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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Pastrana, M.A. Filho, Jose Oniram De A. Limaverde Oliveira, Luiz Henrique Bautista, Jaider Fortaleza, Eugenio Munoz, Daniel M. Department of Mechanical Engineering Brasília Brazil University of Brasília Department of Electrical Engineering Brasília Brazil University of the Amazonia Faculty of Engineering Systems Undergraduate Program Florencia Colombia

ISBN: (纸本)9798350374575

This paper provides a comprehensive comparative analysis of the performance of four bioinspired algorithms (Differential Evolution, Grasshopper Optimization Algorithm, Moth-flame Optimization, and Particle Swarm Optimization) in designing a flatness-based controller for a ball and beam system simulated in MATLAB/Simulink environment. The assessment involves the tuning of feedback gains utilizing four distinct fitness functions: Integral Square Error, Integral Absolute Error, Integral Time Absolute Error, and an ad-hoc cost function. Hypothesis tests are employed to choose the optimal controllers from each combination for every bioinspired algorithm and a fitness function. Subsequently, a control performance analysis of these controllers for the ball and beam system is conducted, focusing on critical parameters such as overshoot, settling time, and steady-state error. This analysis demonstrates that all the controllers achieve a zero steady-state error. Noteworthy is the flatness-based controller tuned with the bioinspired Grasshopper Optimization Algorithm and utilizing the Integral Time Absolute Error fitness function, which stands out for achieving the fastest response with the lowest overshoot. This particular controller emerges as the most recommended choice for the specified application. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Speech Recognition for Intelligent System in Service Robots: A Review 4

Speech Recognition for Intelligent System in Service Robots:...

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4th International Conference on electrical engineering and Computer Science, ICECOS 2024

作者： Atika, Ratna Dwijayanti, Suci Yudho Suprapto, Bhakti Doctoral Program in Engineering Science Universitas Sriwijaya Department of Electrical Engineering Polytechnic of Sriwijaya Palembang Indonesia Faculty of Engineering Universitas Sriwijaya Department of Electrical Engineering Palembang Indonesia Faculty of Engineering Palembang Universitas Department of Electrical Engineering Sriwijaya Indonesia

ISBN: (纸本)9798350368253

Speech recognition and response system technology in service robot research continues to evolve alongside technical advances and the increasing demand for intelligent automation across industries. The development of machine learning, digital signal processing, and artificial neural networks has brought significant advancements to speech recognition systems. While speech recognition has been implemented in various systems, there is limited discussion on categorizing these systems by examining four aspects: speech recognition applications, datasets used, emotional speech recognition, and automatic speech recognition. In this study, a review of these four aspects is conducted, focusing on the algorithms and methods used, along with their advantages and disadvantages, particularly in the context of implementing them in service robots using the Indonesian language. This study involves a literature review of 100 research papers from the last five years. The review concludes that the use of the transformer method combined with other techniques and Indonesian language datasets is still very limited. Therefore, future research will focus on developing and implementing these methods in humanoid service robots. © 2024 IEEE.

关键词： Intelligent systems

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Texture development and surface reconstruction of BiVO_(4)photoanode via one-pot hydrothermal reaction for enhanced photoelectrochemical water splitting

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Journal of Advanced Ceramics 2025年第3期14卷 133-141页

作者： Sung Won Hwang Yoo Jae Jeong Runfa Tan Indhujasri Saravanan Hyun Soo Han Dong Hoe Kim In Sun Cho Department of Energy Systems Research Ajou UniversitySuwon 16499Republic of Korea Department of Material Science&Engineering Ajou UniversitySuwon 16499Republic of Korea Department of Mechanical Engineering Stanford UniversityStanford 94305USA Department of Material Science&Engineering Korea UniversitySeoul 02841Republic of Korea Materials Science and Engineering Program University of Colorado BoulderBoulder 80303USA

The simultaneous optimization of the bulk and surface characteristics of photoelectrodes is essential to maximize their photoelectrochemical(PEC)*** report a novel one-pot hydrothermal synthesis of textured and surface-reconstructed BiVO_(4)photoanodes(ts-BVO),achieving significant improvements in PEC water *** controlling precursor molarity and ethylene glycol(EG)addition,we developed a stepwise dual reaction(SDR)mechanism,which enables simultaneous bulk texture development and surface *** optimized CoBi/ts-BVO photoanode exhibited a photocurrent density of 4.3 mA∙cm^(−2)at 1.23 V *** hydrogen electrode(RHE)with a high Faradaic efficiency of 98%under one sun *** with nontextured BiVO_(4),the charge transport efficiency increased from 8%to 70%,whereas the surface charge transfer efficiency improved from 9%to 85%.These results underscore the critical role of both bulk and surface engineering in enhancing PEC *** findings offer a streamlined approach for improving the intrinsic properties of photoanodes in solar water splitting.

