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1 – 10 of 11The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some…
Abstract
Purpose
The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.
Design/methodology/approach
The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.
Findings
The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.
Originality/value
In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.
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En-Ze Rui, Guang-Zhi Zeng, Yi-Qing Ni, Zheng-Wei Chen and Shuo Hao
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural…
Abstract
Purpose
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.
Design/methodology/approach
A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.
Findings
Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.
Originality/value
In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.
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Lucas Silva and Alfredo Gay Neto
When establishing a mathematical model to simulate solid mechanics, considering realistic geometries, special tools are needed to translate measured data, possibly with noise…
Abstract
Purpose
When establishing a mathematical model to simulate solid mechanics, considering realistic geometries, special tools are needed to translate measured data, possibly with noise, into idealized geometrical entities. As an engineering application, wheel-rail contact interactions are fundamental in the dynamic modeling of railway vehicles. Many approaches used to solve the contact problem require a continuous parametric description of the geometries involved. However, measured wheel and rail profiles are often available as sets of discrete points. A reconstruction method is needed to transform discrete data into a continuous geometry.
Design/methodology/approach
The authors present an approximation method based on optimization to solve the problem of fitting a set of points with an arc spline. It consists of an initial guess based on a curvature function estimated from the data, followed by a least-squares optimization to improve the approximation. The authors also present a segmentation scheme that allows the method to increment the number of segments of the spline, trying to keep it at a minimal value, to satisfy a given error tolerance.
Findings
The paper provides a better understanding of arc splines and how they can be deformed. Examples with parametric curves and slightly noisy data from realistic wheel and rail profiles show that the approach is successful.
Originality/value
The developed methods have theoretical value. Furthermore, they have practical value since the approximation approach is better suited to deal with the reconstruction of wheel/rail profiles than interpolation, which most methods use to some degree.
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The general attitude of the ancient theatre conservation strategies and policies is still concerned primarily with their architectural physical appearance without considering…
Abstract
Purpose
The general attitude of the ancient theatre conservation strategies and policies is still concerned primarily with their architectural physical appearance without considering their authentic scientific acoustical qualities. The paper attempts to illustrate and discuss how to enhance their acoustic heritage to arouse the audience's interest and needs. Thus, supporting their reconstruction based on recent acoustical research and community needs-related concerns and opportunities for ancient theatre's modern use.
Design/methodology/approach
It is based on reviewing the main issues related to reconstruction in the international charters and conventions and how to infuse ancient theatres with their full role. It discusses the dilemma and debates regarding the theatre stage wall, colonnade (portico) restoration and anastylosis. Is it sufficient enough to recover the theatre sound volume? Or to rethink for full physical reconstructions of these missing related acoustical theatre architectural elements to their original level and layout as in ancient times in parallel to their virtual reconstruction?
Findings
The cultural significance of the authentic theatre's acoustical qualities needs to reform the conservation strategies and policies for a more flexible and resilient approach. It should be postulated, re-examined and advocated parallel to their 3D virtual reconstruction in the related international charters and conventions.
Practical implications
The paper's implications are not immediate; it is far-reaching. It suggests the importance of acoustics in analysing historic theatre performance venues and reforming conservation strategies and approaches. This issue is especially critical for architects, conservators, the heritage community and the public audience.
Originality/value
Recommendations are made for potential bold reconstruction actions that may be taken to achieve further sustainability, comfort, and permeability in modern theatre-use performances. Their physical reconstruction for improving the performance of contemporary theatre use regarding retaining the acoustic cultural significance should be more flexible and resilient in the charters.
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Hongwei Zhang, Shihao Wang, Hongmin Mi, Shuai Lu, Le Yao and Zhiqiang Ge
The defect detection problem of color-patterned fabric is still a huge challenge due to the lack of manual defect labeling samples. Recently, many fabric defect detection…
Abstract
Purpose
The defect detection problem of color-patterned fabric is still a huge challenge due to the lack of manual defect labeling samples. Recently, many fabric defect detection algorithms based on feature engineering and deep learning have been proposed, but these methods have overdetection or miss-detection problems because they cannot adapt to the complex patterns of color-patterned fabrics. The purpose of this paper is to propose a defect detection framework based on unsupervised adversarial learning for image reconstruction to solve the above problems.
