Contexto e modularização em redes neurais recorrentes para aprendizagem de seqüências temporais

Este trabalho apresenta um sistema neural modular, que processa separadamente informações de contexto espacial e temporal, para a tarefa de reprodução de sequências temporais. Para o desenvolvimento do sistema neural foram considerados redes neurais recorrentes, modelos estocásticos, sistemas neurais modulares e processamento de informações de contexto. Em seguida, foram estudados três modelos com abordagens distintas para aprendizagem de seqüências temporais: uma rede neural parcialmente recorrente, um exemplo de sistema neural modular e um modelo estocástico utilizando a teoria de modelos markovianos escondidos. Com base nos estudos e modelos apresentados, esta pesquisa propõe um sistema formado por dois módulos sucessivos distintos. Uma rede de propagação direta (módulo estimador de contexto espacial) realiza o processamento de contexto espacial identificando a seqüência a ser reproduzida e fornecendo um protótipo do contexto para o segundo módulo. Este é formado por uma rede parcialmente recorrente (módulo de reprodução de sequências temporais) para aprender as informações de contexto temporal e reproduzir em suas saídas a seqüência identificada pelo módulo anterior. Para a finalidade mencionada, este mestrado utiliza a distribuição de Gibbs na saída do módulo para contexto espacial de forma que este forneça probabilidades de contexto espacial, indicando o grau de certeza do módulo e possibilitando a utilização de procedimentos especiais para os casos de dúvida. O sistema neural foi testado em conjuntos contendo trajetórias abertas, fechadas, e com diferentes situações de ambigüidade e complexidade. Duas situações distintas foram avaliadas: (a) capacidade do sistema em reproduzir trajetórias a partir de pontos iniciais treinados; e (b) capacidade de generalização do sistema reproduzindo trajetórias considerando pontos iniciais ou finais em situações não treinadas. A situação (b) é um problema de difícil ) solução em redes neurais devido à falta de contexto temporal, essencial na reprodução de seqüências. Foram realizados experimentos comparando o desempenho do sistema modular proposto com o de uma rede parcialmente recorrente operando sozinha e um sistema modular neural (TOTEM). Os resultados sugerem que o sistema proposto apresentou uma capacidade de generalização significamente melhor, sem que houvesse uma deterioração na capacidade de reproduzir seqüências treinadas. Esses resultados foram obtidos em sistema mais simples que o TOTEM.

The contribution of modularity to green operations practices

This paper discusses the possible contributions from modularity and industrial condominiums towards enhancing environmental performance in the automotive industry. The research described in this study is underpinned by a review of journal articles and books on the topics of: modularity of production systems; green operations practices, and the automotive industry and sustainability. The methodology is based on theoretical analysis of the contribution of the modular production system characteristics used in the automotive industry for Green Operations Practices (GOP). The following GOPs were considered: green buildings, eco-design, green supply chains, greener manufacturing, and reverse logistics. The results are theoretical in nature; however, due to the small number of studies that investigate the relationship between modularity and sustainability, this work is relevant to increase knowledge in academic circles and among practitioners in order to understand the possible environmental benefits from modular production systems. For instance, based upon our analysis, we could deduce that the existing modular production systems in the automotive industry may contribute in different ways to the implementation of GOPs. In all types of modularity, product simplification through the use of modules can enhance environmental performance and facilitate further activities such as maintenance and repair contributing to a longer life of cars on the road. Moreover, modules will make automobiles easier to disassembly, so increasing the chances of reuse of valuable components and a better final disposal of scrap. Regarding the potential benefits of each type of modularity, it is expected that modular consortia will have a better integration of environmental practices with suppliers and seize on high efficiency during manufacturing and logistics compared with conventional production systems.

