Computer and Systems Architecture Commons^™

A Cloud Interoperability Broker (Cib) For Data Migration In Saas, Hassan Ali, Ramdan Mowad, Amira Farouk

Future Computing and Informatics Journal

Cloud computing is becoming increasingly popular. Information technology market leaders, e.g., Microsoft, Google, and Amazon, are extensively shifting toward cloud-based solutions. However, there is isolation in the cloud implementations provided by the cloud vendors. Limited interoperability can cause one user to adhere to a single cloud provider; thus, a required migration of an application or data from one cloud provider to another may necessitate a significant effort and/or full-cycle redevelopment to fit the new provider's standards and implementation. The ability to move from one cloud vendor to another would be a step toward advancing cloud computing interoperability and increasing customer …

Fixing Rules For Data Cleaning Based On Conditional Functional Dependency, Asmaa Abdo

Future Computing and Informatics Journal

Most existing databases suffer from data inconsistencies. Enhancing data quality efforts are necessary to resolve this issue. In this paper, two techniques are proposed for mining accurate conditional functional dependencies rules from such databases to be employed for data cleaning. The idea of the proposed techniques is to mine firstly maximal closed frequent patterns, then mine the dependable conditional functional dependencies rules with the help of lift measure. Moreover, data repairing algorithm is proposed for fixing inconsistent tuples found in the database exploiting the generated rules. An extensive experimental is conducted study to confirm the effectiveness of the proposed techniques …

Benefits And Challenges Of Cloud Erp Systems – A Systematic Literature Review, Mohamed Abd Elmonem, Eman Nasr, Mervat Geith

Future Computing and Informatics Journal

Enterprise Resource Planning (ERP) systems provide extensive benefits and facilities to the whole enterprise. ERP systems help the enterprise to share and transfer data and information across all functions units inside and outside the enterprise. Sharing data and information between enterprise departments helps in many aspects and aims to achieve different objectives. Cloud computing is a computing model which takes place over the internet and provides scalability, reliability, availability and low cost of computer reassures. Implementing and running ERP systems over the cloud offers great advantages and benefits, in spite of its many difficulties and challenges. In this paper, we …

Intelligent Sdn Traffic Classification Using Deep Learning: Deep-Sdn, Ali Malik, Ruairí De Fréin, Mohammed Al-Zeyadi, Javier Andreu-Perez

Conference papers

Accurate traffic classification is fundamentally important for various network activities such as fine-grained network management and resource utilisation. Port-based approaches, deep packet inspection and machine learning are widely used techniques to classify and analyze network traffic flows. However, over the past several years, the growth of Internet traffic has been explosive due to the greatly increased number of Internet users. Therefore, both port-based and deep packet inspection approaches have become inefficient due to the exponential growth of the Internet applications that incurs high computational cost. The emerging paradigm of software-defined networking has reshaped the network architecture by detaching the control …

Otter Vector Extension, Alexis A. Peralta

Computer Engineering

This paper offers an implementation of a subset of the "RISC-V 'V' Vector Extension", v0.7.x. The "RISC-V 'V' Vector Extension" is the proposed vector instruction set for RISC-V open-source architecture. Vectors are inherently data-parallel, allowing for significant performance increases. Vectors have applications in fields such as cryptography, graphics, and machine learning. A vector processing unit was added to Cal Poly's RISC-V multi-cycle architecture, known as the OTTER. Computationally intensive programs running on the OTTER Vector Extension ran over three times faster when compared to the baseline multi-cycle implementation. Memory intensive applications saw similar performance increases.

Robust Drone Landing, Alvin Xuan Quan Chui

Computer Engineering

The growth of drone technology goes with the demands of computer vision. Computer vision provides opportunities for developers to design and create, giving rise to a new innovation. It is also a basis for a full autonomous system when implemented with an intelligent agent. Surveillance drones are installed with cameras, and cameras are the most common approach to computer vision. However, a high-resolution camera with great performance could be expensive, while other low-cost cameras might lack reading accuracy. To improve the performances and maximize a camera’s capability, many different object trackers come into play. This paper will investigate and study …

