Computer Engineering Commons^™

Nsu Student Handbook 2019-2020, Nova Southeastern University

College of Engineering and Computing Course Catalogs

No abstract provided.

College Of Computing And Engineering Graduate Catalog 2019-2020, Nova Southeastern University

College of Engineering and Computing Course Catalogs

No abstract provided.

Development Of Enhanced Weed Detection System With Adaptive Thresholding, K-Means And Support Vector Machine, Dheeman Saha

Electronic Theses and Dissertations

This paper proposes a sophisticated classification process to segment the leaves of carrots from weeds (mostly Chamomile). In the early stages, of the plants’ development, both weeds and carrot leaves are intermixed with each other and have similar color texture. This makes it difficult to identify without the help of the domain experts. Therefore, it is essential to remove the weed regions so that the carrot plants can grow without any interruptions. The process of identifying the weeds become more challenging when both plant and weed regions overlap (inter-leaves). The proposed system addresses this problem by creating a sophisticated means …

Examination Of Adoption Theory On The Devops Practice Of Continuous Delivery, Andrew John Anderson

Walden Dissertations and Doctoral Studies

Many organizations have difficulty adopting advanced software development practices. Some software development project managers in large organizations are not aligned with the relationship between performance expectancy, effort expectancy, social influence, and facilitating conditions, as moderated by experience, with intent to adopt the DevOps practice of continuous delivery. The purpose of this study was to examine the statistical relationships between the independent variables—performance expectancy, effort expectancy, social influence, and facilitating conditions, as moderated by experience—and the dependent variable of behavioral intent to adopt a continuous delivery system. Venkatesh, Morris, Davis, and Davis's unified theory of acceptance and use of technology provided …

Sdn Testbed For Evaluation Of Large Exo-Atmospheric Emp Attacks, Diogo Oliveira, Nasir Ghani, Majeed M. Hayat, Jorge Crichigno, Elias Bou-Harb

Electrical and Computer Engineering Faculty Research and Publications

Large-scale nuclear electromagnetic pulse (EMP) attacks and natural disasters can cause extensive network failures across wide geographic regions. Although operational networks are designed to handle most single or dual faults, recent efforts have also focused on more capable multi-failure disaster recovery schemes. Concurrently, advances in software-defined networking (SDN) technologies have delivered highly-adaptable frameworks for implementing new and improved service provisioning and recovery paradigms in real-world settings. Hence this study leverages these new innovations to develop a robust disaster recovery (counter-EMP) framework for large backbone networks. Detailed findings from an experimental testbed study are also presented.

Microscale Direct Measurement Of Localized Photothermal Heating In Tissue-Mimetic Hydrogels, Benyamin Davaji, James E. Richie, Chung-Hoon Lee

Electrical and Computer Engineering Faculty Research and Publications

Photothermal hyperthermia is proven to be an effective diagnostic tool for cancer therapy. The efficacy of this method directly relies on understanding the localization of the photothermal effect in the targeted region. Realizing the safe and effective concentration of nano-particles and the irradiation intensity and time requires spatiotemporal temperature monitoring during and after laser irradiation. Due to uniformities of the nanoparticle distribution and the complexities of the microenvironment, a direct temperature measurement in micro-scale is crucial for achieving precise thermal dose control. In this study, a 50 nm thin film nickel resistive temperature sensor was fabricated on a 300 nm …

Predicting Cascading Failures In Power Grids Using Machine Learning Algorithms, Rezoan Ahmed Shuvro, Pankaz Das, Majeed M. Hayat, Mitun Talukder

Electrical and Computer Engineering Faculty Research and Publications

Although there has been notable progress in modeling cascading failures in power grids, few works included using machine learning algorithms. In this paper, cascading failures that lead to massive blackouts in power grids are predicted and classified into no, small, and large cascades using machine learning algorithms. Cascading-failure data is generated using a cascading failure simulator framework developed earlier. The data set includes the power grid operating parameters such as loading level, level of load shedding, the capacity of the failed lines, and the topological parameters such as edge betweenness centrality and the average shortest distance for numerous combinations of …

An Empirical Analysis Of An Algorithm For The Budgeted Maximum Vertex Cover Problem In Trees, Mujidat Abisola Adeyemo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Covering problems are commonly studied in fields such as mathematics, computer science, and engineering. They are also applicable in the real world, e.g., given a city, can we build base-stations such that there is network availability everywhere in the city. However, in the real world, there are usually constraints such as cost and resources. The Budgeted Maximum Vertex Cover is a generalization of covering problems. It models situations with constraints. In this thesis, we empirically analyze an algorithm for the problem of finding the Budgeted Maximum Vertex Cover in undirected trees (BMVCT). The BMVCT problem is defined as follows: Given …

Investigation And Development Of Exhaust Flow Rate Estimation Methodologies For Heavy-Duty Vehicles, Chakradhar Reddy Vardhireddy

Graduate Theses, Dissertations, and Problem Reports (ETD)

Exhaust gas flow rate from a vehicle tailpipe has a great influence on emission mass rate calculations, as the emission fractions of individual gases in the exhaust are calculated by using the measured exhaust flow rate. The development of high-end sensor technologies and emission pollutant measurement instruments, which can give instantaneous values of volume concentration of pollutants flowing out of the engine are gaining importance because of their ease of operation. The volume concentrations measured can then be used with the instantaneous exhaust flow rate values to obtain mass flow rates of pollutants.

