Thèses sur le sujet « Attribute estimation »
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Azzeh, Mohammad Y. A. « Analogy-based software project effort estimation : contributions to projects similarity measurement, attribute selection and attribute weighting algorithms for analogy-based effort estimation ». Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/4442.
Texte intégralThiyagarajah, Murali. « Attribute cardinality maps, new query result size estimation techniques for database systems ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0007/NQ42810.pdf.
Texte intégralThiyagarajah, Murali (Muralitharam) Carleton University Dissertation Computer Science. « Attribute cardinality maps ; new query result size estimation techniques for database systems ». Ottawa, 1999.
Trouver le texte intégralDivelbiss, David L. « Evaluation of the Impact of Product Detail on the Accuracy of Cost Estimates ». Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1127165055.
Texte intégralMoser, Paolo 1985, Alexander Christian 1959 Vibrans, Ronald McRoberts et Universidade Regional de Blumenau Programa de Pós-Graduação em Engenharia Ambiental. « Statistical and computational methods of forest attribute estimation and classification based on remotely sensed data ». reponame:Biblioteca Digital de Teses e Dissertações FURB, 2018. http://www.bc.furb.br/docs/TE/2018/364705_1_1.pdf.
Texte intégralCoorientador: Ronald McRoberts.
Tese (Doutorado em Engenharia Ambiental) - Programa de Pós-Graduação em Engenharia Ambiental, Centro de Ciências Tecnológicas, Universidade Regional de Blumenau, Blumenau.
FABBRI, MATTEO. « Sfruttare i Dati Sintetici per Migliorare la Comprensione del Comportamento Umano ». Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2021. http://hdl.handle.net/11380/1239978.
Texte intégralMost recent Deep Learning techniques require large volumes of training data in order to achieve human-like performance. Especially in Computer Vision, datasets are expensive to create because they usually require a considerable manual effort that can not be automated. Indeed, manual annotation is error-prone, inconsistent for subjective tasks (e.g. age classification), and not applicable to particular data (e.g. high frame-rate videos). For some tasks, like pose estimation and tracking, an alternative to manual annotation implies the use of wearable sensors. However, this approach is not feasible under some circumstances (e.g. in crowded scenarios) since the need to wear sensors limits its application to controlled environments. To overcome all the aforementioned limitations, we collected a set of synthetic datasets exploiting a photorealistic videogame. By relying on a virtual simulator, the annotations are error-free and always consistent as there is no manual annotation involved. Moreover, our data is suitable for in-the-wild applications as it contains multiple scenarios and a high variety of people appearances. In addition, our datasets are privacy compliant as no real human was involved in the data acquisition. Leveraging this newly collected data, extensive studies have been conducted on a plethora of tasks. In particular, for 2D pose estimation and tracking, we propose a deep network architecture that jointly extracts people body parts and associates them across short temporal spans. Our model explicitly deals with occluded body parts, by hallucinating plausible solutions of not visible joints. For 3D pose estimation, we propose to use high-resolution volumetric heatmaps to model joint locations, devising a simple and effective compression method to drastically reduce the size of this representation. For attribute classification, we overcome a common problem in surveillance, namely people occlusion, by designing a network capable of hallucinating occluded people with a plausible aspect. From a more practical point of view, we design an edge-AI system capable of evaluating in real-time the COVID-19 contagion risk of a monitored area by analyzing video streams. As synthetic data might suffer domain-shift related problems, we further investigate image translation techniques for the tasks of head pose estimation, attribute recognition and face landmark localization.
Park, Joonam. « Development and Application of Probabilistic Decision Support Framework for Seismic Rehabilitation of Structural Systems ». Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4898.
Texte intégralLi, Gengxiang. « Rehaussement et détection des attributs sismiques 3D par techniques avancées d'analyse d'images ». Phd thesis, Université Michel de Montaigne - Bordeaux III, 2012. http://tel.archives-ouvertes.fr/tel-00731886.
Texte intégralTachfouti, Nabil. « Estimation de la mortalité attribuée au tabac au Maroc ». Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0382/document.
