Synchronization and Channel Estimation Design for Multi-Stream MIMO System in Sub-Terahertz Channel Model by Chung-Lun Tu, Chen-Yuan Tseng, Wei-Che Lee, Kang-Lun Chiu, Pei-Yun Tsai, Shyh-Jye Jou

“…This meets the IEEE Std. 802.15.3d standard of <inline-formula> <tex-math notation="LaTeX">$10^{-12}$ </tex-math></inline-formula> at SNRs of 19.6 dB and 25.6 dB for these modulation schemes after error correction. …”
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A Fourfold Bi-Filter and Permuted Bi-Quad-Wrapper Feature Selection Method for Finding Optimal Moments of Multi-Trajectory Transient Records in Transient Analysis by Seyed Alireza Bashiri Mosavi, Omid Khalaf Beigi

“…Generally, wrapper stages include <inline-formula> <tex-math notation="LaTeX">${ }_{TWSVM}^{SVM} \textrm {IWSS}_{RBF/\,POL}^{RBF/\,DTW\,} $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${ }_{TWSVM}^{SVM} \textrm {IWSSr}_{RBF/\,POL}^{RBF/\,DTW\,}$ </tex-math></inline-formula> in a 24-way permutation. …”
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A Hybrid Retrieval Method for an &#x03A9;-Class Bianisotropic Metamaterial Using Scattering Parameter Method by Gokhan Ozturk, Ugur Cem Hasar, Yunus Kaya, Huseyin Korkmaz, Ivaylo Stoyanov

“…In this study, a hybrid retrieval method is proposed to retrieve all terms in the electric and magnetic tensors (along with coupling tensors) of <inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula>-class bianisotropic metamaterial (MM) slabs using scattering (S-) parameters of both normal incidence TE2 mode and oblique incidence TM2 and TE modes. …”
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SRAM and Mixed-Signal Logic With Noise Immunity in 3-nm Nano-Sheet Technology by Rajiv V. Joshi, J. Frougier, Alberto Cestero, Crystal Castellanos, Sudipto Chakraborty, Carl Radens, M. Silvestre, S. Lucarini, I. Ahsan, E. Leobandung

“…Functionality is shown down to a cell supply of 0.45 V with an estimated margin/speed of 6 GHz for SRAM cells (high density&#x2014;<inline-formula> <tex-math notation="LaTeX">$0.026~\mu $ </tex-math></inline-formula>m², and high current&#x2014;<inline-formula> <tex-math notation="LaTeX">$0.032~\mu $ </tex-math></inline-formula>m²).…”
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A Bore-Integrated Patch Antenna Array for Whole-Body Excitation in Ultra-High-Field Magnetic Resonance Imaging by Svetlana S. Egorova, Nikolai A. Lisachenko, Egor I. Kretov, Yang Gao, Xiaotong Zhang, Stanislav B. Glybovski, Georgiy A. Solomakha

“…The human body&#x2019;s ultra-high field magnetic resonance imaging suffers from the inhomogeneity of the radio frequency magnetic field <inline-formula> <tex-math notation="LaTeX">$B_{1}^{+}$ </tex-math></inline-formula> and the high-peak levels of SAR created in body tissues during transmission. …”
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CGDINet: A Deep Learning-Based Salient Object Detection Algorithm by Chengyu Hu, Jianxin Guo, Hanfei Xie, Qing Zhu, Baoxi Yuan, Yujie Gao, Xiangyang Ma, Jialu Chen, Juan Tian

“…The results show that CGDINet outperforms other mainstream significance object detection models in evaluation metrics such as <inline-formula> <tex-math notation="LaTeX">${\mathrm {maxF}}_{\mathrm {\beta }}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\mathrm {S}_{\mathrm {\alpha }}$ </tex-math></inline-formula>, and MAE, with almost no increase in computational cost (FLOPs) and parameters. …”
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Enhanced SVPWM Techniques for Six-Phase Inverters: Mitigation of Current Harmonics and Common Mode Voltage by Kotb B. Tawfiq, Hatem Zeineldin, Ahmed Al-Durra, Ehab F. El-Saadany

