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The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.

In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance the capacity of polynomials approximation and the manifolds optimization method was introduced to solve the co-related optimization problem.

Two multi-variable Laguerre polynomials regression methods are designed. Firstly, Laguerre polynomials are combined with feature selection method. Secondly, manifolds component analysis is adopted in cascaded Laguerre polynomials regression method. Two methods are brought to enhance the accuracy of multi-variable regression method.

With the increasing number of variables in regression problem, the stable accuracy performance might not be kept by using manifold-based optimization method. Moreover, the methods mentioned in this paper are not suitable for the classification problem.

Experiments are conducted on three types of datasets to evaluate the performance of the proposed regression methods. The best accuracy was achieved by the combination of cascade, manifold optimization and Chebyshev polynomials, which implies that the manifolds optimization has stronger contribution than the genetic algorithm and Laguerre polynomials.

SNS, namely social networking sites, has become one of the most effective and fast channels of information diffusion and dissemination. As an influential way of online marketing, SNS has been increasingly used by tourism organizations and enterprises to shape their destination image. On the basis of previews literature of destination image and SNS, this paper used the text analysis software ROST Content Mining (ROST CM) System to do a case study of the SNS destination marketing of Singapore on Chinese market. The authors analyze the text related to Singapore tourism on the major SNS in mainland China: Renren, Sina Weibo, and Douban, through word frequency analysis and the social semantic network, to summarize the destination image of Singapore on SNS. The paper also focuses on the difference of image building by official and individual SNS. Results found by this paper can be used by the relevant tourism organizations and enterprises to improve their destination marketing and image building on SNS channels.

This study aims to find a novel solution to the calibration of three-axis magnetometers to suppress errors of sensors. The nature of the calibration process is parameter estimation and hence the purpose of the paper is to calculate the error parameters and eliminate sensor errors and obtain the true value of the pure magnetic field.

The paper puts forward a calibration method using an alternative iteration looping optimization (AILO) to estimate the parameters. The proposed method divided the parameters to be estimated into two parts: a portion less than one and the other greater than one. Parameters with different orders of magnitude are calculated respectively, which let one part to be a known quantity and the other part is derived by the known quantity; the derived quantity is used to calculate the known quantity again, and looping iteration multiple times until the iteration termination condition is satisfied.

The simulation and experimental results indicate that the calibration accuracy is improved at least by two orders by the proposed method compared to the two-step method and the linear decreasing weight particle swarm optimization (LDW-PSO) algorithm which proves the validity of the proposed method.

The proposed method can improve the calibration accuracy of total magnetic field, which provides a reference to the calibration of three-axis magnetometers.

A calibration method based on the AILO is proposed in this paper, which is used to improve the calibration accuracy of the three-axis magnetometer.

The purpose of this paper is to present a novel scheme of high‐dynamic global positioning system (GPS) software receiver in order to improve the capturing speed and trading accuracy of GPS receiver.

First, the beginning of C/A code can be found through the delay and multiply approach. To solve the problems of estimating a certain satellite's Doppler shift from the signals of several visible satellites, the “delay and accumulation unit” is put forward, and besides, performance of inertial navigation system‐assisted tracking loop in high‐dynamic circumstance is analysed by means of mathematical modelling and simulation experiments, whose results verified the validity of the proposed tracking scheme.

In this paper, the two‐dimension searching process in conventional acquisition scheme is transformed into two one‐dimension searching processes, thus improving the capturing speed.

This software receiver has only been verified by means of mathematical simulation, and the validity in hardware receiver is still obscured.

This paper presents a novel high‐dynamic GPS software receiver scheme, which can be seen as a reference of engineering application and simulation research.

Accurate and timely cost prediction is critical to the success of construction projects which is still facing challenges especially at the early stage. In the context of rapid development of machine learning technology and the massive cost data from historical projects, this paper aims to propose a novel cost prediction model based on historical data with improved performance when only limited information about the new project is available.

The proposed approach combines regression analysis (RA) and artificial neural network (ANN) to build a novel hybrid cost prediction model with the former as front-end prediction and the latter as back-end correction. Firstly, the main factors influencing the cost of building projects are identified through literature research and subsequently screened by principal component analysis (PCA). Secondly the optimal RA model is determined through multi-model comparison and used for front-end prediction. Finally, ANN is applied to construct the error correction model. The hybrid RA-ANN model was trained and tested with cost data from 128 completed construction projects in China.

The results show that the hybrid cost prediction model has the advantages of both RA and ANN whose prediction accuracy is higher than that of RA and ANN only with the information such as total floor area, height and number of floors.

(1) The most critical influencing factors of the buildings’ cost are found out by means of PCA on the historical data. (2) A novel hybrid RA-ANN model is proposed which proved to have the advantages of both RA and ANN with higher accuracy. (3) The comparison among different models has been carried out which is helpful to future model selection.

This paper aims to elucidate the effects of lubricant groove shape, vertical load, swing angle and grease injection cycle on the friction and wear performances of journal bearings under the grease lubrication condition.

