Miracle-dz/UniFAR-FTUs huggingface dataset:
A hyperspectral plant health monitoring system for space crop production

Compact and automated sensing systems are needed to monitor plant health for NASA’s controlled-environment space crop production. A new hyperspectral system was designed for early detection of plant stresses using both reflectance and fluorescence imaging in visible and near-infrared (VNIR) wavelength range (400–1000 nm). The prototype system mainly includes two LED line lights providing VNIR broadband and UV-A (365 nm) light for reflectance and fluorescence measurement, respectively, a line-scan hyperspectral camera, and a linear motorized stage with a travel range of 80 cm. In an overhead sensor-to-sample arrangement, the stage translates the lights and camera over the plants to acquire reflectance and fluorescence images in sequence during one cycle of line-scan imaging. System software was developed using LabVIEW to realize hardware parameterization, data transfer, and automated imaging functions. The imaging unit was installed in a plant growth chamber at NASA Kennedy Space Center for health monitoring studies for pick-and-eat salad crops. A preliminary experiment was conducted to detect plant drought stress for twelve Dragoon lettuce samples, of which half were well-watered and half were under-watered while growing. A machine learning method using an optimized discriminant classifier based on VNIR reflectance spectra generated classification accuracies over 90% for the first four days of the stress treatment, showing great potential for early detection of the drought stress on lettuce leaves before any visible symptoms and size differences were evident. The system is promising to provide useful information for optimization of growth environment and early mitigation of stresses in space crop production.
Factors affecting the knowledge of vegetable farmers of Chitwan and Makwanpur district over pesticide use

A study was conducted in two districts of Nepal to determine the factors influencing the knowledge of vegetable farmers regarding pesticide use. The use of pesticides in agriculture is considered necessary but can pose significant risks if handled inadequately or impractically. The study collected data from 136 vegetable growers, with 68 farmers from each district, and also involved 5 agro vets from both districts using random sampling techniques. The findings indicated that only 13.23% of the farmers were found to wear full personal protective equipment (PPE), while 83.08% used partial PPE, and 3.67% applied pesticides without any protective gear. This finding was statistically significant at the 10% level. Among the different types of protective gear, masks were the most commonly used by the farmers. The majority of farmers (62.5%) reported being poisoned during pesticide mixing and spraying, with eye irritation being the most frequently reported symptom. Farm households that underwent training in pesticide usage and vegetable cultivation experienced a statistical enhancement of 20.6% in their knowledge. Moreover, farmers who were educated, had access to extension services, had long experience in pesticide usage, or had a history of poisoning in their farm household witnessed corresponding improvements of 9%, 18%, 2.1%, and 9.3% in their knowledge of pesticide use. The study urges agricultural organizations to implement training, promote literacy, offer extension services, and raise awareness to enhance farmers' knowledge and safety, contributing to sustainable agriculture and farmer well-being.
Asymmetric local velocity distribution in a vibro-uidized granular gas and its non-classical hydrodynamic description

The present thesis is dedicated to the experimental and simulation study of vibro-fluidized granular gases dynamics. Granular gases are characterized by dissipation due to inelastic collisions. To keep a steady state, continuous energy is injected to balance dissipation by vibration. This system provides a platform to study the physics of non-linear, non-equilibrium and dissipative systems. This dissertation insisted on the necessity of understanding the local state in the granular gases and building a new model for vibration-fluidized granular gases. Research approach included experiments in micro-gravity, event-driven molecular dynamic simulation and experiments in tilted plane with various gravity. Micro-gravity experiments were performed on Airbus A380 (Parabolic flight) to avoid friction with the bottom and gravity field. A long range boundary effect is found to exist in 2D vibration granular gases. Local distributions of the velocity component in the vibration direction are asymmetric in the whole cell except for the center bin. In the system, energy equi-partition breaks down. ``Granular temperature" is not efficient to describe such a system. We proposed a superposition of two Gaussian model to describe the local asymmetric velocity profiles along the vibration direction. We demonstrated the performance of this model by the Airbus experimental data and others’ simulation works. Event-driven molecular dynamics simulation was utilized. Results showed support for experiment results. Furthermore, we found this long range boundary effect is related to the system dissipation. This effect becomes pronounced if the coefficient of restitution (e<1) decreased or the number of particles increased. For the elastic situation, there is no such effect. This effect cannot be ignored and treated only as a local boundary effect as in hydrodynamics. We studied a 2D vibration fluidized granular system in a tilted plane systematically. The inclined angle is changed from horizontal to vertical, changing the "effective gravity". These results also showed asymmetric local velocity distributions. Other than the number density profiles deviate from an exponential form, the spatial profiles of the number density of particles moving up and down are not equal, and non symetric from cell center.
Weighted composite quantile regression for partially linear varying coefficient models

