Academic literature on the topic 'Raisin – Analyse informatique'

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Journal articles on the topic "Raisin – Analyse informatique"

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Moraes, Claudiney P. De, Giovanna Oliveira Ferreira, Larissa Lais da Silva Montenegro, Luana Lima Leite, and Patrícia Teixeira Morote. "GRIPE AVIÁRIA: CONSCIENTIZANDO A POPULAÇÃO." Revista ft 28, no. 139 (2024): 54–55. http://dx.doi.org/10.69849/revistaft/ar10202410290954.

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Avian influenza outbreaks have already hit several countries and contact between domestic and migratory birds has been the source of many epidemic outbreaks, with high mortality rates in humans and animals. There is great concern about the spread to continents not yet affected, especially via migratory birds. Transmission occurs mainly through direct contact with infected birds, through saliva, feces, respiratory secretions and aerosols. Awareness-raising is therefore essential as a prophylactic measure. Therefore, the methodology of the work developed was a survey to analyze the population's knowledge of the disease. Based on the results, an informative video was produced and published. In this way, by being clear about the forms of transmission, the spread of avian influenza can be prevented and avoided.
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Ferreira, Carla Yasmin Pires, and Juliana Carvalho Piva. "O BULLYING ESCOLAR NA LEGISLAÇÃO BRASILEIRA: UMA ANÁLISE DE UM CRIME SILENCIOSO." Revista ft 29, no. 146 (2025): 42–43. https://doi.org/10.69849/revistaft/ch10202505292042.

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This study aims to analyze Brazilian legislation aimed at combating bullying in schools, highlighting the distribution and nature of laws in Brazilian states and the Federal District. The research, which was of a documentary nature, identified and classified the laws according to their informative, preventive and/or punitive nature. The results demonstrate that there is a significant legislative effort to establish measures aimed at raising awareness and preventing, as well as holding perpetrators and institutions accountable for cases of bullying. It was evident that most laws are preventive in nature, focusing on the training of education professionals and the development of pedagogical actions. It is concluded that, although the legislation represents progress in protecting students, its effectiveness depends on its concrete application in the school environment, the training of professionals and the articulation between school, family and community.
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Souza, Lucas Santos, Camila Freitas Almeida, Guilherme Lopes Yamamoto, et al. "Manifesting carriers of X-linked myotubular myopathy." Neurology Genetics 6, no. 5 (2020): e513. http://dx.doi.org/10.1212/nxg.0000000000000513.

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ObjectiveTo analyze the modulation of the phenotype in manifesting carriers of recessive X-linked myotubular myopathy (XLMTM), searching for possible genetic modifiers.MethodsTwelve Brazilian families with XLMTM were molecularly and clinically evaluated. In 2 families, 4 of 6 and 2 of 5 manifesting female carriers were identified. These females were studied for X chromosome inactivation. In addition, whole-exome sequencing was performed, looking for possible modifier variants. We also determined the penetrance rate among carriers of the mutations responsible for the condition.ResultsMutations in the MTM1 gene were identified in all index patients from the 12 families, being 4 of them novel. In the heterozygotes, X chromosome inactivation was random in 3 of 4 informative manifesting carriers. The disease penetrance rate was estimated to be 30%, compatible with incomplete penetrance. Exome comparative analyses identified variants within a segment of 4.2 Mb on chromosome 19, containing the killer cell immunoglobulin-like receptor cluster of genes that were present in all nonmanifesting carriers and absent in all manifesting carriers. We hypothesized that these killer cell immunoglobulin-like receptor variants may modulate the phenotype, acting as a protective factor in the nonmanifesting carriers.ConclusionsAffected XLMTM female carriers have been described with a surprisingly high frequency for a recessive X-linked disease, raising the question about the pattern of inheritance or the role of modifier factors acting on the disease phenotype. We demonstrated the possible existence of genetic mechanisms and variants accountable for the clinical manifestation in these women, which can become future targets for therapies.
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Vartanov, S. A. "The Economic Theory of Advertising: The Directions of Formation." Administrative Consulting, no. 8 (September 30, 2020): 157–74. http://dx.doi.org/10.22394/1726-1139-2020-8-157-174.

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One of the key tools that are traditionally used in solving media strategizing problems is advertising. The impacts of advertising on the processes taking place in the economy are significant and remarkably diverse, thus raising a big question to the media strategists to systematize and classify both the types of such impacts and the economic theories that study it. This work is devoted to the study of this issue: the most significant approaches to a comprehensive study of advertising at various planning periods (from instant to long-term strategic) are presented. We analyze the informative and persuasive functions of advertisement, compare the influence of its visual and textual forms and discuss key points of cognitive and behavior approaches to understand how advertisement affects the consumers’ demand. We describe basic models of economic equilibrium, which take the advertisement influence on different market structures into account, as well as two-sided models of media markets. It is shown that the less developed field of the economics of advertising is behavior and market influence analysis of the firms whose specialization is creating and distributing media content and advertisement. Due to this, we introduce the way to construct a new class of market models involving three types of economic agents — consumers, media firms and economic goods producers.
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Cui, Saishi, Sina Nassiri, and Issa Zakeri. "Mcadet: A feature selection method for fine-resolution single-cell RNA-seq data based on multiple correspondence analysis and community detection." PLOS Computational Biology 20, no. 10 (2024): e1012560. http://dx.doi.org/10.1371/journal.pcbi.1012560.

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Single-cell RNA sequencing (scRNA-seq) data analysis faces numerous challenges, including high sparsity, a high-dimensional feature space, and biological noise. These challenges hinder downstream analysis, necessitating the use of feature selection methods to identify informative genes, and reduce data dimensionality. However, existing methods for selecting highly variable genes (HVGs) exhibit limited overlap and inconsistent clustering performance across benchmark datasets. Moreover, these methods often struggle to accurately select HVGs from fine-resolution scRNA-seq datasets and minority cell types, which are more difficult to distinguish, raising concerns about the reliability of their results. To overcome these limitations, we propose a novel feature selection framework for scRNA-seq data called Mcadet. Mcadet integrates Multiple Correspondence Analysis (MCA), graph-based community detection, and a novel statistical testing approach. To assess the effectiveness of Mcadet, we conducted extensive evaluations using both simulated and real-world data, employing unbiased metrics for comparison. Our results demonstrate the superior performance of Mcadet in the selection of HVGs in scenarios involving fine-resolution scRNA-seq datasets and datasets containing minority cell populations. Overall, we demonstrate that Mcadet enhances the reliability of selected HVGs, although the impact of HVG selection on various downstream analyses varies and needs to be further investigated.
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Pobel, E. A., L. M. Bengus, and N. V. Dedukh. "MARKERS OF BONE METABOLISM IN LONG BONE’S ADHESION." Osteoporosis and Bone Diseases 15, no. 2 (2012): 25–32. http://dx.doi.org/10.14341/osteo2012225-32.

