Digital Commons Network^™

On-Device Intelligence For Ai-Enabled Bio-Inspired Autonomous Underwater Vehicles (Auvs), Aryan Anand, M Yuva Bharath, Prabha Sundaravadivel, J. Preetha Roselyn, R. Annie Uthra

Electrical Engineering Faculty Publications and Presentations

This paper introduces an innovative approach to underwater exploration by integrating Artificial Intelligence (AI) into Autonomous Underwater Vehicles (AUVs). This collaboration between AI and biomimicry marks a new era for AUVs, enabling them to emulate marine creatures’ graceful and efficient movements. By infusing AI capabilities into AUVs, AUVs are empowered to learn and adapt, making autonomous real-time decisions without human intervention. This dynamic integration equips AUVs to effectively navigate complex underwater terrains, evade obstacles, and seamlessly interact with marine life. Inspired by the remarkable propulsion mechanisms found in marine organisms, this work proposes a pioneering propulsion system tailored for AUVs. …

Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback

Doctoral Dissertations and Master's Theses

College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …

State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems, Chris Hays

Doctoral Dissertations and Master's Theses

Resiliency in multi-agent system navigation is reliant on the inherent ability of the system to withstand, overcome, or recover from adverse conditions and disturbances. In large part, resiliency is achieved through reducing the impact of critical failure points to the success and/or performance of the system. In this view, decentralized multi-agent architectures have become an attractive solution for multi-agent navigation, but decentralized architectures place the burden of information acquisition directly on the agents themselves. In fact, the design of distributed estimators has been a growing interest to enable complex multi-sensor/multi-agent tasks. In such scenarios, it is important that each local …

Estimating Direction Of Arrival For Multi-Arm Spiral Antennas Using Machine Learning, Samuel Pearson

Honors Theses

Military systems require monitoring a wide frequency range of the RF spectrum to detect and monitor enemy targets. A vital component of that is calculating the direction of arrival of enemy radars. The use of compressive sensing architectures like the Nyquist Folding Receiver (NyFR) allow for computationally cheap capturing of wideband signals; however, these techniques make traditional direction of arrival (DOA) estimation techniques difficult. Given the advantages of compressive sensing, this research aims to apply machine learning (ML) techniques to multi-arm spiral antennas to estimate the incoming DOA. Software like MATLAB was used to simulate the multi-arm spiral antenna and …

Exploring Lstm-Based Attention Mechanisms With Pso And Grid Search Under Different Normalization Techniques For Energy Demands Time Series Forecasting, Andri Pranolo, Xiaofeng Zhou, Yingchi Mao, Bambang Widi Pratolo, Aji Prasetya Wibawa, Agung Bella Putra Utama, Abdoul Fatakhou Ba, Abdullahi Uwaisu Muhammad

Knowledge Engineering and Data Science

Advanced analytical approaches are required to accurately forecast the energy sector's rising complexity and volume of time series data. This research aims to forecast the energy demand utilising sophisticated Long Short-Term Memory (LSTM) configurations with Attention mechanisms (Att), Grid search, and Particle Swarm Optimization (PSO). In addition, the study also examines the influence of Min-Max and Z-Score normalization approaches in the preprocessing stage on the accuracy performances of the baselines and the proposed models. PSO and Grid Search techniques are used to select the best hyperparameters for LSTM models, while the attention mechanism selects the important input for the LSTM. …

Hybrid Method For User Review Sentiment Categorization In Chatgpt Application Using N-Gram And Word2vec Features, Husna Luthfiatun Nisa, Atina Ahdika

Knowledge Engineering and Data Science

The rapid development of Artificial Intelligence (AI) has significantly influenced nearly all aspects of life. One AI product widely used by people worldwide is the Chat Generative Pre-Training Transformer (ChatGPT), which can respond to questions conversationally. Although data indicates that the use of ChatGPT in Indonesia is less widespread than in other countries, a Populix survey reveals that half of the respondents have utilized ChatGPT, using AI more than once a month. This indicates its crucial role among the Indonesian population. ChatGPT is not limited to browsers; it is also available as a downloadable application on the Google Play Store. …

