• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.18-34
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• 1999

This paper is a brief review of the different procedures that are available for fitting theoretical distributions to data. The use of each technique Is illustrated by reference to a distribution system which including the Pearson, Johnson and Burr functions. These functions can be used to calculate percent out of specification. Therefore, in this paper a new method for estimating a measure of process capability for Gamma distributed variable data proposed using the percentage nonconforming. Process capability indices combines with the percentage nonconforming Information can be used to evaluate more accurately process capability.

• Journal of the Korea Safety Management & Science
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• v.2 no.2
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• pp.41-55
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• 2000

The main objective of this paper is to propose a measure of evaluation for non-normal process capability. If a process is not normally distributed, but normal-based techniques are used, serious errors can result. Our approach to solve this problem is that the Pearson system, the Johnson system, and the Burr system are selected for estimating a measure of process capability using the percentage nonconforming. In this paper, we found that the Pearson system and the Johnson system were a conparatively reasonable methods to calculate out of specification by example.

• ETRI Journal
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• v.35 no.3
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• pp.459-468
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• 2013

A novel integrated laser, that is, a distributed reflector laser diode integrated with an electroabsorption modulator, is proposed to improve the output efficiency, single-mode stability, and chirp. The proposed laser can be realized using the selective metalorganic vapor phase epitaxy technique (that is, control of the width of the insulating mask), and its fabrication process is almost the same as the conventional electroabsorption modulated laser (EML) process except for the asymmetric coupling coefficient structure along the cavity. For our analysis, an accurate time-domain transfer-matrix-based laser model is developed. Based on this model, we perform steady-state and large-signal analyses. The performances of the proposed laser, such as the output power, extinction ratio, and chirp, are compared with those of the EML. Under 10-Gbps NRZ modulation, we can obtain a 30% higher output power and about 50% lower chirp than the conventional EML. In particular, the simulation results show that the chirp provided by the proposed laser can appear to have a longer wavelength side at the leading edge of the pulse and a shorter wavelength side at the falling edge.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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• pp.231-242
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• 2003

Multidisciplinary Design Optimization (MDO) is an optimization technique considering simultaneously multiple disciplines such as dynamics, mechanics, structural analysis, thermal and fluid analysis and electromagnetic analysis. A software system enabling multidisciplinary design optimization is called MDO framework. An MDO framework provides an integrated and automated design environment that increases product quality and reliability, and decreases design cycle time and cost. The MDO framework also works as a common collaborative workspace for design experts on multiple disciplines. In this paper, we present the architecture for an MDO framework along with the requirement analysis for the framework. The requirement analysis has been performed through interviews of design experts in industry and thus we claim that it reflects the real needs in industry. The requirements include integrated design environment, friendly user interface, highly extensible open architecture, distributed design environment, application program interface, and efficient data management to handle massive design data. The resultant MDO framework is datasever-oriented and designed around a centralized data server for extensible and effective data exchange in a distributed design environment among multiple design tools and software.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.241-246
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• 2020

Hadoop is a framework to process large data sets in a distributed way across clusters of nodes. It has been a popular platform to process big data, but in recent years, other platforms became competitive ones depending on the characteristics of the application. Spark is one of distributed platforms to enable real-time data processing and improve overall processing performance over Hadoop by introducing in-memory processing instead of disk I/O. Whereas Hadoop is designed to work on Java and data analysis is processed using Java API, Spark provides a variety of APIs with Scala, Python, Java and R. In this paper, the goal is to find out whether the APIs of different programming languages af ect the performances in Spark. We chose two popular APIs: Python and Scala. Python is easy to learn and is used in AI domain in a wide range. Scala is a programming language with advantages of parallelism. Our experiment shows much faster processing with Scala API than Python API. For the performance issues on AI-based analysis, further study is needed.

