Usabilidade da Interface do Sistema Eletrônico de Editoração de Revistas: um estudo da revista BiblioCanto da UFRN

The electronic journals correspond publishing channels and dissemination of scientific information. Through them, users can spread their studies as well as developing new researches. One of the systems used for creation and e-journals management is the Electronic System for Journal Publishing (SEER), used in the construction of periodic portals, as well as the creation of magazines in isolation. In this purport, it is believed that the management systems and creation of e-journals should be developed (internally and externally) according to the needs of its users. In the case of internal development, some of these processes refer to the copyright registration and submission of articles, which, in turn, are relevant tasks in the editorial process. Thus, the proposed study, thematic Usability of scientific journals, aims to analyze the usability of the copyright registration process and submission of articles in the Electronic System for Journal Publishing through BiblioCanto magazine, part of the Electronic Journals Portal of the Federal University of Rio Grande do Norte (UFRN). For the realization of the research, two valuation techniques were used: the Usability Test with a total of twenty participants and the Cooperative Evaluation, with the same number of participants separated in four categories considered target audience of that magazine, namely: undergraduate students, graduate students, teachers and librarians. The results indicated that the two analyzed processes (copyright registration and submission of articles) need improvement. In the case of the registration process, the following needs are: signalizing of the conducting registration ambient; description and exclusion of requested information on the registration form. In the process of article submission, it is emphasized improvement of aspects: the early steps to submission, signaling of required fields, concise description of the steps, minimization and review of the steps. To this end, it is believed that in general idea the SEER partially meets the needs of its users regarding the usability of such software.

Usabilidade da Interface do Sistema Eletrônico de Editoração de Revistas: um estudo da revista BiblioCanto da UFRN

The electronic journals correspond publishing channels and dissemination of scientific information. Through them, users can spread their studies as well as developing new researches. One of the systems used for creation and e-journals management is the Electronic System for Journal Publishing (SEER), used in the construction of periodic portals, as well as the creation of magazines in isolation. In this purport, it is believed that the management systems and creation of e-journals should be developed (internally and externally) according to the needs of its users. In the case of internal development, some of these processes refer to the copyright registration and submission of articles, which, in turn, are relevant tasks in the editorial process. Thus, the proposed study, thematic Usability of scientific journals, aims to analyze the usability of the copyright registration process and submission of articles in the Electronic System for Journal Publishing through BiblioCanto magazine, part of the Electronic Journals Portal of the Federal University of Rio Grande do Norte (UFRN). For the realization of the research, two valuation techniques were used: the Usability Test with a total of twenty participants and the Cooperative Evaluation, with the same number of participants separated in four categories considered target audience of that magazine, namely: undergraduate students, graduate students, teachers and librarians. The results indicated that the two analyzed processes (copyright registration and submission of articles) need improvement. In the case of the registration process, the following needs are: signalizing of the conducting registration ambient; description and exclusion of requested information on the registration form. In the process of article submission, it is emphasized improvement of aspects: the early steps to submission, signaling of required fields, concise description of the steps, minimization and review of the steps. To this end, it is believed that in general idea the SEER partially meets the needs of its users regarding the usability of such software.

Testes cosmológicos aplicados a modelos de energia escura

A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.

Testes cosmológicos aplicados a modelos de energia escura

A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.

Optimized square Fresnel zone plates for microoptics applications

Polygonal Fresnel zone plates with a low number of sides have deserved attention in micro and nanoptics, because they can be straightforwardly integrated in photonic devices, and, at the same time, they represent a balance between the high-focusing performance of a circular zone plate and the easiness of fabrication at micro and nano-scales of polygons. Among them, the most representative family are Square Fresnel Zone Plates (SFZP). In this work, we propose two different customized designs of SFZP for optical wavelengths. Both designs are based on the optimization of a SFZP to perform as close as possible as a usual Fresnel Zone Plate. In the first case, the criterion followed to compute it is the minimization of the difference between the area covered by the angular sector of the zone of the corresponding circular plate and the one covered by the polygon traced on the former. Such a requirement leads to a customized polygon-like Fresnel zone. The simplest one is a square zone with a pattern of phases repeating each five zones. On the other hand, an alternative SFZP can be designed guided by the same criterion but with a new restriction. In this case, the distance between the borders of different zones remains unaltered. A comparison between the two lenses is carried out. The irradiance at focus is computed for both and suitable merit figures are defined to account for the difference between them.

Efeito da concentração de sólidos e de variáveis operacionais no desempenho de um hidrociclone concentrador

The hydrocycloning operation has a goal to separate solid-liquid suspensions and liquid-liquid emulsions through the centrifugal force action. Hydrocyclones are equipment with reduced size and used in both clarification and thickening. This device is used in many areas, like petrochemical and minerals process, and accumulate advantages like versatility and low cost of maintenance. However, the demand to improve the process and to reduce the costs has motivated several studies of equipment optimization. The filtering hydrocyclone is a non-conventional equipment developed at FEQUI/UFU with objective to improve the hydrocycloning separation efficiency. The purpose of this study is to evaluate the operating conditions of feed concentration and underflow diameter on the performance of a filtering geometry optimized to minimization of energy costs. The filtration effect was investigated through the comparison between the performance of the Optimized Filtering Hydrocyclone (HCOF) and the Optimized Concentrator Hydrocyclone (HCO). Because of the resemblance of hydrocyclones performance, the filtration did not represent significant effect on the performance of the HCOF. It was found that in this geometry the decrease of the variable underflow diameter was very favorable to thickening operation. The suspension concentration of quartzite at 1.0% of solids in volume was increased about 42 times when the 3 mm underflow diameter was used. The increase on the feed solid percentage was good for decreasing the energy spent, so that a minimum number of Euler of 730 was achieved at CVA = 10.0%v. However, a greater amount of solids in suspension leads to a lower efficiency of the equipment. Therefore, to minimize the underflow-to-throughput ratio and keep a high efficiency level, it is indicated to work with dilute suspension (CVA = 1.0%) and 3 mm underflow diameter (η = 67%). But if it is necessary to work with high feed concentration, the use of 5 mm underflow diameter provides a rise in the efficiency. The HCO hydrocyclone was compared to the traditional family of hydrocyclones Rietema and presented advantages like higher efficiency (34% higher in average) and lower energy costs (20% lower in average). Finally, the efficiency curves and project equation have been raised for the HCO hydrocyclone each with satisfactory adjust.

