• Korean Chemical Engineering Research
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• v.51 no.2
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• pp.221-225
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• 2013

Sustainability, in general, means the protection of environmental resources and economic prosperity, with the consideration of the social, economic and environmental effect, as well as human health and the enhancement of life. Profound consideration about sustainability has to handle the overall cycle of feedstock, resource extraction, transportation and production in addition to the environmental effect. Sustainable development of the chemical industries should be carried out complementarily by strengthening the chemical process safety of the industries. In this respect, chemical process safety can be called an opportunity to enhance the compatibility internationally. Changing new paradigm in chemical process safety is formed from the overall life cycle considering basic design of existing systems and production processes. To improve the chemical process safety, the integrated smart system is necessary, comprising various chemical safety database and knowledge base and improved methods of quantitative risk analysis, including management system. This paper discussed the necessity of overall life cycle in chemical process safety and proposed new technology to improve the sustainability. To develop the sustainable industries in process systems engineering, three S, which include Safety, Stability and Security, will have to be combined appropriate.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.169-199
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• 2015

Information and communication technologies (ICT) have been combined with products from other industries to provide new functionality, as recently shown in the cases of Internet of Things (IoT). Modularity assumes a crucial role in such technological convergence, and has impacts on the relationship between organizations as well as competition within an industry. Interface standards, which ensure the connectivity between modules, serve as a critical factor in the process by which modularity affects organization systems and industry structure. To understand the aforementioned phenomenon, we studied modularity and interface standards with a focus on the interaction between technology and organization systems and subsequent changes in industrial dynamics. This paper examines previous literature on modularity and interface standards in the aspects of product architecture, organization systems, and institutional factors. With this analytical framework, we conducted a comparative analysis of electronic and automotive industries to derive implications for standardization policy. This research has shown the significance of external open interface standards in shaping an industrial landscape where a variety of module producers horizontally compete. It also advises that policymakers take into account product characteristics, engagement of leading firms in an industry, and institutional factors such as WTO law in the design of standardization policy.

• Smart Structures and Systems
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• v.25 no.4
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• pp.487-499
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• 2020

This paper proposes a novel approach to model updating for a large-scale cable-stayed bridge based on ambient vibration tests coupled with a hybrid metaheuristic search algorithm. Vibration measurements are carried out under excitation sources of passing vehicles and wind. Based on the measured structural dynamic characteristics, a finite element (FE) model is updated. For long-span bridges, ambient vibration test (AVT) is the most effective vibration testing technique because ambient excitation is freely available, whereas a forced vibration test (FVT) requires considerable efforts to install actuators such as shakers to produce measurable responses. Particle swarm optimization (PSO) is a famous metaheuristic algorithm applied successfully in numerous fields over the last decades. However, PSO has big drawbacks that may decrease its efficiency in tackling the optimization problems. A possible drawback of PSO is premature convergence leading to low convergence level, particularly in complicated multi-peak search issues. On the other hand, PSO not only depends crucially on the quality of initial populations, but also it is impossible to improve the quality of new generations. If the positions of initial particles are far from the global best, it may be difficult to seek the best solution. To overcome the drawbacks of PSO, we propose a hybrid algorithm combining GA with an improved PSO (HGAIPSO). Two striking characteristics of HGAIPSO are briefly described as follows: (1) because of possessing crossover and mutation operators, GA is applied to generate the initial elite populations and (2) those populations are then employed to seek the best solution based on the global search capacity of IPSO that can tackle the problem of premature convergence of PSO. The results show that HGAIPSO not only identifies uncertain parameters of the considered bridge accurately, but also outperforms than PSO, improved PSO (IPSO), and a combination of GA and PSO (HGAPSO) in terms of convergence level and accuracy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.96-100
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• 2012

In high static field magnetic resonance imaging(MRI) systems, $B_0$ fields of 7 T and 9.4 T, the impressed RF field shows larger inhomogeneity than in clinical MRI systems with B0 fields of 1.5 T and 3.0 T. In multi-channel RF coils, the magnitude and phase of the input to each coil element can be controlled independently to reduce the non-uniformity of the impressed RF $B_1^+$ field. The convex optimization technique has been used to obtain the optimum excitation parameters with iterative solutions for homogeneity in a selected ROI(Region of Interest). To demonstrate the technique, the multichannel transmission line coil was modeled together with a human head phantom at 400 MHz for the 9.4 T MRI system and $B_1^+$ fields are obtained. In this paper, all the optimized $B_1^+$ in each isolated ROIs are combined to achieve significantly improved homogeneity over the entire field of view. The simulation results for 9.4 T MRI systems are discussed in detail.

• Journal of Energy Engineering
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• v.25 no.3
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• pp.1-8
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• 2016

North Korea is currently undergoing an economic crisis of industrial productivity reduction, which resulted from decreased energy production and economic sanctions due to conflicts with the international society. This paper examined the technological status of North Korea's natural gas and coal industries which are essential sectors for recovery of the economy and North-South cooperation on energy industry. This paper also analyzed investment strategies in North Korean energy industries and calculated the size of economic ripple effect of the investment on North and South Korea. In order to analyze the effect of the investment on North Korean economy, we constructed an inter-industry relation table of North Korea for year 2014 and used an input-output model. The ripple effect of the investment in natural gas and coal industries turned out to be 1.012 billion dollars and 2.742 billion dollars respectively. In order to analyze the ripple effect of the investment on South Korean economy, we constructed an inter-industry relation table of South Korea for year 2013 and used a demand-driven model for inter-industry analysis. As a result, production, added-value and employment inducement coefficients of the investment were calculated as 2.02073, 0.62697 and 8.99409 for the natural gas industry and 2.02130, 0.62701 and 9.00413 for the coal industry respectively.

