A Multi-scale Model for Copper Dishing in Chemical-Mechanical Polishing

The present success in the manufacture of multi-layer interconnects in ultra-large-scale integration is largely due to the acceptable planarization capabilities of the chemical-mechanical polishing (CMP) process. In the past decade, copper has emerged as the preferred interconnect material. The greatest challenge in Cu CMP at present is the control of wafer surface non-uniformity at various scales. As the size of a wafer has increased to 300 mm, the wafer-level non-uniformity has assumed critical importance. Moreover, the pattern geometry in each die has become quite complex due to a wide range of feature sizes and multi-level structures. Therefore, it is important to develop a non-uniformity model that integrates wafer-, die- and feature-level variations into a unified, multi-scale dielectric erosion and Cu dishing model. In this paper, a systematic way of characterizing and modeling dishing in the single-step Cu CMP process is presented. The possible causes of dishing at each scale are identified in terms of several geometric and process parameters. The feature-scale pressure calculation based on the step-height at each polishing stage is introduced. The dishing model is based on pad elastic deformation and the evolving pattern geometry, and is integrated with the wafer- and die-level variations. Experimental and analytical means of determining the model parameters are outlined and the model is validated by polishing experiments on patterned wafers. Finally, practical approaches for minimizing Cu dishing are suggested.

Automating the product derivation process of multi-agent systems product lines

Agent-oriented software engineering and software product lines are two promising software engineering techniques. Recent research work has been exploring their integration, namely multi-agent systems product lines (MAS-PLs), to promote reuse and variability management in the context of complex software systems. However, current product derivation approaches do not provide specific mechanisms to deal with MAS-PLs. This is essential because they typically encompass several concerns (e.g., trust, coordination, transaction, state persistence) that are constructed on the basis of heterogeneous technologies (e.g., object-oriented frameworks and platforms). In this paper, we propose the use of multi-level models to support the configuration knowledge specification and automatic product derivation of MAS-PLs. Our approach provides an agent-specific architecture model that uses abstractions and instantiation rules that are relevant to this application domain. In order to evaluate the feasibility and effectiveness of the proposed approach, we have implemented it as an extension of an existing product derivation tool, called GenArch. The approach has also been evaluated through the automatic instantiation of two MAS-PLs, demonstrating its potential and benefits to product derivation and configuration knowledge specification.

Multilayer perceptron neural networks training through charged system search and its Application for non-technical losses detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others nature-inspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids. © 2013 IEEE.

O uso de rede neural artificial MLP na predição de estruturas secundárias de proteínas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Evaluation of a multi variated analysis for the selection of t-tbar multijet events in the current CMS implemented environment at LHC

In the present study we are using multi variate analysis techniques to discriminate signal from background in the fully hadronic decay channel of ttbar events. We give a brief introduction to the role of the Top quark in the standard model and a general description of the CMS Experiment at LHC. We have used the CMS experiment computing and software infrastructure to generate and prepare the data samples used in this analysis. We tested the performance of three different classifiers applied to our data samples and used the selection obtained with the Multi Layer Perceptron classifier to give an estimation of the statistical and systematical uncertainty on the cross section measurement.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Strong Down-Valley Low-Level Jets over the Atacama Desert: Observational Characterization

The near-surface wind and temperature regime at three points in the Atacama Desert of northern Chile is described using two-year multi-level measurements from 80-m towers located in an altitude range between 2100 and 2700 m ASL. The data reveal the frequent development of strong nocturnal drainage flows at all sites. Down-valley nose-shaped wind speed profiles are observed with maximum values occurring at heights between 20 m and 60 m AGL. The flow intensity shows considerable inter-daily variability and a seasonal modulation of maximum speeds, which in the cold season can attain hourly average values larger than 20 m s−1. Turbulent mixing appears significant over the full tower layer, affecting the curvature of the nighttime temperature profile and possibly explaining the observed increase of surface temperatures in the down-valley direction. Nocturnal valley winds and temperatures are weakly controlled by upper-air conditions observed at the nearest aerological station. Estimates of terms in the momentum budget for the development and the quasi-stationary phases of the down-valley flows suggest that the pressure gradient force due to the near-surface cooling along the sloping valley axes plays an important role in these drainage flows. A scale for the jet nose height of equilibrium turbulent down-slope jets is proposed, based on surface friction velocity and surface inversion intensity. At one of the sites this scale explains about 70% of the case-to-case observed variance of jet nose heights. Further modeling and observational work is needed, however, in order to better define the dynamics, extent and turbulence structure of this flow system, which has significant wind-energy, climatic and environmental implications.

