Simple Software Package Research Articles

Оценка фрактальной размерности звездообразных полимеров с разным числом лучей в компьютерном эксперименте

One of the important characteristics of a polymer molecule is its fractal dimension. Fractals are objects whose Hausdorff dimension is fractional and exceeds the topological dimension. The main distinguishing feature of such objects is self-similarity. The fractal characteristics of polymer macromolecules largely determine the chemical, physicochemical, and physical properties of these objects, such as the Mark-Kuhn-Houwink scaling parameters, toughness, tangent of the angle of mechanical losses, and dynamic modulus of elasticity. Today the fractal properties of topologically linear polymers are studied in detail, however, the fractal properties of practically significant star polymers are still poorly studied. This is probably due to the fact that computer simulation of polymer systems by methods of classical mechanics requires lengthy calculations even on supercomputers. In this regard, it is interesting to evaluate the possibility of using relatively simple software packages such as HyperChem in molecular modeling of polymers. The purpose of the research was to determine the fractal dimension for 3, 4, 5, and 6-arm star (-CH2-CH2-)n polymers in a state of minimum potential energy in an isolated system and in a state of thermodynamic equilibrium at a constant temperature, comparing the obtained values with the fractal dimension of linear polyethylene and to mfke an assessment of the appropriateness of using the HyperChem software package for macromolecular calculations. A computer experiment was conducted using the HyperChem package. To obtain isolated molecules in a state of minimum potential energy, a simulation by the conjugate gradient method was performed. To bring the macromolecules to a state of thermodynamic equilibrium at a constant temperature, the molecular modeling in the canonical ensemble was carried out. For the studied polymers, the values of the fractal dimension and critical Flory index were calculated. The data obtained confirm the relation between fractal dimension and conformation of the macromolecule and, within the accuracy achieved, indicate the absence of fractal properties for star macromolecules with a large number of arms.

Numerical method for nonlinear optical spectroscopies: Ultrafast ultrafast spectroscopy.

We outline a novel numerical method, called Ultrafast Ultrafast (UF2) spectroscopy, for calculating the nth-order wavepackets required for calculating n-wave mixing signals. The method is simple to implement, and we demonstrate that it is computationally more efficient than other methods in a wide range of use cases. The resulting spectra are identical to those calculated using the standard response function formalism but with increased efficiency. The computational speed-ups of UF2 come from (a) nonperturbative and costless propagation of the system time-evolution, (b) numerical propagation only at times when perturbative optical pulses are nonzero, and (c) use of the fast Fourier transform convolution algorithm for efficient numerical propagation. The simplicity of this formalism allows us to write a simple software package that is as easy to use and understand as the Feynman diagrams that organize the understanding of n-wave mixing processes.

Atlas of airborne particles from Kozani area, Northern Greece

During a whole year (March 2003 to February 2004), several filters that capture airborne particles were collected from seven sampling sites spread throughout the Ptolemais-Kozani region (Western Macedonia), northern Greece. Environmental Scanning Electron Microscopy (ESEM), coupled with Energy Dispersive X-Ray analysis (EDX) was employed for the characterisation of the airborne particles. A classification of these airborne particles is attempted in this study. Aerosols with various morphological characteristics (angular, irregular, rounded, spherical, spheroidal, acicular), variable size (mostly between 5ßm and 20pm) and composition (aluminosilicates, oxides, carbonates, sulphates, metallic) were recognized. The airborne particulates were also categorized according to their origin. Geogenie, biogenic, anthropogenic (mainly fly ash released from lignite-fired power plants), carbonaceous and metalliferous (mainly iron and copper enriched) were the main categories. A database of characteristic airborne particles from Kozani area is being created using a simple software package, in order to help similar studies in the future.

Performance evaluation of prototype‐based clustering algorithms combined MDL index

AbstractClustering algorithms are used to group data depending on a distance. Best clustering analysis should be resisting the presence of outliers, less sensitive to initialization as well as the input sequence ordering. This article compares the performance among three of prototype‐based unsupervised clustering algorithms: Neural Gas (NG), Growing Neural Gas (GNG) and Robust Growing Neural Gas (RGNG). Based on NG and GNG, there are different clustering algorithms proposed and suggested in different literatures. So, in this work a comparison between the two basic clustering algorithms NG and GNG have presented using the performance evaluation of these techniques, in contrast to the RGNG which was proposed within the GNG. Another comparison due to the MDL criterion between RGNG that used MDL value as the clustering validity index, versus GNG and NG combined with MDL. Statistical estimations are applied to explain the meaning of the output results when these algorithms fed to the synthetic 2D dataset. Moreover, a simple software package is designed and implemented as an automatic clustering model for any dataset to use as a part of the neural network course. NG, GNG and RGNG algorithms are performed in the same package using a MATLAB‐based Graphical User Interface (GUI) tool. This visual tool lets the students/ researchers visualize the desired results using plots also clicking a few buttons.

