• Title/Summary/Keyword: 기술 분류

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Exploring the National Competency Standard Curriculum of Graduate School Professors (직무능력표준의 교육과정도입에 대한 전문대학원 교수자 역량)

  • Kim, Jin-Hee;Do, Jaewoo
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.6 no.10
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    • pp.145-153
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    • 2016
  • The purpose of the study is to draw competencies of faculty members at graduate school faculty to implements the NCS-based curriculum. A set of competency was deductively derived from a total of three professors and consultants with more than ten-year experiences and has been involved in developing the college curriculum. The political endeavors of the Korean government toward the competency-based education have been implemented as a movement to the NCS-based curriculum. The requirements for the reorganization of curriculum and education system as well as cooperation among faculty, industry, region and development part of NCS were suggested for the activation of NCS based education and the operation of NCS. However, one of the most critical factors in introducing and implementing the NCS-based curriculum is the role of faculty members. Therefore, it is an urgent issue to equip the faculties with required competencies. Result showed that the competencies required professors at graduate school for the NCS-based curriculum implementation were classified into four areas: marco-level curriculum development; micro-level course design; knowledge across areas; and attitude across areas.

An Index Structure for Efficiently Handling Dynamic User Preferences and Multidimensional Data (다차원 데이터 및 동적 이용자 선호도를 위한 색인 구조의 연구)

  • Choi, Jong-Hyeok;Yoo, Kwan-Hee;Nasridinov, Aziz
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.7
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    • pp.925-934
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    • 2017
  • R-tree is index structure which is frequently used for handling spatial data. However, if the number of dimensions increases, or if only partial dimensions are used for searching the certain data according to user preference, the time for indexing is greatly increased and the efficiency of the generated R-tree is greatly reduced. Hence, it is not suitable for the multidimensional data, where dimensions are continuously increasing. In this paper, we propose a multidimensional hash index, a new multidimensional index structure based on a hash index. The multidimensional hash index classifies data into buckets of euclidean space through a hash function, and then, when an actual search is requested, generates a hash search tree for effective searching. The generated hash search tree is able to handle user preferences in selected dimensional space. Experimental results show that the proposed method has better indexing performance than R-tree, while maintaining the similar search performance.

Mentoring activity Effects for Multicultural Students : Using Logic Model (다문화학생을 위한 멘토링 활동 효과 : 논리모델을 중심으로)

  • Lee, Mijung;Kim, Jinhee;Park, Misuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.5 no.4
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    • pp.435-442
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    • 2015
  • The purpose of this study is to examine the effect of mentoring program using logic model in university students. We surveyed 40 mentors who participated mentoring program in 2014. Data collection were open-ended questions. Questions was made of with a steps in logic model and content analysis was carried out. The results are as follows: first, according to the step of the inputs, many students questioned said that public relations, selection process, matching, orientations, activity costs was proper. Secondly, in the activities, it was showed that mentor met firstly mentee with teacher in school and mentoring activities comprised 80% of studying and 20% of counseling and experiencing. third, in the outputs, most of participants expressed satisfaction in mentoring period, time, place. Lastly, in the outcomes, this program affected both mentor and mentee with cognitive, emotional and behavior development. Consequentially, this results have influence on improvement of following mentoring programs.

User Interface Design through Mental Accounting : A Case Study on Account book Application (멘탈 어카운팅을 활용한 사용자 인터페이스 디자인 : 가계부 어플리케이션 사례연구)

  • Ga, Ye-Rin;Lee, Jooyoup
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.7
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    • pp.865-874
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    • 2017
  • According to Mental accounting theory, humans sort money according to their psychological purpose. It plays a major role as a means of self-control. However, humans sometimes make mistakes that violate very simple economic principles. Many consumers experience this mistakes. So consumers use account book to manage their income and expenses. These days, they use mobile account book applications. And because of platform characteristics, there are various user interfaces. This paper examines an efficient user interface design that can reduce errors caused by mental accounting and support rational economic activities. For this, we compared and analyzed households exposed on top of Application store based on advanced research on Mental Accounting. Through this case study, We found some cases of efficient user interface for reasonable consumption. In further studies, We will design optimal account book's UI and do a usability test based on this.

