• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.27-36
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• 2024

In this paper, we analyze the unified requirements of international association of classification societies - cyber resilience of ships, ahead of implementation of the agreement on July 1, 2024, and respond to ship cyber security and resilience programs based on 5 requirements, 17 details, and documents that must be submitted or maintained according to the ship's cyber resilience,. Measures include document management such as classification certification documents and design documents, configuration of a network with enhanced security, establishment of processes for accident response, configuration management using software tools, integrated network management, malware protection, and detection of ship network security threats with security management solutions. proposed a technology capable of real-time response.

• Herbal Formula Science
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• v.32 no.1
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• pp.1-9
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• 2024

Objective : This study aims to assess the potential of utilizing large language models in pattern identification education by developing a simulated patient with fatigue and dual deficiency of the heart-spleen pattern. Methods : A simulated patient dataset was constructed using the clinical practice examination module provided by the National Institute for Korean Medicine Development. The dataset was divided into patient characteristics, sample questions, and responses, and utilized to design the system, assistant, and user prompts, respectively. A web-based interface was developed using the Django framework and WebSocket. Results : We developed a simulated fatigue patient representing dual deficiency of the heart-spleen pattern through prompt engineering. To make practical tools, we further implemented web-based interfaces for the examinee's and evaluator's roles. The interface for examinees allows one to examine the simulated patient and provides access to a personalized number for future access. In addition, the interface for evaluators included a page that provided an overview of each examinees' chat history and evaluation criteria in real-time. Conclusion : This study is the first development of an educational tool integrated with a large language model for pattern identification education, which is expected to be widely applied to Korean medicine education.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.251-264
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• 2008

One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

• Information Systems Review
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• v.18 no.4
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• pp.89-106
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• 2016

The latest movement in live video streaming service is mobile personal broadcasting (MPB), which refers to consumers accessing the service through social media with mobile devices, such as smartphones and tablet PCs. This service is possible through the advancements in mobile video technology and platforms. Features such as enhanced user interaction, personalization, and real-time broadcasting, combined with a greater variety of content, have led to the development of MPB. The increase in MPB users calls for research, including that on the hedonic motivational angle. This study aims to assess MPB users' intrinsic motives through the hedonic-motivation system adoption model (HMSAM) using seven factors: joy, temporal dissociation, escapism, focused immersion, perceived ease of use, perceived usefulness and intention to watch. Survey data collected from 154 samples were analyzed with statistical techniques, such as structural equation modeling. Results showed that time dissociation, escapism, and perceived ease of use have a positive relationship with heightened enjoyment. Joy significantly affects focused immersion and intention to watch. Escapism also had a statistically significant influence on focused immersion. This study contributes to the advancement of the MPB study under the HMSAM theoretical framework and offers practical suggestions to managers to enhance MPB content viewership.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.214-224
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• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.427-436
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• 2016

Due to disasters such as earthquakes and landslides in urban areas, persons have been buried inside collapsed buildings and structures. Rescuers have mainly utilized detection equipment by applying sound, video and electric waves, but these are expensive and due to the directional approaches onto the collapsed site, secondary collapse risk can arise. In addition, due to poor utilization of such equipment, new human detection technology with quick and high reliability has not been utilized. To address these issues, this study develops a wireless signal-based human detection module that can be loaded into an Unmanned Aerial Vehicle (UAV). The human detection module searches for the 3D location for buried persons by collecting Wi-Fi signal and barometer sensors data transmitted from the mobile phones. This module can gain diverse information from mobile phones for buried persons in real time. We present a development framework of the module that provides 3D location data with more reliable information by delivering the collected data into a local computer in the ground. This study verified the application feasibility of the developed module in a real collapsed area. Therefore, it is expected that these results can be used as a core technology for the quick detection of buried persons' location and for relieving them after disasters that induce building collapses.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.71-90
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• 2012

Although it has been studied for a long time in various disciplines, most of control theories remain being developed by analyzing relatively simple tasks. Even recent research on control of information systems development explains only a small part of control phenomena observed in the real world projects. This research focuses on identifying and analyzing the concepts and structures in order to make them useful for understanding and explaining control of information systems development comprehensively This investigation utilizes the complementary relationship between views on control from organizational and economic perspectives. A conceptual framework developed by integrating previous research on control allows us to analyze the development of information systems for control purposes. The results of discussion about control mechanisms and network can be used as guidelines for designing control systems in real projects. Analysis of control networks shows that control of development projects requires quite complex networks intertwining a variety of controllers and controlees. The results of this research are expected to contribute to correcting the unbalanced status of IS research which has emphasized too heavily on planning and implementation, and deepening and widening our understanding about controlling development projects. Practitioners can use the results as guidelines for designing control mechanisms and networks, and get alerted by them about the agency risks inherent in outsourced developments.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.28-36
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• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.159-174
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• 2023

In this paper, we proposed a methodology to effectively determine the selection and prioritization of new business and innovation projects using AI technology. AI technology is a technology that can upgrade the business of companies in various industries and increase the added value of the entire industry. However, there are various constraints and difficulties in the decision-making process of selecting and implementing AI projects in the enterprise. In this paper, we propose a new methodology for prioritizing AI projects using Morphology, AHP, and TOPSIS. The proposed methodology helps prioritize AI projects by simultaneously considering the technical feasibility of AI technology and real-world user requirements. In this study, we applied the proposal methodology to a real enterprise that wanted to prioritize multiple AI projects in the HR field and evaluated the results. The results confirm the practical applicability of the methodology and suggest ways to use it to help companies make decisions about AI projects. The significance of the methodology proposed in this study is that it is a framework for prioritizing multiple AI projects considered by a company in the most reasonable way by considering both business and technical factors at the same time.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.