<p>Izmenama u konstrukciji vertikalne me&scaron;alice zamenom originalne obloge pužnice sa oblogama koje su imale 13,5%, 27% i 40% perforacija je pobolj&scaron;an proces me&scaron;anja. Ova pobolj&scaron;anja se ogledaju u skraćenju vremena me&scaron;anja 15%, 30% i 50% u odnosu na originalnu konstrukciju, smanjenju utro&scaron;ka rada i energije i otvaranja mogućnosti vraćanja ove vrste me&scaron;alica u masovniju upotrebu, jer su tro&scaron;kovi kupovine i održavanja ove vrste me&scaron;alica daleko niži u odnosu na druge. Izrađen je model sistem za cilindričnu me&scaron;alicu, na bazi primene teorije Markovljevog niza, kao pogodan način za predviđanje procesa me&scaron;anja u ovoj vrsti me&scaron;alica, čak i u industrijskim uslovima. Dobijeni rezultati<br />su pokazali slaganje sa eksperimentalno dobijenim rezultatima, pri čemu je utvrđeno vreme neophodno za postizanje homogenosti u cilindričnoj me&scaron;alici iznosilo 5 minuta za odnos me&scaron;anja 1:10.000, dok za odnos me&scaron;anja 1:100.000 i vreme od 5 minuta, homogenost nije postignuta Poređenjem rezultata programa za analizu slike, koji je prethodno razvijen u okviru metode Microtracer-a, sa ručno dobijenim rezultatima, utvrđen je visok stepen korelacije (R=0.995, 0.979 i 0.987) i ovaj program je ocenjen kao značajno pobolj&scaron;anje i skraćenje vremena potrebnog za dobijanje rezultata.</p> / <p>Changes in the construction of vertical mixers by replacement of the original screw barrel with barrel which had 13.5%, 27% and 40% perforation generally have improved process of mixing. These improvements are reflected in shortening the mixing time of 15%, 30% and 50% comparing to the original construction, reduction of labor and energy and create the possibility of returning these types of mixers in the more common, as the cost of purchasing and maintaining these types of mixers is far lower compared to others. A model system for the cylindrical mixer, based on the theory of Markov chain, as a convenient way to predict the mixing process in this type of mixer, even in industrial conditions. The results show agreement with experimental results, with a determined time necessary to achieve homogeneity in a cylindrical mixer was 5 minutes for mixing ratio 1:10,000, and more than 5 minutes for the mixing ratio 1:100,000. Comparing the results of program for image analysis, which was previously developed under a Microtracers methods with manually obtained results revealed a high degree of correlation (R = 0995, 0979 and 0987) and this program was rated as significantly improving and shortening the time needed to obtain results</p>

Monte Carlo light transport simulation has become a de-facto standard tool for photorealistic rendering. However, the algorithms used by the current rendering systems are often ineffective, especially in scenes featuring light transport due to multiple highly glossy or specular interactions and complex visibility between the camera and light sources. It is therefore desirable to adopt more robust algorithms in practice. Light transport algorithms based on Markov chain Monte Carlo (MCMC) are known to be effective at sampling many different kinds of light transport paths even in the presence of complex visibility. However, the current MCMC algorithms often over-sample some of the paths while under-sampling or completely missing other paths. We attribute this behavior to insufficient global exploration of path space which leads to their unpredictable convergence and causes the occurrence of image artifacts. This in turn prohibits adoption of MCMC algorithms in practice. In this thesis we therefore focus on improving global exploration in MCMC algorithms for light transport simulation. First, we present a new MCMC algorithm that utilizes replica exchange to improve global exploration. To maximize efficiency of replica exchange we introduce tempering of the path space, which allows easier discovery of important...