Aplicación de técnicas de inteligencia artificial para contribuir en la detección de microcalcificaciones en mamografía digitalizada

A nivel mundial, el cáncer de mama es el tipo de cáncer más frecuente además de una de las principales causas de muerte entre la población femenina. Actualmente, el método más eficaz para detectar lesiones mamarias en una etapa temprana es la mamografía. Ésta contribuye decisivamente al diagnóstico precoz de esta enfermedad que, si se detecta a tiempo, tiene una probabilidad de curación muy alta. Uno de los principales y más frecuentes hallazgos en una mamografía, son las microcalcificaciones, las cuales son consideradas como un indicador importante de cáncer de mama. En el momento de analizar las mamografías, factores como la capacidad de visualización, la fatiga o la experiencia profesional del especialista radiólogo hacen que el riesgo de omitir ciertas lesiones presentes se vea incrementado. Para disminuir dicho riesgo es importante contar con diferentes alternativas como por ejemplo, una segunda opinión por otro especialista o un doble análisis por el mismo. En la primera opción se eleva el coste y en ambas se prolonga el tiempo del diagnóstico. Esto supone una gran motivación para el desarrollo de sistemas de apoyo o asistencia en la toma de decisiones. En este trabajo de tesis se propone, se desarrolla y se justifica un sistema capaz de detectar microcalcificaciones en regiones de interés extraídas de mamografías digitalizadas, para contribuir a la detección temprana del cáncer demama. Dicho sistema estará basado en técnicas de procesamiento de imagen digital, de reconocimiento de patrones y de inteligencia artificial. Para su desarrollo, se tienen en cuenta las siguientes consideraciones: 1. Con el objetivo de entrenar y probar el sistema propuesto, se creará una base de datos de imágenes, las cuales pertenecen a regiones de interés extraídas de mamografías digitalizadas. 2. Se propone la aplicación de la transformada Top-Hat, una técnica de procesamiento digital de imagen basada en operaciones de morfología matemática. La finalidad de aplicar esta técnica es la de mejorar el contraste entre las microcalcificaciones y el tejido presente en la imagen. 3. Se propone un algoritmo novel llamado sub-segmentación, el cual está basado en técnicas de reconocimiento de patrones aplicando un algoritmo de agrupamiento no supervisado, el PFCM (Possibilistic Fuzzy c-Means). El objetivo es encontrar las regiones correspondientes a las microcalcificaciones y diferenciarlas del tejido sano. Además, con la finalidad de mostrar las ventajas y desventajas del algoritmo propuesto, éste es comparado con dos algoritmos del mismo tipo: el k-means y el FCM (Fuzzy c-Means). Por otro lado, es importante destacar que en este trabajo por primera vez la sub-segmentación es utilizada para detectar regiones pertenecientes a microcalcificaciones en imágenes de mamografía. 4. Finalmente, se propone el uso de un clasificador basado en una red neuronal artificial, específicamente un MLP (Multi-layer Perceptron). El propósito del clasificador es discriminar de manera binaria los patrones creados a partir de la intensidad de niveles de gris de la imagen original. Dicha clasificación distingue entre microcalcificación y tejido sano. ABSTRACT Breast cancer is one of the leading causes of women mortality in the world and its early detection continues being a key piece to improve the prognosis and survival. Currently, the most reliable and practical method for early detection of breast cancer is mammography.The presence of microcalcifications has been considered as a very important indicator ofmalignant types of breast cancer and its detection and classification are important to prevent and treat the disease. However, the detection and classification of microcalcifications continue being a hard work due to that, in mammograms there is a poor contrast between microcalcifications and the tissue around them. Factors such as visualization, tiredness or insufficient experience of the specialist increase the risk of omit some present lesions. To reduce this risk, is important to have alternatives such as a second opinion or a double analysis for the same specialist. In the first option, the cost increases and diagnosis time also increases for both of them. This is the reason why there is a great motivation for development of help systems or assistance in the decision making process. This work presents, develops and justifies a system for the detection of microcalcifications in regions of interest extracted fromdigitizedmammographies to contribute to the early detection of breast cancer. This systemis based on image processing techniques, pattern recognition and artificial intelligence. For system development the following features are considered: With the aim of training and testing the system, an images database is created, belonging to a region of interest extracted from digitized mammograms. The application of the top-hat transformis proposed. This image processing technique is based on mathematical morphology operations. The aim of this technique is to improve the contrast betweenmicrocalcifications and tissue present in the image. A novel algorithm called sub-segmentation is proposed. The sub-segmentation is based on pattern recognition techniques applying a non-supervised clustering algorithm known as Possibilistic Fuzzy c-Means (PFCM). The aim is to find regions corresponding to the microcalcifications and distinguish them from the healthy tissue. Furthermore,with the aim of showing themain advantages and disadvantages this is compared with two algorithms of same type: the k-means and the fuzzy c-means (FCM). On the other hand, it is important to highlight in this work for the first time the sub-segmentation is used for microcalcifications detection. Finally, a classifier based on an artificial neural network such as Multi-layer Perceptron is used. The purpose of this classifier is to discriminate froma binary perspective the patterns built from gray level intensity of the original image. This classification distinguishes between microcalcifications and healthy tissue.

