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Full-Text Articles in Physical Sciences and Mathematics

Enhancing Urban Life: A Policy-Based Autonomic Smart City Management System For Efficient, Sustainable, And Self-Adaptive Urban Environments, Elham Okhovat Dec 2023

Enhancing Urban Life: A Policy-Based Autonomic Smart City Management System For Efficient, Sustainable, And Self-Adaptive Urban Environments, Elham Okhovat

Electronic Thesis and Dissertation Repository

This thesis proposes the concept of the Policy-based Autonomic Smart City Management System, an innovative framework designed to comprehensively manage diverse aspects of urban environments, ranging from environmental conditions such as temperature and air quality to the infrastructure which comprises multiple layers of infrastructure, from sensors and devices to advanced IoT platforms and applications. Efficient management requires continuous monitoring of devices and infrastructure, data analysis, and real-time resource assessment to ensure seamless city operations and improve residents' quality of life. Automating data monitoring is essential due to the vast array of hardware and data exchanges, and round-the-clock monitoring is critical. …


Framework For Assessing Information System Security Posture Risks, Syed Waqas Hamdani Jun 2023

Framework For Assessing Information System Security Posture Risks, Syed Waqas Hamdani

Electronic Thesis and Dissertation Repository

In today’s data-driven world, Information Systems, particularly the ones operating in regulated industries, require comprehensive security frameworks to protect against loss of confidentiality, integrity, or availability of data, whether due to malice, accident or otherwise. Once such a security framework is in place, an organization must constantly monitor and assess the overall compliance of its systems to detect and rectify any issues found. This thesis presents a technique and a supporting toolkit to first model dependencies between security policies (referred to as controls) and, second, devise models that associate risk with policy violations. Third, devise algorithms that propagate risk when …


Evaluating The Likelihood Of Bug Inducing Commits Using Metrics Trend Analysis, Parul Parul Jun 2023

Evaluating The Likelihood Of Bug Inducing Commits Using Metrics Trend Analysis, Parul Parul

Electronic Thesis and Dissertation Repository

Continuous software engineering principles advocate a release-small, release-often process model, where new functionality is added to a system, in small increments and very frequently. In such a process model, every time a change is introduced it is important to identify as early as possible, whether the system has entered a state where faults are more likely to occur. In this paper, we present a method that is based on process, quality, and source code metrics to evaluate the likelihood that an imminent bug-inducing commit is highly probable. More specifically, the method analyzes the correlations and the rate of change of …


Ai Applications On Planetary Rovers, Alexis David Pascual Mar 2023

Ai Applications On Planetary Rovers, Alexis David Pascual

Electronic Thesis and Dissertation Repository

The rise in the number of robotic missions to space is paving the way for the use of artificial intelligence and machine learning in the autonomy and augmentation of rover operations. For one, more rovers mean more images, and more images mean more data bandwidth required for downlinking as well as more mental bandwidth for analyzing the images. On the other hand, light-weight, low-powered microrover platforms are being developed to accommodate the drive for planetary exploration. As a result of the mass and power constraints, these microrover platforms will not carry typical navigational instruments like a stereocamera or a laser …


Extracting Microservice Dependencies Using Log Analysis, Andres O. Rodriguez Ishida Sep 2022

Extracting Microservice Dependencies Using Log Analysis, Andres O. Rodriguez Ishida

Electronic Thesis and Dissertation Repository

Microservice architecture is an architectural style that supports the design and implementation of very scalable systems by distributing complex functionality to highly granular components. These highly granular components are referred to as microservices and can be dynamically deployed on Docker containers. These microservice architecture systems are very extensible since new microservices can be added or replaced as the system evolves. In such highly granular architectures, a major challenge that arises is how to quickly identify whether any changes in the system’s structure violate any policies or design constraints. Examples of policies and design constraints include whether a microservice can call …


Towards A Novel And Intelligent E-Commerce Framework For Smart-Shopping Applications, Susmitha Hanumanthu Aug 2022

Towards A Novel And Intelligent E-Commerce Framework For Smart-Shopping Applications, Susmitha Hanumanthu

Electronic Thesis and Dissertation Repository

Nowadays, with the advancement of market digitalization accompanied by internet technologies, consumers can buy products from anywhere in the world. Finding the best-offered deal from numerous e-commerce sites and online stores is overwhelming, time-consuming, and often not very effective. Customers need to visit many online stores to find their desired product at the desired price. Also, the option of finding a product in the future time that is not currently available is limited in the current e-commerce platform. To address these limitations, there is a need to develop a new one-stop e-shopping model that would allow customers to search for …


The Design And Implementation Of A High-Performance Polynomial System Solver, Alexander Brandt Aug 2022

The Design And Implementation Of A High-Performance Polynomial System Solver, Alexander Brandt

Electronic Thesis and Dissertation Repository

This thesis examines the algorithmic and practical challenges of solving systems of polynomial equations. We discuss the design and implementation of triangular decomposition to solve polynomials systems exactly by means of symbolic computation.

