• Title/Summary/Keyword: Generation Model

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A Study on Method of Framework Data Update and Computing Land Change Ratio using UFID (UFID를 이용한 기본지리정보 갱신 및 지형변화율 산출 방안 연구)

  • Kim, Ju Han;Kim, Byung Guk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1D
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    • pp.157-167
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    • 2006
  • During the first and second NGIS projects by the Korean government, The first one (1995~2000) was limited on constructing geographic information and the second (2001~2005) was focused on circulation and practical use of geoinformation from the result of the first project. In the latter half of 2nd NGIS project, However, the geographic information from the NGIS projects have not been renewed even though there were significant geographical changes. The accurate renewal of geoinformation is a matter of great importance to the next generation industry (e.g. LBS, Ubiquitous, Telematics). In this respect, it is time to update the geographic information in the latter half of the second NGIS project. Therefore, It is not only important to build an accurate geoinformation but also rapid and correct renewal of the geoinformation. NGII (National Geographic Information Institute) has been studying for improvement of digital map that was constructed by the result of the 1st NGIS project. Through the construction of clean digital map, NGII constructed Framework Data to three kinds of formats (NGI, NDA, NRL). Framework Data was contained to other database, and provided the reference system of location or contents for combining geoinformation. Framework Data is consist of Data Set, Data Model and UFID (Unique Feature Identifier). It will be achieved as national infrastructure data. This paper attempts to explore a method of the update to practical framework data with realtime geoinformation on feature's creation, modification and destruction managed by 'Feature management agency' using UFID's process. Furthermore, it suggests a method which can provide important data in order to plan the Framework update with the land change ratio.

Analysis and Orange Utilization of Training Data and Basic Artificial Neural Network Development Results of Non-majors (비전공자 학부생의 훈련데이터와 기초 인공신경망 개발 결과 분석 및 Orange 활용)

  • Kyeong Hur
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.381-388
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    • 2023
  • Through artificial neural network education using spreadsheets, non-major undergraduate students can understand the operation principle of artificial neural networks and develop their own artificial neural network software. Here, training of the operation principle of artificial neural networks starts with the generation of training data and the assignment of correct answer labels. Then, the output value calculated from the firing and activation function of the artificial neuron, the parameters of the input layer, hidden layer, and output layer is learned. Finally, learning the process of calculating the error between the correct label of each initially defined training data and the output value calculated by the artificial neural network, and learning the process of calculating the parameters of the input layer, hidden layer, and output layer that minimize the total sum of squared errors. Training on the operation principles of artificial neural networks using a spreadsheet was conducted for undergraduate non-major students. And image training data and basic artificial neural network development results were collected. In this paper, we analyzed the results of collecting two types of training data and the corresponding artificial neural network SW with small 12-pixel images, and presented methods and execution results of using the collected training data for Orange machine learning model learning and analysis tools.

The Study for EV Charging Infrastructure connected with Microgrid (마이크로그리드와 연계된 전기자동차 충전인프라에 관한 연구)

  • Hun Shim
    • Journal of Internet of Things and Convergence
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    • v.10 no.1
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    • pp.1-6
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    • 2024
  • In order to increase the use of electric vehicles (EVs) and minimize grid strain, microgrid using renewable energy must take an important role. Microgrid may use fossil fuels such as small diesel power, but in many cases, they can be supplied with energy from renewable energy, which is an eco-friendly energy source. However, renewable energy such as solar and wind power have variable output characteristics. Therefore, in order to meet the charging and discharging energy demands of electric vehicles and at the same time supply load power stably, it is necessary to review the configuration of electric vehicle charging infrastructure that utilizes diesel power or electric vehicle-to-grid (V2G) as a parallel energy source in the microgrid. Against this background, this study modelized a microgrid that can stably supply power to loads using solar power, wind power, diesel power, and V2G. The proposed microgrid uses solar power and wind power generation as the primary supply energy source to respond to power demand, and determines the operation type of the load's electric vehicles and the rotation speed of the load synchronous machine to provide stable power from diesel power for insufficient generations. In order to verify the system performance of the proposed model, we studied the stable operation plan of the microgrid by simulating it with MATLAB /Simulink.

Modeling the Effect of Intake Depth on the Thermal Stratification and Outflow Water Temperature of Hapcheon Reservoir (취수 수심이 합천호의 수온성층과 방류 수온에 미치는 영향 모델링)

