Subjects -> ENGINEERING (Total: 2688 journals)
    - CHEMICAL ENGINEERING (229 journals)
    - CIVIL ENGINEERING (237 journals)
    - ELECTRICAL ENGINEERING (176 journals)
    - ENGINEERING (1325 journals)
    - ENGINEERING MECHANICS AND MATERIALS (452 journals)
    - HYDRAULIC ENGINEERING (56 journals)
    - INDUSTRIAL ENGINEERING (98 journals)
    - MECHANICAL ENGINEERING (115 journals)

ENGINEERING (1325 journals)            First | 1 2 3 4 5 6 7 | Last

Showing 201 - 400 of 1205 Journals sorted alphabetically
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 8)
Control Engineering Practice     Hybrid Journal   (Followers: 46)
Control Theory and Informatics     Open Access   (Followers: 9)
Corrosion Science     Hybrid Journal   (Followers: 23)
CT&F - Ciencia, Tecnología y Futuro     Open Access  
CTheory     Open Access  
Current Applied Physics     Full-text available via subscription   (Followers: 4)
Current Applied Science and Technology     Open Access  
Current Journal of Applied Science and Technology     Open Access  
Current Research in Nanotechnology     Open Access   (Followers: 23)
Current Science     Open Access   (Followers: 115)
Dams and Reservoirs     Hybrid Journal   (Followers: 3)
Data-Centric Engineering     Open Access  
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 1)
Design Journal : An International Journal for All Aspects of Design     Hybrid Journal   (Followers: 33)
Designed Monomers and Polymers     Open Access   (Followers: 1)
Designs     Open Access  
Designs, Codes and Cryptography     Hybrid Journal   (Followers: 7)
Development Engineering     Open Access   (Followers: 3)
Diálogos Interdisciplinares     Open Access  
Diffusion Foundations     Full-text available via subscription   (Followers: 4)
Digital Signal Processing     Hybrid Journal   (Followers: 34)
Dinamisia : Jurnal Pengabdian Kepada Masyarakat     Open Access  
Discrete Optimization     Full-text available via subscription   (Followers: 7)
Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi     Open Access  
Düzce Üniversitesi Bilim ve Teknoloji Dergisi / Duzce University Journal of Science & Technology     Open Access  
Dyes and Pigments     Hybrid Journal   (Followers: 1)
Dynamical Systems : An International Journal     Hybrid Journal  
E&S Engineering and Science     Open Access  
e-Phaïstos : Revue d’histoire des techniques / Journal of the history of technology     Open Access  
EAU Heritage Journal Science and Technology     Open Access   (Followers: 1)
El-Cezeri Fen ve Mühendislik Dergisi / El-Cezeri Journal of Science and Engineering     Open Access  
Electromagnetics     Hybrid Journal   (Followers: 13)
Electrophoresis     Hybrid Journal   (Followers: 18)
Elkawnie : Journal of Islamic Science and Technology     Open Access  
Emerging Science Journal     Open Access   (Followers: 1)
Emitter : International Journal of Engineering Technology     Open Access  
ENERGETIKA. Proceedings of CIS higher education institutions and power engineering associations     Open Access  
Energies     Open Access   (Followers: 4)
Energy and Power Engineering     Open Access   (Followers: 23)
Energy Conversion and Management     Hybrid Journal   (Followers: 15)
Energy Conversion and Management : X     Open Access   (Followers: 1)
Energy Engineering     Full-text available via subscription   (Followers: 8)
Energy for Sustainable Development     Hybrid Journal   (Followers: 13)
Energy Science & Engineering     Open Access   (Followers: 6)
Energy Science and Technology     Open Access   (Followers: 10)
Energy Sources, Part A: Recovery, Utilization, and Environmental Effects     Hybrid Journal   (Followers: 1)
Energy Sources, Part B: Economics, Planning, and Policy     Hybrid Journal   (Followers: 7)
Energy Systems     Hybrid Journal   (Followers: 11)
EnergyChem     Hybrid Journal   (Followers: 1)
Engenharia de Interesse Social     Open Access  
ENGEVISTA     Open Access  
Engineer : Journal of the Institution of Engineers, Sri Lanka     Open Access  
Engineering     Open Access   (Followers: 1)
Engineering & Technology     Hybrid Journal   (Followers: 22)
Engineering Analysis with Boundary Elements     Hybrid Journal   (Followers: 2)
Engineering Computations     Hybrid Journal   (Followers: 3)
Engineering Economics     Open Access   (Followers: 4)
Engineering Economist, The     Hybrid Journal   (Followers: 4)
Engineering Failure Analysis     Hybrid Journal   (Followers: 68)
Engineering Geology     Hybrid Journal   (Followers: 16)
Engineering Journal of Research and Development     Open Access  
Engineering Management in Production and Services     Open Access  
Engineering Management Research     Open Access   (Followers: 6)
