Perceptual control and feedback control in the analysis of complex tasks

Despite its extensive and successful use in the human factors specialist's work, there remain challenges for the development of task analysis. One such challenge is posed by the need to capture the features of the dynamic, complex tasks that take place in modern socio-technical systems. In this paper, we discuss the theoretical and practical implications of using perceptual control theory (PCT) as a theoretical grounding for task analysis. In particular, we describe the ability of PCT to combine the notion of perceptual control (which is similar to the assumptions underlying ecological design) with that of feedback control (which is fundamental to some traditional task analysis approaches). We describe some of the current PCT-based task analysis methods before introducing a new method that aims to integrate PCT concepts into hierarchical task analysis. Finally, we demonstrate how this method might be applied to a real-world dynamic control task.     

On the representation of automation using a work domain analysis

Work domain analysis (WDA) has been applied extensively within cognitive engineering as an analytic framework for the evaluation of complex sociotechnical systems in support of design. However, the WDAs described in the literature have not explored the representation of automated system components, despite the documented problems associated with operator-automation interaction and the requirements for operator support in complex automated systems. The current research examines the application of WDA to model an example automated system – a camera – by representing the camera along with its automated components as separate systems using the abstraction hierarchy (AH). Additionally, we contrasted this modelling approach with the more typical approach of modelling automation within a cognitive work analysis (CWA) by performing a control task analysis using the decision ladder. The results of these analyses suggest that, similar to non-automated systems, considering a separate representation of an automated system within the WDA may provide useful system design guidance in terms of user support and information requirements. The comparison of the AH and the decision ladder (DL) models indicates that the models provide different information about the requirements and support different user needs: the AH provides information about specific subsystems and components of the automation that are used for control and how they support functions and purposes of the automation while the DL shows how the control tasks are achieved interleaving automated actions with those of the user. The information obtained from modelling automation with the AH is different from what would normally be obtained by performing only a control task analysis, yet is necessary for operator support.     

A comparison of domain integral evaluation techniques for boundary element methods

In many cases, boundary integral equations contain a domain integral. This can be evaluated by discretization of the domain into domain elements. Historically, this was seen as going against the spirit of boundary element methods, and several methods were developed to avoid this discretization, notably dual and multiple reciprocity methods and particular solution methods. These involved the representation of the interior function with a set of basis functions, generally of the radial type. In this study, meshless methods (dual reciprocity and particular solution) are compared to the direct domain integration methods. The domain integrals are evaluated using traditional methods and also with multipole acceleration. It is found that the direct integration always results in better accuracy, as well as smaller computation times. In addition, the multipole method further improves on the computation times, in particular where multiple evaluations of the integral are required, as when iterative solvers are used. The additional error produced by the multipole acceleration is negligible. Copyright © 2001 John Wiley & Sons, Ltd.     

A survey on deep learning for patent analysis

Patent document collections are an immense source of knowledge for research and innovation communities worldwide. The rapid growth of the number of patent documents poses an enormous challenge for retrieving and analyzing information from this source in an effective manner. Based on deep learning methods for natural language processing, novel approaches have been developed in the field of patent analysis. The goal of these approaches is to reduce costs by automating tasks that previously only domain experts could solve. In this article, we provide a comprehensive survey of the application of deep learning for patent analysis. We summarize the state-of-the-art techniques and describe how they are applied to various tasks in the patent domain. In a detailed discussion, we categorize 40 papers based on the dataset, the representation, and the deep learning architecture that were used, as well as the patent analysis task that was targeted. With our survey, we aim to foster future research at the intersection of patent analysis and deep learning and we conclude by listing promising paths for future work.     

Some remarks on particular solution used in BEM formulation

Considerable work has been done by many investigators recently in the use of particular solution collocation methods which effectively replace the domain integrals by BEM solutions with modified boundary conditions. This technique enables us to avoid the domain integral which is the major advantage of BEM formulation.For an arbitrary distributed inhomogeneous domain term one idea is to choose a series of basis functions for which a particular solution can be found without difficulty, and then use these basis functions to interpolate the inhomogeneous term. It was pointed out that the success of the proposed particular solution method is strongly dependent on the choice of the basis function (Nardini and Brebbia, 1985; Bala and Sládeks, 1989). Tang and Brebbia (1989) compared the radial basis function with Fourier series basis function (Gründemann, 1989) and obtained the same conclusion. We are not aware of any mathematical analysis on this topic.In the paper presented here, a mathematical error analysis for thermoelasticity is done. The examples show that if there is a domain source distribution or the problem is a transient thermal conduction problem, the boundary data only is not sufficient to define the problem. In this case, the domain collocation points are very important for correct and accurate solutions.     