Incremental triangular decomposition solves one equation from the input list of polynomials at a time. Each step may produce several different components (points, curves, surfaces, etc.) of the solution set. Independent components imply that the solving process may proceed on each component concurrently. This so-called component-level parallelism is a theoretical and practical challenge characterized by irregular parallelism. Parallelism is not an algorithmic property but rather a geometrical …


Reputation-Based Trust Assessment Of Transacting Service Components, Konstantinos Tsiounis Jul 2022

Reputation-Based Trust Assessment Of Transacting Service Components, Konstantinos Tsiounis

Electronic Thesis and Dissertation Repository

As Service-Oriented Systems rely for their operation on many different, and most often, distributed software components, a key issue that emerges is how one component can trust the services offered by another component. Here, the concept of trust is considered in the context of reputation systems and is viewed as a meta-requirement, that is, the level of belief a service requestor has that a service provider will provide the service in a way that meets the requestor’s expectations. We refer to the service offering components as service providers (SPs) and the service requesting components as service clients (SCs).

In this …


Machine Learning With Big Data For Electrical Load Forecasting, Alexandra L'Heureux Jun 2022

Machine Learning With Big Data For Electrical Load Forecasting, Alexandra L'Heureux

Electronic Thesis and Dissertation Repository

Today, the amount of data collected is exploding at an unprecedented rate due to developments in Web technologies, social media, mobile and sensing devices and the internet of things (IoT). Data is gathered in every aspect of our lives: from financial information to smart home devices and everything in between. The driving force behind these extensive data collections is the promise of increased knowledge. Therefore, the potential of Big Data relies on our ability to extract value from these massive data sets. Machine learning is central to this quest because of its ability to learn from data and provide data-driven …


Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri Apr 2022

Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri

Electronic Thesis and Dissertation Repository

Electricity load forecasting has been attracting increasing attention because of its importance for energy management, infrastructure planning, and budgeting. In recent years, the proliferation of smart meters has created new opportunities for forecasting on the building and even individual household levels. Machine learning (ML) has achieved great successes in this domain; however, conventional ML techniques require data transfer to a centralized location for model training, therefore, increasing network traffic and exposing data to privacy and security risks. Also, traditional approaches employ offline learning, which means that they are only trained once and miss out on the possibility to learn from …


Multi-Device Data Analysis For Fault Localization In Electrical Distribution Grids, Jacob D L Hunte Apr 2022

Multi-Device Data Analysis For Fault Localization In Electrical Distribution Grids, Jacob D L Hunte

Electronic Thesis and Dissertation Repository

The work presented in this dissertation represents work which addresses some of the main challenges of fault localization methods in electrical distribution grids. The methods developed largely assume access to sophisticated data sources that may not be available and that any data sets recorded by devices are synchronized. These issues have created a barrier to the adoption of many solutions by industry. The goal of the research presented in this dissertation is to address these challenges through the development of three elements. These elements are a synchronization protocol, a fault localization technique, and a sensor placement algorithm.

The synchronization protocol …


Cache-Friendly, Modular And Parallel Schemes For Computing Subresultant Chains, Mohammadali Asadi Oct 2021

Cache-Friendly, Modular And Parallel Schemes For Computing Subresultant Chains, Mohammadali Asadi

Electronic Thesis and Dissertation Repository

The RegularChains library in Maple offers a collection of commands for solving polynomial systems symbolically with taking advantage of the theory of regular chains. The primary goal of this thesis is algorithmic contributions, in particular, to high-performance computational schemes for subresultant chains and underlying routines to extend that of RegularChains in a C/C++ open-source library.