• Journal of Plant Biotechnology
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• v.37 no.1
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• pp.12-24
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• 2010

Plant metabolomics is a research field for identifying all of the metabolites found in a certain plant cell, tissue, organ, or whole plant in a given time and conditions and for studying changes in metabolic profiling as time goes or conditions change. Metabolomics is one of the most recently developed omics for holistic approach to biology and is a kind of systems biology. Metabolomics or metabolite fingerprinting techniques usually involves collecting spectra of crude solvent extracts without purification and separation of pure compounds or not in standardized conditions. Therefore, that requires a high degree of reproducibility, which can be achieved by using a standardized method for sample preparation and data acquisition and analysis. In plant biology, metabolomics is applied for various research fields including rapid discrimination between plant species, cultivar and GM plants, metabolic evaluation of commercial food stocks and medicinal herbs, understanding various physiological, stress responses, and determination of gene functions. Recently, plant metabolomics is applied for characterization of gene function often in combination with transcriptomics by analyzing tagged mutants of the model plants of Arabidopsis and rice. The use of plant metabolomics combined by transcriptomics in functional genomics will be the challenge for the coming year. This review paper attempted to introduce current status and prospects of plant metabolomics research.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.347-357
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• 2019

The usefulness of processing and analysis systems of GIS-based agricultural climate data is affected by the reliability and availability of computing infrastructures such as cloud, on-premises, and hybrid. Cloud technology has grown in popularity. However, various reference cases accumulated over the years of operational experiences point out important features that make on-premises technology compatible with cloud technology. Both cloud and on-premises technologies have their advantages and disadvantages in terms of operational time and cost, reliability, and security depending on cases of applications. In this study, we have described characteristics of four general computing platforms including cloud, on-premises with hardware-level virtualization, on-premises with operating system-level virtualization and hybrid environments, and compared them in terms of advantages and disadvantages when a huge amount of GIS-based agricultural climate data were stored and processed to provide public services of agro-meteorological and climate information at high spatial and temporal resolutions. It was found that migrating high-resolution agricultural climate data to public cloud would not be reasonable due to high cost for storing a large amount data that may be of no use in the future. Therefore, we recommended hybrid systems that the on-premises and the cloud environments are combined for data storage and backup systems that incur a major cost, and data analysis, processing and presentation that need operational flexibility, respectively.

• Journal of Surface Science and Engineering
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• v.12 no.3
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• pp.207-216
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• 1979

Environmental pollution or contaminations caused by various kinds of pollutants have become one of most serious problems of our time. Environ mental pollution is the unfavoralble alteration of our surroundings, through direct or indirect effects of changes in energy patterns, rediation levels, chemical and physical constitution and abundances of organisms. These changes may affect humans directly or through their supplies of water and of agicultural and other biological products, their physical objects or possessions, or their opportunities for recreation and appreciation of nature. Pollutants that meet the criteria of this definition of environmental pollution are numerous: gases (such as sulfur dioxide and nitrogen oxides) and paniculate matter (such as smoke particles, lead aerosols, and asbestos) in the atmosphere; pesticides and radioactive isotopes in the atmosphee and in waterways; sewage, organic. chemicals, and phosphates in water; solid wastes on land; excessive heating (thermal pollution) of rivers and lakes; and many others. Some of these pollutants are introduced into the environment naturally, others by human actions, and most in both ways. Our major concer is with environmental pollution resulting wholly or largely as a by-product of human activities, because these can be controlled most readily. Environmental pollution cannot be solved by science and technology alone. It should be handled by an interdisciplinary approach with combined methods of science and technology as wen as social science disciplines for the better solution of this critical problem. In this respect, introducing "Environmental Science," a new scientific approach for the solution of environmental problems, which is now widely accepted by most developed countries of the world will be very helpful for systematization of theoretical basis for a new scientific approach to environmental pollution. Environmental science is "the study of all systems of air, land, water, energy, and life that surround Man. It includes all sciences directed to the system-level of understanding of the environment, drawing especially upon such disciplines as meteorology, geophysics, oceanography, and ecology, and utilizing to the fullest knowledge and techniques developed in such fields as physics, chemistry, biology, mathematics and engineering as well as many social science disciplines, such as economics, such as economics, law, political science and public administration." The components of this discipline are not new, for they are drawn from existing areas of science within biology chemistry, physics, and geoscience. What is really new about environmental science, however, is it siewpoint - its orientation to global problems, its conception of the earth as a set of interlocking, interacting systems, and its interest in Man as a part of these systems.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• The Journal of the Acoustical Society of Korea
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• v.38 no.6
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• pp.703-709
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• 2019

This paper proposes speech recognition systems employing Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) structures combined with Hidden Markov Moldel (HMM) to effectively recognize the speech of VeloPharyngeal Insufficiency (VPI) patients, and compares the recognition performance of the systems to the Gaussian Mixture Model (GMM-HMM) and fully-connected Deep Neural Network (DNNHMM) based speech recognition systems. In this paper, the initial model is trained using normal speakers' speech and simulated VPI speech is used for generating a prior model for speaker adaptation. For VPI speaker adaptation, selected layers are trained in the CNN-HMM based model, and dropout regulatory technique is applied in the LSTM-HMM based model, showing 3.68 % improvement in recognition accuracy. The experimental results demonstrate that the proposed LSTM-HMM-based speech recognition system is effective for VPI speech with small-sized speech data, compared to conventional GMM-HMM and fully-connected DNN-HMM system.