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5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2023

作者： Raheem, Afnan Ayad Raheem Tureli, Didem Kivanc İstanbul Okan University Advanced Electronics and Communication Technology Program Turkey

ISBN: (纸本)9798350337525

This paper addresses the issues of intelligent reflective surface (IRS) based MIMO design system for millimeter wave (mmw) applications. The proposed IRS has a resonating frequency around of 26GHz with about 2GHz bandwidth. Beam reflection control is addressed through numerical and analytical simulations. The results show that the obtained electromagnetic beam of the proposed IRS design can be steered effectively from -26o to + 26o to suite the modern wireless communications systems at mmw. The proposed IRS layer consists of 64×64 elements;that is designed using electromagnetic theory. Finally, the results show maximum channel capacity (CC) which is enhanced rapidly with respect to array size increase. © 2023 IEEE.

关键词： Millimeter waves

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Digital Color Output Conformity to ISO12647-7 Standards (GRACoL 2013 [CGATS21-2-CRPC6]) With the Use of Statistical Process Control (SPC)

Journal of Technology, Management, and Applied Engineering

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Journal of technology, Management, and Applied Engineering 2023年第4期39卷 1-18页

作者： Dharavath, Haji Naik Program Coordinator for the BS degree in Graphics Technology Department of Computer Electronics & Graphics Technology Central Connecticut State University New BritainCT06050 United States

The purpose of this applied research was to apply the statistical process control (SPC) to determine the digital color output conformity to ISO12647-7 standards in a color managed digital printing workflow (CMDPW) over a period of 100 days (N = 100). The quality of digital color printing is determined by these influential factors: screening method applied, type of printing process, calibration method, device profile, ink (dry toner or liquid toner), printer resolution, and the substrate (paper). For this research, only the color printing attribute overall average color deviation (ACD;ΔE(2000)) was analyzed to examine the CMDPW process consistency in a day-to-day digital printing operation. Printed colors from the random sample size (n= 80) were measured against the General Requirement for the Applications in the Commercial Offset Lithography (GRACoL 2013) standards to derive the colorimetric/ densitometric values. Reference colorimetric values used in the analysis were the threshold deviations (acceptable color deviations) as outlined in the ISO12647-7 standards (GRACoL 2013). A control chart analysis was applied for further determining the process (CMDPW) ACD variation. The data collected were run through multiple software applications (Microsoft Excel/SPSS/Minitab) to apply various statistical methods. Analyzed data from the experiment revealed that the printed colorimetric values were in match (aligned) with the GRACoL 2013 (reference/target) standards. Since the color values were in control throughout the process, this enabled the CMDPW to produce consistent acceptable color deviation (average printed ΔE(2000) = 2.978). (The acceptable threshold color deviation is ΔE(2000) ≤ 3.00.) © 2023 The Author(s). This is an open access article published under a Creative Commons Attribution 4.0 International License (https://***/licenses/by/4.0).

关键词： Colorimetry

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Designing a Detection Device for Absorber Usage on Anesthetic Machine 4

Designing a Detection Device for Absorber Usage on Anestheti...

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4th International Conference on Electronic and Electrical Engineering and Intelligent System, ICE3IS 2024

作者： Fajrin, Hanifah Rahmi Syafira, Annisa Rilam Wibowo, Susilo Ari Universitas Muhammadiyah Yogyakarta Department of Medical Electronics Technology Vocational Program Yogyakarta Indonesia Islam Public Hospital Klaten Indonesia

