• Title/Summary/Keyword: 컴퓨터공학 교육

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Program Plagiarism Detection based on X-treeDiff+ (X-treeDiff+ 기반의 프로그램 복제 탐지)

  • Lee, Suk-Kyoon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.4
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    • pp.44-53
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    • 2010
  • Program plagiarism is a significant factor to reduce the quality of education in computer programming. In this paper, we propose the technique of identifying similar or identical programs in order to prevent students from reckless copying their programming assignments. Existing approaches for identifying similar programs are mainly based on fingerprints or pattern matching for text documents. Different from those existing approaches, we propose an approach based on the program structur. Using paring progrmas, we first transform programs into XML documents by representing syntactic components in the programs with elements in XML document, then run X-tree Diff+, which is the change detection algorithm for XML documents, and produce an edit script as a change. The decision of similar or identical programs is made on the analysis of edit scripts in terms of program plagiarism. Analysis of edit scripts allows users to understand the process of conversion between two programs so that users can make qualitative judgement considering the characteristics of program assignment and the degree of plagiarism.

A Logical Simulation of Dynamic Natural Phenomena Based on Event Propagation Graph (사건 전파그래프에 기반한 동적인 자연현상의 논리적 시뮬레이션)

  • Park, Jung-Yong;Park, Jong-Hee
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.4
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    • pp.10-21
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    • 2001
  • This paper develops a logical simulation method for by dyversity of situations. Most existing systems, for example, games and infant tutoring systems lead users to virtual environment with unfolding situations, but are not designed to induce the change of the environment itself. In this paper, a logically simulated environment is created by defining situations and single events based on situation hierarchy structure. We elaborate the occurrence of events by classifying the causality. The occurrence or natural phenomena is dictated by physical laws and natural phenomena are expressed as the transition of the event based on event association. Specifically we define the source of the event for natural phenomena and we consider the existence of objects as a primary factor in event occurrence. The advantages of this approach include the reuse of events, that is, different events can be generated in the same flow with fresh conditions. This allows us to implement a more practical and logical environment. A drawback to this method is the difficulty in dividing a situation into events. The proposed method was implemented in the context of the change of season among natural phenomena.

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Implementation of A Plagiarism Detecting System with Sentence and Syntactic Word Similarities (문장 및 어절 유사도를 이용한 표절 탐지 시스템 구현)

  • Maeng, Joosoo;Park, Ji Su;Shon, Jin Gon
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.3
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    • pp.109-114
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    • 2019
  • The similarity detecting method that is basically used in most plagiarism detecting systems is to use the frequency of shared words based on morphological analysis. However, this method has limitations on detecting accurate degree of similarity, especially when similar words concerning the same topics are used, sentences are partially separately excerpted, or postpositions and endings of words are similar. In order to overcome this problem, we have designed and implemented a plagiarism detecting system that provides more reliable similarity information by measuring sentence similarity and syntactic word similarity in addition to the conventional word similarity. We have carried out a comparison of on our system with a conventional system using only word similarity. The comparative experiment has shown that our system can detect plagiarized document that the conventional system can detect or cannot.

Minimum-Cost Path Finding Algorithm in Real-Time For Computer Generated Force (실시간성을 고려한 가상군 최소비용 길 찾기 알고리즘)

  • Han, Chang-Hee;Min, Young-Hye;Park, Sang-Hyuk;Kim, Jai-Hoon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.1
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    • pp.17-25
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    • 2011
  • At the computer games, we can experience a variety of environments using a virtual object. It is similar to that be trained in War-game simulator of the defense. Actual soldiers and a computer-generated virtual group(Computer Generated Force: CGF) in 3-D virtual battlefield environment are training. However, path finding algorithm, one of the techniques of simulation models, to the current level only considers the shortest time path. So, this current level at the special situation of the army in the battlefield for selecting the optimal path is limited. The focus of this paper is to select the least-cost path using the deadline with several different mission conditions(METT+TC). For the only shortest time path algorithm and the least-cost path algorithm using dealine,($d_t$, one of METT+TC elements), Its usefulness is verifying the change of the move spent time(t) for all possible paths and the fighting power of the combat troops(Troops ability, a) through a comparison of the total cost of moves(c(t)). According to the results, when considering the deadline, the proposed algorithm saves about 62.5% of the maximum cost.

Directions for Developing Database Schema of Records in Archives Management Systems (영구기록물관리를 위한 기록물 데이터베이스 스키마 개발 방향)

