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57th Annual Conference on Information Sciences and systems, CISS 2023

作者： Zhang, Xi Wang, Jingqing Poor, H. Vincent Texas AandM University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States

ISBN: (纸本)9781665451819

Significant effort has been devoted to the problem of guaranteeing stringent ultra-reliable and low-latency communications (URLLC) while introducing new requirements for better quality-of-services (QoS) over next generation wireless networks. One of the major design issues raised by URLLC is how to support explosively growing demands for delay-sensitive multimedia applications while guaranteeing ultra-reliability. Towards this end, there have been a wide spectrum of promising techniques, including statistical delay and error rate-bounded QoS provisioning, cell-free (CF) massive multiple-input-multiple-output (m-MIMO), finite blocklength coding (FBC), hybrid automatic repeat request with incremental redundancy (HARQ-IR) protocol, etc. However, when being integrated with FBC, how to rigorously and efficiently characterize the dynamics of mobile wireless networks in terms of statistical delay and error-rate bounded QoS provisioning for CF m-MIMO has imposed many new challenges not encountered before. To overcome these challenges, in this paper we develop statistical delay and error-rate bounded QoS analytical modeling schemes to characterize the FBC-based ϵ-effective capacity over 6G CF m-MIMO wireless networks using HARQ-IR. In particular, first we establish CF m-MIMO based system architecture models. Second, we apply a HARQ-IR protocol for deriving the channel coding rate, outage probability, and FBC based ϵ-effective capacity function using the Mellin transform. Finally, we conduct a set of simulations to validate and evaluate our proposed schemes. © 2023 IEEE.

关键词： Wireless networks

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Differentially Private Online Federated Learning with Correlated Noise 63

Differentially Private Online Federated Learning with Correl...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Zhang, Jiaojiao Zhu, Linglingzhi Johansson, Mikael Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science StockholmSE-100 44 Sweden Chinese University of Hong Kong Department of Systems Engineering and Engineering Management Hong Kong

ISBN: (纸本)9798350316339

We introduce a novel differentially private algorithm for online federated learning that employs temporally correlated noise to enhance utility while ensuring privacy of continuously released models. To address challenges posed by DP noise and local updates with streaming non-iid data, we develop a perturbed iterate analysis to control the impact of the DP noise on the utility. Moreover, we demonstrate how the drift errors from local updates can be effectively managed under a quasi-strong convexity condition. Subject to an (, δ) DP budget, we establish a dynamic regret bound over the entire time horizon, quantifying the impact of key parameters and the intensity of changes in dynamic environments. Numerical experiments confirm the efficacy of the proposed algorithm. © 2024 IEEE.

关键词： Federated learning

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Massive-MIMO Based RSMA Under Nakagami-m Channel Over 6G mURLLC Wireless Networks 57

Massive-MIMO Based RSMA Under Nakagami-m Channel Over 6G mUR...

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57th Annual Conference on Information Sciences and systems, CISS 2023

作者： Zhang, Xi Zhu, Qixuan Poor, H. Vincent Texas AandM University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States

ISBN: (纸本)9781665451819

The sixth generation (6G) mobile wireless networks are expected to provide massive ultra-reliable and low-latency communications (mURLLC) for data services, which require extremely stringent quality-of-services (QoS) with massive connectivity. Rate splitting (RS) multiple access schemes have been proposed recently for tackling the difficulty of the massive access yielded by a large number of mobile users (MUs) requesting to connect to a single base station. Massive multiple-input and multiple-output (massive-MIMO) communication is considered a promising solution to serve massive MUs in 6G wireless networks. However, how to apply RS schemes into massive-MIMO techniques to support the massive access has not been sufficiently studied. In this paper, we propose to integrate RS schemes with massive-MIMO techniques to achieve mURLLC transmissions under a Nakagamir $m$ fading wireless channel. First, we establish the system model for the integrated RS and massive-MIMO schemes. Then, we derive closed-form expressions for the signal-to-interference-plus-noise ratios (SINRs) under a Nakagami- $-m$ fading channel and obtain the channel capacity. Finally, we use numerical analyses to validate and evaluate our proposed RS and massive-MIMO integrated schemes. © 2023 IEEE.

关键词： Wireless networks

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INC: In channel Crossing ECC for LPDDR Compression Attached Memory Module 21

INC: In channel Crossing ECC for LPDDR Compression Attached ...

