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Dissertations / Theses on the topic 'CNN MODEL'

Author: Grafiati

Published: 11 September 2023

Last updated: 25 July 2025

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1

Meng, Zhaoxin. "A deep learning model for scene recognition." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-36491.

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Scene recognition is a hot research topic in the field of image recognition. It is necessary that we focus on the research on scene recognition, because it is helpful to the scene understanding topic, and can provide important contextual information for object recognition. The traditional approaches for scene recognition still have a lot of shortcomings. In these years, the deep learning method, which uses convolutional neural network, has got state-of-the-art results in this area. This thesis constructs a model based on multi-layer feature extraction of CNN and transfer learning for scene rec

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Hubková, Helena. "Named-entity recognition in Czech historical texts : Using a CNN-BiLSTM neural network model." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385682.

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The thesis presents named-entity recognition in Czech historical newspapers from Modern Access to Historical Sources Project. Our goal was to create a specific corpus and annotation manual for the project and evaluate neural networks methods for named-entity recognition within the task. We created the corpus using scanned Czech historical newspapers. The scanned pages were converted to digitize text by optical character recognition (OCR) method. The data were preprocessed by deleting some OCR errors. We also defined specific named entities types for our task and created an annotation manual wi

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Al-Kadhimi, Staffan, and Paul Löwenström. "Identification of machine-generated reviews : 1D CNN applied on the GPT-2 neural language model." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280335.

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With recent advances in machine learning, computers are able to create more convincing text, creating a concern for an increase in fake information on the internet. At the same time, researchers are creating tools for detecting computer-generated text. Researchers have been able to exploit flaws in neural language models and use them against themselves; for example, GLTR provides human users with a visual representation of texts that assists in classification as human-written or machine-generated. By training a convolutional neural network (CNN) on GLTR output data from analysis of machine-gen

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Huss, Anders. "Hybrid Model Approach to Appliance Load Disaggregation : Expressive appliance modelling by combining convolutional neural networks and hidden semi Markov models." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-179200.

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The increasing energy consumption is one of the greatest environmental challenges of our time. Residential buildings account for a considerable part of the total electricity consumption and is further a sector that is shown to have large savings potential. Non Intrusive Load Monitoring (NILM), i.e. the deduction of the electricity consumption of individual home appliances from the total electricity consumption of a household, is a compelling approach to deliver appliance specific consumption feedback to consumers. This enables informed choices and can promote sustainable and cost saving action

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Laine, Emmi. "Desirability, Values and Ideology in CNN Travel -- Discourse Analysis on Travel Stories." Thesis, Stockholms universitet, Institutionen för mediestudier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-102742.

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Title: Values, Desirability and Ideology in CNN Travel -- a Discourse Analysis on Travel Stories Author: Emmi Laine Course: Journalistikvetenskap, Kandidatkurs, H13 J Kand (Bachelor of Journalism, Fall 2013), JMK, Stockholm University, Sweden Aim: The aim is to examine which values and ideologies CNN Travel fulfills in their stories. Method: Qualitative discourse analysis. Summary: This Bachelor ́s thesis asks what is desirable, which are the values of CNN Travel, the major U.S. news corporation CNN ́s online travel site. The question has been answered through a qualitative discourse analysis

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Appelstål, Michael. "Multimodal Model for Construction Site Aversion Classification." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-421011.

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Aversion on construction sites can be everything from missingmaterial, fire hazards, or insufficient cleaning. These aversionsappear very often on construction sites and the construction companyneeds to report and take care of them in order for the site to runcorrectly. The reports consist of an image of the aversion and atext describing the aversion. Report categorization is currentlydone manually which is both time and cost-ineffective. The task for this thesis was to implement and evaluate an automaticmultimodal machine learning classifier for the reported aversionsthat utilized both the im

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Anam, Md Tahseen. "Evaluate Machine Learning Model to Better Understand Cutting in Wood." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448713.

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Wood cutting properties for the chains of chainsaw is measured in the lab by analyzing the force, torque, consumed power and other aspects of the chain as it cuts through the wood log. One of the essential properties of the chains is the cutting efficiency which is the measured cutting surface per the power used for cutting per the time unit. These data are not available beforehand and therefore, cutting efficiency cannot be measured before performing the cut. Cutting efficiency is related to the relativehardness of the wood which means that it is affected by the existence of knots (hardstruct

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Ghibellini, Alessandro. "Trend prediction in financial time series: a model and a software framework." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24708/.

