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SSRN 2024年

作者： Saxena, Sanjay Panda, Soumyaranjan Tiwari, Ekta Singh, Rajesh Fouda, Mostafa M. Kalra, Mannudeep K. Kotecha, Ketan Saba, Luca Suri, Jasjit S. Department of Computer Science & Engineering International Institute of Information Technology Odisha Bhubaneswar India Department of Computer Science & Information Technology Mahatma Gandhi Central University Bihar India Department of Computer & Engineering Visvesvaraya National Institute of Technology Maharashtra Nagpur India Department of Research and Innovation Uttaranchal Institute of Technology Uttaranchal University Dehradun248007 India Department of Electrical and Computer Engineering Idaho State University PocatelloID83209 United States Department of Radiology Massachusetts General Hospital BostonMA United States Symbiosis centre for Applied Artificial Intelligence Symbiosis Institute of Technology Symbiosis International University Pune India Cagliari Italy Department of ECE Idaho State University PocatelloID83209 United States Department of CE Graphics Era Deemed to be University Dehradun248002 India University Center for Research & Development Chandigarh University Mohali India Pune India Stroke Diagnostic and Monitoring Division AtheroPoint RosevilleCA95661 United States Harvard Medical School United States University Hospital of Cagliari Italy

This comprehensive review presents the role of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in neuro-oncology, focussing their groundbreaking impact on the field. It gives a historical overview of AI's evolution in area of neuro-oncology, representing its progress from basic data management to high-level predictive analytics that now significantly makes personalized treatment ***, This study examines various ML based methods that emphasize brain tumor classification, genetic profiling, and individualized care plans proposals, which basically reflects the shift towards precision medicine. This paper also highlights, developments in DL particularly in the development of neuro-imaging analysis, which has significantly guided surgical planning and radiation therapy for improved patient outcomes. Through various case studies, the paper presents recent breakthroughs where AI interventions have noticeably enhanced the treatment of neuro-oncological conditions. Moreover, It also addresses the ethical considerations encompassing the use of automated decision-making tools, emphasizing the need for ethical governance in AI deployment. By integrating multidisciplinary perspectives, the study underscores the collaborative effort between clinicians, data scientists, and ethicists, which is very crucial for the ethical and effective implementation of AI in current clinical practice. The main aim of discussion is to equip neurooncologists/sergeons and doctors with understandings into sustainable AI adoption which ensures that AI's path in neuro-oncology aligns with both clinical needs for personalized medicine and ethical *** paper concludes by outlining considered methods and frameworks for the future integration of AI in neuro-oncology, predicting trends, and preparing to meet the challenges ahead. © 2024, The Authors. All rights reserved.

关键词： Personalized medicine

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Advanced Development On Real Time Monitoring Of Bridges Using Wireless Fidelity

Advanced Development On Real Time Monitoring Of Bridges Usin...

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International Conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： D. Ferlin Deva Shahila Valantina Stephen L. Padma Suresh Ashwini. A Shally. S. P Anushia R M Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of EEE Saveetha School of Engineering Thandalam Chennai India Computer Science and Engineering Baselios Mathews II College of Engineering Kollam Department of ECE DMI College of Engineering Chennai India Department of CSE DMI College of Engineering Chennai India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

Wireless fidelity technology enables communication without the use of wires or connections between two or more people across large distances. Wireless technology encompasses communications that utilize both radio frequencies (RF) and infrared waves. The origin of wireless technology can be traced back to the invention of electromagnetic waves by the German physicist, geophysicist, and engineer, Heinrich Hertz. In the late nineteenth century, the commercial wireless telegraph service was established by the Italian entrepreneur Gugliello Marconi, more than half a century after the invention of the first commercially available wired telegraph in 1832. In the early twentieth century, Marconi was one of the pioneers of radio communications, transmitting radio signals to mobile receivers on ships. Wireless has always been more advanced than wired technology, and it's usually more expensive too, but it's also given us the added benefit of being able to move around and get and send *** this project, we'll be using MATLAB software to design and test the full model. We'll also be looking at wireless bridge health monitoring systems. ZigBee acts as the wireless network for short-range IEEE 802.11 communication between sensors in the bridge.

