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SSRN 2022年

作者： Mahmood, Khalid Saleem, Muhammad Asad Shamshad, Salman Ghaffar, Zahid Akram, Muhammad Wahid Conti, Mauro Das, Ashok Kumar National Yunlin University of Science and Technology Yunlin Taiwan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Pakistan Department of Software Engineering The University of Lahore Lahore54590 Pakistan Department of Computer Science Barani Institute of Sciences Sahiwal57000 Pakistan Department of Mathematics University of Padua Padua35131 Italy Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad500032 India Virginia Modeling Analysis and Simulation Center Old Dominion University SuffolkVA23435 United States

The Internet of Drones (IoD) offers supervised admittance to drones in a targeted fly zone as the byproduct of the Internet of Things (IoT). The term drone is the trendy alias for Intelligent Flying Vehicle (IFV). The contemporary sensing, processing, and connectivity services enriches the use of drones in a plethora of civilian and military applications. In these applications, consumers can acquire the real-time information directly from flying drones in a smart city environment. No doubt, this feature empowers the consumers, but it is deemed critical as direct access privilege can cause serious security threats. To prevent such threats, we propose an anonymous for consumer flying vehicles in smart city application. The proposed protocol utilizes a physically unclonable function to sustain the physical security of the flying vehicles. We ratify the security fortitude and persistence of our protocol through inclusive security analysis. Whereas, we demonstrate the performance evaluation under diverse performance metrics which shows that overall our devised protocol incurs 11 . 5771 ms to complete the authentication cycle. The careful performance comparison attests to the precedence of our protocol over peer protocols. © 2022, The Authors. All rights reserved.

关键词： Internet of things

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Improvement of the Conjugate Heat Transfer in High Temperature Chamber Furnaces for Firing of Ceramic Ware

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Journal of Civil Engineering and Architecture 2019年第4期13卷 265-272页

作者： Kalin S. Krumov Nina Y. Penkova Center of Mathematical Modeling and Computer Simulation University of Chemical Technology and MetallurgySofia 1756Bulgaria

The firing of ceramic ware in chamber furnaces is a transient multiphysical process,including turbulence combustion and fluid flow in the gas space,convective and radiation heat transfer from the flue gases to the furnace walls and ceramic ware,surface to surface radiation between the solid surfaces and conduction heat transfer in combination with endothermic or exothermic processes in the ceramic *** and conceptions for numerical analysis of that conjugate heat transfer(CHT)in such thermal aggregates are *** are validated on the base of information,obtained by in situ measurements at a furnace for firing of technical ***-uniform thermal and fluid flow fields in the furnace space that cause problems in the surrounding walls and wastes at the ceramic ware are ascertained in *** impossibility to improve the furnace operation at the existing construction and combustion installation is established.A variant for reconstruction of the furnace is investigated *** includes changes of the number,power and topology of the burners and different arrangement of the ceramic ware in the furnace *** temperature fields and reduction of the specific fuel consumption at the suggested configuration of the thermal aggregate are established.

关键词： Ceramic firing CHT,furnace design topology optimization combustion computational fluid dynamics(CFD)

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Hopping-Transport Mechanism for Reconfigurable Logic in Disordered Dopant Networks

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Physical Review Applied 2022年第6期17卷 064025-064025页

作者： Henri Tertilt Jesse Bakker Marlon Becker Bram de Wilde Indrek Klanberg Bernard J. Geurts Wilfred G. van der Wiel Andreas Heuer Peter A. Bobbert Institut für physikalische Chemie Westfälische Wilhelms-Universität Münster Münster Germany NanoElectronics Group University of Twente Enschede Netherlands Multiscale Modeling and Simulation Group Faculty of Electrical Engineering Mathematics and Computer Science MESA+ Institute for Nanotechnology and Center for Brain-Inspired Nano Systems (BRAINS) University of Twente Enschede Netherlands Center for Computational Energy Research (CCER) Eindhoven University of Technology Netherlands Fachbereich Physik Westfälische Wilhelms-Universität Münster Münster Germany Department of Applied Physics Eindhoven University of Technology Netherlands