A Study of Aggressive Driver Detection Combining Machine Learning Model and Questionnaire Approaches (기계학습 모델과 설문결과를 융합한 공격적 성향 운전자 탐색 연구)

  • Park, Kwi Woo;Park, Chansik
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.3
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    • pp.361-370
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    • 2017
  • In this paper, correlation analysis was performed between questionnaire and machine learning based aggressive tendency measurements. this study is part of a aggressive driver detection using machine learning and questionnaire. To collect two types tendency from questionnaire and measurements system, we constructed experiments environments and acquired the data from 30 drivers. In experiment, the machine learning based aggressive tendency measurements system was designed using a driver behavior detection model. And the model was constructed using accelerate and brake position data and hidden markov model method through supervised learning. We performed a correlation analysis between two types tendency using Pearson method. The result was represented to high correlation. The results will be utilize for fusing questionnaire and machine learning. Furthermore, It is verified that the machine learning based aggressive tendency is unique to each driver. The aggressive tendency of driver will be utilized as measurements for advanced driver assistance system such as attention assist, driver identification and anti-theft system.

A Study on User Interface and Control Method of Web-based Remote Control Platform (웹 기반 원격제어 플랫폼의 사용자 인터페이스와 제어 기법에 관한 연구)

  • Lee, Kangwon;Shin, Yejin;Lee, Yeonji;Seol, Soonuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.6
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    • pp.827-837
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    • 2017
  • Since the area of smart home has been attracting attention, researches have been conducted to control syntagmatically various electronic products with a single remote controller. Previous researches have developed a dedicated controller or an application that acts as a remote controller and controls electronic products by configuring control screen for each product. However, these approaches are not suitable for controlling various electronic products that should be controlled by configuring separate control screens for each product. In this paper, we propose a web-based remote control platform. We define universal user interfaces applicable to various devices by categorizing user interactions of electronic goods and implement them as APIs. By applying the APIs to IPTV and car navigation devices we show that it is possible to control them through only a web browser. We also propose a method to group multiple control requests in order to efficiently handle consecutive control requests and show the improved response time and data usage.

Efficient Thread Allocation Method of Convolutional Neural Network based on GPGPU (GPGPU 기반 Convolutional Neural Network의 효율적인 스레드 할당 기법)

  • Kim, Mincheol;Lee, Kwangyeob
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.10
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    • pp.935-943
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    • 2017
  • CNN (Convolution neural network), which is used for image classification and speech recognition among neural networks learning based on positive data, has been continuously developed to have a high performance structure to date. There are many difficulties to utilize in an embedded system with limited resources. Therefore, we use GPU (General-Purpose Computing on Graphics Processing Units), which is used for general-purpose operation of GPU to solve the problem because we use pre-learned weights but there are still limitations. Since CNN performs simple and iterative operations, the computation speed varies greatly depending on the thread allocation and utilization method in the Single Instruction Multiple Thread (SIMT) based GPGPU. To solve this problem, there is a thread that needs to be relaxed when performing Convolution and Pooling operations with threads. The remaining threads have increased the operation speed by using the method used in the following feature maps and kernel calculations.

A Study on Effective Interpretation of AI Model based on Reference (Reference 기반 AI 모델의 효과적인 해석에 관한 연구)

  • Hyun-woo Lee;Tae-hyun Han;Yeong-ji Park;Tae-jin Lee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.3
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    • pp.411-425
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    • 2023
  • Today, AI (Artificial Intelligence) technology is widely used in various fields, performing classification and regression tasks according to the purpose of use, and research is also actively progressing. Especially in the field of security, unexpected threats need to be detected, and unsupervised learning-based anomaly detection techniques that can detect threats without adding known threat information to the model training process are promising methods. However, most of the preceding studies that provide interpretability for AI judgments are designed for supervised learning, so it is difficult to apply them to unsupervised learning models with fundamentally different learning methods. In addition, previously researched vision-centered AI mechanism interpretation studies are not suitable for application to the security field that is not expressed in images. Therefore, In this paper, we use a technique that provides interpretability for detected anomalies by searching for and comparing optimization references, which are the source of intrusion attacks. In this paper, based on reference, we propose additional logic to search for data closest to real data. Based on real data, it aims to provide a more intuitive interpretation of anomalies and to promote effective use of an anomaly detection model in the security field.

