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Evaluating Topological Insulator-Based FETs in Circuit-Level Performance with Advanced Device Simulations

Evaluating Topological Insulator-Based FETs in Circuit-Level...

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2023 international conference on Power Energy, Environment and intelligent control, PEEIC 2023

作者： Karthik, A. Asha, V. Ramu, T. Bhargava Sharma, Rupa Rani Nijhawan, Ginni Mohsen, Zahraa Salem Institute of Aeronautical Engineering Hyderabad Dundigal India New Horizon College of Engineering Department of Computer Applications Bangalore India Mlr Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Gl Bajaj Institute of Technology & Management Dept. of Ash U.P. Greater Noida India Lovely Professional University Phagwara India College of Engineering Technology National University of Science and Technology Dhi Qar Iraq

ISBN: (纸本)9798350357769

In recent years., topological insulators (TIs) have emerged as a promising material class in the realm of advanced electronic devices due to their unique electronic properties. This paper presents a comprehensive evaluation of Field-Effect Transistors (FETs) based on topological insulators through advanced device simulations to understand their potential in circuit-level applications. We have employed state-of-the-art simulation tools to model the behavior of TI-based FETs under various operating conditions and benchmarked their performance against conventional semiconductor-based FETs. Our results indicate that TI-based FETs exhibit superior switching characteristics., reduced leakage currents., and enhanced thermal stability. Furthermore., the inherent spin-momentum locking property of TIs introduces a new dimension in device design., paving the way for spintronic applications. The study also highlights the challenges associated with integrating TI-based FETs in conventional circuits., such as interface quality and material purity. In conclusion., while topological insulator-based FETs hold significant promise for next-generation electronics., meticulous material engineering and device optimization are crucial for their successful integration into mainstream circuitry. © 2023 IEEE.

关键词： Advanced Device Simulations Circuit-Level Performance Field-Effect Transistors Spintronics. Top of Form Topological Insulators

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Current Status and Consideration of Entrepreneurship Education for engineering Major Students at National Institute of Technology, Tsuruoka College 28th

Current Status and Consideration of Entrepreneurship Educati...

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28th international conference on Knowledge Based and intelligent information and engineering Systems, KES 2024

作者： Kurata, Karin Yajima, Kuniaki Sato, Jun National Institute of Technology Tsuruoka College Tsuruoka997-8511 Japan National Institute of Technology Sendai College Sendai989-3128 Japan

This paper introduces and examines the status of students' perception of entrepreneurship education at the National Institute of Technology, Tsuruoka College. This research aims to identify and consider the factors that influence the development of entrepreneurship intention. The significance of this paper is conducting a study of students who aim to become engineers since most of the entrepreneurship education discussion happens in the field of business. Based on the theory of planned behavior, this study will conduct multiple regression analysis using SPSS software to identify the relationship between attitude, subjective norm, and perceived behavioral control with entrepreneurship intention. Results indicated that there were significant and positive effects of attitude and perceived behavior control toward entrepreneurship intention. However, there were no significant effects shown by the subjective norm. These results indicate that when conducting entrepreneurship education for students who study engineering, it is important to focus on fostering students' attitudes and perceived behavior control. The theoretical implication is that we have extended the theory of planned behavior to examine students who are studying science and engineering from the age of 15. The practical implication of this study is that it is important to foster perceived behavior control. This study will support policymakers, educators, and researchers to foster entrepreneurship education in the engineering field. © 2024 The Authors.

关键词： Students

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AI-Powered 6G Networks: Transforming Wireless Communication with Intelligence and Terahertz Waves

AI-Powered 6G Networks: Transforming Wireless Communication ...

