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Rozprawy doktorskie na temat „Data-driven techniques”

Autor: Grafiati

Data publikacji: 30 listopada 2024

Data aktualizacji: 31 lipca 2025

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1

Mousas, Christos. "Data-driven techniques for animating virtual characters." Thesis, University of Sussex, 2015. http://sro.sussex.ac.uk/id/eprint/52967/.

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One of the key goals of current research in data-driven computer animation is the synthesis of new motion sequences from existing motion data. This thesis presents three novel techniques for synthesising the motion of a virtual character from existing motion data and develops a framework of solutions to key character animation problems. The first motion synthesis technique presented is based on the character's locomotion composition process. This technique examines the ability of synthesising a variety of character's locomotion behaviours while easily specified constraints (footprints) are pla

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Battle, Leilani Marie. "Behavior-driven optimization techniques for scalable data exploration." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111853.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 153-162).<br>Interactive visualizations are a popular medium used by scientists to explore, analyze and generally make sense of their data. However, with the overwhelming amounts of data that scientists collect from various i

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Massey, Tammara. "Data driven and optimization techniques for mobile health systems." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1930907801&sid=4&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Nordahl, Christian. "Data-Driven Techniques for Modeling and Analysis of User Behavior." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18667.

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Our society is becoming more digitalized for each day. Now, we are able to gather data from individual users with higher resolution than ever. With the increased amount of data on an individual user level, we can analyze their behavior. This is of interest in many different domains, for example service providers wanting to improve their service for their customers. If they know how their service is used, they have more insight in how they can improve. But, it also imposes additional difficulties. When we reach the individual user, the irregularities in the regular behavior makes it harder to m

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Ogweno, Austin Juma. "Power efficient, event driven data acquisition and processing using asynchronous techniques." Thesis, University of Newcastle upon Tyne, 2018. http://hdl.handle.net/10443/4121.

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Data acquisition systems used in remote environmental monitoring equipment and biological sensor nodes rely on limited energy supply soured from either energy harvesters or battery to perform their functions. Among the building blocks of these systems are power hungry Analogue to Digital Converters and Digital Signal Processors which acquire and process samples at predetermined rates regardless of the monitored signal's behavior. In this work we investigate power efficient event driven data acquisition and processing techniques by implementing an asynchronous ADC and an event driven power gate

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Essaidi, Moez. "Model-Driven Data Warehouse and its Automation Using Machine Learning Techniques." Paris 13, 2013. http://scbd-sto.univ-paris13.fr/secure/edgalilee_th_2013_essaidi.pdf.

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L'objectif de ce travail de thèse est de proposer une approche permettant l'automatisation complète du processus de transformation de modèles pour le développement d'entrepôts de données. L'idée principale est de réduire au mieux l'intervention des experts humains en utilisant les traces de transformations réalisées sur des projets similaires. L'objectif est d'utiliser des techniques d'apprentissage supervisées pour traiter les définitions de concepts avec le même niveau d'expression que les données manipulées. La nature des données manipulées nous a conduits à choisir les langages relationnel

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Stender, Merten [Verfasser]. "Data-driven techniques for the nonlinear dynamics of mechanical structures / Merten Stender." Hamburg : Universitätsbibliothek der Technischen Universität Hamburg-Harburg, 2020. http://d-nb.info/1221669583/34.

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Godwin, Jamie Leigh. "Exploiting robust multivariate statistics and data driven techniques for prognosis and health management." Thesis, Durham University, 2015. http://etheses.dur.ac.uk/11157/.

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This thesis explores state of the art robust multivariate statistical methods and data driven techniques to holistically perform prognostics and health management (PHM). This provides a means to enable the early detection, diagnosis and prognosis of future asset failures. In this thesis, the developed PHM methodology is applied to wind turbine drive train components, specifically focussed on planetary gearbox bearings and gears. A novel methodology for the identification of relevant time-domain statistical features based upon robust statistical process control charts is presented for high freq

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Fields, Evan(Evan Jerome). "Demand uncensored : car-sharing mobility services using data-driven and simulation-based techniques." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121825.

