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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Kajanan Kanathipan John Lam Dept. of Electrical Engineering and Computer Science York University Toronto Canada

A modular photovoltaic (PV) step-up converter with embedded high frequency power balancers that utilize an interlinking controller capable of power efficiency optimization over a wide operating range for Medium Voltage (MV) DC distribution is proposed in this paper. The converter utilizes an integrated boost-CLL resonant circuit with power balancing active voltage quadruplers (AVQ) to achieve step-up voltage conversion, individual maximum power point tracking (MPPT) and modular power balancing. The proposed interlinking power balancer controller optimizes the transmission of mismatched power while simultaneously achieving soft-switching operation on all AVQ circuits. The modular nature of the system allows for additional modules to be added without requiring parameter changes to the existing system. Analysis of the proposed converter and power balancing technique along with 10kW, 10kV-output system simulation and preliminary results on a scaled down 500W, 850V-output system are provided to highlight the features of the proposed system.

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A comparative study of different scheduling approaches for splittable latency sensitive tasks in Fog-Cloud environment

A comparative study of different scheduling approaches for s...

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Ambient Intelligence in Health Care (ICAIHC), International Conference on

作者： Kone Sai Sandeep Challa Aditya Koundinya Adapa Venkata Prabhas Chinmaya Kumar Swain Sambit Kumar Mishra Dept. of Computer Science Engineering SRM University

IoT has revolutionized the way we live and the work we do by connecting different devices through the Internet. In the present scenario, the number of IoT devices are increasing rapidly due to the increase in technology and the increase in the comforts of life. Nowadays we can see that many of them are using IoT devices regularly, it's estimated that by the end of 2030, there will be 30 billion users who will be using IoT applications. These devices send data to the cloud for processing. Due to the distance of the cloud from the IoT devices, the application requests get delayed service responses. So to handle the latency sensitive applications we require the micro cloud service like fog servers deployed near to the data generation points. The fog layer lies between the IoT devices and Cloud which acts as an intermediate layer. This helps in reducing latency of the tasks and provide better performance. As the number of IoT applications keeps on increasing, the resources available with the fog nodes may not handle the upcoming demands. So to overcome these demands, we are using splittable methods to allocate the tasks to Fog/ Cloud nodes more compactly. If a task can be splitted before the deadline into different modules, then we split the given task and allocate those tasks to different fog nodes/ servers and then collecting back the data from the fog nodes/ servers and merging them into a single unit. With the help of this method, we can increase the performance of the system.

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A Performance Analysis Modeling Framework for Extended Reality Applications in Edge-Assisted Wireless Networks

A Performance Analysis Modeling Framework for Extended Reali...

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International Conference on Distributed Computing Systems

作者： Anik Mallik Jiang Xie Zhu Ran The Dept. of Electrical and Computer Engineering The University of North Carolina Charlotte NC USA The Dept. of Electrical and Computer Engineering University of Houston TX USA Dept. of Computer Science and Engineering Kyung Hee University Seoul South Korea

ISBN: (数字)9798350386059

ISBN: (纸本)9798350386066

Extended reality (XR) is at the center of attraction in the research community due to the emergence of augmented, mixed, and virtual reality applications. The performance of such applications needs to be uptight to maintain the requirements of latency, energy consumption, and freshness of data. Therefore, a comprehensive performance analysis model is required to assess the effectiveness of an XR application but is challenging to design due to the dependence of the performance metrics on several difficult-to-model parameters, such as computing resources and hardware utilization of XR and edge devices, which are controlled by both their operating systems and the application itself. Moreover, the heterogeneity in devices and wireless access networks brings additional challenges in modeling. In this paper, we propose a novel modeling framework for performance analysis of XR applications considering edge-assisted wireless networks and validate the model with experimental data collected from testbeds designed specifically for XR applications. In addition, we present the challenges associated with performance analysis modeling and present methods to overcome them in detail. Finally, the performance evaluation shows that the proposed analytical model can analyze XR applications' performance with high accuracy compared to the state-of-the-art analytical models.

关键词： Performance evaluation Analytical models Solid modeling Energy consumption Extended reality Computational modeling Wireless networks

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A 4x4 MIMO Antenna Array for the Wi-Fi7Access Point on a Metal Wall Application

A 4x4 MIMO Antenna Array for the Wi-Fi7Access Point on a Met...

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International Symposium on Antennas and Propagation (ISAP)

作者： Hsin-Lung Su You-Sheng Zhan Dept. of Computer and Communication National Pingtung University Taiwan Dept. of Computer Science and Information Engineering National Pingtung University Taiwan

ISBN: (数字)9798350364774

ISBN: (纸本)9798350364781

4×4 CPW MIMO Antenna array with an artificial magnetic conductor (AMC) reflector is presented for Wi-Fi7 access point on a metal wall application in the study. The 10-dB impedance of the integrated MIMO antenna array covers the Wi-Fi 7 operating bands, and the transmission coefficients are under -15 dB in the whole Wi-Fi7 bands. This proposed integrated MIMO antenna is low profile and has good total radiation efficiency (over 60%). The height of the integrated MIMO antenna array is 6.325 mm.

