Shanghai Maritime University

This paper addresses the harmonic stability caused by the interactions among the wideband control of power converters and passive components in an ac power-electronics-based power system. The impedance-based analytical approach is employed and expanded to a meshed and balanced three-phase network which is dominated by multiple current- and voltage-controlled inverters with LCL- and LC-filters. A method of deriving the impedance ratios for the different inverters is proposed by means of the nodal admittance matrix. Thus, the contribution of each inverter to the harmonic stability of the power system can be readily predicted through Nyquist diagrams. Time-domain simulations and experimental tests on a three-inverter-based power system are presented. The results validate the effectiveness of the theoretical approach.

Abstract Modern corporations are faced with many environmental challenges and pressures. Managers of firms have realized that green innovation is an important factor in sustainable development and that it can offer a competitive advantage. This study uses organizational identity and organizational creativity theory to create a theoretical framework for understanding green innovation strategy. The results indicated that green innovation strategy positively influences both green organizational identity and green creativity. Positive relationships are found between green organizational identity and green creativity, and green creativity positively affects green innovation. In addition, we find that green organizational identity partially mediates the relationship between green innovation strategy and green creativity. We also find that green organizational identity fully mediates the relationship between green innovation strategy and green innovation, which means that green innovation strategy does not directly influence green innovation but indirectly stimulates such innovation via green organizational identity. These results suggest that managers should seek to enhance their organizations' sense of green identity and to encourage green creativity, as this will enhance their firm's capability of sustainable development. The theoretical and practical implications of these findings are also discussed. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment

The disasters caused by epidemic outbreaks is different from other disasters due to two specific features: their long-term disruption and their increasing propagation. Not controlling such disasters brings about severe disruptions in the supply chains and communities and, thereby, irreparable losses will come into play. Coronavirus disease 2019 (COVID-19) is one of these disasters that has caused severe disruptions across the world and in many supply chains, particularly in the healthcare supply chain. Therefore, this paper, for the first time, develops a practical decision support system based on physicians' knowledge and fuzzy inference system (FIS) in order to help with the demand management in the healthcare supply chain, to reduce stress in the community, to break down the COVID-19 propagation chain, and, generally, to mitigate the epidemic outbreaks for healthcare supply chain disruptions. This approach first divides community residents into four groups based on the risk level of their immune system (namely, very sensitive, sensitive, slightly sensitive, and normal) and by two indicators of age and pre-existing diseases (such as diabetes, heart problems, or high blood pressure). Then, these individuals are classified and are required to observe the regulations of their class. Finally, the efficiency of the proposed approach was measured in the real world using the information from four users and the results showed the effectiveness and accuracy of the proposed approach.

The concept of safety culture is characterised by complexity. On the one hand, the concept is challenging content-wise, and on the other hand, is it a multi-dimensional and cross-disciplinary research domain. In this paper, bibliometric analysis has been applied to the field of safety culture to identify fundamental influences and to obtain a structured overview of the characteristics and the developments in this research domain. In total, 1789 publications published between 1900 and 2015 related to safety culture were identified in Web of Science. The 1789 publications cover 4591 authors, 775 journals, 76 countries or territories, and 1866 institutions. Two main research areas can be distinguished in the domain of safety culture: (1) organisational safety culture and (2) health-care and patient safety culture. The latter research area stands in a dominant position in safety culture research nowadays. Key publications are from Guldenmund (2000) and Sexton et al. (2006). Furthermore, ‘Safety Science’ is the key journal publishing on safety culture research, and the USA, England and China are the countries that dominate the publication production. It can be concluded that there is much collaborative research in the safety culture domain as multi-authored publications make up about three quarters of all publications. Also, safety culture research is characterised by a wide variety of research themes and multidisciplinarity. Geographical inequality in the publication output is identified as a point of concern. A movement away from technical aspects towards more human aspects could be detected as a noteworthy change in research focus.

