Miracle-dz/UniFAR-FTUs huggingface dataset:
Finite Element Solution of Poisson Equation over Polygonal Domains using an Explicit Integration Scheme and a novel Auto Mesh Generation Technique

: This paper presents an explicit finite element integration scheme to compute the stiffness matrices for linear convex quadrilaterals. Finite element formulationals express stiffness matrices as double integrals of the products of global derivatives. These integrals can be shown to depend on triple products of the geometric properties matrix and the matrix of integrals containing the rational functions with polynomial numerators and linear denominator in bivariates as integrands over a 2-square. These integrals are computed explicitely by using symbolic mathematics capabilities of MATLAB. The proposed explicit finite element integration scheme can be applied solve boundary value problems in continuum mechanics over convex polygonal domains.We have also developed an automatic all quadrilateral mesh generation technique for convex polygonal domain which provides the nodal coordinates and element connectivity. We have used the explicit integration scheme and the novel mesh generation technique to solve the Poisson equation with given Dirichlet boundary conditions over convex polygonal domains. This proposes the explicit integration scheme for a unique linear convex quadrilateral which can be obtained from an arbitrary linear triangle by joining the centroid to the midpoints of sides of the triangle. The explicit integration scheme proposed for these unique linear convex quadrilaterals is derived by using the standard transformations in two steps. We first map an arbitrary triangle into a standard right isosceles triangle by using a affine linear transformation from global (x, y) space into a local space (u, v). We discritise this standard right isosceles triangle in (u, v) space into
Evaluation of irrigation scheduling to maximize tomato production using comparative assessment of soil moisture and evapotranspiration in restricted irrigated regions

Abstract Evaluating and comparing two different irrigation scheduling methods like soil moisture (SM) and evapotranspiration (ET)-based irrigation scheduling methods were assessed scientifically to maximize tomato yield, especially in areas where restricted irrigation facilities are available. The experimental design was arranged in a Randomized Complete Block Design (RCBD) with 100%, 75%, and 50% water requirements with three replications. The water was applied to furrows using Randomized Block Design (RBC) flume with an inflow rate of 1.62 l/s. The total amount of water applied in SM- and ET-based methods were 229.1 mm and 280 mm, respectively. The collected data were analyzed using ANOVA (statistical software) at 5% significance level. Values on agronomic characteristics, yield attributes, and yield were determined for those two methods. T1–T6 are the total treatments used in this research. Out of which, T1, T2, and T3 are taken as SM-based represented for 100%, 75%, and 50% of requirements and T4, T5, and T6 as ET-based represented for the same percentage of requirements. The results did not illustrate a huge difference in yield potential. The highest net benefit on yield was obtained at T2 (SM-based), whereas the lowest in T6 (ET-based). It was also observed that SM-based method saved around 18.2% of irrigation water compared to ET-based approach. Therefore, to cultivate high water demanding crops such as tomato in water scarce areas, SM-based irrigation scheduling method is comparatively better than ET-based as far as yield is concerned.
Non-Muslims' Intention to Consume Halal Food in Indonesia

The effect of religiosity on intention to consume halal food among non-Muslims on a national scale has not been examined in previous studies. This research aims to gauge the acceptance of non-Muslims toward halal-certified food in Indonesia by investigating the effect of attitude, subjective norms, perceived behavioral control, and religiosity on the intention of non-Muslims to consume halal food. Data was collected from 250 respondents in each province using convenience sampling and analyzed using PLS-SEM. The results show that attitude, subjective norms, and religiosity significantly affect intention, while perceived behavioral control does not show significance. Theoretical implications of this research lie in its potential contribution to the academic discourse surrounding the acceptance of halal-certified food among non-Muslim people. Additionally, this study is expected to yield practical benefits by informing campaigns aimed at promoting halal-certified food among non-Muslims.
Structured prediction for sequential data