ABSTRACT Partially linear varying coefficient models (PLVCMs) with heteroscedasticity are considered in this article. Based on composite quantile regression, we develop a weighted composite quantile regression (WCQR) to estimate the non parametric varying coefficient functions and the parametric regression coefficients. The WCQR is augmented using a data-driven weighting scheme. Moreover, the asymptotic normality of proposed estimators for both the parametric and non parametric parts are studied explicitly. In addition, by comparing the asymptotic relative efficiency theoretically and numerically, WCQR method all outperforms the CQR method and some other estimate methods. To achieve sparsity with high-dimensional covariates, we develop a variable selection procedure to select significant parametric components for the PLVCM and prove the method possessing the oracle property. Both simulations and data analysis are conducted to illustrate the finite-sample performance of the proposed methods.
The physiological demands of wind instrument performance

The playing of musical wind instruments goes back to the dawn of hwnan history, but it is only recently that we have begun to understand in detail the physical principles governing sound productIOn and the physiological variables that must be controlled by the player during perfonnance. Along with this goes a better understanding of the design and construction of the instruments themselves, but that, as they say, is another story. Setting aside the pipe organ, we can divide musical wind instruments into three classes: reed-driven instruments such as the clarinet, oboe, bassoon and saxophone; lip-driven bras~ instrumenls such as the trumpet, trombone and tuba; and airjet driven instruments of the flute family. In all of these, the player must learn to control the pitch of the note being played by manipulating finger Ireys, valves or slides, and then nrust carefully control the actual sound-producing mechanism to produce a satisfactory result. This requires deliberate control of physiological variables such as lip position and tension, blowing pressure, and perhaps vocal-tract configuration. It is the purpose of the present paper to describe what is known of the requirements on each of these variables. Details of the acoustics of the instrwnents themselves can be found in Fletcher and Rossing (1998).
Model E-Channel Design System Dengan Bank Biometric Aplication Pada Bank Di Indonesia

Peningkatan biaya perbankan di seluruh dunia telah mendorong lembaga keuangan untuk mencari pendekatan baru untuk masalah ini. Akibatnya, bank telah mulai mendefinisikan teknologi baru, khususnya penggunaan internet, karena berkaitan dengan transaksi keuangan. Akses internet telah berevolusi dari telepon darat ke komputer pribadi ke ponsel dan sekarang smartphone. Mobile banking, sering dikenal sebagai m-banking, dengan cepat menjadi norma untuk melakukan transaksi keuangan, mengantarkan era baru bagi industri perbankan global secara keseluruhan. Saat ini ada beberapa aplikasi mobile banking yang menggunakan metode login aman Sidik Jari. Satu-satunya aplikasi mobile banking yang menggunakan biometrik seperti wajah pengguna, sidik jari, atau pemindaian iris untuk memverifikasi identitas adalah yang Anda lihat saat ini.
Defect detection of PCB based on Bayes feature fusion