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This review presents the current evidence about the use of markers of bone metabolism in the prediction of fracture healing, differences in concentrations of blood markers of bone metabolism in patients with normal and delayed consolidation of bone fragments. We analyze the relationship between the fracture site, time-stage features of its healing and urinary macromolecules, reflecting bone metabolism. Increase in bone turnover, which is observed after the fracture, is characterized by activation markers of bone resorption, with a subsequent increase in the concentration of blood markers of bone formation. However, there is a marked variability in data concerning the levels of bone markers in plasma at different stages of fracture healing. We show that in patients with delayed fracture healing there is a significant delay in raising osteocalcin levels. Prognostic features for determining fracture nonunion include low concentrations of N-terminal propeptide of procollagen type I. Determination of markers of bone metabolism in blood can serve as informative criterion for the course of reparative osteogenesis, but one must consider the nature of traumatic injury, time passed from injury, especially the state of bone tissue at the time of injury, age of the patient to identify the early stages of consolidation disturbances.
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Костирко, Лідія Андріївна, та Тетяна Василівна Соломатіна. "ФІНАНСОВИЙ ПОТЕНЦІАЛ КРЕДИТНИХ СПІЛОК У СИСТЕМІ РОЗВИТКУ МАЛИХ ФОРМ АГРОБІЗНЕСУ". TIME DESCRIPTION OF ECONOMIC REFORMS, № 1 (5 травня 2020): 57–64. http://dx.doi.org/10.32620/cher.2020.1.08.

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Formulation of problem. The article is focused on the analysis of trends of development of credit unions and the basis for scientific and practical recommendations regarding increasing the financial potential of credit unions in system of development of small forms of agrarian business. The aim of research is the development of theoretical aspects and practical recommendations regarding increasing the financial potential of credit unions in system of development of small forms of governance in agrarian area. The object of the research is the financial potential of credit unions. Methods, used in research: generalization, comparison, logical and informative, scientific knowledge, induction, analysis. The hypothesis of the research: analytical evaluation of development trends of credit unions for identification of the feasibility of fund-raising for small forms agrarian business. The statement of basic materials. The dynamics of quantity of credit unions, the number of persons included by them, the amount of capital, loan and deposit portfolio, risks of activity is analysed as a whole and in the frames of all -Ukrainian association. The critical estimation of le gal status and prudential regulation is provided, their influence on the disclosure of financial potential of credit unions and their advantages for small forms of agrarian business as representation in regions with developed agricultural production, territorial accessibility, the opportunity of to give modest amouts of credit sums for a long term for household plots and farms is determined. The originality and practical significance of the research is the development of recommendations regarding support for small forms of governance in agrarian area by credit unions. Conclusions and perspectives of further researches. Credit unions (CU) have significant competitive advantages over banks at the level of consumer loans and credit for rural commodity producers. Therefore, free fund-raising of credit unions will play an important role in the development of small forms of governance in agrarian area.
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Kocira, Sławomir. "Concepts and Methods of Mathematic Modelling of Plant Growth and Development. Plant Germination -Part I." Agricultural Engineering 22, no. 3 (2018): 11–20. http://dx.doi.org/10.1515/agriceng-2018-0022.

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AbstractContemporary agricultural engineering searches for “safe” methods of raising crop yields, using a combination of knowledge from a number of sciences. Thus, computer modelling of plant growth and development fits this range, because it has become an area of interdisciplinary research. Presentation of knowledge in the form of mathematical computer models is one of paradigms of agricultural production systems based on the scientific and practical knowledge and information. In the scientific activity concerning agricultural engineering research tasks related to mathematical modelling of agrobiological processes have been carried out for many years. Additionally, the use of modern forecasting techniques in agriculture may bring real financial advantages with regard to the fact that based on crop yield prediction estimation of their cultivation profitability is possible. Dynamic and continuous progress of computer and informative technologies creates new opportunities showing thus growth directions of agricultural engineering. Taking this into consideration, it should be emphasised that mathematical modelling constitutes a support for decision processes which take place in agricultural production. This article discusses mathematical models, where the analysed system is described with the use of mathematical formulas. The objective of the paper was to present the current state of knowledge on mathematical methods in describing and predicting seeds germination. Possibilities of their use and new challenges which occur in the description of seeds germination were presented.
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Aria, Ednanda Belva. "Peran Media Sosial Facebook Dalam Pembentukan Opini Publik Terhadap Perdagangan Satwa Liar Ilegal Di Indonesia." Jurnal Ilmu Sosial dan Ilmu Politik 6, no. 2 (2025): 129–41. https://doi.org/10.56552/jisipol.v6i2.245.

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Abstract Illegal wildlife trade has become an issue that threatens biodiversity and animal welfare in Indonesia. This activity not only harms the environment but also has the potential to disrupt the overall balance of ecosystems. As one of the most widely used social media platforms in Indonesia, Facebook has great potential in shaping public opinion and raising public awareness on various issues, including this one. This study aims to analyze the role of Facebook in influencing public opinion regarding the illegal wildlife trade. The study uses a case study method. Data for this study was collected through observation, content analysis, and interviews with several Facebook users in Indonesia. Data analysis was carried out using a thematic approach. The findings of this study indicate that the role of Facebook in shaping public opinion regarding the illegal wildlife trade in Indonesia has not been effectively carried out. While Facebook posts can present informative visual evidence and facts, audience responses tend to be passive, limited to likes or shares without substantial discussion or comments. Recommendations from this study suggest that there is a need to improve the strategy for disseminating information regarding the wildlife trade in Indonesia, both from society and the government, so that the message about illegal wildlife trade can reach a wider public and encourage more active engagement.
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Isyraf Iskandar, NORISAN KARIM, Fauziah Redzuan, and Rogayah Abdul Majid. "Data Visualization on Number of Cancer deaths Worldwide Analysis." Applied Mathematics and Computational Intelligence (AMCI) 14, no. 2 (2025): 119–34. https://doi.org/10.58915/amci.v14i2.1186.

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Cancer is a highly lethal and challenging disease that has tremendous effects on the death rates of the people across the globe. However, the heterogeneity in cancer types as well as their respective death rates among the regions makes it very difficult to understand the global cancer map. CancerAtlas: The Data Visualization on Cancer Deaths Cases Analysis project aims at raising the awareness about the patterns in cancer death rates worldwide and also regional inequalities. The project uses data analytics to create informative infographics on cancer death in the world, which allows us to reflect this complicated data in an understandable way. Using the CancerAtlas dashboard, users can interactively assess, compare, and analyze the cancer mortality rates in different areas, and different age groups with various types of cancer. Usability testing showed that the dashboard is very user-friendly, and it was so easy to understand the presented information including predictive analysis. This implies that data analytics, data visualization and predictive analysis are very powerful tools for creating public awareness regarding the global cancer trends. Since the CancerAtlas dashboard possesses great potential, it is recommended that future versions of the project include real-time data to deliver live visualizations and forecasts, thereby making the insights obtained from the data more accurate and also relevant. Keywords: Cancer mortality rates, Data visualization, Predictive analysis, Data analytics
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Dissertations / Theses on the topic "Raisin – Analyse informatique"

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Lefévre, Soizic. "Caractérisation de la qualité des raisins par imagerie." Electronic Thesis or Diss., Reims, 2023. http://www.theses.fr/2023REIMS017.

