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This study aims to examine the problems encountered during the establishment of the Central Police Academy (CPA) under the Nationalist regime from 1936 to 1949. While the authoritarian party-state unified the police academies by forceful means, this catalyzed the cleavage between the schools of police studies and resulted in power struggles over police education, intellectual thought, collectivity and even the national reform of police administration. More than narrating the progress of power consolidation, this study attempts to identify the problems underlying the factional strife and to reveal the interwoven pattern of these power struggles, exploring the confusion regarding what the police is, a question that troubled Chinese policemen from the mainland to Taiwan.

This paper explains the emergence of the factional strife from the beginning of the preliminary growth of the Police Academies in Nanking and Chekiang. It widely makes use of the official archives from Japan Center for Asian Historical Records and Historica Academia to show the dynamic situation in police education and administration. Rather, the official publications of the Police Academies and their affiliated associations reveal the hidden political agenda behind a unified framework as the party-state claimed. Moreover, official gazettes, memorials and newspapers are also used to strengthen the core argument of this study.

This paper examines the impact of the factional strife between the police leaders Dai Li and Li Shizhen on the CPA from 1936 to 1949. It illustrates that the establishment of the CPA ostensibly unified the nationwide police force but triggered power struggles over the control of the police administration. More importantly, it also shows how the factions strove for larger shares of power under the supreme doctrines that Chiang Kai-shek and the party-state imposed.

The failure of police education to become powerful was a special case among other more typical institutions. The governors coercively merged the police academies and created robust conditions for growth under the shelter of state authority. The police force did not follow the same path of national monopoly as what recent studies found but drifted apart with its vested interests and incompatible beliefs. Hence, the greater the demand for centralized control by the state, the greater the tension of the factional strife.

The green innovation behavior of construction enterprises is the key to reducing the construction industry's carbon emissions and realizing the green transformation of the construction industry. The purpose of this study is to reveal the evolutionary mechanism of green innovation behavior in construction enterprises.

This study is based on resource-based theory, Porter's hypothesis and signaling theory. First, a measurement model of the green innovation behavior of construction enterprises was constructed from three aspects: environmental regulation, enterprise resources and public opinion through hierarchical analysis. Then, the state values of the measurement model of green innovation behavior of construction enterprises were calculated through the time series data from 2011–2018. Finally, the Markov chain model was used to predict the evolutionary trend of green innovation behavior of construction enterprises, and the accuracy of the prediction effect of the Markov chain model was verified using the time series data of 2019.

The Markov chain model of green innovation behavior of construction enterprises constructed in this study has high accuracy. This model finds that the transition of the growth state of green innovation behavior in China's construction industry is fluid and predicts the evolution trend of the innovation behavior of construction enterprises. In the future, the green innovation behavior of construction enterprises has a probability of 70.17% to be in a continuous growth state and 40.27% to be in a rapid growth state.

Based on the Markov chain model of green innovation behavior of construction enterprises, this study finds that the transition of the growth state of green innovation behavior of construction enterprises in China has the characteristics of liquidity. In addition, it reveals the development process of the green innovation behavior of construction enterprises from 2011–2018 and predicts the evolution trend of the green innovation behavior of construction enterprises.

The purpose of this paper is to develop a small data set forecasting method to improve the effectiveness when making managerial decisions.

In the grey modeling process, appropriate background values are one of the key factors in determining forecasting accuracy. In this paper, grey compensation terms are developed to make more appropriate background values to further improve the forecasting accuracy of grey models.

In the experiment, three real cases were used to validate the effectiveness of the proposed method. The experimental results show that the proposed method can improve the accuracy of grey predictions. The results further indicate that background values determined by the proposed compensation terms can improve the accuracy of grey model in the three cases.

Previous studies determine appropriate background values within the limitation of traditional grey modeling process, while this study makes new background values without the limitation. The experimental results would encourage researchers to develop more accuracy grey models without the limitation when determining background values.

Since robot’s structural stiffness is usually less than 1 N/µm, mode coupling chatter occurs frequently during robotic milling process, and chatter frequency is close to the natural frequency of the robot itself. Chatter not only affects the surface quality but also damages the robot and reduces the positioning accuracy. Therefore, it is necessary to predict chatter in robotic machining process.

