Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 38 for “"Data mining algorithms"”.
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Data Mining Algorithms for Classification of Complex Biomedical Data
… protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray classification, samples belong to several predefined categories (e.g., cancer vs. control tissues) and the goal is to build a predictor that classifies a new tissue sample based on its …
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NOVEL DATA MINING ALGORITHMS FOR ANALYSIS OF ELECTRONIC HEALTH RECORDS
… representations suitable for deep learning algorithms, (2) how to help healthcare researchers select a patient cohort from EHRs, and (3) how to use EHRs to identify patient diagnoses and treatments. In the first part of the thesis, we present a new method for learning vector representations …
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The discovery of new functional oxides using combinatorial techniques and advanced data mining algorithms
… synthesis and characterisation with advanced data mining to develop novel materials. Dielectric ceramics are of interest for use in telecommunications equipment; oxygen ion conductors are examined for use in fuel cell cathodes. Both applications are subject to ever increasing industry demands …
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Application of Data Mining Algorithms for the Improvement and Synthesis of Diagnostic Metrics for Rotating Machinery
… failure conditions and incipient faults. The algorithms which process the raw data into diagnostic and prognostic indicators are typically derived from theoretical models, traditional signal processing metrics, or through trial-and-error observations. Condition monitoring devices are becoming …
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Data Mining with Newton's Method.
<p>Capable and well-organized data mining algorithms are essential and fundamental to helpful, useful, and successful knowledge discovery in databases. We discuss several data mining algorithms including genetic algorithms (GAs). In addition, we propose a modified multivariate Newton's method (NM) …
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Enhancing web marketing by using ontology
… marketing knowledge can be augmented by applying data mining algorithms. Therefore, this knowledge which connects customers to products can be used for marketing purposes and for targeting existing and potential customers. The Web Marketing Project with Ontology Support has the purpose to find and …
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High Performance Data Mining Techniques For Intrusion Detection
… transformed the way in which information and data was stored. With this new paradigm of data access, comes the threat of this information being exposed to unauthorized and unintended users. Many systems have been developed which scrutinize the data for a deviation from the normal behavior of a …
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Strategic capacity planning using data science, optimization, and machine learning
… visualization tool that integrates demand data with historical manufacturing data. Through automated data mining algorithms of factory data sources, capacity utilization and overall equipment effectiveness (OEE) for factory operations are evaluated. Machine learning methods are then …
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Detecting Inference Attacks Involving Sensor Data
… Nevertheless, according to the GDPR (General Data Protection Regulation), the organizations have to protect collected data. Access Control (AC) mechanisms are traditionally used to secure information systems against unauthorized access to sensitive data. The increased availability of personal …
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Sequential pattern mining with uncertain data
… have led to the proliferation of uncertain data. However, traditional data mining algorithms are usually inapplicable in uncertain data because of its probabilistic nature. Uncertainty has to be carefully handled; otherwise, it might significantly downgrade the quality of underlying data …
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Data-mining natural language materials syntheses
… thesis aims to realize the potential of this data for informing the syntheses of inorganic materials through the use of data-mining algorithms. Critically, the methods used and produced in this thesis are fully automated, thus maximizing the impact for accelerated synthesis planning by human …
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Enhancing quality of assertion generation: methods for automatic assertion generation and evaluation
… detail the GoldMine methodology and each of its data mining algorithms. We introduce the Best-Gain Decision Forest algorithm to mine concise RTL assertions. We develop an assertion ranking methodology. We define assertion importance, complexity, rank and ideality and we detail methods to compute …
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Fusion: a Visualization Framework for Interactive Ilp Rule Mining With Applications to Bioinformatics
… aids the biologists in performing microarray data analysis by providing them with both visual data exploration and data mining capabilities. Its multiple view visual framework allows the user to choose different views for different types of data. Fusion uses Proteus, an Inductive Logic …
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Insider threat simulation and performance analysis of insider detection algorithms with role based models
… facing the detection mechanisms is that the real data for modeling is not easily available. This thesis describes a simulator which can simulate the insiders and generate access information in the form of logs. Currently there are many methods which use data mining algorithms to detect insider …
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Meta-learning in Medicine
… the opportunity for knowledge discovery and data mining algorithms to gain insight from this digital health data. Predictive modeling of clinical risks from EHRs, such as in-hospital mortality rate, in-hospital length of stay and chronic disease onset, can be helpful to the improvement of the …
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Development and evaluation of machine learning algorithms for biomedical applications
… This dissertation develops machine learning and data mining algorithms, and applies these algorithms to solve the two important biomedical problems. Specifically, to tackle the gene network inference problem, the dissertation proposes (i) new techniques for selecting topological features suitable …
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Intelligent Instability Detection for Islanding Prediction
… is to use decision trees and neural network data mining algorithms, performed off-line, to determine the PMU locations, detection parameters, and their triggering values for islanding detection. With the information obtained from accurate system models PMUs can be used online to predict …
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A new model for worm detection and response. Development and evaluation of a new model based on knowledge discovery and data mining techniques to detect and respond to worm infection by integrating incident response, security metrics and apoptosis.
… (KDD) in modeling the STAKCERT model and the data mining algorithms were used. This STAKCERT model has produced encouraging results and outperformed comparative existing work for worm detection. It produces an overall accuracy rate of 98.75% with 0.2% for false positive rate and 1.45% is false …
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Network Problem Diagnosis and Status Assessment for Wireless Sensor Network in Civil Infrastructure Monitoring
… and employing deterministic methods and data-mining algorithms to identify significant parameters associated with network problems and network status. The implementation of the methodology is tested on real WSN devices in a testbed, demonstrating its capability to diagnose network …
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New Algorithms for Mining Network Datasets: Applications to Phenotype and Pathway Modeling
Biological network data is plentiful with practically every experimental methodology giving 'network views' into cellular function and behavior. Bioinformatic screens that yield network data include, for example, genome-wide deletion screens, protein-protein interaction assays, RNA interference …
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