this paper presents a solution for leveraging High-Performance computing (HPC) infrastructures, and investigates the integration of distributed deep learning (DDL) techniques to address Industry 4.0 challenges across ...
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ISBN:
(纸本)9783031786976;9783031786983
this paper presents a solution for leveraging High-Performance computing (HPC) infrastructures, and investigates the integration of distributed deep learning (DDL) techniques to address Industry 4.0 challenges across three distinct applications: intrusion detection with multi-layer perceptron, defect identification with convolutional neural networks, and predictive maintenance with recurrent neural network. Experimental results, underscore the scalability and efficiency of the proposed DDL approach. Notably, computations are accelerated by up to 46 times. In addition to performance metrics, this research places significant emphasis on environmental sustainability. Detailed examination of energy consumption patterns on the HPC infrastructure aims to minimize the carbon footprint associated with deep learning processes. this dual focus on efficiency and sustainability positions the approach as a holistic and responsible solution for Industry 4.0 applications. the practical insights enhance the efficiency of deploying DDL in HPC infrastructure. Additionally, they highlight the significance of ecofriendly AI practices for ethical and environmentally sustainable technological progress.
Efficient processing of extensive datasets is crucial in data-driven applications, particularly for anomaly detection. this article explores the application of parallel and distributed machine learning techniques to e...
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the increasing demand for real-time data analysis in Internet of things (IoT) ecosystems has created several challenges, particularly in environments where resources are limited, and minimizing data processing latency...
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this paper presents 50-dB attenuation range low insertion loss 100nm Gallium Arsenide (GaAs) digital step attenuators at the Ku-band and Ka-band. the distributed type, combined withparallel RC compensation and reduce...
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ISBN:
(纸本)9798350379808;9798350379792
this paper presents 50-dB attenuation range low insertion loss 100nm Gallium Arsenide (GaAs) digital step attenuators at the Ku-band and Ka-band. the distributed type, combined withparallel RC compensation and reduced-size quarterwavelength techniques, is utilized to achieve low insertion loss, good attenuation, and phase error. Specifically, the 14-18 GHz DSA exhibits an insertion loss of less than 4.8 dB and a Root-Mean-Square (RMS) amplitude error of 0.72 dB. Similarly, the 34-37 GHz DSA achieves an insertion loss of under 6.4 dB and RMS amplitude error of 1.14 dB. the output third-order intercept point (OIP3) of both designs is approximately 40 dBm.
While the popularity of electric vehicles brings great convenience to our lives, battery charging also leads to an increase in accidents, resulting in personal injuries and economic losses. the methods currently embed...
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this paper examines how co-locating multiple VMs on a single physical server with shared storage impacts I/O performance, specifically focusing on latency of I/O operations, and the overall throughput. We introduce a ...
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the disruption caused by Software Defined Network and Network Function Virtualization (SDN/NFV) technologies will have many impacts on the telecom network. Specifically, the network architecture based on ETSI MANO com...
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the recognition and tracking of a person of interest is a crucial task in many applications, including search and rescue, security, and surveillance. this paper presents a distributed system architecture that leverage...
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ISBN:
(纸本)9798350323023
the recognition and tracking of a person of interest is a crucial task in many applications, including search and rescue, security, and surveillance. this paper presents a distributed system architecture that leverages the asynchronous threading and communication property of ROS2 to develop and implement a real-time efficient Deep Learning (DL) based method for recognizing and tracking a person of interest. the DL model receives snapshots from the quadcopter's camera and sends back an information vector, which includes all recognized persons and their corresponding position information within the camera frame of the quadcopter. the person of interest tracking control system receives face set information about the person of interest and generates reference velocity signals to be tracked by low-level controllers embedded within the drone. Experiments conducted in a cluttered and complex environment demonstrate the efficiency of the DL-based architecture for quadcopters. the presented real-world results validate the effectiveness of the proposed approach in recognizing and tracking a person of interest. the experimental video is available at https://***/i7bYXnRy8Vc.
the emergence of the Internet of things (IoT) has raised several issues related to the development and deployment of IoT applications within IT infrastructures. In this context, cloud computing is often faced with lat...
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ISBN:
(纸本)9781665496070
the emergence of the Internet of things (IoT) has raised several issues related to the development and deployment of IoT applications within IT infrastructures. In this context, cloud computing is often faced with latency issues when hosting such applications, even though the cloud environment offers promising opportunities to increase productivity and reduce costs significantly. therefore, it is important to review the current conformance scheme in the cloud environments by considering the coordination challenges during data processing. For this purpose, we suggest an architecture for conformance testing of IoT based implementations in the Cloud. the idea is to set parallel testers to handle the conformance of the distributed implementation with respect to the specification. In this case, the testing process must support coordination between the different distributed components in order to detect the resulting faults. therefore, the main contribution of this work is to propose a new architecture based on Markov decision processes with an adaptive controller to monitor and optimize the overall testing process in the distributed Cloud.
Scalability is a crucial factor determining the performance of massive heterogeneous parallel CFD applications on the multi-GPUs platforms, particularly after the single-GPU implementations have achieved optimal perfo...
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