Computer Sciences Commons^™

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, 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, 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, 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 …

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, 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 …

Topology Optimization For Artificial Neural Networks, Justin Mills

Masters Theses & Specialist Projects

This thesis examines the feasibility of implementing two simple optimization methods, namely the Weights Power method (Hagiwara, 1994) and the Tabu Search method (Gupta & Raza, 2020), within an existing framework. The study centers around the generation of artificial neural networks using these methods, assessing their performance in terms of both accuracy and the capacity to reduce components within the Artificial Neural Network’s (ANN) topology.

The evaluation is conducted on three classification datasets: Air Quality (Shahane, 2021), Diabetes (Soni, 2021), and MNIST (Deng, 2012). The main performance metric used is accuracy, which measures the network's predictive capability for the classification …

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. …

Web Based Management System For Housing Society, Likhitha Reddy Eddala

Electronic Theses, Projects, and Dissertations

Web Based Management System for Housing Society plays a major role in our day-to-day life. We develop a global web dependent application using AngularJS, Node JS and MySQL, with Xampp as the server to make an effective management system. This system is designed to provide a user-friendly and efficient platform for managing all the details of daily notices, monthly meetings, events, payments, maids etc., This system mainly consists of three modules, they are: Admin, User and Security. Each module here serves specific features and functionalities present within society. Admin module provides the features for managing user, houses, security, maids, notices, …

Fostering Human Dimension Of Smart Cities: Lessons From Jakarta For Nusantara, Indonesia’S New Capital City In The Making, Wicaksono Sarosa, Nurulitha Andini Susetyo, Marsa Nur Aulianisa, Mahbub Ridhoo Maulaa, Pradamas Giffary

Smart City

A city’s problems often arise as the population grows and urbanization happens. This process is linear to the development of information-and-communication technologies (ICT), especially in urban areas. As a result, cities have adopted an initiative to solve the problems which are popularly known as the smart city. Over decades, the idea of a smart city has evolved from a mere technological modernization to advanced utilization through community involvement. However, in practice, smart city ideas and initiatives often put a heavy emphasis on technical aspects and ignored the more human side, which has caused a digital divide. This paper argues that …

Enhanced Quantum Chemistry With Machine Learning, Brock Dyer

Physics and Astronomy Summer Fellows

This file is a catalogue of the relevant quantum mechanical and computer programming topics that I learned during the summer which will be helping me to generate an artificial intelligence that will be able to perform computational chemical calculations at a much faster rate and comparable or better accuracy than current methods.

On Training Neurons With Bounded Compilations, Lance Kennedy

Master of Science in Computer Science Theses

Knowledge compilation offers a formal approach to explaining and verifying the behavior of machine learning systems, such as neural networks. Unfortunately, compiling even an individual neuron into a tractable representation such as an Ordered Binary Decision Diagram (OBDD), is an NP-hard problem. In this thesis, we consider the problem of training a neuron from data, subject to the constraint that it has a compact representation as an OBDD. Our approach is based on the observation that a neuron can be compiled into an OBDD in polytime if (1) the neuron has integer weights, and (2) its aggregate weight is bounded. …

Sentiment Analysis Before And During The Covid-19 Pandemic, Emily Musgrove

Mathematics Summer Fellows

This study examines the change in connotative language use before and during the Covid-19 pandemic. By analyzing news articles from several major US newspapers, we found that there is a statistically significant correlation between the sentiment of the text and the publication period. Specifically, we document a large, systematic, and statistically significant decline in the overall sentiment of articles published in major news outlets. While our results do not directly gauge the sentiment of the population, our findings have important implications regarding the social responsibility of journalists and media outlets especially in times of crisis.

