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AI is an emerging tool in HRM practices that has drawn increasing attention from HRM researchers and HRM practitioners. While there is little doubt that AI-enabled HRM exerts positive effects, it also triggers negative influences. Gaining a better understanding of the dark side of AI-enabled HRM holds great significance for managerial implementation and for enriching related theoretical research.

In this study, the authors conducted a systematic review of the published literature in the field of AI-enabled HRM. The systematic literature review enabled the authors to critically analyze, synthesize and profile existing research on the covered topics using transparent and easily reproducible procedures.

In this study, the authors used AI algorithmic features (comprehensiveness, instantaneity and opacity) as the main focus to elaborate on the negative effects of AI-enabled HRM. Drawing from inconsistent literature, the authors distinguished between two concepts of AI algorithmic comprehensiveness: comprehensive analysis and comprehensive data collection. The authors also differentiated instantaneity into instantaneous intervention and instantaneous interaction. Opacity was also delineated: hard-to-understand and hard-to-observe. For each algorithmic feature, this study connected organizational behavior theory to AI-enabled HRM research and elaborated on the potential theoretical mechanism of AI-enabled HRM's negative effects on employees.

Building upon the identified secondary dimensions of AI algorithmic features, the authors elaborate on the potential theoretical mechanism behind the negative effects of AI-enabled HRM on employees. This elaboration establishes a robust theoretical foundation for advancing research in AI-enable HRM. Furthermore, the authors discuss future research directions.

This paper aimed a fractional-order sliding mode-based lateral lane-change control method that was proposed to improve the path-tracking accuracy of vehicle lateral motion.

In this paper the vehicle presighting and kinematic models were established, and a new sliding mode control isokinetic convergence law was devised based on the fractional order calculus to make the front wheel turning angle approach the desired value quickly. On this basis, a fractional gradient descent algorithm was proposed to adjust the radial basis function (RBF) neuron parameter update rules to improve the compensation speed of the neural network.

The simulation results revealed that, compared to the traditional sliding mode control strategy, the designed controller eliminated the jitter of the sliding mode control, sped up the response of the controller, reduced the overshoot of the system parameters and facilitated accurate and fast tracking of the desired path when the vehicle changed lanes at low speeds.

This paper combines the idea of fractional order calculus with gradient descent algorithm, proposed a fractional-order gradient descent method applied to RBF neural network and fast adjustment the position and width of neurons.

The aim of this study is to present a novel approach based on semantic fingerprinting and a clustering algorithm called density-based spatial clustering of applications with noise (DBSCAN), which can be used to convert investor records into 128-bit semantic fingerprints. Inventor disambiguation is a method used to discover a unique set of underlying inventors and map a set of patents to their corresponding inventors. Resolving the ambiguities between inventors is necessary to improve the quality of the patent database and to ensure accurate entity-level analysis. Most existing methods are based on machine learning and, while they often show good performance, this comes at the cost of time, computational power and storage space.

Using DBSCAN, the meta and textual data in inventor records are converted into 128-bit semantic fingerprints. However, rather than using a string comparison or cosine similarity to calculate the distance between pair-wise fingerprint records, a binary number comparison function was used in DBSCAN. DBSCAN then clusters the inventor records based on this distance to disambiguate inventor names.

Experiments conducted on the PatentsView campaign database of the United States Patent and Trademark Office show that this method disambiguates inventor names with recall greater than 99 per cent in less time and with substantially smaller storage requirement.

A better semantic fingerprint algorithm and a better distance function may improve precision. Setting of different clustering parameters for each block or other clustering algorithms will be considered to improve the accuracy of the disambiguation results even further.

Compared with the existing methods, the proposed method does not rely on feature selection and complex feature comparison computation. Most importantly, running time and storage requirements are drastically reduced.

Asphalt mixture is widely used in road engineering, and its performance research is particularly important. But the study of asphalt mixture performance needs a lot of tests, such as bending test, splitting test and so on. It also needs a lot of time and material resources. The purpose of this paper is to obtain test results through finite element numerical simulation, and show that this saves a lot of manpower and material resources.

The mechanical parameters of the material are obtained through uniaxial compression tests. The true stress and plastic strain are calculated according to nominal stress and nominal strain. A constitutive model is established. Then a finite element model of asphalt mixture is established. The numerical simulation and performance study of asphalt mixture bending test is carried out. At the same time, according to the above method, the asphalt mixture is subjected to freeze-thaw cycles and ultraviolet aging, and the mechanical parameters are obtained by a uniaxial compression test. A numerical model is established to simulate the bending characteristics of asphalt mixture after freeze-thaw cycles and ultraviolet aging.

