Search results for: parallel architectures

Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

Procedia PDF Downloads 81

Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

Procedia PDF Downloads 103

Authors: Sana Kouchi, Hassina Nacer, Kadda Beghdad-bey

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Cloud computing is growing very fast in the market and has become one of the most controversial discussed developments in recent years. Cloud computing providers become very numerous in these areas and each of them prefers its own cloud computing infrastructure, due to the incompatibility of standards and cloud access formats, which prevents them from accepting to support cloud computing applications in a standardized manner, this heterogeneity creates the problem of interoperability between clouds, and considering that cloud customers are probably in search of an interoperable cloud computing, where they will have total control over their applications and simply migrate their services as needed, without additional development investment. A cloud federation strategy should be considered. In this article, we propose a common architecture for the cloud that is based on existing architectures and also the use of best practices from ICT frameworks, such as IBM, ITIL, NIST, etc., to address the interoperability of architectures issues in a multi-cloud system.

Keywords: cloud computing, reference architecture, interoperability, standard

Procedia PDF Downloads 133

Authors: Di Yao, Gunther Prokop, Kay Buttner

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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

Authors: S. Ghasemi, K. Khorasani

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In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures.

Keywords: component, formation flight of satellites, extended Kalman filter, fault detection and isolation, actuator fault

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Authors: Nagi Mekhiel

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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 239

Authors: Trapti Sharma, Devesh Kumar Srivastava

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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

Authors: Jung–Min Yang

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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

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Authors: Alireza Naserpoor

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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

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Authors: Jung-Min Yang

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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

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Authors: Kamalpreet Kaur, Renu Dhir

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Climate prediction is an essential component of climate research, which helps evaluate possible effects on economies, communities, and ecosystems. Climate prediction involves short-term weather prediction, seasonal prediction, and long-term climate change prediction. Climate prediction can use the information gathered from satellites, ground-based stations, and ocean buoys, among other sources. The paper's four architectures, such as ResNet50, VGG19, Inception-v3, and Xception, have been combined using an ensemble approach for overall performance and robustness. An ensemble of different models makes a prediction, and the majority vote determines the final prediction. The various architectures such as ResNet50, VGG19, Inception-v3, and Xception efficiently classify the dataset RSI-CB256, which contains satellite images into cloudy and non-cloudy. The generated ensembled S-E model (Sar-ensembled model) provides an accuracy of 99.25%.

Keywords: climate, satellite images, prediction, classification

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

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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 623

Authors: Efrain Rodriguez, Cristhian Riano, Alberto Alvares

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In recent years, robots manipulators with parallel architectures are used in additive manufacturing processes – 3D printing. These robots have advantages such as speed and lightness that make them suitable to help with the efficiency and productivity of these processes. Consequently, the interest for the development of parallel robots for additive manufacturing applications has increased. This article deals with the conceptual design and dimensional synthesis of the linear delta robot for additive manufacturing. Firstly, a methodology based on structured processes for the development of products through the phases of informational design, conceptual design and detailed design is adopted: a) In the informational design phase the Mudge diagram and the QFD matrix are used to aid a set of technical requirements, to define the form, functions and features of the robot. b) In the conceptual design phase, the functional modeling of the system through of an IDEF0 diagram is performed, and the solution principles for the requirements are formulated using a morphological matrix. This phase includes the description of the mechanical, electro-electronic and computational subsystems that constitute the general architecture of the robot. c) In the detailed design phase, a digital model of the robot is drawn on CAD software. A list of commercial and manufactured parts is detailed. Tolerances and adjustments are defined for some parts of the robot structure. The necessary manufacturing processes and tools are also listed, including: milling, turning and 3D printing. Secondly, a dimensional synthesis method applied on design of the linear delta robot is presented. One of the most important key factors in the design of a parallel robot is the useful workspace, which strongly depends on the joint space, the dimensions of the mechanism bodies and the possible interferences between these bodies. The objective function is based on the verification of the kinematic model for a prescribed cylindrical workspace, considering geometric constraints that possibly lead to singularities of the mechanism. The aim is to determine the minimum dimensional parameters of the mechanism bodies for the proposed workspace. A method based on genetic algorithms was used to solve this problem. The method uses a cloud of points with the cylindrical shape of the workspace and checks the kinematic model for each of the points within the cloud. The evolution of the population (point cloud) provides the optimal parameters for the design of the delta robot. The development process of the linear delta robot with optimal dimensions for additive manufacture is presented. The dimensional synthesis enabled to design the mechanism of the delta robot in function of the prescribed workspace. Finally, the implementation of the robotic platform developed based on a linear delta robot in an additive manufacturing application using the Fused Deposition Modeling (FDM) technique is presented.

