Miracle-dz/UniFAR-FTUs huggingface dataset:
Wave diffraction and radiation from a semi-submersible floating foundation for wind turbines: A semi-analytical study

Many marine structures are composed of vertical axisymmetric floats. In this paper, a semi-analytical model based on the linear potential flow theory and an eigenfunction expansion method is developed to study wave diffraction and radiation by an array of cylindrical structures. Each structure can be formed by three coaxial cylinders of different dimensions. Based on the semi-analytical model, a constrained matrix equation of motion is presented and solved to evaluate the performance of multiple interconnected cylindrical structures. In order to verify the accuracy of the semi-analytical model, a typical OC4-DeepCwind floating offshore wind turbine (FOWT) is selected for validation. The validated model is, then, applied to study the effect of base column submergence depth, radius, and thickness on the motion response of a semi-submersible platform. Although the results of this study are of significance for the selection of the optimum semi-submersible FOWT for specific locations (with specific prevailing wave directions), the focus of this work was placed on the semi-analytical model itself, which is efficient in modeling the interaction of the wave field and can be used in future FOWT projects.
Background Modeling using PID Control

Methods for common background modeling and detection have been advanced based on the assumption that the extracts and scenes are at a stagnant state with a slight movement. This research delivers an algorithm based on the Proportional-Integral-Derivative (PID) controller to efficiently process an accurate detection of a real-time mobile object. In comparison, unlike the usual methods, the outcomes derived from experiments based on PID demonstrated that the suggested method acclimates swiftly to the changes of the dynamic background. This method was effective and successful in accomplishing precisely detecting mobile objects and suppressing lot of the false detections possibly produced by the dynamic changes in the background.
Automated Non-Gaussian Clustering of Polarimetric SAR

This paper presents an automatic image segmentation method for Polarimetric SAR data. It utilises the full polarimetric information and incorporates texture by modelling with a non-Gaussian distribution. The modelling is based upon the well known product model, with a Gamma distributed texture parameter, leading to the K-Wishart model for the covariance matrix. The automatic clustering is achieved through a modified Expectation Maximisation algorithm, with an additional Goodness-of-fit test allowing splitting and merging of clusters. The resulting image segmentation depicts the statistically significant clusters within the image. Real world examples are shown to demonstrate the technique.
The Optimal Time for Initiating Probiotics for Preterm and Very-Low-Birth-Weight Infants: A 10-Year Experience in a Single Neonatal Intensive Care Unit

Purpose The starting time for probiotic supplementation in preterm infants after birth varies widely. This study aimed to investigate the optimal time for initiating probiotics to reduce adverse outcomes in preterm or very low birth weight (VLBW) infants. Methods Medical records of preterm infants born at a gestational age (GA) of <32 weeks or VLBW infants in 2011–2020 were reviewed respectively. The infants who received Saccharomyces boulardii probiotics within 7 days of birth were grouped into an early introduction (EI) group, and those who received supplemented probiotics after 7 days of birth were part of the late introduction (LI) group. Clinical characteristics were compared between the two groups and analyzed statistically. Results A total of 370 infants were included. The mean GA (29.1 weeks vs. 31.2 weeks, p<0.001) and birth weight (1,235.9 g vs. 1491.4 g, p<0.001) were lower in the LI group (n=223) than in the EI group. The multivariate analysis indicated that factors affecting the LI of probiotics were GA at birth (odds ratio [OR], 1.52; p<0.001) and the enteral nutrition start day (OR, 1.47; p<0.001). The late probiotic introduction was associated with a risk of late-onset sepsis (OR, 2.85; p=0.020), delayed full enteral nutrition (OR, 5.44; p<0.001), and extrauterine growth restriction (OR, 1.67; p=0.033) on multivariate analyses after adjusting for GA. Conclusion Early supplementation of probiotics within a week after birth may reduce adverse outcomes among preterm or VLBW infants.
Subdivision for Modeling and Animation

