• 한국통신학회논문지
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• 제35권7C호
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• pp.642-650
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• 2010

협력 스펙트럼 감지(collaborative spectrum sensing) 방식은 지역적으로 분산되어 있는 다수의 부 사용자(secondary user)들이 협력하여 주 사용자(primary user)의 활동을 감지하는 방법으로, 페이딩으로 인해 발생하는 검파 성능의 손실을 상당히 줄일 수 있는 것으로 알려져 있다. 현재까지 이 방식에 대한 대부분의 연구는 개별부 사용자들이 내린 스펙트럼 감지 결정이 통계적으로 서로 독립이라고 가정한 것에 기초한 것이다. 그러나 실제 상황에서는 음영 효과(shadowing effect)로 인해 이 가정이 유효하지 않은 경우가 발생한다. 본 논문에서는 부 사용자들이 직선상에 일정 간격으로 배치되고, 이웃하는 부 사용자의 스펙트럼 감지 결정사이에서만 상관 관계가 존재하는 경우를 대상으로 하여, 상관 정도가 협력 스펙트럼 감지 방식의 성능에 미치는 영향과 그에 따른 인지 무선 시스템의 전송 용량 변화를 분석하고자 한다. 이때 개별 부 사용자의 결정을 융합하는 규칙으로는 AND 규칙과 OR 규칙을 고려하였다. 분석 결과 AND 융합 규칙을 사용하는 경우가 OR 규칙을 사용하는 경우보다 전송용량 측면에서 우수하다는 점을 확인할 수 있었다.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.268-282
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• 2022

One of the most important technologies today is augmented reality technology, it allows users to experience the real world using virtual objects that are combined with the real world. This technology is interesting and has become applied in many sectors such as the shopping and medicine, also it has been included in the sector of education. In the field of education, AR technology has become widely used due to its effectiveness. It has many benefits, such as arousing students' interest in learning imaginative concepts that are difficult to understand. On the other hand, studies have proven that collaborative between students increases learning opportunities by exchanging information, and this is known as Collaborative Learning. The use of multimodal creates a distinctive and interesting experience, especially for students, as it increases the interaction of users with the technologies. The research aims at developing collaborative framework for developing achievement of 6th graders through designing a framework that integrated a collaborative framework with a multimodal input "hand-gesture and touch", considering the development of an effective, fun and easy to use framework with a multimodal interaction in AR technology that was applied to reformulate the genetics and traits lesson from the science textbook for the 6th grade, the first semester, the second lesson, in an interactive manner by creating a video based on the science teachers' consultations and a puzzle game in which the game images were inserted. As well, the framework adopted the cooperative between students to solve the questions. The finding showed a significant difference between post-test and pre-test of the experimental group on the mean scores of the science course at the level of remembering, understanding, and applying. Which indicates the success of the framework, in addition to the fact that 43 students preferred to use the framework over traditional education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• 대한안전경영과학회지
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• 제23권4호
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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• pp.75-81
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• 1997

A new DTPP (Desk-Top Program Production) system has been developed that enables multiple program producers (directors) working at different locations to collaborate over a computer network and prepare a single program for broadcasting. In this system, information is shared among users by exchanging data edited on non-linear editing terminals in program post-production work over a network in real time. In short, the new DTPP system provides a collaborative work space for producing TV programs. The system does not make use of a special server for collaborative work but rather multiple interconnected editing terminals having the same functions. In this configuration, data at a terminal which has just been edited by some operation is forwarded to all other connected terminals for updating. This form of information sharing, however, requires that some sort of data synchronizing method be established since multiple terminals are operating on the same data simultaneously. We therefore adopt a method whereby the system synchronizes the clocks on each terminal at the time of connection and sends an operation time stamp together with edited data. This enables most recently modified data to be identified and all information on all terminals to be updated appropriately. This paper provides an overview of this new collaborative DTPP system and describes the techniques for exchanging edited data and synchronizing data.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.56-66
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• 2023

The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.

• 한국비블리아학회지
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• 제24권1호
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• pp.149-169
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• 2013

본 연구는 이용자의 요구에 필요한 자원을 확보하기 위해 지역사회 내의 작은도서관들이 연계 및 협력하는 네트워크의 특성을 탐색적으로 분석하였다. 이를 위해 부천지역 내의 60개의 작은도서관을 대상으로 협력네트워크에 관한 관계데이터를 수집하였다. 네트워크의 구조적인 특성을 분석하기 위해 사회연결망분석법을 사용하였다. 분석 결과 공립작은도서관 간에는 연계가 긴밀하게 이루어지고 있었다. 중심성에서도 공립작은도서관이 상위그룹을 형성하였고 지방자치단체 등 외부 행위자를 포함한 네트워크에서도 공공도서관과 공립작은도서관이 중심적인 역할을 수행하고 있는 것으로 나타났다. 반면에 사립작은도서관은 대부분 고립되어 있어 연계가 미약한 것으로 분석되었다.

