• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3480-3500
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• 2017

Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with densely distributed sensor nodes. The non-localizable problem is prone to happening when a target moves into the WSN with sparsely distributed sensor nodes. To solve this problem, we propose a collaborative and predictive localization algorithm (CPLA). The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory. In addition, the collaborative and predictive schemes are designed to solve the non-localizable problems in the two-anchor nodes locating, one-anchor node locating and non-anchor node locating situations. Simulation results prove that the CPLA exhibits higher localization accuracy than other tested predictive localization algorithms either in the WSN with sparsely distributed sensor nodes or in the WSN with densely distributed sensor nodes.

• Agribusiness and Information Management
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• 제3권1호
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• pp.1-10
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• 2011

In this exploratory analysis, we investigate the genesis and the evolution of local food-purchasing networks created and operated by consumers. In details, we describe how collecting and sharing information about food-products can become a central activity for some consumers' communities and how these communities are starting to play an active role in the food supply chain. We define this community-based food-purchasing model as collaborative food network (CFN), and we analytically describe its characteristics and differences with respect to the traditional and industrialized agrifood supply chain models. A collaborative food network community in Italy, known as GAS ("Gruppi di Acquisto Solidale" - "Solidarity Purchasing Groups"), is introduced as an example of our analytical model. We will use this empirical example to present the strengths and weaknesses of the CFN model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1330-1347
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• 2018

Mobile Ad hoc Network (MANET) is a collection of nodes or communication devices that wish to communicate without any fixed infrastructure and predetermined organization of available links. The effort has been made by proposing a scheme to overcome the critical security issue in MANET. The insufficiency of security considerations in the design of Ad hoc On-Demand Distance Vector protocol makes it vulnerable to the threats of collaborative black hole attacks, where hacker nodes attack the data packets and drop them instead of forwarding. To secure mobile ad hoc networks from collaborative black hole attacks, we implement our scheme and considered sensor's energy as a key feature with a better packet delivery ratio, less delay time and high throughput. The proposed scheme has offered an improved solution to diminish collaborative black hole attacks with high performance and benchmark results as compared to the existing schemes EDRIAODV and DRIAODV respectively. This paper has shown that throughput and packet delivery ratio increase while the end to end delay decreases as compared to existing schemes. It also reduces the overall energy consumption and network traffic by maintaining accuracy and high detection rate which is more safe and reliable for future work.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.877-880
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• 2003

In a competitive and globalized business environment, the need for the green products becomes stronger. To meet these trends, the environmental assessment besides delivery, cost and quality of products should be considered as an important factor in new product development phase. In this paper. a knowledge-based approximate life cycle assessment system (KALCAS) for the collaborative design environment is developed to assess the environmental impacts in context of product concept development. It aims at improving the environmental efficiency of the product using artificial neural networks consisting of high-level product attributes and LCA results. The overall framework of the collaborative environment including KALCAS is proposed. This architecture uses the CO environment to allow users on a wide variety of platforms to access the product data and other related information. It enables us to trade-off the evaluation results between the objectives of the product development including the approximate environmental assessment in the collaborative design environment.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2005년도 추계학술대회 발표 논문집
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• pp.463-470
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• 2005

In a rapidly changing business environment, the improvement of managerial techniques through IT utilization brings about remarkable increases in profitability and redesign of work process for better performances. IT innovation by electronic instruments such as ICT e-business provides accelerates forming inter-organizational information network and helps them benchmark the best practices of advanced organizations. A new shift of paradigm by e-business across all enterprises has turned the traditional aspects of inter-organizational competition and relationship into a form of collaboration. Collaboration enables business activities in parallel position among companies and facilitates cooperation between partner enterprises. Lately, the concept of 'Synchronization' is emerging beyond dimension of cooperation between networks, and the most concepts related to it are converging into 'Collaboration Networks'. This research observes a virtual organization as a form of collaborative networks, and measures the degree of virtualization of Korean collaborative organizations.

