Computer Sciences Commons^™

Simple Linear Interpolation Explains All Usual Choices In Fuzzy Techniques: Membership Functions, T-Norms, T-Conorms, And Defuzzification, Vladik Kreinovich, Jonathan Quijas, Esthela Gallardo, Caio De Sa Lopes, Olga Kosheleva, Shahnaz Shahbazova

Departmental Technical Reports (CS)

Most applications of fuzzy techniques use piece-wise linear (triangular or trapezoid) membership functions, min or product t-norms, max or algebraic sum t-conorms, and centroid defuzzification. Similarly, most applications of interval-valued fuzzy techniques use piecewise-linear lower and upper membership functions. In this paper, we show that all these choices can be explained as applications of simple linear interpolation.

Compensatory Enlargement Of Ossabaw Miniature Swine Coronary Arteries In Diffuse Atherosclerosis, Jenny Susana Choy, Tong Luo, Yunlong Huo, Thomas Wischgoll, Kyle Schultz, Shawn D. Teague, Michael Sturek, Ghassan S. Kassab

Computer Science and Engineering Faculty Publications

Studies in human and non-human primates have confirmed the compensatory enlargement or positive remodeling (Glagov phenomenon) of coronary vessels in the presence of focal stenosis. To our knowledge, this is the first study to document arterial enlargement in a metabolic syndrome animal model with diffuse coronary artery disease (DCAD) in the absence of severe focal stenosis. Two different groups of Ossabaw miniature pigs were fed a high fat atherogenic diet for 4 months (Group I) and 12 months (Group II), respectively. Group I (6 pigs) underwent contrast enhanced computed tomographic angiography (CCTA) and intravascular ultrasound (IVUS) at baseline and after …

Fail-Safe Test Generation Of Safety Critical Systems, Salwa Elakeili

Electronic Theses and Dissertations

This dissertation introduces a technique for testing proper failure mitigation in safety critical systems. Unlike other approaches which integrate behavioral and failure models, and then generate tests from the integrated model, we build safety mitigation tests from an existing behavioral test suite, using an explicit mitigation model for which we generate mitigation paths which are then woven at selected failure points into the original test suite to create failure-mitigation tests (safety mitigation test).

Video-To-Video Pose And Expression Invariant Face Recognition Using Volumetric Directional Pattern, Vijayan K. Asari, Almabrok Essa

Electrical and Computer Engineering Faculty Publications

Face recognition in video has attracted attention as a cryptic method of human identification in surveillance systems. In this paper, we propose an end-to-end video face recognition system, addressing a difficult problem of identifying human faces in video due to the presence of large variations in facial pose and expression, and poor video resolution. The proposed descriptor, named Volumetric Directional Pattern (VDP), is an oriented and multi-scale volumetric descriptor that is able to extract and fuse the information of multi frames, temporal (dynamic) information, and multiple poses and expressions of faces in input video to produce feature vectors, which are …

A Study Of Decision Process In Mcdm Problems With Large Number Of Criteria, Jian Liu, Peng Liu, Si Feng Liu, Xian Zhong Zhou, Tao Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an effective decision process method is proposed to address the challenge in a multiple criteria decision-making (MCDM) problem because of large number of criteria. This method is based on the criteria reduction, tolerance relation, and prospect theory (PT). By building a discernibility matrix for tolerance relation (DMTR) in an MCDM problem with numerical values or interval numbers, this method first allows us to recognize a set of critical criteria from a large criteria pool and ignore the other criteria. Next, it establishes the criteria weights through the DMTR as they are usually not indicated in the data. …

Click-Boosting Multi-Modality Graph-Based Reranking For Image Search, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

Image reranking is an effective way for improving the retrieval performance of keyword-based image search engines. A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns from the initial search results. Ideally, these patterns can be leveraged to upgrade the ranks of visually similar images, which are also likely to be relevant. The challenge, nevertheless, originates from the fact that keyword-based queries are used to be ambiguous, resulting in difficulty in predicting the search intention. Mining useful patterns without understanding query is risky, and may lead to incorrect judgment in …

A Proposed Model For The Approach To Augmented Reality Deployment In Marketing Communications, Stephen O'Mahony

Dept. of Marketing & International Business Conference Material

In the contemporary landscape, human interaction is characterized by the pervasive mediation of intelligent agents. Owing to advances in computer science and engineering, phenomena once limited to fixed locations are metamorphosing from extraneous entities to implicit components of the everyday. Computing power has simultaneously enhanced and miniaturized to the extent that contemporary consumer devices demonstrate power equivalent to or greater than that of personal computers of recent memory. At the same time, network connectivity has proliferated to ubiquitous levels, reflected in the fact that the amount of inanimate objects connected to the Internet has recently surpassed the human population of …

Identifying Locations Of Active Corrosion Growth From Successive In-Line Inspections, Tom Bubenik, William V. Harper, Pam Moreno, Steven Polasik

Mathematics Faculty Scholarship

The integrated approach covered by this paper identifies corrosion activity using a combination of statistics, inspection-signal comparisons, and engineering analyses. The approach relies on an understanding of ILI and the mechanisms that cause corrosion and its growth. Pipeline operators can use the approach to calculate remaining lives, prioritize repairs and mitigation, and extend reassessment intervals. This process is collectively known as statistically-active corrosion.

