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User preference profiling is important in both social networking mining and recommender systems. Facebook provides information of page category over two hundred relating to user preferences, but the predefined categories may not fit application well. Explicitly mapping those categories to a desirable set of user preferences is a tedious task. This paper proposes an effective user profiling technique...
The breast cancer is one of the most popular cause of death among women. It is also one of the diseases that can be cured and has high healing chances when it is detected in the early stages [1]. Detecting the cancer and differentiating between the diagnosis that affirm whether a patient has breast cancer or not has been considered as a big challenge. In order to have an accurate diagnosis, Support...
Drug-Drug Interactions (DDI) is a cause of treatment inefficacy and toxicity. The most DDI involve drug metabolism which related to enzyme and transporter protein. Drug-enzyme actions that alter the metabolism of other drugs consist of substrate, inhibitor and inducer. Non-communicable diseases (NCDs) are the leading cause of death, drugs that are used in NCDs can increase interaction probability...
Grape constitutes one of the most widely grown fruit crop in the India. Manual observation of experts is used in practice for detection of leaf diseases, which takes more time for further control action. Without accurate disease diagnosis, proper control actions cannot be taken at appropriate time. This is where modern agriculture technique is required to detect and prevent the leaf from different...
In software project management, software development effort estimation (SDEE) is one of the critical activities. Analogy-Based Estimation (ABE) is most popular estimation technique suggested in SDEE literature [1, 7, 22]. Researchers have proposed various methods to improve the accuracy of ABE by adjusting the retrieved solution. The research suggests all published calibration methods depend on linear...
With the large volume of network traffic flow, it is necessary to preprocess raw data before classification to gain the accurate results speedily. Feature selection is an essential approach in preprocessing phase. The Principal Component Analysis (PCA) is recognized as an effective and efficient method. In this paper, we classify network traffic by using the PCA technique together with six machine...
The demand of text classification is growing significantly in web searching, data mining, web ranking, recommendation systems and so many other fields of information and technology. This paper illustrates the text classification process on different dataset using some standard supervised machine learning techniques. Text documents can be classified through various kinds of classifiers. Labeled text...
Dengue virus infection or dengue fever is caused by the dengue virus (DENV). It is transmitted to humans by mosquitoes. There are four serotypes classified together based on their surface antigens. Each serotype can provide specific immunity and short-term cross-immunity in human. Several studies have examined the classification of dengue molecules into four major classes including methods such as...
Liver fibrosis is the natural wound healing response to parenchymal injury in chronic liver diseases and may eventually result in liver cirrhosis. Noninvasive imaging methods widely used for the diagnosis of liver fibrosis are Magnetic Resonance Imaging (MRI), Computed tomography (CT), Ultrasound and Elastography. This work aims to extract texture features from ultrasonic liver images. The Artificial...
This paper provides a review of research on the application of data mining techniques for decision making in agriculture. The paper reports the application of a number of data mining techniques including artificial neural networks, Bayesian networks and support vector machines. The review has outlined a number of promising techniques that have been used to understand the relationships of various climate...
A challenge is indexing the facial beauty by a machine as same evaluated by human beings. A question arises: Can beauty be learnt by machines? Every individual have different concept of facial beauty. Somebody can be attracted by someone but might not be by another person. In recent past, many psychologists, neurologists and other scientists have done tremendous work in this area. This work presents...
Supervised learning of convolutional neural networks (CNNs) can require very large amounts of labeled data. Labeling thousands or millions of training examples can be extremely time consuming and costly. One direction towards addressing this problem is to create features from unlabeled data. In this paper we propose a new method for training a CNN, with no need for labeled instances. This method for...
The advent of Optical Coherence Tomography (OCT) imaging has engendered a quantum leap in ophthalmological disease diagnosis. Specifically, in relation to various retinal disorders, OCT has facilitated visualization of minute structural changes in retinal and choroid layers. However, due to dearth of ophthalmologists, and time and effort required in manual analysis, a large number of patients fail...
Authorship identification is a problem of data mining and classification. There are numerous methods and algorithms have been published to understand its nature. Although, researchers still investigate best and simple solutions due to its heterogeneous and multilingual characteristics. This study introduced new authorship identification process based on artificial neural network (ANN) model using...
Most of the Natural and Spoken Language Processing tasks now employ Neural Networks (NN), allowing them to reach impressive performances. Embedding features allow the NLP systems to represent input vectors in a latent space and to improve the observed performances. In this context, Recurrent Neural Network (RNN) based architectures such as Long Short-Term Memory (LSTM) are well known for their capacity...
The personal identification from the features of personal face and voice is described in this study. The face area is detected from the picture including both the face and the complicated background by using Microsoft Kinect sensor. The personal voice is also recorded from Kinect microphone array, which is used for the personal identification. The features of the personal face are calculated from...
Microarray data analysis directly relates with the state of disease through gene expression profile, and is based upon several feature extractions to classification methodologies. This paper focuses on the study of 8 different ways of feature selection preprocess methods from 4 different feature selection methods. They are Minimum Redundancy-Maximum Relevance (mRMR), Max Relevance (MaxRel), Quadratic...
Physical measurement have been becoming increasingly helpful in monitoring the humans health status. Manual measurement of physical status is time consuming and may result in misdiagnosing, so an automatic method for identification the status of physical is urgently needed. This paper presents a novel feature extraction method based on using constrained high dispersal network for depth images and...
Computer-aided schizophrenia diagnosis is a difficult task that has been developing for last decades. Since traditional classifiers have not reached sufficient sensitivity and specificity, another possible way is combining the classifiers in ensembles. In this paper, we take advantage of random subspace ensemble method and combine it with multi-layer perceptron (MLP) and support vector machines (SVM)...
The following paper discusses the development of a risk-based cost estimation model for completing non-standard manufacturing orders. The model in question is a hybrid of Monte Carlo Simulation (MCS), which constitutes the main module of the applied model. Vector of order risk probability, which is the input data for the MCS module, is highly difficult to assess and is burdened to a considerable degree...
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