Computer Engineering Commons^™

Explicit Bounds And Parallel Algorithms For Counting Multiply Gleeful Numbers, Sara Moore, Jonathan P. Sorenson

Computer Science and Software Engineering

Let k ≥ 1 be an integer. A positive integer n is k-\textit{gleeful} if n can be represented as the sum of kth powers of consecutive primes. For example, 35=2³+3³ is a 3-gleeful number, and 195=5²+7²+11² is 2-gleeful. In this paper, we present some new results on k-gleeful numbers for k > 1.

First, we extend previous analytical work. For given values of x and k, we give explicit upper and lower bounds on the number of k-gleeful representations of integers n ≤ x.

Second, we describe and analyze two new, efficient parallel …

Ti-Ulpcs: Threshold-Issuance - Un-Linkable Policy Compliant Signatures, Kiran Deep Ghosh

Master’s Dissertations

Digital signatures, as a strong cryptographic primitive, ensure the authenticity and integrity of signed messages. On one hand, no one can forge a verifiable signature without knowing the secret key, on the other hand, any correctly formed signature is always verifiable under the public key of the signer. Besides signing digital data, they serve as foundational components in more advanced cryptographic systems, including blind signatures, group signatures, direct anonymous attestation, e-cash, e-voting protocols, adaptive oblivious transfer, anonymous credential schemes, Policy-Compliant Signatures, etc. Policy-Compliant Signatures (PCS) enable the enforcement of joint policies between the signer and the verifier. A signature of …

Zkipv: Zero-Knowledge Proofs For Image Provenance Verification, Bibek Ghosh

Master’s Dissertations

Recent advances in generative AI have significantly improved the ability to create photorealistic synthetic images, including so-called deepfakes, raising concerns about misinformation and the erosion of trust in digital media. Ensuring the integrity and authenticity of images, especially in sensitive domains like journalism, is thus increasingly critical. Existing solutions such as the C2PA (Content Provenance and Authenticity) framework provide origin verification through cameragenerated digital signatures, but fail to account for image modifications that invalidate these signatures. To address this limitation, we propose a zero-knowledge approach to verifiable image editing that preserves both integrity and privacy. This system, ZK-IPV, introduces a …

Efficient Simd Based Implementation Of Xoodyak, Soham Biswas

Master’s Dissertations

Modern computing devices—particularly in the domains of the Internet of Things (IoT), mobile computing, and embedded systems—often operate under severe resource constraints in terms of processing power, memory (RAM/ROM), bandwidth, and battery life. Devices such as IoT sensors, smart cards, medical implants, RFID tags, and wearable systems typically rely on low-power hardware, including 8-bit microcontrollers with only a few kilobytes of memory. Conventional cryptographic algorithms are frequently unsuitable for such environments, as they may consume excessive power, introduce unacceptable latency, or fail to execute altogether. Lightweight cryptography addresses these challenges by providing cryptographic primitives specifically designed to operate efficiently on …

The Monodromy Leak For A Generalized Montgomery Ladder, Arani Raychaudhuri

Master’s Dissertations

The Diffie-Hellman key exchange protocol using elliptic curves is the most wide-spread approach to the establishment of a secure internet connection. As an important subroutine, Alice and Bob need to perform multiplications of elliptic curve points by large scalars. The textbook method for scalar multiplication is the double-and-add algorithm. For the sake of efficiency, one usually performs x-coordinate only arithmetic using projective coordinates, and doubling-and-adding is done using the Montgomery ladder. The advantage of using projective coordinates is that this avoids costly field inversions at each iteration. However, when Alice (say) uses the double-and-add algorithm for computing her public key …

Design Of A Simplified Biomimetic Autonomous Entertainment Robot, Jessica E. Morris, Shanny May Ruiz, Morgan Snyder, Hannah Guild, Gabriel Cardona-Tous

Graduate Scholarship and Creative Works

The advancement of technology has paved the way for robots with the purpose of entertainment to become more popular. However, the exploration of biomimetic actions as a factor of entertainment is majorly limited to the mimicry of young domesticated animals such as puppies and kittens, with some notable exceptions. However, there is a wide range of possibilities for robotics that mimic animals marketed as pets, outside of the common examples. This work seeks to explore the opportunity for autonomous systems with entertainment driven and expressive actions in the family of Testudines (turtles and tortoises), an undomesticated species, but still often …

Enhancing Visibility On A Science Dmz With P4-Perfsonar, Ali Mazloum, Elie Kfoury, Ali Alsabeh, Jose Gomez, Jorge Crichigno

