Basu, D K
2014-01-01
Very Large Scale Integrated Circuits (VLSI) design has moved from costly curiosity to an everyday necessity, especially with the proliferated applications of embedded computing devices in communications, entertainment and household gadgets. As a result, more and more knowledge on various aspects of VLSI design technologies is becoming a necessity for the engineering/technology students of various disciplines. With this goal in mind the course material of this book has been designed to cover the various fundamental aspects of VLSI design, like Categorization and comparison between various technologies used for VLSI design Basic fabrication processes involved in VLSI design Design of MOS, CMOS and Bi CMOS circuits used in VLSI Structured design of VLSI Introduction to VHDL for VLSI design Automated design for placement and routing of VLSI systems VLSI testing and testability The various topics of the book have been discussed lucidly with analysis, when required, examples, figures and adequate analytical and the...
Einspruch, Norman G
1986-01-01
VLSI Electronics Microstructure Science, Volume 14: VLSI Design presents a comprehensive exposition and assessment of the developments and trends in VLSI (Very Large Scale Integration) electronics. This volume covers topics that range from microscopic aspects of materials behavior and device performance to the comprehension of VLSI in systems applications. Each article is prepared by a recognized authority. The subjects discussed in this book include VLSI processor design methodology; the RISC (Reduced Instruction Set Computer); the VLSI testing program; silicon compilers for VLSI; and special
Chandrasetty, Vikram Arkalgud
2011-01-01
This book provides insight into the practical design of VLSI circuits. It is aimed at novice VLSI designers and other enthusiasts who would like to understand VLSI design flows. Coverage includes key concepts in CMOS digital design, design of DSP and communication blocks on FPGAs, ASIC front end and physical design, and analog and mixed signal design. The approach is designed to focus on practical implementation of key elements of the VLSI design process, in order to make the topic accessible to novices. The design concepts are demonstrated using software from Mathworks, Xilinx, Mentor Graphic
Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis
Brouwer, Randall Jay
1991-01-01
The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.
Directory of Open Access Journals (Sweden)
Rachmad Vidya Wicaksana Putra
2016-06-01
Full Text Available Convolutional encoding and data decoding are fundamental processes in convolutional error correction. One of the most popular error correction methods in decoding is the Viterbi algorithm. It is extensively implemented in many digital communication applications. Its VLSI design challenges are about area, speed, power, complexity and configurability. In this research, we specifically propose a VLSI architecture for a configurable and low-complexity design of a hard-decision Viterbi decoding algorithm. The configurable and low-complexity design is achieved by designing a generic VLSI architecture, optimizing each processing element (PE at the logical operation level and designing a conditional adapter. The proposed design can be configured for any predefined number of trace-backs, only by changing the trace-back parameter value. Its computational process only needs N + 2 clock cycles latency, with N is the number of trace-backs. Its configurability function has been proven for N = 8, N = 16, N = 32 and N = 64. Furthermore, the proposed design was synthesized and evaluated in Xilinx and Altera FPGA target boards for area consumption and speed performance.
Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm
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I. Hameem Shanavas
2014-01-01
Full Text Available In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.
Parallel computation of nondeterministic algorithms in VLSI
Energy Technology Data Exchange (ETDEWEB)
Hortensius, P D
1987-01-01
This work examines parallel VLSI implementations of nondeterministic algorithms. It is demonstrated that conventional pseudorandom number generators are unsuitable for highly parallel applications. Efficient parallel pseudorandom sequence generation can be accomplished using certain classes of elementary one-dimensional cellular automata. The pseudorandom numbers appear in parallel on each clock cycle. Extensive study of the properties of these new pseudorandom number generators is made using standard empirical random number tests, cycle length tests, and implementation considerations. Furthermore, it is shown these particular cellular automata can form the basis of efficient VLSI architectures for computations involved in the Monte Carlo simulation of both the percolation and Ising models from statistical mechanics. Finally, a variation on a Built-In Self-Test technique based upon cellular automata is presented. These Cellular Automata-Logic-Block-Observation (CALBO) circuits improve upon conventional design for testability circuitry.
Synthesis algorithm of VLSI multipliers for ASIC
Chua, O. H.; Eldin, A. G.
1993-01-01
Multipliers are critical sub-blocks in ASIC design, especially for digital signal processing and communications applications. A flexible multiplier synthesis tool is developed which is capable of generating multiplier blocks for word size in the range of 4 to 256 bits. A comparison of existing multiplier algorithms is made in terms of speed, silicon area, and suitability for automated synthesis and verification of its VLSI implementation. The algorithm divides the range of supported word sizes into sub-ranges and provides each sub-range with a specific multiplier architecture for optimal speed and area. The algorithm of the synthesis tool and the multiplier architectures are presented. Circuit implementation and the automated synthesis methodology are discussed.
Johnsson, Lennart
1980-01-01
Integrated circuit technology is rapidly approaching a state where feature sizes of one micron or less are tractable. Chip sizes are increasing slowly. These two developments result in considerably increased complexity in chip design. The physical characteristics of integrated circuit technology are also changing. The cost of communication will be dominating making new architectures and algorithms both feasible and desirable. A large number of processors on a single chip will be possible....
Artificial immune system algorithm in VLSI circuit configuration
Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd
2017-08-01
In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.
Application of evolutionary algorithms for multi-objective optimization in VLSI and embedded systems
2015-01-01
This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO, and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing, and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation, and operators like crossover, mutation, etc. can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field ...
Power efficient and high performance VLSI architecture for AES algorithm
Directory of Open Access Journals (Sweden)
K. Kalaiselvi
2015-09-01
Full Text Available Advanced encryption standard (AES algorithm has been widely deployed in cryptographic applications. This work proposes a low power and high throughput implementation of AES algorithm using key expansion approach. We minimize the power consumption and critical path delay using the proposed high performance architecture. It supports both encryption and decryption using 256-bit keys with a throughput of 0.06 Gbps. The VHDL language is utilized for simulating the design and an FPGA chip has been used for the hardware implementations. Experimental results reveal that the proposed AES architectures offer superior performance than the existing VLSI architectures in terms of power, throughput and critical path delay.
VLSI Design of Trusted Virtual Sensors
Directory of Open Access Journals (Sweden)
Macarena C. Martínez-Rodríguez
2018-01-01
Full Text Available This work presents a Very Large Scale Integration (VLSI design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF based on a Static Random Access Memory (SRAM to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS technology show that the active silicon area of the trusted virtual sensor is 0.86 mm 2 and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 μ s. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time.
VLSI Design of Trusted Virtual Sensors.
Martínez-Rodríguez, Macarena C; Prada-Delgado, Miguel A; Brox, Piedad; Baturone, Iluminada
2018-01-25
This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR) model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated) input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF) based on a Static Random Access Memory (SRAM) to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS) technology show that the active silicon area of the trusted virtual sensor is 0.86 mm 2 and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 μ s. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time).
Multi-valued LSI/VLSI logic design
Santrakul, K.
A procedure for synthesizing any large complex logic system, such as LSI and VLSI integrated circuits is described. This scheme uses Multi-Valued Multi-plexers (MVMUX) as the basic building blocks and the tree as the structure of the circuit realization. Simple built-in test circuits included in the network (the main current), provide a thorough functional checking of the network at any time. In brief, four major contributions are made: (1) multi-valued Algorithmic State Machine (ASM) chart for describing an LSI/VLSI behavior; (2) a tree-structured multi-valued multiplexer network which can be obtained directly from an ASM chart; (3) a heuristic tree-structured synthesis method for realizing any combinational logic with minimal or nearly-minimal MVMUX; and (4) a hierarchical design of LSI/VLSI with built-in parallel testing capability.
Compact MOSFET models for VLSI design
Bhattacharyya, A B
2009-01-01
Practicing designers, students, and educators in the semiconductor field face an ever expanding portfolio of MOSFET models. In Compact MOSFET Models for VLSI Design , A.B. Bhattacharyya presents a unified perspective on the topic, allowing the practitioner to view and interpret device phenomena concurrently using different modeling strategies. Readers will learn to link device physics with model parameters, helping to close the gap between device understanding and its use for optimal circuit performance. Bhattacharyya also lays bare the core physical concepts that will drive the future of VLSI.
Harnessing VLSI System Design with EDA Tools
Kamat, Rajanish K; Gaikwad, Pawan K; Guhilot, Hansraj
2012-01-01
This book explores various dimensions of EDA technologies for achieving different goals in VLSI system design. Although the scope of EDA is very broad and comprises diversified hardware and software tools to accomplish different phases of VLSI system design, such as design, layout, simulation, testability, prototyping and implementation, this book focuses only on demystifying the code, a.k.a. firmware development and its implementation with FPGAs. Since there are a variety of languages for system design, this book covers various issues related to VHDL, Verilog and System C synergized with EDA tools, using a variety of case studies such as testability, verification and power consumption. * Covers aspects of VHDL, Verilog and Handel C in one text; * Enables designers to judge the appropriateness of each EDA tool for relevant applications; * Omits discussion of design platforms and focuses on design case studies; * Uses design case studies from diversified application domains such as network on chip, hospital on...
DPL/Daedalus design environment (for VLSI)
Energy Technology Data Exchange (ETDEWEB)
Batali, J; Mayle, N; Shrobe, H; Sussman, G; Weise, D
1981-01-01
The DPL/Daedalus design environment is an interactive VLSI design system implemented at the MIT Artificial Intelligence Laboratory. The system consists of several components: a layout language called DPL (for design procedure language); an interactive graphics facility (Daedalus); and several special purpose design procedures for constructing complex artifacts such as PLAs and microprocessor data paths. Coordinating all of these is a generalized property list data base which contains both the data representing circuits and the procedures for constructing them. The authors first review the nature of the data base and then turn to DPL and Daedalus, the two most common ways of entering information into the data base. The next two sections review the specialized procedures for constructing PLAs and data paths; the final section describes a tool for hierarchical node extraction. 5 references.
Directory of Open Access Journals (Sweden)
Guilherme Corrêa
2012-01-01
Full Text Available In H.264/AVC, the encoding process can occur according to one of the 13 intraframe coding modes or according to one of the 8 available interframes block sizes, besides the SKIP mode. In the Joint Model reference software, the choice of the best mode is performed through exhaustive executions of the entire encoding process, which significantly increases the encoder's computational complexity and sometimes even forbids its use in real-time applications. Considering this context, this work proposes a set of heuristic algorithms targeting hardware architectures that lead to earlier selection of one encoding mode. The amount of repetitions of the encoding process is reduced by 47 times, at the cost of a relatively small cost in compression performance. When compared to other works, the fast hierarchical mode decision results are expressively more satisfactory in terms of computational complexity reduction, quality, and bit rate. The low-complexity mode decision architecture proposed is thus a very good option for real-time coding of high-resolution videos. The solution is especially interesting for embedded and mobile applications with support to multimedia systems, since it yields good compression rates and image quality with a very high reduction in the encoder complexity.
Technology computer aided design simulation for VLSI MOSFET
Sarkar, Chandan Kumar
2013-01-01
Responding to recent developments and a growing VLSI circuit manufacturing market, Technology Computer Aided Design: Simulation for VLSI MOSFET examines advanced MOSFET processes and devices through TCAD numerical simulations. The book provides a balanced summary of TCAD and MOSFET basic concepts, equations, physics, and new technologies related to TCAD and MOSFET. A firm grasp of these concepts allows for the design of better models, thus streamlining the design process, saving time and money. This book places emphasis on the importance of modeling and simulations of VLSI MOS transistors and
VLSI PARTITIONING ALGORITHM WITH ADAPTIVE CONTROL PARAMETER
Directory of Open Access Journals (Sweden)
P. N. Filippenko
2013-03-01
Full Text Available The article deals with the problem of very large-scale integration circuit partitioning. A graph is selected as a mathematical model describing integrated circuit. Modification of ant colony optimization algorithm is presented, which is used to solve graph partitioning problem. Ant colony optimization algorithm is an optimization method based on the principles of self-organization and other useful features of the ants’ behavior. The proposed search system is based on ant colony optimization algorithm with the improved method of the initial distribution and dynamic adjustment of the control search parameters. The experimental results and performance comparison show that the proposed method of very large-scale integration circuit partitioning provides the better search performance over other well known algorithms.
NASA Space Engineering Research Center for VLSI systems design
1991-01-01
This annual review reports the center's activities and findings on very large scale integration (VLSI) systems design for 1990, including project status, financial support, publications, the NASA Space Engineering Research Center (SERC) Symposium on VLSI Design, research results, and outreach programs. Processor chips completed or under development are listed. Research results summarized include a design technique to harden complementary metal oxide semiconductors (CMOS) memory circuits against single event upset (SEU); improved circuit design procedures; and advances in computer aided design (CAD), communications, computer architectures, and reliability design. Also described is a high school teacher program that exposes teachers to the fundamentals of digital logic design.
Handbook of VLSI chip design and expert systems
Schwarz, A F
1993-01-01
Handbook of VLSI Chip Design and Expert Systems provides information pertinent to the fundamental aspects of expert systems, which provides a knowledge-based approach to problem solving. This book discusses the use of expert systems in every possible subtask of VLSI chip design as well as in the interrelations between the subtasks.Organized into nine chapters, this book begins with an overview of design automation, which can be identified as Computer-Aided Design of Circuits and Systems (CADCAS). This text then presents the progress in artificial intelligence, with emphasis on expert systems.
VLSI Design with Alliance Free CAD Tools: an Implementation Example
Directory of Open Access Journals (Sweden)
Chávez-Bracamontes Ramón
2015-07-01
Full Text Available This paper presents the methodology used for a digital integrated circuit design that implements the communication protocol known as Serial Peripheral Interface, using the Alliance CAD System. The aim of this paper is to show how the work of VLSI design can be done by graduate and undergraduate students with minimal resources and experience. The physical design was sent to be fabricated using the CMOS AMI C5 process that features 0.5 micrometer in transistor size, sponsored by the MOSIS Educational Program. Tests were made on a platform that transfers data from inertial sensor measurements to the designed SPI chip, which in turn sends the data back on a parallel bus to a common microcontroller. The results show the efficiency of the employed methodology in VLSI design, as well as the feasibility of ICs manufacturing from school projects that have insufficient or no source of funding
VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.
Feng, Lichen; Li, Zunchao; Wang, Yuanfa
2018-02-01
Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consists of a feature extraction (FE) module and an SVM module. The FE module performs the three-level Daubechies discrete wavelet transform to fit the physiological bands of the electroencephalogram (EEG) signal and extracts the time-frequency domain features reflecting the nonstationary signal properties. The SVM module integrates the modified sequential minimal optimization algorithm with the table-driven-based Gaussian kernel to enable efficient on-chip learning. The presented design is verified on an Altera Cyclone II field-programmable gate array and tested using the two publicly available EEG datasets. Experiment results show that the designed VLSI system improves the detection accuracy and training efficiency.
Design of a VLSI Decoder for Partially Structured LDPC Codes
Directory of Open Access Journals (Sweden)
Fabrizio Vacca
2008-01-01
of their parity matrix can be partitioned into two disjoint sets, namely, the structured and the random ones. For the proposed class of codes a constructive design method is provided. To assess the value of this method the constructed codes performance are presented. From these results, a novel decoding method called split decoding is introduced. Finally, to prove the effectiveness of the proposed approach a whole VLSI decoder is designed and characterized.
Using Software Technology to Specify Abstract Interfaces in VLSI Design.
1985-01-01
with the complexity lev- els inherent in VLSI design, in that they can capitalize on their foundations in discrete mathemat- ics and the theory of...basis, rather than globally. Such a partitioning of module semantics makes the specification easier to construct and verify intelectual !y; it also...access function definitions. A standard language improves executability characteristics by capitalizing on portable, optimized system software developed
Formal verification an essential toolkit for modern VLSI design
Seligman, Erik; Kumar, M V Achutha Kiran
2015-01-01
Formal Verification: An Essential Toolkit for Modern VLSI Design presents practical approaches for design and validation, with hands-on advice for working engineers integrating these techniques into their work. Building on a basic knowledge of System Verilog, this book demystifies FV and presents the practical applications that are bringing it into mainstream design and validation processes at Intel and other companies. The text prepares readers to effectively introduce FV in their organization and deploy FV techniques to increase design and validation productivity. Presents formal verific
Directory of Open Access Journals (Sweden)
B. SENTHILKUMAR
2015-05-01
Full Text Available A novel implementation of code based cryptography (Cryptocoding technique for multi-layer key distribution scheme is presented. VLSI chip is designed for storing information on generation of round keys. New algorithm is developed for reduced key size with optimal performance. Error Control Algorithm is employed for both generation of round keys and diffusion of non-linearity among them. Two new functions for bit inversion and its reversal are developed for cryptocoding. Probability of retrieving original key from any other round keys is reduced by diffusing nonlinear selective bit inversions on round keys. Randomized selective bit inversions are done on equal length of key bits by Round Constant Feedback Shift Register within the error correction limits of chosen code. Complexity of retrieving the original key from any other round keys is increased by optimal hardware usage. Proposed design is simulated and synthesized using VHDL coding for Spartan3E FPGA and results are shown. Comparative analysis is done between 128 bit Advanced Encryption Standard round keys and proposed round keys for showing security strength of proposed algorithm. This paper concludes that chip based multi-layer key distribution of proposed algorithm is an enhanced solution to the existing threats on cryptography algorithms.
Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance
National Research Council Canada - National Science Library
Horiuchi, Timothy K; Krishnaprasad, P. S
2007-01-01
.... This includes multiple efforts related to a VLSI-based echolocation system being developed in one of our laboratories from algorithm development, bat flight data analysis, to VLSI circuit design...
Design of two easily-testable VLSI array multipliers
Energy Technology Data Exchange (ETDEWEB)
Ferguson, J.; Shen, J.P.
1983-01-01
Array multipliers are well-suited to VLSI implementation because of the regularity in their iterative structure. However, most VLSI circuits are very difficult to test. This paper shows that, with appropriate cell design, array multipliers can be designed to be very easily testable. An array multiplier is called c-testable if all its adder cells can be exhaustively tested while requiring only a constant number of test patterns. The testability of two well-known array multiplier structures are studied. The conventional design of the carry-save array multipler is shown to be not c-testable. However, a modified design, using a modified adder cell, is generated and shown to be c-testable and requires only 16 test patterns. Similar results are obtained for the baugh-wooley two's complement array multiplier. A modified design of the baugh-wooley array multiplier is shown to be c-testable and requires 55 test patterns. The implementation of a practical c-testable 16*16 array multiplier is also presented. 10 references.
VLSI architecture and design for the Fermat Number Transform implementation
Energy Technology Data Exchange (ETDEWEB)
Pajayakrit, A.
1987-01-01
A new technique of sectioning a pipelined transformer, using the Fermat Number Transform (FNT), is introduced. Also, a novel VLSI design which overcomes the problems of implementing FNTs, for use in fast convolution/correlation, is described. The design comprises one complete section of a pipelined transformer and may be programmed to function at any point in a forward or inverse pipeline, so allowing the construction of a pipelined convolver or correlator using identical chips, thus the favorable properties of the transform can be exploited. This overcomes the difficulty of fitting a complete pipeline onto one chip without resorting to the use of several different designs. The implementation of high-speed convolver/correlator using the VLSI chips has been successfully developed and tested. For impulse response lengths of up to 16 points the sampling rates of 0.5 MHz can be achieved. Finally, the filter speed performance using the FNT chips is compared to other designs and conclusions drawn on the merits of the FNT for this application. Also, the advantages and limitations of the FNT are analyzed, with respect to the more conventional FFT, and the results are provided.
Global floor planning approach for VLSI design
International Nuclear Information System (INIS)
LaPotin, D.P.
1986-01-01
Within a hierarchical design environment, initial decisions regarding the partitioning and choice of module attributes greatly impact the quality of the resulting IC in terms of area and electrical performance. This dissertation presents a global floor-planning approach which allows designers to quickly explore layout issues during the initial stages of the IC design process. In contrast to previous efforts, which address the floor-planning problem from a strict module placement point of view, this approach considers floor-planning from an area planning point of view. The approach is based upon a combined min-cut and slicing paradigm, which ensures routability. To provide flexibility, modules may be specified as having a number of possible dimensions and orientations, and I/O pads as well as layout constraints are considered. A slicing-tree representation is employed, upon which a sequence of traversal operations are applied in order to obtain an area efficient layout. An in-place partitioning technique, which provides an improvement over previous min-cut and slicing-based efforts, is discussed. Global routing and module I/O pin assignment are provided for floor-plan evaluation purposes. A computer program, called Mason, has been developed which efficiently implements the approach and provides an interactive environment for designers to perform floor-planning. Performance of this program is illustrated via several industrial examples
vPELS: An E-Learning Social Environment for VLSI Design with Content Security Using DRM
Dewan, Jahangir; Chowdhury, Morshed; Batten, Lynn
2014-01-01
This article provides a proposal for personal e-learning system (vPELS [where "v" stands for VLSI: very large scale integrated circuit])) architecture in the context of social network environment for VLSI Design. The main objective of vPELS is to develop individual skills on a specific subject--say, VLSI--and share resources with peers.…
VLSI electronics microstructure science
1981-01-01
VLSI Electronics: Microstructure Science, Volume 3 evaluates trends for the future of very large scale integration (VLSI) electronics and the scientific base that supports its development.This book discusses the impact of VLSI on computer architectures; VLSI design and design aid requirements; and design, fabrication, and performance of CCD imagers. The approaches, potential, and progress of ultra-high-speed GaAs VLSI; computer modeling of MOSFETs; and numerical physics of micron-length and submicron-length semiconductor devices are also elaborated. This text likewise covers the optical linewi
Design of a Low-Power VLSI Macrocell for Nonlinear Adaptive Video Noise Reduction
Directory of Open Access Journals (Sweden)
Sergio Saponara
2004-09-01
Full Text Available A VLSI macrocell for edge-preserving video noise reduction is proposed in the paper. It is based on a nonlinear rational filter enhanced by a noise estimator for blind and dynamic adaptation of the filtering parameters to the input signal statistics. The VLSI filter features a modular architecture allowing the extension of both mask size and filtering directions. Both spatial and spatiotemporal algorithms are supported. Simulation results with monochrome test videos prove its efficiency for many noise distributions with PSNR improvements up to 3.8 dB with respect to a nonadaptive solution. The VLSI macrocell has been realized in a 0.18 ÃŽÂ¼m CMOS technology using a standard-cells library; it allows for real-time processing of main video formats, up to 30 fps (frames per second 4CIF, with a power consumption in the order of few mW.
Digital VLSI design with Verilog a textbook from Silicon Valley Technical Institute
Williams, John
2008-01-01
This unique textbook is structured as a step-by-step course of study along the lines of a VLSI IC design project. In a nominal schedule of 12 weeks, two days and about 10 hours per week, the entire verilog language is presented, from the basics to everything necessary for synthesis of an entire 70,000 transistor, full-duplex serializer - deserializer, including synthesizable PLLs. Digital VLSI Design With Verilog is all an engineer needs for in-depth understanding of the verilog language: Syntax, synthesis semantics, simulation, and test. Complete solutions for the 27 labs are provided on the
VLSI top-down design based on the separation of hierarchies
Spaanenburg, L.; Broekema, A.; Leenstra, J.; Huys, C.
1986-01-01
Despite the presence of structure, interactions between the three views on VLSI design still lead to lengthy iterations. By separating the hierarchies for the respective views, the interactions are reduced. This separated hierarchy allows top-down design with functional abstractions as exemplified
VLSI design of an RSA encryption/decryption chip using systolic array based architecture
Sun, Chi-Chia; Lin, Bor-Shing; Jan, Gene Eu; Lin, Jheng-Yi
2016-09-01
This article presents the VLSI design of a configurable RSA public key cryptosystem supporting the 512-bit, 1024-bit and 2048-bit based on Montgomery algorithm achieving comparable clock cycles of current relevant works but with smaller die size. We use binary method for the modular exponentiation and adopt Montgomery algorithm for the modular multiplication to simplify computational complexity, which, together with the systolic array concept for electric circuit designs effectively, lower the die size. The main architecture of the chip consists of four functional blocks, namely input/output modules, registers module, arithmetic module and control module. We applied the concept of systolic array to design the RSA encryption/decryption chip by using VHDL hardware language and verified using the TSMC/CIC 0.35 m 1P4 M technology. The die area of the 2048-bit RSA chip without the DFT is 3.9 × 3.9 mm2 (4.58 × 4.58 mm2 with DFT). Its average baud rate can reach 10.84 kbps under a 100 MHz clock.
An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm
Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En
2015-01-01
A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction. PMID:26287193
Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En
2015-08-13
A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.
VLSI implementations for image communications
Pirsch, P
1993-01-01
The past few years have seen a rapid growth in image processing and image communication technologies. New video services and multimedia applications are continuously being designed. Essential for all these applications are image and video compression techniques. The purpose of this book is to report on recent advances in VLSI architectures and their implementation for video signal processing applications with emphasis on video coding for bit rate reduction. Efficient VLSI implementation for video signal processing spans a broad range of disciplines involving algorithms, architectures, circuits
Carbon nanotube based VLSI interconnects analysis and design
Kaushik, Brajesh Kumar
2015-01-01
The brief primarily focuses on the performance analysis of CNT based interconnects in current research scenario. Different CNT structures are modeled on the basis of transmission line theory. Performance comparison for different CNT structures illustrates that CNTs are more promising than Cu or other materials used in global VLSI interconnects. The brief is organized into five chapters which mainly discuss: (1) an overview of current research scenario and basics of interconnects; (2) unique crystal structures and the basics of physical properties of CNTs, and the production, purification and applications of CNTs; (3) a brief technical review, the geometry and equivalent RLC parameters for different single and bundled CNT structures; (4) a comparative analysis of crosstalk and delay for different single and bundled CNT structures; and (5) various unique mixed CNT bundle structures and their equivalent electrical models.
National Research Council Canada - National Science Library
Altmeyer, Ronald
2002-01-01
This thesis documents the research, circuit design, and simulation testing of a VLSI ASIC which extracts phase angle information from a complex sampled signal using the arctangent relationship: (phi=tan/-1 (Q/1...
An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm
Directory of Open Access Journals (Sweden)
Ying-Lun Chen
2015-08-01
Full Text Available A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO, and the feature extraction is carried out by the generalized Hebbian algorithm (GHA. To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.
VLSI Architectures for the Multiplication of Integers Modulo a Fermat Number
Chang, J. J.; Truong, T. K.; Reed, I. S.; Hsu, I. S.
1984-01-01
Multiplication is central in the implementation of Fermat number transforms and other residue number algorithms. There is need for a good multiplication algorithm that can be realized easily on a very large scale integration (VLSI) chip. The Leibowitz multiplier is modified to realize multiplication in the ring of integers modulo a Fermat number. This new algorithm requires only a sequence of cyclic shifts and additions. The designs developed for this new multiplier are regular, simple, expandable, and, therefore, suitable for VLSI implementation.
Multi-operation cryptographic engine: VLSI design and implementation
International Nuclear Information System (INIS)
Selimis, George; Koufopavlou, Odysseas
2005-01-01
The environment of smart card lacks of system resources but the commercial and economic transactions via smart cards demand the use of certificated and secure cryptographic methods. In this paper a cryptographic approach in hardware for smart cards is proposed. The proposed system supports two basic operations of cryptography, authentication and encryption. The basic component of system is the one round of DES algorithm which supports the DES, Triple DES and the ANSI X9.17 standards. The proposed system is efficient in terms of area resources and techniques for low power consumption have applied. Due to the fact that the system is for smart card applications the overall throughput outperforms the typical smart card throughput standards
Principles of VLSI RTL design a practical guide
Churiwala, Sanjay; Gianfagna, Mike
2011-01-01
This book examines the impact of register transfer level (RTL) design choices that may result in issues of testability, data synchronization across clock domains, synthesizability, power consumption and routability, that appear later in the product lifecycle.
A novel configurable VLSI architecture design of window-based image processing method
Zhao, Hui; Sang, Hongshi; Shen, Xubang
2018-03-01
Most window-based image processing architecture can only achieve a certain kind of specific algorithms, such as 2D convolution, and therefore lack the flexibility and breadth of application. In addition, improper handling of the image boundary can cause loss of accuracy, or consume more logic resources. For the above problems, this paper proposes a new VLSI architecture of window-based image processing operations, which is configurable and based on consideration of the image boundary. An efficient technique is explored to manage the image borders by overlapping and flushing phases at the end of row and the end of frame, which does not produce new delay and reduce the overhead in real-time applications. Maximize the reuse of the on-chip memory data, in order to reduce the hardware complexity and external bandwidth requirements. To perform different scalar function and reduction function operations in pipeline, this can support a variety of applications of window-based image processing. Compared with the performance of other reported structures, the performance of the new structure has some similarities to some of the structures, but also superior to some other structures. Especially when compared with a systolic array processor CWP, this structure at the same frequency of approximately 12.9% of the speed increases. The proposed parallel VLSI architecture was implemented with SIMC 0.18-μm CMOS technology, and the maximum clock frequency, power consumption, and area are 125Mhz, 57mW, 104.8K Gates, respectively, furthermore the processing time is independent of the different window-based algorithms mapped to the structure
Ramachandran, S
2007-01-01
Digital VLSI Systems Design is written for an advanced level course using Verilog and is meant for undergraduates, graduates and research scholars of Electrical, Electronics, Embedded Systems, Computer Engineering and interdisciplinary departments such as Bio Medical, Mechanical, Information Technology, Physics, etc. It serves as a reference design manual for practicing engineers and researchers as well. Diligent freelance readers and consultants may also start using this book with ease. The book presents new material and theory as well as synthesis of recent work with complete Project Designs
Digital VLSI design with Verilog a textbook from Silicon Valley Polytechnic Institute
Williams, John Michael
2014-01-01
This book is structured as a step-by-step course of study along the lines of a VLSI integrated circuit design project. The entire Verilog language is presented, from the basics to everything necessary for synthesis of an entire 70,000 transistor, full-duplex serializer-deserializer, including synthesizable PLLs. The author includes everything an engineer needs for in-depth understanding of the Verilog language: Syntax, synthesis semantics, simulation, and test. Complete solutions for the 27 labs are provided in the downloadable files that accompany the book. For readers with access to appropriate electronic design tools, all solutions can be developed, simulated, and synthesized as described in the book. A partial list of design topics includes design partitioning, hierarchy decomposition, safe coding styles, back annotation, wrapper modules, concurrency, race conditions, assertion-based verification, clock synchronization, and design for test. A concluding presentation of special topics inclu...
VLSI Design of a Variable-Length FFT/IFFT Processor for OFDM-Based Communication Systems
Directory of Open Access Journals (Sweden)
Jen-Chih Kuo
2003-12-01
Full Text Available The technique of {orthogonal frequency division multiplexing (OFDM} is famous for its robustness against frequency-selective fading channel. This technique has been widely used in many wired and wireless communication systems. In general, the {fast Fourier transform (FFT} and {inverse FFT (IFFT} operations are used as the modulation/demodulation kernel in the OFDM systems, and the sizes of FFT/IFFT operations are varied in different applications of OFDM systems. In this paper, we design and implement a variable-length prototype FFT/IFFT processor to cover different specifications of OFDM applications. The cached-memory FFT architecture is our suggested VLSI system architecture to design the prototype FFT/IFFT processor for the consideration of low-power consumption. We also implement the twiddle factor butterfly {processing element (PE} based on the {{coordinate} rotation digital computer (CORDIC} algorithm, which avoids the use of conventional multiplication-and-accumulation unit, but evaluates the trigonometric functions using only add-and-shift operations. Finally, we implement a variable-length prototype FFT/IFFT processor with TSMC 0.35Ã¢Â€Â‰ÃŽÂ¼m 1P4M CMOS technology. The simulations results show that the chip can perform (64-2048-point FFT/IFFT operations up to 80Ã¢Â€Â‰MHz operating frequency which can meet the speed requirement of most OFDM standards such as WLAN, ADSL, VDSL (256Ã¢ÂˆÂ¼2K, DAB, and 2K-mode DVB.
8. Algorithm Design Techniques
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 8. Algorithms - Algorithm Design Techniques. R K Shyamasundar. Series Article Volume 2 ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...
Driving a car with custom-designed fuzzy inferencing VLSI chips and boards
Pin, Francois G.; Watanabe, Yutaka
1993-01-01
Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human
VLSI Architectures for Computing DFT's
Truong, T. K.; Chang, J. J.; Hsu, I. S.; Reed, I. S.; Pei, D. Y.
1986-01-01
Simplifications result from use of residue Fermat number systems. System of finite arithmetic over residue Fermat number systems enables calculation of discrete Fourier transform (DFT) of series of complex numbers with reduced number of multiplications. Computer architectures based on approach suitable for design of very-large-scale integrated (VLSI) circuits for computing DFT's. General approach not limited to DFT's; Applicable to decoding of error-correcting codes and other transform calculations. System readily implemented in VLSI.
Hardware Genetic Algorithm Optimization by Critical Path Analysis using a Custom VLSI Architecture
Directory of Open Access Journals (Sweden)
Farouk Smith
2015-07-01
Full Text Available This paper propose a Virtual-Field Programmable Gate Array (V-FPGA architecture that allows direct access to its configuration bits to facilitate hardware evolution, thereby allowing any combinational or sequential digital circuit to be realized. By using the V-FPGA, this paper investigates two possible ways of making evolutionary hardware systems more scalable: by optimizing the system’s genetic algorithm (GA; and by decomposing the solution circuit into smaller, evolvable sub-circuits. GA optimization is done by: omitting a canonical GA’s crossover operator (i.e. by using a 1+λ algorithm; applying evolution constraints; and optimizing the fitness function. A noteworthy contribution this research has made is the in-depth analysis of the phenotypes’ CPs. Through analyzing the CPs, it has been shown that a great amount of insight can be gained into a phenotype’s fitness. We found that as the number of columns in the Cartesian Genetic Programming array increases, so the likelihood of an external output being placed in the column decreases. Furthermore, the number of used LEs per column also substantially decreases per added column. Finally, we demonstrated the evolution of a state-decomposed control circuit. It was shown that the evolution of each state’s sub-circuit was possible, and suggest that modular evolution can be a successful tool when dealing with scalability.
VLSI electronics microstructure science
1982-01-01
VLSI Electronics: Microstructure Science, Volume 4 reviews trends for the future of very large scale integration (VLSI) electronics and the scientific base that supports its development.This book discusses the silicon-on-insulator for VLSI and VHSIC, X-ray lithography, and transient response of electron transport in GaAs using the Monte Carlo method. The technology and manufacturing of high-density magnetic-bubble memories, metallic superlattices, challenge of education for VLSI, and impact of VLSI on medical signal processing are also elaborated. This text likewise covers the impact of VLSI t
Hu, Kai; Ho, Tsung-Yi
2017-01-01
This book provides a comprehensive overview of flow-based, microfluidic VLSI. The authors describe and solve in a comprehensive and holistic manner practical challenges such as control synthesis, wash optimization, design for testability, and diagnosis of modern flow-based microfluidic biochips. They introduce practical solutions, based on rigorous optimization and formal models. The technical contributions presented in this book will not only shorten the product development cycle, but also accelerate the adoption and further development of modern flow-based microfluidic biochips, by facilitating the full exploitation of design complexities that are possible with current fabrication techniques. Offers the first practical problem formulation for automated control-layer design in flow-based microfluidic biochips and provides a systematic approach for solving this problem; Introduces a wash-optimization method for cross-contamination removal; Presents a design-for-testability (DfT) technique that can achieve 100...
Directory of Open Access Journals (Sweden)
Urard Pascal
2006-01-01
Full Text Available We propose an efficient IP-block-based design environment for high-throughput VLSI systems. The flow generates SystemC register-transfer-level (RTL architecture, starting from a Matlab functional model described as a netlist of functional IP. The refinement model inserts automatically control structures to manage delays induced by the use of RTL IPs. It also inserts a control structure to coordinate the execution of parallel clocked IP. The delays may be managed by registers or by counters included in the control structure. The flow has been used successfully in three real-world DSP systems. The experimentations show that the approach can produce efficient RTL architecture and allows to save huge amount of time.
Chen, Wai-Kai
2007-01-01
Written by a stellar international panel of expert contributors, this handbook remains the most up-to-date, reliable, and comprehensive source for real answers to practical problems. In addition to updated information in most chapters, this edition features several heavily revised and completely rewritten chapters, new chapters on such topics as CMOS fabrication and high-speed circuit design, heavily revised sections on testing of digital systems and design languages, and two entirely new sections on low-power electronics and VLSI signal processing. An updated compendium of references and othe
McKenzie, Neil
1989-12-01
We present a design for a low-cost, functional VLSI chip tester. It is based on the Apple MacIntosh II personal computer. It tests chips that have up to 128 pins. All pin drivers of the tester are bidirectional; each pin is programmed independently as an input or an output. The tester can test both static and dynamic chips. Rudimentary speed testing is provided. Chips are tested by executing C programs written by the user. A software library is provided for program development. Tests run under both the Mac Operating System and A/UX. The design is implemented using Xilinx Logic Cell Arrays. Price/performance tradeoffs are discussed.
On the impact of communication complexity in the design of parallel numerical algorithms
Gannon, D.; Vanrosendale, J.
1984-01-01
This paper describes two models of the cost of data movement in parallel numerical algorithms. One model is a generalization of an approach due to Hockney, and is suitable for shared memory multiprocessors where each processor has vector capabilities. The other model is applicable to highly parallel nonshared memory MIMD systems. In the second model, algorithm performance is characterized in terms of the communication network design. Techniques used in VLSI complexity theory are also brought in, and algorithm independent upper bounds on system performance are derived for several problems that are important to scientific computation.
A VLSI image processor via pseudo-mersenne transforms
International Nuclear Information System (INIS)
Sei, W.J.; Jagadeesh, J.M.
1986-01-01
The computational burden on image processing in medical fields where a large amount of information must be processed quickly and accurately has led to consideration of special-purpose image processor chip design for some time. The very large scale integration (VLSI) resolution has made it cost-effective and feasible to consider the design of special purpose chips for medical imaging fields. This paper describes a VLSI CMOS chip suitable for parallel implementation of image processing algorithms and cyclic convolutions by using Pseudo-Mersenne Number Transform (PMNT). The main advantages of the PMNT over the Fast Fourier Transform (FFT) are: (1) no multiplications are required; (2) integer arithmetic is used. The design and development of this processor, which operates on 32-point convolution or 5 x 5 window image, are described
Einspruch, Norman G
1989-01-01
VLSI Electronics Microstructure Science, Volume 17: VLSI in Medicine deals with the more important applications of VLSI in medical devices and instruments.This volume is comprised of 11 chapters. It begins with an article about medical electronics. The following three chapters cover diagnostic imaging, focusing on such medical devices as magnetic resonance imaging, neurometric analyzer, and ultrasound. Chapters 5, 6, and 7 present the impact of VLSI in cardiology. The electrocardiograph, implantable cardiac pacemaker, and the use of VLSI in Holter monitoring are detailed in these chapters. The
The VLSI design of the sub-band filterbank in MP3 decoding
Liu, Jia-Xin; Luo, Li
2018-03-01
The sub-band filterbank is one of the most important modules which has the largest amount of calculation in MP3 decoding. In order to save CPU resources and integrate the sub-band filterbank part into MP3 IP core, the hardware circuit of the sub-band filterbank module is designed in this paper. A fast algorithm suit for hardware implementation is proposed and achieved on FPGA development board. The results show that the sub-band filterbank function is correct in the case of using very few registers and the amount of calculation and ROM resources are reduced greatly.
PLA realizations for VLSI state machines
Gopalakrishnan, S.; Whitaker, S.; Maki, G.; Liu, K.
1990-01-01
A major problem associated with state assignment procedures for VLSI controllers is obtaining an assignment that produces minimal or near minimal logic. The key item in Programmable Logic Array (PLA) area minimization is the number of unique product terms required by the design equations. This paper presents a state assignment algorithm for minimizing the number of product terms required to implement a finite state machine using a PLA. Partition algebra with predecessor state information is used to derive a near optimal state assignment. A maximum bound on the number of product terms required can be obtained by inspecting the predecessor state information. The state assignment algorithm presented is much simpler than existing procedures and leads to the same number of product terms or less. An area-efficient PLA structure implemented in a 1.0 micron CMOS process is presented along with a summary of the performance for a controller implemented using this design procedure.
