Engineering Commons^™

Behaviors Of Real-Time Schedulers Under Resource Modification And A Steady Scheme With Bounded Utilization, Refi̇k Samet, Orhan Fi̇kret Duman

Turkish Journal of Electrical Engineering and Computer Sciences

In this article we present an analysis for task models having random resource needs and different arrival patterns. In hard real-time environments like avionic systems or nuclear reactors, the inputs to the system are obtained from real world by using sensors. And it is highly possible for a task to have different resource needs for each period according to these changing conditions of real world. We made an analysis of schedulers for task models having random resources in each period. Since feasibility tests for usual task models are just limited to some specific schedulers and arrival patterns, we made our …

Mining Frequent Generalized Patterns For Web Personalization In The Presence Of Taxonomies, Panagiotis Giannikopoulos, Iraklis Varlamis, Magdalini Eirinaki

Magdalini Eirinaki

The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usage-based approach to generate recommendations that takes as input the navigation paths recorded on the Web page level, is not as effective. Moreover, most of the content available online is either explicitly or implicitly characterized by a set of categories organized in a taxonomy, allowing the page-level navigation patterns to be generalized to a higher, aggregate level. In this direction, the authors present the Frequent Generalized Pattern (FGP) algorithm. FGP takes as input the transaction data and a hierarchy …

Visualization Of Complex Unsteady 3d Flow: Flowing Seed Points And Dynamically Evolving Seed Curves With Applications To Vortex Visualization In Cfd Simulations Of Ultra Low Reynolds Number Insect Flight, Christopher M. Koehler

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Three dimensional integration-based geometric visualization is a very powerful tool for analyzing flow phenomena in time dependent vector fields. Streamlines in particular have many perceptual benefits due to their ability to provide a snapshot of the vectors near key features of complex 3D flows at any instant in time. However, streamlines do not lend themselves well to animation. Subtle changes in the vector field at each time step lead to increasingly large changes between streamlines with the same seed point the longer they are integrated. Path lines, which show particle trajectories over time suffer from similar problems when attempting to …

Algorithmic Techniques Employed In The Quantification And Characterization Of Nuclear Magnetic Resonance Spectroscopic Data, Paul Edward Anderson

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Nuclear magnetic resonance (NMR) based metabolomics is a developing research field with broad applicability, including the identification of biomarkers associated with pathophysiologic changes, sample classification based on the mechanism of toxicity, and clinical diagnosis. Intrinsic to these applications is the need for statistical and computational techniques to facilitate the associated data analysis. Further, a typical 1H NMR spectrum of pure proteins, biofluids, or tissue may contain thousands of resonances (i.e., peaks), thus, a pure visual inspection is insufficient to fully utilize the spectral information.

Common practice within the NMR-based metabolomics community is to evaluate and validate novel algorithms on empirical …

Prediction Of Brain Tumor Progression Using A Machine Learning Technique, Yuzhong Shen, Debrup Banerjee, Jiang Li, Adam Chandler, Yufei Shen, Frederic D. Mckenzie, Jihong Wang, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)

Electrical & Computer Engineering Faculty Publications

A machine learning technique is presented for assessing brain tumor progression by exploring six patients' complete MRI records scanned during their visits in the past two years. There are ten MRI series, including diffusion tensor image (DTI), for each visit. After registering all series to the corresponding DTI scan at the first visit, annotated normal and tumor regions were overlaid. Intensity value of each pixel inside the annotated regions were then extracted across all of the ten MRI series to compose a 10 dimensional vector. Each feature vector falls into one of three categories:normal, tumor, and normal but progressed to …

Security In Ad Hoc Networks And Pervasive Computing, Isaac Z. Wu, X.-Y. Li, M. Song, C.-M. Liu

