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Evaluation of Adversarial Attacks and Detection on Transfer Learning Model

Evaluation of Adversarial Attacks and Detection on Transfer ...

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international conference on Computing Methodologies and Communication (ICCMC)

作者： Dhairya Vyas Viral V. Kapadia Computer Science and Engineering Department The Maharaja Sayajirao University of Baroda Vadodara India

In the field of transfer learning, the ability of models to make accurate predictions about future events can be compromised by targeted or untargeted adversarial attacks. Researchers have found that when images are subjected to such attacks, the feature construction process in every network produces noise, posing both challenges and opportunities for the study of convolutional neural networks (CNNs). To address this issue, the researchers developed a unique feature-map that describes the effects of adversarial attacks on individual object feature-maps. this approach was inspired by the observation of adversarial perturbations on image pixel attacks. By calculating the weight of each object's class activation map, a combined activation map is generated using a novel detection technique. the exploit feature-map developed in this study significantly advances the state-of-the-art in adversarial resistance. It was tested using several transfers learning models, including AlexNet, VGGNet19, and ResNet50, in both white-box and black-box assault scenarios. Moreover, the feature-map was shown to be effective in detecting assaults on ImageNet that use various techniques, such as the Fast Gradient Sign Method (FGSM), DeepFool, and Projected Gradient Descent (PGD).

关键词： Training Resistance Error analysis Computational modeling Perturbation methods Transfer learning Closed box

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Enhancing LoRa Communication: A Comprehensive Review of Improvement Techniques

Enhancing LoRa Communication: A Comprehensive Review of Impr...

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international conference on System Reliability and science (ICSRS)

作者： Andres Felipe Robayo Lara Edward Paul Guillén Wilson Mauro Rojas Reales Leonardo Juan Ramirez Lopez Engineering Department Universidad El Bosque Bogotá Colombia

this review examines the application of LoRa (long-range) technology in real-world test environments in the context of the Internet of things (IoT). It provides an overview of the types of test environments used in LoRa-based experiments that maximize the capabilities of the traditional LoRa application, highlighting key features. through a literature review, the articles are categorized into four main approaches: Energy Efficiency, Packet Loss Reduction, Range Efficiency, and Key Applications that Demonstrate the Importance of LoRa Implementation with Architectures Focused on System Enhancement. this taxonomy allows for the classification of elements into specific categories, enabling a structured analysis of the state of the art in LoRa testbed studies. For each scenario, a variety of performance enhancements are evaluated. the focus on efficiency and performance includes metrics such as energy efficiency, range extension and reliability. Results show applications that further unlock LoRa's potential, demonstrating energy savings and range extensions from 40% to 55%, as well as reliability results averaging over 90% packet loss reduction under extreme conditions. A comparison table is provided to analyze the different proposals studied.

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REEF: A Framework for Collecting Real-World Vulnerabilities and Fixes

REEF: A Framework for Collecting Real-World Vulnerabilities ...

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IEEE international conference on Automated Software engineering (ASE)

作者： Chaozheng Wang Zongjie Li Yun Pena Shuzheng Gao Sirong Chen Shuai Wang Cuiyun Gao Michael R. Lyu School of Computer Science and Technology Harbin Institute of Technology Shenzhen China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong China Computer Science and Engineering Department The Chinese University of Hong Kong Hong Kong China

