the same amount of carbonates? <br />
<br />
A solution to this problem is to skip the food products the user doesn't want. The system can look now in two ways for alternative foodproducts. <br />
* food products allready eaten. The system will search for food products in the entries de user has inserted in the database. The thought is that what people like to eat in the past they probally will eat in the future.<br />
* food products from the NEVO-table. The system will search through the NEVO-Table. It will throw up every posible alternative.<br />
<br />
----<br />
<br />
Example:<br />
<br />
'''entry is:'''<br />
<br />
1 slice of bread<br><br />
1 slice of cheese<br><br />
1 glass of milk<br><br />
1 apple(30 g)<br><br />
carbonate 390 gr<br><br />
<br />
'''What is an alternative for : apple ?'''<br />
<br />
1 slice of bread<br><br />
1 slice of cheese<br><br />
1 glass of milk<br><br />
carbonate 300gr<br><br />
<br />
'''query wordt dan:'''<br />
<br />
ken nog niet de query taal van Jena.</div>Justhttps://wiki.aardrock.com/index.php?title=Find_alternatives&diff=2059Find alternatives2006-05-26T20:31:59Z<p>Just: </p>
<hr />
<div>Giel discovered during the interviews with dietists, that many users of our application will ask the system that: what kind of variation can i make while staying on the same amount of carbonates? <br />
<br />
A solution to this problem is to skip the food products the user doesn't want. The system can look now in two ways for alternative foodproducts. <br />
* food products allready eaten. The system will search for food products in the entries de user has inserted in the database. The thought is that what people like to eat in the past they probally will eat in the future.<br />
* food products from the NEVO-table. The system will search through the NEVO-Table. It will throw up every posible alternative.<br />
<br />
Example:<br />
<br />
entry is:<br />
<br />
1 slice of bread<br><br />
1 slice of cheese<br><br />
1 glass of milk<br><br />
1 apple(30 g)<br><br />
carbonate 390 gr<br><br />
What is an alternative for : apple ?<br />
<br />
1 slice of bread<br><br />
1 slice of cheese<br><br />
1 glass of milk<br><br />
carbonate 300gr<br><br />
<br />
query wordt dan:</div>Justhttps://wiki.aardrock.com/index.php?title=Find_alternatives&diff=2058Find alternatives2006-05-26T20:31:28Z<p>Just: </p>
<hr />
<div>Giel discovered during the interviews with dietists, that many users of our application will ask the system that: what kind of variation can i make while staying on the same amount of carbonates? <br />
<br />
A solution to this problem is to skip the food products the user doesn't want. The system can look now in two ways for alternative foodproducts. <br />
* food products allready eaten. The system will search for food products in the entries de user has inserted in the database. The thought is that what people like to eat in the past they probally will eat in the future.<br />
* food products from the NEVO-table. The system will search through the NEVO-Table. It will throw up every posible alternative.<br />
<br />
Example:<br />
<br />
entry is:<br />
<br />
1 slice of bread<br />
1 slice of cheese<br />
1 glass of milk<br />
1 apple(30 g)<br />
carbonate 390 gr<br />
What is an alternative for : apple ?<br />
<br />
1 slice of bread<br />
1 slice of cheese<br />
1 glass of milk<br />
carbonate 300gr<br><br />
<br />
query wordt dan:</div>Justhttps://wiki.aardrock.com/index.php?title=Neural_network&diff=2057Neural network2006-05-26T20:05:29Z<p>Just: </p>
<hr />
<div>After research, neural networks do not give the patient the answer he wants. Its output is ownly 0 or 1 or a decree believe in that (range from 0 to 1). Neural networks are nice to identify patrons, but not for this problem.<br />
<br />
== What is the problem? ==<br />
<br />
After fussy search did his rounds. It has a collections of entries from the past. Each entry has the answer on the question: "How much insuline has to be used?" The problem is wich answer is the best answer.<br />
<br />
== Instance based learning ==<br />
<br />
Some quotes:<br />
<br />
"Learning in these algorithms consists of simply storing the presented training data. When a new query instance is encountered, a set of similar related instances is retrieved from memory and used to classify the new query instance."<br />
<br />
This is exectly what is descriped on the previous page. Training instances (the log entrees the user insert into the database) are memoriezed. A question to the system like": "How much insuline has to be used?" is the new query instance. The right answer is the classification. <br />
<br />
There are a few algoritms that can be used:<br />
* k-nearest Neighbor algorithm.<br />
* Locally weigthed regression<br />
* Radial basis funcions<br />
<br />
<br />
== k - nearest Neighbor algorithm ==<br />
<br />
After fusy-search finished its search rounds. The algoritm will measure the distance between each founded entry and the k nearest entries will be added to the advise and presented to the user. Giel has to determine what the value of k much be. He know the prefferences of the users better. how many entry are usefull for users and how many entries can they compriand.</div>Justhttps://wiki.aardrock.com/index.php?title=Make_combinations&diff=1940Make combinations2006-05-23T12:06:15Z<p>Just: </p>
<hr />
<div>There are 2 ways for searching in de basebase for possible entrees that add to the advise the system can give.<br />
* direct search<br />
* fussy search<br />
<br />
I show the meanings with an example.<br />
<br />
my entries at 8:40 are<br />
<br />
* 8:30 2 slice of cheese<br />
* 8:30 2 slice of white bread<br />
* 8:30 1 glass of milk<br />
* 8:35 1 apple (30 g)<br />
* health status: normal<br />
<br />
question to the system. how much insulin do i have to inject if i want that my concentration glucose in blood is around 5 mmol/l at 11:00.<br />
<br />
In the system happens a few things:<br />
* First a new entry is set in the database.<br />
* second it calculates the amount of koolhydrate of the foodintake<br />
* Third it makes a query of the question to search with in the database<br />
<br />
This query is not a straightforward thing. First it will search directly at entries in the past. If it find a match then this is the most trustfull advise the system can give. This in relation to the definition of reproduction. If you do an experiment in the past and you know the results and you do the experiment again. You can expect to get the same result. To give the query a fair change to find entrees, the query have to losen up. How much has to be done experimented empericaly.<br />
for the example this means:<br />
<br />
look for: 8:15 - 8:45 350-400 gr koolhydrate(with white bread, cheese, milk and apple as food-intake)<br />
10:30 - 11:30 4,5 - 5,5 mmol/l glucose units insuline<br />
<br />
Lets say it finds entries from previous entries in past. with amounts of units insuline. We can present the mean to the user, if the difference is not signifide, and the entries where the advise is build from is presented to the user. If the user is not satisfied it can say that to the system and it will [[narrow it searchparameters]]. The problem is which one so thats still a design thought.<br />
