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An Intelligent Secure Adversarial Examples Detection Scheme in Heterogeneous Complex Environments

Computers, Materials & Continua 2023年第9期76卷 3859-3876页

作者： Weizheng Wang Xiangqi Wang Xianmin Pan Xingxing Gong Jian Liang Pradip Kumar Sharma Osama Alfarraj Wael Said College of Information Science and Engineering HunanWomen’s UniversityChangsha410138China School of Mathematics and Statistics Hunan First Normal UniversityChangsha410138China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410114China Department of Computing Science University of AberdeenAberdeenAB243FXUK Department of Computer Science Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazig44511Egypt

Image-denoising techniques are widely used to defend against Adversarial Examples(AEs).However,denoising alone cannot completely eliminate adversarial *** remaining perturbations tend to amplify as they propagate through deeper layers of the network,leading to ***,image denoising compromises the classification accuracy of original *** address these challenges in AE defense through image denoising,this paper proposes a novel AE detection *** proposed technique combines multiple traditional image-denoising algorithms and Convolutional Neural Network(CNN)network *** used detector model integrates the classification results of different models as the input to the detector and calculates the final output of the detector based on a machine-learning voting *** analyzing the discrepancy between predictions made by the model on original examples and denoised examples,AEs are detected *** technique reduces computational overhead without modifying the model structure or parameters,effectively avoiding the error amplification caused by *** proposed approach demonstrates excellent detection performance against mainstream AE *** results show outstanding detection performance in well-known AE attacks,including Fast Gradient Sign Method(FGSM),Basic Iteration Method(BIM),DeepFool,and Carlini&Wagner(C&W),achieving a 94%success rate in FGSM detection,while only reducing the accuracy of clean examples by 4%.

关键词： Deep neural networks adversarial example image denoising adversarial example detection machine learning adversarial attack

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Artificial Intelligence-Based Optimised Energy Management System for Microgrids 58

Artificial Intelligence-Based Optimised Energy Management Sy...

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58th International Universities Power Engineering Conference, UPEC 2023

作者： Hussain, Muhammad Majid Nazir, Mian Hammad Akhtar, Muhammad Naveed Javed, Waqas Razaq, Abdul Pasha, Ahmad Hesham School of Engineering & Physical Sciences Heriot-Watt University Edinburgh United Kingdom University of South Wales Faculty of Computing Engineering & Science Cardiff United Kingdom Rachna College of Engineering & Technology Department of Electrical Engineering Gujranwala Pakistan James Watt School of Engineering University of Glasgow Glasgow United Kingdom School of Design and Informatics Abertay University Dundee United Kingdom

ISBN: (纸本)9798350316834

Electric power consistency is one of the essential variables in the social and economic growth of a smart city. In contrast, innovative energy sources and intelligent electricity networks are the primary components in making a city smart. This study describes an artificial neural network (ANN)- based controller for increasing power supply consistency by employing a dynamic voltage restorer. The optimisation approach particle swarm optimisation (PSO) is also discussed in this work, used to compute the maximum power point tracking (MPPT) of wind/photovoltaic hybrid power systems. The proposed PSO and ANN techniques can detect load, wind velocity, and solar irradiation fluctuations to optimise generating device power output, allowing hybrid power systems to function steadily, safely, and economically. This paper predicts and compares results with two cases using PSO and ANN to show the greater robustness and comparability of microgrid hybrid energies, namely photovoltaic and wind power. The simulation results show that the ANN-based controller with the PSO technique gives better performance as compared to the fuzzy controller. Further, the simulation results show that the converter can follow the hybrid system's maximum power point. © 2023 IEEE.

关键词： Neural networks

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Grasshopper Optimization Algorithm Based Spam Detection System Using Multi-Objective Wrapper Feature Selection and Neural Network Classification 2nd

Grasshopper Optimization Algorithm Based Spam Detection Syst...

