• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.537-539
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• 1998

In this paper, we construct the on-line model structure for the nonlinear process systems using the adaptive fuzzy-neural network. Adaptive fuzzy-neural network usually consists of two distinct modifiable structure, with both, the premise and the consequent part. These two parts can be adapted by different optimization methods, which are the hybrid learning procedure combining gradient descent method and least square method. To achieve the on-line model structure, we use the recursive least square method for the consequent parameter identification of nonlinear process. We design the interface between PLC and main computer, and construct the monitoring and control simulator for the nonlinear process. The proposed on-line modeling to real process is carried out to obtain the effective and accurate results.

• ETRI Journal
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• 제36권6호
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• pp.960-967
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• 2014

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi-channel wireless multihop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems - flow control; next-hop routing; rate allocation and scheduling; power control; and channel allocation - and finally solved by a low-complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.

• 진공이야기
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• 제2권2호
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• pp.12-16
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• 2015

Organic photovoltaics (OPVs) have attracted significant interest in an interdisciplinary research field for the decades as a next-generation photovoltaic device due to their unique advantages. One of requirements for OPVs having high power conversion efficiency is the favorable energy level alignment between the electrode/organic and organic/organic interfaces to manage the exciton dissociation and improve the charge transport. In this review, strategies to enhance the OPV performance by controlling the energy level alignment are discussed. The insertion of an exciton blocking layer leads to the efficient dissociation of photogenerated excitons at the donor/acceptor interface enhancing the short-circuit current density. The choice of a donor having a high ionization energy and an acceptor having a low electron affinity increases the open-circuit voltage. The insertion of an appropriate work function modifier which reduces the charge injection barrier removes the S-kink in current density-voltage characteristics of OPVs and improves the fill factor. This review would give a valuable guide to design the efficient OPV structure.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 춘계학술발표대회
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• pp.136-138
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• 2015

SQL의 사용자 편의성과 맵리듀스의 함수형 분산 처리 능력을 동시에 활용하기 위한 통합 작업이 이루어지고 있다. 본 논문에서는 최근 이루어진 관련 연구를 질의 인터페이스 측면과 질의 최적화 측면으로 나누어 살펴보고, 향후 연구 과제에 대해 알아본다.

• 한국멀티미디어학회논문지
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• 제22권4호
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• pp.491-501
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• 2019

Variational methods, which cast deformation as an energy-minimization problem, are known to provide a good trade-off between practicality and speed. However, the time required to deform a fully detailed shape means that these methods are largely unsuitable for real-time applications. We simplify a 2D shape into a curve skeleton, which can be deformed much more rapidly than the original shape. The curve skeleton also provides a simplified control for the user, utilizing a small number of control handles. Our system deforms the curve skeleton using an energy-minimization method and then applies the resulting deformation to the original shape using linear blend skinning. This approach effectively reduces the size of the variational optimization problem while producing deformations of a similar quality to those obtained from full-scale nonlinear variational methods.

• 센서학회지
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• 제27권6호
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• pp.374-379
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• 2018

The piezocomposite transducer is widely used because it is highly efficient in transforming electric energy into mechanical energy, and its frequency range is broader than that of other types of ultrasound transducers. A general piezocomposite transducer is composed of an acoustic lens, impedance matching layers, piezoelectric materials, and backing layers. When an input voltage is applied to a piezoelectric material as an active material, it generates sound waves while vibrating. At that time, an impedance matching layer helps the sound waves to propagate forward while reducing the impedance mismatch that may occur at the interface between the active material and its front material. The impedance mismatch has a negative effect on the signal of an ultrasound transducer; thus, it is important to design a matching layer to overcome the issue. In this study, an optimized feature of a matching layer with gradient properties is studied. An objective function is defined to minimize both the average and the deviation of the reflection coefficients that are functions of the frequencies. As a result, an improvement in the signal characteristics with respect to the sensitivity and bandwidth is reported.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.115-120
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• 2019

In this paper, we propose a system and an intuitive interface that can create an athletic scene among athletes. We allow you to enter motion as if you were playing a game, so that the user's action becomes the player's action. The user can take various actions in front of the motion sensor and control the object flying to him. When a user specifies an opponent to pass or attack, and takes appropriate action in front of the motion sensor, the movement trajectory of the object is automatically generated by the physical optimization technique in accordance with the motion. In this way, you can create scenes where multiple players play together in a virtual environment. The method of this paper will be very useful for rapid prototyping for cinematic trailers of based on athletics games or animations.

• Journal of the Korean Wood Science and Technology
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• 제51권6호
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• pp.481-492
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• 2023

The ecofriendly lifestyle has attracted considerable support for sustainable development. Natural dyes, as sustainable products, have become a research focus and development area for many scientists. Ecofriendly processing also supports circular sustainable development. This study effectively obtained tannins as a natural dye from merbau (Intsia bijuga) sawdust using water as an ecofriendly solvent. Merbau sawdust is an underutilized industrial waste. Temperature and solid-solvent ratio variations were performed to extract tannins from merbau sawdust. Temperature and solid-solvent ratio positively affected solution yield and tannin concentration. The optimal condition was identified using response surface methodology and experimental observations. A yield of 0.2217 g tannins/g merbau was obtained under the conditions of 333.15 K and 0.125 solid-solvent ratio. Extraction was controlled by convective mass transfer at the interface of solid particles.

• 한국지반공학회논문집
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• 제37권3호
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• pp.31-41
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• 2021

도저는 토공사 현장에서 부지를 평탄화하거나 토사를 모으기 위해 사용되는 장비이다. 도저의 성능은 지반-궤도 접지면에서 발현되는 지반추력에 의해 결정되는데, 주어진 조건에서 최대한의 지반추력을 발현시키기 위해서 무한궤도 표면에 그라우저를 부착하는 것이 일반적이다. 본 연구에서는 다양한 형상비를 가지는 그라우저가 부착된 도저의 지반추력을 산정하고, 이를 바탕으로 지반 특성을 고려한 최적 그라우저 형상비를 평가했다. 그라우저는 궤도 측면에서 추가적인 지반추력(측면지반추력)을 발현시키고 지반-궤도 사이의 전단을 지반-지반 사이의 전단으로 전환시켜, 도저의 지반추력을 약 1.3~1.6배 증가시켰다. 그라우저 형상비가 지반추력에 미치는 영향은 도저가 구동하는 지반의 다짐도에 따라 다르게 나타났다. 느슨한 지반에서는 형상비가 작은 그라우저가, 조밀한 지반에서는 형상비가 큰 그라우저가 도저의 지반추력을 가장 크게 증가시킬 수 있는 최적의 형상으로 평가되었다. 무한궤도에 지반의 다짐도를 고려한 최적 그라우저를 부착한다면 도저의 작업 성능을 보다 크게 강화할 수 있을 것이며, 이를 통해 장비의 효율적 활용 및 토공사 생산성 향상이 가능할 것으로 기대된다.

• Journal of Construction Engineering and Project Management
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• 제5권1호
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• pp.11-19
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• 2015

This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.