This paper presented a method to build a predictable smart ammunition logistics system using the 4th industrial technology for ammunition logistics, which is the core functions in the field of defense and logistics. We have analyzed the current level of ammunition logistics with various perspectives such as domestic and overseas logistics policies, technology trends, ammunition logistics characteristics, the smart logistics certification measures by Ministry of Land, Infrastructure and Transport. As a result it is considered that the current ammunition logistics needs needs improvement. To improve this, we presented a direction based on the implications derived after analyzing various ongoing programs such as wired/wireless-based automation, smart ammunition depots, and logistics innovation of the army, navy, and air force that can be applied to the ammunition logistics. In order to implement a data-based smart ammunition logistics management system that can achieve innovation and efficiency of total life cycle while meeting changes in the battlefield environment, we presented 4 objectives such as "automation and modernization of field work", "3D-based storage management & improvement of issuing at war," and "data management for prediction-oriented ammunition management". it is expected that there will be benefits such as improvement of operational continuity, guarantee of ammunition reliability, budget reduction, improvement of inefficiencies such as delay, waiting, and double work, and reduction of accidents.
With the development of the virtual community, the benefits that IT technology provides to people in fields such as healthcare, industry, communication, and culture are increasing, and the quality of life is also improving. Accordingly, there are various malicious attacks targeting the developed network environment. Firewalls and intrusion detection systems exist to detect these attacks in advance, but there is a limit to detecting malicious attacks that are evolving day by day. In order to solve this problem, intrusion detection research using machine learning is being actively conducted, but false positives and false negatives are occurring due to imbalance of the learning dataset. In this paper, a Random Oversampling method is used to solve the unbalance problem of the UNSW-NB15 dataset used for network intrusion detection. And through experiments, we compared and analyzed the accuracy, precision, recall, F1-score, training and prediction time, and hardware resource consumption of the models. Based on this study using the Random Oversampling method, we develop a more efficient network intrusion detection model study using other methods and high-performance models that can solve the unbalanced data problem.
The restoration of cultural heritage materials is an important research theme. This study improved the existing cultural heritage restoration method and attempted to establish a restoration system for cultural heritage data based on historical documents and visual materials. Recognizing the limitations of existing studies, this paper attempted to restore cultural heritage data through interdisciplinary research. In addition, 3D restoration was carried out after restoration in 2D form based on literature documents rather than existing visual sources. The object of restoration that was selected was "Jeol," which represents the power of the king of Koguryo. Koguryo's Jeol is a type of flag. Jeol appears in the mural in Anak Tomb No. 3. Rather than using only photographic materials of murals, the restoration was carried out through cross-validation of literature data and materials on archaeological art history. This is important in that the restoration carried out in this study is an accurate restoration with a historical understanding based on the literature of the relevant cultural heritage. In this study, a restoration process based on historical records was established. A 3D restoration process was performed by adding and applying visual materials after the object was first shaped based on the literature data. Restoration based on literature and visual materials was carried out based on interdisciplinary research. Therefore, this study aims to build a digital restoration system for cultural heritages and to contribute to spreading the 3D digital restoration research of cultural heritages that can be applied to various platforms.
Vibrio parahaemolyticus and V. vulnificus are known to be infected to human via fisheries products. Therefore, food safety of fisheries products is important for public health and fish industry. This paper was conducted to know how well these human isolates can survive in olive flounder (Paralichthys olivaceus). The growth of V. parahaemolyticus and V. vulnificus showed about 50~60% reduced rates at 25℃ than at 37℃ and did not show any differences according to NaCl concentration of media except the increasing in the growth of V. vulnificus in medium containing 3% NaCl. Artificial infection of 1×106 CFU/fish was carried out to confirm the sensitivity of olive flounder against V. parahaemolyticus and V. vulnificus. After 1 week from injection, no fish was dead. To evaluate nonspecific defense of olive flounder against V. parahaemolyticus and V. vulnificus, the antibacterial potency of serum and epidermal mucus were tested. The number of the vibrios exposed to serum obtained from olive flounder significantly decreased after 3 hours, and epidermal mucus showed decrease of the bacteria over than 90% until 12 hours from exposure. Phagocytosis of head kidney leucocytes of healthy olive flounder against V. parahaemolyticus and V. vulnificus showed in over 70% of leucocytes at the 2 hours. Therefore, cultured olive flounder only as vehicle for human pathogen in environmental water is well developed its antibacterial potency against human pathogens, so the viability of V. parahaemolyticus and V. vulnificus in cultured olive flounder was considered very low.
