• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.81-103
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• 2005

The Neuron structure in a nervous system consists of inhibitory neurons and excitory neurons. Both neurons are activated by agonistic neurons and inactivated by antagonist neurons. In this paper, we proposed a physiological fuzzy neural network by analyzing the physiological neuron structure in the nervous system. The proposed structure selectively activates the neurons which go through a state of excitement caused by agonistic neurons and also transmit the signal of these neurons to the output layers. The proposed physiological fuzzy neural networks based on the nervous system consists of a input player, and the hidden layer which classifies features of learning data, and output layer. The proposed fuzzy neural network is applied to recognize bronchial squamous cell carcinoma images and car plate images. The result of the experiments shows that the learning time, the convergence, and the recognition rate of the proposed physiological fuzzy neural networks outperform the conventional neural networks.

• Journal of Life Science
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• v.17 no.3 s.83
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• pp.381-385
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• 2007

Facilitates chromatin transcription (FACT) is a chromatin-specific elongation factor required for transcription of chromatin templates in vivo and in vitro. FACT consists of human homologue of the Saccharomyces cerevisiae Spt16/Cdc68 protein (hSpt16) and the high mobility group-1-like protein structure-specific recognition protein-1 (SSRP-1). Here we show that the protein level of hSpt16 is massively down-regulated in quiescent T98C cells using both immunofluorescence and western blot analysis. In contrast, we observe high level of the hspt16 expression in the proliferative T98G cells. Interestingly, the expression of SSRP-1 is not altered in both quiescent and proliferative states. Taken together, our findings implicate that the expression of hSpt16 is associated with the proliferative state and can be used as a proliferation marker.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.804-809
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• 2013

The current state monitoring system at a semiconductor manufacturing process is based on the manually collected sensor data, which involves limitations when it comes to complex malfunction detection and real time monitoring. This study aims to design a situation recognition algorithm to form a network over time by creating a domain ontology and to suggest a system to provide users with services by generating events upon finding risk factors in the semiconductor process. To this end, a multiple sensor node for situational inference was designed and tested. As a result of the experiment, events to which the rule of time inference was applied occurred for the contents formed over time with regard to a quantity of collected data while the events that occurred with regard to malfunction and external time factors provided log data only.

• Journal of Arbitration Studies
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• v.31 no.1
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• pp.107-127
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• 2021

Vietnam is an important country with many trade transactions with the Republic of Korea. Arbitration is a method of resolving disputes that can arise with the increase in trade transactions. It is essential to study the legal system and precedents of Vietnam on the approval and enforcement of foreign arbitral awards. Such is the case because the law in Vietnam and the court's position on the approval and enforcement of foreign arbitration awards issued by the courts depend on the possibility of realizing the parties' rights concerning their disputes. Therefore, it is of great value both theoretically and practically to analyze the exact differences between approval and the denial of approval. Vietnam has enacted the Commercial Arbitration Act, which replaces the previous Commercial Arbitration Decree and creates an arbitration-friendly environment that meets international arbitration standards. Regarding the approval and execution of foreign arbitration awards, the Commercial Arbitration Act, the Civil Procedure Act, the Civil Execution Act, and the Vietnam Foreign Arbitration Awards Approval and Enforcement Ordinance are regulated. Following these laws and regulations, the reasons for the approval, enforcement, and rejection of the arbitral award are specified. In accordance with these laws and inappropriate arbitration agreements, an arbitral award beyond the scope of its right of disposition, an arbitral tribunal, or the concerned parties could not be involved in a proceeding or an arbitral award if the involved party does not have an opportunity to exercise its rights lawfully. If the state agency in the forum does not recognize the arbitral award, the dispute is not subject to arbitration under Vietnamese law, or the arbitral award does not conform to the basic principles of Vietnamese law, the parties are not bound, and the foreign arbitration award is rejected for approval and execution.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.74-83
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• 2019

This study designs a squat posture recognition system that can provide correct squat posture guidelines. This system comprises two modules: a Kinect camera for monitoring users' body movements and a Wii Balance Board(WBB) for measuring balanced postures with legs. Squat posture recognition involves two states: "Stand" and "Squat." Further, each state is divided into two postures: correct and incorrect. The incorrect postures of the Stand and Squat states were classified into three and two different types of postures, respectively. The factors that determine whether a posture is incorrect or correct include the difference between shoulder width and ankle width, knee angle, and coordinate of center of pressure(CoP). An expert and 10 participants participated in experiments, and the three factors used to determine the posture were measured using both Kinect and WBB. The acquired data from each device show that the expert's posture is more stable than that of the subjects. This data was classified using a support vector machine (SVM) and $na{\ddot{i}}ve$ Bayes classifier. The classification results showed that the accuracy achieved using the SVM and $na{\ddot{i}}ve$ Bayes classifier was 95.61% and 81.82%, respectively. Therefore, the developed system that used Kinect and WBB could classify correct and incorrect postures with high accuracy. Unlike in other studies, we obtained the spatial coordinates using Kinect and measured the length of the body. The balance of the body was measured using CoP coordinates obtained from the WBB, and meaningful results were obtained from the measured values. Finally, the developed system can help people analyze the squat posture easily and conveniently anywhere and can help present correct squat posture guidelines. By using this system, users can easily analyze the squat posture in daily life and suggest safe and accurate postures.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.93-102
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• 2019

