Engineering Commons^™

Simultaneous Evaluation Of Tibiofemoral And Patellofemoral Mechanics In Total Knee Arthroplasty: A Combined Experimental And Computational Approach, Yashar A. Behnam, Ahilan Anantha Krishnan, Hayden Wilson, Chadd W. Clary

Center for Orthopaedic Biomechanics: Faculty Scholarship

Contemporary total knee arthroplasty (TKA) has not fully restored natural patellofemoral (P-F) mechanics across the patient population. Previous experimental simulations have been limited in their ability to create dynamic, unconstrained, muscle-driven P-F articulation while simultaneously controlling tibiofemoral (T-F) contact mechanics. The purpose of this study was to develop a novel experimental simulation and validate a corresponding finite element model to evaluate T-F and P-F mechanics. A commercially available wear simulator was retrofitted with custom fixturing to evaluate whole-knee TKA mechanics with varying patella heights during a simulated deep knee bend. A corresponding dynamic finite element model was developed to validate …

Modeling Overdraft-Driven Nitrate Transport In Shallow Wells For Mitigation And Scenario Planning, Jonathan Cronk

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

In Nebraska, average nitrate concentrations in groundwater have doubled since 1974, making water quality management more important than ever. As droughts, heat waves, and floods become more common climate events, understanding their impacts will be necessary to make informed management decisions. Emerging literature describes that drought correlates to an increase in the concentration of nitrate-N at domestic and irrigation wells, however the relative contributions of the mechanisms thought to be responsible is currently unknown.

This research assessed the impact of recharge and pumping rate changes as two mechanisms affecting nitrate-N concentration during drought, assessed the relationship between well depth and …

Development Of A Hospital Discharge Planning System Augmented With A Neural Clinical Decision Support Engine, David Mulqueen

Dissertations

The process of discharging patients from a tertiary care hospital, is one of the key activities to ensure the efficient and effective operation of a hospital. However, the decision to discharge a patient from a hospital is complex, as it requires multiple interactions with nurses, family, consultants, health information records and doctors, which can be very time consuming and prone to error. This thesis descries how a neural network based Clinical Decision Support system can be developed, to help in the decision making process and dramatically reduce the time and effort in running the discharge process in a hospital. A …

Law School News: National Housing Advocate Named To Lead Rwu's New Real Estate Initiatives 02/08/2022, Roger Williams University School Of Law

Life of the Law School (1993- )

No abstract provided.

On The Use Of High-Frequency Surface Wave Oceanographic Research Radars As Bistatic Single-Frequency Oblique Ionospheric Sounders, Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, Teresa Updyke

CCPO Publications

We demonstrate that bistatic reception of high-frequency oceanographic radars can be used as single-frequency oblique ionospheric sounders. We develop methods that are agnostic of the software-defined radio system to estimate the group range from the bistatic observations. The group range observations are used to estimate the virtual height and equivalent vertical frequency at the midpoint of the oblique propagation path. Uncertainty estimates of the virtual height and equivalent vertical frequency are presented. We apply this analysis to observations collected from two experiments run at two locations in different years, but utilizing similar software-defined radio data collection systems. In the first …

Validation Of The Ambassador Questionnaire For Undergraduate Students Conducting Engineering Outreach, Melissa G. Kuhn, Shanan Chappell Moots, Joanna K. Garner

Center for Educational Partnerships Publications

Although K-12 engineering outreach commonly involves college students, the young professionals who act as ambassadors for their field are less likely to be studied than the students they serve. Yet, outreach activities may offer opportunities for undergraduate students to develop aspects of their professional selves. As there is currently no comprehensive measure that allows researchers, program evaluators, and outreach advisors to examine ambassadors' professional development and growth, this study sought to develop and validate an Ambassador Questionnaire (AQ). The multi-step process included the selection and adaptation of items from extant measures of engineering students' motivation, beliefs, professional skills, and perceptions …

Raising Dielectric Permittivity Mitigates Dopant-Induced Disorder In Conjugated Polymers, Meenakshi Upadhyaya, Michael Lu-Díaz, Subhayan Samanta, Muhammad Abdullah, Keith Dusoe, Kevin R. Kittilstved, Dhandapani Venkataraman, Zlatan Akšamija

Electrical and Computer Engineering Faculty Publication Series

Conjugated polymers need to be doped to increase charge carrier density and reach the electrical conductivity necessary for electronic and energy applications. While doping increases carrier density, Coulomb interactions between the dopant molecules and the localized carriers are poorly screened, causing broadening and a heavy tail in the electronic density-of-states (DOS). The authors examine the effects of dopant-induced disorder on two complimentary charge transport properties of semiconducting polymers, the Seebeck coefficient and electrical conductivity, and demonstrate a way to mitigate them. Their simulations, based on a modified Gaussian disorder model with Miller-Abrahams hopping rates, show that dopant-induced broadening of the …

