• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1158-1168
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• 2020

The distance vector-hop wireless sensor node location method is one of typical range-free location methods. In distance vector-hop location method, if a wireless node A can directly communicate with wireless sensor network nodes B and C at its communication range, the hop count from wireless sensor nodes A to B is considered to be the same as that form wireless sensor nodes A to C. However, the real distance between wireless sensor nodes A and B may be dissimilar to that between wireless sensor nodes A and C. Therefore, there may be a discrepancy between the real distance and the estimated hop count distance, and this will affect wireless sensor node location error of distance vector-hop method. To overcome this problem, it proposes a wireless sensor network node location method by modifying the method of distance estimation in the distance vector-hop method. Firstly, we set three different communication powers for each node. Different hop counts correspond to different communication powers; and so this makes the corresponding relationship between the real distance and hop count more accurate, and also reduces the distance error between the real and estimated distance in wireless sensor network. Secondly, distance difference between the estimated distance between wireless sensor network anchor nodes and their corresponding real distance is computed. The average value of distance errors that is computed in the second step is used to modify the estimated distance from the wireless sensor network anchor node to the unknown sensor node. The improved node location method has smaller node location error than the distance vector-hop algorithm and other improved location methods, which is proved by simulations.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.977-987
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• 2014

Many of the recent performance evaluation of clustering schemes in wireless sensor networks considered one sink node operation and fixed sink node location without mentioning about any network application requirements. However, application environments have variable requirements about their networks. In addition, network performance is sufficiently influenced by different sink node location scenarios in multi-hop based network. We also know that sink location can influence to the sensor network performance evaluation because of changed multipath of sensor nodes and changed overload spots in multipath based wireless sensor network environment. Thus, the performance evaluation results are hard to trust because sensor network is easily changed their network connection through their routing algorithms. Therefore, we suggest that these schemes need to evaluate with different sink node location scenarios to show fair evaluation result. Under the results of that, network performance evaluation results are acknowledged by researchers. In this paper, we measured several clustering scheme's performance variations in accordance with various types of sink node location scenarios. As a result, in the case of the clustering scheme that did not consider various types of sink location scenarios, fair evaluation cannot be expected.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.473-480
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• 2013

In this paper, location recognition algorithm is developed to improve the accuracy using improve Trilateration. The location recognition algorithm is first calculate the location refer to the measured signal power. Error can be occurred when measure distance with arranged node in specific location. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. Second, we apply algorithm of section filtering. If there are 4 sections in node, we consider 1 section to 6 location recognition coordinates. A special characteristic drawback of RF is that the actual distance is actually farther than the calculated received distance data. This is error is incurred when the signal strength increases. We reduce the location recognition error by applying an improved algorithm as secondary after filtering primary through section filtering.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.917-922
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• 2004

Mobile ad hoc networks (MANETs) are networks of mobile nodes that have no fixed network infrastructure. Since the mobile node's location changes frequently, it is an attractive area to maintain the node's location efficiently. In this paper, we present an adaptive randomized database group (ARDG) scheme to manage the mobile nodes mobility in MHANETs. The proposed scheme stores the network nodes' location in location databases to manage the nodes' mobility. When a mobile node changes its location or needs a node's location, the node randomly select some databases to update or que교 the location information. The number of the selected databases is fixed in the case of querying while the number of the databases is determined according to the node's popularity in the case of updating. We evaluated the performance of the proposed scheme using an analytical model, and compared the performance with that of the conventional randomized database group (RDG) scheme.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.289-295
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• 2012

Routing technique of wireless sensor network that is presented to improve effectiveness of consumption in energy at the previous study is existing in various ways, however for routing, its own location data and nodes' location data close to with 1-hop distance should be kept. And it uses multi-hop transmission method that transmits data to BS node via several nodes. This technique makes electronic consumption of sensor node and entire network's energy consumption so that it makes effective energy management problem. Therefore, this paper suggests location based 1-hop routing technique of BS node that satisfies distance $d{\pm}{\alpha}$ with source node using RSSI and radio wave range of sensor node.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.491-493
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• 2006

We introduce Location PDA Program which is a mobile system to display current location on PDA. The current location is calculated based on collecting location through each fixed node. Each fixed node sends location information of mobile node to Cell Manager system. And then, Cell Manager calculates final location based on related information and sends it to every mobile system which is connected to server and displays current location.

