• Korean Journal of Schizophrenia Research
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• v.21 no.2
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• pp.74-80
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• 2018

Objectives : This study investigated whether long-acting injectable (LAI) paliperidone is different from its oral form in terms of the effect on cognitive function in schizophrenia spectrum and other psychotic disorders. Methods : We reviewed the medical records of patients in Seoul National University Bundang Hospital who were diagnosed as having schizophrenia and/or other psychotic disorders based on DSM-5 from 2016 to 2017. Seven patients were treated with oral paliperidone and 11 were treated with paliperidone palmitate. All patients underwent clinical and neuropsychological assessment, including the Korean version of the MATRICS Consensus Cognitive Battery (MCCB) at their first visit or within one month of their initial treatment. MCCB was repeated within three to 12 months after the initial assessment. Results : There was no significant difference between the two groups in most cognitive domains including speed of processing, attention and vigilance, working memory, verbal learning, visual learning and reasoning and problem solving domain. However, patients treated with paliperidone palmitate showed better improvement in social cognition domain than those taking oral paliperidone. The standardized values of social cognition domain scores had significantly improved over time in patients under paliperidone palmitate, demonstrating a significant time-by-group interaction. Conclusion : Our results show that long-acting injectable paliperidone could be helpful in some aspects of improving cognitive function in schizophrenia spectrum and other psychotic disorders. Further studies with other antipsychotics are necessary to generalize the results.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.51-58
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• 2023

Blockchains have recently struggled to design for the ideal distributed trust networks by solving scalability trilemma. However, local conflicts between some countries lead to imbalance on energy distribution. Besides, blockchain networks (e.g., Bitcoin) currently consume enormous energy for transaction and mining. The existing data volume based trust model evaluated an increasing blockchain size better than Lubin's trust model in scalability trilemma. In this paper, we propose a scalability based energy model to evaluate sustainability for blockchain networks, considering energy consumption for transaction, time duration, and the blockchain size of growing blockchain networks. Through the rigorous numerical analysis, we compare the proposed scalability based energy model with the existing model for the satisfaction and optimal blockchain size. Thus, the scalability based energy model will provide an assessment tool to choose the proper blockchain networks to solve scalability trilemma problem and prove sustainability.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.53-58
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• 2024

IoT, Big-data, AI, and Cloud technologies, which are core technologies of the 4th Industrial Revolution, have recently been applied to various fields and are being used as core technologies for new growth engines. Accordingly, these core technologies are applied to the agricultural field without exception, contributing to solving the problem of labor shortage, reducing production costs, and reducing environmental burden through remote and automated production without time and space constraints. However, as these core technologies are utilized, security incidents are occurring in the agricultural field as well. Accordingly, this study divides smart farms into three stages(Basic, Middle, and High) and presents the characteristics and security threats of each stage. In particular, as the number of container-based services and research increases under cloud platforms, we would like to suggest countermeasures focusing on security threats.

• Journal of Korean Clinical Nursing Research
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• v.29 no.3
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• pp.283-295
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• 2023

Purpose: The purpose of this study was to provide basic data to understand the organizational culture of nurses by categorizing nurses' experience of coping with bullying in the workplace through Q methodology and analyzing the characteristics of each type, and to induce correct policy measures and interventions to create an atmosphere created in the nursing clinical field to be more advanced and positive. Methods: To form the Q population, focus group interviews were conducted with nurses working for more than six months at two general hospitals in Seoul and Gyeonggi. Interviews were conducted by 12 nurses introduced to participants who can provide researchers with a wealth of information on workplace bullying experiences without filtration. In addition, the Q population was extracted by reviewing the results. Based on the results derived from this, 38 Q statements in total were extracted. Forty clinical nurses were required to classify Q sample statements, and the data collected through this were analyzed using the pc-QUANAL program. Results: As a result of the analysis, a total of five types of clinical nurses' experiences of coping with bullying in the workplace were identified: 'tense emotion-based tolerance response,' 'positive thinking-based self-effort response', 'individualistic thinking-based passive response', 'support system-based emotional expression response' and 'active response centered on problem-solving'. Conclusion: The derived response types are expected to be guidelines for suggesting strategies to eradicate bullying in the workplace at the organizational level, individual level, prevention level, and organizational culture level.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.197-205
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• 2023

This study is to apply the Havruta teaching-learning method to college students' major classes and analyze the relationship between the effectiveness evaluation of communication skills and sub-factors using a structural equation model. As a result of the study, the communication ability score was different before and after Havruta teaching-learning, and it was found that after Havruta teaching-learning was higher than before Havruta teaching-learning. The path effect was found to be significant in all of the total, direct, and indirect effects among latent variables, except for the relationship between interpretation ability, role-playing ability, and goal-setting ability in the direct effect. In this study, it was found that the Havruta teaching-learning method not only improves creativity and thinking ability, but also improves self-directed learning ability. In addition, it was reconfirmed that it is a teaching-learning method that can develop social skills and communication skills as well as problem-solving skills while experiencing opinions different from one's own. As a result, research on a thorough student-centered teaching-learning method suitable for the Homo Machina era must be continued and its application in the educational field must be implemented.

