• Asia Marketing Journal
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• v.7 no.1
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• pp.67-89
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• 2005

In recent decades, product variety has increased dramatically in most industries. Rapidly evolving technologies, global competition, and sophisticated customers have contributed to an increase in product variety in many industries. In this paper, I study the impact of product variety on several businesses in the supply chain through literature review. By study of literature. this paper presents the benefits and drawbacks of increasing product variety on functions performed in several departments, such as engineering, manufacturing, purchasing, logistics and marketing. It provides a brief overview of the various techniques like modularity, component sharing, and platform-based development, which are helpful in reducing the costs, when designing for variety. It also provides a brief overview of order processing, purchased component/part variety, which are helpful in reducing the purchasing costs, and customer satisfaction, market advantage, market share, competitive advantage and demand forecast, which are useful in impact of product variety on marketing. Future research directions are discussed.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.9-16
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• 2023

Technological advancement is being advanced in sports such as electronic protection of taekwondo competition and VAR of soccer. However, a person judges and guides the posture by looking at the posture, so sometimes a judgment dispute occurs at the site of the competition in Taekwondo Poomsae. This study proposes an artificial intelligence model that can more accurately judge and evaluate Taekwondo movements using artificial intelligence. In this study, after pre-processing the photographed and collected data, it is separated into train, test, and validation sets. The separated data is trained by applying each model and conditions, and then compared to present the best-performing model. The models under each condition compared the values of loss, accuracy, learning time, and top-n error, and as a result, the performance of the model trained under the conditions using ResNet50 and Adam was found to be the best. It is expected that the model presented in this study can be utilized in various fields such as education sites and competitions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1055-1065
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• 2023

Recently, various studies using deep reinforcement learning (deep RL) technology have been conducted to solve complex problems using big data collected at industrial internet of things. Deep RL uses reinforcement learning"s trial-and-error algorithms and cumulative compensation functions to generate and learn its own data and quickly explore neural network structures and parameter decisions. However, studies so far have shown that the larger the size of the learning data is, the higher are the memory usage and search time, and the lower is the accuracy. In this study, model-agnostic learning for efficient federated deep RL was utilized to solve privacy invasion by increasing robustness as 55.9% and achieve 97.8% accuracy, an improvement of 5.5% compared with the comparative optimization-based meta learning models, and to reduce the delay time by 28.9% on average.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.99-105
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• 2023

In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

• Journal of Practical Agriculture & Fisheries Research
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• v.25 no.3
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• pp.14-18
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• 2023

White leg shrimps cultured in an inland private aquaculture farm with low salinity waters showed abnormal swimming behavior and appetite reduction in July 2022. Then, gradual mortality was observed in the aquaculture farm. During the diagnosis, bacterial strain KNUAF-SHP3 was isolated from the hepatopancreas of the dead shrimps. Based on the sequence of 16S rRNA gene, KNUAF-SHP3 was proved to be Shewanella sp., clustering into a group with S. algae MARS 14 and S. chilikensis JC5T. According to the result of experimental infection test, all shrimps challenged with high concentrations, 2.1×108 CFU/ml and 2.1×109 CFU/ml showed apparent disease symptoms and the cumulative mortality rates reached 100% in 7 days post challenge. These results emphasized that Shewanella isolate in this study can be a potential pathogen of white leg shrimp cultured in low salinity water.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.83-88
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• 2023

In this paper, we developed a workout and diet assistance application to meet the growing demand for workout and dietary support services due to the increase in the home training population. The application analyzes the user's workout posture in real-time through the camera and guides the correct posture using guiding lines and voice feedback. It also classifies the foods included in the captured photos, estimates the amount of each food, and calculates and provides nutritional information such as calories. Nutritional information calculations are executed on the server, which then transmits the results back to the application. Once received, this data is presented visually to the user. Additionally, workout results and nutritional information are saved and organized by date for users to review.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.21-26
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• 2023

Knowledge distillation (KD) is a model lightening technology that transfers the knowledge of deep models to light models. Most KD methods have been developed for classification models, and there have been few KD studies in the field of super-resolution (SR). In this paper, various KD methods are applied to an SR model and their performance is compared. Specifically, we modified the loss function to apply each KD method to the SR model and conducted an experiment to learn a student model that was about 27 times lighter than the teacher model and to double the image resolution. Through the experiment, it was confirmed that some KD methods were not valid when applied to SR models, and that the performance was the highest when the relational KD and the traditional KD methods were combined.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_2
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• pp.1055-1062
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• 2023

Globally, the need for remanufacturing or reusing ships and various mechanical parts continues to increase due to environmental problems including global warming. Research on remanufacturing is being carried out in many areas. However, research on inspection and classification to identify the performance or degree of wear of mechanical parts is insufficient. In particular, studies on the inspection-ability and classification-ability of mechanical parts equipped with various materials and complex forms are highly required. Remanufacturing must be considered from the stage of design to extend the life cycle of mechanical parts. Particularly, it is very important to perform research for evaluating the degree of ease to inspect and classify various sorts of wear or deterioration of parts caused by long-term use easily. In this study, the degree of ease in inspecting or classifying mechanical parts for remanufacturing is defined as inspection-ability and classification-ability. In fact, to remanufacture old parts, inspection-ability and classification-ability should be reflected from the stage of design. The purpose of this study is to evaluate the inspection-ability and classification-ability of ships and various mechanical parts. This researcher has presented the quantitative evaluation procedure of inspection-ability and classification-ability, derived the factors and ranges that influence each of the details of easiness, assigned scores according to the ranges of the factors, and calculated weights. Lastly, this study presents the procedure of scoring to evaluate the overall weights of inspection-ability and classification-ability and also inspection-ability and classification-ability quantitatively.

• Korean Journal of Ichthyology
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• v.35 no.4
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• pp.294-304
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• 2023

Seasonal variations in the community structure of larval fish assemblage in the coastal waters off Gadeok-do were investigated in May, August and November of 2019, and February in 2020. During the study period, a total of 85 larvae species belonging to 45 families were collected. The dominant species were Engraulis japonica, Gobiidae sp., Clupea pallasii, Decapterus maruadsi, and Callionymidae sp.. These five species accounted for 84.1% of the total number of larvae during the survey period. E. japonica, Gobiidae sp., D. maruadsi, and Callionymidae sp. were the dominant species in the summer, while C. pallasii was the dominant species in the winter. The Species Diversity Index was highest in the summer and lower in the fall and winter months, with the lowest values in the spring. As a result of cluster analysis using the number of individual larval fish showed that they are divided into four seasonal groups. In particular, due to seasonal changes in water temperature, an appropriate growth environment was formed in the summer, and an appropriate hatching water temperature for winter spawning fish species was formed in winter, reflecting the seasonal characteristics of the larval fish community.

• Journal of The Korean Association For Science Education
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• v.28 no.1
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• pp.47-66
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• 2008

This is a qualitative review of research literature on the expertise of science teachers. The study first identified a common point of view which the relevant literature shared about teacher expertise. Research methods employed in previous studies were then categorized into four groups, and the characteristics of each group of research methods were discussed. The groups of research methods included uses of questionnaires and interviews, visual representations, classroom observations and discourse analyses, and narrative inquiry. The study finally suggested what aspects of science teachers' expertise should be considered and what sorts of research methods could be employed for future research in this area.