Three different types of lubricant grooves, namely, numeral eight-shaped, axial straight line-shaped and circular blind hole-shaped, were designed and machined in the bearing bush of journal bearings. The tribological behaviors of these journal bearings were investigated on the self-developed reciprocating swing friction and wear tester. Experimental data including the friction coefficient, the friction temperature, the wear loss and wear time were analyzed in detail. The wear morphologies of friction pairs were observed by scanning electron microscope and confocal laser scanning microscope.

The load carrying capacity and service life of the journal bearing with circular blind hole-shaped lubricant grooves are not affected. However, the load carrying capacities of journal bearings with numeral eight-shaped and axial straight line-shaped lubricant grooves are declined. The coverage areas of lubricating grease in the bearing bush are associated with the swing angle. The smaller the swing angle is, the more limited the coverage areas of lubricating grease get. Among these journal bearings, the maintenance-free time of journal bearing with circular blind hole-shaped lubricant grooves is the longest because of its large grease storage capacity.

The journal bearing with circular blind hole-shaped lubricant grooves exhibits the excellent antifriction and wear-resistant properties, making it suitable for the application in the low-speed and heavy-load engineering conditions.

The purpose of this paper is to study the road segmentation problem of cross-modal remote sensing images.

First, the baseline network based on the U-net is trained under a large-scale dataset of remote sensing imagery. Then, the cross-modal training data are used to fine-tune the first two convolutional layers of the pre-trained network to achieve the adaptation to the local features of the cross-modal data. For the cross-modal data of different band, an autoencoder is designed to achieve data conversion and local feature extraction.

The experimental results show the effectiveness and practicability of the proposed method. Compared with the ordinary method, the proposed method gets much better metrics.

The originality is the transfer learning strategy that fine-tunes the low-level layers for the cross-modal data application. The proposed method can achieve satisfied road segmentation with a small amount of cross-modal training data, so that is has a good application value. Still, for the similar application of cross-modal data, the idea provided by this paper is helpful.

The purpose of this paper is to examine the post-enactment status of China’s Labour Contract Law and Labour Dispute Mediation and Arbitration Law, focusing on the dramatic rise in remuneration litigation amidst much criticism of weak or ineffective implementation of these laws.

This paper deploys both quantitative and qualitative analysis methods to investigate the features of remuneration litigation. Remuneration judgments by Beijing People’s Courts from 1 January 2014 to 31 December 2017 provide the primary empirical data. The intrinsic features of remuneration disputes are investigated to delineate subcategories of claims. Several judges were also interviewed to further explore the nature of remuneration disputes.

Four types of remuneration claims were identified: regular wage, minimum wage, overtime and others (including subsidies and welfare). Examination of these four types, especially how they are processed until concluded by court adjudication, provides a fuller picture of the post-enactment status of these laws and yields objective and rational findings. To explain the continuing steady rise in the volume of remuneration claims, as more workers have knowledge of their rights and access to the courts, this study identifies an increase in the number of factually complicated cases (e.g. overtime claims) and abmiguity in the relevant law, leaving some remuneration disputes difficult, if not impossible, to adjudicate. Conversely, the study also finds significant positive trends following these laws’ enactment, particularly a reduction in straightforward cases, such as disputes concerning non-payment of wages/minimum wages, on which the law is clear. It is evidently imperative to improve the clarity of the current laws through further legislation, as the most appropriate next step in China’s juridification process of developing its own rule of Labour Law.

This study is purposely limited to examining remuneration litigation in Beijing’s courts from 2014 to 2017, which is representative of the national trend of dramatically rising remuneration disputes, and thus provides valuable insights. Future studies should cover a wider geographic territory and other categories of labour disputes to provide an even more comprehensive picture of the challenges and potential solutions.

By understanding the driving factors of rising labour remuneration disputes, the legislature, workers and employers can act accordingly to curb labour conflicts. The growing complexity and technicality of remuneration litigation indicates that the pressing need of labour juridification is to deploy a subtle, comprehensive method to improve legal clarity and judicial professionalism.

This study uniquely divides the types of remuneration litigation in Beijing, adopting methods and yielding findings absent from the prior literature. Both the progress and challenges in China’s rule of Labour Law process are reflected in this work, together with public policy and theoretical implications for further study.

The paper aims to analyze some properties of GM(1,1,β) model based on the principle that the grey GM(1,1) model parameters are grey and adjustable.

At first, according to the principle that grey GM(1,1) model parameters are grey and adjustable, and the GM(1,1,β) model with parameter packet is put forward. Second, some properties of the GM(1,1,β) model are discussed, and the applicable region of the GM(1,1,β) model is given based on the grey differential equation of the GM(1,1,β) model. At last, the background value coefficient's calculation formula and optimization algorithm of the GM(1,1,β) model are also given. A numeric example is also computed in the last part of the paper.

The result of the study shows that the application scope of the GM(1,1,β) model is (−8,+8).

The GM(1,1,β) model provides the theoretical basis for the GM(1,1) model's optimization and can hence forecast its precision.

The paper succeeds in realizing the GM(1,1) model's application scope (−2,+2) is broadened to (−8,+8).