关键词： BiVO_(4) hydrothermal texture surface reconstruction ethylene glycol(EG) photoelectrochemical water splitting

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CRAFT: Criticality-Aware Fault-Tolerance Enhancement Techniques for Emerging Memories-Based Deep Neural Networks

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and systems 2023年第10期42卷 3289-3300页

作者： Nguyen, Thai-Hoang Imran, Muhammad Choi, Jaehyuk Yang, Joon-Sung Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Electrical Engineering School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad44000 Pakistan Department of Semiconductor Systems Engineering Sungkyunkwan University Suwon16419 Korea Republic of School of Electrical and Electronic Engineering Department of System Semiconductor Engineering Yonsei University Seoul03722 Korea Republic of

Deep neural networks (DNNs) have emerged as the most effective programming paradigm for computer vision and natural language processing applications. With the rapid development of DNNs, efficient hardware architectures for deploying DNN-based applications on edge devices have been extensively studied. Emerging nonvolatile memories (NVMs), with their better scalability, nonvolatility, and good read performance, are found to be promising candidates for deploying DNNs. However, despite the promise, emerging NVMs often suffer from reliability issues, such as stuck-at faults, which decrease the chip yield/memory lifetime and severely impact the accuracy of DNNs. A stuck-at cell can be read but not reprogrammed, thus, stuck-at faults in NVMs may or may not result in errors depending on the data to be stored. By reducing the number of errors caused by stuck-at faults, the reliability of a DNN-based system can be enhanced. This article proposes CRAFT, i.e., criticality-aware fault-tolerance enhancement techniques to enhance the reliability of NVM-based DNNs in the presence of stuck-at faults. A data block remapping technique is used to reduce the impact of stuck-at faults on DNNs accuracy. Additionally, by performing bit-level criticality analysis on various DNNs, the critical-bit positions in network parameters that can significantly impact the accuracy are identified. Based on this analysis, we propose an encoding method which effectively swaps the critical bit positions with that of noncritical bits when more errors (due to stuck-at faults) are present in the critical bits. Experiments of CRAFT architecture with various DNN models indicate that the robustness of a DNN against stuck-at faults can be enhanced by up to 105 times on the CIFAR-10 dataset and up to 29 times on ImageNet dataset with only a minimal amount of storage overhead, i.e., 1.17%. Being orthogonal, CRAFT can be integrated with existing fault-tolerance schemes to further enhance the robustness of DNNs aga

关键词： Fault tolerance

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Recent advances in tip-enhanced Raman spectroscopy probe designs

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Nano Research 2023年第4期16卷 5555-5571页

作者： Da Xu Boqun Liang Yaodong Xu Ming Liu Department of Electrical and Computer Engineering University of California-RiversideRiversideCalifornia 92521USA Materials Science and Engineering program University of California-RiversideRiversideCalifornia 92521USA

Tip-enhanced Raman spectroscopy(TERS)imaging is a super-resolution imaging technique that features the merits of both surface-enhanced Raman spectroscopy(SERS)and scanning probe microscopy(SPM),such as the high chemical sensitivity from the former and the nanoscale spatial resolution from the *** advantages make TERS an essential nanospectroscopic characterization technique for chemical analysis,materials science,bio-sensing,*** probes,the most critical factor determining the TERS imaging quality,are expected to provide a highly confined electromagnetic hotspot with a minimized scattering background for the generation of Raman signals with high spatial *** two decades of development,numerous probe design concepts have been proposed and *** review provides a comprehensive overview of the state-of-the-art TERS probe designs,from the working mechanism to the practical *** start with reviewing the recent development of TERS configurations and the corresponding working mechanisms,including the SPM platforms,optical excitation/collection techniques,and probe preparation *** then review the emerging novel TERS probe designs,including the remote-excitation probes,the waveguide-based nanofocusing probes,the metal-coated nanofocusing probes,the nanowire-assisted selective-coupling probes,and the tapered metal-insulator-metal *** discussion focuses on a few critical aspects,including the surface-plasmon-polariton(SPP)hotspot excitation technique,conversion efficiency,working frequency,and *** the end,we review the latest TERS applications and give a perspective on the future of TERS.

