Data Mining is a discipline of Machine Learning which is used to find or extract the information from the huge database of any organization by using some informative techniques. These informative techniques are then d...
Data Mining is a discipline of Machine Learning which is used to find or extract the information from the huge database of any organization by using some informative techniques. These informative techniques are then divided into different categories like clustering, classification, regression and association rule mining etc. Data Mining is widely used techniques in different fields like education, telecommunication, hospital, hospitality industry etc. As education plays a crucial role in the life of a human being therefore its proper monitoring is also very important. Thus, to predict the academic performance of any student on time and to help students improve their academic perform different researcher is working in the field and tried to develop a system which help to improve the prediction result. In this paper, different classification algorithms are used on academic dataset of the student in conjunction with different ensemble learning algorithm to improve the prediction result as compared to prediction result given by simple classification algorithm. At the end a comparison is also given which show the performance improvement by ensemble learning as compared to simple classification. The maximum improvement is shown by Multilayer perceptron algorithm and it is up to 15%.
Hybrid Plug-in Electric vehicles (HPEV) are new automobiles that can operate on gasoline and electricity stored in a battery pack. As a result, by utilizing the cheaper renewable and nonrenewable energy sources access...
Hybrid Plug-in Electric vehicles (HPEV) are new automobiles that can operate on gasoline and electricity stored in a battery pack. As a result, by utilizing the cheaper renewable and nonrenewable energy sources accessible at the household electric outlet, these cars may considerably cut their fuel usage. As a result, PHEVs have the potential to reduce overall greenhouse gas emissions from vehicles dramatically. A simplified power train of a power split PHEV is modeled in this study. The primary goal of the research is to improve the PHEV’s fuel economy. To accomplish this, the aforementioned simplified model has been used to implement the Optimized Neural Network approach. An optimization problem is developed with Equivalent Fuel Consumption Minimization (EFCM) as the primary objective function and various constraints. The particle swarm optimization (PSO) methodology is used to improve the efficiency of HPEV, estimates by optimizing the process parameters of the ANN. In comparison to existing approaches, the suggested method can produce optimistic outcomes based on the simulation studies.
Agriculture is the primary concern in India and it requires more technological developments to be incorporated when compared to other industrial developments. Information and Communication Technologies (ICT) provides ...
Agriculture is the primary concern in India and it requires more technological developments to be incorporated when compared to other industrial developments. Information and Communication Technologies (ICT) provides a simple and cost effective technique to the farmers for enabling the precision agriculture. An information sharing system is developed through this study to support the small scale farmers. The technological developments in smart phone application and web application are used as a path to reach the small scale farmers. The application developed through this study shares an information about sugar cane crop like fertilizer requirement, pesticide requirement etc. This system will provide important and timely information to the small scale farmers like a handy agriculture guide.
On p. 2, first column, last paragraph, the sentence before the last contains a typographical error: “decrease” should be changed to “increase,” i.e., the senten
On p. 2, first column, last paragraph, the sentence before the last contains a typographical error: “decrease” should be changed to “increase,” i.e., the senten
In the present article the author develop the solution of Fractional Kinetic Equation in a new and further generalized form by involving the ζ-Gauss Hypergeometric Functions as Kinetic Equations are having great impo...
In the present article the author develop the solution of Fractional Kinetic Equation in a new and further generalized form by involving the ζ-Gauss Hypergeometric Functions as Kinetic Equations are having great importance in certain astrophysical problems. The change of chemical composition in star like the sun can be computed by this new generalized form of Kinetic equations. The main fold generality of the ζ-Gauss Hypergeometric Functions is discussed in terms of the solution of the Fractional Kinetic Equation. Special case involving the Gauss Hypergeometric function are also considered. The obtained results imply more precisely the known results and easily computable solution can also be established by the given results.
Due to the poor regularization capability of single Convolutional Neural Network (CNN), the performance of face recognition system is severely affected. Also, the input facial image data for recognition is influenced ...