Subresultants are one of the most fundamental tools in computer algebra. They are at the core of numerous algorithms including, but not limited to, polynomial GCD computations, polynomial system solving, and symbolic integration. When the subresultant chain of two polynomials is involved in a client …


Westernaccelerator:Rapid Development Of Microservices, Haoran Wei Aug 2021

Westernaccelerator:Rapid Development Of Microservices, Haoran Wei

Electronic Thesis and Dissertation Repository

Context & Motivation/problem: In the context that cloud platforms are widely adopted, Microservice Architecture (MSA) has quickly become the new paradigm for modern software development due to its great modularity, scalability, and resiliency, which fits well in the cloud environment. However, to embrace the benefits of MSA, organizations must overcome the challenges of adopting new methodologies and processes to deal with the extra development complexities that microservices created, e.g., establishing interface-based communication between distributed services and managing the configurations and locations of services. Consequently, creating a microservice-based application is relatively complex and effortful. Research Question: How to create a tool …


Fuzzy And Probabilistic Rule-Based Approaches To Identify Fault Prone Files, Piyush Kumar Korlepara Jul 2021

Fuzzy And Probabilistic Rule-Based Approaches To Identify Fault Prone Files, Piyush Kumar Korlepara

Electronic Thesis and Dissertation Repository

Most software fault proneness prediction techniques utilize machine learning models which act as black boxes when performing predictions. Software developers cannot obtain any insights as to why such trained models reached their conclusions when applied to new data. This leads to a reduced confidence in accepting the prediction results while applying the model in complex systems. In this thesis, we propose two rule-based and programming language-agnostic fault proneness prediction techniques. The first technique utilizes fuzzy reasoning, while the second utilizes Markov Logic Networks. The rules operate on facts that are produced by harvesting and postprocessing raw data extracted from the …


Calibration Between Eye Tracker And Stereoscopic Vision System Employing A Linear Closed-Form Perspective-N-Point (Pnp) Algorithm, Mohammad Karami Apr 2021

Calibration Between Eye Tracker And Stereoscopic Vision System Employing A Linear Closed-Form Perspective-N-Point (Pnp) Algorithm, Mohammad Karami

Electronic Thesis and Dissertation Repository

In many advanced driver assistance systems (ADAS) applications, it is essential to figure out where gaze of driver locates in image area of stereoscopic vision system. This problem, which involves a cross calibration between the stereo vision system and eye tracker, is a challenging task since the two systems are not consistent in modality and do not share a common image area. The eye tracker system provides a 3D gaze vector which describes the direction of driver’s 3D line of gaze, while the stereoscopic vision system provides a depth image frame. In this thesis, this crosscalibration was performed with a …


Automatically Classifying Non-Functional Requirements With Feature Extraction And Supervised Machine Learning Techniques, Mahtab Ezzatikarami Dec 2020

Automatically Classifying Non-Functional Requirements With Feature Extraction And Supervised Machine Learning Techniques, Mahtab Ezzatikarami

Electronic Thesis and Dissertation Repository

Abstract. Context and Motivation: Non-functional requirements (NFRs) of a system need to be classified into different types such as usability, performance, etc. This would enable stakeholders to ensure the completeness of their work by extracting specific NFRs related to their expertise. Question/Problem: Because of the size and complexity of requirement specification documents, the manual classification of NFRs is time-consuming, labour-intensive, and error-prone. We thus need an automated solution that can provide a highly accurate and efficient categorization of NFRs. Principal ideas/results: In this investigation, using natural language processing and supervised machine learning (SML) techniques, we investigate with feature extraction techniques …


Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat Jul 2020

Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat

Electronic Thesis and Dissertation Repository

The rapid growth of the Internet and related technologies has led to the collection of large amounts of data by individuals, organizations, and society in general [1]. However, this often leads to information overload which occurs when the amount of input (e.g. data) a human is trying to process exceeds their cognitive capacities [2]. Machine learning (ML) has been proposed as one potential methodology capable of extracting useful information from large sets of data [1]. This thesis focuses on two applications. The first is education, namely e-Learning environments. Within this field, this thesis proposes different optimized ML ensemble models to …


Automated Anomaly Detection And Localization System For A Microservices Based Cloud System, Priyanka Prakash Naikade Jul 2020

Automated Anomaly Detection And Localization System For A Microservices Based Cloud System, Priyanka Prakash Naikade

