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Articles 211 - 240 of 4524
Full-Text Articles in Computer Sciences
A Predictive Analytics Approach To Building A Decision Support System For Improving Graduation Rates At A Four-Year College, Xuan Wang, Helmut Schneider, Kenneth R. Walsh
A Predictive Analytics Approach To Building A Decision Support System For Improving Graduation Rates At A Four-Year College, Xuan Wang, Helmut Schneider, Kenneth R. Walsh
Information Systems Faculty Publications
Although graduation rates have interested stakeholders, educational researchers, and policymakers for some time, little progress has been made on the overall graduation rate at four-year state colleges. Even though selective admission based on academic indicators such as high school GPA and ACT/ SAT have widely been used in the USA for years, and recent statistics show that less than 40% of students graduate from four-year state colleges in four years in the US. The authors propose using an ensemble of analytic models that considers cost as a better form of analysis that can be used as input to decision support …
Image Encryption Using Gingerbreadman Map And Rc4a Stream Cipher, Abdul Gaffar, A. B. Joshi,, Dhanesh Kumar
Image Encryption Using Gingerbreadman Map And Rc4a Stream Cipher, Abdul Gaffar, A. B. Joshi,, Dhanesh Kumar
Applications and Applied Mathematics: An International Journal (AAM)
Day to day increasing flow of sensitive or confidential information, such as images, audio, video, etc., over unsecured medium (like Internet) has motivated more concentration for concrete crypto algorithms. In this paper, an image encryption algorithm based on a permutation and substitution cipher has been proposed. In permutation stage, image pixels are shuffled using gingerbreadman map while in substitution stage, pixels are bit-wise XOR-ed with the keystream generated using RC4A (Rivest Cipher 4A) stream cipher algorithm. For the proposed scheme, statistical analyses, like histogram, adjacent pixels correlation coefficient, and information entropy are given. Security analyses, like key sensitivity, occlusion analysis …
Analysis Of Map/Ph/1 Queueing Model With Breakdown, Instantaneous Feedback And Server Vacation, G. Ayyappan, K. Thilagavathy
Analysis Of Map/Ph/1 Queueing Model With Breakdown, Instantaneous Feedback And Server Vacation, G. Ayyappan, K. Thilagavathy
Applications and Applied Mathematics: An International Journal (AAM)
In this article, we analyze a single server queueing model with feedback, a single vacation under Bernoulli schedule, breakdown and repair. The arriving customers follow the Markovian Arrival Process (MAP) and service follow the phase-type distribution. When the server returns from vacation, if there is no one present in the system, the server will wait until the customer’s arrival. When the service completion epoch if the customer is not satisfied then that customer will get the service immediately. Under the steady-state probability vector that the total number of customers are present in the system is probed by the Matrix-analytic method. …
Proactive Management In Academic Libraries: Promoting Improved Communication And Inclusion Of Academic Librarians And Archivists In Cybersecurity Policy Creation, Paul J. Luft
Theses and Dissertations
Although increasing cybersecurity threats continue in libraries, not many studies are available which examine surrounding cybersecurity policies. Even less has been done on specific types of libraries such as academic and archives. When it comes to academic libraries, cybersecurity policies take a top-down approach to managing and creating policies. The problem is that both academic libraries and archives are unique areas within a university setting. Some of the general policies do not always handle specific issues dealt with in an academic library or archives. This paper investigates if an actual gap or void in policy exists which could create issues …
Exploring Information For Quantum Machine Learning Models, Michael Telahun
Exploring Information For Quantum Machine Learning Models, Michael Telahun
Electronic Theses and Dissertations
Quantum computing performs calculations by using physical phenomena and quantum mechanics principles to solve problems. This form of computation theoretically has been shown to provide speed ups to some problems of modern-day processing. With much anticipation the utilization of quantum phenomena in the field of Machine Learning has become apparent. The work here develops models from two software frameworks: TensorFlow Quantum (TFQ) and PennyLane for machine learning purposes. Both developed models utilize an information encoding technique amplitude encoding for preparation of states in a quantum learning model. This thesis explores both the capacity for amplitude encoding to provide enriched state …
Neural Network Development In An Artificial Intelligence Gomoku Program, David Garcia
Neural Network Development In An Artificial Intelligence Gomoku Program, David Garcia
Theses and Dissertations
The game of Gomoku, also called Five in a Row, is an abstract strategy board game. The Gomoku program is constructed upon an algebraic monomial theory to aid values for each possible move and estimate chances for the artificial intelligence program to accomplish a winning path for each move and rounds. With the utilization of the monomial theory, winning configurations are successfully converted into monomials of variables which are represented on board positions. In the artificial intelligence program, an arduous task is how to perform the present configuration of the Gomoku game along with the past moves of the two …
Reinforcement Learning Environment For Orbital Station-Keeping, Armando Herrera Iii
Reinforcement Learning Environment For Orbital Station-Keeping, Armando Herrera Iii
Theses and Dissertations
In this thesis, a Reinforcement Learning Environment for orbital station-keeping is created and tested against one of the most used Reinforcement Learning algorithm called Proximal Policy Optimization (PPO). This thesis also explores the foundations of Reinforcement Learning, from the taxonomy to a description of PPO, and shows a thorough explanation of the physics required to make the RL environment. Optuna optimizes PPO's hyper-parameters for the created environment via distributed computing. This thesis then shows and analysis the results from training a PPO agent six times.