Software plays a crucial role in our daily lives, and therefore the quality and security of software systems have become increasingly important. However, vulnerabilities in software still pose a significant threat, as they can have serious consequences. Recent advances in automated program repair have sought to automatically detect and fix bugs using data-driven techniques. Sophisticated deep learning methods have been applied to this area and have achieved promising results. However, existing benchmarks for training and evaluating these techniques remain limited, as they tend to focus on a single programming language and have relatively small datasets. Moreover, many benchmarks tend to be outdated and lack diversity, focusing on a specific codebase. Worse still, the quality of bug explanations in existing datasets is low, as they typically use imprecise and uninformative commit messages as explanations. To address these issues, we propose an automated collecting framework REEF to collect REal-world vulnErabilities and Fixes from open-source repositories. We focus on vulnerabilities since they are exploitable and have serious consequences. We develop a multi-language crawler to collect vulnerabilities and their fixes, and design metrics to filter for high-quality vulnerability-fix pairs. Furthermore, we propose a neural language model-based approach to generate high-quality vulnerability explanations, which is key to producing informative fix messages. through extensive experiments, we demonstrate that our approach can collect high-quality vulnerability-fix pairs and generate strong explanations. the dataset we collect contains 4,466 CVEs with 30,987 patches (including 236 CWE) across 7 programming languages with detailed related information, which is superior to existing benchmarks in scale, coverage, and quality. Evaluations by human experts further confirm that our framework produces high-quality vulnerability explanations.

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Fast Numerical Evaluation for Symbolic Expressions in Java

Fast Numerical Evaluation for Symbolic Expressions in Java

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Yueming Liu Peng Zhang Meikang Qiu Department of Mathematics University of Texas at Arlington Arlington TX United States Biomedical Engineering Department Stony Brook University Stony Brook NY United States Computer Science Department Pace University New York NY United States

ISBN: (纸本)9781479989386

the symbolic-numeric computation has been extensively developed in scientific computing for experimenting mathematics in numerical programs, like in optimization problems and finite element methods. Many software and libraries have been developed to support symbolic-numeric computation especially in the recent years. However, most of the implementations are cumbersome and inefficient for numerically evaluating symbolic expressions. the popular implementation chooses the way that generates C/C++/FORTRAN source codes for symbolic expressions and compiles the source files using the external compilers. the compiled machine codes are then linked back to the symbolic manipulation language environment. thi sprocess suffers from slow compilation and significant overhead of external function calls. To address this problem, this paper presents a handy approach that provides fast numerical evaluation for symbolic expressions in Java. In our approach, Java bytecode is generated in memory for symbolic expressions and further Just-In-Time (JIT) compiled to machine codes onJava Virtual Machine (JVM) at runtime. We have developedSymJava (https://***/yuemingl/SymJava) to implement our approach and tested a range of benchmark problems. the results show that SymJava is 1~3 orders of magnitude faster than the existing implementations including Matlab, Mathematica, Sage, theano and SymPy. Additionally, SymJava offers a human friendly programming style for symbolic expressions by overloading operators in Java. Our approach opens up a new avenue for the development of next generation symbolic-numeric software.

关键词： Java Libraries MATLAB Benchmark testing Mathematics Runtime

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Welcome to the Seventh international Workshop on Crowd-Based Requirements engineering (CrowdRE'23)

Welcome to the Seventh International Workshop on Crowd-Based...

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IEEE international Requirements engineering conference Workshops (REW)

作者： Oliver Karras Irit Hadar Muneera Bano James Tizard TIB – Leibniz Information Centre for Science and Technology Hannover Germany University of Haifa Carmel Mount Israel Data61 - CSIRO Melbourne Australia University of Auckland Auckland New Zealand

Welcome to the 7th international Workshop on Crowd-Based Requirements engineering (CrowdRE'23), where scientists and representatives of industry meet to exchange ideas, experiences, and other contributions regarding the state of the art of Crowd-Based Requirements engineering (CrowdRE). the discipline of CrowdRE seeks to address the challenges of traditional requirements engineering (RE) in scaling up to settings with thousands to millions of users of (software) products or (software-driven) services, who form a large and heterogeneous group that can be denoted as a ‘crowd’ [1], [2]. the user feedback generated by the crowd, such as texts or usage data, can be a valuable source of requirements, problems, wishes, and needs. Responding quickly, effectively, and iteratively to this feedback can greatly increase a product's success. CrowdRE comprises any approach that provides RE with suitable means for this crowd paradigm, especially by involving the crowd and by collecting, harmonizing, analyzing, and Interpreting their user feedback.

