Iterative Triangulation Research Articles

Iterative particle matching for three-dimensional particle-tracking velocimetry

A new evaluation scheme for double exposure three-dimensional particle-tracking velocimetry is proposed. Its main feature, a robust multi-pass matching algorithm, is presented and validated by investigating its performance when applied to a synthetic data set. To evaluate real measurement data, the approach is supplemented by an iterative triangulation scheme, in which the resulting particle positions are validated through the matching algorithm. The comparison with tomographic particle-image velocimetry data shows good agreement. The proposed algorithm allows this approach to be applied to volumetric measurements with seeding densities exceeding standard particle-tracking applications. Therefore, it can serve as a drop-in replacement for tomographic particle-image velocimetry at significantly reduced computational cost.Graphic abstract

Extraction and monitoring approach of dynamic urban commercial area using check-in data from Weibo

Urban hot spot detection and commercial area analysis for city economic planning and dynamic urban planning is of vital importance. However, it is difficult to obtain a more accurate commercial area boundary in the past. Check-in data obtained by a social networking service (SNS) and/or a location-based service (LBS) is a type of crowd-sourced geographic data that can reveal mass daily life activities, which provides a new big data source for urban hot spot detection and commercial area analysis. In this paper, a dynamic urban commercial area extraction and monitoring approach is proposed using SINA Weibo (a social network) check-in data. First, a check-in data pre-process model is proposed to simplify the amount of check-in data and improve the efficiency of cluster analysis. The spatial autocorrelation validation is implemented to validate the significant patterns of the spatial clustering of check-in data. Then, an exploratory spatial analysis and hot spot clustering method based on check-in data is proposed to detect urban hot spots and extract commercial areas using a geographic distribution metric with urban commercial hot spots. Second, the hot spot cluster analysis results are taken to determine the center of the commercial area and calculate the distribution of an ellipse, which is adopted to obtain the rough boundary of the commercial area. A planar Delaunay iterative triangulation algorithm is presented to determine the exact boundary of the commercial area. Then, the time sequence extraction result of the commercial area is presented to analyze the evolutionary trend in the city business space. Finally, the Weibo check-in data from 2012 to 2014 of Wuhan city are taken as an example dataset for the commercial area extraction and detection with the proposed approach. The results show that the method can accurately determine the boundary of and changes within the commercial area in Wuhan city. This study provides a new method for the monitoring of hot spots and the geographical situations of city commercial areas.

Signaling Principles in Interactive Learning Media through Expert's Walkthrough

This study analyzes the impact of signaling principles upon the effective use of interactive learning media. Normally, designers just design and develop learning media for use in schools without considering the way it eases users’ tasks. Bearing in mind that signaling users while they are learning through interactive learning media is important, this study incorporates signaling principles while designing it. Thus, this paper aims to discuss the appropriate signaling principles for learning media from experts’ perspective. The Iterative Triangulation Methodology was applied to achieve the aim. Altogether, activities were carried out in three phases: requirement analysis, design and development of the prototype, and expert evaluation using a walkthrough. Results revealed that although the prototype was designed by involving users, experts still discovered a number of flaws in the exercises as a result of not properly applying the signaling principles.

A knowledge audit model for requirement elicitation: A case study to assess knowledge in requirement elicitation

This paper aims to develop a knowledge audit (KA) model with the focus on knowledge assessment in the requirements elicitation process (REP) to allay the problems of REP regarding knowledge communication. The principal problems with REP are knowledge conflict and the failure to mention a variety of knowledge and requirements changes. Despite of many existing studies relating to KA, inadequate effort has been directed towards investigating the full part played by the KA process in REP. The purpose of this paper is to bridge this gap using a software prototype that uses the KA model in the REP. This study proposes a KA model using an iterative triangulation method. The proposed model is validated through a case study by using a software prototype developed based on the proposed KA model to see if this KA model is effective for software developers in REP by improving the completeness, correctness, and understandability of the elicited requirements knowledge. Research findings are based on responses of 40 respondents from software development organizations. The results of case study confirmed the effectiveness of KA model for REP with respect to completeness, correctness, and understandability. This research answers the call to assess knowledge in REP by developing a KA model and prototype to fill the existing gap in this area. Overall, a KA model for REP is introduced and validated to identify and assess knowledge that supports knowledge communication in REP.

PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study

IntroductionSurvivors of critical illness experience multidimensional disabilities that reduce quality of life, and 25–30% require unplanned hospital readmission within 3 months following index hospitalisation. We aim to understand factors associated...

Shake-The-Box: Lagrangian particle tracking at high particle image densities

A Lagrangian tracking method is introduced, which uses a prediction of the particle distribution for the subsequent time-step as a mean to seize the temporal domain. Errors introduced by the prediction process are corrected by an image matching technique (‘shaking’ the particle in space), followed by an iterative triangulation of particles newly entering the measurement domain. The scheme was termed ‘Shake-The-Box’ and previously characterized as ‘4D-PTV’ due to the strong interaction with the temporal dimension. Trajectories of tracer particles are identified at high spatial accuracy due to a nearly complete suppression of ghost particles; a temporal filtering scheme further improves on accuracy and allows for the extraction of local velocity and acceleration as derivatives of a continuous function. Exploiting the temporal information enables the processing of densely seeded flows (beyond 0.1 particles per pixel, ppp), which were previously reserved for tomographic PIV evaluations. While TOMO-PIV uses statistical means to evaluate the flow (building an ‘anonymous’ voxel space with subsequent spatial averaging of the velocity information using correlation), the Shake-The-Box approach is able to identify and track individual particles at numbers of tens or even hundreds of thousands per time-step. The method is outlined in detail, followed by descriptions of applications to synthetic and experimental data. The synthetic data evaluation reveals that STB is able to capture virtually all true particles, while effectively suppressing the formation of ghost particles. For the examined four-camera set-up particle image densities N I up to 0.125 ppp could be processed. For noise-free images, the attained accuracy is very high. The addition of synthetic noise reduces usable particle image density (N I ≤ 0.075 ppp for highly noisy images) and accuracy (still being significantly higher compared to tomographic reconstruction). The solutions remain virtually free of ghost particles. Processing an experimental data set on a transitional jet in water demonstrates the benefits of advanced Lagrangian evaluation in describing flow details—both on small scales (by the individual tracks) and on larger structures (using an interpolation onto an Eulerian grid). Comparisons to standard TOMO-PIV processing for synthetic and experimental evaluations show distinct benefits in local accuracy, completeness of the solution, ghost particle occurrence, spatial resolution, temporal coherence and computational effort.

Perspectives and reflections on the practice of behaviour change communication for infant and young child feeding.

Behaviour change communication (BCC) is a critical component of infant and young child feeding (IYCF) interventions. In this study we asked BCC practitioners working in low- and middle-income countries to participate in an examination of BCC practice. We focus here on results of their personal reflections related to larger issues of practice. We used a combination of iterative triangulation and snowball sampling procedures to obtain a sample of 29 BCC professionals. Major themes include (1) participants using tools and guidelines to structure their work, and many consider their organisation's tools to be their most important contribution to the field; (2) they value research to facilitate programme design and implementation; (3) half felt research needed to increase; (4) they have a strong commitment to respecting cultural beliefs and culturally appropriate programming; (5) they are concerned about lack of a strong theoretical foundation for their work. Based on participants' perspectives and the authors' reflections, we identified the following needs: (1) conducting a systematic examination of the alternative theoretical structures that are available for nutrition BCC, followed by a review of the evidence base and suggestions for future programmatic research to fill the gaps in knowledge; (2) developing a checklist of common patterns to facilitate efficiency in formative research; (3) developing an analytic compendium of current IYCF BCC guidelines and tools; (4) developing tools and guidelines that cover the full programme process, including use of innovative channels to support 'scaling up nutrition'; and (5) continued support for programmes of proven effectiveness.

