Generative adversarial networks (GANs) have gained popularity for their ability to synthesize images from random inputs in deep learning models. One of the notable applications of this technology is the creation of re...
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The smart city idea differs between cities and nations. In all meanings and characteristics of a smart city, public involvement is the only thing that remains common. Therefore, it is a very significant field to study...
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A phishing attack is a form of cyber-attack where the attacker uses various social engineering techniques to obtain personal or sensitive data from a common man or an organization. Moreover, with the introduction of w...
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Access control is one of the most basic information security requirements, which prevents unauthorized people from accessing the system or facilities. The access control process relies on specified policies and rules ...
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The unprecedented circumstances encountered during the COVID-19 pandemic in a variety of life aspects such as health, economy, and environment have urged the humanity to devise new solutions to control and mitigate th...
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The increasing usage of image processing applications in modern technological environments is driven by their ability to enhance visual quality in diverse applications, from social media to medical imaging. The design...
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Stock market forecasting is one of the most exciting areas of time series forecasting both for the industry and academia. Stock market is a complex, non-linear and non-stationary system with many governing factors and...
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Cloud computing has become one of the leading technologies in the world *** benefits of cloud computing affect end users *** are several cloud computing frameworks,and each has ways of monitoring and providing *** com...
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Cloud computing has become one of the leading technologies in the world *** benefits of cloud computing affect end users *** are several cloud computing frameworks,and each has ways of monitoring and providing *** computing eliminates customer requirements such as expensive system configuration and massive infrastructure while improving dependability and *** the user’s perspective,cloud computing makes it easy to upload multiagents and operate on different web *** this paper,the authors used a restful web service and an agent system to discuss,deployments,and analysis of load performance parameters like memory use,cen-tral processing unit(CPU)utilization,network latency,etc.,both on localhost and an Amazon Web Service Elastic Cloud Computing(AWS-EC2)*** Java Agent Development Environment(JADE)tool has been used to propose an archi-tecture and conduct a comparative study on both local and remote *** is an open-source tool for maintaining applications on AWS *** focus of the study should be to reduce the complexity and time of load perfor-mance parameters by using an agent system on a cloud server instead of establish-ing a massive infrastructure on a local system,even for a small application.
Small object detection in radiological images has been a key challenge in the field of medical diagnosis for the last decade. Radiological modalities such as computed tomography scan imaging are often used to evaluate...
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Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient t...
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Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.
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