University of Nebraska - Lincoln
Governors State University
Biola University
SUNY Fredonia
University of Pennsylvania
Bryant University
California State University, San Bernardino
Software Jimenae Allows Efficient Dynamic Simulations Of Boolean Networks, Centrality And System State Analysis,
2023
Biozentrum der Universität Würzburg
Software Jimenae Allows Efficient Dynamic Simulations Of Boolean Networks, Centrality And System State Analysis, Martin Kaltdorf, Tim Breitenbach, Stefan Karl, Maximilian Fuchs, David Komla Kessie, Eric Psota, Martina Prelog, Edita Sarukhanyan, Regina Ebert, Franz Jakob, Gudrun Dandekar, Muhammad Naseem, Chunguang Liang, Thomas Dandekar
All Works
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity …
Predicting New Crescent Moon Visibility Applying Machine Learning Algorithms,
2023
Abu Dhabi University
Predicting New Crescent Moon Visibility Applying Machine Learning Algorithms, Murad Al-Rajab, Samia Loucif, Yazan Al Risheh
All Works
The world's population is projected to grow 32% in the coming years, and the number of Muslims is expected to grow by 70%—from 1.8 billion in 2015 to about 3 billion in 2060. Hijri is the Islamic calendar, also known as the lunar Hijri calendar, which consists of 12 lunar months, and it is tied to the Moon phases where a new crescent Moon marks the beginning of each month. Muslims use the Hijri calendar to determine important dates and religious events such as Ramadan, Haj, Muharram, etc. Till today, there is no consensus on deciding on the beginning of …
Key Communication Technologies, Applications, Protocols And Future Guides For Iot-Assisted Smart Grid Systems: A Review,
2023
Edith Cowan University
Key Communication Technologies, Applications, Protocols And Future Guides For Iot-Assisted Smart Grid Systems: A Review, Md Ohirul Qays, Iftekhar Ahmad, Ahmed Abu-Siada, Md Liton Hossain, Farhana Yasmin
Research outputs 2022 to 2026
Towards addressing the concerns of conventional power systems including reliability and security, establishing modern Smart Grids (SGs) has been given much attention by the global electric utility applications during the last few years. One of the key advantageous of SGs is its ability for two-way communication and bi-directional power flow that facilitates the inclusion of distributed energy resources, real time monitoring and self-healing systems. As such, the SG employs a large number of digital devices that are installed at various locations to enrich the observability and controllability of the system. This calls for the necessity of employing Internet of Things …
Form Auto Generation: An Analysis Of Gui Generation,
2023
University of Nebraska at Omaha
Form Auto Generation: An Analysis Of Gui Generation, Jedadiah Mcfarland
Theses/Capstones/Creative Projects
Graphical User Interfaces (GUIs) have transformed how we interact with computers, offering visually appealing and intuitive systems. This paper explores the origins and evolution of GUIs, explicitly focusing on form auto-generation in modern GUI-driven environments. Form auto-generation has emerged as a prominent practice, enabling automatic form creation based on predefined models. To better understand form auto-generation, I investigate SurveyJS, an open-source form auto-generation library known for its active development and support. This investigation aims to understand how SurveyJS recognizes and renders objects from a JSON model. The methodology involves a trial and error examination of the library, exploring its live …
Constrained Route Optimization With Fleet Considerations For Electrified Heavy-Duty Freight Vehicles,
2023
Utah State University
Constrained Route Optimization With Fleet Considerations For Electrified Heavy-Duty Freight Vehicles, Zarin Subah Shamma
All Graduate Theses and Dissertations
Almost 75% of traffic-related emissions are caused by heavy-duty freight trucks and significantly impact neighborhoods, schools, and communities around shipping and distribution lines. With poor air quality and respiratory health, many children in at-risk and disadvantaged communities experience high rates of asthma, lower attendance in school, and lower concentration. This research creates to improve the impacts of heavy-duty electric freight by improving the route efficiency (in terms of energy, time, or route distance) of EV trucks. Our software and algorithms are tested in a simulation environment using data from several thousand fleet trucks operating in the Salt Lake City area. …
Towards Intelligent Runtime Framework For Distributed Heterogeneous Systems,
2023
Old Dominion University
Towards Intelligent Runtime Framework For Distributed Heterogeneous Systems, Polykarpos Thomadakis
Computer Science Theses & Dissertations