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L’identification des états sanitaires du raisin au moment de la vendange est un enjeu majeur afin de produire des vins de qualité. Pour répondre à cet enjeu, des données sont acquises par spectrométrie, imagerie hyperspectrale et imagerie RGB sur des échantillons de raisin au cours des vendanges.Plusieurs prétraitements adaptés à chaque type de données sont appliqués tels que la normalisation, la réduction, l’extraction de vecteurs de caractéristiques et la segmentation de zones utiles. D’un point de vue imagerie, la reconstitution en fausses couleurs des images hyperspectrales, éloignée de la réalité, ne permet pas d’étiqueter toute la diversité intra-classe. En revanche, la qualité visuelle de l’imagerie RGB favorise l’étiquetage des classes avec précision. A partir de cet étiquetage, des classifieurs tels que les machines à vecteurs de support, les forêts aléatoires, l’estimation du maximum de vraisemblance, la mise en correspondance spectrale, les k-moyennes sont testés et entrainés sur les bases étiquetées. En fonction de la nature des données, le plus performant est appliqué sur les images entières de grappes ou caisses de raisins de plusieurs cépages provenant de différentes parcelles.Les indices de qualité obtenus à partir du traitement des images RGB sont très proches des estimations effectuées par les experts du domaine<br>Identifying the health conditions of the grapes at harvest time is a major issue in order to produce quality wines. To meet this issue, data are acquired by spectrometry, hyperspectral imaging and RGB imaging on grape samples during harvest.Several pre-treatments adapted to each type of data are applied such as normalization, reduction, extraction of characteristic vectors, and segmentation of useful areas. From an imaging point of view, the reconstruction in false colors of hyperspectral images, far from reality, doesn’t allow to label all the intra-class diversity. On the other hand, the visual quality of RGB imaging enables accurate class labelling. From this labelling, classifiers such as support vector machines, random forests, maximum likelihood estimation, spectral mapping, k-means are tested and trained on labelled bases. Depending on the nature of the data, the most effective is applied to whole images of grape clusters or crates of grapes of several grape varieties from different parcels.The quality indices obtained from RGB image processing are very close to the estimates made by experts in the field
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Dahmane, Khouloud. "Analyse d'images par méthode de Deep Learning appliquée au contexte routier en conditions météorologiques dégradées." Thesis, Université Clermont Auvergne‎ (2017-2020), 2020. http://www.theses.fr/2020CLFAC020.

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De nos jours, les systèmes de vision sont de plus en plus utilisés dans le contexte routier. Ils permettent ainsi d'assurer la sécurité et faciliter la mobilité. Ces systèmes de vision sont généralement affectés par la dégradation des conditions météorologiques en présence de brouillard ou de pluie forte, phénomènes limitant la visibilité et réduisant ainsi la qualité des images. Afin d'optimiser les performances des systèmes de vision, il est nécessaire de disposer d'un système de détection fiable de ces conditions météorologiques défavorables.Il existe des capteurs météorologiques dédiés à la mesure physique, mais ils sont coûteux. Ce problème peut être résolu en utilisant les caméras qui sont déjà installées sur les routes. Ces dernières peuvent remplir simultanément deux fonctions : l'acquisition d'images pour les applications de surveillance et la mesure physique des conditions météorologiques au lieu des capteurs dédiés. Suite au grand succès des réseaux de neurones convolutifs (CNN) dans la classification et la reconnaissance d'images, nous avons utilisé une méthode d'apprentissage profond pour étudier le problème de la classification météorologique. L'objectif de notre étude est de chercher dans un premier temps à mettre au point un classifieur du temps, qui permet de discriminer entre temps « normal », brouillard et pluie. Dans un deuxième temps, une fois la classe connue, nous cherchons à développer un modèle de mesure de la distance de visibilité météorologique du brouillard. Rappelons que l'utilisation des CNN exige l'utilisation de bases de données d'apprentissage et de test. Pour cela, deux bases de données ont été utilisées, "Cerema-AWP database" (https://ceremadlcfmds.wixsite.com/cerema-databases), et la base "Cerema-AWH database", en cours d'acquisition depuis 2017 sur le site de la Fageole sur l'autoroute A75. Chaque image des deux bases est labellisée automatiquement grâce aux données météorologiques relevées sur le site permettant de caractériser diverses gammes de pluie et de brouillard. La base Cerema-AWH, qui a été mise en place dans le cadre de nos travaux, contient cinq sous-bases : conditions normales de jour, brouillard fort, brouillard faible, pluie forte et pluie faible. Les intensités de pluie varient de 0 mm/h à 70 mm/h et les visibilités météorologiques de brouillard varient entre 50m et 1800m. Parmi les réseaux de neurones connus et qui ont montré leur performance dans le domaine de la reconnaissance et la classification, nous pouvons citer LeNet, ResNet-152, Inception-v4 et DenseNet-121. Nous avons appliqué ces réseaux dans notre système de classification des conditions météorologiques dégradées. En premier lieu, une étude justificative de l'usage des réseaux de neurones convolutifs est effectuée. Elle étudie la nature de la donnée d'entrée et les hyperparamètres optimaux qu'il faut utiliser pour aboutir aux meilleurs résultats. Ensuite, une analyse des différentes composantes d'un réseau de neurones est menée en construisant une architecture instrumentale de réseau de neurones. La classification des conditions météorologiques avec les réseaux de neurones profonds a atteint un score de 83% pour une classification de cinq classes et 99% pour une classification de trois classes.Ensuite, une analyse sur les données d'entrée et de sortie a été faite permettant d'étudier l'impact du changement de scènes et celui du nombre de données d'entrée et du nombre de classes météorologiques sur le résultat de classification.Enfin, une méthode de transfert de bases de données a été appliquée. Cette méthode permet d'étudier la portabilité du système de classification des conditions météorologiques d'un site à un autre. Un score de classification de 63% a été obtenu en faisant un transfert entre une base publique et la base Cerema-AWH. (...)<br>Nowadays, vision systems are becoming more and more used in the road context. They ensure safety and facilitate mobility. These vision systems are generally affected by the degradation of weather conditions, like heavy fog or strong rain, phenomena limiting the visibility and thus reducing the quality of the images. In order to optimize the performance of the vision systems, it is necessary to have a reliable detection system for these adverse weather conditions.There are meteorological sensors dedicated to physical measurement, but they are expensive. Since cameras are already installed on the road, they can simultaneously perform two functions: image acquisition for surveillance applications and physical measurement of weather conditions instead of dedicated sensors. Following the great success of convolutional neural networks (CNN) in classification and image recognition, we used a deep learning method to study the problem of meteorological classification. The objective of our study is to first seek to develop a classifier of time, which discriminates between "normal" conditions, fog and rain. In a second step, once the class is known, we seek to develop a model for measuring meteorological visibility.The use of CNN requires the use of train and test databases. For this, two databases were used, "Cerema-AWP database" (https://ceremadlcfmds.wixsite.com/cerema-databases), and the "Cerema-AWH database", which has been acquired since 2017 on the Fageole site on the highway A75. Each image of the two bases is labeled automatically thanks to meteorological data collected on the site to characterize various levels of precipitation for rain and fog.The Cerema-AWH base, which was set up as part of our work, contains 5 sub-bases: normal day conditions, heavy fog, light fog, heavy rain and light rain. Rainfall intensities range from 0 mm/h to 70mm/h and fog weather visibilities range from 50m to 1800m. Among the known neural networks that have demonstrated their performance in the field of recognition and classification, we can cite LeNet, ResNet-152, Inception-v4 and DenseNet-121. We have applied these networks in our adverse weather classification system. We start by the study of the use of convolutional neural networks. The nature of the input data and the optimal hyper-parameters that must be used to achieve the best results. An analysis of the different components of a neural network is done by constructing an instrumental neural network architecture. The conclusions drawn from this analysis show that we must use deep neural networks. This type of network is able to classify five meteorological classes of Cerema-AWH base with a classification score of 83% and three meteorological classes with a score of 99%Then, an analysis of the input and output data was made to study the impact of scenes change, the input's data and the meteorological classes number on the classification result.Finally, a database transfer method is developed. We study the portability from one site to another of our adverse weather conditions classification system. A classification score of 63% by making a transfer between a public database and Cerema-AWH database is obtained.After the classification, the second step of our study is to measure the meteorological visibility of the fog. For this, we use a neural network that generates continuous values. Two fog variants were tested: light and heavy fog combined and heavy fog (road fog) only. The evaluation of the result is done using a correlation coefficient R² between the real values and the predicted values. We compare this coefficient with the correlation coefficient between the two sensors used to measure the weather visibility on site. Among the results obtained and more specifically for road fog, the correlation coefficient reaches a value of 0.74 which is close to the physical sensors value (0.76)
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Books on the topic "Raisin – Analyse informatique"

