• Journal of the Korea Society of Computer and Information
• /
• v.13 no.4
• /
• pp.127-132
• /
• 2008

Wireless sensor network technologies applicable to various industrial fields are rapidly growing. Because it is difficult to change a battery for the once distributed wireless sensor network, energy efficient design is very critical. In order to achieve this purpose in network design, a number of studies have been examining the energy efficient routing protocol. The sensor network consumes energy in proportion to the distance of data transmission and the data to send. Cluster-based routing Protocols such as LEACH-C achieve energy efficiency through minimizing the distance of data transmission. In LEACH-C, however, the total distance between the nodes consisting the clusters are considered important in constructing clustering. This paper examines the cluster-head-selection-algorithm that reflect the distance between the base station and the cluster-head having a big influence on energy consumption. The Proposed method in this paper brought the result that the performance improved average $4{\sim}7%$ when LEACH-C and the base station are located beyond a certain distance. This result showed that the distance between cluster-head and the base station had a substantial influence on lifetime performance in the cluster-based routing protocol.

• Korean Journal of Veterinary Research
• /
• v.31 no.1
• /
• pp.27-32
• /
• 1991

The pancreatic endocrine cells of the cat-shark, S. torazame, were studied using immunohistochemical method. Five kinds of endocrine cells (glucagon-, somatostatin-, insulin-, 5-HT-and BPP-immunoreactive cells) identified in this study. The chracteristic findings of the distributions of five immunoreactive cells were as follows. Glucagon-immunoreactive cells were detected as clustering group in the epithelia of the interlobular duct and singly the pancreatic acini, respectively. Insulin -immunoreactive cells were moderately observed in the epithelia of the interlobular duct or in the periphery of the islet. Somatostatin-immunoreactive cells were distributed in single or mass groups in the epithelia of the interlobular duct and the exocrine gland of the pancreas. A very few 5-HTimmunoreactive cells were seen in the periphery of the islet and the acini of the pancreas-BPP-immunoreactive cell was singly located in the periphery of the pancreatic islet, but GAS/CCK-and Chromogranin-immunoreactive cells were not found in this study.

• Journal of Digital Convergence
• /
• v.12 no.5
• /
• pp.1-12
• /
• 2014

Recently, the need for non-stop service is increasing by the business mission-critical Internet banking, e-payment, e-commerce, home shopping, securities trading, and petition business increases, clustered in a single database of existing, redundant research on high-availability technologies related to technique, etc. is increasing. It provides an API based on the Active Log in addition to the technique of redundancy, ALTIBASE$^{TM}$ Log Analyzer (below, ALA), provides scalability and communication of the same model or between heterogeneous. In this paper, we evaluated the performance of ALA by presenting the design of the database system that you can use the ALA, to satisfy all the synchronization features high scalability and high availability, real-time.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.1
• /
• pp.157-165
• /
• 2011

It is challenging to detect foreground objects when background includes an illumination variation, shadow or structural variation due to its motion. Basically pixel-based background models including codebook-based modeling suffer from statistical randomness of each pixel. This paper proposes an algorithm that incorporates Markov random field model into pixel-based background modeling to achieve more accurate foreground detection. Under the assumptions the distance between the pixel on the input imaging and the corresponding background model and the difference between the scene estimates of the spatio-temporally neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameters is proposed. The proposed method alternates between estimating the parameters with the intermediate foreground detection and estimating the foreground detection with the estimated parameters, after computing it with random initial parameters. Extensive experiment is conducted with several videos recorded both indoors and outdoors to compare the proposed method with the standard codebook-based algorithm.

• Journal of the Korea Convergence Society
• /
• v.8 no.7
• /
• pp.237-243
• /
• 2017

Recently, the Korean government is planning to create ICT-centered clusters that will lead the fourth industrial revolution in the Yangjae-Umyeun area. In order for a cluster to be successful, innovation environments such as support systems and institutions should be appropriately prepared. In this study, we present a hierarchical model of ICT SME support measures after comprehending the support measures for existing SMEs and the factors needed for clustering, and then deriving the priorities of support measures. The questionnaire was distributed to 9 ICT SMEs and R&D experts. A total of 6 copies were collected. The priority of the support measures in this study is expected to be utilized for the successful development of R&CD cluster and the allocation of the support budget.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.2
• /
• pp.399-406
• /
• 2009

In this study, Polynomial Radial Basis Function Neural Network(pRBFNN) based on Fuzzy Inference System is designed and its parameters such as learning rate, momentum coefficient, and distributed weight (width of RBF) are optimized by means of Particle Swarm Optimization. The proposed model can be expressed as three functional module that consists of condition part, conclusion part, and inference part in the viewpoint of fuzzy rule formed in 'If-then'. In the condition part of pRBFNN as a fuzzy rule, input space is partitioned by defining kernel functions (RBFs). Here, the structure of kernel functions, namely, RBF is generated from HCM clustering algorithm. We use Gaussian type and Inverse multiquadratic type as a RBF. Besides these types of RBF, Conic RBF is also proposed and used as a kernel function. Also, in order to reflect the characteristic of dataset when partitioning input space, we consider the width of RBF defined by standard deviation of dataset. In the conclusion part, the connection weights of pRBFNN are represented as a polynomial which is the extended structure of the general RBF neural network with constant as a connection weights. Finally, the output of model is decided by the fuzzy inference of the inference part of pRBFNN. In order to evaluate the proposed model, nonlinear function with 2 inputs, waster water dataset and gas furnace time series dataset are used and the results of pRBFNN are compared with some previous models. Approximation as well as generalization abilities are discussed with these results.

