• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.815-823
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• 2012

In this paper reliability growth model in which the operating time between successive failure is a continuous random variable is proposed. This model is for Burr type XII distribution with two parameters which is discussed in two versions: the order statistics and non-homogeneous Poisson process. The two software reliability measures are obtained. The performance for two versions of the suggested model is tested on real data set by U-plot and Y-plot using Kolmogorov distance.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.51-59
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• 2008

In wireless sensor networks, one of most common location detection methods that do not require additional devices such as GPS and ultrasonic sensor, is the location detection method based on received signal strength. However, measured received signal strength will fluctuate over time mainly due to physical radio channel characteristics between nodes, which subsequently will cause errors to measured distance between nodes. Since these contaminated distance data are utilized to detect the location of unknown node, there will be accumulated errors in the location of unknown node. In order to overcome the limitation of the location detection method based on received signal strength, we propose a location scheme in which reliability information of distance data as well as distance data between nodes are utilized to estimate the location of unknown node. Through simulation, it is shown that the proposed scheme can accomplish 30% capacity improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3071-3095
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• 2013

Configuring optimization of wireless sensor networks, which can improve the network performance such as utilization efficiency and network lifetime with minimal energy, has received considerable attention in recent years. In this paper, a cross layer optimal approach is proposed for multi-source linear network and grid network under Rayleigh block-fading channels, which not only achieves an optimal utility but also guarantees the end-to-end reliability. Specifically, in this paper, we first strictly present the optimization method for optimal nodal number $N^*$, nodal placement $d^*$ and nodal transmission structure $p^*$ under constraints of minimum total energy consumption and minimum unit data transmitting energy consumption. Then, based on the facts that nodal energy consumption is higher for those nodes near the sink and those nodes far from the sink may have remaining energy, a cross layer optimal design is proposed to achieve balanced network energy consumption. The design adopts lower reliability requirement and shorter transmission distance for nodes near the sink, and adopts higher reliability requirement and farther transmission distance for nodes far from the sink, the solvability conditions is given as well. In the end, both the theoretical analysis and experimental results for performance evaluation show that the optimal design indeed can improve the network lifetime by 20-50%, network utility by 20% and guarantee desire level of reliability.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.710-714
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• 2009

Optical discs' capacity has increased. In case of Blu-Disc, it can store data up to 25 GB. Due to the large capacity, it can substitute tape devices for the use of backup. However, optical discs' surfaces are exposed so that it can lose data easily by exterior damages like scratches. Therefore additional reliability must be provided to maintain data for a long time. In this paper, we suggest a writing technique that gives optical discs additional reliability. Redundant data, generated by LDPC codes, are stored in disc along with the original data. These original data and redundant data are scattered over the disc to avoid losing a large part of data with one scratch. By deploying data with the distance that provides the reliability a user wants, we can enhance optical discs' reliability.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.262-271
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• 2024

In this paper, by applying deep learning, one of the A.I. techniques, through angle information, which is optical observation data generated when observing satellites at observatories, distance information from observatories is learned to predict range data, thereby increasing the precision of satellite's orbit determination. To this end, we generated observational data from GMAT, reduced the learning data error of deep learning through preprocessing of the generated observational data, and conducted deep learning through MATLAB. Based on the predicted distance information from learning, trajectory determination was performed using an extended Kalman filter, one of the filtering techniques for trajectory determination, through GMAT. The reliability of the model was verified by comparing and analyzing the orbital determination with angular information without distance information and the orbital determination result with predicted distance information from the model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3034-3055
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• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• Journal of the Korean Society for Railway
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• v.11 no.3
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• pp.240-247
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• 2008

Recently, railway corporations have built maintenance information systems and collected failure and maintenance data. For example Seoul Metropolitan Rapid Transit Corporation (SMRT) built the Electric Motor Unit-Information System (EMU-IS) which is the first maintenance information system in Korea. It has been operated from August, 2000. This paper deals with a case study on determining maintenance interval through reliability analysis using EMU-IS fault data. Door system is considered for the case study in which reliability is evaluated for operating time and distance and the overhaul interval is determined.

• Fire Science and Engineering
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• v.23 no.6
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• pp.75-81
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• 2009

In this paper, USN of wireless communication with easy to install and effectiveness with variety information gathering has been proposed as a alternative of wired-based line for transmission of fire sensing data. But, The sensor node using USN should be considered for wireless transmission range and reliability of information. In this study, the zigbee protocol sensor node was implemented and then tested transmission range of sensor node as 10m interval using voltage information of DC 3V & 5V. Here, maximum transmission distance was confirmed 90m inside-outside. When used mesh routing relay node, distance was not limited. In USN network building, when fire sensing data transmitted, the sensing data same between direct sensing data from sensor and collecting data at USN. Therefore, was confirmed reliability for transmission range and information of proposed zigbee sensor node.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.586-589
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• 2013

In this paper, the proposed scheme is STBC system combined with convolutional code to ensure the reliability of data transmission for a high rate wireless communication. In addition, this scheme uses a modified viterbi algorithm in order to get a high system gain when data is transmitted. Because we combine STBC and comvolutional code, the proposed scheme can get a diversity gain of STBC and coding gain of convolutional code at the same time. Unlike existing viterbi docoding algorithm using Hamming distance in order to calculate branch matrix, the modified viterbi algorithm uses Euclidean distance value between received symbol and reference symbol. To analyze the system proposed, it was simulated by changing the constraint length of the convolutional code and the number of transmit and receive antennas of STBC.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.753-762
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• 2021

Google provides mapping services using satellite imagery, this is widely used for the study. Since about 20 years ago, research and business using drones have been expanding. Pix4D is widely used to create 3D information models using drones. This study compared the distance error by comparing the result of the road construction site with the DSM data of Google Earth and Pix4 D. Through this, we tried to understand the reliability of the result of distance measurement in Google Earth. A DTM result of 3.08 cm/pixel was obtained as a result of matching with 49666 key points for each image. The length and altitude of Pix4D and Google Earth were measured and compared using the obtained PCD. As a result, the average error of the distance based on the data of Pix4D was measured to be 0.68 m, confirming that the error was relatively small. As a result of measuring the altitude of Google Earth and Pix4D and comparing them, it was confirmed that the maximum error was 83.214m, which was measured using satellite images, but the error was quite large and there was inaccuracy. Through this, it was confirmed that there are difficulties in analyzing and acquiring data at road construction sites using Google Earth, and the result was obtained that point cloud data using drones is necessary.