Several types of multirotor unmanned aerial vehicles (UAVs) are widely used in various industrial activities. UAVs with electric ducted fans (EDFs) have been developed to mitigate the risks associated with rotary blad...
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Vehicles are becoming physical computer systems that connect with other cars and collect data from numerous pieces of equipment. These improvements contribute to developing smart and connected automobiles that will su...
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In recent years, the development of a green supply chain model that takes sustainability into consideration has become an urgent issue in corporate management and policy operation. For example, in the fashion industry...
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In post-secondary education engineers are not formally introduced to socially just engineering. This education focuses on technical expertise, often overlooking the social impacts of engineering outputs. Using essay p...
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The practice of using deep learning methods in safety critical vision systems such as autonomous driving has come a long way. As vision systems supported by deep learning methods become ubiquitous, the possible securi...
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Smart grids are at risk of cyber-attacks due to more connected devices being introduced. Different kinds of attacks may incur different consequences in the operation of smart grids. Attackers have identified different...
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Facial recognition technology has become integral to daily life, facilitating processes such as online payments, smart door locks, and mobile phone unlocking, while enhancing security. However, its accuracy can be com...
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The COVID-19 pandemic has profoundly affected various facets of society. This research explores the discourse on social media, specifically "X"(Twitter), to understand public sentiment and needs regarding he...
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Today, corporate social responsibility (CSR) is known as a critical element of supply chain (SC) operations. In this article, we analytically study an SC coordination problem with social efforts for charity. The propo...
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Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other ...
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Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other SLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrSL)using the UrSL-CNN model,a convolutional neural network(CNN)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,GaussianNaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrSL alphabets dataset demonstrated the superiority of UrSL-CNN,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.
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