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检索条件"任意字段=7th International Conference on the Art, Science, and Engineering of Programming, Programming 2023"

共 1140 条记录，以下是921-930 订阅

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international conference on Modelling, Identification and Control (ICMIC)

作者： Nan Pan Jingshu Yang Zeguang Yi Yi Liu Faculty of Mechanical & Electrical Engineering Kunming University of Science and Technology Kunming Yunnan Province China Kunming SNLab Tech Co. Ltd. Xishan District Kunming Yunnan Province China

It's usually not easy to compare linear toolmarks quickly and quantitatively with the current image processing and three-dimensional scanning methods. In order to deal with these kinds of problems, a similarity matching algorithm for laser detection signals of linear marks is proposed. In this method, locally weighted scatterplot smoothing algorithm is used to performs noise reduction on the surface signals of linear marks that are picked up by a laser displacement sensor; followed by the identification of the features of `thick and consistent' trends in the signal data. then the feature vectors are quantized by cosine vector curve fitting to individually calculate the spatial distance of the sample. Results from similarity comparison tests of actual cutting marks validate the accuracy and validity of proposed method.

关键词： Feature extraction Curve fitting Smoothing methods Mathematical model Fitting Surface emitting lasers Dynamic programming

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A Hybrid Localization Algorithm Based on Carrier Phase Ranging in UHF RFID System 7th

A Hybrid Localization Algorithm Based on Carrier Phase Rangi...

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7th international conference on artificial Intelligence and Security, ICAIS 2021

作者： Tian, Zengshan Liu, Xixi Liu, Kaikai Xie, Liangbo School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9783030786113

In this paper, we present a solution to locate the targets with tags in an ultrahigh-frequency (UHF) radio frequency identification (RFID) system, which achieves centimeter level localization accuracy. Many prior works use the Newton iteration method based on Least squares method (LS-Newton) to solve the coordinate of the target for accurate indoor localization, and the performance depends on an initial guess. However, it is difficult to get a good initial value close to the true value. In order to solve the problem, we propose a hybrid localization algorithm, which can effectively solve the initial guess problem and realize a good localization accuracy. First, we establish the objective localization equations and convert them into an LS problem. Second, we transform the LS problem into Semi-Definite programming (SDP) problem by adopting the semidefinite relaxation technique (SDR). third, we obtain a coarse coordinate estimate of the target by solving the SDP problem. In the end, we input this estimate into the LS-Newton method for iterative calculation and obtain high localization accuracy. Our experiments are conducted in a multi-static transceiving system with 1 transmitter and 3 receivers using the software-defined platform and commercial reader Impinj R420. the comprehensive test in indoor environments indicates that our proposed algorithm can solve the initial guess problem of the LS-Newton method, ensure the convergence of the algorithm, and finally achieve a probability accuracy of 95% when the localization error is less than 50 cm. © 2021, Springer Nature Switzerland AG.

关键词： Newton-Raphson method

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Extending GENET for non-binary CSP's

Extending GENET for non-binary CSP's

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international conference on Tools for artificial Intelligence (ICTAI)

作者： J.H.M. Lee H.F. Leung H.W. Won Department of Computer Science and Engineering Chinese University of Hong Kong New Territories Hong Kong China

GENET has been shown to be efficient and effective on certain hard or large constraint satisfaction problems. Although GENET has been enhanced to handle also the atmost and illegal constraints in addition to binary constraints, it is deficient in handling non binary constraints in general. We present E-GENET, an extended GENET. E-GENET features a convergence and learning procedure similar to that of GENET and a generic representation scheme for general constraints, which range from disjunctive constraints to non linear constraints to symbolic constraints. We have implemented an efficient prototype of E-GENET for single processor machines. Benchmarking results confirms the efficiency and flexibility of E-GENET. Our implementation also compares well against CHIP, PROCLANN, and GENET.

关键词： Computer science Convergence Prototypes artificial intelligence Computer vision Job shop scheduling Processor scheduling Logic programming Iterative algorithms Large-scale systems

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A knowledge-based approach to requirements analysis

A knowledge-based approach to requirements analysis

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international conference on Tools for artificial Intelligence (ICTAI)

作者： A. Liu J.J.P. Tsai Department of Electrical Engineering National Chung Cheng University Taiwan Department of Electrical Engineering and Computer Science University of Illinois Chicago Chicago IL USA

In software engineering, requirements analysis is a knowledge intensive task: and it requires an expert to understand what the clients need. We introduce a method which contains different AI techniques to perform this task, and a knowledge-based requirements analysis system, RAKES is presented to explain our approach. With RAKES, not only the ordinary functional requirements are collected, but also the non-traditional information. Nonfunctional requirements include the quality of operations or the background information for constructing the requirements which are gathered through a knowledge-based support. Different kinds of information collected are stored and organized in a knowledge base and can be used as the source of the user input in the latter phases of software development. Algorithms and procedures have been developed for constructing the interface language, organizing the knowledge base, and applying the knowledge base to different tasks. RAKES is integrated to the FRORL architecture to offer a systematic way toward requirements analysis, specification production, prototype generation, specification debugging, and code transformation.

