Assessing the sustainability of wheat-based cropping systems using simulation modelling: sustainability

Concepts of agricultural sustainability and possible roles of simulation modelling for characterising sustainability were explored by conducting, and reflecting on, a sustainability assessment of rain-fed wheat-based systems in the Middle East and North Africa region. We designed a goal-oriented, model-based framework using the cropping systems model Agricultural Production Systems sIMulator (APSIM). For the assessment, valid (rather than true or false) sustainability goals and indicators were identified for the target system. System-specific vagueness was depicted in sustainability polygons-a system property derived from highly quantitative data-and denoted using descriptive quantifiers. Diagnostic evaluations of alternative tillage practices demonstrated the utility of the framework to quantify key bio-physical and chemical constraints to sustainability. Here, we argue that sustainability is a vague, emergent system property of often wicked complexity that arises out of more fundamental elements and processes. A 'wicked concept of sustainability' acknowledges the breadth of the human experience of sustainability, which cannot be internalised in a model. To achieve socially desirable sustainability goals, our model-based approach can inform reflective evaluation processes that connect with the needs and values of agricultural decision-makers. Hence, it can help to frame meaningful discussions, from which actions might emerge.

Environmental factors affecting the occurrence of periglacial landforms in Finnish Lapland: a numerical approach

Determination of the environmental factors controlling earth surface processes and landform patterns is one of the central themes in physical geography. However, the identification of the main drivers of the geomorphological phenomena is often challenging. Novel spatial analysis and modelling methods could provide new insights into the process-environment relationships. The objective of this research was to map and quantitatively analyse the occurrence of cryogenic phenomena in subarctic Finland. More precisely, utilising a grid-based approach the distribution and abundance of periglacial landforms were modelled to identify important landscape scale environmental factors. The study was performed using a comprehensive empirical data set of periglacial landforms from an area of 600 km2 at a 25-ha resolution. The utilised statistical methods were generalized linear modelling (GLM) and hierarchical partitioning (HP). GLMs were used to produce distribution and abundance models and HP to reveal independently the most likely causal variables. The GLM models were assessed utilising statistical evaluation measures, prediction maps, field observations and the results of HP analyses. A total of 40 different landform types and subtypes were identified. Topographical, soil property and vegetation variables were the primary correlates for the occurrence and cover of active periglacial landforms on the landscape scale. In the model evaluation, most of the GLMs were shown to be robust although the explanation power, prediction ability as well as the selected explanatory variables varied between the models. The great potential of the combination of a spatial grid system, terrain data and novel statistical techniques to map the occurrence of periglacial landforms was demonstrated in this study. GLM proved to be a useful modelling framework for testing the shapes of the response functions and significances of the environmental variables and the HP method helped to make better deductions of the important factors of earth surface processes. Hence, the numerical approach presented in this study can be a useful addition to the current range of techniques available to researchers to map and monitor different geographical phenomena.

Acoustic emission source location and damage detection in a metallic structure using a graph-theory-based geodesic pproach

A geodesic-based approach using Lamb waves is proposed to locate the acoustic emission (AE) source and damage in an isotropic metallic structure. In the case of the AE (passive) technique, the elastic waves take the shortest path from the source to the sensor array distributed in the structure. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. The same approach is extended for detection of damage in a structure. The wave response matrix of the given sensor configuration for the healthy and the damaged structure is obtained experimentally. The healthy and damage response matrix is compared and their difference gives the information about the reflection of waves from the damage. These waves are backpropagated from the sensors and the above method is used to locate the damage by finding the point where intersection of geodesics occurs. In this work, the geodesic approach is shown to be suitable to obtain a practicable source location solution in a more general set-up on any arbitrary surface containing finite discontinuities. Experiments were conducted on aluminum specimens of simple and complex geometry to validate this new method.

Elliptical summary randomisation for sensor-based human activity recognition

Many conventional statistical machine learning al- gorithms generalise poorly if distribution bias ex- ists in the datasets. For example, distribution bias arises in the context of domain generalisation, where knowledge acquired from multiple source domains need to be used in a previously unseen target domains. We propose Elliptical Summary Randomisation (ESRand), an efficient domain generalisation approach that comprises of a randomised kernel and elliptical data summarisation. ESRand learns a domain interdependent projection to a la- tent subspace that minimises the existing biases to the data while maintaining the functional relationship between domains. In the latent subspace, ellipsoidal summaries replace the samples to enhance the generalisation by further removing bias and noise in the data. Moreover, the summarisation enables large-scale data processing by significantly reducing the size of the data. Through comprehensive analysis, we show that our subspace-based approach outperforms state-of-the-art results on several activity recognition benchmark datasets, while keeping the computational complexity significantly low.

