Operations Research, Systems Engineering and Industrial Engineering Commons^™

Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon

Electronic Thesis and Dissertation Repository

Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices.

One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor …

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

Research Of Three-Phases Current’S Transducers Of Filter-Compensation Devices For Control Reactive Power’S Consumption Of Asynchronous Motor, Ilkhomjon Khakimovich Siddikov, Dilyorbek Karimjonov Doniyorbek O'G'Li -, Abdumutal Abdikarimovich Abdigapirov

Chemical Technology, Control and Management

In the article given materials of developing of three-phase electromagnetic current transducers of reactive power, using with asynchronous motor, methods connecting of two sensing element, series, parallel and differential and loops suitable for each phase, dynamic characteristics of output signals of three-phase electromagnetic current transducers asynchronous motor.

On the basis of modern calculation and design complexes are of great importance in the research variable sizes of three-phase current electromagnetic transducers of filter-compensation devices of reactive power of asynchronous motors. Presented mathematical model of research of electrical, electromagnetic and magnetic elements of electromagnetic current transducers in the …

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …

The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami

Future Computing and Informatics Journal

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …

Collaborative All-Source Navigation With Integrity, Jonathon S. Gipson

Theses and Dissertations

The novel ARMAS-SOM framework fuses collaborative all-source sensor information in a resilient manner with fault detection, exclusion, and integrity solutions recognizable to a GNSS user. This framework uses a multi-filter residual monitoring approach for fault detection and exclusion and is augmented with an additional "observability" EKF sub-layer for resilience. We monitor the a posteriori state covariances in this sub-layer to provide intrinsic awareness when navigation state observability assumptions required for integrity are in danger. This is used to selectively augment the framework with offboard information to preserve resilience. By maintaining split parallel collaborative and proprioceptive estimation instances and employing a …

New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams

Theses and Dissertations

A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …

Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban

Future Computing and Informatics Journal

The telecommunication sector has been developed rapidly and with large amounts of data obtained as a result of increasing in the number of subscribers, modern techniques, data-based applications, and services. As well as better awareness of customer requirements and excellent quality that meets their satisfaction. This satisfaction raises rivalry between firms to maintain the quality of their services and upgrade them. These data can be helpfully extracted for analysis and used for predicting churners. Researchers around the world have conducted important research to understand the uses of Data mining (DM) that can be used to predict customers' churn. This …

Efficiently Estimating Survival Signature And Two-Terminal Reliability Of Heterogeneous Networks Through Multi-Objective Optimization, Daniel Bruno Lopes Da Silva

Graduate Theses and Dissertations

The two-terminal reliability problem is a classical reliability problem with applications in wired and wireless communication networks, electronic circuit design, computer networks, and electrical power distribution, among other systems. However, the two-terminal reliability problem is among the hardest combinatorial problems and is intractable for large, complex networks. Several exact methods to solve the two-terminal reliability problem have been proposed since the 1960s, but they have exponential time complexity in general. Hence, practical studies involving large network-type systems resort to approximation methods to estimate the system's reliability. One attractive approach for quantifying the reliability of complex systems is to use signatures, …

Bibliometric Review Of Predictive Maintenance Using Vibration Analysis, Aashna Midha Ms., Ishita Maheshwari Ms., Kaushik Ojha Mr., Kritika Gupta Ms., Shripad V. Deshpande Mr.

Library Philosophy and Practice (e-journal)

Every day the world is depending more and more on machines in almost every aspect of life. With the increasing use of machines, there also needs to be an evolution in the maintenance of these machines. Predictive maintenance is a process used to monitor the equipment and machinery during its operation to detect any damages and/or deteriorations and enable the required maintenance plan in advance, resulting in reduced operational costs and full utilization of tools and parts. The fundamental goal of this bibliometric review paper is a comprehension of the extent and sources of the literature available for predictive maintenance …

Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan

Future Computing and Informatics Journal

In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …

In-Situ Process Monitoring For Metal Additive Manufacturing (Am) Through Acoustic Technique, Md Shahjahan Hossain

Electronic Theses and Dissertations

Additive Manufacturing (AM) is currently a widely used technology in different industries such as aerospace, medical, and consumer products. Previously it was mainly used for prototyping of the products, but now it is equally valuable for commercial product manufacturing. More profound understanding is still needed to track and identify defects during the AM process to ensure higher quality products with less material waste. Nondestructive testing becomes an essential form of testing for AM parts, where AE is one of the most used methods for in situ process monitoring. The Acoustic Emission (AE) approach has gained a reputation in nondestructive testing …

Quality Assurance Of Lightweight Structures Via Phase-Based Motion Estimation, Ikenna E. Ifekaonwu

Electronic Theses and Dissertations

In recent years, lightweight structures have become mature and adopted in various applications. The importance of quality assurance cannot be overemphasized hence extensive research has been conducted to assess the quality of lightweight structures. This study investigates a novel process that exploits motion magnification to investigate the damage characteristics of lightweight mission-critical parts. The goal is to assure the structural integrity of 3D printed structures and composite structures by determining the inherent defects present in the part by exploiting their vibration characteristics. The minuscule vibration of the structure was recorded with the aid of a high-speed digital camera, and the …