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2025 international conference on intelligent control, Computing and Communications, IC3 2025

作者： Singh, Navdeep Devi, Runumi Singh, Jay Rajalakshmi, B. Mohammed, Mohammed Wael Thandra, Nagarjuna Vidyadhari, Chalasanvi Lovely Professional University Phagwara India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India Gl Bajaj Institute of Technology and Management Dept. of Eee U.P. Gr. Noida India New Horizon College of Engineering Department of Computer Science Engineering Bangalore India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Griet Department of Information Technology Bachupally Telangana Hyderabad India

ISBN: (纸本)9798331527495

From 2027 to 2030, Sixth Generation (6G) wireless communication systems are expected to be launched to revolutionize human and machine interaction with ultra fast data transmission speeds and low, or virtually zero latency communication. In this paper, we investigate the transformative potential of 6G networks enabled by AI, and describe key 6G network technologies, including artificial intelligence (AI), machine learning (ML), and sub miiitter wave technology. In addition to being able to exceed 5G Maximum Throughput (MT), 6G is forecast to enable advanced applications including holographic communications, XR (extended reality), and ubiquitous M2M (machine to machine) interaction. Although significant obstacles remain with respect to security, energy efficiency, and spectrum management. In this paper, 5G development existing gaps are identified, and a comprehensive AI driven framework for resource allocation, latency reduction, and spectrum utilization optimization is proposed for 6G systems. This study further explores the position of edge computing, IoT integration, and AI powered network security protocols. Finally, we demonstrate real world applications, such as smart healthcare, autonomous vehicles, and space communications, discussing privacy and sustainability aspects of 6G technology. © 2025 IEEE.

关键词： Resource allocation

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Nature-Inspired Hybrid Virtual Machine Placement Approach in Cloud

Nature-Inspired Hybrid Virtual Machine Placement Approach in...

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international conference on advances in Data-driven Computing and intelligent Systems, ADCIS 2022

作者： Bhatt, Chayan Singhal, Sunita Department of Computer Science Engineering Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9789819932498

Many nature-inspired, swarm intelligent, and hybrid algorithms have been designed to figure out an optimal virtual machine (VM) placement solution. In this paper, a hybridized intelligent water drop cycle algorithm (IWCDA) has been proposed that aims to achieve better resource utilization and minimum energy consumption in cloud datacenters. The algorithm works in two phases. First, intelligent water drop (IWD) is adapted to construct an efficient VM placement solution by using its unique heuristic function. In the second phase, the water cycle algorithm (WCA) is applied to bring out the best solution for the VM placement problem. At the end, the solutions of both phases are compared and the best one is taken as an optimal VM placement solution after undergoing several iterations. Energy and resource aware schemes are involved in selecting suitable physical machines (PM) for respective VM in both phases, respectively. The proposed work has been implemented on MATLAB, and simulation results have shown that IWDCA performed better as compared to IWD and WCA by 4% and 7%, respectively, in terms of energy consumption, number of active servers, and resource utilization rate. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Virtual machine

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TOGAF-based Enterprise Architecture Framework for Utilizing Artificial Intelligence 10

TOGAF-based Enterprise Architecture Framework for Utilizing ...

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10th international conference on computer, control, Informatics and its Applications, IC3INA 2023

作者： Fitriani, Leni Khodra, Masayu Leylia Surendro, Kridanto Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350394870

TOGAF (The Open Group Architecture Framework) has become a fundamental guideline in developing integrated enterprise architecture. At the same time, artificial intelligence is an increasingly important technology in supporting an organization's digital transformation. Integrating Artificial Intelligence has become the key to increasing organizational competitiveness in this digital transformation era. However, there are several problems with implementing artificial intelligence in enterprise architecture. Existing research focuses only on one or two significant domains of enterprise architecture. Based on the TOGAF framework, this research contributes to designing an enterprise architectural framework that utilizes artificial intelligence in all of these domains, and the aim is to provide a guide that organizations can use in utilizing AI to accelerate their digital transformation, increase efficiency, and achieve better business goals. Further research could explore practical implementation and further evaluation of this framework to support the development of more intelligent and more adaptive enterprise architectures. © 2023 IEEE.

关键词： Artificial intelligence

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Distributed Analytics in Smart Grids with Edge Computing and Computational Intelligence

Distributed Analytics in Smart Grids with Edge Computing and...

