• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.186-194
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• 2019

Deterministic optimization, commonly used to find the geophysical inverse solutions, have its limitation that it cannot find the proper solution since it might converge into the local minimum. One of the solutions to this problem is to use global optimization based on a stochastic approach, among which a large number of particle swarm optimization (PSO) applications have been introduced. In this paper, I developed a geophysical inversion algorithm applying PSO method for the layered-earth resistivity inversion of the small-loop electromagnetic (EM) survey data and carried out numerical inversion experiments on synthetic datasets. From the results, it is confirmed that the PSO inversion algorithm could increase the inversion success rate even when attempting the inversion of small-loop EM survey data from which it might be difficult to find a best solution by applying the Gauss-Newton inversion algorithm.

• KIEE International Transactions on Power Engineering
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• v.5A no.3
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• pp.269-279
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• 2005

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to find the optimal switch position because of its numerous local minima. In this investigation, a parallel AEA was developed for the reconfiguration of the distribution system. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of GA and the local search capability of ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC-cluster system consisting of 8 PCs·was developed. Each PC employs the 2 GHz Pentium IV CPU, and is connected with others through switch based fast Ethernet. The new developed algorithm has been tested and is compared to distribution systems in the reference paper to verify the usefulness of the proposed method. From the simulation results, it is found that the proposed algorithm is efficient and robust for distribution system reconfiguration in terms of the solution quality, speedup, efficiency, and computation time.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.401-406
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• 2011

In order to solve a complex optimization problem more efficiently than traditional approaches, various meta-heuristic algorithms such as genetic algorithm, ant-colony algorithm, and harmony search algorithm have been extensively researched. Compared with other meta-heuristic algorithm, harmony search algorithm shows a better result to resolve the complex optimization issues. Harmony search algorithm is inspired by the improvision process of musician for most suitable harmony. In general, the performance of harmony search algorithm is determined by the value of harmony memory considering rate, and pitch adjust rate. In this paper, modified harmony search algorithm is proposed in order to derive best harmony. If the optimal solution of a specific problem can not be found for a certain period of time, a part of original harmony memory is updated as the selected suitable harmonies. Experimental results using test function demonstrate that the updated harmony memory can induce the approximation of reliable optimal solution in the short iteration, because of a few change of fitness.

• Korean Medical Education Review
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• v.18 no.2
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• pp.51-57
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• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.43-55
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• 2015

In the case of satellite navigation positioning, the shielding of satellite signals is determined by the environment of the region at which a user is located, and the navigation performance is determined accordingly. The accuracy of user position determination varies depending on the dilution of precision (DOP) which is a measuring index for the geometric characteristics of visible satellites; and if the minimum visible satellites are not secured, position determination is impossible. Currently, the GLObal NAvigation Satellite system (GLONASS) of Russia is used to supplement the navigation performance of the Global Positioning System (GPS) in regions where GPS cannot be used. In addition, the European Satellite Navigation System (Galileo) of the European Union, the Chinese Satellite Navigation System (BeiDou) of China, the Quasi-Zenith Satellite System (QZSS) of Japan, and the Indian Regional Navigation Satellite System (IRNSS) of India are aimed to achieve the full operational capability (FOC) operation of the navigation system. Thus, the number of satellites available for navigation would rapidly increase, particularly in the Asian region; and when integrated navigation is performed, the improvement of navigation performance is expected to be much larger than that in other regions. To secure a stable and prompt position solution, GPS-GLONASS integrated navigation is generally performed at present. However, as available satellite navigation systems have been diversified, finding the minimum satellite constellation combination to obtain the best navigation performance has recently become an issue. For this purpose, it is necessary to examine and predict the navigation performance that could be obtained by the addition of the third satellite navigation system in addition to GPS-GLONASS. In this study, the current status of the integrated navigation performance for various satellite constellation combinations was analyzed based on 2014, and the navigation performance in 2020 was predicted based on the FOC plan of the satellite navigation system for each country. For this prediction, the orbital elements and nominal almanac data of satellite navigation systems that can be observed in the Korean Peninsula were organized, and the minimum elevation angle expecting signal shielding was established based on Matlab and the performance was predicted in terms of DOP. In the case of integrated navigation, a time offset determination algorithm needs to be considered in order to estimate the clock error between navigation systems, and it was analyzed using two kinds of methods: a satellite navigation message based estimation method and a receiver based method where a user directly performs estimation. This simulation is expected to be used as an index for the establishment of the minimum satellite constellation for obtaining the best navigation performance.