关键词： Software engineering artificial intelligence Performance analysis programming Organizing Computer architecture Production systems Software prototyping Prototypes Debugging

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Switching Harmonic Attenuation of Grid-Tied Converters Using LLCL Filters and MPC-SVPWM

Switching Harmonic Attenuation of Grid-Tied Converters Using...

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China international Electrical and Energy conference (CIEEC)

作者： Muhamamd Waqas Qaisar Jingyang Fang Wenrui Li School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

this paper introduces an enhancement in grid-tied converter technology by incorporating a Model Predictive Control (MPC)-based space vector pulse width modulation (SVPWM) along with an advanced $LLCL$ filter. this approach aims to improve the conversion efficiency in grid-tied applications to three-phase ac, offering better harmonic attenuation than standard $LC$ and $LCL$ filters. the implementation of dual-mode control for dc voltage stabilization and the use of quadratic programming for inverter switching optimization is proposed to reduce switching losses, thereby augmenting system efficiency. Comparative simulations demonstrate a measurable efficiency improvement over traditional linear inverter methods, indicating a notable advancement in grid-tied converter technology, especially in terms of harmonic reduction and overall system performance enhancement.

关键词： Space vector pulse width modulation System performance Switching loss Switches Harmonic analysis Inverters Quadratic programming

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Linear and Non-Linear Filter-based Counter-Forensics Against Image Splicing Detection 7th

Linear and Non-Linear Filter-based Counter-Forensics Against...

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7th international conference on Computer Vision and Image Processing, CVIP 2022

作者： Das, Debjit Bhunia, Banalata Naskar, Ruchira Chakraborty, Rajat Subhra Department of Information Technology Indian Institute of Engineering Science and Technology West Bengal Shibpur Howrah711103 India Vellore Institute of Technology Tamil Nadu Vellore India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal Kharagpur721302 India

ISBN: (纸本)9783031314063

Digital images are widely used as primary sources of evidence in today’s world, spanning security, forensics, and legal domains. However, image tampering poses a shallow technical skill barrier with the wide availability of sophisticated, easy-to-use image manipulation software. Tampered images are often used intentionally for unlawful and malicious purposes. One of the most common forms of image manipulation attack is image splicing, which is performed by combining regions from multiple source images to synthesize an artificial image that looks natural. Digital forensic measures have been widely explored in the literature to detect such type of image forgery. However, the recent growth of counter-forensics poses a threat to such forensic/security measures. Forensic techniques can be easily deceived by adopting counter-forensic manipulation of forged images. In this work, we explore different linear and non-linear filtering-based counter-forensic modifications to digital images and hence investigate the after-effects of those, in terms of severity of such manipulations in rendering state-of-the-art forensic splicing detection methods useless. In this paper, we implement two forensic image splicing detection techniques based on feature extraction from image along with machine learning and deep CNN with transfer learning. then, different filtering techniques have been applied to the image dataset, investigating their effectiveness as a counter-forensic attack against image splicing detection. Experimental results show that the Gaussian filter and Average filter are the two most effective counter-forensic filtering methods against image splicing detection, suggesting the need for further strengthening the existing family of forensic techniques. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Median filters

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Distributed Optimisation under a Weight-unbalanced Digraph

Distributed Optimisation under a Weight-unbalanced Digraph

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international conference on Autonomous Robots and Agents, ICARA

作者： Prateek Priyaranjan Pradhan Arijit Sen Mangal Kothari Ketan Rajawat Department of Aerospace Engineering Indian Institute of Technology Kanpur India Department of Electrical Engineering and Computer Science Indian Institute of Science Education and Research Bhopal India Department of Electrical Engineering Indian Institute of Technology Kanpur India

Distributed optimisation (DO) problems in application to networked multi-agent system (MAS) have been an intriguing topic for research among different research communities. Despite the substantial number of works in this field over the past decade, the existing literature lacks a generalised algorithm for solving the DO problem for a strongly-connected weight unbalanced graph. this paper presents an information state dynamics for optimising the convex global objective function in a distributed manner under a strongly-connected weight-unbalanced digraph. Unlike few of the existing algorithms, the proposed dynamics does not require any global information, rather it solely depends on the locally available information and the information that the agent receives from the neighbours only. Numerical simulations with a comparative study with the state-of-the-art algorithm solving a DO problem under a weight-unbalanced digraph are also demonstrated in the paper to prove the claims.

