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
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
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.
[An algorithm of a wavelet-based medical image quantization].
Hou, Wensheng; Wu, Xiaoying; Peng, Chenglin
2002-12-01
The compression of medical image is the key to study tele-medicine & PACS. We have studied the statistical distribution of wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is very much similar to that of Laplacian distribution. Based on the statistical properties of image wavelet decomposition, an image quantization algorithm is proposed. In this algorithm, we selected the sample-standard-deviation as the key quantization threshold in every wavelet subimage. The test has proved that, the main advantages of this algorithm are simple computing and the predictability of coefficients in different quantization threshold range. Also, high compression efficiency can be obtained. Therefore, this algorithm can be potentially used in tele-medicine and PACS. PMID:12561372
Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms
NASA Astrophysics Data System (ADS)
Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan
2010-12-01
This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.
Adaptive NUC algorithm for uncooled IRFPA based on neural networks
NASA Astrophysics Data System (ADS)
Liu, Ziji; Jiang, Yadong; Lv, Jian; Zhu, Hongbin
2010-10-01
With developments in uncooled infrared plane array (UFPA) technology, many new advanced uncooled infrared sensors are used in defensive weapons, scientific research, industry and commercial applications. A major difference in imaging techniques between infrared IRFPA imaging system and a visible CCD camera is that, IRFPA need nonuniformity correction and dead pixel compensation, we usually called it infrared image pre-processing. Two-point or multi-point correction algorithms based on calibration commonly used may correct the non-uniformity of IRFPAs, but they are limited by pixel linearity and instability. Therefore, adaptive non-uniformity correction techniques are developed. Two of these adaptive non-uniformity correction algorithms are mostly discussed, one is based on temporal high-pass filter, and another is based on neural network. In this paper, a new NUC algorithm based on improved neural networks is introduced, and involves the compare result between improved neural networks and other adaptive correction techniques. A lot of different will discussed in different angle, like correction effects, calculation efficiency, hardware implementation and so on. According to the result and discussion, it could be concluding that the adaptive algorithm offers improved performance compared to traditional calibration mode techniques. This new algorithm not only provides better sensitivity, but also increases the system dynamic range. As the sensor application expended, it will be very useful in future infrared imaging systems.
A Pressure Based Multi-Fluid Algorithm for Multiphase Flow
NASA Astrophysics Data System (ADS)
Ming, P. J.; Zhang, W. P.; Lei, G. D.; Zhu, M. G.
A new finite volume-based numerical algorithm for predicting multiphase flow phenomena is presented. The method is formulated on an orthogonal coordinate system in collocated primitive variables. The SIMPLE-like algorithms are based on the prediction and correction procedure, and they are extended for all speed range. The object of the present work is to extent single phase SIMPLE algorithm to multiphase flow. The overview of the algorithm is described and relevant numerical issues are discussed extensively, including implicit process of the moment interaction with “partial elimination” (of the drag term), introduction of under-relaxation factor, formulation of momentum interpolation, and pressure correction equation. This model is based on the k-ɛ model assumed that the turbulence is dictated by the continuous phase. Thus only the transport equation for the continuous phase turbulence energy kc needed to be solved while a algebraic turbulence model is used for dispersed phase. The present author also designed a general program with FORTRAN90 program language for the new algorithm based on the household code General Transport Equation Analyzer (GTEA). The performance of the new method is assessed by solving a 3D bubbly two-phase flow in a vertical pipe. A good agreement is achieved between the numerical result and experimental data in the literature.
A Turn-Projected State-Based Conflict Resolution Algorithm
NASA Technical Reports Server (NTRS)
Butler, Ricky W.; Lewis, Timothy A.
2013-01-01
State-based conflict detection and resolution (CD&R) algorithms detect conflicts and resolve them on the basis on current state information without the use of additional intent information from aircraft flight plans. Therefore, the prediction of the trajectory of aircraft is based solely upon the position and velocity vectors of the traffic aircraft. Most CD&R algorithms project the traffic state using only the current state vectors. However, the past state vectors can be used to make a better prediction of the future trajectory of the traffic aircraft. This paper explores the idea of using past state vectors to detect traffic turns and resolve conflicts caused by these turns using a non-linear projection of the traffic state. A new algorithm based on this idea is presented and validated using a fast-time simulator developed for this study.
Template based illumination compensation algorithm for multiview video coding
NASA Astrophysics Data System (ADS)
Li, Xiaoming; Jiang, Lianlian; Ma, Siwei; Zhao, Debin; Gao, Wen
2010-07-01
Recently multiview video coding (MVC) standard has been finalized as an extension of H.264/AVC by Joint Video Team (JVT). In the project Joint Multiview Video Model (JMVM) for the standardization, illumination compensation (IC) is adopted as a useful tool. In this paper, a novel illumination compensation algorithm based on template is proposed. The basic idea of the algorithm is that the illumination of the current block has a strong correlation with its adjacent template. Based on this idea, firstly a template based illumination compensation method is presented, and then a template models selection strategy is devised to improve the illumination compensation performance. The experimental results show that the proposed algorithm can improve the coding efficiency significantly.
Multiple sequence alignment based on combining genetic algorithm with chaotic sequences.
Gao, C; Wang, B; Zhou, C J; Zhang, Q
2016-01-01
In bioinformatics, sequence alignment is one of the most common problems. Multiple sequence alignment is an NP (nondeterministic polynomial time) problem, which requires further study and exploration. The chaos optimization algorithm is a type of chaos theory, and a procedure for combining the genetic algorithm (GA), which uses ergodicity, and inherent randomness of chaotic iteration. It is an efficient method to solve the basic premature phenomenon of the GA. Applying the Logistic map to the GA and using chaotic sequences to carry out the chaotic perturbation can improve the convergence of the basic GA. In addition, the random tournament selection and optimal preservation strategy are used in the GA. Experimental evidence indicates good results for this process. PMID:27420977
Musolino, M. Tahraoui, A.; Limbach, F.; Lähnemann, J.; Jahn, U.; Brandt, O.; Geelhaar, L.; Riechert, H.
2014-08-25
We investigate the effect of the p-type top contact on the optoelectronic characteristics of light emitting diodes (LEDs) based on (In,Ga)N/GaN nanowire (NW) ensembles grown by molecular beam epitaxy on Si substrates. We compare devices fabricated with either Ni/Au or indium tin oxide (ITO) top contact. The NW-LEDs with ITO exhibit a number density of NWs emitting electroluminescence about ten times higher, significantly lower turn-on voltage and series resistance, and a relative external quantum efficiency more than one order of magnitude higher than the sample with Ni/Au. These results show that limitations in the performance of such devices reported so far can be overcome by improving the p-type top-contact.
Degradation mechanisms of Ti/Al/Ni/Au-based Ohmic contacts on AlGaN/GaN HEMTs
Hwang, Ya-Hsi; Ahn, Shihyun; Dong, Chen; Zhu, Weidi; Kim, Byung-Jae; Le, Lingcong; Ren, Fan; Lind, Aaron G.; Dahl, James; Jones, Kevin S.; et al
2015-04-27
We investigated the degradation mechanism of Ti/Al/Ni/Au-based Ohmic metallization on AlGaN/GaN high electron mobility transistors upon exposure to buffer oxide etchant (BOE). The major effect of BOE on the Ohmic metal was an increase of sheet resistance from 2.89 to 3.69 Ω/ₜafter 3 min BOE treatment. The alloyed Ohmic metallization consisted 3–5 μm Ni-Al alloy islands surrounded by Au-Al alloy-rings. The morphology of both the islands and ring areas became flatter after BOE etching. Lastly, we used energy dispersive x-ray analysis and Auger electron microscopy to analyze the compositions and metal distributions in the metal alloys prior to and aftermore » BOE exposure.« less
Degradation mechanisms of Ti/Al/Ni/Au-based Ohmic contacts on AlGaN/GaN HEMTs
Hwang, Ya-Hsi; Ahn, Shihyun; Dong, Chen; Zhu, Weidi; Kim, Byung-Jae; Le, Lingcong; Ren, Fan; Lind, Aaron G.; Dahl, James; Jones, Kevin S.; Pearton, Stephen J.; Kravchenko, Ivan I.; Zhang, Ming-Lan
2015-04-27
We investigated the degradation mechanism of Ti/Al/Ni/Au-based Ohmic metallization on AlGaN/GaN high electron mobility transistors upon exposure to buffer oxide etchant (BOE). The major effect of BOE on the Ohmic metal was an increase of sheet resistance from 2.89 to 3.69 Ω/ₜafter 3 min BOE treatment. The alloyed Ohmic metallization consisted 3–5 μm Ni-Al alloy islands surrounded by Au-Al alloy-rings. The morphology of both the islands and ring areas became flatter after BOE etching. Lastly, we used energy dispersive x-ray analysis and Auger electron microscopy to analyze the compositions and metal distributions in the metal alloys prior to and after BOE exposure.
Jia, Xiuling; Chen, Dunjun; Bin, Liu; Lu, Hai; Zhang, Rong; Zheng, Youdou
2016-01-01
A novel ion-imprinted electrochemical sensor based on AlGaN/GaN high electron mobility transistors (HEMTs) was developed to detect trace amounts of phosphate anion. This sensor combined the advantages of the ion sensitivity of AlGaN/GaN HEMTs and specific recognition of ion imprinted polymers. The current response showed that the fabricated sensor is highly sensitive and selective to phosphate anions. The current change exhibited approximate linear dependence for phosphate concentration from 0.02 mg L−1 to 2 mg L−1, the sensitivity and detection limit of the sensor is 3.191 μA/mg L−1 and 1.97 μg L−1, respectively. The results indicated that this AlGaN/GaN HEMT-based electrochemical sensor has the potential applications on phosphate anion detection. PMID:27278795
NASA Astrophysics Data System (ADS)
Jia, Xiuling; Chen, Dunjun; Bin, Liu; Lu, Hai; Zhang, Rong; Zheng, Youdou
2016-06-01
A novel ion-imprinted electrochemical sensor based on AlGaN/GaN high electron mobility transistors (HEMTs) was developed to detect trace amounts of phosphate anion. This sensor combined the advantages of the ion sensitivity of AlGaN/GaN HEMTs and specific recognition of ion imprinted polymers. The current response showed that the fabricated sensor is highly sensitive and selective to phosphate anions. The current change exhibited approximate linear dependence for phosphate concentration from 0.02 mg L‑1 to 2 mg L‑1, the sensitivity and detection limit of the sensor is 3.191 μA/mg L‑1 and 1.97 μg L‑1, respectively. The results indicated that this AlGaN/GaN HEMT-based electrochemical sensor has the potential applications on phosphate anion detection.
Jia, Xiuling; Chen, Dunjun; Bin, Liu; Lu, Hai; Zhang, Rong; Zheng, Youdou
2016-01-01
A novel ion-imprinted electrochemical sensor based on AlGaN/GaN high electron mobility transistors (HEMTs) was developed to detect trace amounts of phosphate anion. This sensor combined the advantages of the ion sensitivity of AlGaN/GaN HEMTs and specific recognition of ion imprinted polymers. The current response showed that the fabricated sensor is highly sensitive and selective to phosphate anions. The current change exhibited approximate linear dependence for phosphate concentration from 0.02 mg L(-1) to 2 mg L(-1), the sensitivity and detection limit of the sensor is 3.191 μA/mg L(-1) and 1.97 μg L(-1), respectively. The results indicated that this AlGaN/GaN HEMT-based electrochemical sensor has the potential applications on phosphate anion detection. PMID:27278795
Tzou, An-Jye; Lin, Da-Wei; Yu, Chien-Rong; Li, Zhen-Yu; Liao, Yu-Kuang; Lin, Bing-Cheng; Huang, Jhih-Kai; Lin, Chien-Chung; Kao, Tsung Sheng; Kuo, Hao-Chung; Chang, Chun-Yen
2016-05-30
In this study, high-performance InGaN-based green light-emitting diodes (LEDs) with a quaternary InAlGaN/GaN superlattice electron blocking layer (QSL-EBL) have been demonstrated. The band structural simulation was employed to investigate the electrostatic field and carriers distribution, show that the efficiency and droop behavior can be intensively improved by using a QSL-EBL in LEDs. The QSL-EBL structure can reduce the polarization-related electrostatic fields in the multiple quantum wells (MQWs), leading to a smoother band diagram and a more uniform carriers distribution among the quantum wells under forward bias. In comparison with green LEDs with conventional bulk-EBL structure, the light output power of LEDs with QSL-EBL was greatly enhanced by 53%. The efficiency droop shows only 30% at 100 A/cm^{2} comparing to its peak value, suggesting that the QSL-EBL LED is promising for future white lighting with high performance. PMID:27410067
Antimonide-Based Long-Wavelength Lasers on GaAs Substrates
KLEM,JOHN F.; Blum, O.
2000-08-17
We have investigated the use of GaAsSb in edge-emitting laser active regions, in order to obtain lasing near 1.3 {micro}m. Single quantum well GaAsSb devices display electroluminescence at wavelengths as long as 1.34 {micro}m, but substantial blueshifts occur under high injection conditions. GaAsSb single quantum well edge emitters have been obtained which lase at 1.275 {micro}m with a room-temperature threshold current density as low as 535 A/cm{sup 2}. Modification of the basic GaAsSb/GaAs structure with the addition of InGaAs layers results in a strongly type-II band alignment which can be used to further extend the emission wavelength of these devices. Using GaAsSb/InGaAs active regions, lasers emitting at 1.17 {micro}m have been obtained with room-temperature threshold current densities of 120 A/cm{sup 2}, and devices operating at 1.29 {micro}m have displayed thresholds as low as 375 A/cm{sup 2}. Characteristic temperatures for devices employing various GaAsSb-based active regions have been measured to be 60-73 K.
A Novel Multiobjective Evolutionary Algorithm Based on Regression Analysis
Song, Zhiming; Wang, Maocai; Dai, Guangming; Vasile, Massimiliano
2015-01-01
As is known, the Pareto set of a continuous multiobjective optimization problem with m objective functions is a piecewise continuous (m − 1)-dimensional manifold in the decision space under some mild conditions. However, how to utilize the regularity to design multiobjective optimization algorithms has become the research focus. In this paper, based on this regularity, a model-based multiobjective evolutionary algorithm with regression analysis (MMEA-RA) is put forward to solve continuous multiobjective optimization problems with variable linkages. In the algorithm, the optimization problem is modelled as a promising area in the decision space by a probability distribution, and the centroid of the probability distribution is (m − 1)-dimensional piecewise continuous manifold. The least squares method is used to construct such a model. A selection strategy based on the nondominated sorting is used to choose the individuals to the next generation. The new algorithm is tested and compared with NSGA-II and RM-MEDA. The result shows that MMEA-RA outperforms RM-MEDA and NSGA-II on the test instances with variable linkages. At the same time, MMEA-RA has higher efficiency than the other two algorithms. A few shortcomings of MMEA-RA have also been identified and discussed in this paper. PMID:25874246
Genetic algorithm based approach to optimize phenotypical traits of virtual rice.
Ding, Weilong; Xu, Lifeng; Wei, Yang; Wu, Fuli; Zhu, Defeng; Zhang, Yuping; Max, Nelson
2016-08-21
How to select and combine good traits of rice to get high-production individuals is one of the key points in developing crop ideotype cultivation technologies. Existing cultivation methods for producing ideal plants, such as field trials and crop modeling, have some limits. In this paper, we propose a method based on a genetic algorithm (GA) and a functional-structural plant model (FSPM) to optimize plant types of virtual rice by dynamically adjusting phenotypical traits. In this algorithm, phenotypical traits such as leaf angles, plant heights, the maximum number of tiller, and the angle of tiller are considered as input parameters of our virtual rice model. We evaluate the photosynthetic output as a function of these parameters, and optimized them using a GA. This method has been implemented on GroIMP using the modeling language XL (eXtended L-System) and RGG (Relational Growth Grammar). A double haploid population of rice is adopted as test material in a case study. Our experimental results show that our method can not only optimize the parameters of rice plant type and increase the amount of light absorption, but can also significantly increase crop yield. PMID:27179460
Zhang, Daqing; Xiao, Jianfeng; Zhou, Nannan; Zheng, Mingyue; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian
2015-01-01
Blood-brain barrier (BBB) is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM) is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy. In most studies, they are treated as two independent problems, but it has been proven that they could affect each other. We designed and implemented genetic algorithm (GA) to optimize kernel parameters and feature subset selection for SVM regression and applied it to the BBB penetration prediction. The results show that our GA/SVM model is more accurate than other currently available log BB models. Therefore, to optimize both SVM parameters and feature subset simultaneously with genetic algorithm is a better approach than other methods that treat the two problems separately. Analysis of our log BB model suggests that carboxylic acid group, polar surface area (PSA)/hydrogen-bonding ability, lipophilicity, and molecular charge play important role in BBB penetration. Among those properties relevant to BBB penetration, lipophilicity could enhance the BBB penetration while all the others are negatively correlated with BBB penetration. PMID:26504797
Improved motion information-based infrared dim target tracking algorithms
NASA Astrophysics Data System (ADS)
Lei, Liu; Zhijian, Huang
2014-11-01
Accurate and fast tracking of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. However, under complex backgrounds, such as clutter, varying illumination, and occlusion, the traditional tracking method often converges to a local maximum and loses the real infrared target. To cope with these problems, three improved tracking algorithm based on motion information are proposed in this paper, namely improved mean shift algorithm, improved Optical flow method and improved Particle Filter method. The basic principles and the implementing procedure of these modified algorithms for target tracking are described. Using these algorithms, the experiments on some real-life IR and color images are performed. The whole algorithm implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying tracking effectiveness and robustness. Meanwhile, it has high tracking efficiency and can be used for real-time tracking.
Auto-focus algorithm based on statistical blur estimation
NASA Astrophysics Data System (ADS)
Kulkarni, Prajit
2013-03-01
Conventional auto-focus techniques in movable-lens camera systems use a measure of image sharpness to determine the lens position that brings the scene into focus. This paper presents a novel wavelet-domain approach to determine the position of best focus. In contrast to current techniques, the proposed algorithm estimates the level of blur in the captured image at each lens position. Image blur is quantified by fitting a Generalized Gaussian Density (GGD) curve to a high-pass version of the image using second-order statistics. The system then moves the lens to the position that yields the least measure of image blur. The algorithm overcomes shortcomings of sharpness-based approaches, namely, the application of large band-pass filters, sensitivity to image noise and need for calibration under different imaging conditions. Since noise has no effect on the proposed blur metric, the algorithm works with a short filter and is devoid of parameter tuning. Furthermore, the algorithm could be simplified to use a single high-pass filter to reduce complexity. These advantages, along with the optimization presented in the paper, make the proposed algorithm very attractive for hardware implementation on cell phones. Experiments prove that the algorithm performs well in the presence of noise as well as resolution and data scaling.
A new root-based direction-finding algorithm
NASA Astrophysics Data System (ADS)
Wasylkiwskyj, Wasyl; Kopriva, Ivica; DoroslovačKi, Miloš; Zaghloul, Amir I.
2007-04-01
Polynomial rooting direction-finding (DF) algorithms are a computationally efficient alternative to search-based DF algorithms and are particularly suitable for uniform linear arrays of physically identical elements provided that mutual interaction among the array elements can be either neglected or compensated for. A popular algorithm in such situations is Root Multiple Signal Classification (Root MUSIC (RM)), wherein the estimation of the directions of arrivals (DOA) requires the computation of the roots of a (2N - 2) -order polynomial, where N represents number of array elements. The DOA are estimated from the L pairs of roots closest to the unit circle, where L represents number of sources. In this paper we derive a modified root polynomial (MRP) algorithm requiring the calculation of only L roots in order to estimate the L DOA. We evaluate the performance of the MRP algorithm numerically and show that it is as accurate as the RM algorithm but with a significantly simpler algebraic structure. In order to demonstrate that the theoretically predicted performance can be achieved in an experimental setting, a decoupled array is emulated in hardware using phase shifters. The results are in excellent agreement with theory.
Wavelets based algorithm for the evaluation of enhanced liver areas
NASA Astrophysics Data System (ADS)
Alvarez, Matheus; Rodrigues de Pina, Diana; Giacomini, Guilherme; Gomes Romeiro, Fernando; Barbosa Duarte, Sérgio; Yamashita, Seizo; de Arruda Miranda, José Ricardo
2014-03-01
Hepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm. 63 computed tomography (CT) slices from 23 patients were assessed. Noncontrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits. A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.
Texture orientation-based algorithm for detecting infrared maritime targets.
Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai
2015-05-20
Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions. PMID:26192503
InGaP-based quantum well solar cells: Growth, structural design, and photovoltaic properties
NASA Astrophysics Data System (ADS)
Hashem, Islam E.; Zachary Carlin, C.; Hagar, Brandon G.; Colter, Peter C.; Bedair, S. M.
2016-03-01
Raising the efficiency ceiling of multi-junction solar cells (MJSCs) through the use of more optimal band gap configurations of next-generation MJSC is crucial for concentrator and space systems. Towards this goal, we propose two strain balanced multiple quantum well (SBMQW) structures to tune the bandgap of InGaP-based solar cells. These structures are based on InxGa1-xAs1-zPz/InyGa1-yP (x > y) and InxGa1-xP/InyGa1-yP (x > y) well/barrier combinations, lattice matched to GaAs in a p-i-n solar cell device. The bandgap of InxGa1-xAs1-zPz/InyGa1-yP can be tuned from 1.82 to 1.65 eV by adjusting the well composition and thickness, which promotes its use as an efficient subcell for next generation five and six junction photovoltaic devices. The thicknesses of wells and barriers are adjusted using a zero net stress balance model to prevent the formation of defects. Thin layers of InGaAsP wells have been grown thermodynamically stable with compositions within the miscibility gap for the bulk alloy. The growth conditions of the two SBMQWs and the individual layers are reported. The structures are characterized and analyzed by optical microscopy, X-ray diffraction, photoluminescence, current-voltage characteristics, and spectral response (external quantum efficiency). The effect of the well number on the excitonic absorption of InGaAsP/InGaP SBMQWs is discussed and analyzed.
Oxygen interstitials and vacancies in LaSrGa3O7-based melilites
NASA Astrophysics Data System (ADS)
Xu, Jungu; Li, Xiaohui; Lu, Fengqi; Fu, Hui; Brown, Craig M.; Kuang, Xiaojun
2015-10-01
The Sr-rich composition of the layered tetrahedral meililite, La0.8Sr1.2Ga3O6.9, was synthesized and a structural investigation on La0.8Sr1.2Ga3O6.9 using neutron powder diffraction revealed a site preference of oxygen vacancies on the bridging oxygen sites of the 4-linked GaO4 tetrahedra. Impedance measurement revealed limited ionic conduction in the oxygen-deficient La0.8Sr1.2Ga3O6.9, presumably associated with oxygen vacancies, which is ~2 orders of magnitude higher than the parent material LaSrGa3O7 but ~3-4 orders of magnitude lower than the interstitial oxide ionic conductivity in La-rich composition, La1.54Sr0.46Ga3O7.27. Low temperature neutron powder diffraction characterization was performed for the oxygen-excess, La-rich composition, La1.54Sr0.46Ga3O7.27, which confirmed the position near the center of the pentagonal tunnels for the oxygen interstitials identified previously using the room temperature data. Solid state 71Ga NMR data collected on these LaSrGa3O7-based materials with stoichometric, excess, and deficient oxygen contents was found not able to distinguish these three compositions. A metastability temperature gap within 850-1280 °C was identified for the oxygen interstitial-conducting La1.54Sr0.46Ga3O7.27. The structures of these oxygen excess and deficient gallate melilites further demonstrate the structural flexibility of the LaSrGa3O7-based layer tetrahedral network.
A Graph Based Backtracking Algorithm for Solving General CSPs
NASA Technical Reports Server (NTRS)
Pang, Wanlin; Goodwin, Scott D.
2003-01-01
Many AI tasks can be formalized as constraint satisfaction problems (CSPs), which involve finding values for variables subject to constraints. While solving a CSP is an NP-complete task in general, tractable classes of CSPs have been identified based on the structure of the underlying constraint graphs. Much effort has been spent on exploiting structural properties of the constraint graph to improve the efficiency of finding a solution. These efforts contributed to development of a class of CSP solving algorithms called decomposition algorithms. The strength of CSP decomposition is that its worst-case complexity depends on the structural properties of the constraint graph and is usually better than the worst-case complexity of search methods. Its practical application is limited, however, since it cannot be applied if the CSP is not decomposable. In this paper, we propose a graph based backtracking algorithm called omega-CDBT, which shares merits and overcomes the weaknesses of both decomposition and search approaches.
A fast image encryption algorithm based on chaotic map
NASA Astrophysics Data System (ADS)
Liu, Wenhao; Sun, Kehui; Zhu, Congxu
2016-09-01
Derived from Sine map and iterative chaotic map with infinite collapse (ICMIC), a new two-dimensional Sine ICMIC modulation map (2D-SIMM) is proposed based on a close-loop modulation coupling (CMC) model, and its chaotic performance is analyzed by means of phase diagram, Lyapunov exponent spectrum and complexity. It shows that this map has good ergodicity, hyperchaotic behavior, large maximum Lyapunov exponent and high complexity. Based on this map, a fast image encryption algorithm is proposed. In this algorithm, the confusion and diffusion processes are combined for one stage. Chaotic shift transform (CST) is proposed to efficiently change the image pixel positions, and the row and column substitutions are applied to scramble the pixel values simultaneously. The simulation and analysis results show that this algorithm has high security, low time complexity, and the abilities of resisting statistical analysis, differential, brute-force, known-plaintext and chosen-plaintext attacks.
LAHS: A novel harmony search algorithm based on learning automata
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Yousefi, Moslem; Abdullah, Abdul Hanan; Darus, Amer Nordin
2013-12-01
This study presents a learning automata-based harmony search (LAHS) for unconstrained optimization of continuous problems. The harmony search (HS) algorithm performance strongly depends on the fine tuning of its parameters, including the harmony consideration rate (HMCR), pitch adjustment rate (PAR) and bandwidth (bw). Inspired by the spur-in-time responses in the musical improvisation process, learning capabilities are employed in the HS to select these parameters based on spontaneous reactions. An extensive numerical investigation is conducted on several well-known test functions, and the results are compared with the HS algorithm and its prominent variants, including the improved harmony search (IHS), global-best harmony search (GHS) and self-adaptive global-best harmony search (SGHS). The numerical results indicate that the LAHS is more efficient in finding optimum solutions and outperforms the existing HS algorithm variants.
NASA Astrophysics Data System (ADS)
Zhou, Mandi; Shu, Jiong; Chen, Zhigang; Ji, Minhe
2012-11-01
Hyperspectral imagery has been widely used in terrain classification for its high resolution. Urban vegetation, known as an essential part of the urban ecosystem, can be difficult to discern due to high similarity of spectral signatures among some land-cover classes. In this paper, we investigate a hybrid approach of the genetic-algorithm tuned fuzzy support vector machine (GA-FSVM) technique and apply it to urban vegetation classification from aerial hyperspectral urban imagery. The approach adopts the genetic algorithm to optimize parameters of support vector machine, and employs the K-nearest neighbor algorithm to calculate the membership function for each fuzzy parameter, aiming to reduce the effects of the isolated and noisy samples. Test data come from push-broom hyperspectral imager (PHI) hyperspectral remote sensing image which partially covers a corner of the Shanghai World Exposition Park, while PHI is a hyper-spectral sensor developed by Shanghai Institute of Technical Physics. Experimental results show the GA-FSVM model generates overall accuracy of 71.2%, outperforming the maximum likelihood classifier with 49.4% accuracy and the artificial neural network method with 60.8% accuracy. It indicates GA-FSVM is a promising model for vegetation classification from hyperspectral urban data, and has good advantage in the application of classification involving abundant mixed pixels and small samples problem.
Influence of piezoelectric fields on InGaN based intermediate band solar cells
NASA Astrophysics Data System (ADS)
Tang, H.; Liu, B.; Wang, T.
