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International Conference on Science Technology engineering and Management (ICONSTEM)

作者： U. Rahamathunnisa Chettiyar Vani Vivekanand Chithras. T Sreedevi. E Venneti Kiran Rajendiran M School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Tamil Nadu Department of Electronics and Communication Engineering RMK College of Engineering and Technology Thiruvallur Tamil Nadu Department of Electrical and Electronics Engineering Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamil Nadu India Department of Computer Science and Engineering KoneruLakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Department of Computer Science and Engineering (AIML) Aditya College of Engineering Surampalem Andhra Pradesh Department of Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

The development and optimisation of energy-efficient communication protocols that are specifically adapted for Internet of Things (IoT) devices is the focus of this research. The proliferation of interoperable bias has given rise to the converse girding energy consumption, which has come a consummate concern in the contemporary period. The primary end of this bid is to probe innovative approaches and protocols with the capacity to reduce the energy consumption of Internet of Effects(IoT) connections. As a result, the bias will retain the capability to attain an extended functional lifetime while coincidently producing a lowered environmental footmark. The presented protocols aim to achieve a result that balances the utilisation of energy coffers with the conservation of dependable communication. A thorough examination of the presently employed protocols, coupled with the perpetration of sophisticated optimisation ways, will be the styles employed to achieve this thing. Theprovides a significant donation to the development and prosecution of communication protocols that effectively address the unique energy constraints encountered by Internet of effects(10T)- connected ecosystems. This contributes to the enhancement of effectiveness and sustainability in the world of networked bias, which is expanding at an accelerated rate.

关键词： Energy consumption Protocols Ecosystems Energy efficiency Internet of Things Sustainable development Probes

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RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation Using Multimodal MRI Inputs

RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation Using ...

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Workshop on Longitudinal Disease Tracking and Modeling with Medical Images and Data, LDTM 2024, 5th International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2024, 1st Workshop on Machine Learning for Multimodal/-sensor Healthcare Data, ML4MHD2024 and Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support, ML-CDS 2024 held in conjunction with the 27th International Conference on Medical Image Computing and computer Assisted Intervention, MICCAI 2024

作者： Feng, Anqi Bian, Zhangxing Dewey, Blake E. Colinco, Alexa Gail Zhuo, Jiachen Prince, Jerry L. Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health BaltimoreMD21224 United States Department of Neurology Johns Hopkins School of Medicine BaltimoreMD21287 United States Department of Diagnostic Radiology and Nuclear Medicine University of Maryland School of Medicine BaltimoreMD21218 United States

ISBN: (纸本)9783031845246

Accurate segmentation of thalamic nuclei is important for better understanding brain function and improving disease treatment. Traditional segmentation methods often rely on a single T1-weighted image, which has limited contrast in the thalamus. In this work, we introduce RATNUS, which uses synthetic T1-weighted images with many inversion times along with diffusion-derived features to enhance the visibility of nuclei within the thalamus. Using these features, a convolutional neural network is used to segment 13 thalamic nuclei. For comparison with other methods, we introduce a unified nuclei labeling scheme. Our results demonstrate an 87.19% average true positive rate (TPR) against manual labeling. In comparison, FreeSurfer and THOMAS achieve TPRs of 64.25% and 57.64%, respectively, demonstrating the superiority of RATNUS in thalamic nuclei segmentation. The source code and pretrained models are available at: https://***/ANQIFENG/RATNUS. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Enhancing Next-Generation Urban Connectivity: Is the Integrated HAPS-Terrestrial Network a Solution?

arXiv

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arXiv 2023年

作者： Shamsabadi, Afsoon Alidadi Yadav, Animesh Yanikomeroglu, Halim Non-Terrestrial Networks Lab. Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada The School of Electrical Engineering and Computer Science Ohio University AthensOH45701 United States

Located in the stratospheric layer of Earth's atmosphere, high altitude platform station (HAPS) is a promising network infrastructure, which can bring significant advantages to sixth-generation (6G) and beyond wireless communications systems by forming vertical heterogeneous networks (vHetNets). However, if not dealt with properly, integrated networks suffer from several performance challenges compared to standalone networks. In harmonized spectrum integrated networks, where different tiers share the same frequency spectrum, interference is an important challenge to be addressed. This work focuses on an integrated HAPS-terrestrial network, serving users in an overlapped urban geographic area, and formulates a fairness optimization problem, aiming to maximize the minimum spectral efficiency (SE) of the network. Due to the highly nonconvex nature of the formulated problem, we develop a rapid converging iterative algorithm that designs the multiple-input multiple-output (MIMO) beamforming weights and the user association scheme such that the propagated inter- and intra-tier interference is managed. Simulation results demonstrate the proposed algorithm's superiority over standalone terrestrial networks and scenario where only the beamforming weights are optimized. © 2023, CC0.