Keywords: additive manufacturing, delta parallel robot, dimensional synthesis, genetic algorithms

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Nyeng P. Gyang

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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

Authors: Li Dan, Zhao Junsuo, Zhang Wenjun

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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 708

Authors: Claude Tadonki

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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

Procedia PDF Downloads 284

Authors: Giselle Maggie-Fer Castañeda Lozano

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The main objective of this research was to explore the role of neural network architectures in simulating behavioral phenomena as a potential explanation for selective associations, specifically related to biological constraints on learning. Biological constraints on learning refer to the limitations observed in conditioning procedures, where learning is expected to occur. The study involved simulations of five different experiments exploring various phenomena and sources of biological constraints in learning. These simulations included the interaction between response and reinforcer, stimulus and reinforcer, specificity of stimulus-reinforcer associations, species differences, neuroanatomical constraints, and learning in uncontrolled conditions. The overall results demonstrated that by manipulating neural network architectures, conditions can be created to model and explain diverse biological constraints frequently reported in comparative psychology literature as learning typicities. Additionally, the simulations offer predictive content worthy of experimental testing in the pursuit of new discoveries regarding the specificity of learning. The implications and limitations of these findings are discussed. Finally, it is suggested that this research could inaugurate a line of inquiry involving the use of neural networks to study biological factors in behavior, fostering the development of more ethical and precise research practices.

Keywords: comparative psychology, connectionism, conditioning, experimental analysis of behavior, neural networks

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Authors: Sushish Baral, Pratibha Joshi, Yaman Maharjan

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Glaucoma is a chronic eye condition that causes vision loss that is irreversible. Early detection and treatment are critical to prevent vision loss because it can be asymptomatic. For the identification of glaucoma, multiple deep learning algorithms are used. Transformer-based architectures, which use the self-attention mechanism to encode long-range dependencies and acquire extremely expressive representations, have recently become popular. Convolutional architectures, on the other hand, lack knowledge of long-range dependencies in the image due to their intrinsic inductive biases. The aforementioned statements inspire this thesis to look at transformer-based solutions and investigate the viability of adopting transformer-based network designs for glaucoma detection. Using retinal fundus images of the optic nerve head to develop a viable algorithm to assess the severity of glaucoma necessitates a large number of well-curated images. Initially, data is generated by augmenting ocular pictures. After that, the ocular images are pre-processed to make them ready for further processing. The system is trained using pre-processed images, and it classifies the input images as normal or glaucoma based on the features retrieved during training. The Vision Transformer (ViT) architecture is well suited to this situation, as it allows the self-attention mechanism to utilise structural modeling. Extensive experiments are run on the common dataset, and the results are thoroughly validated and visualized.

Keywords: glaucoma, vision transformer, convolutional architectures, retinal fundus images, self-attention, deep learning

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Authors: Yiwei Huang, Chunyu Zhao, Jingjing Ding

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Electrical Resistivity Tomography has been widely used in the medicine and the geology, such as the imaging of the lung impedance and the analysis of the soil impedance, etc. Linear Back Projection is the core algorithm of Electrical Resistivity Tomography, but the traditional Linear Back Projection can not make full use of the information of the electric field. In this paper, an imaging method of Parallel Electrode Linear Back Projection for Electrical Resistivity Tomography is proposed, which generates the electric field distribution that is not linearly related to the traditional Linear Back Projection, captures the new information and improves the imaging accuracy without increasing the number of electrodes by changing the connection mode of the electrodes. The simulation results show that the accuracy of the image obtained by the inverse operation obtained by the Parallel Electrode Linear Back Projection can be improved by about 20%.

