Computer Sciences Commons^™

Teachers’ Engagement And Self-Efficacy In A Pk–12 Computer Science Teacher Virtual Community Of Practice, Robert Schwarzhaupt, Feng Liu, Joseph Wilson, Fanny Lee, Melissa Rasberry

Journal of Computer Science Integration

Prekindergarten to 12th-grade teachers of computer science (CS) face many challenges, including isolation, limited CS professional development resources, and low levels of CS teaching self-efficacy that could be mitigated through communities of practice (CoPs). This study used survey data from 420 PK–12 CS teacher members of a virtual CoP, CS for All Teachers, to examine the needs of these teachers and how CS teaching self-efficacy, community engagement, and sharing behaviors vary by teachers’ instructional experiences and school levels taught. Results show that CS teachers primarily join the CoP to gain high-quality pedagogical, assessment, and instructional resources. The study also found …

Accelerated Online Certificate In Quantum Computing, Joanna Burkhardt

Library Impact Statements

No abstract provided.

Digital Forensic Readiness Framework Based On Honeypot And Honeynet For Byod, Audrey Asante, Vincent Amankona

Journal of Digital Forensics, Security and Law

The utilization of the internet within organizations has surged over the past decade. Though, it has numerous benefits, the internet also comes with its own challenges such as intrusions and threats. Bring Your Own Device (BYOD) as a growing trend among organizations allow employees to connect their portable devices such as smart phones, tablets, laptops, to the organization’s network to perform organizational duties. It has gained popularity over the years because of its flexibility and cost effectiveness. This adoption of BYOD has exposed organizations to security risks and demands proactive measures to mitigate such incidents. In this study, we propose …

Efficient Neuromorphic Algorithms For Gamma-Ray Spectrum Denoising And Radionuclide Identification, Merlin Phillip Carson

Dissertations and Theses

Radionuclide detection and identification are important tasks for deterring a potentially catastrophic nuclear event. Due to high levels of background radiation from both terrestrial and extraterrestrial sources, some form of noise reduction pre-processing is required for a gamma-ray spectrum prior to being analyzed by an identification algorithm so as to determine the identity of anomalous sources. This research focuses on the use of neuromorphic algorithms for the purpose of developing low power, accurate radionuclide identification devices that can filter out non-anomalous background radiation and other artifacts created by gamma-ray detector measurement equipment, along with identifying clandestine, radioactive material.

A sparse …

Bone Quality And Fractures In Women With Osteoporosis Treated With Bisphosphonates For 1 To 14 Years, Hartmut H. Malluche, Jin Chen, Florence Lima, Lucas J. Liu, Marie-Claude Monier-Faugere, David A. Pienkowski

Internal Medicine Faculty Publications

Oral bisphosphonates are the primary medication for osteoporosis, but concerns exist regarding potential bone-quality changes or low-energy fractures. This cross-sectional study used artificial intelligence methods to analyze relationships among bisphosphonate treatment duration, a wide variety of bone-quality parameters, and low-energy fractures. Fourier transform infrared spectroscopy and histomorphometry quantified bone-quality parameters in 67 osteoporotic women treated with oral bisphosphonates for 1 to 14 years. Artificial intelligence methods established two models relating bisphosphonate treatment duration to bone-quality changes and to low-energy clinical fractures. The model relating bisphosphonate treatment duration to bone quality demonstrated optimal performance when treatment durations of 1 to 8 …

Multi-Feature Data Repository Development And Analytics For Image Cosegmentation In High-Throughput Plant Phenotyping, Rubi Quiñones, Francisco Munoz-Arriola, Sruti Das Choudhury, Ashok Samal

School of Computing: Faculty Publications

Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in high segmentation accuracy. Although there are proposed machine learning and deep learning algorithms for plant segmentation, predictions rely on the specific features being present in the training set. The need for a multi-featured dataset and analytics for cosegmentation becomes critical to better understand and predict plants’ responses to the environment. High-throughput phenotyping produces an abundance of data that can be leveraged to improve segmentation accuracy …

The Development Of Teaching Case Studies To Explore Ethical Issues Associated With Computer Programming, Michael Collins, Damian Gordon, Dympna O'Sullivan

Conference papers

In the past decade software products have become pervasive in many aspects of people’s lives around the world. Unfortunately, the quality of the experience an individual has interacting with that software is dependent on the quality of the software itself, and it is becoming more and more evident that many large software products contain a range of issues and errors, and these issues are not known to the developers of these systems, and they are unaware of the deleterious impacts of those issues on the individuals who use these systems. The authors of this paper are developing a new digital …

Localized Learning: A Possible Alternative To Current Deep Learning Techniques, Javier Viana, Kelly Cohen, Anca Ralescu, Stephan Ralescu, Vladik Kreinovich

Departmental Technical Reports (CS)

At present, the most efficient deep learning technique is the use of deep neural networks. However, recent empirical results show that in some situations, it is even more efficient to use "localized" learning -- i.e., to divide the domain of inputs into sub-domains, learn the desired dependence separately on each sub-domain, and then "smooth" the resulting dependencies into a single algorithm. In this paper, we provide theoretical explanation for these empirical successes.

