Electrical and Computer Engineering Commons^™

Real-Time Deep Learning Detection Of Toraja Carving Motifs Using Yolo11m For Cultural Heritage Preservation, Herman Herman, Farid Wajdi Mufti, Abdul Rachman Manga, Haidawati Nasir

Knowledge Engineering and Data Science

Toraja carvings are an important part of Indonesia’s cultural heritage, rich in symbolic, aesthetic, and philosophical meaning. However, the identification and preservation of carving motifs still rely on subjective, time-consuming manual processes, limiting scalability and inconsistent knowledge transmission. From a Knowledge Engineering and Cognitive Data Science perspective, this challenge highlights the need for mechanisms that can transform visual cultural artifacts into structured, machine-interpretable knowledge. This study investigates the use of the YOLO11m model as a data-driven approach for modeling cultural knowledge through automated detection of three Toraja carving motifs: pa_tedong, pa_kapu_baka, and pa_manu_londongan using original images collected directly from traditional …

A Parallel Interval Modeling Framework For Nonlinear Systems: Application To A Modified Duffing Oscillator, Roman Voliansky, Nina Volianska

Northeast Journal of Complex Systems (NEJCS)

The paper presents a mathematical framework for converting nonlinear dynamical systems into parallel forms. This framework replaces the exact system motion equations with interval equations, enabling the representation of nonlinear functions over piecewise linear domains. Such representation enables the description of system motions using linear-like differential equations, which can be analyzed and manipulated using well-known control methods. One such method is eigenvalue analysis, a powerful tool in classical control theory since many techniques rely on the system’s characteristic polynomial and its eigenvalues. We apply this method to define interval system eigenvalues and track their variation during system operation. These eigenvalues …

Exploring Interactive Robotic Music Therapy Systems For Rehabilitation: A Survey Paper, Hector A. Salinas Gordillo

Discovery Undergraduate Interdisciplinary Research Internship

Interactive robotic music therapy introduces an innovative opportunity, where human guided musical interaction with robotic systems can create adaptive and engaging therapeutic experiences. This survey explores the current state of research at the intersection of robotics, music, and rehabilitation, focusing on emerging technologies such as human robot interaction methods and system designs that help enable real time, interactive music therapy.

Potential patient groups include individuals undergoing motor or cognitive rehabilitation, such as those recovering from stroke, living with Parkinson’s disease, cerebral palsy, or other motor impairments, as well as individuals with developmental disorders or limited mobility.

Traditional rehabilitation exercises may …

Adaptive Deep Learning In Physical Layer Applications, Ali Owfi

All Dissertations

Traditionally, signal processing models in communication systems have been designed based on solid foundations in statistics and information theory, often assuming linearity and optimizing for simplified models. However, real-world communication systems exhibit numerous imperfections and non-linearities that traditional linear models struggle to capture accurately. Deep Learning (DL)-based approaches, unconstrained by rigid mathematical models, have shown promise in optimizing system performance by accommodating specific hardware configurations and dynamic channel conditions as an alternative to the traditional methods. Despite all the recent research efforts on DL-based methods for physical layer applications, DL models have still not been widely applied to physical layer …

Deterministic Methods To Improve The Field-Of-View For Direction Finding Using Sparse Digital Arrays, Nolan J. Egging

Master's Theses

Direction finding algorithms are used with digital phased arrays to determine the incoming angle of arrival (AoA) of an incident signal. These algorithms, and direction finding as a whole, have a wide range of civilian and military applications from radar, electronic reconnaissance, mobile communication, et cetera. However, for situations where the spacing between antenna elements needs to be large, gating lobes appear in the radiation pattern of analog arrays. This work demonstrates that for digital beamforming algorithms, the field of view (FoV) of a uniform linear digital array matches the grating lobe free range of a similarly spaced analog array. …

Reinforcement Learning Based Security Schemes For Distributed Ai Systems, Ashan Chamath Gunawardena

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Distributed machine learning (DML) is a component of modern intelligent systems, enabling collaborative training across devices such as mobile clients, vehicles, and edge networks. However, the decentralized nature of these systems introduces vulnerabilities, particularly data poisoning attacks that compromise model integrity and degrade performance. Traditional defenses, such as statistical filtering, robust aggregation, and privacy-preserving techniques, often struggle to adapt to overwhelming adversaries or operate under strict privacy and real-time constraints. This dissertation proposes the use of reinforcement learning (RL) and deep reinforcement learning (DRL) based misbehavior detection schemes that dynamically identify poisoning attempts in distributed AI systems, including federated learning, …

A Light-Dependent Resistor Based Embedded Image Acquisition System For Use In Low-Resolution Application-Specific Data Processing, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper proposes an efficient hardware-based approach to image acquisition & processing to replace complex camera systems in simple industrial & commercial applications.

