• Journal of the Korea Fashion and Costume Design Association
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• v.15 no.2
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• pp.77-89
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• 2013

This study investigated the formation of silhouette and hemline shape of knit flare skirts according to the properties of knit material through virtual clothing with a 3D virtual clothing system called i-Designer of Technoa, thus building a database of the property data of knit material to reduce the number of sample making steps repeated and implemented several times in the process of clothes making. The results would help to estimate a silhouette in advance, offer assistance to the development of original knit wear, and explore ways to provide basic data for the development of the knit industry of the nation. The investigator made 12 kinds of experimental clothes to the angles(width of skirt: $90^{\circ}$ and $180^{\circ}$), gauge(7G, 12G, and 15G), and grain directions(wale and bias direction) of experimental clothes for virtual clothing. The dynamic characteristics of knit skirt samples according to each gauge were measured with the KES-FB system. Draper shapes were analyzed with the sectional shape data of hemline based on i-Designer. As for the measurements of the sectional shape of hemline and the formation of silhouette, the number of nodes, the average height of node mountains and valleys, and the hemline width right and left and before and after increased at the angle of $180^{\circ}$ than $90^{\circ}$. As gauges multiplied, the number of nodes, and silhouette angle dropping. When considering grain directions, the number of nodes and silhouette index increased in the wale direction at the angle of $90^{\circ}$ with the number of nodes and silhouette angle increasing in the wale direction at the angle of $180^{\circ}$.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.81-88
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• 2017

Solar-powered wireless sensor nodes can use extra energy to obtain additional data to increase the precision. However, if the amount of data sensed is increased indiscriminately, the overhead of relay nodes may increase, and their energy may be exhausted. In this paper, we introduce a sensing and compression rate selection scheme to increase the amount of data obtained while preventing energy exhaustion. In this scheme, the neighbor nodes of the sink node determine the limit of data to be transmitted according to the allocated energy and their descendant nodes, and the other nodes select a compression algorithm appropriate to the allocated energy and the limitation of data to be transmitted. A simulation result verifies that the proposed scheme gathers more data with a lower number of blackout nodes than other schemes. We also found that it adapts better to changes in node density and the amount of energy harvested.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.41-51
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• 2006

Clustering is to group similar objects into clusters. Until now there are a lot of approaches using Self-Organizing feature Maps (SOFMS) But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of c output-layer nodes, if they want to make c clusters. This approach has problems to classify elaboratively. This Paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We un find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. The proposed algorithm was tested on well-known IRIS data and TSPLIB. The results of this computational study demonstrate the superiority of the proposed algorithm.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.1-10
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• 2021

The Internet of things (IoT) is the main advancement in data processing and communication technologies. In IoT, intelligent devices play an exciting role in wireless communication. Although, sensor nodes are low-cost devices for communication and data gathering. However, sensor nodes are more vulnerable to different security threats because these nodes have continuous access to the internet. Therefore, the multiparty security credential-based key generation mechanism provides effective security against several attacks. The key generation-based methods are implemented at sensor nodes, edge nodes, and also at server nodes for secure communication. The main challenging issue in a collaborative key generation scheme is the extensive multiplication. When the number of parties increased the multiplications are more complex. Thus, the computational cost of batch key and multiparty key-based schemes is high. This paper presents a Secure Multipart Key Distribution scheme (SMKD) that provides secure communication among the nodes by generating a multiparty secure key for communication. In this paper, we provide node authentication and session key generation mechanism among mobile nodes, head nodes, and trusted servers. We analyzed the achievements of the SMKD scheme against SPPDA, PPDAS, and PFDA schemes. Thus, the simulation environment is established by employing an NS 2. Simulation results prove that the performance of SMKD is better in terms of communication cost, computational cost, and energy consumption.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.73-78
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• 2016

In wireless sensor networks, sensors have capabilities of sensing and wireless communication, computing power and collect data such as sound, movement, vibration. Sensors need to communicate wirelessly to send their sensing data to other sensors or the base station and so they are vulnerable to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic mechanisms. To defend against such attacks, a behavior-based attack detection is used in which some specialized monitoring nodes overhear the communications of their neighbors(normal nodes) to detect illegitimate behaviors. It is desirable that the total sensing area of normal nodes covered by monitoring nodes is as large as possible. The previous researches have focused on selecting the monitoring nodes so as to maximize the number of normal nodes(node coverage), which does not guarantee that the area sensed by the selected normal nodes is maximized. In this study, we have developed an algorithm for selecting the monitoring nodes needed to cover the maximum sensing area. We also have compared experimentally the covered sensing areas computed by our algorithm and the node coverage algorithm.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.61-62
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• 2006

In this paper, using Bianchi's model with channel idle probability we analyze performance of power management scheme of IEEE 802.11 DCF according to ATIM window size and number of nodes for wireless ad hoc networks. The analytical results show that, when the number of nodes is given, the selected ATIM window size limits the performance.

