• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.5
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• pp.1337-1348
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• 1990

Estimations of the thermodynamic properties are made for the selected binary non-azeotropic refrigerant mixtures including R13B1/R114, R22/R114, R12/R114, R152a/R114, R13B1/R152a and R13B1/R12 using the Peng-Robinson equation of state and mixing rules. In this study, we find that the binary interaction coefficients for the above mixtures have an effect upon the vapor-liquid equilibria and the thermodynamic properties. As the binary interaction coefficient becomes larger, the deviation from the idealized model, say, Raoult`s rule, is obvious. A correlation is proposed to relate the binary interaction coefficient to the difference between the dipole moments op each pure refrigerant. Vapor-liquid equilibrium are also accurately estimated using the binary interaction coefficient. Pressure-enthalpy and temperature-entropy relations are plotted for a certain composition ratio of each refrigerant mixture. Results show that the estimating method in this study can be applied to the investigation of the thermodynamic properties for the binary non-azeotropic refrigerant mixtures.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.36-43
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• 2009

In this paper, we propose a Cooperative Routing using ARQ-based Transmission (CRARQ) in Mobile Ad-hoc Wireless Sensor Networks (MAWSN). The goals of the CRARQ are to improve both the efficiency of transmission and the reliability of transmission together. The main features and contributions of the proposed CRARQ for supporting these goals are as follows. First, CRARQ uses a reactive concept to construct a route from a source to a destination. Second, CRARQ chooses the most stable relay at each hop along the route by mobility-based strategy. Third, cooperative transmission using the ARQ technique which can improve reliability is used at each hop to send data packets from source to destination. Finally, we present a theoretical analysis model for the proposed CRARQ. The performance evaluation of our protocol is implemented via simulation using Optimized Network Engineering Tool (OPNET) and analysis. The results of both simulation and analysis show that CRARQ achieves the improved packet delivery ratio (PDR) and outage probability.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.352-363
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• 2019

Background: Invasive plant species are considered a major threat to biodiversity, ecosystem functioning, and human wellbeing worldwide. Climatically suitable ranges for invasive plant species are expected to expand due to future climate change. The identification of current invasions and potential range expansion of invasive plant species is required to plan for the management of these species. Here, we predicted climatically suitable habitats for 11 invasive plant species and calculated the potential species richness and their range expansions in different provinces of the Republic of Korea (ROK) under current and future climate change scenarios (RCP 4.5 and RCP 8.5) using the maximum entropy (MaxEnt) modeling approach. Results: Based on the model predictions, areas of climatically suitable habitats for 90.9% of the invasive plant species are expected to retain current ecological niches and expand to include additional climatically suitable areas under future climate change scenarios. Species richness is predicted to be relatively high in the provinces of the western and southern regions (e.g., Jeollanam, Jeollabuk, and Chungcheongnam) under current climatic conditions. However, under future climates, richness in the provinces of the northern, eastern, and southeastern regions (e.g., Seoul, Incheon, Gyeonggi, Gyeongsangnam, Degue, Busan, and Ulsan) is estimated to increase up to 292%, 390.75%, and 468.06% by 2030, 2050, and 2080, respectively, compared with the current richness. Conclusions: Our study revealed that the rates of introduction and dispersion of invasive plant species from the western and southern coasts are relatively high and are expanding across the ROK through different modes of dispersion. The negative impacts on biodiversity, ecosystem dynamics, and economy caused by invasive plant species will be high if preventive and eradication measures are not employed immediately. Thus, this study will be helpful to policymakers for the management of invasive plant species and the conservation of biodiversity.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.4
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• pp.397-403
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• 2015

In this paper, a method of ISAR geometric calibration is represented by using impulse-radio UWB radar. The ir-UWB is good for using a signal processing in time domain, so, it does not occur a multi-path or coupling problem. If a signal that between antennas and target is assumed a plane wave, a center of rotation in ISAR geometry model can be estimated by using point target. Before image is reconstructed with sinogram, the center of rotation can be calculated by using least square fitting. This method can be obtained a more contrast image, and a maximum value of entropy of image. The method, that estimates a center of rotation in received data, will be used a initial setup of instruments or a periodic compensation to reconstruct image. It would be useful in medical, security and surveillance imaging equipments that have a fixed geometry.

