Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Perceived Overqualification of the employees of millennial generation on Job Crafting in the Background of Popular Higher Education

Overqualification appears commonly in China with the development of higher education. The study takes 308 employees of millennial generation as samples, using SPSS24.0 and LISREL8.7 statistical software to verify the effect of perceived overqualification on employees’ job crafting, and the mechanism of goal orientation. Results show: (1)perceived overqualification has a significant negative impact on employee job crafting; (2)Learning goal orientation and proving goal orientation significantly reduce the negative impact of perceived overqualification on job crafting.
Influence of GFP GAN on Melanoma Classification

Imaging is widely used to detect and diagnose Melanoma skin cancer early. The ISIC facilitates public reposit to collect, label, and categorize malignant and benign images. It also provides relevant metadata for these images from dermatologists, radiologists, or researchers. The ever-growing uses of dermoscopy and the complexity of the imaging process make it difficult to find the correct pattern in images of Melanoma skin cancer. Thus, while evaluation of performance metrics of classification methods continues to be inappropriate or not as per our expectations, many artifacts and noise such as hair, veins, and water residue make images very complex.Consequently, inspired and motivated by our previous study outcome when applying classification methods (CNN, RNN, and XG-Boost) on Melanomas’ images dataset, we found that the border detection and feature extraction for classification methods was challenging. Therefore, we applied Generative Facial Prior (GFP) Generative Adversarial Network (GAN) method to preprocess the Melanoma images. We also changed a few architectures and optimization methods for these classification algorithms. Finally, an extensive evaluation of the validation dataset is conducted. After that, it is compared with the values of performance metrics with previous results. This outcome impacts the dermatologist, scientific, and medical community. As a result, it is an excellent service to humanity to cure the deadliest form of skin cancer - Melanoma.
Retrieving significant wave height in the Indian Ocean near Visakhapatnam using Jason-2 altimeter data

Five-parameter model (BETA5) has been used to derive significant wave height (SWH) using 20-Hz Jason-2/OSTM Ku band waveforms in the Bay of Bengal basin of the Indian Ocean near the Indian city of Visakhapatnam for the years 2010–2012. Majority of the waveforms are traditional ocean-like waveforms based on Brown model. Nevertheless, quite a few of them have shapes differing significantly from the Brown model. Historically, two standard methods have been used for waveform retracking. One is maximum likelihood estimator (MLE) with 4 parameters, i.e. MLE4 (OCEAN retracker), which uses analytical second-order Brown model and the second one using first-order Brown model is MLE with three parameters, i.e. MLE3. It has been found in the study that standard MLE retrackers are not appropriate for retracking the nontraditional waveforms. Estimated SWHs have been validated against SWH measured by a buoy located in the close proximity of Visakhapatnam. SWH from BETA5 retracker matches buoy-derived SWH quite well except for a positive bias. Also, the bias is less for SWH retrieved using BETA5 than using MLE retrackers. Quantitatively, at a distance of 8 km from the coast correlation coefficient between BETA5 retracked SWH and buoy measured SWH is 0.85 and the unbiased root mean square error (RMSE) of the retracked SWH is 0.26 m. These are better than the corresponding values for MLE3 and OCEAN retrackers.
Data Analytics in Farming: Rice price prediction in Andhra Pradesh

The variances regarding prices of horticultural commodities adversely affect the nations GDP. The ranchers are genuinely and monetarily influenced as their long stretches of difficult work go to no end. Forecast of the prices might help the farming production network in settling on vital choices in limiting and dealing with the danger in value variances. By the way of outcome of the diminution of crop yield making due to uneven atmosphere circumstances and global warming. Rice is a significant yield developed in India, with Andhra Pradesh (AP) state being second as far as creation. At present ranchers in AP are moving from rice development to different harvests on account of worth variances and environmental variation. In this research, the costs of rice in AP remain anticipated utilizing time-series using data analytics like Machine Learning (ML) models. The prototypes SARIMA, Holt-Winter's Periodic technique, and Long Short-Term Memory (LSTM) Neural Networks (NN)be situated and utilized, and their recital was assessed dependent on the RMSE esteem on the rice database whose costs from 2001 to 2020. The conclusions demonstrate that the recommended process, LSTM neural network method is actual expectant and finest method which is suitable for the data.
Multi-Objective Symbolic Regression for Data-Driven Scoring System Management