Engineering Optimization     Hybrid Journal   (Followers: 19)
Engineering Reports     Open Access  
Engineering Science and Technology, an International Journal     Open Access   (Followers: 1)
Engineering Sciences     Open Access  
Engineering Studies     Hybrid Journal   (Followers: 1)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Engineering, Technology & Applied Science Research     Open Access   (Followers: 1)
ENP Engineering Science Journal     Open Access  
Entramado     Open Access  
Entre Ciencia e Ingeniería     Open Access  
Entropy     Open Access   (Followers: 5)
Environmental & Engineering Geoscience     Full-text available via subscription   (Followers: 5)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Environmetrics     Hybrid Journal  
Épités - Épitészettudomány     Full-text available via subscription   (Followers: 1)
EPJ Photovoltaics     Open Access   (Followers: 2)
Ergonomics in Design: The Quarterly of Human Factors Applications     Hybrid Journal   (Followers: 21)
ESAIM: Control Optimisation and Calculus of Variations     Open Access   (Followers: 2)
ESAIM: Mathematical Modelling and Numerical Analysis     Open Access   (Followers: 5)
ESAIM: Proceedings     Open Access  
eScience     Open Access   (Followers: 1)
Estuaries and Coasts     Hybrid Journal   (Followers: 22)
EUREKA : Physics and Engineering     Open Access  
Euro-Mediterranean Journal for Environmental Integration     Hybrid Journal  
European Journal of Combinatorics     Full-text available via subscription   (Followers: 3)
European Journal of Engineering Education     Hybrid Journal   (Followers: 9)
European Journal of Lipid Science and Technology     Hybrid Journal   (Followers: 1)
European Journal of Mass Spectrometry     Hybrid Journal   (Followers: 16)
European Physical Journal - Applied Physics     Full-text available via subscription   (Followers: 19)
European Transport Research Review     Open Access   (Followers: 22)
Evolutionary Intelligence     Hybrid Journal   (Followers: 2)
Evolving Systems     Hybrid Journal  
Experimental and Computational Multiphase Flow     Hybrid Journal  
Experimental Techniques     Hybrid Journal   (Followers: 51)
Experiments in Fluids     Hybrid Journal   (Followers: 17)
Farm Engineering and Automation Technology Journal     Open Access  
Fibers and Polymers     Full-text available via subscription   (Followers: 4)
FIGEMPA : Investigación y Desarrollo     Open Access   (Followers: 1)
Filtration & Separation     Full-text available via subscription   (Followers: 4)
Finite Fields and Their Applications     Full-text available via subscription   (Followers: 5)
Fırat University Turkish Journal of Science & Technology     Open Access  
Fire Science Reviews     Open Access   (Followers: 12)
Flexible Services and Manufacturing Journal     Hybrid Journal   (Followers: 2)
Flow, Turbulence and Combustion     Hybrid Journal   (Followers: 30)
Fluid Dynamics     Hybrid Journal   (Followers: 27)
Fluid Phase Equilibria     Hybrid Journal   (Followers: 4)
Focus on Catalysts     Full-text available via subscription  
Focus on Pigments     Full-text available via subscription   (Followers: 3)
Focus on Powder Coatings     Full-text available via subscription   (Followers: 5)
Focus on Surfactants     Full-text available via subscription   (Followers: 2)
Food Engineering Reviews     Hybrid Journal   (Followers: 2)
Food Science and Technology     Open Access   (Followers: 2)
Forces in Mechanics     Open Access   (Followers: 2)
Formación Universitaria     Open Access   (Followers: 4)
FORMakademisk - forskningstidsskrift for design og designdidaktikk     Open Access   (Followers: 2)
Formal Methods in System Design     Hybrid Journal   (Followers: 6)
Forschung     Hybrid Journal   (Followers: 1)
Forschung im Ingenieurwesen     Hybrid Journal  
Foundations and Trends in Systems and Control     Full-text available via subscription   (Followers: 4)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Electronic Design Automation     Full-text available via subscription   (Followers: 1)
Foundations of Science     Hybrid Journal   (Followers: 1)
Frontiers in Aerospace Engineering     Open Access   (Followers: 20)
Frontiers in Energy     Hybrid Journal   (Followers: 4)
Frontiers in Nanotechnology     Open Access   (Followers: 1)
Frontiers of Environmental Science & Engineering     Hybrid Journal   (Followers: 3)
Fuel and Energy Abstracts     Full-text available via subscription   (Followers: 7)
Fuel Cells     Hybrid Journal   (Followers: 8)
Fuel Cells Bulletin     Full-text available via subscription   (Followers: 9)
Fusion Engineering and Design     Hybrid Journal   (Followers: 6)
Fuzzy Information and Engineering     Open Access   (Followers: 2)
