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arXiv 2023年

作者： Fakih, Mohamad Kanj, Rouwaida Kurdahi, Fadi Fouda, Mohammed E. Electrical and Computer Engineering Dept. American University of Beirut Lebanon1107 202 Lebanon Center for Embedded & Cyber-physical Systems University of California-Irvine IrvineCA92697-2625 United States

Automatic Speech Recognition systems have been shown to be vulnerable to adversarial attacks that manipulate the command executed on the device. Recent research has focused on exploring methods to create such attacks, however, some issues relating to Over-The-Air (OTA) attacks have not been properly addressed. In our work, we examine the needed properties of robust attacks compatible with the OTA model, and we design a method of generating attacks with arbitrary such desired properties, namely the invariance to synchronization, and the robustness to filtering: this allows a Denial-of-Service (DoS) attack against ASR systems. We achieve these characteristics by constructing attacks in a modified frequency domain through an inverse Fourier transform. We evaluate our method on standard keyword classification tasks and analyze it in OTA, and we analyze the properties of the cross-domain attacks to explain the efficiency of the approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Frequency domain analysis

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Estimation of ZnO Nanoparticles Crystallite Parameters at Different Compression Temperatures 5

Estimation of ZnO Nanoparticles Crystallite Parameters at Di...

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5th International Conference on electrical engineering and Information and Communication technology, ICEEICT 2021

作者： Uddin, Zia Uddin, Md. Jaber Islam, Mohammad Rafiqul Alam, M. Shafiul Soga, Tetsuo Choudhury, Md. Shamimul Haque International Islamic University Chittagong Dept. of Electrical and Electronic Engineering Bangladesh Manarat International University Dept. of Computer Science and Engineering Bangladesh King Fahad University of Petroleum and Minerals K.A. CARE Energy Research and Innovation Center Dhahran Saudi Arabia Nagoya Institute of Technology Dept. of Electrical and Mechanical Engineering Nagoya Japan

ISBN: (纸本)9781665495226

In this work, ZnO films were processed utilizing a standard blade coating procedure at different compression temperatures (50 to 90{circ}mathrm{C} temperature at 120 MPa compression). The X-ray Diffraction (XRD) technique is used to characterize the films. The crystallite sizes, microstrains, and dislocation densities of the ZnO nanoparticles (NPs) sample were studied using several methods, including the Modified Scherrer method, the Wagner-Agua (W-A) method, and the Halder-Wagner (H-W) method, based on XRD data. The results were compared to observe the effects of compression temperatures on various structural parameters. From the analysis, it is evident that ZnO nanoparticles are crystallite in nature with a hexagonal wurtzite phase. The crystallite size calculated from the Modified Scherrer method, the H-W, and the W-A methods match very well, are greatly inter-correlated, and range from 12.7 to 15.29 nm. The dislocation density and lattice strain exhibited an inverse relationship with crystallite size. The crystallinity improves gradually up to 70{circ}mathrm{C} with increasing compression temperatures, then decreases. However, impacts on various crystallite components caused by various temperatures at 120 MPa pressure are also utilized to characterize the Dye-sensitized solar cells (DSSCs) behavior. The photovoltaic performance of the 70{circ}mathrm{C} temperature 120 MPa compressed cell was shown to be better where the average crystallite size was comparatively large. © 2021 IEEE.

关键词： X ray diffraction

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G Loaded Complementary Split Square Ring Resonator-Based SNG Metamaterial for Wi-Fi, IoT & Satellite Applications 7

G Loaded Complementary Split Square Ring Resonator-Based SNG...

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7th International Conference on Space Science and Communication, IconSpace 2021

作者： Islam, Md. Rashedul Bais, Badariah Samsuzzaman, Md. Mahmud, Md. Zulfiker Arshad, Haslina Sahar, Norsuzlin Mohd Singh, Mandeep Singh Jit Universiti Kebangsaan Malaysia Dept. Of Electrical Electronic And Systems Engineering Selangor Bangi43600 Malaysia Patuakhali Science And Technology University Dept. Of Computer And Communication Engineering Patuakhali8602 Bangladesh Jagannath University Dept. Of Computer Science And Engineering Dhaka1100 Bangladesh Universiti Kebangsaan Malaysia Institute Of IR4.0 Ipi Bangi Selangor43600 Malaysia