Electrical & Computer Engineering Faculty Publications

Pervasive computing is an exciting and blooming research field, in which innovative techniques and applications are continuously emerging and aim to provide ambient and personalized services to users with high quality. Ad hoc networks are wireless, self-organizing systems formed by cooperating nodes within communication range of each other that form temporary networks. Their topology is dynamic, decentralized, ever changing and the nodes may move around arbitrarily. The last few years have witnessed a wealth of research ideas on ad hoc networking that are moving rapidly into implemented standards. Technology under development for ad hoc networks and pervasive computing is making …

Bitopological Duality For Distributive Lattices And Heyting Algebras, Guram Bezhanishvili, Nick Bezhanishvili, David Gabelaia, Alexander Kurz

Engineering Faculty Articles and Research

We introduce pairwise Stone spaces as a natural bitopological generalization of Stone spaces—the duals of Boolean algebras—and show that they are exactly the bitopological duals of bounded distributive lattices. The category PStone of pairwise Stone spaces is isomorphic to the category Spec of spectral spaces and to the category Pries of Priestley spaces. In fact, the isomorphism of Spec and Pries is most naturally seen through PStone by first establishing that Pries is isomorphic to PStone, and then showing that PStone is isomorphic to Spec. We provide the bitopological and spectral descriptions of many algebraic concepts important for the study …

On Universal Algebra Over Nominal Sets, Alexander Kurz, Daniela Petrişan

Engineering Faculty Articles and Research

We investigate universal algebra over the category Nom of nominal sets. Using the fact that Nom is a full re ective subcategory of a monadic category, we obtain an HSP-like theorem for algebras over nominal sets. We isolate a `uniform' fragment of our equational logic, which corresponds to the nominal logics present in the literature. We give semantically invariant translations of theories for nominal algebra and NEL into `uniform' theories and systematically prove HSP theorems for models of these theories.

Algebraic Theories Over Nominal Sets, Alexander Kurz, Daniela Petrişan, Jiří Velebil

Engineering Faculty Articles and Research

We investigate the foundations of a theory of algebraic data types with variable binding inside classical universal algebra. In the first part, a category-theoretic study of monads over the nominal sets of Gabbay and Pitts leads us to introduce new notions of finitary based monads and uniform monads. In a second part we spell out these notions in the language of universal algebra, show how to recover the logics of Gabbay-Mathijssen and Clouston-Pitts, and apply classical results from universal algebra.

Periodic Resource Reallocation In Two-Echelon Repairable Item Inventory Systems, Hoong Chuin Lau, Jie Pan, Huawei Song

Research Collection School Of Computing and Information Systems

Given an existing stock allocation in an inventory system, it is often necessary to perform reallocation over multiple time points to address inventory imbalance and maximize availability. In this paper, we focus on the situation where there are two opportunities to perform reallocation within a replenishment cycle. We derive a mathematical model to determine when and how to perform reallocation. Furthermore, we consider the extension of this model to the situation allowing an arbitrary number of reallocations. Experimental results show that the two-reallocation approach achieves better performance compared with the single-reallocation approach found in the literature. We also illustrate how …

Introducing Communication In Dis-Pomdps With Locality Of Interaction, Makoto Tasaki, Yuichi Yabu, Yuki Iwanari, Makoto Yokoo, Janusz Marecki, Pradeep Reddy Varakantham, Milind Tambe

Research Collection School Of Computing and Information Systems

The Networked Distributed POMDPs (ND-POMDPs) can model multiagent systems in uncertain domains and has begun to scale-up the number of agents. However, prior work in ND-POMDPs has failed to address communication. Without communication, the size of a local policy at each agent within the ND-POMDPs grows exponentially in the time horizon. To overcome this problem, we extend existing algorithms so that agents periodically communicate their observation and action histories with each other. After communication, agents can start from new synchronized belief state. Thus, we can avoid the exponential growth in the size of local policies at agents. Furthermore, we introduce …

An Fpga-Based System For Tracking Digital Information Transmitted Via Peer-To-Peer Protocols, Karl R. Schrader, Barry E. Mullins, Gilbert L. Peterson, Robert F. Mills