Towards A More Effective Bidirectional Lstm-Based Learning Model For Human-Bacterium Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Yaochu Jin

Faculty of Engineering and Information Sciences - Papers: Part B

The identification of protein-protein interaction (PPI) is one of the most important tasks to understand the biological functions and disease mechanisms. Although numerous databases of biological interactions have been published in debt to advanced high-throughput technology, the study of inter-species protein-protein interactions, especially between human and bacterium pathogens, remains an active yet challenging topic to harness computational models tackling the complex analysis and prediction tasks. In this paper, we comprehensively revisit the prediction task of human-bacterium protein-protein interactions (HB-PPI), which is a first ever endeavour to report an empirical evaluation in learning and predicting HB-PPI based on machine learning models. …

A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The need for long-distance High Frequency (HF) communications in the 3-30 MHz frequency range seemed to diminish at the end of the 20th century with the advent of space-based communications and the spread of fiber optic-connected digital networks. Renewed interest in HF has emerged as an enabler for operations in austere locations and for its ability to serve as a redundant link when space-based and terrestrial communication channels fail. Communications system designers can create a “digital twin” system to explore the operational advantages and constraints of the new capability. Existing wireless channel models can adequately simulate communication channel conditions with …

Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin

Faculty of Engineering and Information Sciences - Papers: Part A

As an emerging pedagogy, micro learning aims to make use of people’s fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains showed …

A Novel Monte Carlo-Based Neural Network Model For Electricity Load Forecasting, Binbin Yong, Zijian Xu, Jun Shen, Huaming Chen, Jianqing Wu, Fucun Li, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

The ongoing rapid growth of electricity over the past few decades greatly promotes the necessity of accurate electricity load forecasting. However, despite a great number of studies, electricity load forecasting is still an enormous challenge for its complexity. Recently, the developments of machine learning technologies in different research areas have demonstrated its great advantages. General Vector Machine (GVM) is a new machine learning model, which has been proven very effective in time series prediction. In this article, we firstly review the basic concepts and implementation of GVM. Then we apply it in electricity load forecasting, which is based on the …

Apex2s: A Two-Layer Machine Learning Model For Discovery Of Host-Pathogen Protein-Protein Interactions On Cloud-Based Multiomics Data, Huaming Chen, Jun Shen, Lei Wang, Chi-Hung Chi

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun

Faculty of Engineering and Information Sciences - Papers: Part B

Micro learning aims to assist users in making good use of smaller chunks of spare time and provides an effective online learning service. However, to provide such personalized online services on the Web, a number of information overload challenges persist. Effectively and precisely mining and extracting valuable information from massive and redundant information is a significant preprocessing procedure for personalizing online services. In this study, we propose a deep sequence labelling model for locating, extracting, and classifying key information for micro learning services. The proposed model is general and combines the advantages of different types of classical neural network. Early …

A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam

Faculty of Engineering and Information Sciences - Papers: Part B

Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV …

Model Predictive Control For A New Magnetic Linked Multilevel Inverter To Integrate Solar Photovoltaic Systems With The Power Grids, A M. Mahfuz-Ur-Rahman, Md Rabiul Islam, Kashem M. Muttaqi, Danny Sutanto

Faculty of Engineering and Information Sciences - Papers: Part B

The multilevel inverters are becoming increasingly popular for use in the grid integration of wind and photovoltaic (PV) power plants due to their higher voltage handling capability and the better output power quality. There are several types of multilevel inverters that have been proposed in the literature; among them the active neutral point clamp (ANPC) multilevel inverters have been drawing significant attention specially for solving the problems with other multilevel inverters. However, with the increase of number of levels, the ANPC requires more electronic switches and flying capacitors, by which the complexity and the cost increases. In this paper, an …

Modelling The Addition Of Limestone In Cement Using Hydcem, Niall Holmes, Denis Kelliher, Mark Tyrer

Conference papers

Hydration models can aid in the prediction, understanding and description of hydration behaviour over time as the move towards more sustainable cements continues.

