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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Abu Eid, Aws Ismail Pethkar, Rajendra Huda, Bintul Patil, Jaykar Bhaskar Gatla, Ranjith Kumar Kumbhar, Ramchandra Arab Open University Faculty of Computing Studies Amman Jordan Jaywant College of Engineering and Polytechnic Department of Mechanical Engineering Karad India Sharda University Department of Computer Science & Technology Srinagar India Jaywant Institute of Management Karad India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineering Hyderabad India Department of Radio-Diagnosis Karad India

ISBN: (纸本)9798350360707

Nowadays robotics is mostly used in the world. There are many industries which used robots for reducing time and to have high precision of work. The use of artificial intelligence is now increasing which helps in automations and processing of machines. Thus, the focus of study is to find the different applications of automation of robotics (i.e. robotic process automation) in the field of healthcare and its impact on the employment of medical field. Four major categories can be used to group AI applications in healthcare: expressive, analytical, prognostic, and prescriptive. The only way to close the skills gap in the healthcare industry is to increase the application of artificial intelligence. Hospitals are developing mental commit robots to treat their patients. Through physical contact, these robots can have an impact on humans' psyche, physiology, and social interactions. Thus, in coming time most of the healthcare industry will be with the robots which will reduces the human interventions with the patients through one of the host servers. © 2024 IEEE.

关键词： Medical robotics

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Shots and variance on noisy quantum circuits

arXiv

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arXiv 2025年

作者： Seksaria, Manav Prabhakar, Anil Centre for Quantum Information Communication and Computing Indian Institute of Technology Madras Chennai India Department of Electrical Engineering Indian Institute of Technology Madras Chennai India

We present a method for estimating the number of shots required for some desired variance in the results of a quantum circuit. First, we establish a baseline for a single qubit characterization of individual noise sources separately. We then extend the method to multi-qubit problems and test our method on two case *** will proceed to estimate the number of shots required for a desired variance in the result or, equivalently estimate the variance at a known number of *** will show we're able to estimate variance accurately to within a factor of 2. Following these, we also provide a closed-form expression for variance at a given number of shots. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

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Precise beam-forming from integrated optics for trapped-ion addressing

Precise beam-forming from integrated optics for trapped-ion ...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Beck, Gillenhaal J. Mehta, Karan K. Home, Jonathan P. Institute for Quantum Electronics ETH Zurich Otto-Stern-Weg 1 Zurich8093 Switzerland Electrical and Computer Engineering Cornell University 315 Phillips Hall IthacaNY14853 United States

We present a design methodology for waveguide-to-free-space grating outcouplers enabling flexible emission angles and unprecedented precision in transverse focusing. We demonstrate its capabilities with micron-scale f... 详细信息

ISBN: (纸本)9781957171258

关键词： Beamforming

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DCSK-based Waveform Design for Self-sustainable RIS-aided Noncoherent SWIPT

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IEEE Transactions on Communications 2025年

作者： Mukherjee, Priyadarshi Psomas, Constantinos Krikidis, Ioannis Indian Statistical Institute Advanced Computing and Microelectronics Unit Kolkata India University of Cyprus Department of Electrical and Computer Engineering Nicosia1678 Cyprus

This paper investigates the problem of transmit waveform design in the context of a chaotic signal-based self-sustainable reconfigurable intelligent surface (RIS)-aided system for simultaneous wireless information and power transfer (SWIPT). Specifically, we propose a differential chaos shift keying (DCSK)-based RIS-aided point-to-point set-up, where the RIS is partitioned into two non-overlapping surfaces. The elements of the first sub-surface perform energy harvesting (EH), which in turn, provide the required power to the other sub-surface operating in the information transfer (IT) mode. In this framework, by considering a generalized frequency-selective Nakagami-m fading scenario as well as the nonlinearities of the EH process, we derive closed-form analytical expressions for both the bit error rate (BER) at the receiver and the harvested power at the RIS. Our analysis demonstrates, that both these performance metrics depend on the parameters of the wireless channel, the transmit waveform design, and the number of reflecting elements at the RIS, which switch between the IT and EH modes, depending on the application requirements. Moreover, we show that, having more reflecting elements in the IT mode is not always beneficial and also, for a given acceptable BER, we derive a lower bound on the number of RIS elements that need to be operated in the EH mode. Furthermore, for a fixed RIS configuration, we investigate a trade-off between the achievable BER and the harvested power at the RIS and accordingly, we propose appropriate transmit waveform designs. Finally, our numerical results illustrate the importance of our intelligent DCSK-based waveform design on the considered framework. © 1972-2012 IEEE.