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The research has the aim to build an autonomous support for traders which in future can be translated in an Active ETF. My thesis work is characterized for a huge focus on problem formulation and an accurate analysis on the impact of the input and the length of the future horizon on the results. I will demonstrate that using financial indicators already used by professional traders every day and considering a correct length of the future horizon, it is possible to reach interesting scores in the forecast of future market states, considering both accuracy, which is around 90% in all the experi

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Rydén, Anna, and Amanda Martinsson. "Evaluation of 3D motion capture data from a deep neural network combined with a biomechanical model." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176543.

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Motion capture has in recent years grown in interest in many fields from both game industry to sport analysis. The need of reflective markers and expensive multi-camera systems limits the business since they are costly and time-consuming. One solution to this could be a deep neural network trained to extract 3D joint estimations from a 2D video captured with a smartphone. This master thesis project has investigated the accuracy of a trained convolutional neural network, MargiPose, that estimates 25 joint positions in 3D from a 2D video, against a gold standard, multi-camera Vicon-system. The p

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Gerima, Kassaye. "Night Setback Identification of District Heating Substations." Thesis, Högskolan Dalarna, Mikrodataanalys, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-36071.

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Energy efficiency of district heating systems is of great interest to energy stakeholders. However, it is not uncommon that district heating systems fail to achieve the expected performance due to inappropriate operations. Night setback is one control strategy, which has been proved to be not a suitable setting for well-insulated modern buildings in terms of both economic and energy efficiency. Therefore, identification of a night setback control is vital to district heating companies to smoothly manage their heat energy distribution to their customers. This study is motivated to automate this

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Sievert, Rolf. "Instance Segmentation of Multiclass Litter and Imbalanced Dataset Handling : A Deep Learning Model Comparison." Thesis, Linköpings universitet, Datorseende, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175173.

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Instance segmentation has a great potential for improving the current state of littering by autonomously detecting and segmenting different categories of litter. With this information, litter could, for example, be geotagged to aid litter pickers or to give precise locational information to unmanned vehicles for autonomous litter collection. Land-based litter instance segmentation is a relatively unexplored field, and this study aims to give a comparison of the instance segmentation models Mask R-CNN and DetectoRS using the multiclass litter dataset called Trash Annotations in Context (TACO) i

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Zhong, Shifa. "Permanganate Reaction Kinetics and Mechanisms and Machine Learning Application in Oxidative Water Treatment." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1618686803768471.

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Viebke, André. "Accelerated Deep Learning using Intel Xeon Phi." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-45491.

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Deep learning, a sub-topic of machine learning inspired by biology, have achieved wide attention in the industry and research community recently. State-of-the-art applications in the area of computer vision and speech recognition (among others) are built using deep learning algorithms. In contrast to traditional algorithms, where the developer fully instructs the application what to do, deep learning algorithms instead learn from experience when performing a task. However, for the algorithm to learn require training, which is a high computational challenge. High Performance Computing can help

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Kovář, Pavel. "Model CNC frézky." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219700.

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The master's thesis deals with the basic parts and principles of CNC machines with a focus on a CNC milling machine. There are also comparisons of several CNC machines sold. Furthermore, the project deals with the description of the manipulator, which is situated in laboratory E-132 in area Kolejní 4, Brno. The work also includes a description of the device, which is located in the manipulator model. We can find there a description of the program generating G-code from the image that you create in the editor. The next section describes possible modifications of the manipulator for its reconstr

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Nixdorf, Timothy Allen. "A Mathematical Model for Carbon Nanoscrolls." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1406060123.

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Truzzi, Stefano. "Event classification in MAGIC through Convolutional Neural Networks." Doctoral thesis, Università di Siena, 2022. http://hdl.handle.net/11365/1216295.

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The Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescopes are able to detect gamma rays from the ground with energies beyond several tens of GeV emitted by the most energetic known objects, including Pulsar Wind Nebulae, Active Galactic Nuclei, and Gamma-Ray Bursts. Gamma rays and cosmic rays are detected by imaging the Cherenkov light produced by the charged superluminal leptons in the extended air shower originated when the primary particle interacts with the atmosphere. These Cherenkov flashes brighten the night sky for short times in the nanosecond scale. From the image topology an

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Ornstein, Charlotte, and Karin Sandahl. "Coopetition and business models : How can they be integrated, and what effect does it have on value creation, delivery and capture?" Thesis, Umeå universitet, Företagsekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-105963.