• 농촌계획
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• 제20권2호
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• pp.23-43
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• 2014

This study aims to analyze the affecting factors-construction of collaborative planning process and effect on Comprehensive Rural Village Development Project. To this end, targeting the 36 districts which were selected for 2004 Comprehensive Rural Village Development Project and completed their 2010 5-year projects, components of collaborative planning process and planning effect will be drawn and the affecting factors-construction of collaborative planning and effect on Comprehensive Rural Village Development Project will be analyzed below. According to the results of this study, the affecting factors of collaborative planning process of Comprehensive Rural Village Development Project on planning effect, The level of effect of individual component on endogenous variable appeared greatest mostly in the upper groups. In terms of the level of individual component effect, social learning process and interaction among participants affected greatest. The process of Comprehensive Rural Village Development Project is evaluated that it reflected collaborative planning theory of Healey enough. Therefore, in the course of Comprehensive Rural Village Development Project progress, collaborative planning model must pass social learning process and interaction among participants which are the most important components out of collaborative planning process as we saw in the upper groups. And in order to maximize the performance and results of Comprehensive Rural Village Development Project, the following sequential affecting factors model as Figure 7 must be suggested as optimal collaborative planning models of Comprehensive Rural Village Development Project. Based on the results of the study, the policy implication was drawn as follows. First, systematic supplementations in the form of a consultative body are required to perform Comprehensive Rural Village Development Project efficiently. Second, network needs to be built among different participants in Comprehensive Rural Village Development Project process. Third, systematic mechanism is required to improve social learning among different participants. Fourth, systematic rearrangement is required to guarantee the residents' realistic participation in the course of Comprehensive Rural Village Development Project process.

• 영어어문교육
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• 제13권2호
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• pp.25-45
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• 2007

In this article, I discuss an International Collaborative Writing Course on the Internet (ICWCI) that focused on the learning effectiveness Korean EFL students (KEFLSs) perceived to be necessary to exchange with international EFL students (IEFLSs). The course development was based on an internet-based instructional module, applying widely accepted EFL theories for modern foreign language instruction: collaborative learning, process writing, project-based learning, and integrated approaches. Data from online discussion forum, mid-of-semester and end-of-semester surveys, and final oral interviews are conducted and discussed. KEFLSs and IEFLSs were questioned about (a) changes in attitude towards computers assisted language learning (CALL); (b) effect of computer background on motivation; (c) perception of their acquired writing skills; and (d) attitude towards collaborative learning. The result of this study demonstrated that the majority of ICWCI participants said they enjoyed the course, gained fruitful confidence in English communication and computer skills, and felt that they made significant progress in writing skills. In spite of positive benefits created by the ICWCI, it was found that there were some issues that are crucial to run appropriate networked collaborative courses. This study demonstrates that participants' computer skills, basic language proficiency, and local time differences are important factors to be considered when incorporating the ICWCI as these may affect the quality of online instructional courses and students' motivation toward network based collaboration interaction.

• 한국콘텐츠학회논문지
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• 제13권11호
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• pp.11-20
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• 2013

최근 SNS(Social Network Service)의 사용이 급격히 증가함에 따라 추천 기법에 대한 연구가 활발히 진행되고 있다. 추천 기법은 사용자들이 좋아하거나 필요할만한 다양한 서비스들을 실시간으로 제공하는 기법이다. 그 중 그룹 추천은 사용자의 성향 정보를 기반으로 적합한 그룹을 제공해 주는 기법이다. 본 논문에서는 소셜 네트워크 환경에서 사용자 프로필 및 협업 필터링을 이용한 그룹 추천 기법을 제안한다. 제안하는 기법은 사용자의 최근 그룹 활동 정보를 수집하여 프로필 정보를 갱신하기 때문에 기존의 정적프로필 기반의 그룹 추천 기법의 최근 사용자의 성향을 고려하지 못하는 문제점을 해결한다. 또한, 협업 필터링을 통해 그룹 내 자신의 성향과 비슷한 사용자들의 프로필 데이터를 활용하여 그룹을 추천함으로써 사용자에게 좀 더 다양한 그룹을 제공한다. 성능 평가 결과 제안하는 기법이 기존 기법에 비해 사용자의 변화하는 성향이 충분히 반영된 다양한 그룹 추천이 이루어지는 것을 확인 할 수 있었다.