• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.107-112
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• 2022

The automotive industry is motivated to provide more and more amenities to its customers. The industry is taking advantage of artificial intelligence by increasing different sensors and gadgets in vehicles machoism is forward collision warning, at the same time road accidents are also increasing which is another concern to address. So there is an urgent need to provide an A.I based system to avoid such incidents which can be address by using artificial intelligence and global positioning system. Automotive/smart vehicles protection has become a major study of research for customers, government and also automotive industry engineers In this study a two layered novel hypothetical approach is proposed which include in-time vehicle/obstacle detection with auto warning mechanism for collision detection & avoidance and later in a case of an accident manifestation GPS & video camera based alerts system and interrupt generation to nearby ambulance or rescue-services units for in-time driver rescue.

• The Optical Journal
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• s.124
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• pp.65-65
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• 2009

• The Journal of Bigdata
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• v.7 no.1
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• pp.125-137
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• 2022

The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.3
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• pp.457-473
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• 2016

This research investigates that role of space-based social capital presented in Dapsimni auto-parts shopping area considering Korean auto-parts industry and the regional characteristics of retailing industrial cluster. For this, it went through the process with in-depth interview and surveys of the owner of Dapsimni, social capital of retailing industrial cluster studied using Lin(1999)'s social capital model by separating formation, accessibility and mobilization of it. The result is that auto-part sellers in Dapsimni make themselves space-based social capital, which provides the profit from certain area: strengthening auto-parts of transaction cost and information exchange among them, creating new market for selling auto-parts. This meant that main factor sustaining the characteristic of retailing industrial cluster despite gradually decline of its role.

• Journal of Korean Society for Quality Management
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• v.39 no.1
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• pp.131-140
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• 2011

Today, due to the global recession car sales have been decreased rapidly and auto makers are competing continuously to expand their market share. Automakers are struggling in order to secure competitive cost and quality through continuous cost reduction and quality innovation activities to win in the competition. In this situation, auto parts makers are trying to reinforce price competitiveness by reducing COPQ (Cost Of Poor Quality) in the mass production stages by securing the quality of components in advance from the design stage through DFSS (Design For Six Sigma) activities which is 6 sigma approach in the R&D field. However, auto parts makers have been undergone various confusion, feeling difficulties to get interrelationship among various activities. Thus, this study is going to suggest approach method for much more effective R&D activities by securing interrelationship between ISO/TS 16949 system established in the auto parts industry and DFSS activities.

• Journal of the Korea Society of Computer and Information
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• v.23 no.5
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• pp.55-63
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• 2018

In this paper, we designed a system that integrate and organize customer management programs and databases, which are performed independently of each other. And we designed the system so that it can be used for future marketing by implementing the system to share and efficiently utilize mutual independent maintenance information. From the CRM perspective, a comprehensive information system ghat manages every information on both new cars and second hand cares grom their purchase, to parts, to insurance, and to scraping needs to be established. The following should be applied in the establishment of the IAMS. Auto makers or auto maintenance services providers exclusive management of information on customers and their car maintenance services is aggravating the customer's inconvenience and complaints. In addition, the service provider has difficulty providing consistent maintenance services because it has little information about previous auto maintenance services the customer received. Besides, the customers who have no information on costs of parts and labor tend to hesitate to trust the costs of maintenance services. This study to provide customers with systematic maintenance service and causing them some inconvenience. Therefore, in order to maintain existing customers, auto maintenance service providers should provide services the customers wanted on the basis of accurate information about them.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.587-596
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• 2024

Cyber Attack and Cyber Threat are getting confused and evolved. Therefore, using AI(Artificial Intelligence), which is the most important technology in Fourth Industry Revolution, to build a Cyber Threat Detection System is getting important. Especially, Government's SOC(Security Operation Center) is highly interested in using AI to build SOAR(Security Orchestration, Automation and Response) Solution to predict and build CTI(Cyber Threat Intelligence). In this thesis, We introduce the Cyber Threat Detection System by analyzing Network Traffic and Web Application Firewall(WAF) Log data. Additionally, we apply the well-known TF-IDF(Term Frequency-Inverse Document Frequency) method and AutoML technology to classify Web traffic attack type.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.151-160
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• 2024

Artificial Neural Networks that enabled Artificial Intelligence are being used in many fields. However, the application to mechanical structures has several problems and research is incomplete. One of the problems is that it is difficult to secure a large amount of data necessary for learning Artificial Neural Networks. In particular, it is important to detect and recognize external forces and forces for safety working and accident prevention of mechanical structures. This study examined the possibility by applying the Current Neural Network of Artificial Neural Networks to detect and recognize the load on the machine. Tens of thousands of data are required for general learning of Recurrent Neural Networks, and to secure large amounts of data, this paper derives load data from ANSYS structural analysis results and applies a stacked auto-encoder technique to secure the amount of data that can be learned. The usefulness of Stacked Auto-Encoder data was examined by comparing Stacked Auto-Encoder data and ANSYS data. In addition, in order to improve the accuracy of detection and recognition of load data with a Recurrent Neural Network, the optimal conditions are proposed by investigating the effects of related functions.

• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

• Journal of the Korea Safety Management & Science
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• v.24 no.2
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• pp.127-134
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• 2022

Production management in the automobile parts industry is carried out according to the production plan of the customer, so it is important to prevent shortages in product supply. As the product composition became increasingly complex, the MES System was built for the purpose of efficient production plan management and inventory management, but its utilization is low. This study analyzed the problems of the MES system and sought to improve it. Through previous studies, it was confirmed that the inventory management of the pull approach that actually occurred in the warehouse is more suitable than the push approach based on the forecast of the warehouse for the volatility, complexity, and uncertainty of orders in the auto parts industry. To realize this, we tried distributed MRP by using the ADO function of VBA to link the standard information of the MES system with Excel and change the structure of the BOM table. Through this, it can help increase the accuracy of production planning and realize efficient inventory management, thereby increasing the utilization of the MES system in the auto parts industry and enhancing the competitiveness of the company.