Modularity and industrial complexes:perspectives for green operations in the automotive industry

This paper discusses the possible contributions from modularity and industrial condominiums towards enhancing environmental performance in the automotive industry. The research described in this study is underpinned by a review of journal articles and books on the topics of: modularity of production systems; green operations practices, and the automotive industry and sustainability. The methodology is based on theoretical analysis of the contribution of the modular production system characteristics used in the automotive industry for Green Operations Practices (GOP). The following GOPs were considered: green buildings, eco design, green supply chains, greener manufacturing, and reverse logistics. The results are theoretical in nature; however, due to the small number of studies that investigate the relationship between modularity and sustainability, this work is relevant to increase knowledge in academic circles and among practitioners in order to understand the possible environmental benefits from modular production systems.

Architecture for IoT Node and Platform

Only recently, during the past five years, consumer electronics has been evolving rapidly. Many products have started to include “smart home” capabilities, enabling communication and interoperability of various smart devices. Even more devices and sensors can be remote controlled and monitored through cloud services. While the smart home systems have become very affordable to average consumer compared to the early solutions decades ago, there are still many issues and things that need to be fixed or improved upon: energy efficiency, connectivity with other devices and applications, security and privacy concerns, reliability, and response time. This paper focuses on designing Internet of Things (IoT) node and platform architectures that take these issues into account, notes other currently used solutions, and selects technologies in order to provide better solution. The node architecture aims for energy efficiency and modularity, while the platform architecture goals are in scalability, portability, maintainability, performance, and modularity. Moreover, the platform architecture attempts to improve user experience by providing higher reliability and lower response time compared to the alternative platforms. The architectures were developed iteratively using a development process involving research, planning, design, implementation, testing, and analysis. Additionally, they were documented using Kruchten’s 4+1 view model, which is used to describe the use cases and different views of the architectures. The node architecture consisted of energy efficient hardware, FC3180 microprocessor and CC2520 RF transceiver, modular operating system, Contiki, and a communication protocol, AllJoyn, used for providing better interoperability with other IoT devices and applications. The platform architecture provided reliable low response time control, monitoring, and initial setup capabilities by utilizing web technologies on various devices such as smart phones, tablets, and computers. Furthermore, an optional cloud service was provided in order to control devices and monitor sensors remotely by utilizing scalable high performance technologies in the backend enabling low response time and high reliability.

On L2 grammar and processing: the case of oblique relative clauses and the Null-Prep phenomenon

This dissertation investigates the acquisition of oblique relative clauses in L2 Spanish by English and Moroccan Arabic speakers in order to understand the role of previous linguistic knowledge and its interaction with Universal Grammar on the one hand, and the relationship between grammatical knowledge and its use in real-time, on the other hand. Three types of tasks were employed: an oral production task, an on-line self-paced grammaticality judgment task, and an on-line self-paced reading comprehension task. Results indicated that the acquisition of oblique relative clauses in Spanish is a problematic area for second language learners of intermediate proficiency in the language, regardless of their native language. In particular, this study has showed that, even when the learners’ native language shares the main properties of the L2, i.e., fronting of the obligatory preposition (Pied-Piping), there is still room for divergence, especially in production and timed grammatical intuitions. On the other hand, reaction time data have shown that L2 learners can and do converge at the level of sentence processing, showing exactly the same real-time effects for oblique relative clauses that native speakers had. Processing results demonstrated that native and non-native speakers alike are able to apply universal processing principles such as the Minimal Chain Principle (De Vincenzi, 1991) even when the L2 learners still have incomplete grammatical representations, a result that contradicts some of the predictions of the Shallow Structure Hypothesis (Clahsen & Felser, 2006). Results further suggest that the L2 processing and comprehension domains may be able to access some type of information that it is not yet available to other grammatical modules, probably because transfer of certain L1 properties occurs asymmetrically across linguistic domains. In addition, this study also explored the Null-Prep phenomenon in L2 Spanish, and proposed that Null-Prep is an interlanguage stage, fully available and accounted within UG, which intermediate L2 as well as first language learners go through in the development of pied-piping oblique relative clauses. It is hypothesized that this intermediate stage is the result of optionality of the obligatory preposition in the derivation, when it is not crucial for the meaning of the sentence, and when the DP is going to be in an A-bar position, so it can get default case. This optionality can be predicted by the Bottleneck Hypothesis (Slabakova, 2009c) if we consider that these prepositions are some sort of functional morphology. This study contributes to the field of SLA and L2 processing in various ways. First, it demonstrates that the grammatical representations may be dissociated from grammatical processing in the sense that L2 learners, unlike native speakers, can present unexpected asymmetries such as a convergent processing but divergent grammatical intuitions or production. This conclusion is only possible under the assumption of a modular language system. Finally, it contributes to the general debate of generative SLA since in argues for a fully UG-constrained interlanguage grammar.

