Computer Sciences Commons^™

"Negative" Results -- When The Measured Quantity Is Outside The Sensor's Range -- Can Help Data Processing, Jonatan Contreras, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich, Martine Ceberio

Departmental Technical Reports (CS)

In many real-life situations, we know the general form of the dependence y = f(x, c₁, ..., c_m) between physical quantities, but the values need to be determined experimentally, based on the results of measuring x and y. In some cases, we do not get any result of measuring y since the actual value is outside the range of the measuring instrument. Usually, such cases are ignored. In this paper, we show that taking these cases into account can help data processing -- by improving the accuracy of our estimates of c_i and thus, …

So How To Make Group Decisions? Arrow's Impossibility Theorem 70 Years After, Hung T. Nguyen, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In 1951, Kenneth Arrow proved that it is not possible to have a group decision making procedure that satisfies reasonable requirements like fairness. From the theoretical viewpoint, this is a great result -- well-deserving the Nobel Prize that was awarded to Professor Arrow. However, from the practical viewpoint, the question remains -- so how should we make group decisions? A usual way to solve this problem is to provide some reasonable heuristic ideas, but the problem is that different seemingly reasonable idea often lead to different group decision -- this is known, e.g., for different voting schemes. In this paper, …

Knot Theory In Virtual Reality, Donald Lee Price

Masters Theses & Specialist Projects

Throughout the study of Knot Theory, there have been several programmatic solutions to common problems or questions. These solutions have included software to draw knots, software to identify knots, or online databases to look up pre-computed data about knots. We introduce a novel prototype of software used to study knots and links by using Virtual Reality. This software can allow researchers to draw links in 3D, run physics simulations on them, and identify them. This technique has not yet been rigorously explored and we believe it will be of great interest to Knot Theory researchers. The computer code is written …

Examining The Effects Of Race On Human-Ai Cooperation, Akil A. Atkins, Christopher L. Dancy, Matthew S. Brown

Faculty Conference Papers and Presentations

Recent literature has shown that racism and implicit racial biases can affect one’s actions in major ways, from the time it takes police to decide whether they shoot an armed suspect, to a decision on whether to trust a stranger. Given that race is a social/power construct, artifacts can also be racialized, and these racialized agents have also been found to be treated differently based on their perceived race. We explored whether people’s decision to cooperate with an AI agent during a task (a modified version of the Stag hunt task) is affected by the knowledge that the AI agent …

Material Detection With Thermal Imaging And Computer Vision: Potentials And Limitations, Jared Poe

Graduate Theses and Dissertations

The goal of my masters thesis research is to develop an affordable and mobile infraredbased environmental sensoring system for the control of a servo motor based on material identification. While this sensing could be oriented towards different applications, my thesis is particularly interested in material detection due to the wide range of possible applications in mechanical engineering. Material detection using a thermal mobile camera could be used in manufacturing, recycling or autonomous robotics. For my research, the application that will be focused on is using this material detection to control a servo motor by identifying and sending control inputs based …

Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning, Laxmi Prasad Poudel

Graduate Theses and Dissertations

This dissertation proposes a novel cooperative 3D printing (C3DP) approach for multi-robot additive manufacturing (AM) and presents scheduling and planning strategies that enable multi-robot cooperation in the manufacturing environment. C3DP is the first step towards achieving the overarching goal of swarm manufacturing (SM). SM is a paradigm for distributed manufacturing that envisions networks of micro-factories, each of which employs thousands of mobile robots that can manufacture different products on demand. SM breaks down the complicated supply chain used to deliver a product from a large production facility from one part of the world to another. Instead, it establishes a network …

What Fuzzy And Quantum Computing Can Learn From The Success Of Deep Learning, Shahnaz Shahbazova, Vladik Kreinovich

Departmental Technical Reports (CS)

How can we apply the ideas that made deep neural networks successful to other aspects of computing? For this purpose, we reformulate these ideas in a more general form -- and we show that this generalization also covers fuzzy and quantum computing. This enables us to suggest that similar ideas can be helpful for fuzzy and quantum computing as well. In this suggestion, we are encouraged by the fact that as we show, to some extent, these ideas are already helpful.

