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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 1136 条记录，以下是941-950 订阅

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Building blocks for secure multiparty federated wireless sensor networks

Building blocks for secure multiparty federated wireless sen...

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international Wireless Communications and Mobile Computing conference, IWCMC

作者： Christophe Huygens Nelson Matthys Jef Maerien Wouter Joosen Danny Hughes Computer Science Department K.U. Leuven Heverlee Belgium Computer Science and Software Engineering Department Xi'an Jiaotong-Liverpool University Suzhou China

Wireless Sensor Networks are increasingly being deployed in enterprise scenarios involving multiple actors. the capabilities of sensors must be shared across many applications and sensors must cooperate across federations spanning administrative domains. this paper describes our efforts towards constructing federated wireless sensor systems. It leverages and details key building blocks designed to achieve federation and sharing: a component model with distributed event-based communication, a policy-driven control infrastructure for resources and communications, a deployment architecture and a mechanism to establish and propagate trust into the wireless sensor network. the building blocks focus on the specific and necessary in-network extensions, such as extensions to sensor run-time, middleware and programming abstractions, rather than the backend challenges. the combination of the building blocks creates a security middleware that supports multiparty federated sensor networks. An estimate of the total cost of federation in terms of footprint is provided and first experiences of application of the middleware are reported upon.

关键词： Wireless sensor networks Middleware Security Runtime Logic gates Engines Peer to peer computing

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A Deep Learning-Based Smart Helmet Detection and Notification with e-Challan Issuance for Traffic Fines

A Deep Learning-Based Smart Helmet Detection and Notificatio...

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India Council international Subsections conference (INDISCON), IEEE

作者： Rajdeep Ghosh Akash Kotal Raja Karmakar Krittika Das Department of Computer Science and Engineering Techno International New Town Kolkata India Department of Computer Science and Engineering Heritage Institute of Technology Kolkata India Department of Computer Science and Engineering Techno International New Town India

the Ministry of Road Transport and Highways estimates that 158,964 two-wheeler road accidents occurred in India in 2020, resulting in 56,873 fatalities, some of which were brought on by the lack of a helmet. this is still an issue on Indian roads and puts the lives of the country's young inhabitants in peril, despite numerous campaigns that have been undertaken by various state governments and the imposition of numerous punishments. the usage of computer vision is a suitable remedy for this issue. An automated system is suggested that employs a state-of-the-art single shot detector (SSD) for detection, image upscaling and Optical Character Recognition (OCR) to identify the vehicle's licence plate, as well as a database for e-challan records. Together with the payment link to clear the challan online, other Short Message Service (SMS) and mail Application programming Interface (API) is also utilised to notify about the challan's issuance. this paper explores a deep-learning-based idea that assures traffic safety and order on Indian roads and is a workable and useful solution to the highlighted issue.

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On a C++ Framework to Support Design by Contract

On a C++ Framework to Support Design by Contract

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2016 IEEE 7th international conference on Software engineering and Service science

作者： Lars Nolle Ivan Flechais Department of Engineering Science Jade University of Applied Sciences Department of Computer Science University of Oxford

Design by Contract(DbC) is a software engineering paradigm that aims to reduce the amount of source code in a computer program by avoiding redundant parameter *** is based on strict interface specifications,including the specification of responsibilities for *** DbC potentially leads to better quality programs,it has to be supported by the programming language/environment *** is not the case for mainstream object-oriented languages like C++or *** paper introduces a novel C++ framework that supports *** benefits gained and the computational costs generated by using the new framework were evaluated by applying it in a C++ case *** metrics were used to compare and to analyze both,the traditional and DbC implementation of the same software design.

关键词： C++ Design by Contract Framework

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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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Prediction of Bushfire Area Using Machine Learning Techniques

Prediction of Bushfire Area Using Machine Learning Technique...

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international conference on Computing Communication Control and Automation (ICCUBEA)

作者： Debabrata Swain Manish Kumar Nikhil Jain Chirag Devnani Computer Science and Engineering Department Pandit Deendayal Energy University Gujarat India Electronics and Communication Engineering Department Pandit Deendayal Energy University Gujarat India

Wildfires are a widespread natural disaster that affect animal and human lives around the world, and can also cause property damage. It is important for fire-prone areas to have effective measures for curbing the damage caused by fires. Predicting the spread of fires is a useful tool for this. this paper explores the use of state-of-the-art machine learning models, tools, and techniques for predicting the estimated fire area using environmental factors like weather and vegetation index as input parameters. Wildfire data of Australia from 2005 to 2020 is used in this study. the importance of different features is studied and the performance of various models is compared for different feature sets calculated using feature selection and extraction techniques. the accuracy and effectiveness of these techniques are analyzed through comparison of the results in terms of different error measures. Out of all the implemented methods, the Random Forest model has shown the most promising result with an MAE of 78.6 km 2 .

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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 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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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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Application domain and programming language readability yardsticks

Application domain and programming language readability yard...

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international conference on Computer science and Information Technology (CSIT)

作者： Mohammed Akour Bouchaib Falah Computer Information Systems Department Yarmouk University Irbid Jordan School of Science and Engineering Al Akhawayn University Ifrane Morocco

ISBN: (纸本)9781467389150

Software maintainability is one of the most factors that used to ensure software quality. It targets the structure of the software rather than its functionality. Hence, code readability is highlighted whenever maintainability is discussed. there is a huge difference between an organized code and a messy code, or between easy to read code and a difficult to read code. this difference can be very subjective but many efforts have been put together in order to formalize it. therefore, the result was a set of readability factors that have a direct or indirect impact on software readability. these factors measure to which extent readers can understand the text of the software code. Many metrics were developed to generalize the readability score across a set of pieces of code. Unfortunately, not all proposed metrics take into account the possibility of having variable readability factors. this paper tries to investigate to which extent the readability factors considering different application domains. Since readability is very subjective, it will be interesting to see whether it is useful to have specialized readability models that measure this attribute. this also implies looking into the impact of these readability models on measuring software quality.

关键词： Syntactics Measurement Java Software quality Readability metrics

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Flexible Joint Manipulator Control Based on Adaptive Dynamic programming

Flexible Joint Manipulator Control Based on Adaptive Dynamic...

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international conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Aiguo Gao Tianmin Zhou Tao Li Yujia Liu Ruizhuo Song Qinglai Wei North China Electric Power Research Institute Co. Ltd Bejing China Chinese Academy of Sciences Institute of Automation Bejing China University of Science and Technology Beijing School of Automation and Electrical Engineering Bejing China

ISBN: (数字)9781728162461

ISBN: (纸本)9781665419352

the authors present an adaptive dynamic programming-based (ADP-based) scheme to solve the tracking control problems of flexible joint manipulator, which can be transformed to solve the Hamilton-Jacobi-Bellman (HJB) equation. For the nominal error system, a critic neural network is established to approximate the value function and an online learning algorithm is proposed to update the weight of the critic neural network. the weight update of the critic neural network occurs at the same time as the system is running. the dynamics of the weight estimation error and the tracking error are proven to be uniformly ultimately bounded via Lyapunov method. Finally, a numerical example is given to illustrate the performance of the present method.

关键词： Estimation error Neural networks Optimal control Stability analysis Mathematical model Manipulator dynamics Lyapunov methods

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