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Heyman, Neil M. World War I. Greenwood Publishing Group, Inc., 1997. http://dx.doi.org/10.5040/9798216039259.

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Designed for secondary school and college student research, this book is a readable analysis and ready-reference guide to the war. An introductory essay presents a lucid overview of the main features of the conflict, incorporating the most recent scholarship. Five essays analyze crucial aspects of the war, from the battlefield to the homefront, and a concluding essay assesses the consequences of the war from a contemporary perspective. Ready-reference features include: a chronology of events; lengthy biographical profiles of twenty-one major figures, stressing their role in the war's origins, conduct, or outcome; the text of fifteen key primary documents such as diaries, memoirs, and newspaper editorials; a glossary of selected terms; and an extensively annotated bibliography of recommended further reading and major documentary and feature films made about the war. The essays are designed to be readable and informative, capturing the tragic character of the war as well as presenting an analysis of its main features. Topics covered include the American role in the war, the collapse of the political systems in Russia and Austria-Hungary, the success of Allied military leaders in meeting the threat of German submarine warfare, and life on the homefront in the United States, Britain, France, and Germany. A concluding essay views the war as a shaping force for the entire twentieth century and its impact on the present day. The book presents the day-to-day course of events as it involved individuals by offering excerpts from diaries and memoirs, while decision-making at the highest level appears in selections from leaders' speeches and memoranda. Shifts in public opinion in the United States are illustrated by excerpts from newspaper editorials. A selection of maps completes the text. By raising issues for discussion about The War to End All Wars and providing reference features, this work is a one-stop resource for students, teachers, and library media specialists.
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Martin-Fiorino, Víctor, Carlos Arturo Ospina Hernández, María Victoria Cadavid-Claussen, et al. Persona y felicidad: aportes desde la educación, la filosofía, la historia, la ética, la política, el derecho y la bioética. Edited by Dalia Jaqueline Santa Cruz-Vera. Editorial Universidad Católica de Colombia, 2021. http://dx.doi.org/10.14718/9789585133679.2021.

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The book includes a collection of articles resulting from research carried out by teachers of the Department of Humanities and whose thematic center is the relationship between people and happiness. Each chapter provides answers from a specific disciplinary field, through a qualitative methodology, the anthropological and ethical problem of achievement of happiness or personal human fulfillment. From education and ethics, the transition from some informative humanities to other performative ones is proposed, which integrate moral formation and values that advocate empathy and solidarity as a human path to happiness. From the anthropological keys of Leonardo Polo, the person can give meaning to their presence in the world, beyond the satisfaction of happiness itself, since human beings has a personal sense capable of manifesting themselves in the hopeful task. Likewise, from the personalistic anthropology, happiness is studied as a life project, moving from the conflict towards spirituality and proposing chose political educational transformations. In the field of historical sciences, the use of the concepts of person and happiness in the Magisterium of John xxiii underlines the perspectives suggested by the Pope and collected by successive pontiffs. From the law, the relationship is analyzed between justice and happiness, applied to the so-called “right to die with dignity”; and from the bioethics, reflections on procreation and happiness are raised based on the current debate on surrogacy.
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Book chapters on the topic "Raisin – Analyse informatique"

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Khamis, Reem. "Coloniality and patterns of scholarly linguistic investigations in Arabic language acquisition studies." In Studies in Arabic Linguistics. John Benjamins Publishing Company, 2025. https://doi.org/10.1075/sal.14.09kha.