Pilot Study on the Introduction of Stationary Fishery in Coastal Waters of Ulleungdo Island, thd East Sea of Korea (울릉도 해역의 정치성 구획어업 도입을 위한 시험 연구)

  • Yoon, Sung-Jin
    • Journal of Marine Life Science
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    • v.3 no.1
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    • pp.22-30
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    • 2018
  • In this study, pilot study on the introduction of stationary fishery was performed to solve the problem of fisheries resource reduction. The Fyke net, which is a test fishing net was selected considering the environment, operation and management costs of Ulleungdo, conditions that can be operated by small fishing vessels and personnel. As a result of 11 times survey using Fyke net from April to May 2017, 2,735 individuals and 983.4 kg caught and the dominant species were red seabream, yellowtail, olive flounder, mitra squid, horse mackerel, filefish, etc. In conclusion, if the production of squid, which is one of the major fisheries resources of Ulleungdo, is continuously decreased, it is considered that introduction of small-scale stationary fishery such as Fyke net would be useful as a means replace income of fishermen.

The Significance and Management of Hyporheic Zone (지표수-지하수 혼합대 의의와 관리 필요성)

  • Ko, Dongwoo;Lee, Namjoo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.283-283
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    • 2021
  • 혼합대는 지표수와 지하수의 수리적 교환이 일어나는 경계부로써 1) 수문학적 관점에서는 하도와 하상간의 물교환이 이루어지는 공간으로 다양한 물리적·화학적 작용이 발생, 2) 생지화학적인 관점에서는 하상 간극수 흐름에 의한 전이대(ecotone)를 형성하여 용존산소·영양물질·용존유기탄소의 이동뿐만이 아니라 지하수로부터 열에너지·무기염류의 공급을 유도하면서 높은 생지화학적 활동과 변환을 야기하는 산화·환원 반응구역, 3) 생태적인 관점에서는 저서생물과 지하 유기체종을 특징으로 하는 서식지이나 잠재적인 레퓨지움(refugium) 등의 관점에서 해석될 수 있다. 국내 하천환경의 생태학적 지속가능성을 위한 지표수-지하수 혼합대 관리에 대한 중요성이 점차 증대되고 있지만 우리나라는 여전히 지하수의 이용 및 보전과 지하수의 안정적인 수량·수질 확보를 목표로 관리를 추진하고 있다. 따라서, 실질적인 지표수-지하수 혼합대에서 발생하는 다양한 현상의 이해나 관리방안에 관한 연구는 아직 미비한 상황이다. 지표수-지하수 혼합대에 관한 보고서, 논문 등을 종합하여 혼합대의 영향인자를 살펴보면 1) 수리수문 특성에는 수리전도도·하천 수위·하천 유속·하천수 수온, 2) 수질 특성에는 유기오염물질·영양염류, 3) 수생태 특성에는 대형무척추동물 등으로 분류할 수 있다. 지금까지 단일 연구분야의 접근방법으로 다양한 현장측정기법 및 모델링을 통한 혼합대 연구가 수행되고 있지만, 혼합대가 가지는 환경적 중요성에 대한 이해와 인식이 부족하고, 혼합대 내부에서 발생하는 복합적인 프로세스로 인해 전문가들조차 연구에 어려움을 가질 것이다. 지표수-지하수 혼합대의 효율적인 관리를 위해서는 수리수문·수질·수생태 등 다양한 시각에서 접근하여 학제간 융합연구를 통해 기초 데이터를 상호교환하고, 기존의 혼합대 조사에 부족한 부분을 해결할 필요가 있다. 향후 하천 기저유출 및 혼합대 기초자료 구축, 혼합대 흐름 정량화, 하천복원사업에 의한 혼합대 영향 규명 등의 연구를 수행함으로써 혼합대를 체계적으로 관리할 수 있는 기술 방안을 제시할 필요가 있다.

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