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Diamagnetically Levitated and Trapped Graphite Mechanical Resonators 38

Diamagnetically Levitated and Trapped Graphite Mechanical Re...

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38th ieee international conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Wang, Yunong Gage, Alexander Lee, Jaesung Feng, Philip X.-L. University of Florida Herbert Wertheim College of Engineering Department of Electrical and Computer Engineering GainesvilleFL32611 United States University of Central Florida College of Engineering & Computer Science Department of Electrical and Computer Engineering OrlandoFL32816 United States

ISBN: (纸本)9798331508890

We report on studying diamagnetic levitation and rigid body resonances of millimeter- to centimeter-scale trapped graphite mechanical resonators, by combining theoretical analysis with experimental demonstrations. Harnessing the strong diamagnetic susceptibility of pyrolytic graphite, we demonstrate stable levitation of square graphite thin plates with varying dimensions and masses above permanent magnets, without the need of active control. The resonance motions are excited by dielectric gradient forces and detected via an ultrasensitive optical interferometry system at room temperature. We observe rigid body resonance modes with frequencies between 25 Hz and 50 Hz and with their quality (Q) factors from 30 to 70. The Q factors are primarily constrained by air damping and eddy current damping. This work represents an initial step toward developing high-stability, anchor-less levitating resonant systems with large masses, paving the way for high-performance resonant sensors with minimal energy dissipation and exceptional thermal and mechanical isolation with very small power consumption. © 2025 ieee.

关键词： Damping

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Augmenting Human Decision-Making: Exploring AI-Driven automation in IT Operations (AIOps) for Enhanced Efficiency and Innovation 4

Augmenting Human Decision-Making: Exploring AI-Driven Automa...

引用

4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Lakshmi Kumar, Tukkisetty Vasantha Naresh, Tippa Ganesh, Chunduru Saran Varma, Chekuri Tarun Raju, K.V. Hema, Chindu Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9798331523923

This article analyzes how artificial intelligence (AI) has changed the IT industry, ushering in an age of unmatched technical growth and new potential for human-AI communication. Through a detailed research, it explores the complex dynamics of AI integration in IT operations, examining the likelihood that AI may supplant people in the workforce and highlighting the complexities and challenges that accompany this paradigm change. By examining present AI technologies, such as machine learning, deep learning, natural language processing, and data science, and emphasizing both the benefits and imminent obstacles, this article discusses the complex environment of AI adoption in IT. It also digs thoroughly into the legal frameworks, social repercussions, and ethical challenges that must be overcome in order to govern the AI-driven revolution of the IT industry. Through this research, the article wants to peacefully cohabit human knowledge with AI talents, opening up new paths for creativity, productivity, and sustainable development in the digital age. © 2025 ieee.

关键词： Adversarial machine learning

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Innovative Approach for Early Heart Disease Prediction: Gaussian Mixture Model and K-Nearest Neighbour 3

Innovative Approach for Early Heart Disease Prediction: Gaus...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Surendran, R. Anandaraj, B. Deepa, P. Mageshwari, M. Balamurugan, K.S. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Madnapalle Institute of Technology & Science Andhra Pradesh Madanapalle India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer science and engineering Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India Department of Electronics and communication engineering Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

An Electrocardiogram (ECG) contributes significantly to early diagnosis and classification of heart diseases, arrhythmia which means irregular heart rate. Regrettably, the process became difficult due to asymmetric and minimal amplitude from recordings of ECG and cannot do the extraction from multiple signals. By using machine learning technology, it can classify and extract multiple samples, but cannot extract the data features from complex data structures. To overcome the limitations, previously introduced metaheuristic optimization (MHO) to improve the classification and extraction. Proposed a method which supports and K-Nearest Neighbour (KNN) Gaussian Mixture Model (GMM) algorithms for determine the abnormalities, predicting cardiac events, and improve diagnostic accuracy. As a result, this can help us to get results more quickly and accurately with sensitivity 99.7% and accuracy 99.2%, for helping healthcare professionals in diagnosing arrythmias, myocardial infarction and any other heart conditions. © 2025 ieee.

