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检索条件"主题词=Software Algorithms"

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Contactless access control system for critical objects based on deep learning neural networks

Contactless access control system for critical objects based...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Alexander A. Tyutyunnik Ekaterina I. Lobaneva Alexey I. Lazarev Management National Research University “Moscow Power Engineering Institute” (Branch) in Smolensk Smolensk Russian Federation

ISBN: (数字)9781728183985

ISBN: (纸本)9781728183992

The paper presents a software product that enables contactless identity verification at various sites using Leap Motion controller and neural network module, which will improve security at critical sites. The authors present the results of a study of numerical sequence generation for identification through two-factor authentication and a predictive hand model recognition module to perform automatic identification of an individual. The process of verification of an identifiable fingerprint is based on a decision support system-by means of a fuzzy rule base, the percentage coefficient of accessibility for an identifiable person is determined. In addition, the algorithm has been optimised to work with devices based on ARM single board computers-the deployment is in this case an independent customer authorisation unit at a remote distance from the information processing server with the varied possibility of working offline and online modes.

关键词： Neural networks software algorithms Authentication Predictive models Prediction algorithms software Servers

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Robot Flexible Polishing Methods for Curved Mold and Adaptive Impedance Control

Robot Flexible Polishing Methods for Curved Mold and Adaptiv...

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International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)

作者： Yong Yang Shengzong Zhou Guangsheng Chang Jinxing Yang Weilong Huang Jun Li Quanzhou Institute of Equipment Manufacturing Chinese Academy of Science Quanzhou China Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou China College of Mechanical Engineering and Applied Electronic Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781665417334

In the automatic polishing process by industrial robot, the curvature variation at the polishing point will cause the problem of uneven polishing quality. To solve the problem, polishing methods based on constant down displacement and constant downforce are analyzed according to elliptical Hertzian contact theory. Then, the constant stress polishing methods based on displacement and force are proposed. Simulations are performed by finite element analysis software. The stress changes of four polishing methods during the polishing process are compared. Finally, a force control strategy based on speed regulation and impedance control algorithm is adopted to ensure the stability of the tool and workpiece contact during machining. The results show that stable polishing stress can be obtained by the constant stress polishing methods based on down displacement and downforce. Therefore, it is feasible to control the uniformity of polishing quality by adjusting the displacement or downforce of an industrial robot.

关键词： Service robots software algorithms Machining Stability analysis software Regulation Finite element analysis

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Speed Control Based PID Configuration of a DC Motor for An Unmanned Agricultural Vehicle

Speed Control Based PID Configuration of a DC Motor for An U...

引用

International Conf on Electrical and Electronic Engineering (ICEEE)

作者： Yavuz Bahadir Koca Yilmaz Aslan Bariş Gökçe Afyon Vocational School Afyon Kocatepe University Afyonkarahisar Turkey Faculty of Engineering Kütahya Dumlupinar University Kütahya Turkey Faculty of Engineering and Architecture Necmettin Erbakan University Konya Turkey

DC motors are used in many areas with their high starting torques and speed regulation features. In particular, the operation of DC motors must control their speed accurately in order to obtain the desired efficiency. Traditional PID control algorithm is preferred for its simplicity and usability in most industrial applications. This article describes the design and implementation of a PID control strategy using a simulation software to control the speed of a DC motor whose parameters are unknown. The mathematical model of the control system is obtained through a system identification by applying an input signal. Using obtained the mathematical model and Bode diagram techniques, a single input / single output configurator was designed. The PID control algorithm parameters P, I and D values are obtained by auto tuning methods. Here, an online identification system is used to set new control parameters. This study, PID controller is implemented using a simulation software and microcontroller integrated control board. The accuracy of the work is verified by the results of the experiments made with motor parameters.

关键词： Adaptation models PI control Microcontrollers software algorithms DC motors software System identification

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Motor Imagery Classification Based on Hybrid Feature Extraction and Deep Neural Network

Motor Imagery Classification Based on Hybrid Feature Extract...