How ‘Human’ Should Robots Be?, Singapore Management University

Perspectives@SMU

Hotel guests like interaction with devices that look and sound like them, but they can spark displeasure after service failures, new CUHK study shows

Freedom Of Will, Physics, And Human Intelligence: An Idea, Miroslav Svitek, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

Among the main fundamental challenges related to physics and human intelligence are: How can we reconcile the free will with the deterministic character of physical equations? What is the physical meaning of extra spatial dimensions needed to make quantum physics consistent? and Why are we often smarter than brain-simulating neural networks? In this paper, we show that while each of these challenges is difficult to resolve on its own, it may be possible to resolve all three of them if we consider them together. The proposed possible solution is that human reasoning uses the extra spatial dimensions. This may sound …

What Is A Reasonable Way To Make Predictions?, Leonardo Orea Amador, Vladik Kreinovich

Departmental Technical Reports (CS)

Predictions are usually based on what is called laws of nature: many times, we observe the same relation between the states at different moments of time, and we conclude that the same relation will occur in the future. The more times the relation repeats, the more confident we are that the same phenomenon will be re-peated again. This is how Newton's laws and other laws came into being. This is what is called inductive reasoning. However, there are other reasonable approaches. For example, assume that a person speeds and is not caught. This may be repeated two times, three times …

International Comparative Studies On The Software Testing Profession, Luiz Fernando Capretz, Pradeep Waychal, Jingdong Jia, Daniel Varona, Yadira Lizama

Electrical and Computer Engineering Publications

This work attempts to fill a gap by exploring the human dimension in particular, by trying to understand the motivation of software professionals for taking up and sustaining their careers as software testers. Towards that goal, four surveys were conducted in four countries—India, Canada, Cuba, and China—to try to understand how professional software engineers perceive and value work-related factors that could influence their motivation to start or move into software testing careers. From our sample of 220 software professionals, we observed that very few were keen to take up testing careers. Some aspects of software testing, such as the potential …

Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

The desire to make applications and machines more intelligent and the aspiration to enable their operation without human interaction have been driving innovations in neural networks, deep learning, and other machine learning techniques. Although reinforcement learning has been primarily used in video games, recent advancements and the development of diverse and powerful reinforcement algorithms have enabled the reinforcement learning community to move from playing video games to solving complex real-life problems in autonomous systems such as self-driving cars, delivery drones, and automated robotics. Understanding the environment of an application and the algorithms’ limitations plays a vital role in selecting the …

How The Pavement's Lifetime Depends On The Stress Level: An Explanation Of The Empirical Formula, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich, Olga Kosheleva, Hoang Phuong Nguyen

Departmental Technical Reports (CS)

We show that natural invariance ideas explain the empirical dependence on the pavement's lifetime on the stress level.

Why Rectified Linear Activation Functions? Why Max-Pooling? A Possible Explanation, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

At present, the most successful machine learning technique is deep learning, that uses rectified linear activation function (ReLU) s(x) = max(x,0) as a non-linear data processing unit. While this selection was guided by general ideas (which were often imprecise), the selection itself was still largely empirical. This leads to a natural question: are these selections indeed the best or are there even better selections? A possible way to answer this question would be to provide a theoretical explanation of why these selections are -- in some reasonable sense -- the best. This paper provides a possible theoretical explanation for this …

Why Normalized Difference Vegetation Index (Ndvi)?, Francisco Zapata, Eric Smith, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

Plants play a very important role in ecological systems -- they transform CO2 into oxygen. It is therefore very important to be able to estimate the overall amount of live green vegetation in a given area. The most efficient way to provide such a global analysis is to use remote sensing, i.e., multi-spectral photos taken from satellites, drones, planes, etc. At present, one of the most efficient ways to detect, based on remote sensing data, how much live green vegetation an area contains is to compute the value of the normalized difference vegetation index (NDVI). In this paper, we provide …

Shall We Be Foxes Or Hedgehogs: What Is The Best Balance For Research?, Miroslav Svitek, Olga Kosheleva, Shahnaz Shahbazova, Vladik Kreinovich

Departmental Technical Reports (CS)

Some researchers have few main ideas that they apply to many different problems -- they are called hedgehogs. Other researchers have many ideas but apply them to fewer problems -- they are called foxes. Both approaches have their advantages and disadvantages. What is the best balance between these two approaches? In this paper, we provide general recommendations about this balance. Specifically, we conclude that the optimal productivity is when the time spent on generating new ideas is equal to the time spent on understanding new applications. So, if for a researcher, understanding a new problem is much easier than generating …

As Complexity Rises, Meaningful Statements Lose Precision -- But Why?, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the motivations for Zadeh's development of fuzzy logic -- and one of the explanations for the success of fuzzy techniques -- is the empirical observation that as complexity rises, meaningful statements lose precision. In this paper, we provide a possible explanation for this empirical phenomenon.