<br />
But what if it cannot find a match? It will search fussy. With this search it broads it search window (see the figure what i mean). it starts with broading 1 parameter of the query, untill it finds a entry that match. then it start anew and broads another parameter. when all the paramaters are done it starts broading 2 parameters, untill it finds a match. Last round will be that all the parameters will losen up untill it finds an entry that match. The broadingsteps are fixed and has to be emperical assessed.<br />
<br />
What do we have? a collection of entrees with different kinds of answers. But which one is the most rightnest or is a couple of entries from different searchround together beter then just from 1 searchround? A learning system as a [[neural network]] could profide that answer. but that part i have to discus with Durk, because maybe he has the answer on that question. Het advise is of less value than a direct search. The user could have the abbility to see which enties the strongest influens had on the advise. Thats simply showing the entries of a searchround with the highest weights.<br />
<br />
At the end the system could ask the user to check it's glucose level in blood at some point in time. This to reference that the advise was a good or bad one so it can ajust it weights.<br />
<br />
The reason to calculate the koolhydrate load is: <br />
* in direct search measures of intake can differ but the koolhydrate load not. example the apple can weight 50 g. but de koolhydrate load is allmost the same.<br />
* in fussy search if we losen the foodintake it goes like this:<br />
*2 slice of cheese 2 slice of cheese<br />
*2 slice of bread 2 slice of bread<br />
*1 glass of milk<br />
*350-400 gr koolhydrate 350-400 gr koolhydrate<br />
<br />
the amount of koolhydrates is important to [[find alternatives]]. In other words you eat different products but the koolhydrate stays the same.<br />
<br />
[[Image:puntenwolk1.jpg]]<br />
* red dots: entries found by direct search<br />
* blue dots: entries found when broading the searchparameters, food intake and time of foodintake<br />
* clear square: searchwindow by direct search<br />
* unclear square: searchwindow broadend after one fussy searchround.</div>Justhttps://wiki.aardrock.com/index.php?title=Make_combinations&diff=1939Make combinations2006-05-23T12:04:59Z<p>Just: </p>
<hr />
<div>There are 2 ways for searching in de basebase for possible entrees that add to the advise the system can give.<br />
* direct search<br />
* fussy search<br />
<br />
I show the meanings with an example.<br />
<br />
my entries at 8:40 are<br />
<br />
* 8:30 2 slice of cheese<br />
* 8:30 2 slice of white bread<br />
* 8:30 1 glass of milk<br />
* 8:35 1 apple (30 g)<br />
* health status: normal<br />
<br />
question to the system. how much insulin do i have to inject if i want that my concentration glucose in blood is around 5 mmol/l at 11:00.<br />
<br />
In the system happens a few things:<br />
* First a new entry is set in the database.<br />
* second it calculates the amount of koolhydrate of the foodintake<br />
* Third it makes a query of the question to search with in the database<br />
<br />
This query is not a straightforward thing. First it will search directly at entries in the past. If it find a match then this is the most trustfull advise the system can give. This in relation to the definition of reproduction. If you do an experiment in the past and you know the results and you do the experiment again. You can expect to get the same result. To give the query a fair change to find entrees, the query have to losen up. How much has to be done experimented empericaly.<br />
for the example this means:<br />
<br />
look for: 8:15 - 8:45 350-400 gr koolhydrate(with white bread, cheese, milk and apple as food-intake)<br />
10:30 - 11:30 4,5 - 5,5 mmol/l glucose units insuline<br />
<br />
Lets say it finds entries from previous entries in past. with amounts of units insuline. We can present the mean to the user, if the difference is not signifide, and the entries where the advise is build from is presented to the user. If the user is not satisfied it can say that to the system and it will [[narrow it searchparameters]]. The problem is which one so thats still a design thought.<br />
<br />
But what if it cannot find a match? It will search fussy. With this search it broads it search window (see the figure what i mean). it starts with broading 1 parameter of the query, untill it finds a entry that match. then it start anew and broads another parameter. when all the paramaters are done it starts broading 2 parameters, untill it finds a match. Last round will be that all the parameters will losen up untill it finds an entry that match. The broadingsteps are fixed and has to be emperical assessed.<br />
<br />
What do we have? a collection of entrees with different kinds of answers. But which one is the most rightnest or is a couple of entries from different searchround together beter then just from 1 searchround? A learning system as a [[neural network]] could profide that answer. but that part i have to discus with Durk, because maybe he has the answer on that question. Het advise is of less value than a direct search. The user could have the abbility to see which enties the strongest influens had on the advise. Thats simply showing the entries of a searchround with the highest weights.<br />
<br />
At the end the system could ask the user to check it's glucose level in blood at some point in time. This to reference that the advise was a good or bad one so it can ajust it weights.<br />
<br />
The reason to calculate the koolhydrate load is: <br />
* in direct search measures of intake can differ but the koolhydrate load not. example the apple can weight 50 g. but de koolhydrate load is allmost the same.<br />
* in fussy search if we losen the foodintake it goes like this:<br />
2 slice of cheese 2 slice of cheese<br />
2 slice of bread 2 slice of bread<br />
1 glass of milk<br />
350-400 gr koolhydrate 350-400 gr koolhydrate<br />
<br />
the amount of koolhydrates is important to [[find alternatives]]. In other words you eat different products but the koolhydrate stays the same.<br />
<br />
[[Image:puntenwolk1.jpg]]<br />
red dots: entries found by direct search<br />
blue dots: entries found when broading the searchparameters, food intake and time of foodintake<br />
clear square: searchwindow by direct search<br />
unclear square: searchwindow broadend after one fussy searchround.</div>Justhttps://wiki.aardrock.com/index.php?title=Make_combinations&diff=1938Make combinations2006-05-23T12:02:48Z<p>Just: uitbreiding hoe combi's te maken voor een advies</p>
<hr />
<div>There are 2 ways for searching in de basebase for possible entrees that add to the advise the system can give.<br />
* direct search<br />
* fussy search<br />
<br />
I show the meanings with an example.<br />
<br />
my entries at 8:40 are<br />
<br />
8:30 2 slice of cheese<br />