With the continuous development of the electronics industry, the number of printed circuit board (PCB) has grown at a rapid rate, and the requirements for the detection systems of PCB have also continuously increased. In the traditional PCB detection, the main reference is the comparison method. However, in a real scene, there are a series of problems such as non-uniform illumination, tilting of the camera angle, and the like, resulting in a less satisfactory effect of the reference comparison method. So, the authors proposed a non-reference comparison framework of PCB defects detection. This framework has achieved good results in speed and accuracy. The authors extract the histogram of oriented gradients and local binary pattern features for each PCB image, respectively, put into the support vector machine to get two independent models. Then, according to Bayes fusion theory, the authors fuse two models for defects classification. The authors have established a PCB data set that includes both defective and defect-free. It has been verified that the accuracy of the verification set is improved compared to the individual features using the fused features. The authors also illustrate the effectiveness of Bayes feature fusion in terms of speed.
Factors Influencing the Application of Strategic Management Accounting: A Study of Manufacturing Enterprises in Hanoi

Strategic management accounting (SMA) information helps managers determine the strategy and strategic position of the business. At the same time, SMA helps managers see and re-evaluate problems so that they can draw on their experiences and lessons for decision-making and control. Currently, manufacturing enterprises in Hanoi are aware of the important role of strategic management accounting information, but the level of application of strategic management accounting techniques is low. This article aims to evaluate the factors affecting the application of strategic management accounting in manufacturing enterprises in Hanoi, thereby making recommendations for these enterprises to increase the use of strategic management accounting information to help business managers make business decisions.
Facilitators and barriers that influence Nursing Professionals in the Adoption of Information Systems: : a systematic review

Through a systematic literature review, the current research aimed to acknowledge the main facilitators and barriers that influence the adoption of Information Systems by nursing professionals. Furthermore, it listed the principal theoretical models used to measure technology acceptance and the methods used to perform data collection. It was possible to see that TAM was the model with the highest frequency of appearance. It was also was possible to identify 19 (nineteen) facilitators and 23 (twenty-three) barriers reported in the selected studies. The findings allowed us to understand better how the phenomenon occurs, what can be worked on to improve technology acceptance, and allow new and in-depth studies to be carried out.
The Reynolds stress in turbulence from a Lagrangian perspective

We present a unique method for solving for the Reynolds stress in turbulent canonical flows, based on the momentum balance for a control volume moving at the local mean velocity. A differential transform converts this momentum balance to a solvable form. Validations with experimental and computational data in simple geometries show quite good results. An alternate Lagrangian analytical method is offered, leading to a potential closure method for the Reynolds stress in terms of computable turbulence parameters.
N-dimensional Rotation Matrix Generation Algorithm

This article presents a new algorithm for generation of N-dimensional rotation matrix M, which rotates given N-dimensional vector X to the direction of given vector Y which has the same dimension. Algorithm, named N-dimensional Rotation Matrix Generation Algorithm (NRMG) includes rotation of given vectors X and Y to the direction of coordinate axis x1 using two-dimensional rotations. Matrix M is obtained as multiplication of matrix MX and inverse of matrix MY, which rotates given vectors to the direction of axis x1. Also examined is the possibility to perform parallel calculations of two-dimensional rotations.
Measuring promotors of school functioning: Informing school-based psychosocial support for crisis-affected students in Lebanon

ABSTRACT The evolving situation in Lebanon is characterized by multiple crises that affect education and can negatively affect a student’s school-functioning and mental health. The Ministry of Education and Higher Education decided in 2019 to further intensify and upscale implementation of school-based psychosocial support. This study is a contextualization and validation of the Student Learning in Emergencies Checklist for use in Lebanon. A 27-item questionnaire was proposed and tested to explore categories for measuring the effect of psychosocial support on academic functioning and academic performance and build evidence for program design. Promotors for school functioning were also explored. The participants (N = 1048) were divided between Lebanese students (N = 573) and non-Lebanese students (N = 520) with a mean age of 11.77 and gender balance. Multiple regression analysis demonstrated that the combined proposed categories explained 33.7% of the variance of school functioning as opposed to other factors. The new categories for safety and support at school and safety and support at home were found to predict academic functioning alone. Lebanese students reported significantly reduced scores in safety and support at school compared to non-Lebanese students. The need for psychosocial and educational support increased significantly with age, and males reported lower scores than females. Content and strategies for school-based psychosocial support for students are discussed.
Actuator surface model for wind turbine flow computations