Rotten Green Tests In Java, Pharo And Python, Vincent Aranega, Julien Delplanque, Matias Martinez, Andrew P. Black, Stéphane Ducasse, Anne Etien, Christopher Fuhrman, Guillermo Polito

Computer Science Faculty Publications and Presentations

Rotten Green Tests are tests that pass, but not because the assertions they contain are true: a rotten test passes because some or all of its assertions are not actually executed. The presence of a rotten green test is a test smell, and a bad one, because the existence of a test gives us false confidence that the code under test is valid, when in fact that code may not have been tested at all. This article reports on an empirical evaluation of the tests in a corpus of projects found in the wild. We selected approximately one hundred mature …

Enterprise Environment Modeling For Penetration Testing On The Openstack Virtualization Platform, Vincent Karovic Jr., Jakub Bartalos, Vincent Karovic, Michal Gregus

Journal of Global Business Insights

The article presents the design of a model environment for penetration testing of an organization using virtualization. The need for this model was based on the constantly increasing requirements for the security of information systems, both in legal terms and in accordance with international security standards. The model was created based on a specific team from the unnamed company. The virtual working environment offered the same functions as the physical environment. The virtual working environment was created in OpenStack and tested with a Linux distribution Kali Linux. We demonstrated that the virtual environment is functional and its security testable. Virtualizing …

Rna Splicing Programs Define Tissue Compartments And Cell Types At Single-Cell Resolution, Julia E. Olivieri, Roozbeh Dehghannasiri, Peter Wang, Sori Jang, Antoine De Morree, Serena Y. Tan, Jingsi Ming, Angela R. Wu, Stephen R. Quake, Mark A. Krasnow, Julia Salzman

All Faculty Articles - School of Engineering and Computer Science

The extent splicing is regulated at single-cell resolution has remained controversial due to both available data and methods to interpret it. We apply the SpliZ, a new statistical approach, to detect cell-type-specific splicing in >110K cells from 12 human tissues. Using 10x data for discovery, 9.1% of genes with computable SpliZ scores are cell-type-specifically spliced, including ubiquitously expressed genes MYL6 and RPS24. These results are validated with RNA FISH, single-cell PCR, and Smart-seq2. SpliZ analysis reveals 170 genes with regulated splicing during human spermatogenesis, including examples conserved in mouse and mouse lemur. The SpliZ allows model-based identification of subpopulations indistinguishable …

Procesi I Web Dizajnimit, Albin Ibrahimi

Theses and Dissertations

Numri i web sajteve në internet gjithnjë e më shumë po rritet, këto sajte zhvillohen nga programerë të ndryshëm duke përdorur gjuhë të ndryshme programuese. Ashtu që produkti final të jetë i suksesshëm, këto web sajte duhet të zhvillohen në bazë të një procesi, i cili do të shpjegohet në detaje dhe është objektiv kryesor i këtij punimi.

Procesi i tillë ndihmon në efikasitet më të lartë të produktit final, pasi që kërkesat kryesore ndahen në kërkesa më të vogla deri ne maksimum ashtu që krijohet një lloj hallke e cila mundëson planifikim shumë të mirë.

Në këtë proces përfshihen …

Ftth, Blerant Gashi

Theses and Dissertations

Rrjetet fibra për në shtepi (FTTH) i përkasin familjes së sistemeve të transmetimit FTT-x brenda botës së telekomunikacionit. Këto rrjete, të cilat konsiderohen broadband, kanë aftësinë për të transportuar sasi të mëdha të të dhënave dhe informacioneve me ritme shumë të larta të bitit. Teknologjia FTTH përfshin futjen e fibrave optike në rrjetin global, si operatori i rrjetit kryesor si linja e fundit e teknologjis. Rrjetet FTTH për kominikimin e dy pajisve ndermjet tyre perdor driten dhe si medium për transmetim të sinjalve përdor fibrin optikë, ku shpejtsia e transmetimin të të dhënave është Gigabitshte. Fibri optik ka shumë avantazhe …

