Computer Engineering Commons^™

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Application Of Deep Learning For Medical Sciences And Epidemiology Data Analysis And Diagnostic Modeling, Somenath Chakraborty

Dissertations

Machine Learning and Artificial Intelligence have made significant progress concurrent with new advancements in hardware and software technologies. Deep learning methods heavily utilize parallel computing and Graphical Processing Units(GPU). It is already used in many applications ranging from image classification, object detection, segmentation, cyber security problems and others. Deep Learning is emerging as a viable choice in dealing with today’s real-time medical problems. We need new methods and technologies in the field of Medical Science and Epidemiology for detecting and diagnosing emerging threats from new viruses such as COVID-19. The use of Artificial Intelligence in these domains is becoming more …

Multi-Sensory Emotion Recognition With Speech And Facial Expression, Qingmei Yao

Dissertations

Emotion plays an important role in human beings’ daily lives. Understanding emotions and recognizing how to react to others’ feelings are fundamental to engaging in successful social interactions. Currently, emotion recognition is not only significant in human beings’ daily lives, but also a hot topic in academic research, as new techniques such as emotion recognition from speech context inspires us as to how emotions are related to the content we are uttering.

The demand and importance of emotion recognition have highly increased in many applications in recent years, such as video games, human computer interaction, cognitive computing, and affective computing. …

Face Recognition With Multi-Stage Matching Algorithms, Xianming Chen

Dissertations

For every face recognition method, the primary goal is to achieve higher recognition accuracy and spend less computational costs. However, as the gallery size increases, especially when one probe image corresponds to only one training image, face recognition becomes more and more challenging. First, a larger gallery size requires more computational costs and memory usage. Meanwhile, that the large gallery sizes degrade the recognition accuracy becomes an even more significant problem to be solved.

A coarse parallel algorithm that equally divides training images and probe images into multiple processors is proposed to deal with the large computational costs and huge …

Novel Bioinformatic Approaches For Analyzing Next-Generation Sequencing Data, Yan Peng

Dissertations

In general, DNA reconstruction is deemed as the key of molecular biology since it makes people realize how genotype affects phenotypes. The DNA sequencing technology emerged exactly towards this and has greatly promoted molecular biology’s development. The traditional method, "Sanger," is effective but extremely expensive on a cost-per-base basis. This shortcoming of Sanger method leads to the rapid development of next-generation sequencing technologies. The NGS technologies are widely used by virtue of their low-cost, high-throughput, and fast nature. However, they still face major drawbacks such as huge amounts of data as well as relatively short read length compared with traditional …

Secure And Reliable Routing Protocol For Transmission Data In Wireless Sensor Mesh Networks, Nooh Adel Bany Muhammad

Dissertations

Abstract

Sensor nodes collect data from the physical world then exchange it until it reaches the intended destination. This information can be sensitive, such as battlefield surveillance. Therefore, providing secure and continuous data transmissions among sensor nodes in wireless network environments is crucial. Wireless sensor networks (WSN) have limited resources, limited computation capabilities, and the exchange of data through the air and deployment in accessible areas makes the energy, security, and routing major concerns in WSN. In this research we are looking at security issues for the above reasons. WSN is susceptible to malicious activities such as hacking and physical …

Development Of Workforce Skills: Student Perceptions Of Mentoring In First Robotics, Katie Joan Veal Wallace

Dissertations

In today’s global economy, new workforce competencies are needed for success at both individual and societal levels. The new workforce skills extend beyond basic reading, writing, and arithmetic to include higher order processes such as critical thinking and problem solving. Technical job opportunities have grown by approximately 17%, yet the United States continues to decline in science, technology, engineering and mathematics (STEM) disciplines. Further, U.S. students earn average or below average test scores when compared to other developed countries. Researchers cite the need to incorporate the learning of workplace skills into secondary education curriculum, and advocates call for new teaching …

Modeling That Leads To The Prediction Of Photocatalytic Coatings Characterization, Biju Bajracharya

Dissertations

One of the abundant sources of energy on earth is a solar energy which is the clean and safest energy source. It is also known as universal energy, the most important source of renewable energy available today. On realizing that the light source has a crucial role in daily life, several scientists and researchers from centuries ago have studied to establish photo induced systems and utilized them. Long after the knowledge of thermal energy, photovoltaic energy, and photosynthesis in plants, two prominent scientists, Fujishima and Honda, have discovered the electrochemical photolysis of water with the Titanium dioxide electrode which was …

Development And Applications Of The Expanded Equivalent Fluid Method, Bharath Kumar Kandula