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Artificial Intelligence and Smart Systems (ICAIS), International Conference on

作者： Rameshwar D. Chintamani Parmalik Kumar Rajneesh Karan Madhyanchal Professional University Bhopal India

ISBN: (数字)9781728195377

ISBN: (纸本)9781728195384

The brain-computer interface increases the capacity of critical diseases diagnosis in neurological science. The increased capacity of diagnosis uses motor imagery electroencephalogram signals. This paper prosed hybrid feature extraction methods based on wavelet packet decomposition and common spatial pattern. The hybrid techniques are very efficient instead of discrete wavelet transform and common spatial pattern. For the process of classification proposed deep neural network-based model. The proposed model enhances the classification ratio despite the machine learning algorithm. The method of classification ratio varies 8-12% instead of the machine learning algorithm. The multi-kernel approach of the deep neural network increases the sample size and boosts data mapping and performance of the classification algorithm. The proposed algorithm is tested on BCI competition-IV dataset (2a and 2b). The simulation process has used the MATLAB R2014a software; this software is a well-known algorithm analysis software. For the evaluation process of result, four parameters such as accuracy, sensitivity, specificity and error are measured. These parameters compare with existing methods of motor imagery EEG classification. The performance of parameters indicates the efficiency of proposed algorithm when compared with the existing methods.

关键词： Machine learning algorithms software algorithms Feature extraction Brain modeling software Classification algorithms Biological neural networks

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Constant-time BCH Error-correcting Code

Constant-time BCH Error-correcting Code

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Walters, Matthew Roy, Sujoy Sinha Univ Birmingham Sch Comp Sci Birmingham W Midlands England

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133201

Error-correcting codes can be useful in reducing decryption failure rate of several lattice-based and code-based public-key encryption schemes. Two schemes, namely LAC and HQC, in NIST's round 2 phase of its post-quantum cryptography standardisation project use the strong error-correcting BCH code. However, direct application of the BCH code in decryption algorithms of public-key schemes could open new avenues to the attacks. For example, a recent attack [1] exploited non-constant-time execution of BCH code to reduce the security of LAC. In this paper we analyse the BCH error-correcting code, identify computation steps that cause timing variations and design a constant-time BCH implementation. We implement our algorithm in software and evaluate its resistance against timing attacks by performing leakage detection tests. To study the computational overhead of the countermeasures, we integrated our constant-time BCH code in the reference and optimised implementations of the LAC scheme as a case study, and observed nearly 1.1 and 1.4 factor slowdown respectively for the CCA-secure primitives.

关键词： Timing Arrays Indexes Cryptography Error correction codes Decoding software algorithms

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A Convolutional Neural Network for End to End Structural Prediction and Lane Detection for Autonomous Vehicle

A Convolutional Neural Network for End to End Structural Pre...

引用

International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT)

作者： Md. Rashidul Islam Taushif Ahmed Siddique Md. Imtiazul Hoque Sakib Shafayat Hossain International Islamic University Chittagong Chittagong Bangladesh

ISBN: (纸本)9781665495233

Real-time automated road lane recognition is an essential aspect of a smart vehicle safety system. The driver assistance system is the most significant advancement for intelligent automobiles. The vision-based driver assistance system of intelligent vehicles provides automatic road lane detection. This paper proposes a novel approach based on CNN for recognizing road lane and road border markings in the development of autonomous vehicle navigation. At first, it transforms the image of the RGB street scene to a gray image and then uses the flood-fill technique to identify the gray image’s related components. Following that, the road region, which is the largest connected component in the labeled image, is extracted using the maximum width and number of pixels. Finally, the outer region is excluded, and the road lane and road border markers are separated from the associated components. The numerical results prove the applicability of the proposed algorithm on both straight and slightly curved road scene photos under various daylight circumstances and the presence of road shadows. The driver support system consists of a camera support system that captures real-time pictures of the vehicle environs and displays pertinent information to the driver. As a result, intelligent vehicles automatically collect information about the road lane and the vehicle’s position corresponding to the lane. The system employed by smart vehicles thus offers the means of alerting drivers who swerve off the lane without using the blinker. Smart vehicles will therefore clearly improve traffic safety if they are extensively adopted.

关键词： Lane detection Image color analysis Roads Image edge detection software algorithms Transforms Prediction algorithms

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ROS Based Heterogeneous Multiple Robots Control Using High Level User Instructions

ROS Based Heterogeneous Multiple Robots Control Using High L...

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IEEE Region 10 International Conference TENCON

作者： U.U.Samantha Kumara Rajapaksha Chandimal Jayawardena Bruce A. MacDonald Sri Lanka Institute of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Malabe Sri Lanaka Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (纸本)9781665495332

Heterogeneous Multiple Robots(HMR) can be used in daily life for smart homes and industry. The differences in implementing different HMR can be minimized using middle-ware like Robot Operating System (ROS). However, the ROS topics, nodes, and message formats to subscribe and publish can differ from one robot to another. When a user expresses high-level instructions through the Web interface, all multiple robots must understand instructions uniformly and take the actions accordingly without considering each robot's internal software and hardware implementation. This paper represents an optimized ontology-based algorithm for HMR registration and control for high-level instructions. Autonomous robot registration was achieved using an ontology-based optimized algorithm. User-level high-level instructions are processed using an ontology-based algorithm to determine the corresponding actions for each robot. Finally, autonomous publication and subscription to different ROS topics were implemented using another optimized algorithm. The evaluation of the proposed algorithms was completed with Turtlebot, Husky and TiaGo robots using gazebo.

