Computer Engineering Commons^™

An Ensemble Deep Convolutional Neural Network Model With Improved D-S Evidence Fusion For Bearing Fault Diagnosis, Shaobo Li, Guokai Liu, Xianghong Tang, Jianguang Lu, Jianjun Hu

Faculty Publications

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster–Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations …

What Are The Ultimate Limits To Computational Techniques: Verifier Theory And Unverifiability, Roman V. Yampolskiy

Faculty Scholarship

Despite significant developments in proof theory, surprisingly little attention has been devoted to the concept of proof verifiers. In particular, the mathematical community may be interested in studying different types of proof verifiers (people, programs, oracles, communities, superintelligences) as mathematical objects. Such an effort could reveal their properties, their powers and limitations (particularly in human mathematicians), minimum and maximum complexity, as well as self-verification and self-reference issues. We propose an initial classification system for verifiers and provide some rudimentary analysis of solved and open problems in this important domain. Our main contribution is a formal introduction of the notion of …

Data Extraction From Web Tables: The Devil Is In The Details, George Nagy, Sharad C. Seth, Dongpu Jin, David W. Embley, Spencer Machado, Mukkai Krishnamoorthy

CSE Conference and Workshop Papers

We present a method based on header paths for efficient and complete extraction of labeled data from tables meant for humans. Although many table configurations yield to the proposed syntactic analysis, some require access to semantic knowledge. Clicking on one or two critical cells per table, through a simple interface, is sufficient to resolve most of these problem tables. Header paths, a purely syntactic representation of visual tables, can be transformed (“factored”) into existing representations of structured data such as category trees, relational tables, and RDF triples. From a random sample of 200 web tables from ten large statistical web …

End-To-End Conversion Of Html Tables For Populating A Relational Database, George Nagy, David W. Embley, Sharad C. Seth

CSE Conference and Workshop Papers

Automating the conversion of human-readable HTML tables into machine-readable relational tables will enable end-user query processing of the millions of data tables found on the web. Theoretically sound and experimentally successful methods for index-based segmentation, extraction of category hierarchies, and construction of a canonical table suitable for direct input to a relational database are demonstrated on 200 heterogeneous web tables. The methods are scalable: the program generates the 198 Access compatible CSV files in ~0.1s per table (two tables could not be indexed).

Application-Aware Cognitive Multi-Hop Wireless Networking Testbed And Experiments, Trenton T. Evans

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we present a new architecture for application-aware cognitive multihop wireless networks (AC-MWN) with testbed implementations and experiments. Cognitive radio is a technique to adaptively use the spectrum so that the resource can be used more efficiently in a low cost way. Multihop wireless networks can be deployed quickly and flexibly without a fixed infrastructure. In presented new architecture, we study backbone routing schemes with network cognition, routing scheme with network coding and spectrum adaptation. A testbed is implemented to test the schemes for AC-MWN. In addition to basic measurements, we implement a video streaming application based on …

An Advanced Multi-Sensor Acousto-Ultrasonic Structural Health Monitoring System: Development And Aerospace Demonstration, Joel Smithard, Nik Rajic, Stephen Van Der Velden, Patrick Norman, Cedric Rosalie, Steve Galea, Hanfei Mei, Bin Lin, Victor Giurgiutiu

Faculty Publications

A key longstanding objective of the Structural Health Monitoring (SHM) research community is to enable the embedment of SHM systems in high value assets like aircraft to provide on-demand damage detection and evaluation. As against traditional non-destructive inspection hardware, embedded SHM systems must be compact, lightweight, low-power and sufficiently robust to survive exposure to severe in-flight operating conditions. Typical Commercial-Off-The-Shelf (COTS) systems can be bulky, costly and are often inflexible in their configuration and/or scalability, which militates against in-service deployment. Advances in electronics have resulted in ever smaller, cheaper and more reliable components that facilitate the development of compact and …

Data Science Solution For User Authentication, Anas Ibrahim

Electronic Thesis and Dissertation Repository

User authentication is considered a key factor in almost any software system and is often the first layer of security in the digital world. Authentication methods utilize one, or a combination of up to two, of the following factors: something you know, something you have and something you are. To prevent serious data breaches that have occurred using the traditional authentication methods, a fourth factor, something you do, that is being discussed among researchers; unfortunately, methods that rely on this fourth factor have problems of their own.

