Miracle-dz/UniFAR-FTUs huggingface dataset:
COMPUTATIONAL COLOR CONSTANCY: TAKING THEORY INTO PRACTICE

The light recorded by a camera is a function of the scene illumination, the reflective characteristics of the objects in the scene, and the camera sensors. The goal of color constancy is to separate the effect of the illumination from that of the reflectances. In this work, this takes the form of mapping images taken under an unknown light into images which are estimates of how the scene would appear under a fixed, known light. The research into color constancy has yielded a number of disparate theoretical results, but testing on image data is rare. The thrust of this work is to move towards a comprehensive algorithm which is applicable to image data. Necessary preparatory steps include measuring the illumination and reflectances expected in real scenes, and determining the camera response function. Next, a number of color constancy algorithms are implemented, with emphasis on the gamut mapping approach introduced by D. Forsyth and recently extended by G. Finlayson. These algorithms all assume that the color of the illumination does not vary across the scene. The results of these algorithms running on a variety of images, as well as on generated data, are presented. In addition, the possibility of using sensor sharpening to improve algorithm performance is investigated. The final part of this work deals with images of scenes where the illumination is not necessarily constant. A recent promising result from Finlayson, Funt, and Barnard demonstrates that if the illumination variation can be identified, it can be used as a powerful constraint. However, in its current form this algorithm requires human input and is limited to using a single such constraint. In this thesis the algorithm is first modified so that it provides conjunctive constraints with the other gamut mapping constraints and utilizes all available constraints due to illumination variation. Then a method to determine the variation in illumination from a properly segmented image is introduced. Finally the comprehensive algorithm is tested on simple images segmented with region growing. The results are very encouraging.
Consensus-based distributed scheduling for cooperative operation of distributed energy resources and storage devices in smart grids

Optimal dispatch of storage devices is crucial for the economic operation of smart grids with distributed energy resources. Through appropriate scheduling, storage devices can store the energy when the renewable production is high or electricity price is low, and support the demand when electricity is expensive. Conventionally, this scheduling requires a control centre to gather information from the entire system and find the optimal schedule in the required horizon for the controllable devices. This study proposes a fully distributed scheduling methodology based on discrete-time optimal control, primal-dual gradient descent, and consensus networks. In the proposed approach, the requirement for the control centre is eliminated and the optimal schedule for all the devices is found solely through iterative coordination of each device with its neighbours. The application of the algorithm is demonstrated in a 5-bus system and its convergence to the global optimum is validated through Monte Carlo simulations. Further, it is shown that the algorithm is robust against communication link failures provided that the communications topology remains connected or reconnects after being disconnected.
Infestazione da Cysticercus tenuicollis in un allevamento di capre

An outbreak of acute cysticercosis occurred in six female goats 2-4 years old and three 50 days old kids from a goat farm in northern Italy. Goats were usually recovered in stable with an outdoor paddock. Post-mortem examination showed a massive infection of Taenia hydatigena larvae in the liver, lungs and on the peritoneum. All recovered Cysticercus tenuicollis were at immature stage.
Analysis of Correlated Data with Measurement Error in Responses or Covariates

