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When solving the cogging torque of complex electromagnetic structures, such as consequent pole hybrid excitation synchronous (CPHES) machine, traditional methods have a huge computational complexity. The notable feature of CPHES machine is the symmetric range of field-strengthening and field-weakening, but this type of machine is destined to be equipped with a complex electromagnetic structure. The purpose of this paper is to propose a hybrid analysis method to quickly and accurately solve the cogging torque of complex 3D electromagnetic structure, which is applicable to CPHES machine with different magnetic pole shapings.

In this paper, a hybrid method for calculating the cogging torque of CPHES machine is proposed, which considers three commonly used pole shapings. Firstly, through magnetic field analysis, the complex 3D finite element analysis (FEA) is simplified to 2D field computing. Secondly, the discretization method is used to obtain the distribution of permeance and permeance differential along the circumference of the air-gap, taking into account the effect of slots. Finally, the cogging torque of the whole motor is obtained by using the idea of modular calculation and the symmetry of the rotor structure.

This method is applicable to different pole shapings. The experimental results show that the proposed method is consistent with 3D FEA and experimental measured results, and the average calculation time is reduced from 8 h to 4 min.

This paper proposes a new concept for calculating cogging torque, which is a hybrid calculation of dimension reduction and discretization modules. Based on magnetic field analysis, the 3D problem is simplified into a 2D issue, reducing computational complexity. Based on the symmetry of the machine structure, a modeling method for discretized analytical models is proposed to calculate the cogging torque of the machine.

Thin cracks on the surface, such as those found in nuclear power plant concrete structures, are difficult to identify because they tend to be thin. This paper aims to design a novel segmentation network, called U-shaped contextual aggregation network (UCAN), for better recognition of weak cracks.

UCAN uses dilated convolutional layers with exponentially changing dilation rates to extract additional contextual features of thin cracks while preserving resolution. Furthermore, this paper has developed a topology-based loss function, called ℓ_cl Dice, which enhances the crack segmentation’s connectivity.

This paper generated five data sets with varying crack widths to evaluate the performance of multiple algorithms. The results show that the UCAN network proposed in this study achieves the highest F1-Score on thinner cracks. Additionally, training the UCAN network with the ℓ_cl Dice improves the F1-Scores compared to using the cross-entropy function alone. These findings demonstrate the effectiveness of the UCAN network and the value of incorporating the ℓ_cl Dice in crack segmentation tasks.

In this paper, an exponentially dilated convolutional layer is constructed to replace the commonly used pooling layer to improve the model receptive field. To address the challenge of preserving fracture connectivity segmentation, this paper introduces ℓ_cl Dice. This design enables UCAN to extract more contextual features while maintaining resolution, thus improving the crack segmentation performance. The proposed method is evaluated using extensive experiments where the results demonstrate the effectiveness of the algorithm.

In response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.

An automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.

The docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.

The proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.

In modern China, sports and nationalism always have close connection, and nationalism is the important reason for the promotion of Chinese sports. However, the relationship between Chinese sports and nationalism in globalised China could be much more examined by academics, as well as its influencing factors. This chapter selects the Beijing 2008 Olympic Games as the context and representative three Chinese sports heroes in the period of globalisation to study. The findings show that in some extent, Beijing 2008 Olympic Games and three Chinese sports heroes represent the national image of China in the globalised world, also bearing the burden of washing away historical humiliation and pursuing national glory. Furthermore, it is manifested that China have a complex nationalism in the process of hosting the 2008 Olympic Games. Under the influence of mass media, market economy and sports professionalisation, nationalism still exists in Chinese sports, but people gradually start to reflect on the ‘Juguo Tizhi’, the traditional Chinese sports system and the concept of ‘winning glory for the nation’. The relationship between Chinese nationalism and sports shows the important implications of rapid Chinese sports development.

Field-effect transistor (FET) has excellent electronic properties and inherent signal amplification, and with the development of nanomaterials technology, FET biosensors with nanomaterials as channels play an important role in the field of heavy metal ion detection. This paper aims to review the research progress of silicon nanowire, graphene and carbon nanotube field-effect tube biosensors for heavy metal ion detection, so as to provide technical support and practical experience for the application and promotion of FET.

The article introduces the structure and principle of three kinds of FET with three kinds of nanomaterials, namely, silicon nanowires, graphene and carbon nanotubes, as the channels, and lists examples of the detection of common heavy metal ions by the three kinds of FET sensors in recent years. The article focuses on the advantages and disadvantages of the three sensors, puts forward measures to improve the performance of the FET and looks forward to its future development direction.

Compared with conventional instrumental analytical methods, FETs prepared using nanomaterials as channels have the advantages of fast response speed, high sensitivity and good selectivity, among which the diversified processing methods of graphene, the multi-heavy metal ions detection of silicon nanowires and the very low detection limit and wider detection range of carbon nanotubes have made them one of the most promising detection tools in the field of heavy metal ions detection. Of course, through in-depth analysis, this type of sensor has certain limitations, such as high cost and strict process requirements, which are yet to be solved.

