• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.2
• /
• pp.267-274
• /
• 2015

In this paper the optimal structure of a neural network based on OpenCV for a golf ball recognition and the intensity of ROI(Region Of Interest) are calculated. The system is composed of preprocess, image processing and machine learning, and a learning model is obtained by multi-layer perceptron using the inputs of 7 Hu's invariant moments, box ration extracted by vertical and horizontal length or ${\pi}$ calculated by area of ROI. Simulation results show that optimal numbers of hidden layer and the node of neuron are selected to 2 and 9 respectively considering the recognition rate and running time, and optimal intensity of ROI is selected to 200.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.16 no.1
• /
• pp.35-44
• /
• 2006

The area of ad hoc networking has been receiving increasing attention among researchers in recent years and a variety of routing protocols targeted specifically at the ad hoc networking environment have been proposed. Selfish nodes are those which do not perform certain operations that the protocol specifies that they should, through a wish to conserve power. We propose a scheme as a mean to mitigate the detrimental effect of selfish nodes. We also propose a new area that might affect nodes' behavior - the environment's influence. In order to let nodes fairly be able to communicate in the networks we proposed solution to this problem. And our scheme can be applied to other reputation methods. We also contain the simulation results in our paper, and through the result, we can conclude that we can solve the problem by adding a little overhead.

• Science of Emotion and Sensibility
• /
• v.9 no.spc3
• /
• pp.209-224
• /
• 2006

Hierarchy which is often named as the tree-structure is used to reduce complexity and show primitive structures of complicated information. This paper aims at explaining information-visualization methods using hierarchies in multimedia domains and prospecting the possible applications by examining how they affect the user's tasks involved in information-seeking activities. As a result, four types of information visualization methods named Treemap, Hyperbolic, Cone Tree and DOI Tree employed in multimedia domain, are presented and pros and cons of each method are explained in this paper. Another important part is defining the core tasks and other related-tasks in information-seeking activities, such as, overview, zoom, filter, details-on-demand, relate, history, and extract. Followings are major findings. Treemap uses 'overview' as the core task, which makes user to gain a overall meaning of the whole information cluster. Hyperbolic and DOI Tree apply 'Boom' task through the function of focus+context or by the function of meaningful scaling to magnify or downsize each node. Cone Tree, also, makes the information organizer to classify the patterns of information acquired in the process of users' information-seeking activities by using 'extract' task. Through this study, it is finally found out that the information-visualization methods using hierarchies in multimedia domains should incorporate the wide variety of functional needs related to users' information-seeking behaviors beyond the visual representation of information.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.12
• /
• pp.101-109
• /
• 2014

Medical technology development and increase the income level of a "Long and healthy Life=Wellness," with the growing interest in actively promoting and maintaining health and wellness has become enlarged. In addition, the demand for personalized health care services is growing and extensive medical moves of big data, disease prevention, too. In this paper, the main interest in the market, highlighting wellness in order to support big data-driven healthcare quality through patient-centered medical services purposes. Patients with drug dependence treatment is not to diet but to improve disease prevention and treatment based on analysis of big data. Analysing your Tweets-daily information and wellness disease prevention and treatment, based on the purpose of the dictionary. Efficient big data analysis for node while increasing processing time experiment. Test result case of total access time efficient 26% of one node to three nodes and case of data storage is 63%, case of data aggregate is 18% efficient of one node to three nodes.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.262-265
• /
• 2015

차세대 미래 인터넷으로 관심을 모으고 있는 CCN은 ICN, CDN, NDN과 비슷한 개념으로 출발한다. 즉, 사용자가 관심을 가지는 데이터를 하나의 컨텐츠로 바라보고 네트워킹을 한다. CCN은 이러한 컨텐츠에 대해 요청 패킷을 보내면 컨텐츠를 가지고 있는 노드에서는 해당 패킷을 보내는 방식이다. IP 기반의 네트워크에서와 마찬가지로 CCN에서도 한정된 네트워크 대역폭에서 소비자에게 전송되는 패킷의 전송 시간에 따른 처리량 향상은 주요 관심사 중의 하나이다. 본 논문에서는 CCN에서의 CCN-Helper 프로토콜을 사용한 소비자의 다운로드 시간 감소 방법을 제안하여 생산자에서 소비자로의 패킷 전송 처리량을 향상시키고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.6
• /
• pp.1-10
• /
• 2021

