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arXiv 2022年

作者： Hasuo, Ichiro Eberhart, Clovis Haydon, James Dubut, Jérémy Bohrer, Rose Kobayashi, Tsutomu Pruekprasert, Sasinee Zhang, Xiao-Yi Pallas, Erik André Yamada, Akihisa Suenaga, Kohei Ishikawa, Fuyuki Kamijo, Kenji Shinya, Yoshiyuki Suetomi, Takamasa Tokyo101-8430 Japan Dept. Computer Science Worcester Polytechnic Institute 100 Institute Road WorcesterMA01609-2280 United States Inst. Software & Systems Engineering University of Augsburg Universitätstraße 6a AugsburgD-86135 Germany Cyber Physical Security Research Center AIST Aomi 2-4-7 Tokyo135-0064 Japan Graduate School of Informatics Kyoto University Kyoto606-8501 Japan Mazda Motor Corporation Fuchu730-8670 Japan SOKENDAI The Graduate University for Advanced Studies Japan Tokyo Japan

We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS rules guarantee goal achievement—in addition to collision avoidance as in the original RSS—requires complex planning over long sequences of manoeuvres. To deal with the complexity, we introduce a compositional reasoning framework based on program logic, in which one can systematically develop RSS rules for smaller subscenarios and combine them to obtain RSS rules for bigger scenarios. As the basis of the framework, we introduce a program logic dFHL that accommodates continuous dynamics and safety conditions. Our framework presents a dFHL-based workflow for deriving goal-aware RSS rules;we discuss its software support, too. We conducted experimental evaluation using RSS rules in a safety architecture. Its results show that goal-aware RSS is indeed effective in realising both collision avoidance and goal achievement. © 2022, CC BY-NC-ND.

关键词： computer circuits

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Automated Diagnosis of Cardiovascular Diseases from Cardiac Magnetic Resonance Imaging Using Deep Learning Models: A Review

arXiv

引用

arXiv 2022年

作者： Jafari, Mahboobeh Shoeibi, Afshin Khodatars, Marjane Ghassemi, Navid Moridian, Parisa Delfan, Niloufar Alizadehsani, Roohallah Khosravi, Abbas Ling, Sai Ho Zhang, Yu-Dong Wang, Shui-Hua Gorriz, Juan M. Rokny, Hamid Alinejad Acharya, U. Rajendra Internship in BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia Data Science and Computational Intelligence Institute University of Granada Spain Department of Medical Engineering Mashhad Branch Islamic Azad University Mashhad Iran Faculty of Computer Engineering Dept. of Artificial Intelligence Engineering K. N. Toosi University of Technology Tehran Iran Deakin University VIC3217 Australia Australia School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Department of Psychiatry University of Cambridge United Kingdom BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia UNSW Data Science Hub The University of New South Wales SydneyNSW2052 Australia Research Centre Macquarie University Sydney2109 Australia Ngee Ann Polytechnic Singapore599489 Singapore Dept. of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan Dept. of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality globally. CVDs appear with minor symptoms and progressively get worse. The majority of people experience symptoms such as exhaustion, shortness of breath, ankle swelling, fluid retention, and other symptoms when starting CVD. Coronary artery disease (CAD), arrhythmia, cardiomyopathy, congenital heart defect (CHD), mitral regurgitation, and angina are the most common CVDs. Clinical methods such as blood tests, electrocardiography (ECG) signals, and medical imaging are the most effective methods used for the detection of CVDs. Among the diagnostic methods, cardiac magnetic resonance imaging (CMR) is increasingly used to diagnose, monitor the disease, plan treatment and predict CVDs. Coupled with all the advantages of CMR data, CVDs diagnosis is challenging for physicians due to many slices of data, low contrast, etc. To address these issues, deep learning (DL) techniques have been employed to the diagnosis of CVDs using CMR data, and much research is currently being conducted in this field. This review provides an overview of the studies performed in CVDs detection using CMR images and DL techniques. The introduction section examined CVDs types, diagnostic methods, and the most important medical imaging techniques. In the following, investigations to detect CVDs using CMR images and the most significant DL methods are presented. Another section discussed the challenges in diagnosing CVDs from CMR data. Next, the discussion section discusses the results of this review, and future work in CVDs diagnosis from CMR images and DL techniques are outlined. The most important findings of this study are presented in the conclusion section. © 2022, CC BY-NC-ND.