• Journal of Plant Biotechnology
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• v.45 no.3
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• pp.190-195
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• 2018

Sweetpotato [Ipomoea batatas (L.) Lam] represents an attractive starch crop that can be used to facilitate solving global food and environmental problems in the $21^{st}$ century. It can be used as industrial bioreactors to produce various high value-added materials, including bio-ethanol, functional feed, antioxidants, as well as food resources. The non-profit Center for Science in the Public Interest (CSPI) announced sweetpotato as one of the ten 'super foods' for better health, since it contains high levels of low molecular weight antioxidants such as vitamin-C, vitamin-E and carotenoids, as well as dietary fiber and potassium. The United States Department of Agriculture (USDA) also reported that sweetpotato is the best bioenergy crop among starch crops on marginal lands, that does not affect food security. The Food and Agriculture Organization (FAO) estimated that world population in 2050 will be 9.7 billion, and require approximately 1.7 times more food than today. In this respect, sweetpotato will be a solution to solving problems such as food, energy, health, and environment facing the globe in the $21^{st}$ century. In this paper, the current status of resources, and cultivation of sweetpotato in the world was first described. Development of a new northern route of the sweetpotato and its prior tasks of large scale cultivation of sweetpotato, were also described in terms of global food security, and production of high-value added biomaterials.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.395-401
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• 2018

Recently, most of mobile devices are equipped with GNSS (Global Navigation Satellite System). When the GNSS signal is available, it is easy to obtain position information. However, GNSS is not suitable solution for indoor localization, since the signals are normally not reachable inside buildings. A wide varieties of technology have been developed as a solution for indoor localization such as Wi-Fi, beacons, and inertial sensor. With the increased sensor combinations in mobile devices, mobile devices also became feasible to provide a solution, which based on PDR (Pedestrian Dead Reckoning) method. In this study, we utilized the combination of three sensors equipped in mobile devices including accelerometer, digital compass, and gyroscope and applied three representative PDR methods. The proposed methods are done in three stages; step detection, step length estimation, and heading determination and the final indoor localization result was evaluated with terrestrial LiDAR (Light Detection And Ranging) data obtained in the same test site. By using terrestrial LiDAR data as reference ground truth for PDR in two differently designed experiments, the inaccuracy of PDR methods that could not be found by existing evaluation method could be revealed. The firstexperiment included extreme direction change and combined with similar pace size. Second experiment included smooth direction change and irregular step length. In using existing evaluation method which only checks traveled distance, The results of two experiments showed the mean percentage error of traveled distance estimation resulted from three different algorithms ranging from 0.028 % to 2.825% in the first experiment and 0.035% to 2.282% in second experiment, which makes it to be seen accurately estimated. However, by using the evaluation method utilizing terrestrial LiDAR data, the performance of PDR methods emerged to be inaccurate. In the firstexperiment, the RMSEs (Root Mean Square Errors) of x direction and y direction were 0.48 m and 0.41 m with combination of the best available algorithm. However, the RMSEs of x direction and y direction were 1.29 m and 3.13 m in the second experiment. The new evaluation result reveals that the PDR methods were not effective enough to find out exact pedestrian position information opposed to the result from existing evaluation method.