We present an atomic-scale mechanism based on variable-range hopping of interacting charges enabling reconfigurable logic in dopant network processing units. Kinetic Monte Carlo simulations of the hopping process show temperature-dependent current-voltage characteristics and artificially evolved basic Boolean logic gates in very good agreement with experiment. The simulations provide unique insights into the local electrostatic potential and current flow in the dopant network, showing subtle changes induced by control voltages that set the conditions for the logic operation. These insights will be crucial in the systematic further development of this burgeoning technology for unconventional computing. The establishment of the principles underlying the logic functionality of these devices encourages the exploration and utilization of the same principles in other materials and device geometries.

关键词： Doping effects Hopping transport Neuromorphic computing Devices for digital logic, storage & processing Disordered systems Doped semiconductors Genetic algorithm Monte Carlo methods

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Multi-Material, Approach-Guided, Controlled-Resolution Breast Meshing for Fe-Based Interactive Surgery simulation

Multi-Material, Approach-Guided, Controlled-Resolution Breas...

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Annual modeling and simulation Conference (ANNSIM)

作者： Motaz Alqaoud John Plemmons Eric Feliberti Krishnanand Kaipa Gabor Fichtinger Yiming Xiao Tanweer Rashid Michel Audette Biomedical Engineering Old Dominion University Norfolk VA USA Department of Radiology Eastern Virginia Medical School Norfolk VA USA Department of Surgery Eastern Virginia Medical School Norfolk VA USA Mechanical & Aerospace Engineering Old Dominion University Norfolk VA USA School of Computing Queen’s University Kingston ON Canada Computer Science & Software Engineering Concordia University Montreal QC Canada Neuroimage Analytics Laboratory University of Texas Health Science Center San Antonio TX USA Computational Modeling & Simulation Engineering Old Dominion University Norfolk VA USA

This paper proposes a guided, controlled resolution framework for 3D multi-material meshing. Using data from magnetic resonance (MR) images, we efficiently focused on demonstrating our framework for patient-specific breast cases. As a result, we can preserve the shared boundaries and enhance the resolution without negating the aspect of simulation computing time needed for finite element analysis (FEA). Our output is a high-quality volumetric mesh comprising 21K cells representing the three main parts for breast surgery simulation and planning, fat, fibroglandular (FGT), and tumor mass. Our approach combines three steps, surface meshing, surface mesh decimation, and generating a volumetric mesh. We showed experimental results for every stage and compared our final output to other literature, proving our method's efficiency in an accurate, simple, and high-quality presentation of a patient-specific breast meshing.

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Epitope identification of SARS-CoV-2 structural proteins using in silico approaches to obtain a conserved rational immunogenic peptide

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Immunoinformatics (Amsterdam, Netherlands) 2022年 7卷 100015页

作者： Leonardo Pereira de Araújo Maria Eduarda Carvalho Dias Gislaine Cristina Scodeler Ana de Souza Santos Letícia Martins Soares Patrícia Paiva Corsetti Ana Carolina Barbosa Padovan Nelson José de Freitas Silveira Leonardo Augusto de Almeida Laboratory of Molecular Biology of Microorganisms Federal University of Alfenas Alfenas Minas Gerais Brazil. Laboratory of Molecular Modeling and Computer Simulation Federal University of Alfenas Alfenas Minas Gerais Brazil.