ISBN: (纸本)9798350378368

In an anesthetic machine, the absorber holds an essential role by absorbing carbon dioxide gas during anesthesia treatment. The absorber quality is highly affected by the duration of anesthetic machine usage and can be observed from the color. However, assessment of color is ineffective as the users or medical staff will change the absorbers once the original color white shifts for 50-80% into a purplish-blue. The color change parameter cannot be used as a proper quality evaluation as the absorber can restore to its original color if it is not used for some time, but the quality is still reduced. The subjective measurement by color change concerns the medical staff and the users. Therefore, the objective of this study is to design a detection device to measure the quality of absorber and CO2 absorption according to the capacity in part per million (PPM). The detection device was used to evaluate three absorbers to investigate the feasibility. The first and second absorbers showed an average value of 1286 PPM and 1196 PPM, respectively, using oxygen volume of 1-10 L. Both values were under the accepted limit of 1500 PPM and are considered GOOD quality. On the other hand, the third absorber had a concentration of 1671 parts per million (PPM), indicating a classification of POOR quality according to the limit as mentioned in the Indonesian Ministry of Health Regulation Number 1077 about the Guidelines for Indoor Air Health which ranged from 350 to 2000 PPM. © 2024 IEEE.

关键词： Anesthesiology

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Measurement of renal blood flow in a rat model using diffuse correlation spectroscopy

Measurement of renal blood flow in a rat model using diffuse...

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Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics

作者： Nakabayashi, Mikie Ono, Yumie Electrical Engineering Program Graduate School of Science and Technology Meiji University Kanagawa Japan Department of Electronics and Bioinformatics School of Science and Technology Meiji University Kanagawa Japan

ISBN: (纸本)9781957171340

关键词： Detectors Laser sources Lasers Near infrared Photon counting Spectroscopy

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Interfacial-Layer-Free Ge0.95Si0.05Nanosheet FeFETs

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IEEE Transactions on Electron Devices 2024年第3期71卷 1758-1763页

作者： Hsieh, Wan-Hsuan Chen, Yu-Rui Liu, Yi-Chun Zhao, Zefu Lee, Jia-Yang Tu, Chien-Te Huang, Bo-Wei Wang, Jer-Fu Lee, M.H. Liu, C.W. Graduate Institute of Electronics Engineering National Taiwan University Taipei10617 Taiwan Institute and Undergraduate Program of Electro-Optical Engineering Graduate School of Advance Technology National Taiwan University Taipei10617 Taiwan National Taiwan University Graduate School of Advance Technology Taipei10617 Taiwan Graduate Institute of Electronics Engineering Graduate Institute of Photonics and Optoelectronics Graduate School of Advanced Technology National Taiwan University Department of Electrical Engineering Taipei10617 Taiwan

The substantial memory window (MW) of 1.8 V is achieved by utilizing stacked two nanosheet (NS) gate-all-around (GAA) Ge0.95 Si0.05 ferroelectric field-effect transistors (FeFETs), employing a low write voltage of 2 V. The channel phosphorus concentration 1E18 cm-3 is used to erase the absence of interfacial layer (IL) can reduce the operation voltage. An isotropic wet etching process is employed for channel release. The stacked two NSs offer the advantages of reducing cell-to-cell variation and doubling the read current. Additionally, the stability of data storage is demonstrated with the data retention of >1E4 s, linearly extrapolated to a span of 10 years, and exhibiting high endurance >1E11 cycles. The thermal budget is as low as 400 °C. © 1963-2012 IEEE.

关键词： III-V semiconductors

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Mini-YOLOX: A Lightweight Network for Real-Time Embedded Applications 66

Mini-YOLOX: A Lightweight Network for Real-Time Embedded App...