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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 141-145).<br>In the design and operation of urban mobility systems, it is often desirable to understand patterns in traveler demand. However, demand is typically unobserved and must be estimated from available data. To address this disconnect, we begin by proposing a method for recovering an unknown probability distribution given a censored or truncated sample from that distribution. The propos

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Reinoso, Nicholas L. "Forecasting Harmful Algal Blooms for Western Lake Erie using Data Driven Machine Learning Techniques." Cleveland State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=csu1494343783463819.

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Farouq, Shiraz. "Towards large-scale monitoring of operationally diverse thermal energy systems with data-driven techniques." Licentiate thesis, Högskolan i Halmstad, CAISR Centrum för tillämpade intelligenta system (IS-lab), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-40964.

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The core of many typical large-scale industrial infrastructure consists of hundreds or thousands of systems that are similar in their basic design and purpose. For instance, District Heating (DH) utilities rely on a large network of substations to deliver heat to their customers. Similarly, a factory may require a large fleet of specialized robots for manufacturing a certain product. Monitoring these systems is important for maintaining the overall efficiency of industrial operations by detecting various problems due to faults and misconfiguration. However, this can be challenging since a well

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Irastorza, valera Luis. "Learning Techniques for Optimization in Engineering : Data-Driven Tools for Mechanical and Biomedical Settings." Electronic Thesis or Diss., Paris, ENSAM, 2025. http://www.theses.fr/2025ENAME020.

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La présente thèse de doctorat englobe une série de casuistiques dans divers domaines de l’ingénierie et de la médecine dont les points communs sont leur complexité conceptuelle et numérique. Cela compromet à son tour la disponibilité et la fiabilité des données expérimentales qui avalisent leurs modèles constitutifs correspondants, si existants. Souvent, ces modèles basés sur des expressions analytiques souffrent d’une complexité inabordable pour l'ordinateur ("malédiction de la dimensionnalité") et/ou sont alourdis par des biais induits dans leur définition (e.g. variables internes non observ

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SELICATI, VALERIA. "Innovative thermodynamic hybrid model-based and data-driven techniques for real time manufacturing sustainability assessment." Doctoral thesis, Università degli studi della Basilicata, 2022. http://hdl.handle.net/11563/157566.

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This doctoral thesis is the result of the supervision and collaboration of the University of Basilicata, the Polytechnic of Bari, and the enterprise Master Italy s.r.l. The main research lines explored and discussed in the thesis are: sustainability in general and, more specifically, manufacturing sustainability, the Industry 4.0 paradigm linked to smart (green) manufacturing, model-based assessment techniques of manufacturing processes, and data-driven analysis methodologies. These seemingly unrelated topics are handled throughout the thesis in such a way that it reveal how strongly interwov

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Spreyer, Kathrin. "Does it have to be trees? : Data-driven dependency parsing with incomplete and noisy training data." Phd thesis, Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2012/5749/.

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We present a novel approach to training data-driven dependency parsers on incomplete annotations. Our parsers are simple modifications of two well-known dependency parsers, the transition-based Malt parser and the graph-based MST parser. While previous work on parsing with incomplete data has typically couched the task in frameworks of unsupervised or semi-supervised machine learning, we essentially treat it as a supervised problem. In particular, we propose what we call agnostic parsers which hide all fragmentation in the training data from their supervised components. We present experimenta

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Quaranta, Giacomo. "Efficient simulation tools for real-time monitoring and control using model order reduction and data-driven techniques." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/667474.

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Numerical simulation, the use of computers to run a program which implements a mathematical model for a physical system, is an important part of today technological world. It is required in many scientific and engineering fields to study the behaviour of systems whose mathematical models are too complex to provide analytical solutions and it makes virtual evaluation of systems responses possible (virtual twins). This drastically reduces the number of experimental tests for accurate designs of the real system that the numerical model represents. However these virtual twins, based on classic

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Sahki, Nassim. "Méthodologie data-driven de détection séquentielle de ruptures pour des signaux physiologiques." Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0185.