Keywords: electrical resistivity tomography, finite element simulation, image optimization, parallel electrode linear back projection

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Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

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The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: reliability, optimization, meta-heuristic, genetic algorithm, redundancy

Procedia PDF Downloads 313

Authors: Chen ChihYu, Tang Wen Tzu, Chen Kuang Hui

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Aim —To compare the dismount skill between Taiwanese and elite international gymnastics in parallel bars following the 2017-2020 code of points. Methods—The gymnasts who advanced to the parallel bars event finals of these four competitions including World Championships, Universiade, the National Games of Taiwan, and the National Intercollegiate Athletic Games of Taiwan both 2017 and 2019 were selected in this study. The dismount skill of parallel bars was analyzed, and the average difficulty score was compared by one-way ANOVA. Descriptive statistics were applied to present the type of dismount skill and the difficulty of each gymnast in these four competitions. The data from World Championships and Universiade were combined as the international group (INT), and data of Taiwanese National Games and National Intercollegiate Athletic Games were also combined as the national group (NAT). The differences between INT and NAT were analyzed by the Chi-square test. The statistical significance of this study was set at α= 0.05. Results— i) There was a significant difference in the mean parallel bars dismount skill in these four competitions analyzed by one-way ANOVA. Both dismount scores of World Championships and Universiade were significantly higher than in Taiwanese National Games and National Intercollegiate Athletic Games (0.58±0.08 & 0.56±0.08 > 0.42±0.06 & 40±0.06, p < 0.05). ii) Most of the gymnasts in World Championships and Universiade selected the 0.6-point skill as the parallel bars dismount element, and for the Taiwanese National Games and the National Intercollegiate Athletic Games, most of the gymnasts performed the 0.4-point dismount skill. iii) The result of the Chi-square test has shown that there was a significant difference in the selection of parallel bars dismount skill. The INT group used the E or E+ difficulty element as the dismount skill, and the NAT group selected the D or D- difficulty element. Conclusion— The level of parallel bars dismount in Taiwanese gymnastics is inferior to elite international gymnastics. It is suggested that Taiwanese gymnastics must try to practice the F difficulty dismount (double salto forward tucked with half twist) in the future.

Keywords: Artistic Gymnastics World Championships, dismount, difficulty score, element

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Authors: Jasbir Singh Gill, Baljit Singh

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Scheduling and mapping the application task graph on multiprocessor parallel systems is considered as the most crucial and critical NP-complete problem. Many genetic algorithms have been proposed to solve such problems. In this paper, two genetic approach based algorithms have been designed and developed with or without task duplication. The proposed algorithms work on two fitness functions. The first fitness i.e. task fitness is used to minimize the total finish time of the schedule (schedule length) while the second fitness function i.e. process fitness is concerned with allocating the tasks to the available highly efficient processor from the list of available processors (load balance). Proposed genetic-based algorithms have been experimentally implemented and evaluated with other state-of-art popular and widely used algorithms.

Keywords: parallel computing, task scheduling, task duplication, genetic algorithm

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Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of single-parameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: hybrid fault diagnosis, dynamic neural networks, nonlinear systems, fault tolerant observer

Procedia PDF Downloads 364

Authors: Tianyu Gao

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Digital architectures use computer-aided design, programming, simulation, and imaging to create virtual forms and physical structures. Today's customers want to know more about their buildings. They want an automatic thermostat to learn their behavior and contact them, such as the doors and windows they want to open with a mobile app. Therefore, the architectural display form is more closely related to the customer's experience. Based on the purpose of building informationization, this paper studies the steel structure design based on BIM. Taking the Zigan office building in Hangzhou as an example, it is divided into four parts, namely, the digital design modulus of the steel structure, the node analysis of the steel structure, the digital production and construction of the steel structure. Through the application of BIM software, the architectural design can be synergized, and the building components can be informationized. Not only can the architectural design be feedback in the early stage, but also the stability of the construction can be guaranteed. In this way, the monitoring of the entire life cycle of the building and the meeting of customer needs can be realized.