We describe a multiresolution representation for meshes based on subdivision, which is a natural extension of the existing patch-based surface representations. Combining subdivision and the smoothing algorithms of Taubin [26] allows us to construct a set of algorithms for interactive multiresolution editing of complex hierarchical meshes of arbitrary topology. The simplicity of the underlying algorithms for refinement and coarsification enables us to make them local and adaptive, thereby considerably improving their efficiency. We have built a scalable interactive multiresolution editing system based on such algorithms.
Photovoltaic Cells Anomaly Classification Using Deep Learning Techniques

In recent years, solar photovoltaic (PV) systems have seen widespread use in the field of environmentally friendly energy harvesting. Additionally, the rate at which units reach the end of their useful life cycle is increasing. Heavy metals like lead, tin, and cadmium can be found in solar modules and cause environmental damage. Regular inspections and maintenance for your solar modules are essential to extending their useful life, cutting down on energy waste, and keeping the environment safe. This paper proposes a system that uses PV cell electroluminescence (EL) and deep learning techniques to efficiently screen for and categorize solar modules that exhibit anomalous behavior. Deep neural networks can accurately predict anomalies and classify types of anomalies. Using PV cell electroluminescence, we propose convolution neural network techniques based on residual network architecture and ensemble technology to accurately predict and classify anomalous solar modules.
Pre-service Teacher Experience in Designing Lesson Using TPACK-21 CL in Teaching Reading for High School Students

This study looked into the experiences of a pre-service teacher in designing a lesson using Technological Pedagogical Content Knowledge for 21st Century Learning framework. The pre-service teacher integrated the use of technology for the teaching learning process because it was to support the students to achieve the 21st skills, especially in reading. This study drew on the narrative inquiry methods to present the finding. The pre-service teacher designed the lesson followed by a reflection. This long scientific endeavor leads the preservice teacher to consider to develop technological pedagogical content knowledge (TPACK) skills to enable herself to become a professional teacher. The finding showed that though the pre-service teacher was finally able todesign the lesson and implement it in the classroom, she needs further discussion with the lecturers and the tutor teacher. The development skills from the experience is important for a teacher to be able to design meaningful learning for the students.
Nanomanipulation of carbon nanotubes using fiber probe-based near-field optical tweezers

In recent years, the near-field optical tweezers have gradually attracted more and more attention due to their high accuracy and low impact. This paper presents a new method for manipulating carbon nanotubes using fiber-optic probes to generate near-field optical tweezers based on a Scanning Electron Microscope(SEM). An electric field analysis model of the near-field optical tweezers was constructed, and the model was analyzed using the Finite Difference Time Domain(FDTD) method to simulate the manipulation process of near-field optical tweezers, which verified the feasibility of its basic theory and the near-field optical tweezers' operating ability. The bending deformation of carbon nanotubes was realized by the integration of the near-field enhanced optical tweezers based on SEM. This method of nanomanipulation with near-field enhanced optical tweezers based on SEM has the advantages of real-time operation and non-contact, which will open up new ideas and technologies for subsequent research.
Multi-sensory fusion of wearable sensors for automatic grasping and releasing with soft-hand exoskeleton

This paper presents a fully integrated soft-hand exoskeleton enabling automated grasping and releasing functions thanks to the multi-sensory fusion. We use enfolded soft textile actuators to assist the hand, IMU sensors for the arm and hand orientations, and customized soft sensors for tactile feedback from the fingers. We propose a state machine controller that uses the information from tactile sensors and the IMUs to switch between different states to trigger grasping and releasing. The control strategy requires no additional user input; it is designed for meal-eating scenarios. Ten healthy participants instructed not to move their hands tested the system performing 190 trials on five tasks: pouring, drinking, eating a fruit, using a fork, and using a spoon. Objects are randomly placed in four different locations in front of the participant. 97.4% of the trials were successfully accomplished. Furthermore, 78.1% grasps and 83.8% releases are triggered by the first attempt. Compared with no assistant condition of a healthy hand, the system reduced 32.2% of muscle activities and required 2.57 more times to finish the task.
What Time is it at (16) Psyche?