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2nd International Conference on Emerging Technologies and Intelligent Systems, ICETIS 2022

作者： Ghaleb, Sanaa A. A. Mohamad, Mumtazimah Ghanem, Waheed A. H. M. Abdullahi, Akibu Mahmoud Nasser, Abdullah B. Saleh, Sami Abdulla Mohsen Arshad, Humaira Omolara, Abiodun Esther Abiodun, Oludare Isaac Ghetas, Mohamed Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Malaysia Faculty of Education Saber University of Lahej Lahej Yemen Faculty of Engineering University of Aden Aden Yemen Faculty of Education Aden University of Aden Aden Yemen Faculty of Computing and Informatics Albukhary International University Kedah Malaysia School of Technology and Innovation University of Vaasa Vaasa Finland School of Electrical and Electronic Engineering Universiti Sains Malaysia Nilai Malaysia Department of Computer Science Islamia University of Bahawalpur Bahawalpur Pakistan Department of Computer Science University of Abuja Abuja Nigeria Department of Computer Science Bingham University Nasarawa Nigeria Faculty of Computer Science Nahda University New Beni Seuf City Egypt

ISBN: (纸本)9783031252730

Email classification is essential to the trouble of email and pattern recognition. Nowadays, a number of unsolicited messages are circulated over the internet. While plenty of machine learning techniques are a success in detecting textual primarily based on totally unsolicited mail, this isn’t the case for messages spams, which can without difficulty avoid those textual-unsolicited mail detection systems. This paper proposes the introduction of MOBGOA constructed on the binary version of the GOA algorithm, for multi-objective selection of features purposes and the wrapper approach of selection of features and purpose of the EGOAMLP algorithm utilized this algorithm as the wrapper classifier. Spam assassin dataset was used to validate the performance of the MOB-EGOAMLP. The result uncovered that the new technique outflanks the wide selection of different methods in previously published works. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Feature Selection

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A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow

A Machine Learning-Based Privacy-Preserving Approach to Inco...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Burak Dindar Can Berk Saner Dogukan Yigit Polat Hüseyin Kemâl Çakmak Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Department of Electrical and Computer Engineering National University of Singapore Singapore School of Computing National University of Singapore Singapore

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

In order to achieve the goal of a carbon-neutral power system, significant changes to the power grid are underway, necessitating enhanced interoperability between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) for effective grid operation, particularly in light of the growing number of distributed generators (DGs). Data privacy concerns, however, complicate decision-making processes, particularly when integrating DGs into system-wide dispatch decisions. In this paper, we propose a machine-learning (ML)-based method to incorporate DGs located within the distribution system (DS) into dispatch decisions, adhering to data privacy by mitigating the exchange of sensitive data, such as system topology and demand profiles, between TSOs and DSOs. The methodology involves training three ML models to represent the behavior of the DS, thereby replacing the standard power flow model that contains sensitive information. Notably, we utilize a novel tailored neural network (NN) architecture to enhance computational efficiency in mapping the feasible region of the DS. Additionally, we employ open-source data to construct the Baden-Wü rttemberg (Germany) electricity grid, allowing to test our method not only on standard systems but also on a model that more accurately represents real-world power systems. The numerical case studies verify that the proposed method achieves results comparable to standard AC optimal power flow (AC-OPF) in both cost-optimality and computational time.

关键词： Data privacy Computational modeling Europe Machine learning Computer architecture Generators Data models Standards Interoperability Load flow

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Efficient online shopping platforms in Southeast Asia 2

Efficient online shopping platforms in Southeast Asia

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2nd International Conference on Smart computing and Electronic Enterprise, ICSCEE 2021

作者： Bamansoor, Samer Pande, Bishwajeet Al Moaiad, Yazeed Pathmanathan, P. Ravindran El-Ebiary, Yousef A. Baker Latiff, Nurul Adilah Abdul Aseh, Khairi Aledinat, Lowai Saleh Yusoff, Fakhrul Hazman MEDIU Faculty of Computer and Information Technology Malaysia Faculty of Informatics and Computing UniSZA Malaysia Gyancity Research Consultancy Pvt Ltd Motihari India MEDIU Faculty of Computer and Information Technology Malaysia International Institute of Applied Science Swiss School of Management Netherlands UniSZA Faculty of Informatics and Computing Malaysia Universiti Malaysia Terengganu Faculty of Ocean Engineering Technology and Informatics Malaysia UniSZA Faculty of Informatics and Computing Malaysia Universiti Teknologi MARA Malaysia

ISBN: (纸本)9781665432221

With the emergence of current developments and their devices that allow correspondence between organizations with each other, just as it is between organizations and service providers, just as with their customers, for some reasons, including advertising and a return to what is acceptable to them with the organization. Items, deals, etc., therefore, this examination provides an internal and external investigation of the current web-based business phase with a focus on promising conditions, risks, qualities, and shortcomings of FashionValet's electronic stage, whose administrations offer more than the Internet. Also, FashionValet is a stage organizer for online shopping and style in Southeast Asia other than Poplook, Zalora, and others, and the bulk of them are important competitors to FashionValet and they implement their own systems. The FashionValet experience, for example, is the history of the creator just as the other company's foundation has been pointed out to characterize how organizations, especially FashionValet, have moved from their primary stage to where they are today as the most aggressive design project. In addition, the technologies and innovations used by FashionValet are shown to provide a comprehensive detailed blueprint. To understand the improvement in style organizations in Malaysia, it was examined further. The paper outlines the critical elements to FashionValet's thriving as an end. © 2021 IEEE.

