Lamb Wave Damage Quantification Using GA-Based LS-SVM

PubMed Central

Sun, Fuqiang; Wang, Ning; He, Jingjing; Guan, Xuefei; Yang, Jinsong

2017-01-01

Lamb waves have been reported to be an efficient tool for non-destructive evaluations (NDE) for various application scenarios. However, accurate and reliable damage quantification using the Lamb wave method is still a practical challenge, due to the complex underlying mechanism of Lamb wave propagation and damage detection. This paper presents a Lamb wave damage quantification method using a least square support vector machine (LS-SVM) and a genetic algorithm (GA). Three damage sensitive features, namely, normalized amplitude, phase change, and correlation coefficient, were proposed to describe changes of Lamb wave characteristics caused by damage. In view of commonly used data-driven methods, the GA-based LS-SVM model using the proposed three damage sensitive features was implemented to evaluate the crack size. The GA method was adopted to optimize the model parameters. The results of GA-based LS-SVM were validated using coupon test data and lap joint component test data with naturally developed fatigue cracks. Cases of different loading and manufacturer were also included to further verify the robustness of the proposed method for crack quantification. PMID:28773003

Multi-objective Optimization Design of Gear Reducer Based on Adaptive Genetic Algorithms

NASA Astrophysics Data System (ADS)

Li, Rui; Chang, Tian; Wang, Jianwei; Wei, Xiaopeng; Wang, Jinming

2008-11-01

An adaptive Genetic Algorithm (GA) is introduced to solve the multi-objective optimized design of the reducer. Firstly, according to the structure, strength, etc. in a reducer, a multi-objective optimized model of the helical gear reducer is established. And then an adaptive GA based on a fuzzy controller is introduced, aiming at the characteristics of multi-objective, multi-parameter, multi-constraint conditions. Finally, a numerical example is illustrated to show the advantages of this approach and the effectiveness of an adaptive genetic algorithm used in optimized design of a reducer.

GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design.

PubMed

Pérez-Castillo, Yunierkis; Lazar, Cosmin; Taminau, Jonatan; Froeyen, Mathy; Cabrera-Pérez, Miguel Ángel; Nowé, Ann

2012-09-24

Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug design. Here we introduce the GA(M)E-QSAR algorithm that combines the search and optimization capabilities of Genetic Algorithms with the simplicity of the Adaboost ensemble-based classification algorithm to solve binary classification problems. We also explore the usefulness of Meta-Ensembles trained with Adaboost and Voting schemes to further improve the accuracy, generalization, and robustness of the optimal Adaboost Single Ensemble derived from the Genetic Algorithm optimization. We evaluated the performance of our algorithm using five data sets from the literature and found that it is capable of yielding similar or better classification results to what has been reported for these data sets with a higher enrichment of active compounds relative to the whole actives subset when only the most active chemicals are considered. More important, we compared our methodology with state of the art feature selection and classification approaches and found that it can provide highly accurate, robust, and generalizable models. In the case of the Adaboost Ensembles derived from the Genetic Algorithm search, the final models are quite simple since they consist of a weighted sum of the output of single feature classifiers. Furthermore, the Adaboost scores can be used as ranking criterion to prioritize chemicals for synthesis and biological evaluation after virtual screening experiments.

Load forecast method of electric vehicle charging station using SVR based on GA-PSO

NASA Astrophysics Data System (ADS)

Lu, Kuan; Sun, Wenxue; Ma, Changhui; Yang, Shenquan; Zhu, Zijian; Zhao, Pengfei; Zhao, Xin; Xu, Nan

2017-06-01

This paper presents a Support Vector Regression (SVR) method for electric vehicle (EV) charging station load forecast based on genetic algorithm (GA) and particle swarm optimization (PSO). Fuzzy C-Means (FCM) clustering is used to establish similar day samples. GA is used for global parameter searching and PSO is used for a more accurately local searching. Load forecast is then regressed using SVR. The practical load data of an EV charging station were taken to illustrate the proposed method. The result indicates an obvious improvement in the forecasting accuracy compared with SVRs based on PSO and GA exclusively.

Bell-Curve Based Evolutionary Optimization Algorithm

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; Laba, K.; Kincaid, R.

1998-01-01

The paper presents an optimization algorithm that falls in the category of genetic, or evolutionary algorithms. While the bit exchange is the basis of most of the Genetic Algorithms (GA) in research and applications in America, some alternatives, also in the category of evolutionary algorithms, but use a direct, geometrical approach have gained popularity in Europe and Asia. The Bell-Curve Based Evolutionary Algorithm (BCB) is in this alternative category and is distinguished by the use of a combination of n-dimensional geometry and the normal distribution, the bell-curve, in the generation of the offspring. The tool for creating a child is a geometrical construct comprising a line connecting two parents and a weighted point on that line. The point that defines the child deviates from the weighted point in two directions: parallel and orthogonal to the connecting line, the deviation in each direction obeying a probabilistic distribution. Tests showed satisfactory performance of BCB. The principal advantage of BCB is its controllability via the normal distribution parameters and the geometrical construct variables.

Adaptively resizing populations: Algorithm, analysis, and first results

NASA Technical Reports Server (NTRS)

Smith, Robert E.; Smuda, Ellen

1993-01-01

Deciding on an appropriate population size for a given Genetic Algorithm (GA) application can often be critical to the algorithm's success. Too small, and the GA can fall victim to sampling error, affecting the efficacy of its search. Too large, and the GA wastes computational resources. Although advice exists for sizing GA populations, much of this advice involves theoretical aspects that are not accessible to the novice user. An algorithm for adaptively resizing GA populations is suggested. This algorithm is based on recent theoretical developments that relate population size to schema fitness variance. The suggested algorithm is developed theoretically, and simulated with expected value equations. The algorithm is then tested on a problem where population sizing can mislead the GA. The work presented suggests that the population sizing algorithm may be a viable way to eliminate the population sizing decision from the application of GA's.

Human emotion detector based on genetic algorithm using lip features

NASA Astrophysics Data System (ADS)

Brown, Terrence; Fetanat, Gholamreza; Homaifar, Abdollah; Tsou, Brian; Mendoza-Schrock, Olga

2010-04-01

We predicted human emotion using a Genetic Algorithm (GA) based lip feature extractor from facial images to classify all seven universal emotions of fear, happiness, dislike, surprise, anger, sadness and neutrality. First, we isolated the mouth from the input images using special methods, such as Region of Interest (ROI) acquisition, grayscaling, histogram equalization, filtering, and edge detection. Next, the GA determined the optimal or near optimal ellipse parameters that circumvent and separate the mouth into upper and lower lips. The two ellipses then went through fitness calculation and were followed by training using a database of Japanese women's faces expressing all seven emotions. Finally, our proposed algorithm was tested using a published database consisting of emotions from several persons. The final results were then presented in confusion matrices. Our results showed an accuracy that varies from 20% to 60% for each of the seven emotions. The errors were mainly due to inaccuracies in the classification, and also due to the different expressions in the given emotion database. Detailed analysis of these errors pointed to the limitation of detecting emotion based on the lip features alone. Similar work [1] has been done in the literature for emotion detection in only one person, we have successfully extended our GA based solution to include several subjects.

Interpreting the cross-sectional flow field in a river bank based on a genetic-algorithm two-dimensional heat-transport method (GA-VS2DH)

NASA Astrophysics Data System (ADS)

Su, Xiaoru; Shu, Longcang; Chen, Xunhong; Lu, Chengpeng; Wen, Zhonghui

2016-12-01

Interactions between surface waters and groundwater are of great significance for evaluating water resources and protecting ecosystem health. Heat as a tracer method is widely used in determination of the interactive exchange with high precision, low cost and great convenience. The flow in a river-bank cross-section occurs in vertical and lateral directions. In order to depict the flow path and its spatial distribution in bank areas, a genetic algorithm (GA) two-dimensional (2-D) heat-transport nested-loop method for variably saturated sediments, GA-VS2DH, was developed based on Microsoft Visual Basic 6.0. VS2DH was applied to model a 2-D bank-water flow field and GA was used to calibrate the model automatically by minimizing the difference between observed and simulated temperatures in bank areas. A hypothetical model was developed to assess the reliability of GA-VS2DH in inverse modeling in a river-bank system. Some benchmark tests were conducted to recognize the capability of GA-VS2DH. The results indicated that the simulated seepage velocity and parameters associated with GA-VS2DH were acceptable and reliable. Then GA-VS2DH was applied to two field sites in China with different sedimentary materials, to verify the reliability of the method. GA-VS2DH could be applied in interpreting the cross-sectional 2-D water flow field. The estimates of horizontal hydraulic conductivity at the Dawen River and Qinhuai River sites are 1.317 and 0.015 m/day, which correspond to sand and clay sediment in the two sites, respectively.

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Complex motion measurement using genetic algorithm

NASA Astrophysics Data System (ADS)

Shen, Jianjun; Tu, Dan; Shen, Zhenkang

1997-12-01

Genetic algorithm (GA) is an optimization technique that provides an untraditional approach to deal with many nonlinear, complicated problems. The notion of motion measurement using genetic algorithm arises from the fact that the motion measurement is virtually an optimization process based on some criterions. In the paper, we propose a complex motion measurement method using genetic algorithm based on block-matching criterion. The following three problems are mainly discussed and solved in the paper: (1) apply an adaptive method to modify the control parameters of GA that are critical to itself, and offer an elitism strategy at the same time (2) derive an evaluate function of motion measurement for GA based on block-matching technique (3) employ hill-climbing (HC) method hybridly to assist GA's search for the global optimal solution. Some other related problems are also discussed. At the end of paper, experiments result is listed. We employ six motion parameters for measurement in our experiments. Experiments result shows that the performance of our GA is good. The GA can find the object motion accurately and rapidly.

Prediction of Industrial Electric Energy Consumption in Anhui Province Based on GA-BP Neural Network

NASA Astrophysics Data System (ADS)

Zhang, Jiajing; Yin, Guodong; Ni, Youcong; Chen, Jinlan

2018-01-01

In order to improve the prediction accuracy of industrial electrical energy consumption, a prediction model of industrial electrical energy consumption was proposed based on genetic algorithm and neural network. The model use genetic algorithm to optimize the weights and thresholds of BP neural network, and the model is used to predict the energy consumption of industrial power in Anhui Province, to improve the prediction accuracy of industrial electric energy consumption in Anhui province. By comparing experiment of GA-BP prediction model and BP neural network model, the GA-BP model is more accurate with smaller number of neurons in the hidden layer.

A novel pipeline based FPGA implementation of a genetic algorithm

NASA Astrophysics Data System (ADS)

Thirer, Nonel

2014-05-01

To solve problems when an analytical solution is not available, more and more bio-inspired computation techniques have been applied in the last years. Thus, an efficient algorithm is the Genetic Algorithm (GA), which imitates the biological evolution process, finding the solution by the mechanism of "natural selection", where the strong has higher chances to survive. A genetic algorithm is an iterative procedure which operates on a population of individuals called "chromosomes" or "possible solutions" (usually represented by a binary code). GA performs several processes with the population individuals to produce a new population, like in the biological evolution. To provide a high speed solution, pipelined based FPGA hardware implementations are used, with a nstages pipeline for a n-phases genetic algorithm. The FPGA pipeline implementations are constraints by the different execution time of each stage and by the FPGA chip resources. To minimize these difficulties, we propose a bio-inspired technique to modify the crossover step by using non identical twins. Thus two of the chosen chromosomes (parents) will build up two new chromosomes (children) not only one as in classical GA. We analyze the contribution of this method to reduce the execution time in the asynchronous and synchronous pipelines and also the possibility to a cheaper FPGA implementation, by using smaller populations. The full hardware architecture for a FPGA implementation to our target ALTERA development card is presented and analyzed.

Comparison of the genetic algorithm and incremental optimisation routines for a Bayesian inverse modelling based network design

NASA Astrophysics Data System (ADS)

Nickless, A.; Rayner, P. J.; Erni, B.; Scholes, R. J.

2018-05-01

The design of an optimal network of atmospheric monitoring stations for the observation of carbon dioxide (CO2) concentrations can be obtained by applying an optimisation algorithm to a cost function based on minimising posterior uncertainty in the CO2 fluxes obtained from a Bayesian inverse modelling solution. Two candidate optimisation methods assessed were the evolutionary algorithm: the genetic algorithm (GA), and the deterministic algorithm: the incremental optimisation (IO) routine. This paper assessed the ability of the IO routine in comparison to the more computationally demanding GA routine to optimise the placement of a five-member network of CO2 monitoring sites located in South Africa. The comparison considered the reduction in uncertainty of the overall flux estimate, the spatial similarity of solutions, and computational requirements. Although the IO routine failed to find the solution with the global maximum uncertainty reduction, the resulting solution had only fractionally lower uncertainty reduction compared with the GA, and at only a quarter of the computational resources used by the lowest specified GA algorithm. The GA solution set showed more inconsistency if the number of iterations or population size was small, and more so for a complex prior flux covariance matrix. If the GA completed with a sub-optimal solution, these solutions were similar in fitness to the best available solution. Two additional scenarios were considered, with the objective of creating circumstances where the GA may outperform the IO. The first scenario considered an established network, where the optimisation was required to add an additional five stations to an existing five-member network. In the second scenario the optimisation was based only on the uncertainty reduction within a subregion of the domain. The GA was able to find a better solution than the IO under both scenarios, but with only a marginal improvement in the uncertainty reduction. These results suggest

A new compound arithmetic crossover-based genetic algorithm for constrained optimisation in enterprise systems

NASA Astrophysics Data System (ADS)

Jin, Chenxia; Li, Fachao; Tsang, Eric C. C.; Bulysheva, Larissa; Kataev, Mikhail Yu

2017-01-01

In many real industrial applications, the integration of raw data with a methodology can support economically sound decision-making. Furthermore, most of these tasks involve complex optimisation problems. Seeking better solutions is critical. As an intelligent search optimisation algorithm, genetic algorithm (GA) is an important technique for complex system optimisation, but it has internal drawbacks such as low computation efficiency and prematurity. Improving the performance of GA is a vital topic in academic and applications research. In this paper, a new real-coded crossover operator, called compound arithmetic crossover operator (CAC), is proposed. CAC is used in conjunction with a uniform mutation operator to define a new genetic algorithm CAC10-GA. This GA is compared with an existing genetic algorithm (AC10-GA) that comprises an arithmetic crossover operator and a uniform mutation operator. To judge the performance of CAC10-GA, two kinds of analysis are performed. First the analysis of the convergence of CAC10-GA is performed by the Markov chain theory; second, a pair-wise comparison is carried out between CAC10-GA and AC10-GA through two test problems available in the global optimisation literature. The overall comparative study shows that the CAC performs quite well and the CAC10-GA defined outperforms the AC10-GA.

An Improved SoC Test Scheduling Method Based on Simulated Annealing Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Jingjing; Shen, Zhihang; Gao, Huaien; Chen, Bianna; Zheng, Weida; Xiong, Xiaoming

2017-02-01

In this paper, we propose an improved SoC test scheduling method based on simulated annealing algorithm (SA). It is our first to disorganize IP core assignment for each TAM to produce a new solution for SA, allocate TAM width for each TAM using greedy algorithm and calculate corresponding testing time. And accepting the core assignment according to the principle of simulated annealing algorithm and finally attain the optimum solution. Simultaneously, we run the test scheduling experiment with the international reference circuits provided by International Test Conference 2002(ITC’02) and the result shows that our algorithm is superior to the conventional integer linear programming algorithm (ILP), simulated annealing algorithm (SA) and genetic algorithm(GA). When TAM width reaches to 48,56 and 64, the testing time based on our algorithm is lesser than the classic methods and the optimization rates are 30.74%, 3.32%, 16.13% respectively. Moreover, the testing time based on our algorithm is very close to that of improved genetic algorithm (IGA), which is state-of-the-art at present.

Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

USGS Publications Warehouse

Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

2007-01-01

To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

A Comparative Study of Probability Collectives Based Multi-agent Systems and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Huang, Chien-Feng; Wolpert, David H.; Bieniawski, Stefan; Strauss, Charles E. M.

2005-01-01

We compare Genetic Algorithms (GA's) with Probability Collectives (PC), a new framework for distributed optimization and control. In contrast to GA's, PC-based methods do not update populations of solutions. Instead they update an explicitly parameterized probability distribution p over the space of solutions. That updating of p arises as the optimization of a functional of p. The functional is chosen so that any p that optimizes it should be p peaked about good solutions. The PC approach works in both continuous and discrete problems. It does not suffer from the resolution limitation of the finite bit length encoding of parameters into GA alleles. It also has deep connections with both game theory and statistical physics. We review the PC approach using its motivation as the information theoretic formulation of bounded rationality for multi-agent systems. It is then compared with GA's on a diverse set of problems. To handle high dimensional surfaces, in the PC method investigated here p is restricted to a product distribution. Each distribution in that product is controlled by a separate agent. The test functions were selected for their difficulty using either traditional gradient descent or genetic algorithms. On those functions the PC-based approach significantly outperforms traditional GA's in both rate of descent, trapping in false minima, and long term optimization.

Multi-robot task allocation based on two dimensional artificial fish swarm algorithm

NASA Astrophysics Data System (ADS)

Zheng, Taixiong; Li, Xueqin; Yang, Liangyi

2007-12-01

The problem of task allocation for multiple robots is to allocate more relative-tasks to less relative-robots so as to minimize the processing time of these tasks. In order to get optimal multi-robot task allocation scheme, a twodimensional artificial swarm algorithm based approach is proposed in this paper. In this approach, the normal artificial fish is extended to be two dimension artificial fish. In the two dimension artificial fish, each vector of primary artificial fish is extended to be an m-dimensional vector. Thus, each vector can express a group of tasks. By redefining the distance between artificial fish and the center of artificial fish, the behavior of two dimension fish is designed and the task allocation algorithm based on two dimension artificial swarm algorithm is put forward. At last, the proposed algorithm is applied to the problem of multi-robot task allocation and comparer with GA and SA based algorithm is done. Simulation and compare result shows the proposed algorithm is effective.

A Novel Extraction Approach of Extrinsic and Intrinsic Parameters of InGaAs/GaN pHEMTs

DTIC Science & Technology

2015-07-01

presented, for the first time, artificial bee colony algorithm is applied to the global-optimization based parameter extraction and a novel intrinsic...conservation of the gate charge is well satisfied which further validates this novel extraction method. Index Terms —InGaAs/GaN pHEMTs, artificial bee ...increase the uniqueness of the extraction. Artificial bee colony (ABC) algorithm is adopted as the optimizer due to its excellent ability to escape

A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization.

PubMed

Sun, Tao; Xu, Ming-Hai

2017-01-01

Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by introducing the rejection region, thus proposing a new binary algorithm, named swarm optimization genetic algorithm (SOGA), because it is more like genetic algorithm (GA) than PSO in form. SOGA has crossover and mutation operator as GA but does not need to set the crossover and mutation probability, so it has fewer parameters to control. The proposed algorithm was tested with several nonlinear high-dimension functions in the binary search space, and the results were compared with those from BPSO, BQPSO, and GA. The experimental results show that SOGA is distinctly superior to the other three algorithms in terms of solution accuracy and convergence.

Determination of composition of non-homogeneous GaInNAs layers

NASA Astrophysics Data System (ADS)

Pucicki, D.; Bielak, K.; Ściana, B.; Radziewicz, D.; Latkowska-Baranowska, M.; Kováč, J.; Vincze, A.; Tłaczała, M.

2016-01-01

Dilute nitride GaInNAs alloys grown on GaAs have become perspective materials for so called low-cost GaAs-based devices working within the optical wavelength range up to 1.6 μm. The multilayer structures of GaInNAs/GaAs multi-quantum well (MQW) samples usually are analyzed by using high resolution X-ray diffraction (HRXRD) measurements. However, demands for precise structural characterization of the GaInNAs containing heterostructures requires taking into consideration all inhomogeneities of such structures. This paper describes some of the material challenges and progress in structural characterization of GaInNAs layers. A new algorithm for structural characterization of dilute nitrides which bounds contactless electro-reflectance (CER) or photo-reflectance (PR) measurements and HRXRD analysis results together with GaInNAs quantum well band diagram calculation is presented. The triple quantum well (3QW) GaInNAs/GaAs structures grown by atmospheric-pressure metalorganic vapor-phase epitaxy (AP-MOVPE) were investigated according to the proposed algorithm. Thanks to presented algorithm, more precise structural data including the nonuniformity in the growth direction of GaInNAs/GaAs QWs were achieved. Therefore, the proposed algorithm is mentioned as a nondestructive method for characterization of multicomponent inhomogeneous semiconductor structures with quantum wells.

The effect of the electron–phonon interaction on reverse currents of GaAs-based p–n junctions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhukov, A. V., E-mail: ZhukovAndreyV@mail.ru

An algorithm for calculating the parameters of the electron–phonon interaction of the EL2 trap has been developed and implemented based on the example of GaAs. Using the obtained parameters, the field dependences of the probabilities of nonradiative transitions from the trap and reverse currents of the GaAs p–n junctions are calculated, which are in good agreement with the experimental data.

Optimal sensor placement for time-domain identification using a wavelet-based genetic algorithm

NASA Astrophysics Data System (ADS)

Mahdavi, Seyed Hossein; Razak, Hashim Abdul

2016-06-01

This paper presents a wavelet-based genetic algorithm strategy for optimal sensor placement (OSP) effective for time-domain structural identification. Initially, the GA-based fitness evaluation is significantly improved by using adaptive wavelet functions. Later, a multi-species decimal GA coding system is modified to be suitable for an efficient search around the local optima. In this regard, a local operation of mutation is introduced in addition with regeneration and reintroduction operators. It is concluded that different characteristics of applied force influence the features of structural responses, and therefore the accuracy of time-domain structural identification is directly affected. Thus, the reliable OSP strategy prior to the time-domain identification will be achieved by those methods dealing with minimizing the distance of simulated responses for the entire system and condensed system considering the force effects. The numerical and experimental verification on the effectiveness of the proposed strategy demonstrates the considerably high computational performance of the proposed OSP strategy, in terms of computational cost and the accuracy of identification. It is deduced that the robustness of the proposed OSP algorithm lies in the precise and fast fitness evaluation at larger sampling rates which result in the optimum evaluation of the GA-based exploration and exploitation phases towards the global optimum solution.

apGA: An adaptive parallel genetic algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liepins, G.E.; Baluja, S.

1991-01-01

We develop apGA, a parallel variant of the standard generational GA, that combines aggressive search with perpetual novelty, yet is able to preserve enough genetic structure to optimally solve variably scaled, non-uniform block deceptive and hierarchical deceptive problems. apGA combines elitism, adaptive mutation, adaptive exponential scaling, and temporal memory. We present empirical results for six classes of problems, including the DeJong test suite. Although we have not investigated hybrids, we note that apGA could be incorporated into other recent GA variants such as GENITOR, CHC, and the recombination stage of mGA. 12 refs., 2 figs., 2 tabs.

Identification of handwriting by using the genetic algorithm (GA) and support vector machine (SVM)

NASA Astrophysics Data System (ADS)

Zhang, Qigui; Deng, Kai

2016-12-01

As portable digital camera and a camera phone comes more and more popular, and equally pressing is meeting the requirements of people to shoot at any time, to identify and storage handwritten character. In this paper, genetic algorithm(GA) and support vector machine(SVM)are used for identification of handwriting. Compare with parameters-optimized method, this technique overcomes two defects: first, it's easy to trap in the local optimum; second, finding the best parameters in the larger range will affects the efficiency of classification and prediction. As the experimental results suggest, GA-SVM has a higher recognition rate.

Genetic algorithm based approach to investigate doped metal oxide materials: Application to lanthanide-doped ceria

NASA Astrophysics Data System (ADS)

Hooper, James; Ismail, Arif; Giorgi, Javier B.; Woo, Tom K.

2010-06-01

A genetic algorithm (GA)-inspired method to effectively map out low-energy configurations of doped metal oxide materials is presented. Specialized mating and mutation operations that do not alter the identity of the parent metal oxide have been incorporated to efficiently sample the metal dopant and oxygen vacancy sites. The search algorithms have been tested on lanthanide-doped ceria (L=Sm,Gd,Lu) with various dopant concentrations. Using both classical and first-principles density-functional-theory (DFT) potentials, we have shown the methodology reproduces the results of recent systematic searches of doped ceria at low concentrations (3.2% L2O3 ) and identifies low-energy structures of concentrated samarium-doped ceria (3.8% and 6.6% L2O3 ) which relate to the experimental and theoretical findings published thus far. We introduce a tandem classical/DFT GA algorithm in which an inexpensive classical potential is first used to generate a fit gene pool of structures to enhance the overall efficiency of the computationally demanding DFT-based GA search.

Non-equilibrium Green's function calculation of AlGaAs-well-based and GaSb-based terahertz quantum cascade laser structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yasuda, H., E-mail: yasuda@nict.go.jp; Hosako, I.

2015-03-16

We investigate the performance of terahertz quantum cascade lasers (THz-QCLs) based on Al{sub x}Ga{sub 1−x}As/Al{sub y}Ga{sub 1−y}As and GaSb/AlGaSb material systems to realize higher-temperature operation. Calculations with the non-equilibrium Green's function method reveal that the AlGaAs-well-based THz-QCLs do not show improved performance, mainly because of alloy scattering in the ternary compound semiconductor. The GaSb-based THz-QCLs offer clear advantages over GaAs-based THz-QCLs. Weaker longitudinal optical phonon–electron interaction in GaSb produces higher peaks in the spectral functions of the lasing levels, which enables more electrons to be accumulated in the upper lasing level.

An optimized BP neural network based on genetic algorithm for static decoupling of a six-axis force/torque sensor

NASA Astrophysics Data System (ADS)

Fu, Liyue; Song, Aiguo

2018-02-01

In order to improve the measurement precision of 6-axis force/torque sensor for robot, BP decoupling algorithm optimized by GA (GA-BP algorithm) is proposed in this paper. The weights and thresholds of a BP neural network with 6-10-6 topology are optimized by GA to develop decouple a six-axis force/torque sensor. By comparison with other traditional decoupling algorithm, calculating the pseudo-inverse matrix of calibration and classical BP algorithm, the decoupling results validate the good decoupling performance of GA-BP algorithm and the coupling errors are reduced.

DeMAID/GA USER'S GUIDE Design Manager's Aid for Intelligent Decomposition with a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Rogers, James L.

1996-01-01

Many companies are looking for new tools and techniques to aid a design manager in making decisions that can reduce the time and cost of a design cycle. One tool that is available to aid in this decision making process is the Design Manager's Aid for Intelligent Decomposition (DeMAID). Since the initial release of DEMAID in 1989, numerous enhancements have been added to aid the design manager in saving both cost and time in a design cycle. The key enhancement is a genetic algorithm (GA) and the enhanced version is called DeMAID/GA. The GA orders the sequence of design processes to minimize the cost and time to converge to a solution. These enhancements as well as the existing features of the original version of DEMAID are described. Two sample problems are used to show how these enhancements can be applied to improve the design cycle. This report serves as a user's guide for DeMAID/GA.

A High-Performance Genetic Algorithm: Using Traveling Salesman Problem as a Case

PubMed Central

Tsai, Chun-Wei; Tseng, Shih-Pang; Yang, Chu-Sing

2014-01-01

This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA. PMID:24892038

A high-performance genetic algorithm: using traveling salesman problem as a case.

PubMed

Tsai, Chun-Wei; Tseng, Shih-Pang; Chiang, Ming-Chao; Yang, Chu-Sing; Hong, Tzung-Pei

2014-01-01

This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

Combinatorial Multiobjective Optimization Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Crossley, William A.; Martin. Eric T.

2002-01-01

The research proposed in this document investigated multiobjective optimization approaches based upon the Genetic Algorithm (GA). Several versions of the GA have been adopted for multiobjective design, but, prior to this research, there had not been significant comparisons of the most popular strategies. The research effort first generalized the two-branch tournament genetic algorithm in to an N-branch genetic algorithm, then the N-branch GA was compared with a version of the popular Multi-Objective Genetic Algorithm (MOGA). Because the genetic algorithm is well suited to combinatorial (mixed discrete / continuous) optimization problems, the GA can be used in the conceptual phase of design to combine selection (discrete variable) and sizing (continuous variable) tasks. Using a multiobjective formulation for the design of a 50-passenger aircraft to meet the competing objectives of minimizing takeoff gross weight and minimizing trip time, the GA generated a range of tradeoff designs that illustrate which aircraft features change from a low-weight, slow trip-time aircraft design to a heavy-weight, short trip-time aircraft design. Given the objective formulation and analysis methods used, the results of this study identify where turboprop-powered aircraft and turbofan-powered aircraft become more desirable for the 50 seat passenger application. This aircraft design application also begins to suggest how a combinatorial multiobjective optimization technique could be used to assist in the design of morphing aircraft.

A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search

PubMed Central

Alba, Enrique; Leguizamón, Guillermo

2016-01-01

This work presents the results of a new methodology for hybridizing metaheuristics. By first locating the active components (parts) of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms. This gives a concrete way of constructing new techniques that contrasts the spread ad hoc way of hybridizing. In this paper, the enhanced algorithm is a Cellular Genetic Algorithm (cGA) which has been successfully used in the past to find solutions to such hard optimization problems. In order to extend and corroborate the use of active components as an emerging hybridization methodology, we propose here the use of active components taken from Scatter Search (SS) to improve cGA. The results obtained over a varied set of benchmarks are highly satisfactory in efficacy and efficiency when compared with a standard cGA. Moreover, the proposed hybrid approach (i.e., cGA+SS) has shown encouraging results with regard to earlier applications of our methodology. PMID:27403153

A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search.

PubMed

Villagra, Andrea; Alba, Enrique; Leguizamón, Guillermo

2016-01-01

This work presents the results of a new methodology for hybridizing metaheuristics. By first locating the active components (parts) of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms. This gives a concrete way of constructing new techniques that contrasts the spread ad hoc way of hybridizing. In this paper, the enhanced algorithm is a Cellular Genetic Algorithm (cGA) which has been successfully used in the past to find solutions to such hard optimization problems. In order to extend and corroborate the use of active components as an emerging hybridization methodology, we propose here the use of active components taken from Scatter Search (SS) to improve cGA. The results obtained over a varied set of benchmarks are highly satisfactory in efficacy and efficiency when compared with a standard cGA. Moreover, the proposed hybrid approach (i.e., cGA+SS) has shown encouraging results with regard to earlier applications of our methodology.

A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

PubMed

Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

2014-05-01

One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

PubMed Central

Mohamed, Ahmed F.; Elarini, Mahdi M.; Othman, Ahmed M.

2013-01-01

One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt. PMID:25685507

Fabrication and improved photoelectrochemical properties of a transferred GaN-based thin film with InGaN/GaN layers.

PubMed

Cao, Dezhong; Xiao, Hongdi; Gao, Qingxue; Yang, Xiaokun; Luan, Caina; Mao, Hongzhi; Liu, Jianqiang; Liu, Xiangdong

2017-08-17

Herein, a lift-off mesoporous GaN-based thin film, which consisted of a strong phase-separated InGaN/GaN layer and an n-GaN layer, was fabricated via an electrochemical etching method in a hydrofluoric acid (HF) solution for the first time and then transferred onto quartz or n-Si substrates, acting as photoanodes during photoelectrochemical (PEC) water splitting in a 1 M NaCl aqueous solution. Compared to the as-grown GaN-based film, the transferred GaN-based thin films possess higher and blue-shifted light emission, presumably resulting from an increase in the surface area and stress relaxation in the InGaN/GaN layer embedded on the mesoporous n-GaN. The properties such as (i) high photoconversion efficiency, (ii) low turn-on voltage (-0.79 V versus Ag/AgCl), and (iii) outstanding stability enable the transferred films to have excellent PEC water splitting ability. Furthermore, as compared to the film transferred onto the quartz substrate, the film transferred onto the n-Si substrate exhibits higher photoconversion efficiency (2.99% at -0.10 V) due to holes (h + ) in the mesoporous n-GaN layer that originate from the n-Si substrate.

Optimization of lamp arrangement in a closed-conduit UV reactor based on a genetic algorithm.

PubMed

Sultan, Tipu; Ahmad, Zeshan; Cho, Jinsoo

2016-01-01

The choice for the arrangement of the UV lamps in a closed-conduit ultraviolet (CCUV) reactor significantly affects the performance. However, a systematic methodology for the optimal lamp arrangement within the chamber of the CCUV reactor is not well established in the literature. In this research work, we propose a viable systematic methodology for the lamp arrangement based on a genetic algorithm (GA). In addition, we analyze the impacts of the diameter, angle, and symmetry of the lamp arrangement on the reduction equivalent dose (RED). The results are compared based on the simulated RED values and evaluated using the computational fluid dynamics simulations software ANSYS FLUENT. The fluence rate was calculated using commercial software UVCalc3D, and the GA-based lamp arrangement optimization was achieved using MATLAB. The simulation results provide detailed information about the GA-based methodology for the lamp arrangement, the pathogen transport, and the simulated RED values. A significant increase in the RED values was achieved by using the GA-based lamp arrangement methodology. This increase in RED value was highest for the asymmetric lamp arrangement within the chamber of the CCUV reactor. These results demonstrate that the proposed GA-based methodology for symmetric and asymmetric lamp arrangement provides a viable technical solution to the design and optimization of the CCUV reactor.

Subpixel displacement measurement method based on the combination of particle swarm optimization and gradient algorithm

NASA Astrophysics Data System (ADS)

Guang, Chen; Qibo, Feng; Keqin, Ding; Zhan, Gao

2017-10-01

A subpixel displacement measurement method based on the combination of particle swarm optimization (PSO) and gradient algorithm (GA) was proposed for accuracy and speed optimization in GA, which is a subpixel displacement measurement method better applied in engineering practice. An initial integer-pixel value was obtained according to the global searching ability of PSO, and then gradient operators were adopted for a subpixel displacement search. A comparison was made between this method and GA by simulated speckle images and rigid-body displacement in metal specimens. The results showed that the computational accuracy of the combination of PSO and GA method reached 0.1 pixel in the simulated speckle images, or even 0.01 pixels in the metal specimen. Also, computational efficiency and the antinoise performance of the improved method were markedly enhanced.

Genetics algorithm optimization of DWT-DCT based image Watermarking

NASA Astrophysics Data System (ADS)

Budiman, Gelar; Novamizanti, Ledya; Iwut, Iwan

2017-01-01

Data hiding in an image content is mandatory for setting the ownership of the image. Two dimensions discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed as transform method in this paper. First, the host image in RGB color space is converted to selected color space. We also can select the layer where the watermark is embedded. Next, 2D-DWT transforms the selected layer obtaining 4 subband. We select only one subband. And then block-based 2D-DCT transforms the selected subband. Binary-based watermark is embedded on the AC coefficients of each block after zigzag movement and range based pixel selection. Delta parameter replacing pixels in each range represents embedded bit. +Delta represents bit “1” and -delta represents bit “0”. Several parameters to be optimized by Genetics Algorithm (GA) are selected color space, layer, selected subband of DWT decomposition, block size, embedding range, and delta. The result of simulation performs that GA is able to determine the exact parameters obtaining optimum imperceptibility and robustness, in any watermarked image condition, either it is not attacked or attacked. DWT process in DCT based image watermarking optimized by GA has improved the performance of image watermarking. By five attacks: JPEG 50%, resize 50%, histogram equalization, salt-pepper and additive noise with variance 0.01, robustness in the proposed method has reached perfect watermark quality with BER=0. And the watermarked image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PubMed

Ma, Changxi; Hao, Wei; Pan, Fuquan; Xiang, Wang

2018-01-01

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

A Novel Algorithm Combining Finite State Method and Genetic Algorithm for Solving Crude Oil Scheduling Problem

PubMed Central

Duan, Qian-Qian; Yang, Gen-Ke; Pan, Chang-Chun

2014-01-01

A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The heuristic returned by the FSM can guide the GA algorithm towards good solutions. The idea behind this is that we can generate promising substructure or partial solution by using FSM. Furthermore, the FSM can guarantee that the entire solution space is uniformly covered. Therefore, the combination of the two algorithms has better global performance than the existing GA or FSM which is operated individually. Finally, a real-life crude oil scheduling problem from the literature is used for conducting simulation. The experimental results validate that the proposed method outperforms the state-of-art GA method. PMID:24772031

Polarization-Engineered Ga-Face GaN-Based Heterostructures for Normally-Off Heterostructure Field-Effect Transistors

NASA Astrophysics Data System (ADS)

Kim, Hyeongnam; Nath, Digbijoy; Rajan, Siddharth; Lu, Wu

2013-01-01

Polarization-engineered Ga-face GaN-based heterostructures with a GaN cap layer and an AlGaN/ p-GaN back barrier have been designed for normally-off field-effect transistors (FETs). The simulation results show that an unintentionally doped GaN cap and p-GaN layer in the buffer primarily deplete electrons in the channel and the Al0.2Ga0.8N back barrier helps to pinch off the channel. Experimentally, we have demonstrated a normally-off GaN-based field-effect transistor on the designed GaN cap/Al0.3Ga0.7N/GaN channel/Al0.2Ga0.8N/ p-GaN/GaN heterostructure. A positive threshold voltage of 0.2 V and maximum transconductance of 2.6 mS/mm were achieved for 80- μm-long gate devices. The device fabrication process does not require a dry etching process for gate recessing, while highly selective etching of the GaN cap against a very thin Al0.3GaN0.7N top barrier has to be performed to create a two-dimensional electron gas for both the ohmic and access regions. A self-aligned, selective etch of the GaN cap in the access region is introduced, using the gate metal as an etch mask. The absence of gate recess etching is promising for uniform and repeatable threshold voltage control in normally-off AlGaN/GaN heterostructure FETs for power switching applications.

GaN based nanorods for solid state lighting

NASA Astrophysics Data System (ADS)

Li, Shunfeng; Waag, Andreas

2012-04-01

In recent years, GaN nanorods are emerging as a very promising novel route toward devices for nano-optoelectronics and nano-photonics. In particular, core-shell light emitting devices are thought to be a breakthrough development in solid state lighting, nanorod based LEDs have many potential advantages as compared to their 2 D thin film counterparts. In this paper, we review the recent developments of GaN nanorod growth, characterization, and related device applications based on GaN nanorods. The initial work on GaN nanorod growth focused on catalyst-assisted and catalyst-free statistical growth. The growth condition and growth mechanisms were extensively investigated and discussed. Doping of GaN nanorods, especially p-doping, was found to significantly influence the morphology of GaN nanorods. The large surface of 3 D GaN nanorods induces new optical and electrical properties, which normally can be neglected in layered structures. Recently, more controlled selective area growth of GaN nanorods was realized using patterned substrates both by metalorganic chemical vapor deposition (MOCVD) and by molecular beam epitaxy (MBE). Advanced structures, for example, photonic crystals and DBRs are meanwhile integrated in GaN nanorod structures. Based on the work of growth and characterization of GaN nanorods, GaN nanoLEDs were reported by several groups with different growth and processing methods. Core/shell nanoLED structures were also demonstrated, which could be potentially useful for future high efficient LED structures. In this paper, we will discuss recent developments in GaN nanorod technology, focusing on the potential advantages, but also discussing problems and open questions, which may impose obstacles during the future development of a GaN nanorod based LED technology.

An FBG acoustic emission source locating system based on PHAT and GA

NASA Astrophysics Data System (ADS)

Shen, Jing-shi; Zeng, Xiao-dong; Li, Wei; Jiang, Ming-shun

2017-09-01

Using the acoustic emission locating technology to monitor the health of the structure is important for ensuring the continuous and healthy operation of the complex engineering structures and large mechanical equipment. In this paper, four fiber Bragg grating (FBG) sensors are used to establish the sensor array to locate the acoustic emission source. Firstly, the nonlinear locating equations are established based on the principle of acoustic emission, and the solution of these equations is transformed into an optimization problem. Secondly, time difference extraction algorithm based on the phase transform (PHAT) weighted generalized cross correlation provides the necessary conditions for the accurate localization. Finally, the genetic algorithm (GA) is used to solve the optimization model. In this paper, twenty points are tested in the marble plate surface, and the results show that the absolute locating error is within the range of 10 mm, which proves the accuracy of this locating method.

Scanning microwave microscopy applied to semiconducting GaAs structures

NASA Astrophysics Data System (ADS)

Buchter, Arne; Hoffmann, Johannes; Delvallée, Alexandra; Brinciotti, Enrico; Hapiuk, Dimitri; Licitra, Christophe; Louarn, Kevin; Arnoult, Alexandre; Almuneau, Guilhem; Piquemal, François; Zeier, Markus; Kienberger, Ferry

2018-02-01

A calibration algorithm based on one-port vector network analyzer (VNA) calibration for scanning microwave microscopes (SMMs) is presented and used to extract quantitative carrier densities from a semiconducting n-doped GaAs multilayer sample. This robust and versatile algorithm is instrument and frequency independent, as we demonstrate by analyzing experimental data from two different, cantilever- and tuning fork-based, microscope setups operating in a wide frequency range up to 27.5 GHz. To benchmark the SMM results, comparison with secondary ion mass spectrometry is undertaken. Furthermore, we show SMM data on a GaAs p-n junction distinguishing p- and n-doped layers.

