• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.359-364
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• 2012

Harvesting energy from the environment is essential for many applications to slow down the deterioration of energy of the devices in sensor networks and in general, the network itself. Energy from the environment is an inexhaustible supply which, if properly managed and harvested from the sources, can allow the system to last for a longer period - more than the expected lifetime at the time of deployment, or even last indefinitely. The goal of this study is to develop a simple algorithm for ns-2 to simulate energy harvesting in wireless sensor network simulations. The algorithm is implemented in the energy module of the simulator. Energy harvesting algorithms have not yet been developed for ns-2. This study will greatly contribute to the existing knowledge of simulating wireless sensor networks with energy harvesting capabilities in ns-2. This paper will also serve as a basis for future research papers that make use of energy harvesting.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.479-481
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• 2023

Generative Adversarial Networks (GANs) have facilitated substantial improvement in single-image super-resolution (SR) by enabling the generation of photo-realistic images. However, the high memory requirements of GAN-based SRs (mainly generators) lead to reduced performance and increased energy consumption, making it difficult to implement them onto resource-constricted devices. In this study, we propose an efficient and compressed architecture for the SR-GAN (generator) model using the model compression technique Knowledge Distillation. Our approach involves the transmission of knowledge from a heavy network to a lightweight one, which reduces the storage requirement of the model by 58% with also an increase in their performance. Experimental results on various benchmarks indicate that our proposed compressed model enhances performance with an increase in PSNR, SSIM, and image quality respectively for x4 super-resolution tasks.

• Journal of Information Management
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• v.32 no.2
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• pp.40-53
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• 2001

The purpose of this study is to explore the current situation and problems in standardizing knowledge information and information technology in the KISTI, and collect the basic data necessary for establishing the national information infrastructure. Through a survey and interviews with nine departments of the Information Services Sector of the KISTI, data were collected regarding the management and exchange of information and the operation of communication networks. According to the analysis of fifty KISTI databases and their operation, tasks to be first standardized include Classification of ST resources, Metadata, Date modeling, Data format, DBMS, ST terminology, and Retrieval protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3945-3964
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• 2015

Since the decentralized structure and the blindness of a large-scale wireless network make it difficult to collect the real-time channel state or other information from random distributed relays, a fundamental question is whether it is feasible to perform the relay selection without this knowledge. In this paper, a Slotted ALOHA based Greedy Relay Selection (SAGRS) scheme is presented. The proposed scheme allows the relays satisfying the user's minimum transmission request to compete for selection by randomly accessing the channel through the slotted ALOHA protocol without the need for the information collection procedure. Moreover, a greedy selection mechanism is introduced with which a user can wait for an even better relay when a suitable one is successfully stored. The optimal access probability of a relay is determined through the utilization of the available relay region, a geographical region consisting of all the relays that satisfy the minimum transmission demand of the user. The average number of the selection slots and the failure probability of the scheme are analyzed in this paper. By simulations, the validation and the effectiveness of the SAGRS scheme are confirmed. With a balance between the selection slots and the instantaneous rate of the selected relay, the proposed scheme outperforms other random access selection schemes.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.566-577
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• 2012

In randomly deployed networks, such as sensor networks, an important problem for each node is to discover its neighbor nodes so that the connectivity amongst nodes can be established. In this paper, we consider this problem by incorporating the physical layer parameters in contrast to the most of the previous work which assumed a collision channel. Specifically, the pilot signals that nodes transmit are successfully decoded if the strength of the received signal relative to the interference is sufficiently high. Thus, each node must extract signal parameter information from the superposition of an unknown number of received signals. This problem falls naturally in the purview of random set theory (RST) which generalizes standard probability theory by assigning sets, rather than values, to random outcomes. The contributions in the paper are twofold: First, we introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms; such an introduction is necessary for the accurate assessment of how an algorithm performs. Secondly, given the double uncertainty of the environment (that is, the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters), we adopt the viewpoint of RST and demonstrate its advantage relative to classical matched filter detection method.

• Journal of Agricultural Extension & Community Development
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• v.9 no.2
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• pp.199-213
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• 2002

The purpose of this study uses agricultural knowledge system theory to explore how the extension system in South Korea was developed and have worked well. By agricultural knowledge system we emphasized the dynamic networks of actors, processes of negotiation, and the diverse ways in which knowledge is constructed and performed. It was possible that individuals may participate in and utilize multiple knowledge systems. The knowledge systems reflected the idea that the boundaries between knowledge groups were not closed and that there could be considerable overlap between knowledge systems. The constructions of agricultural knowledge systems thus included social interactions, communication, and the diverse processes individuals employ to create, use, and evaluate multiple types and sources of information. As such, there were six priorities to development agricultural extension system; the linkage between agricultural colleges, Rural Development Administration(RDA), branch of RDA, establishing the research institution of research and extension linkage. exchange research agent with extension agent, developing information technology system, bottom-up approach, the linkage between national project and regional within extension projects, enforcement of informal learning.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.61-74
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• 2010

The knowledge sharing in a knowledge management process is much affecting generation and distribution of knowledge. Especially, the knowledge distribution is being revitalized with the center of social media service like twitter and library service 2.0 in the knowledge-based IT (Information Technology) environment. The present research analyzed the structure and characteristics of a social network inside an organization that is growing like an organism through self-organization through tools for SNA (Social Network Analysis) and multiple regression analysis of independent variables such as 1) a relationship between social network's structure and knowledge sharing, 2) a relationship between structural holes and knowledge sharing influence of centrality, 3) a relationship between individual ability and knowledge sharing of information technology and work recognition.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.501-508
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• 2011

A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

• Knowledge Management Research
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• v.16 no.4
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• pp.89-108
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• 2015

Social networking communities (SNCs) are media designed to facilitate social interaction using highly accessible and scalable publishing techniques. SNCs can constitute individuals' their own profiles in the online environment and share texts, images and photos in a variety ways. In other words, one of the other motivators is knowledge sharing. Various sites, such as Facebook, Orkut, MySpace, and Hi5 are categorized as SNCs. SNCs have become increasingly popular in recent years among youths, especially students, who use them to build social networks. This study examines whether this usage of SNCs inculcates a sense of community among their members. Several studies have examined the role of a sense of community through increased usage in the context of virtual communities. Although this result may be true of virtual communities, this paper contends that the opposite relationship prevails in the case of SNCs because members interact to build networks and are not obliged to interact. The results reveal that maintaining long-term interactions in the SNCs is helpful in building a sense of community in SNCs. Although short-term usage may not boost the development of a sense of community in SNCs, it does matter if the premise is for a long-term commitment to SNCs. Implications for theory and practice are discussed.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.