The Psyche Project is a mission to the asteroid (16) Psyche, featuring three science instruments, a gravity science investigation, and a Deep Space Optical Communication technology demonstration. (16) Psyche, located in the asteroid belt between Mars and Jupiter, will be the first potential metal world-instead of rock or ice─visited by the National Aeronautics and Space Administration (NASA). This Jet Propulsion Laboratory (JPL) managed mission will explore Psyche after a 2023 launch and a multi-year cruise. The mission uses a science instrument suite consisting of a pair of multispectral imagers, a gamma ray and neutron spectrometer, and a pair of magnetometers in a gradiometry arrangement. The Psyche timekeeping system is comprised of functions distributed throughout the Spacecraft, Payload, and Mission Systems. Readers will be introduced to the clocks and time systems used by the mission and the various correlation activities which transfer time knowledge between the Spacecraft Avionics and the ground and between the Spacecraft Avionics and the Payload instruments. This core of this paper provides a brief overview of the driving pointing control, pointing reconstruction, on-board ephemeris knowledge, and optical navigation requirements of the Psyche mission. Each of these requirements has a budget which suballocates the total allowable error to various sources, one of which is the timekeeping error. This paper will present a bottoms-up analysis of the timekeeping uncertainty for each driving pointing and navigation requirement for each phase of the mission. It will present the Project time budgets and walk through how each line item was calculated and the assumptions made in these calculations. The approaches and results of oscillator thermal stability, oscillator aging, flight system thermal performance, and avionics time correlation performance testing will be presented as supporting evidence of the time budget line items. The paper will provide readers an understanding of how to bound the uncertainty of reconstructed UTC measurement time, on-board ephemeris time knowledge, and predicted UTC command execution time for a deep space Spacecraft without an ultra-stable oscillator using the Psyche timekeeping architecture and mission plan as an example.
Solar Thermal Collector System with Parabolic Collector for Applications in Organic Rankine Cycle: Design, Manufacturing and Testing

Generating power using an Organic Rankine Cycle (ORC) has the advantage of converting waste energy into useful power. This technology can utilize various low-level heat sources such as biomass, engine waste heat, geothermal and solar, and it significantly reduces thermal pollution as well as the reliance on fossil fuels. In this research, a parabolic collector with a tube length of 18.12 meters was designed and manufactured. The results showed that the parabolic trough can reach a temperature of 56.6℃ with a water flow rate of 0.042kg/s, from an initial temperature of 28.2℃ during a 2-hour test. The average turbine output power was 430.04 W in theoretical calculations and 248.57 W in reality for the ORC system. The highest thermal efficiency was achieved at a turbine inlet temperature of 63.5℃ and a turbine inlet pressure of 10.5 bar, with a value of 4.489%. Overall, using ORC technology can effectively utilize low-level heat sources and contribute to reducing reliance on fossil fuels and thermal pollution.
Modified Variation of Parameters Method for Differential Equations

In this paper, we apply the Modified Variation of Parameters Method (MVPM) for solving nonlinear differential equations which are associated with oscillators. The proposed modification is made by the elegant coupling of traditional Variation of Parameters Method (VPM) and He's polynomials. The suggested algorithm is more efficient and easier to handle as compare to decomposition method. Numerical results show the efficiency of the proposed algorithm.
A preliminary study of micro thin wall fabrication on PMMA using an in-house developed micromilling machine

Micromilling has been increasingly employed for fabrication of micro geometrical features in many miniature parts, but the machining of micro thin walls is considered as difficult due to low material rigidity, and easy deformation by cutting force. In this study, a low-cost and reconfigurable 3-axis micromilling machine was developed by integrating a XYZ precision motion stage with a high-speed spindle. The development and configuration of the micromilling platform is introduced, along with a calibration of the motion accuracy and a vision-assisted tool tip positioning approach. Preliminary experimental study was conducted to fabricate micro thin walls on PMMA workpiece under different conditions. While the thin walls with a target thickness of 300 μm were successfully machined, it was found that there were many issues encountered in the machining of the 30 μm thin walls. The defects were analyzed to identify the root-causes and future research directions.
Hand gesture recognition using EMD and VMD techniques