关键词： Heterogeneous networks

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Leakage Localization in Water Distribution Networks: A Model-Based Approach

arXiv

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arXiv 2022年

作者： Lindström, Ludvig Gracy, Sebin Magnússon, Sindri Sandberg, Henrik The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden The Department of Computer and Systems Sciences Stockholm University Sweden

The paper studies the problem of leakage localization in water distribution networks. For the case of a single pipe that suffers from a single leak, by taking recourse to pressure and flow measurements, and assuming those are noiseless, we provide a closed-form expression for leak localization, leak exponent and leak constant. For the aforementioned setting, but with noisy pressure and flow measurements, an expression for estimating the location of the leak is provided. Finally, assuming the existence of a single leak, for a network comprising of more than one pipe and assuming that the network has a tree structure, we provide a systematic procedure for determining the leak location, the leak exponent, and the leak constant. © 2022, CC BY.

关键词： Water distribution systems

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Time-resolved HBT interferometry of an integrated pulsed biphoton frequency comb

Time-resolved HBT interferometry of an integrated pulsed bip...

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Laser Science, LS 2022

作者： Seshadri, Suparna Myilswamy, Karthik V. Liu, Junqiu Kippenberg, Tobias J. Weiner, Andrew M. Lukens, Joseph M. School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States LausanneCH-1015 Switzerland Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States

We use electro-optic phase modulation to characterize the time-resolved second-order coherence of a multimode signal field generated via pulsed spontaneous four-wave mixing in an integrated 40.5 GHz Si3N4 microring. &... 详细信息

ISBN: (纸本)9781557528209

关键词： Silicon compounds

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Cryptanalysis via Machine Learning Based Information Theoretic Metrics

arXiv

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arXiv 2025年

作者： Kim, Benjamin D. Vasudevan, Vipindev Adat D’Oliveira, Rafael G.L. Cohen, Alejandro Stahlbuhk, Thomas Médard, Muriel Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign ChampaignIL61820 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States School of Mathematical and Statistical Sciences Clemson University ClemsonSC29631 United States Technion Faculty of Electrical Engineering Technion Israel Institute of Technology Haifa32000 Israel MIT Lincoln Laboratory LexingtonMA02421 United States

The fields of machine learning (ML) and cryptanalysis share an interestingly common objective of creating a function, based on a given set of inputs and outputs. However, the approaches and methods in doing so vary vastly between the two fields. In this paper, we explore integrating the knowledge from the ML domain to provide empirical evaluations of cryptosystems. Particularly, we utilize information theoretic metrics to perform ML-based distribution estimation. We propose two novel applications of ML algorithms that can be applied in a known plaintext setting to perform cryptanalysis on any cryptosystem. We use mutual information neural estimation to calculate a cryptosystem’s mutual information leakage, and a binary cross entropy classification to model an indistinguishability under chosen plaintext attack (CPA). These algorithms can be readily applied in an audit setting to evaluate the robustness of a cryptosystem and the results can provide a useful empirical bound. We evaluate the efficacy of our methodologies by empirically analyzing several encryption schemes. Furthermore, we extend the analysis to novel network coding-based cryptosystems and provide other use cases for our algorithms. We show that our classification model correctly identifies the encryption schemes that are not IND-CPA secure, such as DES, RSA, and AES ECB, with high accuracy. It also identifies the faults in CPA-secure cryptosystems with faulty parameters, such a reduced counter version of AES-CTR. We also conclude that with our algorithms, in most cases a smaller-sized neural network using less computing power can identify vulnerabilities in cryptosystems, providing a quick check of the sanity of the cryptosystem and help to decide whether to spend more resources to deploy larger networks that are able to break the cryptosystem. © 2025, CC BY-NC-ND.

关键词： Information leakage

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TrojanWhisper: Evaluating Pre-trained LLMs to Detect and Localize Hardware Trojans

arXiv

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arXiv 2024年

作者： Faruque, Md Omar Jamieson, Peter Patooghy, Ahmad Badawy, Abdel-Hameed A. Klipsch School of ECE New Mexico State University Las CrucesNM88003 United States Department of Electrical and Computer Engineering Miami University OxfordOH United States Computer Systems Technology North Carolina A&T State University GreensboroNC United States

Existing Hardware Trojans (HT) detection methods face several critical limitations: logic testing struggles with scalability and coverage for large designs, side-channel analysis requires golden reference chips, and formal verification methods suffer from state-space explosion. The emergence of Large Language Models (LLMs) offers a promising new direction for HT detection by leveraging their natural language understanding and reasoning capabilities. For the first time, this paper explores the potential of general-purpose LLMs in detecting various HTs inserted in Register Transfer Level (RTL) designs, including SRAM, AES, and UART modules. We propose a novel tool for this goal that systematically assesses state-of-the-art LLMs (GPT-4o, Gemini 1.5 pro, and Llama 3.1) in detecting HTs without prior fine-tuning. To address potential training data bias, the tool implements perturbation techniques, i.e., variable name obfuscation, and design restructuring, that make the cases more sophisticated for the used LLMs. Our experimental evaluation demonstrates perfect detection rates by GPT-4o and Gemini 1.5 pro in baseline scenarios (100%/100% precision/recall), with both models achieving better trigger line coverage (TLC: 0.82-0.98) than payload line coverage (PLC: 0.32-0.46). Under code perturbation, while Gemini 1.5 pro maintains perfect detection performance (100%/100%), GPT-4o (100%/85.7%) and Llama 3.1 (66.7%/85.7%) show some degradation in detection rates, and all models experience decreased accuracy in localizing both triggers and payloads. This paper validates the potential of LLM approaches for hardware security applications, highlighting areas for future improvement. TrojanWhisper’s HT detection results will be available here https://***/HSTRG1/***. Copyright © 2024, The Authors. All rights reserved.

