Digital Commons Network^™

Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion, Yi Luo, Jia Deng

Journal of System Simulation

Abstract: To improve the efficiency and quality of dynamic path planning for mobile robots in complex environments, this paper proposed a path planning algorithm that combined an improved RRT-connect with the DWA. Two expanding random trees were introduced for alternating expansion, and a dynamically restricted sampling area was set to reduce the randomness of the sampling process while ensuring the probability completeness of the algorithm. A target bias adaptive step size strategy was employed to enhance the target orientation of the random tree expansion process. A greedy strategy was adopted to prune redundant nodes in the path and smooth the …

An Integrated Decision Support System For Bim Level 3 Implementation, Lama Abumoeilak, Salwa Beheiry, Serter Atabay

Civil and Environmental Engineering Faculty Publications

The Architecture, Engineering, and Construction (AEC) sector accounts for 39% of greenhouse gas emissions, 40% of solid waste, and 12% of potablewater usage globally, underscoring the need for sustainable, efficient practices. Building Information Modeling (BIM) offers a digital framework to address these challenges through lifecycle management, collaboration, and efficiency gains. However, most organizations remain at BIM Level 2 maturity, which limits their potential for full integration. This study proposes a comprehensive Decision Support System (DSS) to facilitate the adoption of BIM Level 3, with an emphasis on collaboration, sustainability, and data interoperability. The DSS integrates Structural Equation Modeling (SEM), Analytical …

Reliability Targeted Snow Loads And Winter Wind Parameters For Locations Outside Of The Conterminous United States, Brennan L. Bean, Nicholas Brimhall, Bikram Bhusal, Marc Maguire, Maha Moussa

Browse all Datasets

The national building standard ASCE 7 moved to reliability-targeted snow loads (RTSLs) in the 2022 version. This necessitates the development of RTSLs for international locations. This repository contains the data and code needed to produce RTSLs and Winter Wind Parameters for locations outside of the Conterminous United States (OCONUS). It relies on annual maximum snow loads provided in a separate data release (see Brimhall et al. 2025).

Tacscope: A Miniaturized Vision-Based Tactile Sensor For Surgical Applications, Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She

School of Industrial Engineering Faculty Publications

The lack of tactile feedback in robot-assisted minimally invasive surgery (RMIS) limits surgeons’ ability to palpate tissues, a critical technique for locating abnormalities such as tumors. To address this challenge, we introduce TacScope, a novel, vision-based tactile sensor leveraging the magnification properties of a spherical-surface elastomer to provide tactile feedback for advanced clinical applications. TacScope features a robust, low-cost, and easyly fabricate design, enabling seamless integration into surgical robotic setups. It reconstructs high-resolution 3D geometry from variations in particle-density distribution across its elastomer surface, requiring only a single image for calibration. The curved elastomer membrane alters particle-density distribution under …

Structure And Principle Of Operation Of The Vibrational Pressing And Dehydration Unit For Semi-Soft Cheese, Qobiljon Akmal Ugl Muxiddinov, Shakhnoza Abduvaxitovna Sultanova, Azamat Bakir Ugli Usenov

Technical science and innovation

This paper investigates the structural design and operational principles of a vibrational pressing and dehydration unit developed for semi – soft cheese production. The equipment is engineered to optimize whey expulsion and moisture uniformity in curd blocks by combining mechanical pressure with controlled vibration. The unit comprises a stainless – steel vibrating chamber, drainage plates with micro – perforations, and an adjustable frequency–amplitude control system. Vibrations in the range of 20–60 Hz are applied during pressing, promoting more efficient capillary flow and enhancing the separation of whey from curd particles. The process ensures uniform density and texture across the cheese …

Intrinsic Defects (Vacancies And Antisites) In Neutron Irradiated Cdsip2 Crystals, Timothy D. Gustafson, Elizabeth M. Scherrer, Nancy C. Giles, Kevin T. Zawilski, Peter G. Schunemann, Jonathan E. Slagle, Kent L. Averett, Larry E. Halliburton

Faculty Publications

Cadmium silicon phosphide (CdSiP₂) is a nonlinear optical material widely used in optical parametric oscillators. Intrinsic defects (vacancies and antisites) are responsible for unwanted broad optical absorption bands in these crystals that degrade the performance of the devices. In the present work, optical absorption and electron paramagnetic resonance (EPR) spectra are acquired (at room temperature and 12 K, respectively) from a neutron-irradiated CdSiP₂ crystal. After the irradiation, the crystal is highly absorbing from the band edge near 600 nm to beyond 1.3 μm because of overlapping defect-related absorption bands. Heating to 550 °C removes nearly all the …