As interest in wellness grows, There is a lot of research about monitoring individual health using wearable devices. Accordingly, a variety of methods have been studied to distinguish exercise from daily activities using wearable devices. Most of these existing studies are machine learning methods. However, there are problems with over-fitting on individual person's learning, data discontinuously recognition by independent segmenting and fake activity. This paper suggests a detection method for exercise activity based on the physiological response principle of heart rate up and down during exercise. This proposed method calculates activity intensity and heart rate from triaxial and photoplethysmography sensor to determine a heart rate recovery, then detects exercise by estimating activity intensity or detecting a heart rate rising state. Experimental results show that our proposed algorithm has 98.64% of averaged accuracy, 98.05% of averaged precision and 98.62% of averaged recall.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.223-230
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• 2021

Currently, self-driving vehicles are on the verge of commercialization after testing. However, even though autonomous vehicles have not been fully commercialized, 81 accidents have occurred, and the driving method of vehicles to avoid accidents relies heavily on LiDAR. In order for the currently commercialized 3-level autonomous vehicle to develop into a 4-level autonomous vehicle, more information must be collected than previously collected information. Therefore, this paper proposes a Driving Situation Judgment System (DSJS) that accurately calculates the crisis situation the vehicle is in by useing the roughness of the road and the state of the passengers of surrounding vehicles including road information and weather information collected from existing autonomous vehicles. As a result of DSJS's PDM experiment, PDM was able to classify passengers 15.52% more accurately on average than the existing vehicle's passenger recognition system. This study can be a basic research to achieve the 4th level autonomous vehicle by collecting more various types than the data collected by the existing 3rd level autonomous vehicle.

• Architectural research
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• v.22 no.4
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• pp.123-133
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• 2020

Light is an essential environmental element for elderly people to do various activities. At senior welfare centers, healthy indoor lighting is especially necessary because the facilities are used by the elderly to perform their mostly indoor activities. The purpose of this study is to evaluate light environments at senior welfare centers for well-being lighting characteristics. We based the study on the 'Biophilia' theory, a concept related to health from happiness. Thus, this study is mainly based on literary review and survey research. For this, we conducted a location focused field study to identify the current state of the lighting environments at senior welfare centers in Busan, South Korea. First, we constructed structural questionnaire to evaluate lighting environment based on 'Light and Space' biophilia theory. Then, to survey subjective evaluation, the participant of research included total of 122 senior welfare center users. Based on the results of this research, the conclusions are as follows; 1) overall, it seems that the overall result of the light environmental evaluation seems to be high because the evaluated facilities in the case survey in large-scale were recently built elderly welfare centers. 2) most of the healing design elements are focused on the introduction of natural light and psychological influence. The satisfaction with actual natural light is evaluated to be high. Although shadow and reflected light are very important in discrimination and recognition of indoor space and wayfinding, the evaluation of reflected light and shadow was low for the study. 3) items that are related to the functionality of the light were highly evaluated, while the items that are related to the spatiality of the light were rated poorly. This study has its significance when examining the effects of light environments within the welfare center form of the perspective of senior citizens. It can be referenced when reconsidering the recognition of light environment as a major consideration factor to establish a desirable senior welfare center environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.859-864
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• 2022

Drowsy driving, one of the biggest causes of traffic accidents every year, is accompanied by various factors. As a general method to check whether or not there is drowsiness, a method of identifying a driver's expression and driving pattern, and a method of analyzing bio-signals are being studied. This paper proposes a driver fatigue detection system using deep learning technology and bio-signal measurement technology. As the first step in the proposed method, deep learning is used to detect the driver's eye shape, yawning presence, and body movement to detect drowsiness. In the second stage, it was designed to increase the accuracy of the system by identifying the driver's fatigue state using the pulse wave signal and body temperature. As a result of the experiment, it was possible to reliably determine the driver's drowsiness and fatigue in real-time images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1723-1728
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• 2021

C-ITS is an intelligent transportation system that can improve transportation convenience and traffic safety by collecting, managing, and providing traffic information between components such as vehicles, road infrastructure, drivers, and pedestrians. In Korea, road infrastructure is being built across the country through the C-ITS project, and various services such as real-time traffic information provision and bus operation management are provided. However, the current state-of-the-art road infrastructure and information linkage system are insufficient to build C-ITS. In this paper, considering the continuity of time in various spatial aspects, we proposed a group-type network-based traffic situation recognition system that can recognize traffic flows and unexpected accidents through information linkage between traffic infrastructures. It is expected that the proposed system can primarily respond to accident detection and warning in the field, and can be utilized as more diverse traffic information services through information linkage with other systems.