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Wireless Sensor Networks (WSNs) consist of small nodes with sensing, computation, and wireless communication capabilities. Wireless Sensor Network (WSN) is a promising data mining solution for precision agriculture. Instrumented with wireless sensors, it will become available to monitor the plants for real time, such as air temperature, soil water content, and nutrition stress. This real time information...
The increasing availability of huge amounts of data pertaining to time and position of moving objects generated by different sources using a wide variety of technologies (e.g., RFID tags, GPS, GSM networks) leads to large spatial data collections. Mining such amounts of data is challenging, since the possibility to extract useful information from this peculiar kind of data is crucial in many application...
Mobile ad hoc networks are becoming an important concept of modern communication technologies and services. It provides some advantages to this communication world such as self-organizing and decentralization. In this paper, we are going to design a cluster-based multi source multicast routing protocol with new cluster head election, path construction and maintenance techniques. The main objective...
Document clustering organizes documents into groups such that each group contains documents with similar content. This paper presents the results of an experimental study of some common document clustering techniques. In particular, comparison of Euclidean K-means (K-Means), Spherical K-means(SK-Means) and unsupervised Principal Direction Divisive Partitioning (PDDP) algorithms is done. A comparative...
Summary form only given. Data streams are continuous flows of data. Examples of data streams include network traffic, sensor data, call center records and so on. Their sheer volume and speed pose a great challenge for the data mining community to mine them. Data streams demonstrate several unique properties: infinite length, concept-drift, concept-evolution, and feature-evolution. Concept-drift occurs...
Traditional method to assesse the equipment support operational skill is by locale examining and examinant experience, it is presented of evaluation method based on traininging process data and k means clustering, and a calculating case is validated. The case shows the arithmetic is used to support operational skill evaluation, whose indexes are quite comprehensive. Historical data of daily traininging,...
The world has fundamentally changed as the Internet has become a universal means of communication. The Web is a huge virtual space where to express individual opinions and influence any aspect of life. Internet contains a wealth of data that can be mined to detect valuable opinions, with implications even in the political arena. Nowadays the Web sources are more accessible and valuable than ever before,...
Many ellipse detection algorithms produce multiple elliptic hypotheses corresponding to a single elliptic object. Thus, it is needed to identify similar ellipses that possibly belong to the same object and cluster them as a single object. This will reduce the computational and memory requirement for further higher level processing of ellipse detection algorithms. Here, we present a method better than...
Topic model is an increasing useful tool to analyze the semantic level meanings and capture the topical features. However, there is few research about the comparative study of the topic models. In this paper, we describe our comparative study of three topic models in the extrinsic application of topic clustering. The topic model distance is defined on the converged parameters of topic models, which...
A fundamental problem that confronts peer-to-peer (P2P) applications is to construct an efficient system which can support flexible search. This paper presents CTL-P2P, a cluster-based two-layered P2P architecture model that addresses this problem. CTL-P2P is a combination of structured topology and unstructured topology. It utilizes semantic-based interest and behavioural peer clustering to form...
Localization is getting more attention in the wireless technology field. Even though that many localization systems have been proposed, but yet there is no good solution for a system with minimized deployment effort and overhead to the wireless network traffic. The purpose of our work is to propose a localization system that may provide accuracy and eliminate the off-line training at the same time.
For the robot vision system in apple harvesting robot, a new image segmentation method based on entropy clustering is proposed in HSI color space. Firstly, noise was wiped off by using weighted algorithm of median filtering in HSI color space instead of traditional algorithm in RGB model; secondly, Hue and Saturation components were extracted to do entropy clustering with their independence with Intensity,...
Similarity is an important concept in information theory. A challenging question is how to measure the amount of shared information between two systems. A large number of metrics are proposed and used to measure similarity between two computer programs or two portions of the same program. In this paper, we present an approach for assessing which metrics are most useful for similarity prediction in...
An energy-aware data gathering protocol called EADGP that maximizes the network lifetime for wireless sensor networks is proposed in this paper. EADGP introduces a novel distributed hierarchical clustering method. In order to reduce energy consumption and realize load balance, a new cost metric and a metric-mapping function is presented during the cluster head selection phase. Unlike traditional energy-based...
This paper proposes a method of data stream clustering for stock data analysis. The method aims to retain shape and tend features during the clustering process. The experimental results show that the shape-based clustering over data streams can get the evolution accuracy of 95% with the reasonable parameters.
This paper presents a method to improve the performance of Information Retrieval System (IRS) by increasing the no of relevant documents retrieved. There are several types of uncertainty and fuzziness associated with IRS like search term uncertainty, relevance uncertainty involved in retrieving of irrelevant documents. The aim of this paper is to eliminate different types of uncertainty and increase...
One of the most important problems in wireless sensor networks is Energy-efficiency Routing Protocol Design. In This Work We propose a hierarchical Clustering Method For energy conservation in Wireless Sensor Networks. first, we divide the sensor nodes to Small Size clusters and determine a cluster head for each cluster in the network. The residual energy and distance to BS are parameters for CH election...
The paper deals with the text classification problem where labeled training samples are very limited while unlabeled data are readily available in large quantities. The paper proposes an efficient classification algorithm that incorporates a weighted k-means clustering scheme into an Expectation Maximization (EM) process. It aims to balance predictive values between labeled and unlabeled training...
The network in case of Mobile Adhoc networks is generally poorly defined or not defined at all. In Such a network the data can be relayed/routed by intermediate nodes whose position keeps on changing. Mobile adhoc networks have some challenges like Limited wireless transmission range, broadcast nature of the wireless medium, hidden terminal and exposed terminal problems, packet losses due to transmission...
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