• International Journal of Computer Science & Network Security
• /
• v.24 no.6
• /
• pp.119-130
• /
• 2024

Universities are open systems that aim to prepare students to meet academic and industrial programs' expectations. It is important for universities to recognize these expectations and to make sure that they are achievable. To do so, graduates' progression tracking system is an essential tool for universities' development to ensure graduate students meet the market requirements. The purpose of this paper is to create automatic tracing system that captures information about students after graduation and creates annual report that represents the status of university students in term of employment or completing their study. It mainly assists graduates to find appropriate jobs that meet their desires or enabling them to complete their higher education by providing all these opportunities in one platform. The system main objective is to improve communication between graduate students, the university and companies. It also aims to identify the difficulties associated with graduate employability and changes are required to serve current students in term of creating new programs or activities. This helps universities to identify and address the existing curriculums and program's strengths and weaknesses and their adequacy, quality and competencies of a graduate in the labor market, which enhances the quality of higher education. we analyzed and implemented the tracing system using PHP language, which speeds up custom web application development and MySQL database, which guarantee data security, high performance, and other features. Graduate students found the proposed system usable and valuable.

• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.113-123
• /
• 2024

Stock market news sentiment analysis (SA) aims to identify the attitudes of the news of the stock on the official platforms toward companies' stocks. It supports making the right decision in investing or analysts' evaluation. However, the research on Arabic SA is limited compared to that on English SA due to the complexity and limited corpora of the Arabic language. This paper develops a model of sentiment classification to predict the polarity of Arabic stock news in microblogs. Also, it aims to extract the reasons which lead to polarity categorization as the main economic causes or aspects based on semantic unity. Therefore, this paper presents an Arabic SA approach based on the logistic regression model and the Bidirectional Encoder Representations from Transformers (BERT) model. The proposed model is used to classify articles as positive, negative, or neutral. It was trained on the basis of data collected from an official Saudi stock market article platform that was later preprocessed and labeled. Moreover, the economic reasons for the articles based on semantic unit, divided into seven economic aspects to highlight the polarity of the articles, were investigated. The supervised BERT model obtained 88% article classification accuracy based on SA, and the unsupervised mean Word2Vec encoder obtained 80% economic-aspect clustering accuracy. Predicting polarity classification on the Arabic stock market news and their economic reasons would provide valuable benefits to the stock SA field.

• Journal of Ginseng Research
• /
• v.48 no.1
• /
• pp.103-111
• /
• 2024

Background: Ginseng (Panax ginseng Mayer) is an important natural medicine. However, a long culture period and challenging quality control requirements limit its further use. Although artificial cultivation can yield a sustainable medicinal supply, research on the association between the transplantation and chaining of metabolic networks, especially the regulation of ginsenoside biosynthetic pathways, is limited. Methods: Herein, we performed Liquid chromatography tandem mass spectrometry based metabolomic measurements to evaluate ginsenoside accumulation and categorise differentially abundant metabolites (DAMs). Transcriptome measurements using an Illumina Platform were then conducted to probe the landscape of genetic alterations in ginseng at various ages in transplantation mode. Using pathway data and crosstalk DAMs obtained by MapMan, we constructed a metabolic profile of transplantation Ginseng. Results: Accumulation of active ingredients was not obvious during the first 4 years (in the field), but following transplantation, the ginsenoside content increased significantly from 6-8 years (in the wild). Glycerolipid metabolism and Glycerophospholipid metabolism were the most significant metabolic pathways, as Lipids and lipid-like molecule affected the yield of ginsenosides. Starch and sucrose were the most active metabolic pathways during transplantation Ginseng growth. Conclusion: This study expands our understanding of metabolic network features and the accumulation of specific compounds during different growth stages of this perennial herbaceous plant when growing in transplantation mode. The findings provide a basis for selecting the optimal transplanting time.

• Knowledge Management Research
• /
• v.24 no.4
• /
• pp.63-85
• /
• 2023

This study aims to identify the primary user group in the growing metaverse space based on the increased interest during the COVID-19 era. It also aims to explore the predictive factors for metaverse adoption. To predict online activities, the study examined user purposes, motivations, and relevant demographic factors as predictive variables through model analysis. The data from the Korean Media Panel Survey were used, and a two-stage analysis with the Heckman two-stage sample selection model was conducted to predict metaverse users. The analysis revealed that the key factors influencing metaverse adoption were offline activities, openness, OTT usage, and purchasing of paid content. Moreover, in the second stage model, openness, gender, and paid content purchases were identified as significant variables for increasing metaverse usage time. These results indicate that understanding metaverse users is essential in the context of the rising interest in online activities during the COVID-19 era and can provide valuable insights for metaverse platform-related companies and developers.

• Information Systems Review
• /
• v.22 no.3
• /
• pp.81-97
• /
• 2020

Recent trends in sentiment analysis have been focused on applying single label classification approaches. However, when considering the fact that a review comment by one person is usually composed of several topics or aspects, it would be better to classify sentiments for those aspects respectively. This paper has two purposes. First, based on the fact that there are various aspects in one sentence, aspect mining is performed to classify the emotions by each aspect. Second, we apply the multiple label classification method to analyze two or more dependent variables (output values) at once. To prove our proposed approach's validity, online review comments about musical performances were garnered from domestic online platform, and the multi-label classification approach was applied to the dataset. Results were promising, and potentials of our proposed approach were discussed.