关键词： Industries Service robots Operating systems software algorithms Robot control Smart homes software

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A Testing Method for Object-oriented Program based on Adaptive Random Testing with Variable Probability

A Testing Method for Object-oriented Program based on Adapti...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Tianxiang Lv Qihao Bao Haibo Chen Chi Zhang School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China

ISBN: (纸本)9781665478373

Object-oriented program (OOP) is very popular in these years for its advantages, but the testing method for OOP is still not mature enough. To deal with the problem that it is impossible to generate the probability density function by simply numeralizing a point in the test case caused by the complex structure of the object-oriented test case, we propose the Adaptive Random Testing through Test Profile for Object-Oriented software (ART TP -OO). It generates a test case at the edge of the input field and calculates the distance between object-oriented test cases using Object and Method Invocation Sequence Similarity (OMISS) metric formula. And the probability density function is generated by the distance to select the test cases, thereby realizing the application of ART TP algorithm in OOP. The experimental results indicate the proposed ART TP -OO consumes less time cost without reducing the detection effectiveness.

关键词： Measurement Costs Conferences Subspace constraints software algorithms software quality Probability density function

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A Hybrid Adaptive Quantum Behaved Particle Swarm Optimization Algorithm Based Multilevel Thresholding for Image Segmentation

A Hybrid Adaptive Quantum Behaved Particle Swarm Optimizatio...

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Information Communication and software Engineering (ICICSE), IEEE International Conference on

作者： Hong-Qi Wang Xin-Wen Cheng Guo-Chao Chen School of Computer Science and Engineering Sichuan University of Science & Engineering Zigong China

ISBN: (纸本)9781665430302

Thresholding is a frequently used method in image processing because of its consistency and low computational cost. Kapur's method is an important threshold segmentation method. However, it is computationally expensive when extended to multilevel thresholding since it exhaustively searched the optimal thresholds to optimize the objective functions. Recently, metaheuristic algorithms have been successfully applied for thresholding problems. A multi-threshold segmentation of 2D Kapur's entropy based on hybrid adaptive quantum behaved particle swarm optimization (HAQPSO) algorithm is proposed. Then, the Gaussian chaotic map model and the Levy flight are employed to increase the search ability of HAQPSO algorithm and balance the exploitation and exploration. The HAQPSO algorithm optimizes the Kapur's multi-threshold method to conduct experiments on standard images, satellite images and sport images. The experimental results show that HAQPSO is an effective image segmentation method, with high segmentation accuracy, good convergence, strong anti-noise and certain engineering practicability.

关键词： Image segmentation Thresholding (Imaging) Chaotic communication software algorithms Search problems Entropy Particle swarm optimization

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Development of Onboard Processing Capabilities for a Slocum Glider Acoustic Doppler Current Profiler

Development of Onboard Processing Capabilities for a Slocum ...

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OCEANS

作者： Joseph C. Gradone Elias J. Hunter Jerald Mullison Travis N. Miles Center for Ocean Observing Leadership (COOL) Rutgers University New Brunswick USA Teledyne RD Instruments Poway USA

ISBN: (纸本)9781665427883

A growing number of increasingly complex instruments have been integrated into autonomous underwater vehicles over the past two decades. While these newly glider integrated sensors provide unprecedented insight into ocean processes, the large data volumes collected by these instruments cannot be efficiently telemetered to shore. Shoreside processing is not possible until after recovery and the use of these data for realtime applications is limited. If vehicles are lost during challenging conditions, or in denied areas, no useful data will be recovered. Thus, there is a need for a sensor agnostic real-time processing software and hardware architecture for autonomous underwater vehicles. The findings detailed here describe initial results from the development and testing of an acoustic Doppler current profiler (ADCP) linear inversion algorithm that will serve as the first test case for the implementation of real-time data processing system onboard a Slocum glider. A new Teledyne RD Instruments Pathfinder ADCP mounted on Slocum glider RU33 and deployed off the coast of New Jersey near a moored buoy with downward looking ADCP. Though quality controls steps and several derived parameters warrant further analysis, initial results from the linear inversion algorithm are highly correlated with the buoy current measurements.

关键词： Autonomous underwater vehicles Instruments software algorithms Computer architecture Real-time systems Hardware Acoustics

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