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Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.

To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.

Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.

This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.

Green energy as a transportation supply trend is irreversible. In this paper, a highway energy supply system (HESS) evolution model is proposed to provide highway transportation vehicles and service facilities with a clean electricity supply and form a new model of a source-grid-load-storage-charge synergistic highway-PV-WT integrated system (HPWIS). This paper aims to improve the flexibility index of highways and increase CO₂ emission reduction of highways.

To maximize the integration potential, a new energy-generation, storage and information-integration station is established with a dynamic master–slave game model. The flexibility index is defined to evaluate the system ability to manage random fluctuations in power generation and load levels. Moreover, CO₂ emission reduction is also quantified. Finally, the Lianhuo Expressway is taken as an example to calculate emission reduction and flexibility.

The results show that through the application of the scheduling strategy to the HPWIS, the flexibility index of the Lianhuo Expressway increased by 29.17%, promoting a corresponding decrease in CO₂ emissions.

This paper proposed a new model to capture the evolution of the HESS, which provides highway transportation vehicles and service facilities with a clean electricity supply and achieves energy transfer aided by an energy storage system, thus forming a new model of a transportation energy system with source-grid-load-storage-charge synergy. An evaluation method is proposed to improve the air quality index through the coordination of new energy generation and environmental conditions, and dynamic configuration and dispatch are achieved with the master–slave game model.

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

The contribution of the banking industry to the financial crisis of 2007/8 has raised public concerns about the financial soundness of banks around the world with many countries still suffering the backlogs of this crisis. The continuous emergence of such crises at both national and international levels increases governments', bank regulators' and financial market participants' need for reliable tools to assess the financial soundness of banks. In this context, this study investigates the financial soundness of the Kazakh banking sector, which is ranked by the World Bank as the first in the world in terms of the percentage of nonperforming loans (NPL) to total gross loans in 2012.

Using data about all Kazakh banks over the period January 01, 2008 to January 01, 2014, the study identifies a number of accounting indicators that influence the financial soundness of banks using principal component analysis (PCA). Then, it uses the outcomes of the PCA in a cluster analysis and groups the Kazakh banks into sound, risky and unsound banks at two points in time: January 01, 2008 and January 01, 2014. This methodology was further tested against a ranking system of banks and proved to be more reliable in detecting risky banks.

Fifteen financial ratios were initially selected as accounting indicators for the assessment of bank financial soundness. Using PCA, twelve indicators were isolated, which explain five principal components of capital adequacy, return on assets, profitability, asset quality, liquidity and leverage. Then using the “k-means” method, the results suggest a structure of the Kazakh banking sector on January 01, 2008 that includes two groups of banks: sound and risky banks. On January 01, 2014, this structure of the banking system has changed to include three groups of banks: sound, risky and unsound banks. Thus, in 2014 a new group of banks has emerged, i.e. financially unsound banks.

The proposed cluster-based methodology has proven to be a reliable tool to detect the financial soundness of Kazakh banks, which makes us advocate its employability for bank monitoring and supervision purposes.

This study is the first to employ a cluster-based methodology to assess the financial soundness of a banking sector. This methodology can be used at a micro-level to determine the structure of a banking sector. Also, it can be used to monitor any changes in the structure of a banking sector and provide early warning signals about the financial health of banks.

In the current dynamic business environment, Internet of Things (IoT) is employed by a number of companies in the logistics industry to achieve intelligent sorting, network optimization, real-time tracking and simplifying last-mile service. Although logistics entities are trying to introduce IoT into their business areas, users' perception of this new technology is still limited. This paper aims to develop a research model for the factors influencing the user adoption of IoT technology in the logistics industry.

In this study, based on the major theories on the application of new technologies such as technology acceptance model (TAM), technology–organization–environment (TOE) and innovation diffusion theory (IDT), a new research model was established to identify factors affecting customers' behavioral intention (BI) to adopt IoT technology provided by logistics companies. In addition, the authors surveyed unspecified customers of Cainiao Logistics Network, which is in charge of the logistics operation of Alibaba Group, China's largest e-commerce company, and tested the causality between the latent variables presented in the model using the structural equation model (SEM).

This empirical study shows that the support system of a logistics company and users' innovative propensity significantly affect perceived ease of use (PEOU) and BI for logistics services to which IoT technology is applied. It also presents that users' perceived security and enjoyment significantly affect perceived usefulness (PU) and BI. In addition, it was possible to confirm that the causal structure between variables suggested by TAM that PEOU has a significant effect on PU and BI, and PU has a substantial effect on BI.

Logistics companies should expand and upgrade technical support systems so that customers can flexibly accept logistics services with IoT technology and make efforts to alleviate customers' concerns about personal information leakage. In addition, it is necessary to find customers with an inclusive attitude toward using new technologies, to induce them to become leading users of logistics devices with IoT technology and to find various ways to amplify their enjoyment. Through a strategic approach to these technical and individual factors, it will be possible to boost customers' intention to use IoT logistics services.

As far as the authors know, this paper is the first study to set significant factors that affect users' BI to use IoT technology-applied logistics services provided by logistics companies and empirically analyze the causal relationships between proposed latent variables.

The purpose of this paper is to propose a smooth double-spline interpolation method for six-degree-of-freedom rotational robot manipulators, achieving the global C2 continuity of the robot trajectory.

This paper presents a smooth double-spline interpolation method, achieving the global C2 continuity of the robot trajectory. The tool center positions and quaternion orientations are first fitted by a cubic B-spline curve and a quartic-polynomial-based quaternion spline curve, respectively. Then, a parameter synchronization model is proposed to realize the synchronous and smooth movement of the robot along the double spline curves. Finally, an extra u-s function is used to record the relationship between the B-spline parameter and its arc length parameter, which may reduce the feed rate fluctuation in interpolation. The seven segments jerk-limited feed rate profile is used to generate motion commands for algorithm validation.

The simulation and experimental results demonstrate that the proposed method is effective and can generate the global C2-continuity robot trajectory.

The main contributions of this paper are as follows: guarantee the C2 continuity of the position path and quaternion orientation path simultaneously; provide a parameter synchronization model to realize the synchronous and smooth movement of the robot along the double spline curves; and add an extra u-s function to realize arc length parameterization of the B-spline path, which may reduce the feed rate fluctuation in interpolation.

This paper presents a generic simulation model to determine the equipment mix (quay, yard and intra-terminal transfer) for a Container Terminal Logistics Operations System (CTLOS). The simulation model for the CTLOS, a typical type of discrete event dynamic system (DEDS), consists of three sub-models: ship queue, loading-unloading operations and yard-gate operations. The simulation model is empirically applied to phase 1 of the Yangshan Deep Water Port in Shanghai. This study considers different scenarios in terms of container throughput levels, equipment utilization rates, and operational bottlenecks, and presents a sensitivity analysis to evaluate and choose reasonable equipment ratio ranges under different operational conditions.

Under the global climate change, carbon footprint has become a hot issue at home and abroad. However, there is no consensus on the concept, measurement and application of carbon footprint.

In this paper, first, the concept and connotation of carbon footprint are reviewed; then, different methods of carbon footprint measurement are compared, and it is found that “bottom-up” life cycle assessment and “top-down” input–output analysis are applicable to different research scales.

Finally, the problems in the process of carbon footprint assessment in textile industry are analyzed and further research directions are proposed.

Analyzed and further research directions are proposed.