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Technological innovations and development have caused rapid changes in the business environment. These changes have forced firms to change in the way they do business and operate. Two industries that are affected by these changes are the telecommunication industry and the information technology (IT) industry. Here, it is no longer possible for firms to operate completely individually, and many firms are pushed to engage in so called coopetition, which is cooperation with both vertical and horizontal competitors. As a consequence of the environmental changes, firms’ business models also need to

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Lind, Johan. "Evaluating CNN-based models for unsupervised image denoising." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176092.

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Images are often corrupted by noise which reduces their visual quality and interferes with analysis. Convolutional Neural Networks (CNNs) have become a popular method for denoising images, but their training typically relies on access to thousands of pairs of noisy and clean versions of the same underlying picture. Unsupervised methods lack this requirement and can instead be trained purely using noisy images. This thesis evaluated two different unsupervised denoising algorithms: Noise2Self (N2S) and Parametric Probabilistic Noise2Void (PPN2V), both of which train an internal CNN to denoise im

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Söderström, Douglas. "Comparing pre-trained CNN models on agricultural machines." Thesis, Umeå universitet, Institutionen för fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185333.

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Venne, Simon. "Can Species Distribution Models Predict Colonizations and Extinctions?" Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38465.

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Aim MaxEnt, a very popular species distribution modelling technique, has been used extensively to relate species’ geographic distributions to environmental variables and to predict changes in species’ distributions in response to environmental change. Here, we test its predictive ability through time (rather than through space, as is commonly done) by modeling colonizations and extinctions. Location Continental U.S. and southern Canada. Time period 1979-2009 Major taxa studied Twenty-one species of passerine birds. Methods We used MaxEnt to relate species’ geographic distribu

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Kurbanoglu, Ozgur. "Electric Energy Policy Models In The European Union: Can There Be A Model For Turkey?" Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605585/index.pdf.

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The thesis discusses Turkish energy sector by using examples, projections made by the European Union, and positions of the experts and scholars. The work discusses the process of reformation of Energy sector, and what the obstacles and difficulties are. It is important that Turkey needs progress in the process of reformation that can be satisfied by using a functioning model in the field. Turkey has to apply the legislation of the European Union as an applicant country. Turkey needs a strategy for achieving the application of the energy legislation. Different countries in the European Union ha

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Du, Chenguang. "How Well Can Two-Wave Models Recover the Three-Wave Second Order Latent Model Parameters?" Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/103856.

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Although previous studies on structural equation modeling (SEM) have indicated that the second-order latent growth model (SOLGM) is a more appropriate approach to longitudinal intervention effects, its application still requires researchers to collect at least three-wave data (e.g. randomized pretest, posttest, and follow-up design). However, in some circumstances, researchers can only collect two-wave data for resource limitations. With only two-wave data, the SOLGM can not be identified and researchers often choose alternative SEM models to fit two-wave data. Recent studies show that the two

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Norlund, Tobias. "The Use of Distributional Semantics in Text Classification Models : Comparative performance analysis of popular word embeddings." Thesis, Linköpings universitet, Datorseende, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-127991.

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In the field of Natural Language Processing, supervised machine learning is commonly used to solve classification tasks such as sentiment analysis and text categorization. The classical way of representing the text has been to use the well known Bag-Of-Words representation. However lately low-dimensional dense word vectors have come to dominate the input to state-of-the-art models. While few studies have made a fair comparison of the models' sensibility to the text representation, this thesis tries to fill that gap. We especially seek insight in the impact various unsupervised pre-trained vect

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Keating, Daniel. "Model Checking Time Triggered CAN Protocols." Thesis, University of Canterbury. Electrical and Computer Engineering, 2011. http://hdl.handle.net/10092/5754.

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Model checking is used to aid in the design and verification of complex concurrent systems. An abstracted finite state model of a system and a set of mathematically based correctness properties based on the design specifications are defined. The model checker then performs an exhaustive state space search of the model, checking that the correctness properties hold at each step. This thesis describes how the SPIN model checker has been used to find and correct problems in the software design of a distributed marine vessel control system currently under development at a control systems specialis

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Ondroušek, Jakub. "Ekonometrický model cen bytů v Brně." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2019. http://www.nusl.cz/ntk/nusl-399645.

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The goal of the thesis „Econometric model of flat prices in Brno“ is to create econometric model based on data from housing market. The theoretical part of the thesis defines variables, and use descriptive statistics. The practical part of the thesis deals with creation econometric model and interactive calculator.