2015-01-01
As it is practically infeasible to fabricate multiple-junction InGaN based tandem solar cells due to an intrinsic limit, intermediate-band solar cells (IBSCs) provide an alternative option for the fabrication of single-junction solar cells with their performance potentially equivalent to that of multiple-junction solar cells. InGaN quantum dots (QD) could be used for designing an IBSC structure. More importantly, it is well-known that there exist very strong piezoelectric fields in an InGaN/GaN system with a high indium composition, which becomes more pronounced for InGaN based QDs. The built-in piezoelectric fields can lead to a significant increase in the open circuit voltage and thus improved performance of solar cells, which has not yet been considered in designing III-nitride based solar cells so far. An optimized InGaN based QD-IBSC structure has been designed, combining the major advantages from the IBSC structure and the benefits due to the strong piezoelectric fields. A conversion efficiency, open-circuit voltage and short-circuit current have been calculated, and a highest conversion efficiency of 55.4% is obtained. The combination of the single-junction IBSC structure and the piezoelectric fields paves the way for the fabrication of InGaN based single-junction solar cells with ultra-high energy efficiency.
(GaMn)As: GaAs-based III?V diluted magnetic semiconductors grown by molecular beam epitaxy
NASA Astrophysics Data System (ADS)
Hayashi, T.; Tanaka, M.; Nishinaga, T.; Shimada, H.; Tsuchiya, H.; Otuka, Y.
1997-05-01
We have grown novel III-V diluted magnetic semiconductors, (Ga 1 - xMn x)As, on GaAs substrates by low-temperature molecular beam epitaxy using strong nonequilibrium growth conditions. When the Mn concentration x is relatively low (≲0.08), homogeneous alloy semiconductors, GaMnAs, are grown with zincblende structure and slightly larger lattice constants than that of GaAs, whereas inhomogeneous structures with zincblende GaMnAs (or GaAs) plus hexagonal MnAs are formed when x is relatively high. Magnetization measurements indicate that the homogeneous GaMnAs films have ferromagnetic ordering at low temperature.
HVPE-GaN growth on GaN-based advanced substrates by Smart CutTM
NASA Astrophysics Data System (ADS)
Iwinska, Malgorzata; Amilusik, Mikolaj; Fijalkowski, Michal; Sochacki, Tomasz; Lucznik, Boleslaw; Grzanka, Ewa; Litwin-Staszewska, Elzbieta; Nowakowska-Siwinska, Anna; Grzegory, Izabella; Guiot, Eric; Caulmilone, Raphael; Seiss, Martin; Mrotzek, Tobias; Bockowski, Michal
2016-02-01
Advanced Substrates consist of a 200-nm-thick GaN layer bonded to a handler wafer. The thin layer is separated from source material by Smart CutTM technology. GaN on Sapphire Advanced Substrates were used as seeds in HVPE-GaN growth. Unintentionally doped and silicon-doped GaN layers were crystallized. Free-standing HVPE-GaN was characterized by X-ray diffraction, defect selective etching, photo-etching, Hall method, Raman spectroscopy, and secondary ion mass spectrometry. The results were compared to HVPE-GaN grown on standard MOCVD-GaN/sapphire templates.
NIC-based Reduction Algorithms for Large-scale Clusters
Petrini, F; Moody, A T; Fernandez, J; Frachtenberg, E; Panda, D K
2004-07-30
Efficient algorithms for reduction operations across a group of processes are crucial for good performance in many large-scale, parallel scientific applications. While previous algorithms limit processing to the host CPU, we utilize the programmable processors and local memory available on modern cluster network interface cards (NICs) to explore a new dimension in the design of reduction algorithms. In this paper, we present the benefits and challenges, design issues and solutions, analytical models, and experimental evaluations of a family of NIC-based reduction algorithms. Performance and scalability evaluations were conducted on the ASCI Linux Cluster (ALC), a 960-node, 1920-processor machine at Lawrence Livermore National Laboratory, which uses the Quadrics QsNet interconnect. We find NIC-based reductions on modern interconnects to be more efficient than host-based implementations in both scalability and consistency. In particular, at large-scale--1812 processes--NIC-based reductions of small integer and floating-point arrays provided respective speedups of 121% and 39% over the host-based, production-level MPI implementation.
NASA Astrophysics Data System (ADS)
Yu, Xuezhe; Li, Lixia; Wang, Hailong; Xiao, Jiaxing; Shen, Chao; Pan, Dong; Zhao, Jianhua
2016-05-01
For the epitaxial growth of Ga-based III-V semiconductor nanowires (NWs) on Si, Ga droplets could provide a clean and compatible solution in contrast to the common Au catalyst. However, the use of Ga droplets is rather limited except for that in Ga-catalyzed GaAs NW studies in a relatively narrow growth temperature (Ts) window around 620 °C on Si. In this paper, we have investigated the two-step growth of Ga-catalyzed III-V NWs on Si (111) substrates by molecular-beam epitaxy. First, by optimizing the surface oxide, vertically aligned GaAs NWs with a high yield are obtained at Ts = 620 °C. Then a two-temperature procedure is adopted to preserve Ga droplets at lower Ts, which leads to an extension of Ts down to 500 °C for GaAs NWs. Based on this procedure, systematic morphological and structural studies for Ga-catalyzed GaAs NWs in the largest Ts range could be presented. Then within the same growth scheme, for the first time, we demonstrate Ga-catalyzed GaAs/GaSb heterostructure NWs. These GaSb NWs are axially grown on the GaAs NW sections and are pure zinc-blende single crystals. Compositional measurements confirm that the catalyst particles indeed mainly consist of Ga and GaSb sections are of high purity but with a minor composition of As. In the end, we present GaAsSb NW growth with a tunable Sb composition. Our results provide useful information for the controllable synthesis of multi-compositional Ga-catalyzed III-V semiconductor NWs on Si for heterogeneous integration.For the epitaxial growth of Ga-based III-V semiconductor nanowires (NWs) on Si, Ga droplets could provide a clean and compatible solution in contrast to the common Au catalyst. However, the use of Ga droplets is rather limited except for that in Ga-catalyzed GaAs NW studies in a relatively narrow growth temperature (Ts) window around 620 °C on Si. In this paper, we have investigated the two-step growth of Ga-catalyzed III-V NWs on Si (111) substrates by molecular-beam epitaxy. First, by
Nonuniformity correction algorithm based on Gaussian mixture model
NASA Astrophysics Data System (ADS)
Mou, Xin-gang; Zhang, Gui-lin; Hu, Ruo-lan; Zhou, Xiao
2011-08-01
As an important tool to acquire information of target scene, infrared detector is widely used in imaging guidance field. Because of the limit of material and technique, the performance of infrared imaging system is known to be strongly affected by the spatial nonuniformity in the photoresponse of the detectors in the array. Temporal highpass filter(THPF) is a popular adaptive NUC algorithm because of its simpleness and effectiveness. However, there still exists the problem of ghosting artifact in the algorithms caused by blind update of parameters, and the performance is noticeably degraded when the methods are applied over scenes with lack of motion. In order to tackle with this problem, a novel adaptive NUC algorithm based on Gaussian mixed model (GMM) is put forward according to traditional THPF. The drift of the detectors is assumed to obey a single Gaussian distribution, and the update of the parameters is selectively performed based on the scene. GMM is applied in the new algorithm for background modeling, in which the background is updated selectively so as to avoid the influence of the foreground target on the update of the background, thus eliminating the ghosting artifact. The performance of the proposed algorithm is evaluated with infrared image sequences with simulated and real fixed-pattern noise. The results show a more reliable fixed-pattern noise reduction, tracking the parameter drift, and presenting a good adaptability to scene changes.
Constrained Multiobjective Optimization Algorithm Based on Immune System Model.
Qian, Shuqu; Ye, Yongqiang; Jiang, Bin; Wang, Jianhong
2016-09-01
An immune optimization algorithm, based on the model of biological immune system, is proposed to solve multiobjective optimization problems with multimodal nonlinear constraints. First, the initial population is divided into feasible nondominated population and infeasible/dominated population. The feasible nondominated individuals focus on exploring the nondominated front through clone and hypermutation based on a proposed affinity design approach, while the infeasible/dominated individuals are exploited and improved via the simulated binary crossover and polynomial mutation operations. And then, to accelerate the convergence of the proposed algorithm, a transformation technique is applied to the combined population of the above two offspring populations. Finally, a crowded-comparison strategy is used to create the next generation population. In numerical experiments, a series of benchmark constrained multiobjective optimization problems are considered to evaluate the performance of the proposed algorithm and it is also compared to several state-of-art algorithms in terms of the inverted generational distance and hypervolume indicators. The results indicate that the new method achieves competitive performance and even statistically significant better results than previous algorithms do on most of the benchmark suite. PMID:26285230
NASA Astrophysics Data System (ADS)
Maiboroda, I. O.; Andreev, A. A.; Perminov, P. A.; Fedorov, Yu. V.; Zanaveskin, M. L.
2014-06-01
Specific features of how nonalloyed ohmic contacts to the 2D conducting channel of high-electron-mobility transistors based on AlGaN/(AlN)/GaN heterostructures are fabricated via deposition of heavily doped n +-GaN through a SiO2 mask by ammonia molecular-beam epitaxy have been studied. The technique developed makes it possible to obtain specific resistances of contacts to the 2D gas as low as 0.11 Ω mm on various types of Ga-face nitride heterostructures, which are several times lower than the resistance of conventional alloyed ohmic contacts.
Lin, Mai; Ranganathan, David; Mori, Tetsuya; Hagooly, Aviv; Rossin, Raffaella; Welch, Michael J; Lapi, Suzanne E
2012-10-01
Interest in using (68)Ga is rapidly increasing for clinical PET applications due to its favorable imaging characteristics and increased accessibility. The focus of this study was to provide our long-term evaluations of the two TiO(2)-based (68)Ge/(68)Ga generators and develop an optimized automation strategy to synthesize [(68)Ga]DOTATOC by using HEPES as a buffer system. This data will be useful in standardizing the evaluation of (68)Ge/(68)Ga generators and automation strategies to comply with regulatory issues for clinical use. PMID:22897970
Silva, Leonardo W. T.; Barros, Vitor F.; Silva, Sandro G.
2014-01-01
In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence. PMID:25196013
Deng, Li; Wang, Guohua; Yu, Suihuai
2016-01-01
In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745
Deng, Li; Wang, Guohua; Yu, Suihuai
2016-01-01
In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745
Soil Moisture Algorithm Validation with Ground Based Networks
Technology Transfer Automated Retrieval System (TEKTRAN)
Validation satellite-based soil moisture algorithms and products is particularly challenging due to the disparity of scales of the two observation methods, conventional measurements of soil moisture are made at a point whereas satellite sensors provide an integrated area/volume value over a large ar...
Density shrinking algorithm for community detection with path based similarity
NASA Astrophysics Data System (ADS)
Wu, Jianshe; Hou, Yunting; Jiao, Yang; Li, Yong; Li, Xiaoxiao; Jiao, Licheng
2015-09-01
Community structure is ubiquitous in real world complex networks. Finding the communities is the key to understand the functions of those networks. A lot of works have been done in designing algorithms for community detection, but it remains a challenge in the field. Traditional modularity optimization suffers from the resolution limit problem. Recent researches show that combining the density based technique with the modularity optimization can overcome the resolution limit and an efficient algorithm named DenShrink was provided. The main procedure of DenShrink is repeatedly finding and merging micro-communities (broad sense) into super nodes until they cannot merge. Analyses in this paper show that if the procedure is replaced by finding and merging only dense pairs, both of the detection accuracy and runtime can be obviously improved. Thus an improved density-based algorithm: ImDS is provided. Since the time complexity, path based similarity indexes are difficult to be applied in community detection for high performance. In this paper, the path based Katz index is simplified and used in the ImDS algorithm.
Optimal fractional order PID design via Tabu Search based algorithm.
Ateş, Abdullah; Yeroglu, Celaleddin
2016-01-01
This paper presents an optimization method based on the Tabu Search Algorithm (TSA) to design a Fractional-Order Proportional-Integral-Derivative (FOPID) controller. All parameter computations of the FOPID employ random initial conditions, using the proposed optimization method. Illustrative examples demonstrate the performance of the proposed FOPID controller design method. PMID:26652128
Measuring Disorientation Based on the Needleman-Wunsch Algorithm
ERIC Educational Resources Information Center
Güyer, Tolga; Atasoy, Bilal; Somyürek, Sibel
2015-01-01
This study offers a new method to measure navigation disorientation in web based systems which is powerful learning medium for distance and open education. The Needleman-Wunsch algorithm is used to measure disorientation in a more precise manner. The process combines theoretical and applied knowledge from two previously distinct research areas,…
Avci, Derya; Dogantekin, Akif
2016-01-01
Parkinson disease is a major public health problem all around the world. This paper proposes an expert disease diagnosis system for Parkinson disease based on genetic algorithm- (GA-) wavelet kernel- (WK-) Extreme Learning Machines (ELM). The classifier used in this paper is single layer neural network (SLNN) and it is trained by the ELM learning method. The Parkinson disease datasets are obtained from the UCI machine learning database. In wavelet kernel-Extreme Learning Machine (WK-ELM) structure, there are three adjustable parameters of wavelet kernel. These parameters and the numbers of hidden neurons play a major role in the performance of ELM. In this study, the optimum values of these parameters and the numbers of hidden neurons of ELM were obtained by using a genetic algorithm (GA). The performance of the proposed GA-WK-ELM method is evaluated using statical methods such as classification accuracy, sensitivity and specificity analysis, and ROC curves. The calculated highest classification accuracy of the proposed GA-WK-ELM method is found as 96.81%. PMID:27274882
Avci, Derya; Dogantekin, Akif
2016-01-01
Parkinson disease is a major public health problem all around the world. This paper proposes an expert disease diagnosis system for Parkinson disease based on genetic algorithm- (GA-) wavelet kernel- (WK-) Extreme Learning Machines (ELM). The classifier used in this paper is single layer neural network (SLNN) and it is trained by the ELM learning method. The Parkinson disease datasets are obtained from the UCI machine learning database. In wavelet kernel-Extreme Learning Machine (WK-ELM) structure, there are three adjustable parameters of wavelet kernel. These parameters and the numbers of hidden neurons play a major role in the performance of ELM. In this study, the optimum values of these parameters and the numbers of hidden neurons of ELM were obtained by using a genetic algorithm (GA). The performance of the proposed GA-WK-ELM method is evaluated using statical methods such as classification accuracy, sensitivity and specificity analysis, and ROC curves. The calculated highest classification accuracy of the proposed GA-WK-ELM method is found as 96.81%. PMID:27274882
Yu, Xuezhe; Li, Lixia; Wang, Hailong; Xiao, Jiaxing; Shen, Chao; Pan, Dong; Zhao, Jianhua
2016-05-19
For the epitaxial growth of Ga-based III-V semiconductor nanowires (NWs) on Si, Ga droplets could provide a clean and compatible solution in contrast to the common Au catalyst. However, the use of Ga droplets is rather limited except for that in Ga-catalyzed GaAs NW studies in a relatively narrow growth temperature (Ts) window around 620 °C on Si. In this paper, we have investigated the two-step growth of Ga-catalyzed III-V NWs on Si (111) substrates by molecular-beam epitaxy. First, by optimizing the surface oxide, vertically aligned GaAs NWs with a high yield are obtained at Ts = 620 °C. Then a two-temperature procedure is adopted to preserve Ga droplets at lower Ts, which leads to an extension of Ts down to 500 °C for GaAs NWs. Based on this procedure, systematic morphological and structural studies for Ga-catalyzed GaAs NWs in the largest Ts range could be presented. Then within the same growth scheme, for the first time, we demonstrate Ga-catalyzed GaAs/GaSb heterostructure NWs. These GaSb NWs are axially grown on the GaAs NW sections and are pure zinc-blende single crystals. Compositional measurements confirm that the catalyst particles indeed mainly consist of Ga and GaSb sections are of high purity but with a minor composition of As. In the end, we present GaAsSb NW growth with a tunable Sb composition. Our results provide useful information for the controllable synthesis of multi-compositional Ga-catalyzed III-V semiconductor NWs on Si for heterogeneous integration. PMID:27194599
GaN-based high contrast grating surface-emitting lasers
NASA Astrophysics Data System (ADS)
Wu, Tzeng-Tsong; Wu, Shu-Hsien; Lu, Tien-Chang; Wang, Shing-Chung
2013-02-01
GaN-based high contrast grating surface-emitting lasers (HCG SELs) with AlN/GaN distributed Bragg reflectors were reported. The device exhibited a low threshold pumping energy density of about 0.56 mJ/cm2 and the lasing wavelength was at 393.6 nm with a high degree of polarization of 73% at room temperature. The specific lasing mode and polarization characterisitcs agreed well with the theoretical modeling. The low threshold characteristics of our GaN-based HCG SELs faciliated by the Fano resonance can serve as the best candidate in blue surface emitting laser sources.
Comparative efficiency analysis of GaN-based light-emitting diodes and laser diodes
NASA Astrophysics Data System (ADS)
Piprek, Joachim
2016-07-01
Nobel laureate Shuji Nakamura predicted in 2014 that GaN-based laser diodes are the future of solid state lighting. However, blue GaN-lasers still exhibit less than 40% wall-plug efficiency, while some GaN-based blue light-emitting diodes exceed 80%. This paper investigates non-thermal reasons behind this difference. The inherently poor hole conductivity of the Mg-doped waveguide cladding layer of laser diodes is identified as main reason for their low electrical-to-optical energy conversion efficiency.
GaN-based surface-emitting lasers using high-contrast grating
NASA Astrophysics Data System (ADS)
Lu, Tien-Chang; Wang, Shing-Chung; Wu, Tzeng-Tsong; Wu, Shu-Hsien; Syu, Yu-Cheng
2014-02-01
GaN-based surface-emitting lasers (SELs) using high contrast grating (HCG) with AlN/GaN distributed Bragg reflectors were reported. The laser device achieved a threshold energy density of about 0.56 mJ/cm2 and the lasing wavelength was at 393.6 nm with a high degree of polarization of 73% at room temperature. The resonant mode and polarization characteristics matched to the theoretical prediction. GaN-based SELs using HCG supported by the Fano resonance can be potential for development of blue surface emitting laser sources
Thickness dependence on the optoelectronic properties of multilayered GaSe based photodetector
NASA Astrophysics Data System (ADS)
Ko, Pil Ju; Abderrahmane, Abdelkader; Takamura, Tsukasa; Kim, Nam-Hoon; Sandhu, Adarsh
2016-08-01
Two-dimensional (2D) layered materials exhibit unique optoelectronic properties at atomic thicknesses. In this paper, we fabricated metal–semiconductor–metal based photodetectors using layered gallium selenide (GaSe) with different thicknesses. The electrical and optoelectronic properties of the photodetectors were studied, and these devices showed good electrical characteristics down to GaSe flake thicknesses of 30 nm. A photograting effect was observed in the absence of a gate voltage, thereby implying a relatively high photoresponsivity. Higher values of the photoresponsivity occurred for thicker layers of GaSe with a maximum value 0.57 AW‑1 and external quantum efficiency of of 132.8%, and decreased with decreasing GaSe flake thickness. The detectivity was 4.05 × 1010 cm Hz1/2 W‑1 at 532 nm laser wavelength, underscoring that GaSe is a promising p-type 2D material for photodetection applications in the visible spectrum.
Detection of parametric curves based on genetic algorithm
NASA Astrophysics Data System (ADS)
Li, Haimin; Wu, Chengke
1998-09-01
Detection of curves with special shapes has been put on great interest in the fields of image processing and recognition. Some commonly used algorithms such as Hough Transform and Generalized Radon Transform are global search methods. When the number of parameters increases, their efficiencies decrease rapidly because of the expansion of parameter space. To solve this problem, a new method based on Genetic Algorithm is presented which combines a local search procedure to improve its performance. Experimental results show that the proposed method improves search efficiency greatly.
Research of Electronic Image Stabilization Algorithm Based on Orbital Character
NASA Astrophysics Data System (ADS)
Xian, Xiaodong; Hou, Peipei; Liang, Shan; Gan, Ping
The monocular vision is the key technology for the locomotive anti-collision warning system. The range precision influence the system's performance. In this paper according to the question of video jitter result in the accuracy reducing, proposes a new EIS algorithm based on the orbital characteristic, through extracting and matching partial feature template obtained the global movement vector. Treat the partial feature template instead of treating the global image, speed of the system is improved obviously. The result of simulation indicates that this algorithm can effectively eliminate image migration which produces because of the video jitter, has solved the deviation of ranging precision, and satisfies the real-time request of system.
Multiple Lookup Table-Based AES Encryption Algorithm Implementation
NASA Astrophysics Data System (ADS)
Gong, Jin; Liu, Wenyi; Zhang, Huixin
Anew AES (Advanced Encryption Standard) encryption algorithm implementation was proposed in this paper. It is based on five lookup tables, which are generated from S-box(the substitution table in AES). The obvious advantages are reducing the code-size, improving the implementation efficiency, and helping new learners to understand the AES encryption algorithm and GF(28) multiplication which are necessary to correctly implement AES[1]. This method can be applied on processors with word length 32 or above, FPGA and others. And correspondingly we can implement it by VHDL, Verilog, VB and other languages.
An Optimal Seed Based Compression Algorithm for DNA Sequences
Gopalakrishnan, Gopakumar; Karunakaran, Muralikrishnan
2016-01-01
This paper proposes a seed based lossless compression algorithm to compress a DNA sequence which uses a substitution method that is similar to the LempelZiv compression scheme. The proposed method exploits the repetition structures that are inherent in DNA sequences by creating an offline dictionary which contains all such repeats along with the details of mismatches. By ensuring that only promising mismatches are allowed, the method achieves a compression ratio that is at par or better than the existing lossless DNA sequence compression algorithms. PMID:27555868
Temporal Response Measurements of GaAs-Based Photocathodes
NASA Astrophysics Data System (ADS)
Honda, Yosuke; Matsuba, Shunya; Jin, Xiuguang; Miyajima, Tsukasa; Yamamoto, Masahiro; Uchiyama, Takashi; Kuwahara, Makoto; Takeda, Yoshikazu
2013-08-01
It is well known that a negative electron affinity GaAs photocathode shows a moderate temporal response when excited by a laser pulse of wavelength close to its band gap energy. We show here that the temporal response can be estimated using a diffusion model that describes the internal transport of the conduction electrons. Using a transverse deflection cavity system, we measured the temporal profile of the electron bunch generated by a DC photocathode gun illuminated by a ps pulsed laser. A systematic set of measurements of GaAs cathodes with various active layer thicknesses and boundary conditions confirmed that the observed temporal response is well understood by the diffusion model calculation.
InGaN-based thin film solar cells: Epitaxy, structural design, and photovoltaic properties
Sang, Liwen; Liao, Meiyong; Koide, Yasuo; Sumiya, Masatomo
2015-03-14
In{sub x}Ga{sub 1−x}N, with the tunable direct bandgaps from ultraviolet to near infrared region, offers a promising candidate for the high-efficiency next-generation thin-film photovoltaic applications. Although the adoption of thick InGaN film as the active region is desirable to obtain efficient light absorption and carrier collection compared to InGaN/GaN quantum wells structure, the understanding on the effect from structural design is still unclear due to the poor-quality InGaN films with thickness and difficulty of p-type doping. In this paper, we comprehensively investigate the effects from film epitaxy, doping, and device structural design on the performances of the InGaN-based solar cells. The high-quality InGaN thick film is obtained on AlN/sapphire template, and p-In{sub 0.08}Ga{sub 0.92}N is achieved with a high hole concentration of more than 10{sup 18 }cm{sup −3}. The dependence of the photovoltaic performances on different structures, such as active regions and p-type regions is analyzed with respect to the carrier transport mechanism in the dark and under illumination. The strategy of improving the p-i interface by using a super-thin AlN interlayer is provided, which successfully enhances the performance of the solar cells.
Fabrication of photonic crystal circuits based on GaN ultrathin membranes by maskless lithography
NASA Astrophysics Data System (ADS)
Volciuc, Olesea; Braniste, Tudor; Sergentu, Vladimir; Ursaki, Veaceslav; Tiginyanu, Ion M.; Gutowski, Jürgen
2015-06-01
We report on maskless fabrication of photonic crystal (PhC) circuits based on ultrathin (d ~ 15 nm) nanoperforated GaN membranes exhibiting a triangular lattice arrangement of holes with diameters of 150 nm. In recent years, we have proposed and developed a cost-effective technology for GaN micro- and nanostructuring, the so-called surface charge lithography (SCL), which opened wide possibilities for a controlled fabrication of GaN ultrathin membranes. SCL is a maskless approach based on direct writing of negative charges on the surface of a semiconductor by a focused ion beam (FIB). These charges shield the material against photo-electrochemical (PEC) etching. Ultrathin GaN membranes suspended on specially designed GaN microstructures have been fabricated using a technological route based on SCL with two selected doses of ion beam treatment. Calculation of the dispersion law in nanoperforated membranes in the approximation of scalar waves is indicative of the occurrence of surface and bulk modes, and there is a range of frequencies where only surface modes can exist. Advantages of the occurrence of two types of modes in ultrathin nanoperforated GaN membranes from the point of view of their incorporation in photonic and optoelectronic integrated circuits are discussed. Along with this, we present the results of a comparative analysis of persistent photoconductivity (PPC) and optical quenching (OQ) effects occurring in continuous and nanoperforated ultrathin GaN suspended membranes, and assess the mechanisms behind these phenomena.
Design of synthetic biological logic circuits based on evolutionary algorithm.
Chuang, Chia-Hua; Lin, Chun-Liang; Chang, Yen-Chang; Jennawasin, Tanagorn; Chen, Po-Kuei
2013-08-01
The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose. PMID:23919952
Robust illumination-invariant tracking algorithm based on HOGs
NASA Astrophysics Data System (ADS)
Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.
2015-09-01
Common tracking systems are usually affected by environmental and technical interferences such as non-uniform illumination, sensors' noise, geometrical scene distortion, etc. Among these issues, the former is particularly interesting because it destroys important spatial characteristics of objects in observed scenes. We propose a two-step tracking algorithm: first, preprocessing locally normalizes the illumination difference between the target object and observed frames; second, the normalized object is tracked by means of a designed template structure based on histograms of oriented gradients and kinematic prediction model. The algorithm performance is tested in terms of recognition and localization errors in real scenarios. In order to achieve high rate of the processing, we use GPU parallel processing technologies. Finally, our algorithm is compared with other state-of-the-art trackers.
A Multi-Scale Settlement Matching Algorithm Based on ARG
NASA Astrophysics Data System (ADS)
Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia
2016-06-01
Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
An ellipse detection algorithm based on edge classification
NASA Astrophysics Data System (ADS)
Yu, Liu; Chen, Feng; Huang, Jianming; Wei, Xiangquan
2015-12-01
In order to enhance the speed and accuracy of ellipse detection, an ellipse detection algorithm based on edge classification is proposed. Too many edge points are removed by making edge into point in serialized form and the distance constraint between the edge points. It achieves effective classification by the criteria of the angle between the edge points. And it makes the probability of randomly selecting the edge points falling on the same ellipse greatly increased. Ellipse fitting accuracy is significantly improved by the optimization of the RED algorithm. It uses Euclidean distance to measure the distance from the edge point to the elliptical boundary. Experimental results show that: it can detect ellipse well in case of edge with interference or edges blocking each other. It has higher detecting precision and less time consuming than the RED algorithm.
An ordinary differential equation based solution path algorithm.
Wu, Yichao
2011-01-01
Efron, Hastie, Johnstone and Tibshirani (2004) proposed Least Angle Regression (LAR), a solution path algorithm for the least squares regression. They pointed out that a slight modification of the LAR gives the LASSO (Tibshirani, 1996) solution path. However it is largely unknown how to extend this solution path algorithm to models beyond the least squares regression. In this work, we propose an extension of the LAR for generalized linear models and the quasi-likelihood model by showing that the corresponding solution path is piecewise given by solutions of ordinary differential equation systems. Our contribution is twofold. First, we provide a theoretical understanding on how the corresponding solution path propagates. Second, we propose an ordinary differential equation based algorithm to obtain the whole solution path. PMID:21532936
Optimization algorithm based characterization scheme for tunable semiconductor lasers.