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An Automated Method for Constructing Ontology

An Automated Method for Constructing Ontology

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

作者： Yang Shu Yao HaiLun You XiangRun Wang Ye Department of Computer Science and Engineering Xin Jiang Agriculture University Modern Education Technology Center Xi Jiang Agriculture University

this paper proposed an automated method for ontology *** techniques used include machine learning and NLP(Natural Language Processing).these techniques are used to construct more accurate ontologies that represented as XML ***,Naive Bayes classification algorithms is used to text categorization which determined what kind of label a document is ***,SVM algorithm is used to calculate document similarity to cluster similar documents that we ***,Luhn's summarization algorithm is employed in order to shorten the text and kept important essential terms for making the domain ***,XML format is used to represent a domain ontology,which has the function of describing term's meaning and their lexical *** the method developed by Python programming language and Natural Language Toolkit.

关键词： Domain Ontology Construction Naive Bayes SVM Text Summarization Algorithm

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A Precision-Compensated Linear Power Flow Model Based on Mapping Voltage Magnitudes from Logarithmic Space to Squared Space

A Precision-Compensated Linear Power Flow Model Based on Map...

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IEEE international conference on Power and Energy Applications (ICPEA)

作者： Haipeng Lai Zhigang Li Jiahui Zhang Xiang Bai Huajian Li Hongyuan Liang J. H. Zheng School of Electric Power Engineering South China University of Technology Guangzhou China School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen China Shanxi Energy Internet Research Institute Taiyuan China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

Linear power flow is widely applied in various areas of power systems. the DC power flow model is a classical linear power flow model, but its main limitation is the inability to account for voltage magnitude. Other classical models that consider voltage magnitude are typically linearized in the original voltage magnitude space, leading to a computational accuracy bottleneck. To address this issue, this study first proposes an improved linear power flow model. the model remaps the voltage magnitude from logarithmic space to square space, preserving the nonlinear characteristics of the original current equation and compensating for the voltage phase angle. this approach overcomes the accuracy bottleneck of classical models. then, through matrix partitioning and transformation, the model achieves complete decoupling of the voltage magnitude and phase angle, avoiding nonconvex quadratic programming problems in optimization and enhancing computational efficiency. Finally, the accuracy and speed of the proposed model are validated through simulations across multiple test systems.

关键词： Visualization Accuracy Computational modeling Voltage Mathematical models Numerical models Power systems Quadratic programming Optimization Load flow

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Fuzzy Multi-Objective Optimization Considering the Uncertainty of Distributed Generation

Fuzzy Multi-Objective Optimization Considering the Uncertain...

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IEEE conference on Energy Internet and Energy System Integration (EI2)

作者： Yi An Luxin Zhan Jing Gao Qinya Qi Long Zhao State Grid Jiangxi Electric Power Co. Ltd. Electric Power Research Institute Nanchang China School of Electrical and Information Engineering Changsha University of Science and Technology Changsha China State Grid Hunan Extra High Voltage Substation Company Changsha China CYG SUNRI Co. LTD. Shenzhen China

Distributed generation makes distribution network become more complex and requirements of distribution system become higher. Due to the uncertainty of distributed new energy, applying traditional heuristic algorithms or intelligent algorithms to distribution network reconfiguration is less stable and may fall into the local optimum, which affects the rapidity and reliability of net-work programming. In this paper, the original nonlinear reconfiguration model is converted into a mixed-integer second-order cone model by second-order cone relaxation. By deriving the re-Iaxation conditions such as phase angle relaxation and second-order cone relaxation in the model power flow equation, the reconstruction model of multi-source distribution network based on second-order cone relaxation is constructed, and MATLAB/CPLEX is used to realize the fast operation. the model is simulated based on the triangular fuzzy theory with the objective function of minimizing the network loss and the main grid power purchase, the multi-objective Pareto front and objective function boundary values are obtained considering the uncertainty of distributed power supply and load. It is verified through simulation that economic reconfiguration through method of this paper can effectively can reduce the network loss, improve the distribution of the system currents, and enhance the system economy.