  • Sun-A Chong;Hye-Ji Kim;Hye-Suk Yi
    • Journal of Environmental Impact Assessment
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    • v.32 no.6
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    • pp.473-487
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    • 2023
  • Korea's multi-purpose dams, which were constructed in the 1970s and 1980s, have a single outlet located near the bottom for hydropower generation. Problems such as freezing damage to crops due to cold water discharge and an increase the foggy days have been raised downstream of some dams. In this study, we analyzed the effect of water intake depth on the reservoir's water temperature stratification structure and outflow temperature targeting Hapcheon Reservoir, where hypolimnetic withdrawal is drawn via a fixed depth outlet. Using AEM3D, a three-dimensional hydrodynamic water quality model, the vertical water temperature distribution of Hapcheon Reservoir was reproduced and the seasonal water temperature stratification structure was analyzed. Simulation periods were wet and dry year to compare and analyze changes in water temperature stratification according to hydrological conditions. In addition, by applying the intake depth change scenario, the effect of water intake depth on the thermal structure was analyzed. As a result of the simulation, it was analyzed that if the hypolimnetic withdrawal is changed to epilimnetic withdrawal, the formation location of the thermocline will decrease by 6.5 m in the wet year and 6.8 m in the dry year, resulting in a shallower water depth. Additionally, the water stability indices, Schmidt Stability Index (SSI) and Buoyancy frequency (N2), were found to increase, resulting in an increase in thermal stratification strength. Changing higher withdrawal elevations, the annual average discharge water temperature increases by 3.5℃ in the wet year and by 5.0℃ in the dry year, which reduces the influence of the downstream river. However, the volume of the low-water temperature layer and the strength of the water temperature stratification within the lake increase, so the water intake depth is a major factor in dam operation for future water quality management.

The Relationship between Leisure Passion, Self-Realization, and Psychological Well-being of Participants in Leisure Activities of Baby boomers (베이비붐세대 여가활동 참여자의 여가열정과 자아실현 및 심리적 행복감의 관계)

  • Kyung-A, Oh
    • Journal of the Korean Applied Science and Technology
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    • v.40 no.5
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    • pp.1136-1148
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    • 2023
  • The purpose of this study was to examine the relationship between leisure passion, self-realization, and psychological well-being for baby boomers who regularly participate in leisure activities, and to provide basic data for baby boomers to participate in leisure sports based on this. This study required the study of baby boomers born between 1995 and 1963 who participated in leisure activities in Seoul and Gyeonggi Province to fill out a questionnaire using the convenient sampling method among non-probability sampling. Frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structural equation model analysis were conducted through the SPSS 20.0 program to achieve the purpose of the study with a total of 310 data processing analysis. The results of this study are as follows. First, it was found that leisure passion has an effect on self-realization. Second, self-realization is affecting psychological well-being. Third, it was found that leisure passion affects psychological well-being. Therefore, it was found that all paths had a statistically significant effect on the relationship between leisure passion, self-realization, and psychological well-being according to the leisure participation of baby boomers. In addition, leisure passion was found to have an indirect effect on psychological well-being, indicating that it had a mediating effect.

A Study on Real-time Autonomous Driving Simulation System Construction based on Digital Twin - Focused on Busan EDC - (디지털트윈 기반 실시간 자율주행 시뮬레이션 시스템 구축 방안 연구 - 부산 EDC 중심으로 -)

  • Kim, Min-Soo;Park, Jong-Hyun;Sim, Min-Seok
    • Journal of Cadastre & Land InformatiX
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    • v.53 no.2
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    • pp.53-66
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    • 2023
  • Recently, there has been a significant interest in the development of autonomous driving simulation environment based on digital twin. In the development of such digital twin-based simulation environment, many researches has been conducted not only performance and functionality validation of autonomous driving, but also generation of virtual training data for deep learning. However, such digital twin-based autonomous driving simulation system has the problem of requiring a significant amount of time and cost for the system development and the data construction. Therefore, in this research, we aim to propose a method for rapidly designing and implementing a digital twin-based autonomous driving simulation system, using only the existing 3D models and high-definition map. Specifically, we propose a method for integrating 3D model of FBX and NGII HD Map for the Busan EDC area into CARLA, and a method for adding and modifying CARLA functions. The results of this research show that it is possible to rapidly design and implement the simulation system at a low cost by using the existing 3D models and NGII HD map. Also, the results show that our system can support various functions such as simulation scenario configuration, user-defined driving, and real-time simulation of traffic light states. We expect that usability of the system will be significantly improved when it is applied to broader geographical area in the future.

Cellular Aging Inhibitory Effect of Perilla Leaf Extract on D-Galactose Induced C2C12 Myoblasts (D-갈락토스 유도 C2C12 근원세포에 대한 자소엽 추출물의 세포 노화 억제 효과)