Texte intégralBackground : To establish the impact of tobacco smoking on mortality is essential to define and monitor public health interventions in developing countries. In Morocco, smoking prevalence has increased from 17.2% to 18.5% between 2000 and 2006. Moreover, no updated estimates are available on smoking attributable mortality (SAM). The aim of this study is to estimate the number of smoking attributable deaths in Morocco. Methods : The Smoking-Attributable Mortality, Morbidity and Economic Costs (SAMMEC) software was used to estimate the smoking attributable mortality for the year 2012. Smoking and ex-smoking prevalence’s of Moroccan’s aged 35 years or older were obtained from the national survey on tobacco “MARTA” data. Mortality data were drawn from the Mortality declaration registries in Casablanca region and extrapolated on Moroccan population. Results : Of total 36548 deaths recorded in Morocco in 2012 among person aged 35 years and older, 4359 were attributed to smoking in the three groups of selected causes; 3835 men’s and 524 women’s. Smoking accounted for 11.9% of all deaths; 18.3 % in men, and 3.4 % in women. Cancer was the most frequent cause, responsible for 50.7% (2112 deaths) of all smoking attributable deaths, followed by cardiovascular diseases (30.7%:1338 deaths) and respiratory diseases (19.6%: 864 deaths). Conclusion : Tobacco use caused one out of five male deaths. Four leading causes (lung cancer, ischemic heart disease, cerebrovascular disease and chronic airways obstruction) accounted for for 64.2% of all SAM; 65.0% among men and 61.6% among women’s. Overall, there is still a 5 high burden of tobacco-related deaths in Germany which leads to considerable costs for the German health system and economy. Effective and comprehensive actions must be taken in order to slow this epidemic in Morocco
Hammoud, Wissam. « Attributes effecting software testing estimation ; is organizational trust an issue ? » Thesis, University of Phoenix, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3583478.
Texte intégralThis quantitative correlational research explored the potential association between the levels of organizational trust and the software testing estimation. This was conducted by exploring the relationships between organizational trust, tester’s expertise, organizational technology used, and the number of hours, number of testers, and time-coding estimated by the software testers. The research conducted on a software testing department of a health insurance organization, employed the use of the Organizational Trust Inventory- Short Form (OTI-SF) developed by Philip Bromiley and Larry Cummings and revealed a strong relationship between organizational trust and software testing estimation. The research reviews historical theories of organizational trust and include a deep discussion about software testing practices and software testing estimation. By examining the significant impact of organizational trust on project estimating and time-coding in this research, software testing leaders can benefit from this research to improve project planning and managing process by improving the levels of trust within their organizations.
Qiu, Xuchong. « 2D and 3D Geometric Attributes Estimation in Images via deep learning ». Thesis, Marne-la-vallée, ENPC, 2021. http://www.theses.fr/2021ENPC0005.
Texte intégralThe visual perception of 2D and 3D geometric attributes (e.g. translation, rotation, spatial size and etc.) is important in robotic applications. It helps robotic system build knowledge about its surrounding environment and can serve as the input for down-stream tasks such as motion planning and physical intersection with objects.The main goal of this thesis is to automatically detect positions and poses of interested objects for robotic manipulation tasks. In particular, we are interested in the low-level task of estimating occlusion relationship to discriminate different objects and the high-level tasks of object visual tracking and object pose estimation.The first focus is to track the object of interest with correct locations and sizes in a given video. We first study systematically the tracking framework based on discriminative correlation filter (DCF) and propose to leverage semantics information in two tracking stages: the visual feature encoding stage and the target localization stage. Our experiments demonstrate that the involvement of semantics improves the performance of both localization and size estimation in our DCF-based tracking framework. We also make an analysis for failure cases.The second focus is using object shape information to improve the performance of object 6D pose estimation and do object pose refinement. We propose to estimate the 2D projections of object 3D surface points with deep models to recover object 6D poses. Our results show that the proposed method benefits from the large number of 3D-to-2D point correspondences and achieves better performance. As a second part, we study the constraints of existing object pose refinement methods and develop a pose refinement method for objects in the wild. Our experiments demonstrate that our models trained on either real data or generated synthetic data can refine pose estimates for objects in the wild, even though these objects are not seen during training.The third focus is studying geometric occlusion in single images to better discriminate objects in the scene. We first formalize geometric occlusion definition and propose a method to automatically generate high-quality occlusion annotations. Then we propose a new occlusion relationship formulation (i.e. abbnom) and the corresponding inference method. Experiments on occlusion reasoning benchmarks demonstrate the superiority of the proposed formulation and method. To recover accurate depth discontinuities, we also propose a depth map refinement method and a single-stage monocular depth estimation method.All the methods that we propose leverage on the versatility and power of deep learning. This should facilitate their integration in the visual perception module of modern robotic systems.Besides the above methodological advances, we also made available software (for occlusion and pose estimation) and datasets (of high-quality occlusion information) as a contribution to the scientific community
Tiemeni, Ghislaine Livie Ngangom. « Performance estimation of wireless networks using traffic generation and monitoring on a mobile device ». University of the Western Cape, 2015. http://hdl.handle.net/11394/4777.