Creative self-efficacy and individual creativity in teams:cross-level interactions with team informational resources

We propose a cross-level perspective on the relation between creative self-efficacy and individual creativity in which team informational resources, comprising both shared “knowledge of who knows what” (KWKW) and functional background diversity, benefit the creativity of individuals more with higher creative self-efficacy. To test our hypotheses, we conducted a multi-level study with 176 employees working in 34 research and development teams of a multinational company in 4 countries. In support of our hypotheses, the link between creative self-efficacy and individual creativity was more positive with greater shared KWKW, and this interactive effect was pronounced for teams of high rather than low functional background diversity. We discuss implications for the study of creative self-efficacy in team contexts. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Examination of the impact of personality, social, and cognitive factors on the co-occurrence of health risk behaviors among multi-problem youth: The utility of an integrative framework

Research has identified a number of putative risk factors that places adolescents at incrementally higher risk for involvement in alcohol and other drug (AOD) use and sexual risk behaviors (SRBs). Such factors include personality characteristics such as sensation-seeking, cognitive factors such as positive expectancies and inhibition conflict as well as peer norm processes. The current study was guided by a conceptual perspective that support the notion that an integrative framework that includes multi-level factors has significant explanatory value for understanding processes associated with the co-occurrence of AOD use and sexual risk behavior outcomes. This study evaluated simultaneously the mediating role of AOD-sex related expectancies and inhibition conflict on antecedents of AOD use and SRBs including sexual sensation-seeking and peer norms for condom use.^ The sample was drawn from the Enhancing My Personal Options While Evaluating Risk (EMPOWER: Jonathan Tubman, PI), data set (N = 396; aged 12-18 years). Measures used in the study included Sexual Sensation-Seeking Scale, Inhibition Conflict for Condom Use, Risky Sex Scale. All relevant measures had well-documented psychometric properties. A global assessment of alcohol, drug use and sexual risk behaviors was used.^ Results demonstrated that AOD-sex related expectancies mediated the influence of sexual sensation-seeking on the co-occurrence of alcohol and other drug use and sexual risk behaviors. The evaluation of the integrative model also revealed that sexual sensation-seeking was positively associated with peer norms for condom use. Also, peer norms predicted inhibition conflict among this sample of multi-problem youth. ^ This dissertation research identified mechanisms of risk and protection associated with the co-occurrence of AOD use and SRBs among a multi-problem sample of adolescents receiving treatment for alcohol or drug use and related problems. This study is informative for adolescent-serving programs that address those individual and contextual characteristics that enhance treatment efficacy and effectiveness among adolescents receiving substance use and related problems services.^

Examination of Personality, Social and Cognitive Factors on the Co-Occurrence of Health Risk Behaviors among Multi-Problem Youth: The Utility of An Integrative Framework