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2023 IEEE 66th International Midwest Symposium on Circuits and Systems, MWSCAS 2023

作者： El-Zeiny, Ahmed N. Hassan, Adham Mostafa, Hassan Khalil, Ahmed H. Cairo University Electronics and Communications Engineering Department Egypt University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza12578 Egypt

ISBN: (纸本)9798350302103

In this paper, we present an efficient real-time object detector designed for embedded system applications. Although increased memory and power consumption pose significant challenges, our network adopts techniques to overcome them. Depthwise and pointwise separable convolutions are used across the backbone, neck, and head of the network to reduce the number of parameters. To compensate for accuracy loss, we employ several techniques including starting with a larger baseline, using depthwise separable convolution mixed with blueprint separable convolution in the backbone, replacing the SiLU activation function with the Mish activation function, and switching from Adam to SGD optimization algorithms. These techniques help to achieve a state-of-the-art object detection network called Mini-YOLOX, which optimizes YOLOX-S from the YOLOX series and reaches only ∽57% of its parameter size and ∽52% of its floating-point operations with better accuracy. Mini-YOLOX achieves impressive results with only 5.08M parameters and 13.95 GFLOPs, resulting in a 40.9 AP score in just 5.71 ms. © 2023 IEEE.

关键词： convolutional neural network (CNN) embedded applications Real-time object detector YOLOX

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Multi-Panel Extra-Large Scale MIMO Based Joint Activity Detection and Channel Estimation for Near-Field Massive IoT Access

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China Communications 2023年第5期20卷 232-243页

作者： Zhen Gao Hanlin Xiu Yikun Mei Anwen Liao Malong Ke Chun Hu Mohamed-Slim Alouini School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of TechnologyBeijing 100081China The Advanced Technology Research Institute of Beijing Institute of Technology Jinan 250307China Yangtze Delta Region Academy of Beijing Institute of Technology(Jiaxing) Jiaxing 314019China Electrical Engineering Program Division of Physical Sciences and EngineeringKing Abdullah University of Science and TechnologyThuwal 23955Saudi Arabia

The extra-large scale multiple-input multiple-output(XL-MIMO)for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access ***,the extremely large antenna array aperture arouses the channel near-field effect,resulting in the deteriorated data rate and other challenges in the practice communication ***,multi-panel MIMO technology has attracted extensive attention due to its flexible configuration,low hardware cost,and wider *** combining the XL-MIMO and multi-panel array structure,we construct multi-panel XL-MIMO and apply it to massive Internet of Things(IoT)***,we model the multi-panel XL-MIMO-based near-field channels for massive IoT access scenarios,where the electromagnetic waves corresponding to different panels have different angles of arrival/departure(AoAs/AoDs).Then,by exploiting the sparsity of the near-field massive IoT access channels,we formulate a compressed sensing based joint active user detection(AUD)and channel estimation(CE)problem which is solved by AMP-EM-MMV *** simulation results exhibit the superiority of the AMP-EM-MMV based joint AUD and CE scheme over the baseline algorithms.

关键词： extra-large scale MIMO massive IoT access active user detection channel estimation multipanel approximate message passing

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Phase-transition-free rivets for layered oxide potassium cathodes

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Nano Research 2024年第11期17卷 9671-9678页

作者： Jie Chen Apparao M. Rao Caitian Gao Jiang Zhou Limei Cha Xiaoming Yuan Bingan Lu School of Physics and Electronics Hunan University Changsha 410082 China Department of Physics and Astronomy Clemson Nanomaterials Institute Clemson University Clemson SC USA School of Materials Science and Engineering Central South University Changsha 410083 China Materials Science and Engineering program Guangdong Technion-Israel Institute of Technology Shantou 515063 China Materials Science and Engineering program Technion-Israel Institute of Technology Haifa 32000 Israel MATEC Key Lab Guangdong Technion-Israel Institute of Technology Shantou 515063 China Hunan Key Laboratory of Nanophotonics and Devices School of Physics Central South University Changsha 410078 China

