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检索条件"主题词=Algorithm Design"

共 563 条记录，以下是331-340 订阅

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Modeling and Analyzing Key Performance Factors of Shared Memory MapReduce

Modeling and Analyzing Key Performance Factors of Shared Mem...

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26th IEEE International Parallel and Distributed Processing Symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Tiwari, Devesh Solihin, Yan N Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA

ISBN: (纸本)9780769546759

MapReduce parallel programming model has seen wide adoption in data center applications. Recently, lightweight, fast, in-memory MapReduce runtime systems have been proposed for shared memory systems. However, what factors affect performance and what performance bottlenecks exist for a given program, are not well understood. This paper builds an analytical model to capture key performance factors of shared memory MapReduce and investigates important performance trends and behavior. Our study discovers several important findings and implications for system designers, performance tuners, and programmers. Our model quantifies relative contribution of different key performance factors for both map and reduce phases, and shows that performance of MapReduce programs are highly input-content dependent. Our model reveals that performance is heavily affected by the order in which distinct keys are encountered during the Map phase, and the frequency of these distinct keys. Our model points out cases in which reduce phase time dominates the total execution time. We also show that data-structure and algorithm design choices affect map and reduce phases differently and sometimes affecting map phase positively while affecting reduce phase negatively. Finally, we propose an application classification framework that can be used to reason about performance bottlenecks for a given application.

关键词： Performance Factors MAPPING(MATHEMATICAL) maps execution time Phase shared memory Reduce Reduce Modeling algorithm design Parallel programming

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Teaching algorithms: Visual Language vs Flowchart vs Textual Language

Teaching Algorithms: Visual Language vs Flowchart vs Textual...

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IEEE Global Engineering Education Conference (EDUCON)

作者： Giordano, Daniela Maiorana, Francesco Univ Catania Dept Elect Elect & Comp Engn Viale A Doria 6 Catania Italy

ISBN: (纸本)9781479919086

There is a strong movement asserting the importance of quality education all over the world and for students of all ages. Many educators believe that in order to achieve this 21st century skills must be taught and that digital literacy should be coupled with rigorous Computer Science principles and computational thinking. Accordingly this work will describe a didactic experience in an introductory programming course by describing the context, pedagogical approach, content of the course based on a procedure-first approach, technologies used, research questions addressed, experimental design adopted, data collection and analysis and the main conclusion supported by qualitative and quantitative data. The research questions focus on understanding which is the best medium to design algorithms by comparing flow chart and the Scratch programming language and by evaluating whether using textual language is worth the effort of the syntactic burden imposed by these languages. An analysis of quantitative and qualitative data revealed that both a visual programming and a flow-chart approach are suitable for algorithm design with no statistical difference in terms of number of errors and time taken to write the corresponding code in a textual language. However, the high number of errors suggest that using visual programming allows the student to focus on the problem solving activities.

关键词： algorithm design initial programming teaching experience pedagogy

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Fast convergence for federated learning in OFDMA systems 32

Fast convergence for federated learning in OFDMA systems

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32nd IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE PIMRC)

作者： Ye, Deshi Chen, Songyang Wang, Can Zhejiang Univ Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781728175867

Device selection is a central issue for federated learning (FL) in a network with limited bandwidth resources, e.g., OFDMA. More participating devices in learning lead to faster convergence but will incur longer communication delays since less bandwidth will be allocated to each device. To balance between device participation and communication delay, Shi et al. [1] propose a joint bandwidth allocation and scheduling problem to achieve fast convergence. But their solution does not guarantee optimality and the computational complexity of the problem remains open. To address this issue, we propose a new algorithm that optimally solves this problem in polynomial-time by casting it into a joint cardinality-constrained device selection and bandwidth allocation problem. Experimental results on non-IID data sets show that our algorithm will attain faster convergence and higher accuracy than existing methods.

关键词： Federated learning Wireless Network Client Selection algorithm design

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Optimization algorithm of Neural Network on RF MEMS Switch for Wireless and Mobile Reconfigurable Antenna Applications

Optimization Algorithm of Neural Network on RF MEMS Switch f...

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2nd IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC)

作者： Chawla, Paras Khanna, Rajesh Thapar Univ ECE Dept Patiala Punjab India

ISBN: (纸本)9781467329255

A neural network based feed-forward back-propagation multi layered-perceptron algorithm is presented for the validation of changing the width of upper beam, dielectric and anchor arm length of RF switch designed specifically for reconfigurable antenna. These physical dimensions are varied and design structure is optimizing for low power consumption and to achieve acceptable level of isolation and insertion loss. The algorithm takes these new data samples during training from finite element method (FEM) based simulation tool Ansoft-HFSS. Results of the artificial neural network (ANN) are compared with those of the electromagnetic solver. The developed procedures allows the optimisation solutions of the design to be carried out by replacing repeated electromagnetic simulations whilst still retaining an excellent accuracy as compared with finite element modelling. This procedure requires less simulation time especially for the designing problem, where there is a need of reliable and fully functional methods. The calculated insertion loss and isolation results are in very good agreement with the experimental results reported elsewhere.