In this manuscript, we consider structured machine learning problems and consider more precisely the ones involving sequential structure. In a first part, we consider the problem of similarity measure learning for two tasks where sequential structure is at stake: (i) the multivariate change-point detection and (ii) the time warping of pairs of time series. The methods generally used to solve these tasks rely on a similarity measure to compare timestamps. We propose to learn a similarity measure from fully labelled data, i.e., signals already segmented or pairs of signals for which the optimal time warping is known. Using standard structured prediction methods, we present algorithmically efficient ways for learning. We propose to use loss functions specifically designed for the tasks. We validate our approach on real-world data. In a second part, we focus on the problem of weak supervision, in which sequential data are not totally labeled. We focus on the problem of aligning an audio recording with its score. We consider the score as a symbolic representation giving: (i) a complete information about the order of events or notes played and (ii) an approximate idea about the expected shape of the alignment. We propose to learn a classifier for each note using this information. Our learning problem is based onthe optimization of a convex function that takes advantage of the weak supervision and of the sequential structure of data. Our approach is validated through experiments on the task of audio-to-score on real musical data.
Facilitating the Production of Place-Based Knowledge for Participatory Community Development in Rural Pennsylvania

Abstract:Place-based knowledge is best actualized through the vehicle of inclusive, participatory processes intended for community improvement. This report is a case study of the production of place-based knowledge in the context of public participation, planning for revitalization, and “asset-based” development in three rural Pennsylvania communities: Selinsgrove, Sunbury and Danville. The study addresses the questions, “How can local communities contribute to place-sensitive development in rural places? ” and “What are the outcomes of adult and child participation in community-based projects? ” The paper reviews the projects' phases and methods for engaging each town's population in identifying and prioritizing issues for revitalization, and reflects on the outcomes of each town's participation and the implications of place-generated knowledge for community development practice.
Classification interactive multi-label pour l’aide à l’organisation personnalisée des données

L’importance croissante donnee actuellement aux contenus personnalises a conduit au developpement de plusieurs systemes de classification interactive pour diverses applications originales. Neanmoins, tous ces systemes recourent a une classification mono-label des items qui limite fortement l’expressivite de l’utilisateur. Le probleme majeur commun a tous les developpeurs d’un systeme de classification interactif et multi-label est : quel classifieur multi-label devrions-nous choisir ? Les evaluations experimentales des systemes d’apprentissage interactifs recents sont essentiellement subjectives. L’importance de leurs conclusions est donc limitee. Pour tirer des conclusions plus generales qui permettent de guider la selection de l’algorithme d’apprentissage approprie lors du developpement d’un tel systeme, nous etudions de maniere approfondie l’impact des contraintes d’interactivite majeures (apprentissage a partir de peu d’exemples en un temps limite) sur les performances predictives et les temps de calcul des classifieurs. Les experimentations mettent en evidence le potentiel d’une approche d’apprentissage ensemble Random Forest of Predictive Clustering Trees (RF-PCT). Cependant, la forte contrainte sur le temps de calcul posee par l’interactivite, nous a conduits a proposer une nouvelle approche d’apprentissage hybride FMDI-RF+ qui associe RF-PCT avec une approche de factorisation de matrice efficace pour la reduction de dimensions. Les resultats experimentaux indiquent que FMDI-RF+ est aussi precise que RF-PCT dans les predictions avec clairement un avantage a FMDI-RF+ pour la vitesse de calcul.
Electromagnetic Scattering in Micro- and Nanostructured Materials

