Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of post-harvest management in agricultural policy and strategies to minimise post harvest losses in Lesotho

Despite global efforts to increase food availability and curb high incidence of malnutrition in Africa, there are concerns with regard to high post-harvest losses in Africa. Lesotho like most countries in sub-Saharan Africa faces documented challenges with food insecurity and nutrition. Food availability could be increased by reduction of post-harvest losses without further exploitation of resources. Mitigation of post-harvest losses is seen as a possible antidote for increasing food availability and nutritional status in countries experiencing high food losses. This study investigated the extent of integration of post-harvest management in agricultural policy in Lesotho and strategies to minimise post-harvest losses. Purposive sampling was utilised in order to select a sample of twenty-five respondents on which interviews were conducted. Thematic analysis was used to identify a set of overarching themes that can be used to describe the policy environment and strategies to reduce post-harvest losses. The analysis suggests that there is absence of a direct policy to guide post-harvest management activities in Lesotho, it is only referred to indirectly in other policies with the exception of dairy products sector which has a direct post harvest management policy. Strategies to curb post-harvest losses were also identified. The study concludes that there is need for a direct policy to address post-harvest management in Lesotho. Key words: Lesotho, post harvest management, natural resources, food policy, agricultural development.
Improving Students’ Problem Solving Ability Through Learning Based Videoscribe

The purpose of this research is to find out the problem-solving physics by using media-based videoscribe learning. Learning with the help of a video will make students more interactive and active because students can understand the concept of abstract and solve the problem of physics related to daily life. The method used in this research was the quasi-experimental method with the research design of The Randomized Post-Test Only Control Group Design, which involved 30 students as samples in Physics Education of Indraprasta PGRI University.The technique analysis of the research using the T-test. The results showed that by using learning media videoscribe could improve the ability of problem-solving physics. We found significant positive effects of the use of videoscribe in conveying physics lessons With the help of video scribe, learning is more efficient in physics learning. The students understand abstract physics material and are able to activate students in learning. These findings are consistent with studies on the improve of the student’s problem-sloving ability on physics learning.
Credit Card Fraud Detection using Machine Learning Framework

—Nowaday’s online payment gaining popularity because of easy and convenience use of ecommerce. It became very easy mode of payment. People choose online payment and e-shopping; because of time convenience, transport convenience, etc. As the result of huge amount of e-commerce use, there is a vast increment in credit card fraud also. Machine Learning has been successfully applied to finance databases to automate analysis of huge volumes of complex data. Machine Learninghas also played a salient role in the detection of credit card fraud in online transactions. Fraud detection in credit card is a big problem, it becomes challenging due to two major reasons–first, the profiles of normal and fraudulent behaviors change frequently and secondly due to reason that credit card fraud data sets are highly skewed. This paper research and checks the performance of Random Forest on highly skewed credit card fraud data. Dataset of credit card transactions is sourced from European cardholders containing 1 lakh transactions. These techniques are applied on the raw and pre-processed data. The performance of the techniques is evaluated based on accuracy, sensitivity, and specificity, precision.
Guided-mode Resonance Filter for Micro-optic Spectrometer

Spectrometers are usually composed of diffraction gratings and prisms, and become large in size for high wavelength resolution. High-density integration of narrowband-pass filters of different wavelengths on a substrate can be expected to produce an ultra-compact spectrometer. We focused on guided-mode resonance (GMR) filters as such filters. The GMR filter consists of a thin-film waveguide and a sub-wavelength grating. GMR filters of different filtering wavelengths can be integrated in the same substrate because their periodic structure in refractive index spread along in-plane direction. On the other hand, GMR filter normally needs an aperture size and beam diameter of hundreds of microns and is not suitable for high-density integration. In this study, we proposed and investigated a GMR filter of a single-layer cross grating for a compact narrowband-pass filter. Different guided modes contributing to the broadband and narrowband reflection propagate orthogonally each other. By using simultaneously these guided modes, both reflections are cancelled at the competing wavelengths, resulting in high transmittance. In this paper, design examples with numerical simulation results are presented. It was predicted that a passband of 15 nm was obtained in the stopband of 200 nm for an incident beam of a 10-micron diameter.
Kinetic Studies on the Adsorption of Sungai Sireh RawWater's Natural Organic Matters