Faculty Publications

This paper presents a Field Programmable Gate Array (FPGA)-based tool designed to process file transfers using the BitTorrent Peer-to-Peer (P2P) protocol and VoIP phone calls made using the Session Initiation Protocol (SIP). The tool searches selected control messages in real time and compares the unique identifier of the shared file or phone number against a list of known contraband files or phone numbers. Results show the FPGA tool processes P2P packets of interest 92% faster than a software-only configuration and is 97.6% accurate at capturing and processing messages at a traffic load of 89.6 Mbps.

Crctol: A Semantic Based Domain Ontology Learning System, Xing Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Domain ontologies play an important role in supporting knowledge‐based applications in the Semantic Web. To facilitate the building of ontologies, text mining techniques have been used to perform ontology learning from texts. However, traditional systems employ shallow natural language processing techniques and focus only on concept and taxonomic relation extraction. In this paper we present a system, known as Concept‐Relation‐Concept Tuple‐based Ontology Learning (CRCTOL), for mining ontologies automatically from domain‐specific documents. Specifically, CRCTOL adopts a full text parsing technique and employs a combination of statistical and lexico‐syntactic methods, including a statistical algorithm that extracts key concepts from a document collection, …

On Coalgebras Over Algebras, Adriana Balan, Alexander Kurz

Engineering Faculty Articles and Research

We extend Barr’s well-known characterization of the final coalgebra of a Set-endofunctor as the completion of its initial algebra to the Eilenberg-Moore category of algebras for a Set-monad M for functors arising as liftings. As an application we introduce the notion of commuting pair of endofunctors with respect to the monad M and show that under reasonable assumptions, the final coalgebra of one of the endofunctors involved can be obtained as the free algebra generated by the initial algebra of the other endofunctor.

Families Of Symmetries As Efficient Models Of Resource Binding, Vincenzo Ciancia, Alexander Kurz, Ugo Montanari

Engineering Faculty Articles and Research

Calculi that feature resource-allocating constructs (e.g. the pi-calculus or the fusion calculus) require special kinds of models. The best-known ones are presheaves and nominal sets. But named sets have the advantage of being finite in a wide range of cases where the other two are infinite. The three models are equivalent. Finiteness of named sets is strictly related to the notion of finite support in nominal sets and the corresponding presheaves. We show that named sets are generalisd by the categorical model of families, that is, free coproduct completions, indexed by symmetries, and explain how locality of interfaces gives good …

Transmitter Optimization In Multiuser Wireless Systems With Quality Of Service Constraints, Danda B. Rawat

Electrical & Computer Engineering Theses & Dissertations

In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other …

Privacy-Preserving Attribute-Based Access Control In A Grid, Sang Mork Park

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A Grid community is composed of diverse stake holders, such as data resource providers, computing resource providers, service providers, and the users of the resources and services. In traditional security systems for Grids, most of the authentication and authorization mechanisms are based on the user's identity or the user's classification information. If the authorization mechanism is based on the user's identity, fine-grained access control policies can be implemented but the scalability of the security system would be limited. If the authorization mechanism is based on the user's classification, the scalability can be improved but the fine-grained access control policies may …

Prognosis: A Wearable System For Health Monitoring Of People At Risk, Alexandros A. Pantelopoulos

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Wearable Health Monitoring Systems (WHMS) have drawn a lot of attention from the research community and the industry during the last decade. The development of such systems has been motivated mainly by increasing healthcare costs and by the fact that the world population is ageing. In addition to that, RandD in WHMS has been propelled by recent technological advances in miniature bio-sensing devices, smart textiles, microelectronics and wireless communications techniques. These portable health systems can comprise various types of small physiological sensors, which enable continuous monitoring of a variety of human vital signs and other physiological parameters such as heart …