关键词： Wireless sensor networks Technological innovation Wireless networks Wires Bridge circuits Zigbee Receivers

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Exploring Cognitive Decline in Hypertension: A Deep Learning Approach to Meningeal Interleukin-17-Producing T Cells in Mice

Exploring Cognitive Decline in Hypertension: A Deep Learning...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Praveen Priyanka Gupta B Rajalakshmi Ginni Nijhawan Neha Kumari Hussein Ali Kadhim Kyhoiesh Knowledge Park II Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh Institute of Aeronautical Engineering Dundigal Hyderabad Department of Computer Science New Horizon College of Engineering Bangalore Lovely Professional University Phagwara AP Dept. of CSE St. Martin’s Engineering College Secunderabad Telangana India College of Health and Medical Technology National University of Science and Technology Dhi Qar Iraq

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

A deep learning approach that targets meningeal interleukin-17-producing T cells is used to research cognitive loss in high blood pressure patients. A detailed ablation study examined and rated each aspect of our recommended procedure. Including cellular activities was crucial since excluding them reduced accuracy. These elements are crucial to high blood pressure-related cognitive impairment. The deep learning model’s layers worked effectively together to uncover complicated data patterns, as shown by removing some layers. Model complexity and computer time trade-offs were found, which can aid future improvements. In conclusion, our deep learning approach appears to be a promising tool to study how elevated blood pressure affects brain function. The ablation investigation proves the procedure works and reveals key components’ responsibilities. This allows for more modifications and breakthroughs. This research helps us understand brain illnesses, including high blood pressure-related memory loss. It also sets the framework for innovative diagnosis and treatment methods. This study’s deep learning and immunology discoveries might revolutionize high blood pressure-related cognitive impairment research and treatment.

关键词： Deep learning Technological innovation Immunology Computational modeling Cells (biology) Brain modeling Blood pressure

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Construction of Efficient Authenticated Key Agreement Protocol for Intelligent Transportation System

Construction of Efficient Authenticated Key Agreement Protoc...

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Electronic Information Technology and Smart Agriculture (ICEITSA), International Conference on

作者： Kiranbala Nongthombam Saurabh Rana Mohammad S. Obaidat Deepak Chhikara Dheerendra Mishra Department of Mathematics Chandigarh University Mohali Punjab India Computer Science Department and Director of CybersecurityCenter University of Texas-Permian Basin Odessa TX USA King Abdullah II School of Information Technology University of Jordan Amman Jordan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Mathematics / Bioinformatics and Computer Applications Maulana Azad National Institute of Technology Bhopal India

ISBN: (纸本)9781665464024

To enable intelligent transportation systems, the Internet of Vehicles (IoV) uses wireless communications between roadside units, onboard units), phones, and other gadgets within a vehicle to deliver a new convenient, comfortable, and safe driving experience. IoV is now more exposed and frequently targeted because of its greatly increased reliance on wireless communication, control, and computer technology, To put it another way, an adversary may target such an open channel to intercept, change, inject malicious messages, or erase loaded data. This could lead to replay, impersonation, middle attack, privileged insider, and other related attacks. An authentication protocol should strive to accomplish security, anonymity, and untraceability among other critical aspects. In this research, we suggest a brand-new key agreement and mutual authentication methodology for IoV powered Intelligent transportation system (ITS). We demonstrate that our suggested system is secure against several known threats in IoV- the enabled ITS environment. Furthermore, a thorough comparison of our proposed system to eight other competing ones reveals that it has the lowest communication and computational costs. In addition, it is more secure and provides more functionality characteristics.

关键词： Wireless communication Smart agriculture Electric potential Protocols Costs Authentication Transportation

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A Survey on computer Vision based Human Analysis in the COVID-19 Era

arXiv

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arXiv 2022年

作者： Eyiokur, Fevziye Irem Kantarcı, Alperen Erakın, Mustafa Ekrem Damer, Naser Ofli, Ferda Imran, Muhammad Križaj, Janez Salah, Albert Ali Waibel, Alexander Štruc, Vitomir Ekenel, Hazım Kemal Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Department of Computer Engineering Istanbul Technical University Istanbul Turkey Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany Qatar Computing Research Institute HBKU Doha Qatar Faculty of Electrical Engineering University of Ljubljana Tržaška cesta 25 Ljubljana1000 Slovenia Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Department of Computer Engineering Boğaziçi University Istanbul Turkey Carnegie Mellon University Pittsburgh United States

The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced around the world to limit the transmission of the disease, including face masks, mandates for social distancing and regular disinfection in public spaces, and the use of screening applications. These developments also triggered the need for novel and improved computer vision techniques capable of (i) providing support to the prevention measures through an automated analysis of visual data, on the one hand, and (ii) facilitating normal operation of existing vision-based services, such as biometric authentication schemes, on the other. Especially important here, are computer vision techniques that focus on the analysis of people and faces in visual data and have been affected the most by the partial occlusions introduced by the mandates for facial masks. Such computer vision based human analysis techniques include face and face-mask detection approaches, face recognition techniques, crowd counting solutions, age and expression estimation procedures, models for detecting face-hand interactions and many others, and have seen considerable attention over recent years. The goal of this survey is to provide an introduction to the problems induced by COVID-19 into such research and to present a comprehensive review of the work done in the computer vision based human analysis field. Particular attention is paid to the impact of facial masks on the performance of various methods and recent solutions to mitigate this problem. Additionally, a detailed review of existing datasets useful for the development and evaluation of methods for COVID-19 related applications is also provided. Finally, to help advance the field further, a discussion on the main open challenges and future research direction is given at the end of the survey. This work is intended to have a broad appeal and be useful not only for comp