Les véhicules aériens sans pilote (UAVs), utilisés et développés pour la première fois dans le domaine militaire, ont connu de profonds changements ces dernières années et sont de plus en plus utilisés dans le domaine civil. Etant plus connus sous le nom des drones, ils sont le plus souvent utilisés dans les domaines civiles et militaires. Ils sont employés pour : la lutte contre les incendies, le sauvetage ainsi que dans des applications spécifiques comme la surveillance et l’attaque. Le vol en formation est de loin le plus utilisé car il permet une répartition judicieuse des tâches et améliore grandement l’efficacité des drones (principe de l’attaque en meute, des animaux carnassiers). Cela pose alors la problématique de la coordination et de la stratégie, ainsi que du type de fonctionnement (maitre/esclave,…).Le type et la qualité d’informations optimums restent aussi à définir.L'utilisation accrue de ces systèmes coopératifs dans des environnements dangereux rend leur fiabilité essentielle pour prévenir tout événement catastrophique. Une performance globale de la flotte des drones doit être garantie, malgré une possible dégradation des composants ou de toute modification du réseau et de l'environnement. Il est nécessaire de détecter les comportements anormaux pouvant contribuer aux collisions et ainsi affecter la mission. Compte tenu des performances et du coût, les systèmes à tolérance de pannes et à redondance ne représentent pas toujours la solution la plus efficace pour ce type de vol de flotte en formation. Différentes méthodes telles que l'analyse par arbre de défaillance (ADD), l'analyse des modes de défaillance, de leurs effets et de leurs criticités (AMDEC) ont été utilisées dans le monde des hélicoptères.Dans une première partie, une méthode statique basée sur l’ADD est proposée, pour assurer la fiabilité de la communication entre les drones d’un côté et entre les drones et la station de base de l’autre côté en accentuant l’échange de flux d’informations. Nous utilisons des arbres de défaillance pour représenter les différentes conditions d’erreur de ce système complexe.Dans une deuxième partie, nous analysons les différents états de défaillance des communications et leurs probabilités. Ce processus étant stochastique, une approche par chaîne de Markov absorbante est développée. L’approche proposée peut être utilisée pour trouver les scenarios les plus risqués et les éléments à prendre en compte pour améliorer la fiabilité.Enfin, dans une troisième partie, nous étudions le problème de réception des messages d’un drone en proposant un protocole basé sur le nombre de retransmissions. La réception est assurée avec une certaine probabilité de fiabilité, en fonction de plusieurs attributs tels que la modulation, le taux d’erreur des bits (BER) caractérisant les drones. / Unmanned aerial vehicles, used and developed initially in the military field, have experienced profound changes in recent years and are increasingly used in the civilian field. Recognized as drones, they are most often used in the civil and military domains. They are used for firefighting, rescue as well as in specific applications such as surveillance and attack. The formation flight is the most used because it allows a judicious distribution of the tasks and greatly improves the efficiency of the drones (principle of the attack in pack, carnivorous animals). This will raise the issue of coordination and strategy, as well as the type of operation (master /slave, ...). The type and quality of optimal information also remain to be defined.The increased use of these cooperative systems in hazardous environments makes their reliability essential to prevent any catastrophic event. Overall performance of the drone fleet should be ensured, despite possible degradation of components or any changes that occur to the network and the environment. It is necessary to detect the anomalous behaviors that might contribute to collisions and thus affect the mission. Taking into consideration performance and cost, the fault-tolerant system and redundant systems are not always the most efficient solution for the formation fleet flight. Different methods like the fault tree analysis (FTA), Failure Modes and Effects Analysis (FMEA) have been used in the helicopter field.In the first part, we propose a static method based on FTA, to ensure a successful communication between the drones from one side, and between the drones and the ground station from the other side by emphasizing on the exchange of information flows. It uses various fault trees to represent the different error conditions of this complex system.In the second part, we analyze the different fault states and their probabilities. As this process is stochastic, an absorbing Markov chain approach is developed. The proposed approach can be used to find the most risky scenarios and considerations for improving reliability.Finally, in the third part, we put the emphasis on the message receipt problem in a drone’s communication network by proposing a protocol based on number of retransmissions. The reception of a message is provided with a certain probability of reliability depending on several attributes such as modulation and bit error rate (BER) characterizing the UAVs.

The hidden state Markov (HSM) model is introduced as a new conceptual framework for modelling long-term persistence in hydrological time series. Unlike the stochastic models currently used, the conceptual basis of the HSM model can be related to the physical processes that influence long-term hydrological time series in the Australian climatic regime. A Bayesian approach was used for model calibration. This enabled rigourous evaluation of parameter uncertainty, which proved crucial for the interpretation of the results. Applying the single site HSM model to rainfall data from selected Australian capital cities provided some revealing insights. In eastern Australia, where there is a significant influence from the tropical Pacific weather systems, the results showed a weak wet and medium dry state persistence was likely to exist. In southern Australia the results were inconclusive. However, they suggested a weak wet and strong dry persistence structure may exist, possibly due to the infrequent incursion of tropical weather systems in southern Australia. This led to the postulate that the tropical weather systems are the primary cause of two-state long-term persistence. The single and multi-site HSM model results for the Warragamba catchment rainfall data supported this hypothesis. A strong two-state persistence structure was likely to exist in the rainfall regime of this important water supply catchment. In contrast, the single and multi-site results for the Williams River catchment rainfall data were inconsistent. This illustrates further work is required to understand the application of the HSM model. Comparisons with the lag-one autoregressive [AR(1)] model showed that it was not able to reproduce the same long-term persistence as the HSM model. However, with record lengths typical of real data the difference between the two approaches was not statistically significant. Nevertheless, it was concluded that the HSM model provides a conceptually richer framework than the AR(1) model. / PhD Doctorate