8:30 2 slice of white bread<br />
8:30 1 glass of milk<br />
8:35 1 apple (30 g)<br />
health status: normal<br />
<br />
question to the system. how much insulin do i have to inject if i want that my concentration glucose in blood is around 5 mmol/l at 11:00.<br />
<br />
In the system happens a few things:<br />
* First a new entry is set in the database.<br />
* second it calculates the amount of koolhydrate of the foodintake<br />
* Third it makes a query of the question to search with in the database<br />
<br />
This query is not a straightforward thing. First it will search directly at entries in the past. If it find a match then this is the most trustfull advise the system can give. This in relation to the definition of reproduction. If you do an experiment in the past and you know the results and you do the experiment again. You can expect to get the same result. To give the query a fair change to find entrees, the query have to losen up. How much has to be done experimented empericaly.<br />
for the example this means:<br />
<br />
look for: 8:15 - 8:45 350-400 gr koolhydrate(with white bread, cheese, milk and apple as food-intake)<br />
10:30 - 11:30 4,5 - 5,5 mmol/l glucose units insuline<br />
<br />
Lets say it finds entries from previous entries in past. with amounts of units insuline. We can present the mean to the user, if the difference is not signifide, and the entries where the advise is build from is presented to the user. If the user is not satisfied it can say that to the system and it will [[narrow it searchparameters]]. The problem is which one so thats still a design thought.<br />
<br />
But what if it cannot find a match? It will search fussy. With this search it broads it search window (see the figure what i mean). it starts with broading 1 parameter of the query, untill it finds a entry that match. then it start anew and broads another parameter. when all the paramaters are done it starts broading 2 parameters, untill it finds a match. Last round will be that all the parameters will losen up untill it finds an entry that match. The broadingsteps are fixed and has to be emperical assessed.<br />
<br />
What do we have? a collection of entrees with different kinds of answers. But which one is the most rightnest or is a couple of entries from different searchround together beter then just from 1 searchround? A learning system as a [[neural network]] could profide that answer. but that part i have to discus with Durk, because maybe he has the answer on that question. Het advise is of less value than a direct search. The user could have the abbility to see which enties the strongest influens had on the advise. Thats simply showing the entries of a searchround with the highest weights.<br />
<br />
At the end the system could ask the user to check it's glucose level in blood at some point in time. This to reference that the advise was a good or bad one so it can ajust it weights.<br />
<br />
The reason to calculate the koolhydrate load is: <br />
* in direct search measures of intake can differ but the koolhydrate load not. example the apple can weight 50 g. but de koolhydrate load is allmost the same.<br />
* in fussy search if we losen the foodintake it goes like this:<br />
2 slice of cheese 2 slice of cheese<br />
2 slice of bread 2 slice of bread<br />
1 glass of milk<br />
350-400 gr koolhydrate 350-400 gr koolhydrate<br />
<br />
the amount of koolhydrates is important to [[find alternatives]]. In other words you eat different products but the koolhydrate stays the same.<br />
<br />
[[Image:puntenwolk1.jpg]]<br />
red dots: entries found by direct search<br />
blue dots: entries found when broading the searchparameters, food intake and time of foodintake<br />
clear square: searchwindow by direct search<br />
unclear square: searchwindow broadend after one fussy searchround.</div>Justhttps://wiki.aardrock.com/index.php?title=File:Puntenwolk1.jpg&diff=1937File:Puntenwolk1.jpg2006-05-23T11:47:48Z<p>Just: </p>
<hr />
<div></div>Justhttps://wiki.aardrock.com/index.php?title=Databased_advisory_System&diff=1932Databased advisory System2006-05-23T10:08:28Z<p>Just: aanmaak nieuwe pagina</p>
<hr />
<div>== Advise without teaching==<br />
<br />
<br />
The user periodicaly enters their personal information into the system.<br />
<br />
Less frequent entries are:<br />
* weight/muscle mass<br />
* maximal kilojoules intake<br />
* health status<br />
<br />
Frequent entries are:<br />
* Food intake (product + volumn)<br />
* Insulin intake (volumn + type)<br />
* Glucose values<br />
* Activities/stress <br />
<br />
These entries has to be marked with a timestamp(default present time, else the time that the activity occured).<br />
<br />
The user fills the database just like he is accustomed with his own personal logboek. This is an advantage, because people gladly work with things which they already known. After time the database will be filled with entries who shows resemblance with each other.<br />
<br />
Example:<br /><br />
02-03-2006 11:50 apple 40 gram<br /><br />
02-03-2006 11:53 sandwich cheese/ham<br /><br />
02-03-2006 11:57 sandwich salad<br /><br />
02-03-2006 15:00 6,6 mmol/l glucose<br /><br />
<br />
14-03-2006 12:00 apple 30 gram<br /><br />
14-03-2006 12:05 sandwich cheese/ham<br /><br />
14-03-2006 12:12 sandwich salad<br /><br />
14-03-2006 15:00 6,5 mmol/l glucose<br /><br />
<br />
The system forms relations by the input taken for the past.<br />
<br />
Absolut geweights are acquired by manual weighting and inserted into the system. In normal life, people use the same amount of food. they use the same plate and cups. The system could be provided with a function that relates the absolute weights with the relative weigths. This could be done with three manual measurements. On the background the absolute values are still being used. Periodically the system has to ask the user to revalidate the weigths the system uses. This protects the system from natural changes.<br />
<br />
The system must be able to [[make combinations]] of entries inserted in the past, to generate advise in the present.<br />
Next idea is based on the MetisII project, a translation machine that translate dutch noun phrases into english ones. When time progresses the database will be filled with entries. When a new entr<br />
Advise can be stated in the form:<br />
* Het foodintake today is justifide, because in de past at day ... has the glucoselevel in blood between 4 and 8 mmmol/l after ... hours.<br />
* Het entries of today are compared from those of the past. The result shows to take a different course of action than that of the past. On ... day were your glucose level not in the safety area of 4-8 mmol/l.<br />
<br />
The results have to been shown in a userfriendly format. In that way the user can decide if the recommendations are usefull or that the system made an error. Maybe it is posible to validate the recommendations the system generates by the user.<br />
<br />
Because more than one user is entering input to the system, other kinds of advise can be generated. It is extremly usefull with entries of new foodintake. Input of others can generate upper and downvalues wich indicates how much insulin can be used.<br />
