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Fingerprint classification reduces the number of possible matches in automated fingerprint identification systems by categorizing fingerprints into predefined classes. Support vector machines (SVMs) are widely used in pattern classification and have produced high accuracy when performing fingerprint classification. In order to effectively apply SVMs to(More)
It is becoming harder to find an app on one's smart phone due to the increasing number of apps available and installed on smart phones today. We collect sensory data including app use from smart phones, to perform a comprehensive analysis of the context related to mobile app use, and build prediction models that calculate the probability of an app in the(More)
As wireless communication advances, research on location-based services using mobile devices has attracted interest, which provides information and services related to user's physical location. As increasing information and services, it becomes difficult to find a proper service that reflects the individual preference at proper time. Due to the small screen(More)
AbsfmcfVarious digital characters, which are automatic and intelligent, are attempted with the introduction of artificial intelligence or artificial life. Since P character’s behaior is designed by a developer, the style can be static and simple. Even complex patterns designed by a developer cannot satisfy various users and easily make them feel tedious. A(More)
Ensuring the validity and usability of activity recognition approaches requires agreement on a set of standard evaluation methods. Due to the diversity of the sensors and other hardware employed, however, designing, implementing, and accepting standard tests is a difficult task. This article presents an initiative to evaluate activity recognition systems: a(More)
Much research in ubiquitous computing assumes that a user's phone will be always on and at-hand, for collecting user context and for communicating with a user. Previous work with the previous generation of mobile phones has shown that such an assumption is false. Here, we investigate whether this assumption about users' proximity to their mobile phones(More)
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produced valuable results. However the medical field requires not only a high-accuracy classifier, but also the in-depth analysis and understanding of classification rules obtained.(More)
With advances in physiological sensors, we are able to understand people's physiological status and recognize stress to provide beneficial services. Despite the great potential in physiological stress recognition, there are some critical issues that need to be addressed such as the sensitivity and variability of physiology to many factors other than stress(More)