Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effectiveness of Breastfeeding Education: An Integrative Review

Purpose: The objective of this integrative review is to evaluate the effectiveness of breastfeeding education. Methods: This integrative review has been composed of the period between January 2000 and February 2015 using the key words “breastfeeding education, prenatal, postnatal”. After searching through these results, a total of 33 full length randomized controlled, cohort, semi experimental papers in English and Turkish focusing on providing breastfeeding education for the mothers, prenatal and postnatal periods have been chosen for evaluation. Results: According to results of the review, in order to promote breastfeeding, prenatal and postnatal breastfeeding education have been conducted. A significant amount of trials about breastfeeding education contains various methods of breastfeeding in this review. The most prominent methods observed in the trials are phone calls, videos/slides, home visits, brochures/written documents/books, individual support/education, and peer counseling/support. Initiation of breastfeeding, breastfeeding duration, exclusive breastfeeding, breastfeeding rate and knowledge level are the variants that were concentrated on the trials. It is observed that in the trials breastfeeding duration, exclusive breastfeeding and breastfeeding rate levels are the most positively affected variants by education and support. Some interventions were also effective on breastfeeding attitude, satisfaction, and self efficacy in some studies. Conclusions: It is of outmost importance that mothers should be educated and counseled by nurses and midwives about initiating breastfeeding, exclusive breastfeeding and effective continuation of it. Other factors which affect breastfeeding beside education should be determined and appropriate interventions should be applied.
Energy Consumption Prediction Model Based on Radial Basis Function Network

Energy consumption prediction is made by the use of radial basis function(RBF) neural network method,and energy consumption prediction model based on RBF neural network is established.The RBF neural network is trained with the actual data of 1978-1997 as learning sample with a good fitting effect.The RBF neural network is tested with the actual data of 1998-2002 and have a high prediction precision.Via the comparision with Back Propagation network,the results show that the RBF neural network is better than BP neural network in accuracy and speed of training.
Efficient Resource Management for Cloud Computing Environments

Cloud computing has recently gained popularity as a cost-effective model for hosting and delivering services over the Internet. In a cloud computing environment, a cloud provider packages its physical resources in data centers into virtual resources and offers them to service providers using a pay-as-you-go pricing model. Meanwhile, a service provider uses the rented virtual resources to host its services. This large-scale multi-tenant architecture of cloud computing systems raises key challenges regarding how data centers resources should be controlled and managed by both service and cloud providers. This thesis addresses several key challenges pertaining to resource management in cloud environments. From the perspective of service providers, we address the problem of selecting appropriate data centers for service hosting with consideration of resource price, service quality as well as dynamic reconfiguration costs. From the perspective of cloud providers, as it has been reported that workload in real data centers can be typically divided into serverbased applications and MapReduce applications with different performance and scheduling criteria, we provide separate resource management solutions for each type of workloads. For server-based applications, we provide a dynamic capacity provisioning scheme that dynamically adjusts the number of active servers to achieve the best trade-off between energy savings and scheduling delay, while considering heterogeneous resource characteristics of both workload and physical machines. For MapReduce applications, we first analyzed task run-time resource consumption of a large variety of MapReduce jobs and discovered it can vary significantly over-time, depending on the phase the task is currently executing. We then present a novel scheduling algorithm that controls task execution at the level of phases with the aim of improving both job running time and resource utilization. Through detailed simulations and experiments using real cloud clusters, we have found our proposed solutions achieve substantial gain compared to current state-of-art resource management solutions, and therefore have strong implications in the design of real cloud resource management systems in practice.
An Implementation and Evaluation of the Least-effort Approach of Crowd Simulation

Crowd simulation serves as an important tool in architecture, where efficiency and safety could be improved with the knowledge of how large groups of people behave, and computer graphics as well as entertainment industry, where demands of animating large amounts of avatars exist. This project has implemented and evaluated an approach of crowd simulation based on the Principle of Least Effort, a fundamental rule of human behavior. The approach is capable of simulating thousands of agent in real time, and can be parallelized naturally to utilize the power of multiprocessor.The approach has been implemented using C++ and OpenMP. Results show that the approach generates smooth, collision-free, and visually plausible agent trajectories. To evaluate the approach in a quantitative manner, a set of metrics have been defined, and a set of test cases have been selected. By comparing the approach with RVO, a similar approach that does not consider the Principle of Least Effort, the evaluation shows that optimization based on the principle leads to agent trajectories that cost less effort and time. In further case studies, the approach has been proved to be able to generate a number of emergent phenomena verified in real crowd.
SDDP vs. ADP: The Effect of Dimensionality in Multistage Stochastic Optimization for Grid Level Energy Storage

