Satellite mission scheduling algorithm based on GA
NASA Astrophysics Data System (ADS)
Sun, Baolin; Mao, Lifei; Wang, Wenxiang; Xie, Xing; Qin, Qianqing
2007-11-01
The Satellite Mission Scheduling problem (SMS) involves scheduling tasks to be performed by a satellite, where new task requests can arrive at any time, non-deterministically, and must be scheduled in real-time. This paper describes a new Satellite Mission Scheduling problem based on Genetic Algorithm (SMSGA). In this paper, it investigates algorithmic approaches for determining an optimal or near-optimal sequence of tasks, allocated to a satellite payload over time, with dynamic tasking considerations. The simulation results show that the proposed approach is effective and efficient in applications to the real problems.
A Test Scheduling Algorithm Based on Two-Stage GA
NASA Astrophysics Data System (ADS)
Yu, Y.; Peng, X. Y.; Peng, Y.
2006-10-01
In this paper, we present a new algorithm to co-optimize the core wrapper design and the SOC test scheduling. The SOC test scheduling problem is first formulated into a twodimension floorplan problem and a sequence pair architecture is used to represent it. Then we propose a two-stage GA (Genetic Algorithm) to solve the SOC test scheduling problem. Experiments on ITC'02 benchmark show that our algorithm can effectively reduce test time so as to decrease SOC test cost.
Genetic Algorithm (GA)-Based Inclinometer Layout Optimization.
Liang, Weijie; Zhang, Ping; Chen, Xianping; Cai, Miao; Yang, Daoguo
2015-01-01
This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors. PMID:25897500
Genetic Algorithm (GA)-Based Inclinometer Layout Optimization
Liang, Weijie; Zhang, Ping; Chen, Xianping; Cai, Miao; Yang, Daoguo
2015-01-01
This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors. PMID:25897500
Chen, Hong-Yan; Zhao, Geng-Xing; Li, Xi-Can; Wang, Xiang-Feng; Li, Yu-Ling
2013-11-01
Taking the Qihe County in Shandong Province of East China as the study area, soil samples were collected from the field, and based on the hyperspectral reflectance measurement of the soil samples and the transformation with the first deviation, the spectra were denoised and compressed by discrete wavelet transform (DWT), the variables for the soil alkali hydrolysable nitrogen quantitative estimation models were selected by genetic algorithms (GA), and the estimation models for the soil alkali hydrolysable nitrogen content were built by using partial least squares (PLS) regression. The discrete wavelet transform and genetic algorithm in combining with partial least squares (DWT-GA-PLS) could not only compress the spectrum variables and reduce the model variables, but also improve the quantitative estimation accuracy of soil alkali hydrolysable nitrogen content. Based on the 1-2 levels low frequency coefficients of discrete wavelet transform, and under the condition of large scale decrement of spectrum variables, the calibration models could achieve the higher or the same prediction accuracy as the soil full spectra. The model based on the second level low frequency coefficients had the highest precision, with the model predicting R2 being 0.85, the RMSE being 8.11 mg x kg(-1), and RPD being 2.53, indicating the effectiveness of DWT-GA-PLS method in estimating soil alkali hydrolysable nitrogen content. PMID:24564148
Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)
NASA Astrophysics Data System (ADS)
Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman
2011-12-01
In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.
Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)
NASA Astrophysics Data System (ADS)
Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman
2012-01-01
In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.
Genetic algorithm-based form error evaluation
NASA Astrophysics Data System (ADS)
Cui, Changcai; Li, Bing; Huang, Fugui; Zhang, Rencheng
2007-07-01
Form error evaluation of geometrical products is a nonlinear optimization problem, for which a solution has been attempted by different methods with some complexity. A genetic algorithm (GA) was developed to deal with the problem, which was proved simple to understand and realize, and its key techniques have been investigated in detail. Firstly, the fitness function of GA was discussed emphatically as a bridge between GA and the concrete problems to be solved. Secondly, the real numbers-based representation of the desired solutions in the continual space optimization problem was discussed. Thirdly, many improved evolutionary strategies of GA were described on emphasis. These evolutionary strategies were the selection operation of 'odd number selection plus roulette wheel selection', the crossover operation of 'arithmetic crossover between near relatives and far relatives' and the mutation operation of 'adaptive Gaussian' mutation. After evolutions from generation to generation with the evolutionary strategies, the initial population produced stochastically around the least-squared solutions of the problem would be updated and improved iteratively till the best chromosome or individual of GA appeared. Finally, some examples were given to verify the evolutionary method. Experimental results show that the GA-based method can find desired solutions that are superior to the least-squared solutions except for a few examples in which the GA-based method can obtain similar results to those by the least-squared method. Compared with other optimization techniques, the GA-based method can obtain almost equal results but with less complicated models and computation time.
A genetic algorithm for ground-based telescope observation scheduling
NASA Astrophysics Data System (ADS)
Mahoney, William; Veillet, Christian; Thanjavur, Karun
2012-09-01
A prototype genetic algorithm (GA) is being developed to provide assisted and ultimately automated observation scheduling functionality. Harnessing the logic developed for manual queue preparation, the GA can build suitable sets of queues for the potential combinations of environmental and atmospheric conditions. Evolving one step further, the GA can select the most suitable observation for any moment in time, based on allocated priorities, agency balances, and realtime availability of the skies' condition.
Ameliorated GA approach for base station planning
NASA Astrophysics Data System (ADS)
Wang, Andong; Sun, Hongyue; Wu, Xiaomin
2011-10-01
In this paper, we aim at locating base station (BS) rationally to satisfy the most customs by using the least BSs. An ameliorated GA is proposed to search for the optimum solution. In the algorithm, we mesh the area to be planned according to least overlap length derived from coverage radius, bring into isometric grid encoding method to represent BS distribution as well as its number and develop select, crossover and mutation operators to serve our unique necessity. We also construct our comprehensive object function after synthesizing coverage ratio, overlap ratio, population and geographical conditions. Finally, after importing an electronic map of the area to be planned, a recommended strategy draft would be exported correspondingly. We eventually import HongKong, China to simulate and yield a satisfactory solution.
Calibration of visual model for space manipulator with a hybrid LM-GA algorithm
NASA Astrophysics Data System (ADS)
Jiang, Wensong; Wang, Zhongyu
2016-01-01
A hybrid LM-GA algorithm is proposed to calibrate the camera system of space manipulator to improve its locational accuracy. This algorithm can dynamically fuse the Levenberg-Marqurdt (LM) algorithm and Genetic Algorithm (GA) together to minimize the error of nonlinear camera model. LM algorithm is called to optimize the initial camera parameters that are generated by genetic process previously. Iteration should be stopped if the optimized camera parameters meet the accuracy requirements. Otherwise, new populations are generated again by GA and optimized afresh by LM algorithm until the optimal solutions meet the accuracy requirements. A novel measuring machine of space manipulator is designed to on-orbit dynamic simulation and precision test. The camera system of space manipulator, calibrated by hybrid LM-GA algorithm, is used for locational precision test in this measuring instrument. The experimental results show that the mean composite errors are 0.074 mm for hybrid LM-GA camera calibration model, 1.098 mm for LM camera calibration model, and 1.202 mm for GA camera calibration model. Furthermore, the composite standard deviations are 0.103 mm for the hybrid LM-GA camera calibration model, 1.227 mm for LM camera calibration model, and 1.351 mm for GA camera calibration model. The accuracy of hybrid LM-GA camera calibration model is more than 10 times higher than that of other two methods. All in all, the hybrid LM-GA camera calibration model is superior to both the LM camera calibration model and GA camera calibration model.
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.
GA-Based Image Restoration by Isophote Constraint Optimization
NASA Astrophysics Data System (ADS)
Kim, Jong Bae; Kim, Hang Joon
2003-12-01
We propose an efficient technique for image restoration based on a genetic algorithm (GA) with an isophote constraint. In our technique, the image restoration problem is modeled as an optimization problem which, in our case, is solved by a cost function with isophote constraint that is minimized using a GA. We consider that an image is decomposed into isophotes based on connected components of constant intensity. The technique creates an optimal connection of all pairs of isophotes disconnected by a caption in the frame. For connecting the disconnected isophotes, we estimate the value of the smoothness, given by the best chromosomes of the GA and project this value in the isophote direction. Experimental results show a great possibility for automatic restoration of a region in an advertisement scene.
Projection Classification Based Iterative Algorithm
NASA Astrophysics Data System (ADS)
Zhang, Ruiqiu; Li, Chen; Gao, Wenhua
2015-05-01
Iterative algorithm has good performance as it does not need complete projection data in 3D image reconstruction area. It is possible to be applied in BGA based solder joints inspection but with low convergence speed which usually acts with x-ray Laminography that has a worse reconstruction image compared to the former one. This paper explores to apply one projection classification based method which tries to separate the object to three parts, i.e. solute, solution and air, and suppose that the reconstruction speed decrease from solution to two other parts on both side lineally. And then SART and CAV algorithms are improved under the proposed idea. Simulation experiment result with incomplete projection images indicates the fast convergence speed of the improved iterative algorithms and the effectiveness of the proposed method. Less the projection images, more the superiority is also founded.
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.
Genetic Algorithm based Decentralized PI Type Controller: Load Frequency Control
NASA Astrophysics Data System (ADS)
Dwivedi, Atul; Ray, Goshaidas; Sharma, Arun Kumar
2016-05-01
This work presents a design of decentralized PI type Linear Quadratic (LQ) controller based on genetic algorithm (GA). The proposed design technique allows considerable flexibility in defining the control objectives and it does not consider any knowledge of the system matrices and moreover it avoids the solution of algebraic Riccati equation. To illustrate the results of this work, a load-frequency control problem is considered. Simulation results reveal that the proposed scheme based on GA is an alternative and attractive approach to solve load-frequency control problem from both performance and design point of views.
Research and experiment of InGaAs shortwave infrared imaging system based on FPGA
NASA Astrophysics Data System (ADS)
Ren, Ling; Min, Chaobo; Sun, Jianning; Gu, Yan; Yang, Feng; Zhu, Bo; Pan, Jingsheng; Guo, Yiliang
2015-04-01
The design and imaging characteristic experiment of InGaAs shortwave infrared imaging system are introduced. Through the adoption of InGaAs focal plane array, the real time image process structure of InGaAs shortwave infrared imaging system is researched. The hardware circuit and image process software of the imaging system based on FPGA are researched. The InGaAs shortwave infrared imaging system is composed of shortwave infrared lens, InGaAs focal plane array, temperature controller module, power supply module, analog-to-digital converter module, digital-to-analog converter module, FPGA image processing module and optical-mechanical structure. The main lock frequency of InGaAs shortwave infrared imaging system is 30MHz. The output mode of the InGaAs shortwave infrared imaging system is PAL analog signal. The power dissipation of the imaging system is 2.6W. The real time signal process in InGaAs shortwave infrared imaging system includes non-uniformly correction algorithm, bad pixel replacement algorithm, and histogram equalization algorithm. Based on the InGaAs shortwave infrared imaging system, the imaging characteristic test of shortwave infrared is carried out for different targets in different conditions. In the foggy weather, the haze and fog penetration are tested. The InGaAs shortwave infrared imaging system could be used for observing humans, boats, architecture, and mountains in the haze and foggy weather. The configuration and performance of InGaAs shortwave infrared imaging system are respectively logical and steady. The research on the InGaAs shortwave infrared imaging system is worthwhile for improving the development of night vision technology.
GA-based discrete dynamic programming approach for scheduling in FMS environments.
Yang, J B
2001-01-01
The paper presents a new genetic algorithm (GA)-based discrete dynamic programming (DDP) approach for generating static schedules in a flexible manufacturing system (FMS) environment. This GA-DDP approach adopts a sequence-dependent schedule generation strategy, where a GA is employed to generate feasible job sequences and a series of discrete dynamic programs are constructed to generate legal schedules for a given sequence of jobs. In formulating the GA, different performance criteria could be easily included. The developed DDF algorithm is capable of identifying locally optimized partial schedules and shares the computation efficiency of dynamic programming. The algorithm is designed In such a way that it does not suffer from the state explosion problem inherent in pure dynamic programming approaches in FMS scheduling. Numerical examples are reported to illustrate the approach. PMID:18244848
Research on Routing Selection Algorithm Based on Genetic Algorithm
NASA Astrophysics Data System (ADS)
Gao, Guohong; Zhang, Baojian; Li, Xueyong; Lv, Jinna
The hereditary algorithm is a kind of random searching and method of optimizing based on living beings natural selection and hereditary mechanism. In recent years, because of the potentiality in solving complicate problems and the successful application in the fields of industrial project, hereditary algorithm has been widely concerned by the domestic and international scholar. Routing Selection communication has been defined a standard communication model of IP version 6.This paper proposes a service model of Routing Selection communication, and designs and implements a new Routing Selection algorithm based on genetic algorithm.The experimental simulation results show that this algorithm can get more resolution at less time and more balanced network load, which enhances search ratio and the availability of network resource, and improves the quality of service.
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.
The royal road for genetic algorithms: Fitness landscapes and GA performance
Mitchell, M.; Holland, J.H. ); Forrest, S. . Dept. of Computer Science)
1991-01-01
Genetic algorithms (GAs) play a major role in many artificial-life systems, but there is often little detailed understanding of why the GA performs as it does, and little theoretical basis on which to characterize the types of fitness landscapes that lead to successful GA performance. In this paper we propose a strategy for addressing these issues. Our strategy consists of defining a set of features of fitness landscapes that are particularly relevant to the GA, and experimentally studying how various configurations of these features affect the GA's performance along a number of dimensions. In this paper we informally describe an initial set of proposed feature classes, describe in detail one such class ( Royal Road'' functions), and present some initial experimental results concerning the role of crossover and building blocks'' on landscapes constructed from features of this class. 27 refs., 1 fig., 5 tabs.
An Evolved Wavelet Library Based on Genetic Algorithm
Vaithiyanathan, D.; Seshasayanan, R.; Kunaraj, K.; Keerthiga, J.
2014-01-01
As the size of the images being captured increases, there is a need for a robust algorithm for image compression which satiates the bandwidth limitation of the transmitted channels and preserves the image resolution without considerable loss in the image quality. Many conventional image compression algorithms use wavelet transform which can significantly reduce the number of bits needed to represent a pixel and the process of quantization and thresholding further increases the compression. In this paper the authors evolve two sets of wavelet filter coefficients using genetic algorithm (GA), one for the whole image portion except the edge areas and the other for the portions near the edges in the image (i.e., global and local filters). Images are initially separated into several groups based on their frequency content, edges, and textures and the wavelet filter coefficients are evolved separately for each group. As there is a possibility of the GA settling in local maximum, we introduce a new shuffling operator to prevent the GA from this effect. The GA used to evolve filter coefficients primarily focuses on maximizing the peak signal to noise ratio (PSNR). The evolved filter coefficients by the proposed method outperform the existing methods by a 0.31 dB improvement in the average PSNR and a 0.39 dB improvement in the maximum PSNR. PMID:25405225
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.
The mGA1.0: A common LISP implementation of a messy genetic algorithm
NASA Technical Reports Server (NTRS)
Goldberg, David E.; Kerzic, Travis
1990-01-01
Genetic algorithms (GAs) are finding increased application in difficult search, optimization, and machine learning problems in science and engineering. Increasing demands are being placed on algorithm performance, and the remaining challenges of genetic algorithm theory and practice are becoming increasingly unavoidable. Perhaps the most difficult of these challenges is the so-called linkage problem. Messy GAs were created to overcome the linkage problem of simple genetic algorithms by combining variable-length strings, gene expression, messy operators, and a nonhomogeneous phasing of evolutionary processing. Results on a number of difficult deceptive test functions are encouraging with the mGA always finding global optima in a polynomial number of function evaluations. Theoretical and empirical studies are continuing, and a first version of a messy GA is ready for testing by others. A Common LISP implementation called mGA1.0 is documented and related to the basic principles and operators developed by Goldberg et. al. (1989, 1990). Although the code was prepared with care, it is not a general-purpose code, only a research version. Important data structures and global variations are described. Thereafter brief function descriptions are given, and sample input data are presented together with sample program output. A source listing with comments is also included.
NASA Astrophysics Data System (ADS)
Que, Dashun; Li, Gang; Yue, Peng
2007-12-01
An adaptive optimization watermarking algorithm based on Genetic Algorithm (GA) and discrete wavelet transform (DWT) is proposed in this paper. The core of this algorithm is the fitness function optimization model for digital watermarking based on GA. The embedding intensity for digital watermarking can be modified adaptively, and the algorithm can effectively ensure the imperceptibility of watermarking while the robustness is ensured. The optimization model research may provide a new idea for anti-coalition attacks of digital watermarking algorithm. The paper has fulfilled many experiments, including the embedding and extracting experiments of watermarking, the influence experiments by the weighting factor, the experiments of embedding same watermarking to the different cover image, the experiments of embedding different watermarking to the same cover image, the comparative analysis experiments between this optimization algorithm and human visual system (HVS) algorithm and etc. The simulation results and the further analysis show the effectiveness and advantage of the new algorithm, which also has versatility and expandability. And meanwhile it has better ability of anti-coalition attacks. Moreover, the robustness and security of watermarking algorithm are improved by scrambling transformation and chaotic encryption while preprocessing the watermarking.
DFT algorithms for bit-serial GaAs array processor architectures
NASA Technical Reports Server (NTRS)
Mcmillan, Gary B.
1988-01-01
Systems and Processes Engineering Corporation (SPEC) has developed an innovative array processor architecture for computing Fourier transforms and other commonly used signal processing algorithms. This architecture is designed to extract the highest possible array performance from state-of-the-art GaAs technology. SPEC's architectural design includes a high performance RISC processor implemented in GaAs, along with a Floating Point Coprocessor and a unique Array Communications Coprocessor, also implemented in GaAs technology. Together, these data processors represent the latest in technology, both from an architectural and implementation viewpoint. SPEC has examined numerous algorithms and parallel processing architectures to determine the optimum array processor architecture. SPEC has developed an array processor architecture with integral communications ability to provide maximum node connectivity. The Array Communications Coprocessor embeds communications operations directly in the core of the processor architecture. A Floating Point Coprocessor architecture has been defined that utilizes Bit-Serial arithmetic units, operating at very high frequency, to perform floating point operations. These Bit-Serial devices reduce the device integration level and complexity to a level compatible with state-of-the-art GaAs device technology.
NASA Astrophysics Data System (ADS)
Song, Kaishan; Li, Lin; Li, Shuai; Tedesco, Lenore; Hall, Bob; Li, Zuchuan
2012-08-01
Eagle Creek, Morse and Geist reservoirs, drinking water supply sources for the Indianapolis, Indiana, USA metropolitan region, are experiencing nuisance cyanobacterial blooms. Hyperspectral remote sensing has been proven to be an effective tool for phycocyanin (C-PC) concentration retrieval, a proxy pigment unique to cyanobacteria in freshwater ecosystems. An adaptive model based on genetic algorithm and partial least squares (GA-PLS), together with three-band algorithm (TBA) and other band ratio algorithms were applied to hyperspectral data acquired from in situ (ASD spectrometer) and airborne (AISA sensor) platforms. The results indicated that GA-PLS achieved high correlation between measured and estimated C-PC for GR (RMSE = 16.3 μg/L, RMSE% = 18.2; range (R): 2.6-185.1 μg/L), MR (RMSE = 8.7 μg/L, RMSE% = 15.6; R: 3.3-371.0 μg/L) and ECR (RMSE = 19.3 μg/L, RMSE% = 26.4; R: 0.7-245.0 μg/L) for the in situ datasets. TBA also performed well compared to other band ratio algorithms due to its optimal band tuning process and the reduction of backscattering effects through the third band. GA-PLS (GR: RMSE = 24.1 μg/L, RMSE% = 25.2, R: 25.2-185.1 μg/L; MR: RMSE = 15.7 μg/L, RMSE% = 37.4, R: 2.0-135.1 μg/L) and TBA (GR: RMSE = 28.3 μg/L, RMSE% = 30.1; MR: RMSE = 17.7 μg/L, RMSE% = 41.9) methods results in somewhat lower accuracy using AISA imagery data, which is likely due to atmospheric correction or radiometric resolution. GA-PLS (TBA) obtained an RMSE of 24.82 μg/L (35.8 μg/L), and RMSE% of 31.24 (43.5) between measured and estimated C-PC for aggregated datasets. C-PC maps were generated through GA-PLS using AISA imagery data. The C-PC concentration had an average value of 67.31 ± 44.23 μg/L in MR with a large range of concentration, while the GR had a higher average value 103.17 ± 33.45 μg/L.
Chaos-based image encryption using a hybrid genetic algorithm and a DNA sequence
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Abdullah, Abdul Hanan; Isnin, Ismail Fauzi
2014-05-01
The paper studies a recently developed evolutionary-based image encryption algorithm. A novel image encryption algorithm based on a hybrid model of deoxyribonucleic acid (DNA) masking, a genetic algorithm (GA) and a logistic map is proposed. This study uses DNA and logistic map functions to create the number of initial DNA masks and applies GA to determine the best mask for encryption. The significant advantage of this approach is improving the quality of DNA masks to obtain the best mask that is compatible with plain images. The experimental results and computer simulations both confirm that the proposed scheme not only demonstrates excellent encryption but also resists various typical attacks.
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.