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Mutarelli, Rita de Cássia. "Estudo da responsabilidade social do Instituto de Pesquisas Energéticas e Nucleares de São Paulo (IPEN/CNEN - SP)." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/85/85133/tde-16072014-141824/.

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Ao longo dos anos, a evolução do conceito socioambiental tem se solidificado por meio de programas, conferências e diversas atividades que ocorrem no Brasil e no mundo. A sustentabilidade e a responsabilidade social passaram a ser parte integrante do cotidiano das organizações. O Instituto de Pesquisas Energéticas e Nucleares (IPEN) 1, que é o foco desse trabalho tem como parte da sua missão o compromisso com a melhoria da qualidade de vida da população brasileira e com base na missão do IPEN e na falta de instrumentos de avaliação de ações socioambientais, este trabalho tem como objetivo prop

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Tenruh, Mahmut. "Extending Controller Area Networks : CAN/CAN cut-through bridging, CAN over ATM, and CAN based ATM FieldBus." Thesis, University of Sussex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340796.

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Truong, Quan, and trunongluongquan@yahoo com au. "Continuous-time Model Predictive Control." RMIT University. Electrical and Computer Engineering, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20090813.163701.

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Model Predictive Control (MPC) refers to a class of algorithms that optimize the future behavior of the plant subject to operational constraints [46]. The merits of the class algorithms include its ability to handle imposed hard constraints on the system and perform on-line optimization. This thesis investigates design and implementation of continuous time model predictive control using Laguerre polynomials and extends the design ap- proaches proposed in [43] to include intermittent predictive control, as well as to include the case of the nonlinear predictive control. In the I

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Suresh, Sreerag. "An Analysis of Short-Term Load Forecasting on Residential Buildings Using Deep Learning Models." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99287.

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Building energy load forecasting is becoming an increasingly important task with the rapid deployment of smart homes, integration of renewables into the grid and the advent of decentralized energy systems. Residential load forecasting has been a challenging task since the residential load is highly stochastic. Deep learning models have showed tremendous promise in the fields of time-series and sequential data and have been successfully used in the field of short-term load forecasting at the building level. Although, other studies have looked at using deep learning models for building energy f

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Vichare, Parag. "A novel methodology for modelling CNC machining system resources." Thesis, University of Bath, 2009. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.518102.

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Nuthmann, Antje, Wolfgang Einhäuser, and Immo Schütz. "How Well Can Saliency Models Predict Fixation Selection in Scenes Beyond Central Bias? A New Approach to Model Evaluation Using Generalized Linear Mixed Models." Universitätsbibliothek Chemnitz, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-232614.

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Since the turn of the millennium, a large number of computational models of visual salience have been put forward. How best to evaluate a given model's ability to predict where human observers fixate in images of real-world scenes remains an open research question. Assessing the role of spatial biases is a challenging issue; this is particularly true when we consider the tendency for high-salience items to appear in the image center, combined with a tendency to look straight ahead (“central bias”). This problem is further exacerbated in the context of model comparisons, because some—but not al

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Šmerda, Ondřej. "Návrh koncepce leteckého motoru na CNG." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-401574.

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Master’s thesis deals with comparsion and rating the compressed natural gas as an aircraft piston engine fuel. An information search of conventional fuels and differences of the fuel systems for AVGAS and CNG is included. Next part describes the aircraft and its engine on which is the mathematic model based. After that perfomance and consumption data are calculated for both fuels and the results are then compared. At the end of the thesis, a design of the CNG fuel system with components selection is described.

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Sivaraman, Gokul. "Development of PMSM and drivetrain models in MATLAB/Simulink for Model Based Design." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301027.

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When developing three-phase drives for Electric Vehicles (EVs), it is essential to verify the controller design. This will help in understanding how fast and accurately the torque of the motor can be controlled. In order to do this, it is always better to test the controller using the software version of the motor or vehicle drivetrain than using actual hardware as it could lead to component damage when replicating extreme physical behavior. In this thesis, plant modelling of Permanent Magnet Synchronous Machine (PMSM) and vehicle drivetrain in MATLAB/Simulink for Model Based Design (MBD) is p

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TAORMINA, Vincenzo. "DEVELOPMENT AND IMPLEMENTATION OF MACHINE LEARNING METHODS FOR THE IIF IMAGES ANALYSIS." Doctoral thesis, Università degli Studi di Palermo, 2021. http://hdl.handle.net/10447/479046.

