Miracle-dz/UniFAR-FTUs huggingface dataset:
Managerial innovation: a new way of managing, SELKANI, I. 1 Alternatives Managériales et Economiques

: The managerial innovation is perceived as an evolution of the management techniques, which constitutes in itself real importance towards the companies that would finish with the old modes and begin with the innovation techniques respecting the well-being of the employees and reaching better performance. According to a survey conducted by Business employees believe that the management of their company is little or no innovative". Indeed, the experience of Fiat is that this approach takes place in an almost perfect environment of confidence, and where the spirit of cooperation is present.
Differentiation of the botanical origin of honeys by fast, non-targeted 1H-NMR profiling and chemometric tools as alternative authenticity screening tool

N. Gerhardt, M. Birkenmeier, T. Kuballa, M. Ohmenhaeuser, S. Rohn and P. Weller* Institute for Instrumental Analytics, Mannheim University of Applied Sciences, Germany. Corresponding Author: p.weller@hs-mannheim.de Chemisches und Veterinaeruntersuchungsamt (CVUA) Karlsruhe, Germany. Thomas.Kuballa@CVUAKA.BWL. DE Chemisches und Veterinaeruntersuchungsamt (CVUA) Freiburg, Germany. Marc.Ohmenhaeuser@cvuafr.bwl. de Institute of Food Chemistry, University of Hamburg, Germany. rohn@chemie.uni-hamburg.de
ANALYSIS OF FOURIER TRANSFORMATION ON IMAGE ENHANCEMENT PROCESS IN DIGITAL IMAGE PROCESSING USING MATLAB

-An image enhancement process has the very important role in processing of image and resolution. This type of existing system assumes that the sensations of color have a strong correlation with reflectance and the amount of visible light reaching observers depends in the product of reflectance and illumination. The main aim of this project work is to produce the best technique to image enhance and protect the naturalness in the image. Here, we propose a naturalness preserved enhancement method for non-uniform illumination images using transformation technique. Now day’s applications require various kinds of images as sources of information for interpretation and inspection. Image enhancement is method of applying different alterations to an input image to make the resultant image more pleasing or to provide a better transform presentation for future automated image processing techniques. There are many pictures like satellite images and medical images are affected by the noisy and sharpness of effect. This is essential to enhance the contrast and remove the noise to increase picture standard. One is presenting a review on various image enhancement techniques for sharpening enhancement
PARAMETERS ESTIMA TION IN THE MODEL FOR IN SITU DEGRADABILITY OF MERTENS AND LOFTEN 1 Estimação dos parâmetros no modelo para degradabilidade in situ de Mertens e Loften

ABSTRACTThe aim of this study is to evaluate the behavior of the parameters of the degradation model proposed by Mertens & Loften(1980) fitted to the results of a rehearsal of degradability in situ. In the experiment, we evaluate the potentially degradable residue ofneutral detergent fiber (NDF) of coastcross grass (Cynodon dactylon x Cynodon nlemfunensis) cut at 60 days, with three replications.The potentially degradable residue of NDF is studied using fifteen incubation times (0; 0.5; 1; 3; 6; 9; 12; 18; 24; 36; 48; 56; 72; 96 and120 hours). The experimental plot is comprised of a non-lactating cow with a permanent ruminal fistula. It is obtained mean andindividual fits for the animals. Variances of parameter estimators is also obtained through both the covariance matrix of the parametersand the jackknife method, then resulting expressions for the estimate of the confidence interval for the parameters of the model. Theresults shows that the jackknife method presents larger variance estimate for the parameters of the model of Mertens & Loften (1980),resulting in confidence intervals of greater amplitude and less precise parameter estimates for both the individual and mean fits.Index terms: Nonlinear regression, ruminal degradability, jackknife method, coast-cross grass.RESUMOObjetiva-se avaliar o comportamento dos parâmetros do modelo de degradacao proposto por Mertens & Loften (1980)ajustado aos resultados de um ensaio de degradabilidade in situ. No experimento e avaliado o residuo potencialmente degradavel dafibra em detergente neutro (FDN) da graminea coastcross (Cynodon dactylon x Cynodon nlemfunensis) cortada aos 60 dias, com tresrepeticoes. O residuo potencialmente degradavel da FDN e estudado utilizando quinze tempos de incubacao (0; 0,5; 1; 3; 6; 9; 12; 18;24; 36; 48; 56; 72; 96 e 120 horas). A parcela experimental e constituida por uma vaca nao lactante, com fistula ruminal permanente.Sao obtidos ajustes medios e individuais para os animais. Obtem-se tambem as variâncias dos estimadores dos parâmetros por meioda matriz de variância e covariância dos parâmetros e pelo metodo jackknife, propondo-se expressoes para a estimacao do intervalode confianca para os parâmetros do modelo. Os resultados mostram que o metodo de jackknife apresenta maior estimativa de variânciapara os parâmetros do modelo de Mertens & Loften (1980), resultando em intervalos de confianca de maior amplitude e estimativasdos parâmetros menos precisas, nos ajustes individuais e medios.Termos para indexacao: Regressao nao-linear, degradabilidade ruminal, metodo jackknife, graminea coastcross.
ASSESSMENT OF TRAFFIC NOISE POLLUTION IN JAIPUR CITY AND ITS IMPACT ON HUMAN HEALTH