Self-consistent optimization of [111]-AlGaInAs/InP MQWs structures lasing at 1.55 μm by a genetic algorithm

NASA Astrophysics Data System (ADS)

Saidi, Hosni; Msahli, Melek; Ben Dhafer, Rania; Ridene, Said

2017-12-01

Band structure and optical gain properties of [111]-oriented AlGaInAs/AlGaInAs-delta-InGaAs multi-quantum wells, subjected to piezoelectric field, for the near-infrared lasers diodes applications was proposed and investigated in this paper. By using genetic algorithm based on optimization technique we demonstrate that the structural parameters can be conveniently optimized to achieve high-efficiency laser diode performance at room temperature. In this work, significant optical gain for the wished emission wavelength at 1.55 μm and low threshold injection current are the optimization target. The end result of this optimization is a laser diode based on InP substrate using quaternary compound material of AlGaInAs in both quantum wells and barriers with different composition. It has been shown that the transverse electric polarized optical gain which reaches 3500 cm-1 may be acquired for λ = 1.55 μm with a threshold carrier density Nth≈1.31018cm-3, which is very promising to serve as an alternative active region for high-efficiency near-infrared lasers. Finally, from the design presented here, we show that it is possible to apply this technique to a different III-V compound semiconductors and wavelength ranging from deep-ultra-violet to far infrared.

GA-based fuzzy reinforcement learning for control of a magnetic bearing system.

PubMed

Lin, C T; Jou, C P

2000-01-01

This paper proposes a TD (temporal difference) and GA (genetic algorithm)-based reinforcement (TDGAR) learning method and applies it to the control of a real magnetic bearing system. The TDGAR learning scheme is a new hybrid GA, which integrates the TD prediction method and the GA to perform the reinforcement learning task. The TDGAR learning system is composed of two integrated feedforward networks. One neural network acts as a critic network to guide the learning of the other network (the action network) which determines the outputs (actions) of the TDGAR learning system. The action network can be a normal neural network or a neural fuzzy network. Using the TD prediction method, the critic network can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the action network. The action network uses the GA to adapt itself according to the internal reinforcement signal. The key concept of the TDGAR learning scheme is to formulate the internal reinforcement signal as the fitness function for the GA such that the GA can evaluate the candidate solutions (chromosomes) regularly, even during periods without external feedback from the environment. This enables the GA to proceed to new generations regularly without waiting for the arrival of the external reinforcement signal. This can usually accelerate the GA learning since a reinforcement signal may only be available at a time long after a sequence of actions has occurred in the reinforcement learning problem. The proposed TDGAR learning system has been used to control an active magnetic bearing (AMB) system in practice. A systematic design procedure is developed to achieve successful integration of all the subsystems including magnetic suspension, mechanical structure, and controller training. The results show that the TDGAR learning scheme can successfully find a neural controller or a neural fuzzy controller for a self-designed magnetic bearing system.

Thermodynamic properties of gadolinium in Ga-Sn and Ga-Zn eutectic based alloys

NASA Astrophysics Data System (ADS)

Maltsev, Dmitry S.; Volkovich, Vladimir A.; Yamshchikov, Leonid F.; Chukin, Andrey V.

2016-09-01

Thermodynamic properties of gadolinium in Ga-Sn and Ga-Zn eutectic based alloys were studied. Temperature dependences of gadolinium activity in the studied alloys were determined at 573-1073 K employing the EMF method. Solubility of gadolinium in the Ga-Sn and Ga-Zn alloys was measured at 462-1073 K using IMCs sedimentation method. Activity coefficients as well as partial and excess thermodynamic functions of gadolinium in the studied alloys were calculated on the basis of the obtained experimental data.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared

Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves

NASA Technical Reports Server (NTRS)

Tarano, Ana; Mathias, Donovan; Wheeler, Lorien; Close, Sigrid

2018-01-01

An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by using an analytic fragment-cloud model (FCM) in conjunction with a Genetic Algorithm (GA). This optimization technique is used to inversely solve for the asteroid's entry properties, such as diameter, density, strength, velocity, entry angle, and strength scaling, from simulations using FCM. The previous parameters' fitness evaluation involves minimizing error to ascertain the best match between the physics-based calculated energy deposition and the observed meteors. This steady-state GA provided sets of solutions agreeing with literature, such as the meteor from Chelyabinsk, Russia in 2013 and Tagish Lake, Canada in 2000, which were used as case studies in order to validate the optimization routine. The assisted exploration and exploitation of this multi-dimensional search space enables inference and uncertainty analysis that can inform studies of near-Earth asteroids and consequently improve risk assessment.

Optical characteristics of p-type GaAs-based semiconductors towards applications in photoemission infrared detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lao, Y. F.; Perera, A. G. U., E-mail: uperera@gsu.edu; Center for Nano-Optics

2016-03-14

Free-carrier effects in a p-type semiconductor including the intra-valence-band and inter-valence-band optical transitions are primarily responsible for its optical characteristics in infrared. Attention has been paid to the inter-valence-band transitions for the development of internal photoemission (IPE) mid-wave infrared (MWIR) photodetectors. The hole transition from the heavy-hole (HH) band to the spin-orbit split-off (SO) band has demonstrated potential applications for 3–5 μm detection without the need of cooling. However, the forbidden SO-HH transition at the Γ point (corresponding to a transition energy Δ{sub 0}, which is the split-off gap between the HH and SO bands) creates a sharp drop around 3.6 μmmore » in the spectral response of p-type GaAs/AlGaAs detectors. Here, we report a study on the optical characteristics of p-type GaAs-based semiconductors, including compressively strained InGaAs and GaAsSb, and a dilute magnetic semiconductor, GaMnAs. A model-independent fitting algorithm was used to derive the dielectric function from experimental reflection and transmission spectra. Results show that distinct absorption dip at Δ{sub 0} is observable in p-type InGaAs and GaAsSb, while GaMnAs displays enhanced absorption without degradation around Δ{sub 0}. This implies the promise of using GaMnAs to develop MWIR IPE detectors. Discussions on the optical characteristics correlating with the valence-band structure and free-hole effects are presented.« less

Warpage improvement on wheel caster by optimizing the process parameters using genetic algorithm (GA)

NASA Astrophysics Data System (ADS)

Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

In injection moulding process, the defects will always encountered and affected the final product shape and functionality. This study is concerning on minimizing warpage and optimizing the process parameter of injection moulding part. Apart from eliminating product wastes, this project also giving out best recommended parameters setting. This research studied on five parameters. The optimization showed that warpage have been improved 42.64% from 0.6524 mm to 0.30879 mm in Autodesk Moldflow Insight (AMI) simulation result and Genetic Algorithm (GA) respectively.

Design of the smart home system based on the optimal routing algorithm and ZigBee network.

PubMed

Jiang, Dengying; Yu, Ling; Wang, Fei; Xie, Xiaoxia; Yu, Yongsheng

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system.

Design of the smart home system based on the optimal routing algorithm and ZigBee network

PubMed Central

Xie, Xiaoxia

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system. PMID:29131868

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm.

PubMed

Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm

PubMed Central

Liang, Lihua; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller. PMID:29709008

Comparative investigation of InGaP/GaAs/GaAsBi and InGaP/GaAs heterojunction bipolar transistors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Yi-Chen; Tsai, Jung-Hui, E-mail: jhtsai@nknucc.nknu.edu.tw; Chiang, Te-Kuang

2015-10-15

In this article the characteristics of In{sub 0.49}Ga{sub 0.51}P/GaAs/GaAs{sub 0.975}Bi{sub 0.025} and In{sub 0.49}Ga{sub 0.51}P/GaAs heterojunction bipolar transistor (HBTs) are demonstrated and compared by two-dimensional simulated analysis. As compared to the traditional InGaP/GaAs HBT, the studied InGaP/GaAs/GaAsBi HBT exhibits a higher collector current, a lower base-emitter (B–E) turn-on voltage, and a relatively lower collector-emitter offset voltage of only 7 mV. Because the more electrons stored in the base is further increased in the InGaP/GaAs/GaAsBi HBT, it introduces the collector current to increase and the B–E turn-on voltage to decrease for low input power applications. However, the current gain is slightlymore » smaller than the traditional InGaP/GaAs HBT attributed to the increase of base current for the minority carriers stored in the GaAsBi base.« less

The reconstruction algorithm used for [68Ga]PSMA-HBED-CC PET/CT reconstruction significantly influences the number of detected lymph node metastases and coeliac ganglia.

PubMed

Krohn, Thomas; Birmes, Anita; Winz, Oliver H; Drude, Natascha I; Mottaghy, Felix M; Behrendt, Florian F; Verburg, Frederik A

2017-04-01

To investigate whether the numbers of lymph node metastases and coeliac ganglia delineated on [ 68 Ga]PSMA-HBED-CC PET/CT scans differ among datasets generated using different reconstruction algorithms. Data were constructed using the BLOB-OS-TF, BLOB-OS and 3D-RAMLA algorithms. All reconstructions were assessed by two nuclear medicine physicians for the number of pelvic/paraaortal lymph node metastases as well the number of coeliac ganglia. Standardized uptake values (SUV) were also calculated in different regions. At least one [ 68 Ga]PSMA-HBED-CC PET/CT-positive pelvic or paraaortal lymph node metastasis was found in 49 and 35 patients using the BLOB-OS-TF algorithm, in 42 and 33 patients using the BLOB-OS algorithm, and in 41 and 31 patients using the 3D-RAMLA algorithm, respectively, and a positive ganglion was found in 92, 59 and 24 of 100 patients using the three algorithms, respectively. Quantitatively, the SUVmean and SUVmax were significantly higher with the BLOB-OS algorithm than with either the BLOB-OS-TF or the 3D-RAMLA algorithm in all measured regions (p < 0.001 for all comparisons). The differences between the SUVs with the BLOB-OS-TF- and 3D-RAMLA algorithms were not significant in the aorta (SUVmean, p = 0.93; SUVmax, p = 0.97) but were significant in all other regions (p < 0.001 in all cases). The SUVmean ganglion/gluteus ratio was significantly higher with the BLOB-OS-TF algorithm than with either the BLOB-OS or the 3D-RAMLA algorithm and was significantly higher with the BLOB-OS than with the 3D-RAMLA algorithm (p < 0.001 in all cases). The results of [ 68 Ga]PSMA-HBED-CC PET/CT are affected by the reconstruction algorithm used. The highest number of lesions and physiological structures will be visualized using a modern algorithm employing time-of-flight information.

Optimal structural design of the midship of a VLCC based on the strategy integrating SVM and GA

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2012-03-01

In this paper a hybrid process of modeling and optimization, which integrates a support vector machine (SVM) and genetic algorithm (GA), was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier (VLCC) ship was carried out according to the direct strength assessment method in common structural rules (CSR), which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.

Development of GaN-based microchemical sensor nodes

NASA Technical Reports Server (NTRS)

Prokopuk, Nicholas; Son, Kyung-Ah; George, Thomas; Moon, Jeong S.

2005-01-01

Sensors based III-N technology are gaining significant interest due to their potential for monolithic integration of RF transceivers and light sources and the capability of high temperature operations. We are developing a GaN-based micro chemical sensor node for remote detection of chemical toxins, and present electrical responses of AlGaN/GaN HEMT (High Electron Mobility Transistor) sensors to chemical toxins as well as other common gases.

Effects of GaN/AlGaN/Sputtered AlN nucleation layers on performance of GaN-based ultraviolet light-emitting diodes

PubMed Central

Hu, Hongpo; Zhou, Shengjun; Liu, Xingtong; Gao, Yilin; Gui, Chengqun; Liu, Sheng

2017-01-01

We report on the demonstration of GaN-based ultraviolet light-emitting diodes (UV LEDs) emitting at 375 nm grown on patterned sapphire substrate (PSS) with in-situ low temperature GaN/AlGaN nucleation layers (NLs) and ex-situ sputtered AlN NL. The threading dislocation (TD) densities in GaN-based UV LEDs with GaN/AlGaN/sputtered AlN NLs were determined by high-resolution X-ray diffraction (XRD) and cross-sectional transmission electron microscopy (TEM), which revealed that the TD density in UV LED with AlGaN NL was the highest, whereas that in UV LED with sputtered AlN NL was the lowest. The light output power (LOP) of UV LED with AlGaN NL was 18.2% higher than that of UV LED with GaN NL owing to a decrease in the absorption of 375 nm UV light in the AlGaN NL with a larger bandgap. Using a sputtered AlN NL instead of the AlGaN NL, the LOP of UV LED was further enhanced by 11.3%, which is attributed to reduced TD density in InGaN/AlInGaN active region. In the sputtered AlN thickness range of 10–25 nm, the LOP of UV LED with 15-nm-thick sputtered AlN NL was the highest, revealing that optimum thickness of the sputtered AlN NL is around 15 nm. PMID:28294166

Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR

PubMed Central

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms. PMID:28979308

Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR.

PubMed

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms.

PID controller tuning using metaheuristic optimization algorithms for benchmark problems

NASA Astrophysics Data System (ADS)

Gholap, Vishal; Naik Dessai, Chaitali; Bagyaveereswaran, V.

2017-11-01

This paper contributes to find the optimal PID controller parameters using particle swarm optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm. The algorithms were developed through simulation of chemical process and electrical system and the PID controller is tuned. Here, two different fitness functions such as Integral Time Absolute Error and Time domain Specifications were chosen and applied on PSO, GA and SA while tuning the controller. The proposed Algorithms are implemented on two benchmark problems of coupled tank system and DC motor. Finally, comparative study has been done with different algorithms based on best cost, number of iterations and different objective functions. The closed loop process response for each set of tuned parameters is plotted for each system with each fitness function.

An image segmentation method based on fuzzy C-means clustering and Cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Wang, Mingwei; Wan, Youchuan; Gao, Xianjun; Ye, Zhiwei; Chen, Maolin

2018-04-01

Image segmentation is a significant step in image analysis and machine vision. Many approaches have been presented in this topic; among them, fuzzy C-means (FCM) clustering is one of the most widely used methods for its high efficiency and ambiguity of images. However, the success of FCM could not be guaranteed because it easily traps into local optimal solution. Cuckoo search (CS) is a novel evolutionary algorithm, which has been tested on some optimization problems and proved to be high-efficiency. Therefore, a new segmentation technique using FCM and blending of CS algorithm is put forward in the paper. Further, the proposed method has been measured on several images and compared with other existing FCM techniques such as genetic algorithm (GA) based FCM and particle swarm optimization (PSO) based FCM in terms of fitness value. Experimental results indicate that the proposed method is robust, adaptive and exhibits the better performance than other methods involved in the paper.

GaAs-based micro/nanomechanical resonators

NASA Astrophysics Data System (ADS)

Yamaguchi, Hiroshi

2017-10-01

Micro/nanomechanical resonators have been extensively studied both for device applications, such as high-performance sensors and high-frequency devices, and for fundamental science, such as quantum physics in macroscopic objects. The advantages of GaAs-based semiconductor heterostructures include improved mechanical properties through strain engineering, highly controllable piezoelectric transduction, carrier-mediated optomechanical coupling, and hybridization with quantum low-dimensional structures. This article reviews our recent activities, as well as those of other groups, on the physics and applications of mechanical resonators fabricated using GaAs-based heterostructures.

Rayleigh wave dispersion curve inversion by using particle swarm optimization and genetic algorithm

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Zor, Ekrem; Karaman, Abdullah

2017-04-01

Inversion of surface wave dispersion curves with its highly nonlinear nature has some difficulties using traditional linear inverse methods due to the need and strong dependence to the initial model, possibility of trapping in local minima and evaluation of partial derivatives. There are some modern global optimization methods to overcome of these difficulties in surface wave analysis such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). GA is based on biologic evolution consisting reproduction, crossover and mutation operations, while PSO algorithm developed after GA is inspired from the social behaviour of birds or fish of swarms. Utility of these methods require plausible convergence rate, acceptable relative error and optimum computation cost that are important for modelling studies. Even though PSO and GA processes are similar in appearence, the cross-over operation in GA is not used in PSO and the mutation operation is a stochastic process for changing the genes within chromosomes in GA. Unlike GA, the particles in PSO algorithm changes their position with logical velocities according to particle's own experience and swarm's experience. In this study, we applied PSO algorithm to estimate S wave velocities and thicknesses of the layered earth model by using Rayleigh wave dispersion curve and also compared these results with GA and we emphasize on the advantage of using PSO algorithm for geophysical modelling studies considering its rapid convergence, low misfit error and computation cost.

Decision Support System for Coastal Protection Layout Design (DSS4CPD) Using Genetic Algorithm (ga) and Multicriteria Analysis (mca)

NASA Astrophysics Data System (ADS)

Jinchai, Phinai; Chittaladakorn, Suwatana

This research has its objective to develop the decision support system on GIS to be used in the coastal erosion protection management. The developed model in this research is called Decision Support System for Coastal Protection Layout Design (DSS4CPD). It has created both for systematic protection and solution measures to the problem by using Genetic Algorithm (GA) and Multicriteria Analysis (MCA) for finding the coastal structure layout optimal solution. In this research, three types of coastal structures were used as structure alternatives for the layout, which are seawall, breakwater, and groin. The coastal area in Nakornsrithammaraj, Thailand was used as the case study. The studied result has found the appropriate position of coastal structures considering the suitable rock size relied on the wave energy, and the appropriate coastal structure position based on the wave breaking line. Using GA and MCA in DSS4CPD, it found the best layout in this project. This DSS4CPD will be used by the authorized decision makers to find the most suitable erosion problem solution.

Near ultraviolet InGaN/AlGaN-based light-emitting diodes with highly reflective tin-doped indium oxide/Al-based reflectors.

PubMed

Choi, Chang-Hoon; Han, Jaecheon; Park, Jae-Seong; Seong, Tae-Yeon

2013-11-04

The enhanced light output power of a InGaN/AlGaN-based light-emitting diodes (LEDs) using three different types of highly reflective Sn-doped indium oxide (ITO)/Al-based p-type reflectors, namely, ITO/Al, Cu-doped indium oxide (CIO)/s-ITO(sputtered)/Al, and Ag nano-dots(n-Ag)/CIO/s-ITO/Al, is presented. The ITO/Al-based reflectors exhibit lower reflectance (76 - 84% at 365 nm) than Al only reflector (91.1%). However, unlike Al only n-type contact, the ITO/Al-based contacts to p-GaN show good ohmic characteristics. Near-UV (365 nm) InGaN/AlGaN-based LEDs with ITO/Al, CIO/s-ITO/Al, and n-Ag/CIO/s-ITO/Al reflectors exhibit forward-bias voltages of 3.55, 3.48, and 3.34 V at 20 mA, respectively. The LEDs with the ITO/Al and CIO/s-ITO/Al reflectors exhibit 9.5% and 13.5% higher light output power (at 20 mA), respectively, than the LEDs with the n-Ag/CIO/s-ITO/Al reflector. The improved performance of near UV LEDs is attributed to the high reflectance and low contact resistivity of the ITO/Al-based reflectors, which are better than those of conventional Al-based reflectors.

Ultrafast Photodetection in the Quantum Wells of Single AlGaAs/GaAs-Based Nanowires.

PubMed

Erhard, N; Zenger, S; Morkötter, S; Rudolph, D; Weiss, M; Krenner, H J; Karl, H; Abstreiter, G; Finley, J J; Koblmüller, G; Holleitner, A W

2015-10-14

We investigate the ultrafast optoelectronic properties of single Al0.3Ga0.7As/GaAs core-shell nanowires. The nanowires contain GaAs-based quantum wells. For a resonant excitation of the quantum wells, we find a picosecond photocurrent which is consistent with an ultrafast lateral expansion of the photogenerated charge carriers. This Dember-effect does not occur for an excitation of the GaAs-based core of the nanowires. Instead, the core exhibits an ultrafast displacement current and a photothermoelectric current at the metal Schottky contacts. Our results uncover the optoelectronic dynamics in semiconductor core-shell nanowires comprising quantum wells, and they demonstrate the possibility to use the low-dimensional quantum well states therein for ultrafast photoswitches and photodetectors.

Adaptive process control using fuzzy logic and genetic algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Genetic algorithm with maximum-minimum crossover (GA-MMC) applied in optimization of radiation pattern control of phased-array radars for rocket tracking systems.

PubMed

Silva, Leonardo W T; Barros, Vitor F; Silva, Sandro G

2014-08-18

In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence.

Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) Applied in Optimization of Radiation Pattern Control of Phased-Array Radars for Rocket Tracking Systems

PubMed Central

Silva, Leonardo W. T.; Barros, Vitor F.; Silva, Sandro G.

2014-01-01

In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence. PMID:25196013

Application of Shuffled Frog Leaping Algorithm and Genetic Algorithm for the Optimization of Urban Stormwater Drainage

NASA Astrophysics Data System (ADS)

Kumar, S.; Kaushal, D. R.; Gosain, A. K.

2017-12-01

Urban hydrology will have an increasing role to play in the sustainability of human settlements. Expansion of urban areas brings significant changes in physical characteristics of landuse. Problems with administration of urban flooding have their roots in concentration of population within a relatively small area. As watersheds are urbanized, infiltration decreases, pattern of surface runoff is changed generating high peak flows, large runoff volumes from urban areas. Conceptual rainfall-runoff models have become a foremost tool for predicting surface runoff and flood forecasting. Manual calibration is often time consuming and tedious because of the involved subjectivity, which makes automatic approach more preferable. The calibration of parameters usually includes numerous criteria for evaluating the performances with respect to the observed data. Moreover, derivation of objective function assosciat6ed with the calibration of model parameters is quite challenging. Various studies dealing with optimization methods has steered the embracement of evolution based optimization algorithms. In this paper, a systematic comparison of two evolutionary approaches to multi-objective optimization namely shuffled frog leaping algorithm (SFLA) and genetic algorithms (GA) is done. SFLA is a cooperative search metaphor, stimulated by natural memetics based on the population while, GA is based on principle of survival of the fittest and natural evolution. SFLA and GA has been employed for optimizing the major parameters i.e. width, imperviousness, Manning's coefficient and depression storage for the highly urbanized catchment of Delhi, India. The study summarizes the auto-tuning of a widely used storm water management model (SWMM), by internal coupling of SWMM with SFLA and GA separately. The values of statistical parameters such as, Nash-Sutcliffe efficiency (NSE) and Percent Bias (PBIAS) were found to lie within the acceptable limit, indicating reasonably good model performance

Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.

PubMed

Ullah, Azmat; Malik, Suheel Abdullah; Alimgeer, Khurram Saleem

2018-01-01

In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.

Pruning Neural Networks with Distribution Estimation Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cantu-Paz, E

2003-01-15

This paper describes the application of four evolutionary algorithms to the pruning of neural networks used in classification problems. Besides of a simple genetic algorithm (GA), the paper considers three distribution estimation algorithms (DEAs): a compact GA, an extended compact GA, and the Bayesian Optimization Algorithm. The objective is to determine if the DEAs present advantages over the simple GA in terms of accuracy or speed in this problem. The experiments used a feed forward neural network trained with standard back propagation and public-domain and artificial data sets. The pruned networks seemed to have better or equal accuracy than themore » original fully-connected networks. Only in a few cases, pruning resulted in less accurate networks. We found few differences in the accuracy of the networks pruned by the four EAs, but found important differences in the execution time. The results suggest that a simple GA with a small population might be the best algorithm for pruning networks on the data sets we tested.« less

Dominant takeover regimes for genetic algorithms

NASA Technical Reports Server (NTRS)

Noever, David; Baskaran, Subbiah

1995-01-01

The genetic algorithm (GA) is a machine-based optimization routine which connects evolutionary learning to natural genetic laws. The present work addresses the problem of obtaining the dominant takeover regimes in the GA dynamics. Estimated GA run times are computed for slow and fast convergence in the limits of high and low fitness ratios. Using Euler's device for obtaining partial sums in closed forms, the result relaxes the previously held requirements for long time limits. Analytical solution reveal that appropriately accelerated regimes can mark the ascendancy of the most fit solution. In virtually all cases, the weak (logarithmic) dependence of convergence time on problem size demonstrates the potential for the GA to solve large N-P complete problems.

Development of GaN-based micro chemical sensor nodes

NASA Technical Reports Server (NTRS)

Son, Kyung-ah; Prokopuk, Nicholas; George, Thomas; Moon, Jeong S.

2005-01-01

Sensors based on III-N technology are gaining significant interest due to their potential for monolithic integration of RF transceivers and light sources and the capability of high temperature operations. We are developing a GaN-based micro chemical sensor node for remote detection of chemical toxins, and present electrical responses of AlGaN/GaN HEMT (High Electron Mobility Transistor) sensors to chemical toxins as well as other common gases.

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

PubMed

Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

2018-02-01

Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to

Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

NASA Technical Reports Server (NTRS)

Taylor, Jaime; Rakoczy, John; Steincamp, James

2003-01-01

Phase retrieval requires calculation of the real-valued phase of the pupil fimction from the image intensity distribution and characteristics of an optical system. Genetic 'algorithms were used to solve two one-dimensional phase retrieval problem. A GA successfully estimated the coefficients of a polynomial expansion of the phase when the number of coefficients was correctly specified. A GA also successfully estimated the multiple p h e s of a segmented optical system analogous to the seven-mirror Systematic Image-Based Optical Alignment (SIBOA) testbed located at NASA s Marshall Space Flight Center. The SIBOA testbed was developed to investigate phase retrieval techniques. Tiphilt and piston motions of the mirrors accomplish phase corrections. A constant phase over each mirror can be achieved by an independent tip/tilt correction: the phase Conection term can then be factored out of the Discrete Fourier Tranform (DFT), greatly reducing computations.

Selective epitaxial growth of monolithically integrated GaN-based light emitting diodes with AlGaN/GaN driving transistors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Zhaojun; Ma, Jun; Huang, Tongde

2014-03-03

In this Letter, we report selective epitaxial growth of monolithically integrated GaN-based light emitting diodes (LEDs) with AlGaN/GaN high-electron-mobility transistor (HEMT) drivers. A comparison of two integration schemes, selective epitaxial removal (SER), and selective epitaxial growth (SEG) was made. We found the SER resulted in serious degradation of the underlying LEDs in a HEMT-on-LED structure due to damage of the p-GaN surface. The problem was circumvented using the SEG that avoided plasma etching and minimized device degradation. The integrated HEMT-LEDs by SEG exhibited comparable characteristics as unintegrated devices and emitted modulated blue light by gate biasing.

Retrieval of Dry Snow Parameters from Radiometric Data Using a Dense Medium Model and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Tedesco, Marco; Kim, Edward J.

2005-01-01

In this paper, GA-based techniques are used to invert the equations of an electromagnetic model based on Dense Medium Radiative Transfer Theory (DMRT) under the Quasi Crystalline Approximation with Coherent Potential to retrieve snow depth, mean grain size and fractional volume from microwave brightness temperatures. The technique is initially tested on both noisy and not-noisy simulated data. During this phase, different configurations of genetic algorithm parameters are considered to quantify how their change can affect the algorithm performance. A configuration of GA parameters is then selected and the algorithm is applied to experimental data acquired during the NASA Cold Land Process Experiment. Snow parameters retrieved with the GA-DMRT technique are then compared with snow parameters measured on field.

Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B.

PubMed

Chen, Xiao Yu; Ma, Li Zhuang; Chu, Na; Zhou, Min; Hu, Yiyang

2013-01-01

Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.

Genetic algorithm based active vibration control for a moving flexible smart beam driven by a pneumatic rod cylinder

NASA Astrophysics Data System (ADS)

Qiu, Zhi-cheng; Shi, Ming-li; Wang, Bin; Xie, Zhuo-wei

2012-05-01

A rod cylinder based pneumatic driving scheme is proposed to suppress the vibration of a flexible smart beam. Pulse code modulation (PCM) method is employed to control the motion of the cylinder's piston rod for simultaneous positioning and vibration suppression. Firstly, the system dynamics model is derived using Hamilton principle. Its standard state-space representation is obtained for characteristic analysis, controller design, and simulation. Secondly, a genetic algorithm (GA) is applied to optimize and tune the control gain parameters adaptively based on the specific performance index. Numerical simulations are performed on the pneumatic driving elastic beam system, using the established model and controller with tuned gains by GA optimization process. Finally, an experimental setup for the flexible beam driven by a pneumatic rod cylinder is constructed. Experiments for suppressing vibrations of the flexible beam are conducted. Theoretical analysis, numerical simulation and experimental results demonstrate that the proposed pneumatic drive scheme and the adopted control algorithms are feasible. The large amplitude vibration of the first bending mode can be suppressed effectively.

Real coded genetic algorithm for fuzzy time series prediction

NASA Astrophysics Data System (ADS)

Jain, Shilpa; Bisht, Dinesh C. S.; Singh, Phool; Mathpal, Prakash C.

2017-10-01

Genetic Algorithm (GA) forms a subset of evolutionary computing, rapidly growing area of Artificial Intelligence (A.I.). Some variants of GA are binary GA, real GA, messy GA, micro GA, saw tooth GA, differential evolution GA. This research article presents a real coded GA for predicting enrollments of University of Alabama. Data of Alabama University is a fuzzy time series. Here, fuzzy logic is used to predict enrollments of Alabama University and genetic algorithm optimizes fuzzy intervals. Results are compared to other eminent author works and found satisfactory, and states that real coded GA are fast and accurate.

Genetic algorithms in adaptive fuzzy control

NASA Technical Reports Server (NTRS)

Karr, C. Lucas; Harper, Tony R.

1992-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

An incremental approach to genetic-algorithms-based classification.

PubMed

Guan, Sheng-Uei; Zhu, Fangming

2005-04-01

Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental learning with statistical algorithms or neural networks, rather than evolutionary algorithms. The work in this paper employs genetic algorithms (GAs) as basic learning algorithms for incremental learning within one or more classifier agents in a multiagent environment. Four new approaches with different initialization schemes are proposed. They keep the old solutions and use an "integration" operation to integrate them with new elements to accommodate new attributes, while biased mutation and crossover operations are adopted to further evolve a reinforced solution. The simulation results on benchmark classification data sets show that the proposed approaches can deal with the arrival of new input attributes and integrate them with the original input space. It is also shown that the proposed approaches can be successfully used for incremental learning and improve classification rates as compared to the retraining GA. Possible applications for continuous incremental training and feature selection are also discussed.

Novel model of a AlGaN/GaN high electron mobility transistor based on an artificial neural network

NASA Astrophysics Data System (ADS)

Cheng, Zhi-Qun; Hu, Sha; Liu, Jun; Zhang, Qi-Jun

2011-03-01

In this paper we present a novel approach to modeling AlGaN/GaN high electron mobility transistor (HEMT) with an artificial neural network (ANN). The AlGaN/GaN HEMT device structure and its fabrication process are described. The circuit-based Neuro-space mapping (neuro-SM) technique is studied in detail. The EEHEMT model is implemented according to the measurement results of the designed device, which serves as a coarse model. An ANN is proposed to model AlGaN/GaN HEMT based on the coarse model. Its optimization is performed. The simulation results from the model are compared with the measurement results. It is shown that the simulation results obtained from the ANN model of AlGaN/GaN HEMT are more accurate than those obtained from the EEHEMT model. Project supported by the National Natural Science Foundation of China (Grant No. 60776052).

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

NASA Technical Reports Server (NTRS)

Ortiz, Francisco

2004-01-01

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions

Efficiency and droop improvement in a blue InGaN-based light emitting diode with a p-InGaN layer inserted in the GaN barriers

NASA Astrophysics Data System (ADS)

Wang, Xing-Fu; Tong, Jin-Hui; Zhao, Bi-Jun; Chen, Xin; Ren, Zhi-Wei; Li, Dan-Wei; Zhuo, Xiang-Jing; Zhang, Jun; Yi, Han-Xiang; Li, Shu-Ti

2013-09-01

The advantages of a blue InGaN-based light-emitting diode with a p-InGaN layer inserted in the GaN barriers is studied. The carrier concentration in the quantum well, radiative recombination rate in the active region, output power, and internal quantum efficiency are investigated. The simulation results show that the InGaN-based light-emitting diode with a p-InGaN layer inserted in the barriers has better performance over its conventional counterpart and the light emitting diode with p-GaN inserted in the barriers. The improvement is due to enhanced Mg acceptor activation and enhanced hole injection into the quantum wells.

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem.

PubMed

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA.

A Biomimetic Algorithm for Flight Stabilization in Airborne Vehicles, Based on Dragonfly Ocellar Vision

DTIC Science & Technology

2006-07-27

9 10 Technical horizon sensors Over the past few years, a remarkable proliferation of designs for micro-aerial vehicles (MAVs) has occurred... photodiode Fig. 15 Fig. 14 Sky scans with a GaP UV pho to dio de a lo ng three vert ical paths. A ngle o f v iew 30 degrees, 50% clo ud co ver, sun at...Australia Email: gert.stange@anu.edu.au A biomimetic algorithm for flight stabilization in airborne vehicles , based on dragonfly ocellar vision

Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Comparison of Genetic Algorithm, Particle Swarm Optimization and Biogeography-based Optimization for Feature Selection to Classify Clusters of Microcalcifications

NASA Astrophysics Data System (ADS)

Khehra, Baljit Singh; Pharwaha, Amar Partap Singh

2017-04-01

Ductal carcinoma in situ (DCIS) is one type of breast cancer. Clusters of microcalcifications (MCCs) are symptoms of DCIS that are recognized by mammography. Selection of robust features vector is the process of selecting an optimal subset of features from a large number of available features in a given problem domain after the feature extraction and before any classification scheme. Feature selection reduces the feature space that improves the performance of classifier and decreases the computational burden imposed by using many features on classifier. Selection of an optimal subset of features from a large number of available features in a given problem domain is a difficult search problem. For n features, the total numbers of possible subsets of features are 2n. Thus, selection of an optimal subset of features problem belongs to the category of NP-hard problems. In this paper, an attempt is made to find the optimal subset of MCCs features from all possible subsets of features using genetic algorithm (GA), particle swarm optimization (PSO) and biogeography-based optimization (BBO). For simulation, a total of 380 benign and malignant MCCs samples have been selected from mammogram images of DDSM database. A total of 50 features extracted from benign and malignant MCCs samples are used in this study. In these algorithms, fitness function is correct classification rate of classifier. Support vector machine is used as a classifier. From experimental results, it is also observed that the performance of PSO-based and BBO-based algorithms to select an optimal subset of features for classifying MCCs as benign or malignant is better as compared to GA-based algorithm.

Voltage stability index based optimal placement of static VAR compensator and sizing using Cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Venkateswara Rao, B.; Kumar, G. V. Nagesh; Chowdary, D. Deepak; Bharathi, M. Aruna; Patra, Stutee

2017-07-01

This paper furnish the new Metaheuristic algorithm called Cuckoo Search Algorithm (CSA) for solving optimal power flow (OPF) problem with minimization of real power generation cost. The CSA is found to be the most efficient algorithm for solving single objective optimal power flow problems. The CSA performance is tested on IEEE 57 bus test system with real power generation cost minimization as objective function. Static VAR Compensator (SVC) is one of the best shunt connected device in the Flexible Alternating Current Transmission System (FACTS) family. It has capable of controlling the voltage magnitudes of buses by injecting the reactive power to system. In this paper SVC is integrated in CSA based Optimal Power Flow to optimize the real power generation cost. SVC is used to improve the voltage profile of the system. CSA gives better results as compared to genetic algorithm (GA) in both without and with SVC conditions.

Application of the gravity search algorithm to multi-reservoir operation optimization

NASA Astrophysics Data System (ADS)

Bozorg-Haddad, Omid; Janbaz, Mahdieh; Loáiciga, Hugo A.

2016-12-01

Complexities in river discharge, variable rainfall regime, and drought severity merit the use of advanced optimization tools in multi-reservoir operation. The gravity search algorithm (GSA) is an evolutionary optimization algorithm based on the law of gravity and mass interactions. This paper explores the GSA's efficacy for solving benchmark functions, single reservoir, and four-reservoir operation optimization problems. The GSA's solutions are compared with those of the well-known genetic algorithm (GA) in three optimization problems. The results show that the GSA's results are closer to the optimal solutions than the GA's results in minimizing the benchmark functions. The average values of the objective function equal 1.218 and 1.746 with the GSA and GA, respectively, in solving the single-reservoir hydropower operation problem. The global solution equals 1.213 for this same problem. The GSA converged to 99.97% of the global solution in its average-performing history, while the GA converged to 97% of the global solution of the four-reservoir problem. Requiring fewer parameters for algorithmic implementation and reaching the optimal solution in fewer number of functional evaluations are additional advantages of the GSA over the GA. The results of the three optimization problems demonstrate a superior performance of the GSA for optimizing general mathematical problems and the operation of reservoir systems.

Saturation of the junction voltage in GaN-based laser diodes

NASA Astrophysics Data System (ADS)

Feng, M. X.; Liu, J. P.; Zhang, S. M.; Liu, Z. S.; Jiang, D. S.; Li, Z. C.; Wang, F.; Li, D. Y.; Zhang, L. Q.; Wang, H.; Yang, H.

2013-05-01

Saturation of the junction voltage in GaN-based laser diodes (LDs) is studied. It is found that there is a bump above the lasing transition in the I(dV/dI)-I curve, instead of a dip as that for GaAs-based LDs. The bump in I(dV/dI)-I curve moves to higher currents along with the lasing threshold. A model considering ambipolar conduction and electron overflow into p-AlGaN cladding layer due to poor carrier confinement in active region is used to explain the anomaly. The characteristic temperature of GaN-based LD is obtained by fitting threshold currents determined from I(dV/dI)-I curves. Moreover, it is found that GaN-based LDs show characteristics with a nonlinear series resistance, which may be due to the electron overflow into p-AlGaN cladding layer and the enhanced activation of Mg acceptors.

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

PubMed Central

Shi, Lei; Wan, Youchuan; Gao, Xianjun

2018-01-01

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy. PMID:29581721

A ripple-spreading genetic algorithm for the aircraft sequencing problem.

PubMed

Hu, Xiao-Bing; Di Paolo, Ezequiel A

2011-01-01

When genetic algorithms (GAs) are applied to combinatorial problems, permutation representations are usually adopted. As a result, such GAs are often confronted with feasibility and memory-efficiency problems. With the aircraft sequencing problem (ASP) as a study case, this paper reports on a novel binary-representation-based GA scheme for combinatorial problems. Unlike existing GAs for the ASP, which typically use permutation representations based on aircraft landing order, the new GA introduces a novel ripple-spreading model which transforms the original landing-order-based ASP solutions into value-based ones. In the new scheme, arriving aircraft are projected as points into an artificial space. A deterministic method inspired by the natural phenomenon of ripple-spreading on liquid surfaces is developed, which uses a few parameters as input to connect points on this space to form a landing sequence. A traditional GA, free of feasibility and memory-efficiency problems, can then be used to evolve the ripple-spreading related parameters in order to find an optimal sequence. Since the ripple-spreading model is the centerpiece of the new algorithm, it is called the ripple-spreading GA (RSGA). The advantages of the proposed RSGA are illustrated by extensive comparative studies for the case of the ASP.

Automated Phase Segmentation for Large-Scale X-ray Diffraction Data Using a Graph-Based Phase Segmentation (GPhase) Algorithm.

PubMed

Xiong, Zheng; He, Yinyan; Hattrick-Simpers, Jason R; Hu, Jianjun

2017-03-13

The creation of composition-processing-structure relationships currently represents a key bottleneck for data analysis for high-throughput experimental (HTE) material studies. Here we propose an automated phase diagram attribution algorithm for HTE data analysis that uses a graph-based segmentation algorithm and Delaunay tessellation to create a crystal phase diagram from high throughput libraries of X-ray diffraction (XRD) patterns. We also propose the sample-pair based objective evaluation measures for the phase diagram prediction problem. Our approach was validated using 278 diffraction patterns from a Fe-Ga-Pd composition spread sample with a prediction precision of 0.934 and a Matthews Correlation Coefficient score of 0.823. The algorithm was then applied to the open Ni-Mn-Al thin-film composition spread sample to obtain the first predicted phase diagram mapping for that sample.

A neural-network-based exponential H∞ synchronisation for chaotic secure communication via improved genetic algorithm

NASA Astrophysics Data System (ADS)

Hsiao, Feng-Hsiag

2016-10-01

In this study, a novel approach via improved genetic algorithm (IGA)-based fuzzy observer is proposed to realise exponential optimal H∞ synchronisation and secure communication in multiple time-delay chaotic (MTDC) systems. First, an original message is inserted into the MTDC system. Then, a neural-network (NN) model is employed to approximate the MTDC system. Next, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion derived in terms of Lyapunov's direct method, thus ensuring that the trajectories of the slave system approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to GA's random global optimisation search capabilities, the lower and upper bounds of the search space can be set so that the GA will seek better fuzzy observer feedback gains, accelerating feedback gain-based synchronisation via the LMI-based approach. IGA, which exhibits better performance than traditional GA, is used to synthesise a fuzzy observer to not only realise the exponential synchronisation, but also achieve optimal H∞ performance by minimizing the disturbance attenuation level and recovering the transmitted message. Finally, a numerical example with simulations is given in order to demonstrate the effectiveness of our approach.