Advanced symbolic analysis for VLSI systems methods and applications
Shi, Guoyong; Tlelo Cuautle, Esteban
2014-01-01
This book provides comprehensive coverage of the recent advances in symbolic analysis techniques for design automation of nanometer VLSI systems. The presentation is organized in parts of fundamentals, basic implementation methods and applications for VLSI design. Topics emphasized include statistical timing and crosstalk analysis, statistical and parallel analysis, performance bound analysis and behavioral modeling for analog integrated circuits . Among the recent advances, the Binary Decision Diagram (BDD) based approaches are studied in depth. The BDD-based hierarchical symbolic analysis approaches, have essentially broken the analog circuit size barrier. In particular, this book • Provides an overview of classical symbolic analysis methods and a comprehensive presentation on the modern BDD-based symbolic analysis techniques; • Describes detailed implementation strategies for BDD-based algorithms, including the principles of zero-suppression, variable ordering and canonical reduction; • Int...
Algorithms in combinatorial design theory
Colbourn, CJ
1985-01-01
The scope of the volume includes all algorithmic and computational aspects of research on combinatorial designs. Algorithmic aspects include generation, isomorphism and analysis techniques - both heuristic methods used in practice, and the computational complexity of these operations. The scope within design theory includes all aspects of block designs, Latin squares and their variants, pairwise balanced designs and projective planes and related geometries.
Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices
Zhu, Wenping; Liu, Leibo; Yin, Shouyi; Hu, Siqi; Tang, Eugene Y.; Wei, Shaojun
2014-05-01
With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human-computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.
VLSI signal processing technology
Swartzlander, Earl
1994-01-01
This book is the first in a set of forthcoming books focussed on state-of-the-art development in the VLSI Signal Processing area. It is a response to the tremendous research activities taking place in that field. These activities have been driven by two factors: the dramatic increase in demand for high speed signal processing, especially in consumer elec tronics, and the evolving microelectronic technologies. The available technology has always been one of the main factors in determining al gorithms, architectures, and design strategies to be followed. With every new technology, signal processing systems go through many changes in concepts, design methods, and implementation. The goal of this book is to introduce the reader to the main features of VLSI Signal Processing and the ongoing developments in this area. The focus of this book is on: • Current developments in Digital Signal Processing (DSP) pro cessors and architectures - several examples and case studies of existing DSP chips are discussed in...
Directory of Open Access Journals (Sweden)
Xie Xiang
2007-01-01
Full Text Available In order to decrease the communication bandwidth and save the transmitting power in the wireless endoscopy capsule, this paper presents a new near-lossless image compression algorithm based on the Bayer format image suitable for hardware design. This algorithm can provide low average compression rate ( bits/pixel with high image quality (larger than dB for endoscopic images. Especially, it has low complexity hardware overhead (only two line buffers and supports real-time compressing. In addition, the algorithm can provide lossless compression for the region of interest (ROI and high-quality compression for other regions. The ROI can be selected arbitrarily by varying ROI parameters. In addition, the VLSI architecture of this compression algorithm is also given out. Its hardware design has been implemented in m CMOS process.
Einspruch, Norman G
1984-01-01
VLSI Electronics: Microstructure Science, Volume 8: Plasma Processing for VLSI (Very Large Scale Integration) discusses the utilization of plasmas for general semiconductor processing. It also includes expositions on advanced deposition of materials for metallization, lithographic methods that use plasmas as exposure sources and for multiple resist patterning, and device structures made possible by anisotropic etching.This volume is divided into four sections. It begins with the history of plasma processing, a discussion of some of the early developments and trends for VLSI. The second section
VLSI implementation of MIMO detection for 802.11n using a novel adaptive tree search algorithm
International Nuclear Information System (INIS)
Yao Heng; Jian Haifang; Zhou Liguo; Shi Yin
2013-01-01
A 4×4 64-QAM multiple-input multiple-output (MIMO) detector is presented for the application of an IEEE 802.11n wireless local area network. The detectoris the implementation of a novel adaptive tree search(ATS) algorithm, and multiple ATS cores need to be instantiated to achieve the wideband requirement in the 802.11n standard. Both the ATS algorithm and the architectural considerations are explained. The latency of the detector is 0.75 μs, and the detector has a gate count of 848 k with a total of 19 parallel ATS cores. Each ATS core runs at 67 MHz. Measurement results show that compared with the floating-point ATS algorithm, the fixed-point implementation achieves a loss of 0.9 dB at a BER of 10 −3 . (semiconductor integrated circuits)
MOD/R : A knowledge assisted approach towards top-down only CMOS VLSI design
Spaanenburg, L.; Beunder, M.; Beune, F.A.; Gerez, Sabih H.; Holstein, B.; Luchtmeyer, R.C.C.; Smit, Jaap; van der Werf, A.; Willems, H.
1985-01-01
MOD/R models all views on the design space in relations. This is achieved by eliminating the package constraints, as are apparent in PCB oriented hardware description languages. Assisted by knowledge engineering it allows for a top-down, mostly hierarchical decomposition, virtually eliminating the
DEFF Research Database (Denmark)
Rasmussen, Ole Steen
constructed. It contains a semantical embedding of Ruby in Zermelo-Fraenkel set theory (ZF) implemented in the Isabelle theorem prover. A small subset of Ruby, called Pure Ruby, is embedded as a conservative extension of ZF and characterised by an inductive definition. Many useful structures used...
Algebraic Algorithm Design and Local Search
National Research Council Canada - National Science Library
Graham, Robert
1996-01-01
.... Algebraic techniques have been applied successfully to algorithm synthesis by the use of algorithm theories and design tactics, an approach pioneered in the Kestrel Interactive Development System (KIDS...
Towards an Analogue Neuromorphic VLSI Instrument for the Sensing of Complex Odours
Ab Aziz, Muhammad Fazli; Harun, Fauzan Khairi Che; Covington, James A.; Gardner, Julian W.
2011-09-01
Almost all electronic nose instruments reported today employ pattern recognition algorithms written in software and run on digital processors, e.g. micro-processors, microcontrollers or FPGAs. Conversely, in this paper we describe the analogue VLSI implementation of an electronic nose through the design of a neuromorphic olfactory chip. The modelling, design and fabrication of the chip have already been reported. Here a smart interface has been designed and characterised for thisneuromorphic chip. Thus we can demonstrate the functionality of the a VLSI neuromorphic chip, producing differing principal neuron firing patterns to real sensor response data. Further work is directed towards integrating 9 separate neuromorphic chips to create a large neuronal network to solve more complex olfactory problems.
VLSI structures for track finding
International Nuclear Information System (INIS)
Dell'Orso, M.
1989-01-01
We discuss the architecture of a device based on the concept of associative memory designed to solve the track finding problem, typical of high energy physics experiments, in a time span of a few microseconds even for very high multiplicity events. This ''machine'' is implemented as a large array of custom VLSI chips. All the chips are equal and each of them stores a number of ''patterns''. All the patterns in all the chips are compared in parallel to the data coming from the detector while the detector is being read out. (orig.)
Baviere, Ph.
Tests which have proven effective for evaluating VLSI circuits for space applications are described. It is recommended that circuits be examined after each manfacturing step to gain fast feedback on inadequacies in the production system. Data from failure modes which occur during operational lifetimes of circuits also permit redefinition of the manufacturing and quality control process to eliminate the defects identified. Other tests include determination of the operational envelope of the circuits, examination of the circuit response to controlled inputs, and the performance and functional speeds of ROM and RAM memories. Finally, it is desirable that all new circuits be designed with testing in mind.
Einspruch, Norman G
1987-01-01
VLSI Electronics Microstructure Science, Volume 16: Lithography for VLSI treats special topics from each branch of lithography, and also contains general discussion of some lithographic methods.This volume contains 8 chapters that discuss the various aspects of lithography. Chapters 1 and 2 are devoted to optical lithography. Chapter 3 covers electron lithography in general, and Chapter 4 discusses electron resist exposure modeling. Chapter 5 presents the fundamentals of ion-beam lithography. Mask/wafer alignment for x-ray proximity printing and for optical lithography is tackled in Chapter 6.
Truong, T. K.; Reed, I.; Yeh, C.; Shao, H.
1985-01-01
Fermat number transformation convolutes two digital data sequences. Very-large-scale integration (VLSI) applications, such as image and radar signal processing, X-ray reconstruction, and spectrum shaping, linear convolution of two digital data sequences of arbitrary lenghts accomplished using Fermat number transform (ENT).
Pursuit, Avoidance, and Cohesion in Flight: Multi-Purpose Control Laws and Neuromorphic VLSI
2010-10-01
spatial navigation in mammals. We have designed, fabricated, and are now testing a neuromorphic VLSI chip that implements a spike-based, attractor...Control Laws and Neuromorphic VLSI 5a. CONTRACT NUMBER 070402-7705 5b. GRANT NUMBER FA9550-07-1-0446 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...implementations (custom Neuromorphic VLSI and robotics) we will apply important practical constraints that can lead to deeper insight into how and why efficient
VLSI 'smart' I/O module development
Kirk, Dan
The developmental history, design, and operation of the MIL-STD-1553A/B discrete and serial module (DSM) for the U.S. Navy AN/AYK-14(V) avionics computer are described and illustrated with diagrams. The ongoing preplanned product improvement for the AN/AYK-14(V) includes five dual-redundant MIL-STD-1553 channels based on DSMs. The DSM is a front-end processor for transferring data to and from a common memory, sharing memory with a host processor to provide improved 'smart' input/output performance. Each DSM comprises three hardware sections: three VLSI-6000 semicustomized CMOS arrays, memory units to support the arrays, and buffers and resynchronization circuits. The DSM hardware module design, VLSI-6000 design tools, controlware and test software, and checkout procedures (using a hardware simulator) are characterized in detail.
Directory of Open Access Journals (Sweden)
Dazhi Jiang
2015-01-01
Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.
Designing algorithms using CAD technologies
Directory of Open Access Journals (Sweden)
Alin IORDACHE
2008-01-01
Full Text Available A representative example of eLearning-platform modular application, Ã¢Â€Â˜Logical diagramsÃ¢Â€Â™, is intended to be a useful learning and testing tool for the beginner programmer, but also for the more experienced one. The problem this application is trying to solve concerns young programmers who forget about the fundamentals of this domain, algorithmic. Logical diagrams are a graphic representation of an algorithm, which uses different geometrical figures (parallelograms, rectangles, rhombuses, circles with particular meaning that are called blocks and connected between them to reveal the flow of the algorithm. The role of this application is to help the user build the diagram for the algorithm and then automatically generate the C code and test it.
Algorithmic Mechanism Design of Evolutionary Computation.
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.
Aljada, Muhsen; Hwang, Seow; Alameh, Kamal
2008-01-21
In this paper we propose and experimentally demonstrate a reconfigurable 10Gbps frequency-encoded (1D) encoder/decoder structure for optical code division multiple access (OCDMA). The encoder is constructed using a single semiconductor optical amplifier (SOA) and 1D reflective Opto-VLSI processor. The SOA generates broadband amplified spontaneous emission that is dynamically sliced using digital phase holograms loaded onto the Opto-VLSI processor to generate 1D codewords. The selected wavelengths are injected back into the same SOA for amplifications. The decoder is constructed using single Opto-VLSI processor only. The encoded signal can successfully be retrieved at the decoder side only when the digital phase holograms of the encoder and the decoder are matched. The system performance is measured in terms of the auto-correlation and cross-correlation functions as well as the eye diagram.
Toward human-centered algorithm design
Directory of Open Access Journals (Sweden)
Eric PS Baumer
2017-07-01
Full Text Available As algorithms pervade numerous facets of daily life, they are incorporated into systems for increasingly diverse purposes. These systems’ results are often interpreted differently by the designers who created them than by the lay persons who interact with them. This paper offers a proposal for human-centered algorithm design, which incorporates human and social interpretations into the design process for algorithmically based systems. It articulates three specific strategies for doing so: theoretical, participatory, and speculative. Drawing on the author’s work designing and deploying multiple related systems, the paper provides a detailed example of using a theoretical approach. It also discusses findings pertinent to participatory and speculative design approaches. The paper addresses both strengths and challenges for each strategy in helping to center the process of designing algorithmically based systems around humans.
Linac design algorithm with symmetric segments
International Nuclear Information System (INIS)
Takeda, Harunori; Young, L.M.; Nath, S.; Billen, J.H.; Stovall, J.E.
1996-01-01
The cell lengths in linacs of traditional design are typically graded as a function of particle velocity. By making groups of cells and individual cells symmetric in both the CCDTL AND CCL, the cavity design as well as mechanical design and fabrication is simplified without compromising the performance. We have implemented a design algorithm in the PARMILA code in which cells and multi-cavity segments are made symmetric, significantly reducing the number of unique components. Using the symmetric algorithm, a sample linac design was generated and its performance compared with a similar one of conventional design
Fashion sketch design by interactive genetic algorithms
Mok, P. Y.; Wang, X. X.; Xu, J.; Kwok, Y. L.
2012-11-01
Computer aided design is vitally important for the modern industry, particularly for the creative industry. Fashion industry faced intensive challenges to shorten the product development process. In this paper, a methodology is proposed for sketch design based on interactive genetic algorithms. The sketch design system consists of a sketch design model, a database and a multi-stage sketch design engine. First, a sketch design model is developed based on the knowledge of fashion design to describe fashion product characteristics by using parameters. Second, a database is built based on the proposed sketch design model to define general style elements. Third, a multi-stage sketch design engine is used to construct the design. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch design process. The experimental results have demonstrated that the proposed method is effective in helping laypersons achieve satisfied fashion design sketches.
Hill, M.T.; Oei, Y.S.; Smit, M.K.
2007-01-01
We examine the use of micro and nano lasers to form digital photonic VLSI building blocks. Problems such as isolation and cascading of building blocks are addressed, and the potential of future nano lasers explored.
International Nuclear Information System (INIS)
Saucier, G.; Read, E.
1987-01-01
Fast-prototyping will be a reality in the very near future if both straightforward design methods and fast manufacturing facilities are available. This book focuses, first, on the motivation for fast-prototyping. Economic aspects and market considerations are analysed by European and Japanese companies. In the second chapter, new design methods are identified, mainly for full custom circuits. Of course, silicon compilers play a key role and the introduction of artificial intelligence techniques sheds a new light on the subject. At present, fast-prototyping on gate arrays or on standard cells is the most conventional technique and the third chapter updates the state-of-the art in this area. The fourth chapter concentrates specifically on the e-beam direct-writing for submicron IC technologies. In the fifth chapter, a strategic point in fast-prototyping, namely the test problem is addressed. The design for testability and the interface to the test equipment are mandatory to fulfill the test requirement for fast-prototyping. Finally, the last chapter deals with the subject of education when many people complain about the lack of use of fast-prototyping in higher education for VLSI
An efficient interpolation filter VLSI architecture for HEVC standard
Zhou, Wei; Zhou, Xin; Lian, Xiaocong; Liu, Zhenyu; Liu, Xiaoxiang
2015-12-01
The next-generation video coding standard of High-Efficiency Video Coding (HEVC) is especially efficient for coding high-resolution video such as 8K-ultra-high-definition (UHD) video. Fractional motion estimation in HEVC presents a significant challenge in clock latency and area cost as it consumes more than 40 % of the total encoding time and thus results in high computational complexity. With aims at supporting 8K-UHD video applications, an efficient interpolation filter VLSI architecture for HEVC is proposed in this paper. Firstly, a new interpolation filter algorithm based on the 8-pixel interpolation unit is proposed in this paper. It can save 19.7 % processing time on average with acceptable coding quality degradation. Based on the proposed algorithm, an efficient interpolation filter VLSI architecture, composed of a reused data path of interpolation, an efficient memory organization, and a reconfigurable pipeline interpolation filter engine, is presented to reduce the implement hardware area and achieve high throughput. The final VLSI implementation only requires 37.2k gates in a standard 90-nm CMOS technology at an operating frequency of 240 MHz. The proposed architecture can be reused for either half-pixel interpolation or quarter-pixel interpolation, which can reduce the area cost for about 131,040 bits RAM. The processing latency of our proposed VLSI architecture can support the real-time processing of 4:2:0 format 7680 × 4320@78fps video sequences.
Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance
2007-03-31
IFinal 03/01/04 - 02/28/07 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Neuromorphic VLSI-based Bat Echolocation for Micro-aerial 5b.GRANTNUMBER Vehicle...uncovered interesting new issues in our choice for representing the intensity of signals. We have just finished testing the first chip version of an echo...timing-based algorithm (’openspace’) for sonar-guided navigation amidst multiple obstacles. 15. SUBJECT TERMS Neuromorphic VLSI, bat echolocation
Genetic Algorithms in Wind Turbine Airfoil Design
Energy Technology Data Exchange (ETDEWEB)
Grasso, F. [ECN Wind Energy, Petten (Netherlands); Bizzarrini, N.; Coiro, D.P. [Department of Aerospace Engineering, University of Napoli ' Federico II' , Napoli (Italy)
2011-03-15
One key element in the aerodynamic design of wind turbines is the use of specially tailored airfoils to increase the ratio of energy capture to the loading and thereby to reduce cost of energy. This work is focused on the design of a wind turbine airfoil by using numerical optimization. Firstly, the optimization approach is presented; a genetic algorithm is used, coupled with RFOIL solver and a composite Bezier geometrical parameterization. A particularly sensitive point is the choice and implementation of constraints; in order to formalize in the most complete and effective way the design requirements, the effects of activating specific constraints are discussed. A numerical example regarding the design of a high efficiency airfoil for the outer part of a blade by using genetic algorithms is illustrated and the results are compared with existing wind turbine airfoils. Finally a new hybrid design strategy is illustrated and discussed, in which the genetic algorithms are used at the beginning of the design process to explore a wide domain. Then, the gradient based algorithms are used in order to improve the first stage optimum.
Algorithms, architectures and information systems security
Sur-Kolay, Susmita; Nandy, Subhas C; Bagchi, Aditya
2008-01-01
This volume contains articles written by leading researchers in the fields of algorithms, architectures, and information systems security. The first five chapters address several challenging geometric problems and related algorithms. These topics have major applications in pattern recognition, image analysis, digital geometry, surface reconstruction, computer vision and in robotics. The next five chapters focus on various optimization issues in VLSI design and test architectures, and in wireless networks. The last six chapters comprise scholarly articles on information systems security coverin
An area-efficient path memory structure for VLSI Implementation of high speed Viterbi decoders
DEFF Research Database (Denmark)
Paaske, Erik; Pedersen, Steen; Sparsø, Jens
1991-01-01
Path storage and selection methods for Viterbi decoders are investigated with special emphasis on VLSI implementations. Two well-known algorithms, the register exchange, algorithm, REA, and the trace back algorithm, TBA, are considered. The REA requires the smallest number of storage elements...
Instrument design and optimization using genetic algorithms
International Nuclear Information System (INIS)
Hoelzel, Robert; Bentley, Phillip M.; Fouquet, Peter
2006-01-01
This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of 'nonstandard' magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods
Instrument design and optimization using genetic algorithms
Hölzel, Robert; Bentley, Phillip M.; Fouquet, Peter
2006-10-01
This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of "nonstandard" magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods.
A multi coding technique to reduce transition activity in VLSI circuits
International Nuclear Information System (INIS)
Vithyalakshmi, N.; Rajaram, M.
2014-01-01
Advances in VLSI technology have enabled the implementation of complex digital circuits in a single chip, reducing system size and power consumption. In deep submicron low power CMOS VLSI design, the main cause of energy dissipation is charging and discharging of internal node capacitances due to transition activity. Transition activity is one of the major factors that also affect the dynamic power dissipation. This paper proposes power reduction analyzed through algorithm and logic circuit levels. In algorithm level the key aspect of reducing power dissipation is by minimizing transition activity and is achieved by introducing a data coding technique. So a novel multi coding technique is introduced to improve the efficiency of transition activity up to 52.3% on the bus lines, which will automatically reduce the dynamic power dissipation. In addition, 1 bit full adders are introduced in the Hamming distance estimator block, which reduces the device count. This coding method is implemented using Verilog HDL. The overall performance is analyzed by using Modelsim and Xilinx Tools. In total 38.2% power saving capability is achieved compared to other existing methods. (semiconductor technology)
Multi-net optimization of VLSI interconnect
Moiseev, Konstantin; Wimer, Shmuel
2015-01-01
This book covers layout design and layout migration methodologies for optimizing multi-net wire structures in advanced VLSI interconnects. Scaling-dependent models for interconnect power, interconnect delay and crosstalk noise are covered in depth, and several design optimization problems are addressed, such as minimization of interconnect power under delay constraints, or design for minimal delay in wire bundles within a given routing area. A handy reference or a guide for design methodologies and layout automation techniques, this book provides a foundation for physical design challenges of interconnect in advanced integrated circuits. • Describes the evolution of interconnect scaling and provides new techniques for layout migration and optimization, focusing on multi-net optimization; • Presents research results that provide a level of design optimization which does not exist in commercially-available design automation software tools; • Includes mathematical properties and conditions for optimal...
Application of genetic algorithm to control design
International Nuclear Information System (INIS)
Lee, Yoon Joon; Cho, Kyung Ho
1995-01-01
A classical PID controller is designed by applying the GA (Genetic Algorithm) which searches the optimal parameters through three major operators of reproduction, crossover and mutation under the given constraints. The GA could minimize the designer's interference and the whole design process could easily be automated. In contrast with other traditional PID design methods which allows for the system output responses only, the design with the GA can take account of the magnitude or the rate of change of control input together with the output responses, which reflects the more realistic situations. Compared with other PIDs designed by the traditional methods such as Ziegler and analytic, the PID by the GA shows the superior response characteristics to those of others with the least control input energy
Hybrid VLSI/QCA Architecture for Computing FFTs
Fijany, Amir; Toomarian, Nikzad; Modarres, Katayoon; Spotnitz, Matthew
2003-01-01
A data-processor architecture that would incorporate elements of both conventional very-large-scale integrated (VLSI) circuitry and quantum-dot cellular automata (QCA) has been proposed to enable the highly parallel and systolic computation of fast Fourier transforms (FFTs). The proposed circuit would complement the QCA-based circuits described in several prior NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; and Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35. The cited prior articles described the limitations of very-large-scale integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCAbased signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes.
Scalable Algorithms for Adaptive Statistical Designs
Directory of Open Access Journals (Sweden)
Robert Oehmke
2000-01-01
Full Text Available We present a scalable, high-performance solution to multidimensional recurrences that arise in adaptive statistical designs. Adaptive designs are an important class of learning algorithms for a stochastic environment, and we focus on the problem of optimally assigning patients to treatments in clinical trials. While adaptive designs have significant ethical and cost advantages, they are rarely utilized because of the complexity of optimizing and analyzing them. Computational challenges include massive memory requirements, few calculations per memory access, and multiply-nested loops with dynamic indices. We analyze the effects of various parallelization options, and while standard approaches do not work well, with effort an efficient, highly scalable program can be developed. This allows us to solve problems thousands of times more complex than those solved previously, which helps make adaptive designs practical. Further, our work applies to many other problems involving neighbor recurrences, such as generalized string matching.
EGNAS: an exhaustive DNA sequence design algorithm
Directory of Open Access Journals (Sweden)
Kick Alfred
2012-06-01
Full Text Available Abstract Background The molecular recognition based on the complementary base pairing of deoxyribonucleic acid (DNA is the fundamental principle in the fields of genetics, DNA nanotechnology and DNA computing. We present an exhaustive DNA sequence design algorithm that allows to generate sets containing a maximum number of sequences with defined properties. EGNAS (Exhaustive Generation of Nucleic Acid Sequences offers the possibility of controlling both interstrand and intrastrand properties. The guanine-cytosine content can be adjusted. Sequences can be forced to start and end with guanine or cytosine. This option reduces the risk of “fraying” of DNA strands. It is possible to limit cross hybridizations of a defined length, and to adjust the uniqueness of sequences. Self-complementarity and hairpin structures of certain length can be avoided. Sequences and subsequences can optionally be forbidden. Furthermore, sequences can be designed to have minimum interactions with predefined strands and neighboring sequences. Results The algorithm is realized in a C++ program. TAG sequences can be generated and combined with primers for single-base extension reactions, which were described for multiplexed genotyping of single nucleotide polymorphisms. Thereby, possible foldback through intrastrand interaction of TAG-primer pairs can be limited. The design of sequences for specific attachment of molecular constructs to DNA origami is presented. Conclusions We developed a new software tool called EGNAS for the design of unique nucleic acid sequences. The presented exhaustive algorithm allows to generate greater sets of sequences than with previous software and equal constraints. EGNAS is freely available for noncommercial use at http://www.chm.tu-dresden.de/pc6/EGNAS.
VLSI and system architecture-the new development of system 5G
Energy Technology Data Exchange (ETDEWEB)
Sakamura, K.; Sekino, A.; Kodaka, T.; Uehara, T.; Aiso, H.
1982-01-01
A research and development proposal is presented for VLSI CAD systems and for a hardware environment called system 5G on which the VLSI CAD systems run. The proposed CAD systems use a hierarchically organized design language to enable design of anything from basic architectures of VLSI to VLSI mask patterns in a uniform manner. The cad systems will eventually become intelligent cad systems that acquire design knowledge and perform automatic design of VLSI chips when the characteristic requirements of VLSI chip is given. System 5G will consist of superinference machines and the 5G communication network. The superinference machine will be built based on a functionally distributed architecture connecting inferommunication network. The superinference machine will be built based on a functionally distributed architecture connecting inference machines and relational data base machines via a high-speed local network. The transfer rate of the local network will be 100 mbps at the first stage of the project and will be improved to 1 gbps. Remote access to the superinference machine will be possible through the 5G communication network. Access to system 5G will use the 5G network architecture protocol. The users will access the system 5G using standardized 5G personal computers. 5G personal logic programming stations, very high intelligent terminals providing an instruction set that supports predicate logic and input/output facilities for audio and graphical information.
Automatic Circuit Design and Optimization Using Modified PSO Algorithm
Directory of Open Access Journals (Sweden)
Subhash Patel
2016-04-01
Full Text Available In this work, we have proposed modified PSO algorithm based optimizer for automatic circuit design. The performance of the modified PSO algorithm is compared with two other evolutionary algorithms namely ABC algorithm and standard PSO algorithm by designing two stage CMOS operational amplifier and bulk driven OTA in 130nm technology. The results show the robustness of the proposed algorithm. With modified PSO algorithm, the average design error for two stage op-amp is only 0.054% in contrast to 3.04% for standard PSO algorithm and 5.45% for ABC algorithm. For bulk driven OTA, average design error is 1.32% with MPSO compared to 4.70% with ABC algorithm and 5.63% with standard PSO algorithm.
Memory Efficient VLSI Implementation of Real-Time Motion Detection System Using FPGA Platform
Directory of Open Access Journals (Sweden)
Sanjay Singh
2017-06-01
Full Text Available Motion detection is the heart of a potentially complex automated video surveillance system, intended to be used as a standalone system. Therefore, in addition to being accurate and robust, a successful motion detection technique must also be economical in the use of computational resources on selected FPGA development platform. This is because many other complex algorithms of an automated video surveillance system also run on the same platform. Keeping this key requirement as main focus, a memory efficient VLSI architecture for real-time motion detection and its implementation on FPGA platform is presented in this paper. This is accomplished by proposing a new memory efficient motion detection scheme and designing its VLSI architecture. The complete real-time motion detection system using the proposed memory efficient architecture along with proper input/output interfaces is implemented on Xilinx ML510 (Virtex-5 FX130T FPGA development platform and is capable of operating at 154.55 MHz clock frequency. Memory requirement of the proposed architecture is reduced by 41% compared to the standard clustering based motion detection architecture. The new memory efficient system robustly and automatically detects motion in real-world scenarios (both for the static backgrounds and the pseudo-stationary backgrounds in real-time for standard PAL (720 × 576 size color video.
Algorithm design of liquid lens inspection system
Hsieh, Lu-Lin; Wang, Chun-Chieh
2008-08-01
In mobile lens domain, the glass lens is often to be applied in high-resolution requirement situation; but the glass zoom lens needs to be collocated with movable machinery and voice-coil motor, which usually arises some space limits in minimum design. In high level molding component technology development, the appearance of liquid lens has become the focus of mobile phone and digital camera companies. The liquid lens sets with solid optical lens and driving circuit has replaced the original components. As a result, the volume requirement is decreased to merely 50% of the original design. Besides, with the high focus adjusting speed, low energy requirement, high durability, and low-cost manufacturing process, the liquid lens shows advantages in the competitive market. In the past, authors only need to inspect the scrape defect made by external force for the glass lens. As to the liquid lens, authors need to inspect the state of four different structural layers due to the different design and structure. In this paper, authors apply machine vision and digital image processing technology to administer inspections in the particular layer according to the needs of users. According to our experiment results, the algorithm proposed can automatically delete non-focus background, extract the region of interest, find out and analyze the defects efficiently in the particular layer. In the future, authors will combine the algorithm of the system with automatic-focus technology to implement the inside inspection based on the product inspective demands.
Trace-based post-silicon validation for VLSI circuits
Liu, Xiao
2014-01-01
This book first provides a comprehensive coverage of state-of-the-art validation solutions based on real-time signal tracing to guarantee the correctness of VLSI circuits. The authors discuss several key challenges in post-silicon validation and provide automated solutions that are systematic and cost-effective. A series of automatic tracing solutions and innovative design for debug (DfD) techniques are described, including techniques for trace signal selection for enhancing visibility of functional errors, a multiplexed signal tracing strategy for improving functional error detection, a tracing solution for debugging electrical errors, an interconnection fabric for increasing data bandwidth and supporting multi-core debug, an interconnection fabric design and optimization technique to increase transfer flexibility and a DfD design and associated tracing solution for improving debug efficiency and expanding tracing window. The solutions presented in this book improve the validation quality of VLSI circuit...
1983-01-01
for otherwise, since sc = xs2 . we would ELIE system. This algorithm also applies to SL) systems have been able to compute zec without looking at block...Prof. Peter R. Cappello of the CompuLer Science Department, University of California, Santa Barbara, I I Im i Ii - 19 - Caiifo:nia. Some of the work...multiple pro- cessors will not be as simple as the MMM ones. Acknowledgments. Several useful ideas and suggestions were made by Jim Gray, Peter Honneyman
Development methods for VLSI-processors
International Nuclear Information System (INIS)
Horninger, K.; Sandweg, G.
1982-01-01
The aim of this project, which was originally planed for 3 years, was the development of modern system and circuit concepts, for VLSI-processors having a 32 bit wide data path. The result of this first years work is the concept of a general purpose processor. This processor is not only logically but also physically (on the chip) divided into four functional units: a microprogrammable instruction unit, an execution unit in slice technique, a fully associative cache memory and an I/O unit. For the ALU of the execution unit circuits in PLA and slice techniques have been realized. On the basis of regularity, area consumption and achievable performance the slice technique has been prefered. The designs utilize selftesting circuitry. (orig.) [de
Design of delay insensitive circuits using multi-ring structures
DEFF Research Database (Denmark)
Sparsø, Jens; Staunstrup, Jørgen; Dantzer-Sørensen, Michael
1992-01-01
The design and VLSI implementation of a delay insensitive circuit that computes the inner product of two vec·tors is described. The circuit is based on an iterative serial-parallel multiplication algorithm. The design is based on a data flow approach using pipelines and rings that are combined...
Majorization arrow in quantum-algorithm design
International Nuclear Information System (INIS)
Latorre, J.I.; Martin-Delgado, M.A.
2002-01-01
We apply majorization theory to study the quantum algorithms known so far and find that there is a majorization principle underlying the way they operate. Grover's algorithm is a neat instance of this principle where majorization works step by step until the optimal target state is found. Extensions of this situation are also found in algorithms based in quantum adiabatic evolution and the family of quantum phase-estimation algorithms, including Shor's algorithm. We state that in quantum algorithms the time arrow is a majorization arrow
Ant System-Corner Insertion Sequence: An Efficient VLSI Hard Module Placer
Directory of Open Access Journals (Sweden)
HOO, C.-S.
2013-02-01
Full Text Available Placement is important in VLSI physical design as it determines the time-to-market and chip's reliability. In this paper, a new floorplan representation which couples with Ant System, namely Corner Insertion Sequence (CIS is proposed. Though CIS's search complexity is smaller than the state-of-the-art representation Corner Sequence (CS, CIS adopts a preset boundary on the placement and hence, leading to search bound similar to CS. This enables the previous unutilized corner edges to become viable. Also, the redundancy of CS representation is eliminated in CIS leads to a lower search complexity of CIS. Experimental results on Microelectronics Center of North Carolina (MCNC hard block benchmark circuits show that the proposed algorithm performs comparably in terms of area yet at least two times faster than CS.
The AMchip: A VLSI associative memory for track finding
International Nuclear Information System (INIS)
Morsani, F.; Galeotti, S.; Passuello, D.; Amendolia, S.R.; Ristori, L.; Turini, N.
1992-01-01
An associative memory to be used for super-fast track finding in future high energy physics experiments, has been implemented on silicon as a full-custom CMOS VLSI chip (the AMchip). The first prototype has been designed and successfully tested at INFN in Pisa. It is implemented in 1.6 μm, double metal, silicon gate CMOS technology and contains about 140 000 MOS transistors on a 1x1 cm 2 silicon chip. (orig.)
A genetic algorithm for solving supply chain network design model
Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.
2013-09-01
Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search
Directory of Open Access Journals (Sweden)
Yuan-Jyun Chang
2016-12-01
Full Text Available The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO. The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.
A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search.
Chang, Yuan-Jyun; Hwang, Wen-Jyi; Chen, Chih-Chang
2016-12-07
The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO). The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.
Fuel pin design algorithm for conceptual design studies
International Nuclear Information System (INIS)
Uselman, J.P.
1979-01-01
Two models are available which are currently verified by part of the requirements and which are adaptable as algorithms for the complete range. Fuel thermal performance is described by the HEDL SIEX model. Cladding damage and total deformation are determined by the GE GRO-II structural analysis code. A preliminary fuel pin performance model for analysis of (U, P/sub U/)O 2 pins in the COROPT core conceptual design system has been constructed by combining the key elements of SIEX and GRO-II. This memo describes the resulting pin performance model and its interfacing with COROPT system. Some exemplary results are presented
VLSI scaling methods and low power CMOS buffer circuit
International Nuclear Information System (INIS)
Sharma Vijay Kumar; Pattanaik Manisha
2013-01-01
Device scaling is an important part of the very large scale integration (VLSI) design to boost up the success path of VLSI industry, which results in denser and faster integration of the devices. As technology node moves towards the very deep submicron region, leakage current and circuit reliability become the key issues. Both are increasing with the new technology generation and affecting the performance of the overall logic circuit. The VLSI designers must keep the balance in power dissipation and the circuit's performance with scaling of the devices. In this paper, different scaling methods are studied first. These scaling methods are used to identify the effects of those scaling methods on the power dissipation and propagation delay of the CMOS buffer circuit. For mitigating the power dissipation in scaled devices, we have proposed a reliable leakage reduction low power transmission gate (LPTG) approach and tested it on complementary metal oxide semiconductor (CMOS) buffer circuit. All simulation results are taken on HSPICE tool with Berkeley predictive technology model (BPTM) BSIM4 bulk CMOS files. The LPTG CMOS buffer reduces 95.16% power dissipation with 84.20% improvement in figure of merit at 32 nm technology node. Various process, voltage and temperature variations are analyzed for proving the robustness of the proposed approach. Leakage current uncertainty decreases from 0.91 to 0.43 in the CMOS buffer circuit that causes large circuit reliability. (semiconductor integrated circuits)
Surface and interface effects in VLSI
Einspruch, Norman G
1985-01-01
VLSI Electronics Microstructure Science, Volume 10: Surface and Interface Effects in VLSI provides the advances made in the science of semiconductor surface and interface as they relate to electronics. This volume aims to provide a better understanding and control of surface and interface related properties. The book begins with an introductory chapter on the intimate link between interfaces and devices. The book is then divided into two parts. The first part covers the chemical and geometric structures of prototypical VLSI interfaces. Subjects detailed include, the technologically most import
Testing block subdivision algorithms on block designs
Wiseman, Natalie; Patterson, Zachary
2016-01-01
Integrated land use-transportation models predict future transportation demand taking into account how households and firms arrange themselves partly as a function of the transportation system. Recent integrated models require parcels as inputs and produce household and employment predictions at the parcel scale. Block subdivision algorithms automatically generate parcel patterns within blocks. Evaluating block subdivision algorithms is done by way of generating parcels and comparing them to those in a parcel database. Three block subdivision algorithms are evaluated on how closely they reproduce parcels of different block types found in a parcel database from Montreal, Canada. While the authors who developed each of the algorithms have evaluated them, they have used their own metrics and block types to evaluate their own algorithms. This makes it difficult to compare their strengths and weaknesses. The contribution of this paper is in resolving this difficulty with the aim of finding a better algorithm suited to subdividing each block type. The proposed hypothesis is that given the different approaches that block subdivision algorithms take, it's likely that different algorithms are better adapted to subdividing different block types. To test this, a standardized block type classification is used that consists of mutually exclusive and comprehensive categories. A statistical method is used for finding a better algorithm and the probability it will perform well for a given block type. Results suggest the oriented bounding box algorithm performs better for warped non-uniform sites, as well as gridiron and fragmented uniform sites. It also produces more similar parcel areas and widths. The Generalized Parcel Divider 1 algorithm performs better for gridiron non-uniform sites. The Straight Skeleton algorithm performs better for loop and lollipop networks as well as fragmented non-uniform and warped uniform sites. It also produces more similar parcel shapes and patterns.
A Fuzzy Gravitational Search Algorithm to Design Optimal IIR Filters
Directory of Open Access Journals (Sweden)
Danilo Pelusi
2018-03-01
Full Text Available The goodness of Infinite Impulse Response (IIR digital filters design depends on pass band ripple, stop band ripple and transition band values. The main problem is defining a suitable error fitness function that depends on these parameters. This fitness function can be optimized by search algorithms such as evolutionary algorithms. This paper proposes an intelligent algorithm for the design of optimal 8th order IIR filters. The main contribution is the design of Fuzzy Inference Systems able to tune key parameters of a revisited version of the Gravitational Search Algorithm (GSA. In this way, a Fuzzy Gravitational Search Algorithm (FGSA is designed. The optimization performances of FGSA are compared with those of Differential Evolution (DE and GSA. The results show that FGSA is the algorithm that gives the best compromise between goodness, robustness and convergence rate for the design of 8th order IIR filters. Moreover, FGSA assures a good stability of the designed filters.
HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN
While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...
Analog Circuit Design Optimization Based on Evolutionary Algorithms
Directory of Open Access Journals (Sweden)
Mansour Barari
2014-01-01
Full Text Available This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs. Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met. Comparisons with available methods like genetic algorithms show that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.
Configurable intelligent optimization algorithm design and practice in manufacturing
Tao, Fei; Laili, Yuanjun
2014-01-01
Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorit
Synthesis of on-chip control circuits for mVLSI biochips
DEFF Research Database (Denmark)
Potluri, Seetal; Schneider, Alexander Rüdiger; Hørslev-Petersen, Martin
2017-01-01
them to laboratory environments. To address this issue, researchers have proposed methods to reduce the number of offchip pressure sources, through integration of on-chip pneumatic control logic circuits fabricated using three-layer monolithic membrane valve technology. Traditionally, mVLSI biochip......-chip control circuit design and (iii) the integration of on-chip control in the placement and routing design tasks. In this paper we present a design methodology for logic synthesis and physical synthesis of mVLSI biochips that use on-chip control. We show how the proposed methodology can be successfully...... applied to generate biochip layouts with integrated on-chip pneumatic control....
