Miracle-dz/UniFAR-FTUs huggingface dataset:
Easy Tracking of UAV Using PID Controller

The main objective of the present paper is to design a mathematical model to estimate the behavior of flying robots with four motors (quadcopters) controlled by three algorithms; P depends on the present errors; I on the accumulation of past errors, and D a prediction of future errors (PID controller design) with simple strategy. In this regard, a governing equation of motion based on Newton Euler’s formularies for rigid body dynamics is presented. In order to design the control algorithm some assumptions are made such as the ignorance of the blade flapping, surrounding fluid velocities. This exclusion of parameters makes the model flexible, simple, and allows the control to be more efficiency and easy to designed without the need of expensive computation. The simulation studies are carried out using MATLAB program.
Assessing the applicability of groundwater monitoring data in the modelling of soil water retention characteristics

The present work focuses on an assessment of the applicability of groundwater table (GWT) measures in the modelling of soil water retention characteristics (SWRC) using artificial neural network (ANN) methods. Model development, testing, validation and verification were performed using data collected across two decades from soil profiles at full‐scale research objects located in Southwest Poland. A positive effect was observed between the initial GWT position data and the accuracy of soil water reserve estimation. On the other hand, no significant effects were observed following the implementation of GWT fluctuation data over the entire growing season. The ANN tests that used data of either soil water content or GWT position gave analogous results. This revealed that the easily obtained data (temperature, precipitation and GWT position) are the most accurate modelling parameters. These outcomes can be used to simplify modelling input data/parameters/variables in the practical implementation of the proposed SWRC modelling variants.
Subjective Evaluation of Orchestral Music Recording Techniques for Three-Dimensional Audio

A double-blind study was conducted to evaluate a recently developed microphone technique for threedimensional orchestral music capture, optimized for 22.2 Multichannel Sound. The proposed technique was evaluated against a current 22.2 production standard for three-dimensional orchestral music capture, as well as a coincident, higher order ambisonics capture system: the EigenmikeTM. Analysis of the results showed no significant difference in listener evaluation between the proposed technique and the current production standard in terms of the subjective attributes “clarity”, “scene depth”, “naturalness”, “environmental envelopment”, and “quality of orchestral image”.
The effect of time-periodic base angular motions upon dynamic response of asymmetric rotor systems

The effect of time-periodic base angular motions upon dynamic response of asymmetric rotor systems is investigated in this article. Both the disk and rotating shaft with asymmetric cross sections are considered. The rigid rotor base rotates around the three axis with time-varying angular speeds. Equations of motion for every components (asymmetric disk and shaft elements) are derived to assembe the finite element model of the whole rotor-bearing system. Due to the rotor asymmetries and angular motions of the rigid base, the finite element model has time-variable mass, gyroscopic, and stiffness coefficients. Parametric instability regions and rotor center orbits are compared with references’ results for model verifications. Then, forced responses of the system under unbalanced excitations, shaft asymmetry, and base angular motions are obtained. Effects of various types of angular motions, amplitudes, and frequency of base motions upon the response spectra and external resonances are discussed. As long as the periodic base angular motion is considered, both the response spectra and external resonances change significantly. Additional frequencies, including base frequency and combined frequencies, are found in the response spectra. Besides the critical and half-critical resonances (for the asymmetric rotor system), there are multiple resonances after considering the periodic base motions.
SkinProfiler: low-cost 3D scanner for skin health monitoring with mobile devices

Melanoma is one of the top three most common skin cancers, originating from skin lesions and moles. Keeping track of skin lesion and mole developments in a precise and long-term manner has long been recommended but overlooked for the lack of accurate and easy-to-access tools. In response, we develop SkinProfiler, a low-cost mobile profiling tool for long-term skin health monitoring. To use SkinProfiler, users clamp an LED ring accessory onto smartphone cameras and take photos of the skin region of interest using the SkinProfiler app. Our modified photometric stereo algorithm leverages 17 photos taken with the skin surface lightened under various conditions to reconstruct 3D models of the skin surfaces. Our system stores 3D information for skin lesion and mole monitoring and diagnosis. The total cost of hardware assembly is under 20 dollars. We ran a preliminary evaluation to verify the performance of our tool. Based on the results, we propose several future steps including evaluations in clinical settings to complete this research.
A new twelve-transistor approximate 4:2 compressor in CNTFET technology