A Study Of Static And Dynamic Characteristics Of Multifunctional Signal Converters, Akmal Abdumalikov

Chemical Technology, Control and Management

The issues of continuity, accuracy, speed and reliability of signal conversion, which are the main problems of quality control and management of production processes, remain relevant. Research shows that in practice there are different signal variables, the study of which is highly formalized in a number of modeling tasks and basic classification studies, in particular transients in converters, its sources and elements requires a unified mathematical approach, that is, visual, highly formalized modeling and research based on it. The paper presents a graph model of multifunctional signal converters that provide microprocessor and electronic devices with signals in the form of …

Structural Health Monitoring Of Pipelines In Radioactive Environments Through Acoustic Sensing And Machine Learning, Michael Thompson

FIU Electronic Theses and Dissertations

Structural health monitoring (SHM) comprises multiple methodologies for the detection and characterization of stress, damage, and aberrations in engineering structures and equipment. Although, standard commercial engineering operations may freely adopt new technology into everyday operations, the nuclear industry is slowed down by tight governmental regulations and extremely harsh environments. This work aims to investigate and evaluate different sensor systems for real-time structural health monitoring of piping systems and develop a novel machine learning model to detect anomalies from the sensor data. The novelty of the current work lies in the development of an LSTM-autoencoder neural network to automate anomaly detection …

Heuristic Approaches For Near-Optimal Placement Of Gps-Based Multi-Static Radar Receivers In American Coastal Waters, Brandon J. Hufstetler

Theses and Dissertations

Narcotics smuggling across the Caribbean Sea is a growing concern for the United States Coast Guard. One vector for this illicit trafficking is via small aircraft. This thesis proposes a multi-static radar architecture using the Global Positioning System (GPS) constellation as a transmission source to detect these aircraft as they transit a detection fence. The system developed in this thesis relies on the forward-scatter phenomenon in which a radar shadow is cast by a target as it crosses in front of a transmitter, creating a measurable difference in the signal amplitude at the receiver. This thesis first develops a mathematical …

Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler

Master's Theses

Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems …

Collaborative Appearance-Based Place Recognition And Improving Place Recognition Using Detection Of Dynamic Objects, Juan Pablo Munoz

Dissertations, Theses, and Capstone Projects

This dissertation makes contributions to the problem of Long-Term Appearance-Based Place Recognition. We present a framework for place recognition in a collaborative scheme and a method to reduce the impact of dynamic objects on place representations. We demonstrate our findings using a state-of-the-art place recognition approach.

We begin in Part I by describing the general problem of place recognition and its importance in applications where accurate localization is crucial. We discuss feature detection and description and also explain the functioning of several place recognition frameworks.

In Part II, we present a novel framework for collaboration between agents from a pure …

An Exact Analysis For Four-Order Acousto-Optic Bragg Diffraction Which Incorporates Both Incident Light Angle And Sound Frequency Dependencies, Adeyinka Sunday Ademola

Electrical Engineering Theses

This thesis extends the prior work which produced an exact solution to the four-order acousto-optic (AO) Bragg cell with assumed fixed center frequency and with exact Bragg angle incident light. The extension predicts the model that incorporates the dependencies of both the input angle of light and the sound frequency. Specifically, a generalized 4^th order linear differential equation (DE), is developed from a simultaneous analysis of four coupled AO system of DEs. Through standard methods, the characteristic roots, which requires solving a quartic equation, is produced. Subsequently, a derived system of homogeneous solutions, which absorbs the roots obtained using …

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …

Experimental Investigation Of Reading Passive Uhf Tags In A Multi-Tag Environment, Yi Zhou

Theses and Dissertations--Mechanical Engineering

Recently, the Internet of things (IoT) has emerged as a promising solution for several industrial applications. One of the key components in IoT is passive radio frequency identification (RFID) tags which do not require a power source for operations. Specifically, ultra-high frequency (UHF) tags are studied in this paper. However, due to factors such as tag-to-tag interference and inaccurate localization, RFID tags that are closely spaced together are difficult to detect and program accurately with unique identifiers. This thesis investigates several factors that affect the ability to encode a specific tag with unique information in the presence of other tags, …

Energy Harvesting And Storage: The Catalyst To The Power Constraint For Leveraging Internet Of Things (Iot) On Trains, Kelechi Nwogu

Computer and Electronics Engineering: Dissertations, Theses, and Student Research

The success of Wireless Sensor Networks is heavily constrained by its reliance on storage technology like batteries, which are a finite resource. Whilst the number of transistors in an IC doubles every 18 months, the energy density of batteries is relatively flat during the same time period. This is a key challenge in leveraging the Internet of Things on trains.