VLSI Technology for Cognitive Radio
VIJAYALAKSHMI, B.; SIDDAIAH, P.
2017-08-01
One of the most challenging tasks of cognitive radio is the efficiency in the spectrum sensing scheme to overcome the spectrum scarcity problem. The popular and widely used spectrum sensing technique is the energy detection scheme as it is very simple and doesn’t require any previous information related to the signal. We propose one such approach which is an optimised spectrum sensing scheme with reduced filter structure. The optimisation is done in terms of area and power performance of the spectrum. The simulations of the VLSI structure of the optimised flexible spectrum is done using verilog coding by using the XILINX ISE software. Our method produces performance with 13% reduction in area and 66% reduction in power consumption in comparison to the flexible spectrum sensing scheme. All the results are tabulated and comparisons are made. A new scheme for optimised and effective spectrum sensing opens up with our model.
Algorithm for designing smart factory Industry 4.0
Gurjanov, A. V.; Zakoldaev, D. A.; Shukalov, A. V.; Zharinov, I. O.
2018-03-01
The designing task of production division of the Industry 4.0 item designing company is being studied. The authors proposed an algorithm, which is based on the modified V L Volkovich method. This algorithm allows generating options how to arrange the production with robotized technological equipment functioning in the automatic mode. The optimization solution of the multi-criteria task for some additive criteria is the base of the algorithm.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Chemical optimization algorithm for fuzzy controller design
Astudillo, Leslie; Castillo, Oscar
2014-01-01
In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions. This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2017-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2014-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Space mapping optimization algorithms for engineering design
DEFF Research Database (Denmark)
Koziel, Slawomir; Bandler, John W.; Madsen, Kaj
2006-01-01
A simple, efficient optimization algorithm based on space mapping (SM) is presented. It utilizes input SM to reduce the misalignment between the coarse and fine models of the optimized object over a region of interest, and output space mapping (OSM) to ensure matching of response and first...... to a benchmark problem. In comparison with SMIS, the models presented are simple and have a small number of parameters that need to be extracted. The new algorithm is applied to the optimization of coupled-line band-pass filter....
Algorithmic test design using classical item parameters
van der Linden, Willem J.; Adema, Jos J.
Two optimalization models for the construction of tests with a maximal value of coefficient alpha are given. Both models have a linear form and can be solved by using a branch-and-bound algorithm. The first model assumes an item bank calibrated under the Rasch model and can be used, for instance,
An electron undulating ring for VLSI lithography
International Nuclear Information System (INIS)
Tomimasu, T.; Mikado, T.; Noguchi, T.; Sugiyama, S.; Yamazaki, T.
1985-01-01
The development of the ETL storage ring ''TERAS'' as an undulating ring has been continued to achieve a wide area exposure of synchrotron radiation (SR) in VLSI lithography. Stable vertical and horizontal undulating motions of stored beams are demonstrated around a horizontal design orbit of TERAS, using two small steering magnets of which one is used for vertical undulating and another for horizontal one. Each steering magnet is inserted into one of the periodic configulation of guide field elements. As one of useful applications of undulaing electron beams, a vertically wide exposure of SR has been demonstrated in the SR lithography. The maximum vertical deviation from the design orbit nCcurs near the steering magnet. The maximum vertical tilt angle of the undulating beam near the nodes is about + or - 2mrad for a steering magnetic field of 50 gauss. Another proposal is for hith-intensity, uniform and wide exposure of SR from a wiggler installed in TERAS, using vertical and horizontal undulating motions of stored beams. A 1.4 m long permanent magnet wiggler has been installed for this purpose in this April
Convolving optically addressed VLSI liquid crystal SLM
Jared, David A.; Stirk, Charles W.
1994-03-01
We designed, fabricated, and tested an optically addressed spatial light modulator (SLM) that performs a 3 X 3 kernel image convolution using ferroelectric liquid crystal on VLSI technology. The chip contains a 16 X 16 array of current-mirror-based convolvers with a fixed kernel for finding edges. The pixels are located on 75 micron centers, and the modulators are 20 microns on a side. The array successfully enhanced edges in illumination patterns. We developed a high-level simulation tool (CON) for analyzing the performance of convolving SLM designs. CON has a graphical interface and simulates SLM functions using SPICE-like device models. The user specifies the pixel function along with the device parameters and nonuniformities. We discovered through analysis, simulation and experiment that the operation of current-mirror-based convolver pixels is degraded at low light levels by the variation of transistor threshold voltages inherent to CMOS chips. To function acceptable, the test SLM required the input image to have an minimum irradiance of 10 (mu) W/cm2. The minimum required irradiance can be further reduced by adding a photodarlington near the photodetector or by increasing the size of the transistors used to calculate the convolution.
DEFF Research Database (Denmark)
Sparsø, Jens; Jørgensen, Henrik Nordtorp; Paaske, Erik
1991-01-01
A topology for single-chip implementation of computing structures based on shuffle-exchange (SE)-type interconnection networks is presented. The topology is suited for structures with a small number of processing elements (i.e. 32-128) whose area cannot be neglected compared to the area required....... The topology has been used in a VLSI implementation of the add-compare-select (ACS) module of a fully parallel K=7, R=1/2 Viterbi decoder. Both the floor-planning issues and some of the important algorithm and circuit-level aspects of this design are discussed. The chip has been designed and fabricated in a 2....... The interconnection network occupies 32% of the area.>...
Algorithm for the real-structure design of neutron supermirrors
International Nuclear Information System (INIS)
Pleshanov, N.K.
2004-01-01
The effect of structure imperfections of neutron supermirrors on their performance is well known. Nevertheless, supermirrors are designed with the algorithms based on the theories of reflection from perfect layered structures. In the present paper an approach is suggested, in which the design of a supermirror is made on the basis of its real-structure model (the RSD algorithm) with the use of exact numerical methods. It allows taking the growth laws and the reflectance of real structures into account. The new algorithm was compared with the Gukasov-Ruban-Bedrizova (GRB) algorithm and with the most frequently used algorithm of Hayter and Mook (HM). Calculations showed that, when the parameters of the algorithms are chosen so that the supermirrors designed for a given angular acceptance m have the same number of bilayers, (a) for perfect layers the GRB, HM and RSD algorithms generate sequences of practically the same reflectance; (b) for real structures with rough interfaces and interdiffusion the GRB and HM algorithms generate sequences with insufficient number of thinner layers and the RSD algorithm turns out to be more responsive and efficient. The efficiency of the RSD algorithm increases for larger m. In addition, calculations have been carried out to demonstrate the effect of fabrication errors and absorption on the reflectance of Ni/Ti supermirrors
Power gating of VLSI circuits using MEMS switches in low power applications
Shobak, Hosam; Ghoneim, Mohamed T.; El Boghdady, Nawal; Halawa, Sarah; Iskander, Sophinese M.; Anis, Mohab H.
2011-01-01
-designed MEMS switch to power gate VLSI circuits, such that leakage power is efficiently reduced while accounting for performance and reliability. The designed MEMS switch is characterized by an 0.1876 ? ON resistance and requires 4.5 V to switch. As a result
Design Automation Algorithm for Soft Robots
National Aeronautics and Space Administration — The majority of design to manufacturing today is still an ad hoc and empirical process. There is a direct need for a single, automated design and fabrication...
Photovoltaic Cells Mppt Algorithm and Design of Controller Monitoring System
Meng, X. Z.; Feng, H. B.
2017-10-01
This paper combined the advantages of each maximum power point tracking (MPPT) algorithm, put forward a kind of algorithm with higher speed and higher precision, based on this algorithm designed a maximum power point tracking controller with ARM. The controller, communication technology and PC software formed a control system. Results of the simulation and experiment showed that the process of maximum power tracking was effective, and the system was stable.
The GLUEchip: A custom VLSI chip for detectors readout and associative memories circuits
International Nuclear Information System (INIS)
Amendolia, S.R.; Galeotti, S.; Morsani, F.; Passuello, D.; Ristori, L.; Turini, N.
1993-01-01
An associative memory full-custom VLSI chip for pattern recognition has been designed and tested in the past years. It's the AMchip, that contains 128 patterns of 60 bits each. To expand the pattern capacity of an Associative Memory bank, the custom VLSI GLUEchip has been developed. The GLUEchip allows the interconnection of up to 16 AMchips or up to 16 GLUEchips: the resulting tree-like structure works like a single AMchip with an output pipelined structure and a pattern capacity increased by a factor 16 for each GLUEchip used
Genetic algorithms applied to nuclear reactor design optimization
International Nuclear Information System (INIS)
Pereira, C.M.N.A.; Schirru, R.; Martinez, A.S.
2000-01-01
A genetic algorithm is a powerful search technique that simulates natural evolution in order to fit a population of computational structures to the solution of an optimization problem. This technique presents several advantages over classical ones such as linear programming based techniques, often used in nuclear engineering optimization problems. However, genetic algorithms demand some extra computational cost. Nowadays, due to the fast computers available, the use of genetic algorithms has increased and its practical application has become a reality. In nuclear engineering there are many difficult optimization problems related to nuclear reactor design. Genetic algorithm is a suitable technique to face such kind of problems. This chapter presents applications of genetic algorithms for nuclear reactor core design optimization. A genetic algorithm has been designed to optimize the nuclear reactor cell parameters, such as array pitch, isotopic enrichment, dimensions and cells materials. Some advantages of this genetic algorithm implementation over a classical method based on linear programming are revealed through the application of both techniques to a simple optimization problem. In order to emphasize the suitability of genetic algorithms for design optimization, the technique was successfully applied to a more complex problem, where the classical method is not suitable. Results and comments about the applications are also presented. (orig.)
Designers' Cognitive Thinking Based on Evolutionary Algorithms
Zhang Shutao; Jianning Su; Chibing Hu; Peng Wang
2013-01-01
The research on cognitive thinking is important to construct the efficient intelligent design systems. But it is difficult to describe the model of cognitive thinking with reasonable mathematical theory. Based on the analysis of design strategy and innovative thinking, we investigated the design cognitive thinking model that included the external guide thinking of "width priority - depth priority" and the internal dominated thinking of "divergent thinking - convergent thinking", built a reaso...
Generative Algorithmic Techniques for Architectural Design
DEFF Research Database (Denmark)
Larsen, Niels Martin
2012-01-01
Architectural design methodology is expanded through the ability to create bespoke computational methods as integrated parts of the design process. The rapid proliferation of digital production techniques within building industry provides new means for establishing seamless flows between digital...... form-generation and the realisation process. A tendency in recent practice shows an increased focus on developing unique tectonic solutions as a crucial ingredient in the design solution. These converging trajectories form the contextual basis for this thesis. In architectural design, digital tools....... The principles are further developed to form new modes of articulation in architectural design. Certain methods are contributions, which suggest a potential for future use and development. Thus, a method is directed towards bottom-up generation of surface topology through the use of an agentbased logic. Another...
Point DCT VLSI Architecture for Emerging HEVC Standard
Ahmed, Ashfaq; Shahid, Muhammad Usman; Rehman, Ata ur
2012-01-01
This work presents a flexible VLSI architecture to compute the -point DCT. Since HEVC supports different block sizes for the computation of the DCT, that is, 4 × 4 up to 3 2 × 3 2 , the design of a flexible architecture to support them helps reducing the area overhead of hardware implementations. The hardware proposed in this work is partially folded to save area and to get speed for large video sequences sizes. The proposed architecture relies on the decomposition of the DCT matrices into ...
VLSI architectures for modern error-correcting codes
Zhang, Xinmiao
2015-01-01
Error-correcting codes are ubiquitous. They are adopted in almost every modern digital communication and storage system, such as wireless communications, optical communications, Flash memories, computer hard drives, sensor networks, and deep-space probing. New-generation and emerging applications demand codes with better error-correcting capability. On the other hand, the design and implementation of those high-gain error-correcting codes pose many challenges. They usually involve complex mathematical computations, and mapping them directly to hardware often leads to very high complexity. VLSI
Theory and Algorithms for Global/Local Design Optimization
National Research Council Canada - National Science Library
Haftka, Raphael T
2004-01-01
... the component and overall design as well as on exploration of global optimization algorithms. In the former category, heuristic decomposition was followed with proof that it solves the original problem...
Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1997-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
Theory and Algorithms for Global/Local Design Optimization
National Research Council Canada - National Science Library
Watson, Layne T; Guerdal, Zafer; Haftka, Raphael T
2005-01-01
The motivating application for this research is the global/local optimal design of composite aircraft structures such as wings and fuselages, but the theory and algorithms are more widely applicable...
Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1998-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
Design Optimization of Space Launch Vehicles Using a Genetic Algorithm
National Research Council Canada - National Science Library
Bayley, Douglas J
2007-01-01
.... A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost...
Algorithms for adaptive histogram equalization
International Nuclear Information System (INIS)
Pizer, S.M.; Austin, J.D.; Cromartie, R.; Geselowitz, A.; Ter Haar Romeny, B.; Zimmerman, J.B.; Zuiderveld, K.
1986-01-01
Adaptive histogram equalization (ahe) is a contrast enhancement method designed to be broadly applicable and having demonstrated effectiveness [Zimmerman, 1985]. However, slow speed and the overenhancement of noise it produces in relatively homogeneous regions are two problems. The authors summarize algorithms designed to overcome these and other concerns. These algorithms include interpolated ahe, to speed up the method on general purpose computers; a version of interpolated ahe designed to run in a few seconds on feedback processors; a version of full ahe designed to run in under one second on custom VLSI hardware; and clipped ahe, designed to overcome the problem of overenhancement of noise contrast. The authors conclude that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clipped ahe can be made adequately fast to be routinely applied in the normal display sequence
Channel Access Algorithm Design for Automatic Identification System
Institute of Scientific and Technical Information of China (English)
Oh Sang-heon; Kim Seung-pum; Hwang Dong-hwan; Park Chan-sik; Lee Sang-jeong
2003-01-01
The Automatic Identification System (AIS) is a maritime equipment to allow an efficient exchange of the navigational data between ships and between ships and shore stations. It utilizes a channel access algorithm which can quickly resolve conflicts without any intervention from control stations. In this paper, a design of channel access algorithm for the AIS is presented. The input/output relationship of each access algorithm module is defined by drawing the state transition diagram, dataflow diagram and flowchart based on the technical standard, ITU-R M.1371. In order to verify the designed channel access algorithm, the simulator was developed using the C/C++ programming language. The results show that the proposed channel access algorithm can properly allocate transmission slots and meet the operational performance requirements specified by the technical standard.
A Topological Model for Parallel Algorithm Design
1991-09-01
effort should be directed to planning, requirements analysis, specification and design, with 20% invested into the actual coding, and then the final 40...be olle more language to learn. And by investing the effort into improving the utility of ai, existing language instead of creating a new one, this...193) it abandons the notion of a process as a fundemental concept of parallel program design and that it facilitates program derivation by rigorously
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
Lohn, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris; Norvig, Peter (Technical Monitor)
2000-01-01
We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.
Starting design for use in variance exchange algorithms | Iwundu ...
African Journals Online (AJOL)
A new method of constructing the initial design for use in variance exchange algorithms is presented. The method chooses support points to go into the design as measures of distances of the support points from the centre of the geometric region and of permutation-invariant sets. The initial design is as close as possible to ...
Application of colony complex algorithm to nuclear component optimization design
International Nuclear Information System (INIS)
Yan Changqi; Li Guijing; Wang Jianjun
2014-01-01
Complex algorithm (CA) has got popular application to the region of nuclear engineering. In connection with the specific features of the application of traditional complex algorithm (TCA) to the optimization design in engineering structures, an improved method, colony complex algorithm (CCA), was developed based on the optimal combination of many complexes, in which the disadvantages of TCA were overcame. The optimized results of benchmark function show that CCA has better optimizing performance than TCA. CCA was applied to the high-pressure heater optimization design, and the optimization effect is obvious. (authors)
Lithography requirements in complex VLSI device fabrication
International Nuclear Information System (INIS)
Wilson, A.D.
1985-01-01
Fabrication of complex very large scale integration (VLSI) circuits requires continual advances in lithography to satisfy: decreasing minimum linewidths, larger chip sizes, tighter linewidth and overlay control, increasing topography to linewidth ratios, higher yield demands, increased throughput, harsher device processing, lower lithography cost, and a larger part number set with quick turn-around time. Where optical, electron beam, x-ray, and ion beam lithography can be applied to judiciously satisfy the complex VLSI circuit fabrication requirements is discussed and those areas that are in need of major further advances are addressed. Emphasis will be placed on advanced electron beam and storage ring x-ray lithography
Development of Radhard VLSI electronics for SSC calorimeters
International Nuclear Information System (INIS)
Dawson, J.W.; Nodulman, L.J.
1989-01-01
A new program of development of integrated electronics for liquid argon calorimeters in the SSC detector environment is being started at Argonne National Laboratory. Scientists from Brookhaven National Laboratory and Vanderbilt University together with an industrial participants are expected to collaborate in this work. Interaction rates, segmentation, and the radiation environment dictate that front-end electronics of SSC calorimeters must be implemented in the form of highly integrated, radhard, analog, low noise, VLSI custom monolithic devices. Important considerations are power dissipation, choice of functions integrated on the front-end chips, and cabling requirements. An extensive level of expertise in radhard electronics exists within the industrial community, and a primary objective of this work is to bring that expertise to bear on the problems of SSC detector design. Radiation hardness measurements and requirements as well as calorimeter design will be primarily the responsibility of Argonne scientists and our Brookhaven and Vanderbilt colleagues. Radhard VLSI design and fabrication will be primarily the industrial participant's responsibility. The rapid-cycling synchrotron at Argonne will be used for radiation damage studies involving response to neutrons and charged particles, while damage from gammas will be investigated at Brookhaven. 10 refs., 6 figs., 2 tabs
High performance VLSI telemetry data systems
Chesney, J.; Speciale, N.; Horner, W.; Sabia, S.
1990-01-01
NASA's deployment of major space complexes such as Space Station Freedom (SSF) and the Earth Observing System (EOS) will demand increased functionality and performance from ground based telemetry acquisition systems well above current system capabilities. Adaptation of space telemetry data transport and processing standards such as those specified by the Consultative Committee for Space Data Systems (CCSDS) standards and those required for commercial ground distribution of telemetry data, will drive these functional and performance requirements. In addition, budget limitations will force the requirement for higher modularity, flexibility, and interchangeability at lower cost in new ground telemetry data system elements. At NASA's Goddard Space Flight Center (GSFC), the design and development of generic ground telemetry data system elements, over the last five years, has resulted in significant solutions to these problems. This solution, referred to as the functional components approach includes both hardware and software components ready for end user application. The hardware functional components consist of modern data flow architectures utilizing Application Specific Integrated Circuits (ASIC's) developed specifically to support NASA's telemetry data systems needs and designed to meet a range of data rate requirements up to 300 Mbps. Real-time operating system software components support both embedded local software intelligence, and overall system control, status, processing, and interface requirements. These components, hardware and software, form the superstructure upon which project specific elements are added to complete a telemetry ground data system installation. This paper describes the functional components approach, some specific component examples, and a project example of the evolution from VLSI component, to basic board level functional component, to integrated telemetry data system.
Algorithmically specialized parallel computers
Snyder, Lawrence; Gannon, Dennis B
1985-01-01
Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster
Artificial neural networks and evolutionary algorithms in engineering design
T. Velsker; M. Eerme; J. Majak; M. Pohlak; K. Karjust
2011-01-01
Purpose: Purpose of this paper is investigation of optimization strategies eligible for solving complex engineering design problems. An aim is to develop numerical algorithms for solving optimal design problems which may contain real and integer variables, a number of local extremes, linear- and non-linear constraints and multiple optimality criteria.Design/methodology/approach: The methodology proposed for solving optimal design problems is based on integrated use of meta-modeling techniques...
A Knowledge Based Approach to VLSI CAD
1983-09-01
Avail-and/or Dist ISpecial L| OI. SEICURITY CLASIIrCATION OP THIS IPA.lErllm S Daene." A KNOwLEDE BASED APPROACH TO VLSI CAD’ Louis L Steinberg and...major issues lies in building up and managing the knowledge base of oesign expertise. We expect that, as with many recent expert systems, in order to
Electro-optic techniques for VLSI interconnect
Neff, J. A.
1985-03-01
A major limitation to achieving significant speed increases in very large scale integration (VLSI) lies in the metallic interconnects. They are costly not only from the charge transport standpoint but also from capacitive loading effects. The Defense Advanced Research Projects Agency, in pursuit of the fifth generation supercomputer, is investigating alternatives to the VLSI metallic interconnects, especially the use of optical techniques to transport the information either inter or intrachip. As the on chip performance of VLSI continues to improve via the scale down of the logic elements, the problems associated with transferring data off and onto the chip become more severe. The use of optical carriers to transfer the information within the computer is very appealing from several viewpoints. Besides the potential for gigabit propagation rates, the conversion from electronics to optics conveniently provides a decoupling of the various circuits from one another. Significant gains will also be realized in reducing cross talk between the metallic routings, and the interconnects need no longer be constrained to the plane of a thin film on the VLSI chip. In addition, optics can offer an increased programming flexibility for restructuring the interconnect network.
Analog Group Delay Equalizers Design Based on Evolutionary Algorithm
Directory of Open Access Journals (Sweden)
M. Laipert
2006-04-01
Full Text Available This paper deals with a design method of the analog all-pass filter designated for equalization of the group delay frequency response of the analog filter. This method is based on usage of evolutionary algorithm, the Differential Evolution algorithm in particular. We are able to design such equalizers to be obtained equal-ripple group delay frequency response in the pass-band of the low-pass filter. The procedure works automatically without an input estimation. The method is presented on solving practical examples.
Towards Automatic Controller Design using Multi-Objective Evolutionary Algorithms
DEFF Research Database (Denmark)
Pedersen, Gerulf
of evolutionary computation, a choice was made to use multi-objective algorithms for the purpose of aiding in automatic controller design. More specifically, the choice was made to use the Non-dominated Sorting Genetic Algorithm II (NSGAII), which is one of the most potent algorithms currently in use...... for automatic controller design. However, because the field of evolutionary computation is relatively unknown in the field of control engineering, this thesis also includes a comprehensive introduction to the basic field of evolutionary computation as well as a description of how the field has previously been......In order to design the controllers of tomorrow, a need has risen for tools that can aid in the design of these. A desire to use evolutionary computation as a tool to achieve that goal is what gave inspiration for the work contained in this thesis. After having studied the foundations...
Design and analysis of cryptographic algorithms
DEFF Research Database (Denmark)
Kölbl, Stefan
. From securing our passwords and personal data to protecting mobile communication from eavesdroppers and our electronic bank transactions from manipulation. These applications would be impossible without cryptography. The main topic of this thesis is the design and security analysis of the most......In today’s world computers are ubiquitous. They can be found in virtually any industry and most households own at least one personal computer or have a mobile phone. Apart from these fairly large and complex devices, we also see computers on a much smaller scale appear in everyday objects...... to this development. However, most of this communication happens over inherently insecure channels requiring methods to protect our communication. A further issue is the vast amount of data generated, which raises serious privacy concerns. Cryptography provides the key components for protecting our communication...
A Cultural Algorithm for Optimal Design of Truss Structures
Directory of Open Access Journals (Sweden)
Shahin Jalili
Full Text Available Abstract A cultural algorithm was utilized in this study to solve optimal design of truss structures problem achieving minimum weight objective under stress and deflection constraints. The algorithm is inspired by principles of human social evolution. It simulates the social interaction between the peoples and their beliefs in a belief space. Cultural Algorithm (CA utilizes the belief space and population space which affects each other based on acceptance and influence functions. The belief space of CA consists of different knowledge components. In this paper, only situational and normative knowledge components are used within the belief space. The performance of the method is demonstrated through four benchmark design examples. Comparison of the obtained results with those of some previous studies demonstrates the efficiency of this algorithm.
A strategy for quantum algorithm design assisted by machine learning
International Nuclear Information System (INIS)
Bang, Jeongho; Lee, Jinhyoung; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin
2014-01-01
We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum–classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch–Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method. (paper)
A strategy for quantum algorithm design assisted by machine learning
Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung
2014-07-01
We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.
Evaluating progressive-rendering algorithms in appearance design tasks.
Jiawei Ou; Karlik, Ondrej; Křivánek, Jaroslav; Pellacini, Fabio
2013-01-01
Progressive rendering is becoming a popular alternative to precomputational approaches to appearance design. However, progressive algorithms create images exhibiting visual artifacts at early stages. A user study investigated these artifacts' effects on user performance in appearance design tasks. Novice and expert subjects performed lighting and material editing tasks with four algorithms: random path tracing, quasirandom path tracing, progressive photon mapping, and virtual-point-light rendering. Both the novices and experts strongly preferred path tracing to progressive photon mapping and virtual-point-light rendering. None of the participants preferred random path tracing to quasirandom path tracing or vice versa; the same situation held between progressive photon mapping and virtual-point-light rendering. The user workflow didn’t differ significantly with the four algorithms. The Web Extras include a video showing how four progressive-rendering algorithms converged (at http://youtu.be/ck-Gevl1e9s), the source code used, and other supplementary materials.
Foundations of digital signal processing theory, algorithms and hardware design
Gaydecki, Patrick
2005-01-01
An excellent introductory text, this book covers the basic theoretical, algorithmic and real-time aspects of digital signal processing (DSP). Detailed information is provided on off-line, real-time and DSP programming and the reader is effortlessly guided through advanced topics such as DSP hardware design, FIR and IIR filter design and difference equation manipulation.
Automatic design of decision-tree induction algorithms
Barros, Rodrigo C; Freitas, Alex A
2015-01-01
Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning, and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain o
Hardware Design Considerations for Edge-Accelerated Stereo Correspondence Algorithms
Directory of Open Access Journals (Sweden)
Christos Ttofis
2012-01-01
Full Text Available Stereo correspondence is a popular algorithm for the extraction of depth information from a pair of rectified 2D images. Hence, it has been used in many computer vision applications that require knowledge about depth. However, stereo correspondence is a computationally intensive algorithm and requires high-end hardware resources in order to achieve real-time processing speed in embedded computer vision systems. This paper presents an overview of the use of edge information as a means to accelerate hardware implementations of stereo correspondence algorithms. The presented approach restricts the stereo correspondence algorithm only to the edges of the input images rather than to all image points, thus resulting in a considerable reduction of the search space. The paper highlights the benefits of the edge-directed approach by applying it to two stereo correspondence algorithms: an SAD-based fixed-support algorithm and a more complex adaptive support weight algorithm. Furthermore, we present design considerations about the implementation of these algorithms on reconfigurable hardware and also discuss issues related to the memory structures needed, the amount of parallelism that can be exploited, the organization of the processing blocks, and so forth. The two architectures (fixed-support based versus adaptive-support weight based are compared in terms of processing speed, disparity map accuracy, and hardware overheads, when both are implemented on a Virtex-5 FPGA platform.
Theoretical and numerical study of an optimum design algorithm
International Nuclear Information System (INIS)
Destuynder, Philippe.
1976-08-01
This work can be separated into two main parts. First, the behavior of the solution of an elliptic variational equation is analyzed when the domain is submitted to a small perturbation. The case of inequations is also considered. Secondly the previous results are used for deriving an optimum design algorithm. This algorithm was suggested by the center-method proposed by Huard. Numerical results show the superiority of the method on other different optimization techniques [fr
Kriging-based algorithm for nuclear reactor neutronic design optimization
International Nuclear Information System (INIS)
Kempf, Stephanie; Forget, Benoit; Hu, Lin-Wen
2012-01-01
Highlights: ► A Kriging-based algorithm was selected to guide research reactor optimization. ► We examined impacts of parameter values upon the algorithm. ► The best parameter values were incorporated into a set of best practices. ► Algorithm with best practices used to optimize thermal flux of concept. ► Final design produces thermal flux 30% higher than other 5 MW reactors. - Abstract: Kriging, a geospatial interpolation technique, has been used in the present work to drive a search-and-optimization algorithm which produces the optimum geometric parameters for a 5 MW research reactor design. The technique has been demonstrated to produce an optimal neutronic solution after a relatively small number of core calculations. It has additionally been successful in producing a design which significantly improves thermal neutron fluxes by 30% over existing reactors of the same power rating. Best practices for use of this algorithm in reactor design were identified and indicated the importance of selecting proper correlation functions.
Simulated annealing algorithm for reactor in-core design optimizations
International Nuclear Information System (INIS)
Zhong Wenfa; Zhou Quan; Zhong Zhaopeng
2001-01-01
A nuclear reactor must be optimized for in core fuel management to make full use of the fuel, to reduce the operation cost and to flatten the power distribution reasonably. The author presents a simulated annealing algorithm. The optimized objective function and the punishment function were provided for optimizing the reactor physics design. The punishment function was used to practice the simulated annealing algorithm. The practical design of the NHR-200 was calculated. The results show that the K eff can be increased by 2.5% and the power distribution can be flattened
Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.
Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert
2017-12-01
Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.
Motion estimation for video coding efficient algorithms and architectures
Chakrabarti, Indrajit; Chatterjee, Sumit Kumar
2015-01-01
The need of video compression in the modern age of visual communication cannot be over-emphasized. This monograph will provide useful information to the postgraduate students and researchers who wish to work in the domain of VLSI design for video processing applications. In this book, one can find an in-depth discussion of several motion estimation algorithms and their VLSI implementation as conceived and developed by the authors. It records an account of research done involving fast three step search, successive elimination, one-bit transformation and its effective combination with diamond search and dynamic pixel truncation techniques. Two appendices provide a number of instances of proof of concept through Matlab and Verilog program segments. In this aspect, the book can be considered as first of its kind. The architectures have been developed with an eye to their applicability in everyday low-power handheld appliances including video camcorders and smartphones.
A Novel Evolutionary Algorithm for Designing Robust Analog Filters
Directory of Open Access Journals (Sweden)
Shaobo Li
2018-03-01
Full Text Available Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP coupled with bond graph modeling. We applied our GP-based robust design (GPRD algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA, our GPRD algorithm with a fitness criterion rewarding robustness, with respect to parameter perturbations, can evolve more robust filters than what was achieved through parameter tuning alone. We also find that inappropriate GA tuning may mislead the search process and that multiple-simulation and perturbed fitness evaluation methods for evolving robustness have complementary behaviors with no absolute advantage of one over the other.
Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms.
Garro, Beatriz A; Vázquez, Roberto A
2015-01-01
Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems.
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.
A superlinear interior points algorithm for engineering design optimization
Herskovits, J.; Asquier, J.
1990-01-01
We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.
A Hybrid Optimization Algorithm for Low RCS Antenna Design
Directory of Open Access Journals (Sweden)
W. Shao
2012-12-01
Full Text Available In this article, a simple and efficient method is presented to design low radar cross section (RCS patch antennas. This method consists of a hybrid optimization algorithm, which combines a genetic algorithm (GA with tabu search algorithm (TSA, and electromagnetic field solver. The TSA, embedded into the GA frame, defines the acceptable neighborhood region of parameters and screens out the poor-scoring individuals. Thus, the repeats of search are avoided and the amount of time-consuming electromagnetic simulations is largely reduced. Moreover, the whole design procedure is auto-controlled by programming the VBScript language. A slot patch antenna example is provided to verify the accuracy and efficiency of the proposed method.
Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs
Directory of Open Access Journals (Sweden)
Haijian Chen
2015-01-01
Full Text Available In recent years, Massive Open Online Courses (MOOCs are very popular among college students and have a powerful impact on academic institutions. In the MOOCs environment, knowledge discovery and knowledge sharing are very important, which currently are often achieved by ontology techniques. In building ontology, automatic extraction technology is crucial. Because the general methods of text mining algorithm do not have obvious effect on online course, we designed automatic extracting course knowledge points (AECKP algorithm for online course. It includes document classification, Chinese word segmentation, and POS tagging for each document. Vector Space Model (VSM is used to calculate similarity and design the weight to optimize the TF-IDF algorithm output values, and the higher scores will be selected as knowledge points. Course documents of “C programming language” are selected for the experiment in this study. The results show that the proposed approach can achieve satisfactory accuracy rate and recall rate.
Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P
2010-10-30
Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy. Copyright © 2010 Elsevier B.V. All rights reserved.
An algorithm, implementation and execution ontology design pattern
Lawrynowicz, A.; Esteves, D.; Panov, P.; Soru, T.; Dzeroski, S.; Vanschoren, J.
2016-01-01
This paper describes an ontology design pattern for modeling algorithms, their implementations and executions. This pattern is derived from the research results on data mining/machine learning ontologies, but is more generic. We argue that the proposed pattern will foster the development of
New design algorithm and reliability testing of solar powered near ...
African Journals Online (AJOL)
New design algorithm and reliability testing of solar powered near-space flight vehicle for defense and security. ... To overcome this problem, we propose a pseudo-satellite system where telecommunication devices are carried on a perpetually flying solar aircraft cruising at stratospheric altitude. Our aircraft will combine ...
Genetic Algorithm Design of a 3D Printed Heat Sink
Energy Technology Data Exchange (ETDEWEB)
Wu, Tong [ORNL; Ozpineci, Burak [ORNL; Ayers, Curtis William [ORNL
2016-01-01
In this paper, a genetic algorithm- (GA-) based approach is discussed for designing heat sinks based on total heat generation and dissipation for a pre-specified size andshape. This approach combines random iteration processesand genetic algorithms with finite element analysis (FEA) to design the optimized heat sink. With an approach that prefers survival of the fittest , a more powerful heat sink can bedesigned which can cool power electronics more efficiently. Some of the resulting designs can only be 3D printed due totheir complexity. In addition to describing the methodology, this paper also includes comparisons of different cases to evaluate the performance of the newly designed heat sinkcompared to commercially available heat sinks.
Reactor controller design using genetic algorithms with simulated annealing
International Nuclear Information System (INIS)
Erkan, K.; Buetuen, E.
2000-01-01
This chapter presents a digital control system for ITU TRIGA Mark-II reactor using genetic algorithms with simulated annealing. The basic principles of genetic algorithms for problem solving are inspired by the mechanism of natural selection. Natural selection is a biological process in which stronger individuals are likely to be winners in a competing environment. Genetic algorithms use a direct analogy of natural evolution. Genetic algorithms are global search techniques for optimisation but they are poor at hill-climbing. Simulated annealing has the ability of probabilistic hill-climbing. Thus, the two techniques are combined here to get a fine-tuned algorithm that yields a faster convergence and a more accurate search by introducing a new mutation operator like simulated annealing or an adaptive cooling schedule. In control system design, there are currently no systematic approaches to choose the controller parameters to obtain the desired performance. The controller parameters are usually determined by test and error with simulation and experimental analysis. Genetic algorithm is used automatically and efficiently searching for a set of controller parameters for better performance. (orig.)
MICRONEEDLE STRUCTURE DESIGN AND OPTIMIZATION USING GENETIC ALGORITHM
N. A. ISMAIL; S. C. NEOH; N. SABANI; B. N. TAIB
2015-01-01
This paper presents a Genetic Algorithm (GA) based microneedle design and analysis. GA is an evolutionary optimization technique that mimics the natural biological evolution. The design of microneedle structure considers the shape of microneedle, material used, size of the array, the base of microneedle, the lumen base, the height of microneedle, the height of the lumen, and the height of the drug container or reservoir. The GA is executed in conjunction with ANSYS simulation system to assess...
Nuclear power control system design using genetic algorithm
International Nuclear Information System (INIS)
Lee, Yoon Joon; Cho, Kyung Ho
1996-01-01
The genetic algorithm(GA) is applied to the design of the nuclear power control system. The reactor control system model is described in the LQR configuration. The LQR system order is increased to make the tracking system. The key parameters of the design are weighting matrices, and these are usually determined through numerous simulations in the conventional design. To determine the more objective and optimal weightings, the improved GA is applied. The results show that the weightings determined by the GA yield the better system responses than those obtained by the conventional design method
Application of ant colony Algorithm and particle swarm optimization in architectural design
Song, Ziyi; Wu, Yunfa; Song, Jianhua
2018-02-01
By studying the development of ant colony algorithm and particle swarm algorithm, this paper expounds the core idea of the algorithm, explores the combination of algorithm and architectural design, sums up the application rules of intelligent algorithm in architectural design, and combines the characteristics of the two algorithms, obtains the research route and realization way of intelligent algorithm in architecture design. To establish algorithm rules to assist architectural design. Taking intelligent algorithm as the beginning of architectural design research, the authors provide the theory foundation of ant colony Algorithm and particle swarm algorithm in architectural design, popularize the application range of intelligent algorithm in architectural design, and provide a new idea for the architects.
Heavy ion tests on programmable VLSI
International Nuclear Information System (INIS)
Provost-Grellier, A.
1989-11-01
The radiation from space environment induces operation damages in onboard computers systems. The definition of a strategy, for the Very Large Scale Integrated Circuitry (VLSI) qualification and choice, is needed. The 'upset' phenomena is known to be the most critical integrated circuit radiation effect. The strategies for testing integrated circuits are reviewed. A method and a test device were developed and applied to space applications candidate circuits. Cyclotron, synchrotron and Californium source experiments were carried out [fr
Applications of VLSI circuits to medical imaging
International Nuclear Information System (INIS)
O'Donnell, M.
1988-01-01
In this paper the application of advanced VLSI circuits to medical imaging is explored. The relationship of both general purpose signal processing chips and custom devices to medical imaging is discussed using examples of fabricated chips. In addition, advanced CAD tools for silicon compilation are presented. Devices built with these tools represent a possible alternative to custom devices and general purpose signal processors for the next generation of medical imaging systems
A new collage steganographic algorithm using cartoon design
Yi, Shuang; Zhou, Yicong; Pun, Chi-Man; Chen, C. L. Philip
2014-02-01
Existing collage steganographic methods suffer from low payload of embedding messages. To improve the payload while providing a high level of security protection to messages, this paper introduces a new collage steganographic algorithm using cartoon design. It embeds messages into the least significant bits (LSBs) of color cartoon objects, applies different permutations to each object, and adds objects to a cartoon cover image to obtain the stego image. Computer simulations and comparisons demonstrate that the proposed algorithm shows significantly higher capacity of embedding messages compared with existing collage steganographic methods.
Designing algorithm visualization on mobile platform: The proposed guidelines
Supli, A. A.; Shiratuddin, N.
2017-09-01
This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively. Our previous review indicated that design guidelines of AV on mobile platform are still few. Mostly, previous guidelines of AV are developed for AV on desktop and website platform. In fact, mobile learning has been proved to enhance engagement in learning circumstances, and thus effect student's performance. In addition, the researchers highly recommend including UI design and Interactivity in designing effective AV system. However, the discussions of these two aspects in previous AV design guidelines are not comprehensive. The UI design in this paper describes the arrangement of AV features in mobile environment, whereas interactivity is about the active learning strategy features based on learning experiences (how to engage learners). Thus, this study main objective is to propose design guidelines of AV on mobile platform (AVOMP) that entails comprehensively UI design and interactivity aspects. These guidelines are developed through content analysis and comparative analysis from various related studies. These guidelines are useful for AV designers to help them constructing AVOMP for various topics on DSA.
Genetic algorithms and Monte Carlo simulation for optimal plant design
International Nuclear Information System (INIS)
Cantoni, M.; Marseguerra, M.; Zio, E.
2000-01-01
We present an approach to the optimal plant design (choice of system layout and components) under conflicting safety and economic constraints, based upon the coupling of a Monte Carlo evaluation of plant operation with a Genetic Algorithms-maximization procedure. The Monte Carlo simulation model provides a flexible tool, which enables one to describe relevant aspects of plant design and operation, such as standby modes and deteriorating repairs, not easily captured by analytical models. The effects of deteriorating repairs are described by means of a modified Brown-Proschan model of imperfect repair which accounts for the possibility of an increased proneness to failure of a component after a repair. The transitions of a component from standby to active, and vice versa, are simulated using a multiplicative correlation model. The genetic algorithms procedure is demanded to optimize a profit function which accounts for the plant safety and economic performance and which is evaluated, for each possible design, by the above Monte Carlo simulation. In order to avoid an overwhelming use of computer time, for each potential solution proposed by the genetic algorithm, we perform only few hundreds Monte Carlo histories and, then, exploit the fact that during the genetic algorithm population evolution, the fit chromosomes appear repeatedly many times, so that the results for the solutions of interest (i.e. the best ones) attain statistical significance
An Algorithm for the Mixed Transportation Network Design Problem.