Design/methodology/approach
The proposed framework consists of three parts: a generator, a discriminator and an image postprocessing module. The generator is able to extract the features of the image and then reconstruct the image. The discriminator can supervise the generator to repair defects in the samples to improve the quality of image reconstruction. The multidifference image postprocessing module is used to obtain the final detection results of color-patterned fabric defects.
Findings
The proposed framework is compared with state-of-the-art methods on the public dataset YDFID-1(Yarn-Dyed Fabric Image Dataset-version1). The proposed framework is also validated on several classes in the MvTec AD dataset. The experimental results of various patterns/classes on YDFID-1 and MvTecAD demonstrate the effectiveness and superiority of this method in fabric defect detection.
Originality/value
It provides an automatic defect detection solution that is convenient for engineering applications for the inspection process of the color-patterned fabric manufacturing industry. A public dataset is provided for academia.
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Bingbing Qi, Lijun Xu and Xiaogang Liu
The purpose of this paper is to exploit the multiple-Toeplitz matrices reconstruction method combined with quadratic spatial smoothing processing to improve the…
Abstract
Purpose
The purpose of this paper is to exploit the multiple-Toeplitz matrices reconstruction method combined with quadratic spatial smoothing processing to improve the direction-of-arrival (DOA) estimation performance of coherent signals at low signal-to-noise ratio (SNRs).
Design/methodology/approach
An improved multiple-Toeplitz matrices reconstruction method is proposed via quadratic spatial smoothing processing. Our proposed method takes advantage of the available information contained in the auto-covariance matrices of individual Toeplitz matrices and the cross-covariance matrices of different Toeplitz matrices, which results in a higher noise suppression ability.
Findings
Theoretical analysis and simulation results show that, compared with the existing Toeplitz matrix processing methods, the proposed method improves the DOA estimation performance in cases with a low SNR. Especially for the cases with a low SNR and small snapshot number as well as with closely spaced sources, the proposed method can achieve much better performance on estimation accuracy and resolution probability.
Research limitations/implications
The study investigates the possibility of reusing pre-existing designs for the DOA estimation of the coherent signals. The proposed technique enables achieve good estimation performance at low SNRs.
Practical implications
The paper includes implications for the DOA problem at low SNRs in communication systems.
Originality/value
The proposed method proved to be useful for the DOA estimation at low SNR.
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Kai Wang, Jiaying Liu, Shuai Yang, Jing Guo and Yongzhen Ke
This paper aims to automatically obtain the implant parameter from the CBCT images to improve the outcome of implant planning.
Abstract
Purpose
This paper aims to automatically obtain the implant parameter from the CBCT images to improve the outcome of implant planning.
Design/methodology/approach
This paper proposes automatic simulated dental implant positioning on CBCT images, which can significantly improve the efficiency of implant planning. The authors introduce the fusion point calculation method for the missing tooth's long axis and root axis based on the dental arch line used to obtain the optimal fusion position. In addition, the authors proposed a semi-interactive visualization method of implant parameters that be automatically simulated by the authors' method. If the plan does not meet the doctor's requirements, the final implant plan can be fine-tuned to achieve the optimal effect.
Findings
A series of experimental results show that the method proposed in this paper greatly improves the feasibility and accuracy of the implant planning scheme, and the visualization method of planting parameters improves the planning efficiency and the friendliness of system use.
Originality/value
The proposed method can be applied to dental implant planning software to improve the communication efficiency between doctors, patients and technicians.
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Sally Helen Stone and Laura Sanderson
This paper considers the exhibition: UnDoing. This research-through-curation project examined interactions within existing spaces and situations. This established links between…
Abstract
Purpose
This paper considers the exhibition: UnDoing. This research-through-curation project examined interactions within existing spaces and situations. This established links between the selected exhibits, the gallery, the city and with the continuum of the previous exhibition.
