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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Hira Rasheed Peyman Mirtaheri Ali Muhtaroglu Dept. of Machines Electronics & Chemistry Faculty of Technology Art and Design (TKD) Oslo Metropolitan University Oslo Norway Biomedical Engineering MS Program Advanced Health Intelligence and Brain-Inspired Technologies (ADEPT)

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Neuromorphic circuits and systems involving spiking neural networks (SNN) have resulted in disruptive advances in performance/joule for relevant applications. A novel reinforcement learning (RL) digital hardware architecture is presented in this work that achieves energy consumption improvements through three fundamental techniques: The first two techniques comprise reduction in the complexity of the arithmetic unit for the optimization of recurring synapse and neuron cores in the network array, which is inspired by "crude" nature of the building blocks in the biological neurons that are tolerant to inaccuracy and noise. As the third technique, the RL SNN middle (hippocampus) layer is equipped with a simple scratchpad to facilitate temporal hysteresis in synaptic plasticity during the RL processes of long-term potentiation/depression (LTP / LTD). This feature is inspired by the non-temperamental behavior of biological synapses. The intelligent allocation significantly reduces learning time in a given task. Implementation on Intel Cyclone IV FPGA demonstrated significant advantages in cost, power dissipation and execution time, resulting in more than two orders of magnitude benefit in energy consumption for a context-dependent learning task on a 16-node 3-layer RL network presented in the literature.

关键词： Energy consumption Circuits and systems Neurons Reinforcement learning Biology Power dissipation Resource management

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UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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Computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh Ali Wagdy Mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization

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Analog-Based Synapse of Double HfZrO2 Ferroelectric FETs With Homogeneous Phase by Superlattice HfO2-ZrO2 Toward Energy Efficient Accelerator

IEEE Transactions on Materials for Electron Devices

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IEEE Transactions on Materials for Electron Devices 2024年 1卷 11-14页

作者： Z.-F. Lou A. Senapati J.-Y. Lee F.-S. Chang K.-Y. Hsiang Y.-T. Chang C. W. Liu S. Maikap M. H. Lee Program for Semiconductor Devices Materials and Hetero-integration Graduate School of Advanced Technology National Taiwan University Taipei Taiwan Department of Electronic Engineering Chang Gung University Taoyuan Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Institute of Electronics Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

Since the analog-based energy-efficient accelerator for synapses is highly demanded in the artificial intelligence (AI) era, the homogeneous and coherence ferroelectric phase of HfZrO 2 (HZO) by superlattice (SL) growth mode with double layers is proposed in this work. The experimental results demonstrate excellent linear alternating consecutive potentiation and depression conductance (α p /α d = −0.85/0.63) with V RMS = 3 V. In addition, the proposed SL technique for HZOs validates the ferroelectric-based orthorhombic phase (o-phase) 75–79% by geometric phase analysis (GPA) compared to the solid-solution process for 62–64%. The double HZO (D-HZO) structure is employed for diverse coercive field (E C ) distributions to exhibit multistate data storage with 8 identical gap V T . The SL-DHZO has a sufficient ferroelectric domain, which is crucial to achieving the requirements of analog-based energy-efficient accelerators for synapses in computing in-memory generation.

关键词： Superlattices Memory Coherence Depression Energy efficiency Hafnium compounds Artificial intelligence

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High Dielectric Constant of HfO2 technology for Memory Applications

High Dielectric Constant of HfO2 Technology for Memory Appli...

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IEEE Electron Devices technology and Manufacturing Conference (EDTM)

作者： Min-Hung Lee Zhao-Feng Luo Chun-Yu Liao Kuo-Yu Hsiang Jia-Yang Lee Fu-Shen Chang Yii-Tay Chang Cheng-Hong Liu Che-Chi Cheng Program for Semiconductor Devices Materials and Hetero-integration (DMHI) Graduate School of Advanced Technology (GSAT) National Taiwan University Taipei Taiwan Institute Program of Electro-Optical Engineering National Taiwan Normal University Taipei Taiwan Institute of Electronics Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798331504168

