• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.226-239
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• 2020

The study seeks to present ways to form and express political opinions while monitoring, regulating and critically accepting the production and distribution of false information and platforms, which are spread channels, through the participation of citizens. First, it logically identified the unfairness of legal regulations on false information. In other words, it is often practically impossible to judge whether false information is false or not, and even false information can sometimes fall within the category of freedom of expression protection. It also revealed that voluntary regulation by platform operators was limited. As an alternative, it was theoretically clear whether civil society should participate in the maintenance and development of democratic public debate sites and create social discourse. The specific method is to find and classify false information and share it with citizens to raise awareness. Second, it forms an autonomous cooperative system with platform operators and others. Third, develop critical media capacity of citizens. Fourth, it responds to producers and platform operators of false information while engaging in community activities as a direct practitioner.

• Smart Media Journal
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• v.7 no.1
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• pp.37-44
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• 2018

Utilizing sequence control and numerical computing, embedded devices are used in a variety of automated systems, including those at industrial sites, in accordance with their control program. Since embedded devices are used as a control system in corporate industrial complexes, nuclear power plants and public transport infrastructure nowadays, deliberate attacks on them can cause significant economic and social damages. Most attacks aimed at embedded devices are data-coded, code-modulated, and control-programmed. The control programs for industry-automated embedded devices are designed to represent circuit structures, unlike common programming languages, and most industrial automation control programs are designed with a graphical language, LAD, which is difficult to process static analysis. Because of these characteristics, the vulnerability analysis and security related studies for industry automation control programs have only progressed up to the formal verification, real-time monitoring levels. Furthermore, the static analysis of industrial automation control programs, which can detect vulnerabilities in advance and prepare for attacks, stays poorly researched. Therefore, this study suggests a method to present a discussion on an industry automation control program designed to represent the circuit structure to increase the efficiency of static analysis of embedded industrial automation programs. It also proposes a medium term translation technology exploiting LLVM IR to comprehensively analyze the industrial automation control programs of various manufacturers. By using LLVM IR, it is possible to perform integrated analysis on dynamic analysis. In this study, a prototype program that converts to a logical expression type of medium language was developed with regards to the S company's control program in order to verify our method.

• Journal of the Ergonomics Society of Korea
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• v.35 no.4
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• pp.205-223
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• 2016

Objective:This study introduced the status of studies and the projects related with agricultural accident prevention carried out by the Rural Development Administration. This study was conducted to promote Korean farmers' agricultural safety activation by analyzing study trends on farmers' agricultural work safety. Background: Agriculture is one of the dangerous industries, and the agricultural accident rate is on the rise, due to recent serious aging and increased female work force. Such a phenomenon emerges as a serious problem from the social perspective, and therefore measures for farmers' healthy and safe agricultural activities and accident prevention are required. Method: This study conducted literature review related with domestic and international agricultural safety and health. This study also examined the hazard factors of agricultural labor and injuries, agricultural safety and health system and policy, support and education for farmers' safety practice, and the status of convenience tools and protection equipment, based on major study activities performed by the Rural Development Administration for recent four to five years. Results: Through the study results, the status of Korea's agricultural safety system, compensation support policy, safety education of farmers for actual practice, and diverse channels including media were confirmed. This study also presented the R&D implementation status on convenience equipment and protective gear to prevent agricultural diseases and safety accidents. Conclusion: This study found out that continuous monitoring and efforts are required to prevent accidents for the Korea's agricultural labor environment and agricultural safety, and that social bond of sympathy formation is demanded through effect analysis on the implemented projects including education and support projects. Furthermore, it can be understood that agricultural accident prevention should be carried out through shift from current government-led top down approach to bottom-up approach from itself. Application: The results of this study can be utilized as useful data for farmers' safety and health.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.31-39
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• 2014

Seasonal influenza epidemics cause 3 to 5 millions severe illness and 250,000 to 500,000 deaths worldwide each year. To prepare better controls on severe influenza epidemics, many studies have been proposed to achieve near real-time surveillance of the spread of influenza. Korea CDC publishes clinical data of influenza epidemics on a weekly basis typically with a 1-2-week reporting lag. To provide faster detection of epidemics, recently approaches using unofficial data such as news reports, social media, and search queries are suggested. Collection of such data is cheap in cost and is realized in near real-time. This research aims to develop regression models for early detecting the outbreak of the seasonal influenza epidemics in Korea with keyword query information provided from the Naver (Korean representative portal site) trend services for PC and mobile device. We selected 20 key words likely to have strong correlations with influenza-like illness (ILI) based on literature review and proposed a logistic regression model and a multiple regression model to predict the outbreak of ILI. With respect of model fitness, the multiple regression model shows better results than logistic regression model. Also we find that a mobile-based regression model is better than PC-based regression model in estimating ILI percentages.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.