9,423 research outputs found

    Customer Segmentation: An application to dental medicine patients

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    Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceCustomer segmentation allows to divide a company’s customers into multiple market segments, enabling the development of customized marketing actions based on each segment’s characteristics. This work describes the application of a customer segmentation approach to the patients of a Portuguese dental company. The approach taken to select the feature subset for the final model was mostly based on the LRFM (length, recency, frequency, and monetary) model, and the monetary variable was split into multiple variables according to the treatment category where the amount was spent. K-Means and Self-organizing maps were used to cluster the company’s patients using these variables, and the results returned by both algorithms are compared. The final solution was obtained with K-Means, and 7 clusters of patients were identified. An overview of the 7 clusters is provided, and possible marketing actions are suggested based on their main characteristics. The results allowed the company to understand how its turnover was distributed across segments, and to develop an initiative to contact the patients belonging to a segment where most of them did not have an appointment in one of the company’s clinics for a long time

    Secure Routing Protocol To Mitigate Attacks By Using Blockchain Technology In Manet

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    MANET is a collection of mobile nodes that communicate through wireless networks as they move from one point to another. MANET is an infrastructure-less network with a changeable topology; as a result, it is very susceptible to attacks. MANET attack prevention represents a serious difficulty. Malicious network nodes are the source of network-based attacks. In a MANET, attacks can take various forms, and each one alters the network's operation in its unique way. In general, attacks can be separated into two categories: those that target the data traffic on a network and those that target the control traffic. This article explains the many sorts of assaults, their impact on MANET, and the MANET-based defence measures that are currently in place. The suggested SRA that employs blockchain technology (SRABC) protects MANET from attacks and authenticates nodes. The secure routing algorithm (SRA) proposed by blockchain technology safeguards control and data flow against threats. This is achieved by generating a Hash Function for every transaction. We will begin by discussing the security of the MANET. This article's second section explores the role of blockchain in MANET security. In the third section, the SRA is described in connection with blockchain. In the fourth phase, PDR and Throughput are utilised to conduct an SRA review using Blockchain employing PDR and Throughput. The results suggest that the proposed technique enhances MANET security while concurrently decreasing delay. The performance of the proposed technique is analysed and compared to the routing protocols Q-AODV and DSR.Comment: https://aircconline.com/ijcnc/V15N2/15223cnc07.pd

    Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse

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    This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses. This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups. In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in users’ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018—6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena

    Short exposure to photo-oxidative damage triggers molecular signals indicative of early retinal degeneration

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    IntroductionAge-related macular degeneration (AMD) is the leading cause of blindness in the developed world, currently affecting over 350 billion people globally. For the most prevalent late-stage form of this disease, atrophic AMD, there are no available prevention strategies or treatments, in part due to inherent difficulties in early-stage diagnosis. Photo-oxidative damage is a well-established model for studying inflammatory and cell death features that occur in late-stage atrophic AMD, however to date has not been investigated as a potential model for studying early features of disease onset. Therefore, in this study we aimed to determine if short exposure to photo-oxidative damage could be used to induce early retinal molecular changes and advance this as a potential model for studying early-stage AMD.MethodsC57BL/6J mice were exposed to 1, 3, 6, 12, or 24h photo-oxidative damage (PD) using 100k lux bright white light. Mice were compared to dim-reared (DR) healthy controls as well as mice which had undergone long periods of photo-oxidative damage (3d and 5d-PD) as known timepoints for inducing late-stage retinal degeneration pathologies. Cell death and retinal inflammation were measured using immunohistochemistry and qRT-PCR. To identify retinal molecular changes, retinal lysates were sent for RNA sequencing, following which bioinformatics analyses including differential expression and pathway analyses were performed. Finally, to investigate modulations in gene regulation as a consequence of degeneration, microRNA (miRNA) expression patterns were quantified using qRT-PCR and visualized using in situ hybridization.ResultsShort exposure to photo-oxidative damage (1-24h-PD) induced early molecular changes in the retina, with progressive downregulation of homeostatic pathways including metabolism, transport and phototransduction observed across this time-course. Inflammatory pathway upregulation was observed from 3h-PD, preceding observable levels of microglia/macrophage activation which was noted from 6h-PD, as well as significant photoreceptor row loss from 24h-PD. Further rapid and dynamic movement of inflammatory regulator miRNA, miR-124-3p and miR-155-5p, was visualized in the retina in response to degeneration.ConclusionThese results support the use of short exposure to photo-oxidative damage as a model of early AMD and suggest that early inflammatory changes in the retina may contribute to pathological features of AMD progression including immune cell activation and photoreceptor cell death. We suggest that early intervention of these inflammatory pathways by targeting miRNA such as miR-124-3p and miR-155-5p or their target genes may prevent progression into late-stage pathology

