• Genomics & Informatics
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• 제20권1호
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• pp.5.1-5.10
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• 2022

Non-syndromic hearing loss (NSHL) is a common hereditary disorder. Both clinical and genetic heterogeneity has created many obstacles to understanding the causes of NSHL. The present study has attempted to ravel the genetic aetiology in NSHL progression and to screen out potential target genes using computational approaches. The reported NSHL target genes (2009-2020) have been studied by analyzing different biochemical and signaling pathways, interpretation of their functional association network, and discovery of important regulatory interactions with three previously established miRNAs in the human inner ear as well as in NSHL such as miR-183, miR-182, and miR-96. This study has identified SMAD4 and SNAI2 as the most putative target genes of NSHL. But pathogenic and deleterious non-synonymous single nucleotide polymorphisms discovered within SMAD4 is anticipated to have an impact on NSHL progression. Additionally, the identified deleterious variants in the functional domains of SMAD4 added a supportive clue for further study. Thus, the identified deleterious variant i.e., rs377767367 (G491V) in SMAD4 needs further clinical validation. The present outcomes would provide insights into the genetics of NSHL progression.

• 한국전자통신학회논문지
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• 제16권4호
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• pp.675-682
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• 2021

제한된 종류, 제한된 수량의 센서를 사용하여야 하는 환경에서 다양한 상황정보를 획득하여야 하는 수요가 나타날 수 있다. 본 연구에서는 제한된 숫자의 센서를 사용하여야 하는 환경에서 한정된 센서를 사용하면서도 이전보다 다양한 상황정보를 획득하기 위한 새로운 방안을 제안하였다. 이를 위하여 생물학 분야에서 큰 관심을 얻고 있는 Exon-Intron이론에서 실마리를 얻어 이를 기초로 다양한 상황정보 획득 방안을 제안하였다. Exon-Intron의 선택적 자르기 및 조합 방안과 같이 각 센서의 이벤트들을 효율적으로 자르고 각 이벤트 데이터들을 조합하여 활용함으로써 획득하는 상황정보의 다양화를 실현할 수 있었다.

• 산업경영시스템학회지
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• 제45권4호
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• pp.79-85
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• 2022

Various non-face-to-face services are being activated due to the influence of the Corona 19 virus around the world. However, unlike the rapid development of delivery services, social awareness of delivery services is causing many problems. Therefore, in this study, we analyze the quality attributes of delivery services from the consumer's point of view, and based on the results, we try to derive a direction for service improvement. In this study, quality factors were established through interviews and surveys with actual consumers, and quality attributes were classified through the Kano model and Timko's customer satisfaction coefficient. "Attractive" is ('Ease of ordering, Accurate delivery to the designated place'), "One Dimensional" is ('Variety of payment methods, Accurate delivery on time, Accurate delivery of ordered food, Degree of non-deformation of packaging conditions, etc., Convenience of use time'), "Must be" is ('Kindness of the delivery person'), "Reverse" is ('provision of services, service response to order discrepancies'). This study has academic significance in that it compensated for the disadvantage of not being able to interpret the mathematical meaning of the Kano model with Teamco's customer satisfaction coefficient. It also has practical implications in that it provides an indirect clue to future improvement directions.

• Journal of Ecology and Environment
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• 제46권1호
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• pp.18-30
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• 2022

Background: Bees and flowering plants associations were initially began during the early Cretaceous, 120 million years ago. This coexistence has led to a mutual relationship where the plant serves as food and in return, the bee help them their reproduction. Animals pollinate about 75% of food crops worldwide, with bees as the world's primary pollinator. In general, bees rely on flower scents to locate blooming flowers as visual clue is limited and also their host plants from a distance. In this review, an attempt is made to collect some relevant 107 published papers from three scientific databases, Google Scholar, Scopus, and Web of Science database, covering the period from 1959 to 2021. Results: Flowering plants are well documented to actively emit volatile organic compounds (VOCs). However, only a few of them are important for eliciting behavioral responses in bees. In this review, fifty-three volatile organic compounds belonging to different class of compounds, mainly terpenoids, benzenoids, and volatile fatty acid derivatives, is compiled here from floral scents that are responsible for eliciting behavioral responses in bees. Bees generally use honest floral signals to locate their host plants with nectar and pollen-rich flowers. Thus, honest signaling mechanism plays a key role in maintaining mutualistic plant-pollinator associations. Conclusions: Considering the fact that floral scents are the primary attractants, understanding and identification of VOCs from floral scent in plant-pollinator networks are crucial to improve crop pollination. Interestingly, current advances in both VOCs scent gene identification and their biosynthetic pathways make it possible to manipulate particular VOCs in plant, and this eventually may lead to increase in crop productivity.

• 산업경영시스템학회지
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• 제46권2호
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• pp.1-12
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• 2023

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.