Convolutional Neural Network In Motion Detection For Physiotherapy Exercise Movement, Dika Fikri Laistulloh, Anik Nur Handayani, Rosa Andrie Asmara, Phillip Taw

Knowledge Engineering and Data Science

Physiotherapy focuses on movement and optimal utilization of the patient's potential. Exercise Therapy is a physiotherapy procedure that specifically focuses exercises on active and passive movements. Cerebral Palsy (CP) patients are one of the sufferers of motor disorders of the upper extremities. Cerebral Palsy (CP) patients suffer from disorders in motor functions of the upper extremities. Physiotherapy Exercise Movement has 4 categories of movement exercises for the therapy of people with upper extremity body disorders: Elbow flexor strengthening in sitting using free weights, lifting an object up, reaching diagonally in sitting, and reaching from a low surface to a high …

Optimizing Malaria Control: Granular And Cost-Effective Mosquito Habitat Index In Endemic Areas Through Satellite Imagery, Nur Ainun Daulay, Salwa Rizqina Putri, Arie Wahyu Wijayanto, Ika Yuni Wulansari

Knowledge Engineering and Data Science

Malaria, classified as a tropical disease under the Sustainable Development Goals (SDGs) indicator 3.3, remains a significant global health challenge. In this study, by taking advantage of multiple spectral composite indexes of multisource satellite imagery to capture various geospatial features relevant to the suitability of marsh mosquito habitat, we introduced the Mosquito Habitat Suitability Index (MHSI) to assess potential Anopheles mosquito breeding sites in terms of the vegetation density, water bodies, environment temperature, and humidity in any particular areas. The MHSI integrates the publicly accessible granular level of the normalized difference vegetation index, water index, land surface temperature, and moisture …

Random Forest Algorithm To Measure The Air Pollution Standard Index, Ariyono Setiawan, Untung Lestari Wibowo, Ahmad Mubarok, Khoirunnisa Larasati

Knowledge Engineering and Data Science

This study uses the Random Forest algorithm to measure and predict the Air Pollution Standard Index (APSI) at Blimbing Banyuwangi Airport. Air pollution data, including concentrations of O3, CO, NO2, SO2, PM2.5, and PM10, were collected from air monitoring stations at the airport from April 15-30, 2024. APSI measurement followed established formulas by relevant authorities. Data analysis utilized statistical approaches and computational algorithms. The findings reveal that air quality at the airport is generally "Moderate," with occasional "Good" days. The Random Forest algorithm effectively predicts APSI based on existing pollution data. These results provide insights for improving air pollution management …

Timbre Style Transfer For Musical Instruments Acoustic Guitar And Piano Using The Generator-Discriminator Model, Widean Nagari, Joan Santoso, Esther Irawati Setiawan

Knowledge Engineering and Data Science

Music style transfer is a technique for creating new music by combining the input song's content and the target song's style to have a sound that humans can enjoy. This research is related to timbre style transfer, a branch of music style transfer that focuses on using the generator-discriminator model. This exciting method has been used in various studies in the music style transfer domain to train a machine learning model to change the sound of instruments in a song with the sound of instruments from other songs. This work focuses on finding the best layer configuration in the generator- …

A Novel Approach To Defect Detection In Arabica Coffee Beans Using Deep Learning: Investigating Data Augmentation And Model Optimization, Yusriel Ardian, Novta Danyel Irawan, Sutoko Sutoko, I Nyoman Gede Arya Astawa

Knowledge Engineering and Data Science

Arabica coffee beans have valuable market worth because of their taste and quality, and there are defects like wholly and partially black beans that can lower the standards of a product, especially in the premium coffee sector. However, the manual processes used to detect the defects take an inordinate amount of time and are inefficient. This study aims to bridge the knowledge gap on the automated detection and recognition of the defects present in the Arabica coffee beans by creating and optimizing a CNN model based on a modified VGG16 architecture. The model applies data augmentation, rotation, cropping, and Bayesian …

Allocation Of Phasor Measurement Units In The Wide-Area Measurement System, Samir Dawoud, Mohamed Elnemr, Alyaa Yehia

