• The Research Journal of the Costume Culture
• /
• v.31 no.3
• /
• pp.330-345
• /
• 2023

This study aimed to categorize consumers using super app functional characteristics to identify demographic differences, and analyze shopping orientations by consumer type. This data can be used by fashion and beauty companies for product planning and marketing strategies. To categorize super app consumers, data were analyzed with SPSS v.26.0 software using frequency, factor, reliability K-mean cluster, and distributed analyses, one-way-ANOVAs, and Scheffe verification. Cross-analysis was conducted to correlate super app consumer types with demographic characteristics. One-way-ANOVAs and Scheffe verification were used to analyze the differences in shopping preferences between super app consumer groups. As a result of our analyses, super app consumers were classified into four types: the ration type, the low-use type, the multifunction type, and the habit type. There were statistically significant differences between these types in age, occupation, marital status, average monthly household income, and shopping impact factors. Five super app user shopping orientations were identified: brand pursuit, pleasure pursuit, trend pursuit, risk perception, and economic orientation. The differences in the preferred orientation between super app consumer types were found to be statistically significant. The majority of respondents were multifunction type consumers. This group used the super app most frequently and effectively. They also demonstrated the highest scores for all five of the shopping orientations. The classification of consumer types in this study will allow the fashion and beauty industries to utilize super apps for more targeted product design and marketing.

• 한국노년학
• /
• v.30 no.3
• /
• pp.895-910
• /
• 2010

This study examined the mediating effect of social isolation on the life satisfaction among lowincome older adults. The purpose of this study was to find out isolated older adults' social isolation rate and mediating effect of sense of community by community dwelling older adults with loweconomic status. This study used the Gijang Welfare Network study(2009). The sample consisted 256 older adults 65 and older residing in Busan(Gijang). As statistical method, correlation analysis and structural equation model used in this paper. The results of this study suggested some practical implications in reducing social isolation for older adults with low economic status. We need to emphasize social relations and social participations as well as outreach program for high-risk elderly of social isolation. In addition, Findings suggested that community based interventions should be provided to protect older people, especially poor elderly from social isolation.

• Korean Journal of Social Welfare Studies
• /
• v.41 no.3
• /
• pp.379-402
• /
• 2010

The aim of this study is to explore the school adaptation and aggression of the children selected from 3 different SES communities and to investigate how parenting styles and children' school adaptation and aggression are different according to community-level socio-economic status. Subjects were 441 elementary school graders(229 boys and 212 girls, from the 4th graders to the 6th graders. Community SES was measured by the proportion of adult population holding a bachelor's degree or higher among the whole adults aged more than 30 and divided into 3 regions(rated high, middle and low in the metropolitan city). Data analysis was by F-test and multiple regression. The children from the high and middle SES community were more adaptive to school and less aggressive than those from the lower SES community. And the parents(or caregivers) from the high and middle SES community were more authoritative than those from other regions. These findings tell us that the children from the lower SES community are at risk and that some special programs to support children and their parents are needed.

• Korean Journal of Culture and Social Issue
• /
• v.12 no.2
• /
• pp.1-19
• /
• 2006

There are less studies on the elderly suicide even though it's steep increase. The purpose of the present study was to investigate factors that influence on the elderly suicide and to categorize them. For these purpose, A total of 23 cases were analyzed through qualitative contents analysis. Specifically, on the basis of the stress-vulnerability model, we scrutinized vulnerability factors(classified personal, family-environment factors) and precipitating events(classified interpersonal events) influencing on the elderly suicide. Personal factor was to be classified into personal mental health, physical health and problematic behavior. Family-environment factor was divided family relationship problem and economic problem. Interpersonal events belonging to the precipitating events was to be classified into interpersonal loss and interpersonal conflict. As the results of this study, elderly suicide classified into 3 types, that is, 'risk type suicide', 'event-response type suicide', 'complex type'. And then we discussed the characteristics of the suicidal types and suggestions for reduction of elderly suicide.

• Smart Structures and Systems
• /
• v.32 no.3
• /
• pp.153-166
• /
• 2023

Health monitoring of civil infrastructures, in particular, old bridges that are still in service, has become more than necessary, given the risk that a possible degradation or failure of these infrastructures can induce on the safety of users in addition to the resulting commercial and economic impact. Bridge integrity assessment has attracted significant research efforts over the past forty years with the aim of developing new damage identification methods applicable to real structures. The bridge of Ouled Mimoun (Tlemcen, Algeria) is one of the oldest railway structure in the country. It was built in 1889. This bridge, which is too low with respect to the level of the road, has suffered multiple shocks from various machines that caused considerable damage to its central part. The present work aims to analyze the stability of this bridge by identifying damages and evaluating the damage rate in different parts of the structure on the basis of a finite element model. The applied method is based on an inverse analysis of the normal stress responses that were calculated from the corresponding recorded strains, during the passage of a real train, by means of a set of strain gauges placed on certain elements of the bridge. The results obtained from the inverse analysis made it possible to successfully locate areas that were really damaged and to estimate the damage rate. These results were also used to detect an excessive rigidity in certain elements due to the presence of plates, which were neglected in the numerical reference model. In the case of the continuous bridge monitoring, this developed method will be a very powerful tool as a smart health monitoring system, allowing engineers to take in time decisions in the event of bridge damage.

