Computer Sciences Commons^™

Transfer Of Personality Through Text Style, Michael O'Mahony, Robert Ross

Other resources

The style of generated text is how something is said rather than what is said. We hypothesize that changing the style of generated text can change the perceived personality of the text generation agent. Dialogue systems that aim to imitate a human agent can appear to have a consistent personality through a consistent, controllable style of conversation. Some recent work on the style of generated text [1] performs impressively in the small number of domains selected for their experiments using transformer and LSTM-based models. Lin et al. [1] used weak supervised learning as their data set lacks parallel data. The …

A Maturity Model Of Data Modeling In Self-Service Business Intelligence Software, Anna Kurenkov

Master of Science in Information Technology Theses

Although Self-Service Business Intelligence (SSBI) is continually being adopted in various industries, there is a lack of research focused on data modeling in SSBI. This research aims to fill that research gap and propose a maturity model for SSBI data modeling which is generalizeable between different software and applicable for users of all technical backgrounds. Through extensive literature review, a five-tier maturity model was proposed, explained, and instantiated in PowerBI and Tableau. The testing of the model was found to be simple and intuitive, and the research concludes that the model is applicable to enterprise SSBI environments. This research is …

Hate-Clipper: Multimodal Hateful Meme Classification Based On Cross-Modal Interaction Of Clip Features, Gokul Karthik Kumar, Karthik Nandakumar

Computer Vision Faculty Publications

Hateful memes are a growing menace on social media. While the image and its corresponding text in a meme are related, they do not necessarily convey the same meaning when viewed individually. Hence, detecting hateful memes requires careful consideration of both visual and textual information. Multimodal pretraining can be beneficial for this task because it effectively captures the relationship between the image and the text by representing them in a similar feature space. Furthermore, it is essential to model the interactions between the image and text features through intermediate fusion. Most existing methods either employ multimodal pre-training or intermediate fusion, …

A Brief Review Of Dns, Root Servers, Vulnerabilities And Decentralization, Mallory Runyan

Cybersecurity Undergraduate Research Showcase

Since the 1980’s and creation of the World Wide Web, Internet utilization is a common and arguably, necessary, part of daily life. The internet is young and still relatively new, but as of 2016, 3.4 billion people were online, and that number has since grown [1]. This is a significant number, but as such a common part of daily life, how elements of the internet or its infrastructure work is complex. The world would very likely be thrown into dark ages if DNS or any other significant aspect of the internet's infrastructure were to succumb to an attack. The Colonial …

Computer Simulation Of The Light Absorption Band Of The Jumping Spider Isorhodopsin, Noah Zoldak

Honors Projects

In order to simulate the photoisomerization of the 9-cis Jumping Spider Isorhodopsin (JSiR-1) it is necessary to first simulate its light-absorption band. Here we report on the absorption band simulated using protein models constructed using the advanced Automatic Rhodopsin Modeling (a-ARM) program. A population of S₀ models was created and the corresponding S₀ to S₁ transitions were determined for each member of the resulting population. The calculation resulted in a Gaussian plot showing that the wavelength of the absorption maximum of 560 nm (a violet color) that is consistent, but red-shifted, with respect the experimentally observed value.

Resilience Monitoring For Multi-Filter All-Source Navigation Framework With Assurance, Jonathon S. Gipson, Robert C. Leishman

Faculty Publications

The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.), do not intrinsically meet this requirement. This paper presents a novel method to monitor real-time overlapping position state observability and introduces an observability bank within the ARMAS framework, known as stable observability monitoring (SOM). SOM …

Actively Guided Cansats For Assisting Localization And Mapping In Unstructured And Unknown Environments, Cary Chun, M. Hassan Tanveer

Symposium of Student Scholars

When navigating in unknown and unstructured environments, Unmanned Arial Vehicles (UAVs) can struggle when attempting to preform Simultaneous Localization and Mapping (SLAM) operations. Particularly challenging circumstance arise when an UAV may need to land or otherwise navigate through treacherous environments. As the primary UAV may be too large and unwieldly to safely investigate in these types of situations, this research effort proposes the use of actively guided CanSats for assisting in localization and mapping of unstructured environments. A complex UAV could carry multiple of these SLAM capable CanSats, and when additional mapping and localization capabilities where required, the CanSat would …

Hydrogen Bonding In Small Model Peptides; The Dft And Mp2 Study, Gracie Smith, Martina Kaledin

Symposium of Student Scholars

Formamide is a small model compound for the study of the peptide bond. The peptide bond links amino acids together, specifies rigidity to the protein backbone, and includes the essential docking sites for hydrogen-bond-mediated protein folding and protein aggregation, namely, the C=O acceptor and the N-H donor parts. Therefore, the infrared C=O (amide-I) and N-H (amide-A) vibrations provide sensitive and widely used probes into the structure of peptides. This computational chemistry work, we study hydrogen bonds in formamide dimer isomers. We evaluate the accuracy of the density functional theory (DFT) and many-body perturbation theory to the 2^nd order (MP2) …

