Temperature measurements in the boron carbide manufacturing process - A hot model study

Boron carbide is produced in a heat resistance furnace using boric oxide and petroleum coke as the raw materials. The product yield is very low. Heat transfer plays an important role in the formation of boron carbide. Temperature at the core reaches up to 2600 K. No experimental study is available in the open literature for this high temperature process particularly in terms of temperature measurement and heat transfer. Therefore, a laboratory scale hot model of the process has been setup to measure the temperatures in harsh conditions at different locations in the furnace using various temperature measurement devices such as pyrometer and various types of thermocouple. Particular attention was paid towards the accuracy and reliability of the measured data. The recorded data were analysed to understand the heat transfer process inside the reactor and the effect of it on the formation of boron carbide.

4th International Workshop on Theory and Application of Visualizations and Human-centric Aspects in Processes

This is the fourth TAProViz workshop being run at the 13th International Conference on Business Process Management (BPM). The intention this year is to consolidate on the results of the previous successful workshops by further developing this important topic, identifying the key research topics of interest to the BPM visualization community. Towards this goal, the workshop topics were extended to human computer interaction and related domains. Submitted papers were evaluated by at least three program committee members, in a double blind manner, on the basis of significance, originality, technical quality and exposition. Three full and one position papers were accepted for presentation at the workshop. In addition, we invited a keynote speaker, Jakob Pinggera, a postdoctoral researcher at the Business Process Management Research Cluster at the University of Innsbruck, Austria.

A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Asymptotic behaviour of point processes with Markov-dependent intervals

This splitting techniques for MARKOV chains developed by NUMMELIN (1978a) and ATHREYA and NEY (1978b) are used to derive an imbedded renewal process in WOLD's point process with MARKOV-correlated intervals. This leads to a simple proof of renewal theorems for such processes. In particular, a key renewal theorem is proved, from which analogues to both BLACKWELL's and BREIMAN's forms of the renewal theorem can be deduced.

Accelerating Pseudo-Marginal MCMC using Gaussian Processes

Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

Marine resources, biophysical processes, and environmental management of a tropical shelf seaway: Torres Strait, Australia-Introduction to the special issue

This special issue of Continental Shelf Research contains 20 papers giving research results produced as part of Australia's Torres Strait Co-operative Research Centre (CRC) Program, which was funded over a three-year period during 2003-2006. Marine biophysical, fisheries, socioeconomic-cultural and extension research in the Torres Strait region of northeastern Australia was carried out to meet three aims: 1) support the sustainable development of marine resources and minimize impacts of resource use in Torres Strait; 2) enhance the conservation of the marine environment and the social, cultural and economic well being of all stakeholders, particularly the Torres Strait peoples; and 3) contribute to effective policy formulation and management decision making. Subjects covered, including commercial and traditional fisheries management, impacts of anthropogenic sediment inputs on seagrass meadows and communication of science results to local communities, have broad applications to other similar environments.

Minimizing overprocessing waste in business processes via predictive activity ordering

Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

Processes leading to the detection of tropical weed infestations during an eradication program.

The authors identify and track processes that have resulted in the detection of six tropical weeds targeted for eradication. The habitats and distributions of these species make detection by field officers and members of the public more likely than targeted searches. The eradication program is increasing the scope of detection processes by conducting and documenting activities to improve weed recognition amongst public, government and industry stakeholders.

Will biological control of Lantana camara ever succeed? Patterns, processes & prospects

