Exploring the Belief Systems of Software Development Professionals

It is commonly accepted that an individual's beliefs and actions are based on his or her assessment and perceptions of the world. In order to determine what practices an individual is likely to follow at any given time, it is necessary to understand the individual's behavioral intention in a given circumstance. From an Information Technology perspective, a software development professional's belief systems are potentially the basis for the adoption and implementation of new and innovative work practices and processes. In this article, we explore the belief systems of software development professionals in order to understand the beliefs underlying intention and practice, and we seek answers about how they adopt or reject new and innovative software development processes and practices. The results point out a strong influence of past experiences, personality types, and repeated behavior on current software development processes and practices in industrial settings.     

Vegetation water content during SMEX04 from ground data and Landsat 5 Thematic Mapper imagery

Vegetation water content is an important parameter for retrieval of soil moisture from microwave data and for other remote sensing applications. Because liquid water absorbs in the shortwave infrared, the normalized difference infrared index (NDII), calculated from Landsat 5 Thematic Mapper band 4 (0.76-0.90 μm wavelength) and band 5 (1.55-1.65 μm wavelength), can be used to determine canopy equivalent water thickness (EWT), which is defined as the water volume per leaf area times the leaf area index (LAI). Alternatively, average canopy EWT can be determined using a landcover classification, because different vegetation types have different average LAI at the peak of the growing season. The primary contribution of this study for the Soil Moisture Experiment 2004 was to sample vegetation for the Arizona and Sonora study areas. Vegetation was sampled to achieve a range of canopy EWT; LAI was measured using a plant canopy analyzer and digital hemispherical (fisheye) photographs. NDII was linearly related to measured canopy EWT with an R² of 0.601. Landcover of the Arizona, USA, and Sonora, Mexico, study areas were classified with an overall accuracy of 70% using a rule-based decision tree using three dates of Landsat 5 Thematic Mapper imagery and digital elevation data. There was a large range of NDII per landcover class at the peak of the growing season, indicating that canopy EWT should be estimated directly using NDII or other shortwave-infrared vegetation indices. However, landcover classifications will still be necessary to obtain total vegetation water content from canopy EWT and other data, because considerable liquid water is contained in the non-foliar components of vegetation.     

Stability under vacuum of silicon trap detectors and their use as transfer instruments in cryogenic radiometry

The stability of the responsivity of trap detectors under vacuum has been studied by means of a special chamber designed for the test of photodetectors at low pressure. The first experiments at a wavelength of 647 nm show that the responsivity variations are smaller than the uncertainties of the measurements, approximately 3 parts in 10(5), when the detector operates successively in air, under vacuum, and then again in air. Calculations based on experiments with single windowless photodiodes indicate that the change in trap responsivity that is due to vacuum effects should be smaller than 1 part in 10(5), at least in the visible part of the wavelength range. This stability makes trap detectors suitable for cryogenic radiometry when one uses transfer detectors under vacuum.     

An assessment of total RMR classification system using unified simulation model based on artificial neural networks

Engineering design has great importance in the cost and safety of engineering structures. Rock mass rating (RMR) system has become a reliable and widespread pre-design system for its ease of use and variety in engineering applications such as tunnels, foundations, and slopes. In RMR system, six parameters are employed in classifying a rock mass: uniaxial compressive strength of intact rock material (UCS), rock quality designation (RQD), spacing of discontinuities (SD), condition of discontinuities (CD), condition of groundwater (CG), and orientation of discontinuities (OD). The ratings of the first three parameters UCS, RQD, and SD are determined via graphic readings where the last three parameters CD, CG, and OD are estimated by the tables that are composed of interval valued linguistic expressions. Because of these linguistic expresions, the estimated rating values of the last three become fuzzy especially when the related conditions are close to border of any two classes. In such cases, these fuzzy situations could lead up incorrect rock class estimations. In this study, an empirical database based on the linguistic expressions for CD, CG, and OD is developed for training Artificial Neural Network (ANN) classifiers. The results obtained from graphical readings and ANN classifiers are unified in a simulation model (USM). The data obtained from five different tunnels, which were excavated for derivation purpose, are used to evaluate classification results of conventional method and proposed model. Finally, it is noted that more accurate and realistic ratings are reached by means of proposed model.     

