Search results for: parallel techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7433

Search results for: parallel techniques

7403 Study of Temperature Difference and Current Distribution in Parallel-Connected Cells at Low Temperature

Authors: Sara Kamalisiahroudi, Jun Huang, Zhe Li, Jianbo Zhang

Abstract:

Two types of commercial cylindrical lithium ion batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah INR-18650), were investigated experimentally. The capacities of these samples were individually measured using constant current-constant voltage (CC-CV) method at different ambient temperatures (-10 ℃, 0 ℃, 25 ℃). Their internal resistance was determined by electrochemical impedance spectroscopy (EIS) and pulse discharge methods. The cells with different configurations of parallel connection NCR-NCR, INR-INR and NCR-INR were charged/discharged at the aforementioned ambient temperatures. The results showed that the difference of internal resistance between cells much more evident at low temperatures. Furthermore, the parallel connection of NCR-NCR exhibits the most uniform temperature distribution in cells at -10 ℃, this feature is quite favorable for the safety of the battery pack.

Keywords: batteries in parallel connection, internal resistance, low temperature, temperature difference, current distribution

Procedia PDF Downloads 449
7402 A Review of Machine Learning for Big Data

Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

Abstract:

Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

Procedia PDF Downloads 407
7401 Exploring MPI-Based Parallel Computing in Analyzing Very Large Sequences

Authors: Bilal Wajid, Erchin Serpedin

Abstract:

The health industry is aiming towards personalized medicine. If the patient’s genome needs to be sequenced it is important that the entire analysis be completed quickly. This paper explores use of parallel computing to analyze very large sequences. Two cases have been considered. In the first case, the sequence is kept constant and the effect of increasing the number of MPI-based processes is evaluated in terms of execution time, speed and efficiency. In the second case the number of MPI-based processes have been kept constant whereas, the length of the sequence was increased.

Keywords: parallel computing, alignment, genome assembly, alignment

Procedia PDF Downloads 240
7400 Security Over OFDM Fading Channels with Friendly Jammer

Authors: Munnujahan Ara

Abstract:

In this paper, we investigate the effect of friendly jamming power allocation strategies on the achievable average secrecy rate over a bank of parallel fading wiretap channels. We investigate the achievable average secrecy rate in parallel fading wiretap channels subject to Rayleigh and Rician fading. The achievable average secrecy rate, due to the presence of a line-of-sight component in the jammer channel is also evaluated. Moreover, we study the detrimental effect of correlation across the parallel sub-channels, and evaluate the corresponding decrease in the achievable average secrecy rate for the various fading configurations. We also investigate the tradeoff between the transmission power and the jamming power for a fixed total power budget. Our results, which are applicable to current orthogonal frequency division multiplexing (OFDM) communications systems, shed further light on the achievable average secrecy rates over a bank of parallel fading channels in the presence of friendly jammers.

Keywords: fading parallel channels, wire-tap channel, OFDM, secrecy capacity, power allocation

Procedia PDF Downloads 477
7399 Numerical Studies for Standard Bi-Conjugate Gradient Stabilized Method and the Parallel Variants for Solving Linear Equations

Authors: Kuniyoshi Abe

Abstract:

Bi-conjugate gradient (Bi-CG) is a well-known method for solving linear equations Ax = b, for x, where A is a given n-by-n matrix, and b is a given n-vector. Typically, the dimension of the linear equation is high and the matrix is sparse. A number of hybrid Bi-CG methods such as conjugate gradient squared (CGS), Bi-CG stabilized (Bi-CGSTAB), BiCGStab2, and BiCGstab(l) have been developed to improve the convergence of Bi-CG. Bi-CGSTAB has been most often used for efficiently solving the linear equation, but we have seen the convergence behavior with a long stagnation phase. In such cases, it is important to have Bi-CG coefficients that are as accurate as possible, and the stabilization strategy, which stabilizes the computation of the Bi-CG coefficients, has been proposed. It may avoid stagnation and lead to faster computation. Motivated by a large number of processors in present petascale high-performance computing hardware, the scalability of Krylov subspace methods on parallel computers has recently become increasingly prominent. The main bottleneck for efficient parallelization is the inner products which require a global reduction. The resulting global synchronization phases cause communication overhead on parallel computers. The parallel variants of Krylov subspace methods reducing the number of global communication phases and hiding the communication latency have been proposed. However, the numerical stability, specifically, the convergence speed of the parallel variants of Bi-CGSTAB may become worse than that of the standard Bi-CGSTAB. In this paper, therefore, we compare the convergence speed between the standard Bi-CGSTAB and the parallel variants by numerical experiments and show that the convergence speed of the standard Bi-CGSTAB is faster than the parallel variants. Moreover, we propose the stabilization strategy for the parallel variants.