Artificial Intelligence In A Main Warehouse In Panasonic: Los Indios, Texas, Edison Antonio Trejo Hernandez
Artificial Intelligence In A Main Warehouse In Panasonic: Los Indios, Texas, Edison Antonio Trejo Hernandez
Theses and Dissertations
The Panasonic Company warehouse is located in Los Indios Texas. The warehouse presents the limitation of the great distances between its headquarters and the Main Warehouse for supplying the branches and main customers, which requires a considerable amount of time to maintain effective communication in the inventory area. In addition, during an online review, it can be confirmed that the website is disabled, contradicting its corporate policy.
The structure of the thesis proposal is arranged in four chapters from the Introduction, Statement of the Problem and Purposes; Previous Studies and Definition of the literature; the Research Methodology and the resources …
Real-Time Full Face Closed Eyes Detection, Lucas De Morais Tramasso
Real-Time Full Face Closed Eyes Detection, Lucas De Morais Tramasso
Theses and Dissertations
Intelligent systems based on machine-learning techniques are becoming a common way of solving problems in many different areas. In this thesis, our goal is to apply machine learning to a computer vision problem. We propose a new solution to detect closed eyes in full-face images. Accurate detection of closed eyes can be used in many problems such as driver drowsiness detection, human-computer interaction, and computer user monitoring. Most algorithms used to detect blinks or closed eyes follow a similar workflow. They require detection of a region of interest that is then used with different algorithms and techniques to determine if …
Static And Dynamical Properties Of Multiferroics, Sayed Omid Sayedaghaee
Static And Dynamical Properties Of Multiferroics, Sayed Omid Sayedaghaee
Graduate Theses and Dissertations
Since the silicon industrial revolution in the 1950s, a lot of effort was dedicated to the research and development activities focused on material and solid-state sciences. As a result, several cutting-edge technologies are emerging including the applications of functional materials in the design and enhancement of novel devices such as sensors, highly capable data storage media, actuators, transducers, and several other types of electronic tools. In the last two decades, a class of functional materials known as multiferroics has captured significant attention because of providing a huge potential for new designs due to possessing multiple ferroic order parameters at the …
Optimal Collaborative Path Planning For Unmanned Surface Vehicles Carried By A Parent Boat Along A Planned Route, Ari Carisza Graha Prasetia, I-Lin Wang, Aldy Gunawan
Optimal Collaborative Path Planning For Unmanned Surface Vehicles Carried By A Parent Boat Along A Planned Route, Ari Carisza Graha Prasetia, I-Lin Wang, Aldy Gunawan
Research Collection School Of Computing and Information Systems
In this paper, an effective mechanism using a fleet of unmanned surface vehicles (USVs) carried by a parent boat (PB) is proposed to complete search or scientific tasks over multiple target water areas within a shorter time . Specifically, multiple USVs can be launched from the PB to conduct such operations simultaneously, and each USV can return to the PB for battery recharging or swapping and data collection in order to continue missions in a more extended range. The PB itself follows a planned route with a flexible schedule taking into consideration locational constraints or collision avoidance in a real-world …
Teaching Applications And Implications Of Blockchain Via Project-Based Learning: A Case Study, Kevin Mentzer, Mark Frydenberg, David J. Yates
Teaching Applications And Implications Of Blockchain Via Project-Based Learning: A Case Study, Kevin Mentzer, Mark Frydenberg, David J. Yates
Information Systems and Analytics Department Faculty Journal Articles
This paper presents student projects analyzing or using blockchain technologies, created by students enrolled in courses dedicated to teaching blockchain, at two different universities during the 2018-2019 academic year. Students explored perceptions related to storing private healthcare information on a blockchain, managing the security of Internet of Things devices, maintaining public governmental records, and creating smart contracts. The course designs, which were centered around project-based learning, include self-regulated learning and peer feedback as ways to improve student learning. Students either wrote a research paper or worked in teams on a programming project to build and deploy a blockchain-based application using …
Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud, Ximeng Liu, Robert H. Deng, Pengfei Wu, Yang Yang
Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud, Ximeng Liu, Robert H. Deng, Pengfei Wu, Yang Yang
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and …
Walls Have Ears: Eavesdropping User Behaviors Via Graphics-Interrupt-Based Side Channel, Haoyu Ma, Jianwen Tian, Debin Gao, Jia Chunfu
Walls Have Ears: Eavesdropping User Behaviors Via Graphics-Interrupt-Based Side Channel, Haoyu Ma, Jianwen Tian, Debin Gao, Jia Chunfu
