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Wearable technology to Assist the Patients Infected with Novel Coronavirus (COVID-19)

SN computer Science 2020年第6期1卷 1-9页

作者： Islam, Md. Milon Mahmud, Saifuddin Muhammad, L.J. Islam, Md. Rabiul Nooruddin, Sheikh Ayon, Safial Islam Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna 9203 Bangladesh Department of Computer Science Kent State University Kent OH United States Department of Mathematics and Computer Science Faculty of Science Federal University of Kashere P.M.B. 0182 Gombe Nigeria Department of Electrical and Electronic Engineering Bangladesh Army University of Engineering and Technology Natore 6431 Bangladesh Department of Computer Science and Engineering Green University of Bangladesh Dhaka 1207 Bangladesh

Wearable technology plays a significant role in our daily life as well as in the healthcare industry. The recent coronavirus pandemic has taken the world’s healthcare systems by surprise. Although trials of possible vaccines are underway, it would take a long time before the vaccines are permitted for public use. Most of the government efforts are currently geared towards preventing the spread of the coronavirus and predicting probable hot zones. The essential and healthcare workers are the most vulnerable towards coronavirus infections due to their required proximity to potential coronavirus patients. Wearable technology can potentially assist in these regards by providing real-time remote monitoring, symptoms prediction, contact tracing, etc. The goal of this paper is to discuss the different existing wearable monitoring devices (respiration rate, heart rate, temperature, and oxygen saturation) and respiratory support systems (ventilators, CPAP devices, and oxygen therapy) which are frequently used to assist the coronavirus affected people. The devices are described based on the services they provide, their working procedures as well as comparative analysis of their merits and demerits with cost. A comparative discussion with probable future trends is also drawn to select the best technology for COVID-19 infected patients. It is envisaged that wearable technology is only capable of providing initial treatment that can reduce the spread of this pandemic. © 2020, Springer Nature Singapore Pte Ltd.

关键词： COVID-19 Novel coronavirus Respiratory support Symptoms monitoring Wearable technology

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Adaptive Contrast for Image Regression in computer-Aided Disease Assessment

arXiv

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arXiv 2021年

作者： Dai, Weihang Li, Xiaomeng Chiu, Wan Hang Keith Kuo, Michael D. Cheng, Kwang-Ting The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong The Department of Diagnostic Radiology LKS Faculty of Medicine The Hong Kong University Hong Kong The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Shenzhen Research Institute Hong Kong The Department of Computer Science and Engineering The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Image regression tasks for medical applications, such as bone mineral density (BMD) estimation and left-ventricular ejection fraction (LVEF) prediction, play an important role in computer-aided disease assessment. Most deep regression methods train the neural network with a single regression loss function like MSE or L1 loss. In this paper, we propose the first contrastive learning framework for deep image regression, namely AdaCon, which consists of a feature learning branch via a novel adaptive-margin contrastive loss and a regression prediction branch. Our method incorporates label distance relationships as part of the learned feature representations, which allows for better performance in downstream regression tasks. Moreover, it can be used as a plug-and-play module to improve performance of existing regression methods. We demonstrate the effectiveness of AdaCon on two medical image regression tasks, i.e., bone mineral density estimation from X-ray images and left-ventricular ejection fraction prediction from echocardiogram videos. AdaCon leads to relative improvements of 3.3% and 5.9% in MAE over state-of-the-art BMD estimation and LVEF prediction methods, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Forecasting

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Low-Profile All-Metal Dual-Band Dual-Polarized Shared-Aperture Phased Arrays for UAV Applications

引用

IEEE Internet of Things Journal 2025年

作者： Chen, Zhenzhong Feng, Wenhao You, Yang Yu, Yingrui Guan, Dongfang Sun, Liying Hu, Yang Lu, Yunlong Ningbo University Faculty of Electrical Engineering and Computer Sciences Zhejiang Ningbo315211 China Ministry of Education School of Electronic and Optical Engineering Nanjing210094 China National University of Defense Technology College of Electronic Science and Technology Changsha410073 China

A low-profile, all-metal, dual-band, dual-polarized shared-aperture phased array (SAPA) is proposed for UAV radar systems. The phased array element consists of a semi-open stepped radiating slot loaded with a pair of metal ridges to achieve the desired small aperture, wide beam, and low cross-polarization properties. Compared with traditional all-metal phased array element, the antenna profile can be reduced while not compromising radiation characteristics. Based on this element, a single-polarized phased array and two dual-polarized SAPAs with different frequency ratio have been developed. By adjusting the spacing between the dual ridges of the elements, the frequency ratio of the dual-band dual-polarized SAPA can be flexibly controlled ranging from 1:1 to 3:1. To validate this concept, a prototype of the SAPA operating in the S-band and C-band was fabricated and measured. The measured results demonstrate a beam scanning range of ± 60° in the dual-band range with a gain drop of within 5.5 dB. The proposed SAPA represents a promise candidate for UAV radar systems that facilitate communication within the Internet of Vehicles. © 2014 IEEE.