<br />
Example of advise is:<br />
* This is new inputdata. Several persons have inserted the same input. The range of insulin intakevalues which were used lays between ... and ... units<br />
<br />
Collecting multiple glucose measurements of persons who ate the same thing, produces a cloud of points. This can be transformed to an area of prediction, which indicates the chances a person gets a hypo or a hyper.<br />
<br />
[[Image:puntenwolk.jpg]]</div>Justhttps://wiki.aardrock.com/index.php?title=Notulen20060516&diff=1931Notulen200605162006-05-23T10:04:13Z<p>Just: notulen 16-5-2006</p>
<hr />
<div>* Datum: 16-05-2006<br />
* Notulist: Just<br />
* Voorzitter: Patrick<br />
* Aanwezig: [[JustBoerlage]], [[User:Martijn|Martijn van Steenbergen]], [[HansPhilippi]], [[SjoerdVanKreel]], [[RoderikDeLangen]], [[PatrickVanKouteren]], [[DurkKingma]], [[ChrisEidhof]]<br />
* Afwezig: [[RoderikDeLangen]], [[ChrisEidhof]]<br />
* Begin vergadering: 15.30<br />
<br />
== Goedkeuring Notulen ==<br />
<br />
De notulen van 9 mei 2006 zijn goedgekeurd.<br />
<br />
== Wie heeft wat gedaan? ==<br />
<br />
* Just: Bezig geweest met het adviserend gedeelte<br />
* Sjoerd: Bezig geweest met de user interface<br />
* Patrick: Bezig geweest met de user interface en de user preferences<br />
* Durk: Heeft zijn idee over het adviserende gedeelte verder uitgewerkt. Heeft harold gevraagd om een gesprek over het adviserend gedeelte van de applicatie en voor testdata.<br />
* Martijn: Heeft gewerkt aan het probleem met de workspace, opgetreden tijdens de user-feedbacktest.<br />
<br />
== Wat gaat iedereen doen? ==<br />
<br />
* Just: Gaat in overleg met Durk het adviserend gedeelte in zijn vaste vorm gieten.<br />
* Martijn: Gaat de laatste hand leggen aan het workspace probleem en gaat zorgen dat cheeta kan draaien op de MAC<br />
* Sjoerd: Gaat samen in overleg met Giel verder met het vorm geven van de user interface<br />
* Patrick: Gaat veder met de user<br />
* Durk: gaat naar Harold voor overleg en gaat het adviserende gedeelte verder vorm geven.<br />
<br />
== W.V.T.T.K ==<br />
<br />
Er is niets doorgeschoven.<br />
<br />
== Rondvraag ==<br />
<br />
* Niemand had wat voor de rondvraag<br />
<br />
== Volgende Vergadering ==<br />
<br />
* 15-16 vergadering INFOSP<br />
<br />
== Sluiting ==<br />
<br />
Suiting vergadering om 15:45 uur.</div>Justhttps://wiki.aardrock.com/index.php?title=Databased_advisory_System&diff=1820Databased advisory System2006-05-16T14:41:20Z<p>Just: /* Advise without teaching */</p>
<hr />
<div>== Advise without teaching==<br />
<br />
<br />
The user periodicaly enters their personal information into the system.<br />
<br />
Less frequent entries are:<br />
* weight/muscle mass<br />
* maximal kilojoules intake<br />
* health status<br />
<br />
Frequent entries are:<br />
* Food intake (product + volumn)<br />
* Insulin intake (volumn + type)<br />
* Glucose values<br />
* Activities/stress <br />
<br />
These entries has to be marked with a timestamp(default present time, else the time that the activity occured).<br />
<br />
The user fills the database just like he is accustomed with his own personal logboek. This is an advantage, because people gladly work with things which they already known. After time the database will be filled with entries who shows resemblance with each other.<br />
<br />
Example:<br /><br />
02-03-2006 11:50 apple 40 gram<br /><br />
02-03-2006 11:53 sandwich cheese/ham<br /><br />
02-03-2006 11:57 sandwich salad<br /><br />
02-03-2006 15:00 6,6 mmol/l glucose<br /><br />
<br />
14-03-2006 12:00 apple 30 gram<br /><br />
14-03-2006 12:05 sandwich cheese/ham<br /><br />
14-03-2006 12:12 sandwich salad<br /><br />
14-03-2006 15:00 6,5 mmol/l glucose<br /><br />
<br />
The system forms relations by the input taken for the past.<br />
<br />
Absolut geweights are acquired by manual weighting and inserted into the system. In normal life, people use the same amount of food. they use the same plate and cups. The system could be provided with a function that relates the absolute weights with the relative weigths. This could be done with three manual measurements. On the background the absolute values are still being used. Periodically the system has to ask the user to revalidate the weigths the system uses. This protects the system from natural changes.<br />
<br />
The system must be able to make combinations of entries inserted in the past, to generate advise in the present.<br />
Next idea is based on the MetisII project, a translation machine that translate dutch noun phrases into english ones. When time progresses the database will be filled with entries. When a new entr<br />
Advise can be stated in the form:<br />
* Het foodintake today is justifide, because in de past at day ... has the glucoselevel in blood between 4 and 8 mmmol/l after ... hours.<br />
* Het entries of today are compared from those of the past. The result shows to take a different course of action than that of the past. On ... day were your glucose level not in the safety area of 4-8 mmol/l.<br />
<br />
The results have to been shown in a userfriendly format. In that way the user can decide if the recommendations are usefull or that the system made an error. Maybe it is posible to validate the recommendations the system generates by the user.<br />
<br />
Because more than one user is entering input to the system, other kinds of advise can be generated. It is extremly usefull with entries of new foodintake. Input of others can generate upper and downvalues wich indicates how much insulin can be used.<br />
<br />
Example of advise is:<br />
* This is new inputdata. Several persons have inserted the same input. The range of insulin intakevalues which were used lays between ... and ... units<br />
<br />
Collecting multiple glucose measurements of persons who ate the same thing, produces a cloud of points. This can be transformed to an area of prediction, which indicates the chances a person gets a hypo or a hyper.<br />
<br />
[[Image:puntenwolk.jpg]]</div>Justhttps://wiki.aardrock.com/index.php?title=Databased_advisory_System&diff=1771Databased advisory System2006-05-09T14:15:30Z<p>Just: </p>
<hr />
<div>== Advise without teaching==<br />
<br />
<br />
The user periodicaly enters their personal information into the system.<br />
<br />
Less frequent entries are:<br />
* weight/muscle mass<br />
* maximal kilojoules intake<br />
* health status<br />
<br />
Frequent entries are:<br />
* Food intake (product + volumn)<br />
* Insulin intake (volumn + type)<br />
* Glucose values<br />
* Activities/stress <br />
<br />
These entries has to be marked with a timestamp(default present time, else the time that the activity occured).<br />
<br />
The user fills the database just like he is accustomed with his own personal logboek. This is an advantage, because people gladly work with things which they already known. After time the database will be filled with entries who shows resemblance with each other.<br />
<br />
Example:<br /><br />
02-03-2006 11:50 apple 40 gram<br /><br />