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
An Algorithm for the Mixed Transportation Network Design Problem.
Directory of Open Access Journals (Sweden)
Xinyu Liu
Full Text Available This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA, for solving a mixed transportation network design problem (MNDP, which is generally expressed as a mathematical programming with equilibrium constraint (MPEC. The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE problem. The idea of the proposed solution algorithm (DDIA is to reduce the dimensions of the problem. A group of variables (discrete/continuous is fixed to optimize another group of variables (continuous/discrete alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems and DNDPs (discrete network design problems repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions. Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
A structured representation for parallel algorithm design on multicomputers
International Nuclear Information System (INIS)
Sun, Xian-He; Ni, L.M.
1991-01-01
Traditionally, parallel algorithms have been designed by brute force methods and fine-tuned on each architecture to achieve high performance. Rather than studying the design case by case, a systematic approach is proposed. A notation is first developed. Using this notation, most of the frequently used scientific and engineering applications can be presented by simple formulas. The formulas constitute the structured representation of the corresponding applications. The structured representation is simple, adequate and easy to understand. They also contain sufficient information about uneven allocation and communication latency degradations. With the structured representation, applications can be compared, classified and partitioned. Some of the basic building blocks, called computation models, of frequently used applications are identified and studied. Most applications are combinations of some computation models. The structured representation relates general applications to computation models. Studying computation models leads to a guideline for efficient parallel algorithm design for general applications. 6 refs., 7 figs
Designing synthetic networks in silico: a generalised evolutionary algorithm approach.
Smith, Robert W; van Sluijs, Bob; Fleck, Christian
2017-12-02
Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.
Vlsi implementation of flexible architecture for decision tree classification in data mining
Sharma, K. Venkatesh; Shewandagn, Behailu; Bhukya, Shankar Nayak
2017-07-01
The Data mining algorithms have become vital to researchers in science, engineering, medicine, business, search and security domains. In recent years, there has been a terrific raise in the size of the data being collected and analyzed. Classification is the main difficulty faced in data mining. In a number of the solutions developed for this problem, most accepted one is Decision Tree Classification (DTC) that gives high precision while handling very large amount of data. This paper presents VLSI implementation of flexible architecture for Decision Tree classification in data mining using c4.5 algorithm.
International Nuclear Information System (INIS)
Jones, W.F.; Byars, L.G.; Casey, M.E.
1988-01-01
A digital electronic architecture for parallel processing of the expectation maximization (EM) algorithm for Positron Emission tomography (PET) image reconstruction is proposed. Rapid (0.2 second) EM iterations on high resolution (256 x 256) images are supported. Arrays of two very large scale integration (VLSI) chips perform forward and back projection calculations. A description of the architecture is given, including data flow and partitioning relevant to EM and parallel processing. EM images shown are produced with software simulating the proposed hardware reconstruction algorithm. Projected cost of the system is estimated to be small in comparison to the cost of current PET scanners
Optimal Design of a Centrifugal Compressor Impeller Using Evolutionary Algorithms
Directory of Open Access Journals (Sweden)
Soo-Yong Cho
2012-01-01
Full Text Available An optimization study was conducted on a centrifugal compressor. Eight design variables were chosen from the control points for the Bezier curves which widely influenced the geometric variation; four design variables were selected to optimize the flow passage between the hub and the shroud, and other four design variables were used to improve the performance of the impeller blade. As an optimization algorithm, an artificial neural network (ANN was adopted. Initially, the design of experiments was applied to set up the initial data space of the ANN, which was improved during the optimization process using a genetic algorithm. If a result of the ANN reached a higher level, that result was re-calculated by computational fluid dynamics (CFD and was applied to develop a new ANN. The prediction difference between the ANN and CFD was consequently less than 1% after the 6th generation. Using this optimization technique, the computational time for the optimization was greatly reduced and the accuracy of the optimization algorithm was increased. The efficiency was improved by 1.4% without losing the pressure ratio, and Pareto-optimal solutions of the efficiency versus the pressure ratio were obtained through the 21st generation.
Optimized design of embedded DSP system hardware supporting complex algorithms
Li, Yanhua; Wang, Xiangjun; Zhou, Xinling
2003-09-01
The paper presents an optimized design method for a flexible and economical embedded DSP system that can implement complex processing algorithms as biometric recognition, real-time image processing, etc. It consists of a floating-point DSP, 512 Kbytes data RAM, 1 Mbytes FLASH program memory, a CPLD for achieving flexible logic control of input channel and a RS-485 transceiver for local network communication. Because of employing a high performance-price ratio DSP TMS320C6712 and a large FLASH in the design, this system permits loading and performing complex algorithms with little algorithm optimization and code reduction. The CPLD provides flexible logic control for the whole DSP board, especially in input channel, and allows convenient interface between different sensors and DSP system. The transceiver circuit can transfer data between DSP and host computer. In the paper, some key technologies are also introduced which make the whole system work efficiently. Because of the characters referred above, the hardware is a perfect flat for multi-channel data collection, image processing, and other signal processing with high performance and adaptability. The application section of this paper presents how this hardware is adapted for the biometric identification system with high identification precision. The result reveals that this hardware is easy to interface with a CMOS imager and is capable of carrying out complex biometric identification algorithms, which require real-time process.
Power gating of VLSI circuits using MEMS switches in low power applications
Shobak, Hosam
2011-12-01
Power dissipation poses a great challenge for VLSI designers. With the intense down-scaling of technology, the total power consumption of the chip is made up primarily of leakage power dissipation. This paper proposes combining a custom-designed MEMS switch to power gate VLSI circuits, such that leakage power is efficiently reduced while accounting for performance and reliability. The designed MEMS switch is characterized by an 0.1876 ? ON resistance and requires 4.5 V to switch. As a result of implementing this novel power gating technique, a standby leakage power reduction of 99% and energy savings of 33.3% are achieved. Finally the possible effects of surge currents and ground bounce noise are studied. These findings allow longer operation times for battery-operated systems characterized by long standby periods. © 2011 IEEE.
An exact algorithm for optimal MAE stack filter design.
Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior
2007-02-01
We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.
Logic hybrid simulation-optimization algorithm for distillation design
Caballero Suárez, José Antonio
2014-01-01
In this paper, we propose a novel algorithm for the rigorous design of distillation columns that integrates a process simulator in a generalized disjunctive programming formulation. The optimal distillation column, or column sequence, is obtained by selecting, for each column section, among a set of column sections with different number of theoretical trays. The selection of thermodynamic models, properties estimation etc., are all in the simulation environment. All the numerical issues relat...
Point DCT VLSI Architecture for Emerging HEVC Standard
Directory of Open Access Journals (Sweden)
Ashfaq Ahmed
2012-01-01
Full Text Available This work presents a flexible VLSI architecture to compute the -point DCT. Since HEVC supports different block sizes for the computation of the DCT, that is, 4×4 up to 32×32, the design of a flexible architecture to support them helps reducing the area overhead of hardware implementations. The hardware proposed in this work is partially folded to save area and to get speed for large video sequences sizes. The proposed architecture relies on the decomposition of the DCT matrices into sparse submatrices in order to reduce the multiplications. Finally, multiplications are completely eliminated using the lifting scheme. The proposed architecture sustains real-time processing of 1080P HD video codec running at 150 MHz.
VLSI-based video event triggering for image data compression
Williams, Glenn L.
1994-02-01
Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.
Carrasco, Manuel; Garde, Andres; Murillo, Pilar; Serrano, Luis
2005-06-01
In this paper a novel design and implementation of a VLSI Analogue Neural Net based on Multi-Layer Perceptron (MLP) with on-chip Back Propagation (BP) learning algorithm suitable for the resolution of classification problems is described. In order to implement a general and programmable analogue architecture, the design has been carried out in a hierarchical way. In this way the net has been divided in synapsis-blocks and neuron-blocks providing an easy method for the analysis. These blocks basically consist on simple cells, which are mainly, the activation functions (NAF), derivatives (DNAF), multipliers and weight update circuits. The analogue design is based on current-mode translinear techniques using MOS transistors working in the weak inversion region in order to reduce both the voltage supply and the power consumption. Moreover, with the purpose of minimizing the noise, offset and distortion of even order, the topologies are fully-differential and balanced. The circuit, named ANNE (Analogue Neural NEt), has been prototyped and characterized as a proof of concept on CMOS AMI-0.5A technology occupying a total area of 2.7mm2. The chip includes two versions of neural nets with on-chip BP learning algorithm, which are respectively a 2-1 and a 2-2-1 implementations. The proposed nets have been experimentally tested using supply voltages from 2.5V to 1.8V, which is suitable for single cell lithium-ion battery supply applications. Experimental results of both implementations included in ANNE exhibit a good performance on solving classification problems. These results have been compared with other proposed Analogue VLSI implementations of Neural Nets published in the literature demonstrating that our proposal is very efficient in terms of occupied area and power consumption.
The PBIL algorithm applied to a nuclear reactor design optimization
Energy Technology Data Exchange (ETDEWEB)
Machado, Marcelo D.; Medeiros, Jose A.C.C.; Lima, Alan M.M. de; Schirru, Roberto [Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ-RJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear. Lab. de Monitoracao de Processos]. E-mails: marcelo@lmp.ufrj.br; canedo@lmp.ufrj.br; alan@lmp.ufrj.br; schirru@lmp.ufrj.br
2007-07-01
The Population-Based Incremental Learning (PBIL) algorithm is a method that combines the mechanism of genetic algorithm with the simple competitive learning, creating an important tool to be used in the optimization of numeric functions and combinatory problems. PBIL works with a set of solutions to the problems, called population, whose objective is create a probability vector, containing real values in each position, that when used in a decoding procedure gives subjects that present the best solutions for the function to be optimized. In this work a new form of learning for algorithm PBIL is developed, having aimed at to reduce the necessary time for the optimization process. This new algorithm will be used in the nuclear reactor design optimization. The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment zone reactor, considering some restrictions. In this optimization is used the computational code HAMMER, and the results compared with other methods of optimization by artificial intelligence. (author)
The PBIL algorithm applied to a nuclear reactor design optimization
International Nuclear Information System (INIS)
Machado, Marcelo D.; Medeiros, Jose A.C.C.; Lima, Alan M.M. de; Schirru, Roberto
2007-01-01
The Population-Based Incremental Learning (PBIL) algorithm is a method that combines the mechanism of genetic algorithm with the simple competitive learning, creating an important tool to be used in the optimization of numeric functions and combinatory problems. PBIL works with a set of solutions to the problems, called population, whose objective is create a probability vector, containing real values in each position, that when used in a decoding procedure gives subjects that present the best solutions for the function to be optimized. In this work a new form of learning for algorithm PBIL is developed, having aimed at to reduce the necessary time for the optimization process. This new algorithm will be used in the nuclear reactor design optimization. The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment zone reactor, considering some restrictions. In this optimization is used the computational code HAMMER, and the results compared with other methods of optimization by artificial intelligence. (author)
Differential evolution and simulated annealing algorithms for mechanical systems design
Directory of Open Access Journals (Sweden)
H. Saruhan
2014-09-01
Full Text Available In this study, nature inspired algorithms – the Differential Evolution (DE and the Simulated Annealing (SA – are utilized to seek a global optimum solution for ball bearings link system assembly weight with constraints and mixed design variables. The Genetic Algorithm (GA and the Evolution Strategy (ES will be a reference for the examination and validation of the DE and the SA. The main purpose is to minimize the weight of an assembly system composed of a shaft and two ball bearings. Ball bearings link system is used extensively in many machinery applications. Among mechanical systems, designers pay great attention to the ball bearings link system because of its significant industrial importance. The problem is complex and a time consuming process due to mixed design variables and inequality constraints imposed on the objective function. The results showed that the DE and the SA performed and obtained convergence reliability on the global optimum solution. So the contribution of the DE and the SA application to the mechanical system design can be very useful in many real-world mechanical system design problems. Beside, the comparison confirms the effectiveness and the superiority of the DE over the others algorithms – the SA, the GA, and the ES – in terms of solution quality. The ball bearings link system assembly weight of 634,099 gr was obtained using the DE while 671,616 gr, 728213.8 gr, and 729445.5 gr were obtained using the SA, the ES, and the GA respectively.
An analog VLSI real time optical character recognition system based on a neural architecture
International Nuclear Information System (INIS)
Bo, G.; Caviglia, D.; Valle, M.
1999-01-01
In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system
An analog VLSI real time optical character recognition system based on a neural architecture
Energy Technology Data Exchange (ETDEWEB)
Bo, G.; Caviglia, D.; Valle, M. [Genoa Univ. (Italy). Dip. of Biophysical and Electronic Engineering
1999-03-01
In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system.
International Conference on VLSI, Communication, Advanced Devices, Signals & Systems and Networking
Shirur, Yasha; Prasad, Rekha
2013-01-01
This book is a collection of papers presented by renowned researchers, keynote speakers and academicians in the International Conference on VLSI, Communication, Analog Designs, Signals and Systems, and Networking (VCASAN-2013), organized by B.N.M. Institute of Technology, Bangalore, India during July 17-19, 2013. The book provides global trends in cutting-edge technologies in electronics and communication engineering. The content of the book is useful to engineers, researchers and academicians as well as industry professionals.
Optimal design of link systems using successive zooming genetic algorithm
Kwon, Young-Doo; Sohn, Chang-hyun; Kwon, Soon-Bum; Lim, Jae-gyoo
2009-07-01
Link-systems have been around for a long time and are still used to control motion in diverse applications such as automobiles, robots and industrial machinery. This study presents a procedure involving the use of a genetic algorithm for the optimal design of single four-bar link systems and a double four-bar link system used in diesel engine. We adopted the Successive Zooming Genetic Algorithm (SZGA), which has one of the most rapid convergence rates among global search algorithms. The results are verified by experiment and the Recurdyn dynamic motion analysis package. During the optimal design of single four-bar link systems, we found in the case of identical input/output (IO) angles that the initial and final configurations show certain symmetry. For the double link system, we introduced weighting factors for the multi-objective functions, which minimize the difference between output angles, providing balanced engine performance, as well as the difference between final output angle and the desired magnitudes of final output angle. We adopted a graphical method to select a proper ratio between the weighting factors.
Design of PID Controller Simulator based on Genetic Algorithm
Directory of Open Access Journals (Sweden)
Fahri VATANSEVER
2013-08-01
Full Text Available PID (Proportional Integral and Derivative controllers take an important place in the field of system controlling. Various methods such as Ziegler-Nichols, Cohen-Coon, Chien Hrones Reswick (CHR and Wang-Juang-Chan are available for the design of such controllers benefiting from the system time and frequency domain data. These controllers are in compliance with system properties under certain criteria suitable to the system. Genetic algorithms have become widely used in control system applications in parallel to the advances in the field of computer and artificial intelligence. In this study, PID controller designs have been carried out by means of classical methods and genetic algorithms and comparative results have been analyzed. For this purpose, a graphical user interface program which can be used for educational purpose has been developed. For the definite (entered transfer functions, the suitable P, PI and PID controller coefficients have calculated by both classical methods and genetic algorithms and many parameters and responses of the systems have been compared and presented numerically and graphically
OSPREY: protein design with ensembles, flexibility, and provable algorithms.
Gainza, Pablo; Roberts, Kyle E; Georgiev, Ivelin; Lilien, Ryan H; Keedy, Daniel A; Chen, Cheng-Yu; Reza, Faisal; Anderson, Amy C; Richardson, David C; Richardson, Jane S; Donald, Bruce R
2013-01-01
We have developed a suite of protein redesign algorithms that improves realistic in silico modeling of proteins. These algorithms are based on three characteristics that make them unique: (1) improved flexibility of the protein backbone, protein side-chains, and ligand to accurately capture the conformational changes that are induced by mutations to the protein sequence; (2) modeling of proteins and ligands as ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal protein design search, guaranteeing that the computational predictions are optimal with respect to the input model. Here, we illustrate the importance of these three characteristics. We then describe OSPREY, a protein redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental validation, in several biomedically relevant settings. We show in detail how OSPREY has been used to predict resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application. OSPREY is free and open source under a Lesser GPL license. The latest version is OSPREY 2.0. The program, user manual, and source code are available at www.cs.duke.edu/donaldlab/software.php. osprey@cs.duke.edu. Copyright © 2013 Elsevier Inc. All rights reserved.
Robust Bioinformatics Recognition with VLSI Biochip Microsystem
Lue, Jaw-Chyng L.; Fang, Wai-Chi
2006-01-01
A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.
Genetic algorithms for optimal design and control of adaptive structures
Ribeiro, R; Dias-Rodrigues, J; Vaz, M
2000-01-01
Future High Energy Physics experiments require the use of light and stable structures to support their most precise radiation detection elements. These large structures must be light, highly stable, stiff and radiation tolerant in an environment where external vibrations, high radiation levels, material aging, temperature and humidity gradients are not negligible. Unforeseen factors and the unknown result of the coupling of environmental conditions, together with external vibrations, may affect the position stability of the detectors and their support structures compromising their physics performance. Careful optimization of static and dynamic behavior must be an essential part of the engineering design. Genetic Algorithms ( GA) belong to the group of probabilistic algorithms, combining elements of direct and stochastic search. They are more robust than existing directed search methods with the advantage of maintaining a population of potential solutions. There is a class of optimization problems for which Ge...
Gravitation search algorithm: Application to the optimal IIR filter design
Directory of Open Access Journals (Sweden)
Suman Kumar Saha
2014-01-01
Full Text Available This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA for the design of 8th order Infinite Impulse Response (IIR, low pass (LP, high pass (HP, band pass (BP and band stop (BS filters considering various non-linear characteristics of the filter design problems. This paper also adopts a novel fitness function in order to improve the stop band attenuation to a great extent. In GSA, law of gravity and mass interactions among different particles are adopted for handling the non-linear IIR filter design optimization problem. In this optimization technique, searcher agents are the collection of masses and interactions among them are governed by the Newtonian gravity and the laws of motion. The performances of the GSA based IIR filter designs have proven to be superior as compared to those obtained by real coded genetic algorithm (RGA and standard Particle Swarm Optimization (PSO. Extensive simulation results affirm that the proposed approach using GSA outperforms over its counterparts not only in terms of quality output, i.e., sharpness at cut-off, smaller pass band ripple, higher stop band attenuation, but also the fastest convergence speed with assured stability.
Energy Technology Data Exchange (ETDEWEB)
Chiang, Patrick [Oregon State Univ., Corvallis, OR (United States)
2014-01-31
The research goal of this CAREER proposal is to develop energy-efficient, VLSI interconnect circuits and systems that will facilitate future massively-parallel, high-performance computing. Extreme-scale computing will exhibit massive parallelism on multiple vertical levels, from thou sands of computational units on a single processor to thousands of processors in a single data center. Unfortunately, the energy required to communicate between these units at every level (on chip, off-chip, off-rack) will be the critical limitation to energy efficiency. Therefore, the PI's career goal is to become a leading researcher in the design of energy-efficient VLSI interconnect for future computing systems.
Design Principles and Algorithms for Air Traffic Arrival Scheduling
Erzberger, Heinz; Itoh, Eri
2014-01-01
This report presents design principles and algorithms for building a real-time scheduler of arrival aircraft based on a first-come-first-served (FCFS) scheduling protocol. The algorithms provide the conceptual and computational foundation for the Traffic Management Advisor (TMA) of the Center/terminal radar approach control facilities (TRACON) automation system, which comprises a set of decision support tools for managing arrival traffic at major airports in the United States. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high-altitude airspace far away from the airport and low-altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time. This report is a revision of an earlier paper first presented as part of an Advisory Group for Aerospace Research and Development (AGARD) lecture series in September 1995. The authors, during vigorous discussions over the details of this paper, felt it was important to the air-trafficmanagement (ATM) community to revise and extend the original 1995 paper, providing more detail and clarity and thereby allowing future researchers to understand this foundational work as the basis for the TMA's scheduling algorithms.
Schema Design and Normalization Algorithm for XML Databases Model
Directory of Open Access Journals (Sweden)
Samir Abou El-Seoud
2009-06-01
Full Text Available In this paper we study the problem of schema design and normalization in XML databases model. We show that, like relational databases, XML documents may contain redundant information, and this redundancy may cause update anomalies. Furthermore, such problems are caused by certain functional dependencies among paths in the document. Based on our research works, in which we presented the functional dependencies and normal forms of XML Schema, we present the decomposition algorithm for converting any XML Schema into normalized one, that satisfies X-BCNF.
Social Welfare in Algorithmic Mechanism Design Without Money
DEFF Research Database (Denmark)
Filos-Ratsikas, Aris
Social choice theory is concerned with collective decision making under different, possibly contrasting opinions and has been part of the core of society since ancient times. The goal is to implement some socially desired objective while at the same time accounting for the fact that people will act...... strategically, in order to manipulate the outcomes in their favor. In this thesis, we consider the well-known objective of social welfare, i.e. the sum of individual utilities as the social objective and following the agenda of algorithmic mechanism design, we study how well our objectives can be approximated...
Design principles and algorithms for automated air traffic management
Erzberger, Heinz
1995-01-01
This paper presents design principles and algorithm for building a real time scheduler. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high altitude airspace far from the airport and low altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time.
Wavelength-encoded OCDMA system using opto-VLSI processors.
Aljada, Muhsen; Alameh, Kamal
2007-07-01
We propose and experimentally demonstrate a 2.5 Gbits/sper user wavelength-encoded optical code-division multiple-access encoder-decoder structure based on opto-VLSI processing. Each encoder and decoder is constructed using a single 1D opto-very-large-scale-integrated (VLSI) processor in conjunction with a fiber Bragg grating (FBG) array of different Bragg wavelengths. The FBG array spectrally and temporally slices the broadband input pulse into several components and the opto-VLSI processor generates codewords using digital phase holograms. System performance is measured in terms of the autocorrelation and cross-correlation functions as well as the eye diagram.
Wavelength-encoded OCDMA system using opto-VLSI processors
Aljada, Muhsen; Alameh, Kamal
2007-07-01
We propose and experimentally demonstrate a 2.5 Gbits/sper user wavelength-encoded optical code-division multiple-access encoder-decoder structure based on opto-VLSI processing. Each encoder and decoder is constructed using a single 1D opto-very-large-scale-integrated (VLSI) processor in conjunction with a fiber Bragg grating (FBG) array of different Bragg wavelengths. The FBG array spectrally and temporally slices the broadband input pulse into several components and the opto-VLSI processor generates codewords using digital phase holograms. System performance is measured in terms of the autocorrelation and cross-correlation functions as well as the eye diagram.
MICRONEEDLE STRUCTURE DESIGN AND OPTIMIZATION USING GENETIC ALGORITHM
Directory of Open Access Journals (Sweden)
N. A. ISMAIL
2015-07-01
Full Text Available This paper presents a Genetic Algorithm (GA based microneedle design and analysis. GA is an evolutionary optimization technique that mimics the natural biological evolution. The design of microneedle structure considers the shape of microneedle, material used, size of the array, the base of microneedle, the lumen base, the height of microneedle, the height of the lumen, and the height of the drug container or reservoir. The GA is executed in conjunction with ANSYS simulation system to assess the design specifications. The GA uses three operators which are reproduction, crossover and mutation to manipulate the genetic composition of the population. In this research, the microneedle is designed to meet a number of significant specifications such as nodal displacement, strain energy, equivalent stress and flow rate of the fluid / drug that flow through its channel / lumen. A comparison study is conducted to investigate the design of microneedle structure with and without the implementation of GA model. The results showed that GA is able to optimize the design parameters of microneedle and is capable to achieve the required specifications with better performance.
A Sequential Circuit-Based IP Watermarking Algorithm for Multiple Scan Chains in Design-for-Test
Directory of Open Access Journals (Sweden)
C. Wu
2011-06-01
Full Text Available In Very Large Scale Integrated Circuits (VLSI design, the existing Design-for-Test(DFT based watermarking techniques usually insert watermark through reordering scan cells, which causes large resource overhead, low security and coverage rate of watermark detection. A novel scheme was proposed to watermark multiple scan chains in DFT for solving the problems. The proposed scheme adopts DFT scan test model of VLSI design, and uses a Linear Feedback Shift Register (LFSR for pseudo random test vector generation. All of the test vectors are shifted in scan input for the construction of multiple scan chains with minimum correlation. Specific registers in multiple scan chains will be changed by the watermark circuit for watermarking the design. The watermark can be effectively detected without interference with normal function of the circuit, even after the chip is packaged. The experimental results on several ISCAS benchmarks show that the proposed scheme has lower resource overhead, probability of coincidence and higher coverage rate of watermark detection by comparing with the existing methods.
Reactor controller design using genetic algorithm with simulated annealing
International Nuclear Information System (INIS)
Willjuice Iruthyarajan, M.
2012-01-01
Many reactor control design work, specifically the problem of synthesis and optimization of reactor networks involving the classical reaction schemes was studied, considering a superstructure formed by a CSTR and a PFR and their possible arrangements. A genetic algorithm was proposed, together with a systematic procedure. Two case studies were solved with the proposed systematic. Both of them present similar results than the published in the literature. The first case studied was the Trambouze reaction scheme. Although selectivity values are smaller then the values published in the referred papers, the reactors system combined volume is always minor them the other ones. The second case studied was the Van de Vusse reaction scheme. In this case, the obtained value for the total volume is always minor then the considered papers. One can conclude that when compared with the other works presented in the literature results are compatible and very interesting. The developed algorithms can be used as a good alternative for reactor networks design and optimization problem
Reduced scale PWR passive safety system designing by genetic algorithms
International Nuclear Information System (INIS)
Cunha, Joao J. da; Alvim, Antonio Carlos M.; Lapa, Celso Marcelo Franklin
2007-01-01
This paper presents the concept of 'Design by Genetic Algorithms (DbyGA)', applied to a new reduced scale system problem. The design problem of a passive thermal-hydraulic safety system, considering dimensional and operational constraints, has been solved. Taking into account the passive safety characteristics of the last nuclear reactor generation, a PWR core under natural circulation is used in order to demonstrate the methodology applicability. The results revealed that some solutions (reduced scale system DbyGA) are capable of reproducing, both accurately and simultaneously, much of the physical phenomena that occur in real scale and operating conditions. However, some aspects, revealed by studies of cases, pointed important possibilities to DbyGA methodological performance improvement
Numerical methods design, analysis, and computer implementation of algorithms
Greenbaum, Anne
2012-01-01
Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, and fractals. Filled with appealing examples that will motivate students, the textbook considers modern application areas, such as information retrieval and animation, and classical topics from physics and engineering. Exercises use MATLAB and promote understanding of computational results. The book gives instructors the flexibility to emphasize different aspects--design, analysis, or computer implementation--of numerical algorithms, depending on the background and interests of students. Designed for upper-division undergraduates in mathematics or computer science classes, the textbook assumes that students have prior knowledge of linear algebra and calculus, although these topics are reviewed in the text. Short discussions of the history of numerical methods are interspersed throughout the chapters. The book a...
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
Long, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris
2000-01-01
Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Directory of Open Access Journals (Sweden)
Nathan eGould
2014-10-01
Full Text Available Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de-novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Energy Technology Data Exchange (ETDEWEB)
Gould, Nathan [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States); Hendy, Oliver [Department of Biology, The College of New Jersey, Ewing, NJ (United States); Papamichail, Dimitris, E-mail: papamicd@tcnj.edu [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States)
2014-10-06
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
Computational Tools and Algorithms for Designing Customized Synthetic Genes
International Nuclear Information System (INIS)
Gould, Nathan; Hendy, Oliver; Papamichail, Dimitris
2014-01-01
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
Natural selection and algorithmic design of mRNA.
Cohen, Barry; Skiena, Steven
2003-01-01
Messenger RNA (mRNA) sequences serve as templates for proteins according to the triplet code, in which each of the 4(3) = 64 different codons (sequences of three consecutive nucleotide bases) in RNA either terminate transcription or map to one of the 20 different amino acids (or residues) which build up proteins. Because there are more codons than residues, there is inherent redundancy in the coding. Certain residues (e.g., tryptophan) have only a single corresponding codon, while other residues (e.g., arginine) have as many as six corresponding codons. This freedom implies that the number of possible RNA sequences coding for a given protein grows exponentially in the length of the protein. Thus nature has wide latitude to select among mRNA sequences which are informationally equivalent, but structurally and energetically divergent. In this paper, we explore how nature takes advantage of this freedom and how to algorithmically design structures more energetically favorable than have been built through natural selection. In particular: (1) Natural Selection--we perform the first large-scale computational experiment comparing the stability of mRNA sequences from a variety of organisms to random synonymous sequences which respect the codon preferences of the organism. This experiment was conducted on over 27,000 sequences from 34 microbial species with 36 genomic structures. We provide evidence that in all genomic structures highly stable sequences are disproportionately abundant, and in 19 of 36 cases highly unstable sequences are disproportionately abundant. This suggests that the stability of mRNA sequences is subject to natural selection. (2) Artificial Selection--motivated by these biological results, we examine the algorithmic problem of designing the most stable and unstable mRNA sequences which code for a target protein. We give a polynomial-time dynamic programming solution to the most stable sequence problem (MSSP), which is asymptotically no more complex
A Compact VLSI System for Bio-Inspired Visual Motion Estimation.
Shi, Cong; Luo, Gang
2018-04-01
This paper proposes a bio-inspired visual motion estimation algorithm based on motion energy, along with its compact very-large-scale integration (VLSI) architecture using low-cost embedded systems. The algorithm mimics motion perception functions of retina, V1, and MT neurons in a primate visual system. It involves operations of ternary edge extraction, spatiotemporal filtering, motion energy extraction, and velocity integration. Moreover, we propose the concept of confidence map to indicate the reliability of estimation results on each probing location. Our algorithm involves only additions and multiplications during runtime, which is suitable for low-cost hardware implementation. The proposed VLSI architecture employs multiple (frame, pixel, and operation) levels of pipeline and massively parallel processing arrays to boost the system performance. The array unit circuits are optimized to minimize hardware resource consumption. We have prototyped the proposed architecture on a low-cost field-programmable gate array platform (Zynq 7020) running at 53-MHz clock frequency. It achieved 30-frame/s real-time performance for velocity estimation on 160 × 120 probing locations. A comprehensive evaluation experiment showed that the estimated velocity by our prototype has relatively small errors (average endpoint error < 0.5 pixel and angular error < 10°) for most motion cases.
Czech Academy of Sciences Publication Activity Database
Šůcha, P.; Hanzálek, Z.; Heřmánek, Antonín; Schier, Jan
2007-01-01
Roč. 46, č. 1 (2007), s. 35-53 ISSN 0922-5773 R&D Projects: GA AV ČR(CZ) 1ET300750402; GA MŠk(CZ) 1M0567; GA MPO(CZ) FD-K3/082 Institutional research plan: CEZ:AV0Z10750506 Keywords : high-level synthesis * cyclic scheduling * iterative algorithms * imperfectly nested loops * integer linear programming * FPGA * VLSI design * blind equalization * implementation Subject RIV: BA - General Mathematics Impact factor: 0.449, year: 2007 http://www.springerlink.com/content/t217kg0822538014/fulltext.pdf
A Design of a Hybrid Non-Linear Control Algorithm
Directory of Open Access Journals (Sweden)
Farinaz Behrooz
2017-11-01
Full Text Available One of the high energy consuming devices in the buildings is the air-conditioning system. Designing a proper controller to consider the thermal comfort and simultaneously control the energy usage of the device will impact on the system energy efficiency and its performance. The aim of this study was to design a Multiple-Input and Multiple-Output (MIMO, non-linear, and intelligent controller on direct expansion air-conditioning system The control algorithm uses the Fuzzy Cognitive Map method as a main controller and the Generalized Predictive Control method is used for assigning the initial weights of the main controller. The results of the proposed controller shows that the controller was successfully designed and works in set point tracking and under disturbance rejection tests. The obtained results of the Generalized Predictive Control-Fuzzy Cognitive Map controller are compared with the previous MIMO Linear Quadratic Gaussian control design on the same direct expansion air-conditioning system under the same conditions. The comparative results indicate energy savings would be achieved with the proposed controller with long-term usage. Energy efficiency and thermal comfort conditions are achieved by the proposed controller.
Memory Based Machine Intelligence Techniques in VLSI hardware
James, Alex Pappachen
2012-01-01
We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...
ORGANIZATION OF GRAPHIC INFORMATION FOR VIEWING THE MULTILAYER VLSI TOPOLOGY
Directory of Open Access Journals (Sweden)
V. I. Romanov
2016-01-01
Full Text Available One of the possible ways to reorganize of graphical information describing the set of topology layers of modern VLSI. The method is directed on the use in the conditions of the bounded size of video card memory. An additional effect, providing high performance of forming multi- image layout a multi-layer topology of modern VLSI, is achieved by preloading the required texture by means of auxiliary background process.
Algorithms and Array Design Criteria for Robust Imaging in Interferometry
Kurien, Binoy George
Optical interferometry is a technique for obtaining high-resolution imagery of a distant target by interfering light from multiple telescopes. Image restoration from interferometric measurements poses a unique set of challenges. The first challenge is that the measurement set provides only a sparse-sampling of the object's Fourier Transform and hence image formation from these measurements is an inherently ill-posed inverse problem. Secondly, atmospheric turbulence causes severe distortion of the phase of the Fourier samples. We develop array design conditions for unique Fourier phase recovery, as well as a comprehensive algorithmic framework based on the notion of redundant-spaced-calibration (RSC), which together achieve reliable image reconstruction in spite of these challenges. Within this framework, we see that classical interferometric observables such as the bispectrum and closure phase can limit sensitivity, and that generalized notions of these observables can improve both theoretical and empirical performance. Our framework leverages techniques from lattice theory to resolve integer phase ambiguities in the interferometric phase measurements, and from graph theory, to select a reliable set of generalized observables. We analyze the expected shot-noise-limited performance of our algorithm for both pairwise and Fizeau interferometric architectures and corroborate this analysis with simulation results. We apply techniques from the field of compressed sensing to perform image reconstruction from the estimates of the object's Fourier coefficients. The end result is a comprehensive strategy to achieve well-posed and easily-predictable reconstruction performance in optical interferometry.
Designing shields for KeV photons with genetic algorithms
International Nuclear Information System (INIS)
Asbury, Stephen; Holloway, James P.
2011-01-01
Shielding of x-ray sources and low energy gamma rays is often accomplished with lead aprons, comprising a thin layer (0.5 mm to 1 mm) of lead or similar high-Z material. In previous work the authors used Genetic Algorithms to explore the design of a shadow shield for space applications. Now those techniques have been applied to the problem of shielding humans from low energy gamma radiation. This paper uses a simple geometry to explore layering various materials as a method to reduce mass and dose for thin gamma shields. The genetic algorithms discover layers of materials with various Z is in fact more effective than an equivalent mass of Pb alone for lower energy gammas, but as the incident radiation energy increases the efficacy of such layering diminishes. The utility of varying Z for lower energy gammas is in part due to their complementary K-edges, where one material compensates for the transmission that would occur just below the K-edge in another material. (author)
District Heating Network Design and Configuration Optimization with Genetic Algorithm
DEFF Research Database (Denmark)
Li, Hongwei; Svendsen, Svend
2013-01-01
In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer...... and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding...... and it is optimized in terms of the net present cost. The optimization results indicates that the optimal DH network configuration is determined by multiple factors such as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding the pressure and temperature...
District Heating Network Design and Configuration Optimization with Genetic Algorithm
DEFF Research Database (Denmark)
Li, Hongwei; Svendsen, Svend
2011-01-01
In this paper, the configuration of a district heating (DH) network which connects from the heating plant to the end users was optimized with emphasizing the network thermal performance. Each end user in the network represents a building block. The locations of the building blocks are fixed while...... the heating plant location is allowed to vary. The connection between the heat generation plant and the end users can be represented with mixed integer and the pipe friction and heat loss formulations are non-linear. In order to find the optimal DH distribution pipeline configuration, the genetic algorithm...... by multi factors as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding pressure and temperature limitation, as well as the corresponding network heat loss....
Performance indices and evaluation of algorithms in building energy efficient design optimization
International Nuclear Information System (INIS)
Si, Binghui; Tian, Zhichao; Jin, Xing; Zhou, Xin; Tang, Peng; Shi, Xing
2016-01-01
Building energy efficient design optimization is an emerging technique that is increasingly being used to design buildings with better overall performance and a particular emphasis on energy efficiency. To achieve building energy efficient design optimization, algorithms are vital to generate new designs and thus drive the design optimization process. Therefore, the performance of algorithms is crucial to achieving effective energy efficient design techniques. This study evaluates algorithms used for building energy efficient design optimization. A set of performance indices, namely, stability, robustness, validity, speed, coverage, and locality, is proposed to evaluate the overall performance of algorithms. A benchmark building and a design optimization problem are also developed. Hooke–Jeeves algorithm, Multi-Objective Genetic Algorithm II, and Multi-Objective Particle Swarm Optimization algorithm are evaluated by using the proposed performance indices and benchmark design problem. Results indicate that no algorithm performs best in all six areas. Therefore, when facing an energy efficient design problem, the algorithm must be carefully selected based on the nature of the problem and the performance indices that matter the most. - Highlights: • Six indices of algorithm performance in building energy optimization are developed. • For each index, its concept is defined and the calculation formulas are proposed. • A benchmark building and benchmark energy efficient design problem are proposed. • The performance of three selected algorithms are evaluated.
Energy-aware system design algorithms and architectures
Kyung, Chong-Min
2011-01-01
Power consumption becomes the most important design goal in a wide range of electronic systems. There are two driving forces towards this trend: continuing device scaling and ever increasing demand of higher computing power. First, device scaling continues to satisfy Moore’s law via a conventional way of scaling (More Moore) and a new way of exploiting the vertical integration (More than Moore). Second, mobile and IT convergence requires more computing power on the silicon chip than ever. Cell phones are now evolving towards mobile PC. PCs and data centers are becoming commodities in house and a must in industry. Both supply enabled by device scaling and demand triggered by the convergence trend realize more computation on chip (via multi-core, integration of diverse functionalities on mobile SoCs, etc.) and finally more power consumption incurring power-related issues and constraints. Energy-Aware System Design: Algorithms and Architectures provides state-of-the-art ideas for low power design methods from ...
Design optimization of space launch vehicles using a genetic algorithm
Bayley, Douglas James
The United States Air Force (USAF) continues to have a need for assured access to space. In addition to flexible and responsive spacelift, a reduction in the cost per launch of space launch vehicles is also desirable. For this purpose, an investigation of the design optimization of space launch vehicles has been conducted. Using a suite of custom codes, the performance aspects of an entire space launch vehicle were analyzed. A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost. The other goals of the design optimization included obtaining the proper altitude and velocity to achieve a low-Earth orbit. Specific mission parameters that are particular to USAF space endeavors were specified at the start of the design optimization process. Solid propellant motors, liquid fueled rockets, and air-launched systems in various configurations provided the propulsion systems for two, three and four-stage launch vehicles. Mass properties models, an aerodynamics model, and a six-degree-of-freedom (6DOF) flight dynamics simulator were all used to model the system. The results show the feasibility of this method in designing launch vehicles that meet mission requirements. Comparisons to existing real world systems provide the validation for the physical system models. However, the ability to obtain a truly minimized cost was elusive. The cost model uses an industry standard approach, however, validation of this portion of the model was challenging due to the proprietary nature of cost figures and due to the dependence of many existing systems on surplus hardware.
Parameterized Algorithms for Survivable Network Design with Uniform Demands
DEFF Research Database (Denmark)
Bang-Jensen, Jørgen; Klinkby Knudsen, Kristine Vitting; Saurabh, Saket
2018-01-01
problem in combinatorial optimization that captures numerous well-studied problems in graph theory and graph algorithms. Consequently, there is a long line of research into exact-polynomial time algorithms as well as approximation algorithms for various restrictions of this problem. An important...... that SNDP is W[1]-hard for both arc and vertex connectivity versions on digraphs. The core of our algorithms is composed of new combinatorial results on connectivity in digraphs and undirected graphs....
