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检索条件"任意字段=2021 3rd International Conference on Computer Modeling, Simulation and Algorithm, CMSA 2021"

共 219 条记录，以下是91-100 订阅

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Copy-Move Image Forgery Detection Using SURF, SIFT, and KAZE 3rd

Copy-Move Image Forgery Detection Using SURF, SIFT, and KAZE

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3rd international conference on Machine Learning, Advances in Computing, Renewable Energy and Communication, MARC 2021

作者： Rani, Anuj Jain, Ajit Department of Computer Science Banasthali Vidyapith Rajasthan Tonk India Department of Computer Science G L Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9789811928277

In this digital world, image forgery is the most common cause for any digital forgery. Nowadays, people accept digital images blindly, even without checking their integrity and authenticity. One of the critical facts in digital image forensics is that we need to keep high confidence in forgery detection algorithms. In this work, multiple image forger detection algorithms are evaluated to check their efficacy using their detection accuracy and execution time. Discrete wavelet transform (DWT) is used for image decomposition at the preprocessing stage. The objective of this work is to suggest a best copy-move forgery detection algorithm among SIFT, SURF, and KAZE. For modeling the code, MATLAB is used as a programming language. Using the SURF algorithm, the accuracy rate is 56.50% with average execution time 1.28 s, while it is 66.75% and 2.78 s using SIFT. The detection rate by using the KAZE algorithm is reported as 61.24% with execution time is 1.50 s. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Discrete wavelet transforms

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Proceedings - 2021 3rd international Workshop on Artificial Intelligence and Education, WAIE 2021

Proceedings - 2021 3rd International Workshop on Artificial ...

引用

3rd international Workshop on Artificial Intelligence and Education, WAIE 2021

ISBN: (纸本)9781665400688

The proceedings contain 15 papers. The topics discussed include: discussion on the application pattern of research-and-discussion teaching in the teaching of computer courses for postgraduates;a case study on the practical knowledge of teaching: creative teacher of preschool;real-time feedback and evaluation algorithm for children's digital writing practice;enhanced knowledge graph for true-false question generation: a case study in computer networks course;to what extent virtual simulation technology can aid education?;developing digital and communication competencies in architecture courses while strengthening international perspectives;constructing the teaching model of flipped classroom for professional courses;modeling and application of precision surveying instrument and equipment;and research on mental health of secondary vocational school students addicted to Internet.

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Neural Network Software to Process Medical Data modeling 3

Neural Network Software to Process Medical Data Modeling

引用

3rd international conference on Control Systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Emelyanov, Egor Polyakov, Maxim Volgograd State University Depart. of Information Systems and Computer Modeling Volgograd Russia

ISBN: (纸本)9781665439817

Microwave radiometry enables measuring the temperature in biological tissues at a depth of several centimeters. Temperature is a crucial source of data on person's physical condition. The paper is devoted to developing an approach to ensure early breast cancer diagnosis by mapping temperature using machine learning techniques, using convolutional neural networks in particular. The novelty of our approach lies in studying the images drawn up based on temperature data obtained from local measurement points, with different color schemes used. Interpolation algorithms were used to improve the quality of the images obtained. The originality of the approach lies in the fact that, in addition to measuring real patients, computer modeling of mammary gland thermal fields is also used. We found that the use of extremely-Accurate neural networks to diagnose breast cancers is an effective and viable approach. Even if few learning samples (192 examples) are available, our proposed algorithm shows roughly 80% high accuracy adjusted to the neural network topology and the color scheme applied. We also demonstrate the dependence of diagnosis quality on the number of source images used while training and testing. We have concluded that the combined use of the left and right mammary gland thermograms greatly improves diagnosis efficiency when using graphical image machine learning. © 2021 IEEE.

关键词： Diagnosis

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FARIMA Model Based on Particle Swarm-genetic Hybrid algorithm Optimization and Application 3

FARIMA Model Based on Particle Swarm-genetic Hybrid Algorith...

