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Full-Text Articles in Engineering

Polyhedral Oligomeric Silsesquioxane-Phosphate Glass Matrix Nanocomposites With Additional Chapter On Phosphate Glass-Poly(Ethylene Terephthalate) Matrix Composites, Kyoungtae Kim Dec 2018

Polyhedral Oligomeric Silsesquioxane-Phosphate Glass Matrix Nanocomposites With Additional Chapter On Phosphate Glass-Poly(Ethylene Terephthalate) Matrix Composites, Kyoungtae Kim

Dissertations

Preparation and characterization of tin fluorophosphate glass (Pglass) matrix nanocomposites incorporating polyhedral oligomeric silsesquioxane (POSS) were investigated on the structural, thermal, morphological, mechanical, and rheological properties. Various processes including synthesis, extrusion and sintering processes were applied to prepare the nanocomposite samples. Another application of POSS with hydrophobic functional groups on the well-structured nanoscale silicate cage with three silanol groups was investigated to present the feasibility to use POSS molecule as a coating material on the surface of the hydrophilic inorganic glass. In addition, Poly(ethylene terephthalate) polymer matrix composites incorporating Pglass was studied to present the benefits of the Pglass ...


Analysing Online User Activity To Implicitly Infer The Mental Workload Of Web-Based Tasks Using Defeasible Reasoning, Paul Mara Sep 2018

Analysing Online User Activity To Implicitly Infer The Mental Workload Of Web-Based Tasks Using Defeasible Reasoning, Paul Mara

Dissertations

Mental workload can be considered the amount of cognitive load or effort used over time to complete a task in a complex system. Determining the limits of mental workload can assist in optimising designs and identify if user performance is affected by that design. Mental workload has also been presented as a defeasible concept, where one reason can defeat another and a 5-layer schema to represent domain knowledge to infer mental workload using defeasible reasoning has compared favourably to state-of-the-art inference techniques. Other previous work investigated using records of user activity for measuring mental workload at scale using web-based tasks ...


Screen Printed Moisture Sensor On Barrier Coated Sbs Board: The Characterizations Of The Hemicellulose-Based Biofilms And Their Applications For Smart Packaging, Ruoxi Ma Aug 2018

Screen Printed Moisture Sensor On Barrier Coated Sbs Board: The Characterizations Of The Hemicellulose-Based Biofilms And Their Applications For Smart Packaging, Ruoxi Ma

Dissertations

Fiber-based packaging materials have many advantages over their petroleum-based plastic competitors, such as sustainability, recyclability and stiffness/weight ratio. However, the poor barrier properties and sensitivity towards moisture are the main challenges for their extended use. Therefore, there has been a need to provide a biodegradable and biocompatible biopolymer packaging material with improved barrier properties for food and pharmaceutical packaging. Also, the moisture loss/gain problem causes a lot of waste every year. Therefore, there is a need of better tracking and sensing methods attached to the package in order to control the moisture level along the supply chain. To ...


A 3d Simulation Of Leukocyte Adhesion In Blood Flow, Tai-Hsien Wu Jun 2018

A 3d Simulation Of Leukocyte Adhesion In Blood Flow, Tai-Hsien Wu

Dissertations

It has been widely acknowledged that further understanding about the dynamics between blood cells and blood flow can help us gain more knowledge about the causes of diseases and discover more effective treatments. Examples of such dynamics include red blood cell (RBC, or erythrocyte) aggregation, white blood cell (WBC, or leukocyte) margination, and WBC extravasation. WBC extravasation is an important multiple-step process in the inflammatory response and therefore has drawn considerable attention over the past two decades. In this multiple-step process, a WBC undergoes at least four steps, including capture, rolling, firm adhesion, and transmigration, and each step is influenced ...


Decontamination Of The Passaic River Sediments Using Ultrasound With Ozone Nano-Bubbles, Janitha Hewa Batagoda May 2018

Decontamination Of The Passaic River Sediments Using Ultrasound With Ozone Nano-Bubbles, Janitha Hewa Batagoda

Dissertations

No abstract provided.


Combustion Of Nanocomposite Thermite Powders, Ian Monk May 2018

Combustion Of Nanocomposite Thermite Powders, Ian Monk

Dissertations

No abstract provided.


