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Full-Text Articles in Engineering
Data Driven Low-Bandwidth Intelligent Control Of A Jet Engine Combustor, Nathan L. Toner
Data Driven Low-Bandwidth Intelligent Control Of A Jet Engine Combustor, Nathan L. Toner
Open Access Dissertations
This thesis introduces a low-bandwidth control architecture for navigating the input space of an un-modeled combustor system between desired operating conditions while avoiding regions of instability and blow-out. An experimental procedure is discussed for identifying regions of instability and gathering sufficient data to build a data-driven model of the system's operating modes. Regions of instability and blow-out are identified experimentally and a data-driven operating point classifier is designed. This classifier acts as a map of the operating space of the combustor, indicating regions in which the flame is in a "good" or "bad" operating mode. A data-driven predictor is also …
Machine Learning Methods For Medical And Biological Image Computing, Rongjian Li
Machine Learning Methods For Medical And Biological Image Computing, Rongjian Li
Computer Science Theses & Dissertations
Medical and biological imaging technologies provide valuable visualization information of structure and function for an organ from the level of individual molecules to the whole object. Brain is the most complex organ in body, and it increasingly attracts intense research attentions with the rapid development of medical and bio-logical imaging technologies. A massive amount of high-dimensional brain imaging data being generated makes the design of computational methods for efficient analysis on those images highly demanded. The current study of computational methods using hand-crafted features does not scale with the increasing number of brain images, hindering the pace of scientific discoveries …
Revelation Of Yin-Yang Balance In Microbial Cell Factories By Data Mining, Flux Modeling, And Metabolic Engineering, Gang Wu
McKelvey School of Engineering Theses & Dissertations
The long-held assumption of never-ending rapid growth in biotechnology and especially in synthetic biology has been recently questioned, due to lack of substantial return of investment. One of the main reasons for failures in synthetic biology and metabolic engineering is the metabolic burdens that result in resource losses. Metabolic burden is defined as the portion of a host cells resources either energy molecules (e.g., NADH, NADPH and ATP) or carbon building blocks (e.g., amino acids) that is used to maintain the engineered components (e.g., pathways). As a result, the effectiveness of synthetic biology tools heavily dependents on cell capability to …
An Investigation Into Off-Link Ipv6 Host Enumeration Search Methods, Clinton Carpene
An Investigation Into Off-Link Ipv6 Host Enumeration Search Methods, Clinton Carpene
Theses: Doctorates and Masters
This research investigated search methods for enumerating networked devices on off-link 64 bit Internet Protocol version 6 (IPv6) subnetworks. IPv6 host enumeration is an emerging research area involving strategies to enable detection of networked devices on IPv6 networks. Host enumeration is an integral component in vulnerability assessments (VAs), and can be used to strengthen the security profile of a system. Recently, host enumeration has been applied to Internet-wide VAs in an effort to detect devices that are vulnerable to specific threats. These host enumeration exercises rely on the fact that the existing Internet Protocol version 4 (IPv4) can be exhaustively …
A Mapreduce-Based Distributed Svm Algorithm For Binary Classification, Ferhat Özgür Çatak, Mehmet Erdal Balaban
A Mapreduce-Based Distributed Svm Algorithm For Binary Classification, Ferhat Özgür Çatak, Mehmet Erdal Balaban
Turkish Journal of Electrical Engineering and Computer Sciences
Although the support vector machine (SVM) algorithm has a high generalization property for classifying unseen examples after the training phase~and a small loss value, the algorithm is not suitable for real-life classification and regression problems. SVMs cannot solve hundreds of thousands of examples in a training dataset. In previous studies on distributed machine-learning algorithms, the SVM was trained in a costly and preconfigured computer environment. In this research, we present a MapReduce-based distributed parallel SVM training algorithm for binary classification problems. This work shows how to distribute optimization problems over cloud computing systems with the MapReduce technique. In the second …
Feature Selection For Movie Recommendation, Zehra Çataltepe, Mahi̇ye Uluyağmur, Esengül Tayfur
Feature Selection For Movie Recommendation, Zehra Çataltepe, Mahi̇ye Uluyağmur, Esengül Tayfur
Turkish Journal of Electrical Engineering and Computer Sciences
TV users have an abundance of different movies they could choose from, and with the quantity and quality of data available both on user behavior and content, better recommenders are possible. In this paper, we evaluate and combine different content-based and collaborative recommendation methods for a Turkish movie recommendation system. Our recommendation methods can make use of user behavior, different types of content features, and other users' behavior to predict movie ratings. We gather different types of data on movies, such as the description, actors, directors, year, and genre. We use natural language processing methods to convert the Turkish movie …
Removal Of Impulse Noise In Digital Images With Na\"Ive Bayes Classifier Method, Cafer Budak, Mustafa Türk, Abdullah Toprak
Removal Of Impulse Noise In Digital Images With Na\"Ive Bayes Classifier Method, Cafer Budak, Mustafa Türk, Abdullah Toprak
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.