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CloudSafe: A tool for an automated security analysis for cloud computing

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arXiv 2019年

作者： An, Seongmo Eom, Taehoon Park, Jong Sou Hong, Jin B. Nhlabatsi, Armstrong Fetais, Noora Khan, Khaled M. Kim, Dong Seong Dept. of Computer Engineering Korea Aerospace University Korea Republic of Department of Computer Science and Software Engineering University of Western Australia Australia KINDI Center for Computing Research Qatar University School of Information Technology and Electrical Engineering University of Queensland Australia

Cloud computing has been adopted widely, providing on-demand computing resources to improve perfornance and reduce the operational costs. However, these new functionalities also bring new ways to exploit the cloud computing environment. To assess the security of the cloud, graphical security models can be used, such as Attack Graphs and Attack Trees. However, existing models do not consider all types of threats, and also automating the security assessment functions are difficult. In this paper, we propose a new security assessment tool for the cloud named CloudSafe, an automated security assessment for the cloud. The CloudSafe tool collates various tools and frameworks to automate the security assessment process. To demonstrate the applicability of the CloudSafe, we conducted security assessment in Amazon AWS, where our experimental results showed that we can effectively gather security information of the cloud and carry out security assessment to produce security reports. Users and cloud service providers can use the security report generated by the CloudSafe to understand the security posture of the cloud being used/provided. Copyright © 2019, The Authors. All rights reserved.

关键词： Cloud security

Exploring the effect of image enhancement techniques on COVID‐19 detection using chest X‐rays images

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arXiv 2020年

作者： Rahman, Tawsifur Khandakar, Amith Qiblawey, Yazan Tahir, Anas Kiranyaz, Serkan Kashem, Saad Bin Abul Islam, Mohammad Tariqul Maadeed, Somaya Al Zughaier, Susu M. Khan, Muhammad Salman Chowdhury, Muhammad E.H. Department of Biomedical Physics & Technology University of Dhaka Dhaka 1000 Bangladesh Department of Electrical Engineering Qatar University Doha2713 Qatar Faculty of Robotics and Advanced Computing Qatar Armed Forces‐Academic Bridge Program Qatar Foundation Doha24404 Qatar Dept. of Electrical Electronics and Systems Engineering Universiti Kebangsaan Malaysia BangiSelangor43600 Malaysia Department of Computer Science and Engineering Qatar University Doha2713 Qatar Department of Basic Medical Sciences College of Medicine Biomedical and Pharmaceutical Research Unit QU Health Qatar University Doha2713 Qatar University of Engineering and Technology Peshawar Pakistan

The use of computer-aided diagnosis in the reliable and fast detection of corona virus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the medical infrastructure. Chest X-ray (CXR) imaging has several advantages over other imaging techniques as it is cheap, easily accessible, fast and portable. CXR images are sometimes of poor quality and so image enhancement techniques can help the machine learning models to extract valuable discriminating features from the image. Numerous works have been reported on COVID-19 detection from smaller set of original X-ray images. However, the effect of image enhancement in COVID-19 detection was not reported in the literature. This paper explores the effect of various popular image enhancement techniques and states the © 2020, CC BY.

关键词： Image enhancement

Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis

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arXiv 2020年

作者： Singh, Nalini M. Iglesias, Juan Eugenio Adalsteinsson, Elfar Dalca, Adrian V. Golland, Polina Computer Science and Artificial Intelligence Laboratory MIT CambridgeMA United States Dept. of Health Sciences & Technology MIT CambridgeMA United States A. A. Martinos Center Massachusetts General Hospital BostonMA United States Harvard Medical School CambridgeMA United States Centre for Medical Image Computing UCL London United Kingdom Research Laboratory of Electronics MIT CambridgeMA United States Dept. of Electrical Engineering & Computer Science MIT CambridgeMA United States

We propose neural network layers that explicitly combine frequency and image feature representations and show that they can be used as a versatile building block for reconstruction from frequency space data. Our work is motivated by the challenges arising in MRI acquisition where the signal is a corrupted Fourier transform of the desired image. The proposed joint learning schemes enable both correction of artifacts native to the frequency space and manipulation of image space representations to reconstruct coherent image structures at every layer of the network. This is in contrast to most current deep learning approaches for image reconstruction that treat frequency and image space features separately and often operate exclusively in one of the two spaces. We demonstrate the advantages of joint convolutional learning for a variety of tasks, including motion correction, denoising, reconstruction from undersampled acquisitions, and combined undersampling and motion correction on simulated and real world multicoil MRI data. The joint models produce consistently high quality output images across all tasks and datasets. When integrated into a state of the art unrolled optimization network with physics-inspired data consistency constraints for undersampled reconstruction, the proposed architectures significantly improve the optimization landscape, which yields an order of magnitude reduction of training time. This result suggests that joint representations are particularly well suited for MRI signals in deep learning networks. Our code and pretrained models are publicly available at https://***/nalinimsingh/interlacer. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