Performance-based seismic design of steel frames utilizing colliding bodies algorithm.
Veladi, H
2014-01-01
A pushover analysis method based on semirigid connection concept is developed and the colliding bodies optimization algorithm is employed to find optimum seismic design of frame structures. Two numerical examples from the literature are studied. The results of the new algorithm are compared to the conventional design methods to show the power or weakness of the algorithm.
VLSI Implementation of a Fixed-Complexity Soft-Output MIMO Detector for High-Speed Wireless
Directory of Open Access Journals (Sweden)
Di Wu
2010-01-01
Full Text Available This paper presents a low-complexity MIMO symbol detector with close-Maximum a posteriori performance for the emerging multiantenna enhanced high-speed wireless communications. The VLSI implementation is based on a novel MIMO detection algorithm called Modified Fixed-Complexity Soft-Output (MFCSO detection, which achieves a good trade-off between performance and implementation cost compared to the referenced prior art. By including a microcode-controlled channel preprocessing unit and a pipelined detection unit, it is flexible enough to cover several different standards and transmission schemes. The flexibility allows adaptive detection to minimize power consumption without degradation in throughput. The VLSI implementation of the detector is presented to show that real-time MIMO symbol detection of 20 MHz bandwidth 3GPP LTE and 10 MHz WiMAX downlink physical channel is achievable at reasonable silicon cost.
Adaptive symbiotic organisms search (SOS algorithm for structural design optimization
Directory of Open Access Journals (Sweden)
Ghanshyam G. Tejani
2016-07-01
Full Text Available The symbiotic organisms search (SOS algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.
Directory of Open Access Journals (Sweden)
Hyo Seon Park
2014-01-01
Full Text Available Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.
Designing optimal degradation tests via multi-objective genetic algorithms
International Nuclear Information System (INIS)
Marseguerra, Marzio; Zio, Enrico; Cipollone, Maurizio
2003-01-01
The experimental determination of the failure time probability distribution of highly reliable components, such as those used in nuclear and aerospace applications, is intrinsically difficult due to the lack, or scarce significance, of failure data which can be collected during the relatively short test periods. A possibility to overcome this difficulty is to resort to the so-called degradation tests, in which measurements of components' degradation are used to infer the failure time distribution. To design such tests, parameters like the number of tests to be run, their frequency and duration, must be set so as to obtain an accurate estimate of the distribution statistics, under the existing limitations of budget. The optimisation problem which results is a non-linear one. In this work, we propose a method, based on multi-objective genetic algorithms for determining the values of the test parameters which optimise both the accuracy in the estimate of the failure time distribution percentiles and the testing costs. The method has been validated on a degradation model of literature
Designing and implementing of improved cryptographic algorithm using modular arithmetic theory
Directory of Open Access Journals (Sweden)
Maryam Kamarzarrin
2015-05-01
Full Text Available Maintaining the privacy and security of people information are two most important principles of electronic health plan. One of the methods of creating privacy and securing of information is using Public key cryptography system. In this paper, we compare two algorithms, Common And Fast Exponentiation algorithms, for enhancing the efficiency of public key cryptography. We express that a designed system by Fast Exponentiation Algorithm has high speed and performance but low power consumption and space occupied compared with Common Exponentiation algorithm. Although designed systems by Common Exponentiation algorithm have slower speed and lower performance, designing by this algorithm has less complexity, and easier designing compared with Fast Exponentiation algorithm. In this paper, we will try to examine and compare two different methods of exponentiation, also observe performance Impact of these two approaches in the form of hardware with VHDL language on FPGA.
Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design
Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.
2014-01-01
In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057
Monolithic active pixel sensors (MAPS) in a VLSI CMOS technology
Turchetta, R; Manolopoulos, S; Tyndel, M; Allport, P P; Bates, R; O'Shea, V; Hall, G; Raymond, M
2003-01-01
Monolithic Active Pixel Sensors (MAPS) designed in a standard VLSI CMOS technology have recently been proposed as a compact pixel detector for the detection of high-energy charged particle in vertex/tracking applications. MAPS, also named CMOS sensors, are already extensively used in visible light applications. With respect to other competing imaging technologies, CMOS sensors have several potential advantages in terms of low cost, low power, lower noise at higher speed, random access of pixels which allows windowing of region of interest, ability to integrate several functions on the same chip. This brings altogether to the concept of 'camera-on-a-chip'. In this paper, we review the use of CMOS sensors for particle physics and we analyse their performances in term of the efficiency (fill factor), signal generation, noise, readout speed and sensor area. In most of high-energy physics applications, data reduction is needed in the sensor at an early stage of the data processing before transfer of the data to ta...
Energy Technology Data Exchange (ETDEWEB)
Pereshenkov, V S [MIFI, Moscow, (Russian Federation); Shishianu, F S; Rusanovskij, V I [S. Lazo KPI, Chisinau, (Moldova, Republic of)
1992-01-01
The paper presents the method used and the experimental results obtained for 8-bit microprocessor irradiated with [gamma]-rays and neutrons. The correlation between the electrical and technological parameters with the irradiation ones is revealed. The influence of leakage current between devices incorporated in VLSI circuits was studied. The obtained results create the possibility to determine the technological parameters necessary for designing the circuit able to work at predetermined doses. The necessary substrate doping concentration for isolation which eliminates the leakage current between devices prevents the VLSI circuit break down was determined. (Author).
Huynh, Trong-Phuoc; Hwang, Chao-Lung; Yang, Shu-Ti
2017-12-01
This experimental study evaluated the performance of normal ordinary Portland cement (OPC) concrete and high-performance concrete (HPC) that were designed by the conventional method (ACI) and densified mixture design algorithm (DMDA) method, respectively. Engineering properties and durability performance of both the OPC and HPC samples were studied using the tests of workability, compressive strength, water absorption, ultrasonic pulse velocity, and electrical surface resistivity. Test results show that the HPC performed good fresh property and further showed better performance in terms of strength and durability as compared to the OPC.
Application of mapping crossover genetic algorithm in nuclear power equipment optimization design
International Nuclear Information System (INIS)
Li Guijiang; Yan Changqi; Wang Jianjun; Liu Chengyang
2013-01-01
Genetic algorithm (GA) has been widely applied in nuclear engineering. An improved method, named the mapping crossover genetic algorithm (MCGA), was developed aiming at improving the shortcomings of traditional genetic algorithm (TGA). The optimal results of benchmark problems show that MCGA has better optimizing performance than TGA. MCGA was applied to the reactor coolant pump optimization design. (authors)
An engineering methodology for implementing and testing VLSI (Very Large Scale Integrated) circuits
Corliss, Walter F., II
1989-03-01
The engineering methodology for producing a fully tested VLSI chip from a design layout is presented. A 16-bit correlator, NPS CORN88, that was previously designed, was used as a vehicle to demonstrate this methodology. The study of the design and simulation tools, MAGIC and MOSSIM II, was the focus of the design and validation process. The design was then implemented and the chip was fabricated by MOSIS. This fabricated chip was then used to develop a testing methodology for using the digital test facilities at NPS. NPS CORN88 was the first full custom VLSI chip, designed at NPS, to be tested with the NPS digital analysis system, Tektronix DAS 9100 series tester. The capabilities and limitations of these test facilities are examined. NPS CORN88 test results are included to demonstrate the capabilities of the digital test system. A translator, MOS2DAS, was developed to convert the MOSSIM II simulation program to the input files required by the DAS 9100 device verification software, 91DVS. Finally, a tutorial for using the digital test facilities, including the DAS 9100 and associated support equipments, is included as an appendix.
Lapidoth, Gideon D; Baran, Dror; Pszolla, Gabriele M; Norn, Christoffer; Alon, Assaf; Tyka, Michael D; Fleishman, Sarel J
2015-08-01
Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function--essential to exert control over all polypeptide degrees of freedom--remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in five cases interface sequence identity is above 30%, and in four of those the backbone conformation at the core of the antibody binding surface is within 1 Å root-mean square deviation from the natural antibodies. Designs recapitulate polar interaction networks observed in natural complexes, and amino acid sidechain rigidity at the designed binding surface, which is likely important for affinity and specificity, is high compared to previous design studies. In designed anti-lysozyme antibodies, complementarity-determining regions (CDRs) at the periphery of the interface, such as L1 and H2, show greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, potentially enhancing affinity and specificity. © 2015 Wiley Periodicals, Inc.
The effects of advanced digital signal processing concepts on VLSIC/VHSIC design
Jankowski, C.
Implementations of sophisticated mathematical techniques in advanced digital signal processors can significantly improve performance. Future VLSI and VHSI circuit designs must include the practical realization of these algorithms. A structured design approach is described and illustrated with examples from a RNS FIR filter processor development project. The CAE hardware and software required to support tasks of this complexity are also discussed. An EWS is recommended for controlling essential functions such as logic optimization, simulation and verification. The total IC design system is illustrated with the implementation of a new high performance algorithm for computing complex magnitude.
Energy Technology Data Exchange (ETDEWEB)
Rubat Du Merac, C; Jutier, P; Laurent, J; Courtois, B
1983-07-01
This paper describes some aspects of specifying, designing and evaluating a specialized machine, Romuald, for the capture, coding, and processing of video and scanning electron microscope (SEM) pictures. First the authors present the functional organization of the process unit of romuald and its hardware, giving details of its behaviour. Then they study the capture and display unit which, thanks to its flexibility, enables SEM images coding. Finally, they describe an application which is now being developed in their laboratory: testing VLSI circuits with new methods: sem+voltage contrast and image processing. 15 references.
Techniques for Computing the DFT Using the Residue Fermat Number Systems and VLSI
Truong, T. K.; Chang, J. J.; Hsu, I. S.; Pei, D. Y.; Reed, I. S.
1985-01-01
The integer complex multiplier and adder over the direct sum of two copies of a finite field is specialized to the direct sum of the rings of integers modulo Fermat numbers. Such multiplications and additions can be used in the implementation of a discrete Fourier transform (DFT) of a sequence of complex numbers. The advantage of the present approach is that the number of multiplications needed for the DFT can be reduced substantially over the previous approach. The architectural designs using this approach are regular, simple, expandable and, therefore, naturally suitable for VLSI implementation.
Report on dynamic speed harmonization and queue warning algorithm design.
2014-02-01
This report provides a detailed description of the algorithms that will be used to generate harmonized recommended speeds : and queue warning information in the proposed Intelligent Network Flow Optimization (INFLO) prototype. This document : describ...
Design and simulation of airport congestion control algorithms
Simaiakis, Ioannis; Balakrishnan, Hamsa
2014-01-01
This paper proposes a stochastic model of runway departures and a dynamic programming algorithm for their control at congested airports. Using a multi-variable state description that includes the capacity forecast, the runway system is modeled as a semi-Markov process. The paper then introduces a queuing system for modeling the controlled departure process that enables the efficient calculation of optimal pushback policies using decomposition techniques. The developed algorithm is simulated a...
Machine Learning in Production Systems Design Using Genetic Algorithms
Abu Qudeiri Jaber; Yamamoto Hidehiko Rizauddin Ramli
2008-01-01
To create a solution for a specific problem in machine learning, the solution is constructed from the data or by use a search method. Genetic algorithms are a model of machine learning that can be used to find nearest optimal solution. While the great advantage of genetic algorithms is the fact that they find a solution through evolution, this is also the biggest disadvantage. Evolution is inductive, in nature life does not evolve towards a good solution but it evolves aw...
Designing machines for lattice physics and algorithm investigation
International Nuclear Information System (INIS)
Fischler, M.; Atac, R.; Cook, A.
1989-10-01
Special-purpose computers are appropriate tools for the study of lattice gauge theory. While these machines deliver considerable processing power, it is also important to be able to program complex physics ideas and investigate algorithms on them. We examine features that facilitate coding of physics problems, and flexibility in algorithms. Appropriate balances among power, memory, communications and I/O capabilities are presented. 10 refs
DESIGN AND EXAMINATION OF ALGORITHMS FOR SOLVING THE KNAPSACK PROBLEM
Directory of Open Access Journals (Sweden)
S. Kantsedal
2015-07-01
Full Text Available The use of methods of branches and boundaries as well as the methods of dynamic programming at solving the problem of «knapsack» is grounded. The main concepts are expounded. The methods and algorithms development for solving the above specified problem are described. Recommendations on practical application of constructed algorithms based on their experimental investigation and carrying out charactheristics comparison are presented.
Design optimization and analysis of selected thermal devices using self-adaptive Jaya algorithm
International Nuclear Information System (INIS)
Rao, R.V.; More, K.C.
2017-01-01
Highlights: • Self-adaptive Jaya algorithm is proposed for optimal design of thermal devices. • Optimization of heat pipe, cooling tower, heat sink and thermo-acoustic prime mover is presented. • Results of the proposed algorithm are better than the other optimization techniques. • The proposed algorithm may be conveniently used for the optimization of other devices. - Abstract: The present study explores the use of an improved Jaya algorithm called self-adaptive Jaya algorithm for optimal design of selected thermal devices viz; heat pipe, cooling tower, honeycomb heat sink and thermo-acoustic prime mover. Four different optimization case studies of the selected thermal devices are presented. The researchers had attempted the same design problems in the past using niched pareto genetic algorithm (NPGA), response surface method (RSM), leap-frog optimization program with constraints (LFOPC) algorithm, teaching-learning based optimization (TLBO) algorithm, grenade explosion method (GEM) and multi-objective genetic algorithm (MOGA). The results achieved by using self-adaptive Jaya algorithm are compared with those achieved by using the NPGA, RSM, LFOPC, TLBO, GEM and MOGA algorithms. The self-adaptive Jaya algorithm is proved superior as compared to the other optimization methods in terms of the results, computational effort and function evalutions.
Directory of Open Access Journals (Sweden)
Fazal NOORBASHA
2012-08-01
Full Text Available In this present study includes the Very Large Scale Integration (VLSI system implementation of 200MHz, 8-bit, 90nm Complementary Metal Oxide Semiconductor (CMOS Arithmetic and Logic Unit (ALU processor control with logic gate design style and 0.12µm six metal 90nm CMOS fabrication technology. The system blocks and the behaviour are defined and the logical design is implemented in gate level in the design phase. Then, the logic circuits are simulated and the subunits are converted in to 90nm CMOS layout. Finally, in order to construct the VLSI system these units are placed in the floor plan and simulated with analog and digital, logic and switch level simulators. The results of the simulations indicates that the VLSI system can control different instructions which can divided into sub groups: transfer instructions, arithmetic and logic instructions, rotate and shift instructions, branch instructions, input/output instructions, control instructions. The data bus of the system is 16-bit. It runs at 200MHz, and operating power is 1.2V. In this paper, the parametric analysis of the system, the design steps and obtained results are explained.
Digital Image Encryption Algorithm Design Based on Genetic Hyperchaos
Directory of Open Access Journals (Sweden)
Jian Wang
2016-01-01
Full Text Available In view of the present chaotic image encryption algorithm based on scrambling (diffusion is vulnerable to choosing plaintext (ciphertext attack in the process of pixel position scrambling, we put forward a image encryption algorithm based on genetic super chaotic system. The algorithm, by introducing clear feedback to the process of scrambling, makes the scrambling effect related to the initial chaos sequence and the clear text itself; it has realized the image features and the organic fusion of encryption algorithm. By introduction in the process of diffusion to encrypt plaintext feedback mechanism, it improves sensitivity of plaintext, algorithm selection plaintext, and ciphertext attack resistance. At the same time, it also makes full use of the characteristics of image information. Finally, experimental simulation and theoretical analysis show that our proposed algorithm can not only effectively resist plaintext (ciphertext attack, statistical attack, and information entropy attack but also effectively improve the efficiency of image encryption, which is a relatively secure and effective way of image communication.
Shyu, H. C.; Reed, I. S.; Truong, T. K.; Hsu, I. S.; Chang, J. J.
1987-01-01
A quadratic-polynomial Fermat residue number system (QFNS) has been used to compute complex integer multiplications. The advantage of such a QFNS is that a complex integer multiplication requires only two integer multiplications. In this article, a new type Fermat number multiplier is developed which eliminates the initialization condition of the previous method. It is shown that the new complex multiplier can be implemented on a single VLSI chip. Such a chip is designed and fabricated in CMOS-Pw technology.
VLSI micro- and nanophotonics science, technology, and applications
Lee, El-Hang; Razeghi, Manijeh; Jagadish, Chennupati
2011-01-01
Addressing the growing demand for larger capacity in information technology, VLSI Micro- and Nanophotonics: Science, Technology, and Applications explores issues of science and technology of micro/nano-scale photonics and integration for broad-scale and chip-scale Very Large Scale Integration photonics. This book is a game-changer in the sense that it is quite possibly the first to focus on ""VLSI Photonics"". Very little effort has been made to develop integration technologies for micro/nanoscale photonic devices and applications, so this reference is an important and necessary early-stage pe
Lawton, Pat
2004-01-01
The objective of this work was to support the design of improved IUE NEWSIPS high dispersion extraction algorithms. The purpose of this work was to evaluate use of the Linearized Image (LIHI) file versus the Re-Sampled Image (SIHI) file, evaluate various extraction, and design algorithms for evaluation of IUE High Dispersion spectra. It was concluded the use of the Re-Sampled Image (SIHI) file was acceptable. Since the Gaussian profile worked well for the core and the Lorentzian profile worked well for the wings, the Voigt profile was chosen for use in the extraction algorithm. It was found that the gamma and sigma parameters varied significantly across the detector, so gamma and sigma masks for the SWP detector were developed. Extraction code was written.
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
ALGORITHMIC FACILITIES AND SOFTWARE FOR VIRTUAL DESIGN OF ANTI-BLOCK AND COUNTER-SLIPPING SYSTEMS
Directory of Open Access Journals (Sweden)
N. N. Hurski
2009-01-01
Full Text Available The paper considers algorithms of designing a roadway covering for virtual test of mobile machine movement dynamics; an algorithm of forming actual values of forces/moments in «road–wheel–car» contact and their derivatives, and also a software for virtual designing of mobile machine dynamics.
Optimum design for rotor-bearing system using advanced generic algorithm
International Nuclear Information System (INIS)
Kim, Young Chan; Choi, Seong Pil; Yang, Bo Suk
2001-01-01
This paper describes a combinational method to compute the global and local solutions of optimization problems. The present hybrid algorithm uses both a generic algorithm and a local concentrate search algorithm (e.g simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The present algorithm can be supplied to minimize the resonance response (Q factor) and to yield the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables
Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm
Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui
2017-05-01
The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.
Optimal design of the heat pipe using TLBO (teaching–learning-based optimization) algorithm
International Nuclear Information System (INIS)
Rao, R.V.; More, K.C.
2015-01-01
Heat pipe is a highly efficient and reliable heat transfer component. It is a closed container designed to transfer a large amount of heat in system. Since the heat pipe operates on a closed two-phase cycle, the heat transfer capacity is greater than for solid conductors. Also, the thermal response time is less than with solid conductors. The three major elemental parts of the rotating heat pipe are: a cylindrical evaporator, a truncated cone condenser, and a fixed amount of working fluid. In this paper, a recently proposed new stochastic advanced optimization algorithm called TLBO (Teaching–Learning-Based Optimization) algorithm is used for single objective as well as multi-objective design optimization of heat pipe. It is easy to implement, does not make use of derivatives and it can be applied to unconstrained or constrained problems. Two examples of heat pipe are presented in this paper. The results of application of TLBO algorithm for the design optimization of heat pipe are compared with the NPGA (Niched Pareto Genetic Algorithm), GEM (Grenade Explosion Method) and GEO (Generalized External optimization). It is found that the TLBO algorithm has produced better results as compared to those obtained by using NPGA, GEM and GEO algorithms. - Highlights: • The TLBO (Teaching–Learning-Based Optimization) algorithm is used for the design and optimization of a heat pipe. • Two examples of heat pipe design and optimization are presented. • The TLBO algorithm is proved better than the other optimization algorithms in terms of results and the convergence
DESIGNING SUSTAINABLE PROCESSES WITH SIMULATION: THE WASTE REDUCTION (WAR) ALGORITHM
The WAR Algorithm, a methodology for determining the potential environmental impact (PEI) of a chemical process, is presented with modifications that account for the PEI of the energy consumed within that process. From this theory, four PEI indexes are used to evaluate the envir...
The variance quadtree algorithm: use for spatial sampling design
Minasny, B.; McBratney, A.B.; Walvoort, D.J.J.
2007-01-01
Spatial sampling schemes are mainly developed to determine sampling locations that can cover the variation of environmental properties in the area of interest. Here we proposed the variance quadtree algorithm for sampling in an area with prior information represented as ancillary or secondary
Application of an imperialist competitive algorithm to the design of a linear induction motor
International Nuclear Information System (INIS)
Lucas, Caro; Nasiri-Gheidari, Zahra; Tootoonchian, Farid
2010-01-01
In this paper a novel optimization algorithm based on imperialist competitive algorithm (ICA) is used for the design of a low speed single sided linear induction motor (LIM). This type of motors is used increasingly in industrial process specially in transportation systems. In these applications having high efficiency with high power factor is very important. So in this paper the objective function of design is presented considering both efficiency and power factor. Finally the results of ICA are compared with the ones of genetic algorithm and conventional design. Comparison shows the success of ICA for design of LIMs.
PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design
Directory of Open Access Journals (Sweden)
Huu-Khoa Tran
2016-09-01
Full Text Available Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO-based algorithm and the evolutionary programming (EP algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models.
Optimum Performance-Based Seismic Design Using a Hybrid Optimization Algorithm
Directory of Open Access Journals (Sweden)
S. Talatahari
2014-01-01
Full Text Available A hybrid optimization method is presented to optimum seismic design of steel frames considering four performance levels. These performance levels are considered to determine the optimum design of structures to reduce the structural cost. A pushover analysis of steel building frameworks subject to equivalent-static earthquake loading is utilized. The algorithm is based on the concepts of the charged system search in which each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Comparison of the results of the hybrid algorithm with those of other metaheuristic algorithms shows the efficiency of the hybrid algorithm.
Izumi, K. H.; Thompson, J. L.; Groce, J. L.; Schwab, R. W.
1986-01-01
The design requirements for a 4D path definition algorithm are described. These requirements were developed for the NASA ATOPS as an extension of the Local Flow Management/Profile Descent algorithm. They specify the processing flow, functional and data architectures, and system input requirements, and recommended the addition of a broad path revision (reinitialization) function capability. The document also summarizes algorithm design enhancements and the implementation status of the algorithm on an in-house PDP-11/70 computer. Finally, the requirements for the pilot-computer interfaces, the lateral path processor, and guidance and steering function are described.
The Great Deluge Algorithm applied to a nuclear reactor core design optimization problem
International Nuclear Information System (INIS)
Sacco, Wagner F.; Oliveira, Cassiano R.E. de
2005-01-01
The Great Deluge Algorithm (GDA) is a local search algorithm introduced by Dueck. It is an analogy with a flood: the 'water level' rises continuously and the proposed solution must lie above the 'surface' in order to survive. The crucial parameter is the 'rain speed', which controls convergence of the algorithm similarly to Simulated Annealing's annealing schedule. This algorithm is applied to the reactor core design optimization problem, which consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering restrictions on the average thermal flux, criticality and sub-moderation. This problem was previously attacked by the canonical genetic algorithm (GA) and by a Niching Genetic Algorithm (NGA). NGAs were designed to force the genetic algorithm to maintain a heterogeneous population throughout the evolutionary process, avoiding the phenomenon known as genetic drift, where all the individuals converge to a single solution. The results obtained by the Great Deluge Algorithm are compared to those obtained by both algorithms mentioned above. The three algorithms are submitted to the same computational effort and GDA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem. One of the great advantages of this algorithm over the GA is that it does not require special operators for discrete optimization. (author)
Secure image encryption algorithm design using a novel chaos based S-Box
International Nuclear Information System (INIS)
Çavuşoğlu, Ünal; Kaçar, Sezgin; Pehlivan, Ihsan; Zengin, Ahmet
2017-01-01
Highlights: • A new chaotic system is developed for creating S-Box and image encryption algorithm. • Chaos based random number generator is designed with the help of the new chaotic system. NIST tests are run on generated random numbers to verify randomness. • A new S-Box design algorithm is developed to create the chaos based S-Box to be utilized in encryption algorithm and performance tests are made. • The new developed S-Box based image encryption algorithm is introduced and image encryption application is carried out. • To show the quality and strong of the encryption process, security analysis are performed and compared with the AES and chaos algorithms. - Abstract: In this study, an encryption algorithm that uses chaos based S-BOX is developed for secure and speed image encryption. First of all, a new chaotic system is developed for creating S-Box and image encryption algorithm. Chaos based random number generator is designed with the help of the new chaotic system. Then, NIST tests are run on generated random numbers to verify randomness. A new S-Box design algorithm is developed to create the chaos based S-Box to be utilized in encryption algorithm and performance tests are made. As the next step, the new developed S-Box based image encryption algorithm is introduced in detail. Finally, image encryption application is carried out. To show the quality and strong of the encryption process, security analysis are performed. Proposed algorithm is compared with the AES and chaos algorithms. According to tests results, the proposed image encryption algorithm is secure and speed for image encryption application.
Numerical analysis of electromigration in thin film VLSI interconnections
Petrescu, V.; Mouthaan, A.J.; Schoenmaker, W.; Angelescu, S.; Vissarion, R.; Dima, G.; Wallinga, Hans; Profirescu, M.D.
1995-01-01
Due to the continuing downscaling of the dimensions in VLSI circuits, electromigration is becoming a serious reliability hazard. A software tool based on finite element analysis has been developed to solve the two partial differential equations of the two particle vacancy/imperfection model.
DEFF Research Database (Denmark)
Nica, Florin Valentin Traian; Ritchie, Ewen; Leban, Krisztina Monika
2013-01-01
, genetic algorithm and particle swarm are shortly presented in this paper. These two algorithms are tested to determine their performance on five different benchmark test functions. The algorithms are tested based on three requirements: precision of the result, number of iterations and calculation time....... Both algorithms are also tested on an analytical design process of a Transverse Flux Permanent Magnet Generator to observe their performances in an electrical machine design application.......Nowadays the requirements imposed by the industry and economy ask for better quality and performance while the price must be maintained in the same range. To achieve this goal optimization must be introduced in the design process. Two of the best known optimization algorithms for machine design...
Satellite constellation design and radio resource management using genetic algorithm.
Asvial, Muhamad.
2003-01-01
A novel strategy for automatic satellite constellation design with satellite diversity is proposed. The automatic satellite constellation design means some parameters of satellite constellation design can be determined simultaneously. The total number of satellites, the altitude of satellite, the angle between planes, the angle shift between satellites and the inclination angle are considered for automatic satellite constellation design. Satellite constellation design is modelled using a mult...
Graph Transformation and Designing Parallel Sparse Matrix Algorithms beyond Data Dependence Analysis
Directory of Open Access Journals (Sweden)
H.X. Lin
2004-01-01
Full Text Available Algorithms are often parallelized based on data dependence analysis manually or by means of parallel compilers. Some vector/matrix computations such as the matrix-vector products with simple data dependence structures (data parallelism can be easily parallelized. For problems with more complicated data dependence structures, parallelization is less straightforward. The data dependence graph is a powerful means for designing and analyzing parallel algorithms. However, for sparse matrix computations, parallelization based on solely exploiting the existing parallelism in an algorithm does not always give satisfactory results. For example, the conventional Gaussian elimination algorithm for the solution of a tri-diagonal system is inherently sequential, so algorithms specially for parallel computation has to be designed. After briefly reviewing different parallelization approaches, a powerful graph formalism for designing parallel algorithms is introduced. This formalism will be discussed using a tri-diagonal system as an example. Its application to general matrix computations is also discussed. Its power in designing parallel algorithms beyond the ability of data dependence analysis is shown by means of a new algorithm called ACER (Alternating Cyclic Elimination and Reduction algorithm.
Optimal Design of a Hydrogen Community by Genetic Algorithms
International Nuclear Information System (INIS)
Rodolfo Dufo Lopez; Jose Luis Bernal Agustin; Luis Correas Uson; Ismael Aso Aguarta
2006-01-01
A study was conducted for the implementation of two Hydrogen Communities, following the recommendations of the HY-COM initiative of the European Commission. The proposed communities find their place in the municipality of Sabinanigo (Aragon, Spain). Two cases are analyzed, one off-grid village house near Sabinanigo, and a house situated in the town proper. The study was carried out with the HOGA program, Hybrid Optimization by Genetic Algorithms. A description is provided for the algorithms. The off-grid study deals with a hybrid pv-wind system with hydrogen storage for AC supply to an isolated house. The urban study is related to hydrogen production by means of hybrid renewable sources available locally (photovoltaic, wind and hydro). These complement the existing industrial electrolysis processes, in order to cater for the energy requirements of a small fleet of municipal hydrogen-powered vehicles. HOGA was used to optimize both hybrid systems. Dimensioning and deployment estimations are also provided. (authors)
Optimal Design of a Hydrogen Community by Genetic Algorithms
International Nuclear Information System (INIS)
Rodolfo Dufo Lopeza; Jose Luis Bernal Agustin; Luis Correas Uson; Ismael Aso Aguarta
2006-01-01
A study was conducted for the implementation of two Hydrogen Communities, following the recommendations of the HY-COM initiative of the European Commission. The proposed communities find their place in the municipality of Sabinanigo (Aragon, Spain). Two cases are analyzed, one off-grid village house near Sabinanigo, and a house situated in the town proper. The study was carried out with the HOGA program, Hybrid Optimization by Genetic Algorithms. A description is provided for the algorithms. The off-grid study deals with a hybrid PV-wind system with hydrogen storage for AC supply to an isolated house. The urban study is related to hydrogen production by means of hybrid renewable sources available locally (photovoltaic, wind and hydro). These complement the existing industrial electrolysis processes, in order to cater for the energy requirements of a small fleet of municipal hydrogen-powered vehicles. HOGA was used to optimize both hybrid systems. Dimensioning and deployment estimations are also provided. (authors)
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
Design of an optimization algorithm for clinical use
International Nuclear Information System (INIS)
Gustafsson, Anders
1995-01-01
Radiation therapy optimization has received much attention in the past few years. In combination with biological objective functions, the different optimization schemes has shown a potential to considerably increase the treatment outcome. With improved radiobiological models and increased computer capacity, radiation therapy optimization has now reached a stage where implementation in a clinical treatment planning system is realistic. A radiation therapy optimization method has been investigated with respect to its feasibility as a tool in a clinical 3D treatment planning system. The optimization algorithm is a constrained iterative gradient method. Photon dose calculation is performed using the clinically validated pencil-beam based algorithm of the clinical treatment planning system. Dose calculation within the optimization scheme is very time consuming and measures are required to decrease the calculation time. Different methods for more effective dose calculation within the optimization scheme have been investigated. The optimization results for adaptive sampling of calculation points, and secondary effect approximations in the dose calculation algorithm are compared with the optimization result for accurate dose calculation in all voxels of interest
Directory of Open Access Journals (Sweden)
Y. Gholipour
Full Text Available This paper focuses on a metamodel-based design optimization algorithm. The intention is to improve its computational cost and convergence rate. Metamodel-based optimization method introduced here, provides the necessary means to reduce the computational cost and convergence rate of the optimization through a surrogate. This algorithm is a combination of a high quality approximation technique called Inverse Distance Weighting and a meta-heuristic algorithm called Harmony Search. The outcome is then polished by a semi-tabu search algorithm. This algorithm adopts a filtering system and determines solution vectors where exact simulation should be applied. The performance of the algorithm is evaluated by standard truss design problems and there has been a significant decrease in the computational effort and improvement of convergence rate.
Genetic local search algorithm for optimization design of diffractive optical elements.
Zhou, G; Chen, Y; Wang, Z; Song, H
1999-07-10
We propose a genetic local search algorithm (GLSA) for the optimization design of diffractive optical elements (DOE's). This hybrid algorithm incorporates advantages of both genetic algorithm (GA) and local search techniques. It appears better able to locate the global minimum compared with a canonical GA. Sample cases investigated here include the optimization design of binary-phase Dammann gratings, continuous surface-relief grating array generators, and a uniform top-hat focal plane intensity profile generator. Two GLSA's whose incorporated local search techniques are the hill-climbing method and the simulated annealing algorithm are investigated. Numerical experimental results demonstrate that the proposed algorithm is highly efficient and robust. DOE's that have high diffraction efficiency and excellent uniformity can be achieved by use of the algorithm we propose.
Optimization design for the stepped impedance transformer based on the genetic algorithm
International Nuclear Information System (INIS)
Zou Dehui; Lai Wanchang; Qiu Dong
2007-01-01
This paper introduces the basic principium and mathematic model of the stepped impedance transformer, then puts the emphasis on comparing two kinds of design methods of the stepped impedance transformer. The design results are simulated by EDA, which indicates that genetic algorithm design is better than Chebyshev integrated design in the term of the most reflect coefficient's module. (authors)
Research on application of complex-genetic algorithm in nuclear component optimal design
International Nuclear Information System (INIS)
He Shijing; Yan Changqi; Wang Jianjun; Wang Meng
2010-01-01
Complex algorithm is one of the most commonly used methods in the mechanical design optimization, such as the optimization of nuclear component. An improved method,complex-genetic algorithm(CGA), is developed based on traditional complex algorithm(TCA), in which the disadvantages of TCA have been overcome. An optimal calculation,which represents the pressurizer, is carried out in order to analyze the optimization capability of CGA. The results show that CGA has better optimizing performance than TCA. (authors)
Coevolutionary and genetic algorithm based building spatial and structural design
Hofmeyer, H.; Davila Delgado, J.M.
2015-01-01
In this article, two methods to develop and optimize accompanying building spatial and structural designs are compared. The first, a coevolutionary method, applies deterministic procedures, inspired by realistic design processes, to cyclically add a suitable structural design to the input of a
Carvajal, Gonzalo; Figueroa, Miguel
2014-07-01
Typical image recognition systems operate in two stages: feature extraction to reduce the dimensionality of the input space, and classification based on the extracted features. Analog Very Large Scale Integration (VLSI) is an attractive technology to achieve compact and low-power implementations of these computationally intensive tasks for portable embedded devices. However, device mismatch limits the resolution of the circuits fabricated with this technology. Traditional layout techniques to reduce the mismatch aim to increase the resolution at the transistor level, without considering the intended application. Relating mismatch parameters to specific effects in the application level would allow designers to apply focalized mismatch compensation techniques according to predefined performance/cost tradeoffs. This paper models, analyzes, and evaluates the effects of mismatched analog arithmetic in both feature extraction and classification circuits. For the feature extraction, we propose analog adaptive linear combiners with on-chip learning for both Least Mean Square (LMS) and Generalized Hebbian Algorithm (GHA). Using mathematical abstractions of analog circuits, we identify mismatch parameters that are naturally compensated during the learning process, and propose cost-effective guidelines to reduce the effect of the rest. For the classification, we derive analog models for the circuits necessary to implement Nearest Neighbor (NN) approach and Radial Basis Function (RBF) networks, and use them to emulate analog classifiers with standard databases of face and hand-writing digits. Formal analysis and experiments show how we can exploit adaptive structures and properties of the input space to compensate the effects of device mismatch at the application level, thus reducing the design overhead of traditional layout techniques. Results are also directly extensible to multiple application domains using linear subspace methods. Copyright © 2014 Elsevier Ltd. All rights
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
Design and Large-Scale Evaluation of Educational Games for Teaching Sorting Algorithms
Battistella, Paulo Eduardo; von Wangenheim, Christiane Gresse; von Wangenheim, Aldo; Martina, Jean Everson
2017-01-01
The teaching of sorting algorithms is an essential topic in undergraduate computing courses. Typically the courses are taught through traditional lectures and exercises involving the implementation of the algorithms. As an alternative, this article presents the design and evaluation of three educational games for teaching Quicksort and Heapsort.…
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
DEFF Research Database (Denmark)
Saadi, Dorthe Bodholt; Egstrup, Kenneth; Branebjerg, Jens
2012-01-01
We have designed and optimized an automatic QRS complex detection algorithm for electrocardiogram (ECG) signals recorded with the DELTA ePatch platform. The algorithm is able to automatically switch between single-channel and multi-channel analysis mode. This preliminary study includes data from ...
Advanced algorithms for radiographic material discrimination and inspection system design
Energy Technology Data Exchange (ETDEWEB)
Gilbert, Andrew J. [Pacific Northwest National Laboratory, Richland, WA 99354 (United States); McDonald, Benjamin S., E-mail: benjamin.mcdonald@pnnl.gov [Pacific Northwest National Laboratory, Richland, WA 99354 (United States); Deinert, Mark R., E-mail: mdeinert@mines.edu [Colorado School of Mines, Golden, CO 80401 (United States)
2016-10-15
X-ray and neutron radiography are powerful tools for non-invasively inspecting the interior of objects. However, current methods are limited in their ability to differentiate materials when multiple materials are present, especially within large and complex objects. Past work has demonstrated that the spectral shift that X-ray beams undergo in traversing an object can be used to detect and quantify nuclear materials. The technique uses a spectrally sensitive detector and an inverse algorithm that varies the composition of the object until the X-ray spectrum predicted by X-ray transport matches the one measured. Here we show that this approach can be adapted to multi-mode radiography, with energy integrating detectors, and that the Cramér–Rao lower bound can be used to choose an optimal set of inspection modes a priori. We consider multi-endpoint X-ray radiography alone, or in combination with neutron radiography using deuterium–deuterium (DD) or deuterium–tritium (DT) sources. We show that for an optimal mode choice, the algorithm can improve discrimination between high-Z materials, specifically between tungsten and plutonium, and estimate plutonium mass within a simulated nuclear material storage system to within 1%.
Algorithme intelligent d'optimisation d'un design structurel de grande envergure
Dominique, Stephane
The implementation of an automated decision support system in the field of design and structural optimisation can give a significant advantage to any industry working on mechanical designs. Indeed, by providing solution ideas to a designer or by upgrading existing design solutions while the designer is not at work, the system may reduce the project cycle time, or allow more time to produce a better design. This thesis presents a new approach to automate a design process based on Case-Based Reasoning (CBR), in combination with a new genetic algorithm named Genetic Algorithm with Territorial core Evolution (GATE). This approach was developed in order to reduce the operating cost of the process. However, as the system implementation cost is quite expensive, the approach is better suited for large scale design problem, and particularly for design problems that the designer plans to solve for many different specification sets. First, the CBR process uses a databank filled with every known solution to similar design problems. Then, the closest solutions to the current problem in term of specifications are selected. After this, during the adaptation phase, an artificial neural network (ANN) interpolates amongst known solutions to produce an additional solution to the current problem using the current specifications as inputs. Each solution produced and selected by the CBR is then used to initialize the population of an island of the genetic algorithm. The algorithm will optimise the solution further during the refinement phase. Using progressive refinement, the algorithm starts using only the most important variables for the problem. Then, as the optimisation progress, the remaining variables are gradually introduced, layer by layer. The genetic algorithm that is used is a new algorithm specifically created during this thesis to solve optimisation problems from the field of mechanical device structural design. The algorithm is named GATE, and is essentially a real number
An SEU analysis approach for error propagation in digital VLSI CMOS ASICs
International Nuclear Information System (INIS)
Baze, M.P.; Bartholet, W.G.; Dao, T.A.; Buchner, S.
1995-01-01
A critical issue in the development of ASIC designs is the ability to achieve first pass fabrication success. Unsuccessful fabrication runs have serious impact on ASIC costs and schedules. The ability to predict an ASICs radiation response prior to fabrication is therefore a key issue when designing ASICs for military and aerospace systems. This paper describes an analysis approach for calculating static bit error propagation in synchronous VLSI CMOS circuits developed as an aid for predicting the SEU response of ASIC's. The technique is intended for eventual application as an ASIC development simulation tool which can be used by circuit design engineers for performance evaluation during the pre-fabrication design process in much the same way that logic and timing simulators are used
The design of 3D scaffold for tissue engineering using automated scaffold design algorithm.
