A generalization of the octonion Fourier transform to 3-D octonion-valued signals: properties and possible applications to 3-D LTI partial differential systems

Multidimensional Systems and Signal Processing - The paper is devoted to the development of the octonion Fourier transform (OFT) theory initiated in 2011 in articles by Hahn and Snopek. It is also...     

Application of piece‐wise linear weight functions for 2D 8‐node quadrilateral element in contact problems

The present study is a continuation of our previous work with the aim to reduce problems caused by standard higher order elements in contact problems. The difficulties can be attributed to the inherent property of the Galerkin method which gives uneven distributions of nodal forces resulting in oscillating contact pressures. The proposed remedy is use of piece‐wise linear weight functions. The methods to establish stiffness and/or mass matrix for 8‐node quadrilateral element in 2D are presented, i.e. the condensing and direct procedures. The energy and nodal displacement error norms are also checked to establish the convergence ratio. Interpretation of calculated contact pressures is discussed. Two new 2D 8‐node quadrilateral elements, QUAD8C and QUAD8D, are derived and tested in many examples, which show their good performance in contact problems. Copyright © 2004 John Wiley & Sons, Ltd.     

Simulation of Temperature Distribution in Stored Wheat without Aeration

A neural-deterministic simulation model applied for calculating distributions of temperatures and moisture content in a bed of wheat stored in a steel silo without aeration is presented in the article. The model consists of differential equations of heat and moisture transfer, initial and boundary conditions, and three artificial neural networks used during simulated ambient air conditions. Experiments and computer simulations were carried out in order to determine temperature fields in wheat grain stored in a steel silo for two months. The computer simulations were carried using MATLAB and FEMLAB software. The difference between measured and simulated temperature in grain near the silo wall at a height of 2.5 m from the bottom was less than 3.0°C. On the basis of the analysis performed it was concluded that the temperature distributions obtained with the model were consistent with the measured results obtained for grain stored in a steel silo without aeration.     

Microprocessor debugging techniques and their application in debugger design

Every microprocessor-based system needs powerful debugging tools. Debugging power strongly depends on a mechanism of control exchange between the debugger and an application program. Several implementation methods of such a mechanism are briefly described and compared in this paper. It is shown that conditional breakpoints facilitate a semantics-oriented approach to program debugging. Some debugging techniques derived from elementary control-exchange mechanisms are proposed. Most of the techniques discussed are implemented in the MD-86 debugger designed for the Intel 8086 microprocessor. The debugger itself is also briefly described.     

The influence of biomass co-combustion on boiler fouling and efficiency

The paper presents an attempt to evaluate the influence of biomass co-combustion on the fouling of boiler convection surfaces. In order to show the influence of co-firing biomass with bituminous coal on boiler efficiency, the calculations of pulverized fuel (PF) OP 140 steam generator have been carried out. Typical Upper Silesian coal with medium fouling inclination has been chosen as a basic fuel. Three kinds of biomass have been taken into consideration: straw, wood and dried sewage sludge. The results confirm that the properties of additional fuels cause deterioration of the boiler efficiency as well as the changes in boilers operational parameters (amount of water injected in attemperators, ash stream, hot air temperature). The biomass during cofiring in fact replaces the coal, but always the additional fuel consumption is higher than that of the substituted coal. Therefore, the actual decrease of coal consumption is smaller than the thermal fraction of the biomass.     

On the effectiveness of early life cycle defect prediction with Bayesian Nets

Standard practice in building models in software engineering normally involves three steps: collecting domain knowledge (previous results, expert knowledge); building a skeleton of the model based on step 1 including as yet unknown parameters; estimating the model parameters using historical data. Our experience shows that it is extremely difficult to obtain reliable data of the required granularity, or of the required volume with which we could later generalize our conclusions. Therefore, in searching for a method for building a model we cannot consider methods requiring large volumes of data. This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. The approach supports (1) and (2), does not require (3), yet still makes accurate defect predictions (an R ² of 0.93 between predicted and actual defects). Since our method does not require detailed domain knowledge it can be applied very early in the process life cycle. The model incorporates a set of quantitative and qualitative factors describing a project and its development process, which are inputs to the model. The model variables, as well as the relationships between them, were identified as part of a major collaborative project. A dataset, elicited from 31 completed software projects in the consumer electronics industry, was gathered using a questionnaire distributed to managers of recent projects. We used this dataset to validate the model by analyzing several popular evaluation measures (R ², measures based on the relative error and Pred). The validation results also confirm the need for using the qualitative factors in the model. The dataset may be of interest to other researchers evaluating models with similar aims. Based on some typical scenarios we demonstrate how the model can be used for better decision support in operational environments. We also performed sensitivity analysis in which we identified the most influential variables on the number of residual defects. This showed that the project size, scale of distributed communication and the project complexity cause the most of variation in number of defects in our model. We make both the dataset and causal model available for research use.