• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.481-486
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• 2023

Anomaly detection holds paramount significance across diverse fields, encompassing fraud detection, risk mitigation, and sensor evaluation tests. Its pertinence extends notably to the military, particularly within the Warrior Platform, a comprehensive combat equipment system with wearable sensors. Hence, we propose a data-compression-based anomaly detection approach tailored to unlabeled time series and sequence data. This method entailed the construction of two distinctive features, typicality and atypicality, to discern anomalies effectively. The typicality of a test sequence was determined by evaluating the compression efficacy achieved through the pattern dictionary. This dictionary was established based on the frequency of all patterns identified in a training sequence generated for each sensor within Warrior Platform. The resulting typicality served as an anomaly score, facilitating the identification of anomalous data using a predetermined threshold. To improve the performance of the pattern dictionary method, we leveraged atypicality to discern sequences that could undergo compression independently without relying on the pattern dictionary. Consequently, our refined approach integrated both typicality and atypicality, augmenting the effectiveness of the pattern dictionary method. Our proposed method exhibited heightened capability in detecting a spectrum of unpredictable anomalies, fortifying the stability of wearable sensors prevalent in military equipment, including the Army TIGER 4.0 system.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.809-818
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• 2024

This paper proposes an action plan for local governments to safely utilize artificial intelligence technology in various local government policies. The proposed method analyzes cases of application of artificial intelligence-related laws and policies in Gyeonggi Province, Seoul City, and New York City, and then presents matters that local governments should consider when utilizing AI technology in their policies. This paper applies the AILocalism-Korea analysis methodology, which is a modified version of the AILocalsm analysis methodology[1] presented by TheGovLab at New York University. AILocalism-Korea is an analysis methodology created to analyze the current activities of each local government in the fields of legal system, public procurement, mutual cooperation, and citizen participation, and to suggest practical alternatives in each area. In this paper, we use this analysis methodology to present 9 action plans that local governments should take based on safe and reliable use of artificial intelligence. By utilizing various AI technologies through the proposed plan in local government policies, it will be possible to realize reliable public services.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.71-76
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• 2010

This paper is focused on implementing a real-time data acquisition system that checks power facility status by applying network based technology to Urban Transit substation power facilities and the results of its on-field tests. This system is composed of a sensor part, a measurement part, a transceiver part, a host computer, and a power source part. The system is designed to collect, save, analyze, and display the online state power facility AI (Analog Input). This system measures voltage and current from positive feeders and negative feeders where it is possible to check abnormalities of the substation‘s main power facilities. By monitoring abnormal data of the Urban Transit power facilities real-time and analyzing stored data, establishing procedures of optimized maintenance is possible.

• Advances in nano research
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• v.12 no.2
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• pp.197-212
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• 2022

The purpose of this study is to develop an automatic software system for bone age evaluation and to evaluate its accuracy in testing and feasibility in clinical practice. 20394 left-hand radiographs of healthy children (2-18 years old) were collected from China Skeletal Development Survey data of 1998 and China Skeletal Development Survey data of 2005. Three experienced radiologists and China-05 standard maker jointly evaluate the stages of bone development and the reference bone age was determined by consensus. 1020 from 20394 radiographs were picked randomly as test set and the remaining 19374 radiographs as training set and validation set. Accuracy of the automatic software system for bone age assessment is evaluated in test set and two clinical test sets. Compared with the reference standard, the automatic software system based on RUS-CHN for bone age assessment has a 0.04 years old mean difference, ±0.40 years old in 95% confidence interval by single reading, a 85.6% percentage agreement of ratings, a 93.7% bone age accuracy rate, 0.17 years old of MAD, 0.29 years old of RMS; Compared with the reference standard, the automatic software system based on TW3-C RUS has a 0.04 years old mean difference, a ±0.38 years old in 95% confidence interval by single reading, a 90.9% percentage agreement of ratings, a 93.2% bone age accuracy rate, a 0.16 years of MAD, and a 0.28 years of RMS. Automatic software system, AI-China-05 showed reliably accuracy in bone age estimation and steady determination in different clinical test sets.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.149-164
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• 2019

Digital Transformation and the Fourth Industrial Revolution, electronic financial services should be provided safely in accordance with rapidly changing technology changes in the times of change. However, telecommunication finance fraud (voice phishing) accidents are currently ongoing, and various efforts are being made to eradicate accidents such as legal amendment and improvement of policy system in order to cope with continuous increase, intelligence and advancement of accidents. In addition, financial institutions are trying to prevent fraudulent accidents by improving and upgrading the abnormal financial transaction detection system, but the results are not very clear. Despite these efforts, telecommunications and financial fraud incidents have evolved to evolve against countermeasures. In this paper, we propose an intelligent over - the - counter financial transaction system modeled through scenario - based Rule model and artificial intelligence algorithm to prevent financial transaction accidents by voice phishing. We propose an implementation model of artificial intelligence abnormal financial transaction detection system and an optimized countermeasure model that can block and respond to analysis and detection results.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.50-57
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• 2022

