Since smartphones became ubiquitous, online grocery and food purchases through take-away delivery platforms have steadily increased in China. Nevertheless, whether the development…
Abstract
Purpose
Since smartphones became ubiquitous, online grocery and food purchases through take-away delivery platforms have steadily increased in China. Nevertheless, whether the development of take-away delivery can ameliorate urban–rural wage inequality still requires further analysis. The purpose of this paper is to clarify whether this positive effect exists.
Design/methodology/approach
This paper makes estimations based on city and individual levels combining the Chinese Household Income Project (CHIP) 2008, CHIP 2013, CHIP2018 survey data and the take-away delivery site data. At the city level, the Oaxaca-Blinder (O-B) decomposition method is employed to construct wage inequality index of urban and rural labors. At the individual level, this paper analyzes urban–rural wage differentials with high or low formal education level.
Findings
The rapid establishment of take-away delivery sites has resulted in an increase of 52.425 yuan on average in the annual wage of rural labors with low formal education level. When the cumulative number of sites increases by 1 unit, the annual wage inequality index decreases by 0.007 on average. Labors with the characteristics of rural household registration and low education can enjoy more dividends. Through inter-/within-industry decomposition, this paper elaborates formal education, age and cross-industry transfer as the main factors for the improvement of urban–rural wage inequality. Narrowing effect of wage differences between different groups in multiple sample slices also contributes to the mechanism analyses.
Originality/value
To the best of the author’s knowledge, this paper is the first to analyze the impact of take-away delivery development on the urban–rural wage inequality from the perspective of the establishment of take-away delivery sites. This empirical study will enrich the existing theoretical perspectives on urban–rural divide under the emergence of new forms of employment. The results indicate that new forms of employment represented by take-away delivery can not only promote economic growth, but also eliminate urban–rural inequality.
Details
Keywords
Shangjie Feng, Buqing Cao, Ziming Xie, Zhongxiang Fu, Zhenlian Peng and Guosheng Kang
With the continuous increase in Web services, efficient identification of Web services that meet developers’ needs and understanding their relationships remains a challenge…
Abstract
Purpose
With the continuous increase in Web services, efficient identification of Web services that meet developers’ needs and understanding their relationships remains a challenge. Previous research has improved recommendation effectiveness by using correlations between Web services through graph neural networks (GNNs), while it has not fully leveraged service descriptions, limiting the depth and diversity of learning. To this end, a Web services recommendation method called LLMSARec, based on Large Language Model and semantic alignment, is proposed. This study aims to extract potential semantic information from services and learn deeper relationships between services.
Design/methodology/approach
This method consists of two core modules: profile generation and maximizing mutual information. The profile generation module uses LLM to analyze the descriptions of services, infer and construct service profiles. Concurrently, it uses LLM as text encoders to encode inferred service profiles for enhanced service representation learning. The maximizing mutual information model aims to align the semantic features of the services text inferred by LLM with structural semantic features of the services captured by GNNs, thus achieving a more comprehensive representation of services. The aligned representation serves as an input for the model to identify services with superior matching accuracy, thereby enhancing the service recommendation capability.
Findings
Experimental comparisons and analyses were conducted on the Programmable Web platform data set, and the results demonstrated that the effectiveness of Web service recommendations can be significantly improved by using LLMSARec.
Originality/value
In this study, the authors propose a Web service recommendation approach based on Large Language Model and semantic alignment. By extracting latent semantic information from services and effectively aligning semantic features with structural features, new representations can be generated to significantly enhance recommendation accuracy.
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Ziming Zhou, Fengnian Zhao and David Hung
Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine…
Abstract
Purpose
Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.
Design/methodology/approach
To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.
Findings
The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.
Originality/value
The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.
Details
Keywords
Ziming Zeng, Shouqiang Sun, Tingting Li, Jie Yin and Yueyan Shen
The purpose of this paper is to build a mobile visual search service system for the protection of Dunhuang cultural heritage in the smart library. A novel mobile visual search…
Abstract
Purpose
The purpose of this paper is to build a mobile visual search service system for the protection of Dunhuang cultural heritage in the smart library. A novel mobile visual search model for Dunhuang murals is proposed to help users acquire rich knowledge and services conveniently.
Design/methodology/approach
First, local and global features of images are extracted, and the visual dictionary is generated by the k-means clustering. Second, the mobile visual search model based on the bag-of-words (BOW) and multiple semantic associations is constructed. Third, the mobile visual search service system of the smart library is designed in the cloud environment. Furthermore, Dunhuang mural images are collected to verify this model.