• Nuclear Engineering and Technology
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• v.39 no.1
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• pp.31-42
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• 2007

Energy supply is increasingly showing up as a major issue for electricity supply, transportation, settlement, and process heat industrial supply including hydrogen production. Nuclear power is part of the solution. For electricity supply, as exemplified in Finland and France, the EPR brings an immediate answer; HTR could bring another solution in some specific cases. For other supply, mostly heat, the HTR brings a solution inaccessible to conventional nuclear power plants for very high or even high temperature. As fossil fuels costs increase and efforts to avoid generation of Greenhouse gases are implemented, a market for nuclear generated process heat will be developed. Following active developments in the 80's, HTR have been put on the back burner up to 5 years ago. Light water reactors are widely dominating the nuclear production field today. However, interest in the HTR technology was renewed in the past few years. Several commercial projects are actively promoted, most of them aiming at electricity production. ANTARES is today AREVA's response to the cogeneration market. It distinguishes itself from other concepts with its indirect cycle design powering a combined cycle power plant. Several reasons support this design choice, one of the most important of which is the design flexibility to adapt readily to combined heat and power applications. From the start, AREVA made the choice of such flexibility with the belief that the HTR market is not so much in competition with LWR in the sole electricity market but in the specific added value market of cogeneration and process heat. In view of the volatility of the costs of fossil fuels, AREVA's choice brings to the large industrial heat applications the fuel cost predictability of nuclear fuel with the efficiency of a high temperature heat source tree of Greenhouse gases emissions. The ANTARES module produces 600 MWth which can be split into the required process heat, the remaining power drives an adapted prorated electric plant. Depending on the process heat temperature and power needs, up to 80% of the nuclear heat is converted into useful power. An important feature of the design is the standardization of the heat source, as independent as possible of the process heat application. This should expedite licensing. The essential conditions for success include: ${\bullet}$ Timely adapted licensing process and regulations, codes and standards for such application and design ${\bullet}$ An industry oriented R&D program to meet the technological challenges making the best use of the international collaboration. Gen IV could be the vector ${\bullet}$ Identification of an end user(or a consortium of) willing to fund a FOAK

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.21-32
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• 2019

Inspired by the social behavior models of a bird flock or fish school, particle swarm optimization (PSO) is a popular metaheuristic optimization algorithm and has been widely used from solving a complex optimization problem to learning a artificial neural network. However, PSO is difficult to apply to many real-life optimization problems involving stochastic noise, since it is originated in a deterministic environment. To resolve this problem, this paper incorporates a resampling method called the uncertainty evaluation (UE) method into PSO. The UE method allows the particles to converge on the accurate optimal solution quickly in a noisy environment by selecting the particles' global best position correctly, one of the significant factors in the performance of PSO. The results of comparative experiments on several benchmark problems demonstrated the improved performance of the propose algorithm compared to the existing studies. In addition, the results of the case study emphasize the necessity of this work. The proposed algorithm is expected to be effectively applied to optimize complex systems through digital twins in the fourth industrial revolution.

• Journal of Environmental Science International
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• v.21 no.1
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• pp.113-123
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• 2012

A unit emission reduction of nitrous oxide ($N_2O$) from anthropogenic sources is equivalent to a 310-unit $CO_2$ emission reduction because the $N_2O$ has the global warming potential (GWP) of 310. This greatly promoted very active development and commercialization of catalysts to control $N_2O$ emissions from large-scale stationary sources, representatively nitric acid production plants, and numerous catalytic systems have been proposed for the $N_2O$ reduction to date and here designated to Options A to C with respect to in-duct-application scenarios. Whether or not these Options are suitable for $N_2O$ emissions control in nitric acid industries is primarily determined by positions of them being operated in nitric acid plants, which is mainly due to the difference in gas temperatures, compositions and pressures. The Option A being installed in the $NH_3$ oxidation reactor requires catalysts that have very strong thermal stability and high selectivity, while the Option B technologies are operated between the $NO_2$ absorption column and the gas expander and catalysts with medium thermal stability, good water tolerance and strong hydrothermal stability are applicable for this option. Catalysts for the Option C, that is positioned after the gas expander thereby having the lowest gas temperatures and pressure, should possess high de$N_2O$ performance and excellent water tolerance under such conditions. Consequently, each de$N_2O$ technology has different opportunities in nitric acid production plants and the best solution needs to be chosen considering the process requirements.