• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1150-1156
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• 2008

This paper introduces the PC clustering of the SIMD structure for a distributed processing of on-line contingency to assess a static security of a power system. To execute on-line contingency analysis of a large-scale power system, we need to use high-speed execution device. Therefore, we constructed PC-cluster system using PC clustering method of the SIMD structure and applied to a power system, which relatively shows high quality on the high-speed execution and has a low price. SIMD(single instruction stream, multiple data stream) is a structure that processes are controlled by one signal. The PC cluster system is consisting of 8 PCs. Each PC employs the 2 GHz Pentium 4 CPU and is connected with the others through ethernet switch based fast ethernet. Also, we consider N-1 line contingency that have high potentiality of occurrence realistically. We propose the distributed process algorithm of the SIMD structure for reducing too much execution time on the on-line N-1 line contingency analysis in the large-scale power system. And we have verified a usefulness of the proposed algorithm and the constructed PC cluster system through IEEE 39 and 118 bus system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.18-27
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• 2019

The process control methods based on the statistical analysis apply the analysis method or mathematical model under the assumption that the process characteristic is normally distributed. However, the distribution of data collected by the automatic measurement system in real time is often not followed by normal distribution. As the statistical analysis tools, the process capability index (PCI) has been used a lot as a measure of process capability analysis in the production site. However, PCI has been usually used without checking the normality test for the process data. Even though the normality assumption is violated, if the analysis method under the assumption of the normal distribution is performed, this will be an incorrect result and take a wrong action. When the normality assumption is violated, we can transform the non-normal data into the normal data by using an appropriate normal transformation method. There are various methods of the normal transformation. In this paper, we consider the Box-Cox transformation among them. Hence, the purpose of the study is to expand the analysis method for the multivariate process capability index using Box-Cox transformation. This study proposes the multivariate process capability index to be able to use according to both methodologies whether data is normally distributed or not. Through the computational examples, we compare and discuss the multivariate process capability index between before and after Box-Cox transformation when the process data is not normally distributed.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1133-1136
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• 1987

In designing and implementing of a distributed system, a programming language which can describe and implement the various interactions between distributed processes in distributed systems is indispensible. High level language constructs such as concurrency. process synchronization between distributed processes and mutually exclusive access to common data could be built in a distributed programming language under the proper support of a language kernel. In this paper, we studied the language constructs a distributed programming language must have and specified the kernel supports necessary in implementing that high level language constructs.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.57-63
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• 2007

Providing the sufficient energy to the mobile device is essential to process the job in distributed wireless network. To solve the restrained conditions of energy problems of mobile devices, this paper suggests the efficient method of processing the distributed job using mobility management in wireless network. Energy consumption can be analyzed using the statistical model and required energy of processing the distributed job in mobile device can be predicted using the mobility management. Therefore, this paper suggests the reliable algorithm to process distributed job through the mobile devices with regular mobility and shows the efficiency of the suggested algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.1-9
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• 2022

The PoN (Proof of Nonce) distributed consensus algorithm basically uses a non-competitive consensus method that can guarantee an equal opportunity for all nodes to participate in the block generation process, and this method was expected to resolve the first trilemma of the blockchain, called the decentralization problem. However, the decentralization performance of the PoN distributed consensus algorithm can be greatly affected by the network transaction transmission delay characteristics of the nodes composing the block chain system. In particular, in the consensus process, differences in network node performance may significantly affect the composition of the congress and committee on a first-come, first-served basis. Therefore, in this paper, we presented a problem by analyzing the decentralization performance of the PoN distributed consensus algorithm, and suggested a fairness control algorithm using a learning-based probabilistic acceptance rule to improve it. In addition, we verified the superiority of the proposed algorithm by conducting a numerical experiment, while considering the block chain systems composed of various heterogeneous characteristic systems with different network transmission delay.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.459-464
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• 2005

The online game system could be largely divided into two parts: servers and clients. Clients accesses to a game server and analyzes the packets transmitted from a server. A game server manages users information and database. U a game server allows a new client to access the server to execute a game, it should accept the access request of the new client maintaining the online connection of the existing users. In this paper, we compare Process method and Thread method within the multiple jobs process methods of a server. Then we propose an asymmetric distributed multi server architecture that is adequate to asymmetric distributed architecture that is widely applied to most game servers. The proposed asymmetric distributed multi server architecture includes login server, game server, communication server and database server to perform its own feature independently. Comparing its other architectures, it shows better performance economically and technically. Especially it improves the stability and expandability of a server.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.663-671
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• 2005

Distributed operation of overall structural design process, by which product and process optimization are implemented, is presented in this paper. The database-interconnected multilevel hybrid method, in which the conventional design method and the optimal design approach are combined, is utilized there. The method selectively takes the accustomed procedure of the conventional method in the conceptional framework of the optimal design. Design conditions are divided into primary and secondary criteria This staged application of design conditions reduces the computational burden for large complex optimization problems. Two kinds of numeric and graphic processes, are simultaneously implemented on the basis of concurrent engineering concepts in the distributed environment of PC networks. Numerical computation on server and graphic works on independent client are communicated through message passing. Numerical design is based on the optimization methodology and the drawing process is carried out by AutoCAD using the AutoLISP programming language. The prototype design experimentation for some steel trusses shows the validity and usability of the method. This study has sufficient adaptability and expandability in methodology, in that it is based on general theory and industry standard systems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.5
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• pp.632-639
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• 2004

In this paper, an inverse problem of glass forming process is studied to determine a number of unknown heat transfer coefficients which are imposed as boundary conditions. An analysis program for transient heat conduction of axi-symmetric dimension is developed to simulate the forming and cooling process. The analysis is repeated until it attains periodic state, which requires at least 30 cycles of iteration. Measurements are made for the temperatures at several available time and positions of glass and moulds in operation. Heat removal by the cooling water from the plunger is also recorded. An optimization problem is formulated to determine heat transfer coefficients which minimize the difference between the measured data and analysis results. Significant time savings are achieved in finite difference based sensitivity computation during the optimization by employing distributed computing technique. The analysis results by the optimum heat transfer coefficients are found to agree well with the measured data.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.297-316
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.