Prediction Of Forelimb Muscle Activities And Movement Phases Using Corticospinal Signals In The Rat, Sinan Gok May 2018

Prediction Of Forelimb Muscle Activities And Movement Phases Using Corticospinal Signals In The Rat, Sinan Gok

Dissertations

No abstract provided.


A Methodological Framework For Quantifying Impacts Of Truck Traffic On Regional Network With Implications To Transport Policy, Chaitanya Narendra Pathak May 2018

A Methodological Framework For Quantifying Impacts Of Truck Traffic On Regional Network With Implications To Transport Policy, Chaitanya Narendra Pathak

Dissertations

No abstract provided.


Development And Evaluation Of Cooperative Intersection Management Algorithm Under Connected Vehicles Environment, Slobodan Gutesa May 2018

Development And Evaluation Of Cooperative Intersection Management Algorithm Under Connected Vehicles Environment, Slobodan Gutesa

Dissertations

No abstract provided.


Borehole Communication Via Drill Strings In Oil Wells, Ali Hamdan Alenezi May 2018

Borehole Communication Via Drill Strings In Oil Wells, Ali Hamdan Alenezi

Dissertations

No abstract provided.


From Geographically Dispersed Data Centers Towards Hierarchical Edge Computing, Abbas Kiani May 2018

From Geographically Dispersed Data Centers Towards Hierarchical Edge Computing, Abbas Kiani

Dissertations

No abstract provided.


Assessing The Effectiveness Of Managed Lane Strategies For The Rapid Deployment Of Cooperative Adaptive Cruise Control Technology, Zijia Zhong May 2018

Assessing The Effectiveness Of Managed Lane Strategies For The Rapid Deployment Of Cooperative Adaptive Cruise Control Technology, Zijia Zhong

Dissertations

No abstract provided.


Silicon Based Uncooled Microbolometer, Asahel Banobre May 2018

Silicon Based Uncooled Microbolometer, Asahel Banobre

Dissertations

No abstract provided.


Secure Entity Authentication, Zuochao Dou May 2018

Secure Entity Authentication, Zuochao Dou

Dissertations

No abstract provided.


Online Edge Caching And Wireless Delivery In Fog-Aided Networks, Seyyed Mohammadreza Azimi May 2018

Online Edge Caching And Wireless Delivery In Fog-Aided Networks, Seyyed Mohammadreza Azimi

Dissertations

No abstract provided.


On Distributed Mobile Edge Computing, Xiang Sun May 2018

On Distributed Mobile Edge Computing, Xiang Sun

Dissertations

No abstract provided.


Design, Analysis And Optimization Of Visible Light Communications Based Indoor Access Systems For Mobile And Internet Of Things Applications, Sihua Shao May 2018

Design, Analysis And Optimization Of Visible Light Communications Based Indoor Access Systems For Mobile And Internet Of Things Applications, Sihua Shao

Dissertations

No abstract provided.


Polymer Nanocomposites Containing High Aspect Ratio Particulates: Innovation In Co-Extruded Multilayer Barrier Films, Kevin Meyers May 2018

Polymer Nanocomposites Containing High Aspect Ratio Particulates: Innovation In Co-Extruded Multilayer Barrier Films, Kevin Meyers

Dissertations

Delaminated montmorillonite (MMT) clay/ maleic anhydride grafted LLDPE nanocomposite multilayer films with alternating layers of LDPE were produced through multilayer co-extrusion. The MMT concentration within the nanocomposite layers was increased through annealing the films in the melt due to a mismatch in interdiffusion rates of the polymer layers. Analysis of the nanocomposite layers upon annealing revealed that the platelets impinged upon one another resulting in significant improvement in oxygen barrier in the multilayer system, exceeding the results of bulk nanocomposites.

Model analysis demonstrated that increasing the nanoplatelet aspect ratio or initial concentration in the filled layers would lead to even ...


