Cyber-Physical Systems (CPS) combine physical and computational elements to produce intelligent systems communicating with their surroundings. By integrating digital and physical processes, CPS provides increased func...
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作者：
Narasimhayya, B.E.Lanke, Ravikumar
Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India
The development of short-range communication protocols has been essential for efficient device discovery. Short-range communication allows two devices to communicate over short distances, typically up to 10 meters, us...
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作者：
Karthikeyan, S.Thomas, Merin
Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India
The recent advancements in mobile computing have opened up the possibilities of decentralized data recovery in mobile grid computing. With the help of improved Red (Recovery of Erased Data) technique, data recovery ca...
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In this study,twelve machine learning(ML)techniques are used to accurately estimate the safety factor of rock slopes(SFRS).The dataset used for developing these models consists of 344 rock slopes from various open-pit...
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In this study,twelve machine learning(ML)techniques are used to accurately estimate the safety factor of rock slopes(SFRS).The dataset used for developing these models consists of 344 rock slopes from various open-pit mines around Iran,evenly distributed between the training(80%)and testing(20%)*** models are evaluated for accuracy using Janbu's limit equilibrium method(LEM)and commercial tool GeoStudio *** assessment metrics show that the random forest model is the most accurate in estimating the SFRS(MSE=0.0182,R2=0.8319)and shows high agreement with the results from the LEM *** results from the long-short-term memory(LSTM)model are the least accurate(MSE=0.037,R2=0.6618)of all the models ***,only the null space support vector regression(NuSVR)model performs accurately compared to the practice mode by altering the value of one parameter while maintaining the other parameters *** is suggested that this model would be the best one to use to calculate the SFRS.A graphical user interface for the proposed models is developed to further assist in the calculation of the SFRS for engineering *** this study,we attempt to bridge the gap between modern slope stability evaluation techniques and more conventional analysis methods.
Knee joint rehabilitation exercise refers to a therapeutic procedure of a patient having dysfunctions in certain abilities to move knee joint due to some medical conditions like trauma or paralysis. The exercise is ba...
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作者：
Mathur, AshwiniBabu, S. Anantha
Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India
An Internet of Things (IoT) appears to be an innovative technology with great potential for widespread development. There has been a rise in data security issues in recent years as a consequence of various technologic...
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Twitter is the best source for sentiment analysis, product reviews, current issues, etc. Sentiment analysis extracts positive and negative opinions from the Twitter data set, and R studio provides the best environment...
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Potatoes are essential for food production and consumption, but pests and illnesses can cause major economic losses. To quickly identify potato leaf diseases, image processing, computer vision, and deep learning can b...
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作者：
Vivek, V.Tr, Mahesh
Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India
The computer system that is used to take attendance online is going to be upgraded as part of this project. This attendance tracking system is able to hold the technology known as facial recognition, which is a useful...
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Algorithms for steganography are methods of hiding data transfers in media *** machine learning architectures have been presented recently to improve stego image identification performance by using spatial information...
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Algorithms for steganography are methods of hiding data transfers in media *** machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image *** with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for *** address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of *** Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or *** Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the *** WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.
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