Suspended GaN-based nanostructure for integrated optics
NASA Astrophysics Data System (ADS)
Bai, Dan; Wu, Tong; Li, Xin; Gao, Xumin; Xu, Yin; Cao, Ziping; Zhu, Hongbo; Wang, Yongjin
2016-01-01
We show the fabrication and characterization of a suspended GaN-based nanostructure in the visible wavelength region that combines InGaN/GaN multiple quantum wells (MQWs) active layer with rib waveguides and then creates multiple separate beamlets. It is implemented on a GaN-on-silicon platform, where silicon substrate is removed and suspended epitaxial films are thinned by back wafer etching technique. When the InGaN/GaN MQWs active layer is optically excited, part of the emitted light is confined inside epitaxial films and acts the light source. The lateral propagation direction is controlled by the rib waveguide, and the light intensity and the propagation mode can be tuned by changing the rib waveguide structure. Experimental and simulated results indicate the proposed suspended GaN-based structure is promising for the integration of emitting device with planar optical circuit in the visible wavelength region.
Economic Dispatch Using Genetic Algorithm Based Hybrid Approach
Tahir Nadeem Malik; Aftab Ahmad; Shahab Khushnood
2006-07-01
Power Economic Dispatch (ED) is vital and essential daily optimization procedure in the system operation. Present day large power generating units with multi-valves steam turbines exhibit a large variation in the input-output characteristic functions, thus non-convexity appears in the characteristic curves. Various mathematical and optimization techniques have been developed, applied to solve economic dispatch (ED) problem. Most of these are calculus-based optimization algorithms that are based on successive linearization and use the first and second order differentiations of objective function and its constraint equations as the search direction. They usually require heat input, power output characteristics of generators to be of monotonically increasing nature or of piecewise linearity. These simplifying assumptions result in an inaccurate dispatch. Genetic algorithms have used to solve the economic dispatch problem independently and in conjunction with other AI tools and mathematical programming approaches. Genetic algorithms have inherent ability to reach the global minimum region of search space in a short time, but then take longer time to converge the solution. GA based hybrid approaches get around this problem and produce encouraging results. This paper presents brief survey on hybrid approaches for economic dispatch, an architecture of extensible computational framework as common environment for conventional, genetic algorithm and hybrid approaches based solution for power economic dispatch, the implementation of three algorithms in the developed framework. The framework tested on standard test systems for its performance evaluation. (authors)
A coupled model tree (MT) genetic algorithm (GA) scheme for biofouling assessment in pipelines.
Opher, Tamar; Ostfeld, Avi
2011-11-15
A computerized learning algorithm was developed for assessing the extent of biofouling formations on the inner surfaces of water supply pipelines. Four identical pipeline experimental systems with four different types of inlet waters were set up as part of a large cooperative project between academia and industry in Israel on biofouling modeling, prediction, and prevention in pipeline systems. Samples were taken periodically for hydraulic, chemical, and biological analyses. Biofilm sampling was done using Robbins devices, carrying stainless steel coupons. An MT-GA, a hybrid model combining model trees (MTs) and genetic algorithms (GAs) in which the sampled input data are selected by the proposed methodology, was developed. The method outcome is a set of empirical linear rules which form a model tree, iteratively optimized by a GA and verified using the dataset resulting from the empirical field studies. Good correlations were achieved between modeled and observed cell coverage area within the biofilm. Sensitivity analysis was conducted by testing the model's response to changes in: (1) the biofilm measure used as output (target) variable; (2) variability of GA parameters; and (3) input attributes. The proposed methodology provides a new tool for biofouling assessment in pipelines. PMID:21978570
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.
Point and Extended Defects in GaN-based Materials
NASA Astrophysics Data System (ADS)
Speck, James
In this presentation, the origin and evolution of threading dislocations in GaN heteroepitaxy are reviewed. For heteroepitaxial of GaN on most substrates (e.g., sapphire, MgAl2O4, SiC, ...) high temperature GaN grows in a Volmer-Weber mode. Threading dislocations result from island coalescence. The evolution of threading dislocations has been extensively modeled. Tensile stress generation via threading dislocation inclination is a major ongoing issue in GaN growth. We review older and more recent work on the impact of threading dislocations in GaN materials properties and device performance. Finally, we review recent work from our group on stress relaxation in nonpolar and semipolar GaN. We demonstrate the first GaN-based laser diodes grown on intentionally stress-relaxed buffer layers and we demonstrate control of relaxation in semipolar laser diodes by selective area growth.
Optical Sensor Based Corn Algorithm Evaluation
Technology Transfer Automated Retrieval System (TEKTRAN)
Optical sensor based algorithms for corn fertilization have developed by researchers in several states. The goal of this international research project was to evaluate these different algorithms and determine their robustness over a large geographic area. Concurrently the goal of this project was to...
Initiative learning algorithm based on rough set
NASA Astrophysics Data System (ADS)
Wang, Guoyin; He, Xiao
2003-03-01
Rough set theory is emerging as a new tool for dealing with fuzzy and uncertain data. In this paper, a theory is developed to express, measure and process uncertain information and uncertain knowledge based on our result about the uncertainty measure of decision tables and decision rule systems. Based on Skowron"s propositional default rule generation algorithm, we develop an initiative learning model with rough set based initiative rule generation algorithm. Simulation results illustrate its efficiency.
Efficiently hiding sensitive itemsets with transaction deletion based on genetic algorithms.
Lin, Chun-Wei; Zhang, Binbin; Yang, Kuo-Tung; Hong, Tzung-Pei
2014-01-01
Data mining is used to mine meaningful and useful information or knowledge from a very large database. Some secure or private information can be discovered by data mining techniques, thus resulting in an inherent risk of threats to privacy. Privacy-preserving data mining (PPDM) has thus arisen in recent years to sanitize the original database for hiding sensitive information, which can be concerned as an NP-hard problem in sanitization process. In this paper, a compact prelarge GA-based (cpGA2DT) algorithm to delete transactions for hiding sensitive itemsets is thus proposed. It solves the limitations of the evolutionary process by adopting both the compact GA-based (cGA) mechanism and the prelarge concept. A flexible fitness function with three adjustable weights is thus designed to find the appropriate transactions to be deleted in order to hide sensitive itemsets with minimal side effects of hiding failure, missing cost, and artificial cost. Experiments are conducted to show the performance of the proposed cpGA2DT algorithm compared to the simple GA-based (sGA2DT) algorithm and the greedy approach in terms of execution time and three side effects. PMID:25254239
Improvement of unsupervised texture classification based on genetic algorithms
NASA Astrophysics Data System (ADS)
Okumura, Hiroshi; Togami, Yuuki; Arai, Kohei
2004-11-01
At the previous conference, the authors are proposed a new unsupervised texture classification method based on the genetic algorithms (GA). In the method, the GA are employed to determine location and size of the typical textures in the target image. The proposed method consists of the following procedures: 1) the determination of the number of classification category; 2) each chromosome used in the GA consists of coordinates of center pixel of each training area candidate and those size; 3) 50 chromosomes are generated using random number; 4) fitness of each chromosome is calculated; the fitness is the product of the Classification Reliability in the Mixed Texture Cases (CRMTC) and the Stability of NZMV against Scanning Field of View Size (SNSFS); 5) in the selection operation in the GA, the elite preservation strategy is employed; 6) in the crossover operation, multi point crossover is employed and two parent chromosomes are selected by the roulette strategy; 7) in mutation operation, the locuses where the bit inverting occurs are decided by a mutation rate; 8) go to the procedure 4. However, this method has not been automated because it requires not only target image but also the number of categories for classification. In this paper, we describe some improvement for implementation of automated texture classification. Some experiments are conducted to evaluate classification capability of the proposed method by using images from Brodatz's photo album and actual airborne multispectral scanner. The experimental results show that the proposed method can select appropriate texture samples and can provide reasonable classification results.
NASA Astrophysics Data System (ADS)
Liu, Hua-Long; Liu, Hua-Dong
2014-10-01
Partial discharge (PD) in power transformers is one of the prime reasons resulting in insulation degradation and power faults. Hence, it is of great importance to study the techniques of the detection and localization of PD in theory and practice. The detection and localization of PD employing acoustic emission (AE) techniques, as a kind of non-destructive testing, plus due to the advantages of powerful capability of locating and high precision, have been paid more and more attention. The localization algorithm is the key factor to decide the localization accuracy in AE localization of PD. Many kinds of localization algorithms exist for the PD source localization adopting AE techniques including intelligent and non-intelligent algorithms. However, the existed algorithms possess some defects such as the premature convergence phenomenon, poor local optimization ability and unsuitability for the field applications. To overcome the poor local optimization ability and easily caused premature convergence phenomenon of the fundamental genetic algorithm (GA), a new kind of improved GA is proposed, namely the sequence quadratic programming-genetic algorithm (SQP-GA). For the hybrid optimization algorithm, SQP-GA, the sequence quadratic programming (SQP) algorithm which is used as a basic operator is integrated into the fundamental GA, so the local searching ability of the fundamental GA is improved effectively and the premature convergence phenomenon is overcome. Experimental results of the numerical simulations of benchmark functions show that the hybrid optimization algorithm, SQP-GA, is better than the fundamental GA in the convergence speed and optimization precision, and the proposed algorithm in this paper has outstanding optimization effect. At the same time, the presented SQP-GA in the paper is applied to solve the ultrasonic localization problem of PD in transformers, then the ultrasonic localization method of PD in transformers based on the SQP-GA is proposed. And
Ellipsometric characterization of surface freezing in Ga-based alloys
NASA Astrophysics Data System (ADS)
Bartel, K.; Nattland, D.; Kumar, A.; Dogel, S.; Freyland, W.
2006-04-01
We present results on surface freezing of Ga-based alloys, GaBi, GaPb and GaTl, above the liquidus line between the Ga-rich eutectic and the monotectic point. Spectroscopic ellipsometry (0.8 eV <=hν<=4.2 eV) and kinetic single wavelength ellipsometry (2.75 eV) have been employed to probe the changes of the interfacial electronic structures on surface freezing. To minimize thermal gradients across the sample a heatable cap that covers the sample and crucible was developed. The surface freezing temperature, TSF, for the spontaneous formation of a solid-like film on top of the Ga-rich liquid on cooling the sample from the homogeneous phase region was found to be independent of the temperature difference between the upper and lower furnace (ΔT: +10 to -10 K) and only weakly dependent on the cooling rate (\\partial T/\\partial t : 2.5-20 K h-1). In the case of GaPb the solid film consists of solid Pb with a thickness h>=400 Å. Comparing with GaBi we draw analogous conclusions for GaPb and GaTl and suggest that the surface freezing transition precedes the bulk phase transition along the liquidus line as the alloy is cooled.
Test Scheduling for Core-Based SOCs Using Genetic Algorithm Based Heuristic Approach
NASA Astrophysics Data System (ADS)
Giri, Chandan; Sarkar, Soumojit; Chattopadhyay, Santanu
This paper presents a Genetic algorithm (GA) based solution to co-optimize test scheduling and wrapper design for core based SOCs. Core testing solutions are generated as a set of wrapper configurations, represented as rectangles with width equal to the number of TAM (Test Access Mechanism) channels and height equal to the corresponding testing time. A locally optimal best-fit heuristic based bin packing algorithm has been used to determine placement of rectangles minimizing the overall test times, whereas, GA has been utilized to generate the sequence of rectangles to be considered for placement. Experimental result on ITC'02 benchmark SOCs shows that the proposed method provides better solutions compared to the recent works reported in the literature.
QPSO-Based Adaptive DNA Computing Algorithm
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
Ultrafast Photodetection in the Quantum Wells of Single AlGaAs/GaAs-Based Nanowires
NASA Astrophysics Data System (ADS)
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.
2015-10-01
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 photo-thermoelectric 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.
Ultrafast Photodetection in the Quantum Wells of Single AlGaAs/GaAs-Based Nanowires.
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. PMID:26356189
Photoelectric properties of solar cells based on GaPNAs/GaP heterostructures
NASA Astrophysics Data System (ADS)
Baranov, A. I.; Gudovskikh, A. S.; Nikitina, E. V.; Egorov, A. Yu.
2013-12-01
It is shown that photovoltaic converters (PVCs) can be based on GaPNAs/GaP heterostructures, which are of considerable interest for the creation of multijunction solar cells on silicon substrates. It is established that p-i-n structures with undoped GaPNAs layer provide for a more effective separation of charge carriers, which makes it possible to obtain a greater short-circuit current than that in p-n structures with an n-type base. A specific feature in spectral characteristics of the proposed PVCs is the presence of two peaks in the spectra of quantum efficiency, which is related to a complicated band structure of GaPNAs.
Beyond Hydrodynamics via a Fluid Element PIC algorithm, GaPH
NASA Astrophysics Data System (ADS)
Bateson, William; Hewett, Dennis; Lambert, Michael
1996-11-01
For strongly-driven gas and plasma systems, issues of interpenetration and turbulence have led to difficulties with fluid models. For example, a Maxwell distribution within the finite volume could miss the interpenetration and shear regions between two fluids. To address these and other issues, we have extended our Grid and Particle Hydrodynamics (GaPH), a fluid element PIC code, beyond the initial high-precision, 1-D collisionless solutions[2] to 2-D with both binary and viscous drag collisions. The GaPH algorithm still aggressively probes for emerging phase space features by fitting new "particles" to the "hydrodynamic" evolution of individual particles and aggressively merges to preserves economy if interesting features fail to materialize. Recent extensions add collisonal diffusion to the hydrodynamics. Through these and other extensions, GaPH approximates Boltzmann transport thus leaving the fluid model assumption of a local Maxwell distribution behind. [1] This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract W-7405-Eng-48 and by Sandia National Laboratory under Contract DE-AC04-94AL85000. [2] "Beyond Hydrodynamics via Fluid Element Particle-In-Cell", WB Bateson and DW Hewett, (submitted J. Comp. Phys. July 1996).
Swarm-based algorithm for phase unwrapping.
da Silva Maciel, Lucas; Albertazzi, Armando G
2014-08-20
A novel algorithm for phase unwrapping based on swarm intelligence is proposed. The algorithm was designed based on three main goals: maximum coverage of reliable information, focused effort for better efficiency, and reliable unwrapping. Experiments were performed, and a new agent was designed to follow a simple set of five rules in order to collectively achieve these goals. These rules consist of random walking for unwrapping and searching, ambiguity evaluation by comparing unwrapped regions, and a replication behavior responsible for the good distribution of agents throughout the image. The results were comparable with the results from established methods. The swarm-based algorithm was able to suppress ambiguities better than the flood-fill algorithm without relying on lengthy processing times. In addition, future developments such as parallel processing and better-quality evaluation present great potential for the proposed method. PMID:25321125
Vector Quantization Algorithm Based on Associative Memories
NASA Astrophysics Data System (ADS)
Guzmán, Enrique; Pogrebnyak, Oleksiy; Yáñez, Cornelio; Manrique, Pablo
This paper presents a vector quantization algorithm for image compression based on extended associative memories. The proposed algorithm is divided in two stages. First, an associative network is generated applying the learning phase of the extended associative memories between a codebook generated by the LBG algorithm and a training set. This associative network is named EAM-codebook and represents a new codebook which is used in the next stage. The EAM-codebook establishes a relation between training set and the LBG codebook. Second, the vector quantization process is performed by means of the recalling stage of EAM using as associative memory the EAM-codebook. This process generates a set of the class indices to which each input vector belongs. With respect to the LBG algorithm, the main advantages offered by the proposed algorithm is high processing speed and low demand of resources (system memory); results of image compression and quality are presented.
Electrical performances of commercial GaN and GaAs based optoelectronics under neutron irradiation
NASA Astrophysics Data System (ADS)
Fauzi, D. Ahmad; Rashid, N. K. A. Md; Karim, J. Abdul; Zin, M. R. Mohamed; Hasbullah, N. F.; Sheik Fareed, O. A.
2013-12-01
This paper aims to demonstrate the effects of displacement damage caused by high energetic neutron particle towards the electrical performances of gallium arsenide (GaAs) and gallium nitride (GaN) p-n based diodes. The investigations are carried out through current-voltage (I-V) and capacitance-voltage (C-V) measurements using Keithley 4200 SCS. Two different commercial optoelectronics diodes; GaN on SiC light emitting diode (LED) and GaAs infrared emitting diode (IRED) were radiated with neutron using pneumatic transfer system (PTS) in the PUSPATI TRIGA Mark II research reactor under total neutron flux of 1×1012 neutron/cm2.s. Following the neutron exposure for 1, 3 and 5 minutes, the I-V forward bias and reverse bias leakage current increase for GaAs IREDs, but minimal changes were observed in the GaN LEDs. The C-V measurements revealed that the capacitance and carrier concentration of GaAs IREDs decrease with increasing radiation flux.
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.
TOPICAL REVIEW: InGaN-based violet laser diodes
NASA Astrophysics Data System (ADS)
Nakamura, S.
1999-06-01
High-efficiency light-emitting diodes emitting amber, green, blue and ultraviolet light have been obtained through the use of InGaN active layers instead of GaN active layers. The localized energy states caused by In composition fluctuation in the InGaN active layer seem to be related to the high efficiency of the InGaN-based emitting devices. Long-lifetime violet InGaN multi-quantum-well/GaN/AlGaN separate-confinement heterostructure laser diodes (LDs) were successfully fabricated using epitaxially laterally overgrown GaN by reducing a large number of threading dislocations originating from the interface between GaN and sapphire substrate. The threading dislocations shorten the lifetime of the LDs through an increase of the threshold current density. The LDs with cleaved mirror facets showed an output power as high as 30 mW under room-temperature continuous-wave (CW) operation with a stable fundamental transverse mode. The lifetime of the LDs at a constant output power of 5 mW was estimated to be approximately 3000 h under CW operation at an ambient temperature of 50 °C. These results indicate that these LDs already can be used for many real applications, such as digital versatile disks, laser printers, sensors and exciting light sources as a commercial product with a high output power and a high reliability.
Optimisation of nonlinear motion cueing algorithm based on genetic algorithm
NASA Astrophysics Data System (ADS)
Asadi, Houshyar; Mohamed, Shady; Rahim Zadeh, Delpak; Nahavandi, Saeid
2015-04-01
Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching
High Brightness GaN-Based Light-Emitting Diodes
NASA Astrophysics Data System (ADS)
Lee, Ya-Ju; Lu, Tien-Chang; Kuo, Hao-Chung; Wang, Shing-Chung
2007-06-01
This paper reviews our recent progress of GaN-based high brightness light-emitting diodes (LEDs). Firstly, by adopting chemical wet etching patterned sapphire substrates in GaN-based LEDs, not only could increase the extraction quantum efficiency, but also improve the internal quantum efficiency. Secondly, we present a high light-extraction 465-nm GaN-based vertical light-emitting diode structure with double diffuse surfaces. The external quantum efficiency was demonstrated to be about 40%. The high performance LED was achieved mainly due to the strong guided-light scattering efficiency while employing double diffuse surfaces.
SOM-based algorithms for qualitative variables.
Cottrell, Marie; Ibbou, Smaïl; Letrémy, Patrick
2004-01-01
It is well known that the SOM algorithm achieves a clustering of data which can be interpreted as an extension of Principal Component Analysis, because of its topology-preserving property. But the SOM algorithm can only process real-valued data. In previous papers, we have proposed several methods based on the SOM algorithm to analyze categorical data, which is the case in survey data. In this paper, we present these methods in a unified manner. The first one (Kohonen Multiple Correspondence Analysis, KMCA) deals only with the modalities, while the two others (Kohonen Multiple Correspondence Analysis with individuals, KMCA_ind, Kohonen algorithm on DISJonctive table, KDISJ) can take into account the individuals, and the modalities simultaneously. PMID:15555858
GaInN-based tunnel junctions with graded layers
NASA Astrophysics Data System (ADS)
Takasuka, Daiki; Akatsuka, Yasuto; Ino, Masataka; Koide, Norikatsu; Takeuchi, Tetsuya; Iwaya, Motoaki; Kamiyama, Satoshi; Akasaki, Isamu
2016-08-01
We demonstrated low-resistivity GaInN-based tunnel junctions using graded GaInN layers. A systematic investigation of the samples grown by metalorganic vapor phase epitaxy revealed that a tunnel junction consisting of a 4 nm both-sides graded GaInN layer (Mg: 1 × 1020 cm‑3) and a 2 nm GaN layer (Si: 7 × 1020 cm‑3) showed the lowest specific series resistance of 2.3 × 10‑4 Ω cm2 at 3 kA/cm2 in our experiment. The InN mole fraction in the 4 nm both-sides graded GaInN layer was changed from 0 through 0.4 to 0. The obtained resistance is comparable to those of standard p-contacts with Ni/Au and MBE-grown tunnel junctions.
Color sorting algorithm based on K-means clustering algorithm
NASA Astrophysics Data System (ADS)
Zhang, BaoFeng; Huang, Qian
2009-11-01
In the process of raisin production, there were a variety of color impurities, which needs be removed effectively. A new kind of efficient raisin color-sorting algorithm was presented here. First, the technology of image processing basing on the threshold was applied for the image pre-processing, and then the gray-scale distribution characteristic of the raisin image was found. In order to get the chromatic aberration image and reduce some disturbance, we made the flame image subtraction that the target image data minus the background image data. Second, Haar wavelet filter was used to get the smooth image of raisins. According to the different colors and mildew, spots and other external features, the calculation was made to identify the characteristics of their images, to enable them to fully reflect the quality differences between the raisins of different types. After the processing above, the image were analyzed by K-means clustering analysis method, which can achieve the adaptive extraction of the statistic features, in accordance with which, the image data were divided into different categories, thereby the categories of abnormal colors were distinct. By the use of this algorithm, the raisins of abnormal colors and ones with mottles were eliminated. The sorting rate was up to 98.6%, and the ratio of normal raisins to sorted grains was less than one eighth.
