• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.105-106
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• 2019

본 논문에서는 무선 센서 네트워크(Wireless Sensor Network, WSN) 환경에 배치되어 물리적 데이터를 감지하는 각 센서들의 데이터를 수집을 위한 싱크(Sink)가 일정 주기로 이동 및 재배치되는 싱크 마이그레이션(Migration) 과정에 있어 다음 배치 위치를 효율적으로 선정하기 위해 클러스터 헤드(Cluster Head, CH)를 기준으로 영역 검색 단계를 추가하여 재배치 정확성 및 효율성 증대 기법을 제안한다. 본 논문에서는 WSN 환경을 바탕으로 싱크 재배치 과정에 해당 기법을 적용하여 시뮬레이션 하였으며, 해당 실험의 결과에 따르면 싱크 재배치의 정확성 및 효율성 증대로 전체 영역에 대한 고른 데이터 수집 및 소모 에너지 균형이 향상되었다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.157-165
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• 2017

Intelligent transportation systems are currently being developed for elemental technology development of cooperative intelligent transport systems, which enable vehicles to communicate with each other or reduce the risk of traffic accidents, We have been defining and standardizing services according to the purpose of solving traffic safety problems depending on countries. Therefore, in this study, the developed countries of V2X(vehicle-to-everything) based on USA, Europe, Japan, etc., analyzed the service cases selected in the field demonstration stage after completion of the element technology devanalyzed the service cases selected in the field demonstration stage after completion of the element technology development, and to suggest the direction of futureelopment, and to suggest the direction of future policy direction.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.121-129
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• 2011

One of the major challenges of minimum energy consumption for wireless sensor networks(WSN) environment. LEACH protocol is hierarchical routing protocol that obtains energy efficiency by using clustering. However, LEACH protocol in each round, because the new cluster configuration, cluster configuration, whenever the energy consumed shorten the life of the network. Therefore in this paper, the cluster is formed in WSN environment in early stage and the problems with energy waste have been solved by selecting C-node. In the initial round of proposed model uses 26 percent more than traditional LEACH energy consumption. However, as the round is ongoing, it has been proved by the network simulation tool that the waste of energy could be diminished up to 35%.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.373-377
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• 2022

Wireless sensor networks are being used in various fields. Wireless sensor networks are applied in many areas, such as security, military detection, environmental management, industrial control, and home automation. There is a problem about the limit of energy that the sensor network basically has. In this paper, we propose the LEACH-CCBD (Low Energy Adaptive Clustering hierarchy - Centrailized with Cluster and Basestation Distance) algorithm that uses energy efficiently by improving network transmission based on LEACH-C among the representative routing protocols. The LEACH-CCBD algorithm is a method of assigning a cluster head to a cluster head by comparing the sum of the distance from the member node to the cluster distance and the distance from the cluster node to the base station with respect to the membership of the member nodes in the cluster when configuring the cluster. The proposed LEACH-CCBD used Matlab simulation to confirm the performance results for each protocol. As a result of the experiment, as the lifetime of the network increased, it was shown to be superior to the LEACH and LEACH-C algorithms.

• Annual Conference of KIPS
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• 2021.11a
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• pp.948-951
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• 2021

본 논문에서는 직육면체 형태의 실내 공간에서 다중 개체 영역을 검출하는 방법을 제안한다. 평면 검출 알고리즘은 평면성을 띄지 않거나 관측이 미흡한 영역에 대해 기하 정보를 검출할 수 없다. 이로 인해 장애물과 같은 개체의 영역을 파악할 수 없는 한계점이 있다. 제안 방법은 유클리드 클러스터링을 기반으로 군집화를 수행하고, 클러스터의 간소화를 통해 다중 개체 영역을 검출한다. 제안 방법은 직육면체 공간의 내부표면을 활용해 직육면체 공간과 좌표계를 공유하는 주요 개체들의 영역을 다량으로 검출한다. 제안 방법은 실험을 통해 다중 개체 영역이 적합하게 검출되었음을 보인다.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1609-1622
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• 2009

In wireless sensor networks, a clustering protocol is an efficient method to prolong network lifetime. In general, it results in more energy consumption at the cluster-head node. Hence, such a protocol must changes the cluster formation and cluster-head node in each round to prolong the network lifetime. But, this method also causes large amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new clustering algorithm. In this algorithm, we exclude duplicated data of adjacent nodes and transmits the threshold value. We define a group as the sensor nodes within close proximity of each other. In a group, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, group is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(group). In the group with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of group size. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• Journal of Korea Multimedia Society
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• v.11 no.8
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• pp.1082-1092
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• 2008

In wireless sensor networks, clustering protocol such as LEACH is an efficient method to increase whole networks lifetime. However, this protocol result in high energy consumption at the cluster head node. Hence, this protocol must changes the cluster formation and cluster head node in each round to prolong the network lifetime. But this method also causes a high amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new cluster formation algorithm. In this algorithm, we define a intra cluster as the sensor nodes within close proximity of each other. In a intra cluster, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, intra cluster is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(intra clusters). In the intra cluster with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of intra cluster size. Also, in the steady-state phase, a node in each intra cluster senses and transmits data to its cluster-head of network cluster on the round-robin basis. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.267-273
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• 2011

In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.17-24
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• 2012

As the resources and power on Ad-hoc networks are limited, new data aggregation techniques are required for energy efficiency. The current research on data aggregation techniques is actively in progress, but existing studies don't consider the density of nodes. If nodes are densely placed in a particular area, the information which the sensor nodes placed on those areas detect can be judged as very strong association. But, the energy spent transmitting this information is a waste of energy. In this paper the densely-concentrated node area is designated as Hotspot_Zone in the multi-hop clustering environment using the AMC and a key node is selected in the area. If the request message of data aggregation is transmitted, the key node among the neighboring nodes sends its environmental information to a manager to avoid duplicate sensing information. Therefore, the life of networks can be prolonged due to this.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.221-226
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• 2019

The characteristic of the beta wave among the EEG waves corresponds to the stress area of human perception. The over-bandwidth of the stress is extracted by analyzing the beta-wave correlation between the low-bandwidth and high-bandwidth. We present a KMeans clustering analysis model for unsupervised machine learning to construct an analytical model for analyzing and extracting the beta-wave correlation. The proposed model classifies the beta wave region into clusters of similar regions and identifies anomalous waveforms in the corresponding clustering category. The abnormal group of waveform clusters and the normal category leaving region are discriminated from the stress risk group. Using this model, it is possible to discriminate the degree of stress of the cognitive state through the EEG waveform, and it is possible to manage and apply the cognitive state of the individual.