These days, many companies store enormous amounts of text data used in their operations in digital format because computers are now used in all processes in every department. However, the valuable information in this enormous amount of text data often cannot be used effectively. Normally, such data contains a lot of useful information for company workers and it is important to use the data effectively for the development of companies. However, the volume of the text data is sometimes too enormous to use the data directly. Even if analysts spend a lot of time in order to extract useful information from the text data, it may be impossible to analyze such huge amounts of text data. Generally, clustering or grouping by similarity and naming each group to provide category information are effective ways to grasp the tendency of the whole data and systematize many ideas. However, analysis by hand can only be carried out for small volumes of data in which analysts can see all data items or ideas. Therefore, it is difficult to apply clustering by hand to the large-scale text data which is stored in companies. If clustering and naming by analysts can be applied to enormous amounts of text data, it will be useful for extracting valuable information. In this study, we propose a new method based on the combination of clustering by hand and text classification in order to effectively analyze large-scale digital data which is stored in a company. The first step of the proposed method is to provide category information by hand for the sample data selected randomly from all the text data. The next step is to estimate classifiers through learning of this sample data, and to classify the rest of the data using the classifiers automatically. Using the proposed method, enormous amounts of text data can be systemized provided that only a small sample set is analyzed by hand. To verify the effectiveness of the proposed method, it is applied to the large-scale text data which was stored in a company as a case study.

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Probability inequalities are used as a means to evaluate the upper bounds of upper probability for an average of some random variables based on finite stochastic properties, excluding the probability distribution functions of respective random variables. Note that in the case of applying the probability inequality, it is not necessary for the population of each random variable to be identical. Of the existing probability inequalities, Hoeffding probability inequality is highly regarded as an excellent probability inequality from the viewpoint of performance. Hoeffding probability inequality evaluates the upper bounds of upper probability for an average of some random variables based on limited stochastic properties such as expectation, variance and codomain in each random variable. However, we consider that there is a room to improve the performance of Hoeffding probability inequality. In this study, we demonstrate a technique for improving the performance of Hoeffding probability inequality in the case that the population of each random variable is not always identical.

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Tactile inspection still plays a major role in inspection processes in industry. Tactile inspection requires upper limb work with repetitive touching of the surface of objects. This type of task causes musculoskeletal load on the upper limb,especially regional excessive load on the wrist joint when the object orientation is in the frontal plane. Therefore,it is important to consider how the load on the wrist joint in the frontal plane condition can be decreased. In this paper,we investigate the effect of the upper limb position,incident to a change of direction of the hand,on the wrist load during tactile inspection. Ten healthy male subjects participated in this experiment. They were asked to inspect objects using three directions of the hand. We used 0,45 and 90 degrees for the direction of hand conditions. The upper limb activities were measured by performing electromyography (EMG). The control force was also measured using a load cell. Furthermore, subjective indices for the burden and difficulty of the task were investigated. EMG was performed at the upper part of the trapezius muscle,the middle part of the deltoid muscle, the clavicular part of the pectoralis major muscle, the biceps brachii muscle, the pronator teres muscle, the extensor carpi radialis longus muscle and the extensor carpi ulnaris muscle. The results showed that tactile inspection in the 90 degrees condition can decrease the load on the wrist joint. However, there is a trade-offbetween the load on the wrist joint and the load on the shoulder and elbow joints in regard to hand direction. Therefore, it is necessary to evaluate the comprehensive upper limb muscle load. The sum of EMGs, the sum of the squared EMGs and the EMG of extensor carpi ulnaris muscle were used as the indicator of comprehensive upper limb muscle load. The result showed that the direction of the hand should be 0degrees at the right side of the surface of objects and 90degrees at the left side of the surface of objects.

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In this paper, we study a privacy preserving linear regression analysis. We propose a new protocol of a distributed calculation method that calculates a least squares estimator, in the case that two parties have different types of explanatory variables. We show the security of privacy in the proposed protocol. Because the protocol have iterative calculations, we evaluate the number of iterations via numerical experiments. Finally, we show an extended protocol that is a distributed calculation method for k parties.

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Human society is now facing serious environmental problems. It is necessary to build a sustainable society in which human economic activities and nature can exist together. To achieve this, environmental education is seen as a way to encourage the youth to have broad perspectives and cooperative attitudes in regard to environmental problems. This study thus aims to develop a card game “GAWL,” based on the Monopoly DEAL, which enables the youth to have this perspective attitude regarding environmental problems through communication among players. This game consists of 146 cards in the three categories of effect, action and eco-point. Using these cards, players gather more ecopoints and develop cooperative attitudes in regard to preventing global warming. Experimental testing of the game was conducted with 12 university students as subjects. In quizzes on selecting environment-friendly actions, the correct answer ratio changed from 44.4% to 66.7% before and after the game. In response to a questionnaire, all of the students answered that they could have fun with the game. These results verified the educational effectiveness of the game.

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Human society is facing serious environmental problems and must build a sustainable society. To achieve this, there has been a recent focus on game materials as an important tool for environmental education in schools and educational institutions. However, existing environmental education games do not always include the environmental education content which an educator intends to teach. This study thus aims to develop a support system for making an environmental education game which includes intended environmental education content. This study devises a procedure to create a “sugoroku” game for environmental education, constructs a database arranged with the environmental information, and designs the basic structure of a game. This study then develops a support system for making an environmental education game with these materials. Furthermore, this study applies the system to make a game and implements it.

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The continuous-review (Q, r) inventory model for simultaneously determining economic order quantity and economic reorder point has been considered. In this paper, we investigate an improvement in the basic continuous-review (Q, r) inventory model. Further, an additional procedure to obtain a feasible solution based on the continuous-review (Q, r) inventory model is proposed.

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