• Nutritional Sciences
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• v.6 no.2
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• pp.118-126
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• 2003

To prevent food-borne diseases and ensure food safety, foodservice operators have been implementing the HACCP system in their facilities. Employees' knowledge of food safety can be improved through training and, as a result, their food safety behavior can be positively changed. A nonequivalent pretest and posttest control group model was designed to investigate the effectiveness of HACCP-based training on hospital foodservice employees' food safety knowledge and behavior, and to determine relationships between food safety knowledge and food safety behavior. The subjects used in this study were 84 hospital foodservice employees, assigned either to the intervention group (n=44) or the control group (n=40). Data were analyzed using the Statistical Package for the Social Sciences (SPSS). Descriptive statistics were computed, while the Student's t-test and ANCOVA (Analysis of Covariance) were used to investigate significant differences between groups, and the Pearson correlation was used to determine significant correlations. There were significant gains in both food safety knowledge and behavior, after the HACCP-based training. However, no significant correlation was found between food safety knowledge and food safety behavior. Based on this study we conclude that HACCP-based training is effective in improving both the food safety knowledge and food safety behavior of hospital foodservice employees.

• Journal of Distribution Science
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• v.11 no.12
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• pp.51-62
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• 2013

Purpose - A pre-study on service quality-based customer value is conducted with the path structure (perceived value of service quality→customer satisfaction→behavior intention) based on the hierarchical model of service quality including interaction and outcome quality, physical environment quality and the SERVQUAL model of process quality, namely, reliability, responsiveness, assurance, empathy, and tangibles. In addition, customer value in the service industry is studied by dividing into the two-way structure of utilitarian and emotional values. This study classifies customer values of family restaurants through the customer value model based on the 4×4 matrix needs system of Jeon and Kim (2009). It illustrates the path structure of customer value→customer satisfaction→behavior intention targeting college students in order to generalize the customer value system of family restaurants. Research design, data, and methodology - This study established seven hypotheses based on the relationship between each type of customer value (food quality, convenience, social, emotional, interior quality, service encounter, and purchasing) and customer satisfaction, and the relationship between customer satisfaction and behavior intention. The study data were collected from students in the Department of Business and Tourism at Kimpo University. In all, 294 survey papers were returned of the 300 distributed: 253 pieces were used in the final analysis excluding 41 with insufficient and less effective answers. For statistical analysis, the statistics software package SPSS 15.0 was used. Results - The results of the analysis are as follows: first, the customer values of family restaurants are classified by seven customer values: goods quality value, emotional value, convenience value, social value, purchasing value, service encounter value, and inner quality value. Second, emotional value, purchasing value, service encounter value, and inner quality value had positive impact on customer satisfaction. In particular, purchasing value through being included in functional value was not classified in the previous study; however, this study could classify and generalize this value in a new way. Finally, customer satisfaction had a positive impact on behavior intention. This showed that college students had behavior intention - repurchase intention and word-of-mouth - because they could be content with the food items on the menu and the service provided by employees. Conclusions - The main points based on the above-mentioned results are as follows. This study with college students as study subjects could be classified into four dimensions, namely, generic value, usage value, purchasing value, and physical value and seven sub-dimensions on customer values of family restaurants based on a 4×4 matrix needs system. Then, to confirm its generalization, the path structure of customer value→customer satisfaction→behavior intention was verified. While existing pre-studies used simplified values by classifying restaurant values largely as utilitarian value and hedonic value, this study classified various forms of customer value, and that customer value especially could be expanded by adding purchasing value. As a result, it is shown that marketers need to diversify their customer services because this study proved that customer values can be classified in various ways based on customer needs.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.72-78
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• 2006

It is essential for robot to have the sensing and communication abilities in the swarm robot system. In general, as the number of robot goes on increasing, the limitation of communication capacity and information overflow occur in global communication system. Therefore a local communication is more effective than global one. In this paper, we propose the novel method for determining the optimal communication radius through the analyzing of the information propagation based on local communication. And we also propose a method of cooperative strategies and group behavior of swarm robot based on artificial immune system.