关键词： Adversarial machine learning

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One Step Toward Touch automation

One Step Toward Touch Automation

引用

2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Tripathi, Shruti Intel Technology Pvt Ltd Silicon Validation Engineer Karnataka Bengaluru560037 India

ISBN: (纸本)9798331529833

Functional validation is the process in which the SoC design is tested after the manufacture of the chip. In industry, many engineers work on the functional validation and test the different IPs using different techniques. There are several responsibilities which come under the account of a functional validation engineer. Taking care of the resources and equipment which will be useful at the time of validation is one of the responsibilities. Touch Host Controller (THC) is one of the IPs, where the engineer has to test the touch panel and touch handling capability of the SoC. Such testing requires the touch panel. The Functional Validation Engineer has to order these materials well in advance in order to ensure timely execution of the *** are however situations where the required display panel may not be available in time, and as every project has deadlines, as engineers may not be able for the touch panel. What can be the solution in such cases?In this paper, a solution is proposed to handle a situation where a touch panel is not readily available for testing. The solution will try to replace the touch panel with a microcontroller that emulates the touch interface of a touch panel. This allows the touch panel to be replaced and testing to proceed in its absence. The solution proposes the Microchip's ARM Cortex M0+ AT SAMD21J18A controller to emulate the touch panel to send the data using the HID over I2C protocol. © 2025 ieee.

关键词： Microcontrollers

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Automated Immune Cell Classification using Image Processing Techniques 6

Automated Immune Cell Classification using Image Processing ...

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Sathiyaprasad, B. Reddy, Arva Hari Vardhan Abdurrahman, Usama Micheal, A. Annie Department of Computer Science and Engineering Sathyabama institute of science and technology Chennai India

ISBN: (纸本)9798331522667

Advances in immunological research are essential for elucidating immune responses and developing targeted therapeutic approaches. This study proposes an automated method for immune cell classification leveraging machine learning and image processing techniques. A novel framework is introduced, combining high-resolution imaging with computational algorithms to accurately classify various immune cell types from biological samples. The methodology incorporated preprocessing steps, like normalization and noise reduction. Then, deep learning models, such as CNNs and SVMs, will be applied for feature extraction and classification. These models were trained on annotated datasets derived from flow cytometry and microscopy, demonstrating better accuracy and reliability. Results demonstrate an improvement in processing speed and accuracy of classification over traditional approaches, which underlines the importance of automation in immunological diagnostics. The data obtained can be used in high-throughput immunotherapy and disease diagnostic screening;it allows for the identification of immune cell populations within a short period and therefore improves research efficiency. The work provides a basis for real-time analysis and incorporation of multiscale datasets that will help to better understand immunity and its associated disorders. © 2025 ieee.

关键词： Convolutional neural networks

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Implementing and Managing Green IT Strategies to Enhance Corporate Sustainability

Implementing and Managing Green IT Strategies to Enhance Cor...

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2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Sudharson, K. Vijayakumar, N. Anitha, L. Subhashini, V. Madhumita, G. Sureshkumar, A. R.M.D. Engineering College Department of Aiml Chennai India B.S.Abdur Rahman Crescent Institute of Science & Technology Department of Commerce Chennai India Jnn Institute of Engineering Department of Mba Chennai India Dwaraka Doss Goverdhan DossVaishnav College Department of Accounting and Finance Chennai India Vels Institute of Science Technology and Advanced Studies VISTAS School of Management Studies Chennai India VelTech HighTech Dr. Rangarajan Dr. Sankunthala Engineering College Department of Mba India

ISBN: (纸本)9798331529833

Importance of Green IT practices is that it improves corporate sustainability through conserving the natural environment and minimizing the use of resource. This paper focuses on next generation IT management for power-optimized hardware, virtualization, cloud computing, and intelligent system through SITOF. Some of the key technologies are: ARM-based low power servers, vSphere-server visualization, Docker- Containerization, Solar/wind hybrid power. It shows that the main benefits of the IT of smart buildings are a 35% saving in energy and 40% reduction in carbons, as well as a quarter decrease in operation costs when compared to traditional IT practices. Moreover, data analytic improve performance measurement and management and hence contributing to an improvement in sustainability issues. These results also show that SITOF is feasible to assist firms in attaining corporate sustainability objectives while embracing the best practice of technology management. © 2025 ieee.

关键词： Green development

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Impact of Electric Vehicle Integration on Power Grids: A Comprehensive Review

Impact of Electric Vehicle Integration on Power Grids: A Com...