Design/methodology/approach
Carefully selected architects, designers and artists were invited to contribute—those who pursued a contextual approach; whose practice explored the way buildings, places and artefacts are reused, reinterpreted and remembered.
Findings
Through the act of curation, this research uncovered a series of different approaches to constructed sites and existing buildings, from layered juxtaposition, the refusal to undo, to interventions of new elements within architectural works.
Research limitations/implications
Curation offered the opportunity to consider works of architecture and of art through the same lens, for direct comparisons to be made and the influence of one upon the other to be comprehended.
Practical implications
The examination processes the architect employs is similar to that of the artist; the development of an understanding of place, and from this synthesis, creative interpretation. However, despite the similarities in the starting position, the elucidation developed by the artist can be vastly different to that of the architect.
Social implications
The juxtaposition and new classifications created by the exhibition encouraged visitors to look at art, architecture and the city in a different way; to grasp the direct link between the different subjects; and the possibilities created.
Originality/value
The two driving factors for UnDoing were places of previous occupation and the city of Manchester. The qualities of surrounding constructed environment combined were combined with attitudes towards existing structures and places.
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Miaomiao Wang, Xinyu Chen, Yuqing Tan and Xiaoxi Zhu
To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.
Abstract
Purpose
To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.
Design/methodology/approach
Considering the dual roles of the e-commerce platform as a seller and an initiator, a typical game-theoretical method is applied to analyze the behavior of supply chain decision-makers and the impact of key variables on equilibriums.
Findings
When loan interest rates are symmetric, whether blockchain is used or not, the e-commerce platform financing mode will always produce higher wholesale price and unit carbon emission reduction, while the retail price is the opposite. Higher unit additional income brought by the blockchain can bring higher economic and environmental performances, and the e-commerce platform financing mode is superior to bank financing mode. The application of blockchain may cause the manufacturer to change his/her financing choice. For bank financing, with the increase of loan interest rates, the advantages brought by blockchain will gradually disappear, but this situation will not occur under e-commerce platform financing.
Originality/value
Blockchain is known for its information transparency properties and its ability to enhance user trust. However, the impacts of applying blockchain in a low-carbon platform supply chain with different financing options are not clear. The authors examine the manufacturer's strategic choices for platform financing and bank financing, whether to adopt blockchain, and the impact of these decisions on carbon emissions reduction, consumer surplus and social welfare. The research conclusion can provide reference for the operation and financing decisions of platform supply chain under the carbon reduction target in the digital economy era.
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Ryszard Kłeczek and Monika Hajdas
This study aims to investigate how art events can enrich novice visitors by transforming their practices.
Abstract
Purpose
This study aims to investigate how art events can enrich novice visitors by transforming their practices.
Design/methodology/approach
This research uses an interpretive case study of the art exhibition “1/1/1/1/1” in the Oppenheim gallery in Wroclaw. It draws on multiple sources of evidence, namely, novice visitors’ interviews, observation including photo studies and content analysis of art-makers’ mediation sources. This study is an example of contextual theorizing from case studies and participatory action research with researchers as change agents.
Findings
The evidence highlights that aesthetic values and experiences are contextual to practices and are transformable into other values. The findings illustrate the role of practice theory in studying how art-makers inspire the transformation of practices, including values driving the latter.
Research limitations/implications
The findings provide implications for transformations of co-creating contextual values in contemporary visual art consumption and customer experience management.
Practical implications
Practical implications to arts organizations are also provided regarding cultural mediation conducted by art-makers. Exhibition makers should explain the meanings of the particularly visible artefacts to allow visitors to develop a congruent understanding of the meanings. The explanations should not provide ready answers or solutions to the problem art-makers suggest to rethink.
Social implications
The social implication of our findings is that stakeholders in artistic ventures may undertake adequate, qualified and convergent actions to maintain or transform the defined interactive practices between them in co-creating contextual aesthetic values.
Originality/value
The study provides new insights into co-creating values in practices in the domain of contemporary art exhibitions by bringing the practice theory together with an audience enrichment category, thus illustrating how novice visitors get enriched by transforming their practices led by contextual values of “liking” and “understanding”.
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