• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.175-178
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• 1996

Power system is becomming more and more complex and large. So system is stressed increasingly. This paper presents a method to select contingency ranking in power systems for EMS operation. Firstly, the proposed method is applied line outage using Thevenin equivalent circuit. Secondly, Contingency harmful to system is selected by loss variation between base case and fault. Thirdly, this paper prescribed simulated line sequence. Therefore this algorithm shows higher computation speed and effective memory use.

• Journal of Mechanical Science and Technology
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• v.20 no.2
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• pp.205-211
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• 2006

Among other critical conditions in rotor systems the large non-linear vibration excited by bearing non-linearity causes the rotor failure. For reducing this catastrophic failure and predictive detection of this phenomenon the analysis of orthotropic bearing non-linearity in rotor system using higher order frequency response functions (HFRFs) is conducted and is shown to be theoretically feasible as that of non-rotating structures. The complex HFRFs based on the Volterra series are newly developed for the process and investigated their features by using the simple forms of the FRFs associated with the forward and the backward modes.

• Preventive Nutrition and Food Science
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• v.1 no.1
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• pp.127-133
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• 1996

The development of high resolution capillary columns and a large variety of different detectors led to a strong position of gas chromatography in instrumental analysis. Every effort has been made to solve sophisticated separation problems by column switching. Nowadays, several systems are commercially available for this purpose. The principle and the capabilities of multidimensional gas chromatography(MDGC) are illustrated by different applications in the field of modern flavor and essential oil research.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• Smart Structures and Systems
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• v.1 no.4
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• pp.355-368
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• 2005

Large and complex structures are being built now-a-days and, they are required to be functional even under extreme loading and environmental conditions. In order to meet the safety and maintenance demands, there is a need to build sensors integrated structural system, which can sense and provide necessary information about the structural response to complex loading and environment. Sophisticated tools have been developed for the design and construction of civil engineering structures. However, very little has been accomplished in the area of monitoring and rehabilitation. The employment of appropriate sensor is therefore crucial, and efforts must be directed towards non-destructive testing techniques that remain functional throughout the life of the structure. Fiber optic sensors are emerging as a superior non-destructive tool for evaluating the health of civil engineering structures. Flexibility, small in size and corrosion resistance of optical fibers allow them to be directly embedded in concrete structures. The inherent advantages of fiber optic sensors over conventional sensors include high resolution, ability to work in difficult environment, immunity from electromagnetic interference, large band width of signal, low noise and high sensitivity. This paper brings out the potential and current status of technology of fiber optic sensors for civil engineering applications. The importance of employing fiber optic sensors for health monitoring of civil engineering structures has been highlighted. Details of laboratory studies carried out on fiber optic strain sensors to assess their suitability for civil engineering applications are also covered.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.891-897
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• 2009

This paper presents a novel load management technique that can lower the peak demand caused by package airconditioner loads in large apartment complex. An intelligent hierarchical load management system composed of a Central Intelligent Management System(CIMS) and multiple Local Intelligent Management Systems(LIMS) is proposed to implement the proposed technique. Once the required amount of the power reduction is set, CIMS issues tokens, which can be used by each LIMS as a right to turn on the airconditioner. CIMS creates and maintains a queue for fair and proper allocation of the tokens among the LIMS requesting tokens. By adjusting the number tokens and queue management policies, desired power reduction can be achieved smoothly. The Markov Birth and Death process and the Balance Equations utilizing the Diffusion Model are employed for evaluation of queue performances during transient periods until the static balances among the states are achieved. The proposed technique is tested using a summer load data of a large apartment complex and give promising results demonstrating the usability in load management while minimizing the customer inconveniences.

• Animal cells and systems
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• v.7 no.1
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• pp.1-9
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• 2003

Programmed cell death, or apoptosis, is one of the most studied areas of modern biology. Apoptosis is a genetically regulated process, which plays an essential role in the development and homeostasis of higher organisms. Mitochondria, known to play a central role in regulating cellular metabolism, was found to be critical for regulating apoptosis induced under both physiological and pathological conditions. Mitochondria are a major source of reactive oxygen species (ROS) but they can also serve as its target during the apoptosis process. Release of apoptogenic factors from mitochondria, the best known of which is cytochrome c, leads to assembly of a large apoptosis-inducing complex called the apoptosome. Cysteine pretenses (called caspases) are recruited to this complex and, following their activation by proteolytic cleavage, activate other caspases, which in turn target for specific cleavage a large number of cellular proteins. The redox regulation of apoptosis during and after cytochrome c release is an area of intense investigation. This review summarizes what is known about the biological role of ROS and its targets in apoptosis with an emphasis on its intricate connections to mitochondria and the basic components of cell death.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.193-202
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• 2017

Development of Intelligent Systems involves effective integration of large-scaled knowledge processing and understanding, human-machine interaction, and intelligent services. Especially, in our project for development of a self-growing knowledge-based system with inference methodologies utilizing the big data technology, we are building a platform called WiseKB as the central knowledge base for storing massive amount of knowledge and enabling question-answering by inferences. WiseKB thus requires an effective methodology to analyze diverse requirements convoluted with the integration of various components of knowledge representation, resource management, knowledge storing, complex hybrid inference, and knowledge learning, In this paper, we propose an integrated requirement analysis method that blends the traditional sequential method and the iterative-incremental method to achieve an efficient requirement analysis for large-scale systems.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.2
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• pp.70-78
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• 2012

Due to the variable nature of renewable energy resources and power demand by consumers, it is difficult to operate a power system installed with only one type of renewable energy resource. Grid-based renewable generation may be the only solution to overcome this problem. The conventional approach based on a low-voltage converter with power frequency transformer is commonly employed for grid connection of offshore renewable energy systems. Because of the heavy weight and large size of the transformer, the system can be expensive and complex in terms of installation and maintenance. In this paper, an 11-kV series connected H-bridge (SCHB) multilevel voltage source converter (VSC) is proposed to achieve a compact and light direct grid connection of renewable energy systems. This paper presents the design, simulation and analysis of a five level (5L)-SCHB and an eleven level (11L)-SCHB VSC for 11-kV grid-based renewable energy systems. The performance, cost, modulation scheme and harmonic spectra of the converter are analyzed.

• Industrial Engineering and Management Systems
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• v.13 no.3
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• pp.289-296
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• 2014

With society becoming more advanced and complex, the required management engineering makes essential the development of human resources that can propose solutions for problems of new phenomena from a different perspective. As an example of such phenomena, we note a consumer electronics 'Eco-point' system campaign in this study. To mitigate global warming, revitalize the economy, and encourage the adoption of terrestrial digital compatible TVs, the consumer electronics Eco-point system campaign was implemented in May 2009 in Japan. In this study, we note a model which is constant term with exponential curve with notion of the growth phenomenon (Nakagiri and Kurita, Journal of the Operations Research Society of Japan, 2002). In our study, we call this model the 'differential equation model of the growth phenomenon.' This model represents a phenomenon with a hierarchical structure for capturing the properties of n species. In this study, we propose a new model which can represent not only the impact of largescale campaigns but also seasonal factors. Accordingly, we understand the phenomenon of fluctuation of sales of some products caused by large-scale campaigns and predict the fluctuation of sales. The final goal of this study is to develop human resources that can propose provision and solution for pre-consumption and reactionary decline in demand by understanding the impact of large-scale campaigns. As the first step of this goal, our objective is to propose a new regression method with different conventional perspective that can describe the fluctuation of sales caused by large-scale campaigns and show the possibility of new management engineering education.