Fuzzy generalized fast marching method for 3D segmentation of brain structures

The aim of this work is to develop a new model for segmentation of brain structures in medical brain MR images. Brain segmentation is a challenging task due to the complex anatomical structure of brain structures as well as intensity nonuniformity, partial volume effects and noise. Generally the structures of interest are of relatively complicated size and have significant shape variations, the structures boundaries may be blurry or even missing, and the surrounding background is full of irrelevant edges. Segmentation methods based on fuzzy models have been developed to overcome the uncertainty caused by these effects. In this study, we propose a robust and accurate brain structures segmentation method based on a combination of fuzzy model and deformable model. Our method breaks up into two great parts. Initially, a preliminary stage allows to construct the various information maps, in particular a fuzzy map, used as a principal information source, constructed using the Fuzzy C‐means method (FCM). Then, a deformable model implemented with the generalized fast marching method (GFMM), evolves toward the structure to be segmented, under the action of a normal force defined from these information maps. In this sense, we used a powerful evolution function based on a fuzzy model, adapted for brain structures. Two extensions of our general method are presented in this work. The first extension concerns the addition of an edge map to the fuzzy model and the use of some rules adapted to the segmentation process. The second extension consists of the use of several models evolving simultaneously to segment several structures. Extensive experiments are conducted on both simulated and real brain MRI datasets. Our proposed approach shows promising and achieves significant improvements with respect to several state‐of‐the‐art methods and with the three practical segmentation techniques widely used in neuroimaging studies, namely SPM, FSL, and Freesurfer.     

A domain decomposition tool for boundary element methods

Domain decomposition boundary element methods have become increasingly popular over the last several years for a variety of reasons. In particular, these methods reduce the storage and CPU requirements, can result in sparse linear systems, are easy to parallelize, and, when used in conjunction with a dual reciprocity method, can significantly improve the conditioning of the associated linear system. Nevertheless, for complex geometries, determining an appropriate decomposition of the domain can be extremely difficult. A domain decomposition tool based on a graph partitioning algorithm is presented to automate the process and provide quality decompositions.     

Phosphorescent cyclometalated complexes for efficient blue organic light-emitting diodes

Phosphorescent emitters are extremely important for efficient organic light-emitting diodes (OLEDs), which attract significant attention. Phosphorescent emitters, which have a high phosphorescence quantum yield at room temperature, typically contain a heavy metal such as iridium and have been reported to emit blue, green and red light. In particular, the blue cyclometalated complexes with high efficiency and high stability are being developed. In this review, we focus on blue cyclometalated complexes. Recent progress of computational analysis necessary to design a cyclometalated complex is introduced. The prediction of the radiative transition is indispensable to get an emissive cyclometalated complex. We summarize four methods to control phosphorescence peak of the cyclometalated complex: (i) substituent effect on ligands, (ii) effects of ancillary ligands on heteroleptic complexes, (iii) design of the ligand skeleton, and (iv) selection of the central metal. It is considered that novel ligand skeletons would be important to achieve both a high efficiency and long lifetime in the blue OLEDs. Moreover, the combination of an emitter and a host is important as well as the emitter itself. According to the dependences on the combination of an emitter and a host, the control of exciton density of the triplet is necessary to achieve both a high efficiency and a long lifetime, because the annihilations of the triplet state cause exciton quenching and material deterioration.     

基于认知任务分析的智能系统交互设计路径研究

目的 在信息技术与人类社会深度融合,以及以人工智能为代表的新兴技术推动机器更为智能的时代,操作人员面临着日益复杂的认知需求。在此背景下,从认知任务分析的视角研究适合智能系统交互设计的路径。方法 通过文献分析、实地观察和访谈,分析并总结认知任务分析的理论和工具,提出适合高速列车菜单引导制动试验系统交互界面设计的认知任务分析方法,以及以此为基础的交互设计路径。结论 从历史角度,认知任务分析的诞生和发展与机器智能程度的不断提升密不可分。认知任务分析在复杂智能系统的设计中历史悠久,应用广泛。基于认知任务分析的交互设计路径是高速列车菜单引导制动试验界面设计的一种合适方法,也可以用于类似的智能系统交互设计场景,路径的关键是根据目标研究领域的实际限制选取认知任务分析方法。     

