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Detecting Pneumonia Lung Infection From X-Ray Images with Deep Learning

Journal of Physics: Conference Series 2021年第1期1950卷

作者： K Raheja A Goel M Mahajan Scholar Department of Computer Science and Engineering SGT University Gurugram India Professor School of Computing Science and Engineering Galgotias university India Professor Faculty of Engineering and Technology SGT University Gurugram India

Pneumonia is one of the most prominent basis of premature death globally, according to some of the major health institutions like WHO more than 1 billion people around the world get infected and more than 4 million people die prematurely due to pneumonia lung infection. Detection of pneumonia infection requires a lot of medical tests, which can be expensive and time consuming. Deep Learning, the technology which gives computer systems the ability to learn and adapt through unstructured data in order to complex solve real world problems has the potential to make the detection of pneumonia easier, cost effective and less time consuming. The motivation behind this paper is to grasp the criticalness and utilizations of deep computational learning and Convolutional Neural Network (CNN) by executing it so as to recognize Pneumonia by examining a patient's chest x-beam pictures.

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Preparing a commercial quantum key distribution system for certification against implementation loopholes

arXiv

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arXiv 2023年

作者： Makarov, Vadim Abrikosov, Alexey Chaiwongkhot, Poompong Fedorov, Aleksey K. Huang, Anqi Kiktenko, Evgeny Petrov, Mikhail Ponosova, Anastasiya Ruzhitskaya, Daria Tayduganov, Andrey Trefilov, Daniil Zaitsev, Konstantin Russian Quantum Center Skolkovo Moscow121205 Russia Vigo Quantum Communication Center University of Vigo VigoE-36310 Spain NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia Department of Physics Faculty of Science Mahidol University Bangkok10400 Thailand Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Bangkok10110 Thailand QRate Skolkovo Moscow143026 Russia Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Steklov Mathematical Institute Russian Academy of Sciences Moscow119991 Russia atlanTTic Research Center University of Vigo VigoE-36310 Spain School of Telecommunication Engineering Department of Signal Theory and Communications University of Vigo VigoE-36310 Spain National Research University Higher School of Economics Moscow101000 Russia

A commercial quantum key distribution (QKD) system needs to be formally certified to enable its wide deployment. The certification should include the system’s robustness against known implementation loopholes and attacks that exploit them. Here we ready a fiber-optic QKD system for this procedure. The system has a prepare-and-measure scheme with decoy-state BB84 protocol, polarisation encoding, qubit source rate of 312.5 MHz, and is manufactured by QRate. We detail its hardware and post-processing. We analyse the hardware for known implementation loopholes, search for possible new loopholes, and discuss countermeasures. We then amend the system design to address the highest-risk loopholes identified. We also work out technical requirements on the certification lab and outline its possible structure. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum cryptography

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Reporting of Scope2 Co2-Emissions and Electricity Consumption in 111 Indian Ocean Cities between 2015-2022

SSRN

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SSRN 2024年

作者： Nematchoua, Modeste Kameni Buratti, Cinza Orosa, Jose A. Attia, Shady Teller, Jacques Bemanana, Muriel Akinola, Olatunji Bernard, Andrianirina Charles Sendrahasina, Rakotomalala Minoson Roy, Sambatra Eric Jean Falisoa, Rafanotsimiva Liva Jean-Pierre, Messina Reiter, Sigrid School of Informatics Computing and Cyber Systems Northern Arizona University 1295 S. Knoles Dr. Building 90 Room 320 FlagstaffAZ86011 United States Department of Engineering University of Perugia Via G. Duranti 63 Perugia06125 Italy Department of N. S. and Marine Engineering Escuela Técnica Superior de N. y M University of A Coruña Paseo de Ronda 51 A Coruna15011 Spain Sustainable Building Design Lab Dept. UEE Applied Sciences University of Liege Belgium LEMA ArGEnCo Department University of Liege Belgium Higher Polytechnic School University of Antsiranana Antsiranana Madagascar Science and Technology’s Higher Institute University of Mahajanga Mahajanga Madagascar University of Antananarivo Po Box 566 Antananarivo101 Madagascar Department of Industrial Engineering Higher Institute of Technology Antsiranana Antsiranana201 Madagascar Faculty of Architecture and Construction Notre-Dame du Kasaï University Congo