A three-dimensional dynamic model for robot’s spatial milling plane is established, and a corresponding stability criterion is obtained. First, the cutting force in milling plane is transformed into the coordinate system of the robot principal stiffness direction based on homogeneous transformation matrix. Then the three-dimensional stability criterion under milling process can be obtained by using system stability analysis. Furthermore, the circle diagram of mode coupling chatter stability is drawn. Each feeding direction’s stability under the two processing forms, referred as spindle vertical milling and spindle horizontal milling, is analyzed.

The experimental results verify that the three-dimensional stability criterion can avoid chatter by selecting machining feed direction in stable area.

This paper established a three-dimensional dynamic model in robot’s spatial milling plane and proposed a three-dimensional stability criterion according to the Routh criterion. The work is also expected to be an efficient tool in the development of robotic milling technology.

This paper aims to design an algorithm which is used to deal with non-linear discrete systems with constraints under the lower computation burden. As a result, we solve the non-holonomic vehicle tracking problem with the lower computational load and the convergence performance.

A fusion event-triggered model predictive control version is developed in this paper. The authors designed a shrinking prediction strategy.

The fusion event-triggered model predictive control scheme combines the strong points of event triggered and self-triggered methods. As the practical state approaches the terminal set, the computational complexity of optimal control problem (OCP) decreases.

The proposed strategy has proven to stabilize the system and also guarantee a reproducible solution for the OCP. Also, it is proved to be effected by the performance of the simulation results.

This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

The purpose of this paper is to establish a new model for non‐equidistance sequence and research affine properties of the new model.

Generalized non‐equidistance GM(1,1) model is put forward based on generalized accumulated generating operation (AGO) theory, and particle swarm optimization is used to solve the parameters of the new model, then affine properties of the new model are researched based on matrix analysis.

The results are convincing: the simulation and prediction precisions of generalized non‐equidistance GM(1,1) model are raised greatly, and it is proved that the affine transformation sequence has the same simulative accuracy with the raw sequence for generalized non‐equidistance GM(1,1) model.

The method exposed in the paper can be used to model and predict for non‐equidistance sequence in the practical problem.

The paper succeeds in establishing a new non‐equidistance grey model and obtaining the affine properties of generalized non‐equidistance GM(1,1) model.

Digitalisation, big data and data analytics are hot topics for today's economic sectors. Given these trends, developing information technology capabilities of those who wish to join the public sector workforce has been emphasised in public administration teaching curricula. In this chapter, focusing on the public sector, we ask: What kind of data is published by governments and how can these data be used in teaching data analytics?

Against the backdrop of the growing importance of data analytics in public sector management curricula, this chapter uses the IMPACT cycle model to demonstrate how datasets from open government data portals can be used for teaching.

Several examples are shown to illustrate the different steps of the IMPACT cycle model. Concluding remarks include a reflection where potential caveats, dysfunctions and limits of data analytics are outlined.

The chapter explicitly focuses on ‘real world’ open government data published on open data portals. A holistic approach to data analytics ‘from start to finish’ is shown, including preparing datasets for the analysis and presenting results to line managers, whereas some of the previous work solely shows parts (e.g. testing the data).

The purpose of this paper is to provide a foundational reference and practical guidance for modelling small and poor data with incomplete information.

The definitions of four basic models of GM(1, 1), such as Even Grey Model (EGM), Original Difference Grey Model (ODGM), Even Difference Grey Model (EDGM) and Discrete Grey Model (DGM), are put forward. The properties and characteristics of different models are studied and their equivalence are proved. The suitable sequences of different models are studied by simulation and analysis with homogeneous exponential sequences, nonhomogeneous exponential increasing sequences and vibration sequences.

The main conclusions have been obtained as follows: first, the three discrete models of ODGM, EDGM and DGM are suitable for homogeneous exponential sequences or sequences which close to a homogeneous exponential sequence; and second the EGM are suitable for nonhomogeneous exponential increasing sequences and vibration sequences.

The outcome obtained in this paper can be consulted for model selection in the course of practical modelling.

This paper systematically defined the four basic forms of model GM(1, 1) and studied their properties and characteristics, especially their suitable sequences. Although significant progress has been made in this field, such a systematic study on these models and their suitable sequences is still missing as far as we know. It can provide reference and basis for people to choose the correct model in the actual modelling process.