Scores are mathematical combinations of elementary indicators (EIs) widely used to measure complex phenomena. Upon the theoretical framework definition, score construction requires a method to aggregate EIs. Aggregation is usually chosen among known methodologies fixing its shape through a try and error approach. Only then are the predictive power, the distribution of the index, and its ability to stratify the population measured. In this paper, we propose a novel data-driven approach that generates analytic aggregation methods relying on multi-objective symbolic regression. We translate the properties that the index must exhibit into optimization goals so that optimal index candidates replicate target variables, data balancing, and stratification. We run experiments on real data sets to solve three main score management problems: data-driven score simplification, generation, and combination. The results obtained show the effectiveness and robustness of the proposed approach.
Flame Stabilization in High-Pressure Liquid Oxygen/Methane Rocket Engine Combustion

Flame stabilization in the near-injector region of a subscale liquid propellant rocket combustion chamber has been investigated using optical diagnostics. Several different single shear coaxial injectors have been used to inject liquid oxygen (LOX) and methane at relevant operating conditions. Three main operating points cover the range of sub-, near-, and superciritical conditions with respect to the thermodynamic cirtical point of oxygen. Whereas liquid temperatures of about 270 K. Similar to previous investigations performed with LOX/H2 combustion, spontaneous OH chemiluminescene has been detected to characterize the flame anchoring zone near the LOX post tip. Theoretical considerations have indicated that the binary mixture of oxygen and methane shows and entirely different behaviour compared with the oxygen/hydrogen system. This is believed to have an influence on the spray evolution and mixing characteristics at supercritical conditions. The experimental investigation includes both the ignition transient a well as the steady-state operating points. It has been detected that the LOX/CH4 flame shows very similar characteristics in comparison with LOX/H2 flame at similar operating conditions. Critical flame stabilization at the startup transient has been found during all hot runs. At steady-state conditions, the influence of the injection parameters on the flame shape is comparable to previous LOX/Hydrogen investigations.
Preservice Teachers’ Understanding of the Relation Between a Fraction or Integer and its Decimal Expansion: The Case of 0.9̄ and 1

In this article, we obtain a genetic decomposition of students’ progress in developing an understanding of the decimal 0.9̄ and its relation to 1. The genetic decomposition appears to be valid for a high percentage of the study participants and suggests the possibility of a new stage in APOS Theory that would be the first substantial change in the theory since its inception (Dubinsky & Lewin, 1986). Our analysis includes a relatively objective and highly efficient methodology that might be useful in other research and in assessment of student learning. RésuméDans cet article, nous proposons une analyse du processus de compréhension, chez les futurs enseignants, de la décimale 0,9̄ et de sa relation avec le nombre 1. Ce processus apparaît valide pour un nombre élevé de participants, c’est pourquoi nous proposons d’ajouter une nouvelle étape à l’APOS, qui constituerait la première modification significative à cette théorie depuis sa formulation (voir Dubinsky et Lewin, 1986). Notre analyse comprend une méthodologie relativement objective et hautement efficace qui pourrait s’avérer utile dans d’autres travaux de recherche ainsi que pour l’évaluation de l’apprentissage des étudiants.
Laser assisted collisions of electrons with metal vapours

