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共 5064 条记录，以下是71-80 订阅

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A 24-28 GHz Frequency Synthesizer for Millimeter Wave Radar Application

A 24-28 GHz Frequency Synthesizer for Millimeter Wave Radar ...

引用

2024 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2024

作者： Chen, Jheng.Long Peng. Kang-Chun Ins. Eng. Science and Technology National Kaohsiung Univ. Science and Technology Kaohsiung Taiwan Dept. Computer and Comm. Eng. National Kaohsiung Univ. Science and Technology Kaohsiung Taiwan

ISBN: (纸本)9798350389210

This paper presents the developed 24-28 GHz frequency synthesizer for millimeter-wave radar applications, incorporating a phase noise filter (PNF) at the input stage of the phase-frequency detector (PFD) to enhance in-band phase noise suppression. Measurement results show that the PNF effectively reduces phase noise from -88.6 dBc/Hz to -97 dBc/Hz at a 10 kHz frequency offset with a locking time of less than 68 us. © 2024 IEEE.

关键词： Frequency synthesizers

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Unmasking Harmful Comments: An Approach to Text Toxicity Classification Using Machine Learning in Native Language

Unmasking Harmful Comments: An Approach to Text Toxicity Cla...

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2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2024

作者： Ahsan, Afia Islam, Mohammad Manzurul Chowdhury, Abdullahi Ali, Md Sawkat Jabid, Taskeed Islam, Maheen Dept. of Computer Science and Eng. East West University Dhaka Bangladesh UniSA Online University of South Australia Adelaide Australia

ISBN: (纸本)9798331533137

In the modern digital era, social media plays a central role in our everyday lives, bringing both advantages and obstacles. While it facilitates global communication and trade, it also brings significant negative impacts, such as the spread of toxic comments that can lead to severe consequences, including mental distress and, in extreme cases, suicide. This study centers on classifying toxic comments by utilizing three different machine learning models: the Stochastic Gradient Descent (SGD) Classifier, the baseline Support Vector Machine (SVM), and an Optimized SVM model. A dataset comprising text comments in both Bangla and eng.ish, collected from various social media platforms, was used to train these models. The initial SVM model, while powerful, showed limitations, particularly in handling class imbalance, leading to suboptimal performance. The SGD Classifier provided a balanced approach but fell short in recall for non-harmful comments. To address these challeng.s, an Optimized SVM model was developed by fine-tuning key hyperparameters, significantly enhancing the model’s performance. The optimized model achieved superior accuracy, precision, recall, and F1-scores across both harmful and non-harmful comment classifications. Our results demonstrate that the Optimized SVM model is the most reliable and effective among the three, making it the preferred choice for deployment in real-world scenarios where accurate classification of toxic comments is critical. ©2024 IEEE.

关键词： Stochastic systems

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Generalized Approach for Fractional-Order Low-Pass Butterworth Filter Realization with an Inverse Follow the Leader Filter (IFLF) Topology

Generalized Approach for Fractional-Order Low-Pass Butterwor...

引用

IEEE Southeastcon

作者： Rowan Aldridge David Kubánek Jaroslav Koton Todd J. Freeborn Dept. Elec. Computer Eng. The University of Alabama Tuscaloosa USA Dept. Telecommunications Brno University of Technology Brno Czech Republic

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

This research presents a generalized approach to determine the coefficients to realize any $(N+\alpha)$ fractional-order low-pass Butterworth response using transfer function forms based on the Inverse Follow the Leader Filter (IFLF) topology. This approach automates the process to create and assemble the required transfer function (based on user specified values) and then apply a numerical optimization to estimate the necessary coefficients to achieve the target filter magnitude response. MATLAB simulations of $(2+\alpha)$ and $(10+\alpha)$ order filters using the generalized approach validate the process. Further, an experimental 2.5-order low-pass filter is experimentally realized (using an approximated fractional-order capacitor) to validate the characteristics of a low-pass filter designed using this process.

关键词： Capacitors Low-pass filters Transfer functions Filtering algorithms Approximation algorithms Topology Numerical models MATLAB Integrated circuit modeling Optimization

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HGDL: heterogeneous graph label distribution learning 24

HGDL: heterogeneous graph label distribution learning

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Yufei Jin Heng.Lian Yi He Xingquan Zhu Dept. of Elec. Eng. & Computer Sci. Florida Atlantic University Boca Raton FL Dept. of Data Science William & Mary Williamsburg VA