The research fields of optical microstructures and plasmonic nanostructures are particularly active these years, and interesting applications in, e.g., quantum information technology in the former and novel types of solar cells in the latter, drive the investigations. Central in both fields is the interaction of light with matter, in the forms of semiconductors and metals in the two cases, and fundamental understanding of the interactions is important to optimize technological designs. To address this, we in the present thesis develop a formalism for determining the electric field in a homogeneous three dimensional space with spherical inhomogeneities embedded. The formalism accounts fully for the multiple reflections the field undergoes in such structures, and likewise the vectorial nature of the field is treated rigorously. The formalism is based on the Lippmann-Schwinger equation and the electromagnetic Green’s tensor and uses an expansion of the field on spherical wavefunctions. Addition theorems for these are extensively used, and all parts of the formalism are expressed analytically. With the formalism, we show that the simpler approach of modeling the spherical scatterers as polarizable dipoles, which is often alluded to in the literature, breaks down in the limit of closely spaced scattering objects. The study of metallic nanoparticles is particularly intriguing when these are in close proximity, due to the coupling of their near-fields, and the breakdown of the simpler approach reveals a need for the present formalism. Additionally, we study dimers and chains of metallic nanoparticles and analyze their spectra, when exposed to fields of different polarizations. The spectral response is highly dependent on the polarization, and we demonstrate for the dimer, under polarization along the dimer axis, a d−1/2-dependence of the relative shift of the resonance wavelength, d being the distance between the particles. This dependence on d is softer than reported earlier, and thus constitutes the foundation for a more systematic study. The correlation of distance and spectral properties may have applications within biosensing and -imaging on the nanoscale. For the chain, we demonstrate a next-nearest neighbor interaction between the nanoparticles through the study of its spectral properties. Finally, we present a calculation of the Green’s tensor for the dimer, illustrating that the formalism may likewise be used for modeling optical microstructures, e.g. three dimensional photonic crystals.
Wastewater Treatment and Electricity Generation with Different Cathode Solutions in MFC

A microbial fuel cell (MFC) with cathode and anode chambers was utilized to generate power while simultaneously removing COD from wastewater. By utilizing various oxidant solutions, it is possible to increase the generated voltage. The anode chamber was used for anaerobic treatment of synthetic wastewater (approximately 1000 mg/L), whereas the cathode chamber contained various oxidant solutions such as dilute hydrogen peroxide (300 mg/L), KMnO4 (300 mg/L), K2Cr2O7 (300 mg/L) and Fenton reagent (H2O2/Fe(II), 300/20 mg/L). Aerobic wastewater treatment and intermittent ozonation were also tested in the cathode chamber. With intermittent ozonation of the cathode chamber, the highest power output (382 mW/m2) was obtained. At the conclusion of the operation period, the COD concentration in the anode chamber decreased from 1170 mg/L to 650 mg/L, resulting in nearly 45% COD removal. In the cathode chamber, the use of diluted KMnO4 and H2O2 solutions produced high power densities of 35 and 23 W/m2, respectively, while the other oxidants produced low power densities. At the end of 72 hours, the COD content of the anaerobic chamber decreased from 800 mg/L to nearly 333 mg/L, resulting in nearly 59% COD removal for the KMnO4 solution. Considering the high cost of ozonation, it is recommended that either aerobic wastewater treatment or dilute KMnO4/H2O2 solutions should be used in the cathode chamber for high power generation.
PROGRESS IN FULLY NONLINEAR POTENTIAL FLOW MODELING OF 3D EXTREME OCEAN WAVES

SG and FE acknowledge the US National Science Foundation (NSF), under grant CMS0100223 of “the Engineering/Earthquake, Hazards and Mitigation Program”, and SG also acknowledges the US Office of Naval Research, under grant N000140510068, for supporting part of this work. Jeff Harris’ help is gratefully acknowledged for providing original data for the last two figures. Frederic.Dias@cmla.ens-cachan.fr. guyenne@math.udel. edu. PG acknowledges support from the University of Delaware Research Foundation and the US NSF under grant DMS-0625931. fochesat@cmla.ens-cachan.fr. enet@alkyon.nl.
An Algorithm to Compute the Stochastically Stable Distribution of a Perturbed Markov Matrix

Recently, some researchers have attempted to exploit state-aggregation techniques to compute stable distributions of high-dimensional Markov matrices (Gambin and Pokarowski, 2001). While these researchers have devised an efficient, recursive algorithm, their results are only approximate. We improve upon past results by presenting a novel state aggregation technique, which we use to give the first (to our knowledge) scalable, exact algorithm for computing the stochastically stable distribution of a perturbed Markov matrix. Since it is not combinatorial in nature, our algorithm is computationally feasible even for high-dimensional models.
Estudio de las actitudes hacia la estadística en estudiantes de psicología

