Modeling and illustrating requirement prioritization in public e-service development from a value-based perspective

A major problem in e-service development is the prioritization of the requirements of different stakeholders. The main stakeholders are governments and their citizens, all of whom have different and sometimes conflicting requirements. In this paper, the prioritization problem is addressed by combining a value-based approach with an illustration technique. This paper examines the following research question: How can multiple stakeholder requirements be illustrated from a value-based perspective in order to be prioritizable? We used an e-service development case taken from a Swedish municipality to elaborate on our approach. Our contributions are: 1) a model of the relevant domains for requirement prioritization for government, citizens, technology, finances and laws and regulations; and 2) a requirement fulfillment analysis tool (RFA) that consists of a requirement-goal-value matrix (RGV), and a calculation and illustration module (CIM). The model reduces cognitive load, helps developers to focus on value fulfillment in e-service development and supports them in the formulation of requirements. It also offers an input to public policy makers, should they aim to target values in the design of e-services.

Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

Modeling and predicting the CBOE market volatility index

This paper performs a thorough statistical examination of the time-series properties of the daily market volatility index (VIX) from the Chicago Board Options Exchange (CBOE). The motivation lies not only on the widespread consensus that the VIX is a barometer of the overall market sentiment as to what concerns investors' risk appetite, but also on the fact that there are many trading strategies that rely on the VIX index for hedging and speculative purposes. Preliminary analysis suggests that the VIX index displays long-range dependence. This is well in line with the strong empirical evidence in the literature supporting long memory in both options-implied and realized variances. We thus resort to both parametric and semiparametric heterogeneous autoregressive (HAR) processes for modeling and forecasting purposes. Our main ndings are as follows. First, we con rm the evidence in the literature that there is a negative relationship between the VIX index and the S&P 500 index return as well as a positive contemporaneous link with the volume of the S&P 500 index. Second, the term spread has a slightly negative long-run impact in the VIX index, when possible multicollinearity and endogeneity are controlled for. Finally, we cannot reject the linearity of the above relationships, neither in sample nor out of sample. As for the latter, we actually show that it is pretty hard to beat the pure HAR process because of the very persistent nature of the VIX index.

Desenvolvimento de um simulador de bombeio por cavidades progressivas

The method of artificial lift of progressing cavity pump is very efficient in the production of oils with high viscosity and oils that carry a great amount of sand. This characteristic converted this lift method into the second most useful one in oil fields production. As it grows the number of its applications it also increases the necessity to dominate its work in a way to define it the best operational set point. To contribute to the knowledge of the operational method of artificial lift of progressing cavity pump, this work intends to develop a computational simulator for oil wells equipped with an artificial lift system. The computational simulator of the system will be able to represent its dynamic behavior when submitted to the various operational conditions. The system was divided into five subsystems: induction motor, multiphase flows into production tubing, rod string, progressing cavity pump and annular tubing-casing. The modeling and simulation of each subsystem permitted to evaluate the dynamic characteristics that defined the criteria connections. With the connections of the subsystems it was possible to obtain the dynamic characteristics of the most important arrays belonging to the system, such as: pressure discharge, pressure intake, pumping rate, rod string rotation and torque applied to polish string. The shown results added to a friendly graphical interface converted the PCP simulator in a great potential tool with a didactic characteristic in serving the technical capability for the system operators and also permitting the production engineering to achieve a more detail analysis of the dynamic operational oil wells equipped with the progressing cavity pump

Structural modeling and mutational analysis of yeast eukaryotic translation initiation factor 5A reveal new critical residues and reinforce its involvement in protein synthesis

