• Smart Media Journal
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• v.4 no.4
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• pp.47-55
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• 2015

Recently, the computing paradigm has been changing and VoIP technology is being revisited to support various services in ICT field. In this paper, we have designed and implemented the systems of software PBX open source Asterisk using light-weighted virtualization Docker technique, hardware platform, and mobile devices to support voice service based on secured mobile VoIP. And we verified the delay test of network traffics and the secured voice communication test in global real network environment.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.449-458
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• 2010

In this paper, we present a distributed resource allocation algorithm for multi-cell uplink systems that increases the weighted sum of the average data rates over the entire network under the average transmit power constraint of each mobile station. For the distributed operation, we arrange each base station (BS) to allocate the resource such that its own utility gets maximized in a noncooperative way. We define the utility such that it incorporates both the weighted sum of the average rates in each cell and the induced interference to other cells, which helps to instigate implicit cooperation among the cells. Since the data rates of different cells are coupled through inter-cell interferences, the resource allocation taken by each BS evolves over iterations. We establish that the resource allocation converges to a unique fixed point under reasonable assumptions. We demonstrate through computer simulations that the proposed algorithm can improve the weighted sum of the average rates substantially without requiring any coordination among the base stations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.99-106
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• 2015

In this study, we propose Radial basis function Neural Network(RBFNN) using Recursive Weighted Least Square Estimation(RWLSE) to effectively deal with big data class meteorological radar data. In the condition part of the RBFNN, Fuzzy C-Means(FCM) clustering is used to obtain fitness values taking into account characteristics of input data, and connection weights are defined as linear polynomial function in the conclusion part. The coefficients of the polynomial function are estimated by using RWLSE in order to cope with big data. As recursive learning technique, RWLSE which is based on WLSE is carried out to efficiently process big data. This study is experimented with both widely used some Machine Learning (ML) dataset and big data obtained from meteorological radar to evaluate the performance of the proposed classifier. The meteorological radar data as big data consists of precipitation echo and non-precipitation echo, and the proposed classifier is used to efficiently classify these echoes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5143-5158
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• 2018

Improving the intrusion detection system (IDS) is a pressing need for cyber security world. With the growth of computer networks, there are constantly daily new attacks. Machine Learning (ML) is one of the most important fields which have great contribution to address the intrusion detection issues. One of these issues relates to the imbalance of the diverse classes of network traffic. Accuracy paradox is a result of training ML algorithm with imbalanced classes. Most of the previous efforts concern improving the overall accuracy of these models which is truly important. However, even they improved the total accuracy of the system; it fell in the accuracy paradox. The seriousness of the threat caused by the minor classes and the pitfalls of the previous efforts to address this issue is the motive for this work. In this paper, we consolidated stratified sampling, cost function and weighted Support Vector Machine (WSVM) method to address the accuracy paradox of ID problem. This model achieved good results of total accuracy and superior results in the small classes like the User-To-Remote and Remote-To-Local attacks using the improved version of the benchmark dataset KDDCup99 which is called NSL-KDD.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.189-194
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• 2024

This paper presents a radiation-hardened-by-design preamplifier that utilizes a self-compensation technique with a charge-sensitive amplifier (CSA) and replica for total ionizing dose (TID) effects. The CSA consists of an operational amplifier (OPAMP) with a 6-bit binary weighted current source (BWCS) and feedback network. The replica circuit is utilized to compensate for the TID effects of the CSA. Two comparators can detect the operating point of the replica OPAMP and generate appropriate signals to control the switches of the BWCS. The proposed preamplifier was fabricated using a general-purpose complementary metal-oxide-silicon field effect transistor 0.18 ㎛ process and verified through a test up to 230 kGy (SiO₂) at a rate of 10.46 kGy (SiO₂)/h. The code of the BWCS control circuit varied with the total radiation dose. During the verification test, the initial value of the digital code was 39, and a final value of 30 was observed. Furthermore, the preamplifier output exhibited a maximum variation error of 2.39%, while the maximum rise-time error was 1.96%. A minimum signal-to-noise ratio of 49.64 dB was measured.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.5
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• pp.607-614
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• 2018

Oryeong-san is a prescription widely used for diseases where water is stagnant because it has the effect of circulating the water in the body and releasing it into the urine. In order to investigate the mechanisms of oryeong-san, we in this paper construct and analysis the compound-target network of medicinal materials constituting oryeong-san based on a systems pharmacology approach. First, the targets related to the 475 chemical compounds of oryeong-san were searched in the STITCH database, and the search results for the interactions between compounds and targets were downloaded as XML files. The compound-target network of oryeong-san is visualized and explored using Gephi 0.8.2, which is an open-source software for graphs and networks. In the network, nodes are compounds and targets, and edges are interactions between the nodes. The edge is weighted according to the reliability of the interaction. In order to analysis the compound-target network, it is clustered using MCL algorithm, which is able to cluster the weighted network. A total of 130 clusters were created, and the number of nodes in the cluster with the largest number of nodes was 32. In the clustered network, it was revealed that the active compounds of medicinal materials were associated with the targets for regulating the blood pressure in the kidney. In the future, we will clarify the mechanisms of oryeong-san by linking the information on disease databases and the network of this research.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2B
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• pp.137-144
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• 2002

In this paper, we optimize the base station placement and transmission power using genetic approach. A new representation describing base station placement and transmit power with real number is proposed, and new genetic operators are introduced. This new representation can describe the locations, powers, and number of base stations, Considering coverage, power and economy efficiency, we also suggest a weighted objective function. Our algorithm is applied to an obvious optimization problem, and then it is verified. Moreover, our approach is tried in inhomogeneous traffic distribution. Simulation result proves that the algorithm enables to fad near optimal solution according to the weighted objective function.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.367-370
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• 2006

Performances of multiple surrogate models are evaluated in a turbomachinery blade shape optimization. The basic models, i.e., Response Surface Approximation, Kriging and Radial Basis Neural Network models as well as weighted average models are tested for shape optimization. Global data based errors for each surrogates are used to calculate the weights. These weights are multiplied with the respective surrogates to get the final weighted average models. The design points are selected using three level fractional factorial D-optimal designs. The present approach can help address the multi-objective design on a rational basis with quantifiable cost-benefit analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.997-1002
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• 2004

Rumbling sound is one of the most important interior sound of a passenger car. The conventional rumbling noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the rumbling sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network theory has been applied to derivation of sound quality index for rumbling sound of a passenger car.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.153-156
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• 2002

As the use of world wide web is increasing, the number of connections to servers is increasing also. These interactions increase the load of networks and servers. therefore efficient caching strategies for web documents are needed to reduce server load and network traffics by migrating copies of server files closer to the clients that use those files. As One idea of caching policy, we propose a Weighted Disk Cache Replacement Policy(WDCRP) which analyses user's interaction to WWW and adds weight value to each web document. Especially the WDCRP takes account of the history data of cache log, the characteristics of Web requests and the importance of user interactive-actions.