• Molecules and Cells
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• v.44 no.5
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• pp.310-317
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• 2021

Cluster of differentiation 1 (CD1) is a family of cell-surface glycoproteins that present lipid antigens to T cells. Humans have five CD1 isoforms. CD1a is distinguished by the small volume of its antigen-binding groove and its stunted A' pocket, its high and exclusive expression on Langerhans cells, and its localization in the early endosomal and recycling intracellular trafficking compartments. Its ligands originate from self or foreign sources. There are three modes by which the T-cell receptors of CD1a-restricted T cells interact with the CD1a:lipid complex: they bind to both the CD1a surface and the antigen or to only CD1a itself, which activates the T cell, or they are unable to bind because of bulky motifs protruding from the antigen-binding groove, which might inhibit autoreactive T-cell activation. Recently, several studies have shown that by producing T_H2 or T_H17 cytokines, CD1a-restricted T cells contribute to inflammatory skin disorders, including atopic dermatitis, psoriasis, allergic contact dermatitis, and wasp/bee venom allergy. They may also participate in other diseases, including pulmonary disorders and cancer, because CD1a-expressing dendritic cells are also located in non-skin tissues. In this mini-review, we discuss the current knowledge regarding the biology of CD1a-reactive T cells and their potential roles in disease.

• Korean Journal of Environmental Biology
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• v.38 no.4
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• pp.497-506
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• 2020

This study surveyed the altitudinal diversity and distribution of butterflies inhabiting Mt. Jirisan. Field surveys were conducted thrice (May, June, and July) using a line transect method along four routes in 2015. During the survey, a total of five families, 58 species, and 769 individuals were collected. Of the species collected, the majority belonged to the family Nymphalidae (28 species), followed by Hesperiidae (nine species), Pieridae (eight species), Lycaenidae (seven species), and Papilionidae (six species). As for the individuals, Pieridae accounted for the largest number (333 individuals), followed by Nymphalidae (309 individuals), Lycaenidae (63 individuals), Hesperiidae (33 individuals), and Papilionidae (31 individuals). A cluster analysis performed on the butterfly species distinguished three altitude zones. The butterflies showed different ecological traits in each of the altitude zones. Analysis of the altitudes of the habitats of eight dominant species revealed that each species inhabited a particular altitude. This study confirmed the hypothesis that continuous monitoring will identify changes in the altitudinal distribution and diversity of butterflies on Mt. Jirisan in response to climate change.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• The Research Journal of the Costume Culture
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• v.30 no.4
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• pp.608-630
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• 2022

The purpose of this study is to examine the relationships between citations and the research trends of The Research Journal of the Costume Culture (RJCC) using bibliometric and network analyses. The results are as follows. First, the RJCC has been cited by a greater number of journals and high-reputation journals today. The RJCC has been mentioned in global academic journals in various fields, and it has been noted the most in environmental science. Second, because of examining the articles published in the RJCC over the past three years (2019 - 2021), it was found that the number of topics was evenly distributed in various subfields of the clothing and textiles sector. The RJCC principally deals with traditional clothing, ethics and sustainability, and technology, which means that the RJCC reflects the past, present, and future. As a result of conducting a cluster analysis using the Wakita-Tsurumi algorithm, the subjects of ethical fashion and sustainability were derived from the subdivisions of the RJCC. This suggests that the RJCC is a journal specialized in ethical fashion and sustainability sectors such as environmental, animal, and labor ethics. This study outlined the current status and future direction of academic journals in the field of clothing through an analysis of the RJCC's influence change and the relationship between citations. In addition, it is academically significant because it identifies research trends and knowledge-structure changes in the apparel science field by identifying changes in research keywords and significant research topics by sector.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2188-2208
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• 2023

Quality of Service (QoS) is a critical feature of Wireless Sensor Networks (WSNs) with routing algorithms. Data packets are moved between cluster heads with QoS using a number of energy-efficient routing techniques. However, sustaining high scalability while increasing the life of a WSN's networks scenario remains a challenging task. Thus, this research aims to develop an energy-balancing component that ensures equal energy consumption for all network sensors while offering flexible routing without congestion, even at peak hours. This research work proposes a Gravitational Blackhole Search Optimised splay tree routing framework. Based on the splay tree topology, the routing procedure is carried out by the suggested method using three distinct steps. Initially, the proposed GBSO decides the optimal route at initiation phases by choosing the root node with optimum energy in the splay tree. In the selection stage, the steps for energy update and trust update are completed by evaluating a novel reliance function utilising the Parent Reliance (PR) and Grand Parent Reliance (GPR). Finally, in the routing phase, using the fitness measure and the minimal distance, the GBSO algorithm determines the best route for data broadcast. The model results demonstrated the efficacy of the suggested technique with 99.52% packet delivery ratio, a minimum delay of 0.19 s, and a network lifetime of 1750 rounds with 200 nodes. Also, the comparative analysis ensured that the suggested algorithm surpasses the effectiveness of the existing algorithm in all aspects and guaranteed end-to-end delivery of packets.