“…The proposed method optimally selects switching states with minimal and&#x002F;or zero CMV and ensures balanced distribution in the <inline-formula><tex-math notation="LaTeX">$x - y$</tex-math></inline-formula> subspace, resulting in null <inline-formula><tex-math notation="LaTeX">$x - y$</tex-math></inline-formula> voltage and current components. …”
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CFO-CR: Carrier Frequency Offset Methodology for High-Rate Common Randomness Generation by Prashanth Kumar Herooru Sheshagiri, Martin Reisslein, Juan A. Cabrera, Frank H. P. Fitzek

“…For generating 2048 bits of CR, other state-of-the-art approaches either require more channel observations (<inline-formula> <tex-math notation="LaTeX">$\ge 2048$ </tex-math></inline-formula>) or incur a higher reconciliation cost (<inline-formula> <tex-math notation="LaTeX">$\ge 450$ </tex-math></inline-formula> bytes).…”
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A Wearable System for Experimental Knee Pain During Real-World Locomotion: Habituation and Motor Adaptation by Jesse M. Charlton, Liam H. Foulger, Calvin Kuo, Jean-Sebastien Blouin

“…A linear model fit the data well for intensities &#x003E;1/10, though a piecewise linear (Adj R<inline-formula> <tex-math notation="LaTeX">$^{{2}} =0.874$ </tex-math></inline-formula>) or exponential model (Adj R<inline-formula> <tex-math notation="LaTeX">$^{{2}} =0.869$ </tex-math></inline-formula>) was required to fit the perception data across the stimulus intensity range (0-5/10). …”
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An Initial Validation of the NASA TROPICS Pathfinder Microwave Radiometer Observations by Amelia Gagnon, Samantha N. Hasler, Juliana Chew, William J. Blackwell, R. Vincent Leslie, Michael DiLiberto, Kerri Cahoy

“…To minimize errors due to radiative transfer uncertainties, we compare TROPICS Pathfinder L1B data from October 2021 with simulated brightness temperature values from the CRTM for observations that are filtered for points near-nadir, over-ocean, free of clouds, and within latitudes from 40<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> N to 40<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> S. …”
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Ultrasonic Testing of Railroad Rails: Cold Temperature Effects and Considerations by Aqeel T. Fadhil, Glenn Washer, Anish Poudel, Kalpana Yadav, Survesh Shrestha

“…The tests were performed in an ultrasonic immersion tank integrated with a heat exchanger and chiller bath to obtain the targeted test temperatures ranging from <inline-formula> <tex-math notation="LaTeX">$- 50~^{\circ }$ </tex-math></inline-formula>C to <inline-formula> <tex-math notation="LaTeX">${+} 20~^{\circ }$ </tex-math></inline-formula>C. …”
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Fully CMOS Boost Converter Operating at 2.65 GHz for Photovoltaic Energy Harvesting by Pedro Mendonca Dos Santos, Ricardo Alexandre Marques Lameirinhas, Catarina P. Correia V. Bernardo, Joao Paulo Neto Torres, Antonio Serralheiro, Rafael Vieira, Nuno Lourenco

“…The system delivers 1.2 V for a 10 k<inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> load, with an output power of the order of <inline-formula> <tex-math notation="LaTeX">$144~\mu $ </tex-math></inline-formula>W. …”
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Deploying the Qline System for a QKD Metropolitan Network on the Berlin OpenQKD Testbed by Matheus Sena, Georg Harder, Ronny Doring, Ralf-Peter Braun, Michaela Ritter, Oliver Holschke, Marc Kaplan, Marc Geitz

“…In this study, we not only observed relatively low QBER (<inline-formula><tex-math notation="LaTeX">$&lt; $</tex-math></inline-formula> 5.5&#x0025;) but also a rather stable key rate between nodes in the Qline system over approximately 130 hours (<inline-formula><tex-math notation="LaTeX">$\approx$</tex-math></inline-formula> 5.4 days) for a lab-based back-to-back setup. …”
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Deep Joint Demosaicking and Super-Resolution for Spectral Filter Array Images by Abdelhamid N. Fsian, Jean-Baptiste Thomas, Jon Y. Hardeberg, Pierre Gouton

