• 한국항공운항학회지
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• 제29권3호
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• pp.84-99
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• 2021

Flight data from operational quality assurance programs plays a significant role in identifying factors as one of the key data in the development of proactive and preventive aviation safety management technologies based on data. The list of events in the flight quality assurance program recommended by the FAA differs from the list set and managed by airlines themselves and is based on the frequency of occurrence rather than the severity of individual events. In this work, we compared the list of FOQA events presented by the FAA with the list of some domestic airlines. We also investigate the severity priorities of events for airline captains and conduct research on how to improve the operation of the operational quality assurance program.

• Ocean Systems Engineering
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• 제9권3호
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• pp.261-285
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• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.

• 품질경영학회지
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• 제46권4호
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• pp.973-982
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• 2018

Purpose: The purpose of this study is to develop an effective simulation modeling formalism for autonomous control systems, such as unmanned aerial vehicles and unmanned surface vehicles. The proposed simulation modeling formalism can be used to evaluate the quality and effectiveness of autonomous control systems. Methods: The proposed simulation modeling formalism is developed by extending the classic DEVS (Discrete Event Systems Specifications) formalism. The main advantages of the classic DEVS formalism includes its rigorous formal definition as well as its support for the specification of discrete event models in a hierarchical and modular manner. Results: Although the classic DEVS formalism has been a popular modeling tool, it has limitations in describing an autonomous control system which needs to make decisions by its own. As a result, we proposed an extended DEVS formalism which enables the effective description of internal decisions according to its conditional variables. Conclusion: The extended DEVS formalism overcomes the limitations of the classic DEVS formalism, and it can be used for the effectiveness simulation of autonomous weapon systems.

• Journal of Platform Technology
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• 제9권3호
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• pp.18-23
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• 2021

초연결사회로 발전됨에 따라 정보통신의 역할이 크게 증대되고 통신재난이 발생할 경우 사회 인프라, 국가핵심기반의 서비스 중단 및 국민생활에 지대한 영향을 초래한다. 또한 정보통신분야는 산업구조가 고도화되면서 이에 대한 의존도가 급격히 증대하였기 때문에 재난으로부터 안전한 정보통신 환경 조성을 위해서는 체계적인 관리가 필요하다. 본 논문에서는 체계적인 관리를 위해서 정보통신, 금융, 보건 및 의료 등 국가핵심기반 및 다양한 분야에서 중요한 역할을 수행하고 있는 정보통신인프라에 발생할 수 있는 재난의 유형 및 위험에 대하여 분석하였다. 정보통신인프라에 재난이 발생할 경우 국가핵심기반의 서비스 중단 및 국민생활에 지대한 영향을 초래할 것으로 사료된다.

• 대한안전경영과학회지
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• 제24권4호
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• pp.149-156
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• 2022

Manufacturing process mining performs various data analyzes of performance on event logs that record production. That is, it analyzes the event log data accumulated in the information system and extracts useful information necessary for business execution. Process data analysis by process mining analyzes actual data extracted from manufacturing execution systems (MES) to enable accurate manufacturing process analysis. In order to continuously manage and improve manufacturing and manufacturing processes, there is a need to structure, monitor and analyze the processes, but there is a lack of suitable technology to use. The purpose of this research is to propose a manufacturing process analysis method using process mining and to establish a manufacturing process mining system by analyzing empirical data. In this research, the manufacturing process was analyzed by process mining technology using transaction data extracted from MES. A relationship model of the manufacturing process and equipment was derived, and various performance analyzes were performed on the derived process model from the viewpoint of work, equipment, and time. The results of this analysis are highly effective in shortening process lead times (bottleneck analysis, time analysis), improving productivity (throughput analysis), and reducing costs (equipment analysis).

• The Journal of Asian Finance, Economics and Business
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• 제9권5호
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• pp.41-51
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• 2022

The research looks into the impact of stock split announcements on stock prices and market efficiency in the Colombo Stock Exchange (CSE). This research uses a sample of 26 stock split announcements that occurred between 2020 and June 2021. According to the Global Industry Classification Standards, the stock split announcements covered in the study pertain to 26 businesses and 9 industries (GICS). To obtain the results, the usual event research methodology is used. The findings demonstrate significant average abnormal returns of 15.01 percent on the day the stock split news is made public and abnormal returns of 4.11 percent and -4.05 percent one day before and after the stock split announcement date, respectively. The study's findings revealed significant positive abnormal returns one day before the disclosure date, indicating information leakage, and significant negative abnormal returns the next day after the announcement date, indicating CSE informational efficiency. Because stock prices adapt so quickly to public information, these findings support the semi-strong form efficient market hypothesis, which states that investors cannot gain an abnormal return by trading in stocks on the day of the stock split announcement.

• 농업과학연구
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• 제48권4호
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• pp.1051-1065
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• 2021

Recent times have seen sustained increases in genetically modified (GM) crops not only for cultivation but also for the utility of food and feed worldwide. Domestically, commercial planting and the accidental or unintentional release of living modified (LM) crops into the environment are not approved. Many detection methods had been devised in an effort to realize effective management of the safety of agricultural genetic resources. In order to develop event-specific polymerase chain reaction (PCR) markers for LM crops, we analyzed the genetic information of LM crops. Genetic components introduced into crops are of key importance to provide a basis for the development of detection methods for LM crops. To this end, a total of 18 varieties from four major LM crop species (maize, canola, cotton, and soybeans) were subjected to an analysis. The genetic components included introduced genes, promoters, terminators and selection markers. Thus, if proper monitoring techniques and single or multiplex PCR strategies that rely on selection markers can be established, such an accomplishment can be regarded as a feasible solution for the safe management of staple crop resources.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.454-454
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• 2022

산불 현장 인근 주민들은 산불의 진행 상황을 파악할 수 있는 정보 부족으로 언론정보와 국가의 대피명령에만 의존하게 되어 불안감이 높아진다. 따라서 산불 발생 시 화재의 진행 상황을 알 수 없었던 불편함을 파악하고 이를 해결하고자 한다. 이는 열적외선 위성영상자료(NASA FIRMS, Fire Information for Resource Management System)의 시스템 인터페이스(API)와 기상자료를 사용하여 산불의 진행상황과 비산물의 확산 정보를 확인 할 수 있도록 하며, 최종적으로 본 연구의 결과물은 GIS기반 시각화를 포함하는 Web을 통해 제공함으로써 주민 입장의 산불상황시 대피를 위한 의사결정 참고 정보를 제공하고자 한다.

• 무역학회지
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• 제47권3호
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• pp.93-110
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• 2022

This study aims to develop online convention service quality and examine the effect of online convention service quality on re-participation intention in the same convention and other types of online conventions. Based on an extensive literature review, the study chose five main factors of online convention service quality: human service, program service, platform service, platform aesthetics, and interaction. A total of 284 data were collected from online convention participants from July 26 to August 6, 2021. For the hypotheses test, multiple regression analysis was used. As a result, interaction and program service quality had positive effects on re-participation intention in the same convention, but except for platform aesthetic, all factors positively affected re-participation intention in other types of online conventions. This study also found that online service quality factors are more helpful in predicting the intention of re-participation in other types of online conventions rather than re-participation in the same convention. Based on the results, theoretical and practical implications were discussed

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.179-191
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• 2024

With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.