Engineering Commons^™

Semantic Components: A Model For Enhancing Retrieval Of Domain- Specific Information, Susan Loucette Price

Dissertations and Theses

Despite the success of general Internet search engines, information retrieval remains an incompletely solved problem. Our research focuses on supporting domain experts when they search domain-specific libraries to satisfy targeted information needs. The semantic components model introduces a schema specific to a particular document collection. A semantic component schema consists of a two-level hierarchy, document classes and semantic components. A document class represents a document grouping, such as topic type or document purpose. A semantic component is a characteristic type of information that occurs in a particular document class and represents an important aspect of the document’s main topic. …

Automatic Drift Compensation Using Phase Correlation Method For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani, Eric W. Bohannan

Electrical and Computer Engineering Faculty Research & Creative Works

Nanomanipulation and nanofabrication with an atomic force microscope (AFM) or other scanning probe microscope (SPM) are a precursor for nanomanufacturing. It is still a challenging task to accomplish nanomanipulation automatically. In ambient conditions without stringent environmental controls, the task of nanomanipulation requires extensive human intervention to compensate for the spatial uncertainties of the SPM. Among these uncertainties, the thermal drift, which affects spatial resolution, is especially hard to solve because it tends to increase with time, and cannot be compensated simultaneously by feedback from the instrument. In this paper, a novel automatic compensation scheme is introduced to measure and estimate …

Digital Signal Processing Leveraged For Intrusion Detection, Theodore J. Erickson

Theses and Dissertations

This thesis describes the development and evaluation of a novel system called the Network Attack Characterization Tool (NACT). The NACT employs digital signal processing to detect network intrusions, by exploiting the Lomb-Scargle periodogram method to obtain a spectrum for sampled network traffic. The Lomb-Scargle method for generating a periodogram allows for the processing of unevenly sampled network data. This method for determining a periodogram has not yet been used for intrusion detection. The spectrum is examined to determine if features exist above a significance level chosen by the user. These features are considered an attack, triggering an alarm. Two traffic …

Signal Processing Design Of Low Probability Of Intercept Waveforms, Nathaniel C. Liefer

Theses and Dissertations

This thesis investigates a modification to Differential Phase Shift Keyed (DPSK) modulation to create a Low Probability of Interception/Exploitation (LPI/LPE) communications signal. A pseudorandom timing offset is applied to each symbol in the communications stream to intentionally create intersymbol interference (ISI) that hinders accurate symbol estimation and bit sequence recovery by a non-cooperative receiver. Two cooperative receiver strategies are proposed to mitigate the ISI due to symbol timing offset: a modified minimum Mean Square Error (MMSE) equalization algorithm and a multiplexed bank of equalizer filters determined by an adaptive Least Mean Square (LMS) algorithm. Both cooperative receivers require some knowledge …

Multi-Class Classification Fusion Using Boosting For Identifying Steganography Methods, Benjamin M. Rodriguez, Gilbert L. Peterson

Faculty Publications

No abstract provided.

The State Of The Art In Flow Visualization: Partition-Based Techniques, Tobias Salzbrunn, Heike Janicke, Thomas Wischgoll, Gerik Scheuermann

Computer Science and Engineering Faculty Publications

Flow visualization has been a very active subfield of scientific visualization in recent years. From the resulting large variety of methods this paper discusses partition-based techniques. The aim of these approaches is to partition the flow in areas of common structure. Based on this partitioning, subsequent visualization techniques can be applied. A classification is suggested and advantages/disadvantages of the different techniques are discussed as well.

Botsniffer: Detecting Botnet Command And Control Channels In Network Traffic, Guofei Gu, Junjie Zhang, Wenke Lee

Computer Science and Engineering Faculty Publications

Botnets are now recognized as one of the most serious security threats. In contrast to previous malware, botnets have the characteristic of a command and control (C&C) channel. Botnets also often use existing common protocols, e.g., IRC, HTTP, and in protocol-conforming manners. This makes the detection of botnet C&C a challenging problem. In this paper, we propose an approach that uses network-based anomaly detection to identify botnet C&C channels in a local area network without any prior knowledge of signatures or C&C server addresses. This detection approach can identify both the C&C servers and infected hosts in the network. Our …

A Suite Of Robust Controllers For The Manipulation Of Microscale Objects, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A suite of novel robust controllers is introduced for the pickup operation of microscale objects in a microelectromechanical system (MEMS). In MEMS, adhesive, surface tension, friction, and van der Waals forces are dominant. Moreover, these forces are typically unknown. The proposed robust controller overcomes the unknown contact dynamics and ensures its performance in the presence of actuator constraints by assuming that the upper bounds on these forces are known. On the other hand, for the robust adaptive critic-based neural network (NN) controller, the unknown dynamic forces are estimated online. It consists of an action NN for compensating the unknown system …

Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann

Research Collection School Of Computing and Information Systems

Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit clusters of varying densities, shapes, and sizes. Traditional algorithms are found to be ineffective in mining these types of clusters. This paper offers a new perspective by exploring the pairwise visual cues deriving from near-duplicate keyframes (NDK) for constraint-based clustering. We propose a constraint-driven co-clustering algorithm (CCC), which utilizes the near-duplicate constraints built on top of text, to mine topic-related stories and the outliers. With CCC, the duality between stories and their underlying …

Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao

Research Collection School Of Computing and Information Systems

This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal difference (TD) methods, the proposed neural model, called TD fusion architecture for learning, cognition, and navigation (TD-FALCON), enables an autonomous agent to adapt and function in a dynamic environment with immediate as well as delayed evaluative feedback (reinforcement) signals. TD-FALCON learns the value functions of the state-action space estimated through on-policy and off-policy TD learning methods, specifically state-action-reward-state-action (SARSA) and Q-learning. The learned value functions are then used to determine the …

Extracting, Representing And Mining Semantic Metadata From Text: Facilitating Knowledge Discovery In Biomedicine, Cartic Ramakrishnan

Browse all Theses and Dissertations

The information access paradigm offered by most contemporary text information systems is a search-and-sift paradigm where users have to manually glean and aggregate relevant information from the large number of documents that are typically returned in response to keyword queries. Expecting the users to glean and aggregate information has lead to several inadequacies in these information systems. Owing to the size of many text databases, search-and-sift is a very tedious often requiring repeated keyword searches refining or generalizing queries terms. A more serious limitation arises from the lack of automated mechanisms to aggregate content across different documents to discover new …

Women And Technology: Reversing The Trends Of Attrition And Obtaining A Balance, Gondy Leroy, Kristin M. Tolle, Linda Perkins

CGU Faculty Publications and Research

Many reports and technical news bulletins presented by organizations such as the National Science Foundation (NSF), the Institute of Electrical and Electronics Engineers (IEEE), the Association for Computing Machinery (ACM), and the National Center for Women & Information Technology (NCWIT) highlight that few female and minority college students are choosing science, technology, engineering, and math (STEM) fields of study or careers. For those who choose STEM fields, attrition both during education and in the workplace is pervasive. NSF reports in its 2006 Science Indicators that women account for only 27% of the bachelor’s degrees in computer sciences. And although the …

What Is Approximate Reasoning?, Sebastian Rudolph, Tuvshintur Tserendorj, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Approximate reasoning for the Semantic Web is based on the idea of sacrificing soundness or completeness for a significant speed-up of reasoning. This is to be done in such a way that the number of introduced mistakes is at least outweighed by the obtained speed-up. When pursuing such approximate reasoning approaches, however, it is important to be critical not only about appropriate application domains, but also about the quality of the resulting approximate reasoning procedures. With different approximate reasoning algorithms discussed and developed in the literature, it needs to be clarified how these approaches can be compared, i.e. what it …

Detecting Curved Objects Against Cluttered Backgrounds, Jan Prokaj

Electronic Theses and Dissertations

Detecting curved objects against cluttered backgrounds is a hard problem in computer vision. We present new low-level and mid-level features to function in these environments. The low-level features are fast to compute, because they employ an integral image approach, which makes them especially useful in real-time applications. The mid-level features are built from low-level features, and are optimized for curved object detection. The usefulness of these features is tested by designing an object detection algorithm using these features. Object detection is accomplished by transforming the mid-level features into weak classifiers, which then produce a strong classifier using AdaBoost. The resulting …

Multi-View Approaches To Tracking, 3d Reconstruction And Object Class Detection, Saad Khan

Electronic Theses and Dissertations

Multi-camera systems are becoming ubiquitous and have found application in a variety of domains including surveillance, immersive visualization, sports entertainment and movie special effects amongst others. From a computer vision perspective, the challenging task is how to most efficiently fuse information from multiple views in the absence of detailed calibration information and a minimum of human intervention. This thesis presents a new approach to fuse foreground likelihood information from multiple views onto a reference view without explicit processing in 3D space, thereby circumventing the need for complete calibration. Our approach uses a homographic occupancy constraint (HOC), which states that if …

Improving Branch Prediction Accuracy Via Effective Source Information And Prediction Algorithms, Hongliang Gao

