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A Novel Iterative Velocity Control algorithm and Its FPGA Implementation Based on Trigonometric Function

Chinese Journal of Electronics 2019年第2期28卷 237-245页

作者： WEN Quangang LIANG Yanchun Adriano Tavares Ricardo Teixeira WU Chunguo Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Department of Industrial Electronics University of Minho Campus de Azurm

The servo motor’s flexible acceleration/deceleration(acc/dec) control is an emerging research topic in the automation field. A velocity control algorithm based on trigonometric function is proposed in this *** required parameters, it transforms trigonometric calculations into elementary mathematical operations and calculates the velocity controlling values iteratively, which could avoid trigonometric calculation and reduce the computation time. Experimental results show that the proposed algorithm is suitable for implementation on field programmable gate arrays and achieves a flexible controlling, enhancing both the equipment’s stability and reliability. It is promising to significantly improve the high-speed computerized numerical control equipment’s controlling accuracy, without a huge hardware resource consumption.

关键词： Acceleration Velocity control algorithm design and analysis Field programmable gate arrays Servomotors

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Uncertainty and Equivalence Relation analysis for Hesitant Fuzzy-Rough Sets and Their Applications in Classification

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COMPUTING IN SCIENCE & ENGINEERING 2019年第6期21卷 26-39页

作者： Zhang, Haiqing Li, Daiwei Wang, Tao Li, Tianrui Yu, Xi Bouras, Abdelaziz Chengdu Univ Informat Technol Sch Software Engn Chengdu Sichuan Peoples R China UJM St Etienne INSA Lyon DISP Lab St Etienne France Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu Sichuan Peoples R China Chengdu Univ Sch Informat Sci & Engn Chengdu Sichuan Peoples R China Qatar Univ Comp Sci Dept ictQATAR Doha Qatar

The fusion of hesitant fuzzy set (HFS) and fuzzy-rough set (FRS) is explored and applied into the task of classification due to its capability of conveying hesitant and uncertainty information. In this paper, on the basis of studying the equivalence relations between hesitant fuzzy elements and HFS operation updating, the target instances are classified by employing the lower and upper approximations in hesitant FRS theory. Extensive performance analysis has been conducted including classification accuracy results, execution time, and the impact of k parameter to evaluate the proposed hesitant fuzzy-rough nearest-neighbor (HFRNN) algorithm. The experimental analysis has shown that the proposed HFRNN algorithm significantly outperforms current leading algorithms in terms of fuzzy-rough nearest-neighbor, vaguely quantified rough sets, similarity nearest-neighbor, and aggregated-similarity nearest-neighbor.

关键词： Classification algorithms Approximation algorithms Fuzzy sets algorithm design and analysis Training Uncertainty hesitant fuzzy set fuzzy-rough sets hesitant fuzzy rough nearest neighbor classification equivalence relation

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An Unsupervised Binary and Multiple Change Detection Approach for Hyperspectral Imagery Based on Spectral Unmixing

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2019年第12期12卷 4888-4906页

作者： Jafarzadeh, Hamid Hasanlou, Mahdi Univ Tehran Sch Surveying & Geospatial Engn Coll Engn Tehran *** Iran

Over the last decade, developments in hyperspectral sensors have caused an increase in the use of hyperspectral images (HSIs) due to fine spectral resolution, which has lead to the precise extraction and identification of the materials of the observed scene. Change detection (CD) is one of the most fundamental applications of remote sensing, which provides timely change information about Earth's surface. This article presents unsupervised binary and multiple CD approaches using bitemporal HSIs based on spectral unmixing (SU) and proposes a new formulation for CD without using threshold selection methods. SU is a powerful technique for analyzing hyperspectral data. CD, by incorporating unmixing, has the potential to obtain subpixel-level information from data. The proposed framework is organized in the context of four steps: Step 1) estimating the number of endmembers, extracting the endmember's signature, calculating abundances, and applying similarity assessment to identify corresponding endmembers;Step 2) discriminating pure changed pixels;Step 3) discriminating mixed changed pixels, and combining results by pure changed pixels to produce a binary change map (BCM);and Step 4) labeling changed pixels based on the proposed formulation and producing a multiple change map. This article presents new strategies for binary and multiple CD, which provide a better figure of merit as they do not need the threshold selection methods and are less time-consuming. The experiments on real hyperspectral datasets revealed that both CD accuracy and computational performance benefited from these strategies. Experimental results proved the high performance of the proposed approaches for detecting changes in both binary and multiple cases.

