Computer Sciences Commons^™

Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l₁/l_q regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …

Adaptive Graph Construction For Isomap Manifold Learning, Loc Tran, Zezhong Zheng, Guoquing Zhou, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the ℓ₁ norm. The ℓ₁ enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than …

A Comparative Study Of Two Prediction Models For Brain Tumor Progression, Deqi Zhou, Loc Tran, Jihong Wang, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images.

We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. …

The Multimodal Brain Tumor Image Segmentation Benchmark (Brats), Bjoern H. Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Khan M. Iftekharuddin, Syed M.S. Reza

Electrical & Computer Engineering Faculty Publications

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low-and high-grade glioma patients-manually annotated by up to four raters-and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions …

Fuzzy Adaptive Resonance Theory: Applications And Extensions, Clayton Parker Smith

Masters Theses

"Adaptive Resonance Theory, ART, is a powerful clustering tool for learning arbitrary patterns in a self-organizing manner. In this research, two papers are presented that examine the extensibility and applications of ART. The first paper examines a means to boost ART performance by assigning each cluster a vigilance value, instead of a single value for the whole ART module. A Particle Swarm Optimization technique is used to search for desirable vigilance values. In the second paper, it is shown how ART, and clustering in general, can be a useful tool in preprocessing time series data. Clustering quantization attempts to meaningfully …

Rote-Lcs Learning Classifier System For Classification And Prediction, Benjamin Daniels

Masters Theses

"Machine Learning (ML) involves the use of computer algorithms to solve for approximate solutions to problems with large, complex search spaces. Such problems have no known solution method, and search spaces too large to allow brute force search to be feasible. Evolutionary algorithms (EA) are a subset of machine learning algorithms which simulate fundamental concepts of evolution. EAs do not guarantee a perfect solution, but rather facilitate convergence to a solution of which the accuracy depends on a given EA's learning architecture and the dynamics of the problem.

Learning classifier systems (LCS) are algorithms comprising a subset of EAs. The …

Deforming Diamond, Ciprian Borcea, Ileana Streinu

Computer Science: Faculty Publications

For materials science, diamond crystals are almost unrivaled for hardness and a range of other properties. Yet, when simply abstracting the carbon bonding structure as a geometric bar-and-joint periodic framework, it is far from rigid. We study the geometric deformations of this type of framework in arbitrary dimension d, with particular regard to the volume variation of a unit cell.

Evaluation Of The Signature Molecular Descriptor With Blosum62 And An All-Atom Description For Use In Sequence Alignment Of Proteins, Lindsay M. Aichinger

Williams Honors College, Honors Research Projects

This Honors Project focused on a few aspects of this topic. The second is comparing the molecular signature kernels to three of the BLOSUM matrices (30, 62, and 90) to test the accuracy of the mathematical model. The kernel matrix was manipulated in order to improve the relationship by focusing on side groups and also by changing how the structure was represented in the matrix by increasing the initial height distance from the central atom (Height 1 and Height 2 included).

There were multiple design constraints for this project. The first was the comparison with the BLOSUM matrices (30, 62, …

Parameters Estimation Of Material Constitutive Models Using Optimization Algorithms, Kiswendsida Jules Kere

Williams Honors College, Honors Research Projects

Optimization Algorithms are very useful for solving engineering problems. Indeed, optimization algorithms can be used to optimize engineering designs in terms of safety and economy. Understanding the proprieties of materials in engineering designs is very important in order to make designs safe. Materials are not really perfectly homogeneous and there are heterogeneous distributions in most materials. In this paper, Self-OPTIM which is an inverse constitutive parameter identification framework will be used to identify parameters of a linear elastic material constitutive model. Data for Self-OPTIM will be obtained using ABAQUS simulation of a dog-bone uniaxial test. Optimization Algorithms will be used …

Building Computing-As-A-Service Mobile Cloud System, Kun Wang

Wayne State University Dissertations

The last five years have witnessed the proliferation of smart mobile devices, the explosion of various mobile applications and the rapid adoption of cloud computing in business, governmental and educational IT deployment. There is also a growing trends of combining mobile computing and cloud computing as a new popular computing paradigm nowadays. This thesis envisions the future of mobile computing which is primarily affected by following three trends: First, servers in cloud equipped with high speed multi-core technology have been the main stream today. Meanwhile, ARM processor powered servers is growingly became popular recently and the virtualization on ARM systems …