  • Yim, Jin-Hee;Lee, Dae-Wook;Kim, Eun-Sil;Kim, Ik-Han
    • The Korean Journal of Archival Studies
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    • no.34
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    • pp.57-105
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    • 2012
  • The CAMS(Central Archives Management System) of NAK(National Archives of Korea) is an important system which receives and manages large amount of electronic records annually from 2015. From the point of view in database design, this paper analyzes the database schema of CAMS and discusses the direction of overall improvement of the CAMS. Firstly this research analyzes the tables for records and folders in the CAMS database which are core tables for the electronic records management. As a result, researchers notice that it is difficult to trust the quality of the records in the CAMS, because two core tables are entirely not normalized and have many columns whose roles are unknown. Secondly, this study suggests directions of normalization for the tables for records and folders in the CAMS database like followings: First, redistributing the columns into proper tables to reduce the duplication. Second, separating the columns about the classification scheme into separate tables. Third, separating the columns about the records types and sorts into separate tables. Lastly, separating metadata information related to the acquisition, takeover and preservation into separate tables. Thirdly, this paper suggests considerations to design and manage the database schema in each phase of archival management. In the ingest phase, the system should be able to process large amount of records as batch jobs in time annually. In the preservation phase, the system should be able to keep the management histories in the CAMS as audit trails including the reclassification, revaluation, and preservation activities related to the records. In the access phase, the descriptive metadata sets for the access should be selected and confirmed in various ways. Lastly, this research also shows the prototype of conceptual database schema for the CAMS which fulfills the metadata standards for records.

CoAID+ : COVID-19 News Cascade Dataset for Social Context Based Fake News Detection (CoAID+ : 소셜 컨텍스트 기반 가짜뉴스 탐지를 위한 COVID-19 뉴스 파급 데이터)

  • Han, Soeun;Kang, Yoonsuk;Ko, Yunyong;Ahn, Jeewon;Kim, Yushim;Oh, Seongsoo;Park, Heejin;Kim, Sang-Wook
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.4
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    • pp.149-156
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    • 2022
  • In the current COVID-19 pandemic, fake news and misinformation related to COVID-19 have been causing serious confusion in our society. To accurately detect such fake news, social context-based methods have been widely studied in the literature. They detect fake news based on the social context that indicates how a news article is propagated over social media (e.g., Twitter). Most existing COVID-19 related datasets gathered for fake news detection, however, contain only the news content information, but not its social context information. In this case, the social context-based detection methods cannot be applied, which could be a big obstacle in the fake news detection research. To address this issue, in this work, we collect from Twitter the social context information based on CoAID, which is a COVID-19 news content dataset built for fake news detection, thereby building CoAID+ that includes both the news content information and its social context information. The CoAID+ dataset can be utilized in a variety of methods for social context-based fake news detection, thus would help revitalize the fake news detection research area. Finally, through a comprehensive analysis of the CoAID+ dataset in various perspectives, we present some interesting features capable of differentiating real and fake news.

A Study on Creativity Convergence Competency for Developing Creativity Human Resources (창의융합인재 양성을 위한 일부 대학생의 창의융합역량 수준 분석)

  • Choi, Yong Keum;Oh, Tae-Jin;Lee, Hyun;Lim, Kunok;Hong, Ji-Heon;Jeong, Su Ra
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.1
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    • pp.656-664
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    • 2020
  • This study obtained basic data for developing human resources with creativity convergence competency by surveying and analyzing the level of creativity convergence competency of university students. The study was conducted from October 1, 2019 to November 10, 2019 on university students attending the departments of computer science, pharmaceutical engineering, physical therapy and dental hygiene. The data from 296 students was finally used for this study, and IBM SPSS/Win statics 23.0 programs were used to analyze the data. Students who graduated from Seoul/Gyeonggi High School or those students with high undergraduate satisfaction were found to have high creativity convergence ability, and these results were statistically significant. Further, the group of students who had experience with Campus/Suburban competition, Global Competency training/ International exchange programs or the Capstone Design/Team Based Project showed high creativity convergence competency, and these results were statistically significant. Thus, this study identified the necessity of developing and operating various extra-curricular programs at education institutes in order to enhance students' creativity convergence capability.

Analysis of Customer Evaluations on the Ethical Response to Service Failures of Foodtech Serving Robots (푸드테크 서빙로봇의 서비스 실패에 대한 직업윤리적 대응에 대한 고객 평가 분석)

  • Han, Jeonghye;Choi, Younglim;Jeong, Sanghyun;Kim, Jong-Wook
    • Journal of Service Research and Studies
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    • v.14 no.1
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    • pp.1-12
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    • 2024
  • As the service robot market grows among the food technology industry, the quality of robot service that affects consumer behavioral intentions in the restaurant industry has become important. Serving robots, which are common in restaurants, reduce employee work through order and delivery, but because they do not respond to service failures, they increase customer dissatisfaction as well as increase employee work. In order to improve the quality of service beyond the simple function of receiving and serving orders, functions of recovery effort, fairness, empathy, responsiveness, and certainty of the process after service failure, such as serving employees, are also required. Accordingly, we assumed the type of failure of restaurant serving service as two internal and external factors, and developed a serving robot with a vocational ethics module to respond with a professional ethical attitude when the restaurant serving service fails. At this time, the expression and action of the serving robot were developed by adding a failure mode reflecting failure recovery efforts and empathy to the normal service mode. And by recruiting college students, we tested whether the service robot's response to two types of service failures had a significant effect on evaluating the robot. Participants responded that they were more uncomfortable with service failures caused by other customers' mistakes than robot mistakes, and that the serving robot's professional ethical empathy and response were appropriate. In addition, unlike the robot's favorability, the evaluation of the safety of the robot had a significant difference depending on whether or not a professional ethical empathy module was installed. A professional ethical empathy response module for natural service failure recovery using generative artificial intelligence should be developed and mounted, and the domestic serving robot industry and market are expected to grow more rapidly if the Korean serving robot certification system is introduced.