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21st International System-on-Chip Design Conference, ISOCC 2024

作者： Yoo, Yoonyul Kim, Jungrae Sungkyunkwan University Suwon Korea Memory Division Samsung Electronics Department of Electrical and Computer Engineering Hwaseong Korea Republic of Sungkyunkwan University Department of Semiconductor Systems Engineering Suwon Korea Republic of

ISBN: (纸本)9798350377088

The industry has developed a form factor known as the Compression Attached Memory Module (CAMM) to address the limitations of SO-DIMMs in terms of size, speed, and scalability. This paper proposes a method to minimize performance degradation caused by the absence of an efficient ECC solution in CAMM systems composed of LPDDR. The IN-channel Crossing (INC) method we propose enhances the efficiency of LPCAMM by reducing performance degradation through the segregation of data and ECC modules within the same channel. © 2024 IEEE.

关键词： Static random access storage

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Optimizing Facial Recognition: An Analytical Comparison of Traditional and Deep Learning Approaches 7

Optimizing Facial Recognition: An Analytical Comparison of T...

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7th International Conference on Data Science and Its Applications, ICoDSA 2024

作者： Sakib, Shadman Siddiky, Md Nurul Absar Arifuzzaman, Md. Chowdhury, Md. Jalal Uddin University of Maryland Baltimore County Department of Information Systems Maryland21250 United States University of North Carolina at Charlotte Department of Electrical and Computer Engineering Charlotte United States Leading University Sylhet Department of Computer Science and Engineering Sylhet Bangladesh

ISBN: (纸本)9798350365351

In the rapidly evolving domains of AI and Internet tech, face recognition, a key machine learning application, is increasingly used in security, identity verification, and public monitoring. As this technology progresses, its applications are expanding. A critical factor in its growing popularity is the advancement of the underlying algorithms, which drives its effectiveness in various applications. This paper investigates facial recognition technologies using the Olivetti faces dataset. It compares the efficacy of Principal Component Analysis (PCA), Eigenface method, Support Vector Machine (SVM) with linear kernel, a standard Convolutional Neural Network (CNN), and a CNN-Transfer Learning approach with MobileNet. The transfer learning is trained with the Adam optimizer (learning rate 0.0004) and categorical cross entropy loss. Over 100 epochs with a batch size of 64, the model's performance, in terms of accuracy and loss, is meticulously tracked and visualized, providing insights into its learning progression. The final evaluation includes a detailed classification report, highlighting precision, recall, and F1-scores, and these metrics are graphically represented for a comprehensive understanding of the model's performance. The CNN model achieved 80% accuracy, while PCA and SVM exhibited high accuracies, reaching 91% and 97.5%, respectively. We have also applied the eigenface method and achieved 91% accuracy in face recognition. Notably, the CNN-Transfer Learning method demonstrates superior performance with a 95% accuracy, highlighting the potential of deep learning in facial recognition applications. © 2024 IEEE.

关键词： Contrastive Learning

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A Reverse Path Planning Approach for Enhanced Performance of Multi-Degree-of-Freedom Industrial Manipulators

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computer Modeling in engineering & Sciences 2024年第5期139卷 1357-1379页

作者： Zhiwei Lin Hui Wang Tianding Chen Yingtao Jiang Jianmei Jiang Yingpin Chen Key Laboratory of Light Field Manipulation and System Integration Applications in Fujian Province School of Physics and Information EngineeringMinnan Normal UniversityZhangzhou363000China Department of Electrical and Computer Engineering University of NevadaLas Vegas89154USA College of Material Engineering Fujian Agriculture and Forestry UniversityFuzhou350000China

In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and *** Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion *** satisfactory results in practical scenarios remains *** response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial *** approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free *** enhance convergence speed,the Q-learning algorithm in RL is augmented with ***,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection ***,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power *** efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target *** results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target ***,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.

关键词： Reverse path planning Dyna-Q bidirectional search posture angle joint motion

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Experimental Analysis of Methods Used to Solve Linear Regression Models

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computers, Materials & Continua 2022年第9期72卷 5699-5712页

作者： Mua’ad Abu-Faraj Abeer Al-Hyari Ziad Alqadi Computer Information Systems Department The University of JordanAqaba77110Jordan Electrical Engineering Department Al-Balqa Applied UniversityAs Salt19117Jordan Computers and Networks Engineering Department Amman15008Jordan

Predicting the value of one or more variables using the values of other variables is a very important process in the various engineering experiments that include large data that are difficult to obtain using different measurement *** is one of the most important types of supervised machine learning,in which labeled data is used to build a prediction model,regression can be classified into three different categories:linear,polynomial,and *** this research paper,different methods will be implemented to solve the linear regression problem,where there is a linear relationship between the target and the predicted *** methods for linear regression will be analyzed using the calculated Mean Square Error(MSE)between the target values and the predicted outputs.A huge set of regression samples will be used to construct the training dataset with selected sizes.A detailed comparison will be performed between three methods,including least-square fit;Feed-Forward Artificial Neural Network(FFANN),and Cascade Feed-Forward Artificial Neural Network(CFFANN),and recommendations will be *** proposed method has been tested in this research on random data samples,and the results were compared with the results of the most common method,which is the linear multiple regression *** should be noted here that the procedures for building and testing the neural network will remain constant even if another sample of data is used.