Eukaryotic translation initiation factor 5A (eIF5A) is a protein that is highly conserved and essential for cell viability. This factor is the only protein known to contain the unique and essential amino acid residue hypusine. This work focused on the structural and functional characterization of Saccharomyces cerevisiae eIF5A. The tertiary structure of yeast eIF5A was modeled based on the structure of its Leishmania mexicana homologue and this model was used to predict the structural localization of new site-directed and randomly generated mutations. Most of the 40 new mutants exhibited phenotypes that resulted from eIF-5A protein-folding defects. Our data provided evidence that the C-terminal alpha-helix present in yeast eIF5A is an essential structural element, whereas the eIF5A N-terminal 10 amino acid extension not present in archaeal eIF5A homologs, is not. Moreover, the mutants containing substitutions at or in the vicinity of the hypusine modification site displayed nonviable or temperature-sensitive phenotypes and were defective in hypusine modification. Interestingly, two of the temperature-sensitive strains produced stable mutant eIF5A proteins - eIF5A(K56A) and eIF5A(Q22H,L93F)- and showed defects in protein synthesis at the restrictive temperature. Our data revealed important structural features of eIF5A that are required for its vital role in cell viability and underscored an essential function of eIF5A in the translation step of gene expression.

Ultrasonic density measurement cell design and simulation of non-ideal effects

This paper presents a theoretical analysis of a density measurement cell using an unidimensional model composed by acoustic and electroacoustic transmission lines in order to simulate non-ideal effects. The model is implemented using matrix operations, and is used to design the cell considering its geometry, materials used in sensor assembly, range of liquid sample properties and signal analysis techniques. The sensor performance in non-ideal conditions is studied, considering the thicknesses of adhesive and metallization layers, and the effect of residue of liquid sample which can impregnate on the sample chamber surfaces. These layers are taken into account in the model, and their effects are compensated to reduce the error on density measurement. The results show the contribution of residue layer thickness to density error and its behavior when two signal analysis methods are used. (c) 2006 Elsevier B.V. All rights reserved.

Modeling and Experimental Aspects of Self-healing Bolted Joint through Shape Memory Alloy Actuators

Bolted joints are a form of mechanical coupling largely used in machinery due to their reliability and low cost. Failure of bolted joints can lead to catastrophic events, such as leaking, train derailments, aircraft crashes, etc. Most of these failures occur due to the reduction of the pre-load, induced by mechanical vibration or human errors in the assembly or maintenance process. This article investigates the application of shape memory alloy (SMA) washers as an actuator to increase the pre-load on loosened bolted joints. The application of SMA washer follows a structural health monitoring procedure to identify a damage (reduction in pre-load) occurrence. In this article, a thermo-mechanical model is presented to predict the final pre-load achieved using this kind of actuator, based on the heat input and SMA washer dimension. This model extends and improves on the previous model of Ghorashi and Inman [2004, "Shape Memory Alloy in Tension and Compression and its Application as Clamping Force Actuator in a Bolted Joint: Part 2 - Modeling," J. Intell. Mater. Syst. Struct., 15:589-600], by eliminating the pre-load term related to nut turning making the system more practical. This complete model is a powerful but complex tool to be used by designers. A novel modeling approach for self-healing bolted joints based on curve fitting of experimental data is presented. The article concludes with an experimental application that leads to a change in joint assembly to increase the system reliability, by removing the ceramic washer component. Further research topics are also suggested.

Effects of cement thickness and bonding on the failure loads of CAD/CAM ceramic crowns: Multi-physics FEA modeling and monotonic testing