• 한국의상디자인학회지
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• 제25권2호
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• pp.31-44
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• 2023

Fashion design in the metaverse is not simply a 3D avatar or virtual fashion, it is an important clue for shopping trends, and the role of fashion design has grown even more because avatars and humans are identified and active. This study, I attempts to understand the metaverse platform accurately and find out the scope of fashion design within the metaverse platform. In addition, we want to provide basic data that can expand the field by using fashion design in various ways on the metabus platform. This study investigated and analyzed various metaverse fashion cases, articles, software, and methods used by metaverse fashion creators, and the results are as follows. First, the metaverse platform is a new level of virtual interaction where users and creators communicate through the convergence of augmented reality, lifelogging, mirror world, and virtual world. Second, most of the users of the metaverse platform are generation Z, and metaverse creators who make money by producing avatars or items, including fashion design, are emerging as a new job field. Third, many fashion brands created spaces on the Metaverse platform, collaborated with games, or opened fashion weeks for publicity, marketing, and sales. Fourth, as a 3D program for metaverse fashion creator activities, open-source software is easier and free of charge compared to programs for fashion design specialists, and most costumes can be reproduced, so it will be easier for fashion design majors to utilize.

• 융합경영연구
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• 제5권3호
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• pp.21-29
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• 2017

This study was conducted to examine the effects of interactivity, entertainment and ease of use, which are positive characteristics of SNS, on SNS using satisfaction and using reluctant intention and the roles of perceived values and trust among users in the relationships among these variables, in order to find a clue to contribution to positive use and development of SNS. For this study, a survey was performed targeting normal people in Seoul and the metropolitan area and a total of 224 effective questionnaires were acquired. Then frequency analysis, descriptive statistic analysis, correlation analysis and structural equation path analysis were carried out. As a result of analysis, interactivity and ease of use increased SNS using satisfaction and decreased using reluctant intention via trust and users' perceived values respectively. The result of analyzing the modification model showed that interactivity and entertainment directly increased SNS using satisfaction. These findings imply that SNS providers fully need to reflect the needs of consumers for interactivity, entertainment and ease of use for improving consumers' perceived values and trust. It is also concluded that consumers can enjoy positive SNS activities by increasing trust with SNS users through a positive understanding of interactivity and participation.

• 한국지형학회지
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• 제28권1호
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• pp.67-81
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• 2021

Geomorphological development and distribution at the macro scale provide a clue to the geotectonic characteristics that have affected the geomorphological system. This is because the developmental characteristics and distribution of the landform at the macro scale remain spatial characteristics due to tectonic processes, such as fault activity. From the perspective of tectonic geomorphology, this study identified the developmental characteristics and distribution of the Quaternary landforms in central-southern Yangsan fault and discussed its relevance to fault activity. In this paper, we presented examples and results of morphotectonic analysis of the Yangsan fault, and will present the results of age dating, stratigraphic relationship of the Quaternary landforms, and calculation of cumulative slip rate in the next paper.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.459-462
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• 2015

Korean construction industry made a huge growth over several decades. However, domestic construction market has shrunk in recent years due to the domestic political environments and global economic crisis. Today, the international construction markets become more important to be investigated, and demands for international construction study have risen. The purpose of this study is to search for measures to compare the potential of Southeast Asian countries' construction markets and select strategic target countries where the Korean construction companies pursue to explore for future investments. The research team investigated a range of selection factors which can represent the construction market condition of each country. These factors included the size of the construction industry, economic growth potential, current relationship with Korea, the level of infrastructure development, political situation, etc. After collecting data, each selection factor was scored by experts' analyses and the total score was given to each country. As a result, the rating identified attractive countries for future investments: Myanmar, Vietnam, and Sri Lanka. For the target countries, analytical methods were used for in-depth market analysis that can provide comprehensive insight and strategic clue for development of short-/mid-/long-term roadmap and action plans. The research findings would be used to support rational decision making of construction investment advancing to the Southeast Asian economic growth.

• Nuclear Engineering and Technology
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• 제56권4호
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• pp.1372-1384
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• 2024

The discrimination of the source for xenon gases' release can provide an important clue for detecting the nuclear activities in the neighboring countries. In this paper, three machine learning techniques, which are logistic regression, support vector machine (SVM), and k-nearest neighbors (KNN), were applied to develop the predictive models for discriminating the source for xenon gases' release based on the xenon isotopic activity ratio data which were generated using the depletion codes, i.e., ORIGEN in SCALE 6.2 and Serpent, for the probable sources. The considered sources for the neighboring countries of South Korea include PWRs, CANDUs, IRT-2000, Yongbyun 5 MWe reactor, and nuclear tests with plutonium and uranium. The results of the analysis showed that the overall prediction accuracies of models with SVM and KNN using six inputs, all exceeded 90%. Particularly, the models based on SVM and KNN that used six or three xenon isotope activity ratios with three classification categories, namely reactor, plutonium bomb, and uranium bomb, had accuracy levels greater than 88%. The prediction performances demonstrate the applicability of machine learning algorithms to predict nuclear threat using ratios of xenon isotopic activity.