Miracle-dz/UniFAR-FTUs huggingface dataset:
Mesures de pertinence par les critères du " maximum de vraisemblance " de " BIC " et " AIC" appliqués à l'évaluation des paramètres stochastiques de Modèles de Markov Cachés

Les modeles de Markov caches ou HMM sont largement utilises dans les domaines de la reconnaissance des formes, de la parole ainsi que dans la modelisation de processus complexes. Nous proposons dans cette etude d'evaluer la pertinence des para- metres de modeles de Markov caches de facon objective sans connaissance a priori. Dans un premier temps, nous faisons un etat de l'art sur les criteres de selection de modeles les plus utilises dans la litterature. Nous presentons ensuite deux criteres permettant d'evaluer la pertinence d'evenements stochastiques issus de modeles de Markov caches. Nous etayons notre etude en nous appuyant sur l'exemple concret d'un processus industriel. Nous evaluons alors les parametres de sortie des differents modeles testes sur ce processus, pour ﬁnalement s'orienter vers le modele le plus pertinent.
Auto-Scaling, Load Balancing and Monitoring in Commercial and Open-Source Clouds

Over the past years, the Cloud phenomenon had an impressive increase in popularity in both the software industry and research worlds. The most interesting feature that Cloud Computing brings, from a Cloud client's point of view, is the on-demand resource provisioning model. This allows Cloud client platforms to be scaled up in order to accommodate more incoming clients and to scale down when the platform has unused resources, and this can all be done while the platform is running. As a result, the physical resources are used more efficiently and the Cloud client saves expenses. Achieving the above mentioned is not trivial and is done by leveraging more direct functionalities that Clouds provide. Three of these key functionalities are automatic scaling, load balancing and monitoring. They represent the focus of the current work. This report is divided into three main parts, one for each of the three main topics of interest: auto-scaling, load balancing and monitoring. We detail each of the three topics and present details on their presence and implementation in the commercial, open-source and research worlds. Among the commercial Cloud platform providers we have focused on Amazon EC2, Microsoft Azure, GoGrid and RackSpace. From the open-source initiatives we have focused our attention on Nimbus, Eucalyptus and OpenNebula. We have also detailed endeavours in the research world that are relevant to the topic of interest and are not connected to any of the Cloud providers. By studying this report, the reader will be able to understand the role that each of the three Cloud features plays for a Cloud client, will understand their inner workings and will be aware of the state-of-the-art available in current commercial and open-source Cloud platforms.
Album Story 1 Description for Images in Isolation & in Sequences Re-telling Story 1 Caption in Sequence Storytelling Story 2 Story 3 Re-telling Preferred Photo Sequence Story 4 Story

We introduce the first dataset for sequential vision-to-language, and explore how this data may be used for the task of visual storytelling. The dataset includes 81,743 unique photos in 20,211 sequences, aligned to descriptive and story language. We establish several strong baselines for the storytelling task, and motivate an automatic metric to benchmark progress. We argue that modelling figurative and social language, as provided for in this data and the storytelling task, has the potential to move artificial intelligence towards more human-like expression and understanding.
Multi‐scale approach for strength properties estimation in functional materials

A new methodology to obtain metallic functional materials with predefined sets of strength properties has been developed. It has been shown that in order to accurately estimate set of material properties at the macro‐level, information from the micro‐level needs to be taken into account. As a result a two‐level estimation model, based on the theory of fuzzy sets, has been proposed. To demonstrate the developed methodology, a reinforcing steel has been analysed. Using microstructural information, derived from an available set of experimentally obtained digital images of material microsections under different heat treatment conditions, macroscopic strength properties of reinforcing steel have been determined.
Measurement of the resonant and CP components in B ̄ 0 →j /ψπ+π- decays MEASUREMENT of the RESONANT and CP ⋯ R. AAIJ et al.

