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Joint Covert and Secure Communication for SWIPT-Assisted CNOMA Systems

IEEE Internet of Things Journal 2025年第12期12卷 20406-20419页

作者： Huang, Gaojian Lei, Yuxin Li, Xingwang Khan, Wali Ullah Wang, Gongpu Nallanathan, Arumugam Henan Polytechnic University School of Physics and Electronic Information Engineering School of Surveying and Land Information Engineering Photoelectric Detection and Sensing Integrated Engineering Technology Research Center of Henan Province Jiaozuo454003 China City University of Macau Faculty of Data Science China Henan Polytechnic University School of Physics and Electronic Information Engineering Jiaozuo454003 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China University of Luxembourg Interdisciplinary Center for Security Reliability and Trust Luxembourg City1855 Luxembourg Beijing Jiaotong University School of Computer Science and Technology Beijing100044 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Kyung Hee University Department of Electronic Engineering Yongin17104 Korea Republic of

With the rapid advancement of physical-layer security technology, the covert and secure communication has become crucial in safeguarding wireless communication systems. In this article, we propose a joint covert and secure transmission scheme for simultaneous wireless information and power transfer (SWIPT) assisted cooperative nonorthogonal multiple access (CNOMA) systems. In the CNOMA system, a greedy relay transmits the confidential information to the far user (Carol), with the assistance of the near user (Bob). Meanwhile, as a SWIPT node, Bob is self-sustained by harvesting energy from relay. What is more, a warden (Alice) and noncolluding eavesdroppers (Eves) always attempt to detect and capture the confidential information, respectively. To counteract the attacks from Alice and Eves, a jamming-assisted scheme is employed. For the proposed system model, we derive closed-form expressions for the detection error probability (DEP) and the average minimum detection error probability (AMDEP) of Alice. Additionally, closed-form expressions for the outage probability (OP) of users and the intercept probability (IP) of Eves are obtained. Furthermore, to maximize the effective covert rate (ECR) of Carol, an optimization problem is formulated, subject to covertness and security constraints. Numerical results are provided to demonstrate the impact of the system parameters on covert and secure performance, with the results showing perfect agreement with the theoretical analysis. © 2014 IEEE.

关键词： Inductive power transmission

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Connecting Cross-Modal Representations for Compact and Robust Multimodal Sentiment Analysis with Sentiment Word Substitution Error

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IEEE Transactions on Affective Computing 2024年

作者： Sun, Qiyuan Zuo, Haolin Liu, Rui Li, Haizhou The Department of Computer Science Inner Mongolia University Hohhot010021 China Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong CUHKShenzhen Shenzhen518172 China University of Bremen Faculty3 Computer Science / Mathematics Enrique-Schmidt-Str. 5 Cartesium Bremen28359 Germany

Multimodal Sentiment Analysis (MSA) seeks to fuse textual, acoustic, and visual information to predict a speaker’s sentiment states effectively. However, in real-world scenarios, the text modality received by MSA systems is often obtained through automatic speech recognition (ASR) models. Unfortunately, ASR may erroneously recognize sentiment words as phonetically similar neutral alternatives, leading to sentiment degradation in text and impacting MSA accuracy. Recent attempts aim to first identify the sentiment word substitution (SWS) error in ASR results and then refine the corrupted word embeddings using multimodal information for final multimodal fusion. However, such a method includes a burdensome and ambiguous detection operation and ignores the inherent correlations and heterogeneity among different modalities. To address these issues, we propose a more compact system, termed ARF-MSA consisting of three key components to achieving robust MSA with SWS errors: 1) Alignment: we establish connections between the "text-acoustic’ and "text-visual" representations to effectively map the "text-acoustic-visual" data into a unified sentiment space by leveraging their multimodal correlation knowledge;2) Refinement: we perform fine-grained comparisons between the text modality and the other two modalities in the unified sentiment space, enabling refinement of the sentiment expression within the text modality more concisely;3) Fusion: Finally, we hierarchically fuse the dominant and non-dominant representation from three heterogeneity modalities to obtain the multimodal feature for MSA. We conduct extensive experiments on the real-world datasets and the results demonstrate the effectiveness of our model. © 2010-2012 IEEE.