Experimental study on subaperture testing with iterative triangulation algorithm

Applying the iterative triangulation stitching algorithm, we provide an experimental demonstration by testing a Φ120 mm flat mirror, a Φ1450 mm off-axis parabolic mirror and a convex hyperboloid mirror. By comparing the stitching results with the self-examine subaperture, it shows that the reconstruction results are in consistent with that of the subaperture testing. As all the experiments are conducted with a 5-dof adjustment platform with big adjustment errors, it proves that using the above mentioned algorithm, the subaperture stitching can be easily performed without a precise positioning system. In addition, with the algorithm, we accomplish the coordinate unification between the testing and processing that makes it possible to guide the processing by the stitching result.

The Development of a Strategic CRM-i Framework: Case Study in Public Institutions of Higher Learning

The mission of Strategic Plan for National Higher Education in Research and Development is the development of human capital to achieve quality research culture and international recognition. The present educational institutions which in the beginning focused on improvement of internal operations began to shift their attention to the human aspect placing importance on customer management. Thus, the Customer Relationship Management (CRM) is seen as a new approach to help educational institutions maximize centralization of customer resources. Research has shown that there is no specific framework available in application of human based approach utilizing CRM in Public Institutions of Higher Learning (IPTA) in Malaysia. The objective of this research is to develop a strategic framework for customer relationship management. The scope of the research is the Centre for Research and Development, IPTA. The methodology of the research is qualitative, using the iterative triangulation method. The framework is named CRM-i and combines three different approaches; CRM, Strategic Information System Planning and Humanity Management. Additionally, this research introduces a new dimension in CRM approach, i.e the Human dimension. This article shall discuss the development of components and phases for the framework. The CRM-i framework has been acknowledged as a suitable customer management framework.

Study on Modeling Technology Based on Polygon Transform

As one of the 3D modeling key technology, polygon transform have some operation and manipulation methods which can be applied neatly and confirmed by the characteristic of practical model. Polygon transform methods such as inserting vertex, inserting polygon, extrusion, transition join, triangulation and iterative triangulation algorithm and so on are discussed by using practical examples of reverse modeling in this paper. The experiment results show that using these methods synthetically have an effect on constructing and transforming complicated 3D model. We can thin polygons, redefine new local models, extrude polygon outwards or inwards and largen or reduce selective polygon borderline, form a new rolling polygon which joins on the original model, and subsection polygon into triangles by defining new borders inside the polygon.

Blind extraction and localization of sound sources using point sources based approaches

This paper presents theoretical models for blind sound source localization and separation of the signals emitted by arbitrary point sources in free space. Source localizations are achieved by a model based approach that accounts for the spherical spreading of an acoustic wave and utilizes an iterative triangulation, based on the signals measured by a three-dimensional microphone array. Once source locations are determined, the source signals are separated by using the point source separation (PSS) method, which is valid for all types of signals, including harmonic, continuous, transient, random, narrowband and broadband. General solutions for signals separation are presented. Theoretically, PSS can reconstruct the individual source signals exactly. This is because it employs the free-space Green's function, which defines the exact correlation among individual sources and measurement microphones. To validate PSS, numerical simulations are carried out and results are compared with those obtained by FastICA (Independent Component Analysis) code. The impacts of various parameters such as the microphone configuration, type of source signals, signal to noise ratio, number of microphones and source localization errors on the quality of signals separation by using PSS and FastICA are examined. The advantages and disadvantages of PSS and FastICA are compared and discussed.

On Disaster Response and Emergent Systems: A New Taxonomy for Operations Management

Disaster response is not readily categorized by the influential taxonomies of operations management (OM). Through the inductive research process of iterative triangulation, we identify patterns of evidence in case studies and other literature to develop a new taxonomy for OM, one which explicitly positions disaster-related operations relative to other industries. This new taxonomy divides the OM domain into the four categories of prescriptive, compliant, swarm and emergent systems. Closer examination of those systems grouped into the emergent sector reveals intriguing similarities between operations such as disaster response and endeavors such as rapid software development and artistic ensembles. These similarities include the simultaneous use of hierarchical and collaborative organizational structures, dual reliance on well-developed rules and provisions to break them, the concept of trajectory as a performance metric, the use of short, iterative planning cycles and a reliance on unstructured communication through some open forum. Each of these patterns suggests research opportunities to further OM’s understanding of how best to operate in a highly uncertain environment, findings of potential value to both disaster response and any ‘normal’ business that might suffer disruption.