: The resonant structure of the reaction B 0 → J/ψπ + π − is studied using data from 3 fb − 1 of integrated luminosity collected by the LHCb experiment, one-third at 7 Tev center-of-mass energy and the remainder at 8 Tev. The invariant mass of the π + π − pair and three decay angular distributions are used to determine the fractions of the resonant and non-resonant components. Six interfering π + π − states: ρ (770) , f 0 (500) , f 2 (1270) , ρ (1450) , ω (782) and ρ (1700) are required to give a good description of invariant mass spectra and decay angular distributions. The positive and negative CP fractions of each of the resonant final states are determined. The f 0 (980) meson is not seen and the upper limit on its presence, compared with the observed f 0 (500) rate, is inconsistent with a model of tetraquark substructure for these scalar mesons at the eight standard deviation level. In the qq model, the absolute value of the mixing angle between the f 0 (980) and the f 0 (500) scalar mesons is limited to be less than 17 ◦ at 90% confidence level. Abstract The resonant structure of the reaction B 0 → J/ψπ + π − is studied using data from 3 fb − 1 of integrated luminosity collected by the LHCb experiment, one-third at 7 TeV center-of-mass energy and the remainder at 8 TeV. The invariant mass of the π + π − pair and three decay angular distributions are used to determine the fractions of the resonant and non-resonant components. Six interfering π + π − states: ρ (770), f 0 (500), f 2 (1270), ρ (1450), ω (782) and ρ (1700) are required to give a good description of invariant mass spectra and decay angular distributions. The positive and negative CP fractions of each of the resonant ﬁnal states are determined. The f 0 (980) meson is not seen and the upper limit on its presence, compared with the observed f 0 (500) rate, is inconsistent with a model where these scalar mesons are formed from two quarks and two anti-quarks (tetraquarks) at the eight standard deviation level. In the qq model, the absolute value of the mixing angle between the f 0 (980) and the f 0 (500) scalar mesons is limited to be less than 17 ◦ at 90% conﬁdence level.
Representation Learning With Autoencoders For Electronic Health Records

REPRESENTATION LEARNING WITH AUTOENCODERS FOR ELECTRONIC HEALTH RECORDS by NAJIBESADAT SADATIJAFARKALAEI August 2020 Advisor: Dr. Dongxiao Zhu Major: Computer Science Degree: Master of Science Increasing volume of Electronic Health Records (EHR) in recent years provides great opportunities for data scientists to collaborate on different aspects of healthcare research by applying advanced analytics to these EHR clinical data. A key requirement however is obtaining meaningful insights from high dimensional, sparse and complex clinical data. Data science approaches typically address this challenge by performing feature learning in order to build more reliable and informative feature representations from clinical data followed by supervised learning. In this research, we propose a predictive modeling approach based on deep feature representations and word embedding techniques. Our method uses different deep architectures (stacked sparse autoencoders, deep belief network, adversarial autoencoders and variational autoencoders) for feature representation in higher-level abstraction to obtain effective and robust features from EHRs, and then build prediction models on top of them. Our approach is particularly useful when the unlabeled data is abundant whereas labeled data is scarce. We investigate the performance of representation learning through a supervised learning approach. Our focus is to present a comparative study to evaluate the performance of different deep architectures through supervised learn-
A Sketch-Based Interface for Annotation of 3 D Brain Vascular Reconstructions