The presence of dissolved organics in potable water supply is aesthetically undesirable. Apart from imparting colour, taste and odour to treated water, it is also potentially hazardous to health. Two types of coconut shell derived activated carbon, KI-6070 and KI8085, provided by Kekwa Indah Sdn Bhd, were studied for the removal of dissolved organic compounds from Sungai Sireh Water Treatment Plant raw water, notorious of its high organic content. The respective external surface area of the KI-6070 and KI-8085 are approximately 277 m/g and 547 m2jg. The rate constant (~) for the KI-8085 was higher than that of the KI-6070, ranging between 30 and 70 %, for adsorbent dosages between 1.0 and 3.0 g. This was expected since the total surface area (specific and external surface areas) of the KI-8085 was higher than that of the KI-6070. The rate constant for the mass transfer was a function of the adsorbent dosage where both adsorbents indicated a proportional increase in the rate constant with increasing adsorbent dosage. The increasing dosage raised the intra particle diffusion rate constant (K.,) for both the KI-6070 and KI-8085, with the KI-8085 having a higher intra particle diffusion rate.
Habilidades para desarrollar la lectoescritura en los niños de educación primaria

Es un estudio cualitativo, bajo la metodologia de la investigacion accion en ninos de primer grado de educacion primaria. Con el objetivo de ensenar habilidades para el desarrollo de la lectoescritura. Dicha propuesta, propone el metodo FAS; una mezcla del modelo fonetico, alfabetico y silabico de Mariela Gonzalez Lopez. Uno de los problemas en el mundo de la ensenanza-aprendizaje, es la falta de habilidades para concretar la alfabetizacion. Se realiza en cinco etapas; diagnostico, planeacion, intervencion educativa, analisis y conclusion. Para la ensenanza-aprendizaje de la lectoescritura se requiere del desarrollo de habilidades de pensamiento, linguisticas, motrices, informacionales, fisicas y socioemocionales. Skills for developing literacy in elemental school children. AbstractIt is a qualitative study, under the action research methodology in children of first grade of primary education. Aiming to teach literacy development skills. Said proposal, the FAS method is proposed; a mixture of the phonetic, alphabetical and syllabic model of Mariela Gonzalez Lopez. One of the problems in the world of teaching-learning is the lack of skills to achieve literacy. The method is in five stages; diagnosis, planning, educational intervention, analysis and conclusion. The teaching-learning of literacy requires the development of thinking, linguistic, motor, informational, physical and socio-emotional skills.
Study on Laser Propagation Characteristic of Downlink Channel in Non-uniform Seawater

ABSTRACT Ao, J.; Zhai, D.Y. , and Ma, C.B. , 2020. Study on laser propagation characteristic of downlink channel in non-uniform seawater. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 655-661. Coconut Creek (Florida), ISSN 0749-0208. In underwater optical communications, accurate evaluation concerning the optical propagation characteristic in seawater is crucial to the design of the communication system. The authors studied the distribution and loss properties of light traveling in seawater using Monte Carlo simulation method for the complex and changeable ocean communication channel. Assuming that the laser intensity is with Gaussian distribution, according to the Argo (Array for Real-time Geotropic Oceanography) data, the non-uniform seawater within 200 meters is layered vertically from the surface down, down, and the scattering and absorption of each layer is deduced. We studied the relation among the spot profile in receiving plane, emitted photons, transmission distance, and attenuation coefficient by using tracking the photon transmission process, and its correction is verified by using Monte Carlo simulation. Experimental results demonstrate that the scattering times of photons in seawater increase with the scattering distance and attenuation coefficient, and result in the enlargement of the receiving spot. Besides, if the seawater is considered as non-uniform, then the spot energy of the downlink is more concentrated than that in uniform seawater. In other words, the beam energy is more concentrated and suitable for long-distance transmission in a vertical direction. Therefore, considering the seawater as nonuniform medium and layering it vertically will make the evaluation of light transmission characteristic closer to practice.
Do Trompe l'oeils Look Right When Viewed from the Wrong Place?