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Cette thèse traite de la problématique de la détection de rupture dans le cadre séquentiel où le signal est supposé être observé en temps réel et le phénomène passe de son état de départ "normal" à un état post-changement "anormal". Le défi de la détection séquentielle est de minimiser le délai de détection, soumis à une limite tolérable de fausse alarme. L'idée est de tester séquentiellement l'existence d'une rupture par l'écriture récursive de la statistique de détection en fonction du score, qui remplace le Log-Likelihood Ratio lorsque la distribution des données est inconnue. La procédure

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Rivers, Derick L. "A Graphical Analysis of Simultaneously Choosing the Bandwidth and Mixing Parameter for Semiparametric Regression Techniques." VCU Scholars Compass, 2009. http://scholarscompass.vcu.edu/etd/1896.

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There has been extensive research done in the area of Semiparametric Regression. These techniques deliver substantial improvements over previously developed methods, such as Ordinary Least Squares and Kernel Regression. Two of these hybrid techniques: Model Robust Regression 1 (MRR1) and Model Robust Regression 2 (MRR2) require the choice of an appropriate bandwidth for smoothing and a mixing parameter that allows a portion of a nonparametric fit to be used in fitting a model that may be misspecifed by other regression methods. The current method of choosing the bandwidth and mixing parameter

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Duran, Villalobos Carlos Alberto. "Run-to-run modelling and control of batch processes." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/runtorun-modelling-and-control-of-batch-processes(1d42c508-b96d-4ee6-96ad-ec649a199913).html.

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The University of ManchesterCarlos Alberto Duran VillalobosDoctor of Philosophy in the Faculty of Engineering and Physical SciencesDecember 2015This thesis presents an innovative batch-to-batch optimisation technique that was able to improve the productivity of two benchmark fed-batch fermentation simulators: Saccharomyces cerevisiae and Penicillin production. In developing the proposed technique, several important challenges needed to be addressed:For example, the technique relied on the use of a linear Multiway Partial Least Squares (MPLS) model to adapt from one operating region to another

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Ayo, Babatope S. "Data-driven flight path rerouting during adverse weather: Design and development of a passenger-centric model and framework for alternative flight path generation using nature inspired techniques." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17387.

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A major factor that negatively impacts flight operations globally is adverse weather. To reduce the impact of adverse weather, avoidance procedures such as finding an alternative flight path can usually be carried out. However, such procedures usually introduce extra costs such as flight delay. Hence, there exists a need for alternative flight paths that efficiently avoid adverse weather regions while minimising costs. Existing weather avoidance methods used techniques, such as Dijkstra’s and artificial potential field algorithms that do not scale adequately and have poor real time performanc

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Rafique, Muhammad T. "Monitoring, diagnostics and improvement of process performance." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/1333.

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The data generated in a chemical industry is a reflection of the process. With the modern computer control systems and data logging facilities, there is an increasing ability to collect large amounts of data. As there are many underlying aspects of the process in that data, with its proper utilization, it is possible to obtain useful information for process monitoring and fault diagnosis in addition to many other decision making activities. The purpose of this research is to utilize the data driven multivariate techniques of Principal Component Analysis (PCA) and Independent Component Analysis

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Granjal, Cruz Gonçalo Jorge. "Development and validation of a bayesian measurement technique for data-driven measurement reduction." Electronic Thesis or Diss., Ecully, Ecole centrale de Lyon, 2024. http://www.theses.fr/2024ECDL0012.

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Ce travail présente une méthodologie de test hybride complète pour évaluer l'écoulement dans turbomachines. Axée sur la minimisation des temps de test et des exigences en instrumentation, la méthodologie intègre de manière stratégique des mesures expérimentales standard avec des simulations numériques, en utilisant des processus gaussiens.La méthodologie réduit systématiquement à la fois les efforts d'instrumentation et les temps de test, fournissant des métriques d'incertitude comparables aux méthodologies traditionnelles. Appliquée initialement à un compresseur axial haute pression de référe

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Darwish, Amani. "Capteur d'images événementiel, asynchrone à échantillonnage non-uniforme." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT071/document.

