The personality construct “rigidity” refers to lacking in flexibility and adaptability when thinking and solving the problems. “More rigid” persons are more difficult to adapt themselves to new surroundings, to behave in accordance with the circumstances, and to change the strategies according to the problems than “less rigid” persons. “Rigidity” sometimes hinders person's vocational activities and occupational decision making. Therefore, when persons make career choices, it is very useful for them to comprehend the nature of their own “rigidity.” In the present study, we constructed the rigidity scale and developed the supporting tool by using “rigidity” for persons' career decision making.
This paper presents a method of discriminating human facial expressions using 5 pattern classifiers, where features based on density distributions are extracted from target regions set in facial feature points. Observing human facial expressions in videos, we could find that wrinkles appear in regions of correlated mimic muscles. The proposed method extracts the degree of similarity based on Zero-Mean Normalized Cross-Correlation as features from target areas where wrinkles often appear. And, 5 pattern classifiers, namely, Nearest Neighbor, Random Forests, Logistic Regression, Support Vector Machine, and Neural Network, are applied to discrimination of 6 basic facial expressions. The efficiency of the proposed method has been confirmed using public facial expression databases.
This study focuses on the development of an experimental system for collaborative problem solving in large groups. The goal of this study was to construct and investigate the following two points: (1) to design a prototype of a computer-based conversation system for problem solvers that are distributed in a local network, and (2) To use this system as illusionary collaborative partners and investigate the factors that influences perspective change during problem solving. A conversation agent was constructed where conversations were generated based on the rule based system. In the verification experiment, the participants' attitude was directed in a way that they thought they were interacting with real human partners. The main point of the experiment was to test the reliability of the experimental paradigm. Results show that the use of the conversational agents as illusionary partners was successful. Throughout the experiment, the so-called `minority influence' was tested and it was found that the presence of a member with different perspectives can influence the problem solvers thinking strategy.
Although rating scales are still a mainstay of data acquisition in psychology and cognitive science, we do not have ample knowledge about how rating decisions unfold over time. In this exploratory study PC cursor trajectories were recorded and analyzed to probe internal states in rating decisions. Major findings are: 1) the variability of cursor trajectories and response RT are highly correlated suggesting that the trajectory variability is the cause of Inverted-U RT effect. 2) The trajectories consist of quick saccadic-like components that are called “strokes” in this paper. The distribution of strokes differed across tasks as a function of cognitive loads. 3) The shape and speed of tangential velocity of trajectories may reflect participant's internal states, especially when cognitive loads are high. Finally, 4) we can infer the decisional vacillation and hesitation using the trajectories. In particular, rating decisions for middle categories are more susceptible to decisional fluctuation. Several suggestions to psychometric theory are provided.
This paper proposes a method for estimating fuzzy membership functions of human emotion from facial expression images. The membership functions are based on the dimensional model of emotion and are defined on the emotion space with coordinate axes of valence and arousal. We discuss two models of membership functions. a) The first model uses results of subjective evaluation experiments for learning facial expression images where mean value and standard deviation for each facial image are respectively adopted to mean and spread parameters of the corresponding membership function. b) The second model is a modification of the first model by introducing information of the distribution of the data in the facial image space. The performance of our method is evaluated by approximation error of the estimated membership functions to the original ones. As statistical techniques, canonical correlation analysis (CCA) and kernel CCA are employed and applied to gray-scale image based data. Using two facial image databases of male and female, our experimental results show valid estimation results which have at most less than twice as much dispersion of that of subjective evaluation by human observers, and in the sense of the dispersion, availability of the proposed method is indicated.
This paper evaluates some correlations between psychosomatic states and human activities such as (1) a frequency and an elapsed time of an opening/closing actions of clamshell formed mobile phones, and (2) a duration of sleeping time. A practical experiment is performed to collect some records of mobile phone activities and sleeping time of 24 subjects for about two months. In addition, a psychological test, Cornell Medical Index (CMI), is carried out to quantify psychosomatic states of these subjects. The result shows the elapsed time follows a distribution which is composed of two power-law functions. The time regions of the functions are different, one is short time region and the other is long time. It also reveals that the human activities have correlation with the psychosomatic state, in particular, there are some correlations among the indices of the power-law functions of the mobile phone activity, the sleeping time bythe self-report and the score of the psychological tests for each subject.
In recent years, an increase in number of school phobia children becomes matter of concern in Japan. The mind disease occupies the greater portion of factor which leads to longer school phobia. However, it is very difficult for general pediatricians to diagnose these since the criterion for the diagnosis is not systematized. Therefore, the criterion which can be treated easily for general pediatricians is required for the rapid medical treatment including introducing to specialized agencies. In this paper, we propose the diagnostic criterion creating system for children's mind disease in school phobia using Genetic Algorithm (GA). In the experimental result, the diagnostic criterion created by proposed system has higher accuracy than the diagnostic criterion without GA.
Centrality is a core concept in the field of network analysis and, therefore, much discussion is concerned with the centrality of each position (node) and less with peripherality. However, we can see that peripheral nodes are faced with a heavier burden than central nodes when expanding telecommunications, transportation, or other networks. Therefore, it is important to discuss the notion of peripherality. Peripherality measures would provide a solution for cost burdenproblems in such situations. In this paper, we propose a new peripherality measure axiomatically. Moreover, pairwise stability of networksis also discussed.
Currently, the components in the control panel for machine tools, electrical wiring connections are called harnesses performed manually. Therefore, it is required by a machine to automate its work. The purpose of this study is performing by image recognition of these two things. First, detecting the pre-installed screw with components in order to wire harness automatically. Second, scanning the connected harness after installing the harness. In this study, we use a technique called generic object recognition which learns and classifies the image feature by means of machine learning. We use HOG (Histograms of Oriented Gradients) and Bag of Keypoints as a method of calculation for the feature, AdaBoost and SVM (Support Vector Machine) as a method of machine learning. In this paper, we show the detection rate of screws and harnesses using the method described above.