Software Supply Chain Security Attacks And Analysis Of Defense, Juanjose Rodriguez-Cardenas, Jobair Hossain Faruk, Masura Tansim, Asia Shavers, Corey Brookins, Shamar Lake, Ava Norouzi, Marie Nassif, Kenneth Burke, Miranda Dominguez

Symposium of Student Scholars

The Software Supply chain or SSC is the backbone of the logistics industry and is crucial to a business's success and operation. The surge of attacks and risks for the SSC has grown in coming years with each attack's impact becoming more significant. These attacks have led to the leaking of both client and company sensitive information, corruption of the data, and having it subject to malware and ransomware installation, despite new practices implemented and investments into SSC security and its branches that have not stopped attackers from developing new vulnerabilities and exploits. In our research, we have investigated Software …

Secure Cloud-Based Iot Water Quality Gathering For Analysis And Visualization, Soin Abdoul Kassif Baba M Traore

Symposium of Student Scholars

Water quality refers to measurable water characteristics, including chemical, biological, physical, and radiological characteristics usually relative to human needs. Dumping waste and untreated sewage are the reasons for water pollution and several diseases to the living hood. The quality of water can also have a significant impact on animals and plant ecosystems. Therefore, keeping track of water quality is a substantial national interest. Much research has been done for measuring water quality using sensors to prevent water pollution. In summary, those systems are built based on online and reagent-free water monitoring SCADA systems in wired networks. However, centralized servers, transmission …

What Pakistani Computer Science And Software Engineering Students Think About Software Testing?, Luiz Fernando Capretz, Abdul Rehman Gilal

Electrical and Computer Engineering Publications

Software testing is one of the crucial supporting processes of the software life cycle. Unfortunately for the software industry, the role is stigmatized, partly due to misperception and partly due to treatment of the role. The present study aims to analyze the situation to explore what restricts computer science and software engineering students from taking up a testing career in the software industry. To conduct this study, we surveyed 88 Pakistani students taking computer science or software engineering degrees. The results showed that the present study supports previous work into the unpopularity of testing compared to other software life cycle …

A High-Accuracy Detection System: Based On Transfer Learning For Apical Lesions On Periapical Radiograph, Yueh Chuo, Wen-Ming Lin, Tsung-Yi Chen, Mei-Ling Chan, Yu-Sung Chang, Yan-Ru Lin, Yuan-Jin Lin, Yu-Han Shao, Chiung-An Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Apical Lesions, one of the most common oral diseases, can be effectively detected in daily dental examinations by a periapical radiograph (PA). In the current popular endodontic treatment, most dentists spend a lot of time manually marking the lesion area. In order to reduce the burden on dentists, this paper proposes a convolutional neural network (CNN)-based regional analysis model for spical lesions for periapical radiographs. In this study, the database was provided by dentists with more than three years of practical experience, meeting the criteria for clinical practical application. The contributions of this work are (1) an advanced adaptive threshold …

College Teaching And Ai, Leo Irakliotis

Computer Science: Faculty Publications and Other Works

Artificial Intelligence will reshape the way we assess student learning in ways that no one has prepared us for.

Behaviors For Which Deinonychosaurs Used Their Feet, Alexander King

Honors Projects

This paper seeks to show for what purpose deinonychosaurs used their feet. Fowler et al., (2011) showed that D. antirrhopus’s feet were closest in function to accipitrids, as they found it was more built for grasping prey than running.

I answered this question by using 2D images of the feet of three modern birds (Buteo jamaicensis, Phasianus colchicus, and Gallus gallus domesticus), one eudromaeosaur (Deinonychus antirrhopus), and one troodontid (Borogovia gracilicrus). I used ImageJ to apply 73 landmarks to each foot, capturing the variation between species in the metatarsals and pedal phalanges. These data were then uploaded to the software …

Critically Observing The Challenges And Changes: An Analysis On Covid-19’S Impact With An Emphasis On Students In Higher Education, Landon Perkins

Honors Theses

This project involves comparing different visualizations related to COVID-19 and higher education in order to determine key impacts of the COVID-19 pandemic on students in higher education, as well as higher education as a whole. The main metrics used to determine the impact were mental health indicators for anxiety or depressive disorders, enrollment numbers by control type (public, private non-profit, or private for-profit) and state for 2020 and 2021, and state mandate lift dates for a variety of mandates implemented across the United States. These metrics were analyzed both individually and against each other to determine if they had any …