We consider a longitudinal system in which transitions between the states are governed by a discrete time finite state space stochastic process X. Our aim, using aggregated sample survey data of the form typically collected by official statistical agencies, is to undertake model based inference for the underlying process X. We will develop inferential techniques for continuing sample surveys of two distinct types. First, longitudinal surveys in which the same individuals are sampled in each cycle of the survey. Second, cross-sectional surveys which sample the same population in successive cycles but with no attempt to track particular individuals from one cycle to the next. Some of the basic results have appeared in Davis et al (2001) and Davis et al (2002).¶ Longitudinal surveys provide data in the form of transition frequencies between the states of X. In Chapter Two we develop a method for modelling and estimating the one-step transition probabilities in the case where X is a non-homogeneous Markov chain and transition frequencies are observed at unit time intervals. However, due to their expense, longitudinal surveys are typically conducted at widely, and sometimes irregularly, spaced time points. That is, the observable frequencies pertain to multi-step transitions. Continuing to assume the Markov property for X, in Chapter Three, we show that these multi-step transition frequencies can be stochastically interpolated to provide accurate estimates of the one-step transition probabilities of the underlying process. These estimates for a unit time increment can be used to calculate estimates of expected future occupation time, conditional on an individual’s state at initial point of observation, in the different states of X.¶ For reasons of cost, most statistical collections run by official agencies are cross-sectional sample surveys. The data observed from an on-going survey of this type are marginal frequencies in the states of X at a sequence of time points. In Chapter Four we develop a model based technique for estimating the marginal probabilities of X using data of this form. Note that, in contrast to the longitudinal case, the Markov assumption does not simplify inference based on marginal frequencies. The marginal probability estimates enable estimation of future occupation times (in each of the states of X) for an individual of unspecified initial state. However, in the applications of the technique that we discuss (see Sections 4.4 and 4.5) the estimated occupation times will be conditional on both gender and initial age of individuals.¶ The longitudinal data envisaged in Chapter Two is that obtained from the surveillance of the same sample in each cycle of an on-going survey. In practice, to preserve data quality it is necessary to control respondent burden using sample rotation. This is usually achieved using a mechanism known as rotation group sampling. In Chapter Five we consider the particular form of rotation group sampling used by the Australian Bureau of Statistics in their Monthly Labour Force Survey (from which official estimates of labour force participation rates are produced). We show that our approach to estimating the one-step transition probabilities of X from transition frequencies observed at incremental time intervals, developed in Chapter Two, can be modified to deal with data collected under this sample rotation scheme. Furthermore, we show that valid inference is possible even when the Markov property does not hold for the underlying process.

自Duncan在1956年提出管制圖的經濟設計以來,陸續有許多學者提出各種不同型態管制圖的經濟設計,但是在這些文章中,尚無將描點的連串檢定列入考慮者,然而在管制圖中加入描點的連串檢定實有其必要性,加入描點的連串檢定可增加管制圖的偵測能力,但是這種作法頗為麻煩,因此Jaehn(1987)提出了區域管制圖來取代傳統管制圖加上連串檢定的不便,本研究提出X Bar-S Square 區域管制圖的經濟設計以改善一般經濟管制圖未將描點的連串檢定列入考慮的缺點.我們以製程中各項製程和成本資料為因子,對經濟區域管制圖的最佳設計參數值做敏感度分析,以找出製程中的關鍵參數.另外我們應用Saniga(1989)經濟統計管制圖的觀念設計經濟統計區域管制圖.雖然經濟統計區域管制圖所計算出的成本會比經濟區域管制圖稍大,但是在統計表現上卻符合我們的要求.