• International Commerce and Information Review
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• v.9 no.3
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• pp.305-320
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• 2007

With expanded use of B2B(between enterprises), B2G(between enterprises and government) and EDI(Electronic Data Interchange), and increased amount of available network information and information protection threat, as it was judged that security can not be perfectly assured only with security technology such as electronic signature/authorization and access control, Bayesian networks have been developed for protection of information. Therefore, this study speculates Bayesian networks system, centering on ERP(Enterprise Resource Planning). The Bayesian networks system is one of the methods to resolve uncertainty in electronic data interchange and is applied to overcome uncertainty of abnormal invasion detection in ERP. Bayesian networks are applied to construct profiling for system call and network data, and simulate against abnormal invasion detection. The host-based abnormal invasion detection system in electronic trade analyses system call, applies Bayesian probability values, and constructs normal behavior profile to detect abnormal behaviors. This study assumes before and after of delivery behavior of the electronic document through Bayesian probability value and expresses before and after of the delivery behavior or events based on Bayesian networks. Therefore, profiling process using Bayesian networks can be applied for abnormal invasion detection based on host and network. In respect to transmission and reception of electronic documents, we need further studies on standards that classify abnormal invasion of various patterns in ERP and evaluate them by Bayesian probability values, and on classification of B2B invasion pattern genealogy to effectively detect deformed abnormal invasion patterns.

• Convergence Security Journal
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• v.13 no.4
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• pp.109-115
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• 2013

Security threats through e-mail service, a representative tool to convey information on the internet, are on the sharp rise. The security threats are made in the path where malicious codes are inserted into documents files attached and infect users' systems by taking advantage of the weak points of relevant application programs. Therefore, to block infection of camouflaged malicious codes in the course of file transfer, this work proposed an integrity-checking and behavior-based detection system using File Transfer System (FTS), logical network partition, and conducted a comparison analysis with the conventional security techniques.

• Structural Engineering and Mechanics
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• v.90 no.2
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• pp.189-208
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• 2024

Artificial intelligence is one of the efficient methods that can be developed to simulate nonlinear behavior and predict the response of building structures. In this regard, an adaptive method based on optimization algorithms is used to train the TSK model of the fuzzy inference system to estimate the seismic behavior of building structures based on analytical data. The optimization algorithm is implemented to determine the parameters of the TSK model based on the minimization of prediction error for the training data set. The adaptive training is designed on the feedback of the results of previous time steps, in which three training cases of 2, 5, and 10 previous time steps were used. The training data is collected from the results of nonlinear time history analysis under 100 ground motion records with different seismic properties. Also, 10 records were used to test the inference system. The performance of the proposed inference system is evaluated on two 3 and 20-story models of nonlinear steel moment frame. The results show that the inference system of the TSK model by combining the optimization method is an efficient computational method for predicting the response of nonlinear structures. Meanwhile, the multi-vers optimization (MVO) algorithm is more accurate in determining the optimal parameters of the TSK model. Also, the accuracy of the results increases significantly with increasing the number of previous steps.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.364-369
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• 2001

As the population of persons over the age of sixty-five is rapidly growing, the population of solitary senior person living at own home is growing in Japan. This situation has caused the social issue of how supports their healthy life. There have been some projects related to improve their quality of life and support their healthy life. Unfortunately mostly they focus the method of measuring vital signal and observing behavior. Nobody reports how utilize the measured data. Aim of our project is how find emergency of the aged people at home. As emergency is big different from regular life behavior, we have to recognize it. We propose concept of the human behavior model and show the some types human behavior knowledge constructed by observed human behavior model and show the some types human behavior knowledge constructed by observed human behavior. This idea is based on human having habitual life. And we discuss the possibility of finding emergency using knowledge and observed data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.125-137
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• 2012

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. For such reason, lots of intrusion detection system has been developed. Intrusion detection system has abilities to detect abnormal behavior and unknown intrusions also it can detect intrusions by using patterns studied from various penetration methods. Various algorithms are studying now such as the statistical method for detecting abnormal behavior, extracting abnormal behavior, and developing patterns that can be expected. Etc. This study using clustering of data mining and association rule analyzes detecting areas based on two models and helps design detection system which detecting abnormal behavior, unknown attack, misuse attack in a large network.

• Fashion & Textile Research Journal
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• v.14 no.5
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• pp.778-790
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• 2012

This research categorizes and analyzes different online fashion store studies conducted over the past 10 years based on study type. The results are as follows. First, it was found that 116 studies out of 118 studies on online fashion stores conducted from 2000 to 2012 were based on PC web. Second, the studies on PC web-based fashion stores were reclassified into 9 different categories based on their topics: purchase behavior, word-of-mouth behavior, website, and product information presentation as well as products for sale, return behavior, customer service, system, present condition, marketing strategy, and promotions. However, mobile web-based studies were categorized into 2 categories of introduction of the fashion stores and purchase behavior. Third, we reclassified the studies chronologically to observe studies conducted at different times. In the early phase (in addition to studies on purchase behavior) studies on present condition, marketing strategy, and website constituted the majority of studies conducted because the field research was just starting to grow; however, studies conducted in the latter phase showed new patterns of study, such as word-of-mouth effect, and return behavior. Future studies conducted on competitive PC web-based fashion stores require a more specific classification of studies (according to their purpose) to develop an effective marketing strategy.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.