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Thomas, Kerry J. "Teaching Mathematical Modelling to Tomorrow's Mathematicians or, You too can make a million dollars predicting football results." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-83131.

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Brien, Jeffrey. "Mixed Emotions: Can People Feel Happy and Sad at the Same Time?" Thesis, Boston College, 2003. http://hdl.handle.net/2345/426.

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Thesis advisor: Timothy A. Duket<br>I studied whether or not people can feel happy and sad at the same moment in time. Participants used a computerized procedure to continuously rate their feelings as they viewed backwardly masked faces designed to elicit pleasant, unpleasant, or mixed feelings. The backward masking procedure and grid were poorly calibrated as participants found all conditions to be unpleasant. Evidence is presented that participants did not perceive the mask faces as neutral. Directions for future studies are discussed<br>Thesis (BA) — Boston College, 2003<br>Submitted to: Bo

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Abalos, Choque Melisa. "Modelo Arima con intervenciones." Universidad Mayor de San Andrés. Programa Cybertesis BOLIVIA, 2009. http://www.cybertesis.umsa.bo:8080/umsa/2009/abalos_cme/html/index-frames.html.

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El desarrollo de gran parte de los modelos y métodos estadísticos, específicamente relacionados con series temporales, ha ido ligado al deseo de estudiar aplicaciones específicas dentro de diversos ámbitos científicos. El presente trabajo también surgió con el objetivo de resolver diversos problemas que se plantean dentro del ámbito econométrico, aunque también puede ser usado en otros ámbitos, todos ellos ligados con un conjunto de datos históricos y con una aplicación muy concreta al estudio del “egreso de divisas” en Bolivia. Se han estudiado a profundidad los modelos para series temporales

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Thomas, Kerry J. "Teaching Mathematical Modelling to Tomorrow''s Mathematicians or, You too can make a million dollars predicting football results." Turning dreams into reality: transformations and paradigm shifts in mathematics education. - Grahamstown: Rhodes University, 2011. - S. 334 - 339, 2012. https://slub.qucosa.de/id/qucosa%3A1949.

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Tůmová, Petra. "Konstrukce předpovědních modelů cen zlata a stříbra." Master's thesis, Česká zemědělská univerzita v Praze, 2016. http://www.nusl.cz/ntk/nusl-260507.

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Diplomová práce je zaměřena na analýzu vývoje časových řad, nominálních cen zlata a stříbra od roku 1968 do roku 2014 a následné využití ARIMA modelu pro sestavení predikce cen obou komodit. Při sestavování predikce bylo využito statistického softwaru Statistica od společnosti StatSoft ČR s. r. o. (licence získána z ČZU) a tabulkového procesoru Microsoft Excel.

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Hamouzová, Michaela. "Analýza vývoje cen nemovitostí v České republice." Master's thesis, Vysoká škola ekonomická v Praze, 2016. http://www.nusl.cz/ntk/nusl-264620.

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The aim of this diploma thesis is to analyze the development of the prices of real estate in the Czech Republic. The thesis is divided into three main parts. The first one deals with the theoretical introduction to valuation of the real estate. Moreover, the thesis presents the current development of the prices of real estate on the Czech market. The last part focuses on co-integration analysis, within which an ADL model is created. This model serves as a base for an error correction model, which describes short-term as well as long-term relations within the time series. The explanatory variab

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Kim, Taejung 1969. "Time-optimal CNC tool paths : a mathematical model of machining." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8861.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.<br>Includes bibliographical references (p. 181-188).<br>Free-form surface machining is a fundamental but time-consuming process in modern manufacturing. The central question we ask in this thesis is how to reduce the time that it takes for a 5-axis CNC (Computer Numerical Control) milling machine to sweep an entire free-form surface in its finishing stage. We formulate a non-classical variational time-optimization problem defined on a 2-dimensional manifold subject to both equality and inequality cons

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Sztendel, Sebastian. "Model referenced condition monitoring of high performance CNC machine tools." Thesis, University of Huddersfield, 2016. http://eprints.hud.ac.uk/id/eprint/34112/.