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3rd international Academic Exchange conference on Science and Technology Innovation, IAECST 2021

作者： Yang, Jingxin Sheng, Hu Wan, Honglin Yu, Fang Dalian Jiaotong University School of Computer and Communication Engineering Dalian China

ISBN: (纸本)9781665402675

To solve the network quality problem, the FARIMA model is used to predict the network traffic according to the characteristics of the network traffic sequence. Since the orders of autoregressive order p, fractional difference order d and sliding average order q in the FARIMA model are the key parameters in the prediction process. Therefore, in order to make the prediction results more accurate, a hybrid particle swarm-genetic algorithm is introduced to find the optimal order of autoregressive order p and sliding average order q more accurately to achieve better prediction results. The simulation is carried out by Matlab, and the results show that the particle swarm-genetic hybrid algorithm is good for improving the prediction accuracy of network traffic. © 2021 IEEE.

关键词： Forecasting

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Performance Analysis of FISSER Model in Rural-Urban Cognitive Radio Networks 3

Performance Analysis of FISSER Model in Rural-Urban Cognitiv...

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2021 3rd international conference on computer modeling, simulation and algorithm, cmsa 2021

作者： Oki, Olukayode Olwal, Thomas Adigun, Matthew Department of Information Technology Walter Sisulu University South Africa Department of Electrical Engineering Tshwane University of Technology South Africa Department of Computer Science University of Zululand South Africa

In the past few decades, Cognitive Radio network (CRN) has been regarded in the literature as the most promising technology for performing dynamic spectrum management. One of the major aspects of spectrum management is referred to as the spectrum-reconfiguration decision-making ability of CR users. Dynamic spectrum reconfiguration has previously been reported to improve the spectrum utilisation in CRN. In exploiting spectrum reconfiguration to improve spectrum utilisation, various approaches have been adopted to develop models. However, none of these research works has been evaluated in the urban and rural settlement context. In a CRN environment, the frequency availability is not static like that of traditional networks. There are resource-rich regions such as in rural areas, where many frequencies are available for the Secondary Users (SUs) and resource-poor regions such as urban areas, where there are only a few frequencies available for SUs. Hence, this paper proposed a novel Foraging Inspired Spectrum Selection and Reconfiguration (FISSER) model. The performance of the FISSER model has been analysed through computer simulations both in the rural and urban CRN, using high and low perceptual radii. A high perceptual radius has been shown in the literature to improve energy efficiency and data communication performance in ad hoc networks. However, the simulation results reported in this paper show that even though the high perceptual radius improves the nodes' energy efficiency it does not achieve optimal data communication performance compared to when the nodes use a low perceptual radius. Also, the efficacy of FISSER model was tested by comparing it against the reinforcement learning model. Based on the obtained results, it was shown that the FISSER model achieved better results in both the network throughput and the channel switching time. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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Solving Double Counting Problems with Dynamic Programming algorithm 3

Solving Double Counting Problems with Dynamic Programming Al...

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2020 3rd international conference on modeling, simulation and Optimization Technologies and Applications, MSOTA 2020

作者： Jiang, Wenrong School of Computer and Information Shanghai Polytechnic University Shanghai China

In view of the repetitive calculation problems that often appear in algorithmic questions, this paper analyzes the common thought methods and dynamic programming for solving such problems. Through several types of classic questions, such as the backpack problem, the longest common subsequence, etc., the analysis methods and scope of application of dynamic programming are summarized. © Published under licence by IOP Publishing Ltd.

关键词： Dynamic programming

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Strong 3c- 3clH∞Stabilization for Networked Control System Based on Lyapunov Function and DoS Attacks 3

Strong 3c- 3clH∞Stabilization for Networked Control System ...

引用

3rd international conference on modeling, simulation, Optimization and algorithm, ICMSOA 2021

作者： Zheng, Ying Zhou, Ying College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Jiangsu Nanjing China

This paper is concerned with the strong 3c - 3cl H∞ stabilization for networked control system under DoS attacks with limited communication bandwidths. The quantizer is employed to the network transmission channel from sensor-to-controller in order to reduce the unnecessary data transmissions. In the network environment, it is assumed that there exist DoS attacks in the transmission channel from controller-to-actuator. By describing DoS attacks as the probability models subject to the Bernoulli distribution, the network control system is modeled as the system with random parameters. With this model, a dynamic output feedback controller is designed, which satisfies the given H∞ bound norm 3c . Under the action of the controller, the closed-loop system is exponential stable in the mean-square sense and satisfies H∞ bound norm 3cl . Especially, a Lyapunov function based on quantization error and attack probability is proposed in the stability analysis. Finally, the effectiveness of the proposed method is verified by a simulation example. © Published under licence by IOP Publishing Ltd.