La Estadistica se ha incorporado en la mayoria de las carreras universitarias y entre ellas en el grado de psicologia donde la ensenanza de conceptos estadisticos presenta problemas didacticos especificos debido a que los estudiantes que lo cursan tienen una base matematica muy heterogenea. En este trabajo nos centramos en el estudio de sus actitudes, por su influencia en el proceso de aprendizaje, y las analizamos a traves de la Escala de Actitudes hacia la Estadistica de Estrada EAEE (ESTRADA, 2002). Los resultados indican actitudes en general moderadas o positivas, con una puntuacion promedio global ligeramente superior a la posicion teorica de indiferencia. El curso y los estudios previos en esta materia inciden en su actitud. Destacamos que la actitud global hacia la estadistica empeora con los anos de estudio, aunque las puntuaciones totales mas bajas se presentan en los estudiantes que nunca estudiaron estadistica, resultados que invitan a la reflexion sobre la manera que se ensenan en los diferentes niveles educativos.
Sentiment Analysis and Text Classification for Depression Detection

Depression is an illness that can harm someone's life. However, many people still do not know that they are having depression and tend to express their feelings through text or social media. Thus, text-based depression detection could help in identifying the early detection of the illness. Therefore, the research aims to build a depression detection that can identify possible depression cues based on Bahasa Malaysia text. The data, in the form of text, has been collected from depressed and healthy people via a google form. There are three questions asked which are “Apakah kenangan manis yang anda ingat? ”, “Apakah rutin harian anda? ” and “Apakah keadaan yang membuatkan anda stress? ” which obtained 172, 169 and 170 responses for each question respectively. All the datasets are stored in a CSV file. Using Python, TF-IDF was extracted as the feature and pipeline into several classifier models such as Random Forest, Multinomial Naïve Bayes, and Logistic Regression. The results were presented using the classification metrics of confusion matrix, accuracy, and F1-score. Also, another method has been conducted using the text sentiment techniques Vader and Text Blob onto the datasets to identify whether depressive text falls under negative sentiment or vice versa. The percentage differences were determined between the actual sentiment compared to Vader and Text Blob sentiment. From the experiment, the highest score is achieved by AdaBoost Classifier with a 0.66-F1 score. The best model is chosen to be utilized in the Graphical User Interface (GUI).
Demystifying meal-sharing experiences through a combination of PLS-SEM and fsQCA

ABSTRACT This research aims to demystify the links between meal-sharing experience, overall satisfaction, and behavioral intentions (e.g., re-purchase and word-of-mouth) based on social practice theory and planned behavior theory. It utilized a questionnaire to test the relationships through the purposeful sampling of 217 Indian domestic travelers. The current study applied both the symmetric method of partial least squares-structural equation modeling (PLS-SEM) and the asymmetric method of fuzzy-set qualitative comparative analysis (fsQCA). The PLS-SEM results showed that only the hospitality dimension of the meal-sharing experience positively relates to travelers’ overall satisfaction, re-purchase, and word-of-mouth (WoM) intentions. Apart from this, the results of fsQCA demonstrated several sufficient combinations of dimensions to generate satisfaction, re-purchase, and WoM intentions. It has several practical implications for hosts of meal-sharing platforms as to how they can improve their guests’ experience to delight and get them to re-purchase their services.
Uniform rotational motion compensation for inverse synthetic aperture radar with non-cooperative targets

In the current scenario of high-range resolution radars, the rotational motion of the target usually generates migration through resolution cells (MTRC) in the inverse synthetic aperture radar (ISAR) images. A technique to correct the MTRC in the case of uniform rotation rate is proposed. An estimation of the rotation vector of the non-cooperative targets is not required. The approach compensates the rotational motion in two steps: the slant-range rotation compensation (SRRC) and the cross-range rotation compensation (CRRC). CRRC is based on an extension of phase difference (PD) and on a robust method to delete outliers. The technique is verified both with simulated and live data from a millimetre-wave linear frequency-modulated continuous wave radar. A comparison with a minimum entropy-based technique is also made.
Reflexiones epistemológicas sobre inter y transdisciplina desde la perspectiva del pensamiento dialéctico y el paradigma de la complejidad