Why Quantum Techniques Are A Good First Approximation To Economic Phenomena, And What Next, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

Somewhat surprisingly, several formulas of quantum physics -- the physics of micro-world -- provide a good first approximation to many social phenomena, in particular, to many economic phenomena, phenomena which are very far from micro-physics. In this paper, we provide three possible explanations for this surprising fact. First, we show that several formulas from quantum physics actually provide a good first-approximation description for many phenomena in general, not only to the phenomena of micro-physics. Second, we show that some quantum formulas represent the fastest way to compute nonlinear dependencies and thus, naturally appear when we look for easily computable models; …

Integrimi I Sistemit Të Menaxhimit Dixhital Të Pasurive Të Patundshme Bazuar Në Arkitekturën E Pastërt Mvc, Mynevere Hyseni

Theses and Dissertations

Integrimi i sistemit të menaxhimit dixhital të pasurive të patundshme është shumë i rëndësishëm për menaxhim të mbarë të pasurive të patundshme dhe pozicionimin e tyre në treg si dhe luan rol të veçantë në sigurimin e avantazhit të një kompanie ose të një individi të vetëm ndaj konkurrentëve. Kur një individ apo kompani dëshiron të shes/jep me qira ndonjë pasuri të vetën, është mjaft e nevojshme që ta prezantojnë atë me botën në mënyrë të zhurmshme. Po ashtu në anën tjetër kur ndonjë individ dëshiron të blej/marr me qira ndonjë pronë kërkon mundësi më të lehtë dhe më të …

Analizë E Testimit Të Aplikacioneve Të Telefonave Mobile, Deliza Muharremaj

Theses and Dissertations

Testimi i aplikacioneve softuerike është një proces i cili shërben për të kontrolluar nëse aplikacioni është pa gabime ose jo. Është proces i verifikimit dhe vlerësimit të shërbimeve softuerike, duke kontrolluar nëse aplikacioni softuerik është duke i plotësuar kërkesat e përdoruesit dhe nëse funksionon sipas karakteristikave. Qëllimi i testimit është të identifikojë gabimet, boshllëqet ose kërkesat që mungojnë në raport me kërkesat aktuale.

Testimi është i rëndësishëm sepse nëse ka ndonjë gabim ai mund të identifikohet herët dhe mund të zgjidhet para dorëzimit përfundimtar të produktit. Testimi i aplikacioneve mobile është një grumbullim i aktiviteteve të lidhuara për gjetjen e …

Zhvillimi I Seo-S Ndër Vite, Berna Zehri

Theses and Dissertations

Duke e pasur parasysh kërkesat e bizneseve që të jenë më të ekspozuara në rrjetet sociale dhe në motorët e kërkimit si Google, thuhet që SEO është thelbësore që të ndihmojë të arrihen shumë nga qëllimet e bizneseve. SEO (Search Engine Optimization) ndihmon të krijohen marrëdhënie më të mira me audiencën, të përmirësohet përvoja e klientit, rrit autoritetin e biznesit, ndihmon në rritjen e klikimeve në faqe, jep përparësi ndaj konkurrencës dhe i rrit konvertimet, që do të thotë më shumë shitje, klientë më besnikë dhe më shumë rritje për bizneset e fushave te ndryshme.

Në këtë punim, analizohet zhvillimi …

Inteligjenca Artificiale (Ai) - Benefitet Dhe Frika Ndaj Së Ardhmës, Ardit Azemi

Theses and Dissertations

Këtë temë diplome e kam përzgjedhur sepse është teknologji relativisht e re, inteligjenca artificiale është e ardhmja e njerëzimit, dhe në një të ardhme të afërt do ju ndihmoj shumë njerëzve duke u lehtuar shumë punë, mirëpo ekziston edhe frika se mos do i zëvendësoj në disa raste të caktuara edhe vet njerëzit, pra punën të cilën ata bëjnë, pa dyshim në disa fusha përkatëse do të ketë ndikim revulucionar.