Systems, Methods And Devices For Vector Control Of Permanent Magnet Synchronous Machines Using Artificial Neural Networks, Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso

Electrical and Computer Engineering Faculty Research & Creative Works

An example method for controlling an AC electrical machine can include providing a PWM converter operably connected between an electrical power source and the AC electrical machine and providing a neural network vector control system operably connected to the PWM converter. The control system can include a current-loop neural network configured to receive a plurality of inputs. The current-loop neural network can be configured to optimize the compensating dq-control voltage. The inputs can be d- and q-axis currents, d- and q-axis error signals, predicted d- and q-axis current signals, and a feedback compensating dq-control voltage. The d- and q-axis error …

Person Identification From Streaming Surveillance Video Using Mid-Level Features From Joint Action-Pose Distribution, Binu M. Nair, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We propose a real time person identification algorithm for surveillance based scenarios from low-resolution streaming video, based on mid-level features extracted from the joint distribution of various types of human actions and human poses.

The proposed algorithm uses the combination of an auto-encoder based action association framework which produces per-frame probability estimates of the action being performed, and a pose recognition framework which gives per-frame body part locations.

The main focus in this manuscript is to effectively combine these per-frame action probability estimates and pose trajectories from a short temporal window to obtain mid-level features. We demonstrate that these mid-level …

Clustering Header Categories Extracted From Web Tables, George Nagy, David W. Embley, Mukkai Krishnamoorthy, Sharad C. Seth

School of Computing: Conference and Workshop Papers

Revealing related content among heterogeneous web tables is part of our long term objective of formulating queries over multiple sources of information. Two hundred HTML tables from institutional web sites are segmented and each table cell is classified according to the fundamental indexing property of row and column headers. The categories that correspond to the multi-dimensional data cube view of a table are extracted by factoring the (often multi-row/column) headers. To reveal commonalities between tables from diverse sources, the Jaccard distances between pairs of category headers (and also table titles) are computed. We show how about one third of our …

Semi-Modular Delay Model Revisited In Context Of Relative Timing, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

A new definition of semi-modularity to accommodate relative timing constraints in self-timed circuits is presented. While previous definitions ignore such constraints, the new definition takes them into account. The difference on a design solution for a well-known speed-independent circuit implementation of the Muller C element and a set of relative timing constraints that renders the implementation hazard free is illustrated. The old definition produces a false semi-modularity conflict that cannot exist due to the set of imposed constraints. The new definition correctly accepts the solution.

Con-Resistant Trust For Improved Reliability In A Smart Grid Special Protection System, Crystal M. Shipman, Kenneth M. Hopkinson, Juan L. Lopez Jr.

Faculty Publications

This paper applies a con-resistant trust mechanism to improve the performance of a communications-based special protection system to enhance its effectiveness and resiliency. Smart grids incorporate modern information technologies to increase reliability and efficiency through better situational awareness. However, with the benefits of this new technology come the added risks associated with threats and vulnerabilities to the technology and to the critical infrastructure it supports. The research in this paper uses con-resistant trust to quickly identify malicious or malfunctioning (untrustworthy) protection system nodes to mitigate instabilities. The con-resistant trust mechanism allows protection system nodes to make trust assessments based on …

Producing High Strength Aluminum Alloy By Combination Of Equal Channel Angular Pressing And Bake Hardening, Hamid Alihosseini, Mohsen Asle Zaeem, Kamran Dehghani, Ghader Faraji

Materials Science and Engineering Faculty Research & Creative Works

A combination of severe plastic deformation by equal channel angular pressing (ECAP) and bake hardening (BH) was used to produce high strength ultrafine-grained AA6061 aluminum alloy. 2, 4 and 8 passes of ECAP were performed, and the bake hardenability of samples was tested by 6% pre-straining followed by baking at 200 °C for 20 min. The microstructures obtained for various passes of ECAP were characterized by XRD, EBSD, and TEM techniques. The microstructures were refined from an average grain size of 20 µm to 212 nm after 8 passes of ECAP. Maximum bake hardenability of 110 MPa, and final yield …

Grafalgo - A Library Of Graph Algorithms And Supporting Data Structures, Jonathan Turner

