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In this paper, we propose a classification model for learning state based on individual biometric data. In particular, we use the pupil size as a biometric data and the data has been collected from 72 participants. We also deploy the support vector machine (SVM) in conjunction with k-fold validation as an analysis tool. In order to improve the performance of the SVM, the we remove outliers from the...
Speech classification is an important part of speech signal processing. It is significant to classify speech accurately and quickly in speech coding and speech synthesis. Because of the diversity and uncertainty of the speech signals, the traditional classification method is slow and not so accurate in the large-scale application of real speech classification. In order to improve the accuracy and...
The non-equilibrium of network traffic data brings about the non-equilibrium of classification. Feature extraction is an effective method to reduce data dimensions, while it can intensify the influence of non-equilibrium further. A secondary feature extraction algorithm of multidimensional assessment is proposed in this study. The features of network traffic are evaluated in different dimensions to...
Location-Based Social Networks (LBSNs) have built bridges between virtual space and real-world mobility in recent years. The massive check-in data generated in LBSNs has made it possible to predict users' future check-in location, which has proved meaningful for e-commerce developments. Existing studies mainly focus on predicting the next check-in location with a coarse granularity, which shows limited...
Nowadays the machine-based classification model has made great progress, but there is still a large gap in dealing with the complex problems when compared with human beings. In addition, most existing classification models pursue high accuracy without consideration of the cost in the decision-making process. To address these issues, a man-machine collaborative recognition mechanism based on humanware...
During the past five years, many researchers have developed different approaches to the classification of images, which are used for a variety of scientific tasks [1, 2, 3 and 4]. The research is aimed at solving task of classification of three-dimensional objects by the images of their projections in systems of automatic recognition of randomly located parts and products in the industrial belt. This...
There has been a new type of attacks, LDoS attack against BGP sessions (BGP-LDoS). It is more harmful than traditional network attacks. However, existing security solutions for inter domain routing system are mainly addressed to deal with threats which come from control plane and generally utilize abnormal inter domain routing information to launch an attack. They are of no effect to detect BGP-LDoS...
There has been a dramatic increase in the sharing of opinions and information across different web platforms and social media, especially online product reviews. Cloud web portals, such as getApp.com, were designed to amalgamate cloud service information and to also examine how consumers evaluate their experience of using cloud computing products. The current literature shows the growing importance...
The attorney's office in Brazil, receive daily a lot of notifications. These notifications must be manually analyzed by procurators to determine what kind of document should they prepare to respond. This situation causes in many cases notifications are not answered in time causing these prescribed. All this has motivated the development of this work whose main objective is the development of a computational...
Software fault prediction is a valuable exercise in software quality assurance to best allocate limited testing resources. Classification is one of the effective methods for software fault prediction. The classification models are trained based on the datasets obtained by mining software historical repositories. However, the performance of the models depends on the quality of datasets. In this paper,...
We present in this paper the analysis results of prominent educational characteristics differentiating people from the two regions in the world: advanced economies versus east Asia and the pacific countries. The automatic multivariate analysis of classification trends has been demonstrated through the visual data mining tool called KNIME. We found from the empirical studies that from the years 1950...
Noises are inevitable when mining software archives for software fault prediction. Although some researchers have investigated the noise tolerance of existing feature selection methods, few studies focus on proposing new feature selection methods with a certain noise tolerance. To solve this issue, we propose a novel method FECS (FEature Clustering with Selection strategies). This method includes...
For the last few years, text mining has been gaining significant importance. Since Knowledge is now available to users through variety of sources i.e. electronic media, digital media, print media, and many more. Due to huge availability of text in numerous forms, a lot of unstructured data has been recorded by research experts and have found numerous ways in literature to convert this scattered text...
At present, user context perception, recognition and prediction is a hot research topic in smart community. As an important user context information, more and more researchers have studied the traffic pattern recognition, however, these studies cannot meet the requirement of high recognition accuracy, rich recognition categories and convenient implementation at the same time. Therefore, the purpose...
Human Activity Recognition (HAR) have been developed for recognize context generated from human. In real environment system required multi -sensor for support large area and get more accuracy result. Using multi-sensor make high dimensional data which inefficacious for classification model. This paper is concerned with developing classification model that supports high dimensional data and reducing...
As the trend changes, the data can be transit through small hand hold devices, though the small hand hold devices are being used by the users and providing simple portability, but these devices are isolate unless they connected via network. The Clouds provide more services than the hand hold devices. Through this paper, we propose A Modern Cyclic Approach to solve a Classification Problem in Cloud...
In this paper, we present our solution and experimental results of the application of semi-supervised machine learning techniques and the improvement of SVM algorithm to build text classification applications. Firstly, we create a features model which is based on labeled data, and then we will be improved it by the unlabeled data. The technique that is to be added a label into new data is based on...
In the context of a magnetic field-based indoor location system, this paper proposes a feature extraction process that uses magnetic-field temporal and spectral features in order to develop a classification model of indoor places, using only a magnetometer included in popular smartphones. We initially propose 46 features, 26 derived from the spectral evolution and 20 from the temporal one, chosen...
Since the traditional detection method of wheat quality was tedious and time-consuming, near infrared reflectance spectroscopy (NIRS) combined with RBF artificial neural network was used to classification and detection wheat quality non-destructively and quickly in this paper. The ware point of samples obtained by the NIRS is too many, resulting in the structure of RBF neural network is too complex,...
Even after a decade of trials, Mobile-Payment systems are yet to witness large-scale commercial deployments. Various studies have been conducted to investigate the cause resulting in the various theories and analysis. Based on the extensive literature survey conducted as part of this research work, three causes have been identified namely, the heterogeneous nature of the m-payment landscape, lack...
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