Mahmoud, Shahenda; Eldeib, Ayman; Samy, Sherif
2015-06-01
Several progresses have been introduced in the field of bone regenerative medicine. A new term tissue engineering (TE) was created. In TE, a highly porous artificial extracellular matrix or scaffold is required to accommodate cells and guide their growth in three dimensions. The design of scaffolds with desirable internal and external structure represents a challenge for TE. In this paper, we introduce a new method known as automated scaffold design (ASD) for designing a 3D scaffold with a minimum mismatches for its geometrical parameters. The method makes use of k-means clustering algorithm to separate the different tissues and hence decodes the defected bone portions. The segmented portions of different slices are registered to construct the 3D volume for the data. It also uses an isosurface rendering technique for 3D visualization of the scaffold and bones. It provides the ability to visualize the transplanted as well as the normal bone portions. The proposed system proves good performance in both the segmentation results and visualizations aspects.
A multichip aVLSI system emulating orientation selectivity of primary visual cortical cells.
Shimonomura, Kazuhiro; Yagi, Tetsuya
2005-07-01
In this paper, we designed and fabricated a multichip neuromorphic analog very large scale integrated (aVLSI) system, which emulates the orientation selective response of the simple cell in the primary visual cortex. The system consists of a silicon retina and an orientation chip. An image, which is filtered by a concentric center-surround (CS) antagonistic receptive field of the silicon retina, is transferred to the orientation chip. The image transfer from the silicon retina to the orientation chip is carried out with analog signals. The orientation chip selectively aggregates multiple pixels of the silicon retina, mimicking the feedforward model proposed by Hubel and Wiesel. The chip provides the orientation-selective (OS) outputs which are tuned to 0 degrees, 60 degrees, and 120 degrees. The feed-forward aggregation reduces the fixed pattern noise that is due to the mismatch of the transistors in the orientation chip. The spatial properties of the orientation selective response were examined in terms of the adjustable parameters of the chip, i.e., the number of aggregated pixels and size of the receptive field of the silicon retina. The multichip aVLSI architecture used in the present study can be applied to implement higher order cells such as the complex cell of the primary visual cortex.
Built-in self-repair of VLSI memories employing neural nets
Mazumder, Pinaki
1998-10-01
The decades of the Eighties and the Nineties have witnessed the spectacular growth of VLSI technology, when the chip size has increased from a few hundred devices to a staggering multi-millon transistors. This trend is expected to continue as the CMOS feature size progresses towards the nanometric dimension of 100 nm and less. SIA roadmap projects that, where as the DRAM chips will integrate over 20 billion devices in the next millennium, the future microprocessors may incorporate over 100 million transistors on a single chip. As the VLSI chip size increase, the limited accessibility of circuit components poses great difficulty for external diagnosis and replacement in the presence of faulty components. For this reason, extensive work has been done in built-in self-test techniques, but little research is known concerning built-in self-repair. Moreover, the extra hardware introduced by conventional fault-tolerance techniques is also likely to become faulty, therefore causing the circuit to be useless. This research demonstrates the feasibility of implementing electronic neural networks as intelligent hardware for memory array repair. Most importantly, we show that the neural network control possesses a robust and degradable computing capability under various fault conditions. Overall, a yield analysis performed on 64K DRAM's shows that the yield can be improved from as low as 20 percent to near 99 percent due to the self-repair design, with overhead no more than 7 percent.
Design optimization of brushed permanent magnet D C motor by genetic algorithm
Amini, S
2002-01-01
Because of field winding replacement with permanent magnet in brushed permanent magnet D C (PMDC) motors, field losses are eliminated and the structure of the motor is more simple. Efficiency of these motors is therefore increased and the manufacturing process is simplified. Hence, these motors are commonly used in low power applications and their design and optimization is an important consideration. Genetic algorithms are proposed for design optimization of PMD motors because of their independence to objective function structure and its derivative. In this paper genetic algorithms are evaluated for PMDC motor design optimization. an introduction is first presented about PMDC motors, general design procedure and elements of their optimization. Genetic algorithms are then briefly described. Finally results of optimization by genetic algorithms are compared with the one obtained using a conventional method.
A general theory known as the WAste Reduction (WASR) algorithm has been developed to describe the flow and the generation of potential environmental impact through a chemical process. This theory integrates environmental impact assessment into chemical process design Potential en...
Design of a Ground-Launched Ballistic Missile Interceptor Using a Genetic Algorithm
National Research Council Canada - National Science Library
Anderson, Murray
1999-01-01
...) minimize maximum U-loading. In 50 generations the genetic algorithm was able to develop two basic types of external aerodynamic designs that performed nearly the same, with miss distances less than 1.0 foot...
Design optimization of brushed permanent magnet D C motor by genetic algorithm
International Nuclear Information System (INIS)
Amini, S.; Oraee, H.
2002-01-01
Because of field winding replacement with permanent magnet in brushed permanent magnet D C (PMDC) motors, field losses are eliminated and the structure of the motor is more simple. Efficiency of these motors is therefore increased and the manufacturing process is simplified. Hence, these motors are commonly used in low power applications and their design and optimization is an important consideration. Genetic algorithms are proposed for design optimization of PMD motors because of their independence to objective function structure and its derivative. In this paper genetic algorithms are evaluated for PMDC motor design optimization. an introduction is first presented about PMDC motors, general design procedure and elements of their optimization. Genetic algorithms are then briefly described. Finally results of optimization by genetic algorithms are compared with the one obtained using a conventional method
GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE
Directory of Open Access Journals (Sweden)
Ashish Jain
2012-07-01
Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.
Vision-based vehicle detection and tracking algorithm design
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.
A novel method to design S-box based on chaotic map and genetic algorithm
International Nuclear Information System (INIS)
Wang, Yong; Wong, Kwok-Wo; Li, Changbing; Li, Yang
2012-01-01
The substitution box (S-box) is an important component in block encryption algorithms. In this Letter, the problem of constructing S-box is transformed to a Traveling Salesman Problem and a method for designing S-box based on chaos and genetic algorithm is proposed. Since the proposed method makes full use of the traits of chaotic map and evolution process, stronger S-box is obtained. The results of performance test show that the presented S-box has good cryptographic properties, which justify that the proposed algorithm is effective in generating strong S-boxes. -- Highlights: ► The problem of constructing S-box is transformed to a Traveling Salesman Problem. ► We present a new method for designing S-box based on chaos and genetic algorithm. ► The proposed algorithm is effective in generating strong S-boxes.
A novel method to design S-box based on chaotic map and genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Wang, Yong, E-mail: wangyong_cqupt@163.com [State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044 (China); Key Laboratory of Electronic Commerce and Logistics, Chongqing University of Posts and Telecommunications, Chongqing 400065 (China); Wong, Kwok-Wo [Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong (Hong Kong); Li, Changbing [Key Laboratory of Electronic Commerce and Logistics, Chongqing University of Posts and Telecommunications, Chongqing 400065 (China); Li, Yang [Department of Automatic Control and Systems Engineering, The University of Sheffield, Mapping Street, S1 3DJ (United Kingdom)
2012-01-30
The substitution box (S-box) is an important component in block encryption algorithms. In this Letter, the problem of constructing S-box is transformed to a Traveling Salesman Problem and a method for designing S-box based on chaos and genetic algorithm is proposed. Since the proposed method makes full use of the traits of chaotic map and evolution process, stronger S-box is obtained. The results of performance test show that the presented S-box has good cryptographic properties, which justify that the proposed algorithm is effective in generating strong S-boxes. -- Highlights: ► The problem of constructing S-box is transformed to a Traveling Salesman Problem. ► We present a new method for designing S-box based on chaos and genetic algorithm. ► The proposed algorithm is effective in generating strong S-boxes.
SENSORS FAULT DIAGNOSIS ALGORITHM DESIGN OF A HYDRAULIC SYSTEM
Directory of Open Access Journals (Sweden)
Matej ORAVEC
2017-06-01
Full Text Available This article presents the sensors fault diagnosis system design for the hydraulic system, which is based on the group of the three fault estimation filters. These filters are used for estimation of the system states and sensors fault magnitude. Also, this article briefly stated the hydraulic system state control design with integrator, which is important assumption for the fault diagnosis system design. The sensors fault diagnosis system is implemented into the Matlab/Simulink environment and it is verified using the controlled hydraulic system simulation model. Verification of the designed fault diagnosis system is realized by series of experiments, which simulates sensors faults. The results of the experiments are briefly presented in the last part of this article.
Optimal Design of the Transverse Flux Machine Using a Fitted Genetic Algorithm with Real Parameters
DEFF Research Database (Denmark)
Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika
2012-01-01
This paper applies a fitted genetic algorithm (GA) to the optimal design of transverse flux machine (TFM). The main goal is to provide a tool for the optimal design of TFM that is an easy to use. The GA optimizes the analytic basic design of two TFM topologies: the C-core and the U-core. First...
DEFF Research Database (Denmark)
Larsen, Niels Vesterdal
2007-01-01
A printed drooping dipole array is designed and constructed. The design is based on a genetic algorithm optimisation procedure used in conjunction with the software programme AWAS. By optimising the array G/T for specific combinations of scan angles and frequencies an optimum design is obtained...
A synthesis/design optimization algorithm for Rankine cycle based energy systems
International Nuclear Information System (INIS)
Toffolo, Andrea
2014-01-01
The algorithm presented in this work has been developed to search for the optimal topology and design parameters of a set of Rankine cycles forming an energy system that absorbs/releases heat at different temperature levels and converts part of the absorbed heat into electricity. This algorithm can deal with several applications in the field of energy engineering: e.g., steam cycles or bottoming cycles in combined/cogenerative plants, steam networks, low temperature organic Rankine cycles. The main purpose of this algorithm is to overcome the limitations of the search space introduced by the traditional mixed-integer programming techniques, which assume that possible solutions are derived from a single superstructure embedding them all. The algorithm presented in this work is a hybrid evolutionary/traditional optimization algorithm organized in two levels. A complex original codification of the topology and the intensive design parameters of the system is managed by the upper level evolutionary algorithm according to the criteria set by the HEATSEP method, which are used for the first time to automatically synthesize a “basic” system configuration from a set of elementary thermodynamic cycles. The lower SQP (sequential quadratic programming) algorithm optimizes the objective function(s) with respect to cycle mass flow rates only, taking into account the heat transfer feasibility constraint within the undefined heat transfer section. A challenging example of application is also presented to show the capabilities of the algorithm. - Highlights: • Energy systems based on Rankine cycles are used in many applications. • A hybrid algorithm is proposed to optimize the synthesis/design of such systems. • The topology of the candidate solutions is not limited by a superstructure. • Topology is managed by the genetic operators of the upper level algorithm. • The effectiveness of the algorithm is proved in a complex test case
A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules.
Daeyaert, Frits; Deem, Micheal W
2017-01-01
We have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Cathodic Protection Design Algorithms for Refineries Aboveground Storage Tanks
Directory of Open Access Journals (Sweden)
Kosay Abdul sattar Majbor
2017-12-01
Full Text Available Storage tanks condition and integrity is maintained by joint application of coating and cathodic protection. Iraq southern region rich in oil and petroleum product refineries need and use plenty of aboveground storage tanks. Iraq went through conflicts over the past thirty five years resulting in holding the oil industry infrastructure behind regarding maintenance and modernization. The primary concern in this work is the design and implementation of cathodic protection systems for the aboveground storage tanks farm in the oil industry. Storage tank external base area and tank internal surface area are to be protected against corrosion using impressed current and sacrificial anode cathodic protection systems. Interactive versatile computer programs are developed to provide the necessary system parameters data including the anode requirements, composition, rating, configuration, etc. Microsoft-Excel datasheet and Visual Basic.Net developed software were used throughout the study in the design of both cathodic protection systems. The case study considered in this work is the eleven aboveground storage tanks farm situated in al-Shauiba refinery in southern IRAQ. The designed cathodic protection systems are to be installed and monitored realistically in the near future. Both systems were designed for a life span of (15-30 years, and all their parameters were within the internationally accepted standards.
Equipment Specific Optimum Blast-Design Using Genetic Algorithm
Directory of Open Access Journals (Sweden)
Rahul Upadhyay
2015-08-01
Full Text Available Design of blasting parameters plays an important role in the optimization of mining cost as well as cost of subsequent processing of ore. Drilling and handling costs are the major mining cost. This work presents an indirect optimization model for mining cost through optimization of blasting parameters for a particular set of drilling and loading equipment.
Emerging Applications for High K Materials in VLSI Technology
Clark, Robert D.
2014-01-01
The current status of High K dielectrics in Very Large Scale Integrated circuit (VLSI) manufacturing for leading edge Dynamic Random Access Memory (DRAM) and Complementary Metal Oxide Semiconductor (CMOS) applications is summarized along with the deposition methods and general equipment types employed. Emerging applications for High K dielectrics in future CMOS are described as well for implementations in 10 nm and beyond nodes. Additional emerging applications for High K dielectrics include Resistive RAM memories, Metal-Insulator-Metal (MIM) diodes, Ferroelectric logic and memory devices, and as mask layers for patterning. Atomic Layer Deposition (ALD) is a common and proven deposition method for all of the applications discussed for use in future VLSI manufacturing. PMID:28788599
Emerging Applications for High K Materials in VLSI Technology
Directory of Open Access Journals (Sweden)
Robert D. Clark
2014-04-01
Full Text Available The current status of High K dielectrics in Very Large Scale Integrated circuit (VLSI manufacturing for leading edge Dynamic Random Access Memory (DRAM and Complementary Metal Oxide Semiconductor (CMOS applications is summarized along with the deposition methods and general equipment types employed. Emerging applications for High K dielectrics in future CMOS are described as well for implementations in 10 nm and beyond nodes. Additional emerging applications for High K dielectrics include Resistive RAM memories, Metal-Insulator-Metal (MIM diodes, Ferroelectric logic and memory devices, and as mask layers for patterning. Atomic Layer Deposition (ALD is a common and proven deposition method for all of the applications discussed for use in future VLSI manufacturing.
Embedded Processor Based Automatic Temperature Control of VLSI Chips
Directory of Open Access Journals (Sweden)
Narasimha Murthy Yayavaram
2009-01-01
Full Text Available This paper presents embedded processor based automatic temperature control of VLSI chips, using temperature sensor LM35 and ARM processor LPC2378. Due to the very high packing density, VLSI chips get heated very soon and if not cooled properly, the performance is very much affected. In the present work, the sensor which is kept very near proximity to the IC will sense the temperature and the speed of the fan arranged near to the IC is controlled based on the PWM signal generated by the ARM processor. A buzzer is also provided with the hardware, to indicate either the failure of the fan or overheating of the IC. The entire process is achieved by developing a suitable embedded C program.
International Nuclear Information System (INIS)
Ohtsuki, Yukiyoshi
2010-01-01
In this paper, molecular quantum computation is numerically studied with the quantum search algorithm (Grover's algorithm) by means of optimal control simulation. Qubits are implemented in the vibronic states of I 2 , while gate operations are realized by optimally designed laser pulses. The methodological aspects of the simulation are discussed in detail. We show that the algorithm for solving a gate pulse-design problem has the same mathematical form as a state-to-state control problem in the density matrix formalism, which provides monotonically convergent algorithms as an alternative to the Krotov method. The sequential irradiation of separately designed gate pulses leads to the population distribution predicted by Grover's algorithm. The computational accuracy is reduced by the imperfect quality of the pulse design and by the electronic decoherence processes that are modeled by the non-Markovian master equation. However, as long as we focus on the population distribution of the vibronic qubits, we can search a target state with high probability without introducing error-correction processes during the computation. A generalized gate pulse-design scheme to explicitly include decoherence effects is outlined, in which we propose a new objective functional together with its solution algorithm that guarantees monotonic convergence.
Indian Academy of Sciences (India)
of programs, illustrate a method of establishing the ... importance of methods of establishing the correctness of .... Thus, the proof will be different for each input ..... Formal methods are pivotal in the design, development, and maintenance of ...
Design of reproducible polarized and non-polarized edge filters using genetic algorithm
International Nuclear Information System (INIS)
Ejigu, Efrem Kebede; Lacquet, B M
2010-01-01
Recent advancement in optical fibre communications technology is partly due to the advancement of optical thin film technology. The advancement of optical thin film technology includes the development of new and existing optical filter design methods. The genetic algorithm is one of the new design methods that show promising results in designing a number of complicated design specifications. It is the finding of this study that the genetic algorithm design method, through its optimization capability, can give more reliable and reproducible designs of any specifications. The design method in this study optimizes the thickness of each layer to get to the best possible solution. Its capability and unavoidable limitations in designing polarized and non-polarized edge filters from absorptive and dispersive materials is well demonstrated. It is also demonstrated that polarized and non-polarized designs from the genetic algorithm are reproducible with great success. This research has accomplished the great task of formulating a computer program using the genetic algorithm in a Matlab environment for the design of a reproducible polarized and non-polarized filters of any sort from any kind of materials
Expert-guided evolutionary algorithm for layout design of complex space stations
Qian, Zhiqin; Bi, Zhuming; Cao, Qun; Ju, Weiguo; Teng, Hongfei; Zheng, Yang; Zheng, Siyu
2017-08-01
The layout of a space station should be designed in such a way that different equipment and instruments are placed for the station as a whole to achieve the best overall performance. The station layout design is a typical nondeterministic polynomial problem. In particular, how to manage the design complexity to achieve an acceptable solution within a reasonable timeframe poses a great challenge. In this article, a new evolutionary algorithm has been proposed to meet such a challenge. It is called as the expert-guided evolutionary algorithm with a tree-like structure decomposition (EGEA-TSD). Two innovations in EGEA-TSD are (i) to deal with the design complexity, the entire design space is divided into subspaces with a tree-like structure; it reduces the computation and facilitates experts' involvement in the solving process. (ii) A human-intervention interface is developed to allow experts' involvement in avoiding local optimums and accelerating convergence. To validate the proposed algorithm, the layout design of one-space station is formulated as a multi-disciplinary design problem, the developed algorithm is programmed and executed, and the result is compared with those from other two algorithms; it has illustrated the superior performance of the proposed EGEA-TSD.
Ship Pipe Routing Design Using NSGA-II and Coevolutionary Algorithm
Directory of Open Access Journals (Sweden)
Wentie Niu
2016-01-01
Full Text Available Pipe route design plays a prominent role in ship design. Due to the complex configuration in layout space with numerous pipelines, diverse design constraints, and obstacles, it is a complicated and time-consuming process to obtain the optimal route of ship pipes. In this article, an optimized design method for branch pipe routing is proposed to improve design efficiency and to reduce human errors. By simplifying equipment and ship hull models and dividing workspace into three-dimensional grid cells, the mathematic model of layout space is constructed. Based on the proposed concept of pipe grading method, the optimization model of pipe routing is established. Then an optimization procedure is presented to deal with pipe route planning problem by combining maze algorithm (MA, nondominated sorting genetic algorithm II (NSGA-II, and cooperative coevolutionary nondominated sorting genetic algorithm II (CCNSGA-II. To improve the performance in genetic algorithm procedure, a fixed-length encoding method is presented based on improved maze algorithm and adaptive region strategy. Fuzzy set theory is employed to extract the best compromise pipeline from Pareto optimal solutions. Simulation test of branch pipe and design optimization of a fuel piping system were carried out to illustrate the design optimization procedure in detail and to verify the feasibility and effectiveness of the proposed methodology.
Thomson, Martin J.; Waddie, Andrew J.; Taghizadeh, Mohammad R.
2006-04-01
We present a genetic algorithm with small population sizes for the design of diffraction gratings in the rigorous domain. A general crossover and mutation scheme is defined, forming fifteen offspring from 3 parents, which enables the algorithm to be used for designing gratings with diverse optical properties by careful definition of the merit function. The initial parents are randomly selected and the parents of the subsequent generations are selected by survival of the fittest. The performance of the algorithm is demonstrated by designing diffraction gratings with specific application to high power laser beam lines. Gratings are designed that act as beam deflectors, polarisers, polarising beam splitters, harmonic separation gratings and pulse compression gratings. By imposing fabrication constraints within the design process, we determine which of these elements have true potential for application within high power laser beam lines.
Drift chamber tracking with a VLSI neural network
International Nuclear Information System (INIS)
Lindsey, C.S.; Denby, B.; Haggerty, H.; Johns, K.
1992-10-01
We have tested a commercial analog VLSI neural network chip for finding in real time the intercept and slope of charged particles traversing a drift chamber. Voltages proportional to the drift times were input to the Intel ETANN chip and the outputs were recorded and later compared off line to conventional track fits. We will discuss the chamber and test setup, the chip specifications, and results of recent tests. We'll briefly discuss possible applications in high energy physics detector triggers
Efficient Algorithms and Design for Interpolation Filters in Digital Receiver
Directory of Open Access Journals (Sweden)
Xiaowei Niu
2014-05-01
Full Text Available Based on polynomial functions this paper introduces a generalized design method for interpolation filters. The polynomial-based interpolation filters can be implemented efficiently by using a modified Farrow structure with an arbitrary frequency response, the filters allow many pass- bands and stop-bands, and for each band the desired amplitude and weight can be set arbitrarily. The optimization coefficients of the interpolation filters in time domain are got by minimizing the weighted mean squared error function, then converting to solve the quadratic programming problem. The optimization coefficients in frequency domain are got by minimizing the maxima (MiniMax of the weighted mean squared error function. The degree of polynomials and the length of interpolation filter can be selected arbitrarily. Numerical examples verified the proposed design method not only can reduce the hardware cost effectively but also guarantee an excellent performance.
Convergence of the Quasi-static Antenna Design Algorithm
2013-04-01
was the first antenna design with quasi-static methods. In electrostatics, a perfect conductor is the same as an equipotential surface . A line of...which can cause the equipotential surface to terminate on the disk or feed wire. This requires an additional step in the solution process; the... equipotential surface is sampled to verify that the charge is enclosed by the equipotential surface . The final solution must be verified with a detailed
An optimized outlier detection algorithm for jury-based grading of engineering design projects
DEFF Research Database (Denmark)
Thompson, Mary Kathryn; Espensen, Christina; Clemmensen, Line Katrine Harder
2016-01-01
This work characterizes and optimizes an outlier detection algorithm to identify potentially invalid scores produced by jury members while grading engineering design projects. The paper describes the original algorithm and the associated adjudication process in detail. The impact of the various...... (the base rule and the three additional conditions) play a role in the algorithm's performance and should be included in the algorithm. Because there is significant interaction between the base rule and the additional conditions, many acceptable combinations that balance the FPR and FNR can be found......, but no true optimum seems to exist. The performance of the best optimizations and the original algorithm are similar. Therefore, it should be possible to choose new coefficient values for jury populations in other cultures and contexts logically and empirically without a full optimization as long...
Directory of Open Access Journals (Sweden)
Giegerich Robert
2004-08-01
Full Text Available Abstract Background The general problem of RNA secondary structure prediction under the widely used thermodynamic model is known to be NP-complete when the structures considered include arbitrary pseudoknots. For restricted classes of pseudoknots, several polynomial time algorithms have been designed, where the O(n6time and O(n4 space algorithm by Rivas and Eddy is currently the best available program. Results We introduce the class of canonical simple recursive pseudoknots and present an algorithm that requires O(n4 time and O(n2 space to predict the energetically optimal structure of an RNA sequence, possible containing such pseudoknots. Evaluation against a large collection of known pseudoknotted structures shows the adequacy of the canonization approach and our algorithm. Conclusions RNA pseudoknots of medium size can now be predicted reliably as well as efficiently by the new algorithm.
Algorithm Design on Network Game of Chinese Chess
Xianmei, Fang
This paper describes the current situation of domestic network game. Contact the present condition of the local network game currently, we inquired to face to a multithread tcp client and server, such as Chinese chess, according to the information, and study the contents and meanings. Combining the Java of basic knowledge, the article study the compiling procedure facing to the object according to the information in Java Swing usage, and the method of the network procedure. The article researched the method and processes of the network procedure carry on the use of Sprocket under the Java Swing. Understood the basic process of compiling procedure using Java and how to compile a network procedure. The most importance is how a pair of machines correspondence-C/S the service system-is carried out. From here, we put forward the data structure,the basic calculate way of the network game- Chinese chess, and how to design and realize the server and client of that procedure. The online games -- chess design can be divided into several modules as follows: server module, client module and the control module.
A novel hybrid genetic algorithm for optimal design of IPM machines for electric vehicle
Wang, Aimeng; Guo, Jiayu
2017-12-01
A novel hybrid genetic algorithm (HGA) is proposed to optimize the rotor structure of an IPM machine which is used in EV application. The finite element (FE) simulation results of the HGA design is compared with the genetic algorithm (GA) design and those before optimized. It is shown that the performance of the IPMSM is effectively improved by employing the GA and HGA, especially by HGA. Moreover, higher flux-weakening capability and less magnet usage are also obtained. Therefore, the validity of HGA method in IPMSM optimization design is verified.
International Nuclear Information System (INIS)
Semwal, Girish; Rastogi, Vipul
2014-01-01
We present design optimization of wavelength filters based on long period waveguide gratings (LPWGs) using the adaptive particle swarm optimization (APSO) technique. We demonstrate optimization of the LPWG parameters for single-band, wide-band and dual-band rejection filters for testing the convergence of APSO algorithms. After convergence tests on the algorithms, the optimization technique has been implemented to design more complicated application specific filters such as erbium doped fiber amplifier (EDFA) amplified spontaneous emission (ASE) flattening, erbium doped waveguide amplifier (EDWA) gain flattening and pre-defined broadband rejection filters. The technique is useful for designing and optimizing the parameters of LPWGs to achieve complicated application specific spectra. (paper)
Design and experimental evaluation of flexible manipulator control algorithms
International Nuclear Information System (INIS)
Kwon, D.S.; Hwang, D.H.; Babcock, S.M.; Kress, R.L.
1995-01-01
Within the Environmental Restoration and Waste Management Program of the US Department of Energy, the remediation of single-shell radioactive waste storage tanks is one of the areas that challenge state-of-the-art equipment and methods. The use of long-reach manipulators is being seriously considered for this task. Because of high payload capacity and high length-to-cross-section ratio requirements, these long-reach manipulator systems are expected to use hydraulic actuators and to exhibit significant structural flexibility. The controller has been designed to compensate for the hydraulic actuator dynamics by using a load-compensated velocity feedforward loop and to increase the bandwidth by using an inner pressure feedback loop. Shaping filter techniques have been applied as feedforward controllers to avoid structural vibrations during operation. Various types of shaping filter methods have been investigated. Among them, a new approach, referred to as a ''feedforward simulation filter'' that uses embedded simulation, has been presented
A Computer Environment for Beginners' Learning of Sorting Algorithms: Design and Pilot Evaluation
Kordaki, M.; Miatidis, M.; Kapsampelis, G.
2008-01-01
This paper presents the design, features and pilot evaluation study of a web-based environment--the SORTING environment--for the learning of sorting algorithms by secondary level education students. The design of this environment is based on modeling methodology, taking into account modern constructivist and social theories of learning while at…
Design of Supply Chain Networks with Supply Disruptions using Genetic Algorithm
Taha, Raghda; Abdallah, Khaled; Sadek, Yomma; El-Kharbotly, Amin; Afia, Nahid
2014-01-01
The design of supply chain networks subject to disruptions is tackled. A genetic algorithm with the objective of minimizing the design cost and regret cost is developed to achieve a reliable supply chain network. The improvement of supply chain network reliability is measured against the supply chain cost.
Exploring design tradeoffs of a distributed algorithm for cosmic ray event detection
Yousaf, S.; Bakhshi, R.; van Steen, M.; Voulgaris, S.; Kelley, J. L.
2013-03-01
Many sensor networks, including large particle detector arrays measuring high-energy cosmic-ray air showers, traditionally rely on centralised trigger algorithms to find spatial and temporal coincidences of individual nodes. Such schemes suffer from scalability problems, especially if the nodes communicate wirelessly or have bandwidth limitations. However, nodes which instead communicate with each other can, in principle, use a distributed algorithm to find coincident events themselves without communication with a central node. We present such an algorithm and consider various design tradeoffs involved, in the context of a potential trigger for the Auger Engineering Radio Array (AERA).
Directory of Open Access Journals (Sweden)
Long-Hua Ma
2011-08-01
Full Text Available A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform.
International Nuclear Information System (INIS)
Sacco, Wagner F.; Oliveira, Cassiano R.E. de
2005-01-01
A new metaheuristic called 'Gravitational Attraction Algorithm' (GAA) is introduced in this article. It is an analogy with the gravitational force field, where a body attracts another proportionally to both masses and inversely to their distances. The GAA is a populational algorithm where, first of all, the solutions are clustered using the Fuzzy Clustering Means (FCM) algorithm. Following that, the gravitational forces of the individuals in relation to each cluster are evaluated and this individual or solution is displaced to the cluster with the greatest attractive force. Once it is inside this cluster, the solution receives small stochastic variations, performing a local exploration. Then the solutions are crossed over and the process starts all over again. The parameters required by the GAA are the 'diversity factor', which is used to create a random diversity in a fashion similar to genetic algorithm's mutation, and the number of clusters for the FCM. GAA is applied to the reactor core design optimization problem which consists in adjusting several reactor cell parameters in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering operational restrictions. This problem was previously attacked using the canonical genetic algorithm (GA) and a Niching Genetic Algorithm (NGA). The new metaheuristic is then compared to those two algorithms. The three algorithms are submitted to the same computational effort and GAA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem. (author)
CMOS VLSI Active-Pixel Sensor for Tracking
Pain, Bedabrata; Sun, Chao; Yang, Guang; Heynssens, Julie
2004-01-01
An architecture for a proposed active-pixel sensor (APS) and a design to implement the architecture in a complementary metal oxide semiconductor (CMOS) very-large-scale integrated (VLSI) circuit provide for some advanced features that are expected to be especially desirable for tracking pointlike features of stars. The architecture would also make this APS suitable for robotic- vision and general pointing and tracking applications. CMOS imagers in general are well suited for pointing and tracking because they can be configured for random access to selected pixels and to provide readout from windows of interest within their fields of view. However, until now, the architectures of CMOS imagers have not supported multiwindow operation or low-noise data collection. Moreover, smearing and motion artifacts in collected images have made prior CMOS imagers unsuitable for tracking applications. The proposed CMOS imager (see figure) would include an array of 1,024 by 1,024 pixels containing high-performance photodiode-based APS circuitry. The pixel pitch would be 9 m. The operations of the pixel circuits would be sequenced and otherwise controlled by an on-chip timing and control block, which would enable the collection of image data, during a single frame period, from either the full frame (that is, all 1,024 1,024 pixels) or from within as many as 8 different arbitrarily placed windows as large as 8 by 8 pixels each. A typical prior CMOS APS operates in a row-at-a-time ( grolling-shutter h) readout mode, which gives rise to exposure skew. In contrast, the proposed APS would operate in a sample-first/readlater mode, suppressing rolling-shutter effects. In this mode, the analog readout signals from the pixels corresponding to the windows of the interest (which windows, in the star-tracking application, would presumably contain guide stars) would be sampled rapidly by routing them through a programmable diagonal switch array to an on-chip parallel analog memory array. The
Model-based fault diagnosis techniques design schemes, algorithms, and tools
Ding, Steven
2008-01-01
The objective of this book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms, and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers. This is a textbook with extensive examples and references. Most methods are given in the form of an algorithm that enables a direct implementation in a programme. Comparisons among different methods are included when possible.
Las Vegas is better than determinism in VLSI and distributed computing
DEFF Research Database (Denmark)
Mehlhorn, Kurt; Schmidt, Erik Meineche
1982-01-01
In this paper we describe a new method for proving lower bounds on the complexity of VLSI - computations and more generally distributed computations. Lipton and Sedgewick observed that the crossing sequence arguments used to prove lower bounds in VLSI (or TM or distributed computing) apply to (ac...
Directory of Open Access Journals (Sweden)
N. M. Okasha
2016-04-01
Full Text Available In this paper, an approach for conducting a Reliability-Based Design Optimization (RBDO of truss structures with linked-discrete design variables is proposed. The sections of the truss members are selected from the AISC standard tables and thus the design variables that represent the properties of each section are linked. Latin hypercube sampling is used in the evaluation of the structural reliability. The improved firefly algorithm is used for the optimization solution process. It was found that in order to use the improved firefly algorithm for efficiently solving problems of reliability-based design optimization with linked-discrete design variables; it needs to be modified as proposed in this paper to accelerate its convergence.
Yang, Yan-Pu; Chen, Deng-Kai; Gu, Rong; Gu, Yu-Feng; Yu, Sui-Huai
2016-01-01
Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design.
A Novel Adaptive Particle Swarm Optimization Algorithm with Foraging Behavior in Optimization Design
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Liu Yan
2018-01-01
Full Text Available The method of repeated trial and proofreading is generally used to the convention reducer design, but these methods is low efficiency and the size of the reducer is often large. Aiming the problems, this paper presents an adaptive particle swarm optimization algorithm with foraging behavior, in this method, the bacterial foraging process is introduced into the adaptive particle swarm optimization algorithm, which can provide the function of particle chemotaxis, swarming, reproduction, elimination and dispersal, to improve the ability of local search and avoid premature behavior. By test verification through typical function and the application of the optimization design in the structure of the reducer with discrete and continuous variables, the results are shown that the new algorithm has the advantages of good reliability, strong searching ability and high accuracy. It can be used in engineering design, and has a strong applicability.
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments
Harman, Radoslav
2018-01-17
We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.
Design Optimization of Tilting-Pad Journal Bearing Using a Genetic Algorithm
Directory of Open Access Journals (Sweden)
Hamit Saruhan
2004-01-01
Full Text Available This article focuses on the use of genetic algorithms in developing an efficient optimum design method for tilting pad bearings. The approach optimizes based on minimum film thickness, power loss, maximum film temperature, and a global objective. Results for a five tilting-pad preloaded bearing are presented to provide a comparison with more traditional optimum design methods such as the gradient-based global criterion method, and also to provide insight into the potential of genetic algorithms in the design of rotor bearings. Genetic algorithms are efficient search techniques based on the idea of natural selection and genetics. These robust methods have gained recognition as general problem solving techniques in many applications.
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments
Harman, Radoslav; Filová , Lenka; Richtarik, Peter
2018-01-01
We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.
Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design.
Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco
2016-11-23
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms.
Analog VLSI Models of Range-Tuned Neurons in the Bat Echolocation System
Directory of Open Access Journals (Sweden)
Horiuchi Timothy
2003-01-01
Full Text Available Bat echolocation is a fascinating topic of research for both neuroscientists and engineers, due to the complex and extremely time-constrained nature of the problem and its potential for application to engineered systems. In the bat's brainstem and midbrain exist neural circuits that are sensitive to the specific difference in time between the outgoing sonar vocalization and the returning echo. While some of the details of the neural mechanisms are known to be species-specific, a basic model of reafference-triggered, postinhibitory rebound timing is reasonably well supported by available data. We have designed low-power, analog VLSI circuits to mimic this mechanism and have demonstrated range-dependent outputs for use in a real-time sonar system. These circuits are being used to implement range-dependent vocalization amplitude, vocalization rate, and closest target isolation.
International Nuclear Information System (INIS)
Bingefors, N.; Ekeloef, T.; Eriksson, C.; Paulsson, M.; Moerk, G.; Sjoelund, A.
1992-01-01
Samples of the preamplifier circuit, as well as of separate n and p channel transistors of the type contained in the circuit, were irradiated with gammas from a 60 Co source up to an integrated dose of 3 Mrad (30 kGy). The VLSI manufacturing technology used is the SOS4 process of ABB Hafo. A first analysis of the tests shows that the performance of the amplifier remains practically unaffected by the radiation for total doses up to 1 Mrad. At higher doses up to 3 Mrad the circuit amplification factor decreases by a factor between 4 and 5 whereas the output noise level remains unchanged. It is argued that it may be possible to reduce the decrease in amplification factor in future by optimizing the amplifier circuit design further. (orig.)
A parallel VLSI architecture for a digital filter of arbitrary length using Fermat number transforms
Truong, T. K.; Reed, I. S.; Yeh, C. S.; Shao, H. M.
1982-01-01
A parallel architecture for computation of the linear convolution of two sequences of arbitrary lengths using the Fermat number transform (FNT) is described. In particular a pipeline structure is designed to compute a 128-point FNT. In this FNT, only additions and bit rotations are required. A standard barrel shifter circuit is modified so that it performs the required bit rotation operation. The overlap-save method is generalized for the FNT to compute a linear convolution of arbitrary length. A parallel architecture is developed to realize this type of overlap-save method using one FNT and several inverse FNTs of 128 points. The generalized overlap save method alleviates the usual dynamic range limitation in FNTs of long transform lengths. Its architecture is regular, simple, and expandable, and therefore naturally suitable for VLSI implementation.
GENETIC ALGORITHM IN OPTIMIZATION DESIGN OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR
Directory of Open Access Journals (Sweden)
Phuong Le Ngo
2017-01-01
Full Text Available Classical method of designing electric motors help to achieve functional motor, but doesn’t ensure minimal cost in manufacturing and operating. Recently optimization is becoming an important part in modern electric motor design process. The objective of the optimization process is usually to minimize cost, energy loss, mass, or maximize torque and efficiency. Most of the requirements for electrical machine design are in contradiction to each other (reduction in volume or mass, improvement in efficiency etc.. Optimization in design permanent magnet synchronous motor (PMSM is a multi-objective optimization problem. There are two approaches for solving this problem, one of them is evolution algorithms, which gain a lot of attentions recently. For designing PMSM, evolution algorithms are more attractive approach. Genetic algorithm is one of the most common. This paper presents components and procedures of genetic algorithms, and its implementation on computer. In optimization process, analytical and finite element method are used together for better performance and precision. Result from optimization process is a set of solutions, from which engineer will choose one. This method was used to design a permanent magnet synchronous motor based on an asynchronous motor type АИР112МВ8.
Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm
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Feifei Dong
2014-01-01
Full Text Available Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC. The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.
Design and implementation of adaptive inverse control algorithm for a micro-hand control system
Directory of Open Access Journals (Sweden)
Wan-Cheng Wang
2014-01-01
Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.
A new hybrid meta-heuristic algorithm for optimal design of large-scale dome structures
Kaveh, A.; Ilchi Ghazaan, M.
2018-02-01
In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.
Design of Low Power Algorithms for Automatic Embedded Analysis of Patch ECG Signals
DEFF Research Database (Denmark)
Saadi, Dorthe Bodholt
, several different cable-free wireless patch-type ECG recorders have recently reached the market. One of these recorders is the ePatch designed by the Danish company DELTA. The extended monitoring period available with the patch recorders has demonstrated to increase the diagnostic yield of outpatient ECG....... Such algorithms could allow the real-time transmission of clinically relevant information to a central monitoring station. The first step in embedded ECG interpretation is the automatic detection of each individual heartbeat. An important part of this project was therefore to design a novel algorithm...
Directory of Open Access Journals (Sweden)
Daniel Antonio Molina
2015-09-01
Full Text Available In this paper we apply to solve the Radio Network Design problem (RND a series of the non-conventional genetic algorithms called Cross generational elitist selection Heterogeneous recombination Cataclysmic mutation (CHC. A set of genetic algorithms is used to perform a comparative performance of the proposed algorithms. An objective function based on signal coverage efficiency is used. Genetic variability of the population is used for both, as a parameter of convergence and detection of incest. Furthermore the variability of the best individual is proposed as a shaking mechanism. This allows generating dynamic populations according to the most promising solutions generating different search spaces. The results obtained by the proposed algorithms are satisfactory.