Noise is a disturbance to the human environment that is escalating at such a high rate that it will become a major threat to the quality of human lives. In the past thirty years, noise in all areas, especially in urban areas, have been increasing rapidly because it is associated with rapid industrialization, urbanization, (expansion of road network) and population growth. The drastic rise in the number of vehicles has increased noise pollution in the Jaipur city. The present study on Jaipur city was performed to find out the impact of traffic noise level on attitudes of exposed pollution. The study was carried out at 5 different locations with Sound Level Meter to assess the day noise level. The study revealed the fact that noise levels have reached an alarming level. People reported that traffic noise is the main cause of headache, high BP and dizziness problems. It is observed that all the selected location, the level of noise was found to be above prescribed noise standard level of Central Pollution Control Board (CPCB) India and Bureau of Indian Standard (BIS). This is considered to be harmful for physiological well being of people and which can interfere with normal activities for humans. The present study is aimed to investigate the impact of noise pollution on residents/community residing near roadside. The degree of annoyance was assessed by means of a questionnaire. It was found that among all noise-generating sources, road traffic was the major source of noise. A health survey reported about 55% of population was suffering by frequent irritation. 46% respondent felt hypertension, and 48.6% observed loss of sleep due to noise pollution. The most serious health hazards associated with high level of noise exposure is deafness which initially causes temporary hearing problem which has been reported in the study area. It is also observed from the study that places with high traffic congestion, narrow roads, and poor traffic management are more vulnerable to high levels of noise and more ill health effects.
Children and the Wealth of Nations (Preliminary)

The welfare of an individual depends on the quality and quantity of life. The quantity of life itself depends on longevity but also on the number of descendants. Speci cally, children, grandchildren, etc, o¤er an alternative way to extend life for altruistic parents. Everything else equal, a lower fertility rate reduces the welfare of altruistic parents. This paper incorporates fertility into an overall assessment of the degree and evolution of cross-country inequality around the world and shows that it is quantitatively important. Our calculations suggest a major quantityquantity trade-o¤: for the period 1970-2005, the overall welfare gains due to longevity improvements were mostly o¤set by the welfare loss due fertility reductions. The e¤ective quantity of life remained roughly constant. Keywords : fertility, children, welfare, quantity of life, world inequality JEL classi cation: I10, I31, J17, O57
Topic Coherence for Dutch