Interpretable Timbre Synthesis Using Variational Autoencoders Regularized On Timbre Descriptors, Anastasia Natsiou, Luca Longo, Sean O'Leary

Conference papers

Controllable timbre synthesis has been a subject of research for several decades, and deep neural networks have been the most successful in this area. Deep generative models such as Variational Autoencoders (VAEs) have the ability to generate a high-level representation of audio while providing a structured latent space. Despite their advantages, the interpretability of these latent spaces in terms of human perception is often limited. To address this limitation and enhance the control over timbre generation, we propose a regularized VAE-based latent space that incorporates timbre descriptors. Moreover, we suggest a more concise representation of sound by utilizing its harmonic …

How Technology May Be Used For Future Disease Predictions, Rich P. Manprisio

Journal of Applied Disciplines

Exasperated by the ongoing global pandemic, the healthcare system is grappling with the formidable challenges posed by proper and effective disease treatments. Nevertheless, amidst these growing difficulties, the healthcare field has witnessed significant technological advancements, offering promising avenues for disease prediction. Notably, a positive correlation exists between the utilization of technologies and their potential to serve as valuable tools for disease prediction. As our reliance on technological sophistication continues progressing, current research highlights numerous viable options to augment the healthcare sector. This review explores the current state of utilizing technologies and their potential to enhance healthcare, shedding light on their …

Using Machine Learning Techniques To Model Encoder/Decoder Pair For Non-Invasive Electroencephalographic Wireless Signal Transmission, Ernst Fanfan

Master of Science in Computer Science Theses

This study investigated the application and enhancement of Non-Invasive Brain-Computer Interfaces (NI-BCIs), focused on enhancing the efficiency and effectiveness of this technology for individuals with severe physical limitations. The core research goal was to improve current limitations associated with wires, noise, and invasive procedures often associated with BCI technology. The key discussed solution involves developing an optimized Encoder/Decoder (E/D) pair using machine learning techniques, particularly those borrowed from Generative Adversarial Networks (GAN) and other Deep Neural Networks, to minimize data transmission and ensure robustness against data degradation. The study highlighted the crucial role of machine learning in self-adjusting and isolating …

An Interactional Account Of Empathy In Human-Machine Communication, Shauna Concannon, Ian Roberts, Marcus Tomalin

Human-Machine Communication

Efforts to develop empathetic agents, or systems capable of responding appropriately to emotional content, have increased as the deployment of such systems in socially complex scenarios becomes more commonplace. In the context of human-machine communication (HMC), the ability to create the perception of empathy is achieved in large part through linguistic behavior. However, studies of how language is used to display and respond to emotion in ways deemed empathetic are limited. This article aims to address this gap, demonstrating how an interactional linguistics informed methodological approach can be applied to the study of empathy in HMC. We present an analysis …

How Do Pedestrians Perceive The Safety, Comfort, And Usefulness Of A Walking Space? An Exploratory Study Of Pedestrian Perception, Amanda Rifqa Marisa, Achmad Hery Fuad

Smart City

Car-oriented development has brought several negative impacts on human quality of life. Therefore, it is necessary to pay more attention to walkability as one of the essential aspects of it, especially in the urban area. In the meantime, most research on walking and walkability still overlooks the role of the pedestrian's perspective in examining walkability. Hence, this research tries to fill the gap in walkability research by exploring the pedestrian perspectives on the safety, comfort, and usefulness of walking space as the three overlapping aspects between walkability and walking needs. This research took context in Suryakencana, Bogor City, Indonesia. To …

Urban Memory Becomes An Idea In The Concept Of Spatial Planning (Study Case: Restoration Area Of Tambora District, West Jakarta), Riska Phillia, Antony Sihombing

Smart City

Urban heritage is a small part of the past of the city that holds the roots of the city's identity and culture, which are the city's identity. The strong identity of the historic area must be maintained, but this has a dilemma because of the need for change today. Therefore efforts are needed to create adaptive urban heritage areas. City spaces have a deep relationship with the people who inhabit them, with the most memorable or most memorable experiences and memories for them. This research contributes to exploring urban memory to develop conceptual spatial plans in restoration areas, using qualitative …

Major Paths Changes In 2013-2022 To Walkability (Case Study: Dukuh Atas Tod), Daniel Harvey Tulis, Antony Sihombing

Smart City

Development area with the concept of Transit Oriented Development (TOD) occurs so rapidly in big cities, which aims to create an integrated transportation system and is supported by the surrounding area. TOD area must have good road access for vehicles and space for pedestrians. Dukuh Atas TOD is one of the transit-oriented areas planned to be the largest TOD area in Jakarta so that developments are felt every year, including visuals and the road traffic system and pedestrian space. This research is using qualitative method by answering specific and actual variables. Time series analysis to see changes every year combined …