Review of GaN-based devices for terahertz operation

NASA Astrophysics Data System (ADS)

Ahi, Kiarash

2017-09-01

GaN provides the highest electron saturation velocity, breakdown voltage, operation temperature, and thus the highest combined frequency-power performance among commonly used semiconductors. The industrial need for compact, economical, high-resolution, and high-power terahertz (THz) imaging and spectroscopy systems are promoting the utilization of GaN for implementing the next generation of THz systems. As it is reviewed, the mentioned characteristics of GaN together with its capabilities of providing high two-dimensional election densities and large longitudinal optical phonon of ˜90 meV make it one of the most promising semiconductor materials for the future of the THz emitters, detectors, mixers, and frequency multiplicators. GaN-based devices have shown capabilities of operation in the upper THz frequency band of 5 to 12 THz with relatively high photon densities in room temperature. As a result, THz imaging and spectroscopy systems with high resolution and deep depth of penetration can be realized through utilizing GaN-based devices. A comprehensive review of the history and the state of the art of GaN-based electronic devices, including plasma heterostructure field-effect transistors, negative differential resistances, hetero-dimensional Schottky diodes, impact avalanche transit times, quantum-cascade lasers, high electron mobility transistors, Gunn diodes, and tera field-effect transistors together with their impact on the future of THz imaging and spectroscopy systems is provided.

Control of Ga-oxide interlayer growth and Ga diffusion in SiO2/GaN stacks for high-quality GaN-based metal-oxide-semiconductor devices with improved gate dielectric reliability

NASA Astrophysics Data System (ADS)

Yamada, Takahiro; Watanabe, Kenta; Nozaki, Mikito; Yamada, Hisashi; Takahashi, Tokio; Shimizu, Mitsuaki; Yoshigoe, Akitaka; Hosoi, Takuji; Shimura, Takayoshi; Watanabe, Heiji

2018-01-01

A simple and feasible method for fabricating high-quality and highly reliable GaN-based metal-oxide-semiconductor (MOS) devices was developed. The direct chemical vapor deposition of SiO2 films on GaN substrates forming Ga-oxide interlayers was carried out to fabricate SiO2/GaO x /GaN stacked structures. Although well-behaved hysteresis-free GaN-MOS capacitors with extremely low interface state densities below 1010 cm-2 eV-1 were obtained by postdeposition annealing, Ga diffusion into overlying SiO2 layers severely degraded the dielectric breakdown characteristics. However, this problem was found to be solved by rapid thermal processing, leading to the superior performance of the GaN-MOS devices in terms of interface quality, insulating property, and gate dielectric reliability.

Creating IRT-Based Parallel Test Forms Using the Genetic Algorithm Method

ERIC Educational Resources Information Center

Sun, Koun-Tem; Chen, Yu-Jen; Tsai, Shu-Yen; Cheng, Chien-Fen

2008-01-01

In educational measurement, the construction of parallel test forms is often a combinatorial optimization problem that involves the time-consuming selection of items to construct tests having approximately the same test information functions (TIFs) and constraints. This article proposes a novel method, genetic algorithm (GA), to construct parallel…

Case Study on Optimal Routing in Logistics Network by Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiaoguang; Lin, Lin; Gen, Mitsuo; Shiota, Mitsushige

Recently, research on logistics caught more and more attention. One of the important issues on logistics system is to find optimal delivery routes with the least cost for products delivery. Numerous models have been developed for that reason. However, due to the diversity and complexity of practical problem, the existing models are usually not very satisfying to find the solution efficiently and convinently. In this paper, we treat a real-world logistics case with a company named ABC Co. ltd., in Kitakyusyu Japan. Firstly, based on the natures of this conveyance routing problem, as an extension of transportation problem (TP) and fixed charge transportation problem (fcTP) we formulate the problem as a minimum cost flow (MCF) model. Due to the complexity of fcTP, we proposed a priority-based genetic algorithm (pGA) approach to find the most acceptable solution to this problem. In this pGA approach, a two-stage path decoding method is adopted to develop delivery paths from a chromosome. We also apply the pGA approach to this problem, and compare our results with the current logistics network situation, and calculate the improvement of logistics cost to help the management to make decisions. Finally, in order to check the effectiveness of the proposed method, the results acquired are compared with those come from the two methods/ software, such as LINDO and CPLEX.

Carrier-injection studies in GaN-based light-emitting-diodes

NASA Astrophysics Data System (ADS)

Nguyen, Dinh Chuong; Vaufrey, David; Leroux, Mathieu

2015-09-01

Although p-type GaN has been achieved by Mg doping, the low hole-mobility still remains a difficulty for GaN-based light-emitting diodes (LEDs). Due to the lack of field-dependent-velocity model for holes, in GaN-based LED simulations, the hole mobility is usually supposed to remain constant. However, as the p-GaN-layer conductivity is lower than the n-GaN-layer conductivity, a strong electric-field exists in the p-side of an LED when the applied voltage exceeds the LED's built-in voltage. Under the influence of this field, the mobilities of electrons and holes are expected to decrease. Based on a field-dependent-velocity model that is usually used for narrow-bandgap materials, an LED structure is modelled with three arbitrarily chosen hole saturation-velocities. The results show that a hole saturation-velocity lower than 4x106 cm/s can negatively affect the LED's behaviors.

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of

RBT-GA: a novel metaheuristic for solving the Multiple Sequence Alignment problem.

PubMed

Taheri, Javid; Zomaya, Albert Y

2009-07-07

Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences.

RBT-GA: a novel metaheuristic for solving the multiple sequence alignment problem

PubMed Central

Taheri, Javid; Zomaya, Albert Y

2009-01-01

Background Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. Results This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. Conclusion RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences. PMID:19594869

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem

PubMed Central

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA. PMID:26167171

Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

PubMed Central

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PubMed

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

Comparison of blue-green response between transmission-mode GaAsP- and GaAs-based photocathodes grown by molecular beam epitaxy

NASA Astrophysics Data System (ADS)

Gang-Cheng, Jiao; Zheng-Tang, Liu; Hui, Guo; Yi-Jun, Zhang

2016-04-01

In order to develop the photodetector for effective blue-green response, the 18-mm-diameter vacuum image tube combined with the transmission-mode Al0.7Ga0.3As0.9 P 0.1/GaAs0.9 P 0.1 photocathode grown by molecular beam epitaxy is tentatively fabricated. A comparison of photoelectric property, spectral characteristic and performance parameter between the transmission-mode GaAsP-based and blue-extended GaAs-based photocathodes shows that the GaAsP-based photocathode possesses better absorption and higher quantum efficiency in the blue-green waveband, combined with a larger surface electron escape probability. Especially, the quantum efficiency at 532 nm for the GaAsP-based photocathode achieves as high as 59%, nearly twice that for the blue-extended GaAs-based one, which would be more conducive to the underwater range-gated imaging based on laser illumination. Moreover, the simulation results show that the favorable blue-green response can be achieved by optimizing the emission-layer thickness in a range of 0.4 μm-0.6 μm. Project supported by the National Natural Science Foundation of China (Grant No. 61301023) and the Science and Technology on Low-Light-Level Night Vision Laboratory Foundation, China (Grant No. BJ2014001).

GaAs/AlGaAs core multishell nanowire-based light-emitting diodes on Si.

PubMed

Tomioka, Katsuhiro; Motohisa, Junichi; Hara, Shinjiroh; Hiruma, Kenji; Fukui, Takashi

2010-05-12

We report on integration of GaAs nanowire-based light-emitting-diodes (NW-LEDs) on Si substrate by selective-area metalorganic vapor phase epitaxy. The vertically aligned GaAs/AlGaAs core-multishell nanowires with radial p-n junction and NW-LED array were directly fabricated on Si. The threshold current for electroluminescence (EL) was 0.5 mA (current density was approximately 0.4 A/cm(2)), and the EL intensity superlinearly increased with increasing current injections indicating superluminescence behavior. The technology described in this letter could help open new possibilities for monolithic- and on-chip integration of III-V NWs on Si.

Non-invasive continuous blood pressure measurement based on mean impact value method, BP neural network, and genetic algorithm.

PubMed

Tan, Xia; Ji, Zhong; Zhang, Yadan

2018-04-25

Non-invasive continuous blood pressure monitoring can provide an important reference and guidance for doctors wishing to analyze the physiological and pathological status of patients and to prevent and diagnose cardiovascular diseases in the clinical setting. Therefore, it is very important to explore a more accurate method of non-invasive continuous blood pressure measurement. To address the shortcomings of existing blood pressure measurement models based on pulse wave transit time or pulse wave parameters, a new method of non-invasive continuous blood pressure measurement - the GA-MIV-BP neural network model - is presented. The mean impact value (MIV) method is used to select the factors that greatly influence blood pressure from the extracted pulse wave transit time and pulse wave parameters. These factors are used as inputs, and the actual blood pressure values as outputs, to train the BP neural network model. The individual parameters are then optimized using a genetic algorithm (GA) to establish the GA-MIV-BP neural network model. Bland-Altman consistency analysis indicated that the measured and predicted blood pressure values were consistent and interchangeable. Therefore, this algorithm is of great significance to promote the clinical application of a non-invasive continuous blood pressure monitoring method.

Polarization Enhanced Charge Transfer: Dual-Band GaN-Based Plasmonic Photodetector.

PubMed

Jia, Ran; Zhao, Dongfang; Gao, Naikun; Liu, Duo

2017-01-13

Here, we report a dual-band plasmonic photodetector based on Ga-polar gallium nitride (GaN) for highly sensitive detection of UV and green light. We discover that decoration of Au nanoparticles (NPs) drastically increases the photoelectric responsivities by more than 50 times in comparition to the blank GaN photodetector. The observed behaviors are attributed to polarization enhanced charge transfer of optically excited hot electrons from Au NPs to GaN driven by the strong spontaneous polarization field of Ga-polar GaN. Moreover, defect ionization promoted by localized surface plasmon resonances (LSPRs) is also discussed. This novel type of photodetector may shed light on the design and fabrication of photoelectric devices based on polar semiconductors and microstructural defects.

A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction

PubMed Central

Zhang, Daqing; Xiao, Jianfeng; Zhou, Nannan; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian

2015-01-01

Blood-brain barrier (BBB) is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM) is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy. In most studies, they are treated as two independent problems, but it has been proven that they could affect each other. We designed and implemented genetic algorithm (GA) to optimize kernel parameters and feature subset selection for SVM regression and applied it to the BBB penetration prediction. The results show that our GA/SVM model is more accurate than other currently available log BB models. Therefore, to optimize both SVM parameters and feature subset simultaneously with genetic algorithm is a better approach than other methods that treat the two problems separately. Analysis of our log BB model suggests that carboxylic acid group, polar surface area (PSA)/hydrogen-bonding ability, lipophilicity, and molecular charge play important role in BBB penetration. Among those properties relevant to BBB penetration, lipophilicity could enhance the BBB penetration while all the others are negatively correlated with BBB penetration. PMID:26504797

SEMICONDUCTOR DEVICES: A Ga-doped ZnO transparent conduct layer for GaN-based LEDs

NASA Astrophysics Data System (ADS)

Zhen, Liu; Xiaofeng, Wang; Hua, Yang; Yao, Duan; Yiping, Zeng

2010-09-01

An 8 μm thick Ga-doped ZnO (GZO) film grown by metal-source vapor phase epitaxy was deposited on a GaN-based light-emitting diode (LED) to substitute for the conventional ITO as a transparent conduct layer (TCL). Electroluminescence spectra exhibited that the intensity value of LED emission with a GZO TCL is markedly improved by 23.6% as compared to an LED with an ITO TCL at 20 mA. In addition, the forward voltage of the LED with a GZO TCL at 20 mA is higher than that of the conventional LED. To investigate the reason for the increase of the forward voltage, X-ray photoelectron spectroscopy was performed to analyze the interface properties of the GZO/p-GaN heterojunction. The large valence band offset (2:24 ± 0:21 eV) resulting from the formation of Ga2O3 in the GZO/p-GaN interface was attributed to the increase of the forward voltage.

GaN MOSFET with Boron Trichloride-Based Dry Recess Process

NASA Astrophysics Data System (ADS)

Jiang, Y.; Wang, Q. P.; Tamai, K.; Miyashita, T.; Motoyama, S.; Wang, D. J.; Ao, J. P.; Ohno, Y.

2013-06-01

The dry recessed-gate GaN metal-oxide-semiconductor field-effect transistors (MOSFETs) on AlGaN/GaN heterostructure using boron trichloride (BCl3) as etching gas were fabricated and characterized. Etching with different etching power was conducted. Devices with silicon tetrachloride (SiCl4) etching gas were also prepared for comparison. Field-effect mobility and interface state density were extracted from current-voltage (I-V) characteristics. GaN MOSFETs on AlGaN/GaN heterostructure with BCl3 based dry recess achieved a high maximum electron mobility of 141.5 cm2V-1s-1 and a low interface state density.

Calculation of the surface tension of liquid Ga-based alloys

NASA Astrophysics Data System (ADS)

Dogan, Ali; Arslan, Hüseyin

2018-05-01

As known, Eyring and his collaborators have applied the structure theory to the properties of binary liquid mixtures. In this work, the Eyring model has been extended to calculate the surface tension of liquid Ga-Bi, Ga-Sn and Ga-In binary alloys. It was found that the addition of Sn, In and Bi into Ga leads to significant decrease in the surface tension of the three Ga-based alloy systems, especially for that of Ga-Bi alloys. The calculated surface tension values of these alloys exhibit negative deviation from the corresponding ideal mixing isotherms. Moreover, a comparison between the calculated results and corresponding literature data indicates a good agreement.

Monolithic photonic integrated circuit with a GaN-based bent waveguide

NASA Astrophysics Data System (ADS)

Cai, Wei; Qin, Chuan; Zhang, Shuai; Yuan, Jialei; Zhang, Fenghua; Wang, Yongjin

2018-06-01

Integration of a transmitter, waveguide and receiver into a single chip can generate a multicomponent system with multiple functionalities. Here, we fabricate and characterize a GaN-based photonic integrated circuit (PIC) on a GaN-on-silicon platform. With removal of the silicon and back wafer thinning of the epitaxial film, ultrathin membrane-type devices and highly confined suspended GaN waveguides were formed. Two suspended-membrane InGaN/GaN multiple-quantum-well diodes (MQW-diodes) served as an MQW light-emitting diode (MQW-LED) to emit light and an MQW photodiode (MQW-PD) to sense light. The optical interconnects between the MQW-LED and MQW-PD were achieved using the GaN bent waveguide. The GaN-based PIC consisting of an MQW-LED, waveguides and an MQW-PD forms an in-plane light communication system with a data transmission rate of 70 Mbps.

Biological engineering applications of feedforward neural networks designed and parameterized by genetic algorithms.

PubMed

Ferentinos, Konstantinos P

2005-09-01

Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.

High-frequency electromechanical resonators based on thin GaTe

NASA Astrophysics Data System (ADS)

Chitara, Basant; Ya'akobovitz, Assaf

2017-10-01

Gallium telluride (GaTe) is a layered material, which exhibits a direct bandgap (˜1.65 eV) regardless of its thickness and therefore holds great potential for integration as a core element in stretchable optomechanical and optoelectronic devices. Here, we characterize and demonstrate the elastic properties and electromechanical resonators of suspended thin GaTe nanodrums. We used atomic force microscopy to extract the Young’s modulus of GaTe (average value ˜39 GPa) and to predict the resonance frequencies of suspended GaTe nanodrums of various geometries. Electromechanical resonators fabricated from suspended GaTe revealed fundamental resonance frequencies in the range of 10-25 MHz, which closely match predicted values. Therefore, this study paves the way for creating a new generation of GaTe based nanoelectromechanical devices with a direct bandgap vibrating element, which can serve as optomechanical sensors and actuators.

GHz Modulation of GaAs-Based Bipolar Cascade VCSELs (Preprint)

DTIC Science & Technology

2006-11-01

VCSELs were grown on n+ GaAs substrates by molecular beam epitaxy . The laser cavities consist of 1-, 2-, or 3-stage 52λ microcavi- ties, each containing...AFRL-SN-WP-TP-2006-128 GHz MODULATION OF GaAs-BASED BIPOLAR CASCADE VCSELs (PREPRINT) W.J. Siskaninetz, R.G. Bedford, T.R. Nelson, Jr., J.E...TITLE AND SUBTITLE GHz MODULATION OF GaAs-BASED BIPOLAR CASCADE VCSELs (PREPRINT) 5c. PROGRAM ELEMENT NUMBER 69199F 5d. PROJECT NUMBER 2002 5e

Emerging GaN-based HEMTs for mechanical sensing within harsh environments

NASA Astrophysics Data System (ADS)

Köck, Helmut; Chapin, Caitlin A.; Ostermaier, Clemens; Häberlen, Oliver; Senesky, Debbie G.

2014-06-01

Gallium nitride based high-electron-mobility transistors (HEMTs) have been investigated extensively as an alternative to Si-based power transistors by academia and industry over the last decade. It is well known that GaN-based HEMTs outperform Si-based technologies in terms of power density, area specific on-state resistance and switching speed. Recently, wide band-gap material systems have stirred interest regarding their use in various sensing fields ranging from chemical, mechanical, biological to optical applications due to their superior material properties. For harsh environments, wide bandgap sensor systems are deemed to be superior when compared to conventional Si-based systems. A new monolithic sensor platform based on the GaN HEMT electronic structure will enable engineers to design highly efficient propulsion systems widely applicable to the automotive, aeronautics and astronautics industrial sectors. In this paper, the advancements of GaN-based HEMTs for mechanical sensing applications are discussed. Of particular interest are multilayered heterogeneous structures where spontaneous and piezoelectric polarization between the interface results in the formation of a 2-dimensional electron gas (2DEG). Experimental results presented focus on the signal transduction under strained operating conditions in harsh environments. It is shown that a conventional AlGaN/GaN HEMT has a strong dependence of drain current under strained conditions, thus representing a promising future sensor platform. Ultimately, this work explores the sensor performance of conventional GaN HEMTs and leverages existing technological advances available in power electronics device research. The results presented have the potential to boost GaN-based sensor development through the integration of HEMT device and sensor design research.

Accurate Descriptions of Hot Flow Behaviors Across β Transus of Ti-6Al-4V Alloy by Intelligence Algorithm GA-SVR

NASA Astrophysics Data System (ADS)

Wang, Li-yong; Li, Le; Zhang, Zhi-hua

2016-09-01

Hot compression tests of Ti-6Al-4V alloy in a wide temperature range of 1023-1323 K and strain rate range of 0.01-10 s-1 were conducted by a servo-hydraulic and computer-controlled Gleeble-3500 machine. In order to accurately and effectively characterize the highly nonlinear flow behaviors, support vector regression (SVR) which is a machine learning method was combined with genetic algorithm (GA) for characterizing the flow behaviors, namely, the GA-SVR. The prominent character of GA-SVR is that it with identical training parameters will keep training accuracy and prediction accuracy at a stable level in different attempts for a certain dataset. The learning abilities, generalization abilities, and modeling efficiencies of the mathematical regression model, ANN, and GA-SVR for Ti-6Al-4V alloy were detailedly compared. Comparison results show that the learning ability of the GA-SVR is stronger than the mathematical regression model. The generalization abilities and modeling efficiencies of these models were shown as follows in ascending order: the mathematical regression model < ANN < GA-SVR. The stress-strain data outside experimental conditions were predicted by the well-trained GA-SVR, which improved simulation accuracy of the load-stroke curve and can further improve the related research fields where stress-strain data play important roles, such as speculating work hardening and dynamic recovery, characterizing dynamic recrystallization evolution, and improving processing maps.

The use of knowledge-based Genetic Algorithm for starting time optimisation in a lot-bucket MRP

NASA Astrophysics Data System (ADS)

Ridwan, Muhammad; Purnomo, Andi

2016-01-01

In production planning, Material Requirement Planning (MRP) is usually developed based on time-bucket system, a period in the MRP is representing the time and usually weekly. MRP has been successfully implemented in Make To Stock (MTS) manufacturing, where production activity must be started before customer demand is received. However, to be implemented successfully in Make To Order (MTO) manufacturing, a modification is required on the conventional MRP in order to make it in line with the real situation. In MTO manufacturing, delivery schedule to the customers is defined strictly and must be fulfilled in order to increase customer satisfaction. On the other hand, company prefers to keep constant number of workers, hence production lot size should be constant as well. Since a bucket in conventional MRP system is representing time and usually weekly, hence, strict delivery schedule could not be accommodated. Fortunately, there is a modified time-bucket MRP system, called as lot-bucket MRP system that proposed by Casimir in 1999. In the lot-bucket MRP system, a bucket is representing a lot, and the lot size is preferably constant. The time to finish every lot could be varying depends on due date of lot. Starting time of a lot must be determined so that every lot has reasonable production time. So far there is no formal method to determine optimum starting time in the lot-bucket MRP system. Trial and error process usually used for it but some time, it causes several lots have very short production time and the lot-bucket MRP would be infeasible to be executed. This paper presents the use of Genetic Algorithm (GA) for optimisation of starting time in a lot-bucket MRP system. Even though GA is well known as powerful searching algorithm, however, improvement is still required in order to increase possibility of GA in finding optimum solution in shorter time. A knowledge-based system has been embedded in the proposed GA as the improvement effort, and it is proven that the

Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification.

PubMed

Haque, Mohammad Nazmul; Noman, Nasimul; Berretta, Regina; Moscato, Pablo

2016-01-01

Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble's output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (α, β) - k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer's disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases.

Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification

PubMed Central

Haque, Mohammad Nazmul; Noman, Nasimul; Berretta, Regina; Moscato, Pablo

2016-01-01

Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble’s output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (α, β) − k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer’s disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases. PMID:26764911

AlGaN/GaN High Electron Mobility Transistor-Based Biosensor for the Detection of C-Reactive Protein

PubMed Central

Lee, Hee Ho; Bae, Myunghan; Jo, Sung-Hyun; Shin, Jang-Kyoo; Son, Dong Hyeok; Won, Chul-Ho; Jeong, Hyun-Min; Lee, Jung-Hee; Kang, Shin-Won

2015-01-01

In this paper, we propose an AlGaN/GaN high electron mobility transistor (HEMT)-based biosensor for the detection of C-reactive protein (CRP) using a null-balancing circuit. A null-balancing circuit was used to measure the output voltage of the sensor directly. The output voltage of the proposed biosensor was varied by antigen-antibody interactions on the gate surface due to CRP charges. The AlGaN/GaN HFET-based biosensor with null-balancing circuit applied shows that CRP can be detected in a wide range of concentrations, varying from 10 ng/mL to 1000 ng/mL. X-ray photoelectron spectroscopy was carried out to verify the immobilization of self-assembled monolayer with Au on the gated region. PMID:26225981

Thermal characterization of GaN-based laser diodes by forward-voltage method

NASA Astrophysics Data System (ADS)

Feng, M. X.; Zhang, S. M.; Jiang, D. S.; Liu, J. P.; Wang, H.; Zeng, C.; Li, Z. C.; Wang, H. B.; Wang, F.; Yang, H.

2012-05-01

An expression of the relation between junction temperature and forward voltage common for both GaN-based laser diodes (LDs) and light emitting diodes is derived. By the expression, the junction temperature of GaN-based LDs emitting at 405 nm was measured at different injection current and compared with the result of micro-Raman spectroscopy, showing that the expression is reasonable. In addition, the activation energy of Mg in AlGaN/GaN superlattice layers is obtained based on the temperature dependence of forward voltage.

Effect of p-GaN layer doping on the photoresponse of GaN-based p-i-n ultraviolet photodetectors

NASA Astrophysics Data System (ADS)

Wang, Jun; Guo, Jin; Xie, Feng; Wang, Wanjun; Wang, Guosheng; Wu, Haoran; Wang, Tanglin; Song, Man

2015-08-01

We report on two-dimensional (2D) numerical simulations of photoresponse characteristics for GaN based p-i-n ultraviolet (UV) photodetectors. Effects of doping density of p-GaN layer on the photoresponse have been investigated. In order to accurately simulate the device performance, the theoretical calculation includes doping-dependent mobility degradation by Arora model and high field saturation model. Theoretical modeling shows that the doping density of p- GaN layer can significantly affect the photoresponse of GaN based p-i-n UV photodetectors, especially at schottky contact. We have to make a suitable choice of the doping in the device design according to the simulation results.

Ga(+) Basicity and Affinity Scales Based on High-Level Ab Initio Calculations.

PubMed

Brea, Oriana; Mó, Otilia; Yáñez, Manuel

2015-10-26

The structure, relative stability and bonding of complexes formed by the interaction between Ga(+) and a large set of compounds, including hydrocarbons, aromatic systems, and oxygen-, nitrogen-, fluorine and sulfur-containing Lewis bases have been investigated through the use of the high-level composite ab initio Gaussian-4 theory. This allowed us to establish rather accurate Ga(+) cation affinity (GaCA) and Ga(+) cation basicity (GaCB) scales. The bonding analysis of the complexes under scrutiny shows that, even though one of the main ingredients of the Ga(+) -base interaction is electrostatic, it exhibits a non-negligible covalent character triggered by the presence of the low-lying empty 4p orbital of Ga(+) , which favors a charge donation from occupied orbitals of the base to the metal ion. This partial covalent character, also observed in AlCA scales, is behind the dissimilarities observed when GaCA are compared with Li(+) cation affinities, where these covalent contributions are practically nonexistent. Quite unexpectedly, there are some dissimilarities between several Ga(+) -complexes and the corresponding Al(+) -analogues, mainly affecting the relative stability of π-complexes involving aromatic compounds. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

PubMed

Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

2013-09-01

Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P < 0.01). This algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P < 0.05), whereas it shows results not significantly different to 3D-COFFEE (P > 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

Positive temperature coefficient of photovoltaic efficiency in solar cells based on InGaN/GaN MQWs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Zhaoying; Zheng, Xiantong; Li, Zhilong

2016-08-08

We report a 23.4% improvement of conversion efficiency in solar cells based on InGaN/GaN multiple quantum wells by using a patterned sapphire substrate in the fabrication process. The efficiency enhancement is due to the improvement of the crystalline quality, as proven by the reduction of the threading dislocation density. More importantly, the better crystalline quality leads to a positive photovoltaic efficiency temperature coefficient up to 423 K, which shows the property and advantage of wide gap semiconductors like InGaN, signifying the potential of III-nitride based solar cells for high temperature and concentrating solar power applications.

GaAs1-xBix/GaNyAs1-y type-II quantum wells: novel strain-balanced heterostructures for GaAs-based near- and mid-infrared photonics.

PubMed

Broderick, Christopher A; Jin, Shirong; Marko, Igor P; Hild, Konstanze; Ludewig, Peter; Bushell, Zoe L; Stolz, Wolfgang; Rorison, Judy M; O'Reilly, Eoin P; Volz, Kerstin; Sweeney, Stephen J

2017-04-19

The potential to extend the emission wavelength of photonic devices further into the near- and mid-infrared via pseudomorphic growth on conventional GaAs substrates is appealing for a number of communications and sensing applications. We present a new class of GaAs-based quantum well (QW) heterostructure that exploits the unusual impact of Bi and N on the GaAs band structure to produce type-II QWs having long emission wavelengths with little or no net strain relative to GaAs, while also providing control over important laser loss processes. We theoretically and experimentally demonstrate the potential of GaAs 1-x Bi x /GaN y As 1-y type-II QWs on GaAs and show that this approach offers optical emission and absorption at wavelengths up to ~3 µm utilising strain-balanced structures, a first for GaAs-based QWs. Experimental measurements on a prototype GaAs 0.967 Bi 0.033 /GaN 0.062 As 0.938 structure, grown via metal-organic vapour phase epitaxy, indicate good structural quality and exhibit both photoluminescence and absorption at room temperature. The measured photoluminescence peak wavelength of 1.72 μm is in good agreement with theoretical calculations and is one of the longest emission wavelengths achieved on GaAs to date using a pseudomorphically grown heterostructure. These results demonstrate the significant potential of this new class of III-V heterostructure for long-wavelength applications.

GaAs1-xBix/GaNyAs1-y type-II quantum wells: novel strain-balanced heterostructures for GaAs-based near- and mid-infrared photonics

NASA Astrophysics Data System (ADS)

Broderick, Christopher A.; Jin, Shirong; Marko, Igor P.; Hild, Konstanze; Ludewig, Peter; Bushell, Zoe L.; Stolz, Wolfgang; Rorison, Judy M.; O'Reilly, Eoin P.; Volz, Kerstin; Sweeney, Stephen J.

2017-04-01

The potential to extend the emission wavelength of photonic devices further into the near- and mid-infrared via pseudomorphic growth on conventional GaAs substrates is appealing for a number of communications and sensing applications. We present a new class of GaAs-based quantum well (QW) heterostructure that exploits the unusual impact of Bi and N on the GaAs band structure to produce type-II QWs having long emission wavelengths with little or no net strain relative to GaAs, while also providing control over important laser loss processes. We theoretically and experimentally demonstrate the potential of GaAs1-xBix/GaNyAs1-y type-II QWs on GaAs and show that this approach offers optical emission and absorption at wavelengths up to ~3 µm utilising strain-balanced structures, a first for GaAs-based QWs. Experimental measurements on a prototype GaAs0.967Bi0.033/GaN0.062As0.938 structure, grown via metal-organic vapour phase epitaxy, indicate good structural quality and exhibit both photoluminescence and absorption at room temperature. The measured photoluminescence peak wavelength of 1.72 μm is in good agreement with theoretical calculations and is one of the longest emission wavelengths achieved on GaAs to date using a pseudomorphically grown heterostructure. These results demonstrate the significant potential of this new class of III-V heterostructure for long-wavelength applications.

A simple algorithm to compute the peak power output of GaAs/Ge solar cells on the Martian surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glueck, P.R.; Bahrami, K.A.

1995-12-31

The Jet Propulsion Laboratory`s (JPL`s) Mars Pathfinder Project will deploy a robotic ``microrover`` on the surface of Mars in the summer of 1997. This vehicle will derive primary power from a GaAs/Ge solar array during the day and will ``sleep`` at night. This strategy requires that the rover be able to (1) determine when it is necessary to save the contents of volatile memory late in the afternoon and (2) determine when sufficient power is available to resume operations in the morning. An algorithm was developed that estimates the peak power point of the solar array from the solar arraymore » short-circuit current and temperature telemetry, and provides functional redundancy for both measurements using the open-circuit voltage telemetry. The algorithm minimizes vehicle processing and memory utilization by using linear equations instead of look-up tables to estimate peak power with very little loss in accuracy. This paper describes the method used to obtain the algorithm and presents the detailed algorithm design.« less

Solar cells based on InP/GaP/Si structure

NASA Astrophysics Data System (ADS)

Kvitsiani, O.; Laperashvil, D.; Laperashvili, T.; Mikelashvili, V.

2016-10-01

Solar cells (SCs) based on III-V semiconductors are reviewed. Presented work emphases on the Solar Cells containing Quantum Dots (QDs) for next-generation photovoltaics. In this work the method of fabrication of InP QDs on III-V semiconductors is investigated. The original method of electrochemical deposition of metals: indium (In), gallium (Ga) and of alloys (InGa) on the surface of gallium phosphide (GaP), and mechanism of formation of InP QDs on GaP surface is presented. The possibilities of application of InP/GaP/Si structure as SC are discussed, and the challenges arising is also considered.

Phase Reconstruction from FROG Using Genetic Algorithms[Frequency-Resolved Optical Gating

DOE Office of Scientific and Technical Information (OSTI.GOV)

Omenetto, F.G.; Nicholson, J.W.; Funk, D.J.

1999-04-12

The authors describe a new technique for obtaining the phase and electric field from FROG measurements using genetic algorithms. Frequency-Resolved Optical Gating (FROG) has gained prominence as a technique for characterizing ultrashort pulses. FROG consists of a spectrally resolved autocorrelation of the pulse to be measured. Typically a combination of iterative algorithms is used, applying constraints from experimental data, and alternating between the time and frequency domain, in order to retrieve an optical pulse. The authors have developed a new approach to retrieving the intensity and phase from FROG data using a genetic algorithm (GA). A GA is a generalmore » parallel search technique that operates on a population of potential solutions simultaneously. Operators in a genetic algorithm, such as crossover, selection, and mutation are based on ideas taken from evolution.« less

GdN nanoisland-based GaN tunnel junctions.

PubMed

Krishnamoorthy, Sriram; Kent, Thomas F; Yang, Jing; Park, Pil Sung; Myers, Roberto C; Rajan, Siddharth

2013-06-12

Tunnel junctions could have a great impact on gallium nitride and aluminum nitride-based devices such as light-emitting diodes and lasers by overcoming critical challenges related to hole injection and p-contacts. This paper demonstrates the use of GdN nanoislands to enhance interband tunneling and hole injection into GaN p-n junctions by several orders of magnitude, resulting in low tunnel junction specific resistivity (1.3 × 10(-3) Ω-cm(2)) compared to the previous results in wide band gap semiconductors. Tunnel injection of holes was confirmed by low-temperature operation of GaN p-n junction with a tunneling contact layer, and strong electroluminescence down to 20 K. The low tunnel junction resistance combined with low optical absorption loss in GdN is very promising for incorporation in GaN-based light emitters.

Hybrid algorithms for fuzzy reverse supply chain network design.

PubMed

Che, Z H; Chiang, Tzu-An; Kuo, Y C; Cui, Zhihua

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods.

Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design

PubMed Central

Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057

A genetic algorithm solution to the unit commitment problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kazarlis, S.A.; Bakirtzis, A.G.; Petridis, V.

1996-02-01

This paper presents a Genetic Algorithm (GA) solution to the Unit Commitment problem. GAs are general purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms such as natural selection, genetic recombination and survival of the fittest. A simple Ga algorithm implementation using the standard crossover and mutation operators could locate near optimal solutions but in most cases failed to converge to the optimal solution. However, using the Varying Quality Function technique and adding problem specific operators, satisfactory solutions to the Unit Commitment problem were obtained. Test results for systems of up to 100 unitsmore » and comparisons with results obtained using Lagrangian Relaxation and Dynamic Programming are also reported.« less

Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means

NASA Astrophysics Data System (ADS)

Saharan, S.; Baragona, R.; Nor, M. E.; Salleh, R. M.; Asrah, N. M.

2018-04-01

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.

Conductivity based on selective etch for GaN devices and applications thereof

DOEpatents

Zhang, Yu; Sun, Qian; Han, Jung

2015-12-08

This invention relates to methods of generating NP gallium nitride (GaN) across large areas (>1 cm.sup.2) with controlled pore diameters, pore density, and porosity. Also disclosed are methods of generating novel optoelectronic devices based on porous GaN. Additionally a layer transfer scheme to separate and create free-standing crystalline GaN thin layers is disclosed that enables a new device manufacturing paradigm involving substrate recycling. Other disclosed embodiments of this invention relate to fabrication of GaN based nanocrystals and the use of NP GaN electrodes for electrolysis, water splitting, or photosynthetic process applications.

Alien Genetic Algorithm for Exploration of Search Space

NASA Astrophysics Data System (ADS)

Patel, Narendra; Padhiyar, Nitin

2010-10-01

Genetic Algorithm (GA) is a widely accepted population based stochastic optimization technique used for single and multi objective optimization problems. Various versions of modifications in GA have been proposed in last three decades mainly addressing two issues, namely increasing convergence rate and increasing probability of global minima. While both these. While addressing the first issue, GA tends to converge to a local optima and addressing the second issue corresponds the large computational efforts. Thus, to reduce the contradictory effects of these two aspects, we propose a modification in GA by adding an alien member in the population at every generation. Addition of an Alien member in the current population at every generation increases the probability of obtaining global minima at the same time maintaining higher convergence rate. With two test cases, we have demonstrated the efficacy of the proposed GA by comparing with the conventional GA.

Genetic algorithms applied to the scheduling of the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Sponsler, Jeffrey L.

1989-01-01

A prototype system employing a genetic algorithm (GA) has been developed to support the scheduling of the Hubble Space Telescope. A non-standard knowledge structure is used and appropriate genetic operators have been created. Several different crossover styles (random point selection, evolving points, and smart point selection) are tested and the best GA is compared with a neural network (NN) based optimizer. The smart crossover operator produces the best results and the GA system is able to evolve complete schedules using it. The GA is not as time-efficient as the NN system and the NN solutions tend to be better.

Fabrication and characterization of GaN-based light-emitting diodes without pre-activation of p-type GaN.

PubMed

Hu, Xiao-Long; Wang, Hong; Zhang, Xi-Chun

2015-01-01

We fabricated GaN-based light-emitting diodes (LEDs) without pre-activation of p-type GaN. During the fabrication process, a 100-nm-thick indium tin oxide film was served as the p-type contact layer and annealed at 500°C in N2 ambient for 20 min to increase its transparency as well as to activate the p-type GaN. The electrical measurements showed that the LEDs were featured by a lower forward voltage and higher wall-plug efficiency in comparison with LEDs using pre-activation of p-type GaN. We discussed the mechanism of activation of p-type GaN at 500°C in N2 ambient. Furthermore, x-ray photoemission spectroscopy examinations were carried out to study the improved electrical performances of the LEDs without pre-activation of p-type GaN.

Lattice Gas Model Based Optimization of Plasma-Surface Processes for GaN-Based Compound Growth

NASA Astrophysics Data System (ADS)

Nonokawa, Kiyohide; Suzuki, Takuma; Kitamori, Kazutaka; Sawada, Takayuki

2001-10-01

Progress of the epitaxial growth technique for GaN-based compounds makes these materials attractive for applications in high temperature/high-power electronic devices as well as in short-wavelength optoelectronic devices. For MBE growth of GaN epilayer, atomic nitrogen is usually supplied from ECR-plasma while atomic Ga is supplied from conventional K-cell. To grow high-quality epilayer, fundamental knowledge of the detailed atomic process, such as adsorption, surface migration, incorporation, desorption and so forth, is required. We have studied the influence of growth conditions on the flatness of the growth front surface and the growth rate using Monte Carlo simulation based on the lattice gas model. Under the fixed Ga flux condition, the lower the nitrogen flux and/or the higher the growth temperature, the better the flatness of the front surface at the sacrifice of the growth rate of the epilayer. When the nitrogen flux is increased, the growth rate reaches saturation value determined from the Ga flux. At a fixed growth temperature, increasing of nitrogen to Ga flux ratio results in rough surface owing to 3-dimensional island formation. Other characteristics of MBE-GaN growth using ECR-plasma can be well reproduced.

Ultra High p-doping Material Research for GaN Based Light Emitters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vladimir Dmitriev

2007-06-30

The main goal of the Project is to investigate doping mechanisms in p-type GaN and AlGaN and controllably fabricate ultra high doped p-GaN materials and epitaxial structures. Highly doped p-type GaN-based materials with low electrical resistivity and abrupt doping profiles are of great importance for efficient light emitters for solid state lighting (SSL) applications. Cost-effective hydride vapor phase epitaxial (HVPE) technology was proposed to investigate and develop p-GaN materials for SSL. High p-type doping is required to improve (i) carrier injection efficiency in light emitting p-n junctions that will result in increasing of light emitting efficiency, (ii) current spreading inmore » light emitting structures that will improve external quantum efficiency, and (iii) parameters of Ohmic contacts to reduce operating voltage and tolerate higher forward currents needed for the high output power operation of light emitters. Highly doped p-type GaN layers and AlGaN/GaN heterostructures with low electrical resistivity will lead to novel device and contact metallization designs for high-power high efficiency GaN-based light emitters. Overall, highly doped p-GaN is a key element to develop light emitting devices for the DOE SSL program. The project was focused on material research for highly doped p-type GaN materials and device structures for applications in high performance light emitters for general illumination P-GaN and p-AlGaN layers and multi-layer structures were grown by HVPE and investigated in terms of surface morphology and structure, doping concentrations and profiles, optical, electrical, and structural properties. Tasks of the project were successfully accomplished. Highly doped GaN materials with p-type conductivity were fabricated. As-grown GaN layers had concentration N{sub a}-N{sub d} as high as 3 x 10{sup 19} cm{sup -3}. Mechanisms of doping were investigated and results of material studies were reported at several International conferences

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

Knowledge-based tracking algorithm

NASA Astrophysics Data System (ADS)

Corbeil, Allan F.; Hawkins, Linda J.; Gilgallon, Paul F.

1990-10-01

This paper describes the Knowledge-Based Tracking (KBT) algorithm for which a real-time flight test demonstration was recently conducted at Rome Air Development Center (RADC). In KBT processing, the radar signal in each resolution cell is thresholded at a lower than normal setting to detect low RCS targets. This lower threshold produces a larger than normal false alarm rate. Therefore, additional signal processing including spectral filtering, CFAR and knowledge-based acceptance testing are performed to eliminate some of the false alarms. TSC's knowledge-based Track-Before-Detect (TBD) algorithm is then applied to the data from each azimuth sector to detect target tracks. In this algorithm, tentative track templates are formed for each threshold crossing and knowledge-based association rules are applied to the range, Doppler, and azimuth measurements from successive scans. Lastly, an M-association out of N-scan rule is used to declare a detection. This scan-to-scan integration enhances the probability of target detection while maintaining an acceptably low output false alarm rate. For a real-time demonstration of the KBT algorithm, the L-band radar in the Surveillance Laboratory (SL) at RADC was used to illuminate a small Cessna 310 test aircraft. The received radar signal wa digitized and processed by a ST-100 Array Processor and VAX computer network in the lab. The ST-100 performed all of the radar signal processing functions, including Moving Target Indicator (MTI) pulse cancelling, FFT Doppler filtering, and CFAR detection. The VAX computers performed the remaining range-Doppler clustering, beamsplitting and TBD processing functions. The KBT algorithm provided a 9.5 dB improvement relative to single scan performance with a nominal real time delay of less than one second between illumination and display.