Within the medical imaging community, 3D models of anatomical structures are now widely used in order to establish more accurate diagnoses than those based on 2D images. Many research works focus on an automatic process to build such 3D models. However automatic reconstruction induces many artifacts if the anatomical structure exhibits tortuous and thin parts (such as vascular networks) and the correction of these artifacts involves 3D-modeling skills and times that radiologists do not have. This article presents a semi-automatic approach to build a correct topology of vascular networks from 3D medical images. The user interface is based on sketching; user strokes both de nes a command and the part of geometry where the command is applied to. Moreover the user-gesture speed is taken into account to adjust the command: a slow and precise gesture will correct a local part of the topology while a fast gesture will correct a larger part of the topology. Our system relies on an automatic segmentation that provides a initial guess that the user can interactively modify using the proposed set of commands. This allows to correct the anatomical aberrations or ambiguities that appear on the segmented model in a few strokes. Key-words: Sketching,3D Reconstruction, Model Annotation ∗ e-mail: david.selosse@li . fr † LIFL, CNRS/IRCICA INRIA Lille-Nord-Europe ‡ e-mail: jeremie.dequidt@li . fr § e-mail: laurent.grisoni@li . fr ha l-0 06 98 83 2, v er si on 1 17 M ay 2 01 2 Une interface Sketch-Based pour l'Annotation de Reconstruction 3D Vasculaire Cérébrale Résumé : Dans le domaine de l'imagerie médicale, la modélisation 3D de structures anatomiques est maintenant largement utilisée dans l'optique d'établir des diagnostics plus précis qu'avec des données basées sur des images 2D. Aujourd'hui, de nombreux travaux mettent l'accent sur les méthodes automatique de reconstruction de modèles 3D mais ces méthodes induisent de nombreuses erreurs. Avec une structure anatomique (réseau cérébral) présente des parties assez nes et tortueuses, des erreurs sont introduites, cela nécessitent de la correction du modèle 3D, mais aussi des compétences et des heures que les radiologistes ne possèdent pas. Cet article présente une approche semi-automatique de reconstruction d'une topologie correcte de réseaux vasculaires issus d'images médicales en 3D. Notre système repose sur une segmentation automatique qui fournit une estimation initiale dont l'utilisateur peut modi er interactivement en utilisant un jeu proposé de commandes basées sur le croquis. Cela permet de corriger les aberrations anatomiques ou les ambiguÃ tés qui apparaissent sur le modèle segmenté en quelques traits. Mots-clés : Annotation de modele, Reconstruction 3D, Sketching ha l-0 06 98 83 2, v er si on 1 17 M ay 2 01 2 A Sketch-Based Interface for Annotation of 3D Brain Vascular Reconstructions 3
An insight into Newton's cooling law using fractional calculus

For small temperature differences between a heated body and its environment, Newton's law of cooling predicts that the instantaneous rate of change of temperature of any heated body with respect to time is proportional to the difference in temperature of the body with the ambient, time being measured in integer units. Our experiments on the cooling of different liquids (water, mustard oil, and mercury) did not fit the theoretical predictions of Newton's law of cooling in this form. The solution was done using both Caputo and Riemann-Liouville type fractional derivatives to check if natural phenomena showed any preference in mathematics. In both cases, we find that cooling of liquids has an identical value of the fractional derivative of time that increases with the viscosity of the liquid. On the other hand, the cooling studies on metal alloys could be fitted exactly by integer order time derivative equations. The proportionality constant between heat flux and temperature difference was examined with resp.
Psychology, Society & Education

The perception of body image is usually affected in the different stages of a woman’s life. The practice of physical exercise would be related to an improvement in the perception of body image, so it is important to investigate how the practice of physical exercise affects body image in the postpartum stage, since at this stage the perception is usually more negative . For this purpose, an online questionnaire was designed, consisting of socio-demographic questions, the International Physical Activity Questionnaire and the Body Shape Questionnaire. The sample consisted of 80 Spanish women, aged between 23 and 42 years, who were mothers in 2020 and 2021. The results show that the Body Mass Index is positively and significantly associated with body dissatisfaction. However, in relation to physical exercise, the results showed an inverse relationship. The women with the highest body dissatisfaction were those with the highest Body Mass Index and the highest level of physical activity, with Body Mass Index being the variable that most explained body dissatisfaction.
A New Regression Equation Proposed For Mixed Dentition Analysis in Chhattisgarh, Central India Population

Objective: To develop and propose a new regression for mixed dentition analysis in Chhattisgarh, Central India population. Material and Methods: The permanent dentition dental casts of 800 (400 males and 400 females) Chhattisgarh subjects were selected. Digital caliper was used to measure the mesiodistal crown widths of teeth. The linear regression equations and correlation between four mandibular incisors and the canine-premolars segments of maxillary and mandibular arches were developed (modified Tanaka-Johnston equation) and proposed for Chhattisgarh population. Results: New standardized regression equations were formulated to predict the mesiodistal widths of unerupted canines and premolars especially for Chhattisgarh, Central India population. The equation in males for maxillary arch was Y = 11.90 + 0.39 (X) and for mandibular arch was Y = 12.23 + 0.36 (X). Similarly, the equation in females for maxillary arch was Y = 14.40 + 0.26 (X) and for mandibular arch was Y= 10.26 + 0.43 (X). A significant sexual dimorphism in teeth sizes was seen with higher mesio distal dimension in males in Chhattisgarh population. Conclusion: Sum of the mesiodistal diameter of permanent mandibular incisors can be used reliably to predict/estimate the sum of mesiodistal diameters of unerupted canines and premolars with the new regression equations.
Image Training, Corner and FAST Features based Algorithm for Face Tracking in Low Resolution Different Background Challenging Video Sequences