Otter Debugger, Keefe Johnson

Computer Engineering

This project is a debugger and programmer for the OTTER CPU, the implementation of the RISC-V ISA used by Cal Poly to teach computer architecture and assembly language in CPE 233/333 and usually implemented on the Basys3 FPGA development board. With this tool, students can quickly program their OTTER with a new/revised RISC-V program binary without resynthesizing the entire FPGA design. They can then use the debugger from a PC to pause/continue/single-step execution and set breakpoints, while inspecting and modifying register and memory contents. This enables real-time debugging of OTTER projects involving custom hardware such as a keyboard and VGA …

Bootstrapping Massively Multiplayer Online Role Playing Games, Mitchell Miller

Master's Theses

Massively Multiplayer Online Role Playing Games (MMORPGs) are a prominent genre in today's video game industry with the most popular MMORPGs generating billions of dollars in revenue and attracting millions of players. As they have grown, they have become a major target for both technological research and sociological research. In such research, it is nearly impossible to reach the same player scale from any self-made technology or sociological experiments. This greatly limits the amount of control and topics that can be explored. In an effort to make up a lacking or non-existent player-base for custom-made MMORPG research scenarios A.I. agents, …

Zenneck Waves In Decision Agriculture: An Empirical Verification And Application In Em-Based Underground Wireless Power Transfer, Usman Raza, Abdul Salam

Faculty Publications

In this article, the results of experiments for the observation of Zenneck surface waves in sub GHz frequency range using dipole antennas are presented. Experiments are conducted over three different soils for communications distances of up to 1 m. This empirical analysis confirms the existence of Zenneck waves over the soil surface. Through the power delay profile (PDP) analysis, it has been shown that other subsurface components exhibit rapid decay as compared to the Zenneck waves. A potential application of the Zenneck waves for energy transmission in the area of decision agriculture is explored. Accordingly, a novel wireless through-the-soil power …

Stay-At-Home Motor Rehabilitation: Optimizing Spatiotemporal Learning On Low-Cost Capacitive Sensor Arrays, Reid Sutherland

Graduate Theses and Dissertations

Repeated, consistent, and precise gesture performance is a key part of recovery for stroke and other motor-impaired patients. Close professional supervision to these exercises is also essential to ensure proper neuromotor repair, which consumes a large amount of medical resources. Gesture recognition systems are emerging as stay-at-home solutions to this problem, but the best solutions are expensive, and the inexpensive solutions are not universal enough to tackle patient-to-patient variability. While many methods have been studied and implemented, the gesture recognition system designer does not have a strategy to effectively predict the right method to fit the needs of a patient. …

Investigation Of The Effects Of A Situated Learning Digital Game On Mathematics Education At The Primary School Level, Mariana Rocha

Doctoral

Previous research suggests games can improve learning outcomesand students’ motivation. However, there still exists insufficient clarity on the design principles and pedagogical approach that should underpinmathematics educational games. This thesis is aimed at evaluating the effects of an educationalgame on the learningperformance and levels of anxiety promoted by mathematics activities of primary school students. The game was designed based on theprinciples of situated learning, following acombination of an in-depth literature review, a collection of teachers’ perceptions about educational games, and features ofclassroom games. Empirical evaluation of the game was performed through a 5-weeks experiment carried out in three Irish schools, …

Minet Magnetic Indoor Localization, Michael Drake

Honors Theses

Indoor localization is a modern problem of computer science that has no unified solution, as there are significant trade-offs involved with every technique. Magnetic localization, though less popular than WiFi signal based localization, is a sub-field that is rooted in infrastructure-free design, which can allow universal setup. Magnetic localization is also often paired with probabilistic programming, which provides a powerful method of estimation, given a limited understanding of the environment. This thesis presents Minet, which is a particle filter based localization system using the Earth's geomagnetic field. It explores the novel idea of state space limitation as a method of …

Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann

Mathematics & Statistics ETDs

This thesis uses a geometric approach to derive and solve nonlinear least squares minimization problems to geolocate a signal source in three dimensions using time differences of arrival at multiple sensor locations. There is no restriction on the maximum number of sensors used. Residual errors reach the numerical limits of machine precision. Symmetric sensor orientations are found that prevent closed form solutions of source locations lying within the null space. Maximum uncertainties in relative sensor positions and time difference of arrivals, required to locate a source within a maximum specified error, are found from these results. Examples illustrate potential requirements …

