Filtering duplicate items over distributed data streams

In recent years many real time applications need to handle data streams. We consider the distributed environments in which remote data sources keep on collecting data from real world or from other data sources, and continuously push the data to a central stream processor. In these kinds of environments, significant communication is induced by the transmitting of rapid, high-volume and time-varying data streams. At the same time, the computing overhead at the central processor is also incurred. In this paper, we develop a novel filter approach, called DTFilter approach, for evaluating the windowed distinct queries in such a distributed system. DTFilter approach is based on the searching algorithm using a data structure of two height-balanced trees, and it avoids transmitting duplicate items in data streams, thus lots of network resources are saved. In addition, theoretical analysis of the time spent in performing the search, and of the amount of memory needed is provided. Extensive experiments also show that DTFilter approach owns high performance.

Simultaneous chemical reaction and distillation of formaldehyde

The thesis is concerned with the development and testing of a mathematical model of a distillation process in which the components react chemically. The formaldehyde-methanol-water system was selected and only the reversible reactions between formaldehyde and water giving methylene glycol and between formaldehyde and methanol producing hemiformal were assumed to occur under the distillation conditions. Accordingly the system has been treated as a five component system. The vapour-liquid equilibrium calculations were performed by solving iteratively the thermodynamic relationships expressing the phase equilibria with the stoichiometric equations expressing the chemical equilibria. Using optimisation techniques, the Wilson single parameters and Henry's constants were calculated for binary systems containing formaldehyde which was assumed to be a supercritical component whilst Wilson binary parameters were calculated for the remaining binary systems. Thus the phase equilibria for the formaldehyde system could be calculated using these parameters and good accuracy was obtained when calculated values were compared with experimental values. The distillation process was modelled using the mass and energy balance equations together with the phase equilibria calculations. The plate efficiencies were obtained from a modified A.I.Ch.E. Bubble Tray method. The resulting equations were solved by an iterative plate to plate calculation based on the Newton Raphson method. Experiments were carried out in a 76mm I.D., eight sieve plate distillation column and the results were compared with the mathematical model calculations. Overall, good agreement was obtained but some discrepancies were observed in the concentration profiles and these may have been caused by the effect of limited physical property data and a limited understanding of the reactions mechanism. The model equations were solved in the form of modular computer programs. Although they were written to describe the steady state distillation with simultaneous chemical reaction of the formaldehyde system, the approach used may be of wider application.

Freshwater Resource Supply Modeling for Developed and Undeveloped Watersheds

Globally, the current state of freshwater resource management is insufficient and impeding the chance at a sustainable future. Human interference within the natural hydrologic cycle is becoming dangerously irreversible and the need to redefine resource managerial approaches is imminent. This research involves the development of a coupled natural-human freshwater resource supply model using a System Dynamics approach. The model was applied to two case studies, Somalia, Africa and the Phoenix Active Management Area in Arizona, USA. It is suggested that System Dynamic modeling would be an invaluable tool for achieving sustainable freshwater resource management in individual watersheds. Through a series of thought experiments, a thorough understanding of the systems’ dynamic behaviors is obtainable for freshwater resource managers and policy-makers to examine various courses of action for alleviating freshwater supply concerns. This thesis reviews the model, its development and an analysis of several thought experiments applied to the case studies.

Analysis of Policies for Safety Improvements on Low-Volume Rural Roadways,1994

In order to determine the adequacy with which safety problems on low-volume rural roadways were addressed by the four states of Federal Region VII (Iowa, Kansas, Missouri, and Nebraska), a review was made of the states' safety policies. After reviewing literature dealing with the identification of hazardous locations, evaluation methodologies, and system-wide safety improvements, a survey of the states' safety policies was conducted. An official from each state was questioned about the various aspects and procedures dealing with safety improvements. After analyzing and comparing the remarkably diverse policies, recommendations were made in the form of a model safety program. This program included special modifications that would help remediate hazards on low-volume rural roadways. Especially encouraged is a system-wide approach to improvement which would cover all parts of the highway system, not just urban and high-volume roadways.