Texte intégral>Magister Scientiae - MSc
LIMA, LUIZ ALBERTO BARBOSA DE. « POROSITY ESTIMATION FROM SEISMIC ATTRIBUTES WITH SIMULTANEOUS CLASSIFICATION OF SPATIALLY STRUCTURED LATENT FACIES ». PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33718@1.
Texte intégralPredição de porosidade em reservatórios de óleo e gás representa em uma tarefa crucial e desafiadora na indústria de petróleo. Neste trabalho é proposto um novo modelo não-linear para predição de porosidade que trata fácies sedimentares como variáveis ocultas ou latentes. Esse modelo, denominado Transductive Conditional Random Field Regression (TCRFR), combina com sucesso os conceitos de Markov random fields, ridge regression e aprendizado transdutivo. O modelo utiliza volumes de impedância sísmica como informação de entrada condicionada aos valores de porosidade disponíveis nos poços existentes no reservatório e realiza de forma simultânea e automática a classificação das fácies e a estimativa de porosidade em todo o volume. O método é capaz de inferir as fácies latentes através da combinação de amostras precisas de porosidade local presentes nos poços com dados de impedância sísmica ruidosos, porém disponíveis em todo o volume do reservatório. A informação precisa de porosidade é propagada no volume através de modelos probabilísticos baseados em grafos, utilizando conditional random fields. Adicionalmente, duas novas técnicas são introduzidas como etapas de pré-processamento para aplicação do método TCRFR nos casos extremos em que somente um número bastante reduzido de amostras rotuladas de porosidade encontra-se disponível em um pequeno conjunto de poços exploratórios, uma situação típica para geólogos durante a fase exploratória de uma nova área. São realizados experimentos utilizando dados de um reservatório sintético e de um reservatório real. Os resultados comprovam que o método apresenta um desempenho consideravelmente superior a outros métodos automáticos de predição em relação aos dados sintéticos e, em relação aos dados reais, um desempenho comparável ao gerado por técnicas tradicionais de geo estatística que demandam grande esforço manual por parte de especialistas.
Estimating porosity in oil and gas reservoirs is a crucial and challenging task in the oil industry. A novel nonlinear model for porosity estimation is proposed, which handles sedimentary facies as latent variables. It successfully combines the concepts of conditional random fields (CRFs), transductive learning and ridge regression. The proposed Transductive Conditional Random Field Regression (TCRFR) uses seismic impedance volumes as input information, conditioned on the porosity values from the available wells in the reservoir, and simultaneously and automatically provides as output the porosity estimation and facies classification in the whole volume. The method is able to infer the latent facies states by combining the local, labeled and accurate porosity information available at well locations with the plentiful but imprecise impedance information available everywhere in the reservoir volume. That accurate information is propagated in the reservoir based on conditional random field probabilistic graphical models, greatly reducing uncertainty. In addition, two new techniques are introduced as preprocessing steps for the application of TCRFR in the extreme but realistic cases where just a scarce amount of porosity labeled samples are available in a few exploratory wells, a typical situation for geologists during the evaluation of a reservoir in the exploration phase. Both synthetic and real-world data experiments are presented to prove the usefulness of the proposed methodology, which show that it outperforms previous automatic estimation methods on synthetic data and provides a comparable result to the traditional manual labored geostatistics approach on real-world data.