Along with the development of the 4^th Industrial Revolution technology, artificial intelligence technology is also being used in the field of systems engineering. This study analyzed the development status of artificial intelligence technology in the areas of systems engineering core processes such as stakeholder needs and requirements definition, system requirement analysis, and system architecture definition, and presented future technology development directions. In the definition of stakeholder needs and requirements, technology development is underway to compensate for the shortcomings of the existing requirement extraction methods. In the field of system requirement analysis, technology for automatically checking errors in individual requirements and technology for analyzing categories of requirements are being developed. In the field of system architecture definition, a technology for automatically generating architectures for each system sector based on requirements is being developed. In this study, these contents were summarized and future development directions were presented.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1249-1249
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• 2022

The facade, an exterior material of a building, is one of the crucial factors that determine its morphological identity and its functional levels, such as energy performance, earthquake and fire resistance. However, regardless of the type of exterior materials, huge property and human casualties are continuing due to frequent exterior materials dropout accidents. The quality of the building envelope depends on the detailed design and is closely related to the back frames that support the exterior material. Detailed design means the creation of a shop drawing, which is the stage of developing the basic design to a level where construction is possible by specifying the exact necessary details. However, due to chronic problems in the construction industry, such as reducing working hours and the lack of design personnel, detailed design is not being appropriately implemented. Considering these characteristics, it is necessary to develop the detailed design process of exterior materials and works based on the domain-expert knowledge of the construction industry using artificial intelligence (AI). Therefore, this study aims to establish a detailed design automation algorithm for AI-based condition-responsive exterior wall panels and their back frames. The scope of the study is limited to "detailed design" performed based on the working drawings during the exterior work process and "stone panels" among exterior materials. First, working-level data on stone works is collected to analyze the existing detailed design process. After that, design parameters are derived by analyzing factors that affect the design of the building's exterior wall and back frames, such as structure, floor height, wind load, lift limit, and transportation elements. The relational expression between the derived parameters is derived, and it is algorithmized to implement a rule-based AI design. These algorithms can be applied to detailed designs based on 3D BIM to automatically calculate quantity and unit price. The next goal is to derive the iterative elements that occur in the process and implement a robotic process automation (RPA)-based system to link the entire "Detailed design-Quality calculation-Order process." This study is significant because it expands the design automation research, which has been rather limited to basic and implemented design, to the detailed design area at the beginning of the construction execution and increases the productivity by using AI. In addition, it can help fundamentally improve the working environment of the construction industry through the development of direct and applicable technologies to practice.

• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.605-611
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• 2023

Accidents at construction sites have a very high rate of fatalities due to the nature of being prone to severe injury patients. In order to reduce the mortality rate of severely injury patients, quick response is required, and some systems that detect accidents using AI technology and cameras have been devised to respond quickly to accidents. However, since existing accident detection systems use only a single camera, there are blind spots, Thus, they cannot detect all accidents at a construction site. Therefore, in this paper, we present the system that minimizes the detection blind spot by using multiple cameras. Our implemented system extracts feature points from the images of multiple cameras with the YOLO-pose library, and inputs the extracted feature points to a Long Short Term Memory-based recurrent neural network in order to detect accidents. In our experimental result, we confirme that the proposed system shows high accuracy while minimizing detection blind spots by using multiple cameras.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.231-247
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• 2020

As artificial intelligence (AI) has emerged as a promising future technology among the fourth industrial revolution, we are trying to apply artificial intelligence technology across all area of society, including libraries. This study investigated the effects, issues, and implications of artificial intelligence on university library services. As a research method, in-depth interviews were conducted with IT experts of university libraries in North America, and conclusions and discussion were drawn from interview results and related documents. Research results revealed that university libraries in North America were trying to build an infrastructure that facilitates information access and retrieval based on artificial intelligence systems and to provide new services in collaboration with AI research institutes in universities. This study raised issues regarding the expansion of the role of libraries and librarians, privacy, and data quality. It was also discussed that the need for re-education of university librarians to become software engineers who play a role in disseminating knowledge. In addition, this study suggested the investment for the establishment of the information system and an artificial intelligence research center in the library. The study discussed limitations of research due to changes in the research environment and suggestions for future research.