Towards Proactive Context-aware Computing and Systems

A primary goal of context-aware systems is delivering the right information at the right place and right time to users in order to enable them to make effective decisions and improve their quality of life. There are three key requirements for achieving this goal: determining what information is relevant, personalizing it based on the users’ context (location, preferences, behavioral history etc.), and delivering it to them in a timely manner without an explicit request from them. These requirements create a paradigm that we term as “Proactive Context-aware Computing”. Most of the existing context-aware systems fulfill only a subset of these requirements. Many of these systems focus only on personalization of the requested information based on users’ current context. Moreover, they are often designed for specific domains. In addition, most of the existing systems are reactive - the users request for some information and the system delivers it to them. These systems are not proactive i.e. they cannot anticipate users’ intent and behavior and act proactively without an explicit request from them. In order to overcome these limitations, we need to conduct a deeper analysis and enhance our understanding of context-aware systems that are generic, universal, proactive and applicable to a wide variety of domains. To support this dissertation, we explore several directions. Clearly the most significant sources of information about users today are smartphones. A large amount of users’ context can be acquired through them and they can be used as an effective means to deliver information to users. In addition, social media such as Facebook, Flickr and Foursquare provide a rich and powerful platform to mine users’ interests, preferences and behavioral history. We employ the ubiquity of smartphones and the wealth of information available from social media to address the challenge of building proactive context-aware systems. We have implemented and evaluated a few approaches, including some as part of the Rover framework, to achieve the paradigm of Proactive Context-aware Computing. Rover is a context-aware research platform which has been evolving for the last 6 years. Since location is one of the most important context for users, we have developed ‘Locus’, an indoor localization, tracking and navigation system for multi-story buildings. Other important dimensions of users’ context include the activities that they are engaged in. To this end, we have developed ‘SenseMe’, a system that leverages the smartphone and its multiple sensors in order to perform multidimensional context and activity recognition for users. As part of the ‘SenseMe’ project, we also conducted an exploratory study of privacy, trust, risks and other concerns of users with smart phone based personal sensing systems and applications. To determine what information would be relevant to users’ situations, we have developed ‘TellMe’ - a system that employs a new, flexible and scalable approach based on Natural Language Processing techniques to perform bootstrapped discovery and ranking of relevant information in context-aware systems. In order to personalize the relevant information, we have also developed an algorithm and system for mining a broad range of users’ preferences from their social network profiles and activities. For recommending new information to the users based on their past behavior and context history (such as visited locations, activities and time), we have developed a recommender system and approach for performing multi-dimensional collaborative recommendations using tensor factorization. For timely delivery of personalized and relevant information, it is essential to anticipate and predict users’ behavior. To this end, we have developed a unified infrastructure, within the Rover framework, and implemented several novel approaches and algorithms that employ various contextual features and state of the art machine learning techniques for building diverse behavioral models of users. Examples of generated models include classifying users’ semantic places and mobility states, predicting their availability for accepting calls on smartphones and inferring their device charging behavior. Finally, to enable proactivity in context-aware systems, we have also developed a planning framework based on HTN planning. Together, these works provide a major push in the direction of proactive context-aware computing.

Aproximación al desarrollo de un sistema de transporte masivo a través de la dinámica de sistemas

El porvenir social y económico de una ciudad depende, en gran medida, de la eficiencia de su sistema de transporte; esto se ve reflejado en la capacidad de transportar personas y bienes de una forma sostenible, con los recursos disponibles. En la actualidad se encuentran en desarrollo sistemas de transporte masivo tipo Bus Rapid Transit [BRT] en siete ciudades colombianas, situación que genera la necesidad de dar seguimiento a su progreso y al crecimiento de su participación en la demanda de viajes unipersonales. El siguiente trabajo busca, a través de una simulación en dinámica de sistemas, describir el desarrollo de un sistema de transporte masivo, con el fin de otorgar una visión acerca del impacto de los parámetros operativos y la reinversión en el sistema y en el desarrollo e incremento de su demanda. Se plantean tres escenarios para evaluar diferentes políticas operativas y de reinversión en el sistema, analizando el comportamiento en su desarrollo.