• International Journal of Computer Science & Network Security
• /
• v.23 no.10
• /
• pp.199-208
• /
• 2023

The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.

• International Journal of Computer Science & Network Security
• /
• v.23 no.10
• /
• pp.135-146
• /
• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• Journal of fish pathology
• /
• v.37 no.1
• /
• pp.97-110
• /
• 2024

The Serranidae is high-quality fish species with good meat quality and is traded at high price, and is attracting attention in South Korea as a cultured species that creates high added value. However, the high-density fish farming for mass production increases the risk of mass mortality due to infectious diseases, leading to enormous economic losses. Therefore, in order to safely prevent and protect farmed fish from serious infectious diseases, it is necessary to conduct disease monitoring on a regular basis. In this study, Hyporthodus septemfasciatus, Epinephelus moara, and the hybrid longtooth grouper (E. moara ♀×E. lanceolatus ♂) were collected once a month from fish farm of Garorim and Aquabiotech Co., Ltd for a total of six months, from July to December 2023. We investigated infections of five species of bacterial diseases, including Flavobacterium columnare, six species of viral diseases, including LCDV (lymphocystis disease virus), and parasitic pathogens in grouper farms. As the result, Vibrio vulnificus and V. harveyi were detected in H. septemfasciatus in August, in the case of viral diseases, NNV was detected in H. septemfasciatus from July to August using RT-PCR or PCR. Finally, In the case of parasitic diseases, Tricodina sp. was detected in E. moara and the hybrid longtooth grouper from August to December.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.28 no.2
• /
• pp.93-101
• /
• 2024

Code-compliant seismic design should be essentially applied to realize the so-called emulative performance of precast concrete (PC) lateral force-resisting systems, and this study developed simple procedures to design precast industrial buildings with intermediate precast bearing wall systems considering both the effect of seismic and blast loads. Seismic design provisions specified in ACI 318 and ASCE 7 can be directly adopted, for which the so-called 1.5S_y condition is addressed in PC wall-to-wall and wall-to-base connections. Various coupling options were considered and addressed in the seismic design of wall-to-wall connections for the longitudinal and transverse design directions to secure optimized performance and better economic feasibility. On the other hand, two possible methods were adopted in blast analysis: 1) Equivalent static analysis (ESA) based on the simplified graphic method and 2) Incremental dynamic time-history analysis (IDTHA). The ESA is physically austere to use in practice for a typical industrial PC-bearing wall system. Still, it showed an overestimating trend in terms of the lateral deformation. The coupling action between precast wall segments appears to be inevitably required due to substantially large blast loads compared to seismic loads with increasing blast risk levels. Even with the coupled-precast shear walls, the design outcome obtained from the ESA method might not be entirely satisfactory to the drift criteria presented by the ASCE Blast Design Manual. This drawback can be overcome by addressing the IDTHA method, where all the design criteria were fully satisfied with precast shear walls' non-coupling and group-coupling strength, where each individual or grouped shear fence was designed to possess 1.5S_y for the seismic design.

• The Journal of Information Systems
• /
• v.33 no.1
• /
• pp.45-68
• /
• 2024

Purpose This paper examines the role of local market-based communities in driving regional revitalization, using detailed analysis of online networks. We aim to dissect a local community's communication network, highlighting members with high engagement levels and exploring their characteristics. Our goal is to identify the conditions that allow local community networks to grow independently and to demonstrate how the activation of these networks contributes to regional revitalization. Design/methodology/approach We employ a mixed-methods approach, combining social network analysis with statistical techniques to investigate the structure of online communication networks. Specifically, we use ANOVA to determine the statistical significance of our findings, ensuring their reliability. To complement our quantitative data, we include qualitative insights from interviews, adding depth and context to our analysis. Findings Our results show that individuals with high centrality in the online network are crucial for maintaining active local communities. We find that leveraging local resources to create a supportive and adaptable environment is essential for the communities' sustainability and expansion. Importantly, our research draws a direct connection between the vitality of local community networks and the broader process of regional revitalization. We argue that energizing local communities is an effective way to address the risk of regional decline. By integrating quantitative analysis with qualitative feedback, this study contributes to the understanding of local market-based communities as key drivers of regional development. It emphasizes the importance of building vibrant, resourceful community networks to revitalize areas experiencing socio-economic challenges.