    Qluster: An easy-to-implement generic workflow for robust clustering of health data

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    The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted population in real life. Nevertheless, contrary to the so-called conventional biostatistical methods where numerous guidelines exist, the standardization of data science approaches in clinical research remains a little discussed subject. This results in a significant variability in the execution of data science projects, whether in terms of algorithms used, reliability and credibility of the designed approach. Taking the path of parsimonious and judicious choice of both algorithms and implementations at each stage, this article proposes Qluster, a practical workflow for performing clustering tasks. Indeed, this workflow makes a compromise between (1) genericity of applications (e.g. usable on small or big data, on continuous, categorical or mixed variables, on database of high-dimensionality or not), (2) ease of implementation (need for few packages, few algorithms, few parameters, ...), and (3) robustness (e.g. use of proven algorithms and robust packages, evaluation of the stability of clusters, management of noise and multicollinearity). This workflow can be easily automated and/or routinely applied on a wide range of clustering projects. It can be useful both for data scientists with little experience in the field to make data clustering easier and more robust, and for more experienced data scientists who are looking for a straightforward and reliable solution to routinely perform preliminary data mining. A synthesis of the literature on data clustering as well as the scientific rationale supporting the proposed workflow is also provided. Finally, a detailed application of the workflow on a concrete use case is provided, along with a practical discussion for data scientists. An implementation on the Dataiku platform is available upon request to the authors

    Examples of works to practice staccato technique in clarinet instrument

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    Klarnetin staccato tekniğini güçlendirme aşamaları eser çalışmalarıyla uygulanmıştır. Staccato geçişlerini hızlandıracak ritim ve nüans çalışmalarına yer verilmiştir. Çalışmanın en önemli amacı sadece staccato çalışması değil parmak-dilin eş zamanlı uyumunun hassasiyeti üzerinde de durulmasıdır. Staccato çalışmalarını daha verimli hale getirmek için eser çalışmasının içinde etüt çalışmasına da yer verilmiştir. Çalışmaların üzerinde titizlikle durulması staccato çalışmasının ilham verici etkisi ile müzikal kimliğe yeni bir boyut kazandırmıştır. Sekiz özgün eser çalışmasının her aşaması anlatılmıştır. Her aşamanın bir sonraki performans ve tekniği güçlendirmesi esas alınmıştır. Bu çalışmada staccato tekniğinin hangi alanlarda kullanıldığı, nasıl sonuçlar elde edildiği bilgisine yer verilmiştir. Notaların parmak ve dil uyumu ile nasıl şekilleneceği ve nasıl bir çalışma disiplini içinde gerçekleşeceği planlanmıştır. Kamış-nota-diyafram-parmak-dil-nüans ve disiplin kavramlarının staccato tekniğinde ayrılmaz bir bütün olduğu saptanmıştır. Araştırmada literatür taraması yapılarak staccato ile ilgili çalışmalar taranmıştır. Tarama sonucunda klarnet tekniğin de kullanılan staccato eser çalışmasının az olduğu tespit edilmiştir. Metot taramasında da etüt çalışmasının daha çok olduğu saptanmıştır. Böylelikle klarnetin staccato tekniğini hızlandırma ve güçlendirme çalışmaları sunulmuştur. Staccato etüt çalışmaları yapılırken, araya eser çalışmasının girmesi beyni rahatlattığı ve istekliliği daha arttırdığı gözlemlenmiştir. Staccato çalışmasını yaparken doğru bir kamış seçimi üzerinde de durulmuştur. Staccato tekniğini doğru çalışmak için doğru bir kamışın dil hızını arttırdığı saptanmıştır. Doğru bir kamış seçimi kamıştan rahat ses çıkmasına bağlıdır. Kamış, dil atma gücünü vermiyorsa daha doğru bir kamış seçiminin yapılması gerekliliği vurgulanmıştır. Staccato çalışmalarında baştan sona bir eseri yorumlamak zor olabilir. Bu açıdan çalışma, verilen müzikal nüanslara uymanın, dil atış performansını rahatlattığını ortaya koymuştur. Gelecek nesillere edinilen bilgi ve birikimlerin aktarılması ve geliştirici olması teşvik edilmiştir. Çıkacak eserlerin nasıl çözüleceği, staccato tekniğinin nasıl üstesinden gelinebileceği anlatılmıştır. Staccato tekniğinin daha kısa sürede çözüme kavuşturulması amaç edinilmiştir. Parmakların yerlerini öğrettiğimiz kadar belleğimize de çalışmaların kaydedilmesi önemlidir. Gösterilen azmin ve sabrın sonucu olarak ortaya çıkan yapıt başarıyı daha da yukarı seviyelere çıkaracaktır