ABSTRACT Power consumption is a serious concern in the field of digital design. Reducing power supply voltage, power gating, transistor downscaling, voltage over scaling, applying modern technology and approximate computing are some candidate means in reducing power consumption. Among these candidates, approximate computing can generate a trade-off between accuracy and power-delay-area efficiency in error resilient applications. According to Moore’s law together with CMOS problems in nanoscale regime, modern technologies emerge to solve these problems. Among these recent technologies, CNTFET technology is considered as promising. As multiplication is frequently applied in multimedia processing, implementing efficient multipliers constitute critical. Compressors are fundamental elements in reduction tree multipliers and improve their efficiency, thus an improvement in multipliers’ performance. A new 12-transistor approximate 4:2 compressor is proposed here. This new appropriate compressor, in terms of area, power consumption, accuracy and reliability design, is more efficient than its existing counterparts.
Detection of Helminthosporium Leaf Blotch Disease Based on UAV Imagery

Helminthosporium leaf blotch (HLB) is a serious disease of wheat causing yield reduction globally. Usually, HLB disease is controlled by uniform chemical spraying, which is adopted by most farmers. However, increased use of chemical controls have caused agronomic and environmental problems. To solve these problems, an accurate spraying system must be applied. In this case, the disease detection over the whole field can provide decision support information for the spraying machines. The objective of this paper is to evaluate the potential of unmanned aerial vehicle (UAV) remote sensing for HLB detection. In this work, the UAV imagery acquisition and ground investigation were conducted in Central China on April 22th, 2017. Four disease categories (normal, light, medium, and heavy) were established based on different severity degrees. A convolutional neural network (CNN) was proposed for HLB disease classification. The experiments on data preprocessing, classification, and hyper-parameters tuning were conducted. The overall accuracy and standard error of the CNN method was 91.43% and 0.83%, which outperformed other methods in terms of accuracy and stabilization. Especially for the detection of the diseased samples, the CNN method significantly outperformed others. Experimental results showed that the HLB infected areas and healthy areas can be precisely discriminated based on UAV remote sensing data, indicating that UAV remote sensing can be proposed as an efficient tool for HLB disease detection.
Survey Tools for Faculty to Quickly Assess Multidisciplinary Team Dyanmics in Capstone Courses

Many engineering faculty have limited skills and/or assessment tools to evaluate team dynamics in multidisciplinary team-based capstone courses. Rapidly deployable tools are needed here to provide proactive feedback to teams to facilitate deeper learning. Two surveys were developed based on industrial and organizational psychology theories around desired high performance industry characteristics. A case study experiment was conducted in an architectural engineering capstone. Here, these surveys were deployed in conjunction with traditional qualitative verbal feedback and technical assessments. Results presented here suggest that capstone teams exhibit high-functioning attributes of effective teams based on the course formulation. Team dynamics evolved as the course progressed naturally and with the help of faculty based on the survey results. Discussions in this paper detail survey development, implementation, and sampled trends to represent how to use and interpret the survey output. Furthermore, best practices for implementing these ideas in other courses is touched on. Evidence is presented to support the surveys as a tool and to show correlations between the results and other technical assignments.
Driver Drowsiness Detection Using Condition-Adaptive Representation Learning Framework

We propose a condition-adaptive representation learning framework for driver drowsiness detection based on a 3D-deep convolutional neural network. The proposed framework consists of four models: spatio-temporal representation learning, scene condition understanding, feature fusion, and drowsiness detection. Spatio-temporal representation learning extracts features that can describe motions and appearances in video simultaneously. Scene condition understanding classifies the scene conditions related to various conditions about the drivers and driving situations, such as statuses of wearing glasses, illumination condition of driving, and motion of facial elements, such as head, eye, and mouth. Feature fusion generates a condition-adaptive representation using two features extracted from the above models. The drowsiness detection model recognizes driver drowsiness status using the condition-adaptive representation. The condition-adaptive representation learning framework can extract more discriminative features focusing on each scene condition than the general representation so that the drowsiness detection method can provide more accurate results for the various driving situations. The proposed framework is evaluated with the NTHU drowsy driver detection video dataset. The experimental results show that our framework outperforms the existing drowsiness detection methods based on visual analysis.
Hydraulic Properties of Baled Switchgrass and Miscanthus