Keywords: bi-conjugate gradient stabilized method, convergence speed, Krylov subspace methods, linear equations, parallel variant

Procedia PDF Downloads 138
7398 Constructing the Density of States from the Parallel Wang Landau Algorithm Overlapping Data

Authors: Arman S. Kussainov, Altynbek K. Beisekov

Abstract:

This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

Procedia PDF Downloads 368
7397 Parallel Evaluation of Sommerfeld Integrals for Multilayer Dyadic Green's Function

Authors: Duygu Kan, Mehmet Cayoren

Abstract:

Sommerfeld-integrals (SIs) are commonly encountered in electromagnetics problems involving analysis of antennas and scatterers embedded in planar multilayered media. Generally speaking, the analytical solution of SIs is unavailable, and it is well known that numerical evaluation of SIs is very time consuming and computationally expensive due to the highly oscillating and slowly decaying nature of the integrands. Therefore, fast computation of SIs has a paramount importance. In this paper, a parallel code has been developed to speed up the computation of SI in the framework of calculation of dyadic Green’s function in multilayered media. OpenMP shared memory approach is used to parallelize the SI algorithm and resulted in significant time savings. Moreover accelerating the computation of dyadic Green’s function is discussed based on the parallel SI algorithm developed.

Keywords: Sommerfeld-integrals, multilayer dyadic Green’s function, OpenMP, shared memory parallel programming

Procedia PDF Downloads 215
7396 GPU-Accelerated Triangle Mesh Simplification Using Parallel Vertex Removal

Authors: Thomas Odaker, Dieter Kranzlmueller, Jens Volkert

Abstract:

We present an approach to triangle mesh simplification designed to be executed on the GPU. We use a quadric error metric to calculate an error value for each vertex of the mesh and order all vertices based on this value. This step is followed by the parallel removal of a number of vertices with the lowest calculated error values. To allow for the parallel removal of multiple vertices we use a set of per-vertex boundaries that prevent mesh foldovers even when simplification operations are performed on neighbouring vertices. We execute multiple iterations of the calculation of the vertex errors, ordering of the error values and removal of vertices until either a desired number of vertices remains in the mesh or a minimum error value is reached. This parallel approach is used to speed up the simplification process while maintaining mesh topology and avoiding foldovers at every step of the simplification.

Keywords: computer graphics, half edge collapse, mesh simplification, precomputed simplification, topology preserving

Procedia PDF Downloads 335
7395 Parallel Asynchronous Multi-Splitting Methods for Differential Algebraic Systems

Authors: Malika Elkyal

Abstract:

We consider an iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm does not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays to be substantial and unpredictable. Accordingly, we note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: parallel methods, asynchronous mode, multisplitting, differential algebraic equations

Procedia PDF Downloads 528
7394 Natural Convection between Two Parallel Wavy Plates

Authors: Si Abdallah Mayouf

Abstract:

In this work, the effects of the wavy surface on free convection heat transfer boundary layer flow between two parallel wavy plates have been studied numerically. The two plates are considered at a constant temperature. The equations and the boundary conditions are discretized by the finite difference scheme and solved numerically using the Gauss-Seidel algorithm. The important parameters in this problem are the amplitude of the wavy surfaces and the distance between the two wavy plates. Results are presented as velocity profiles, temperature profiles and local Nusselt number according to the important parameters.

Keywords: free convection, wavy surface, parallel plates, fluid dynamics

Procedia PDF Downloads 280
7393 Parallelizing the Hybrid Pseudo-Spectral Time Domain/Finite Difference Time Domain Algorithms for the Large-Scale Electromagnetic Simulations Using Massage Passing Interface Library

Authors: Donggun Lee, Q-Han Park

Abstract:

Due to its coarse grid, the Pseudo-Spectral Time Domain (PSTD) method has advantages against the Finite Difference Time Domain (FDTD) method in terms of memory requirement and operation time. However, since the efficiency of parallelization is much lower than that of FDTD, PSTD is not a useful method for a large-scale electromagnetic simulation in a parallel platform. In this paper, we propose the parallelization technique of the hybrid PSTD-FDTD (HPF) method which simultaneously possesses the efficient parallelizability of FDTD and the quick speed and low memory requirement of PSTD. Parallelization cost of the HPF method is exactly the same as the parallel FDTD, but still, it occupies much less memory space and has faster operation speed than the parallel FDTD. Experiments in distributed memory systems have shown that the parallel HPF method saves up to 96% of the operation time and reduces 84% of the memory requirement. Also, by combining the OpenMP library to the MPI library, we further reduced the operation time of the parallel HPF method by 50%.