Protocol For Energy Efficient Cluster Head Election For Collaborative Cluster Head Elections., David Otu Jan 2018

Protocol For Energy Efficient Cluster Head Election For Collaborative Cluster Head Elections., David Otu

Dissertations

In wireless sensor networks (WSNs) , energy is a major constrain.Energy efficient network protocols is required to maintain reliable sensing of the sensing field . WSNs that use LEACH protocol, have node in a cluster periodically take trials to become cluster - head,such that the nodes in the cluster becomes cluster - head evenly. Nodes with greater transmission distance to the base station in the cluster dies out faster because it performs more work in transmitting data when it is cluster-head. The distance-based algorithm presented in this project, ensures that work is allocated to the nodes in the cluster more evenly ,thus ...


Supervised Learning Models To Predict Stock Direction Within Different Sectors In A Bull And Bear Market, Tiffany Razy Jan 2018

Supervised Learning Models To Predict Stock Direction Within Different Sectors In A Bull And Bear Market, Tiffany Razy

Dissertations

Forecasting stock market price movement is a well researched and an alluring topic within the machine learning and financial realm. Supervised machine learning algorithms such as Random Forest (RF) and Support Vector Machines (SVM) have been used independently to gain insight on the market. With such volatility in the market the scope of this study will utilized the RF and SVM in a very volatility market to determine if these models will perform at a high level or outperform each other in both markets. This relative study is performed on 16 stocks in 4 different sectors over the bear market ...


Spoilage Detection In Raspberry Fruit Based On Spectral Imaging Using Convolutional Neural Networks, Karthik Kuchangi Jothi Prakash Jan 2018

Spoilage Detection In Raspberry Fruit Based On Spectral Imaging Using Convolutional Neural Networks, Karthik Kuchangi Jothi Prakash

Dissertations

Effective spoilage detection of perishable food items like fruits and vegetables is essential for retailers who stock and sell large quantities of these items. This research is aimed at developing a non-destructive, rapid and accurate method which is based on Spectral Imaging (SI) used in tandem with Convolutional Neural Network (CNN) to predict whether the fruit is fresh or rotten. The study also aims to determine the number of days before which the fruit rots. This research employs a primary, quantitative and inductive methods to investigate the Deep Learning based approach to detect fruit spoilage. Raspberry fruit in particular has ...


An Application Of Natural Language Processing For Triangulation Of Cognitive Load Assessments In Third Level Education, Luis Alfredo Contreras Jan 2018

An Application Of Natural Language Processing For Triangulation Of Cognitive Load Assessments In Third Level Education, Luis Alfredo Contreras

Dissertations

Work has been done to measure Mental Workload based on applications mainly related to ergonomics, human factors, and Machine Learning. The influence of Machine Learning is a reflection of an increased use of new technologies applied to areas conventionally dominated by theoretical approaches. However, collaboration between MWL and Natural Language Processing techniques seems to happen rarely. In this sense, the objective of this research is to make use of Natural Languages Processing techniques to contribute to the analysis of the relationship between Mental Workload subjective measures and Relative Frequency Ratios of keywords gathered during pre-tasks and post-tasks of MWL activities ...


Beef Cattle Instance Segmentation Using Mask R-Convolutional Neural Network, Mohammad Danish Jan 2018

Beef Cattle Instance Segmentation Using Mask R-Convolutional Neural Network, Mohammad Danish

Dissertations

Maintaining the cattle farm along with the wellbeing of every heifer has been the major concern in dairy farm. A robust system is required which can tackle the problem of continuous monitoring of cows. the computer vision techniques provide a new way to understand the challenges related to the identification and welfare of the cows. This paper presents a state-of-art instance segmentation mask RCNN algorithm to train and build a model on a very challenging cow dataset that is captured during the winter season. The dataset poses many challenges such as overlapping of cows, partial occlusion, similarity between cows and ...


From Business Understanding To Deployment: An Application Of Machine Learning Algorithms To Forecast Customer Visits Per Hour To A Fast-Casual Restaurant In Dublin, Odunayo David Adedeji Jan 2018

From Business Understanding To Deployment: An Application Of Machine Learning Algorithms To Forecast Customer Visits Per Hour To A Fast-Casual Restaurant In Dublin, Odunayo David Adedeji

Dissertations

This research project identifies the significant factors that affects the number of customer visits to a fast-casual restaurant every hour and proceeds to develop several machine learning models to forecast customer visits. The core value proposition of fast-casual restaurants is quality food delivered at speed which means they have to prepare meals in advance of customers visit but the problem with this approach is in forecasting future demand, under estimating demand could lead to inadequate meal preparation which would leave customers unsatisfied while over estimation of demand could lead to wastage especially with restaurants having to comply with food safety ...