Chen, Quanan; Liu, Gonghai; Lu, Qiaoyin; Guo, Weihua
2016-09-01
In this paper, an optimization algorithm based characterization scheme for tunable semiconductor lasers is proposed and demonstrated. In the process of optimization, the ratio between the power of the desired frequency and the power except of the desired frequency is used as the figure of merit, which approximately represents the side-mode suppression ratio. In practice, we use tunable optical band-pass and band-stop filters to obtain the power of the desired frequency and the power except of the desired frequency separately. With the assistance of optimization algorithms, such as the particle swarm optimization (PSO) algorithm, we can get stable operation conditions for tunable lasers at designated frequencies directly and efficiently. PMID:27607701
Photoinduced effect in Ga Ge S based thin films
NASA Astrophysics Data System (ADS)
Messaddeq, S. H.; Li, M. Siu; Inoue, S.; Ribeiro, S. J. L.; Messaddeq, Y.
2006-10-01
Glassy films of Ga 10Ge 25S 65 with 4 μm thickness were deposited on quartz substrates by electron beam evaporation. Photoexpansion (PE) (photoinduced increase in volume) and photobleaching (PB) (blue shift of the bandgap) effects have been examined. The exposed areas have been analyzed using perfilometer and an expansion of 1.7 μm (Δ V/ V ≈ 30%) is observed for composition Ga 10Ge 25S 65 exposed during 180 min and 3 mW/cm 2 power density. The optical absorption edge measured for the film Ge 25Ga 10S 65 above and below the bandgap show that the blue shift of the gap by below bandgap photon illumination is considerable higher (Δ Eg = 440 meV) than Δ Eg induced by above bandgap illumination (Δ Eg = 190 meV). The distribution of the refraction index profile showed a negative change of the refraction index in the irradiated samples (Δ n = -0.6). The morphology was examined using a scanning electron microscopy (SEM). The chemical compositions measured using an energy dispersive analyzer (EDX) indicate an increase of the oxygen atoms into the irradiated area. Using a Lloyd's mirror setup for continuous wave holography it was possible to record holographic gratings using the photoinduced effects that occur in them. Diffraction efficiency up to 25% was achieved for the recorded gratings and atomic force microscopy images are presented.
Validation of Patellar Stabilization Surgical Algorithm Based on Congruence
Kejriwal, Ritwik; Dalrymple, Rhydian; Annear, Peter
2016-01-01
Background: Multiple algorithms exist for proximal and/or distal stabilisation surgery for patellar instability with no consensus in the literature. Aim: To validate our surgical algorithm based on patellofemoral congruence for patellar instability. Algorithm: Once patellar stabilization surgery is clinically indicated, we determine patellofemoral congruence abnormality based on quadriceps active CT and intraoperative arthroscopic assessment. Arthroscopic lateral release is carried out if indicated. For patients with minimal incongruence post lateral release, MPFL reconstruction alone (MPFL group) is performed, and we perform tibial tubercle transfer and MPFL reconstruction (TTT group) for significant incongruence Methods: Retrospective study with prospective follow up of patients operated on between 2008 and 2015. We excluded patients with skeletal immaturity, previous patellofemoral surgery, and distalisation of tibial tubercle. Chart review, pre and post operative quadriceps active CT, Kujala score, and patient’s subjective stability analysed. Results: 98 patients were reviewed with mean follow up 37 weeks. 14 patients had MPFL alone. Recurrence of instability occurred in 4% of patients, all in TTT group. Reoperation rate was 19%, almost all in TTT group, with removal of hardware being the most common reason. There was no significant difference in TTTG between the two groups on pre operative CT measurement. Conclusion: Patellar stabilization surgical algorithm based on congruence is valid in preventing further instability. Reoperation rate is high due to majority of patients receiving TTT procedure.
Evolving Stochastic Learning Algorithm based on Tsallis entropic index
NASA Astrophysics Data System (ADS)
Anastasiadis, A. D.; Magoulas, G. D.
2006-03-01
In this paper, inspired from our previous algorithm, which was based on the theory of Tsallis statistical mechanics, we develop a new evolving stochastic learning algorithm for neural networks. The new algorithm combines deterministic and stochastic search steps by employing a different adaptive stepsize for each network weight, and applies a form of noise that is characterized by the nonextensive entropic index q, regulated by a weight decay term. The behavior of the learning algorithm can be made more stochastic or deterministic depending on the trade off between the temperature T and the q values. This is achieved by introducing a formula that defines a time-dependent relationship between these two important learning parameters. Our experimental study verifies that there are indeed improvements in the convergence speed of this new evolving stochastic learning algorithm, which makes learning faster than using the original Hybrid Learning Scheme (HLS). In addition, experiments are conducted to explore the influence of the entropic index q and temperature T on the convergence speed and stability of the proposed method.
Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation
Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi
2015-01-01
Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it. PMID:26221133
A novel Retinex algorithm based on alternating direction optimization
NASA Astrophysics Data System (ADS)
Fu, Xueyang; Lin, Qin; Guo, Wei; Huang, Yue; Zeng, Delu; Ding, Xinghao
2013-10-01
The goal of the Retinex theory is to removed the effects of illumination from the observed images. To address this typical ill-posed inverse problem, many existing Retinex algorithms obtain an enhanced image by using different assumptions either on the illumination or on the reflectance. One significant limitation of these Retinex algorithms is that if the assumption is false, the result is unsatisfactory. In this paper, we firstly build a Retinex model which includes two variables: the illumination and the reflectance. We propose an efficient and effective algorithm based on alternating direction optimization to solve this problem where FFT (Fast Fourier Transform) is used to speed up the computation. Comparing with most existing Retinex algorithms, the proposed method solve the illumination image and reflectance image without converting images to the logarithmic domain. One of the advantages in this paper is that, unlike other traditional Retinex algorithms, our method can simultaneously estimate the illumination image and the reflectance image, the later of which is the ideal image without the illumination effect. Since our method can directly separate the illumination and the reflectance, and the two variables constrain each other mutually in the computing process, the result is robust to some degree. Another advantage is that our method has less computational cost and can be applied to real-time processing.
Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation.
Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi
2015-01-01
Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it. PMID:26221133
NASA Astrophysics Data System (ADS)
Zhu, Li; He, Yongxiang; Xue, Haidong; Chen, Leichen
Traditional genetic algorithms (GA) displays a disadvantage of early-constringency in dealing with scheduling problem. To improve the crossover operators and mutation operators self-adaptively, this paper proposes a self-adaptive GA at the target of multitask scheduling optimization under limited resources. The experiment results show that the proposed algorithm outperforms the traditional GA in evolutive ability to deal with complex task scheduling optimization.
Measurement Theory in Deutsch's Algorithm Based on the Truth Values
NASA Astrophysics Data System (ADS)
Nagata, Koji; Nakamura, Tadao
2016-08-01
We propose a new measurement theory, in qubits handling, based on the truth values, i.e., the truth T (1) for true and the falsity F (0) for false. The results of measurement are either 0 or 1. To implement Deutsch's algorithm, we need both observability and controllability of a quantum state. The new measurement theory can satisfy these two. Especially, we systematically describe our assertion based on more mathematical analysis using raw data in a thoughtful experiment.
NASA Astrophysics Data System (ADS)
Salih, A. L.; Mühlbauer, M.; Grumpe, A.; Pasckert, J. H.; Wöhler, C.; Hiesinger, H.
2016-06-01
The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes very time-consuming for large surface areas and/or high image resolution. With increasing availability of high-resolution (nearly) global image mosaics of planetary surfaces, a variety of automated methods for the detection of craters based on image data and/or topographic data have been developed. In this contribution a template-based crater detection algorithm is used which analyses image data acquired under known illumination conditions. Its results are used to establish the CSFD for the examined area, which is then used to estimate the absolute model age of the surface. The detection threshold of the automatic crater detection algorithm is calibrated based on a region with available manually determined CSFD such that the age inferred from the manual crater counts corresponds to the age inferred from the automatic crater detection results. With this detection threshold, the automatic crater detection algorithm can be applied to a much larger surface region around the calibration area. The proposed age estimation method is demonstrated for a Kaguya Terrain Camera image mosaic of 7.4 m per pixel resolution of the floor region of the lunar crater Tsiolkovsky, which consists of dark and flat mare basalt and has an area of nearly 10,000 km2. The region used for calibration, for which manual crater counts are available, has an area of 100 km2. In order to obtain a spatially resolved age map, CSFDs and surface ages are computed for overlapping quadratic regions of about 4.4 x 4.4 km2 size offset by a step width of 74 m. Our constructed surface age map of the floor of Tsiolkovsky shows age values of typically 3.2-3.3 Ga, while for small regions lower (down to 2.9 Ga) and higher
Correlation on GaN epilayer quality and strain in GaN-based LEDs grown on 4-in. Si(1 1 1) substrate
NASA Astrophysics Data System (ADS)
Zhu, Youhua; Wang, Meiyu; Shi, Min; Huang, Jing; Zhu, Xiaojun; Yin, Haihong; Guo, Xinglong; Egawa, Takashi
2015-09-01
GaN-based LEDs with different thickness of n-GaN have been grown on 4-in. Si(1 1 1) substrate by metal-organic chemical vapor deposition. Quality of GaN epilayer has been evaluated by X-ray diffraction (XRD). Strain information in the structure has been directly investigated by means of micro-Raman scattering. It can be concluded that the compressive strain has varied to a tensile one with increasing n-GaN thickness from 0.5 to 2.0 μm. As a result, in a sample with a 2 μm n-GaN thickness, the tensile stress of GaN epilayer was calculated to be 0.44 GPa. Moreover, the strain states of GaN epilayer have been revealed from the variations of its a- and c-lattice constants, which have been calculated using XRD results. In addition, emission peak shift of GaN epilayer has been confirmed by cathodoluminescence measurement, and light output power of LEDs has also been measured. Nevertheless, some correlations in this study would inspire researcher to design much more reasonable GaN-LEDs structures in future.
NASA Astrophysics Data System (ADS)
Gang-Cheng, Jiao; Zheng-Tang, Liu; Hui, Guo; Yi-Jun, Zhang
2016-04-01
In order to develop the photodetector for effective blue–green response, the 18-mm-diameter vacuum image tube combined with the transmission-mode Al0.7Ga0.3As0.9 P 0.1/GaAs0.9 P 0.1 photocathode grown by molecular beam epitaxy is tentatively fabricated. A comparison of photoelectric property, spectral characteristic and performance parameter between the transmission-mode GaAsP-based and blue-extended GaAs-based photocathodes shows that the GaAsP-based photocathode possesses better absorption and higher quantum efficiency in the blue–green waveband, combined with a larger surface electron escape probability. Especially, the quantum efficiency at 532 nm for the GaAsP-based photocathode achieves as high as 59%, nearly twice that for the blue-extended GaAs-based one, which would be more conducive to the underwater range-gated imaging based on laser illumination. Moreover, the simulation results show that the favorable blue–green response can be achieved by optimizing the emission-layer thickness in a range of 0.4 μm–0.6 μm. Project supported by the National Natural Science Foundation of China (Grant No. 61301023) and the Science and Technology on Low-Light-Level Night Vision Laboratory Foundation, China (Grant No. BJ2014001).
On the importance of AlGaN electron blocking layer design for GaN-based light-emitting diodes
Sheng Xia, Chang Simon Li, Z. M.; Sheng, Yang
2013-12-02
There has been confusion regarding the usefulness of AlGaN electron blocking layer (EBL) in GaN-based light-emitting diodes (LEDs) with some published experimental data indicating that the LEDs without EBL performed better than those with it. InGaN/GaN LEDs have been investigated numerically to analyze its actual effect in these devices. Simulation results show that hole blocking effect of EBL mainly determines the effectiveness of using it which is more sensitive to its Al composition, band offset ratio, and polarization charges. It is found that the choice of Al composition is critical for EBL to improve the optical performance of GaN-based LEDs.
Microwave-based medical diagnosis using particle swarm optimization algorithm
NASA Astrophysics Data System (ADS)
Modiri, Arezoo
This dissertation proposes and investigates a novel architecture intended for microwave-based medical diagnosis (MBMD). Furthermore, this investigation proposes novel modifications of particle swarm optimization algorithm for achieving enhanced convergence performance. MBMD has been investigated through a variety of innovative techniques in the literature since the 1990's and has shown significant promise in early detection of some specific health threats. In comparison to the X-ray- and gamma-ray-based diagnostic tools, MBMD does not expose patients to ionizing radiation; and due to the maturity of microwave technology, it lends itself to miniaturization of the supporting systems. This modality has been shown to be effective in detecting breast malignancy, and hence, this study focuses on the same modality. A novel radiator device and detection technique is proposed and investigated in this dissertation. As expected, hardware design and implementation are of paramount importance in such a study, and a good deal of research, analysis, and evaluation has been done in this regard which will be reported in ensuing chapters of this dissertation. It is noteworthy that an important element of any detection system is the algorithm used for extracting signatures. Herein, the strong intrinsic potential of the swarm-intelligence-based algorithms in solving complicated electromagnetic problems is brought to bear. This task is accomplished through addressing both mathematical and electromagnetic problems. These problems are called benchmark problems throughout this dissertation, since they have known answers. After evaluating the performance of the algorithm for the chosen benchmark problems, the algorithm is applied to MBMD tumor detection problem. The chosen benchmark problems have already been tackled by solution techniques other than particle swarm optimization (PSO) algorithm, the results of which can be found in the literature. However, due to the relatively high level
A vertical handoff decision algorithm based on ARMA prediction model
NASA Astrophysics Data System (ADS)
Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan
2011-12-01
With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.
A vertical handoff decision algorithm based on ARMA prediction model
NASA Astrophysics Data System (ADS)
Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan
2012-01-01
With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.
Entropy-Based Search Algorithm for Experimental Design
NASA Astrophysics Data System (ADS)
Malakar, N. K.; Knuth, K. H.
2011-03-01
The scientific method relies on the iterated processes of inference and inquiry. The inference phase consists of selecting the most probable models based on the available data; whereas the inquiry phase consists of using what is known about the models to select the most relevant experiment. Optimizing inquiry involves searching the parameterized space of experiments to select the experiment that promises, on average, to be maximally informative. In the case where it is important to learn about each of the model parameters, the relevance of an experiment is quantified by Shannon entropy of the distribution of experimental outcomes predicted by a probable set of models. If the set of potential experiments is described by many parameters, we must search this high-dimensional entropy space. Brute force search methods will be slow and computationally expensive. We present an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment for efficient experimental design. This algorithm is inspired by Skilling's nested sampling algorithm used in inference and borrows the concept of a rising threshold while a set of experiment samples are maintained. We demonstrate that this algorithm not only selects highly relevant experiments, but also is more efficient than brute force search. Such entropic search techniques promise to greatly benefit autonomous experimental design.
Point of Care and Factor Concentrate-Based Coagulation Algorithms
Theusinger, Oliver M.; Stein, Philipp; Levy, Jerrold H.
2015-01-01
In the last years it has become evident that the use of blood products should be reduced whenever possible. There is increasing evidence regarding serious adverse events, including higher mortality and morbidity, related to transfusions. The use of point of care (POC) devices integrated in algorithms is one of the important mechanisms to limit blood product exposure. Any type of algorithm, especially the POC-based ones, allows goal-directed transfusions of blood products and even better targeted factor concentrate substitutions. Different types of algorithms in different surgical settings (cardiac surgery, trauma, liver surgery etc.) have been established with growing interest in their use as they offer objective therapy for management and reduction of blood product use. The use of POC devices with evidence-based algorithms is important in the bleeding patient independent of its origin (traumatic vs. surgical). The use of factor concentrates compared to the classical blood products can be cost-saving, beneficial for the patient, and in agreement with the WHO-requested standard of care. The empiric and uncontrolled use of blood products such as fresh frozen plasma, red blood cells, and platelets without POC monitoring should no longer be followed with regard to actual evidence in literature. Furthermore, the use of factor concentrates may provide better outcomes and potential for cost saving. PMID:26019707
Task-Based Flocking Algorithm for Mobile Robot Cooperation
NASA Astrophysics Data System (ADS)
He, Hongsheng; Ge, Shuzhi Sam; Tong, Guofeng
In this paper, one task-based flocking algorithm that coordinates a swarm of robots is presented and evaluated based on the standard simulation platform. Task-based flocking algorithm(TFA) is an effective framework for mobile robots cooperation. Flocking behaviors are integrated into the cooperation of the multi-robot system to organize a robot team to achieve a common goal. The goal of the whole team is obtained through the collaboration of the individual robot’s task. The flocking model is presented, and the flocking energy function is defined based on that model to analyze the stability of the flocking and the task switching criterion. The simulation study is conducted in a five-versus-five soccer game, where the each robot dynamically selects its task in accordance with status and the whole robot team behaves as a flocking. Through simulation results and experiments, it is proved that the task-based flocking algorithm can effectively coordinate and control the robot flock to achieve the goal.
Fano resonances GaN-based high contrast grating surface-emitting lasers
NASA Astrophysics Data System (ADS)
Wu, Tzeng-Tsong; Wu, Shu-Hsien; Lu, Tien-Chang; Kuo, Hao-Chung; Wang, Shing-Chung
2013-03-01
GaN-based high contrast grating surface-emitting lasers (HCG SELs) with AlN/GaN distributed Bragg reflectors were reported. The device exhibited a low threshold pumping energy density of about 0.56 mJ/cm2 and the lasing wavelength was at 393.6 nm with a high degree of polarization of 73% at room temperature. The specific lasing mode and polarization characteristics agreed well with the theoretical modeling. The low threshold characteristics of our GaNbased HCG SELs utilized by the Fano resonance can be potential for development of blue surface emitting laser sources
GaN-Based High Temperature and Radiation-Hard Electronics for Harsh Environments
NASA Technical Reports Server (NTRS)
Son, Kyung-ah; Liao, Anna; Lung, Gerald; Gallegos, Manuel; Hatakeh, Toshiro; Harris, Richard D.; Scheick, Leif Z.; Smythe, William D.
2010-01-01
We develop novel GaN-based high temperature and radiation-hard electronics to realize data acquisition electronics and transmitters suitable for operations in harsh planetary environments. In this paper, we discuss our research on metal-oxide-semiconductor (MOS) transistors that are targeted for 500 (sup o)C operation and >2 Mrad radiation hardness. For the target device performance, we develop Schottky-free AlGaN/GaN MOS transistors, where a gate electrode is processed in a MOS layout using an Al2O3 gate dielectric layer....
Novel tree-based algorithms for computational electromagnetics
NASA Astrophysics Data System (ADS)
Aronsson, Jonatan
Tree-based methods have wide applications for solving large-scale problems in electromagnetics, astrophysics, quantum chemistry, fluid mechanics, acoustics, and many more areas. This thesis focuses on their applicability for solving large-scale problems in electromagnetics. The Barnes-Hut (BH) algorithm and the Fast Multipole Method (FMM) are introduced along with a survey of important previous work. The required theory for applying those methods to problems in electromagnetics is presented with particular emphasis on the capacitance extraction problem and broadband full-wave scattering. A novel single source approximation is introduced for approximating clusters of electrostatic sources in multi-layered media. The approximation is derived by matching the spectra of the field in the vicinity of the stationary phase point. Combined with the BH algorithm, a new algorithm is shown to be an efficient method for evaluating electrostatic fields in multilayered media. Specifically, the new BH algorithm is well suited for fast capacitance extraction. The BH algorithm is also adapted to the scalar Helmholtz kernel by using the same methodology to derive an accurate single source approximation. The result is a fast algorithm that is suitable for accelerating the solution of the Electric Field Integral Equation (EFIE) for electrically small structures. Finally, a new version of FMM is presented that is stable and efficient from the low frequency regime to mid-range frequencies. By applying analytical derivatives to the field expansions at the observation points, the proposed method can rapidly evaluate vectorial kernels that arise in the FMM-accelerated solution of EFIE, the Magnetic Field Integral Equation (MFIE), and the Combined Field Integral Equation (CFIE).
AlGaN/GaN high-electron mobility transistor-based sensors for environmental and bio-applications
NASA Astrophysics Data System (ADS)
Chu, B. H.; Wang, Y. L.; Chen, K. H.; Chang, C. Y.; Lo, C. F.; Pearton, S. J.; Papadi, G.; Coleman, J. K.; Sheppard, B. J.; Dungen, C. F.; Kroll, Kevin; Denslow, Nancy; Dabiran, A.; Chow, P. P.; Johnson, J. W.; Pine, E. L.; Linthicum, K. J.; Ren, F.
2010-04-01
A promising sensing technology utilizing AlGaN/GaN high electron mobility transistors (HEMTs) has been developed to analyze a wide variety of environmental and biological gases and liquids. The conducting 2DEG channel of GaN/AlGaN HEMTs is very close to the surface and extremely sensitive to adsorption of analytes. Examples of detecting mercury ions, perkinsus, lactic acid, carbon dioxide, and vitellogenin are discussed in this paper.
GaN-Based Detector Enabling Technology for Next Generation Ultraviolet Planetary Missions
NASA Technical Reports Server (NTRS)
Aslam, S.; Gronoff, G.; Hewagama, T.; Janz, S.; Kotecki, C.
2012-01-01
The ternary alloy AlN-GaN-InN system provides several distinct advantages for the development of UV detectors for future planetary missions. First, (InN), (GaN) and (AlN) have direct bandgaps 0.8, 3.4 and 6.2 eV, respectively, with corresponding wavelength cutoffs of 1550 nm, 365 nm and 200 nm. Since they are miscible with each other, these nitrides form complete series of indium gallium nitride (In(sub l-x)Ga(sub x)N) and aluminum gallium nitride (Al(sub l-x)Ga(sub x)N) alloys thus allowing the development of detectors with a wavelength cut-off anywhere in this range. For the 2S0-365 nm spectral wavelength range AlGaN detectors can be designed to give a 1000x solar radiation rejection at cut-off wavelength of 325 nm, than can be achieved with Si based detectors. For tailored wavelength cut-offs in the 365-4S0 nm range, InGaN based detectors can be fabricated, which still give 20-40x better solar radiation rejection than Si based detectors. This reduced need for blocking filters greatly increases the Detective Quantum efficiency (DQE) and simplifies the instrument's optical systems. Second, the wide direct bandgap reduces the thermally generated dark current to levels allowing many observations to be performed at room temperature. Third, compared to narrow bandgap materials, wide bandgap semiconductors are significantly more radiation tolerant. Finally, with the use of an (AI, In)GaN array, the overall system cost is reduced by eliminating stringent Si CCD cooling systems. Compared to silicon, GaN based detectors have superior QE based on a direct bandgap and longer absorption lengths in the UV.
Lunar Crescent Detection Based on Image Processing Algorithms
NASA Astrophysics Data System (ADS)
Fakhar, Mostafa; Moalem, Peyman; Badri, Mohamad Ali
2014-11-01
For many years lunar crescent visibility has been studied by many astronomers. Different criteria have been used to predict and evaluate the visibility status of new Moon crescents. Powerful equipment such as telescopes and binoculars have changed capability of observations. Most of conventional statistical criteria made wrong predictions when new observations (based on modern equipment) were reported. In order to verify such reports and modify criteria, not only previous statistical parameters should be considered but also some new and effective parameters like high magnification, contour effect, low signal to noise, eyestrain and weather conditions should be viewed. In this paper a new method is presented for lunar crescent detection based on processing of lunar crescent images. The method includes two main steps, first, an image processing algorithm that improves signal to noise ratio and detects lunar crescents based on circular Hough transform (CHT). Second using an algorithm based on image histogram processing to detect the crescent visually. Final decision is made by comparing the results of visual and CHT algorithms. In order to evaluate the proposed method, a database, including 31 images are tested. The illustrated method can distinguish and extract the crescent that even the eye can't recognize. Proposed method significantly reduces artifacts, increases SNR and can be used easily by both groups astronomers and who want to develop a new criterion as a reliable method to verify empirical observation.
Staff line detection and revision algorithm based on subsection projection and correlation algorithm
NASA Astrophysics Data System (ADS)
Yang, Yin-xian; Yang, Ding-li
2013-03-01
Staff line detection plays a key role in OMR technology, and is the precon-ditions of subsequent segmentation 1& recognition of music sheets. For the phenomena of horizontal inclination & curvature of staff lines and vertical inclination of image, which often occur in music scores, an improved approach based on subsection projection is put forward to realize the detection of original staff lines and revision in an effect to implement staff line detection more successfully. Experimental results show the presented algorithm can detect and revise staff lines fast and effectively.
DWFS: a wrapper feature selection tool based on a parallel genetic algorithm.
Soufan, Othman; Kleftogiannis, Dimitrios; Kalnis, Panos; Bajic, Vladimir B
2015-01-01
Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem's dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filtering methods that may be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs. PMID:25719748
DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm
Soufan, Othman; Kleftogiannis, Dimitrios; Kalnis, Panos; Bajic, Vladimir B.
2015-01-01
Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem’s dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filtering methods that may be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs. PMID:25719748
Genetic algorithm-based feature selection in high-resolution NMR spectra
Cho, Hyun-Woo; Jeong, Myong K.; Park, Youngja; Ziegler, Thomas R.; Jones, Dean P.
2011-01-01
High-resolution nuclear magnetic resonance (NMR) spectroscopy has provided a new means for detection and recognition of metabolic changes in biological systems in response to pathophysiological stimuli and to the intake of toxins or nutrition. To identify meaningful patterns from NMR spectra, various statistical pattern recognition methods have been applied to reduce their complexity and uncover implicit metabolic patterns. In this paper, we present a genetic algorithm (GA)-based feature selection method to determine major metabolite features to play a significant role in discrimination of samples among different conditions in high-resolution NMR spectra. In addition, an orthogonal signal filter was employed as a preprocessor of NMR spectra in order to remove any unwanted variation of the data that is unrelated to the discrimination of different conditions. The results of k-nearest neighbors and the partial least squares discriminant analysis of the experimental NMR spectra from human plasma showed the potential advantage of the features obtained from GA-based feature selection combined with an orthogonal signal filter. PMID:21472035
Emotion state identification based on heart rate variability and genetic algorithm.
Sung-Nien Yu; Shu-Feng Chen
2015-08-01
The objective of this study is to develop an effective emotion recognition system based on ECG. The proposed emotion recognition system is capable of differentiating four kinds of emotions, namely neutral, happiness, stress, and sadness, based on the heart rate variability (HRV). Ten male subjects were involved in the study. Both visual and auditory stimuli were used to stimulate the emotions. Four categories of HRV features, namely time-domain, frequency-domain, Poincare plot, and differential features, were exploited to characterize the physiological changes during the affective stimuli. The support vector machine (SVM) was employed as the classifier. The genetic algorithm (GA) was exploited as feature selector. Without feature selector, only 52.2% recognition rate was achieved. However, with the GA feature selector, an optimal recognition rate of 90% was achieved. Compared with other user-independent systems published in the literature, the proposed method achieves an accuracy of 90% which is demonstrated to be the most effective for discriminating four kinds of emotions with user-independent design policy. PMID:26736318
Emerging GaN-based HEMTs for mechanical sensing within harsh environments
NASA Astrophysics Data System (ADS)
Köck, Helmut; Chapin, Caitlin A.; Ostermaier, Clemens; Häberlen, Oliver; Senesky, Debbie G.
2014-06-01
Gallium nitride based high-electron-mobility transistors (HEMTs) have been investigated extensively as an alternative to Si-based power transistors by academia and industry over the last decade. It is well known that GaN-based HEMTs outperform Si-based technologies in terms of power density, area specific on-state resistance and switching speed. Recently, wide band-gap material systems have stirred interest regarding their use in various sensing fields ranging from chemical, mechanical, biological to optical applications due to their superior material properties. For harsh environments, wide bandgap sensor systems are deemed to be superior when compared to conventional Si-based systems. A new monolithic sensor platform based on the GaN HEMT electronic structure will enable engineers to design highly efficient propulsion systems widely applicable to the automotive, aeronautics and astronautics industrial sectors. In this paper, the advancements of GaN-based HEMTs for mechanical sensing applications are discussed. Of particular interest are multilayered heterogeneous structures where spontaneous and piezoelectric polarization between the interface results in the formation of a 2-dimensional electron gas (2DEG). Experimental results presented focus on the signal transduction under strained operating conditions in harsh environments. It is shown that a conventional AlGaN/GaN HEMT has a strong dependence of drain current under strained conditions, thus representing a promising future sensor platform. Ultimately, this work explores the sensor performance of conventional GaN HEMTs and leverages existing technological advances available in power electronics device research. The results presented have the potential to boost GaN-based sensor development through the integration of HEMT device and sensor design research.
