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More and more e-commerce web sites are using online customer reviews (OCRs) for customer segmentation. However, for durable products, customer purchases, and reviews only once for a long time, as while the product review score may highly affected by service factors or be “gently” evaluated. Existing regression or machine learning-based methods suffer from low accuracy when applied to the OCRs of durable products on e-commerce web sites. The purpose of this paper is to propose a new approach for customer segment analysis base on OCRs of durable products.

The research proposes a two-stage approach that employs latent class analysis (LCA): the feature-mention matrix construction stage and the LCA-based customer segmentation stage. The approach considers reviewers’ mention on product features, and the probability-based LCA method is adopted upon the characteristics of online reviews, to effectively cluster reviewers into specified segmentations.

The research finding is that, using feature-mention instead of feature-opinion records makes segment analysis more effective. The research also finds that, LCA method can better explain the characteristics of the OCR data of durable products for customer segmentation.

The research proposes a new approach to durable product review mining for customer segmentation analysis. The segment analysis result can provide supports for new product design and development, repositioning of existing products, marketing strategy development and product differentiation.

A new approach for customer segmentation analysis base on OCRs of durable products is proposed.

This qualitative study explores how Chinese senior outbound tourists perceive support from their adult children and what kinds of support they desire.

Qualitative data were collected from semi-structured interviews with 26 participants. Transcribed interviews were analysed via thematic analysis.

This study captured the contradictory feelings of different types of Chinese senior outbound tourists (i.e. independent, neutral, and dependent) according to the degree of desire for support from their adult children. The results further identified the real desires among Chinese senior outbound tourists for children's attitudinal support, caring support, appropriate financial support, companionship, and timing support.

Since this qualitative research is based on small samples with typical social and cultural characteristics, our research results only describe an existence. Our findings provide insight into the existence of the phenomenon, rather than allowing the results to be generalized to the wider population (Gram et al., 2019).

The tourism industry could develop products to alleviate such feelings. Integrating the concept of filial piety into adult children's support for their parents' overseas travel can not only meet parents' expectations but also relieve parents' ambivalence. Destination operators and travel agencies could thus design mixed products targeting Chinese elderly parents and their adult children by providing activities for both generations. Purchasing behaviour represents a type of emotional and instrumental support for the elderly. Destination operators and travel agencies can also launch products suitable for in-depth outbound travel that cater to adult children's leisure travel while meeting the elderly's travel needs.

This study also extends both intergenerational support theory and intergenerational ambivalence theory regarding Chinese senior outbound tourists.

The purpose of this study is to explore the potential of trainable activation functions to enhance the performance of deep neural networks, specifically ResNet architectures, in the task of image classification. By introducing activation functions that adapt during training, the authors aim to determine whether such flexibility can lead to improved learning outcomes and generalization capabilities compared to static activation functions like ReLU. This research seeks to provide insights into how dynamic nonlinearities might influence deep learning models' efficiency and accuracy in handling complex image data sets.

This research integrates three novel trainable activation functions – CosLU, DELU and ReLUN – into various ResNet-n architectures, where “n” denotes the number of convolutional layers. Using CIFAR-10 and CIFAR-100 data sets, the authors conducted a comparative study to assess the impact of these functions on image classification accuracy. The approach included modifying the traditional ResNet models by replacing their static activation functions with the trainable variants, allowing for dynamic adaptation during training. The performance was evaluated based on accuracy metrics and loss profiles across different network depths.

The findings indicate that trainable activation functions, particularly CosLU, can significantly enhance the performance of deep learning models, outperforming the traditional ReLU in deeper network configurations on the CIFAR-10 data set. CosLU showed the highest improvement in accuracy, whereas DELU and ReLUN offered varying levels of performance enhancements. These functions also demonstrated potential in reducing overfitting and improving model generalization across more complex data sets like CIFAR-100, suggesting that the adaptability of activation functions plays a crucial role in the training dynamics of deep neural networks.

This study contributes to the field of deep learning by introducing and evaluating the impact of three novel trainable activation functions within widely used ResNet architectures. Unlike previous works that primarily focused on static activation functions, this research demonstrates that incorporating trainable nonlinearities can lead to significant improvements in model performance and adaptability. The introduction of CosLU, DELU and ReLUN provides a new pathway for enhancing the flexibility and efficiency of neural networks, potentially setting a new standard for future deep learning applications in image classification and beyond.

This paper aims to automatically generate load shedding sequences due to insufficient power supply, to ensure flight safety and complete flight task.

In this paper, a power allocation and load management model, including logical and physical submodels of the distribution system, is first established according to different requirements of the loads in different flight phase and the current total power supply. Then, an optimal load management scheme based on an improved ant colony algorithm is proposed to automatically generate load shedding sequences for both safety-critical and nonsafety critical loads, to achieve a reliable and safe power supply.

To verify the efficiency and feasibility of the algorithm, the proposed method is verified in a virtual simulation platform. Simulation result illustrates that the proposed algorithm is efficient and feasible.

The proposed method can provide guidance on load power supply when the civil aircraft is under abnormal power supply situation.

An optimal load management scheme is proposed by considering different requirements of the loads in different flight phase and the current total power supply.

The self-assembled monolayers (SAMs) of inositol hexakisphosphoric (IP6) formed in NaCl solution at room temperature on the surface of Type 430 stainless steel (SS430) were studied. The paper aims to discuss these issues.

The corrosion inhibition behavior of the SAMs was examined by electrochemical polarization curves, and surface characterizations were studied by X-ray photoelectron spectroscopy.