ISBN: (纸本)9798331504175

$\text{HfO}_{2}$ with ferroelectricity has been widely investigated for memory and logic applications, including doped by Zr, Si, La, … etc. The superlamination (SL) technique exhibits higher capacitance and dielectric constant as compared to solidsolution (SS). The maximum dielectric constant achieves as high as 46 for HZZ at $[\text{Zr}]=66 \%$ with morphotropic phase boundary (MPB) effect. Ferroelectric-based memory of ferroelectric capacitive memory (FCM) has gained significant attention due to the charge transfer concept, which is adopted with the SL technique. The SL technique exhibits higher capacitance and applicable remnant polarization ( $\mathrm{P}_{\mathrm{r}}$ ) benefits for FCM application to demonstrate a $\mathrm{C}_{\text{HCS}} / \mathrm{C}_{\text{LCS}}$ ratio of 245x. The feasible concept of coupling the MPB SL $\text{Hf}_{1-\mathrm{x}} \text{Zr}_{\mathrm{x}} \mathrm{O}_{2}$ is practicable into emerging memory/synapse.

关键词： Couplings Dielectric constant Zirconium Nonvolatile memory Capacitance Silicon Manufacturing Hafnium compounds Logic Charge transfer

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Deep learning-based denoising for unbiased analysis of morphology and stiffness in amyloid fibrils

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Computers in Biology and Medicine 2025年 184卷 109410-109410页

作者： Park, Jaehee Cheong, Da Yeon Lee, Gyudo Han, Cheol E. Department of Electronics and Information Engineering Korea University Sejong30019 Korea Republic of Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong30019 Korea Republic of Department of Biotechnology and Bioinformatics Korea University Sejong30019 Korea Republic of

Understanding the morphology of amyloid fibrils is crucial for comprehending the aggregation and degradation mechanisms of abnormal proteins implicated in various diseases, such as Alzheimer's disease, Parkinson's disease, type II diabetes, and various forms of amyloidosis. Atomic force microscopy (AFM) stands as the most representative method for studying amyloid fibril morphology. However, obstacles in AFM images, including noise, salt, and amorphous aggregates, often impede accurate sample quantification. In this study, we developed denoising software employing a U-Net deep learning architecture to address this issue. The software efficiently eliminated various impediments that interfere with fibril analysis in noisy AFM images, thereby facilitating precise quantification of amyloid fibrils. We also developed automated fibril analysis technologies using the denoised AFM images, leading to quicker, more precise, and more objective assessments of fibril morphology. Furthermore, we presented a method for fibril stiffness extraction from a modulus image through mask creation based on a denoised height image. Our approach secures time efficiency and precision in analyzing amyloid morphology, and we believe it will significantly advance the currently stagnant research on amyloid-related diseases. © 2024 The Authors

关键词： Neurodegenerative diseases

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Can in-home laboratories foster learning, self-efficacy, and motivation during the COVID-19 pandemic? - A case study in two engineering programs

arXiv

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arXiv 2022年

作者： Ariza, Jonathan Álvarez Program of Technology in Electronics Engineering Faculty Corporación Universitaria Minuto de Dios-UNIMINUTO Bogotá111021 Colombia

The COVID-19 pandemic has represented a challenge for higher education in terms to provide quality education despite the lockdown periods, the transformation of the in-person classes to virtual classes, and the demotivation and anxiety that are experimented by the students. Because the basis of engineering is the experimentation through hands-on activities and learning by doing, the lockdown periods and the temporary suspension of the in-person classes and laboratories have meant a problem for educators that try to teach and motivate the students despite the situation. In this context, this study presents an educational methodology based on Problem-Based Learning (PBL) and in-home laboratories in engineering. The methodology was carried out in two phases during 2020, in the academic programs of Industrial Engineering and technology in electronics with (n=44) students. The in-home laboratories were sent to the students as part of "kits" with the devices needed in each subject. Besides, due to the difficulties in monitoring the learning process, the students made videos and blogs as a strategy to reinforce their learning and evidence the progress in the courses. The outcomes of the methodology show mainly the following points: (1) An improvement of the academic performance and learning of the students in the courses. (2) A positive influence of the usage of in-home laboratories in motivation, self-efficacy, and reduction of anxiety. (3) Positive correlations between the usage of in-home laboratories, the blogs and videos, and the teacher's feedback for learning, motivation, and self-efficacy. Thus, these results evidence that other alternatives that gather the cognitive and affective learning domains can emerge from engineering to deal with the educational problems produced by the crisis periods. © 2022, CC BY-NC-ND.