Probing Conformational Landscapes And Mechanisms Of Allosteric Communication In The Functional States Of The Abl Kinase Domain Using Multiscale Simulations And Network-Based Mutational Profiling Of Allosteric Residue Potentials, Keerthi Krishnan, Hao Tian, Peng Tao, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

In the current study, multiscale simulation approaches and dynamic network methods are employed to examine the dynamic and energetic details of conformational landscapes and allosteric interactions in the ABL kinase domain that determine the kinase functions. Using a plethora of synergistic computational approaches, we elucidate how conformational transitions between the active and inactive ABL states can employ allosteric regulatory switches to modulate intramolecular communication networks between the ATP site, the substrate binding region, and the allosteric binding pocket. A perturbation-based network approach that implements mutational profiling of allosteric residue propensities and communications in the ABL states is proposed. Consistent with …

The Interaction Of Normalisation And Clustering In Sub-Domain Definition For Multi-Source Transfer Learning Based Time Series Anomaly Detection, Matthew Nicholson, Rahul Agrahari, Clare Conran, Haythem Assem, John D. Kelleher

Articles

This paper examines how data normalisation and clustering interact in the definition of sub-domains within multi-source transfer learning systems for time series anomaly detection. The paper introduces a distinction between (i) clustering as a primary/direct method for anomaly detection, and (ii) clustering as a method for identifying sub-domains within the source or target datasets. Reporting the results of three sets of experiments, we find that normalisation after feature extraction and before clustering results in the best performance for anomaly detection. Interestingly, we find that in the multi-source transfer learning scenario clustering on the target dataset and identifying subdomains in the …

Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak

Honors Capstones

In this research project, natural language processing techniques’ ability to accurately classify medical text was measured to reinforce the relevance of artificial intelligence in the medical field. Sentiment analyses (analyses to determine whether the text was positive or negative) were performed on the prescription drug reviews in an open-source dataset using four different models: lexical, a neural network, a support vector machine, and a logistic regression model. Each model’s effectiveness was gauged by its ability to correctly classify unlabeled drug reviews (i.e., a percentage representing accuracy). The machine learning models were able to accurately classify the text, while the lexical …

Algorithms For Compression Of Electrocardiogram Signals, Yuliyan Velchev

Books

The study is dedicated to modern methods and algorithms for compression of electrocardiogram (ECG) signals. In its original part, two lossy compression algorithms based on a combination of linear transforms are proposed. These algorithms are with relatively low computational complexity, making them applicable for implementation in low power designs such as mobile devices or embedded systems. Since the algorithms do not provide perfect signal reconstruction, they would find application in ECG monitoring systems rather than those intended for precision medical diagnosis.

This monograph consists of abstract, preface, five chapters and conclusion. The chapters are as follows: Chapter 1 — Introduction …

The History Of The Enigma Machine, Jenna Siobhan Parkinson

History Publications

The history of the Enigma machine begins with the invention of the rotor-based cipher machine in 1915. Various models for rotor-based cipher machines were developed somewhat simultaneously in different parts of the world. However, the first documented rotor machine was developed by Dutch naval officers in 1915. Nonetheless, the Enigma machine was officially invented following the end of World War I by Arthur Scherbius in 1918 (Faint, 2016).

Improving Adjacency List Storage Methods For Polypeptide Similarity Analysis, Arianna Swensen

Honors Theses

Protein design is a complex biomolecular and computational problem. Working on increasingly large protein folding problems requires an improvement in current analysis methods available. This work first discusses various methods of protein design, including de novo protein design, which is the primary focus of this thesis. Then, a new approach utilizing a B+ tree to effectively store and query a graph of keys and vertices is proposed in order to store the number of times two polypeptides are considered to be similar. This approach is found to have a reduction in time complexity from current mapping methods and thus provides …

An Empirical Study On The Classification Of Python Language Features Using Eye-Tracking, Jigyasa Chauhan

School of Computing: Dissertations, Theses, and Student Research

Python, currently one of the most popular programming languages, is an object-
oriented language that also provides language feature support for other programming
paradigms, such as functional and procedural. It is not currently understood how
support for multiple paradigms affects the ability of developers to comprehend that
code. Understanding the predominant paradigm in code, and how developers classify
the predominant paradigm, can benefit future research in program comprehension as
the paradigm may factor into how people comprehend that code. Other researchers
may want to look at how the paradigms in the code interact with various code smells.
To investigate how …

Scaling Epa-Rimm With Multicore System Management Interrupt Handlers, Alexander K. Freed

Dissertations and Theses

Continuous runtime integrity measurement mechanisms (RIMMs) can be used for timely detection of kernel and hypervisor rootkits. Researchers have proposed running RIMMs in privileged execution environments, such as the x86 architecture’s System Management Mode (SMM), to detect interference from rootkits that have gained control of the host operating system. However, the extended amount of time in SMM required to perform inspections can cause severe disruption to the host. A previously proposed RIMM design called EPA-RIMM addresses this by decomposing long inspections across multiple System Management Interrupts (SMI), the interrupt used to invoke SMM.

