• Title/Summary/Keyword: 개별 시스템

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The Present and Future of Service Science (서비스학의 현재와 미래)

  • Hyunsoo Kim
    • Journal of Service Research and Studies
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    • v.12 no.4
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    • pp.139-163
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    • 2022
  • This study analyzes the past and present of service science research as a central discipline that will lead a new economy and society, and presents a guide for future research. In the 21st century, service research has developed into a new discipline that is different from the existing service studies. Service science is a discipline that collectively refers to all research related to services. This study analyzes this development process and suggests the direction of future service science research. First, we analyze the research before the birth of service science, an early model of service studies. And the early research on the birth of service science is analyzed. Through this process, the service science framework that expanded and developed the initial service science is analyzed. We introduce each field of service science, which is a new innovation of the existing academic system from a modern perspective, and analyzes the structure of the service philosophy that is the basis of independent academic fields. And we suggest the future direction of service science research. The direction of paradigm innovation research of existing individual disciplines is presented first. As an example, innovation from existing business administration to service business administration is introduced. We also suggest a new economic and social system research direction that requires the convergence of multiple academic fields. Finally, we present a direction for multidimensional, broad-based convergence research. We suggest that the future of service science can be the process of reverting back to integration and convergence, centered on humans and the world, of the disciplines that have continued to diverge in the history. We present a model in which all disciplines are reintegrated into service science as the Eastern and Western spirits converge.

Understanding User Perception of Generative AI and Copyright of AI-Generated Outputs: focusing on differences by user group (생성 AI와 AI 창작물 저작권에 대한 사용자의 인식 연구: 사용자 그룹의 차이를 중심으로)

  • Dahye Choi;Jungyong Kim;Daeun Han;Changhoon Oh
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.777-786
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    • 2023
  • Generative AI systems are expected to be more widely utilized. However, relatively little attention has been paid to understanding how users perceive and accept generative AI results. To identify strategies for increasing the future use of generative AI and prepare for potential issues, we organized design workshop for the general user group and the designer group. They created artwork utilizing Novel AI and semi-structured interview was followed to evaluate their attitudes toward generative AI and its copyright. Results indicate that the general public views generative AI positively, while the design-related group views it quite negatively. The participants expressed concerns as to the misuse the system, specifically related to copyright issues. People who are likely to utilize generative AI outcomes have insisted more strongly that copyrights should be their own. Those working in the design field highly evaluated the possibility of using generative AI in their work. Copyright perceptions were not significantly influenced by users' satisfaction or their level of involvement in the creation process. We discuss design implications for interfaces using generative AI based on the findings.

Method of Earthquake Acceleration Estimation for Predicting Damage to Arbitrary Location Structures based on Artificial Intelligence (임의 위치 구조물의 손상예측을 위한 인공지능 기반 지진가속도 추정방법 )

  • Kyeong-Seok Lee;Young-Deuk Seo;Eun-Rim Baek
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.3
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    • pp.71-79
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    • 2023
  • It is not efficient to install a maintenance system that measures seismic acceleration and displacement on all bridges and buildings to evaluate the safety of structures after an earthquake occurs. In order to maintain this, an on-site investigation is conducted. Therefore, it takes a lot of time when the scope of the investigation is wide. As a result, secondary damage may occur, so it is necessary to predict the safety of individual structures quickly. The method of estimating earthquake damage of a structure includes a finite element analysis method using approved seismic information and a structural analysis model. Therefore, it is necessary to predict the seismic information generated at arbitrary location in order to quickly determine structure damage. In this study, methods to predict the ground response spectrum and acceleration time history at arbitrary location using linear estimation methods, and artificial neural network learning methods based on seismic observation data were proposed and their applicability was evaluated. In the case of the linear estimation method, the error was small when the locations of nearby observatories were gathered, but the error increased significantly when it was spread. In the case of the artificial neural network learning method, it could be estimated with a lower level of error under the same conditions.

