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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3579-3594页

作者： Chakraborty, Prabuddha Bhunia, Swarup University of Maine Department of Electrical & Computer Engineering OronoME04469 United States University of Florida Department of Electrical & Computer Engineering GainesvilleFL32603 United States

Edge computing devices in Internet-of-Things (IoT) systems are being widely used in diverse application domains including industrial automation, surveillance, and smart housing. These applications typically employ a large array of sensors, store a high volume of data, and search within the stored data for specific patterns using machine intelligence. Due to this heavy reliance on data in these applications, optimizing the memory performance in edge devices has become an important research focus. In this work, we note (based on some preliminary quantitative studies) that the memory requirements of such application-specific systems tend to differ drastically from traditional general-purpose computing systems. Inspired by these findings and also through drawing inspiration from the human brain (which excels at being highly adaptive), we design a digital memory framework that can continually adapt to the specific needs of different edge devices. This adaption is made possible through a continual reinforcement-based learning methodology, and it aims at creating a digital memory framework that is always self-aware of the data it hold and queries being made. Through a methodical implementation of the framework, we demonstrate its effectiveness for different use-cases, settings, and hyperparameters in comparison with traditional content-addressable memory. © 2020 IEEE.

关键词： Internet of things

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A Review of Anonymization Algorithms and Methods in Big Data

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Annals of Data Science 2025年第1期12卷 253-279页

作者： Shamsinejad, Elham Banirostam, Touraj Pedram, Mir Mohsen Rahmani, Amir Masoud Department of Computer Engineering Central Tehran Branch Islamic Azad University Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran

In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of users. This study was conducted with the aim of finding a solution to this challenge. In this study, we examined various data anonymization methods, including differential privacy, advanced encryption, and strong access controls. In addition, the operation, advantages, disadvantages, and use of these methods, the challenges of adapting these methods to big data, and possible solutions for them were also examined. Our results show that traditional data anonymization methods lack scalability, leading to privacy breaches and data loss. When faced with large volumes of data, these methods may not be able to fully process the data. Also, these methods may be ineffective against re-identification attacks, linkage attacks, and inference attacks. We introduced emerging methods that are capable of providing improved privacy with minimal data loss. These methods have scalability for big data. Finally, we examined future research works and raised important questions that can help improve existing algorithms or develop new methods, better manage the complexity and scale of unstructured data. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Big data

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Robotic FDM for free-form fabrication: evaluating adaptive non-planar slicing with different contour methods

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Rapid Prototyping Journal 2025年第11期31卷 160-178页

作者： Furlan, Valentina Insero, Federico Giberti, Hermes Department of Electrical Computer and Biomedical Engineering Università di Pavia Pavia Italy

Purpose: This study aims to investigate and compare three nonplanar (NP) slicing algorithms. The algorithms aim to control the layer thickness variation (LTV), which is a common issue in supportless fabrication of free-form parts. The comparison underlines the differences between theoretical and real scenarios, resulting in guidelines for toolpath generation of complex objects. Design/methodology/approach: The algorithm comparison uses a representative complex geometry, i.e. the quarter of torus. It presents an increasing overhang and constant curvature. It is represented using a parametric definition in the first two algorithms and by triangular meshes as the real scenario. The algorithms work on the contouring stage, whereas a B-spline approach is used to build the inner side of layers. Constant layer thickness (LT) is imposed, and an adaptive approach is adopted to avoid over-extrusion. Three algorithms are validated with a robotized fused deposition modeling system. LTs are measured on cross-sectioned samples and compared with the theoretical cases. Findings: The results show that two algorithms can provide an LTV of about 0% on the contour. Nevertheless, the theoretical results on the inner side are divergent from the previous evidence, moving on to higher LTV (approximately 90%). The need for an adaptive approach is demonstrated, resulting in an LTV reduction (approximately 30%). Printed parts present the same trends of theoretical results confirming the algorithms’ capabilities. Originality/value: The work shows, for the first time, a comparison between NP slicing techniques. The LTV problem in hollow and filled components is analyzed through theoretical and experimental evidence. The results are promising for supportless fabrication of free-form parts. © 2025, Valentina Furlan, Federico Insero and Hermes Giberti.