Pasiqë është një teknologji e cila ka një degëzim shumë të gjerë po thuajse në çdo sferë të jetës dhe po ashtu për shumë kë termi “Inteligjencë Artificiale” është i …

Zhvillimi I Një Ueb Aplikacioni Duke Përdorur Arkitekturën E Mikroserviseve Dhe Kubernetes, Fisnik Zejnullahu

Theses and Dissertations

Në këtë punim diplome do të shqyrtohen mënyrat e ndryshme që përdoren për zhvillimin e aplikacioneve, e sidomos do të shqyrtohen mënyrat dhe teknologjitë moderne që po përdoren dhe që janë të preferueshme të përdoren në ditët e sotme. Lexuesi në fillim do të njoftohet me një hyrje rreth mënyrave dhe teknologjive që përdoren për zhvillimin e aplikacioneve, pastaj do të njoftohet me problemet dhe vështirësitë rreth zhvillimit të aplikacioneve e si mund t’i zgjidhim ato probleme. Do të vazhdohet me shqyrtimin e literaturës për këto teknologji, dhe diskutimi më në detaje rreth tyre. Do të flasim për të mirat …

Insights And Lessons Learned From The Design, Development And Deployment Of Pervasive Location-Based Mobile Systems “In The Wild”, Konstantinos Papangelis, Alan Chamberlain, Nicolas Lalone, Ting Cao

Presentations and other scholarship

This paper, based on a reflective approach, presents several insights and lessons learned from the design, development, and deployment of a location-based social network and a location-based game. These are analyzed and discussed against the life-cycle of our studies and range from engaging with the participants to dealing with technical issues while on the field. Overall, the insights and lessons learned illustrate that one should be prepared and flexible enough to accommodate any issues as they arise in a professional manner considering not only the results of the study but also the participants and the researchers involved.The aim of this …

Self-Supervised Contrastive Learning For Code Retrieval And Summarization Via Semantic-Preserving Transformations, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

We propose Corder, a self-supervised contrastive learning framework for source code model. Corder is designed to alleviate the need of labeled data for code retrieval and code summarization tasks. The pre-trained model of Corder can be used in two ways: (1) it can produce vector representation of code which can be applied to code retrieval tasks that do not have labeled data; (2) it can be used in a fine-tuning process for tasks that might still require label data such as code summarization. The key innovation is that we train the source code model by asking it to recognize similar …

A Mean-Field Markov Decision Process Model For Spatial-Temporal Subsidies In Ride-Sourcing Markets, Zheng Zhu, Jintao Ke, Hai Wang

Research Collection School Of Computing and Information Systems

Ride-sourcing services are increasingly popular because of their ability to accommodate on-demand travel needs. A critical issue faced by ride-sourcing platforms is the supply-demand imbalance, as a result of which drivers may spend substantial time on idle cruising and picking up remote passengers. Some platforms attempt to mitigate the imbalance by providing relocation guidance for idle drivers who may have their own self-relocation strategies and decline to follow the suggestions. Platforms then seek to induce drivers to system-desirable locations by offering them subsidies. This paper proposes a mean-field Markov decision process (MF-MDP) model to depict the dynamics in ride-sourcing markets …

Meta-Inductive Node Classification Across Graphs, Zhihao Wen, Yuan Fang, Zemin Liu

Research Collection School Of Computing and Information Systems

Semi-supervised node classification on graphs is an important research problem, with many real-world applications in information retrieval such as content classification on a social network and query intent classification on an e-commerce query graph. While traditional approaches are largely transductive, recent graph neural networks (GNNs) integrate node features with network structures, thus enabling inductive node classification models that can be applied to new nodes or even new graphs in the same feature space. However, inter-graph differences still exist across graphs within the same domain. Thus, training just one global model (e.g., a state-of-the-art GNN) to handle all new graphs, whilst …

Marina: Faster Non-Convex Distributed Learning With Compression, Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtarik

Research Collection School Of Computing and Information Systems

We develop and analyze MARINA: a new communication efficient method for non-convex distributed learning over heterogeneous datasets. MARINA employs a novel communication compression strategy based on the compression of gradient differences that is reminiscent of but different from the strategy employed in the DIANA method of Mishchenko et al. (2019). Unlike virtually all competing distributed first-order methods, including DIANA, ours is based on a carefully designed biased gradient estimator, which is the key to its superior theoretical and practical performance. The communication complexity bounds we prove for MARINA are evidently better than those of all previous first-order methods. Further, we …

Deep Transfer Bug Localization, Xuan Huo, Ferdian Thung, Ming Li, David Lo, Shu-Ting Shi

Research Collection School Of Computing and Information Systems

Many projects often receive more bug reports than what they can handle. To help debug and close bug reports, a number of bug localization techniques have been proposed. These techniques analyze a bug report and return a ranked list of potentially buggy source code files. Recent development on bug localization has resulted in the construction of effective supervised approaches that use historical data of manually localized bugs to boost performance. Unfortunately, as highlighted by Zimmermann et al., sufficient bug data is often unavailable for many projects and companies. This raises the need for cross-project bug localization -- the use of …

Effect Of Team Cohesion Nn Flow: An Empirical Study Of Team-Based Gamification For Enterprise Resource Planning Systems In Online Classes, Yu Zhao, Mark Srite, Sumin Kim, Jinwoong Lee

Business and Information Technology Faculty Research & Creative Works

Pedagogy using gamification has recently received much attention as a way of enhancing student learning and retention. Additionally, academic institutions are making extensive use of online resources to expand teaching beyond the traditional classroom setting. Both academic institutions and companies utilize virtual teams to accomplish remote teamwork, particularly in a post-COVID environment. Despite the growing interest in incorporating gamification into teaching for business school courses, prior researchers have paid little attention to team-based gamification in the online learning environment. The purpose of this study is to examine if team members' perceived team cohesion influences their perceptions of flow. Also, we …

Improving Collection Understanding For Web Archives With Storytelling: Shining Light Into Dark And Stormy Archives, Shawn M. Jones

Computer Science Theses & Dissertations

Collections are the tools that people use to make sense of an ever-increasing number of archived web pages. As collections themselves grow, we need tools to make sense of them. Tools that work on the general web, like search engines, are not a good fit for these collections because search engines do not currently represent multiple document versions well. Web archive collections are vast, some containing hundreds of thousands of documents. Thousands of collections exist, many of which cover the same topic. Few collections include standardized metadata. Too many documents from too many collections with insufficient metadata makes collection understanding …

A Unified Framework For Parallel Anisotropic Mesh Adaptation, Christos Tsolakis

Computer Science Theses & Dissertations

Finite-element methods are a critical component of the design and analysis procedures of many (bio-)engineering applications. Mesh adaptation is one of the most crucial components since it discretizes the physics of the application at a relatively low cost to the solver. Highly scalable parallel mesh adaptation methods for High-Performance Computing (HPC) are essential to meet the ever-growing demand for higher fidelity simulations. Moreover, the continuous growth of the complexity of the HPC systems requires a systematic approach to exploit their full potential. Anisotropic mesh adaptation captures features of the solution at multiple scales while, minimizing the required number of elements. …

Deep Learning Approaches For Seagrass Detection In Multispectral Imagery, Kazi Aminul Islam

Electrical & Computer Engineering Theses & Dissertations

Seagrass forms the basis for critically important marine ecosystems. Seagrass is an important factor to balance marine ecological systems, and it is of great interest to monitor its distribution in different parts of the world. Remote sensing imagery is considered as an effective data modality based on which seagrass monitoring and quantification can be performed remotely. Traditionally, researchers utilized multispectral satellite images to map seagrass manually. Automatic machine learning techniques, especially deep learning algorithms, recently achieved state-of-the-art performances in many computer vision applications. This dissertation presents a set of deep learning models for seagrass detection in multispectral satellite images. It …

Quantifying Cyber Risk By Integrating Attack Graph And Impact Graph, Omer F. Keskin

Engineering Management & Systems Engineering Theses & Dissertations

Being a relatively new risk source, models to quantify cyber risks are not well developed; therefore, cyber risk management in most businesses depends on qualitative assessments. With the increase in the economic consequences of cyber incidents, the importance of quantifying cyber risks has increased. Cyber risk quantification is also needed to establish communication among decision-makers of different levels of an enterprise, from technical personnel to top management.