Parianos, John Michael. « Geology of the Clarion-Clipperton Zone : fundamental attributes in polymetallic nodule resource development ». Doctoral thesis, Universidade de Évora, 2021. http://hdl.handle.net/10174/31069.
Texte intégralPike, Quinton David. « Empirical estimation of attributes influencing warehouse/distribution center operations an in-depth analysis of the Washington warehouse industry / ». Online access for everyone, 2005. http://www.dissertations.wsu.edu/Thesis/Spring2005/q%5Fpike%5F050605.pdf.
Texte intégralJimenez, Laura. « Estimating the Reliability of Concept Map Ratings Using a Scoring Rubric Based on Three Attributes ». BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2284.
Texte intégralGolinkoff, Jordan Seth. « Estimation and modeling of forest attributes across large spatial scales using BiomeBGC, high-resolution imagery, LiDAR data, and inventory data ». Thesis, University of Montana, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3568103.
Texte intégralThe accurate estimation of forest attributes at many different spatial scales is a critical problem. Forest landowners may be interested in estimating timber volume, forest biomass, and forest structure to determine their forest's condition and value. Counties and states may be interested to learn about their forests to develop sustainable management plans and policies related to forests, wildlife, and climate change. Countries and consortiums of countries need information about their forests to set global and national targets to deal with issues of climate change and deforestation as well as to set national targets and understand the state of their forest at a given point in time.
This dissertation approaches these questions from two perspectives. The first perspective uses the process model Biome-BGC paired with inventory and remote sensing data to make inferences about a current forest state given known climate and site variables. Using a model of this type, future climate data can be used to make predictions about future forest states as well. An example of this work applied to a forest in northern California is presented. The second perspective of estimating forest attributes uses high resolution aerial imagery paired with light detection and ranging (LiDAR) remote sensing data to develop statistical estimates of forest structure. Two approaches within this perspective are presented: a pixel based approach and an object based approach. Both approaches can serve as the platform on which models (either empirical growth and yield models or process models) can be run to generate inferences about future forest state and current forest biogeochemical cycling.
Benelli, Alessandro <1978>. « Hyperspectral imaging and other optical techniques for (in-field/in-lab) physico-chemical attributes estimation of agri-food vegetal products ». Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10429/1/Benelli_Alessandro_PhD_Thesis.pdf.
Texte intégralPeduzzi, Alicia. « Estimating forest attributes using laser scanning data and dual-band, single-pass interferometric aperture radar to improve forest management ». Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/39456.
Texte intégralPh. D.
Meurer, Ismael. « Estudo de diferentes métodos na estimativa da curva de retenção da água no solo ». Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/11/11140/tde-05052014-102750/.
Texte intégralSoil provides support and acts as a water reservoir to plants, promoting essential conditions to root growth and to water and nutrient dynamics. The understanding of its hydraulic properties, like the water retention curve, is of great importance for the description and prediction of the processes of water and solute transport. The objective of this study was to determine soil water retention curve through the traditional method using porous plate funnel and pressure chamber, through the field method using tensiometers and through the water evaporation in soil sample with tensiometer in the laboratory. The studied soil was classified as clayey Rhodic Hapludox, which had been cultivated with coffee for more than 10 years. The comparison of curves obtained through the three methods indicated that the evaporation method was statistically different from the method using funnel and chamber, and statistically equal to the method of tensiometers at field. For its easy execution, low cost and quickness to determine soil water retention curve until the tension of about 100 kPa, the evaportation method presented here is a feasible option. As for the method of tensiometers at field, although it is more realistic, it is very laborious.
Fisher, Geoffrey W. « Value Estimation and Comparison in Multi-Attribute Choice ». Thesis, 2015. https://thesis.library.caltech.edu/8862/1/Fisher_Geoffrey_2015_thesis.pdf.
Texte intégralThe following work explores the processes individuals utilize when making multi-attribute choices. With the exception of extremely simple or familiar choices, most decisions we face can be classified as multi-attribute choices. In order to evaluate and make choices in such an environment, we must be able to estimate and weight the particular attributes of an option. Hence, better understanding the mechanisms involved in this process is an important step for economists and psychologists. For example, when choosing between two meals that differ in taste and nutrition, what are the mechanisms that allow us to estimate and then weight attributes when constructing value? Furthermore, how can these mechanisms be influenced by variables such as attention or common physiological states, like hunger?