  • Song-Mi Park;Sung-Woo Cho;Yung-Hyun Choi
    • Journal of Korean Medicine Rehabilitation
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    • v.34 no.2
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    • pp.15-28
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    • 2024
  • Objectives We used the D-galactose (D-gal) induced C2C12 myoblast senescence model to investigate whether ethanol extract of Perilla. fructescens leaves (EEPF) could delay cellular senescence and regulate related mechanisms. Methods C2C12 myogenic cells were cultured in an incubator under 37 ℃ and 5% CO2 conditions. EEPF, dried perilla leaves were pulverized and extracted at 1:10 (v/v) at 50 ℃ for 4 hours. Cell counting kit-8 and western blot analysis was performed. Annexin V-FITC apoptosis detection kit and DAPI staining was applied. Catalase (CAT), glutathione peroxidase (GSH-Px), total antioxidant capacity (T-AOC), superoxide dismutase (SOD), and malondialdehyde analysis kits were used. To measure the level of reactive oxygen species generation, staining and flow cytometry was used. To analyze the mitochondrial activity, membrane potential changes were measured using JC-1. 𝛽-gal activity was analyzed using SA-𝛽-gal staining solution, and DNA damage was analyzed by using 𝛾-H2AX. Quantikine ELISA kit was used to analyze inflammatory cytokine production. Results According to the results of this study, EEPF significantly alleviated the decrease in cell viability in C2C12 cells treated with D-gal and suppressed the decrease in the expression of proliferating cell nuclear antigen. EEPF also markedly blocked D-gal-induced C2C12 cell apoptosis and restored reduced activity of CAT, GSH-Px, T-AOC, SOD. In addition, EEPF suppressed the decrease in 𝛽-galactosidase activity, the induction of DNA damage and the increase in expression of senescence-associated secretory phenotype proteins such as p16, p53 and p21 in D-gal-treated C2C12 cells. Furthermore, EEPF significantly attenuated D-gal-induced production and expression of inflammatory cytokines such as interleukin (IL)-6 and IL-18. Conclusions The results of this study indicate that EEPF can be used as a potential candidate for the prevention and treatment of muscle aging.

Evaluation of Changes in Particle Size and Production of Sand and Cake Produced in Wet Aggregate Production Process (습식 골재 생산 공정에서 모래 및 케이크 발생량 평가)

  • Young-Wook Cheong;Jin-Young Lee;Sei-Sun Hong
    • Economic and Environmental Geology
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    • v.57 no.2
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    • pp.177-184
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    • 2024
  • This study was conducted to find a way to reduce the production of cakes generated in the domestic aggregate production process. Cakes from 8 wet aggregate producers were collected and particle size was analyzed. Samples were collected step by step from an aggregate producer A, particle size analysis was performed, and the material balance was calculated before and after an sand recovery unit by modeling the production process. As a result of the particle size analysis of eight cakes, one sample contained 50% sand, and the rest contained about 5% to 25% sand. The results showing that the cake contained a variety of sand in cakes may indicate that the recovery efficiency of the sand recovery units in the field varied. Sieve analysis of the samples showed that the generation of sand particles increased 2.8 times during the third crushing compared to the second crushing, and more cake particles were generated. As a result of simulating the sand recovery unit model, the lower the cut point of the cyclone and dewatering screen, the higher the sand production and the less cake production appeared. In order to reduce the production of cake in the field, it was determined that an optimal operation of the sand recovery unit was necessary in the aggregate production process.

What Concerns Does ChatGPT Raise for Us?: An Analysis Centered on CTM (Correlated Topic Modeling) of YouTube Video News Comments (ChatGPT는 우리에게 어떤 우려를 초래하는가?: 유튜브 영상 뉴스 댓글의 CTM(Correlated Topic Modeling) 분석을 중심으로)

  • Song, Minho;Lee, Soobum
    • Informatization Policy
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    • v.31 no.1
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    • pp.3-31
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    • 2024
  • This study aimed to examine public concerns in South Korea considering the country's unique context, triggered by the advent of generative artificial intelligence such as ChatGPT. To achieve this, comments from 102 YouTube video news related to ethical issues were collected using a Python scraper, and morphological analysis and preprocessing were carried out using Textom on 15,735 comments. These comments were then analyzed using a Correlated Topic Model (CTM). The analysis identified six primary topics within the comments: "Legal and Ethical Considerations"; "Intellectual Property and Technology"; "Technological Advancement and the Future of Humanity"; "Potential of AI in Information Processing"; "Emotional Intelligence and Ethical Regulations in AI"; and "Human Imitation."Structuring these topics based on a correlation coefficient value of over 10% revealed 3 main categories: "Legal and Ethical Considerations"; "Issues Related to Data Generation by ChatGPT (Intellectual Property and Technology, Potential of AI in Information Processing, and Human Imitation)"; and "Fear for the Future of Humanity (Technological Advancement and the Future of Humanity, Emotional Intelligence, and Ethical Regulations in AI)."The study confirmed the coexistence of various concerns along with the growing interest in generative AI like ChatGPT, including worries specific to the historical and social context of South Korea. These findings suggest the need for national-level efforts to ensure data fairness.

Enhancing Empathic Reasoning of Large Language Models Based on Psychotherapy Models for AI-assisted Social Support (인공지능 기반 사회적 지지를 위한 대형언어모형의 공감적 추론 향상: 심리치료 모형을 중심으로)

  • Yoon Kyung Lee;Inju Lee;Minjung Shin;Seoyeon Bae;Sowon Hahn
    • Korean Journal of Cognitive Science
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    • v.35 no.1
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    • pp.23-48
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    • 2024
  • Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.