There has been widespread interest in the use of grid-level storage to handle the variability from increasing penetrations of wind and solar energy. This problem setting requires optimizing energy storage and release decisions for anywhere from a half-dozen, to potentially hundreds of storage devices spread around the grid as new technologies evolve. We approach this problem using two competing algorithmic strategies. The first, developed within the stochastic programming literature, is stochastic dual dynamic programming (SDDP) which uses Benders decomposition to create a multidimensional value function approximations, which have been widely used to manage hydro reservoirs. The second approach, which has evolved using the language of approximate dynamic programming, uses separable, piecewise linear value function approximations, a method which has been successfully applied to high-dimensional fleet management problems. This paper brings these two approaches together using a common notational system, and contrasts the algorithmic strategies (which are both a form of approximate dynamic programming) used by each approach. The methods are then subjected to rigorous testing using the context of optimizing grid level storage.
Engaging Science Students with Handheld Technology and Applications by Revisiting the Thayer Method of Teaching and Learning

Organic chemistry instructors integrate handheld technology and applications into course lecture and lab to engage students with tools and techniques students use in the modern world. This technology and applications enable instructors to re-visit the Thayer Method of teaching and learning to create an updated method that works with 21 st century students. The Thayer Method is based on the premise that students are willing and capable of making substantial preparation before coming to class and lab in order to maximize efficiency of student-instructor contact time. During this student preparation phase, we engage students with handheld technology and content applications including smart phone viewable course administrative materials; “flashcards” containing basic organic chemistry nomenclature, molecular structures, and chemical reactions; mini-lectures prepared using the Smart Board Airliner Interactive Tablet for upcoming class periods and laboratory technique videos demonstrating tasks they will perform as part of laboratory experimentation. Coupled with a student friendly course text, these handheld applications enable substantial student preparation before class and lab. The method, in conjunction with handheld technology and applications, has been used with positive results in our organic chemistry courses.
Italian Sociologists’ Approach to Qualitative Interviews

L’approche des sociologues italiens des entretiens qualitatifs : Dans le cadre de la recherche sociale, il n’est pas rare de se trouver face à la lecture d’entretiens transcrits ou à l’écoute d’entretiens enregistrés qui présentent des modalités de conduite extrêmement diverses les unes des autres et qui semblent aller à l’encontre de ce qui est conseillé ou indiqué dans la majeure partie des ouvrages concernant la conduite d’entretiens qualitatifs. Afin de comprendre les raisons de ces différents styles de conduite, nous avons réalisé une enquête auprès de sociologues italiens qui déclarent effectuer leurs recherches à travers des entretiens qualitatifs. Ce travail a pour but principal d’examiner les comportements d’un groupe de chercheurs et d’interviewers envers les interviewés dans le cadre de la recherche qualitative. It is common to come across interviews, both transcribed and recorded, that were conducted according to remarkably different strategies that seem to contrast with the recommendations and indications of a large part of the literature on this subject. To understand the reasons behind these different strategies, I will present the outcomes of a study carried out among Italian sociologists who base their research on qualitative interviews. The aim of my study is to examine the attitude of a group of researchers and interviewers towards the interviewees in the field of qualitative research.
Evaluation of sequence based typing methods (SPA and MSLT) for clonal characterization of staphylococcus aureus

Staphylococcus aureus is a well-recognized human pathogen that exists in clinical and community settings worldwide. It can present a serious health issue, especially for the immunocompromised host . Staphylococcus aureus can cause for both asymptomatically colonizing the human and a wide spectrum of illnesses, ranging from skin and soft tissue infections to life-threatening endocarditis, septicemia and toxic shock syndrome. The emergence of resistance to methicillin shortly after the introduction of the drug into clinical practice in 1960, and the global distribution of methicillin resistant Staphylococcus aureus (MRSA) has become a major concern, especially in the hospitals associated with incidences of higher severity and mortality. The incidence of MRSA has been significant increased and reached more than 30% in southern European countries such as France, Spain and Italy by the mid-1990s. Some epidemic Staphylococcus aureus strains have appeared with high epidemiological potentials, enabling the organism to spread rapidly and widely. Therefore, the detection of outbreaks caused by staphylococci with identification of “successful” clones possessActa Medica Mediterranea, 2016, 32: 1851
L'utilisation de la stéatite dans les grottes des Balzi Rossi (ou grottes de Grimaldi)