关键词： Students

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ICU Bed Capacity Analysis with Transformer-Based Length of Stay Prediction and Erlang Loss Formula

ICU Bed Capacity Analysis with Transformer-Based Length of S...

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International Conference on Electrical Engineering/electronics, Computer, Telecommunications and Information technology, ECTI-CON

作者： Sahawat Tanutsiriteeradet Wuttipong Kumwiaisak Jisue Youn Kumwilaisak Ratchapon Thammacharo Kanya Kumwilaisak Phornlert Chatkaew Electronics and Telecommunication Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand Gifted Math Program Triam Udom Suksa School Bangkok Thailand Gifted Math Program Mahidol Wittayanusorn School Nakorn Pathom Thailand Department of Anesthesiology King Chulalongkorn Memorial Hospital Bangkok Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

This paper introduces a new method for predicting the length of stay in the ICU using a transformer-based architecture. The predicted results are used for analyzing ICU bed capacity with the Erlang loss formula. The prediction architecture comprises two transformer layers, one global average pooling layer, and two fully connected layers. The proposed model classifies the length of stay into four classes depending on how long patients are admitted to the ICU based on patient data. In addition, the model estimates the length of stay in days of each patient. We then utilize the estimated length of stay to analyze ICU resources with the Erlang loss model. Given ICU blocking probabilities, the required ICU bed numbers are estimated with Erlang-B. Patient data from the MIMIC-III dataset, including various vital signs and patient health conditions, and the actual statistics from the Pediatric ICU at King Chulalongkorn Memorial Hospital are deployed to evaluate the proposed method. Experimental results show that the transformed-based architecture surpasses previous works regarding length of stay prediction accuracy. In addition, our analysis of ICU resources provides close results to those from the actual statistics from the Pediatric ICU at King Chulalongkorn Memorial Hospital.

关键词： Analytical models Accuracy Hospitals Computational modeling MIMICs Predictive models Probability

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Corrugated Quad-Ridged Dual-Polarized Wideband Horn Antenna For mm-Wave Applications

Corrugated Quad-Ridged Dual-Polarized Wideband Horn Antenna ...

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National Conference on Radio Science (NSRC)

作者： Mohamed N. Salem Mohamed I. Ahmed Amr H. Hussein Department of Electronics and communication Engineering Institute of Aviation Engineering and Technology (IAET) Giza Egypt Microstrip department Electronics Research Institute El-Nuzha Cairo Electronics and Communication Program Faculty of Engineering Egypt University of informatics New Administrative Capital Knowledge City Egypt Electronics and Electrical Communications Engineering Dept. Faculty of Engineering Tanta University Tanta Egypt Electronics and Electrical Communications Engineering Department Faculty of Engineering Horus University Egypt New Damietta Egypt

This paper showcases the development of a wideband Dual-polarized horn antenna for mm-wave applications. It can be used for reflector feeding, imaging, satellite communication and power transmission due to its enhanced parameters. The working bandwidth is 10 GHz from 4 GHz to 14 GHz (VSWR $\lt1.9)$. This design is formed of three parts: 1) the waveguide is designed to support the entire bandwidth and to improve the impedance matching 2) four ridges to enable Dual-polarized antenna 3) the flared part is corrugated to enhance the side lobe level (SLL). The insertion between the two ports is less than -25 dB for most frequencies. The SLL is less than -25 dB for the low frequencies and -30 dB for the high frequencies. The co- and cross-pol radiation pattern simulation shows that the cross-pol magnitude is 20-30 dB less than the co-pol magnitude. These results have been proved using the CST MWS and Ansys HFSS software.

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2D Polynomial Regression Modeling for Predictive Analysis of Glucose Concentration in NP-Model Fractal Microwave Sensor Using Frequency and Transmission Coefficient Disparities

2D Polynomial Regression Modeling for Predictive Analysis of...