A new approach based on decomposition techniques for better feature extraction of recognition of dynamic hand gesture recognition system. In this paper we are analyzing a comparison of two useful noise removal techniques, empirical mode decomposition (EMD) and variation mode decomposition (VMD) for strong occlusions, nonstationary and weak robustness complex backgrounds. So implemented results show the feature extraction by using EMD with different values of intrinsic mode function (IMFs) and VMD with different values of modes and obtain a noise free signal. A non-stationary electromyography (EMG) signal of hand movement is measured of VIVA (Vision for Intelligent Vehicles and Applications) dataset, where eight subjects are performing 19 types of dynamic hand gestures in a vehicle and this is captured by Microsoft kinetic.
Design of Vector-Vortex Coronagraphs for Exoplanet Science using a Six Meter Space Telescope

In this paper, we present a concept for an active, 6-meter space telescope (6MST) for space-based general astrophysics and consider its potential for coronagraphy. The telescope operates in spectral regions from about 100nm up to $\boldsymbol{2}\upmu\mathrm{m}$, thus having the range comparable to Large Ultraviolet Optical Infrared Surveyor (LUVOIR) and Habitable Exoplanet Observatory (HabEx) in the longer wavelength end. In this paper, we produce the design for a vector-vortex coronagraph instrument for exoplanet work. We evaluate the impact of Primary Mirror (PM) segment gaps on the 20% broadband contrast floor when a charge 4 or charge 6 vortex mask and two $\boldsymbol{64}\mathrm{x}\boldsymbol{64}$ actuators sequential Deformable Mirrors (DM's) are used in the coronagraph, and compare the performance of a Lyot-mask and a pupil apodization mask relative to one another.
Efficient Computational Tools for Nonlinear Flight Dynamic Analysis in the Full envelope

Equilibrium analysis for an aircraft is very important for control law design and development. Computation of equilibrium point is also required to initialize the aircraft model in flight simulation. This equilibrium point is obtained by solving for the zeros of the right hand sides of the aircraft equations of motion simultaneously. Mathematically, this is achieved using the conventional numerical optimization methods which are iterative and require more number of iterations. The typical flight envelope of a fighter aircraft ranges from 20% to 200% of the speed of sound and sea level to 15 km in terms of altitude. This places significant computational demand to generate hundreds of linearized aircraft mathematical models needed for control law design and evaluation. The Approximate Trim calculations, proposed in this paper, provide good initial guess values throughout the flight envelope for the conventional optimization methods resulting in faster convergence. Thus the time and effort required to generate the aircraft mathematical models is reduced. The aerodynamic database is obtained by wind tunnel testing. To reduce the wind tunnel testing costs, the aerodynamic database with respect to angle of attack is generated within the aircraft performance limits. This results in a reduction in the range of the aerodynamic data with respect to angle of attack as speed increases. Therefore, only three points are available for the interpolation at the extreme points in the flight envelope. In order to solve this problem, we propose barycentric (triangular) interpolation in combination with the conventional rectangular interpolation for these two dimensional tables.
A Novel Technique To Realize a Flexible Tactile Sensor

A cost-effective, flexible tactile sensor with a PDMS (polydimethylsiloxane) layer with a nanostructure pattern serving as the dielectric layer has been demonstrated. The creation of the PDMS layer with a nanostructure design uses an anodized porous alumina (APA) layer as a mold. The APA is created by electrochemically etching the aluminum material in oxalic acid. Due to the great elasticity and deformability of the nanostructures on the PDMS layer, the created tactile sensor device demonstrated remarkable sensitivity. For a pressure of 0.1 kPa, the tactile sensing device was shown to have a sensitivity of 1.1 kPa-1. The sensor can find applications in tactile sensing in low-pressure ranges (0-0.3kPa), where soft touch is desirable for non-destructive sensing.
Higher-order MRFs based image super resolution: MMSE or MAP?