GaAs1−xBix/GaNyAs1−y type-II quantum wells: novel strain-balanced heterostructures for GaAs-based near- and mid-infrared photonics

PubMed Central

Broderick, Christopher A.; Jin, Shirong; Marko, Igor P.; Hild, Konstanze; Ludewig, Peter; Bushell, Zoe L.; Stolz, Wolfgang; Rorison, Judy M.; O’Reilly, Eoin P.; Volz, Kerstin; Sweeney, Stephen J.

2017-01-01

The potential to extend the emission wavelength of photonic devices further into the near- and mid-infrared via pseudomorphic growth on conventional GaAs substrates is appealing for a number of communications and sensing applications. We present a new class of GaAs-based quantum well (QW) heterostructure that exploits the unusual impact of Bi and N on the GaAs band structure to produce type-II QWs having long emission wavelengths with little or no net strain relative to GaAs, while also providing control over important laser loss processes. We theoretically and experimentally demonstrate the potential of GaAs1−xBix/GaNyAs1−y type-II QWs on GaAs and show that this approach offers optical emission and absorption at wavelengths up to ~3 µm utilising strain-balanced structures, a first for GaAs-based QWs. Experimental measurements on a prototype GaAs0.967Bi0.033/GaN0.062As0.938 structure, grown via metal-organic vapour phase epitaxy, indicate good structural quality and exhibit both photoluminescence and absorption at room temperature. The measured photoluminescence peak wavelength of 1.72 μm is in good agreement with theoretical calculations and is one of the longest emission wavelengths achieved on GaAs to date using a pseudomorphically grown heterostructure. These results demonstrate the significant potential of this new class of III-V heterostructure for long-wavelength applications. PMID:28422129

GaN light-emitting device based on ionic liquid electrolyte

NASA Astrophysics Data System (ADS)

Hirai, Tomoaki; Sakanoue, Tomo; Takenobu, Taishi

2018-06-01

Ionic liquids (ILs) are attractive materials for fabricating unique hybrid devices based on electronics and electrochemistry; thus, IL-gated transistors and organic light-emitting devices of light-emitting electrochemical cells (LECs) are investigated for future low-voltage and high-performance devices. In LECs, voltage application induces the formation of electrochemically doped p–n homojunctions owing to ion rearrangements in composites of semiconductors and electrolytes, and achieves electron–hole recombination for light emission at the homojunctions. In this work, we applied this concept of IL-induced electrochemical doping to the fabrication of GaN-based light-emitting devices. We found that voltage application to the layered IL/GaN structure accumulated electrons on the GaN surface owing to ion rearrangements and improved the conductivity of GaN. The ion rearrangement also enabled holes to be injected by the strong electric field of electric double layers on hole injection contacts. This simultaneous injection of holes and electrons into GaN mediated by ions achieves light emission at a low voltage of around 3.4 V. The light emission from the simple IL/GaN structure indicates the usefulness of an electrochemical technique in generating light emission with great ease of fabrication.

Detecting REM sleep from the finger: an automatic REM sleep algorithm based on peripheral arterial tone (PAT) and actigraphy.

PubMed

Herscovici, Sarah; Pe'er, Avivit; Papyan, Surik; Lavie, Peretz

2007-02-01

Scoring of REM sleep based on polysomnographic recordings is a laborious and time-consuming process. The growing number of ambulatory devices designed for cost-effective home-based diagnostic sleep recordings necessitates the development of a reliable automatic REM sleep detection algorithm that is not based on the traditional electroencephalographic, electrooccolographic and electromyographic recordings trio. This paper presents an automatic REM detection algorithm based on the peripheral arterial tone (PAT) signal and actigraphy which are recorded with an ambulatory wrist-worn device (Watch-PAT100). The PAT signal is a measure of the pulsatile volume changes at the finger tip reflecting sympathetic tone variations. The algorithm was developed using a training set of 30 patients recorded simultaneously with polysomnography and Watch-PAT100. Sleep records were divided into 5 min intervals and two time series were constructed from the PAT amplitudes and PAT-derived inter-pulse periods in each interval. A prediction function based on 16 features extracted from the above time series that determines the likelihood of detecting a REM epoch was developed. The coefficients of the prediction function were determined using a genetic algorithm (GA) optimizing process tuned to maximize a price function depending on the sensitivity, specificity and agreement of the algorithm in comparison with the gold standard of polysomnographic manual scoring. Based on a separate validation set of 30 patients overall sensitivity, specificity and agreement of the automatic algorithm to identify standard 30 s epochs of REM sleep were 78%, 92%, 89%, respectively. Deploying this REM detection algorithm in a wrist worn device could be very useful for unattended ambulatory sleep monitoring. The innovative method of optimization using a genetic algorithm has been proven to yield robust results in the validation set.

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

NASA Astrophysics Data System (ADS)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

Optimal clustering of MGs based on droop controller for improving reliability using a hybrid of harmony search and genetic algorithms.

PubMed

Abedini, Mohammad; Moradi, Mohammad H; Hosseinian, S M

2016-03-01

This paper proposes a novel method to address reliability and technical problems of microgrids (MGs) based on designing a number of self-adequate autonomous sub-MGs via adopting MGs clustering thinking. In doing so, a multi-objective optimization problem is developed where power losses reduction, voltage profile improvement and reliability enhancement are considered as the objective functions. To solve the optimization problem a hybrid algorithm, named HS-GA, is provided, based on genetic and harmony search algorithms, and a load flow method is given to model different types of DGs as droop controller. The performance of the proposed method is evaluated in two case studies. The results provide support for the performance of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Investigation of HCl-based surface treatment for GaN devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Okada, Hiroshi, E-mail: okada@ee.tut.ac.jp; Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka, Tempaku-cho, Toyohashi 441-8580; Shinohara, Masatohi

2016-02-01

Surface treatments of GaN in HCl-based solutions are studied by X-ray photoelectron spectroscopy (XPS) and electrical characterization of fabricated GaN surfaces. A dilute-HCl treatment (HCl:H{sub 2}O=1:1) at room temperature and a boiled-HCl treatment (undiluted HCl) at 108°C are made on high-temperature annealed n-GaN. From the XPS study, removal of surface oxide by the dilute-HCl treatment was found, and more thoroughly oxide-removal was confirmed in the boiled-HCl treatment. Effect of the surface treatment on electrical characteristics on AlGaN/GaN transistor is also studied by applying treatment processes prior to the surface SiN deposition. Increase of drain current is found in boiled-HCl treatedmore » samples. The results suggest that the boiled-HCl treatment is effective for GaN device fabrication.« less

Linear facing target sputtering of the epitaxial Ga-doped ZnO transparent contact layer on GaN-based light-emitting diodes

NASA Astrophysics Data System (ADS)

Shin, Hyun-Su; Lee, Ju-Hyun; Kwak, Joon-Seop; Lee, Hyun Hwi; Kim, Han-Ki

2013-10-01

In this study, we reported on the plasma damage-free sputtering of epitaxial Ga-doped ZnO (GZO) films on the p-GaN layer for use as a transparent contact layer (TCL) for GaN-based light-emitting diodes (LEDs) using linear facing target sputtering (LFTS). Effective confinement of high-density plasma between faced GZO targets and the substrate position located outside of the plasma region led to the deposition of the epitaxial GZO TCL with a low sheet resistance of 25.7 Ω/s and a high transmittance of 84.6% on a p-GaN layer without severe plasma damage, which was found using the conventional dc sputtering process. The low turn-on voltage of the GaN-based LEDs with an LFTS-grown GZO TCL layer that was grown at a longer target-to-substrate distance (TSD) indicates that the plasma damage of the GaN-LED could be effectively reduced by adjusting the TSD during the LFTS process.

Synthesis design of artificial magnetic metamaterials using a genetic algorithm.

PubMed

Chen, P Y; Chen, C H; Wang, H; Tsai, J H; Ni, W X

2008-08-18

In this article, we present a genetic algorithm (GA) as one branch of artificial intelligence (AI) for the optimization-design of the artificial magnetic metamaterial whose structure is automatically generated by computer through the filling element methodology. A representative design example, metamaterials with permeability of negative unity, is investigated and the optimized structures found by the GA are presented. It is also demonstrated that our approach is effective for the synthesis of functional magnetic and electric metamaterials with optimal structures. This GA-based optimization-design technique shows great versatility and applicability in the design of functional metamaterials.

Effect of interfacial composition on Ag-based Ohmic contact of GaN-based vertical light emitting diodes

NASA Astrophysics Data System (ADS)

Wu, Ning; Xiong, Zhihua; Qin, Zhenzhen

2018-02-01

By investigating the effect of a defective interface structure on Ag-based Ohmic contact of GaN-based vertical light-emitting diodes, we found a direct relationship between the interfacial composition and the Schottky barrier height of the Ag(111)/GaN(0001) interface. It was demonstrated that the Schottky barrier height of a defect-free Ag(111)/GaN(0001) interface was 2.221 eV, and it would be dramatically decreased to 0.375 eV with the introduction of one Ni atom and one Ga vacancy at the interface structure. It was found that the tunability of the Schottky barrier height can be attributed to charge accumulations around the interfacial defective regions and an unpinning of the Fermi level, which explains the experimental phenomenon of Ni-assisted annealing improving the p-type Ohmic contact characteristic. Lastly, we propose a new method of using Cu as an assisted metal to realize a novel Ag-based Ohmic contact. These results provide a guideline for the fabrication of high-quality Ag-based Ohmic contact of GaN-based vertical light-emitting diodes.

Experience with a Genetic Algorithm Implemented on a Multiprocessor Computer

NASA Technical Reports Server (NTRS)

Plassman, Gerald E.; Sobieszczanski-Sobieski, Jaroslaw

2000-01-01

Numerical experiments were conducted to find out the extent to which a Genetic Algorithm (GA) may benefit from a multiprocessor implementation, considering, on one hand, that analyses of individual designs in a population are independent of each other so that they may be executed concurrently on separate processors, and, on the other hand, that there are some operations in a GA that cannot be so distributed. The algorithm experimented with was based on a gaussian distribution rather than bit exchange in the GA reproductive mechanism, and the test case was a hub frame structure of up to 1080 design variables. The experimentation engaging up to 128 processors confirmed expectations of radical elapsed time reductions comparing to a conventional single processor implementation. It also demonstrated that the time spent in the non-distributable parts of the algorithm and the attendant cross-processor communication may have a very detrimental effect on the efficient utilization of the multiprocessor machine and on the number of processors that can be used effectively in a concurrent manner. Three techniques were devised and tested to mitigate that effect, resulting in efficiency increasing to exceed 99 percent.

Clavulanic acid production estimation based on color and structural features of Streptomyces clavuligerus bacteria using self-organizing map and genetic algorithm.

PubMed

Nurmohamadi, Maryam; Pourghassem, Hossein

2014-05-01

The utilization of antibiotics produced by Clavulanic acid (CA) is an increasing need in medicine and industry. Usually, the CA is created from the fermentation of Streptomycen Clavuligerus (SC) bacteria. Analysis of visual and morphological features of SC bacteria is an appropriate measure to estimate the growth of CA. In this paper, an automatic and fast CA production level estimation algorithm based on visual and structural features of SC bacteria instead of statistical methods and experimental evaluation by microbiologist is proposed. In this algorithm, structural features such as the number of newborn branches, thickness of hyphal and bacterial density and also color features such as acceptance color levels are extracted from the SC bacteria. Moreover, PH and biomass of the medium provided by microbiologists are considered as specified features. The level of CA production is estimated by using a new application of Self-Organizing Map (SOM), and a hybrid model of genetic algorithm with back propagation network (GA-BPN). The proposed algorithm is evaluated on four carbonic resources including malt, starch, wheat flour and glycerol that had used as different mediums of bacterial growth. Then, the obtained results are compared and evaluated with observation of specialist. Finally, the Relative Error (RE) for the SOM and GA-BPN are achieved 14.97% and 16.63%, respectively. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Peak-to-average power ratio reduction in orthogonal frequency division multiplexing-based visible light communication systems using a modified partial transmit sequence technique

NASA Astrophysics Data System (ADS)

Liu, Yan; Deng, Honggui; Ren, Shuang; Tang, Chengying; Qian, Xuewen

2018-01-01

We propose an efficient partial transmit sequence technique based on genetic algorithm and peak-value optimization algorithm (GAPOA) to reduce high peak-to-average power ratio (PAPR) in visible light communication systems based on orthogonal frequency division multiplexing (VLC-OFDM). By analysis of hill-climbing algorithm's pros and cons, we propose the POA with excellent local search ability to further process the signals whose PAPR is still over the threshold after processed by genetic algorithm (GA). To verify the effectiveness of the proposed technique and algorithm, we evaluate the PAPR performance and the bit error rate (BER) performance and compare them with partial transmit sequence (PTS) technique based on GA (GA-PTS), PTS technique based on genetic and hill-climbing algorithm (GH-PTS), and PTS based on shuffled frog leaping algorithm and hill-climbing algorithm (SFLAHC-PTS). The results show that our technique and algorithm have not only better PAPR performance but also lower computational complexity and BER than GA-PTS, GH-PTS, and SFLAHC-PTS technique.

Perspective: Toward efficient GaN-based red light emitting diodes using europium doping

NASA Astrophysics Data System (ADS)

Mitchell, Brandon; Dierolf, Volkmar; Gregorkiewicz, Tom; Fujiwara, Yasufumi

2018-04-01

While InGaN/GaN blue and green light-emitting diodes (LEDs) are commercially available, the search for an efficient red LED based on GaN is ongoing. The realization of this LED is crucial for the monolithic integration of the three primary colors and the development of nitride-based full-color high-resolution displays. In this perspective, we will address the challenges of attaining red luminescence from GaN under current injection and the methods that have been developed to circumvent them. While several approaches will be mentioned, a large emphasis will be placed on the recent developments of doping GaN with Eu3+ to achieve an efficient red GaN-based LED. Finally, we will provide an outlook to the future of this material as a candidate for small scale displays such as mobile device screens or micro-LED displays.

Using and comparing metaheuristic algorithms for optimizing bidding strategy viewpoint of profit maximization of generators

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Hosein; Nazemi, Ali; Hafezalkotob, Ashkan

2015-03-01

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous optimization of multiple parameters. The problem is formulated analytically using the Nash equilibrium concept for games composed of large numbers of players having discrete and large strategy spaces. The solution methodology is based on a characterization of Nash equilibrium in terms of minima of a function and relies on a metaheuristic optimization approach to find these minima. This paper presents some metaheuristic algorithms to simulate how generators bid in the spot electricity market viewpoint of their profit maximization according to the other generators' strategies, such as genetic algorithm (GA), simulated annealing (SA) and hybrid simulated annealing genetic algorithm (HSAGA) and compares their results. As both GA and SA are generic search methods, HSAGA is also a generic search method. The model based on the actual data is implemented in a peak hour of Tehran's wholesale spot market in 2012. The results of the simulations show that GA outperforms SA and HSAGA on computing time, number of function evaluation and computing stability, as well as the results of calculated Nash equilibriums by GA are less various and different from each other than the other algorithms.

Impact ionisation in Al0.9Ga0.1As0.08Sb0.92 for Sb-based avalanche photodiodes

NASA Astrophysics Data System (ADS)

Collins, X.; Craig, A. P.; Roblin, T.; Marshall, A. R. J.

2018-01-01

We report the impact ionisation coefficients of the quaternary alloy Al0.9Ga0.1As0.08Sb0.92 lattice matched to GaSb substrates within the field range of 150 to 550 kV cm-1 using p-i-n and n-i-p diodes of various intrinsic thicknesses. The coefficients were found with an evolutionary fitting algorithm using a non-local recurrence based multiplication model and a variable electric field profile. These coefficients indicate that an avalanche photodiode not only can be designed to be a function in the mid-wave infrared but also can be operated at lower voltages. This is due to the high magnitude of the impact ionisation coefficients at relatively low fields compared to other III-V materials typically used in avalanche multiplication regions.

Comparison of genetic algorithm and imperialist competitive algorithms in predicting bed load transport in clean pipe.

PubMed

Ebtehaj, Isa; Bonakdari, Hossein

2014-01-01

The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations.

GaN-Based Detector Enabling Technology for Next Generation Ultraviolet Planetary Missions

NASA Technical Reports Server (NTRS)

Aslam, S.; Gronoff, G.; Hewagama, T.; Janz, S.; Kotecki, C.

2012-01-01

The ternary alloy AlN-GaN-InN system provides several distinct advantages for the development of UV detectors for future planetary missions. First, (InN), (GaN) and (AlN) have direct bandgaps 0.8, 3.4 and 6.2 eV, respectively, with corresponding wavelength cutoffs of 1550 nm, 365 nm and 200 nm. Since they are miscible with each other, these nitrides form complete series of indium gallium nitride (In(sub l-x)Ga(sub x)N) and aluminum gallium nitride (Al(sub l-x)Ga(sub x)N) alloys thus allowing the development of detectors with a wavelength cut-off anywhere in this range. For the 2S0-365 nm spectral wavelength range AlGaN detectors can be designed to give a 1000x solar radiation rejection at cut-off wavelength of 325 nm, than can be achieved with Si based detectors. For tailored wavelength cut-offs in the 365-4S0 nm range, InGaN based detectors can be fabricated, which still give 20-40x better solar radiation rejection than Si based detectors. This reduced need for blocking filters greatly increases the Detective Quantum efficiency (DQE) and simplifies the instrument's optical systems. Second, the wide direct bandgap reduces the thermally generated dark current to levels allowing many observations to be performed at room temperature. Third, compared to narrow bandgap materials, wide bandgap semiconductors are significantly more radiation tolerant. Finally, with the use of an (AI, In)GaN array, the overall system cost is reduced by eliminating stringent Si CCD cooling systems. Compared to silicon, GaN based detectors have superior QE based on a direct bandgap and longer absorption lengths in the UV.

The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

NASA Astrophysics Data System (ADS)

Abedini, M. J.; Nasseri, M.; Burn, D. H.

2012-04-01

In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

Design and simulation of GaN based Schottky betavoltaic nuclear micro-battery.

PubMed

San, Haisheng; Yao, Shulin; Wang, Xiang; Cheng, Zaijun; Chen, Xuyuan

2013-10-01

The current paper presents a theoretical analysis of Ni-63 nuclear micro-battery based on a wide-band gap semiconductor GaN thin-film covered with thin Ni/Au films to form Schottky barrier for carrier separation. The total energy deposition in GaN was calculated using Monte Carlo methods by taking into account the full beta spectral energy, which provided an optimal design on Schottky barrier width. The calculated results show that an 8 μm thick Schottky barrier can collect about 95% of the incident beta particle energy. Considering the actual limitations of current GaN growth technique, a Fe-doped compensation technique by MOCVD method can be used to realize the n-type GaN with a carrier concentration of 1×10(15) cm(-3), by which a GaN based Schottky betavoltaic micro-battery can achieve an energy conversion efficiency of 2.25% based on the theoretical calculations of semiconductor device physics. Copyright © 2013 Elsevier Ltd. All rights reserved.

Use of genetic algorithm for the selection of EEG features

NASA Astrophysics Data System (ADS)

Asvestas, P.; Korda, A.; Kostopoulos, S.; Karanasiou, I.; Ouzounoglou, A.; Sidiropoulos, K.; Ventouras, E.; Matsopoulos, G.

2015-09-01

Genetic Algorithm (GA) is a popular optimization technique that can detect the global optimum of a multivariable function containing several local optima. GA has been widely used in the field of biomedical informatics, especially in the context of designing decision support systems that classify biomedical signals or images into classes of interest. The aim of this paper is to present a methodology, based on GA, for the selection of the optimal subset of features that can be used for the efficient classification of Event Related Potentials (ERPs), which are recorded during the observation of correct or incorrect actions. In our experiment, ERP recordings were acquired from sixteen (16) healthy volunteers who observed correct or incorrect actions of other subjects. The brain electrical activity was recorded at 47 locations on the scalp. The GA was formulated as a combinatorial optimizer for the selection of the combination of electrodes that maximizes the performance of the Fuzzy C Means (FCM) classification algorithm. In particular, during the evolution of the GA, for each candidate combination of electrodes, the well-known (Σ, Φ, Ω) features were calculated and were evaluated by means of the FCM method. The proposed methodology provided a combination of 8 electrodes, with classification accuracy 93.8%. Thus, GA can be the basis for the selection of features that discriminate ERP recordings of observations of correct or incorrect actions.

Simplified gas sensor model based on AlGaN/GaN heterostructure Schottky diode

DOE Office of Scientific and Technical Information (OSTI.GOV)

Das, Subhashis, E-mail: subhashis.ds@gmail.com; Majumdar, S.; Kumar, R.

2015-08-28

Physics based modeling of AlGaN/GaN heterostructure Schottky diode gas sensor has been investigated for high sensitivity and linearity of the device. Here the surface and heterointerface properties are greatly exploited. The dependence of two dimensional electron gas (2DEG) upon the surface charges is mainly utilized. The simulation of Schottky diode has been done in Technology Computer Aided Design (TCAD) tool and I-V curves are generated, from the I-V curves 76% response has been recorded in presence of 500 ppm gas at a biasing voltage of 0.95 Volt.

Progress and prospects of GaN-based LEDs using nanostructures

NASA Astrophysics Data System (ADS)

Zhao, Li-Xia; Yu, Zhi-Guo; Sun, Bo; Zhu, Shi-Chao; An, Ping-Bo; Yang, Chao; Liu, Lei; Wang, Jun-Xi; Li, Jin-Min

2015-06-01

Progress with GaN-based light emitting diodes (LEDs) that incorporate nanostructures is reviewed, especially the recent achievements in our research group. Nano-patterned sapphire substrates have been used to grow an AlN template layer for deep-ultraviolet (DUV) LEDs. One efficient surface nano-texturing technology, hemisphere-cones-hybrid nanostructures, was employed to enhance the extraction efficiency of InGaN flip-chip LEDs. Hexagonal nanopyramid GaN-based LEDs have been fabricated and show electrically driven color modification and phosphor-free white light emission because of the linearly increased quantum well width and indium incorporation from the shell to the core. Based on the nanostructures, we have also fabricated surface plasmon-enhanced nanoporous GaN-based green LEDs using AAO membrane as a mask. Benefitting from the strong lateral SP coupling as well as good electrical protection by a passivation layer, the EL intensity of an SP-enhanced nanoporous LED was significantly enhanced by 380%. Furthermore, nanostructures have been used for the growth of GaN LEDs on amorphous substrates, the fabrication of stretchable LEDs, and for increasing the 3-dB modulation bandwidth for visible light communication. Project supported by the National Natural Science Foundation of China (Grant No. 61334009), the National High Technology Research and Development Program of China (Grant Nos. 2015AA03A101 and 2014BAK02B08), China International Science and Technology Cooperation Program (Grant No. 2014DFG62280), the “Import Outstanding Technical Talent Plan” and “Youth Innovation Promotion Association Program” of the Chinese Academy of Sciences.

Hybrid employment recommendation algorithm based on Spark

NASA Astrophysics Data System (ADS)

Li, Zuoquan; Lin, Yubei; Zhang, Xingming

2017-08-01

Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.

Comparison of Metabolic Pathways in Escherichia coli by Using Genetic Algorithms.

PubMed

Ortegon, Patricia; Poot-Hernández, Augusto C; Perez-Rueda, Ernesto; Rodriguez-Vazquez, Katya

2015-01-01

In order to understand how cellular metabolism has taken its modern form, the conservation and variations between metabolic pathways were evaluated by using a genetic algorithm (GA). The GA approach considered information on the complete metabolism of the bacterium Escherichia coli K-12, as deposited in the KEGG database, and the enzymes belonging to a particular pathway were transformed into enzymatic step sequences by using the breadth-first search algorithm. These sequences represent contiguous enzymes linked to each other, based on their catalytic activities as they are encoded in the Enzyme Commission numbers. In a posterior step, these sequences were compared using a GA in an all-against-all (pairwise comparisons) approach. Individual reactions were chosen based on their measure of fitness to act as parents of offspring, which constitute the new generation. The sequences compared were used to construct a similarity matrix (of fitness values) that was then considered to be clustered by using a k-medoids algorithm. A total of 34 clusters of conserved reactions were obtained, and their sequences were finally aligned with a multiple-sequence alignment GA optimized to align all the reaction sequences included in each group or cluster. From these comparisons, maps associated with the metabolism of similar compounds also contained similar enzymatic step sequences, reinforcing the Patchwork Model for the evolution of metabolism in E. coli K-12, an observation that can be expanded to other organisms, for which there is metabolism information. Finally, our mapping of these reactions is discussed, with illustrations from a particular case.

Comparison of Metabolic Pathways in Escherichia coli by Using Genetic Algorithms

PubMed Central

Ortegon, Patricia; Poot-Hernández, Augusto C.; Perez-Rueda, Ernesto; Rodriguez-Vazquez, Katya

2015-01-01

In order to understand how cellular metabolism has taken its modern form, the conservation and variations between metabolic pathways were evaluated by using a genetic algorithm (GA). The GA approach considered information on the complete metabolism of the bacterium Escherichia coli K-12, as deposited in the KEGG database, and the enzymes belonging to a particular pathway were transformed into enzymatic step sequences by using the breadth-first search algorithm. These sequences represent contiguous enzymes linked to each other, based on their catalytic activities as they are encoded in the Enzyme Commission numbers. In a posterior step, these sequences were compared using a GA in an all-against-all (pairwise comparisons) approach. Individual reactions were chosen based on their measure of fitness to act as parents of offspring, which constitute the new generation. The sequences compared were used to construct a similarity matrix (of fitness values) that was then considered to be clustered by using a k-medoids algorithm. A total of 34 clusters of conserved reactions were obtained, and their sequences were finally aligned with a multiple-sequence alignment GA optimized to align all the reaction sequences included in each group or cluster. From these comparisons, maps associated with the metabolism of similar compounds also contained similar enzymatic step sequences, reinforcing the Patchwork Model for the evolution of metabolism in E. coli K-12, an observation that can be expanded to other organisms, for which there is metabolism information. Finally, our mapping of these reactions is discussed, with illustrations from a particular case. PMID:25973143

Laser diode bars based on strain-compensated AlGaPAs/GaAs heterostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marmalyuk, Aleksandr A; Ladugin, M A; Yarotskaya, I V

2012-01-31

Traditional (in the AlGaAs/GaAs system) and phosphorus-compensated (in the AlGaAs/AlGaPAs/GaAs system) laser heterostructures emitting at a wavelength of 850 nm are grown by MOVPE and studied. Laser diode bars are fabricated and their output characteristics are studied. The method used to grow heterolayers allowed us to control (minimise) mechanical stresses in the AlGaPAs/GaAs laser heterostructure, which made it possible to keep its curvature at the level of the initial curvature of the substrate. It is shown that the use of a compensated AlGaPAs/GaAs heterostructure improves the linear distribution of emitting elements in the near field of laser diode arrays andmore » allows the power - current characteristic to retain its slope at high pump currents owing to a uniform contact of all emitting elements with the heat sink. The radius of curvature of the grown compensated heterostructures turns out to be smaller than that of traditional heterostructures.« less

The thickness design of unintentionally doped GaN interlayer matched with background doping level for InGaN-based laser diodes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, P.; Zhao, D. G., E-mail: dgzhao@red.semi.ac.cn; Jiang, D. S.

2016-03-15

In order to reduce the internal optical loss of InGaN laser diodes, an unintentionally doped GaN (u-GaN) interlayer is inserted between InGaN/GaN multiple quantum well active region and Al{sub 0.2}Ga{sub 0.8}N electron blocking layer. The thickness design of u-GaN interlayer matching up with background doping level for improving laser performance is studied. It is found that a suitably chosen u-GaN interlayer can well modulate the optical absorption loss and optical confinement factor. However, if the value of background doping concentration of u-GaN interlayer is too large, the output light power may decrease. The analysis of energy band diagram of amore » LD structure with 100 nm u-GaN interlayer shows that the width of n-side depletion region decreases when the background concentration increases, and may become even too small to cover whole MQW, resulting in a serious decrease of the output light power. It means that a suitable interlayer thickness design matching with the background doping level of u-GaN interlayer is significant for InGaN-based laser diodes.« less

Hyperspectral recognition of processing tomato early blight based on GA and SVM

NASA Astrophysics Data System (ADS)

Yin, Xiaojun; Zhao, SiFeng

2013-03-01

Processing tomato early blight seriously affect the yield and quality of its.Determine the leaves spectrum of different disease severity level of processing tomato early blight.We take the sensitive bands of processing tomato early blight as support vector machine input vector.Through the genetic algorithm(GA) to optimize the parameters of SVM, We could recognize different disease severity level of processing tomato early blight.The result show:the sensitive bands of different disease severity levels of processing tomato early blight is 628-643nm and 689-692nm.The sensitive bands are as the GA and SVM input vector.We get the best penalty parameters is 0.129 and kernel function parameters is 3.479.We make classification training and testing by polynomial nuclear,radial basis function nuclear,Sigmoid nuclear.The best classification model is the radial basis function nuclear of SVM. Training accuracy is 84.615%,Testing accuracy is 80.681%.It is combined GA and SVM to achieve multi-classification of processing tomato early blight.It is provided the technical support of prediction processing tomato early blight occurrence, development and diffusion rule in large areas.

A study of GaN-based LED structure etching using inductively coupled plasma

NASA Astrophysics Data System (ADS)

Wang, Pei; Cao, Bin; Gan, Zhiyin; Liu, Sheng

2011-02-01

GaN as a wide band gap semiconductor has been employed to fabricate optoelectronic devices such as light-emitting diodes (LEDs) and laser diodes (LDs). Recently several different dry etching techniques for GaN-based materials have been developed. ICP etching is attractive because of its superior plasma uniformity and strong controllability. Most previous reports emphasized on the ICP etching characteristics of single GaN film. In this study dry etching of GaN-based LED structure was performed by inductively coupled plasmas (ICP) etching with Cl2 as the base gas and BCl3 as the additive gas. The effects of the key process parameters such as etching gases flow rate, ICP power, RF power and chamber pressure on the etching properties of GaN-based LED structure including etching rate, selectivity, etched surface morphology and sidewall was investigated. Etch depths were measured using a depth profilometer and used to calculate the etch rates. The etch profiles were observed with a scanning electron microscope (SEM).

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

NASA Astrophysics Data System (ADS)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

N-polar InGaN-based LEDs fabricated on sapphire via pulsed sputtering

NASA Astrophysics Data System (ADS)

Ueno, Kohei; Kishikawa, Eiji; Ohta, Jitsuo; Fujioka, Hiroshi

2017-02-01

High-quality N-polar GaN epitaxial films with an atomically flat surface were grown on sapphire (0001) via pulsed sputtering deposition, and their structural and electrical properties were investigated. The crystalline quality of N-polar GaN improves with increasing film thickness and the full width at half maximum values of the x-ray rocking curves for 0002 and 101 ¯ 2 diffraction were 313 and 394 arcsec, respectively, at the film thickness of 6 μ m . Repeatable p-type doping in N-polar GaN films was achieved using Mg dopant, and their hole concentration and mobility can be controlled in the range of 8 × 1016-2 × 1018 cm-3 and 2-9 cm2V-1s-1, respectively. The activation energy of Mg in N-polar GaN based on a temperature-dependent Hall measurement was estimated to be 161 meV, which is comparable to that of the Ga-polar GaN. Based on these results, we demonstrated the fabrication of N-polar InGaN-based light emitting diodes with the long wavelength up to 609 nm.

Optimization of HAART with genetic algorithms and agent-based models of HIV infection.

PubMed

Castiglione, F; Pappalardo, F; Bernaschi, M; Motta, S

2007-12-15

Highly Active AntiRetroviral Therapies (HAART) can prolong life significantly to people infected by HIV since, although unable to eradicate the virus, they are quite effective in maintaining control of the infection. However, since HAART have several undesirable side effects, it is considered useful to suspend the therapy according to a suitable schedule of Structured Therapeutic Interruptions (STI). In the present article we describe an application of genetic algorithms (GA) aimed at finding the optimal schedule for a HAART simulated with an agent-based model (ABM) of the immune system that reproduces the most significant features of the response of an organism to the HIV-1 infection. The genetic algorithm helps in finding an optimal therapeutic schedule that maximizes immune restoration, minimizes the viral count and, through appropriate interruptions of the therapy, minimizes the dose of drug administered to the simulated patient. To validate the efficacy of the therapy that the genetic algorithm indicates as optimal, we ran simulations of opportunistic diseases and found that the selected therapy shows the best survival curve among the different simulated control groups. A version of the C-ImmSim simulator is available at http://www.iac.cnr.it/~filippo/c-ImmSim.html

QPSO-Based Adaptive DNA Computing Algorithm

PubMed Central

Karakose, Mehmet; Cigdem, Ugur

2013-01-01

DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm. PMID:23935409

Oxygen-induced high diffusion rate of magnesium dopants in GaN/AlGaN based UV LED heterostructures.

PubMed

Michałowski, Paweł Piotr; Złotnik, Sebastian; Sitek, Jakub; Rosiński, Krzysztof; Rudziński, Mariusz

2018-05-23

Further development of GaN/AlGaN based optoelectronic devices requires optimization of the p-type material growth process. In particular, uncontrolled diffusion of Mg dopants may decrease the performance of a device. Thus it is meaningful to study the behavior of Mg and the origins of its diffusion in detail. In this work we have employed secondary ion mass spectrometry to study the diffusion of magnesium in GaN/AlGaN structures. We show that magnesium has a strong tendency to form Mg-H complexes which immobilize Mg atoms and restrain their diffusion. However, these complexes are not present in samples post-growth annealed in an oxygen atmosphere or Al-rich AlGaN structures which naturally have a high oxygen concentration. In these samples, more Mg atoms are free to diffuse and thus the average diffusion length is considerably larger than for a sample annealed in an inert atmosphere.

High-Temperature Growth of GaN and Al x Ga1- x N via Ammonia-Based Metalorganic Molecular-Beam Epitaxy

NASA Astrophysics Data System (ADS)

Billingsley, Daniel; Henderson, Walter; Doolittle, W. Alan

2010-05-01

The effect of high-temperature growth on the crystalline quality and surface morphology of GaN and Al x Ga1- x N grown by ammonia-based metalorganic molecular-beam epitaxy (NH3-MOMBE) has been investigated as a means of producing atomically smooth films suitable for device structures. The effects of V/III ratio on the growth rate and surface morphology are described herein. The crystalline quality of both GaN and AlGaN was found to mimic that of the GaN templates, with (002) x-ray diffraction (XRD) full-widths at half- maximum (FWHMs) of ~350 arcsec. Nitrogen-rich growth conditions have been found to provide optimal surface morphologies with a root-mean-square (RMS) roughness of ~0.8 nm, yet excessive N-rich environments have been found to reduce the growth rate and result in the formation of faceted surface pitting. AlGaN exhibits a decreased growth rate, as compared with GaN, due to increased N recombination as a result of the increased pyrolysis of NH3 in the presence of Al. AlGaN films grown directly on GaN templates exhibited Pendellösung x-ray fringes, indicating an abrupt interface and a planar AlGaN film. AlGaN films grown for this study resulted in an optimal RMS roughness of ~0.85 nm with visible atomic steps.

p -n Junction Rectifying Characteristics of Purely n -Type GaN-Based Structures

NASA Astrophysics Data System (ADS)

Zuo, P.; Jiang, Y.; Ma, Z. G.; Wang, L.; Zhao, B.; Li, Y. F.; Yue, G.; Wu, H. Y.; Yan, H. J.; Jia, H. Q.; Wang, W. X.; Zhou, J. M.; Sun, Q.; Liu, W. M.; Ji, An-Chun; Chen, H.

2017-08-01

The GaN-based p -n junction rectifications are important in the development of high-power electronics. Here, we demonstrate that p -n junction rectifying characteristics can be realized with pure n -type structures by inserting an (In,Ga)N quantum well into the GaN /(Al ,Ga )N /GaN double heterostructures. Unlike the usual barriers, the insertion of an (In,Ga)N quantum well, which has an opposite polarization field to that of the (Al,Ga)N barrier, tailors significantly the energy bands of the system. The lifted energy level of the GaN spacer and the formation of the (In ,Ga )N /GaN interface barrier can improve the reverse threshold voltage and reduce the forward threshold voltage simultaneously, forming the p -n junction rectifying characteristics.

Hybrid modelling based on support vector regression with genetic algorithms in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain).

PubMed

García Nieto, P J; Alonso Fernández, J R; de Cos Juez, F J; Sánchez Lasheras, F; Díaz Muñiz, C

2013-04-01

Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational waters. As a result, anticipate its presence is a matter of importance to prevent risks. The aim of this study is to use a hybrid approach based on support vector regression (SVR) in combination with genetic algorithms (GAs), known as a genetic algorithm support vector regression (GA-SVR) model, in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain). The GA-SVR approach is aimed at highly nonlinear biological problems with sharp peaks and the tests carried out proved its high performance. Some physical-chemical parameters have been considered along with the biological ones. The results obtained are two-fold. In the first place, the significance of each biological and physical-chemical variable on the cyanotoxins presence in the reservoir is determined with success. Finally, a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained. Copyright © 2013 Elsevier Inc. All rights reserved.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Scalability problems of simple genetic algorithms.

PubMed

Thierens, D

1999-01-01

Scalable evolutionary computation has become an intensively studied research topic in recent years. The issue of scalability is predominant in any field of algorithmic design, but it became particularly relevant for the design of competent genetic algorithms once the scalability problems of simple genetic algorithms were understood. Here we present some of the work that has aided in getting a clear insight in the scalability problems of simple genetic algorithms. Particularly, we discuss the important issue of building block mixing. We show how the need for mixing places a boundary in the GA parameter space that, together with the boundary from the schema theorem, delimits the region where the GA converges reliably to the optimum in problems of bounded difficulty. This region shrinks rapidly with increasing problem size unless the building blocks are tightly linked in the problem coding structure. In addition, we look at how straightforward extensions of the simple genetic algorithm-namely elitism, niching, and restricted mating are not significantly improving the scalability problems.

GaN-based light-emitting diodes on various substrates: a critical review.

PubMed

Li, Guoqiang; Wang, Wenliang; Yang, Weijia; Lin, Yunhao; Wang, Haiyan; Lin, Zhiting; Zhou, Shizhong

2016-05-01

GaN and related III-nitrides have attracted considerable attention as promising materials for application in optoelectronic devices, in particular, light-emitting diodes (LEDs). At present, sapphire is still the most popular commercial substrate for epitaxial growth of GaN-based LEDs. However, due to its relatively large lattice mismatch with GaN and low thermal conductivity, sapphire is not the most ideal substrate for GaN-based LEDs. Therefore, in order to obtain high-performance and high-power LEDs with relatively low cost, unconventional substrates, which are of low lattice mismatch with GaN, high thermal conductivity and low cost, have been tried as substitutes for sapphire. As a matter of fact, it is not easy to obtain high-quality III-nitride films on those substrates for various reasons. However, by developing a variety of techniques, distincts progress has been made during the past decade, with high-performance LEDs being successfully achieved on these unconventional substrates. This review focuses on state-of-the-art high-performance GaN-based LED materials and devices on unconventional substrates. The issues involved in the growth of GaN-based LED structures on each type of unconventional substrate are outlined, and the fundamental physics behind these issues is detailed. The corresponding solutions for III-nitride growth, defect control, and chip processing for each type of unconventional substrate are discussed in depth, together with a brief introduction to some newly developed techniques in order to realize LED structures on unconventional substrates. This is very useful for understanding the progress in this field of physics. In this review, we also speculate on the prospects for LEDs on unconventional substrates.

The prediction in computer color matching of dentistry based on GA+BP neural network.

PubMed

Li, Haisheng; Lai, Long; Chen, Li; Lu, Cheng; Cai, Qiang

2015-01-01

Although the use of computer color matching can reduce the influence of subjective factors by technicians, matching the color of a natural tooth with a ceramic restoration is still one of the most challenging topics in esthetic prosthodontics. Back propagation neural network (BPNN) has already been introduced into the computer color matching in dentistry, but it has disadvantages such as unstable and low accuracy. In our study, we adopt genetic algorithm (GA) to optimize the initial weights and threshold values in BPNN for improving the matching precision. To our knowledge, we firstly combine the BPNN with GA in computer color matching in dentistry. Extensive experiments demonstrate that the proposed method improves the precision and prediction robustness of the color matching in restorative dentistry.