引用

2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Sarathkumar, D. Sajin, J.B. Manivel, Murugesan Jayakumar, T. Ragul, S. Ponnusamy, Sabarish Kongu Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638 060 India Sree Buddha College of Engineering Department of Mechanical Engineering Kerala 690 529 India Karpagam Institute of Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore641021 India Nandha Engineering College Department of Electrical and Electronics Engineering Tamilnadu 638052 India Kongunadu College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu 621215 India Department of Electrical and Electronics Engineering Tamil Nadu Samayapuram621112 India

ISBN: (纸本)9798331529833

The rapid growth of electric vehicles (EVs) poses significant challenges and opportunities for modern power grids. This comprehensive review examines the impact of large-scale EV integration on power grid infrastructure, focusing on key areas such as load demand, grid stability, energy storage, and renewable energy integration. We analyze the effects of EV charging on peak loads, voltage regulation, and grid reliability, highlighting the need for advanced control strategies and smart grid technologies. Additionally, this paper explores bidirectional power flow, vehicle-to-grid (V2G) systems, and their potential to enhance grid resilience and support renewable energy adoption. Through a detailed examination of current research and emerging trends, we present potential solutions for mitigating integration challenges, including smart charging, demand response, and distributed energy resources. This review provides insights into how the synergy between EVs and power grids can lead to more sustainable and efficient energy systems. © 2025 ieee.

关键词： Demand response

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Design Of Robust Controller for Ball and Beam

Design Of Robust Controller for Ball and Beam

引用

2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Jekan, P. Dharshini, R. Mohith, R. Swathi, A. Srm Institute of Science and Technology Electronics and Instrumentation Engineering Faculty Chennai India Srm Institute of Science and Technology Electronics and Instrumentation Engineering Student Chennai India

ISBN: (纸本)9798331529833

In this study, fuzzy logic controllers, PID, PD, and fractional-order PID are used to build a dependable control system for a ball and beam setup. Due to its extreme nonlinearity and instability, the ball and beam system presents considerable difficulties in preserving stability and accurate control in the face of uncertainties and shocks. Four control strategies - fuzzy logic controllers, fractional-order PID, proportional-derivative (PD), and proportional-integral-derivative (PID) - are created and put into practice to handle these problems. The PID controller balances fast reaction times with little overshoot by reducing steady-state error and offering comprehensive control. With an emphasis on improving stability and transient responsiveness while lowering the risk of overshoot, the PD controller streamlines the control architecture. By using fractional calculus, the fractional-order PID controller improves performance when managing nonlinearities and gives the user more control over the dynamics of the system. Linguistic variables are also used by the fuzzy logic controller to address system uncertainties and enhance flexibility. During the design stage, develops a mathematical model for the ball and beam system. © 2025 ieee.

关键词： Three term control systems

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Multivariate Time series Forecasting for Cloud Machine Utilization 3

Multivariate Time series Forecasting for Cloud Machine Utili...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Naik, Archana Sooda, Kavitha Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology Bangalore India Department of Computer Science and Engineering B.M.S. College of Engineering Bangalore India

ISBN: (纸本)9798331527549

The cloud machine utilization prediction using a multivariate time series model is explored in this study. The cloud machine usage data set samples are selected with varied patterns. The long sequence forecasting model Informer is investigated for the forecasting. The model results are benchmarked against LSTM, GRU, Prophet, and XGBoost across the diverse datasets. The performance is evaluated using RMSE. Experimental results show that the Prophet model performs best overall due to its ability to capture both seasonal and irregular patterns accurately. The RMSE value for Informer is 0.13, Prophet is 0.097, XGBoost is 0.096, LSTM is 0.1725, and GRU is 0.1547. © 2025 ieee.

关键词： Time series

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Advanced Facial Emotion Classification with 135 Classes for Enhanced Cybersecurity Applications 4

Advanced Facial Emotion Classification with 135 Classes for ...

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4th ieee international conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Powers, Gregory Jin, Aobo Tonmoy, Abdul Basit Cao, Haowei Gohel, Hardik Deng, Qixin Wabash College Mathematics and Computer Science Crawfordsville United States University of Houston Victoria Computer Science Victoria United States Johns Hopkins University Electrical and Computer Engineering Baltimore United States

ISBN: (纸本)9798331518882

A key component of behavior analysis and human-computer interaction (HCI) is facial expression detection, which helps systems understand and react to human emotions more effectively and nuancedly. While previous research predominantly focuses on classifying seven or eight primary emotions, there has been limited exploration into more detailed and varied emotional expressions. In this paper, we address this gap by utilizing a recently published dataset that includes 135 distinct emotional classes, significantly increasing the complexity and granularity of emotion recognition tasks. To tackle this challenge, we propose a novel framework that combines U-Net and ResNet architectures, leveraging the strengths of each to capture intricate emotional cues and spatial features. Our approach achieves higher accuracy than current state-of-the-art (SOTA) methods, demonstrating its effectiveness for high-dimensional emotion classification in complex, real-world applications. © 2025 ieee.

关键词： computer vision deep learning facial emotion recognition

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