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Over the past few years, several approaches have been proposed to assist in the early diagnosis of Alzheimer's disease (AD) and its prodromal stage of mild cognitive impairment (MCI). For solving this high dimensional classification problem, the widely used algorithm remains to be Support Vector Machines (SVM). But due to the high variance of the data, the classification performance of SVM remains...
It is important to develop defense mechanisms to bolster the cyber-physical security of critical infocomm infrastructure (CII) systems. A basic method of defense for CII systems is a firewall. Since SCADA / ICS systems may be negatively impacted by latencies and delays introduced by firewalls, which will translate to real world impacts, any implemented firewall in the network should attempt to minimize...
Slowing cystic fibrosis (CF) lung disease progression is crucial to survival, but point-of-care technologies aimed at early detection — and possibly prevention — of rapid lung function decline are limited. This proof-of-principle study leverages a rich national patient registry and follow-up data on a local CF cohort to build an algorithm and prototype prognostic tool aimed at early detection of rapid...
The biological signals collected by the multi-electrode array are contaminated by heavy noise signals. How to quickly classify the original action potential from the measured noisy signals accurately is the basis of researches in the field of neuroscience. In this paper, we analyze the characteristics and shortcomings of Wave-clus sorting algorithm, and present a novel sorting algorithm to solve the...
Clustering is an important tool for analyzing gene expression data. Many clustering algorithms have been proposed for the analysis of gene expression data. In this article we have clustered real life gene expression data via K-Means which is one of clustering algorithms. Also, we have proposed a new method determining the initial cluster centers for K-means. We have compared results of our method...
Clustering is an important unsupervised data analysis technique, which divides data objects into clusters based on similarity. Clustering has been studied and applied in many different fields, including pattern recognition, data mining, decision science and statistics. Clustering algorithms can be mainly classified as hierarchical and partitional clustering approaches. Partitioning around medoids...
The paper is dedicated to the systemic botany domain and analyzes the degree of affinity between the species, genera and families based on fractal theory. The research is conducted on the image information from Gentianaceae family plant, in order to determine their membership to the recognized genera Gentiana, Gentianella and Gentianopsis which were previously tagged into a single genus. Some concepts...
Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it is an open issue in computer science. Analyzing and evaluating these websites can be an effective step for discovering and categorizing the features of these websites...
DDoS attacks bring huge threaten to network, how to effectively detect DDoS is a hot topic of information security. Currently, there are some methods designed to detect DDoS attacks, but the detection rate of them is low. Moreover, DDoS detection is easily misled by flash crowd traffic. In this paper, a new method to detect DDoS attacks based on RDF-SVM algorithm is proposed. By considering the importance...
Positioning applications become more popular with the advancement of location aware services. Global Positioning System is a successful solution for outdoors whereas it is not suitable for indoor environments due to the lack of line of sight for radio frequency signals. Therefore, various systems have been developed to solve the indoor positioning problem. Enhancing the performance of these systems...
Current hierarchical clustering algorithms face the risk of privacy leakage during the clustering process for big dataset. While differential privacy is a relatively recent development in the field of privacy-preserving data mining, offering more robust privacy guarantees. In the paper, BIRCH algorithm under differential privacy is studied and analyzed. Firstly, Diff-BIRCH algorithm which directly...
This paper proposes an intelligent fault diagnosis technique to detect and classify possible faults occurring in Photovoltaic strings, based on the analysis of the symptoms observed in the I-V characteristic. The technique consists of two algorithms: The first one allows the classification of faults that have not the same symptoms evolution; whi le for the second one, two Artificial Neural Networks...
The growth of social media has been exponential in the recent years. Immense amount of data is being put out onto the public domain through social media. This huge publicly available data can be used for research and a variety of applications. The objective of this paper is to counter problems with the social media dataset, namely : short text nature - the limited quantity of text data (140 to 160...
At present, shallow characteristics are usually utilized to represent the distributed features of text for Chinese spam classification, causing the problem of inexact text vector representation and low classification performance. A novel Chinese spam classification method based on weighted distributed feature is proposed by combining the features of TF-IDF weighted algorithm with the distributed text-based...
Association rule mining is a very essential data mining technique in different fields. The enormous development of the information needs increased computational power. To address this issue, it is important to study executions of mining algorithms. To find out the frequent itemsets is an essential and vital issue in numerous information mining applications. There are many algorithms present to extract...
In recent years advent of social networking services has created large amounts of data. Microblogging website is a kind of social network in which users share short messages with others. One of the most popular microblogging services is Twitter. Every day millions of people post their opinions and sentiments in this microblog. Due to the large numbers of tweets, finding new approaches to discover...
In semi administered bunching is one of the vital errands and goes for gathering the information objects into classes (groups) to such an extent that the similitude of items inside bunches is high and the comparability of articles between bunches is Less. The dataset once in a while might be in blended nature that is it might comprise of both numeric and unmitigated sort of information. So two types...
Word wide web is considered as the most important information store in recent years. Web development expands to a great extent with new technologies. Search engines are ineffective when the number of docs in the web is multiplied. In the same way, the retrieval of queries, most of which are not related to what the user was looking for. The documents are of varied and flexible web, there are tough...
Clustering is one of the prime topics in data mining. Clustering partitions the data and classifies the data into meaningful subgroups. Document clustering is a set of the document into groups such that two groups show different characteristics with respect to likeness. In this paper, an experimental exploration of similarity based method, HSC for measuring the similarity between data objects particularly...
Musical instruments are consist of wide variety of domain so manual classification of these instruments is difficult and challenging task. To make the process of classifying musical instrument easy and less dependent on human supervision given system is designed. There are some algorithm are available for classification tsk from which we uses SVM, MLP and AdaBoost for better result. This system mainly...
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