Abstract Previous studies on the effect of International Financial Reporting Standards (IFRS) on accounting quality often have difficulties to control for confounding factors on accounting quality. As a result, the observed changes in accounting quality could not be attributed mainly to IFRS. We use a unique research setting to address this issue by comparing the accounting quality of publicly listed companies in 15 member states of the European Union (EU) before and after the full adoption of IFRS in 2005. We use five indicators as proxies for accounting quality. We find that the majority of accounting quality indicators improved after IFRS adoption in the EU. That is, there is less of managing earnings toward a target, a lower magnitude of absolute discretionary accruals, and higher accruals quality. But our results also show that firms engage in more earnings smoothing and recognize large losses in a less timely manner in post‐IFRS periods. In addition, we examine the effects of institutional variables on financial reporting quality. Our contribution to the literature is that we show the improved accounting quality is attributable to IFRS, rather than changes in managerial incentives, institutional features of capital markets, and general business environment, etc.

A higher order passive power filter (LLCL filter) for the grid-tied inverter is becoming attractive for industrial applications due to the possibility to reduce the cost of the copper and the magnetic material. However, similar to the conventional LCL filter, the grid-tied inverter is facing control challenges. An active or a passive damping measure can be adopted to suppress the possible resonances between the grid and the inverter. For an application with a stiff grid, a passive damping method is often preferred for its simpleness and low cost. This paper introduces a new passive damping scheme with low power loss for the LLCL filter. Also, a simple engineering design criterion is proposed to find the optimized damping resistor value, which is both effective for the LCL filter and the LLCL filter. The control analysis and the power loss comparison for different filter cases are given. All these are verified through the experiments on a 2-kW single-phase grid-tied inverter prototype using proportional resonant controllers. It is concluded that, compared with the LCL filter, the proposed passive damped LLCL filter can not only save the total filter inductance and reduce the volume of the filter but also reduce the damping power losses for a stiff grid application.

A new bio-inspired algorithm, namely Bird Swarm Algorithm (BSA), is proposed for solving optimisation applications. BSA is based on the swarm intelligence extracted from the social behaviours and social interactions in bird swarms. Birds mainly have three kinds of behaviours: foraging behaviour, vigilance behaviour and flight behaviour. Birds may forage for food and escape from the predators by the social interactions to obtain a high chance of survival. By modelling these social behaviours, social interactions and the related swarm intelligence, four search strategies associated with five simplified rules are formulated in BSA. Simulations and comparisons based on eighteen benchmark problems demonstrate the effectiveness, superiority and stability of BSA. Some proposals for future research about BSA are also discussed.

Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.

This research introduces a path planning method based on the geometric A-star algorithm. The whole approach is applied to an Automated Guided Vehicle (AGV) in order to avoid the problems of many nodes, long-distance and large turning angle, and these problems usually exist in the sawtooth and cross paths produced by the traditional A-star algorithm. First, a grid method models a port environment. Second, the nodes in the close-list are filtered by the functions P(x,y ) and W(x,y ) and the nodes that do not meet the requirements are removed to avoid the generation of irregular paths. Simultaneously, to enhance the stability of the AGV regarding turning paths, the polyline at the turning path is replaced by a cubic B-spline curve. The path planning experimental results applied to different scenarios and different specifications showed that compared with other seven different algorithms, the geometric A-star algorithm reduces the number of nodes by 10% ~ 40%, while the number of turns is reduced by 25%, the turning angle is reduced by 33.3%, and the total distance is reduced by 25.5%. Overall, the simulation results of the path planning confirmed the effectiveness of the geometric A-star algorithm.

This paper presents a new topology of higher order power filter for grid-tied voltage-source inverters, named the LLCL filter, which inserts a small inductor in the branch loop of the capacitor in the traditional LCL filter to compose a series resonant circuit at the switching frequency. Particularly, it can attenuate the switching-frequency current ripple components much better than an LCL filter, leading to a decrease in the total inductance and volume. Furthermore, by decreasing the inductance of a grid-side inductor, it raises the characteristic resonance frequency, which is beneficial to the inverter system control. The parameter design criteria of the proposed LLCL filter is also introduced. The comparative analysis and discussions regarding the traditional LCL filter and the proposed LLCL filter have been presented and evaluated through experiment on a 1.8-kW-single-phase grid-tied inverter prototype.

