Modeling the Value-Based Software Process with Object-Petri-Nets

Commercial organizations increasingly need software processes sensitive to busi- ness value, quick to apply, supportive of multi-stakeholder collaboration, and capable of early analysis for subprocess consistency and compatibility. This paper and a companion paper \Applying Value-Based Software Process: An ERP Example" present our experience in ap- plying a lightweight synthesis of a Value-Based Software Quality Achievement (VBSQA) process and an Object-Petri-Net (OPN) based process model to achieve a stakeholder win- win outcome for software quality achievement in an ERP software project in China. We attempt to answer such questions as (1) whether it is possible to model various project stakeholder perspectives using formal process modeling languages in a real-world project? (2) how to make stakeholders synchronize and stabilize their value propositions, activities and commitments as needed. The companion paper presents the VBSQA process and its application to the ERP project; this paper presents the OPN-based process modeling and its application. The application results of OPN process modeling conˉrmed that (1) the OPN- based process model provided project managers with a synchronization and stabilization framework for process activities, success-critical stakeholders and their value propositions; (2) process visualization and simulation tools signiˉcantly increased management visibility and controllability for the success of the software project.     

Exploring Particle Density Effects on Partial Mobility of Steelhead Spawning Gravels

Yellowbank Creek is a small stream in coastal central California being assessed for salmonid habitat limiting factors and restoration potential. Yellowbank flows through low‐density marine mudstone bedrock, which is the gravel source for the stream. To assess the potential effects of the low‐density substrate on spawning gravels, a tracer stone study comparing the incipient motion of low‐density mudstone particles and typical density granitic particles was used to populate a logistic regression particle entrainment model. A model comparison approach was used to test the strength of the model. Results demonstrate partial mobility of both mudstone and granitic particles under boundary shear conditions ranging from 6.9 to 42.2 N m^‐2. The modelling results quantify the strong negative correlation between particle entrainment and particle density. Mudstone gravel was three times more likely to be entrained than granitic gravel, within the context of the experimental conditions. The effect of density difference on partial mobility was greater in smaller grain size fractions. This work has implications for salmonid spawning success in atypical geologic settings and may assist in prioritization of restoration efforts. Copyright © 2013 John Wiley & Sons, Ltd.     

PID controller tuning for a multivariable glass furnace process by genetic algorithm

Standard genetic algorithms (SGAs) are investigated to optimise discrete-time proportional-integral-derivative (PID) controller parameters, by three tuning approaches, for a multivariable glass furnace process with loop interaction. Initially, standard genetic algorithms (SGAs) are used to identify control oriented models of the plant which are subsequently used for controller optimisation. An individual tuning approach without loop interaction is considered first to categorise the genetic operators, cost functions and improve searching boundaries to attain the desired performance criteria. The second tuning approach considers controller parameters optimisation with loop interaction and individual cost functions. While, the third tuning approach utilises a modified cost function which includes the total effect of both controlled variables, glass temperature and excess oxygen. This modified cost function is shown to exhibit improved control robustness and disturbance rejection under loop interaction.     

Reviewing VTAM and NetView Security Controls

Abstract

The basic premise of developing any information system is to increase efficiency and manage information in an improved manner. Based on the definitions above, an information system is “a group of devices or artificial objects serving a common purpose to communicate knowledge or intelligence.” Most information systems evolve from processes that either manipulate much information or rely on complex calculations. In other words, information systems are developed either to manage information or to manipulate it. Systems are meant to receive input, manipulate the input, and provide output.     

Pseudorandom generators for combinatorial checkerboards

We define a combinatorial checkerboard to be a function f : {1, . . . , m} ^d → {1,?1} of the form ${f(u_1,\ldots,u_d)=\prod_{i=1}^df_i(u_i)}$ for some functions f _i : {1, . . . , m} → {1,?1}. This is a variant of combinatorial rectangles, which can be defined in the same way but using {0, 1} instead of {1,?1}. We consider the problem of constructing explicit pseudorandom generators for combinatorial checkerboards. This is a generalization of small-bias generators, which correspond to the case m = 2. We construct a pseudorandom generator that ${\epsilon}$ -fools all combinatorial checkerboards with seed length ${O\bigl(\log m+\log d\cdot\log\log d+\log^{3/2} \frac{1}{\epsilon}\bigr)}$ . Previous work by Impagliazzo, Nisan, and Wigderson implies a pseudorandom generator with seed length ${O\bigl(\log m+\log^2d+\log d\cdot\log\frac{1}{\epsilon}\bigr)}$ . Our seed length is better except when ${\frac{1}{\epsilon}\geq d^{\omega(\log d)}}$ .     

How to “alternatize” a clustering algorithm

Given a clustering algorithm, how can we adapt it to find multiple, nonredundant, high-quality clusterings? We focus on algorithms based on vector quantization and describe a framework for automatic ‘alternatization’ of such algorithms. Our framework works in both simultaneous and sequential learning formulations and can mine an arbitrary number of alternative clusterings. We demonstrate its applicability to various clustering algorithms—k-means, spectral clustering, constrained clustering, and co-clustering—and effectiveness in mining a variety of datasets.     

Validation of a morphometric reconstruction technique applied to a juvenile pelvis

Three-dimensional reconstructions of bone geometry from microCT (computed tomography) data are frequently used in biomechanical and finite element analyses. Digitization of bone models is usually a simple process for specimens with a complete geometry, but in instances of damage or disarticulation it can be very challenging. Subsequent to digitization, further imaging techniques are often required to estimate the geometry of missing bone or connecting cartilage. This paper presents an innovative approach to the reconstruction of incomplete scan data, to reproduce proper anatomical arrangements of bones, including absent connecting cartilaginous elements. Utilizing geometric morphometric tools, the reconstruction technique is validated through comparison of a reconstructed 9 year old pelvis, to the original CT data. A principal component analysis and an overlay of the two pelves provide a measure of the accuracy of the reconstructed model. Future work aims to investigate the biomechanical effects of any minor positional error on the bone's predicted structural properties through the use of finite element analysis.     

Flow measurements in sewers based on image analysis: automatic flow velocity algorithm

Discharges of combined sewer overflows (CSOs) and stormwater are recognized as an important source of environmental contamination. However, the harsh sewer environment and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. An in situ system for sewer water flow monitoring based on video images was evaluated. Algorithms to determine water velocities were developed based on image-processing techniques. The image-based water velocity algorithm identifies surface features and measures their positions with respect to real world coordinates. A web-based user interface and a three-tier system architecture enable remote configuration of the cameras and the image-processing algorithms in order to calculate automatically flow velocity on-line. Results of investigations conducted in a CSO are presented. The system was found to measure reliably water velocities, thereby providing the means to understand particular hydraulic behaviors.     

Samplinghelper a web-based tool to assess the reliability of sampling strategies in sewers and receiving waters

Sampling is a key step in the analysis of chemical compounds. It is particularly important in the environmental field, for example for wastewater effluents, wet-weather discharges or streams in which the flows and concentrations vary greatly over time. In contrast to the improvements that have occurred in analytical measurement, developments in the field of sampling are less active. However, sampling errors may exceed by an order of magnitude those related to analytical processes. We proposed an Internet-based application based on a sampling theory to identify and quantify the errors in the process of taking samples. This general theory of sampling, already applied to different areas, helps to answer questions related to the number of samples, their volume, their representativeness, etc. The use of the internet to host this application facilitates use of theoretical tools and raise awareness of the uncertainties related to sampling. An example is presented, which highlights the importance of the sampling step in the quality of analytical results.