This thesis addresses the issues of the fourth authentication factor and proposes a …

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …

Custom 3d Printer And Resin For 18 Μm × 20 Μm Mi- Crofluidic Flow Channels, Hua Gong, Bryce P. Bickham, Adam T. Woolley, Gregory P. Nordin

Faculty Publications

While there is great interest in 3D printing for microfluidic device fabrication, to-date the achieved feature sizes have not been in the truly microfluidic regime (μm). In this paper we demonstrate that a custom Digital Light Processor stereolithographic (DLP-SLA) 3D printer and a specifically-designed, low cost, custom resin can readily achieve flow channel cross sections as small as 18 μm × 20 μm. Our 3D printer has a projected image plane resolution of 7.6 μm and uses a 385 nm LED, which dramatically increases the available selection of UV absorbers for resin formulation compared to 3D printers with 405 nm …

Virtualization Of Closed-Loop Sensor Networks, Priyanka Dattatri Kedalagudde

Masters Theses

The existing closed-loop sensor networks are based on architectures that are designed and implemented for one specific application and require dedicated sensing and computational resources. This prevents the sharing of these networks. In this work, we propose an architecture of virtualization to allow sharing of closed-loop sensor networks. We also propose a scheduling approach that will manage requests from competing applications and evaluate their impact on system utilization against utilization achieved by more traditional, dedicated sensor networks. These algorithms are evaluated through trace-driven simulations, where the trace data is taken from CASA’s closed-loop weather radar sensor network. Results from this …

Packet Scheduling Algorithms In Lte/Lte-A Cellular Networks: Multi-Agent Q-Learning Approach, Najem Nafiz Sirhan

Electrical and Computer Engineering ETDs

Spectrum utilization is vital for mobile operators. It ensures an efficient use of spectrum bands, especially when obtaining their license is highly expensive. Long Term Evolution (LTE), and LTE-Advanced (LTE-A) spectrum bands license were auctioned by the Federal Communication Commission (FCC) to mobile operators with hundreds of millions of dollars. In the first part of this dissertation, we study, analyze, and compare the QoS performance of QoS-aware/Channel-aware packet scheduling algorithms while using CA over LTE, and LTE-A heterogeneous cellular networks. This included a detailed study of the LTE/LTE-A cellular network and its features, and the modification of an open source …

Belief-Space Planning For Resourceful Manipulation And Mobility, Dirk Ruiken

Doctoral Dissertations

Robots are increasingly expected to work in partially observable and unstructured environments. They need to select actions that exploit perceptual and motor resourcefulness to manage uncertainty based on the demands of the task and environment. The research in this dissertation makes two primary contributions. First, it develops a new concept in resourceful robot platforms called the UMass uBot and introduces the sixth and seventh in the uBot series. uBot-6 introduces multiple postural configurations that enable different modes of mobility and manipulation to meet the needs of a wide variety of tasks and environmental constraints. uBot-7 extends this with the use …

Multiple Attributes Decision Fusion For Wireless Sensor Networks Based On Intuitionistic Fuzzy Set, Zhenjiang Zhang, Ziqi Hao, Sherali Zeadally, Jing Zhang, Bowen Han, Han-Chieh Chao

Information Science Faculty Publications

Decision fusion is an important issue in wireless sensor networks (WSN), and intuitionistic fuzzy set (IFS) is a novel method for dealing with uncertain data. We propose a multi-attribute decision fusion model based on IFS, which includes two aspects: data distribution-based IFS construction algorithm (DDBIFCA) and the category similarity weight-based TOPSIS intuitionistic fuzzy decision algorithm (CSWBT-IFS). The DDBIFCA is an IFS construction algorithm that transforms the original attribute values into intuitionistic fuzzy measures, and the CSWBT-IFS is an intuitionistic fuzzy aggregation algorithm improved by the traditional TOPSIS algorithm, which combines intuitionistic fuzzy values of different attributes and obtains a final …