关键词： Fabrication

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Innovative Design for Mutual Coupling Reduction in Dual-Element Array Antennas for ISM Applications Using Whale Optimization Algorithm

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Progress in Electromagnetics Research C 2025年 152卷 121-129页

作者： Atashpanjeh, Elham Rezaei, Pejman Department of Electrical and Computer Engineering Semnan University Semnan35131-19111 Iran

This paper introduces a decoupled dual-element array antenna designed to address the challenges of mutual coupling between elements. To tackle this issue, a neutralization line is strategically incorporated to suppress leaky surface currents, while ensuring that the antenna’s central frequency and radiation pattern remain intact. The dimensions of the neutralization line are carefully optimized using the Whale Optimization Algorithm (WOA) to achieve the best possible performance, focusing on minimizing mutual coupling and enhancing gain. By placing the neutralization line nearby between the two elements, surface currents are efficiently redirected back to the radiating element, preventing leakage to neighboring elements. This approach also results in a more compact structure. The proposed antenna, with overall dimensions of 50 mm × 30 mm × 1.6 mm, is simulated using analytic software. It achieves an impressive 27 dB reduction in mutual coupling and delivers an ultra-wide bandwidth of 1.2 GHz within the Industrial Scientific and Medical (ISM) band at an operating frequency of 2.4 GHz, with a measured maximum gain of −5.19 dB. The structure was fabricated, and experimental results closely matched the simulations, confirming the design’s effectiveness. By leveraging the WOA optimization method, the geometry of the neutralization line was fine-tuned to maximize performance, significantly improving inter-element decoupling. This design approach is simple yet effective and can be readily extended to other antenna array configurations, demonstrating strong potential for compact and efficient ISM band applications. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Directional patterns (antenna)

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TPUXtract: An Exhaustive Hyperparameter Extraction Framework

IACR Transactions on Cryptographic Hardware and Embedded Sys...

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IACR Transactions on Cryptographic Hardware and Embedded Systems 2025年第1期2025卷 78-103页

作者： Kurian, Ashley Dubey, Anuj Yaman, Ferhat Aysu, Aydin Department of Electrical and Computer Engineering North Carolina State University United States

Model stealing attacks on AI/ML devices undermine intellectual property rights, compromise the competitive advantage of the original model developers, and potentially expose sensitive data embedded in the model’s behavior to unauthorized parties. While previous research works have demonstrated successful side-channelbased model recovery in embedded microcontrollers and FPGA-based accelerators, the exploration of attacks on commercial ML accelerators remains largely unexplored. Moreover, prior side-channel attacks fail when they encounter previously unknown models. This paper demonstrates the first successful model extraction attack on the Google Edge Tensor Processing Unit (TPU), an off-the-shelf ML accelerator. Specifically, we show a hyperparameter stealing attack that can extract al l layer configurations including the layer type, number of nodes, kernel/filter sizes, number of filters, strides, padding, and activation function. Most notably, our attack is the first comprehensive attack that can extract previously unseen models. This is achieved through an online template-building approach instead of a pre-trained ML-based approach used in prior works. Our results on a black-box Google Edge TPU evaluation show that, through obtained electromagnetic traces, our proposed framework can achieve 99.91% accuracy, making it the most accurate one to date. Our findings indicate that attackers can successfully extract various types of models on a black-box commercial TPU with utmost detail and call for countermeasures. © 2025, Ruhr-University of Bochum. All rights reserved.