Research Collection School Of Computing and Information Systems
Graphics Processing Units (GPUs) are now playing a vital role in many devices and systems including computing devices, data centers, and clouds, making them the next target of side-channel attacks. Unlike those targeting CPUs, existing side-channel attacks on GPUs exploited vulnerabilities exposed by application interfaces like OpenGL and CUDA, which can be easily mitigated with software patches. In this paper, we investigate the lower-level and native interface between GPUs and CPUs, i.e., the graphics interrupts, and evaluate the side channel they expose. Being an intrinsic profile in the communication between a GPU and a CPU, the pattern of graphics interrupts …
Renewal Of An Information Systems Curriculum To Support Career Based Tracks: A Case Study, Swapna Gottipati, Venky Shankararaman, Kyong Jin Shim
Renewal Of An Information Systems Curriculum To Support Career Based Tracks: A Case Study, Swapna Gottipati, Venky Shankararaman, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
The pace at which technology redefines traditional job functions is picking up rapidly. This trend is triggered particularly by advances in analytics, security, cloud computing, Artificial Intelligence and big data. The purpose of this paper is to present a case study on our approach to renewing an undergraduate IS Major curriculum to align with the needs of the industry. We adopt a survey based approach to study Information Systems (IS) graduate skills requirements and re-design the curriculum framework for the IS program at our school. The paper describes in detail the process, the redesigned IS curriculum, the impact of the …
A Social Network Analysis Of Jobs And Skills, Derrick Ming Yang Lee, Dion Wei Xuan Ang, Grace Mei Ching Pua, Lee Ning Ng, Sharon Purbowo, Eugene Wen Jia Choy, Kyong Jin Shim
A Social Network Analysis Of Jobs And Skills, Derrick Ming Yang Lee, Dion Wei Xuan Ang, Grace Mei Ching Pua, Lee Ning Ng, Sharon Purbowo, Eugene Wen Jia Choy, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
In this study, we analyzed job roles and skills across industries in Singapore. Using social network analysis, we identified job roles with similar required skills, and we also identified relationships between job skills. Our analysis visualizes such relationships in an intuitive way. Insights derived from our analyses are expected to assist job seekers, employers as well as recruitment agencies wanting to understand trending and required job roles and skills in today’s fast changing world.
Robust, Fine-Grained Occupancy Estimation Via Combined Camera & Wifi Indoor Localization, Anuradha Ravi, Archan Misra
Robust, Fine-Grained Occupancy Estimation Via Combined Camera & Wifi Indoor Localization, Anuradha Ravi, Archan Misra
Research Collection School Of Computing and Information Systems
We describe the development of a robust, accurate and practically-validated technique for estimating the occupancy count in indoor spaces, based on a combination of WiFi & video sensing. While fusing these two sensing-based inputs is conceptually straightforward, the paper demonstrates and tackles the complexity that arises from several practical artefacts, such as (i) over-counting when a single individual uses multiple WiFi devices and under-counting when the individual has no such device; (ii) corresponding errors in image analysis due to real-world artefacts, such as occlusion, and (iii) the variable errors in mapping image bounding boxes (which can include multiple possible types …
Jointly Optimizing Sensing Pipelines For Multimodal Mixed Reality Interaction, Darshana Rathnayake, Ashen De Silva, Dasun Puwakdandawa, Lakmal Meegahapola, Archan Misra, Indika Perera
Jointly Optimizing Sensing Pipelines For Multimodal Mixed Reality Interaction, Darshana Rathnayake, Ashen De Silva, Dasun Puwakdandawa, Lakmal Meegahapola, Archan Misra, Indika Perera
Research Collection School Of Computing and Information Systems
Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural cues. However, supporting low-latency and accurate comprehension of such multimodal instructions (MMI), on resource-constrained wearable devices, remains an open challenge, especially as the state-of-the-art comprehension techniques for each individual modality increasingly utilize complex Deep Neural Network models. We demonstrate the possibility of overcoming the core limitation of latency--vs.--accuracy tradeoff by exploiting cross-modal dependencies -- i.e., by compensating for the inferior performance of one model with an increased accuracy of more complex model of a different modality. We …
Artificial Intelligence For Social Impact: Learning And Planning In The Data-To-Deployment Pipeline, Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe
Artificial Intelligence For Social Impact: Learning And Planning In The Data-To-Deployment Pipeline, Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe
Research Collection School Of Computing and Information Systems