A Framework To Detect Presentation Attacks, Laeticia Etienne

Master of Science in Information Technology Theses

Biometric-based authentication systems are becoming the preferred choice to replace password-based authentication systems. Among several variations of biometrics (e.g., face, eye, fingerprint), iris-based authentication is commonly used in every day applications. In iris-based authentication systems, iris images from legitimate users are captured and certain features are extracted to be used for matching during the authentication process. Literature works suggest that iris-based authentication systems can be subject to presentation attacks where an attacker obtains printed copy of the victim’s eye image and displays it in front of an authentication system to gain unauthorized access. Such attacks can be performed by displaying …

Load Balancing Of Financial Data Using Machine Learning And Cloud Analytics, Dimple Jaiswal

Masters Theses & Specialist Projects

The rising use of technology for web applications, android applications, digital marketing, and e-application systems for financial investments benefits a large sector of stakeholders and common people. It allows investors to make an appropriate choice for investment and to increase their capital growth. This requires proper research of investment companies, their trends in price and analysis of historical and current information. In addition, prediction of prices makes the process of investment more comfortable and reliable for investors as shares are the most volatile type of investment. To offer this service to multiple users spread across the globe, there are certain …

Optimization Study Of An Image Classification Deep Neural Network, Rose Ault

Honors Projects

Machine Learning is an important and growing field within Artificial Intelligence. It is particularly useful in situations where developing an algorithm to perform the task in a conventional way would be extremely difficult. Instead of being programmed specifically to complete a task, a program embodies a trained model that can recognize patterns present in given example data, and is able use that model to make predictions on future data. Neural networks are a prominent example of machine learning models used for this purpose. Neural networks are models that are based on how brains work, with massive numbers of connected processing …

Efficient Hardware/Software Partitioning Techniques For A Cloud-Scale Cpu-Fpga Platform, Samah Ziyad Rahamneh

Dissertations

The diversity of workload characteristics has stimulated the deployment of heterogeneous architectures to accommodate workloads’ requirements disparity in cloud data centers. In heterogeneous computing, co-processors are utilized to support Central Processing Units (CPUs) in fulfilling workload demands. Field Programmable Gate Arrays (FPGAs) have advantages over other accelerators because of their power, performance and re-configurability benefits. In order to achieve the most benefit of a heterogeneous platform, efficient partitioning of workload between the CPU and the FPGA is a crucial demand.

This dissertation first presents a design and implementation of cooperative CPU-FPGA execution techniques, which include code and data partitioning, of …

Two Can Play That Game: An Adversarial Evaluation Of A Cyber-Alert Inspection System, Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam

Research Collection School Of Computing and Information Systems

Cyber-security is an important societal concern. Cyber-attacks have increased in numbers as well as in the extent of damage caused in every attack. Large organizations operate a Cyber Security Operation Center (CSOC), which forms the first line of cyber-defense. The inspection of cyber-alerts is a critical part of CSOC operations (defender or blue team). Recent work proposed a reinforcement learning (RL) based approach for the defender’s decision-making to prevent the cyber-alert queue length from growing large and overwhelming the defender. In this article, we perform a red team (adversarial) evaluation of this approach. With the recent attacks on learning-based decision-making …

A Study Of Execution Performance For Rust-Based Object Vs Data Oriented Architectures, Joseph A. Vagedes

Theses and Dissertations

To investigate the Data-Oriented Design (DOD) paradigm, in particular, an architecture built off its principles: the Entity-Component-System (ECS). ECS is commonly used by video game engines due to its ability to store data in a way that is optimal for the cache to access. Additionally, the structure of this paradigm produces a code-base that is simple to parallelize as the workload can be distributed across a thread-pool based on the data used with little to no need for data safety measures such as mutexes and locks. A final benefit, although not easily measured, is that the DOD paradigm produces a …

Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi

Engineering Faculty Articles and Research

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this study is to investigate these questions, primarily through simulations where the weight-sharing assumption is relaxed. Taking inspiration from neural circuitry, we explore the use of Free Convolutional Networks and neurons with variable connection patterns. Using Free Convolutional Networks, we show that while weight-sharing is a pragmatic optimization …