This paper elaborates on the detection principle and classification of field-effect tube, investigates and researches the application status of three kinds of FET biosensors in the detection of common heavy metal ions. By comparing the advantages and disadvantages of each of the three sensors in practical applications, the paper focuses on the feasibility of improvement measures, looks forward to the development trend in the field of heavy metal detection and ultimately promotes the application of field-effect tube development technology to continue to progress, so that its performance continues to improve and the application field is constantly expanding.

The proliferation of big data analytics (BDA)-enabled tools and technologies has endowed organizations with the capacity to augment decision-making processes, optimize operational endeavors and foster innovation across diverse business domains. Consequently, BDA has been posited as a catalyst for enhanced customer relationship management, improved risk mitigation strategies and heightened operational efficiencies, all of which converge to augment overall firm performance. Thus, the purpose of this research is to introduce a conceptual framework aimed at explaining the influence of BDA capabilities on the performance of telecommunications firms in Pakistan. Additionally, it examines the potential mediating effect of talent capabilities and moderating effect of top management attitude on firm performance.

Data from a sample comprising 520 participants were collected via survey questionnaires. The study employed Partial Least Squares-Structural Equation Modeling to empirically evaluate the proposed model.

Results reveal a positive association between BDA technology and information capabilities with both BDA talent capabilities and firm performance. Furthermore, the analysis suggests that BDA talent capabilities mediate the relationship between BDA dynamic capabilities and firm performance, while top management attitude acts as a moderator, enhancing the relationship between BDA talent capabilities and firm performance.

There is a scarcity of research that has examined the relationship of BDA capabilities, top management attitude and firm performance. This study attempts to examine their interrelationships. First, it enhances the extant literature by elucidating the mediating role of BDA talent capabilities in the relationship between BDA technology and information capabilities and firm performance. Second, the study introduces a novel dimension by incorporating top management attitude as a moderator variable. This augmentation adds layers of complexity to comprehending BDA implementation dynamics, emphasizing leadership’s role in fostering an enabling environment for effective utilization of BDA capabilities.

The present study is performed to identify the propagation mechanism of the ripple effect as well as examine the simultaneous impact of risks on supply chain (SC) performance.

A theoretical framework with many hypotheses regarding the relationships between SC risk types and performance is established. The data are collected from a large-scale survey supported by a project of the Japanese government to promote sustainable socioeconomic development for the Association of Southeast Asian Nations (ASEAN) region, with the participation of 207 firms. Structural equation modeling (SEM) is used to test the hypotheses of the theoretical framework.

It is indicated that human-made risk causes operational risk, while natural risk causes both supply risk and operational risk. Furthermore, the impacts of human-made risk and natural risk on performance are amplified through operational risk.

This study is one of the first attempts that identifies the propagation mechanism of the ripple effect and examines the simultaneous impact of risks on performance in construction SCs.

Although many studies on risk management in construction SCs have been carried out, they mainly focus on risk identification or quantification of risk impact. It is observed that research on the ripple effect of disruptions has been very scarce.

This study aims to examine the relationship between corporate social responsibility (CSR) and job pursuit intention (JPI), and the role of job seekers’ perception on employer prosocial orientation, value congruence and employer attractiveness in this relationship. CSR is measured based on internal and external CSR.

By adopting quantitative approach, data was obtained through survey questionnaire from 420 bachelor’s degree university fresh graduates from five universities in Malaysia who are actively seeking for jobs. Data was analysed using structural equation modelling technique.

Research findings show that internal and external CSR positively impact job seekers’ perception of employer prosocial orientation. Job seekers’ perception towards employer prosocial orientation has a significant positive impact on value congruence. Value congruence has a significant positive influence on employer attractiveness. Finally, employer attractiveness has a significant positive impact on JPI.

The findings are useful for human resources management. Organisations (employers) should focus on effective internal and external CSR practices through a prosocial orientation approach to attract the best talents and create a strong position in the job market.

This study extends the Signalling Theory and P-O Fit theory by applying them to an entirely different context of CSR and JPI, by incorporated the holistic job seekers’ psychological processes of the recruitment signals (internal and external CSR), signalling process and person-organisation fit (perception on employer prosocial orientation, value congruence and employer attractiveness) thoroughly.

The study aims to determine the impact of sustainable manufacturing on environmental performance through government regulation and eco-innovation in Indonesian small and medium-sized enterprises (SMEs).

The results indicate sustainable manufacturing plays a significant role in SMEs' environmental performance and regulations, and eco-innovation can moderate it. It also reveals that government regulation has a positive and significant effect on environmental performance. Moreover, eco-innovation has a positive and significant effect on environmental performance.

The findings of this study indicate that SMEs can embrace sustainable manufacturing practices and achieve their long-term sustainability goals by adhering to regulations, collaborating with stakeholders and implementing eco-friendly innovations.

This research uncovers ground-breaking perspectives on the evolution of scientific knowledge about the impact of eco-innovation, regulatory measures and sustainable manufacturing practices on the environmental performance of SMEs.