A branch and efficiency algorithm for the optimal design of supply chain networks

Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.

Bayesian Emulation for Sequential Modeling, Inference and Decision Analysis

The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.

Nonholonomically Constrained Dynamics and Optimization of Rolling Isolation Systems

Rolling Isolation Systems provide a simple and effective means for protecting components from horizontal floor vibrations. In these systems a platform rolls on four steel balls which, in turn, rest within shallow bowls. The trajectories of the balls is uniquely determined by the horizontal and rotational velocity components of the rolling platform, and thus provides nonholonomic constraints. In general, the bowls are not parabolic, so the potential energy function of this system is not quadratic. This thesis presents the application of Gauss's Principle of Least Constraint to the modeling of rolling isolation platforms. The equations of motion are described in terms of a redundant set of constrained coordinates. Coordinate accelerations are uniquely determined at any point in time via Gauss's Principle by solving a linearly constrained quadratic minimization. In the absence of any modeled damping, the equations of motion conserve energy. This mathematical model is then used to find the bowl profile that minimizes response acceleration subject to displacement constraint.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Delay-Sensitive Service Request Scheduling for Cloud Computing

Cloud computing realizes the long-held dream of converting computing capability into a type of utility. It has the potential to fundamentally change the landscape of the IT industry and our way of life. However, as cloud computing expanding substantially in both scale and scope, ensuring its sustainable growth is a critical problem. Service providers have long been suffering from high operational costs. Especially the costs associated with the skyrocketing power consumption of large data centers. In the meantime, while efficient power/energy utilization is indispensable for the sustainable growth of cloud computing, service providers must also satisfy a user's quality of service (QoS) requirements. This problem becomes even more challenging considering the increasingly stringent power/energy and QoS constraints, as well as other factors such as the highly dynamic, heterogeneous, and distributed nature of the computing infrastructures, etc. In this dissertation, we study the problem of delay-sensitive cloud service scheduling for the sustainable development of cloud computing. We first focus our research on the development of scheduling methods for delay-sensitive cloud services on a single server with the goal of maximizing a service provider's profit. We then extend our study to scheduling cloud services in distributed environments. In particular, we develop a queue-based model and derive efficient request dispatching and processing decisions in a multi-electricity-market environment to improve the profits for service providers. We next study a problem of multi-tier service scheduling. By carefully assigning sub deadlines to the service tiers, our approach can significantly improve resource usage efficiencies with statistically guaranteed QoS. Finally, we study the power conscious resource provision problem for service requests with different QoS requirements. By properly sharing computing resources among different requests, our method statistically guarantees all QoS requirements with a minimized number of powered-on servers and thus the power consumptions. The significance of our research is that it is one part of the integrated effort from both industry and academia to ensure the sustainable growth of cloud computing as it continues to evolve and change our society profoundly.

Delay Assignment Optimization Strategies at Pre- Tactical and Tactical Levels

This paper compares different optimization strategies for the minimization of flight and passenger delays at two levels: pre-tactical, with on-ground delay at origin, and tactical, with airborne delay close to the destination airport. The optimization model is based on the ground holding problem and uses various cost functions. The scenario considered takes place in a busy European airport and includes realistic values of traffic. Uncertainty is introduced in the model for the passenger allocation, minimum time required for turnaround and tactical uncertainty. Performance of the various optimization processes is presented and compared to ratio by schedule results.

GIS technologies and spatial organization patterns among hunter-gatherers: an archaeological case study from Southern Patagonia (southern South America)

This paper discusses some aspects of hunter-gatherer spatial organization in southern South Patagonia, in later times to 10,000 cal yr BP. Various methods of spatial analysis, elaborated with a Geographic Information System (GIS) were applied to the distributional pattern of archaeological sites with radiocarbon dates. The shift in the distributional pattern of chronological information was assessed in conjunction with other lines of evidence within a biogeographic framework. Accordingly, the varying degrees of occupation and integration of coastal and interior spaces in human spatial organization are explained in association with the adaptive strategies hunter-gatherers have used over time. Both are part of the same human response to changes in risk and uncertainty variability in the region in terms of resource availability and environmental dynamics.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Mathematical methods for the configuration of transportation systems with a focus on continuous and modular matrix conveyors

The lack of flexibility in logistic systems currently on the market leads to the development of new innovative transportation systems. In order to find the optimal configuration of such a system depending on the current goal functions, for example minimization of transport times and maximization of the throughput, various mathematical methods of multi-criteria optimization are applicable. In this work, the concept of a complex transportation system is presented. Furthermore, the question of finding the optimal configuration of such a system through mathematical methods of optimization is considered.