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1 – 10 of over 8000Tingwei Gu, Shengjun Yuan, Lin Gu, Xiaodong Sun, Yanping Zeng and Lu Wang
This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic…
Abstract
Purpose
This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.
Design/methodology/approach
The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.
Findings
The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.
Originality/value
An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.
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Hong-Sen Yan, Zhong-Tian Bi, Bo Zhou, Xiao-Qin Wan, Jiao-Jun Zhang and Guo-Biao Wang
The present study is intended to develop an effective approach to the real-time modeling of general dynamic nonlinear systems based on the multidimensional Taylor network (MTN).
Abstract
Purpose
The present study is intended to develop an effective approach to the real-time modeling of general dynamic nonlinear systems based on the multidimensional Taylor network (MTN).
Design/methodology/approach
The authors present a detailed explanation for modeling the general discrete nonlinear dynamic system by the MTN. The weight coefficients of the network can be obtained by sampling data learning. Specifically, the least square (LS) method is adopted herein due to its desirable real-time performance and robustness.
Findings
Compared with the existing mainstream nonlinear time series analysis methods, the least square method-based multidimensional Taylor network (LSMTN) features its more desirable prediction accuracy and real-time performance. Model metric results confirm the satisfaction of modeling and identification for the generalized nonlinear system. In addition, the MTN is of simpler structure and lower computational complexity than neural networks.
Research limitations/implications
Once models of general nonlinear dynamical systems are formulated based on MTNs and their weight coefficients are identified using the data from the systems of ecosystems, society, organizations, businesses or human behavior, the forecasting, optimizing and controlling of the systems can be further studied by means of the MTN analytical models.
Practical implications
MTNs can be used as controllers, identifiers, filters, predictors, compensators and equation solvers (solving nonlinear differential equations or approximating nonlinear functions) of the systems of ecosystems, society, organizations, businesses or human behavior.
Social implications
The operating efficiency and benefits of social systems can be prominently enhanced, and their operating costs can be significantly reduced.
Originality/value
Nonlinear systems are typically impacted by a variety of factors, which makes it a challenge to build correct mathematical models for various tasks. As a result, existing modeling approaches necessitate a large number of limitations as preconditions, severely limiting their applicability. The proposed MTN methodology is believed to contribute much to the data-based modeling and identification of the general nonlinear dynamical system with no need for its prior knowledge.
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Jun Liu, Junyuan Dong, Mingming Hu and Xu Lu
Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic…
Abstract
Purpose
Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.
Design/methodology/approach
In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.
Findings
Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.
Originality/value
In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.
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The purpose of this paper is to build a System Dynamics model to reveal the structure and dynamics of knowledge coupling affecting firms' innovation results in the digital context.
Abstract
Purpose
The purpose of this paper is to build a System Dynamics model to reveal the structure and dynamics of knowledge coupling affecting firms' innovation results in the digital context.
Design/methodology/approach
Drawing on the recombined view of innovation, this paper divides knowledge coupling into two dimensions: component knowledge coupling and architectural knowledge coupling. Then, the authors build a system dynamics model to identify the interaction of knowledge coupling factors and use the professional Vensim PLE to conduct simulation analysis to capture the dynamic interaction of motivation factors in knowledge coupling system.
Findings
The results show that both technology resources and digital dynamic capability play positive effects in the mechanism of knowledge coupling influencing firms' innovation results, while organizational inertia negatively affects the process of knowledge coupling to achieve innovation outcomes.
Originality/value
This study develops a holistic system dynamics model to reveal and elaborate on the complex dynamic mechanism of knowledge coupling impacting firms' innovation results in the context of digitization and provides a theoretical reference for companies to effectively adopt digital technology to carry out knowledge coupling strategy.
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Jianjin Yue, Wenrui Li, Jian Cheng, Hongxing Xiong, Yu Xue, Xiang Deng and Tinghui Zheng
The calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type…
Abstract
Purpose
The calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type, there is currently no model that considers the time factor to accurately calculate the CFP of hospital building throughout their life cycle. This paper aims to establish a CFP calculation model that covers the life cycle of hospital building and considers time factor.