The interest in underwater acoustic sensor networks (UWASNs), along with the rapid development of underwater industries, has increased. To operate UWASNs efficiently, it is important to adopt well-designed medium access control (MAC) protocols that prevent collisions and allow the sharing of resources between nodes efficiently. On the other hand, underwater channels suffer from a narrow bandwidth, long propagation delay, and low data rate, so existing terrestrial node pairing schemes for non orthogonal multiple access (NOMA) cannot be applied directly to underwater environments. Therefore, a multi-dimensional node pairing scheme is proposed to consider the unique underwater channel in UWASNs. Conventional NOMA schemes have considered the channel quality only in node pairing. Unlike previous schemes, the proposed scheme considers the channel gain and many other features, such as node fairness, traffic load, and the age of data packets to find the best node-pair. In addition, the sender employs a list of candidates for node-pairs rather than path loss to reduce the computational complexity. The simulation results showed that the proposed scheme outperforms the conventional scheme by considering the fairness factor with 23.8% increases in throughput, 28% decreases in latency, and 5.7% improvements in fairness at best.

• Journal of KIISE:Databases
• /
• v.32 no.4
• /
• pp.429-440
• /
• 2005

As rapid improvement in electronic technologies makes sensor hardware more powerful and capable, the application range of sensor networks Is getting to be broader. The main purpose of sensor networks is to monitor the phenomena in interesting regions (e.g., factory warehouses, disaster areas, wild fields, etc) and return required data. The k Nearest Neighbor (KNN) query that finds k objects which are geographically close to the given point is an Important application in sensor networks. However, most previous approaches are either seem to be impractical or are not energy-efficient in resource-limited sensor networks. In this paper. we propose an efficient KNN query processing method in sensor networks. In the proposed method, we dynamically increase searching boundary, if necessary, and traverse nodes inside the boundary until finding k nearest neighbors. Since only the representative sensor nodes are visited, our algorithm reduces a number of messages. We show thorough experiments that the proposed method performs better than the existing method in various network environments.

• Journal of Internet Computing and Services
• /
• v.17 no.5
• /
• pp.17-23
• /
• 2016

Wireless sensor-actuator networks (WSANs) enhance the existing wireless sensor networks (WSNs) by equipping sensor nodes with an actuator. The actuators work with the sensor nodes and perform application-specific operations. The WSAN systems have several applications such as disaster relief, intelligent building, military surveillance, health monitoring, and infrastructure security. These applications require capability of reliable data transfer to act responsively and accurately. Biologically inspired modeling techniques have received considerable attention for achieving robustness, scalability, and adaptability, while retaining individual simplicity. In this paper, an epidemic-inspired algorithm for data dissemination with delay constraints while minimizing energy consumption in WSAN is proposed. The steady states and system stability are analyzed using control theory. Also, simulation results indicate that the proposed scheme provides desirable dissemination delay and energy saving.

• Journal of Digital Contents Society
• /
• v.12 no.1
• /
• pp.133-139
• /
• 2011

Structured P2P (peer-to-peer) networks have received much attention in research communities and the industry. The data stored in structured P2P networks can be located in a log-scale time without using central severs. The link-structure of structured P2P networks should be maintained for keeping log-scale search performance of it. When nodes join or leave structured P2P networks frequently, some links become unavailable and search performance is degraded by these links. To sustain search performance of structured P2P networks, periodic link recovery scheme is generally used. However, when the link recovery period is short or long compared with node join and leave rates, it is possible that sufficient number of links are not restored or excessive messages are used after the link-structure is restored. We propose the adaptive link recovery determination algorithm to maintain the link-structure of structured P2P networks when the rates of node joining and leaving are changed dynamically. The simulation results show that the proposed algorithm can maintain similar QoS under various node leaving rates.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.12
• /
• pp.2885-2890
• /
• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.