ISBN: (纸本)9781665425230

In this study, a novel miniaturized G-inspired complementary split square ring resonator-based single negative (SNG) metamaterial (MTM) has been developed for wireless fidelity (Wi-Fi), internet of thing (IoT), and Satellite applications. Commercially available user-friendly computer simulation technology (CST-2019) electromagnetic simulator was used for the layout design and detailed analysis of the produced structure. The MTM unit cell size is 8×8 mm2, and it is integrated on a Rogers RO4350B dielectric substrate. A high effective medium ratio (EMR) is obtained from this structure;the value of it is 15.63. The effective medium parameters were extracted using the Nicolson-Ross-Weir (NRW) approach. To design the recommended MTM, various parametric studies have been done. Over a wide frequency range, the constructed structure has negative permittivity and also the negative refractive index. The obtained transmission coefficient (S21) resonance frequencies are 2.40, 4.18, 6.57, and 10.36 GHz, which covers S-, C-, and X-bands. Since the size of the designed cell is small, high EMR, desired resonance frequency, and the maximum band have been found;hence it can be used in Wi-Fi, IoT, and satellite applications. © 2021 IEEE.

关键词： Metamaterials

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Carotid Plaque Motion Analysis in Ultrasound Videos to Discover Rupture-Prone Plaque Areas

Carotid Plaque Motion Analysis in Ultrasound Videos to Disco...

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IEEE International Symposium on Biomedical Imaging

作者： Georgia D. Liapi Christos P. Loizou Andrew Nicolaides Maura Griffin Dimitrios Kardoulas Constantinos Pattichis Efthyvoulos Kyriacou Dept. of Electrical Engineering Computer Eng. and Informatics Cyprus University of Technology Limassol Cyprus Vascular Screening and Diagnostic Center Nicosia Cyprus Hemodynamic Unit Vascular Surgery Clinic National and Kapodistrian University of Athens Attikon General University Hospital Athens Greece Dept. of Computer Science University of Cyprus Nicosia Cyprus

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Identification of carotid plaque motion alterations, throughout the cardiac cycle (CC), may reveal rupture-prone plaque components and assist doctors in ischemic stroke risk stratification. In this study, we investigated Ultrasound (U/S) carotid plaque motion, focusing on middle-systole (MS), the interval between early systole (ES) and peak systole (PS) expecting that the dynamic forces applied on the plaque at the beginning of systole are more profound from cardiac ES to MS, compared to PS. We deployed a computer tool, previously developed by researchers of the e-health laboratory at Cyprus University of technology, for carotid plaque motion estimation in B-mode U/S videos. We included 16 carotid U/S videos (8 Asymptomatic, AS; 8 Symptomatic, SY patients) and performed video frame (VF) resolution standardization, manual region of interest (ROI) selection, identification of 5 CCs (ES and MS pairs), and plaque motion spread and magnitude measurement, based on dense optical flow. The Maximum Angular Spread (MAXFW 20 , first 20% of the plaque’s overall MAXFW; units: 0° to 360°), a measure we created to determine angle differences between motion vectors, in all plaque areas, can assist in classifying the plaque as concordant (low-strain), moderate(m)-discordant (mid-strain) or discordant (highstrain). We identified 1 concordant, 8 m-discordant, and 7 discordant plaques, with MAXFW 20 ranging from 58±7.45°, 91±43.9°, 156±49.2° (mean±standard deviation), respectively. As our primary findings support our hypothesis, in the future, we will also derive the stress applied on the carotid plaque, in ES and MS.

关键词： Ultrasonic imaging Standardization Stroke (medical condition) Vectors Real-time systems Motion measurement Motion analysis

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Aloe Vera Tissue Modeling and Parameter Identification Using Meta-heuristic Optimization Algorithm

Aloe Vera Tissue Modeling and Parameter Identification Using...