Keywords: FDTD, hybrid, MPI, OpenMP, PSTD, parallelization

Procedia PDF Downloads 114
7392 Detecting the Edge of Multiple Images in Parallel

Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

Abstract:

Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

Procedia PDF Downloads 446
7391 A Practical Protection Method for Parallel Transmission-Lines Based on the Fault Travelling-Waves

Authors: Mohammad Reza Ebrahimi

Abstract:

In new restructured power systems, swift fault detection is very important. The parallel transmission-lines are vastly used in this kind of power systems because of high amount of energy transferring. In this paper, a method based on the comparison of two schemes, i.e., i) maximum magnitude of travelling-wave (TW) energy ii) the instants of maximum energy occurrence at the circuits of parallel transmission-line is proposed. Using the travelling-wave of fault in order to faulted line identification this method has noticeable operation time. Moreover, the algorithm can cover for identification of faults as external or internal faults. For an internal fault, the exact location of the fault can be estimated confidently. A lot of simulations have been done with PSCAD/EMTDC to verify the performance of the proposed algorithm.

Keywords: travelling-wave, maximum energy, parallel transmission-line, fault location

Procedia PDF Downloads 157
7390 An Improved Parallel Algorithm of Decision Tree

Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

Abstract:

Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

Procedia PDF Downloads 100
7389 Identification of Vehicle Dynamic Parameters by Using Optimized Exciting Trajectory on 3- DOF Parallel Manipulator

Authors: Di Yao, Gunther Prokop, Kay Buttner

Abstract:

Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

Procedia PDF Downloads 238
7388 Analyzing the Factors that Cause Parallel Performance Degradation in Parallel Graph-Based Computations Using Graph500

Authors: Mustafa Elfituri, Jonathan Cook

Abstract:

Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: graph computation, graph500 benchmark, parallel architectures, parallel programming, workload characterization.

Procedia PDF Downloads 113
7387 Parallel Vector Processing Using Multi Level Orbital DATA

Authors: Nagi Mekhiel

Abstract:

Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

Procedia PDF Downloads 241
7386 Verification & Validation of Map Reduce Program Model for Parallel K-Mediod Algorithm on Hadoop Cluster

Authors: Trapti Sharma, Devesh Kumar Srivastava

Abstract:

This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

Procedia PDF Downloads 341
7385 Conditions for Fault Recovery of Interconnected Asynchronous Sequential Machines with State Feedback

Authors: Jung–Min Yang

Abstract:

In this paper, fault recovery for parallel interconnected asynchronous sequential machines is studied. An adversarial input can infiltrate into one of two submachines comprising parallel composition of the considered asynchronous sequential machine, causing an unauthorized state transition. The control objective is to elucidate the condition for the existence of a corrective controller that makes the closed-loop system immune against any occurrence of adversarial inputs. In particular, an efficient existence condition is presented that does not need the complete modeling of the interconnected asynchronous sequential machine.

Keywords: asynchronous sequential machines, parallel composi-tion, corrective control, fault tolerance

Procedia PDF Downloads 202
7384 Islamic Financial Instrument, Standard Parallel Salam as an Alternative to Conventional Derivatives

Authors: Alireza Naserpoor

Abstract:

Derivatives are the most important innovation which has happened in the past decades. When it comes to financial markets, it has changed the whole way of operations of stock, commodities and currency market. Beside a lot of advantages, Conventional derivatives contracts have some disadvantages too. Some problems have been caused by derivatives contain raising Volatility, increasing Bankruptcies and causing financial crises. Standard Parallel Salam contract as an Islamic financial product meanwhile is a financing instrument can be used for risk management by investors. Standard Parallel Salam is a Shari’ah-Compliant contract. Furthermore, it is an alternative to conventional derivatives. Despite the fact that the unstructured types of that, has been used in several Islamic countries, This contract as a structured and standard financial instrument introduced in Iran Mercantile Exchange in 2014. In this paper after introducing parallel Salam, we intend to examine a collection of international experience and local measure regarding launching standard parallel Salam contract and proceed to describe standard scenarios for trading this instrument and practical experience in Iran Mercantile Exchange about this instrument. Afterwards, we make a comparison between SPS and Futures contracts as a conventional derivative. Standard parallel salam contract as an Islamic financial product, can be used for risk management by investors. SPS is a Shariah-Compliant contract. Furthermore it is an alternative to conventional derivatives. This contract as a structured and standard financial instrument introduced in Iran Mercantile Exchange in 2014. despite the fact that the unstructured types of that, has been used in several Islamic countries. In this article after introducing parallel salam, we intend to examine a collection of international experience and local measure regarding launching standard parallel salam contract and proceed to describe standard scenarios for trading this instrument containing two main approaches in SPS using, And practical experience in IME about this instrument Afterwards, a comparison between SPS and Futures contracts as a conventional derivatives.

Keywords: futures contracts, hedging, shari’ah compliant instruments, standard parallel salam

Procedia PDF Downloads 352
7383 Performance Comparison of Droop Control Methods for Parallel Inverters in Microgrid

Authors: Ahmed Ismail, Mustafa Baysal

Abstract:

Although the energy source in the world is mainly based on fossil fuels today, there is a need for alternative energy generation systems, which are more economic and environmentally friendly, due to continuously increasing demand of electric energy and lacking power resources and networks. Distributed Energy Resources (DERs) such as fuel cells, wind and solar power have recently become widespread as alternative generation. In order to solve several problems that might be encountered when integrating DERs to power system, the microgrid concept has been proposed. A microgrid can operate both grid connected and island mode to benefit both utility and customers. For most distributed energy resources (DER) which are connected in parallel in LV-grid like micro-turbines, wind plants, fuel cells and PV cells electrical power is generated as a direct current (DC) and converted to an alternative currents (AC) by inverters. So the inverters are assumed to be primary components in a microgrid. There are many control techniques of parallel inverters to manage active and reactive sharing of the loads. Some of them are based on droop method. In literature, the studies are usually focused on improving the transient performance of inverters. In this study, the performance of two different controllers based on droop control method is compared for the inverters operated in parallel without any communication feedback. For this aim, a microgrid in which inverters are controlled by conventional droop controller and modified droop controller is designed. Modified controller is obtained by adding PID into conventional droop control. Active and reactive power sharing performance, voltage and frequency responses of those control methods are measured in several operational cases. Study cases have been simulated by MATLAB-SIMULINK.

Keywords: active and reactive power sharing, distributed generation, droop control, microgrid

Procedia PDF Downloads 563
7382 Compilation and Statistical Analysis of an Arabic-English Legal Corpus in Sketch Engine

Authors: C. Brierley, H. El-Farahaty, A. Farhan

Abstract:

The Leeds Parallel Corpus of Arabic-English Constitutions is a parallel corpus for the Arabic legal domain. Analysis of legal language via Corpus Linguistics techniques is an important development. In legal proceedings, a corpus-based approach to disambiguating meaning is set to replace the dictionary as an interpretative tool, and legal scholarship in the States is now attuned to the potential for Text Analytics over vast quantities of text-based legal material, following the business and medical industries. This trend is reflected in Europe: the interdisciplinary research group in Computer Assisted Legal Linguistics mines big data collections of legal and non-legal texts to analyse: legal interpretations; legal discourse; the comprehensibility of legal texts; conflict resolution; and linguistic human rights. This paper focuses on ‘dignity’ as an important aspect of the overarching concept of human rights in current constitutions across the Arab world. We have compiled a parallel, Arabic-English raw text corpus (169,861 Arabic words and 205,893 English words) from reputable websites such as the World Intellectual Property Organisation and CONSTITUTE, and uploaded and queried our corpus in Sketch Engine. Our most challenging task was sentence-level alignment of Arabic-English data. This entailed manual intervention to ensure correspondence on a one-to-many basis since Arabic sentences differ from English in length and punctuation. We have searched for morphological variants of ‘dignity’ (رامة ك, karāma) in the Arabic data and inspected their English translation equivalents. The term occurs most frequently in the Sudanese constitution (10 instances), and not at all in the constitution of Palestine. Its most frequent collocate, determined via the logDice statistic in Sketch Engine, is ‘human’ as in ‘human dignity’.