EPA-RIMM is intended for deployment on server-class …

Gc-308 Heart Disease Prediction And Analysis By Machine Learning, Venkata Sabarinath Nekkalapu, Venkata Anusha Yammada, Mrinal Kapoor, Sai Sindhu Ponugoti, Suman Pudota

C-Day Computing Showcase

The heart is the most crucial part of the Human body. The organ circulates blood out of the circulatory system’s blood vessels. Any disease or failure of this organ causes death. Heart disease is one of the primary sources of death in the cutting-edge world. There are 2,380 deaths from heart disease each day, based on 2018 data. Also, heart disease causes the highest number of deaths globally, with approximately 18 million people dying yearly, meaning around 31This prediction can be made using Machine Learning techniques. With machine learning. Combining a prediction model with machine learning correctly classified results for …

Gr-267 Churn Prediction, Manoj Kumar Dasari, Nikhil Thota, Dinesh Kumar Thota, Rishi Sai Basava, Prudhvi Kalyan Sai Sugguna

C-Day Computing Showcase

Employee churn is a situation where people leave the organization voluntarily or involuntarily. This has become a serious problem in recent times. We have also seen that attrition rates in several industries are going high. So, it is very much required to understand and analyze the reason behind attrition and why this is happening. We must conduct an analysis to know what the factors affecting employee churn are. It will create a huge impact on the organization if the attrition rate goes high. In order to resolve this issue, we are trying to take up this issue and find the …

Gr-283 Chatbot, Vamsi Krishna Dhulipalla

C-Day Computing Showcase

Mental health issue are the most common issue facing in human society. These issues are mostly in impact negatively on working peoples, on the individual, his/her family, workplace, community, and the economy. Our project is based on mental health chat bot of natural language processing with deep learning models .We have a structure data set of Mental Health. In the data set we have nine columns. We use neural networks to create our models .We use another method call scratch in which we create a model by our self and use it so our project we create a layer with …

Gr-303 Dempster-Shafer Theory Of Computation, Dhanunjai Bandi, Sandeep Eadara, Sri Manju Nannapaneni, Jayanth Kumar Rayavarapu, Taraka Vishnu Yarlagadda

C-Day Computing Showcase

To implement the Dempster-Shafer Theory algorithm as well as check the prediction accuracy using this mentioned algorithm in the iris dataset. The actual aim of this paper is to understand and implement the Dempster-Shafer Theory using the python programming language. To reflect doubt and inaccuracies in the evidence, one might use a belief structure that is defined as a set function m that satisfies. The conjecture of this report is to get the closable prediction accuracy that can help to understand future improvement as well as the gap of the applied implementation techniques

Uc-247 Wild Fire: Friend Or Foe, Christian R. Henderson, Revian C. Jennings, Kwentin Shelton

C-Day Computing Showcase

The U.S. Army Corp of Engineers in Carters Lake required a game that attempts to educate on the principles of both prescribed and non-prescribed fires. They request that the game be playable on an android device housed in a HOLOFIL holographic display. Additionally, it needed to be created in the mirrored format as the projection flips everything. We decided to use Unity Real-Time Development Platform to complete the game’s development. Unity is a set of tools to give content creators an all-in-one development environment that helps content creators develop games and applications. “Unity is royalty-free and does not charge on …

Gc-311 Singsingmarketplace.Com: E-Commerce Marketplace For Remote Vendors, Daniel K. Tor, Ebikela Ogegbene-Ise

C-Day Computing Showcase

American residents in the (Nigerian, Liberian, Indian, Ghanaian, etc.) Diaspora have strong ties back home and as such support loved ones, back home, on a regular basis, by sending cash remittances through Western Union, MoneyGram, etc. Remittances are expensive. Remitters have no control over how funds are spent once received. Remitters cannot send small amounts because the fees cannot be justified. We built a marketplace platform that allows the Diaspora to remit goods and services, instead of sending money to relatives back home in. The objectives are to remove or greatly reduce the cost of remittances, give more control to …

Gr-241 On Training Explainable Neurons, Lance Kennedy

C-Day Computing Showcase

Neural networks have become increasingly powerful and commonplace tools for guiding decision-making. However, due to the black-box nature of many of these networks, it is often difficult to understand exactly what guides them to a certain prediction, making them dangerous to use for sensitive decision making, and making it difficult to ensure confidence in their output. For instance, a network which classifies images of dogs and cats may turn out to be flawed with little consequence, but a neural network that diagnoses the presence of diseases should be assured to make sound predictions. By understanding why a network makes the …