In order to investigate these and similar questions, we use a combination of choice and attentional data, where the attentional data was collected by recording eye movements as individuals made decisions. Chapter 1 designs and tests a neuroeconomic model of multi-attribute choice that makes predictions about choices, response time, and how these variables are correlated with attention. Chapter 2 applies the ideas in this model to intertemporal decision-making, and finds that attention causally affects discount rates. Chapter 3 explores how hunger, a common physiological state, alters the mechanisms we utilize as we make simple decisions about foods.
Hsieh, Hui-Lan, et 謝蕙蘭. « Multi-task Learning for Face Recognition and Attribute Estimation ». Thesis, 2016. http://ndltd.ncl.edu.tw/handle/35301995068739966019.
Texte intégral國立臺灣大學
資訊網路與多媒體研究所
104
Convolution neural network (CNN) has been shown as the state-of-the-art approach for learning face representations in recent years. However, previous works only utilized identity information instead of leveraging human attributes (e.g., gender and age) which contain high-level semantic meanings to learn robuster features. In this work, we aim to learn discriminative features to improve face recognition through multi-task learning with human attributes. Specifically, we focus on simultaneously optimizing face recognition and human attributes estimation. In our experiments, we learn face representation by training the largest publicly face dataset CASIA-WebFace with gender and age label, and then evaluate learned features on widely-used LFW benchmark for face verification and identification. We also compare the effectiveness of different attributes for identification. The results show that the proposed model outperforms hand-crafted feature such as high-dimensional LBP, and human attributes really provide useful semantic cues. We also do experiments on gender and age estimation on Adience benchmark to justify that human attribute prediction can also benefit from rich identity information.
DI, FINA DARIO. « Multi-Target Tracking and Facial Attribute Estimation in Smart Environments ». Doctoral thesis, 2016. http://hdl.handle.net/2158/1029030.
Texte intégral(7484339), Fu-Chen Chen. « Deep Learning Studies for Vision-based Condition Assessment and Attribute Estimation of Civil Infrastructure Systems ». Thesis, 2021.
Trouver le texte intégralYaghoubi, Ehsan. « Soft Biometric Analysis : MultiPerson and RealTime Pedestrian Attribute Recognition in Crowded Urban Environments ». Doctoral thesis, 2021. http://hdl.handle.net/10400.6/12081.
Texte intégralThis thesis was prepared at the University of Beria Interior, IT Instituto de Telecomunicações, Soft Computing and Image Analysis Laboratory (SOCIA Lab), Covilhã Delegation, and was submitted to the University of Beira Interior for defense in a public examination session.
Gould, Gregory M. « A spatial analysis of passenger vehicle attributes, environmental impact and policy / ». 2006. http://www.library.umaine.edu/theses/pdf/GouldGM2006.pdf.
Texte intégralZhou, Jiawen. « Estimating attribute-based reliability in cognitive diagnostic assessment ». Phd thesis, 2010. http://hdl.handle.net/10048/1052.
Texte intégral"A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Measurement, Evaluation and Cognition, Department of Educational Psychology, University of Alberta." Title from pdf file main screen (viewed on May 19, 2010) Includes bibliographical references.
Čabaravdić, Azra [Verfasser]. « Efficient estimation of forest attributes with k NN / vorgelegt von Azra Čabaravdić ». 2007. http://d-nb.info/985124164/34.
Texte intégralWu, Wen-sheng, et 吳文盛. « Applying Attribute Values Partitioning and GA Clustering Technique for Estimating Missing Values ». Thesis, 2009. http://ndltd.ncl.edu.tw/handle/68591033503377203601.
