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This work is devoted to the fusion of fuzzy sets generated by already existing, highly sophisticated built-up area detection algorithms in order to enhance the quality of urban area extraction results. Coarse resolution ASAR Wide Swath Mode (75 m) and high resolution ASAR Fine Mode (30 m) has been used for analysis. Through the combination of multi-resolution information the advantages of both data...
It has been already proved that ASAR Wide Swath Mode data can be used to extract human settlement extents at the global level with a consistent quality all over the world. To improve this performance, a different and more refined approach has been designed and tested. The improved procedure involves the knowledge about the amount of scenes that are combined for the input ASAR WSM data to the procedure,...
With the proliferation of Internet of Things (IoT) devices such as smartphones, sensors, cameras, and RFIDs, it is possible to collect massive amount of data for localization and tracking of people within commercial buildings. Enabled by such occupancy monitoring capabilities, there are extensive opportunities for improving the energy consumption of buildings via smart HVAC control. In this respect,...
As data sources and algorithm choices become increasingly more available for automatically extracting and reconstructing 3D buildings, methods are needed to assess the accuracy of the classification process. Our research goal is to compare validation data sources and methods to assess objectivity, sensitivity, and reliability of current validation approaches. Our results show that when relying on...
With the rapid maturity of internet and web technology over the last decades, the number of Indonesian online news articles is growing rapidly on the web at a pace we never experienced before. In this paper, we introduce a combination of rule-based and machine learning approach to find the sentences that have tropical disease information in them, such as the incidence date and the number of casualty,...
This study analyses the factors affecting students' academic performance that contributes to the prediction of their failure and dropout using educational data mining. This paper suggests the use of various data mining techniques to identify the weak students who are likely to perform poorly in their academics. WEKA, an open source tool for data mining was used to evaluate the attributes predicting...
Business and Research organizations are continuously generating huge amount of high dimensional data. They need to analyze this data in real-time with minimum cost. Data pre-processing techniques in combination with dimensionality reduction techniques are widely used by researchers to improve the quality of data and reduce the time, cost required to analyze the data. But standard methods are not available...
Internet has become a more popular medium of sharing the opinions or feedback about particular topics. The feedbacks are often in the form of numerical ratings and text. Numerical ratings are easily processed but waste amount of unstructured textual data present on the internet in the forms of web blogs, emails, customer experiences, tweets etc that is left unprocessed. This data should be processed...
For extorting the helpful comprehension concealed in the biggest compilation of a database the data mining technology is used. There are some negative approaches occurred about the data mining technology, among which the potential privacy incursion and potential discrimination. The latter consists of irrationally considering individuals on the source of their fitting to an exact group. Data mining...
Recent emerging growth of data created so many challenges in data mining. Data mining is the process of extracting valid, previously known & comprehensive datasets for the future decision making. As the improved technology by World Wide Web the streaming data come into picture with its challenges. The data which change with time & update its value is known as streaming data. As the...
Due to the huge number of research articles in the biomedical domain, it becomes more and more important to develop methods to find relevant articles of our specific research interests. Keyword extraction is a useful method to find important topics from documents and summarize their major information. Unfortunately, it is hard to select appropriate keywords extracted by traditional method of keyword...
In this paper, we propose an expert search scheme in social networks. The proposed scheme updates a profile by analyzing recent activities, and considers the reliability scores of users and users' ratings that are computed by the updated profile. A user's profile is created by extracting a keyword from the recent activity information and calculating similarity with the keyword. To verify the performance...
We analyze the performance of classification schemes on information collected from social conversation posted in Twitter among audiences of a popular US based TV show. In this research, we consider entropy as a measure of information exchange in a group conversation that is related to social, temporal, and second screen device features. The group conversations are identified by hashtags present in...
Accurate robot mapping, localisation and navigation remains an unsolved problem for challenging real-life indoor environments. Many approaches to Simultaneous Localisation And Mapping (SLAM) have been proposed but few attempts have been made to improve performance by using appropriate prior maps. Information such as floor plans or architectural drawings is available and there is a rich literature...
From a large amount of data, significant knowledge is discovered by means of applying techniques in the knowledge management process and those techniques is known as Data mining techniques. For a specific domain, a form of knowledge discovery called data mining is necessary for solving the problems. The classes of unknown data are detected by the technique called classification. Neural networks, rule...
This paper proposes a method to identify the arohana-avarohana of carnatic raga. Carnatic raga is broadly classified as melakarta (parent) and janya (child) raga. Arohana-avarohana of 10 different ragas is collected from 16 different singers. 16 audio data are collected for each raga. 11 among the 16 are used in the training phase and the remaining 5 are used for testing. The acoustic feature, MFCC...
With the widespread use of Internet, the possibilities of exposing confidential data to invaders or attackers increases. Intrusion Detection System (IDS) is used for detecting various intrusions in network environment and to prevent data from malicious attackers. In this paper, a combined algorithm based on Principal Component Analysis (PCA) and Core Vector Machine (CVM), which is an extremely fast...
Feature selection is an effective technique for dimensionality reduction and an essential step in successful data mining applications. It is a process of selecting a subset of features from the candidate set of features according to certain criteria. The main goal of supervised learning is finding feature subset that produces higher classification accuracy. The proposed method is to select an optimal...
Classification is widely used technique in the data mining domain, where scalability and efficiency are the immediate problems in classification algorithms for large databases Now a day's large amount of data is. generated, that need to be analyse, and pattern have to be extracted from that to get some knowledge. Classification is a supervised machine learning task which builds a model from labelled...
To employ and develop the performance of the dimensionality reduction for microarray data there is need of good dimension reduction technique. High-dimensional data bring great challenges in terms of computational complexity and classification performance. Therefore, it is necessary to effectively compress in a low-dimensional feature space from high dimensional feature space to design a learner with...
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