• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.207-214
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• 2000

For last 20 years, a number of researches and developments on finite element mesh generation has been carried out and most of them are comported of node generation part and node generation part. However these algorithms are inefficient in mesh veneration process and difficult to control the shape of elements when comparing with the generation of nodes and elements concurrently. In this study, therefore, an algorithm it proposed to generate nodes and elements concurrently for various two-dimensional objects having multiple holes. Inner node generation is performed by choosing three consecutive boundary nodes and comparing them with other close boundary nodes. As soon as inner nodes are determined, element generation is conducted based on the comparison of the distances among the generated inner nodes, three consecutive boundary nodes and other close boundary nodes. the generated element nodes become new boundary nodes for further repeated process. The processes are repeated through out each region until three consecutive boundary nodes finally form a tirangular element.

• International Journal of Contents
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• v.10 no.1
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• pp.18-22
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• 2014

Hidden nodes have a key role in the information processing of feed-forward neural networks in which inputs are processed through a series of weighted sums and nonlinear activation functions. In order to understand the role of hidden nodes, we must analyze the effect of the nonlinear activation functions on the weighted sums to hidden nodes. In this paper, we focus on the effect of nonlinear functions in a viewpoint of information theory. Under the assumption that the nonlinear activation function can be approximated piece-wise linearly, we prove that the entropy of weighted sums to hidden nodes decreases after piece-wise linear functions. Therefore, we argue that the nonlinear activation function decreases the uncertainty among hidden nodes. Furthermore, the more the hidden nodes are saturated, the more the entropy of hidden nodes decreases. Based on this result, we can say that, after successful training of feed-forward neural networks, hidden nodes tend not to be in linear regions but to be in saturated regions of activation function with the effect of uncertainty reduction.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.27-34
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• 2013

In wireless sensor networks, sensors need to communicate with each other to send their sensing data to the administration node and so they are susceptible to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic approaches. A behavior-based detection is used to defend against such attacks in which some specialized monitoring nodes overhear the communications of their neighbors to detect bad packets. As monitoring nodes use more energy, it is desirable to use the minimal number of monitoring nodes to cover the whole or maximal part of the network. The monitoring nodes can either be selected among the deployed normal nodes or differ in type from normal nodes. In this study, we have developed an algorithm for selecting the predefined number of monitoring nodes needed to cover the maximum number of normal nodes when the different types of normal nodes and monitoring nodes are deployed. We also have investigated experimentally how the number of monitoring nodes and their transmission range affect the connection ratio of the monitoring nodes and the coverage of the normal nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1113-1135
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• 2018

Existing trust evaluation models for wireless sensor networks can accurately and objectively evaluate trust value of nodes, but the nodes' energy saving problem was ignored. Especially when there are a few malicious nodes in a network, the overall trust value calculation for all nodes would waste lots of energy. Beside that, the network failure caused by nodes death was also not considered. In this paper, we proposed a method for avoiding energy hole which applied trust evaluation models and a trust evaluation method based on information entropy, so as to achieve the purpose of improving nodes utilization. Simulation results show that the proposed method can effectively improve nodes utilization, and it has reasonable detection rate and lower false alert rate compared to other classical methods.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.694-708
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• 2018

China possesses a passenger dedicated line system of large scale, passenger flow intensity with uneven distribution, and passenger nodes with complicated relations. Consequently, the significance of passenger nodes shall be considered and the dissimilarity of passenger nodes shall be analyzed in compiling passenger train operation and conducting transportation allocation. For this purpose, the passenger nodes need to be hierarchically divided. Targeting at problems such as hierarchical dividing process vulnerable to subjective factors and local optimum in the current research, we propose a clustering approach based on self-organizing map (SOM) and k-means, and then, harnessing the new approach, hierarchical dividing of passenger dedicated line passenger nodes is effectuated. Specifically, objective passenger nodes parameters are selected and SOM is used to give a preliminary passenger nodes clustering firstly; secondly, Davies-Bouldin index is used to determine the number of clusters of the passenger nodes; and thirdly, k-means is used to conduct accurate clustering, thus getting the hierarchical dividing of passenger nodes. Through example analysis, the feasibility and rationality of the algorithm was proved.