关键词： neural network wireless mobile RF switch Reconfigurable antenna algorithm design

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Safe Storage algorithm of Spreadsheet Data Based on Internet of Things Technology 5th

Safe Storage Algorithm of Spreadsheet Data Based on Internet...

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5th EAI International Conference on Advanced Hybrid Information Processing (ADHIP)

作者： Zong, Yong-sheng Huang, Guo-yan Yanshan Univ Coll Informat Sci & Engn Qinhuangdao 066004 Hebei Peoples R China Qinhuangdao Vocat & Tech Coll Qinhuangdao 066004 Peoples R China

ISBN: (纸本)9783030945541;9783030945534

The traditional data security storage algorithm of spreadsheet is mainly designed for single user scenario. When encountering the problem of multi-user, the traditional method will appear the problem of high delay and high repetition rate. In order to solve this problem, a new secure data storage algorithm is proposed in this paper. The intelligent gateway of Internet of Things is designed, the core board, the expansion board and the flash memory are designed, the multi-copy association model is established, and the association of the same source data is realized by copy cataloging. Finally, lossless coding is used to compress the data of spreadsheet, and the secure data storage algorithm based on Internet of Things is realized. In the simulation experiment, the traditional data security storage algorithm and the designed algorithm are used respectively. Experimental results show that the proposed algorithm can effectively reduce the latency, and the repetition rate of data storage is very low.

关键词： Internet of Things technology Electronic forms Data security storage algorithm design

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An Experimental Study of Machine Learning algorithms for Predicting Start-Up Success 6th

An Experimental Study of Machine Learning Algorithms for Pre...

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6th World Conference on Smart Trends in Systems, Security and Sustainability, WS4 2022

作者： Mishra, Ajai Jat, Dharm Singh Mishra, Durgesh Kumar Computer Science Namibia University of Science and Technology Windhoek Namibia Computer Science and Engineering Sri Aurobindo Institute of Technology Indore India

ISBN: (纸本)9789811976599

In recent years, our data storage and processing abilities have been enhanced significantly. Machine learning (ML) has become able to capture and analyze huge data without human interference. In this context, the ML techniques will also be used for measuring, predicting, and recommending the consequences of start-up success. Therefore, first, we studied some essential contributions which employ the ML models for business success. Next, a system architecture has been demonstrated that will be able to predict the success of a start-up and also recommend the key insights. Further, we proposed and implemented a start-up success prediction model. In this modeling, we initially used four supervised learning algorithms, namely support vector machine (SVM), k-nearest neighbor (KNN), Naïve Bayes, and logistic regression. In addition, two unsupervised algorithms such as k-means and fuzzy c-means (FCM) are implemented. During experiments, we have found these models are able to provide only 58% of classification accuracy. Therefore, we have proposed to use convolutional neural network (CNN) for training and prediction. In this context, we have crafted three variants of CNN models for experimental study. According to obtained results, we found the first model provides only 48% classification accuracy, the second model provides (69%) accuracy, and the third model provides higher accuracy (74%). Thus, we found promising to work with the CNN and Crunchbase datasets. Therefore, in near future, we proposed to design a CNN model with the feature engineering processes. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： algorithm design Business data analytics Handholding of start-ups Machine learning Recommendation system Support system

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Modelling of Process Control that have Time Delay Verification of algorithms Suitable for Process Control Containing Time Delay by Simulation

Modelling of Process Control that have Time Delay Verificati...

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12th International Conference on Computer Modelling and Simulation (UKSim)

作者： Alexik, Mikulas Univ Zilina Dept Tech Cybernet Fac Management Control & Informat Zilina Slovakia

ISBN: (纸本)9780769540160

This paper describes such extension of known DB(n) control algorithm which improve behaviour quality of control processes with time delay, This extension, called eDBd algorithm, was derived by author. It can function even if controller output is limited. The synthesis was derived for control loop with proportional third order behaviour of controlled plant. The algorithm can be generalized for controlled plants with higher order and applied for plants with non-minimal phase, plant with time delay and its combination, as is shown in simulation experiments. For experimental evaluation of the control algorithm in real time, hardware in loop simulation was used. Rather, analogue model of real plant with A/D and D/A converters and PC as a controller.

