• The KSFM Journal of Fluid Machinery
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• v.14 no.1
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• pp.66-76
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• 2011

The heat transfer and pressure loss characteristics of a rotating two-pass channel with a guide vane in the turning region have been studied using three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis, and the shape of the guide vane has been optimized using surrogate modeling optimization technique. For the optimization, thickness, location and angle of the guide vanes have been selected as design variables. The objective function has been defined as a linear combination of the heat transfer and the friction loss related terms with a weighting factor. Latin hypercube sampling has been applied to determine the design points as design of experiments. A weighted-average surrogate model, PBA has been used as the surrogate model. The guide vane in the turning region does not influence the heat transfer in the first passage upstream of the turning region, but enhances largely the heat transfer in the turning region and the second passage. In an example of the optimization, the objective function has been increased by 13.6%.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.813-821
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• 2012

Environmental and public health concern for the emission of air pollutants from burn-up process in waste incineration plants located in the vicinity of living environment was increased during the past decade. The purpose of this study was to suggest of the simple and rapid method of priority setting model for the decision of full-scale public health assessment. This method was consists of total 5-step. Step 1 was "secure the satellite map" and we can use the satellite map which serves from the website such as NAVER Co. Step 2 was "drawing mesh on the map" for catch the point of occupation of environmental sensitivity facilities, and step 3 was "identification and sorting of the facilities", Step 4 was "setting of weight" using the "weighted linear combination (WLC) method". Finally, all facility was sorted by score. As a result, we can set a priority of 145 facilities based on 177 facilities which managed in local government. Facilities in Seoul metropolitan area was high rank in priority list. On the other side, Facilities located at the country or rural area was low rank because of low occupation of the house and the environmental sensitivity facilities such as kindergarten, elementary school, and hospital. In this study, we suggested simple and rapid method that using for screening procedure of public health assessment.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.111.2-111.2
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• 2011

While many astrophysical disks are vertically stratified and obey a polytropic equation of state, most studies on gravitational instability (GI) of flattened systems consider isothermal, razor-thin disks by taking vertical averages of disk properties. We investigate local GI of rotating pressure-confined polytropic disks with resolved vertical stratification by performing linear stability analysis. We find that the GI of vertically-stratified disks is in general a combination of conventional razor-thin Jeans modes and incompressible modes. The incompressible modes that dominate in the limit of the maximal disk compression require surface distortion and are an unstable version of terrestrial water waves. Disks with a steeper equation of state are found to be more Jeans unstable because they tend to have a smaller vertical scale height as well as a steeper temperature gradient corresponding to lower pressure support. GI depends more sensitively on the vertical temperature than density distribution. The density-weighted, harmonic mean, rather than the simple mean, of the adiabatic sound speed well describes the dispersion relation of horizontal modes, and thus is appropriate in the expression for Toomre Q stability parameter of razor-thin disks. We generalize Q into vertically-stratified disks, and discuss astrophysical application of our work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.4
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• pp.756-765
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• 2001

An effective dexterous motion control method of redundant robot manipulators based on neural optimization network is proposed to satisfy multi-criteria such as singularity avoidance, minimizing energy consumption, and avoiding physical limits of actuator, while performing a given task. The method employs a neural optimization network with parallel processing capability, where only a simple geometric analysis for resolved motion of each joint is required instead of computing of the Jacobian and its pseudo inverse matrix. For dexterous motion, a joint geometric manipulability measure(JGMM) is proposed. JGMM evaluates a contribution of each joint differential motion in enlarging the length of the shortest axis among principal axes of the manipulability ellipsoid volume approximately obtained by a geometric analysis. Redundant robot manipulators is then controlled by neural optimization networks in such a way that 1) linear combination of the resolved motion by each joint differential motion should be equal to the desired velocity, 2) physical limits of joints are not violated, and 3) weighted sum of the square of each differential joint motion is minimized where weightings are adjusted by JGMM. To show the validity of the proposed method, several numerical examples are illustrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.268-278
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• 2017

In this paper, we propose two novel detection schemes with low-complexity based on the unified receiver architecture which minimizes a fundamental tradeoff at rate-energy region in SWIPT system. The proposed detection schemes are twofold: The two-stage detection scheme and Euclidean distance combination detection scheme. The two-stage detection scheme detects amplitude information of symbols from rectified signals for energy harvesting. In the sequel, it detects symbols based on phase information of baseband signals for information decoding. The Euclidean distance combination detection scheme detects symbols using linear positive-weighted sum of two metrics: Euclidean distance based on baseband signals for information decoding and Euclidean distance based on rectified signals for energy harvesting. For numerical results, we confirm that the proposed detection scheme can achieve better performance than the conventional scheme in terms of symbol error rate, symbol success rate-energy region and achievable rate-energy region.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.5 no.3
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• pp.76-85
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• 2024