Faculty Publications

The Science Demilitarized Zone (Science DMZ) is a specialized network designed to facilitate the transfer of large-scale scientific data. One of the key elements of the Science DMZ is perfSONAR, an active performance measurement device that monitors end-to-end paths over multiple domains. Although versatile, perfSONAR faces limitations such as restricted visibility of events and coarse-grained measurements. This paper proposes a scheme that integrates P4 programmable data plane (PDP) switches with perfSONAR. P4 PDP switches are passively installed and operate on real-time traffic copies, providing flexibility to collect fine-grained custom measurements and report events in the data plane. This integration enables …

Edge-Streamer: A Lightweight, Self-Supervised Event Segmentation Model, Lucas Miller

USF Tampa Graduate Theses and Dissertations

Event segmentation is the practice of autonomously detecting the boundaries of semantically connected sequences of actions within a video. It is connected to many areas of computer vision, including action recognition and event understanding. Nearly all current work requires the entire video to be stored in memory to be processed in multiple passes. This takes up valuable resources, increases processing time, prevents the use of low-power, low-memory devices, and precludes long-form content and live videos from undergoing event segmentation.

This thesis introduces EDGE-STREAMER, a real-time, lightweight, self-supervised, transformer architecture capable of performing event segmentation in a single pass. EDGE-STREAMER uses …

Tripping The Telematic Fantastic: Adventures In Presenting Telematic Musicing At In-Person Conferences In 2024, Tom Zlabinger

Journal of Network Music and Arts

This article documents my challenges, successes, and what I learned while demonstrating what I describe as telematic musicing at six academic conferences in the U.S., Scotland, Finland, and Lithuania in 2024. Through personal narrative, autoethnography, and audience reactions, I share observations and conclusions I drew as a result of demoing telematic musicing to different audiences. I outline the technological and attitudinal challenges I encountered at the conferences and assess whether I was able to resolve them. I also discuss the need to strike and maintain a balance between hardware, software, and what Peter Neumann calls “peopleware.” Finally, I reflect on …

Transmission: Works Of Sarah Rose Weaver And Collaborations (2022–2024), Sarah Rose Weaver

Journal of Network Music and Arts

The Transmission Series took place between 2022 and 2024, primarily in a virtual network music setting. The series consists of my compositions and collaborations for solo, chamber, and large ensemble performance, building on my works and essays since 1998 that engage in-person, hybrid, and virtual spaces. This essay details the artistic and technological strategies employed in the Transmission Series, including audio, video, and score excerpts. The technologies discussed include networked audio and video, along with streaming and recording methods. The works featured in the discussion are “Transcendence Transmission” (2022) for large ensemble, “Sub Way” (2022) for chamber ensemble, “Here Mirror” …

Reconceptualizing The Organ Through Networked Spaces: Interviews With Participants Of The 2023 Global Hyperorgan Concert, Daniil Pilchen, Rebekah Wilson

Journal of Network Music and Arts

This paper examines the Global Hyperorgan concert held at the 16th annual Orgelpark Symposium in Amsterdam, Netherlands, in June 2023. The Symposium aims to reimagine the historically significant yet underused pipe organs. As part of meeting this aim, the concert featured performances linking Amsterdam and Vancouver using the Global Hyperorgan, a system that connects pipe organs via network technology. Interviews were conducted with the participating musicians to explore their experiences with this musical platform. Three key themes of primary interest to these musicians are revealed: alternative control interfaces, space and acoustics, and latency as a creative tool that drives innovations …

Traces Of Presence: Remembering Daniel Pinheiro, Billy Clark

Journal of Network Music and Arts

A tribute article in memory of artist Daniel Pinheiro (1982–2025).

The Zone: Hyperintimacy In Telemersive Performance, Benjamin Burger, Patrick Muller, Joel De Giovanni, Martin Frölich, Eric Larrieux, Hannah Walter

Journal of Network Music and Arts

This article explores how immersive technologies can create intimate connections between physically separated people through the telematic performance titled The Zone. The project links two stage spaces—one for a performer and one for an audience member—using advanced technologies including volumetric video, 3D scanning, spatial audio, motion capture, and augmented reality. Developed at the Institute of Computer Music and Sound Technology at the Zurich University of the Arts, these Extended Reality (XR) tools enable what we call hyperintimacy—an enhanced form of connection that transcends physical distance through immersive telepresence. Despite the artificial technological context, participants experience genuine encounters that balance digital …