Journal of Engineering Research

WIDE Area in the power system which has been introduced to power system literature in the late 1980s. They are now commercially in power systems for purposes of monitoring, operation, and control. The wide area is a combination between the phasor measurement unit (PMU) and communication infrastructure (CI). In this paper, the location of the PMU and the CI can be optimized to involve system observability. There are a lot of methods to solve the optimal placement of PMU. The communication infrastructure is designed and implemented to collect the data from PMU and transfer data to the control center. In …

Recent Progress And Challenges Of Implantable Biodegradable Biosensors, Fahmida Alam, Md Ashfaq Ahmed, Ahmed Hasnain Jalal, Ishrak Siddiquee, Rabeya Zinnat Adury, G M Mehedi Hossain, Nezih Pala

Electrical and Computer Engineering Faculty Publications

Implantable biosensors have evolved to the cutting-edge technology of personalized health care and provide promise for future directions in precision medicine. This is the reason why these devices stand to revolutionize our approach to health and disease management and offer insights into our bodily functions in ways that have never been possible before. This review article tries to delve into the important developments, new materials, and multifarious applications of these biosensors, along with a frank discussion on the challenges that the devices will face in their clinical deployment. In addition, techniques that have been employed for the improvement of the …

A Gateway To Next-Generation Patient Monitoring System, Kishore Kumar Kadari

USF Tampa Graduate Theses and Dissertations

Healthcare patient monitoring is undergoing a significant digital transformation, and the integration of Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) is becoming increasingly crucial in reshaping patient care. In an era where digital technology is revolutionizing medical practices, this research aims to take a leading role in advancing a fundamental aspect of predictive and sustainable healthcare practices, enhancing patient outcomes and uplifting the practice of medicine.

This research focuses on the study of Digital Twins for precision health, which are designed to monitor and provide intricate, personalized feedback dynamically during a patient's healthcare experience. The architecture of the system is …

Development Of Novel Algorithms For The Investigation Of Small Displacement Optical Flow For Opto Kinetic Nystagmus (Okn) Detection And Large Displacement Optical Flow For Surveillance, Jaiseeli C

Theses and Dissertations

Motion is a significant component of the modern visual experience, aiding with oculomotor control, object recognition, scene interpretation, perceptual organization and the acquisition of 3D shapes. Identifying motion vectors that characterize two-dimensional image transitions, usually from video frames, is necessary to estimate motion.

Optical flow is a motion-tracking technique that estimates the trajectory and velocity of a moving object in a video by shifting each pixel between frames using displacement vectors. This work has two objectives based on small and large displacement optical flow and computes optical flow using Lucas-Kanade and Brox flow, which seem to be superior to other …

Development Demand, Power Energy Consumption And Green And Low-Carbon Transition For Computing Power In China, Xiaohong Chen, Liaoying Cao, Jiaolong Chen, Jinghui Zhang, Wenzhi Cao, Yangjie Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a critical digital infrastructure, computing power has become the core productivity and a new engine driving economic growth in the digital economy. Nevertheless, the power-hungry nature of computing/data centers, representing the computing infrastructure, consumes a significant amount of electrical energy. Currently, China’s economy is transitioning from high-speed growth to high-quality development. It is imperative to study how to coordinate the development of computing power while ensuring its safety and achieving green and low-carbon goals. Based on an overview of the current status of computing power development, this study predicts the future demand for computing power in China, analyzes the …

Intelligent Protection Scheme Using Combined Stockwell-Transform And Deep Learning-Based Fault Diagnosis For The Active Distribution System, Latha Maheswari Kandasamy, Kanakaraj Jaganathan

Turkish Journal of Electrical Engineering and Computer Sciences

This study aims to perform fast fault diagnosis and intelligent protection in an active distribution network (ADN) with high renewable energy penetration. Several time-domain simulations are carried out in EMTP-RV to extract time-synchronized current and voltage data. The Stockwell transform (ST) was used in MATLAB/SIMULINK to preprocess these input datasets to train the adaptive fault diagnosis deep convolutional neural network (AFDDCNN) for fault location identification, fault type identification, and fault phase-detection for different penetration levels. Based on the AFDDCNN output, the intelligent protection scheme (IDOCPS) generates the signal for isolating a faulty section of the ADN. An intelligent fault diagnosis …