The results showed that the IP6 molecules were adsorbed successfully on the SS430 surface and demonstrated the capability of corrosion inhibition. A maximum IE value of 71.81 percent was achieved due to co-adsorption of water. The SS430 electrodes exposed to media containing 5×10−3 mol/L of IP6 exhibited the best anti-corrosive performance.

The present paper will report for the first time the adsorption and corrosion inhibition performances of IP6 SAMs on the SS430.

The purpose of this paper is to construct a self-assembled double layer of organosilane on the surface of stainless steel and to investigate its corrosion inhibitive capability.

A monolayer of 3-glycidoxypropyltrimethoxysilane (GPTMS) was grafted onto an oxidized AISI 430SS (AISI 430 stainless steel) surface substrate from dry toluene solution. The hydrolysis of 1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDS) molecules was used to anchor a second organic layer from mixed water-ethanol solution. The adsorption behavior and corrosion inhibition properties of the monolayer and also the bilayer were investigated by potentiodynamic polarization, scanning electron microscope (SEM), Fourier transformed infrared spectroscopy (FTIR) and contact angle measurements.

The GPTMS/PFDS bilayer was successfully deposited onto the oxidized AISI 430SS surface. The optimal assembling time for the filming of the first GPTMS monolayer is 6 hours. Suitable values of pH and temperature of the PFDS self-assembly solution were pivotal to the successful deposition of the second layer. Compared to the GPTMS monolayer, the GPTMS/PFDS bilayer exhibited a significant enhancement of the corrosion inhibition performance of AISI 430SS in NaCl solution.

The contact angle value measured on the bilayer-modified surface was somewhat lower than the reported value of a complete fluorinated surface. However, further optimization of the assembling condition is needed to obtain more orderly and denser films.

This paper provides useful information regarding the preparation of an organosilane bilayer on the surface of stainless steel and its corrosion inhibition properties in NaCl solution. It illustrates potential application prospects of GPTMS/PFDS bilayers for surface treatment of stainless steel.

The purpose of this paper is to determine the corrosion fatigue behavior and mechanism of 6005A aluminum alloy and welded joint.

Electron back-scattered diffraction (EBSD) were adopted to characterize the microstructure of 6005A aluminum alloy and welded joint. Through potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and corrosion fatigue experiments, the corrosion fatigue behavior and mechanism of 6005A aluminum alloy base metal and welded joint were studied.

The results show that the corrosion fatigue crack initiation of 6005A aluminum alloy base metal and welded joint is mainly caused by the preferential anodic dissolution and hydrogen concentration in the areas with inclusions and welding defects.

The research is an originality study on the corrosion fatigue behavior and mechanism of 6005A aluminum alloy and welded joint.

This paper aims to examine the effect of consumer inertia – a tendency to adhere to prior purchase decisions despite the existence of preferable alternatives – on the relationships between switching costs and customer retention, and explain the controversy within them in the context of budget hotels.

An empirical test was conducted via structural equation modelling based on 337 self-administered questionnaires from customers at six of Chinese popular budget hotels.

Consumer inertia was a significant mediator between switching costs and customer retention. Specifically, consumer inertia completely mediated the effects of financial switching costs on customer retention, but partially did between procedural switching costs and customer retention. By introducing consumer inertia, the explanatory power of customer retention improved significantly by 19%.

This paper clarifies the effects of multiple dimensions of switching costs on customer retention via the mediating role of consumer inertia and partly addresses the inconsistency in the prior studies from an inertia perspective.

This study aims to understand the epistemic foundation of the classification applied in the first Chinese library catalogue, the Seven Epitomes (Qilue).

Originating from a theoretical stance that situates knowledge organization in its social context, the study applies a multifaceted framework pertaining to five categories of textual data: the Seven Epitomes; biographical information about the classificationist Liu Xin; and the relevant intellectual, political, and technological history.

The study discovers seven principles contributing to the epistemic foundation of the catalogue's classification: the Han imperial library collection imposed as the literary warrant; government functions considered for structuring texts; classicist morality determining the main classificatory structure; knowledge perceived and organized as a unity; objects, rather than subjects, of concern affecting categories at the main class level; correlative thinking connecting all text categories to a supreme knowledge embodied by the Six Classics; and classicist moral values resulting in both vertical and horizontal hierarchies among categories as well as texts.

A major limitation of the study is its focus on the main classes, with limited attention to subclasses. Future research can extend the analysis to examine subclasses of the same scheme. Findings from these studies may lead to a comparison between the epistemic approach in the target classification and the analytic one common in today's bibliographic classification.

The study is the first to examine in depth the epistemic foundation of traditional Chinese bibliographic classification, anchoring the classification in its appropriate social and historical context.

With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the social climate of China.

This study examines 97 severe corruption cases of high-ranking officials in China, which occurred between 2012 and 2015. As this insinuates that both institutional and social corruption are major problems in China, the analysis delves into multiple facts of corruption, including different types, four primary underlying causes, and suggestions regarding the implementation of three significant governmental shifts that focus on investigation, prevention tactics and legal regulations.

China’s corruption is not only individual-based but also it has developed into institutional corruption and social corruption. Besides human nature and instinct, the causes of corruption can be organised into four categories, namely, social customs, social transitions, institutional designs and institutional operations. For the removed high-ranking officials, the formation of interest chains was an important underlying cause behind their corruption.

This study makes a significant contribution to the literature because this study provides a well-rounded approach to a complex issue by highlighting the significance of democracy and the rule of law as ways to regulate human behaviour to combat future corruption.