Electronic Theses and Dissertations

Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughput. Given the trend of deep pipelines and large instruction windows, a branch misprediction will incur a large performance penalty and result in a significant amount of energy wasted by the instructions along wrong paths. With their critical role in high performance processors, there has been extensive research on branch predictors to improve the prediction accuracy. Conceptually a dynamic branch prediction scheme includes three major components: a source, an information processor, and a predictor. Traditional works mainly focus on the algorithm for the predictor. In this dissertation, …

Lightweight Objective Quality Of Voice Estimation Through Machine Learning, Daniel Riordan

Theses

Communication systems are undergoing constant and rapid innovation, both at the design stage and in the field. This in turn has led to an inereasing need for fast, efficient, portable and economic methods for the testing of these systems. For voice carrying communication systems the quality of the transmitted voice that the system produces is a large factor in the overall performance rating of the system. This measure is known as the ‘Quality of Voice’ (QoV) and can be evaluated either subjectively or objectively.

Speech quality is a complex subjective phenomenon that can be best quantified by subjective testing. A …

Analysis Of Information Remaining On Hand Held Devices Offered For Sale On The Second Hand, Andy Jones, Craig Valli, Iain Sutherland

Journal of Digital Forensics, Security and Law

The ownership and use of mobile phones, Personal Digital Assistants and other hand held devices is now ubiquitous both for home and business use. The majority of these devices have a high initial cost, a relatively short period before they become obsolescent and a relatively low second hand value. As a result of this, when the devices are replaced, there are indications that they tend to be discarded. As technology has continued to develop, it has led to an increasing diversity in the number and type of devices that are available, and the processing power and the storage capacity of …

A Framework For Efficient Data Distribution In Peer-To-Peer Networks., Darshan Purandare

Electronic Theses and Dissertations

Peer to Peer (P2P) models are based on user altruism, wherein a user shares its content with other users in the pool and it also has an interest in the content of the other nodes. Most P2P systems in their current form are not fair in terms of the content served by a peer and the service obtained from swarm. Most systems suffer from free rider's problem where many high uplink capacity peers contribute much more than they should while many others get a free ride for downloading the content. This leaves high capacity nodes with very little or no …

Real-Time Realistic Rendering Of Nature Scenes With Dynamic Lighting, Kevin Boulanger

Electronic Theses and Dissertations

Rendering of natural scenes has interested the scientific community for a long time due to its numerous applications. The targeted goal is to create images that are similar to what a viewer can see in real life with his/her eyes. The main obstacle is complexity: nature scenes from real life contain a huge number of small details that are hard to model, take a lot of time to render and require a huge amount of memory unavailable in current computers. This complexity mainly comes from geometry and lighting. The goal of our research is to overcome this complexity and to …

Taming Crowded Visual Scenes, Saad Ali

Electronic Theses and Dissertations

Computer vision algorithms have played a pivotal role in commercial video surveillance systems for a number of years. However, a common weakness among these systems is their inability to handle crowded scenes. In this thesis, we have developed algorithms that overcome some of the challenges encountered in videos of crowded environments such as sporting events, religious festivals, parades, concerts, train stations, airports, and malls. We adopt a top-down approach by first performing a global-level analysis that locates dynamically distinct crowd regions within the video. This knowledge is then employed in the detection of abnormal behaviors and tracking of individual targets …

Optimization In Multi-Agent Systems : Structures And Procedures, Ingo Stengel

Theses

The main advantage for the use of agent technology is in the capacity of agents to represent the interests of individual entities and to act autonomously on their behalf. In multi-agent systems this involves communication, coordination and negotiation.

The focus of this dissertation is to find ways to optimize multi-agent systems at different levels by taking into consideration their structure and the procedures used. As optimization depends to a large extent on the problem to be solved, group forming scenarios, in which self-interested agents compete to form and join groups, have been selected here for consideration. Optimization issues are discussed …

Management Framework For Hybrid Wireless Networks, Chong Shen

Theses

The objective of the Hybrid Wireless Network with dedicated Relay Nodes (HWN*) architecture is to interface the Base Station (BS) Oriented Mobile Network (BSON) and the 802.fix based Mobile Ad hoc Wireless Network (MANET) so that one system can be utilised as an alternative radio access network for data transmissions, while the incorporation of Relay Nodes (RN) is to extend the communication coverage, optimise medium resource sharing, increase spatial reuse opportunity, stabilise MANET link and create more micro-cells. The HWN* keeps the existing cellular infrastructure and a Mobile Terminal (MT) can borrow radio resources from other cells via secure multi-hop …