Abstract. This study characterized the hydraulic properties within baled switchgrass ( L., variety Alamo) and miscanthus (x), thereby enabling a better understanding of moisture changes in baled biomass during on-farm storage and/or high-solids bioconversion. Fully saturated bales were drained by gravity, and the moisture content was determined over 60 h. The average initial moisture content ranged between 55.9% and 71.9% (w.b.) for switchgrass and between 60.5% and 73.9% (w.b.) for miscanthus bales depending on the dry bale density. As the bale drained by gravity, rapid leaching of water was observed within the first 0.1 h, with a reduction in moisture content of 7.3 and 7.0 percentage points (w.b.) for switchgrass and miscanthus, respectively. Leaching then continued at a steady rate until termination of the experiment, with further reductions of 4.3 and 4.4 percentage points (w.b.) for switchgrass and miscanthus, respectively. Final moisture contents after 60 h ranged from 45.8% to 58.3% for switchgrass and from 48.7% to 60% for miscanthus, with the higher moisture contents observed in the lowest density bales. Hydraulic conductivity tests were carried out with bales of switchgrass and miscanthus with a constant head system. The average saturated hydraulic conductivity ranged between 0.103 and 0.616 cm s-1 for baled switchgrass and between 0.219 and 0.658 cm s-1 for baled miscanthus depending on the bale density. The matric suction of baled switchgrass was also assessed at variable densities and moisture contents using the contact filter paper method. The van Genuchten parameters were found to range between 0.235 and 0.270 m-1 for α and between 5.415 and 10.345 for n, depending on the density. Infiltration tests were also carried out on baled switchgrass at variable densities and moisture contents using a minidisk infiltrometer. The curve-fitting parameters of Philip‘s two-term equation ranged between 0.086 x 10-6 and 0.779 x 10-6 cm s-1 for C1 and between 0.200 and 5.805 x 10-6 cm s-1/2 for C2, depending on the density and moisture content. The unsaturated hydraulic conductivity ranged between 0.019 and 0.272 cm s-1, while sorptivity ranged between 0.048 and 2.103 cm s-1/2, depending on the density and moisture content. These results provide data required to evaluate water flow through variable-density rectangular bales and indicate a potential to remove end-products of biomass conversion from baled biomass.
Studying Driving Behavior on Horizontal Curves using Naturalistic Driving Study Data

Many studies have been conducted to develop models to predict speed and driver comfort thresholds on horizontal curves, and to evaluate design consistency. The approaches used to develop these models differ from one another in data collection, data processing, assumptions, and analysis. However, some issues might be associated with the data collection that can affect the reliability of collected data and developed models. In addition, analysis of speed behavior on the assumption that vehicles traverse horizontal curves at a constant speed is far from actual driving behavior. Using the Naturalistic Driving Study (NDS) database can help overcome problems associated with data collection. This paper aimed at using NDS data to investigate driving behavior on horizontal curves in terms of speed, longitudinal acceleration, and comfort threshold. The NDS data were valuable in providing clear insight on drivers’ behavior during daytime and favorable weather conditions. A methodology was developed to evaluate driver behavior and was coded in Matlab. Sensitivity analysis was performed to recommend values for the parameters that can affect the output. Analysis of the drivers’ speed behavior and comfort threshold highlighted several issues that describe how drivers traverse horizontal curves that need to be considered in horizontal curve design and consistency evaluation.
Immunogenicity Following Two Doses of the BBIBP-CorV Vaccine and a Third Booster Dose with a Viral Vector and mRNA COVID-19 Vaccines against Delta and Omicron Variants in Prime Immunized Adults with Two Doses of the BBIBP-CorV Vaccine

Coronavirus disease 2019 (COVID-19) booster vaccination is being comprehensively evaluated globally due to waning immunity and the emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Therefore, this study aimed to evaluate antibody responses in individuals vaccinated with two doses of BBIBP-CorV vaccine and to explore the boosting effect of the different vaccine platforms in BBIBP-CorV-primed healthy adults, including viral vector vaccine (AZD122) and mRNA vaccines (BNT162b2 and mRNA-1273). The results showed that, in the BBIBP-CorV prime group, the total receptor-binding domain (RBD) immunoglobulin (Ig) and anti-RBD IgG levels waned significantly at 3 months after receiving the second dose. However, after the booster, RBD-specific binding antibody levels increased. Neutralizing antibody measured by a surrogate neutralization test showed of inhibition over 90% against the SARS-CoV-2 delta variant but less than 70% against omicron variant after the third dose on day 28. All booster vac-cines could induce the total IFN-{gamma} T-cell response. The reactogenicity was acceptable and well tolerated without serious adverse events. This study supported administration of the third dose with either viral vector or mRNA vaccine for the BBIBP-CorV-primed individuals to stimulate antibody and T cell responses.
Managerial Control and the Limits to Employee Participation in Retail Work Spaces: Evidence from a UK IKEA Store

This article contributes to labour process debates around managerial control and worker autonomy in the retail workplace. Through critical analysis of managerial strategies in the production of organisational space within an IKEA store, it explores how spatial design and practice shape managerial control and employee participation. Rather than the rhetoric of employee participation espoused by IKEA, our findings emphasise how managers use space to foster employee commitment to corporate objectives. While employees do exercise their own agency and spatial practice, their actions are moulded and constrained by dominant organisational structures and managerial strategies. As such, the article augments existing labour process research by developing new insights about how the spatial dimension shapes managerial control in retail workplaces. Although workers are far from the passive recipients of management decisions apparent in much labour process theory, their participation largely serves the strategic visions and spatial plans of their employer.
Machine Learning Approaches for Outdoor Air Quality Modelling: A Systematic Review