Scientific applications strive for increased memory and computing performance, requiring massive amounts of data and time to produce results. Applications utilize large-scale, parallel computing platforms with advanced architectures to accommodate their needs. However, developing performance-portable applications for modern, heterogeneous platforms requires lots of effort and expertise in both the application and systems domains. This is more relevant for unstructured applications whose workflow is not statically predictable due to their heavily data-dependent nature. One possible solution for this problem is the introduction of an intelligent Domain-Specific Language (iDSL) that transparently helps to maintain correctness, hides the idiosyncrasies of lowlevel hardware, and …
Cyber Attack Surface Mapping For Offensive Security Testing,
2023
Clemson University
Cyber Attack Surface Mapping For Offensive Security Testing, Douglas Everson
All Dissertations
Security testing consists of automated processes, like Dynamic Application Security Testing (DAST) and Static Application Security Testing (SAST), as well as manual offensive security testing, like Penetration Testing and Red Teaming. This nonautomated testing is frequently time-constrained and difficult to scale. Previous literature suggests that most research is spent in support of improving fully automated processes or in finding specific vulnerabilities, with little time spent improving the interpretation of the scanned attack surface critical to nonautomated testing. In this work, agglomerative hierarchical clustering is used to compress the Internet-facing hosts of 13 representative companies as collected by the Shodan search …
The Internet Of Things (Iot) In Healthcare: Taking Stock And Moving Forward,
2023
Edith Cowan University
The Internet Of Things (Iot) In Healthcare: Taking Stock And Moving Forward, Abderahman Rejeb, Karim Rejeb, Horst Treiblmaier, Andrea Appolloni, Salem Alghamdi, Yaser Alhasawi, Mohammad Iranmanesh
Research outputs 2022 to 2026
Recent improvements in the Internet of Things (IoT) have allowed healthcare to evolve rapidly. This article summarizes previous studies on IoT applications in healthcare. A comprehensive review and a bibliometric analysis were performed to objectively summarize the growth of IoT research in healthcare. To begin, 2,990 journal articles were carefully selected for further investigation. These publications were analyzed based on various bibliometric metrics, including publication year, journals, authors, institutions, and countries. Keyword co-occurrence and co-citation networks were generated to unravel significant research hotspots. The findings show that IoT research has received considerable interest from the healthcare community. Based on the …
Theme Park Visitors Prefer Human-Like Robots In Customer Service Interactions,
2023
University of Central Florida
Theme Park Visitors Prefer Human-Like Robots In Customer Service Interactions, Ady Milman, Asli D.A. Tasci
Rosen Research Review
Service robots are becoming increasingly popular in many industries and social settings, including education, childcare, elderly therapy centers, and even theme parks. Tourism and hospitality industries are adopting robots enthusiastically and are being closely studied to observe guest engagement and reaction to robotic services. Service robots are becoming increasingly popular in many industries and social settings, including education, childcare, elderly therapy centers, and even theme parks. Tourism and hospitality industries are adopting robots enthusiastically and are being closely studied to observe guest engagement and reaction to robotic services. UCF Rosen College of Hospitality Management researchers, Dr. Ady Milman and Dr. …
Robust And Parallel Segmentation Model (Rpsm) For Early Detection Of Skin Cancer Disease Using Heterogeneous Distributions,
2023
Department of Computer Sciences, Faculty of Science, Beirut Arab University, Lebanon
Robust And Parallel Segmentation Model (Rpsm) For Early Detection Of Skin Cancer Disease Using Heterogeneous Distributions, Nancy Zreika, Ali El-Zaart, Abdallah El Chakik
BAU Journal - Science and Technology
Melanoma is the most common dangerous type of skin cancer; however, it is preventable if it is diagnosed early. Diagnosis of Melanoma would be improved if an accurate skin image segmentation model is available. Many computer vision methods have been investigated, yet the problem of finding a consistent and robust model that extracts the best threshold value, persists. This paper suggests a novel image segmentation approach using a multilevel cross entropy thresholding algorithm based on heterogeneous distributions. The proposed strategy searches the problem space by segmenting the image into several levels, and applying for each level one of the three …
Economic Value Of User Interface Design,
2023
University of Nebraska-Lincoln
Economic Value Of User Interface Design, Anna Kruse
Honors Theses, University of Nebraska-Lincoln
The economic value of well-designed user interfaces (UI) and user experiences (UX) is challenging to quantify, a topic that the current literature does not sufficiently explore. Those responsible for deciding whether to invest resources in UI/UX typically base these decisions on monetary considerations. The link between effective UI/UX design and profit may not be immediately clear to most, yet it is universally acknowledged that satisfied customers lead to successful business. To underscore the importance of investing in UI/UX, it is crucial to define the relationship between effective design and economic success in a way that can be understood by designers, …
