Are genetic algorithms useful for the parameter estimation of FM signals?

The estimation of polynomial-phase signals (PPSs) is a multiparameter problem, and the maximum likelihood (ML) optimization functions have numerous local optima, making the application of gradient techniques impossible. The common solution to this problem is based on the phase differentiation (PD) techniques that reduce the number of dimensions but, at the same time, reduce the accuracy and generate additional difficulties such as spurious components and error propagation. Here we show that genetic algorithms (GAs) can serve as a powerful alternative to the PD techniques. We investigate the limits of accuracy of the ML technique, and of some alternatives such as the high-order cubic phase function (HO-CPF) and high-order Wigner distribution (HO-WD). The ML approach combined with the proposed GA setup is limited up to the fifth-order PPS, which is not sufficient in many applications. However, the HO-CPF and HO-WD techniques coupled with the GA are able to accurately estimate phase parameters up to the tenth-order PPS. They significantly improve the accuracy with respect to the high-order ambiguity function (HAF) and product HAF (PHAF) and, for higher-order PPSs, they are much simpler and more efficient than the integrated generalized ambiguity function (IGAF).     

Enhancing design-for-test for active analog filters by using CLP(ℜ)

We describe a computer-aided approach to automatic fault isolation in active analog filters which enhances the design-for-test (DFT) methodology proposed by Soma (1990). His primary concern was in increased controllability and observability while the fault isolation procedure was sketched only in general terms. We operationalize and extend the DFT methodology by using CLP() to model analog circuits and by a model-based diagnosis approach to implement a diagnostic algorithm. CLP() is a logic programming language which combines symbolic and numeric computation. The diagnostic algorithm uses different DFT test modes and results of voltage measurements for different frequencies and computes a set of suspected components. Ranking of suspected components is based on a measure of (normalized) standard deviations from predicted mean values of component parameters. The diagnosis is performed incrementally, in each step reducing the set of potential candidates for the detected fault. Case studies show encouraging results in isolation of soft faults of a given low-pass biquad filter.     

Awareness Support in Distributed Software Development: A Systematic Review and Mapping of the Literature

The developers’ physical dispersion in Distributed Software Development (DSD) imposes challenges related to awareness support during collaboration in such scenario. In this paper, we present a systematic literature review and mapping that gathered, analyzed, and classified studies that improve awareness support in DSD, providing an overview of the area. Our initial search returned 1967 papers, of which 91 were identified as reporting some awareness support to DSD. These papers were then analyzed, and classified according to the 3 C collaboration model and to the Gutwin et al. Awareness Framework. Our findings suggest that awareness in DSD is gaining increasingly attention, 71 out of 91 papers were published from 2006 to 2010. Most part of the papers presented tools with some awareness support. The classification showed that the coordination is by far the most supported dimension of the 3C model, while communication is the less explored. It also showed that workspace awareness elements play a central role on DSD collaboration.     

Forecasting risks of natural gas consumption in Slovenia

Efficient operation of modern energy distribution systems often requires forecasting future energy demand. This paper proposes a strategy to estimate forecasting risk. The objective of the proposed method is to improve knowledge about expected forecasting risk and to estimate the expected cash flow in advance, based on the risk model. The strategy combines an energy demand forecasting model, an economic incentive model and a risk model. Basic guidelines are given for the construction of a forecasting model that combines past energy consumption data, weather data and weather forecast. The forecasting model is required to estimate expected forecasting errors that are the basis for forecasting risk estimation. The risk estimation strategy also requires an economic incentive model that describes the influence of forecasting accuracy on the energy distribution systems’ cash flow. The economic model defines the critical forecasting error levels that most strongly influence cash flow. Based on the forecasting model and the economic model, the development of a risk model is proposed. The risk model is associated with critical forecasting error levels in the context of various influential parameters such as seasonal data, month, day of the week and temperature. The risk model is applicable to estimating the daily forecasting risk based on the influential parameters. The proposed approach is illustrated by a case study of a Slovenian natural gas distribution company.     

Utilization of waste for large capacity productions of phosphorus-containing products based on the system analysis methods

Waste from the phosphorus industry are one of the key environmental problems for manufacturers all over the world. An innovative strategy for phosphorus industry waste utilization was developed by the authors in collaboration with their colleagues within EC INCO-Copernicus ECOPHOS project. The first stage involves the analysis of main indicators of innovative development of leading phosphorus sector companies taking into account the influence of innovations on reduction of environmental pollution. At the second stage, a strategy was developed for phosphorus industry waste utilization, which was underpinned by development of an information CALS-system of marketing analysis. The analysis was done according to the following three top level criteria: the raw material and processing market analysis; analysis of processing technologies; and analysis of utilization products markets. At the third stage, analysis of the technologies of phosphorus industry waste processing was carried out on the basis flexible technology of phosphoric sludge utilization case study. The study was carried out within the advanced system of computer support—CALS-technologies (Continuous Acquisition and Life cycle Support).     

Geometry,mechanical properties and mounting of perforated plates for ballistic application

In this paper, the ballistic resistance of perforated plates made of different types of steel, mounting and geometry was investigated. Different types of steel in various heat treatment conditions were tested. Target mounting was also varied: rigid, oblique and hanging. Furthermore, four different perforated plate geometries were tested: two plate thicknesses and two hole diameters. Their behaviour was tested using impact from firing 12.7 mm M-8 API ammunition at eleven perforated plate samples. These samples were placed by means of a steel frame over a 13 mm RHA plate, at two distances. Damaged area on targets was correlated to ballistic resistance of the whole armour to find the optimal perforated plate. It was found that perforated plates, in optimized case offer a frequent fracture of the penetrating core in up to five parts. This debris is unable to penetrate the basic plate, offering mass effectiveness of the whole armour model of 1.76 and the mass effectiveness of the perforated plate of 5.91.