Advanced Hyperthermia Treatment: Optimizing Microwave Energy Focus For Breast Cancer Therapy, Burak Acar, Tuba Yilmaz Abdolsaheb, Ali Yapar

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a fast antenna phase optimization scheme to enable microwave power focusing for breast cancer hyperthermia. The power focusing is achieved through the maximization of the deposited electric field on the target malignant tumor tissue. To do so, a malignant breast tumor, the surrounding breast medium, and the skin of the breast are modeled as a cylindrical structure composed of eccentric cylinders, and electric field distribution is computed analytically in terms of cylindrical harmonics. This approach minimized the computational cost and simplified the breast medium model. To ensure applicability across various breast types, the dielectric properties (DPs) of …

Effects Of Unobservable Bus States On Detection And Localization Of False Data Injection Attacks In Smart Grids, Moheb Abdelmalak

USF Tampa Graduate Theses and Dissertations

In an era increasingly marked by sophisticated cyber-attacks, this thesis investigates the critical issue of bus unobservability in smart grids and its impact on the effectiveness of cyber-attack detection and localization models. Given that unobservability is a prevalent challenge in smart grids due to various factors, researchers have developed numerous algorithms for optimal Phasor Measurement Unit (PMU) placement under scenarios of limited observability. However, these models primarily focus on enhancing network observability, often without considering whether this placement optimally facilitates attack detection. This research is driven by the hypothesis that a deeper understanding of the effects of unobservable buses can …

Consensus-Based Virtual Leader Tracking Algorithm For Flight Formation Control Of Swarm Uavs, Berat Yıldız, Akif Durdu, Ahmet Kayabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

Technological developments in industrial areas also impact unmanned aerial vehicles (UAVs). Recent improvements in both software and hardware have significantly increased the use of many UAVs in social and military fields. In particular, the widespread use of these vehicles in social areas such as entertainment, shipping, transportation, and delivery and military areas such as surveillance, tracking, and offensive measures has accelerated the research on swarm systems. This study examined the previous investigations on swarm UAVs and aimed to create a more efficient algorithm. The effectiveness of the proposed algorithm was compared with other leader-based applications. A swarm consisting of 5 …

Cascade Controller Design Via Controller Synthesis For Load Frequency Control Of Electrical Power Systems, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

The regulation of tie-line electricity flow and frequency of electrical power systems (EPS) is crucial for ensuring their robustness to parameter changes and efficient management of disturbances. To this end, a novel cascade control design approach utilizing a serial Proportional-Integral-Derivative controller with a filter (PIDF) is proposed in this paper. The parameters of the controllers are derived analytically, and it is employed in both loops of the cascade control system to regulate the Load Frequency Control (LFC) of EPS. The implementation of PIDF controllers in both loops is utilized in the cascade control scheme for various power systems featuring different …

Development Of A Plant Growth And Health Monitoring System Using Imaging And Sensor Array Information For Cubesat Applications, Kat-Kim Phan

USF Tampa Graduate Theses and Dissertations

Space exploration has been a topic of interest in the scientific community, such as the planned missions to Mars. To accomplish this would require being able to provide astronauts with a steady supply of food beyond freeze-dried foods leading to the need to grow food in space. Although this is a topic still being investigated, the CubeSat platform opens the possibility of carrying out studies on plant growth under more strenuous space conditions unlike that in the International Space Station (ISS). Developing a plant-focused mission for a CubeSat, though, entails being able to develop a system to sustain plant life …

Comparing Task Graph Scheduling Algorithms: An Adversarial Approach, Jared Coleman, Bhaskar Krishnamachari

Computer Science Faculty Works

Scheduling a task graph representing an application over a heterogeneous network of computers is a fundamental problem in distributed computing. It is known to be not only NP-hard but also not polynomial-time approximable within a constant factor. As a result, many heuristic algorithms have been proposed over the past few decades. Yet it remains largely unclear how these algorithms compare to each other in terms of the quality of schedules they produce. We identify gaps in the traditional benchmarking approach to comparing task scheduling algorithms and propose a simulated annealing-based adversarial analysis approach called PISA to help address them. We …