Keywords: Arabic constitution, corpus-based legal linguistics, human rights, parallel Arabic-English legal corpora

Procedia PDF Downloads 152
7381 Embedded Hw-Sw Reconfigurable Techniques For Wireless Sensor Network Applications

Authors: B. Kirubakaran, C. Rajasekaran

Abstract:

Reconfigurable techniques are used in many engineering and industrial applications for the efficient data transmissions through the wireless sensor networks. Nowadays most of the industrial applications are work for try to minimize the size and cost. During runtime the reconfigurable technique avoid the unwanted hang and delay in the system performance. In recent world Field Programmable Gate Array (FPGA) as one of the most efficient reconfigurable device and widely used for most of the hardware and software reconfiguration applications. In this paper, the work deals with whatever going to make changes in the hardware and software during runtime it’s should not affect the current running process that’s the main objective of the paper our changes be done in a parallel manner at the same time concentrating the cost and power transmission problems during data trans-receiving. Analog sensor (Temperature) as an input for the controller (PIC) through that control the FPGA digital sensors in generalized manner.

Keywords: field programmable gate array, peripheral interrupt controller, runtime reconfigurable techniques, wireless sensor networks

Procedia PDF Downloads 380
7380 Multi Biomertric Personal Identification System Based On Hybird Intellegence Method

Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

Abstract:

Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

Procedia PDF Downloads 511
7379 Urban Analysis of the Old City of Oran and Its Building after an Earthquake

Authors: A. Zatir, A. Mokhtari, A. Foufa, S. Zatir

Abstract:

The city of Oran, like any other region of northern Algeria, is subject to frequent seismic activity, the study presented in this work will be based on an analysis of urban and architectural context of the city of Oran before the date of the earthquake of 1790, and then try to deduce the differences between the old city before and after the earthquake. The analysis developed as a specific objective to tap into the seismic history of the city of Oran parallel to its urban history. The example of the citadel of Oran indicates that constructions presenting the site of the old citadel, may present elements of resistance for face to seismic effects. Removed in city observations of these structures, showed the ingenuity of the techniques used by the ancient builders, including the good performance of domes and arches in resistance to seismic forces.

Keywords: earthquake, citadel, performance, traditional techniques, constructions

Procedia PDF Downloads 276
7378 On Fault Diagnosis of Asynchronous Sequential Machines with Parallel Composition

Authors: Jung-Min Yang

Abstract:

Fault diagnosis of composite asynchronous sequential machines with parallel composition is addressed in this paper. An adversarial input can infiltrate one of two submachines comprising the composite asynchronous machine, causing an unauthorized state transition. The objective is to characterize the condition under which the controller can diagnose any fault occurrence. Two control configurations, state feedback and output feedback, are considered in this paper. In the case of output feedback, the exact estimation of the state is impossible since the current state is inaccessible and the output feedback is given as the form of burst. A simple example is provided to demonstrate the proposed methodology.

Keywords: asynchronous sequential machines, parallel composition, fault diagnosis, corrective control

Procedia PDF Downloads 274
7377 Parallel Particle Swarm Optimization Optimized LDI Controller with Lyapunov Stability Criterion for Nonlinear Structural Systems

Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen

Abstract:

In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence

Procedia PDF Downloads 625
7376 Performance Evaluation of Parallel Surface Modeling and Generation on Actual and Virtual Multicore Systems

Authors: Nyeng P. Gyang

Abstract:

Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: cloud computing systems, multicore systems, parallel Delaunay triangulation, parallel surface modeling and generation

Procedia PDF Downloads 178
7375 An Improved Many Worlds Quantum Genetic Algorithm

Authors: Li Dan, Zhao Junsuo, Zhang Wenjun

Abstract:

Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.

Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator

Procedia PDF Downloads 710
7374 Parallel Computation of the Covariance-Matrix

Authors: Claude Tadonki

Abstract:

We address the issues related to the computation of the covariance matrix. This matrix is likely to be ill conditioned following its canonical expression, thus consequently raises serious numerical issues. The underlying linear system, which therefore should be solved by means of iterative approaches, becomes computationally challenging. A huge number of iterations is expected in order to reach an acceptable level of convergence, necessary to meet the required accuracy of the computation. In addition, this linear system needs to be solved at each iteration following the general form of the covariance matrix. Putting all together, its comes that we need to compute as fast as possible the associated matrix-vector product. This is our purpose in the work, where we consider and discuss skillful formulations of the problem, then propose a parallel implementation of the matrix-vector product involved. Numerical and performance oriented discussions are provided based on experimental evaluations.

Keywords: covariance-matrix, multicore, numerical computing, parallel computing

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