Dissertations

Ocean acoustics is the study of sound in the oceans. Electromagnetic waves attenuate rapidly in the water medium. Sound is the best means to transmit information underwater. Computational numerical simulations play an important role in ocean acoustics. Simulations of acoustic propagation in the oceans are challenging due to the complexities involved in the ocean environment. Different methods have been developed to simulate underwater sound propagation. The Parabolic-Equation (PE) method is the best choice in several ocean acoustic problems. In shallow water acoustic experiments, sound loses some of its energy when it interacts with the bottom. An equivalent fluid technique was …

Reducing Ambiguities In Customer Requirements Through Historical Rule-Based Knowledge In A Small Organization, Silvia Brum Preston

Dissertations

During the elicitation process the requirements for a software application are obtained from the customer. Customers often do not know how to clearly express the requirements of the application to be built, causing requirements to be ambiguous. Many studies have been found to cover different characteristics of the requirements elicitation process including methods for reducing ambiguities in requirements. The methods and findings of these studies were found to be too general when it comes to the specific domain of the requirements and knowledge about the requirements. In addition, some studies did not take into consideration the level of expertise of …

Synergy Of The Developed 6d Bim Framework And Conception Of The Nd Bim Framework And Nd Bim Process Ontology, Shawn Edward O'Keeffe

Dissertations

The author developed a unified nD framework and process ontology for Building Information Modeling (BIM). The research includes a framework developed for 6D BIM, nD BIM, and nD ontology that defines the domain and sub-domain constructs for future nD BIM dimensions. The nD ontology defines the relationships of kinds within any new proposed dimensional domain for BIM. The developed nD BIM framework and ontology takes into account the current 2D-5D BIM dimensions. There is a synergy between the 6D and nD framework that allows the nD framework and ontology to be utilized as a unified template for future dimensional development. …

New Fault Tolerant Multicast Routing Techniques To Enhance Distributed-Memory Systems Performance, Masoud Esmail Masoud Shaheen

Dissertations

Distributed-memory systems are a key to achieve high performance computing and the most favorable architectures used in advanced research problems. Mesh connected multicomputer are one of the most popular architectures that have been implemented in many distributed-memory systems. These systems must support communication operations efficiently to achieve good performance. The wormhole switching technique has been widely used in design of distributed-memory systems in which the packet is divided into small flits. Also, the multicast communication has been widely used in distributed-memory systems which is one source node sends the same message to several destination nodes. Fault tolerance refers to the …

Error Estimation Techniques To Refine Overlapping Aerial Image Mosaic Processes Via Detected Parameters, William Glenn Bond

Dissertations

In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid.

The method presented first locates the images from a data set that it predicts will not align well via the mosaic process, then it uses a correlation function, optimized by a modified Hooke and Jeeves algorithm, to provide a more optimal transformation function input to the mosaic program. Using this improved …

Bemdec: An Adaptive And Robust Methodology For Digital Image Feature Extraction, Isaac Kueth Gang

Dissertations

The intriguing study of feature extraction, and edge detection in particular, has, as a result of the increased use of imagery, drawn even more attention not just from the field of computer science but also from a variety of scientific fields. However, various challenges surrounding the formulation of feature extraction operator, particularly of edges, which is capable of satisfying the necessary properties of low probability of error (i.e., failure of marking true edges), accuracy, and consistent response to a single edge, continue to persist. Moreover, it should be pointed out that most of the work in the area of feature …

Entropy And Certainty In Lossless Data Compression, James Jay Jacobs

Dissertations

Data compression is the art of using encoding techniques to represent data symbols using less storage space compared to the original data representation. The encoding process builds a relationship between the entropy of the data and the certainty of the system. The theoretical limits of this relationship are defined by the theory of entropy in information that was proposed by Claude Shannon. Lossless data compression is uniquely tied to entropy theory as the data and the system have a static definition. The static nature of the two requires a mechanism to reduce the entropy without the ability to alter either …

Inferring Gene Regulatory Networks From Time Series Microarray Data, Peng Li

Dissertations

The innovations and improvements in high-throughput genomic technologies, such as DNA microarray, make it possible for biologists to simultaneously measure dependencies and regulations among genes on a genome-wide scale and provide us genetic information. An important objective of the functional genomics is to understand the controlling mechanism of the expression of these genes and encode the knowledge into gene regulatory network (GRN). To achieve this, computational and statistical algorithms are especially needed.

Inference of GRN is a very challenging task for computational biologists because the degree of freedom of the parameters is redundant. Various computational approaches have been proposed for …