Technology is needed today;with technology, many things can be done quickly. Currently, houses with traditional lock security systems are very easy to break into by thieves. For this reason, it needs to be improved so...
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The importance of this paper comes from the fact that it presented a study of the double integrals of 2-refined neutrosophic functions and its applications, where we presented several theories for the concept of the d...
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The concept of Corporate Social Responsibility (CSR) involves a partnership responsibility between the government, companies, and the active and dynamic local community (Anatan, 2010). There are many ways to implement...
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As part of a doctoral thesis, an information system is to be developed to support the education system, particularly for STEM subjects. The basic functionality of the information system would be to inform the student ...
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The trajectory planning and tracking problem are critical points of intelligent vehicles concerning their safety and *** these parts are separated,interactions should be made between them,especially when sudden change...
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The trajectory planning and tracking problem are critical points of intelligent vehicles concerning their safety and *** these parts are separated,interactions should be made between them,especially when sudden changes and disturbances *** paper presents a method that integrates the two parts using a cascade ***,the proposed method deals with the interaction between the lateral and the longitudinal trajectory based on dynamical *** whole problem is handled using the model predictive method based on online *** system receives the path borders as input and generates the control requests for the actuators on its *** configuration space of the system can be maximized to gain stability by handling the lateral-longitudinal parts and the trajectory planning and tracking in one complex *** main advantage of the proposed approach is that the optimization problem in the predictive method is formulated so that the path and dynamics are considered equality and inequality constraints,and the cost function includes only a physical phenomenon to be minimized without tuning *** evaluation of the proposed algorithm is presented in this paper based on simulation and real-time measurements results.
This study addresses the challenge of selecting research topics for undergraduate students, focusing on computer science, by evaluating a recommendation model based on the k-Nearest Neighbor algorithm (kNN). The objec...
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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
The importance of using a security scanner to find web application weaknesses before they are released is very beneficial for the continuity of an organization. In this study, we analyze web security using Awasp and A...
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This research explores the synergistic integration of value engineering methods and green energy systems in Denpasar Health Polytechnic building construction innovations. The application of value engineering methods u...
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This research investigates the potential scenario for transitioning Trans Metro Dewata's conventional bus operations to electric buses. It employs a multifaceted approach to assess the feasibility of this transiti...
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