An efficient time‐domain perfectly matched layers formulation for elastodynamics on spherical domains

Many practical applications require the analysis of elastic wave propagation in a homogeneous isotropic media in an unbounded domain. One widely used approach for truncating the infinite domain is the so‐called method of perfectly matched layers (PMLs). Most existing PML formulations are developed for finite difference methods based on the first‐order velocity‐stress form of the elasticity equations, and they are not straight‐forward to implement using standard finite element methods (FEMs) on unstructured meshes. Some of the problems with these formulations include the application of boundary conditions in half‐space problems and in the treatment of edges and/or corners for time‐domain problems. Several PML formulations, which do work with FEMs have been proposed, although most of them still have some of these problems and/or they require a large number of auxiliary nodal history/memory variables. In this work, we develop a new PML formulation for time‐domain elastodynamics on a spherical domain, which reduces to a two‐dimensional formulation under the assumption of axisymmetry. Our formulation is well‐suited for implementation using FEMs, where it requires lower memory than existing formulations, and it allows for natural application of boundary conditions. We solve example problems on two‐dimensional and three‐dimensional domains using a high‐order discontinuous Galerkin (DG) discretization on unstructured meshes and explicit time‐stepping. We also study an approach for stabilization of the discrete equations, and we show several practical applications for quality factor predictions of micromechanical resonators along with verifying the accuracy and versatility of our formulation. Copyright © 2014 John Wiley & Sons, Ltd.     

Information mapping across injection moulding design and manufacture domains

The process of developing new products is complex, partly due to the wide areas of expertise that need to work together to achieve the best results. Whilst a broad range of software tools is now available to support specific areas of product development, and Product Lifecycle Management systems are starting to support information sharing, the provision of software environments that enable the sharing of information and knowledge across multiple domains of expertise is still a major issue. This paper utilises a set of engineering domain ontologies and investigates the development of mapping methods between them. The work focuses on the development of plastic injection moulded products and has used the particular domains of mouldability, mould cavity design and mould cavity manufacturing to explore the mapping methods across domains. It identifies the critical requirement for mapping methods as understanding the pre-conditional knowledge that constrains the domain boundaries. Experimental mapping methods based on these requirements have been constructed and are discussed in the context of case studies in information sharing for injection moulded product development.     

Surrogate representation of a task as a method for data reduction in calculating cumulative spinal loading

The goal of the current investigation was to propose and evaluate a method for estimating cumulative spinal loading based on the hypothesis that cumulative loading for a single task will be linearly proportional to its cycle time. The association between cumulative spinal loading and low-back pain has driven ergonomists and researchers to develop new methods for estimating cumulative workplace exposure. Despite new advances that reduce the amount of data for analysis, methods are still quite labour intensive and prohibitive for widespread industrial usage. In order to assess the proposed method, 15 workers performing six tasks from four different job cells were analysed by video analysis. Two equations to predict cumulative loading of a task based on the known cumulative loading of a similar task were developed. An ‘interpolation’ equation used a task with a longer cycle time to predict cumulative spinal loading for a similar task with a shorter cycle time. An ‘extrapolation’ equation allowed for the opposite prediction to occur. These estimates were compared to a criterion measure produced from the video analysis. There were no significant differences between the criterion measure and the estimated output from the proposed prediction method for four of the five cumulative loading variables. Cumulative compression was the most accurately predicted variable (3.9%). A large range of relative per cent errors (23–202.4%) were found for cumulative shear and extension moment. The proposed method produced promising results for estimating cumulative loading in tasks that differ in length but have similar musculoskeletal demands, especially when combined with other methods of data reduction and has the potential to be used to proactively estimate cumulative loading and quickly screen for tasks that are in need of a full, in depth analysis. Further investigation into defining criteria for ‘similar’ tasks, the influence of task constituent components, and its use in other areas of industry is necessary before the approach should be widely employed.     

