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Statistics show that selecting the best investment program based on both cost and effectiveness can avoid financial losses. However, investment evaluation of a power transformer is full of uncertainty as it is hard to obtain accurate and useful cost-effectiveness results. Therefore, the purpose of the paper is to establish an investment evaluation model.

The cost-effectiveness evaluation model in this study used grey correlation analysis for the power transformer selection based on life cycle cost (LCC). Indices of cost and effectiveness factors were chosen to form a three-level index system including quantitative and qualitative factors. Evidential reasoning was applied to quantify the qualitative indexes. Grey correlation analysis was applied to select the best investment program.

The results from this study show that the proposed approach is effective and offers a new approach to evaluating transformer investment.

The model was applied to an investing decision-making problem of the transformer in a new substation in Wuhan, China.

It is very important to select the best transformer program in the candidate investment programs because the investment program decides almost 70 percent of the LCC of the power transformer.

Many cities implement freight traffic restriction policy (FTRP) intending to reduce traffic congestion and air pollution. At the same time, city distribution had some negative effects. The purpose of this paper is therefore to study the freight group behavior under FTRP, and to provide some recommendations for the government.

This paper establishes a city distribution system model built by a simulation method of Agent, which includes the complex adaptability of freight individual, event of restriction policy, the influence factor of freight group behavior and its changes from the perspective of restriction policy. The rules of microscopic freight group behavior to macroscopic freight group behavior, the effects on freight group behavior exerted by restriction policy and the dynamic mechanism of freight group behavior are all studied. The model is also simulated with the traffic data of Beijing in China.

Theoretical results ensure that restriction of the passport is not the sole reason that may produce illegal trucks, and other measures need to be taken to solve the traffic problems. And in the long run, increasing fines has a greater effect than strengthening supervision frequency on illegal trucks reduction.

From city distribution perspective, this paper studied freight group behavior under FTRP. This paper also applied the Agent modeling method to build a model of urban distribution system in the FTRP.

To solve problems of low intelligence and poor robustness of traditional navigation systems, the purpose of this paper is to propose a brain-inspired localization method of the unmanned aerial vehicle (UAV).

First, the yaw angle of the UAV is obtained by modeling head direction cells with one-dimension continuous attractor neural network (1 D-CANN) and then inputs into 3D grid cells. After that, the motion information of the UAV is encoded as the firing of 3 D grid cells using 3 D-CANN. Finally, the current position of the UAV can be decoded from the neuron firing through the period-adic method.

Simulation results suggest that continuous yaw and position information can be generated from the conjunctive model of head direction cells and grid cells.

The proposed period-adic cell decoding method can provide a UAV with the 3 D position, which is more intelligent and robust than traditional navigation methods.

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.

Studies of the antecedents of daily abusive supervision have mainly focused on work stressors and family stressors, ignoring the potential importance of commuting stressors that are encountered enroute to work. Based in affective events theory, the authors propose a daily, within-person model to examine how the commuting stressors faced by supervisors affect their propensity to engage in abusive supervision behavior and the mechanisms underlying this effect.

Using experience-sampling methodology, the authors collected data from 49 supervisors in China who responded to two daily surveys for 10 working days.

The authors found that daily morning commuting anger mediates the link between daily morning commuting stressors and subsequent abusive supervision. The authors also found that trait-displaced aggression moderates this relationship, such that the mediating effect occurs only when supervisors' trait-displaced aggression is high rather than low.

This study enriches the antecedents of daily abusive supervision and extends the commuting literature to the leadership context.

The practice of management having control over auditor appointment and compensation is believed to be a fundamental cause for the lack of auditor independence. While researchers propose alternative auditor appointment procedures to improve auditor independence, there are a few settings that allow researchers to examine alternative auditor appointment procedures such as regulator designation of auditors. This research aims to investigate the effects of regulator designation of auditors and litigation risk on auditor independence in a Chinese setting

This study adopts a 2 × 2 between-subjects experimental design. A total of 110 surveys were sent out and 81 were collected from eastern China.

The results of an experiment with 81 Chinese auditors indicate that regulator designation of auditors improves auditor independence. In particular, auditors designated by the regulator feel less pressure from the audited company, perceive themselves to be more independent and are more willing to challenge the audited company’s aggressive financial reporting compared with those directly hired by the company. In addition, litigation risk moderates the effect of regulator designation of auditors on auditor independence such that regulator designation of auditors has a stronger impact on auditor independence when the litigation risk is low.