All Computer Science and Engineering Research

This report provides an overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. Grafalgo is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/. Source code documentation is at www.arl.wustl.edu/~jst/doc/grafalgo. While not designed as production …

Advantages Of A Finite Extensible Nonlinear Elastic Potential In Lattice Boltzmann Simulations, Tai-Hsien Wu, Dewei Qi

The Hilltop Review

A new structure, generalized lattice nonlinear spring model (GLNSM), which adopts non-linear FENE-LJ potential instead of harmonic potential, has been coupled with lattice Boltzmann simulation for solving fluid-solid interaction problem. In this article, a significant work is the relationship between the GLNSM (FENE-LJ potential) and Young’s modulus has been described in detail. A validation has also been presented to prove that GLNSM is reliable.

Static Conflict Detection For A Policy Language, Alix Trou, Robert Dockins, Andrew Tolmach

Computer Science Faculty Publications and Presentations

We present a static control flow analysis used in the Simple Unified Policy Programming Language (SUPPL) compiler to detect internally inconsistent policies. For example, an access control policy can decide to both “allow” and “deny” access for a user; such an inconsistency is called a conflict. Policies in Suppl. follow the Event-Condition-Action paradigm; predicates are used to model conditions and event handlers are written in an imperative way. The analysis is twofold; it first computes a superset of all conflicts by looking for a combination of actions in the event handlers that might violate a user-supplied definition of conflicts. SMT …

Numerical Investigation On Charring Ablator Geometric Effects: Study Of Stardust Sample Return Capsule Heat Shield, Haoyue Weng, Alexandre Martin

Mechanical Engineering Faculty Publications

Sample geometry is very influential in small charring ablative articles where 1D assumption might not be accurate. In heat shield design, 1D is often assumed since the nose radius is much larger than the thickness of charring. Whether the 1D assumption is valid for the heat shield is unknown. Therefore, the geometric effects of Stardust sample return capsule heat shield are numerically studied using a material response program. The developed computer program models material charring, conductive heat transfer, surface energy balance, pyrolysis gas transport and orthotropic material properties in 3D Cartesian coordinates. Simulation results show that the centerline temperatures predicted …

Direct Optimization For Classification With Boosting, Shaodan Zhai

Browse all Theses and Dissertations

Boosting, as one of the state-of-the-art classification approaches, is widely used in the industry for a broad range of problems. The existing boosting methods often formulate classification tasks as a convex optimization problem by using surrogates of performance measures. While the convex surrogates are computationally efficient to globally optimize, they are sensitive to outliers and inconsistent under some conditions. On the other hand, boosting's success can be ascribed to maximizing the margins, but few boosting approaches are designed to directly maximize the margin. In this research, we design novel boosting algorithms that directly optimize non-convex performance measures, including the empirical …

Contrast Pattern Aided Regression And Classification, Vahid Taslimitehrani

Browse all Theses and Dissertations

Regression and classification techniques play an essential role in many data mining tasks and have broad applications. However, most of the state-of-the-art regression and classification techniques are often unable to adequately model the interactions among predictor variables in highly heterogeneous datasets. New techniques that can effectively model such complex and heterogeneous structures are needed to significantly improve prediction accuracy. In this dissertation, we propose a novel type of accurate and interpretable regression and classification models, named as Pattern Aided Regression (PXR) and Pattern Aided Classification (PXC) respectively. Both PXR and PXC rely on identifying regions in the data space where …

Potential Of Cognitive Computing And Cognitive Systems, Ahmed K. Noor

Computational Modeling & Simulation Engineering Faculty Publications

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The …

Optimizing Pred(25) Is Np-Hard, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Usually, in data processing, to find the parameters of the models that best fits the data, people use the Least Squares method. One of the advantages of this method is that for linear models, it leads to an easy-to-solve system of linear equations. A limitation of this method is that even a single outlier can ruin the corresponding estimates; thus, more robust methods are needed. In particular, in software engineering, often, a more robust pred(25) method is used, in which we maximize the number of cases in which the model's prediction is within the 25% range of the observations. In …

Feature Extraction Using Dimensionality Reduction Techniques: Capturing The Human Perspective, Ashley B. Coleman

Browse all Theses and Dissertations

The purpose of this paper is to determine if any of the four commonly used dimensionality reduction techniques are reliable at extracting the same features that humans perceive as distinguishable features. The four dimensionality reduction techniques that were used in this experiment were Principal Component Analysis (PCA), Multi-Dimensional Scaling (MDS), Isomap and Kernel Principal Component Analysis (KPCA). These four techniques were applied to a dataset of images that consist of five infrared military vehicles. Out of the four techniques three out of the five resulting dimensions of PCA matched a human feature. One out of five dimensions of MDS matched …