The Lateralizer: a tool for students to explore the divided brain

Despite a profusion of popular misinformation about the left brain and right brain, there are functional differences between the left and right cerebral hemispheres in humans. Evidence from split-brain patients, individuals with unilateral brain damage, and neuroimaging studies suggest that each hemisphere may be specialized for certain cognitive processes. One way to easily explore these hemispheric asymmetries is with the divided visual field technique, where visual stimuli are presented on either the left or right side of the visual field and task performance is compared between these two conditions; any behavioral differences between the left and right visual fields may be interpreted as evidence for functional asymmetries between the left and right cerebral hemispheres. We developed a simple software package that implements the divided visual field technique, called the Lateralizer, and introduced this experimental approach as a problem-based learning module in a lower-division research methods course. Second-year undergraduate students used the Lateralizer to experimentally challenge and explore theories of the differences between the left and right cerebral hemispheres. Measured learning outcomes after active exploration with the Lateralizer, including new knowledge of brain anatomy and connectivity, were on par with those observed in an upper-division lecture course. Moreover, the project added to the students' research skill sets and seemed to foster an appreciation of the link between brain anatomy and function.

AmpliPHOX Colorimetric Detection on a DNA Microarray for Influenza

DNA microarrays have emerged as a powerful tool for pathogen detection.1-5 For instance, many examples of the ability to type and subtype influenza virus have been demonstrated.6-11 The identification and subtyping of influenza on DNA microarrays has applications in both public health and the clinic for early detection, rapid intervention, and minimizing the impact of an influenza pandemic. Traditional fluorescence is currently the most commonly used microarray detection method. However, as microarray technology progresses towards clinical use,1 replacing expensive instrumentation with low cost detection technology exhibiting similar performance characteristics to fluorescence will make microarray assays more attractive and cost-effective. The ampliPHOX colorimetric detection technology is intended for research applications, and has a limit of detection within one order of magnitude of traditional fluorescence11, with a main advantage being an approximate ten-fold lower instrument cost compared to the confocal microarray scanners required for fluorescence microarray detection. Another advantage is the compact size of the instrument which allows for portability and flexibility, unlike traditional fluorescence instruments. Because the polymerization technology is not as inherently linear as fluorescence detection, however, it is best suited for lower density microarray applications in which a yes/no answer for the presence of a certain sequence is desired, such as for pathogen detection arrays. Currently the maximum spot density compatible with ampliPHOX detection is ˜1800 spots/array. Because of the spot density limitations, higher density microarrays are not suitable for ampliPHOX detection. Here, we present ampliPHOX colorimetric detection technology as a method of signal amplification on a low density microarray developed for the detection and characterization of influenza viruses (FluChip). Although this protocol uses the FluChip (a DNA microarray) as one specific application of ampliPHOX detection, any microarray incorporating biotinylated target can be labeled and detected in a similar manner. The microarray design and biotinylation of the target to be captured are the responsibility of the user. Once the biotinylated target has been captured on the array, ampliPHOX detection can be performed by first tagging the array with a streptavidin-label conjugate (ampliTAG). Upon light exposure using the ampliPHOX Reader instrument, polymerization of a monomer solution (ampliPHY) occurs only in regions containing ampliTAG-labeled targets. The polymer formed can be subsequently stained with a non-toxic solution to improve visual contrast, followed by imaging and analysis using a simple software package (ampliVIEW). The entire FluChip assay from un-extracted sample to result can be performed in about 6 hours, and the ampliPHOX detection steps described above can be completed in about 30 min.