Pitch angle control in wind turbines above the rated wind speed by multi-layer perceptron and radial basis function neural networks

In wind energy conversion systems, one of the operational problems is the changeability and discontinuity of wind. In most cases, wind speed can fluctuate rapidly. Hence, quality of produced energy becomes an important problem in wind energy conversion plants. Several control techniques have been applied to improve the quality of power generated from wind turbines. Pitch control is the most efficient and popular power control method, especially for variable-speed wind turbines. It is a useful method for power regulation above the rated wind speed. This paper proposes an artificial neural network-based pitch angle controller for wind turbines. In the simulations, a variable-speed wind turbine is modeled, and its operation is observed by using two types of artificial neural network controllers. These are multi-layer perceptrons with back propagation learning algorithm and radial basis function network. It is shown that the power output was successfully regulated during high wind speed, and as a result overloading or outage of the wind turbine was prevented.     

Contribution of laser microdissection-based technology to proteomic analysis in hepatocellular carcinoma developing on cirrhosis

Hepatocellular carcinoma (HCC) is a major cause of cancer worldwide. Proteomic studies provide opportunities to uncover targets for the diagnosis and treatment of this disease. However, in HCC developing in a setting of cirrhosis, the detection of proteome alterations may be hampered by the increased cellular heterogeneity of tissue when analysing global liver homogenates. The aim of this study was to evaluate whether the identification of proteome alterations in these HCC cases was improved when the differential protein profile between tumour and non-tumour areas of liver was determined using hepatocytes isolated by laser microdissection (LM). Differential profiles established with LM-hepatocytes and liver section homogenates using 2-DE and MS exhibited noticeable differences: 30% of the protein spots with deregulated expression in tumorous LM-samples did not display any modification in homogenates; conversely 15% of proteins altered in tumorous homogenates were not impaired in LM-hepatocytes. These alterations resulted from the presence in cirrhotic liver of fibrotic stroma which displayed a protein pattern different from that determined in LM-hepatocytes. In conclusion, our data demonstrate the interest of LM in distinguishing between fibrotic and hepatocyte proteome alterations and thus the benefit of LM to proteome studies of HCC developing in a context of cirrhosis.     

A spectral Integral method (SIM) for layered media

A spectral integral method is presented for electromagnetic scattering from dielectric and perfectly electric conducting (PEC) objects with a closed boundary embedded in a layered medium. Two-dimensional layered medium Green's functions are computed adaptively by using Gaussian quadratures. The singular terms in the Green's functions and the non-smooth terms in their derivatives are handled appropriately to achieve exponential convergence. Numerical results, compared with the ones obtained by using other methods, demonstrate the spectral accuracy and high efficiency of the proposed method. They also confirm that the spectral integral method (SIM) is applicable to concave objects.     

Layered precursors for new zeolitic materials: Synthesis and characterization of B-RUB-39 and its condensation product B-RUB-41

Condensation of layered silicate precursors leads to new, all silica zeolite frameworks. In order to introduce catalytic functionality, boron has been substituted into the silicate layer of RUB-39 in a single step synthesis process. Condensation of the silicate layer to the zeolite framework of RUB-41, RRO framework structure type, preserved B as constituent of the material. Analysis of structural details obtained from Rietveld analysis of powder diffraction data, ¹¹B and ²⁹Si NMR experiments of the as synthesized precursor as well as of the zeolite condensation product, and crystal chemical reasoning indicates segregation of B on one specific T-site. This T-site is buried in the silicate anionic layer of the precursor shielding the additional negative charge introduced by the trivalent T-atom.     

Mechanochemical processing and microstructural characterization of pure Fe2B nanocrystals

The results of current investigation demonstrate that mechanochemical processing can be used to synthesize high purity Fe₂B nanocrystals by selecting well-optimized milling conditions, reaction paths and proper starting materials. Microstructure, phase analyses, specific surface area, and magnetic properties of the synthesized nanocrystals were examined by using X-ray diffraction/spectroscopy, electron microscopy, nitrogen adsorption–desorption methods following Brunauer-Emmett-Teller equation and vibrating sample magnetometer techniques, respectively. Removal of MgO impurity phase by leaching the resulting powder in the acetic acid solution yielded single phase Fe₂B nanocrystals with the crystallite size and specific surface area of 12.5 nm and 29 m²/g, respectively. Magnetization results clearly indicated the ferromagnetic behavior of Fe₂B nanocrystals with saturation magnetization observed around 96.26 emu·g^?1. Electron microscope images revealed coaxial/spherical powder shape and morphology of the single-phase Fe₂B nanocrystals.