关键词： COVID-19

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Real-time Settings and Their Transformation through Distributed Intelligence Communication Technologies

Real-time Settings and Their Transformation through Distribu...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Manjunatha M Hari Krishna Vijay Kumar Rai Navdeep Singh Ashwani Kumar Mohammed I. Habelalmateen Department of Mechanical Engineering New Horizon College of Engineering Bangalore Institute of Aeronautical Engineering Dundigal Hyderabad India Department of Computer Science & Engineering IES College of Technology Bhopal M. P India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Greater Noida Uttar Pradesh The Islamic university Najaf Iraq

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

Modern real-time settings and dispersed intelligence communication technologies require new solutions to improve efficiency, flexibility, and scalability. This research introduces dynamic edge-cloud orchestration for real-time intelligence. The approach uses the Dynamic Task Allocation Algorithm (DTAA), the Predictive Resource Scaling Algorithm (PRSA), and the Adaptive Communication Routing Algorithm. DTAA distributes work between edge devices and the cloud based on priority, processing time, and resources. PRSA estimates future resource needs, making edge and cloud scaling easier. ACRA adjusts communication routes based on latency, job priority, and network circumstances. We use numbers to compare the new strategy to six popular ones. These include SDA, TFA, RBI, FBA, and PRT. The proposed option outperforms the others in latency, scalability, security, reliability, freedom, and resource utilization. Due to its comprehensive framework for smart task assignment, resource management, and communication enhancement, DECO-RTI is a major advance in real-time settings. The approach can adapt to changing situations and automatically scale up resources, making it ahead of the curve for distributed intelligent communication systems.

关键词： Heuristic algorithms Scalability computer network reliability Prediction algorithms Routing Dynamic scheduling Real-time systems

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Expected and unexpected routes to synchronization in a system of swarmalators

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Physical Review E 2024年第6期110卷 L062301-L062301页

作者： Steve J. Kongni Thierry Njougouo Patrick Louodop Robert Tchitnga Fernando F. Ferreira Hilda A. Cerdeira Research Unit Condensed Matter Electronics and Signal Processing University of Dschang P.O. Box 67 Dschang Cameroon Dschang Cameroon IMT School for Advanced Studies 55100 Lucca Italy Faculty of Computer Science and Namur Institute for Complex Systems (naXys) University of Namur 5000 Namur Belgium Department of Electrical and Electronic Engineering Faculty of Engineering and Technology (FET) University of Buea Buea Cameroon ICTP South American Institute for Fundamental Research São Paulo State University (UNESP) Instituto de Física Teórica Rua Doutor Bento Teobaldo Ferraz 271 Bloco II Barra Funda 01140-070 São Paulo Brazil Department of Physics-FFCLRP University of São Paulo Ribeirao Preto 14040-901 São Paulo Brazil São Paulo State University (UNESP) Instituto de Física Teórica Rua Doutor Bento Teobaldo Ferraz 271 Bloco II Barra Funda 01140-070 São Paulo Brazil Epistemic Gomez & Gomez Ltda. Micro Empresa (ME) Rua Paulo Franco 520 Vila Leopoldina 05305-031 São Paulo Brazil

Systems of oscillators whose internal phases and spatial dynamics are coupled, swarmalators, present diverse collective behaviors which in some cases lead to explosive synchronization in a finite population as a function of the coupling parameter between internal phases. Near the synchronization transition, the phase energy of the particles is represented by the XY model, and they undergo a transition which can be of the first order or the second depending on the distribution of natural frequencies of their internal dynamics. The first-order transition is obtained after an intermediate state (static wings phase wave state) from which the nodes, in cascade over time, achieve complete phase synchronization at a precise value of the coupling constant. For a particular case of natural frequencies distribution, a new phenomenon, the rotational splintered phase wave state, is observed and leads progressively to synchronization through clusters switching alternatively from one to two and for which the frequency decreases as the phase coupling increases.

关键词： Collective behavior in networks Dynamics of networks Network phase transitions Synchronization transition

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Reliability-Redundancy Optimization of an Overspeed Protection System of a Gas Turbine by Modified Wild Horse Optimizer

Reliability-Redundancy Optimization of an Overspeed Protecti...