Environment Mapping And Gps-Based Trailer Parking Using Low-Cost Peripheral Sensors And Post-Processing Algorithms, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper explores the merit of software data optimization through two practical examples: environment mapping & GPS navigation.

Maximum Likelihood Symbol Timing Algorithm Based On Cyclic Prefix For Ofdm Systems, Kwame S. Ibwe

Tanzania Journal of Engineering and Technology (TJET)

In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-division multiplexing (OFDM) systems, and a timing function based on the redundancy of the cyclic prefix (CP) is introduced. The existing algorithms rely on the prior knowledge of the channel energy distribution i.e. channel power profile. In practical environment the channel power profile is unknown to the receiver and its statistics are expected to be highly changing. Nevertheless, the use of pilot symbols in channel profile estimation reduces efficiency as data subcarriers are used to carry pilots instead of payload. In this paper a timing function that accounts …

Building A Smart Transportation Network To Prevent Multi-Vehicle Collisions During Sudden Slowdowns, Leo Huang, Patrick Zhao

College of Engineering Summer Undergraduate Research Program

This proposed SURP project aims to design and evaluate a smart transportation network capable of preventing multiple-vehicle collisions due to sudden slowdowns in traffic. This project will simulate abrupt braking scenarios and implement adaptive vehicle-to-vehicle (V2V) communication protocols. By enhancing real-time awareness and responsiveness among vehicles, the system will reduce pileup risks and improve road safety.

Building Pathways To Computer Science Careers For Latinx Students Through Multilingual Collaborative Block-Based Programming, Cis Garcia, Noemi Corona Calvario

College of Engineering Summer Undergraduate Research Program

The underrepresentation of Latinx students in computer science highlights the need for innovative and inclusive educational approaches. This project addresses challenges such as limited access to educational resources and the demand for multilingual learning tools by developing a co-located, collaborative, game-based programming environment. Designed for use on phones, tablets, and laptops, this tool supports English, Spanish, and Mixtec, facilitating broader engagement. By promoting peer collaboration and interactive learning, our approach challenges traditional notions of solitary programming and reinforces the idea that expertise is shared, fostering an inclusive and equitable learning environment.

Generative Ai: Another Chapter Of Human-Machine Communication, Seungahn Nah, Patric R. Spence

Human-Machine Communication

This editorial introduces a special issue of Human-Machine Communication that explores how generative AI reshapes the communicative relationship between humans and machines. It highlights emerging research on technology use, education, interpersonal dynamics, and trust in AI-generated content, emphasizing that generative AI’s significance lies not in novelty but in the social negotiations it provokes around meaning, authority, and credibility.

Interference Management For Device-To-Device Communications In Heterogeneous Cellular Networks Using Deep Reinforcement Learningdevice-To-Device Communication; Mmwave Communication; Spectrum Resource Allocation; Deep Reinforcement Learning; Hcns, Suzan Mohamed Shukry

Journal of Engineering Research

Integrating Device-to-Device (D2D) communication into Heterogeneous Cellular Networks (HCNs) augmented with Millimeter Wave (mmWave) technology presents a compelling approach to fulfill the escalating demands for ultra-high data throughput in next-generation wireless systems. Although these advancements significantly improve data transmission efficiency and network scalability, the coexistence of D2D and cellular users within a shared spectral environment triggers considerable interference, complicating network coordination. To mitigate this, the interference scenario is modeled as a unified optimization task involving mode selection and resource allocation, aiming to enhance the aggregate system throughput while adhering to strict SINR constraints for both communication tiers. To tackle this …

Satellite Internet Technology: Connect The Unconnected, Nora Turki Alamoudi Ms., Aziza I.Hussien Proffessor