As a cathode material for potassium-ion batteries (PIBs), manganese-based layered oxides have attracted widespread attention due to their low cost, ease of synthesis, and high performance. However, the Jahn-Teller effect caused by Mn3+ and the irreversible phase transformation of the structure leads to poor cycle stability, limiting the development of layered oxides in PIBs. Herein, we demonstrate the use of phase-transition-free CaTiO_(3) as rivets in K_(0.5)Mn_(0.9)Ti_(0.1)O_(2) by a simple solid-state method. As verified by the in situ X-ray diffraction, the CaTiO_(3) rivets effectively prevent the slippage of the transition metal layer during charge and discharge, inhibiting structural degradation. As a result, the obtained K_(0.5)Mn_(0.9)Ti_(0.1)O_(2)-0.02CaTiO_(3) shows excellent cycling stability and rate performance, with high capacities of 119.3 and 70.1 mAh·g^(-1) at 20 and 1000 mA·g^(-1), respectively. At 200 mA·g^(-1), the capacity retention remains 94.7% after more than 300 cycles. This work represents a new avenue for designing and optimizing layered cathode materials for PIBs and other batteries.

关键词： potassium cathodes layered oxide phase-transition-free perovskite rivets

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A Comparative Study of DeepLabCut and Other Open-Source Pupillometry Data Analysis Algorithms – Which to Choose?

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Machine Graphics and Vision 2024年第2期33卷 77-90页

作者： Badkul, Amitesh Mishra, Sonakshi Kommajosyula, Srinivasa P. Department of Electrical & Electronics Engineering Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Department of Pharmacy Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Ph.D. Program in Computer Science The Graduate Center The City University of New York New YorkNY United States

Pupillometry measures pupil size, and several open-source algorithms are available to analyse pupillometry data. However, only a few studies compared these algorithms’ accuracy and computational resources. This study aims to compare the accuracy of computer vision-based algorithms (Swirski, Starburst, PuRe, ElSe, ExCuSe algorithms) and the machine learning algorithm, DeepLabCut, to the double-blinded human examiners (gold-standard). Training of DeepLabCut with different architectures and a variable number of markers (2-9 markers) was done on an open-source dataset. The duration of training was statistically longer for the ResNet152 model compared to the MobileNet model. The pupil diameters in computer vision-based software such as PuRe, Starburst, and Swirski were statistically different from human measurements. MobileNet 2 and 3 marker models were the closest to the human measurements. In conclusion, this work highlights the efficiency of lower marker models based on MobileNet architecture in DeepLabCut, which consumes fewer computational resources and is more accurate. © 2024 Institute of Information technology, Warsaw University of Life Sciences - SGGW. All rights reserved.

关键词： Adversarial machine learning

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Classification of Human Tactile Perception Using Vibration Data 23

Classification of Human Tactile Perception Using Vibration D...

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23rd International Conference on Cyberworlds, CW 2024

作者： Lee, Hyung-Tak Bak, Keungyonh Chun, Sungwoo Hwang, Han-Jeong Korea University Dept. Electronics and Information Engineering Sejong Korea Republic of Korea University Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Sejong Korea Republic of

ISBN: (纸本)9798331527174

To enhance the sense of reality in the VR environment, it is essential to incorporate not only visual and hearing but also tactile feedback. Previous studies related to tactile sensation have only focused on object classification to identify the object in contact with the tactile sensor. When people encounter a new object, they can use tactile perception information, such as roughness, to understand the object's attributes and functions. Therefore, for tactile research to be applicable in real-life scenarios, tactile perception classification is essential not only for classifying an object but also for recognizing its attributes and functions. This study aims to investigate the possibility of predicting roughness, one of the important human tactile perceptions, using deep learning models. We created 63 tactile samples, measured the vibration data of each sample using an acceleration sensor, and investigated how humans perceive the roughness of the tactile samples with five different levels. Object classification was performed using five deep learning models, among which the Shallow ConvNet achieved the highest performance, confirming its suitability as the most appropriate model for analyzing vibration data. Using the Shallow ConvNet, we attained a high accuracy of 98.6 ±5.6% for the identification of five levels of roughness, demonstrating that different levels of tactile perception information can be discriminated with high performance. © 2024 IEEE.

关键词： Deep learning Human tactile perception Roughness Vibration data Virtual reality

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