Picture perception and ordinary perception of real objects differ in several respects. Two of their main differences are: (1) Depicted objects are not perceived as present and (2) We cannot perceive significant spatial shifts as we move with respect to them. Some special illusory pictures escape these visual effects obtained in usual picture perception. First, trompe l'oeil paintings violate (1): the depicted object looks, even momentarily, like a present object. Second, anamorphic paintings violate (2): they lead to appreciate spatial shifts resulting from movement. However, anamorphic paintings do not violate (1): they are still perceived as clearly pictorial, that is, nonpresent. What about the relation between trompe l'oeil paintings and (2)? Do trompe l'oeils allow us to perceive spatial shifts? Nobody has ever focused on this aspect of trompe l'oeil perception. I offer the first speculation about this question. I suggest that, if we follow our most recent theories in philosophy and vision science about the mechanisms of picture perception, then, the only plausible answer, in line with phenomenological intuitions, is that, differently from nonillusory, usual picture perception, and similarly to ordinary perception, trompe l'oeil perception does allow us to perceive spatial shifts resulting from movement. I also discuss the philosophical implications of this claim.
VARIABILIDAD DE LA FRECUENCIA CARDIACA Y EJERCICIO. ¿FUNDAMENTACIÓN FISIOLÓGICA?

Este trabajo pretende dos objetivos: 1º) dar una visión pedagógica de la complejidad relativa al tratamiento matemático de la variabilidad de la frecuencia cardiaca y 2º) analizar si el tratamiento matemático de la señal RR (distancia entre dos ondas R del electrocardiograma) tiene una base fisiológica. Se revisan los mecanismos fisiológicos que explican uno de los fenómenos de base para el análisis de la variabilidad: la arritmia sinusal respiratoria. Se analizan las bases matemáticas, así como los métodos matemáticos de valoración, de la variabilidad. Finalmente, se realiza una revisión del significado fisiológico de las bandas de frecuencia obtenidas mediante las diversas metodologías del tratamiento de la señal RR. No está claro si los métodos matemáticos de tratamiento de la señal RR pueden ser una herramienta de valoración de la función vegetativa. Por ello, debemos tener precaución al interpretar esta variable, sobre todo en el contexto del ejercicio físico y entrenamiento.
Hiccups and Success: Principals Speak out about Equitable Performance Pay in a Large South Texas Urban Border District.

This study sheds light on principal perceptions of the impact of performance pay in an urban South Texas School District that is situated on the border of Texas and Mexico. This qualitative naturalistic inquiry case study used researcher as instrument (Lincoln & Guba, 1985). in order to glean the perceptions of principals who serve campuses of students that are predominantly Hispanic and underserved low-socioeconomic students. Strategies to facilitate trustworthiness and credibility of the study were implemented (Erlandson, Harris, Skipper, & Allen, 1993). Major themes include: 1) the critical need for teacher quality, 2) the significance and impact of principals as teacher coaches, 3) the necessity of discernment in understanding of the purpose of performance base compensation as well as the impact of performance-based compensation (including the impact of that at three levels); and, 4) the impact on student achievement. The fifth theme evidenced participant perspectives on whether performance-based compensation improves recruitment and retention of quality teachers.
Temporal Multiple Kernel Learning (tMKL) model for predicting resting state FC via characterizing fMRI connectivity dynamics

Over the last decade there has been growing interest in understanding the brain activity in the absence of any task or stimulus captured by the resting-state functional magnetic resonance imaging (rsfMRI). These resting state patterns are not static, but exhibit complex spatio-temporal dynamics. In the recent years substantial effort has been put to characterize different FC configurations while brain states makes transitions over time. The dynamics governing this transitions and their relationship with stationary functional connectivity remains elusive. Over the last years a multitude of methods has been proposed to discover and characterize FC dynamics and one of the most accepted method is sliding window approach. Moreover, as these FC configurations are observed to be cyclically repeating in time there was further motivation to use of a generic clustering scheme to identify latent states of dynamics. We discover the underlying lower-dimensional manifold of the temporal structure which is further parameterized as a set of local density distributions, or latent transient states. We propose an innovative method that learns parameters specific to these latent states using a graph-theoretic model (temporal Multiple Kernel Learning, tMKL) and finally predicts the grand average functional connectivity (FC) of the unseen subjects by leveraging a state transition Markov model. tMKL thus learns a mapping between the underlying anatomical network and the temporal structure. Training and testing were done using the rs-fMRI data of 46 healthy participants and the results establish the viability of the proposed solution. Parameters of the model are learned via state-specific optimization formulations and yet the model performs at par or better than state-of-the-art models for predicting the grand average FC. Moreover, the model shows sensitivity towards subject-specific anatomy. The proposed model performs significantly better than the established models of predicting resting state functional connectivity based on whole-brain dynamic mean-field model, single diffusion kernel model and another version of multiple kernel learning model. In summary, We provide a novel solution that does not make strong assumption about underlying data and is generally applicable to resting or task data to learn subject specific state transitions and successful characterization of SC-dFC-FC relationship through an unifying framework.
Comparision and Classification of Medicinal Plant Leaf Based on Texture Feature