Correlated data frequently arise from epidemiological studies, especially familial and longitudinal studies. Longitudinal design has been used by researchers to investigate the changes of certain characteristics over time at the individual level as well as how potential factors influence the changes. Familial studies are often designed to investigate the dependence of health conditions among family members. Various models have been developed for this type of multivariate data, and a wide variety of estimation techniques have been proposed. However, data collected from observational studies are often far from perfect, as measurement error may arise from different sources such as defective measuring systems, diagnostic tests without gold references, and self-reports. Under such scenarios only rough surrogate variables are measured. Measurement error in covariates in various regression models has been discussed extensively in the literature. It is well known that naive approaches ignoring covariate error often lead to inconsistent estimators for model parameters. In this thesis, we develop inferential procedures for analyzing correlated data with response measurement error. We consider three scenarios: (i) likelihood-based inferences for generalized linear mixed models when the continuous response is subject to nonlinear measurement errors; (ii) estimating equations methods for binary responses with misclassifications; and (iii) estimating equations methods for ordinal responses when the response variable and categorical/ordinal covariates are subject to misclassifications. The first problem arises when the continuous response variable is difficult to measure. When the true response is defined as the long-term average of measurements, a single measurement is considered as an error-contaminated surrogate. We focus on generalized linear mixed models with nonlinear response error and study the induced bias in naive estimates. We propose likelihood-based methods that can yield consistent and efficient estimators for both fixed-effects and variance parameters. Results of simulation studies and analysis of a data set from the Framingham Heart Study are presented. Marginal models have been widely used for correlated binary, categorical, and ordinal data. The regression parameters characterize the marginal mean of a single
Etude sérologique et bactériologique des mycoplasmoses aviaires dans la région du Cap Bon en Tunisie

Les mycoplasmoses aviaires à Mycoplasma gallisepticum et Mycoplasma synoviae sont responsables de troubles respiratoires et articulaires chez la poule, la dinde et chez d’autres espèces aviaires (26, 27). Ces infections engendrent des conséquences économiques importantes dans tous les secteurs de production en aviculture : retard de croissance pour la filière chair et baisse de production d’œufs pour les pondeuses et reproductrices (14). L’antibiothérapie est coûteuse et les molécules actives sur les mycoplasmes sont peu nombreuses (8). A la connaissance des auteurs, aucune étude sur la mycoplasmose clinique en Tunisie n’a été publiée. Les animaux prélevés au cours de cette enquête étaient d’apparence saine. Cette étude a concerné tous les secteurs de production avicole rencontrés au Cap Bon, région à forte concentration aviaire. Elle a porté sur la recherche des anticorps anti-Mycoplasma par la technique de l’agglutination rapide sur lame (18) et ELISA (2), ainsi que sur l’isolement de Mycoplasma gallisepticum et Mycoplasma synoviae sur des milieux de culture spécifiques (5, 10). ■ MATERIEL ET METHODES
Análise físico-química de méis de abelhas africanizada e nativa

O estudo relata as análises comparativas realizadas entre a composição físico-química de amostras de mel de abelhas africanizadas (Apis mellifera L.) e amostras de mel de abelhas sem ferrão (Scaptotrigona bipunctata H.). As amostras de mel de S. bipunctata foram colhidas em Mauriti-CE e as de A. mellifera foram coletadas em Limoeiro do Norte-CE. Os parâmetros analisados foram: hidroximetilfurfural, sólidos insolúveis em água, açúcares redutores, sacarose aparente, cinzas, acidez livre, umidade, Brix e pH. Os resultados foram submetidos à análise de variância (ANOVA) e a comparação de médias foi feita pelo teste de Tukey em nível de 5% de probabilidade. As amostras analisadas apresentaram diferença significativa em alguns parâmetros avaliados, destacando-se a umidade, açúcares redutores e hidroximetilfurfural. O pH foi o único parâmetro que não apresentou diferença estatisticamente significativa. Este estudo ressalta a necessidade de efetuar a implementação de uma legislação específica que trate da qualidade dos méis de abelhas nativas, uma vez que diferenças significativas foram verificadas em alguns parâmetros físico-químicos entre as amostras analisadas.
Occlusion-adaptive fusion for gait-based motion recognition

This paper presents a new architecture for motion- and video-based event recognition using the fusion of multiple hidden Markov models (HMw with a Bayesian belief network. We begin with a fifteen para- meter structural model of the human body, where unique parameter groups and extracted gait variables define individual nodes of the network. Each node is character- ized by a conditional probability mass function (PMF) in addition to evidence regarding its current state given a set of observations. The evidence for each state is virtual and derived from the conditional ou@ut probabilities of two HMM; one represents a fundamental activity while the other defines a tracking failure event. This novel inte- gration provides a means of recognizing a variety of activities in the presence of noise, occlusion, ambiguity, and entirely missing observations. We demonstrate the effectiveness of our approach on numerous multi-view video sequences of complex human motion.
The Relationship between Text Message Volume and Formal Writing Performance among Upper Level High School Students and College Freshmen.