Design/methodology/approach
On the basis of field and literature research, the basic framework is built using dynamic life cycle assessment (DLCA), and the gray prediction model is used to predict the future value. Finally, a CFP model covering the whole life cycle has been constructed and applied to a hospital building in China.
Findings
The results applied to the case show that the CO2 emission in the operation stage of the hospital building is much higher than that in other stages, and the total CO2 emission in the dynamic and static analysis operation stage accounts for 83.66% and 79.03%, respectively; the difference of annual average emission of CO2 reached 28.33%. The research results show that DLCA is more accurate than traditional static life cycle assessment (LCA) when measuring long-term objects such as carbon emissions in the whole life cycle of hospital building.
Originality/value
This research established a carbon emission calculation model that covers the life cycle of hospital building and considered time factor, which enriches the research on carbon emission of hospital building, a special and extensive public building, and dynamically quantifies the resource consumption of hospital building in the life cycle. This paper provided a certain reference for the green design, energy saving, emission reduction and efficient use of hospital building, obviously, the limitation is that this model is only applicable to hospital building.
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Yanqing Shi, Hongye Cao and Si Chen
Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of…
Abstract
Purpose
Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.
Design/methodology/approach
The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.
Findings
There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.
Originality/value
This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.
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Ivo Hristov, Matteo Cristofaro, Riccardo Camilli and Luna Leoni
This paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four…
Abstract
Purpose
This paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four balanced scorecard (BSC) perspectives in operations management (OM) contexts and (2) understand how performance drivers and outcome measures (and substantiated perspectives) are related.
Design/methodology/approach
We undertake a systematic literature review of the BSC literature in OM journals. From the final sample of 40 articles, performance drivers and outcome measures have been identified, and the relationships amongst them have been synthesised according to the system dynamics approach.
Findings
Findings show (1) the most relevant performance drivers and outcome measures within each BSC perspective, (2) their relationships, (3) how the perspectives are linked through the performance drivers and outcome measures and (4) how the different measures relate systemically. Accordingly, four causal loops amongst identified measures have been built, which – jointly considered – allowed for the creation of a dynamic strategy map for OM.
Originality/value
This study is the first one that provides a comprehensive and holistic view of how the different performance drivers and outcome measures within and between the four BSC perspectives in OM relate systemically, increasing the knowledge and understanding of scholars and practitioners.
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Social enterprises (SEs), part of the third sector, are hybrid organizations combining the pursuit of social scopes with commercial business solutions. In seeking for social…
Abstract
Social enterprises (SEs), part of the third sector, are hybrid organizations combining the pursuit of social scopes with commercial business solutions. In seeking for social value, they pair for-profit and non-profit features, thereby compensating for shortcomings of both the public sector and the commercial market. Therefore, the performance management of such organizations assumes a crucial relevance. Among the available tools, the balanced scorecard (BSC) aims to capture performance multidimensionality, at the same time fostering legitimacy towards stakeholders.
In general terms, the BSC has the limit to follow a linear and static logic of construction and functioning. For this reason, scholars combine it with system dynamics (SD) to create dynamic balanced scorecards (DBSCs). However, literature seems to devote scarce attention to the adoption of such analytic tools in the third sector, particularly in SEs. This chapter wants to contribute to bridging this gap by proposing a tailored application in the context of a social cooperative, active in the clothing recycle and in the re-integration of disadvantaged social categories. By referring to previous literature about DBSC, two modelling strategies are identified: the BSC-driven and the SD-driven. The latter, based on inductive reasoning, is the one privileged for the study because of its wider flexibility. The modelling outputs consider different perspectives than the ones within traditional BSCs, contain elements of circular causality and show how financial and non-financial performances interplay and co-determine each other. Insights from the proposed model can be useful to support both decision-making and stakeholder engagement.
