• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.41-47
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• 2021

Detection of protein-protein interactions (PPIs) remains essential for the development of therapies against diseases. Experimental studies to detect PPI are longer and more expensive. Today, with the availability of PPI data, several computer models for predicting PPIs have been proposed. One of the big challenges in this task is feature extraction. The relevance of the information extracted by some extraction techniques remains limited. In this work, we first propose an extraction method based on correlation relationships between the physicochemical properties of amino acids. The proposed method uses a correlation matrix obtained from the hydrophobicity and hydrophilicity properties that it then integrates in the calculation of the bigram. Then, we use the SVM algorithm to detect the presence of an interaction between 2 given proteins. Experimental results show that the proposed method obtains better performances compared to the approaches in the literature. It obtains performances of 94.75% in accuracy, 95.12% in precision and 96% in sensitivity on human HPRD protein data.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.91-109
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• 2021

Recently, social and economic environment has been rapidly changed. In particular, the development of IT technology accelerated the introduction of databases, communication networks, information processing and analyzing systems, making the use of such information and communication technology an essential factor for corporate management innovation. This change also affected the accounting areas. The purpose of this study is to document changes in accounting areas due to the adoption of IT technologies in the era of technology and information, to define the required accounting professions in this era, and to present the efficient educational methodologies for training such accounting experts. An accounting expert suitable for the era of technology and information means an accounting profession not only with basic accounting knowledge, competence, independency, reliability, communication skills, and flexible interpersonal skills, but also with IT skills, data utilization and analysis skills, the understanding big data and artificial intelligence, and blockchain-based accounting information systems. In order to educate future accounting experts, the accounting curriculum should be reorganized to strengthen the IT capabilities, and it should provide a wide variety of learning opportunities. It is also important to provide a practical level of education through industry and academic cooperation. Distance learning, web-based learning, discussion-type classes, TBL, PBL, and flipped-learnings will be suitable for accounting education methodologies to foster future accounting experts. This study is meaningful because it can motivate to consider accounting educational system and curriculum to enhance IT capabilities.

• The Journal of Economics, Marketing and Management
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• v.9 no.2
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• pp.11-20
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• 2021

Purpose: The importance of creativity has been emphasized in the transition from industrial society to knowledge-based society. Recently, design thinking has attracted great attention as one of the ways to increase the creativity of the organization. From the perspective of solving urban problems through collaboration between technology and citizens, the active participation of citizens is indispensable for realizing smart cities. Research design, data and methodology: From the perspective of solving urban problems through collaboration between technology and citizens, the active participation of citizens is indispensable for realizing smart cities. Results: Therefore, the purpose of this research was to design a citizen-participation type system and contents using a specific space to realize a smart city. This system utilizes the concept of space as a tool to promote innovation activities with the participation of citizens and makes it easy for users of space to participate based on urban problems derived from living labs and the internal structure and user flow line have been designed. Conclusions: It was been also used voice recognition, artificial intelligence, the Internet of Things, and big data as important technologies for experiencing smart cities. The system and content were designed with an emphasis on allowing citizens to directly recognize and experience smart city technology, especially through space-based information visualization and multi-faceted stimulus elements.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.582-587
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• 2021

Book recommender system, which suggests book to users according to their book taste and preference effectively improves users' book-reading experience and exposes them to variety of books. Insufficient dataset of book rating records by users degrades the quality of recommendation. In this study, we suggest a book recommendation system that makes use of user's book ratings collaboratively with user's movie ratings where more abundant datasets are available. Through comprehensive experiment, we prove that our methods improve the recommendation quality and effectively recommends more diverse kind of books. In addition, this will be the first attempt for book recommendation system to utilize movie rating data, which is from the media-platform other than books.

• International Journal of Contents
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• v.17 no.1
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• pp.1-10
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• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.199-206
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• 2021

This study investigated the main concerns and strategies in Indonesian large family businesses to undertake intergenerational succession effectively. The research data was obtained to shed light on the incumbents' mindsets, key preferences, and experiences during the succession process. Access to incumbents of large family businesses that are conglomerates is scant. The preceding survey research was conducted to sensitize with the intricacy of the intergenerational succession process in large family businesses before entailing interpretative phenomenology analysis of qualitative data from interviews, observations, and field notes by approaching family members in five conglomerate groups that have major impacts on the economy. The findings explicate the incumbents' preferred criteria in choosing their successors as well as their perceived concerns revolving around the appointment. Additionally, the incumbents' succession approaches such as apprentice learning by successors, adaptability to external forces by successors, nurturing the entrepreneurial spirit in successors, governance establishment in the firms, business interest stimulation in successors, role modeling by incumbents, and collaboration between family and key non-family members are elicited during the intergenerational succession process. This study concluded with noteworthy implications for incumbents and successors in large family businesses, especially providing explicit criteria and strategies to appoint suitable successors, and suggesting potential avenues for future research.