Effat Undergraduate Research Journal

Satellite Internet is the internet provided through a network of communication satellite constellations in space. This type of internet can cover an area of a wider range than the commonly used cable internet. The development of small-sized satellite technology in the commercial space sector has entered a vigorous phase of development. However, approximately four billion individuals worldwide lack internet access. Most of these citizens live in developing countries. It is in this context that the industry of satellite internet is expanding its social and economic development through connectivity. The implementation of the idea requires examining the advantages provided by satellite …

Owl Solar-Powered Link: Duck Radio Mesh For Autonomous Monitoring, Jaden Tran, Shane Williams

Electrical Engineering

The Solar Duck Sensor Node transforms a standard DuckLink into a fully self-sustaining environmental monitor. A compact solar panel / power bank module plugs into the power ports of both the DuckLink and the Raspberry Pi Zero 2 W, keeping them charged through day-night cycles. The Pi Zero 2 W will perform local processing of sensor data. Sensor output will come from the Raspberry Pi AI Camera and its object detection capabilities. This output will be distilled into metadata and advertised over BLE. The DuckLink captures these packets, encapsulates them into LoRa payloads, and forwards them across the ClusterDuck mesh …

The Rise Of Foss In India: Empirical Evidence And Insights From Cross-Sectoral Case Studies, Arul George Scaria, Suryaprakash Mishra, Shubham Shinde, Rashi Singhal

Research Reports

The report analyses the adoption of FOSS in India, primarily through case studies across four sectors (healthcare, education, finance, and software and IT services) and different types of organisations (start-ups, non-profits, medium, large, and public sector organisations). The study highlights both the benefits and challenges experienced by organisations using FOSS. The study illustrates that while organisations benefit from increased innovations, cost/ time savings, flexibility, and enhanced security, they also face challenges such as lack of enough skilled personnel and limited community support. Organisations are also seen taking a cautious approach to licensing, favouring permissive licenses over restrictive ones. Based on …

The Rise Of Foss In India: Empirical Evidence And Insights From Cross-Sectoral Case Studies, Arul George Scaria, Suryaprakash Mishra, Shubham Shinde, Rashi Singhal

Research Reports

The report analyses the adoption of FOSS in India, primarily through case studies across four sectors (healthcare, education, finance, and software and IT services) and different types of organisations (start-ups, non-profits, medium, large, and public sector organisations). The study highlights both the benefits and challenges experienced by organisations using FOSS. The study illustrates that while organisations benefit from increased innovations, cost/ time savings, flexibility, and enhanced security, they also face challenges such as lack of enough skilled personnel and limited community support. Organisations are also seen taking a cautious approach to licensing, favouring permissive licenses over restrictive ones. Based on …

The Rise Of Foss In India: Empirical Evidence And Insights From Cross-Sectoral Case Studies, Arul George Scaria, Suryaprakash Mishra, Shubham Shinde, Rashi Singhal

Research Reports

The report analyses the adoption of FOSS in India, primarily through case studies across four sectors (healthcare, education, finance, and software and IT services) and different types of organisations (start-ups, non-profits, medium, large, and public sector organisations). The study highlights both the benefits and challenges experienced by organisations using FOSS. The study illustrates that while organisations benefit from increased innovations, cost/ time savings, flexibility, and enhanced security, they also face challenges such as lack of enough skilled personnel and limited community support. Organisations are also seen taking a cautious approach to licensing, favouring permissive licenses over restrictive ones. Based on …

الأمن السيبراني والذكاء الاصطناعي: حلول لإدارة أزمات البنية التحتية الرقمية, عبدالله سعد الغامدي

Journal of the Association of Arab Universities for Research in Higher Education مجلة اتحاد الجامعات العربية للبحوث في التعليم العالي

في ظل التحول الرقمي المتسارع، أصبحت إدارة الأزمات التقنية تحديًا استراتيجيًا يستوجب تبني حلول مبتكرة للحفاظ على استمرارية الأعمال وحماية البنية التحتية الرقمية. ناقشت هذه الورقة دور الأمن السيبراني والذكاء الاصطناعي في تعزيز قدرات المنظمات والجهات على التنبؤ بالأزمات والاستجابة لها بفعالية ، وتعتمد على منهجية تحليلية تجمع بين دراسة الحالات الواقعية وتحليل البيانات باستخدام تقنيات التعلم العميق Deep Learning ونظم الأمن السيبراني المتقدمة مثل SIEM وSOAR ومدى الاستفادة من دمج هذه التقنيات لتحسين زمن الاستجابة وتقليل معدل الهجمات الناجحة، مع التدليل على أمثلة من المملكة العربية السعودية والتي سجلت أكثر من 38 مليون محاولة هجوم سيبراني في عام 2024. …