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Saswati Tripathi and Siddhartha Shankar Roy
This article aims to comprehensively review the measurement and management of supply chain performance (SCP) and strategic performance (SP). It strives to identify integrable…
Abstract
Purpose
This article aims to comprehensively review the measurement and management of supply chain performance (SCP) and strategic performance (SP). It strives to identify integrable features regarding frameworks, measurement approaches, practices and emerging research issues in these areas to integrate SCP and SP for measuring and managing performance. It intends to develop a dynamic-integrated-performance-system by incorporating integrable aspects of SCP and SP to link these domains for organizational performance improvement.
Design/methodology/approach
Using systematic-literature-review, this study analyzes 154 articles published in selected peer-reviewed international journals from 2000 to 2023 regarding SCP and SP. It assesses existing knowledge regarding research-design followed, challenging areas and imperatives in these critical business domains to investigate the prior conceptual, empirical, case study-based and literature-review-based articles.
Findings
The study identifies integrable features regarding key theoretical and measurement frameworks, critical objectives, significant measures, effective practices for measuring and managing SCP and SP and emerging research issues common to these areas. The findings help develop a dynamic-integrated-performance-system that uses the theoretical lenses of resource-based-view/dynamic-capability-theory and adopts a comprehensive framework like DBSC (system-dynamic-model with BSC perspectives). It incorporates identified integrable measures and best practices to monitor, measure, manage and improve organizational performance for sustainable competitive advantage. The article reveals that earlier studies have overlooked analyzing SCP and SP integration aspects.
Research limitations/implications
From the theoretical viewpoint, the present SLR is unique in three ways: first, in investigating both the measurement and management of SCP and SP holistically; second, in identifying integrative features of these two; and third, in proposing a DIPS to link SCP and SP for performance improvement. The study reveals that existing literature has focused on measuring and managing SCP and SP in isolation without attempting a comprehensive and unified approach to integrate the respective domains. The present SLR adopts a holistic approach to link SCP and SP from SCM and strategic-management perspectives. The study proposes a dynamic-integrated-performance-system to measure, manage and improve performance in a unified method.
Practical implications
This study provides SC and strategy practitioners with an understanding of strategy-performance pathways for achieving strategic objectives and executing risk mitigation initiatives to counter disruptions. It enables SC managers to comprehend SC practices and SCP leading to dynamic SC capabilities development. Operationalizing the proposed DIPS will help firms link SCP and SP, align operational SC practices with strategic sustainability and circularity objectives and meet sustainable development goals while benefiting social and environmental stakeholders.
Originality/value
Assessing relationships and identifying a unified approach integrating SCP with SP have not been addressed earlier. This study's uniqueness is finding integrable features of SCP and SP and constructing a dynamic-integrated-performance-system to link these domains for achieving strategic competitiveness.
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Ramatu Abdulkadir, Dante Benjamin Matellini, Ian D. Jenkinson, Robyn Pyne and Trung Thanh Nguyen
This study aims to determine the factors and dynamic systems behaviour of essential medicine stockout in public health-care supply chains. The authors examine the constraints and…
Abstract
Purpose
This study aims to determine the factors and dynamic systems behaviour of essential medicine stockout in public health-care supply chains. The authors examine the constraints and effects of mental models on medicine stockout to develop a dynamic theory of medicine availability towards saving patients’ lives.
Design/methodology/approach
This study uses a mixed-method approach. Starting with a survey method, followed by in-depth interviews with stakeholders within five health-care supply chains to determine the dynamic feedback leading to stockout and conclude by developing a network mental model for medicines availability.
Findings
The authors identified five constraints and developed five case mental models. The authors develop a dynamic theory of medicine availability across cases and identify feedback loops and variables leading to medicine availability.
Research limitations/implications
The need to include mental models of stakeholders like manufacturers and distributors of medicines to understand the system completely. Group surveys are prone to power dynamics and bias from group thinking. This survey’s quantitative output could minimize the bias.
Originality/value
This study uniquely uses a mixed-method of survey method and in-depth interviews of experts to assess the essential medicine stockout in Nigeria. To improve medicine availability, the authors develop a dynamic network mental model to understand the system structure, feedback and behaviour driving stockouts. This research will benefit public policymakers and hospital managers in designing policies that reduce medicine stockout.
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