Summary The paper presents a new numerical technique for simulating wind turbine flows. The method, denoted as the actuator surface technique, consists of a three-dimensional Navier-Stokes solver and a body force distributed along the blade surfaces of a wind turbine. The force at each airfoil section is obtained from tabulated lift and drag coefficients, which depend on local angle of attack and resulting velocity. The local force is further distributed by a set of pre-determined functions that depends on angle of attack and airfoil shape. The pre-determined functions are curve-fitted using the TableCurve 2D software and based on pressure distributions obtained from a viscous-inviscid interactive code (XFOIL). The actuator surface technique is applied to compute the flow past a Nordtank 500kW turbine. Detailed comparisons with the previously developed Actuator Line model show that the new model determines more correctly the flow structures in the region close to the tips of the rotor blades.
Verification on Head-Related Transfer Functions of a Snowman Model Simulated Using the Finite-Difference Time-Domain Method

Although finite-difference time-domain (FDTD) simulations are extensively used in acoustics, studies assessing the reliability and the accuracy of the implemented method are scarce. Moreover, the operational validity of a simulation method is context-dependent. Motivated by the context of head-related transfer function (HRTF) prediction, this work presents a verification procedure for FDTD-simulated HRTFs from a simplified model of a human head and torso which comprises two spheres and is known as the snowman model. The analytic solution required by the code verification is computed with the multipole reexpansion technique and used to compute convergence rate estimates. A solution verification process follows in which asymptotic predictions are computed. Results from the code verification show scattered convergence rates which attained the expected first-order accuracy at frequencies below 1 kHz when a linear regression model was used as the estimation procedure. Results from the solution verification show that the asymptotic predictions are accurate up to 10 kHz, after which bias is observed. Assessing the accuracy of the employed solution verification procedure revealed that the absolute difference between the $\log $-magnitude of the asymptotic predictions and this of the analytic solution is within 1 dB up to 11589 Hz across the HRTF directions considered.
Is inverse cascade of passive scalar energy advected by incompressible two-dimensional turbulence genuinely impossible?

More serious works on 2D2C, 2D3C, 2C2Dcw1C3D, 3D3C, rotating turbulence, thin-layer flows, quasi-static magnetohydrodynamics (QSMHD), and all that are wanted, but we report timely here some studies on locally and globally 2C2Dcw1C3D flows, with the hope to promote smarter and deeper works.
SPATIAL MACHINE LEARNING FOR MONITORING TEA LEAVES AND CROP YIELD ESTIMATION USING SENTINEL-2 IMAGERY, (A Case of Gunung Mas Plantation, Bogor)

Indonesia's tea production and export volume have fluctuated with a downward trend in the last five years, partly due to the increasingly competitive world tea quality. Crop yield estimation is part of the management of tea plucking, affecting tea quality and quantity. The constraint in estimating crop yields requires technology that can make the process more effective and efficient. Remote sensing technology and machine learning have been widely used in precision agriculture. Recently, big data processing, especially remote sensing data, machine learning, and deep learning have been carried out using a cloud computing platform. Therefore, we propose using GeoAI, a combination of Sentinel-2A imagery, machine learning, and Google Collaboratory, to predict ready for plucking tea leaves at optimal plucking time at Gunung Mas Plantation Bogor. We used selected bands of Sentinel-2A and extracted more features (i.e., NDVI) as a training set. Then we utilized the tea blocks boundary and tea plucking data to generate labels using Random Forest (RF) and Support Vector Machine (SVM). The classification results were further used to estimate the production of crop tea yield. The RF classifier is able to achieve overall accuracy at 51% and SVM at 54%. Meanwhile, accuracy at optimally aged tea blocks is able to achieve at 75.62% for RF and 52.88% for SVM. Thus, the SVM classifier is better in terms of overall accuracy. Meanwhile, the RF classifier is superior in predicting ready for plucking tea at optimally aged tea blocks.
Analysis and evaluation of morphological and molecular polymorphism in the hybridization of Elaeagnus ×maritima and E. ×submacrophylla