Smart cities have been a global concern in recent years, involving comprehensive scientific research. To obtain a structural overview and assist researchers in making insights into the characteristics of smart cities research, bibliometric analysis was carried out in this paper. With the application of the bibliometric analysis software VOSviewer and CiteSpace, 4409 smart cities were identified by the core collection of the Web of Science in publications between 1998 and 2019 and used in the analysis of this paper. Concretely, this research visually demonstrates a comprehensive overview of the field relating to smart cities in terms of the production of regular publications, main domain of smart cities researchers, most influential countries (institutions, sources and authors), and interesting research directions in the smart city researches. We also present the research collaboration among countries (regions), organizations and authors based on a series of cooperation analyses. The bibliometric analysis of the existing work provided a valuable and seminal reference for researchers and practitioners in smart cities-related research communities.

Grid-tied voltage source inverters using LCL filter have been widely adopted in distributed power generation systems (DPGSs). As high-order LCL filters contain multiple resonant frequencies, switching harmonics generated by the inverter and current harmonics generated by the active/passive loads would cause the system resonance, and thus the output current distortion and oscillation. Such phenomenon is particularly critical when the power grid is weak with the unknown grid impedance. In order to stabilize the operation of the DPGS and improve the waveform of the injected currents, many innovative damping methods have been proposed. A comprehensive overview on those contributions and their classification on the inverter- and grid-side damping measures are presented. Based on the concept of the impedance-based stability analysis, all damping methods can ensure the system stability by modifying the effective output impedance of the inverter or the effective grid impedance. Classical damping methods for industrial applications will be analyzed and compared. Finally, the future trends of the impedance-based stability analysis, as well as some promising damping methods, will be discussed.

As many unethical practices and violations of social norms originate from higher tier suppliers and their sub-suppliers, it is of paramount importance to ensure social sustainability in the entire supply chain, especially for higher tier suppliers. This has led to a considerable increase in interest among the researchers and academicians working in the domain of social sustainability. This article reviews 129 research papers published in different journals and attempted to identify drivers, issues, barriers, tensions, practices, and performances related to social sustainability in multi-tier supply chains. The prevalent theories and governance mechanisms of social sustainability in multi-tier supply chains have also been presented. The commonly used theories are stakeholder theory, institutional theory, resource based view theory, transaction cost economics theory, grounded theory, and resource dependence theory. It is observed that most of the papers have presented drivers, barriers, issues, and practices in generic ways by conducting exploratory case studies using single case or multiple cases; there is a distinct lack of multi-tier perspectives devoted to the context of emerging economies. The tension, an important aspect of implementation of social sustainability practices, has not been addressed adequately in the extant literature for multi-tier supply chains. This review also proposes a conceptual framework of social sustainability linking drivers, issues, barriers, tensions, practices, and performances. Finally, future avenues of research on social sustainability have been outlined.

In this paper, we investigate the combined active front-wheel steering/direct yaw-moment control for the improvement of vehicle lateral stability and vehicle handling performance. A more practical assumption in this work is that the longitudinal velocity is not constant but varying within a range. Both the nonlinear tire model and the variation of longitudinal velocity are considered in vehicle system modeling. A linear-parameter-varying model with norm-bounded uncertainties is obtained. To track the system reference, a generalized proportional-integral (PI) control law is proposed. Since it is difficult to get the analytic solution for the PI gains, an augmented system is developed, and the PI control is then converted into the state-feedback control for the augmented system. Both the stability and the energy-to-peak performance of the augmented system are explored. Based on the analysis results, the controller-gain tuning method is proposed. The proposed control law and controller design method are illustrated via an electric vehicle model.

After optimization using percolation theory, excellent absorbing properties (90% absorption) were achieved for Ni/C nanocomposites with advantages such as thin thickness (1.75 and 1.5 mm) and light weight (25 and 30 wt%).

With the advent of the Internet of Things (IoT), the security of the network layer in the IoT is getting more and more attention. The traditional intrusion detection technologies cannot be well adapted in the complex Internet environment of IoT. For the deep learning algorithm of intrusion detection, a neural network structure may have fine detection accuracy for one kind of attack, but it may not have a good detection effect when facing other attacks. Therefore, it is urgent to design a self-adaptive model to change the network structure for different attack types. This paper presents an intrusion detection model based on improved genetic algorithm (GA) and deep belief network (DBN). Facing different types of attacks, through multiple iterations of the GA, the optimal number of hidden layers and number of neurons in each layer are generated adaptively, so that the intrusion detection model based on the DBN achieves a high detection rate with a compact structure. Finally, the NSL-KDD dataset was used to simulate and evaluate the model and algorithms. The experimental results show that the improved intrusion detection model combined with DBN can effectively improve the recognition rate of intrusion attacks and reduce the complexity of the neural network structure.