• Annual Conference on Human and Language Technology
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• 2006.10e
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• pp.268-272
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• 2006

질의응답 시스템은 사용자 질의에 해당하는 정답을 찾기 위해서 세부 분류된 개체명을 사용한다. 이러한 세부 분류 개체명 인식을 위해서 대부분의 시스템이 일반 대분류 개체명인식 후에 사전 등을 이용하여 세부 분류로 나누는 방법을 이용하고 있다. 본 논문에서는 질의응답 시스템을 위한 세부 분류 개체명 인식을 위해서 Conditional Random Fields를 이용한다. 개체명 인식의 과정을 개체명 경계 인식과 경계가 인식된 개체명의 클래스 분류의 두 단계로 나누어, 개체명 경계 인식에 Conditional Random Fields를 이용하고, 경계 인식된 개체명의 클래스 분류에는 Maximum Entropy를 이용한다. 실험결과 147개의 세부분류 개체명 인식에 대해서 정확도 85.8%, 재현률 81.1%. F1=83.4의 성능을 얻었고. baseline model 보다 학습 시간이 27%로 줄고 성능은 증가하였다. 또한 제안된 세부 분류개체명 인식기를 이용하여 질의응답 시스템에 적용한 결과 26%의 성능향상을 보였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.677-680
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• 2005

In numerical analysis on the thermal performance of the heat exchanger with phase change fluids, the numerical values of thermodynamic properties are needed. But the steam table should be modeled properly as the direct use of thermodynamic properties of the steam table is impossible. In this study the function approximation characteristics of neural networks was used in modeling the saturated vapor region of refrigerant R12. The neural network consists of one input layer with one node, two hidden layers with 10 and 20 nodes each and one output layer with 7 nodes. Input can be both saturation temperature and saturation pressure and two cases were examined. The proposed model gives percentage error of ${\pm}$0.005% for enthalpy and entropy, ${\pm}$0.02% for specific volume and ${\pm}$0.02% for saturation pressure and saturation temperature except several points. From this results neural network could be a powerful method in function approximation of saturated vapor region of R12.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.324-333
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• 2001

In this paper we present a novel color image segmentation algorithm based on a Gaussian Mixture Model(GMM). It is introduced a Deterministic Annealing Expectation Maximization(DAEM) algorithm which is developed using the principle of maximum entropy to overcome the local maxima problem associated with the standard EM algorithm. In our approach, the GMM is used to represent the multi-colored objects statistically and its parameters are estimated by DAEM algorithm. We also develop the automatic determination method of the number of components in Gaussian mixtures models. The segmentation of image is based on the maximum posterior probability distribution which is calculated by using the GMM. The experimental results show that the proposed DAEM can estimate the parameters more accurately than the standard EM and the determination method of the number of mixture models is very efficient. When tested on two natural images, the proposed algorithm performs much better than the traditional algorithm in segmenting the image fields.

• Journal of the Korean association of regional geographers
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• v.21 no.1
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• pp.21-38
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• 2015

This study attempts to estimate the complementarity between 21 cities in the Korean Southeastern Region using data on the network time distance and the volume of flow between the cities. Four types of flows recognized are people, commodities, information and finance. The first two types of flows are thought to be made on the transportation network while the last two are on the communication network. For the purpose of the study, the expected volumes of flows between cities are first estimated using the gravity-based regression and doubly-constrained entropy maximization models. These baseline volumes are then subtracted from the observed volumes of flows (of people and commodities) or the estimated volumes of flows (of information and finance) in order to identify positive differences or complementarities. The result shows that these four types of complementarity flows form distinctive urban networks in terms of spatial pattern and urban hierarchy. This suggests that more customized strategies to different types of complementarity are recommended to properly address the issues related to network infrastructure provision in the pursuit of the network city model in the region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2008-2013
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• 2006

In numerical analysis on evaluating the thermal performance of the thermal equipment, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table itself cannot be used without modelling. In this study applicability of neural networks in modelling the wide temperature range of wet saturated vapor region was examined. the multi-layer neural network consists of a input layer with 1 node, two hidden layers with 10 and 20 nodes respectively and a output layer with 6 nodes. Quadratic and cubic spline interpoations methods were also applied for comparison. Neural network model revealed similar percentage error to spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the wide range of the steam table.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.685-690
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• 2008

In numerically evaluating the thermal performance of the heat exchanger, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be directly used without modelling. In this study the applicability of neural networks in modelling superheated water vapor was examined. The multi-layer neural networks consist of an input layer with 2 nodes, two hidden layers with 15 and 25 nodes respectively and an output layer with 3 nodes. Quadratic spline interpolation was also applied for comparison. Neural networks model revealed smaller percentage error compared with spline interpolation. From this result, it is confirmed that the neural networks could be a powerful method in modelling the superheated water vapor.