• 정보처리학회논문지D
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• 제16D권5호
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• pp.729-736
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• 2009

소프트웨어 공학에서 정확한 개발 비용 예측은 성공적인 개발 프로젝트를 위한 필수적인 요소로, 현재까지 많은 소프트웨어 비용산정을 위한 모델들이 개발되어 왔다. 전통적인 통계적 기법부터 기계학습을 적용한 알고리즘까지 다양한 분야의 아이디어를 접목하고 있다. 본 논문에서는 소프트웨어 개발 비용 예측을 위한 방법으로 유전 알고리즘과 서포트 벡터 머신의 회귀모델인 서포트 벡터 회귀를 결합한 GA-SVR 모델을 제안한다. 제안된 모델은 기존의 연구에 비해 향상된 결과를 보이고 있다.

• 한국의학물리학회지:의학물리
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• 제22권4호
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• pp.172-177
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• 2011

본 연구에서는 소동물의 심근에서 $^{68}Ga$-BAPEN PET 영상분석을 통해 심혈 영상 추적자로서의 적용가능성을 보고자 하였다. 소동물용 PET/CT에서 쥐 9마리를 대상으로 120분간의 $^{68}Ga$-BAPEN PET/CT 스캔을 시행하였다. 특별히 킷트를 통해 간편하고 저비용으로 $^{68}Ga$-BAPEN을 합성이 가능하였다. PET 영상은 쥐의 몸통부분에서 $^{68}Ga$-BAPEN의 생체 동적분포를 나타낸다. $^{68}Ga$-BAPEN PET 영상은 처음 수분간 대동맥과 간에서의 섭취가 나타났고 점차 심근에서의 섭취가 이루어졌다. 관심영역은 좌심근, 심혈, 폐, 간에 그렸고 시간-방사능 곡선을 얻었다. 시간-방사능 곡선에서 $^{68}Ga$-BAPEN이 쥐 심근에 잘 결합하는 것을 확인 할 수 있었다. 정확한 약동학적 파라미터 도출을 위한 최소 PET 스캔시간은 타장 기와의 영상 대조도가 일정비에 이르는 주사 후 60분이 적합하였다. 이때 심근의 섭취를 심혈, 간, 폐에서의 섭취로 나누어 얻은 영상 대조도는 각각 1.66, 0.60, 2.82였다. 결론적으로 $^{68}Ga$-BAPEN은 심근 혈류 질환을 진단하기 위한 추적자로서 적합하며 지속적인 연구가 이루어진다면 임상에서의 진단활용에 도움이 될 것이라 예상된다.

• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• IEIE Transactions on Smart Processing and Computing
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• 제2권6호
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• pp.367-372
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• 2013

Cloud computing technology has been developing at an increasing expansion rate. Today most of firms are using this technology, making improving the quality of service one of the most important issues. To achieve this, the system must operate efficiently with less idle time and without deteriorating the customer satisfaction. This paper focuses on enhancing the efficiency of a conventional Genetic Algorithm (GA) for task scheduling in cloud computing using Fuzzy Logic (FL). This study collected a group of task schedules and assessed the quality of each task schedule with the user expectation. The work iterates the best scheduling order genetic operations to make the optimal task schedule. General GA takes considerable time to find the correct scheduling order when all the fitness function parameters are the same. GA is an intuitive approach for solving problems because it covers all possible aspects of the problem. When this approach is combined with fuzzy logic (FL), it behaves like a human brain as a problem solver from an existing database (Memory). The present scheme compares GA with and without FL. Using FL, the proposed system at a 100, 400 and 1000 sample size*5 gave 70%, 57% and 47% better improvement in the task time compared to GA.

• JSTS:Journal of Semiconductor Technology and Science
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• 제14권5호
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• pp.682-687
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• 2014

We have performed reverse gate bias stress tests on AlGaN/GaN-on-Si Heterostructure FETs (HFETs). The shift of threshold voltage ($V_{th}$) and the reduction of on-current were observed from the stressed devices. These changes of the device parameters were not permanent. We investigated the temporary behavior of the stressed devices by analyzing the temperature dependence of the instabilities and TCAD simulation. As the baseline temperature of the electrical stress tests increased, the changes of the $V_{th}$ and the on-current were decreased. The on-current reduction was caused by the positive shift of the $V_{th}$ and the increased resistance of the gate-to-source and the gate-to-drain access region. Our experimental results suggest that electron-trapping effect into the shallow traps in devices is the main cause of observed instabilities.