• 디지털융복합연구
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• 제17권1호
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• pp.123-130
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• 2019

웹 추천기법에서 가장 많이 사용하는 방식 중의 하나는 협업필터링 기법이다. 협업필터링 관련 많은 연구에서 정확도를 개선하기 위한 방안이 제시되어 왔다. 본 연구는 Word2Vec과 앙상블 합성곱 신경망을 활용한 영화추천 방안에 대해 제안한다. 먼저 사용자, 영화, 평점 정보에서 사용자 문장과 영화 문장을 구성한다. 사용자 문장과 영화 문장을 Word2Vec에 입력으로 넣어 사용자 벡터와 영화 벡터를 구한다. 사용자 벡터는 사용자 합성곱 모델에 입력하고, 영화 벡터는 영화 합성곱 모델에 입력한다. 사용자 합성곱 모델과 영화 합성곱 모델은 완전연결 신경망 모델로 연결된다. 최종적으로 완전연결 신경망의 출력 계층은 사용자 영화 평점의 예측값을 출력한다. 실험결과 전통적인 협업필터링 기법과 유사 연구에서 제안한 Word2Vec과 심층 신경망을 사용한 기법에 비해 본 연구의 제안기법이 정확도를 개선함을 알 수 있었다.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2001년도 e-Biz World Conference
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• pp.157-172
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• 2001

Agenda From Supply Chains to e-Supply Networks Emarkets Overview ＆ Current Developments Which eMarket Model Should We Pursue？(omitted)

• 한국콘텐츠학회논문지
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• 제12권10호
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• pp.11-21
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• 2012

하이브리드 네트워크 인프라는 Internet2, SURFNet 등의 선도 연구망 커뮤니티에게 가장 우선적인 기술로 대두되고 있다. 그러나, 첨단(high-end) 응용의 종단 간 협업 연구를 위하여 필수적인 하이브리드 연구망 간의 인터도메인 협업 인프라는 실질적인 아키텍쳐의 설계와 구현에 있어서 아직도 많은 연구를 필요로 하고 있다. 따라서 본 논문에서는 하이브리드 연구망 기반의 분산 가상형 네트워크 운영과 리소스 정보 관리를 위한 프레임워크를 제안하고, 이를 기반으로 코어 시스템을 구현하였다. 제안된 프레임워크는 멀티도메인 하이브리드 연구망 운영과 관리를 위하여 분산형 아키텍쳐로 설계되었다. 분산 가상형 네트워크 운영 프레임워크는 네트워크 도메인 내에서 자치성과 독립적인 제어를 유지하면서 인터도메인 네트워크 간의 협업을 가능케 함으로써, 연구자 및 실험자가 스스로 생성한 가상 네트워크를 운영 관리 할 수 있는 환경을 제공할 수 있다. 본 논문에서는 제안된 프레임워크를 위한 세부적인 구조와 기술을 다루며, 이러한 환경이 어떻게 고성능 첨단(high-end) 응용을 위하여 활용될 수 있는지에 대하여 고찰한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1999-2005
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• 2005

Collaboration in wireless sensor networks must be fault-tolerant due to the harsh environmental conditions in which such networks can be deployed. This paper focuses on finding signal processing algorithms for collaborative target detection based on the generalized approach to signal processing in the presence of noise that are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor network. Two algorithms, namely, value fusion and decision fusion constructed according to the generalized approach to signal processing in the presence of noise, are identified first. When comparing their performance and communication overhead, decision fusion is found to become superior to value fusion as the ratio of faulty sensors to fault free sensors increases. The use of the generalized approach to signal processing in the presence of noise under designing value and decision fusion algorithms in wireless sensor networks allows us to obtain the same performance, but at low values of signal energy, as under the employment of universally adopted signal processing algorithms widely used in practice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1643-1660
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• 2016

Connectivity and trust in social networks have been exploited to propose applications on top of these networks, including routing, Sybil defenses, and anonymous communication systems. In these networks, and for such applications, connectivity ensures good performance of applications while trust is assumed to always hold, so as collaboration and good behavior are always guaranteed. In this paper, we study the impact of differential behavior of users on performance in typical social network-enabled routing applications. We classify users into either collaborative or rational (probabilistically collaborative) and study the impact of this classification and the associated behavior of users on the performance of such applications, including random walk-based routing, shortest path based routing, breadth-first-search based routing, and Dijkstra routing. By experimenting with real-world social network traces, we make several interesting observations. First, we show that some of the existing social graphs have high routing costs, demonstrating poor structure that prevents their use in such applications. Second, we study the factors that make probabilistically collaborative nodes important for the performance of the routing protocol within the entire network and demonstrate that the importance of these nodes stems from their topological features rather than their percentage of all the nodes within the network.