The culpability of a person, as determined by due process of law, for any of his actions that are defined as criminal. Determination of such responsibility is a legal function, not a psychiatric one, although a psychiatrist may be called upon to present evidence to the court in order to aid the judge or jury in reaching a decision as to responsibility. Determination of responsibility varies with the laws of the state in which the accused is being tried, but in general all states base their laws on three famous judicial decisions concerning criminal responsibility. 1. the M'Naghten(McNaughton) rule(a. to establish such a defense the accused, at the time the act was committed, must be shown to have been laboring under such defect of reason as not to know the nature and quality of the act he was doing, b. if he did know it, he did or know that what he was doing was wrong). 2. the irresistible impulse test. 3. the Durham decision. Under the Durham test, however, the psychiatrist may give any relevant testmony concerning the mental illness at issue. The psychological and behavioral appearance of a person, in clinical psychiatry this term is commonly used to refer to the results of the mental examination of a patient. The written report of the mental status usually contains specific references to the following areas: I. Attitude and General Behavior (1)General health and appearance. (2)General habits of dress. (3)Personal habits. (4)General mood. (5)Use of leisure time. (6)Degree of sociability. (7)Speech. II. Attitude and Behavior during interview (1)Co-operativeness. (2)Poise. (3)Facial expression. (4)Motor activity. (5)Mental activity. (6)Emotional reactions. (7)Trend of thought. III. Sensorium, mental grasp, and capacity (1)Orientation. (2)Memory and retention. (3)Estimate of intelligence. (4)Abstraction ability. (5)Tests of absurdity, interpretation of proverbs. (6)Judgment.
Recently, many researchers have developed applications for automated contract and negotiation using agent technologies on electronic commerce. Especially, they have tried to study negotiation mechanism applying agent instead of buyers and sellers. Traditional researches, however, often had limitations. In the researches of automated negotiation, the agents had to negotiate with the other agents for a simple negotiation issue because the mechanisms were naive. In the researches of negotiation by user interaction, the agents did not have supported the procedures and methodologies for making the automated negotiation but only supported the users by providing communication environment during the negotiation process by users. In this paper, we propose efficient negotiation model using the modified negotiation model of the game theory. In the proposed model, the agents negotiate automatically with the partner agent and make good benefits by the strategic method during the negotiation process. Each agent makes negotiation issues with user's requirements and exchanges its suggestion alternatively in each step of the negotiation process. The agent evaluates degree of satisfaction for the opposite's suggestion and uses it in the next step of suggestion. To find out the negotiation strategies of opposite side, the agent uses teaming by weights of issues. As a result, the agent improves each own benefits for the contract and reduces the unbalance of its benefits through the proposed negotiation mechanism. We implement the negotiating agents according to the proposed mechanism and prove the efficiency of the proposed model by various experimentation.
An autonomous virtual character can conduct itself like a human after recognizing and interpreting the virtual environment. Artificial vision is mainly used in the recognition of the environment for a virtual character. The present artificial vision that has been developed takes all the information at once from everything that comes into view. However, this can reduce the efficiency and reality of the system by saving too much information at once, and it also causes problems because the speed slows down in the dynamic environment of the game. Therefore, to construct a vision system similar to that of humans, a visual observation system which saves only the required information is needed. For that reason, this research focuses on the descriptive artificial intelligence engine which detects the most important information visually recognized by the character in the virtual world and saves it into the memory by degrees. In addition, a visual system is constructed in accordance with an image transaction theory to make it sense and recognize human feelings. This system finds the attention area of moving objects quickly and effectively through the experiment of the virtual environment with three dynamic dimensions. Also the experiment enhanced processing speed more than 1.6 times.
Collaborative filtering recommends products using customers' preferences, so it cannot recommend products to the new customer who has no preference information. This paper proposes a novel approach to new customer recommendations using the social network analysis which is used to search relationships among social entities such as genetics network, traffic network, organization network, etc. The proposed recommendation method identifies customers most likely to be neighbors to the new customer using the centrality theory in social network analysis and recommends products those customers have liked in the past. The procedure of our method is divided into four phases : purchase similarity analysis, social network construction, centrality-based neighborhood formation, and recommendation generation. To evaluate the effectiveness of our approach, we have conducted several experiments using a data set from a department store in Korea. Our method was compared with the best-seller-based method that uses the best-seller list to generate recommendations for the new customer. The experimental results show that our approach significantly outperforms the best-seller-based method as measured by F1-measure.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.13
no.1
/
pp.145-155
/
2018
The matter of cultivating entrepreneurship and will to start a business of university students majoring in agriculture and life sciences and college students majoring in agriculture as a future leader in the sector is a very important object of study. However, the discussion on entrepreneurship, establishment of a business and venture based on creative technology and innovative management have been scarcely had, because traditionally the majority of agricultural business has been a small-sized and simple business run by a small farmer. Education for starting an agricultural business in agriculture industry has been ignored even in the developed countries. ICT and AI(artificial intelligence)-based smart agriculture in the 4th Industrial Revolution Age is emerging as a new growth potential of our agriculture industry. Thus, the interest in farmers to start a business and venture agriculture is growing in the agriculture industry. Accordingly, the study draws the influence factors regarding the effect of the planned behavior of the university students who take part in the education course for starting an agricultural business and an agricultural venture business on entrepreneurship and will to start the business and conducts the empirical analysis. The businessmen who newly join the agriculture industry should perform the technical innovation and the creative business activities to be able to compete in the agriculture industry.
