Дисертації з теми "Distance-based measure"
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Rogers, Wendy Laurel. "A Mahalanobis-distance-based image segmentation error measure with applications in automated microscopy /." Thesis, McGill University, 1985. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66025.
Повний текст джерелаNordström, Markus. "Automatic Source Code Classification : Classifying Source Code for a Case-Based Reasoning System." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-25519.
Повний текст джерелаGashayija, Jean Marie. "Image classification, storage and retrieval system for a 3 u cubesat." Thesis, Cape Peninsula University of Technology, 2014. http://hdl.handle.net/20.500.11838/1189.
Повний текст джерелаSmall satellites, such as CubeSats are mainly utilized for space and earth imaging missions. Imaging CubeSats are equipped with high resolution cameras for the capturing of digital images, as well as mass storage devices for storing the images. The captured images are transmitted to the ground station and subsequently stored in a database. The main problem with stored images in a large image database, identified by researchers and developers within the last number of years, is the retrieval of precise, clear images and overcoming the semantic gap. The semantic gap relates to the lack of correlation between the semantic categories the user requires and the low level features that a content-based image retrieval system offers. Clear images are needed to be usable for applications such as mapping, disaster monitoring and town planning. The main objective of this thesis is the design and development of an image classification, storage and retrieval system for a CubeSat. This system enables efficient classification, storing and retrieval of images that are received on a daily basis from an in-orbit CubeSat. In order to propose such a system, a specific research methodology was chosen and adopted. This entails extensive literature reviews on image classification techniques and image feature extraction techniques, to extract content embedded within an image, and include studies on image database systems, data mining techniques and image retrieval techniques. The literature study led to a requirement analysis followed by the analyses of software development models in order to design the system. The proposed design entails classifying images using content embedded in the image and also extracting image metadata such as date and time. Specific features extraction techniques are needed to extract required content and metadata. In order to achieve extraction of information embedded in the image, colour feature (colour histogram), shape feature (Mathematical Morphology) and texture feature (GLCM) techniques were used. Other major contributions of this project include a graphical user interface which enables users to search for similar images against those stored in the database. An automatic image extractor algorithm was also designed to classify images according to date and time, and colour, texture and shape features extractor techniques were proposed. These ensured that when a user wishes to query the database, the shape objects, colour quantities and contrast contained in an image are extracted and compared to those stored in the database. Implementation and test results concluded that the designed system is able to categorize images automatically and at the same time provide efficient and accurate results. The features extracted for each image depend on colour, shape and texture methods. Optimal values were also incorporated in order to reduce retrieval times. The mathematical morphological technique was used to compute shape objects using erosion and dilation operators, and the co-occurrence matrix was used to compute the texture feature of the image.
Suñé, Socias Víctor Manuel. "Failure distance based bounds of dependability measures." Doctoral thesis, Universitat Politècnica de Catalunya, 2000. http://hdl.handle.net/10803/6375.
Повний текст джерелаEls sistemes considerats a la tesi es conceptualitzen com formats per components (hardware o software) que fallen i, en el cas de sistemes reparables, són reparats. Els components s'agrupen en classes de forma que els components d'una mateixa classe són indistingibles. Per tant, un component és considerat com a una instància d'una classe de components i el sistema inclou un bag de classes de components definit sobre un cert domini. L'estat no fallada/fallada del sistema es determina a partir de l'estat no fallada/fallada dels components mitjançant una funció d'estructura coherent que s'especifica amb un arbre de fallades amb classes d'esdeveniments bàsics. (Una classe d'esdeveniment bàsic és la fallada d'un component d'una classe de components.)
La classe de models basats en CMTC considerada a la tesi és força àmplia i permet, per exemple, de modelar el fet que un component pot tenir diversos modes de fallada. També permet de modelar fallades de cobertura mitjançant la introducció de components ficticis que no fallen per ells mateixos i als quals es propaguen les fallades d'altres components. En el cas de sistemes reparables, la classe de models considerada admet polítiques de reparació complexes (per exemple, nombre limitat de reparadors, prioritats, inhibició de reparació) així com reparació en grup (reparació simultània de diversos components). Tanmateix, no és possible de modelar la reparació diferida (és a dir, el fet de diferir la reparació d'un component fins que una certa condició es compleixi).
A la tesi es consideren dues mesures de confiabilitat: la no fiabilitat en un instant de temps donat en el cas de sistemes no reparables i la no disponibilitat en règim estacionari en el cas sistemes reparables.
Els mètodes de fitació desenvolupats a la tesi es basen en el concepte de "distància a la fallada", que es defineix com el nombre mínim de components que han de fallar a més dels que ja han fallat per fer que el sistema falli.