Topic modeling has become a popular technique for exploring and analyzing the contents of large text corpora. The method ﬁnds latent topics by grouping together words that co-occur in documents. Topic modeling is unsupervised and probabilistic, and as a result of this topics are not always semantically coherent or meaningful. Because creating manual usefulness ratings is costly, researchers have been trying to come up with ways to automatically assess the interpretability of topics. A potential solution to this problem are topic coherence measures, which are calculated by taking into account word co-occurence statistics of an external corpus, such as Wikipedia. A recent study proposes a framework for topic coherence measures, and systematically evaluates the correlation between manual usefulness ratings and a wide variety of topic coherence measures [4]. However, all calculations are done for English topics, using the English Wikipedia. Having a resource to calculate topic coherence for Dutch could beneﬁt researchers in digital humanities. In this paper, we describe how we created such a resource from the Dutch Wikipedia, using Palmetto, a tool provided by the authors of [4]. In addition, we present the results of a case study to determine the best topic coherence measure for Dutch. The Palmetto database for Dutch was generated from a Wikipedia dump containing articles 1 . Preprocessing of the articles consisted of lemmatization and stopword removal. Palmetto and the database based on the Dutch Wikipedia are available online 2 In order to determine what topic coherence measure works best for Dutch, we conducted a case study. Topics were learned from the proceedings of the Dutch house of parliament and senate from parliamentary years 1999/2000– 2011/2012 3 . Because in our project we were interested in a special form of topic modeling, cross-perspective topic modeling [2], topics were learned from the nouns in the corpus only. We extracted 100 topics from 20594 documents. Manual useful ratings were gathered for the top 10 topic words of these topics. Three independent judges were asked to rate topics on a 3-point Likert scale. A
A Novel Neural Network based Model Predictive Controller for Congestion Prevention in IP Networks

Design of a neural network based model predictive controller for UDP(User Datagram Protocol) flow caused congestion, in IP( Internet protocol) networks is proposed in this paper. The objectives of congestion control are prevention of congestion collapse, maximum network bandwidth utilization, TCP-friendliness and smoothness for streaming media applications. Various approaches for controlling congestion in networks are present in the literature. Many of these are make use of network models, which are already identified. In this paper a neural network utilizing Levenberg-Marquardt learning algorithm for on-line identification of non-linear plant(network) model is implemented and combined with a model predictive optimization technique using back tracking line search routine over a specified time horizon. Simulations were carried out to prove the effectiveness of the designed controller. Significant increase in the network bandwidth utilization is also established.
Customer perception towards banking sector in Nepal

In order to survive and excel in the competitive scenario, organizations have to understand the customers’ requirements. Service quality can be measured with the help of the two important instruments, namely SERVQUAL and SERVPERF. BANKSERV model can be used to measure the service quality of the banking sector. Customers’ perception with regard to various services rendered by the banking industry was taken for this study. Data were collected from 350 customers of the bank located in Kathmandu Valley, Nepal. In order to evaluate the association between the variables used in the model, structural equation modeling (SEM) was used for data analysis. The findings of the research showed that, absolute fit indices fits the sample data and reveals that the proposed model has the acceptable fit, by way of satisfying the recommended values.
Critical Values Robust to P-hacking

P-hacking is prevalent in reality but absent from classical hypothesis testing theory. As a consequence, significant results are much more common than they are supposed to be when the null hypothesis is in fact true. In this paper, we build a model of hypothesis testing with p-hacking. From the model, we construct critical values such that, if the values are used to determine significance, and if scientists' p-hacking behavior adjusts to the new significance standards, significant results occur with the desired frequency. Such robust critical values allow for p-hacking so they are larger than classical critical values. To illustrate the amount of correction that p-hacking might require, we calibrate the model using evidence from the medical sciences. In the calibrated model the robust critical value for any test statistic is the classical critical value for the same test statistic with one fifth of the significance level.
An Accelerated Expectation-Maximization Algorithm for Multi-Reference Alignment

