Modeling and Analysis of Two-Part Type Manufacturing Systems

This paper presents a model and analysis of a synchronous tandem flow line that produces different part types on unreliable machines. The machines operate according to a static priority rule, operating on the highest priority part whenever possible, and operating on lower priority parts only when unable to produce those with higher priorities. We develop a new decomposition method to analyze the behavior of the manufacturing system by decomposing the long production line into small analytically tractable components. As a first step in modeling a production line with more than one part type, we restrict ourselves to the case where there are two part types. Detailed modeling and derivations are presented with a small two-part-type production line that consists of two processing machines and two demand machines. Then, a generalized longer flow line is analyzed. Furthermore, estimates for performance measures, such as average buffer levels and production rates, are presented and compared to extensive discrete event simulation. The quantitative behavior of the two-part type processing line under different demand scenarios is also provided.

Statistical modeling on coordinates

This paper is a first draft of the principle of statistical modelling on coordinates. Several causes —which would be long to detail—have led to this situation close to the deadline for submitting papers to CODAWORK’03. The main of them is the fast development of the approach along the last months, which let appear previous drafts as obsolete. The present paper contains the essential parts of the state of the art of this approach from my point of view. I would like to acknowledge many clarifying discussions with the group of people working in this field in Girona, Barcelona, Carrick Castle, Firenze, Berlin, G¨ottingen, and Freiberg. They have given a lot of suggestions and ideas. Nevertheless, there might be still errors or unclear aspects which are exclusively my fault. I hope this contribution serves as a basis for further discussions and new developments

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Experimental Modeling and Control Strategies on an Open Mobile Robot Platform PRIM

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

Modeling of hybrid systems by piecewise decomposition

Piecewise linear models systems arise as mathematical models of systems in many practical applications, often from linearization for nonlinear systems. There are two main approaches of dealing with these systems according to their continuous or discrete-time aspects. We propose an approach which is based on the state transformation, more particularly the partition of the phase portrait in different regions where each subregion is modeled as a two-dimensional linear time invariant system. Then the Takagi-Sugeno model, which is a combination of local model is calculated. The simulation results show that the Alpha partition is well-suited for dealing with such a system

Two isomeric reaction products: hydrogen-bonded sheets in methyl 4-(5-amino-3-phenyl-1H-pyrazol-1-yl)-3-nitrobenzoate and hydrogen-bonded chains of edge-fused rings in methyl 3-nitro-4-[(5-phenyl-1H-pyrazol-3-yl)amino] benzoate

In methyl 4-(5-amino-3-phenyl-1H-pyrazol-1-yl)-3-nitrobenzoate, C17H14N4O4, the molecules are linked into complex sheets by a combination of N-H center dot center dot center dot N, N-H center dot center dot center dot O and C - H center dot center dot center dot O hydrogen bonds. In the isomeric methyl 3-nitro-4-[(5-phenyl- 1H-pyrazol-3-yl)amino] benzoate, molecules exhibit a polarized molecular-electronic structure and are linked into chains of edge-fused rings by a combination of N-H center dot center dot center dot O and C - H center dot center dot center dot O hydrogen bonds.

Application of agent-based modeling to the study of gender stereotypes

Gender stereotypes are sets of characteristics that people believe to be typically true of a man or woman. We report an agent-based model (ABM) that simulates how stereotypes disseminate in a group through associative mechanisms. The model consists of agents that carry one of several different versions of a stereotype, which share part of their conceptual content. When an agent acts according to his/her stereotype, and that stereotype is shared by an observer, then the latter’s stereotype strengthens. Contrarily, if the agent does not act according to his/ her stereotype, then the observer’s stereotype weakens. In successive interactions, agents develop preferences, such that there will be a higher probability of interaction with agents that confirm their stereotypes. Depending on the proportion of shared conceptual content in the stereotype’s different versions, three dynamics emerge: all stereotypes in the population strengthen, all weaken, or a bifurcation occurs, i.e., some strengthen and some weaken. Additionally, we discuss the use of agent-based modeling to study social phenomena and the practical consequences that the model’s results might have on stereotype research and their effects on a community

Modeling the monetary policy reaction function of the colombian central bank

This paper proposes a simple Ordered Probit model to analyse the monetary policy reaction function of the Colombian Central Bank. There is evidence that the reaction function is asymmetric, in the sense that the Bank increases the Bank rate when the gap between observed inflation and the inflation target (lagged once) is positive, but it does not reduce the Bank rate when the gap is negative. This behaviour suggests that the Bank is more interested in fulfilling the announced inflation target rather than in reducing inflation excessively. The forecasting performance of the model, both within and beyond the estimation period, appears to be particularly good.

