• Title/Summary/Keyword: Computer-networks

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An Energy-based PEGASIS Protocol for Efficient Routing in Wireless Sensor Networks (WSN에서의 효율적 라우팅을 위한 에너지 기반 PEGASIS 프로토콜)

  • Hyun-Woo Do;Tae-Wook Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.5
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    • pp.809-816
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    • 2024
  • In a Wireless Sensor Network (WSN) environment, where numerous small sensors are arranged in a certain space to form a wireless network, each sensor has limited battery power. Therefore, the lifetime of each sensor node is directly related to the network's lifetime, necessitating efficient routing to maximize the network's lifespan. This study proposes a routing protocol based on PEGASIS, a representative energy-efficient routing protocol in WSN environments. The proposed protocol categorizes nodes into groups based on their distance from the sink node, forms multiple chains within each group, and selects the leader node for each group by comparing the remaining energy levels. The proposed method ensures that each group's leader node is the one with the highest energy within that group, which has been shown to increase the network's lifespan compared to the traditional PEGASIS method.

An Energy-Efficient Multi-Path Multi-Hop Routing Techniques based on LEACH in WSN Environment (WSN LEACH 기반 에너지 효율적인 다중 패스 멀티 홉 라우팅 기법 연구)

  • Park Tae Bin;Tae-Wook Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.5
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    • pp.827-834
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    • 2024
  • LEACH, a layer-based routing protocol used in wireless sensor networks, sends fused data from the cluster head to the sink node in a single hop, so as the network size increases, the distance to the sink node increases significantly, which increases energy consumption. In addition, existing multi-hop transmission studies to solve this problem have problems with reverse transmission in the process of finding the next node to be transmitted and passing through this node. In this paper, we propose a multi-hop routing technique that selects a relay node based on the distance to the sink node and transmits it to a relay node via general nodes located in a straight line between the relay node and each cluster head. By reducing the transmission distance between nodes and minimizing reverse transmission occurring in the process through adjacent nodes, it was confirmed that the network life was extended compared to the previously proposed LEACH and EEACP protocols.

Deep Learning-Based Plant Health State Classification Using Image Data (영상 데이터를 이용한 딥러닝 기반 작물 건강 상태 분류 연구)

  • Ali Asgher Syed;Jaehawn Lee;Alvaro Fuentes;Sook Yoon;Dong Sun Park
    • Journal of Internet of Things and Convergence
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    • v.10 no.4
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    • pp.43-53
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    • 2024
  • Tomatoes are rich in nutrients like lycopene, β-carotene, and vitamin C. However, they often suffer from biological and environmental stressors, resulting in significant yield losses. Traditional manual plant health assessments are error-prone and inefficient for large-scale production. To address this need, we collected a comprehensive dataset covering the entire life span of tomato plants, annotated across 5 health states from 1 to 5. Our study introduces an Attention-Enhanced DS-ResNet architecture with Channel-wise attention and Grouped convolution, refined with new training techniques. Our model achieved an overall accuracy of 80.2% using 5-fold cross-validation, showcasing its robustness in precisely classifying the health states of tomato plants.

A Graph Layout Algorithm for Scale-free Network (척도 없는 네트워크를 위한 그래프 레이아웃 알고리즘)

  • Cho, Yong-Man;Kang, Tae-Won
    • Journal of KIISE:Computer Systems and Theory
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    • v.34 no.5_6
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    • pp.202-213
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    • 2007
  • A network is an important model widely used in natural and social science as well as engineering. To analyze these networks easily it is necessary that we should layout the features of networks visually. These Graph-Layout researches have been performed recently according to the development of the computer technology. Among them, the Scale-free Network that stands out in these days is widely used in analyzing and understanding the complicated situations in various fields. The Scale-free Network is featured in two points. The first, the number of link(Degree) shows the Power-function distribution. The second, the network has the hub that has multiple links. Consequently, it is important for us to represent the hub visually in Scale-free Network but the existing Graph-layout algorithms only represent clusters for the present. Therefor in this thesis we suggest Graph-layout algorithm that effectively presents the Scale-free network. The Hubity(hub+ity) repulsive force between hubs in suggested algorithm in this thesis is in inverse proportion to the distance, and if the degree of hubs increases in a times the Hubity repulsive force between hubs is ${\alpha}^{\gamma}$ times (${\gamma}$??is a connection line index). Also, if the algorithm has the counter that controls the force in proportion to the total node number and the total link number, The Hubity repulsive force is independent of the scale of a network. The proposed algorithm is compared with Graph-layout algorithm through an experiment. The experimental process is as follows: First of all, make out the hub that exists in the network or not. Check out the connection line index to recognize the existence of hub, and then if the value of connection line index is between 2 and 3, then conclude the Scale-free network that has a hub. And then use the suggested algorithm. In result, We validated that the proposed Graph-layout algorithm showed the Scale-free network more effectively than the existing cluster-centered algorithms[Noack, etc.].