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Face aux défis actuels liés à la conception de capteurs d'images à forte résolution comme la limitation de la consommation électrique, l'augmentation du flux de données ainsi que le traitement de données associé, on propose, à travers cette thèse, un capteur d'image novateur asynchrone à échantillonnage non uniforme.Ce capteur d’images asynchrone est basé sur une matrice de pixels événementiels qui intègrent un échantillonnage non uniforme par traversée de niveaux. Contrairement aux imageurs conventionnels, où les pixels sont lus systématiquement lors de chaque trame, les pixels événementiels

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Alabdulrahman, Rabaa. "Towards Personalized Recommendation Systems: Domain-Driven Machine Learning Techniques and Frameworks." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41012.

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Recommendation systems have been widely utilized in e-commerce settings to aid users through their shopping experiences. The principal advantage of these systems is their ability to narrow down the purchase options in addition to marketing items to customers. However, a number of challenges remain, notably those related to obtaining a clearer understanding of users, their profiles, and their preferences in terms of purchased items. Specifically, recommender systems based on collaborative filtering recommend items that have been rated by other users with preferences similar to those of the targ

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Henclewood, Dwayne Anthony. "Real-time estimation of arterial performance measures using a data-driven microscopic traffic simulation technique." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44792.

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Traffic congestion is a one hundred billion dollar problem in the US. The cost of congestion has been trending upward over the last few decades, but has experienced slight decreases in recent years partly due to the impact of congestion reduction strategies. The impact of these strategies is however largely experienced on freeways and not arterials. This discrepancy in impact is partially linked to the lack of real-time, arterial traffic information. Toward this end, this research effort seeks to address the lack of arterial traffic information. To address this dearth of information, thi

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Jose, Sagar. "Stratégies d'apprentissage multimodal pour le diagnostic et le pronostic de la santé des machines industrielles dans un contexte de manque de données." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEP093.

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Les approches de Pronostic et gestion de la santé des systèmes (Prognostics and Health Management : PHM) guidées par les données sont fortement dépendantes de la disponibilité et de la qualité d’historiques de défaillances, une exigence souvent difficile à satisfaire dans les systèmes de surveillance en conditions industrielles. Cette divergence crée un écart significatif entre les méthodologies de PHM et leur application pratique sur des systèmes réels. L’accent prédominant mis sur les ensembles de données unimodales dans les travaux de recherche en PHM basée sur les données met en lumière le

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Jaber, Sara. "Resilience as a Service : a multimodal transport strategy combining simulation, optimization, and data-driven resource allocation." Electronic Thesis or Diss., Université Gustave Eiffel, 2025. http://www.theses.fr/2025UEFL2004.

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L'objectif de cette thèse est la conception et le développement d'un système d'exploitation coopératif, des modes des transports collectifs traditionnels et les ressources existantes, afin d'offrir un réseau de transport résilient pouvant faire face aux perturbations de grandes ou petites échelles. Les véhicules seront utilisées comme service de desserte des transports collectifs traditionnels existants et comme élément régulateur en cas de perturbation. Ce système doit être capable d'aider les opérateurs à gérer de manière efficace les réseaux en cas de dérèglements ou de ruptures (problème d

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Oteniya, Lloyd. "Bayesian belief networks for dementia diagnosis and other applications : a comparison of hand-crafting and construction using a novel data driven technique." Thesis, University of Stirling, 2008. http://hdl.handle.net/1893/497.

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The Bayesian network (BN) formalism is a powerful representation for encoding domains characterised by uncertainty. However, before it can be used it must first be constructed, which is a major challenge for any real-life problem. There are two broad approaches, namely the hand-crafted approach, which relies on a human expert, and the data-driven approach, which relies on data. The former approach is useful, however issues such as human bias can introduce errors into the model. We have conducted a literature review of the expert-driven approach, and we have cherry-picked a number of common met

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Belmar, Gil Mario. "Computational study on the non-reacting flow in Lean Direct Injection gas turbine combustors through Eulerian-Lagrangian Large-Eddy Simulations." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/159882.