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The concept of decoloniality has gained increasing attention, as it involves an ongoing process of identifying and dismantling power structures and knowledge dominations rooted in colonial legacies within the modern world system. This process has been applied to various aspects of knowledge production, including specific fields of study such as linguistics, neuroscience, and cognitive sciences. However, there is a noticeable gap in the literature when it comes to applying decolonial perspectives to the study of Arabic language acquisition. This paper aims to fill that void by reflecting on how coloniality influences personal investigations into language acquisition. The reflection illustrates how coloniality permeates all stages of knowledge production, from the formulation of research questions to data collection, analysis, theoretical frameworks, and interpretation. The key points raised in this reflection underscore the critical need for embracing decoloniality in Arabic linguistic studies. Such an approach can propel us beyond conventional monolingual normative frameworks of inquiry and open up innovative avenues for inquiry. It can transform Arabic acquisition scholarship, moving from prescriptive perspective to informative one that empowers idiolectic inquiry viewed from the internal perspective of the individual and separated from the external perspective of the society. The paper calls upon scholars in Arabic acquisition studies to embark on a journey of self-refection, to critically examine their positionality, and to actively contribute to social justice through their professional work. By adopting decolonial perspectives, scholars can work towards a more inclusive, diverse, and equitable future for the study of Arabic language acquisition.
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Montgomery, Erwin B. "Irreproducibility in Biomedical Science." In Medical Reasoning. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190912925.003.0016.

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Widespread irreproducibility of biomedical research has raised concerns. Journal editors and grant administrators are calling for greater safeguards. The causes go far beyond fraud, lack of transparency, and poor statistical analyses, as commonly thought. The root cause may stem from the same epistemic issues that confront medical reasoning, the necessary use of logical fallacies. However, the use of these fallacies increases the risk of uncertainty and subsequent irreproducibility. Furthermore, many procedures in data analysis actually result in an irretrievable loss of information by the Second Law of Thermodynamics as Applied to Information, thereby increasing the risk for irreproducibility. The second law holds that any irreversible process, such as operating only from the central tendency, as in the mean of a sample, results in a loss of information about the actual sample. The loss of that information makes the study less informative about the management of the individual patient.
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Correa, Kelly de Souza, Roberta Ribeiro Batista Barbosa, and Fernando Rocha Oliveira. "Autism spectrum disorder (ASD): Lines of care and public policies in Brazil." In CHALLENGES AND INNOVATIONS IN EDUCATION: SCIENTIFIC PERSPECTIVES. Seven Editora, 2023. http://dx.doi.org/10.56238/chaandieducasc-009.

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Over the years, public policies aimed at Autism Spectrum Disorder (ASD) have evolved in Brazil. Despite this, we still face challenges, such as expanding access to specialized services and raising societal awareness of ASD. It is important that the diagnosis is made early by a multidisciplinary team, so that appropriate treatment can be started as early as possible. Treatment involves several interventions and should be personalized. In addition, it is essential that public policies ensure access to quality diagnosis and treatment for all. The purpose of this chapter is to analyze the Ministry of Health guidelines for the treatment of Autism Spectrum Disorder and to discuss possible long-term consequences. Challenges related to the diagnosis and treatment of autism in the context of the Unified Health System are also addressed. This is a narrative literature review, which aims to understand the development of Autism Spectrum Disorder (ASD), its Lines of Care and Public Policies in Brazil, through the analysis of the scientific production available in the databases Scientific Electronic Library Online (Scielo), National Library of Medicine (PubMed), books and other informative media. Autism Spectrum Disorder (ASD) in Brazil still faces challenges, such as a lack of trained professionals and unequal resources. To ensure adequate and quality care, it is necessary to invest in training and training of professionals, awareness of families and joint work between government, civil society and families, making it possible to build a more inclusive and welcoming society for people with ASD.
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John P, Pace. "9 The Great Enterprise Today (2006)." In The United Nations Commission on Human Rights. Oxford University Press, 2020. http://dx.doi.org/10.1093/law/9780198863151.003.0010.

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This chapter studies the arrival of the Human Rights Council. The idea of a Human Rights Council was raised in 1976, as the Great Enterprise entered a new phase. The documentation in 1976 on this issue is comprehensive, consisting of no less than five informative reports. In addition, the Commission on Human Rights had before it the analysis of the observations received from some Member States. They included an analysis of the deliberations at the Assembly that had taken place in November of 1975, which covered a range of topics, including ‘the possibility of transforming the Trusteeship Council into a Human Rights Council’. In 2005, the Secretary-General announced his plans to propose the establishment of a Human Rights Council to the Commission. A few months later, the World Summit decided on the establishment of a Human Rights Council. The Human Rights Council inaugurated its work with the adoption of two international human rights instruments, which had reached completion in the Commission on Human Rights: the International Convention for the Protection of All Persons from Enforced Disappearance and the United Nations Declaration on the Rights of Indigenous Peoples. It also extended the mandate of the Working Group formed under the Commission to elaborate an optional protocol to the International Covenant on Economic, Social and Cultural Rights and of the Commission’s Working Group on the Right to Development.
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Wilson, Samuel G. "Enhancement and Identity." In Global Issues and Ethical Considerations in Human Enhancement Technologies. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6010-6.ch014.

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Advances in human enhancement technologies raise the prospect that people's identities may be altered so radically by enhancement that they will be essentially a different person after enhancement. To illustrate, some scholars of enhancement claim that individuals are unlikely to “survive” enhancement, in the sense that they continue to exist as one and the same person. Yet, others claim that enhancement is dehumanizing. Common to these claims is the assumption that enhancement affects a discontinuity between an individual's pre- and post-enhancement selves. Although extant analyses of the relationship between enhancement and identity have yielded many useful insights into the possible effects of human enhancement technologies on identity, progress in our understanding is marred by conceptual imprecision, the use of excessively thin conceptions of identity, and the conflation of distinct senses of identity. With respect to the latter, the conflation of numerical and narrative identity is particularly problematic. However, although these senses of identity are distinct, the fact that they are conflated is nevertheless informative about how people untutored in the metaphysics of identity—that is, the vast majority of people—reason about the effects of enhancement on identity. In this chapter, the authors draw on psychological research into self-continuity and dehumanization, respectively, to offer insights into why numerical and narrative identity are conflated, and they argue that future analyses of the relationship between enhancement and identity must be more deeply grounded in psychological and neuroscientific research than has been evidenced to date.
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Anderson, Malcolm, Monica Den Boer, Peter Cullen, William Gilmore, Charles Raab, and Neil Walker. "The Political Theory of European Police Co-operation." In Policing the European Union. Oxford University PressOxford, 1996. http://dx.doi.org/10.1093/oso/9780198259657.003.0004.

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Abstract In the present chapter, we broaden our perspective m order to address the macro-political context of European police cooperation. Our aim is to examine the nature of the relationship between, on the one hand, new transnational and supranational initiatives in the police sector, and on the other, macro-political trends towards integration within the EU and the more general reconfiguration of international relations. The analysis of the relationship between political integration and law enforcement co-operation within the EU contributes to a wider theoretical debate. It raises the general question of the relationship between the forms of policing and the forms of political life. To what extent, and in what manner, are policing arrangements within any society informed by, and informative of the broader institutions, practices and ideas in terms of which that society constitutes itself as a political entity? When social scientists and social theorists conduct this inquiry, they usually do so in either historical or counter-factual terms. They may engage in retrospective analysis of the manner in which the unfolding forms of political life within different societies have become interwoven with the development of a policing function (Robinson and Skaglion 1987). Alternatively, they may proceed by means of hypothetical discussion, attempting to gain insight into the broader significance of policing institutions by asking what difference it would make to the wider polity if such institutions had not evolved in their present form (Bittner 1971; Cohen 1985; Klockars 1985). Both methods have their short comings.
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Conference papers on the topic "Raisin – Analyse informatique"

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Dev, Samrat, and Bhaskar Mishra. "Enhancing public engagement and awareness: An analysis of internet meme posts usage by Indian police departments on Instagram." In 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1004974.