GaAs-based optoelectronic neurons
NASA Technical Reports Server (NTRS)
Lin, Steven H. (Inventor); Kim, Jae H. (Inventor); Psaltis, Demetri (Inventor)
1993-01-01
An integrated, optoelectronic, variable thresholding neuron implemented monolithically in GaAs integrated circuit and exhibiting high differential optical gain and low power consumption is presented. Two alternative embodiments each comprise an LED monolithically integrated with a detector and two transistors. One of the transistors is responsive to a bias voltage applied to its gate for varying the threshold of the neuron. One embodiment is implemented as an LED monolithically integrated with a double heterojunction bipolar phototransistor (detector) and two metal semiconductor field effect transistors (MESFET's) on a single GaAs substrate and another embodiment is implemented as an LED monolithically integrated with three MESFET's (one of which is an optical FET detector) on a single GaAs substrate. The first noted embodiment exhibits a differential optical gain of 6 and an optical switching energy of 10 pJ. The second embodiment has a differential optical gain of 80 and an optical switching energy of 38 pJ. Power consumption is 2.4 and 1.8 mW, respectively. Input 'light' power needed to turn on the LED is 2 micro-W and 54 nW, respectively. In both embodiments the detector is in series with a biasing MESFET and saturates the other MESFET upon detecting light above a threshold level. The saturated MESFET turns on the LED. Voltage applied to the biasing MESFET gate controls the threshold.
Optimal caching algorithm based on dynamic programming
NASA Astrophysics Data System (ADS)
Guo, Changjie; Xiang, Zhe; Zhong, Yuzhuo; Long, Jidong
2001-07-01
With the dramatic growth of multimedia streams, the efficient distribution of stored videos has become a major concern. There are two basic caching strategies: the whole caching strategy and the caching strategy based on layered encoded video, the latter can satisfy the requirement of the highly heterogeneous access to the Internet. Conventional caching strategies assign each object a cache gain by calculating popularity or density popularity, and determine which videos and which layers should be cached. In this paper, we first investigate the delivery model of stored video based on proxy, and propose two novel caching algorithms, DPLayer (for layered encoded caching scheme) and DPWhole (for whole caching scheme) for multimedia proxy caching. The two algorithms are based on the resource allocation model of dynamic programming to select the optimal subset of objects to be cached in proxy. Simulation proved that our algorithms achieve better performance than other existing schemes. We also analyze the computational complexity and space complexity of the algorithms, and introduce a regulative parameter to compress the states space of the dynamic programming problem and reduce the complexity of algorithms.
Auger effect in yellow light emitters based on InGaN–AlGaN–GaN quantum wells
NASA Astrophysics Data System (ADS)
Huong Ngo, Thi; Gil, Bernard; Valvin, Pierre; Damilano, Benjamin; Lekhal, Kaddour; De Mierry, Philippe
2016-05-01
The Auger effect and its impact on the internal quantum efficiency (IQE) of yellow light emitters based on silicon-doped InGaN–AlGaN–GaN quantum wells are investigated by power dependence measurement and using an ABC model. Photoluminescence intensity recorded as a function of excitation power density follows a linear dependence up to a threshold P T that depends on the design of the sample. Above this threshold, the variation of the intensity becomes sublinear, which is characteristic of the onset of Auger recombination processes. After extracting the evolution of IQE with pump power from the experimental data, we use a modified ABC modeling that includes the residual n-type doping to estimate the contribution of different recombination channels. We find that the Auger effect dominates in the high-excitation regime. In addition, we find that intercalating an AlGaN-strain-compensating layer reduces not only the coefficient of nonradiative recombination rates but also reduces the onset of Auger recombination.
Rafiei, Hamid; Khanzadeh, Marziyeh; Mozaffari, Shahla; Bostanifar, Mohammad Hassan; Avval, Zhila Mohajeri; Aalizadeh, Reza; Pourbasheer, Eslam
2016-01-01
Quantitative structure-activity relationship (QSAR) study has been employed for predicting the inhibitory activities of the Hepatitis C virus (HCV) NS5B polymerase inhibitors. A data set consisted of 72 compounds was selected, and then different types of molecular descriptors were calculated. The whole data set was split into a training set (80 % of the dataset) and a test set (20 % of the dataset) using principle component analysis. The stepwise (SW) and the genetic algorithm (GA) techniques were used as variable selection tools. Multiple linear regression method was then used to linearly correlate the selected descriptors with inhibitory activities. Several validation technique including leave-one-out and leave-group-out cross-validation, Y-randomization method were used to evaluate the internal capability of the derived models. The external prediction ability of the derived models was further analyzed using modified r2, concordance correlation coefficient values and Golbraikh and Tropsha acceptable model criteria's. Based on the derived results (GA-MLR), some new insights toward molecular structural requirements for obtaining better inhibitory activity were obtained. PMID:27065774
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).
Structure-based algorithms for microvessel classification
Smith, Amy F.; Secomb, Timothy W.; Pries, Axel R.; Smith, Nicolas P.; Shipley, Rebecca J.
2014-01-01
Objective Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries and venules. PMID:25403335
Automatic 3D image registration using voxel similarity measurements based on a genetic algorithm
NASA Astrophysics Data System (ADS)
Huang, Wei; Sullivan, John M., Jr.; Kulkarni, Praveen; Murugavel, Murali
2006-03-01
An automatic 3D non-rigid body registration system based upon the genetic algorithm (GA) process is presented. The system has been successfully applied to 2D and 3D situations using both rigid-body and affine transformations. Conventional optimization techniques and gradient search strategies generally require a good initial start location. The GA approach avoids the local minima/maxima traps of conventional optimization techniques. Based on the principles of Darwinian natural selection (survival of the fittest), the genetic algorithm has two basic steps: 1. Randomly generate an initial population. 2. Repeated application of the natural selection operation until a termination measure is satisfied. The natural selection process selects individuals based on their fitness to participate in the genetic operations; and it creates new individuals by inheritance from both parents, genetic recombination (crossover) and mutation. Once the termination criteria are satisfied, the optimum is selected from the population. The algorithm was applied on 2D and 3D magnetic resonance images (MRI). It does not require any preprocessing such as threshold, smoothing, segmentation, or definition of base points or edges. To evaluate the performance of the GA registration, the results were compared with results of the Automatic Image Registration technique (AIR) and manual registration which was used as the gold standard. Results showed that our GA implementation was a robust algorithm and gives very close results to the gold standard. A pre-cropping strategy was also discussed as an efficient preprocessing step to enhance the registration accuracy.
A model-base comparison - GaAs/GaAlAs HBT versus silicon bipolar
NASA Astrophysics Data System (ADS)
Kurata, M.; Katoh, R.; Yoshida, J.; Akagi, J.
1986-10-01
A pure model-base comparison is made between the GaAs/GaAlAs heterojunction bipolar transistor and the silicon bipolar transistor for the high-speed switching performance under ring oscillator operation. Full utilization is made of the earlier developed (Kurata et al., 1984 and 1985) modeling tools, which include a 'physical' one-dimensional transistor model, a hybrid model to represent a realistic device structure, and a circuit simulator to allow direct access to the physical model. Delay time versus power characteristics, as well as dynamic carrier profiles are demonstrated, with discussion about limiting factors for the switching speed.
Simplified gas sensor model based on AlGaN/GaN heterostructure Schottky diode
Das, Subhashis Majumdar, S.; Kumar, R.; Bag, A.; Chakraborty, A.; Biswas, D.
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.
Simplified gas sensor model based on AlGaN/GaN heterostructure Schottky diode
NASA Astrophysics Data System (ADS)
Das, Subhashis; Majumdar, S.; Kumar, R.; Chakraborty, A.; Bag, A.; Biswas, D.
2015-08-01
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.
Terahertz intersubband photodetectors based on semi-polar GaN/AlGaN heterostructures
NASA Astrophysics Data System (ADS)
Durmaz, Habibe; Nothern, Denis; Brummer, Gordie; Moustakas, Theodore D.; Paiella, Roberto
2016-05-01
Terahertz intersubband photodetectors are developed based on GaN/AlGaN quantum wells grown on a free-standing semi-polar ( 20 2 ¯ 1 ¯ ) GaN substrate. These quantum wells are nearly free of the polarization-induced internal electric fields that severely complicate the design of nitride intersubband devices on traditional c-plane substrates. As a result, a promising bound-to-quasi-bound THz photodetector design can be implemented. Pronounced photocurrent peaks at the design frequency near 10 THz are measured, covering frequencies that are fundamentally inaccessible to existing arsenide intersubband devices due to reststrahlen absorption. This materials system provides a favorable platform to utilize the intrinsic advantages of nitride semiconductors for THz optoelectronics.
Numerical Algorithms Based on Biorthogonal Wavelets
NASA Technical Reports Server (NTRS)
Ponenti, Pj.; Liandrat, J.
1996-01-01
Wavelet bases are used to generate spaces of approximation for the resolution of bidimensional elliptic and parabolic problems. Under some specific hypotheses relating the properties of the wavelets to the order of the involved operators, it is shown that an approximate solution can be built. This approximation is then stable and converges towards the exact solution. It is designed such that fast algorithms involving biorthogonal multi resolution analyses can be used to resolve the corresponding numerical problems. Detailed algorithms are provided as well as the results of numerical tests on partial differential equations defined on the bidimensional torus.
Algorithmic Differentiation for Calculus-based Optimization
NASA Astrophysics Data System (ADS)
Walther, Andrea
2010-10-01
For numerous applications, the computation and provision of exact derivative information plays an important role for optimizing the considered system but quite often also for its simulation. This presentation introduces the technique of Algorithmic Differentiation (AD), a method to compute derivatives of arbitrary order within working precision. Quite often an additional structure exploitation is indispensable for a successful coupling of these derivatives with state-of-the-art optimization algorithms. The talk will discuss two important situations where the problem-inherent structure allows a calculus-based optimization. Examples from aerodynamics and nano optics illustrate these advanced optimization approaches.
Analogue factoring algorithm based on polychromatic interference
NASA Astrophysics Data System (ADS)
Tamma, Vincenzo; Garuccio, Augusto; Shih, Yanhua
2010-08-01
We present a novel factorization algorithm which can be computed using an analogue computer based on a polychromatic source with a given wavelength bandwidth, a multi-path interferometer and a spectrometer. The core of this algorithm stands on the measurement of the periodicity of a "factoring" function given by an exponential sum at continuous argument by recording a sequence of interferograms associated with suitable units of displacement in the inteferometer. A remarking rescaling property of such interferograms allows, in principle, the prime number decomposition of several large integers. The information about factors is encoded in the location of the inteferogram maxima.
NASA Astrophysics Data System (ADS)
Wang, Xuewu; Shi, Yingpan; Ding, Dongyan; Gu, Xingsheng
2016-02-01
Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm-particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.
A Reliability-Based Track Fusion Algorithm
Xu, Li; Pan, Liqiang; Jin, Shuilin; Liu, Haibo; Yin, Guisheng
2015-01-01
The common track fusion algorithms in multi-sensor systems have some defects, such as serious imbalances between accuracy and computational cost, the same treatment of all the sensor information regardless of their quality, high fusion errors at inflection points. To address these defects, a track fusion algorithm based on the reliability (TFR) is presented in multi-sensor and multi-target environments. To improve the information quality, outliers in the local tracks are eliminated at first. Then the reliability of local tracks is calculated, and the local tracks with high reliability are chosen for the state estimation fusion. In contrast to the existing methods, TFR reduces high fusion errors at the inflection points of system tracks, and obtains a high accuracy with less computational cost. Simulation results verify the effectiveness and the superiority of the algorithm in dense sensor environments. PMID:25950174
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.
A graph spectrum based geometric biclustering algorithm.
Wang, Doris Z; Yan, Hong
2013-01-21
Biclustering is capable of performing simultaneous clustering on two dimensions of a data matrix and has many applications in pattern classification. For example, in microarray experiments, a subset of genes is co-expressed in a subset of conditions, and biclustering algorithms can be used to detect the coherent patterns in the data for further analysis of function. In this paper, we present a graph spectrum based geometric biclustering (GSGBC) algorithm. In the geometrical view, biclusters can be seen as different linear geometrical patterns in high dimensional spaces. Based on this, the modified Hough transform is used to find the Hough vector (HV) corresponding to sub-bicluster patterns in 2D spaces. A graph can be built regarding each HV as a node. The graph spectrum is utilized to identify the eigengroups in which the sub-biclusters are grouped naturally to produce larger biclusters. Through a comparative study, we find that the GSGBC achieves as good a result as GBC and outperforms other kinds of biclustering algorithms. Also, compared with the original geometrical biclustering algorithm, it reduces the computing time complexity significantly. We also show that biologically meaningful biclusters can be identified by our method from real microarray gene expression data. PMID:23079285
Fast Algorithms for Model-Based Diagnosis
NASA Technical Reports Server (NTRS)
Fijany, Amir; Barrett, Anthony; Vatan, Farrokh; Mackey, Ryan
2005-01-01
Two improved new methods for automated diagnosis of complex engineering systems involve the use of novel algorithms that are more efficient than prior algorithms used for the same purpose. Both the recently developed algorithms and the prior algorithms in question are instances of model-based diagnosis, which is based on exploring the logical inconsistency between an observation and a description of a system to be diagnosed. As engineering systems grow more complex and increasingly autonomous in their functions, the need for automated diagnosis increases concomitantly. In model-based diagnosis, the function of each component and the interconnections among all the components of the system to be diagnosed (for example, see figure) are represented as a logical system, called the system description (SD). Hence, the expected behavior of the system is the set of logical consequences of the SD. Faulty components lead to inconsistency between the observed behaviors of the system and the SD. The task of finding the faulty components (diagnosis) reduces to finding the components, the abnormalities of which could explain all the inconsistencies. Of course, the meaningful solution should be a minimal set of faulty components (called a minimal diagnosis), because the trivial solution, in which all components are assumed to be faulty, always explains all inconsistencies. Although the prior algorithms in question implement powerful methods of diagnosis, they are not practical because they essentially require exhaustive searches among all possible combinations of faulty components and therefore entail the amounts of computation that grow exponentially with the number of components of the system.
Investigation of amber light-emitting diodes based on InGaN/AlN/AlGaN quantum wells
NASA Astrophysics Data System (ADS)
Iida, Daisuke; Lu, Shen; Hirahara, Sota; Niwa, Kazumasa; Kamiyama, Satoshi; Ohkawa, Kazuhiro
2016-05-01
We investigated InGaN-based amber light-emitting diodes (LEDs) with AlN/(Al)GaN barrier layers grown by metalorganic vapor-phase epitaxy. Tensilely strained AlN/Al0.03Ga0.97N barriers improved the crystalline quality of compressively strained InGaN quantum wells. We found that strain compensation among wells and barriers improves the external quantum efficiency of high-In-content InGaN-based amber LEDs. The amber LEDs with AlN/Al0.03Ga0.97N barriers have shown an electroluminescence (EL) intensity approximately 2.5-fold that of LEDs with the AlN/GaN barriers at 20 mA.
Edge detection based on genetic algorithm and sobel operator in image
NASA Astrophysics Data System (ADS)
Tong, Xin; Ren, Aifeng; Zhang, Haifeng; Ruan, Hang; Luo, Ming
2011-10-01
Genetic algorithm (GA) is widely used as the optimization problems using techniques inspired by natural evolution. In this paper we present a new edge detection technique based on GA and sobel operator. The sobel edge detection built in DSP Builder is first used to determine the boundaries of objects within an image. Then the genetic algorithm using SOPC Builder proposes a new threshold algorithm for the image processing. Finally, the performance of the new edge detection technique-based the best threshold approaches in DSP Builder and Quartus II software is compared both qualitatively and quantitatively with the single sobel operator. The new edge detection technique is shown to perform very well in terms of robustness to noise, edge search capability and quality of the final edge image.
LSB Based Quantum Image Steganography Algorithm
NASA Astrophysics Data System (ADS)
Jiang, Nan; Zhao, Na; Wang, Luo
2016-01-01
Quantum steganography is the technique which hides a secret message into quantum covers such as quantum images. In this paper, two blind LSB steganography algorithms in the form of quantum circuits are proposed based on the novel enhanced quantum representation (NEQR) for quantum images. One algorithm is plain LSB which uses the message bits to substitute for the pixels' LSB directly. The other is block LSB which embeds a message bit into a number of pixels that belong to one image block. The extracting circuits can regain the secret message only according to the stego cover. Analysis and simulation-based experimental results demonstrate that the invisibility is good, and the balance between the capacity and the robustness can be adjusted according to the needs of applications.
Automated Vectorization of Decision-Based Algorithms
NASA Technical Reports Server (NTRS)
James, Mark
2006-01-01
Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.
Network-based recommendation algorithms: A review
NASA Astrophysics Data System (ADS)
Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš
2016-06-01
Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.
GaAs/InGaP Core-Multishell Nanowire-Array-Based Solar Cells
NASA Astrophysics Data System (ADS)
Nakai, Eiji; Yoshimura, Masatoshi; Tomioka, Katsuhiro; Fukui, Takashi
2013-05-01
Semiconductor nanowires (NWs) are good candidate for light-absorbing material in next generation photovoltaic and III-V NW-based multi-heterojunction solar cells using lattice-mismatched material system are expected as high energy-conversion efficiencies under concentrated light. Here we demonstrate core-shell GaAs NW arrays by using catalyst-free selective-area metal organic vapor phase epitaxy (SA-MOVPE) as a basis for multijunction solar cells. The reflectance of the NW array without any anti-reflection coating showed much lower reflection than that of a planar wafer. Next we then fabricated core-shell GaAs NW array solar cells with radial p-n junction. Despite the low reflectance, the energy-conversion efficiency was 0.71% since a high surface recombination rate of photo-generated carriers and poor ohmic contact between the GaAs and transparent indium-tin-oxide (ITO) electrode. To avoid these degradations, we introduced an InGaP layer and a Ti/ITO electrode. As a result, we obtained a short-circuit current of 12.7 mA cm-2, an open-circuit voltage of 0.5 V, and a fill factor of 0.65 for an overall efficiency of 4.01%.
NASA Astrophysics Data System (ADS)
Kim, Eunsu; Kim, Manseok; Kim, Jong-Wook
In this paper, a humanoid is simulated and implemented to walk up and down a staircase using the blending polynomial and genetic algorithm (GA). Both ascending and descending a staircase are scheduled by four steps. Each step mimics natural gait of human being and is easy to analyze and implement. Optimal trajectories of ten motors in a lower extremity of a humanoid are rigorously computed to simultaneously satisfy stability condition, walking constraints, and energy efficiency requirements. As an optimization method, GA is applied to search optimal trajectory parameters in blending polynomials. The feasibility of this approach will be validated by simulation with a small humanoid robot.
Research on the key techniques of form and position evaluation based on the genetic algorithm
NASA Astrophysics Data System (ADS)
Cui, Changcai; Li, Bing
2006-11-01
The Evolutionary Algorithm (EA)-Genetic Algorithm (GA) was improved to evaluate the form and position errors that were summarized as nonlinear optimization problems. The key techniques in the implementation of the GA have been studied in detail. The emphasis was on the fitness functions of the GA concerned with the concrete problem so that they were proposed first. Second the expression of the desired solutions was discussed in the continual space optimization problem. Because different expression was suitable for different problem, here the real numbers were used to express the solutions to find which were called as chromosomes in the GA. Third the improved evolutionary strategies of GA were described respectively on emphasis. They were the selection operation of Odd Number Selection plus Roulette Wheel Selection, the crossover operation of Arithmetic Crossover Between Near Relatives and Far Relatives, and the mutation operation of Adaptive Gaussian mutation. The evolutionary strategies determined the update of the whole population and the terminal solution. After operations from generation to generation, the initial stochastic population on the basis of the least squared solutions would be improved until the best chromosome/individual appeared. Finally some examples were computed to verify the devised method. The experimental results show that the GA-based method can find the desired solutions that are superior to the least squared solutions and almost equal to those given by other optimization techniques except a few examples give a similar result.
Photoemission characteristics of thin GaAs-based heterojunction photocathodes
Feng, Cheng; Zhang, Yijun Qian, Yunsheng; Shi, Feng; Zou, Jijun; Zeng, Yugang
2015-01-14
To better understand the different photoemission mechanism of thin heterojunction photocathodes, the quantum efficiency models of reflection-mode and transmission-mode GaAs-based heterojunction photocathodes are revised based on one-dimensional continuity equations, wherein photoelectrons generated from both the emission layer and buffer layer are taken into account. By comparison of simulated results between the revised and conventional models, it is found that the electron contribution from the buffer layer to shortwave quantum efficiency is closely related to some factors, such as the thicknesses of emission layer and buffer layer and the interface recombination velocity. Besides, the experimental quantum efficiency data of reflection-mode and transmission-mode AlGaAs/GaAs photocathodes are well fitted to the revised models, which confirm the applicability of the revised quantum efficiency models.
A new structure of p-GaN/InGaN heterojunction to enhance hole injection for blue GaN-based LEDs
NASA Astrophysics Data System (ADS)
Lin, Zhiting; Wang, Haiyan; Lin, Yunhao; Yang, Meijuan; Li, Guoqiang; Xu, Bingshe
2016-07-01
A new structure of p-GaN/InGaN heterojunction has been proposed to enhance hole injection for blue GaN-based light-emitting diodes (LEDs). It is demonstrated by the simulation results that a p-GaN (50 nm)/In0.05Ga0.95N (150 nm) heterojunction can make a 25% and 10% increment of hole and electron concentration in the active region, respectively, finally resulting in a 55% improvement on the LED’s radiative recombination intensity. The simulation also reveals that the efficiency droop is alleviated from 32.9% to 21.7% at the current density of 100 A cm‑2. The enhanced hole injection is mainly attributed to the increased average background hole concentration of the area between the p-AlGaN electron blocking layer (EBL) to the p-GaN/InGaN heterojunction. The increasing potential barrier of the conduction band, resulting from the introduction of p-GaN/InGaN heterojunction, would also weaken electron leakage and is favorable to the LED’s luminous performance. The experimental results show that the wall-plug efficiency (WPE) of the p-GaN/InGaN LED increases by 26.0% at the injection current of 75 mA, in spite of the increasing electric resistance, which impairs the improvement of the LED’s performance from the enhanced hole injection. The structure of the p-GaN/InGaN heterojunction is novel in the field of p-type region design, and is a simple but effective way to promote the LED’s performance, which is very promising for application in further high-performance LED fabrication.
