• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.544-547
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• 2004

Current increasingly information systems log historic information in a systematic way. Not only workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called 'event log'. Unfortunately, the information in these event logs is rarely used to analyze the underlying processes. Process mining aims at improving this problem by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs. This paper focuses on the mining social networks. This is possible because event logs typically record information about the users executing the activities recorded in the log. To do this we combine concepts from workflow management and social network analysis. This paper introduces the approach and presents a tool to mine social networks from event logs.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.229-238
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• 2022

Due to digitization, data has become a tsunami in almost every data-driven business sector. The information wave has been greatly boosted by man-to-machine (M2M) digital data management. An explosion in the use of ICT for farm management has pushed technical solutions into rural areas and benefited farmers and customers alike. This study discusses the benefits and possible pitfalls of using information and communication technology (ICT) in conventional farming. Information technology (IT), the Internet of Things (IoT), and robotics are discussed, along with the roles of Machine learning (ML), Artificial intelligence (AI), and sensors in farming. Drones are also being studied for crop surveillance and yield optimization management. Global and state-of-the-art Internet of Things (IoT) agricultural platforms are emphasized when relevant. This article analyse the most current publications pertaining to precision agriculture using ML and AI techniques. This study further details about current and future developments in AI and identify existing and prospective research concerns in AI for agriculture based on this thorough extensive literature evaluation.

• Journal of Construction Engineering and Project Management
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• v.3 no.2
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• pp.13-20
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• 2013

Construction industry has become a larger and highly competitive industry. A successful construction project cannot be achieved only by efficient and fast construction techniques but also reasonable material cost and adequate transferring time of materials to installation. The steel industry in East Asia has become the mainstream in overall steel industries in over the world during the middle of the 21st century. China, Japan and Korea has been the main exportation countries. However, even though the international economic failure, China has increased the exportation amount and became an only exporting country which must be considered a serious problem regarding competitiveness in the international steel exportation industry. Thus, this study analyses the factors affecting the supply and demand amount of reinforced bars in the domestic field and moreover suggesting a unit cost prediction model using the System Dynamics simulation methodology, one of powerful prediction tools using cause-effect relationships. It is expected that this study contributes to the domestic steel industry growth in competitiveness in the international industry. In addition, the methodology used in this paper presents the frameworks for appropriate tools for market trend analysis and prediction of other markets.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.682-684
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• 2003

With the explosive rapid expansion of computer using during the past few years, security has become a crucial issue for modem computer systems. Today, there are many intrusion detection systems (IDS) on the Internet. A variety of intrusion detection techniques and tools exist in the computer security community such as enterprise security management system (ESM) and system integrity checking tools. However, there is a potential problem involved with intrusion detection systems that are installed locally on the machines to be monitored. If the system being monitored is compromised, it is quite likely that the intruder will after the system logs and the intrusion logs while the intrusion remains undetected. In this project KIT-I, we adopt remote logging server (RLS) mechanism, which is used to backup the log files to the server. Taking into account security, we make use of the function of SSL of Java and certificate authority (CA) based key management. Furthermore, Support Vector Machine (SVM) is applied in our project to detect the intrusion activities.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.209-214
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• 2024

This is an extended research paper focusing on the applications of Machine Learing and Artificial Intelligence in virtual learning environment. The world is moving at a fast pace having the application of Machine Learning (ML) and Artificial Intelligence (AI) in all the major disciplines and the educational sector is also not untouched by its impact especially in an online learning environment. This paper attempts to elaborate on the benefits of ML and AI in E-Learning (EL) in general and explain how King Khalid University (KKU) EL Deanship is making the best of ML and AI in its practices. Also, researchers have focused on the future of ML and AI in any academic program. This research is descriptive in nature; results are based on qualitative analysis done through tools and techniques of EL applied in KKU as an example but the same modus operandi can be implemented by any institution in its EL platform. KKU is using Learning Management Services (LMS) for providing online learning practices and Blackboard (BB) for sharing online learning resources, therefore these tools are considered by the researchers for explaining the results of ML and AI.