Design Of A Novel Usb Crypto Bridge Device, Orhan Şengül

Turkish Journal of Electrical Engineering and Computer Sciences

Information technologies have emerging use of portable drives. Hence, the readability and security of the content is at great risk in the event that it is lost or stolen. An effective solution to this issue is the use of removable disks in encrypted form. In this paper, a novel USB device that has cryptobridge capability is proposed.

Project Maelstrom: Forensic Analysis Of The Bittorrent-Powered Browser, Jason Farina, M-Tahar Kechadi, Mark Scanlon

Journal of Digital Forensics, Security and Law

In April 2015, BitTorrent Inc. released their distributed peer-to-peer powered browser, Project Maelstrom, into public beta. The browser facilitates a new alternative website distribution paradigm to the traditional HTTP-based, client-server model. This decentralised web is powered by each of the visitors accessing each Maelstrom hosted website. Each user shares their copy of the website;s source code and multimedia content with new visitors. As a result, a Maelstrom hosted website cannot be taken offline by law enforcement or any other parties. Due to this open distribution model, a number of interesting censorship, security and privacy considerations are raised. This paper explores …

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2015, Ven Basco

Libraries' Newsletters

No abstract provided.

Automatic Emotion Identification From Text, Wenbo Wang

Browse all Theses and Dissertations

People's emotions can be gleaned from their text using machine learning techniques to build models that exploit large self-labeled emotion data from social media. Further, the self-labeled emotion data can be effectively adapted to train emotion classifiers in different target domains where training data are sparse.

Emotions are both prevalent in and essential to most aspects of our lives. They influence our decision-making, affect our social relationships and shape our daily behavior. With the rapid growth of emotion-rich textual content, such as microblog posts, blog posts, and forum discussions, there is a growing need to develop algorithms and techniques for …

A Language For Inconsistency-Tolerant Ontology Mapping, Kunal Sengupta

Browse all Theses and Dissertations

Ontology alignment plays a key role in enabling interoperability among various data sources present in the web. The nature of the world is such, that the same concepts differ in meaning, often so slightly, which makes it difficult to relate these concepts. It is the omni-present heterogeneity that is at the core of the web. The research work presented in this dissertation, is driven by the goal of providing a robust ontology alignment language for the semantic web, as we show that description logics based alignment languages are not suitable for aligning ontologies.

The adoption of the semantic web technologies …

Orthogonal Moment-Based Human Shape Query And Action Recognition From 3d Point Cloud Patches, Huaining Cheng

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With the recent proliferation of 3D sensors such as Light Detection and Ranging (LIDAR), it is essential to develop feature representation methods that can best characterize the point clouds produced by these devices. When these devices are employed in targeting and surveillance of human actions from both ground and aerial platforms, the corresponding point clouds of body shape often comprise low-resolution, disjoint, and irregular patches of points resulted from self-occlusions and viewing angle variations. The prevailing method of depth image analysis has the limitation of relying on 2D features that are not native representation of 3D spatial relationships. On the …

Ontology Pattern-Based Data Integration, Adila Alfa Krisnadhi

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Data integration is concerned with providing a unified access to data residing at multiple sources. Such a unified access is realized by having a global schema and a set of mappings between the global schema and the local schemas of each data source, which specify how user queries at the global schema can be translated into queries at the local schemas. Data sources are typically developed and maintained independently, and thus, highly heterogeneous. This causes difficulties in integration because of the lack of interoperability in the aspect of architecture, data format, as well as syntax and semantics of the data. …

Learning To Rank Algorithms And Their Application In Machine Translation, Tian Xia