关键词： Antenna phased arrays

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New Strategies for Computational Electromagnetic Simulation of Antennas and Related Circuits in the Context of 5G and Beyond

New Strategies for Computational Electromagnetic Simulation ...

引用

IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Raj Mittra Abdelkhalek Nasri Prashant Chaudhary Vikrant Kaim Ravi Kumar Arya Junwei Dong Electrical and Computer Engineering University of Central Florida Orlando FL USA Electrical and Computer Engineering Department Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia Department of Electronic Science University of Delhi New Delhi India School of Computational and Integrative Sciences Jawaharlal Nehru University Xiangshan Laboratory Zhongshan Institute of Changchun University of Science and Technology China

In the current work, we discuss the status of the development of the Computational Electromagnetics (CEM) codes that are available in the market and can help solve recent problems of designing millimeter-wave antennas.

关键词： Codes Millimeter wave circuits 5G mobile communication Computational modeling Computational electromagnetics Microwave circuits Microwave antenna arrays

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Chatbots and Customer Service: Enhancing Marketing Management with AI Technologies

Chatbots and Customer Service: Enhancing Marketing Managemen...

引用

Pervasive Computational Technologies (ICPCT), International Conference on

作者： Rajchandar K Somanchi Hari Krishna Showkat Khalil Wani Supriya Pathak Amit Kumar Jain C M Naveen Kumar School of CS & AI SR University Warangal Telangana India Department of Business Management Vignana Bharathi Institute of Technology Telangana State India Department of Business Administration College of Administrative and Financial Sciences Saudi Electronic University Riyadh Saudi Arabia Faculty of Management and Commerce Oriental University Indore Madhya Pradesh Department of Electrical & Electronics Engineering Poornima University Jaipur Rajasthan India Department of Computer Science & Business Systems Malnad College of Engineering Hassan Karnataka India

ISBN: (数字)9798331508685

ISBN: (纸本)9798331519476

By increasing engagement, expediting client contacts, and boosting satisfaction through AI-driven solutions, chatbot integration in customer service has revolutionised marketing management. With an emphasis on how model assessment techniques—such as accuracy, precision, recall, and F1 score—can be applied to enhance chatbot efficacy in customer service scenarios, this paper investigates the role of machine learning models in optimising chatbot performance. In order to appropriately meet a variety of consumer demands, this research offers perspectives into the selection, training, and evaluation of chatbot models by analysing a range of AI technologies, such as natural language processing (NLP) and predictive analytics. The influence of chatbots on customer loyalty and retention is highlighted in this article, which also explores the benefits and limitations of utilising AI in real-time consumer interactions. According to research, well-considered ML models can produce more precise and sympathetic answers, which enhances brand perception and opens up new channels for CRM in marketing plans.

关键词： Industries Training Support vector machines Ethics Customer services Companies Chatbots Marketing management Artificial intelligence Business

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MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability

引用

Genomics, Proteomics & Bioinformatics 2020年第1期18卷 65-71页

作者： Peng Jia Xiaofei Yang Li Guo Bowen Liu Jiadong Lin Hao Liang Jianyong Sun Chengsheng Zhang Kai Ye School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China MOE Key Laboratory for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Leiden Institute of Advanced Computer Science Leiden UniversityLeiden 2311 ZENetherlands School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’an 710049China Precision Medicine Center the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China Jackson Laboratory for Genomic Medicine FarmingtonCT 06032USA Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China

Microsatellite instability(MSI)is a key biomarker for cancer therapy and *** experimental assays are laborious and time-consuming,and next-generation sequencingbased computational methods do not work on leukemia samples,paraffin-embedded samples,or patient-derived xenografts/organoids,due to the requirement of matched normal ***,we developed MSIsensor-pro,an open-source single sample MSI scoring method for research and clinical ***-pro introduces a multinomial distribution model to quantify polymerase slippages for each tumor sample and a discriminative site selection method to enable MSI detection without matched normal *** demonstrate that MSIsensor-pro is an ultrafast,accurate,and robust MSI calling *** samples with various sequencing depths and tumor purities,MSIsensor-pro significantly outperformed the current leading methods in both accuracy and computational ***-pro is available at https://***/xjtu-omics/msisensor-pro and free for non-commercial use,while a commercial license is provided upon request.

