• Journal of Korea Game Society
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• v.20 no.6
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• pp.63-74
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• 2020

Recently, research on automating game tests using artificial intelligence agents instead of humans is attracting attention. This paper aims to collect play data from human and artificial intelligence and analyze their similarity as a preliminary study for game balancing automation. At this time, constraints were added at the learning stage in order to create artificial intelligence that can play similar to humans. Play datas obtained 14 people and 60 artificial intelligence by playing Flippy bird games 10 times each. The collected datas compared and analyzed for movement trajectory, action position, and dead position using the cosine similarity method. As a result of the analysis, an artificial intelligence agent with a similarity of 0.9 or more with humans was found.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.33 no.4
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• pp.84-90
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• 2022

Personal life and achievements are the process and result of a person's past, present, and future interacting with each other. In this regard, if one fully understands the life and background of the person who developed the theory of psychoanalysis, one can understand and use the theory more appropriately. The holding environment theory developed by Donald Woods Winnicott is useful for understanding the process by which infants grow healthy under the care of a mother who is good enough. In this paper, the background of the birth of the holding environment theory is reviewed based on Winnicott's developmental background and marital life. He grew up with a holding environment from good enough 'multiple mothers'. Born with excellent athletic ability and musical talent, he was more curious than anyone else and particularly active in discovering new things. After the unhappy first marriage, Claire Britton's second marriage was happy academically and personally. Claire was a fellow paediatric psychoanalyst who published Winnicott's research and theories after his death. Psychoanalysis or psychotherapy itself can be a holding environment, and the holding environment theory can be applied to various fields in the digital era.

• ETRI Journal
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• v.44 no.2
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• pp.286-299
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• 2022

Human activity recognition in real time is a challenging task. Recently, a plethora of studies has been proposed using deep learning architectures. The implementation of these architectures requires the high computing power of the machine and a massive database. However, handcrafted features-based machine learning models need less computing power and very accurate where features are effectively extracted. In this study, we propose a handcrafted model based on three-dimensional sequential skeleton data. The human body skeleton movement over a frame is computed through joint positions in a frame. The joints of these skeletal frames are projected into two-dimensional space, forming a "movement polygon." These polygons are further transformed into a one-dimensional space by computing amplitudes at different angles from the centroid of polygons. The feature vector is formed by the sampling of these amplitudes at different angles. The performance of the algorithm is evaluated using a support vector machine on four public datasets: MSR Action3D, Berkeley MHAD, TST Fall Detection, and NTU-RGB+D, and the highest accuracies achieved on these datasets are 94.13%, 93.34%, 95.7%, and 86.8%, respectively. These accuracies are compared with similar state-of-the-art and show superior performance.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.103-112
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• 2022

The goal of pattern mining is to identify novel patterns in a database. High utility itemset mining (HUIM) is a research direction for pattern mining. This is different from frequent itemset mining (FIM), which additionally considers the quantity and profit of the commodity. Several algorithms have been used to mine high utility itemsets (HUIs). The original BPSO algorithm lacks local search capabilities in the subsequent stage, resulting in insufficient HUIs to be mined. Compared to the transfer function used in the original PSO algorithm, the V-shaped transfer function more sufficiently reflects the probability between the velocity and position change of the particles. Considering the influence of the acceleration factor on the particle motion mode and trajectory, a nonlinear acceleration strategy was used to enhance the search ability of the particles. Experiments show that the number of mined HUIs is 73% higher than that of the original BPSO algorithm, which indicates better performance of the proposed algorithm.