Movie Recommended System base on Analysis for the User Review utilizing Ontology Visualization (온톨로지 시각화를 활용한 사용자 리뷰 분석 기반 영화 추천 시스템)

  • Mun, Seong Min;Kim, Gi Nam;Choi, Gyeong cheol;Lee, Kyung Won
    • Design Convergence Study
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    • v.15 no.2
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    • pp.347-368
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    • 2016
  • Recently, researches for the word of mouth(WOM) imply that consumers use WOM informations of products in their purchase process. This study suggests methods using opinion mining and visualization to understand consumers' opinion of each goods and each markets. For this study we conduct research that includes developing domain ontology based on reviews confined to "movie" category because people who want to have watching movie refer other's movie reviews recently, and it is analyzed by opinion mining and visualization. It has differences comparing other researches as conducting attribution classification of evaluation factors and comprising verbal dictionary about evaluation factors when we conduct ontology process for analyzing. We want to prove through the result if research method will be valid. Results derived from this study can be largely divided into three. First, This research explains methods of developing domain ontology using keyword extraction and topic modeling. Second, We visualize reviews of each movie to understand overall audiences' opinion about specific movies. Third, We find clusters that consist of products which evaluated similar assessments in accordance with the evaluation results for the product. Case study of this research largely shows three clusters containing 130 movies that are used according to audiences'opinion.

Toward understanding learning patterns in an open online learning platform using process mining (프로세스 마이닝을 활용한 온라인 교육 오픈 플랫폼 내 학습 패턴 분석 방법 개발)

  • Taeyoung Kim;Hyomin Kim;Minsu Cho
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.285-301
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    • 2023
  • Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

Development of an IMU-based Wearable Ankle Device for Military Motion Recognition (군사 동작 인식을 위한 IMU 기반 발목형 웨어러블 디바이스 개발)

  • Byeongjun Jang;Jeonghoun Cho;Dohyeon Kim;Kyeong-Won Park
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.23-34
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    • 2023
  • Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.

A Study on the Analysis of Factors Affecting the Development of Specialized Libraries (전문도서관 발전에 영향을 미치는 요인 분석에 관한 연구)

  • Eunhyoung Kim;Younghee Noh
    • Journal of the Korean Society for information Management
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    • v.40 no.2
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    • pp.81-114
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    • 2023
  • In this study, a survey was conducted targeting specialized librarians, and the impact on the work area according to changes in the internal and external environment and policy support measures was analyzed. In this study, we tried to derive factors that affect library development and policy suggestions accordingly. As a result of the study, first, it was confirmed that 58.3% of the negative opinions in terms of the importance of library development plans were positive in recognition of the role of library status within individual institutions. Second, in order to increase the status of specialized libraries, it was found that awareness of academic research activities was necessary by recognizing the importance of major functions and roles. Third, among the comprehensive library development plans, the recognition of specialized libraries and operational evaluation was the highest in recognition of the expansion of national public information services to the public. In addition, it was confirmed that among the five-year development strategies, the policy that should be implemented first is the preference for updating the status of specialized libraries and establishing a system for investigation. Fourth, as a result of analyzing effective alternatives and improvement indicators to increase the participation rate in library operation evaluation, the weighting of the "institutional library operation evaluation" item in the evaluation item of public enterprises was the highest at 4.01 on average. Therefore, for the development of specialized libraries, it was recognized as the most urgent task to establish a system that can comprehensively grasp the current status of specialized libraries as well as active academic research and support them.

Analysis of data on prevention of school violence based on AI unsupervised learning (AI 비지도 학습 기반의 학교폭력 예방 데이터 분석)

  • Jung, Soyeong;Ma, Youngji;Koo, Dukhoi
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.85-91
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    • 2021
  • School violence has long been recognized as a social problem, and various efforts have been made to prevent it. In this study, we propose a system that can prevent school violence by analyzing data on the frequency of conversations between students, and identify peer relationships. The frequency of conversations between students in the class was quantified using a rating scale questionnaire, and this data was grouped into the appropriate number of clusters using the K-means algorithm. Additionally, the homeroom teacher observed the frequency and nature of conversations between students, and targeted specific individuals or groups for counseling and intervention, with the aim of reducing school violence. Data analysis revealed that the teachers' qualitative observations were consistent with the quantified data based on student questionnaires, and therefore applicable as quantitative data towards the identification and understanding of student relationships within the classroom. The study has potential limitations. The data used is subjective and based on peer evaluations which can be inconsistent as the students may use different criteria to evaluate one another. It is expected that this study will help homeroom teachers in their efforts to prevent school violence by understanding the relationships between students within the classroom.