A Deep Learning Convolutional Neural Network For Antenna Near-Field Prediction And Surrogate Modeling, Md Rayhan Khan, Constantinos L. Zekios, Shubhendu Bhardwaj, Stavros V. Georgakopoulos

Department of Electrical and Computer Engineering: Faculty Publications

This study investigates the use of deep learning techniques for building a generalized surrogate model that can accurately and very efficiently predict antenna performance parameters. Notably, we focus on applications where a substantial amount of simulation time is required and prior data is available for deep learning use. Specifically, for these applications, we introduce deep learning models that efficiently and reliably model the near-field of the antenna. These models, in turn, accurately predict far-field properties and essential antenna metrics, such as the reflection coefficient. To demonstrate the efficiency of our method, the widely used rectangular patch antenna is considered, encompassing …

Quantum-Powered Battery Scheduling In Modern Distribution Grids, Diba Ehsani

Electronic Theses and Dissertations

The rising need for exploiting a novel and evolved computation is an increasing concern in the power distribution system to address the exponential growth of distribution-connected devices. Scheduling numerous battery energy storage systems in an optimal way is one of the emerging challenges that will be more noticeable as the number of batteries, including residential, community, and vehicle batteries, increases in the grid. This thesis focuses on this topic and offers a necessary component in building the quantum-compatible distribution system of the future. Using a constrained quadratic model (CQM) on D-Wave’s hybrid solver as well as a binary quadratic model …

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …

Investigating Customer Churn In Banking: A Machine Learning Approach And Visualization App For Data Science And Management, Pahul Preet Singh, Fahim Islam Anik, Rahul Senapati, Arnav Sinha, Nazmus Sakib, Eklas Hossain

Electrical and Computer Engineering Faculty Publications and Presentations

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connection with the bank. Therefore, customer retention is essential in today’s extremely competitive banking market. Additionally, having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele. These factors make reducing client attrition a crucial step that banks must pursue. In our research, we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers. …

Design And Analysis Of Zero Voltage Switching Hybrid Voltage Divider, Stephen Ulysses Alvarado Estrada

Master's Theses

This work explores the design, construction, and analysis of a novel DC-DC converter which incorporates combinations of switching capacitors and inductors to achieve an integer voltage divider function, without the need for a feedback loop controller to achieve the desired output voltage. The proposed Hybrid Voltage Divider additionally provides zero voltage switching (ZVS) at turn on transitions which yields improved overall efficiency of the converter. Besides a proof-of-concept via computer simulations, another primary goal of this thesis is to demonstrate the functionalities of the proposed Zero Voltage Switching Hybrid Voltage Divider (ZVS-HVD) through hardware prototyping. The proposed ZVS-HVD was designed …

A Sindy Hardware Accelerator For Efficient System Identification On Edge Devices, Michael Sean Gallagher

Master's Theses

The SINDy (Sparse Identification of Non-linear Dynamics) algorithm is a method of turning a set of data representing non-linear dynamics into a much smaller set of equations comprised of non-linear functions summed together. This provides a human readable system model the represents the dynamic system analyzed. The SINDy algorithm is important for a variety of applications, including high precision industrial and robotic applications. A Hardware Accelerator was designed to decrease the time spent doing calculations. This thesis proposes an efficient hardware accelerator approach for a broad range of applications that use SINDy and similar system identification algorithms. The accelerator is …

Pa2blo: Low-Power, Personalized Audio Badge, Hemanth Sabbella, Dulaj Sanjaya Weerakoon, Manoj Gulati, Archan Misra

Research Collection School Of Computing and Information Systems

We present the hardware design and software pipeline for an ultra-low power device, in the form factor of a wearable badge, that supports energy efficient sensing, processing and wireless transfer of human voice commands and interactions. The proposed system, called PA2BLO, is envisioned to support both: (a) real-time, scalable, authorized voice based interaction and control of devices and appliances, and (b) longitudinal, low-power logging of natural voice interactions. PA2BLO in-troduces two key novel capabilities. First, it includes a low power, low-complexity voice authentication module that is able to reliably authenticate an authorized user only using low sampling rate (500 Hz) …