The multi-reference alignment (MRA) problem entails estimating an image from multiple noisy and rotated copies of itself. If the noise level is low, one can reconstruct the image by estimating the missing rotations, aligning the images, and averaging out the noise. While accurate rotation estimation is impossible if the noise level is high, the rotations can still be approximated, and thus can provide indispensable information. In particular, learning the approximation error can be harnessed for efficient image estimation. In this paper, we propose a new computational framework, called Synch-EM, that consists of angular synchronization followed by expectation-maximization (EM). The synchronization step results in a concentrated distribution of rotations; this distribution is learned and then incorporated into the EM as a Bayesian prior. The learned distribution also dramatically reduces the search space, and thus the computational load of the EM iterations. We show by extensive numerical experiments that the proposed framework can significantly accelerate EM for MRA in high noise levels, occasionally by a few orders of magnitude, without degrading the reconstruction quality.
Heat transport of the kagom\'{e} Heisenberg quantum spin liquid candidate YCu$_3$(OH)$_{6.5}$Br$_{2.5}$: localized magnetic excitations and spin gap

The spin-1/2 kagom\'{e} Heisenberg antiferromagnet is generally accepted as one of the most promising two-dimensional models to realize a quantum spin liquid state. Previous experimental efforts were almost exclusively on only one archetypal material, the herbertsmithite ZnCu$_3$(OH)$_6$Cl$_2$, which unfortunately suffers from the notorious orphan spins problem caused by magnetic disorders. Here we turn to YCu$_3$(OH)$_{6.5}$Br$_{2.5}$, recently recognized as another host of a globally undistorted kagom\'{e} Cu$^{2+}$ lattice free from the orphan spins, thus a more feasible system for studying the intrinsic kagom\'{e} quantum spin liquid physics. Our high-resolution low-temperature thermal conductivity measurements yield a vanishing small residual linear term of $\kappa/T$ ($T\rightarrow 0$), and thus clearly rule out itinerant gapless fermionic excitations. Unusual scattering of phonons grows exponentially with temperature, suggesting thermally activated phonon-spin scattering and hence a gapped magnetic excitation, consistent with a $\mathbb{Z}_2$ quantum spin liquid ground state. Additionally, the analysis of magnetic field impact on the thermal conductivity reveals a field closing of the spin gap, while the excitations remain localized.
New Index for Dynamic Stability Assessment in Smart Power Systems Using PMU Data

In this paper, new indexes for evaluating the dynamic stability of smart power systems in different operation conditions are proposed.The proposed indexes do not require any dynamic model of the power system and only usedata obtained from the output signal of the Phasor Measurement Unit (PMU). This data can include voltage signal, current signal, power and speed of the generators. In this paper the voltage signals are applied. For this purpose, initially a key index based on the length of the error vector is proposed.Then three dynamic stability assessment indexes due tospecific statuses ofthefundamental index are introduced. These indexes are investigated in four operation conditions. Two of the indexes proposed need output signal of the PMU and the other index needs dominant poles that are estimated by analyzing Prony. The effectiveness of the proposed dynamic stability index is tested on IEEE 39-bus standard system.
New Versions of Gradient Temporal-Difference Learning

Sutton, Szepesvári and Maei introduced the first gradient temporal-difference (GTD) learning algorithms compatible with both linear function approximation and off-policy training. The goal of this article is 1) to propose some variants of GTDs with extensive comparative analysis and 2) to establish new theoretical analysis frameworks for the GTDs. These variants are based on convex–concave saddle-point interpretations of GTDs, which effectively unify all the GTDs into a single framework, and provide simple stability analysis based on recent results on primal–dual gradient dynamics. Finally, numerical comparative analysis is given to evaluate the new approaches.
Expressive Pattern Matching with Logol. Application to the Modelling of -1 Ribosomal Frameshift events

The current practice of pattern matching tools and the gap that may be observed with the actual modelling needs of people analysing genome structures clearly demonstrates the need for higher level languages to describe and search for these structures in genomic sequences. It appears necessary to offer new tools allowing to build more expressive models of families of biological sequences, on the basis of their content and structure. This article presents Logol, a new application designed to achieve pattern matching in possibly large sequences with realistic biological motifs. Logol consists in both a language for describing patterns, and the associated parser for effectively scanning sequences (RNA, DNA or protein) with such motifs. The language, based on an high level gramatical formalism, allows to express ﬂexible patterns (with misparings and indels) composed of both sequential and structural elements (such as repeats or pseudoknots). A web page on the GenOuest BioInformatics Platform http://www.genouest. org/ gives access to the Logol application. It includes an interface for graphically drawing the motif model and an interface to display the resulting matches within the targetted pattern. Logol is presented through an illustrative application using a quite intricate motif model, which is the detection of -1 ribosomal frameshifting events in messenger RNA sequences.
The Association between the Perceived Cybersickness and Amount of Visual Detail in Virtual Environments