Block-based feature detection and matching for mosaicing of camera-captured document images

In this paper, we present a new feature-based approach for mosaicing of camera-captured document images. A novel block-based scheme is employed to ensure that corners can be reliably detected over a wide range of images. 2-D discrete cosine transform is computed for image blocks defined around each of the detected corners and a small subset of the coefficients is used as a feature vector A 2-pass feature matching is performed to establish point correspondences from which the homography relating the input images could be computed. The algorithm is tested on a number of complex document images casually taken from a hand-held camera yielding convincing results.

Essential nursing care of the critically ill patient

This chapter is about essential nursing care. Because it is often referred to as basic nursing, nurses may not always perceive it as deserving of priority. Yet, how well patients are cared for has a direct effect on their sense of wellbeing and their recovery. ‘Interventional patient hygiene’ is a systematic, evidence-based approach to nursing actions designed to improve patient outcomes using a framework of hygiene, catheter care, skin care, mobility and oral care.1 This chapter focuses on the physical care, infection control, preventative therapies and transport of critically ill patients. The first two areas are closely linked: poor-quality physical care increases the risk of infection. The final areas are essential features of critical care nursing.

An Expenditure-Based Estimation of Self-Employment Income Underreporting in Finland

This paper estimates the extent of income underreporting by the self-employed in Finland using the expenditure based approach developed by Pissarides & Weber (1989). Household spending data are for the years 1994 to 1996. The results suggest that self-employment income in Finland is underreported by some 27% on average. Since income for the self-employed is about 8 % of all incomes in Finland, the size of this part of the black economy in Finland is estimated to be about 2,3% of GDP.

Specification-driven approach for protocol design of distributed computing systems

An important issue in the design of a distributed computing system (DCS) is the development of a suitable protocol. This paper presents an effort to systematize the protocol design procedure for a DCS. Protocol design and development can be divided into six phases: specification of the DCS, specification of protocol requirements, protocol design, specification and validation of the designed protocol, performance evaluation, and hardware/software implementation. This paper describes techniques for the second and third phases, while the first phase has been considered by the authors in their earlier work. Matrix and set theoretic based approaches are used for specification of a DCS and for specification of the protocol requirements. These two formal specification techniques form the basis of the development of a simple and straightforward procedure for the design of the protocol. The applicability of the above design procedure has been illustrated by considering an example of a computing system encountered on board a spacecraft. A Petri-net based approach has been adopted to model the protocol. The methodology developed in this paper can be used in other DCS applications.

Novel approach to estimate fringe order in Moire profilometry

A novel approach to estimate fringe order in Moire topography is proposed. Along with the light source used to create shadow of the grating on the object (as in conventional moire), proposed method uses a second light source which illuminates the object with color bands from the side. Width of each colored band is set to match that height which leads to a 2 pi phase shift in moire fringes. This facilitates one to rule the object with colored bands, which can be used to estimate fringe order using a color camera with relatively low spatial resolution with out any compromise in height sensitivity. Current proposal facilitates one to extract 3D profile of objects with surface discontinuities. It also deals with the possible usage of moire topography (when combined with the proposed method) in extracting 3D surface profile of many objects with height discontinuities using a single 2D image. Present article deals with theory and simulations of this novel side illumination based approach.

On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

A checking method for probabilistic seismic-hazard assessment: case studies on three cities

The conventional Cornell's source-based approach of probabilistic seismic-hazard assessment (PSHA) has been employed all around the world, whilst many studies often rely on the use of computer packages such as FRISK (McGuire FRISK-a computer program for seismic risk analysis. Open-File Report 78-1007, United States Geological Survey, Department of Interior, Washington 1978) and SEISRISK III (Bender and Perkins SEISRISK III-a computer program for seismic hazard estimation, Bulletin 1772. United States Geological Survey, Department of Interior, Washington 1987). A ``black-box'' syndrome may be resulted if the user of the software does not have another simple and robust PSHA method that can be used to make comparisons. An alternative method for PSHA, namely direct amplitude-based (DAB) approach, has been developed as a heuristic and efficient method enabling users to undertake their own sanity checks on outputs from computer packages. This paper experiments the application of the DAB approach for three cities in China, Iran, and India, respectively, and compares with documented results computed by the source-based approach. Several insights regarding the procedure of conducting PSHA have also been obtained, which could be useful for future seismic-hazard studies.