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Social media has become integral to individuals' everyday routines, with messaging applications and platforms serving as the predominant online destinations globally. These platforms have played a significant role in increasing the prominence of internet memes, which serve as vehicles for disseminating information through the utilization of comedy and sarcasm. In this study, we examine how Instagram posts by Mumbai, Delhi, Assam, Rajasthan, and Uttarakhand police about road safety, cybercrime, women's safety, and consent engage with the public, raise awareness about these issues, and improve police-public relations. We collected 100 static memes from the Instagram pages of the police departments between January 1, 2022, and February 28, 2023, and conducted a synthesis of metadata related to these internet memes to assess their likes and comments as a secondary source of information. In addition, we used exportcomments.com to export comments from posts to.csv files and Azure Machine Learning (AML) web services to assess the sentiments (positive, neutral, or negative) of the comments. As primary data, a questionnaire survey with 90 participants (ages ranging from 23 to 43 years, 34% male and 66% female) was conducted to analyze the potential impact of internet memes on social awareness, their informativeness, and the level of trust associated with the information they convey. Purposive random sampling was employed for the selection of the respondents. A bivariate Pearson's correlation coefficient (r) was calculated to determine the strength and direction of the linear relationship between social awareness, informativeness, and the level of trust in conveyed information. The results showed that the internet memes in the corpus received over 2 million likes and were liked an average of 3369 times. The sentiment analysis of the 692 comments reveals that of them, 90.50% (629) were favorable or positive, 5.61% (39) were neutral, and 3.88% (27) were negative. This shows that people's perceptions of and interactions with the police department on Instagram are generally positive due to the platform's wide reach, high level of involvement in the form of likes, and the dearth of comments expressing dissatisfaction. The bivariate correlation (r (88) =.79, p &lt;.001) between these two factors (social awareness and informativeness) was positive and high. There is a significant association between the potential to alter public awareness and the level of informative substance transmitted by internet memes. The study concludes that the strategic use of internet memes by Indian police departments on Instagram significantly enhances public awareness, engagement, and positive perceptions regarding road safety, cybercrime, women's safety, and consent issues. In addition, Internet memes have the potential to be a beneficial and novel tool for social awareness issues, addressing social and public concerns across social media platforms.
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Andov, Stojan, Violeta Cvetkoska, and Tea Mijac. "Unveiling Global Road Accident Patterns - Insights, Analytics, and Implications for Safer Driving Practices." In Economic and Business Trends Shaping the Future. Ss Cyril and Methodius University, Faculty of Economics-Skopje, 2023. http://dx.doi.org/10.47063/ebtsf.2023.0031.

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Every day, we are confronted with alarming news of serious injuries and fatalities resulting from car accidents. In the past decade, these incidents have been on the rise, posing a significant concern for individuals and societies worldwide. The impact of these accidents is particularly devastating when innocent lives, including children, are affected by the long-lasting consequences. While driver behavior remains a major contributing factor to road accidents, there are also other indirect reasons such as infrastructure issues and weather conditions. Addressing this global problem is of utmost importance to safeguard lives and create a safer driving environment for everyone. Sunkpho and Wipulanusat (2020) utilized Business Intelligence (BI) methods, specifically data visualization and analytics, to analyze accident data and provincial data obtained from the Talend Data Integration tool, loaded into a MySQL database, and visualized using Tableau. Their aim was to provide insights into highway accidents and advise the Thai government on adopting this system for formulating strategy options and contingency plans to improve the accident situation. Nour et al. (2020) employ advanced data analytics methods, specifically predictive modeling techniques, to predict injury severity levels and evaluate their performance using publicly available road accident data from the UK Department of Transport spanning 2005 to 2019. Golhar and Kshirsagar M (2021) propose and implement various strategies using the Map-Reduce framework, combining video surveillance and big data analytics, to address the issues of increasing on-road traffic, road congestion, rule violations, and road accidents, aiming to improve road traffic management and make urban population life more comfortable. Yuksel and Atmaca S. (2021) use accelerometer and gyroscope sensor data and applied various machine learning algorithms, including C4.5 Decision Tree, Random Forest, Artificial Neural Network, Support-Vector Machine, K-Nearest Neighbor, Naive Bayes, and K-Star algorithms, to model and evaluate risky driving behaviors, ultimately developing a highly accurate and cost-effective system capable of recording and identifying risky driving behaviors, with potential applications in usage-based insurance policies to incentivize safe driving practices. Mesquitela et al. (2022) use a data fusion process, incorporating information from various sources such as road accidents, weather conditions, local authority reports, traffic, and fire brigade, to analyze and identify geo-referenced accident hotspots in urban areas using ArcGIS Pro and Kernel Density and Hot Spot Analysis tools, aiming to evaluate the factors influencing accident severity and provide knowledge for local municipalities to improve their infrastructure and quality of life, with the results validated by an expert committee, and the approach being applicable to other cities with similar data availability. Based on our Scopus search on "road accidents" and "analytics," no existing references were found directly aligned with our research idea. This highlights the originality of our paper, which aims to raise awareness about road accidents as a significant global issue and provide a comprehensive understanding of their key contributing factors through the analysis of road accident data from six representative countries across different continents including the UK, USA, Chile, Australia, Japan/UAE, and South Africa/Egypt. Our research sheds light on critical aspects of these incidents, explores trends, identifies influential factors, determines countries with low accident rates and casualties, and evaluates the potential impact of data analysis techniques on enhancing road safety. We will use datasets from the selected representative countries, focusing on road accidents that occurred between 2021 and 2022. By employing various analytical methods, we will explore the data from different angles, including descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, and cognitive analytics. Each method will contribute valuable insights to our analysis and understanding of the problem. We will employ Power BI for descriptive and diagnostic analytics, Python for predictive analytics using multilinear regression, Power BI for visualizing regression results, MaxDea Lite and Microsoft Excel for prescriptive analytics such as Data Envelopment Analysis (DEA) and Linear Programming, and also simulations to aid decision-making. Through our analysis, we will address key questions related to road accidents and their impact. For instance, we will determine whether the number of road accidents decreased or increased from 2021 to 2022 and identify the major contributing factors. Furthermore, we will assess the countries with the lowest accident rates and casualties based on ratios per million inhabitants for both years. By leveraging visualization techniques in Power BI, we will present the findings in an accessible and informative manner, enabling stakeholders to grasp the insights easily. The visualization and analysis will provide a deeper understanding of the trends, underlying factors, and the potential of data analysis techniques, such as DEA and Linear Programming, in addressing road safety. The importance of this research lies in its potential to generate significant impact. By shedding light on road accidents as a pressing global issue, the findings will raise awareness among individuals worldwide. Understanding the data from the six representative countries will enable comparisons, identification of best practices, and the formulation of informed strategies to reduce accidents and casualties. The results will benefit researchers, policymakers, and organizations involved in road safety initiatives. The insights gained will help shape evidence-based decisions, implement targeted interventions, and promote safer driving practices to prevent tragic outcomes caused by road accidents.
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A. Buzzetto-Hollywood, Nicole, Austin J. Hill, and Troy Banks. "Early Findings of a Study Exploring the Social Media, Political and Cultural Awareness, and Civic Activism of Gen Z Students in the Mid-Atlantic United States [Abstract]." In InSITE 2021: Informing Science + IT Education Conferences. Informing Science Institute, 2021. http://dx.doi.org/10.28945/4762.