• Information Systems Review
• /
• v.21 no.2
• /
• pp.69-89
• /
• 2019

Recently, consumers are increasingly interested in the sharing economy, which utilizes various resources by sharing unused or under-used products/services with others. This study focuses on Airbnb, a representative sharing economy platform, to identify the success factors of the sharing accommodation services. The key properties of sharing accommodation services are extensively surveyed from extant literature and are classified them into the three important factors (economic, convenience, and trust) that influence the success of room-sharing services. The research data include 1,673 Airbnb hosts who offered accommodations in New York City, USA, in June 2018. The research variables of economic-, convenience-, and trust-related factors are utilized in the empirical analyses. The results of this study show that the number of available facilities, flexibility of refunds, the response rate and time to customer requests, and the status of Super host are positively associated with guest satisfaction from sharing accommodation services. This study bears significant managerial implications by suggesting a set of practical guidelines to participants in sharing accommodation services.

• Journal of Fashion Business
• /
• v.28 no.2
• /
• pp.125-138
• /
• 2024

The purpose of this study is to develop and implement a step-by-step upcycling fashion education program that can be utilized within the local community. This program aims to provide basic data by analyzing the current state of community-based upcycling projects and upcycling center programs. To achieve this, the study first examined the meaning and value of upcycling in fashion through literature research and explored upcycling projects and programs in connection with local communities. Subsequently, an upcycling fashion education program platform was developed and applied using the design thinking process. The program involved students from nine high schools in Gwangju Metropolitan City. Depending on the school's circumstances, the time and difficulty level of the upcycling education program were adjusted accordingly. A unique eco-bag making kit, using jeans developed in this study, was employed. Following the completion of the program, a satisfaction survey was conducted among 167 participating students from the high school community class. The findings indicated that the majority of students experienced an increased appreciation, attraction, and interest in upcycling products. They also demonstrated an understanding of the environmental impact of upcycling products and the distinction between upcycling and recycling. It is believed that the educational program developed in this study can promote ethical fashion and foster a sense of value-based consumption. This program can be customized and flexibly adapted to different educational levels and institutional characteristics, making it accessible to a wide range of learners.

• Communications of Mathematical Education
• /
• v.38 no.2
• /
• pp.231-246
• /
• 2024

In this paper, we present the development and a case study on 'Mathematics & Coding Mobile Contents' tailored for secondary education. These innovative resources aim to alleviate the burden of laborious calculations, enabling students to allocate more time to engage in discussions and visualize complex mathematical concepts. By integrating these contents into the curriculum, students can effectively meet the national standards for achievement in mathematics. They are empowered to develop their mathematical thinking skills through active engagement with the material. When properly integrated into secondary mathematics education, these resources not only facilitate attainment of national curriculum standards but also foster students' confidence in their mathematical abilities. Furthermore, they serve as valuable tools for nurturing both computational and mathematical thinking among students.

• The Research Journal of the Costume Culture
• /
• v.32 no.3
• /
• pp.419-437
• /
• 2024

This study analyzed differences in the purchase satisfaction and repurchase intention of customers who buy clothing products from online platforms. The participants were teenage individuals to those in their 50s residing in Busan, Ulsan, and Gyeongsangnam-do. The data were examined via factor analysis, a t-test, Analysis of variance(ANOVA), Duncan's multiple range test, two-way ANOVA, and linear regression analysis. The factors for satisfaction with clothing products from online platforms were wearing comfort and quality, design, and price and purchase convenience. The findings revealed that purchase satisfaction based on these factors significantly varied among the participants depending on marital status, age, and occupation. Satisfaction with wearing comfort, quality, and design differed by gender. Satisfaction with wearing comfort, quality, and price and purchase convenience varied by type of purchase and type of online platforms. The interaction effects among the variables that affected purchase satisfaction were as follows. The interaction effects among the variables for wearing comfort and quality showed significant interactions between gender and type of purchase and between occupation and type of online platforms. Those for design showed significant interactions between marital status and age, between age and occupation, and so on. The interaction effects for price and purchase convenience showed significant interactions between marital status and gender and between age and occupation. The results on repurchase intention showed significant differences in such intention by marital status, age, and occupation. Repurchase intention was influenced by wearing comfort and quality, price and purchase convenience, design, and age.

• Journal of Radiation Industry
• /
• v.17 no.3
• /
• pp.265-273
• /
• 2023

To effectively and safely manage the radiation exposure to nuclear power plant (NPP) workers in accidents, major overseas NPP operators such as the United States, Germany, and France have developed and applied realistic 3D model radiation dose assessment software for workers. Continuous research and development have recently been conducted, such as performing NPP accident management using 3D-VR based on As Low As Reasonably Achievable (ALARA) planning tool. In line with this global trend, it is also required to secure technology to manage radiation exposure of workers in Korea efficiently. Therefore, in this paper, it is described the application method and assessment results of radiation exposure scenarios for workers in response to accidents assessment technology, which is one of the fundamental technologies for constructing a realistic platform to be utilized for radiation exposure prediction, diagnosis, management, and training simulations following accidents. First, the post-accident sampling after the Loss of Coolant Accident(LOCA) was selected as the accident and response scenario, and the assessment area related to this work was established. Subsequently, the structures within the assessment area were modeled using MCNP, and the radiation source of the equipment was inputted. Based on this, the radiation dose distribution in the assessment area was assessed. Afterward, considering the three principles of external radiation protection (time, distance, and shielding) detailed work scenarios were developed by varying the number of workers, the presence or absence of a shield, and the location of the shield. The radiation exposure doses received by workers were compared and analyzed for each scenario, and based on the results, the optimal accident response scenario was derived. The results of this study plan to be utilized as a fundamental technology to ensure the safety of workers through simulations targeting various reactor types and accident response scenarios in the future. Furthermore, it is expected to secure the possibility of developing a data-based ALARA decision support system for predicting radiation exposure dose at NPP sites.