关键词： Microsatellite Polymerase slippage Multinomial distribution Microsatellite instability Tumor

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Domain Generalization for Face Anti-spoofing via Content-aware Composite Prompt engineering

arXiv

引用

arXiv 2025年

作者： Guo, Jiabao Liu, Ajian Diao, Yunfeng Zhang, Jin Ma, Hui Zhao, Bo Hong, Richang Wang, Meng School of Computer Science Hefei University of Technology China Beijing100190 China School of Electronic information Engineering Taiyuan University of Technology China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China School of Cyber Science and Engineering Wuhan University Wuhan China

The challenge of Domain Generalization (DG) in Face Anti-Spoofing (FAS) is the significant interference of domain-specific signals on subtle spoofing clues. Recently, some CLIP-based algorithms have been developed to alleviate this interference by adjusting the weights of visual classifiers. However, our analysis of this class-wise prompt engineering suffers from two shortcomings for DG FAS: (1) The categories of facial categories, such as real or spoof, have no semantics for the CLIP model, making it difficult to learn accurate category descriptions. (2) A single form of prompt cannot portray the various types of spoofing. In this work, instead of class-wise prompts, we propose a novel Content-aware Composite Prompt engineering (CCPE) that generates instance-wise composite prompts, including both fixed template and learnable prompts. Specifically, our CCPE constructs content-aware prompts from two branches: (1) Inherent content prompt explicitly benefits from abundant transferred knowledge from the instruction-based Large Language Model (LLM). (2) Learnable content prompts implicitly extract the most informative visual content via Q-Former. Moreover, we design a Cross-Modal Guidance Module (CGM) that dynamically adjusts unimodal features for fusion to achieve better generalized FAS. Finally, our CCPE has been validated for its effectiveness in multiple cross-domain experiments and achieves state-of-the-art (SOTA) results. Copyright © 2025, The Authors. All rights reserved.

关键词： engineering education

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BERT-Deep CNN: State-of-the-Art for Sentiment Analysis of COVID-19 Tweets

arXiv

引用

arXiv 2022年

作者： Joloudari, Javad Hassannataj Hussain, Sadiq Nematollahi, Mohammad Ali Bagheri, Rouhollah Fazl, Fatemeh Alizadehsani, Roohallah Lashgari, Reza Talukder, Ashis Department of Computer Engineering Faculty of Engineering University of Birjand Birjand*** Iran Dibrugarh University Assam786004 India Department of Computer Sciences Fasa University Fasa Iran Department of Management Faculty of Economics and Administrative Sciences Ferdowsi University of Mashhad Iran Department of Electronic Engineering Faculty of Electrical and Computer Engineering University of Birjand Birjand Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC Australia Institute of Medical Science and Technology Shahid Beheshti University Tehran Iran Statistics Discipline Khulna University Khulna9208 Bangladesh

The free flow of information has been accelerated by the rapid development of social media technology. There has been a significant social and psychological impact on the population due to the outbreak of Coronavirus disease (COVID-19). The COVID-19 pandemic is one of the current events being discussed on social media platforms. In order to safeguard societies from this pandemic, studying people's emotions on social media is crucial. As a result of their particular characteristics, sentiment analysis of texts like tweets remains challenging. Sentiment analysis is a powerful text analysis tool. It automatically detects and analyzes opinions and emotions from unstructured data. Texts from a wide range of sources are examined by a sentiment analysis tool, which extracts meaning from them, including emails, surveys, reviews, social media posts, and web articles. To evaluate sentiments, natural language processing (NLP) and machine learning techniques are used, which assign weights to entities, topics, themes, and categories in sentences or phrases. Machine learning tools learn how to detect sentiment without human intervention by examining examples of emotions in text. In a pandemic situation, analyzing social media texts to uncover sentimental trends can be very helpful in gaining a better understanding of society's needs and predicting future trends. We intend to study society's perception of the COVID-19 pandemic through social media using state-of-the-art BERT and Deep CNN models. The superiority of BERT models over other deep models in sentiment analysis is evident and can be concluded from the comparison of the various research studies mentioned in this article. © 2022, CC BY-SA.