Multi-View Face Recognition From Single Rgbd Models Of The Faces, Donghun Kim, Bharath Comandur, Henry P. Medeiros, Noha M. Elfiky, Avinash Kak

Electrical and Computer Engineering Faculty Research and Publications

This work takes important steps towards solving the following problem of current interest: Assuming that each individual in a population can be modeled by a single frontal RGBD face image, is it possible to carry out face recognition for such a population using multiple 2D images captured from arbitrary viewpoints? Although the general problem as stated above is extremely challenging, it encompasses subproblems that can be addressed today. The subproblems addressed in this work relate to: (1) Generating a large set of viewpoint dependent face images from a single RGBD frontal image for each individual; (2) using hierarchical approaches based …

Introduction To Signal Timing & Traffic Control, Sarah V. Hernandez, Mariah Crew, Karla Diaz-Corro, Taslima Akter

Civil Engineering Teaching and Learning

The purpose of these lesson plans is to introduce students to traffic signalization basics. Students will be lead through a series of mini-lectures on traffic control and signalization including a discussion on the limitations and benefits of traffic signalization. The lesson plans compliment a computer simulation “game” in which students act as manual operators for a single up to four by four gridded intersection. Students attempt to control the progression of signals to understand the relationship between signal timing and user delay. Through experimentation with the simulation, students generate a presentation discussing the benefits and drawbacks of signal timing and …

A Half-Yearly E-Newsletter Of The Department Of Computer Science And Engineering Manipal Institute Of Technology,, Ashalatha Nayak

Faculty work

No abstract provided.

How Technology Is Reshaping Financial Services: Essays On Consumer Behavior In Card, Channel And Cryptocurrency Services, Dan Geng

Dissertations and Theses Collection

The financial services sector has seen dramatic technological innovations in the last several years associated with the “fintech revolution.” Major changes have taken place in channel management, credit card rewards marketing, cryptocurren-cy, and wealth management, and have influenced consumers’ banking behavior in different ways. As a consequence, there has been a growing demand for banks to rethink their business models and operations to adapt to changing consumer be-havior and counter the competitive pressure from other banks and non-bank play-ers. In this dissertation, I study consumer behavior related to different aspects of financial innovation by addressing research questions that are motivated …

Performance Resilience Analysis Of Dynamic Feedback Controllers For Both Multiplicative And Additive Gain Perturbations, Fan Feng, Susan C. Schneider, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

In this work, a procedure is presented for performance resilience analysis of continuous-time systems controlled by full-order dynamic feedback compensators. The resilience property is defined in terms of defining maximum perturbations on both the controller and observer gains that will maintain controller and observer eigenvalues in disjoint regions in the complex plane so that the closed loop system will sustain certain performance characteristics. The desired performance is characterized by the response speed and magnitude bounds on the response. Therefore, the intersection of two regions are chosen, vertical strips and sector regions, to guarantee upper and lower bounds on the settling …

Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, Usha Lokala, Srinivas Nowduri, Prabhakar K Sharma

Publications

Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new …

Modeling Micro-Porous Surfaces For Secondary Electron Emission Control To Suppress Multipactor, J. M. Sattler, Ronald A. Coutu Jr., R. Lake, T. Laurvick, T. Back, S. Fairchild

Electrical and Computer Engineering Faculty Research and Publications

This work seeks to understand how the topography of a surface can be engineered to control secondary electron emission (SEE) for multipactor suppression. Two unique, semi-empirical models for the secondary electron yield (SEY) of a micro-porous surface are derived and compared. The first model is based on a two-dimensional (2D) pore geometry. The second model is based on a three-dimensional (3D) pore geometry. The SEY of both models is shown to depend on two categories of surface parameters: chemistry and topography. An important parameter in these models is the probability of electron emissions to escape the surface pores. This probability …