A trained filter-based higher-order Markov Random Fields (MRFs) model the so called Fields of Experts (FoE), has proved a highly effective image prior model for many classic image restoration problems. Generally, two options are available to incorporate the learned FoE prior in the inference procedure: (1) sampling-based minimum mean square error (MMSE) estimate, and (2) energy minimization-based maximum a posteriori (MAP) estimate. It is well-known the sampling-based MMSE estimate is very time consuming, but the MAP inference has a remarkable advantage of high computational efficiency. In a recent paper, the FoE prior model was exploited for the single image super resolution (SR) task by using the MMSE inference, based on a seemingly correct conclusion that the MAP inference of the FoE prior based model, which leads a non-convex optimization problem, is prone to getting stuck in some bad local minima. However, in this letter, we demonstrate that this simpler inference criterion the MAP estimate, works equally well compared to the complicated MMSE estimate with exactly the same prior model. Moreover, with our discriminatively trained FoE prior model, the MAP inference can even lead to further improvements. Consequently, we argue that for higher-order natural image prior based SR problem, it is not necessary to employ the time consuming MMSE estimation.
Reliable p-type organic permeable base transistors—the missing component for integrated circuits

Due to their nm-range channel length, vertical organic transistors are gaining scientific interest to overcome the frequency limitations of lateral organic transistor. Especially, vertical organic permeable base transistors (OPBTs) with a structure resembling a vacuum-tube-triode stand out due to their excellent electrical performance. Recently, n-type OPBTs have been demonstrated with excellent performance and great potential to be applied in high-frequency logic circuits, display driving circuits, and light-emitting devices. However, achieving adequate p-type OPBTs to catch up with the performance of n-type devices is still challenging. Here, we report on the peculiar finding that the extended exposure of p-type OPBTs to ambient air during the fabrication has a positive effect on the electrical performance and tremendously improves the yield of devices to 100% . Upon exposing the fresh device to air, oxygen diffuses into the semiconductor layer interacting with the base electrode, which facilitates the formation of pinholes in the base and creates an insulator layer around the base. Moreover, as oxygen acts as a p-dopants to the p-type semiconductors used in this work, the device performance is further improved, manifesting in an increased on-state current. However, as the exposure time increases, different p-type organic semiconductors show different behavior depending on their ionization potential. Comparing two semiconductor materials with a difference in their ionization potential of 0.4 eV, we show that long-term degradation could be effectively suppressed. Therefore, the positive effect of air exposure could be utilized to optimize p-type OPBTs, which offers a simple and universal way to construct high performance p-type OPBTs and possibly also complementary circuits.
The impact of technology on the general insurance sector's organizational customers' perception of value

In this study, the impact of technology is especially examined as a factor in the determination of customer perceived value and satisfaction in the professional business-to-business services of the general insurance industry. Five hundred forty-seven relevant responses from randomly chosen Vietnamese consumers who bought insurance products were acquired using both a hypothetical-deductive method and an inductive technique employing structured questionnaires. The regression study shows that while technology and technical abilities are judged to be unimportant, risk coverage, reputation, reliability, and premium positively influence consumers' opinions of value toward insurance firms. As technology cannot replace the relationships developed with service professionals, organizational consumers do not view technology as a deciding factor when choosing insurance, so avoiding favoring technology over human interaction is imperative. This warning could impact people's views, quality of life, and society. The performance of service workers should be improved through soft HRM techniques in the future, and marketers and politicians should prioritize reputation-building initiatives and training in interpersonal communication. Future research on insurance purchase behavior in business-to-business settings, particularly in developing economies, can use the proposed model as a guide. Additionally, by concentrating on the most advantageous aspects of resource allocation, this framework provides invaluable insights for firms looking to create or strengthen their competitive advantage.