关键词： Electrocardiography

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An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works

arXiv

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arXiv 2021年

作者： Shoeibi, Afshin Moridian, Parisa Khodatars, Marjane Ghassemi, Navid Jafari, Mahboobeh Alizadehsani, Roohallah Kong, Yinan Gorriz, Juan Manuel Ramírez, Javier Khosravi, Abbas Nahavandi, Saeid Acharya, U. Rajendra Data Science and Computational Intelligence Institute University of Granada Spain Faculty of Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Medical Engineering Mashhad Branch Islamic Azad University Mashhad Iran Computer Engineering department Ferdowsi University of Mashhad Mashhad Iran Electrical and Computer Engineering Faculty Semnan University Semnan Iran Deakin University VIC3217 Australia School of Engineering Macquarie University Sydney2109 Australia Department of Signal Theory Networking and Communications Universidad de Granada Spain Ngee Ann Polytechnic Singapore599489 Singapore Dept. of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan Dept. of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements. Epileptic seizure detection methods involve neurological exams, blood tests, neuropsychological tests, and neuroimaging modalities. Among these, neuroimaging modalities have received considerable attention from specialist physicians. One method to facilitate the accurate and fast diagnosis of epileptic seizures is to employ computer-aided diagnosis systems (CADS) based on deep learning (DL) and neuroimaging modalities. This paper has studied a comprehensive overview of DL methods employed for epileptic seizures detection and prediction using neuroimaging modalities. First, DL-based CADS for epileptic seizures detection and prediction using neuroimaging modalities are discussed. Also, descriptions of various datasets, preprocessing algorithms, and DL models which have been used for epileptic seizures detection and prediction have been included. Then, research on rehabilitation tools has been presented, which contains brain-computer interface (BCI), cloud computing, internet of things (IoT), hardware implementation of DL techniques on field-programmable gate array (FPGA), etc. In the discussion section, a comparison has been carried out between research on epileptic seizure detection and prediction. The challenges in epileptic seizures detection and prediction using neuroimaging modalities and DL models have been described. In addition, possible directions for future works in this field, specifically for solving challenges in datasets, DL, rehabilitation, and hardware models, have been proposed. The final section is dedicated to the conclusion which summarizes the significant findings of the paper. © 2021, CC BY-NC-ND.

关键词： Forecasting

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COMPARISON OF OPTIMAL POWER FLOW FORMULATIONS IN ACTIVE DISTRIBUTION GRIDS

COMPARISON OF OPTIMAL POWER FLOW FORMULATIONS IN ACTIVE DIST...

引用

The 12th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2020)

作者： C. Mylonas S. Karagiannopoulos P. Aristidou D. Shchetinin G. Hug Power Systems Laboratory ETH Zurich 8092 Zurich Switzerland Dept. of Electrical Engineering Computer Engineering & Informatics Cyprus University of Technology 3036 Limassol Cyprus ABB Corporate Research Center 5405 Baden Switzerland

Active Distribution Networks (DNs) are expected to host an increasing number of Distributed Generators (DGs) and other Distributed Energy Resources (DERs), offering new flexible sources and enabling the provision of ancillary services to system operators. Centralized DER controls that use Optimal Power Flow (OPF) methods necessitate tractable and scalable computational tools that can handle large DNs with satisfactory performance. In this paper, we compare an iterative OPF method against.the standard exact AC OPF calculations in terms of the computational effort and solution quality. Furthermore, we highlight the suitability of the selected formulation to offer voltage support (VS) as an ancillary service to the transmission network. The results are demonstrated using a combination of a medium and low voltage grid, and show that tractable OPF formulations can unlock financial business cases for DNs that can actively participate in VS schemes.