Texte intégral南華大學
資訊管理學系碩士班
97
Data mining is a vitally important technique to uncover hidden information from a set of raw data. The managers can exploit the mining results to make effective decisions. However, missing data significantly distort data mining results. Therefore, data preprocessing of missing values is very critical in successful data mining. Data clustering techniques is the partitioning of a dataset into subsets so that the data in each subset share common pattern. The shared pattern can be utilized to estimate the missing values. In this study, we propose an attribute values partitioning technique to preserve the relationships between attributes for estimating missing values. In addition, genetic algorithm is a powerful population-based stochastic search process for finding the robust clustering result. Therefore, we also propose a genetic clustering-based approach to estimate the missing data. Furthermore, we integrate the attribute values partitioning with the genetic clustering techniques to improve the estimation performance. Effectiveness of the proposed approaches is demonstrated on four datasets for four different rates of missing data. The empirical evaluation shows the integrated missing data processing approach provides competitive results or performs well compared with the existing methods.
Peng, Shu-Ya, et 彭書亞. « The Effect of Firm-Level Attributes Using Market-Share Estimation Based on Aggregate Data ». Thesis, 2019. http://ndltd.ncl.edu.tw/handle/zb4tvf.
Texte intégral國立臺灣大學
商學研究所
107
This study explores the impact of different firm-level variables on the consumer utility and market share. We introduce the BLP model to analyze the consumers utility and further convert them into market share. And then, we select firms and variables from the dataset to conduct the empirical study. We modify the BLP model due to encountering the problem of parameter divergence. After modification, we obtain precise prediction and discover that product margin is the key factor to influence the market share of a firm.
Dutton, Jennifer Michelle. « Estimating the value of brand and attributes for retail fresh beef products ». 2007. http://digital.library.okstate.edu/etd/umi-okstate-2342.pdf.
Texte intégralLi, Wen-Chun, et 李文鈞. « Estimating the House Economic Values of Cultural Heritage Attributes in Tainan City ». Thesis, 2015. http://ndltd.ncl.edu.tw/handle/94203200110328128681.
Texte intégral國立東華大學
社會學系
103
A historic site shows different times in a space through history reflecting social values, economic situations, and cultural background of a particular period. Base on Tourism increases, protection and managing of cultural heritage have now become the focal point of our society. Due to manpower, time and fund, Economic Evaluation of cultural goods and services have become an increasingly important hot topic in the world. These public goods properties of cultural goods and services have a great contribution to social welfare, therefore government always by remit taxation or financial support to help grow national cultural heritage organization. In this study, the research scope of Tainan, the application of hedonic price method combined with geographic information systems (Geographic Information Systems, GIS) construct a cultural monument features covering property prices evaluation model, determined the structure of variable housing sample points (such as housing age, buildings transferred a total area and buildings pattern, etc.), monuments external variables (such as estimates Boroughs Housing sample points to national historic site, the actual distance of the city historic site and various monuments classified) and monuments feature variables (such as country houses set around Collocation, given the number of city monuments and various categories of monuments, etc.), further use of regression analysis Collocation factors affecting prices Tainan explore monuments and features external variables affect the relationship between prices of Tainan City, Tainan monuments to further assess the characteristics of the impact on the price of the marginal value. Above all we applied geographic information systems (Geographic Information Systems, the following called GIS) with spatial scales and historic characteristics to integrate and analyze the data of preservation of cultural assets, then according to those data link connect to land administration, urban planning and cultural heritage preservation planning. Apply the characteristics of the value of cultural relics to cultural budget, preservation of cultural assets and heritage management will implement progressively. The development of cultural relic’s sustainable preservation and use will decide on its course after overall considerations.
« The estimation of Eucalyptus plantation forest structural attributes using medium and high spatial resolution satellite imagery ». Thesis, 2008. http://hdl.handle.net/10413/354.
Texte intégralThesis (Ph.D.) - University of KwaZulu-Natal, Pietermaritzburg, 2008.
Pierson, Margaret Parker. « Price competition and the impact of service attributes : Structural estimation and analytical characterizations of equilibrium behavior ». Thesis, 2012. https://doi.org/10.7916/D89029WZ.
Texte intégralCheng, Wen-chieh, et 鄭文傑. « Estimating Cyclist’s Preference on Service Attributes of Special Green Trains:Heterogeneity by Recreation Specialization ». Thesis, 2009. http://ndltd.ncl.edu.tw/handle/48909192763403472122.