关键词： tip-enhanced Raman spectroscopy plasmonics scanning probe microscopy nanoscale imaging nanophotonics nanofocusing

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Wireless Power Transfer Optimization Using FEM-GA Method 3

Wireless Power Transfer Optimization Using FEM-GA Method

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3rd International Conference on Advanced electrical engineering, ICAEE 2024

作者： Fatima, Bennia Aimad, Boudouda University of Boumerdes Department of Electrical Systems Engineering Boumerdes Algeria

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349351

This paper addresses the challenges associated with designing high-performance wireless power transfer (WPT) systems for various applications. The efficient operation of WPT systems is crucial, but it must meet specific restrictions imposed by the application. This is particularly true for WPT systems used in biomedical implants, sensor applications, and IoT devices, where a small receiving coil is required while maintaining high power transfer efficiency (PTE). The PTE is dependent on several design parameters, such as coil design, coil size, relative geometry, operating frequency, and load. Our paper begins by defining the finite element method and details the parametric-coil modeling in Ansys Maxwell. We then propose the optimization of the wireless power transfer efficiency via the FEM-GA. Furthermore, the suggested WPT coil design method improves the transfer efficiency by a maximum of 74%. Ultimately, we verify the accuracy of our findings by employing finite element simulation with Simplorer. © 2024 IEEE.

关键词： Inductive power transmission

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Revealing Mechanism of Non-Accumulative Disturb and Approach Toward Disturb Suppression in HZO/Si FeFET Memory

Revealing Mechanism of Non-Accumulative Disturb and Approach...

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2024 IEEE Symposium on VLSI Technology and Circuits, VLSI Technology and Circuits 2024

作者： Otomo, M. Toprasertpong, K. Cai, Z. Liu, Z. Takenaka, M. Takagi, S. The University of Tokyo Department of Electrical Engineering and Information Systems Japan

ISBN: (纸本)9798350361469

The mechanism of repeated read/write disturb in Hf0.5Zr0.5O2 (HZO)/Si FeFETs is systematically studied. Disturb in FeFETs, found not to be a simple accumulation of repeated disturbs, is modeled with a combination of two mechanisms: trap dynamics and polarization dynamics. The amount of polarization reversed by disturb is evaluated to separate the two dynamics. We show that the suppression of disturb field in HZO due to de-trapping (trap dynamics model) and the relaxation of partially reversed polarization during the disturb interval (polarization dynamics model) are the two origins of the non-accumulative property of disturb, where each mechanism dominates in different disturb voltage and duration. We also show that the disturb behavior depends on the HZO thickness, and demonstrate a new approach to suppress disturb by applying substrate bias (Vsub) during disturb intervals. © 2024 IEEE.

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Data-Driven Multiple Resonant Filter Design Integrating Notch Filters and Peak Filters in Dual-Stage Actuator Hard Disk Drives

Data-Driven Multiple Resonant Filter Design Integrating Notc...

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2025 IEEE International Conference on Mechatronics, ICM 2025

作者： Mae, Masahiro The University of Tokyo Department of Electrical Engineering and Information Systems Tokyo Japan

ISBN: (纸本)9798331533892

Magnetic-head positioning performance of hard disk drives in data center infrastructures is fundamental to the large storage capacity. The aim of this paper is to develop a feedback controller design method for hard disk drives integrating robust stabilization and disturbance rejection simultaneously. Notch filters for resonant mode stabilization and peak filters for disturbance rejection are designed simultaneously by resonant filters in the same structure. Multiple resonant filters are designed by frequency response data-driven iterative convex optimization for robust stabilization and disturbance rejection at the same time. The disturbance rejection performance improvement with robust stability is validated in a dual-stage actuator hard disk drive benchmark problem. © 2025 IEEE.

关键词： Disturbance rejection

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Transformer Hetero-CiM: Heterogeneous Integration of ReRAM CiM and SRAM CiM for Vision Transformer at Edge Devices 25

Transformer Hetero-CiM: Heterogeneous Integration of ReRAM C...

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30th Asia and South Pacific Design Automation Conference, ASP-DAC 2025

作者： Misawa, Naoko Wang, Tao Matsui, Chihiro Takeuchi, Ken Department of Electrical Engineering and Information Systems The University of Tokyo Tokyo Japan

ISBN: (纸本)9798400706356

This paper proposes design of Transformer Hetero-Computation-in-Memory (CiM) for Vision Transformer (ViT) at edge devices. ViT achieves high inference accuracy using parallel processing. However, ViT is computationally intensive due to a huge number of multiply-accumulate (MAC) operations. Moreover, ViT has the diverse requirements of Read-MAC operation in linear & FC layers and Read/Write-MAC operation in self-attention. Thus, proposed Transformer Hetero-CiM overcomes the issues by heterogeneous integration system of MLC ReRAM CiM, SRAM CiM and digital processors. As a result, proposed Transformer Hetero-CiM achieves 97.9% inference accuracy with reducing 89.1% of array area. © 2025 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Static random access storage

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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif Zohaib Mushtaq Muhammad Irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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