Electronic Thesis and Dissertation Repository

Context: With an increasing number of applications running on a microservices-based cloud system (such as AWS, GCP, IBM Cloud), it is challenging for the cloud providers to offer uninterrupted services with guaranteed Quality of Service (QoS) factors. Problem Statement: Existing monitoring frameworks often do not detect critical defects among a large volume of issues generated, thus affecting recovery response times and usage of maintenance human resource. Also, manually tracing the root causes of the issues requires a significant amount of time. Objective: The objective of this work is to: (i) detect performance anomalies, in real-time, through monitoring KPIs (Key Performance …


Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh May 2020

Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh

Electronic Thesis and Dissertation Repository

Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …


Identifying External Cross-References Using Natural Language Processing (Nlp), Elham Rahmani Apr 2020

Identifying External Cross-References Using Natural Language Processing (Nlp), Elham Rahmani

Electronic Thesis and Dissertation Repository

[Context and motivation] Software engineers build systems that need to be compliant with relevant regulations. These regulations are stated in authoritative documents from which regulatory requirements need to be elicited. Project contract contains cross-references to these regulatory requirements in external documents. [Problem] Exploring and identifying the regulatory requirements in voluminous textual data is enormously time consuming, and hence costly, and error-prone in sizable software projects. [Principal idea and novelty] We use Natural Language Processing (NLP), Pattern Recognition and Web Scrapping techniques for automatically extracting external cross-references from contractual requirements and prepare a map for representing related external cross-references …


A Requirements Measurement Program For Systems Engineering Projects: Metrics, Indicators, Models, And Tools For Internal Stakeholders, Ibtehal Noorwali Apr 2020

A Requirements Measurement Program For Systems Engineering Projects: Metrics, Indicators, Models, And Tools For Internal Stakeholders, Ibtehal Noorwali

Electronic Thesis and Dissertation Repository

Software engineering (SE) measurement has shown to lead to improved quality and productivity in software and systems projects and, thus, has received significant attention in the literature, particularly for the design and development stages. In requirements engineering (RE), research and practice has recognized the importance of requirements measurement (RM) for tracking progress, identifying gaps in downstream deliverables related to requirements, managing requirements-related risks, reducing requirements errors and defects, and project management and decision making.

However, despite the recognized benefits of RM, research indicates that only 5\% of the literature on SE measurement addresses requirements. This small percentage is reflected in …


A Visual Analytics System For Making Sense Of Real-Time Twitter Streams, Amir Haghighatimaleki Jan 2020

A Visual Analytics System For Making Sense Of Real-Time Twitter Streams, Amir Haghighatimaleki

Electronic Thesis and Dissertation Repository

Through social media platforms, massive amounts of data are being produced. Twitter, as one such platform, enables users to post “tweets” on an unprecedented scale. Once analyzed by machine learning (ML) techniques and in aggregate, Twitter data can be an invaluable resource for gaining insight. However, when applied to real-time data streams, due to covariate shifts in the data (i.e., changes in the distributions of the inputs of ML algorithms), existing ML approaches result in different types of biases and provide uncertain outputs. This thesis describes a visual analytics system (i.e., a tool that combines data visualization, human-data interaction, and …


A Programming Model For Internetworked Things, Hao Jiang Sep 2019

A Programming Model For Internetworked Things, Hao Jiang

Electronic Thesis and Dissertation Repository

The Internet of Things (IoT) emerges as a system paradigm that encompasses a wide spectrum of technologies and protocols related to Internetworking, services computing, and device connectivity. The main objective is to achieve an environment whereby physical devices and everyday objects can communicate and interact with each other over the Internet. The Internet of Things is heralded as the next generation Internet, and introduces significant opportunities for novel applications in many different domains. What is missing right now is a programming model whereby developers as well as end-users can specify any addressable resource at a higher level of abstraction, and …


Spatiotemporal Forecasting At Scale, Rafael Felipe Nascimento De Aguiar Aug 2019

Spatiotemporal Forecasting At Scale, Rafael Felipe Nascimento De Aguiar

Electronic Thesis and Dissertation Repository

Spatiotemporal forecasting can be described as predicting the future value of a variable given when and where it will happen. This type of forecasting task has the potential to aid many institutions and businesses in asking questions, such as how many people will visit a given hospital in the next hour. Answers to these questions have the potential to spur significant socioeconomic impact, providing privacy-friendly short-term forecasts about geolocated events, which in turn can help entities to plan and operate more efficiently. These seemingly simple questions, however, present complex challenges to forecasting systems. With more GPS-enabled devices connected every year, …