• The KIPS Transactions:PartC
• /
• v.13C no.1 s.104
• /
• pp.103-112
• /
• 2006

Since sensor node has a limited energy supply in a wireless sensor network, it is very important to maximize the network lifetime through energy-efficient routing. Thus, many routing protocols have been developed for wireless sensor networks and can be classified into flat and hierarchical routing protocols. Recent researches focus on hierarchical routing scheme and LEACH is a representative hierarchical routing protocol. In this paper, we investigated the problems of the LEACH and proposed a novel energy efficient routing scheme, called ENTER(ENergy efficient Two-tiEr Routing protocol), to resolve the problem. ENTER reduces an energy consumption and increases a network lifetime by organizing clusters by the same distributed algerian as in the LEACH and establishing paths among cluster-heads to transmit the aggregated data to the sink node. We compared the performance of the ENTER with the LEACH through simulation and showed that the ENTER could enhance the network lifetime by utilizing the resources more efficiently.

• Journal of Communications and Networks
• /
• v.18 no.3
• /
• pp.387-396
• /
• 2016

Multiuser communication has been an important research area of underwater acoustic communications and networking. This paper studies the use of adaptive orthogonal frequency-division multiple access (OFDMA) in a downlink scenario, where a central node sends data to multiple distributed nodes simultaneously. In practical implementations, the instantaneous channel state information (CSI) cannot be perfectly known by the central node in time-varying underwater acoustic (UWA) channels, due to the long propagation delays resulting from the low sound speed. In this paper, we explore the CSI feedback for resource allocation. An adaptive power-bit loading algorithm is presented, which assigns subcarriers to different users and allocates power and bits to each subcarrier, aiming to minimize the bit error rate (BER) under power and throughput constraints. Simulation results show considerable performance gains due to adaptive subcarrier allocation and further improvement through power and bit loading, as compared to the non-adaptive interleave subcarrier allocation scheme. In a lake experiment, channel feedback reduction is implemented through subcarrier clustering and uniform quantization. Although the performance gains are not as large as expected, experiment results confirm that adaptive subcarrier allocation schemes based on delayed channel feedback or long term statistics outperform the interleave subcarrier allocation scheme.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.2
• /
• pp.277-284
• /
• 2016

Various network attacks such as DDoS(Distributed Denial of service) and orm are one of the biggest problems in the modern society. These attacks reduce the quality of internet service and caused the cyber crime. To solve the above problem, signature based IDS(Intrusion Detection System) has been developed by network vendors. It has a high detection rate by using database of previous attack signatures or known malicious traffic pattern. However, signature based IDS have the fatal weakness that the new types of attacks can not be detected. The reason is signature depend on previous attack signatures. In this paper, we propose a k-means clustering based malicious traffic detection method to complement the problem of signature IDS. In order to demonstrate efficiency of the proposed method, we apply the bayesian theorem.

• Asian-Australasian Journal of Animal Sciences
• /
• v.32 no.1
• /
• pp.38-48
• /
• 2019

Objective: In this study, the transcriptome profile of cow experiencing miscarriage during peri-implantation was investigated. Methods: Total transcriptomes were checked by RNA sequencing, and the analyzed by bioinformatics methods, the differentially expressed genes (DEGs) were analysed with hierarchical clustering and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis. Results: The results suggested that serum progesterone levels were significantly decreased in cows that miscarried as compared to the pregnant cows at 18, 21, 33, 39, and 51 days after artificial insemination. The RNA sequencing results suggested that 32, 176, 5, 10, and 2 DEGs were identified in the pregnant cows and miscarried cows at 18, 21, 33, 39, and 51 d after artificial insemination. And 15, 101, 1, 2, and 2 DEGs were upregulated, and 17, 74, 4, and 8 DEGs were downregulated in the cows in the pregnant and miscarriage groups, respectively at 18, 21, 33, and 39, but no gene was downregulated at 51 d after artificial insemination. These DEGs were distributed to 13, 20, 3, 6, and 20 pathways, and some pathway essential for pregnancy, such as cell adhesion molecules, tumor necrosis factor signaling pathway and PI3K-Akt signaling pathway. Conclusion: This analysis has identified several genes and related pathways crucial for pregnancy and miscarriage in cows, as well as these genes supply molecular markers to predict the miscarriage in cows.