02-03-2006 11:53 sandwich cheese/ham<br /><br />
02-03-2006 11:57 sandwich salad<br /><br />
02-03-2006 15:00 6,6 mmol/l glucose<br /><br />
<br />
14-03-2006 12:00 apple 30 gram<br /><br />
14-03-2006 12:05 sandwich cheese/ham<br /><br />
14-03-2006 12:12 sandwich salad<br /><br />
14-03-2006 15:00 6,5 mmol/l glucose<br /><br />
<br />
The system forms relations by the input taken for the past.<br />
<br />
Absolut geweights are acquired by manual weighting and inserted into the system. In normal life, people use the same amount of food. they use the same plate and cups. The system could be provided with a function that relates the absolute weights with the relative weigths. This could be done with three manual measurements. On the background the absolute values are still being used. Periodically the system has to ask the user to revalidate the weigths the system uses. This protects the system from natural changes.<br />
<br />
The system must be able to make combinations of entries inserted in the past, to generate advise in the present. Advise can be stated in the form:<br />
* Het foodintake today is justifide, because in de past at day ... has the glucoselevel in blood between 4 and 8 mmmol/l after ... hours.<br />
* Het entries of today are compared from those of the past. The result shows to take a different course of action than that of the past. On ... day were your glucose level not in the safety area of 4-8 mmol/l.<br />
<br />
The results have to been shown in a userfriendly format. In that way the user can decide if the recommendations are usefull or that the system made an error. Maybe it is posible to validate the recommendations the system generates by the user.<br />
<br />
Because more than one user is entering input to the system, other kinds of advise can be generated. It is extremly usefull with entries of new foodintake. Input of others can generate upper and downvalues wich indicates how much insulin can be used.<br />
<br />
Example of advise is:<br />
* This is new inputdata. Several persons have inserted the same input. The range of insulin intakevalues which were used lays between ... and ... units<br />
<br />
Collecting multiple glucose measurements of persons who ate the same thing, produces a cloud of points. This can be transformed to an area of prediction, which indicates the chances a person gets a hypo or a hyper.<br />
<br />
[[Image:puntenwolk.jpg]]</div>Justhttps://wiki.aardrock.com/index.php?title=File:Puntenwolk.jpg&diff=1769File:Puntenwolk.jpg2006-05-09T14:13:26Z<p>Just: </p>
<hr />
<div></div>Justhttps://wiki.aardrock.com/index.php?title=Databased_advisory_System&diff=1763Databased advisory System2006-05-09T12:44:06Z<p>Just: setup page</p>
<hr />
<div>== Advise without teaching==<br />
<br />
<br />
The user periodicaly enters their personal information into the system.<br />
<br />
Less frequent entries are:<br />
* weight/muscle mass<br />
* maximal kilojoules intake<br />
* health status<br />
<br />
Frequent entries are:<br />
* Food intake (product + volumn)<br />
* Insulin intake (volumn + type)<br />
* Glucose values<br />
* Activities/stress <br />
<br />
These entries has to be marked with a timestamp(default present time, else the time that the activity occured).<br />
<br />
The user fills the database just like he is accustomed with his own personal logboek. This is an advantage, because people gladly work with things which they already known. After time the database will be filled with entries who shows resemblance with each other.<br />
<br />
Example:<br /><br />
02-03-2006 11:50 apple 40 gram<br /><br />
02-03-2006 11:53 sandwich cheese/ham<br /><br />
02-03-2006 11:57 sandwich salad<br /><br />
02-03-2006 15:00 6,6 mmol/l glucose<br /><br />
<br />
14-03-2006 12:00 apple 30 gram<br /><br />
14-03-2006 12:05 sandwich cheese/ham<br /><br />
14-03-2006 12:12 sandwich salad<br /><br />
14-03-2006 15:00 6,5 mmol/l glucose<br /><br />
<br />
The system forms relations by the input taken for the past.<br />
<br />
Absolut geweights are acquired by manual weighting and inserted into the system. In normal life, people use the same amount of food. they use the same plate and cups. The system could be provided with a function that relates the absolute weights with the relative weigths. This could be done with three manual measurements. On the background the absolute values are still being used. Periodically the system has to ask the user to revalidate the weigths the system uses. This protects the system from natural changes.<br />
<br />
The system must be able to make combinations of entries inserted in the past, to generate advise in the present. Advise can be stated in the form:<br />
* Het foodintake today is justifide, because in de past at day ... has the glucoselevel in blood between 4 and 8 mmmol/l after ... hours.<br />
* Het entries of today are compared from those of the past. The result shows to take a different course of action than that of the past. On ... day were your glucose level not in the safety area of 4-8 mmol/l.<br />
<br />
The results have to been shown in a userfriendly format. In that way the user can decide if the recommendations are usefull or that the system made an error. Maybe it is posible to validate the recommendations the system generates by the user.<br />
<br />
Because more than one user is entering input to the system, other kinds of advise can be generated. It is extremly usefull with entries of new foodintake. Input of others can generate upper and downvalues wich indicates how much insulin can be used.<br />
<br />
Example of advise is:<br />
* This is new inputdata. Several persons have inserted the same input. The range of insulin intakevalues which were used lays between ... and ... units<br />
<br />
Collecting multiple glucose measurements of persons who ate the same thing, produces a cloud of points. This can be transformed to an area of prediction, which indicates the chances a person gets a hypo or a hyper.</div>Justhttps://wiki.aardrock.com/index.php?title=DesignThoughts&diff=1761DesignThoughts2006-05-09T11:16:11Z<p>Just: </p>
<hr />
<div>= Design Thoughts =<br />
<br />
We can use this page to describe how we intend to implement certain ideas, and to discuss designs. Note that this is from the Developer's point of view, while the [wiki:Stories Stories] and CheetahUserManual are from the User's point of view.<br />
<br />
* [[CheetahInstallation]]<br />
* [[SoftwareUpdates]]<br />
* [[CheetahApplicationLifecycle]]<br />
* [[Internationalization]] (I18N)<br />
* [[ExceptionLogging]]<br />
* [[ProgressMonitoring]]<br />
* [[UserPreferences]]<br />
* [[DataModel|Data Model]]<br />
* [[RegistrationProcedure| Registration Procedure]]<br />
* [[LoginProcedure| Login procedure]]<br />
* [[Wizard Rabbit Treasurer]]<br />
* [[Advisory System]]<br />
* [[Condition Effect Learning]]<br />
* [[Databased advisory System]]<br />
* [[Validations]]</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1760LogboekJustBoerlage2006-05-09T11:09:50Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
<br />
<br />
{| <br />
|Datum || Van || Tot || Duur || Cumulatief || Activiteit <br />