Forensic Audit: Enhancing Certified Public Accountant Using Artificial Intelligence Techniques, Hasan Mazloum, Nawaf Mazloum, Ahmad Mohamad Saleh

BAU Journal - Science and Technology

Forensic accounting was developed after the widespread corruption in the world of business today. It is now considered a fundamental branch of accounting since it revolves around disputes and issues in the law that require accounting and legal knowledge and practices to be resolved. This study examines the impact of two forensic accounting domains – the expert witness and litigation support – on financial corruption in Lebanon by using AI The objective of this study is to investigate the potential of artificial intelligence (AI) techniques in enhancing forensic audit . The study adopts the analytical descriptive approach utilizing an empirical …

Towards Effective Academia-Industry Collaborations: The Case Of Higher Learning Institutions In Tanzania, Fatuma S. Ikuja

Tanzania Journal of Engineering and Technology (TJET)

Industries are the main consumers of products from higher learning institutions (HLIs); graduates for employment and research outputs for socio-economic development. Research outputs from HLIs are commercialized as services or products facilitated by academia-industry collaborations. The collaborations are expected to address mismatch between labour market needs and HLIs’ products, which has resulted in graduates’ employability challenges. Despite their importance, effective academia-industry collaborations remain challenging. This study explores the effectiveness of Academia-Industry collaborations established by HLIs in implementing the Higher Education Economic Transformation (HEET) project (2021-2026) in Tanzania. One of the project objectives is to build functional linkages between industry and …

The Dynamics Of Word-Of-Mouth Marketing: An Agent-Based Modeling Approach To Message Credibility And Consumer Engagement, Ali Nasirzonouzi, Carlos Gershenson

Northeast Journal of Complex Systems (NEJCS)

Word-of-mouth (WOM) marketing is a critical factor in the dissemination of information and adoption of products in social networks. This paper investigates the impact of two important factors message credibility and consumer engagement on WOM adoption dynamics using agent-based modeling (ABM). This study proposes a simple qualitative model to investigate how these factors influence adoption rates through both broadcast communication and peer-to-peer influence by simulating interactions on a spatially clustered network.

The findings show that increased message credibility significantly boosts adoption, achieving a balance between broadcast and social mechanisms. Also, consumer engagement primarily affects the adoption mechanism, shifting the effect …

Mutual Coupling Impedance Effect On Ris-Assisted Terahertz Communication, Radwa A. Roshdy Dr., Hossam M. Kasem Prof., Mohammed A. Salem Dr.

Journal of Engineering Research

Terahertz (THz) communication based on reconfigurable intelligent surfaces (RIS) is a promising technology in future wireless networks, with the capabilities of ultra-high data rates and energy-efficient beam communicating. Nevertheless, the mutual coupling impedance of the closely spaced RIS reveals the inefficacy in existing channel estimation schemes, while it is usually ignored in the literature. In this paper, we fill this gap by developing an EM-compliant channel model that integrates mutual coupling explicitly for RIS-assisted THz systems. We evaluate the performance of mutual impedance-induced influence to the accuracy of the root mean square error (RMSE), which is considered as a pivotal …

The Evolution Of Global Gold And Copper Trade Networks, Oleksandr Hulianskyi

Northeast Journal of Complex Systems (NEJCS)

Gold and copper have emerged as two of the most vital commodities in global trade. Despite serving distinct purposes, their international trade networks reveal interconnected patterns, critical to understanding the dynamics of global economics. This paper studies these attributes and their evolution during the last 36 years for both metals and finds correlations between them. The first part of the research is focused on the sustainability of networks through efficiency and robustness indexes; the second part is dedicated to interconnectedness – the Louvain and Bayesian SBM algorithms, partition, and modularity instruments are used. Community detection algorithms provide valuable insights into …

