The organizational design literature strongly supports the notion of “structure follows strategy”, and suggests that a misfit between the two has a negative effect on performance. Building on this ...line of argument, we examine to what extent the (mis)fit between purchasing strategy and purchasing structure impacts purchasing performance. We focus on cost and innovation purchase category strategies, and examine how the deviation from an ideal purchasing structure defined along three dimensions (centralization, formalization, and cross-functionality) impacts purchasing performance. Analysing data collected from 469 firms in ten countries, we demonstrate that a strategy-structure misfit negatively impacts purchasing performance in both cost and innovation strategies. We also find that purchasing proficiency is a mediator in this relationship between misfit and performance. Our findings aid managerial decision making by empirically validating the necessity of having the right purchasing structure for successfully executing different purchasing strategies.
•Purchasing strategy and purchasing structure vary across purchase categories.•Purchasing strategy-structure misfit is negatively related to purchasing performance.•Purchasing proficiency is a mediator between misfit and purchasing performance.
Accurate solar power forecasting plays a critical role in ensuring the reliable and economic operation of power grids. Most of existing literature directly uses available weather conditions as input ...features, which might ignore some key weather factors and the coupling among weather conditions. Therefore, a novel solar power forecasting approach is proposed in this paper by exploring key weather factors from photovoltaic (PV) analytical modeling. The proposed approach is composed of three engines: (1) analytical modeling of PV systems; (2) machine learning methods for mapping weather features with solar power; and (3) a deviation analysis for solar power forecast adjustment. In contrast to the existing research that directly uses available weather conditions, this paper explores the physical knowledge from PV models. Different irradiance components and PV cell temperatures are derived from PV analytical modeling. These weather features are used to reformulate the input of machine learning methods, which helps achieve a better forecasting performance. Moreover, based on the historical forecasting deviations, a compensation term is presented to adjust the solar power forecast. Case studies based on measured datasets from PV systems in Australia demonstrate that the forecasting performance can be highly improved by taking advantage of the key weather features derived from PV models.
•This study is based on a random survey in Chinese cities.•Factors influencing residents’ urban garbage classification (UGC) are examined.•A deviation exists between the willingness and behavior of ...residents to the UGC.•The deviation depends on contextual factors and public’s attitudes and knowledge.
Increasing municipal garbage poses a great threat to city sustainability especially in developing countries. It has become one of the main sources of environmental pollution in Chinese cities. Accordingly, Urban Garbage Classification is of great significance to city sustainability. Essentially, it’s a social behavior and entails public participation. Based on a random survey conducted in Chinese major cities, this paper investigates public participation in Urban Garbage Classification. Our findings show that (1) more willingness to garbage classifications do not mean a higher chance of behavior of garbage classification, which indicates a deviation exists between public’s willingness to garbage classification and the behavior of garbage classification. (2) Such a deviation depends mainly on contextual factors and the public’s attitudes and knowledge about urban garbage classification. (3) Those who pay more attention to urban environmental pollution, who know more about urban garbage classification, and who live in a community with more supporting facilities are more likely to participate in garbage classification. Our study provides a new perspective for understanding the importance of public participation in city sustainability. It can provide useful references for the government to reduce urban waste and the sustainable development of cities.
The primary objective of conducting deviation analysis in the context of assembly process is to ascertain and guarantee the quality and precision of the final product. The deviation analysis is ...important for components that are prone to deformation. The conventional analysis approach primarily relies on the identification of local feature points on individual components to establish relationship between deviations before and after assembly. However, the method does not sufficiently represent the spatial distribution of deviations across the parts. The conventional approach also fails to account for shape inaccuracies and the influence of multiple sources of deviation coupling to certain degree. Therefore, this paper proposes a novel deviation framework for analyzing the sheet metal assembly process based on the skin model shapes and a conditional Generative Adversarial Network (cGAN). The cross-scale shape errors of the critical feature surfaces are modeled by taking the statistical parameters into account. Additionally, the contour maps of the established surface models and the multiple-source deviations are combined using images in order to construct the data for the flexible deviation network models. Then, the finite element method is used to simulate the assembly process, yielding the final component deviations. The contour maps of the assembly deviations and the images of the part deviations are utilized as the input conditions and ground truth for the dataset. The simulations and experiments conducted in this study provide evidence to support the effectiveness of the proposed method in predicting field-to-field deviation deformation. The results indicate that the proposed method outperforms traditional approaches in terms of accuracy. Furthermore, this approach enables end-to-end deviation prediction. The well-trained model is capable of directly outputting the corresponding predicted deviations given input of deviation factors. By employing such a deviation analysis framework, it enables achieve an accurate and high efficiency analysis in the assembly process.
We demonstrate a fork-shape edge coupler consisting of a two-tip taper and subwavelength gratings for optical interconnects in optical communication scenarios. The proposed fiber-to-chip edge coupler ...can achieve a low coupling loss of around 1.0 dB at 1550 nm wavelength for TE mode. The edge coupler also presents a stable performance over a 100-nm wavelength range, owing to the high degree of freedom of subwavelength gratings. The effects of fabrication deviations and fiber misalignments on the coupler are investigated and analyzed in detail. Three types of potential deviations during the fabrication process are taken into consideration, including the distance deviation between coupler facet and the chip facet, lithography deviations, and surface roughness of the chip facet. As for the discussions about the effects of fiber misalignments, both the spatial displacement and the angular misalignment of the optical fiber are included. Simulation results indicate that the fabrication deviations can have certain impacts on the coupling performances and the edge coupler is tolerant to the fiber misalignments. Our numerical simulations and theoretical analysis can provide useful guidance for the fabrication processes and experimental measurements of the proposed edge coupler.