The gravity of this problem is increased by an order of magnitude when the network is to be scaled up to hundreds or thousands of nodes. Comprehensive research and development efforts have been devoted to building ultra-low power sensors. These …

X-Band Dual Polarization Phased-Array Radar For Meteorological Applications, Krzysztof Orzel

Doctoral Dissertations

This dissertation details the development and operation of a novel dual-polarized Phase-Tilt Weather Radar (PTWR) designed for meteorological applications. The use of radar has a well-documented history in detection and classification of weather phenomena, but due to the limited mechanical scanning speed, its usage for severe weather observations remains far from ideal. The PTWR utilizes phased-array technology and provides unique capabilities such as smart scanning, fast scan update, and tracking. This technology is considered a candidate for a replacement and consolidation of the current US weather and surveillance radar networks. The dissertation can be divided into three parts. First, the …

Automated Image Interpretation For Science Autonomy In Robotic Planetary Exploration, Raymond Francis

Electronic Thesis and Dissertation Repository

Advances in the capabilities of robotic planetary exploration missions have increased the wealth of scientific data they produce, presenting challenges for mission science and operations imposed by the limits of interplanetary radio communications. These data budget pressures can be relieved by increased robotic autonomy, both for onboard operations tasks and for decision- making in response to science data.

This thesis presents new techniques in automated image interpretation for natural scenes of relevance to planetary science and exploration, and elaborates autonomy scenarios under which they could be used to extend the reach and performance of exploration missions on planetary surfaces.

Two …

Development And Experimental Analysis Of Wireless High Accuracy Ultra-Wideband Localization Systems For Indoor Medical Applications, Michael Joseph Kuhn

Doctoral Dissertations

This dissertation addresses several interesting and relevant problems in the field of wireless technologies applied to medical applications and specifically problems related to ultra-wideband high accuracy localization for use in the operating room. This research is cross disciplinary in nature and fundamentally builds upon microwave engineering, software engineering, systems engineering, and biomedical engineering. A good portion of this work has been published in peer reviewed microwave engineering and biomedical engineering conferences and journals. Wireless technologies in medicine are discussed with focus on ultra-wideband positioning in orthopedic surgical navigation. Characterization of the operating room as a medium for ultra-wideband signal transmission …

Implementation Of Dual-Polarization On An Airborne Scatterometer And Preliminary Data Quality, Jason Dvorsky

Masters Theses 1911 - February 2014

The Imaging Wind and RAin Profiler (IWRAP) is an airborne scatterometer system built and operated by University of Massachusetts Amherst's Microwave Remote Sensing Laboratory (MIRSL). The radar is seasonally deployed aboard one of the two National Oceanic and Atmospheric Administration (NOAA) WP-3D Orion ``Hurricane Hunter'' aircraft based out of MacDill AFB in Tampa, Florida. IWRAP is a dual-frequency, Ku- and C-band, scatterometer that uses two conically scanning antennas to estimate the ocean surface wind vectors as well as intervening rain profiles. Data that is gathered with IWRAP is used to improve current Geophysical Model Functions (GMF) or to help derive …

Robust Multichannel Functional-Data-Analysis Methods For Data Recovery In Complex Systems, Jian Sun

Doctoral Dissertations

In recent years, Condition Monitoring (CM), which can be performed via several sensor channels, has been recognized as an effective paradigm for failure prevention of operational equipment or processes. However, the complexity caused by asynchronous data collection with different and/or time-varying sampling/transmission rates has long been a hindrance in the effective use of multichannel data in constructing empirical models. The problem becomes more challenging when sensor readings are incomplete. Traditional sensor data recovery techniques are often prohibited in asynchronous CM environments, not to mention sparse datasets. The proposed Functional Principal Component Analysis (FPCA) methodologies, e.g., nonparametric FPC model and semi-parametric …

Development, Deployment, And Characterization Of A Ku-Band Interferometer, Anthony Swochak

Masters Theses 1911 - February 2014

Space-borne radar interferometry provides a global vantage point to understand climate change, global weather phenomenon, and other Earth dynamics. For climate change observations, space-borne interferometers can be utilized to relate ocean topography to temperature, thus providing a global map of ocean temperatures. Since the oceans are in constant motion, a single-pass interferometer is needed to successfully make these measurements of ocean height. The feasibility of a single-pass measurement is dependent on the physical size of the instrument, hence it is cheaper and more practical to launch a small, light weight instrument into space. Since instrument size scales inversely with operating …

Multi-Modular Integral Pressurized Water Reactor Control And Operational Reconfiguration For A Flow Control Loop, Sergio Ricardo Pereira Perillo

Doctoral Dissertations

This dissertation focused on the IRIS design since this will likely be one of the designs of choice for future deployment in the U.S and developing countries. With a net 335 MWe output IRIS novel design falls in the “medium” size category and it is a potential candidate for the so called modular reactors, which may be appropriate for base load electricity generation, especially in regions with smaller electricity grids, but especially well suited for more specialized non-electrical energy applications such as district heating and process steam for desalination. The first objective of this dissertation is to evaluate and quantify …