使用管制圖追蹤品質特性在製造過程中的變異前，使用者應先決定管制圖 的設計參數值 (Design Parameters) ， 如樣本大小、抽樣時間間隔，及 管制界限寬度等。當已知每次抽樣的樣本大小大於 10 ，且非隨機因素 (Assignable Causes) 的發生只會使製程變異增大時，則 S 管制圖應被 選用來追蹤製程是否穩定。 S 管制圖的經濟設計，首由 Collani 及 Sheil(1989) 提出，文中他們只考慮單一非隨機因素的情形。唯實務上， 製程常同時受多重非隨機困素的影響。為使製程模式假設更合理，使用更 有彈性，我們先將多重非隨機因素製程表示為更新過程 (Renewal Processes) ， 其中每個更新循環 (Renewal Cycles) 則表示為馬可夫過 程 (Markov Process) 。 接著，以 S 管制圖追蹤的製程平均循環時間 (The Expected Cycle Time) 及平均循環成本 (The Expected Cycle Cost)應用馬可夫性質可容易的推導出。最後，目標函數可利用更新報酬 過程 (Renewal Reward Processes) 性質獲得。 由於目標函數是設計參 數之函數， 因此藉著最佳化目標函數， S管制圖之最適設計參數值可被 決定。由針對一個特例所做的變異數分析及回應圖分析結果，我們可決定 重要製程與成本參數，這些參數的了解可做為決策者決策上的參考。另外 ， S 經濟管制圖所發生的品質成本遠比傳統 S 管制圖的小,而在製程失 控下， S 經濟管制圖的偵測力也比傳統 S 管制圖的強。 是以 S 經濟管 制圖優於傳統的 S 管制圖。本研究所推導出的製程模式及 S 管制圖設 計方法可應用於各種分配的製程變數 (Process Variable) 及其他類型管 制圖的設計上。

Derivative pricing, and in particular the pricing of options, is an important area of current research in financial mathematics. Experts debate on the best method of pricing and the most appropriate model of a price process to use. In this thesis, a ``Switching Black-Scholes'' model of a price process is proposed. This model is based on the standard geometric Brownian motion (or Black-Scholes) model of a price process. However, the drift and volatility parameters are permitted to vary between a finite number of possible values at known times, according to the state of a hidden Markov chain. This type of model has been found to replicate the Black-Scholes implied volatility smiles observed in the market, and produce option prices which are closer to market values than those obtained from the traditional Black-Scholes formula. As the Markov chain incorporates a second source of uncertainty into the Black-Scholes model, the Switching Black-Scholes market is incomplete, and no unique option pricing methodology exists. In this thesis, we apply the methods of mean-variance hedging, Esscher transforms and minimum entropy in order to price options on assets which evolve according to the Switching Black-Scholes model. C programs to compute these prices are given, and some particular numerical examples are examined. Finally, filtering techniques and reference probability methods are applied to find estimates of the model parameters and state of the hidden Markov chain. / Thesis (Ph.D.)--Applied Mathematics, 2003.

Cette thèse a pour objet l'étude de l'incertitude attachée à l'estimation de la géometrie d'une scène à partir d'un couple stéréoscopique d'images. La mise en correspondance des points homologues d'un couple suppose la similarité locale des deux images et nécessite une information radiométrique discriminante. Dans de nombreuses situations cependant (déformations géométriques, bruit d'acquisition, manque de contraste, ....), ces hypothèses sont mises en défaut et les erreurs d'appariemment qui en résultent dépendent fortement de l'information contenue dans le couple et non du sytème stéréoscopique lui-meme. <br />Afin d'aborder ce problème, nous proposons un cadre bayésien et l'application de méthodes de Monte Carlo par chaînes de Markov. Celles-ci consistent à simuler la distribution conditionnelle du champ de disparité connaissant le couple stéréoscopique et permettent de déterminer les zones où des erreurs importantes peuvent apparaitre avec une probabilité éventuellement faible. Différents modèles stochastiques sont comparés et testés a partir de scènes stéréoscopiques SPOT, et nous donnons quelques pistes pour étendre ces modèles à d'autres types d'images. Nous nous intéressons également au probleme de l'estimation des paramètres de ces modèles et proposons un certain nombre d'algorithmes permettant une estimation automatique. Enfin, une part importante du travail est consacrée à l'étude d'algorithmes de simulation reposant sur la théorie des chaînes de Markov. L'apport essentiel réside dans l'extension de l'algorithme de Metropolis-Hastings dans une perspective multi-dimensionnelle. Une application performante reposant sur l'utilisation de la loi gaussienne est donnée. De plus, nous montrons comment le recours à des techniques d'échantillonnage d'importance permet de diminuer efficacement le temps de calcul.

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