关键词： distributed power generation distribution networks load flow power grids iterative methods centralised control

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Kinetic Model Evaluation of Dynamical Properties of Nanaorod Antennas Embedded in a Polymer Carrying the Nuclei of Fusion Fuel

arXiv

引用

arXiv 2022年

作者： Papp, István Bravina, Larissa Csete, Mária Kumari, Archana Mishustin, Igor N. Motornenko, Anton Rácz, Péter Satarov, Leonid M. Stöcker, Horst Strottman, Daniel D. Szenes, András Vass, Dávid Szokol, Ágnes Nagyné Kámán, Judit Bonyár, Attila Biró, Tamás S. Csernai, László P. Kroó, Norbert Wigner Research Centre for Physics Budapest Hungary Hungarian Bureau for Research Development and Innovation Hungary Dept. of Physics and Technology University of Bergen Norway Department of Physics University of Oslo Norway Dept. of Optics and Quantum Electronics Univ. of Szeged Hungary Frankfurt Institute for Advanced Studies Frankfurt/Main Germany Inst. für Theoretische Physik Goethe Universität Frankfurt/Main Germany GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany Los Alamos National Laboratory Los AlamosNM United States Department of Electronics Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary Csernai Consult Bergen Bergen Norway Hungarian Academy of Sciences Budapest Hungary

Recently laser induced fusion with simultaneous volume ignition, a spin-off from relativistic heavy ion collisions, was proposed, where implanted nanoantennas regulated and amplified the light absorption in the fusion target. Studies of resilience of the nanoantennas was published recently in vacuum. These studies are extended to nanoantennas embedded into a polymer, which modifies the nanoantenna’s lifetime and absorption properties. Copyright © 2022, The Authors. All rights reserved.

关键词： Gold nanoparticles

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Using a 22-layer U-Net to perform segmentation of squamous cell carcinoma on digitized head and neck histological images

Using a 22-layer U-Net to perform segmentation of squamous c...

引用

Medical Imaging 2020: Digital Pathology

作者： Mavuduru, Amol Halicek, Martin Shahedi, Maysam Little, James V. Chen, Amy Y. Myers, Larry L. Fei, Baowei Dept. of Bioengineering University of Texas DallasTX United States Dept. of Computer Science University of Texas DallasTX United States Dept. of Biomedical Engineering Georgia Inst. of Tech. Emory Univ. AtlantaGA United States Emory Univ. School of Medicine Dept. of Pathology and Laboratory Medicine AtlantaGA United States Emory Univ. School of Medicine Dept. of Otolaryngology AtlantaGA United States Dept. of Otolaryngology Univ. of Texas Southwestern Medical Center DallasTX United States Advanced Imaging Research Center Univ. of Texas Southwestern Medical Center DallasTX United States Dept. of Radiology Univ. of Texas Southwestern Medical Center DallasTX United States

ISBN: (纸本)9781510634077

Squamous cell carcinoma (SCC) comprises over 90 percent of tumors in the head and neck. The diagnosis process involves performing surgical resection of tissue and creating histological slides from the removed tissue. Pathologists detect SCC in histology slides, and may fail to correctly identify tumor regions within the slides. In this study, a dataset of patches extracted from 200 digitized histological images from 84 head and neck SCC patients was used to train, validate and test the segmentation performance of a fully-convolutional U-Net architecture. The neural network achieved a pixel-level segmentation AUC of 0.89 on the testing group. The average segmentation time for whole slide images was 72 seconds. The training, validation, and testing process in this experiment produces a model that has the potential to help segment SCC images in histological images with improved speed and accuracy compared to the manual segmentation process performed by pathologists. © 2020 SPIE. All rights reserved.

关键词： PSISDG

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Combining Photometric Features and Relative Position to Detect and Track Target Person

Combining Photometric Features and Relative Position to Dete...

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International Conference on computer engineering, Network and Intelligent Multimedia (CENIM)

作者： Bima Sena Bayu Dewantara Jun Miura Dept. of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia Dept. of Computer Science and Engineering Toyohashi University of Technology Toyohashi Japan

ISBN: (纸本)9781728129662

Tracking a target person is a vital job in human-robot interaction. The robot must always notice a particular person as the interaction target partner. However, it is sometimes very hard to distinguish the target person because there are many other persons around the target. In this paper, we propose a target person detection and tracking system by combining person's frontal photometric features such as face and clothing color, and coordinate of the person's location in the real world. We apply an illumination invariant face recognition method named OptiFuzz. Hue-Saturation histogram (HS-histogram) is used to obtain the clothing color feature, and a location of the person is acquired from a calibrated single camera view. All these features are then fed into an algorithm of Naive Bayes to discriminate between the target person and others. Our experimental results indicate a successful outcome as it is always possible to detect and track the target person.

