• Resources Recycling
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• v.31 no.4
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• pp.3-11
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• 2022

Owing to the increasing demand for electric vehicles (EVs), appropriate management of their waste batteries is required urgently for scrapped vehicles or for addressing battery aging. With respect to technological developments, data-driven diagnosis of waste EV batteries and management technologies have drawn increasing attention. Moreover, robot-based automatic dismantling technologies, which are seemingly interesting, require industrial verifications and linkages with future battery-related database systems. Among these, it is critical to develop and disseminate various advanced battery diagnosis and assessment techniques to improve the efficiency and safety/environment of the recirculation of waste batteries. Incorporation of lithium-related chemical substances in the public pollutant release and transfer register (PRTR) database as well as in-depth risk assessment of gas emissions in waste EV battery combustion and their relevant fire safety are some of the necessary steps. Further research and development thus are needed for optimizing the lifecycle management of waste batteries from various aspects related to data-based diagnosis/classification/disassembly processes as well as reuse/recycling and final disposal. The idea here is that the data should contribute to clean design and manufacturing to reduce the environmental burden and facilitate reuse/recycling in future production of EV batteries. Such optimization should also consider the future technological and market trends.

• Smart Media Journal
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• v.11 no.3
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• pp.54-61
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• 2022

With the increase in the types of information systems managed by public institutions and companies, a security certification system is being implemented in Korea to quickly respond to vulnerabilities that may arise due to insufficient security checks. The korea security evaluation system, such as ISMS-P, performs a systematic security evaluation for each category by dividing the categories for technical inspection items. NIST in the United States has developed SCAP that can create security checklists and automate vulnerability checks, and the security checklists used for SCAP can be written in OVAL. Each manufacturer prepares a security check list and shares it through the SCAP community, but it's difficult to use it in Korea because it is not categorized according to the korea security evaluation system. Therefore, in this paper, we present a mechanism to categorize the OVAL definition, which is an inspection item written in OVAL, to apply SCAP to the korea security evaluation system. It was shown that 189 out of 230 items of the Red Hat 8 STIG file could be applied to the korea security evaluation system, and the statistics of the categorized Redhat definition file could be analyzed to confirm the trend of system vulnerabilities by category.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.1-18
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• 2021

While content word-based frequency analysis has obvious limitations to intentional deception or irony, KLIWC has evolved into functional word analysis and KrKwic has evolved as a way to visualize co-occurrence frequencies. However, after more than 10 years of development, several issues still need improvement. Therefore, we tried to develop a new psychological language analysis program by analyzing KLIWC and KrKwic. First, the two programs were analyzed. In particular, the morpheme classification of KLIWC and the Korean morpheme analyzer was compared to enhance the functional word analysis function, and the psychological dictionary were analyzed to strengthen the psychological analysis. As a result of the analysis, the Hannanum part-of-speech analyzer was the most subdivided, but KLIWC for personal pronouns and KKMA for endings and endings were more subdivided, suggesting the integrated use of multiple part-of-speech analyzers to strengthen functional word analysis. Second, the research trends of studies that analyzed texts with these programs were analyzed. As a result of the analysis, the two programs were used in various academic fields, including the field of Interdisciplinary Studies. In particular, KrKwic was used a lot for the analysis of papers and reports, and KLIWC was used a lot for the comparative study of the writer's thoughts, emotions, and personality. Based on these results, the necessity and direction of development of a new psychological language analysis program were suggested.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.5
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• pp.144-155
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• 2022

The Korea Coast Guard evaluates the risk of major coastal activity places to prevent coastal accidents, and patrols and manages them based on that, but it is not responding properly to the continuously increasing number of coastal accidents. The reason for this is that, despite the gradual expansion of coastal activity places, there is a lack of manpower to manage and supervise them, resulting in blind spots in coastal accident safety management. Therefore, in order to solve this problem, it is necessary to prepare more efficient and effective measures that check and supplement the current coastal safety management system. Coastal accidents show different characteristics of accident causes and places due to differences in the activity characteristics of users according to time. As a result of analyzing coastal accident data (2017~2021), the frequency of daytime accidents is high in the case of sea rock, beach, and offshore, where family leisure activities are frequent. In the case of wharf, tidal flat and bridge, where accidents due to drinking, disorientation, and suicide mainly occur, the frequency of accidents at night is high. In addition, there were more accidents on weekends when the number of users increased compared to weekdays. This trend indicates that the user's temporal activity characteristics must be reflected in the risk assessment of coastal activity places. Therefore, in this study, based on the case of coastal accidents, the characteristics of accidents at coastal activity places according to time were identified, and the criteria were presented for risk evaluation by grading them. It is expected that it will be possible to lay the foundation for reducing coastal accidents by efficiently managing and supervising coastal activity places over time using the presented evaluation criteria.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.3
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• pp.268-278
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• 2022