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2023 international conference on Power Energy, Environment and intelligent control, PEEIC 2023

作者： Joshi, Apoorva Preethi, D. Gill, Amandeep Noida Institute of Engineering & Technology Master of Computer Application Uttar Pradesh Greater Noida India Department of Computer Science Bangalore India Vivekananda Global University Department of R&d Cell Jaipur India

ISBN: (纸本)9798350357769

Conventional methods like classification or clustering have limits when it comes to handling the complex task for dispersed data mining across heterogeneous sources and divergent data formats. This is especially true in scenarios where stochastic models or mathematical formulas may not be feasible. Data centralization is a prevalent trend that exacerbates problems including communication channel congestion and privacy difficulties related to sensitive data flows. In order to overcome these obstacles, this paper presents the Distributed Academic Engine (DAE), an adaptive edge-based scattered analytic engine designed for distributed networks. The DAE routinely breaks down and divides computations that need data from multiple sources among the nodes that are already in place, enabling the sharing of partial results without disclosing the original data. To get the full expression output, the master node combines these partial results. The expression is decomposed and processing jobs are distributed among nodes using three computational intelligence techniques: genetic algorithm, genetic algorithm using evolution control, the particle swarm optimization. This method's effectiveness is illustrated with a case study on smart grid KPI identification, which shows a noteworthy (over 91%) decrease in communication messages over conventional approaches. This demonstrates how well the suggested method works to reduce the difficulties related to distributed data mining. © 2023 IEEE.

关键词： Computational Intelligence Data Integration and Heterogeneous Data Source Integration Distributed Analytics Edge Computing Genetic Algorithm Particle Swarm Optimization Smart Grid

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Rolling Horizon Co-evolution for Snake AI Competition 13th

Rolling Horizon Co-evolution for Snake AI Competition

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13th IFIP TC 12 international conference on intelligent Information Processing, IIP 2024

作者： Li, Hui Zhou, Jiayi Zhang, Qingquan Research Institute of Trustworthy Autonomous System Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9783031578076

The Snake game, a classic in the gaming world, gains new dimensions with the Snake AI competition, where two players controlled by AI algorithms can now compete simultaneously in the same game session. This competition holds significance in advancing our understanding of artificial intelligence (AI) algorithms. In the 2020 and 2021 Snake AI competitions, popular algorithms, using graph-based search or heuristic strategies, demonstrate competitive performance, such as the A* algorithm, Monte Carlo Tree Search (MCTS). Contrary to these heuristic approaches, the Rolling Horizon Co-evolution Algorithm (RHCA), characterised by its core principles of rolling horizon evaluation and co-evolution, maintains two populations, one for each player, to co-evolve with each other without reliance on heuristics. RHCA has been verified its effectiveness in a two-player spaceship game. In this paper, we extend the RHCA application to the two-player Snake AI game, comparing it with other state-of-the-art methods. Additionally, we introduce various obstacles to create different complex scenarios, ensuring a comprehensive analysis. Experimental results reveal RHCA’s superior and stable performance, especially in resource-constrained and complex scenarios. Furthermore, an analysis of RHCA’s behaviours across maps with diverse obstacle scenarios highlights its ability to make intelligent decisions in competing with state-of-the-art methods. © IFIP international Federation for Information Processing 2024.

关键词： Trees (mathematics)

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intelligent Infrared Thermometer of Transmission Line UAV Based on Multi-Sensor Cooperative Detection

Intelligent Infrared Thermometer of Transmission Line UAV Ba...