AmpliPHOX Colorimetric Detection on a DNA Microarray for Influenza

DNA microarrays have emerged as a powerful tool for pathogen detection. For instance, many examples of the ability to type and subtype influenza virus have been demonstrated. The identification and subtyping of influenza on DNA microarrays has applications in both public health and the clinic for early detection, rapid intervention, and minimizing the impact of an influenza pandemic. Traditional fluorescence is currently the most commonly used microarray detection method. However, as microarray technology progresses towards clinical use, replacing expensive instrumentation with low cost detection technology exhibiting similar performance characteristics to fluorescence will make microarray assays more attractive and cost-effective. The ampliPHOX colorimetric detection technology is intended for research applications, and has a limit of detection within one order of magnitude of traditional fluorescence, with a main advantage being an approximate ten-fold lower instrument cost compared to the confocal microarray scanners required for fluorescence microarray detection. Another advantage is the compact size of the instrument which allows for portability and flexibility, unlike traditional fluorescence instruments. Because the polymerization technology is not as inherently linear as fluorescence detection, however, it is best suited for lower density microarray applications in which a yes/no answer for the presence of a certain sequence is desired, such as for pathogen detection arrays. Currently the maximum spot density compatible with ampliPHOX detection is ˜1800 spots/array. Because of the spot density limitations, higher density microarrays are not suitable for ampliPHOX detection. Here, we present ampliPHOX colorimetric detection technology as a method of signal amplification on a low density microarray developed for the detection and characterization of influenza viruses (FluChip). Although this protocol uses the FluChip (a DNA microarray) as one specific application of ampliPHOX detection, any microarray incorporating biotinylated target can be labeled and detected in a similar manner. The microarray design and biotinylation of the target to be captured are the responsibility of the user. Once the biotinylated target has been captured on the array, ampliPHOX detection can be performed by first tagging the array with a streptavidin-label conjugate (ampliTAG). Upon light exposure using the ampliPHOX Reader instrument, polymerization of a monomer solution (ampliPHY) occurs only in regions containing ampliTAG-labeled targets. The polymer formed can be subsequently stained with a non-toxic solution to improve visual contrast, followed by imaging and analysis using a simple software package (ampliVIEW). The entire FluChip assay from un-extracted sample to result can be performed in about 6 hours, and the ampliPHOX detection steps described above can be completed in about 30 min.

Impacto dos fatores de interação homem-máquina no Enterprise Resource Planning (ERP) software design

Enterprise Resource Planning (ERP) systems integrate processes and functions across the company by using a single data repository. Today ERP systems are not only accepted as simple software packages but a core engine of a framework for business processes. Since adopters of ERP systems have a great number of alternatives during the selection process, software vendors should differentiate their product. Various differentiation policies can be applied by software vendors to achieve competitive advantage in the market. This paper is focusing on one of these policies; area of man-machine interaction. In this study, first, adaptive and intelligent characteristics for the user interface of the ERP package were explored by conducting survey to ERP system end-users. In this survey, we primarily aim to understand and model the factors that are affecting end-user satisfaction with the ERP system and its interface design. The results indicate that ease of use (EoU) and usefulness are determinants of end-user satisfaction with ERP system and its interface design. This paper discusses these findings, the models that we were inspired while we had been forming our model, our model framework and finally describes future study opportunities about human and computer interaction analysis and prototyping studies in ERP systems.

Developing a Decision Support Tool for Nighttime Construction in Highway Projects

This paper presents a decision support tool that is intended to help highway agencies in evaluating the suitability of nighttime construction for highway projects. This tool was developed as part of a research project sponsored by the Illinois Department of Transportation. The tool is a simple software package that was developed using a Microsoft Excel spreadsheet and Visual Basic for Applications. The proposed tool utilizes the cost-effectiveness analysis as a basis for comparison between daytime and nighttime operations. The proposed tool is mainly used whenever night shift is thought of as an alternative to the conventional daytime shift. Nonetheless, the tool is also generic in the sense that it can be used to compare different alternative plans such as different lane closure strategies or scheduling alternatives.

Enhancing chemical analysis with signal derivatization using simple available software packages

Derivative techniques for analytical signal processing are useful for solving some noise and signal resolution problems in various fields of study such as titrimetry, spectrophotometry, chromatography and electrochemistry. The broad use of these techniques, however, is often limited by costly inflexible built-in software packages in commercial analytical instruments. We propose here the application of commercial simple software packages such as Microsoft® Excel and Microcal Origin for signal smoothing and fitting, and for obtaining derivative analytical signals in batch and flow-based analyses, including potentiometric titration, spectrophotometry, chromatography, voltammetry and sequential injection analysis (SIA). The worldwide (especially Excel) software packages are easy-to-use for less experienced users and have also capabilities for advanced users, and therefore employing such packages can result in expansion of useful derivative techniques. We demonstrate application of the available package-aided derivative capabilities for enhancing some chemical analyses, including potentiometric acid–base titration, Bradford assay of protein, chromatographic separation of ajmaline and reserpine and anodic stripping voltammetry of copper. The derivative signals from smoothed and fitted curves offer better accuracy and precision, even for non-resolving peaks and tailing peaks. In some cases, the optimization of experimental conditions is not further required, which can lead to fast method development.

