• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.851-858
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• 2009

Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management. This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.

• International Area Studies Review
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• v.17 no.4
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• pp.109-130
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• 2013

This study aims to identify the priority for the Gwangyang and Qingdao hinterlands which are in the same category of benchmarking crowed paths. This study has been mainly done with comparison. There is certain limitation to use competitive factors of existing research so, this study has had proper competitive factors deriving from factors analysis and studied hinterland priority of competing factors by AHP. Major results are as follows. First, the factor analysis resulted in 20 factor that were 0.6 or higher loading level of commonality and then these 20 factors were divided into groups: operating factors, service factors, cost factors, port infrastructure factors, and hinterland conditions factors with the rotated component matrix analysis. Second, according to the result of top competitive factors, the best factor was the hinterland condition(0.256). The other factors such as infrastructure, economy, accessibility, incentive, and port traffic in hinterland were highly ranked in terms of general importance using multiple weights. Third, the result of detailed properties importance about the final alternative, Gwangyang hinterland was considered more highly than Qingdao hinterland in the port information system, the support a variety of administrative services, the efficiency of the customs, and the tax benefits.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.3
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• pp.22-30
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• 2019

The demand for National Woodland Burial Grounds is expected to increase as interest in natural burial, including woodland burial, is increasing. This study was performed to provide evaluation criteria applying weighting factors to the evaluation for location selection. Through literature review, location selection evaluation factors for forest facilities, similar to forest welfare facilities, were reviewed and analyzed. As a result of the analysis, 74 preliminary evaluation criteria were selected. Based on the results, three expert groups (public servants in central and local governments and other public agencies in charge of forest welfare facility, related field researchers, and civil experts) reviewed the preliminary evaluation factors. Evaluation factors were classified into two categories, 6 sub-categories, and 22 segments. The selected evaluation factors were layered for the second preference survey. They were classified into Forest Environment and Human Environment, and those categories were further classified into three categories. Then they were further classified into segments. After segmentation, the experts who participated in the first survey checked the differences in the significance of the layered factors by utilizing AHP. The site evaluation criteria table was prepared using the evaluation criteria and the significance of each layer. In order to apply it to the candidate sites, 10 sites including the existing National Woodland Burial Grounds and 9 candidate sites considered in the previous studies were compared and analyzed including Ulju County Ulsan City, Suncheon City Jeollanam-do and Janggun-myeon Sejeong City.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.153-160
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• 2019

In this study, The purpose of this study is to analyze how the rating scale and review contents attributes of social network-based services and products affect consumer purchasing patterns. information provided by screening the main factors. These analyzes are closely and quickly integrated between individuals and businesses, and enable to analyze the transaction that the impact of changing consumers on consumption and purchasing through the usefulness and a priori estimates of reviews and ratings at this time when networks and smart technologies are involved in a wide range of consumer activities. For this study, hierarchical analysis (AHP) and delphi (Delphi) methods applied to classify the high end variables into usefulness, technicality and value, Each subvariable was grouped into three factors and analyzed for importance through evaluation weights. As a result, we could analyze the importance of durability, usefulness, technological innovation, and cost and quality of value. Therefore, this study is expected to provide supplementary and additional useful information to consumers and companies participating in economic activities in various ways by simultaneously analyzing the review score and the reliability of posting information provided by verifying the main factors.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.9-15
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• 2021

With the recent development of 5G and artificial intelligence technologies, it is interested in AIOT technology to collect, process, and analyze information in cloud edge environments. AIIoT technology is being applied to various smart environments, but research is needed to perform fast response processing through accurate analysis of collected information. In this paper, we propose a technique to minimize bandwidth and processing time by blocking the connection processing between AIOT information through fast processing and accurate analysis/forecasting of information collected in the smart environment. The proposed technique generates seeds for data indexes on AIOT devices by multipointing information collected by blockchain, and blocks them along with collection information to deliver them to the data center. At this time, we deploy Deep Neural Network (DNN) models between cloud and AIOT devices to reduce network overhead. Furthermore, server/data centers have improved the accuracy of inaccurate AIIoT information through the analysis and predicted results delivered to minimize latency. Furthermore, the proposed technique minimizes data latency by allowing it to be partitioned into a layered multilayer network because it groups it into blockchain by applying weights to AIOT information.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.1-12
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• 2009

Mobbing is going the rounds through a society rapidly and Military is not exception. Because mobbing of military is expressed not only psychology exclusion that is mobbing pattern of adult society but also sometimes psychologic and physical mobbing, is possible to join serious military discipline like a suicide and outrageous behavior. Specially military try to protect occurrence of victims that is public service through various rules and management plan but victims is going on happen. It means importance of grasp not only current mobbing victims but also potential mobbing victims better than preparation of various rules and management plans. Therefore this paper extracts seven factors and fifty attributes that are related to this matter mobbing. Next, by using Gunwoo's Social Network Service that is made for oneself and expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function(Dice's coefficient) to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and propose Mobbing Value(MV) Algorithm through this total summation. Finally through this algorithm which will contribute to efficient personnel management, we can grasp mobbing victims and tentative mobbing victims.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• 한국노년학
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• v.31 no.2
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• pp.195-209
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• 2011

This study examined the prevalence of and factors associated with unmet care need among community-dwelling middle-aged and older people in Korea. Data were from the 2006 Korean Longitudinal Study on Ageing (KLoSA), a national survey of 10,254 non-institutionalized adults aged 45 or older. Having unmet care needs was defined as needing personal assistance with activities of daily living (ADL) or instrumental activities of daily living (IADL) but having no available helper. Weighted logistic regressions were fitted to examine factors associated with unmet care needs. Overall, 7.3%, 14.5%, and 41.8% of subjects among the middle-aged, younger old, and older old, respectively, reported care needs of these, 34%, 33%,and 24% had unmet needs. Factors associated with unmet needs differed among the three groups: Education and income level were negatively associated with unmet needs among the middle-aged, but living alone was the only factor positively associated with unmet needs in both the younger and older old. The prevalence of and factors associated with unmet care needs differ by life-stage. Needed are home- and community-based care and services to meet the need for personal assistance among the elderly living alone in a community.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.671-679
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• 2023

This study aims to establish an evaluation model by quantifying the evaluation index as a follow-up study to the development of evaluation index for work-study parallel learning companies. An evaluation model was established by verifying the 2nd level components based on the quantitative factors of the learning company, the qualitative factors, the competency factors of the person in charge, and the competency factors of the learning workers, which are the highest-level components derived from previous study. For the evaluation of a learning company, an AHP survey was conducted with experts in charge of the company consulting to derive important factors that determine the quality of on-site education and training, and the evaluation model of the learning company was completed and grouped by calculating the weight between evaluation items proceeded. Work-study parallel program was promoted as a key policy to resolve the mismatch between industrial sites and school education and realize a competency-centered society, and as of December 2022, 16,664 companies participated in the training. Learning companies play a very important role as education and training supply organizations that conduct field training. It is expected that the support and consulting plan for each level of learning companies according to the evaluation model presented in this study will be used as basic data to improve the quality of work-study parallel program.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.