Genetic algorithm based optimization of pulse profile for MOPA based high power fiber lasers
NASA Astrophysics Data System (ADS)
Zhang, Jiawei; Tang, Ming; Shi, Jun; Fu, Songnian; Li, Lihua; Liu, Ying; Cheng, Xueping; Liu, Jian; Shum, Ping
2015-03-01
Although the Master Oscillator Power-Amplifier (MOPA) based fiber laser has received much attention for laser marking process due to its large tunabilty of pulse duration (from 10ns to 1ms), repetition rate (100Hz to 500kHz), high peak power and extraordinary heat dissipating capability, the output pulse deformation due to the saturation effect of fiber amplifier is detrimental for many applications. We proposed and demonstrated that, by utilizing Genetic algorithm (GA) based optimization technique, the input pulse profile from the master oscillator (current-driven laser diode) could be conveniently optimized to achieve targeted output pulse shape according to real parameters' constraints. In this work, an Yb-doped high power fiber amplifier is considered and a 200ns square shaped pulse profile is the optimization target. Since the input pulse with longer leading edge and shorter trailing edge can compensate the saturation effect, linear, quadratic and cubic polynomial functions are used to describe the input pulse with limited number of unknowns(<5). Coefficients of the polynomial functions are the optimization objects. With reasonable cost and hardware limitations, the cubic input pulse with 4 coefficients is found to be the best as the output amplified pulse can achieve excellent flatness within the square shape. Considering the bandwidth constraint of practical electronics, we examined high-frequency component cut-off effect of input pulses and found that the optimized cubic input pulses with 300MHz bandwidth is still quite acceptable to satisfy the requirement for the amplified output pulse and it is feasible to establish such a pulse generator in real applications.
A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning
NASA Astrophysics Data System (ADS)
Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei
2013-03-01
In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.
A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning
NASA Astrophysics Data System (ADS)
Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei
2012-04-01
In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.
Multi-Objective Community Detection Based on Memetic Algorithm
2015-01-01
Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646
NASA Astrophysics Data System (ADS)
Duboz, J. Y.; Frayssinet, E.; Chenot, Sebastien; Reverchon, J. L.; Idir, M.
2013-03-01
The potential of GaN for X-ray detection in the range from 5 to 40 keV has been assessed. The absorption coefficient has been measured as a fonction of photon energy. Various detectors have been fabricated including MSM and Schottky diodes. They were tested under polychromatic X-ray illumination and under monochromatic irradiation from 6 to 22 keV in the Soleil synchrotron facility. The vertical Schottky diodes perform better as their geometry is better suited to the thick layers required by the low absorption coefficient. The operation mode is discussed in terms of photoconductive and photovoltaic behaviors. Some parasitic effects related to the electrical activation of defects by high energy photons and to the tunnel effect in lightly doped Schottky diodes have been evidenced. These effects disappear in diodes where the doping profile has been optimized. The spectral response is found to be very consistent with the spectral absorption coefficient. The sensitivity of GaN Schottky diodes is evaluated and found to be on the order of 40 photons per second. The response is fast nd linear.
Artificial Bee Colony Algorithm Based on Information Learning.
Gao, Wei-Feng; Huang, Ling-Ling; Liu, San-Yang; Dai, Cai
2015-12-01
Inspired by the fact that the division of labor and cooperation play extremely important roles in the human history development, this paper develops a novel artificial bee colony algorithm based on information learning (ILABC, for short). In ILABC, at each generation, the whole population is divided into several subpopulations by the clustering partition and the size of subpopulation is dynamically adjusted based on the last search experience, which results in a clear division of labor. Furthermore, the two search mechanisms are designed to facilitate the exchange of information in each subpopulation and between different subpopulations, respectively, which acts as the cooperation. Finally, the comparison results on a number of benchmark functions demonstrate that the proposed method performs competitively and effectively when compared to the selected state-of-the-art algorithms. PMID:25594992
A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.
Li, Shan; Kang, Liying; Zhao, Xing-Ming
2014-01-01
With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks. PMID:24729969
A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics
Li, Shan; Zhao, Xing-Ming
2014-01-01
With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks. PMID:24729969
A GaAs-based self-aligned stripe distributed feedback laser
NASA Astrophysics Data System (ADS)
Lei, H.; Stevens, B. J.; Fry, P. W.; Babazadeh, N.; Ternent, G.; Childs, D. T.; Groom, K. M.
2016-08-01
We demonstrate operation of a GaAs-based self-aligned stripe (SAS) distributed feedback (DFB) laser. In this structure, a first order GaInP/GaAs index-coupled DFB grating is built within the p-doped AlGaAs layer between the active region and the n-doped GaInP opto-electronic confinement layer of a SAS laser structure. In this process no Al-containing layers are exposed to atmosphere prior to overgrowth. The use of AlGaAs cladding affords the luxury of full flexibility in upper cladding design, which proved necessary due to limitations imposed by the grating infill and overgrowth with the GaInP current block layer. Resultant devices exhibit single-mode lasing with high side-mode-suppression of >40 dB over the temperature range 20 °C–70 °C. The experimentally determined optical profile and grating confinement correlate well with those simulated using Fimmwave.
InGaN-based UV/blue/green/amber LEDs
NASA Astrophysics Data System (ADS)
Mukai, Takashi; Yamada, Motokazu; Nakamura, Shuji
1999-04-01
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 instead of GaN active layers. Red LEDs with an emission wavelength of 680 nm which emission energy was smaller than the band-gap energy of InN were fabricated mainly resulting from the piezoelectric field due to the strain. 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. InGaN single-quantum-well- structure blue LEDs were grown on epitaxially laterally overgrown GaN and sapphire substrates. The emission spectra showed the similar blue shift with increasing forward currents between both LEDs. The output power of both LEDs was almost the same, as high as 6 mW at a current of 20 mA. These results indicate that the In composition fluctuation is not caused by dislocations, the dislocations are not effective to reduce the efficiency of the emission, and that the dislocations from the leakage current pathway in InGaN.
Study of Surface and Interface Roughness of GaN-Based Films Using Spectral Reflectance Measurements
NASA Astrophysics Data System (ADS)
Benzarti, Z.; Khelifi, M.; Halidou, I.; El Jani, B.
2015-10-01
GaN films were grown using SiN treatment of sapphire substrate by metalorganic vapor-phase epitaxy in a home-made vertical reactor at atmospheric pressure. The growth was interrupted at different stages to investigate the impact of interface and surface roughness on the optical properties of the GaN layers. A transition from a three-dimensional (3D) to two-dimensional (2D) growth mode was revealed by real-time in situ laser reflectometry ( λ = 632.8 nm) as well as by atomic force microscopy images. A theoretical model is proposed to determine the refractive index evolution during GaN layer growth based on the Bruggeman effective medium approximation. Ex situ multiwavelength reflectivity signals were fit to the thin-film interference equations to derive the evolution of the effective refractive indexes for the surface and interface GaN layer, thereby determining the refractive index of the GaN layer during growth. Ex situ spectroscopic ellipsometry measurements of the GaN layer refractive indexes at different growth stages were compared with calculated results. Moreover, an empirical law was developed to fit the refractive index evolution during GaN layer growth and used for in situ reflectivity signal simulation in order to deduce the growth rate. Finally, good agreement was observed between the experimental and theoretical findings.
Historical feature pattern extraction based network attack situation sensing algorithm.
Zeng, Yong; Liu, Dacheng; Lei, Zhou
2014-01-01
The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously. PMID:24892054
A disturbance based control/structure design algorithm
NASA Technical Reports Server (NTRS)
Mclaren, Mark D.; Slater, Gary L.
1989-01-01
Some authors take a classical approach to the simultaneous structure/control optimization by attempting to simultaneously minimize the weighted sum of the total mass and a quadratic form, subject to all of the structural and control constraints. Here, the optimization will be based on the dynamic response of a structure to an external unknown stochastic disturbance environment. Such a response to excitation approach is common to both the structural and control design phases, and hence represents a more natural control/structure optimization strategy than relying on artificial and vague control penalties. The design objective is to find the structure and controller of minimum mass such that all the prescribed constraints are satisfied. Two alternative solution algorithms are presented which have been applied to this problem. Each algorithm handles the optimization strategy and the imposition of the nonlinear constraints in a different manner. Two controller methodologies, and their effect on the solution algorithm, will be considered. These are full state feedback and direct output feedback, although the problem formulation is not restricted solely to these forms of controller. In fact, although full state feedback is a popular choice among researchers in this field (for reasons that will become apparent), its practical application is severely limited. The controller/structure interaction is inserted by the imposition of appropriate closed-loop constraints, such as closed-loop output response and control effort constraints. Numerical results will be obtained for a representative flexible structure model to illustrate the effectiveness of the solution algorithms.
Digital watermarking algorithm based on HVS in wavelet domain
NASA Astrophysics Data System (ADS)
Zhang, Qiuhong; Xia, Ping; Liu, Xiaomei
2013-10-01
As a new technique used to protect the copyright of digital productions, the digital watermark technique has drawn extensive attention. A digital watermarking algorithm based on discrete wavelet transform (DWT) was presented according to human visual properties in the paper. Then some attack analyses were given. Experimental results show that the watermarking scheme proposed in this paper is invisible and robust to cropping, and also has good robustness to cut , compression , filtering , and noise adding .
NCUBE - A clustering algorithm based on a discretized data space
NASA Technical Reports Server (NTRS)
Eigen, D. J.; Northouse, R. A.
1974-01-01
Cluster analysis involves the unsupervised grouping of data. The process provides an automatic procedure for generating known training samples for pattern classification. NCUBE, the clustering algorithm presented, is based upon the concept of imposing a gridwork on the data space. The NCUBE computer implementation of this concept provides an easily derived form of piecewise linear discrimination. This piecewise linear discrimination permits the separation of some types of data groups that are not linearly separable.
Physics-based signal processing algorithms for micromachined cantilever arrays
Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W
2013-11-19
A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.
DNA-based watermarks using the DNA-Crypt algorithm
Heider, Dominik; Barnekow, Angelika
2007-01-01
Background The aim of this paper is to demonstrate the application of watermarks based on DNA sequences to identify the unauthorized use of genetically modified organisms (GMOs) protected by patents. Predicted mutations in the genome can be corrected by the DNA-Crypt program leaving the encrypted information intact. Existing DNA cryptographic and steganographic algorithms use synthetic DNA sequences to store binary information however, although these sequences can be used for authentication, they may change the target DNA sequence when introduced into living organisms. Results The DNA-Crypt algorithm and image steganography are based on the same watermark-hiding principle, namely using the least significant base in case of DNA-Crypt and the least significant bit in case of the image steganography. It can be combined with binary encryption algorithms like AES, RSA or Blowfish. DNA-Crypt is able to correct mutations in the target DNA with several mutation correction codes such as the Hamming-code or the WDH-code. Mutations which can occur infrequently may destroy the encrypted information, however an integrated fuzzy controller decides on a set of heuristics based on three input dimensions, and recommends whether or not to use a correction code. These three input dimensions are the length of the sequence, the individual mutation rate and the stability over time, which is represented by the number of generations. In silico experiments using the Ypt7 in Saccharomyces cerevisiae shows that the DNA watermarks produced by DNA-Crypt do not alter the translation of mRNA into protein. Conclusion The program is able to store watermarks in living organisms and can maintain the original information by correcting mutations itself. Pairwise or multiple sequence alignments show that DNA-Crypt produces few mismatches between the sequences similar to all steganographic algorithms. PMID:17535434
Fast wavelet based algorithms for linear evolution equations
NASA Technical Reports Server (NTRS)
Engquist, Bjorn; Osher, Stanley; Zhong, Sifen
1992-01-01
A class was devised of fast wavelet based algorithms for linear evolution equations whose coefficients are time independent. The method draws on the work of Beylkin, Coifman, and Rokhlin which they applied to general Calderon-Zygmund type integral operators. A modification of their idea is applied to linear hyperbolic and parabolic equations, with spatially varying coefficients. A significant speedup over standard methods is obtained when applied to hyperbolic equations in one space dimension and parabolic equations in multidimensions.
New image watermarking algorithm based on mixed scales wavelets
NASA Astrophysics Data System (ADS)
El Hajji, Mohamed; Douzi, Hassan; Mammass, Driss; Harba, Rachid; Ros, Frédéric
2012-01-01
Watermarking is a technology for embedding secure information in digital content such as audio, images, and video. An effective watermarking algorithm is proposed based on a discrete wavelet transform (DWT) using mixed scales representation. The watermark is embedded in dominant blocks using quantization index modulation (QIM). These dominant blocks correspond to the texture and contour zones. Experimental results demonstrate that the proposed method is robust against various attacks and improves watermark invisibility.
A background suppression algorithm for infrared image based on shearlet
NASA Astrophysics Data System (ADS)
Zou, Ruibin; Shi, Caicheng; Qin, Xiao
2015-04-01
Because of the relative far distance between infrared imaging system and target or the wide field infrared optical, the imaging area of infrared target is only a few pixels, which is isolated or spots to be showed in the field of view. The only available is the intensity information (gray value) for the target detection. Simultaneously, there are many shortcomings of the infrared image, such as large noise, interference and so on, therefore the small target is always buried in the background and noises. The small target is relatively difficult to detect, so generally, it is impossible to make reliable detection to this target in a single frame image. Summarily, the core of the infrared small target detection algorithm is the background and noise suppression based on a single frame image. Aiming at the infrared small target detection and the above problems, a shearlets-based background suppression algorithm for infrared image is proposed. The algorithm demonstrates the performance of advantage based on shearlets, which is especially designed to address anisotropic and directional information at various scales. This transform provides an optimally efficient representation of images, which is greatly reduced the amount of the information and the available information representation. In the paper, introducing the principle of shearlets first, and then proposing the theory of the algorithm and explaining the implementation step. Finally, giving the simulation results. In Matlab simulations with this method for several sets of infrared images, simulation results conformed to the theory on background suppression based on shearlets. The result showed that this method can effectively suppress background, and improve the SCR and achieve a satisfactory effect in the sky background. The method is very effectively for target detection, identification, track in infrared image system for the future.
InGaN-based visible light-emitting diodes on ScAlMgO4(0001) substrates
NASA Astrophysics Data System (ADS)
Ozaki, Takuya; Funato, Mitsuru; Kawakami, Yoichi
2015-06-01
High-quality InGaN-based visible light-emitting diodes (LEDs) are demonstrated on ScAlMgO4 (SCAM) (0001) substrates. GaN grown on SCAM by metal-organic vapor phase epitaxy is nearly strain-free with an in-plane compressive strain of -1.26 × 10-3, which is much smaller than that in conventional GaN/sapphire owing to the smaller thermal expansion mismatch between GaN and SCAM. We fabricate InGaN/GaN quantum well LEDs on GaN/SCAM templates, and observe bright blue electroluminescence at ˜470 nm wavelength. The device performances of LEDs on SCAM are comparable to those of LEDs on sapphire. Our achievements indicate that highly efficient InGaN-based light emitters are possible on SCAM substrates.
An optimized hybrid encode based compression algorithm for hyperspectral image
NASA Astrophysics Data System (ADS)
Wang, Cheng; Miao, Zhuang; Feng, Weiyi; He, Weiji; Chen, Qian; Gu, Guohua
2013-12-01
Compression is a kernel procedure in hyperspectral image processing due to its massive data which will bring great difficulty in date storage and transmission. In this paper, a novel hyperspectral compression algorithm based on hybrid encoding which combines with the methods of the band optimized grouping and the wavelet transform is proposed. Given the characteristic of correlation coefficients between adjacent spectral bands, an optimized band grouping and reference frame selection method is first utilized to group bands adaptively. Then according to the band number of each group, the redundancy in the spatial and spectral domain is removed through the spatial domain entropy coding and the minimum residual based linear prediction method. Thus, embedded code streams are obtained by encoding the residual images using the improved embedded zerotree wavelet based SPIHT encode method. In the experments, hyperspectral images collected by the Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) were used to validate the performance of the proposed algorithm. The results show that the proposed approach achieves a good performance in reconstructed image quality and computation complexity.The average peak signal to noise ratio (PSNR) is increased by 0.21~0.81dB compared with other off-the-shelf algorithms under the same compression ratio.
Image-based surface matching algorithm oriented to structural biology.
Merelli, Ivan; Cozzi, Paolo; D'Agostino, Daniele; Clematis, Andrea; Milanesi, Luciano
2011-01-01
Emerging technologies for structure matching based on surface descriptions have demonstrated their effectiveness in many research fields. In particular, they can be successfully applied to in silico studies of structural biology. Protein activities, in fact, are related to the external characteristics of these macromolecules and the ability to match surfaces can be important to infer information about their possible functions and interactions. In this work, we present a surface-matching algorithm, based on encoding the outer morphology of proteins in images of local description, which allows us to establish point-to-point correlations among macromolecular surfaces using image-processing functions. Discarding methods relying on biological analysis of atomic structures and expensive computational approaches based on energetic studies, this algorithm can successfully be used for macromolecular recognition by employing local surface features. Results demonstrate that the proposed algorithm can be employed both to identify surface similarities in context of macromolecular functional analysis and to screen possible protein interactions to predict pairing capability. PMID:21566253
Manufacturing of 100mm diameter GaSb substrates for advanced space based applications
NASA Astrophysics Data System (ADS)
Allen, L. P.; Flint, J. P.; Meshew, G.; Trevethan, J.; Dallas, G.; Khoshakhlagh, A.; Hill, C. J.
2012-01-01
Engineered substrates such as large diameter (100mm) GaSb wafers need to be ready years in advance of any major shift in DoD and commercial technology, and typically before much of the rest of the materials and equipment for fabricating next generation devices. Antimony based III-V semiconductors are of significant interest for advanced applications in optoelectronics, high speed transistors, microwave devices, and photovoltaics. GaSb demand is increasing due to its lattice parameter matching of various ternary and quaternary III-V compounds, as their bandgaps can be engineered to cover a wide spectral range. For these stealth and spaced based applications, larger format IRFPAs benefit clearly from next generation starting substrates. In this study, we have manufactured and tested 100mm GaSb substrates. This paper describes the characterization process that provides the best possible GaSb material for advanced IRFPA and SLS epi growth. The analysis of substrate by AFM surface roughness, particles, haze, GaSb oxide character and desorption using XPS, flatness measurements, and SLS based epitaxy quality are shown. By implementing subtle changes in our substrate processing, we show that a Sb-oxide rich surface is routinely provided for rapid desorption. Post-MBE CBIRD structures on the 100mm ULD GaSb were examined and reveals a high intensity, 6.6nm periodicity, low (15.48 arcsec) FWHM peak distribution that suggests low surface strain and excellent lattice matching. The Ra for GaSb is a consistent ~0.2-4nm, with average batch wafer warp of ~4 μm to provide a clean, flat GaSb template critical for next generation epi growth.
NASA Astrophysics Data System (ADS)
Zhang, Jian; Qin, Xiaoying; Li, Di; Liu, Yongfei; Li, Yuanyue; Song, Chunjun; Xin, Hongxing; Zhu, Xiaoguang
2016-02-01
CuGaTe2 based composites incorporated with graphite nanosheets (GNs) CuGaTe2/x G (G = GNs, 0 ≤ x ≤ 3.04 vol. %) were prepared, and the thermoelectric properties of the composites were studied from 300 to 875 K. The results show that the incorporation of GNs into the CuGaTe2 matrix can enhance the Seebeck coefficient and power factor over the whole temperature range investigated due to energy filtering effects, and the reduction of thermal conductivity below 750 K owing to interface scattering. Although the resistivity increases, energy filtering significantly raises the Seebeck component, and the overall effect on power factor is positive. The sample with 2.28 vol. % GNs had the largest ZT value, reaching 0.93 at 873 K, which is a ˜21% improvement on pure CuGaTe2.
GaN-based vertical cavity surface emitting lasers with periodic gain structures
NASA Astrophysics Data System (ADS)
Matsui, Kenjo; Kozuka, Yugo; Ikeyama, Kazuki; Horikawa, Kosuke; Furuta, Takashi; Akagi, Takanobu; Takeuchi, Tetsuya; Kamiyama, Satoshi; Iwaya, Motoaki; Akasaki, Isamu
2016-05-01
We have achieved room-temperature CW operations of GaN-based vertical cavity surface emitting lasers (VCSELs) with periodic gain structures (PGSs). The PGS-VCSEL consisted of 4.5λ-thick optical cavity length and two GaInN 5-quantum-well (QW) active regions separated with a Mg-doped GaN intermediate layer. The uniform carrier injection into the two active regions was also investigated using light-emitting diodes (LEDs). It is found that the use of an optimum Mg concentration in the intermediate layers improves the uniform carrier injection in the two active regions. From these results, we realized the CW operation of VCSELs with PGSs grown on AlInN/GaN distributed Bragg reflectors (DBRs). The VCSEL under CW operation showed a threshold current density of 16.5 kA/cm2 and its operation wavelength was 409.9 nm.
Confocal microphotoluminescence of InGaN-based light-emitting diodes
NASA Astrophysics Data System (ADS)
Okamoto, Koichi; Kaneta, Akio; Kawakami, Yoichi; Fujita, Shigeo; Choi, Jungkwon; Terazima, Masahide; Mukai, Takashi
2005-09-01
Spatially resolved photoluminescence (PL) of InGaN/GaN/AlGaN-based quantum-well-structured light-emitting diodes (LEDs) with a yellow-green light (530 nm) and an amber light (600 nm) was measured by using confocal microscopy. Submicron-scale spatial inhomogeneities of both PL intensities and spectra were found in confocal micro-PL images. We also found clear correlations between PL intensities and peak wavelength for both LEDs. Such correlations for yellow-green and amber LEDs were different from the reported correlations for blue or green LEDs. This discrepancy should be due to different diffusion, localization, and recombination dynamics of electron-hole pairs generated in InGaN active layers, and should be a very important property for influencing the optical properties of LEDs. In order to explain the results, we proposed a possible carrier dynamics model based on the carrier localization and partial reduction of the quantum confinement Stark effect depending on an indium composition in InGaN active layers. By using this model, we also considered the origin of the reduction of the emission efficiencies with a longer emission wavelength of InGaN LEDs with high indium composition.
High-power laser diodes based on InGaAsP alloys
NASA Astrophysics Data System (ADS)
Razeghi, Manijeh
1994-06-01
HIGH-POWER, high-coherence solid-state lasers, based on dielectric materials such as ruby or Nd:YAG (yttrium aluminium garnet), have many civilian and military applications. The active media in these lasers are insulating, and must therefore be excited (or `pumped') by optical, rather than electrical, means. Conventional gas-discharge lamps can be used as the pumping source, but semiconductor diode lasers are more efficient, as their wavelength can be tailored to match the absorption properties of the lasing material. Semiconducting AlGaAs alloys are widely used for this purpose1, 2, but oxidation of the aluminium and the spreading of defects during device operation limit the lifetime of the diodes3, and hence the reliability of the system as a whole. Aluminium-free InGaAsP compounds, on the other hand, do not have these lifetime-limiting properties4-8. We report here the fabrication of high-power lasers based on InGaAsP (lattice-matched to GaAs substrates), which operate over the same wavelength range as conventional AlGaAs laser diodes and show significantly improved reliability. The other optical and electrical properties of these diodes are either comparable or superior to those of the AlGaAs system.
NASA Astrophysics Data System (ADS)
Zhao, Jia-qing; Zeng, Pan; Lei, Li-ping; Ma, Yuan
2012-03-01
Digital image correlation (DIC) has received a widespread research and application in experimental mechanics. In DIC, the performance of subpixel registration algorithm (e.g., Newton-Raphson method, quasi-Newton method) relies heavily on the initial guess of deformation. In the case of small inter-frame deformation, the initial guess could be found by simple search scheme, the coarse-fine search for instance. While for large inter-frame deformation, it is difficult for simple search scheme to robustly estimate displacement parameters and deformation parameters simultaneously with low computational cost. In this paper, we proposed three improving strategies, i.e. Q-stage evolutionary strategy (T), parameter control strategy (C) and space expanding strategy (E), and then combined them into three population-based intelligent algorithms (PIAs), i.e. genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO), and finally derived eighteen different algorithms to calculate the initial guess for qN. The eighteen algorithms were compared in three sets of experiments including large rigid body translation, finite uniaxial strain and large rigid body rotation, and the results showed the effectiveness of proposed improving strategies. Among all compared algorithms, DE-TCE is the best which is robust, convenient and efficient for large inter-frame deformation measurement.
Performance evaluation of PCA-based spike sorting algorithms.
Adamos, Dimitrios A; Kosmidis, Efstratios K; Theophilidis, George
2008-09-01
Deciphering the electrical activity of individual neurons from multi-unit noisy recordings is critical for understanding complex neural systems. A widely used spike sorting algorithm is being evaluated for single-electrode nerve trunk recordings. The algorithm is based on principal component analysis (PCA) for spike feature extraction. In the neuroscience literature it is generally assumed that the use of the first two or most commonly three principal components is sufficient. We estimate the optimum PCA-based feature space by evaluating the algorithm's performance on simulated series of action potentials. A number of modifications are made to the open source nev2lkit software to enable systematic investigation of the parameter space. We introduce a new metric to define clustering error considering over-clustering more favorable than under-clustering as proposed by experimentalists for our data. Both the program patch and the metric are available online. Correlated and white Gaussian noise processes are superimposed to account for biological and artificial jitter in the recordings. We report that the employment of more than three principal components is in general beneficial for all noise cases considered. Finally, we apply our results to experimental data and verify that the sorting process with four principal components is in agreement with a panel of electrophysiology experts. PMID:18565614
Matched field localization based on CS-MUSIC algorithm
NASA Astrophysics Data System (ADS)
Guo, Shuangle; Tang, Ruichun; Peng, Linhui; Ji, Xiaopeng
2016-04-01
The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered. A matched field localization algorithm based on CS-MUSIC (Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning. The signal matrix is calculated through the SVD (Singular Value Decomposition) of the observation matrix. The observation matrix in the sparse mathematical model is replaced by the signal matrix, and a new concise sparse mathematical model is obtained, which means not only the scale of the localization problem but also the noise level is reduced; then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS (Compressive Sensing) method and MUSIC (Multiple Signal Classification) method. The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots, and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large, which will be proved in this paper.
A Resampling Based Clustering Algorithm for Replicated Gene Expression Data.
Li, Han; Li, Chun; Hu, Jie; Fan, Xiaodan
2015-01-01
In gene expression data analysis, clustering is a fruitful exploratory technique to reveal the underlying molecular mechanism by identifying groups of co-expressed genes. To reduce the noise, usually multiple experimental replicates are performed. An integrative analysis of the full replicate data, instead of reducing the data to the mean profile, carries the promise of yielding more precise and robust clusters. In this paper, we propose a novel resampling based clustering algorithm for genes with replicated expression measurements. Assuming those replicates are exchangeable, we formulate the problem in the bootstrap framework, and aim to infer the consensus clustering based on the bootstrap samples of replicates. In our approach, we adopt the mixed effect model to accommodate the heterogeneous variances and implement a quasi-MCMC algorithm to conduct statistical inference. Experiments demonstrate that by taking advantage of the full replicate data, our algorithm produces more reliable clusters and has robust performance in diverse scenarios, especially when the data is subject to multiple sources of variance. PMID:26671802
A Radio-Map Automatic Construction Algorithm Based on Crowdsourcing.