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Water resources planning for the Sesan and Srepok river basin in Vietnam using DSS-2S based on MIKE Hydro Basin (MIKE Hydro Basin 기반 DSS-2S를 활용한 베트남 Sesan 및 Srepok 강 유역 수자원 계획 수립)

  • Choi, Byung Man;Ko, Ick Hwan;Kim, Jeongkon;Pi, Wan Seop;Oh, Yoon Keun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.43-43
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    • 2021
  • Sesan강과 Srepok강은 베트남, 캄보디아, 라오스가 공유하는 3S강 유역 (Sesan강, Srepok강, Sekong강)의 일부로 국제 공유하천으로 관리되고 있다. 3S강 유역은 Mekong강의 중요한 지류이며 Mekong강 유역의 상당 부분을 구성한다(Mekong강 유역 면적의 10%, 연간 총 유출량의 20%). 베트남에 속해 있는 Sesan강 유역면적은 11,255km2, Srepok강 유역면적은 18,162km2이다. Sesan강과 Srepok강의 상류는 베트남 중부 고원의 긴 산맥에 위치하고 있으며, 하류는 캄보디아에 위치해 있어 상·하류간 긴밀한 협력이 필요하다. Sesan강과 Srepok강 유역은 기후변화에 따른 홍수, 가뭄, 수력발전소 건설로 인한 유출량 변동에 따른 상·하류 분쟁, 사면침식 및 퇴적 등 많은 문제와 도전에 직면할 것으로 예측되고 있다. 본 연구에서는 World Bank의 "Viet Nam Mekong Integrated Water Resources Management (M-IWRM) Project의 일환으로 베트남 정부 차원에서 처음으로 구축한 수자원관리 의사결정지원시스템인 "DSS-2S"를 활용하여, Sesan-Srepok강 유역의 수자원 계획을 수립하였다. DSS-2S는 MIKE Hydro Basin을 기반으로 SWAT모델 등과 연계 하여 구축되었다. DSS-2S는 2S 유역의 모든 주요 하천과 지류를 반영하였으며. 여기에는 17개의 수력발전 댐과 주요 지류에서 용량이 3백만 m3 이상인 기타 저수지가 포함되었다. 이 보다 작은 용량의 저수지는 대표적인 저수지로 그룹화 되어 반영되었다. 기후변화 및 사회-경제적 발전계획 등을 반영하여, 2030년과 2050년을 목표연도로 생활, 공업, 농업, 관광, 유지용수 등 용수 수요를 추정하였다. 50% 및 85% 빈도의 공급 가능성을 고려하여 물 배분은 물 수요를 충족하고 지하수 개발 최소화를 기준으로 고려되었다. 분석 결과에 의하면 2S강 유역의 총 수자원은 32.2억 m3으로 그중 지표수자원은 29.2억 m3, 안정적으로 이용 가능한 지하수자원은 2.97억 m3으로 분석 되었으며, 지표수와 지하수 연계를 고려하면 전체 2S 강 유역에 물 부족하지는 않으나, 개별 공급 지점을 고려할 때 4월과 5월에 일부 지역에서 물 부족이 나타날 것으로 예측 된다. 장래 물 부족 해결을 위한 대안들을 제시하였으며, 본 성과는 베트남 중앙 정부의 장기수자원 종합계획 수립의 기본 자료로 활용 될 예정이다.

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Risk Assessment on the Water BOT Business Participation in China : Domestic EPC Contractor's View (해외기업의 중국 수처리 BOT시장 참여 저해 위험요인 분석 : 국내 EPC 건설기업의 관점)

  • Choi, Jae-ho;Li, Shoushuang;Lee, Seungho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5D
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    • pp.695-703
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    • 2008
  • China water market has huge potential for increased use of BOT mode and one of the most attractive markets of doing business. However, the current China water BOT market shows that many foreign companies are retreating from the market while Chinese water companies fast growing. From the view no domestic companies have track records in China BOT water market, the research identified twenty market access barriers in terms of construction laws, regulations, BOT-related policy and the recent market situation. These are evaluated based on interview results with 10 professionals direct or indirect having a China water BOT experience. All the factors are found to be highly influential to foreign company's decision on the market participation. Among those, no fixed return policy and low water price, difficulty in water price adjustment and approval, and no government guarantees, all directly related to the project viability and under the control of government, were the most critical factors, implying government's role is the key in increasing the market competition by attracting more foreign participation on the market. In addition, new construction law regulating foreign EPC contractor's construction work, namely Decree 113, and requirement of applying competitive bidding in selecting EPC contractor in a BOT project are also considered signigicant barriers on foreign participation, which contradicts international norm and therefore necessitates an adjustment on current decision process in domestic companies.