Objectives: This study aimed to establish a control group based on the big data from National Health Insurance Service. We also presented presented the number of incidences for each cancer, and analyzed the cancer incidence rate among Korean workers. Methods: The cohort definition was separated by 'baseline cohort', 'dynamic cohort', and 'fixed- industry cohort' according to the definition. Cancer incidence was calculated based on the Korean Standard Classification of Disease code. Incidence rate was calculated among the group of all workers and public officials. Based on the study subjects and each cohort definition, the number of observations, incidences, and the incidence rate according to sex and age groups was calculated. The incidence rate was estimated based on the incidence per 100,000 person-year, and 95% confidence intervals calculated according to the Poisson distribution. Results: The result shows that the number of cancer cases in the all-worker group decreases after the age of 55, but the incidence rate tends to increase, which is attributed to the retirement of workers over 55 years old. Despite the specific characteristics of the workers, the trend and figures of cancer incidence revealed in this study are similar to those reported in previous studies of the overall South Korean population. When comparing the incidence rates of all workers and the control group of public officials, the incidence rate of public officials is generally observed to be higher in the age group under the age of 55. On the other hand, for workers aged 60 or older, the incidence rates were 1,065.4 per 100,000 person-year for all workers and 1,023.7 per 100,000 person-year for civil servants. Conclusions: This study analyzed through health insurance data including all workers in Korea, and analyzed the incidence of cancer of workers by sex and age. In addition, further in-depth researches are needed to determine the incidence of cancer by industry.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.337-348
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• 2022

In the light of the researchers' recognition towards the designs of tellers and listeners in storytelling classes, the purpose of this study was to analyze a research trend in Korean Education in which storytelling had been utilized and to suggest a proper direction in the related education and research. The most essential thing in the conceptualization towards storytelling was thought to be 'intercommunication.' Also, it is considered as the most basic conceptual factor who we would regard as 'tellers' and 'listeners' in order to plan and construct Korean language classes. Based on this understanding, this study searched and analyzed total 28 research results, which had been published from 2008 to 2021(May), through an academic searching site, Riss with the keyword "Korean Education Storytelling." The analysis exhibited that the formation of Korean classes utilizing storytelling originated from three kinds of researchers' previous conceptualization towards storytelling.: Writers' storytelling, teachers' storytelling, and learners' storytelling. Among them, the most large portion was devoted to 'leaners' storytelling'; its subcategories were learners' retelling, interpretative storytelling, learners' negotiated storytelling and learners' creative storytelling. This study, according to the classification on conceptualization of storytelling above, categorized the results and discussed the characteristics of each subcategory and their educational implications respectively.

• The Journal of Bigdata
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• v.7 no.2
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• pp.153-172
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• 2022

Online shopping has transformed and rapidly grown the entire market at the forefront of wholesale and retail services as an effective solution to issues such as digital transformation and social distancing policy (COVID-19 pandemic). Small business owners, who form the majority at the center of the online shopping industry, are constantly collecting policy changes and market trend information to overcome these problems and use them for marketing and other sales activities in order to overcome these problems and continue to grow. Objective and refined information that is more closely related to the business is also needed. Therefore, in this paper, through the collection and analysis of big data information, which is the core technology of digital transformation, key variables are set in product classification, sales trends, consumer preferences, and review information of online shopping malls, and a method of using them for competitor comparison analysis and business sustainability evaluation has been prepared and we would like to propose it as a service. If small and medium-sized businesses can benchmark competitors or excellent businesses based on big data and identify market trends and consumer tendencies, they will clearly recognize their level and position in business and voluntarily strive to secure higher competitiveness. In addition, if the sustainable growth of the online shopping mall operator can be confirmed as an indicator, more efficient policy establishment and risk management can be expected because it has an improved measurement method.

• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.127-134
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• 2024

The article highlights the problems of the digitalization of the educational process, which affect the pedagogical cluster and are of a psychological nature. The authors investigate the transformational changes in education in general and the individual beliefs of each subject of the educational process, caused by both the change in the format of learning (distance, mixed), and the use of new technologies (digital, communication). The purpose of the article is to identify the strategic trend of the educational process, which is a synergistic combination of pedagogical methodology and psychological practice and avoiding dialectical opposition of these components of the educational space. At the same time, it should be noted that the introduction of digital technologies in the educational process allows for short-term difficulties, which is a usual phenomenon for innovations in the educational sphere. Consequently, there is a need to differentiate the fundamental problems and temporary shortcomings that are inherent in the new format of learning (pedagogical features). Based on the awareness of this classification, it is necessary to develop psychological techniques that will prevent a negative reaction to the new models of learning and contribute to a painless moral and spiritual adaptation to the realities of the present (psychological characteristics). The methods used in the study are divided into two main groups: general-scientific, which investigates the pedagogical component (synergetic, analysis, structural and typological methods), and general-scientific, which are characterized by psychological direction (dialectics, observation, and comparative analysis). With the help of methods disclosed psychological and pedagogical features of the process of digitalization of education in a mixed learning environment. The result of the study is to develop and carry out methodological constants that will contribute to the synergy for the new pedagogical components (digital technology) and the psychological disposition to their proper use (awareness of the effectiveness of new technologies). So, the digitalization of education has demonstrated its relevance and effectiveness in the pedagogical dimension in the organization of blended and distance learning under the constraints of the COVID-19 pandemic. The task of the psychological cluster is to substantiate the positive aspects of the digitalization of the educational process.

• Information Systems Review
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• v.22 no.4
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• pp.75-92
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• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.