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[ES] El principal desafío en los motores turbina de gas empleados en aviación reside en aumentar la eficiencia del ciclo termodinámico manteniendo las emisiones contaminantes por debajo de las rigurosas restricciones. Ésto ha conllevado la necesidad de diseñar nuevas estrategias de inyección/combustión que operan en puntos de operación peligrosos por su cercanía al límite inferior de apagado de llama. En este contexto, el concepto Lean Direct Injection (LDI) ha emergido como una tecnología prometedora a la hora de reducir los óxidos de nitrógeno (NOx) emitidos por las plantas propulsoras de lo

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Teng, Sin Yong. "Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-433427.

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S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a pr

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Samal, K. Krishna Rani. "Exploring Deep Learning Techniques for Data-driven Air Quality Modeling and Forecasting." Thesis, 2022. http://ethesis.nitrkl.ac.in/10415/1/2022_PhD_KKRSamal_517CS6019_Exploring.pdf.

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Air pollution has become a significant issue, especially in high-density urban areas. Since the first industrial revolution in the 19th century, human activities have badly affected the earth and the environment. The world has become inhabitable day by day due to inappropriate human activities, construction patterns, and unsustainable cities development. Moreover, due to these activities, environmental air quality has become worst day by day. World Health Organization (WHO) provided evidence that urban air pollution is becoming the main threat to human health, especially in high-density countr

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Cernaut, Oana-Maria. "Customer targeting models using data mining techniques." Master's thesis, 2019. http://hdl.handle.net/10773/30010.

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In recent years, the segmentation process has undergone numerous changes, once with the advances in data mining. Knowledge discovery can automatize and provide better insights into customer trends and dynamics. The objective of the paper is to improve the quality of the marketing segmentation for company T. More specifically, the research question it plans to answer is whether data mining techniques deliver a better segmentation model than intuitive approaches. The segmentation steps comprise the identification of the necessary variables, the selection of the relevant ones to conduct the segme

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Amorim, Inês Oliveira. "Analytical CRM in a management consulting firm : an application of data driven techniques." Master's thesis, 2021. http://hdl.handle.net/10400.14/34745.

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Considering the competitive environment in which companies operate nowadays and the importance of customer relationship management (CRM), it is crucial to analyse customer-related data to gain knowledge and insights about them in order to increase their retention and company’s performance. The presented investigation resulted from a curricular internship carried out at Inova+, a management consulting firm specialised in supporting the growth of organizations. In this sense, the aim of this investigation is to support the CRM system and the customer’s management strategies of Inova+, contribut

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Zhao, Ming. "Iterative Receiver Techniques for Data-Driven Channel Estimation and Interference Mitigation in Wireless Communications." Phd thesis, 2009. http://hdl.handle.net/1885/8033.

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Wireless mobile communications were initially a way for people to communicate through low data rate voice call connections. As data enabled devices allow users the ability to do much more with their mobile devices, so to will the demand for more reliable and pervasive wireless data. This is being addressed by so-called 4th generation wireless systems based on orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) antenna systems. Mobile wireless customers are becoming more demanding and expecting to have a great user experience over high speed broadband acc

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OVIEDO, HERNANDEZ GUILLERMO. "Improving the quality of PV plant performance analysis by increasing data integrity and reliability: a data-driven approach using Machine Learning techniques." Doctoral thesis, 2021. http://hdl.handle.net/11573/1587657.

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PV modules are engineered to produce electricity for 30+ years and are being deployed worldwide in ever more and ever bigger PV plants. Continuous quality assurance and performance analysis are the cornerstone for long-term reliability to maximize financial and energy returns. In today’s highly competitive Operation and Maintenance (O&M) market, employing and maintaining extensive networks of on-site sensors for remote monitoring purposes, proves challenging. Within this framework, data-driven solutions play a leading role to turn raw data from the field into reliable actionable insights.

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Song, Lixing. "Adaptive wireless rate control driven by highly fine-grained channel assessment." 2014. http://liblink.bsu.edu/uhtbin/catkey/1749603.

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Access to abstract permanently restricted to Ball State community only.<br>Background : a survey for rate adaptation -- ABEP metric and channell assessment -- ABEP-based adaptive rate control -- Performance evaluation.<br>Access to thesis permanently restricted to Ball State community only.<br>Department of Computer Science

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