• Journal of Korean Society for Quality Management
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• v.33 no.3
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• pp.19-30
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• 2005

Recently many organization to become survival in changing marketplace, they must commit to implementing tools, systems, and quality management techniques. In this paper we develop process method of Team's problem-solving to reduce in failure costs. This paper suggest the step process how to measure quality cost reasonably that works in all types organizations. Or what is continuous improvement? Continuous improvement can be described as the continuous reduction of variation. Variation has many sources(machines, methods, materials, measurements, people, and environments) and cause(special & common in organization). As quality cost are not the answer to every organization financial, or quality-related problem, it's real results are designing & implementing quality cost system might be the answer.

• Journal of Engineering Education Research
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• v.21 no.6
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• pp.90-98
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• 2018

This paper proposes a framework of engineering education for product development processes based on product data management (PDM) software and 3D printing. The PDM software supports the product development process-oriented educational coursework, collaborative team projects and project-based learning environment. The 3D printing supports the prototyping step in the product development process and helps participants consider physical realization of their designs during the product design and development phases. The framework was implemented in an introductory course for engineering students to product design and development, and author found that it is important to support rich communication among participants including lecturers, teaching assistants and students to enhance the quality of education and to overcome the burden of learning various computer-aided tools and 3D printing techniques needed for the framework.

• Nuclear Engineering and Technology
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• v.36 no.4
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• pp.295-303
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• 2004

Software inspection is widely believed to be an effective method for software verification and validation (V&V). However, software inspection is labor-intensive and, since it uses little technology, software inspection is viewed upon as unsuitable for a more technology-oriented development environment. Nevertheless, software inspection is gaining in popularity. KAIST Nuclear I&C and Information Engineering Laboratory (NICIEL) has developed software management and inspection support tools, collectively named "SIS-RT. "SIS-RT is designed to partially automate the software inspection processes. SIS-RT supports the analyses of traceability between a given set of specification documents. To make SIS-RT compatible for documents written in Korean, certain techniques in natural language processing have been studied [9]. Among the techniques considered, case grammar is most suitable for analyses of the Korean language [3]. In this paper, we propose a methodology that uses a case grammar approach to analyze the traceability between documents written in Korean. A discussion regarding some examples of such an analysis will follow.

• Journal of Distribution Science
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• v.8 no.1
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• pp.13-19
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• 2010

Segmentation, targeting, and positioning are marketing tools used by a company to gain competitive advantage in the market. For an accurate segmentation, various statistics models or datamining techniques are used. Especially, datamining techniques are introduced in the beginning of the 1980s and solved several marketing problems effectively. In this paper, we research about datamining technique for segmentation and analyze customer's transaction data of Department Store using Decision Tree Analysis, one of the dataming technique. After that, we discuss effects and advantages of segmentation using Decision Tree.

• International Journal of Industrial Entomology and Biomaterials
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• v.47 no.1
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• pp.1-11
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• 2023

The Indian golden muga silkworm, Antheraea assamensis Helfer is an economically important wild silkworm endemic to Northeastern part of India. In recent years, climate change has posed a threat to muga silk production due to the requirement that larvae be reared outdoors. Since the muga silkworm larvae are exposed to the vagaries of nature, the changing climate has increased the incidence of microbial diseases in the rearing fields. Accurate diagnosis of the disease causing pathogens and its associated epidemiology are prerequisites to manage the diseases in the rearing field. Although conventional microbial culturing methods are widely used to identify pathogenic bacteria, they would not provide meaningful information on a wide variety of silkworm pathogens. The information on use of molecular diagnostic tools in detection of microbial pathogens of wild silk moths is very limited. A wide range of molecular and immunodiagnostic techniques including denaturing gradient gel electrophoresis (DGGE), random amplified polymorphism (RAPD), 16S rRNA/ITSA gene sequencing, multiplex polymerase chain reaction (M-PCR), fluorescence in situ hybridization (FISH), immunofluorescence, and repetitive-element PCR (Rep-PCR), have been used for detecting and characterizing the pathogens of insects with economic significance. Nevertheless, the application of these molecular tools for detecting and typing entomopathogens in surveillance studies of muga silkworm rearing is very limited. Here, we discuss the possible application of these molecular techniques, their advantages and major limitations. These methods show promise in better management of diseases in muga ecosystem.