• Journal of KIISE
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• v.42 no.12
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• pp.1495-1502
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• 2015

Data compression involves a trade-off between delay time and data size. Greater delay times require smaller data sizes and vice versa. There have been many studies performed in the field of wireless sensor networks on increasing network life cycle durations by reducing data size to minimize energy consumption; however, reductions in data size result in increases of delay time due to the added processing time required for data compression. Meanwhile, as energy generation occurs periodically in solar energy-based wireless sensor networks, redundant energy is often generated in amounts sufficient to run a node. In this study, this excess energy is used to reduce the delay time between nodes in a sensor network consisting of solar energy-based nodes. The energy threshold value is determined by a formula based on the residual energy and charging speed. Nodes with residual energy below the threshold transfer data compressed to reduce energy consumption, and nodes with residual energy above the threshold transfer data without compression to reduce the delay time between nodes. Simulation based performance verifications show that the technique proposed in this study exhibits optimal performance in terms of both energy and delay time compared with traditional methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.83-94
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• 2015

Deduplication, which is a technique of eliminating redundant data by storing only a single copy of each data, provides clients and a cloud server with efficiency for managing stored data. Since the data is saved in untrusted public cloud server, however, both invasion of data privacy and data loss can be occurred. Over recent years, although many studies have been proposed secure deduplication schemes, there still remains both the security problems causing serious damages and inefficiency. In this paper, we propose secure and efficient client-side deduplication with Key-server based on Bellare et. al's scheme and challenge-response method. Furthermore, we point out potential risks of client-side deduplication and show that our scheme is secure against various attacks and provides high efficiency for uploading big size of data.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.438-449
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• 2018

Recently, various graph data have been utilized in various fields such as social networks and citation networks. As the graph changes dynamically over time, it is necessary to manage the graph historical data for tracking changes and retrieving point-in-time graphs. Most historical data changes partially according to time, so unchanged data is stored redundantly when data is stored in units of time. In this paper, we propose a graph history storage management method to minimize the redundant storage of time graphs. The proposed method continuously detects the change of the graph and stores the overlapping subgraph in intersection snapshot. Intersection snapshots are connected by a number of delta snapshots to maintain change data over time. It improves space efficiency by collectively managing overlapping data stored in intersection snapshots. We also linked intersection snapshots and delta snapshots to retrieval the graph at that point in time. Various performance evaluations are performed to show the superiority of the proposed scheme.

• Journal of KIISE:Information Networking
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• v.32 no.2
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• pp.261-277
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• 2005

We propose the PAD (Power Aware Data-centric Routing Protocol), which finds minimum energy routes and prolongs network life-time, for the data-centric sensor networks. Firstly, the PAD discovers the minimum energy Property graph by removing redundant communication links. The proposed a1gorithm to find the minimum energy property graph is faster, simpler and easier to implement than existing aIgorithms. Secondly, the PAD runs the DDBF (Distributed Data-centric Bellman-Ford Algorithm) to determine routing paths between a base node and all sensor nodes. The DDBF selves the drawbacks of the distributed bellman-ford algorithm, i.e. slow convergence and a possible cyclic routing path. Since the PAD is a fully distributed algorithm with low overhead, it can be used in various kinds of resource limited sensor network applications.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.1-14
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• 2009

A currently domestic governmental R&D business is early to 100. And this is each managed individually in 15 professional organizations of research and management by characteristics of a business. For this Reason, A redundant investment issue regarding national R&D occurs, and an issue regarding efficiency of R&D investment by insufficiency of systematic R&D research project and result management is continuously raised. Ministry of Education Science and Technology establishing National Science & Technology Information Service(NTIS) in order to solve these issues. NTIS is the national R&D Portal System which can support efficiency of research and development to result utilization in planning of national research and development. In this paper We consider integrated DB constructions and Information Linking of R&D Participants/Projects/Results information in a NTIS system for data quality Improvement. and then We analyze the cause of the data quality problem, and we propose the improvement plan for data quality elevation of NTIS system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.650-652
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• 2013

As VANET(Vehicular Ad-hoc NETwork) improves road safety, efficiency, and comfort, and provides a value-added service such as commerce information or internet access. it is the most important technology in ITS(Intelligent Transportation System). But, In VANETs, better communication efficiency can be achieved by sacrificing security and vice versa. VANETs cannot get started without either of them. Therefore, to solve these problems simultaneously, this paper proposes MAC(Message Authentication Code) based SDAP(Secure Data Aggregation Protocol) which removes redundant data or abnormal data between vehicles and verifies the integrity of message. The MAC based SDAP not only improves the efficiency of data delivery but also enhances the security by detecting malicious attacks such as propagation jamming attack, forgery attack, and disguised attack.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.160-166
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• 2007

When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a user preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or ron-spam in a meaningful way. We also suggest a new rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1217-1222
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• 2004

This paper describes the development of tele-robotic interface for the hot-line maintenance robot system. One of main issues in designing human-robot interface for the hot-line maintenance robot system is to plan the control procedure for each part of the robotic system. Another issue is that the actual degree of freedom (DOF) in the hot-line maintenance robot system is much greater than that of available control devices such as joysticks and gloves in the remote-cabin. For this purpose, a virtual simulator, which includes the virtual hot-line maintenance robot system and the environment, is developed in the 3D environment using CAD data. It is assumed that the control operation is done in the remote cabin and the overall work process is observed using the main-camera with 2 DOFs. For the input device, two joysticks, one pedal, two data gloves, and a Head Mounted Display (HMD) with tracker sensor were used. The interface is developed for each control mode. Designed human-interface system is operated using high-level control commands which are intuitive and easy to understand without any special training.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.1
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• pp.15-23
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• 2001

This study was a methodological research to develop computerized patient classification system. The subjects of this investigation were 435 inpatients except redundant data and outliers in P University Hospital from January 18, 2000 to January 24, 2000. The data was analyzed by discrimination analysis and adopted discriminant variables were 1) sum of frequency for the nursing activities, 2) the number of nursing activities that do not need to consider intensity of the activities, and 3) total hours of nursing activities that need to consider their intensities. Discriminant function developed by this study classified the patients into 4 groups; class I, 251 ; class II, 125 ; class III, 39 ; class IV, 20. The Hit ratio was 89.23. Based on this study, following suggestions can be made for the future research 1. Inclusive patient classification system, which includes more expanded direct nursing care factors, need to be developed and examined. 2. This developed classification system can be utilized to evaluate patient distribution and to estimate adequate numbers of nursing staffs in each nursing unit.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.87-94
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• 2004

The feature subset selection is used as a preprocessing step of a teaming algorithm. If collected data are irrelevant or redundant information, we can improve the performance of learning by removing these data before creating of the learning model. The feature subset selection can also reduce the search space and the storage requirement. This paper proposed a new feature subset selection algorithm that is using the heuristic function based on entropy to evaluate the performance of the abstracted feature subset and feature selection. The ACS algorithm was used as a search method. We could decrease a size of learning model and unnecessary calculating time by reducing the dimension of the feature that was used for learning.