Exploring The Potential Of Large Language Models (Llms) To Simulate Social Group Dynamics: A Case Study Using The Board Game "Secret Hitler", Kaj Hansteen Izora, Christof Teuscher

Northeast Journal of Complex Systems (NEJCS)

This study explores the capacity of large language model-powered agents to simulate human-like behavior in multi-agent social systems. Using Secret Hitler — a hidden-role board game centered on trust, deception, and strategic communication — we evaluate how LLM agents navigate dynamic group interactions. Our findings show that agents exhibit human-like behaviors, including strategic temporal adaptation, contextual reasoning, and complex social cognition such as theory of mind and implicit coordination. Notably, 85% of agent decisions factored in at least two other players’ mental states, highlighting their capacity for multi-agent mental state inference. However, they struggled with key aspects of human gameplay, …

How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael

Dartmouth College Ph.D Dissertations

September Arctic sea ice extent has diminished by roughly 50% in the 45 years since satellite observations began. The Arctic Ocean may experience ice-free summers within the next decade, with implications for habitat, resource extraction, geopolitics, and local and global climate change. To predict how Arctic sea ice will change in the future, we need to understand its behavior in the present. In situ sea ice mass balance measurements (snow accumulation, ice growth, snow and ice surface melt, and bottom melt) are essential for studying the processes driving rapid changes in the ice pack, and for validating remote sensing measurements …

Exploring The Interplay Between Economic Growth And Sustainable Development: A Complex Systems Approach To Gsdp And Sdgs In Indian States, Rosewine Joy, Helen Josephine, Divya D, Midhun Raj

Northeast Journal of Complex Systems (NEJCS)

Pursuing Sustainable Development Goals (SDGs) necessitates aligning business and management practices on a global scale. This paper delves into the intricate dynamics between Gross State Domestic Product (GSDP) and SDGs across diverse states in India, offering nuanced insights to policymakers, businesses, and stakeholders. This paper explores the dynamic relationship between Gross State Domestic Product (GSDP) and the Sustainable Development Goals (SDGs) in the context of India's diverse states by applying modern machine learning techniques such as XG boost, Decision trees, and K mean clustering. The study delves into how economic growth influences the progress towards SDGs. The research integrates complex …

Orchestrating Complexity: The Art Of Virtual Leadership In System Modelling, Vijay Kumar Sonawane, Bipllab Roy, Purnendu Bikash Acharjee, Indu Pv

Northeast Journal of Complex Systems (NEJCS)

This paper explores the dynamics of virtual leadership within global remote work environments, focusing on the application of complex system modelling to understand and enhance leadership efficacy. The application of computational modelling has been a regular feature in economics, science and technology fields, however its application in virtual leadership with linkage to sport leadership appears to be a novel concept. Adopting a multidisciplinary approach, this paper incorporates Game Theory as a conceptual framework to make the leadership model more relevant and applicable that can offer simpler understanding of complex play of leadership drivers. The model incorporates five key leadership dimensional …

Leveraging Usage Of Ai In Education: Knowledge, Attitude And Behavioral Analysis On Students, Bipllab Roy, Purnendu Bikash Acharjee, Rohit Kumar Sharma, Ruptaheen Kramsapi, Shruti P

Northeast Journal of Complex Systems (NEJCS)

The paper explores the possible advantages and drawbacks of artificial intelligence (AI) on sustainability, with an emphasis on using AI to positively achieve SDGs. The study finds a significant vacuum in the literature on the association between knowledge, attitudes, and behaviors towards the use of AI tools and techniques in education and demographic characteristics (sex, age, education level, area of study, and city of origin). The purpose of this research is to close this knowledge gap and advance our understanding of how these demographic factors affect the integration of AI in educational environments. The study specifically aims to comprehend how …

Study On The Application Of Smart Electric Meters For Secondary Voltage Protection, Jayaditya Sisodia

Master's Theses

The purpose of our research is to utilize PG&E’s Smart Meters installed across California to protect the Secondary Voltage delivered to the meter. This means detecting electrical faults between the utility’s distribution transformer and the installed Smart Meter. Our goal is to propose and implement various solutions through additional devices and protocols to detect and prevent these faults, communicate them with the meter, and forward fault information to the utility. A device will be designed to be installed on the transformer, detect faults, shut off power transmission, and communicate to the meter via fiber optic cable. Research will then be …