ISBN: (纸本)9798331314385

Label Distribution Learning (LDL) has been extensively studied in IID data applications such as computer vision, thanks to its more generic setting over single-label and multi-label classification. This paper advances LDL into graph domains and aims to tackle a novel and fundamental heterogeneous graph label distribution learning (HGDL) problem. We argue that the graph heterogeneity reflected on node types, node attributes, and neighborhood structures can impose significant challeng.s for generalizing LDL onto graphs. To address the challeng.s, we propose a new learning framework with two key components: 1) proactive graph topology homogenization, and 2) topology and content consistency-aware graph transformer. Specifically, the former learns optimal information aggregation between meta-paths, so that the node heterogeneity can be proactively addressed prior to the succeeding embedding learning; the latter leverages an attention mechanism to learn consistency between meta-path and node attributes, allowing network topology and nodal attributes to be equally emphasized during the label distribution learning. By using KL-divergence and additional constraints, HGDL delivers an end-to-end solution for learning and predicting label distribution for nodes. Both theoretical and empirical studies substantiate the effectiveness of our HGDL approach. Our code and datasets are available at https://***/Listener-Watcher/HGDL.

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Deep Learning for Cyberthreats: Performance Analysis and Application of Malware Classification in Edge Computing 2

Deep Learning for Cyberthreats: Performance Analysis and App...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, elec.rical and elec.ronics, ICIITCEE 2024

作者： Akhil, M.R. Sharma, Adithya Krishna V. Nadig, Abhijith Pavan, A. Shetty, Ashray Sumathi, A. Pes University Dept. of Computer Science Bengaluru India Red Hat Bengaluru India Jss Academy of Technology Dept. of Elec. and Comm. Bengaluru India BNM Institute of Technology Dept. of Ece Bengaluru India

ISBN: (纸本)9798350306415

In the context of the escalating malware threat landscape and the ongoing challeng. of identifying modern malware, this research investigates the utility of Deep Neural Networks (DNNs) for malware classification. Various DNN architectures are explored, revealing their ability to accurately classify malware across different types with consistently high accuracy rates. The study also examines the feasibility of deploying DNN models on edge devices for real-time classification in resource-constrained settings, emphasizing the importance of efficient performance optimization. This research contributes to advancing malware detection techniques and highlights the significance of early malware detection for preventing adverse consequences. It additionally addresses the distribution of security tasks to edge devices to maintain the integrity and availability of large-scale IoT systems, fostering a more resilient and secure digital ecosystem. © 2024 IEEE.

关键词： Cybersecurity Data Protection Deep Neural Networks IoT Security Malware Classification Performance Evaluation

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Fractional-Order Equivalent Circuit Representation of Sucrose Solutions elec.rical Impedance Measured in Bipolar Configuration

Fractional-Order Equivalent Circuit Representation of Sucros...

引用

IEEE Southeastcon

作者： Colin L. Duckworth Roman Sotner Jan Jerabek Todd J. Freeborn Dept. Elec. Computer Eng. The University of Alabama Tuscaloosa USA Dept. Telecommunications Brno University of Technology Brno Czech Republic

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

In this work, the alteration in elec.rical impedance of a liquid (unsweetened FuzeTea) with varying increases in sucrose concentrations (up to 785 mM) was investigated. The aim was to further understand how changes in liquid solutions with adulterants (in this case sucrose) change the elec.rical impedance as a potential method for food quality monitoring. The elec.rical impedance was measured from 100 Hz to 1 MHz using gold and platinum elec.rodes, then numerical optimization was applied to collected datasets to estimate the model parameters of a fractional-order equivalent circuit model to best represent the data. This model demonstrated less than 2% impedance magnitude and less than 6% impedance phase deviation compared to the experimental data. Overall, the model parameter representing the liquid resistance showed large increases for increasing concentrations of sucrose, suggesting that it may be a potential marker for assessing sucrose adulterants in liquid solutions.

关键词： Gold Liquids Impedance measurement Platinum Data models Numerical models Impedance Integrated circuit modeling Sugar Monitoring

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Graphon-based Synthetic Power System Model and its Application in System Risk Analysis 9

Graphon-based Synthetic Power System Model and its Applicati...

引用

9th IEEE International Smart Cities Conference, ISC2 2023

作者： Atat, Rachad Ismail, Muhammad Serpedin, Erchin Texas A&m University at Qatar Dept. Electrical and Computer Eng. Doha Qatar Tennessee Technological University Dept. of Computer Science CookevilleTN United States Texas A&m University Dept. of Electrical and Computer Eng. College StationTX United States

ISBN: (纸本)9798350397758

The high confidentiality level of power system's data has motivated the ongoing research on the generation of synthetic power grids that mimic actual systems. The existing synthetic models rely on specific geographical and parametric assumptions, which leads to non-generalizable models that overfit the observed data. To fill up this research gap, this paper proposes the use of graphon, a non-parametric graph processing method, to generate graph samples of different sizes with similar topological and elec.rical characteristics as actual power systems. We first estimate the graphon based on realistic parameters of the observed actual power system. Then as an example of a use case, we sample multiple graphs from the graphon in order to provide a general assessment of the power system vulnerabilities. © 2023 IEEE.