Yu, Ning; Xiao, Chenxian; Wu, Yinfeng; Feng, Renjian
2016-01-01
Traditional radio-map-based localization methods need to sample a large number of location fingerprints offline, which requires huge amount of human and material resources. To solve the high sampling cost problem, an automatic radio-map construction algorithm based on crowdsourcing is proposed. The algorithm employs the crowd-sourced information provided by a large number of users when they are walking in the buildings as the source of location fingerprint data. Through the variation characteristics of users' smartphone sensors, the indoor anchors (doors) are identified and their locations are regarded as reference positions of the whole radio-map. The AP-Cluster method is used to cluster the crowdsourced fingerprints to acquire the representative fingerprints. According to the reference positions and the similarity between fingerprints, the representative fingerprints are linked to their corresponding physical locations and the radio-map is generated. Experimental results demonstrate that the proposed algorithm reduces the cost of fingerprint sampling and radio-map construction and guarantees the localization accuracy. The proposed method does not require users' explicit participation, which effectively solves the resource-consumption problem when a location fingerprint database is established. PMID:27070623
An Enhanced Differential Evolution Algorithm Based on Multiple Mutation Strategies
Xiang, Wan-li; Meng, Xue-lei; An, Mei-qing; Li, Yin-zhen; Gao, Ming-xia
2015-01-01
Differential evolution algorithm is a simple yet efficient metaheuristic for global optimization over continuous spaces. However, there is a shortcoming of premature convergence in standard DE, especially in DE/best/1/bin. In order to take advantage of direction guidance information of the best individual of DE/best/1/bin and avoid getting into local trap, based on multiple mutation strategies, an enhanced differential evolution algorithm, named EDE, is proposed in this paper. In the EDE algorithm, an initialization technique, opposition-based learning initialization for improving the initial solution quality, and a new combined mutation strategy composed of DE/current/1/bin together with DE/pbest/bin/1 for the sake of accelerating standard DE and preventing DE from clustering around the global best individual, as well as a perturbation scheme for further avoiding premature convergence, are integrated. In addition, we also introduce two linear time-varying functions, which are used to decide which solution search equation is chosen at the phases of mutation and perturbation, respectively. Experimental results tested on twenty-five benchmark functions show that EDE is far better than the standard DE. In further comparisons, EDE is compared with other five state-of-the-art approaches and related results show that EDE is still superior to or at least equal to these methods on most of benchmark functions. PMID:26609304
A Radio-Map Automatic Construction Algorithm Based on Crowdsourcing
Yu, Ning; Xiao, Chenxian; Wu, Yinfeng; Feng, Renjian
2016-01-01
Traditional radio-map-based localization methods need to sample a large number of location fingerprints offline, which requires huge amount of human and material resources. To solve the high sampling cost problem, an automatic radio-map construction algorithm based on crowdsourcing is proposed. The algorithm employs the crowd-sourced information provided by a large number of users when they are walking in the buildings as the source of location fingerprint data. Through the variation characteristics of users’ smartphone sensors, the indoor anchors (doors) are identified and their locations are regarded as reference positions of the whole radio-map. The AP-Cluster method is used to cluster the crowdsourced fingerprints to acquire the representative fingerprints. According to the reference positions and the similarity between fingerprints, the representative fingerprints are linked to their corresponding physical locations and the radio-map is generated. Experimental results demonstrate that the proposed algorithm reduces the cost of fingerprint sampling and radio-map construction and guarantees the localization accuracy. The proposed method does not require users’ explicit participation, which effectively solves the resource-consumption problem when a location fingerprint database is established. PMID:27070623
Orthogonalizing EM: A design-based least squares algorithm
Xiong, Shifeng; Dai, Bin; Huling, Jared; Qian, Peter Z. G.
2016-01-01
We introduce an efficient iterative algorithm, intended for various least squares problems, based on a design of experiments perspective. The algorithm, called orthogonalizing EM (OEM), works for ordinary least squares and can be easily extended to penalized least squares. The main idea of the procedure is to orthogonalize a design matrix by adding new rows and then solve the original problem by embedding the augmented design in a missing data framework. We establish several attractive theoretical properties concerning OEM. For the ordinary least squares with a singular regression matrix, an OEM sequence converges to the Moore-Penrose generalized inverse-based least squares estimator. For ordinary and penalized least squares with various penalties, it converges to a point having grouping coherence for fully aliased regression matrices. Convergence and the convergence rate of the algorithm are examined. Finally, we demonstrate that OEM is highly efficient for large-scale least squares and penalized least squares problems, and is considerably faster than competing methods when n is much larger than p. Supplementary materials for this article are available online. PMID:27499558
Performance of a community detection algorithm based on semidefinite programming
NASA Astrophysics Data System (ADS)
Ricci-Tersenghi, Federico; Javanmard, Adel; Montanari, Andrea
2016-03-01
The problem of detecting communities in a graph is maybe one the most studied inference problems, given its simplicity and widespread diffusion among several disciplines. A very common benchmark for this problem is the stochastic block model or planted partition problem, where a phase transition takes place in the detection of the planted partition by changing the signal-to-noise ratio. Optimal algorithms for the detection exist which are based on spectral methods, but we show these are extremely sensible to slight modification in the generative model. Recently Javanmard, Montanari and Ricci-Tersenghi [1] have used statistical physics arguments, and numerical simulations to show that finding communities in the stochastic block model via semidefinite programming is quasi optimal. Further, the resulting semidefinite relaxation can be solved efficiently, and is very robust with respect to changes in the generative model. In this paper we study in detail several practical aspects of this new algorithm based on semidefinite programming for the detection of the planted partition. The algorithm turns out to be very fast, allowing the solution of problems with O(105) variables in few second on a laptop computer.
PACS model based on digital watermarking and its core algorithms
NASA Astrophysics Data System (ADS)
Que, Dashun; Wen, Xianlin; Chen, Bi
2009-10-01
PACS model based on digital watermarking is proposed by analyzing medical image features and PACS requirements from the point of view of information security, its core being digital watermarking server and the corresponding processing module. Two kinds of digital watermarking algorithm are studied; one is non-region of interest (NROI) digital watermarking algorithm based on wavelet domain and block-mean, the other is reversible watermarking algorithm on extended difference and pseudo-random matrix. The former belongs to robust lossy watermarking, which embedded in NROI by wavelet provides a good way for protecting the focus area (ROI) of images, and introduction of block-mean approach a good scheme to enhance the anti-attack capability; the latter belongs to fragile lossless watermarking, which has the performance of simple implementation and can realize tamper localization effectively, and the pseudo-random matrix enhances the correlation and security between pixels. Plenty of experimental research has been completed in this paper, including the realization of digital watermarking PACS model, the watermarking processing module and its anti-attack experiments, the digital watermarking server and the network transmission simulating experiments of medical images. Theoretical analysis and experimental results show that the designed PACS model can effectively ensure confidentiality, authenticity, integrity and security of medical image information.
Enhancing the light extraction efficiency of GaN-based LEDs
NASA Astrophysics Data System (ADS)
Niu, Pingjuan; Li, Yanling; Li, Xiaoyun; Liu, Hongwei; Tian, Haitao; Gao, Tiecheng; Yang, Guanghua
2007-11-01
GaN-based light-emitting diode (LED) has been widely used in recent years, and tremendous progress has been achieved in GaN-based semiconductor materials and relevant process. However, owing to the large refractive index contrast between GaN-based semiconductor materials and air, light can be easily totally internally reflected at the semiconductor/air interface, and the critical angle for light to escape from the semiconductor is small. Therefore, the light extraction efficiency for GaN-based LED is still low and needs improving. Some of the leading approaches to enhance light extraction efficiency of GaN-based LED such as surface texturing or roughening, omnidirectional reflectors, photonic crystals, laser liftoff, transparent electrode, patterned substrate and so on are introduced in detail. For each approach, how the variation in device structure or material improves the light extraction efficiency is analyzed thoroughly. At last, some of mentioned approaches that are promising are evaluated and viewed briefly.
Linear vs. function-based dose algorithm designs.
Stanford, N
2011-03-01
The performance requirements prescribed in IEC 62387-1, 2007 recommend linear, additive algorithms for external dosimetry [IEC. Radiation protection instrumentation--passive integrating dosimetry systems for environmental and personal monitoring--Part 1: General characteristics and performance requirements. IEC 62387-1 (2007)]. Neither of the two current standards for performance of external dosimetry in the USA address the additivity of dose results [American National Standards Institute, Inc. American National Standard for dosimetry personnel dosimetry performance criteria for testing. ANSI/HPS N13.11 (2009); Department of Energy. Department of Energy Standard for the performance testing of personnel dosimetry systems. DOE/EH-0027 (1986)]. While there are significant merits to adopting a purely linear solution to estimating doses from multi-element external dosemeters, differences in the standards result in technical as well as perception challenges in designing a single algorithm approach that will satisfy both IEC and USA external dosimetry performance requirements. The dosimetry performance testing standards in the USA do not incorporate type testing, but rely on biennial performance tests to demonstrate proficiency in a wide range of pure and mixed fields. The test results are used exclusively to judge the system proficiency, with no specific requirements on the algorithm design. Technical challenges include mixed beta/photon fields with a beta dose as low as 0.30 mSv mixed with 0.05 mSv of low-energy photons. Perception-based challenges, resulting from over 20 y of experience with this type of performance testing in the USA, include the common belief that the overall quality of the dosemeter performance can be judged from performance to pure fields. This paper presents synthetic testing results from currently accredited function-based algorithms and new developed purely linear algorithms. A comparison of the performance data highlights the benefits of each
A Matrix Pencil Algorithm Based Multiband Iterative Fusion Imaging Method
Zou, Yong Qiang; Gao, Xun Zhang; Li, Xiang; Liu, Yong Xiang
2016-01-01
Multiband signal fusion technique is a practicable and efficient way to improve the range resolution of ISAR image. The classical fusion method estimates the poles of each subband signal by the root-MUSIC method, and some good results were get in several experiments. However, this method is fragile in noise for the proper poles could not easy to get in low signal to noise ratio (SNR). In order to eliminate the influence of noise, this paper propose a matrix pencil algorithm based method to estimate the multiband signal poles. And to deal with mutual incoherent between subband signals, the incoherent parameters (ICP) are predicted through the relation of corresponding poles of each subband. Then, an iterative algorithm which aimed to minimize the 2-norm of signal difference is introduced to reduce signal fusion error. Applications to simulate dada verify that the proposed method get better fusion results at low SNR. PMID:26781194
Clustering-based robust three-dimensional phase unwrapping algorithm.
Arevalillo-Herráez, Miguel; Burton, David R; Lalor, Michael J
2010-04-01
Relatively recent techniques that produce phase volumes have motivated the study of three-dimensional (3D) unwrapping algorithms that inherently incorporate the third dimension into the process. We propose a novel 3D unwrapping algorithm that can be considered to be a generalization of the minimum spanning tree (MST) approach. The technique combines characteristics of some of the most robust existing methods: it uses a quality map to guide the unwrapping process, a region growing mechanism to progressively unwrap the signal, and also cut surfaces to avoid error propagation. The approach has been evaluated in the context of noncontact measurement of dynamic objects, suggesting a better performance than MST-based approaches. PMID:20357860
Reconstruction algorithms for optoacoustic imaging based on fiber optic detectors
NASA Astrophysics Data System (ADS)
Lamela, Horacio; Díaz-Tendero, Gonzalo; Gutiérrez, Rebeca; Gallego, Daniel
2011-06-01
Optoacoustic Imaging (OAI), a novel hybrid imaging technology, offers high contrast, molecular specificity and excellent resolution to overcome limitations of the current clinical modalities for detection of solid tumors. The exact time-domain reconstruction formula produces images with excellent resolution but poor contrast. Some approximate time-domain filtered back-projection reconstruction algorithms have also been reported to solve this problem. A wavelet transform implementation filtering can be used to sharpen object boundaries while simultaneously preserving high contrast of the reconstructed objects. In this paper, several algorithms, based on Back Projection (BP) techniques, have been suggested to process OA images in conjunction with signal filtering for ultrasonic point detectors and integral detectors. We apply these techniques first directly to a numerical generated sample image and then to the laserdigitalized image of a tissue phantom, obtaining in both cases the best results in resolution and contrast for a waveletbased filter.
A Matrix Pencil Algorithm Based Multiband Iterative Fusion Imaging Method
NASA Astrophysics Data System (ADS)
Zou, Yong Qiang; Gao, Xun Zhang; Li, Xiang; Liu, Yong Xiang
2016-01-01
Multiband signal fusion technique is a practicable and efficient way to improve the range resolution of ISAR image. The classical fusion method estimates the poles of each subband signal by the root-MUSIC method, and some good results were get in several experiments. However, this method is fragile in noise for the proper poles could not easy to get in low signal to noise ratio (SNR). In order to eliminate the influence of noise, this paper propose a matrix pencil algorithm based method to estimate the multiband signal poles. And to deal with mutual incoherent between subband signals, the incoherent parameters (ICP) are predicted through the relation of corresponding poles of each subband. Then, an iterative algorithm which aimed to minimize the 2-norm of signal difference is introduced to reduce signal fusion error. Applications to simulate dada verify that the proposed method get better fusion results at low SNR.
CS based confocal microwave imaging algorithm for breast cancer detection.
Sun, Y P; Zhang, S; Cui, Z; Qu, L L
2016-04-29
Based on compressive sensing (CS) technology, a high resolution confocal microwave imaging algorithm is proposed for breast cancer detection. With the exploitation of the spatial sparsity of the target space, the proposed image reconstruction problem is cast within the framework of CS and solved by the sparse constraint optimization. The effectiveness and validity of the proposed CS imaging method is verified by the full wave synthetic data from numerical breast phantom using finite-difference time-domain (FDTD) method. The imaging results have shown that the proposed imaging scheme can improve the imaging quality while significantly reducing the amount of data measurements and collection time when compared to the traditional delay-and-sum imaging algorithm. PMID:27177106
Adaptive inpainting algorithm based on DCT induced wavelet regularization.
Li, Yan-Ran; Shen, Lixin; Suter, Bruce W
2013-02-01
In this paper, we propose an image inpainting optimization model whose objective function is a smoothed l(1) norm of the weighted nondecimated discrete cosine transform (DCT) coefficients of the underlying image. By identifying the objective function of the proposed model as a sum of a differentiable term and a nondifferentiable term, we present a basic algorithm inspired by Beck and Teboulle's recent work on the model. Based on this basic algorithm, we propose an automatic way to determine the weights involved in the model and update them in each iteration. The DCT as an orthogonal transform is used in various applications. We view the rows of a DCT matrix as the filters associated with a multiresolution analysis. Nondecimated wavelet transforms with these filters are explored in order to analyze the images to be inpainted. Our numerical experiments verify that under the proposed framework, the filters from a DCT matrix demonstrate promise for the task of image inpainting. PMID:23060331
An improved piecewise linear chaotic map based image encryption algorithm.
Hu, Yuping; Zhu, Congxu; Wang, Zhijian
2014-01-01
An image encryption algorithm based on improved piecewise linear chaotic map (MPWLCM) model was proposed. The algorithm uses the MPWLCM to permute and diffuse plain image simultaneously. Due to the sensitivity to initial key values, system parameters, and ergodicity in chaotic system, two pseudorandom sequences are designed and used in the processes of permutation and diffusion. The order of processing pixels is not in accordance with the index of pixels, but it is from beginning or end alternately. The cipher feedback was introduced in diffusion process. Test results and security analysis show that not only the scheme can achieve good encryption results but also its key space is large enough to resist against brute attack. PMID:24592159
An Improved Piecewise Linear Chaotic Map Based Image Encryption Algorithm
Hu, Yuping; Wang, Zhijian
2014-01-01
An image encryption algorithm based on improved piecewise linear chaotic map (MPWLCM) model was proposed. The algorithm uses the MPWLCM to permute and diffuse plain image simultaneously. Due to the sensitivity to initial key values, system parameters, and ergodicity in chaotic system, two pseudorandom sequences are designed and used in the processes of permutation and diffusion. The order of processing pixels is not in accordance with the index of pixels, but it is from beginning or end alternately. The cipher feedback was introduced in diffusion process. Test results and security analysis show that not only the scheme can achieve good encryption results but also its key space is large enough to resist against brute attack. PMID:24592159
A Matrix Pencil Algorithm Based Multiband Iterative Fusion Imaging Method.
Zou, Yong Qiang; Gao, Xun Zhang; Li, Xiang; Liu, Yong Xiang
2016-01-01
Multiband signal fusion technique is a practicable and efficient way to improve the range resolution of ISAR image. The classical fusion method estimates the poles of each subband signal by the root-MUSIC method, and some good results were get in several experiments. However, this method is fragile in noise for the proper poles could not easy to get in low signal to noise ratio (SNR). In order to eliminate the influence of noise, this paper propose a matrix pencil algorithm based method to estimate the multiband signal poles. And to deal with mutual incoherent between subband signals, the incoherent parameters (ICP) are predicted through the relation of corresponding poles of each subband. Then, an iterative algorithm which aimed to minimize the 2-norm of signal difference is introduced to reduce signal fusion error. Applications to simulate dada verify that the proposed method get better fusion results at low SNR. PMID:26781194
Hybrid regularization image restoration algorithm based on total variation
NASA Astrophysics Data System (ADS)
Zhang, Hongmin; Wang, Yan
2013-09-01
To reduce the noise amplification and ripple phenomenon in the restoration result by using the traditional Richardson-Lucy deconvolution method, a novel hybrid regularization image restoration algorithm based on total variation is proposed in this paper. The key ides is that the hybrid regularization terms are employed according to the characteristics of different regions in the image itself. At the same time, the threshold between the different regularization terms is selected according to the golden section point which takes into account the human eye's visual feeling. Experimental results show that the restoration results of the proposed method are better than that of the total variation Richardson-Lucy algorithm both in PSNR and MSE, and it has the better visual effect simultaneously.
Missile placement analysis based on improved SURF feature matching algorithm
NASA Astrophysics Data System (ADS)
Yang, Kaida; Zhao, Wenjie; Li, Dejun; Gong, Xiran; Sheng, Qian
2015-03-01
The precious battle damage assessment by use of video images to analysis missile placement is a new study area. The article proposed an improved speeded up robust features algorithm named restricted speeded up robust features, which combined the combat application of TV-command-guided missiles and the characteristics of video image. Its restrictions mainly reflected in two aspects, one is to restrict extraction area of feature point; the second is to restrict the number of feature points. The process of missile placement analysis based on video image was designed and a video splicing process and random sample consensus purification were achieved. The RSURF algorithm is proved that has good realtime performance on the basis of guarantee the accuracy.
Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.
2013-01-01
Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933
NASA Astrophysics Data System (ADS)
Khatir, S.; Belaidi, I.; Serra, R.; Benaissa, B.; Ait Saada, A.
2015-07-01
The detection techniques based on non-destructive testing (NDT) defects are preferable because of their low cost and operational aspects related to the use of the analyzed structure. In this study, we used the genetic algorithm (GA) for detecting and locating damage. The finite element was used for diagnostic beams. Different structures considered may incur damage to be modelled by a loss of rigidity supposed to represent a defect in the structure element. Identification of damage is formulated as an optimization problem using three objective functions (change of natural frequencies, Modal Assurance Criterion MAC and MAC natural frequency). The results show that the best objective function is based on the natural frequency and MAC while the method of the genetic algorithm present its efficiencies in indicating and quantifying multiple damage with great accuracy. Three defects have been created to enhance damage depending on the elements 2, 5 and 8 with a percentage allocation of 50% in the beam structure which has been discretized into 10 elements. Finally the defect with noise was introduced to test the stability of the method against uncertainty.
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389
A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389
MIRA: mutual information-based reporter algorithm for metabolic networks
Cicek, A. Ercument; Roeder, Kathryn; Ozsoyoglu, Gultekin
2014-01-01
Motivation: Discovering the transcriptional regulatory architecture of the metabolism has been an important topic to understand the implications of transcriptional fluctuations on metabolism. The reporter algorithm (RA) was proposed to determine the hot spots in metabolic networks, around which transcriptional regulation is focused owing to a disease or a genetic perturbation. Using a z-score-based scoring scheme, RA calculates the average statistical change in the expression levels of genes that are neighbors to a target metabolite in the metabolic network. The RA approach has been used in numerous studies to analyze cellular responses to the downstream genetic changes. In this article, we propose a mutual information-based multivariate reporter algorithm (MIRA) with the goal of eliminating the following problems in detecting reporter metabolites: (i) conventional statistical methods suffer from small sample sizes, (ii) as z-score ranges from minus to plus infinity, calculating average scores can lead to canceling out opposite effects and (iii) analyzing genes one by one, then aggregating results can lead to information loss. MIRA is a multivariate and combinatorial algorithm that calculates the aggregate transcriptional response around a metabolite using mutual information. We show that MIRA’s results are biologically sound, empirically significant and more reliable than RA. Results: We apply MIRA to gene expression analysis of six knockout strains of Escherichia coli and show that MIRA captures the underlying metabolic dynamics of the switch from aerobic to anaerobic respiration. We also apply MIRA to an Autism Spectrum Disorder gene expression dataset. Results indicate that MIRA reports metabolites that highly overlap with recently found metabolic biomarkers in the autism literature. Overall, MIRA is a promising algorithm for detecting metabolic drug targets and understanding the relation between gene expression and metabolic activity. Availability and
Algorithmic support for commodity-based parallel computing systems.
Leung, Vitus Joseph; Bender, Michael A.; Bunde, David P.; Phillips, Cynthia Ann
2003-10-01
The Computational Plant or Cplant is a commodity-based distributed-memory supercomputer under development at Sandia National Laboratories. Distributed-memory supercomputers run many parallel programs simultaneously. Users submit their programs to a job queue. When a job is scheduled to run, it is assigned to a set of available processors. Job runtime depends not only on the number of processors but also on the particular set of processors assigned to it. Jobs should be allocated to localized clusters of processors to minimize communication costs and to avoid bandwidth contention caused by overlapping jobs. This report introduces new allocation strategies and performance metrics based on space-filling curves and one dimensional allocation strategies. These algorithms are general and simple. Preliminary simulations and Cplant experiments indicate that both space-filling curves and one-dimensional packing improve processor locality compared to the sorted free list strategy previously used on Cplant. These new allocation strategies are implemented in Release 2.0 of the Cplant System Software that was phased into the Cplant systems at Sandia by May 2002. Experimental results then demonstrated that the average number of communication hops between the processors allocated to a job strongly correlates with the job's completion time. This report also gives processor-allocation algorithms for minimizing the average number of communication hops between the assigned processors for grid architectures. The associated clustering problem is as follows: Given n points in {Re}d, find k points that minimize their average pairwise L{sub 1} distance. Exact and approximate algorithms are given for these optimization problems. One of these algorithms has been implemented on Cplant and will be included in Cplant System Software, Version 2.1, to be released. In more preliminary work, we suggest improvements to the scheduler separate from the allocator.
Long, Yi; Du, Zhi-jiang; Wang, Wei-dong; Dong, Wei
2016-01-01
A lower limb assistive exoskeleton is designed to help operators walk or carry payloads. The exoskeleton is required to shadow human motion intent accurately and compliantly to prevent incoordination. If the user's intention is estimated accurately, a precise position control strategy will improve collaboration between the user and the exoskeleton. In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. The proposed control strategy (SMC_GA_CMAC) is compared with three other types of approaches, that is, conventional SMC without optimization, optimal SMC with GA (SMC_GA), and SMC with CMAC compensation (SMC_CMAC), all of which are employed to track the desired joint angular position which is deduced from Clinical Gait Analysis (CGA) data. Position tracking performance is investigated with cosimulation using ADAMS and MATLAB/SIMULINK in two cases, of which the first case is without disturbances while the second case is with a bounded disturbance. The cosimulation results show the effectiveness of the proposed control strategy which can be employed in similar exoskeleton systems. PMID:27069353
Long, Yi; Du, Zhi-Jiang; Wang, Wei-Dong; Dong, Wei
2016-01-01
A lower limb assistive exoskeleton is designed to help operators walk or carry payloads. The exoskeleton is required to shadow human motion intent accurately and compliantly to prevent incoordination. If the user's intention is estimated accurately, a precise position control strategy will improve collaboration between the user and the exoskeleton. In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. The proposed control strategy (SMC_GA_CMAC) is compared with three other types of approaches, that is, conventional SMC without optimization, optimal SMC with GA (SMC_GA), and SMC with CMAC compensation (SMC_CMAC), all of which are employed to track the desired joint angular position which is deduced from Clinical Gait Analysis (CGA) data. Position tracking performance is investigated with cosimulation using ADAMS and MATLAB/SIMULINK in two cases, of which the first case is without disturbances while the second case is with a bounded disturbance. The cosimulation results show the effectiveness of the proposed control strategy which can be employed in similar exoskeleton systems. PMID:27069353
Spin tunneling and magnetotransport in GaMnAs-based heterostructures
NASA Astrophysics Data System (ADS)
Tanaka, Masaaki
2003-03-01
In this talk, we present the spin-dependent tunneling (vertical transport) and in-plane magnetotransport properties of GaMnAs-based ferromagnetic heterostructures. First we describe tunneling magnetoresistance (TMR) in all-semiconductor GaMnAs/AlAs/GaMnAs magnetic tunnel junctions (MTJs) [1][2]. Very high TMR ratios (max. 75 were observed at 8 K for the junction with the AlAs barrier thickness d<1.6nm. For d>1.6nm, the TMR ratio was found to decrease with increasing d, which can be explained by theoretical calculations based on k_allel conservation of tunneling carriers. Unlike the conventional MTJs, the present MTJs are all-epitaxial monocrystalline semiconductor-based junctions, which have some advantages including good compatibility with semiconductor devices and more freedom in the design of structures [3]. Second, we show our magnetotransport study on ferromagnetic III-V semiconductor heterostructures with higher Curie temperature TC [4]. In selectively doped heterostructures (Mn delta-doped GaAs / Be-doped AlGaAs), in which holes are supplied from the Be-doped p-AlGaAs layer resembling an inverted high electron mobility transistor (I-HEMT) structure, ferromagnetic ordering was clearly observed. In the heterostructure prepared with proper conditions, its TC was as high as 172 K, far above the TC of InAs- or GaAs-based random-alloy magnetic semiconductors. [1] M. Tanaka and Y. Higo, Phys. Rev. Lett. 87 (2001) 026602; Physica E13 (2002) 495. [2] Y. Higo, H. Shimizu, and M. Tanaka, J. Appl. Phys. 89 (2001) 6745. [3] T. Hayashi, M. Tanaka, and Asamitsu, J. Appl. Phys. 87 (2000) 4673. [4] A. M. Nazmul, S. Sugahara, and M. Tanaka, Appl. Phys. Lett. 80 (2002) 3120; cond-mat/0208299 (2002).
GaN-based light-emitting diodes on various substrates: a critical review
NASA Astrophysics Data System (ADS)
Li, Guoqiang; Wang, Wenliang; Yang, Weijia; Lin, Yunhao; Wang, Haiyan; Lin, Zhiting; Zhou, Shizhong
2016-05-01
GaN and related III-nitrides have attracted considerable attention as promising materials for application in optoelectronic devices, in particular, light-emitting diodes (LEDs). At present, sapphire is still the most popular commercial substrate for epitaxial growth of GaN-based LEDs. However, due to its relatively large lattice mismatch with GaN and low thermal conductivity, sapphire is not the most ideal substrate for GaN-based LEDs. Therefore, in order to obtain high-performance and high-power LEDs with relatively low cost, unconventional substrates, which are of low lattice mismatch with GaN, high thermal conductivity and low cost, have been tried as substitutes for sapphire. As a matter of fact, it is not easy to obtain high-quality III-nitride films on those substrates for various reasons. However, by developing a variety of techniques, distincts progress has been made during the past decade, with high-performance LEDs being successfully achieved on these unconventional substrates. This review focuses on state-of-the-art high-performance GaN-based LED materials and devices on unconventional substrates. The issues involved in the growth of GaN-based LED structures on each type of unconventional substrate are outlined, and the fundamental physics behind these issues is detailed. The corresponding solutions for III-nitride growth, defect control, and chip processing for each type of unconventional substrate are discussed in depth, together with a brief introduction to some newly developed techniques in order to realize LED structures on unconventional substrates. This is very useful for understanding the progress in this field of physics. In this review, we also speculate on the prospects for LEDs on unconventional substrates.
Badgutdinov, M. L.; Korobov, E. V.; Luk'yanov, F. A.; Yunovich, A. E. Kogan, L. M.; Gal'china, N. A.; Rassokhin, I. T.; Soshchin, N. P.
2006-06-15
The luminescence spectra, efficiency, and color characteristics of white-light-emitting diodes fabricated from p-n InGaN/AlGaN/GaN blue-light-emitting heterostructures grown on SiC substrates and coated with yellow-green phosphors based on the rare-earth-doped yttrium-aluminum garnets were studied. The efficiency of blue-emitting diodes is as high as 22% at a current of 350 mA and a voltage of 3.3 V. The white-emitting diodes have luminous efficiency as high as 40 lm/W and luminous flux up to 50 lm at 350 mA.