Current studies show that traditional deterministic models tend to struggle to capture the non-linear relationship between the concentration of air pollutants and their sources of emission and dispersion. To tackle such a limitation, the most promising approach is to use statistical models based on machine learning techniques. Nevertheless, it is puzzling why a certain algorithm is chosen over another for a given task. This systematic review intends to clarify this question by providing the reader with a comprehensive description of the principles underlying these algorithms and how they are applied to enhance prediction accuracy. A rigorous search that conforms to the PRISMA guideline is performed and results in the selection of the 46 most relevant journal papers in the area. Through a factorial analysis method these studies are synthetized and linked to each other. The main findings of this literature review show that: (i) machine learning is mainly applied in Eurasian and North American continents and (ii) estimation problems tend to implement Ensemble Learning and Regressions, whereas forecasting make use of Neural Networks and Support Vector Machines. The next challenges of this approach are to improve the prediction of pollution peaks and contaminants recently put in the spotlights (e.g., nanoparticles).
Seismic Performance of a New Structural Design Solution for First-Story Isolated RC Buildings with Coupled Beam-Column Connections

This study proposes a new structural design of the first-story isolation system in reinforced concrete (RC) structures. Compared to the conditional buildings with independent columns, this new design integrates the independent columns with beams to increase the seismic capacity of the building by increasing the integrated stiffness of the coupled columns and the stability of the isolation system. The seismic responses of the proposed structure and the corresponding isolation effect were investigated by performing a series of numerical simulation and shaking table tests on a typical 7-story RC frame structure. The structure models were subjected to four earthquake waves with two PGAs (peak ground acceleration) of 0.30 g and 0.40 g for seismic analysis regarding the peak acceleration and inter-story displacement. Both simulation and testing results showed that the story acceleration and inter-story displacement of the superstructure in the isolated model decreased significantly. While the substructure below the isolation layer had a negligible decrease of acceleration. The connection of beams with concrete columns significantly increases the seismic capacity of the RC frame buildings compared to non-isolated frame buildings. The coupled beam-column connections could thus be potentially adopted in the practical first-story isolation system to avoid the requirements of large column stiffness and large column size.
High-frequency feedback robust control for flocking of multi-agent system with unknown parameters

ABSTRACT In this paper, a kind of high-frequency feedback robust control for flocking of a multi-agent system with unknown parameters is put forward in detail. Firstly, a high-frequency feedback robust control scheme is proposed for the flocking problem of a multi-agent system with unknown parameters. Secondly, through the employment of Lyapunov stability theory, it's proved that velocity error is gradually stabilized and collisions between agents are also avoided. In addition, the high-frequency feedback robust control for flocking of a multi-agent system with unknown parameters is further proved. Finally, it is verified with the help of numerical simulation.
3-D EHD Enhanced Natural Convection over a Horizontal Plate Flow with Optimal Design of a Needle Electrode System

The present study is intended to investigate the effect of electrohydrodynamic (EHD) enhanced heat transfer on natural convection flow. The flow is assumed to be three-dimensional, turbulent and steady. An experiment was carried out to verify the accuracy of the numerical results and to provide electric properties such as induced current and power consumption to be used as the criteria for the numerical solution procedures. An optimal analysis was carried out along with the simplified conjugate-gradient method, where the objective function was defined as the heat transfer enhancement per input power, which is maximized by searching for the optimum electrode pitch ( SL ) and height ( H ) combination. A search for the optimum electrode pitch ( SL ) and electrode height ( H ), ranging from 50 mm < SL < 200 mm and 15 mm < H < 55 mm, respectively, with V 0 (12, 14, 16, 18 and 20 kV) and Δ T (33, 53 and 73 K), was performed, respectively. The results showed that the maximum heat transfer enhancement per power consumption reached 4.42–9.72.
Examining the myths of connected and autonomous vehicles: analysing the pathway to a driverless mobility paradigm

Connected and autonomous vehicles (CAVs) could become the most powerful mobility intervention in the history of human race; possibly greater than the conception of the wheel itself or the shift from horse-carriages to automobiles. Despite CAVs' likely traffic safety, economic, environmental, social inclusion and network performance benefits their full-scale implementation may not be as predictable, uncomplicated, acceptable and risk-free as it is often communicated by a large share of automotive industries, policy-makers and transport experts. Framing an 'unproven', 'disruptive' and 'life-changing' intervention, primarily based on its competitive advantages over today's conventional automobile technologies, may create misconceptions, overreaching expectations and room for errors that societies need to be cautious about. This article 'tests' eleven myths referring to an overly optimistic CAVs' development and adoption timeline. This approach highlights unresolved issues that need to be addressed before an inescapable CAV-based mobility paradigm transition takes place and provides relevant policy recommendations on how to achieve that.