Abstract: In recent years, the number of document data has been
increasing since the spread of the Internet. Many methods have been
studied for extracting topics from large document data. We proposed
Independent Topic Analysis (ITA) to extract topics independent of
each other from large document data such as newspaper data. ITA is a
method for extracting the independent topics from the document data
by using the Independent Component Analysis. The topic represented
by ITA is represented by a set of words. However, the set of words
is quite different from the topics the user imagines. For example,
the top five words with high independence of a topic are as follows.
Topic1 = {"scor", "game", "lead", "quarter", "rebound"}. This Topic
1 is considered to represent the topic of "SPORTS". This topic name
"SPORTS" has to be attached by the user. ITA cannot name topics.
Therefore, in this research, we propose a method to obtain topics easy
for people to understand by using the web search engine, topics given
by the set of words given by independent topic analysis. In particular,
we search a set of topical words, and the title of the homepage of
the search result is taken as the topic name. And we also use the
proposed method for some data and verify its effectiveness.
Abstract: The purpose of this research is to construct a watching system that monitors human activity in a room and detects abnormalities at an early stage to prevent unattended deaths of people living alone. In this article, we propose a method whereby highly urgent abnormal conditions of a person are determined by changes in the concentration of CO2 generated from activity and respiration in a room. We also discussed the effects the amount of activity has on the determination. The results showed that this discrimination method is not dependent on the amount of activity and is effective in judging highly urgent abnormal conditions.
Abstract: The purpose of this research is to improve the convenience of waiting for trains at level crossings and stations and to prevent accidents resulting from forcible entry into level crossings, by providing level crossing users and passengers with information that tells them when the next train will pass through or arrive. For this paper, we proposed methods for estimating operation by means of an average value method, variable response smoothing method, and exponential smoothing method, on the basis of open data, which has low accuracy, but for which performance schedules are distributed in real time. We then examined the accuracy of the estimations. The results showed that the application of an exponential smoothing method is valid.
Abstract: In this paper, we present a method of applying
Independent Topic Analysis (ITA) to increasing the number of
document data. The number of document data has been increasing
since the spread of the Internet. ITA was presented as one method
to analyze the document data. ITA is a method for extracting the
independent topics from the document data by using the Independent
Component Analysis (ICA). ICA is a technique in the signal
processing; however, it is difficult to apply the ITA to increasing
number of document data. Because ITA must use the all document
data so temporal and spatial cost is very high. Therefore, we
present Incremental ITA which extracts the independent topics from
increasing number of document data. Incremental ITA is a method
of updating the independent topics when the document data is added
after extracted the independent topics from a just previous the data.
In addition, Incremental ITA updates the independent topics when the
document data is added. And we show the result applied Incremental
ITA to benchmark datasets.
Abstract: In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy), using this information to judge such conditions as bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as “normal” when the person was in good physical condition or as “abnormal” when the person was in bad physical condition.