• The KSFM Journal of Fluid Machinery
• /
• v.10 no.3 s.42
• /
• pp.33-38
• /
• 2007

Fan selection procedure and fan noise evaluation method are presented for the system electronic cooling by combining FNM(Flow Network Model) and fan noise correlation model. Internal flow paths and distribution in electronic system we analyzed by using the FNM with the flow resistances for flow elements of the system. Based on the fan operation point predicted from the FNM analysis results, the present fan noise model predicts overall sound power, pressure levels and spectrum. The predictions of the flow distribution, the fan operation and the noise level in electronic system by the present method are well agreed with 3-D CFD and actual test results.

• ETRI Journal
• /
• v.10 no.2
• /
• pp.13-19
• /
• 1988

This paper describes on the interworking services. interworking issues and the design concepts in the Interworking System (IWS) between Pubilc Switched Telephone Network (PSTN) and Packet Switched Data Network (PSDN), which has been developed at the Electronics and Tedecommunications Research Institute (ETRI). As a gateway between PSTN and PSDN, IWS provides the interconnection between PSTN and PSDN. In addition to the provision of basic interconnection services (i.e. dial-in/dial-out services), IWS provides the Maintenance and Administration (M&A) services for system itself and the supplementary services such as the call barring, direct call and closed user group. The architecture of IWS is based on the multiprocessor system with single system bus. And a multiprocessor real time kernel is used to support the inter-board communication as well as the inter-process commmunications. Especially, the operation and maintenance functions of IWS are treated in detail.

• Journal of the Korea Society for Simulation
• /
• v.14 no.1
• /
• pp.9-18
• /
• 2005

Attempts to attack hosts in the network have become diverse, due to crackers developments of new creative attacking methods. Under these circumstances the role of intrusion detection system as a security system component gets considerably importance. Therefore, in this paper, we have suggested multiple intrusion detection system based on the contract net protocol which provides the communication among multiple agents. In this architecture, fuzzy rule based system has been applied for agent selection among agents competing for being activated. The simulation models are designed and implemented based on DEVS formalism which is theoretically well grounded means of expressing discrete event simulation models.

• KSTLE International Journal
• /
• v.1 no.1
• /
• pp.21-28
• /
• 2000

A computer program fur the analysis of engine lubrication systems has been developed. And a case study of a four cylinders gasoline engine is illustrated. This paper gives the mathematical models far oil flow through hydraulic tappet as well as those of oil jet and plain journal bearings. And the flow from an oil pump and the flow resistance through an oil filter is considered at various temperatures. In the analysis, the various design guidelines are applied. The distribution of flow and pressure of an engine lubrication system are calculated, and the pressure data compared with the experimental data at a few points in the engine lubrication system. This method is helpful to design of engine lubrication system efficiently.

• Journal of Digital Contents Society
• /
• v.7 no.3
• /
• pp.193-197
• /
• 2006

In this paper, We proposed monitoring verification system using virtual reality simulation technology in monitoring fields for peculiar environment. Also, we analyzed the proposed system about required technology issues and operation process. The proposed monitoring verification system available wireless communication network is expected that application is possible in medical treatment field or special dangerous article processing filed as well as monitoring verification of mobile electric railcar

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.271-275
• /
• 2021

The article assesses the role of the human factor in management, analyzes the personnel policy, as well as the style and methods of management at the enterprise. The purpose of the article is to study the place and role of personnel management in the general management system of an organization. Particular tasks of the research have been solved: the place and role of personnel management in the system of general management theory have been determined; determined the place of personnel management in the system of modern sciences.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.7
• /
• pp.1858-1872
• /
• 2023

With the advance of radar technologies, the availability of synthetic aperture radar (SAR) images increases. To improve application of SAR images, a management system for SAR images is proposed in this paper. The system provides trainable land cover classification module and display of SAR images on the map. Users of the system can create their own classifier with their data, and obtain the classified results of newly captured SAR images by applying the classifier to the images. The classifier is based on convolutional neural network structure. Since there are differences among SAR images depending on capturing method and devices, a fixed classifier cannot cover all types of SAR land cover classification problems. Thus, it is adopted to create each user's classifier. In our experiments, it is shown that the module works well with two different SAR datasets. With this system, SAR data and land cover classification results are managed and easily displayed.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.73-82
• /
• 2022

Early detection continues to be the mainstay of breast cancer control as well as the improvement of its treatment. Even so, the absence of cancer symptoms at the onset has early detection quite challenging. Therefore, various researchers continue to focus on cancer as a topic of health to try and make improvements from the perspectives of diagnosis, prevention, and treatment. This research's chief goal is development of a system with deep learning for classification of the breast cancer as non-malignant and malignant using mammogram images. The following two distinct approaches: the first one with the utilization of patches of the Region of Interest (ROI), and the second one with the utilization of the overall images is used. The proposed system is composed of the following two distinct stages: the pre-processing stage and the Convolution Neural Network (CNN) building stage. Of late, the use of meta-heuristic optimization algorithms has accomplished a lot of progress in resolving these problems. Teaching-Learning Based Optimization algorithm (TIBO) meta-heuristic was originally employed for resolving problems of continuous optimization. This work has offered the proposals of novel methods for training the Residual Network (ResNet) as well as the CNN based on the TLBO and the Genetic Algorithm (GA). The classification of breast cancer can be enhanced with direct application of the hybrid TLBO- GA. For this hybrid algorithm, the TLBO, i.e., a core component, will combine the following three distinct operators of the GA: coding, crossover, and mutation. In the TLBO, there is a representation of the optimization solutions as students. On the other hand, the hybrid TLBO-GA will have further division of the students as follows: the top students, the ordinary students, and the poor students. The experiments demonstrated that the proposed hybrid TLBO-GA is more effective than TLBO and GA.

• Journal of Advanced Navigation Technology
• /
• v.27 no.1
• /
• pp.43-49
• /
• 2023

Object tracking is being studied with various techniques such as Kalman filter and Luenberger tracker. Even in situations, such as the one in which the system model is not well specified, to which existing signal processing techniques are not successfully applicable, it is possible to design artificial neural networks to track objects. In this paper, we propose an artificial neural network, which we call 'maximum-likelihood weighted-average neural network', to continuously track unpredictably moving objects. This neural network does not directly estimate the locations of an object but obtains location estimates by making weighted average combining various results of maximum likelihood tracking with different data lengths. We compare the performance of the proposed system with those of Kalman filter and maximum likelihood object trackers and show that the proposed scheme exhibits excellent performance well adapting the change of object moving characteristics.

• Journal of Korea Multimedia Society
• /
• v.17 no.8
• /
• pp.988-994
• /
• 2014

Software Defined Network (SDN) is a new technology in computer network area which enables user to centralize control plane. The security issue is important in computer network to protect system from attackers. SYN flooding attack is one of Distributed Denial of Service attack methods which are popular to degrade availability of targeted service on Internet. There are many methods to protect system from attackers, i.e. firewall and IDS. Even though firewall is designed to protect network system, but it cannot mitigate DDoS attack well because it is not designed to do so. To improve performance of DDOS mitigation we utilize another mechanism by using SDN technology such as OpenFlow and sFlow. The methodology of sFlow to detect attacker is by capturing and sum cumulative traffic from each agent to send to sFlow collector to analyze. When sFlow collector detect some traffics as attacker, OpenFlow controller will modify the rule in OpenFlow table to mitigate attacks by blocking attack traffic. Hence, by combining sum cumulative traffic use sFlow and blocking traffic use OpenFlow we can detect and mitigate SYN flooding attack quickly and cheaply.