Self-consistent vertical transport calculations in AlxGa1-xN/GaN based resonant tunneling diode
NASA Astrophysics Data System (ADS)
Rached, A.; Bhouri, A.; Sakr, S.; Lazzari, J.-L.; Belmabrouk, H.
2016-03-01
The formation of two-dimensional electron gases (2DEGs) at AlxGa1-xN/GaN hexagonal double-barriers (DB) resonant tunneling diodes (RTD) is investigated by numerical self-consistent (SC) solutions of the coupled Schrödinger and Poisson equations. Spontaneous and piezoelectric effects across the material interfaces are rigorously taken into account. Conduction band profiles, band edges and corresponding envelope functions are calculated in the AlxGa1-xN/GaN structures and likened to those where no polarization effects are included. The combined effect of the polarization-induced bound charge and conduction band offsets between the hexagonal AlGaN and GaN results in the formation of 2DEGs on one side of the DB and a depletion region on the other side. Using the transfer matrix formalism, the vertical transport (J-V characteristics) in AlGaN/GaN RTDs is calculated with a fully SC calculation in the ballistic regime. Compared to standard calculations where the voltage drop along the structure is supposed to be linear, the SC method leads to strong quantitative changes in the J-V characteristics showing that the applied electric field varies significantly in the active region of the structure. The influences of the aluminum composition and the GaN(AlGaN) thickness layers on the evolution of the current characteristics are also self-consistently investigated and discussed. We show that the electrical characteristics are very sensitive to the potential barrier due to the interplay between the potential symmetry and the barrier height and width. More interestingly, we demonstrate that the figures of merit namely the peak-to-valley ratio (PVR) of GaN/AlGaN RTDs can be optimized by increasing the quantum well width.
The Prediction in Computer Color Matching of Dentistry Based on GA+BP Neural Network
Li, Haisheng; Lai, Long; Chen, Li; Lu, Cheng; Cai, Qiang
2015-01-01
Although the use of computer color matching can reduce the influence of subjective factors by technicians, matching the color of a natural tooth with a ceramic restoration is still one of the most challenging topics in esthetic prosthodontics. Back propagation neural network (BPNN) has already been introduced into the computer color matching in dentistry, but it has disadvantages such as unstable and low accuracy. In our study, we adopt genetic algorithm (GA) to optimize the initial weights and threshold values in BPNN for improving the matching precision. To our knowledge, we firstly combine the BPNN with GA in computer color matching in dentistry. Extensive experiments demonstrate that the proposed method improves the precision and prediction robustness of the color matching in restorative dentistry. PMID:25873990
AlGaN/GaN High Electron Mobility Transistor-Based Biosensor for the Detection of C-Reactive Protein
Lee, Hee Ho; Bae, Myunghan; Jo, Sung-Hyun; Shin, Jang-Kyoo; Son, Dong Hyeok; Won, Chul-Ho; Jeong, Hyun-Min; Lee, Jung-Hee; Kang, Shin-Won
2015-01-01
In this paper, we propose an AlGaN/GaN high electron mobility transistor (HEMT)-based biosensor for the detection of C-reactive protein (CRP) using a null-balancing circuit. A null-balancing circuit was used to measure the output voltage of the sensor directly. The output voltage of the proposed biosensor was varied by antigen-antibody interactions on the gate surface due to CRP charges. The AlGaN/GaN HFET-based biosensor with null-balancing circuit applied shows that CRP can be detected in a wide range of concentrations, varying from 10 ng/mL to 1000 ng/mL. X-ray photoelectron spectroscopy was carried out to verify the immobilization of self-assembled monolayer with Au on the gated region. PMID:26225981
MBE growth of active regions for electrically pumped, cw-operating GaSb-based VCSELs
NASA Astrophysics Data System (ADS)
Kashani-Shirazi, K.; Bachmann, A.; Boehm, G.; Ziegler, S.; Amann, M.-C.
2009-03-01
Electrically pumped, cw-operating, single-mode GaSb-based VCSELs are attractive light sources for trace-gas sensing systems using tunable diode laser absorption spectroscopy (TDLAS) [A. Vicet, D.A. Yarekha, A. Pérona, Y. Rouillard, S. Gaillard, Spectrochimica Acta Part A 58 (2002) 2405-2412]. Only recently, the first electrically pumped (EP) devices emitting at 2.325 μm in cw-mode at room temperature have been reported [A. Bachmann, T. Lim, K. Kashani-Shirazi, O. Dier, C. Lauer, M.-C. Amann, Electronics Letters 44(3) (2008) 202-203]. The fabrication of these devices employs the molecular beam epitaxy (MBE) growth of GaSb/AlAsSb-distributed Bragg mirrors, a multi-quantum-well active region made of AlGaAsSb/InGaAsSb and an InAsSb/GaSb-buried-tunnel junction. As VCSELs are usually driven under high injection rates, an optimum electrical design of active regions is essential for high-performance devices. In this paper we present an enhanced simulation of current flow in the active region under operation conditions. The calculation includes carrier transport by drift, diffusion and tunneling. We discuss different design criteria and material compositions for active regions. Active regions with various barrier materials were incorporated into edge emitter samples to evaluate their performance. Aluminum-containing barriers show better internal efficiency compared to active regions with GaSb as the barrier material.
Light-Emitting Devices Based on Top-down Fabricated GaAs Quantum Nanodisks
Higo, Akio; Kiba, Takayuki; Tamura, Yosuke; Thomas, Cedric; Takayama, Junichi; Wang, Yunpeng; Sodabanlu, Hassanet; Sugiyama, Masakazu; Nakano, Yoshiaki; Yamashita, Ichiro; Murayama, Akihiro; Samukawa, Seiji
2015-01-01
Quantum dots photonic devices based on the III–V compound semiconductor technology offer low power consumption, temperature stability, and high-speed modulation. We fabricated GaAs nanodisks (NDs) of sub-20-nm diameters by a top-down process using a biotemplate and neutral beam etching (NBE). The GaAs NDs were embedded in an AlGaAs barrier regrown by metalorganic vapor phase epitaxy (MOVPE). The temperature dependence of photoluminescence emission energies and the transient behavior were strongly affected by the quantum confinement effects of the embedded NDs. Therefore, the quantum levels of the NDs may be tuned by controlling their dimensions. We combined NBE and MOVPE in a high-throughput process compatible with industrial production systems to produce GaAs NDs with tunable optical characteristics. ND light emitting diode exhibited a narrow spectral width of 38 nm of high-intensity emission as a result of small deviation of ND sizes and superior crystallographic quality of the etched GaAs/AlGaAs layer. PMID:25792119
Light-Emitting Devices Based on Top-down Fabricated GaAs Quantum Nanodisks
NASA Astrophysics Data System (ADS)
Higo, Akio; Kiba, Takayuki; Tamura, Yosuke; Thomas, Cedric; Takayama, Junichi; Wang, Yunpeng; Sodabanlu, Hassanet; Sugiyama, Masakazu; Nakano, Yoshiaki; Yamashita, Ichiro; Murayama, Akihiro; Samukawa, Seiji
2015-03-01
Quantum dots photonic devices based on the III-V compound semiconductor technology offer low power consumption, temperature stability, and high-speed modulation. We fabricated GaAs nanodisks (NDs) of sub-20-nm diameters by a top-down process using a biotemplate and neutral beam etching (NBE). The GaAs NDs were embedded in an AlGaAs barrier regrown by metalorganic vapor phase epitaxy (MOVPE). The temperature dependence of photoluminescence emission energies and the transient behavior were strongly affected by the quantum confinement effects of the embedded NDs. Therefore, the quantum levels of the NDs may be tuned by controlling their dimensions. We combined NBE and MOVPE in a high-throughput process compatible with industrial production systems to produce GaAs NDs with tunable optical characteristics. ND light emitting diode exhibited a narrow spectral width of 38 nm of high-intensity emission as a result of small deviation of ND sizes and superior crystallographic quality of the etched GaAs/AlGaAs layer.
Light-emitting devices based on top-down fabricated GaAs quantum nanodisks.
Higo, Akio; Kiba, Takayuki; Tamura, Yosuke; Thomas, Cedric; Takayama, Junichi; Wang, Yunpeng; Sodabanlu, Hassanet; Sugiyama, Masakazu; Nakano, Yoshiaki; Yamashita, Ichiro; Murayama, Akihiro; Samukawa, Seiji
2015-01-01
Quantum dots photonic devices based on the III-V compound semiconductor technology offer low power consumption, temperature stability, and high-speed modulation. We fabricated GaAs nanodisks (NDs) of sub-20-nm diameters by a top-down process using a biotemplate and neutral beam etching (NBE). The GaAs NDs were embedded in an AlGaAs barrier regrown by metalorganic vapor phase epitaxy (MOVPE). The temperature dependence of photoluminescence emission energies and the transient behavior were strongly affected by the quantum confinement effects of the embedded NDs. Therefore, the quantum levels of the NDs may be tuned by controlling their dimensions. We combined NBE and MOVPE in a high-throughput process compatible with industrial production systems to produce GaAs NDs with tunable optical characteristics. ND light emitting diode exhibited a narrow spectral width of 38 nm of high-intensity emission as a result of small deviation of ND sizes and superior crystallographic quality of the etched GaAs/AlGaAs layer. PMID:25792119
Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization.
Chiu, Chung-Cheng; Ting, Chih-Chung
2016-01-01
Image enhancement methods have been widely used to improve the visual effects of images. Owing to its simplicity and effectiveness histogram equalization (HE) is one of the methods used for enhancing image contrast. However, HE may result in over-enhancement and feature loss problems that lead to unnatural look and loss of details in the processed images. Researchers have proposed various HE-based methods to solve the over-enhancement problem; however, they have largely ignored the feature loss problem. Therefore, a contrast enhancement algorithm based on gap adjustment for histogram equalization (CegaHE) is proposed. It refers to a visual contrast enhancement algorithm based on histogram equalization (VCEA), which generates visually pleasing enhanced images, and improves the enhancement effects of VCEA. CegaHE adjusts the gaps between two gray values based on the adjustment equation, which takes the properties of human visual perception into consideration, to solve the over-enhancement problem. Besides, it also alleviates the feature loss problem and further enhances the textures in the dark regions of the images to improve the quality of the processed images for human visual perception. Experimental results demonstrate that CegaHE is a reliable method for contrast enhancement and that it significantly outperforms VCEA and other methods. PMID:27338412
Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization
Chiu, Chung-Cheng; Ting, Chih-Chung
2016-01-01
Image enhancement methods have been widely used to improve the visual effects of images. Owing to its simplicity and effectiveness histogram equalization (HE) is one of the methods used for enhancing image contrast. However, HE may result in over-enhancement and feature loss problems that lead to unnatural look and loss of details in the processed images. Researchers have proposed various HE-based methods to solve the over-enhancement problem; however, they have largely ignored the feature loss problem. Therefore, a contrast enhancement algorithm based on gap adjustment for histogram equalization (CegaHE) is proposed. It refers to a visual contrast enhancement algorithm based on histogram equalization (VCEA), which generates visually pleasing enhanced images, and improves the enhancement effects of VCEA. CegaHE adjusts the gaps between two gray values based on the adjustment equation, which takes the properties of human visual perception into consideration, to solve the over-enhancement problem. Besides, it also alleviates the feature loss problem and further enhances the textures in the dark regions of the images to improve the quality of the processed images for human visual perception. Experimental results demonstrate that CegaHE is a reliable method for contrast enhancement and that it significantly outperforms VCEA and other methods. PMID:27338412
Visual tracking method based on cuckoo search algorithm
NASA Astrophysics Data System (ADS)
Gao, Ming-Liang; Yin, Li-Ju; Zou, Guo-Feng; Li, Hai-Tao; Liu, Wei
2015-07-01
Cuckoo search (CS) is a new meta-heuristic optimization algorithm that is based on the obligate brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. It has been found to be efficient in solving global optimization problems. An application of CS is presented to solve the visual tracking problem. The relationship between optimization and visual tracking is comparatively studied and the parameters' sensitivity and adjustment of CS in the tracking system are experimentally studied. To demonstrate the tracking ability of a CS-based tracker, a comparative study of tracking accuracy and speed of the CS-based tracker with six "state-of-art" trackers, namely, particle filter, meanshift, PSO, ensemble tracker, fragments tracker, and compressive tracker are presented. Comparative results show that the CS-based tracker outperforms the other trackers.
Detection algorithm of big bandwidth chirp signals based on STFT
NASA Astrophysics Data System (ADS)
Wang, Jinzhen; Wu, Juhong; Su, Shaoying; Chen, Zengping
2014-10-01
Aiming at solving the problem of detecting the wideband chirp signals under low Signal-to-Noise Ratio (SNR) condition, an effective signal detection algorithm based on Short-Time-Fourier-Transform (STFT) is proposed. Considering the characteristic of dispersion of noise spectrum and concentration of chirp spectrum, STFT is performed on chirp signals with Gauss window by fixed step, and these frequencies of peak spectrum obtained from every STFT are in correspondence to the time of every stepped window. Then, the frequencies are binarized and the approach similar to mnk method in time domain is used to detect the chirp pulse signal and determine the coarse starting time and ending time. Finally, the data segments, where the former starting time and ending time locate, are subdivided into many segments evenly, on which the STFT is implemented respectively. By that, the precise starting and ending time are attained. Simulations shows that when the SNR is higher than -28dB, the detection probability is not less than 99% and false alarm probability is zero, and also good estimation accuracy of starting and ending time is acquired. The algorithm is easy to realize and surpasses FFT in computation when the width of STFT window and step length are selected properly, so the presented algorithm has good engineering value.
Building simplification algorithms based on user cognition in mobile environment
NASA Astrophysics Data System (ADS)
Shen, Jie; Shi, Junfei; Wang, Meizhen; Wu, Chenyan
2008-10-01
With the development of LBS, mobile map should adaptively satisfy the cognitive requirement of user. User cognition in mobile environment is much more objective oriented and also seem to be a heavier burden than the user in static environment. The holistic idea and methods of map generalization can not fully suitable for the mobile map. This paper took the building simplification in habitation generalization as example, analyzed the characteristic of user cognition in mobile environment and the basic rules of building simplification, collected and studied the state-of-the-art of algorithms of building simplification in the static and mobile environment, put forward the idea of hierarchical building simplification based on user cognition. This paper took Hunan road business district of Nanjing as test area and took the building data with shapfile format of ESRI as test data and realized the simplification algorithm. The method took user as center, calculated the distance between user and the building which will be simplified and took the distance as the basis for choosing different simplification algorithm for different spaces. This contribution aimed to hierarchically present the building in different level of detail by real-time simplification.
Feature extraction algorithm for space targets based on fractal theory
NASA Astrophysics Data System (ADS)
Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin
2007-11-01
In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.
An improved Richardson-Lucy algorithm based on local prior
NASA Astrophysics Data System (ADS)
Yongpan, Wang; Huajun, Feng; Zhihai, Xu; Qi, Li; Chaoyue, Dai
2010-07-01
Ringing is one of the most common disturbing artifacts in image deconvolution. With a totally known kernel, the standard Richardson-Lucy (RL) algorithm succeeds in many motion deblurring processes, but the resulting images still contain visible ringing. When the estimated kernel is different from the real one, the result of the standard RL iterative algorithm will be worse. To suppress the ringing artifacts caused by failures in the blur kernel estimation, this paper improves the RL algorithm based on the local prior. Firstly, the standard deviation of pixels in the local window is computed to find the smooth region and the image gradient in the region is constrained to make its distribution consistent with the deblurring image gradient. Secondly, in order to suppress the ringing near the edge of a rigid body in the image, a new mask was obtained by computing the sharp edge of the image produced using the first step. If the kernel is large-scale, where the foreground is rigid and the background is smoothing, this step could produce a significant inhibitory effect on ringing artifacts. Thirdly, the boundary constraint is strengthened if the boundary is relatively smooth. As a result of the steps above, high-quality deblurred images can be obtained even when the estimated kernels are not perfectly accurate. On the basis of blurred images and the related kernel information taken by the additional hardware, our approach proved to be effective.
Sonoluminescence Bubble Measurements using Vision-Based Algorithms
NASA Technical Reports Server (NTRS)
Hall, Nancy R.; Mackey, Jeffrey R.; Matula, Thomas J.
2003-01-01
Vision-based measurement methods were used to measure bubble sizes in this sonoluminescence experiment. Bubble imaging was accomplished by placing the bubble between a bright light source and a microscope-CCD camera system. A collimated light-emitting diode was operated in a pulsed model with an adjustable time delay with respect to the piezo-electric transducer drive signal. The light-emitting diode produced a bubble shadowgraph consisting of a multiple exposure made by numerous light pulses imaged onto a charge-couple device camera. Each image was transferred from the camera to a computer-controlled machine vision system via a frame grabber. The frame grabber was equipped with on-board memory to accomodate sequential image buffering while images were transferred to the host processor and analyzed. This configuration allowed the host computer to perform diameter measurements, centroid position measurements and shape estimation in "real-time" as the next image was being acquired. Bubble size measurement accuracy with an uncertainty of 3 microns was achieved using standard lenses and machine vision algorithms. Bubble centroid position accuracy was also within the 3 micron tolerance of the vision system. This uncertainty estimation accounted for the optical spatial resolution, digitization errors and the edge detection algorithm accuracy. The vision algorithms include camera calibration, thresholding, edge detection, edge position determination, distance between two edges computations and centroid position computations.
Ballast: A Ball-based Algorithm for Structural Motifs
He, Lu; Vandin, Fabio; Pandurangan, Gopal
2013-01-01
Abstract Structural motifs encapsulate local sequence-structure-function relationships characteristic of related proteins, enabling the prediction of functional characteristics of new proteins, providing molecular-level insights into how those functions are performed, and supporting the development of variants specifically maintaining or perturbing function in concert with other properties. Numerous computational methods have been developed to search through databases of structures for instances of specified motifs. However, it remains an open problem how best to leverage the local geometric and chemical constraints underlying structural motifs in order to develop motif-finding algorithms that are both theoretically and practically efficient. We present a simple, general, efficient approach, called Ballast (ball-based algorithm for structural motifs), to match given structural motifs to given structures. Ballast combines the best properties of previously developed methods, exploiting the composition and local geometry of a structural motif and its possible instances in order to effectively filter candidate matches. We show that on a wide range of motif-matching problems, Ballast efficiently and effectively finds good matches, and we provide theoretical insights into why it works well. By supporting generic measures of compositional and geometric similarity, Ballast provides a powerful substrate for the development of motif-matching algorithms. PMID:23383999
Abedini, Mohammad; Moradi, Mohammad H; Hosseinian, S M
2016-03-01
This paper proposes a novel method to address reliability and technical problems of microgrids (MGs) based on designing a number of self-adequate autonomous sub-MGs via adopting MGs clustering thinking. In doing so, a multi-objective optimization problem is developed where power losses reduction, voltage profile improvement and reliability enhancement are considered as the objective functions. To solve the optimization problem a hybrid algorithm, named HS-GA, is provided, based on genetic and harmony search algorithms, and a load flow method is given to model different types of DGs as droop controller. The performance of the proposed method is evaluated in two case studies. The results provide support for the performance of the proposed method. PMID:26767800
NASA Astrophysics Data System (ADS)
Chen, Zheng; Mi, Chris Chunting; Xiong, Rui; Xu, Jun; You, Chenwen
2014-02-01
This paper introduces an online and intelligent energy management controller to improve the fuel economy of a power-split plug-in hybrid electric vehicle (PHEV). Based on analytic analysis between fuel-rate and battery current at different driveline power and vehicle speed, quadratic equations are applied to simulate the relationship between battery current and vehicle fuel-rate. The power threshold at which engine is turned on is optimized by genetic algorithm (GA) based on vehicle fuel-rate, battery state of charge (SOC) and driveline power demand. The optimal battery current when the engine is on is calculated using quadratic programming (QP) method. The proposed algorithm can control the battery current effectively, which makes the engine work more efficiently and thus reduce the fuel-consumption. Moreover, the controller is still applicable when the battery is unhealthy. Numerical simulations validated the feasibility of the proposed controller.
Utrilla, A. D.; Ulloa, J. M. Guzman, A.; Hierro, A.
2014-07-28
The application of a GaAsSb/GaAsN short-period superlattice capping layer (CL) on InAs/GaAs quantum dots (QDs) is shown to be an option for providing improved luminescence properties to this system. Separating both GaAsSb and GaAsN ternaries during the growth in 2 monolayer-thick phases solves the GaAsSbN immiscibility-related problems. Strong fluctuations in the CL composition and strain field as well as in the QD size distribution are significantly reduced, and a more regular CL interface is also obtained. Room-temperature (RT) photoluminescence (PL) is obtained for overall N contents as high as 3%, yielding PL peak wavelengths beyond 1.4 μm in samples with a type-II band alignment. High external quantum efficiency electroluminescence and photocurrent from the QD ground state are also demonstrated at RT in a single QD-layer p-i-n device. Thus, it becomes possible to combine and transfer the complementary benefits of Sb- and N-containing GaAs alloys to InAs QD-based optoelectronics.
Creating IRT-Based Parallel Test Forms Using the Genetic Algorithm Method
ERIC Educational Resources Information Center
Sun, Koun-Tem; Chen, Yu-Jen; Tsai, Shu-Yen; Cheng, Chien-Fen
2008-01-01
In educational measurement, the construction of parallel test forms is often a combinatorial optimization problem that involves the time-consuming selection of items to construct tests having approximately the same test information functions (TIFs) and constraints. This article proposes a novel method, genetic algorithm (GA), to construct parallel…
Status and future of GaN-based vertical-cavity surface-emitting lasers
NASA Astrophysics Data System (ADS)
Feezell, Daniel F.
2015-03-01
Vertical-cavity surface-emitting lasers (VCSELs) offer distinct advantages over conventional edge-emitting lasers, including lower power consumption, single-longitudinal-mode operation, circularly symmetric output beams, waferlevel testing, and the ability to form densely packed, two-dimensional arrays. High-performance GaN-based VCSELs are well suited for applications in high-density optical data storage, high-resolution printing, lighting, displays, projectors, miniature atomic clocks, and chemical/biological sensing. Thus far, the performance of these devices has been limited by challenges associated with the formation of high-reflectance distributed Bragg reflectors (DBRs), optical mode confinement, carrier transport, lateral current spreading, polarization-related electric fields, and cavity-length control. This manuscript discusses the state-of-the-art results for electrically injected GaN-based VCSELs and reviews approaches to overcome the key challenges currently preventing higher performance devices. The manuscript also describes the development of nonpolar GaN-based VCSELs on free-standing GaN. Nonpolar orientations exhibit anisotropic optical gain within the quantum well plane and uniquely enable VCSELs with a well-defined and stable polarization state. In addition, a detailed description of a band-gap-selective photoelectrochemical etching (BGS PECE) process for substrate removal and fine cavity length control on free-standing GaN substrates is provided.
A SAT Based Effective Algorithm for the Directed Hamiltonian Cycle Problem
NASA Astrophysics Data System (ADS)
Jäger, Gerold; Zhang, Weixiong
The Hamiltonian cycle problem (HCP) is an important combinatorial problem with applications in many areas. While thorough theoretical and experimental analyses have been made on the HCP in undirected graphs, little is known for the HCP in directed graphs (DHCP). The contribution of this work is an effective algorithm for the DHCP. Our algorithm explores and exploits the close relationship between the DHCP and the Assignment Problem (AP) and utilizes a technique based on Boolean satisfiability (SAT). By combining effective algorithms for the AP and SAT, our algorithm significantly outperforms previous exact DHCP algorithms including an algorithm based on the award-winning Concorde TSP algorithm.
NASA Astrophysics Data System (ADS)
Nakamura, Eiji; Ueno, Kohei; Ohta, Jitsuo; Fujioka, Hiroshi; Oshima, Masaharu
2014-02-01
P-type doping of GaN by pulsed sputtering deposition (PSD) at a low growth temperature of 480 °C and dramatic reduction in the growth process temperature for InGaN-based light-emitting diodes (LEDs) were achieved. Mg-doped GaN layers grown on semi-insulating GaN at 480 °C exhibited clear p-type conductivity with a hole concentration and mobility of 3.0 × 1017 cm-3 and 3.1 cm2 V-1 s-1, respectively. GaN/In0.33Ga0.67N/GaN LEDs fabricated at 480 °C showed clear rectifying characteristics and a bright electroluminescence emission near 640 nm. These results indicate that this low temperature PSD growth technique is quite promising for the production of nitride-based light-emitting devices on large-area glass substrates.
A point matching algorithm based on reference point pair
NASA Astrophysics Data System (ADS)
Zou, Huanxin; Zhu, Youqing; Zhou, Shilin; Lei, Lin
2016-03-01
Outliers and occlusions are important degradation in the real application of point matching. In this paper, a novel point matching algorithm based on the reference point pairs is proposed. In each iteration, it firstly eliminates the dubious matches to obtain the relatively accurate matching points (reference point pairs), and then calculates the shape contexts of the removed points with reference to them. After re-matching the removed points, the reference point pairs are combined to achieve better correspondences. Experiments on synthetic data validate the advantages of our method in comparison with some classical methods.
CAD Model Retrieval Based on Graduated Assignment Algorithm
NASA Astrophysics Data System (ADS)
Tao, Songqiao
2015-06-01
A retrieval approach for CAD models based on graduated assignment algorithm is proposed in this paper. First, CAD models are transformed into face adjacency graphs (FAGs). Second, the vertex compatibility matrix and edge compatibility matrix between the FAGs of the query and data models are calculated, and the similarity metric for the two comparison models is established from their compatibility matrices, which serves as the optimization objective function for selecting vertex mapping matrix M between the two comparison models. Finally, Sinkhorn's alternative normalization approach for M's rows and columns is adopted to find the optimal vertex mapping matrix M. Experimental results have shown that the proposed approach supports CAD model retrieval.
Polygon star identification based on ant colony algorithm
NASA Astrophysics Data System (ADS)
Ma, Baolin; Wu, Jie; Zhang, Hongbo
2014-11-01
In order to enhance the rate of star identification under different view fields and reduce memory storage, this paper presents a polygon star identification based on ACO algorithm .First, fast cluster analysis. Second, calculate argument for each guide star, using the advantages of ACO in fast path optimization to complete building feature polygon. Third, comparing optimization results and optimization data of guide database to realize match and identifying. Through the simulation shows that the above method can simplify searching process and structure of storage. It can promise the completeness of characteristic patterns of star image. The robustness and reliability are better than traditional triangle identification.
A multiobjective memetic algorithm based on particle swarm optimization.
Liu, Dasheng; Tan, K C; Goh, C K; Ho, W K
2007-02-01
In this paper, a new memetic algorithm (MA) for multiobjective (MO) optimization is proposed, which combines the global search ability of particle swarm optimization with a synchronous local search heuristic for directed local fine-tuning. A new particle updating strategy is proposed based upon the concept of fuzzy global-best to deal with the problem of premature convergence and diversity maintenance within the swarm. The proposed features are examined to show their individual and combined effects in MO optimization. The comparative study shows the effectiveness of the proposed MA, which produces solution sets that are highly competitive in terms of convergence, diversity, and distribution. PMID:17278557
NASA Astrophysics Data System (ADS)
Khehra, Baljit Singh; Pharwaha, Amar Partap Singh
2016-06-01
Ductal carcinoma in situ (DCIS) is one type of breast cancer. Clusters of microcalcifications (MCCs) are symptoms of DCIS that are recognized by mammography. Selection of robust features vector is the process of selecting an optimal subset of features from a large number of available features in a given problem domain after the feature extraction and before any classification scheme. Feature selection reduces the feature space that improves the performance of classifier and decreases the computational burden imposed by using many features on classifier. Selection of an optimal subset of features from a large number of available features in a given problem domain is a difficult search problem. For n features, the total numbers of possible subsets of features are 2n. Thus, selection of an optimal subset of features problem belongs to the category of NP-hard problems. In this paper, an attempt is made to find the optimal subset of MCCs features from all possible subsets of features using genetic algorithm (GA), particle swarm optimization (PSO) and biogeography-based optimization (BBO). For simulation, a total of 380 benign and malignant MCCs samples have been selected from mammogram images of DDSM database. A total of 50 features extracted from benign and malignant MCCs samples are used in this study. In these algorithms, fitness function is correct classification rate of classifier. Support vector machine is used as a classifier. From experimental results, it is also observed that the performance of PSO-based and BBO-based algorithms to select an optimal subset of features for classifying MCCs as benign or malignant is better as compared to GA-based algorithm.