Fuzzy Sets and Systems     Hybrid Journal   (Followers: 3)
Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards     Hybrid Journal   (Followers: 8)
Géotechnique     Hybrid Journal   (Followers: 27)
Geothermics     Hybrid Journal   (Followers: 7)
Glass Technology - European Journal of Glass Science and Technology Part A     Full-text available via subscription   (Followers: 1)
Global Journal of Engineering Research     Full-text available via subscription  
Global Transitions Proceedings     Open Access  
GPS Solutions     Hybrid Journal   (Followers: 28)
Graphs and Combinatorics     Hybrid Journal   (Followers: 4)
Grass and Forage Science     Hybrid Journal   (Followers: 4)
Groundwater for Sustainable Development     Full-text available via subscription   (Followers: 5)
Heat Transfer - Asian Research     Hybrid Journal   (Followers: 10)
Heat Transfer Engineering     Hybrid Journal   (Followers: 36)
Heat Treatment and Surface Engineering     Open Access  
High Voltage     Open Access  
Himalayan Journal of Science and Technology     Open Access  
Historical Records of Australian Science     Hybrid Journal   (Followers: 2)
Human Behavior and Emerging Technologies     Hybrid Journal   (Followers: 1)
Human Factors in Ergonomics & Manufacturing     Hybrid Journal   (Followers: 12)
Human-Intelligent Systems Integration     Hybrid Journal  
I+D Revista de Investigaciones     Open Access  
IBM Journal of Research and Development     Hybrid Journal   (Followers: 16)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 112)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 88)
IEEE Communications Magazine     Full-text available via subscription   (Followers: 139)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 60)
IEEE Engineering Management Review     Full-text available via subscription   (Followers: 117)
IEEE Geoscience and Remote Sensing Letters     Hybrid Journal   (Followers: 149)
IEEE Geoscience and Remote Sensing Magazine     Hybrid Journal   (Followers: 6)
IEEE Industry Applications Magazine     Full-text available via subscription   (Followers: 82)
IEEE Instrumentation & Measurement Magazine     Hybrid Journal   (Followers: 148)
IEEE Journal of Biomedical and Health Informatics     Hybrid Journal   (Followers: 14)
IEEE Journal of Oceanic Engineering     Hybrid Journal   (Followers: 11)
IEEE Journal of Selected Topics in Quantum Electronics     Hybrid Journal   (Followers: 7)
IEEE Journal of Selected Topics in Signal Processing     Hybrid Journal   (Followers: 43)
IEEE Journal of Solid-State Circuits     Full-text available via subscription   (Followers: 24)
IEEE Journal on Selected Areas in Communications     Hybrid Journal   (Followers: 39)
IEEE Latin America Transactions     Full-text available via subscription   (Followers: 2)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
IEEE Microwave and Wireless Components Letters     Hybrid Journal   (Followers: 35)
IEEE Microwave Magazine     Full-text available via subscription   (Followers: 63)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 45)
IEEE Open Journal of Engineering in Medicine and Biology     Open Access   (Followers: 1)
IEEE Open Journal of Nanotechnology     Open Access   (Followers: 1)
IEEE Potentials     Full-text available via subscription   (Followers: 42)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 19)
IEEE Signal Processing Letters     Hybrid Journal   (Followers: 60)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 11)
IEEE Spectrum     Full-text available via subscription   (Followers: 219)
IEEE Technology and Society Magazine     Full-text available via subscription   (Followers: 8)
IEEE Transactions on Advanced Packaging     Full-text available via subscription   (Followers: 8)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 78)
IEEE Transactions on Applied Superconductivity     Hybrid Journal   (Followers: 5)
IEEE Transactions on Automation Science and Engineering     Full-text available via subscription   (Followers: 13)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 35)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 11)
IEEE Transactions on Circuits and Systems II: Express Briefs     Hybrid Journal   (Followers: 20)
IEEE Transactions on Components and Packaging Technologies     Full-text available via subscription   (Followers: 17)
IEEE Transactions on Control Systems Technology     Hybrid Journal   (Followers: 111)
IEEE Transactions on Education     Hybrid Journal   (Followers: 11)
IEEE Transactions on Electronics Packaging Manufacturing     Hybrid Journal   (Followers: 21)
IEEE Transactions on Energy Conversion     Hybrid Journal   (Followers: 16)
IEEE Transactions on Engineering Management     Hybrid Journal   (Followers: 74)