HYDCEM is a new model to predict the phase assemblage, degree of hydration and heat release over time for cements undergoing hydration for any w/c ratio and curing temperatures up to 450C. HYDCEM, written in MATLAB, complements more sophisticated thermodynamic models by predicting these properties over time using user-friendly inputs within one code. A number of functions and methods based on up to date cement hydration behaviour from the literature are hard-wired into the code along with …

Model Based Analysis Of The Accuracy And Precision Of Auscultatory Blood Pressure Measurements In Patients With Atrial Fibrillation, Charles F. Babbs

Weldon School of Biomedical Engineering Faculty Working Papers

Accurate measurement of blood pressure in the presence of atrial fibrillation remains an open problem. The present study combines the techniques of stochastic mathematical modeling with physiological models of the systemic circulation, cuff, and arm (1) to explore mechanisms underlying both the lack of accuracy and the lack of precision in cuff-based arterial pressure measurements during atrial fibrillation and (2) to develop strategies to correct for errors. Both the cardiovascular system and the measurement technique are described using mathematics, including both numerical techniques and analytical probability theory. Preliminary results with numerical models suggested that, despite variability, average systolic pressures tend …

Hydcem: A New Cement Hydration Model, Niall Holmes, Denis Kelliher, Mark Tyrer

Conference papers

Hydration models are useful to predict, understand and describe the behaviour of different cementitious-based systems. They are indispensable for undertaking long-term performance and service life predictions for existing and new products for generating quantitative data in the move towards more sustainable cements while optimising natural resources. One such application is the development of cement-based thermoelectric applications.

HYDCEM is a new model to predict the phase assemblage, degree of hydration, heat release and changes in pore solution chemistry over time for cements undergoing hydration for any w/c ratio and curing temperatures up to 450C. HYDCEM, written in MATLAB, is aimed at …

Using A Balloon-Launched Unmanned Glider To Validate Real-Time Wrf Modeling, Travis J. Schuyler, S. M. Iman Gohari, Gary Pundsack, Donald Berchoff, Marcelo I. Guzman

Chemistry Faculty Publications

The use of small unmanned aerial systems (sUAS) for meteorological measurements has expanded significantly in recent years. SUAS are efficient platforms for collecting data with high resolution in both space and time, providing opportunities for enhanced atmospheric sampling. Furthermore, advances in mesoscale weather research and forecasting (WRF) modeling and graphical processing unit (GPU) computing have enabled high resolution weather modeling. In this manuscript, a balloon-launched unmanned glider, complete with a suite of sensors to measure atmospheric temperature, pressure, and relative humidity, is deployed for validation of real-time weather models. This work demonstrates the usefulness of sUAS for validating and improving …

A Novel Empirical Heat Transfer Model For A Solar Thermal Storage Process Using Phase Change Materials, Yu Bie, Ming Li, Fei Chen, Grzegorz Krolczyk, Lin Yang, Zhixiong Li, Weihua Li

Faculty of Engineering and Information Sciences - Papers: Part B

Numerical and experimental analyses are often used to evaluate the solar thermal system with latent heat thermal energy storage (LHTES). However, the relationship between the numerical simulation and actual heat transfer process is still unclear. This work compares the simulated average temperature of two different phase change materials (PCMs) with experimental result at different operation conditions for the purpose of developing a temperature correction model. A novel empirical heat transfer model is then established to improve the simulation accuracy of PCM-based solar thermal systems. The contributions of this work include that (1) the system performance could be evaluated by the …

Leveraging Smote In A Two-Layer Model For Prediction Of Protein-Protein Interactions, Huaming Chen, Lei Wang, Chi-Hung Chi, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

The research of the mechanisms of infectious diseases between host and pathogens remains a hot topic. It takes stock of the interactions data between host and pathogens, including proteins and genomes, to facilitate the discoveries and prediction of underlying mechanisms. However, the incomplete protein-protein interactions data impediment the advances in this exploration and solicit the wet-lab experiments to examine and verify the latent interactions. Although there have been numerous studies trying to leverage the computational models, especially machine learning models, the performances of these models were not good enough to produce high-fidelity candidates of interactions data due to the nature …

Optimization Of Pv Powered Spd Switchable Glazing To Minimise Probability Of Loss Of Power Supply, Aritra Ghosh, Brian Norton

Articles

Suspended particle device (SPD) glazing is an electrically actuated switchable glazing. It requires alternate current (AC) power supply to switch from opaque to transparent state. To power this glazing using PV device requires inverter. Optimization of AC powered switchable SPD glazing using photovoltaic (PV) device has been evaluated using loss of power supply probability (LPSP). Electrically switchable direct current (DC) powered electrochromic glazing was also considered in this investigation as it doesn't need any inverter to couple with PV. It is concluded that behaviour of these glazings is the dominant factor in performance optimization outweighting than azimuthal orientation and inclination …

A Theoretical Model For Total Suction Effects By Tree Roots, Udeshini Pathirage, Buddhima Indraratna, Muditha Pallewattha, Ana Heitor

Faculty of Engineering and Information Sciences - Papers: Part B

Strengthening soft and weak soil by way of root reinforcement is a well-known strategy that is adopted worldwide. In Australia, native gum trees remain evergreen throughout the year and have been utilised to stabilise transportation corridors by way of reinforcement provided by the roots and the suction generated within the root domain as a function of evapotranspiration through the canopy. A mature gum tree can induce a missive total suction pressure exceeding 30MPa through its root water and solute uptake in terms of matric plus osmotic suction. This cumulative effect of matric and osmotic suctions contributes to the overall shear …