A la tesi es desenvolupen quatre mètodes de fitació. El primer mètode dóna fites per a la no fiabilitat de sistemes no reparables emprant distàncies a la fallada exactes. Aquestes distàncies es calculen usant el conjunt de talls mínims de la funció d'estructura del sistema. El conjunt de talls mínims s'obté amb un algorisme desenvolupat a la tesi que obté els talls mínims per a arbres de fallades amb classes d'esdeveniments bàsics. El segon mètode dóna fites per a la no fiabilitat usant fites inferiors per a les distàncies a la fallada. Aquestes fites inferiors s'obtenen analitzant l'arbre de fallades del sistema, no requereixen de conèixer el conjunt de talls mínims i el seu càlcul és poc costós. El tercer mètode dóna fites per a la no disponibilitat en règim estacionari de sistemes reparables emprant distàncies a la fallada exactes. El quart mètode dóna fites per a la no disponibilitat en règim estacionari emprant les fites inferiors per a les distàncies a la fallada.
Finalment, s'il·lustren les prestacions de cada mètode usant diversos exemples. La conclusió és que cada un dels mètodes pot funcionar molt millor que altres mètodes prèviament existents i estendre de forma significativa la complexitat de sistemes tolerants a fallades per als quals és possible de calcular fites ajustades per a la no fiabilitat o la no disponibilitat en règim estacionari.
The subject of this dissertation is the development of bounding methods for a class of continuous-time Markov chain (CTMC) dependability models of fault-tolerant systems.
The systems considered in the dissertation are conceptualized as made up of components (hardware or software) that fail and, for repairable systems, are repaired. Components are grouped into classes, the components of the same class being indistinguishable. Thus, a component is regarded as an instance of some component class and the system includes a bag of component classes defined over a certain domain. The up/down state of the system is determined from the unfailed/failed state of the components through a coherent structure function specified by a fault tree with basic event classes. (A basic event class is the failure of a component of a component class.)
The class of CTMC models considered in the dissertation is quite wide and allows, for instance, to model the fact that a component may have different failure modes. It also allows to model coverage failures by means of introducing fictitious components that do not fail by themselves and to which uncovered failures of other components are propagated. In the case of repairable systems, the considered class of models supports very complex repair policies (e.g., limited repairpersons, priorities, repair preemption) as well as group repair (i.e., simultaneous repair of several components). However, deferred repair (i.e., the deferring of repair until some condition is met) is not allowed.
Two dependability measures are considered in the dissertation: the unreliability at a given time epoch for non-repairable systems and the steady-state unavailability for repairable systems.
The bounding methods developed in the dissertation are based on the concept of "failure distance from a state," which is defined as the minimum number of components that have to fail in addition to those already failed to take the system down.
We develop four bounding methods. The first method gives bounds for the unreliability of non-repairable fault-tolerant systems using (exact) failure distances. Those distances are computed using the set of minimal cuts of the structure function of the system. The set of minimal cuts is obtained using an algorithm developed in the dissertation that obtains the minimal cuts for fault trees with basic event classes. The second method gives bounds for the unreliability using easily computable lower bounds for failure distances. Those lower bounds are obtained analyzing the fault tree of the system and do not require the knowledge of the set of minimal cuts. The third method gives bounds for the steady-state unavailability using (exact) failure distances. The fourth method gives bounds for the steady-state unavailability using the lower bounds for failure distances.
Finally, the performance of each method is illustrated by means of several large examples. We conclude that the methods can outperform significantly previously existing methods and extend significantly the complexity of the fault-tolerant systems for which tight bounds for the unreliability or steady-state unavailability can be computed.
Goussakov, Roma. "Hellinger Distance-based Similarity Measures for Recommender Systems." Thesis, Umeå universitet, Statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172385.
Повний текст джерелаDey, Rajarshi. "Inference for the K-sample problem based on precedence probabilities." Diss., Kansas State University, 2011. http://hdl.handle.net/2097/12000.
Повний текст джерелаDepartment of Statistics
Paul I. Nelson
Rank based inference using independent random samples to compare K>1 continuous distributions, called the K-sample problem, based on precedence probabilities is developed and explored. There are many parametric and nonparametric approaches, most dealing with hypothesis testing, to this important, classical problem. Most existing tests are designed to detect differences among the location parameters of different distributions. Best known and most widely used of these is the F- test, which assumes normality. A comparable nonparametric test was developed by Kruskal and Wallis (1952). When dealing with location-scale families of distributions, both of these tests can perform poorly if the differences among the distributions are among their scale parameters and not in their location parameters. Overall, existing tests are not effective in detecting changes in both location and scale. In this dissertation, I propose a new class of rank-based, asymptotically distribution- free tests that are effective in detecting changes in both location and scale based on precedence probabilities. Let X_{i} be a random variable with distribution function F_{i} ; Also, let _pi_ be the set of all permutations of the numbers (1,2,...,K) . Then P(X_{i_{1}}<...