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Similar Journals
Journal Cover
IEEE Journal of Selected Topics in Signal Processing
Journal Prestige (SJR): 1.331
Citation Impact (citeScore): 7
Number of Followers: 43  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1932-4553
Published by IEEE Homepage  [228 journals]
  • Frontcover

    • Free pre-print version: Loading...

      Abstract: Presents the front cover for this issue of the publication.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • IEEE Signal Processing Society

    • Free pre-print version: Loading...

      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • IEEE Signal Processing Society

    • Free pre-print version: Loading...

      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Editorial: Intelligent Signal Analysis for Contagious Virus Diseases

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      Authors: Björn W. Schuller;Yonina Eldar;Maja Pantic;Shrikanth Narayanan;Tuomas Virtanen;Jianhua Tao;
      Pages: 159 - 163
      Abstract: COVID-19 infection’s recent outbreak triggered by the SARS-CoV-2 Corona virus had already led to more than two million reported infected individuals when we first addressed the community by our call – by now, the number sadly rose to roughly half a billion cases worldwide. The outbreak of COIVD-19 has also re-shaped and accelerated the scientific publication landscape in no time. One can observe a massive uprise in interest in work related to the topic of highly contagious virus diseases and potential contributions of digital health including intelligent signal processing. In addition, most publishers have reacted in one or the other way to the crises such as by opening up to pre-prints, waiving publication fees for COVID-19-related research, providing search functions and tools for COVID-19 research, and many more. Here, we gathered 13 carefully selected novel contributions across signal types such as audio, speech, image, video, or symbolic information, as well as their multimodal combination for application in the risk assessment, diagnosis, and monitoring of contagious virus diseases.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Detection of SARS-CoV-2 in COVID-19 Patient Nasal Swab Samples Using
           Signal Processing

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      Authors: Mahmoud Al Ahmad;Lillian J. A. Olule;Mohammed Meetani;Farrukh Amin Sheikh;Rahima Al Blooshi;Neena G. Panicker;Farah Mustafa;Tahir A. Rizvi;
      Pages: 164 - 174
      Abstract: This work presents an opto-electrical method that measures the viral nucleocapsid protein and anti-N antibody interactions to differentiate between SARS-CoV-2 negative and positive nasal swab samples. Upon light exposure of the patient nasal swab sample mixed with the anti-N antibody, charge transfer (CT) transitions within the altered protein folds are initiated between the charged amino acids side chain moieties and the peptide backbone that play the role of donor and acceptor groups. A Figure of Merit (FOM) was introduced to correlate the relative variations of the samples with and without antibody at two different voltages. Empirically, SARS-CoV-2 in patient nasal swab samples was detected within two minutes, if an extracted FOM threshold of >1 was achieved; otherwise, the sample wasconsidered negative.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Project Achoo: A Practical Model and Application for COVID-19 Detection
           From Recordings of Breath, Voice, and Cough

