Electric Vehicles (EVs) become very important issue and gained attention due to many reasons like its economic price, saving environment and more reliable. In this study, controlling speed for EV is utilized by tracki...
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Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pn...
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The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the...
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The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the lung cancer diagnosis, the higher the survival rate. For radiologists, recognizing malignant lung nodules from computed tomography (CT) scans is a challenging and time-consuming process. As a result, computer-aided diagnosis (CAD) systems have been suggested to alleviate these burdens. Deep-learning approaches have demonstrated remarkable results in recent years, surpassing traditional methods in different fields. Researchers are currently experimenting with several deep-learning strategies to increase the effectiveness of CAD systems in lung cancer detection with CT. This work proposes a deep-learning framework for detecting and diagnosing lung cancer. The proposed framework used recent deep-learning techniques in all its layers. The autoencoder technique structure is tuned and used in the preprocessing stage to denoise and reconstruct the medical lung cancer dataset. Besides, it depends on the transfer learning pre-trained models to make multi-classification among different lung cancer cases such as benign, adenocarcinoma, and squamous cell carcinoma. The proposed model provides high performance while recognizing and differentiating between two types of datasets, including biopsy and CT scans. The Cancer Imaging Archive and Kaggle datasets are utilized to train and test the proposed model. The empirical results show that the proposed framework performs well according to various performance metrics. According to accuracy, precision, recall, F1-score, and AUC metrics, it achieves 99.60, 99.61, 99.62, 99.70, and 99.75%, respectively. Also, it depicts 0.0028, 0.0026, and 0.0507 in mean absolute error, mean squared error, and root mean square error metrics. Furthermore, it helps physicians effectively diagnose lung cancer in its early stages and allows spe
A model of a two-level hierarchical system with many participants is studied assuming that lower-level elements choose Pareto optimal outcomes. Two classes of games are studied: without feedback and with feedback. The...
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Thepaper deals with a formalized description of a computer-aided crop rotation engineering system based on a mathematical crop system optimization model implemented in the digital platform for industry management that...
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Personnel selection for software projects is about finding people who are ready to work in conditions of extreme uncertainty. Therefore, the extreme uncertainty in the selection of personnel must be mitigated primaril...
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Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods...
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This paper proposes a novel approach to improving speech recognition performance by combining spectrogram images with extracted formant frequency data within a dual input neural network framework. While spectrograms a...
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There is a justified need for a cross-platform implementation of an OPC UA server for a CNC system. The available open-source libraries that implement the OPC UA stack have been analyzed, and a solution based on open6...
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This article contemplates the problem of collecting and storing technological data during multichannel and multi - coordinate machining on CNC machines obtained using the OPC UA protocol and applying Node-RED open-sou...
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