A uniaxial compression test of the asphalt mixture is conducted to obtain nominal stress and nominal strain. The true stress and plastic strain are calculated and the elastic modulus is established with Poisson’s ratio as the elastic part, and the true stress and plastic strain as the plastic part. The model is constructed, the finite element model is established and the bending test is numerically simulated. The verified trend is consistent, and the method is feasible. According to the above method, the concrete is subjected to freeze-thaw cycle and ultraviolet aging, and the finite element model is established by using uniaxial compression test to obtain parameters. The bending test is simulated and the verification method is feasible. With the increase of the number of freeze-thaw cycles and the increase of UV aging time, the maximum bending strain of SBS modified asphalt mixture and matrix asphalt mixture is decreased .The low-temperature performance of SBS modified asphalt mixture is better than that of matrix asphalt mixture.

A method of simulating asphalt mixture test by finite element method numerical simulation is established. By using this method, the performance of asphalt mixture is studied, which saves a lot of manpower and material resources. At the same time, this method can be used to study the characteristics of asphalt mixture under complex conditions.

The purpose of this paper is to propose a method for hand measurement based on image and marker watershed algorithm, and combine the data to analyze the shape and characteristics of the hand.

A portable hand image capturing instrument was designed and manufactured, and the hand images and dimensions of 328 young men in Zhejiang area were obtained. The outer contour curve of the hand and the key points of finger root, fingertip, wrist and knuckle position were extracted. Then, the size of each hand part was calculated. The hand data obtained from the two-dimensional image was compared with the manual measurement data. Finally, the hands were classified according to the measurement data, and the relationship between hand control size and hand length, hand width and the relationship between hand length and height were explored.

The data comparison results show that the two measurement methods have high data consistency and are replaceable. In addition, analyzing the data obtained four major characteristic factors that affect the shape of the hand, divided the hands of young men in Zhejiang into five categories, and obtained the regression equations of basic hand size, hand length and hand width, and obtained the regression equation of hand length and height.

The method proposed in this study to obtain hand size based on the image and mark watershed algorithm has lower requirements on the external environment and testers, conforms to the development trend of applying artificial intelligence to anthropometric engineering and provides a useful reference value for data collection of gloves specification design. In addition, the results of data analysis can provide a valuable reference basis for consumer hand shape predictions, which can be used to guide the research and production of hand instruments, the design of specifications series and the purchase of hand products.

This paper examines diverging views on the Chongqing model, the policy experiment led by Bo Xilai from 2007 to 2012 that was famous for its “red songs” and the campaign against organized crime. It has impressed both the supporters of socialist identity of China and the supporters of liberal identity and led to an intense debate concerning China’s path of development. This paper attempts to discuss and clarify to what extent the Chongqing model represented a genuine socialist experiment and the implications of the model for China’s future.

The chapter aims to evaluate the efficacy of stakeholder participation in the solid waste management system of Mauritius in view of providing a possible mechanism to attain the goals of a sustainable waste management framework.

The study employs qualitative indicators, namely, User Inclusivity and Producer Inclusivity of the Wasteaware Benchmark Indicators. Secondary data are used to conduct a critical and comprehensive analysis of the sub-indicators falling under each of the two main indicators to determine the overall compliance level with respect to stakeholder engagement of the waste management sector of Mauritius.

The results of the study show a LOW/MEDIUM compliance level for both User Inclusivity and Provider Inclusivity indicators, which indicates that improvement is required in the stakeholder engagement mechanism in Mauritius. The main weaknesses identified comprise of lack of an adequate legal framework with clear definition of waste types with regards to segregation, especially for non-hazardous wastes, low efficiency of sustainable waste management awareness campaigns and lack of inclusion of the informal sector. The main strengths identified consist of a proper bidding mechanism in place and a good level of equity in the provision of waste management services with respect to comingled waste collection. Suggested improvement areas include a revamping of the existing legal framework related to waste management to cater for higher inclusivity of all stakeholders together with including sustainable waste management topics in the formal education curriculum.

The User Inclusivity and Producer Inclusivity indicators were previously applied only to cities to measure the level of stakeholder participation, but this study has demonstrated that these indicators can also be adopted on a nation-wide level to evaluate stakeholder engagement. The use of these indicators together with secondary data presents a less time-consuming method to assess stakeholder participation in the waste sector, which can be particularly useful for Small Island Developing States.

Drawing on the socially embedded model of thriving at work, this study aims to test a moderated mediation model to elucidate the mediating effect of work meaningfulness and the moderating role of perceived interpersonal justice on the relationship between servant leadership and thriving at work.

Based on a sample of 221 employees from the manufacturing industry in South Korea, a series of hierarchical regression analyses were conducted by using statistical package for the social sciences (SPSS) software. For conducting moderated mediation analysis, the PROCESS macro for SPSS was utilized.

The findings show that servant leadership significantly relates to thriving at work, and work meaningfulness and perceived interpersonal justice act as a mediating mechanism and a boundary condition, respectively. Based on moderated mediation analysis, the collective effect of servant leadership, work meaningfulness and perceived interpersonal justice on thriving at work were also confirmed.

The findings suggest that organizations should adopt servant leadership to promote employee thriving at work. In doing so, it is important to ensure that employees experience work meaningfulness, and are treated with respect and dignity.

This study extends research on servant leadership, and sheds light on important mechanisms and boundary conditions under which servant leadership promotes thriving at work.