关键词： Transmitting antennas Metals Directive antennas Reflector antennas Conductors Coplanar waveguides Impedance Wireless fidelity Antenna arrays Antenna radiation patterns

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Slax: A Composable JAX Library for Rapid and Flexible Prototyping of Spiking Neural Networks

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arXiv 2024年

作者： Summe, Thomas M. Joshi, Siddharth Dept. of Computer Science and Engineering University of Notre Dame United States

Recent advances to algorithms for training spiking neural networks (SNNs) often leverage their unique dynamics. While backpropagation through time (BPTT) with surrogate gradients dominate the field, a rich landscape of alternatives can situate algorithms across various points in the performance, bio-plausibility, and complexity landscape. Evaluating and comparing algorithms is currently a cumbersome and error-prone process, requiring them to be repeatedly re-implemented. We introduce Slax, a JAX-based library designed to accelerate SNN algorithm design, compatible with the broader JAX and Flax ecosystem. Slax provides optimized implementations of diverse training algorithms, allowing direct performance comparison. Its toolkit includes methods to visualize and debug algorithms through loss landscapes, gradient similarities, and other metrics of model behavior during training. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Parallel Neural Computing for Scene Understanding from LiDAR Perception in Autonomous Racing

Parallel Neural Computing for Scene Understanding from LiDAR...

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Intelligent Systems and Embedded Design (ISED), International Conference on

作者： Suwesh Prasad Sah Suchismita Chinara Dept. Computer Science and Engineering National Institute of Technology Rourkela India

ISBN: (数字)9798331522612

ISBN: (纸本)9798331522629

Autonomous driving in high-speed racing, as opposed to urban environments, presents significant challenges in scene understanding due to rapid changes in the track environment. Traditional sequential network approaches may struggle to meet the real-time knowledge and decision-making demands of an autonomous agent covering large displacements in a short time. This paper proposes a novel baseline architecture for developing sophisticated models capable of true hardware-enabled parallelism, achieving neural processing speeds that mirror the agent's high velocity. The proposed model (Parallel Perception Network (PPN)) consists of two independent neural networks, segmentation and reconstruction networks, running parallelly on separate accelerated hardware. The model takes raw 3D point cloud data from the LiDAR sensor as input and converts it into a 2D Bird's Eye View Map on both devices. Each network independently extracts its input features along space and time dimensions and produces outputs parallelly. The proposed method's model is trained on a system with two NVIDIA T4 GPUs, using a combination of loss functions, including edge preservation, and demonstrates a 2x speedup in model inference time compared to a sequential configuration. Implementation is available at: github/ParallelPerceptionNetwork. Learned parameters of the trained networks are provided at: huggingface/ParallelPercentionNetwork.

关键词： Point cloud compression Solid modeling Laser radar Three-dimensional displays Computational modeling Neural networks Urban areas computer architecture Parallel processing Feature extraction

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Gotcha: Real-Time Video Deepfake Detection via Challenge-Response

Gotcha: Real-Time Video Deepfake Detection via Challenge-Res...

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IEEE European Symposium on Security and Privacy (EuroS&P)

作者： Govind Mittal Chinmay Hegde Nasir Memon Dept. of Computer Science and Engineering Tandon School of Engineering New York University USA

ISBN: (数字)9798350354256

ISBN: (纸本)9798350354263

With the rise of AI-enabled Real-Time Deepfakes (RTDFs), the integrity of online video interactions has become a growing concern. RTDFs have now made it feasible to replace an imposter's face with their victim in live video interactions. Such advancement in deepfakes also coaxes detection to rise to the same standard. However, existing deepfake detection techniques are asynchronous and hence ill-suited for RTDFs. To bridge this gap, we propose a challenge-response approach that establishes authenticity in live settings. We focus on talking-head style video interaction and present a taxonomy of challenges that specifically target inherent limitations of RTDF generation pipelines. We evaluate representative examples from the taxonomy by collecting a unique dataset comprising eight challenges, which consistently and visibly degrades the quality of state-of-the-art deepfake generators. These results are corroborated both by humans and a new automated scoring function, leading to 88.6% and 80.1% AUC, respectively. The findings under-score the promising potential of challenge-response systems for explainable and scalable real-time deepfake detection in practical scenarios. We provide access to data and code at https://***/mittalgovind/GOTCHA-Deepfakes.

关键词： Deepfakes Codes Taxonomy Pipelines Streaming media Real-time systems Robustness

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Human Interaction in Virtual and Mixed Reality Through Hand Tracking

Human Interaction in Virtual and Mixed Reality Through Hand ...

