Videos with tag mining
Results 1-6 of 6
 
19:26
19:26
19:26

Using User Interface Toolkits to Improve Human Computer Interaction in Medical Diagnostics

User interface toolkits are software aids used by developers to add to interface design. The libraries, connecting application programming interfaces (APIs) or even analysis tools allow developers to improve the human computer interaction (HCI) process in less development and resource time than they would if they were to design the interface from scratch.

In this video, we examine effectiveness of toolkits in collecting and analyzing patient data for various medical diagnostic objectives versus traditional development and the challenges and limitations with these toolkits. We evaluate a medical health analysis diagnostic service (MHADS) as an example of a user interface toolkit that would address some of these challenges and limitations. Using toolkits such as a statistical analysis tools and an integrated development environment (IDE) that includes web language libraries, the MHADS software demonstrates that user interface toolkits do indeed improve human computer interaction in medical diagnostics by reducing data collection, analysis and development time.

Added: 1264 days ago by dmitchnick

Views: 1639 | Comments: 0 | Not yet rated

 
00:31.44
00:31.44
00:31.44

Next Stop Recommender-30-second video

User wandering behaviours may involve many location visits in different order. The research team has proposed an algorithm which can provide users recommendation for their next visit according to the similarity of their behaviours between each others and the connections amongst locations. In order to test the effectiveness of proposed algorithm the research team develops a mobile app – Next Stop Recommender – for Android platform. The mobile app and the web user interface can collect sequential positioning data of travelers. The server side Java servlets can find the visit lists of travelers and summarize popular route patterns; moreover, it can turn the route patterns into recommendation rules and make recommendations for travelers. We can record mobile learner's behaviors (including where they spent more time and what is the sequence for learning) and compare one's with others to make recommendations (could be more than one recommendation when the learner asks) for the mobile learners.

Added: 1456 days ago by maiga

Views: 538 | Comments: 0 | Not yet rated

 
07:04
07:04
07:04

Next Stop Recommendation Service

Next Stop Recommendation Service uses time-series data mining technique to calculate next stop recommendation according to users' wandering behaviours. Dirksen Liu and Maiga Chang. (2011). Next-Stop Recommendation to Travelers according to Their Sequential Wandering Behaviours. Journal of Internet Technology, 12(1), 171-179. (SCI-E, impact factor 0.448) http://nextstop.dyndns.info:4735

Added: 1620 days ago by maiga

Views: 305 | Comments: 0 | Not yet rated

 
21:15
21:15
21:15

Towards a Framework For Automated Open Source Repository...

Describes a toolset framework for the extraction of data from open source software repositories such as Bugzilla and CVS.

Added: 2858 days ago by under_score

Views: 578 | Comments: 0 | star star star star star star star star star star 

 
26:28
26:28
26:28

Classifying Software Changes: Clean or Buggy?

Abstract: The paper under review suggests novel technique, Change Classification, for predicting latent software bugs by implementing machine learning algorithms, namely the Support Vector Machine algorithm to classify changes as either clean or buggy immediately after the commit has been made. The classifier is trained using features in the SCM repository of the system under investigation. Results were tested with 12 open source projects with 78% accuracy and a 60% buggy change recall on average.

Added: 3044 days ago by mohammedy

Views: 268 | Comments: 0 | Not yet rated

 
19:24
19:24
19:24

Text mining and software engineering

Witte, R., Li, Y., Zhang, Y. and Rilling, J.: ‘Text mining and software engineering: an integrated source code and document analysis approach’. IET Softw., 2008, 2(1), pp. 3 – 16. Retrieved September 2008 from http://0-ieeexplore.ieee.org.aupac.lib.athabascau.ca/iel5/4124007/4460888/04460890.pdf?tp=&arnumber=4460890&isnumber=4460888. doi: 10.1049/iet-sen:20070110

Added: 3294 days ago by Laurie

Views: 549 | Comments: 0 | star star star star star star star star star star