Mediating The Exquisite: Aesthetic Affordances Of The Network Arts, Seth Adams

Journal of Network Music and Arts

This paper argues that the Network Arts afford uniquely nuanced aesthetic interactions among humans and between humans and machines. After defining these moments under a new concept I call exquisite musicking, I investigate how distributed networks of human and nonhuman actors create experiences that challenge or complicate traditional notions of agency, ensemble, aesthetics, and synchrony. Using Actor-Network Theory as a lens of inquiry, I explore the exquisite affordances of network-based musicking, discussing how pitch, timbre, and texture are co-created in networked performances. I also examine how exquisite musicking could serve as a fruitful concept in music education, particularly in pedagogical …

Editorial, Sarah Rose Weaver

Journal of Network Music and Arts

No abstract provided.

Exact Solutions Of M-Fractional Complex Ginzburg-Landau Equation Via Two Analytical Methods, Nematollah Kadkhoda, Mojtaba Baymani, Maad M. Mijwil, Mostafa Abotaleb

Iraqi Journal for Computer Science and Mathematics

This article investigates the M-fractional complex Ginzburg-Landau (CGL) equationby utilizing the modified simplest equation method and the modified G'G-expansion method. The CGL holds significant importance in the realm of oscillatory phenomena and optical fibers. By implementing a fractional complex transformation, the M-fractional CGL equation is transformed into an ordinary differential equation (ODE).By employing these methodologies, bright periodic solutions, periodic solutions, and dark wave solutions relevant to phenomena witnessed in nonlinear optics or plasma environments are ascertained.It is demonstrated that these methods are very powerful and efficient to solve many fractional differential equations.

Reason for Expression of Concern: …

Enhancing Image Denoising Performance Through Cosine Similarity-Based Block Matching And Adaptive Thresholding - Ca-Ebm3d, R. Padmapriya, A. Jeyasekar

Iraqi Journal for Computer Science and Mathematics

Image denoising plays a vital role in enhancing visual quality by effectively suppressing noise while retaining critical image structures and textures. Traditional Block-Matching and 3D (BM3D) Filtering techniques, although widely adopted, often encounter challenges in achieving an optimal trade-off between noise reduction and feature preservation due to limitations in fixed-thresholding strategies and suboptimal block matching. To address these shortcomings, this study introduces a novel Cosine Adaptive BM3D (CA-BM3D) approach, which integrates cosine similarity for more accurate block matching and incorporates adaptive thresholding to enhance denoising efficiency. The proposed method was evaluated on six standard 8-bit grayscale images such as Leena …

From Industrial Automation To Intelligent Automation: The Impact Of Iiot On Process Control - A Review?, Ali S. Allahloh, Mohammad Sarfraz, Duraid Y. Mohammed, Nadeen Khaleel Ibrahim, Hayder Hussein Thary

Iraqi Journal for Computer Science and Mathematics

The Industrial Internet of Things (IIoT) is reshaping process control, turning torrents of plant data into near-instant insight. Field evidence already shows unplanned-downtime cuts of 55%, maintenance-budget savings of 40%, and gains in overall-equipment-effectiveness of roughly 15%; nevertheless, fewer than 30% of facilities have pushed beyond pilot scale to full, always-on predictive maintenance. To clarify why, this review screens 312 Scopus records published between 2010 and 2023, then subjects 62 peer-reviewed studies and a broad set of industry reports to deep content analysis, bibliometric mapping, and thematic clustering.The results reveal four tightly connected research fronts—IIoT/Industry 4.0 core technologies, classical process-control …

Reliability-Based Design Optimization Using Differential-Algebraic Equations, Saad Abbas Abed, Mona Ghassan, Shaimaa Qais Latef, Hind S. Hassan

Iraqi Journal for Computer Science and Mathematics

Reliability-based design optimization (RBDO) determines optimal design parameters by incorporating reliability constraints. This paper presents a RBDO approach using differential-algebraic equations (DAEs) for modeling and constraints. DAEs provide an accurate representation of dynamic engineering systems with coupled differential and algebraic equations. However, the nonlinearity and implicit nature of DAEs pose challenges for uncertainty propagation and optimization. This study proposes an efficient RBDO methodology based on stochastic collocation to quantify uncertainty in DAEs. The DAEs are transformed into an explicit ODE system to enable direct uncertainty analysis via sampling. Optimization under reliability constraints is achieved using a sequential approximate programming strategy. …

