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Laser Induced Breakdown Spectroscopy (LIBS) is an analytical technique for rapid chemical sensing that is becoming increasingly in field applications. LIBS is a form of atomic emission spectroscopy. When a high-powered pulsed laser beam is focused on the sample, it produces a plasma that emits wavelengths of light that can be observed using a spectrograph to identify the composition of the target...
A ‘weak classifier’ is a classifier that performed badly for many raisons. In general, bad performance can be caused by the highly dimensionality of the data and also the instability of the classifier. Ensemble methods has been developed in order to overcome this problems. The most popular are bagging and Random Subspace Methods (RSM). We propose to use a combination of concepts used in Bagging and...
Cognitive radio (CR) is a recent technology to tackle the problem of radio spectrum scarcity. Successful spectrum sensing is fundamental in performance of CR networks; hence, a PSO-based weighting method is proposed in order to improve the functionality of machine learning techniques which are used with the aim of detecting the activity of secondary users in cooperative cognitive radio (CCR) networks...
The earlier remote password authentication schemes required a service providing server to authenticate a legitimate user for remote login. However, the traditional schemes are not useful in multi-server architecture because of multiple user ids and passwords. In this paper, we present a remote password authentication scheme for multi-server architecture that can be robust and improved network security...
In recent years, the detection of drowsiness based on Electroencephalogram (EEG) signal has been paid great attentions. Most of the popular algorithms used for Brain Computer Interface (BCI) applications are, the Support Vector Machine (SVM) and the Artificial Neuronal Network (ANN)). The challenge is to developed a drowsiness detection system that is at once adapt to an embedded implementation and...
Speech emotion recognition has become an active topic in pattern recognition. Specifically, support vector machine (SVM) is an effective classifier due to the application of the nonlinear mapping function, which can map the data into high or ever infinite dimensional feature space. However, a single kernel function might not sufficient to describe the different properties of spontaneous speech emotion...
Email is a rapid and cheap communication medium for sending and receiving information where spam is becoming a nuisance for such communication. A good spam filtering cannot only be achieved by high performance accuracy but low false positive is also necessary. This paper presents a combining classifiers approach with committee selection mechanism where the main objective is to combine individual decisions...
Multi-view face detection is a challenging problem due to dramatic appearance changes under various pose, illumination and expression conditions. In this paper we consider the problem of multi-view face detection. In this paper detection, It propose to apply Deep Convolutional Neural Networks (DCNN) as the post filter, which is known to be able to extract effective features automatically during learning...
Support vector machine (SVM) is a supervised method widely used in the statistical classification and regression analysis. SVM training can be solved via the interior point method (IPM) with the advantages of low storage, fast convergence and easy parallelization. However, it is still confronted with the challenges of training speed and memory use. In this paper, we propose a parallel primal-dual...
Support vector machine (SVM) is a supervised method widely used in the statistical classification and regression analysis. SVM training can be solved via the interior point method (IPM) with the advantages of low storage, fast convergence and easy parallelization. However, it is still confronted with the challenges of training speed and memory use. In this paper, we propose a parallel primal-dual...
Image classification is one of the most multifaceted disciplines in image processing. There are quite a few approaches to categorize images and they offer good classification outcome but they not be up to snuff to provide acceptable classification upshots when the image comprises blurry content. The two chief techniques for image classification are supervised and unsupervised classification. Mutually...
In this study, we designed and constructed a system to identify human actions using integrated sensors in smartphones. There are six actions that are selected for recognition include: walking, standing, sitting, lying down, up the stairs, down the stairs. In this system, Support Vector Machine (SVM) is used to classify and identify action. Collected data from sensors are analyzed for the classification...
The increasing cardiac diseases of people in recent years demand an early detection of heart diseases using electrocardiogram (ECG) signal processing techniques. In this work we present a semi automatic scheme to discriminate patient-specific ECG beats by using a kernel based feature extraction technique called kernel canonical correlation analysis (KCCA). The heartbeat classification scheme uses...
This paper describes an experiment done to investigate author profiling of tweets in English and Spanish, particularly for cross genre evaluation. Profiling consists of age and gender classification. The training sets were taken from tweets while genres for evaluation come from blogs, hotel reviews, other tweets collected in a different time, as well as other social media. Comparisons were done between...
Degradation data is an important information source which is usually used to predict products' lifetime, for instance in accelerated degradation testing (ADT) and health management. Degradation data can be easier and cheaper obtained than failure data. As a result, it has been widely applied. However, due to some restrictions of funds and the development cycle, the degradation data of some products...
In Korea, authors of the newspaper article tend to express their intention indirectly, that is, they choose a method to leave out some important facts, or sometimes uses biased terms to support their opinion. Since they're not expressing their opinion directly, detecting the political bias is a difficult task. In this paper, we propose a method to detect political bias in the Korean articles by first...
Development of Optical Character Recognition (OCR) system for Indian script is an active area of research today. In this paper, we are concerned with the recognition of printed Oriya script a popular Indian script. The development of OCR for this script is challenging as number of identified classes are more than 380 which includes similar looking and compound characters. This paper presents the gradient...
Recommendation systems aim at recommending relevant items to the users of the system. Recommendation Systems provide efficient recommendations based on algorithms used for classification and ranking. There exist various ways by which classification can be achieved in a supervised or unsupervised manner. Since the sample datasets that are used for experiments are large and also contain more number...
The expansion of the dynamic Web increases the digital documents, which has attracted many researchers to work in the field of text classification. It is an important and well studied area of machine learning with a variety of modern applications. A good feature selection is of paramount importance to increase the efficiency of the classifiers working on text data. Choosing the most relevant features...
This paper presents a novelty classification method based on multivariate Bernoulli naive Bayes with Dirichlet prior and hyper parameter optimization. We test the proposed method on 15-Scenes and Msrc-v2 data set by comparing with basic multivariate Bernoulli naive Bayes and SVM (Support Vector Machine). The experiments show that our method has advantages both in running time and classification precision.
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