Microstructural Evaluation Of Aluminium Alloy A365 T6 In Machining Operation, Bankole I. Oladapo, S. Abolfazl Zahedi, Francis T. Omigbodun, Edwin A. Oshin, Victor A. Adebiyi, Olaoluwa B. Malachi

Electrical & Computer Engineering Faculty Publications

The optimum cutting parameters such as cutting depth, feed rate, cutting speed and magnitude of the cutting force for A356 T6 was determined concerning the microstructural detail of the material. Novel test analyses were carried out, which include mechanical evaluation of the materials for density, glass transition temperature, tensile and compression stress, frequency analysis and optimisation as well as the functional analytic behaviour of the samples. The further analytical structure of the particle was performed, evaluating the surface luminance structure and the profile structure. The cross-sectional filter profile of the sample was extracted, and analyses of Firestone curve for the …

Physical Modeling Of Flow Nets In Groundwater And Determination Of Hydraulic Conductivity, Hannah Nicholas, Moses Karakouzian

AANAPISI Poster Presentations

The goal of this study is to physically model the paths that water particles take through soil, and estimate hydraulic conductivity for several soil configurations. Water paths, or flow lines, are shown by injecting dye into sand contained in a rectangular acrylic glass tank with a vertical barrier in the center; water is poured on one side of the tank and a pump is used to maintain constant head loss. If flow lines are formed, a flow net is to be drawn using photos of the tank and hydraulic conductivity is to be calculated.

This project consists of four phases: …

Analytical Cpg Model Driven By Limb Velocity Input Generates Accurate Temporal Locomotor Dynamics, Sergiy Yakovenko, Anton Sobinov, Valeriya Gritsenko

Faculty & Staff Scholarship

The ability of vertebrates to generate rhythm within their spinal neural networks is essential for walking, running, and other rhythmic behaviors. The central pattern generator (CPG) network responsible for these behaviors is well-characterized with experimental and theoretical studies, and it can be formulated as a nonlinear dynam- ical system. The underlying mechanism responsible for locomotor behavior can be expressed as the process of leaky integration with resetting states generating appropriate phases for changing body velocity. The low-dimensional input to the CPG model generates the bilateral pattern of swing and stance modulation for each limb and is consistent with the desired …

A Self-Organized Learning Model For Anomalies Detection: Application To Elderly People, Nicolas R. Verstaevel, Jean-Pierre George, Carole Bernon, Marie-Pierre Gleizes

SMART Infrastructure Facility - Papers

In a context of a rapidly growing population of elderly people, this paper introduces a novel method for behavioural anomaly detection relying on a self-organized learning process. This method first models the Circadian Activity Rhythm of a set of sensors and compares it to a nominal profile to determine variations in patients' activities. The anomalies are detected by a multi-agent system as a linear relation of those variations, weighted by influence parameters. The problem of adaptation to a particular patient then becomes the problem of learning the adequate influence parameters. Those influence parameters are self-adjusted, using feedback provided at any …

Formulation Of A Model Predictive Control Algorithm To Enhance The Performance Of A Latent Heat Solar Thermal System, Gianluca Serale, Massimo Fiorentini, Alfonso Capozzoli, Paul Cooper, Marco Perino

Faculty of Engineering and Information Sciences - Papers: Part B

Model predictive control has proved to be a promising control strategy for improving the operational performance of multi-source thermal energy generation systems with the aim of maximising the exploitation of on-site renewable resources. This paper presents the formulation and implementation of a model predictive control strategy for the management of a latent heat thermal energy storage unit coupled with a solar thermal collector and a backup electric heater. The system uses an innovative Phase Change Material slurry for both the heat transfer fluid and storage media. The formulation of a model predictive controller of such a closed-loop solar system is …

Developing A Theoretical Model And Questionnaire Survey Instrument To Measure The Success Of Electronic Health Records In Residential Aged Care, Ping Yu, Siyu Qian

Faculty of Engineering and Information Sciences - Papers: Part B

Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: …

Model Predictive Control (Mpc) For Enhancing Building And Hvac System Energy Efficiency: Problem Formulation, Applications And Opportunities, Gianluca Serale, Massimo Fiorentini, Alfonso Capozzoli, Daniele Bernardini, Alberto Bemporad

Faculty of Engineering and Information Sciences - Papers: Part B

In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems and the availability of a significant amount of monitored building data. MPC has found successful implementation in building thermal regulation, fully exploiting the potential of building thermal mass. Moreover, MPC has been positively applied to active energy storage systems, as well as to the optimal management of on-site renewable energy sources. MPC also opens up several opportunities …