Image enhancement based on edge boosting algorithm
NASA Astrophysics Data System (ADS)
Ngernplubpla, Jaturon; Chitsobhuk, Orachat
2015-12-01
In this paper, a technique for image enhancement based on proposed edge boosting algorithm to reconstruct high quality image from a single low resolution image is described. The difficulty in single-image super-resolution is that the generic image priors resided in the low resolution input image may not be sufficient to generate the effective solutions. In order to achieve a success in super-resolution reconstruction, efficient prior knowledge should be estimated. The statistics of gradient priors in terms of priority map based on separable gradient estimation, maximum likelihood edge estimation, and local variance are introduced. The proposed edge boosting algorithm takes advantages of these gradient statistics to select the appropriate enhancement weights. The larger weights are applied to the higher frequency details while the low frequency details are smoothed. From the experimental results, the significant performance improvement quantitatively and perceptually is illustrated. It can be seen that the proposed edge boosting algorithm demonstrates high quality results with fewer artifacts, sharper edges, superior texture areas, and finer detail with low noise.
Schwarz-Based Algorithms for Compressible Flows
NASA Technical Reports Server (NTRS)
Tidriri, M. D.
1996-01-01
We investigate in this paper the application of Schwarz-based algorithms to compressible flows. First we study the combination of these methods with defect-correction procedures. We then study the effect on the Schwarz-based methods of replacing the explicit treatment of the boundary conditions by an implicit one. In the last part of this paper we study the combination of these methods with Newton-Krylov matrix-free methods. Numerical experiments that show the performance of our approaches are then presented.
Utilizing knowledge-base semantics in graph-based algorithms
Darwiche, A.
1996-12-31
Graph-based algorithms convert a knowledge base with a graph structure into one with a tree structure (a join-tree) and then apply tree-inference on the result. Nodes in the join-tree are cliques of variables and tree-inference is exponential in w*, the size of the maximal clique in the join-tree. A central property of join-trees that validates tree-inference is the running-intersection property: the intersection of any two cliques must belong to every clique on the path between them. We present two key results in connection to graph-based algorithms. First, we show that the running-intersection property, although sufficient, is not necessary for validating tree-inference. We present a weaker property for this purpose, called running-interaction, that depends on non-structural (semantical) properties of a knowledge base. We also present a linear algorithm that may reduce w* of a join-tree, possibly destroying its running-intersection property, while maintaining its running-interaction property and, hence, its validity for tree-inference. Second, we develop a simple algorithm for generating trees satisfying the running-interaction property. The algorithm bypasses triangulation (the standard technique for constructing join-trees) and does not construct a join-tree first. We show that the proposed algorithm may in some cases generate trees that are more efficient than those generated by modifying a join-tree.
Investigation of InGaN/GaN laser degradation based on luminescence properties
NASA Astrophysics Data System (ADS)
Wen, Pengyan; Zhang, Shuming; Liu, Jianping; Li, Deyao; Zhang, Liqun; Sun, Qian; Tian, Aiqin; Zhou, Kun; Zhou, Taofei; Yang, Hui
2016-06-01
Degradation of InGaN/GaN laser diode (LD) is investigated based on the luminescence properties. Gradual degradation of the LD is presented with the threshold current increase and the slope efficiency decrease. The cathodoluminescence and photoluminescence characterizations of the LD show a dislocation independent degradation of the active region under the ridge. Detailed studies on the temperature-dependent micro-photoluminescence and the electroluminescence indicate that the degradation of the LD is attributed to the generation of non-radiative recombination centers in the local multiple quantum well regions with lower indium content. The activation energy of the non-radiative recombination centers is about 10.2 meV.
NASA Astrophysics Data System (ADS)
Zadeh, Daryoush H.; Tanabe, Shinichi; Watanabe, Noriyuki; Matsuzaki, Hideaki
2016-05-01
The ohmic properties of Ti/Al/Mo/Au contacts on a high-quality AlGaN/GaN heterostructure epitaxially grown on a GaN substrate were investigated. Systematic structural and electrical analyses of the metal/AlGaN interface after annealing in N2 at 700 and 900 °C were conducted. After annealing at 900 °C, a new Al-rich interlayer with nitrogen vacancies was formed at the metal/AlGaN interface. Ohmic contacts with a low specific contact resistance (ρc) of 5.1 × 10‑6 Ω cm2 and a dominant field emission carrier transport mechanism were achieved. The fabrication of recessed-AlGaN-structured ohmic contact with ρc as low as 2.4 × 10‑5 Ω cm2 at a low annealing temperature of 650 °C, was also successfully demonstrated. This result indicates that a process methodology can be provided for fabricating low-resistivity ohmic contacts with a low thermal budget on a high-quality AlGaN/GaN structure, which is based on an appropriate control of the metal/AlGaN interface and AlGaN thickness rather than relying on the existence of threading dislocations.
Yasuda, H. 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.
Automated DNA Base Pair Calling Algorithm
Energy Science and Technology Software Center (ESTSC)
1999-07-07
The procedure solves the problem of calling the DNA base pair sequence from two channel electropherogram separations in an automated fashion. The core of the program involves a peak picking algorithm based upon first, second, and third derivative spectra for each electropherogram channel, signal levels as a function of time, peak spacing, base pair signal to noise sequence patterns, frequency vs ratio of the two channel histograms, and confidence levels generated during the run. Themore » ratios of the two channels at peak centers can be used to accurately and reproducibly determine the base pair sequence. A further enhancement is a novel Gaussian deconvolution used to determine the peak heights used in generating the ratio.« less
NASA Astrophysics Data System (ADS)
Zhang, XiaoLi; Liang, DaKai; Zeng, Jie; Asundi, Anand
2012-02-01
Structural Health Monitoring (SHM) based on fiber Bragg grating (FBG) sensor network has attracted considerable attention in recent years. However, FBG sensor network is embedded or glued in the structure simply with series or parallel. In this case, if optic fiber sensors or fiber nodes fail, the fiber sensors cannot be sensed behind the failure point. Therefore, for improving the survivability of the FBG-based sensor system in the SHM, it is necessary to build high reliability FBG sensor network for the SHM engineering application. In this study, a model reconstruction soft computing recognition algorithm based on genetic algorithm-support vector regression (GA-SVR) is proposed to achieve the reliability of the FBG-based sensor system. Furthermore, an 8-point FBG sensor system is experimented in an aircraft wing box. The external loading damage position prediction is an important subject for SHM system; as an example, different failure modes are selected to demonstrate the SHM system's survivability of the FBG-based sensor network. Simultaneously, the results are compared with the non-reconstruct model based on GA-SVR in each failure mode. Results show that the proposed model reconstruction algorithm based on GA-SVR can still keep the predicting precision when partial sensors failure in the SHM system; thus a highly reliable sensor network for the SHM system is facilitated without introducing extra component and noise.
Biosensors based on GaN nanoring optical cavities
NASA Astrophysics Data System (ADS)
Kouno, Tetsuya; Takeshima, Hoshi; Kishino, Katsumi; Sakai, Masaru; Hara, Kazuhiko
2016-05-01
Biosensors based on GaN nanoring optical cavities were demonstrated using room-temperature photoluminescence measurements. The outer diameter, height, and thickness of the GaN nanorings were approximately 750–800, 900, and 130–180 nm, respectively. The nanorings functioned as whispering-gallery-mode (WGM)-type optical cavities and exhibited sharp resonant peaks like lasing actions. The evanescent component of the WGM was strongly affected by the refractive index of the ambient environment, the type of liquid, and the sucrose concentration of the analyzed solution, resulting in shifts of the resonant wavelengths. The results indicate that the GaN nanorings can potentially be used in sugar sensors of the biosensors.
GaAs-based high temperature electrically pumped polariton laser
Baten, Md Zunaid; Bhattacharya, Pallab Frost, Thomas; Deshpande, Saniya; Das, Ayan; Lubyshev, Dimitri; Fastenau, Joel M.; Liu, Amy W. K.
2014-06-09
Strong coupling effects and polariton lasing are observed at 155 K with an edge-emitting GaAs-based microcavity diode with a single Al{sub 0.31}Ga{sub 0.69}As/Al{sub 0.41}Ga{sub 0.59}As quantum well as the emitter. The threshold for polariton lasing is observed at 90 A/cm{sup 2}, accompanied by a reduction of the emission linewidth to 0.85 meV and a blueshift of the emission wavelength by 0.89 meV. Polariton lasing is confirmed by the observation of a polariton population redistribution in momentum space and spatial coherence. Conventional photon lasing is recorded in the same device at higher pump powers.
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.
Differential Search Algorithm Based Edge Detection
NASA Astrophysics Data System (ADS)
Gunen, M. A.; Civicioglu, P.; Beşdok, E.
2016-06-01
In this paper, a new method has been presented for the extraction of edge information by using Differential Search Optimization Algorithm. The proposed method is based on using a new heuristic image thresholding method for edge detection. The success of the proposed method has been examined on fusion of two remote sensed images. The applicability of the proposed method on edge detection and image fusion problems have been analysed in detail and the empirical results exposed that the proposed method is useful for solving the mentioned problems.
Binary image authentication based on watermarking algorithm
NASA Astrophysics Data System (ADS)
Masoodifar, Behrang; Hashemi, S. Mojtaba; Zarei, Omid
2011-06-01
A digital image watermark embedding and extracting algorithm is presented based on the Finite Ridgelet Transform (FRT) which can efficiently represent image with linear singularities. In general RT also has directional sensitivity so that among the transformed coefficients the most significant one represents the most energetic direction of straight edges in an image. In this paper effect of RT is compared with wavelet transform in watermarking application. Different noises with different PSNR are added into the watermarked image in the experiments and the results are of robustness and transparency.
A novel method for non-destructive Compton scatter imaging based on the genetic algorithm
NASA Astrophysics Data System (ADS)
Ashrafi, Saleh; Jahanbakhsh, Okhtay; Alizadeh, Davood; Salehpour, Behrooz
2013-05-01
Compton scattering tomography is widely used in numerous applications such as biomedical imaging, nondestructive industrial testing and environmental survey, etc. This paper proposes the use of the genetic algorithm (GA), which utilizes bio-inspired mathematical models, to construct an image of the insides of a test object via the scattered photons, from a voxel within the object. A NaI(Tl) scintillation detector and a 185 MBq 137Cs gamma ray source were used in the experimental measurements. The obtained results show that the proposed GA based method performs well in constructing images of objects.
Optimization of lamp arrangement in a closed-conduit UV reactor based on a genetic algorithm.
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. PMID:27191576
NASA Astrophysics Data System (ADS)
Jia, Chuanyu; Yu, Tongjun; Feng, Xiaohui; Wang, Kun; Zhang, Guoyi
2016-09-01
The carrier confinement effect and piezoelectric field-induced quantum-confined stark effect of different GaN-based near-UV LED samples from 395 nm to 410 nm emission peak wavelength were investigated theoretically and experimentally. It is found that near-UV LEDs with InGaN/AlGaN multiple quantum wells (MQWs) active region have higher output power than those with InGaN/GaN MQWs for better carrier confinement effect. However, as emission peak wavelength is longer than 406 nm, the output power of the near-UV LEDs with AlGaN barrier is lower than that of the LEDs with GaN barrier due to more serious spatial separation of electrons and holes induced by the increase of piezoelectric field. The N-doped InGaN/AlGaN superlattices (SLs) were adopted as a strain relief layer (SRL) between n-GaN and MQWs in order to suppress the polarization field. It is demonstrated the output power of near-UV LEDs is increased obviously by using SLs SRL and AlGaN barrier for the discussed emission wavelength range. Besides, the forward voltage of near-UV LEDs with InGaN/AlGaN SLs SRL is lower than that of near-UV LEDs without SRL.
Method of plasma etching Ga-based compound semiconductors
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.
Fault diagnosis using noise modeling and a new artificial immune system based algorithm
NASA Astrophysics Data System (ADS)
Abbasi, Farshid; Mojtahedi, Alireza; Ettefagh, Mir Mohammad
2015-12-01
A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.
A swarm intelligence based memetic algorithm for task allocation in distributed systems
NASA Astrophysics Data System (ADS)
Sarvizadeh, Raheleh; Haghi Kashani, Mostafa
2011-12-01
This paper proposes a Swarm Intelligence based Memetic algorithm for Task Allocation and scheduling in distributed systems. The tasks scheduling in distributed systems is known as an NP-complete problem. Hence, many genetic algorithms have been proposed for searching optimal solutions from entire solution space. However, these existing approaches are going to scan the entire solution space without considering the techniques that can reduce the complexity of the optimization. Spending too much time for doing scheduling is considered the main shortcoming of these approaches. Therefore, in this paper memetic algorithm has been used to cope with this shortcoming. With regard to load balancing efficiently, Bee Colony Optimization (BCO) has been applied as local search in the proposed memetic algorithm. Extended experimental results demonstrated that the proposed method outperformed the existing GA-based method in terms of CPU utilization.
A swarm intelligence based memetic algorithm for task allocation in distributed systems
NASA Astrophysics Data System (ADS)
Sarvizadeh, Raheleh; Haghi Kashani, Mostafa
2012-01-01
This paper proposes a Swarm Intelligence based Memetic algorithm for Task Allocation and scheduling in distributed systems. The tasks scheduling in distributed systems is known as an NP-complete problem. Hence, many genetic algorithms have been proposed for searching optimal solutions from entire solution space. However, these existing approaches are going to scan the entire solution space without considering the techniques that can reduce the complexity of the optimization. Spending too much time for doing scheduling is considered the main shortcoming of these approaches. Therefore, in this paper memetic algorithm has been used to cope with this shortcoming. With regard to load balancing efficiently, Bee Colony Optimization (BCO) has been applied as local search in the proposed memetic algorithm. Extended experimental results demonstrated that the proposed method outperformed the existing GA-based method in terms of CPU utilization.
NASA Astrophysics Data System (ADS)
Radosavljević, S.; Radovanović, J.; Milanović, V.; Tomić, S.
2014-07-01
We have described a method for structural parameters optimization of GaN/AlGaN multiple quantum well based up-converter for silicon solar cells. It involves a systematic tuning of individual step quantum wells by use of the genetic algorithm for global optimization. In quantum well structures, the up-conversion process can be achieved by utilizing nonlinear optical effects based on intersubband transitions. Both single and double step quantum wells have been tested in order to maximize the second order susceptibility derived from the density matrix formalism. The results obtained for single step wells proved slightly better and have been further pursued to obtain a more complex design, optimized for conversion of an entire range of incident photon energies.
Radosavljević, S.; Radovanović, J. Milanović, V.; Tomić, S.
2014-07-21
We have described a method for structural parameters optimization of GaN/AlGaN multiple quantum well based up-converter for silicon solar cells. It involves a systematic tuning of individual step quantum wells by use of the genetic algorithm for global optimization. In quantum well structures, the up-conversion process can be achieved by utilizing nonlinear optical effects based on intersubband transitions. Both single and double step quantum wells have been tested in order to maximize the second order susceptibility derived from the density matrix formalism. The results obtained for single step wells proved slightly better and have been further pursued to obtain a more complex design, optimized for conversion of an entire range of incident photon energies.
PDE Based Algorithms for Smooth Watersheds.
Hodneland, Erlend; Tai, Xue-Cheng; Kalisch, Henrik
2016-04-01
Watershed segmentation is useful for a number of image segmentation problems with a wide range of practical applications. Traditionally, the tracking of the immersion front is done by applying a fast sorting algorithm. In this work, we explore a continuous approach based on a geometric description of the immersion front which gives rise to a partial differential equation. The main advantage of using a partial differential equation to track the immersion front is that the method becomes versatile and may easily be stabilized by introducing regularization terms. Coupling the geometric approach with a proper "merging strategy" creates a robust algorithm which minimizes over- and under-segmentation even without predefined markers. Since reliable markers defined prior to segmentation can be difficult to construct automatically for various reasons, being able to treat marker-free situations is a major advantage of the proposed method over earlier watershed formulations. The motivation for the methods developed in this paper is taken from high-throughput screening of cells. A fully automated segmentation of single cells enables the extraction of cell properties from large data sets, which can provide substantial insight into a biological model system. Applying smoothing to the boundaries can improve the accuracy in many image analysis tasks requiring a precise delineation of the plasma membrane of the cell. The proposed segmentation method is applied to real images containing fluorescently labeled cells, and the experimental results show that our implementation is robust and reliable for a variety of challenging segmentation tasks. PMID:26625408
Speech Enhancement based on Compressive Sensing Algorithm
NASA Astrophysics Data System (ADS)
Sulong, Amart; Gunawan, Teddy S.; Khalifa, Othman O.; Chebil, Jalel
2013-12-01
There are various methods, in performance of speech enhancement, have been proposed over the years. The accurate method for the speech enhancement design mainly focuses on quality and intelligibility. The method proposed with high performance level. A novel speech enhancement by using compressive sensing (CS) is a new paradigm of acquiring signals, fundamentally different from uniform rate digitization followed by compression, often used for transmission or storage. Using CS can reduce the number of degrees of freedom of a sparse/compressible signal by permitting only certain configurations of the large and zero/small coefficients, and structured sparsity models. Therefore, CS is significantly provides a way of reconstructing a compressed version of the speech in the original signal by taking only a small amount of linear and non-adaptive measurement. The performance of overall algorithms will be evaluated based on the speech quality by optimise using informal listening test and Perceptual Evaluation of Speech Quality (PESQ). Experimental results show that the CS algorithm perform very well in a wide range of speech test and being significantly given good performance for speech enhancement method with better noise suppression ability over conventional approaches without obvious degradation of speech quality.
Double Motor Coordinated Control Based on Hybrid Genetic Algorithm and CMAC
NASA Astrophysics Data System (ADS)
Cao, Shaozhong; Tu, Ji
A novel hybrid cerebellar model articulation controller (CMAC) and online adaptive genetic algorithm (GA) controller is introduced to control two Brushless DC motor (BLDCM) which applied in a biped robot. Genetic Algorithm simulates the random learning among the individuals of a group, and CMAC simulates the self-learning of an individual. To validate the ability and superiority of the novel algorithm, experiments have been done in MATLAB/SIMULINK. Analysis among GA, hybrid GA-CMAC and CMAC feed-forward control is also given. The results prove that the torque ripple of the coordinated control system is eliminated by using the hybrid GA-CMAC algorithm.
NASA Astrophysics Data System (ADS)
Wu, Qiong; Wang, Jihua; Wang, Cheng; Xu, Tongyu
2016-09-01
Genetic algorithm (GA) has a significant effect in the band optimization selection of Partial Least Squares (PLS) correction model. Application of genetic algorithm in selection of characteristic bands can achieve the optimal solution more rapidly, effectively improve measurement accuracy and reduce variables used for modeling. In this study, genetic algorithm as a module conducted band selection for the application of hyperspectral imaging in nondestructive testing of corn seedling leaves, and GA-PLS model was established. In addition, PLS quantitative model of full spectrum and experienced-spectrum region were established in order to suggest the feasibility of genetic algorithm optimizing wave bands, and model robustness was evaluated. There were 12 characteristic bands selected by genetic algorithm. With reflectance values of corn seedling component information at spectral characteristic wavelengths corresponding to 12 characteristic bands as variables, a model about SPAD values of corn leaves acquired was established by PLS, and modeling results showed r = 0.7825. The model results were better than those of PLS model established in full spectrum and experience-based selected bands. The results suggested that genetic algorithm can be used for data optimization and screening before establishing the corn seedling component information model by PLS method and effectively increase measurement accuracy and greatly reduce variables used for modeling.
Method of plasma etching GA-based compound semiconductors
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.
A Support Vector Machine Blind Equalization Algorithm Based on Immune Clone Algorithm
NASA Astrophysics Data System (ADS)
Yecai, Guo; Rui, Ding
Aiming at affecting of the parameter selection method of support vector machine(SVM) on its application in blind equalization algorithm, a SVM constant modulus blind equalization algorithm based on immune clone selection algorithm(CSA-SVM-CMA) is proposed. In this proposed algorithm, the immune clone algorithm is used to optimize the parameters of the SVM on the basis advantages of its preventing evolutionary precocious, avoiding local optimum, and fast convergence. The proposed algorithm can improve the parameter selection efficiency of SVM constant modulus blind equalization algorithm(SVM-CMA) and overcome the defect of the artificial setting parameters. Accordingly, the CSA-SVM-CMA has faster convergence rate and smaller mean square error than the SVM-CMA. Computer simulations in underwater acoustic channels have proved the validity of the algorithm.
Comparison of cone beam artifacts reduction: two pass algorithm vs TV-based CS algorithm
NASA Astrophysics Data System (ADS)
Choi, Shinkook; Baek, Jongduk
2015-03-01
In a cone beam computed tomography (CBCT), the severity of the cone beam artifacts is increased as the cone angle increases. To reduce the cone beam artifacts, several modified FDK algorithms and compressed sensing based iterative algorithms have been proposed. In this paper, we used two pass algorithm and Gradient-Projection-Barzilai-Borwein (GPBB) algorithm to reduce the cone beam artifacts, and compared their performance using structural similarity (SSIM) index. In two pass algorithm, it is assumed that the cone beam artifacts are mainly caused by extreme-density(ED) objects, and therefore the algorithm reproduces the cone beam artifacts(i.e., error image) produced by ED objects, and then subtract it from the original image. GPBB algorithm is a compressed sensing based iterative algorithm which minimizes an energy function for calculating the gradient projection with the step size determined by the Barzilai- Borwein formulation, therefore it can estimate missing data caused by the cone beam artifacts. To evaluate the performance of two algorithms, we used testing objects consisting of 7 ellipsoids separated along the z direction and cone beam artifacts were generated using 30 degree cone angle. Even though the FDK algorithm produced severe cone beam artifacts with a large cone angle, two pass algorithm reduced the cone beam artifacts with small residual errors caused by inaccuracy of ED objects. In contrast, GPBB algorithm completely removed the cone beam artifacts and restored the original shape of the objects.