iii CHAPTER 1: INTRODUCTION 1 Background 1 Problem Statement 5 Purpose Statement 6 Significance of the Study 6 Research Questions 9 Hypotheses 9 Identification of Variables 10 Assumptions and Limitations 12 Research Plan 16 CHAPTER 2: LITERATURE REVIEW 18 Introduction 18 Theoretical Framework 20 Review of the Literature 21 Summary 56 CHAPER 3: METHODOLOGY 57 Introduction 57 Participants 58 Setting 61 Instrumentation 65 Validity 68 Procedures 69
Influência da adubação orgânica e mineral no cultivo de manjericão cv. Genovese

Sweet basil is a plant used for culinary, aromatics, and medical purpose. Despite its importance, scientific publications on sweet basil nutritional requirements for commercial proposes in the Northeast of Brazil are scarce. Therefore, this research aimed to evaluate the effect of organic and mineral fertilization, as well as harvest times on the biomass production and essential oil content of sweet basil (Ocimum basilicum L.) cv. Genovese. The essays were carried out in the Rural Campus of “Universidade Federal de Sergipe” (UFS), under field conditions. The experimental design was random blocks, in a factorial system 5x3. Treatments comprised five types of fertilizers (Hortosafraâ fertilizer, chicken manure, chicken manure plus Hortosafraâ fertilizer, bovine manure, bovine manure plus Hortosafraâ fertilizer) and three harvest hours (08:00AM, Noon, and 4:00PM), with three replicants, Aerial dry matter production was significantly superior for plants fertilized with Hortosafraâ fertilizer plus chicken manure as compared to those plants fertilized with cow manure alone. Harvest time did not significantly affect plant essential oil content and yield of sweet basil cv. Genovese.
An analytic model and optimal clustering for multiple-bus multiprocessor systems

Analytic results are presented for the bandwidth of multiple-bus interconnection networks with two types of arbiter. These analytic results are in close agreement with previously published simulation data. An optimal clustering scheme is proposed and verified by the analytic results, which show that the scheme characterizes the highest memory bandwidth in current partial-bus interconnection networks. <<ETX>>
Comparative reactivity of serum samples from Argentinean HIV-infected patients with V3 peptides from subtype B or BF

To analyze humoral cross-reactivity to V3 peptides from subtype B and BF recombinant forms, plasma samples from 50 HIV-1-infected patients were characterized by sequencing fragments of the env and pol genes. An in-house EIA was performed using peptides corresponding to the 15 central amino acids of the V3 loop of gp120 from subtypes B (MN, SF2) and F1 and a con- sensus peptide from Argentinean BF recombinants. No differences were found with respect to the infecting sub- type, but significant differences were found among the peptides. Reactivity was higher against the MN and BF peptides in both groups infected with subtype B (n = 28) and BF (n = 22) recombinants than against subtype F1 and SF2 peptides.
Immunological Aspects of Varicocele

Varicocele is the most common cause of infertility in men. The mechanism by which varicocele cause the variable effect on male infertility and is still unknown. Varicocele is found in 35 to 81 % of infertile men, and is one treatable form of male infertility. Although many advances have occurred in the treatment of varicocele, it still represents an important and challenging aspect of basic research (male reproductive physiology and endocrinology, pathophysiology, and pharmacology of reproduction and fertility) and medical practice for urologists, pediatric surgeons, and general physicians, to date. This review provides an overview of the epidemiology, Clinical classification and Immunological aspects of varicocele and discusses the indications for, and interpretation of Immunological aspects of varicocele.
Susceptibility of five landscape pines to pitch canker disease, caused by Fusarium subglutinans f.sp. pini

