• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.6
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• pp.8-17
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• 2010

This paper proposes a novel LCD CCFL-backlight electronic ballast using the phase-shift full-bridge inverter. The proposed electronic ballast reduces the ignition voltage and eliminates current spikes using the new digital dimming control applied with soft-starting. Thus the electronic ballast improves ignition behavior of the CCFL and hence increases the CCFL's life span. For this, this paper analyzes the full-bridge inverter topology of the proposed electronic ballast and explains the new digital dimming control algorithm applied to the ballast, briefly. And this paper shows a design example of the prototype circuit and explains an implementation method of the digital dimming control which is implemented on a single-chip microcontroller with software. This was implemented as actual prototype electronic ballast, and its experimental results showed that the proposed electronic ballast operates correctly. The ignition voltage of the prototype in the digital dimming operation was reduced about 30[%] compared with the conventional electronic ballast and there were not any current spikes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2A
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• pp.144-153
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• 2006

In this paper, we propose an efficient video data transmission protocol using the cross-layer approach in ad hoc networks. Due to node movement, the MANET is frequently changing path and each path has different transmission rate so that it has low performance when transmitters select a constant transmission late at the encoding time. Because MANET is running limited energy, efficient energy management is important because it increases network life time and network throughput. Therefore we need an effective video transmission method that considers physical layer channelstatistics, node's energy status, and network topology changes at the same time unlike the OSI recommendation protocol in that each layer isindependent and hard to transmit adaptively video data according to the network conditions. Therefore, in this paper we propose a cross-layer effective video transmission protocol and mechanism that can select an optimal path using multilayer information such as node's residual energy, channel condition and hop counts and can determine the adequate coding rate adaptively.

• The Journal of Korean Medicine
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• v.31 no.5
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• pp.103-111
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• 2010

Objectives: Because of the characteristics of traditional Korean medicine, there are few overseas patents and SCI papers. Researchers are struggling to analyze the research trend using existing patent analysis system and paper analysis system. We aim to build up a web-based paper map analysis system for Traditional Korean Medicine to improve the situation. Methods: We studied the following three sub topics. First, we surveyed the research trend analysis method for traditional Korean medicine. Second, we designed a paper map analysis model and made the algorithm for it. Finally, the development of the paper map analysis system was conducted. Results: We developed a web-based paper map analysis system which has the three main functions being analysis chart, topology map and contour map. For the rich internet application, we used the flex development tool and java integrated development environment. Conclusion: We will provide our paper map analysis system in the OASIS through the minor changes to provide easy use. We hope that this system will be a useful tool to analyze the research trends for traditional Korean medicine.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.665-675
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• 2002

It is very closely related with the reliability of the pipe network to predict pipe burst and diminish burst effect in water distribution system. Most of the engineers have not consider pipe layout and the effect of pipe burst in conservative pipe network design. In this study, The effect of pipe burst in the network is analyzed with respect to pipe network geometric topology and the method of increasing the system reliability is presented by reducing pipe-burst effect. In existing pipe system, it is only designed to the closed loop system but in case of each pipe burst, it cannot transmit appropriate water to consumers and occurs severe hydraulic head drop in many nodes. The techniques developed in this study allow proper pipe diameter and pipe layout to pipe system through the analysis of pipe-burst effect. Thus, when each pipe is bursted, pipe system is prevented from severe pressure head drop in demand nodes and can supply stable flowrate to consumer.

• Journal of Platform Technology
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• v.11 no.3
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• pp.76-82
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• 2023

Starting from the 4th industrial revolution, core technologies were applied to industries to build various smart environments. Smart factories in the manufacturing industry produce high-quality products by applying IIoT as a core technology that can collect and control a wide range of data for customized production. However, the network environment of the smart factory converted to open through IIoT was exposed to various security risks. In accordance with security breaches, IIoT has shown degradation in the quality of manufactured products and production processes due to network disturbance, use and maintenance of forged IIoT, and can cause reliability problems in business. Accordingly, in this study, a method for safe connection and utilization of IIoT was studied during the initial establishment of a smart factory. Specifically, a study was conducted to check the IIoT connection situation so that the practicality of the IIoT connected to the smart factory could be confirmed and the harmless environment established.

• International Journal of High-Rise Buildings
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• v.9 no.2
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• pp.127-154
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• 2020

Disproportionate collapse triggered by local structural failure may cause huge casualties and economic losses, being one of the most critical civil engineering incidents. It is generally recognized that ensuring robustness of a structure, defined as its insensitivity to local failure, is the most acceptable and effective method to arrest disproportionate collapse. To date, the concept of robustness in its definition and quantification is still an issue of controversy. This paper presents a detailed review on about 50 quantitative measures of robustness for building structures, being classified into structural attribute-based and structural performance-based measures (deterministic and probabilistic). The definition of robustness is first described and distinguished from that of collapse resistance, vulnerability and redundancy. The review shows that deterministic measures predominate in quantifying structural robustness by comparing the structural responses of an intact and damaged structure. The attribute-based measures based on structural topology and stiffness are only applicable to elastic state of simple structural forms while the probabilistic measures receive growing interest by accounting for uncertainties in abnormal events, local failure, structural system and failure-induced consequences, which can be used for decision-making tools. There is still a lack of generalized quantifications of robustness, which should be derived based on the definition and design objectives and on the response of a structure to local damage as well as the associated consequences of collapse. Critical issues and recommendations for future design and research on quantification of robustness are provided from the views of column removal scenarios, types of structures, regularity of structural layouts, collapse modes, numerical methods, multiple hazards, degrees of robustness, partial damage of components, acceptable design criteria.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.294-302
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• 2020

In a genetic algorithm, computer simulations are performed based on the natural evolution process of life, such as selection, crossover, and mutation. The genetic algorithm searches the approximate optimal solution by the parallel arrangement of Schema, which has a short definition length, low order, and high adaptability. This study examined the possibility of improving the efficiency of the optimal solution by considering the characteristics of the building block hypothesis, which are one of the key operating principles of a genetic algorithm. This study evaluated the efficiency of the optimization results according to the gene sequence for the implementation in solving problems. The optimal design problem of the water pipe was selected, and the genetic arrangement order reflected the engineering specificity by dividing into the existing, the network topology-based, and the flowrate-based arrangement. The optimization results with a flowrate-based arrangement were, on average, approximately 2-3% better than the other batches. This means that to increase the efficiency of the actual engineering optimization problem, a methodology that utilizes clear prior knowledge (such as hydraulic properties) to prevent such excellent solution characteristics from disappearing is essential. The proposed method will be considered as a tool to improve the efficiency of large-scale water supply network optimization in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.687-697
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• 2014

This study ranges from planning phase to the detailed design phase of steel box girder bridge and proposes ways to generate semantic information of components through Industry Foundation Classes (IFC), a data model for Building Information Modeling (BIM). The classification of components of steel box girder bridge was performed to define information items required for identifying semantic information based on IFC, and spatial information items based on topology and physical information items based on functions of components were classified to create additional properties that does not support IFC by applying user-defined property set within the IFC framework. Steel box girder bridge information model based on IFC was implemented through BIM software and semantic information input interface, which was developed in this study to examine the effectiveness of the additionally created user-defined property. Furthermore, the quantity take-off of components was performed through information model of steel box girder bridge, and the applicability of the proposed method was tested by comparing the quantity take-off based on design document with the result.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.