关键词： Energy harvesting

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Passive on-chip isolators based on the thin-film lithium niobate platform

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Chinese Physics B 2025年第3期34卷 408-413页

作者： Jiacheng Liu Gongyu Xia Qilin Hong Pingyu Zhu Kai-Kai Zhang Keyu Xia Ping Xu Shiqiao Qin Zhihong Zhu College of Advanced Interdisciplinary Studies&Hunan Provincial Key Laboratory of Novel Nano Optoelectronic Information Materials and Devices National University of Defense TechnologyChangsha 410073China Institute for Quantum Information and State Key Laboratory of High-Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China College of Engineering and Applied Sciences National Laboratory of Solid State Microstructuresand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China

Optical isolators,the photonic analogs of electronic diodes,are essential for ensuring the unidirectional flow of light in optical systems,thereby mitigating the destabilizing effects of back ***-film lithium niobate(TFLN),hailed as“the silicon of photonics,”has emerged as a pivotal material in the realm of chip-scale nonlinear optics,propelling the demand for compact optical *** report a breakthrough in the development of a fully passive,integrated optical isolator on the TFLN platform,leveraging the Kerr effect to achieve an impressive 10.3 dB of isolation with a minimal insertion loss of 1.87 *** theoretical simulations have demonstrated that our design,when applied to a microring resonator with a Q factor of 5×10^(6),can achieve 20 dB of isolation with an input power of merely 8 *** advancement underscores the immense potential of lithium niobate-based Kerr-effect isolators in propelling the integration and application of high-performance on-chip lasers,heralding a new era in integrated photonics.

关键词： thin-film lithium niobate Kerr effect optical isolator

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Enhancing Agricultural IoT with Predictive Analytics and Reinforcement Learning Models 2

Enhancing Agricultural IoT with Predictive Analytics and Rei...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Krishnan, R. Santhana Raj, J. Relin Francis Christopher, V. Bibin Nandini, N. Muthu, A. Essaki Puvanadevi, C. SCAD College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Ssveetha School of Engineering Saveetha Institute of Medical and Technical Science Department of Electronics and Communication Engineering Chennai India Faculty of Engineering and Technology SRM Institute of Science and Technology Department of Computing Technologies School of Computing College of Engineering and Technology Kattankulathur Chennai India RajaRajeswari College of Engineering Department of Electrical and Electronics Engineering Bangalore India SCAD College of Engineering and Technology Department of Computer Science and Engineering Cheranmahadevi India Adhiyamaan College of Engineering Department of Information Technology Hosur India

ISBN: (纸本)9798350317558

This research explores the augmentation of Agricultural Internet of Things (IoT) systems through the integration of advanced predictive analytics and reinforcement learning models. A novel algorithm, termed "CropQL,"is proposed to optimize crop yield prediction and resource allocation in precision agriculture. CropQL amalgamates the strengths of the CropNet IoT model with Q-Learning for reinforcement learning and Random Forest for predictive analytics. Simulation analyses are conducted to evaluate the performance of CropQL against established algorithms, employing diverse metrics such as precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC-ROC). The proposed CropQL algorithm exhibits superior predictive accuracy, demonstrating a significant enhancement in crop yield forecasting when compared to baseline algorithms. Precision and recall metrics reveal the algorithm's efficacy in minimizing false positives and negatives, ensuring precision agriculture systems make informed decisions. F1 score indicates the balanced optimization of precision and recall, reinforcing the algorithm's robustness. AUC-ROC analysis further corroborates the superior discriminative power of CropQL in distinguishing between positive and negative instances. In comparison to existing algorithms, including AgriSensNet, PrecisionCropNet, and IoTFarmGuard, CropQL consistently outperforms in predictive accuracy and resource optimization. The simulation results underscore the efficacy of the proposed algorithm in enhancing the efficiency of agricultural IoT systems, providing a promising avenue for sustainable precision farming. © 2024 IEEE.

关键词： Agricultural IoT CropQL Precision Agriculture Predictive Analytics Reinforcement Learning Sustainable Farming

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Guest Editorial Enabling Technologies and Systems for Industry 5.0: From Foundation Models to Foundation Intelligence

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2024年第11期54卷 6496-6499页

作者： Tang, Ying Tian, Yonglin Lin, Yilun Lv, Chen Fanti, Maria Pia Rowan University Department of Electrical and Computer Engineering GlassboroNJ08028 United States Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Shanghai AI Laboratory Urban Computing Laboratory Shanghai200232 China Nanyang Technological University School of Mechanical and Aerospace Engineering Jurong West639798 Singapore Polytechnic University of Bari Department of Electrical and Information Engineering Bari70126 Italy

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MenUnet: An End-to-End 3D Neural Network for Meningioma Segmentation from Multiparametric MRI 1