Harnessing Artificial Intelligence For Early And Evolution Of Alzheimer’S Disease Detections And Enhancing Senior Mental Health Through Innovative Art-Singing Therapies: A Multidisciplinary Approach,
2023
Laval University
Harnessing Artificial Intelligence For Early And Evolution Of Alzheimer’S Disease Detections And Enhancing Senior Mental Health Through Innovative Art-Singing Therapies: A Multidisciplinary Approach, Jocelyne Kiss, Geoffreyjen Edwards, Rachel Bouserhal, Elaine Champagne, Thierry Belleguic, Valéry Psyché, Charles Batcho, Carol Hudon, Sylsvie Ratté, Ingrid Verdruyckt, Marie-Hélène Parizeau, Aaron Liu-Rosenbaum, James Hudson, Marie-Louise Bourbeau, Marie Lemieux, Annik Charbonneau
Faculty Scholarship
The well-documented therapeutic potential of group singing for patients living with Alzheimer’s disease (PLAD) has been hindered by COVID-19 restrictions, exacerbating loneliness and cognitive decline among seniors in residential and long-term care centers (CHSLDs). Addressing this challenge, the multidisciplinary study aims to develop a patient-oriented virtual reality (XR) interaction system facilitating group singing for mental health support during confinement and enhancing the understanding of the links between Alzheimer’s disease, social interaction, and singing. The researchers also propose to establish an early AD detection system using voice, facial, and non-invasive biometric measurements and validate the efficacy of selected intervention practices. The …
Possible Attacks On Match-In-Database Fingerprint Authentication,
2023
University of Minnesota Morris
Possible Attacks On Match-In-Database Fingerprint Authentication, Jadyn Sondrol
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Biometrics are used to help keep users’ data private. There are many different biometric systems, all dealing with a unique attribute of a user, such as fingerprint, face, retina, iris and voice recognition. Fingerprint biometric systems, specifically match-in-database, have universally become the most implemented biometric system. To make these systems more secure, threat models are used to identify potential attacks and ways to mitigate them. This paper introduces a threat model for match-in-database fingerprint authentication systems. It also describes some of the most frequent attacks these systems come across and some possible mitigation efforts that can be adapted to keep …
Probing As A Technique To Understand Abstract Spaces,
2023
University of Minnesota Morris
Probing As A Technique To Understand Abstract Spaces, Ashlen A. Plasek
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Machine learning models, while very powerful, have their operation obfuscated behind millions of parameters. This obfuscation can make deriving a human meaningful process from a machine learning model very difficult. However, while the intermediate states of a machine learning model are similarly obfuscated, using probing, we can start to explore looking at possible structure in those intermediate states. Large language models are a prime example of this obfuscation, and probing can begin to allow novel experimentation to be performed.
Deep-Learning Realtime Upsampling Techniques In Video Games,
2023
University of Minnesota Morris
Deep-Learning Realtime Upsampling Techniques In Video Games, Biruk Mengistu
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
This paper addresses the challenge of keeping up with the ever-increasing graphical complexity of video games and introduces a deep-learning approach to mitigating it. As games get more and more demanding in terms of their graphics, it becomes increasingly difficult to maintain high-quality images while also ensuring good performance. This is where deep learning super sampling (DLSS) comes in. The paper explains how DLSS works, including the use of convolutional autoencoder neural networks and various other techniques and technologies. It also covers how the network is trained and optimized, as well as how it incorporates temporal antialiasing and frame generation …
Lidar Segmentation-Based Adversarial Attacks On Autonomous Vehicles,
2023
University of Minnesota Morris
Lidar Segmentation-Based Adversarial Attacks On Autonomous Vehicles, Blake Johnson
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Autonomous vehicles utilizing LiDAR-based 3D perception systems are susceptible to adversarial attacks. This paper focuses on a specific attack scenario that relies on the creation of adversarial point clusters with the intention of fooling the segmentation model utilized by LiDAR into misclassifying point cloud data. This can be translated into the real world with the placement of objects (such as road signs or cardboard) at these adversarial point cluster locations. These locations are generated through an optimization algorithm performed on said adversarial point clusters that are introduced by the attacker.