Recently in HCI research, emotion recognition is one of the core processes to implement emotional intelligence. There are many studies using bio signals in order to recognize human emotions, but it has been done merely for the basic emotions and very few exists for the other emotions. The purpose of present study is to confirm the difference of autonomic nervous system (ANS) response in three emotions (boredom, pain, and surprise). There were totally 217 of participants (male 96, female 121), we presented audio-visual stimulus to induce boredom and surprise, and pressure by using the sphygmomanometer for pain. During presented emotional stimuli, we measured electrodermal activity (EDA), skin temperature (SKT), electrocardiac activity (ECG) and photoplethysmography (PPG), besides; we required them to classify their present emotion and its intensity according to the emotion assessment scale. As the results of emotional stimulus evaluation, emotional stimulus which we used was shown to mean 92.5% of relevance and 5.43 of efficiency; this inferred that each emotional stimulus caused its own emotion quite effectively. When we analyzed the results of the ANS response which had been measured, we ascertained the significant difference between the baseline and emotional state on skin conductance response, SKT, heart rate, low frequency and blood volume pulse amplitude. In addition, the ANS response caused by each emotion had significant differences among the emotions. These results can probably be able to use to extend the emotion theory and develop the algorithm in recognition of three kinds of emotions (boredom, surprise, and pain) by response measurement indicators and be used to make applications for differentiating various human emotions in computer system.
Social changes due to ICT like Big Data, IoT, Cloud and Mobile is progressing rapidly. Now, we get out of the old-fashioned frame was measured at the level of the information society through the introduction of PC, Internet speed and Internet subscribers etc and there is a need for a new type of diagnostic information society framework. This study is the study for the framework established to diagnose and measure post-information society. The framework and indicators were chosen in accordance with the technological society coevolution theory and information society-related indicators presented from authoritative international organizations. Empirical results utilizing the indicators and framework developed in this study were as follows: First, the three sectors, six clusters (items), 25 nodes (indicators) that make up the information society showed that all strongly connected. Second, it was diagnosed as information society development (50.34%), technology-based expansion (25.03%) and ICT effect (24.63%) through a network analysis (ANP) for the measurement of importance of the information society. Third, the result of calculating the relative importance of the cluster and nodes showed us (1)social development potential (26.04%), (2)competitiveness (15.9%), (3)ICT literacy (15.5%) (4) (social)capital (24.3 %), (5)ICT acceptance(9.54%), (6)quality of life(8.7%). Consequently, We should take into account the effect of the economy and quality of life beyond ICT infrastructure-centric when we measure the post-information society. By applying the weighting we should performs a comparison between countries and we should diagnose the level of Korea and provide policy implications for the preparation of post-information society.
Journal of Agricultural Extension & Community Development
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v.21
no.1
/
pp.177-217
/
2014
The purpose of this study is to examine the relation between Program Satisfaction and the leadership types of who participating in the program of village lifelong education leader. The detail goals of this study are to (1) understand the concepts about the training program of village lifelong education leader. (2) study the theory related to the leadership of village lifelong education leader. (3) examine the relation between program satisfaction and leadership types by personal characteristics. The results of this study are as follows: First, there is the significant difference between the transactional leadership and the exceptive management leadership which is the transactional leadership's sub-type in age. Second, there is the significant difference between the exceptive management leadership which transactional leadership's sub-type and charisma leadership that is transformational leadership's sub-type by participated in or not the lifelong education program before. Third, the average value of the transformational leadership is more higher than the transactional leader's average value. Fourth. the ranking of the transformational leaders' activities are as follows; (1) individual relationship (2) spiritual motivation (3) intelligence stimulus (4) charisma. Fifth, the ranking of the transactional leader's activities are as follows; (1) reward to achievement (2) exceptional management.
Understanding market convergence has became essential for small and mid-size enterprises. Identifying convergence items among heterogeneous markets could lead to product innovation and successful market introduction. Previous researches have two limitations. First, traditional researches focusing on patent databases are suitable for detecting technology convergence, however, they have failed to recognize market demands. Second, most researches concentrate on identifying the relationship between existing products or technology. This study presents a platform to identify the opportunity of market convergence by using product databases from a global B2B marketplace. We also attempt to identify convergence opportunity in different industries by applying Structural Hole theory. This paper shows the mechanisms for market convergence: attributes extraction of products and services using text mining and association analysis among attributes, and network analysis based on structural hole. In order to discover market demand, we analyzed 240,002 e-catalog from January 2013 to July 2016.
Context-aware computing, as a core of smart space development, has been widely regarded as useful in realizing individual service provision. However, most of context-aware services so fat are in its early stage to be dispatched for actual usage in the real world, caused mainly by user's privacy concerns. Moreover, since legacy context-aware services have focused on acquiring in an automatic manner the extra-personal context such as location, weather and objects near by, the services are very limited in terms of quality and variety if the service should identify intra-personal context such as attitudes and privacy concern, which are in fact very useful to select the relevant and timely services to a user. Hence, the purpose of this paper is to propose a novel methodology to infer the user's privacy concern as intra-personal context in an intelligent manner. The proposed methodology includes a variety of stimuli from outside the person and then performs model-based reasoning with social theory models from model base to predict the user's level of privacy concern semi-automatically. To show the feasibility of the proposed methodology, a survey has been performed to examine the performance of the proposed methodology.
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