Despite biocontrol research spanning over 100 years, the hybrid weed, commonly referred to as Lantana camara, is not under adequate control. Host specificity and varietal preference of released agents, climatic suitability of a region for released agents, number of agents introduced and range or area of infestation appear to play a role in limiting biocontrol success. At least one of 41 species of mainly leaf- or flower-feeding insects has been introduced, or spread, to 41 of the 70 countries or regions where lantana occurs. Over half (26) of these species have established, achieving varying levels of herbivory and presumably some degree of control. Accurate taxonomy of the plant and adaptation of potential agents to the host plant are some of the better predictors of at least establishment success. Retrospective analysis of the hosts of introduced biocontrol agents for L. camara show that a greater proportion of agents that were collected from L. camara or Lantana urticifolia established, than agents that were collected from other species of Lantana. Of the introduced agents that had established and were oligophagous, 18 out of 22 established. The proportion of species establishing, declined with the number of species introduced. However, there was no trend when oceanic islands were treated separately from mainland areas and the result is likely an artefact of how introductions have changed over time. A calculated index of the degree of herbivory due to agents known to have caused some damage per country, was not related to land area infested with lantana for mainlands nor for oceanic islands. However, the degree of herbivory is much higher on islands than mainlands. This difference between island and mainland situations may reflect population dynamics in patchy or metapopulation landscapes. Basic systematic studies of the host remain crucial to successful biocontrol, especially of hybrid weeds like L. camara. Potential biocontrol agents should be monophages collected from the most closely related species to the target weed or be phytophages that attack several species of lantana. Suitable agents should be released in the most ideal ecoclimatic area. Since collection of biocontrol agents has been limited to a fraction of the known number of phytophagous species available, biocontrol may be improved by targeting insects that feed on stems and roots, as well as the agents that feed on leaves and flowers.

Analytical model of reactive transport processes with spatially variable coefficients

Analytical solutions of partial differential equation (PDE) models describing reactive transport phenomena in saturated porous media are often used as screening tools to provide insight into contaminant fate and transport processes. While many practical modelling scenarios involve spatially variable coefficients, such as spatially variable flow velocity, v(x), or spatially variable decay rate, k(x), most analytical models deal with constant coefficients. Here we present a framework for constructing exact solutions of PDE models of reactive transport. Our approach is relevant for advection-dominant problems, and is based on a regular perturbation technique. We present a description of the solution technique for a range of one-dimensional scenarios involving constant and variable coefficients, and we show that the solutions compare well with numerical approximations. Our general approach applies to a range of initial conditions and various forms of v(x) and k(x). Instead of simply documenting specific solutions for particular cases, we present a symbolic worksheet, as supplementary material, which enables the solution to be evaluated for different choices of the initial condition, v(x) and k(x). We also discuss how the technique generalizes to apply to models of coupled multispecies reactive transport as well as higher dimensional problems.

Special Issue on Spatial Moment Techniques for Modelling Biological Processes

Over the last two decades, there has been an increasing awareness of, and interest in, the use of spatial moment techniques to provide insight into a range of biological and ecological processes. Models that incorporate spatial moments can be viewed as extensions of mean-field models. These mean-field models often consist of systems of classical ordinary differential equations and partial differential equations, whose derivation, at some point, hinges on the simplifying assumption that individuals in the underlying stochastic process encounter each other at a rate that is proportional to the average abundance of individuals. This assumption has several implications, the most striking of which is that mean-field models essentially neglect any impact of the spatial structure of individuals in the system. Moment dynamics models extend traditional mean-field descriptions by accounting for the dynamics of pairs, triples and higher n-tuples of individuals. This means that moment dynamics models can, to some extent, account for how the spatial structure affects the dynamics of the system in question.

Impact of working conditions on the quality of working life: Case manufacturing sector colombian Caribbean Region [Impacto de las Condiciones de Trabajo en Calidad de Vida Laboral: Caso del Sector Manufacturero de la Región Caribe Colombiana]

La presenta investigación centra su atención en evaluar el impacto de las Condiciones de Trabajo en la Calidad de Vida Laboral del talento humano de sector manufacturero de la región Caribe colombiana. Para analizar este proceso se entrevistaron a 518 empleados del sector. El diseño utilizado fue no experimental de tipo transversal descriptivo, puesto que a cada participante se le aplicó una entrevista con el instrumento de Condiciones de Trabajo y la Herramienta de Calidad de Vida Laboral (Condiciones Salariales y Subjetivas). Los datos fueron analizados mediante análisis de correlación y modelos de regresión logística. Los resultados mostraron que el ambiente térmico y las normas de seguridad en el trabajo afectan de forma positiva la Calidad de Vida Laboral de los empleados del sector. Estos resultados ponen de manifiesto que la relación entre las condiciones de trabajo y la CVL se basa en la competencia y distan de ser una relación lineal y simple relacionada con la consideración de la presencia o la ausencia de las condiciones de trabajo. Ello tiene implicaciones a la hora de formular políticas, programas e intervenciones para prevenir, erradicar y amortiguar los efectos negativos de las condiciones de trabajo y mejorar la seguridad industrial dentro de las empresas.

Complete and interpretable conformance checking of business processes

This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.