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Sensor arrays and pattern recognition-based electronic nose (E-nose) is a typical detection and recognition instrument for indoor air quality (IAQ). The E-nose is able to monitor several pollutants in the air by mimicking the human olfactory system. Formaldehyde concentration prediction is one of the major functionalities of the E-nose, and three typical machine learning (ML) algorithms are most frequently used, including back propagation (BP) neural network, radial basis function (RBF) neural network and support vector regression (SVR).

This paper comparatively evaluates and analyzes those three ML algorithms under controllable environment, which is built on a marketable sensor arrays E-nose platform. Variable temperature (T), relative humidity (RH) and pollutant concentrations (C) conditions were measured during experiments to support the investigation.

Regression models have been built using the above-mentioned three typical algorithms, and in-depth analysis demonstrates that the model of the BP neural network results in a better prediction performance than others.

Finally, the empirical results prove that ML algorithms, combined with low-cost sensors, can make high-precision contaminant concentration detection indoor.

The purpose of this study is to identify the dynamic parameters of journal bearings in asymmetric rotor systems without additional test runs or excitations.

An asymmetric rotor-bearing test rig was set up for the identification experiment. Comparations were made between the measured response of the asymmetric rotor and the symmetric rotor. The mathematical model of the asymmetric rotor is established by the finite element method. The identification algorithm is based on the model of the rotor and the measured vibration response to identify bearing parameters. The influence of modeling error and measurement noise on the identification results are numerically analyzed. The dynamic parameters of the journal bearings under different rotational speeds are identified and compared with the theoretical values calculated by the perturbation method.

The experiment results show that the vibration characteristics of the asymmetric rotor and the symmetric rotor are different. The numerical evaluation of the identification algorithm shows that the algorithm is accurate and has good robustness to modeling error and measurement noise. The identified dynamic parameters agree reasonably well with the parameters derived from the theoretical bearing model.

The proposed identification method uses the unique vibration characteristics of asymmetric rotors to identify the bearing dynamic parameters. As the method does not require excitations or additional test runs, it is suitable for the field test.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0096/

Asymmetric rotating machinery supported by oil film bearings is relatively common in practical applications. The purpose of this study is to propose a method for estimating the oil film parameters of the bearings in an asymmetric rotor-bearing system.

The proposed method requires the finite element model and translational displacement responses at the center of mass and bearings locations to form a regression equation to estimate the unknown parameters. Due to the transverse stiffness of the asymmetric rotor is not symmetrical, the analysis and parameter estimation procedures are performed in a rotating coordinate. Numerical simulations were carried out to illustrate the vibration characteristics of the asymmetric rotor system. The proposed method is applied to the simulated responses to estimate the assumed oil film parameters. The influence of the estimated parameter deviations on the rotor dynamic characteristics is discussed.

The vibration characteristics of asymmetric rotors are different from those of symmetrical rotors. The bearing parameters estimated by the proposed method are close to the assumed values, within a maximum error of 9%. The deviations of the estimated parameters have little effect on the vibration characteristic of the rotor system.

The proposed method does not require changing the rotational speed or applying additional excitation force to the rotor, which is suitable for the field test.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2023-0111/

In response to food scares related to high levels of agro-chemical residues sometimes found on foods, consumers in China increasingly demand for organic foods. As little is known on consumer perceptions and attitudes toward organic food products, the purpose of this paper is to gain insight into the purchase of organic food products by consumers and to explore the main factors driving this process.

Mixed (quantitative and qualitative) market survey approaches were used to provide a potentially deeper insight into consumer’s perspective and could help get a better picture of the complex factors involved.

The main trigger for purchasing organic food products is that consumers expect them to be healthier and safer. The respondents who have bought organic food products tend to have a higher education level and disposable incomes, be families with children and be older than those who have not bought them. The main barriers to increasing the market share of organic food products are the consumers’ lack of knowledge, the relatively high price premium and the lack of availability of organic food products. Informing consumers about unique characteristics of organic production methods, the decline in the prices of and increasing the availability of organic food products to its customers might be a promising strategy to develop the market for organic food products.

This paper provides a unique insight into buying behavior and attitudes of organic consumers in China. The results of the research could provide information for the organic food industry to expand its market and improve its profitability and reliability.

The purpose of this study is to explore the seismic damage mechanism of the Dayemaling Bridge during the Maduo earthquake and discuss the seismic damage characteristics of the high-pier curved girder bridge.