关键词： Hyperspectral imaging algorithm design and analysis Satellites Abundance binary change map (BCM) change detection (CD) endmember hyperspectral multiple change map (MCM) spectral unmixing (SU)

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MPSAGA: a matrix-based pair-wise sequence alignment algorithm for global alignment with position based sequence representation

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2019年第7期44卷 1-17页

作者： Lakhani, Jyoti Khunteta, Ajay Choudhary, Anupama Harwani, Dharmesh Maharaja Ganga Singh Univ Dept Comp Sci Bikaner 334004 India Poornima Univ Dept Comp Engn Jaipur Rajasthan India Keen Coll Dept Comp Sci Bikaner India Maharaja Ganga Singh Univ Dept Microbiol Bikaner 334004 India

The proposed algorithm is a novel matrix-based global pair-wise sequence alignment with a de novo sequence representation. Needleman-Wunsch, noblest, Emboss-Needle, ALIGN, LALIGN, FOGSAA, DIALIGN, ACANA, MUMmer, etc. are few other algorithms that are most commonly used for global pair-wise sequence alignment. Needleman-Wunsch algorithm is one of the most popular algorithms that provides the best possible pair-wise sequence alignment, but the algorithm output is associated with high time and space complexities. To resolve these complex issues, researchers have proposed several algorithms to reduce time and space complexities in the pair-wise sequence alignment. Most of these algorithms provide solutions, but compromise the optimal result in favor of plummeting time and space complexities. An attempt has been made in the present research to develop MPSAGA and a completely unique positional matrix (PM) based sequence representation to deal with the time and space complexities without compromising sequence alignment results (MPSAGA is in public domain available at https://***/JyotiLakhani1/MPSAGA). A benchmarking of the proposed algorithm has also been performed with other popular pair-wise sequence alignment algorithms with and without positional matrix-based sequence representation. The use of an integer instead of string data type and exclusive clustering method in MPSAGA with positional matrix based sequence representation resulted in a noteworthy reduction in the memory usage (space) and execution time in the pair-wise alignment of biological sequences.

关键词： Clustering algorithms algorithm design and analysis data mining dynamic programming

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Congestion-Minimizing Network Update in Data Centers

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2019年第5期12卷 800-812页

作者： Zheng, Jiaqi Xu, Hong Chen, Guihai Dai, Haipeng Wu, Jie Nanjing Univ State Key Lab Novel Software Technol Nanjing Shi 210000 Jiangsu Sheng Peoples R China City Univ Hong Kong Dept Comp Sci Kowloon Tong Hong Kong Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA

The SDN control plane needs to frequently update the data plane as the network conditions change. Since each switch updates its flow table independently and asynchronously, the transition of data plane state-if done directly from the initial to the final stage-may result in serious flash congestion. Prior work strives to find a congestion-free update plan with multiple stages, each with the property that there will be no congestion independent of the update order. Yet congestion-free update may prevent the network from being fully utilized. It also requires solving a series of LP which is time-consuming. In this paper, we propose congestion-minimizing update and focus on two general problems: The first is to find routing at each intermediate stage that minimizes transient congestion for a given number of intermediate stages. The second is to find the minimum number of intermediate stages and an update plan for a given maximum level of transient congestion. We formulate them as two optimization programs and prove their hardness. We propose a set of algorithms to find the update plan in a scalable manner. Extensive experiments with Mininet show that our solution reduces update time by 50 percent and saves control overhead by 38 percent compared to prior work.

关键词： Routing Switches Transient analysis Approximation algorithms algorithm design and analysis Wide area networks Optimization SDN data center networks network update transient congestion

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Randomized Admission Policy for Efficient Top-k, Frequency, and Volume Estimation

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IEEE-ACM TRANSACTIONS ON NETWORKING 2019年第4期27卷 1432-1445页

作者： Ben Basat, Ran Chen, Xiaoqi Einziger, Gil Friedman, Roy Kassner, Yaron Harvard Univ Dept Comp Sci Cambridge MA 02138 USA Princeton Univ Dept Comp Sci Princeton NJ 08540 USA Ben Gurion Univ Negev Dept Comp Sci IL-84105 Beer Sheva Israel Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

Network management protocols often require timely and meaningful insight about per flow network traffic. This paper introduces Randomized Admission Policy (RAP) -a novel algorithm for the frequency, top-k, and byte volume estimation problems, which are fundamental in network monitoring. We demonstrate space reductions compared to the alternatives, for the frequency estimation problem, by a factor of up to 32 on real packet traces and up to 128 on heavy-tailed workloads. For top-k identification, RAP exhibits memory savings by a factor of between 4 and 64 depending on the workloads' skewness. These empirical results are backed by formal analysis, indicating the asymptotic space improvement of our probabilistic admission approach. In Addition, we present d-way RAP, a hardware friendly variant of RAP that empirically maintains its space and accuracy benefits.