关键词： Risk analysis

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Maximizing Group-Based Vehicle Communications and Fairness: A Reinforcement Learning Approach

Maximizing Group-Based Vehicle Communications and Fairness: ...

引用

IEEE Conference on Wireless Communications and Networking

作者： Pronab Ghosh Thiago Eustaquio Alves de Oliveira Fadi Alzhouri Dariush Ebrahimi Dept. of Computer Science Lakehead University Thunder Bay Ontario Canada Dept. of Elec. & Computer Eng. Concordia University Montreal Quebec Canada Dept. of Computer Science Wilfrid Laurier University Waterloo Ontario Canada

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Vehicle-to-vehicle (V2V) communications retain immense potential in elevating network throughput for next-generation vehicular applications. This study investigates the problem of maximizing the total number of communications while ensuring fairness among V2V communication pairs (MVGCF). In the experiments conducted, each vehicle has a dedicated data stream to be shared among others in the same group. However, not all pairs can directly communicate due to communication range limitations. Hence, the current study focuses on relaying data packets in networks through multi-hop vehicles sharing resource blocks within a time frame while adhering to signal-to-interference-plus-noise ratio (SINR) and half-duplex constraints. To accomplish the research objectives mentioned above, two reinforcement learning (RL) algorithms, namely Q-Learning and Double Deep Q-Networks (DDQN), are proposed. However, to overcome the scalability and computational limitations of RL methods, we devise hybrid heuristic-based reinforcement learning methods, MVGCF_QLearning and MVGCF_DDQN. The numerical results demonstrate the hybrid approaches' effectiveness in terms of the number of successful communications and max-min fairness when compared to a random_agent, and the conventional RL methods for small and large networks.

关键词： Q-learning Scalability Power control Vehicular ad hoc networks Spread spectrum communication Interference Routing

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BNART: A Novel Centralized Traffic Management Approach for Autonomous Vehicles

BNART: A Novel Centralized Traffic Management Approach for A...

引用

International Workshop on Design of Reliable Communication Networks (DRCN)

作者： Dariush Ebrahimi Govind Sudarshan Fadi Alzhouri Dept. of Computer Science Wilfrid Laurier University Waterloo Ontario Canada Dept. of Computer Science Lakehead University Thunder Bay Ontario Canada Dept. of Elec. & Computer Eng. Concordia University Montreal Quebec Canada

ISBN: (数字)9798350348972

ISBN: (纸本)9798350348989

Traffic management poses a critical challeng. in modern metropolitan areas, where efficient management can significantly reduce travel time and vehicle emissions. With the vision of smart cities in mind, the increasing prominence of autonomous cars is anticipated to revolutionize road networks under the control of a central supercomputer known as the Central Traffic Control Unit, which maintains real-time location information for each vehicle within its jurisdiction and assumes responsibility for path planning. This paper investigates the problem of traffic management for self-driving vehicles, focusing on the utilization of essential information, such as source and destination locations, to guide vehicles along the most efficient routes, mitigating road congestion and ensuring prompt arrivals. To address this challeng., we formulate the problem as a mixed-integer linear programming model. Furthermore, due to its complexity, we propose a heuristic method called the Best Neighbor Algorithm for Routing Traffic (BNART). We extensively evaluate the performance of our proposed heuristic approach against optimal solutions on small-scale instances and other state-of-the-art methods such as the shortest path algorithm on large-scale instances. Through simulation, we demonstrate that our proposed method outperforms other methods in terms of average travel time, exhibiting a negligible gap to the optimal solution.

关键词： Smart cities Roads Heuristic algorithms Traffic control Routing Real-time systems Path planning

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Decomposition-Based Representation of Symmetric Multiple-Valued Functions 53

Decomposition-Based Representation of Symmetric Multiple-Val...

引用

53rd IEEE International Symposium on Multiple-Valued Logic, ISMVL 2023

作者： Nagayama, Shinobu Sasao, Tsutomu Butler, Jon T. Hiroshima City University Dept. of Computer and Network Eng. Hiroshima Japan Meiji University Dept. of Computer Science Kawasaki Japan Naval Postgraduate School Dept. of Electr. and Comp. Eng. MontereyCA United States

ISBN: (纸本)9781665464161

Symmetric multiple-valued functions are a basic class of multiple-valued functions such that function values are unchanged by any permutation of input variable labels. They appear in various situations such as arithmetic operations. A compact representation of symmetric multiple-valued functions benefits many applications. To represent symmetric multiple-valued functions compactly, this paper focuses on functional decomposition and decision diagrams. We propose a method that decomposes a symmetric multiple-valued function into three parts, and represents the three parts using suitable decision diagrams. This paper also derives theorems on sizes of the decision diagrams. Experimental results using randomly generated symmetric multiple-valued functions show the effectiveness of the proposed method. © 2023 IEEE.

关键词： Graphic methods

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