Search results

According to the survey and measurement on rural housing in the Northeast severe cold regions of China, this paper analyzed the existing situation and problems of current rural housing in terms of integral development, functional layout, envelop structure, interior thermal environment, heating system and energy utilization etc.. Based on the climatic features of severe cold regions, as well as rural financial and technical conditions, living and production mode, residential construction characteristics and existing resource status etc., the feasible approaches of achieving building energy saving has been proposed, thus acting as a guidance for new rural housing design in severe cold regions.

The purpose of this work is to develop a computational paradigm for performance analysis of low-frequency electromagnetic devices containing both magnetic metamaterials (MTMs) and natural media.

A time domain finite element method (TDFEM) is proposed. The electromagnetic properties of the MTMs are modeled by a nonstandard Lorentz model. The time domain governing equation is derived by converting the one from the frequency domain into the time domain based on the Laplace transform and convolution. The backward difference is used for the temporal discretization. An auxiliary variable is introduced to derive the recursive formula.

The numerical results show good agreements between the time domain solutions and the frequency domain solutions. The error convergence trajectory of the proposed TDFEM conforms to the first-order accuracy.

To the best knowledge of the authors, the presented work is the first one focusing on TDFEMs for low-frequency near fields computations of MTMs. Consequently, the proposed TDFEM greatly benefits the future explorations and performance evaluations of MTM-based near field devices and systems in low-frequency electrical and electronic engineering.

This paper provides empirical evidence on the impact of societal trust in three dimensions of banking activity: the quantity and quality of credit granted by banks and their economic performance.

The paper uses a sample of 1,366 European banks from 36 countries between 2014 and 2020. In our estimations, we control for bank-specific and country-specific determinants of banking activity. Moreover, we perform several robustness tests, including estimation by instrumental variables and hierarchical linear methods, variable definitions, and subsamples.

Societal trust increases the weight of credit on the balance sheets of banks and decreases the weight of nonperforming loans and net interest margins. Moreover, the results suggest a smaller (higher) impact of trust on loans and net interest margins (nonperforming loans) in the European Monetary Union (EMU) countries. Also, on the importance of loans and net interest margins, our results suggest a substitution effect between trust and the credit-favorable nature of the legal environment.

The symmetrical sign of the effect of societal trust on the importance of loans – positive – and nonperforming loans and net interest margins – negative – suggests that potential asymmetric information biases may be less severe or better accounted for by the credit risk evaluation in highly trustworthy environments. Also, bank managers should recognize risk factors related to trust levels and benefit from targeted risk mitigation measures and from implementing strategies aimed at enhancing profitability in different societal trust scenarios.

This paper provides empirical evidence on the impact of societal trust on banking activity from the perspective of the lending activity, risk and performance of banks. It also analyses the effects of EMU membership and the credit-favorable nature of the legal environment.

Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

Although interdisciplinary research is an increasing trend in scientific funding projects, they are suffering from a lower probability of being funded. The purpose of this paper is to analyze the current situation on successful case of funding application and provides suggestions on how libraries can expand services to help scientific funding application.

This paper utilizes the co-occurrences of disciplinary application codes to construct an interdisciplinary knowledge flow network. Based on 193517 sponsored projects of the National Natural Science Foundation of China, the authors study the interdisciplinary flow of knowledge and investigate the evolution of network structure using social network analysis.

Results show that the interdisciplinary knowledge flow network is not only a small-world network but also a scale-free network. Two main knowledge flow paths across scientific departments exist, showing the heterogeneity of knowledge distributions across scientific disciplines. The authors also find that if two disciplines in the same scientific department both have a wide influence to other disciplines, they are more prone to link together and create a knowledge chain.

Funding consultation currently has not occupied an advisory role either in library services or in the research team. This paper conducts a co-occurrences network analysis of interdisciplinary knowledge flow in scientific funding projects. Considering the complexity of funding application and the advantage of traditional library services on information collection, integration, and utilization, the authors conclude the possibility and necessity of embedding funding consultation in traditional library services.

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.

This paper aims to propose a novel system identification and resonance suppression strategy for motor-driven system with high-order flexible manipulator.

In this paper, first, a unified mathematical model is proposed to describe both the flexible joints and the flexible link system. Then to suppress the resonance brought by the system flexibility, a model based high-order notch filter controller is proposed. To get the true value of the parameters of the high-order flexible manipulator system, a fuzzy-Kalman filter-based two-step system identification algorithm is proposed.

Compared to the traditional system identification algorithm, the proposed two-step system identification algorithm can accurately identify the unknown parameters of the high order flexible manipulator system with high dynamic response. The performance of the two-step system identification algorithm and the model-based high-order notch filter is verified via simulation and experimental results.

The proposed system identification method can identify the system parameters with both high accuracy and high dynamic response. With the proposed system identification and model-based controller, the positioning accuracy of the flexible manipulator can be greatly improved.

A class of robust and efficient beamforming methods is developed in this paper for the optimised design of realistic microstrip antennas on arbitrarily curved substrates. More specifically, this paper aims to focus on the formulation of an effective and computationally light beamforming algorithm and its implementation on a novel realistic cylindrical-substrate microstrip array antenna with significantly decreased size, wideband operation and enhanced radiation characteristics.

The proposed multi-parametric schemes introduce an efficient null-steering concept, which drastically annihilates the undesired beamformer waveform artefacts, while retaining the real output signal undistorted. In particular, the key objective is the accurate calculation of the appropriate complex feeding weights, required to set nulls along the propagation directions of the unwanted signals and a maximum towards the propagation direction of the desired incoming signal. The featured technique, combined with a modified finite element method, is applied to the design of a new family of cylindrical-substrate microstrip array antennas.

Numerical results, mainly concerning customisable three-dimensional radiation patterns and attributes, certify the merits of the algorithm and its limited system demands. The introduced beamforming algorithms are applied to a variety of different inputs (desired radiation patterns), which indicate that the designed cylindrical-substrate antenna overwhelms existing designs in terms of computational cost for the beamforming algorithm, while retaining acceptable values for radiation characteristics, such as gain, directivity and side-lobe suppression. In this manner, the effectiveness of the prior methodology and the benefits of this newly shaped array antenna are comprehensively revealed and substantiated.

Rigorous beamforming techniques in conjunction with a class of contemporary array antennas are developed for potential use in high-end communication systems, such as 5G configurations. The proposed cylindrical-shaped structures are systematically designed, with an emphasis on space efficiency and wideband radiation effectiveness to offer fully adjustable setups. To this aim, the cylindrical-substrate microstrip antenna, because of its inherent azimuthal symmetry and confined overall dimensions, provides reliable operation and promising performance.