• Korean Journal of Veterinary Research
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• v.39 no.5
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• pp.855-864
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• 1999

Hemal nodes and hemolymph nodes are lymphoid organs that share morphologic and functional characteristics of lymph nodes and spleens. The aim of the present study was to obtain new informations on the distinct morphological structures of hemal nodes and hemolymph nodes according to ages, and to get the basic data for their functions in Korean native goats. Goats were divided into 5 groups, consisting of 3 animals aged 1, 3, 6, 10 and 12 months, respectively. Ultrastructural features of the organs were observed by transmission and scanning electron microscopes. The sinuses of hemal nodes and hemolymph nodes were lined by endothelial-like reticular cells which had euchromatin-rich nuclei and many cytoplasmic processes, surrounding collagen fibrils. Macrophages containing phagocytosed erythrocytes were often noted in the diffuse lymphatic tissues of hemal nodes and hemolymph nodes. Some mast cells were in contact with the plasma cells near the blood vessel. Hemal nodes and hemolymph nodes had venous sinusal-like vessels which were different from the deep sinus. The lymph vessels with valves were observed in the capsule of the hemolymph node. There were no ultrastructural differences of the organs in the age different groups of the animals. These results suggest that hemal nodes and hemolymph nodes may take part in hemopoiesis, blood filtration and immune reaction in Korean native goats.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.820-827
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• 2014

One of the basic problems in Wireless Sensor Networks (WSNs) is the localization of the sensor nodes based on the known location of numerous anchor nodes. WSNs generally consist of a large number of sensor nodes and recording the location of each sensor nodes becomes a difficult task. On the other hand, based on the application environment, the nodes may be subject to mobility and their location changes with time. Therefore, a scheme that will autonomously estimate or calculate the position of the sensor nodes is desirable. This paper presents an intelligent localization scheme, which is an artificial neural network (ANN) based localization scheme used to estimate the position of the unknown nodes. In the proposed method, three anchors nodes are used. The mobile or deployed sensor nodes request a beacon from the anchor nodes and utilizes the received signal strength indicator (RSSI) of the beacons received. The RSSI values vary depending on the distance between the mobile and the anchor nodes. The three RSSI values are used as the input to the ANN in order to estimate the location of the sensor nodes. A feed-forward artificial neural network with back propagation method for training has been employed. An average Euclidian distance error of 0.70 m has been achieved using a ANN having 3 inputs, two hidden layers, and two outputs (x and y coordinates of the position).

• Journal of Chest Surgery
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• v.25 no.11
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• pp.1180-1184
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• 1992

The use of computed tomography of the chest in mediastinal staging of lung carcinoma lies the premiss that malignant lymph nodes are larger than benign ones. We have studied the size of mediastinal lymph nodes & the malignancy rate in 55 lung carcinomas from March 1990 to July 1992 at the Department of Thoracic and Cardiovascular Surgery, Yongdong Severance Hospital, Yonsei University College of medicine. The lack of relationship between the size of mediastinal lymph node and the probability of malignancy helps to clarify the limitations of the use of computed tomography in the staging of the mediastinum in lung carcinoma. There was no tendency for all malignant lymph nodes to be larger than benign nodes. To allow comparison with our data, malignancy rates for all lymph nodes larger than 10mm are 24.8% in sensitivity & benign rates for all lymph nodes less than 10mm are 96% in specificity. But all mediastinal lymph nodes larger than 30mm are metastatic lymph nodes in our cases. We are going to try to have thoracotomy for complete resection of lung carcinoma as possible as we can if there no evidence of contralateral mediastinal metastases of lymph nodes, even though there are large mediastinal lymph nodes in lung carcinoma.

• East Asian mathematical journal
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• v.22 no.2
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• pp.163-170
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• 2006

In networking, it is essential to analyse the nodes along with their neighbours. The properties of fuzzy finite graphs are very much useful in obtaining solutions to many problems like traffic congestion problem. In this paper, free nodes and busy nodes are defined and the properties of nodes are examined at various levels of their degrees.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3823-3840
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• 2017

This paper analyzes the nodes deployment optimization problem in energy constrained wireless sensor networks, which multi-hop cooperative beamforming (CB) based cooperative-multi-input-single-output (CMISO) transmission is adopted to reduce the energy consumption. Firstly, we establish the energy consumption models for multi-hop SISO, multi-hop DSTBC based CMISO, multi-hop CB based CMISO transmissions under random nodes deployment. Then, we minimize the energy consumption by searching the optimal nodes deployment for the three transmissions. Furthermore, numerical results present the optimal nodes deployment parameters for the three transmissions. Energy consumption of the three transmissions are compared under optimal nodes deployment, which shows that CB based CMISO transmission consumes less energy than SISO and DSTBC based CMISO transmissions. Meanwhile, under optimal nodes deployment, the superiorities of CB based CMISO transmission over SISO and DSTBC based CMISO transmissions can be more obvious when path-loss-factor becomes low.