We are proposing a novel algorithm for tracking human face(s) in different background video sequences. We have trained both face and non-face images which help in face(s) detection process. At first, FAST features and corner points are extracted from the detected face(s). Further, mid points are calculated from corner points. FAST features, corner points and mid points are combined together. Using the combined points, point tracker tracks face(s) in the frames of the video sequence. Standard metrics were adopted for measuring the performance of the proposed algorithm. Low resolution video sequences with challenges such as partial occlusion, changes in expression, variations in illumination and pose took part while testing the proposed algorithm. Test results clearly indicate the robustness of the proposed algorithm on all different background challenging video sequences.
Better Rewards Yield Better Summaries : Learning to Summarise Without

where zi is the word embedding of the ith word in s and e is the dimension of the word embeddings. The addition, multiplication and exponentiation operations are element-wise. p ∈ R ∪ {±∞} controls “weights” assigned to each element: with p = 1, for instance, each word element is weighted equally and φ(s; 1) is the standard average-pooling; with the increase of p, it assigns higher weights to the elements with higher values. With p = +∞, PMeans is equivalent to element-wise max-pooling.
Light Weight Circular Error Learning Algorithm (CELA) for Secure Data Communication Protocol in IoT-Cloud Systems

—The data driven smart applications, utilize the IoT, Cloud Computing, AI and other digital technologies to create, curate and operate on large amounts of data to provide intelligent solutions for day-to-day problems. Security of Data in the IoT-Cloud systems has become very crucial as there are several attacks such as ransomware, data thieving, and data corruption, causing huge loss to the application users. The basic impediment in providing strong security solutions for the IoT systems, is due the resource limitations of IoT devices. Recently, there is an additional threat of quantum computing being able to break the traditional cryptographic techniques. The objective of this research is to address the bifold challenge and design a light weight quantum secure communication protocol for the IoT Cloud ecosystem. The Ring Learning With Errors (RLWE) lattice based cryptography has emerged as the most popular in the NIST PQC Standardization Program. A light weight Circular Learning Error Algorithm (CELA) has been proposed by optimizing RLWE to make it suitable for IoT-Cloud environment. The CELA inherits the advantages of quantum security and homomorphic encryption from RLWE. It is observed that CELA is light weight in terms of execution time and a slightly bigger cipher text size provides higher security as compared to RLWE. The paper also offers plausible solutions for future quantum secure cryptographic protocols.
Lower Bounds and Hierarchies for Quantum Automata Communication Protocols and Quantum Ordered Binary Decision Diagrams with Repeated Test

We explore multi-round quantum automata communication protocols. It is restricted version of multi-round quantum communication protocols. “Automata” term means that players forget history from previous rounds, and its behavior is obtained only by input and message from the opposite player. This model is interesting because it allows to get lower bounds for models like automata, Ordered Binary Decision Diagrams and streaming algorithms. In the same time, we can prove stronger results with this restriction. We present a lower bound for that automata protocol. Additionally, we show lower bound for Disjointness function for this model. As an application of communication complexity results, we consider a quantum Ordered Read-k-times Branching Programs (kQOBDD). Our communication complexity result allows us to get lower bound for k-QOBDD and hierarchies for sublinear width bounded error k-QOBDDs, for k = o( √ n). Also we prove a hierarchy for polynomial size bounded error k-QOBDDs for constant k, and it differs from the situation with unbounded error where it is known that increasing of k does not give any advantage.
Principals’ Toxic Leadership Behaviour and Teachers’ Workplace Incivility in Public Senior Secondary Schools, Lagos State, Nigeria

