Evolutionary multiobjective optimization (EMO) has been a subject of intensive study in the past two decades, owing to its research challenges and practical values. With the progress and development of multiobjective ...
The growing energy demand and the need for sustainable solutions have led to the rise of smart buildings equipped with innovative technologies aimed at optimizing energy use. Machine learning (ML) algorithms play a pi...
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The emergence of the Multi-Microgrid (MMG) concept can be attributed to the increased interaction between Microgrids (MGs). To tackle the intermittency of renewable energy resources (RES) and enhance the dependability...
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Detecting mental health problems at the earliest can help professionals provide correct treatment and increase the value of patients. One of the most prevalent types of impairment in the world is depression. It is imp...
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This research explores the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) to enhance energy efficiency and power quality management in prefabricated intelligent buildings. The study exami...
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This paper presents an improved sensorless control system for dual three-phase permanent magnet synchronous motors (DTP-PMSMS), aimed at overcoming the limitations of conventional sliding mode observer (SMO) algorithm...
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In today's era of rapid internet expansion, the need for efficient information retrieval tools is paramount. Recommendation systems serve as indispensable instruments, aiding users in navigating vast datasets swif...
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These networks are seriously threatened by wormhole and blackhole attacks, which manipulate the routing protocol for malicious paths to disrupt data communication. Classic route optimization algorithms between nodes i...
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While Field Programmable Gate Arrays (FPGAs) and other forms of reconfigurable hardware have been available to designers for the better part of the past three decades, many implementations still fail to take use of th...
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ISBN:
(纸本)9798350398465
While Field Programmable Gate Arrays (FPGAs) and other forms of reconfigurable hardware have been available to designers for the better part of the past three decades, many implementations still fail to take use of the devices' full potential. systems that execute partial runtime reconfiguration of the device have the potential to make more efficient use of available resources if they are designed and implemented early in the process. The speed and size of reconfigurable FPGA fabric have increased in recent years as the number of complex parallel programmes that may be run on a single device has increased. It has never been possible to acquire such skill. Each time a device performs a partial reconfiguration of a segment of the fabric, the system's operation is disturbed since it is unable to get access to the resource. This means that when the device is redesigned, more of the available reconfigurable resource will become accessible. The fundamental goal of this thesis is to increase the efficiency and reduce the power consumption of run-time digital systems that rely on dynamic partial reconfiguration, all without sacrificing the functionality of these systems (DPR). The idea enabled two major advances. The first positive step towards the desired reconfigurable system was made when a method was established for building the programmable logic reprogramming array using Recurrent Neural Network (RNN). An FPGA's main purpose is to reprogram the interconnects of an array system, in addition to programming logic blocks. DPR was designed to be as efficient as possible in terms of both power consumption and physical footprint so that the cognitive system could be managed and accessed in real time. Its setup, design flow, and portability are only a few of the metrics used to evaluate the system's overall efficacy. In compared to a full reconfiguration, it requires less time, space, and power to get the job done. Our success may be attributed to our use of the Cadence-CMOS
In the realm of remote sensing, hyperspectral imaging is a new field of study. Hyperspectral sensors use the surface of the earth to record hundreds of continuous spectral bands as a three-dimensional cube. The maximu...
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