Cranial-base surgery: a reconstructive algorithm.
Georgantopoulou, A; Hodgkinson, P D; Gerber, C J
2003-01-01
Skull-base surgery is associated with a high risk of cerebrospinal fluid (CSF) leak, infection, and functional and aesthetic deformity. Appropriate reconstruction of cranial-base defects following surgery helps to prevent these complications. Between March 1998 and May 2000, 28 patients (age: 1-68 years) underwent reconstruction of the anterior and middle cranial fossae. The indications for surgery were tumours, trauma involving the anterior cranial fossa, midline dermoid cysts with intracranial extension, late post-traumatic CSF leak, craniofacial deformity and recurrent frontal mucocoele. We used local anteriorly based pericranial flaps (23 flaps, alone or in combination with other flaps), bipedicled galeal flaps (seven patients) and free flaps (nine patients; radial forearm fascial/fasciocutaneous flaps, rectus abdominis muscle flap and latissimus dorsi muscle flap). Follow-up has been 4-24 months. We had no deaths, no flap failure and no incidence of infection. Complications included two CSF leaks, three intracranial haematomas and one pulsatile enophthalmos. All patients had a very good aesthetic result. We present an algorithm for skull-base reconstruction and comment on the design and vascularity of the bipedicled galeal flap. The monitoring of intracranial flaps and the difficulties of perioperative management of free flaps in neurosurgical patients are also discussed. PMID:12706142
NASA Astrophysics Data System (ADS)
Lao, Y. F.; Perera, A. G. U.; Wang, H. L.; Zhao, J. H.; Jin, Y. J.; Zhang, D. H.
2016-03-01
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 Δ0, which is the split-off gap between the HH and SO bands) creates a sharp drop around 3.6 μm 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 Δ0 is observable in p-type InGaAs and GaAsSb, while GaMnAs displays enhanced absorption without degradation around Δ0. 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.
Genetic algorithm-based neural fuzzy decision tree for mixed scheduling in ATM networks.
Lin, Chin-Teng; Chung, I-Fang; Pu, Her-Chang; Lee', Tsern-Huei; Chang, Jyh-Yeong
2002-01-01
Future broadband integrated services networks based on asynchronous transfer mode (ATM) technology are expected to support multiple types of multimedia information with diverse statistical characteristics and quality of service (QoS) requirements. To meet these requirements, efficient scheduling methods are important for traffic control in ATM networks. Among general scheduling schemes, the rate monotonic algorithm is simple enough to be used in high-speed networks, but does not attain the high system utilization of the deadline driven algorithm. However, the deadline driven scheme is computationally complex and hard to implement in hardware. The mixed scheduling algorithm is a combination of the rate monotonic algorithm and the deadline driven algorithm; thus it can provide most of the benefits of these two algorithms. In this paper, we use the mixed scheduling algorithm to achieve high system utilization under the hardware constraint. Because there is no analytic method for schedulability testing of mixed scheduling, we propose a genetic algorithm-based neural fuzzy decision tree (GANFDT) to realize it in a real-time environment. The GANFDT combines a GA and a neural fuzzy network into a binary classification tree. This approach also exploits the power of the classification tree. Simulation results show that the GANFDT provides an efficient way of carrying out mixed scheduling in ATM networks. PMID:18244889
Positive temperature coefficient of photovoltaic efficiency in solar cells based on InGaN/GaN MQWs
NASA Astrophysics Data System (ADS)
Chen, Zhaoying; Zheng, Xiantong; Li, Zhilong; Wang, Ping; Rong, Xin; Wang, Tao; Yang, Xuelin; Xu, Fujun; Qin, Zhixin; Ge, Weikun; Shen, Bo; Wang, Xinqiang
2016-08-01
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.
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.
An, Jianfei; Song, Kezhu; Zhang, Shuangxi; Yang, Junfeng; Cao, Ping
2014-01-01
An improved method based on a genetic algorithm (GA) is developed to design a broadband electrical impedance matching network for piezoelectric ultrasound transducer. A key feature of the new method is that it can optimize both the topology of the matching network and perform optimization on the components. The main idea of this method is to find the optimal matching network in a set of candidate topologies. Some successful experiences of classical algorithms are absorbed to limit the size of the set of candidate topologies and greatly simplify the calculation process. Both binary-coded GA and real-coded GA are used for topology optimization and components optimization, respectively. Some calculation strategies, such as elitist strategy and clearing niche method, are adopted to make sure that the algorithm can converge to the global optimal result. Simulation and experimental results prove that matching networks with better performance might be achieved by this improved method. PMID:24743156
Electrical properties of GaN-based heterostructures adopting InAlN/AlGaN bilayer barriers
NASA Astrophysics Data System (ADS)
Xu, Z. Y.; Xu, F. J.; Huang, C. C.; Wang, J. M.; Zhang, X.; Yang, Z. J.; Wang, X. Q.; Shen, B.
2016-08-01
Electrical properties of GaN-based heterostructures adopting InAlN/AlGaN bilayer barriers are investigated by Hall-effect and current-voltage measurements. It is found that this structure possesses both merits of high two-dimensional electron gas (2DEG) density and low gate leakage current density, while maintaining high 2DEG mobility. Furthermore, temperature dependence of the 2DEG density in this structure is verified to follow a combined tendency of InAlN/GaN (increase) and AlGaN/GaN (decrease) heterostructures with increasing temperature from 90 K to 400 K, which is mainly caused by superposition of the effects from carrier thermal activation induced by extrinsic factors in InAlN layer and the reduced conduction-band discontinuity.
A Collaborative Recommend Algorithm Based on Bipartite Community
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
A New Aloha Anti-Collision Algorithm Based on CDMA
NASA Astrophysics Data System (ADS)
Bai, Enjian; Feng, Zhu
The tags' collision is a common problem in RFID (radio frequency identification) system. The problem has affected the integrity of the data transmission during the process of communication in the RFID system. Based on analysis of the existing anti-collision algorithm, a novel anti-collision algorithm is presented. The new algorithm combines the group dynamic frame slotted Aloha algorithm with code division multiple access technology. The algorithm can effectively reduce the collision probability between tags. Under the same number of tags, the algorithm is effective in reducing the reader recognition time and improve overall system throughput rate.
A new frame-based registration algorithm.
Yan, C H; Whalen, R T; Beaupre, G S; Sumanaweera, T S; Yen, S Y; Napel, S
1998-01-01
This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required. PMID:9472834
A new frame-based registration algorithm
NASA Technical Reports Server (NTRS)
Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Sumanaweera, T. S.; Yen, S. Y.; Napel, S.
1998-01-01
This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required.
A genetic algorithm based method for docking flexible molecules
Judson, R.S.; Jaeger, E.P.; Treasurywala, A.M.
1993-11-01
The authors describe a computational method for docking flexible molecules into protein binding sites. The method uses a genetic algorithm (GA) to search the combined conformation/orientation space of the molecule to find low energy conformation. Several techniques are described that increase the efficiency of the basic search method. These include the use of several interacting GA subpopulations or niches; the use of a growing algorithm that initially docks only a small part of the molecule; and the use of gradient minimization during the search. To illustrate the method, they dock Cbz-GlyP-Leu-Leu (ZGLL) into thermolysin. This system was chosen because a well refined crystal structure is available and because another docking method had previously been tested on this system. Their method is able to find conformations that lie physically close to and in some cases lower in energy than the crystal conformation in reasonable periods of time on readily available hardware.
Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.
Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar
2015-01-01
Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed. PMID:25972896
Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering
Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar
2015-01-01
Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed. PMID:25972896
Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven
2010-05-01
Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.
Comparison of neuron selection algorithms of wavelet-based neural network
NASA Astrophysics Data System (ADS)
Mei, Xiaodan; Sun, Sheng-He
2001-09-01
Wavelet networks have increasingly received considerable attention in various fields such as signal processing, pattern recognition, robotics and automatic control. Recently people are interested in employing wavelet functions as activation functions and have obtained some satisfying results in approximating and localizing signals. However, the function estimation will become more and more complex with the growth of the input dimension. The hidden neurons contribute to minimize the approximation error, so it is important to study suitable algorithms for neuron selection. It is obvious that exhaustive search procedure is not satisfying when the number of neurons is large. The study in this paper focus on what type of selection algorithm has faster convergence speed and less error for signal approximation. Therefore, the Genetic algorithm and the Tabu Search algorithm are studied and compared by some experiments. This paper first presents the structure of the wavelet-based neural network, then introduces these two selection algorithms and discusses their properties and learning processes, and analyzes the experiments and results. We used two wavelet functions to test these two algorithms. The experiments show that the Tabu Search selection algorithm's performance is better than the Genetic selection algorithm, TSA has faster convergence rate than GA under the same stopping criterion.
Cordic based algorithms for software defined radio (SDR) baseband processing
NASA Astrophysics Data System (ADS)
Heyne, B.; Götze, J.
2006-09-01
This paper presents two Cordic based algorithms which may be used for digital baseband processing in OFDM and/or CDMA based communication systems. The first one is a linear least squares based multiuser detector for CDMA incorporating descrambling and despreading. The second algorithm is a pure Cordic based FFT implementation. Both algorithms can be implemented using solely Cordic based architectures (e.g. coprocessors or ASIPs). The algorithms exactly fit the needs of a multistandard terminal as they both are freely parameterizable. This regards to the accuracy of the results as well as to the parameters of the performed function (e.g. size of the FFT).
Photonic crystal based on anti-reflection structure for GaN/InGaN heterojunction solar cells
NASA Astrophysics Data System (ADS)
Ding, Wen; Xia, Deyang; Li, Qiang; Huang, Yaping; Zheng, Min; Zhang, Linzhao; Wang, Jin; Zhang, Ye; Guo, Maofeng; Liu, Shuo; Su, Xilin; Yun, Feng; Hou, Xun
2015-02-01
The III-V nitride material such as InGaN has many favorable physical properties including a wide direct band-gap (0.7- 3.4eV), high absorption coefficients (105 cm-1), and high radiation resistance. As such, InGaN has been chosen as an excellent material for full-solar-spectrum photovoltaic applications utilizing its wide and tunable band-gap. The refractive index of GaN is about 2.5 in the full-solar-spectrum. According to the Fresnel formula, there is a high reflection of ~18.4% as the sun light entering GaN. Anti-reflection films could be used on InGaN/GaN solar cell to decrease the reflection loss. The photonic crystal structure is a kind of anti-reflection based on the effective medium theory without any limitations, for example the mismatched thermal expansion coefficient. In this paper, we reported our research work on the design and fabrication of photonic crystal structure on the surface of GaN. FDTD Solutions is used to simulate the reflectivity on the surface of GaN with hexagonal close-packed pillar which has different period-a, diameter-d and height-h. When the parameters a is 500nm, d is 300nm, the reflectivity reached the lowest point of 4.18%. The self-assembly method was used to fabricate the photonic crystal structure on the GaN surface and the fabrication process was also researched. The photonic crystal structures on the surface of p-GaN were obtained and their characteristics of the antireflective film will be discussed in detail.
Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin
2016-01-01
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974
Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin
2016-01-01
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974
Electrical spin injection using GaCrN in a GaN based spin light emitting diode
Banerjee, D.; Ganguly, S.; Saha, D.; Adari, R.; Sankaranarayan, S.; Kumar, A.; Aldhaheri, R. W.; Hussain, M. A.; Balamesh, A. S.
2013-12-09
We have demonstrated electrical spin-injection from GaCrN dilute magnetic semiconductor (DMS) in a GaN-based spin light emitting diode (spin-LED). The remanent in-plane magnetization of the thin-film semiconducting ferromagnet has been used for introducing the spin polarized electrons into the non-magnetic InGaN quantum well. The output circular polarization obtained from the spin-LED closely follows the normalized in-plane magnetization curve of the DMS. A saturation circular polarization of ∼2.5% is obtained at 200 K.
GaAs-based triangular barrier photodiodes with embedded type-II GaSb quantum dots
NASA Astrophysics Data System (ADS)
Vitushinskiy, Pavel; Ohmori, Masato; Kuroda, Tomohiro; Noda, Takeshi; Kawazu, Takuya; Sakaki, Hiroyuki
2016-05-01
We fabricate GaAs-based triangular barrier photodiodes (TBPs), in which type-II GaSb quantum dots (QDs) are embedded in the vertex part of their triangular barriers. Their current–voltage characteristics and photo-responses are studied at low temperatures to show that GaSb QDs enhance the number and lifetime of photo-generated holes that are trapped by QDs in the barrier, resulting in the increase in the electron current around positively charged QDs. An extremely high responsivity of 109 A/W is achieved.
Microscopic, electrical and optical studies on InGaN/GaN quantum wells based LED devices
Mutta, Geeta Rani; Venturi, Giulia; Castaldini, Antonio; Cavallini, Anna
2014-02-21
We report here on the micro structural, electronic and optical properties of a GaN-based InGaN/GaN MQW LED grown by the MOVPE method. The present study shows that the threading dislocations present in these LED structures are terminated as V pits at the surface and have an impact on the electrical and optical activity of these devices. It has been pointed that these dislocations were of edge, screw and mixed types. EBIC maps suggest that the electrically active defects are screw and mixed dislocations and behave as nonradiative recombinant centres.
Waveguide effect of GaAsSb quantum wells in a laser structure based on GaAs
Aleshkin, V. Ya.; Afonenko, A. A.; Dikareva, N. V.; Dubinov, A. A. Kudryavtsev, K. E.; Morozov, S. V.; Nekorkin, S. M.
2013-11-15
The waveguide effect of GaAsSb quantum wells in a semiconductor-laser structure based on GaAs is studied theoretically and experimentally. It is shown that quantum wells themselves can be used as waveguide layers in the laser structure. As the excitation-power density attains a value of 2 kW/cm{sup 2} at liquid-nitrogen temperature, superluminescence at the wavelength corresponding to the optical transition in bulk GaAs (at 835 nm) is observed.
NASA Astrophysics Data System (ADS)
Kajitani, Ryo; Tanaka, Kenichiro; Ogawa, Masahiro; Ishida, Hidetoshi; Ishida, Masahiro; Ueda, Tetsuzo
2015-04-01
A GaN-based normally off heterostructure field effect transistor (HFET) with high current density and with a quaternary InAlGaN barrier instead of an AlGaN barrier is investigated. It is difficult to obtain both high-current operation and normally off operation in the GaN-based HFET because of the need to control the polarization-induced charge. In order to obtain a normally off operation using quaternary InAlGaN barrier, the InAlGaN barrier is selectively removed and the p-AlGaN layer is formed as the gate electrode. The obtained threshold voltage of the InAlGaN-based HFET is +1.1 V. The maximum drain current reaches as high as 0.73 A/mm, which is almost twice that of a conventional AlGaN-based normally off gate injection transistor (GIT).
Bicriteria Network Optimization Problem using Priority-based Genetic Algorithm
NASA Astrophysics Data System (ADS)
Gen, Mitsuo; Lin, Lin; Cheng, Runwei
Network optimization is being an increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. In many applications, however, there are several criteria associated with traversing each edge of a network. For example, cost and flow measures are both important in the networks. As a result, there has been recent interest in solving Bicriteria Network Optimization Problem. The Bicriteria Network Optimization Problem is known a NP-hard. The efficient set of paths may be very large, possibly exponential in size. Thus the computational effort required to solve it can increase exponentially with the problem size in the worst case. In this paper, we propose a genetic algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including maximum flow (MXF) model and minimum cost flow (MCF) model. The objective is to find the set of Pareto optimal solutions that give possible maximum flow with minimum cost. This paper also combines Adaptive Weight Approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. Computer simulations show the several numerical experiments by using some difficult-to-solve network design problems, and show the effectiveness of the proposed method.
Azimuthally isotropic irradiance of GaN-based light-emitting diodes with GaN microlens arrays.
Wu, Mount-Learn; Lee, Yun-Chih; Yang, Shih-Pu; Lee, Po-Shen; Chang, Jenq-Yang
2009-04-13
In this paper, the irradiance-modifying concept is proposed by introducing a microlens array on the p-GaN layer of GaN-based light-emitting diode (LED). Every microlens can locally modulate photons emitting from a micro-scaled active region of multiple quantum wells (MQWs) just beneath the microlens. The azimuthally isotropic irradiance from the GaN-based LED with microlens arrays is demonstrated numerically and experimentally. To realize such a novel LED, one-dimensional GaN microlens array with a period of 1.6 microm and a filling factor of 0.64 are fabricated by using dry etching. According to experimental results, the azimuthally isotropic light emission of proposed LED is observed. By using the angular-resolved photoluminescence, its intensity variation corresponding to the azimuth angles is as low as 10% within the angle region of +/-50 degrees. PMID:19365437
Laser diode bars based on strain-compensated AlGaPAs/GaAs heterostructures
Marmalyuk, Aleksandr A; Ladugin, M A; Yarotskaya, I V; Panarin, V A; Mikaelyan, G T
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 and 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.
A hybrid features based image matching algorithm
NASA Astrophysics Data System (ADS)
Tu, Zhenbiao; Lin, Tao; Sun, Xiao; Dou, Hao; Ming, Delie
2015-12-01
In this paper, we present a novel image matching method to find the correspondences between two sets of image interest points. The proposed method is based on a revised third-order tensor graph matching method, and introduces an energy function that takes four kinds of energy term into account. The third-order tensor method can hardly deal with the situation that the number of interest points is huge. To deal with this problem, we use a potential matching set and a vote mechanism to decompose the matching task into several sub-tasks. Moreover, the third-order tensor method sometimes could only find a local optimum solution. Thus we use a cluster method to divide the feature points into some groups and only sample feature triangles between different groups, which could make the algorithm to find the global optimum solution much easier. Experiments on different image databases could prove that our new method would obtain correct matching results with relatively high efficiency.
Combined string searching algorithm based on knuth-morris- pratt and boyer-moore algorithms
NASA Astrophysics Data System (ADS)
Tsarev, R. Yu; Chernigovskiy, A. S.; Tsareva, E. A.; Brezitskaya, V. V.; Nikiforov, A. Yu; Smirnov, N. A.
2016-04-01
The string searching task can be classified as a classic information processing task. Users either encounter the solution of this task while working with text processors or browsers, employing standard built-in tools, or this task is solved unseen by the users, while they are working with various computer programmes. Nowadays there are many algorithms for solving the string searching problem. The main criterion of these algorithms’ effectiveness is searching speed. The larger the shift of the pattern relative to the string in case of pattern and string characters’ mismatch is, the higher is the algorithm running speed. This article offers a combined algorithm, which has been developed on the basis of well-known Knuth-Morris-Pratt and Boyer-Moore string searching algorithms. These algorithms are based on two different basic principles of pattern matching. Knuth-Morris-Pratt algorithm is based upon forward pattern matching and Boyer-Moore is based upon backward pattern matching. Having united these two algorithms, the combined algorithm allows acquiring the larger shift in case of pattern and string characters’ mismatch. The article provides an example, which illustrates the results of Boyer-Moore and Knuth-Morris- Pratt algorithms and combined algorithm’s work and shows advantage of the latter in solving string searching problem.
CoPt ferromagnetic injector in light-emitting Schottky diodes based on InGaAs/GaAs nanostructures
Zdoroveyshchev, A. V. Dorokhin, M. V.; Demina, P. B.; Kudrin, A. V.; Vikhrova, O. V.; Ved’, M. V.; Danilov, Yu. A.; Erofeeva, I. V.; Krjukov, R. N.; Nikolichev, D. E.
2015-12-15
The possibility of fabricating a ferromagnetic injector based on a near-equiatomic CoPt alloy with pronounced perpendicular magnetization anisotropy in the InGaAs/GaAs spin light-emitting diode is shown. The physical properties of experimental spin light-emitting diode prototypes are comprehensively studied. Circularly polarized electroluminescence of fabricated diodes is obtained in zero magnetic field due to the remanent magnetization of CoPt layers.
An Innovative Thinking-Based Intelligent Information Fusion Algorithm
Hu, Liang; Liu, Gang; Zhou, Jin
2013-01-01
This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information. PMID:23956699
Vinokurov, D. A. Vasilyeva, V. V.; Kapitonov, V. A.; Lyutetskiy, A. V.; Nikolaev, D. N.; Pikhtin, N. A.; Slipchenko, S. O.; Stankevich, A. L.; Shamakhov, V. V.; Fetisova, N. V.; Tarasov, I. S.
2010-02-15
The effect of the active region thickness on the basic characteristics of high-power semiconductor lasers based on AlGaAs/GaAs/InGaAs asymmetric separate-confinement heterostructures grown by MOCVD epitaxy has been studied. It is shown that the threshold current, temperature sensitivity of the threshold current density, internal quantum efficiency of stimulated emission, and differential quantum efficiency are improved as the active region thickness increases. It is demonstrated that the maximum attainable optical emission power of a semiconductor laser and the internal quantum efficiency of photoluminescence are the most sensitive to defect formation in the heterostructure and become lower as the critical thickness of the strained In{sub x}Ga{sub 1-x} As layer in the active region is exceeded.
Liu, Zhaojun; Ma, Jun; Huang, Tongde; Liu, Chao; May Lau, Kei
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.
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. PMID:25685507
A simple algorithm to compute the peak power output of GaAs/Ge solar cells on the Martian surface
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 array 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.