|-<br />
|08-02-06 || 13:00 || 16:00 || 03:00 || 03:00 || Vergadering INFOSP en AardRock<br />
|- <br />
|13-02-06 || 15:00 || 16:30 || 01:30 || 04:30 || Vergadering INFOSP <br />
|- <br />
|14-02-06 || 15:00 || 18:00 || 03:00 || 07:30 || XP game <br />
|-<br />
|20-02-06 || 15:00 || 16:30 || 01:30 || 09:00 || Vergadering INFOSP <br />
|- <br />
|21-02-06 || 15:00 || 17:00 || 02:00 || 11:00 || Vergadering AardRock <br />
|- <br />
|27-02-06 || 15:00 || 17:00 || 02:00 || 13:00 || Vergadering INFOSP <br />
|- <br />
|28-02-06 || 15:00 || 17:30 || 02:30 || 15:30 || Vergadering AardRock <br />
|- <br />
|05-03-06 || 19:00 || 22:30 || 03:30 || 19:00 || Gezocht naar medische bronnen <br />
|- <br />
|06-03-06 || 12:00 || 15:00 || 03:00 || 22:00 || Emails gelezen; medische bronnen verwerkt <br />
|-<br />
|06-03-06 || 15:00 || 17:00 || 02:00 || 24:00 || Vergadering INFOSP <br />
|-<br />
|07-03-06 || 15:00 || 17:30 || 02:30 || 26:30 || Vergadering AardRock <br />
|-<br />
|12-03-06 || 18:00 || 21:00 || 03:00 || 29:30 || Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
|-<br />
|14-03-06 || 12:00 || 15:30 || 03:30 || 33:00 || Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
|-<br />
|20-03-06 || 12:30 || 16:30 || 04:00 || 37:00 || Voedingtabel info verwerken; vergadering INFOSP <br />
|-<br />
|21-03-06 || 10:30 || 17:00 || 06:30 || 43:30 || Story 23, Notulen maken; <br />
|-<br />
|22-03-06 || 13:00 || 15:30 || 02:30 || 46:00 || Story 21, praatje met hans <br />
|-<br />
|27-03-06 || 11:30 || 16:30 || 05:00 || 51:00 || Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
|-<br />
|28-03-06 || 12:30 || 17:00 || 04:30 || 55:30 || Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
|- <br />
|03-04-06 || 15:00 || 16:00 || 01:00 || 56:30 || Mail lezen en vergadering <br />
|-<br />
|03-04-06 || 23:00 || 24:00 || 01:00 || 57:30 || Notulen maken <br />
|-<br />
|04-04-06 || 13:30 || 16:30 || 03:30 || 61:00 || Verwerken gegevens van GI<br />
|-<br />
|29-04-06 || 12:00 || 14:00 || 02:00 ||||Lezen van dieet relateerde info<br />
|-<br />
|30-04-06 || 12:00 || 15:00 || 03:00 ||||Lezen van dieet relateerde info<br />
|-<br />
|02-05-06 || 10:00 || 19:30 || 09:30 ||||ontwikkeling advieserend model<br />
|-<br />
|09-05-06 || 9:30 || 17:00 || 07:30 || || ontwikkeling advieserend model, lezen maven hfd 1& 2<br />
|-}</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1759LogboekJustBoerlage2006-05-09T10:56:33Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
<br />
<br />
{| <br />
|Datum || Van || Tot || Duur || Cumulatief || Activiteit <br />
|-<br />
|08-02-06 || 13:00 || 16:00 || 03:00 || 03:00 || Vergadering INFOSP en AardRock<br />
|- <br />
|13-02-06 || 15:00 || 16:30 || 01:30 || 04:30 || Vergadering INFOSP <br />
|- <br />
|14-02-06 || 15:00 || 18:00 || 03:00 || 07:30 || XP game <br />
|-<br />
|20-02-06 || 15:00 || 16:30 || 01:30 || 09:00 || Vergadering INFOSP <br />
|- <br />
|21-02-06 || 15:00 || 17:00 || 02:00 || 11:00 || Vergadering AardRock <br />
|- <br />
|27-02-06 || 15:00 || 17:00 || 02:00 || 13:00 || Vergadering INFOSP <br />
|- <br />
|28-02-06 || 15:00 || 17:30 || 02:30 || 15:30 || Vergadering AardRock <br />
|- <br />
|05-03-06 || 19:00 || 22:30 || 03:30 || 19:00 || Gezocht naar medische bronnen <br />
|- <br />
|06-03-06 || 12:00 || 15:00 || 03:00 || 22:00 || Emails gelezen; medische bronnen verwerkt <br />
|-<br />
|06-03-06 || 15:00 || 17:00 || 02:00 || 24:00 || Vergadering INFOSP <br />
|-<br />
|07-03-06 || 15:00 || 17:30 || 02:30 || 26:30 || Vergadering AardRock <br />
|-<br />
|12-03-06 || 18:00 || 21:00 || 03:00 || 29:30 || Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
|-<br />
|14-03-06 || 12:00 || 15:30 || 03:30 || 33:00 || Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
|-<br />
|20-03-06 || 12:30 || 16:30 || 04:00 || 37:00 || Voedingtabel info verwerken; vergadering INFOSP <br />
|-<br />
|21-03-06 || 10:30 || 17:00 || 06:30 || 43:30 || Story 23, Notulen maken; <br />
|-<br />
|22-03-06 || 13:00 || 15:30 || 02:30 || 46:00 || Story 21, praatje met hans <br />
|-<br />
|27-03-06 || 11:30 || 16:30 || 05:00 || 51:00 || Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
|-<br />
|28-03-06 || 12:30 || 17:00 || 04:30 || 55:30 || Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
|- <br />
|03-04-06 || 15:00 || 16:00 || 01:00 || 56:30 || Mail lezen en vergadering <br />
|-<br />
|03-04-06 || 23:00 || 24:00 || 01:00 || 57:30 || Notulen maken <br />
|-<br />
|04-04-06 || 13:30 || 16:30 || 03:30 || 61:00 || Verwerken gegevens van GI<br />
}</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1758LogboekJustBoerlage2006-05-09T10:55:24Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
<br />
<br />
{| <br />
|Datum || Van || Tot || Duur || Cumulatief || Activiteit <br />
|-<br />
|08-02-06 || 13:00 || 16:00 || 03:00 || 03:00 || Vergadering INFOSP en AardRock<br />
|- <br />
|13-02-06 || 15:00 || 16:30 || 01:30 || 04:30 || Vergadering INFOSP <br />
|- <br />
|14-02-06 || 15:00 || 18:00 || 03:00 || 07:30 || XP game <br />
|-<br />
|20-02-06 || 15:00 || 16:30 01:30 || 09:00 || Vergadering INFOSP <br />
|- <br />
|21-02-06 || 15:00 || 17:00 02:00 || 11:00 || Vergadering AardRock <br />
|- <br />
|27-02-06 || 15:00 || 17:00 02:00 || 13:00 || Vergadering INFOSP <br />
|- <br />
|28-02-06 || 15:00 || 17:30 02:30 || 15:30 || Vergadering AardRock <br />
|- <br />
|05-03-06 || 19:00 || 22:30 03:30 || 19:00 || Gezocht naar medische bronnen <br />
|- <br />
|06-03-06 || 12:00 || 15:00 03:00 || 22:00 || Emails gelezen; medische bronnen verwerkt <br />
|-<br />
|06-03-06 || 15:00 || 17:00 || 02:00 || 24:00 || Vergadering INFOSP <br />
|-<br />
|07-03-06 || 15:00 || 17:30 || 02:30 || 26:30 || Vergadering AardRock <br />
|-<br />
|12-03-06 || 18:00 || 21:00 || 03:00 || 29:30 || Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
|-<br />
|14-03-06 || 12:00 || 15:30 || 03:30 || 33:00 || Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
|-<br />
|20-03-06 || 12:30 || 16:30 || 04:00 || 37:00 || Voedingtabel info verwerken; vergadering INFOSP <br />
|-<br />
|21-03-06 || 10:30 || 17:00 || 06:30 || 43:30 || Story 23, Notulen maken; <br />
|-<br />
|22-03-06 || 13:00 || 15:30 || 02:30 || 46:00 || Story 21, praatje met hans <br />
|-<br />
|27-03-06 || 11:30 || 16:30 || 05:00 || 51:00 || Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
|-<br />
|28-03-06 || 12:30 || 17:00 || 04:30 || 55:30 || Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
|- <br />
|03-04-06 || 15:00 || 16:00 || 01:00 || 56:30 || Mail lezen en vergadering <br />
|-<br />
|03-04-06 || 23:00 || 24:00 || 01:00 || 57:30 || Notulen maken <br />
|-<br />
|04-04-06 || 13:30 || 16:30 || 03:30 || 61:00 || Verwerken gegevens van GI<br />
}</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1757LogboekJustBoerlage2006-05-09T10:53:49Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
<br />
<br />
{| <br />
|Datum || Van || Tot || Duur || Cumulatief || Activiteit <br />
|-<br />
|08-02-06 || 13:00 || 16:00 || 03:00 || 03:00 || Vergadering INFOSP en AardRock<br />
|- <br />
|13-02-06 || 15:00 || 16:30 || 01:30 || 04:30 || Vergadering INFOSP <br />
|- <br />