Findings
The findings reveal that the BOW_SIFT_HSV_MSA model has better search performance for Dunhuang mural images when the scale-invariant feature transform (SIFT) and the hue, saturation and value (HSV) are used to extract local and global features of the images. Compared with different methods, this model is the most effective way to search images with the semantic association in the topic, time and space dimensions.
Research limitations/implications
Dunhuang mural image set is a part of the vast resources stored in the smart library, and the fine-grained semantic labels could be applied to meet diverse search needs.
Originality/value
The mobile visual search service system is constructed to provide users with Dunhuang cultural services in the smart library. A novel mobile visual search model based on BOW and multiple semantic associations is proposed. This study can also provide references for the protection and utilization of other cultural heritages.
Details
Keywords
Yu Liu and Ziming Zeng
Previous research mainly uses graph neural networks on syntactic dependency graphs, often neglecting emotional cues in sarcasm detection and failing to integrate image features…
Abstract
Purpose
Previous research mainly uses graph neural networks on syntactic dependency graphs, often neglecting emotional cues in sarcasm detection and failing to integrate image features for multimodal information effectively. To address these limitations, this study proposes a novel multimodal sarcasm detection model based on the directed graph isomorphism network with sentiment enhancement and multimodal fusion (DGIN-SE-MF).
Design/methodology/approach
The approach extracts image and text features through vision transformer and BERT, respectively. To deeply integrate the extracted features, the author develops a text-guided multi-head attention fusion mechanism module. Subsequently, a directed graph is constructed through SE and the multimodal factorized bilinear pooling method to integrate image features into the graph. The DGIN then fuses the image and text features, using a weighted attention mechanism to generate the final representation.
Findings
The model is validated on three datasets: English, Chinese and an Indonesian–English dataset. The results demonstrate that the proposed model consistently outperforms other baseline models, particularly on the Chinese and English sarcasm datasets, achieving F1 scores of 88.75 % and 83.10 %, respectively.
Originality/value
The proposed model addresses the inadequacies of previous methods by effectively integrating emotional cues and image features into sarcasm detection. To the best of the authors’ knowledge, this is the first work to leverage a DGIN-SE-MF for this task, leading to significant improvements in detection performance across different languages.
Details
Keywords
Junyi Chen, Buqing Cao, Zhenlian Peng, Ziming Xie, Shanpeng Liu and Qian Peng
With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application…
Abstract
Purpose
With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.
Design/methodology/approach
In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.
Findings
Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.
Originality/value
In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.
Details
Keywords
Qingqing Li, Ziming Zeng, Shouqiang Sun, Chen Cheng and Yingqi Zeng
The paper aims to construct a spatiotemporal situational awareness framework to sense the evolutionary situation of public opinion in social media, thus assisting relevant…
Abstract
Purpose
The paper aims to construct a spatiotemporal situational awareness framework to sense the evolutionary situation of public opinion in social media, thus assisting relevant departments in formulating public opinion control measures for specific time and space contexts.
Design/methodology/approach
The spatiotemporal situational awareness framework comprises situational element extraction, situational understanding and situational projection. In situational element extraction, the data on the COVID-19 vaccine, including spatiotemporal tags and text contents, is extracted. In situational understanding, the bidirectional encoder representation from transformers – latent dirichlet allocation (BERT-LDA) and bidirectional encoder representation from transformers – bidirectional long short-term memory (BERT-BiLSTM) are used to discover the topics and emotional labels hidden in opinion texts. In situational projection, the situational evolution characteristics and patterns of online public opinion are uncovered from the perspective of time and space through multiple visualisation techniques.
Findings
From the temporal perspective, the evolution of online public opinion is closely related to the developmental dynamics of offline events. In comparison, public views and attitudes are more complex and diversified during the outbreak and diffusion periods. From the spatial perspective, the netizens in hotspot areas with higher discussion volume are more rational and prefer to track the whole process of event development, while the ones in coldspot areas with less discussion volume pay more attention to the expression of personal emotions. From the perspective of intertwined spatiotemporal, there are differences in the focus of attention and emotional state of netizens in different regions and time stages, caused by the specific situations they are in.
Originality/value
The situational awareness framework can shed light on the dynamic evolution of online public opinion from a multidimensional perspective, including temporal, spatial and spatiotemporal perspectives. It enables decision-makers to grasp the psychology and behavioural patterns of the public in different regions and time stages and provide targeted public opinion guidance measures and offline event governance strategies.