Research on Palmprint Identification Method Based on Quantum Algorithms
Zhang, Zhanzhan
2014-01-01
Quantum image recognition is a technology by using quantum algorithm to process the image information. It can obtain better effect than classical algorithm. In this paper, four different quantum algorithms are used in the three stages of palmprint recognition. First, quantum adaptive median filtering algorithm is presented in palmprint filtering processing. Quantum filtering algorithm can get a better filtering result than classical algorithm through the comparison. Next, quantum Fourier transform (QFT) is used to extract pattern features by only one operation due to quantum parallelism. The proposed algorithm exhibits an exponential speed-up compared with discrete Fourier transform in the feature extraction. Finally, quantum set operations and Grover algorithm are used in palmprint matching. According to the experimental results, quantum algorithm only needs to apply square of N operations to find out the target palmprint, but the traditional method needs N times of calculation. At the same time, the matching accuracy of quantum algorithm is almost 100%. PMID:25105165
An Evolution Based Biosensor Receptor DNA Sequence Generation Algorithm
Kim, Eungyeong; Lee, Malrey; Gatton, Thomas M.; Lee, Jaewan; Zang, Yupeng
2010-01-01
A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements. PMID:22315543
Algorithm-Based Fault Tolerance for Numerical Subroutines
NASA Technical Reports Server (NTRS)
Tumon, Michael; Granat, Robert; Lou, John
2007-01-01
A software library implements a new methodology of detecting faults in numerical subroutines, thus enabling application programs that contain the subroutines to recover transparently from single-event upsets. The software library in question is fault-detecting middleware that is wrapped around the numericalsubroutines. Conventional serial versions (based on LAPACK and FFTW) and a parallel version (based on ScaLAPACK) exist. The source code of the application program that contains the numerical subroutines is not modified, and the middleware is transparent to the user. The methodology used is a type of algorithm- based fault tolerance (ABFT). In ABFT, a checksum is computed before a computation and compared with the checksum of the computational result; an error is declared if the difference between the checksums exceeds some threshold. Novel normalization methods are used in the checksum comparison to ensure correct fault detections independent of algorithm inputs. In tests of this software reported in the peer-reviewed literature, this library was shown to enable detection of 99.9 percent of significant faults while generating no false alarms.
Registration algorithm of point clouds based on multiscale normal features
NASA Astrophysics Data System (ADS)
Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua
2015-01-01
The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.
Multi-expert tracking algorithm based on improved compressive tracker
NASA Astrophysics Data System (ADS)
Feng, Yachun; Zhang, Hong; Yuan, Ding
2015-12-01
Object tracking is a challenging task in computer vision. Most state-of-the-art methods maintain an object model and update the object model by using new examples obtained incoming frames in order to deal with the variation in the appearance. It will inevitably introduce the model drift problem into the object model updating frame-by-frame without any censorship mechanism. In this paper, we adopt a multi-expert tracking framework, which is able to correct the effect of bad updates after they happened such as the bad updates caused by the severe occlusion. Hence, the proposed framework exactly has the ability which a robust tracking method should process. The expert ensemble is constructed of a base tracker and its formal snapshot. The tracking result is produced by the current tracker that is selected by means of a simple loss function. We adopt an improved compressive tracker as the base tracker in our work and modify it to fit the multi-expert framework. The proposed multi-expert tracking algorithm significantly improves the robustness of the base tracker, especially in the scenes with frequent occlusions and illumination variations. Experiments on challenging video sequences with comparisons to several state-of-the-art trackers demonstrate the effectiveness of our method and our tracking algorithm can run at real-time.
NASA Astrophysics Data System (ADS)
Alim, Mohammad A.; Rezazadeh, Ali A.; Gaquiere, Christophe
2016-05-01
Thermal and small-signal model parameters analysis have been carried out on 0.5 μm × (2 × 100 μm) AlGaAs/GaAs HEMT grown on semi-insulating GaAs substrate and 0.25 μm × (2 × 100 μm) AlGaN/GaN HEMT grown on SiC substrate. Two different technologies are investigated in order to establish a detailed understanding of their capabilities in terms of frequency and temperature using on-wafer S-parameter measurement over the temperature range from -40 to 150 °C up to 50 GHz. The equivalent circuit parameters as well as their temperature-dependent behavior of the two technologies were analyzed and discussed for the first time. The principle elevation or degradation of transistor parameters with temperature demonstrates the great potential of GaN device for high frequency and high temperature applications. The result provides some valuable insights for future design optimizations of advanced GaN and a comparison of this with the GaAs technology.
Strain relaxation of thick (11–22) semipolar InGaN layer for long wavelength nitride-based device
Kim, Jaehwan; Min, Daehong; Jang, Jongjin; Lee, Kyuseung; Chae, Sooryong; Nam, Okhyun
2014-10-28
In this study, the properties of thick stress-relaxed (11–22) semipolar InGaN layers were investigated. Owing to the inclination of growth orientation, misfit dislocations (MDs) occurred at the heterointerface when the strain state of the (11–22) semipolar InGaN layers reached the critical point. We found that unlike InGaN layers based on polar and nonpolar growth orientations, the surface morphologies of the stress-relaxed (11–22) semipolar InGaN layers did not differ from each other and were similar to the morphology of the underlying GaN layer. In addition, misfit strain across the whole InGaN layer was gradually relaxed by MD formation at the heterointerface. To minimize the effect of surface roughness and defects in GaN layers on the InGaN layer, we conducted further investigation on a thick (11–22) semipolar InGaN layer grown on an epitaxial lateral overgrown GaN template. We found that the lateral indium composition across the whole stress-relaxed InGaN layer was almost uniform. Therefore, thick stress-relaxed (11–22) semipolar InGaN layers are suitable candidates for use as underlying layers in long-wavelength devices, as they can be used to control strain accumulation in the heterostructure active region without additional influence of surface roughness.
NASA Astrophysics Data System (ADS)
Rajan, C. Christober Asir
2010-10-01
The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Genetic Algorithms (GA's) are general-purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms such as neural section, genetic recombination and survival of the fittest. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status ("flat start"). Here the parents are obtained from a pre-defined set of solution's i.e. each and every solution is adjusted to meet the requirements. Then, a random recommitment is carried out with respect to the unit's minimum down times. And SA improves the status. A 66-bus utility power system with twelve generating units in India demonstrates the effectiveness of the proposed approach. Numerical results are shown comparing the cost solutions and computation time obtained by using the Genetic Algorithm method and other conventional methods.
NASA Astrophysics Data System (ADS)
Zhang, Xiuping
In this paper, the weights of a Neural Network using Chaotic Imperialist Competitive Algorithm are updated. A three-layered Perseptron Neural Network applied for prediction of the maximum worth of the stocks changed in TEHRAN's bourse market. We trained this neural network with CICA, ICA, PSO and GA algorithms and compared the results with each other. The consideration of the results showed that the training and test error of the network trained by the CICA algorithm has been reduced in comparison to the other three methods.
Vision-based vehicle detection and tracking algorithm design
NASA Astrophysics Data System (ADS)
Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi
2009-12-01
The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.
Averkiev, N. S.; Slipchenko, S. O. Sokolova, Z. N.; Pikhtin, N. A.; Tarasov, I. S.
2007-03-15
Generation of a difference-frequency wave by two electromagnetic waves propagating in a heterolaser is analyzed theoretically. Calculations are carried out for InGaAs/GaAs/AlGaAs heterostructures of design optimized to attain maximum lasing power. It is shown that phase matching between the primary waves and the difference-frequency wave may persist over a distance of {approx}1 mm, comparable to the cavity length (2-3 mm), and the conversion coefficient can be as large as several percent.
68Ga-PET radiopharmacy: A generator-based alternative to 18F-radiopharmacy.
Maecke, H R; André, J P
2007-01-01
Positron emission tomography (PET) is becoming a dominating method in the field of molecular imaging. Most commonly used radionuclides are accelerator produced 11C and 18F. An alternative method to label biomolecules is the use of metallic positron emitters; among them 68Ga is the most promising as it can be produced from a generator system consisting of an inorganic or organic matrix immobilizing the parent radionuclide 68Ge. Germanium-68 has a long half-life of 271 days which allows the production of long-lived, potentially very cost-effective generator systems. A commercial generator from Obninsk, Russia, is available which uses TiO2 as an inorganic matrix to immobilize 68Ge in the oxidation state IV+. 68Ge(IV) is chemically sufficiently different to allow efficient separation from 68Ga(III). Ga3+ is redox-inert; its coordination chemistry is dominated by its hard acid character. A variety of mono- and bifunctional chelators were developed which allow immobilization of 68Ga3+ and convenient coupling to biomolecules. Especially peptides targeting G-protein coupled receptors overexpressed on human tumour cells have been studied preclinically and in patient studies showing high and specific tumour uptake and specific localization. 68Ga-radiopharmacy may indeed be an alternative to 18F-based radiopharmacy. Freeze-dried, kit-formulated precursors along with the generator may be provided, similar to the 99Mo/99mTc-based radiopharmacy, still the mainstay of nuclear medicine. PMID:17172157
Abernathy, C.R.; Cho, H.; Hahn, Y.B.; Hays, D.C.; Hobson, W.S.; Jung, K.B.; Lambers, E.S.; Pearton, S.J.; Shul, R.J.
1998-11-23
A parametric study of Inductively Coupled Plasma etching of InP, InSb, InGaP and InGaAs has been carried out in IC1/Ar and IBr/Ar chemistries. Etch rates in excess of 3.1 prrdmin for InP, 3.6 prnh-nin for InSb, 2.3 pm/min for InGaP and 2.2 ~rrdmin for InGaAs were obtained in IBr/Ar plasmas. The ICP etching of In-based materials showed a general tendency: the etch rates increased substantially with increasing the ICP source power and rf chuck power in both chemistries, while they decreased with increasing chamber pressure. The IBr/Ar chemistry typically showed higher etch rates than IC1/Ar, but the etched surface mophologies were fairly poor for both chemistries.
A class of kernel based real-time elastography algorithms.
Kibria, Md Golam; Hasan, Md Kamrul
2015-08-01
In this paper, a novel real-time kernel-based and gradient-based Phase Root Seeking (PRS) algorithm for ultrasound elastography is proposed. The signal-to-noise ratio of the strain image resulting from this method is improved by minimizing the cross-correlation discrepancy between the pre- and post-compression radio frequency signals with an adaptive temporal stretching method and employing built-in smoothing through an exponentially weighted neighborhood kernel in the displacement calculation. Unlike conventional PRS algorithms, displacement due to tissue compression is estimated from the root of the weighted average of the zero-lag cross-correlation phases of the pair of corresponding analytic pre- and post-compression windows in the neighborhood kernel. In addition to the proposed one, the other time- and frequency-domain elastography algorithms (Ara et al., 2013; Hussain et al., 2012; Hasan et al., 2012) proposed by our group are also implemented in real-time using Java where the computations are serially executed or parallely executed in multiple processors with efficient memory management. Simulation results using finite element modeling simulation phantom show that the proposed method significantly improves the strain image quality in terms of elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe) and mean structural similarity (MSSIM) for strains as high as 4% as compared to other reported techniques in the literature. Strain images obtained for the experimental phantom as well as in vivo breast data of malignant or benign masses also show the efficacy of our proposed method over the other reported techniques in the literature. PMID:25929595
A genetic algorithm approach for assessing soil liquefaction potential based on reliability method
NASA Astrophysics Data System (ADS)
Bagheripour, M. H.; Shooshpasha, I.; Afzalirad, M.
2012-02-01
Deterministic approaches are unable to account for the variations in soil's strength properties, earthquake loads, as well as source of errors in evaluations of liquefaction potential in sandy soils which make them questionable against other reliability concepts. Furthermore, deterministic approaches are incapable of precisely relating the probability of liquefaction and the factor of safety (FS). Therefore, the use of probabilistic approaches and especially, reliability analysis is considered since a complementary solution is needed to reach better engineering decisions. In this study, Advanced First-Order Second-Moment (AFOSM) technique associated with genetic algorithm (GA) and its corresponding sophisticated optimization techniques have been used to calculate the reliability index and the probability of liquefaction. The use of GA provides a reliable mechanism suitable for computer programming and fast convergence. A new relation is developed here, by which the liquefaction potential can be directly calculated based on the estimated probability of liquefaction ( P L ), cyclic stress ratio (CSR) and normalized standard penetration test (SPT) blow counts while containing a mean error of less than 10% from the observational data. The validity of the proposed concept is examined through comparison of the results obtained by the new relation and those predicted by other investigators. A further advantage of the proposed relation is that it relates P L and FS and hence it provides possibility of decision making based on the liquefaction risk and the use of deterministic approaches. This could be beneficial to geotechnical engineers who use the common methods of FS for evaluation of liquefaction. As an application, the city of Babolsar which is located on the southern coasts of Caspian Sea is investigated for liquefaction potential. The investigation is based primarily on in situ tests in which the results of SPT are analysed.
NASA Astrophysics Data System (ADS)
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
A Progressive Image Compression Method Based on EZW Algorithm
NASA Astrophysics Data System (ADS)
Du, Ke; Lu, Jianming; Yahagi, Takashi
A simple method based on the EZW algorithm is presented for improving image compression performance. Recent success in wavelet image coding is mainly attributed to recognition of the importance of data organization and representation. There have been several very competitive wavelet coders developed, namely, Shapiro's EZW(Embedded Zerotree Wavelets)(1), Said and Pearlman's SPIHT(Set Partitioning In Hierarchical Trees)(2), and Bing-Bing Chai's SLCCA(Significance-Linked Connected Component Analysis for Wavelet Image Coding)(3). The EZW algorithm is based on five key concepts: (1) a DWT(Discrete Wavelet Transform) or hierarchical subband decomposition, (2) prediction of the absence of significant information across scales by exploiting self-similarity inherent in images, (3) entropy-coded successive-approximation quantization, (4) universal lossless data compression which is achieved via adaptive arithmetic coding. and (5) DWT coefficients' degeneration from high scale subbands to low scale subbands. In this paper, we have improved the self-similarity statistical characteristic in concept (5) and present a progressive image compression method.
A cooperative control algorithm for camera based observational systems.
Young, Joseph G.
2012-01-01
Over the last several years, there has been considerable growth in camera based observation systems for a variety of safety, scientific, and recreational applications. In order to improve the effectiveness of these systems, we frequently desire the ability to increase the number of observed objects, but solving this problem is not as simple as adding more cameras. Quite often, there are economic or physical restrictions that prevent us from adding additional cameras to the system. As a result, we require methods that coordinate the tracking of objects between multiple cameras in an optimal way. In order to accomplish this goal, we present a new cooperative control algorithm for a camera based observational system. Specifically, we present a receding horizon control where we model the underlying optimal control problem as a mixed integer linear program. The benefit of this design is that we can coordinate the actions between each camera while simultaneously respecting its kinematics. In addition, we further improve the quality of our solution by coupling our algorithm with a Kalman filter. Through this integration, we not only add a predictive component to our control, but we use the uncertainty estimates provided by the filter to encourage the system to periodically observe any outliers in the observed area. This combined approach allows us to intelligently observe the entire region of interest in an effective and thorough manner.
Particle swarm optimization algorithm based low cost magnetometer calibration
NASA Astrophysics Data System (ADS)
Ali, A. S.; Siddharth, S., Syed, Z., El-Sheimy, N.
2011-12-01
Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments
Digital super-resolution microscopy using example-based algorithm
NASA Astrophysics Data System (ADS)
Ishikawa, Shinji; Hayasaki, Yoshio
2015-05-01
We propose a super-resolution microscopy with a confocal optical setup and an example-based algorithm. The example-based super-resolution algorithm was performed by an example database which is constructed by learning a lot of sets of a high-resolution patch and a low-resolution patch. The high-resolution patch is a part of the high-resolution image of an object model expressed in a computer, and the low-resolution patch is calculated from the high-resolution patch in consideration with a spatial property of an optical microscope. In the reconstruction process, a low-resolution image observed by the confocal optical setup with an image sensor is converted to the super-resolved high-resolution image selected by a pattern matching method from the example database. We demonstrate the adequate selection of the patch size and the weighting superposition method performs the super resolution with a low signal-to noise ratio.
Algorithm design for a gun simulator based on image processing
NASA Astrophysics Data System (ADS)
Liu, Yu; Wei, Ping; Ke, Jun
2015-08-01
In this paper, an algorithm is designed for shooting games under strong background light. Six LEDs are uniformly distributed on the edge of a game machine screen. They are located at the four corners and in the middle of the top and the bottom edges. Three LEDs are enlightened in the odd frames, and the other three are enlightened in the even frames. A simulator is furnished with one camera, which is used to obtain the image of the LEDs by applying inter-frame difference between the even and odd frames. In the resulting images, six LED are six bright spots. To obtain the LEDs' coordinates rapidly, we proposed a method based on the area of the bright spots. After calibrating the camera based on a pinhole model, four equations can be found using the relationship between the image coordinate system and the world coordinate system with perspective transformation. The center point of the image of LEDs is supposed to be at the virtual shooting point. The perspective transformation matrix is applied to the coordinate of the center point. Then we can obtain the virtual shooting point's coordinate in the world coordinate system. When a game player shoots a target about two meters away, using the method discussed in this paper, the calculated coordinate error is less than ten mm. We can obtain 65 coordinate results per second, which meets the requirement of a real-time system. It proves the algorithm is reliable and effective.
Chaos Time Series Prediction Based on Membrane Optimization Algorithms
Li, Meng; Yi, Liangzhong; Pei, Zheng; Gao, Zhisheng
2015-01-01
This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ, m) and least squares support vector machine (LS-SVM) (γ, σ) by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM) broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). PMID:25874249
Rank-based algorithms for anlaysis of microarrays
NASA Astrophysics Data System (ADS)
Liu, Wei-min; Mei, Rui; Bartell, Daniel M.; Di, Xiaojun; Webster, Teresa A.; Ryder, Tom
2001-06-01
Analysis of microarray data often involves extracting information from raw intensities of spots of cells and making certain calls. Rank-based algorithms are powerful tools to provide probability values of hypothesis tests, especially when the distribution of the intensities is unknown. For our current gene expression arrays, a gene is detected by a set of probe pairs consisting of perfect match and mismatch cells. The one-sided upper-tail Wilcoxon's signed rank test is used in our algorithms for absolute calls (whether a gene is detected or not), as well as comparative calls (whether a gene is increasing or decreasing or no significant change in a sample compared with another sample). We also test the possibility to use only perfect match cells to make calls. This paper focuses on absolute calls. We have developed error analysis methods and software tools that allow us to compare the accuracy of the calls in the presence or absence of mismatch cells at different target concentrations. The usage of nonparametric rank-based tests is not limited to absolute and comparative calls of gene expression chips. They can also be applied to other oligonucleotide microarrays for genotyping and mutation detection, as well as spotted arrays.
Implicit function-based phantoms for evaluation of registration algorithms
NASA Astrophysics Data System (ADS)
Gopalakrishnan, Girish; Poston, Timothy; Nagaraj, Nithin; Mullick, Rakesh; Knoplioch, Jerome
2005-04-01
Medical image fusion is increasingly enhancing diagnostic accuracy by synergizing information from multiple images, obtained by the same modality at different times or from complementary modalities such as structural information from CT and functional from PET. An active, crucial research topic in fusion is validation of the registration (point-to-point correspondence) used. Phantoms and other simulated studies are useful in the absence of, or as a preliminary to, definitive clinical tests. Software phantoms in specific have the added advantage of robustness, repeatability and reproducibility. Our virtual-lung-phantom-based scheme can test the accuracy of any registration algorithm and is flexible enough for added levels of complexity (addition of blur/anti-alias, rotate/warp, and modality-associated noise) to help evaluate the robustness of an image registration/fusion methodology. Such a framework extends easily to different anatomies. The feature of adding software-based fiducials both within and outside simulated anatomies prove more beneficial when compared to experiments using data from external fiducials on a patient. It would help the diagnosing clinician make a prudent choice of registration algorithm.
Chaos time series prediction based on membrane optimization algorithms.
Li, Meng; Yi, Liangzhong; Pei, Zheng; Gao, Zhisheng; Peng, Hong
2015-01-01
This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ, m) and least squares support vector machine (LS-SVM) (γ, σ) by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM) broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). PMID:25874249
GPU-based parallel algorithm for blind image restoration using midfrequency-based methods
NASA Astrophysics Data System (ADS)
Xie, Lang; Luo, Yi-han; Bao, Qi-liang
2013-08-01
GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images.
Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang
2015-01-01
To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466
TEM based analysis of III-Sb VECSELs on GaAs substrates for improved laser performance.
NASA Astrophysics Data System (ADS)
Ahirwar, P.; Shima, D.; Rotter, T. J.; Clark, S. P. R...; Addamane, S. J.; Hains, C. P.; Dawson, L. R.; Balakrishnan, G.; Bedford, R.; Lai, Y. Y.; Laurain, A.; Hader, J.; Moloney, J. V.
2013-02-01
The antimonide based vertical external cavity surface emitting lasers (VECSELs) operating in the 1.8 to 2.8 Tm wavelength range are typically based on InGaAsSb/AlGaAsSb quantum wells on AlAsSb/GaSb distributed Bragg reflectors (DBRs) grown lattice-matched on GaSb substrates. The ability to grow such antimonide VECSEL structures on GaAs substrates can take advantage of the superior AlAs based etch-stop layers and mature DBR technology based on GaAs substrates. The growth of such III-Sb VECSELs on GaAs substrates is non-trivial due to the 7.78% lattice mismatch between the antimonide based active region and the GaAs/AlGaAs DBR. The challenge is therefore to reduce the threading dislocation density in the active region without a very thick metamorphic buffer and this is achieved by inducing 90 ° interfacial mist dislocation arrays between the GaSb and GaAs layers. In this presentation we make use of cross section transmission electron microscopy to analyze a variety of approaches to designing and growing III-Sb VECSELs on GaAs substrates to achieve a low threading dislocation density. We shall demonstrate the failure mechanisms in such growths and we analyze the extent to which the threading dislocations are able to permeate a thick active region. Finally, we present growth strategies and supporting results showing low-defect density III-Sb VECSEL active regions on GaAs.
Interpreting lateral 2-D bank hyporheic flux based on GA-VS2DH
NASA Astrophysics Data System (ADS)
Su, Xiaoru; Shu, Longcang; Wen, Zhonghui; Lu, Chengpeng; Eshete, Abunu
2015-04-01
Hyporheic flux is of great significance for evaluating water resources and protecting ecosystem health. Heat as a tracer was widely used in recognizing the hyporheic flux with high precision, low cost and great convenience. The hyporheic flux in bank cross-section occurs in vertical and lateral directions. In order to depict the hyporheic flow path and its spatial distribution in bank area, a GA-VS2DH nested loop method was developed based on Microsoft Visual Basic 6.0. VS2DH was applied to model 2-D bank hyporheic flow and GA was used to calibrate the model automatically by minimizing the difference between observed and simulated temperatures of sediments in bank area. A hypothetic model was developed to assess the reliability of GA-VS2DH in simulating hyporheic flux and parameters estimation in river bank system. Some numerical experiments were conducted to recognize the capability of GA-VS2DH. Then the GA-VS2DH was applied in two field sites with river bank sediments made by sand and clay, respectively, to verify the reliability of the method. The results indicated that the simulated hyporheic flux and parameters of GA-VS2DH were reliable. GA-VS2DH could be applied in interpreting lateral 2-D bank hyporheic flux. Hydraulic conductivity (K) and dispersivity (D) are the two most sensitive parameters and the estimates of these two parameters have more reliability than the others. The estimates of hydraulic conductivity at Dawen River site and Qinhuai River site are 1.293 and 0.019 m/d, respectively, which corresponded to sand and clay sediment in the two sites.
Calciati, Marco; Vallone, Marco; Zhou, Xiangyu; Ghione, Giovanni; Goano, Michele Bertazzi, Francesco; Meneghini, Matteo; Meneghesso, Gaudenzio; Zanoni, Enrico; Verzellesi, Giovanni; Zhu, Dandan; Humphreys, Colin
2014-06-15
Electroluminescence (EL) characterization of InGaN/GaN light-emitting diodes (LEDs), coupled with numerical device models of different sophistication, is routinely adopted not only to establish correlations between device efficiency and structural features, but also to make inferences about the loss mechanisms responsible for LED efficiency droop at high driving currents. The limits of this investigative approach are discussed here in a case study based on a comprehensive set of current- and temperature-dependent EL data from blue LEDs with low and high densities of threading dislocations (TDs). First, the effects limiting the applicability of simpler (closed-form and/or one-dimensional) classes of models are addressed, like lateral current crowding, vertical carrier distribution nonuniformity, and interband transition broadening. Then, the major sources of uncertainty affecting state-of-the-art numerical device simulation are reviewed and discussed, including (i) the approximations in the transport description through the multi-quantum-well active region, (ii) the alternative valence band parametrizations proposed to calculate the spontaneous emission rate, (iii) the difficulties in defining the Auger coefficients due to inadequacies in the microscopic quantum well description and the possible presence of extra, non-Auger high-current-density recombination mechanisms and/or Auger-induced leakage. In the case of the present LED structures, the application of three-dimensional numerical-simulation-based analysis to the EL data leads to an explanation of efficiency droop in terms of TD-related and Auger-like nonradiative losses, with a C coefficient in the 10{sup −30} cm{sup 6}/s range at room temperature, close to the larger theoretical calculations reported so far. However, a study of the combined effects of structural and model uncertainties suggests that the C values thus determined could be overestimated by about an order of magnitude. This preliminary
A genetic algorithm based multi-objective shape optimization scheme for cementless femoral implant.
Chanda, Souptick; Gupta, Sanjay; Kumar Pratihar, Dilip
2015-03-01
The shape and geometry of femoral implant influence implant-induced periprosthetic bone resorption and implant-bone interface stresses, which are potential causes of aseptic loosening in cementless total hip arthroplasty (THA). Development of a shape optimization scheme is necessary to achieve a trade-off between these two conflicting objectives. The objective of this study was to develop a novel multi-objective custom-based shape optimization scheme for cementless femoral implant by integrating finite element (FE) analysis and a multi-objective genetic algorithm (GA). The FE model of a proximal femur was based on a subject-specific CT-scan dataset. Eighteen parameters describing the nature of four key sections of the implant were identified as design variables. Two objective functions, one based on implant-bone interface failure criterion, and the other based on resorbed proximal bone mass fraction (BMF), were formulated. The results predicted by the two objective functions were found to be contradictory; a reduction in the proximal bone resorption was accompanied by a greater chance of interface failure. The resorbed proximal BMF was found to be between 23% and 27% for the trade-off geometries as compared to ∼39% for a generic implant. Moreover, the overall chances of interface failure have been minimized for the optimal designs, compared to the generic implant. The adaptive bone remodeling was also found to be minimal for the optimally designed implants and, further with remodeling, the chances of interface debonding increased only marginally. PMID:25392855
Optimized Laplacian image sharpening algorithm based on graphic processing unit
NASA Astrophysics Data System (ADS)
Ma, Tinghuai; Li, Lu; Ji, Sai; Wang, Xin; Tian, Yuan; Al-Dhelaan, Abdullah; Al-Rodhaan, Mznah
2014-12-01
In classical Laplacian image sharpening, all pixels are processed one by one, which leads to large amount of computation. Traditional Laplacian sharpening processed on CPU is considerably time-consuming especially for those large pictures. In this paper, we propose a parallel implementation of Laplacian sharpening based on Compute Unified Device Architecture (CUDA), which is a computing platform of Graphic Processing Units (GPU), and analyze the impact of picture size on performance and the relationship between the processing time of between data transfer time and parallel computing time. Further, according to different features of different memory, an improved scheme of our method is developed, which exploits shared memory in GPU instead of global memory and further increases the efficiency. Experimental results prove that two novel algorithms outperform traditional consequentially method based on OpenCV in the aspect of computing speed.