Challenges And Constraints In Trajectory Planning For Autonomous Robots, Jawad Abdouni, Tarik Jarou, Toufik Mzili, Abderrahim Waga, Karima Bensassi

Iraqi Journal for Computer Science and Mathematics

Autonomous mobile robots have revolutionized navigation by operating without human intervention, leveraging advanced data acquisition systems such as cameras, radar, and LIDAR, along with sophisticated planning, localization, and control algorithms. A critical challenge in this domain is path planning: determining optimal trajectories to ensure safe and efficient travel in diverse environments. This paper addresses the need to systematically evaluate trajectory-planning algorithms, whose selection directly impacts navigation performance. We present a comprehensive analysis of various classes of path-planning methods, detailing their advantages, limitations, and application contexts. By comparing these algorithms, we identify key criteria for selecting the most suitable approach for …

Diagnosis Of Covid-19 And Viral Pneumonia With Chest X-Ray Images Using Resnet-34, Sudhir Anakal, Krishna Prasad K, Chandrashekhar Uppin, Dileep Kumar M

Iraqi Journal for Computer Science and Mathematics

COVID-19 is a highly contagious viral infection that primarily affects the respiratory system, causing symptoms such as high fever, cough, and severe respiratory distress. Early detection of the disease is of utmost importance to control the spread and severity. Common diagnostic methods include Reverse Transcription Polymerase Chain Reaction (RT-PCR), antigen tests, chest X-rays, and computed tomography (CT) scans. Similarly, viral pneumonia, another severe lung infection, leads to fluid or pus accumulation in the lungs, causing symptoms such as chest pain, fatigue, excessive sweating, and nausea. The elderly and young children are particularly vulnerable to severe complications. Similarly, viral pneumonia, another …

Algorithms For Combined Regular Synthesis Of Controller Parameters In Control Systems For Dynamic Objects, Khusan Zakirovich Igamberdiev, Latafat Abbas Gizi Gardashova, Yulduz Mukhtarkhodjayevna Abdurakhmanova, Uktam Farkhodovich Mamirov

Technical science and innovation

Nonlinear control system that includes m-dimensional input control signal and extended (n+s) - dimensional state vector, the last s components of which form a vector of unknown parameters θ satisfying a general difference equation is being considered. The quality criterion is determined by the loss function. The optimal control must satisfy the Bellman equation with respect to the optimal loss function. To be defined an approximate solution that preserves an active use of information. For this purpose, the system is linearized in accordance to the nominal trajectory. This problem is seen as incorrectly stated. The values of the preliminary data …

Intelligent Control Of Reducing Energy Consumption And Water Loss In Smart Home Systems, Hakimjon Nasriddinovich Zaynidinov, Damira Farxodovna Hodjaeva, Dhananjay Singh

Technical science and innovation

The article presents an innovative approach to developing an intelligent control system for managing temperature and water level in smart home systems. The proposed method integrates an adaptive PID controller with fuzzy logic algorithms, enabling dynamic adjustment of the PID controller coefficients in real time. The mathematical model of the system incorporates heat balance equations, differential heat transfer relations, and nonlinear models of fluid loss. The adaptive control algorithms developed within the study allow the system to effectively respond to changes in input data.

A comprehensive analysis of the membership functions is conducted, along with adaptive tuning of the PID …

A Comprehensive Review Of Software Requirements Dependencies Analysis Techniques, Nahla Mohamed, Sherif Mazen, Waleed Helmy

Iraqi Journal for Computer Science and Mathematics

The software Requirements Prioritization (RP) process is essential for producing a successful software project. Requirements are interdependent in software projects, so handling their dependency during the RP process is mandatory. Many researchers have shown that requirements dependency is challenging for large-scale systems. Extracting requirements dependency is difficult since requirements are documented in natural language. Improper handling of dependencies among requirements while prioritization can cause inaccurate prioritization results and deadlocks, which cause project delays, rework, and redesign. Many techniques have been introduced to automate the dependency analysis process among software requirements, including artificial intelligence (AI) and other logic-based methods such as …

Fixed Points Of Multi-Valued Graph Maps In Strong B-Metric, Shaimia Qais Latif, Salwa Salman Abed, Haider Ahmed Shihab