La steatite est une pierre tendre, de couleur variable, parfois translucide. On la trouve dans les formations metamorphiques des massifs montagneux et, parfois, sous forme de galets dans le lit des cours d'eau. Par raclage, on peut en tirer de la poudre de talc. Elle a servi, au Paleolithique superieur, a confectionner des pendentifs et des statuettes. Le complexe des grottes des Balzi Rossi, a la frontiere entre l'Italie et la France, trop tot fouille, a fourni un nombre relativement eleve de ces pieces. Leur provenance exacte et leur position stratigraphique sont discutees. On etablit des comparaisons avec d'autres exemplaires de sites italiens et francais. On remarque un affinement progressif des techniques de travail, surtout en ce qui concerne la perforation des pendentifs. Cette matiere semble avoir ete particulierement recherchee, sous forme de galets, pour la fabrication des venus au Gravettien-Epigravettien ancien. A l'extreme fin du Paleolithique, la possibilite d'explorer les massifs montagneux liberes des glaces peut en avoir favorise l'exploitation. L'emploi de la poudre de talc (par exemple dans le travail de la peau) est possible, mais non prouve.
Automatic Classification of Project Documents on the Basis of Text Content

AbstractOrganizing construction project documents based on semantic similarities offers several advantages over traditional metadata criteria, including facilitating document retrieval and enhancing knowledge reuse. In this study, the use of text classifiers for automatically classifying documents according to their corresponding group of semantically related documents is evaluated. Supporting documents of claims were used as representations of document discourses. The evaluation was performed under varying general conditions (such as dimensionality level and weighting method) to assess the effect of such conditions on performance, and varying classifier-specific parameters. The highest performance in terms of classification accuracy was achieved by a Rocchio classifier and a kNN classifier with the application of dimensionality reduction and using the tf-idf weighting method. A combined classifier approach was also evaluated in which the classification outcome is based on a majority vote strategy between.
A Thesis on Sketch-Based Techniques for Mesh Deformation and Editing

The goal of this research is to develop new and more intuitive ways for editing a mesh from a static camera angle. I present two ways to edit a mesh via a simple sketching system. The first method is a gray-scale editor which allows the user to specify a fall off function for the region being deformed. The second method is a profile editor in which the user can re-sketch a mesh’s profile. Lastly, the types of edits possible will be discussed and our results will be presented. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 SEVER INSTITUTE OF TECHNOLOGY MASTER OF SCIENCE DEGREE
The Roles of Awareness, Sanctions, and Ethics in Software Compliance

ABSTRACT Monitoring agencies continue to express concern over the use of unlicensed business software in organizations because of the ethical, legal, and financial implications of noncompliance. We constructed a multiple mediation model based on protection motivation theory in order to examine the threat and coping evaluation processes of employees regarding software license compliance. The responses of 138 organizational employees were used to empirically test the research model. The research model helps explain why compliance awareness influences compliance attitudes and behavior. The empirical findings indicate that compliance attitudes result from both consequence and coping appraisals with ethical beliefs having a stronger influence on compliance attitudes compared to the threat of sanctions. Furthermore, awareness drives the formation of threat and coping beliefs and directly influences attitude. We discuss the theoretical and practical implications of the findings that will enable organizations to meet the compliance challenge.
Content Based Image Retrieval by Online andOffline

With many potential practical applications, content- based image retrieval (CBIR) has attracted substantial attention during the past few years. A variety of relevance feedback (RF) schemes have been developed as a powerful tool to bridge the semantic gap between low-level visual features and high-level semantic concepts, and thus to improve the performance of CBIR systems. Among various RF approaches, support-vector-machine (SVM)-based RF is one of the most popular techniques in CBIR. Despite the success, directly using SVM as an RF scheme has two main drawbacks. First, it treats the positive and negative feedbacks equally, which is not appropriate since the two groups of training feedbacks have distinct properties. Second, as the size of image database increases search and retrieval become slow and it affects the performance of the system. To explore solutions to overcome these two drawbacks, CBIR system is implemented as both offline and online and which make use of the properties of images.
Design of low-density parity-check codes for multi-input multi-output systems

In previous works, density evolution schemes have been used to design an irregular low-density parity-check (LDPC) code for the multi-input multi-output (MIMO) systems. However the code design based on the density evolution can be used only for simple code structure like LDPC codes and repeat-accumulate (RA) codes. Recently simple and accurate irregular LDPC code design method based on the extrinsic information transfer (EXIT) chart was introduced for an AWGN channel. This code design scheme is much flexible, therefore it can be used for any kind of code structure like turbo codes. In this paper we design an irregular LDPC code for a MIMO system using the EXIT chart based scheme. The EXIT charts are used to obtain the optimal edge degree distribution of the irregular LDPC code combined with the MMSE-SIC MIMO detector. This scheme can be generalized for designing the optimal iterative MIMO detector combined with any kind of channel codes including turbo codes.
Hybrid permutation frequency phase modulation