Regeneration of a defective Railroad Surface for defect detection with Deep Convolution Neural Networks (Deep Convolution Neural Networks 이용하여 결함 검출을 위한 결함이 있는 철도선로표면 디지털영상 재 생성)

  • Kim, Hyeonho;Han, Seokmin
    • Journal of Internet Computing and Services
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    • v.21 no.6
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    • pp.23-31
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    • 2020
  • This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

Channel assignment for 802.11p-based multi-radio multi-channel networks considering beacon message dissemination using Nash bargaining solution (802.11p 기반 다중 라디오 다중채널 네트워크 환경에서 안전 메시지 전송을 위한 내쉬 협상 해법을 이용한 채널할당)

  • Kwon, Yong-Ho;Rhee, Byung-Ho
    • Journal of Internet Computing and Services
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    • v.15 no.3
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    • pp.63-69
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    • 2014
  • For the safety messages in IEEE 802.11p vehicles network environment(WAVE), strict periodic beacon broadcasting requires status advertisement to assist the driver for safety. WAVE standards apply multiple radios and multiple channels to provide open public road safety services and improve the comfort and efficiency of driving. Although WAVE standards have been proposed multi-channel multi-radio, the standards neither consider the WAVE multi-radio environment nor its effect on the beacon broadcasting. Most of beacon broadcasting is designed to be delivered on only one physical device and one control channel by the WAVE standard. also conflict-free channel assignment of the fewest channels to a given set of radio nodes without causing collision is NP-hard, even with the knowledge of the network topology and all nodes have the same transmission radio. Based on the latest standard IEEE 802.11p and IEEE 1609.4, this paper proposes an interference aware-based channel assignment algorithm with Nash bargaining solution that minimizes interference and increases throughput with wireless mesh network, which is deigned for multi-radio multi-cahnnel structure of WAVE. The proposed algorithm is validated against numerical simulation results and results show that our proposed algorithm is improvements on 8 channels with 3 radios compared to Tabu and random channel allocation algorithm.

Highly Linear Wideband LNA Design Using Inductive Shunt Feedback (Inductive Shunt 피드백을 이용한 고선형성 광대역 저잡음 증폭기)

  • Jeonng, Nam Hwi;Cho, Choon Sik
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.11
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    • pp.1055-1063
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    • 2013
  • Low noise amplifiers(LNAs) are an integral component of RF receivers and are frequently required to operate at wide frequency bands for various wireless systems. For wideband operation, important performance metrics such as voltage gain, return loss, noise figures and linearity have been carefully investigated and characterized for the proposed LNA. An inductive shunt feedback configuration is successfully employed in the input stage of the proposed LNA which incorporates cascaded networks with a peaking inductor in the buffer stage. Design equations for obtaining low and high input matching frequencies are easily derived, leading to a relatively simple method for circuit implementation. Careful theoretical analysis explains that poles and zeros are characterized and utilized for realizing the wideband response. Linearity is significantly improved because the inductor between gate and drain decreases the third-order harmonics at the output. Fabricated in $0.18{\mu}m$ CMOS process, the chip area of this LNA is $0.202mm^2$, including pads. Measurement results illustrate that input return loss shows less than -7 dB, voltage gain greater than 8 dB, and a little high noise figure around 7~8 dB over 1.5~13 GHz. In addition, good linearity(IIP3) of 2.5 dBm is achieved at 8 GHz and 14 mA of current is consumed from a 1.8 V supply.