Evolution And Analysis Of Neuromorphic Flapping-Wing Flight Controllers, Sanjay Kumar Boddhu

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The control of insect-sized flapping-wing micro air vehicles is attracting increasing interest. Solution of the problem requires construction of a controller that is physically small, extremely power efficient, and capable. In addition, process variation in the creation of very small wings and armatures as well as the potential for accumulating damage and wear over the course of a vehicle's lifetime suggest that controllers be able to self-adapt to the specific and possibly changing nature of the vehicles in which they are embedded. Previous work with Evolvable Hardware Continuous Time Recurrent Neural Networks (CTRNNs) as applied to adaptive control of walking …

A Novel Synergistic Diagnosis Methodology For Identifying Abnormalities In Wireless Capsule Endoscopy Videos, Alexandros Karargyris

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Wireless Capsule Endoscopy (WCE) is a new technology that allows medical personnel to view the gastrointestinal (GI) mucosa. It is a swallowable miniature capsule device the size of a pill that transmits thousands of screenshots of the digestive tract to a wearable receiver. When the procedure finishes the video is uploaded to a workstation for viewing. Capsule Endoscopy has been established as a tool to identify various gastrointestinal (GI) conditions, such as blood-based abnormalities, polyps, ulcers, Crohn's disease in the small intestine, where the classical endoscopy is not regularly used.

As of 2009 the market is dominated by Given Imaging …

Semantic Provenance: Modeling, Querying, And Application In Scientific Discovery, Satya Sanket Sahoo

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Provenance metadata, describing the history or lineage of an entity, is essential for ensuring data quality, correctness of process execution, and computing trust values. Traditionally, provenance management issues have been dealt with in the context of workflow or relational database systems. However, existing provenance systems are inadequate to address the requirements of an emerging set of applications in the new eScience or Cyberinfrastructure paradigm and the Semantic Web. Provenance in these applications incorporates complex domain semantics on a large scale with a variety of uses, including accurate interpretation by software agents, trustworthy data integration, reproducibility, attribution for commercial or legal …

Understanding User-Generated Content On Social Media, Bala Meenakshi Nagarajan

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Over the last few years, there has been a growing public and enterprise fascination with 'social media' and its role in modern society. At the heart of this fascination is the ability for users to participate, collaborate, consume, create and share content via a variety of platforms such as blogs, micro-blogs, email, instant messaging services, social network services, collaborative wikis, social bookmarking sites, and multimedia sharing sites.

This dissertation is devoted to understanding informal user-generated textual content on social media platforms and using the results of the analysis to build Social Intelligence Applications.

The body of research presented in this …

Joint Feature Selection And Classification For Taxonomic Problems Within Fish Species Complexes, Yixin Chen, Shuqing Huang, Huimin Chen, Henry L. Bart

Huimin Chen

It is estimated that 90% of the world’s species are yet to be discovered and described. The main reason for the slow pace of new species description is that the science of taxonomy can be very laborious. To formally describe a new species, taxonomists have to manually gather and analyze data from large numbers of specimens and identify the smallest subset of external body characters that uniquely diagnose the new species as distinct from all its known relatives. In this paper, we present an automated feature selection and classification scheme using logistic regression with controlled false discovery rate to address …

Diagnosing Intermittent And Persistent Faults Using Static Bayesian Networks, Ole J. Mengshoel, Brian Ricks

Ole J Mengshoel

Both intermittent and persistent faults may occur in a wide range of systems. We present in this paper the introduction of intermittent fault handling techniques into ProDiagnose, an algorithm that previously only handled persistent faults. We discuss novel algorithmic techniques as well as how our static Bayesian networks help diagnose, in an integrated manner, a range of intermittent and persistent faults. Through experiments with data from the ADAPT electrical power system test bed, generated as part of the Second International Diagnostic Competition (DXC-10), we show that this novel variant of ProDiagnose diagnoses intermittent faults accurately and quickly, while maintaining strong …