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An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab
An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab
Electronic Theses and Dissertations
Early identification and detection of abnormal time series patterns is vital for a number of manufacturing. Slide shifts and alterations of time series patterns might be indicative of some anomaly in the production process, such as machinery malfunction. Usually due to the continuous flow of data monitoring of manufacturing processes requires automated Control Chart Pattern Recognition(CCPR) algorithms. The majority of CCPR literature consists of supervised classification algorithms. Less studies consider unsupervised versions of the problem. Despite the profound advantage of unsupervised methodology for less manual data labeling their use is limited due to the fact that their performance is not …
Learning Collective Behavior In Multi-Relational Networks, Xi Wang
Learning Collective Behavior In Multi-Relational Networks, Xi Wang
Electronic Theses and Dissertations
With the rapid expansion of the Internet and WWW, the problem of analyzing social media data has received an increasing amount of attention in the past decade. The boom in social media platforms offers many possibilities to study human collective behavior and interactions on an unprecedented scale. In the past, much work has been done on the problem of learning from networked data with homogeneous topologies, where instances are explicitly or implicitly inter-connected by a single type of relationship. In contrast to traditional content-only classification methods, relational learning succeeds in improving classification performance by leveraging the correlation of the labels …
Integrated Data Fusion And Mining (Idfm) Technique For Monitoring Water Quality In Large And Small Lakes, Benjamin Vannah
Integrated Data Fusion And Mining (Idfm) Technique For Monitoring Water Quality In Large And Small Lakes, Benjamin Vannah
Electronic Theses and Dissertations
Monitoring water quality on a near-real-time basis to address water resources management and public health concerns in coupled natural systems and the built environment is by no means an easy task. Furthermore, this emerging societal challenge will continue to grow, due to the ever-increasing anthropogenic impacts upon surface waters. For example, urban growth and agricultural operations have led to an influx of nutrients into surface waters stimulating harmful algal bloom formation, and stormwater runoff from urban areas contributes to the accumulation of total organic carbon (TOC) in surface waters. TOC in surface waters is a known precursor of disinfection byproducts …
Multi-Level Safety Performance Functions For High Speed Facilities, Mohamed Ahmed
Multi-Level Safety Performance Functions For High Speed Facilities, Mohamed Ahmed
Electronic Theses and Dissertations
High speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the safety of these high speed facilities to ensure better and efficient operation. Safety problems could be assessed through several approaches that can help in mitigating the …
A Study Of Factors Contributing To Self-Reported Anomalies In Civil Aviation, Chris Andrzejczak
A Study Of Factors Contributing To Self-Reported Anomalies In Civil Aviation, Chris Andrzejczak
Electronic Theses and Dissertations
A study investigating what factors are present leading to pilots submitting voluntary anomaly reports regarding their flight performance was conducted. The study employed statistical methods, text mining, clustering, and dimensional reduction techniques in an effort to determine relationships between factors and anomalies. A review of the literature was conducted to determine what factors are contributing to these anomalous incidents, as well as what research exists on human error, its causes, and its management. Data from the NASA Aviation Safety Reporting System (ASRS) was analyzed using traditional statistical methods such as frequencies and multinomial logistic regression. Recently formalized approaches in text …
Detecting Malicious Software By Dynamicexecution, Jianyong Dai
Detecting Malicious Software By Dynamicexecution, Jianyong Dai
Electronic Theses and Dissertations
Traditional way to detect malicious software is based on signature matching. However, signature matching only detects known malicious software. In order to detect unknown malicious software, it is necessary to analyze the software for its impact on the system when the software is executed. In one approach, the software code can be statically analyzed for any malicious patterns. Another approach is to execute the program and determine the nature of the program dynamically. Since the execution of malicious code may have negative impact on the system, the code must be executed in a controlled environment. For that purpose, we have …
Estimation Of Hybrid Models For Real-Time Crash Risk Assessment On Freeways, Anurag Pande
Estimation Of Hybrid Models For Real-Time Crash Risk Assessment On Freeways, Anurag Pande
Electronic Theses and Dissertations
Relevance of reactive traffic management strategies such as freeway incident detection has been diminishing with advancements in mobile phone usage and video surveillance technology. On the other hand, capacity to collect, store, and analyze traffic data from underground loop detectors has witnessed enormous growth in the recent past. These two facts together provide us with motivation as well as the means to shift the focus of freeway traffic management toward proactive strategies that would involve anticipating incidents such as crashes. The primary element of proactive traffic management strategy would be model(s) that can separate 'crash prone' conditions from 'normal' traffic …
High Performance Data Mining Techniques For Intrusion Detection, Muazzam Ahmed Siddiqui
High Performance Data Mining Techniques For Intrusion Detection, Muazzam Ahmed Siddiqui
Electronic Theses and Dissertations
The rapid growth of computers 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 user or system, or search for a known signature within the data. These systems are termed as Intrusion Detection Systems (IDS). These systems employ different techniques varying from statistical methods to machine learning algorithms. Intrusion detection systems use audit data generated by operating systems, application softwares or …
Modifications To The Fuzzy-Artmap Algorithm For Distributed Learning In Large Data Sets, Jose R. Castro
Modifications To The Fuzzy-Artmap Algorithm For Distributed Learning In Large Data Sets, Jose R. Castro
Electronic Theses and Dissertations
The Fuzzy–ARTMAP (FAM) algorithm has been proven to be one of the premier neural network architectures for classification problems. FAM can learn on line and is usually faster than other neural network approaches. Nevertheless the learning time of FAM can slow down considerably when the size of the training set increases into the hundreds of thousands. In this dissertation we apply data partitioning and network partitioning to the FAM algorithm in a sequential and parallel setting to achieve better convergence time and to efficiently train with large databases (hundreds of thousands of patterns). We implement our parallelization on a Beowulf …