Satellites and high-altitude unmanned aerial vehicles are the top platforms for electro-optical remote sensing for both civilian and military applications. Since early 2000s high altitude electro-optical remote sensin...
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Infrared (IR) imaging sensors designed to acquire the 0.9-14 micrometers wavelength band offer unique advantages over the daylight cameras for a multitude of consumer, industrial and defense applications. However, IR ...
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The forward-forward algorithm is a recently introduced method that can be used to train artificial neural networks. Currently, the canonical approach to training artificial neural networks is using (batched) stochasti...
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This research focuses on exploring the nanosecond laser-driven coil systems capable of generating kT magnetic fields and the diverse applications of this system. Through investigating the effects of laser parameters a...
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Millimeter-wave network deployment is an essential and ongoing problem due to the limited coverage and expensive network infrastructure. In this work, we solve a joint network deployment and resource allocation optimi...
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This paper presents our participation in the CLEF2024 CheckThat! Lab's Task-1 which focuses on determining whether passages from tweets or transcriptions are check-worthy. Task 1 covers three languages including E...
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Dynamic structure of languages poses significant challenges in applying natural language processing models on historical texts, causing decreased performance in various downstream tasks. Turkish is a prominent example...
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Breast cancer seriously affects many *** breast cancer is detected at an early stage,it may be *** paper proposes a novel classification model based improved machine learning algorithms for diagnosis of breast cancer ...
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Breast cancer seriously affects many *** breast cancer is detected at an early stage,it may be *** paper proposes a novel classification model based improved machine learning algorithms for diagnosis of breast cancer at its initial *** has been used by combining feature selection and Bayesian optimization approaches to build improved machine learning *** Vector Machine,K-Nearest Neighbor,Naive Bayes,Ensemble Learning and Decision Tree approaches were used as machine learning *** experiments were tested on two different datasets,which are Wisconsin Breast Cancer Dataset(WBCD)and Mammographic Breast Cancer Dataset(MBCD).Experiments were implemented to obtain the best classification ***,Least Absolute Shrinkage and Selection Operator(LASSO)and Sequential Forward Selection were used to determine the most relevant features,*** machine learning models were optimized with the help of Bayesian optimization approach to obtain optimal hyperparameter *** results showed the unified feature selection-hyperparameter optimization method improved the classification performance in all machine learning *** the various experiments,LASSO-BO-SVM showed the highest accuracy,precision,recall and F1-score for two datasets(97.95%,98.28%,98.28%,98.28%for MBCD and 98.95%,97.17%,100%,98.56%for MBCD),yielding outperforming results compared to recent studies.
Social anxiety disorder (SAD) involves an intense fear of social interactions, leading to distress and impaired daily functioning. This study aims to develop a wearable technology to predict and mitigate anxiety attac...
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Nowadays, DC (direct current) motors are widely used in industry. Air conditioners, computer drives, electric toothbrushes, portable vacuum cleaners, drilling machines, trimmers, food mixers are some areas where DC mo...
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