|14-02-06 || 15:00 || 18:00 || 03:00 || 07:30 || XP game <br />
|-<br />
20-02-06 || 15:00 || 16:30 01:30 || 09:00 || Vergadering INFOSP <br />
|- <br />
21-02-06 || 15:00 || 17:00 02:00 || 11:00 || Vergadering AardRock <br />
|- <br />
27-02-06 || 15:00 || 17:00 02:00 || 13:00 || Vergadering INFOSP <br />
|- <br />
28-02-06 || 15:00 || 17:30 02:30 || 15:30 || Vergadering AardRock <br />
|- <br />
05-03-06 || 19:00 || 22:30 03:30 || 19:00 || Gezocht naar medische bronnen <br />
|- <br />
06-03-06 || 12:00 || 15:00 03:00 || 22:00 || Emails gelezen; medische bronnen verwerkt <br />
|-<br />
06-03-06 || 15:00 || 17:00 || 02:00 || 24:00 || Vergadering INFOSP <br />
|-<br />
07-03-06 || 15:00 || 17:30 || 02:30 || 26:30 || Vergadering AardRock <br />
|-<br />
12-03-06 || 18:00 || 21:00 || 03:00 || 29:30 || Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
|-<br />
14-03-06 || 12:00 || 15:30 || 03:30 || 33:00 || Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
|-<br />
20-03-06 || 12:30 || 16:30 || 04:00 || 37:00 || Voedingtabel info verwerken; vergadering INFOSP <br />
|-<br />
21-03-06 || 10:30 || 17:00 || 06:30 || 43:30 || Story 23, Notulen maken; <br />
|-<br />
22-03-06 || 13:00 || 15:30 || 02:30 || 46:00 || Story 21, praatje met hans <br />
|-<br />
27-03-06 || 11:30 || 16:30 || 05:00 || 51:00 || Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
|-<br />
28-03-06 || 12:30 || 17:00 || 04:30 || 55:30 || Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
|- <br />
03-04-06 || 15:00 || 16:00 || 01:00 || 56:30 || Mail lezen en vergadering <br />
|-<br />
03-04-06 || 23:00 || 24:00 || 01:00 || 57:30 || Notulen maken <br />
|-<br />
04-04-06 || 13:30 || 16:30 || 03:30 || 61:00 || Verwerken gegevens van GI<br />
}</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1756LogboekJustBoerlage2006-05-09T10:51:34Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
<br />
<br />
{| <br />
|Datum || Van || Tot || Duur || Cumulatief || Activiteit <br />
|-<br />
|08-02-06 || 13:00 || 16:00 || 03:00 || 03:00 || Vergadering INFOSP en AardRock<br />
|- <br />
|13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
|- <br />
|14-02-06 15:00 18:00 03:00 07:30 XP game <br />
|-<br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
|- <br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
|- <br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
|- <br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
|- <br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
|- <br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
|-<br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
|-<br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
|-<br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
|-<br />
14-03-06 12:00 15:30 03:30 33:00 Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
|-<br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
|-<br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
|-<br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
|-<br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
|-<br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
|- <br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
|-<br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
|-<br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI<br />
}</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1755LogboekJustBoerlage2006-05-09T10:50:01Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
<br />
<br />
{| border="1" cellspacing="0" cellpadding="6" align="center"<br />
<br />
Datum Van Tot Duur Cumulatief Activiteit <br />
|-<br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock<br />
|- <br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
|- <br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
|-<br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
|- <br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
|- <br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
|- <br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
|- <br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
|- <br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
|-<br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
|-<br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
|-<br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
|-<br />
14-03-06 12:00 15:30 03:30 33:00 Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
|-<br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
|-<br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
|-<br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
|-<br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
|-<br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
|- <br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
|-<br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
|-<br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI<br />
}</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1754LogboekJustBoerlage2006-05-09T10:34:29Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
Datum Van Tot Duur Cumulatief Activiteit <br />
<br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock<br />
<br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
<br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
<br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
<br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
<br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
<br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
<br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
<br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
<br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
<br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
<br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
<br />
14-03-06 12:00 15:30 03:30 33:00 Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
<br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
<br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
<br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
<br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
<br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
<br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
<br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
<br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1753LogboekJustBoerlage2006-05-09T10:34:06Z<p>Just: </p>
<hr />
<div> == Logboek Just Boerlage ==<br />
<nowiki><br />
Datum Van Tot Duur Cumulatief Activiteit <br />
<br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock<br />
<br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
<br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
<br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
<br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
<br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
<br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
<br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
<br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
<br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
<br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
<br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