The short time between the first cases of COVID-19 and the declaration of a pandemic initiated the search for ways to stop the spread of SARS-CoV-2. There are great expectations regarding the development of effective vaccines that protect against all variants, and in the search for it, we hypothesized the obtention of a predicted rational immunogenic peptide from structural components of SARS-CoV-2 might help the vaccine research direction. In the search for a candidate of an immunogenic peptide of the SARS-CoV-2 envelope (E), membrane (M), nucleocapsid (N), or spike (S) proteins, we access the predicted sequences of each protein after the genome sequenced worldwide. We obtained the consensus amino acid sequences of about 14,441 sequences of each protein of each continent and the worldwide consensus sequence. For epitope identification and characterization from each consensus structural protein related to MHC-I or MHC-II interaction and B-cell receptor recognition, we used the IEDB reaching 68 epitopes to E, 174 to M, 245 to N, and 833 to S proteins. To select an epitope with the highest probability of binding to the MHC or BCR, all epitopes of each consensus sequence were aligned. The curation indicated 1, 4, 8, and 21 selected epitopes for E, M, N, and S proteins, respectively. Those epitopes were tested in silico for antigenicity obtaining 16 antigenic epitopes. Physicochemical properties and allergenicity evaluation of the obtained epitopes were done. Ranking the results, we obtained one epitope of each protein except for the S protein that presented two epitopes after the selection. To check the 3D position of each selected epitope in the protein structure, we used molecular homology modeling. Afterward, each selected epitope was evaluated by molecular docking to reference MHC-I or MHC-II allelic protein sequences. Taken together, the results obtained in this study showed a rational search for a putative immunogenic peptide of SARS-CoV-2 structural proteins tha

关键词： COVID-19 New coronavirus Reverse vaccinology SARS-CoV-2

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ABCSS: A novel approach for increasing the TCP congestion window in a network

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Procedia computer Science 2021年 191卷 437-444页

作者： N.M. Kasoro S.K. Kasereka G.K. Alpha K. Kyamakya University of Kinshasa Faculty of Sciences Mathematics and Computer Science Department Kinshasa Democratic Republic of the Congo Artificial intelligence Big data and modeLing simulation research center (ABIL) Kinshasa Democratic Republic of the Congo Université Libre des Pays des Grands Lacs Faculty of Sciences and Technologies Goma Democratic Republic of the Congo Alpen-Adria-Universitaet Klagenfurt Institute of Smart Systems Technologies Department of Mathematical Sciences Klagenfurt Austria

Congestion control is a useful task to be taken into account in order to maintain a good traffic in a network. In the case of a TCP/IP (Transmission Control Protocol/Internet Protocol) network, congestion creates queues in routers and even packet rejection. It is the reason why research have been conducted to improve congestion control mechanisms. Nowadays, several TCP congestion algorithms have been implemented. However, with the technology evolution and the need in terms of traffic capacity, various mechanisms implemented by these algorithms have shown their limitations and still need to be improved. The aim of this paper is to develop a novel TCP congestion control approach based on two famous algorithms: Appropriate Byte Counting (ABC) and Slow Start (SS). The results obtained show that ABC increases the congestion window appropriately compared to Slow Start. However, the congestion window remains invariant during the first round trips, which causes the TCP burst phenomenon. The TCP splitting can cause buffer overflows and long queues. For theses shortcomings, we propose ABCSS as a novel approach that appropriately increase the TCP congestion window and minimize the TCP splitting problem. The simulations of ABCSS algorithm provide interesting results compared to some known algorithms.

关键词： Congestion TCP ABC Slow Start Congestion window Congestion control ABCSS

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Report: Convalescent blood treatment for COVID-19: are local donors enough?

arXiv

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arXiv 2020年

作者： Douglas, Pamela K. Farahani, Farzad V. Douglas, David B. Bookheimer, Susan Department of Psychiatry and Biobehavioral Medicine David Geffen School of Medicine UCLA United States Modeling Simulation and Computer Science UCF Harvard T.H. Chan School of Public Health United States

COVID-19 is now a global pandemic, and an effective vaccine may be many months away. Over 100 years ago, Spanish flu fatalities were attenuated when doctors began treating patients with blood plasma donated by recovered (or convalesced) survivors. Passive immunity transfer via administration of convalesced blood product (CBP) appears to represent a readily available and promising avenue for mitigating mortalities, expediting recovery time, and even prophylaxis against the SARS-CoV-2 virus. Here, we review challenges to CBP efficacy, and present a graph theoretical model of transmission dynamics that identifies evolving "hubs" of COVID-19 cases. Importantly, this model suggests that CBP efficacy may rest on an efficient and distributed global sampling scheme as opposed to CBP pooled from local donors alone. Copyright © 2020, The Authors. All rights reserved.