Structural And Biological Properties Of Chitosan/Copper Polymetallic Complexes Synthesized From Apis Mellifera-Derved Chitosan, Dilnoza Sohibovna Isomitdinova, Gulnora Akmalovna Ikhtiyarova, Nazira Madusmanovna Kuchkarbayeva, Nafisa Akhrorovna Ergasheva

Technical science and innovation

In this study, a chitosan/copper (Ch/Cu²⁺) polymetallic complex was synthesized from chitosan obtained by the cryogenic method from Apis mellifera bees. The structural and physicochemical properties of the complex were investigated using FTIR, UV-Vis, XRD, TGA, and DLS analyses. FTIR spectra showed shifts in absorption bands at 1400-1339 cm⁻¹ and 1640-1550 cm⁻¹, confirming the coordination of Cu²⁺ ions with amino and hydroxyl groups. UV-Vis spectra revealed absorption peaks in the 410-540 nm range, while XRD analysis indicated new crystalline peaks at 2θ = 24°, 27°, and 37°. Thermal analysis demonstrated high thermal stability of the complex, and DLS confirmed a …

Exploring The World Of Medical Exoskeleton Robots: A Classification Guide, Javlonbek Rakhmatillaev, Vytautas Bučinskas

Technical science and innovation

This article describes the classification of exoskeletons. This classification is based on the use of exoskeletons in the medical field, shape, power source, generation, parts related to the human body, structural material, and control forms based on sensor and actuator devices. In addition, examples of each category are given. The main goal is to comprehensively evaluate medical exoskeletons, pay special attention to their functions and goals, conduct scientific research, and further develop these devices. As a result, a completely new type of classification of medical exoskeletons was developed. The developed new type of classification serves as an important guide in …

Measures To Improve The Structure And Operating Principle Of Perovsite Light-Emitting Devices, Latofat Utkir Qizi Shuhratova, Rustam Rashidovich Kabulov, Farrux Anvar Ugli Akbarov, Anvar Akbarovich Alimov

Technical science and innovation

Since the discovery of the unique properties of perovskite materials, these materials have been used as active layers in various optoelectronic devices. In particular, perovskite-based light-emitting diodes (LEDs) have attracted the attention of many researchers as a highly efficient and versatile technology for lighting and display devices. Perovskite-based LEDs allow for tunable light emission and can be manufactured at low cost and with flexible fabrication technology. These advantages make them suitable for use in devices ranging from modern displays to wearable electronics. Despite their potential, solving problems such as material stability and industrial scale is one of the current challenges …

Methodology For Creating An Intelligent Mechatron Module Based On A Synergistic Approach, Nurbek Rustamovich Matyokubov, Temurbek Omonboyevich Rakhimov

Technical science and innovation

This article is devoted to the methodology of creating an intelligent mechatron module based on a synergistic approach. Creating a multi-coordinate intelligent mechatron module and expanding the functional capabilities of the controlled object based on them, allows to optimize the dynamic characteristics. Also, the methodology for creating an intelligent mechatronic module based on a synergistic approach allows for the integration of electrical, magnetic, and mechanical components into a single circuit, the integration of technical parameter modification, and the integration of processing functions into a single information-measuring module. In addition, the article proposes a Eurorhythm scheme for expressing how …

Scalable Biosynthesis And Recovery Of Poly-3-Hydroxybutyrate Produced From Cotton-Derived Glucose By Cupriavidus Necator, Ashley M. Clark, Lucia E. Gargano, Gabriella M. Fioravanti, Hannah M. Schapiro, Ron G. Kander

School of Design and Engineering Papers

To combat the growing issue of petroleum plastic waste, alternative bio-based polymers are being developed. Many of these biopolymers are made from bio-derived materials, or are biodegradable, but the most promising polymers fall in both categories. Polyhydroxyalkanoates (PHAs) are one such class of polymers, and poly-3-hydroxybutyrate (P3HB), the most popular PHA, has shown great potential. This study utilized two types of cotton-derived glucose, alongside commercial glucose, as a feedstock for the biosynthesis of P3HB by Cupriavidus necator (also known as Ralstonia eutropha). The fermentation took place in a 2-L bioreactor, showing potential for scale-up. A single-solvent extraction method was …

An Integrated Pcb-Based Heating And Auto-Ranging Platform For Volatile Organic Compound (Voc) Detection Using Carbon Nanotube Based Sensors, Thomas Kalach