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International Conference on Microelectronics, ICM

作者： Mohamed S. Ghoneim Dalia A. Fathi Lobna A. Said Ahmed H. Madian Magdy A. Bayoumi Department of Electrical and Computer Engineering University of Louisiana at Lafayette LA USA Nanoelectronics Integrated Systems Center (NISC) Nile University Cairo Egypt Radiation Engineering Dept. NCRRT Egyptian Atomic Energy Cairo Egypt Center for Advanced Computer Studies University of Louisiana at Lafayette LA USA

The agricultural industry's use of non-invasive bioimpedance monitoring methods is expanding quickly. These measured impedance fluctuations reflect imperceptible biophysical and biochemical changes in living and non-living tissues. Bioimpedance circuit modeling is a valuable method for fitting the measured impedance in biology and medicine. A study on two samples of Aloe Vera leaves is conducted to identify the best model representing Aloe Vera leaves, and two different interelectrode spacing distances are used to measure each sample. An electrochemical station (SP150) is used to detect bio-impedance at frequencies between 80 Hz and 200 kHz. The effectiveness of the employed models is evaluated by fitting them to the measured data. Among all models used, the medical plant stem and simplified plant stem models show the best results for all inter-electrode spacing distances.

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VVoIP Quality Improvement Over IMS Network based on background subtraction

VVoIP Quality Improvement Over IMS Network based on backgrou...

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Learning and technology Conference (L&T)

作者： Hanafy M. Ali Aziza I. Hussein Waled M. Ismail Yahia B. Hassan Computers and Systems Engineering Dept. Faculty of Engineering Minia University El Minia Egypt College of Engineering Energy and Technology Research Center Effat University Saudi Arabia Mobile Core Back Office Engineer Telecom Egypt Co. Egypt Electrical Eng. Dept Higher Institute of Engineering Minia Egypt

The dependence on making Voice and Video over Internet Protocol (VVoIP) calls has increased dramatically in recent times. The use of VVoIP applications is not limited to social applications only but extended to business applications. The improvement of VVoIP call quality is one of the most important factors that enhance the spread of VVoIP services. In many cases, the high network traffic prevents the possibility of sending high data rate live video streams as sending high data rate live stream over high-traffic networks causes an increase in the data loss *** this paper, the codec switching techniques used to improve the quality under live networks with high traffic are discussed. In addition, A technique based on background subtraction to improve the quality of VVoIP calls using Python code to detect the moving pixels (foreground) and subtract them from the frame to discard the background is *** proposed technique was tested on large scale live network. The tested parameters impacting the Quality of Service (QoS) were packet loss and delay variation (Jitter). The study based on the comparison of packet loss and Jitter for the three common resolutions 480P, 720P and, 1080P over high traffic network without using background subtraction vs. using background subtraction. The results showed a significant improvement in different rates for each resolution and network condition.

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A Review of Algorithms’s Complexities on Different Valued Sorted and Unsorted Data

A Review of Algorithms’s Complexities on Different Valued S...

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IT and Industrial Technologies (ICIT), International Conference on

作者： Attia Shabbir Asad Majeed Mahnoor Iftikhar Raja Hashim Ali Usama Arshad Muhammad Zeeshan Shabbir Ali Zeeshan Ijaz Nisar Ali Ali Aftab Faculty of Computer Science & Engineering GIK Institute of Engg. Sciences & Technology Topi Pakistan Dept. of Technology & Software Engineering University of Europe for Applied Sciences Berlin Germany Department of Electrical Engineering University of Engineering & Technology (UET) Lahore Pakistan Faculty of Electronic Systems Engineering University of Regina Regina Canada

Sorting and searching are critical processes for effecttive data analysis. In this paper, we evaluate the performance of various sorting and searching algorithms and compare their time and space complexities on both sorted and unsorted data. The algorithms we analyzed include six common sorting algorithms (insertion, radix, bucket, merge, bubble, and quick sort) and three search algorithms (linear, binary, and jump search). The results of our study provide insights into the best algorithms to use for different input sizes and types of data. It was found that for small input sizes, all algorithms perform similarly, but for larger input sizes, insertion and radix sorts are better for time complexity while bubble sort is better for space complexity. Additionally, jump search outperformed linear and binary search algorithms in both time and space complexity. Besides, difference between time and space complexity of sorted and unsorted data was significant.

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“Should I Lead?” Feasibility Study of User Perception on Following-Robot for Gait Assessment

“Should I Lead?” Feasibility Study of User Perception on F...