关键词： Networked control systems

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Multi-agent deep reinforcement learning for traffic signal control with Nash Equilibrium 23

Multi-agent deep reinforcement learning for traffic signal c...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Wei, Wei Wu, Qiang Wu, Jianqing Du, Bo Shen, Jun Li, Tinghong School of Computer Science and Engineering Xi'an University of Technology Xi'an China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu China University of Wollongong Smart Infrastructure Facility Wollongong Australia China Mobile Communications Corporation Lanzhou China

ISBN: (纸本)9781665494571

Traffic signal control is an essential and chal-lenging real-world problem, which aims to alleviate traffic congestion by coordinating vehicles' movements at road in-tersections. Deep reinforcement learning (DRL) combines deep neural networks (DNNs) with a framework of reinforcement learning, which is a promising method for adaptive traffic signal control in complex urban traffic networks. Now, multi-agent deep reinforcement learning (MARL) has the potential to deal with traffic signal control at a large scale. However, current traffic signal control systems still rely heavily on simplified rule- based methods in practice. In this paper, we propose: (1) a MARL algorithm based on Nash Equilibrium and DRL, namely Nash Asynchronous Advantage Actor-Critic (Nash-A3C);(2) an urban simulation environment (SENV) to be essentially close to the real-world scenarios. We apply our method in SENV, obtaining better performance than benchmark traffic signal control methods by 22.1%, which proves that Nash-A3C to be more suitable for large industrial level deployment. © 2021 IEEE.

关键词： Performance evaluation Deep learning Computational modeling Roads Neural networks Reinforcement learning Nash equilibrium

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Image Watermark Combining with Discrete Wavelet Transform and Singular Value Decomposition 1

引用

3rd international conference on Big Data and Security, ICBDS 2021

作者： Yao, Juncai Shen, Jing School of Computer Engineering Nanjing Institute of Technology Nanjing211167 China

ISBN: (数字)9789811908521

ISBN: (纸本)9789811908514

In this paper, using the spectrum characteristics of discrete wavelet transform (DWT) and the features of image singular value decomposition (SVD), an image watermarking algorithm is proposed, which combined with the contrast sensitivity characteristics of human visual system (HVS). In the algorithm, the scrambled watermark is embedded into the singular value matrix of image with some intensity, and its inverse process is used to extract the watermark, by using HVS characteristics. The algorithm is verified by simulation, and tested by compression, shearing, Gaussian noise, and median filter attacks, and compared with 8 reported watermarking algorithms on the anti-attack performance. The results indicate that under the strong compression attack with a quality factor of 20%, the NC value of the extracted watermark can still reach 0.8467, and PSNR and SSIM of the watermarked image can reach 26.1793 dB and 0.8517, which has better robustness than the 8 existing watermarking algorithms. The comprehensive results indicate that the proposed algorithm can commendably balance the relationship among robustness, visual transparency and watermark embedding amount in the process of watermark embedding. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Discrete wavelet transforms

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Kinematics and simulation Analysis of Longitudinal-Torsional Ultrasonic Assisted Grinding of Zirconia Ceramics 3

Kinematics and Simulation Analysis of Longitudinal-Torsional...

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3rd international conference on modeling, simulation, Optimization and algorithm, ICMSOA 2021

作者： Wei, Mengbo Feng, Pingfa Zha, Huiting Xu, Chao Ma, Yuan Feng, Feng International Graduate School at Shenzhen Tsinghua University Shenzhen518055 China Department of Mechanical Engineering Tsinghua University Beijing100084 China

Zirconia ceramics is a typical hard and brittle material, which is very difficult to process. In recent years, with the rapid development of the 3C industry, zirconia ceramic materials have achieved a wide range of applications. Longitudinal-torsional ultrasonic assisted grinding (LTUAG) is efficient for processing hard and brittle materials. However, the mechanism of LTUAG of zirconia ceramic is not studied sufficiently. In this study, the spatial trajectory of the grinding grain in three different grinding methods is established and the critical cutting speed of LTUAG is calculated. simulation model of LTUAG of zirconia ceramic is established. The results show that the longitudinal-torsional ultrasonic vibration increases the spatial trajectory length of the grinding grain, thereby reducing the thickness of the maximum removal layer and reducing the cutting force. When the cutting speed is less than the critical cutting speed, LTUAG can significantly reduce the Mises stress, the subsurface damage and the cutting force. © Published under licence by IOP Publishing Ltd.

关键词： Grinding (machining)

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