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The density and pattern of urban parks, traffic conditions are the main factors affecting urban park accessibility. To clarify the influence of traffic mode and urban road network on urban park accessibility, we examine downtown area of Nanjing, China, and based on GIS network analysis, analyze urban park accessibility under different traffic modes in the current year (2017) and the Nanjing master planning target year (2030). The results shows: Using automobiles takes the shortest time to get to urban parks in 2017 and 2030 (if the problem of parking is ignored). Comparing the results of 2030 and 2017, by when the ground transportation network in the study area will be further improved, urban park accessibility was improved by a small margin under walking and automobile traffic modes, however, the density of rail traits increased fastest, urban park accessibility is improved most under this mode of transportation, rail transit route development becomes the dominant factor in improving park accessibility in downtown area of Nanjing. To a certain extent, this study reveals the leading factors of improving the accessibility of urban parks on the premise that the system of urban parks tends to be stable, and provides a reference for improving urban park accessibility.

This study aims to explore the effect of negotiating audit differences on auditors’ internal control deficiency (ICD) severity assessments, an ensuing, non-negotiated judgment, in an integrated audit.

The experiment manipulates the client’s concession timing strategy as either immediate or gradual, holding the outcome constant. A total of 34 auditors (primarily managers) resolve an audit difference with the client.

The client’s concession timing strategy during the negotiation of an audit difference spills over to affect auditors’ severity assessment of a related ICD. Auditors judged the ICD severity to be higher (lower) in the immediate (gradual) condition. Client retention risk inferences mediate this effect.

The effect on auditors’ ICD severity assessments may not ultimately affect the audit report. Participants did not control their negotiation strategy, allowing the client’s negotiation strategy and the outcome to be held constant; it is possible that interactive effects between the client and auditor’s strategy might affect the study’s implications.

Features of the auditor–client negotiation process may influence auditors’ downstream, post-negotiation judgments and may therefore help to explain empirical evidence and Public Company Accounting Oversight Board inspection findings that show auditors often fail to identify an internal control material weakness after identifying a financial statement misstatement.

This paper expands current negotiation research by exploring the impact of inferences made based on counterparty concession strategy for downstream, non-negotiated judgments and current integrated audit research by identifying client retention perceptions as a driving factor of lower ICD severity assessments.

The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

Considering the unique characteristics of equity crowdfunding platforms including the removal of stringent structural barriers (e.g. lack of co-location), high visibility and traceability of investor characteristics, large pool of available investors and simplified transaction process, the authors aim to examine how the two most prevalent mechanisms (i.e. homophily and repeated ties) unfold in this context by incorporating the contextual characteristics. The authors theorize an inverted U-shaped relationship between leader-backer similarity and the likelihood of co-investment in a syndicate on equity crowdfunding platforms. In addition, a leader–backer dyad is more likely to form new syndicates if the students have more prior co-investment ties.

The empirical study is based on data from the AngelList syndicate platform and a linear probability model (LPM) with fixed effects is adopted to estimate the syndicate formation.

The authors find that the similarity between a leader and a backer has an inverted U-shaped relationship with the leader and backer's likelihood of co-investment in a syndicate, which is different from the dominant homophily-based tie formation in venture capital (VC) syndicates and other digital platform contexts. Although equity crowdfunding platforms encourage the possibility of exploring new partners, investors are more likely to co-invest with others who have stronger prior ties.

This research theoretically contributes to the scant literature of equity crowdfunding syndicates by contextualizing two most prevalent mechanisms (i.e. homophily and repeated ties) driving tie formation in VC syndicates and digital platforms.

The purpose of this paper is to study the importance of image data in hotel selection-recommendation using different types of cognitive features and to explore whether there are reinforcing effects among these cognitive features.

This study represents user-generated images “cognitive” in a knowledge graph through multidimensional (shallow, middle and deep) analysis. This approach highlights the clustering of hotel destination imagery.

This study develops a novel hotel selection-recommendation model based on image sentiment and attribute representation within the construction of a knowledge graph. Furthermore, the experimental results show an enhanced effect between different types of cognitive features and hotel selection-recommendation.

This study enhances hotel recommendation accuracy and user satisfaction by incorporating cognitive and emotional image attributes into knowledge graphs using advanced machine learning and computer vision techniques.

This study advances the understanding of user-generated images’ impact on hotel selection, helping users make better decisions and enabling marketers to understand users’ preferences and trends.

This research is one of the first to propose a new method for exploring the cognitive dimensions of hotel image data. Furthermore, multi-dimensional cognitive features can effectively enhance the selection-recommendation process, and the authors have proposed a novel hotel selection-recommendation model.

Based on the theory of social networks, it is crucial to enhance information superiority through joint venture capital (VC). The purpose of this paper is to explore the impacts of different roles’ structural and relational embeddedness on the information superiority of joint VC alliances.