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advances in Electrical engineering and computer Applications( AEECA), 2020 IEEE international conference on

作者： Wendong Shi Yongsheng Cheng Chuncheng Han Da Wang Yuan Gao Ultra-High Voltage Company of State Grid Jilin Electric Power Co. Ltd Changchun Jilin China

As an important part of the power system, whether the transmission line can be safe, smooth operation, related to the smooth development of the national economy. However, with the intensification of power grid maintenance, the traditional manual inspection of transmission lines can no longer meet the requirements of efficient power grid inspection. Therefore, the State Grid Corporation vigorously promotes UAV line inspection across the application of robots, drones and other intelligent equipment to carry out real-time data acquisition and state monitoring of power facilities, find defects in time, and effectively promote the efficiency of power maintenance and overhaul. Based on this, the research goal of this paper is the application of UAV intelligent technology in transmission line detection. Using the non-contact and non-destructive properties of infrared thermometer technology, a inspection scheme of transmission line based on infrared thermometer as the core and pan-tilt-head control system is proposed. The intelligent detection system mainly includes an airborne detection system and a ground control system. The detection image of the airborne detection system can be transmitted to the ground control system in real time, and the ground control system sends control instructions to the airborne detection system through the wireless communication module. The experiment shows that the infrared detection is used to measure the temperature of the transmission line, and the multiple linear regression model is used to establish the predicted value of the transmission line temperature with the reference of current, ambient temperature and voltage. Compared with the actual measured value of the transmission line temperature, the overall error of the system is only 0.3%, which shows that the error of the transmission line temperature collected by the infrared temperature sensor is very small.

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StyleEditorGAN: Transformer-Based Image Inversion and Realistic Facial Editing 11

StyleEditorGAN: Transformer-Based Image Inversion and Realis...

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11th international conference on Dependable Systems and Their Applications, DSA 2024

作者： Hu, Jing Zhang, Xinsheng Hubei University School of Computer Science and Information Engineering Wuhan China

ISBN: (纸本)9798331532390

Recent advances in StyleGAN research have shown significant progress in semantic disentanglement. While controlled editing of facial images has been achieved to some extent, attaining highly controllable attribute editing remains a challenging task. Existing GAN inversion methods require a trade-off between reconstruction fidelity and editing quality. To further investigate facial attribute editing, dual-space GANs have been employed to better disentangle style and content representations. However, these methods still struggle to achieve precise, highly controllable editing results for complex attributes. In response, this paper introduces a novel model, StyleEditorGAN, designed to enable more accurate and intricate attribute control. The proposed model presents an innovative dual-space editing and GAN inversion approach, emphasizing the significance of interaction within dual-space GANs, and leverages a Transformer framework to enhance this interaction for more precise and controllable editing. Extensive experiments on the CelebA-HQ and FFHQ datasets demonstrate the superiority of the proposed StyleEditorGAN model in image reconstruction quality, editing capability, and flexible style transfer, underscoring its effectiveness in highly controllable facial editing. © 2024 IEEE.

关键词： Image reconstruction

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intelligent Network Traffic control with AI and Machine Learning 16

Intelligent Network Traffic Control with AI and Machine Lear...

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16th IEEE international conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Shetty, Sweekrithi Thrisha, M.S. Vandana, H.M. Shaikh, Rizawan N Alva's Institute of Engineering and Technology Department of Computer Science Mangalore India

ISBN: (纸本)9798331505264

Given the rising complexity in communication networks and data traffic, novel strategies are badly needed to handle the effective transmission of data, especially in a broadcasting scenario where reliability comes into prime focus. The paper discusses how AI and ML can particularly be a panacea for solving such challenges. We start with traditional approaches like static routing and traffic shaping, which already aren't relevant in the face of more contemporary AI based solutions. AI and ML algorithms can predict congestion on the network and automatically find the most effective routes so that efficiency is optimized without any human intervention. To tackle this issue more concretely, several use cases from the telecommunications and content distribution networks are illustrated regarding how AI/ML is already making a difference in optimizing bandwidth, eliminating lag times, and providing stable internet connections for services such as video calls. However, AI/ML systems challenge the control of gigantic data and obtaining user's trust. Tomorrow, we find the potential for AI to autonomously run networks, particularly when new technologies like 5G and 6G are released. © 2024 IEEE.

关键词： Quality of service

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