Vertical decomposition with Genetic Algorithm for Multiple Sequence Alignment

PubMed Central

2011-01-01

Background Many Bioinformatics studies begin with a multiple sequence alignment as the foundation for their research. This is because multiple sequence alignment can be a useful technique for studying molecular evolution and analyzing sequence structure relationships. Results In this paper, we have proposed a Vertical Decomposition with Genetic Algorithm (VDGA) for Multiple Sequence Alignment (MSA). In VDGA, we divide the sequences vertically into two or more subsequences, and then solve them individually using a guide tree approach. Finally, we combine all the subsequences to generate a new multiple sequence alignment. This technique is applied on the solutions of the initial generation and of each child generation within VDGA. We have used two mechanisms to generate an initial population in this research: the first mechanism is to generate guide trees with randomly selected sequences and the second is shuffling the sequences inside such trees. Two different genetic operators have been implemented with VDGA. To test the performance of our algorithm, we have compared it with existing well-known methods, namely PRRP, CLUSTALX, DIALIGN, HMMT, SB_PIMA, ML_PIMA, MULTALIGN, and PILEUP8, and also other methods, based on Genetic Algorithms (GA), such as SAGA, MSA-GA and RBT-GA, by solving a number of benchmark datasets from BAliBase 2.0. Conclusions The experimental results showed that the VDGA with three vertical divisions was the most successful variant for most of the test cases in comparison to other divisions considered with VDGA. The experimental results also confirmed that VDGA outperformed the other methods considered in this research. PMID:21867510

InGaAs/GaAsSb Type-II superlattice based photodiodes for short wave infrared detection

NASA Astrophysics Data System (ADS)

Uliel, Y.; Cohen-Elias, D.; Sicron, N.; Grimberg, I.; Snapi, N.; Paltiel, Y.; Katz, M.

2017-08-01

Short Wave Infra-Red (SWIR) photodetectors operating above the response cutoff of InGaAs- based detectors (1.7-2.5 μm) are required for both defense and civil applications. Type II Super-Lattices (T2SL) were recently proposed For near- room temperature SWIR detection as a possible system enabling bandgap adjustment in the required range. The work presented here focuses on a T2SL with alternating nano-layers of InGaAs and GaAsSb lattice-matched to an InP substrate. A near room temperature SWIR cutoff of 2.4 μm was measured. Electrical junctions were realized using Zn diffusion p-doping process. We realized and studied both mesa- and selective diffusion- based p-i-n photodiodes. Dark currents of mesa-based devices were 1.5 mA/cm2 and 32 μA/cm2 at 300 and 230 K respectively. Dark currents were reduced to 1.2 mA/cm2 and 12 μA/cm2 respectively by utilizing the selective diffusion process. The effect of operating voltage is discussed. At 300 K the quantum efficiency was up to 40% at 2.18 μm in mesa devices. D∗ was 1.7 ×1010cm ·√{Hz } /W at 2 μm.

Robust MST-Based Clustering Algorithm.

PubMed

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

GaN Based Electronics And Their Applications

NASA Astrophysics Data System (ADS)

Ren, Fan

2002-03-01

The Group III-nitrides were initially researched for their promise to fill the void for a blue solid state light emitter. Electronic devices from III-nitrides have been a more recent phenomenon. The thermal conductivity of GaN is three times that of GaAs. For high power or high temperature applications, good thermal conductivity is imperative for heat removal or sustained operation at elevated temperatures. The development of III-N and other wide bandgap technologies for high temperature applications will likely take place at the expense of competing technologies, such as silicon-on-insulator (SOI), at moderate temperatures. At higher temperatures (>300°C), novel devices and components will become possible. The automotive industry will likely be one of the largest markets for such high temperature electronics. One of the most noteworthy advantages for III-N materials over other wide bandgap semiconductors is the availability of AlGaN/GaN and InGaN/GaN heterostructures. A 2-dimensional electron gas (2DEG) has been shown to exist at the AlGaN/GaN interface, and heterostructure field effect transistors (HFETs) from these materials can exhibit 2DEG mobilities approaching 2000 cm2 / V?s at 300K. Power handling capabilities of 12 W/mm appear feasible, and extraordinary large signal performance has already been demonstrated, with a current state-of-the-art of >10W/mm at X-band. In this talk, high speed and high temperature AlGaN/GaN HEMTs as well as MOSHEMTs, high breakdown voltage GaN (>6KV) and AlGaN (9.7 KV) Schottky diodes, and their applications will be presented.

Routing design and fleet allocation optimization of freeway service patrol: Improved results using genetic algorithm

NASA Astrophysics Data System (ADS)

Sun, Xiuqiao; Wang, Jian

2018-07-01

Freeway service patrol (FSP), is considered to be an effective method for incident management and can help transportation agency decision-makers alter existing route coverage and fleet allocation. This paper investigates the FSP problem of patrol routing design and fleet allocation, with the objective of minimizing the overall average incident response time. While the simulated annealing (SA) algorithm and its improvements have been applied to solve this problem, they often become trapped in local optimal solution. Moreover, the issue of searching efficiency remains to be further addressed. In this paper, we employ the genetic algorithm (GA) and SA to solve the FSP problem. To maintain population diversity and avoid premature convergence, niche strategy is incorporated into the traditional genetic algorithm. We also employ elitist strategy to speed up the convergence. Numerical experiments have been conducted with the help of the Sioux Falls network. Results show that the GA slightly outperforms the dual-based greedy (DBG) algorithm, the very large-scale neighborhood searching (VLNS) algorithm, the SA algorithm and the scenario algorithm.

An Intelligent Model for Pairs Trading Using Genetic Algorithms

PubMed Central

Hsu, Chi-Jen; Chen, Chi-Chung; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice. PMID:26339236

An Intelligent Model for Pairs Trading Using Genetic Algorithms.

PubMed

Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

GaSbBi/GaSb quantum-well and wire laser diodes

NASA Astrophysics Data System (ADS)

Ridene, Said

2018-06-01

In this work, we present detailed theoretical studies of the optical gain spectra and the emission wavelength of GaSb1-xBix/GaSb and traditional GaAs1-xBix/GaAs dilute-bismide quantum wells and wires (QWs, QWRs) focusing on comparison between their performances. It is found that the optical gain and the emission wavelength of the GaSb-based QW and QWRs lasers would be considerably greater than that of the GaAs-based QW lasers and QWRs for the same QW-, QWR-width, Bi-content and carrier density. The theoretical results were found to be in good agreement with available experimental data, especially for the emission wavelength given by GaSb-based QW laser diodes.

Progress and challenges in electrically pumped GaN-based VCSELs

NASA Astrophysics Data System (ADS)

Haglund, A.; Hashemi, E.; Bengtsson, J.; Gustavsson, J.; Stattin, M.; Calciati, M.; Goano, M.

2016-04-01

ABSTRACT The Vertical-Cavity Surface-Emitting Laser (VCSEL) is an established optical source in short-distance optical communication links, computer mice and tailored infrared power heating systems. Its low power consumption, easy integration into two-dimensional arrays, and low-cost manufacturing also make this type of semiconductor laser suitable for application in areas such as high-resolution printing, medical applications, and general lighting. However, these applications require emission wavelengths in the blue-UV instead of the established infrared regime, which can be achieved by using GaN-based instead of GaAs-based materials. The development of GaN-based VCSELs is challenging, but during recent years several groups have managed to demonstrate electrically pumped GaN-based VCSELs with close to 1 mW of optical output power and threshold current densities between 3-16 kA/cm2. The performance is limited by challenges such as achieving high-reflectivity mirrors, vertical and lateral carrier confinement, efficient lateral current spreading, accurate cavity length control and lateral optical mode confinement. This paper summarizes different strategies to solve these issues in electrically pumped GaN-VCSELs together with state-of-the-art results. We will highlight our work on combined transverse current and optical mode confinement, where we show that many structures used for current confinement result in unintentionally optically anti-guided resonators. Such resonators can have a very high optical loss, which easily doubles the threshold gain for lasing. We will also present an alternative to the use of distributed Bragg reflectors as high-reflectivity mirrors, namely TiO2/air high contrast gratings (HCGs). Fabricated HCGs of this type show a high reflectivity (>95%) over a 25 nm wavelength span.

Properties of Ir-based Ohmic contacts to AlGaN/GaN high electron mobility transistors

NASA Astrophysics Data System (ADS)

Fitch, R. C.; Gillespie, J. K.; Moser, N.; Jenkins, T.; Sewell, J.; Via, D.; Crespo, A.; Dabiran, A. M.; Chow, P. P.; Osinsky, A.; La Roche, J. R.; Ren, F.; Pearton, S. J.

2004-03-01

Measurement of the electrical characteristics of 250 devices on the same 2 in. diameter wafer shows that Ti/Al/Ir/Au Ohmic contacts on AlGaN/GaN high electron mobility transistors (HEMTs) have lower average specific contact resistance after annealing at 850 °C for 30 s (4.6×10-5 Ω cm2) compared to more standard Ti/Al/Ni/Au contacts (2×10-4 Ω cm2). HEMTs with these Ir-based contacts also show average interdevice isolation currents approximately a factor of 2 lower, higher peak transconductance (134 mS/mm compared to 121 mS/mm), and higher device breakdown voltage (31 V compared to 23 V) than the devices with Ni-based contacts. This Ir-based contact metallurgy looks promising for applications requiring extended thermal stability of the HEMTs.

Enhancement of light output power of GaN-based light-emitting diodes with photonic quasi-crystal patterned on p-GaN surface and n-side sidewall roughing.

PubMed

Lai, Fang-I; Yang, Jui-Fu

2013-05-17

In this paper, GaN-based light-emitting diodes (LEDs) with photonic quasi-crystal (PQC) structure on p-GaN surface and n-side roughing by nano-imprint lithography are fabricated and investigated. At an injection current of 20 mA, the LED with PQC structure on p-GaN surface and n-side roughing increased the light output power of the InGaN/GaN multiple quantum well LEDs by a factor of 1.42, and the wall-plug efficiency is 26% higher than the conventional GaN-based LED type. After 500-h life test (55°C/50 mA), it was found that the normalized output power of GaN-based LED with PQC structure on p-GaN surface and n-side roughing only decreased by 6%. These results offer promising potential to enhance the light output powers of commercial light-emitting devices using the technique of nano-imprint lithography.

Enhancement of light output power of GaN-based light-emitting diodes with photonic quasi-crystal patterned on p-GaN surface and n-side sidewall roughing

PubMed Central

2013-01-01

In this paper, GaN-based light-emitting diodes (LEDs) with photonic quasi-crystal (PQC) structure on p-GaN surface and n-side roughing by nano-imprint lithography are fabricated and investigated. At an injection current of 20 mA, the LED with PQC structure on p-GaN surface and n-side roughing increased the light output power of the InGaN/GaN multiple quantum well LEDs by a factor of 1.42, and the wall-plug efficiency is 26% higher than the conventional GaN-based LED type. After 500-h life test (55°C/50 mA), it was found that the normalized output power of GaN-based LED with PQC structure on p-GaN surface and n-side roughing only decreased by 6%. These results offer promising potential to enhance the light output powers of commercial light-emitting devices using the technique of nano-imprint lithography. PMID:23683526

A Collaborative Recommend Algorithm Based on Bipartite Community

PubMed Central

Fu, Yuchen; Liu, Quan; Cui, Zhiming

2014-01-01

The recommendation algorithm based on bipartite network is superior to traditional methods on accuracy and diversity, which proves that considering the network topology of recommendation systems could help us to improve recommendation results. However, existing algorithms mainly focus on the overall topology structure and those local characteristics could also play an important role in collaborative recommend processing. Therefore, on account of data characteristics and application requirements of collaborative recommend systems, we proposed a link community partitioning algorithm based on the label propagation and a collaborative recommendation algorithm based on the bipartite community. Then we designed numerical experiments to verify the algorithm validity under benchmark and real database. PMID:24955393

Emission spectra of a laser based on an In(Ga)As/GaAs quantum-dot superlattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sobolev, M. M., E-mail: m.sobolev@mail.ioffe.ru; Buyalo, M. S.; Nevedomskiy, V. N.

2015-10-15

The spectral characteristics of a laser with an active region based on a ten-layer system of In(Ga)As/GaAs vertically correlated quantum dots with 4.5-nm GaAs spacer layers between InAs quantum dots are studied under the conditions of spontaneous and stimulated emission, depending on the current and the duration of pump pulses. Data obtained by transmission electron microscopy and electroluminescence and absorption polarization anisotropy measurements make it possible to demonstrate that the investigated system of tunnel-coupled InAs quantum dots separated by thin GaAs barriers represents a quantum-dot superlattice. With an increase in the laser pump current, the electroluminescence intensity increases linearly andmore » the spectral position of the electroluminescence maximum shifts to higher energies, which is caused by the dependence of the miniband density-of-states distribution on the pump current. Upon exceeding the threshold current, multimode lasing via the miniband ground state is observed. One of the lasing modes can be attributed to the zero-phonon line, and the other is determined by the longitudinal-optical phonon replica of quantum-dot emission. The results obtained give evidence that, under conditions of the laser pumping of an In(Ga)As/GaAs quantum-dot superlattice, strong coupling between the discrete electron states in the miniband and optical phonons takes place. This leads to the formation of quantum-dot polarons, resulting from the resonant mixing of electronic states whose energy separation is comparable to the optical-phonon energy.« less

Method of plasma etching Ga-based compound semiconductors

DOEpatents

Qiu, Weibin; Goddard, Lynford L.

2012-12-25

A method of plasma etching Ga-based compound semiconductors includes providing a process chamber and a source electrode adjacent to the process chamber. The process chamber contains a sample comprising a Ga-based compound semiconductor. The sample is in contact with a platen which is electrically connected to a first power supply, and the source electrode is electrically connected to a second power supply. The method includes flowing SiCl.sub.4 gas into the chamber, flowing Ar gas into the chamber, and flowing H.sub.2 gas into the chamber. RF power is supplied independently to the source electrode and the platen. A plasma is generated based on the gases in the process chamber, and regions of a surface of the sample adjacent to one or more masked portions of the surface are etched to create a substantially smooth etched surface including features having substantially vertical walls beneath the masked portions.

Inverting the parameters of an earthquake-ruptured fault with a genetic algorithm

NASA Astrophysics Data System (ADS)

Yu, Ting-To; Fernàndez, Josè; Rundle, John B.

1998-03-01

Natural selection is the spirit of the genetic algorithm (GA): by keeping the good genes in the current generation, thereby producing better offspring during evolution. The crossover function ensures the heritage of good genes from parent to offspring. Meanwhile, the process of mutation creates a special gene, the character of which does not exist in the parent generation. A program based on genetic algorithms using C language is constructed to invert the parameters of an earthquake-ruptured fault. The verification and application of this code is shown to demonstrate its capabilities. It is determined that this code is able to find the global extreme and can be used to solve more practical problems with constraints gathered from other sources. It is shown that GA is superior to other inverting schema in many aspects. This easy handling and yet powerful algorithm should have many suitable applications in the field of geosciences.

On the AlxGa1-xN/AlyGa1-yN/AlxGa1-xN (x>y) p-electron blocking layer to improve the hole injection for AlGaN based deep ultraviolet light-emitting diodes

NASA Astrophysics Data System (ADS)

Chu, Chunshuang; Tian, Kangkai; Fang, Mengqian; Zhang, Yonghui; Li, Luping; Bi, Wengang; Zhang, Zi-Hui

2018-01-01

This work proposes the [0001] oriented AlGaN-based deep ultraviolet (DUV) light-emitting diode (LED) possessing a specifically designed p-electron blocking layer (p-EBL) to achieve the high internal quantum efficiency. Both electrons and holes can be efficiently injected into the active region by adopting the Al0.60Ga0.40N/Al0.50Ga0.50N/Al0.60Ga0.40N structured p-EBL, in which a p-Al0.50Ga0.50N layer is embedded into the p-EBL. Moreover, the impact of different thicknesses for the p-Al0.50Ga0.50N insertion layer on the hole and electron injections has also been investigated. Compared with the DUV LED with the bulk p-Al0.60Ga0.40N as the EBL, the proposed LED architectures improve the light output power if the thickness of the p-Al0.50Ga0.50N insertion layer is properly designed.

Smell Detection Agent Based Optimization Algorithm

NASA Astrophysics Data System (ADS)

Vinod Chandra, S. S.

2016-09-01

In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

Truss Optimization for a Manned Nuclear Electric Space Vehicle using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Benford, Andrew; Tinker, Michael L.

2004-01-01

The purpose of this paper is to utilize the genetic algorithm (GA) optimization method for structural design of a nuclear propulsion vehicle. Genetic algorithms provide a guided, random search technique that mirrors biological adaptation. To verify the GA capabilities, other traditional optimization methods were used to generate results for comparison to the GA results, first for simple two-dimensional structures, and then for full-scale three-dimensional truss designs.

Genetic algorithms in conceptual design of a light-weight, low-noise, tilt-rotor aircraft

NASA Technical Reports Server (NTRS)

Wells, Valana L.

1996-01-01

This report outlines research accomplishments in the area of using genetic algorithms (GA) for the design and optimization of rotorcraft. It discusses the genetic algorithm as a search and optimization tool, outlines a procedure for using the GA in the conceptual design of helicopters, and applies the GA method to the acoustic design of rotors.

Long-term evaluation of TiO2-based 68Ge/68Ga generators and optimized automation of [68Ga]DOTATOC radiosynthesis.

PubMed

Lin, Mai; Ranganathan, David; Mori, Tetsuya; Hagooly, Aviv; Rossin, Raffaella; Welch, Michael J; Lapi, Suzanne E

2012-10-01

Interest in using (68)Ga is rapidly increasing for clinical PET applications due to its favorable imaging characteristics and increased accessibility. The focus of this study was to provide our long-term evaluations of the two TiO(2)-based (68)Ge/(68)Ga generators and develop an optimized automation strategy to synthesize [(68)Ga]DOTATOC by using HEPES as a buffer system. This data will be useful in standardizing the evaluation of (68)Ge/(68)Ga generators and automation strategies to comply with regulatory issues for clinical use. Copyright © 2012 Elsevier Ltd. All rights reserved.

Selective Area Sublimation: A Simple Top-down Route for GaN-Based Nanowire Fabrication.

PubMed

Damilano, B; Vézian, S; Brault, J; Alloing, B; Massies, J

2016-03-09

Post-growth in situ partial SiNx masking of GaN-based epitaxial layers grown in a molecular beam epitaxy reactor is used to get GaN selective area sublimation (SAS) by high temperature annealing. Using this top-down approach, nanowires (NWs) with nanometer scale diameter are obtained from GaN and InxGa1-xN/GaN quantum well epitaxial structures. After GaN regrowth on InxGa1-xN/GaN NWs resulting from SAS, InxGa1-xN quantum disks (QDisks) with nanometer sizes in the three dimensions are formed. Low temperature microphotoluminescence experiments demonstrate QDisk multilines photon emission around 3 eV with individual line widths of 1-2 meV.

On the increased efficiency in InGaN-based multiple quantum wells emitting at 530-590 nm with AlGaN interlayers

NASA Astrophysics Data System (ADS)

Koleske, D. D.; Fischer, A. J.; Bryant, B. N.; Kotula, P. G.; Wierer, J. J.

2015-04-01

InGaN/AlGaN/GaN-based multiple quantum wells (MQWs) with AlGaN interlayers (ILs) are investigated, specifically to examine the fundamental mechanisms behind their increased radiative efficiency at wavelengths of 530-590 nm. The AlzGa1-zN (z 0.38) IL is 1-2 nm thick, and is grown after and at the same growth temperature as the 3 nm thick InGaN quantum well (QW). This is followed by an increase in temperature for the growth of a 10 nm thick GaN barrier layer. The insertion of the AlGaN IL within the MQW provides various benefits. First, the AlGaN IL allows for growth of the InxGa1-xN QW well below typical growth temperatures to achieve higher x (up to 0.25). Second, annealing the IL capped QW prior to the GaN barrier growth improves the AlGaN IL smoothness as determined by atomic force microscopy, improves the InGaN/AlGaN/GaN interface quality as determined from scanning transmission electron microscope images and x-ray diffraction, and increases the radiative efficiency by reducing non-radiative defects as determined by time-resolved photoluminescence measurements. Finally, the AlGaN IL increases the spontaneous and piezoelectric polarization induced electric fields acting on the InGaN QW, providing an additional red-shift to the emission wavelength as determined by Schrodinger-Poisson modeling and fitting to the experimental data. The relative impact of increased indium concentration and polarization fields on the radiative efficiency of MQWs with AlGaN ILs is explored along with implications to conventional longer wavelength emitters.

Collaboration space division in collaborative product development based on a genetic algorithm

NASA Astrophysics Data System (ADS)

Qian, Xueming; Ma, Yanqiao; Feng, Huan

2018-02-01

The advance in the global environment, rapidly changing markets, and information technology has created a new stage for design. In such an environment, one strategy for success is the Collaborative Product Development (CPD). Organizing people effectively is the goal of Collaborative Product Development, and it solves the problem with certain foreseeability. The development group activities are influenced not only by the methods and decisions available, but also by correlation among personnel. Grouping the personnel according to their correlation intensity is defined as collaboration space division (CSD). Upon establishment of a correlation matrix (CM) of personnel and an analysis of the collaboration space, the genetic algorithm (GA) and minimum description length (MDL) principle may be used as tools in optimizing collaboration space. The MDL principle is used in setting up an object function, and the GA is used as a methodology. The algorithm encodes spatial information as a chromosome in binary. After repetitious crossover, mutation, selection and multiplication, a robust chromosome is found, which can be decoded into an optimal collaboration space. This new method can calculate the members in sub-spaces and individual groupings within the staff. Furthermore, the intersection of sub-spaces and public persons belonging to all sub-spaces can be determined simultaneously.

An improved conscan algorithm based on a Kalman filter

NASA Technical Reports Server (NTRS)

Eldred, D. B.

1994-01-01

Conscan is commonly used by DSN antennas to allow adaptive tracking of a target whose position is not precisely known. This article describes an algorithm that is based on a Kalman filter and is proposed to replace the existing fast Fourier transform based (FFT-based) algorithm for conscan. Advantages of this algorithm include better pointing accuracy, continuous update information, and accommodation of missing data. Additionally, a strategy for adaptive selection of the conscan radius is proposed. The performance of the algorithm is illustrated through computer simulations and compared to the FFT algorithm. The results show that the Kalman filter algorithm is consistently superior.

An Image Encryption Algorithm Based on Information Hiding

NASA Astrophysics Data System (ADS)

Ge, Xin; Lu, Bin; Liu, Fenlin; Gong, Daofu

Aiming at resolving the conflict between security and efficiency in the design of chaotic image encryption algorithms, an image encryption algorithm based on information hiding is proposed based on the “one-time pad” idea. A random parameter is introduced to ensure a different keystream for each encryption, which has the characteristics of “one-time pad”, improving the security of the algorithm rapidly without significant increase in algorithm complexity. The random parameter is embedded into the ciphered image with information hiding technology, which avoids negotiation for its transport and makes the application of the algorithm easier. Algorithm analysis and experiments show that the algorithm is secure against chosen plaintext attack, differential attack and divide-and-conquer attack, and has good statistical properties in ciphered images.

White light emission of monolithic InGaN/GaN grown on morphology-controlled, nanostructured GaN templates.

PubMed

Song, Keun Man; Kim, Do-Hyun; Kim, Jong-Min; Cho, Chu-Young; Choi, Jehyuk; Kim, Kahee; Park, Jinsup; Kim, Hogyoug

2017-06-02

We demonstrated an InGaN/GaN-based, monolithic, white light-emitting diode (LED) without phosphors by using morphology-controlled active layers formed on multi-facet GaN templates containing polar and semipolar surfaces. The nanostructured surface morphology was controlled by changing the growth time, and distinct multiple photoluminescence peaks were observed at 360, 460, and 560 nm; these features were caused by InGaN/GaN-based multiple quantum wells (MQWs) on the nanostructured facets. The origin of each multi-peak was related to the different indium (In) compositions in the different planes of the quantum wells grown on the nanostructured GaN. The emitting units of MQWs in the LED structures were continuously connected, which is different from other GaN-based nanorod or nanowire LEDs. Therefore, the suggested structure had a larger active area. From the electroluminescence spectrum of the fabricated LED, monolithic white light emission with CIE color coordinates of x = 0.306 and y = 0.333 was achieved via multi-facet control combined with morphology control of the metal organic chemical vapor deposition-selective area growth of InGaN/GaN MQWs.

White light emission of monolithic InGaN/GaN grown on morphology-controlled, nanostructured GaN templates

NASA Astrophysics Data System (ADS)

Song, Keun Man; Kim, Do-Hyun; Kim, Jong-Min; Cho, Chu-Young; Choi, Jehyuk; Kim, Kahee; Park, Jinsup; Kim, Hogyoug

2017-06-01

We demonstrated an InGaN/GaN-based, monolithic, white light-emitting diode (LED) without phosphors by using morphology-controlled active layers formed on multi-facet GaN templates containing polar and semipolar surfaces. The nanostructured surface morphology was controlled by changing the growth time, and distinct multiple photoluminescence peaks were observed at 360, 460, and 560 nm; these features were caused by InGaN/GaN-based multiple quantum wells (MQWs) on the nanostructured facets. The origin of each multi-peak was related to the different indium (In) compositions in the different planes of the quantum wells grown on the nanostructured GaN. The emitting units of MQWs in the LED structures were continuously connected, which is different from other GaN-based nanorod or nanowire LEDs. Therefore, the suggested structure had a larger active area. From the electroluminescence spectrum of the fabricated LED, monolithic white light emission with CIE color coordinates of x = 0.306 and y = 0.333 was achieved via multi-facet control combined with morphology control of the metal organic chemical vapor deposition-selective area growth of InGaN/GaN MQWs.

Application of genetic algorithm in integrated setup planning and operation sequencing

NASA Astrophysics Data System (ADS)

Kafashi, Sajad; Shakeri, Mohsen

2011-01-01

Process planning is an essential component for linking design and manufacturing process. Setup planning and operation sequencing is two main tasks in process planning. Many researches solved these two problems separately. Considering the fact that the two functions are complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved economically and competitively. This paper present a generative system and genetic algorithm (GA) approach to process plan the given part. The proposed approach and optimization methodology analyses the TAD (tool approach direction), tolerance relation between features and feature precedence relations to generate all possible setups and operations using workshop resource database. Based on these technological constraints the GA algorithm approach, which adopts the feature-based representation, optimizes the setup plan and sequence of operations using cost indices. Case study show that the developed system can generate satisfactory results in optimizing the setup planning and operation sequencing simultaneously in feasible condition.

Analysis of improved dc and ac performances of an InGaP/GaAs heterojunction bipolar transistor with a graded Al xGa 1- xAs layer at emitter/base heterojunction

NASA Astrophysics Data System (ADS)

Cheng, Shiou-Ying

2004-07-01

An InGaP/GaAs heterojunction bipolar transistor (HBT) with a continuous conduction-band structure is demonstrated and theoretically investigated. This device exhibited good performance including lower turn-on voltage, lower offset voltage and smaller collector current saturation voltage. The novel aspect of device structure design is the adoption of the compositionally linear-graded AlGaAs layer between the InGaP-emitter and GaAs-base layers. Therefore, the device studied shows better dc and ac performances than a conventional device. Consequently, this causes the substantial benefit for practical analog and digital applications especially for lower operation voltage, lower power consumption commercial and military products.

Formation mechanism of thermally optimized Ga-doped MgZnO transparent conducting electrodes for GaN-based light-emitting diodes

NASA Astrophysics Data System (ADS)

Jang, Seon-Ho; Jo, Yong-Ryun; Lee, Young-Woong; Kim, Sei-Min; Kim, Bong-Joong; Bae, Jae-Hyun; An, Huei-Chun; Jang, Ja-Soon

2015-05-01

We report a highly transparent conducting electrode (TCE) scheme of MgxZn1-xO:Ga/Au/NiOx which was deposited on p-GaN by e-beam for GaN-based light emitting diodes (LEDs). The optical and electrical properties of the electrode were optimized by thermal annealing at 500°C for 1 minute in N2 + O2 (5:3) ambient. The light transmittance at the optimal condition increased up to 84-97% from the UV-A to yellow region. The specific contact resistance decreased to 4.3(±0.3) × 10-5 Ωcm2. The improved properties of the electrode were attributed to the directionally elongated crystalline nanostructures formed in the MgxZn1-xO:Ga layer which is compositionally uniform. Interestingly, the Au alloy nano-clusters created in the MgxZn1-xO:Ga layer during annealing at 500°C may also enhance the properties of the electrode by acting as a conducting bridge and a nano-sized mirror. Based on studies of the external quantum efficiency of blue LED devices, the proposed electrode scheme combined with an optimized annealing treatment suggests a potential alternative to ITO. [Figure not available: see fulltext.

Spiral bacterial foraging optimization method: Algorithm, evaluation and convergence analysis

NASA Astrophysics Data System (ADS)

Kasaiezadeh, Alireza; Khajepour, Amir; Waslander, Steven L.

2014-04-01

A biologically-inspired algorithm called Spiral Bacterial Foraging Optimization (SBFO) is investigated in this article. SBFO, previously proposed by the same authors, is a multi-agent, gradient-based algorithm that minimizes both the main objective function (local cost) and the distance between each agent and a temporary central point (global cost). A random jump is included normal to the connecting line of each agent to the central point, which produces a vortex around the temporary central point. This random jump is also suitable to cope with premature convergence, which is a feature of swarm-based optimization methods. The most important advantages of this algorithm are as follows: First, this algorithm involves a stochastic type of search with a deterministic convergence. Second, as gradient-based methods are employed, faster convergence is demonstrated over GA, DE, BFO, etc. Third, the algorithm can be implemented in a parallel fashion in order to decentralize large-scale computation. Fourth, the algorithm has a limited number of tunable parameters, and finally SBFO has a strong certainty of convergence which is rare in existing global optimization algorithms. A detailed convergence analysis of SBFO for continuously differentiable objective functions has also been investigated in this article.

Optimization of Boiling Water Reactor Loading Pattern Using Two-Stage Genetic Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kobayashi, Yoko; Aiyoshi, Eitaro

2002-10-15

A new two-stage optimization method based on genetic algorithms (GAs) using an if-then heuristic rule was developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). In the first stage, the LP is optimized using an improved GA operator. In the second stage, an exposure-dependent control rod pattern (CRP) is sought using GA with an if-then heuristic rule. The procedure of the improved GA is based on deterministic operators that consist of crossover, mutation, and selection. The handling of the encoding technique and constraint conditions by that GA reflects the peculiar characteristics of the BWR. In addition, strategies suchmore » as elitism and self-reproduction are effectively used in order to improve the search speed. The LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and constraints dependent on three dimensions have always necessitated the use of three-dimensional core simulators for BWRs, so that optimization of computational efficiency is required. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant in two phases. One phase is only LP optimization applying the Haling technique. The other phase is an LP optimization that considers the CRP during reactor operation. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained.« less

Pure AlN layers in metal-polar AlGaN/AlN/GaN and AlN/GaN heterostructures grown by low-temperature ammonia-based molecular beam epitaxy

NASA Astrophysics Data System (ADS)

Kaun, Stephen W.; Mazumder, Baishakhi; Fireman, Micha N.; Kyle, Erin C. H.; Mishra, Umesh K.; Speck, James S.

2015-05-01

When grown at a high temperature (820 °C) by ammonia-based molecular beam epitaxy (NH3-MBE), the AlN layers of metal-polar AlGaN/AlN/GaN heterostructures had a high GaN mole fraction (∼0.15), as identified by atom probe tomography in a previous study (Mazumder et al 2013 Appl. Phys. Lett. 102 111603). In the study presented here, growth at low temperature (<740 °C) by NH3-MBE yielded metal-polar AlN layers that were essentially pure at the alloy level. The improved purity of the AlN layers grown at low temperature was correlated to a dramatic increase in the sheet density of the two-dimensional electron gas (2DEG) at the AlN/GaN heterointerface. Through application of an In surfactant, metal-polar AlN(3.5 nm)/GaN and AlGaN/AlN(2.5 nm)/GaN heterostructures grown at low temperature yielded low 2DEG sheet resistances of 177 and 285 Ω/□, respectively.

Gradient Evolution-based Support Vector Machine Algorithm for Classification

NASA Astrophysics Data System (ADS)

Zulvia, Ferani E.; Kuo, R. J.

2018-03-01

This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

Study on Multi-stage Logistics System Design Problem with Inventory Considering Demand Change by Hybrid Genetic Algorithm

NASA Astrophysics Data System (ADS)

Inoue, Hisaki; Gen, Mitsuo

The logistics model used in this study is 3-stage model employed by an automobile company, which aims to solve traffic problems at a total minimum cost. Recently, research on the metaheuristics method has advanced as an approximate means for solving optimization problems like this model. These problems can be solved using various methods such as the genetic algorithm (GA), simulated annealing, and tabu search. GA is superior in robustness and adjustability toward a change in the structure of these problems. However, GA has a disadvantage in that it has a slightly inefficient search performance because it carries out a multi-point search. A hybrid GA that combines another method is attracting considerable attention since it can compensate for a fault to a partial solution that early convergence gives a bad influence on a result. In this study, we propose a novel hybrid random key-based GA(h-rkGA) that combines local search and parameter tuning of crossover rate and mutation rate; h-rkGA is an improved version of the random key-based GA (rk-GA). We attempted comparative experiments with spanning tree-based GA, priority based GA and random key-based GA. Further, we attempted comparative experiments with “h-GA by only local search” and “h-GA by only parameter tuning”. We reported the effectiveness of the proposed method on the basis of the results of these experiments.

Score-Level Fusion of Phase-Based and Feature-Based Fingerprint Matching Algorithms

NASA Astrophysics Data System (ADS)

Ito, Koichi; Morita, Ayumi; Aoki, Takafumi; Nakajima, Hiroshi; Kobayashi, Koji; Higuchi, Tatsuo

This paper proposes an efficient fingerprint recognition algorithm combining phase-based image matching and feature-based matching. In our previous work, we have already proposed an efficient fingerprint recognition algorithm using Phase-Only Correlation (POC), and developed commercial fingerprint verification units for access control applications. The use of Fourier phase information of fingerprint images makes it possible to achieve robust recognition for weakly impressed, low-quality fingerprint images. This paper presents an idea of improving the performance of POC-based fingerprint matching by combining it with feature-based matching, where feature-based matching is introduced in order to improve recognition efficiency for images with nonlinear distortion. Experimental evaluation using two different types of fingerprint image databases demonstrates efficient recognition performance of the combination of the POC-based algorithm and the feature-based algorithm.

Genetic Algorithm for Optimization: Preprocessor and Algorithm

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam A.

2006-01-01

Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.

Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

PubMed Central

Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.

2013-01-01

Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933

Optimisation of process parameters on thin shell part using response surface methodology (RSM) and genetic algorithm (GA)

NASA Astrophysics Data System (ADS)

Faiz, J. M.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

This study conducts the simulation on optimisation of injection moulding process parameters using Autodesk Moldflow Insight (AMI) software. This study has applied some process parameters which are melt temperature, mould temperature, packing pressure, and cooling time in order to analyse the warpage value of the part. Besides, a part has been selected to be studied which made of Polypropylene (PP). The combination of the process parameters is analysed using Analysis of Variance (ANOVA) and the optimised value is obtained using Response Surface Methodology (RSM). The RSM as well as Genetic Algorithm are applied in Design Expert software in order to minimise the warpage value. The outcome of this study shows that the warpage value improved by using RSM and GA.

Genetic Algorithm Approaches for Actuator Placement

NASA Technical Reports Server (NTRS)

Crossley, William A.

2000-01-01

This research investigated genetic algorithm approaches for smart actuator placement to provide aircraft maneuverability without requiring hinged flaps or other control surfaces. The effort supported goals of the Multidisciplinary Design Optimization focus efforts in NASA's Aircraft au program. This work helped to properly identify various aspects of the genetic algorithm operators and parameters that allow for placement of discrete control actuators/effectors. An improved problem definition, including better definition of the objective function and constraints, resulted from this research effort. The work conducted for this research used a geometrically simple wing model; however, an increasing number of potential actuator placement locations were incorporated to illustrate the ability of the GA to determine promising actuator placement arrangements. This effort's major result is a useful genetic algorithm-based approach to assist in the discrete actuator/effector placement problem.

Exploiting Fractional Order PID Controller Methods in Improving the Performance of Integer Order PID Controllers: A GA Based Approach

NASA Astrophysics Data System (ADS)

Mukherjee, Bijoy K.; Metia, Santanu

2009-10-01

The paper is divided into three parts. The first part gives a brief introduction to the overall paper, to fractional order PID (PIλDμ) controllers and to Genetic Algorithm (GA). In the second part, first it has been studied how the performance of an integer order PID controller deteriorates when implemented with lossy capacitors in its analog realization. Thereafter it has been shown that the lossy capacitors can be effectively modeled by fractional order terms. Then, a novel GA based method has been proposed to tune the controller parameters such that the original performance is retained even though realized with the same lossy capacitors. Simulation results have been presented to validate the usefulness of the method. Some Ziegler-Nichols type tuning rules for design of fractional order PID controllers have been proposed in the literature [11]. In the third part, a novel GA based method has been proposed which shows how equivalent integer order PID controllers can be obtained which will give performance level similar to those of the fractional order PID controllers thereby removing the complexity involved in the implementation of the latter. It has been shown with extensive simulation results that the equivalent integer order PID controllers more or less retain the robustness and iso-damping properties of the original fractional order PID controllers. Simulation results also show that the equivalent integer order PID controllers are more robust than the normal Ziegler-Nichols tuned PID controllers.

A guided search genetic algorithm using mined rules for optimal affective product design

NASA Astrophysics Data System (ADS)

Fung, Chris K. Y.; Kwong, C. K.; Chan, Kit Yan; Jiang, H.

2014-08-01

Affective design is an important aspect of new product development, especially for consumer products, to achieve a competitive edge in the marketplace. It can help companies to develop new products that can better satisfy the emotional needs of customers. However, product designers usually encounter difficulties in determining the optimal settings of the design attributes for affective design. In this article, a novel guided search genetic algorithm (GA) approach is proposed to determine the optimal design attribute settings for affective design. The optimization model formulated based on the proposed approach applied constraints and guided search operators, which were formulated based on mined rules, to guide the GA search and to achieve desirable solutions. A case study on the affective design of mobile phones was conducted to illustrate the proposed approach and validate its effectiveness. Validation tests were conducted, and the results show that the guided search GA approach outperforms the GA approach without the guided search strategy in terms of GA convergence and computational time. In addition, the guided search optimization model is capable of improving GA to generate good solutions for affective design.

Prediction of temperature and HAZ in thermal-based processes with Gaussian heat source by a hybrid GA-ANN model

NASA Astrophysics Data System (ADS)

Fazli Shahri, Hamid Reza; Mahdavinejad, Ramezanali

2018-02-01

Thermal-based processes with Gaussian heat source often produce excessive temperature which can impose thermally-affected layers in specimens. Therefore, the temperature distribution and Heat Affected Zone (HAZ) of materials are two critical factors which are influenced by different process parameters. Measurement of the HAZ thickness and temperature distribution within the processes are not only difficult but also expensive. This research aims at finding a valuable knowledge on these factors by prediction of the process through a novel combinatory model. In this study, an integrated Artificial Neural Network (ANN) and genetic algorithm (GA) was used to predict the HAZ and temperature distribution of the specimens. To end this, a series of full factorial design of experiments were conducted by applying a Gaussian heat flux on Ti-6Al-4 V at first, then the temperature of the specimen was measured by Infrared thermography. The HAZ width of each sample was investigated through measuring the microhardness. Secondly, the experimental data was used to create a GA-ANN model. The efficiency of GA in design and optimization of the architecture of ANN was investigated. The GA was used to determine the optimal number of neurons in hidden layer, learning rate and momentum coefficient of both output and hidden layers of ANN. Finally, the reliability of models was assessed according to the experimental results and statistical indicators. The results demonstrated that the combinatory model predicted the HAZ and temperature more effective than a trial-and-error ANN model.

Multibias and thermal behavior of microwave GaN and GaAs based HEMTs

NASA Astrophysics Data System (ADS)

Alim, Mohammad A.; Rezazadeh, Ali A.; Gaquiere, Christophe

2016-12-01

Multibias and thermal characterizations on 0.25 μm × (2 × 100) μm AlGaN/GaN/SiC HEMT and 0.5 μm × (2 × 100) μm AlGaAs/InGaAs pseudomorphic HEMT have carried out for the first time. Two competitive device technologies are investigated with the variations of bias and temperature in order to afford a detailed realization of their potentialities. The main finding includes the self heating effect in the GaN device, zero temperature coefficient points at the drain current and transconductance in the GaAs device. The thermal resistance RTH of 7.1, 8.2 and 9.4 °C mm/W for the GaN device was estimated at 25, 75 and 150 °C respectively which are consistent with those found in the open literature. The temperature trend of the threshold voltage VT, Schottky barrier height ϕb, sheet charge densities of two dimensional electron gas ns, and capacitance under the gate Cg are exactly opposite in the two devices; whereas the knee voltage Vk, on resistance Ron, and series resistance Rseries are shows similar trend. The multi-bias and thermal behavior of the output current Ids, output conductance gds, transconductance gm, cut-off frequency ft, maximum frequency fmax, effective velocity of electron, veff and field dependent mobility, μ demonstrates a great potential of GaN device. These results provide some valuable insights for technology of preference for future and current applications.