Keywords: digital architectures, BIM, steel structure, architectural design

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Authors: Jyothirmayee Pola

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Ideally, a test-driven development (TDD) or agile or any other process should be able to define and implement performance, scalability, and reliability (PSR) of the product with a higher quality of service (QOS) and should have the ability to fix any PSR issues with lesser cost before it hits the production. Most PSR test strategies for new product introduction (NPI) include assumptions about production load requirements but never accurate. NPE (New product Enhancement) include assumptions for new features that are being developed whilst workload distribution for older features can be derived by analyzing production transactions. This paper talks about how to shift left PSR towards design phase of release management process to get better QOS w.r.t PSR for any product under development. It also explains the ROI for future customer onboarding both for Service Oriented Architectures (SOA) and Microservices architectures and how to define PSR requirements.

Keywords: component PSR, performance engineering, performance tuning, reliability, return on investment, scalability, system PSR

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Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

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Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

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Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

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Authors: Zheng Sun, Weiwei Cui, Xiaodong Ma, Hongxin Jin, Dongpao Hong, Jinsong Yang, Jingyi Sun

Abstract:

With the improvement of the performance and complexity of modern equipment, automatic test system (ATS) becomes widely used for condition monitoring and fault diagnosis. However, the conventional ATS mainly works in a serial mode, and lacks the ability of testing several equipments at the same time. That leads to low test efficiency and ATS redundancy. Especially for a large majority of equipment under test, the conventional ATS cannot meet the requirement of efficient testing. To reduce the support resource and increase test efficiency, we propose a method of design for the parallel test based on the embedded system in this paper. Firstly, we put forward the general framework of the parallel test system, and the system contains a central management system (CMS) and several distributed test subsystems (DTS). Then we give a detailed design of the system. For the hardware of the system, we use embedded architecture to design DTS. For the software of the system, we use test program set to improve the test adaption. By deploying the parallel test system, the time to test five devices is now equal to the time to test one device in the past. Compared with the conventional test system, the proposed test system reduces the size and improves testing efficiency. This is of great significance for equipment to be put into operation swiftly. Finally, we take an industrial control system as an example to verify the effectiveness of the proposed method. The result shows that the method is reasonable, and the efficiency is improved up to 500%.

Keywords: parallel test, embedded system, automatic test system, automatic test system (ATS), central management system, central management system (CMS), distributed test subsystems, distributed test subsystems (DTS)

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Authors: A. Kok

Abstract:

The South African experience of the general upsurge in protest movements internationally is characterised by a tension between a neo-patrimonial state on the one hand, and a society with growing middle-class needs and interests on the other. This tension translates into local community service delivery protests – often violent in nature – that have been steadily increasing in number since 2008, student uprisings that have reached their height in October 2015, and various continuing local social #MustFall movements that are geared towards addressing government corruption and transforming neo-liberal structures. As a result, growing citizen (and non-citizen) revolt in South Africa has seen the (i) creeping securitization of the neo-patrimonial state and (ii) the 'top-down' misuse of a current 'bottom-up' people’s ideology, decoloniality, in an attempt by a faction in the ruling party (representing the neo-patrimonial state) to legitimize its actions and consolidate its power. The neo-patrimonial state’s creeping securitization and ideological positioning lead to a further mistrust of public institutions, people’s disengagement with traditional politics, and the creation of a 'parallel polis' by citizens and non-citizens that bypasses the official and oftentimes corrupt structures of the state. By applying the concept 'parallel polis' – originally developed by Václav Benda in connection with the movement Charter 77 in former Czechoslovakia – to a South African case study, it is illustrated that, even in the absence of overt oppression and the use of terror by a ruling elite, entrenched neo-patrimonialism can be potent enough to fuel the creation of various independent parallel public spheres (or, as a whole, understood as a 'parallel polis') to bypass dysfunctional state channels. A flourishing parallel polis offers possibilities for political, social and economic renewal. This is especially relevant in the consolidation of South Africa’s relatively young democracy.

Keywords: decoloniality, neo-patrimonialism, 'parallel polis', protest movements, South Africa, state securitization

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