关键词： Formal verification

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Optimal Input Design for Sparse System Identification

Optimal Input Design for Sparse System Identification

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European Control Conference (ECC)

作者： Javad Parsa Cristian R. Rojas Hå kan Hjalmarsson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9783907144077

ISBN: (纸本)9781665497336

In this contribution we consider sparse linear regression problems. It is well known that the mutual coherence, i.e. the maximum correlation of the regressors, is important for the ability of any algorithm to recover the sparsity pattern of an unknown parameter vector from data. A low mutual coherence improves the ability of recovery. In optimal experiment design this requirement may be in conflict with other objectives encoded by the desired Fisher matrix. In this contribution we alleviate this issue by combining optimal input design with a recently proposed approach to achieve low mutual coherence by way of a linear coordinate transformation. The resulting optimization problem is solved using cyclic minimization. Via simulations we demonstrate that the resulting algorithm is able to achieve a Fisher matrix which results in a performance close to the performance if the sparsity would have been known, while at the same time being able to recover the sparsity pattern.

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Kinetic granular temperature and its measurement using speckle visibility spectroscopy

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Particuology 2020年第1期18卷 160-169页

作者： Hui Yang Yonghai Zhu Ran Li Qicheng Sun School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical Systems University of Shanghai for Science and TechnologyShanghai 200093China State Key Laboratory of Hydroscience and Engineering Tsinghua UniversityBeijing 100084China

The occurrence of a mesoscopic scale in granular materials leads to a sharp increase in the number of interaction processes at both intra-and inter-scale *** mesoscopic scale is the main source of the complex macroscopic properties of granular *** quantification of mesoscopic disordered movements is often referred to as granular *** this paper,we first introduce the physical meaning of the original granular temperature of a kinetic nature,Tk,and then briefly summarize the advances made over the past few *** research group has focused on Tk measurement using speckle visibility *** principle of this technique and the instruments developed in our research group are briefly *** work shows great promise in the measurement of kinetic granular ***,a summary of granular temperature and some recent developments in speckle visibility spectroscopy measurements are presented.

关键词： Granular flow Mesoscopic process Granular temperature Speckle visibility spectroscopy

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An Empirical Study of Data Sampling Techniques for Just-in-Time Software Defect Prediction

SSRN

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SSRN 2023年

作者： Li, Zhiqiang Du, Qiannan Niu, Jingwen Zhang, Hongyu Jing, Xiao-Yuan School of Computer Science Shaanxi Normal University Shaanxi Xi’an710119 China School of Computer and Information Engineering Xinxiang University Henan Xinxiang453003 China School of Electrical Engineering and Computing The University of Newcastle CallaghanNSW2308 Australia School of Computer Science Wuhan University Hubei Wuhan430072 China School of Computer Science Guangdong Provincial Key Laboratory on Petrochemical Equipment Fault Diagnosis Guangdong University of Petrochemical Technology Guangdong Maoming525000 China

Predicting whether there are defects in code changes submitted by developers is called just-in-time software defect prediction (JIT-SDP). Unfortunately, JIT-SDP usually suffers from the class imbalance problem, which affects its prediction performance. To overcome this problem, data sampling is one of the commonly-used class imbalance techniques. However, there is a lack of comprehensive empirical study to compare different data sampling techniques on the performance of JIT-SDP. In this paper, we consider both defect classification and defect ranking, two typical application scenarios. We perform an empirical comparison of 10 data sampling algorithms on the performance of JIT-SDP with three widely-used classifiers. Extensive experiments on 10 projects show that: (1) In the scenario of defect classification, sampling techniques can significantly improve the performance of Recall while are unfavorable for the performance of Precision and Pf. (2) In the scenario of defect ranking, sampling techniques can significantly improve the performance of Recall@20% while are unfavorable for the performance of Precision@20% and PCI@20%. Generally, ROM and SMOTE are more stable and effective sampling algorithms across several performance measures for JIT-SDP in both defect classification and defect ranking scenarios. Hence, our study suggests that future JIT-SDP research can use ROM and SMOTE rebalancing defect data. © 2023, The Authors. All rights reserved.

关键词： Defects

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