This paper examines the connection between toxic leadership and workplace incivility among teachers in the selected public senior secondary schools in Lagos, Nigeria. Using the stratified sampling technique, 1,274 respondents consisting of 98 principals, 196 vice-principals, and 980 teachers were selected from a total population of 20,243. A structured questionnaire was used to collect quantitative data. The Statistical Package for Social Science (SPSS) version 24.0 was used to analyse quantitative data, and the Pearson’s Product-Moment Correlation was used to test the hypotheses with the results shows that toxic leadership behaviour had a negative and non-significant correlation with teachers’ hostility in Lagos State senior secondary (r = -0.029, >0.05), and toxic leadership behaviour showed no significant correlation with teachers' withdrawal behaviour (r = 0.025, >0.05). The paper concludes that toxic leadership accounts for the derogatory treatment meted on teachers at work on Lagos State’s public senior secondary schools; and recommend the need for the Lagos State Education Districts to replace toxic leaders in schools with contemporary leadership styles that encourage team work and collaboration among teachers and allow participation in the process of decision-making.
Quantum treatment of field propagation in a fiber near the zero dispersion wavelength

In this report, we present a quantum theory describing the propagation of the electromagnetic radiation in a fiber in the presence of the third order dispersion coefficient. We obtained the quantum photon-polariton field, hence, we provide herein a coupled set of operator forms for the corresponding nonlinear Schrödinger equations when the third order dispersion coefficient is included. Coupled stochastic nonlinear Schrödinger equations were obtained by applying a positive P-representation that governs the propagation and interaction of quantum solitons in the presence of the third-order dispersion term. Finally, to reduce the fluctuations near solitons in the first approximation, we developed coupled stochastic linear equations.
Clayton copula for survival data with dependent censoring: An application to a tuberculosis treatment adherence data

Ignoring the presence of dependent censoring in data analysis can lead to biased estimates, for example, not considering the effect of abandonment of the tuberculosis treatment may influence inferences about the cure probability. In order to assess the relationship between cure and abandonment outcomes, we propose a copula Bayesian approach. Therefore, the main objective of this work is to introduce a Bayesian survival regression model, capable of taking into account the dependent censoring in the adjustment. So, this proposed approach is based on Clayton's copula, to provide the relation between survival and dependent censoring times. In addition, the Weibull and the piecewise exponential marginal distributions are considered in order to fit the times. A simulation study is carried out to perform comparisons between different scenarios of dependence, different specifications of prior distributions, and comparisons with the maximum likelihood inference. Finally, we apply the proposed approach to a tuberculosis treatment adherence dataset of an HIV cohort from Alvorada‐RS, Brazil. Results show that cure and abandonment outcomes are negatively correlated, that is, as long as the chance of abandoning the treatment increases, the chance of tuberculosis cure decreases.
Algoritmo semisupervisado de agrupamiento que combina SUBCLU y el agrupamiento basado en restricciones, para la detección de grupos en conjuntos de alta dimensionalidad

Los datos de alta dimensionalidad plantean un desafío para los algoritmos de agrupamiento tradicionales, ya que las medidas de similitud convencionales utilizadas por estos no son significativas cuando se aplican sobre el espacio completo de datos, por lo que afectan la calidad de los grupos. Ante esto, los algoritmos de agrupamiento de subespacios han sido propuestos como alternativa para encontrar todos los grupos en todos los espacios del conjunto de datos. Al detectar grupos en espacios de menor dimensionalidad, cada grupo detectado puede pertenecer a diferentes subespacios del conjunto de datos original. Consecuentemente, atributos que el usuario considere de interés pueden ser excluidos en algunos o todos los grupos, perdiendo información importante y reduciendo el valor del resultado para los analistas. En este proyecto, se propone un nuevo método que combina el algoritmo SUBCLU y el algoritmo de agrupamiento por restricciones, el cual permite al usuario identificar variables como atributos de interés con base en conocimiento previo del dominio, esto con el objeto de dirigir la detección de grupos hacia espacios que incluyan estos atributos y, por ende, generar grupos más significativos.