With the recent promulgation of real world …

Car Image Classification Using Deep Neural Networks, Mingchen Li

Honors Theses

Image classification is widely used in many fields of study. Deep neural networks are proven to be effective classifier structure due to its massive parameters and training capability. This paper outlines the development of Deep Neural Network in recent years and applied them on a Car image data set in order to compare their performances.

Integrating Multi-Source Weather Data For Deep Learning, Haidar A. Alanbari Mr

Dissertations and Theses

Big Data has been playing a major role in the domain of Deep Learning applications as many companies and institutions continue to find solutions and extract certain trends in fields of climate change, weather forecasting and meteorology. This project extracts weather events data from multiple data sources that are supported by National Centers for Environmental information (NCEI) [1] and Amazon Web Services (AWS) [2]. Data sources include Next-Generation NEXRAD [3] Doppler radar reflectivity, GOES-16 [4] multi-channel satellite imagery and NCEI [1] storm events. Then, it integrates and refines data in proper formats to be fed to the open-source Detectron [5] …

Programming Of Collaborative Robot (Cobot) To Selectively Disassemble Products To Obtain Critical Materials, Brittany Felder

Research Opportunities for Engineering Undergraduates (ROEU) Program 2018-19

End-of-life products that contain critical materials, such as rare earth magnets, are often discarded even though there is remaining value that can be fed back into a remanufacturing process. This research aims to develop high throughput and economic value recovery from electric machines using collaborative robotics.

Scalable Clustering For Immune Repertoire Sequence Analysis, Prem Bhusal

Browse all Theses and Dissertations

The development of the next-generation sequencing technology has enabled systems immunology researchers to conduct detailed immune repertoire analysis at the molecule level. Large sequence datasets (e.g., millions of sequences) are being collected to comprehensively understand how the immune system of a patient evolves over different stages of disease development. A recent study has shown that the hierarchical clustering (HC) algorithm gives the best results for B-cell clones analysis - an important type of immune repertoire sequencing (IR-Seq) analysis. However, due to the inherent complexity, the classical hierarchical clustering algorithm does not scale well to large sequence datasets. Surprisingly, no algorithms …

Controlled Switching In Kalman Filtering And Iterative Learning Controls, He Li

Masters Theses

“Switching is not an uncommon phenomenon in practical systems and processes, for examples, power switches opening and closing, transmissions lifting from low gear to high gear, and air planes crossing different layers in air. Switching can be a disaster to a system since frequent switching between two asymptotically stable subsystems may result in unstable dynamics. On the contrary, switching can be a benefit to a system since controlled switching is sometimes imposed by the designers to achieve desired performance. This encourages the study of system dynamics and performance when undesired switching occurs or controlled switching is imposed. In this research, …

Routing Algorithm For The Ground Team In Transmission Line Inspection Using Unmanned Aerial Vehicle, Yu Li

Masters Theses

"With the rapid development of robotics technology, robots are increasingly used to conduct various tasks by utility companies. An unmanned aerial vehicle (UAV) is an efficient robot that can be used to inspect high-voltage transmission lines. UAVs need to stay within a data transmission range from the ground station and periodically land to replace the battery in order to ensure that the power system can support its operation. A routing algorithm must be used in order to guide the motion and deployment of the ground station while using UAV in transmission line inspection. Most existing routing algorithms are dedicated to …

Less Is More: Beating The Market With Recurrent Reinforcement Learning, Louis Kurt Bernhard Steinmeister

Masters Theses

"Multiple recurrent reinforcement learners were implemented to make trading decisions based on real and freely available macro-economic data. The learning algorithm and different reinforcement functions (the Differential Sharpe Ratio, Differential Downside Deviation Ratio and Returns) were revised and the performances were compared while transaction costs were taken into account. (This is important for practical implementations even though many publications ignore this consideration.) It was assumed that the traders make long-short decisions in the S&P500 with complementary 3-month treasury bill investments. Leveraged positions in the S&P500 were disallowed. Notably, the Differential Sharpe Ratio and the Differential Downside Deviation Ratio are risk …