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      Authors: Alexander Ponomarchuk;Ilya Burenko;Elian Malkin;Ivan Nazarov;Vladimir Kokh;Manvel Avetisian;Leonid Zhukov;
      Pages: 175 - 187
      Abstract: The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. The approach combines signal processing and noise removal methods with an ensemble of fine-tuned deep learning networks and enables COVID detection on coughs. We have also developed and deployed a mobile application that uses a symptoms checker together with voice, breath, and cough signals to detect COVID-19 infection. The application showed robust performance on both openly sourced datasets and the noisy data collected during beta testing by the end users.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • A Speech Obfuscation System to Preserve Data Privacy in 24-Hour Ambulatory
           Cough Monitoring

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      Authors: Terence E. Taylor;Frank Keane;Yaniv Zigel;
      Pages: 188 - 196
      Abstract: Audio analysis of cough sounds can provide objective measures of respiratory clinical features such as cough frequency. Audio-based 24-hour ambulatory cough monitoring systems currently lead the way in providing these objective measures across a range of respiratory diseases. However, to preserve data privacy in cough audio recordings, there is interest to remove any identifiable information contained within patient and third-party speech. In this study we employed real-life patient audio recordings from the VitaloJAK 24-hour ambulatory cough monitoring device. We developed an audio-based speech obfuscation system that specifically detects and obfuscates intelligible speech while retaining cough events. An algorithm was developed to detect vowel sounds since most intelligible information is contained here. The detection algorithm employed audio features including energy, spectral centroid and an adaptive voiced speech feature. The detected vowel sounds were obfuscated by replacing the original audio signal with a synthetic version generated using the original energy and pitch but without formants information. The system was designed using seven hours of audio recordings from seven different patients with respiratory disease. The system was then evaluated on five 24-hour real-life patient audio recordings (120 hours in total) which consisted of 21.6 hours of intelligible speech along with 3,376 coughs. The system obfuscated 99.3% (21.5 hours) of intelligible speech while retaining 99.6% (3,362) of coughs. This speech obfuscation system can preserve data privacy while using 24-hour ambulatory cough monitors. Furthermore, it can retain cough events and other aspects of 24-hour cough recordings which may be of clinical interest.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • $_2$ +Monitoring+Using+Smartphone+Cameras&rft.title=IEEE+Journal+of+Selected+Topics+in+Signal+Processing&rft.issn=1932-4553&rft.date=2022&rft.volume=16&rft.spage=197&rft.epage=207&rft.aulast=Wu;&rft.aufirst=Xin&rft.au=Xin+Tian;Chau-Wai+Wong;Sushant+M.+Ranadive;Min+Wu;">A Multi-Channel Ratio-of-Ratios Method for Noncontact Hand Video Based
           SpO $_2$ Monitoring Using Smartphone Cameras

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      Authors: Xin Tian;Chau-Wai Wong;Sushant M. Ranadive;Min Wu;
      Pages: 197 - 207
      Abstract: Blood oxygen saturation (SpO$_2$) is an important indicator forpulmonary and respiratory functionalities. Clinical findings on COVID-19 show that many patients had dangerously low blood oxygen levels not long before conditions worsened. It is therefore recommended, especially for the vulnerable population, to regularly monitor the blood oxygen level for precaution. Recent works have investigated how ubiquitous smartphone cameras can be used to infer SpO$_2$. Most of these works are contact-based, requiring users to cover a phone’s camera and its nearby light source with a finger to capture reemitted light from the illuminated tissue. Contact-based methods may lead to skin irritation and sanitary concerns, especially during a pandemic. In this paper, we propose a noncontact method for SpO$_2$ monitoring using hand videos acquired by smartphones. Considering the optical broadband nature of the red (R), green (G), and blue (B) color channels of the smartphone cameras, we exploit all three channels of RGB sensing to distill the SpO$_2$ information beyond the traditional ratio-of-ratios (RoR) method that uses only two wavelengths. To further facilitate an accurate SpO$_2$ prediction, we design adaptive narrow bandpass filters based on accurately estimated heart rate to obtain the most cardiac-related AC component for each color channel. Experimental results show that our proposed blood oxygen estimation method can reach a mean absolute error of 1.26% when a pulse oximeter is used as a reference, outperforming the traditional RoR method by 25%.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • milliTRACE-IR: Contact Tracing and Temperature Screening via mmWave and
           Infrared Sensing