This study is also subject to limitations. First, regulator designation of auditors in China was examined. While regulator designation of auditors seems to improve auditor independence in the Chinese context, it is unclear if the same results will be observed in other economies, as China is a unique setting. For example, the majority of listed companies in China are under the control of government-related agencies. Consequently, the government has significant power in influencing auditor appointment policy. In contrast, the majority of other economies are more market-oriented with less government influence. Future studies in other markets will further enrich the understanding on regulator designation of auditors. Second, only regulator designation of auditors for state-owned enterprises was examined. It is unclear how regulator designation of auditors would affect non-state-owned enterprises. Moreover, future research could investigate the designation of auditors in other forms such as the designation of auditors by investors. Third, auditor appointment procedure may affect perceived risk of loss of client which in turn influences auditor independence. Future research could further investigate the mechanism through which regulator designation of auditors affect auditor independence.

Results of an experiment with 81 Chinese auditors show that regulator designation of auditors can improve auditor independence. In a decision context where auditors must provide judgments relating to a proposed audit adjustment that is quantitatively material and will affect the client’s ability to meet debt covenants, auditors designated by the State-Owned Assets Management Bureaus are more resistant to management pressure and are less willing to accept the management’s aggressive financial reporting practice than those directly hired by the company.

The purpose of this study is to present the results of an experiment that examines the effects of client management’s increased disclosure of related party transactions (RPTs) on auditors’ judgments of financial reports that contain RPTs.

This study used a 2 × 2 between-subjects experiment to investigate auditors’ judgments in response to questionable RPTs in a Chinese context.

The results show that the auditor participants assessed a lower likelihood that the client’s financial statements were intentionally misstated and that they were less likely to request additional evidence when the client management chose to disclose more, as opposed to less, detailed RPT information in their disclosure. Moreover, there was a significant interaction between disclosure level and client incentive to manipulate earnings on the likelihood of the auditor requesting additional evidence.

This study should be of interest to regulatory agencies that have expressed concerns over auditing practices related to RPTs.

The findings from this study help to provide a more in-depth understanding of disclosure literature by investigating voluntary RPT disclosure and the moderation role of clients’ incentives to manipulate earnings.

The number of cultural centres in South China shows an increasing trend. However, there is still a lack of research of this public building type and its related design strategy. This paper aims to identify general characteristics and presents design principles of cultural centres and thus enriches the theory of compact design strategies.

In total, 66 cases of cultural centres in South China have been investigated. The design patterns of these cultural centres projects are analysed by Statistical Product and Service Solutions (SPSS). The theory of compact design strategies is thus used to emphasize the systemic characteristics of cultural centres.

Cultural centres mostly have an overall floor area between 20,000-40,000 square metres (m²). Much cultural centres consist of three to four functional components. Different functional blocks are intensively organized in parallel or in series along a horizontal or vertical direction. The combination of multiple functions is divided into four usual composition types. The most common type is the “synthetical integration”. There are a total of four different distribution modes of integrated layout. Each of these modes can express different narrative themes according its needs, and four kinds of narrative themes are summarized.

Appropriate compact design strategies may be applied to improve the quality of public buildings in a region with the problem of land use limitation. Applications of results of this paper may enhance design efficiency or lead to more appropriate works.

Compact design strategies can be a guide for appropriate architectural design. The findings of this research provide regular design patterns for designers and engineers to streamline their design process.

Using the industrial data between 2000 and 2016, this study analysed the process of coupling and coordinated development of technological innovation and standardisation. Accordingly, the study considered the high-tech industry (five sub-sectors) in China as the research object.

Based on the summary of innovation and standardisation literature review, this study constructed a theoretical model of the influence of technological innovation and standardisation on industrial development from the perspective of the coupling system. Furthermore, the study employed multivariate linear regression analysis to explore coupling coordination relationships.

The study results revealed that high coupling coordination between technological innovation and standardisation is highly conducive to industrial development. Moreover, requirements for standardisation levels differ owing to different stages and characteristics in each segmented industry.

This study primarily contributes to the literature by using a bibliometrics tool to summarise related literature on innovation and standardisation and provides a new perspective of reviewing, and it also offers new evidence on the coupling coordination relationship between innovation and standardisation in the high-tech industry.

This paper proposes a recommendation method that mines the semantic relationship between resources and combine it with collaborative filtering (CF) algorithm for crowdsourcing knowledge-sharing communities.

First, structured tag trees are constructed based on tag co-occurrence to overcome the tags' lack of semantic structure. Then, the semantic similarity between tags is determined based on tag co-occurrence and the tag-tree structure, and the semantic similarity between resources is calculated based on the semantic similarity of the tags. Finally, the user-resource evaluation matrix is filled based on the resource semantic similarity, and the user-based CF is used to predict the user's evaluation of the resources.

Folksonomy is a knowledge classification method that is suitable for crowdsourcing knowledge-sharing communities. The semantic similarity between resources can be obtained according to the tags in the folksonomy system, which can be used to alleviate the data sparsity and cold-start problems of CF. Experimental results show that compared with other algorithms, the algorithm in this paper performs better in mean absolute error (MAE) and F1, which indicates that the proposed algorithm yields better performance.

The proposed folksonomy-based CF method can help users in crowdsourcing knowledge-sharing communities to better find the resources they need.