Due to the poor regularization capability of single Convolutional Neural Network (CNN), the performance of face recognition system is severely affected. Also, the input facial image data for recognition is influenced by surrounding information like light, expression, brightness, contrast, pose variations and other factors. This issue is overcome by using ensemble-based feature learning ofCNN and local binary patterns (LBP). It also aids in improving the occlusion-related low pedestrian detection rate. To begin, the LBP operator is used to extract texture features from the face and by using different 10 CNN architectures, different part of facial information is learnt. This is mainly used to improve the performance of underlying networking attributes and thereby it leads to enhanced classification results using the Softmaxactivation function. With the introduced new form of face recognition focused on parallel ensemble learning of convolutional neural network and local binary pattern for feature extraction, the obtained results outperforms the existing state-of-art techniques. Finally, utilizing majority voting, the approach of parallel ensemble learning is employed to obtain the final result of face recognition. The ORL and Yale-B face datasets identification rates climb to 98.1% and 99.2 percent, respectively, for our propose system. The proposed approach is demonstrated in the experiments to improve not only the model’s immunity to withstand with different illumination, expression, lighting, brightness and posture conditions, but also the accuracy of face recognition with the poor regularization metrics, which denies in reaching the global solution in the solution space.
In this paper, a subdomain Galerkin method is set up to find solutions of singularly perturbed boundary value problems which are used widely in many areas such as chemical reactor theory, aerodynamics, quantum mechani...
In this paper, a subdomain Galerkin method is set up to find solutions of singularly perturbed boundary value problems which are used widely in many areas such as chemical reactor theory, aerodynamics, quantum mechanics, reaction-diffusion process, optimal control, etc. A combination of the cubic B-spline base functions as an approximation function is used to build up the presented method over the geometrically graded mesh. Thus finer mesh can be established through the end parts of the problem domain where steep solutions exist.
Glaucoma is a leading type of eye disease that affects the optic nerve causing permanent vision loss. As this optic nerve is important for good vision safety, glaucoma can be prevented only if detected earlier. Optic ...
Glaucoma is a leading type of eye disease that affects the optic nerve causing permanent vision loss. As this optic nerve is important for good vision safety, glaucoma can be prevented only if detected earlier. Optic disc to cup ratio is one of the key factors for glaucoma diagnosis with abnormally high eye pressure. A descriptive analysis of glaucoma diagnosis using Convolutional Neural Network (CNN) for spectral color detection of the eye is presented in this study. Initially, the color components are separated as red, green, and blue. Then, the region of Interest (ROI) is obtained from the green channel of the fundus image for the feature extraction. The Green channel is used for the fundus image analysis and detection because it is the only sensitive and high contrast color that the other two components for humans. Finally, the proposed system’s glaucoma color spectral diagnosis and its performance are analyzed using CNN with accuracy.
In this paper, image stitching strategy is proposed to prepare a virtual slide image of the sample of activated sludge obtained from the wastewater treatment plant. The bright-field microscopic images have inherent pr...
In this paper, image stitching strategy is proposed to prepare a virtual slide image of the sample of activated sludge obtained from the wastewater treatment plant. The bright-field microscopic images have inherent problem of vignetting and less contrast, which result into failed image registration by conventional methods. Our method involves illumination correction, image segmentation, image registration and finally, image stitching. First, flat-field correction method is applied to all the acquired field of views (FOVs) to balance the illumination on each FOV. In the second step, adaptive thresholding method is employed to segment all the acquired FOVs to convert into binary images. This step is meant to increase the accuracy of finding the overlapping region during image registration. Then, phase correlation is used to find the overlapping region between images in horizontal direction during image stitching for each row of the microscopy slide, and in vertical direction subsequently for image stitching between the rows. The proposed method has been compared with the state-of-the-art algorithms using subjective inspection, and no reference evaluation indices of entropy and clarity. From the evaluation, we had observed that the proposed method performs better.
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