A novel method of computation and optimization for multi-layered radar absorbing coatings using open source software

We created a simple software package based on open source software (GNU/Linux). This software package combined the electromagnetic parameters database and an optimization engine based on genetic algorithms, by which we can store and manage a large number of electromagnetic parameters towards radar absorbing materials, and can also design multi-layered radar absorbing coatings (RACs) using the materials stored in the database. The electromagnetic parameters of initial materials can be obtained either from experiment measurement or from theory computation. The software package is approved to be effective in designing examples. Some tests also proved that the solution towards multi-layered RACs presented in this paper has a good performance in computation.

An Interactive Framework for Teaching Power System Harmonics

Electrical engineering education textbooks usually restrict the linking between theory and practical work in power system harmonics. This paper presents a comprehensive definition, mathematical description, and practical experiments in power harmonics. To realise the application in a real environment, a simple software package, based on FFT (Fast Fourier Transform) in the MATLAB program, to identify and analyse the power system harmonics, is introduced.

Statistical techniques for the classification of chromites in diamond exploration samples

A database of 1267 quality-screened major- and trace-element analyses of chromites (s.l.) from kimberlites, lamproites, ultramafic lamprophyres (UMLs) and crustal sources (‘greenstones’, including ophiolites, gabbros, basalts and komatiites) has been subjected to statistical analysis, in order to derive discriminants for use in diamond exploration. The techniques used included nearest-neighbour analysis, CART (classification and regression trees) and MARS (multivariate adaptive regression splines). The results show that both CART and MARS approaches can correctly discriminate kimberlite/lamproite chromites from UML/‘greenstone’ chromites at levels near 90%. Discrimination into the four classes separately is achieved at levels of ca. 80% by MARS and > 70% by CART; much of the misclassification is between the kimberlite and lamproite classes. These results probably represent the maximum probable level of discrimination on chemical criteria, given that ascending magmas may sample both mantle and crustal rocks. The CART approach produces a classification tree that requires no further computation to classify a given grain; the MARS approach requires the use of a simple software package. Tests on known samples illustrate the high level of accuracy of the methods in an exploration context, as well as the useful petrogenetic conclusions that can be drawn from some ‘misclassifications’.

Novel method for WKB analysis of multidimensional systems

The availability of powerful microcomputers with graphics capabilities expands the range of numerical procedures that can be employed for undergraduate use. The use of simple software packages for the evaluation of multidimensional WKB approximate eigenvalues is discussed. Introductory courses in quantum mechanics rarely make use of semiclassical theories, such as WKB, to relate quantum mechanics to classical mechanics. This relationship can be helpful for the student’s understanding of quantum mechanics, and a computer experiment can provide a useful avenue for making the concepts concrete. The major components of the approach involve the use of a package for the integration of differential equations, to treat the classical equations of motion, and a computer-aided design package to determine the phase integral areas. The codes are not expensive, and all exploit the graphical capabilities of microcomputers, which are critical for visualizing the relationship between classical and quantum ideas.

A logical design methodology for relational databases using the extended entity-relationship model

A database design methodology is defined for the design of large relational databases. First, the data requirements are conceptualized using an extended entity-relationship model, with the extensions being additional semantics such as ternary relationships, optional relationships, and the generalization abstraction. The extended entity-relationship model is then decomposed according to a set of basic entity-relationship constructs, and these are transformed into candidate relations. A set of basic transformations has been developed for the three types of relations: entity relations, extended entity relations, and relationship relations. Candidate relations are further analyzed and modified to attain the highest degree of normalization desired. The methodology produces database designs that are not only accurate representations of reality, but flexible enough to accommodate future processing requirements. It also reduces the number of data dependencies that must be analyzed, using the extended ER model conceptualization, and maintains data integrity through normalization. This approach can be implemented manually or in a simple software package as long as a "good" solution is acceptable and absolute optimality is not required.