A Study DH the Identification Of Critical Intelligent Information Technologies and Application Areas in the Defence Side (국방부문 핵심지능정보기술 식별 및 활용방안 연구)

  • 김화수;이승구
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.11a
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    • pp.407-416
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    • 2000
  • 국방 부문에 종사하는 관리자들은 국방정보시스템 사업관리에 있어서 최신정보기술에 대한 기본적인 사항은 알고있어야 효율적이고 효과적이며 성공적인 사업관리를 진행할 수 있을 것이다. 국방 부문에 종사하는 관리자들이 저비용 고효율의 국방정보시스템을 건설하고 운영 유지관리 하기 위하여 알아야 할 핵심 및 최신정보기술은 크게 인공지능기술, 멀티미디어 정보화 기술, 가상현실 기술, 시뮬레이션 기술, 텔레프레즌스 기술, 나노테크놀로지 기술, 데이터베이스 기술, 병렬처리 기술, 로봇공학 기술, 소프트웨어 공학에 관련된 기술 등이 있다. 그러나 국방부문에 종사하는 정보통신 전문 인력을 제외한 관리자들이 국방관련 사업관리를 수행하면서 정보기술에 대한 이해 수준이 비교적 낮기 때문에 효율적으로 국방사업을 준비, 계획, 추진하기 어려운 실정이다. 따라서 국방부문에 종사하는 관리자들이 정보기술을 알기 쉽게 이해할 수 있도록 국방부문 핵심지능형정보기술 발전 및 군 활용방안을 이해하기 쉽도록 작성하며 효율적인 사업관리가 이루어질 수 있는 방안을 연구하였다. 본 논문은 국방부문핵심 지능정보기술 식별 및 활용방안을 연구하여 핵심적으로 식별된 사항들을 우리 국방부문의 $C^4$I(지휘, 통제, 통신, 컴퓨터시스템)시스템, 내장형 무기시스템, 각종 교육훈련 정보시스템, 자원관리 정보시스템 등에 어떻게 적용할 것이며 적용시 기대효과는 무엇인가를 제시토록 하여 국방부문에 종사하는 관리자들이 각종 국방사업을 조정, 통제, 확인, 감독, 준비/계획하면서 참고하여 저비용 고효율의 국방관련 각층 사업을 관리할 수 있는 능력을 배양시키도록 연구를 수행하였다. 국방관련 각종 사업을 관리할 수 있는 능력을 배양시키도록 연구를 수행하였다. 국방부문 핵심지능정보기술 발전 및 활용 방안에 포함될 주요 내용을 요약하여 제시하였다.의 경향성을 나타내는 오차 주기(error cyc1e)를 이용함으로써 고객들의 수요의 경향성을 좀 더 세밀한 부분까지 파악할 수 있게 해 준다.ction, secondary electron microscopy, atomic force microscoy, $\alpha$-step, Raman scattering spectroscopu, Fourier transform infrared spectroscopy 및 micro hardness tester를 이용하여 기판 bias 전압이 DLC 박막의 특성에 미치는 영향을 조사하였다. 분석결과 본 연구에서 제작된 DLC 박막은 탄소와 수소만으로 구성되어 있으며, 비정질 상태임을 알 수 있었다. 기판 bias 전압의 증가에 따라 박막의 두께가 감소됨을 알 수 있었고, -150V에서는 박막이 거의 만들어지지 않았으며, -200V에서는 기판 표면이 식각되었다. 이것은 기판 bias 전압과 ECR 플라즈마에 의한 이온충돌 효과 때문으로 판단되며, 150V 이하에서는 증착되는 양보다 re-sputtering 되는 양이 더 많을 것으로 생각된다. 기판 bias 전압을 증가시킬수록 플라즈마에 의한 이온충돌 현상이 두드러져 탄소와 결합하고 있던 수소원자들이 떨어져 나가는 탈수소화 (dehydrogenation) 현상을 확인할 수 있었으며, 이것은 C-H 결합에너지가 C-C 결합이나 C=C 결합보다 약하여 수소 원자가 비교적 해리가 잘되므로 이러한 현상이 일어난다고 판단된다. 결합이 끊어진 탄소 원자들은 다른 탄소원자들과 결합하여 3차원적 cross-link를 형성시켜 나가면서 내부 압축응력을 증가시키는 것으로 알려져 있으며, hardness 시험 결과로 이것을 확인할 수 있었다. 그리고 표면거칠기는 기판 bias 전압을 증가시킬수록 더 smooth 해짐을 확인

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Trends in the Use of Artificial Intelligence in Medical Image Analysis (의료영상 분석에서 인공지능 이용 동향)

  • Lee, Gil-Jae;Lee, Tae-Soo
    • Journal of the Korean Society of Radiology
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    • v.16 no.4
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    • pp.453-462
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    • 2022
  • In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.