This paper presents the design and implementation of a transmission line fault detection system aimed at improving electrical safety and reliability. The system uses a flame sensor to detect fire or sparks and an Ardu...
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This paper proposes one approach with federated learning technique to address practical challenges faced by the emerging green energy industries, i.e., wind turbines in terms of Predictive Health Management (PHM). Not...
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ISBN:
(纸本)9798350389463;9798350389470
This paper proposes one approach with federated learning technique to address practical challenges faced by the emerging green energy industries, i.e., wind turbines in terms of Predictive Health Management (PHM). Not as many federated learning applications being used in the scenarios only for simulation, the application of federated learning in this paper is focused on the real industrial problems with raw data collected from the fields. Huge amount of real data was collected by sensors on more than ten wind turbines across different areas in China and transmitted to the storage for in-time processing. The framework proposed in this paper called TurboFed, can handle the raw data and achieves good prediction performance in the practical wind generated power systems. The framework showed its help on improving the efficiency of the wind turbines. The paper has brought three novel results. First, as far as known, the framework here is the first federated learning framework addressing position adjustment of wind turbines in the real environment. Second, it deploys customized recurrent neural computing models to the wind turbines which are considered the client devices under the federated learning paradigm. Finally, it incorporates new customized aggregation algorithms on the sever side.
Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with ...
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ISBN:
(纸本)9798350364613;9798350364606
Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with an existing interest in this course material. These discussions revealed an enthusiasm for making software pertimmance engineering a more prominent part of a curriculum for computer scientists and engineers. Here, we discuss how MIT's longstanding efforts in this area may serve as a launching point for community development of a software performance engineering curriculum, challenges in and solutions for providing the necessary infrastructure to universities, and future directions.
Considering the increasing demand of automobiles, the chances of accidents occurring have also increased. Accidents that happen during parking are rife nowadays. To prevent accidents at home when parking a vehicle in ...
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ISBN:
(纸本)9798350387919;9798350387902
Considering the increasing demand of automobiles, the chances of accidents occurring have also increased. Accidents that happen during parking are rife nowadays. To prevent accidents at home when parking a vehicle in the garage, a Parking Assistant System is designed to provide guidance to the driver to park safely. In the design of this project, LCD (Liquid Crystal Display), LEDs, Buzzer, Ultrasouic sensor, ATMega328 microcontroller and Arduino Uno microcontroller board are used. The device measures the distance between the front end of a vehicle and the garage wall. LED lighting is used to alert the driver to stop before collision occurs during parking inside the home garage. The driver is also be able to set the warning distance to accommodate different lengths of car sizes inside the garage at home. The driver will use a laptop with Arduino IDE to set the alarm or warning distance when necessary.
Edge caching is an effective way to reduce congestion and latency in 5G networks. Non-volatile memory (NVM) devices are developing fast, with the potential of fast access, and higher endurance versus traditional stora...
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ISBN:
(数字)9781665471770
ISBN:
(纸本)9781665471770
Edge caching is an effective way to reduce congestion and latency in 5G networks. Non-volatile memory (NVM) devices are developing fast, with the potential of fast access, and higher endurance versus traditional storage devices, to further boost mobile data offloading efficiency in 5G networks. This paper studies how to effectively use the two-layer storage system (NVM-enhanced) in 5G edge caching. We first model an edge caching optimization problem with NVM storage devices included and develop a parallel distributed algorithm with guaranteed convergence in joint caching and routing decisions. A fully decentralized algorithm for scenarios without any coordination is further developed which also guarantees the convergence. Real-world trace-driven simulations and experiments over a small-scale system demonstrate that NVM significantly boosts the performance of edge caching and the proposed algorithms outperform the existing ones.
The Open structure for allotted and Cooperative Media Algorithms (OADCMA) is an open-deliver framework imparting a plug-in platform that lets customers, without problem, develop distributed and cooperative media algor...
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The proceedings contain 30 papers. The topics discussed include: a robust scheduling algorithm for overload-tolerant real-time systems;elastic scheduling for fixed-priority constrained-deadline tasks;a scheduling mode...
ISBN:
(纸本)9798350339024
The proceedings contain 30 papers. The topics discussed include: a robust scheduling algorithm for overload-tolerant real-time systems;elastic scheduling for fixed-priority constrained-deadline tasks;a scheduling model inspired by security considerations;you can’t always check what you wanted: : selective checking and trusted execution to prevent false actuations in real-time Internet-of-Things;variable window and deadline-aware sensor attack detector for automotive CPS;compiler-directed constant execution time on flat memory systems;shared resource orchestration extensions for Kubernetes to support real-time cloud containers;dataset placement and data loading optimizations for cloud-native deep learning workloads;a collaborative and distributed task management system for real-time systems;and end-to-end timing modeling and analysis of TSN in component-based vehicular software.
A hierarchical approximate dynamic programming (ADP) strategy is presented to determine intra-day operations of distributed energy storage cluster for demand management and frequency response service. According to the...
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Existing motion intent recognition systems in lower limb rehabilitation robots primarily rely on the fusion of multiple sensor features. Such systems capture the motion characteristics of healthy volunteers during spe...
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ISBN:
(纸本)9798350352900;9798350352894
Existing motion intent recognition systems in lower limb rehabilitation robots primarily rely on the fusion of multiple sensor features. Such systems capture the motion characteristics of healthy volunteers during specific m ovements a nd t hen process the data using machine learning algorithms to accurately recognize human motion events, such as forward and backward movements. We address the complexity and inaccuracies of current intent recognition systems by synthesizing feedback from rehabilitation physicians and patients and adopting modular design principles to develop an integrated human motion intent recognition system for lower limb rehabilitation robots. The system utilizes dual physical sensors to collect data on the movement characteristics of the patient's waist, abdomen, and shoulders, which are then classified using the Transformer-LSTM algorithm. The dataset employed for training and testing the algorithm was gathered from a tertiary care hospital, focusing on the movement characteristics of patients with functional hemiplegia of the lower extremities. Clinical trial results demonstrated that the Transformer-LSTM algorithm achieved an average classification accuracy of 97.54% in recognizing human lower limb movement events, compared to 87.48% with the LSTM algorithm. This lower limb rehabilitation robot also significantly enhances patient motivation and comfort during training.
Wireless sensor Networks (WSNs) are widely used in diverse applications, including environmental monitoring and military surveillance. However, their open and distributed nature makes them vulnerable to clone node att...
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