CAS algorithm-based optimum design of PID controller in AVR system
International Nuclear Information System (INIS)
Zhu Hui; Li Lixiang; Zhao Ying; Guo Yu; Yang Yixian
2009-01-01
This paper presents a novel design method for determining the optimal PID controller parameters of an automatic voltage regulator (AVR) system using the chaotic ant swarm (CAS) algorithm. In the tuning process of parameters, the CAS algorithm is iterated to give the optimal parameters of the PID controller based on the fitness theory, where the position vector of each ant in the CAS algorithm corresponds to the parameter vector of the PID controller. The proposed CAS-PID controllers can ensure better control system performance with respect to the reference input in comparison with GA-PID controllers. Numerical simulations are provided to verify the effectiveness and feasibility of PID controller based on CAS algorithm.
Directory of Open Access Journals (Sweden)
T. Kalavathi Devi
2015-01-01
Full Text Available Convolutional codes are comprehensively used as Forward Error Correction (FEC codes in digital communication systems. For decoding of convolutional codes at the receiver end, Viterbi decoder is often used to have high priority. This decoder meets the demand of high speed and low power. At present, the design of a competent system in Very Large Scale Integration (VLSI technology requires these VLSI parameters to be finely defined. The proposed asynchronous method focuses on reducing the power consumption of Viterbi decoder for various constraint lengths using asynchronous modules. The asynchronous designs are based on commonly used Quasi Delay Insensitive (QDI templates, namely, Precharge Half Buffer (PCHB and Weak Conditioned Half Buffer (WCHB. The functionality of the proposed asynchronous design is simulated and verified using Tanner Spice (TSPICE in 0.25 µm, 65 nm, and 180 nm technologies of Taiwan Semiconductor Manufacture Company (TSMC. The simulation result illustrates that the asynchronous design techniques have 25.21% of power reduction compared to synchronous design and work at a speed of 475 MHz.
A robust controller design method for feedback substitution schemes using genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Trujillo, Mirsha M; Hadjiloucas, Sillas; Becerra, Victor M, E-mail: s.hadjiloucas@reading.ac.uk [Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY (United Kingdom)
2011-08-17
Controllers for feedback substitution schemes demonstrate a trade-off between noise power gain and normalized response time. Using as an example the design of a controller for a radiometric transduction process subjected to arbitrary noise power gain and robustness constraints, a Pareto-front of optimal controller solutions fulfilling a range of time-domain design objectives can be derived. In this work, we consider designs using a loop shaping design procedure (LSDP). The approach uses linear matrix inequalities to specify a range of objectives and a genetic algorithm (GA) to perform a multi-objective optimization for the controller weights (MOGA). A clonal selection algorithm is used to further provide a directed search of the GA towards the Pareto front. We demonstrate that with the proposed methodology, it is possible to design higher order controllers with superior performance in terms of response time, noise power gain and robustness.
Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm
Pak, Chan-gi; Li, Wesley
2009-01-01
Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) to automate analysis and design process by leveraging existing tools to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic, and hypersonic aircraft. This is a promising technology, but faces many challenges in large-scale, real-world application. This report describes current approaches, recent results, and challenges for multidisciplinary design, analysis, and optimization as demonstrated by experience with the Ikhana fire pod design.!
The design and results of an algorithm for intelligent ground vehicles
Duncan, Matthew; Milam, Justin; Tote, Caleb; Riggins, Robert N.
2010-01-01
This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for its 2009 Intelligent Ground Vehicle Competition (IGVC) robot called Anassa V. The BSC robotics team is comprised of undergraduate computer science, engineering technology, marketing students, and one robotics faculty advisor. The team has participated in IGVC since the year 2000. A major part of the design process that the BSC team uses each year for IGVC is a fully documented "Post-IGVC Analysis." Over the nine years since 2000, the lessons the students learned from these analyses have resulted in an ever-improving, highly successful autonomous algorithm. The algorithm employed in Anassa V is a culmination of past successes and new ideas, resulting in Anassa V earning several excellent IGVC 2009 performance awards, including third place overall. The paper will discuss all aspects of the design of this autonomous robotic system, beginning with the design process and ending with test results for both simulation and real environments.
An algorithm for the design and tuning of RF accelerating structures with variable cell lengths
Lal, Shankar; Pant, K. K.
2018-05-01
An algorithm is proposed for the design of a π mode standing wave buncher structure with variable cell lengths. It employs a two-parameter, multi-step approach for the design of the structure with desired resonant frequency and field flatness. The algorithm, along with analytical scaling laws for the design of the RF power coupling slot, makes it possible to accurately design the structure employing a freely available electromagnetic code like SUPERFISH. To compensate for machining errors, a tuning method has been devised to achieve desired RF parameters for the structure, which has been qualified by the successful tuning of a 7-cell buncher to π mode frequency of 2856 MHz with field flatness algorithm and tuning method have demonstrated the feasibility of developing an S-band accelerating structure for desired RF parameters with a relatively relaxed machining tolerance of ∼ 25 μm. This paper discusses the algorithm for the design and tuning of an RF accelerating structure with variable cell lengths.
Energy Technology Data Exchange (ETDEWEB)
Wang, Cheng-Der, E-mail: jdwang@iner.gov.tw [Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan, ROC (China); Lin, Chaung [National Tsing Hua University, Department of Engineering and System Science, 101, Section 2, Kuang Fu Road, Hsinchu 30013, Taiwan (China)
2013-02-15
Highlights: ► The PSO algorithm was adopted to automatically design a BWR CRP. ► The local search procedure was added to improve the result of PSO algorithm. ► The results show that the obtained CRP is the same good as that in the previous work. -- Abstract: This study developed a method for the automatic design of a boiling water reactor (BWR) control rod pattern (CRP) using the particle swarm optimization (PSO) algorithm. The PSO algorithm is more random compared to the rank-based ant system (RAS) that was used to solve the same BWR CRP design problem in the previous work. In addition, the local search procedure was used to make improvements after PSO, by adding the single control rod (CR) effect. The design goal was to obtain the CRP so that the thermal limits and shutdown margin would satisfy the design requirement and the cycle length, which is implicitly controlled by the axial power distribution, would be acceptable. The results showed that the same acceptable CRP found in the previous work could be obtained.
Multi-objective optimum design of fast tool servo based on improved differential evolution algorithm
International Nuclear Information System (INIS)
Zhu, Zhiwei; Zhou, Xiaoqin; Liu, Qiang; Zhao, Shaoxin
2011-01-01
The flexure-based mechanism is a promising realization of fast tool servo (FTS), and the optimum determination of flexure hinge parameters is one of the most important elements in the FTS design. This paper presents a multi-objective optimization approach to optimizing the dimension and position parameters of the flexure-based mechanism, which is based on the improved differential evolution algorithm embedding chaos and nonlinear simulated anneal algorithm. The results of optimum design show that the proposed algorithm has excellent performance and a well-balanced compromise is made between two conflicting objectives, the stroke and natural frequency of the FTS mechanism. The validation tests based on finite element analysis (FEA) show good agreement with the results obtained by using the proposed theoretical algorithm of this paper. Finally, a series of experimental tests are conducted to validate the design process and assess the performance of the FTS mechanism. The designed FTS reaches up to a stroke of 10.25 μm with at least 2 kHz bandwidth. Both of the FEA and experimental results demonstrate that the parameters of the flexure-based mechanism determined by the proposed approaches can achieve the specified performance and the proposed approach is suitable for the optimum design of FTS mechanism and of excellent performances
Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm
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.
Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.
Barros, Rodrigo C; Winck, Ana T; Machado, Karina S; Basgalupp, Márcio P; de Carvalho, André C P L F; Ruiz, Duncan D; de Souza, Osmar Norberto
2012-11-21
This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.
The design of control algorithm for automatic start-up model of HWRR
International Nuclear Information System (INIS)
Guo Wenqi
1990-01-01
The design of control algorithm for automatic start-up model of HWRR (Heavy Water Research Reactor), the calculation of μ value and the application of digital compensator are described. Finally The flow diagram of the automatic start-up and digital compensator program for HWRR are given
Wu, Yue; Li, Q.; Hu, Qingjie; Borgart, A.
2017-01-01
Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly,
Optimization Algorithms for Calculation of the Joint Design Point in Parallel Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
In large structures it is often necessary to estimate the reliability of the system by use of parallel systems. Optimality criteria-based algorithms for calculation of the joint design point in a parallel system are described and efficient active set strategies are developed. Three possible...
Design of Wire Antennas by Using an Evolved Particle Swarm Optimization Algorithm
Lepelaars, E.S.A.M.; Zwamborn, A.P.M.; Rogovic, A.; Marasini, C.; Monorchio, A.
2007-01-01
A Particle Swarm Optimization (PSO) algorithm has been used in conjunction with a full-wave numerical code based on the Method of Moments (MoM) to design and optimize wire antennas. The PSO is a robust stochastic evolutionary numerical technique that is very effective in optimizing multidimensional
An Algorithm for the Design of an Axial Flow Compressor of a Power ...
African Journals Online (AJOL)
This paper focuses on the development of an algorithm for designing an axial flow compressor for a power generation gas turbine and attempts to bring to the public domain some parameters regarded as propriety data by plant manufacturers. The theory used in this work is based on simple thermodynamics and ...
Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm
Directory of Open Access Journals (Sweden)
Lianghong Wu
2011-08-01
Full Text Available This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE algorithm. The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE, which adopts an adaptive mutation operator that combines with the advantages of the DE/rand/1/bin strategy and the DE/best/2/bin strategy. As a result, its convergence performance is improved greatly. Numerical experiment results confirm the conclusion. The proposedSAMDE approach is effectively applied to test a numerical example and is compared with previous design methods. The computational experiments show that the SAMDE approach can obtain better results than previous design methods.
Optimal Design of Pumped Pipeline Systems Using Genetic Algorithm and Mathematical Optimization
Directory of Open Access Journals (Sweden)
Mohammadhadi Afshar
2007-12-01
Full Text Available In recent years, much attention has been paid to the optimal design of pipeline systems. In this study, the problem of pipeline system optimal design has been solved through genetic algorithm and mathematical optimization. Pipe diameters and their thicknesses are considered as decision variables to be designed in a manner that water column separation and excessive pressures are avoided in the event of pump failure. Capabilities of the genetic algorithm and the mathematical programming method are compared for the problem under consideration. For simulation of transient streams, explicit characteristic method is used in which devices such as pumps are defined as boundary conditions of the equations defining the hydraulic behavior of pipe segments. The problem of optimal design of pipeline systems is a constrained problem which is converted to an unconstrained optimization problem using an external penalty function approach. The efficiency of the proposed approaches is verified in one example and the results are presented.
Computational issues in alternating projection algorithms for fixed-order control design
DEFF Research Database (Denmark)
Beran, Eric Bengt; Grigoriadis, K.
1997-01-01
Alternating projection algorithms have been introduced recently to solve fixed-order controller design problems described by linear matrix inequalities and non-convex coupling rank constraints. In this work, an extensive numerical experimentation using proposed benchmark fixed-order control design...... examples is used to indicate the computational efficiency of the method. These results indicate that the proposed alternating projections are effective in obtaining low-order controllers for small and medium order problems...
Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong
2018-01-01
Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.
Directory of Open Access Journals (Sweden)
Kazem Mohammadi- Aghdam
2015-10-01
Full Text Available This paper proposes the application of a new version of the heuristic particle swarm optimization (PSO method for designing water distribution networks (WDNs. The optimization problem of looped water distribution networks is recognized as an NP-hard combinatorial problem which cannot be easily solved using traditional mathematical optimization techniques. In this paper, the concept of dynamic swarm size is considered in an attempt to increase the convergence speed of the original PSO algorithm. In this strategy, the size of the swarm is dynamically changed according to the iteration number of the algorithm. Furthermore, a novel mutation approach is introduced to increase the diversification property of the PSO and to help the algorithm to avoid trapping in local optima. The new version of the PSO algorithm is called dynamic mutated particle swarm optimization (DMPSO. The proposed DMPSO is then applied to solve WDN design problems. Finally, two illustrative examples are used for comparison to verify the efficiency of the proposed DMPSO as compared to other intelligent algorithms.
Lee, Donggil; Lee, Kyounghoon; Kim, Seonghun; Yang, Yongsu
2015-04-01
An automatic abalone grading algorithm that estimates abalone weights on the basis of computer vision using 2D images is developed and tested. The algorithm overcomes the problems experienced by conventional abalone grading methods that utilize manual sorting and mechanical automatic grading. To design an optimal algorithm, a regression formula and R(2) value were investigated by performing a regression analysis for each of total length, body width, thickness, view area, and actual volume against abalone weights. The R(2) value between the actual volume and abalone weight was 0.999, showing a relatively high correlation. As a result, to easily estimate the actual volumes of abalones based on computer vision, the volumes were calculated under the assumption that abalone shapes are half-oblate ellipsoids, and a regression formula was derived to estimate the volumes of abalones through linear regression analysis between the calculated and actual volumes. The final automatic abalone grading algorithm is designed using the abalone volume estimation regression formula derived from test results, and the actual volumes and abalone weights regression formula. In the range of abalones weighting from 16.51 to 128.01 g, the results of evaluation of the performance of algorithm via cross-validation indicate root mean square and worst-case prediction errors of are 2.8 and ±8 g, respectively. © 2015 Institute of Food Technologists®
Latief, Y.; Berawi, M. A.; Koesalamwardi, A. B.; Supriadi, L. S. R.
2018-03-01
Near Zero Energy House (NZEH) is a housing building that provides energy efficiency by using renewable energy technologies and passive house design. Currently, the costs for NZEH are quite expensive due to the high costs of the equipment and materials for solar panel, insulation, fenestration and other renewable energy technology. Therefore, a study to obtain the optimum design of a NZEH is necessary. The aim of the optimum design is achieving an economical life cycle cost performance of the NZEH. One of the optimization methods that could be utilized is Genetic Algorithm. It provides the method to obtain the optimum design based on the combinations of NZEH variable designs. This paper discusses the study to identify the optimum design of a NZEH that provides an optimum life cycle cost performance using Genetic Algorithm. In this study, an experiment through extensive design simulations of a one-level house model was conducted. As a result, the study provide the optimum design from combinations of NZEH variable designs, which are building orientation, window to wall ratio, and glazing types that would maximize the energy generated by photovoltaic panel. Hence, the design would support an optimum life cycle cost performance of the house.
Directory of Open Access Journals (Sweden)
Zhang Ziran
2018-01-01
Full Text Available In the study, context-creativity of Teresa M. Amabile was used as The foundation to apply it in the bags & luggage design course. Moreover, the sectional creative training education mode of prior heuristic task and postpositional algorithmic task was proposed. 26 junior students in product design were used as the trial objects. The Consensual Technique for Creativity (CAT was considered as the scoring standard of creative performance. In the end, the sectional theoretical framework of effective creative training in product design was finally proposed.
Design and Implementation of the Automated Rendezvous Targeting Algorithms for Orion
DSouza, Christopher; Weeks, Michael
2010-01-01
The Orion vehicle will be designed to perform several rendezvous missions: rendezvous with the ISS in Low Earth Orbit (LEO), rendezvous with the EDS/Altair in LEO, a contingency rendezvous with the ascent stage of the Altair in Low Lunar Orbit (LLO) and a contingency rendezvous in LLO with the ascent and descent stage in the case of an aborted lunar landing. Therefore, it is not difficult to realize that each of these scenarios imposes different operational, timing, and performance constraints on the GNC system. To this end, a suite of on-board guidance and targeting algorithms have been designed to meet the requirement to perform the rendezvous independent of communications with the ground. This capability is particularly relevant for the lunar missions, some of which may occur on the far side of the moon. This paper will describe these algorithms which are designed to be structured and arranged in such a way so as to be flexible and able to safely perform a wide variety of rendezvous trajectories. The goal of the algorithms is not to merely fly one specific type of canned rendezvous profile. Conversely, it was designed from the start to be general enough such that any type of trajectory profile can be flown.(i.e. a coelliptic profile, a stable orbit rendezvous profile, and a expedited LLO rendezvous profile, etc) all using the same rendezvous suite of algorithms. Each of these profiles makes use of maneuver types which have been designed with dual goals of robustness and performance. They are designed to converge quickly under dispersed conditions and they are designed to perform many of the functions performed on the ground today. The targeting algorithms consist of a phasing maneuver (NC), an altitude adjust maneuver (NH), and plane change maneuver (NPC), a coelliptic maneuver (NSR), a Lambert targeted maneuver, and several multiple-burn targeted maneuvers which combine one of more of these algorithms. The derivation and implementation of each of these
Homotopy Algorithm for Fixed Order Mixed H2/H(infinity) Design
Whorton, Mark; Buschek, Harald; Calise, Anthony J.
1996-01-01
Recent developments in the field of robust multivariable control have merged the theories of H-infinity and H-2 control. This mixed H-2/H-infinity compensator formulation allows design for nominal performance by H-2 norm minimization while guaranteeing robust stability to unstructured uncertainties by constraining the H-infinity norm. A key difficulty associated with mixed H-2/H-infinity compensation is compensator synthesis. A homotopy algorithm is presented for synthesis of fixed order mixed H-2/H-infinity compensators. Numerical results are presented for a four disk flexible structure to evaluate the efficiency of the algorithm.
Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design Processes
Rogers, James L.; McCulley, Collin M.; Bloebaum, Christina L.
1996-01-01
The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.
Evolving spiking neural networks: a novel growth algorithm exhibits unintelligent design
Schaffer, J. David
2015-06-01
Spiking neural networks (SNNs) have drawn considerable excitement because of their computational properties, believed to be superior to conventional von Neumann machines, and sharing properties with living brains. Yet progress building these systems has been limited because we lack a design methodology. We present a gene-driven network growth algorithm that enables a genetic algorithm (evolutionary computation) to generate and test SNNs. The genome for this algorithm grows O(n) where n is the number of neurons; n is also evolved. The genome not only specifies the network topology, but all its parameters as well. Experiments show the algorithm producing SNNs that effectively produce a robust spike bursting behavior given tonic inputs, an application suitable for central pattern generators. Even though evolution did not include perturbations of the input spike trains, the evolved networks showed remarkable robustness to such perturbations. In addition, the output spike patterns retain evidence of the specific perturbation of the inputs, a feature that could be exploited by network additions that could use this information for refined decision making if required. On a second task, a sequence detector, a discriminating design was found that might be considered an example of "unintelligent design"; extra non-functional neurons were included that, while inefficient, did not hamper its proper functioning.
New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.
Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng
2016-05-16
The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.
Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers.
Church, Philip C; Goscinski, Andrzej; Holt, Kathryn; Inouye, Michael; Ghoting, Amol; Makarychev, Konstantin; Reumann, Matthias
2011-01-01
The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.
International Nuclear Information System (INIS)
Chen, Wang Chih; Chen Jahau Lewis
2014-01-01
The work proposes a new design tool that integrates design-around concepts with the algorithm for inventive problem solving (Russian acronym: ARIZ). ARIZ includes a complete procedure for analyzing problems and related resource, resolving conflicts and generating solutions. The combination of ARIZ and design-around concepts and understanding identified principles that govern patent infringements can prevent patent infringements whenever designers innovate, greatly reducing the cost and time associated with the product design stage. The presented tool is developed from an engineering perspective rather than a legal perspective, and so can help designers easily to prevent patent infringements and succeed in innovating by designing around. An example is used to demonstrate the proposed method.
VLSI Design Tools, Reference Manual, Release 2.0.
1984-08-01
eder. 2.3 ITACV: Libary ofC readne. far oesumdg a layoit 1-,, tiling. V ~2.4 "QUILT: CeinS"Wbesa-i-M-8euar ray f atwok til 2.5 "TIL: Tockmeleff...8217patterns package was added so that complex and repetitive digital waveforms could be generated far more easily. The recently written program MTP (Multiple...circuit model to estimate timing delays through digital circuits. It also has a mode that allows it to be used as a switch (gate) level simulator
Opto-VLSI-based reconfigurable free-space optical interconnects architecture
DEFF Research Database (Denmark)
Aljada, Muhsen; Alameh, Kamal; Chung, Il-Sug
2007-01-01
is the Opto-VLSI processor which can be driven by digital phase steering and multicasting holograms that reconfigure the optical interconnects between the input and output ports. The optical interconnects architecture is experimentally demonstrated at 2.5 Gbps using high-speed 1×3 VCSEL array and 1......×3 photoreceiver array in conjunction with two 1×4096 pixel Opto-VLSI processors. The minimisation of the crosstalk between the output ports is achieved by appropriately aligning the VCSEL and PD elements with respect to the Opto-VLSI processors and driving the latter with optimal steering phase holograms....
International Nuclear Information System (INIS)
Martin-del-Campo, Cecilia; Francois, Juan Luis; Avendano, Linda; Gonzalez, Mario
2004-01-01
An optimization system based on Genetic Algorithms (GAs), in combination with expert knowledge coded in heuristics rules, was developed for the design of optimized boiling water reactor (BWR) fuel loading patterns. The system was coded in a computer program named Loading Pattern Optimization System based on Genetic Algorithms, in which the optimization code uses GAs to select candidate solutions, and the core simulator code CM-PRESTO to evaluate them. A multi-objective function was built to maximize the cycle energy length while satisfying power and reactivity constraints used as BWR design parameters. Heuristic rules were applied to satisfy standard fuel management recommendations as the Control Cell Core and Low Leakage loading strategies, and octant symmetry. To test the system performance, an optimized cycle was designed and compared against an actual operating cycle of Laguna Verde Nuclear Power Plant, Unit I
GST-PRIME: an algorithm for genome-wide primer design.
Leister, Dario; Varotto, Claudio
2007-01-01
The profiling of mRNA expression based on DNA arrays has become a powerful tool to study genome-wide transcription of genes in a number of organisms. GST-PRIME is a software package created to facilitate large-scale primer design for the amplification of probes to be immobilized on arrays for transcriptome analyses, even though it can be also applied in low-throughput approaches. GST-PRIME allows highly efficient, direct amplification of gene-sequence tags (GSTs) from genomic DNA (gDNA), starting from annotated genome or transcript sequences. GST-PRIME provides a customer-friendly platform for automatic primer design, and despite the relative simplicity of the algorithm, experimental tests in the model plant species Arabidopsis thaliana confirmed the reliability of the software. This chapter describes the algorithm used for primer design, its input and output files, and the installation of the standalone package and its use.
Improved PSO algorithm based on chaos theory and its application to design flood hydrograph
Directory of Open Access Journals (Sweden)
Si-Fang Dong
2010-06-01
Full Text Available The deficiencies of basic particle swarm optimization (bPSO are its ubiquitous prematurity and its inability to seek the global optimal solution when optimizing complex high-dimensional functions. To overcome such deficiencies, the chaos-PSO (COSPSO algorithm was established by introducing the chaos optimization mechanism and a global particle stagnation-disturbance strategy into bPSO. In the improved algorithm, chaotic movement was adopted for the particles' initial movement trajectories to replace the former stochastic movement, and the chaos factor was used to guide the particles' path. When the global particles were stagnant, the disturbance strategy was used to keep the particles in motion. Five benchmark optimizations were introduced to test COSPSO, and they proved that COSPSO can remarkably improve efficiency in optimizing complex functions. Finally, a case study of COSPSO in calculating design flood hydrographs demonstrated the applicability of the improved algorithm.
Multi-objective optimal design of sandwich panels using a genetic algorithm
Xu, Xiaomei; Jiang, Yiping; Pueh Lee, Heow
2017-10-01
In this study, an optimization problem concerning sandwich panels is investigated by simultaneously considering the two objectives of minimizing the panel mass and maximizing the sound insulation performance. First of all, the acoustic model of sandwich panels is discussed, which provides a foundation to model the acoustic objective function. Then the optimization problem is formulated as a bi-objective programming model, and a solution algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is provided to solve the proposed model. Finally, taking an example of a sandwich panel that is expected to be used as an automotive roof panel, numerical experiments are carried out to verify the effectiveness of the proposed model and solution algorithm. Numerical results demonstrate in detail how the core material, geometric constraints and mechanical constraints impact the optimal designs of sandwich panels.
Directory of Open Access Journals (Sweden)
Yu Wang
2015-01-01
Full Text Available This paper presents a multiobjective mathematical programming model to optimize airline fleet size and structure with consideration of several critical factors severely affecting the fleet planning process. The main purpose of this paper is to reveal how multiairline competitive behaviors impact airline fleet size and structure by enhancing the existing route-based fleet planning model with consideration of the interaction between market share and flight frequency and also by applying the concept of equilibrium optimum to design heuristic algorithm for solving the model. Through case study and comparison, the heuristic algorithm is proved to be effective. By using the algorithm presented in this paper, the fleet operational profit is significantly increased compared with the use of the existing route-based model. Sensitivity analysis suggests that the fleet size and structure are more sensitive to the increase of fare price than to the increase of passenger demand.
Son, Min; Ko, Sangho; Koo, Jaye
2014-06-01
A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was applied, and the profile was calculated using Rao's method. One-dimensional heat transfer was assumed along the profile, and cooling channels were designed. For the gas-generator design, non-equilibrium properties were derived from a counterflow analysis, and a vaporization model for the fuel droplet was adopted to calculate residence time. Finally, a genetic algorithm was adopted to optimize the designs. The combustor and gas generator were optimally designed for 30-tonf, 75-tonf, and 150-tonf engines. The optimized combustors demonstrated superior design characteristics when compared with previous non-optimized results. Wall temperatures at the nozzle throat were optimized to satisfy the requirement of 800 K, and specific impulses were maximized. In addition, the target turbine power and a burned-gas temperature of 1000 K were obtained from the optimized gas-generator design.
Design of intelligent locks based on the triple KeeLoq algorithm
Directory of Open Access Journals (Sweden)
Huibin Chen
2016-04-01
Full Text Available KeeLoq algorithm with high security was usually used in wireless codec. Its security lack is indicated in this article according to the detailed rationale and the introduction of previous attack researches. Taking examples from Triple Data Encryption Standard algorithm, the triple KeeLoq codec algorithm was first proposed. Experimental results showed that the algorithm would not reduce powerful rolling effect and in consideration of limited computing power of embedded microcontroller three 64-bit keys were suitable to increase the crack difficulties and further improved its security. The method was applied to intelligent door access system for experimental verification. 16F690 extended Bluetooth or WiFi interface was employed to design the lock system on door. Key application was constructed on Android platform. The wireless communication between the lock on door and Android key application employed triple KeeLoq algorithm to ensure the higher security. Due to flexibility and multiformity (an Android key application with various keys of software-based keys, the solution owned overwhelmed advantages of low cost, high security, humanity, and green environmental protection.
Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm
Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung
2016-07-01
In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.
Multi-machine power system stabilizers design using chaotic optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Shayeghi, H., E-mail: hshayeghi@gmail.co [Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power System Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Jalilzadeh, S.; Safari, A. [Technical Engineering Department, Zanjan University, Zanjan (Iran, Islamic Republic of)
2010-07-15
In this paper, a multiobjective design of the multi-machine power system stabilizers (PSSs) using chaotic optimization algorithm (COA) is proposed. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from the local optimum, is a promising tool for the engineering applications. The PSSs parameters tuning problem is converted to an optimization problem which is solved by a chaotic optimization algorithm based on Lozi map. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization problem introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. Two different objective functions are proposed in this study for the PSSs design problem. The first objective function is the eigenvalues based comprising the damping factor, and the damping ratio of the lightly damped electro-mechanical modes, while the second is the time domain-based multi-objective function. The robustness of the proposed COA-based PSSs (COAPSS) is verified on a multi-machine power system under different operating conditions and disturbances. The results of the proposed COAPSS are demonstrated through eigenvalue analysis, nonlinear time-domain simulation and some performance indices. In addition, the potential and superiority of the proposed method over the classical approach and genetic algorithm is demonstrated.
Solution Algorithm for a New Bi-Level Discrete Network Design Problem
Directory of Open Access Journals (Sweden)
Qun Chen
2013-12-01
Full Text Available A new discrete network design problem (DNDP was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.
Directory of Open Access Journals (Sweden)
Yue Wu
2017-01-01
Full Text Available Firefly Algorithm (FA, for short is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.
Directory of Open Access Journals (Sweden)
Yi Zhang
2012-01-01
Full Text Available In consideration of the significant role the brake plays in ensuring the fast and safe running of vehicles, and since the present parameter optimization design models of brake are far from the practical application, this paper proposes a multiobjective optimization model of drum brake, aiming at maximizing the braking efficiency and minimizing the volume and temperature rise of drum brake. As the commonly used optimization algorithms are of some deficiency, we present a differential evolution cellular multiobjective genetic algorithm (DECell by introducing differential evolution strategy into the canonical cellular genetic algorithm for tackling this problem. For DECell, the gained Pareto front could be as close as possible to the exact Pareto front, and also the diversity of nondominated individuals could be better maintained. The experiments on the test functions reveal that DECell is of good performance in solving high-dimension nonlinear multiobjective problems. And the results of optimizing the new brake model indicate that DECell obviously outperforms the compared popular algorithm NSGA-II concerning the number of obtained brake design parameter sets, the speed, and stability for finding them.
Directory of Open Access Journals (Sweden)
Ali Akbar Hasani
2016-11-01
Full Text Available In this paper, a comprehensive model is proposed to design a network for multi-period, multi-echelon, and multi-product inventory controlled the supply chain. Various marketing strategies and guerrilla marketing approaches are considered in the design process under the static competition condition. The goal of the proposed model is to efficiently respond to the customers’ demands in the presence of the pre-existing competitors and the price inelasticity of demands. The proposed optimization model considers multiple objectives that incorporate both market share and total profit of the considered supply chain network, simultaneously. To tackle the proposed multi-objective mixed-integer nonlinear programming model, an efficient hybrid meta-heuristic algorithm is developed that incorporates a Taguchi-based non-dominated sorting genetic algorithm-II and a particle swarm optimization. A variable neighborhood decomposition search is applied to enhance a local search process of the proposed hybrid solution algorithm. Computational results illustrate that the proposed model and solution algorithm are notably efficient in dealing with the competitive pressure by adopting the proper marketing strategies.
Fan, Xiao-Ning; Zhi, Bo
2017-07-01
Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization (RBDO) offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliability strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reliability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its α-percentile performance, thereby avoiding convergence failure, calculation error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.
A parallel row-based algorithm for standard cell placement with integrated error control
Sargent, Jeff S.; Banerjee, Prith
1989-01-01
A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel approaches to control error in parallel cell-placement algorithms: (1) Heuristic Cell-Coloring; (2) Adaptive Sequence Length Control.
Optimization Design by Genetic Algorithm Controller for Trajectory Control of a 3-RRR Parallel Robot
Directory of Open Access Journals (Sweden)
Lianchao Sheng
2018-01-01
Full Text Available In order to improve the control precision and robustness of the existing proportion integration differentiation (PID controller of a 3-Revolute–Revolute–Revolute (3-RRR parallel robot, a variable PID parameter controller optimized by a genetic algorithm controller is proposed in this paper. Firstly, the inverse kinematics model of the 3-RRR parallel robot was established according to the vector method, and the motor conversion matrix was deduced. Then, the error square integral was chosen as the fitness function, and the genetic algorithm controller was designed. Finally, the control precision of the new controller was verified through the simulation model of the 3-RRR planar parallel robot—built in SimMechanics—and the robustness of the new controller was verified by adding interference. The results show that compared with the traditional PID controller, the new controller designed in this paper has better control precision and robustness, which provides the basis for practical application.
Design of a centrifugal compressor impeller using multi-objective optimization algorithm
International Nuclear Information System (INIS)
Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong; Choi, Jae Ho
2009-01-01
This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with ε-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.
Design of a centrifugal compressor impeller using multi-objective optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong [Inha University, Incheon (Korea, Republic of); Choi, Jae Ho [Samsung Techwin Co., Ltd., Changwon (Korea, Republic of)
2009-07-01
This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with {epsilon}-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.
Thickness determination in textile material design: dynamic modeling and numerical algorithms
International Nuclear Information System (INIS)
Xu, Dinghua; Ge, Meibao
2012-01-01
Textile material design is of paramount importance in the study of functional clothing design. It is therefore important to determine the dynamic heat and moisture transfer characteristics in the human body–clothing–environment system, which directly determine the heat–moisture comfort level of the human body. Based on a model of dynamic heat and moisture transfer with condensation in porous fabric at low temperature, this paper presents a new inverse problem of textile thickness determination (IPTTD). Adopting the idea of the least-squares method, we formulate the IPTTD into a function minimization problem. By means of the finite-difference method, quasi-solution method and direct search method for one-dimensional minimization problems, we construct iterative algorithms of the approximated solution for the IPTTD. Numerical simulation results validate the formulation of the IPTTD and demonstrate the effectiveness of the proposed numerical algorithms. (paper)
Custom VLSI circuits for high energy physics
International Nuclear Information System (INIS)
Parker, S.
1998-06-01
This article provides a brief guide to integrated circuits, including their design, fabrication, testing, radiation hardness, and packaging. It was requested by the Panel on Instrumentation, Innovation, and Development of the International Committee for Future Accelerators, as one of a series of articles on instrumentation for future experiments. Their original request emphasized a description of available custom circuits and a set of recommendations for future developments. That has been done, but while traps that stop charge in solid-state devices are well known, those that stop physicists trying to develop the devices are not. Several years spent dodging the former and developing the latter made clear the need for a beginner's guide through the maze, and that is the main purpose of this text
Custom VLSI circuits for high energy physics
Energy Technology Data Exchange (ETDEWEB)
Parker, S. [Univ. of Hawaii, Honolulu, HI (United States)
1998-06-01
This article provides a brief guide to integrated circuits, including their design, fabrication, testing, radiation hardness, and packaging. It was requested by the Panel on Instrumentation, Innovation, and Development of the International Committee for Future Accelerators, as one of a series of articles on instrumentation for future experiments. Their original request emphasized a description of available custom circuits and a set of recommendations for future developments. That has been done, but while traps that stop charge in solid-state devices are well known, those that stop physicists trying to develop the devices are not. Several years spent dodging the former and developing the latter made clear the need for a beginner`s guide through the maze, and that is the main purpose of this text.
Pop, Paul; Madsen, Jan
2016-01-01
This book presents the state-of-the-art techniques for the modeling, simulation, testing, compilation and physical synthesis of mVLSI biochips. The authors describe a top-down modeling and synthesis methodology for the mVLSI biochips, inspired by microelectronics VLSI methodologies. They introduce a modeling framework for the components and the biochip architecture, and a high-level microfluidic protocol language. Coverage includes a topology graph-based model for the biochip architecture, and a sequencing graph to model for biochemical application, showing how the application model can be obtained from the protocol language. The techniques described facilitate programmability and automation, enabling developers in the emerging, large biochip market. · Presents the current models used for the research on compilation and synthesis techniques of mVLSI biochips in a tutorial fashion; · Includes a set of "benchmarks", that are presented in great detail and includes the source code of several of the techniques p...
Hardware Algorithm Implementation for Mission Specific Processing
2008-03-01
knowledge about the VLSI technology and understands VHDL, scripting, and intergrating the script in Cadencersoftware pro- gram or Modelsimr. The main...possible to have a trade off between parallel and serial logic design for the circuit. Power can be saved by using parallization, pipelining, or a
ALE-PSO: An Adaptive Swarm Algorithm to Solve Design Problems of Laminates
Directory of Open Access Journals (Sweden)
Paolo Vannucci
2009-04-01
Full Text Available This paper presents an adaptive PSO algorithm whose numerical parameters can be updated following a scheduled protocol respecting some known criteria of convergence in order to enhance the chances to reach the global optimum of a hard combinatorial optimization problem, such those encountered in global optimization problems of composite laminates. Some examples concerning hard design problems are provided, showing the effectiveness of the approach.
Design and Implementation of DC-DC Converter with Inc-Cond Algorithm
Mustafa Engin Basoğlu; Bekir Çakır
2015-01-01
The most important component affecting the efficiency of photovoltaic power systems are solar panels. In other words, efficiency of these systems are significantly affected due to the being low efficiency of solar panel. Thus, solar panels should be operated under maximum power point conditions through a power converter. In this study, design of boost converter has been carried out with maximum power point tracking (MPPT) algorithm which is incremental conductance (Inc-Co...
International Nuclear Information System (INIS)
Schalkoff, R.J.; Shaaban, K.M.; Carver, A.E.
1996-01-01
The ARIES number-sign 1 (Autonomous Robotic Inspection Experimental System) vision system is used to acquire drum surface images under controlled conditions and subsequently perform autonomous visual inspection leading to a classification as 'acceptable' or 'suspect'. Specific topics described include vision system design methodology, algorithmic structure,hardware processing structure, and image acquisition hardware. Most of these capabilities were demonstrated at the ARIES Phase II Demo held on Nov. 30, 1995. Finally, Phase III efforts are briefly addressed
Phan, Thanh Duoc; Lim, James; Tanyimboh, Tiku T.; Sha, Wei
2013-01-01
The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. Previous GAs in the literature were characterized by poor convergence, including slow progress, that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal sol...
Prototype architecture for a VLSI level zero processing system. [Space Station Freedom
Shi, Jianfei; Grebowsky, Gerald J.; Horner, Ward P.; Chesney, James R.
1989-01-01
The prototype architecture and implementation of a high-speed level zero processing (LZP) system are discussed. Due to the new processing algorithm and VLSI technology, the prototype LZP system features compact size, low cost, high processing throughput, and easy maintainability and increased reliability. Though extensive control functions have been done by hardware, the programmability of processing tasks makes it possible to adapt the system to different data formats and processing requirements. It is noted that the LZP system can handle up to 8 virtual channels and 24 sources with combined data volume of 15 Gbytes per orbit. For greater demands, multiple LZP systems can be configured in parallel, each called a processing channel and assigned a subset of virtual channels. The telemetry data stream will be steered into different processing channels in accordance with their virtual channel IDs. This super system can cope with a virtually unlimited number of virtual channels and sources. In the near future, it is expected that new disk farms with data rate exceeding 150 Mbps will be available from commercial vendors due to the advance in disk drive technology.
International Nuclear Information System (INIS)
Azadeh, A.; Tarverdian, S.
2007-01-01
This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on genetic algorithm (GA), computer simulation and design of experiments using stochastic procedures. First, time-series model is developed as a benchmark for GA and simulation. Computer simulation is developed to generate random variables for monthly electricity consumption. This is achieved to foresee the effects of probabilistic distribution on monthly electricity consumption. The GA and simulated-based GA models are then developed by the selected time-series model. Therefore, there are four treatments to be considered in analysis of variance (ANOVA) which are actual data, time series, GA and simulated-based GA. Furthermore, ANOVA is used to test the null hypothesis of the above four alternatives being equal. If the null hypothesis is accepted, then the lowest mean absolute percentage error (MAPE) value is used to select the best model, otherwise the Duncan Multiple Range Test (DMRT) method of paired comparison is used to select the optimum model, which could be time series, GA or simulated-based GA. In case of ties the lowest MAPE value is considered as the benchmark. The integrated algorithm has several unique features. First, it is flexible and identifies the best model based on the results of ANOVA and MAPE, whereas previous studies consider the best-fit GA model based on MAPE or relative error results. Second, the proposed algorithm may identify conventional time series as the best model for future electricity consumption forecasting because of its dynamic structure, whereas previous studies assume that GA always provide the best solutions and estimation. To show the applicability and superiority of the proposed algorithm, the monthly electricity consumption in Iran from March 1994 to February 2005 (131 months) is used and applied to the proposed algorithm
A methodology for the geometric design of heat recovery steam generators applying genetic algorithms
International Nuclear Information System (INIS)
Durán, M. Dolores; Valdés, Manuel; Rovira, Antonio; Rincón, E.