• Journal of Korea Multimedia Society
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• v.24 no.6
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• pp.789-795
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• 2021

In order to provide useful Internet of Things (IoT) services, the locations of IoT devices should be well managed. However, frequent location updates of lots of IoT devices result in signaling overhead in networks. To solve this problem, this paper utilizes the opportunistic fog node (OFN) which is opportunistically available according to the mobility to perform the location updates as a representative of IoT devices. Therefore, the location updates through OFN can reduce the signaling loads of networks. To show the performance of the proposed scheme, we develop an analytic model for the opportunistic location update offloading probability that the location update can be offloaded to OFN from the IoT device. Then, the extensive simulation results are given to validate the analytic model and to assess the performance of the proposed scheme in terms of the opportunistic location update offloading probability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.364-367
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• 2007

We combined CC2431(Chipcon, Norway), as the platform for the Indoor Location Tracking, which follows Zigbee/IEEE802.15.4 standards in RSSI (Received Signal Strength Indicator) and Base Station Node and then, embodied Indoor Location Tracking System. CC2431 is composed of the Reference Node that transfer its current position at the designated place and the Blind Node. The Blind node receives the current position(X and Y coordinates) of the Reference Node fields which are being contiguous and also, calculates its current position and transfers it to the Base Station Node. The base station node is used for receiving the current position of blind node and passing its data to the PC as a gateway. We can make sure where is the Blind Node not only from the out-of-the-way place of the server side but from the outside in a real-time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2196-2204
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• 2015

Location-based density information of mobile node could be used well in various, new and expanding areas such as location-based services, internet of things, smart grid technologies, and intelligent building. In general, receiving mobile nodes of a wireless mobile node depend on the maximum communication range of transmitting mobile node. In this paper, efficient computing method for mobile node using Delaunay triangulation is proposed, which is irrespective of mobile node's maximum communication range and reflect relative location in a given situation. Proposed method may be good used to find out the density of network constructed by various max communication range devices as Internet of Things. This method suggested in this paper could work well for location-based services, internet of things, smart grid technologies, and intelligent building.

• Journal of Gastric Cancer
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• v.11 no.2
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• pp.86-93
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• 2011

Purpose: When performing a laparoscopic assisted gastrectomy, a function-preserving gastrectomy is performed depending on the location of the primary gastric cancer. This study examined the incidence of lymph node metastasis by the lymph node station number by tumor location to determine the optimal extent of the lymph node dissection. Materials and Methods: The subjects consisted of 1,510 patients diagnosed with gastric cancer who underwent a gastrectomy between 1996 and 2005. The patients were divided into three groups: upper, middle and lower third, depending on the location of the primary tumor. The lymph node metastasis patterns were analyzed in the total and early gastric cancer patients. Results: In all patients, lymph node station numbers 1, 2, 3, 7, 10 and 11 metastases were dominant in the cancer originating in the upper third, whereas station numbers 4, 5, 6 and 8 were dominant in the lower third. In early gastric cancer patients, the station number of lymph nodes with a metastasis did not show a significant difference in stage pT1a disease. On the other hand, a metastasis in lymph node station number 6 was dominant in stage pT1b disease that originated in the lower third of the stomach. Conclusions: When performing a laparoscopic-assisted gastrectomy for early gastric cancer, a limited lymphadenectomy is considered adequate during a function-preserving gastrectomy in mucosal (T1a) cancer. On the other hand, for submucosal (T1b) cancer, a number 6 node dissection should be performed when performing a pylorus preserving gastrectomy.