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Aim/Purpose: This paper provides the results of the preliminary analysis of the findings of an ongoing study that seeks to examine the social media use, cultural and political awareness, civic engagement, issue prioritization, and social activism of Gen Z students enrolled at four different institutional types located in the Mid-Atlantic region of the United States. The aim of this study is to look at the group as a whole as well as compare findings across populations. The institutional types under consideration include a mid-sized majority serving or otherwise referred to as a traditionally white institution (TWI) located in a small coastal city on the Atlantic Ocean, a small Historically Black University (HBCU) located in a rural area, a large community college located in a county that is a mixture of rural and suburban and which sits on the border of Maryland and Pennsylvania, and graduating high school students enrolled in career and technical education (CTE) programs in a large urban area. This exploration is purposed to examine the behaviors and expectations of Gen Z students within a representative American region during a time of tremendous turmoil and civil unrest in the United States. Background: Over 74 million strong, Gen Z makes up almost one-quarter of the U.S. population. They already outnumber any current living generation and are the first true digital natives. Born after 1996 and through 2012, they are known for their short attention spans and heightened ability to multi-task. Raised in the age of the smart phone, they have been tethered to digital devices from a young age with most having the preponderance of their childhood milestones commemorated online. Often called Zoomers, they are more racially and ethnically diverse than any previous generation and are on track to be the most well-educated generation in history. Gen Zers in the United States have been found in the research to be progressive and pro-government and viewing increasing racial and ethnic diversity as positive change. Finally, they are less likely to hold xenophobic beliefs such as the notion of American exceptionalism and superiority that have been popular with by prior generations. The United States has been in a period of social and civil unrest in recent years with concerns over systematic racism, rampant inequalities, political polarization, xenophobia, police violence, sexual assault and harassment, and the growing epidemic of gun violence. Anxieties stirred by the COVID-19 pandemic further compounded these issues resulting in a powder keg explosion occurring throughout the summer of 2020 and leading well into 2021. As a result, the United States has deteriorated significantly in the Civil Unrest Index falling from 91st to 34th. The vitriol, polarization, protests, murders, and shootings have all occurred during Gen Z’s formative years, and the limited research available indicates that it has shaped their values and political views. Methodology: The Mid-Atlantic region is a portion of the United States that exists as the overlap between the northeastern and southeastern portions of the country. It includes the nation’s capital, as well as large urban centers, small cities, suburbs, and rural enclaves. It is one of the most socially, economically, racially, and culturally diverse parts of the United States and is often referred to as the “typically American region.” An electronic survey was administered to students from 2019 through 2021 attending a high school dual enrollment program, a minority serving institution, a majority serving institution, and a community college all located within the larger mid-Atlantic region. The survey included a combination of multiple response, Likert scaled, dichotomous, open ended, and ordinal questions. It was developed in the Survey Monkey system and reviewed by several content and methodological experts in order to examine bias, vagueness, or potential semantic problems. Finally, the survey was pilot tested prior to implementation in order to explore the efficacy of the research methodology. It was then modified accordingly prior to widespread distribution to potential participants. The surveys were administered to students enrolled in classes taught by the authors all of whom are educators. Participation was voluntary, optional, and anonymous. Over 800 individuals completed the survey with just over 700 usable results, after partial completes and the responses of individuals outside of the 18-24 age range were removed. Findings: Participants in this study overwhelmingly were users of social media. In descending order, YouTube, Instagram, Snapchat, Twitter, Facebook, Pinterest, WhatsApp, LinkedIn and Tik Tok were the most popular social media services reported as being used. When volume of use was considered, Instagram, Snapchat, YouTube and Twitter were the most cited with most participants reporting using Instagram and Snapchat multiple times a day. When asked to select which social media service they would use if forced to choose just one, the number one choice was YouTube followed by Instagram and Snapchat. Additionally, more than half of participants responded that they have uploaded a video to a video sharing site such as YouTube or Tik Tok. When asked about their familiarity with different technologies, participants overwhelmingly responded that they are “very familiar” with smart phones, searching the Web, social media, and email. About half the respondents said that they were “very familiar” with common computer applications such as the Microsoft Office Suite or Google Suite with another third saying that they were “somewhat familiar.” When asked about Learning Management Systems (LMS) like Blackboard, Course Compass, Canvas, Edmodo, Moodle, Course Sites, Google Classroom, Mindtap, Schoology, Absorb, D2L, itslearning, Otus, PowerSchool, or WizIQ, only 43% said they were “very familiar” with 31% responding that they were “somewhat familiar.” Finally, about half the students were either “very” or “somewhat” familiar with operating systems such as Windows. A few preferences with respect to technology in the teaching and learning process were explored in the survey. Most students (85%) responded that they want course announcements and reminders sent to their phones, 76% expect their courses to incorporate the use of technology, 71% want their courses to have course websites, and 71% said that they would rather watch a video than read a book chapter. When asked to consider the future, over 81% or respondents reported that technology will play a major role in their future career. Most participants considered themselves “informed” or “well informed” about current events although few considered themselves “very informed” or “well informed” about politics. When asked how they get their news, the most common forum reported for getting news and information about current events and politics was social media with 81% of respondents reporting. Gen Z is known to be an engaged generation and the participants in this study were not an exception. As such, it came as no surprise to discover that, in the past year more than 78% of respondents had educated friends or family about an important social or political issue, about half (48%) had donated to a cause of importance to them, more than a quarter (26%) had participated in a march or rally, and a quarter (26%) had actively boycotted a product or company. Further, about 37% consider themselves to be a social activist with another 41% responding that aren’t sure if they would consider themselves an activist and only 22% saying that they would not consider themselves an activist. When asked what issues were important to them, the most frequently cited were Black Lives Matter (75%), human trafficking (68%), sexual assault/harassment/Me Too (66.49%), gun violence (65.82%), women’s rights (65.15%), climate change (55.4%), immigration reform/deferred action for childhood arrivals (DACA) (48.8%), and LGBTQ+ rights (47.39%). When the schools were compared, there were only minor differences in social media use with the high school students indicating slightly more use of Tik Tok than the other participants. All groups were virtually equal when it came to how informed they perceived themselves about current events and politics. Consensus among groups existed with respect to how they get their news, and the community college and high school students were slightly more likely to have participated in a march, protest, or rally in the last 12 months than the university students. The community college and high school students were also slightly more likely to consider themselves social activists than the participants from either of the universities. When the importance of the issues was considered, significant differences based on institutional type were noted. Black Lives Matter (BLM) was identified as important by the largest portion of students attending the HBCU followed by the community college students and high school students. Less than half of the students attending the TWI considered BLM an important issue. Human trafficking was cited as important by a higher percentage of students attending the HBCU and urban high school than at the suburban and rural community college or the TWI. Sexual assault was considered important by the majority of students at all the schools with the percentage a bit smaller from the majority serving institution. About two thirds of the students at the high school, community college, and HBCU considered gun violence important versus about half the students at the majority serving institution. Women’s rights were reported as being important by more of the high school and HBCU participants than the community college or TWI. Climate change was considered important by about half the students at all schools with a slightly smaller portion reporting out the HBCU. Immigration reform/DACA was reported as important by half the high school, community college, and HBCU participants with only a third of the students from the majority serving institution citing it as an important issue. With respect to LGBTQ rights approximately half of the high school and community college participants cited it as important, 44.53% of the HBCU students, and only about a quarter of the students attending the majority serving institution. Contribution and Conclusion: This paper provides a timely investigation into the mindset of generation Z students living in the United States during a period of heightened civic unrest. This insight is useful to educators who should be informed about the generation of students that is currently populating higher education. The findings of this study are consistent with public opinion polls by Pew Research Center. According to the findings, the Gen Z students participating in this study are heavy users of multiple social media, expect technology to be integrated into teaching and learning, anticipate a future career where technology will play an important role, informed about current and political events, use social media as their main source for getting news and information, and fairly engaged in social activism. When institutional type was compared the students from the university with the more affluent and less diverse population were less likely to find social justice issues important than the other groups. Recommendations for Practitioners: During disruptive and contentious times, it is negligent to think that the abounding issues plaguing society are not important to our students. Gauging the issues of importance and levels of civic engagement provides us crucial information towards understanding the attitudes of students. Further, knowing how our students gain information, their social media usage, as well as how informed they are about current events and political issues can be used to more effectively communicate and educate. Recommendations for Researchers: As social media continues to proliferate daily life and become a vital means of news and information gathering, additional studies such as the one presented here are needed. Additionally, in other countries facing similarly turbulent times, measuring student interest, awareness, and engagement is highly informative. Impact on Society: During a highly contentious period replete with a large volume of civil unrest and compounded by a global pandemic, understanding the behaviors and attitudes of students can help us as higher education faculty be more attuned when it comes to the design and delivery of curriculum. Future Research This presentation presents preliminary findings. Data is still being collected and much more extensive statistical analyses will be performed.
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Reports on the topic "Raisin – Analyse informatique"