关键词： Automation Heuristic algorithms Bandwidth Numerical simulation Linear programming Optimization Robots

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A robust Carrier Frequency and Timing Offset Estimation in Inter-UAV OFDM Communication Links

A robust Carrier Frequency and Timing Offset Estimation in I...

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international Multi-Topic ICT conference (IMTIC)

作者： Farzana Kulsoom Iraj Fatima Hassan Nazeer Chaudhry Aneeqa Gul Adeel Akram Telecommunication Engineering Dpt. University of Engineering and Technology Taxila Pakistan Computer Science Dpt. Barani Institute of Technology Rawalpindi Pakistan

the UAV-mounted base station has been integrated into 5G and beyond to provide communication in an emergency when conventional systems fail due to some reason. Moreover, it is also used in coverage enhancement and for other strategic purposes. In this work, we have considered a MIMO-OFDM based UAV system that is inclined to fast-fading channels due to the continuous motion of UAVs. Due to the mobility of UAVs, there is a frequency and timing offset which must be estimated for proper and seamless communication. For that purpose, we have proposed a data-aided maximum likelihood-based scheme that efficiently estimates the carrier frequency and timing offset. Results show that our algorithm outperforms the state-of-the-art system in terms of MSE.

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T3SFNet: A Tuned Topological Temporal-Spatial Fusion Network for Motor Imagery with Rehabilitation Exoskeleton 7th

T3SFNet: A Tuned Topological Temporal-Spatial Fusion Network...

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7th international conference on Cognitive Systems and Information Processing, ICCSIP 2022

作者： Shi, Kecheng Mu, Fengjun Zou, Chaobin Qin, Yizhe Peng, Zhinan Huang, Rui Cheng, Hong Center for Robotics School of Automation Engineering University of Electronic Science and Technology of China Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9789819906161

In recent years, motor imagery-based brain computer interfaces (MI-BCI) combined with exoskeleton robot has proved to be a promising method for spinal cord injury (SCI) rehabilitation training. the core of BCI is to achieve a high accurate movement prediction based on patient’s MI. the inconsistent response frequency of MI in different trials and subjects leads to the limited performance accuracy of MI movement prediction method for the single subject. the individual differences in the activation patterns of MI brain regions bring a greater challenge to the generalization ability of the method. According to the MI mechanism, this paper proposes a graph-based tuned topological temporal-spatial fusion network (T3SFNet) for MI electroencephalography (MI-EEG) limb movement prediction. the proposed method designs a learnable EEG tuning mechanism to fuse and enhance the subject’s MI response band data, and then uses a channel node-based graph convolutional network and a temporal-spatial fusion convolutional network to extract the topological features and spatiotemporal coupling features of the fused band data respectively. We evaluate the proposed approach on two MI datasets and show that our method outperforms state-of-the-art methods in both within-subject and cross-subject situations. Furthermore, our method shows surprising results on the small-sample migration test, reaching the prediction baseline with only of the data sample size. Ablation experiments of the model demonstrate the effectiveness and necessity of the proposed framework. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electroencephalography

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A Multi-Strategy Adversarial Attack Method for Deep Learning Based Malware Detectors

A Multi-Strategy Adversarial Attack Method for Deep Learning...

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Cryptography, Security and Privacy (CSP), IEEE international conference on

作者： Wang Yang Fan Yin School of Cyber Science and Engineering Southeast University Nanjing China

Deep learning allows building high-accuracy malware detectors without complicated feature engineering. However, research shows that the deep learning model is vulnerable and can be deceived if attackers add perturbation to input samples to craft adversarial examples deliberately. By altering the pixel values of the images, attackers have been able to generate adversarial examples that can fool state-of-the-art deep learning based image classifiers. However, Windows malware is a structured binary program file. therefore, arbitrarily altering its contents will often break the program's functionality. In order to solve this problem, a standard but inefficient method is to run the sample in the sandbox to verify whether its functionality is preserved. this paper proposes a multi-strategy adversarial attack method, which can generate malware adversarial examples with functionality-preserving. Our method manipulates the redundant or extended space in the Windows malware binary, so it will not break functionality. Experiments show that our method has a high attack success rate and efficiency.

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