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IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： S. Geetha Aditya G Chetan Reddy M Nischith G Dept. of Computer Science and Engineering BNM Institute of Technology Bengaluru India

ISBN: (数字)9798350385922

ISBN: (纸本)9798350385939

This paper explores the potential and possibilities of hand tracking in virtual reality (VR) and mixed reality (MR), focusing on its role in human interaction dynamics. An application was designed in Unity leveraging the XR Interaction toolkit, within which various items across three important domains: daily life, education, and recreation, were crafted to demonstrate the versatility of hand tracking along with hand gesture-based shortcuts for interaction. Integration of elements in MR ensures that users can seamlessly enjoy virtual experiences while remaining connected to their physical surroundings. Precise hand tracking enables effortless interaction with the virtual space, enhancing presence and control with a user-friendly interface. Additionally, the paper explores the effectiveness of integrating hand tracking into education and training scenarios. A computer assembly simulation was created to demonstrate this, featuring component inspection and zoom capabilities along with a large language model (LLM) integrated with hand gestures to provide for interaction capabilities.

关键词： Training Visualization Accuracy Three-dimensional displays Tracking Mixed reality Virtual reality

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BCHJam: a Brain-computer Music Interface for Live Music Performance in Shared Mixed Reality Environments

BCHJam: a Brain-Computer Music Interface for Live Music Perf...

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Internet of Sounds, International Symposium on the

作者： Michele Romani Gregorio Andrea Giudici Domenico Stefani Devis Zanoni Alberto Boem Luca Turchet Dept. of Information Engineering and Computer Science University of Trento Trento Italy

ISBN: (数字)9798350366525

ISBN: (纸本)9798350366532

To date, the integration of brain-computer interfaces and mixed reality headsets in Internet of Musical Things (IoMusT) performance ecosystems has received remarkably little attention from the research community. To bridge this gap, in this paper, we present BCHJam: an IoMusT-based performance ecosystem composed of performers, audience members, brain- computer interfaces, smart musical instruments, and mixed reality headsets. In BCHJam, one or more musicians are fitted with a brain-computer music interface (BCMI) giving them the possibility to actively or passively control the processing of their instrument's audio. Moreover, the BCMI's signal controls mixed reality visual effects displayed in XR headsets worn by audience members. All the components of BCHJam communicate through a Wi-Fi network via Open Sound Control messages. We refined the system through a series of test performance sessions, resulting in the creation of a signal quality filter that improved the musician's experience, along with a tuning of control parameters. The developed ecosystem was validated by realizing a musical performance. We provide a critical reflection on the achieved results and discuss the lessons learned while developing this first of its kind IoMusT performance ecosystem.

关键词： Headphones Instruments Ecosystems Music Mixed reality Visual effects Brain-computer interfaces Internet Wireless fidelity Tuning

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Cloud-Infused AWS Services: Automobile Database Management System

Cloud-Infused AWS Services: Automobile Database Management S...

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International Conference on Networking, Embedded and Wireless Systems (ICNEWS)

作者： Uthej K Nagandla Krishna Sai Keerthan Nikhil Kumar Musunuru Beena B M Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru India

ISBN: (数字)9798350367461

ISBN: (纸本)9798350367478

A Cloud-based Automobile Database Management System serves as a specialized software application dedicated to efficiently managing databases hosted on cloud infrastructure, encompassing both system hard drives and networked servers. Various types of DBMS are intricately designed to oversee and regulate databases tailored for specific purposes. In the context of organizing comprehensive information on automobiles, leveraging cloud technology is not merely beneficial but imperative. As part of our strategic initiative, we are implementing a cutting-edge approach that involves the utilization of diverse cloud services, including S3 (Simple Storage Service), EC2 (Elastic Compute Cloud), and IAM (Identity and Access Management), Cognito, Cloud Watch, Simple Notification System (SNS), AWS RDS (Relational Database Service). Our proactive strategy involves the development of an intuitive user interface hosted on the cloud. This interface empowers customers to seamlessly select and explore their preferred vehicles based on individual usage criteria. The innovative integration of cloud services, such as S3 for robust storage, EC2 for scalable computing power, and IAM for secure access control, ensures scalability, accessibility, and smooth functionality, RDS optimizes database management, SNS enables real-time communication, and CloudWatch ensures proactive monitoring. Cognito enhances user authentication and authorization. This comprehensive approach not only enhances the overall user experience but also simplifies the process of selecting a dream vehicle for our customers. A comparative analysis has been sustained for AWS Servies, MySQL of 38% more reliable in retrieval time with Google Cloud Platform (GCP), MySQL.

关键词： Scalability Relational databases User interfaces Aerodynamics Real-time systems Database systems Automobiles Reliability Vehicle dynamics Monitoring

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