关键词： algorithm design time delay sampling interval simulation experimentst

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Harnessing Phenotypic Diversity towards Multiple Independent Objectives

Harnessing Phenotypic Diversity towards Multiple Independent...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Smith, Davy Tokarchuk, Laurissa Wiggins, Geraint Queen Mary Univ London Sch Elect Engn & Comp Sci London E1 4NS England

ISBN: (纸本)9781450343237

Multiple assessment directed novelty search (MADNS), introduced by the authors in [20], is an extension to the novelty search algorithm which exploits the observation that populations optimised for phenotypic novelty may contain solutions to multiple independent and conflicting objectives. It has been shown that, through the application of MADNS, an evolutionary trajectory may be simultaneously directed towards multiple conflicting objectives. Previous results from a series of simulated maze navigation experiments have shown that MADNS may significantly outperform novelty search in domains where the potential for phenotypic exploration is high [20]. In this paper we further explore the MADNS algorithm, assessing the effect upon the diversity and performance of the population as the phenotypic landscape increases. A series of experiments in domains with multiple conflicting objectives and expanding areas of irrelevant space show that the relative performance gain of MADNS increases alongside the potential for exploration. We conclude that, as the potential for exploration within a domain expands, the importance of directing novelty becomes ever more necessary.

关键词： Novelty search algorithm design phenotypic diversity neuroevolution evolutionary robotics

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Brace: A pairing algorithm for mentorship using compatibility score 10

Brace: A pairing algorithm for mentorship using compatibilit...

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10th IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT)

作者： Gupta, Ishita Purohit, Geetanjali Kumari, Aparna Ray, Subhasree Kumar, Prasun Kumar, Sushil Ganpat Univ CSE Dept Mehsana Gujarat India Swinburne Univ Technol Dept CSE Hawthorn Campus Melbourne Vic Australia Nirma Univ Inst Technol Dept CSE Ahmadabad Gujarat India Sharda Univ Dept Life Sci SBSR Greater Noida India MNR Med Coll & Hosp MNR Fdn Res Innovat Mohd Shapur Telangana India Jawaharlal Nehru Univ Sch Comp & Syst Sci New Delhi India

ISBN: (纸本)9798350385939;9798350385922

Pairing is a vital task in industries today for rational allocation of resources and generating the best match for high productivity. To develop the most compatible match for a huge database, pairing the records without the help of an automated approach is impractical. so this paper proposes a computerized pairing algorithm, i.e., Brace, which is designed to cater to the most compatible human resource pairing. A few of its applications include pairing mentor-mentee, co-workers for a project, etc. Brace generates a score for each field, affecting the pairing of every record to create a final compatibility matrix. The matrix is cumulative of all individual compatibility scores for the fields of every record on both category sides. The paper takes the intricacies of algorithm design through a use case of mentor-mentee pairing. Finally, Brace performance evaluation demonstrates its effectiveness based on various parameters.

关键词： Compatibility Score algorithm design Matching Theory Inference System Matrix Computation Block-chain

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The Development of Markov Random Field Theory and Applications on Image Segmentation algorithm

The Development of Markov Random Field Theory and Applicatio...

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International Conference on Communication and Electronics Systems (ICCES)

作者： Zhang, Renqian Huang, Yuru Fu, Sirui Fudan Univ Renqian Zhang Elect Engn Informat Dept Shanghai Peoples R China Beijing Univ Technol Beijing Peoples R China Lanzhou Univ Lanzhou Peoples R China

ISBN: (纸本)9781509010660

Image segmentation algorithm is to divide the images into several regions with specific and unique characteristics, and is an important technology to extract the interested target. Image segmentation is the key step to realize the research from general image processing into image analysis, and is vital preprocessing method of image recognition and computer vision. We cannot obtain correct recognition if we do not have correct segmentation. Nevertheless, the only basis of segmentation process is brightness or color of pixels in an image. In the processing of computer automatic segmentation, we experience several problems, such as uneven illumination, effect of noise, indistinct part in image, and shadow, and these factors may cause false segmentation. In order to overcome the disadvantages of the traditional segmentation algorithm, in this paper, we propose a novel segmentation algorithm based on Markov Random Field. The segmentation algorithm proposed in this paper is based on Markov Random Field Mode and Bayesian theory, and we determine the objective function in image segmentation problem on the basis of optimality criterion of statistical decision and estimation theory. Some optimization algorithms are used to obtain the maximum possible distribution of Markov Random Field which satisfy these conditions. The experimental result reflects the effectiveness and robustness of our algorithm. As a supplement, we analyze the development trend of the Markov Random Field theory.

关键词： Markov Random Field image segmentation Bayesian theory mathematical optimization algorithm design

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