In mobile radio and satellite communications, power and bandwidth efficient modulation schemes are highly desirable, For this purpose, we propose a new modulation technique called hybrid permutation frequency phase modulation (HPM). The performance of HPM has been studied in AWGN and frequency selective Rayleigh fading channels. Coded HPM is proposed for achieving diversity transmission over fading channels.
Hand motion and image stabilization in hand-held devices

The mobile imaging market is a rapidly developing market, and has outgrown the traditional imaging market. This market is dominated by CMOS sensors, with pixels getting small and smaller. As pixel size is reduced, the sensitivity is lowered and must be compensated by longer exposure times. However, in the mobile market, this amount to increased motion blur. We characterize the hand motion with a typical shooting scenario. This data can be used to create an evaluation procedure for image stabilization solutions, and we indeed present one such procedure.
Human Brain Function, Second Edition

This updated second edition provides the state of the art perspective of the theory, practice and application of modern non-invasive imaging methods employed in exploring the structural and functional architecture of the normal and diseased human brain. Like the successful first edition, it is written by members of the Functional Imaging Laboratory - the Wellcome Trust funded London lab that has contributed much to the development of brain imaging methods and their application in the last decade. This book should excite and intrigue anyone interested in the new facts about the brain gained from neuroimaging and also those who wish to participate in this area of brain science. © 2004 Elsevier Inc. All rights reserved.
Evolutionary programming based machine parameters estimation for field oriented control

It is generally aware that real-time parameter estimation of the AC induction machine is very important for the efficient operation of vector-controlled drives. However, most existing methods have not taken into account the four imperfections within the system, i.e. the existence of severe power harmonics due to the PWM inverter drive, the imbalancing of the 3-phase supply from the inverter, the variation of supply frequency under load changing and acceleration/deceleration, and the changes in resistance. In this paper, we have developed a new method of parameter estimation based on real time data sampling of voltages and currents, no matter whether they are sinusoidal or not. The assumption of a synchronous rotating speed of the stator flux is not critical. With the aid of evolutionary programming techniques, the model has been found useful for on-line speed/torque control in most field orientation control schemes as it is much easier to achieve a global minimum during the optimisation process.
Robust speaker adaptation using a piecewise linear acoustic mapping

In a large vocabulary speech recognition system, it is desirable to make use of previously acquired speech data when encountering new speakers. The authors describe an adaptation strategy based on a piecewise linear mapping between the feature space of a new speaker and that of a reference speaker. This speaker-normalizing mapping is used to transform the previously acquired parameters of the reference speaker onto the space of the new speaker. This results in a robust speaker adaptation procedure which allows for a drastic reduction in the amount of training data required from the new speaker. The performance of this method is illustrated on an isolated utterance speech recognition task with a vocabulary of 20000 words. <<ETX>>
La conservation des collections en fluide

La connaissance de l'historique des specimens se trouvant dans une collection en fluide est importante, car elle permet de determiner au mieux les produits chimiques ayant pu etre utilises a l'epoque de sa realisation. On pourra ainsi savoir si les pieces ont ete fixees, ou si elles n'ont ete que plongees dans un conservateur qui n'empechera ni la degradation ni l'eventuelle disparition de la collection. Il sera aussi facile de prendre les dispositions necessaires en matiere de protection individuelle avant toute intervention.
Using token-based semantic vector spaces for corpus-linguistic analyses: From practical applications to tests of theoretical claims

Abstract This paper presents token-based semantic vector spaces as a tool that can be applied in corpus-linguistic analyses such as word sense comparisons, comparisons of synonymous lexical items, and matching of concordance lines with a given text. We demonstrate how token-based semantic vector spaces are created, and we illustrate the kinds of result that can be obtained with this approach. Our main argument is that token-based semantic vector spaces are not only useful for practical corpus-linguistic applications but also for the investigation of theory-driven questions. We illustrate this point with a discussion of the asymmetric priming hypothesis (Jäger and Rosenbach 2008). The asymmetric priming hypothesis, which states that grammaticalizing constructions will be primed by their lexical sources but not vice versa, makes a number of empirically testable predictions. We operationalize and test these predictions, concluding that token-based semantic vector spaces yield conclusions that are relevant for linguistic theory-building.