Daehan san'eob gonghag hoeji最新文献

{"title":"A Shoreline Change Prediction Technique Combining Physics and Data-driven Model","authors":"Yongmin Kim, Hyunsoo Yoon, Su-Hong Min, Changbin Lim, Jung-Lyul Lee, Jihoon Kang","doi":"10.7232/jkiie.2023.49.5.433","DOIUrl":"https://doi.org/10.7232/jkiie.2023.49.5.433","url":null,"abstract":"In modern engineering, Artificial Intelligence (AI) and several data analysis techniques are frequently used and developed in various fields. These quantitative approaches, however, are somewhat focused on the assumption that sensor data properly expresses the physical phenomenon. Besides they still have limitations such as nonlinearity, different environmental condition and complexity of response. Another issue is that the data can be obtained through experiments, but due to the constraints of time and cost of experiments, obtaining a large amount of data that may be able to fully explain diverse natural occurrences is impossible. To deal with the aforementioned issues, we propose shoreline prediction techniques using a combination of physics and data analysis models. The physical coefficients of the existing differential equation are optimized through a genetic algorithm and approximate solution is obtained through the Euler method. This was used as prior knowledge and combined with a data analysis model to predict the shoreline position. As a result of the experiment, when there was enough training data, the performance of data analysis model was better than that of the proposed method, but the performance of the proposed method was better in situations where the training data was insufficient.","PeriodicalId":488346,"journal":{"name":"Daehan san'eob gonghag hoeji","volume":"41 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the Effectiveness of the Multiple Short Range High Speed Target According to the Engagement Distance","authors":"Sejun Lee, Ilseob Shin, Changhyun Han, Beomcheol Na","doi":"10.7232/jkiie.2023.49.5.448","DOIUrl":"https://doi.org/10.7232/jkiie.2023.49.5.448","url":null,"abstract":"In order to defend facilities from the threat of multiple short range high speed target of North Korea, the counter long-range artillery intercept system(CLRAIS) is in progress. It is similar with air defense operations, however there is a characteristic that three thousand rounds per minuter are concentrated. To provide protection against low-altitude and multi target, threat and the weapon must be decided quickly and accurately with the shortest time. In this paper, we propose a threat assessment and weapon-target assignment in multi-target and multi-weapon environments. According to the engagement distance, we study the effectiveness of the engagement. In order to figure out the factor, we define the variables to be used in the simulation. according to engagement scenario, the effectiveness analysis is verified the monte-carlo simulation. The results of this study, It can be used to predict and analyze for intercept probability.","PeriodicalId":488346,"journal":{"name":"Daehan san'eob gonghag hoeji","volume":"248 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Study on the Corporate ESG Impacts on the Company’s Internal Management Performance and ESG Management Types by Industry","authors":"Young-Ju Cho, Jun-Sung Park, Joon-Woo Yoo, Chang-Geun Lee, Hee-Jun Park","doi":"10.7232/jkiie.2023.49.5.417","DOIUrl":"https://doi.org/10.7232/jkiie.2023.49.5.417","url":null,"abstract":"The ESG (Environmental, Social, and Governance) management of companies has become essential in the innovative management field of business as the interest in sustainable growth and value-centric investment increases worldwide. Using Refinitiv ESG data, this paper identifies ESG activities that significantly impact corporate performance and analyzes their effects on customers, shareholders, and employee performance by ESG factors. Furthermore, this paper analyzes the current status of ESG management by industry through K-means clustering to provide implications to policymakers and companies for future indicators and ESG practice development. Thus, this paper identified the major variables from the Refinitiv ESG evaluation framework through exploratory factor analysis, conducts confirmatory factor analysis to confirm the model’s fitness, and analyzes the effects of a company’s ESG management activities on performance using structural equation modeling. Through this study, this paper examines that a company’s ESG activities have a positive impact on customer loyalty; however, efforts to improve the environment can have a negative impact on employee satisfaction. Similarly, efforts to improve the environment and governance can have a negative impact on shareholder satisfaction. This implies that there is a need to alleviate the burden derived from environmental and governmental practices and enhance awareness of ESG practices’ necessity to those stakeholders. Additionally, in industry-specific analysis, the manufacturing and infrastructure industries were found to have relatively superior ESG performance, while the absence of physical assets in the banking and some service industries could lead to low ESG performance. As awareness of the global climate crisis and social recognition of sustainable management continues to grow, ESG management and evaluation are expected to become more critical. Therefore, considering the industrial characteristics of companies, it is expected that different ESG evaluation and support methods will be necessary.","PeriodicalId":488346,"journal":{"name":"Daehan san'eob gonghag hoeji","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovering New Technology Opportunities from Convergence Analysis of Utility Patents and Design Patents","authors":"Ki-Sik Song, Jae-Hyung Ahn, Sang-Young Park, Sung-Joo Lee, Jae-Hoon Kim","doi":"10.7232/jkiie.2023.49.5.395","DOIUrl":"https://doi.org/10.7232/jkiie.2023.49.5.395","url":null,"abstract":"Design patents contain as much unique information as utility patent data. The text dat+a of design patents is simpler compared to that of utility patents. The importance of design patent analysis is emerging to consider legal rights for designs. Despite the importance of design patents as a