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Design and Analysis of Graphene Based Tunnel Field Effect Transistor with Various Ambipolar Reducing Techniques

computers, Materials & Continua 2023年第7期76卷 1309-1320页

作者： Puneet Kumar Mishra Amrita Rai Nitin Sharma Kanika Sharma Nitin Mittal Mohd Anul Haq Ilyas Khan ElSayed M.Tag El Din Department of Electronics and Communication Engineering G L Bajaj Institute of Technology and ManegmentGretear NoidaIndia Department of Electronics and Communication Engineering Chandigarh UnievrsityMohaliPunjabIndia Department of Electronics and Communication Engineering NITTTRChandigarhIndia University Center of Research&Development Chandigarh UniversityMohali121102India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah University11952Al-MajmaahSaudi Arabia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt

The fundamental advantages of carbon-based graphene material,such as its high tunnelling probability,symmetric band structure(linear dependence of the energy band on the wave direction),low effective mass,and characteristics of its 2D atomic layers,are the main focus of this research *** impact of channel thickness,gate under-lap,asymmetric source/drain doping method,workfunction of gate contact,and High-K material on Graphene-based Tunnel Field Effect Transistor(TFET)is analyzed with 20 nm *** modelling and electrical characteristic performance have been simulated using the Atlas device simulator of SILVACO TCAD with user-defined material syntax for the newly included graphene material in comparison to silicon carbide(SiC).The simulation results in significant suppression of ambipolar current to voltage characteristics of TFET and modelled device exhibits a significant improvement in subthreshold swing(0.0159 V/decade),the ratio of Ion/Ioff(1000),and threshold voltage(-0.2 V with highly doped p-type source and 0.2 V with highly doped n-type drain)with power supply of 0.5 V,which make it useful for low power digital applications.

关键词： Graphene tunnel field effect transistor(TFET) band to band tunnelling subthreshold swing

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Semantic Segmentation Based Real-Time Traffic Monitoring via Res-UNet Classifier and Kalman Filter

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SN computer science 2025年第1期6卷 1-17页

作者： Qureshi, Asifa Mehmood Algarni, Asaad Aljuaid, Hanan Alatiyyah, Mohammed Hamad Alnowaiser, Khaled Jalal, Ahmad Department of Creative Technologies Air University E-9 Islamabad 44000 Pakistan Department of Computer Sciences Faculty of Computing and Information Technology Northern Border University Rafha 91911 Saudi Arabia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Computer Science College of Sciences and Humanities in Aflaj Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia Department of Computer Engineering College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabia Department of Computer Science Air University E-9 Islamabad 44000 Pakistan

In computer vision, accurate vehicle recognition and tracking is a challenging research topic. Manual surveillance systems are cumbersome, labor-intensive, and inefficient in today's congested traffic environment. Automated traffic monitoring systems are needed in today's world because they provide potential solutions to these issues. However, there are still some challenges in automating these systems which need to be addressed. One of the challenges is the extraction of foreground from a complex environment that only contains vehicles along with spatial and temporal information. In this paper, a semantic segmentation-based foreground extraction model is proposed to overcome these challenges. After segmentation, a blob detection technique is applied to detect each vehicle. To overcome the issue of vehicle-to-vehicle occlusion we extracted Harris corner points and computed the separation line based on the vehicle geometry coordinates. Furthermore, we introduce an ID assignment mechanism based on VGG-16 extracted features. Based on the detections, the number of cars is also counted for each frame. For tracking, we first applied Farneback optical flow algorithm to detect motion in vehicles. Only those vehicles were passed to the tracking algorithm in which motion was detected. To estimate each vehicle's location in succeeding image frames Kalman filter was implemented. A vehicle reidentification and ID recovery module are also proposed to enhance the tracking outcome. Vehicle trajectories based on vehicle location midpoint were also estimated. Extensive experiments are used to validate the proposed system and achieved a precision score of 0.965 and 0.931 over Roundabout and AU-AIR datasets for vehicle detection. However, for vehicle tracking the precision is 0.948 over the Roundabout dataset and 0.839 for the AU-AIR dataset. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blob detection Detection and tracking Kalman filter Occlusion handling Res-Unet Semantic segmentation

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Storytelling in the Context of Education: A Pattern Language 23

Storytelling in the Context of Education: A Pattern Language

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Proceedings of the 28th European Conference on Pattern Languages of Programs

作者： Anja Bertels Dominik Deimel Faculty of Computer Science and Engineering Science Cologne University of Applied Sciences (TH Köln) Germany

ISBN: (纸本)9798400700408

Learning is a fundamental part of daily life across all ages. Educators and researchers continually seek new approaches to enhance its efficiency and overall experience. Therefore, knowledge transfer has been a well researched topic for several decades. One approach that has gained prominence is the use of Storytelling. In this paper, we define Storytelling and its implementations using pattern. The resulting pattern language aims to help educators create an optimal learning experience for each environment by addressing several adjustable factors.