Functorial Coalgebraic Logic: The Case Of Many-Sorted Varieties, Alexander Kurz, Daniela Petrişan

Engineering Faculty Articles and Research

Following earlier work, a modal logic for T-coalgebras is a functor L on a suitable variety. Syntax and proof system of the logic are given by presentations of the functor. This paper makes two contributions. First, a previous result characterizing those functors that have presentations is generalized from endofunctors on one-sorted varieties to functors between many-sorted varieties. This yields an equational logic for the presheaf semantics of higher-order abstract syntax. As another application, we show how the move to functors between many-sorted varieties allows to modularly combine syntax and proof systems of different logics. Second, we show how to associate …

Generation Of High-Repetition-Rate Pulses Utilizing Cascaded Single Mode Fiber And Semiconductor Optical Amplifier, Jianwei Wu, Hai-Bo Bao

Turkish Journal of Electrical Engineering and Computer Sciences

To generate high-repetition-rate optical pulses, a novel and simple device is demonstrated, in which the cascaded single mode fiber (SMF) with negative third order dispersion and semiconductor optical amplifier (SOA) are adopted. Numerical research results show that let an optical pulse with center wavelength in zero dispersion wavelength of optical fiber transit in SMF for generating an oscillation pulse. Subsequently, the followed SOA is provided for amplification. As a consequence, the high-repetition-rate optical pulses can be obtained.

A Study On The Reliability Of Polyester Insulators Blended With Borax, Aysel Ersoy, Yasi̇n Özcelep, Ayten Kuntman

Turkish Journal of Electrical Engineering and Computer Sciences

Tracking is the main factor which limits the safe working electric stress of insulation in power system applications. Polymer samples have been tested in laboratory conditions according to ASTM D2303 on accelerated inclined plane tracking test. In this paper, a model based on improved Weibull statistics is proposed for estimating the breakdown time of polymeric insulating materials with borax. The confidence intervals of the Weibull shape parameter and the Weibull scale parameter are determined for the borax concentration values using the Weibull 7++ program.

Recent Advances In Perfectly Matched Layers In Finite Element Applications, Özlem Özgün, Mustafa Kuzuoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

We present a comparative evaluation of two novel and practical perfectly matched layer (PML) implementations to the problem of mesh truncation in the finite element method (FEM): locally-conformal PML, and multi-center PML techniques. The most distinguished feature of these methods is the simplicity and flexibility to design conformal PMLs over challenging geometries, especially those with curvature discontinuities, in a straightforward way without using artificial absorbers. These methods are based on specially- and locally-defined complex coordinate transformations inside the PML region. They can easily be implemented in a conventional FEM by just replacing the nodal coordinates inside the PML region by …

Network Formation Using Ant Colony Optimization -- A Systematic Review, Steven C. Oimoen, Gilbert L. Peterson, Kenneth M. Hopkinson

Faculty Publications

A significant area of research in the field of hybrid communications is the Network Design Problem (NDP) [1]. The NDP is an NP complete problem [1] that focuses on identifying the optimal network topology for transmitting commodities between nodes, under constraints such as bandwidth, limited compatible directed channels, and link and commodity costs. The NDP focuses on designing a flexible network while trying to achieve optimal flow or routing. If a link (or arc) is used, then an associated fixed cost of the edge is incurred. In addition, there is a cost for using the arc depending on the flow. …

New Method For Approximating Vague Sets To Fuzzy Sets Based On Voting Model, Jian Liu, Zhizhan Liu, Shunxiang Wu, Yongjian Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

By analyzing Vague Sets voting model, we bring forth a new method for approximating Vague Sets to Fuzzy Sets, and its general process is presented in the article. In a voting model, firstly, we suppose that the abstainers must vote for once more, and the results are close studied. Then the randomicity, uncertainty, and conformity of voting are found. As we know, an abstainer may favor somebody, oppose somebody, or just abstain. In this article, we suppose the distribution of results is consistent with a normal distribution. So, we advance the new approximation method based on Gauss Distribution. © 2008 …

Efficient Corona Training Protocols For Sensor Networks, Alan A. Bertossi, Stephan Olariu, Cristina M. Pinotti

Computer Science Faculty Publications

Phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireless communications capabilities. It is expected that these small devices, referred to as sensors, will be mass-produced and deployed, making their production cost negligible. Due to their small form factor and modest non-renewable energy budget, individual sensors are not expected to be GPS-enabled. Moreover, in most applications, exact geographic location is not necessary, and all that the individual sensors need is a coarse-grain location awareness. The task of acquiring such a coarse-grain location awareness is referred to as training. …