The goal of this research is to build a probabilistic cybersecurity risk analysis model that relates attack propagation with impact propagation through internal dependencies and allows temporal analysis.

The contributions of the developed …

Numerical Approaches Of Pricing European Options In The Cox-Ross-Rubenstein Models, Hai Phan, Seonguk Kim Phd

Annual Student Research Poster Session

The Cox-Ross-Rubinstein (CRR) market mode is used to price European and American Options without complex elements, including dividends, stocks, and stock indexes paying a continuous dividend yield, futures, and currency options. The model is an elegant, simple, but strong model to explain the general economic intuition behind option pricing and its principal techniques. In the paper, the CRR model's numerical elements and equations are indicated, and a practical event is examined to demonstrate the application of the model in the financial market. To make it easier to understand, figures, including tables and graphs, are also included to visualize and simplify …

Ivy Plot: Enhancing A Dot Plot By Representing Observations As Leaflets, Tri Ha Minh Nguyen '23, Mamunur Rashid, Jyotirmoy Sarkar

Student Research

For a large data set, a dot plot poses a challenge—albeit unintended—in counting the dots. To overcome this shortcoming Sarkar and Rashid (2021) proposed an IVY plot, which represents tied data in batches of five by depicting an IVY leaf with five leaflets. These leaves are bottom-justified and stacked vertically, with the topmost leaf possibly having fewer than five leaflets, until the number of leaflets equals the frequency at each value

The Design Of A Framework For The Detection Of Web-Based Dark Patterns, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney, Ioannis Stavrakakis

Conference Papers

In the theories of User Interfaces (UI) and User Experience (UX), the goal is generally to help understand the needs of users and how software can be best configured to optimize how the users can interact with it by removing any unnecessary barriers. However, some systems are designed to make people unwillingly agree to share more data than they intend to, or to spend more money than they plan to, using deception or other psychological nudges. User Interface experts have categorized a number of these tricks that are commonly used and have called them Dark Patterns. Dark Patterns are varied …

Developing An Effective Targeted Mobile Application To Enhance Transportation Safety And Use Of Active Transportation Modes In Fresno County: The Role Of Application Design & Content, Samer Sarofim

Mineta Transportation Institute

Do pedestrians and cyclists need their own app? Pedestrians and cyclists in Fresno county think so, and this research examined this need and how it relates to the importance of app design. Survey participants (all who regularly use active transportation modes) along with a variety of transportation stakeholders, including the Fresno Council of Government, the California Department of Transportation (Caltrans) District 6, and the City of Fresno — Public Works Department, indicated the importance of designing effective communication tools to enhance the utilization of active transportation modes and to ensure the safety of vulnerable road users. In this study, over …

Mobile Application To Travel The World Using Virtual Reality And Machine Learning, Valentina Quiroga, Francisco Olivares, José Najera

ICT

This research intends to make travel and culture an accessible possibility for all. With a phone and a VRHeadset, people will have the opportunity to see some of the most amazing scenes in the world and learn about the history and culture of famous landmarks without leaving the comfort of their own homes.

Awegnn: Auto-Parametrized Weighted Element-Specific Graph Neural Networks For Molecules., Timothy Szocinski, Duc Duy Nguyen, Guo-Wei Wei

Mathematics Faculty Publications

While automated feature extraction has had tremendous success in many deep learning algorithms for image analysis and natural language processing, it does not work well for data involving complex internal structures, such as molecules. Data representations via advanced mathematics, including algebraic topology, differential geometry, and graph theory, have demonstrated superiority in a variety of biomolecular applications, however, their performance is often dependent on manual parametrization. This work introduces the auto-parametrized weighted element-specific graph neural network, dubbed AweGNN, to overcome the obstacle of this tedious parametrization process while also being a suitable technique for automated feature extraction on these internally complex …