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Text-to-Speech (TTS), an astounding feature to assemble computer with intelligence and to induce sound is seemingly a challenging task as it is related to the propagation of uncertainty with the input. This is because TTS evolutes the input based on the probabilities and not with certainty ratios. TTS is accomplished by generating the sound structure/phoneme and then classifying these phonemes in...
Network Intrusion Detection Systems must effectively identify security threats and protect the applications. The focus of the paper is the presence of class imbalance problem in intrusion datasets. An efficient intrusion detection system must accurately identify all threats even if they form a small fraction of the intrusion data. The effect of class imbalance on the benchmark NSL_KDD dataset is evaluated...
The N-Queens problem has been studied for over a century. The N-Queens problem may be solved using a variety of methods including backtracking algorithms and mathematical equations such as magic squares. We propose a more efficient approach to the most used technique, backtracking, by removing the threatened cells in order to decrease the number of trial and error steps.
Today's world is made of electronic networks. Everyday huge amount of sensitive data are passed through these networks. These networks are the backbones of the industries like banking, transportation, healthcare, defense, communication etc. So securing the data passed through these networks is essential. Organizations are investing more and more money to secure their data from the attackers. On the...
In recent years, many successful machine learning applications have been developed. Classification & Clustering is one such. This application is cross-disciplinary, now that it is based on data mining algorithms on the technical side and on graphemes and morphophonemic on the linguistic side. It will thus map the correspondence between grapheme 〈y〉 and related phonemes via morphemes in a given...
Classification systems adapts many machine learning techniques for quality performance in data classification. The neural networks has some unique characteristics and features which can handle high dimensional features and documents with noise and contradictory data. Classification is important to classify the input text into different domains appropriately. This paper give out a move towards classification...
Besides required courses which are compulsory for each student to be taken, universities also offer elective courses chosen by the students themselves. In their undergraduate study, since students are not guided about the elective courses, they lack information about the description and content of the course and generally fail to take the appropriate ones for their course of study. As a solution,...
There is a need to analyze sentiments of people with the advancement of social media like social networks, blogs, and presentations. Sentiment analysis is a very challenging task as there is a huge amount of data present online. It is the analysis of sentiments on a particular entity in terms of positive, negative or neutral polarity. The challenge is the identification of the meaning of the word...
Decimal arithmetic is gaining more and more importance in business, commercial and financial applications due to error free and high speed computations. In this work, high speed radix10 divider architecture has been proposed to reduce the delay. This paper presents a modified architecture in which intermediate results are utilized to perform the high speed division. The modified architecture is simulated...
Cloud computing is fast gaining popularity in educational institutions of developing countries like Nigeria. Software as a Service, Platform as a Service and Infrastructure as a Service are the three key models through which cloud computing services are delivered to end-users. A number of studies have been conducted to identify the enabling factors as well as the issues being faced as regards the...
A defensive mechanism, which encompasses a variety of services and protections, has been proposed by several researchers for many organizations to protect system resources from misuse. In the practical use of defensive mechanisms such as CAPTCHAs and spam filters, attackers and defenders exchange 'victories,' each celebrating (temporary) success in breaking and defending. In this paper, since most...
Sentiment classification has been an important issue in natural language processing in recent years. In order to solve the distribution difference problem in cross-domain sentiment classification, we propose a featured-adjusted EM-based naïve Bayes algorithm which combines feature adaption and instance adaption simultaneously, and this algorithm can adjust the parameters in EM algorithm by the results...
Feature selection is a process of selecting desired number of features from a large set of original features that purely contribute to the prediction of a test data with the help of a classifier. Many application areas such as, gene expression array analysis, test processing of internet document and combinatorial chemistry make use of feature selection, due to the presence of tens or hundreds of thousands...
Network security has become one of the well-known concerns in the last decades. Machine learning techniques are robust methods in detecting malicious activities and network threats. Most previous works learn offline supervised classifiers while they require large amounts of labeled examples and also should update models because the data change over time in real world applications. To alleviate these...
Geometry features especially triangle has been widely used in face, fingerprint, vehicle detection and digit recognition. Features from the triangle are used to generate useful features for classification processed. Recently, triangle features used in digit recognition has adopted angle as part of features. This has influenced accuracy due to big gap between angle values and other feature values such...
Educational data mining concerns of developing methods to discover hidden patterns from educational data. The quality of data mining techniques depends on the collected data and features. In this paper, we proposed a new student performance model with a new category of features, which called behavioral features. This type of features is related to the learner interactivity with e-learning system....
The main goal of attack detection system is classification of system activities into two basic groups of normal activities and intrusion activities. However many studies have been done in the field of intrusion detection, finding a method with min error and max accuracy is still a challenge. The main aim of this study is presenting a DOS attack intrusion detection system by using support vector regression...
Chronic kidney disease is a universal common obstacle which its outcomes can be prevented or delayed by early detection and cure. Classification of kidney disease is vital for global improvement and accomplishment of practical guidance. Therefore, data mining and machine learning techniques can be used to discover knowledge and identify patterns for classification. Since there exist features that...
In this paper, a new algorithm for visualization of high-multidimensional data is described. The algorithm follows several steps. At first, centers representing several categories are selected, and Euclidean distances between these centers are calculated in a high-dimensional space. Then these centers are placed in a 2-dimensional space in such a way that distances in this 2-dimensional space are...
In this paper, we proposed a novel medical images based computer aided diagnosis method named ECARMI. It combines the cost-sensitive learning with selective ensemble techniques to improve the medical images based diagnosis performance. At first, selective cost-sensitive SVM ensemble is utilized to perform the classification of medical images. Then, the Regions of Interest (ROIs) in positively identified...
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