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      Authors: Marco Canil;Jacopo Pegoraro;Michele Rossi;
      Pages: 208 - 223
      Abstract: Social distancing and temperature screening have been widely employed to counteract the COVID-19 pandemic, sparking great interest from academia, industry and public administrations worldwide. While most solutions have dealt with these aspects separately, their combination would greatly benefit the continuous monitoring of public spaces and help trigger effective countermeasures. This work presents milliTRACE-IR, a joint mmWave radar and infrared imaging sensing system performing unobtrusive and privacy preserving human body temperature screening and contact tracing in indoor spaces. milliTRACE-IR combines, via a robust sensor fusion approach, mmWave radars and infrared thermal cameras. It achieves fully automated measurement of distancing and body temperature, by jointly tracking the subjects’s faces in the thermal camera image plane and the human motion in the radar reference system. Moreover, milliTRACE-IR performs contact tracing: a person with high body temperature is reliably detected by the thermal camera sensor and subsequently traced across a large indoor area in a non-invasive way by the radars. When entering a new room, a subject is re-identified among several other individuals by computing gait-related features from the radar reflections through a deep neural network and using a weighted extreme learning machine as the final re-identification tool. Experimental results, obtained from a real implementation of milliTRACE-IR, demonstrate decimeter-level accuracy in distance/trajectory estimation, inter-personal distance estimation (effective for subjects getting as close as 0.2 m), and accurate temperature monitoring (max. errors of 0.5 °C). Furthermore, milliTRACE-IR provides contact tracing through highly accurate (95%) person re-identification, in less than 20 seconds.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • On the Use of Uncertainty in Classifying Aedes Albopictus
           Mosquitoes

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      Authors: Gereziher Adhane;Mohammad Mahdi Dehshibi;David Masip;
      Pages: 224 - 233
      Abstract: The re-emergence of mosquito-borne diseases (MBDs), which kill hundreds of thousands of people each year, has been attributed to increased human population, migration, and environmental changes. Convolutional neural networks (CNNs) have been used by several studies to recognise mosquitoes in images provided by projects such as Mosquito Alert to assist entomologists in identifying, monitoring, and managing MBD. Nonetheless, utilising CNNs to automatically label input samples could involve incorrect predictions, which may mislead future epidemiological studies. Furthermore, CNNs require large numbers of manually annotated data. In order to address the mentioned issues, this paper proposes using the Monte Carlo Dropout method to estimate the uncertainty scores in order to rank the classified samples to reduce the need for human supervision in recognising Aedes albopictus mosquitoes. The estimated uncertainty was also used in an active learning framework, where just a portion of the data from large training sets was manually labelled. The experimental results show that the proposed classification method with rejection outperforms the competing methods by improving overall performance and reducing entomologist annotation workload. We also provide explainable visualisations of the different regions that contribute to a set of samples’ uncertainty assessment.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Epidemic Source Detection in Contact Tracing Networks: Epidemic Centrality
           in Graphs and Message-Passing Algorithms

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      Authors: Pei-Duo Yu;Chee Wei Tan;Hung-Lin Fu;
      Pages: 234 - 249
      Abstract: We study the epidemic source detection problem in contact tracing networks modeled as a graph-constrained maximum likelihood estimation problem using the susceptible-infected model in epidemiology. Based on a snapshot observation of the infection subgraph, we first study finite degree regular graphs and regular graphs with cycles separately, thereby establishing a mathematical equivalence in maximal likelihood ratio between the case of finite acyclic graphs and that of cyclic graphs. In particular, we show that the optimal solution of the maximum likelihood estimator can be refined to distances on graphs based on a novel statistical distance centrality that captures the optimality of the nonconvex problem. An efficient contact tracing algorithm is then proposed to solve the general case of finite degree-regular graphs with multiple cycles. Our performance evaluation on a variety of graphs shows that our algorithms outperform the existing state-of-the-art heuristics using contact tracing data from the SARS-CoV 2003 and COVID-19 pandemics by correctly identifying the superspreaders on some of the largest superspreading infection clusters in Singapore and Taiwan.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data