• Smart Structures and Systems
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• v.32 no.6
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• pp.349-358
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• 2023

Real-Time Hybrid Testing (RTHT) requires the numerical substructure calculations to be completed within the defined integration time interval due to its real-time loading demands. For solving the problem, A Real-Time Hybrid Testing based on Restart-Loading Technology (RTHT-RLT) is proposed in this paper. In the proposed method, in case of the numerical substructure calculations cannot be completed within the defined integration time interval, the experimental substructure was returned back to the initial state statically. When the newest loading commands were calculated by the numerical substructure, the experimental substructure was restarted loading from the initial state to the newest loading commands so as to precisely disclosing the dynamic performance of the experimental substructure. Firstly, the methodology of the RTHT-RLT is proposed. Furthermore, the numerical simulations and experimental tests on one frame structure with a viscous damper are conducted for evaluating the feasibility and effectiveness of the proposed RTHT-RLT. It is shown that the proposed RTHT-RLT innovatively renders the nonreal-time refined calculation of the numerical substructure feasible for the RTHT. The numerical and experimental results show that the proposed RTHT-RLT exhibits excellent performance in terms of stability and accuracy. The proposed RTHT-RLT may have broad application prospects for precisely investigating the dynamic behavior of large and complex engineering structures with specific experimental substructure where a restarting procedure does not affect the relevant hysteretic response.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.124-130
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• 2023

Recently, fan out wafer level packaging, which enables high integration, miniaturization, and low cost, is being rapidly applied in the semiconductor industry. In particular, FOWLP is attracting attention in the mobile and Internet of Things fields, and is recognized as a core technology that will lead to technological advancements such as 5G, self-driving cars, and artificial intelligence in the future. However, as chip density and package size within the package increase, FOWLP warpage is emerging as a major problem. These problems have a direct impact on the reliability and electrical performance of semiconductor products, and in particular, cause defects such as vacuum leakage in the manufacturing process or lack of focus in the photolithography process, so technical demands for solving them are increasing. In this paper, warpage simulation according to the thickness of FOWLP material was performed using finite element analysis. The thickness range was based on the history of similar packages, and as a factor causing warpage, the curing temperature of the materials undergoing the curing process was applied and the difference in deformation due to the difference in thermal expansion coefficient between materials was used. At this time, the stacking order was reflected to reproduce warpage behavior similar to reality. After performing finite element analysis, the influence of each variable on causing warpage was defined, and based on this, it was confirmed that warpage was controlled as intended through design modifications.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.487-495
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• 2023

Ammonia is either a crucial resource of fertilizer production for solving the food problem of mankind or an important energy source as both an eco-friendly hydrogen carrier and a carbon-free fuel. Therefore, nowadays ammonia synthesis and decomposition become promising. Then, a catalyst is required to effectively perform the ammonia synthesis and decomposition. In order to design high-performing as well as cheap novel catalysts for ammonia synthesis and decomposition, it is necessary to test huge amount of catalyst candidates, but it is inevitably time-consuming and expensive to search and analyze using only traditional approaches. Recently, new methods using machine learning which is one of the core technologies of the 4th industrial revolution that can quickly and accurately search high-performance catalysts has been emerging. In this paper, we investigate reaction mechanisms of ammonia synthesis and decomposition, and we described recent research and prospects of machine learning-driven methods that can efficiently find high-performing and economical catalysts for ammonia synthesis and decomposition.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.121-130
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• 2023

In the school field, AI convergence education is recommended, which utilizes AI in education to change the paradigm of society. This study was conducted to define the terms of AI and AI convergence education to minimize the confusion of terms and to analyze the educational needs of teachers from the perspective of conducting AI convergence education. To achieve the purpose, 19 experts' opinions were collected, and a self-administered questionnaire was administered to 125 secondary school teachers enrolled in the AI convergence major at the Graduate School of Education. As a result of the analysis, the experts defined AI convergence education as a methodology for problem solving, not AI-based or utilization education. In the analysis of teachers' educational needs, "AI and big data" was ranked first, followed by "AI convergence education methodology" and "learning practice using AI". The significance of this study is that it defined the terminology by collecting the opinions of experts amidst the confusion of various terms related to AI, and presented the educational direction of AI convergence education for in-service teachers.

• Industry Promotion Research
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• v.8 no.4
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• pp.229-239
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• 2023

This research as a literature study is to clarify solution method of hypochondriasis through focused distraction. Hypochondriasis is called by various terms such as somatization symptoms, health anxiety, illness phobia, illness anxiety disorder, hypochondriacal disorder, hypochondriacal neurosis, and hypochondria personality disorder. Hypochondria is basically a factor that causes worry, fear, anxiety, and even phobia, lowering the quality of life at home, work, and society. As the quality of life of individuals is decreasing, the field of counseling psychology and psychological counseling has the task of solving this problem and restoring psychological peace. Accordingly, this study is an attempt to explore the symptoms of hypochondria by using the distraction strategy among cognitive strategies as a way to resolve the condition. Focused distraction strategy can be said to be a kind of cognitive 'avoidance strategy'. Focused distraction strategy is a way to avoid being overly focused on one's health. In addition, it weakens health concerns by 'dispersing' or 'distracting' the 'attention' focused on health in another direction.