Research has identified a number of putative risk factors that places adolescents at incrementally higher risk for involvement in alcohol and other drug (AOD) use and sexual risk behaviors (SRBs). Such factors include personality characteristics such as sensation-seeking, cognitive factors such as positive expectancies and inhibition conflict as well as peer norm processes. The current study was guided by a conceptual perspective that support the notion that an integrative framework that includes multi-level factors has significant explanatory value for understanding processes associated with the co-occurrence of AOD use and sexual risk behavior outcomes. This study evaluated simultaneously the mediating role of AOD-sex related expectancies and inhibition conflict on antecedents of AOD use and SRBs including sexual sensation-seeking and peer norms for condom use. The sample was drawn from the Enhancing My Personal Options While Evaluating Risk (EMPOWER: Jonathan Tubman, PI), data set (N = 396; aged 12-18 years). Measures used in the study included Sexual Sensation-Seeking Scale, Inhibition Conflict for Condom Use, Risky Sex Scale. All relevant measures had well-documented psychometric properties. A global assessment of alcohol, drug use and sexual risk behaviors was used. Results demonstrated that AOD-sex related expectancies mediated the influence of sexual sensation-seeking on the co-occurrence of alcohol and other drug use and sexual risk behaviors. The evaluation of the integrative model also revealed that sexual sensation-seeking was positively associated with peer norms for condom use. Also, peer norms predicted inhibition conflict among this sample of multi-problem youth. This dissertation research identified mechanisms of risk and protection associated with the co-occurrence of AOD use and SRBs among a multi-problem sample of adolescents receiving treatment for alcohol or drug use and related problems. This study is informative for adolescent-serving programs that address those individual and contextual characteristics that enhance treatment efficacy and effectiveness among adolescents receiving substance use and related problems services.

Perceived learning environments and metacognitive strategy knowledge at the upper secondary school level

There is evidence that students benefit from teachers’ explicit fostering of metacognitive strategy knowledge (MSK). However, there is insufficient understanding about the effect of implicit promotion of MSK in regular school instruction. This study investigates the relationship between perceived characteristics of learning environments (social climate, support, autonomy, self-reflection) and students’ MSK. A representative cohort of students (Nt1 = 1,272/Nt2 = 1,126) in Grades 10 and 11 at schools at the upper secondary education level (ISCED Level 3A) in Switzerland participated in this two-wave longitudinal study. Multilevel analysis showed effects on both the individual and the class level. Students who experienced higher social integration showed a higher extent of MSK at the beginning of the school year than students who experienced less social integration. Perceived autonomy was also positively related to students’ MSK on the individual level. In contrast, the results showed a negative relationship between perceived self-reflection and students’ MSK. On the class level, there was a negative relationship between self-reflection and students’ MSK. Teachers’ support did not correlate with students’ MSK on either the individual or the class level. Implications of these results for education and further studies are discussed. (DIPF/Orig.)

The role of affect, fairness, and social perception in team member exchange

Accumulating evidence suggests that Team-member exchange (TMX) influences employee work attitudes and behaviours separately from the effects of leader-member exchange (LMX). In particular, little is known of the effect of LMX differentiation (in-group versus out-group) as a process of social exhange that can, in turn, affect TMX quality. To explore this phenomenon, this chapter presents a multi-level model of TMX in organizations, which incorporates LMX differentiation, team identification, team member affect at the individual level, and fairness of LMX differentiation and affective climate at the group-level. We conclude with a discussion of the implications of our model for theory, research, and practice.

Atoms in squeezed light fields

Squeezed light is of interest as an example of a non-classical state of the electromagnetic field and because of its applications both in technology and in fundamental quantum physics. This review concentrates on one aspect of squeezed light, namely its application in atomic spectroscopy. The general properties, detection and application of squeezed light are first reviewed. The basic features of the main theoretical methods (master equations, quantum Langevin equations, coupled systems) used to treat squeezed light spectroscopy are then outlined. The physics of squeezed light interactions with atomic systems is dealt with first for the simpler case of two-level atoms and then for the more complex situation of multi-level atoms and multi-atom systems. Finally the specific applications of squeezed light spectroscopy are reviewed.

The impact of life stage and societal culture on subordinate influence ethics: A study of Brazil, China, Germany, and the US

In this paper, we investigate the effects of societal values and life stage on subordinate influence ethics. Based on the evolving crossvergence theory of macro-level predictors of values evolution, we demonstrate the applicability of crossvergence theory in the micro-level context. Furthermore, our study provides the first empirical multi-level analysis of influence ethics utilizing a multi pie-country sample. Thus, we illustrate how the breath of crossvergence can be expanded to provide a multi-level theoretical foundation of values and behavior evolution across cultures. Specifically, we integrate micro-level life stage theory and macro-level societal culture theory to concurrently assess the contributions of each theory in explaining subordinate influence ethics across the diverse societies of Brazil. China, Germany and the U.S. Consistent with previous research, we found significant societal differences in influence ethics. However, we also found that life stage theory played a significant role in understanding influence ethics. Thus, our findings expand the crossvergence perspective on societal change, indicating that key micro-level predictors (e.g., life stage) should be included in cross-cultural research. (C) 2009 Elsevier Inc. All rights reserved.