• Asia pacific journal of information systems
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• v.33 no.4
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• pp.957-976
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• 2023

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.597-602
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• 2011

A robust asset management methodology is essential for effective decision-making of maintenance, repair and rehabilitation of a bridge network. It can be achieved by a computer-based bridge management system (BMS). Successful BMS development requires a reliable bridge deterioration model, which is the most crucial component in a BMS, and an optimal management philosophy. The maintenance optimization methodology proposed in this paper is developed for a small bridge network with limited structural condition rating records. . The methodology is organized in three major components: (1) bridge health index (BHI); (2) maintenance and budget optimization; and (3) reliable Artificial Intelligence (AI) based bridge deterioration model. The outcomes of the paper will help to identify BMS implementation problems and to provide appropriate solutions for managing small bridge networks.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.2
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• pp.133-140
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• 2024

This study offers a comprehensive evaluation of the role and impact of advanced power semiconductors in solar module systems. Focusing on silicon carbide (SiC) and gallium nitride (GaN) materials, it highlights their superiority over traditional silicon in enhancing system efficiency and reliability. The research underscores the growing industry demand for high-performance semiconductors, driven by global sustainable energy goals. This shift is crucial for overcoming the limitations of conventional solar technology, paving the way for more efficient, economically viable, and environmentally sustainable solar energy solutions. The findings suggest significant potential for these advanced materials in shaping the future of solar power technology.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.234-241
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• 2024

In higher education, integration of technologies - particularly generative artificial intelligence (AI) such as ChatGPT - has become increasingly widespread, serving numerous purposes to its stakeholders. While users acknowledge the utility of technology, concerns have emerged regarding its misuses. The present study is designed to investigate authentic perspectives and opinions of college freshman students to critically address the relevant concerns, and suggest meaningful solutions. To this end, seven college freshman student participants were recruited in a four-days-long online questionnaire. Their responses indicated that the college student participants appear to find ChatGPT positive in terms of its practicality and usefulness. However, they also showed concerns about a few potential issues (i.e., possible plagiarism and copyright problems). With recommendations the student participants suggested to reduce the aforementioned problems, the article discusses implications of the findings, providing valuable insights into the balance between implementation of AI technologies and dealing with the associated challenges in higher education in general.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.27-30
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• 2000

Many human inventions were inspired by nature. The artificial neural network is one example. Another example is Genetic Algorithms(GA). GAs search by simulating evolution, starting from an initial set of solutions or hypotheses, and generating successive "generations" of solutions. This particular branch of AI was inspired by the way living things evolved into more successful organisms in nature. To simulate the process of GA in a computer, we must simulate many times according to varying many GA parameters. This paper describes the implementation of Java Package for efficient applications on Genetic Algorithms, called "JavaGA". The JavaGA used as a application program as well as applet provides graphical user interface of assigning major GA parameters.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.135-138
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• 1996

In solving the Travel Salesman Problem(TSP), we easily reach local optimal solutions with the existing methods such as TWO-OPT, THREE-OPT, and Lin-Kernighen. Tabu search, as a meta heuristic, is a good mechanism to get an optimal or a near optimal solution escaping from the local optimal. By utilizing AI concepts, tabu search continues to search for improved solutions. In this study, we focus on developing a new neighborhood structure that maintains the feasibility of the tours created by exchange operations in TSP. Intelligent methods are discussed, which keeps feasible tour routes even after exchanging several edges continuously. An extended tabu search model, performing cycle detection and diversification with memory structure, is applied to TSP. The model uses effectively the information gathered during the search process. Finally, the results of tabu search and simulated annealing are compared based on the TSP problems in the prior literatures.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.34-41
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• 2020

The existing Von Neumann architecture places limits to data processing in AI, a booming technology. To address this issue, research is being conducted on computing architectures and artificial neural networks that simulate neurons and synapses, which are the hardware of the human brain. With high-speed, high-throughput data communication infrastructures, photonic solutions today are a mature industrial reality. In particular, due to the recent outstanding achievements of artificial neural networks, there is considerable interest in improving their speed and energy efficiency by exploiting photonic-based neuromorphic hardware instead of electronic-based hardware. This paper covers recent photonic neuromorphic studies and a classification of existing solutions (categorized into multilayer perceptrons, convolutional neural networks, spiking neural networks, and reservoir computing).

• Corrosion Science and Technology
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• v.2 no.6
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• pp.277-282
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• 2003

Holographic interferometry, an electromagnetic method, was used to study corrosion of carbon steel, aluminum and copper nickel alloys in NaOH, KCI and $H_2SO_4$ solutions respectively. The technique, called electrochemical emission spectroscopy, consisted of in-situ monitoring of changes in the number of fringe evolutions during the corrosion process. It allowed a detailed picture of anodic dissolution rate changes of alloys. The results were compared to common corrosion measurement methods such as linear polarization resistance measurements and electrochemical impedance spectroscopy. A good agreement between both data was found, thus indicating that holographic interferometry can be a very powerful technique for in-situ corrosion monitoring.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.8-14
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• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.235-246
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• 2023

In the rapid technological development of artificial intelligence (AI), electric vehicles, and robots based the fourth industrial revolution, semiconductors determine the core performance, and semiconductor competitiveness is directly related to national competitiveness. However, the Korean semiconductor industry has continuously weakened its competitiveness in the system semiconductor field, excluding memory semiconductors, so in this study, a new smart contract basedblockchain business model to engage the global market, which is the most urgent need for the growth of Korean fabless system semiconductor industry in recession. F-SBM (Fabless-Smart contract based Blockchain Model) proposed. In this study, through the new F-SBM, it was verified how to engage new customers for fabless firms through smart contract based consortium blockchain regarding technology, economy, and reliability items of fabless. This model has great significance in improving the high entry barriers to engaging new customers for the long-cherished desire of the Korean fabless system semiconductor industry and deriving new growth solutions.