Market-based model in CR-IoT: A Q-probabilistic multi-agent learning approach

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arXiv 2019年

作者： Wang, Dan Zhang, Wei Song, Bin Du, Xiaojiang Guizani, Mohsen State Key Laboratory of Integrated Services Networks Xidian University 710071 China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology China Dept. of Computer and Information Sciences Temple University PhiladelphiaPA19122 United States Dept. of Electrical and Computer Engineering University of Idaho MoscowID83844 United States

The ever-increasingly urban population and its material demands have brought an unprecedented burden to cities. Smart cities leverage emerging technologies like CR-IoT to provide better QoE and QoS for all citizens. However, resource allocation is an important problem in CR-IoT. Currently, this problem is handled by auction theory or game theory. To make CR-IoT nodes smarter and more autonomously allocate resources, we propose a multiagent reinforcement learning (MARL) algorithm to learn the optimal resource allocation strategies in the oligopolistic market model. Firstly, we model a multi-agent scenario with two primary users (PUs) as sellers and multiple secondary users (SUs) as buyers, which is a Bertrand market model. Then, we propose the Q-probabilistic multiagent learning (QPML) and apply it for allocating resource in a market. In the situation of multiagent interaction, the PUs and SUs learn strategies to maximize their revenue. Experimental results prove our multiagent learning approach performs well and convergence also well. Copyright © 2019, The Authors. All rights reserved.

关键词： Resource allocation

Frequency comb distillation for optical superchannel transmission

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arXiv 2021年

作者： Prayoonyong, Chawaphon Boes, Andreas Xu, Xingyuan Tan, Mengxi Chu, Sai T. Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Corcoran, Bill Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Optical Sciences Centre Swinburne University Hawthorne VIC3122 Australia Centre for Micro-Photonics Swinburne University Hawthorne VIC3122 Australia Department of Physics City University of Hong Kong Tat Chee Ave Hong Kong Xi’an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi’an China INRS – EMT VarennesQCJ3X 1S2 Canada Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China

Optical frequency combs can potentially provide an efficient light source for multi-terabit-per-second optical superchannels. However, as the bandwidth of these multiwavelength light sources is increased, it can result in low per-line power. Optical amplifiers can be used to overcome power limitations, but the accompanying spontaneous optical noise can degrade performance in optical systems. To overcome this, we demonstrate wideband noise reduction for comb lines using a high-Q microring resonator whose resonances align with the comb lines, providing tight optical filtering of multiple combs lines at the same time. By distilling an optical frequency comb in this way, we are able to reduce the required comb line OSNR when these lines are used in a coherent optical communications system. Through performance tests on a 19.45-GHz-spaced comb generating 71 lines, using 18 Gbaud, 64-QAM sub-channels at a spectral efficiency of 10.6 b/s/Hz, we find that noise-corrupted comb lines can reduce the optical signal-to-noise ratio required for the comb by ~ 9 dB when used as optical carriers at the transmitter side, and by ~ 12 dB when used as a local oscillator at the receiver side. This demonstration provides a method to enable low power optical frequency combs to be able to support high bandwidth and high-capacity communications. © 2021, CC BY.

关键词： Natural frequencies

Optical frequency microcomb distillation for super channel data transmission

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TechRxiv

TechRxiv 2021年

作者： Prayoonyong, Chawaphon Boes, Andreas Xu, Xingyuan Tan, Mengxi Chu, Sai T. Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Corcoran, Bill Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Optical Sciences Centre Swinburne University Hawthorne VIC3122 Australia Centre for Micro-Photonics Swinburne University Hawthorne VIC3122 Australia Department of Physics City University of Hong Kong Tat Chee Ave Hong Kong Xi’an Institute of Optics and Precision Mechanics The Chinese Academy of Sciences Xi’an China INRS – EMT VarennesQCJ3X 1S2 Canada Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China

Microcombs provide a potential compact and efficient light source for multi-Terabit-per-second optical superchannels. However, as the bandwidth of these multiwavelength light sources is increased, this can result in low per-line power. Optical amplifiers can be used to overcome power limitations, but the accompanying spontaneous optical noise can degrade performance in optical systems. To overcome this issue, we propose wideband noise reduction for comb lines using a high-Q microring resonator, whose resonances align with comb lines. When applying the proposed distillation to a superchannel system with 18 Gbaud, 64-QAM sub-channels in a > 10 Tb/s optical superchannel, we find that noise-corrupted comb lines can reduce the optical signal-to-noise ratio required for the comb by ~ 9 dB when used as optical carriers at the transmitter side, and by ~ 12 dB when used as a local oscillator at the receiver side. © 2021, CC BY.

关键词： Distillation

Fir-based narrowband active noise control with a new online secondary-path modeling subsystem 25

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Fir-based narrowband active noise control with a new online ...