Volatility transmission between stock and exchange-rate markets: A connectedness analysis

This paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to January 2015. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.

Planning Processes for Transport Solutions An Application To the City of Bologna

Mathematical models and the involved methods applied to real contexts are essential tools for designing and evaluating solutions concerning physical elements and/or organizational components of transportation systems. To deal with this, the systems engineering approach is used, which considers the relationships among the transportation system elements and their performances. This approach allows quantifying the effects of transportation projects by taking into account the intrinsic complexity of the transportation system and then assessing the effects of solutions to solve – or mitigate – transportation problems. This thesis focuses on the application of the transport system engineering approach to a real city – Bologna, in northern Italy – in order to: 1. simulate the current transportation system conditions (status quo); 2. compare and assess the results obtained by two different approaches for simulating the link traffic flows on the road transportation network and their related impacts (externalities) 3. identify potential solutions to solve critical aspects, particularly in terms of traffic flow congestion and related environmental impacts (findings)

Compositional amalgamations and balances: a critical approach

The amalgamation operation is frequently used to reduce the number of parts of compositional data but it is a non-linear operation in the simplex with the usual geometry,the Aitchison geometry. The concept of balances between groups, a particular coordinate system designed over binary partitions of the parts, could be an alternative to theamalgamation in some cases. In this work we discuss the proper application of bothconcepts using a real data set corresponding to behavioral measures of pregnant sows

Compositional amalgamations and balances: a critical approach

The amalgamation operation is frequently used to reduce the number of parts of compositional data but it is a non-linear operation in the simplex with the usual geometry, the Aitchison geometry. The concept of balances between groups, a particular coordinate system designed over binary partitions of the parts, could be an alternative to the amalgamation in some cases. In this work we discuss the proper application of both concepts using a real data set corresponding to behavioral measures of pregnant sows

Anthropogenic influences in a lagoonal environment: a multiproxy approach at the valo grande mouth, Cananéia-Iguape system (SE Brazil)

The Cananéia-Iguape system, SE Brazil, consists of a complex of lagoonal channels, located in a United Nations Educational, Scientific and Cultural Organization (UNESCO) Biosphere Reserve. Nevertheless, important environmental changes have occurred in approximately the last 150 yrs due to the opening of an artificial channel, the Valo Grande, connecting the Ribeira de Iguape River to the lagoonal system. Our objective is to assess the historical record of the uppermost layers of the sedimentary column of the lagoonal system in order to determine the history of environmental changes caused by the opening of the artificial channel. In this sense, an integrated geochemical-faunal approach is used. The environmental changes led significant modifications in salinity, in changes of the depositional patterns of sediments and foraminiferal assemblages (including periods of defaunation), and, more drastically, in the input of heavy metals to the coastal environment. The concentrations Pb in the core analyzed here were up to two times higher than the values measured in contaminated sediments from the Santos estuary, the most industrialized coastal zone in Brazil.

A calibration approach based on Takagi-Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.

Lattice-dome design using a knowledge-based system approach

In the design of lattice domes, design engineers need expertise in areas such as configuration processing, nonlinear analysis, and optimization. These are extensive numerical, iterative, and lime-consuming processes that are prone to error without an integrated design tool. This article presents the application of a knowledge-based system in solving lattice-dome design problems. An operational prototype knowledge-based system, LADOME, has been developed by employing the combined knowledge representation approach, which uses rules, procedural methods, and an object-oriented blackboard concept. The system's objective is to assist engineers in lattice-dome design by integrating all design tasks into a single computer-aided environment with implementation of the knowledge-based system approach. For system verification, results from design examples are presented.