“…Moreover, for joint demosaicking and super resolution our model averages 35.26 (dB) and 26.29 (dB), respectively for <inline-formula> <tex-math notation="LaTeX">$\times 2$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\times 4$ </tex-math></inline-formula> upscale, outperforming state-of-the-art sequential approach.The codes and datasets are available at <uri>https://github.com/HamidFsian/DRDmSR</uri>.…”
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Study of Highly Stable Nitrogen-Doped a-InGaSnO Thin-Film Transistors by Wenyang Zhang, Li Lu, Chenfei Li, Weijie Jiang, Wenzhao Wang, Xingqiang Liu, Ablat Abliz, Da Wan

“…Compared with undoped a-IGTO TFTs, a-IGTO TFTs with 6 min N plasma treatment exhibit superior bias stress stability and a threshold voltages (<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {th}}$ </tex-math></inline-formula>) closer to 0 V with almost no decline in mobility. …”
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Adaptive Modification in Agonist Common Drive After Combined Blood Flow Restriction and Neuromuscular Electrical Stimulation by Yi-Ching Chen, Chia-Chan Wu, Yeng-Ting Lin, Yueh Chen, Ing-Shiou Hwang

“…The results showed a significant decrease in MVC after training (<inline-formula> <tex-math notation="LaTeX">$\text {p}\lt 0.001$ </tex-math></inline-formula>). …”
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Amplitude Modulation Depth Coding Method for SSVEP-Based Brain&#x2013;Computer Interfaces by Ruxue Li, Zhenyu Wang, Xi Zhao, Guiying Xu, Honglin Hu, Ting Zhou, Tianheng Xu

“…The results show that the proposed paradigm obtains an average classification accuracy of <inline-formula> <tex-math notation="LaTeX">$81.7~\pm ~12.6$ </tex-math></inline-formula>% with an average information transfer rate (ITR) of <inline-formula> <tex-math notation="LaTeX">$45.4~\pm ~11.5$ </tex-math></inline-formula> bits/min. …”
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An Ultrasound-Based Non-Invasive Blood Pressure Estimation Method Based on Optimal Vascular Wall Tracking Position by Liyuan Liu, Xingguang Geng, Fei Yao, Yitao Zhang, Haiying Zhang, Yunfeng Wang, Zhaoying Zheng

“…The overall mean deviation for systolic blood pressure was <inline-formula> <tex-math notation="LaTeX">$2.2~\pm ~2.1$ </tex-math></inline-formula> mmHg, and for diastolic blood pressure, it was <inline-formula> <tex-math notation="LaTeX">$2.1~\pm ~2.2$ </tex-math></inline-formula> mmHg. …”
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Comparison of Deep-Learning-Based Segmentation Models: Using Top View Person Images by Imran Ahmed, Misbah Ahmad, Fakhri Alam Khan, Muhammad Asif

“…The experimental results reveal the effectiveness and performance of segmentation models by achieving <inline-formula> <tex-math notation="LaTeX">$IoU$ </tex-math></inline-formula> of 83&#x0025;, 84&#x0025;, and 86&#x0025; and <inline-formula> <tex-math notation="LaTeX">$mIoU$ </tex-math></inline-formula> of 80&#x0025; 82&#x0025; and 84&#x0025; for FCN, U-Net, and DeepLabv3 respectively. …”
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Concatenated Vertical Channel Modeling and Performance Analysis for HAP-Based Optical Networks by Neha Tiwari, Swades De, Dharmaraja Selvamuthu

“…For HAP-based optical networks facing weak turbulence, the newly developed expressions provide an accuracy of about 2 dB for a BER of <inline-formula><tex-math notation="LaTeX">$10^{-4}$</tex-math></inline-formula> as compared to the existing competitive models. …”
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