关键词： SARS

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Enforcing Security and Privacy in Distributed Ledgers by Intel SGX

Enforcing Security and Privacy in Distributed Ledgers by Int...

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Spring simulation Conference (SpringSim)

作者： Xueping Liang Sachin Shetty Peter Foytik Deepak Tosh Department of Engineering and Computer Science Virginia State University Petersburg VA USA Virginia Modeling Analysis and Simulation Center Old Dominion University Suffolk VA USA Department of Computer Science The University of Texas at El Paso El Paso TX USA

ISBN: (数字)9781565553705

ISBN: (纸本)9781728163642

Distributed Ledger Technology (DLT) utilizes an architecture that can host a large number of nodes without pre-established trust to provide decentralized services. The blockchain is the most widely used architecture of distributed ledger, where transactions across the whole network are visible to all participants in a chain to prevent tampering. However, transactions may contain sensitive information such as business contract. To secure the system and protect user privacy, we propose a multi-channel architecture that leverages Intel Software Guard Extensions (SGX). We illustrate how SGX capabilities help to defend against attacks on distributed ledgers, by way of SGX enforcement on the participating machines. We adopt the design and implementation of a two layer architecture for securing the blockchain mining process and enhancing the transaction privacy. The security analysis and performance evaluation show that the design and protocols are capable of protecting privacy, defending against adversarial attacks and scalable.

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Perturbations and Phase Transitions in Swarm Optimization Algorithms

arXiv

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arXiv 2025年

作者： Vantuch, Tomáš Zelinka, Ivan Adamatzky, Andrew Marwan, Norbert Center ENET Technical University of Ostrava Czech Republic Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical & Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science Technical University of Ostrava Czech Republic Unconventional Computing Lab UWE Bristol United Kingdom Leibniz Association Potsdam Germany

Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that swarm optimization algorithms also exhibit transitions from chaos, analogous to a motion of gas molecules, when particles explore solution space disorderly, to order, when particles follow a leader, similar to molecules propagating along diffusion gradients in liquid solutions of reagents. We analyze these ‘phase-like’ transitions in swarm optimization algorithms using recurrence quantification analysis and Lempel-Ziv complexity estimation. We demonstrate that converging iterations of the optimization algorithms are statistically different from non-converging ones in a view of applied chaos, complexity and predictability estimating indicators. An identification of a key factor responsible for the intensity of their phase transition is the main contribution of this paper. We examined an optimization as a process with three variable factors – an algorithm, number generator and optimization function. More than 9.000 executions of the optimization algorithm revealed that the nature of an applied algorithm itself is the main source of the phase transitions. Some of the algorithms exhibit larger transition-shifting behavior while others perform rather transition-steady computing. These findings might be important for future extensions of these algorithms. © 2025, CC BY-NC-ND.

关键词： Cellular automata

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Deep learning in biomedical optics

arXiv

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arXiv 2021年

作者： Tian, Lei Hunt, Brady Lediju Bell, Muyinatu A. Yi, Ji Smith, Jason T. Ochoa, Marien Intes, Xavier Durr, Nicholas J. Department of Electrical and Computer Engineering Boston University BostonMA United States Thayer School of Engineering Dartmouth College HanoverNH United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD United States Department of Biomedical Engineering Johns Hopkins University BaltimoreMD United States Department of Computer Science Johns Hopkins University BaltimoreMD United States Department of Ophthalmology Johns Hopkins University BaltimoreMD United States Center for Modeling Simulation and Imaging in Medicine Rensselaer Polytechnic Institute

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical tomography

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