Haptics-Enabled, Gpu Augmented Surgical Simulation Platform For Glenoid Reaming, Vlad Popa Apr 2019

Haptics-Enabled, Gpu Augmented Surgical Simulation Platform For Glenoid Reaming, Vlad Popa

Electronic Thesis and Dissertation Repository

Surgical simulators are technological platforms that provide virtual substitutes to the current cadaver-based medical training models. The advantages of exposure to these devices have been thoroughly studied, with enhanced surgical proficiency being one of the assets gained after extensive use. While simulators have already penetrated numerous medical domains, the field of orthopedics remains stagnant despite a demand for the ability to practice uncommon surgeries, such as total shoulder arthroplasty (TSA). Here we extrapolate the algorithms of an inhouse software engine revolving around glenoid reaming, a critical step of TSA. The project’s purpose is to provide efficient techniques for future simulators, …


Predicting Software Fault Proneness Using Machine Learning, Sanjay Ghanathey Dec 2018

Predicting Software Fault Proneness Using Machine Learning, Sanjay Ghanathey

Electronic Thesis and Dissertation Repository

Context: Continuous Integration (CI) is a DevOps technique which is widely used in practice. Studies show that its adoption rates will increase even further. At the same time, it is argued that maintaining product quality requires extensive and time consuming, testing and code reviews. In this context, if not done properly, shorter sprint cycles and agile practices entail higher risk for the quality of the product. It has been reported in literature [68], that lack of proper test strategies, poor test quality and team dependencies are some of the major challenges encountered in continuous integration and deployment.

Objective: The objective …


Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali Dec 2018

Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali

Electronic Thesis and Dissertation Repository

The main concept behind business intelligence (BI) is how to use integrated data across different business systems within an enterprise to make strategic decisions. It is difficult to map internal and external BI’s users to subsets of the enterprise’s data warehouse (DW), resulting that protecting the privacy of this data while maintaining its utility is a challenging task. Today, such DW systems constitute one of the most serious privacy breach threats that an enterprise might face when many internal users of different security levels have access to BI components. This thesis proposes a data masking framework (iMaskU: Identify, Map, Apply, …


A Framework For Modelling User Activity Preferences, Roberto Barboza Junior Apr 2018

A Framework For Modelling User Activity Preferences, Roberto Barboza Junior

Electronic Thesis and Dissertation Repository

The availability of location data increases every day and brings the opportunity to mine these data and extract valuable knowledge about human behaviour. More specifically, these data may contain information about users’ activities, which can enable, for example, services to improve advertising campaigns or enhance the user experience of a mobile application. However, several techniques ignore the fact that users’ context other than location and time, such as weather conditions, influences their behaviour. Moreover, several studies focus only on a single data source, addressing either data collected without any type of user interaction, such as GPS data, or data spontaneously …


Rendering Real-Time Dashboards Using A Graphql-Based Ui Architecture, Naresh Eeda Dec 2017

Rendering Real-Time Dashboards Using A Graphql-Based Ui Architecture, Naresh Eeda

Electronic Thesis and Dissertation Repository

With the increase in the complexity of the systems being built and demand in the quality of service by the customers, developing and providing highly efficient real-time systems is one of the biggest challenges today for software enterprises. BluemixTM ─ IBM’s cloud offering implemented on Cloud Foundry, an open source “Platform as a Service” (PaaS), is an example of such a system. Currently, there are approx. 26 infrastructural services running in the background from where the data is fetched and is rendered on different dashboards of the system. However, the system suffers from performance issues.

This thesis explores the …


Secure Integer Comparisons Using The Homomorphic Properties Of Prime Power Subgroups, Rhys A. Carlton Aug 2017

Secure Integer Comparisons Using The Homomorphic Properties Of Prime Power Subgroups, Rhys A. Carlton

Electronic Thesis and Dissertation Repository

Secure multi party computation allows two or more parties to jointly compute a function under encryption without leaking information about their private inputs. These secure computations are vital in many fields including law enforcement, secure voting and bioinformatics because the privacy of the information is of paramount importance.

One common reference problem for secure multi party computation is the Millionaires' problem which was first introduced by Turing Award winner Yao in his paper "Protocols for secure computation". The Millionaires' problem considers two millionaires who want to know who is richer without disclosing their actual worth.

There are public-key cryptosystems that …