Texte intégral國立成功大學
交通管理學系碩博士班
97
Bicycle tourism is an increasingly important mode during vacation. However, the mobility of bicycle tourism will be affected by the remoteness from the departure to the end of the destination, so a reciprocal utilizing of bicycle and train becomes a type of new travel way. This kind of special green train is a new service for cyclist in Taiwan. Therefore, understanding cyclists’ preference in terms of green train service attributes can provide insightful information for managerial policy-making planning. The objective of this study is to valuate of cyclist’s preference and their willingness to pay for hypothetical managerial developments of the special green train service attributes, as well, to evaluate how segment of recreation specialization level of cyclists affects the different preference of service attributes. The results indicate that within baggage area, fixed frame with special area, space for bicycle and people in same carriage, and frequency exhibit a statistically significant effect on choice probability. The negative coefficient of price indicates that the increasing levels of fares lead to a negative effect on utility and reduce the choice probability. This result fluctuation indicates that high recreation specialization cyclists and low recreation specialization cyclists demonstrate preference differences in service attributes among these two segments.
Tzi-Li, Chang, et 張自立. « A Study of Estimating Comprehensive National Power Using Data Envelope Analysis and Fuzzy Multiple Attribute Decision Making ». Thesis, 2001. http://ndltd.ncl.edu.tw/handle/35829483962529977690.
Texte intégral國防管理學院
資源管理研究所
89
There are many methods, including Index Method, Analytic Hierarchy Process and Delphi Method(FMADM)etc, for evaluating a national Comprehensive National Power(CNP). Some methods describe with qualitative modes, the others quantify with mathematical modes. Among those evaluating methods, there are different viewpoint, explanation, advantages and disadvantages. In the evaluation of CNP, we need to consider its property of multi-input and multi-output and multiple attribute involving incomplete messages. The purpose of this study is to solve the difficulties of the evaluating multi-input and multi-output and multiple attribute involving incomplete messages. Hence, in this research ,the factors for evaluating CNP are selected in accordance with the related reference and expert’s opinion on the basis of grounded theory, and the evaluation procedures for the CNP system in two stages should be suggested as follows:(1)we should apply Data Envelopment Analysis(DEA)to obtain relative efficiency among different national CPN, and sift more relative efficiency ones out..(2)we should apply Fuzzy Multiple Attribute Decision Making(FMADM)to solve such problems as incapable of quantification, incomplete messages, vague conception, for example, politics, economy, science and technology, military, and so on. The main contribution of this research states as below: (1)By means of consulting literatures and expert interviews on the basis of grounded theory, measuring criterion of evaluating CNP and conception of forming those criterion. (2)This research integrates related theories, considering that evaluating factors of a national CNP system should be human resources, natural resources, science and technology, domestic economy, business management, internationalization, government, infrastructure, defense capability. (3)This research compare six main national CNP ordering, creating a new and simple mode measuring national CNP by using DEA and FMADM methods
(6949067), Aaron J. Staples. « Consumer Willingness-to-Pay for Sustainability Attributes in Beer : A Choice Experiment Using Eco-Labels ». Thesis, 2019.
Trouver le texte intégralCommercial and regional brewers are increasingly investing in sustainability equipment that reduces input use, operating costs, and environmental impact. These technologies often require significant upfront costs that can limit market access to microbreweries. One potential solution for these brewers is to market their product as sustainable and charge a premium for their product to offset some of the costs. A stated preference choice experiment of a nationally-representative sample is undertaken to elicit consumer willingness-to-pay (WTP) for sustainability attributes in beer, thus determining whether a market for sustainably-made beer exists. The facets of sustainability, including water reduction, energy reduction, and landfill diversion, are portrayed through eco-labels affixed the front of the primary packaging (aluminum can or glass bottle). Multiple specifications are employed to handle model shortcomings and incorporate discrete heterogeneity. Across all model specifications, consumers show a positive and statistically significant marginal WTP for landfill diversion practices and carbon reduction practices, ranging from $0.40 to $1.37 per six-pack and $0.67 to $1.21 per six-pack, respectively. These results indicate consumers do in fact place value on beer produced using sustainable practices, and the demographics of consumers with the greatest WTP are similar to that of craft beer consumer.