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Monetary Policy Report, October 2023. Banco de la República, 2023. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr4-2023.

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Inflation has decreased since April, and it is projected to continue to reduce significantly throughout 2024 as it converges toward 3%. In September 2023, the headline annual inflation rate was 10.99% and completed six consecutive months of declines. Core inflation, excluding food and regulated items, has experienced three consecutive months of reductions and currently stands at 9.5%. The reduction in inflation has been slower than the projected by the Central Bank and market analysts, primarily due to: More persistent price increases in services and regulated baskets, which are affected by indexation mechanisms of past inflation and minimum wage. Increases in some prices of perishable food items. Going forward, monetary policy actions will continue contributing to inflation reduction in 2024 and its convergence toward the 3% target during 2025. Projections for 2024 consider the impact of the El Niño with moderate effects on food and energy prices, the implementation of healthy taxes, and necessary adjustments in fuel prices. Economic activity and employment continue to grow, with a projected GDP growth of 1.2% for 2023. The economic slowdown this year allows economic activity and consumption and investment expenditures to align with the long-term productive capacity of the economy, contributing to inflation reduction. For the third quarter, available economic indicators suggest an annual GDP growth of 0.4%. Despite the low growth rate, economic activity would maintain the high levels achieved in the first half of the year. Employment continues to grow in most economic sectors, and the unemployment rate remains historically low. The economic slowdown has been milder than the projected by the Central Bank, resulting in an upward revision of the 2023 growth rate from 0.9% to 1.2%. For 2024, the economy is expected to maintain a slow growth pace (0.8%), contributing to the inflation convergence to the target. Private consumption will adjust, while investment levels will remain lower than before the pandemic. In 2025, the economy is expected to return to growth rates close to those sustainable in the long-term. These adjustments in the economy are reflected in a reduction of the current account deficit and less vulnerability to external conditions changes. The policy interest rate remains at 13.25%, currently appropriate level to consolidate inflation reduction toward the 3% target and to foster sustainable economic growth. In the September and October meetings of 2023, the Board of Directors, by majority, decided to keep the interest rate unchanged at 13.25%. The current monetary policy stance is driven by persistent high inflation, forecasts and expectations of inflation exceeding the 3% target, and with levels of economic activity close to its productive capacity. The Bank will continue to monitor the economy and its key risks to make decisions that are in the best interest of the country. Some important risk factors to watch in the coming months include: El Niño phenomenon evolution, which may result in additional impacts on inflation. Wage adjustments that will be determined in the coming months. The persistence of higher price increases, particularly, in the services sub-basket. The behavior of global short and long-term interest rates that may affect the exchange rate. The economic slowdown. Reducing inflation brings multiple benefits to the economy: Reducing inflation toward the target supports the preservation of wage purchasing power. Low and stable inflation prevents regressive income and wealth redistributions. In particular, low-income individuals and the unemployed have fewer mechanisms to shield themselves from the eroding impact of inflation on their income and savings. When inflation is low, it becomes more predictable and facilitates the development and continuity of long-term financing markets (such as TES and mortgages), enabling the financing of government, corporate, and household investment projects. Additionally, when inflation is low, real interest rates are lower, making it more affordable to finance these projects. When inflation is low and stable, price movements of goods and services are more informative about the sectors in which it is most valuable to increase production. This leads to a better sectoral allocation of capital and labor and, therefore, to raising the total productivity of the economy.
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