With the maturing of artificial intelligence (AI) and multiagent systems research, we have a tremendous opportunity to direct these advances toward addressing complex societal problems. In pursuit of this goal of AI for social impact, we as AI researchers must go beyond improvements in computational methodology; it is important to step out in the field to demonstrate social impact. To this end, we focus on the problems of public safety and security, wildlife conservation, and public health in low-resource communities, and present research advances in multiagent systems to address one key cross-cutting challenge: how to effectively deploy our limited intervention …
How Do Monetary Incentives Influence Prosocial Fundraising? An Empirical Investigation Of Matching Subsidies On Crowdfunding, Zhiyuan Gao
Dissertations and Theses Collection (Open Access)
Monetary incentives, such as matching subsidies, are widely used in traditional fundraising and crowdfunding platforms to boost funding activities and improve funding outcomes. However, its effectiveness on prosocial fundraising is still unclear from both theoretical (Bénabou and Tirole, 2006; Frey, 1997; Meier, 2007a) and empirical studies (Ariely et al., 2009; Karlan and List, 2007; Rondeau and List, 2008). This dissertation aims to examine the effectiveness of matching subsidies on prosocial fundraising in the crowdfunding context. Specifically, I study how the presence of matching subsidies affects overall funding outcomes and funding dynamics in the online prosocial crowdfunding environment.
The first essay …
The Processj C++ Runtime System And Code Generator, Alexander Christian Thomason
The Processj C++ Runtime System And Code Generator, Alexander Christian Thomason
UNLV Theses, Dissertations, Professional Papers, and Capstones
ProcessJ is a modern Process-Oriented language that builds on previous work from other languages like occam and occam-pi. However, the only readily-available runtime system is built on top of the Java Virtual Machine (JVM). This is not a choice made intentionally, but simply out of a lack of other implementations -- until now. This thesis introduces the new C++-based runtime system for ProcessJ, coupled with a new C++ code generator for the ProcessJ compiler. This thesis later examines the implementation details of the runtime system, including the components that make it up. We also examine the ability to cooperatively schedule …
In-Depth Analysis Of College Students’ Data Privacy Awareness, Vernon D. Andrews
In-Depth Analysis Of College Students’ Data Privacy Awareness, Vernon D. Andrews
Theses and Dissertations
While attending university, college students need to be aware of issues related to data privacy. Regardless of the age, gender, race, or education level of college students, every student can relate to the advancement of the internet within the last decades. The internet has completely transformed the way the world receives and stores messages. Positively, the internet allows messages to be sent across the globe within the fraction of a second and provides students with access to potentially unlimited information on a variety of subjects. On the downside, there are issues on the internet that can cause more harm than …
On The Generation, Structure, And Semantics Of Grammar Patterns In Source Code Identifiers, Christian D. Newman,, Reem S. Alsuhaibani, Michael J. Decker, Anthony Peruma, Dishant Kaushik, Mohamed Wiem Mkaouer, Emily Hill
On The Generation, Structure, And Semantics Of Grammar Patterns In Source Code Identifiers, Christian D. Newman,, Reem S. Alsuhaibani, Michael J. Decker, Anthony Peruma, Dishant Kaushik, Mohamed Wiem Mkaouer, Emily Hill
Articles
Identifier names are the atoms of program comprehension. Weak identifier names decrease developer productivity and degrade the performance of automated approaches that leverage identifier names in source code analysis; threatening many of the advantages which stand to be gained from advances in artificial intelligence and machine learning. Therefore, it is vital to support developers in naming and renaming identifiers. In this paper, we extend our prior work, which studies the primary method through which names evolve: rename refactorings. In our prior work, we contextualize rename changes by examining commit messages and other refactorings. In this extension, we further consider data …
Unsupervised Structural Graph Node Representation Learning, Mikel Joaristi
Unsupervised Structural Graph Node Representation Learning, Mikel Joaristi
Boise State University Theses and Dissertations
Unsupervised Graph Representation Learning methods learn a numerical representation of the nodes in a graph. The generated representations encode meaningful information about the nodes' properties, making them a powerful tool for tasks in many areas of study, such as social sciences, biology or communication networks. These methods are particularly interesting because they facilitate the direct use of standard Machine Learning models on graphs. Graph representation learning methods can be divided into two main categories depending on the information they encode, methods preserving the nodes connectivity information, and methods preserving nodes' structural information. Connectivity-based methods focus on encoding relationships between nodes, …
Refinements Of The Concept Of Privacy In Distributed Computing, Entisar Seedi Alshammry