Several sources related that the electricity sector emits almost a quarter of greenhouse gases each year in the world. It is therefore one of the important sectors to take into account to limit global warming. Indian Ocean cities produce significant CO2 emissions during electricity consumption. Their volume and accuracy remain practically unknown and untested. Indeed, until now, there is no methodology suggested by the researchers to evaluate Fossil Fuel carbon dioxide (FFCO2) emission, and electricity consumption in this region. Aware of these crucial problems, this study was carried out to assess and analyse CO2 emissions coming from Electricity consumption (called Scope2) in 111 cities located in the Indian Ocean from 55 Power plants between 2015-2022 (08 years) and in four sectors (Residential, Commercial, Industrial, and On-road). To carry out a good comparison, all the data were grouped into three categories, Before COVID (2015-2018);During COVID (2019-2020);and After COVID (2021-2022)). The results showed that the CO2 emission difference is significant in the residential and commercial sectors. It was observed that CO2 emissions increased in 2019-2022 in the residential, industrial, and on-road sectors whereas, simultaneously during the same period, it decreased in the commercial sector. During the three periods, the CO2 emissions rate was the highest in the residential sector (around 52%), and the least on-road (around 1%). The significant difference in the commercial sector suggests a decrease in electricity consumption during the peak of the pandemic due to reduced business activities. Businesses adapted to new operating conditions, such as reduced hours or enhanced energy efficiency measures, which also contributed to the change in consumption patterns. © 2024, The Authors. All rights reserved.

关键词： Low emission

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Investigation of the influence of tank geometry on a vessel's stability under free surface effect when in coastal waters

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Journal of Physics: Conference Series 2021年第1期1834卷

作者： Ross Fuge Jahir Rizvi School of Engineering Computing and Mathematics Faculty of Science and Engineering University of Plymouth Drake Circus Plymouth PL4 8AA UK

Tank sizes on liquid cargo carriers are becoming larger to minimise wasted spaces on-board and maximise payload capacity. This trend can significantly affect a vessel's stability and its design. Therefore, this paper investigates whether spherical tanks provide better stability than a traditional tank formed with vertical sides under a range of free surface scenarios. The motions of a model liquid cargo carrier hull with various sizes of tanks and various fill levels has been investigated in a coastal basin. Regular waves of various heights and frequencies have been generated and the rolling motions of the hull have been documented. Results have shown that spherical tanks offer less free surface effects compared to vertical sided tanks thus create less rolling motion. In contrast, when the hull has four tanks, all of those with free surfaces, the vertical sided tanks provide better stability up to 50% fill levels whereas spherical tanks induce less roll between the fill levels 50% and 100%.

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The Localized Subtraction Approach For EEG and MEG Forward Modeling

arXiv

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arXiv 2023年

作者： Höltershinken, Malte B. Lange, Pia Erdbrügger, Tim Buschermöhle, Yvonne Wallois, Fabrice Buyx, Alena Pursiainen, Sampsa Vorwerk, Johannes Engwer, Christian Wolters, Carsten H. Institute for Biomagnetism and Biosignalanalysis University of Münster Münster Germany Institute of Medical Informatics University of Münster Münster Germany Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience University of Münster Münster Germany INSERM U1105 Research Group on Multimodal Analysis of Brain Function Jules Verne University of Picardie Amiens France Pediatric functional exploration of the nervous system department CHU Picardie Amiens France Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Computing Sciences Unit Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland Institute of Electrical and Biomedical Engineering Private University for Health Sciences Medical Informatics and Technology Hall in Tyrol Austria Faculty of Mathematics and Computer Science University of Münster Münster Germany

In FEM-based EEG and MEG source analysis, the subtraction approach has been proposed to simulate sensor measurements generated by neural activity. While this approach possesses a rigorous foundation and produces accurate results, its major downside is that it is computationally prohibitively expensive in practical applications. To overcome this, we developed a new approach, called the localized subtraction approach. This approach is designed to preserve the mathematical foundation of the subtraction approach, while also leading to sparse right-hand sides in the FEM formulation, making it efficiently computable. We achieve this by introducing a cut-off into the subtraction, restricting its influence to the immediate neighborhood of the source. In this work, this approach will be presented, analyzed, and compared to other state-of-the-art FEM right-hand side approaches. Furthermore, we discuss how to arrive at an efficient and stable implementation. We perform validation in multi-layer sphere models where analytical solutions exist. There, we demonstrate that the localized subtraction approach is vastly more efficient than the subtraction approach. Moreover, we find that for the EEG forward problem, the localized subtraction approach is less dependent on the global structure of the FEM mesh, while the subtraction approach is sensitive to the mesh structure even at a distance to the source. Additionally, we show the localized subtraction approach to rival, and in many cases even surpass, the other investigated approaches in terms of accuracy. Especially for the MEG forward problem, where Biot-Savart’s law is employed, we show the localized subtraction approach and the subtraction approach to produce highly accurate approximations of the volume currents close to the source. The localized subtraction approach thus reduces the computational cost of the subtraction approach to an extent that makes it usable in practical applications without sacrificing the rigorousness and