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International Conference on Advanced Robotics (ICAR)

作者： Alessandra Sorrentino Bruno Ferreira Paulo Menezes Jorge Batista Jorge Dias Laura Fiorini Pietro Benvenuti Filippo Cavallo Department of Industrial Engineering University of Florence Florence Italy Dept. of Electrical and Computer Engineering University of Coimbra Institute of Systems and Robotics Coimbra Portugal Khalifa University of Science and Technology Khalifa University Center for Autonomous Robotic Systems Abu Dhabi UAE BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy

Current techniques of gait assessment rely on wearable sensors, pressure-sensitive walkway systems, and optical motion capture systems. A less invasive and more portable solution could be represented by a mobile robot that follows the user during the gait activity. The main idea behind this work relies on finding the best robot configuration for less invasive gait analysis with high acceptability from the end users. To this aim, two follow-me configurations have been designed: human-leader (i.e. the robot follows the person from behind), and robot-leader (i.e. robot follows the person from the front). We asked 27 young participants to test both modalities and to evaluate their perception of the robot in 5 domains: comfort, expected conformity, safety, trust, and unobtrusiveness. Additionally, we extracted quantitative parameters related to the walking experience from the data recorded by the platform and we analyzed them in tandem with the qualitative results. The results reported that robot-leader configuration tended to be more appreciated in terms of comfort, trust, and safety. On the contrary, the human-leader configuration is perceived as less obtrusive, less invasive, and in line with users' expectations. Considering the gait assessment application, we expect the human-leader configuration to return more promising and accurate results.

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A Comprehensive Survey of Text Classification Techniques and Their Research Applications: Observational and Experimental Insights

arXiv

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arXiv 2024年

作者： Taha, Kamal Yoo, Paul D. Yeun, Chan Homouz, Dirar Taha, Aya Department of Computer Science Khalifa University United Arab Emirates Department of Computer Science & Information Systems University of London Birkbeck College United Kingdom Center for Cyber-Physical Systems Dept. of Electrical Engineering and Computer Science Khalifa University United Arab Emirates Department of Physics Khalifa University United Arab Emirates Brighton College Dubai United Arab Emirates

The exponential growth of textual data presents substantial challenges in management and analysis, notably due to high storage and processing costs. Text classification, a vital aspect of text mining, provides robust solutions by enabling efficient categorization and organization of text data. These techniques allow individuals, researchers, and businesses to derive meaningful patterns and insights from large volumes of text. This survey paper introduces a comprehensive taxonomy specifically designed for text classification based on research fields. The taxonomy is structured into hierarchical levels: research field-based category, research field-based sub-category, methodology-based technique, methodology sub-technique, and research field applications. We employ a dual evaluation approach: empirical and experimental. Empirically, we assess text classification techniques across four critical criteria. Experimentally, we compare and rank the methodology sub-techniques within the same methodology technique and within the same overall research field sub-category. This structured taxonomy, coupled with thorough evaluations, provides a detailed and nuanced understanding of text classification algorithms and their applications, empowering researchers to make informed decisions based on precise, field-specific insights. © 2024, CC BY-NC-SA.

关键词： Deep learning

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A Federated Learning Framework Based on Spatio-Temporal Agnostic Subsampling (STAS) for Forest Fire Prediction

A Federated Learning Framework Based on Spatio-Temporal Agno...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Abdul Mutakabbir Chung-Horng Lung Samuel A. Ajila Kshirasagar Naik Marzia Zaman Richard Purcell Srinivas Sampalli Thambirajah Ravichandran Department of Systems and Computer Engineering Carleton University Ottawa ON Canada Dept. Electrical and Computer Eng. University of Waterloo Waterloo ON Canada Research and Development Cistel Technology Ottawa ON Canada Faculty of Computer Science Dalhousie University Halifax NS Canada Research and Development Hegyi Geomatics International Inc. Ottawa ON Canada

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Prevention of forest fires increasingly impacted by climate change is essential to maintain ecological balance, preserve natural resources, prevent economic loss, and protect human and animal life. Data for forest fires is available from multiple sources and is huge. Federated learning can be implemented to distribute the computing across multiple edge devices by saving transmission costs, protecting data privacy, and maintaining security with no single point of failure as local models exist across multiple resources in different geographic regions. The proposed framework extends the Spatio-Temporal Agnostic Subsampling (STAS) technique by distributing the data into multiple computation nodes to leverage federated learning. It was found that the models trained using federated learning on weather data gained on average 0.3 in F1 for classifying the occurrence of fire. This study also demonstrates how to optimally choose the sources of data for either predicting the occurrence of fire or the severity of fire.

关键词： Climate change Big Data Federated learning Fires Forests Lightning Deep learning Remote sensing Ecology Environmental monitoring Spatial temporal resolution Sampling methods Predictive models

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