• Korea Trade Review
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• v.43 no.4
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• pp.177-217
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• 2018

The purpose of this study is to classify the types of internationalization strategies utilized by Korean ventures and to examine whether there is a significant relationship between these types and internationalization performances. Specifically we tested whether there is a good feasibility through empirical analysis of the study model constructed through the following process. As a criterion of typification, the capability of international entrepreneurship and the capability of effectuation of a venture were chosen, and a model in which those three types exist based on the capabilities is established. The characteristics of each type and the contents of internationalization strategy are explained and empirical analysis is conducted. We also test whether there are significant differences in internationalization performance for each type. As a result of the cluster analysis, we concluded that there are three types : pioneer, careful preparation and passive response. In addition, these three types have significant differences in the levels of performances of reputation in foreign markets and the accumulation of knowledge in international management. This implies significant differences among the performances of each type of ventures according to their internationalization strategy positions. Therefore, the type of venture should be considered when a venture establishes its internationalization strategy and governments set supporting policy for venture companies.

• The Plant Pathology Journal
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• v.40 no.1
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• pp.59-72
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• 2024

A comprehensive survey of mungbean-growing areas was conducted to observe leaf spot disease caused by Alternaria alternata. Alternaria leaf spot symptoms were observed on the leaves. Diversity of 50 genotypes of mungbean was assessed against A. alternata and data on pathological traits was subjected to cluster analysis. The results showed that genotypes of mungbean were grouped into four clusters based on resistance parameters under the influence of disease. The principal component biplot demonstrated that all the disease-related parameters (% disease incidence, % disease intensity, lesion area, and % of infection) were strongly correlated with each other. Alt a 1 gene that is precisely found in Alternaria species and is responsible for virulence and pathogenicity. Alt a 1 gene was amplified using gene specific primers. The isolated pathogen produced similar symptoms when inoculated on mungbean and tobacco. The sequence analysis of the internal transcribed spacer (ITS) region, a 600 bp fragment amplified using specific primers, ITS1 and ITS2 showed 100% identity with A. alternata. Potato virus X (PVX) -based silencing vector expressing Alt a 1 gene was constructed to control this pathogen through RNA interference in tobacco. Out of 50 inoculated plants, 9 showed delayed onset of disease. Furthermore, to confirm our findings at molecular level semi-quantitative reverse transcriptase polymerase chain reaction was used. Both phenotypic and molecular investigation indicated that RNAi induced through the VIGS vector was efficacious in resisting the pathogen in the model host, Tobacco (Nicotiana tabacum). To the best of our knowledge, this study has been reported for the first time.

• Journal of Forest and Environmental Science
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• v.40 no.3
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• pp.210-226
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• 2024

Old-growth mixed-conifer forests in Bhutan are characterized by remarkable tree species compositional heterogeneity. However, our knowledge of tree species assemblages and their structural attributes in these forests has been limited. Therefore, forest classification has been reliant on a single dominant species. This study aimed to distinguish tree species assemblages in an old-growth mixed conifer forest in Western Bhutan and to describe their natural compositional and stand structural characteristics. Furthermore, the regeneration status of species was investigated and the quantity and quality of accumulated coarse woody debris were assessed. Ninety simple random sampling plots were surveyed in the study site between 3,000 and 3,600 meters above sea level. Tree, standing deadwood, regeneration, and coarse woody debris data were collected. Seven tree species assemblages were distinguished by Hierarchical Cluster Analysis and Indicator Species Analysis, representing five previously undescribed tree species associations with unique set of consistent species. Principal Component Analysis revealed two transitional pathways of species dominance along an altitudinal gradient, highly determined by relative topographic position. The level of stand stratification varied within a very wide range, corresponding to physiognomic composition. Rotated-sigmoid and negative exponential diameter distributions were formed by overstorey species with modal, and understorey species with negative exponential distribution. Overstorey dominant species showed extreme nurse log dependence during regeneration, which supports the formation of their modal distribution by an early natural selection process. This allows the coexistence of overstorey and understorey dominant species, increasing the sensitivity of these primary ecosystems to forest management.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.