Reducing control selection errors associated with underground bolting equipment

Selecting the incorrect control during the operation of underground bolting and drilling equipment causes serious injuries. Shape coding and the layout of dual control banks are two aspects of control design which require further examination. The aims of this research were: (i) to determine whether arbitrary shape coding was effective in reducing selection error rates in a virtual analogy of roof-bolting; and (ii) to determine whether any advantages exist for mirror or place layouts for dual control situations in this situation. Two experiments were conducted to address these questions. No benefits of arbitrary shape coding were evident while control location remained constant. When control location was altered, shape coding did provide a significant reduction in selection error rate. No differences between mirror or place arrangements were detected and this question remains open.     

Simulation of rotating stall in a whole stage of an axial compressor

Aerodynamic instabilities that naturally occur in compression systems, such as surge and rotating stall, largely reduce the life duration and performance of system components. The prediction of the compressor operating range is thus a key parameter for the design of gas turbines. This paper investigates the ability of an unsteady flow solver to simulate the rotating stall phenomenon in the full annulus of an axial compressor stage. A comparison with experimental data indicates that the simulation correctly estimates the stability limit. However the rotating stall flow patterns are different. While measurements show only one full span rotating stall cell (40 Hz), the simulation shows first a part span stall with 10 cells (790 Hz) that evolves then towards a full span stall with three cells (170 Hz). A spectral analysis based on numerical results underlines the role of rotor-stator interactions in the development of rotating stall. The effects of downstream volumes and inlet distortions are also discussed, showing the necessity to consider the whole geometry to correctly predict the rotating stall frequency.     

A CSP model for simple non-reversible and parallel repair plans

This work presents a constraint satisfaction problem (CSP) model for the planning and scheduling of disassembly and assembly tasks when repairing or substituting faulty parts. The problem involves not only the ordering of assembly and disassembly tasks, but also the selection of them from a set of alternatives. The goal of the plan is the minimization of the total repairing time, and the model considers, apart from the durations and resources used for the assembly and disassembly tasks, the necessary delays due to the change of configuration in the machines, and to the transportation of intermediate subassemblies between different machines. The problem considers that sub-assemblies that do not contain the faulty part are nor further disassembled, but allows non-reversible and parallel repair plans. The set of all feasible repair plans are represented by an extended And/Or graph. This extended representation embodies all of the constraints of the problem, such as temporal and resource constraints and those related to the selection of tasks for obtaining a correct plan.     

Visual extraction of information from web pages

In this paper we present a graphical software system that provides an automatic support to the extraction of information from web pages. The underlying extraction technique exploits the visual appearance of the information in the document, and is driven by the spatial relations occurring among the elements in the page. However, the usual information extraction modalities based on the web page structure can be used in our framework, too. The technique has been integrated within the Spatial Relation Query (SRQ) tool. The tool is provided with a graphical front-end which allows one to define and manage a library of spatial relations, and to use a SQL-like language for composing queries driven by these relations and by further semantic and graphical attributes.     

Parallel Approach for Ensemble Learning with Locally Coupled Neural Networks

Ensemble learning has gained considerable attention in different tasks including regression, classification and clustering. Adaboost and Bagging are two popular approaches used to train these models. The former provides accurate estimations in regression settings but is computationally expensive because of its inherently sequential structure, while the latter is less accurate but highly efficient. One of the drawbacks of the ensemble algorithms is the high computational cost of the training stage. To address this issue, we propose a parallel implementation of the Resampling Local Negative Correlation (RLNC) algorithm for training a neural network ensemble in order to acquire a competitive accuracy like that of Adaboost and an efficiency comparable to that of Bagging. We test our approach on both synthetic and real datasets from the UCI and Statlib repositories for the regression task. In particular, our fine-grained parallel approach allows us to achieve a satisfactory balance between accuracy and parallel efficiency.     

Transmission power and data rate aware routing on wireless networks

Wireless networks can vary both the transmission power and modulation of links. Existing routing protocols do not take transmission power control (TPC) and modulation adaptation (also known as rate adaptation – RA) into account at the same time, even though the performance of wireless networks can be significantly improved when routing algorithms use link characteristics to build their routes. This article proposes and evaluates extensions to routing protocols to cope with TPC and RA. The enhancements can be applied to any link state or distance vector routing protocols. An evaluation considering node density, node mobility and link error show that TPC- and RA-aware routing algorithms improve the average latency and the end-to-end throughput, while consuming less energy than traditional protocols.     

A flexible,object-centric approach for business process modelling

Mainstream business process modelling techniques often promote a design paradigm wherein the activities that may be performed within a case, together with their usual execution order, form the backbone on top of which other aspects are anchored. This Fordist paradigm, while effective in standardised and production-oriented domains, breaks when confronted with processes in which case-by-case variations and exceptions are the norm. We contend that the effective design of flexible processes calls for a substantially different modelling paradigm. Motivated by requirements from the human services domain, we explore the hypothesis that a framework consisting of a small set of coordination concepts, combined with established object-oriented modelling principles, provides a suitable foundation for designing highly flexible processes. Several human service delivery processes have been designed using this framework, and the resulting models have been used to realise a system to support these processes in a pilot environment.     

Effects of soil composition and mineralogy on remote sensing of crop residue cover

The management of crop residues (non-photosynthetic vegetation) in agricultural fields influences soil erosion and soil carbon sequestration. Remote sensing methods can efficiently assess crop residue cover and related tillage intensity over many fields in a region. Although the reflectance spectra of soils and crop residues are often similar in the visible, near infrared, and the lower part of the shortwave infrared (400-1900 nm) wavelength region, specific diagnostic chemical absorption features are evident in the upper shortwave infrared (1900-2500 nm) region. Two reflectance band height indices used for estimating residue cover are the Cellulose Absorption Index (CAI) and the Lignin-Cellulose Absorption (LCA) index, both of which use reflectances in the upper shortwave infrared (SWIR). Soil mineralogy and composition will affect soil spectral properties and may limit the usefulness of these spectral indices in certain areas. Our objectives were to (1) identify minerals and soil components with absorption features in the 2000 nm to 2400 nm wavelength region that would affect CAI and LCA and (2) assess their potential impact on remote sensing estimates of crop residue cover. Most common soil minerals had CAI values ≤ 0.5, whereas crop residues were always > 0.5, allowing for good contrast between soils and residues. However, a number of common soil minerals had LCA values > 0.5, and, in some cases, the mineral LCA values were greater than those of the crop residues, which could limit the effectiveness of LCA for residue cover estimation. The LCA of some dry residues and live corn canopies were similar in value, unlike CAI. Thus, the Normalized Difference Vegetation Index (NDVI) or similar method should be used to separate out green vegetation pixels. Mineral groups, such as garnets and chlorites, often have wide ranges of CAI and LCA values, and thus, mineralogical analyses often do not identify individual mineral species required for precise CAI estimation. However, these methods are still useful for identifying mineral soils requiring additional scrutiny. Future advanced multi- and hyperspectral remote sensing platforms should include CAI bands to allow for crop residue cover estimation.