General principles for raising the precision of measuring devices

Conclusions The circuit methods for raising the precision of measuring devices are the most promising under existing conditions. It can be considered that structural methods (the use of precise and stable components, stable materials, precision manufacturing technology, etc.) have already been exhausted to a considerable extent. It is doubtful whether it would be possible by their means to raise the precision of existing measuring systems to the level which is now required.The diversity of known circuit methods for raising the MD precision is covered by the suggested classification which separates methods on the basis of their fundamental properties due to the different MD process algorithms.In developing modern measuring systems for which increasinglystringent metrologicaland operating requirements are specified, it is necessary to have a substantiated approach to the selection of rational methods for providing high precision of measuring devices in each specific case. For this purpose it is necessary to know both the general fundamental properties and the particular technical properties of various methods, i.e., it is necessary to have a general theory of circuit methods for providing measuring devices with a high precision and for investigating the technical realization of these methods.This requirement is fully met only by the negative feedback methods. The compound parameter methods have been also developed, although to a smaller extent. The practical application and especially the theory of the very promising important group of error correction methods is in a rudimentary stage. The development of these methods is a very pressing task.Translated from Izmeritel'naya Tekhnika, No. 5, pp. 9–15, May, 1968.     

Consideration of a CVBEM approximation for plane hydrodynamics

The complex variable boundary element method (CVBEM) represents a very useful working tool for applied mathematics in general and for hydrodynamics in particular. The goal of the present work is to give a brief survey on some approximation procedures given the data on the working domain contour in view of getting a rapid convergence of the whole process within a CVBEM. In the first section of this work we will see how some important mixed boundary value problems, for simply connected domains and for the Laplace operator, are transformed into equivalent Dirichlet problems and consequently these Dirichlet problems are the only boundary value problems we will deal with for a CVBEM. In the second section of the present work, some convergent algorithms of a CVBEM, for a Dirichlet boundary problem are built up in view of fluid dynamics (but not only!) applications.     

Fractional factorial analysis to the configuration of simulated annealing applied to the multi-objective optimization of master production scheduling problems

Searching for the global optimal solution in a Master Production Scheduling problem usually demands an effort most industries are not willing to pay. Therefore, the use of meta-heuristics that generates good solutions in reasonable computer time becomes an attractive alternative. However, such strategies are usually complex to implement and configuring their parameters is not a trivial task because of the number of usually conflicting objectives involved. The use of statistical methods that facilitate the set-up of the heuristic's parameters becomes therefore necessary. Knowing which parameters are more important, that is, the ones that really affect the solution quality, and those that are irrelevant, is very important for chosen technique performance. This work presents how fractional factorial analysis can be applied to the configuration of simulated annealing used for optimization of Master Production Scheduling problems. Two scheduling scenarios illustrate the use of the proposed method.     

A spectral finite element for axial-flexural-shear coupled wave propagation analysis in lengthwise graded beam

A new spectral element (SE) is formulated to analyse wave propagation in anisotropic inhomogeneous beam. The inhomogeneity is considered in the longitudinal direction. Due to this particular pattern of inhomogeneity, the governing partial differential equations (PDEs) have variable coefficients and an exact solution for arbitrary variation of material properties, even in frequency domain, is not possible to obtain. However, it is shown in this work that for exponential variation of material properties, the equations can be solved exactly in frequency domain, when the same parameter governs the variation of elastic moduli and density. The SE is formed using this exact solution as interpolating polynomial. As a result a single element can replace hundreds of finite elements (FEs), which are essential for all wave propagation analysis and also for accurate representation of the inhomogeneity. The developed element is used for eliciting several advantages of the gradation, including mode selection, mode blockage and smoothening of stress waves.     

Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification

In the current era of the internet, people use online media for conversation, discussion, chatting, and other similar purposes. Analysis of such material where more than one person is involved has a spate challenge as compared to other text analysis tasks. There are several approaches to identify users’ emotions from the conversational text for the English language, however regional or low resource languages have been neglected. The Urdu language is one of them and despite being used by millions of users across the globe, with the best of our knowledge there exists no work on dialogue analysis in the Urdu language. Therefore, in this paper, we have proposed a model which utilizes deep learning and machine learning approaches for the classification of users’ emotions from the text. To accomplish this task, we have first created a dataset for the Urdu language with the help of existing English language datasets for dialogue analysis. After that, we have preprocessed the data and selected dialogues with common emotions. Once the dataset is prepared, we have used different deep learning and machine learning techniques for the classification of emotion. We have tuned the algorithms according to the Urdu language datasets. The experimental evaluation has shown encouraging results with 67% accuracy for the Urdu dialogue datasets, more than 10, 000 dialogues are classified into five emotions i.e., joy, fear, anger, sadness, and neutral. We believe that this is the first effort for emotion detection from the conversational text in the Urdu language domain.