25th International Congress on Sound and Vibration 2018: Hiroshima Calling, ICSV 2018

作者： Ma, Yaping Xiao, Yegui Wei, Guo Sun, Jinwei Ma, Liying Khorasani, Khashayar Dept. Automatic Testing and Control Harbin Institute of Technology Harbin150001 China Dept. Information and Management Systems Prefectural University of Hiroshima Hiroshima734-8558 Japan Dept. Electrical and Computer Engineering Concordia University MontrealQC Canada

ISBN: (纸本)9781510868458

Injecting auxiliary random noise is an effective approach to implementing the online secondary-path modeling (SPM) subsystem in active noise control (ANC). In this paper, a typical FIR-based narrowband ANC (NANC) system with online SPM is proposed to reduce the sinusoidal noise generated by rotating machines, especially its lower frequency portion. A first-order FIR filter or magnitude/phase adjuster (MPA) serves as a sub-controller in each frequency channel. The contributions of this work are twofold. A bandpass filter bank based on IIR notch filters is introduced to mitigate the coupling between the controller (MPAs) and the SPM subsystem, which significantly improves the performance of the overall system. Furthermore, the proposed system requires only one x-filtering block regardless of the number of targeted frequencies, which considerably reduces the computational cost of the system. Simulations as well as application to real noise are conducted to demonstrate that the proposed system is superior to its conventional version in terms of overall system convergence and online SPM quality. © 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling. All rights reserved.

关键词： Controllers

Designing a virtual reality system for clinical education and examination

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Computers and Education: X Reality

computers and Education: X Reality 2024年 5卷

作者： Akinwale, Olawale Babatunde Abiona, Olatunde Oluwatope, Ayodeji Oludola Otuyemi, Olayinka Donald Ijarotimi, Omotade Adebimpe Olubusola Komolafe, Abiola Aregbesola, Stephen Babatunde Kolawole, Babatope Ayodeji Adetutu, Olufemi Mayowa Agunbiade, Ojo Melvin Ayinde, Adeboye Titus Idowu, Lanre Okunola, Oluseye Ademola Adediwura, Alaba Adeyemi Department of Electronic and Electrical Engineering Faculty of Technology Obafemi Awolowo University Ile-Ife 220005 Nigeria Computer Information Systems Department College of Arts and Sciences Indiana University Northwest 3400 Broadway Gary 46408 IN United States Department of Computer Science and Engineering Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Child Dental Health Faculty of Dentistry College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Obstetrics Gynaecology and Perinatology Faculty of Clinical Sciences College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Nursing Science Faculty of Basic Medical Science College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Oral and Maxillofacial Surgery Faculty of Dentistry College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Medicine Faculty of Clinical Sciences College of Health Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Dept. of Demography and Social Statistics Faculty of Social Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Sociology and Anthropology Faculty of Social Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Psychology Faculty of Social Sciences Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Educational Technology and Library Studies Obafemi Awolowo University Ile-Ife 220005 Nigeria Department of Educational Foundation and Counselling Obafemi Awolowo University Ile-Ife 220005 Nigeria

The COVID-19 pandemic clearly showed how much medical and clinical students’ education relied on physical instruction and examination. The work presented here was born by the fact that medical and clinical education had to be suspended during the social distancing phase of the pandemic. This work presents the lessons learned from creating a virtual reality system (VTRACS) for educating and assessing clinical students on a limited budget. Our work showed that clinical education could be done in a virtual space with a minimal virtual reality setup and a low-cost virtual reality headset. © 2024 The Authors

关键词： Clinical education Haptic feedback Low-cost Medical education Virtual reality

First Demonstration of CMOS Inverter and 6T-SRAM Based on GAA CFETs Structure for 3D-IC Applications

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First Demonstration of CMOS Inverter and 6T-SRAM Based on GA...

International Electron Devices Meeting (IEDM)

作者： S.-W. Chang P.-J. Sung T-Y. Chu D. D. Lu C.-J. Wang N.-C. Lin C.-J. Su S.-H. Lo H.-F. Huang J.-H. Li M.-K. Huang Y.-C. Huang S.-T. Huang H.-C. Wang Y.-J. Huang J.-Y. Wang L. - W Yu Y.-F. Huang F. - K. Hsueh C.-T. Wu W. C.-Y. Ma K.-H. Kao Y. - J. Lee C.-L. Lin R. W. Chuang K.-P. Huang S. Samukawa Y. Li W. - H. Lee T.-S. Chao G. - W. Huang W.-F. Wu J. - Y. Li J.-M. Shieh W. - K. Yeh Y.-H. Wang Taiwan Semiconductor Research Institute Hsinchu Taiwan Dept. of Electrical Engineering National Cheng Kung University Tainan Taiwan Dept. of Electrophysics National Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering National Sun Yat-sen University Kaohsiung Taiwan Dept. of Electronic Engineering Feng Chia University Taichung Taiwan Mechanical and Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Institute of Fluid Science Tohoku University Sendai Japan Dept. of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering and Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan

For the first time, CMOS inverters and 6T-SRAM cells based on vertically stacked gate-all-around complementary FETs (CFETs) are experimentally demonstrated. Manufacturing difficulties of vertically stacked source and drain electrodes of the CFETs have been overcome by using junctionless transistors, thereby reducing the number of lithographic steps required. Furthermore, with post metallization treatments, both the voltage transfer characteristics (VTCs) of CMOS inverters and butterfly curves of SRAM show significant improvements due to the symmetry of nMOS and pMOS threshold voltages. Simulation shows that 3-dimensional CFET inverters have lower input parasitic capacitance than standard 2-dimensional CMOS, leading to reduced gate delay and lower power consumption.

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