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Green Energy Aware Avatar Migration Strategy in Green Cloudlet Networks

Green Energy Aware Avatar Migration Strategy in Green Cloudl...

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IEEE international conference on Cloud Computing Technology and science (CloudCom)

作者： Xiang Sun Nirwan Ansari Qiang Fan Department of Electrical & Computer Engineering New Jersey Institute of Technology Newark NJ USA

We propose a Green Cloudlet Network (GCN) architecture to provide seamless Mobile Cloud Computing (MCC) services to User Equipments (UEs) with low latency in which each cloudlet is powered by both green and brown energy. Fully utilizing green energy can significantly reduce the operational cost of cloudlet providers. However, owing to the spatial dynamics of energy demand and green energy generation, the energy gap among different cloudlets in the network is unbalanced, i.e., some cloudlets' energy demands can be fully provided by green energy but others need to utilize on-grid energy (i.e., brown energy) to satisfy their energy demands. We propose a Green-energy awarE Avatar migRation (GEAR) strategy to minimize the on-grid energy consumption in GCN by redistributing the energy demands via Avatar migration among cloudlets according to cloudlets' green energy generation. Furthermore, GEAR ensures the Service Level Agreement (SLA) in terms of the maximum Avatar propagation delay by avoiding Avatars hosted in the remote cloudlets. We formulate the GEAR strategy as a mixed integer linear programming problem, which is NP-hard, and thus apply the Branch and Bound search to find its sub-optimal solution. Simulation results demonstrate that GEAR can save on-grid energy consumption significantly as compared to the Follow me AvataR (FAR) migration strategy, which aims to minimize the propagation delay between an UE and its Avatar.

关键词： Avatars Cloud computing Servers Green products Power demand Propagation delay Energy consumption

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Advancing Residential Energy Management: Integrating Renewable Resources and Vehicle-to-Grid Systems for Optimized Electrical Grid Performance

Advancing Residential Energy Management: Integrating Renewab...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Rakesh Chandrashekar D Shobha Rani Ginni Nijhawan A Balaram Prateek Chaturvedi B Sankara Babu Department of Mechanical Engineering New Horizon College of Engineering Bangalore Karnataka India Department of Electrical and Electronics Engineering Institute of Aeronautical Engineering Hyderabad Telangana India Lovely Professional University Phagwara Punjab India Department of Computer Science & Engineering MLR Institute of Technology Hyderabad Telangana India Amity School of Engineering and Technology Amity University Greater Noida Uttar Pradesh India Department of Computer Science and Engineering GRIET Bachupally Hyderabad India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

the term “smart grid” describes the future generation of electrical power networks, which are very complicated systems. It must take into account all aspects of the electrical system, increasing its intelligence and adaptability. In response to shifts in the electrical market, this idea is put out with the intention of controlling the rising demand while guaranteeing higher service quality and enhanced safety. this research presents an urban scenario that incorporates dispersed energy sources into a smart grid. the research incorporates renewable energy sources like solar panels and tiny windmills into the system, as well as battery storage and grid-connected vehicles that can power the electrical grid by drawing electricity from the storage device. So, to maximize the energy production and absorption systems as well as the recharging and discharging time for a home user’s electric car, a mixed integer linear programming is proposed. Additionally, a number of case studies are provided by changing important variables using the Taguchi technique of design of experiments in order to identify the best solution and demonstrate how each influences the system’s complexity.

关键词： Vehicle-to-grid Renewable energy sources Electricity Production Safety Mixed integer linear programming Solar panels Informatics Energy management Optimization

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