Carbon reactivation kinetics in the base of heterojunction GaInP-GaAs bipolar transistors

NASA Astrophysics Data System (ADS)

Mimila-Arroyo, J.; Bland, S. W.; Chevallier, J.

2002-05-01

The reactivation kinetics of carbon acceptors in the base region of GaInP/GaAs heterojunction bipolar transistors was studied. The reactivation was achieved by ex situ thermal annealing, through a multistage annealing experiment where the carrier concentration was monitored at each stage. Results indicate that carbon reactivation follows a first-order kinetics process in which the activation energy appears to be the sum of the energy needed to debond the hydrogen from the carbon-hydrogen complex, and the energy necessary to overcome the electrostatic junction barrier. The reactivation constant is thermally activated with an activation energy of 2.83 eV and an attempt frequency of 1.2×1013 s-1.

Research on energy-saving optimal control of trains in a following operation under a fixed four-aspect autoblock system based on multi-dimension parallel GA

NASA Astrophysics Data System (ADS)

Lu, Qiheng; Feng, Xiaoyun

2013-03-01

After analyzing the working principle of the four-aspect fixed autoblock system, an energy-saving control model was created based on the dynamics equations of the trains in order to study the energy-saving optimal control strategy of trains in a following operation. Besides the safety and punctuality, the main aims of the model were the energy consumption and the time error. Based on this model, the static and dynamic speed restraints under a four-aspect fixed autoblock system were put forward. The multi-dimension parallel genetic algorithm (GA) and the external punishment function were adopted to solve this problem. By using the real number coding and the strategy of ramps divided into three parts, the convergence of GA was speeded up and the length of chromosomes was shortened. A vector of Gaussian random disturbance with zero mean was superposed to the mutation operator. The simulation result showed that the method could reduce the energy consumption effectively based on safety and punctuality.

Optimization of a Boiling Water Reactor Loading Pattern Using an Improved Genetic Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kobayashi, Yoko; Aiyoshi, Eitaro

2003-08-15

A search method based on genetic algorithms (GA) using deterministic operators has been developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). The search method uses an Improved GA operator, that is, crossover, mutation, and selection. The handling of the encoding technique and constraint conditions is designed so that the GA reflects the peculiar characteristics of the BWR. In addition, some strategies such as elitism and self-reproduction are effectively used to improve the search speed. LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and three-dimensional-dependent constraints have alwaysmore » necessitated the use of three-dimensional core simulators for BWRs, so that an optimization method is required for computational efficiency. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant applying the Haling technique. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained.« less

A genetic algorithm-based framework for wavelength selection on sample categorization.

PubMed

Anzanello, Michel J; Yamashita, Gabrielli; Marcelo, Marcelo; Fogliatto, Flávio S; Ortiz, Rafael S; Mariotti, Kristiane; Ferrão, Marco F

2017-08-01

In forensic and pharmaceutical scenarios, the application of chemometrics and optimization techniques has unveiled common and peculiar features of seized medicine and drug samples, helping investigative forces to track illegal operations. This paper proposes a novel framework aimed at identifying relevant subsets of attenuated total reflectance Fourier transform infrared (ATR-FTIR) wavelengths for classifying samples into two classes, for example authentic or forged categories in case of medicines, or salt or base form in cocaine analysis. In the first step of the framework, the ATR-FTIR spectra were partitioned into equidistant intervals and the k-nearest neighbour (KNN) classification technique was applied to each interval to insert samples into proper classes. In the next step, selected intervals were refined through the genetic algorithm (GA) by identifying a limited number of wavelengths from the intervals previously selected aimed at maximizing classification accuracy. When applied to Cialis®, Viagra®, and cocaine ATR-FTIR datasets, the proposed method substantially decreased the number of wavelengths needed to categorize, and increased the classification accuracy. From a practical perspective, the proposed method provides investigative forces with valuable information towards monitoring illegal production of drugs and medicines. In addition, focusing on a reduced subset of wavelengths allows the development of portable devices capable of testing the authenticity of samples during police checking events, avoiding the need for later laboratorial analyses and reducing equipment expenses. Theoretically, the proposed GA-based approach yields more refined solutions than the current methods relying on interval approaches, which tend to insert irrelevant wavelengths in the retained intervals. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Survey of gene splicing algorithms based on reads.

PubMed

Si, Xiuhua; Wang, Qian; Zhang, Lei; Wu, Ruo; Ma, Jiquan

2017-11-02

Gene splicing is the process of assembling a large number of unordered short sequence fragments to the original genome sequence as accurately as possible. Several popular splicing algorithms based on reads are reviewed in this article, including reference genome algorithms and de novo splicing algorithms (Greedy-extension, Overlap-Layout-Consensus graph, De Bruijn graph). We also discuss a new splicing method based on the MapReduce strategy and Hadoop. By comparing these algorithms, some conclusions are drawn and some suggestions on gene splicing research are made.

High Piezoelectric Conversion Properties of Axial InGaN/GaN Nanowires.

PubMed

Jegenyes, Nikoletta; Morassi, Martina; Chrétien, Pascal; Travers, Laurent; Lu, Lu; Julien, Francois H; Tchernycheva, Maria; Houzé, Frédéric; Gogneau, Noelle

2018-05-25

We demonstrate for the first time the efficient mechanical-electrical conversion properties of InGaN/GaN nanowires (NWs). Using an atomic force microscope equipped with a modified Resiscope module, we analyse the piezoelectric energy generation of GaN NWs and demonstrate an important enhancement when integrating in their volume a thick In-rich InGaN insertion. The piezoelectric response of InGaN/GaN NWs can be tuned as a function of the InGaN insertion thickness and position in the NW volume. The energy harvesting is favoured by the presence of a PtSi/GaN Schottky diode which allows to efficiently collect the piezo-charges generated by InGaN/GaN NWs. Average output voltages up to 330 ± 70 mV and a maximum value of 470 mV per NW has been measured for nanostructures integrating 70 nm-thick InGaN insertion capped with a thin GaN top layer. This latter value establishes an increase of about 35% of the piezo-conversion capacity in comparison with binary p-doped GaN NWs. Based on the measured output signals, we estimate that one layer of dense InGaN/GaN-based NW can generate a maximum output power density of about 3.3 W/cm². These results settle the new state-of-the-art for piezo-generation from GaN-based NWs and offer a promising perspective for extending the performances of the piezoelectric sources.

Chaotic genetic algorithm and Adaboost ensemble metamodeling approach for optimum resource planning in emergency departments.

PubMed

Yousefi, Milad; Yousefi, Moslem; Ferreira, Ricardo Poley Martins; Kim, Joong Hoon; Fogliatto, Flavio S

2018-01-01

Long length of stay and overcrowding in emergency departments (EDs) are two common problems in the healthcare industry. To decrease the average length of stay (ALOS) and tackle overcrowding, numerous resources, including the number of doctors, nurses and receptionists need to be adjusted, while a number of constraints are to be considered at the same time. In this study, an efficient method based on agent-based simulation, machine learning and the genetic algorithm (GA) is presented to determine optimum resource allocation in emergency departments. GA can effectively explore the entire domain of all 19 variables and identify the optimum resource allocation through evolution and mimicking the survival of the fittest concept. A chaotic mutation operator is used in this study to boost GA performance. A model of the system needs to be run several thousand times through the GA evolution process to evaluate each solution, hence the process is computationally expensive. To overcome this drawback, a robust metamodel is initially constructed based on an agent-based system simulation. The simulation exhibits ED performance with various resource allocations and trains the metamodel. The metamodel is created with an ensemble of the adaptive neuro-fuzzy inference system (ANFIS), feedforward neural network (FFNN) and recurrent neural network (RNN) using the adaptive boosting (AdaBoost) ensemble algorithm. The proposed GA-based optimization approach is tested in a public ED, and it is shown to decrease the ALOS in this ED case study by 14%. Additionally, the proposed metamodel shows a 26.6% improvement compared to the average results of ANFIS, FFNN and RNN in terms of mean absolute percentage error (MAPE). Copyright © 2017 Elsevier B.V. All rights reserved.

Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton

PubMed Central

Long, Yi; Du, Zhi-jiang; Wang, Wei-dong; Dong, Wei

2016-01-01

A lower limb assistive exoskeleton is designed to help operators walk or carry payloads. The exoskeleton is required to shadow human motion intent accurately and compliantly to prevent incoordination. If the user's intention is estimated accurately, a precise position control strategy will improve collaboration between the user and the exoskeleton. In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. The proposed control strategy (SMC_GA_CMAC) is compared with three other types of approaches, that is, conventional SMC without optimization, optimal SMC with GA (SMC_GA), and SMC with CMAC compensation (SMC_CMAC), all of which are employed to track the desired joint angular position which is deduced from Clinical Gait Analysis (CGA) data. Position tracking performance is investigated with cosimulation using ADAMS and MATLAB/SIMULINK in two cases, of which the first case is without disturbances while the second case is with a bounded disturbance. The cosimulation results show the effectiveness of the proposed control strategy which can be employed in similar exoskeleton systems. PMID:27069353

Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton.

PubMed

Long, Yi; Du, Zhi-Jiang; Wang, Wei-Dong; Dong, Wei

2016-01-01

A lower limb assistive exoskeleton is designed to help operators walk or carry payloads. The exoskeleton is required to shadow human motion intent accurately and compliantly to prevent incoordination. If the user's intention is estimated accurately, a precise position control strategy will improve collaboration between the user and the exoskeleton. In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. The proposed control strategy (SMC_GA_CMAC) is compared with three other types of approaches, that is, conventional SMC without optimization, optimal SMC with GA (SMC_GA), and SMC with CMAC compensation (SMC_CMAC), all of which are employed to track the desired joint angular position which is deduced from Clinical Gait Analysis (CGA) data. Position tracking performance is investigated with cosimulation using ADAMS and MATLAB/SIMULINK in two cases, of which the first case is without disturbances while the second case is with a bounded disturbance. The cosimulation results show the effectiveness of the proposed control strategy which can be employed in similar exoskeleton systems.

Influence of dislocation density on internal quantum efficiency of GaN-based semiconductors

NASA Astrophysics Data System (ADS)

Yu, Jiadong; Hao, Zhibiao; Li, Linsen; Wang, Lai; Luo, Yi; Wang, Jian; Sun, Changzheng; Han, Yanjun; Xiong, Bing; Li, Hongtao

2017-03-01

By considering the effects of stress fields coming from lattice distortion as well as charge fields coming from line charges at edge dislocation cores on radiative recombination of exciton, a model of carriers' radiative and non-radiative recombination has been established in GaN-based semiconductors with certain dislocation density. Using vector average of the stress fields and the charge fields, the relationship between dislocation density and the internal quantum efficiency (IQE) is deduced. Combined with related experimental results, this relationship is fitted well to the trend of IQEs of bulk GaN changing with screw and edge dislocation density, meanwhile its simplified form is fitted well to the IQEs of AlGaN multiple quantum well LEDs with varied threading dislocation densities but the same light emission wavelength. It is believed that this model, suitable for different epitaxy platforms such as MOCVD and MBE, can be used to predict to what extent the luminous efficiency of GaN-based semiconductors can still maintain when the dislocation density increases, so as to provide a reasonable rule of thumb for optimizing the epitaxial growth of GaN-based devices.

Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

PubMed

Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

2017-09-01

Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

Computerized decision support system for mass identification in breast using digital mammogram: a study on GA-based neuro-fuzzy approaches.

PubMed

Das, Arpita; Bhattacharya, Mahua

2011-01-01

In the present work, authors have developed a treatment planning system implementing genetic based neuro-fuzzy approaches for accurate analysis of shape and margin of tumor masses appearing in breast using digital mammogram. It is obvious that a complicated structure invites the problem of over learning and misclassification. In proposed methodology, genetic algorithm (GA) has been used for searching of effective input feature vectors combined with adaptive neuro-fuzzy model for final classification of different boundaries of tumor masses. The study involves 200 digitized mammograms from MIAS and other databases and has shown 86% correct classification rate.

Aluminum gallium nitride (GaN)/GaN high electron mobility transistor-based sensors for glucose detection in exhaled breath condensate.

PubMed

Chu, Byung Hwan; Kang, Byoung Sam; Hung, Sheng Chun; Chen, Ke Hung; Ren, Fan; Sciullo, Andrew; Gila, Brent P; Pearton, Stephen J

2010-01-01

Immobilized aluminum gallium nitride (AlGaN)/GaN high electron mobility transistors (HEMTs) have shown great potential in the areas of pH, chloride ion, and glucose detection in exhaled breath condensate (EBC). HEMT sensors can be integrated into a wireless data transmission system that allows for remote monitoring. This technology offers the possibility of using AlGaN/GaN HEMTs for extended investigations of airway pathology of detecting glucose in EBC without the need for clinical visits. HEMT structures, consisting of a 3-microm-thick undoped GaN buffer, 30-A-thick Al(0.3)Ga(0.7)N spacer, and 220-A-thick silicon-doped Al(0.3)Ga(0.7)N cap layer, were used for fabricating the HEMT sensors. The gate area of the pH, chloride ion, and glucose detection was immobilized with scandium oxide (Sc(2)O(3)), silver chloride (AgCl) thin film, and zinc oxide (ZnO) nanorods, respectively. The Sc(2)O(3)-gated sensor could detect the pH of solutions ranging from 3 to 10 with a resolution of approximately 0.1 pH. A chloride ion detection limit of 10(-8) M was achieved with a HEMT sensor immobilized with the AgCl thin film. The drain-source current of the ZnO nanorod-gated AlGaN/GaN HEMT sensor immobilized with glucose oxidase showed a rapid response of less than 5 seconds when the sensor was exposed to the target glucose in a buffer with a pH value of 7.4. The sensor could detect a wide range of concentrations from 0.5 nM to 125 microM. There is great promise for using HEMT-based sensors to enhance the detection sensitivity for glucose detection in EBC. Depending on the immobilized material, HEMT-based sensors can be used for sensing different materials. These electronic detection approaches with rapid response and good repeatability show potential for the investigation of airway pathology. The devices can also be integrated into a wireless data transmission system for remote monitoring applications. This sensor technology could use the exhaled breath condensate to measure the

Aluminum Gallium Nitride (GaN)/GaN High Electron Mobility Transistor-Based Sensors for Glucose Detection in Exhaled Breath Condensate

PubMed Central

Chu, Byung Hwan; Kang, Byoung Sam; Hung, Sheng Chun; Chen, Ke Hung; Ren, Fan; Sciullo, Andrew; Gila, Brent P.; Pearton, Stephen J.

2010-01-01

Background Immobilized aluminum gallium nitride (AlGaN)/GaN high electron mobility transistors (HEMTs) have shown great potential in the areas of pH, chloride ion, and glucose detection in exhaled breath condensate (EBC). HEMT sensors can be integrated into a wireless data transmission system that allows for remote monitoring. This technology offers the possibility of using AlGaN/GaN HEMTs for extended investigations of airway pathology of detecting glucose in EBC without the need for clinical visits. Methods HEMT structures, consisting of a 3-μm-thick undoped GaN buffer, 30-Å-thick Al0.3Ga0.7N spacer, and 220-Å-thick silicon-doped Al0.3Ga0.7N cap layer, were used for fabricating the HEMT sensors. The gate area of the pH, chloride ion, and glucose detection was immobilized with scandium oxide (Sc2O3), silver chloride (AgCl) thin film, and zinc oxide (ZnO) nanorods, respectively. Results The Sc2O3-gated sensor could detect the pH of solutions ranging from 3 to 10 with a resolution of ∼0.1 pH. A chloride ion detection limit of 10-8 M was achievedt with a HEMT sensor immobilized with the AgCl thin film. The drain–source current of the ZnO nanorod-gated AlGaN/GaN HEMT sensor immobilized with glucose oxidase showed a rapid response of less than 5 seconds when the sensor was exposed to the target glucose in a buffer with a pH value of 7.4. The sensor could detect a wide range of concentrations from 0.5 nM to 125 μM. Conclusion There is great promise for using HEMT-based sensors to enhance the detection sensitivity for glucose detection in EBC. Depending on the immobilized material, HEMT-based sensors can be used for sensingt different materials. These electronic detection approaches with rapid response and good repeatability show potential for the investigation of airway pathology. The devices can also be integrated into a wireless data transmission system for remote monitoring applications. This sensor technology could use the exhaled breath condensate to

GaAs Monolithic Microwave Subsystem Technology Base

DTIC Science & Technology

1980-01-01

To provide a captive source of reliable, high-quality GaAs substrates, a new crystal growth and substrate preparation facility which utilizes a high...Symp. GaAs and Related Compounds, Inst. Phys. Conf. Ser. 24, 6. 20. Wood, Woodcock and Harris (1978) GaAs and Related Compounds, Inst. Phys. Conf

AlGaN-Cladding-Free m-Plane InGaN/GaN Laser Diodes with p-Type AlGaN Etch Stop Layers

NASA Astrophysics Data System (ADS)

Farrell, Robert M.; Haeger, Daniel A.; Hsu, Po Shan; Hardy, Matthew T.; Kelchner, Kathryn M.; Fujito, Kenji; Feezell, Daniel F.; Mishra, Umesh K.; DenBaars, Steven P.; Speck, James S.; Nakamura, Shuji

2011-09-01

We present a new method of improving the accuracy and reproducibility of dry etching processes for ridge waveguide InGaN/GaN laser diodes (LDs). A GaN:Al0.09Ga0.91N etch rate selectivity of 11:1 was demonstrated for an m-plane LD with a 40 nm p-Al0.09Ga0.91N etch stop layer (ESL) surrounded by Al-free cladding layers, establishing the effectiveness of AlGaN-based ESLs for controlling etch depth in ridge waveguide InGaN/GaN LDs. These results demonstrate the potential for integrating AlGaN ESLs into commercial device designs where accurate control of the etch depth of the ridge waveguide is necessary for stable, kink-free operation at high output powers.

An efficient multi-resolution GA approach to dental image alignment

NASA Astrophysics Data System (ADS)

Nassar, Diaa Eldin; Ogirala, Mythili; Adjeroh, Donald; Ammar, Hany

2006-02-01

Automating the process of postmortem identification of individuals using dental records is receiving an increased attention in forensic science, especially with the large volume of victims encountered in mass disasters. Dental radiograph alignment is a key step required for automating the dental identification process. In this paper, we address the problem of dental radiograph alignment using a Multi-Resolution Genetic Algorithm (MR-GA) approach. We use location and orientation information of edge points as features; we assume that affine transformations suffice to restore geometric discrepancies between two images of a tooth, we efficiently search the 6D space of affine parameters using GA progressively across multi-resolution image versions, and we use a Hausdorff distance measure to compute the similarity between a reference tooth and a query tooth subject to a possible alignment transform. Testing results based on 52 teeth-pair images suggest that our algorithm converges to reasonable solutions in more than 85% of the test cases, with most of the error in the remaining cases due to excessive misalignments.

Improved efficiency of InGaN/GaN-based multiple quantum well solar cells by reducing contact resistance

NASA Astrophysics Data System (ADS)

Song, Jun-Hyuk; Oh, Joon-Ho; Shim, Jae-Phil; Min, Jung-Hong; Lee, Dong-Seon; Seong, Tae-Yeon

2012-08-01

We report on the improvement in the performance of InGaN/GaN multi-quantum well-based solar cells by the introduction of a Cu-doped indium oxide (CIO) layer at the interface between indium tin oxide (ITO) p-electrode and p-GaN. The solar cell fabricated with the 3 nm-sample exhibits an external quantum efficiency of 29.8% (at a peak wavelength of 376 nm) higher than those (25.2%) of the cell with the ITO-only sample. The use of the 3-nm-thick CIO layer gives higher short circuit current density (0.72 mA/cm2) and fill factor (78.85%) as compared to those (0.65 mA/cm2 and 74.08%) of the ITO only sample. Measurements show that the conversion efficiency of the solar cells with the ITO-only sample and the 3 nm-sample is 1.12% and 1.30%, respectively. Based on their electrical and optical properties, the dependence of the CIO interlayer thickness on the efficiency of solar cells is discussed.

High-precision approach to localization scheme of visible light communication based on artificial neural networks and modified genetic algorithms

NASA Astrophysics Data System (ADS)

Guan, Weipeng; Wu, Yuxiang; Xie, Canyu; Chen, Hao; Cai, Ye; Chen, Yingcong

2017-10-01

An indoor positioning algorithm based on visible light communication (VLC) is presented. This algorithm is used to calculate a three-dimensional (3-D) coordinate of an indoor optical wireless environment, which includes sufficient orders of multipath reflections from reflecting surfaces of the room. Leveraging the global optimization ability of the genetic algorithm (GA), an innovative framework for 3-D position estimation based on a modified genetic algorithm is proposed. Unlike other techniques using VLC for positioning, the proposed system can achieve indoor 3-D localization without making assumptions about the height or acquiring the orientation angle of the mobile terminal. Simulation results show that an average localization error of less than 1.02 cm can be achieved. In addition, in most VLC-positioning systems, the effect of reflection is always neglected and its performance is limited by reflection, which makes the results not so accurate for a real scenario and the positioning errors at the corners are relatively larger than other places. So, we take the first-order reflection into consideration and use artificial neural network to match the model of a nonlinear channel. The studies show that under the nonlinear matching of direct and reflected channels the average positioning errors of four corners decrease from 11.94 to 0.95 cm. The employed algorithm is emerged as an effective and practical method for indoor localization and outperform other existing indoor wireless localization approaches.

Fabrication of full-color GaN-based light-emitting diodes on nearly lattice-matched flexible metal foils.

PubMed

Kim, Hyeryun; Ohta, Jitsuo; Ueno, Kohei; Kobayashi, Atsushi; Morita, Mari; Tokumoto, Yuki; Fujioka, Hiroshi

2017-05-18

GaN-based light-emitting diodes (LEDs) have been widely accepted as highly efficient solid-state light sources capable of replacing conventional incandescent and fluorescent lamps. However, their applications are limited to small devices because their fabrication process is expensive as it involves epitaxial growth of GaN by metal-organic chemical vapor deposition (MOCVD) on single crystalline sapphire wafers. If a low-cost epitaxial growth process such as sputtering on a metal foil can be used, it will be possible to fabricate large-area and flexible GaN-based light-emitting displays. Here we report preparation of GaN films on nearly lattice-matched flexible Hf foils using pulsed sputtering deposition (PSD) and demonstrate feasibility of fabricating full-color GaN-based LEDs. It was found that introduction of low-temperature (LT) grown layers suppressed the interfacial reaction between GaN and Hf, allowing the growth of high-quality GaN films on Hf foils. We fabricated blue, green, and red LEDs on Hf foils and confirmed their normal operation. The present results indicate that GaN films on Hf foils have potential applications in fabrication of future large-area flexible GaN-based optoelectronics.

MADM-based smart parking guidance algorithm

PubMed Central

Li, Bo; Pei, Yijian; Wu, Hao; Huang, Dijiang

2017-01-01

In smart parking environments, how to choose suitable parking facilities with various attributes to satisfy certain criteria is an important decision issue. Based on the multiple attributes decision making (MADM) theory, this study proposed a smart parking guidance algorithm by considering three representative decision factors (i.e., walk duration, parking fee, and the number of vacant parking spaces) and various preferences of drivers. In this paper, the expected number of vacant parking spaces is regarded as an important attribute to reflect the difficulty degree of finding available parking spaces, and a queueing theory-based theoretical method was proposed to estimate this expected number for candidate parking facilities with different capacities, arrival rates, and service rates. The effectiveness of the MADM-based parking guidance algorithm was investigated and compared with a blind search-based approach in comprehensive scenarios with various distributions of parking facilities, traffic intensities, and user preferences. Experimental results show that the proposed MADM-based algorithm is effective to choose suitable parking resources to satisfy users’ preferences. Furthermore, it has also been observed that this newly proposed Markov Chain-based availability attribute is more effective to represent the availability of parking spaces than the arrival rate-based availability attribute proposed in existing research. PMID:29236698

Method of plasma etching GA-based compound semiconductors

DOEpatents

Qiu, Weibin; Goddard, Lynford L.

2013-01-01

A method of plasma etching Ga-based compound semiconductors includes providing a process chamber and a source electrode adjacent thereto. The chamber contains a Ga-based compound semiconductor sample in contact with a platen which is electrically connected to a first power supply, and the source electrode is electrically connected to a second power supply. SiCl.sub.4 and Ar gases are flowed into the chamber. RF power is supplied to the platen at a first power level, and RF power is supplied to the source electrode. A plasma is generated. Then, RF power is supplied to the platen at a second power level lower than the first power level and no greater than about 30 W. Regions of a surface of the sample adjacent to one or more masked portions of the surface are etched at a rate of no more than about 25 nm/min to create a substantially smooth etched surface.

Inversion of particle-size distribution from angular light-scattering data with genetic algorithms.

PubMed

Ye, M; Wang, S; Lu, Y; Hu, T; Zhu, Z; Xu, Y

1999-04-20

A stochastic inverse technique based on a genetic algorithm (GA) to invert particle-size distribution from angular light-scattering data is developed. This inverse technique is independent of any given a priori information of particle-size distribution. Numerical tests show that this technique can be successfully applied to inverse problems with high stability in the presence of random noise and low susceptibility to the shape of distributions. It has also been shown that the GA-based inverse technique is more efficient in use of computing time than the inverse Monte Carlo method recently developed by Ligon et al. [Appl. Opt. 35, 4297 (1996)].

Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

PubMed Central

Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

2015-01-01

In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597

Hole transport in c-plane InGaN-based green laser diodes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheng, Yang; Liu, Jianping, E-mail: jpliu2010@sinano.ac.cn; Tian, Aiqin

2016-08-29

Hole transport in c-plane InGaN-based green laser diodes (LDs) has been investigated by both simulations and experiments. It is found that holes can overflow from the green double quantum wells (DQWs) at high current density, which reduces carrier injection efficiency of c-plane InGaN-based green LDs. A heavily silicon-doped layer right below the green DQWs can effectively suppress hole overflow from the green DQWs.

A new memetic algorithm for mitigating tandem automated guided vehicle system partitioning problem

NASA Astrophysics Data System (ADS)

Pourrahimian, Parinaz

2017-11-01

Automated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and controls conflicts and congestions. This paper presents the development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search (TS) has been developed and combined with a GA to refine the newly generated individuals by GA. The aim of the proposed algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated using Matlab. This study also compared the objective function of the proposed MA with GA. The results showed that the TS, as a local search, significantly improves the objective function of the GA for different system sizes with large and small numbers of zone by 1.26 in average.

Al x Ga1‑ x N-based semipolar deep ultraviolet light-emitting diodes

NASA Astrophysics Data System (ADS)

Akaike, Ryota; Ichikawa, Shuhei; Funato, Mitsuru; Kawakami, Yoichi

2018-06-01

Deep ultraviolet (UV) emission from Al x Ga1‑ x N-based light-emitting diodes (LEDs) fabricated on semipolar (1\\bar{1}02) (r-plane) AlN substrates is presented. The growth conditions are optimized. A high NH3 flow rate during metalorganic vapor phase epitaxy yields atomically flat Al y Ga1‑ y N (y > x) on which Al x Ga1‑ x N/Al y Ga1‑ y N multiple quantum wells with abrupt interfaces and good periodicity are fabricated. The fabricated r-Al x Ga1‑ x N-based LED emits at 270 nm, which is in the germicidal wavelength range. Additionally, the emission line width is narrow, and the peak wavelength is stable against the injection current, so the semipolar LED shows promise as a UV emitter.

Pilot-based parametric channel estimation algorithm for DCO-OFDM-based visual light communications

NASA Astrophysics Data System (ADS)

Qian, Xuewen; Deng, Honggui; He, Hailang

2017-10-01

Due to wide modulation bandwidth in optical communication, multipath channels may be non-sparse and deteriorate communication performance heavily. Traditional compressive sensing-based channel estimation algorithm cannot be employed in this kind of situation. In this paper, we propose a practical parametric channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based visual light communication (VLC) systems based on modified zero correlation code (ZCC) pair that has the impulse-like correlation property. Simulation results show that the proposed algorithm achieves better performances than existing least squares (LS)-based algorithm in both bit error ratio (BER) and frequency response estimation.

Modeling, design, fabrication and experimentation of a GaN-based, 63Ni betavoltaic battery

NASA Astrophysics Data System (ADS)

E Munson, C., IV; Gaimard, Q.; Merghem, K.; Sundaram, S.; Rogers, D. J.; de Sanoit, J.; Voss, P. L.; Ramdane, A.; Salvestrini, J. P.; Ougazzaden, A.

2018-01-01

GaN is a durable, radiation hard and wide-bandgap semiconductor material, making it ideal for usage with betavoltaic batteries. This paper describes the design, fabrication and experimental testing of 1 cm2 GaN-based betavoltaic batteries (that achieve an output power of 2.23 nW) along with a full model that accurately simulates the device performance which is the highest to date (to the best of our knowledge) for GaN-based devices with a 63Ni source.

High-electron-mobility GaN grown on free-standing GaN templates by ammonia-based molecular beam epitaxy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kyle, Erin C. H., E-mail: erinkyle@umail.ucsb.edu; Kaun, Stephen W.; Burke, Peter G.

2014-05-21

The dependence of electron mobility on growth conditions and threading dislocation density (TDD) was studied for n{sup −}-GaN layers grown by ammonia-based molecular beam epitaxy. Electron mobility was found to strongly depend on TDD, growth temperature, and Si-doping concentration. Temperature-dependent Hall data were fit to established transport and charge-balance equations. Dislocation scattering was analyzed over a wide range of TDDs (∼2 × 10{sup 6} cm{sup −2} to ∼2 × 10{sup 10} cm{sup −2}) on GaN films grown under similar conditions. A correlation between TDD and fitted acceptor states was observed, corresponding to an acceptor state for almost every c lattice translation along each threading dislocation. Optimizedmore » GaN growth on free-standing GaN templates with a low TDD (∼2 × 10{sup 6} cm{sup −2}) resulted in electron mobilities of 1265 cm{sup 2}/Vs at 296 K and 3327 cm{sup 2}/Vs at 113 K.« less

GaAs/AlOx high-contrast grating mirrors for mid-infrared VCSELs

NASA Astrophysics Data System (ADS)

Almuneau, G.; Laaroussi, Y.; Chevallier, C.; Genty, F.; Fressengeas, N. s.; Cerutti, L.; Gauthier-Lafaye, Olivier

2015-02-01

Mid-infrared Vertical cavity surface emitting lasers (MIR-VCSEL) are very attractive compact sources for spectroscopic measurements above 2μm, relevant for molecules sensing in various application domains. A long-standing issue for long wavelength VCSEL is the large structure thickness affecting the laser properties, added for the MIR to the tricky technological implementation of the antimonide alloys system. In this paper, we propose a new geometry for MIR-VCSEL including both a lateral confinement by an oxide aperture, and a high-contrast sub-wavelength grating mirror (HCG mirror) formed by the high contrast combination AIOx/GaAs in place of GaSb/A|AsSb top Bragg reflector. In addition to drastically simplifying the vertical stack, HCG mirror allows to control through its design the beam properties. The robust design of the HCG has been ensured by an original method of optimization based on particle swarm optimization algorithm combined with an anti-optimization one, thus allowing large error tolerance for the nano-fabrication. Oxide-based electro-optical confinement has been adapted to mid-infrared lasers, byusing a metamorphic approach with (Al) GaAs layer directly epitaxially grown on the GaSb-based VCSEL bottom structure. This approach combines the advantages of the will-controlled oxidation of AlAs layer and the efficient gain media of Sb-based for mid-infrared emission. We finally present the results obtained on electrically pumped mid-IR-VCSELs structures, for which we included oxide aperturing for lateral confinement and HCG as high reflectivity output mirrors, both based on AlxOy/GaAs heterostructures.

Evaluation of Demons- and FEM-Based Registration Algorithms for Lung Cancer.

PubMed

Yang, Juan; Li, Dengwang; Yin, Yong; Zhao, Fen; Wang, Hongjun

2016-04-01

We evaluated and compared the accuracy of 2 deformable image registration algorithms in 4-dimensional computed tomography images for patients with lung cancer. Ten patients with non-small cell lung cancer or small cell lung cancer were enrolled in this institutional review board-approved study. The displacement vector fields relative to a specific reference image were calculated by using the diffeomorphic demons (DD) algorithm and the finite element method (FEM)-based algorithm. The registration accuracy was evaluated by using normalized mutual information (NMI), the sum of squared intensity difference (SSD), modified Hausdorff distance (dH_M), and ratio of gross tumor volume (rGTV) difference between reference image and deformed phase image. We also compared the registration speed of the 2 algorithms. Of all patients, the FEM-based algorithm showed stronger ability in aligning 2 images than the DD algorithm. The means (±standard deviation) of NMI were 0.86 (±0.05) and 0.90 (±0.05) using the DD algorithm and the FEM-based algorithm, respectively. The means of SSD were 0.006 (±0.003) and 0.003 (±0.002) using the DD algorithm and the FEM-based algorithm, respectively. The means of dH_M were 0.04 (±0.02) and 0.03 (±0.03) using the DD algorithm and the FEM-based algorithm, respectively. The means of rGTV were 3.9% (±1.01%) and 2.9% (±1.1%) using the DD algorithm and the FEM-based algorithm, respectively. However, the FEM-based algorithm costs a longer time than the DD algorithm, with the average running time of 31.4 minutes compared to 21.9 minutes for all patients. The preliminary results showed that the FEM-based algorithm was more accurate than the DD algorithm while compromised with the registration speed. © The Author(s) 2015.

Microwave power amplifiers based on AlGaN/GaN transistors with a two-dimensional electron gas

NASA Astrophysics Data System (ADS)

Vendik, O. G.; Vendik, I. B.; Tural'chuk, P. A.; Parnes, Ya. M.; Parnes, M. D.

2016-11-01

A technique for synthesis of microwave power amplifiers based on transistors with a AlGaN/GaN heterojunction is discussed. Special focus is on the development of a technique for synthesis of transformation circuits of the power amplifier to increase efficiency with a retained high output power. The use of independent matching at the harmonic frequencies and fundamental frequency makes it possible to control the attainable efficiency in a wide frequency band along with the total suppression of harmonics beyond the operational band. Microwave power amplifiers for operation at 4 and 9 GHz have been developed and experimentally investigated.

A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Genrang; Lin, ZhengChun

The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

On Parallel Push-Relabel based Algorithms for Bipartite Maximum Matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langguth, Johannes; Azad, Md Ariful; Halappanavar, Mahantesh

2014-07-01

We study multithreaded push-relabel based algorithms for computing maximum cardinality matching in bipartite graphs. Matching is a fundamental combinatorial (graph) problem with applications in a wide variety of problems in science and engineering. We are motivated by its use in the context of sparse linear solvers for computing maximum transversal of a matrix. We implement and test our algorithms on several multi-socket multicore systems and compare their performance to state-of-the-art augmenting path-based serial and parallel algorithms using a testset comprised of a wide range of real-world instances. Building on several heuristics for enhancing performance, we demonstrate good scaling for themore » parallel push-relabel algorithm. We show that it is comparable to the best augmenting path-based algorithms for bipartite matching. To the best of our knowledge, this is the first extensive study of multithreaded push-relabel based algorithms. In addition to a direct impact on the applications using matching, the proposed algorithmic techniques can be extended to preflow-push based algorithms for computing maximum flow in graphs.« less

Anodic etching of GaN based film with a strong phase-separated InGaN/GaN layer: Mechanism and properties

NASA Astrophysics Data System (ADS)

Gao, Qingxue; Liu, Rong; Xiao, Hongdi; Cao, Dezhong; Liu, Jianqiang; Ma, Jin

2016-11-01

A strong phase-separated InGaN/GaN layer, which consists of multiple quantum wells (MQW) and superlattices (SL) layers and can produce a blue wavelength spectrum, has been grown on n-GaN thin film, and then fabricated into nanoporous structures by electrochemical etching method in oxalic acid. Scanning electron microscopy (SEM) technique reveals that the etching voltage of 8 V leads to a vertically aligned nanoporous structure, whereas the films etched at 15 V show branching pores within the n-GaN layer. Due to the low doping concentration of barriers (GaN layers) in the InGaN/GaN layer, we observed a record-low rate of etching (<100 nm/min) and nanopores which are mainly originated from the V-pits in the phase-separated layer. In addition, there exists a horizontal nanoporous structure at the interface between the phase-separated layer and the n-GaN layer, presumably resulting from the high transition of electrons between the barrier and the well (InGaN layer) at the interface. As compared to the as-grown MQW structure, the etched MQW structure exhibits a photoluminescence (PL) enhancement with a partial relaxation of compressive stress due to the increased light-extracting surface area and light-guiding effect. Such a compressive stress relaxation can be further confirmed by Raman spectra.

Characteristics of GaN-based LEDs using Ga-doped or In-doped ZnO transparent conductive layers grown by atomic layer deposition

NASA Astrophysics Data System (ADS)

Yen, Kuo-Yi; Chiu, Chien-Hua; Hsiao, Chi-Ying; Li, Chun-Wei; Chou, Chien-Hua; Lo, Ko-Ying; Chen, Tzu-Pei; Lin, Chu-Hsien; Lin, Tai-Yuan; Gong, Jyh-Rong

2014-02-01

Ga-doped ZnO (GZO) and In-doped ZnO (IZO) films were prepared by atomic layer deposition (ALD), and the ALD-grown GZO (or IZO) films with (or without) N2 annealing were employed to serve as transparent conducting layers (TCLs) in InGaN/GaN (multiple quantum well) MQW LEDs. Based on θ-to-2θ X-ray diffraction (XRD) analyses, the N2-annealed GZO was found to show almost the same lattice constant c as ZnO does, while the lattice constant c of a N2-annealed IZO was detected to be larger than that of the ZnO. It appears that the implementation of N2-annealed ALD-grown GZO (or IZO) in an InGaN/GaN MQW LED allows to enable light extraction and forward voltage reduction of the LED under certain conditions. At 20 mA operating condition, the 400 °C N2-annealed n-GZO-coated and the 600 °C N2-annealed n-IZO-coated InGaN/GaN MQW LEDs were found to exhibit optimized forward voltages of 3.1 and 3.2 V, respectively, with the specific contact resistances of the n-GZO/p-GaN and n-IZO/p-GaN contacts being 4.1×10-3 and 8.8×10-3 Ω-cm2. By comparing with an InGaN/GaN MQW LED structure having a commercial-grade indium tin oxide (ITO) TCL, the 400 °C N2-annealed n-GZO-coated InGaN/GaN MQW LED shows an increment of light output power of 15% at 20 mA. It is believed that the enhanced light extraction of the n-GZO-coated InGaN/GaN MQW LED is due to a higher refractive index of n-GZO than that of ITO along with a comparable optical transmittance of n-GZO to that of ITO.

Aging behavior of Au-based ohmic contacts to GaAs

NASA Technical Reports Server (NTRS)

Fatemi, Navid S.

1989-01-01

Gold based alloys, commonly used as ohmic contacts for solar cells, are known to react readily with GaAs. It is shown that the contact interaction with the underlying GaAs can continue even at room temperature upon aging, altering both the electrical characteristics of the contacts and the nearby pn junction. Au-Ge-Ni as-deposited (no heat-treatment) contacts made to thin emitter (0.15 microns) GaAs diodes have shown severe shunting of the pn junction upon aging for several months at room temperature. The heat-treated contacts, despite showing degradation in contact resistance, did not affect the underlying pn junction. Au-Zn-Au contacts to p-GaAs emitter (0.2 microns) diodes, however, showed slight improvement in contact resistance upon 200 C isothermal annealing for several months, without degrading the pn junction. The effect of aging on electrical characteristics of the as-deposited and heat-treated contacts and the nearby pn junction, as well as on the surface morphology of the contacts are presented.

Aging behavior of Au-based ohmic contacts to GaAs

NASA Technical Reports Server (NTRS)

Fatemi, Navid S.

1988-01-01

Gold based alloys, commonly used as ohmic contacts for solar cells, are known to react readily with GaAs. It is shown that the contact interaction with the underlying GaAs can continue even at room temperature upon aging, altering both the electrical characteristics of the contacts and the nearby pn junction. Au-Ge-Ni as-deposited (no heat treatment) contacts made to thin emitter (0.15 micrometer) GaAs diodes have shown severe shunting of the pn junction upon aging for several months at room temperature. The heat-treated contacts, despite showing degradation in contact resistance did not affect the underlying pn junction. Au-Zn-Au contacts to p-GaAs emitter (0.2 micrometer) diodes, however, showed slight improvement in contact resistance upon 200 C isothermal annealing for several months, without degrading the pn junction. The effect of aging on electrical characteristics of the as-deposited and heat-treated contacts and the nearby pn junction, as well as on the surface morphology of the contacts are presented.

Ga metal nanoparticle-GaAs quantum molecule complexes for Terahertz generation.