Skin Color Detection Using Partially Connected Multi-layer Perceptron of Two Color Models (두 칼라 모델의 부분연결 다층 퍼셉트론을 사용한 피부색 검출)

  • Kim, Sung-Hoon;Lee, Hyon-Soo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.3
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    • pp.107-115
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    • 2009
  • Skin color detection is used to classify input pixels into skin and non skin area, and it requires the classifier to have a high classification rate. In previous work, most classifiers used single color model for skin color detection. However the classification rate can be increased by using more than one color model due to the various characteristics of skin color distribution in different color models, and the MLP is also invested as a more efficient classifier with less parameters than other classifiers. But the input dimension and required parameters of MLP will be increased when using two color models in skin color detection, as a result, the increased parameters will cause the huge teaming time in MLP. In this paper, we propose a MLP based classifier with less parameters in two color models. The proposed partially connected MLP based on two color models can reduce the number of weights and improve the classification rate. Because the characteristic of different color model can be learned in different partial networks. As the experimental results, we obtained 91.8% classification rate when testing various images in RGB and CbCr models.

A Customized Cancer Radiation Treatment Planning Simulation (ccRTPs) System via Web and Network (웹과 네트워크 기술을 이용한 환자 맞춤식 암치료 계획 시뮬레이션 시스템)

  • Khm, O-Yeon
    • Progress in Medical Physics
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    • v.17 no.3
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    • pp.144-152
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    • 2006
  • The telemedicine using independent client-server system via networks can provide high quality normalized services to many hospitals, specifically to local/rural area hospitals. This will eventually lead to a decreased medical cost because the centralized institute can handle big computer hardware systems and complicated software systems efficiently and economically, Customized cancer radiation treatment planning for each patient Is very useful for both a patient and a doctor because it makes possible for the most effective treatment with the least possible dose to patient. Radiation planners know that too small a dose to the tumor can result in recurrence of the cancer, while too large a dose to healthy tissue can cause complications or even death. The best solution is to build an accurate planning simulation system to provide better treatment strategies based on each patient's computerized tomography (CT) image. We are developing a web-based and a network-based customized cancer radiation therapy simulation system consisting of four Important computer codes; a CT managing code for preparing the patients target data from their CT image files, a parallel Monte Carlo high-energy beam code (PMCEPT code) for calculating doses against the target generated from the patient CT image, a parallel linear programming code for optimizing the treatment plan, and scientific data visualization code for efficient pre/post evaluation of the results. The whole softwares will run on a high performance Beowulf PC cluster of about 100-200 CPUs. Efficient management of the hardware and software systems is not an easy task for a hospital. Therefore, we integrated our system into the client-sewer system via network or web and provide high quality normalized services to many hospitals. Seamless communication with doctors is maintained via messenger function of the server-client system.

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Road Networks and Crime Occurrence Multi-Agent Simulation for Smart Safe City (스마트 안전도시 조성을 위한 도로망 특성과 범죄발생 멀티에이전트(Multi-Agent) 시뮬레이션)

  • MOON, Tae-Heon;CHO, Jung-Hun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.2
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    • pp.120-134
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    • 2015
  • Under the hypothesis that the form of road network could affect crime occurrence, this study demonstrates to prove them using Space Syntax with real crime data. We calculated integration, control, connection index by means of Space Syntax and analyzed the relationship between the three indexes and the number of crime occurrence on the each road. Next, in order to generalize the analysis results we adopted Multi-Agent Model and simulated several scenarios on the computer virtual space. The results revealed that integration index has the strongest relationship with crime occurrence both in the case of real study area and virtual space simulations. Though this study has several limitations on the extent of virtual space and realistic computer programming of agents' behavior, the results are meaningful to verify the relationship between the form of read network and crime occurrence. Moreover the simulation platform that this study developed has promising possibilities to find realistic solutions on the effective police deployment or facility layout to improve smart safe city development.