Three separate experiments are described which use laser radiation to probe the details of electron scattering processes from metal vapour targets. Results from superelastic scattering experiments from calcium are presented. The experiments were carried out at incident energies of 25·7 and 45 eV referred to the ground state. Scattering amplitudes derived from these experiments demonstrate that current theories are inadequate. The coherence of the excitation process has been studied by measuring the total polarisation. It is shown that the excitation process is coherent over the whole kinematic range. Preliminary results from a study of superelastic electron scattering from lithium are discussed where it is shown that a quantum electrodynamical model can be used to describe the optical pumping process in 6Li and 7Li. In addition the first superelastic electron spectrum is presented for experiments on lithium. A stepwise excitation technique is described with which cross sections for the electron impact excitation of the 3d9 4s2 2D state in copper can be measured. The experiments are complicated by the presence of D states in the incident copper beam. The origin of these D states is described as is a modification of the technique which leads to their removal.
Comparative Study of Deep Learning models to Recognize Palm Leaf Malayalam Characters

Palm-leaf manuscripts are historical records written mainly in many local languages in many South Asian countries. These texts have suffered damage over many years and centuries. Many organizations have scanned and digitally imaged palm-leaf manuscripts to preserve these potentially priceless records. Machine readable text conversion should be done on these images for the easy retrieval and processing. A comparative study of deep learning models for recognizing palm-leaf Malayalam characters (PLMC) was conducted in this work. Characters were segmented directly from palm leaves using the contour method. Various CNN architectures were employed to recognize these segmented characters, namely, VGG16, LeNet, MobileNet, Resnet152v2, VGG19, and DenseNet121. Additionally, a custom CNN architecture was developed and experimented with. It was observed that the custom CNN architecture provides the best recognition accuracy at 96%.
Permanent dichroic coloring of surfaces by laser-induced formation of chain-like self-organized silver nanoparticles within crystalline titania films

Laser-induced periodic surface structures, also known as ripples, have been investigated for a long time on various materials. They are self-organized grating-like structures that form spontaneously upon irradiation with a single laser beam; their formation requiring a high temperature rise, it generally results from interactions with ultrashort laser pulses. Recently, similar phenomena leading to periodic changes in the morphology of metallic nanoparticles embedded in polymer films have been reported under femtosecond laser exposure. Here, we demonstrate that chain-like self-organized silver nanoparticles can be grown, from an ionic silver precursor, within titania films under continuous wave visible laser beam. The nanoparticle chains are periodically spaced with a period that depends on the wavelength and are oriented parallel to the laser polarization. The samples present no significant surface modulation since all of the grown nanoparticles are located at the substrate-film interface, protected by a crystallized TiO2 film. SEM, TEM, HRTEM and EDX characterizations of the film nanostructuring are shown. Due to the coupling of incident light to a guided mode of the TiO2 film by the first diffraction order of the NP grating, such samples exhibit a strong dichroism whose characteristics depend on the laser exposure conditions. Color changes and spectral variations with polarization are measured and interpreted. The high stability of such colored films under high temperature rises or high intensity UV or visible exposures is demonstrated; it makes them good candidates for colored data storage.
Production of neutrons up to 18 MeV in high-intensity, short-pulse laser matter interactions

The generation of high-energy neutrons using laser-accelerated ions is demonstrated experimentally using the Titan laser with 360 J of laser energy in a 9 ps pulse. In this technique, a short-pulse, high-energy laser accelerates deuterons from a CD2 foil. These are incident on a LiF foil and subsequently create high energy neutrons through the 7Li(d,xn) nuclear reaction (Q = 15 MeV). Radiochromic film and a Thomson parabola ion-spectrometer were used to diagnose the laser accelerated deuterons and protons. Conversion efficiency into protons was 0.5%, an order of magnitude greater than into deuterons. Maximum neutron energy was shown to be angularly dependent with up to 18 MeV neutrons observed in the forward direction using neutron time-of-flight spectrometry. Absolutely calibrated CR-39 detected spectrally integrated neutron fluence of up to 8 × 108 n sr−1 in the forward direction.
Linear Quadratic Integral Differential Game applied to the Real-time Control of a Quadrotor Experimental setup