Pitch canker, caused by Fusarium subglutinans f.sp. pini, causes branch dieback and stem cankers in many species of pine. Monterey pine (Pinus radiata D. Don), one of the most widely planted pines in the world, is extremely susceptible to pitch canker, Four other pine species, which might serve as alternatives to Monterey pine in landscape settings, were found to be relatively resistant, based on the size of lesions resulting from branch inoculations under greenhouse conditions. Of these species, Japanese black pine (P. thunbergiana Franco) was the most resistant, followed by Canary Island pine (P. canariensis Sweet ex K.Spreng), Italian stone pine (P.pinea L.), and Aleppo pine (P. halepensis Mill.). Consistent with these findings, a field survey conducted in Alameda County, Calif. , revealed Monterey pine to have the highest incidence of infection, with significantly lower levels in Aleppo, Canary Island, and Italian stone pines. Japanese black pine was not observed in the survey area.
Intrusion Detection in Control Systems using Sequence Characteristics

Intrusion detection is considered effective in control systems. Sequences of the control application behavior observed in the communication, such as the order of the control device to be controlled, are important in control systems. However, most intrusion detection systems do not effectively reflect sequences in the application layer into the detection rules. In our previous work, we considered utilizing sequences for intrusion detection in control systems, and demonstrated the usefulness of sequences for intrusion detection. However, manually writing the detection rules for a large system can be difficult, so using machine learning methods becomes feasible. Also, in the case of control systems, there have been very few observed cyber attacks, so we have very little knowledge of the attack data that should be used to train the intrusion detection system. In this paper, we use an approach that combines CRF (Conditional Random Field) considering the sequence of the system, thus able to reflect the characteristics of control system sequences into the intrusion detection system, and also does not need the knowledge of attack data to construct the detection rules. We use CRF to construct the intrusion detection model, and also retain the information needed for the communication sequences observed in the control system. We only use the legitimate communication data for the learning process. We used the DARPA intrusion detection evaluation data set to evaluate the system. Table 1 shows the results of the experiments. We also compared the results with previous work on rule based sequences, which constructed the intrusion detection rule sets manually. As the DARPA set does not take control systems into account, we also applied the method to intrusion detection in a model control system network, shown in Figure 1. The control system slave server in the controlled station sends state information of the field devices to the control system master server in the control center. The operator console in the control center can see the state information, and can send control commands to the field devices through the control system server. Security measures such as encryption, a firewall and other access controls are in place. The intrusion detection system is placed in the control center where most of the communication in the system can be monitored. For the assessment, we used control system specific attack patterns. Table 2 shows the results of the experiments. The values used in for evaluation are precision, recall, and F-measure, as shown in equations (1-3).
Young Learners’ Perceptions of Learning English Using Language Games in a Non - Formal Context

In Malaysian schools where English is taught as a second language, the need to maximize learners’ exposure to the language outside the classroom is vital. Learning is greatly enhanced, especially among young learners through exposure to English media and language learning activities. However, learners in rural primary schools have very limited exposure to English media and hardly ever use English outside the classroom despite constant encouragement from teachers. They also refrain from participating in English class activities because of a lack of motivation and self-confidence. This paper reports on a possible initiative that may address this need of young rural learners. Forty BA English Language Studies 3rd year undergraduates enrolled in a course that required them to create language games as their final class project. A rural school was selected to execute the pilot project in an informal classroom setting. Acting as facilitators to 112 students all aged 9 years, these undergraduates engaged the pupils in language games that they had created, taking into account the learners’ age, English proficiency and interests. Pupils were observed to become less inhibited in the company of these young facilitators in a non-threatening, informal environment. The project offered opportunities for the student facilitators and their young learners to interact. At the end of the session, the learners were asked to respond to a self-report questionnaire to provide feedback about their perception of the games and the facilitators involved. The encouraging results are good reason for continuing such engagements between undergraduates and pupils. DOI: 10.5901/mjss.2015. v6n6s5p375
Analysis of the statistical time-access fairness index of one-bit feedback fair scheduler