• Fashion & Textile Research Journal
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• v.25 no.4
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• pp.429-438
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• 2023

In the 21st century fashion industry, the rise of digital environments has transformed it into a dynamic medium, expanding the horizons of media utilization. Consequently, digital fashion film has emerged as a pivotal tool for fashion communication. Functioning as a visual expression medium, fashion film animates fashion concepts into immersive moving images. Proficiency in digital fashion communication has become imperative, considering the attributes of fashion media. Notably, the role of creative directors in ensuring coherent communication across diverse fashion media platforms has gained prominence, underscoring the need for systematic fashion education to nurture specialized talent. This study, therefore, devised a comprehensive curriculum amalgamating fashion communication and practical digital media skills, implemented within fashion major courses. Through this approach, students gained experimental media proficiency and explored innovative approaches to crafting fashion films that eloquently convey fashion narratives. The participants were exposed to the entire spectrum of fashion media production, encompassing digital storytelling, fashion film conceptualization, filming techniques, meticulous editing, and adept utilization of special effects technology. The study's pedagogical strategy, characterized by a focused learning trajectory, garnered significant acclaim. In essence, this study holds significance by formulating a curriculum that nurtures the imaginative and pragmatic aptitudes of fashion majors, immersing them in the dynamic realm of rapidly evolving digital fashion films and their integration with fashion content.

• Advances in nano research
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• v.14 no.5
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• pp.409-419
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• 2023

Tracking the motion of tennis balls is a challenging task in using cameras around the tennis court. The most important instance of the tennis trajectory is the time of impact and touch the court which in some cases could not be detected precisely. In the present study, we aim to present a novel design of tennis balls equipped with nano-sensors to detect the touch of the ball to the court. In the impact instance, tennis ball receives significant acceleration and change in the linear momentum. This large acceleration could deform a small-beam structure with piezoelectric layer to produce voltage. The voltage could further be utilized to produce infrared waves which could be easily detected by infrared detection sensors installed on the same video cameras or separately near the tennis court. Therefore, the exact time of the impact could be achieved with higher accuracy than image analyzing method. A detailed dynamical property of such sensors is discussed using nonlinear beam equations. The results show that within the acceleration range of tennis ball during an impact, the piezoelectric patches of the nano-sensors in the tennis ball could produce enough voltages to propagate infrared waves to be detected by infrared detectors.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.3
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• pp.451-466
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• 2024

This study investigated the current statuses of and challenges faced by 19 textile and fashion museums in Seoul and Daegu. Through interviews conducted via email, phone, and face-to-face meetings with museum officials, this research analyzed the prevalent difficulties encountered by the museums based on the concept of the new museum. The results indicate that domestic museums experience different difficulties depending on operating organization rather than collection or exhibition content. This is related to the distribution of museums by operating institutions, as most textile craft museums are private establishments, and, the majority of dress and fashion museums are university-affiliated institutions. Accordingly, this study explored the major problems confronting textile craft, dress and fashion, and accessory museums with a consideration for operating institutions. It proposes improvements in domestic textile and fashion museums through a comparative analysis with overseas museums as new museums.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.29-34
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• 2024

Since the outbreak of COVID-19, there has been a surge in sports conducted through online platforms due to the increase in remote and non-contact activities. Billiards, being suitable for online platforms, has received much attention, leading to research on detecting the position and trajectory of balls. In this paper, we propose a new method utilizing machine vision to detect the position of the balls accurately. The proposed method detects the outline of the ball using the Canny edge detection and then employs simple correlation to determine its position. This correlation-based approach offers satisfactory system performance and is easily applicable in practical systems due to its low implementation complexity and robustness to noise.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.1-9
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• 2024

Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.57 no.4
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• pp.479-488
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• 2024

In recent years, changes in the fishing ground environment have led to reduced catches by fishermen at traditional fishing spots and increased operational costs related to vessel exploration, fuel, and labor. In this study, we developed a deep learning model to classify the fishing activities of drift gillnet fishing boats using AIS (automatic identification system) trajectory data. The proposed model integrates long short-term memory and 1-dimensional convolutional neural network layers to effectively distinguish between fishing (throwing and hauling) and non-fishing operations. Training on a dataset derived from AIS and validation against a subset of CCTV footage, the model achieved high accuracy, with a classification accuracy of 90% for fishing events. These results show that the model can be used effectively to monitor and manage fishing activities in coastal waters in real time.