    Document Clustering as an approach to template extraction

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceA great part of customer support is done via the exchange of emails. As the number of emails exchanged daily is constantly increasing, companies need to find approaches to ensure its efficiency. One common strategy is the usage of template emails as an answer. These answers templates are usually found by a human agent through the repetitive usage of the same answer. In this work, we use a clustering approach to find these answer templates. Several clustering algorithms are researched in this work, with a focus on the k-means methodology, as well as other clustering components such as similarity measures and pre-processing steps. As we are dealing with text data, several text representation methods are also compared. Due to the peculiarity of the provided data, we are able to design methodologies to ensure the feasibility of this task and develop strategies to extract the answer templates from the clustering results

    Science and corporeal religion: a feminist materialist reconsideration of gender/sex diversity in religiosity

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    This dissertation develops a feminist materialist interpretation of the role the neuroendocrine system plays in the development of gender/sex differences in religion. Data emerging from psychology, sociology, and cognitive science have continually indicated that women are more religious than men, in various senses of those contested terms, but the factors contributing to these findings are little understood and disciplinary perspectives are often unhelpfully siloed. Previous scholarship has tended to highlight socio-cultural factors while ignoring biological factors or to focus on biological factors while relying on problematic and unsubstantiated gender stereotypes. Addressing gender/sex difference is vital for understanding religion and how we study it. This dissertation interprets this difference by means of a multidisciplinary theoretical and methodological approach. This approach builds upon insights from the cognitive and evolutionary science of religion, affect theory and affective neuroscience, and social neuroendocrinology, and it is rooted in the foundational insights of feminist materialism, including that cultural and micro-sociological forces are inseparable from biological materiality. The dissertation shows how a better way of understanding gender/sex differences in religion emerges through focusing on the co-construction of biological materiality and cultural meanings. This includes deploying a gene-culture co-evolutionary explanation of ultrasociality and an understanding of the biology of performativity to argue that religious behavior and temperaments emerge from the enactment and hormonal underpinnings of six affective adaptive desires: the desires for (1) bonding and attachment, (2) communal mythos, (3) deliverance from suffering, (4) purpose, (5) understanding, and (6) reliable leadership. By hypothesizing the patterns of hormonal release and activation associated with ritualized affects—primarily considering oxytocin, testosterone, vasopressin, estrogen, dopamine, and serotonin—the dissertation theorizes four dimensions of religious temperament: (1) nurturant religiosity, (2) ecstatic religiosity, (3) protective/hierarchical religiosity, and (4) antagonistic religiosity. This dissertation conceptualizes hormones as chemical messengers that enable the diversity emerging from the imbrication of physical materiality and socio-cultural forces. In doing so, it demonstrates how hormonal aspects of gender/sex and culturally constructed aspects of gender/sex are always already intertwined in their influence on religiosity. This theoretical framework sheds light on both the diversity and the noticeable patterns observed in gender/sex differences in religious behaviors and affects. This problematizes the terms of the “women are more religious than men” while putting in place a more adequate framework for interpreting the variety of ways it appears in human lives

    Special Topics in Information Technology

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    This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists
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