The authors design the multiple linear regression models to investigate the leader’s investment ratio from a network embeddedness perspective. Panel data analysis and robustness tests are adopted based on the data from Chinese VCs Database.

The results show that VC leaders enjoy information search advantages because of their better network positions, while their followers lack this superiority. Information sharing among investors and investees may enhance the influences of structural embeddedness on investors’ information search advantages. Joint VC’s scale and its number of leaders could also increase VC alliances’ information superiority.

This research provides a more holistic understanding of the formation of joint VC alliances’ information superiority from a social network perspective. Both VC managers and social planners can seek guidance from this study to implement better strategies and policies to promote information symmetry in the VC market.

The purpose of this paper is to introduce and analyze a dual-side-permanent-magnet Halbach array vernier (DSPMHV) machine and to propose methods for achieving high torque density.

Flux harmonics and torque characteristics are analyzed by using finite element analysis. First, a suitable pole-slot combination is selected by comparison. Second, field modulation processes of DSPMHV machine are analyzed to identify the reason for high torque density. And it is compared with dual-side-PM (DSPM) machine to analyze flux harmonic and verify the flux concentrating effect of the Halbach array.

The permanent magnet (PM) field of the DSPM machine is approximately equal to the superposition of stator-PM field and rotor-PM field, which is the reason for high torque density. And the Halbach array can reduce flux leakage and increase the amplitude of main flux harmonics, then further improves torque. Improvement of torque can be achieved by choosing right pole-slot combination, adopting DSPM machine structure, reducing flux leakage and adopting field modulation principle.

The DSPMHV machine with split-tooth is proposed in this paper by combining the Halbach array with DSPM structure. This paper analyzes the bidirectional field modulation process, the reason for high torque density of the DSPM machine is obtained. Comparison with the DSPM machine verifies the flux concentrating effect of Halbach array. To alleviate the magnetic saturation in part of stator teeth, this paper proposes an improved DSPMHV machine with shaped auxiliary magnet.

This paper aims to further develop stator permanent magnet (PM) type memory machines by providing generalized design guidelines for double-stator memory machines (DSMMs) with hybrid PMs. This paper discusses the design experience of DSMMs and presents a comparative study of radial magnetization (RM) and circumferential magnetization (CM) types.

It begins with an introduction to RM and CM operating principles and magnetization mechanisms. Then, a comparative study is conducted for one of the RM-DSMM rotor pole pairs, inner and outer stator clamping angles and low coercive force PMs thickness. Finally, the two machines’ finite element simulation performance is compared. The validity of the proposed machine structure is demonstrated.

In this paper, the double-stator structure is extended to parallel hybrid PM memory machines, and two novel DSMMs with RM and CM configurations are proposed. Two types of DSMMs have PMs and magnetizing windings on the inner stator and armature windings on the outer stator. The main difference between the two is the arrangement of PMs on the inner stator.

Conventional stator PM memory machines have geometrical space conflicts between the PM and armature windings. The proposed double-stator structure can alleviate these conflicts and increase the torque density accordingly. In addition, this paper contributes to comparing the arrangement of hybrid PMs for DSMMs.

This study aims to report the oxidation behaviors of the T91 ferritic/martensitic steel (T91 steel) and 304 austenitic stainless steel (304 steel) in supercritical water (SCW) at 600°C.

The microstructure, elemental distribution and phase structure of the oxidation layers derived from the corrosion of the T91 steel and 304 steel were analyzed by scanning electron microscopy, Oxford Instrument X-ray spectroscopy, electron scattered diffraction and transmission electron microscopy.

The oxidation layers on the T91 steel and 304 steel have duplex structure. The two steels all suffer internal oxidation, and the phase of the internal oxidation layers are indexed as Fe-Cr spinel, although their morphologies are different. The formation of a continuous Cr-rich layer is not detected because of the relatively low Cr content of the steels, which is attributed to the corrosion property.

The accelerated corrosion and corrosion mechanism of the T91 steel and 304 steel with low Cr occurring in SCW at 600°C was clarified.

The purpose of this paper is to provide a modified welding image feature extraction algorithm for rotating arc narrow gap metal active-gas welding (MAG) welding, which is significant for improving the accuracy and reliability of the welding process.

An infrared charge-coupled device (CCD) camera was utilized to obtain the welding image by passive vision. The left/right arc position was used as a triggering signal to capture the image when the arc is approaching left/right sidewall. Comparing with the conventional method, the authors’ sidewall detection method reduces the interference from arc; the median filter removes the welding spatter; and the size of the arc area was verified to reduce the reflection from welding pool. In addition, the frame loss was also considered in the authors’ method.

The modified welding image feature extraction method improves the accuracy and reliability of sidewall edge and arc position detection.

The algorithm can be applied to welding seam tracking and penetration control in rotating or swing arc narrow gap welding.

The modified welding image feature extraction method is robust to typical interference and, thus, can improve the accuracy and reliability of the detection of sidewall edge and arc position.