Automated classification system for medicinal plants is very rigorous and it’s challenging problem. India is a country where we can find numerous plants species and each plant contains its own medicinal value. Manual identification and classification process requires prior knowledge and it very difficult for human beings to remember all plant species name and its uses. Conservation of these medicinal plants is important as it is will be beneficial to many sectors such as in the field of medicine, botanic researches and plant taxonomy study. Existing systems are not capable of modelling Indian medicinal plants species. The proposed system helps in classifying the medicinal plants by utilizing the texture features that majorly contributes in leaf recognition. The main phases in proposed methodology are image enhancement, feature extraction and classification. The leaf images are captured by using smart phones further by digital image processing techniques the features are extracted and comparison is performed among them. Finally K-nearest neighbor (KNN) classifier is implemented to design an automatic classifier.
Alternative Vine Management Programs for Fresh-Market Potatoes

Abstract Economically solvent fresh-market potato production is predominantly dependent on the ability to efficiently produce consistent tuber quality and high yield, and the ability to meet first-to-market demand with early-season potatoes. Unfortunately, these two qualifiers often work against each other in terms of production management. In response, we studied integrated potato vine management programs that support timely early-season potato harvest. Vine management with a flail chopper, roller, and flame burner used alone or followed by diquat was evaluated when initiated 21 or 14 d prior to harvest in 2015 and 2016. Potato varieties included ‘Yukon Gold' and ‘Dark Red Norland'. Potato leaf and stem management, as well as tuber skinning, stolon separation, grade, and yield were quantified. Among mechanical methods, potato leaf and stem management were poor when vines were rolled or mowed but better when flail chopped. In general, vine management and tuber skin set was better when treatments were initiated 21 d prior to harvest as opposed to 14 d. Vine management, tuber skin set, and yield were comparable when potato vines were flail chopped followed by flame burning and where diquat was applied twice, offering a viable program for smaller scale or organic production. Nomenclature: Diquat; potato, Solanum tuberosum L.
Entrepreneurial, strategy and performance in restaurants and similars

Restaurants tend to be small businesses, operated almost in a self managed way, by their entrepreneur owners or a contracted manager. The way these managers conduct their business depends much on their individual abilities to run the company. This research aimed to investigate the possibly existing influences between individual entrepreneurial orientation (IEO), service strategy (SS) and business performance (BP). A construct was developed to run the study, including hypothesis joining the three influences. Questionnaires using Likert scale were built and validated. Survey was conducted with 260 restaurant, bars and hotel owners or managers. Data were analyzed through modeling of structural equations. Results confirmed the three hypothesis: H1: IEO positively influences SS; H2: IEO positively influences BP; H3: SS positively influences BP. Theoretical contributions were made through the construct building. Managerial implications are listed, in order to help restaurant management better run their business.
Iris Ciphertext Authentication System Based on Fully Homomorphic Encryption

With the application and promotion of biometric technology, biometrics has become more and more important to identity authentication. In order to ensure the privacy of the user, the biometrics cannot be stored or manipulated in plaintext. Aiming at this problem, this paper analyzes and summarizes the scheme and performance of the existing biometric authentication system, and proposes an iris-based ciphertext authentication system based on fully homomorphic encryption using the FV scheme. The implementation of the system is partly powered by Microsoft’s SEAL (Simple Encrypted Arithmetic Library). The entire system can complete iris authentication without decrypting the iris feature template, and the database stores the homomorphic ciphertext of the iris feature template. Thus, there is no need to worry about the leakage of the iris feature template. At the same time, the system does not require a trusted center for authentication, and the authentication is completed on the server side directly using the one-time MAC authentication method. Tests have shown that when the system adopts an iris algorithm with a low depth of calculation circuit such as the Hamming distance comparison algorithm, it has good performance, which basically meets the requirements of real application scenarios.
Simplified Vector Control of a Nested-Loop Rotor Brush-less Doubly Fed Induction Motor

The paper presents a dq-model used to analyze a brushless doubly fed induction machines’ closed loop control-ability. A simplified vector control algorithm is proposed by reducing the controllers dependence on cross compensation in the power-winding current control loop. Simulink is used to show the viability of the controller in operation. It is found that this simplification provides a robust and responsive controller with good response times and acceptable disturbance rejection. Finally simulation results are used to show the models’ response to variations in speed, reactive power and torque whilst operating in motoring mode.