• 한국광학회지
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• 제22권1호
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• pp.35-39
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• 2011

다층 비율 방정식을 이용한 1550 nm InGaAsP 레이저 다이오드의 PSPICE 등가회로 모델을 제안하고 구현하였다. 비율 방정식에 필요한 레이저 다이오드 파라미터들은 자기충족적 양자우물 해석법을 이용하여 도출하였다. 이 모델을 이용하여 실제 레이저 다이오드와 드라이버 IC를 포함하는 광송신기 회로 전체를 PSPICE로 구현하여 그 출력 값과 측정치를 비교하였다. 이 비교를 통하여 실제 레이저 다이오드의 패키징 시 발생하는 기생 커패시터 값을 산출하였다. 이를 바탕으로 한 PSPICE 출력 값은 여러 동작 주파수에서 실제 회로의 측정값과 일치함을 보였다.

• 한국재료학회지
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• 제12권3호
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• pp.190-194
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• 2002

InN/GaN multi-layers were grown by metalorganic chemical vapor deposition(MOCVD) in order to get the appropriate structure for an high power blue-green light emitting diode(LED), and effects of growth conditions (growth temperature, pressure, and $trimethylindium(TMIn)-NH_3-N_2\; flow\; rare)$ on the integrated photoluminescence (PL) intensity and PL peak energy in InN/GaN multi-layers were investigated. The optimized growth conditions with the highest integrated PL intensity for InN/GaN multi-layers were obtained: the growth temperature at $780^{\circ}C$, the growth pressure at 325 Torr, the TMIn flow rate with 150 $m\ell$/min, the $NH_3$flow rate with 3.2 ι/min, and $N_2$ flow rate with 2 ι/min.

• 대한화학회지
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• 제60권4호
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• pp.225-234
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• 2016

The activity of 34 sulfonamide derivatives has been estimated by means of multiple linear regression (MLR), artificial neural network (ANN), simulated annealing (SA) and genetic algorithm (GA) techniques. These models were also utilized to select the most efficient subsets of descriptors in a cross-validation procedure for non-linear -log (IC50) prediction. The results obtained using GA-ANN were compared with MLR-MLR, MLR-ANN, SA-ANN and GA-ANN approaches. A high predictive ability was observed for the MLR-MLR, MLR-ANN, SA-ANN and MLR-GA models, with root mean sum square errors (RMSE) of 0.3958, 0.1006, 0.0359, 0.0326 and 0.0282 in gas phase and 0.2871, 0.0475, 0.0268, 0.0376 and 0.0097 in solvent, respectively (N=34). The results obtained using the GA-ANN method indicated that the activity of derivatives of sulfonamides depends on different parameters including DP03, BID, AAC, RDF035v, JGI9, TIE, R7e+, BELM6 descriptors in gas phase and Mor 32u, ESpm03d, RDF070v, ATS8m, MATS2e and R4p, L1u and R3m in solvent. In conclusion, the comparison of the quality of the ANN with different MLR models showed that ANN has a better predictive ability.

• Journal of Magnetics
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• 제7권2호
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• pp.40-44
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• 2002

Crystallographic and magnetic properties of ;$LaFe_{1-x}Ga_xO_3$($\chi$= 0, 0.1, 0.3, 0.5, and 0.7) were studied using XRD and Mossbauer spectroscopy. The crystal structures were found to be orthorhombic and the lattice parameters $\alpha$, b, and c were found to decrease with increasing Ga substitution. M$\ddot{o}$ssbauer spectra were obtained at various absorber temperatures ranging from 20 K to 750 K. The M$\ddot{o}$ssbauer spectra were all sextets below $T_N$ and were all singlets above $T_N$. Asymmetric broadening of the M$\ddot{o}$ssbauer spectral lines at 20 K was explained by the multitude of possible environments for an iron nucleus. As the temperature increases to $T_N$, a systematic line broadening in M$\ddot{o}$ssbauer spectra was observed and interpreted to originate from different temperature dependencies of the magnetic hyperfine fields at various iron sites.

• Earthquakes and Structures
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• 제22권1호
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• pp.53-64
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• 2022

This study proposes an intelligent semi-active isolation system combining a variable-stiffness control device and ground motion characteristic prediction. To determine the optimal control parameter in real-time, a genetic algorithm (GA)-fuzzy control law was developed in this study. Data on various types of ground motions were collected, and the ground motion characteristics were quantified to derive a near-fault (NF) characteristic ratio by employing an on-site earthquake early warning system. On the basis of the peak ground acceleration (PGA) and the derived NF ratio, a fuzzy inference system (FIS) was developed. The control parameters were optimized using a GA. To support continuity under near-fault and far-field ground motions, the optimal control parameter was linked with the predicted PGA and NF ratio through the FIS. The GA-fuzzy law was then compared with other control laws to verify its effectiveness. The results revealed that the GA-fuzzy control law could reliably predict different ground motion characteristics for real-time control because of the high sensitivity of its control parameter to the ground motion characteristics. Even under near-fault and far-field ground motions, the GA-fuzzy control law outperformed the FPEEA control law in terms of controlling the isolation layer displacement and the superstructure acceleration.