The accurate attitude control of a quadrotor is necessary, especially when facing disturbance. In this study, a linear quadratic with integral action based on the differential game theory is implemented on a quadrotor experimental setup. A continuous state-space model of the setup is derived using the linearization of nonlinear equations of motion, and its parameters are identified with the experimental results. Then, the attitude control commands of the quadrotor are derived based on two players; one finds the best attitude control command, and the other creates the disturbance by mini-maximizing a quadratic criterion, defined as the sum of outputs plus the weighted control effort and disturbance. The performance of the proposed structure is investigated in level flight and compared to the linear quadratic regulator controller. Results demonstrate that the proposed approach has an excellent performance in dissipating the disturbances.
SmartPredi – Development of Agricultural Crop Wastage Reduction System using Machine Learning

The culture and economy of Sri Lanka heavily depend on agriculture. The All-Island Farmers Federation (AIFF) claims that post-harvest produce loss is a problem that has plagued farmers in all regions of Sri Lanka and occurs both on farms and in commercial locations. The lack of a suitable system to handle produce, such as fruits and vegetables, has been identified as the key problem. The process of sowing seeds to generating the harvest and transporting it to the consumers is an overly complex process. If this process is not correctly identified the demand and supply may not be at equilibrium. Farmers tend to take decisions based on their experiences or from the knowledge gathered from past generations. Over the year environmental factors as well as economic factors have changed, therefore there is a high chance that the decisions taken by farmers might lead to wastage of crops. This research hopes to produce a mobile application for the farmers by considering some factors that affect the wastage in crops and try to provide timely relevant information to minimize the crop wastage by deploying machine learning, one of the advanced technologies in crop prediction.
Implementation of Active Disturbance Rejection Control based on Super-Twisting Algorithm on Delta Robot

In this article, a super-twisting algorithm-based ADRC structure is proposed. This structure contains three parts, a super twisting sliding mode controller, an extended state estimator, and an optimal tracking differentiator. This proposed ADRC is employed to control the Delta parallel robot both numerically, in MATLAB, and experimentally. In numerical simulations, the robustness of the proposed ADRC is verified by applying various external disturbances. Both the numerical and experimental results show the ability of the proposed ADRC structure in controlling the Delta robot in the presence of disturbances and uncertainties.
Study on Interactive and Highly Efficient 3D Reconstruction System

As wooden cultural relics are difficult to preserve, the number and types of them gradually decrease, which makes them face the phenomenon of cultural successors. How to activate the vitality of wooden cultural heritage in today’s social background is an urgent problem. In this study, taking Nuo mask, a wooden cultural relic, as an example, an interactive multi-view 3D reconstruction system combining close-range photogrammetry technology with mobile phone camera equipment is used to optimize the efficiency of 2D image acquisition and realize efficient restoration of color, texture, geometry and material information. The experiment shows that the system effectively promotes the rapid collection and reconstruction of the data of wooden cultural relics. Meanwhile, the system has been applied and practiced in the online exhibition of the official website of Guizhou Nuo Culture Museum, which promotes the digital protection and dissemination of wooden cultural relics.
A Bio-Mimetic Three-Dimensional Design and Modeling of a Fish-Like Robot

Bio-inspired criteria have ensured that robotic fish are able to get benefit from their living environments for locomotion. Bio-inspired fish robot has been designed for broad underwater exploration applications. Fish robots with tail oscillations can swim just in the plane. Among limited studies in the compliant fish robots, three-dimensional maneuvering ability is investigated. In the proposed model, we implemented two nozzles to add out-of-plane motions. The design of a compact and energy-efficient locomotion is critical; hence we investigated the source power and energy level at the next step. This article studies the dynamic behavior of a bio-inspired robotic fish. A novel design of the fish robot is presented based on the Fish Tail Fluidic Actuator (FTFA) deflections. We will show that our compliant mechanism is used to mimic the motions of a living animal. The resulting swimming performance of the fish robot was acceptable compared to biological fish performance. This mechanism with biomimetic locomotion has significant advantages since the mechanism is simpler and more robust than traditional mechanisms used for fish robots, while the performance is also comparable.
The Stage/Individual Distinction and (In)alienable Possession

