Is presenting guidance of information performance measurement as government PRM version 2.0 these common reference models in public sector. Government PRM is consisted of assessment classification system and standard line of sight and performance management standard form. Through this, is sorting performance element and define cause-and effect. Government PRM is supplying measurement categories at assessment classification system, but relative importance for application standard by measurement categories is not presenting. In this study, importance for government PRM's measurement categories been applying by commonness Test of information performance measurement of public sector wishes to deduce estimation and priority. Research model used Fuzzy QFD, and designed so that can reflect well PRM's development purpose. I applied Fuzzy AHP and FPP method that graft together fuzzy theory to minimize uncertainty and ambiguity in that expert opinion. Is drawn to element that "Standard model offer for information department and management" is the most important in government PRM's development purpose. "Quality of service" is showing the highest priority in customer results in measurement category. Importance for government PRM's measurement categories can offer common valuation basis in government and public institution. Hereafter if examine closely quantitative cause-and effect for structure model of measurement classification system when study government PRM more objective and efficient reference model become.
Journal of the Korea Institute of Information Security & Cryptology
/
v.13
no.6
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pp.129-140
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2003
Recently viruses and various hacking tools that threat hosts on a network becomes more intelligent and cleverer, and so the various security mechanisms against them have ken developed during last decades. To detect these network attacks, many NIPSs(Network-based Intrusion Prevention Systems) that are more functional than traditional NIDSs are developed by several companies and organizations. But, many previous NIPSS are hewn to have some weakness in protecting important hosts from network attacks because of its incorrectness and post-management aspects. The aspect of incorrectness means that many NIPSs incorrectly discriminate between normal and attack network traffic in real time. The aspect of post-management means that they generally respond to attacks after the intrusions are already performed to a large extent. Therefore, to detect network attacks in realtime and to increase the capability of analyzing packets, faster and more active responding capabilities are required for NIPS frameworks. In this paper, we propose a framework for real-time intrusion prevention. This framework consists of packet filtering component that works on netfilter in Linux kernel and traffic control component that have a capability of step-by-step control over abnormal network traffic with the CBQ mechanism.
Bae, Jang Won;Choi, Seon Han;Lee, Chun-Hee;Paik, Euihyun
Journal of the Korea Society for Simulation
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v.30
no.1
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pp.103-112
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2021
In recent years, public bicycle systems are widely spread over the world according to the development of ICT technology. Since the public bicycle systems in large cities need to secure both publicity and convenience for citizens, analysis of various their issues from introduction to operation is required. In addition, it is also necessary to prepare for various scenarios for coexistence with the PM business, which is recently in the spotlight as a last mile means and normally managed privately. This paper introduces modeling and simulation for efficient operations of public bicycle systems. In particular, the proposed method was developed in a form that can be easily used in other cities by modeling the general structure and behavior of the public bicycle system, and it was developed to facilitate modification and expansion of the future model with a component-based model configuration. This paper provides a case study of the propose method, which is the public bicycle simulation in Sejong City. The simulation results were derived by applying the data from the public bicycle system of Sejong City, and they were verified with the associated real data of Sejong City. Using the verified model, it is expected that it can be used as a tool to design and analyze various services on the public bicycle systems, which were especially suitable for Sejong City.
A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.
Recent increases in uncertainty and speed of market change are driving the adoption of new intelligent mobile office systems. Organizational information systems paradigm suggests that a right match between organizational characteristics and the use of technology is critical in producing desired results. Following such perspective this study developed the mobile office system case of Seoul Metropolitan Railway Transit(SMRT) in Korea. SMRT developed the mobile task-supporting environment that help the management of subway lines real-time without the restriction of time and space. They named the system as ST&F(SMRT Talk and Flash). They decided to develop the application systems in-houses they did not want to be overly dependent on external services in future changes and developments of the system. The new practice reduced the time for moving back and forth to 10% of their working time from previous 20%. The time used for paper works and administration chore also reduce to 10% of their working time from previous 30% on the average. The employees could use 80% of their time to concentrate on the completion of assigned task. The effects of this improvement resulted in the heightened efficiency of the use of human resources and the heightened level of railway safety. The case of SMRT shows that the mobile office system can be applied and extended to various business areas such as facility management and maintenance beyond such typical uses as sales and marketing support. Also, The result of case study will be a useful guideline on the construction and using of mobile office system.