Improved large-MIMO detection based on damped belief propagation

In this paper, we consider the application of belief propagation (BP) to achieve near-optimal signal detection in large multiple-input multiple-output (MIMO) systems at low complexities. Large-MIMO architectures based on spatial multiplexing (V-BLAST) as well as non-orthogonal space-time block codes(STBC) from cyclic division algebra (CDA) are considered. We adopt graphical models based on Markov random fields (MRF) and factor graphs (FG). In the MRF based approach, we use pairwise compatibility functions although the graphical models of MIMO systems are fully/densely connected. In the FG approach, we employ a Gaussian approximation (GA) of the multi-antenna interference, which significantly reduces the complexity while achieving very good performance for large dimensions. We show that i) both MRF and FG based BP approaches exhibit large-system behavior, where increasingly closer to optimal performance is achieved with increasing number of dimensions, and ii) damping of messages/beliefs significantly improves the bit error performance.

Modeling of nonreacting and reacting turbulent spray jets using a fully stochastic separated flow approach

Numerical modeling of several turbulent nonreacting and reacting spray jets is carried out using a fully stochastic separated flow (FSSF) approach. As is widely used, the carrier-phase is considered in an Eulerian framework, while the dispersed phase is tracked in a Lagrangian framework following the stochastic separated flow (SSF) model. Various interactions between the two phases are taken into account by means of two-way coupling. Spray evaporation is described using a thermal model with an infinite conductivity in the liquid phase. The gas-phase turbulence terms are closed using the k-epsilon model. A novel mixture fraction based approach is used to stochastically model the fluctuating temperature and composition in the gas phase and these are then used to refine the estimates of the heat and mass transfer rates between the droplets and the surrounding gas-phase. In classical SSF (CSSF) methods, stochastic fluctuations of only the gas-phase velocity are modeled. Successful implementation of the FSSF approach to turbulent nonreacting and reacting spray jets is demonstrated. Results are compared against experimental measurements as well as with predictions using the CSSF approach for both nonreacting and reacting spray jets. The FSSF approach shows little difference from the CSSF predictions for nonreacting spray jets but differences are significant for reacting spray jets. In general, the FSSF approach gives good predictions of the flame length and structure but further improvements in modeling may be needed to improve the accuracy of some details of the Predictions. (C) 2011 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

A mixture model approach for formant tracking and the robustness of student's-t distribution

We address the problem of robust formant tracking in continuous speech in the presence of additive noise. We propose a new approach based on mixture modeling of the formant contours. Our approach consists of two main steps: (i) Computation of a pyknogram based on multiband amplitude-modulation/frequency-modulation (AM/FM) decomposition of the input speech; and (ii) Statistical modeling of the pyknogram using mixture models. We experiment with both Gaussian mixture model (GMM) and Student's-t mixture model (tMM) and show that the latter is robust with respect to handling outliers in the pyknogram data, parameter selection, accuracy, and smoothness of the estimated formant contours. Experimental results on simulated data as well as noisy speech data show that the proposed tMM-based approach is also robust to additive noise. We present performance comparisons with a recently developed adaptive filterbank technique proposed in the literature and the classical Burg's spectral estimator technique, which show that the proposed technique is more robust to noise.

Assessment of seismic hazard and liquefaction potential of Gujarat based on probabilistic approaches

Gujarat is one of the fastest-growing states of India with high industrial activities coming up in major cities of the state. It is indispensable to analyse seismic hazard as the region is considered to be most seismically active in stable continental region of India. The Bhuj earthquake of 2001 has caused extensive damage in terms of causality and economic loss. In the present study, the seismic hazard of Gujarat evaluated using a probabilistic approach with the use of logic tree framework that minimizes the uncertainties in hazard assessment. The peak horizontal acceleration (PHA) and spectral acceleration (Sa) values were evaluated for 10 and 2 % probability of exceedance in 50 years. Two important geotechnical effects of earthquakes, site amplification and liquefaction, are also evaluated, considering site characterization based on site classes. The liquefaction return period for the entire state of Gujarat is evaluated using a performance-based approach. The maps of PHA and PGA values prepared in this study are very useful for seismic hazard mitigation of the region in future.