Optical modulator based on GaAs photonic crystals
NASA Astrophysics Data System (ADS)
Li, Jiusheng
2005-11-01
In this letter, we propose a novel optical modulator based on GaAs photonic crystals and investigate its optically properties numerically by using the finite-difference time-domain method. The position of the cutoff frequency can be varied by free carriers injection, and the band gap shift can be observed. Band gap shift is used to modulate light. Bing several micrometers length, low insertion loss, and large extinction ratios, the modulator can be used in ultra-small and ultra-dense photonic integrated circuits.
Characterization of etched facets for GaN-based lasers
NASA Astrophysics Data System (ADS)
Scherer, M.; Schwegler, V.; Seyboth, M.; Eberhard, F.; Kirchner, C.; Kamp, M.; Ulu, G.; Ünlü, M. S.; Gruhler, R.; Hollricher, O.
2001-09-01
Dry-etching of laser facets is commonly used for (InAl)GaN/sapphire-based structures since the epitaxial planes of the nitride layers are rotated with respect to the substrate planes making cleaving impractical. To achieve steep and smooth facets by chemically assisted ion beam etching, a 3-layer resist system is developed for patterning. Characterization by scanning electron microscopy and atomic force microscopy shows facets with root-mean-square roughnesses of 7 nm and inclination angles of 2-4°. Optically pumped lasers yield low threshold excitation densities for fully doped separate confinement heterostructure lasers.
Review of radiation damage in GaN-based materials and devices
Pearton, Stephen J.; Deist, Richard; Ren, Fan; Liu, Lu; Polyakov, Alexander Y.; Kim, Jihyun
2013-09-15
A review of the effects of proton, neutron, γ-ray, and electron irradiation on GaN materials and devices is presented. Neutron irradiation tends to create disordered regions in the GaN, while the damage from the other forms of radiation is more typically point defects. In all cases, the damaged region contains carrier traps that reduce the mobility and conductivity of the GaN and at high enough doses, a significant degradation of device performance. GaN is several orders of magnitude more resistant to radiation damage than GaAs of similar doping concentrations. In terms of heterostructures, preliminary data suggests that the radiation hardness decreases in the order AlN/GaN > AlGaN/GaN > InAlN/GaN, consistent with the average bond strengths in the Al-based materials.
Tree-based shortest-path routing algorithm
NASA Astrophysics Data System (ADS)
Long, Y. H.; Ho, T. K.; Rad, A. B.; Lam, S. P. S.
1998-12-01
A tree-based shortest path routing algorithm is introduced in this paper. With this algorithm, every network node can maintain a shortest path routing tree topology of the network with itself as the root. In this algorithm, every node constructs its own routing tree based upon its neighbors' routing trees. Initially, the routing tree at each node has the root only, the node itself. As information exchanges, every node's routing tree will evolve until a complete tree is obtained. This algorithm is a trade-off between distance vector algorithm and link state algorithm. Loops are automatically deleted, so there is no count-to- infinity effect. A simple routing tree information storage approach and a protocol data until format to transmit the tree information are given. Some special issues, such as adaptation to topology change, implementation of the algorithm on LAN, convergence and computation overhead etc., are also discussed in the paper.
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.
Solving SAT Problem Based on Hybrid Differential Evolution Algorithm
NASA Astrophysics Data System (ADS)
Liu, Kunqi; Zhang, Jingmin; Liu, Gang; Kang, Lishan
Satisfiability (SAT) problem is an NP-complete problem. Based on the analysis about it, SAT problem is translated equally into an optimization problem on the minimum of objective function. A hybrid differential evolution algorithm is proposed to solve the Satisfiability problem. It makes full use of strong local search capacity of hill-climbing algorithm and strong global search capability of differential evolution algorithm, which makes up their disadvantages, improves the efficiency of algorithm and avoids the stagnation phenomenon. The experiment results show that the hybrid algorithm is efficient in solving SAT problem.
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.
Machine learning algorithms for damage detection: Kernel-based approaches
NASA Astrophysics Data System (ADS)
Santos, Adam; Figueiredo, Eloi; Silva, M. F. M.; Sales, C. S.; Costa, J. C. W. A.
2016-02-01
This paper presents four kernel-based algorithms for damage detection under varying operational and environmental conditions, namely based on one-class support vector machine, support vector data description, kernel principal component analysis and greedy kernel principal component analysis. Acceleration time-series from an array of accelerometers were obtained from a laboratory structure and used for performance comparison. The main contribution of this study is the applicability of the proposed algorithms for damage detection as well as the comparison of the classification performance between these algorithms and other four ones already considered as reliable approaches in the literature. All proposed algorithms revealed to have better classification performance than the previous ones.
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.
Raytracing Based upon the Sympletic Algorithm
NASA Astrophysics Data System (ADS)
Wang, Y.; Li, C.
2014-12-01
The raytracing is the basic problem in seismic imaging, and the reliability of the imaging depends on the accuracies both spatial trajectory and traveltime of the ray, and is using in seismology broadly. The seismic ray travels through the inhomogeneous media fallows the the eikonal equation, and the eikonal equation is an one order differential equation of traveltime, and satisfies the Hamilton System. In Cartesian coordinate system, we use a separable Hamilton System function. In this paper, the Sympletic algorithm method with bi-cubic convolution algorithm was used to solve the Hamilton System to deal with the raytracing problem. Compared with the Fsat Marching Method (FMM), The result shows that the Sympletic algorithm method (SAM) can keep the stability of the solution for the eikonal equation. Due to the use of the Sympletic algorithm, the method can produce a reliable seismic wavefront with an accurate ray trajectory (Fig.1). Meanwhile, the numerical modeling shows that the use of SAM can not only keep the stability of the Hamilton System with a fast computation but also improve the accuracy of the seismic ray tracing (Fig.2).
Function-Based Algorithms for Biological Sequences
ERIC Educational Resources Information Center
Mohanty, Pragyan Sheela P.
2015-01-01
Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…
GA-Based Computer-Aided Electromagnetic Design of Two-Phase SRM for Compressor Drives
NASA Astrophysics Data System (ADS)
Kano, Yoshiaki; Kosaka, Takashi; Matsui, Nobuyuki
This paper presents an approach to Genetic Algorithm (GA)-based computer-aided autonomous electromagnetic design of 2-phase Switched Reluctance Motor drives. The proposed drive is designed for compressor drives in low-priced refrigerators as an alternative to existing brushless DC motors drives with rare-earth magnets. In the proposed design approach, three GA loops work to optimize the lamination design so as to meet the requirements for the target application under the given constraints while simultaneously fine-tuning the control parameters. To achieve the design optimization within an acceptable CPU-time, the repeated-calculation required to obtain fitness evaluation in the proposed approach does not use FEM, but consists of geometric flux tube-based non-linear magnetic analysis and a dynamic simulator based on an analytical expression of the magnetizing curves obtained from the non-linear magnetic analysis. The design results show the proposed approach can autonomously find a feasible design solution of SRM drive for the target application from huge search space. The experimental studies using a 2-phase 8/6 prototype manufactured in accordance with the optimized design parameters show the validity of the proposed approach.
Adaptive image contrast enhancement algorithm for point-based rendering
NASA Astrophysics Data System (ADS)
Xu, Shaoping; Liu, Xiaoping P.
2015-03-01
Surgical simulation is a major application in computer graphics and virtual reality, and most of the existing work indicates that interactive real-time cutting simulation of soft tissue is a fundamental but challenging research problem in virtual surgery simulation systems. More specifically, it is difficult to achieve a fast enough graphic update rate (at least 30 Hz) on commodity PC hardware by utilizing traditional triangle-based rendering algorithms. In recent years, point-based rendering (PBR) has been shown to offer the potential to outperform the traditional triangle-based rendering in speed when it is applied to highly complex soft tissue cutting models. Nevertheless, the PBR algorithms are still limited in visual quality due to inherent contrast distortion. We propose an adaptive image contrast enhancement algorithm as a postprocessing module for PBR, providing high visual rendering quality as well as acceptable rendering efficiency. Our approach is based on a perceptible image quality technique with automatic parameter selection, resulting in a visual quality comparable to existing conventional PBR algorithms. Experimental results show that our adaptive image contrast enhancement algorithm produces encouraging results both visually and numerically compared to representative algorithms, and experiments conducted on the latest hardware demonstrate that the proposed PBR framework with the postprocessing module is superior to the conventional PBR algorithm and that the proposed contrast enhancement algorithm can be utilized in (or compatible with) various variants of the conventional PBR algorithm.
Conductivity based on selective etch for GaN devices and applications thereof
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.
Analysis of image thresholding segmentation algorithms based on swarm intelligence
NASA Astrophysics Data System (ADS)
Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo
2013-03-01
Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.
Advances on image interpolation based on ant colony algorithm.
Rukundo, Olivier; Cao, Hanqiang
2016-01-01
This paper presents an advance on image interpolation based on ant colony algorithm (AACA) for high resolution image scaling. The difference between the proposed algorithm and the previously proposed optimization of bilinear interpolation based on ant colony algorithm (OBACA) is that AACA uses global weighting, whereas OBACA uses local weighting scheme. The strength of the proposed global weighting of AACA algorithm depends on employing solely the pheromone matrix information present on any group of four adjacent pixels to decide which case deserves a maximum global weight value or not. Experimental results are further provided to show the higher performance of the proposed AACA algorithm with reference to the algorithms mentioned in this paper. PMID:27047729
Image processing with genetic algorithm in a raisin sorting system based on machine vision
NASA Astrophysics Data System (ADS)
Abbasgholipour, Mahdi; Alasti, Behzad Mohammadi; Abbasgholipour, Vahdi; Derakhshan, Ali; Abbasgholipour, Mohammad; Rahmatfam, Sharmin; Rahmatfam, Sheyda; Habibifar, Rahim
2012-04-01
This study was undertaken to develop machine vision-based raisin detection technology. Supervised color image segmentation using a Permutation-coded Genetic Algorithm (GA) identifying regions in Hue-Saturation-Intensity (HSI) color space (GAHSI) for desired and undesired raisin detection was successfully implemented. Images were captured to explore the possibility of using GAHSI to locate desired raisin and undesired raisin regions in color space simultaneously. In this research, images were processed separately using three segmentation method, K-Means clustering in L*a*b* color space and GAHSI for single image, GA for single image in Red-Green-Blue (RGB) color space (GARGB). The GAHSI results provided evidence for the existence and separability of such regions. When compared with cluster analysis-based segmentation results, the GAHSI method showed no significant difference.
Genetic algorithm based design optimization of a permanent magnet brushless dc motor
NASA Astrophysics Data System (ADS)
Upadhyay, P. R.; Rajagopal, K. R.
2005-05-01
Genetic algorithm (GA) based design optimization of a permanent magnet brushless dc motor is presented in this paper. A 70 W, 350 rpm, ceiling fan motor with radial-filed configuration is designed by considering the efficiency as the objective function. Temperature-rise and motor weight are the constraints and the slot electric loading, magnet-fraction, slot-fraction, airgap, and airgap flux density are the design variables. The efficiency and the phase-inductance of the motor designed using the developed CAD program are improved by using the GA based optimization technique; from 84.75% and 5.55 mH to 86.06% and 2.4 mH, respectively.
Enhanced light output power of InGaN-based amber LEDs by strain-compensating AlN/AlGaN barriers
NASA Astrophysics Data System (ADS)
Iida, Daisuke; Lu, Shen; Hirahara, Sota; Niwa, Kazumasa; Kamiyama, Satoshi; Ohkawa, Kazuhiro
2016-08-01
We investigated the effect of a combined AlN/Al0.03Ga0.97N barrier on InGaN-based amber light-emitting diodes (LEDs) grown by metalorganic vapor-phase epitaxy. InGaN-based multiple quantum wells with a combined AlN/Al0.03Ga0.97N barrier showed intense photoluminescence with a narrow full-width at half-maximum. The amber LEDs with a combined AlN/Al0.03Ga0.97N barrier achieved a light output power enhanced approximately 2.5-fold at 20 mA compared to that of the LED with a combined AlN/GaN barrier, owing to the reduction of defects in InGaN active layers. Thus, the efficiency of high-In-content InGaN-based LEDs can be improved in the spectrum range of amber.
Barzilai-Borwein method in graph drawing algorithm based on Kamada-Kawai algorithm
NASA Astrophysics Data System (ADS)
Hasal, Martin; Pospisil, Lukas; Nowakova, Jana
2016-06-01
Extension of Kamada-Kawai algorithm, which was designed for calculating layouts of simple undirected graphs, is presented in this paper. Graphs drawn by Kamada-Kawai algorithm exhibit symmetries, tend to produce aesthetically pleasing and crossing-free layouts for planar graphs. Minimization of Kamada-Kawai algorithm is based on Newton-Raphson method, which needs Hessian matrix of second derivatives of minimized node. Disadvantage of Kamada-Kawai embedder algorithm is computational requirements. This is caused by searching of minimal potential energy of the whole system, which is minimized node by node. The node with highest energy is minimized against all nodes till the local equilibrium state is reached. In this paper with Barzilai-Borwein (BB) minimization algorithm, which needs only gradient for minimum searching, instead of Newton-Raphson method, is worked. It significantly improves the computational time and requirements.
Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability
NASA Astrophysics Data System (ADS)
Titare, L. S.; Singh, P.; Arya, L. D.
2014-12-01
This paper presents an algorithm to calculate optimum load shedding with voltage stability consideration based on sensitivity of proximity indicator using genetic algorithm (GA). Schur's inequality based proximity indicator of load flow Jacobian has been selected, which indicates system state. Load flow Jacobian of the system is obtained using Continuation power flow method. If reactive power and active rescheduling are exhausted, load shedding is the last line of defense to maintain the operational security of the system. Load buses for load shedding have been selected on the basis of sensitivity of proximity indicator. The load bus having large sensitivity is selected for load shedding. Proposed algorithm predicts load bus rank and optimum load to be shed on load buses. The algorithm accounts inequality constraints not only in present operating conditions, but also for predicted next interval load (with load shedding). Developed algorithm has been implemented on IEEE 6-bus system. Results have been compared with those obtained using Teaching-Learning-Based Optimization (TLBO), particle swarm optimization (PSO) and its variant.
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.
Robust facial expression recognition algorithm based on local metric learning
NASA Astrophysics Data System (ADS)
Jiang, Bin; Jia, Kebin
2016-01-01
In facial expression recognition tasks, different facial expressions are often confused with each other. Motivated by the fact that a learned metric can significantly improve the accuracy of classification, a facial expression recognition algorithm based on local metric learning is proposed. First, k-nearest neighbors of the given testing sample are determined from the total training data. Second, chunklets are selected from the k-nearest neighbors. Finally, the optimal transformation matrix is computed by maximizing the total variance between different chunklets and minimizing the total variance of instances in the same chunklet. The proposed algorithm can find the suitable distance metric for every testing sample and improve the performance on facial expression recognition. Furthermore, the proposed algorithm can be used for vector-based and matrix-based facial expression recognition. Experimental results demonstrate that the proposed algorithm could achieve higher recognition rates and be more robust than baseline algorithms on the JAFFE, CK, and RaFD databases.
A vehicle detection algorithm based on deep belief network.
Wang, Hai; Cai, Yingfeng; Chen, Long
2014-01-01
Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications. In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN) is proposed. In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection. On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets. PMID:24959617
Identification of Traceability Barcode Based on Phase Correlation Algorithm
NASA Astrophysics Data System (ADS)
Lang, Liying; Zhang, Xiaofang
In the paper phase correlation algorithm based on Fourier transform is applied to the traceability barcode identification, which is a widely used method of image registration. And there is the rotation-invariant phase correlation algorithm which combines polar coordinate transform with phase correlation, that they can recognize the barcode with partly destroyed and rotated. The paper provides the analysis and simulation for the algorithm using Matlab, the results show that the algorithm has the advantages of good real-time and high performance. And it improves the matching precision and reduces the calculation by optimizing the rotation-invariant phase correlation.
Comparison of Beam-Based Alignment Algorithms for the ILC
Smith, J.C.; Gibbons, L.; Patterson, J.R.; Rubin, D.L.; Sagan, D.; Tenenbaum, P.; /SLAC
2006-03-15
The main linac of the International Linear Collider (ILC) requires more sophisticated alignment techniques than those provided by survey alone. Various Beam-Based Alignment (BBA) algorithms have been proposed to achieve the desired low emittance preservation. Dispersion Free Steering, Ballistic Alignment and the Kubo method are compared. Alignment algorithms are also tested in the presence of an Earth-like stray field.
A Danger-Theory-Based Immune Network Optimization Algorithm
Li, Tao; Xiao, Xin; Shi, Yuanquan
2013-01-01
Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times. PMID:23483853
Community detection based on modularity and an improved genetic algorithm
NASA Astrophysics Data System (ADS)
Shang, Ronghua; Bai, Jing; Jiao, Licheng; Jin, Chao
2013-03-01
Complex networks are widely applied in every aspect of human society, and community detection is a research hotspot in complex networks. Many algorithms use modularity as the objective function, which can simplify the algorithm. In this paper, a community detection method based on modularity and an improved genetic algorithm (MIGA) is put forward. MIGA takes the modularity Q as the objective function, which can simplify the algorithm, and uses prior information (the number of community structures), which makes the algorithm more targeted and improves the stability and accuracy of community detection. Meanwhile, MIGA takes the simulated annealing method as the local search method, which can improve the ability of local search by adjusting the parameters. Compared with the state-of-art algorithms, simulation results on computer-generated and four real-world networks reflect the effectiveness of MIGA.
Improved artificial bee colony algorithm based gravity matching navigation method.
Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang
2014-01-01
Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019
Fast parallel algorithm for slicing STL based on pipeline
NASA Astrophysics Data System (ADS)
Ma, Xulong; Lin, Feng; Yao, Bo
2016-04-01
In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.
Fast parallel algorithm for slicing STL based on pipeline
NASA Astrophysics Data System (ADS)
Ma, Xulong; Lin, Feng; Yao, Bo
2016-05-01
In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.
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.
A knowledge-based clustering algorithm driven by Gene Ontology.
Cheng, Jill; Cline, Melissa; Martin, John; Finkelstein, David; Awad, Tarif; Kulp, David; Siani-Rose, Michael A
2004-08-01
We have developed an algorithm for inferring the degree of similarity between genes by using the graph-based structure of Gene Ontology (GO). We applied this knowledge-based similarity metric to a clique-finding algorithm for detecting sets of related genes with biological classifications. We also combined it with an expression-based distance metric to produce a co-cluster analysis, which accentuates genes with both similar expression profiles and similar biological characteristics and identifies gene clusters that are more stable and biologically meaningful. These algorithms are demonstrated in the analysis of MPRO cell differentiation time series experiments. PMID:15468759
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.
Liquid phase sensors based on chemically functionalized GaAs/AlGaAs heterostructures
NASA Astrophysics Data System (ADS)
Luber, S. M.; Adlkofer, K.; Rant, U.; Ulman, A.; Gölzhäuser, A.; Grunze, M.; Schuh, D.; Tanaka, M.; Tornow, M.; Abstreiter, G.
2004-03-01
We report on surface-near two-dimensional electron gases in GaAs/AlGaAs heterostructures for application in potential chemical or biochemical sensors in liquid environment. GaAs cap layers of the heterostructures were coated with self-assembled monolayers of 4‧-substituted 4-mercaptobiphenyls (MBP), showing stable device performance in physiological (aqueous) buffers. Deposition of MBP with different 4‧-substituents led to systematic changes in the lateral resistance, which can be correlated to the electrical potential drop across the established surface dipole layers. Furthermore, the lateral resistance showed a clear dependency on organic solvents with different polarities, suggesting its high sensitivity to the polarity of physisorbed molecules.
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.
Ultra High p-doping Material Research for GaN Based Light Emitters
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 in 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 providing
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.
Tumuluru, J.S.; Sokhansanj, Shahabaddine
2008-12-01
Abstract In the present study, response surface method (RSM) and genetic algorithm (GA) were used to study the effects of process variables like screw speed, rpm (x1), L/D ratio (x2), barrel temperature ( C; x3), and feed mix moisture content (%; x4), on flow rate of biomass during single-screw extrusion cooking. A second-order regression equation was developed for flow rate in terms of the process variables. The significance of the process variables based on Pareto chart indicated that screw speed and feed mix moisture content had the most influence followed by L/D ratio and barrel temperature on the flow rate. RSM analysis indicated that a screw speed>80 rpm, L/D ratio> 12, barrel temperature>80 C, and feed mix moisture content>20% resulted in maximum flow rate. Increase in screw speed and L/D ratio increased the drag flow and also the path of traverse of the feed mix inside the extruder resulting in more shear. The presence of lipids of about 35% in the biomass feed mix might have induced a lubrication effect and has significantly influenced the flow rate. The second-order regression equations were further used as the objective function for optimization using genetic algorithm. A population of 100 and iterations of 100 have successfully led to convergence the optimum. The maximum and minimum flow rates obtained using GA were 13.19 10 7 m3/s (x1=139.08 rpm, x2=15.90, x3=99.56 C, and x4=59.72%) and 0.53 10 7 m3/s (x1=59.65 rpm, x2= 11.93, x3=68.98 C, and x4=20.04%).
Finite-sample based learning algorithms for feedforward networks
Rao, N.S.V.; Protopopescu, V.; Mann, R.C.; Oblow, E.M.; Iyengar, S.S.
1995-04-01
We discuss two classes of convergent algorithms for learning continuous functions (and also regression functions) that are represented by FeedForward Networks (FFN). The first class of algorithms, applicable to networks with unknown weights located only in the output layer, is obtained by utilizing the potential function methods of Aizerman et al. The second class, applicable to general feedforward networks, is obtained by utilizing the classical Robbins-Monro style stochastic approximation methods. Conditions relating the sample sizes to the error bounds are derived for both classes of algorithms using martingale-type inequalities. For concreteness, the discussion is presented in terms of neural networks, but the results are applicable to general feedforward networks, in particular to wavelet networks. The algorithms can also be directly applied to concept learning problems. A main distinguishing feature of the this work is that the sample sizes are based on explicit algorithms rather than information-based methods.