关键词： Linear regression ANN CFFANN FFANN MSE training cycle training set

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Spacecraft potential effects on low-energy ion measurements to be made by probe B1 of Comet Interceptor

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RAS Techniques and Instruments 2024年第1期3卷 333-346页

作者： Bergman, S. Kasahara, S. Stenberg Wieser, G. Division of Space and Plasma Physics School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Department of Earth and Planetary Science Graduate School of Science The University of Tokyo Swedish Institute of Space Physics

Spacecraft charging causes notorious issues for low-energy plasma measurements. The charged particles are accelerated towards or repelled from the spacecraft surface, affecting both their energy and travel direction. The latter results in a distortion of the effective field of view (FOV) of the instrument making the measurements. The Comet Interceptor mission, planned to be launched in 2029, will make a flyby of a long-period or interstellar comet that ideally is dynamically new. The mission comprises one main spacecraft A, developed by the European Space Agency (ESA), and two sub-probes B1 and B2, developed by the Japan Aerospace Exploration Agency and ESA, respectively. The low-energy plasma measurements made by Comet Interceptor will likely be affected by the spacecraft potential in the case of low relative flyby velocities. On probe B1, the Cometary Ion Mass Spectrometer (CIMS) of the Plasma Suite is an ion mass spectrometer, capable of measuring ions with energies down to 10 eV/q. In this work, we use the Spacecraft Plasma Interaction Software to study the influence of the spacecraft potential on the low-energy ion measurements to be made by CIMS in the inner cometary magnetosphere. The results show that the effective FOV of CIMS is distorted at low energies when the flyby velocity is low. The distortion level is highly geometry dependent, and the largest distortions are caused by the magnetometer boom. Furthermore, the results show that cold ions with bulk velocities in the range 1-10 km s-1, flowing both radially away from and inward towards the nucleus, are detectable by the instrument considering the nominal observation geometry. © 2024 The Author(s).

关键词： Comets Data Methods Instrumentation Numerical Methods Plasma SPIS

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Quantum Resource Estimation of Arithmetic Primitives 4

Quantum Resource Estimation of Arithmetic Primitives

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Hansen, Ethan Joshi, Sanskriti Rarick, Hannah University of Washington Department of Physics Seattle United States University of Washington Department of Electrical and Computer Engineering Seattle United States

ISBN: (纸本)9798350343236

A major component of RSA cryptanalsysis, factoring a number that is a product of two large primes is computationally intensive. Using Shor's algorithm, there is a possibility of the factorization taking a fraction of the time on a quantum computer. To implement this level of algorithm, an analysis of the resources required would help with understanding the requirements for the hardware based on the software implementation and vice versa. © 2023 IEEE.

关键词： Software design

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A 2×2 MIMO Antenna for 28 GHz 5G Communication Applications with High Isolation

A 2×2 MIMO Antenna for 28 GHz 5G Communication Applications...

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2024 International Conference on Innovations in Science, engineering and Technology, ICISET 2024

作者： Islam, Md. Mirajul Mia, Md. Sharif Kamrunnaher Akter, Suma Islam, Mohammad Tariqul Azim, Rezaul University of Chittagong Research Laboratory for CEM Department of Physics Chattogram4331 Bangladesh Universiti Kebangsaan Malaysia Department of Electrical Electronic and Systems Engineering Bangi43600 Malaysia

ISBN: (纸本)9798350355499

Global communications are predicted to radically change with the arrival of fifth-generation (5G) mobile communications technology. This paper proposes a 2 × 2 MIMO antenna for 28 GHz broadband communications applications. The design is initiated by designing an antenna for 28 GHz, then a rectangular slot is added to enhance the impedance matching, and finally, a circular patch is inserted. The single element of the anticipated MIMO antenna on the RT5880 substrate resonates at 28.09 GHz with an S11 of-3 9. 3 5 dB. The MIMO structure has a volumetric dimension of 30.32 × 3 0. 3 2 × 1.575 mm3, resonates at 28.13 GHz, and achieves a working bandwidth of 3.07 GHz (26.63 to 29.70 GHz). Moreover, it achieves a maximum isolation of -58.04 dB, a maximum efficiency of 9 9 %, and a peak gain of 7.41 dBi. The achieved ECC ≤ 0.0005, and the DG is nearer 10 dB. Compared to the recently reported mmWave MIMO antennas, the designed MIMO antenna demonstrates superior performance in terms of operating bandwidth, isolation, gain, efficiency, ECC, and DG, which makes it an effective nominee for 5 GmmWave, satellite, and mobile communication applications. © 2024 IEEE.

关键词： Microwave antennas

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