• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.31-36
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• 2007

This paper proposes Co-MAC (Coexistence MAC), an energy efficient medium access control protocol designed for large-scale sensor networks. In Co-MAC protocol, an overall network is divided into independent subnets, and each subnet orthogonally operates on time line in a temporal fashion. The basic idea of Co-MAC is to evenly distribute sensor nodes in a certain geographic area based on subnets to minimize overhearing which means the reception of unnecessary data packets from neighboring nodes. In our simulation, it was observed that energy efficiency of Co-MAC outperforms conventional MAC protocols under the given conditions.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.101-110
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• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.212-218
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• 2021

Low-power and Lossy Networks (LLNs) have become the common network infrastructure for a wide scope of Internet of Things (IoT) applications. For efficient routing in LLNs, IETF provides a standard solution, namely the IPv6 Routing Protocol for LLNs (RPL). It enables effective interconnectivity with IP networks and flexibly can meet the different application requirements of IoT deployments. However, it still suffers from different open issues, particularly in large-scale setups. These include the node unreachability problem which leads to increasing routing losses at RPL sink nodes. It is a result of the event of memory overflow at LLNs devices due to their limited hardware capabilities. Although this can be alleviated by the establishment of multi-sink topologies, RPL still lacks the support for effective load balancing among multiple sinks. In this paper, we address the need for an efficient multi-sink load balancing solution to enhance the performance of PRL in large-scale scenarios and alleviate the node unreachability problem. We propose a new RPL objective function, Multi-Sink Load Balancing Objective Function (MSLBOF), and introduce the Memory Utilization metrics. MSLBOF enables each RPL node to perform optimal sink selection in a way that insure better memory utilization and effective load balancing. Evaluation results demonstrate the efficiency of MSLBOF in decreasing packet loss and enhancing network stability, compared to MRHOF in standard RPL.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.27-35
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• 2020

The Korean semiconductor industry is the top export item, and its technological prowess is also higher than that of its competitors. However, the technology gap with rivals will narrow. And the semiconductor industry is facing difficulties due to trade friction. Therefore, semiconductor firms should be more efficient in their production. we study analyzes the efficiency semiconductor firms using DEA model. We evaluate the CCR, BBC efficiency and RTS(return to scale) of 30 Korean semiconductor firms. There are a total of 13 efficient DMUs with a BCC of 1. There are a total of 6 efficient DMUs with a CCR of 1. A total of 10 DMUs were IRS in Scale Efficiency and a total of 9 DMUs were CRS in Scale Efficiency and a total of 11 DMUs were DRS in Scale Efficiency. We also suggest the semiconductor firms which can be benchmarked based on analyzed information.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.151-158
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• 2019

The high-technological in the electric and electronic industries is recognized in overseas markets as well. However, the competition for technologies in these industries is increasing. Therefore, electric and electronic firms should be more efficient in their production. so, This paper analyzes the efficiency of High-growth Electrical and Electronics firms using DEA model. We evaluate the CCR, BBC efficiency and RTS(return to scale) of 20 Korean high-growth Electrical and Electronics firms. There are a total of 12 efficient DMUs with a BCC of 1. There are a total of 4 efficient DMUs with a CCR of 1. A total of 11 DMUs were IRS in Scale Efficiency and a total of 6 DMUs were CRS in Scale Efficiency and a total of 3 DMUs were DRS in Scale Efficiency. We also suggest the Electrical and Electronics firms which can be benchmarked based on analyzed information.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.1
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• pp.13-17
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• 2012

Indexing allows converting raw document collection into easily searchable representation. Web searching by Google or Yahoo provides subsecond response time which is made possible by efficient indexing of web-pages over the entire Web. Indexing process gets challenging when the scale gets bigger. Parallel techniques, such as MapReduce framework can assist in efficient large-scale indexing process. In this paper we propose PDFindexer, system for indexing scientific papers in PDF using MapReduce programming model. Unlike Web search engines, our target domain is scientific papers, which has pre-defined structure, such as title, abstract, sections, references. Our proposed system enables parsing scientific papers in PDF recreating their structure and performing efficient distributed indexing with MapReduce framework in a cluster of nodes. We provide the overview of the system, their components and interactions among them. We discuss some issues related with the design of the system and usage of MapReduce in parsing and indexing of large document collection.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.969-970
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• 2008

This paper proposes illumination-efficient iris image capturing method. face capture method for extraction of iris pattern with one high resolution camera needs a large scale near infrared illumination. we replace high-resolution camera with co-optic-axial combination between wide view camera and narrow view camera. because this method needs small scale illumination that illuminate only narrow camera viewing angle, we can capture iris pattern image with small scale near infrared illumination.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.64-70
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• 1993

This paper presents an efficient SOFM(self-organizing feature map) algorithm for the solution of the large scale TSPs(traveling salesman problems). Because no additional winner neuron for each city is created in the next competition, the proposed algorithm requires just only the N output neurons and 2N connections, which are fixed during the whole process, for N-city TSP, and it does not requires any extra algorithm of creation of deletion of the neurons. And due to direct exploitation of the output potential in adaptively controlling the neighborhood, the proposed algorithm can obtain higher convergence rate to the suboptimal solutions. Simulation results show about 30% faster convergence and better solution than the conventional algorithm for solving the 30-city TSP and even for the large scale of 1000-city TSPs.

• Journal of Power System Engineering
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• v.9 no.3
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• pp.39-43
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• 2005

Among many other alternative energy resources, small scale hydropower has been brought into attention as a reliable source of energy today, which had been relatively neglected since 1960s. Present low head of Francis turbines and small scale hydroturbines, however, have limitations in the minimum required head and flow rate for efficient operation. This study attempts to develope the Francis turbine which is expected to run efficiently even in very low head and small flow rate, so that the limitations on the conventional small scale hydropower could alleviated and competition with other alternative energy sources in the changable design conditions could attained. The Francis turbine of a new concept was designed based on changable design conditions, hydrodynamics and theory of power transmission. The result of the study shows that two stages runner is more efficient, cheaper in construction, faster responding, and easier maintaining than single stage runner of Francis turbine

• ETRI Journal
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• v.30 no.3
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• pp.483-485
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• 2008

A micro-sensor network is comprised of a large number of small sensors with limited memory capacity. Current key-establishment schemes for symmetric encryption require too much memory for micro-sensor networks on a large scale. In this paper, we propose a memory-efficient hypercube key establishment scheme that only requires logarithmic memory overhead.