The stage-level/individual-level distinction, which has so far been limited to verbal and adjectival predicates, should be extended to (underived) nominal predicates as well. Specifically, while simple nominals are individual-level predicates, event nominals and inalienable possession nominals are stage-level predicates. The currently prevailing distinction between the stage-level and individual-level predicates, that is, whether a predicate denotes a transitory state or an inherent and unchangeable stage, must be reconsidered. Current suggestions in line with this move will be discussed.
Fractional counts for authorship attribution: a numerical study

Responding to Leimkuhler's call for more computer experimentation in informetrics, this numerical study aims to illustrate observed appearances of fractional counts graphs. For instance, assuming a Lotka distribution for articles per author, it shows that for fields in which the single‐author article dominates, a maximum value will always occur at one. However, in fields where the multiauthored article dominates, this maximum may be smaller than one. © 1995 John Wiley & Sons, Inc.
Flush Mountable Multi-Octave Band Circularly Polarized Printed Antenna for Missile and Satellite Applications

For wideband circular polarization, an impressed, bidirectional antenna fed by a microstrip line is proposed. The proposed antenna evolves by transforming a Bow-tie dipole geometry into a symmetric rotational structure for the generation of circularly polarized wideband (CP) radiation. The dipole configuration side arms are adjusted by loading with rectangular stubs. The feeding edges of the bow-tie dipole system contain filets. The feeding edges of the bow-tie dipole system contain filets. This modification helps to considerably improve the bandwidth of the Axial Ratio (AR). The anticipated multi-octave antenna’s simulated and calculated impedance bandwidth (S11 <-10 dB) is from 1.3 GHz to 6GHz, and from 1.55 GHz to 6 GHz respectively. The antenna’s measured 3-dB AR bandwidth is from 0.93 GHz to 5.89 GHz.
Self-Tuning Robust Tracking Control for Autonomous Underwater Vehicles

This paper addresses the control design problem for a nonlinear and nonholonomic dynamics model of an autonomous underwater vehicle. The kinematics control algorithm is a PID controller while a self-tuning control method is used for trajectory tracking. The kinetics control algorithm is based on an integral sliding mode technique that is robust against time-varying disturbances. The obtained results presented here use the Remote Environmental Monitoring UnitS (REMUS) underwater vehicle model and show the high performance of the controller. Based on the results demonstrated for the two designated trajectories, the tracking quality of self-tuning robust control, despite the significant similarity of the control input of both algorithms for x, y, and z, is much better than the sliding mode control. As a result, AUV was able to follow the desired trajectory, and tracking errors converged to zero. It is worth noting that at non-derivative points of the path (1st trajectory), tracking errors were entirely within response quality limits (y = ±0.05[m]). The order of control efforts of the proposed control is suitable and can be implemented in the physical system.
Patient Monitoring System for Elderly Care using AI Robot

The use of robots in numerous industries has expanded in recent decades. Self-guiding robots have started to arise in human life, particularly in sectors pertaining to the lives of old people. Age-related population growth is accelerating globally. As a result, there is a rising need for personal care robots. The purpose of this requirement is to increase opportunities for mobility and support independence. To meet this demand, a robot with specific functionalities to help older people has been designed. The standard values of healthcare parameters are stored in the database by recording and comparing the current values the system will give an alarm and also sends a message to the doctor or caretaker so that a proper care would be given to the patients. We are including a preset distance value to monitor the elder people. Here we are using some sensors to detect the health parameters from the person. Robot have designed to intimate the family members if any changes occur in the health parameters. It helps the people to stay alone in home with safe manner.