关键词： algorithm design and analysis approximation algorithms

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A Fast Logic Mapping algorithm for Multiple-Type-Defect Tolerance in Reconfigurable Nano-Crossbar Arrays

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2019年第4期7卷 518-529页

作者： Tunali, Onur Altun, Mustafa Istanbul Tech Univ Dept Nanosci & Nanoengn TR-34469 Istanbul Turkey Istanbul Tech Univ Dept Elect & Commun Engn TR-34469 Istanbul Turkey

Unlike conventional CMOS circuits, nano-crossbar arrays have considerably high defect rates. Multiple-type defects randomly occur both on crosspoint switches and wires that substantially complicates the design phase of the circuits with an elimination of systematic design choices. In order to overcome this problem, a logic mapping methodology is presented in this paper. A fast heuristic algorithm using pre-mapping logic morphing, defect oriented adaptive sorting, matching with Hadamard multiplication, and backtracking is introduced. The proposed algorithm covers both crosspoint defects including stuck-open and stuck-closed types and wire defects including bridging and broken types. Effects of stuck-closed defects, mostly disregarded in the literature, are studied in depth. In simulations, an industrial benchmark suit is used for obtaining runtime and success rate values of the proposed algorithm in comparison with those of the existing algorithms in the literature. A relative accuracy evaluation is also given in comparison with exact mapping techniques. Finally, the steps of the algorithm that are based on pre-mapping and heuristic matching techniques, are separately justified with experimental results.

关键词： Wires algorithm design and analysis Frequency modulation Sorting Logic functions Programmable logic arrays Switches Reconfigurable nano-crossbars defect tolerance switching arrays

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Warning Propagation algorithm for the MAX-3-SAT Problem

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2019年第4期7卷 578-584页

作者： Wang, Xiaofeng Jiang, Jiulei Beifang Univ Nationalities Coll Comp Sci & Engn Ningxia 750021 Peoples R China

Message propagation algorithms are widely used in approximate inference e.g. Cyber-Social Data Processing and Intelligence Mining. Especially, these algorithms enable hard region become narrower and thus they are very effective in solving satisfiability problems. Warning Propagation algorithm is one kind of basic message propagation algorithms. Based on this Warning Propagation algorithm, we designed a WPY algorithm to solve the MAX-3-SAT problem. We obtained a set of stable warning information, and the value of the partial variable is decided by using the stable set with high probability. Finally, the experiment results show that the WPY algorithm can effectively solve the random MAX-3-SAT instances.

关键词： algorithm design and analysis Approximation algorithms Convergence Heuristic algorithms Inference algorithms Software algorithms Computer science Warning propagation algorithm maximum satisfiability problems factor graph

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An Immunization Framework for Social Networks Through Big Data Based Influence Modeling

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2019年第6期16卷 984-995页

作者： Peng, Sancheng Wang, Guojun Zhou, Yongmei Wan, Cong Wang, Cong Yu, Shui Niu, Jianwei Guangdong Univ Foreign Studies Sch Informat Sci & Technol Guangzhou 510420 Guangdong Peoples R China Guangdong Univ Foreign Studies Lab Language Engn & Comp Guangzhou 510420 Guangdong Peoples R China Guangzhou Univ Sch Comp & Educ Software Guangzhou 510006 Guangdong Peoples R China Cent South Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China Northeastern Univ Qinhuangdao Sch Comp & Commun Engn Qinhuangdao 06600 Hebei Peoples R China Deakin Univ Sch Informat Technol 221 Burwood HWY Burwood Vic 3125 Australia Beihang Univ State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China

Social networks are critical in terms of information or malware propagation. However, how to contain the spreading of malware in social networks is still an open and challenging issue. In this paper, we propose a novel defending method through big data based influence modeling. We first establish a social interaction graph based on big data sets of the studied object. Based on the graph, we are able to measure direct influence of individuals by computing each nodes strength, which includes the degree of the node and the total number of messages sent by each user to her friends. Then, we design an algorithm to construct influence spreading tree using the breadth first search strategy, and measure indirect influence of individuals by traversing the tree. We identify the top $k$k influential nodes among all the nodes via the social influence strength, and propose an immunization algorithm to defend social networks against various attacks. The extensive experiments show that influence can spread easily in social networks, and the greater the influence of initial spread node is, the more impact it is on the malware propagation in social networks. The proposed method provides an effective solution to the prevention of malware or malicious messages propagation in social networks.

关键词： Malware Social network services Big Data Mobile communication Smart phones algorithm design and analysis Computational modeling Malware propagation social influence big data propagation model containment scheme immunization algorithm

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Distributionally Robust Radio Frequency Localization

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2019年第2期5卷 390-403页

作者： Jagadeesan, Nachikethas A. Krishnamachari, Bhaskar Univ Southern Calif Dept Elect Engn Los Angeles CA 90089 USA

We consider the problem of estimating the location of an RF-device using observations such as received signal strengths, generated according to an uncertain distribution from a set of transmitters with known locations. We present a distributionally robust formulation of the localization problem that explicitly takes into account the uncertainty in the distribution that generates the observations. We identify the structure of the robust solution and demonstrate how to construct the optimization problem so that it is easily computed, and always yields the optimal solution. We show that the robust estimate outperforms traditional methods in the presence of modeling errors, while remaining close to the traditional estimate when the modeling is exact. This suggests that the formulation presented here is an attractive option in applications where we use a model that may not be an exact fit to our environment or if changes in our environment have induced errors in an empirically derived model.

关键词： Indoor environments algorithm design and analysis estimation optimization Bayes methods

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