•High-performance silicon photonic fiber-to-chip edge coupler based on subwavelength gratings and a double-tip taper.•Discussions about the effects of fabrication deviations on edge coupler performance, including lithography deviations and surface roughness.•Analysis of edge coupler performance variation caused by spatial displacements and angular tilts of the optical fiber.•Theoretical instructions for practical fabrication processes and experimental measurements given by numerical simulations.
•Reevaluating pressure sensitive paint method assumptions for film cooling.•Universal film cooling effectiveness deviation under multiple conditions.•Identifying positive–negative-positive deviation ...regions along the flow direction.•Effective correction method with oxygen mixtures in Test3.
The application of pressure-sensitive paint (PSP) has been extensively utilized to measure the effectiveness of film cooling. During the experiment, the pressure fields for the air-jet case and the foreign-gas-jet case are usually assumed to be identical. However, when there is a disparity in density between the foreign gas and the air, the difference in pressure distributions cannot be disregarded in high-speed or complex flow conditions. The film cooling effectiveness deviation caused by pressure variation was analyzed by formula derivation. The deviation distribution was obtained through the numerical simulation of the experimental process. The results indicated that the deviation is universal under various conditions. For the film cooling on a flat plate, there is a butterfly-shaped negative deviation region and a narrow symmetrical positive deviation zone. The presence of the compound angle significantly increases the deviation and results in a positive deviation region upstream of the hole. The measurement deviation is widely distributed and exhibits significant magnitudes on the blade tip. The deviation range on the suction side is primarily concentrated near the hole. Specifically, the deviation on the pressure side can be almost neglected. A correction method is proposed, involving the use of an oxygen mixture with the same density as the foreign gas and the same oxygen mole fraction as air. This method proves effective in significantly reducing the deviation in all cases.
•Interdisciplinary approach between architectural and structural surveying.•3D modelling issue as an important intersection between two complementary disciplines.•Filling the gap between FE ...structural analysis and TLS technology.
This paper presents a multi-disciplinary approach for identification of historic buildings structural health with combination of Terrestrial Laser Scanning (TLS) survey, Deviation Analysis (DA) and Finite Element (FE) numerical modelling. The proposed methodology was discussed through the application to an illustrative case study: an early medieval period brick minaret (Eğri Minaret) located in Aksaray (central Turkey). After standing upright for several centuries, the minaret has developed tilt, and today the structure is supported with steel cables. Precise direction of inclination, leaning angle, local deviations from circular building shape, deflections from vertical planes, local curvatures and related maps were obtained with high accuracy by DA, based on detailed point cloud 3D mesh model. Differently from traditional approaches in FE analysis, the paper discusses a method for direct transfer of high accuracy TLS based 3D model to FE structural analysis software, subsequently employed to interpret and verify structural health of the historic building. Through the discussion of the results, it can be considered that the integration of these different techniques (being the whole process non-destructive, effective and expeditious for surface analysis) is a promising methodology for health assessment and analysis of historic constructions.
Objectives
This study aimed to investigate the symmetry of the Chinese pelvis.
Methods
Computed tomography scan images of each of 50 Chinese pelvises were converted to 3D models and the left sides of ...the pelvises were reflected on Mimics software. Then, the reflected left side model was aligned with the right side using the closest point algorithm function of Geomagic software to perform symmetry analysis. The volume and surface area of either side of the pelvises were also calculated. The mean standard deviation (SD), the mean percentage of permissible deviations within the ±2 mm range, the percentage differences in volume and surface area were measured to compare pelvic symmetry. In addition, the distribution of pelvic bilateral symmetry associated with both age and sex were compared.
Results
The mean SD was 1.15 ± 0.16 mm and the mean percentage of permissible deviations was 90.82% ± 4.67%. The deviation color maps showed that the specific areas of asymmetry were primarily localized to major muscle or ligament attachment sites and the sacroiliac joint surfaces. There was no significant difference between the bilateral sides of the pelvis in either volume or surface area. Additionally, no difference in any indexes was exhibited in relation to sex and age distribution.
Conclusion
Our results demonstrated that the pelvis has high bilateral symmetry, which confirmed the potential of using contralateral pelvic models to create fully patient‐specific and custom‐made pelvic implants applicable for the treatment of fracture and bony destruction.
This investigation using computer aided design software avoided some limitations of previous studies and filled an important research gap in the literature of pelvic symmetry. The bilateral hemi‐pelvises showed a high degree of symmetry. It would be feasible and effective to apply the concept of pelvic symmetry to create fully patient‐specific and custom‐made pelvic implants by using contralateral pelvic models for the treatment of fracture and bony destruction.
This paper proposes a stability-guaranteed bias-compensated normalized least-mean-square (BC-NLMS) algorithm for noisy inputs. The bias-compensated algorithms require the estimated input noise ...variance in the elimination process of the bias caused by noisy inputs. However, the conventional methods of estimating the input noise variance in those algorithms might cause the instability for a specific situation. This paper first analyzes the stability of the BC-NLMS algorithm by investigating the dynamics of both the mean deviation and the mean-square deviation in the BC-NLMS algorithm. Based on the analysis, the estimation of the input noise variance and the adjustment of the step size are carried out to perform a stabilization as well as a performance enhancement in terms of a steady-state error and a convergence rate. Simulations in system identification and acoustic echo cancellation scenarios with noisy inputs show that the proposed algorithm outperforms the existing bias-compensated algorithms in the aspect of the stability, the steady-state error, and the convergence rate.
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