USF Tampa Graduate Theses and Dissertations

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, …

Assessing Riparian Evapotranspiration Dynamics In A Water Conflict Region In Nebraska, Usa, Ivo Z. Gonçalves, Burdette Barker, Christopher M. U. Neale, Derrel L. Martin, Sammy Z. Akasheh

Civil and Environmental Engineering Faculty Publications

The escalating pressure on water resources in agricultural regions has become a catalyst for water conflicts. The adoption of innovative approaches to estimate actual evapotranspiration (ETa) offers potential solutions to mitigate conflicts related to water usage. This research presents the application of a remote sensing-based methodology for estimating actual evapotranspiration (ETa) based on a two-source energy balance model (TSEB) for riparian vegetation in Nebraska, US using the Spatial EvapoTranspiration Modeling Interface (SETMI). Estimated results through SETMI and field data using the eddy covariance system (EC) considering the period 2008–2013 were used to validate the energy balance components and ETa. Modeled …

Climate Change Projections Through Optimized Machine Learning And Deep Learning Models: A Comprehensive Analysis, Hala H. Youssef, Salma S. Mohammed, Hanan M. Amer, Abeer T. Khalil

Mansoura Engineering Journal

One major worldwide issue that has far-reaching effects on environmental stability and the avoidance of natural disasters is climate change. Developing efficient mitigating strategies depends on precise climate change forecasts. To predict important climate change indicators, including temperature fluctuations, greenhouse gas (CO2, N2O, CH4, and SF6) emissions, population dynamics, sea level changes, Arctic Sea ice extent, and Antarctica mass, this study evaluated the predictive capabilities of several Machine Learning (ML) and Deep Learning (DL) techniques. The set of machine learning algorithms includes Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Support Vector Machines (SVMs), Artificial Neural Networks (ANN), Random Forest (RF), …

Improved Streamflow Forecasting Through Swe-Augmented Spatio-Temporal Graph Neural Networks, Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar

Computer Science Student Research

Streamflow forecasting in snowmelt-dominated basins is essential for water resource planning, flood mitigation, and ecological sustainability. This study presents a comparative evaluation of statistical, machine learning (Random Forest), and deep learning models (Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Spatio-Temporal Graph Neural Network (STGNN)) using 30 years of data from 20 monitoring stations across the Upper Colorado River Basin (UCRB). We assess the impact of integrating meteorological variables—particularly, the Snow Water Equivalent (SWE)—and spatial dependencies on predictive performance. Among all models, the Spatio-Temporal Graph Neural Network (STGNN) achieved the highest accuracy, with a Nash–Sutcliffe Efficiency (NSE) of 0.84 …

Evaluation Of Different Design Standards For The Design Of Axial Loaded Concrete Filled Steel Tube Columns Under Fire, Ebtsam Youssef Ibrahim Abd El Ghaffar, Nabil Said Mahmoud, Fikry A. Salem, Mohammed. M. Ghannam

Mansoura Engineering Journal

This paper compares various codes and standards for the behavior of “Concrete-Filled Steel Tubes” (CFST) columns under fire and axial load. The codes evaluated include European standards (EC4.2 and EC3.2), the American standard (AISC 360), and the Australian standard (AS/NZS 2327). The fire resistance of Concrete-Filled Steel Tubular (CFST) and steel hollow (SH) columns was assessed using a computer program developed with Visual Studio .NET. The program's results were compared with previous experimental data to evaluate the accuracy of various codes and standards in predicting the behavior of these columns under fire conditions. This study highlights the importance of selecting …

Incorporating The Influence Of Vehicle Mix On Crash Frequency And Severity, Shahrior Pervaz, Manmohan Joshi, Tanmoy Bhowmik, Dewan Ashraful Parvez, Kai Wang, John N. Ivan, Naveen Eluru

Civil and Environmental Engineering Faculty Publications and Presentations

The current approaches for crash frequency and severity prediction in the Highway Safety Manual (HSM) do not employ vehicle mix information. In this research effort, we build advanced alternatives to HSM methods while incorporating vehicle mix information. Two model systems—(a) multivariate Poisson-lognormal model and (b) negative binomial-ordered probit fractional split model—are estimated by incorporating vehicle mix variables. The developed model systems can also capture the influence of observed and unobserved heterogeneity of different independent variables including vehicle mix variables. We estimate the models for three facility types including Urban Arterial 4-Lane Divided segments, Rural 3-Leg STOP-Controlled and Rural 4-Leg STOP-Controlled …