Prosumer concept and digitilization offer the exciting potential of microgrid transactive energy systems at distribution level for reducing transmission losses, decreasing electric infrastructure expenditure, improving reliability, enhancing local energy use, and minimizing customers' electricity bills. Distributed energy resources, demand response, distributed ledger technologies, and local energy markets are integral parts of transaction energy system for emergence of decentralized smart grid system. Hence, this paper discusses transactive energy concept and proposes seven functional layers architecture for designing transactive energy system. The proposed architecture is compared with practical case study of Brooklyn microgrid. Moreover, this paper reviews the existing architectures and explains the widely known distributed ledger technologies (blockchain, directed acyclic graph, hashgraph, holochain, and tempo) alongwith their advantages and challenges. The local energy market concept is presented and critically analyzed for energy trade within a transactive energy system. This paper also reviews the potential and challenges of peer-to-peer and community-based energy markets. Proposed architecture and analytical review of distributed ledger technologies and local energy markets pave the way for advanced research and industrialization of transactive energy systems.

Modern power systems face different challenges such as the ever-increasing electrical energy demand, the massive growth of renewable energy with distributed generations, the large-scale Internet of Things (IoT) devices adaptation, the emerging cyber-physical security threats, and the main goal of maintaining the system's stability and reliability. These challenges pose extreme pressure on finding advanced technologies and sustainable solutions for secure and reliable operations of the power system. The blockchain is one of the recent technologies that have gained lots of attention in different applications including smart grid for its uniqueness and decentralized nature. In the last few years, this technology grew a momentum specifically with the cryptocurrencies' industry such as the Bitcoin and Etherium. The Blockchain's applications in the smart grids could offer many innovative and affordable solutions to some of the challenges that the future and the current smart grids will be facing. This paper reviews different prospects, advantages, approaches, and technical challenges of utilizing the blockchain technology in the smart grid, and presents frameworks for key smart grid blockchain-based applications; more specifically, it is shown that how the blockchain can be used as the smart grid's cyber-physical layer.

In recent decades, reverse logistics has garnered considerable attention since it recovers value of returning products, satisfies environmental requirements, and pays attention to customers’ rights. Suppliers, as the first layer of the supply chain network, pose a great impact on environmental pollution. Therefore, in this paper a hybrid approach of fuzzy analysis network process (FANP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL), and multi-objective mixed-integer linear programming (MOMILP) models are developed for circular supplier selection and order allocation in a multi-product circular closed-loop supply chain (C-CLSC) considering multi-depot, capacitated green routing problem using heterogeneous vehicles. In this regard, a mathematical model concerning an inventory-location-routing problem is developed that minimises cost and shortage simultaneously and also deals with imposed uncertainties. A fuzzy solution approach is proposed to simultaneously incorporate uncertainty and to change the multi-objective model into a single-objective model. To motivate the practical aspect of the proposed model in real world applications, we applied the model to an automotive timing belt manufacturer. The obtained results indicate that the proposed model is cost efficient and environmentally friendly for CLSC network designs.

IoT devices have some special characteristics, such as mobility, limited performance, and distributed deployment, which makes it difficult for traditional centralized access control methods to support access control in current large-scale IoT environment. To address these challenges, this paper proposes an access control system in IoT named fabric-iot, which is based on Hyperledger Fabric blockchain framework and attributed based access control (ABAC). The system contains three kinds of smart contracts, which are Device Contract (DC), Policy Contract (PC), and Access Contract (AC). DC provides a method to store the URL of resource data produced by devices, and a method to query it. PC provides functions to manage ABAC policies for admin users. AC is the core program to implement an access control method for normal users. Combined with ABAC and blockchain technology, fabric-iot can provide decentralized, fine-grained and dynamic access control management in IoT. To verify the performance of this system, two groups of simulation experiments are designed. The results show that fabric-iot can maintain high throughput in large-scale request environment and reach consensus efficiently in a distributed system to ensure data consistency.