Vibration-based damage detection algorithm for WTT structures
NASA Astrophysics Data System (ADS)
Nguyen, Tuan-Cuong; Kim, Tae-Hwan; Choi, Sang-Hoon; Ryu, Joo-Young; Kim, Jeong-Tae
2016-04-01
In this paper, the integrity of a wind turbine tower (WTT) structure is nondestructively estimated using its vibration responses. Firstly, a damage detection algorithm using changes in modal characteristics to predict damage locations and severities in structures is outlined. Secondly, a finite element (FE) model based on a real WTT structure is established by using a commercial software, Midas FEA. Thirdly, forced vibration tests are performed on the FE model of the WTT structure under various damage scenarios. The changes in modal parameters such as natural frequencies and mode shapes are examined for damage monitoring in the structure. Finally, the feasibility of the vibration-based damage detection method is numerically verified by predicting locations and severities of the damage in the FE model of the WTT structure.
Controller design based on μ analysis and PSO algorithm.
Lari, Ali; Khosravi, Alireza; Rajabi, Farshad
2014-03-01
In this paper an evolutionary algorithm is employed to address the controller design problem based on μ analysis. Conventional solutions to μ synthesis problem such as D-K iteration method often lead to high order, impractical controllers. In the proposed approach, a constrained optimization problem based on μ analysis is defined and then an evolutionary approach is employed to solve the optimization problem. The goal is to achieve a more practical controller with lower order. A benchmark system named two-tank system is considered to evaluate performance of the proposed approach. Simulation results show that the proposed controller performs more effective than high order H(∞) controller and has close responses to the high order D-K iteration controller as the common solution to μ synthesis problem. PMID:24314832
NASA Astrophysics Data System (ADS)
Kaun, Stephen W.; Mazumder, Baishakhi; Fireman, Micha N.; Kyle, Erin C. H.; Mishra, Umesh K.; Speck, James S.
2015-05-01
When grown at a high temperature (820 °C) by ammonia-based molecular beam epitaxy (NH3-MBE), the AlN layers of metal-polar AlGaN/AlN/GaN heterostructures had a high GaN mole fraction (∼0.15), as identified by atom probe tomography in a previous study (Mazumder et al 2013 Appl. Phys. Lett. 102 111603). In the study presented here, growth at low temperature (<740 °C) by NH3-MBE yielded metal-polar AlN layers that were essentially pure at the alloy level. The improved purity of the AlN layers grown at low temperature was correlated to a dramatic increase in the sheet density of the two-dimensional electron gas (2DEG) at the AlN/GaN heterointerface. Through application of an In surfactant, metal-polar AlN(3.5 nm)/GaN and AlGaN/AlN(2.5 nm)/GaN heterostructures grown at low temperature yielded low 2DEG sheet resistances of 177 and 285 Ω/□, respectively.
Slot plasmonic waveguide based on doped-GaAs for terahertz deep-subwavelength applications.
Amarloo, Hadi; Safavi-Naeini, Safieddin
2015-11-01
A new plasmonic waveguide for deep-subwavelength field localization at the terahertz (THz) range of frequency is proposed. GaAs with optimum doping level is used as the plasmonic material. The waveguide structure is a narrow slot in a thin GaAs film on top of the quartz substrate. The waveguide characteristics are analyzed, and its dimensions are optimized to minimize the losses. It is shown that the mode size of the proposed waveguide is less than λ/16 by λ/16. The proposed plasmonic waveguide can be a platform for numerous THz plasmonic-based integrated devices, such as integrated sensors and imagers. PMID:26560933
Broadband nanophotonic waveguides and resonators based on epitaxial GaN thin films
Bruch, Alexander W.; Xiong, Chi; Leung, Benjamin; Poot, Menno; Han, Jung; Tang, Hong X.
2015-10-05
We demonstrate broadband, low loss optical waveguiding in single crystalline GaN grown epitaxially on c-plane sapphire wafers through a buffered metal-organic chemical vapor phase deposition process. High Q optical microring resonators are realized in near infrared, infrared, and near visible regimes with intrinsic quality factors exceeding 50 000 at all the wavelengths we studied. TEM analysis of etched waveguide reveals growth and etch-induced defects. Reduction of these defects through improved material and device processing could lead to even lower optical losses and enable a wideband photonic platform based on GaN-on-sapphire material system.
A MEMS-Based Micro Biopsy Actuator for the Capsular Endoscope Using LiGA Process
NASA Astrophysics Data System (ADS)
Park, Sunkil; Koo, Kyo-In; Kim, Gil-Sub; Bang, Seoung Min; Song, Si Young; Chu, Chong Nam; Jeon, Doyoung; Cho, Dongil ``Dan''
2007-01-01
This paper presents a LiGA (German acronym for LIthografie, Galvanoformung, Abformung) based micro biopsy actuator for the capsular endoscope. The proposed fabricated actuator aims to extract sample tissues inside small gastric intestines, that cannot be reached by conventional biopsy. The actuator size is 10 mm in diameter and 1.8 mm in length. The mechanism is of a slider-crank type. The actuator consists of trigger, rotational module, and micro biopsy tool. The core components are fabricated using the LiGA process, for overcoming the limitations in accuracy of conventional precision machining.
Cryogenic operation of GaAs based multiplier chains to 400 GHz
NASA Technical Reports Server (NTRS)
Maestrini, A.; Pukala, D.; Maiwald, F.; Schlecht, E.; Chattopadhyay, G.; Mehdi, I.
2000-01-01
The FIRST/HIFI mission allows for the local oscillator frequency multiplier chains to be cooled to 120 - 150 K in order to increase available output power. This paper will discuss the implication of cooling on GaAs based planar Schottky diode varactors for flight applications.
Hyperspectral recognition of processing tomato early blight based on GA and SVM
NASA Astrophysics Data System (ADS)
Yin, Xiaojun; Zhao, SiFeng
2013-03-01
Processing tomato early blight seriously affect the yield and quality of its.Determine the leaves spectrum of different disease severity level of processing tomato early blight.We take the sensitive bands of processing tomato early blight as support vector machine input vector.Through the genetic algorithm(GA) to optimize the parameters of SVM, We could recognize different disease severity level of processing tomato early blight.The result show:the sensitive bands of different disease severity levels of processing tomato early blight is 628-643nm and 689-692nm.The sensitive bands are as the GA and SVM input vector.We get the best penalty parameters is 0.129 and kernel function parameters is 3.479.We make classification training and testing by polynomial nuclear,radial basis function nuclear,Sigmoid nuclear.The best classification model is the radial basis function nuclear of SVM. Training accuracy is 84.615%,Testing accuracy is 80.681%.It is combined GA and SVM to achieve multi-classification of processing tomato early blight.It is provided the technical support of prediction processing tomato early blight occurrence, development and diffusion rule in large areas.
Development of chemically assisted etching method for GaAs-based optoelectronic devices
Gaillard, M.; Rhallabi, A.; Elmonser, L.; Talneau, A.; Pommereau, F.; Pagnod-Rossiaux, Ph.; Bouadma, N.
2005-03-01
Chemically assisted ion beam etching of GaAs-based materials using Cl{sub 2} reactive gas was has been experimentally and theoretically examined. The primary effort was the design of an etching system for high reproducibility and improved throughput. Characteristics of the etching process, i.e., etch rate, etch profiles, and surface morphology as a function of etching parameters, i.e., substrate temperature, Cl{sub 2} flow rate, ion current density, and energy are reported. In addition, we have analyzed the etched surfaces qualitatively by Auger electron spectroscopy, and quantitatively by atomic force microscopy. The developed process yielded stoichiometric and smooth GaAs surfaces. Moreover, in order to understand the mechanism of the Cl{sub 2} etching reaction with GaAs, a simulation of the etch profile evolution with time as function of etching parameters was carried out. Simulations were compared with experimentally derived data and were found to be in good agreement. Finally, the developed process was successfully applied to the fabrication of ridge waveguides GaAs/GaAlAs lasers with cw optical characteristics similar to wet chemical etched lasers.
Thickness dependence on the optoelectronic properties of multilayered GaSe based photodetector.
Ko, Pil Ju; Abderrahmane, Abdelkader; Takamura, Tsukasa; Kim, Nam-Hoon; Sandhu, Adarsh
2016-08-12
Two-dimensional (2D) layered materials exhibit unique optoelectronic properties at atomic thicknesses. In this paper, we fabricated metal-semiconductor-metal based photodetectors using layered gallium selenide (GaSe) with different thicknesses. The electrical and optoelectronic properties of the photodetectors were studied, and these devices showed good electrical characteristics down to GaSe flake thicknesses of 30 nm. A photograting effect was observed in the absence of a gate voltage, thereby implying a relatively high photoresponsivity. Higher values of the photoresponsivity occurred for thicker layers of GaSe with a maximum value 0.57 AW(-1) and external quantum efficiency of of 132.8%, and decreased with decreasing GaSe flake thickness. The detectivity was 4.05 × 10(10) cm Hz(1/2) W(-1) at 532 nm laser wavelength, underscoring that GaSe is a promising p-type 2D material for photodetection applications in the visible spectrum. PMID:27354428
A novel wavelength-adjusting method in InGaN-based light-emitting diodes
Deng, Zhen; Jiang, Yang; Ma, Ziguang; Wang, Wenxin; Jia, Haiqiang; Zhou, Junming; Chen, Hong
2013-01-01
The pursuit of high internal quantum efficiency (IQE) for green emission spectral regime is referred as “green gap” challenge. Now researchers place their hope on the InGaN-based materials to develop high-brightness green light-emitting diodes. However, IQE drops fast when emission wavelength of InGaN LED increases by changing growth temperature or well thickness. In this paper, a new wavelength-adjusting method is proposed and the optical properties of LED are investigated. By additional process of indium pre-deposition before InGaN well layer growth, the indium distribution along growth direction becomes more uniform, which leads to the increase of average indium content in InGaN well layer and results in a redshift of peak-wavelength. We also find that the IQE of LED with indium pre-deposition increases with the wavelength redshift. Such dependence is opposite to the IQE-wavelength behavior in conventional InGaN LEDs. The relations among the IQE, wavelength and the indium pre-deposition process are discussed. PMID:24343166
Frequency-tunable continuous-wave terahertz sources based on GaAs plasmonic photomixers
NASA Astrophysics Data System (ADS)
Yang, Shang-Hua; Jarrahi, Mona
2015-09-01
We present frequency-tunable, continuous-wave terahertz sources based on GaAs plasmonic photomixers, which offer high terahertz radiation power levels at 50% radiation duty cycle. The use of plasmonic contact electrodes enhances photomixer quantum efficiency while maintaining its ultrafast operation by concentrating a large number of photocarriers in close proximity to the device contact electrodes. Additionally, the relatively high thermal conductivity and high resistivity of GaAs allow operation under high optical pump power levels and long duty cycles without reaching the thermal breakdown limit of the photomixer. We experimentally demonstrate continuous-wave terahertz radiation with a radiation frequency tuning range of more than 2 THz and a record-high radiation power of 17 μW at 1 THz through plasmonic photomixers fabricated on a low temperature grown GaAs substrate at 50% radiation duty cycle.
Epitaxial Growth of GaN-based LEDs on Simple Sacrificial Substrates
Ian Ferguson; Chris Summers
2009-12-31
The objective of this project is to produce alternative substrate technologies for GaN-based LEDs by developing an ALD interlayer of Al{sub 2}O{sub 3} on sacrificial substrates such as ZnO and Si. A sacrificial substrate is used for device growth that can easily be removed using a wet chemical etchant leaving only the thin GaN epi-layer. After substrate removal, the GaN LED chip can then be mounted in several different ways to a metal heat sink/reflector and light extraction techniques can then be applied to the chip and compared for performance. Success in this work will lead to high efficiency LED devices with a simple low cost fabrication method and high product yield as stated by DOE goals for its solid state lighting portfolio.
Structure, magnetism, and electron-transport properties of Mn2CrGa-based nanomaterials
NASA Astrophysics Data System (ADS)
Zhang, Wenyong; Kharel, Parashu; Skomski, Ralph; Valloppilly, Shah; Li, Xingzhong; Sellmyer, David J.
2016-05-01
Mn2CrGa in the disordered cubic structure has been synthesized using rapid quenching and subsequent annealing. The cubic phase transforms to a stable tetragonal phase when a fraction of Cr or Ga is replaced by Pt or Al, respectively. All samples are ferrimagnetic with high Curie temperatures (Tc); Mn2CrGa exhibits the highest Tc of about 813 K. The tetragonal samples have appreciable values of magnetocrystalline anisotropy energy, which leads to an increase in coercivity (Hc) that approaches about 10 kOe in the Pt-doped sample. The Hc linearly increases with a decrease of temperature, concomitant with the anisotropy change with temperature. All samples are metallic and show negative magnetoresistance with room-temperature resistivities on the order of 1 mΩcm. The magnetic properties including high Tc and low magnetic moment suggest that these tetragonal materials have potential for spin-transfer-torque-based devices.
Demonstration of a GaAs-based 1550-nm continuous wave photomixer
Zhang, W.-D. Brown, E. R.; Middendorf, J. R.
2015-01-12
An Er:GaAs-based 1550-nm CW photomixer is demonstrated. The related mechanism is extrinsic photoconductivity with optical absorption between the localized deep levels created by the Er and the extended states above the conduction band edge of GaAs. With the power boost made possible by a fiber-coupled erbium-doped-fiber amplifier, the Er:GaAs photomixers, operating at 1550 nm, radiate THz power levels easily measured by a Golay cell, and display a power spectrum having a −3 dB roll-off frequency of 307 GHz. This corresponds to a photocarrier lifetime of 520 fs, in good agreement with a previous measurement of the bandwidth of the same material in a photoconductive switch.
Vertical architecture for enhancement mode power transistors based on GaN nanowires
NASA Astrophysics Data System (ADS)
Yu, F.; Rümmler, D.; Hartmann, J.; Caccamo, L.; Schimpke, T.; Strassburg, M.; Gad, A. E.; Bakin, A.; Wehmann, H.-H.; Witzigmann, B.; Wasisto, H. S.; Waag, A.
2016-05-01
The demonstration of vertical GaN wrap-around gated field-effect transistors using GaN nanowires is reported. The nanowires with smooth a-plane sidewalls have hexagonal geometry made by top-down etching. A 7-nanowire transistor exhibits enhancement mode operation with threshold voltage of 1.2 V, on/off current ratio as high as 108, and subthreshold slope as small as 68 mV/dec. Although there is space charge limited current behavior at small source-drain voltages (Vds), the drain current (Id) and transconductance (gm) reach up to 314 mA/mm and 125 mS/mm, respectively, when normalized with hexagonal nanowire circumference. The measured breakdown voltage is around 140 V. This vertical approach provides a way to next-generation GaN-based power devices.
Frequency-tunable continuous-wave terahertz sources based on GaAs plasmonic photomixers
Yang, Shang-Hua; Jarrahi, Mona
2015-09-28
We present frequency-tunable, continuous-wave terahertz sources based on GaAs plasmonic photomixers, which offer high terahertz radiation power levels at 50% radiation duty cycle. The use of plasmonic contact electrodes enhances photomixer quantum efficiency while maintaining its ultrafast operation by concentrating a large number of photocarriers in close proximity to the device contact electrodes. Additionally, the relatively high thermal conductivity and high resistivity of GaAs allow operation under high optical pump power levels and long duty cycles without reaching the thermal breakdown limit of the photomixer. We experimentally demonstrate continuous-wave terahertz radiation with a radiation frequency tuning range of more than 2 THz and a record-high radiation power of 17 μW at 1 THz through plasmonic photomixers fabricated on a low temperature grown GaAs substrate at 50% radiation duty cycle.
Metal-semiconductor-metal UV photodetector based on Ga doped ZnO/graphene interface
NASA Astrophysics Data System (ADS)
Kumar, Manoj; Noh, Youngwook; Polat, Kinyas; Kemal Okyay, Ali; Lee, Dongjin
2015-12-01
Fabrication and characterization of metal-semiconductor-metal (MSM) ultraviolet (UV) photodetector (PD) based on Ga doped ZnO (ZnO:Ga)/graphene is presented in this work. A low dark current of 8.68 nA was demonstrated at a bias of 1 V and a large photo to dark contrast ratio of more than four orders of magnitude was observed. MSM PD exhibited a room temperature responsivity of 48.37 A/W at wavelength of 350 nm and UV-to-visible rejection ratio of about three orders of magnitude. A large photo-to-dark contrast and UV-to-visible rejection ratio suggests the enhancement in the PD performance which is attributed to the existence of a surface plasmon effect at the interface of the ZnO:Ga and underlying graphene layer.
Hu, Xiao-Long; Wang, Hong; Zhang, Xi-Chun
2015-01-01
We fabricated GaN-based light-emitting diodes (LEDs) without pre-activation of p-type GaN. During the fabrication process, a 100-nm-thick indium tin oxide film was served as the p-type contact layer and annealed at 500°C in N2 ambient for 20 min to increase its transparency as well as to activate the p-type GaN. The electrical measurements showed that the LEDs were featured by a lower forward voltage and higher wall-plug efficiency in comparison with LEDs using pre-activation of p-type GaN. We discussed the mechanism of activation of p-type GaN at 500°C in N2 ambient. Furthermore, x-ray photoemission spectroscopy examinations were carried out to study the improved electrical performances of the LEDs without pre-activation of p-type GaN. PMID:25852381
A High-Performance Genetic Algorithm: Using Traveling Salesman Problem as a Case
Tsai, Chun-Wei; Tseng, Shih-Pang; Yang, Chu-Sing
2014-01-01
This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA. PMID:24892038
ANNIT - An Efficient Inversion Algorithm based on Prediction Principles
NASA Astrophysics Data System (ADS)
Růžek, B.; Kolář, P.
2009-04-01
Solution of inverse problems represents meaningful job in geophysics. The amount of data is continuously increasing, methods of modeling are being improved and the computer facilities are also advancing great technical progress. Therefore the development of new and efficient algorithms and computer codes for both forward and inverse modeling is still up to date. ANNIT is contributing to this stream since it is a tool for efficient solution of a set of non-linear equations. Typical geophysical problems are based on parametric approach. The system is characterized by a vector of parameters p, the response of the system is characterized by a vector of data d. The forward problem is usually represented by unique mapping F(p)=d. The inverse problem is much more complex and the inverse mapping p=G(d) is available in an analytical or closed form only exceptionally and generally it may not exist at all. Technically, both forward and inverse mapping F and G are sets of non-linear equations. ANNIT solves such situation as follows: (i) joint subspaces {pD, pM} of original data and model spaces D, M, resp. are searched for, within which the forward mapping F is sufficiently smooth that the inverse mapping G does exist, (ii) numerical approximation of G in subspaces {pD, pM} is found, (iii) candidate solution is predicted by using this numerical approximation. ANNIT is working in an iterative way in cycles. The subspaces {pD, pM} are searched for by generating suitable populations of individuals (models) covering data and model spaces. The approximation of the inverse mapping is made by using three methods: (a) linear regression, (b) Radial Basis Function Network technique, (c) linear prediction (also known as "Kriging"). The ANNIT algorithm has built in also an archive of already evaluated models. Archive models are re-used in a suitable way and thus the number of forward evaluations is minimized. ANNIT is now implemented both in MATLAB and SCILAB. Numerical tests show good
Algorithm for Stabilizing a POD-Based Dynamical System
NASA Technical Reports Server (NTRS)
Kalb, Virginia L.
2010-01-01
This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.
CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET
Bajwa, Khalid Bashir; Khan, Salabat; Chaudary, Nadeem Majeed; Akram, Adeel
2016-01-01
A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO. PMID:27149517
A SIFT feature based registration algorithm in automatic seal verification
NASA Astrophysics Data System (ADS)
He, Jin; Ding, Xuewen; Zhang, Hao; Liu, Tiegen
2012-11-01
A SIFT (Scale Invariant Feature Transform) feature based registration algorithm is presented to prepare for the seal verification, especially for the verification of high quality counterfeit sample seal. The similarities and the spatial relationships between the matched SIFT features are combined for the registration. SIFT features extracted from the binary model seal and sample seal images are matched according to their similarities. The matching rate is used to define the similar sample seal that is similar with its model seal. For the similar sample seal, the false matches are eliminated according to the position relationship. Then the homography between model seal and sample seal is constructed and named HS . The theoretical homography is namedH . The accuracy of registration is evaluated by the Frobenius norm of H-HS . In experiments, translation, filling and rotation transformations are applied to seals with different shapes, stroke number and structures. After registering the transformed seals and their model seals, the maximum value of the Frobenius norm of their H-HS is not more than 0.03. The results prove that this algorithm can accomplish accurate registration, which is invariant to translation, filling, and rotation transformation, and there is no limit to the seal shapes, stroke number and structures.
Fast Field Calibration of MIMU Based on the Powell Algorithm
Ma, Lin; Chen, Wanwan; Li, Bin; You, Zheng; Chen, Zhigang
2014-01-01
The calibration of micro inertial measurement units is important in ensuring the precision of navigation systems, which are equipped with microelectromechanical system sensors that suffer from various errors. However, traditional calibration methods cannot meet the demand for fast field calibration. This paper presents a fast field calibration method based on the Powell algorithm. As the key points of this calibration, the norm of the accelerometer measurement vector is equal to the gravity magnitude, and the norm of the gyro measurement vector is equal to the rotational velocity inputs. To resolve the error parameters by judging the convergence of the nonlinear equations, the Powell algorithm is applied by establishing a mathematical error model of the novel calibration. All parameters can then be obtained in this manner. A comparison of the proposed method with the traditional calibration method through navigation tests shows the classic performance of the proposed calibration method. The proposed calibration method also saves more time compared with the traditional calibration method. PMID:25177801
CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET.
Aadil, Farhan; Bajwa, Khalid Bashir; Khan, Salabat; Chaudary, Nadeem Majeed; Akram, Adeel
2016-01-01
A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO. PMID:27149517
Optical feedback in 905 nm power laser-thyristors based on AlGaAs/GaAs heterostructures
NASA Astrophysics Data System (ADS)
Podoskin, A. A.; Soboleva, O. S.; Zakharov, M. S.; Veselov, D. A.; Zolotarev, V. V.; Pikhtin, N. A.; Tarasov, I. S.; Bagaev, T. A.; Ladugin, M. A.; Marmalyuk, A. A.; Simakov, V. A.; Slipchenko, S. O.
2015-12-01
An experimental study of factors determining the optical feedback efficiency in the structure of a laser-thyristor emitting at a wavelength of 905 nm has been carried out. It is shown that the spontaneous emission spectrum undergoes a significant change in the working range of currents due to the presence of GaAs-spacers in the structure of the active region of the laser part and to the absence of saturation of the spontaneous emission flux beyond the lasing threshold. It is demonstrated that the influence exerted by the reverse voltage across the collector p-n junction of the transistor part comes down to the following two effects: deformation of the edge of the absorption spectrum and turn-on of the impact ionization. Experimental dependences of the photogeneration rate on both current and voltage were obtained for the p-base of the transistor part. These dependences are an important tool to be used in subsequent studies aimed to simulate and examine the injection and generation processes in power laser-thyristors.
A Competency-Based Guided-Learning Algorithm Applied on Adaptively Guiding E-Learning
ERIC Educational Resources Information Center
Hsu, Wei-Chih; Li, Cheng-Hsiu
2015-01-01
This paper presents a new algorithm called competency-based guided-learning algorithm (CBGLA), which can be applied on adaptively guiding e-learning. Computational process analysis and mathematical derivation of competency-based learning (CBL) were used to develop the CBGLA. The proposed algorithm could generate an effective adaptively guiding…
Graph-based optimization algorithm and software on kidney exchanges.
Chen, Yanhua; Li, Yijiang; Kalbfleisch, John D; Zhou, Yan; Leichtman, Alan; Song, Peter X-K
2012-07-01
Kidney transplantation is typically the most effective treatment for patients with end-stage renal disease. However, the supply of kidneys is far short of the fast-growing demand. Kidney paired donation (KPD) programs provide an innovative approach for increasing the number of available kidneys. In a KPD program, willing but incompatible donor-candidate pairs may exchange donor organs to achieve mutual benefit. Recently, research on exchanges initiated by altruistic donors (ADs) has attracted great attention because the resultant organ exchange mechanisms offer advantages that increase the effectiveness of KPD programs. Currently, most KPD programs focus on rule-based strategies of prioritizing kidney donation. In this paper, we consider and compare two graph-based organ allocation algorithms to optimize an outcome-based strategy defined by the overall expected utility of kidney exchanges in a KPD program with both incompatible pairs and ADs. We develop an interactive software-based decision support system to model, monitor, and visualize a conceptual KPD program, which aims to assist clinicians in the evaluation of different kidney allocation strategies. Using this system, we demonstrate empirically that an outcome-based strategy for kidney exchanges leads to improvement in both the quantity and quality of kidney transplantation through comprehensive simulation experiments. PMID:22542649
Buried graphene electrodes on GaN-based ultra-violet light-emitting diodes
NASA Astrophysics Data System (ADS)
Kim, Byung-Jae; Lee, Chongmin; Mastro, Michael A.; Hite, Jennifer K.; Eddy, Charles R.; Ren, Fan; Pearton, Stephen J.; Kim, Jihyun
2012-07-01
We report that the oxidation of graphene-based highly transparent conductive layers to AlGaN/GaN/AlGaN ultra-violet (UV) light-emitting diodes (LEDs) was suppressed by the use of SiNX passivation layers. Although graphene is considered to be an ideal candidate as the transparent conductive layer to UV-LEDs, oxidation of these layers at high operating temperatures has been an issue. The oxidation is initiated at the un-saturated carbon atoms at the edges of the graphene and reduces the UV light intensity and degrades the current-voltage (I-V) characteristics. The oxidation also can occur at defects, including vacancies. However, GaN-based UV-LEDs deposited with SiNX by plasma-enhanced chemical vapor deposition showed minimal degradation of light output intensity and I-V characteristics because the graphene-based UV transparent conductive layers were shielded from the oxygen molecules. This is a simple and effective approach for maintaining the advantages of graphene conducting layers as electrodes on UV-LEDs.
A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search.
Villagra, Andrea; Alba, Enrique; Leguizamón, Guillermo
2016-01-01
This work presents the results of a new methodology for hybridizing metaheuristics. By first locating the active components (parts) of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms. This gives a concrete way of constructing new techniques that contrasts the spread ad hoc way of hybridizing. In this paper, the enhanced algorithm is a Cellular Genetic Algorithm (cGA) which has been successfully used in the past to find solutions to such hard optimization problems. In order to extend and corroborate the use of active components as an emerging hybridization methodology, we propose here the use of active components taken from Scatter Search (SS) to improve cGA. The results obtained over a varied set of benchmarks are highly satisfactory in efficacy and efficiency when compared with a standard cGA. Moreover, the proposed hybrid approach (i.e., cGA+SS) has shown encouraging results with regard to earlier applications of our methodology. PMID:27403153
A Methodology for the Hybridization Based in Active Components: The Case of cGA and Scatter Search
Alba, Enrique; Leguizamón, Guillermo
2016-01-01
This work presents the results of a new methodology for hybridizing metaheuristics. By first locating the active components (parts) of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms. This gives a concrete way of constructing new techniques that contrasts the spread ad hoc way of hybridizing. In this paper, the enhanced algorithm is a Cellular Genetic Algorithm (cGA) which has been successfully used in the past to find solutions to such hard optimization problems. In order to extend and corroborate the use of active components as an emerging hybridization methodology, we propose here the use of active components taken from Scatter Search (SS) to improve cGA. The results obtained over a varied set of benchmarks are highly satisfactory in efficacy and efficiency when compared with a standard cGA. Moreover, the proposed hybrid approach (i.e., cGA+SS) has shown encouraging results with regard to earlier applications of our methodology. PMID:27403153
An improved SIFT algorithm based on KFDA in image registration
NASA Astrophysics Data System (ADS)
Chen, Peng; Yang, Lijuan; Huo, Jinfeng
2016-03-01
As a kind of stable feature matching algorithm, SIFT has been widely used in many fields. In order to further improve the robustness of the SIFT algorithm, an improved SIFT algorithm with Kernel Discriminant Analysis (KFDA-SIFT) is presented for image registration. The algorithm uses KFDA to SIFT descriptors for feature extraction matrix, and uses the new descriptors to conduct the feature matching, finally chooses RANSAC to deal with the matches for further purification. The experiments show that the presented algorithm is robust to image changes in scale, illumination, perspective, expression and tiny pose with higher matching accuracy.