关键词： Online systems

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Characterizing the Users of Patient Portal Messaging: A Single Institutional Cohort Study 11

Characterizing the Users of Patient Portal Messaging: A Sing...

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11th IEEE International Conference on Healthcare informatics, ICHI 2023

作者： Huang, Ming Khurana, Aditya Mastorakos, George Zhou, Jiawei Zong, Nansu Yu, Yue Prigge, Julie E. Patten, Christi A. Liu, Hongfang Costello, Brian A. Mayo Clinic Department of Artificial Intelligence and Informatics RochesterMN United States Mayo Clinic Mayo Clinic Alix School of Medicine ScottsdaleAZ United States Georgia Institute of Technology School of Interactive Computing College of Computing AtlantaGA United States Mayo Clinic Center for Connected Care RochesterMN United States Mayo Clinic Center for Clinical and Translational Science Community Engagement Program RochesterMN United States

ISBN: (纸本)9798350302639

This work studied message communications on patient portals and examined both the longitudinal trends and the correlations with characteristics of message senders. We analyzed over 5.6 million secure messages sent on the Mayo Clinic patient portal between February 18, 2010, and December 31, 2017. We studied the longitudinal changes in the number of portal messages, patient senders' demographics and medical conditions (PheCodes), and provider senders' care settings (e.g., primary or specialty) and practice roles (e.g., physician, nurse practitioner, and registered nurses). When compared to non-message-senders, patient message senders had a significantly higher proportion of the demographics: age 41-60, female, married, white, and English-speaking. From 2010-2017, an individual patient sent an average of 9.8 messages per person while a provider sent 418.4. The average number of PheCodes for all patients regardless of portal usage increased from 7.5 +/-6.9 in 2010 to 10.7 +/- 10.1 in 2017. The Pearson correlation coefficient between average PheCodes per patient and average messages per patient was 0.273 (p © 2023 IEEE.

关键词： Nursing

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Telecom Churn Analysis using Machine Learning in Smart Cities 1

Telecom Churn Analysis using Machine Learning in Smart Citie...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Sharma, Ashish Shukla, Prafullit Gourisaria, Mahendra Kumar Sharma, Bhisham Dhaou, Imed Ben GLA University Department of Computer Engineering & Applications UP Mathura India KIIT Deemed to Be University School of Computer Engineering Odisha Bhubaneswar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Dar Al-Hekma University Hekma School of Engineering Computing and Informatics Department of Computer Science Jeddah Saudi Arabia

ISBN: (纸本)9781665472753

With the increase in the Telecom industry, service providers are more attentive toward the action of becoming larger or more extensive to the subscriber base. For surviving in telecom companies, the continued possession of holding customers must be a big challenge. According to consideration in the telecom environment, the market price of obtaining the new purchaser is more than holding the existing purchaser. Through collecting knowledge from the telecom industry to analyze the association of the customer whether will leave or not the company. Such types of the Decision tree and Logistic regression model have been compared on the 3334 instances of the dataset. The classification model derived from logistic regression has an accuracy of 80% and the decision tree classifier with an accuracy of 97%. © 2023 IEEE.

关键词： Decision trees

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IMUGPT 2.0: Language-Based Cross Modality Transfer for Sensor-Based Human Activity Recognition

arXiv

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arXiv 2024年

作者： Leng, Zikang Bhattacharjee, Amitrajit Rajasekhar, Hrudhai Zhang, Lizhe Bruda, Elizabeth Kwon, Hyeokhyen Plötz, Thomas College of Computing Georgia Institute of Technology AtlantaGA United States School of Interactive Computing Georgia Institute of Technology AtlantaGA United States College of Engineering Georgia Institute of Technology AtlantaGA United States Department of Biomedical Informatics Emory University AtlantaGA United States