关键词： Mesh generation

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Implementation of GPSR protocol with various mobility models in VANET Scenario

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Journal of Physics: Conference Series 2021年第1期1950卷

作者： K Raheja M Mahajan A Goel Scholar Department of Computer Science and Engineering SGT University Gurugram India Professor School of Computing Science and Engineering Galgotias university India Professor Faculty of Engineering and Technology SGT University Gurugram India

In Vehicular Ad hoc Networks (VANET), topology varies very frequently because vehicles move in high speed. VANET is deployed on road. In GPSR Protocol, as the data packets are forwarded depending upon on the beacon information sent by neighboring nodes, which contain the location of neighbors. Hence nodes move in mobile nature as they change their positions. Mobile pattern of node is reflected by Mobility Models, as they characterize the movement of users who are mobile on the road, with respect to their direction, velocity and location over a period of time. Mobility models are practiced in implementation of protocols and the pattern by which the mobility models reflect real world practices of vehicles on the roads. Using simple pattern randomly, graph constrained mobility models are common practices while doing research. These models donot describe mobility of vehicles in realistic manner. For instance while accelerating and decelerating in the presence of nearby vehicles, these situations greatly affect the Network performance. Selecting the mobility model which is realistic one is the main focus of this paper. To address the challenges such as high mobility of vehicle nodes on the road and random topology, VANET needs a suitable mobility model to obtain improved Packet Delivery Ratio, Throughput, End to End Delay etc. This paper first implements the GPSR Protocol and then GPSR is analyzed by applying different mobility models such as Random Way Point, Gauss Markov, Manhattan Grid, Reference Point Group and Random direction. Results are analyzed by taking the following parameters: Routing overhead, Throughput, PDR and End to End Delivery. The implementation is carried out using NS—2.35 and Bonmotion is used to create mobility models.

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Super-resolving Herschel imaging: A proof of concept using Deep Neural Networks

arXiv

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arXiv 2021年

作者： Lauritsen, Lynge Dickinson, Hugh Bromley, Jane Serjeant, Stephen Lim, Chen-Fatt Gao, Zhen-Kai Wang, Wei-Hao School of Physical Sciences Faculty of Science Technology Engineering & Mathematics The Open University Walton Hall Kents Hill Milton KeynesMK7 6AA United Kingdom School of Computing & Communications Faculty of Science Technology Engineering & Mathematics The Open University Walton Hall Kents Hill Milton KeynesMK7 6AA United Kingdom Graduate Institute of Astrophysics National Taiwan University Taipei10617 Taiwan No. 1 Section 4 Roosevelt Road Taipei10617 Taiwan Graduate Institute of Astronomy National Central University Taoyuan32001 Taiwan

Wide-field sub-millimetre surveys have driven many major advances in galaxy evolution in the past decade, but without extensive follow-up observations the coarse angular resolution of these surveys limits the science exploitation. This has driven the development of various analytical deconvolution methods. In the last half a decade Generative Adversarial Networks have been used to attempt deconvolutions on optical data. Here we present an autoencoder with a novel loss function to overcome this problem in the sub-millimeter wavelength range. This approach is successfully demonstrated on Herschel SPIRE 500 µm COSMOS data, with the super-resolving target being the JCMT SCUBA-2 450 µm observations of the same field. We reproduce the JCMT SCUBA-2 images with high fidelity using this autoencoder. This is quantified through the point source fluxes and positions, the completeness and the purity. Copyright © 2021, The Authors. All rights reserved.

关键词： Data handling

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The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue

引用

Medical Image Analysis 2024年 97卷 103257页

作者： Weitz, Philippe Valkonen, Masi Solorzano, Leslie Carr, Circe Kartasalo, Kimmo Boissin, Constance Koivukoski, Sonja Kuusela, Aino Rasic, Dusan Feng, Yanbo Pouplier, Sandra Sinius Sharma, Abhinav Eriksson, Kajsa Ledesma Robertson, Stephanie Marzahl, Christian Gatenbee, Chandler D. Anderson, Alexander R.A. Wodzinski, Marek Jurgas, Artur Marini, Niccolò Atzori, Manfredo Müller, Henning Budelmann, Daniel Weiss, Nick Heldmann, Stefan Lotz, Johannes Wolterink, Jelmer M. De Santi, Bruno Patil, Abhijeet Sethi, Amit Kondo, Satoshi Kasai, Satoshi Hirasawa, Kousuke Farrokh, Mahtab Kumar, Neeraj Greiner, Russell Latonen, Leena Laenkholm, Anne-Vibeke Hartman, Johan Ruusuvuori, Pekka Rantalainen, Mattias Department of Medical Epidemiology and Biostatistics Karolinska Insitutet Stockholm Sweden Institute of Biomedicine University of Turku Turku Finland Institute of Biomedicine University of Eastern Finland Kuopio Finland Department of Surgical Pathology Zealand University Hospital Roskilde Denmark Department of Oncology and Pathology Karolinska Institutet Stockholm Sweden Gestalt Diagnostics Spokane United States Department of Integrated Mathematical Oncology Moffitt Cancer Center Tampa United States Informatics Institute University of Applied Sciences Western Switzerland Switzerland Department of Measurement and Electronics AGH University of Kraków Poland Department of Computer Science University of Geneva Geneva Switzerland Department of Neuroscience University of Padova Italy Medical Faculty University of Geneva Switzerland Fraunhofer Institute for Digital Medicine MEVIS Lübeck Germany Department of Applied Mathematics Technical Medical Centre University of Twente Enschede Netherlands Multimodality Medical Imaging Technical Medical Centre University of Twente Enschede Netherlands Department of Electrical Engineering Indian Institute of Technology Bombay India Graduate School of Engineering Muroran Institute of Technology Hokkaido Japan Faculty of Medical Technology Niigata University of Health and Welfare Niigata Japan FORXAI Business Operations Konica Minolta Inc. Osaka Japan Department of Computing Science University of Alberta EdmontonAlberta United States Alberta Machine Intelligence Institute Edmonton Canada MedTechLabs BioClinicum Karolinska University Hospital Stockholm Sweden Faculty of Medicine and Health Technology Tampere University Tampere Finland

The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability of large WSI datasets have revolutionised WSI analysis. Therefore, the current state-of-the-art in WSI registration is unclear. To address this, we conducted the ACROBAT challenge, based on the largest WSI registration dataset to date, including 4,212 WSIs from 1,152 breast cancer patients. The challenge objective was to align WSIs of tissue that was stained with routine diagnostic immunohistochemistry to its H&E-stained counterpart. We compare the performance of eight WSI registration algorithms, including an investigation of the impact of different WSI properties and clinical covariates. We find that conceptually distinct WSI registration methods can lead to highly accurate registration performances and identify covariates that impact performances across methods. These results provide a comparison of the performance of current WSI registration methods and guide researchers in selecting and developing methods. © 2024

关键词： Tissue

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An improved genetic algorithm to optimize vehicle scheduling for relief efforts

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International Journal of Performability engineering 2019年第9期15卷 2356-2363页

作者： Zhou, You Sun, Lecheng Zhou, Xu Parmar, Milan Wang, Liupu College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbol Computation Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Cancer Hospital Attached Xinjiang Medical University Urumqi830000 China Faculty of Engineering and Computing Coventry University CoventryCV1 5FB United Kingdom

The vehicle scheduling problem is a typical multi-objective optimization problem. It is a core logistics dispatching problem and the key to realize system optimization. Optimizing vehicle scheduling for relief efforts has important practical significance and can be applied to a broader range of applications. Compared with other vehicle scheduling problems, vehicle optimal scheduling for relief efforts is mostly used to perform spot delivery or security tasks. In this paper, we propose an improved genetic algorithm and apply it to solve the vehicle scheduling problem for relief efforts in the equipment technical area. The experimental results demonstrate the effectiveness and robustness of our proposed algorithm. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Genetic algorithms

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Preface

Advanced Structured Materials

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Advanced Structured Materials 2024年 208卷 v页

作者： Ismail, Azman Zulkipli, Fatin Nur Daril, Mohd Amran Mohd Öchsner, Andreas Maritime Engineering Technology and Centre for Women Advancement and Leadership Malaysian Institute of Marine Engineering Technology Universiti Kuala Lumpur Perak Lumut Malaysia Information Science Studies College of Computing Informatics and Mathematics Universiti Teknologi MARA Kelantan Machang Malaysia Malaysian Institute of Industrial Technology Universiti Kuala Lumpur Johor Masai Malaysia Faculty of Mechanical and Systems Engineering Esslingen University of Applied Sciences Esslingen am Neckar Baden-Württemberg Germany

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