A Workload Balanced Mapreduce Framework On Gpu Platforms, Yue Zhang

Browse all Theses and Dissertations

The MapReduce framework is a programming model proposed by Google to process large datasets. It is an efficient framework that can be used in many areas, such as social network, scientific research, electronic business, etc. Hence, more and more MapReduce frameworks are implemented on different platforms, including Phoenix (based on multicore CPU), MapCG (based on GPU), and StreamMR (based on GPU). However, these MapReduce frameworks have limitations, and they cannot handle the collision problem in the map phase, and the unbalanced workload problems in the reduce phase. To improve the performance of the MapReduce framework on GPGPUs, in this thesis, …

Introduction To Mips Assembly Language Programming, Charles W. Kann

Open Educational Resources

This book was written to introduce students to assembly language programming in MIPS. As with all assembly language programming texts, it covers basic operators and instructions, subprogram calling, loading and storing memory, program control, and the conversion of the assembly language program into machine code.

However this book was not written simply as a book on assembly language programming. The larger purpose of this text is to show how concepts in Higher Level Languages (HLL), such as Java or C/C++, are represented in assembly. By showing how program constructs from these HLL map into assembly, the concepts will be easier …

Modeling Crowd Mobility And Communication In Wireless Networks, Gurkan Solmaz

Electronic Theses and Dissertations

This dissertation presents contributions to the fields of mobility modeling, wireless sensor networks (WSNs) with mobile sinks, and opportunistic communication in theme parks. The two main directions of our contributions are human mobility models and strategies for the mobile sink positioning and communication in wireless networks. The first direction of the dissertation is related to human mobility modeling. Modeling the movement of human subjects is important to improve the performance of wireless networks with human participants and the validation of such networks through simulations. The movements in areas such as theme parks follow specific patterns that are not taken into …

Collaborative Knowledge As A Service Applied To The Disaster Management Domain, Katarina Grolinger, Emna Mezghani, Miriam Am Capretz, Ernesto Exposito

Electrical and Computer Engineering Publications

Cloud computing offers services which promise to meet continuously increasing computing demands by using a large number of networked resources. However, data heterogeneity remains a major hurdle for data interoperability and data integration. In this context, a Knowledge as a Service (KaaS) approach has been proposed with the aim of generating knowledge from heterogeneous data and making it available as a service. In this paper, a Collaborative Knowledge as a Service (CKaaS) architecture is proposed, with the objective of satisfying consumer knowledge needs by integrating disparate cloud knowledge through collaboration among distributed KaaS entities. The NIST cloud computing reference architecture …

A Generalized Service Replication Process In Distributed Environments, Hany F. Elyamany, Marwa F. Mohamed, Katarina Grolinger, Miriam Am Capretz

Electrical and Computer Engineering Publications

Replication is one of the main techniques aiming to improve Web services’ (WS) quality of service (QoS) in distributed environments, including clouds and mobile devices. Service replication is a way of improving WS performance and availability by creating several copies or replicas of Web services which work in parallel or sequentially under defined circumstances. In this paper, a generalized replication process for distributed environments is discussed based on established replication studies. The generalized replication process consists of three main steps: sensing the environment characteristics, determining the replication strategy, and implementing the selected replication strategy. To demonstrate application of the generalized …

Energy Cost Forecasting For Event Venues, Katarina Grolinger, Andrea Zagar, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Electricity price, consumption, and demand forecasting has been a topic of research interest for a long time. The proliferation of smart meters has created new opportunities in energy prediction. This paper investigates energy cost forecasting in the context of entertainment event-organizing venues, which poses significant difficulty due to fluctuations in energy demand and wholesale electricity prices. The objective is to predict the overall cost of energy consumed during an entertainment event. Predictions are carried out separately for each event category and feature selection is used to select the most effective combination of event attributes for each category. Three machine learning …

Novel Incorportation Of Biomedical Engineering Algorithms (Bispectral Index Guided Or Anesthetic Concentration Guided) In Real-Time Decision Support To Prevent Intraoperative Awareness Using An Electronic Anesthesia Information Mananagement System, Amy Melanie Shanks

Wayne State University Dissertations

Background: Intraoperative awareness with explicit recall (AWR) is a feared complication of surgery that can lead to significant psychological distress. Several large prospective trials have been completed comparing two methods of monitoring anesthetic depth [minimum alveolar concentration (MAC) or electroencephalography (EEG) monitoring using the bispectral index (BIS)] for the prevention of AWR. However, these trials were conducted in high risk populations, limiting generalizability.

Research Hypothesis: Real-time decision support with Anesthesia Information Management System alerts based on a novel anesthetic concentration algorithm (incorporating the use of intravenous anesthetics) or an EEG-guided algorithm will reduce the known incidence of AWR.

Methods: First, …