• Journal of Gastric Cancer
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• v.14 no.2
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• pp.111-116
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• 2014

Purpose: The standard surgical procedure recommended to treat gastric cancer in advanced cases is dissection of D2 lymph nodes (LNs). However, the optimum number of LNs that should be retrieved in advanced gastric cancer (AGC) remains debatable. Therefore, this study aimed to investigate the optimum number of retrieved LNs and determine the clinical implications of retrieved LN numbers on the treatment of AGC. Materials and Methods: Of 575 AGC patients reviewed, 369 who underwent open curative gastrectomy with D2 or more extensive LN dissection at our institution were analyzed according to their clinicopathologic characteristics and number of LNs retrieved. Results: Multivariate regression analysis revealed that tumor size (P=0.006), depth of invasion (P=0.000), LN metastasis (P=0.000), and stage (P=0.000) were independent variables with predictive value. The 5-year survival rates were differed significantly according to the numbers of LNs retrieved ([1] 15~25 vs. >25 and [2] 15~39 vs. ${\geq}40$) in patients with differentiated carcinoma. Conclusions: Tumor size, depth of invasion, LN metastasis, and stage were independent predictive factors for survival. The number of retrieved LNs was significantly associated with a long-term survival benefit in patients with differentiated carcinoma. Therefore, our data suggest that the retrieval of a minimum of 15 LNs may not be sufficient to warrant a recommendation for further curative surgery and that extensive LN dissection should be considered in advanced carcinoma of the differentiated type.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.152-159
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• 2002

Neural networks are used to predict the sense of touch of polyurethane coated fabrics. In this study, we used the multi layer perceptron (MLP) neural networks in Neural Connection. The learning algorithm for neural networks is back-propagation algorithm. We used 29 polyurethane coated fabrics to train the neural networks and 4 samples to test the neural networks. Input variables are 17 mechanical properties measured with KES-FB system, and output variable is the sense of touch of polyurethane coated fabrics. The influence of MLF function, the number of hidden layers, and the number of hidden nodes on the prediction accuracy is investigated. The results were as follows: MLP function, the number of hidden layer and the number of hidden nodes have some influence on the prediction accuracy. In this work, tangent function, the architecture of the double hidden layers and the 24-12-hidden nodes has the best prediction accuracy with the lowest RMS error. Using the neural networks to predict the sense of touch of polyurethane coated fabrics has hotter prediction accuracy than regression approach used in our previous study.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1239-1249
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• 1990

In this paper, using the neural network design techniques, an adaptive Mahalanobis distance classifier(AMDC) is designed. This classifier has three layers: input layer, internal layer and output layer. The connection from input layer to internal layer is fully connected, and that from internal to output layer has partial connection that might be thought as an Oring. If two ormore clusters of patterns of one class are laid apart in the feature space, the network adaptively generate the internal nodes, whhch are corresponding to the subclusters of that class. The number of the output nodes in just same as the number of the classes to classify, on the other hand, the number of the internal nodes is defined by the number of the subclusters, and can be optimized by itself. Using the method of making the subclasses, the different patterns that are of the same class can easily be distinguished from other classes. If additional training is needed after the completion of the traning, the AMDC does not have to repeat the trainging that has already done. To test the performance of the AMDC, the experiments of classifying 500 Hangeuls were done. In experiment, 20 print font sets of Hangeul characters(10,000 cahracters) were used for training, and with 3 sets(1,500 characters), the AMDC was tested for various initial variance \ulcornerand threshold \ulcorner and compared with other statistical or neural classifiers.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.63-71
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• 1986

In the organization with a hierarchical network queue structure a production function is derived whose input factors are the numbers of servers at nodes and output is the number of served customers. Its useful properties are investigated. Using this production function, the contributions of servers to the number of served customers are studied. Also given an expected waiting time in the system for each customer, the optimal numbers of servers at nodes are obtained minimizing a cost function.