Automatic Cerebrovascular Segmentation Methods - A Review, Fatma Taher, Neema Prakash

All Works

Cerebrovascular diseases are one of the serious causes for the increase in mortality rate in the world which affect the blood vessels and blood supply to the brain. In order, diagnose and study the abnormalities in the cerebrovascular system, accurate segmentation methods can be used. The shape, direction and distribution of blood vessels can be studied using automatic segmentation. This will help the doctors to envisage the cerebrovascular system. Due to the complex shape and topology, automatic segmentation is still a challenge to the clinicians. In this paper, some of the latest approaches used for segmentation of magnetic resonance angiography …

Pathogenesis, Symptomatology, And Transmission Of Sars-Cov-2 Through Analysis Of Viral Genomics And Structure, Halie M. Rando, Adam L. Maclean, Alexandra J. Lee, Ronan Lordan, Sandipan Ray, Vikas Bansal, Ashwin N. Skelly, Elizabeth Sell, John J. Dziak, Lamonica Shinholster, Lucy D’Agostino Mcgowan, Marouen Ben Guebila, Nils Wellhausen, Sergey Knyazev, Simina M. Boca, Stephen Capone, Yanjun Qi, Yo Son Park, David Mai, Yuchen Sun, Joel D. Boerckel, Christian Brueffer, James Brian Byrd, Jeremy P. Kamil, Jinhui Wang, Ryan Velazquez, Gregory L. Szeto, John P. Barton, Rishi Raj Goel, Serghei Mangul, Tiago Lubiana, Anthony Gitter

Computer Science: Faculty Publications

The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host. Because the …

Advancing Proper Dataset Partitioning And Classification Of Visual Search And The Vigilance Decrement Using Eeg Deep Learning Algorithms, Alexander J. Kamrud

Theses and Dissertations

Electroencephalography (EEG) classification of visual search and vigilance tasks has vast potential in its benefits. In future human-machine teaming systems, EEG could act as the tool for operator state assessment, enabling AI teammates to know when to assist the operator in these tasks, with the potential to lead to increased safety of operations, better training systems for our operators, and improved operational effectiveness. This research investigates deep learning methods which utilize EEG signals to classify the efficiency of an operator's search and to classify whether an operator is in a decrement during a vigilance type task, and investigates performing these …

A Positive Data Control System For The Automation Of Data Governance Functions, Yanbin Ye

Theses and Dissertations

Data governance is mission critical. Organizations start to realize the data and information are very important assets. Data governance program could minimize the risk of data lose and maximize the data values. As existing best practices to implement data governance program, most of these practices rely on management strategies, which focus on data governance literacy education, enforcing data policy, standard and processes, etc. However, IT infrastructure strategy has not changed too much to support data governance achievement. Data governance requirements for system design usually is the last concern on the list. Most of the data governance programs collect metadata or …

Managing Health Locus Of Control In Patient-Provider Relationships, James Wallace

USF Tampa Graduate Theses and Dissertations

Patient locus of control is a strong determinant of health outcomes, yet health care professionals do not typically address it in care plans. In fact, management of most medical conditions is hindered because the treating physician has little information about the patient’s locus of control. This research addresses the question “How can locus of control be used to enable health care practitioners to improve medical outcomes?”

Research Methodology. Using an engaged scholarship approach incorporating the Elaborated Action Design Research methodology, the research drives the guided, emergent design of a novel protocol and two separate artifacts for management of health locus …

In-Game Social Interactions To Facilitate Esl Students' Morphological Awareness, Language And Literacy Skills, Yolanda A. Rankin, Sana Tibi, Casey Kennington, Na-Eun Han

Computer Science Faculty Publications and Presentations

Video games that require players to utilize a target or second language to complete tasks have emerged as alternative pedagogical tools for Second Language Acquisition (SLA). With the exception of vocabulary acquisition, much of the prior research in game-based SLA fails to gauge students' literacy skills, specifically their morphological awareness or understanding of the smallest meaningful linguistic units (e.g., prefixes, suffixes, and roots). Given this shortcoming, we utilize a two-player online game to facilitate social interactions between Native English Speakers (NES) and English as a Second Language (ESL) students as a mechanism to generate ESL students' written output in the …

Infinitesimal Periodic Deformations And Quadrics, Ciprian S. Borcea, Ileana Streinu

Computer Science: Faculty Publications

We describe a correspondence between the infinitesimal deformations of a periodic bar-and-joint framework and periodic arrangements of quadrics. This intrinsic correlation provides useful geometric characteristics. A direct consequence is a method for detecting auxetic deformations, identified by a pattern consisting of homothetic ellipsoids. Examples include frameworks with higher crystallographic symmetry.