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International Electrical Engineering Congress (iEECON)

作者： Nutyada Nantapanich Pisit Mahatthanajatuphat Norakamon Wongsin Wilaiporn Lee Department of Electronics and Telecommunication Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathum Thani Thailand Regular Program in Mathematics-Science Yothinburana School Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

The article introduces a two-dimensional polynomial regression model for the predictive analysis of glucose concentration in a fractal microwave sensor NP model, utilizing frequency and transmission coefficient differences to examine their correlation with glucose concentration levels. The sensor employed in this investigation is fabricated on an economical FR-4 substrate to minimize costs. The sensor structure is developed with the fractal structure reduction method established by the NP model to operate at a frequency of roughly 2.97 GHz. The CST Studio software is utilized to analyze the findings from the simulation of the suggested sensor structure. Furthermore, the proposed sensor is integrated into a test apparatus comprising a sensor platform and a liquid tube constructed from PPA material. The liquid under examination is a glucose and water mixture at varying concentrations. It was analyzed using a VNA instrument to evaluate its frequency response and the magnitude of the alteration in the transmission coefficient. The values are utilized to create a two-dimensional polynomial regression model. The experiments demonstrated that the proposed sensor model possesses an Adjusted R² value of 0.99499 and an average error of approximately 3.57% for glucose concentration analysis throughout the range of 5% to 30%, with sensitivities of 0.00879 dB/% for insertion loss and 0.092 MHz/% for frequency variation, facilitating accurate glucose concentration prediction analysis.

关键词： Analytical models Adaptation models Correlation Liquids Predictive models Microwave sensors Polynomials Fractals Glucose Predictive analytics

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Van der Waals device integration beyond the limits of van der Waals forces using adhesive matrix transfer

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Nature electronics 2024年第1期7卷 17-28页

作者： Satterthwaite, Peter F. Zhu, Weikun Jastrzebska-Perfect, Patricia Tang, Melbourne Spector, Sarah O. Gao, Hongze Kitadai, Hikari Lu, Ang-Yu Tan, Qishuo Tang, Shin-Yi Chueh, Yu-Lun Kuo, Chia-Nung Lue, Chin Shan Kong, Jing Ling, Xi Niroui, Farnaz Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA United States Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA United States Department of Physics Massachusetts Institute of Technology CambridgeMA United States Department of Chemistry Boston University BostonMA United States Department of Materials Science and Engineering National Tsing Hua University Hsinchu Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu Taiwan Department of Physics National Cheng Kung University Tainan Taiwan Taiwan Consortium of Emergent Crystalline Materials National Science and Technology Council Taipei Taiwan Program on Key Materials Academy of Innovative Semiconductor and Sustainable Manufacturing National Cheng Kung University Tainan Taiwan Division of Materials Science and Engineering Boston University BostonMA United States The Photonics Center Boston University BostonMA United States

Pristine van der Waals (vdW) heterostructures formed between two-dimensional (2D) and other materials can be used to create optical and electronic devices. However, the weak vdW forces alone do not allow direct physical stacking of arbitrary layers. As a result, vdW heterostructure fabrication typically requires solvents, sacrificial layers or high temperatures, which can introduce damage and contaminants. Here, we show that adhesive matrix transfer can eliminate these limitations and can provide vdW integration beyond the limits of vdW forces. In the approach, a hybrid high- and low-adhesion surface is used to decouple the forces driving the transfer from the vdW forces defining the heterostructure of interest. We show that the technique can be used to achieve direct vdW integration of diverse 2D materials (MoS2, WSe2, PtS2 and GaS) with dielectrics (SiO2 and Al2O3), which is conventionally forbidden but critical for active devices and scalable, aligned heterostructure formation. The approach also allows single-step 2D material-to-device integration, which we illustrate by fabricating arrays of monolayer MoS2 transistors. As any exposure to solvents or polymers is avoided, the interfaces and surfaces remain pristine. Thus, intrinsic 2D material properties can be probed without the influence of processing steps. The materials can be further engineered through surface treatments and used to fabricate unconventional device form factors. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

关键词： Van der Waals forces

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