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In this thesis, we discuss two issues in the learning to rank area, choosing effective objective loss function, constructing effective regresstion trees in the gradient boosting framework, as well as a third issus, applying learning to rank models into statistcal machine translation. First, list-wise based learning to rank methods either directly optimize performance measures or optimize surrogate functions of performance measures that have smaller gaps between optimized losses and performance measures, thus it is generally believed that they should be able to lead to better performance than point-and pair-wise based learning to rank methods. However, in real-world applications, state-of-the-art practical …

Browser Based Visualization For Parameter Spaces Of Big Data Using Client-Server Model, Kurtis M. Glendenning

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Visualization is an important task in data analytics, as it allows researchers to view abstract patterns within the data instead of reading through extensive raw data. Allowing the ability to interact with the visualizations is an essential aspect since it provides the ability to intuitively explore data to find meaning and patterns more efficiently. Interactivity, however, becomes progressively more difficult as the size of the dataset increases. This project begins by leveraging existing web-based data visualization technologies and extends their functionality through the use of parallel processing. This methodology utilizes state-of-the-art techniques, such as Node.js, to split the visualization rendering …

Owl Query Answering Using Machine Learning, Todd Huster

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The formal semantics of the Web Ontology Language (OWL) enables automated reasoning over OWL knowledge bases, which in turn can be used for a variety of purposes including knowledge base development, querying and management. Automated reasoning is usually done by means of deductive (proof-theoretic) algorithms which are either provably sound and complete or employ approximate methods to trade some correctness for improved efficiency. As has been argued elsewhere, however, reasoning methods for the Semantic Web do not necessarily have to be based on deductive methods, and approximate reasoning using statistical or machine-learning approaches may bring improved speed while maintaining high …

Temporally Biased Search Result Snippets, J. Abhiram Tatineni

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The search engine result snippets are an important source of information for the user to obtain quick insights into the corresponding result documents. When the search terms are too general, like a person's name or a company's name, creating an appropriate snippet that effectively summarizes the document's content can be challenging owing to multiple occurrences of the search term in the top ranked documents, without a simple means to select a subset of sentences containing them to form result snippet. In web pages classified as narratives and news articles, multiple references to explicit, implicit and relative temporal expressions can be …

Design Of A Novel Low - Cost, Portable, 3d Ultrasound System With Extended Imaging Capabilities For Point-Of-Care Applications, Michail Tsakalakis

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Ultrasound Imaging (USI) or Medical Sonography (MS), as it is formally called, has been widely used in biomedical applications over the last decades. USI can provide clinicians with a thorough view of the internal parts of the human body, making use of sound waves of higher frequencies than humans can perceive. USI systems are considered highly portable and of low-cost, compared to other imaging modalities. However, despite those advantages, Ultrasound Systems (US) and especially 3D ones, have not been yet extensively utilized for Point-of-Care (POC) applications, due to numerous restrictions and artifacts that they currently present.

Hardware complexity and real-time …

Mining Behavior Of Citizen Sensor Communities To Improve Cooperation With Organizational Actors, Hemant Purohit

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Web 2.0 (social media) provides a natural platform for dynamic emergence of citizen (as) sensor communities, where the citizens generate content for sharing information and engaging in discussions. Such a citizen sensor community (CSC) has stated or implied goals that are helpful in the work of formal organizations, such as an emergency management unit, for prioritizing their response needs. This research addresses questions related to design of a cooperative system of organizations and citizens in CSC. Prior research by social scientists in a limited offline and online environment has provided a foundation for research on cooperative behavior challenges, including 'articulation' …

Behavioral Operations Management In Federal Governance, Frederick Leonard Mobley

Walden Dissertations and Doctoral Studies

The environmental uncertainty of federal politics and acquisition outsourcing in competitive markets requires an adaptive decision-analysis structure. Practitioners oriented toward exclusively static methods face severe challenges in understanding qualitative aspects of organizational governance. The purpose of this grounded theory study was to examine and understand behavioral relationship attributes within intuitive, choice, judgment, or preference decision-making processes. The problem addressed in this study was the detrimental effects of organizational citizenship behavior (OCB), compulsory citizenship behavior (CCB), and social exchange theory (SET) on the acquisition management relationship The OCB, CCB, SET dictates that sound business development, relationship acumen, emotional intelligence and perceptiveness …