El objetivo de la presentación es ofrecer algunas reflexiones de raigambre epistemológica para la discusión entre paradigmas de actualidad. Atenderemos a las siguientes dimensiones analíticas: - Cuestiones ontológicas: andamiaje categorial para una concepción orgánica y holística de los fenómenos que se estudian, atendiendo al carácter estratigráfico de la realidad y a la dialéctica-diferenciación e integración propia de toda realidad organizada (Hegel, Piaget, Goldmann). - Cuestiones epistemológicas: modelos disponibles para superar las concepciones atomistas, desvitalizadas y a-histórica promovidas por la ciencia clásica y el positivismo (ecología de saberes -Bateson, Samaja, De Sousa Santos-, semiótica dialéctica Peirce-Samaja, aportes de las ciencias de la complejidad provenientes de las llamadas “ciencias duras”. - Cuestiones pedagógicas: formación de profesionales sensibles a su contexto social e histórico, capaces de pensar globalmente para actuar localmente, formación basada en problemas, promoción de la agencialidad, el protagonismo y el compromiso social, cultores de la producción colectiva del conocimiento. - Cuestiones metodológicas: una metodología ampliada que integre con igual validez los contextos de descubrimiento como los de justificación, motivada por una reflexión crítico-epistemológica, alejada de toda concepción prescriptivista, que oferte recursos y modelos para investigar desde la complejidad. - Cuestiones ético-ideológicas: Vocación dialógica y colectivista en la producción de conocimiento. Motivación por la creatividad al servicio de transformaciones socialmente potenciadoras e inclusivas, que promueva prácticas de resistencia a la ciencia hegemónica al servicio de la reproducción del capital. - Cuestiones programático-institucionales: Redefinir prácticas institucionales, motivando la integración entre profesionales, recuperar el sentido plenario de la vida humana (que resista a la enajenación propia de la sociedad de consumo). Concebir propuestas integradoras y colectivistas. Articular la investigación con actores provenientes de múltiples espacios sociales. Como marco general de la reflexión comentaremos el “Manifiesto de la Transdisciplinariedad” de Basarab Nicolescu, que inspira los fundamentos de cada una de las dimensiones analíticas propuestas.
Linguistic choices vs. probabilities – how much and what can linguistic theory explain?

The purpose of this paper is to present a case study elucidating how multivariate models can be interpreted to shed light on the nature of the use and choice among lexical and structural alternatives in language, more specifically near-synonyms, and the underlying explanatory factors. By multivariate models I imply both the use of multiple linguistic variables from a range of categories, instead of only one or two, in order to study and explain some linguistic phenomenon, as well as the use of multivariate statistical methods such as polytomous logistic regression.
Optimal Torque Distribution for the Stability Improvement of a Four-Wheel Distributed-Driven Electric Vehicle Using Coordinated Control

This paper presented an optimal torque distribution scheme for the stability improvement of a distributed-driven electric vehicle (DEV). The nonlinear dynamics and tire model of the DEV are constructed. Moreover, the single-point preview optimal curvature model with the proportional-integral-derivative (PID) process is developed to simulate the driver's behavior. By using coordinated control and sliding mode control, a three-layer hierarchical control system was developed. In the upper level, the integral two degree-of-freedom (DOF) linear model is used to compute the equivalent yaw moment for vehicle stability. With the actuators' restrictions, the middle level solved the linear quadratic regulator (LQR) problem via a weighted least square (WLS) method to optimally distribute the wheel torque. In the lower level, a slip rate controller (SRC) was presented to reallocate the actual torques based on the sliding mode method. The simulation results show that the proposed scheme has high path-tracking accuracy and that vehicle stability under limited conditions is improved efficiently. Moreover, the safety under actuator failure is enhanced.