Refinements Of The Concept Of Privacy In Distributed Computing, Entisar Seedi Alshammry
Theses and Dissertations
In light of the tremendous development of technology in the modern world in which we live, privacy concerns are increasing, especially after the massive spread of distributed computing systems and the technologies that depend on it, whether in personal devices or public services. Hence, this research proposes refinements on the concept of privacy for enhancing the development of privacy-related strategies in distributed computing systems to address the elements of privacy. In particular, the study introduces the new concept of Privacy Appetite to describe and model the nature of the relationship between the intended disclosure of private information and gained value …
Real-Time Action Classification Using Intermediate Skeletal Pose Estimation, Kleanthis Zisis Tegos
Real-Time Action Classification Using Intermediate Skeletal Pose Estimation, Kleanthis Zisis Tegos
Theses and Dissertations
The topic of Human Action Classification has attracted significant interest these past years, which can be attributed to the advancements in deep learning methodologies. Its applications range from robotics to surveillance and automated video categorization, as well as in the healthcare industry. The literature, however, has primarily focused on offline action classification, without significant attention being given to the constraints of an online real-time classifier. Using an intermediate skeletal representation of humans, while convoluted, provides a scalable means of tackling the action classification problem. This project discusses the existing literature, and adapts two of the state-of-the-art approaches for real-time analysis. …
Implementation Of An Electronic Alert For Improving Adherence To Diabetic Foot Exam Screenings In Type 2 Diabetic Patients In Primary Care Clinics, Ruby Denson
Student Scholarly Projects
Practice Problem: Patients with type 2 diabetes mellitus (T2DM) are at an increased risk of complications including foot ulcerations (Harris-Hayes et al., 2020). Preventive care is essential for the early detection of foot ulcers but despite the advantages of preventive screening, a limited number of primary care providers perform annual foot exams (Williams et al., 2018).
PICOT: The clinical question that guided this project was, “In adult patients with T2DM receiving care in a primary care setting, will the implementation of an electronic clinical reminder alert (ECR) increase provider adherence to performing an annual diabetic foot exam and risk …
Lightweight Deep Learning For Botnet Ddos Detection On Iot Access Networks, Eric A. Mccullough
Lightweight Deep Learning For Botnet Ddos Detection On Iot Access Networks, Eric A. Mccullough
Graduate Theses/Dissertations
With the proliferation of the Internet of Things (IoT), computer networks have rapidly expanded in size. While Internet of Things Devices (IoTDs) benefit many aspects of life, these devices also introduce security risks in the form of vulnerabilities which give hackers billions of promising new targets. For example, botnets have exploited the security flaws common with IoTDs to gain unauthorized control of hundreds of thousands of hosts, which they then utilize to carry out massively disruptive distributed denial of service (DDoS) attacks. Traditional DDoS defense mechanisms rely on detecting attacks at their target and deploying mitigation strategies toward the attacker …
Development Of Computational To Ols To Target Microrna, Luo Song
Development Of Computational To Ols To Target Microrna, Luo Song
Dissertations and Theses (Open Access)
MicroRNAs (a.k.a, miRNAs) play an important role in disease development. However, few of their structures have been determined and structure-based computational methods remain challenging in accurately predicting their interactions with small molecules. To address this issue, my thesis is to develop integrated approaches to screening for novel inhibitors by targeting specific structure motifs in miRNAs. The project starts with implementing a tool to find potential miRNA targets with desired motifs. I combined both sequence information of miRNAs and known RNA structure data from Protein Data Bank (PDB) to predict the miRNA structure and identify the motif to target, then I …
Predicting Personality Type From Writing Style, Tanay Gottigundala
Predicting Personality Type From Writing Style, Tanay Gottigundala
Master's Theses
The study of personality types gained traction in the early 20th century, when Carl Jung's theory of psychological types attempted to categorize individual differences into the first modern personality typology. Iterating on Jung's theories, the Myers-Briggs Type Indicator (MBTI) tried to categorize each individual into one of sixteen types, with the theory that an individual's personality type manifests in virtually all aspects of their life. This study explores the relationship between an individual's MBTI type and various aspects of their writing style. Using a MBTI-labeled dataset of user posts on a personality forum, three ensemble classifiers were created to predict …