• Journal of electromagnetic engineering and science
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• v.16 no.1
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• pp.44-51
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• 2016

A commercial $0.25{\mu}m$ GaN process is used to implement 6-18 GHz wideband power amplifier (PA) monolithic microwave integrated circuits (MMICs). GaN HEMTs are advantageous for enhancing RF power due to high breakdown voltages. However, the large-signal models provided by the foundry service cannot guarantee model accuracy up to frequencies close to their maximum oscillation frequency ($F_{max}$). Generally, the optimum output load point of a PA varies severely according to frequency, which creates difficulties in generating watt-level output power through the octave bandwidth. This study overcomes these issues by the development of in-house large-signal models that include a thermal model and by applying distributed L-C output load matching to reactive matched amplifiers. The proposed GaN PAs have successfully accomplished output power over 5 W through the octave bandwidth.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.36-54
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• 2014

Resource sharing is a major advantage of distributed computing. However, a distributed computing system may have some physical or virtual resource that may be accessible by a single process at a time. The mutual exclusion issue is to ensure that no more than one process at a time is allowed to access some shared resource. The article proposes a token-based mutual exclusion algorithm for the clustered mobile ad hoc networks (MANETs). The mechanism that is adapted to handle token passing at the inter-cluster level is different from that at the intra-cluster level. It makes our algorithm message efficient and thus suitable for MANETs. In the interest of efficiency, we implemented a centralized token passing scheme at the intra-cluster level. The centralized schemes are inherently failure prone. Thus, we have presented an intra-cluster token passing scheme that is able to tolerate a failure. In order to enhance reliability, we applied a distributed token circulation scheme at the inter-cluster level. More importantly, the message complexity of the proposed algorithm is independent of N, which is the total number of nodes in the system. Also, under a heavy load, it turns out to be inversely proportional to n, which is the (average) number of nodes per each cluster. We substantiated our claim with the correctness proof, complexity analysis, and simulation results. In the end, we present a simple approach to make our protocol fault tolerant.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.89-96
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• 2009

In the future energy environment, a power information system will meet the real-time capability to process the emergency events, unexpected blackouts or over-load, and the high performance to provide the consumer service events such as remote meter reading. In addition to, it must have facility which is able to process a large information occurred on system effectively. In this paper, we developed a distributed power information system based on event with metadata processing technique which was both load balancing and decreased hot spot using XML that was efficient for information exchange. In order to experiment, we made a reduced future power system with controling power device using wireless communications and we could do experiments through it.

• Journal of KIISE
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• v.43 no.4
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• pp.450-459
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• 2016

Every year, RDFS data tends further toward scalability; hence, the manner of SPARQL processing needs to be changed for fast query. The query processing method of SPARQL has been studied using a scalable distributed processing framework. Current studies indicate that the query engine based on the scalable distributed processing framework i.e., Hadoop(MapReduce) is not suitable for real-time processing because of the repetitive tasks; in addition, it is difficult to construct a query engine based on an In-memory Distributed Query engine, because distributed structure on the low-level is required to be considered. In this paper, we proposed a method to construct a query engine for improving the speed of the query process with the mass triple data. The query engine processes the query of SPARQL using the SparkSQL, which is an In-memory based, distributed query processing framework. SparkSQL is a high-level distributed query engine that facilitates existing SQL statement. In order to process the SPARQL query, after generating the Algebra Tree using Jena, the Algebra Tree is required to be translated to Spark Algebra Tree for application in the Spark system, and construction of the system that generated the SparkSQL query. Furthermore, we proposed the design of triple property table based on DataFrame for more efficient query processing in the Spark system. Finally, we verified the validity through comparative evaluation with the query engine, which is the existing distributed processing framework.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.187-192
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• 2004

In this paper, we proposed the method to design fuzzy controller using the experience of the operating expert and experimental numeric data for the robust control about the noise and disturbance instead of the traditional PID controller for the main steam temperature control of the thermal power plant. The temperature of main steam temperature process has to be controlled uniformly for the stable electric power output. The process has the problem of the hunting for the cases of various disturbances. In that case, the manual action of the operator happened to be introduced in some cases. We adopted the TSK (Takagi-Sugeno-Kang) model as the fuzzy controller and designed the fuzzy rules using the informations extracted directly from the real plant and various operating condition to solve the above problems and to apply practically. We implemented the real fuzzy controller as the Function Block module in the DCS(Distributed Control System) and evaluated the feasibility through the experimental results of the simulation.