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Challenge on Brain Tumor Segmentation, BraTS 2023, International Challenge on Cross-Modality Domain Adaptation for Medical Image Segmentation, CrossMoDA 2023, held in conjunction with the Medical Image computing for computer Assisted Intervention Conference, MICCAI 2023

作者： Lin, Hui Cheng, Xi Chen, Ziru Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Department of Civil Materials and Environmental Engineering University of Illinois Chicago ChicagoIL60607 United States College of Computing Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (数字)9783031761638

ISBN: (纸本)9783031761621

Meningioma is one of the most common and serious intracranial tumors. Multiparametric MRI (mpMRI) has been shown to provide significant information for precise tumor diagnosis. Manual segmentation of the meningioma is both lengthy and challenging. Automatic segmentation with high accuracy is of high interest. However, the state-of-art studies investigating automatic meningioma segmentation are unsatisfying in accuracy. An end-to-end network, MenUnet, is proposed to directly segment the whole 3D volume of MRIs. It captures the correlation among the surrounding slices in the 3D volume for accurate meningioma segmentation. It is validated in the public Brain Tumor Segmentation (BraTS) 2023 Meningioma Challenge, achieving the 5th in the validation phase. The dice scores of Enhancing Tumor (ET), Tumor core (TC), and whole tumor (WT), respectively, are 82.62%, 82.21%, and 83.00%. In the testing phase, the dice scores of Enhancing Tumor (ET), Tumor core (TC), and whole tumor (WT), respectively, are 83.01%, 82.01%, and 76.05%. The results show that MenUnet has the potential to assist the clinical practice of meningioma diagnosis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep neural networks

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AutoQ 2.0: From Verification of quantum Circuits to Verification of quantum Programs 31th

AutoQ 2.0: From Verification of Quantum Circuits to Verific...

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31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2025, which was held as part of the International Joint Conferences on Theory and Practice of Software, ETAPS 2025

作者： Chen, Yu-Fang Chung, Kai-Min Hsieh, Min-Hsiu Huang, Wei-Jia Lengál, Ondřej Lin, Jyun-Ao Tsai, Wei-Lun Institute of Information Science Academia Sinica Taipei Taiwan Hon Hai Quantum Computing Research Center Taipei Taiwan Faculty of Information Technology Brno University of Technology Brno Czech Republic Innovation Frontier Institute of Research for Science and Technology & Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9783031906596

We present a verifier of quantum programs called AutoQ 2.0. quantum programs extend quantum circuits (the domain of AutoQ 1.0) by classical control flow constructs, which enable users to describe advanced quantum algorithms in a formal and precise manner. The extension is highly non-trivial, as we needed to tackle both theoretical challenges (such as the treatment of measurement, the normalization problem, and lifting techniques for verification of classical programs with loops to the quantum world), and engineering issues (such as extending the input format with a support for specifying loop invariants). We have successfully used AutoQ 2.0 to verify two types of advanced quantum programs that cannot be expressed using only quantum circuits: the repeat-until-success (RUS) algorithm and the weak-measurement-based version of Grover’s search algorithm. AutoQ 2.0 can efficiently verify all our benchmarks: all RUS algorithms were verified instantly and, for the weak-measurement-based version of Grover’s search, we were able to handle the case of 100 qubits in ∼20 minutes. © The Author(s) 2025.

关键词： Qubits

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A Simple and Tighter Derivation of Achievability for Classical-quantum Channel Coding

A Simple and Tighter Derivation of Achievability for Classic...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Cheng, Hao-Chung Department of Electrical Engineering Graduate Institute of Communication Engineering National Taiwan University Taipei106 Taiwan Department of Mathematics National Taiwan University Taiwan Center for Quantum Science and Engineering National Taiwan University Taiwan Quantum Computing Center New Taipei City236 Taiwan Physics Division National Center for Theoretical Sciences Taipei10617 Taiwan

ISBN: (纸本)9781665475549

In this paper, we propose an elegant and simple one-shot achievability proof for classical-quantum channel coding. The established one-shot bound admits a closed-form expression as in the celebrated Holevo-Helstrom Theorem. Namely, the average error probability of sending M messages through a classical-quantum channel is upper bounded by the minimum error of distinguishing the joint state between channel input and output against (M-1)-many products of its marginals. Our result provides the tightest achievable one-shot capacity for classical-quantum channel coding, and it improves the third-order coding rate in the asymptotic scenario. Moreover, the derived bound directly leads to asymptotic achievability results in the large deviation, small deviation, and moderate deviation regimes in a unified *** full version of the manuscript can be found at [arXiv:2208.02132] [1]. © 2023 IEEE.

关键词： Channel coding

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