PubMed

Bietti, Sergio; Basso Basset, Francesco; Scarpellini, David; Fedorov, Alexey; Ballabio, Andrea; Esposito, Luca; Elborg, Martin; Kuroda, Takashi; Nemcsics, Akos; Toth, Lajos; Manzoni, Cristian; Vozzi, Caterina; Sanguinetti, Stefano

2018-06-18

A hybrid metal-semiconductor nanosystem for the generation of THz radiation, based on the fabrication of GaAs quantum molecules-Ga metal nanoparticles complexes through a self assembly approach, is proposed. The role of the growth parameters, the substrate temperature, the Ga and As flux during the quantum dot molecule fabrication and the metal nanoparticle alignment is discussed. The tuning of the relative positioning of quantum dot molecules and metal nanoparticles is obtained through the careful control of Ga droplet nucleation sites via Ga surface diffusion. The electronic structure of a typical quantum dot molecule was evaluated on the base of the morphological characterizations performed by Atomic Force Microscopy and cross sectional Scanning Electron Microscopy, and the predicted results confirmed by micro-photoluminescence experiments, showing that the Ga metal nanoparticle-GaAs quantum molecule complexes are suitable for terahertz generation from intraband transition. . © 2018 IOP Publishing Ltd.

Absolute GPS Positioning Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Ramillien, G.

A new inverse approach for restoring the absolute coordinates of a ground -based station from three or four observed GPS pseudo-ranges is proposed. This stochastic method is based on simulations of natural evolution named genetic algorithms (GA). These iterative procedures provide fairly good and robust estimates of the absolute positions in the Earth's geocentric reference system. For comparison/validation, GA results are compared to the ones obtained using the classical linearized least-square scheme for the determination of the XYZ location proposed by Bancroft (1985) which is strongly limited by the number of available observations (i.e. here, the number of input pseudo-ranges must be four). The r.m.s. accuracy of the non -linear cost function reached by this latter method is typically ~10-4 m2 corresponding to ~300-500-m accuracies for each geocentric coordinate. However, GA can provide more acceptable solutions (r.m.s. errors < 10-5 m2), even when only three instantaneous pseudo-ranges are used, such as a lost of lock during a GPS survey. Tuned GA parameters used in different simulations are N=1000 starting individuals, as well as Pc=60-70% and Pm=30-40% for the crossover probability and mutation rate, respectively. Statistical tests on the ability of GA to recover acceptable coordinates in presence of important levels of noise are made simulating nearly 3000 random samples of erroneous pseudo-ranges. Here, two main sources of measurement errors are considered in the inversion: (1) typical satellite-clock errors and/or 300-metre variance atmospheric delays, and (2) Geometrical Dilution of Precision (GDOP) due to the particular GPS satellite configuration at the time of acquisition. Extracting valuable information and even from low-quality starting range observations, GA offer an interesting alternative for high -precision GPS positioning.

GaN-Based High Temperature and Radiation-Hard Electronics for Harsh Environments

NASA Technical Reports Server (NTRS)

Son, Kyung-ah; Liao, Anna; Lung, Gerald; Gallegos, Manuel; Hatakeh, Toshiro; Harris, Richard D.; Scheick, Leif Z.; Smythe, William D.

2010-01-01

We develop novel GaN-based high temperature and radiation-hard electronics to realize data acquisition electronics and transmitters suitable for operations in harsh planetary environments. In this paper, we discuss our research on metal-oxide-semiconductor (MOS) transistors that are targeted for 500 (sup o)C operation and >2 Mrad radiation hardness. For the target device performance, we develop Schottky-free AlGaN/GaN MOS transistors, where a gate electrode is processed in a MOS layout using an Al2O3 gate dielectric layer....

Design of Low Inductance Switching Power Cell for GaN HEMT Based Inverter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gurpinar, Emre; Iannuzzo, Francesco; Yang, Yongheng

Here in this paper, an ultra-low inductance power cell is designed for a three-Level Active Neutral Point Clamped (3LANPC) based on 650 V gallium nitride (GaN) HEMT devices. The 3L-ANPC topology with GaN HEMT devices and the selected modulation scheme suitable for wide-bandgap (WBG) devices are presented. The commutation loops, which mainly contribute to voltage overshoots and increase of switching losses, are discussed. The ultra-low inductance power cell design based on a fourlayer Printed Circuit Board (PCB) with the aim to maximize the switching performance of GaN HEMTs is explained. The design of gate drivers for the GaN HEMT devicesmore » is presented. Parasitic inductance and resistance of the proposed design are extracted with finite element analysis and discussed. Common mode behaviours based on the SPICE model of the converter are analyzed. Experimental results on the designed 3L-ANPC with the output power of up to 1 kW are presented, which verifies the performance of the proposed design in terms of ultra-low inductance.« less

Comparing a Coevolutionary Genetic Algorithm for Multiobjective Optimization

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Kraus, William F.; Haith, Gary L.; Clancy, Daniel (Technical Monitor)

2002-01-01

We present results from a study comparing a recently developed coevolutionary genetic algorithm (CGA) against a set of evolutionary algorithms using a suite of multiobjective optimization benchmarks. The CGA embodies competitive coevolution and employs a simple, straightforward target population representation and fitness calculation based on developmental theory of learning. Because of these properties, setting up the additional population is trivial making implementation no more difficult than using a standard GA. Empirical results using a suite of two-objective test functions indicate that this CGA performs well at finding solutions on convex, nonconvex, discrete, and deceptive Pareto-optimal fronts, while giving respectable results on a nonuniform optimization. On a multimodal Pareto front, the CGA finds a solution that dominates solutions produced by eight other algorithms, yet the CGA has poor coverage across the Pareto front.

Non-equilibrium Green's function calculation for GaN-based terahertz-quantum cascade laser structures

NASA Astrophysics Data System (ADS)

Yasuda, H.; Kubis, T.; Hosako, I.; Hirakawa, K.

2012-04-01

We theoretically investigated GaN-based resonant phonon terahertz-quantum cascade laser (QCL) structures for possible high-temperature operation by using the non-equilibrium Green's function method. It was found that the GaN-based THz-QCL structures do not necessarily have a gain sufficient for lasing, even though the thermal backfilling and the thermally activated phonon scattering are effectively suppressed. The main reason for this is the broadening of the subband levels caused by a very strong interaction between electrons and longitudinal optical (LO) phonons in GaN.

DeMAID/GA an Enhanced Design Manager's Aid for Intelligent Decomposition

NASA Technical Reports Server (NTRS)

Rogers, J. L.

1996-01-01

Many companies are looking for new tools and techniques to aid a design manager in making decisions that can reduce the time and cost of a design cycle. One tool is the Design Manager's Aid for Intelligent Decomposition (DeMAID). Since the initial public release of DeMAID in 1989, much research has been done in the areas of decomposition, concurrent engineering, parallel processing, and process management; many new tools and techniques have emerged. Based on these recent research and development efforts, numerous enhancements have been added to DeMAID to further aid the design manager in saving both cost and time in a design cycle. The key enhancement, a genetic algorithm (GA), will be available in the next public release called DeMAID/GA. The GA sequences the design processes to minimize the cost and time in converging a solution. The major enhancements in the upgrade of DeMAID to DeMAID/GA are discussed in this paper. A sample conceptual design project is used to show how these enhancements can be applied to improve the design cycle.

A community detection algorithm based on structural similarity

NASA Astrophysics Data System (ADS)

Guo, Xuchao; Hao, Xia; Liu, Yaqiong; Zhang, Li; Wang, Lu

2017-09-01

In order to further improve the efficiency and accuracy of community detection algorithm, a new algorithm named SSTCA (the community detection algorithm based on structural similarity with threshold) is proposed. In this algorithm, the structural similarities are taken as the weights of edges, and the threshold k is considered to remove multiple edges whose weights are less than the threshold, and improve the computational efficiency. Tests were done on the Zachary’s network, Dolphins’ social network and Football dataset by the proposed algorithm, and compared with GN and SSNCA algorithm. The results show that the new algorithm is superior to other algorithms in accuracy for the dense networks and the operating efficiency is improved obviously.

Engineering of electric field distribution in GaN(cap)/AlGaN/GaN heterostructures: theoretical and experimental studies

NASA Astrophysics Data System (ADS)

Gladysiewicz, M.; Janicki, L.; Misiewicz, J.; Sobanska, M.; Klosek, K.; Zytkiewicz, Z. R.; Kudrawiec, R.

2016-09-01

Polarization engineering of GaN-based heterostructures opens a way to develop advanced transistor heterostructures, although measurement of the electric field in such heterostructures is not a simple task. In this work, contactless electroreflectance (CER) spectroscopy has been applied to measure the electric field in GaN-based heterostructures. For a set of GaN(d  =  0, 5, 15, and 30 nm)/AlGaN(20 nm)/GaN(buffer) heterostructures a decrease of electric field in the GaN(cap) layer from 0.66 MV cm-1 to 0.27 MV cm-1 and an increase of the electric field in the AlGaN layer from 0.57 MV cm-1 to 0.99 MV cm-1 have been observed with the increase in the GaN(cap) thickness from 5-30 nm. For a set of GaN(20 nm)/AlGaN(d  =  10, 20, 30, and 40 nm)/GaN(buffer) heterostructures a decrease of the electric field in the AlGaN layer from 1.77 MV cm-1 to 0.64 MV cm-1 and an increase of the electric field in the GaN layer from 0.57 MV cm-1 to 0.99 MV cm-1 were observed with the increase in the AlGaN thickness from 10-40 nm. To determine the distribution of the electric field in these heterostructures the Schrödinger and Poisson equations are solved in a self-consistent manner and matched with experimental data. It is shown that the built-in electric field in the GaN(cap) and AlGaN layers obtained from measurements does not reach values of electric field resulting only from polarization effects. The measured electric fields are smaller due to a screening of polarization effects by free carriers, which are inhomogeneously distributed across the heterostructure and accumulate at interfaces. The results clearly demonstrate that CER measurements supported by theoretical calculations are able to determine the electric field distribution in GaN-based heterostructures quantitatively, which is very important for polarization engineering in this material system.

An investigation of messy genetic algorithms

NASA Technical Reports Server (NTRS)

Goldberg, David E.; Deb, Kalyanmoy; Korb, Bradley

1990-01-01

Genetic algorithms (GAs) are search procedures based on the mechanics of natural selection and natural genetics. They combine the use of string codings or artificial chromosomes and populations with the selective and juxtapositional power of reproduction and recombination to motivate a surprisingly powerful search heuristic in many problems. Despite their empirical success, there has been a long standing objection to the use of GAs in arbitrarily difficult problems. A new approach was launched. Results to a 30-bit, order-three-deception problem were obtained using a new type of genetic algorithm called a messy genetic algorithm (mGAs). Messy genetic algorithms combine the use of variable-length strings, a two-phase selection scheme, and messy genetic operators to effect a solution to the fixed-coding problem of standard simple GAs. The results of the study of mGAs in problems with nonuniform subfunction scale and size are presented. The mGA approach is summarized, both its operation and the theory of its use. Experiments on problems of varying scale, varying building-block size, and combined varying scale and size are presented.

Growth temperature optimization of GaAs-based In0.83Ga0.17As on InxAl1-xAs buffers

NASA Astrophysics Data System (ADS)

Chen, X. Y.; Gu, Y.; Zhang, Y. G.; Ma, Y. J.; Du, B.; Zhang, J.; Ji, W. Y.; Shi, Y. H.; Zhu, Y.

2018-04-01

Improved quality of gas source molecular beam epitaxy grown In0.83Ga0.17As layer on GaAs substrate was achieved by adopting a two-step InxAl1-xAs metamorphic buffer at different temperatures. With a high-temperature In0.83Al0.17As template following a low-temperature composition continuously graded InxAl1-xAs (x = 0.05-0.86) buffer, better structural, optical and electrical properties of succeeding In0.83Ga0.17As were confirmed by atomic force microscopy, photoluminescence and Hall-effect measurements. Cross-sectional transmission electron microscopy revealed significant effect of the two-step temperature grown InAlAs buffer layers on the inhibition of threading dislocations due to the deposition of high density nuclei on GaAs substrate at the low growth temperature. The limited reduction for the dark current of GaAs-based In0.83Ga0.17As photodetectors on the two-step temperature grown InxAl1-xAs buffer layers was ascribed to the contribution of impurities caused by the low growth temperature of InAlAs buffers.

WS-BP: An efficient wolf search based back-propagation algorithm

NASA Astrophysics Data System (ADS)

Nawi, Nazri Mohd; Rehman, M. Z.; Khan, Abdullah

2015-05-01

Wolf Search (WS) is a heuristic based optimization algorithm. Inspired by the preying and survival capabilities of the wolves, this algorithm is highly capable to search large spaces in the candidate solutions. This paper investigates the use of WS algorithm in combination with back-propagation neural network (BPNN) algorithm to overcome the local minima problem and to improve convergence in gradient descent. The performance of the proposed Wolf Search based Back-Propagation (WS-BP) algorithm is compared with Artificial Bee Colony Back-Propagation (ABC-BP), Bat Based Back-Propagation (Bat-BP), and conventional BPNN algorithms. Specifically, OR and XOR datasets are used for training the network. The simulation results show that the WS-BP algorithm effectively avoids the local minima and converge to global minima.

Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems.

PubMed

Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K

2017-12-19

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  <  ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K.

2018-01-01

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  <  ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

Heuristic rules embedded genetic algorithm for in-core fuel management optimization

NASA Astrophysics Data System (ADS)

Alim, Fatih

The objective of this study was to develop a unique methodology and a practical tool for designing loading pattern (LP) and burnable poison (BP) pattern for a given Pressurized Water Reactor (PWR) core. Because of the large number of possible combinations for the fuel assembly (FA) loading in the core, the design of the core configuration is a complex optimization problem. It requires finding an optimal FA arrangement and BP placement in order to achieve maximum cycle length while satisfying the safety constraints. Genetic Algorithms (GA) have been already used to solve this problem for LP optimization for both PWR and Boiling Water Reactor (BWR). The GA, which is a stochastic method works with a group of solutions and uses random variables to make decisions. Based on the theories of evaluation, the GA involves natural selection and reproduction of the individuals in the population for the next generation. The GA works by creating an initial population, evaluating it, and then improving the population by using the evaluation operators. To solve this optimization problem, a LP optimization package, GARCO (Genetic Algorithm Reactor Code Optimization) code is developed in the framework of this thesis. This code is applicable for all types of PWR cores having different geometries and structures with an unlimited number of FA types in the inventory. To reach this goal, an innovative GA is developed by modifying the classical representation of the genotype. To obtain the best result in a shorter time, not only the representation is changed but also the algorithm is changed to use in-core fuel management heuristics rules. The improved GA code was tested to demonstrate and verify the advantages of the new enhancements. The developed methodology is explained in this thesis and preliminary results are shown for the VVER-1000 reactor hexagonal geometry core and the TMI-1 PWR. The improved GA code was tested to verify the advantages of new enhancements. The core physics code

Evidence-based algorithm for heparin dosing before cardiopulmonary bypass. Part 1: Development of the algorithm.

PubMed

McKinney, Mark C; Riley, Jeffrey B

2007-12-01

The incidence of heparin resistance during adult cardiac surgery with cardiopulmonary bypass has been reported at 15%-20%. The consistent use of a clinical decision-making algorithm may increase the consistency of patient care and likely reduce the total required heparin dose and other problems associated with heparin dosing. After a directed survey of practicing perfusionists regarding treatment of heparin resistance and a literature search for high-level evidence regarding the diagnosis and treatment of heparin resistance, an evidence-based decision-making algorithm was constructed. The face validity of the algorithm decisive steps and logic was confirmed by a second survey of practicing perfusionists. The algorithm begins with review of the patient history to identify predictors for heparin resistance. The definition for heparin resistance contained in the algorithm is an activated clotting time < 450 seconds with > 450 IU/kg heparin loading dose. Based on the literature, the treatment for heparin resistance used in the algorithm is anti-thrombin III supplement. The algorithm seems to be valid and is supported by high-level evidence and clinician opinion. The next step is a human randomized clinical trial to test the clinical procedure guideline algorithm vs. current standard clinical practice.

Investigation of GaAs/Al(x)Ga(1-x)As and In(y)Ga(1-y)As/GaAs superlattices on Si substrates

NASA Technical Reports Server (NTRS)

Reddy, U. K.; Ji, G.; Huang, D.; Munns, G.; Morkoc, H.

1987-01-01

The optical properties of lattice-matched GaAs/Al(x)Ga(1-x)As and In(y)Ga(1-y)As/GaAs strained-layer superlattices grown on Si substrates have been studied using the photoreflectance technique. These preliminary results show that good quality III-IV epilayers can be grown on Si. The experimental data were compared with calculations based on the envelope-function approximation and fitted to the third-derivative functional form of reflectance modulation theory.

Application of genetic algorithms to tuning fuzzy control systems

NASA Technical Reports Server (NTRS)

Espy, Todd; Vombrack, Endre; Aldridge, Jack

1993-01-01

Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.

A range-based predictive localization algorithm for WSID networks

NASA Astrophysics Data System (ADS)

Liu, Yuan; Chen, Junjie; Li, Gang

2017-11-01

Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

Receiver Diversity Combining Using Evolutionary Algorithms in Rayleigh Fading Channel

PubMed Central

Akbari, Mohsen; Manesh, Mohsen Riahi

2014-01-01

In diversity combining at the receiver, the output signal-to-noise ratio (SNR) is often maximized by using the maximal ratio combining (MRC) provided that the channel is perfectly estimated at the receiver. However, channel estimation is rarely perfect in practice, which results in deteriorating the system performance. In this paper, an imperialistic competitive algorithm (ICA) is proposed and compared with two other evolutionary based algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA), for diversity combining of signals travelling across the imperfect channels. The proposed algorithm adjusts the combiner weights of the received signal components in such a way that maximizes the SNR and minimizes the bit error rate (BER). The results indicate that the proposed method eliminates the need of channel estimation and can outperform the conventional diversity combining methods. PMID:25045725

InGaP-based quantum well solar cells: Growth, structural design, and photovoltaic properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hashem, Islam E.; Zachary Carlin, C.; Hagar, Brandon G.

2016-03-07

Raising the efficiency ceiling of multi-junction solar cells (MJSCs) through the use of more optimal band gap configurations of next-generation MJSC is crucial for concentrator and space systems. Towards this goal, we propose two strain balanced multiple quantum well (SBMQW) structures to tune the bandgap of InGaP-based solar cells. These structures are based on In{sub x}Ga{sub 1−x}As{sub 1−z}P{sub z}/In{sub y}Ga{sub 1−y}P (x > y) and In{sub x}Ga{sub 1−x}P/In{sub y}Ga{sub 1−y}P (x > y) well/barrier combinations, lattice matched to GaAs in a p-i-n solar cell device. The bandgap of In{sub x}Ga{sub 1−x}As{sub 1−z}P{sub z}/In{sub y}Ga{sub 1−y}P can be tuned from 1.82 to 1.65 eV by adjustingmore » the well composition and thickness, which promotes its use as an efficient subcell for next generation five and six junction photovoltaic devices. The thicknesses of wells and barriers are adjusted using a zero net stress balance model to prevent the formation of defects. Thin layers of InGaAsP wells have been grown thermodynamically stable with compositions within the miscibility gap for the bulk alloy. The growth conditions of the two SBMQWs and the individual layers are reported. The structures are characterized and analyzed by optical microscopy, X-ray diffraction, photoluminescence, current-voltage characteristics, and spectral response (external quantum efficiency). The effect of the well number on the excitonic absorption of InGaAsP/InGaP SBMQWs is discussed and analyzed.« less

DE and NLP Based QPLS Algorithm

NASA Astrophysics Data System (ADS)

Yu, Xiaodong; Huang, Dexian; Wang, Xiong; Liu, Bo

As a novel evolutionary computing technique, Differential Evolution (DE) has been considered to be an effective optimization method for complex optimization problems, and achieved many successful applications in engineering. In this paper, a new algorithm of Quadratic Partial Least Squares (QPLS) based on Nonlinear Programming (NLP) is presented. And DE is used to solve the NLP so as to calculate the optimal input weights and the parameters of inner relationship. The simulation results based on the soft measurement of diesel oil solidifying point on a real crude distillation unit demonstrate that the superiority of the proposed algorithm to linear PLS and QPLS which is based on Sequential Quadratic Programming (SQP) in terms of fitting accuracy and computational costs.

Time series segmentation: a new approach based on Genetic Algorithm and Hidden Markov Model

NASA Astrophysics Data System (ADS)

Toreti, A.; Kuglitsch, F. G.; Xoplaki, E.; Luterbacher, J.

2009-04-01

The subdivision of a time series into homogeneous segments has been performed using various methods applied to different disciplines. In climatology, for example, it is accompanied by the well-known homogenization problem and the detection of artificial change points. In this context, we present a new method (GAMM) based on Hidden Markov Model (HMM) and Genetic Algorithm (GA), applicable to series of independent observations (and easily adaptable to autoregressive processes). A left-to-right hidden Markov model, estimating the parameters and the best-state sequence, respectively, with the Baum-Welch and Viterbi algorithms, was applied. In order to avoid the well-known dependence of the Baum-Welch algorithm on the initial condition, a Genetic Algorithm was developed. This algorithm is characterized by mutation, elitism and a crossover procedure implemented with some restrictive rules. Moreover the function to be minimized was derived following the approach of Kehagias (2004), i.e. it is the so-called complete log-likelihood. The number of states was determined applying a two-fold cross-validation procedure (Celeux and Durand, 2008). Being aware that the last issue is complex, and it influences all the analysis, a Multi Response Permutation Procedure (MRPP; Mielke et al., 1981) was inserted. It tests the model with K+1 states (where K is the state number of the best model) if its likelihood is close to K-state model. Finally, an evaluation of the GAMM performances, applied as a break detection method in the field of climate time series homogenization, is shown. 1. G. Celeux and J.B. Durand, Comput Stat 2008. 2. A. Kehagias, Stoch Envir Res 2004. 3. P.W. Mielke, K.J. Berry, G.W. Brier, Monthly Wea Rev 1981.

A difference tracking algorithm based on discrete sine transform

NASA Astrophysics Data System (ADS)

Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

2018-04-01

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

Redundancy checking algorithms based on parallel novel extension rule

NASA Astrophysics Data System (ADS)

Liu, Lei; Yang, Yang; Li, Guangli; Wang, Qi; Lü, Shuai

2017-05-01

Redundancy checking (RC) is a key knowledge reduction technology. Extension rule (ER) is a new reasoning method, first presented in 2003 and well received by experts at home and abroad. Novel extension rule (NER) is an improved ER-based reasoning method, presented in 2009. In this paper, we first analyse the characteristics of the extension rule, and then present a simple algorithm for redundancy checking based on extension rule (RCER). In addition, we introduce MIMF, a type of heuristic strategy. Using the aforementioned rule and strategy, we design and implement RCHER algorithm, which relies on MIMF. Next we design and implement an RCNER (redundancy checking based on NER) algorithm based on NER. Parallel computing greatly accelerates the NER algorithm, which has weak dependence among tasks when executed. Considering this, we present PNER (parallel NER) and apply it to redundancy checking and necessity checking. Furthermore, we design and implement the RCPNER (redundancy checking based on PNER) and NCPPNER (necessary clause partition based on PNER) algorithms as well. The experimental results show that MIMF significantly influences the acceleration of algorithm RCER in formulae on a large scale and high redundancy. Comparing PNER with NER and RCPNER with RCNER, the average speedup can reach up to the number of task decompositions when executed. Comparing NCPNER with the RCNER-based algorithm on separating redundant formulae, speedup increases steadily as the scale of the formulae is incrementing. Finally, we describe the challenges that the extension rule will be faced with and suggest possible solutions.

From Competence to Efficiency: A Tale of GA Progress

NASA Technical Reports Server (NTRS)

Goldberg, David E.

1996-01-01

Genetic algorithms (GAs) - search procedures based on the mechanics of natural selection and genetics - have grown in popularity for the solution of difficult optimization problems. Concomitant with this growth has been a rising cacaphony of complaint asserting that too much time must be spent by the GA practitioner diddling with codes, operators, and GA parameters; and even then these GA cassandras continue, and the user is still unsure that the effort will meet with success. At the same time, there has been a rising interest in GA theory by a growing community - a theorocracy - of mathematicians and theoretical computer scientists, and these individuals have turned their efforts increasingly toward elegant abstract theorems and proofs that seem to the practitioner to offer little in the way of answers for GA design or practice. What both groups seem to have missed is the largely unheralded 1993 assembly of integrated, applicable theory and its experimental confirmation. This theory has done two key things. First, it has predicted that simple GAs are severely limited in the difficulty of problems they can solve, and these limitations have been confirmed experimentally. Second, it has shown the path to circumventing these limitations in nontraditional GA designs such as the fast messy GA. This talk surveys the history, methodology, and accomplishment of the 1993 applicable theory revolution. After arguing that these accomplishments open the door to universal GA competence, the paper shifts the discussion to the possibility of universal GA efficiency in the utilization of time and real estate through effective parallelization, temporal decomposition, hybridization, and relaxed function evaluation. The presentation concludes by suggesting that these research directions are quickly taking us to a golden age of adaptation.

Internal quantum efficiency in yellow-amber light emitting AlGaN-InGaN-GaN heterostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ngo, Thi Huong; Gil, Bernard; Valvin, Pierre

2015-09-21

We determine the internal quantum efficiency of strain-balanced AlGaN-InGaN-GaN hetero-structures designed for yellow-amber light emission, by using a recent model based on the kinetics of the photoluminescence decay initiated by Iwata et al. [J. Appl. Phys. 117, 075701 (2015)]. Our results indicate that low temperature internal quantum efficiencies sit in the 50% range and we measure that adding an AlGaN layer increases the internal quantum efficiency from 50% up to 57% with respect to the GaN-InGaN case. More dramatic, it almost doubles from 2.5% up to 4.3% at room temperature.

Genetic Algorithm Design of a 3D Printed Heat Sink

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Tong; Ozpineci, Burak; Ayers, Curtis William

2016-01-01

In this paper, a genetic algorithm- (GA-) based approach is discussed for designing heat sinks based on total heat generation and dissipation for a pre-specified size andshape. This approach combines random iteration processesand genetic algorithms with finite element analysis (FEA) to design the optimized heat sink. With an approach that prefers survival of the fittest , a more powerful heat sink can bedesigned which can cool power electronics more efficiently. Some of the resulting designs can only be 3D printed due totheir complexity. In addition to describing the methodology, this paper also includes comparisons of different cases to evaluate themore » performance of the newly designed heat sinkcompared to commercially available heat sinks.« less

GA-optimization for rapid prototype system demonstration

NASA Technical Reports Server (NTRS)

Kim, Jinwoo; Zeigler, Bernard P.

1994-01-01

An application of the Genetic Algorithm (GA) is discussed. A novel scheme of Hierarchical GA was developed to solve complicated engineering problems which require optimization of a large number of parameters with high precision. High level GAs search for few parameters which are much more sensitive to the system performance. Low level GAs search in more detail and employ a greater number of parameters for further optimization. Therefore, the complexity of the search is decreased and the computing resources are used more efficiently.

Implementation of atomic layer deposition-based AlON gate dielectrics in AlGaN/GaN MOS structure and its physical and electrical properties

NASA Astrophysics Data System (ADS)

Nozaki, Mikito; Watanabe, Kenta; Yamada, Takahiro; Shih, Hong-An; Nakazawa, Satoshi; Anda, Yoshiharu; Ueda, Tetsuzo; Yoshigoe, Akitaka; Hosoi, Takuji; Shimura, Takayoshi; Watanabe, Heiji

2018-06-01

Alumina incorporating nitrogen (aluminum oxynitride; AlON) for immunity against charge injection was grown on a AlGaN/GaN substrate through the repeated atomic layer deposition (ALD) of AlN layers and in situ oxidation in ozone (O3) ambient under optimized conditions. The nitrogen distribution was uniform in the depth direction, the composition was controllable over a wide range (0.5–32%), and the thickness could be precisely controlled. Physical analysis based on synchrotron radiation X-ray photoelectron spectroscopy (SR-XPS) revealed that harmful intermixing at the insulator/AlGaN interface causing Ga out-diffusion in the gate stack was effectively suppressed by this method. AlON/AlGaN/GaN MOS capacitors were fabricated, and they had excellent electrical properties and immunity against electrical stressing as a result of the improved interface stability.

Comparison of alloy disorder scatterings in Ga- and N-polar AlGaN/GaN heterostructures

NASA Astrophysics Data System (ADS)

Kang, He; Li, Hui-Jie; Yang, Shao-Yan; Zhang, Wei; Zhu, Ming; Liu, Li; Li, Nan

2018-01-01

The two-dimensional electron gas (2DEG) mobilities limited by alloy disorder (AD) scattering in both Ga- and N-polar AlGaN/GaN heterostructures are investigated. It was found that the AD scattering limited electron mobility in N-polar heterostructures is on the order of 103-104 cm2/Vs, which is comparable to the optical phonon scattering at room-temperature. In comparison, the AD scattering in Ga-polar samples is much less important. Moreover, the electron mobility decreases with the 2DEG density in the Ga-polar device but shows a reverse trend in the N-polar counterpart. This is found to be caused by the rather different electric field distributions in Ga- and N-polar AlGaN/GaN heterostructures. In addition, we find that an AlN interlayer can effectively reduce the alloy scattering, mainly due to the large band offset between AlN and GaN. The calculated mobilities have been compared with the experiment results and good agreements are found. We believe that our results are important for the design of AlGaN/GaN heterostructure-based devices, especially the N-polar ones.

Stability and superconducting properties of GaH5 at high pressure

NASA Astrophysics Data System (ADS)

Ning, Yan-Li; Yang, Wen-Hua; Zang, Qing-Jun; Lu, Wen-Cai

2017-11-01

Using genetic algorithm (GA) method combined with first-principles calculations, the structures, dynamical and thermodynamic stabilities of GaH5 were studied. The calculated results suggested that at the pressure range 150-400 GPa, the P21/m phase of GaH5 is the most favorable phase and dynamically stable, but thermodynamically it is unstable and can decompose into GaH3 and H2. The superconducting property of GaH5 was further calculated, and the predicted superconducting transformation temperature Tc of GaH5 P21/m phase is about 35.63 K at 250 GPa. Besides, we compared the GaH5 and GaH3 superconducting properties, and found that GaH3-Pm-3n structure has a larger DOS near Fermi level than GaH5-P21/m structure, which may be the main reason causing higher Tc of GaH3 than GaH5.

Algorithm-Based Fault Tolerance Integrated with Replication

NASA Technical Reports Server (NTRS)

Some, Raphael; Rennels, David

2008-01-01

In a proposed approach to programming and utilization of commercial off-the-shelf computing equipment, a combination of algorithm-based fault tolerance (ABFT) and replication would be utilized to obtain high degrees of fault tolerance without incurring excessive costs. The basic idea of the proposed approach is to integrate ABFT with replication such that the algorithmic portions of computations would be protected by ABFT, and the logical portions by replication. ABFT is an extremely efficient, inexpensive, high-coverage technique for detecting and mitigating faults in computer systems used for algorithmic computations, but does not protect against errors in logical operations surrounding algorithms.

A genetic-algorithm-based remnant grey prediction model for energy demand forecasting.

PubMed

Hu, Yi-Chung

2017-01-01

Energy demand is an important economic index, and demand forecasting has played a significant role in drawing up energy development plans for cities or countries. As the use of large datasets and statistical assumptions is often impractical to forecast energy demand, the GM(1,1) model is commonly used because of its simplicity and ability to characterize an unknown system by using a limited number of data points to construct a time series model. This paper proposes a genetic-algorithm-based remnant GM(1,1) (GARGM(1,1)) with sign estimation to further improve the forecasting accuracy of the original GM(1,1) model. The distinctive feature of GARGM(1,1) is that it simultaneously optimizes the parameter specifications of the original and its residual models by using the GA. The results of experiments pertaining to a real case of energy demand in China showed that the proposed GARGM(1,1) outperforms other remnant GM(1,1) variants.

A genetic-algorithm-based remnant grey prediction model for energy demand forecasting

PubMed Central

2017-01-01

Energy demand is an important economic index, and demand forecasting has played a significant role in drawing up energy development plans for cities or countries. As the use of large datasets and statistical assumptions is often impractical to forecast energy demand, the GM(1,1) model is commonly used because of its simplicity and ability to characterize an unknown system by using a limited number of data points to construct a time series model. This paper proposes a genetic-algorithm-based remnant GM(1,1) (GARGM(1,1)) with sign estimation to further improve the forecasting accuracy of the original GM(1,1) model. The distinctive feature of GARGM(1,1) is that it simultaneously optimizes the parameter specifications of the original and its residual models by using the GA. The results of experiments pertaining to a real case of energy demand in China showed that the proposed GARGM(1,1) outperforms other remnant GM(1,1) variants. PMID:28981548

List-Based Simulated Annealing Algorithm for Traveling Salesman Problem

PubMed Central

Zhan, Shi-hua; Lin, Juan; Zhang, Ze-jun

2016-01-01

Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedious work. To simplify parameters setting, we present a list-based simulated annealing (LBSA) algorithm to solve traveling salesman problem (TSP). LBSA algorithm uses a novel list-based cooling schedule to control the decrease of temperature. Specifically, a list of temperatures is created first, and then the maximum temperature in list is used by Metropolis acceptance criterion to decide whether to accept a candidate solution. The temperature list is adapted iteratively according to the topology of the solution space of the problem. The effectiveness and the parameter sensitivity of the list-based cooling schedule are illustrated through benchmark TSP problems. The LBSA algorithm, whose performance is robust on a wide range of parameter values, shows competitive performance compared with some other state-of-the-art algorithms. PMID:27034650

List-Based Simulated Annealing Algorithm for Traveling Salesman Problem.

PubMed

Zhan, Shi-hua; Lin, Juan; Zhang, Ze-jun; Zhong, Yi-wen

2016-01-01

Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedious work. To simplify parameters setting, we present a list-based simulated annealing (LBSA) algorithm to solve traveling salesman problem (TSP). LBSA algorithm uses a novel list-based cooling schedule to control the decrease of temperature. Specifically, a list of temperatures is created first, and then the maximum temperature in list is used by Metropolis acceptance criterion to decide whether to accept a candidate solution. The temperature list is adapted iteratively according to the topology of the solution space of the problem. The effectiveness and the parameter sensitivity of the list-based cooling schedule are illustrated through benchmark TSP problems. The LBSA algorithm, whose performance is robust on a wide range of parameter values, shows competitive performance compared with some other state-of-the-art algorithms.

Research on personalized recommendation algorithm based on spark

NASA Astrophysics Data System (ADS)

Li, Zeng; Liu, Yu

2018-04-01

With the increasing amount of data in the past years, the traditional recommendation algorithm has been unable to meet people's needs. Therefore, how to better recommend their products to users of interest, become the opportunities and challenges of the era of big data development. At present, each platform enterprise has its own recommendation algorithm, but how to make efficient and accurate push information is still an urgent problem for personalized recommendation system. In this paper, a hybrid algorithm based on user collaborative filtering and content-based recommendation algorithm is proposed on Spark to improve the efficiency and accuracy of recommendation by weighted processing. The experiment shows that the recommendation under this scheme is more efficient and accurate.

Evaporation-based Ge/.sup.68 Ga Separation

DOEpatents

Mirzadeh, Saed; Whipple, Richard E.; Grant, Patrick M.; O'Brien, Jr., Harold A.

1981-01-01

Micro concentrations of .sup.68 Ga in secular equilibrium with .sup.68 Ge in strong aqueous HCl solution may readily be separated in ionic form from the .sup.68 Ge for biomedical use by evaporating the solution to dryness and then leaching the .sup.68 Ga from the container walls with dilute aqueous solutions of HCl or NaCl. The chloro-germanide produced during the evaporation may be quantitatively recovered to be used again as a source of .sup.68 Ga. If the solution is distilled to remove any oxidizing agents which may be present as impurities, the separation factor may easily exceed 10.sup.5. The separation is easily completed and the .sup.68 Ga made available in ionic form in 30 minutes or less.

Fast image matching algorithm based on projection characteristics

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun

2011-06-01

Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.

Indoor high precision three-dimensional positioning system based on visible light communication using modified genetic algorithm

NASA Astrophysics Data System (ADS)

Chen, Hao; Guan, Weipeng; Li, Simin; Wu, Yuxiang

2018-04-01

To improve the precision of indoor positioning and actualize three-dimensional positioning, a reversed indoor positioning system based on visible light communication (VLC) using genetic algorithm (GA) is proposed. In order to solve the problem of interference between signal sources, CDMA modulation is used. Each light-emitting diode (LED) in the system broadcasts a unique identity (ID) code using CDMA modulation. Receiver receives mixed signal from every LED reference point, by the orthogonality of spreading code in CDMA modulation, ID information and intensity attenuation information from every LED can be obtained. According to positioning principle of received signal strength (RSS), the coordinate of the receiver can be determined. Due to system noise and imperfection of device utilized in the system, distance between receiver and transmitters will deviate from the real value resulting in positioning error. By introducing error correction factors to global parallel search of genetic algorithm, coordinates of the receiver in three-dimensional space can be determined precisely. Both simulation results and experimental results show that in practical application scenarios, the proposed positioning system can realize high precision positioning service.

GPU-based parallel algorithm for blind image restoration using midfrequency-based methods

NASA Astrophysics Data System (ADS)

Xie, Lang; Luo, Yi-han; Bao, Qi-liang

2013-08-01

GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images.

A combined ANN-GA and experimental based technique for the estimation of the unknown heat flux for a conjugate heat transfer problem

NASA Astrophysics Data System (ADS)

M K, Harsha Kumar; P S, Vishweshwara; N, Gnanasekaran; C, Balaji

2018-05-01

The major objectives in the design of thermal systems are obtaining the information about thermophysical, transport and boundary properties. The main purpose of this paper is to estimate the unknown heat flux at the surface of a solid body. A constant area mild steel fin is considered and the base is subjected to constant heat flux. During heating, natural convection heat transfer occurs from the fin to ambient. The direct solution, which is the forward problem, is developed as a conjugate heat transfer problem from the fin and the steady state temperature distribution is recorded for any assumed heat flux. In order to model the natural convection heat transfer from the fin, an extended domain is created near the fin geometry and air is specified as a fluid medium and Navier Stokes equation is solved by incorporating the Boussinesq approximation. The computational time involved in executing the forward model is then reduced by developing a neural network (NN) between heat flux values and temperatures based on back propagation algorithm. The conjugate heat transfer NN model is now coupled with Genetic algorithm (GA) for the solution of the inverse problem. Initially, GA is applied to the pure surrogate data, the results are then used as input to the Levenberg- Marquardt method and such hybridization is proven to result in accurate estimation of the unknown heat flux. The hybrid method is then applied for the experimental temperature to estimate the unknown heat flux. A satisfactory agreement between the estimated and actual heat flux is achieved by incorporating the hybrid method.

Optimization of Straight Cylindrical Turning Using Artificial Bee Colony (ABC) Algorithm

NASA Astrophysics Data System (ADS)

Prasanth, Rajanampalli Seshasai Srinivasa; Hans Raj, Kandikonda

2017-04-01

Artificial bee colony (ABC) algorithm, that mimics the intelligent foraging behavior of honey bees, is increasingly gaining acceptance in the field of process optimization, as it is capable of handling nonlinearity, complexity and uncertainty. Straight cylindrical turning is a complex and nonlinear machining process which involves the selection of appropriate cutting parameters that affect the quality of the workpiece. This paper presents the estimation of optimal cutting parameters of the straight cylindrical turning process using the ABC algorithm. The ABC algorithm is first tested on four benchmark problems of numerical optimization and its performance is compared with genetic algorithm (GA) and ant colony optimization (ACO) algorithm. Results indicate that, the rate of convergence of ABC algorithm is better than GA and ACO. Then, the ABC algorithm is used to predict optimal cutting parameters such as cutting speed, feed rate, depth of cut and tool nose radius to achieve good surface finish. Results indicate that, the ABC algorithm estimated a comparable surface finish when compared with real coded genetic algorithm and differential evolution algorithm.

An introduction to kernel-based learning algorithms.

PubMed

Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

2001-01-01

This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

Polarization-enhanced InGaN/GaN-based hybrid tunnel junction contacts to GaN p-n diodes and InGaN LEDs

NASA Astrophysics Data System (ADS)

Mughal, Asad J.; Young, Erin C.; Alhassan, Abdullah I.; Back, Joonho; Nakamura, Shuji; Speck, James S.; DenBaars, Steven P.

2017-12-01

Improved turn-on voltages and reduced series resistances were realized by depositing highly Si-doped n-type GaN using molecular beam epitaxy on polarization-enhanced p-type InGaN contact layers grown using metal-organic chemical vapor deposition. We compared the effects of different Si doping concentrations and the addition of p-type InGaN on the forward voltages of p-n diodes and light-emitting diodes, and found that increasing the Si concentrations from 1.9 × 1020 to 4.6 × 1020 cm-3 and including a highly doped p-type InGaN at the junction both contributed to reductions in the depletion width, the series resistance of 4.2 × 10-3-3.4 × 10-3 Ω·cm2, and the turn-on voltages of the diodes.