Autonomous Quadcopter Videographer, Quiquia Rey Coaguila

Electronic Theses and Dissertations

In recent years, the interest in quadcopters as a robotics platform for autonomous photography has increased. This is due to their small size and mobility, which allow them to reach places that are difficult or even impossible for humans. This thesis focuses on the design of an autonomous quadcopter videographer, i.e. a quadcopter capable of capturing good footage of a specific subject. In order to obtain this footage, the system needs to choose appropriate vantage points and control the quadcopter. Skilled human videographers can easily spot good filming locations where the subject and its actions can be seen clearly in …

Modeling User Transportation Patterns Using Mobile Devices, Erfan Davami

Electronic Theses and Dissertations

Participatory sensing frameworks use humans and their computing devices as a large mobile sensing network. Dramatic accessibility and affordability have turned mobile devices (smartphone and tablet computers) into the most popular computational machines in the world, exceeding laptops. By the end of 2013, more than 1.5 billion people on earth will have a smartphone. Increased coverage and higher speeds of cellular networks have given these devices the power to constantly stream large amounts of data. Most mobile devices are equipped with advanced sensors such as GPS, cameras, and microphones. This expansion of smartphone numbers and power has created a sensing …

Mras-Based Sensorless Speed Backstepping Control For Induction Machine, Using A Flux Sliding Mode Observer, Mohamed Moutchou, Ahmed Abbou, Hassan Mahmoudi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, an induction machine rotor speed and rotor flux control using a sensorless backstepping control scheme is discussed. The most interesting point of this technique is that it deals with the nonlinearity of a high-order system by using the virtual control variable to make this system simple, and thus the control outputs can be derived step by step through appropriate Lyapunov functions. To avoid the use of a mechanical sensor, the rotor speed estimation is made by an observer using the model reference adaptive system (MRAS) technique; in order to estimate rotor flux, a sliding mode observer is …

Designing And Implementing A Reliable Thermal Monitoring System Based On The 1-Wire Protocol On Fpga For A Leo Satellite, Reza Omidi Gosheblagh, Karim Mohammadi

Turkish Journal of Electrical Engineering and Computer Sciences

Thermal control and monitoring is one of the most important factors in the design of satellite systems. An appropriate thermal design should make sure that the satellite's sensitive components remain in their nominated range, even under the vacuum condition of outer space. To achieve this purpose, a reliable and stable monitoring system is required. This paper proposes a monitoring system based on the 1-wire protocol, which provides the reliability requirements in the sensor networking and bus controller sections. In the networking section, we outline some practical topologies and discuss on their complexity and reliability. Despite the fact that the point-to-point …

Temporal Logic Extension For Self-Referring, Nonexistence, Multiple Recurrence, And Anterior Past Events, Şadi̇ Evren Şeker

Turkish Journal of Electrical Engineering and Computer Sciences

This study focuses on the possible extensions of current temporal logics. In this study, 4 extensions are proposed: self-referring events, nonexisting events, multiple recurrence of events, and an improvement on anterior past events. Each of these extensions is on a different level of temporal logics. The main motivation behind the extensions is the temporal analysis of Turkish. Similar to temporal logic studies built on other natural languages, like French, Ukrainian, Italian, Korean, English, or Romanian, this is the first time that the Turkish language has been deeply questioned in the sense of computable temporal logic using the view of a …

Discrete-Time Modeling Of Hamiltonian Systems, Yaprak Yalçin, Leyla Gören Sümer, Salman Kurtulan

Turkish Journal of Electrical Engineering and Computer Sciences

The problem of discrete-time modeling of the lumped-parameter Hamiltonian systems is considered for engineering applications. Hence, a novel gradient-based method is presented, exploiting the discrete gradient concept and the forward Euler discretization under the assumption of the continuous Hamiltonian model is known. It is proven that the proposed discrete-time model structure defines a symplectic difference system and has the energy-conserving property under some conditions. In order to provide alternate discrete-time models, 3 different discrete-gradient definitions are given. The proposed models are convenient for the design of sampled-data controllers. All of the models are considered for several well-known Hamiltonian systems and …