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      Authors: Shixiang Zhu;Alexander Bukharin;Liyan Xie;Khurram Yamin;Shihao Yang;Pinar Keskinocak;Yao Xie;
      Pages: 250 - 260
      Abstract: Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to local health departments to limit the spread of the disease. Understanding the spatio-temporal dynamics of hotspot events is of great importance to support policy decisions and prevent large-scale outbreaks. This paper presents a spatio-temporal Bayesian framework for early detection of COVID-19 hotspots (at the county level) in the United States. We assume both the observed number of cases and hotspots depend on a class of latent random variables, which encode the underlying spatio-temporal dynamics of the transmission of COVID-19. Such latent variables follow a zero-mean Gaussian process, whose covariance is specified by a non-stationary kernel function. The most salient feature of our kernel function is that deep neural networks are introduced to enhance the model’s representative power while still enjoying the interpretability of the kernel. We derive a sparse model and fit the model using a variational learning strategy to circumvent the computational intractability for large data sets. Our model demonstrates better interpretability and superior hotspot-detection performance compared to other baseline methods.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Hybrid Modeling of Regional COVID-19 Transmission Dynamics in the U.S.

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      Authors: Yue Bai;Abolfazl Safikhani;George Michailidis;
      Pages: 261 - 275
      Abstract: The fast transmission rate of COVID-19 worldwide has made this virus the most important challenge of year 2020. Many mitigation policies have been imposed by the governments at different regional levels (country, state, county, and city) to stop the spread of this virus. Quantifying the effect of such mitigation strategies on the transmission and recovery rates, and predicting the rate of new daily cases are two crucial tasks. In this paper, we propose a hybrid modeling framework which not only accounts for such policies but also utilizes the spatial and temporal information to characterize the pattern of COVID-19 progression. Specifically, a piecewise susceptible-infected-recovered (SIR) model is developed while the dates at which the transmission/recover rates change significantly are defined as “break points” in this model. A novel and data-driven algorithm is designed to locate the break points using ideas from fused lasso and thresholding. In order to enhance the forecasting power and to describe additional temporal dependence among the daily number of cases, this model is further coupled with spatial smoothing covariates and vector auto-regressive (VAR) model. The proposed model is applied to several U.S. states and counties, and the results confirm the effect of  “stay-at-home orders” and some states’ early “re-openings” by detecting break points close to such events. Further, the model provided satisfactory short-term forecasts of the number of new daily cases at regional levels by utilizing the estimated spatio-temporal covariance structures. They were also better or on par with other proposed models in the literature, including flexible deep learning ones. Finally, selected theoretical results and empirical performance of the proposed methodology on synthetic data are reported which justify the good perfor-ance of the proposed method.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Predicting the Epidemics Trend of COVID-19 Using Epidemiological-Based
           Generative Adversarial Networks

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      Authors: Haishuai Wang;Guangyu Tao;Jiali Ma;Shangru Jia;Lianhua Chi;Hong Yang;Ziping Zhao;Jianhua Tao;
      Pages: 276 - 288
      Abstract: The Coronavirus disease 2019 (COVID-19) is a respiratory illness that can spread from person to person. Since the COVID-19 pandemic is spreading rapidly over the world and its outbreak has affected different people in different ways, it is significant to study or predict the evolution of its epidemic trend. However, most of the studies focused solely on either classical epidemiological models or machine learning models for COVID-19 pandemic forecasting, which either suffer from the limitation of the generalization ability and scalability or the lack of surveillance data. In this work, we propose T-SIRGAN that integrates the strengths of the epidemiological theories and deep learning models to be able to represent complex epidemic processes and model the non-linear relationship for more accurate prediction of the growth of COVID-19. T-SIRGAN first adopts the Susceptible-Infectious-Recovered (SIR) model to generate epidemiological-based simulation data, which are then fed into a generative adversarial network (GAN) as adversarial examples for data augmentation. Then, Transformers are used to predict the future trends of COVID-19 based on the generated synthetic data. Extensive experiments on real-world datasets demonstrate the superiority of our method. We also discuss the effectiveness of vaccine based on the difference between the predicted and the reported number of COVID-19 cases.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Modeling Social Distancing and Quantifying Epidemic Disease Exposure in a
           Built Environment