2013-01-01
This paper shows how the geometric design of heat recovery steam generators (HRSG) can be achieved. The method calculates the product of the overall heat transfer coefficient (U) by the area of the heat exchange surface (A) as a function of certain thermodynamic design parameters of the HRSG. A genetic algorithm is then applied to determine the best set of geometric parameters which comply with the desired UA product and, at the same time, result in a small heat exchange area and low pressure losses in the HRSG. In order to test this method, the design was applied to the HRSG of an existing plant and the results obtained were compared with the real exchange area of the steam generator. The findings show that the methodology is sound and offers reliable results even for complex HRSG designs. -- Highlights: ► The paper shows a methodology for the geometric design of heat recovery steam generators. ► Calculates product of the overall heat transfer coefficient by heat exchange area as a function of certain HRSG thermodynamic design parameters. ► It is a complement for the thermoeconomic optimization method. ► Genetic algorithms are used for solving the optimization problem
Directory of Open Access Journals (Sweden)
Andreas König
2009-11-01
Full Text Available The emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain of the computational system model still has to be assembled manually by experienced designers in a time and labor consuming process. In this research work, this challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multi-sensor systems employing multi-objective evolutionary computation are introduced. The proposed methodology tackles the challenge of rapid-prototyping of such systems under realization constraints and, additionally, includes features of system instance specific self-correction for sustained operation of a large volume and in a dynamically changing environment. The extension of these concepts to the reconfigurable hardware platform renders so called self-x sensor systems, which stands, e.g., for self-monitoring, -calibrating, -trimming, and -repairing/-healing systems. Selected experimental results prove the applicability and effectiveness of our proposed methodology and emerging tool. By our approach, competitive results were achieved with regard to classification accuracy, flexibility, and design speed under additional design constraints.
Conceptual design based on scale laws and algorithms for sub-critical transmutation reactors
Energy Technology Data Exchange (ETDEWEB)
Lee, Kwang Gu; Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)
1997-12-31
In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making for both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors. 6 refs., 5 figs., 1 tab. (Author)
Conceptual design based on scale laws and algorithms for sub-critical transmutation reactors
Energy Technology Data Exchange (ETDEWEB)
Lee, Kwang Gu; Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)
1998-12-31
In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making for both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors. 6 refs., 5 figs., 1 tab. (Author)
A VR Based Interactive Genetic Algorithm Framework For Design of Support Schemes to Deep Excavations
International Nuclear Information System (INIS)
Wei, Riyu; Wu, Heng
2002-01-01
An interactive genetic algorithm (IGA) framework for the design of support schemes to deep excavations is proposed in this paper, in which virtual reality (VR) is used as an aid to the evaluation of design schemes that is performed interactively. The fitness of a scheme individual is evaluated by two steps. Firstly a fitness value is automatically assigned to a scheme individual according to the the estimated construction cost of the individual. And the human evaluation is introduced to modify the fitness value by taking into account other factors, such as the feasibility factor. The design scheme is composed of four basic categories, i. e., cantilever walls, reinforced soil walls, tieback systems and bracing systems, each of which is encoded by a binary string. To assist human evaluation, 3D models of design schemes are created and visualized in a virtual reality environment, providing designers with a reality sense of various schemes
Directory of Open Access Journals (Sweden)
Jie Zhang
2013-01-01
Full Text Available In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.
Zhang, Jie; Wang, Yuping; Feng, Junhong
2013-01-01
In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.
Optimum Design of Gravity Retaining Walls Using Charged System Search Algorithm
Directory of Open Access Journals (Sweden)
S. Talatahari
2012-01-01
Full Text Available This study focuses on the optimum design retaining walls, as one of the familiar types of the retaining walls which may be constructed of stone masonry, unreinforced concrete, or reinforced concrete. The material cost is one of the major factors in the construction of gravity retaining walls therefore, minimizing the weight or volume of these systems can reduce the cost. To obtain an optimal seismic design of such structures, this paper proposes a method based on a novel meta-heuristic algorithm. The algorithm is inspired by the Coulomb's and Gauss’s laws of electrostatics in physics, and it is called charged system search (CSS. In order to evaluate the efficiency of this algorithm, an example is utilized. Comparing the results of the retaining wall designs obtained by the other methods illustrates a good performance of the CSS. In this paper, we used the Mononobe-Okabe method which is one of the pseudostatic approaches to determine the dynamic earth pressure.
Multiobjective pressurized water reactor reload core design by nondominated genetic algorithm search
International Nuclear Information System (INIS)
Parks, G.T.
1996-01-01
The design of pressurized water reactor reload cores is not only a formidable optimization problem but also, in many instances, a multiobjective problem. A genetic algorithm (GA) designed to perform true multiobjective optimization on such problems is described. Genetic algorithms simulate natural evolution. They differ from most optimization techniques by searching from one group of solutions to another, rather than from one solution to another. New solutions are generated by breeding from existing solutions. By selecting better (in a multiobjective sense) solutions as parents more often, the population can be evolved to reveal the trade-off surface between the competing objectives. An example illustrating the effectiveness of this novel method is presented and analyzed. It is found that in solving a reload design problem the algorithm evaluates a similar number of loading patterns to other state-of-the-art methods, but in the process reveals much more information about the nature of the problem being solved. The actual computational cost incurred depends on the core simulator used; the GA itself is code independent
Ushijima, Timothy T.; Yeh, William W.-G.
2013-10-01
An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.
A Single Chip VLSI Implementation of a QPSK/SQPSK Demodulator for a VSAT Receiver Station
Kwatra, S. C.; King, Brent
1995-01-01
This thesis presents a VLSI implementation of a QPSK/SQPSK demodulator. It is designed to be employed in a VSAT earth station that utilizes the FDMA/TDM link. A single chip architecture is used to enable this chip to be easily employed in the VSAT system. This demodulator contains lowpass filters, integrate and dump units, unique word detectors, a timing recovery unit, a phase recovery unit and a down conversion unit. The design stages start with a functional representation of the system by using the C programming language. Then it progresses into a register based representation using the VHDL language. The layout components are designed based on these VHDL models and simulated. Component generators are developed for the adder, multiplier, read-only memory and serial access memory in order to shorten the design time. These sub-components are then block routed to form the main components of the system. The main components are block routed to form the final demodulator.
A fast algorithm for estimating transmission probabilities in QTL detection designs with dense maps
Directory of Open Access Journals (Sweden)
Gilbert Hélène
2009-11-01
Full Text Available Abstract Background In the case of an autosomal locus, four transmission events from the parents to progeny are possible, specified by the grand parental origin of the alleles inherited by this individual. Computing the probabilities of these transmission events is essential to perform QTL detection methods. Results A fast algorithm for the estimation of these probabilities conditional to parental phases has been developed. It is adapted to classical QTL detection designs applied to outbred populations, in particular to designs composed of half and/or full sib families. It assumes the absence of interference. Conclusion The theory is fully developed and an example is given.
Ferentinos, Konstantinos P
2005-09-01
Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.
International Nuclear Information System (INIS)
Coban, Ramazan
2011-01-01
Research highlights: → A closed-loop fuzzy logic controller based on the particle swarm optimization algorithm was proposed for controlling the power level of nuclear research reactors. → The proposed control system was tested for various initial and desired power levels, and it could control the reactor successfully for most situations. → The proposed controller is robust against the disturbances. - Abstract: In this paper, a closed-loop fuzzy logic controller based on the particle swarm optimization algorithm is proposed for controlling the power level of nuclear research reactors. The principle of the fuzzy logic controller is based on the rules constructed from numerical experiments made by means of a computer code for the core dynamics calculation and from human operator's experience and knowledge. In addition to these intuitive and experimental design efforts, consequent parts of the fuzzy rules are optimally (or near optimally) determined using the particle swarm optimization algorithm. The contribution of the proposed algorithm to a reactor control system is investigated in details. The performance of the controller is also tested with numerical simulations in numerous operating conditions from various initial power levels to desired power levels, as well as under disturbance. It is shown that the proposed control system performs satisfactorily under almost all operating conditions, even in the case of very small initial power levels.
Hardware-Efficient Design of Real-Time Profile Shape Matching Stereo Vision Algorithm on FPGA
Directory of Open Access Journals (Sweden)
Beau Tippetts
2014-01-01
Full Text Available A variety of platforms, such as micro-unmanned vehicles, are limited in the amount of computational hardware they can support due to weight and power constraints. An efficient stereo vision algorithm implemented on an FPGA would be able to minimize payload and power consumption in microunmanned vehicles, while providing 3D information and still leaving computational resources available for other processing tasks. This work presents a hardware design of the efficient profile shape matching stereo vision algorithm. Hardware resource usage is presented for the targeted micro-UV platform, Helio-copter, that uses the Xilinx Virtex 4 FX60 FPGA. Less than a fifth of the resources on this FGPA were used to produce dense disparity maps for image sizes up to 450 × 375, with the ability to scale up easily by increasing BRAM usage. A comparison is given of accuracy, speed performance, and resource usage of a census transform-based stereo vision FPGA implementation by Jin et al. Results show that the profile shape matching algorithm is an efficient real-time stereo vision algorithm for hardware implementation for resource limited systems such as microunmanned vehicles.
Efficient Algorithm and Architecture of Critical-Band Transform for Low-Power Speech Applications
Directory of Open Access Journals (Sweden)
Gan Woon-Seng
2007-01-01
Full Text Available An efficient algorithm and its corresponding VLSI architecture for the critical-band transform (CBT are developed to approximate the critical-band filtering of the human ear. The CBT consists of a constant-bandwidth transform in the lower frequency range and a Brown constant- transform (CQT in the higher frequency range. The corresponding VLSI architecture is proposed to achieve significant power efficiency by reducing the computational complexity, using pipeline and parallel processing, and applying the supply voltage scaling technique. A 21-band Bark scale CBT processor with a sampling rate of 16 kHz is designed and simulated. Simulation results verify its suitability for performing short-time spectral analysis on speech. It has a better fitting on the human ear critical-band analysis, significantly fewer computations, and therefore is more energy-efficient than other methods. With a 0.35 m CMOS technology, it calculates a 160-point speech in 4.99 milliseconds at 234 kHz. The power dissipation is 15.6 W at 1.1 V. It achieves 82.1 power reduction as compared to a benchmark 256-point FFT processor.
Automatic boiling water reactor loading pattern design using ant colony optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Wang, C.-D. [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China); Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China)], E-mail: jdwang@iner.gov.tw; Lin Chaung [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China)
2009-08-15
An automatic boiling water reactor (BWR) loading pattern (LP) design methodology was developed using the rank-based ant system (RAS), which is a variant of the ant colony optimization (ACO) algorithm. To reduce design complexity, only the fuel assemblies (FAs) of one eight-core positions were determined using the RAS algorithm, and then the corresponding FAs were loaded into the other parts of the core. Heuristic information was adopted to exclude the selection of the inappropriate FAs which will reduce search space, and thus, the computation time. When the LP was determined, Haling cycle length, beginning of cycle (BOC) shutdown margin (SDM), and Haling end of cycle (EOC) maximum fraction of limit for critical power ratio (MFLCPR) were calculated using SIMULATE-3 code, which were used to evaluate the LP for updating pheromone of RAS. The developed design methodology was demonstrated using FAs of a reference cycle of the BWR6 nuclear power plant. The results show that, the designed LP can be obtained within reasonable computation time, and has a longer cycle length than that of the original design.
Modeling selective attention using a neuromorphic analog VLSI device.
Indiveri, G
2000-12-01
Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.
PERFORMANCE OF LEAKAGE POWER MINIMIZATION TECHNIQUE FOR CMOS VLSI TECHNOLOGY
Directory of Open Access Journals (Sweden)
T. Tharaneeswaran
2012-06-01
Full Text Available Leakage power of CMOS VLSI Technology is a great concern. To reduce leakage power in CMOS circuits, a Leakage Power Minimiza-tion Technique (LPMT is implemented in this paper. Leakage cur-rents are monitored and compared. The Comparator kicks the charge pump to give body voltage (Vbody. Simulations of these circuits are done using TSMC 0.35µm technology with various operating temper-atures. Current steering Digital-to-Analog Converter (CSDAC is used as test core to validate the idea. The Test core (eg.8-bit CSDAC had power consumption of 347.63 mW. LPMT circuit alone consumes power of 6.3405 mW. This technique results in reduction of leakage power of 8-bit CSDAC by 5.51mW and increases the reliability of test core. Mentor Graphics ELDO and EZ-wave are used for simulations.
International Nuclear Information System (INIS)
Sencan Sahin, Arzu; Kilic, Bayram; Kilic, Ulas
2011-01-01
Highlights: → Artificial Bee Colony for shell and tube heat exchanger optimization is used. → The total cost is minimized by varying design variables. → This new approach can be applied for optimization of heat exchangers. - Abstract: In this study, a new shell and tube heat exchanger optimization design approach is developed. Artificial Bee Colony (ABC) has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size, baffle spacing, etc. Finally, the results are compared to those obtained by literature approaches. The obtained results indicate that Artificial Bee Colony (ABC) algorithm can be successfully applied for optimal design of shell and tube heat exchangers.
Energy Technology Data Exchange (ETDEWEB)
Sencan Sahin, Arzu, E-mail: sencan@tef.sdu.edu.tr [Department of Mechanical Education, Technical Education Faculty, Sueleyman Demirel University, 32260 Isparta (Turkey); Kilic, Bayram, E-mail: bayramkilic@hotmail.com [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey); Kilic, Ulas, E-mail: ulaskilic@mehmetakif.edu.tr [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey)
2011-10-15
Highlights: {yields} Artificial Bee Colony for shell and tube heat exchanger optimization is used. {yields} The total cost is minimized by varying design variables. {yields} This new approach can be applied for optimization of heat exchangers. - Abstract: In this study, a new shell and tube heat exchanger optimization design approach is developed. Artificial Bee Colony (ABC) has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size, baffle spacing, etc. Finally, the results are compared to those obtained by literature approaches. The obtained results indicate that Artificial Bee Colony (ABC) algorithm can be successfully applied for optimal design of shell and tube heat exchangers.
A Rule-Based Local Search Algorithm for General Shift Design Problems in Airport Ground Handling
DEFF Research Database (Denmark)
Clausen, Tommy
We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework with mul......We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework...... with multiple neighborhoods and a loosely coupled rule engine based on simulated annealing is presented. Computational experiments on real-life data from various airport ground handling organization show the performance and flexibility of the proposed algorithm....
Directory of Open Access Journals (Sweden)
Khaled Yassin
2015-08-01
Full Text Available This work aims to optimize the aerodynamic parameters (airfoil chord lengths and twist angles smoothed using Bezier curves of the NREL 5MW wind turbine and a wind turbine designed for site-specific wind conditions to increase the wind turbine's annual energy production (AEP under this site conditions. This optimization process is carried out using a Genetic Algorithm (GA developed in MATLAB and coupled with NREL's FAST Modularization Framework. The results shows that after optimizing the NREL 5MW wind turbine design, the AEP was improved by 5.9% of the baseline design AEP while a site-specific designed wind turbine using Schmitz equations shows 1.2% improvement in AEP. These results shows that optimization of wind turbine blade aerodynamic parameters for site-specific wind conditions leads to improvement in AEP and hence decreasing cost of energy generated by wind turbines.
Robust state feedback controller design of STATCOM using chaotic optimization algorithm
Directory of Open Access Journals (Sweden)
Safari Amin
2010-01-01
Full Text Available In this paper, a new design technique for the design of robust state feedback controller for static synchronous compensator (STATCOM using Chaotic Optimization Algorithm (COA is presented. The design is formulated as an optimization problem which is solved by the COA. Since chaotic planning enjoys reliability, ergodicity and stochastic feature, the proposed technique presents chaos mapping using Lozi map chaotic sequences which increases its convergence rate. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results reveal that the proposed controller has an excellent capability in damping power system low frequency oscillations and enhances greatly the dynamic stability of the power systems. Moreover, the system performance analysis under different operating conditions shows that the phase based controller is superior compare to the magnitude based controller.
Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm
International Nuclear Information System (INIS)
Duan, Chen; Wang, Xinggang; Shu, Shuiming; Jing, Changwei; Chang, Huawei
2014-01-01
Highlights: • An improved thermodynamic model taking into account irreversibility parameter was developed. • A multi-objective optimization method for designing Stirling engine was investigated. • Multi-objective particle swarm optimization algorithm was adopted in the area of Stirling engine for the first time. - Abstract: In the recent years, the interest in Stirling engine has remarkably increased due to its ability to use any heat source from outside including solar energy, fossil fuels and biomass. A large number of studies have been done on Stirling cycle analysis. In the present study, a mathematical model based on thermodynamic analysis of Stirling engine considering regenerative losses and internal irreversibilities has been developed. Power output, thermal efficiency and the cycle irreversibility parameter of Stirling engine are optimized simultaneously using Particle Swarm Optimization (PSO) algorithm, which is more effective than traditional genetic algorithms. In this optimization problem, some important parameters of Stirling engine are considered as decision variables, such as temperatures of the working fluid both in the high temperature isothermal process and in the low temperature isothermal process, dead volume ratios of each heat exchanger, volumes of each working spaces, effectiveness of the regenerator, and the system charge pressure. The Pareto optimal frontier is obtained and the final design solution has been selected by Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP). Results show that the proposed multi-objective optimization approach can significantly outperform traditional single objective approaches
A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train
Directory of Open Access Journals (Sweden)
Wensen Chang
2012-04-01
Full Text Available High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.
A high precision position sensor design and its signal processing algorithm for a maglev train.
Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen
2012-01-01
High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.
VLSI for High-Speed Digital Signal Processing
1994-09-30
particular, the design, layout and fab - rication of integrated circuits. The primary project for this grant has been the design and implementation of a...targeted at 33.36 dB, and PSNR (dB) Rate ( bpp ) the FRSBC algorithm, targeted at 0.5 bits/pixel, respec- Filter FDSBC FRSBC FDSBC FRSBC tively. The filter...to mean square error d by as shown in Fig. 6, is used, yielding a total of 16 subbands. 255’ The rates, in bits per pixel ( bpp ), and the peak signal
Chen, Tinggui; Xiao, Renbin
2014-01-01
Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.
CASTOR a VLSI CMOS mixed analog-digital circuit for low noise multichannel counting applications
International Nuclear Information System (INIS)
Comes, G.; Loddo, F.; Hu, Y.; Kaplon, J.; Ly, F.; Turchetta, R.; Bonvicini, V.; Vacchi, A.
1996-01-01
In this paper we present the design and first experimental results of a VLSI mixed analog-digital 1.2 microns CMOS circuit (CASTOR) for multichannel radiation detectors applications demanding low noise amplification and counting of radiation pulses. This circuit is meant to be connected to pixel-like detectors. Imaging can be obtained by counting the number of hits in each pixel during a user-controlled exposure time. Each channel of the circuit features an analog and a digital part. In the former one, a charge preamplifier is followed by a CR-RC shaper with an output buffer and a threshold discriminator. In the digital part, a 16-bit counter is present together with some control logic. The readout of the counters is done serially on a common tri-state output. Daisy-chaining is possible. A 4-channel prototype has been built. This prototype has been optimised for use in the digital radiography Syrmep experiment at the Elettra synchrotron machine in Trieste (Italy): its main design parameters are: shaping time of about 850 ns, gain of 190 mV/fC and ENC (e - rms)=60+17 C (pF). The counting rate per channel, limited by the analog part, can be as high as about 200 kHz. Characterisation of the circuit and first tests with silicon microstrip detectors are presented. They show the circuit works according to design specification and can be used for imaging applications. (orig.)
The Bilevel Design Problem for Communication Networks on Trains: Model, Algorithm, and Verification
Directory of Open Access Journals (Sweden)
Yin Tian
2014-01-01
Full Text Available This paper proposes a novel method to solve the problem of train communication network design. Firstly, we put forward a general description of such problem. Then, taking advantage of the bilevel programming theory, we created the cost-reliability-delay model (CRD model that consisted of two parts: the physical topology part aimed at obtaining the networks with the maximum reliability under constrained cost, while the logical topology part focused on the communication paths yielding minimum delay based on the physical topology delivered from upper level. We also suggested a method to solve the CRD model, which combined the genetic algorithm and the Floyd-Warshall algorithm. Finally, we used a practical example to verify the accuracy and the effectiveness of the CRD model and further applied the novel method on a train with six carriages.
The methods and algorithms for designing complex three-dimensional robots
International Nuclear Information System (INIS)
Solovjev, A.E.; Naumov, V.B.
1996-01-01
For automation designing by the Robotics laboratory were executed some fundamental and applied researches. This researching allowed to create rational mathematical model for numeric modeling with real-time simulation. In the mathematical model used set of equations of rigid body's motion in Lagrange's form and set of Appel's equations taking into consideration holonomic and non-holonomic connections. In present article are considered methods and algorithms of dynamic modeling of a system of rigid bodies for robotics task and brief description of the package Computer Aided Engineering for Industrial Robots, based on considered algorithms. So far as, in researching of robots the dynamic tasks (direct and inverse) are more interesting than another tasks, authors pay attention just on these problems
Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm
International Nuclear Information System (INIS)
Chaudhary, Kailash; Chaudhary, Himanshu
2015-01-01
In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).
International Nuclear Information System (INIS)
Muda, Zakaria Che; Thiruchelvam, Sivadass; Mustapha, Kamal Nasharuddin; Omar, Rohayu Che; Usman, Fathoni; Alam, Md Ashrafu
2013-01-01
Optimization of transmission tower structures is traditionally based on either optimization of members sizes with fixed topographical shape or based on structural analysis modelling strategies without taking cognizance of fabrication and constructability issue facing the contractors . This paper look into an integrated optimum design approach strategies whereby size, shape and topology are combined together with the fabrication issues in the construction of the transmission tower. The topographical algorithm is based on changing the inclination degree of the legs of the tower at first with optimum individual members sizing and later rationalized member sizes are performed through member groupings for the ease fabrication and construction of the transmission tower. The optimum weight using topographical algorithm obtained for the transmission tower is 10,924 kg for singular members and 18,430 kg for element grouping at 10° inclination angle.
Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Chaudhary, Kailash; Chaudhary, Himanshu [Malaviya National Institute of Technology, Jaipur (Malaysia)
2015-11-15
In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).
Directory of Open Access Journals (Sweden)
Chenlu Miao
2016-01-01
Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.
The Optimal Hydraulic Design of Centrifugal Impeller Using Genetic Algorithm with BVF
Directory of Open Access Journals (Sweden)
Xin Zhou
2014-01-01
Full Text Available Derived from idea of combining the advantages of two-dimensional hydraulic design theory, genetic algorithm, and boundary vorticity flux diagnosis, an optimal hydraulic design method of centrifugal pump impeller was developed. Given design parameters, the desired optimal centrifugal impeller can be obtained after several iterations by this method. Another 5 impellers with the same parameters were also designed by using single arc, double arcs, triple arcs, logarithmic spiral, and linear-variable angle spiral as blade profiles to make comparisons. Using Reynolds averaged N-S equations with a RNG k-ε two-equation turbulence model and log-law wall function to solve 3D turbulent flow field in the flow channel between blades of 6 designed impellers by CFD code FLUENT, the investigation on velocity distributions, pressure distributions, boundary vorticity flux distributions on blade surfaces, and hydraulic performance of impellers was presented and the comparisons of impellers by different design methods were demonstrated. The results showed that the hydraulic performance of impeller designed by this method is much better than the other 5 impellers under design operation condition with almost the same head, higher efficiency, and lower rotating torque, which implied less hydraulic loss and energy consumption.
Design of sparse Halbach magnet arrays for portable MRI using a genetic algorithm.
Cooley, Clarissa Zimmerman; Haskell, Melissa W; Cauley, Stephen F; Sappo, Charlotte; Lapierre, Cristen D; Ha, Christopher G; Stockmann, Jason P; Wald, Lawrence L
2018-01-01
Permanent magnet arrays offer several attributes attractive for the development of a low-cost portable MRI scanner for brain imaging. They offer the potential for a relatively lightweight, low to mid-field system with no cryogenics, a small fringe field, and no electrical power requirements or heat dissipation needs. The cylindrical Halbach array, however, requires external shimming or mechanical adjustments to produce B 0 fields with standard MRI homogeneity levels (e.g., 0.1 ppm over FOV), particularly when constrained or truncated geometries are needed, such as a head-only magnet where the magnet length is constrained by the shoulders. For portable scanners using rotation of the magnet for spatial encoding with generalized projections, the spatial pattern of the field is important since it acts as the encoding field. In either a static or rotating magnet, it will be important to be able to optimize the field pattern of cylindrical Halbach arrays in a way that retains construction simplicity. To achieve this, we present a method for designing an optimized cylindrical Halbach magnet using the genetic algorithm to achieve either homogeneity (for standard MRI applications) or a favorable spatial encoding field pattern (for rotational spatial encoding applications). We compare the chosen designs against a standard, fully populated sparse Halbach design, and evaluate optimized spatial encoding fields using point-spread-function and image simulations. We validate the calculations by comparing to the measured field of a constructed magnet. The experimentally implemented design produced fields in good agreement with the predicted fields, and the genetic algorithm was successful in improving the chosen metrics. For the uniform target field, an order of magnitude homogeneity improvement was achieved compared to the un-optimized, fully populated design. For the rotational encoding design the resolution uniformity is improved by 95% compared to a uniformly populated design.
Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.
Directory of Open Access Journals (Sweden)
Xiao-Lin Wu
Full Text Available Low-density (LD single nucleotide polymorphism (SNP arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD or high-density (HD SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE or haplotype-averaged Shannon entropy (HASE and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus
A Genetic Algorithm for Selection of Fixed-Size Subsets with Application to Design Problems
Directory of Open Access Journals (Sweden)
Mark A. Wolters
2015-11-01
Full Text Available The R function kofnGA conducts a genetic algorithm search for the best subset of k items from a set of n alternatives, given an objective function that measures the quality of a subset. The function fills a gap in the presently available subset selection software, which typically searches over a range of subset sizes, restricts the types of objective functions considered, or does not include freely available code. The new function is demonstrated on two types of problem where a fixed-size subset search is desirable: design of environmental monitoring networks, and D-optimal design of experiments. Additionally, the performance is evaluated on a class of constructed test problems with a novel design that is interesting in its own right.
International Nuclear Information System (INIS)
Abreu Pereira, Claudio Marcio Nascimento do; Schirru, Roberto; Martinez, Aquilino Senra
1999-01-01
Here is presented an engineering optimization tool based on a genetic algorithm, implemented according to the method proposed in recent work that has demonstrated the feasibility of the use of this technique in nuclear reactor core designs. The tool is simulator-independent in the sense that it can be customized to use most of the simulators which have the input parameters read from formatted text files and the outputs also written from a text file. As the nuclear reactor simulators generally use such kind of interface, the proposed tool plays an important role in nuclear reactor designs. Research reactors may often use non-conventional design approaches, causing different situations that may lead the nuclear engineer to face new optimization problems. In this case, a good optimization technique, together with its customizing facility and a friendly man-machine interface could be very interesting. Here, the tool is described and some advantages are outlined. (author)
Yelk, Joseph; Sukharev, Maxim; Seideman, Tamar
2008-08-14
An optimal control approach based on multiple parameter genetic algorithms is applied to the design of plasmonic nanoconstructs with predetermined optical properties and functionalities. We first develop nanoscale metallic lenses that focus an incident plane wave onto a prespecified, spatially confined spot. Our results illustrate the mechanism of energy flow through wires and cavities. Next we design a periodic array of silver particles to modify the polarization of an incident, linearly polarized plane wave in a desired fashion while localizing the light in space. The results provide insight into the structural features that determine the birefringence properties of metal nanoparticles and their arrays. Of the variety of potential applications that may be envisioned, we note the design of nanoscale light sources with controllable coherence and polarization properties that could serve for coherent control of molecular, electronic, or electromechanical dynamics in the nanoscale.
Directory of Open Access Journals (Sweden)
J. M. Jeevani W. Jayasinghe
2015-01-01
Full Text Available Genetic algorithm (GA has been a popular optimization technique used for performance improvement of microstrip patch antennas (MPAs. When using GA, the patch geometry is optimized by dividing the patch area into small rectangular cells. This has an inherent problem of adjacent cells being connected to each other with infinitesimal connections, which may not be achievable in practice due to fabrication tolerances in chemical etching. As a solution, this paper presents a novel method of dividing the patch area into cells with nonuniform overlaps. The optimized design, which is obtained by using fixed overlap sizes, shows a quad-band performance covering GSM1800, GSM1900, LTE2300, and Bluetooth bands. In contrast, use of nonuniform overlap sizes leads to obtaining a pentaband design covering GSM1800, GSM1900, UMTS, LTE2300, and Bluetooth bandswith fractional bands with of 38% due to the extra design flexibility.
Design of the algorithm of photons migration in the multilayer skin structure
Bulykina, Anastasiia B.; Ryzhova, Victoria A.; Korotaev, Valery V.; Samokhin, Nikita Y.
2017-06-01
Design of approaches and methods of the oncological diseases diagnostics has special significance. It allows determining any kind of tumors at early stages. The development of optical and laser technologies provided increase of a number of methods allowing making diagnostic studies of oncological diseases. A promising area of biomedical diagnostics is the development of automated nondestructive testing systems for the study of the skin polarizing properties based on backscattered radiation detection. Specification of the examined tissue polarizing properties allows studying of structural properties change influenced by various pathologies. Consequently, measurement and analysis of the polarizing properties of the scattered optical radiation for the development of methods for diagnosis and imaging of skin in vivo appear relevant. The purpose of this research is to design the algorithm of photons migration in the multilayer skin structure. In this research, the algorithm of photons migration in the multilayer skin structure was designed. It is based on the use of the Monte Carlo method. Implemented Monte Carlo method appears as a tracking the paths of photons experiencing random discrete direction changes before they are released from the analyzed area or decrease their intensity to negligible levels. Modeling algorithm consists of the medium and the source characteristics generation, a photon generating considering spatial coordinates of the polar and azimuthal angles, the photon weight reduction calculating due to specular and diffuse reflection, the photon mean free path definition, the photon motion direction angle definition as a result of random scattering with a Henyey-Greenstein phase function, the medium's absorption calculation. Biological tissue is modeled as a homogeneous scattering sheet characterized by absorption, a scattering and anisotropy coefficients.
Highway Passenger Transport Based Express Parcel Service Network Design: Model and Algorithm
Directory of Open Access Journals (Sweden)
Yuan Jiang
2017-01-01
Full Text Available Highway passenger transport based express parcel service (HPTB-EPS is an emerging business that uses unutilised room of coach trunk to ship parcels between major cities. While it is reaping more and more express market, the managers are facing difficult decisions to design the service network. This paper investigates the HPTB-EPS network design problem and analyses the time-space characteristics of such network. A mixed-integer programming model is formulated integrating the service decision, frequency, and network flow distribution. To solve the model, a decomposition-based heuristic algorithm is designed by decomposing the problem as three steps: construction of service network, service path selection, and distribution of network flow. Numerical experiment using real data from our partner company demonstrates the effectiveness of our model and algorithm. We found that our solution could reduce the total cost by up to 16.3% compared to the carrier’s solution. The sensitivity analysis demonstrates the robustness and flexibility of the solutions of the model.
Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures
Directory of Open Access Journals (Sweden)
Ayang Xiao
2014-01-01
Full Text Available Due to the fact that vastly different variables and constraints are simultaneously considered, truss layout optimization is a typical difficult constrained mixed-integer nonlinear program. Moreover, the computational cost of truss analysis is often quite expensive. In this paper, a novel fitness estimation based particle swarm optimization algorithm with an adaptive penalty function approach (FEPSO-AP is proposed to handle this problem. FEPSO-AP adopts a special fitness estimate strategy to evaluate the similar particles in the current population, with the purpose to reduce the computational cost. Further more, a laconic adaptive penalty function is employed by FEPSO-AP, which can handle multiple constraints effectively by making good use of historical iteration information. Four benchmark examples with fixed topologies and up to 44 design dimensions were studied to verify the generality and efficiency of the proposed algorithm. Numerical results of the present work compared with results of other state-of-the-art hybrid algorithms shown in the literature demonstrate that the convergence rate and the solution quality of FEPSO-AP are essentially competitive.
Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms
Mohan, K. Aditya
2017-10-01
4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.
Chaotic logic gate: A new approach in set and design by genetic algorithm
International Nuclear Information System (INIS)
Beyki, Mahmood; Yaghoobi, Mahdi
2015-01-01
How to reconfigure a logic gate is an attractive subject for different applications. Chaotic systems can yield a wide variety of patterns and here we use this feature to produce a logic gate. This feature forms the basis for designing a dynamical computing device that can be rapidly reconfigured to become any wanted logical operator. This logic gate that can reconfigure to any logical operator when placed in its chaotic state is called chaotic logic gate. The reconfiguration realize by setting the parameter values of chaotic logic gate. In this paper we present mechanisms about how to produce a logic gate based on the logistic map in its chaotic state and genetic algorithm is used to set the parameter values. We use three well-known selection methods used in genetic algorithm: tournament selection, Roulette wheel selection and random selection. The results show the tournament selection method is the best method for set the parameter values. Further, genetic algorithm is a powerful tool to set the parameter values of chaotic logic gate
Zhang, Yuli; Han, Jun; Weng, Xinqian; He, Zhongzhu; Zeng, Xiaoyang
This paper presents an Application Specific Instruction-set Processor (ASIP) for the SHA-3 BLAKE algorithm family by instruction set extensions (ISE) from an RISC (reduced instruction set computer) processor. With a design space exploration for this ASIP to increase the performance and reduce the area cost, we accomplish an efficient hardware and software implementation of BLAKE algorithm. The special instructions and their well-matched hardware function unit improve the calculation of the key section of the algorithm, namely G-functions. Also, relaxing the time constraint of the special function unit can decrease its hardware cost, while keeping the high data throughput of the processor. Evaluation results reveal the ASIP achieves 335Mbps and 176Mbps for BLAKE-256 and BLAKE-512. The extra area cost is only 8.06k equivalent gates. The proposed ASIP outperforms several software approaches on various platforms in cycle per byte. In fact, both high throughput and low hardware cost achieved by this programmable processor are comparable to that of ASIC implementations.
Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm
Liechty, Derek S.
2014-01-01
Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.
Multivariable PID controller design tuning using bat algorithm for activated sludge process
Atikah Nor’Azlan, Nur; Asmiza Selamat, Nur; Mat Yahya, Nafrizuan
2018-04-01
The designing of a multivariable PID control for multi input multi output is being concerned with this project by applying four multivariable PID control tuning which is Davison, Penttinen-Koivo, Maciejowski and Proposed Combined method. The determination of this study is to investigate the performance of selected optimization technique to tune the parameter of MPID controller. The selected optimization technique is Bat Algorithm (BA). All the MPID-BA tuning result will be compared and analyzed. Later, the best MPID-BA will be chosen in order to determine which techniques are better based on the system performances in terms of transient response.
Multiobjective optimization of building design using genetic algorithm and artificial neural network
Energy Technology Data Exchange (ETDEWEB)
Magnier, L.; Zhou, L.; Haghighat, F. [Concordia Univ., Centre for Building Studies, Montreal, PQ (Canada). Dept. of Building, Civil and Environmental Engineering
2008-07-01
This paper addressed the challenge of designing modern buildings that are energy efficient, affordable, environmentally sound and comfortable for occupants. Building optimization is a time consuming process when so many objectives must be met. In particular, the use of genetic algorithm (GA) for building design has limitations due to the high number of simulations required. This paper presented an efficient approach to overcome the limitations of GA for building design. The approach expanded the GA methodology to multiobjective optimization. The GA integrating neural network (GAINN) approach first uses a simulation-based artificial neural network (ANN) to characterize building behaviour, and then combines it with a GA for optimization. The process was shown to provide fast and reliable optimization. GAINN was further improved by integrating multiobjective evolutionary algorithms (MOEAs). Two new MOEAs named NSGAINN and PLAGUE were designed for the proposed methodology. The purpose of creating a new MOEA was to take advantage of GAINN fast evaluations. This paper presented bench test results and compared them with with NSGA-2. A previous case study using GAINN methodology was re-optimized with the newly developed MOEA. The design to be optimized was a ventilation system of a standard office room in the summer, with 2 occupants and 4 underfloor air distribution diffusers. The objectives included thermal comfort, indoor air quality, and energy conservation for cooling. The control variables were temperature of the air supply, speed of air supply, distance from the diffuser to the occupant, and the distance from the return grill to the contaminant source. The results showed that the newly presented GAINN methodology was better in both convergence and range of choices compared to a weighted sum GA. 13 refs., 2 tabs., 9 figs.
National Aeronautics and Space Administration — SSCI proposes to develop and test a framework referred to as the ADVANCE (Algorithm Design and Validation for Adaptive Nonlinear Control Enhancement), within which...
Multi-Stage Hybrid Rocket Conceptual Design for Micro-Satellites Launch using Genetic Algorithm
Kitagawa, Yosuke; Kitagawa, Koki; Nakamiya, Masaki; Kanazaki, Masahiro; Shimada, Toru
The multi-objective genetic algorithm (MOGA) is applied to the multi-disciplinary conceptual design problem for a three-stage launch vehicle (LV) with a hybrid rocket engine (HRE). MOGA is an optimization tool used for multi-objective problems. The parallel coordinate plot (PCP), which is a data mining method, is employed in the post-process in MOGA for design knowledge discovery. A rocket that can deliver observing micro-satellites to the sun-synchronous orbit (SSO) is designed. It consists of an oxidizer tank containing liquid oxidizer, a combustion chamber containing solid fuel, a pressurizing tank and a nozzle. The objective functions considered in this study are to minimize the total mass of the rocket and to maximize the ratio of the payload mass to the total mass. To calculate the thrust and the engine size, the regression rate is estimated based on an empirical model for a paraffin (FT-0070) propellant. Several non-dominated solutions are obtained using MOGA, and design knowledge is discovered for the present hybrid rocket design problem using a PCP analysis. As a result, substantial knowledge on the design of an LV with an HRE is obtained for use in space transportation.
Design Procedure for High-Speed PM Motors Aided by Optimization Algorithms
Directory of Open Access Journals (Sweden)
Francesco Cupertino
2018-02-01
Full Text Available This paper considers the electromagnetic and structural co-design of superficial permanent magnet synchronous machines for high-speed applications, with the aid of a Pareto optimization procedure. The aim of this work is to present a design procedure for the afore-mentioned machines that relies on the combined used of optimization algorithms and finite element analysis. The proposed approach allows easy analysis of the results and a lowering of the computational burden. The proposed design method is presented through a practical example starting from the specifications of an aeronautical actuator. The design procedure is based on static finite element simulations for electromagnetic analysis and on analytical formulas for structural design. The final results are validated through detailed transient finite element analysis to verify both electromagnetic and structural performance. The step-by-step presentation of the proposed design methodology allows the reader to easily adapt it to different specifications. Finally, a comparison between a distributed-winding (24 slots and a concentrated-winding (6 slots machine is presented demonstrating the advantages of the former winding arrangement for high-speed applications.
Directory of Open Access Journals (Sweden)
Taek Seo Jung
2006-03-01
Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.
International Nuclear Information System (INIS)
Alpman, Emre
2014-01-01
The effect of selecting the twist angle and chord length distributions on the wind turbine blade design was investigated by performing aerodynamic optimization of a two-bladed stall regulated horizontal axis wind turbine. Twist angle and chord length distributions were defined using Bezier curve using 3, 5, 7 and 9 control points uniformly distributed along the span. Optimizations performed using a micro-genetic algorithm with populations composed of 5, 10, 15, 20 individuals showed that, the number of control points clearly affected the outcome of the process; however the effects were different for different population sizes. The results also showed the superiority of micro-genetic algorithm over a standard genetic algorithm, for the selected population sizes. Optimizations were also performed using a macroevolutionary algorithm and the resulting best blade design was compared with that yielded by micro-genetic algorithm
International Nuclear Information System (INIS)
Jia Baoshan; Yu Jiyang; You Songbo
2005-01-01
This article focuses on the development of an improved genetic algorithm and its application in the optimal design of the ship nuclear reactor system, whose goal is to find a combination of system parameter values that minimize the mass or volume of the system given the power capacity requirement and safety criteria. An improved genetic algorithm (IGA) was developed using an 'average fitness value' grouping + 'specified survival probability' rank selection method and a 'separate-recombine' duplication operator. Combining with a simulated annealing algorithm (SAA) that continues the local search after the IGA reaches a satisfactory point, the algorithm gave satisfactory optimization results from both search efficiency and accuracy perspectives. This IGA-SAA algorithm successfully solved the design optimization problem of ship nuclear power system. It is an advanced and efficient methodology that can be applied to the similar optimization problems in other areas. (authors)