关键词： human-robot interaction target partner illumination invariant face recognition HS-histogram Naive Bayes Persons Human machine interaction Targets Photomechanics relative positioning

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A novel portable fluorophore-free photonic qPCR for point-of-care applications

A novel portable fluorophore-free photonic qPCR for point-of...

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Clinical and Translational Biophotonics, Translational 2020

作者： Mohammadyousef, P. Paliouras, M. Trifiro, M. Kirk, A.G. Electrical and Computer Engineering Dept. McGill University 3480 Rue University MontréalQCH3A 2K6 Canada Lady Davis Inst. for Medical Research Jewish General Hospital 3755 Chemin de la Côte-Sainte-Catherine MontréalQCH3T 1E2 Canada

Plasmonic-driven Polymerase Chain Reaction is accomplished by a surface-emitting laser with real-time amplification detected via monitoring of DNA-UV transmission. This miniature device provides high amplification eff... 详细信息

ISBN: (纸本)9781943580743

关键词： Polymerase chain reaction

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Performance-complexity tradeoffs of concatenated FEC for 64-QAM MLC and BICM 45

Performance-complexity tradeoffs of concatenated FEC for 64-...

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45th European Conference on Optical Communication, ECOC 2019

作者： Barakatain, Masoud Lentner, Diego Böcherer, Georg Kschischang, Frank R. Dept. of Electrical and Computer Eng. Univ. of Toronto Toronto Canada Inst. for Communications Eng. Technical Univ. of Munich Munich Germany Optical Communication Technology Lab. Huawei Paris France

ISBN: (纸本)9781839531859

Multilevel coding (MLC) is compared with bit-interleaved coded modulation (BICM) from a performance-versus-complexity standpoint. In both approaches, complexity-optimized error-reducing inner codes are designed for concatenation with an outer staircase code, assuming signaling with 64-point quadrature amplitude modulation. The codes are designed to achieve various points on the Pareto frontier characterizing the performance-complexity tradeoff. computer simulations of the resulting codes reveal that the MLC approach (a) provides significant advantages compared to BICM and (b) has a clear edge over an existing MLC proposal, providing a net coding gain of up to 13.6 dB at 28% overall overhead, yet with reasonable decoding complexity. © 2019 inst.tution of engineering and technology. All rights reserved.

关键词： Complex networks

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A Survey on OFDM Interference Challenge to improve its BER 2

A Survey on OFDM Interference Challenge to improve its BER

引用

2nd International Conference on Electronics, Communication and Aerospace technology, ICECA 2018

作者： Jadav, Nilesh Kumar Computer Engineering Dept. MEF Group of Inst. Rajkot Gujarat360003 India

ISBN: (纸本)9781538609651

Generation of wireless network from past to present deals with many fatal problems such as - spectrum scarcity, lower data rates, power deficiency, synchronization, unfavorable diversity, inferior QoS, and Interference. Many of the above problems are resolved in some manner using a better modulation and multiplexing technique using Orthogonal Frequency Division Multiplexing (OFDM), however, it still interlocks with Interference hindrance. In the paper, we surveyed all about OFDM interference's - Inter Symbol Interference (lSI), Inter Carrier Interference (ICI) and Co- Channel Interference (CCI) which greatly inhibits the Bit Error Rate (BER) of OFDM. Moreover, this paper also reviews some of the good research on interference mitigation techniques. We also surveyed the work on wavelet transform which is quite effective in OFDM system compare to conventional Fourier transform. Channel coding is a measurable parameter which is a mere technique in reducing the CCI effect from the wireless system, for that we elaborate Space Time Block Code-OFDM (STBC-OFDM) to reduce ICI and CCI. © 2018 IEEE.

关键词： Orthogonal frequency division multiplexing

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