Objective. To determine the influence of cement thickness and ceramic/cement bonding on stresses and failure of CAD/CAM crowns, using both multi-physics finite element analysis and monotonic testing.Methods. Axially symmetric FEA models were created for stress analysis of a stylized monolithic crown having resin cement thicknesses from 50 to 500 mu m under occlusal loading. Ceramic-cement interface was modeled as bonded or not-bonded (cement-dentin as bonded). Cement polymerization shrinkage was simulated as a thermal contraction. Loads necessary to reach stresses for radial cracking from the intaglio surface were calculated by FEA. Experimentally, feldspathic CAD/CAM crowns based on the FEA model were machined having different occlusal cementation spaces, etched and cemented to dentin analogs. Non-bonding of etched ceramic was achieved using a thin layer of poly(dimethylsiloxane). Crowns were loaded to failure at 5 N/s, with radial cracks detected acoustically.Results. Failure loads depended on the bonding condition and the cement thickness for both FEA and physical testing. Average fracture loads for bonded crowns were: 673.5 N at 50 mu m cement and 300.6 N at 500 mu m. FEA stresses due to polymerization shrinkage increased with the cement thickness overwhelming the protective effect of bonding, as was also seen experimentally. At 50 mu m cement thickness, bonded crowns withstood at least twice the load before failure than non-bonded crowns.Significance. Occlusal "fit" can have structural implications for CAD/CAM crowns; pre-cementation spaces around 50-100 mu m being recommended from this study. Bonding benefits were lost at thickness approaching 450-500 mu m due to polymerization shrinkage stresses. (C) 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Dynamic Scaling and Growth Kinetics of 3-Glycidoxypropyltrimethoxysilane-Derived Organic/Silica Hybrids

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

High precision calculation of multipolar dynamic polarizabilities and two- and three-body dispersion coefficients of atomic hydrogen

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Molecular modeling and small angle X-ray scattering studies of Hoplosternum littorale cathodic haemoglobin

Considerable interest is currently focused on fish haemoglobins in order to identify the structural basis for their diversity of functional behavior. Hoplosternum littorale is a catfish that presents bimodal gill (water)/gut (air) -breathing, which allows this species to survive in waters with low oxygen content. The hemolysate of this fish showed the presence of two main haemoglobins, cathodic and anodic. This work describes structural features analyzed here by integration of molecular modeling with small angle X-ray scattering. Here is described a molecular model for the cathodic haemoglobin in the unliganded and liganded states. The models were determined by molecular modeling based on the high-resolution crystal structure of fish haemoglobins. The structural models for both forms of H. littorale haemoglobin were compared to human haemoglobin. (C) 2004 Elsevier B.V. All rights reserved.

OUTPUT CONTROL WITH DYNAMIC COMPENSATORS AND STRICTLY POSITIVE REAL SYSTEMS

We present new results on the output control of uncertain dynamical systems. The design method uses dynamical compensators to turn the compensated plant into a strictly positive real system, and then chooses the control law-for example, a sliding mode control. This result is compared with another result from the literature which uses static compensators. An example is presented where the control with dynamic compensation works while a static compensation does not.

Absorption and fluorescence of Er3+-doped LiYF4: Measurements and simulation

Er3+:LiYF4 single crystal has been studied by absorption and fluorescence spectroscopy in the IR-visible-UV (0-44000 cm-1) region from 4.2 K to room temperature. Polarized spectra were recorded in order to assign numerous Stark levels of electronic transitions mentioned but not attributed before in the related literature and to discuss the irreducible representations (irreps) of the 4I15/2 sublevels. A parametric hamiltonian, including free ion (Eν, α, β, γ, Tλ, ζ, Mk and Pi) and crystal field parameters (B2 0, B4 0, B4 4, B6 0 and B6 4) in an approximate D2d symmetry for the rare earth site in this scheelite type structure, was used to simulate 109 energy positions of the Er ion with a r.m.s. standard deviation of 14.6 cm-1. A comparison with previously published results for Nd3+ in the same matrix is done. © 1998 Elsevier Science S.A.

Modeling and identification of fertility maps using artificial neural networks

The application of agricultural fertilizers using variable rates along the field can be made through fertility maps previously elaborated or through real-time sensors. In most of the cases applies maps previously elaborated. These maps are identified from analyzes done in soil samples collected regularly (a sample for each field cell) or irregularly along the field. At the moment, mathematical interpolation methods such as nearest neighbor, local average, weighted inverse distance, contouring and kriging are used for predicting the variables involved with elaboration of fertility maps. However, some of these methods present deficiencies that can generate different fertility maps for a same data set. Moreover, such methods can generate inprecise maps to be used in precision farming. In this paper, artificial neural networks have been applied for elaboration and identification of precise fertility maps which can reduce the production costs and environmental impacts.