การแปลงกระแสงานยอร์ลที่มีเงื่อนไขเวลาไปเป็นสโตแคสติกเพทริเน็ตส์ทั่วไป, สุพัตรา บุญญะวัตร

Chulalongkorn University Theses and Dissertations (Chula ETD)

ในปัจจุบันโลกทางธุรกิจมีการแข่งขันกันอยู่ตลอดเวลา ผู้ประกอบการทางธุรกิจจึงจำเป็นต้องมีการวางแผนและการบริหารจัดการเวลา ทรัพยากร รวมไปถึงค่าใช้จ่ายต่าง ๆ ให้เป็นไปตามแผนที่วางไว้ ในปัจจุบันมีเครื่องมือที่ช่วยในการจำลองกระบวนการทางธุรกิจ เช่น แผนภาพบีพีเอ็มเอ็น บีเพล และกระแสงานยอว์ล เป็นต้น แต่เครื่องมือดังกล่าวยังไม่สามารถระบุเวลาเฉลี่ยของแต่ละงานในการพัฒนาระบบได้ งานวิทยานิพนธ์นี้ได้เสนอการแปลงกระแสงานยอว์ลไปเป็นสโตแคสติกเพทริเน็ตแบบทั่วไป ซึ่งในงานวิทยานิพนธ์นี้เลือกใช้กระแสงานยอว์ลมาใช้ในการสร้างแบบจำลองกระบวนการทางธุรกิจเพราะกระแสงานยอว์ลมีเครื่องมือ YAWL Editor ที่มีฟีเจอร์ในการตรวจสอบคุณสมบัติของแบบจำลองที่สร้างขึ้น เช่น ตรวจสอบสภาวะติดตายของระบบ เป็นต้น ถึงแม้ว่ากระแสงานยอว์ลจะมีฟีเจอร์ที่ดีดังที่ได้กล่าวไว้ข้างต้น แต่กระแสงานยอว์ลไม่สามารถวิเคราะห์ข้อจำกัดด้านเวลาได้ ดังนั้นในงานวิทยานิพนธ์นี้จึงได้เสนอการแปลงกระแสงานยอว์ลที่มีเงื่อนไขของเวลาไปเป็นสโตแคสติกเพทริเน็ตส์ทั่วไป โดยผู้วิจัยจะเพิ่มค่าเฉลี่ยของเวลาเข้าไปในสัญลักษณ์ของกระแสงานยอว์ลมาตรฐานหลังจากที่แปลงเป็นสโตแคสติกเพทริเน็ตส์ทั่วไปแล้ว โดยใช้การวิเคราะห์ความน่าจะเป็นของเวลาในรูปแบบความน่าจะเป็นที่มีการแจกแจงแบบเอ็กโพเนนเชียลในการสาธิตการใช้งานโมเดล

Accelerating Reverse Engineering Image Processing Using Fpga, Matthew Joshua Harris

Browse all Theses and Dissertations

In recent decades, field programmable gate arrays (FPGAs) have evolved beyond simple, expensive computational components with minimal computing power to complex, inexpensive computational engines. Today, FPGAs can perform algorithmically complex problems with improved performance compared to sequential CPUs by taking advantage of parallelization. This concept can be readily applied to the computationally dense field of image manipulation and analysis. Processed on a standard CPU, image manipulation suffers with large image sets processed by highly sequential algorithms, but by carefully adhering to data dependencies, parallelized FPGA functions or kernels offer the possibility of significant improvement through threaded CPU functions. This thesis …

Virtual Reality And Analysis Framework For Studying Different Layout Designs, Madison Glines

Browse all Theses and Dissertations

This thesis describes the tools for studying different design prototypes. The goal was to develop effective tools to study these designs using a data-driven approach. “Proof of concept” experiments were conducted, in which participants were allowed to interact with a virtual environment depicting different designs as data pertaining to their virtual location and orientation was recorded for later analysis. The designs included “flat” store racks, as opposed to racks with more varied shapes, as well as “curved” racks. Focus of the design studies was to assist in identifying optimal locations for different product types. The automated data collection mechanisms required …

Securing Modern Cyberspace Using A Multi-Faceted Approach, Yu Li

Browse all Theses and Dissertations

Security has become one of the most significant concerns for our cyberspace. Securing the cyberspace, however, becomes increasingly challenging. This can be attributed to the rapidly growing diversities and complexity of the modern cyberspace. Specifically, it is not any more dominated by connected personal computers (PCs); instead, it is greatly characterized by cyber-physical systems (CPS), embedded systems, dynamic services, and human-computer interactions. Securing modern cyberspace therefore calls for a multi-faceted approach capable of systematically integrating these emerging characteristics. This dissertation presents our novel and significant solutions towards this direction. Specifically, we have devised automated, systematic security solutions to three critical …