<br />
14-03-06 12:00 15:30 03:30 33:00 Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
<br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
<br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
<br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
<br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
<br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
<br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
<br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
<br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI<br />
</nowiki></div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1752LogboekJustBoerlage2006-05-09T10:33:20Z<p>Just: </p>
<hr />
<div><nowiki>Insert non-formatted text here</nowiki>== Logboek Just Boerlage ==<br />
<br />
Datum Van Tot Duur Cumulatief Activiteit <br />
<br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock<br />
<br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
<br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
<br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
<br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
<br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
<br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
<br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
<br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
<br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
<br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
<br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
<br />
14-03-06 12:00 15:30 03:30 33:00 Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
<br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
<br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
<br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
<br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
<br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
<br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
<br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
<br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1751LogboekJustBoerlage2006-05-09T10:32:47Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
Datum Van Tot Duur Cumulatief Activiteit <br />
<br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock<br />
<br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
<br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
<br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
<br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
<br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
<br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
<br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
<br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
<br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
<br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
<br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
<br />
14-03-06 12:00 15:30 03:30 33:00 Uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
<br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
<br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
<br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
<br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
<br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock<br />
<br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
<br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
<br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1750LogboekJustBoerlage2006-05-09T10:22:51Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
Datum Van Tot Duur Cumulatief Activiteit <br />
<br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock<br />
<br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
14-03-06 12:00 15:30 03:30 33:00 uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock <br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1749LogboekJustBoerlage2006-05-09T10:19:28Z<p>Just: </p>
<hr />
<div>== Logboek Just Boerlage ==<br />
<br />
|Datum |Van |Tot |Duur| Cumulatief |Activiteit | <br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock <br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
14-03-06 12:00 15:30 03:30 33:00 uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock <br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI</div>Justhttps://wiki.aardrock.com/index.php?title=LogboekJustBoerlage&diff=1748LogboekJustBoerlage2006-05-09T10:19:04Z<p>Just: </p>
<hr />
<div><br />
== Logboek Just Boerlage ==<br />
<br />
Datum Van Tot Duur Cumulatief Activiteit <br />
08-02-06 13:00 16:00 03:00 03:00 Vergadering INFOSP en AardRock <br />
13-02-06 15:00 16:30 01:30 04:30 Vergadering INFOSP <br />
14-02-06 15:00 18:00 03:00 07:30 XP game <br />
20-02-06 15:00 16:30 01:30 09:00 Vergadering INFOSP <br />
21-02-06 15:00 17:00 02:00 11:00 Vergadering AardRock <br />
27-02-06 15:00 17:00 02:00 13:00 Vergadering INFOSP <br />
28-02-06 15:00 17:30 02:30 15:30 Vergadering AardRock <br />
05-03-06 19:00 22:30 03:30 19:00 Gezocht naar medische bronnen <br />
06-03-06 12:00 15:00 03:00 22:00 Emails gelezen; medische bronnen verwerkt <br />
06-03-06 15:00 17:00 02:00 24:00 Vergadering INFOSP <br />
07-03-06 15:00 17:30 02:30 26:30 Vergadering AardRock <br />
12-03-06 18:00 21:00 03:00 29:30 Materiaal gezocht over lerende algoritmen, spelinfo voor Giel <br />
14-03-06 12:00 15:30 03:30 33:00 uitwerken spelidee; zoeken info voedingstabel; emails lezen <br />
20-03-06 12:30 16:30 04:00 37:00 Voedingtabel info verwerken; vergadering INFOSP <br />
21-03-06 10:30 17:00 06:30 43:30 Story 23, Notulen maken; <br />
22-03-06 13:00 15:30 02:30 46:00 Story 21, praatje met hans <br />
27-03-06 11:30 16:30 05:00 51:00 Story 21 en 23, Voorbereiding van het gesrek van Marco, Vergadering INFOSP <br />
28-03-06 12:30 17:00 04:30 55:30 Voorbereiding van het gesprek van Marco, Scrum, Vergadering AardRock <br />
03-04-06 15:00 16:00 01:00 56:30 Mail lezen en vergadering <br />
03-04-06 23:00 24:00 01:00 57:30 Notulen maken <br />
04-04-06 13:30 16:30 03:30 61:00 Verwerken gegevens van GI</div>Justhttps://wiki.aardrock.com/index.php?title=JustBoerlage&diff=1747JustBoerlage2006-05-09T10:16:32Z<p>Just: </p>
<hr />
<div>== Personal details ==<br />
<br />
Born may 4, 1979 <br />
Living in Amsterdam <br />
<br />
== Education ==<br />
<br />
September 2000 until now: Computer science at Utrecht University. <br />
<br />
== Hobbies ==<br />
<br />
Sports <br />
Reading <br />
Video games <br />
<br />
== Contact ==<br />
<br />
T: +31 646 396 118 <br />
E: jboerlag@cs.uu.nl <br />
MSN: just700@hotmail.com <br />
* [[LogboekJustBoerlage]]</div>Justhttps://wiki.aardrock.com/index.php?title=JustBoerlage&diff=1746JustBoerlage2006-05-09T10:16:06Z<p>Just: </p>
<hr />
<div><br />
== Personal details ==<br />
<br />
Born may 4, 1979 <br />
Living in Amsterdam <br />
<br />
== Education ==<br />
<br />
September 2000 until now: Computer science at Utrecht University. <br />
<br />
== Hobbies ==<br />
<br />
Sports <br />
Reading <br />
Video games <br />
<br />
== Contact ==<br />
<br />
T: +31 646 396 118 <br />
E: jboerlag@cs.uu.nl <br />
MSN: just700@hotmail.com <br />
* LogboekJustBoerlage</div>Just