Details
Keywords
Ziming Zeng, Shouqiang Sun, Jingjing Sun, Jie Yin and Yueyan Shen
Dunhuang murals are rich in cultural and artistic value. The purpose of this paper is to construct a novel mobile visual search (MVS) framework for Dunhuang murals, enabling users…
Abstract
Purpose
Dunhuang murals are rich in cultural and artistic value. The purpose of this paper is to construct a novel mobile visual search (MVS) framework for Dunhuang murals, enabling users to efficiently search for similar, relevant and diversified images.
Design/methodology/approach
The convolutional neural network (CNN) model is fine-tuned in the data set of Dunhuang murals. Image features are extracted through the fine-tuned CNN model, and the similarities between different candidate images and the query image are calculated by the dot product. Then, the candidate images are sorted by similarity, and semantic labels are extracted from the most similar image. Ontology semantic distance (OSD) is proposed to match relevant images using semantic labels. Furthermore, the improved DivScore is introduced to diversify search results.
Findings
The results illustrate that the fine-tuned ResNet152 is the best choice to search for similar images at the visual feature level, and OSD is the effective method to search for the relevant images at the semantic level. After re-ranking based on DivScore, the diversification of search results is improved.
Originality/value
This study collects and builds the Dunhuang mural data set and proposes an effective MVS framework for Dunhuang murals to protect and inherit Dunhuang cultural heritage. Similar, relevant and diversified Dunhuang murals are searched to meet different demands.
Details
Keywords
Juan Wu, Ziming Kou and Gongjun Cui
The purpose of this paper is to prepare carbon fiber-reinforced polyimide matrix composites and to investigate the single role of carbon fiber in polyimide composites on…
Abstract
Purpose
The purpose of this paper is to prepare carbon fiber-reinforced polyimide matrix composites and to investigate the single role of carbon fiber in polyimide composites on tribological performance under distilled water condition.
Design/methodology/approach
Three carbon fiber-reinforced polyimide matrix composites were fabricated by using a hot press molding technique. The tribological behaviors of carbon fiber-reinforced polyimide matrix composites sliding against steel ball were evaluated with a ball-on-disk tribotester under distilled water condition. Meanwhile, the effect of different length of carbon fiber on the wear resistance of polyimide matrix composites was investigated during the sliding process.
Findings
The friction coefficients and specific wear rates of polyimide composites containing 100 μm carbon fibers were lower than those of other specimens. The wear mechanism of carbon fiber-reinforced composites was delamination under distilled water condition. The interfacial combination between the carbon fiber and matrix became worse with the increase of length of carbon fiber.
Originality/value
This paper reported the effect of the different length of carbon fiber on polyimide matrix composites to prepare mechanical parts in mining industrial fields.
Details
Keywords
Evangelos Bellos, Ilias Daniil and Christos Tzivanidis
The purpose of this paper is to investigate a cylindrical flow insert for a parabolic trough solar collector. Centrally placed and eccentric placed inserts are investigated in a…
Abstract
Purpose
The purpose of this paper is to investigate a cylindrical flow insert for a parabolic trough solar collector. Centrally placed and eccentric placed inserts are investigated in a systematic way to determine which configuration leads to the maximum thermal enhancement.
Design/methodology/approach
The analysis is performed in SolidWorks Flow Simulation with a validated computational fluid dynamics model. Moreover, the useful heat production and the pumping work demand increase are evaluated using the exergy and the overall efficiency criteria. The different scenarios are compared for inlet temperature of 600 K, flow rate of 100 L/min and Syltherm 800 as the working fluid. Moreover, the inlet temperature is examined from 450 to 650 K, and the diameter of the insert is investigated up to 50 mm.
Findings
According to the final results, the use of a cylindrical insert of 30 mm diameter is the most sustainable choice which leads to 0.56 per cent thermal efficiency enhancement. This insert was examined in various eccentric positions, and it is found that the optimum location is 10 mm over the initial position in the vertical direction. The thermal enhancement, in this case, is about 0.69 per cent. The pumping work demand was increased about three times with the insert of 30 mm, but the absolute values of this parameter are too low compared to the useful heat production. So, it is proved that the increase in the pumping work is not able to eliminate the useful heat production increase. Moreover, the thermal enhancement is found to be greater at higher temperature levels and can reach up to 1 per cent for an inlet temperature of r650 K.
Originality/value
The present work is a systematic investigation of the cylindrical flow insert in a parabolic trough collector. Different diameters of this insert, as well as different positions in two dimensions, are examined using a parametrization of angle-radius. To the authors’ knowledge, there is no other study in the literature that investigates the presented many cases systematically with the followed methodology on parabolic trough collectors. Moreover, the results of this work are evaluated with various criteria (thermal, exergy and overall efficiency), something which is not found in the literature.