关键词： COVID-19

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Bi-level expansion planning of power system considering wind farms based on economic and technical objectives of transmission system operator

引用

Heliyon 2024年第19期10卷 e38468页

作者： Chen, Ran Basem, Ali Shami, Hayder Oleiwi Alfalahi, Saad T.Y. Al-Rubaye, Ameer H. Ouyang, Min Zhang, Jinju Amini, Shiva School of Electronic Science and Engineering Hunan University of Information Technology Changsha 410151 China Faculty of Engineering Warith Al-Anbiyaa University Karbala 56001 Iraq Department of Accounting Al-Amarah University College Maysan Iraq College of Administration and Economics Department of Economics University of Misan Iraq Department of Computer Engineering Techniques Madenat Alelem University College Baghdad Iraq Department of Petroleum Engineering Al-Amarah University College Maysan Iraq Wuling Power Corporation Ltd Changsha 410004 China Department of Electrical and Computer Engineering University of Kurdistan Kurdistan Sanandaj Iran

Planning for the expansion of generation and transmission infrastructure, with a focus on integrating wind farms is presented in this study according to the goals of economic efficiency, operational performance, security, and reliability of the transmission system operator. The approach incorporates a bi-level optimization framework, with the upper level outlining the formulation of power system expansion planning to reduce construction and operational costs while adhering to the investment budget limits. In the lower-level model, which economic reliable-secure functioning is formulated for the transmission network. The objective function of the problem aims to minimize operational costs, energy losses, and anticipated energy not supplied, and the voltage security index. The constraints of this problem include AC optimal power flow model, security, and reliability limits. Scheme extracts a convex-linear model for the formulation using the conventional linearization technique. Pareto optimization driven by the aggregation of weighted functions results in a single-objective framework for the lower-level problem, and the Karush-Kuhn-Tucker technique presents a single-level model for the scheme. The approach utilizes stochastic optimization has been adopted to model load, wind farms, and network equipment availability uncertainties. Finally, the study cases yielded numerical findings that showcase the efficacy of the proposed scheme in achieving the desired economic, operational, security, and reliability status within the transmission network. This is particularly true in situations where there is appropriate generation and transmission expansion. © 2024 The Authors

关键词： Bi-level multi-objective optimization Economic reliable-secure operation Expansion planning Stochastic optimization Wind farms

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Optimisation-based alignment of wideband integrated superconducting spectrometers for sub-mm astronomy

arXiv

引用

arXiv 2024年

作者： Moerman, A. Karatsu, K. Yates, S.J.C. Huiting, R. Steenvoorde, F. Dabironezare, S.O. Takekoshi, T. Baselmans, J.J.A. Brandl, B.R. Endo, A. Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands SRON-Netherlands Institute for Space Research Niels Bohrweg 4 Leiden2333 CA Netherlands SRON-Netherlands Institute for Space Research Landleven 12 Groningen9747 AD Netherlands DEMO: Electronic and Mechanical Support Division Delft University of Technology Mekelweg 4 Delft2628CD Netherlands Kitami Institute of Technology 165 Koen-cho Kitami Hokkaido090-8507 Japan Leiden Observatory Leiden University PO Box 9513 Leiden2300 RA Netherlands Faculty of Aerospace Engineering Delft University of Technology Kluyverweg 1 Delft2629 HS Netherlands

Context. Integrated superconducting spectrometers (ISSs) for wideband sub-mm astronomy utilise quasi-optical systems for coupling radiation from the telescope to the instrument. Misalignment in these systems is detrimental to the system performance. The common method of using an optical laser to align the quasi-optical components requires accurate alignment of the laser to the sub-mm beam coming from the instrument, which is not always guaranteed to a sufficient accuracy. Aims. To develop an alignment strategy for wideband ISSs directly utilising the sub-mm beam of the wideband ISS. The strategy should be applicable in both telescope and laboratory environments. Moreover, the strategy should deliver similar quality of the alignment across the spectral range of the wideband ISS. Methods. We measure misalignment in a quasi-optical system operating at sub-mm wavelengths using a novel phase and amplitude measurement scheme, capable of simultaneously measuring the complex beam patterns of a direct-detecting ISS across a harmonic range of frequencies. The direct detection nature of the MKID detectors in our device-under-test, DESHIMA 2.0, necessitates the use of this measurement scheme. Using geometrical optics, the measured misalignment, a mechanical hexapod, and an optimisation algorithm, we follow a numerical approach to optimise the positioning of corrective optics with respect to a given cost function. Laboratory measurements of the complex beam patterns are taken across a harmonic range between 205 and 391 GHz and simulated through a model of the ASTE telescope in order to assess the performance of the optimisation at the ASTE telescope. Results. Laboratory measurements show that the optimised optical setup corrects for tilts and offsets of the sub-mm beam. Moreover, we find that the simulated telescope aperture efficiency is increased across the frequency range of the ISS after the optimisation. © 2024, CC BY.

关键词： Alignment

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