TOPICAL REVIEW: GaN-based diodes and transistors for chemical, gas, biological and pressure sensing

NASA Astrophysics Data System (ADS)

Pearton, S. J.; Kang, B. S.; Kim, Suku; Ren, F.; Gila, B. P.; Abernathy, C. R.; Lin, Jenshan; Chu, S. N. G.

2004-07-01

There is renewed emphasis on development of robust solid-state sensors capable of uncooled operation in harsh environments. The sensors should be capable of detecting chemical, gas, biological or radiation releases as well as sending signals to central monitoring locations. We discuss the advances in use of GaN-based solid-state sensors for these applications. AlGaN/GaN high electron mobility transistors (HEMTs) show a strong dependence of source/drain current on the piezoelectric polarization-induced two-dimensional electron gas (2DEG). Furthermore, spontaneous and piezoelectric polarization-induced surface and interface charges can be used to develop very sensitive but robust sensors to detect gases, polar liquids and mechanical pressure. AlGaN/GaN HEMT structures have been demonstrated to exhibit large changes in source-drain current upon exposing the gate region to various block co-polymer solutions. Pt-gated GaN Schottky diodes and Sc2O3/AlGaN/GaN metal-oxide semiconductor diodes also show large change in forward currents upon exposure to H2. Of particular interest is detection of ethylene (C2H4), which has strong double bonds and hence is difficult to dissociate at modest temperatures. Apart from combustion gas sensing, the AlGaN/GaN heterostructure devices can be used as sensitive detectors of pressure changes. In addition, large changes in source-drain current of the AlGaN/GaN HEMT sensors can be detected upon adsorption of biological species on the semiconductor surface. Finally, the nitrides provide an ideal platform for fabrication of surface acoustic wave (SAW) devices. The GaN-based devices thus appear promising for a wide range of chemical, biological, combustion gas, polar liquid, strain and high temperature pressure-sensing applications. In addition, the sensors are compatible with high bit-rate wireless communication systems that facilitate their use in remote arrays.

Laser diode arrays based on AlGaAs/GaAs quantum-well heterostructures with an efficiency up to 62%

NASA Astrophysics Data System (ADS)

Ladugin, M. A.; Marmalyuk, A. A.; Padalitsa, A. A.; Telegin, K. Yu; Lobintsov, A. V.; Sapozhnikov, S. M.; Danilov, A. I.; Podkopaev, A. V.; Simakov, V. A.

2017-08-01

The results of development of quasi-cw laser diode arrays operating at a wavelength of 808 nm with a high efficiency are demonstrated. The laser diodes are based on semiconductor AlGaAs/GaAs quantum-well heterostructures grown by MOCVD. The measured spectral, spatial, electric and power characteristics are presented. The output optical power of the array with an emitting area of 5 × 10 mm is 2.7 kW at a pump current of 100 A, and the maximum efficiency reaches 62%.

High-Efficiency InGaN/GaN Quantum Well-Based Vertical Light-Emitting Diodes Fabricated on β-Ga2O3 Substrate.

PubMed

Muhammed, Mufasila M; Alwadai, Norah; Lopatin, Sergei; Kuramata, Akito; Roqan, Iman S

2017-10-04

We demonstrate a state-of-the-art high-efficiency GaN-based vertical light-emitting diode (VLED) grown on a transparent and conductive (-201)-oriented (β-Ga 2 O 3 ) substrate, obtained using a straightforward growth process that does not require a high-cost lift-off technique or complex fabrication process. The high-resolution scanning transmission electron microscopy (STEM) images confirm that we produced high quality upper layers, including a multiquantum well (MQW) grown on the masked β-Ga 2 O 3 substrate. STEM imaging also shows a well-defined MQW without InN diffusion into the barrier. Electroluminescence (EL) measurements at room temperature indicate that we achieved a very high internal quantum efficiency (IQE) of 78%; at lower temperatures, IQE reaches ∼86%. The photoluminescence (PL) and time-resolved PL analysis indicate that, at a high carrier injection density, the emission is dominated by radiative recombination with a negligible Auger effect; no quantum-confined Stark effect is observed. At low temperatures, no efficiency droop is observed at a high carrier injection density, indicating the superior VLED structure obtained without lift-off processing, which is cost-effective for large-scale devices.

Rapid thermal anneal in InP, GaAs and GaAs/GaAlAs

NASA Astrophysics Data System (ADS)

Descouts, B.; Duhamel, N.; Godefroy, S.; Krauz, P.

Ion implantation in semiconductors provides a doping technique with several advantages over more conventional doping methods and is now extensively used for device applications, e.g. field effect transistors (MESFET GaAs, MIS (InP), GaAs/GaAlAs heterojunction bipolar transistors (HBT). Because of the lattice disorder produced by the implantation, the dopant must be made electrically active by a postimplant anneal. As the device performances are very dependent on its electrical characteristics, the anneal is a very important stage of the process. Rapid anneal is known to provide less exodiffusion and less induffusion of impurities compared to conventional furnace anneal, so this technique has been used in this work to activate an n-type dopant (Si) in InP and a p-type dopant (Mg) in GaAs and GaAs/GaAIAs. These two ions have been chosen to realize implanted MIS InP and the base contacts for GaAs/GaAlAs HBTs. The experimental conditions to obtain the maximum electrical activity in these two cases will be detailed. For example, although we have not been able to obtain a flat profile in Mg + implanted GaAs/GaAlAs heterostructure by conventional thermal anneal, rapid thermal anneal gives a flat hole profile over a depth of 0.5 μm with a concentration of 1 x 10 19 cm -3.

Modeling and Simulation of Capacitance-Voltage Characteristics of a Nitride GaAs Schottky Diode

NASA Astrophysics Data System (ADS)

Ziane, Abderrezzaq; Amrani, Mohammed; Benamara, Zineb; Rabehi, Abdelaziz

2018-06-01

A nitride GaAs Schottky diode has been fabricated by the nitridation of GaAs substrates using a radio frequency discharge nitrogen plasma source with a layer thickness of approximately 0.7 nm of GaN. The capacitance-voltage (C-V) characteristics of the Au/GaN/GaAs structure were investigated at room temperature for different frequencies, ranging from 1 kHz to 1 MHz. The C-V measurements for the Au/GaN/GaAs Schottky diode were found to be strongly dependent on the bias voltage and the frequency. The capacitance curves depict an anomalous peak and a negative capacitance phenomenon, indicating the presence of continuous interface state density behavior. A numerical drift-diffusion model based on the Scharfetter-Gummel algorithm was elaborated to solve a system composed of the Poisson and continuities equations. In this model, we take into account the continuous interface state density, and we have considered exponential and Gaussian distributions of trap states in the band gap. The effects of the GaAs doping concentration and the trap state density are discussed. We deduce the shape and values of the trap states, then we validate the developed model by fitting the computed C-V curves with experimental measurements at low frequency.

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

Simplified NaCl based (68)Ga concentration and labeling procedure for rapid synthesis of (68)Ga radiopharmaceuticals in high radiochemical purity.

PubMed

Mueller, Dirk; Klette, Ingo; Baum, Richard P; Gottschaldt, M; Schultz, Michael K; Breeman, Wouter A P

2012-08-15

A simple sodium chloride (NaCl) based (68)Ga eluate concentration and labeling method that enables rapid, high-efficiency labeling of DOTA conjugated peptides in high radiochemical purity is described. The method utilizes relatively few reagents and comprises minimal procedural steps. It is particularly well-suited for routine automated synthesis of clinical radiopharmaceuticals. For the (68)Ga generator eluate concentration step, commercially available cation-exchange cartridges and (68)Ga generators were used. The (68)Ga generator eluate was collected by use of a strong cation exchange cartridge. 98% of the total activity of (68)Ga was then eluted from the cation exchange cartridge with 0.5 mL of 5 M NaCl solution containing a small amount of 5.5 M HCl. After buffering with ammonium acetate, the eluate was used directly for radiolabeling of DOTATOC and DOTATATE. The (68)Ga-labeled peptides were obtained in higher radiochemical purity compared to other commonly used procedures, with radiochemical yields greater than 80%. The presence of (68)Ge could not be detected in the final product. The new method obviates the need for organic solvents, which eliminates the required quality control of the final product by gas chromatography, thereby reducing postsynthesis analytical effort significantly. The (68)Ga-labeled products were used directly, with no subsequent purification steps, such as solid-phase extraction. The NaCl method was further evaluated using an automated fluid handling system and it routinely facilitates radiochemical yields in excess of 65% in less than 15 min, with radiochemical purity consistently greater than 99% for the preparation of (68)Ga-DOTATOC.

Q-Learning-Based Adjustable Fixed-Phase Quantum Grover Search Algorithm

NASA Astrophysics Data System (ADS)

Guo, Ying; Shi, Wensha; Wang, Yijun; Hu, Jiankun

2017-02-01

We demonstrate that the rotation phase can be suitably chosen to increase the efficiency of the phase-based quantum search algorithm, leading to a dynamic balance between iterations and success probabilities of the fixed-phase quantum Grover search algorithm with Q-learning for a given number of solutions. In this search algorithm, the proposed Q-learning algorithm, which is a model-free reinforcement learning strategy in essence, is used for performing a matching algorithm based on the fraction of marked items λ and the rotation phase α. After establishing the policy function α = π(λ), we complete the fixed-phase Grover algorithm, where the phase parameter is selected via the learned policy. Simulation results show that the Q-learning-based Grover search algorithm (QLGA) enables fewer iterations and gives birth to higher success probabilities. Compared with the conventional Grover algorithms, it avoids the optimal local situations, thereby enabling success probabilities to approach one.

Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

PubMed

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

Hierarchical trie packet classification algorithm based on expectation-maximization clustering

PubMed Central

Bi, Xia-an; Zhao, Junxia

2017-01-01

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm. PMID:28704476

Hierarchical trie packet classification algorithm based on expectation-maximization clustering.

PubMed

Bi, Xia-An; Zhao, Junxia

2017-01-01

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm.

Laser diode bars based on AlGaAs/GaAs quantum-well heterostructures with an efficiency up to 70%

NASA Astrophysics Data System (ADS)

Ladugin, M. A.; Marmalyuk, A. A.; Padalitsa, A. A.; Bagaev, T. A.; Andreev, A. Yu.; Telegin, K. Yu.; Lobintsov, A. V.; Davydova, E. I.; Sapozhnikov, S. M.; Danilov, A. I.; Podkopaev, A. V.; Ivanova, E. B.; Simakov, V. A.

2017-05-01

The results of the development and fabrication of laser diode bars (λ = 800 - 810 nm) based on AlGaAs/GaAs quantum-well heterostructures with a high efficiency are presented. An increase in the internal quantum and external differential efficiencies together with a decrease in the working voltage and the series resistance allowed us to improve the output parameters of the semiconductor laser under quasi-cw pumping. The output power of the laser diode bars with a 5-mm transverse length reached 210 W, and the efficiency was ~70%.

Modeling Self-Healing of Concrete Using Hybrid Genetic Algorithm-Artificial Neural Network.

PubMed

Ramadan Suleiman, Ahmed; Nehdi, Moncef L

2017-02-07

This paper presents an approach to predicting the intrinsic self-healing in concrete using a hybrid genetic algorithm-artificial neural network (GA-ANN). A genetic algorithm was implemented in the network as a stochastic optimizing tool for the initial optimal weights and biases. This approach can assist the network in achieving a global optimum and avoid the possibility of the network getting trapped at local optima. The proposed model was trained and validated using an especially built database using various experimental studies retrieved from the open literature. The model inputs include the cement content, water-to-cement ratio (w/c), type and dosage of supplementary cementitious materials, bio-healing materials, and both expansive and crystalline additives. Self-healing indicated by means of crack width is the model output. The results showed that the proposed GA-ANN model is capable of capturing the complex effects of various self-healing agents (e.g., biochemical material, silica-based additive, expansive and crystalline components) on the self-healing performance in cement-based materials.

Nuclear fuel management optimization using genetic algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeChaine, M.D.; Feltus, M.A.

1995-07-01

The code independent genetic algorithm reactor optimization (CIGARO) system has been developed to optimize nuclear reactor loading patterns. It uses genetic algorithms (GAs) and a code-independent interface, so any reactor physics code (e.g., CASMO-3/SIMULATE-3) can be used to evaluate the loading patterns. The system is compared to other GA-based loading pattern optimizers. Tests were carried out to maximize the beginning of cycle k{sub eff} for a pressurized water reactor core loading with a penalty function to limit power peaking. The CIGARO system performed well, increasing the k{sub eff} after lowering the peak power. Tests of a prototype parallel evaluation methodmore » showed the potential for a significant speedup.« less

Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm

NASA Technical Reports Server (NTRS)

2005-01-01

This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.

Normally-off AlGaN/GaN-based MOS-HEMT with self-terminating TMAH wet recess etching

NASA Astrophysics Data System (ADS)

Son, Dong-Hyeok; Jo, Young-Woo; Won, Chul-Ho; Lee, Jun-Hyeok; Seo, Jae Hwa; Lee, Sang-Heung; Lim, Jong-Won; Kim, Ji Heon; Kang, In Man; Cristoloveanu, Sorin; Lee, Jung-Hee

2018-03-01

Normally-off AlGaN/GaN-based MOS-HEMT has been fabricated by utilizing damage-free self-terminating tetramethyl ammonium hydroxide (TMAH) recess etching. The device exhibited a threshold voltage of +2.0 V with good uniformity, extremely small hysteresis of ∼20 mV, and maximum drain current of 210 mA/mm. The device also exhibited excellent off-state performances, such as breakdown voltage of ∼800 V with off-state leakage current as low as ∼10-12 A and high on/off current ratio (Ion/Ioff) of 1010. These excellent device performances are believed to be due to the high quality recessed surface, provided by the simple self-terminating TMAH etching.

Low operation voltage of GaN-based LEDs with Al-doped ZnO upper contact directly on p-type GaN without insert layer

NASA Astrophysics Data System (ADS)

Chen, P. H.; Chen, Yu An; Chang, L. C.; Lai, W. C.; Kuo, Cheng Huang

2015-07-01

Al-doped ZnO (AZO) film was evaporated on double-side polished sapphire, p-GaN layers, n+-InGaN-GaN short-period superlattice (SPS) structures, and GaN-based light-emitting diodes (LEDs) by e-beam. The AZO film on the p-GaN layer after thermal annealing exhibited an extremely high transparency (98% at 450 nm) and a small specific contact resistance of 2.19 × 10-2 Ω cm2, which was almost the same as that of as-deposited AZO on n+-SPS structure. With 20 mA injection current, the forward voltages were 3.30 and 3.27 V, whereas the output powers were 4.32 and 4.07 mW for the LED with AZO on insert n+-SPS upper contact and the LED with AZO on p-GaN upper contact (without insert layer), respectively. The small specific contact resistance and low operation voltage of LED with AZO on p-GaN upper contact was achieved by rapid thermal annealing (RTA) process.

GaAs-based resonant tunneling diode (RTD) epitaxy on Si for highly sensitive strain gauge applications.

PubMed

Li, Jie; Guo, Hao; Liu, Jun; Tang, Jun; Ni, Haiqiao; Shi, Yunbo; Xue, Chenyang; Niu, Zhichuan; Zhang, Wendong; Li, Mifeng; Yu, Ying

2013-05-08

As a highly sensitive strain gauge element, GaAs-based resonant tunneling diode (RTD) has already been applied in microelectromechanical system (MEMS) sensors. Due to poor mechanical properties and high cost, GaAs-based material has been limited in applications as the substrate for MEMS. In this work, we present a method to fabricate the GaAs-based RTD on Si substrate. From the experimental results, it can be concluded that the piezoresistive coefficient achieved with this method reached 3.42 × 10-9 m2/N, which is about an order of magnitude higher than the Si-based semiconductor piezoresistors.

The Secondary Development of ABAQUS by using Python and the Application of the Advanced GA

NASA Astrophysics Data System (ADS)

Luo, Lilong; Zhao, Meiying

Realizing the secondary development of the ABAQUS based on the manual of ABAQUS. In order to overcome the prematurity and the worse convergence of the Simple Genetic Algorithm (SGA), a new strategy how to improve the efficiency of the SGA has been put forward. In the new GA, the selection probability and the mutation probability are self-adaptive. Taking the stability of the composite laminates as the target, the optimized laminates sequences and radius of the hatch are analyzed with the help of ABAQUS. Compared with the SGA, the new GA method shows a good consistency, fast convergence and practical feasibility.

Effect of growth temperature on closely lattice-matched GaAsSbN intrinsic layer for GaAs-based 1.3 {mu}m p-i-n photodetector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wicaksono, S.; Yoon, S.F.; Loke, W.K.

2006-05-15

GaAsSbN layers closely lattice-matched to GaAs were studied for application as the intrinsic layer in GaAs-based 1.3 {mu}m p-i-n photodetector. The GaAsSbN was grown as the intrinsic layer for the GaAs/GaAsSbN/GaAs photodetector structure using solid-source molecular beam epitaxy in conjunction with a radio frequency plasma-assisted nitrogen source and valved antimony cracker source. The lattice mismatch of the GaAsSbN layer to GaAs was kept below 4000 ppm, which is sufficient to maintain coherent growth of {approx}0.45 {mu}m thick GaAsSbN on the GaAs substrate. The growth temperature of the GaAsSbN layer was varied from 420-480 deg. C. All samples exhibit room temperaturemore » photocurrent response in the 1.3 {mu}m wavelength region, with dark current density of {approx}0.3-0.5 mA/cm{sup 2} and responsivity of up to 33 mA/W at 2 V reverse bias. Reciprocal space maps reveal traces of point defects and segregation (clustering) of N and Sb, which may have a detrimental effect on the photocurrent responsivity.« less

Flexible ligand docking using a genetic algorithm

NASA Astrophysics Data System (ADS)

Oshiro, C. M.; Kuntz, I. D.; Dixon, J. Scott

1995-04-01

Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.

Study of a GaAs:Cr-based Timepix detector using synchrotron facility

NASA Astrophysics Data System (ADS)

Smolyanskiy, P.; Kozhevnikov, D.; Bakina, O.; Chelkov, G.; Dedovich, D.; Kuper, K.; Leyva Fabelo, A.; Zhemchugov, A.

2017-11-01

High resistivity gallium arsenide compensated by chromium fabricated by Tomsk State University has demonstrated a good suitability as a sensor material for hybrid pixel detectors used in X-ray imaging systems with photon energies up to 60 keV. The material is available with a thickness up to 1 mm and due to its Z number a high absorption efficiency in this energy region is provided. However, the performance of thick GaAs:Cr-based detectors in spectroscopic applications is limited by readout electronics with relatively small pixels due to the charge sharing effect. In this paper, we present the experimental investigation of the charge sharing effect contribution in the GaAs:Cr-based Timepix detector. By means of scanning the detector with a pencil photon beam generated by the synchrotron facility, the geometrical mapping of pixel sensitivity is obtained, as well as the energy resolution of a single pixel. The experimental results are supported by numerical simulations. The observed limitation of the GaAs:Cr-based Timepix detector for the high flux X-ray imaging is discussed.

Simulation and optimization performance of GaAs/GaAs0.5Sb0.5/GaSb mechanically stacked tandem solar cells

NASA Astrophysics Data System (ADS)

Tayubi, Y. R.; Suhandi, A.; Samsudin, A.; Arifin, P.; Supriyatman

2018-05-01

Different approaches have been made in order to reach higher solar cells efficiencies. Concepts for multilayer solar cells have been developed. This can be realised if multiple individual single junction solar cells with different suitably chosen band gaps are connected in series in multi-junction solar cells. In our work, we have simulated and optimized solar cells based on the system mechanically stacked using computer simulation and predict their maximum performance. The structures of solar cells are based on the single junction GaAs, GaAs0.5Sb0.5 and GaSb cells. We have simulated each cell individually and extracted their optimal parameters (layer thickness, carrier concentration, the recombination velocity, etc), also, we calculated the efficiency of each cells optimized by separation of the solar spectrum in bands where the cell is sensible for the absorption. The optimal values of conversion efficiency have obtained for the three individual solar cells and the GaAs/GaAs0.5Sb0.5/GaSb tandem solar cells, that are: η = 19,76% for GaAs solar cell, η = 8,42% for GaAs0,5Sb0,5 solar cell, η = 4, 84% for GaSb solar cell and η = 33,02% for GaAs/GaAs0.5Sb0.5/GaSb tandem solar cell.

New knowledge-based genetic algorithm for excavator boom structural optimization

NASA Astrophysics Data System (ADS)

Hua, Haiyan; Lin, Shuwen

2014-03-01

Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the configurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, are taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Structural and optical studies of nitrogen incorporation into GaSb-based GaInSb quantum wells

NASA Astrophysics Data System (ADS)

Nair, Hari P.; Crook, Adam M.; Yu, Kin M.; Bank, Seth R.

2012-01-01

We investigate the incorporation of nitrogen into (Ga,In)Sb grown on GaSb and report room temperature photoluminescence from GaInSb(N) quantum wells. X-ray diffraction and channeling nuclear reaction analysis, together with Rutherford backscattering, were employed to identify the optimal molecular beam epitaxial growth conditions that minimized the incorporation of non-substitutional nitrogen into GaNSb. Consistent with this hypothesis, GaInSb(N) quantum wells grown under the conditions that minimized non-substitutional nitrogen exhibited room temperature photoluminescence, indicative of significantly improved radiative efficiency. Further development of this material system could enable type-I laser diodes emitting throughout the (3-5 μm) wavelength range.

Deep Ultraviolet Light Emitters Based on (Al,Ga)N/GaN Semiconductor Heterostructures

NASA Astrophysics Data System (ADS)

Liang, Yu-Han

Deep ultraviolet (UV) light sources are useful in a number of applications that include sterilization, medical diagnostics, as well as chemical and biological identification. However, state-of-the-art deep UV light-emitting diodes and lasers made from semiconductors still suffer from low external quantum efficiency and low output powers. These limitations make them costly and ineffective in a wide range of applications. Deep UV sources such as lasers that currently exist are prohibitively bulky, complicated, and expensive. This is typically because they are constituted of an assemblage of two to three other lasers in tandem to facilitate sequential harmonic generation that ultimately results in the desired deep UV wavelength. For semiconductor-based deep UV sources, the most challenging difficulty has been finding ways to optimally dope the (Al,Ga)N/GaN heterostructures essential for UV-C light sources. It has proven to be very difficult to achieve high free carrier concentrations and low resistivities in high-aluminum-containing III-nitrides. As a result, p-type doped aluminum-free III-nitrides are employed as the p-type contact layers in UV light-emitting diode structures. However, because of impedance-mismatch issues, light extraction from the device and consequently the overall external quantum efficiency is drastically reduced. This problem is compounded with high losses and low gain when one tries to make UV nitride lasers. In this thesis, we provide a robust and reproducible approach to resolving most of these challenges. By using a liquid-metal-enabled growth mode in a plasma-assisted molecular beam epitaxy process, we show that highly-doped aluminum containing III-nitride films can be achieved. This growth mode is driven by kinetics. Using this approach, we have been able to achieve extremely high p-type and n-type doping in (Al,Ga)N films with high aluminum content. By incorporating a very high density of Mg atoms in (Al,Ga)N films, we have been able to

Schottky x-ray detectors based on a bulk β-Ga2O3 substrate

NASA Astrophysics Data System (ADS)

Lu, Xing; Zhou, Leidang; Chen, Liang; Ouyang, Xiaoping; Liu, Bo; Xu, Jun; Tang, Huili

2018-03-01

β-Ga2O3 Schottky barrier diodes (SBDs) have been fabricated on a bulk (100) β-Ga2O3 substrate and tested as X-ray detectors in this study. The devices exhibited good rectification properties, such as a high rectification ratio and a close-to-unity ideality factor. A high photo-to-dark current ratio exceeding 800 was achieved for X-ray detection, which was mainly attributed to the low reverse leakage current in the β-Ga2O3 SBDs. Furthermore, transient response of the β-Ga2O3 X-ray detectors was investigated, and two different detection mechanisms, photovoltaic and photoconductive, were identified. The results imply the great potential of β-Ga2O3 based devices for X-ray detection.

Effect of Dopant Activation on Device Characteristics of InGaN-based Light Emitting Diodes

NASA Astrophysics Data System (ADS)

Lacroce, Nicholas; Liu, Guangyu; Tan, Chee-Keong; Arif, Ronald A.; Lee, Soo Min; Tansu, Nelson

2015-03-01

Achieving high uniformity in growths and device characteristics of InGaN-based light-emitting diodes (LEDs) is important for large scale manufacturing. Dopant activation and maintaining control of variables affecting dopant activation are critical steps in the InGaN-based light emitting diodes (LEDs) fabrication process. In the epitaxy of large scale production LEDs, in-situ post-growth annealing is used for activating the Mg acceptor dopant in the p-AlGaN and p-GaN of the LEDs. However, the annealing temperature varies with respect to position in the reactor chamber, leading to severe uniform dopant activation issue across the devices. Thus, it is important to understand how the temperature gradient and the resulting variance in Mg acceptor activation will alter the device properties. In this work, we examine the effect of varying p-type doping levels in the p-GaN layers and AlGaN electron blocking layer of the GaN LEDs on the optoelectronic properties including the band profile, carrier concentration, current density, output power and quantum efficiency. By understanding the variations and its effect, the identification of the most critical p-type doping layer strategies to address this variation will be clarified.

Detection of nasopharyngeal cancer using confocal Raman spectroscopy and genetic algorithm technique

NASA Astrophysics Data System (ADS)

Li, Shao-Xin; Chen, Qiu-Yan; Zhang, Yan-Jiao; Liu, Zhi-Ming; Xiong, Hong-Lian; Guo, Zhou-Yi; Mai, Hai-Qiang; Liu, Song-Hao

2012-12-01

Raman spectroscopy (RS) and a genetic algorithm (GA) were applied to distinguish nasopharyngeal cancer (NPC) from normal nasopharyngeal tissue. A total of 225 Raman spectra are acquired from 120 tissue sites of 63 nasopharyngeal patients, 56 Raman spectra from normal tissue and 169 Raman spectra from NPC tissue. The GA integrated with linear discriminant analysis (LDA) is developed to differentiate NPC and normal tissue according to spectral variables in the selected regions of 792-805, 867-880, 996-1009, 1086-1099, 1288-1304, 1663-1670, and 1742-1752 cm-1 related to proteins, nucleic acids and lipids of tissue. The GA-LDA algorithms with the leave-one-out cross-validation method provide a sensitivity of 69.2% and specificity of 100%. The results are better than that of principal component analysis which is applied to the same Raman dataset of nasopharyngeal tissue with a sensitivity of 63.3% and specificity of 94.6%. This demonstrates that Raman spectroscopy associated with GA-LDA diagnostic algorithm has enormous potential to detect and diagnose nasopharyngeal cancer.

Improved modeling of GaN HEMTs for predicting thermal and trapping-induced-kink effects

NASA Astrophysics Data System (ADS)

Jarndal, Anwar; Ghannouchi, Fadhel M.

2016-09-01

In this paper, an improved modeling approach has been developed and validated for GaN high electron mobility transistors (HEMTs). The proposed analytical model accurately simulates the drain current and its inherent trapping and thermal effects. Genetic-algorithm-based procedure is developed to automatically find the fitting parameters of the model. The developed modeling technique is implemented on a packaged GaN-on-Si HEMT and validated by DC and small-/large-signal RF measurements. The model is also employed for designing and realizing a switch-mode inverse class-F power amplifier. The amplifier simulations showed a very good agreement with RF large-signal measurements.

Advantages of an InGaN-based light emitting diode with a p-InGaN/p-GaN superlattice hole accumulation layer

NASA Astrophysics Data System (ADS)

Liu, Chao; Ren, Zhi-Wei; Chen, Xin; Zhao, Bi-Jun; Wang, Xing-Fu; Yin, Yi-An; Li, Shu-Ti

2013-05-01

P-InGaN/p-GaN superlattices (SLs) are developed for a hole accumulation layer (HAL) of a blue light emitting diode (LED). Free hole concentration as high as 2.6 × 1018 cm-3 is achieved by adjusting the Cp2Mg flow rate during the growth of p-InGaN/p-GaN SLs. The p-InGaN/p-GaN SLs with appropriate Cp2Mg flow rates are then incorporated between the multi-quantum well and AlGaN electron blocking layer as an HAL, which leads to the enhancement of light output power by 29% at 200 mA, compared with the traditional LED without such SL HAL. Meanwhile, the efficiency droop is also effectively alleviated in the LED with the SL HAL. The improved performance is attributed to the increased hole injection efficiency, and the reduced electron leakage by inserting the p-type SL HAL.

GaSb thermophotovoltaic cells grown on GaAs by molecular beam epitaxy using interfacial misfit arrays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Juang, Bor-Chau, E-mail: bcjuang@ucla.edu; Laghumavarapu, Ramesh B.; Foggo, Brandon J.

There exists a long-term need for foreign substrates on which to grow GaSb-based optoelectronic devices. We address this need by using interfacial misfit arrays to grow GaSb-based thermophotovoltaic cells directly on GaAs (001) substrates and demonstrate promising performance. We compare these cells to control devices grown on GaSb substrates to assess device properties and material quality. The room temperature dark current densities show similar characteristics for both cells on GaAs and on GaSb. Under solar simulation the cells on GaAs exhibit an open-circuit voltage of 0.121 V and a short-circuit current density of 15.5 mA/cm{sup 2}. In addition, the cells on GaAsmore » substrates maintain 10% difference in spectral response to those of the control cells over a large range of wavelengths. While the cells on GaSb substrates in general offer better performance than the cells on GaAs substrates, the cost-savings and scalability offered by GaAs substrates could potentially outweigh the reduction in performance. By further optimizing GaSb buffer growth on GaAs substrates, Sb-based compound semiconductors grown on GaAs substrates with similar performance to devices grown directly on GaSb substrates could be realized.« less

GDPC: Gravitation-based Density Peaks Clustering algorithm

NASA Astrophysics Data System (ADS)

Jiang, Jianhua; Hao, Dehao; Chen, Yujun; Parmar, Milan; Li, Keqin

2018-07-01

The Density Peaks Clustering algorithm, which we refer to as DPC, is a novel and efficient density-based clustering approach, and it is published in Science in 2014. The DPC has advantages of discovering clusters with varying sizes and varying densities, but has some limitations of detecting the number of clusters and identifying anomalies. We develop an enhanced algorithm with an alternative decision graph based on gravitation theory and nearby distance to identify centroids and anomalies accurately. We apply our method to some UCI and synthetic data sets. We report comparative clustering performances using F-Measure and 2-dimensional vision. We also compare our method to other clustering algorithms, such as K-Means, Affinity Propagation (AP) and DPC. We present F-Measure scores and clustering accuracies of our GDPC algorithm compared to K-Means, AP and DPC on different data sets. We show that the GDPC has the superior performance in its capability of: (1) detecting the number of clusters obviously; (2) aggregating clusters with varying sizes, varying densities efficiently; (3) identifying anomalies accurately.

Insertion of two-dimensional photonic crystal pattern on p-GaN layer of GaN-based light-emitting diodes using bi-layer nanoimprint lithography.

PubMed

Byeon, Kyeong-Jae; Hwang, Seon-Yong; Hong, Chang-Hee; Baek, Jong Hyeob; Lee, Heon

2008-10-01

Nanoimprint lithography (NIL) was adapted to fabricate two-dimensional (2-D) photonic crystal (PC) pattern on the p-GaN layer of InGaN/GaN multi quantum well light-emitting diodes (LEDs) structure to improve the light extraction efficiency. For the uniform transfer of the PC pattern, a bi-layer imprinting method with liquid phase resin was used. The p-GaN layer was patterned with a periodic array of holes by an inductively coupled plasma etching process, based on SiCl4/Ar plasmas. As a result, 2-D photonic crystal patterns with 144 nm, 200 nm and 347 nm diameter holes were uniformly formed on the p-GaN layer and the photoluminescence (PL) intensity of each patterned LED samples was increased by more than 2.6 times, as compared to that of the un-patterned LED sample.

GaN-based light-emitting diodes with graphene/indium tin oxide transparent layer.

PubMed

Lai, Wei-Chih; Lin, Chih-Nan; Lai, Yi-Chun; Yu, Peichen; Chi, Gou Chung; Chang, Shoou-Jinn

2014-03-10

We have demonstrated a gallium nitride (GaN)-based green light-emitting diode (LED) with graphene/indium tin oxide (ITO) transparent contact. The ohmic characteristic of the p-GaN and graphene/ITO contact could be preformed by annealing at 500 °C for 5 min. The specific contact resistance of p-GaN/graphene/ITO (3.72E-3 Ω·cm²) is one order less than that of p-GaN/ITO. In addition, the 20-mA forward voltage of LEDs with graphene/ITO transparent (3.05 V) is 0.09 V lower than that of ITO LEDs (3.14 V). Besides, We have got an output power enhancement of 11% on LEDs with graphene/ITO transparent contact.

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

PubMed

Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

2015-06-01

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

GaAs-based resonant tunneling diode (RTD) epitaxy on Si for highly sensitive strain gauge applications

PubMed Central

2013-01-01

As a highly sensitive strain gauge element, GaAs-based resonant tunneling diode (RTD) has already been applied in microelectromechanical system (MEMS) sensors. Due to poor mechanical properties and high cost, GaAs-based material has been limited in applications as the substrate for MEMS. In this work, we present a method to fabricate the GaAs-based RTD on Si substrate. From the experimental results, it can be concluded that the piezoresistive coefficient achieved with this method reached 3.42 × 10−9 m2/N, which is about an order of magnitude higher than the Si-based semiconductor piezoresistors. PMID:23651496

Self-consistent vertical transport calculations in AlxGa1-xN/GaN based resonant tunneling diode

NASA Astrophysics Data System (ADS)

Rached, A.; Bhouri, A.; Sakr, S.; Lazzari, J.-L.; Belmabrouk, H.

2016-03-01

The formation of two-dimensional electron gases (2DEGs) at AlxGa1-xN/GaN hexagonal double-barriers (DB) resonant tunneling diodes (RTD) is investigated by numerical self-consistent (SC) solutions of the coupled Schrödinger and Poisson equations. Spontaneous and piezoelectric effects across the material interfaces are rigorously taken into account. Conduction band profiles, band edges and corresponding envelope functions are calculated in the AlxGa1-xN/GaN structures and likened to those where no polarization effects are included. The combined effect of the polarization-induced bound charge and conduction band offsets between the hexagonal AlGaN and GaN results in the formation of 2DEGs on one side of the DB and a depletion region on the other side. Using the transfer matrix formalism, the vertical transport (J-V characteristics) in AlGaN/GaN RTDs is calculated with a fully SC calculation in the ballistic regime. Compared to standard calculations where the voltage drop along the structure is supposed to be linear, the SC method leads to strong quantitative changes in the J-V characteristics showing that the applied electric field varies significantly in the active region of the structure. The influences of the aluminum composition and the GaN(AlGaN) thickness layers on the evolution of the current characteristics are also self-consistently investigated and discussed. We show that the electrical characteristics are very sensitive to the potential barrier due to the interplay between the potential symmetry and the barrier height and width. More interestingly, we demonstrate that the figures of merit namely the peak-to-valley ratio (PVR) of GaN/AlGaN RTDs can be optimized by increasing the quantum well width.

NLSE: Parameter-Based Inversion Algorithm

NASA Astrophysics Data System (ADS)

Sabbagh, Harold A.; Murphy, R. Kim; Sabbagh, Elias H.; Aldrin, John C.; Knopp, Jeremy S.

Chapter 11 introduced us to the notion of an inverse problem and gave us some examples of the value of this idea to the solution of realistic industrial problems. The basic inversion algorithm described in Chap. 11 was based upon the Gauss-Newton theory of nonlinear least-squares estimation and is called NLSE in this book. In this chapter we will develop the mathematical background of this theory more fully, because this algorithm will be the foundation of inverse methods and their applications during the remainder of this book. We hope, thereby, to introduce the reader to the application of sophisticated mathematical concepts to engineering practice without introducing excessive mathematical sophistication.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

NASA Astrophysics Data System (ADS)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

Degradation mechanisms of Ti/Al/Ni/Au-based Ohmic contacts on AlGaN/GaN HEMTs

DOE PAGES

Hwang, Ya-Hsi; Ahn, Shihyun; Dong, Chen; ...

2015-04-27

We investigated the degradation mechanism of Ti/Al/Ni/Au-based Ohmic metallization on AlGaN/GaN high electron mobility transistors upon exposure to buffer oxide etchant (BOE). The major effect of BOE on the Ohmic metal was an increase of sheet resistance from 2.89 to 3.69 Ω/ₜafter 3 min BOE treatment. The alloyed Ohmic metallization consisted 3–5 μm Ni-Al alloy islands surrounded by Au-Al alloy-rings. The morphology of both the islands and ring areas became flatter after BOE etching. Lastly, we used energy dispersive x-ray analysis and Auger electron microscopy to analyze the compositions and metal distributions in the metal alloys prior to and aftermore » BOE exposure.« less

Dielectric function of InGaAs in the visible

NASA Technical Reports Server (NTRS)

Alterovitz, S. A.; Sieg, R. E.; Yao, H. D.; Snyder, P. G.; Woollam, J. A.; Pamulapati, J.; Bhattacharya, P. K.; Sekula-Moise, P. A.

1990-01-01

Measurements are reported of the dielectric function of thermodynamically stable In(x)Ga(1-x)As in the composition range 0.3 equal to or less than X = to or less than 0.7. The optically thick samples of InGaAs were made by molecular beam epitaxy (MBE) in the range 0.4 = to or less than X = to or less than 0.7 and by metal-organic chemical vapor deposition (MOCVD) for X = 0.3. The MBE made samples, usually 1 micron thick, were grown on semi-insulating InP and included a strain release structure. The MOCVD sample was grown on GaAs and was 2 microns thick. The dielectric functions were measured by variable angle spectroscopic ellipsometry in the range 1.55 to 4.4 eV. The data was analyzed assuming an optically thick InGaAs material with an oxide layer on top. The thickness of this layer was estimated by comparing the results for the InP lattice matched material, i.e., X = 0.53, with results published in the literature. The top oxide layer mathematically for X = 0.3 and X = 0.53 was removed to get the dielectric function of the bare InGaAs. In addition, the dielectric function of GaAs in vacuum, after a protective arsenic layer was removed. The dielectric functions for X = 0, 0.3, and 0.53 together with the X = 1 result from the literature to evaluate an algorithm for calculating the dielectric function of InGaAs for an arbitrary value of X(0 = to or less than X = to or less than 1) were used. Results of the dielectric function calculated using the algorithm were compared with experimental data.

Dielectric function of InGaAs in the visible

NASA Technical Reports Server (NTRS)

Alterovitz, S. A.; Yao, H. D.; Snyder, P. G.; Woolam, J. A.; Pamulapati, J.; Bhattacharya, P. K.; Sekula-Moise, P. A.; Sieg, R. E.

1990-01-01

Measurements are reported of the dielectric function of thermodynamically stable In(x)Ga(1-x)As in the composition range 0.3 equal to or less than X = to or less than 0.7. The optically thick samples of InGaAs were made by molecular beam epitaxy (MBE) in the range 0.4 = to or less than X = to or less than 0.7 and by metal-organic chemical vapor deposition (MOCVD) for X = 0.3. The MBE made samples, usually 1 micron thick, were grown on semi-insulating InP and included a strain release structure. The MOCVD sample was grown on GaAs and was 2 microns thick. The dielectric functions were measured by variable angle spectroscopic ellipsometry in the range 1.55 to 4.4 eV. The data was analyzed assuming an optically thick InGaAs material with an oxide layer on top. The thickness of this layer was estimated by comparing the results for the InP lattice matched material, i.e., X = 0.53, with results published in the literature. The top oxide layer mathematically for X = 0.3 and X = 0.53 was removed to get the dielectric function of the bare InGaAs. In addition, the dielectric function of GaAs in vacuum, after a protective arsenic layer was removed. The dielectric functions for X = 0, 0.3, and 0.53 together with the X = 1 result from the literature to evaluate an algorithm for calculating the dielectric function of InGaAs for an arbitrary value of X (0 = to or less than X = to or less than 1) were used. Results of the dielectric function calculated using the algorithm were compared with experimental data.

Research on compressive sensing reconstruction algorithm based on total variation model

NASA Astrophysics Data System (ADS)

Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

2017-12-01

Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

Coaxial metal-oxide-semiconductor (MOS) Au/Ga2O3/GaN nanowires.

PubMed

Hsieh, Chin-Hua; Chang, Mu-Tung; Chien, Yu-Jen; Chou, Li-Jen; Chen, Lih-Juann; Chen, Chii-Dong

2008-10-01

Coaxial metal-oxide-semiconductor (MOS) Au-Ga2O3-GaN heterostructure nanowires were successfully fabricated by an in situ two-step process. The Au-Ga2O3 core-shell nanowires were first synthesized by the reaction of Ga powder, a mediated Au thin layer, and a SiO2 substrate at 800 degrees C. Subsequently, these core-shell nanowires were nitridized in ambient ammonia to form a GaN coating layer at 600 degrees C. The GaN shell is a single crystal, an atomic flat interface between the oxide and semiconductor that ensures that the high quality of the MOS device is achieved. These novel 1D nitride-based MOS nanowires may have promise as building blocks to the future nitride-based vertical nanodevices.