Https://Www.Cambridge.Org/Core/Journals/Theory-And-Practice-Of-Logic-Programming/Article/System-Predictor-Grounding-Size-Estimator-For-Logic-Programs-Under-Answer-Set-Semantics/9ee3d47f0dcda77e39328e53b0816cd9#:~:Text=System%20predictor%3a%20grounding%20size%20estimator%20for%20logic%20programs%20under%20answer%20set%20semantics,
2023
University of Nebraska at Omaha
Https://Www.Cambridge.Org/Core/Journals/Theory-And-Practice-Of-Logic-Programming/Article/System-Predictor-Grounding-Size-Estimator-For-Logic-Programs-Under-Answer-Set-Semantics/9ee3d47f0dcda77e39328e53b0816cd9#:~:Text=System%20predictor%3a%20grounding%20size%20estimator%20for%20logic%20programs%20under%20answer%20set%20semantics, Daniel Bresnahan, Nicholas Hippen, Yuliya Lierler
Computer Science Faculty Publications
Answer set programming is a declarative logic programming paradigm geared towards solving difficult combinatorial search problems. While different logic programs can encode the same problem, their performance may vary significantly. It is not always easy to identify which version of the program performs the best. We present the system PREDICTOR (and its algorithmic backend) for estimating the grounding size of programs, a metric that can influence a performance of a system processing a program. We evaluate the impact of PREDICTOR when used as a guide for rewritings produced by the answer set programming rewriting tools PROJECTOR and LPOPT. The results …
The Use Of Artificial Intelligence In Higher Education: A Study On Faculty Perspectives In Universities In Egypt,
2023
American University in Cairo
The Use Of Artificial Intelligence In Higher Education: A Study On Faculty Perspectives In Universities In Egypt, Farah S. Sharawy
Theses and Dissertations
Artificial Intelligence (AI) is an emerging technology that is transforming various aspects of society, including higher education. This paper examines faculty perspectives from five different institutions; The American University in Cairo (AUC), The German University in Cairo (GUC), The Arab Academy for Science and Technology (AAST), Ain Shams University, and Cairo University, on the use of AI in higher education in teaching and learning in Egypt, with all its challenges and resources available to support it, and how it can be used to achieve equity and accessibility. This research was conducted through a qualitative study using semi-structured one- on-one interviews …
Performance Analysis Of Deep-Learning Based Open Set Recognition Algorithms For Network Intrusion Detection Systems,
2023
Army Cyber Institute, U.S. Military Academy
Performance Analysis Of Deep-Learning Based Open Set Recognition Algorithms For Network Intrusion Detection Systems, Gaspard Baye, Priscila Silva, Alexandre Broggi, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul
ACI Journal Articles
Open Set Recognition (OSR) is the ability of a machine learning (ML) algorithm to classify the known and recognize the unknown. In other words, OSR enables novelty detection in classification algorithms. This broader approach is critical to detect new types of attacks, including zero-days, thereby improving the effectiveness and efficiency of various ML-enabled mission-critical systems, such as cyber-physical, facial recognition, spam filtering, and cyber defense systems such as intrusion detection systems (IDS). In ML algorithms, like deep learning (DL) classifiers, hyperparameters control the learning process; their values affect other model parameters, such as weights and biases, which affect the performance …
The Power Of (Virtual) Convergence: The Unrealized Potential Of Pair Programming And Remote Work,
2023
Portland State University
The Power Of (Virtual) Convergence: The Unrealized Potential Of Pair Programming And Remote Work, Mikayla Maki
University Honors Theses
Remote work is expensive. It can lead to isolation, miscommunications, and ossified organizations. These problems occur because of a synchronicity mismatch between how we need to communicate as humans, and what today's tools are capable of. This mismatch can be solved by the adoption of remote pair programming, as exemplified by the authors work at a startup (Zed). Pair programming provides the organic, synchronous, reciprocal interaction necessary to develop the sorts of relationships that remote firms currently lack.