Development and illustrative outputs of the Community Integrated Assessment System (CIAS), a multi-institutional modular integrated assessment approach for modelling climate change.

This paper describes the development and first results of the “Community Integrated Assessment System” (CIAS), a unique multi-institutional modular and flexible integrated assessment system for modelling climate change. Key to this development is the supporting software infrastructure, SoftIAM. Through it, CIAS is distributed between the community of institutions which has each contributed modules to the CIAS system. At the heart of SoftIAM is the Bespoke Framework Generator (BFG) which enables flexibility in the assembly and composition of individual modules from a pool to form coupled models within CIAS, and flexibility in their deployment onto the available software and hardware resources. Such flexibility greatly enhances modellers’ ability to re-configure the CIAS coupled models to answer different questions, thus tracking evolving policy needs. It also allows rigorous testing of the robustness of IA modelling results to the use of different component modules representing the same processes (for example, the economy). Such processes are often modelled in very different ways, using different paradigms, at the participating institutions. An illustrative application to the study of the relationship between the economy and the earth’s climate system is provided.

Roof modular system in wood and particle board (OSB) to rural construction

Wood is a material of great applicability in construction, with advantageous properties to form various structural systems, such as walls and roof. Most of the roof structural systems follow models that have remained unchanged for a long time. A roof modular system in distinguished materials is proposed: reforested wood (Pine), oriented strand board (OSB) and roof tiles made of recycled long-life packaging material in order to be applied in rural construction. In this alternative, besides the benefit of giving destination packages with long-life thermal comfort, it also highlights the use of reforestated wood being the cultivation of such species that provides incentive for agribusiness. The structural performance of this alternative was evaluated through computer modeling and test results of two modular panels. The analysis is based on the results of vertical displacements, deformations and stresses. A positive correlation between theoretical and experimental values was observed, indicating the model's feasibility for use in roof structures. Therefore, the modular system represents a solution to new architecture conceptions to rural construction, for example, storage construction, cattle handling and poultry, with benefits provided by prefabricated building systems.

Partial collapse of a ventilated stone façade: Diagnosis and analysis of the anchorage system

The mechanical behaviour of transventilated façades performed by natural stone is necessarily based on the correct execution of both anchoring elements on the stone cladding as in the ones corresponding to the enclosure support, either with brick masonry walls or reinforced concrete walls. In the case studied in the present work, the origin of the damages suffered on the façade of a building located in Alcoy has been analyzed, where the detachment of part of the outer enclosure occurred. This enclosure is a transventilated façade formed by Bateig Blue stone tiles. To this end, “in situ” tests of the anchoring systems employed have been performed, as well as laboratory tests of mechanical characterization of the material and of different types of anchor, comparing these results with those obtained in both the simplified analytical models of continuum mechanics as developed by the Finite Element Method (FEM).

MUMS, a modular unified microprocessor system /

Originally presented as the author's thesis, University of Illinois at Urbana-Champaign.

Implementation of a triple modular redundant FPGA based safety critical system for reliable software execution

This paper describes the implementation of a TMR (Triple Modular Redundant) microprocessor system on a FPGA. The system exhibits true redundancy in that three instances of the same processor system (both software and hardware) are executed in parallel. The described system uses software to control external peripherals and a voter is used to output correct results. An error indication is asserted whenever two of the three outputs match or all three outputs disagree. The software has been implemented to conform to a particular safety critical coding guideline/standard which is popular in industry. The system was verified by injecting various faults into it.