关键词： Alignment

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Sentiment Analysis: Indonesia Netflix User's Comment Using Multiple Lexicon-Based Dictionaries

Sentiment Analysis: Indonesia Netflix User's Comment Using M...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Sebastianus Adi Santoso Mola Tiwuk Widiastuti Rosa V. K. Isabela Ohe Roma Andrea Stevens Karnyoto Bens Pardamean Faculty of Science and Engineering University of Nusa Cendana Kupang Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

A subscription movie streaming service from the United States, Netflix, has been present in Indonesia since 2016 and provides a wide variety of films without showing any single advertisements that can be viewed from anywhere, as long as there is access to the internet. Despite these advantages, many users have complained through the Google Play Store's comments column. Some of the common complaints include frequent buffering and connectivity issues, dissatisfaction with the limited selection of Indonesian movies, lack of subtitles for specific languages, or pricing concerns have also been raised. In this study developed two combined scenario methods using the InSet and SentiStrength_id dictionary to obtain better performance and compare them against independent InSet and SentiStrength_id. This study collected users' comments for the Netflix app in the Google Play Store as a dataset using web scraping techniques through the Google Collaboration tool. The dataset contains 3250 rows spanning the period from January 22, 2024, through June 6, 2024. To ensure proper processing of the text, data cleaning, lowercasing, normalization, tokenization, stemming, and stopwords removal are conducted. The results show that most user opinions are negative. The InSet dictionary has an accuracy of 92%, SentiStrength_id 78%, Combined scenario 1 is 87%, and scenario 2 reaches the highest among others which is 92.52%.

关键词： Sentiment analysis Dictionaries Accuracy Films Collaboration Pricing Motion pictures Tokenization Cleaning Internet

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TCNAS: Transformer Architecture Evolving in Code Clone Detection

TCNAS: Transformer Architecture Evolving in Code Clone Detec...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hongyan Xu Xiaohuan Pei Xiu Su Shan You Chang Xu School of Computer Science and Engineering University of New South Wales Australia Data61 The Commonwealth Scientific and Industrial Research Organisation (CSIRO) School of Computer Science Faculty of Engineering The University of Sydney Australia Big Data Institute Central South University SenseTime Research

Code clone detection aims at finding code fragments with syntactic or semantic similarity. Most of current approaches mainly focus on detecting syntactic similarity while ignoring semantic long-term context alignment, and these detection methods encode the source code using human-designed models, a process which requires both expert input and a significant cost of time for experimentation and refinement. To address these challenges, we introduce the Transformer Code Neural Architecture Search (TCNAS), an approach designed to optimize transformer-based architectures for detection. In TCNAS, all channels are trained and evaluated equitably to enhance search efficiency. Besides, we introduce the dataflow of the code by extracting the semantic information from the code fragments. TCNAS facilitates the discovery of an optimal model structure geared towards the detection, eliminating the need for manual design. The searched optimal architecture is utilized to detect the code pairs. We conduct various empirical experiments on the benchmark, which covering all four types of code clone detection. The results demonstrate our approach consistently yields competitive detection scores across a range of evaluations.

关键词：

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A Temporal Graphlet Kernel for Classifying Dissemination in Evolving networks

arXiv

引用

arXiv 2022年

作者： Oettershagen, Lutz Kriege, Nils M. Jordan, Claude Mutzel, Petra Institute of Computer Science University of Bonn Bonn Germany Faculty of Computer Science University of Vienna Vienna Austria Research Network Data Science University of Vienna Vienna Austria

We introduce the temporal graphlet kernel for classifying dissemination processes in labeled temporal graphs. Such dissemination processes can be spreading (fake) news, infectious diseases, or computer viruses in dynamic networks. The networks are modeled as labeled temporal graphs, in which the edges exist at specific points in time, and node labels change over time. The classification problem asks to discriminate dissemination processes of different origins or parameters, e.g., infectious diseases with different infection probabilities. Our new kernel represents labeled temporal graphs in the feature space of temporal graphlets, i.e., small subgraphs distinguished by their structure, time-dependent node labels, and chronological order of edges. We introduce variants of our kernel based on classes of graphlets that are efficiently countable. For the case of temporal wedges, we propose a highly efficient approximative kernel with low error in expectation. We show that our kernels are faster to compute and provide better accuracy than state-of-the-art methods. Copyright © 2022, The Authors. All rights reserved.

关键词： computer viruses

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Enhanced Anomaly Detection in Embedded Payment Systems using Depthwise Separable CNN with Dandelion Optimizer

Enhanced Anomaly Detection in Embedded Payment Systems using...