Journal of Korean Society of Disaster and Security
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v.15
no.3
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pp.57-66
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2022
According to the official letter of the Ministry of Employment and Labor (recent guidance on the status of deaths in the construction industry and thorough safety management, April 4, 2022), 17 deaths occurred in construction works worth more than 5 billion won until March 31, 2022. In terms of the size of the construction, 7 cases of 5 billion won to 12 billion won, 5 cases of 12 billion won to 80 billion won, and 5 cases of more than 80 billion won occurred. The causes of death accidents were found to be nine cases (50%), five cases (28%), two cases of collapse (11%), one case of entrapment (5%), and one case of drowning (5%). Safety facilities need to be strengthened to reduce deaths caused by falling, which accounts for most of the deaths, and if fall prevention nets, openings, and safety rails are completely installed, most falling accidents can be prevented. Therefore, this paper intends to present cases of development and use of patent technology through improvement of safety facilities in order to prevent accidents corresponding to the fall of new urban living housing sites, which are small apartment houses.
The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.
The term environmental, social and governance (ESG) was first used in the 2003 United Nations Environmental Programme Finance Initiative (UNEP FI). Among the three areas of ESG, environment refers to the impact of companies on the environment. Environmental factors address climate change policies and attempts to reduce emissions, waste and natural resource consumption. Social factors refer to the direction in which a company can improve the social impact of stakeholder includes employees, customers, communities, and governments involved in direct or indirect interaction with the organization itself and the company. Governance factors refer to stakeholders who make major decisions, the composition of the board of directors, their diversity and independence, and the internal policies that set limits and expectations for decision-making. Research related to ESG management is part of corporate social responsibility, sustainability, corporate or financial performance, and social responsibility investment. Through case studies and data-based empirical studies, it was confirmed that ESG management companies had positive results for most of the ESG related fields. Through literature analysis of domestic and international ESG history, introduction background, and management performance, this paper presents theoretical, practical implications by confirming that ESG's introduction and operation strategies are strong competitive strategies that directly affect corporate growth by creating attractive factors.
Journal of the Korea Society of Computer and Information
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v.27
no.10
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pp.43-57
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2022
In this paper, we propose a method of analyzing research papers published by researchers belonging to university departments in the field of disaster & safety for the scientometric analysis of the research status in the field of disaster safety. In order to conduct analysis research, the dataset constructed in previous studies was newly improved and utilized. In detail, for research papers of authors belonging to the disaster prevention and safety engineering type department of domestic universities, institution identification, cited journal identification of references, department type classification, disaster safety type classification, researcher major information, KSIC(Korean Standard Industrial Classification) mapping information was reflected in the experimental data. The proposed method has a difference from previous studies in the field of disaster & safety and data set based on related keyword searches. As a result of the analysis, the type and regional distribution of organizations belonging to the department of disaster prevention and safety engineering, the composition of co-authored department types, the researchers' majors, the status of disaster safety types and standard industry classification, the status of citations in academic journals, and major keywords were identified in detail. In addition, various co-occurrence networks were created and visualized for each analysis unit to identify key connections. The research results will be used to identify and recommend major organizations and information by disaster type for the establishment of an intelligent crisis warning system. In order to provide comprehensive and constant analysis information in the future, it is necessary to expand the analysis scope and automate the identification and classification process for data set construction.
This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.
Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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2010.05a
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pp.48-48
/
2010
Sound quality and NVH-issues(Noise, Vibration and Harshness) of vehicles has become very important for car manufacturers. It is interpreted as among the most relevant factors regarding perceived product quality, and is important in gaining market advantage. The general sound quality of vehicles was gradually improved over the years. However, today the development cycles in the automotive industry are constantly reduced to meet the customers' demands and to react quickly to market needs. In addition, new drive and fuel concepts, tightened ecological specifications, increase of vehicle classes and increasing diversification(increasing market for niche vehicles), etc. challenge the acoustic engineers trying to develop a pleasant, adequate, harmonious passenger cabin sound. Another aspect concerns the general pressure for reducing emission and fuel consumption, which lead to vehicle weight reductions through material changes also resulting in new noise and vibration conflicts. Furthermore, in the context of alternative powertrains and engine concepts, the new objective is to detect and implement the vehicle sound, tailored to suit the auditory expectations and needs of the target group. New questions must be answered: What are appropriate sounds for hybrid or electric vehicles? How are new vehicle sounds perceived and judged? How can customer-oriented, client-specific target sounds be determined? Which sounds are needed to fulfil the driving task, and so on? Thus, advanced methods and tools are necessary which cope with the increasing complexity of NVH-problems and conflicts and at the same time which cope with the growing expectations regarding the acoustical comfort. Moreover, it is exceedingly important to have already detailed and reliable information about NVH-issues in early design phases to guarantee high quality standards. This requires the use of sophisticated simulation techniques, which allow for the virtual construction and testing of subsystems and/or the whole car in early development stages. The virtual, testing is very important especially with respect to alternative drive concepts(hybrid cars, electric cars, hydrogen fuel cell cars), where complete new NVH-problems and challenges occur which have to be adequately managed right from the beginning. In this context, it is important to mention that the challenge is that all noise contributions from different sources lead to a harmonious, well-balanced overall sound. The optimization of single sources alone does not automatically result in an ideal overall vehicle sound. The paper highlights modern and innovative NVH measurement technologies as well as presents solutions of recent NVH tasks and challenges. Furthermore, future prospects and developments in the field of automotive acoustics are considered and discussed.
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