关键词： Network security

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COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第6期6卷 1664-1678页

作者： Hossain, Md. Ismail Rakib, Mohammed Elahi, M. M. Lutfe Mohammed, Nabeel Rahman, Shafin North South University Department of Electrical and Computer Engineering Dhaka1229 Bangladesh

Pruning refers to the elimination of trivial weights from neural networks. The sub-networks within an overparameterized model produced after pruning are often called Lottery tickets. This research aims to generate winning lottery tickets from a set of lottery tickets that can achieve accuracy similar to that of the original unpruned network. We introduce a novel winning ticket called Cyclic Overlapping Lottery Ticket (COLT) by data splitting and cyclic retraining of the pruned network from scratch. We apply a cyclic pruning algorithm that keeps only the overlapping weights of different pruned models trained on different data segments. Our results demonstrate that COLT can achieve similar accuracies (obtained by the unpruned model) while maintaining high sparsities. Based on object recognition and detection tasks, we show that the accuracy of COLT is on par with the winning tickets of the Lottery Ticket Hypothesis (LTH) and, at times, is better. Moreover, COLTs can be generated using fewer iterations than tickets generated by the popular Iterative Magnitude Pruning (IMP) method. In addition, we also notice that COLTs generated on large datasets can be transferred to small ones without compromising performance, demonstrating its generalizing capability. We conduct all our experiments on Cifar-10, Cifar-100, TinyImageNet, and ImageNet datasets and report superior performance than the state-of-the-art methods. The codes are available at: https://***/ismail31416/COLT. © 2020 IEEE.

关键词： Object detection

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Negative Group Delay Prototype Filter Based on the Reciprocal Transfer Function of a Low-Pass Butterworth Filter Capped at Finite Out-of-Band Gain

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Progress In Electromagnetics Research B 2024年 106卷 17-38页

作者： Kandic, Miodrag Bridges, Greg E. Department of Electrical and Computer Engineering University of Manitoba WinnipegMB Canada

A Negative Group Delay (NGD) prototype filter design based on the reciprocal transfer function of a low-pass Butterworth filter of a given order, is presented. The out-of-band gain of the prototype transfer function is capped at a finite constant value via multiplication by a transfer function of a low-pass Butterworth filter with 3 dB bandwidth that is wider than the reciprocal function bandwidth. Such synthesized transfer function exhibits maximal magnitude characteristic flatness within the 3 dB bandwidth (Butterworth-like property), while it also exhibits NGD and satisfies Kramers-Kronig relations (causal transfer function). The prototype design achieves an NGD-bandwidth product that in the upper asymptotic limit as the design order increases, is a linear function of out-of-band gain in decibels. This is an improvement compared with previously reported cascaded first-order and second-order designs, which have NGDbandwidth functional dependency of out-of-band gain in decibels to the power of 1/2 and 3/4, respectively. It is shown that the transfer function of the corresponding design transformed to a non-zero center frequency can be exactly implemented with a Sallen-Key topology employing parallel resonators, or approximately implemented with an all-passive ladder topology. An in-band magnitude/phase distortion metric is applied to the prototype designs, evaluated for Gaussian and sinc pulse input waveforms, and compared with values obtained for a well-known commonly used medium. It is also shown that when the specified bandwidth corresponds to the entire bandwidth over which the group delay characteristic is negative, the magnitude characteristic variation approximately equals half the out-of-band gain value in decibels. Therefore, for any NGD design with large out-of-band gain (typically higher than 6 dB), using the entire bandwidth where group delay is negative can result in strong levels of distortion and should be checked for applied waveforms. © (2024), Ele

关键词： Transfer functions

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Evaluation of the Economic Viability and Sustainability of Renewable Energy using Building Integrated Photovoltaics in an Urban Apartment Complex

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Transactions of the Korean Institute of electrical Engineers 2024年第3期73卷 508-515页

作者： Gong, Youngmin Kim, Insu Dept. of Electrical Engineering Inha University Korea Republic of Department of Electrical and Computer Engineering Inha University Korea Republic of