Sooful, Jayren Jugpal. "Automated phoneme mapping for cross-language speech recognition." Diss., Pretoria [s.n.], 2004. http://upetd.up.ac.za/thesis/available/etd-01112005-131128.
Повний текст джерелаLin, Chia-Wen, and 林嘉文. "A Novel Content-Based Image Retrieval System Based on Distance Measure Approach." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/4m2xy9.
Повний текст джерела國立臺中科技大學
資訊工程系碩士班
101
For the last two dacades, content-based image retrieval (CBIR) is a very popular topic in image processing area. Researchers aim to extract features of color, texture, shape or position information from an image and then via a distance measure method, they retrieve images most similar to the query image from a particular image database. A lot of content-based image retrieval methods have been proposed and the performance of each mothod has been demonstrated in each proposed paper. In this paper, we proposed a novel distance meature approach (re-rank,shorted as RRK) for CBIR system. First, we get the retrieved images from our simple CBIR system. Then we used these images to set reference feature. Finally, we retrieved again using the referenced feature and obtained more precise result. According to the experimental results, the proposed method is simple and efficient. Furthermore, the proposed method can be applied in other CBIR system easily.
Chiang, Cheng-Yuan, and 江正元. "Speaker Recognition with Independent Corpus Based on RM Distance Measure." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/9zur32.
Повний текст джерела淡江大學
電機工程學系碩士班
104
The speaker recognition is always a hot topic in the research field. Technologies of speaker recognition under white and color noisy environments have been proposed in recent years. Sparse representation algorithm has been introduced into noise filtering for improving the assessments of speech quality, such as SNR, SNRseg, LLR and PESQ, but the cost time is lengthy. So we employ Label Consistent K-SVD sparse coding (LC-KSVD) to de-noise speech data and decrease processing time. Speaker recognition systems almost use Euclidean distance to compute the distance between features, currently. Our goal is to have short corpus and independent corpus, which makes it more difficult to achieve high recognition accuracy. We propose Riemannian distance replace Euclidean distance, but our experimental results show that Euclidean distance is superior than Riemannian distance. We use waveform, MFCC and MFCC smoothing spectrum with RD and ED for speaker recognition experiment in this paper.
Liu, Kuan-Liang, and 劉冠良. "A Subset gene selection method based on clustering analysis and distance measure." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/40328330647012774931.
Повний текст джерела國立成功大學
資訊管理研究所
95
After the Human Genome Project, the next challenge for bio-researchers is to understand the meanings of genes and the inter-relationship between them. As the technique of gene expression microarray stores all the gene expression data in a tiny chip, researchers become able to analyze all expression data of genes simultaneously. Nevertheless, compared to the original statistic data, the huge dimensionality and comparatively few sample amounts of gene expression data are still research obstacles. The objective of this research is to screen a representative set of genes according to a specific problem. Although many gene selection methods have been proposed in recent years, problems, such as gene collinearity, lack of consideration for combination genes, and work complexity, are not thoroughly examined and worked out. The gene selection algorithm of this research is tailored to the problems mentioned above. We first distribute the whole data set of genes using density-based clustering technique and screen out genes that are similar and have comparatively lower individual gene rank values. Then we select and substitute combinative genes according to examination of distance measure value, , and cluster similarity index. Considering the characteristic of gene expression data, we introduce relation-based methods and measure similarity between genes. Coupled with the data of tumor classification, the algorithm proposed in this research is tested and the accuracy rate of classification was improved. The gene set of enhanced can really get a higher accuracy rate of classification. In addition, the accuracy rates of gene sets from our selection algorithm are better than the gene sets from individual gene ranking methods.
Meghdadi, Amir Hossein. "Fuzzy Tolerance Neighborhood Approach to Image Similarity in Content-based Image Retrieval." 2012. http://hdl.handle.net/1993/8094.
Повний текст джерелаMukhopadhyay, Sayan. "Variance of Difference as Distance Like Measure in Time Series Microarray Data Clustering." Thesis, 2014. http://etd.iisc.ernet.in/handle/2005/2986.
Повний текст джерелаGhobadi, Razieh. "Geostatistical modelling and simulation of karst systems." Thesis, 2016. http://hdl.handle.net/2440/103460.
Повний текст джерелаThesis (M.Phil.) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 2016.
Jabłoński, Jędrzej. "Structured population models for predator-prey interactions. The case of Daphnia and size selective planktivorous fish." Doctoral thesis, 2014.
Знайти повний текст джерелаSodabanlu, Sirawit. "A Likelihood Ratio Based Forensic Text Comparison with Multiple Types of Features." Master's thesis, 2021. http://hdl.handle.net/1885/262301.
Повний текст джерелаSegoe, Bobo Aaron. "Learner support in the provision of distance teaching programmes for under qualified teachers." Thesis, 2012. http://hdl.handle.net/10500/8559.
Повний текст джерелаCurriculum and Instructional Studies
D. Ed. (Didactics)