A Comparison Of Real Time Stream Processing Frameworks, Jonathan Curtis Jan 2018

A Comparison Of Real Time Stream Processing Frameworks, Jonathan Curtis

Dissertations

The need to process the ever-expanding volumes of information being generated daily in the modern world is driving radical changes in traditional data analysis techniques. As a result of this, a number of open source tools for handling real-time data streams has become available in recent years. Four, in particular, have gained significant traction: Apache Flink, Apache Samza, Apache Spark and Apache Storm. Despite the rising popularity of these frameworks, however, there are few studies that analyse their performance in terms of important metrics, such as throughput and latency. This study aims to correct this, by running several benchmarks against ...


Can Machine Learning Beat Physics At Modeling Car Crashes?, Gavin Byrne Jan 2018

Can Machine Learning Beat Physics At Modeling Car Crashes?, Gavin Byrne

Dissertations

This study aimed to look at a traditional method used for measuring the severity and principle direction of force of a car crash and see if it could be improved on using machine learning models. The data used was publicly available from the NHTSA database and included descriptions of the vehicle, test and sensors as well as the accelerometer data over the period of the crashes. The models built were SVM classifiers and multinomial regression models. Although the SVM and Regression models were built successfully and gave higher levels of accuracy than the momentum models in terms of the severity ...


Application Of Synthetic Informative Minority Over-Sampling (Simo) Algorithm Leveraging Support Vector Machine (Svm) On Small Datasets With Class Imbalance, Akshatha Fakkeriah Kallappanamatt Jan 2018

Application Of Synthetic Informative Minority Over-Sampling (Simo) Algorithm Leveraging Support Vector Machine (Svm) On Small Datasets With Class Imbalance, Akshatha Fakkeriah Kallappanamatt

Dissertations

Developing predictive models for classification problems considering imbalanced datasets is one of the basic difficulties in data mining and decision-analytics. A classifier’s performance will decline dramatically when applied to an imbalanced dataset. Standard classifiers such as logistic regression, Support Vector Machine (SVM) are appropriate for balanced training sets whereas provides suboptimal classification results when used on unbalanced dataset. Performance metric with prediction accuracy encourages a bias towards the majority class, while the rare instances remain unknown though the model contributes a high overall precision. There are chances where minority instances might be treated as noise and vice versa. (Haixiang ...


Identifying Expert Investors On Financial Microblog Via Artificial Neural Networks, Pierluca Del Buono Jan 2018

Identifying Expert Investors On Financial Microblog Via Artificial Neural Networks, Pierluca Del Buono

Dissertations

In the recent years, thanks to social media platform, a plethora of information has been available to financial investors, that were traditionally dependent from financial institutions advisors. Strategies are now shared among web users, performances of stocks are commented in web communities and hints and suggestions are travelling on the internet with a fast pace, in a way that was unthinkable few years before. Several attempts have been made in the recent past, to predict Market movements and trends from activity of Financial Social Networks participants, and to evaluate if contributions from individuals with high level of expertise distinguish themselves ...


Comparing The Effectiveness Of Different Classification Techniques In Predicting Dns Tunnels, Patrick Walsh Jan 2018

Comparing The Effectiveness Of Different Classification Techniques In Predicting Dns Tunnels, Patrick Walsh

Dissertations

DNS is one of the most widely used protocols on the internet and is used in the translation of domain names into IP address in order to correctly route messages between computers. It presents an attractive attack vector for criminals as the service is not as closely monitored by security experts as other protocols such as HTTP or FTP. Its use as a covert means of communication has increased with the availability of tools that allow for the creation of DNS tunnels using the protocol. One of the primary motivations for using DNS tunnels is the illegal extraction of information ...


Electric-Field Assisted Manipulation And Self-Assembly Of Particle Suspensions, Edison Chijioke Amah Jan 2018

Electric-Field Assisted Manipulation And Self-Assembly Of Particle Suspensions, Edison Chijioke Amah

Dissertations

No abstract provided.