The purpose of this study is to propose a new method of analysis focusing on interconnections between species rather than traditional biodiversity analysis, which represents ecosystems in terms of species and individual counts such as species diversity and species richness. This new approach aims to enhance our understanding of ecosystem networks. Utilizing data from the 4th National Natural Environment Survey (2014-2018), the following eight taxonomic groups were targeted for our study: herbaceous plants, woody plants, butterflies, Passeriformes birds, mammals, reptiles & amphibians, freshwater fishes, and benthonic macroinvertebrates. A co-occurrence frequency analysis was conducted using nationwide data collected over five years. As a result, in all eight taxonomic groups, the degree value represented by a linear regression trend line showed a slope of 0.8 and the weighted degree value showed an exponential nonlinear curve trend line with a coefficient of determination (R²) exceeding 0.95. The average value of the clustering coefficient was also around 0.8, reminiscent of well-known social phenomena. Creating a combination set from the species list grouped by temporal information such as survey date and spatial information such as coordinates or grids is an easy approach to discern species distributed regionally and locally. Particularly, grouping by species or taxonomic groups to produce data such as co-occurrence frequency between survey points could allow us to discover spatial similarities based on species present. This analysis could overcome limitations of species data. Since there are no restrictions on time or space, data collected over a short period in a small area and long-term national-scale data can be analyzed through appropriate grouping. The co-occurrence frequency analysis enables us to measure how many species are associated with a single species and the frequency of associations among each species, which will greatly help us understand ecosystems that seem too complex to comprehend. Such connectivity data and graphs generated by the co-occurrence frequency analysis of species are expected to provide a wealth of information and insights not only to researchers, but also to those who observe, manage, and live within ecosystems.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.952-958
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• 1999

This paper presented the application of GAs as a means of finding optimal solutions over a parameter space in the controller design for a fuzzy control system. The performance can involve a weighted combination of various performance characteristics such as rise-time, settling-time, settling-time, overshoot. The results obtained here are compared with those for a traditional design obtained using the root-locus method. In contrast to traditional methods, the GA-based method does not require the usual mathematical processess or mathematical model of the system. In this paper, the Ga-based Fuzzy control system combining Fuzzy control theory with the GA, that is known to be very effective in the optimization problem, will be proposed The effectiveness of the proposed control system will be demonstrated by computer simulations using task tracking position system in stable and unstable linear systems. It is shown that the GA-based controller is better than the traditional controller used It stable and unstable linear systems.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.66-72
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• 2004

PID control has been well used for several decades. For PID algorithms, some tuning methods are used for selecting PID parameters and with these selected parameters, PID control system is designed. But in some cases various kinds of performance indices are used instead of well-known tuning rules, and so variable type of performance index must be tested so that the designed control system meets the some specifications. For 2 DOF PID controller design this paper presents a linear combinational type of performance indices constituting of index for robust performance, which is obtained by h infinity norm of a weighted complementary sensitivity function, including other time domain indices such as error, energy and changing rate of control input. By numerical methods, the optimal 2 DOF PID parameters are obtained. Therefore various types of 2 degree of freedom PID controllers such as I-PD controller are used so that this two degree of freedom PID controllers may give more desirable output characteristics. Simulations are done with MATLAB m file and mdl files.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.82-92
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• 2007

This paper describes a novel global shape (GS) feature based on radial basis function network (RBFN) and the extraction method of the proposed feature for 3D face recognition. RBFN is the weighted sum of RBfs, it well present the non-linearity of a facial shape using the linear combination of RBFs. It is the proposed facial feature that the weights of RBFN learned by the horizontal profiles of a face. RBFN based feature expresses the locality of the facial shape even if it is GS feature, and it reduces the feature complexity like existing global methods. And it also get the smoothing effect of the facial shape. Through the experiments, we get 94.7% using the proposed feature and hidden markov model (HMM) to match the features for 100 gallery set with those for 300 test set.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.339-346
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• 2003

This paper proposes a multiple classifier system having massive micro classifiers. The micro classifiers are trained by using a local set of training patterns. The k nearest neighboring training patterns of one training pattern comprise the local region for training a micro classifier. Each training pattern is incorporated with one or more micro classifiers. Two types of micro classifiers are adapted in this paper. SVM with linear kernel and SVM with RBF kernel. Classification is done by selecting the best micro classifier among the micro classifiers in vicinity of incoming test pattern. To measure the goodness of each micro classifier, the weighted sum of correctly classified training patterns in vicinity of the test pattern is used. Experiments have been done on Elena database. Results show that the proposed method gives better classification accuracy than any conventional classifiers like SVM, k-NN and the conventional classifier combination/selection scheme.