• Journal of Distribution Science
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• v.19 no.4
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• pp.25-35
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• 2021

Purpose: This study aims to analyze the factors affecting customer satisfaction in the customer reviews of omni-channel, posted on Internet blogs, cafes, and YouTube using text mining analysis. Research, data, and Methodology: In this study, frequency analysis is performed and the LDA (Latent Dirichlet Allocation) is used to analyze social big data to respond to reviewers' reaction to the recently opened omni-channel shopping reviews by L Shopping Company. Additionally, based on the topic analysis, we conduct a sentiment analysis on purchase reviews and analyze the characteristics of each topic on the positive or negative sentiments of omni-channel app users. Results: As a result of a topic analysis, four main topics are derived: delivery and events, economic value, recommendations and convenience, and product quality and brand awareness. The emotional analysis reveals that the reviewers have many positive evaluations for price policy and product promotion, but negative evaluations for app use, delivery, and product quality. Conclusions: Retailers can establish customized marketing strategies by identifying the customer's major interests through text mining analysis. Additionally, the analysis of sentiment by subject becomes an important indicator for developing products and services that customers want by identifying areas that satisfy customers and areas that evoke negative reactions.

• Human Ecology Research
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• v.59 no.3
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• pp.311-324
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• 2021

The purpose of this study was to reveal the effects of internal characteristics, such as fashion involvement, personality characteristics, and customer orientation of fashion brand salespeople on the core sales tasks, and how the core sales tasks and internal characteristics differ depending on differences in the way salespeople are remunerated. The data were collected as a questionnaire to fashion brand salespeople in Gwangju from September to October 2020. Using 235 responses, the data were analyzed with SPSS 21.0 for frequency analysis, reliability analysis, t-test, factor analysis, and regression analysis. The research results were as follows. First, fashion involvement comprises factors such as 'fashion passion and sense'and 'fashion trend interest', and the greater the 'fashion passion and sense', the better the 'sales management'and 'customer relationship management'jobs. Second, 'esthetic openness', 'responsibility' and 'extroversion' of the big five personality characteristics have a positive impact on 'sales management' and 'customer relationship management' tasks. Third, customer orientation comprises factors such as 'customer-centric understanding'and 'gain customer trust', the greater the customer-orientation, the better the 'sales management'and 'customer relationship management'tasks. Fourth, according to the position of the salesperson, the group of professional salespeople at manager level had high responses in core sales tasks, fashion involvement, customer orientation, and characteristics such as 'agreeableness', 'esthetic openness', and 'responsibility'.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.469-474
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• 2021

Nowadays, a lot of software engineers struggle with the efficient back-end design of mobile application programs operated on the new mobile platform. It is simply because not only their lack of experiences in developing large scale system but also the unstructured nature of the mobile software, where there are no standard solutions. Furthermore, since big data is at the center of many challenges in system design of mobile software, so an efficient system design scheme is required for the development of such data-intensive applications. In this paper, we propose a systematic and efficient system design method that can figure out the substantial nature of the mobile software and solve the difficulties of the back-end software engineers.

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.790-798
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• 2021

With digital technology innovation, increased data access and mobile network use by consumers, products and services are changing toward pursuing differentiated values for personalization, and personalized markets are rapidly emerging in the fashion industry. This study aims to identify trends in digital customized automation technology by deriving types of digital customizing and analyzing cases by type, and to present directions for the development of digital customizing processes and the use of technology in the future. As a research method, a literature study for a theoretical background, a case study for classification and analysis of types was conducted. The results of the study are as follows. The types of digital customizing can be classified into three types: 'cooperative customization', 'selective composition and combination', 'transparent suggestion', and automation technologies shown in each type include 3D printing, 3D virtual clothing, robot mannequin, human automatic measurement program, AR-based fitting service, big data, and AI-based curation function. With the development of digital automation technology, the fashion industry environment is also changing from existing manufacturing-oriented to consumer-oriented, and the production process is rapidly changing with IT and artificial intelligence-based automation technology. The results of this study hope that digital customized automation technology will meet various needs of personalization and customization and present the future direction of digital fashion technology, where fashion brands will expand based on the spread of digital technology.