In order to cope with the current climate crisis, reducing greenhouse gas emissions is an important issue, and it is necessary to increase the amount of renewable energy generation. However, there is a problem of economics in renewable energy, and in the case of the Republic of Korea, there is a problem of geographical mismatch between the supply and demand of renewable energy. This study proposes building integrated photovoltaics (BIPV) as a way to solve the problems associated with renewable energy. In this study, a model for charging an electric bus by the power generated by building integrated photovoltaics was proposed, evaluated and analyzed. The results show that BIPV can generate revenue of KRW 39.9 billion over 30 years and can contribute to increasing the amount of renewable energy generation in Seoul by accounting for 1.85% of the annual solar power generation in Seoul. © 2024 Korean Institute of electrical Engineers. All rights reserved.

关键词： Solar power generation

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Single-And Dual-Beam Pattern Reconfigurable Patch Antenna With Dual Switchable CP for Internet of Vehicles

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IEEE Internet of Things Journal 2025年第12期12卷 21904-21914页

作者： Wang, Shi-Tong Zhu, Lei University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

In this article, a novel method is proposed to facilitate the design of compact, low-profile, pattern reconfigurable antennas with fixed or switchable circular polarization (CP) for Internet of Vehicles (IoV) applications. The proposed method eliminates the need for a complex beamforming or phase-tuning network by innovatively exploiting four resonant modes of a square patch antenna. Specifically, the TM01 and TM10 modes are utilized to accomplish the single-beam CP pattern, while, the dualbeam CP pattern is achieved by combining the TM11 and TM02 modes. An electric current model is developed to investigate the far-field radiation, revealing that the radiation pattern of TM11 mode can be effectively reshaped from quad-beam to dual-beam by manipulating the surface current distribution. The complete design method is verified by an antenna prototype working at 3.5 GHz, which consists of a radiative patch, a pair of open-ended stubs, a pair of slots, and four equivalent switchable pins. Different from the conventional pin-loading method, the proposed equivalent switchable pins attain excellent CP performance during switching by compensating for the detrimental electric coupling. The prototype is fabricated and measured. Its radiation can be switched between single-beam (7.8 dBic) and dual-beam CP pattern (3.5 dBic), exhibiting an overlapped CP coverage from -123° to 73°. Furthermore, another prototype with the extended switchable CP capability is realized. Without increasing the number of p-i-n diodes, this prototype achieves four operating states with independent pattern (single-and dual-beam) and polarization (right-and left-handed CP) reconfiguration. The merits of compact size, low profile, and flexible reconfigurability make the proposed method and design cases excellent candidates for IoV applications and intelligent transportation systems (ITSs). © 2014 IEEE.

关键词： Circular polarization

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An end-to-end network for co-saliency detection in one single image

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Science China(Information Sciences) 2023年第11期66卷 5-22页

作者： Yuanhao YUE Qin ZOU Hongkai YU Qian WANG Zhongyuan WANG Song WANG School of Cyber Science and Engineering Wuhan University School of Computer Science Wuhan University Department of Electrical Engineering and Computer Science Cleveland State University Department of Computer Science and Engineering University of South Carolina

Co-saliency detection within a single image is a common vision problem that has not yet been well addressed. Existing methods often used a bottom-up strategy to infer co-saliency in an image in which salient regions are firstly detected using visual primitives such as color and shape and then grouped and merged into a co-saliency map. However, co-saliency is intrinsically perceived complexly with bottom-up and top-down strategies combined in human vision. To address this problem, this study proposes a novel end-toend trainable network comprising a backbone net and two branch nets. The backbone net uses ground-truth masks as top-down guidance for saliency prediction, whereas the two branch nets construct triplet proposals for regional feature mapping and clustering, which drives the network to be bottom-up sensitive to co-salient regions. We construct a new dataset of 2019 natural images with co-saliency in each image to evaluate the proposed method. Experimental results show that the proposed method achieves state-of-the-art accuracy with a running speed of 28 fps.

关键词： saliency detection convolutional neural network regional feature mapping co-saliency detection deep learning

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