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      Authors: Chaitra Hegde;Ali Bahrami Rad;Reza Sameni;Gari David Clifford;
      Pages: 289 - 299
      Abstract: As we transition away from pandemic-induced isolation and social distancing, there is a need to estimate the risk of exposure in built environments. We propose a novel metric to quantify social distancing and the potential risk of exposure to airborne diseases in an indoor setting, which scales with distance and the number of people present. The risk of exposure metric is designed to incorporate the dynamics of particle movement in an enclosed set of rooms for people at different immunity levels, susceptibility due to age, background infection rates, intrinsic individual risk factors (e.g., comorbidities), mask-wearing levels, the half-life of the virus and ventilation rate in the environment. The model parameters have been selected for COVID-19, although the modeling framework applies to other airborne diseases. The performance of the metric is tested using simulations of a real physical environment, combining models for walking, path length dynamics, and air-conditioning replacement action. We have also created a visualization tool to help identify high-risk areas in the built environment. The resulting software framework is being used to help with planning movement and scheduling in a clinical environment ahead of reopening of the facility, for deciding the maximum time within an environment that is safe for a given number of people, for air replacement settings on air-conditioning and heating systems, and for mask-wearing policies. The framework can also be used for identifying locations where foot traffic might create high-risk zones and for planning timetabled transitions of groups of people between activities in different spaces. Moreover, when coupled with individual-level location tracking (via radio-frequency tagging, for example), the exposure risk metric can be used in real-time to estimate the risk of exposure to the coronavirus or other airborne illnesses, and intervene through air-conditioning action modification, changes in timetabling of group acti-ities, mask-wearing policies, or restricting the number of individuals entering a given room/space. All software are provided online under an open-source license.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Mathematical Modeling of COVID-19 and Prediction of Upcoming Wave

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      Authors: Arti M.K.;
      Pages: 300 - 306
      Abstract: We investigate the problem of mathematical modeling of new corona virus (COVID-19) spread in practical scenarios in various countries, specifically in India, the United States of America (USA), France, Brazil, and Turkey. We propose a mathematical model to characterize COVID-19 disease and predict the new/upcoming wave of COVID-19. This prediction is very much required to prepare medical set-ups and proceed with future plans of action. A mixture Gaussian model is proposed to characterize the COVID-19 disease. Specifically, the data corresponding to new active cases of COVID-19 per day is considered, and then we try to fit the data to a mathematical function. It is observed that the Gaussian mixture model is suitable to characterize the new active cases of COVID-19. Further, it is assumed that there are N waves of COVID-19 and the information of each upcoming wave is present in the current and previous waves as well. By using this concept, prediction of the upcoming wave can be performed. A close match between analytical results and the available results shows the correctness of the considered model.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
  • Model-Based Prediction and Optimal Control of Pandemics by
           Non-Pharmaceutical Interventions

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      Authors: Reza Sameni;
      Pages: 307 - 317
      Abstract: A model-based signal processing framework is proposed for pandemic trend forecasting and control, by using non-pharmaceutical interventions (NPI) at regional and country levels worldwide. The control objective is to prescribe quantifiable NPI strategies at different levels of stringency, which balance between human factors (such as new cases and death rates) and cost of intervention per region/country. Due to infrastructural disparities and differences in priorities of regions and countries, strategists are given the flexibility to weight between different NPIs and to select the desired balance between the human factor and overall NPI cost. The proposed framework is based on a finite-horizon optimal control (FHOC) formulation of the bi-objective problem and the FHOC is numerically solved by using an ad hoc extended Kalman filtering/smoothing framework for optimal NPI estimation and pandemic trend forecasting. The algorithm enables strategists to select the desired balance between the human factor and NPI cost with a set of weights and parameters. The parameters of the model are partially selected by epidemiological facts from COVID-19 studies, and partially trained by using machine learning techniques. The developed algorithm is applied on ground truth data from the Oxford COVID-19 Government Response Tracker project, which has categorized and quantified the regional responses to the pandemic for more than 300 countries and regions worldwide, since January 2020. The dataset was used for NPI-based prediction and prescription during the XPRIZE Pandemic Response Challenge.
      PubDate: Feb. 2022
      Issue No: Vol. 16, No. 2 (2022)
       
 
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