source of technological information, previous studies have rarely researched utility patents and design patents simultaneously. In addition, research using design patents is limited to macroscopic analysis, which results in a lack of systematic research to identify specific product development opportunities. To fill this research gap, this study proposes an approach for identifying new opportunities in product development through the convergence analysis of utility patents and design patents. This approach was applied to a case study involving a future mobility cockpit. In this approach, we initially gather data using the same search formula for both utility patents and design patents. Then, Utility patent-tree and Design patent-tree are derived based on text-mining and clustering analysis. Finally, by analyzing the similarity between the Utility patent-tree and the Design patent-tree, we present technology strategies for areas with high similarities and strategies for areas with low similarities. The results of this study will contribute to the discovery of opportunities in product technology, considering both technical and design concepts.","PeriodicalId":488346,"journal":{"name":"Daehan san'eob gonghag hoeji","volume":"225 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anomaly Detection and Root Cause Analysis of Ship Main Engines: Explainable Artificial Intelligence-Based Methodology Considering Internal Sensors and External Environmental Factors","authors":"Mingyu Park, Hyunjoo Kim, Sangbong Lee, Jihwan Lee","doi":"10.7232/jkiie.2023.49.5.379","DOIUrl":"https://doi.org/10.7232/jkiie.2023.49.5.379","url":null,"abstract":"The main engine of a ship plays a crucial role in providing propulsion. In recent times, there has been growing interest in a data-driven monitoring approach that utilizes sensor data to complement the preventive maintenance-centered maintenance strategy. Previous studies have proposed methodologies that apply anomaly detection algorithms to the sensor data within the main engine. However, these methodologies have limitations as they only focus on analyzing internal sensor data and fail to consider external factors such as operating conditions, marine environment, and weather. Additionally, the use of black-box approaches makes it challenging to determine the specific factors causing anomalies. To address these limitations, this study introduces a method that employs Explainable Artificial Intelligence (XAI) techniques to identify the causes of anomalies in ship main engines. The proposed method involves calculating anomaly scores using Variational AutoEncoder on collected sensor data and training a separate model to predict anomaly scores by considering external factors like operating conditions and weather. Furthermore, the SHAP (Shapley Additive Explanations) technique is utilized to quantify the contributions of external factors to the anomaly scores. This enables the analysis of individual data features and facilitates both local and global analysis for identifying the causes of anomalies and diagnosing faults. The proposed methodology was validated through a case study using data collected from a container ship over an 18-month period, demonstrating its effectiveness in identifying the causes of anomalies in the ship’s main engine.","PeriodicalId":488346,"journal":{"name":"Daehan san'eob gonghag hoeji","volume":"37 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting the Level and Types of North Korea’s Provocations with Text Mining","authors":"Sunkyo Cha, Bongkyoo Yoon","doi":"10.7232/jkiie.2023.49.5.441","DOIUrl":"https://doi.org/10.7232/jkiie.2023.49.5.441","url":null,"abstract":"Research into the feasibility of predicting specific events using Text Mining techniques has been actively pursued in conjunction with the advancement of Machine Learning. Consequently, the potential for predicting North Korea’s provocations utilizing Text Mining methods has emerged. However, the field lags behind other domains due to challenges in acquiring high-quality training data and the complexity associated with event classification. This study addresses these limitations by leveraging a Pre-trained BERT model to establish a comprehensive classification framework for North Korea’s provocative behavior, moving beyond binary classifications (provocation or peace) used in previous research. Original data from the Korean Central News Agency (KCNA) and domestic media sources were gathered and analyzed as training data. Notably, the findings demonstrated that employing original data from the KCNA increased prediction accuracy compared to utilizing data from domestic media. This study offers a way to enhance the informational value of North Korea’s provocations through scientific predictions, ultimately bolstering the reliability of qualitative expert judgments.","PeriodicalId":488346,"journal":{"name":"Daehan san'eob gonghag hoeji","volume":"98 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Framework for Developing Public Data-map Using Similarity between Meta-data and Graph: The Case of Public Data from Seoul","authors":"Junhyuk Choi, Minji Kwon, Junchul Kim, Junegak Joung","doi":"10.7232/jkiie.2023.49.5.406","DOIUrl":"https://doi.org/10.7232/jkiie.2023.49.5.406","url":null,"abstract":"The South Korean government is actively working to make data available to the public. However, as data from different departments is integrated and made accessible, efficient search algorithms for big data have become a major issue. This paper proposes a framework for developing a public data-map that uses metadata similarity and graph concepts to suggest ways to visualize and search related data. Additionally, to improve the performance of measuring similarity, we develop the domain-specific data pre-processing for public data and incorporate the step into the framework. To validate the framework, an empirical study was conducted using the case of the Seoul Metropolitan Government’s Big Data Division. The results show that this framework can significantly improve the usability of public data and facilitate its open access.","PeriodicalId":488346,"journal":{"name":"Daehan san'eob gonghag hoeji","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}