Using Serial Open Circuit Potentiometry To Study Ce And Gd Deposition In Molten Licl-Kcl Eutectic, Ranon G. Fuller, Guy L. Fredrickson, Devin Rappleye

Faculty Publications

The ability to electrochemically separate individual species in a pyrochemical reprocessing salt relies on first being able to detect a separation in their reaction potentials. This requires the ability to measure reaction potentials with extreme precision. In this work, we introduce a novel technique called serial open circuit potentiometry (SOCP) and demonstrate its effectiveness at precisely measuring metal deposition reaction potentials. SOCP has several advantages over traditional open circuit potentiometry, including its abilities to quantify the error of measured equilibrium potentials by averaging many individual OCP measurements, determine overpotential deposition nucleation potentials to instrument precision, and simultaneously determine the nucleation …

Honey, I Shrunk The Pk Weir: A Case Study Of Burton Pond Dam, David Bisio

4th International Workshop on Labyrinth and Piano Key Weirs

Between a low-head tidal environment, razor-thin hydraulic margins, and a long list of site restrictions, the Burton Pond Dam Rehabilitation project offered the chance to pursue a one-of-a-kind solution: a miniature stainless steel piano key weir as part of a new mixed active-passive spillway. This case study will explore how established hydraulic designs were modified specifically for the site and verified with computational flow dynamics; how the innovative cantilevered geometry was analyzed structurally with finite element modeling; and how detailing, fabrication and constructability were considered throughout the design process. From conceptual-level design submissions to the final construction walkthrough, the whole …

Synthetically Expressive: Evaluating Gesture And Voice For Emotion And Empathy In Vr And 2d Scenarios, Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel Mcdonnell, Cathy Ennis

Conference papers

The creation of virtual humans increasingly leverages automated synthesis of speech and gestures, enabling expressive, adaptable agents that effectively engage users. However, the independent development of voice and gesture generation technologies, alongside the growing popularity of virtual reality (VR), presents significant questions about the integration of these signals and their ability to convey emotional detail in immersive environments. In this paper, we evaluate the influence of real and synthetic gestures and speech, alongside varying levels of immersion (VR vs. 2D displays) and emotional contexts (positive, neutral, negative) on user perceptions. We investigate how immersion affects the perceived match between gestures …

An Innovative Association Of Fusegate And Pk-Weir, F. Lempérière, A. Chapuis, F. Del Rey, C. Bessière

4th International Workshop on Labyrinth and Piano Key Weirs

The combination on the same dam of Piano Key weir (PK-Weir) and fusible structures offers a highly effective passive solution for managing flood discharges. This concept first introduced by Hydrocoop in 2015 as « Innovative Associated Spillways » can leverage the strength of each system. More than 30 years after its first application, the returns of experience of the Hydroplus Fusegate® system applications on more than 80 dams in 25 different countries have confirmed their reliability in terms of sequentially overturning on the downstream side for the correct design flood. With their high discharge capacity at low head, PK-Weirs optimize …

The Performance Of Satellite-Based Precipitation Data To Reproduce Observed Precipitation In Tanzania's Little Ruaha Catchment, Florence H. Mahay

Tanzania Journal of Engineering and Technology (TJET)

Satellite-based precipitation datasets have emerged as promising tools for addressing rainfall data scarcity in regions with limited ground observations, such as Sub-Saharan Africa. This study evaluates the performance of five satellite-based precipitation products CHIRPS, CPC, GPCC, MERRA-2, and ERA5 in capturing rainfall characteristics over the Little Ruaha Catchment in Tanzania. The assessment was carried out at daily, monthly, and seasonal timescales and focused on key rainfall indices including onset and cessation dates, length of the rainy season, total rainfall, and frequency of rainy days. Validation was conducted using statistical indicators such as the correlation coefficient (r), Nash–Sutcliffe Efficiency (NSE), Root …

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 …

Condition Optimization For The Synthesis Of Castor Oil Templated Mesoporous Silica, Godlisten Namwel Shao

Tanzania Journal of Engineering and Technology (TJET)

The present work provides suitable conditions for the synthesis of mesoporous materials with improved porosity using an optimization technique. The proposed preparation method involves forming final products by varying the amount of castor oil, media, and template removal. The obtained samples were examined by TGA, XRD, DRIFT and nitrogen physisorption studies. It was observed that the porosity of the obtained samples was dependent on the conditions under which the materials were synthesized. All synthesized materials showed the Type IV adsorption-desorption isotherm features of mesoporous, regardless of the conditions utilized during the synthesis. The sample synthesized using 2.5 g of a …