Iraqi Journal for Computer Science and Mathematics

This paper involves adopting a well-known generalization method in the branches that dealing with fixed points via weakening the suppositions. As appearing in previous sources, letting (Ω,Sb,K) be a strong b-MS, and F,H be two multi-valued maps on Ω equipped with a graph σ s.t the set of vertices of σ,Λ(σ) = Ω and the set of edges of σ, Ξ(σ) ⊆ Ω × Ω. The acceptable assupmtions have been adopted to finding a common fixed point for in Ω. …

Enhanced Detection Of Intracranial Hemorrhage: A New Hybrid Model Design Based On The U-Net Segmentation Method, Hassan F. Hassan, Hadeel K. Aljobouri, Oktay Algin

Iraqi Journal for Computer Science and Mathematics

Intracranial hemorrhage (ICH) denotes bleeding inside the skull, which can occur in or around the brain. Computed tomography (CT) has been used to detect ICH due to its high efficiency and accuracy. Nowadays, deep learning model design is introduced to allow an accurate and efficient classification of ICH in CT images. This work focused on developing U-Net-based models for the segmenting of ICH. Furthermore, the proposed model employed two transfer learning models, MobileNet and Xception, as the backbones of the U-Net topology. This approach aims to establish metrics that improve ICH treatment through precise segmentation techniques. A free dataset from …

Retracted: A Novel Benchmarking Framework For Selecting The Best Deep Learning Model Diagnosing Covid-19 Based On New Development For Dual Mcdm Methods, Mahmood M. Salih, Yousif Raad Muhsen, M.A. Ahmed, Reem D. Ismael, Moceheb Lazam Shuwandy, Z.T. Al-Qaysi

Iraqi Journal for Computer Science and Mathematics

COVID-19 was diagnosed using deep learning models by a group of studies. Evaluating and benchmarking these models are essential to achieving the most suitable model for diagnosing coronavirus. Objective: In this investigation, we offer an inclusive valuation of several deep learning models to detect the maximum appropriate and active model which gratifies doctors' requirements and assessment criteria. Method: This study combines Fuzzy decision by the opinion score method (FDOSM) and Fuzzy-Weighted Zero-Inconsistency (FWZIC). According to the advantage of Trapezoidal Intuitionistic fuzzy, we developed FWZIC into Trapezoidal Intuitionistic fuzzy named (TrIF-FWZIC) for weighting criteria and FDOSM into Trapezoidal Intuitionistic fuzzy FDOSM …

Leveraging Machine Learning For Accurate Prediction Of Nba Player Salaries, Ye Cheng, Yan Song, Mingqi Wang

Iraqi Journal for Computer Science and Mathematics

Basketball players in the NBA are renowned for their talent, athleticism, and commitment to the game. NBA players may make enormous sums of money; however, they vary greatly. Rookie agreements begin at a lower price and go up following performance. NBA players’ pays are influenced by several factors. Because they influence games and the success of the club, exceptional players fetch larger compensation. This study employs Machine Learning (ML) techniques, including Lasso Regression and Random Forest Regression (RFR) models to analyze wage trends, enhanced by the Slime Mould Algorithm (SMA) and Artificial Rabbit Optimization (ARO) for accuracy. The goal is …

Tkbe : Two Key Broadcast Encryption For The Iot, Rachit Parikh

Master’s Dissertations

The growing usage of the Internet of Things (IoT) has made it necessary to ensure

the security of these interconnected devices. Key management becomes particularly

challenging when devices are not always online due to resource constraints or business

decisions. Moreover, the IoT infrastructure typically relies on the publish-subscribe

model for communication, which raises additional security considerations since the

message broker becomes a central point of attack. Existing solutions with end-toend

encryption from publisher to subscriber are either computationally expensive for

resource constrained devices or compromise on the decoupling in publish/subscribe

systems. This thesis tackles the problem of efficient key management …

Uncertainty-Driven Fusion For Conflictive Multiview Data: Beyond View Alignment Assumptions, Puspamalya Sahoo

Master’s Dissertations

Multiview learning aims to integrate diverse feature representations to achieve a comprehen- sive understanding of data. Traditional approaches often assume strict alignment across views, making them ill-suited for real-world scenarios where low-quality conflictive instances, i.e. in- stances with conflicting information across views are prevalent. Existing methods largely focus on eliminating conflicting instances by discarding them or substituting conflicting views, over- looking the need for practical decision making in such cases. Furthermore, while the recently proposed Reliable Conflictive Multiview Learning (RCML) framework introduces the idea of attaching reliabilities to decision outcomes, it leaves certain theoretical gaps unaddressed, es-pecially prioritization of conflictive …