An artificial economy based on reinforcement learning and agent based modeling

In this paper, we employ techniques from artificial intelligence such as reinforcement learning and agent based modeling as building blocks of a computational model for an economy based on conventions. First we model the interaction among firms in the private sector. These firms behave in an information environment based on conventions, meaning that a firm is likely to behave as its neighbors if it observes that their actions lead to a good pay off. On the other hand, we propose the use of reinforcement learning as a computational model for the role of the government in the economy, as the agent that determines the fiscal policy, and whose objective is to maximize the growth of the economy. We present the implementation of a simulator of the proposed model based on SWARM, that employs the SARSA(λ) algorithm combined with a multilayer perceptron as the function approximation for the action value function.

Modeling tuition fees in presence of social heterogeneity. 'Como modelar las tasas de matrícula en presencia de la heterogeneidad social'.

Resumen basado en el de la publicación

Blackbody emission under laser excitation of silicon nanopowder produced by plasma-enhanced chemical-vapor deposition

Previous results concerning radiative emission under laser irradiation of silicon nanopowder are reinterpreted in terms of thermal emission. A model is developed that considers the particles in the powder as independent, so under vacuum the only dissipation mechanism is thermal radiation. The supralinear dependence observed between the intensity of the emitted radiation and laser power is predicted by the model, as is the exponential quenching when the gas pressure around the sample increases. The analysis allows us to determine the sample temperature. The local heating of the sample has been assessed independently by the position of the transverse optical Raman mode. Finally, it is suggested that the photoluminescence observed in porous silicon and similar materials could, in some cases, be blackbody radiation

Gas collisions and pressure quenching of the photoluminescence of silicon nanopowder grown by plasma-enhanced chemical vapor deposition

The quenching of the photoluminescence of Si nanopowder grown by plasma-enhanced chemical vapor deposition due to pressure was measured for various gases ( H2, O2, N2, He, Ne, Ar, and Kr) and at different temperatures. The characteristic pressure, P0, of the general dependence I(P)=I0exp(-P/P0) is gas and temperature dependent. However, when the number of gas collisions is taken as the variable instead of pressure, then the quenching is the same within a gas family (mono- or diatomic) and it is temperature independent. So it is concluded that the effect depends on the number of gas collisions irrespective of the nature of the gas or its temperature

Efficient 3D scene modeling and mosaicing

El modelat d'escenes és clau en un gran ventall d'aplicacions que van des de la generació mapes fins a la realitat augmentada. Aquesta tesis presenta una solució completa per a la creació de models 3D amb textura. En primer lloc es presenta un mètode de Structure from Motion seqüencial, a on el model 3D de l'entorn s'actualitza a mesura que s'adquireix nova informació visual. La proposta és més precisa i robusta que l'estat de l'art. També s'ha desenvolupat un mètode online, basat en visual bag-of-words, per a la detecció eficient de llaços. Essent una tècnica completament seqüencial i automàtica, permet la reducció de deriva, millorant la navegació i construcció de mapes. Per tal de construir mapes en àrees extenses, es proposa un algorisme de simplificació de models 3D, orientat a aplicacions online. L'eficiència de les propostes s'ha comparat amb altres mètodes utilitzant diversos conjunts de dades submarines i terrestres.

Signal processing of microstructure profiles: integrating turbulent spatial scales in aquatic ecological modeling

The main objective of this thesis was the integration of microstructure information in synoptic descriptors of turbulence, that reflects the mixing processes. Turbulent patches are intermittent in space and time, but they represent the dominant process for mixing. In this work, the properties of turbulent patches were considered the potential input for integrating the physical microscale measurements. The development of a method for integrating the properties of the turbulent patches required solving three main questions: a) how can we detect the turbulent patches from he microstructure measurements?; b) which are the most relevant properties of the turbulent patches?; and ) once an interval of time has been selected, what kind of synoptic parameters could better reflect the occurrence and properties of the turbulent patches? The answers to these questions were the final specific objectives of this thesis.