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Generally, machine tool monitoring is the prediction of the system’s health based on signal acquisition and processing and classification in order to identify the causes of the problem. The producers of machine tools need to pay more attention to their products life cycle because their customers increasingly focus on machine tool reliability and costs. The present study is concerned with the development of a condition monitoring system for high speed Computer Numerical Control (CNC) milling machine tools. A model is a simplification of a real machine to visualize the dynamics of a mechatronic

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Srinivasan, Srikant. "A Compact Model for the Coaxially Gated Schottky Barrier Carbon Nanotube Field Effect Transistor." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1161897189.

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Vopatřilová, Lenka. "Podnik v regulovaném vodohospodářském odvětví." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-113498.

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The Thesis intends to introduce business in government regulated Water Industry, accurately the area of Water Supply and Sewerage. Its aim is to describe the business market of this field. Moreover, to find out whether the companies in private multinational corporation ownership don't burden their customers with too high price of water supply and find if there is any relationship between the price of water and the profitability of these enterprises. To achieve this aim, companies are categorized into five groups and compared. These groups are created on the basis of the shares of private forei

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GUPTA, RASHI. "IMAGE FORGERY DETECTION USING CNN MODEL." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19175.

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Image forgery detection has become more relevant in the real world in recent years since it is so easy to change a particular image and share it throughout social media, which may quickly lead to fake news and fake rumors all over the world. These editing softwares have posed a significant challenge to image forensics in terms of proposing and implementing various methods and strategies for detecting image counterfeiting. There have been a variety of traditional approaches for forgery detection, but they all focus on simple feature extraction and are more specialized to the type of

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LIAO, PEN-MIN, and 廖本閔. "Streamflow Forecasting by CNN-GRU Model." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/8rs76r.

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碩士<br>逢甲大學<br>水利工程與資源保育學系<br>107<br>During the last two decades, the application of artificial intelligence in the field of flood forecasting has increased noticeably. Since the information of flood forecasting is the most important part of disaster management, also the emergency response and the mechanism of Recurrent Neural Network (RNN) include the behavior of the time series, this study attempt to adopt the Gated Recurrent Unit (GRU) which is a type of RNN used to develop a rainfall-runoff model for the mentioned purpose above. In this research RNN is using Gated Recurrent Unit (GRU). In e

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Lin, Chun-Man, and 林君蔓. "Apparent Age Estimation Based on CNN Model." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/g9wspb.

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碩士<br>國立東華大學<br>資訊工程學系<br>107<br>Age estimation has been one of hot topics in computer vision. Identifying personal characteristics such as age, personal identity, gender, and ethnicity through images is an interesting but challenging problem. In recent years, age estimation has become an attractive research topic because it can be widely applied to human life. For example: (1) devices with age recognition can automatically filter age-restricted products, such as cigarettes and alcohol. (2) Since shopping habit and preferences of different age groups are very different, the automatic collectio

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SONI, ANKIT. "DETECTING DEEPFAKES USING HYBRID CNN-RNN MODEL." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19168.

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We are living in the world of digital media and are connected to various types of digital media contents present in form of images and videos. Our lives are surrounded by digital contents and thus originality of content is very important. In the recent times, there is a huge emergence of deep learning-based tools that are used to create believable manipulated media known as Deepfakes. These are realistic fake media, that can cause threat to reputation, privacy and can even prove to be a serious threat to public security. These can even be used to create political distress, spread f

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Huang, Ya-Bo, and 黃雅博. "Perceptual-Based CNN Model for Watercolor Mixing Prediction." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/nf4394.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>107<br>In the paper, we propose a model to predict the mixture of watercolor pigments using convolutional neural networks (CNN). With a watercolor dataset, we train our model to minimize the loss function of sRGB differences. In metric of color difference ∆ELab, our model achieves 88.7% of data that ∆ELab < 5 on the test set, which means the difference cannot easily be detected by the human eye. In addition, an interesting phenomenon is found; Even if the reflectance curve of the predicted color is not as smooth as the ground truth curve, the RGB color is still c

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KATARIA, MEGHA. "PEDESTRIAN WALKING DIRECTION DETECTION USING HYBRID CNN-SVM MODEL." Thesis, 2019. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16849.

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Pedestrian movement direction recognition is an important factor in autonomous driver assistance and security surveillance systems. Pedestrians are the most crucial and fragile moving objects in streets, roads, and events, where thousands of people may gather on a regular basis. People flow analysis on zebra crossings and in shopping centers or events such as demonstrations are a key element to improve safety and to enable autonomous cars to drive in real life environments. This thesis focuses on deep learning techniques such as hybrid Convolutional Neural Networks (CNN) – Support Vector Machi

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