Jeong, In Seon;Lee, Chung Geon;Cho, La Hoon;Park, Sun Yong;Kim, Seok Jun;Kim, Dae Hyun;Oh, Jae-Heun
Journal of Bio-Environment Control
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v.30
no.4
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pp.278-286
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2021
In this study, based on the Computational Fluid Dynamics (CFD) simulation model developed through previous study, inner environmenct of the modified glass greenhouse was predicted. Also, suggested the optimal shape of the greenhouse and location of the heat exchangers for heat energy management of the greenhouse using the developed model. For efficient heating energy management, the glass greenhouse was modified by changing the cross-section design and the location of the heat exchanger. The optimal cross-section design was selected based on the cross-section design standard of Republic of Korea's glass greenhouse, and the Fan Coil Unit(FCU) and the radiating pipe were re-positioned based on "Standard of greenhouse environment design" to enhance energy saving efficiency. The simulation analysis was performed to predict the inner temperature distribution and heat transfer with the modified greenhouse structure using the developed inner environment prediction model. As a result of simulation, the mean temperature and uniformity of the modified greenhouse were 0.65℃, 0.75%p higher than those of the control greenhouse, respectively. Also, the maximum deviation decreased by an average of 0.25℃. And the mean age of air was 18 sec. lower than that of the control greenhouse. It was confirmed that efficient heating energy management was possible in the modified greenhouse, when considered the temperature uniformity and the ventilation performance.
As customer management rises by important issue in electronic commerce, virtue study about CRM have proceeded much. However, because existent researches were positive researches of most statistical base, There are some limitation that does not show dynamic change with CRM flow by flowing of time, and can not forecast propriety and future result about CRM strategy. Therefore, in order to overcome existent limitation on these CRM study, this study designed dynamic model which draws factors that compose CRM strategy of on-line shopping mall, and do based on technique in system dynamics so that can analyze dynamic change between these factors. Concretely, atomized customer focuses in the on-line shopping mall and does based on Permission marketing theory, and applied CRM of different level to atomized customers and know change of customer satisfaction measurement and discomfort degree accordingly. According to the result of Simulation practice, situation that achieve CRM strategy of different level by atomize customer more increase the customer satisfaction than situation that is not so. Dynamic pattern that presented in this study is expected that can verify validity about CRM achievement strategy of different level at each CRM point of contact & how Internet enterprise including on-line shopping mall is establishing CRM strategy reasonably.
Smart factories represent production facilities where cutting-edge information and communication technologies are fused with manufacturing processes, reflecting rapid advancements and changes in the global manufacturing sector. They capitalize on the integration of robotics and automation, the Internet of Things (IoT), and the convergence of artificial intelligence technologies to maximize production efficiency in various manufacturing environments. However, the smart factory environment is prone to security threats and vulnerabilities due to various attack techniques. When security threats occur in smart factories, they can lead to financial losses, damage to corporate reputation, and even human casualties, necessitating an appropriate security response. Therefore, this paper proposes a security authentication mechanism for safe communication in the smart factory environment. The components of the proposed authentication mechanism include smart devices, an internal operation management system, an authentication system, and a cloud storage server. The smart device registration process, authentication procedure, and the detailed design of anomaly detection and update procedures were meticulously developed. And the safety of the proposed authentication mechanism was analyzed, and through performance analysis with existing authentication mechanisms, we confirmed an efficiency improvement of approximately 8%. Additionally, this paper presents directions for future research on lightweight protocols and security strategies for the application of the proposed technology, aiming to enhance security.
We studied how to achieve successful implementation of massive research and development projects requiring collaboration among industries, universities and government-supported research institute. We have set up an engineering process innovation model to be deemed most adequately for all practical purposes, relying on the theoretical studies on the merits and analysis of the effect of the information system based on Milestone Management, Work Breakdown Structures and Web, which is known to be effective for research project (schedule) management and the objective management, and implemented a real-world web-based project objective management system. After a review of various R & D Project Schedule Management methods, we found that this information system was very compatible with project objective management. This project objective management information system carries out research and development projects effectively and efficiently, getting together in cyber-space and sharing information, and has been equipped with an Early Warning Subsystem to allow for pre-analysis and timely response to potential problems arising from the course of the project. The system also contains an Executive Information System that in real time, automatically provides the management information required by managers with the rate of project progress (achievement, fulfillment and delay). Lastly, actual progress can be cross-checked through both on-line objective management on the web-based information system and design review meeting held on site, to improve the efficiency and validity of the information system. Moreover, overall effect was analyzed through questionnaires on how well the system and generated information meet requirements and on the ultimate impact of the system upon objective management and communication. The questionnaire on the system effect revealed that the information system was useful to objective management and communication, and that the quality of the system was more than acceptable as well.
Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.
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