• Fisheries and Aquatic Sciences
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• v.25 no.4
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• pp.231-242
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• 2022

Effect of different concentrations of hypotaurine (HTU) on melanosis and quality of shrimps during 10 d storage in ice were studied. During refrigeration, the total plate count and total volatile basic nitrogen of shrimps treated with 20 g/L HTU were the lowest, and the hardness and microstructure were the best. Moreover, the score of melanoses, pH and total bile acid of shrimps treated with 20 g/L HTU were also low. Sensory evaluation showed that HTU treatment could make the shelf life of shrimps 3-4 days longer compared with the control. Based on the above physical and chemical indexes, 20 g/L HTU showed great potential as a safe inhibitor in the treatment of shrimps' melanosis.

• Journal of Biomedical Engineering Research
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• v.43 no.3
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• pp.170-176
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• 2022

Cell separation from a heterogenous mixture sample is an essential process for downstream analysis in biological, chemical, and clinical applications. This study demonstrates an integrated hybrid device of the viscoelastic focusing in a straight rectangular channel and subsequent size-based separation using acoustophoresis to attain high efficiency and separation tunability. For particle pre-alignment in a viscoelastic fluid, the flow rate higher than 10 μl/min was required. Surface acoustic wave-based lateral migration of particles with different sizes (13 and 27 ㎛) was examined at various applied voltages and flow rate conditions. Therefore, the flow rate of 100 μl/min and the applied voltage of 20 V_pp can be used for size-based particle separation.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.365-373
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• 2000

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications and merits, some features of DEA remain bothersome. DEA offers no guideline about to which direction relatively inefficient DMUs improve since a reference set of an inefficient DMU, several efficient DMUs, hardly provides a stepwise path for improving the efficiency of the inefficient DMU.In this paper, we aim to show that DEA can be used to evaluate the efficiency of life insurance companies while overcoming its limitation with the aids of machine learning methods.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.465-474
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• 2001

미래의 시스템은 보다 동적이고 복잡한 환경에서 작동될 것으로 예측된다. 이러한 환경에서는 학습, 적응, 진화, 퍼지, 추론, 계획, 보안, 자기 조직화, 감성 등 소위 지능적 능력들이 필수적으로 요청된다. 본 논문에서는 생명체 패러다임 SAL(System As a Life)을 제안한다. SAL은 생명체 고유의 창발적 속성에 기반을 둔 시스템 설계 방법론으로 객체 패러다임을 확장한 구조를 갖는다. SAL 기반으로 시스템을 설계할 경우 상기의 지능적 능력들이 자연스럽게 구현될 수 있다.

• Steel and Composite Structures
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• v.50 no.3
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• pp.363-374
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• 2024

The fatigue life of steel wire is affected not only by fatigue load, but also by corrosion environment in service period. Specially, the corrosion pit will lead to stress concentration on the surface of steel wire inducing the formation of fatigue cracks, and the fatigue cracks will accelerate the corrosion process. Therefore, the corrosion fatigue of steel wire is a coupling effect. In this study, the corrosion-fatigue coupling life curve is derived with considering corrosion-fatigue pitting stage, corrosion-fatigue short crack stage and corrosion-fatigue long crack stage. In addition, the stress concentration factors of different corrosion pits are calculated by COMSOL software. Furthermore, the effect of corrosion environment factors, that is, corrosion rate, corrosion pit morphology, frequency and action factor of fatigue load, on fatigue life of steel wire is analyzed. And then, the corrosion-fatigue coupling life curve is compared with the fatigue life curve and fatigue life curve with pre-corrosion. The result showed that the anti-fatigue performance of the steel wire with considering corrosion-fatigue coupling is 68.08% and 41.79% lower than fatigue life curve and fatigue life curve with pre-corrosion. Therefore, the corrosion-fatigue coupling effect should be considered in the design of steel wire.

• Journal of Fashion Business
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• v.22 no.1
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• pp.41-55
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• 2018

The purpose of this study was to investigate the trends of product design for textile convergence wearable smart textile fashion products according to college students' fashion life style. In this study, we used information obtained from a questionnaire issued to 201 female college students who were 20 years old for the final analysis. The questionnaires were to classify female college students groups according to the fashion life style, to examine characteristics, needs and wants of each group. The survey on the tendency of wearable smart textiles consisted of 22 items about concept and type of smart clothing product, functional material and intelligent material, recognition, preference, purchase intention, purchase factor and brand preference tendency. A total of 201 samples were analyzed by factor analysis, cluster analysis, ANOVA, crosstabs and $x^2-test$ using SPSS package program. 'brand preference oriented type was found to be interested in 'wearable' smart clothing product with monitoring function of bio-signal' and 'high functional fiber and textile product', but the credibility of 'smart clothes that can be worn and smart textile products to be useful in modern life' was low. 'fashionable individuality oriented' type showed interest in 'smart clothing and smart product', 'intelligent fiber' and 'wearable smart clothing product with monitoring function of bio-signal', but the preferences of 'light emitting fiber products' was low. 'practically purchasing-oriented' type was very interested in 'high-functional fiber and its textile products', but had inadequate knowledge on 'smart clothing and smart textile product' and showed low interest. Despite the fact that 'wearable smart clothing and smart textile products' are expensive, they were willing to purchase considering practicality and sophisticated style.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.416-422
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• 2006

Most of the existing statistical models of software manpower profile are based on the assumptions of the usage and development process. Therefore, there is no universally applicable estimation and prediction model. To develop a prediction model, this paper suggests the predictive filter as a prediction model for software manpower profile. Firs of all, we investigate the software manpower profile and we suggest the input-output of predictive filter and method for parameter determination. Then, its usefulness is empirically verified by analyzing the actual data obtained from the software projects. Based on the average relative prediction error and Pred(0.25), the suggested predictive filter is compared with other well-known statistical estimation models. As a result, the predictive filter generally has a simple structure and on the other hand, it adapts the software manpower profile very well.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.805-812
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• 2005

Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user's behavior preference pattern is proposed in the sense of reductive user's cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.327-336
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• 2004

In distributed autonomous mobile robot system, each robot (predator or prey) must behave by itself according to its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot have both learning and evolution ability to adapt to dynamic environment. This paper proposes a pursuing system utilizing the artificial life concept where virtual robots emulate social behaviors of animals and insects and realize their group behaviors. Each robot contains sensors to perceive other robots in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used for behavior decision controller. The input of the neural network is decided by the existence of other robots and the distance to the other robots. The output determines the directions in which the robot moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation. Besides, in this paper, we could have observed the robots' emergent behaviors during simulation.