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Disruptive Technologies (ICDT), International Conference on

作者： Shshank Chaube Sangeeta Pant B.P. Joshi Anuj Kumar Manoj K. Singh Ketan Kotecha Department of Physical Sciences Jaypee University Anoopshar Uttar Pradesh India Department of Applied Sciences Symbiosis Institute of Technology Symbiosis International (Deemed University) (SIU) Lavale Pune Maharashtra India Department of Mathematics Graphic Era Hill University Bhimtal India School of Computer Science Engg. & Applications D. Y. Patil International University (DYPIU) Akurdi Pune India School of Computer Science Engineering and Technology Bennett University Techzone II Greater Noida Uttar Pradesh India Symbiosis Institute of Technology Symbiosis International (Deemed University) (SIU) Lavale Pune Maharashtra India

This article addresses the persistent challenges involved in the complex system reliability redundancy optimization of the overspeed protection system of a gas turbine (OPSGT), which is an essential complex system for ensuring the turbine's safety. The optimal functionality of this complex reliability-redundancy is achieved by means of a novel nature-inspired computational approach named the Modified Wild Horse Optimization Algorithm (MWHO), inspired by the behavior of wild horses. The MWHO algorithm efficiently delivers optimal solutions to this complex NP-hard problem, showcasing its potential in solving various complex system reliability optimization problems. This efficiency is easily verified through extensive numerical simulations, demonstrating that the outcomes produced by MWHO exhibit outstanding performance when compared to various existing metaheuristics. Hence, the MWHO not only introduces a fresh perspective in tackling associated reliability-redundancy optimization challenges but also establishes itself as a competitive and efficient algorithm in the complex realm of system reliability optimization.

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Efficient dataflow modeling of peripheral encoding in the human visual system

arXiv

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arXiv 2021年

作者： Brown, Rachel Dutell, Vasha Walter, Bruce Rosenholtz, Ruth Shirley, Peter McGuire, Morgan Luebke, David NVIDIA Research Vision Science UC Berkeley Computer Graphics Cornell University Brain and Cognitive Sciences CSAIL Massachusetts Institute of Technology NVIDIA Research

computer graphics seeks to deliver compelling images, generated within a computing budget, targeted at a specific display device, and ultimately viewed by an individual user. The foveated nature of human vision offers an opportunity to efficiently allocate computation and compression to appropriate areas of the viewer's visual field, especially with the rise of high resolution and wide field-of-view display devices. However, while the ongoing study of foveal vision is advanced, much less is known about how humans process imagery in the periphery of their vision-which comprises, at any given moment, the vast majority of the pixels in the image. We advance computational models for peripheral vision aimed toward their eventual use in computer graphics. In particular, we present a dataflow computational model of peripheral encoding that is more efficient than prior pooling-based methods and more compact than contrast sensitivity-based methods. Further, we account for the explicit encoding of "end stopped" features in the image, which was missing from previous methods. Finally, we evaluate our model in the context of perception of textures in the periphery. Our improved peripheral encoding may simplify development and testing of more sophisticated, complete models in more robust and realistic settings relevant to computer graphics. © 2021, CC BY.

关键词： Budget control

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Modeling flux tunability in Josephson Traveling Wave Parametric Amplifiers with an open-source frequency-domain simulator

arXiv

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arXiv 2024年

作者： Levochkina, A. Chatterjee, I. Darvehi, P. Ahmad, H.G. Mastrovito, P. Massarotti, D. Montemurro, D. Tafuri, F. Pepe, G.P. O’Brien, Kevin P. Esposito, M. Department of Physics University Federico II Naples80126 Italy CNR-SPIN Complesso di Monte S. Angelo Via Cintia Napoli80126 Italy Department of Electrical Engineering and Information Technology University Federico II Naples80125 Italy CNR INO Largo Enrico Fermi 6 Florence50125 Italy Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

Josephson Traveling Wave Parametric Amplifiers (JTWPAs) are integral parts of many experiments carried out in quantum technologies. Being composed of hundreds of Josephson junction-based unit cells, such devices exhibit complex nonlinear behavior that typically cannot be fully explained with simple analytical models, thus necessitating the use of numerical simulators. A very useful characteristic of JTWPAs is the possibility of being biased by an external magnetic flux, allowing in-situ control of the nonlinearity. It is therefore very desirable for numerical simulators to support this feature. Open-source numerical tools that allow to model JTWPA flux biasing, such as WRSPICE or PSCAN2, are based on time-domain approaches, which typically require long simulation times to get accurate results. In this work, we model the gain performance in a prototypical flux-tunable JTWPA by using ***, a recently developed frequency-domain open-source numerical simulator, which has the benefit of simulation times about 10,000 faster than time-domain methods. By comparing the numerical and experimental results, we validate this approach for modeling the flux dependent behavior of JTWPAs. Copyright © 2024, The Authors. All rights reserved.

关键词： Frequency domain analysis

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