引用

2025 International Conference on Intelligent Computing and Control Systems, ICICCS 2025

作者： Nagarajan, Sevinthi Kali Sankar Adwani, Rabail Ponnuchamy, Kardeepa Shah, Harshal Gurpur, Shashikala Maranan, Ramya 12460 Lanthimos San Antonio 78254 TX United States MS in Data Science Cranston RI United States Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology Gujarat India Symbiosis International (Deemed University) (SIU) Vimannagar Faculty of Law Symbiosis Law School (SLS) Maharashtra Pune India SIMATS Saveetha School of Engineering Department of Research and Innovation Chennai India

ISBN: (纸本)9798331512088

Due to the prevalence of online payments, it is essential to identify instances of payment fraud. Plans that break rules and regulations within the payment systems not only cost money but also erode customer confidence. Finding these fraudulent transactions can be challenging because of the complexity of fraud and the sheer number of transactions. In this study, a new deep learning technique for identifying online payment fraud is proposed. The classification phase, hybrid feature selection, and sophisticated preprocessing form its foundation. Starting with the IEEE CIS Fraud dataset and the PaySim Financial Credit dataset, the suggested approach is implemented. To ensure that all of the data sets have identical scales, a preprocessing step that uses Min-Max scaler normalization is utilized. The optimal qualities are picked using a hybrid approach that combines Gooseneck Barnacle Optimization (GBO) and the Artificial Hummingbird Algorithm (AHA). A depthwise separable convolutional neural network (DS-CNN) is then employed for classification, which facilitates the differentiation between fraudulent and non-fraudulent transactions. Additionally, to increase the detection rate, the Dandelion Optimizer (DO) optimizes the entire system. The aforementioned study indicates that the suggested approach has a high accuracy rate in detecting fraudulent transactions, which means it has almost infinite potential to speed up the entire process. In both datasets, the proposed method achieves an impressive 99% accuracy rate, proving its dependability and efficiency. This exceptional outcome shows how flexible the approach is to complex patterns and data variations, indicating its high level of reliability. © 2025 IEEE.

关键词： And Online Payments Fraud Detection Dandelion Optimizer Depth Wise Separable Convolutional Neural network Fraudulent Hybrid Feature Selection Min-Max Scaler Normalization Non- Fraudulent

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data-Driven Active Power Dispatch for Wind Farms 13

Data-Driven Active Power Dispatch for Wind Farms

引用

13th IEEE data Driven Control and Learning Systems Conference, DDCLS 2024

作者： Jiao, Xuguo Zhang, Daoyuan Wang, Xin Ma, Zhaoxing Zhang, Zhenyong Liu, Wenfeng School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China School of Civil Engineering Qingdao University of Technology Qingdao266520 China

ISBN: (纸本)9798350361674

Active power dispatch of wind farms plays an important role in power grid scheduling. In this paper, a data-driven active power dispatch strategy for wind farms is proposed, which uses the key point of minimizing the standard deviation of wind turbines' output power series to reduce their fluctuations. First, to build the optimization problem, the historical active power output data of each wind turbine is collected from the Supervisory Control And data Acquisition (SCADA) system. Then, the objective function is developed based on the idea of minimizing the standard deviation of the output power time series. Meanwhile, considering the constraints of wind turbines' output power and active power balance of the grid, the feasible domain of the cost function is constructed. Further, to solve the proposed nonlinear optimization problem with equality and inequality constraints, the trust region interior point method (TRIPM) is employed to explore optimal solution within the feasible domain. Finally, actual data collected from wind farms is used to test effectiveness of the designed approach and experimental results show that our method can achieve better output power smoothing performance than conventional Proportional Dispatch (PD) method. © 2024 IEEE.

关键词： Cost functions

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Relative magnetic field and slipping effect on Casson dusty fluid of two phase fluctuating flow over inclined parallel plate

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South African Journal of Chemical Engineering 2023年 44卷 135-146页

作者： khan, Dolat Kumam, Poom Kumam, Wiyada Suttiarporn, Panawan Rehman, Ali Fixed Point Research Laboratory Fixed Point Theory and Applications Research Group Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Applied Mathematics for Science and Engineering Research Unit (AMSERU) Program in Applied Statistics Department of Mathematics and Computer Science Faculty of Science and Technology Rajamangala University of Technology Thanyaburi (RMUTT) Pathum Thani 12110 Thailand Faculty of Science Energy and Environment King Mongkut's University of Technology North Bangkok Rayong Campus Rayong 21120 Thailand Special Interest Group for Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia

Due to its significant applications in magnetic devices for cell separation, magnetic drugs for cancer tumor treatment, blood flow adjustment during surgery, magnetic endoscopy, and fluid pumping in industrial and engineering processes, magnetohydrodynamics (MHD) has a wide range of applications. Therefore, the aim of this study to investigate the Relative Magnetic Field and slipping effect on Casson dusty fluid of two-phase fluctuating flow over inclined parallel plate. More exactly, the relative magnetic phenomena are fixed relatively to the plate (MFFRP) or fixed relatively to the fluid (MFFRF). The mathematical modeling was established as the set of partial differential equations for dusty Casson fluid. Buckingham's pi theorem is used to find out the dimensionless variables, to make our system dimensionless. The solution in perturb form is to find out by incorporating Poincare–Lighthill perturbation technique (PLPT). To know in-depth different parameters the graphical results for both velocities are plotted with the help of software Mathcad- 15. It is clearly detected that the relative magnetic field performs a vital part in the fluid as well as particle motion. Moreover, the relative magnetic field play a vital role in the decreasing of skin friction of both plates. © 2023

关键词： Brinkman fluid Dust particles Fluctuating vertical plate Inclined relative magnetic field PLPT

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arXiv

引用

arXiv 2024年

作者： Klimczak, Jakub Hamed, Ahmed Abdeen Faculty of Computer Science AGH Kawiory 31 Cracow30-055 Poland Clinical Data Science - Network Medicine and AI Sano Centre for Computational Medicine Nawojki 11 Cracow30-072 Poland

Background - The emergence of generative AI tools, empowered by Large Language Models (LLMs), has shown powerful capabilities in generating content. To date, the assessment of the usefulness of such content, generated by what is known as prompt engineering, has become an interesting research question. Objectives - Using the mean of prompt engineering, we assess the similarity and closeness of such contents to real literature produced by scientists. Methods - In this exploratory analysis, (1) we prompt-engineer ChatGPT and Google Bard to generate clinical content to be compared with literature counterparts, (2) we assess the similarities of the contents generated by comparing them with counterparts from biomedical literature. Our approach is to use text-mining approaches to compare documents and associated bigrams and to use network analysis to assess the terms' centrality. Results - The experiments demonstrated that ChatGPT outperformed Google Bard in cosine document similarity (38% to 34%), Jaccard document similarity (23% to 19%), TF-IDF bigram similarity (47% to 41%), and term network centrality (degree and closeness). We also found new links that emerged in ChatGPT bigram networks that did not exist in literature bigram networks. Conclusions - The obtained similarity results show that ChatGPT outperformed Google Bard in document similarity, bigrams, and degree and closeness centrality. We also observed that ChatGPT offers linkage to terms that are connected in the literature. Such connections could inspire asking interesting questions and generate new hypotheses. © 2024, CC BY.

关键词： data mining

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Joining Cast Mg AZ91 and Wrought Al 6082 Through Friction Stir Welding 1

引用

12th Symposium on Friction Stir Welding and Processing, held at the TMS Annual Meeting and Exhibition, TMS 2023

作者： Mroczka, Krzysztof Dymek, Stanislaw Pietras, Adam Węglowska, Aleksandra Hamilton, Carter Kopyściański, Mateusz Department of Materials Engineering Faculty of Materials Science and Physics Cracow University of Technology Krakow Poland Faculty of Metal Engineering and Industrial Computer Science AGH University of Science and Technology Krakow Poland The Lukasiewicz Research Network Institute of Welding Gliwice Poland Department of Mechanical and Manufacturing Engineering Miami University College of Engineering and Computing 56N Garland Hall OxfordOH45056 United States

ISBN: (数字)9783031226618

ISBN: (纸本)9783031226601

Dissimilar welds of cast magnesium AZ91 with wrought aluminium 6082-T6 were fabricated by friction stir welding (6 mm thick) with the alloys alternately placed on the advancing and retreating sides. The unique weld microstructures were characterized through light and electron microscopies (SEM, EDS), tensile tests were performed on samples containing the entire welds and the microhardness was measured across the weld cross-sections. Preliminary results demonstrate that some regions contain a significant amount of the brittle Al12Mg17 phase. To complement the microstructural and mechanical characterization, numerical simulations of the welding process provided deeper insight into the material flow during mixing and to the temperature distributions across the weld zones. Future work will include micro tensile specimens (cross-sectional area of 0.7 × 0.7 mm) to supplement the conventional tensile tests. These micro tensile specimens will be excised from distinct weld areas to highlight differences in local properties that influence weld behavior. © 2023, The Minerals, Metals & Materials Society.

关键词： Welds

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