Cybersickness is a condition similar to motion sickness that can affect people who are immersed in a virtual reality. Cybersickness has been studied for multiple decades and a large part of its research base comes from older areas of motion sickness studies, such as simulator sickness studies. Questionnaires have been the main data gathering method in cybersickness studies, although recently opting for more objective measurement methods have been on the rise. The level of visual detail appears to correlate with the perceived cybersickness. In this thesis, a data collection is done to compare two scenes has been done for later analysis. The scenes are otherwise identical, but different in amount of visual detail. The intention is to compare the scenes with each other to see if there is a difference in the cybersickness they cause. The subjects were shown a high-detail scene and a low-detail scene, one subject seeing both scenes. Cybersickness was assessed with questionnaires. Various sensor data were also collected and the point-of-view of the subject in the virtual scene was recorded. Altogether 22 subjects participated in the study. The perceived level of cybersickness was slightly lower in scenes with lower amount of visual detail when compared to the more realistic scene. In particular, the realistic scene appeared to cause slightly more nausea than the simple scene. However, small sample size and the subjective nature of cybersickness lower the overall reliability of the results.
Framework for Evaluating the Severity of Cybervulnerability of a Traffic Cabinet

The increasing connectivity in transportation infrastructure is driving a need for additional security in transportation systems. For security decisions in a budget-constrained environment, the possible effect of a cyberattack must be numerically characterized. The size of an effect depends on the level of access and the vehicular demand on the intersections being controlled. This paper proposes a framework for better understanding of the levels of access and the effect that can be had in scenarios with varying demand. Simulations are performed on a simplistic corridor to provide numerical examples of the possible effects. The paper concludes that the possibility of some levels of cyberthreat may be acceptable in locations where traffic volumes would not be able to create an unmanageable queue. The more intimate levels of access can cause serious safety concerns by modifying the settings of the traffic controller in ways that encourage red-light running and accidents. The proposed framework can be used by transportation professionals and cybersecurity professionals to prioritize the actions to be taken to secure the infrastructure.
THE JOURNEY OF AN EMPOWERED WOMAN: THE LADY Z NARRATIVE

Lady Z was featured as an exceptional woman who achieved the pillars of her goals. Her memoir presented a consistent narrative of her life’s challenges illumined a notable trait of courage and a remarkable strength to have excelled in education without a maternal guidance, surpassed the battle of being a single mom, and was able to balance time to combine career and advanced studies. The agents of Lady Z’s success carved a persona of being independent and strong when her mom left her when she was a child. This event was repeated when her husband also left her and her children. These scenarios catapulted her success stories characterized with an illumined assiduousness to be resilient to life with strong faith in God. To Lady Z, becoming a successful individual necessitated to have possessed the values of being resilient in obtaining double jobs and by being emotionally strong. By being a teacher, Lady Z advocated to use life’s examples in teaching and to become more humanistic in the journey of teaching. By becoming a teacher, Lady Z believed that being successful in life would start with a big dream. The most important piece of advice she yielded was to never lose a sight to educate a child.
Stress Detection of Human Using Heart Rate Variability Analysis Based on Low Cost Camera

— The article presents a non-contact solution to a stress detection. Computer human interfaces must be able to consider human’s emotions. Being able to detect a stressful situation has several applications: Secure and assist Computer -Human Interfaces, telemedicine, driving assistance. This capacity allows to detect the user’s state and improve the interface ‘s performance. We proposed a method based on a stress classification system with a sensor in contact and we compared with different classification methods based on sensors in contact. Our solution is based on a facial analysis obtained by image processing.