Cnn-Based Hybrid Model For Detecting Blight Diseases In Potato Crops With Advanced Image Processing Techniques, Farian S. Ishengoma

Tanzania Journal of Engineering and Technology (TJET)

Potato production plays a vital role in global agriculture as a major food source for large populations. However, potato crops are highly susceptible to diseases, particularly Early Blight and Late Blight, which result in substantial yield losses. Timely detection and effective control of these diseases are essential for maintaining stable crop output. This study explores the integration of Convolutional Neural Networks (CNNs) and advanced image processing techniques to differentiate between diseased and healthy potato plants accurately. Two datasets comprising original and enhanced images were used to train four CNN models: InceptionV3, Xception, Densenet201, and Resnet152V2. The original images underwent background …

Enhancing 6g Network Security With Quantum Key Distribution: A Comprehensive Review, Bassma M. Kamil

Al-Esraa University College Journal for Engineering Sciences

With the considerable progress of sixth-generation (6G) networks further on the horizon, security has attracted much attention in the face of increasingly sophisticated threats, especially from quantum computing. Classical cryptographic schemes based on computational hardness are becoming more and more brittle, as they can easily be attacked with a quantum computer. Quantum Key Distribution (QKD) arises as a promising tool for information-theoretic security through quantum mechanics to obtain an unbreakable key by exchanging unknown bit sequences. In this paper, we provide an extensive survey on the integration of QKD both in the envisioned 6G architecture, including current implementations, technical feasibility, …

Protection The Nfv Net-Work Using The Random Forest Classification, Mustafa H. Taha, Ibtesam Jomaa Hawi, Wafaa Waheeb Abdullah Ali

Al-Esraa University College Journal for Engineering Sciences

A misuse attack is the most common and dangerous type of attack that could target NFV (Network Function Virtualization). In a misuse attack, the attacker attempts to consume the NVF environment’s resources by sending a large amount of traffic. To protect the NFV environment, an early and accurate misuse attack detection system has been proposed based on NFV and Random Forest Classifier. The proposed model starts with importing the dataset and analyzing it then pre-processing and feature selection using a PSO (particle swarm optimization) Test algorithm, classification is based on the most common and efficient machine learning technique, which is …

Foundations Of Artificial Intelligence In Healthcare Diagnostics: A Systematic Survey, Raghad Tariq Al-Hassani

Al-Esraa University College Journal for Engineering Sciences

Artificial Intelligence (AI) is becoming the cornerstone of the future of healthcare diagnostics, that has to ability to change the healthcare diagnostic landscape in terms of diagnostic accuracy, speed, and availability. This systematic review investigates the basic methods, tools, applications, and challenges involved in the integration of AI in diagnostic medicine. It emphasizes the using of machine learning models, deep learning networks (e.g., CNNs), NLP for clinical documentation, and smart computing infrastructures, such as edge device and IoMT. They are making possible real-time, data-driven decision making that is already at human-expert-level performance or, in some cases, even better (in the …

Groundwater Quality Analyses For Irrigation Purposes In Salah Al-Din, Iraq: A Review, Noor A. Radhi, Dawood E. Sachit, Abdul-Sahib T. Al-Madhhachi

Al-Esraa University College Journal for Engineering Sciences

The focus of this study is the effect of the physical and chemical characteristics of groundwaters on plants and agricultural crops, following the last studies on this matter. The results underscore the necessity for groundwater treatment before its utilization in irrigation for sustainable agricultural farming. It is also possible to identify which crop type can be grown in well-watered land, according to the characteristics of irrigation water and the yield of each crop. The study also introduces some ideas about irrigation water quality parameters such as Electrical conductivity (EC), Total Dissolved Solids (TDS), pH, Chloride (Cl^–), Sodium (Na …

Towards Autonomous Energy Management: Machine Learning For Effective Auditing And Optimization, Sameh O. Abdellatif, Sherif Ashraf, Mira Mohsen

Electrical Engineering

This study presents a fully automated procedure for energy management and auditing, applicable to a diverse range of residential and commercial loads, leveraging machine learning techniques across three key phases: load classification, benchmarking, and smart monitoring. The model effectively categorizes energy loads based on consumption patterns, establishes performance benchmarks through historical data analysis, and employs real-time monitoring to identify inefficiencies and predict future energy usage. Evaluating the model through four distinct case studies demonstrates its capability to optimize energy consumption in a techno-economic manner, achieving significant energy savings of 34.73 MWh/year for essential loads in Egypt, 215.67 MWh/year for HVAC …