Recently various schedulers exploiting multiuser diversity in wireless networks have been proposed and studied. Although the utilization of multiuser diversity can increase the information theoretic capacity, there exists a tradeoff between the capacity and fairness. Among schedulers exploiting multiuser diversity, the one-bit feedback fair scheduler is considered as an attractive choice for the reduction of feedback overheads and the ease of implementation. In this paper, we study the short term fairness of the one-bit feedback fair scheduler. Since the short term fairness has a strong impact on the quality-of-service of each mobile station, it is important to examine the short term fairness properties of the scheduler. As a short term fairness index, we consider the statistical time-access fairness index (STAFI). We then develop two numerical methods to estimate the STAFI of the scheduler. The first method calculates the exact value of the STAFI by using the inverse discrete FFT method. The second method estimates the asymptotic decay rate of the STAFI by using the theory of large deviations. Numerical results show that the threshold value of the one-bit feedback fair scheduler greatly affects its short term fairness properties.
TEACHING BAYESIAN STATISTICS TO UNDERGRADUATES: WHO, WHAT, WHERE, WHEN, WHY, AND HOW ®

Approximately 50% of total statistics degrees awarded in the USA during 1995 were at Masters level, and only about 33% at Bachelors level, (Iglewicz, 1998). Furthermore, from 1981 to 1995 the rate of increase in Bachelor degrees with statistics as a major (18%) was substantially less than that for Masters degrees (58%) and Doctoral degrees (60%) in statistics. Clearly statistics as a career option has low visibility to undergraduates. Yet, very large proportions of undergraduates are required to take a service course in statistics. We need to enthuse the best students in these service courses into taking further statistics courses. We aren’t doing that now. This should not surprise us. As professional statisticians, we know Bayes methods have great theoretical advantages, and that these advantages can now be realized in practice with the advent of Markov chain Monte Carlo methods. I suggest that introducing Bayesian methods may be the key to revitalizing our undergraduate programmes in statistics. My answers to the journalistic questions on the place of Bayesian statistics posed in the title follow (but in a different order).
Uréia para vacas leiteiras no pós-parto: desempenhos produtivo e reprodutivo

Fifteen crossbred cows (Holstein-Zebu) from EPAMIG-Leopoldina Experimental Farm with an average weight of 511.8 kg were allocated into an experiment in a complete randommized design, in four treatments, with four animals in the treatments 1, 2, and 4 and three in the treatment 3. The treatments were cosntituted of diets with corn silage and concentrate (60:40) and were fed individually and ad libitum and their contents in percentage of urea were: T1=0.0; T2= 0.7; T3= 1.4 and T4=2.1 corresponding to the 2.08; 4.01; 5.76 and 8.07% of crude protein in the form of non-protein nitrogen (NNP), respectively. The average dry matter intake (DMI) expressed in kg/day and in the percentage of body weight were: 16.04; 16.49; 11.64; 11.93 and 3.29; 3.09; 2.47 and 2.35, respectively. The milk production for 3.5% of fat were: 21.18; 24.92; 20.63 and 18.83 kg/day for the NNP concentrations of 2.08; 4.01; 5.76 and 8.07, respectively and decreased with the increase of NNP concentrations in the rations. The mean plasma concentrations of urea and N-urea were: 46.33 and 21.59 mg/dL, and were not affected by the concentrations of NNP in the diets. The number of follicular waves per cycle and the emergency of the first and second follicular waves and its diameter were not affected by the concentrations of NNP in the diets. The first estrus and ovulation occurred on days 55±23 and 81±36, respectively and were not affected by the NNP concentrations of the diets.