One of the primary challenges in the field of human activity recognition (HAR) is the lack of large labeled datasets. This hinders the development of robust and generalizable models. Recently, cross modality transfer approaches have been explored that can alleviate the problem of data scarcity. These approaches convert existing datasets from a source modality, such as video, to a target modality (IMU). With the emergence of generative AI models such as large language models (LLMs) and text-driven motion synthesis models, language has become a promising source data modality as well as shown in proof of concepts such as IMUGPT. In this work, we conduct a large-scale evaluation of language-based cross modality transfer to determine their effectiveness for HAR. Based on this study, we introduce two new extensions for IMUGPT that enhance its use for practical HAR application scenarios: a motion filter capable of filtering out irrelevant motion sequences to ensure the relevance of the generated virtual IMU data, and a set of metrics that measure the diversity of the generated data facilitating the determination of when to stop generating virtual IMU data for both effective and efficient processing. We demonstrate that our diversity metrics can reduce the effort needed for the generation of virtual IMU data by at least 50%, which open up IMUGPT for practical use cases beyond a mere proof of concept. Copyright © 2024, The Authors. All rights reserved.

关键词： Large datasets

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Insect Identification in Pulsed Lidar Images Using Changepoint Detection Algorithms

Insect Identification in Pulsed Lidar Images Using Changepoi...

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2023 Annual Intermountain Engineering, technology and computing, IETC 2023

作者： Sweeney, Nathaniel Xu, Caroline Shaw, Joseph A. Hocking, Toby D. Whitaker, Bradley M. Montana State University Electrical and Computer Engineering Department United States University of Michigan Electrical Engineering and Computer Science Department United States Montana State University Optical Technology Center United States School of Informatics Computing and Cyber Systems Northern Arizona University United States

ISBN: (纸本)9798350335903

Noninvasive entomological insect monitoring often utilizes a variety of tools such as LiDAR to gather information without interfering with the insects in their habitat. These collection methods often result in large amounts of data that can be te-dious and lengthy to interpret and analyze. Machine learning has been previously used in the past in order to analyze Li-DAR images to detect insects, but often suffers from pitfalls such as long training times and large computational power requirements. In an attempt to offer an alternative that takes little to no training on the data and much less computational power, this paper looks at the use of changepoint detection algorithms to analyze LiDAR images containing insects. By analyzing the rows or columns of a LiDAR image, the algorithms should be able to detect abrupt changes in the image that would represent the insects. While not as accurate, the changepoint detection algorithms give comparable results to a machine learning algorithm tested on the same dataset without the need for supervised training. © 2023 IEEE.

关键词： Anomaly detection

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Enhancing UX Design Through Eye-Tracking and Image Processing: Practical Insights and Applications 10

Enhancing UX Design Through Eye-Tracking and Image Processin...

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10th International Conference on Platform technology and Service, PlatCon 2024

作者： Baharum, Aslina Ismail, Rozita Halamy, Suhaida Rahim, Emelia Abdul Noor, Noorsidi Aizuddin Mat Deris, Farhana Diana School of Engineering and Technology Sunway University Bandar Sunway Selangor Malaysia College of Computing and Informatics Universiti Tenaga Nasional Putrajaya Campus Selangor Kajang Malaysia School of Information Science College of Computing Informatics and Mathematics Universiti Teknologi MARA Cawangan Sarawak Sarawak Kota Samarahan Malaysia Faculty of Business Management Universiti Teknologi MARA Cawangan Sarawak Sarawak Kota Samarahan Malaysia Mass Appraisal Housing and Planning Research Group Centre for Real Estate Studies Real Estate Department Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Faculty of Social Sciences and Humanities Universiti Teknologi Malaysia Johor Johor Bahru Malaysia

ISBN: (纸本)9798350367874

In the digital age, optimizing user experience (UX) is paramount for the success of various applications and interfaces. Eye-tracking, a method used to monitor and analyze eye movements, has emerged as a powerful tool in UX research. This study investigates the intersection of eye-tracking and image processing, focusing on how insights derived from eye-tracking data can enhance UX design. Through a series of case studies, this research explores the practical applications of eye-tracking in improving user interaction with image-based interfaces. By analyzing user attention patterns, gaze fixation durations, and visual engagement metrics, the study uncovers valuable insights into user behaviour and preferences. These insights inform design decisions related to interface layout, content placement, and visual hierarchy, ultimately leading to more intuitive and engaging user experiences. The findings from this study provide practical guidelines and best practices for integrating eye tracking into the UX design process, offering valuable insights for designers, developers, and researchers seeking to optimize user interaction with image-based applications and interfaces. © 2024 IEEE.

关键词： Eye movements

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