关键词： Digital Storytelling Education Pattern Storytelling

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The development of virtual healing environment in VR platform 7

The development of virtual healing environment in VR platfor...

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Juliantino, Chris Nathania, Mega Putri Hendarti, Religiana Darmadi, Herru Suryawinata, Bonny A Architecture Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The purpose of this research is to build a healing environment that can be experienced through virtual reality (VR) to reduce stress levels of the user because of the lengthy period of COVID-19 pandemic that forced people to stay at home. The healing environment is created based on several theories on the principles of Healing Environments related to Architectural design. And as for the development of the simulation software, it is using the method of Extreme Programming that is based on Agile principle that combined with Architectural design flow. The VR is targeted to run optimally in low-end devices with cardboard and common Bluetooth controller so that it can be accessed inclusively. The evaluation is conducted using a user acceptance test with expert judgment and survey to 32 respondents. The findings are that they enjoyed the simulation because of the guidance is clear and the virtual environment looks more real compared to others that looks cartoonish. © 2022 Elsevier B.V.. All rights reserved.

关键词： Virtual reality

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Top-Down Cooling and its Role in Sustaining the Laugarnes Geothermal Field, Iceland

SSRN

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SSRN 2025年

作者： Bravo, Adolph Scott, Samuel Pálsson, Halldór Gunnarsson, Gunnar Faculty of Earth Sciences University of Iceland Iceland Faculty of Industrial Engineering Mechanical Engineering and Computer Science University of Iceland Iceland Orkuveitan Iceland

关键词： Geothermal fields

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A Reconfigurable Actuation Unit for Modular Cable-Driven Robots 16th

A Reconfigurable Actuation Unit for Modular Cable-Driven Rob...

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16th International Federation of Theory of Machines and Mechanisms World Congress, IFToMM WC 2023

作者： Chaparro-Rico, Betsy Dayana Marcela Russo, Matteo Cafolla, Daniele Independent Researcher Swansea United Kingdom Department of Industrial Engineering University of Rome Tor Vergata Via del Politecnico 1 Rome00133 Italy Faculty of Science and Engineering Department of Computer Science Swansea University Swansea United Kingdom

ISBN: (纸本)9783031457692

To address most of the cable-driven robot challenges, this work aims to create a fully modular, portable, customizable, adaptable, collaborative, and reconfigurable cable-driven robot. An actuation unit composed of a reconfigurable SP (Spherical-Parallel) serial architecture that manipulates a cable is the core of the proposed design. The proposed actuation unit can be connected in series with others and can collaborate in parallel with other units to control a load/end-effector position using multiple cables. Actuation units collaborating between them in parallel configuration can be connected to different reference frames such as chairs, tables, stretchers, and other shaped frames. The proposed modular design for cable-driven robots is ideal for performing tasks where scenarios and user requirements change, and the robot-obstacle and the robot-load/end-effector interaction are variable such as rehabilitation applications. The conceptual design of the proposed actuation unit is described in this paper. Simulations showed the feasibility of the proposed design. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cables

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Powering Next-Generation Wireless Communication With Cooperative Strategies

Powering Next-Generation Wireless Communication With Coopera...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Nair, Amrutha V Panduranga Rao, M.V. Agrawal, Trapty Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka 562112 India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350357769

Recent research has been focused on RF energy transmission and recovery as a potential strategy to greatly increase the lifespan of resource wireless networks. This method has the ability to remotely supply items with vitality that is comparatively steady and prolonged;as a result, it introduced a new methodological approach known as WPC, that had created numerous new research avenues with broad uses. In these, the creation and evaluation of effective joint plans has recently garnered a lot of study attention. The collaboration continuum communicating initiatives for behavioral connectivity networks, the collaborating crosstalk techniques forward into mobile broadband network security, and the explaining policies and procedures for wap data transmission are all highlighted in this article's general introduction of working in multiple approaches. Again once we wrap up this piece, we also highlight a number of intriguing study paths in this field. © 2023 IEEE.