The taxonomic identity of Elaeagnus ×maritima and E. ×submacrophylla (Elaeagnaceae) in Korea is unclear, yet they are presumed to be hybrid taxa based on their morphology. To determine their hybrid origins, a morphological analysis (field surveys and specimen examinations) and a molecular analysis involving two nuclear ribosomal DNA (nrDNA) regions (internal transcribed spacer and 5S non-transcribed spacer) and one chloroplast DNA (cpDNA) region (matK) were conducted. The morphological analysis revealed that E. ×maritima showed certain morphological similarities to E. glabra, whereas E. ×submacrophylla showed certain morphological similarities to E. pungens. However, the molecular analysis indicated that E. ×maritima exhibited additive species-specific sites of E. glabra and E. macrophylla in the nrDNA regions. Notably, E. ×submacrophylla showed various aspects, with some individuals exhibiting additive species-specific sites of E. pungens and E. macrophylla in the nrDNA and E. macrophylla sequences in the cpDNA regions, some individuals exhibiting E. macrophylla sequences in the nrDNA and E. pungens sequences in the cpDNA regions, and some individuals displaying E. macrophylla sequences in both the nrDNA and cpDNA regions, despite an intermediate morphology between E. pungens and E. macrophylla. These results indicate that these two species are of hybrid origin and frequently cross between parental and hybrid individuals.
ANALISIS TECHNOLOGY ACCEPTANCE MODEL TERHADAP PENGGUNA E-MARKETPLACE BUKALAPAK

Permasalah pokok yang diangkat pada penelitian ini yaitu, kurangnya penerimaan user pada e-marketplace bukalapak. Metode deskriptif kuantitatif digunakan dalam penelitian ini. Model penerimaan teknologi/TAM digunakan sebagai model acuan untuk kemudian dimodifikasi terhadap permasalahan yang diangkat. Teknik analisis data pada penelitian ini, yaitu menggunakan analisis regresi linier. Hasil penelitian menunjukan bahwa Variabel Content Richness, Security,dan Perceived Ease of Use berpengaruh secara signifikan terhadap Perceived Ease of Use. Penelitian ini juga menunjukan bahwa implementasi setiap variabel penelitian telah dilaksanakan, meskipun masih ada beberapa variabel yang perlu ditingkatkan lagi pelaksanaan kongkritnya pada aplikasi e-marketplace bukalapak.
Engineering Optics 2.0: A Revolution in Optical Materials, Devices, and Systems

Along with the rapid development of micro/nanofabrication and characterization techniques, as well as the advancement of electronic computer and numerical simulation algorithms, modern engineering optics has entered a new phase termed Engineering Optics 2.0 (EO 2.0), which breaks the fundamental limitations of classic optical laws with respect to many aspects of optics (including reflection, refraction, diffraction, absorption and radiation, etc.). These theoretical breakthroughs may provide a new scheme for engineering optical applications. In this perspective, on the basis of anomalous optical and electromagnetic phenomena discovered in ordered subwavelength structures, we analyzed the opportunities and main challenges toward practical applications. Rather than replacing traditional optical components, we argue that subwavelength structured materials should be merged with the state-of-art technologies to make EO 2.0 more competitive in both miniature and large optical systems.