Enterprise Resource Planning (ERP) Implementation Process: Project Management Perspective

Enterprise Resource Planning (ERP) system is an advanced manufacturing system that enables the integration of transactions-oriented data and business functions throughout an enterprise. ERP system holds the potential of greatly enhancing organizational performance and establishing competitive advantage. ERP project team can reduce their implementation costs by having a well thought out ERP implementation process. This research examines the ERP implementation process from the project management based perspective. The theoretical framework is developed to specify the ERP implementation process, which is categorized into five phases in project life cycle: initiating, planning, executing, controlling and closing. The research adopts the iterative triangulation as a methodology to establish this study, and one large company in Iran has been chosen by researchers to examine the proposed framework.

Assistive Courseware for Hearing Impaired Learners in Malaysia

This paper reports a research on Hearing Impaired (HI) learners in Malaysia which focuses on beginner level. This research has been carried out with intention to solve problem faced by parents of HI children in teaching their children to know the six basic sounds which is known as Ling-6 Sound. The HI learners were assisted by speciallydeveloped electronic-learning application or known as Assistive Courseware (AC) in their teaching and learning process. The AC utilizes their mother tongue language. The objectives of the study include 1) To identify the characteristic of AC for HI learners, 2) To design the storyboard of AC for HI learners, and 3) To design the interface of AC for HI learners. This study adapts the Iterative Triangulation Methodology, and is integrated with the IntView Methodology. The storyboard of the prototype is outlined next. The findings of this paper highlight the prototype of the AC labelled with certain characteristics that has been identified and the result is based on interview with parents. The final part concludes this paper.

Supply chain best practices – identification and categorisation of measures and benefits

PurposeThis research aims to identify, categorise and compare supply chain measures and benefits listed in literature‐based case studies that were named as “best practices”.Design/methodology/approachThe research applies iterative triangulation which is a method used to build theories from existing case studies. Selected case studies collected by project partners are used as a source of secondary data. The paper applies various approaches to classifying supply chains as well as identifying the difference between measures proposed in the literature and those used by case companies.FindingsThe analysis of the selected sample of cases indicated that the most common measures were related to economic aspects and to operational level activities. There is a lack of shared supply chain measures at the inter‐organizational level, while social and environmental aspects are largely ignored.Originality/valueThe majority of the measures identified in the collected cases were economic (relating to cost, time, quality and customer). Metrics at an operational level dominate, while supply chain metrics are hardly used. Findings indicate that current performance measurement approaches do not generally include social and environmental issues, which are becoming increasingly important in business.

A Comment on Boeri's Iterative Triangulation

We certainly appreciate this opportunity to return to the important ideas surrounding the place of tri angulation in social science methods, and are especially pleased that the author of Iterative Triangulation found our presentation useful in framing her own fine extension of the arguments. There are at least three clear strengths to Miriam Boeri's paper. It succinctly draws out the main themes of our own recent work, it makes a prima facie case for extension, and the extension and surrounding discussion are particularly, though not exclusively, relevant for applied sociology. We should begin by pointing out that our intent was not to exhaust the types of triangulation. Therefore, Boeri's addition is most welcome indeed. Recall our discussion of Denzin's early pres entation of methodological triangulation. Three other types of triangulation were elaborated which we subsequently ignored in stressing the issues of methods and measurement. Boeri does take up our argument in terms of measurement, and addresses our central point—that explicit attention to the synthesis of multiple measures is required. Commensurability is a fairly strong version of this, and most applicable to the bias reduction objective of triangulation. However, even what we called aggregation requires explicit synthesis, and it is clear that we did not sufficiently make this point. Recall that in contrast to syntheses that correct one measure by employing another method (validation and bias reduction), we wrote of syntheses that take individual measures as given but incomplete and seek to extend our understanding by including additional measures (aggregation or extension). Boeri writes:

Three-dimensional shape reconstruction from images by shape-from-silhouette technique and iterative triangulation

We propose an image-based three-dimensional shape determination system. The shape, and thus the three-dimensional coordinate information of the 3-D object, is determined solely from captured images of the 3-D object from a prescribed set of viewpoints. The approach is based on the shape-from-silhouette (SFS) technique, and the efficacy of the SFS method is tested using a sample data set. The extracted three-dimensional shape is modeled with polygons generated by a new iterative triangulation algorithm, and the polygon model can be exported to commercial software. The proposed system may be used to visualize the 3-D object efficiently, or to quickly generate initial CAD data for reverse engineering purposes, including three dimensional design applications such as 3-D animation and 3-D games.

One-dimensional dense disparity estimation for three-dimensional reconstruction

We present a method for fully automatic three-dimensional (3D) reconstruction from a pair of weakly calibrated images in order to deal with the modeling of complex rigid scenes. A two-dimensional (2D) triangular mesh model of the scene is calculated using a two-step algorithm mixing sparse matching and dense motion estimation approaches. The 2D mesh is iteratively refined to fit any arbitrary 3D surface. At convergence, each triangular patch corresponds to the projection of a 3D plane. The proposed algorithm relies first on a dense disparity field. The dense field estimation modelized within a robust framework is constrained by the epipolar geometry. The resulting field is then segmented according to homographic models using iterative Delaunay triangulation. In association with a weak calibration and camera motion estimation algorithm, this 2D planar model is used to obtain a VRML-compatible 3D model of the scene.

Iterative triangulation: a theory development process using existing case studies

AbstractTo cope with the growing frequency and magnitude of changes in technology and managerial methods, Operations Management (OM) researchers have been calling for greater employment of field‐based research methods. A notable example is grounded theory development using original case studies. Based on in‐depth examinations of ‘real‐world’ operations conditions, case studies potentially improve the relevance and workability of resulting OM theory. However, developing original case studies requires considerable time and expense, straining research resources and often limiting the number of operations settings that can be studied and compared during induction. Existing case studies offer a potentially effective and efficient means for comparing complex and disparate operations settings. This paper proposes a novel theory development process, termediterative triangulation, for tapping this potential. Iterative triangulation employs systematic iterations between literature review, case evidence, and intuition. The process enhances theory creativity, utility, and validity by deliberately increasing the diversity and quantity of literature reviewed, of cases found, of conjectures examined, and of conjecture selection criteria. Comparing and contrasting emerging constructs and theory across case settings refines conceptual definitions and strengthens internal validity, enhancing testability of resulting theory. A study of advanced manufacturing technology design illustrates the method.

A Surface of Minimum Area Metric for the Structural Comparison of Proteins

A new method for comparing protein structures, based on a minimal surface metric, is developed. A virtual polypeptide backbone is created by joining consecutive C αatoms in a protein structure. The minimal surface between the virtual backbones of two proteins (the Area Functional) is determined numerically using an iterative triangulation strategy. The first protein is then rotated and translated in space until the smallest minimal surface is obtained. Such a technique yields the optimal structural superposition between two protein segments. It requires no initial sequence alignment, is relatively insensitive to insertions and deletions, and obviates the need to select a gap penalty. The optimal minimal area can then be converted to the Area-C αdistance, measured in angstroms, to determine the structural similarity. This technique has been applied to a large class of proteins and is able to detect not only small-scale differences between closely related proteins but also large-scale topological similarities between evolutionary unrelated proteins that lack any obvious sequence homology. To measure the similarity between structurally dissimilar proteins, an additional measure (the Fit Comparison) is developed. This is a scale-invariant measure of a structural similarity that is useful for determining topological similarities between dissimilar proteins with unrelated sequences.