A Moment-Based Condensed History Algorithm
Tolar, D.R.; Larsen, E.W.
2000-06-15
''Condensed History'' algorithms are Monte Carlo models for electron transport problems, They describe the aggregate effect of multiple collisions that occur when an electron travels a path length s{sub 0}. This path length is the distance each Monte Carlo electron travels between Condensed History steps. Conventional Condensed History schemes employ a splitting routine over the range 0 {le} s {le} s{sub 0}. For example, the Random Hinge method splits each path length step into two substeps; one with length {xi}s{sub 0} and one with length (1-{xi})s{sub 0}, where {xi} is a random number from 0 < {xi} < 1. Here we develop a new Condensed History algorithm to improve the accuracy of electron transport simulations by preserving the mean position and the variance in the mean of electrons that have traveled a path length s and are traveling with the direction cosine {mu}. These means and variances are obtained from the zeroth-, first-, and second-order spatial moments of the Boltzmann transport equation. Hence, our method is a Monte Carlo application of the ''Method of Moments''.
CUDT: A CUDA Based Decision Tree Algorithm
Sheu, Ruey-Kai; Chiu, Chun-Chieh
2014-01-01
Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new technology help. In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture), which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. We have conducted many experiments to evaluate system performance of CUDT and made a comparison with traditional CPU version. The results show that CUDT is 5∼55 times faster than Weka-j48 and is 18 times speedup than SPRINT for large data set. PMID:25140346
Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis
May Permann
2007-03-01
Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.
Effects of p-type GaN thickness on optical properties of GaN-based light-emitting diodes
NASA Astrophysics Data System (ADS)
Xu, Ming-sheng; Zhang, Heng; Zhou, Quan-bin; Wang, Hong
2016-07-01
The influence of p-type GaN (pGaN) thickness on the light output power ( LOP) and internal quantum efficiency ( IQE) of light emitting diode (LED) was studied by experiments and simulations. The LOP of GaN-based LED increases as the thickness of pGaN layer decreases from 300 nm to 100 nm, and then decreases as the thickness decreases to 50 nm. The LOP of LED with 100-nm-thick pGaN increases by 30.9% compared with that of the conventional LED with 300-nm-thick pGaN. The variation trend of IQE is similar to that of LOP as the decrease of GaN thickness. The simulation results demonstrate that the higher light efficiency of LED with 100-nm-thick pGaN is ascribed to the improvements of the carrier concentrations and recombination rates.
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.
A modified density-based clustering algorithm and its implementation
NASA Astrophysics Data System (ADS)
Ban, Zhihua; Liu, Jianguo; Yuan, Lulu; Yang, Hua
2015-12-01
This paper presents an improved density-based clustering algorithm based on the paper of clustering by fast search and find of density peaks. A distance threshold is introduced for the purpose of economizing memory. In order to reduce the probability that two points share the same density value, similarity is utilized to define proximity measure. We have tested the modified algorithm on a large data set, several small data sets and shape data sets. It turns out that the proposed algorithm can obtain acceptable results and can be applied more wildly.
A novel bit-quad-based Euler number computing algorithm.
Yao, Bin; He, Lifeng; Kang, Shiying; Chao, Yuyan; Zhao, Xiao
2015-01-01
The Euler number of a binary image is an important topological property in computer vision and pattern recognition. This paper proposes a novel bit-quad-based Euler number computing algorithm. Based on graph theory and analysis on bit-quad patterns, our algorithm only needs to count two bit-quad patterns. Moreover, by use of the information obtained during processing the previous bit-quad, the average number of pixels to be checked for processing a bit-quad is only 1.75. Experimental results demonstrated that our method outperforms significantly conventional Euler number computing algorithms. PMID:26636023
Effects of Ga Addition on Interfacial Reactions Between Sn-Based Solders and Ni
NASA Astrophysics Data System (ADS)
Wang, Chao-Hong; Li, Kuan-Ting
2016-07-01
The use of Ga as a micro-alloying element in Sn-based solders can change the microstructure of solder joints to improve the mechanical properties, and even suppress the interfacial intermetallic compound (IMC) growth. This research investigated the effects of Ga addition (0.2-1 wt.%Ga) on the IMC formation and morphological evolution in the Sn-based solder joints with Ni substrate. In the soldering reaction at 250°C and with less than 0.2 wt.%Ga addition, the formed phase was Ni3Sn4. When the Ga addition increased to 0.5 wt.%, it changed to a thin Ni2Ga3 layer of ˜1 μm thick, which stably existed at the interface in the initial 1-h reaction. Subsequently, the whole Ni2Ga3 layer detached from the Ni substrate and drifted into the molten solder. The Ni3Sn4 phase became dominant in the later stage. Notably, the Ga addition significantly reduced the grain size of Ni3Sn4, resulting in the massive spalling of Ni3Sn4 grains. With 1 wt.%Ga addition, the Ni2Ga3 layer remained very thin with no significant growth, and it stably existed at the interface for more than 10 h. In addition, the solid-state reactions were examined at temperatures of 160°C to 200°C. With addition of 0.5 wt.%Ga, the Ni3Sn4 phase dominated the whole reaction. By contrast, with increasing to 1 wt.%Ga, only a thin Ni2Ga3 layer was found even after aging at 160°C for more than 1200 h. The 1 wt.%Ga addition in solder can effectively inhibit the Ni3Sn4 formation in soldering and the long-term aging process.
Emission spectra of a laser based on an In(Ga)As/GaAs quantum-dot superlattice
Sobolev, M. M. Buyalo, M. S.; Nevedomskiy, V. N.; Zadiranov, Yu. M.; Zolotareva, R. V.; Vasil’ev, A. P.; Ustinov, V. M.; Portnoi, E. L.
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 and 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.
Simple-random-sampling-based multiclass text classification algorithm.
Liu, Wuying; Wang, Lin; Yi, Mianzhu
2014-01-01
Multiclass text classification (MTC) is a challenging issue and the corresponding MTC algorithms can be used in many applications. The space-time overhead of the algorithms must be concerned about the era of big data. Through the investigation of the token frequency distribution in a Chinese web document collection, this paper reexamines the power law and proposes a simple-random-sampling-based MTC (SRSMTC) algorithm. Supported by a token level memory to store labeled documents, the SRSMTC algorithm uses a text retrieval approach to solve text classification problems. The experimental results on the TanCorp data set show that SRSMTC algorithm can achieve the state-of-the-art performance at greatly reduced space-time requirements. PMID:24778587
A ray-based algorithm for multi-dimensional linearconversion
Tracy, Eugene R.; Kaufman, Allan N.; Jaun, Andre
2004-04-19
A numerical algorithm is proposed for connecting the incoming and outgoing wave fields in studies of linear conversion. This is the first such ray-based algorithm for wave conversion in multiple spatial dimensions. it is demonstrated that, aside from the overall phase of the coupling, one can directly evaluate all quantities needed for the connection coefficients from the ray geometry. The ray dynamics is generated using the determinant of the dispersion matrix as the hamiltonian. Using information available while following an incoming ray, the algorithm automatically detects that the ray has entered a conversion region, evaluates the transmission and conversion coefficients, and launches the transmitted ray. The algorithm does not require any prior knowledge of the geometry of the conversion region. The algorithm is illustrated using a two-dimensional toroidal model with resonant conversion from a magnetosonic to an ion-hybrid wave.
Simple-Random-Sampling-Based Multiclass Text Classification Algorithm
Liu, Wuying; Wang, Lin; Yi, Mianzhu
2014-01-01
Multiclass text classification (MTC) is a challenging issue and the corresponding MTC algorithms can be used in many applications. The space-time overhead of the algorithms must be concerned about the era of big data. Through the investigation of the token frequency distribution in a Chinese web document collection, this paper reexamines the power law and proposes a simple-random-sampling-based MTC (SRSMTC) algorithm. Supported by a token level memory to store labeled documents, the SRSMTC algorithm uses a text retrieval approach to solve text classification problems. The experimental results on the TanCorp data set show that SRSMTC algorithm can achieve the state-of-the-art performance at greatly reduced space-time requirements. PMID:24778587
Ocean feature recognition using genetic algorithms with fuzzy fitness functions (GA/F3)
NASA Technical Reports Server (NTRS)
Ankenbrandt, C. A.; Buckles, B. P.; Petry, F. E.; Lybanon, M.
1990-01-01
A model for genetic algorithms with semantic nets is derived for which the relationships between concepts is depicted as a semantic net. An organism represents the manner in which objects in a scene are attached to concepts in the net. Predicates between object pairs are continuous valued truth functions in the form of an inverse exponential function (e sub beta lxl). 1:n relationships are combined via the fuzzy OR (Max (...)). Finally, predicates between pairs of concepts are resolved by taking the average of the combined predicate values of the objects attached to the concept at the tail of the arc representing the predicate in the semantic net. The method is illustrated by applying it to the identification of oceanic features in the North Atlantic.
Dielectrics for GaN based MIS-diodes
Ren, F.; Abernathy, C.R.; MacKenzie, J.D.
1998-02-01
GaN MIS diodes were demonstrated utilizing AlN and Ga{sub 2}O{sub 3}(Gd{sub 2}O{sub 3}) as insulators. A 345 {angstrom} of AlN was grown on the MOCVD grown n-GaN in a MOMBE system using trimethylamine alane as Al precursor and nitrogen generated from a wavemat ECR N2 plasma. For the Ga{sub 2}O{sub 3}(Gd{sub 2}O{sub 3}) growth, a multi MBE chamber was used and a 195 {angstrom} oxide is E-beam evaporated from a single crystal source of Ga{sub 5}Gd{sub 3}O{sub 12}. The forward breakdown voltage of AlN and Ga{sub 2}O{sub 3}(Gd{sub 2}O{sub 3}) diodes are 5V and 6V, respectively, which are significantly improved from {approximately} 1.2 V of schottky contact. From the C-V measurements, both kinds of diodes showed good charge modulation from accumulation to depletion at different frequencies. The insulator GaN interface roughness and the thickness of the insulator were measured with x-ray reflectivity.
NASA Astrophysics Data System (ADS)
Wang, Li-yong; Li, Le; Zhang, Zhi-hua
2016-07-01
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.
Thermophotovoltaic Converters Based on Poly-crystalline GaSb
NASA Astrophysics Data System (ADS)
Corregidor, V.; Vincent, J.; Algora, C.; Diéguez, E.
2007-02-01
In this work we present the development obtained on GaSb converters manufactured from GaSb polycrystals substrates since the last TPV Conference. As one of the main problem of these GaSb converters was the surface preparation, we present new surface treatments, besides higher structural quality of the ingots. The substrates were selected from polycrystalline ingots grown by vertical Bridgman technique. The electrical measurements show the n-type mobility values up to 1000 cm2ṡV-1ṡs-1. On these substrates, 4 mm2 thermophotovoltaic cells were manufactured and characterized by illuminated J-V curves and quantum efficiency techniques.
Analysis and modelling of GaN Schottky-based circuits at millimeter wavelengths
NASA Astrophysics Data System (ADS)
Pardo, D.; Grajal, J.
2015-11-01
This work presents an analysis of the capabilities of GaN Schottky diodes for frequency multipliers and mixers at millimeter wavelengths. By using a Monte Carlo (MC) model of the diode coupled to a harmonic balance technique, the electrical and noise performances of these circuits are investigated. Despite the lower electron mobility of GaN compared to GaAs, multipliers based on GaN Schottky diodes can be competitive in the first stages of multiplier chains, due to the excellent power handling capabilities of this material. The performance of these circuits can be improved by taking advantage of the lateral Schottky diode structures based on AlGaN/GaN HEMT technology.
AlGaN/GaN-based HEMTs for electrical stimulation of neuronal cell cultures
NASA Astrophysics Data System (ADS)
Witte, H.; Warnke, C.; Voigt, T.; de Lima, A.; Ivanov, I.; Vidakovic-Koch, T. R.; Sundmacher, K.; Krost, A.
2011-09-01
Unipolar source-drain voltage pulses of GaN/AlGaN-high electron mobility transistors (HEMTs) were used for stimulation of cultured neuronal networks obtained from embryonic rat cerebral cortex. The HEMT sensor was grown by metal organic vapour phase epitaxy on a 2 inch sapphire substrate consisting of 10 single HEMTs concentrically arranged around the wafer centre. Electrolytic reactions between the HEMT sensor surface and the culture medium were not detected using cyclic voltammetry. During voltage pulses and resulting neuronal excitation, capacitances were recharged giving indications of the contributions of the AlGaN and AlOx isolation layers between the two-dimensional electron gas channel and the neuron culture. The resulting threshold current for stimulation of neuron activity strongly depended on the culture and HEMT position on the sensor surface under consideration which was caused by different impedances of each neuron culture and position within the culture. The differences of culture impedances could be explained by variations of composition, thickness and conductivity of the culture areas.
GaN-based light-emitting diodes suitable for white light
NASA Astrophysics Data System (ADS)
Mukai, Takashi; Yamada, Motokazu; Mitani, Tomotsugu; Narukawa, Yukio; Shioji, Shuji; Niki, Isamu; Sonobe, Shin-ya; Izuno, Kunihiro; Suenaga, Ryoma
2003-07-01
High-efficient light emitting diodes (LEDs) emitting red, amber, green, blue and ultraviolet light have been obtained through the use of an InGaN active layers. The localized energy states caused by In composition fluctuation in the InGaN active layer seem to be related to the high efficiency of the InGaN-based emitting devices in spite of having a large number of threading dislocations (TDs). InGaN single-quantum-well-structure blue LEDs were grown on epitaxially laterally overgrown GaN (ELOG) and sapphire substrates. The characteristics of both LEDs was almost same. These results indicate that the dislocation doesn't affect the efficiency practically. Recently, the development of high-power light source using GaN-based LEDs has become active. In such high-power LEDs, the density of forward current is much higher than that of past LEDs. Therefore, an advantage of carrier localization in InGaN active layer becomes small, because of band filling under high injection level. This means that reducing the density of TDs becomes important, just like GaN-based laser diodes. Also, we show recent results of GaN-based LEDs.
NASA Astrophysics Data System (ADS)
Chen, P.; Zhao, D. G.; Jiang, D. S.; Zhu, J. J.; Liu, Z. S.; Yang, J.; Li, X.; Le, L. C.; He, X. G.; Liu, W.; Li, X. J.; Liang, F.; Zhang, B. S.; Yang, H.; Zhang, Y. T.; Du, G. T.
2016-03-01
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 Al0.2Ga0.8N 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 a 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.
Vardhan, J. Vishnu; Balasubramaniam, Krishnan; Krishnamurthy, C. V.
2007-03-21
The determination of material symmetries and principle plane orientations of anisotropic plates, whose planes of symmetries are not known apriori, were calculated using a Genetic Algorithm (GA) based blind inversion method. The ultrasonic phase velocity profiles were used as input data to the inversion. The assumption of a general anisotropy was imposed during the start of each blind inversion. The multi-parameter solution space of the Genetic Algorithm was exploited to identify the 'statistically significant' solution sets of elastic moduli in the geometric coordinate system of the plate, by thresholding the coefficients-of-variation (Cv). Using these ''statistically significant'' elastic moduli, the unknown material symmetry and the principle planes (angles between the geometrical coordinates and the material symmetry coordinates) were evaluated using the method proposed by Cowin and Mehrabadi. This procedure was verified using simulated ultrasonic velocity data sets on material with orthotropic symmetry. Experimental validation was also performed on unidirectional Graphite Epoxy [0]7s fiber reinforced composite plate.
Guided macro-mutation in a graded energy based genetic algorithm for protein structure prediction.
Rashid, Mahmood A; Iqbal, Sumaiya; Khatib, Firas; Hoque, Md Tamjidul; Sattar, Abdul
2016-04-01
Protein structure prediction is considered as one of the most challenging and computationally intractable combinatorial problem. Thus, the efficient modeling of convoluted search space, the clever use of energy functions, and more importantly, the use of effective sampling algorithms become crucial to address this problem. For protein structure modeling, an off-lattice model provides limited scopes to exercise and evaluate the algorithmic developments due to its astronomically large set of data-points. In contrast, an on-lattice model widens the scopes and permits studying the relatively larger proteins because of its finite set of data-points. In this work, we took the full advantage of an on-lattice model by using a face-centered-cube lattice that has the highest packing density with the maximum degree of freedom. We proposed a graded energy-strategically mixes the Miyazawa-Jernigan (MJ) energy with the hydrophobic-polar (HP) energy-based genetic algorithm (GA) for conformational search. In our application, we introduced a 2×2 HP energy guided macro-mutation operator within the GA to explore the best possible local changes exhaustively. Conversely, the 20×20 MJ energy model-the ultimate objective function of our GA that needs to be minimized-considers the impacts amongst the 20 different amino acids and allow searching the globally acceptable conformations. On a set of benchmark proteins, our proposed approach outperformed state-of-the-art approaches in terms of the free energy levels and the root-mean-square deviations. PMID:26878130
Heuristic-based scheduling algorithm for high level synthesis
NASA Technical Reports Server (NTRS)
Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye
1992-01-01
A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.
Quantum Image Encryption Algorithm Based on Quantum Image XOR Operations
NASA Astrophysics Data System (ADS)
Gong, Li-Hua; He, Xiang-Tao; Cheng, Shan; Hua, Tian-Xiang; Zhou, Nan-Run
2016-03-01
A novel encryption algorithm for quantum images based on quantum image XOR operations is designed. The quantum image XOR operations are designed by using the hyper-chaotic sequences generated with the Chen's hyper-chaotic system to control the control-NOT operation, which is used to encode gray-level information. The initial conditions of the Chen's hyper-chaotic system are the keys, which guarantee the security of the proposed quantum image encryption algorithm. Numerical simulations and theoretical analyses demonstrate that the proposed quantum image encryption algorithm has larger key space, higher key sensitivity, stronger resistance of statistical analysis and lower computational complexity than its classical counterparts.
Rate control algorithm based on frame complexity estimation for MVC
NASA Astrophysics Data System (ADS)
Yan, Tao; An, Ping; Shen, Liquan; Zhang, Zhaoyang
2010-07-01
Rate control has not been well studied for multi-view video coding (MVC). In this paper, we propose an efficient rate control algorithm for MVC by improving the quadratic rate-distortion (R-D) model, which reasonably allocate bit-rate among views based on correlation analysis. The proposed algorithm consists of four levels for rate bits control more accurately, of which the frame layer allocates bits according to frame complexity and temporal activity. Extensive experiments show that the proposed algorithm can efficiently implement bit allocation and rate control according to coding parameters.
A Novel Image Encryption Algorithm Based on DNA Subsequence Operation
Zhang, Qiang; Xue, Xianglian; Wei, Xiaopeng
2012-01-01
We present a novel image encryption algorithm based on DNA subsequence operation. Different from the traditional DNA encryption methods, our algorithm does not use complex biological operation but just uses the idea of DNA subsequence operations (such as elongation operation, truncation operation, deletion operation, etc.) combining with the logistic chaotic map to scramble the location and the value of pixel points from the image. The experimental results and security analysis show that the proposed algorithm is easy to be implemented, can get good encryption effect, has a wide secret key's space, strong sensitivity to secret key, and has the abilities of resisting exhaustive attack and statistic attack. PMID:23093912
Quantum Image Encryption Algorithm Based on Quantum Image XOR Operations
NASA Astrophysics Data System (ADS)
Gong, Li-Hua; He, Xiang-Tao; Cheng, Shan; Hua, Tian-Xiang; Zhou, Nan-Run
2016-07-01
A novel encryption algorithm for quantum images based on quantum image XOR operations is designed. The quantum image XOR operations are designed by using the hyper-chaotic sequences generated with the Chen's hyper-chaotic system to control the control-NOT operation, which is used to encode gray-level information. The initial conditions of the Chen's hyper-chaotic system are the keys, which guarantee the security of the proposed quantum image encryption algorithm. Numerical simulations and theoretical analyses demonstrate that the proposed quantum image encryption algorithm has larger key space, higher key sensitivity, stronger resistance of statistical analysis and lower computational complexity than its classical counterparts.
Genetic Algorithm Based Neural Networks for Nonlinear Optimization
Energy Science and Technology Software Center (ESTSC)
1994-09-28
This software develops a novel approach to nonlinear optimization using genetic algorithm based neural networks. To our best knowledge, this approach represents the first attempt at applying both neural network and genetic algorithm techniques to solve a nonlinear optimization problem. The approach constructs a neural network structure and an appropriately shaped energy surface whose minima correspond to optimal solutions of the problem. A genetic algorithm is employed to perform a parallel and powerful search ofmore » the energy surface.« less
A novel image encryption algorithm based on DNA subsequence operation.
Zhang, Qiang; Xue, Xianglian; Wei, Xiaopeng
2012-01-01
We present a novel image encryption algorithm based on DNA subsequence operation. Different from the traditional DNA encryption methods, our algorithm does not use complex biological operation but just uses the idea of DNA subsequence operations (such as elongation operation, truncation operation, deletion operation, etc.) combining with the logistic chaotic map to scramble the location and the value of pixel points from the image. The experimental results and security analysis show that the proposed algorithm is easy to be implemented, can get good encryption effect, has a wide secret key's space, strong sensitivity to secret key, and has the abilities of resisting exhaustive attack and statistic attack. PMID:23093912
Ray-tracing-based reconstruction algorithms for digital breast tomosynthesis
NASA Astrophysics Data System (ADS)
Zhou, Weihua; Lu, Jianping; Zhou, Otto; Chen, Ying
2015-03-01
As a breast-imaging technique, digital breast tomosynthesis has great potential to improve the diagnosis of early breast cancer over mammography. Ray-tracing-based reconstruction algorithms, such as ray-tracing back projection, maximum-likelihood expectation maximization (MLEM), ordered-subset MLEM (OS-MLEM), and simultaneous algebraic reconstruction technique (SART), have been developed as reconstruction methods for different breast tomosynthesis systems. This paper provides a comparative study to investigate these algorithms by computer simulation and phantom study. Experimental results suggested that, among the four investigated reconstruction algorithms, OS-MLEM and SART performed better in interplane artifact removal with a fast speed convergence.