关键词： Cognitive Radio Networks Collaborative Strategies Cooperative Jamming and Network Topologies Energy Harvesting Relay Selection Secure Communications Spectrum Sharing Wireless-Powered Communications Energy Transmission

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Brain-inspired artificial intelligence research: A review

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science China(Technological sciences) 2024年第8期67卷 2282-2296页

作者： WANG GuoYin BAO HuaNan LIU Qun ZHOU TianGang WU Si HUANG TieJun YU ZhaoFei LU CeWu GONG YiHong ZHANG ZhaoXiang HE Sheng Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Cyberspace Big Data Intelligent Security Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer and Information Science Chongqing Normal UniversityChongqing 401331China State Key Laboratory of Brain and Cognitive Science Institute of BiophysicsChinese Academy of SciencesBeijing 100101China School of Psychological and Cognitive Sciences Peking UniversityBeijing 100871China State Key Laboratory of Multimedia Information Processing School of Computer SciencePeking UniversityBeijing 100871China Department of Computer Science School of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Faculty of Electronic and Information Engineering Xi’an Jiaotong UniversityXi’an 710049China The Center for Research on Intelligent Perception and Computing Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Biophysics Chinese Academy of SciencesBeijing 100101China

Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.

关键词： artificial intelligence cognitive science brain science intelligence science large language model

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Deduction and Demonstration of Building Construction Carbon Emission Model Based on BIM Model 2

Deduction and Demonstration of Building Construction Carbon ...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Kuppusamy, Mudiarasan Abdullah, Syed Kadir Gowindasamy, Maniyarasi Raub, Noor Adila Abdul Al-Jawahry, Hassan M. Uma, N. Faculty of Business & Technology University of Cyberjaya Malaysia College of technical engineering The Islamic university Najaf Iraq Department of Computer Science & Engineering New Horizon College of Engineering Ring Road Bellandur Post Bengaluru560103 India

ISBN: (纸本)9798350305418

This study focuses on building construction carbon emission model based on BIM model, specific model deduction and practical application. In this study, the current construction life cycle carbon emission composition is mainly analyzed, and then the main calculation method of the construction life cycle carbon emission of the building is proposed. Based on this calculation and deduction process, a BIM-based carbon emission measurement model is established. In view of the corresponding calculation steps of carbon emission measurement in the application process of this model, the results of this study show that the BIM based carbon emission model of building construction can effectively complete the measurement of carbon emission coefficient. However, it will be affected by the architectural environment to a certain extent. Therefore, in further application, the variable and adaptability of the experimental results should be considered based on the differences between other regions. © 2023 IEEE.

关键词： BIM model construction carbon emission model deduction empirical

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Object Detection Using Coco Dataset

Object Detection Using Coco Dataset

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2022 International Conference on Cyber Resilience, ICCR 2022

作者： Jain, Swasti Dash, Sonali Deorari, Rajesh Kavita Chandigarh University Department of Computer Science Punjab Gharuan India Uttaranchal University Dehradun248007 India Sgt University Faculty of Computer Science and Engineering Gurugram122505 India

ISBN: (纸本)9781665461221

Object identification is the process of determining where articles appear in a given image (object confinement) and with which class each item belongs (object grouping). Because of item identification's cozy relationship with video examination and picture getting it, it has drawn in much exploration consideration as of late. Customary article recognition techniques are based on carefully assembled highlights and shallow teachable designs. To gain a comprehensive picture knowledge, we should concentrate on grouping similar images while also attempting to unequivo-cally assess the thoughts and regions of articles featured in each image. Object recognition comprises of perceiving, recognizing and finding objects with precision. I will distinguish the items with the assistance of coco dataset and python. COCO dataset is a huge scope object identification dataset distributed by Microsoft. AI and computer Vision designs famously utilize the COCO dataset for different PC vision projects. Discovery of the item will be finished by two assignment for example Grouping and Detection. Grouping remembers one class of items though recognition yields a square shape, additionally called jumping box to portray where the articles are available. Course classifier is being utilized in grouping the articles. Roughly 87 % of exactness is accomnlished. © 2022 IEEE.

关键词： Object detection

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