Evaporation-based Ge/.sup.68 Ga Separation
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.
Tani, M; Matsuura, S; Sakai, K; Nakashima, S
1997-10-20
Terahertz radiation was generated with several designs of photoconductive antennas (three dipoles, a bow tie, and a coplanar strip line) fabricated on low-temperature-grown (LT) GaAs and semi-insulating (SI) GaAs, and the emission properties of the photoconductive antennas were compared with each other. The radiation spectrum of each antenna was characterized with the photoconductive sampling technique. The total radiation power was also measured by a bolometer for comparison of the relative radiation power. The radiation spectra of the LT-GaAs-based and SI-GaAs-based photoconductive antennas of the same design showed no significant difference. The pump-power dependencies of the radiation power showed saturation for higher pump intensities, which was more serious in SI-GaAs-based antennas than in LT-GaAs-based antennas. We attributed the origin of the saturation to the field screening of the photocarriers. PMID:18264312
Plasmonic terahertz detectors based on a high-electron mobility GaAs/AlGaAs heterostructure
Białek, M. Witowski, A. M.; Grynberg, M.; Łusakowski, J.; Orlita, M.; Potemski, M.; Czapkiewicz, M.; Umansky, V.
2014-06-07
In order to characterize magnetic field (B) tunable THz plasmonic detectors, spectroscopy experiments were carried out at liquid helium temperatures and high magnetic fields on devices fabricated on a high electron mobility GaAs/AlGaAs heterostructure. The samples were either gated (the gate of a meander shape) or ungated. Spectra of a photovoltage generated by THz radiation were obtained as a function of B at a fixed THz excitation from a THz laser or as a function of THz photon frequency at a fixed B with a Fourier spectrometer. In the first type of measurements, the wave vector of magnetoplasmons excited was defined by geometrical features of samples. It was also found that the magnetoplasmon spectrum depended on the gate geometry which gives an additional parameter to control plasma excitations in THz detectors. Fourier spectra showed a strong dependence of the magnetoplasmon resonance amplitude on the conduction-band electron filling factor which was explained within a model of the electron gas heating with THz radiation. The study allows to define both the advantages and limitations of plasmonic devices based on high-mobility GaAs/AlGaAs heterostructures for THz detection at low temperatures and high magnetic fields.
A novel iris segmentation algorithm based on small eigenvalue analysis
NASA Astrophysics Data System (ADS)
Harish, B. S.; Aruna Kumar, S. V.; Guru, D. S.; Ngo, Minh Ngoc
2015-12-01
In this paper, a simple and robust algorithm is proposed for iris segmentation. The proposed method consists of two steps. In first step, iris and pupil is segmented using Robust Spatial Kernel FCM (RSKFCM) algorithm. RSKFCM is based on traditional Fuzzy-c-Means (FCM) algorithm, which incorporates spatial information and uses kernel metric as distance measure. In second step, small eigenvalue transformation is applied to localize iris boundary. The transformation is based on statistical and geometrical properties of the small eigenvalue of the covariance matrix of a set of edge pixels. Extensive experimentations are carried out on standard benchmark iris dataset (viz. CASIA-IrisV4 and UBIRIS.v2). We compared our proposed method with existing iris segmentation methods. Our proposed method has the least time complexity of O(n(i+p)) . The result of the experiments emphasizes that the proposed algorithm outperforms the existing iris segmentation methods.
Algorithm for calculating torque base in vehicle traction control system
NASA Astrophysics Data System (ADS)
Li, Hongzhi; Li, Liang; Song, Jian; Wu, Kaihui; Qiao, Yanjuan; Liu, Xingchun; Xia, Yongguang
2012-11-01
Existing research on the traction control system(TCS) mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS (referred to as the torque base in this paper), which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop(HIL) simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.
Medical image compression algorithm based on wavelet transform
NASA Astrophysics Data System (ADS)
Chen, Minghong; Zhang, Guoping; Wan, Wei; Liu, Minmin
2005-02-01
With rapid development of electronic imaging and multimedia technology, the telemedicine is applied to modern medical servings in the hospital. Digital medical image is characterized by high resolution, high precision and vast data. The optimized compression algorithm can alleviate restriction in the transmission speed and data storage. This paper describes the characteristics of human vision system based on the physiology structure, and analyses the characteristics of medical image in the telemedicine, then it brings forward an optimized compression algorithm based on wavelet zerotree. After the image is smoothed, it is decomposed with the haar filters. Then the wavelet coefficients are quantified adaptively. Therefore, we can maximize efficiency of compression and achieve better subjective visual image. This algorithm can be applied to image transmission in the telemedicine. In the end, we examined the feasibility of this algorithm with an image transmission experiment in the network.
NASA Astrophysics Data System (ADS)
Jamshidi, Saeid; Boozarjomehry, Ramin Bozorgmehry; Pishvaie, Mahmoud Reza
2009-10-01
In pore network modeling, the void space of a rock sample is represented at the microscopic scale by a network of pores connected by throats. Construction of a reasonable representation of the geometry and topology of the pore space will lead to a reliable prediction of the properties of porous media. Recently, the theory of multi-cellular growth (or L-systems) has been used as a flexible tool for generation of pore network models which do not require any special information such as 2D SEM or 3D pore space images. In general, the networks generated by this method are irregular pore network models which are inherently closer to the complicated nature of the porous media rather than regular lattice networks. In this approach, the construction process is controlled only by the production rules that govern the development process of the network. In this study, genetic algorithm has been used to obtain the optimum values of the uncertain parameters of these production rules to build an appropriate irregular lattice network capable of the prediction of both static and hydraulic information of the target porous medium.
A new augmentation based algorithm for extracting maximal chordal subgraphs
Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh
2014-10-18
If every cycle of a graph is chordal length greater than three then it contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms’ parallelizability. In our paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. Finally, we experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.
A new augmentation based algorithm for extracting maximal chordal subgraphs
Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh
2014-10-18
If every cycle of a graph is chordal length greater than three then it contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms’more » parallelizability. In our paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. Finally, we experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.« less
A New Augmentation Based Algorithm for Extracting Maximal Chordal Subgraphs
Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh
2014-01-01
A graph is chordal if every cycle of length greater than three contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms’ parallelizability. In this paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. We experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph. PMID:25767331
Ga(+) Basicity and Affinity Scales Based on High-Level Ab Initio Calculations.
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. PMID:26269224
A SAR ATR algorithm based on coherent change detection
Harmony, D.W.
2000-12-01
This report discusses an automatic target recognition (ATR) algorithm for synthetic aperture radar (SAR) imagery that is based on coherent change detection techniques. The algorithm relies on templates created from training data to identify targets. Objects are identified or rejected as targets by comparing their SAR signatures with templates using the same complex correlation scheme developed for coherent change detection. Preliminary results are presented in addition to future recommendations.
Effect of object identification algorithms on feature based verification scores
NASA Astrophysics Data System (ADS)
Weniger, Michael; Friederichs, Petra
2015-04-01
Many modern spatial verification techniques rely on feature identification algorithms. We study the importance of the choice of algorithm and its parameters for the resulting scores. SAL is used as an example to show that these choices have a statistically significant impact on the distributions of object dependent scores. Non-continuous operators used for feature identification are identified as the underlying reason for the observed stability issues, with implications for many feature based verification techniques.
Monolithic enhancement-mode and depletion-mode GaN-based MOSHEMTs
NASA Astrophysics Data System (ADS)
Lee, Ching-Ting; Chang, Jhe-Hao; Tseng, Chun-Yen
2016-02-01
GaN-based metal-oxide-semiconductor high-electron-mobility transistors (MOSHEMTs) with outstanding properties of high operation speed and high breakdown voltage are promising for high frequency switching operation in ICs. To further develop the GaN-based digital ICs, the AlGaN/GaN MOSHEMT inverters integrated with the enhancement/depletion-mode (E/D-mode) transistors were investigated. In this work, the ferroelectric LiNbO3 (LNO) gate oxide layer and the photoelectrochemical (PEC)-recessed structure were simultaneously utilized to fabricate the critical E-mode AlGaN/GaN MOSHEMTs. Among the ferroelectric materials, the high dielectric constant LNO film with the larger spontaneous polarization of 80 μC/cm2, the wider bandgap of 3.9 eV, and the lower interface state density on the GaN-based semiconductor was beneficial to the modulation of the two-dimensional electron gas (2DEG) channel and the reduction of the gate leakage current. Besides, using the PEC-recessed structure could improve the transconductance of the E-mode transistors and adjust the operation current of the D-mode transistors without destroying the etched AlGaN surface. Instead of the typical tuning area size method, the PEC etching method was demonstrated in this work to adjust the current ratio (β) of the E/D-mode transistors with keeping the matched area size for the miniaturization of the AlGaN/GaN MOSHEMT inverters. From the voltage transfer curve, the corresponded VOUT was equaled to VIN = VDD/2 = 2.5 V, and the output swing were about 4.9 Vp-p as the input signal was 5 Vp-p. It revealed that the resulting AlGaN/GaN MOSHEMT inverter with the β of 25 was operated as a high performance un-skewed inverter.
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.
List-Based Simulated Annealing Algorithm for Traveling Salesman Problem
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.
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. PMID:27034650
Ling, Steve S H; Nguyen, Hung T
2011-03-01
Hypoglycemia or low blood glucose is dangerous and can result in unconsciousness, seizures, and even death. It is a common and serious side effect of insulin therapy in patients with diabetes. Hypoglycemic monitor is a noninvasive monitor that measures some physiological parameters continuously to provide detection of hypoglycemic episodes in type 1 diabetes mellitus patients (T1DM). Based on heart rate (HR), corrected QT interval of the ECG signal, change of HR, and the change of corrected QT interval, we develop a genetic algorithm (GA)-based multiple regression with fuzzy inference system (FIS) to classify the presence of hypoglycemic episodes. GA is used to find the optimal fuzzy rules and membership functions of FIS and the model parameters of regression method. From a clinical study of 16 children with T1DM, natural occurrence of nocturnal hypoglycemic episodes is associated with HRs and corrected QT intervals. The overall data were organized into a training set (eight patients) and a testing set (another eight patients) randomly selected. The results show that the proposed algorithm performs a good sensitivity with an acceptable specificity. PMID:21349796
Integrated micro-optical multichip module based on an uncooled InGaAsSb/AlGaAsSb photodetector
NASA Astrophysics Data System (ADS)
Lohokare, Saurabh K.; Sulima, Oleg V.; Dillon, Thomas E.; Prather, Dennis W.
2005-09-01
This paper focuses on the integration of InGaAsSb photodetectors along with micro-optics in order to realize a prototype system that can achieve a stronger response during atmospheric profiling and spectroscopy measurements. The integration of the detector was executed using a novel conductive-adhesive-based flip-chip integration process. The design, fabrication, and integration of the constituent technologies and experimental results from their characterization are presented.
GaSb substrates with extended IR wavelength for advanced space based applications
Allen, Lisa P.; Flint, Patrick; Dallas, Gordon; Bakken, Daniel; Blanchat, Kevin; Brown, Gail J.; Vangala, Shivashankar R.; Goodhue, William D.; Krishnaswami, Kannan
2009-05-01
GaSb substrates have advantages that make them attractive for implementation of a wide range of infrared (IR) detectors with higher operating temperatures for stealth and space based applications. A significant aspect that would enable widespread commercial application of GaSb wafers for very long wavelength IR (VLWIR) applications is the capability for transmissivity beyond 15 m. Due largely to the GaSb (antisite) defect and other point defects in undoped GaSb substrates, intrinsic GaSb is still slightly p-type and strongly absorbs in the VLWIR. This requires backside thinning of the GaSb substrate for IR transmissivity. An extremely low n-type GaSb substrate is preferred to eliminate thinning and provide a substrate solution for backside illuminated VLWIR devices. By providing a more homogeneous radial distribution of the melt solute to suppress GaSb formation and controlling the cooling rate, ultra low doped n:GaSb has been achieved. This study examines the surface properties and IR transmission spectra of ultra low doped GaSb substrates at both room and low temperatures. Atomic force microscopy (AFM), homoepitaxy by MBE, and infrared Fourier transform (FTIR) analysis was implemented to examine material quality. As compared with standard low doped GaSb, the ultra low doped substrates show over 50% transmission and consistent wavelength transparency past 23 m with improved %T at low temperature. Homoepitaxy and AFM results indicate the ultra low doped GaSb has a low thermal desorbtion character and qualified morphology. In summary, improvements in room temperature IR transmission and extended wavelength characteristics have been shown consistently for ultra low doped n:GaSb substrates.
Flexible Phrase Based Query Handling Algorithms.
ERIC Educational Resources Information Center
Wilbur, W. John; Kim, Won
2001-01-01
Flexibility in query handling can be important if one types a search engine query that is misspelled, contains terms not in the database, or requires knowledge of a controlled vocabulary. Presents results of experiments that suggest the optimal form of similarity functions that are applicable to the task of phrase based retrieval to find either…
Study of InGaAs based MODFET structures using variable angle spectroscopic ellipsometry
NASA Technical Reports Server (NTRS)
Alterovitz, S. A.; Sieg, R. M.; Yao, H. D.; Snyder, P. G.; Woollam, J. A.; Pamulapati, J.; Bhattacharya, P. K.; Sekula-Moise, P. A.
1991-01-01
Variable angle spectroscopic ellipsometry was used to estimate the thicknesses of all layers within the optical penetration depth of InGaAs based MODFET structures. Strained and unstrained InGaAs channels were made by MBE on InP substrates and by MOCVD on GaAs substrates. In most cases, ellipsometrically determined thicknesses were within 10 percent of the growth calibration results. The MBE made InGaAs strained layers showed large strain effects, indicating a probable shift in the critical points of their dielectric function toward the InP lattice matched concentration.
Particle flow reconstruction based on the directed tree clustering algorithm
Chakraborty, D.; Lima, J. G. R.; McIntosh, R.; Zutshi, V.
2006-10-27
We present the status of particle flow algorithm development at Northern Illinois University. A key element in our approach is the calorimeter-based directed tree clustering algorithm. We have attempted to identify and tackle the essential challenges and analyze the effect of several different approaches to the reconstruction of jet energies and the Z-boson mass. A number of possibilities have been studied, such as analog vs. digital energy measurement, hit density-based clustering and the use of single or multiple energy thresholds. We plan to use this PFA-based reconstruction to compare some of the proposed detector technologies and geometries.
An ab initio-based approach to the stability of GaN(0 0 0 1) surfaces under Ga-rich conditions
NASA Astrophysics Data System (ADS)
Ito, Tomonori; Akiyama, Toru; Nakamura, Kohji
2009-05-01
Structural stability of GaN(0 0 0 1) under Ga-rich conditions is systematically investigated by using our ab initio-based approach. The surface phase diagram for GaN(0 0 0 1) including (2×2) and pseudo-(1×1) is obtained as functions of temperature and Ga beam equivalent pressure by comparing chemical potentials of Ga atom in the gas phase with that on the surface. The calculated results reveal that the pseudo-(1×1) appearing below 684-973 K changes its structure to the (2×2) with Ga adatom at higher temperatures beyond 767-1078 K via the newly found (1×1) with two adlayers of Ga. These results are consistent with the stable temperature range of both the pseudo-(1×1) and (2×2) with Ga adatom obtained experimentally. Furthermore, it should be noted that the structure with another coverage of Ga adatoms between the (1×1) and (2×2)-Ga does not appear as a stable structure of GaN(0 0 0 1). Furthermore, ghost island formation observed by scanning tunneling microscopy is discussed on the basis of the phase diagram.
NASA Astrophysics Data System (ADS)
Yang, Weijia; Wang, Wenliang; Lin, Yunhao; Liu, Zuolian; Zhou, Shizhong; Qian, Huirong; Li, Guoqiang
2015-08-01
High-quality nonpolar m-plane GaN-based light-emitting diode (LED) wafers on LiGaO2(100) substrates have been grown in this work by the combination of pulsed laser deposition and molecular beam epitaxy technologies. This work systemically studies the crystalline quality, surface morphology, as well as optoelectronic properties of as-grown nonpolar m-plane GaN-based LED wafers. The as-grown nonpolar m-plane GaN-based LED wafers on LiGaO2(100) substrates show good structural properties with estimated dislocation density ˜108 cm-2 and abrupt InGaN/GaN interfaces. A photoluminescence peak at approximately 446 nm with full-width at half-maximum (FWHM) of 21.2 nm is identified at room temperature. A strong electroluminescence (EL) peak observed at 446 nm with FWHM of 20.7 nm is obtained at an injection current of 20 mA. Furthermore, there is a slight blue shift in the EL emission wavelength with increase in the injection current, while the EL FWHM can be kept stable thanks to the absence of the quantum confined Stark effect. This study of high-quality nonpolar m-plane GaN-based LEDs is of paramount importance for future application of high-efficiency GaN-based devices.
A robust DCT domain watermarking algorithm based on chaos system
NASA Astrophysics Data System (ADS)
Xiao, Mingsong; Wan, Xiaoxia; Gan, Chaohua; Du, Bo
2009-10-01
Digital watermarking is a kind of technique that can be used for protecting and enforcing the intellectual property (IP) rights of the digital media like the digital images containting in the transaction copyright. There are many kinds of digital watermarking algorithms. However, existing digital watermarking algorithms are not robust enough against geometric attacks and signal processing operations. In this paper, a robust watermarking algorithm based on chaos array in DCT (discrete cosine transform)-domain for gray images is proposed. The algorithm provides an one-to-one method to extract the watermark.Experimental results have proved that this new method has high accuracy and is highly robust against geometric attacks, signal processing operations and geometric transformations. Furthermore, the one who have on idea of the key can't find the position of the watermark embedded in. As a result, the watermark not easy to be modified, so this scheme is secure and robust.
Research on Bayes matting algorithm based on Gaussian mixture model
NASA Astrophysics Data System (ADS)
Quan, Wei; Jiang, Shan; Han, Cheng; Zhang, Chao; Jiang, Zhengang
2015-12-01
The digital matting problem is a classical problem of imaging. It aims at separating non-rectangular foreground objects from a background image, and compositing with a new background image. Accurate matting determines the quality of the compositing image. A Bayesian matting Algorithm Based on Gaussian Mixture Model is proposed to solve this matting problem. Firstly, the traditional Bayesian framework is improved by introducing Gaussian mixture model. Then, a weighting factor is added in order to suppress the noises of the compositing images. Finally, the effect is further improved by regulating the user's input. This algorithm is applied to matting jobs of classical images. The results are compared to the traditional Bayesian method. It is shown that our algorithm has better performance in detail such as hair. Our algorithm eliminates the noise well. And it is very effectively in dealing with the kind of work, such as interested objects with intricate boundaries.
Genetic-algorithm-based tri-state neural networks
NASA Astrophysics Data System (ADS)
Uang, Chii-Maw; Chen, Wen-Gong; Horng, Ji-Bin
2002-09-01
A new method, using genetic algorithms, for constructing a tri-state neural network is presented. The global searching features of the genetic algorithms are adopted to help us easily find the interconnection weight matrix of a bipolar neural network. The construction method is based on the biological nervous systems, which evolve the parameters encoded in genes. Taking the advantages of conventional (binary) genetic algorithms, a two-level chromosome structure is proposed for training the tri-state neural network. A Matlab program is developed for simulating the network performances. The results show that the proposed genetic algorithms method not only has the features of accurate of constructing the interconnection weight matrix, but also has better network performance.
Filter model based dwell time algorithm for ion beam figuring
NASA Astrophysics Data System (ADS)
Li, Yun; Xing, Tingwen; Jia, Xin; Wei, Haoming
2010-10-01
The process of Ion Beam Figuring (IBF) can be described by a two-dimensional convolution equation which including dwell time. Solving the dwell time is a key problem in IBF. Theoretically, the dwell time can be solved from a two-dimensional deconvolution. However, it is often ill-posed]; the suitable solution of that is hard to get. In this article, a dwell time algorithm is proposed, depending on the characters of IBF. Usually, the Beam Removal Function (BRF) in IBF is Gaussian, which can be regarded as a headstand Gaussian filter. In its stop-band, the filter has various filtering abilities for various frequencies. The dwell time algorithm proposed in this article is just based on this concept. The Curved Surface Smooth Extension (CSSE) method and Fast Fourier Transform (FFT) algorithm are also used. The simulation results show that this algorithm is high precision, effective, and suitable for actual application.
Validation of a Bayesian-based isotope identification algorithm
NASA Astrophysics Data System (ADS)
Sullivan, C. J.; Stinnett, J.
2015-06-01
Handheld radio-isotope identifiers (RIIDs) are widely used in Homeland Security and other nuclear safety applications. However, most commercially available devices have serious problems in their ability to correctly identify isotopes. It has been reported that this flaw is largely due to the overly simplistic identification algorithms on-board the RIIDs. This paper reports on the experimental validation of a new isotope identification algorithm using a Bayesian statistics approach to identify the source while allowing for calibration drift and unknown shielding. We present here results on further testing of this algorithm and a study on the observed variation in the gamma peak energies and areas from a wavelet-based peak identification algorithm.