In this study, the numerical simulation method is used to analyze the seismic response using synthetic near-field ground motion records.

The near-field ground motion of the Maduo earthquake has an obvious directional effect, it is more likely to cause bridge seismic damage. Considering the longitudinal slope of the bridge and adopting the continuous girder bridge form, the beam end displacement of the curved bridge can be effectively reduced, and the collision force of the block and the bending moment of the pier bottom are reduced, so the curved bridge with longitudinal slope is adopted.

Combined with the seismic damage phenomenon of bridges in real earthquakes, the seismic damage mechanism and vulnerability characteristics of high-pier curved girder bridges are discussed by the numerical simulation method, which provides technical support for the application of such bridges in high seismic intensity areas.

This study aims to explore the perceptions about Chinese brands from the point of views of young Chinese consumers.

A qualitative method is used including focus groups and in-depth personal interviews with young Chinese consumers who are currently living and working in Australia.

Two key findings emerge from the results, namely, young Chinese consumers attach symbolic values to Chinese brands and Chinese brands are perceived positively by young Chinese consumers.

This study demonstrates that symbolic values (such as pride, lifestyle, feeling of home and being happy) constitute one of the primary motivations for young Chinese consumers’ purchase of domestic brands. The results of this study challenge the traditional view that Chinese brands are perceived negatively in the Chinese market.

This is one of the very few studies investigating how young Chinese consumers perceive brands from their home country rather than foreign brands.

The purpose of this paper is to establish a combined model for selecting key indexes of complex equipment, and then improve the cost forecasting precision of the model. The problem how to choose the key elements of complex products has always been concerned on many fields, such as cost assessment, investment decision making, etc.

Using Grey System Theory to establish a cost estimation model of complicated equipment is more reasonable under the few data and poor information. Therefore, this paper constructs cost index’s system of complex equipment, and then quantitative and qualitative analysis methods are utilized to calculate the grey entropy between the characteristic parameter and the behavior parameters. Further, establish the grey relational clustering matrix of the behavior sequences by using the grey relative incidence analysis. Finally, the authors select key indicators according to the grey degree.

The experiment demonstrates that the cost key parameters of complex equipment can be successfully screened out by the proposed approach, and the cost estimation accuracy of complicated products is improved.

The method proposed in this paper could be utilized to solve some practical problems, particularly the selection of cost critical parameters for complex products with few samples and poor information. Taking the cost key indexes of civil aircraft as an example, the results verified the validity of the GICM model.

In this paper, the authors develop the method of GICM model. Taking the data of civil aircraft as an example, the authors screen the key indicators of complex products successfully, and improve the prediction accuracy of the GM (1, N) model by using the selected parameters, which provides a reference for some firms.

The present paper aims to synthesize SrAl2O4:Eu2⁺, Dy3⁺ green-emitting phosphor nano-pigment powder using a combination of citrate – gel processing and microwave-assisted heating route.

Microwave-assisted citrate – gel processing of SrAl2O4:Eu2⁺, Dy3⁺ green-emitting phosphor nano-pigment powder has been carried out by varying the pH and the molar ratio of H3Cit/Al3⁺ + Sr2⁺ +Eu2⁺⁺Dy3⁺ (f/o). X-ray diffraction analysis showed that the produced powders were nearly pure SrAl2O4 phase, in which the SrAl2O4 host phase has the maximum fraction of green-emitting monoclinic SrAl2O4 phase.

Spectrophotometer results revealed that two excitation peaks appeared at 238 and 339 nm and an emission peak at 515 nm. The crystallite size of the green-emitting phosphor nano-pigment powder was about 37 nm as determined by Scherrer’s formula. The best conditions for formation of monoclinic SrAl2O4 phase with high purity were achieved at pH of precursor solution equal to 7 and the molar ratio of f/o equal to 3.

The present research work for the first time (to the best of the authors’ knowledge) has used microwave and sol–gel combination techniques to produce green-emitting phosphor nano-pigment powder (without using any other heating system).

The purpose of this study is to restore the spatial distribution of overseas remittance businesses in Shantou during the 1940s. It explores various socioeconomic factors that influenced the concentration of local remittance business investment in real estate. By reconstructing the spatial distribution of remittance business activities in Shantou, this study hopes to lay a foundation for further analysis of the business strategies of Chaoshan merchants.

This research draws on information from the published Swatow Guide, archival sources and cadastral maps to identify the location of remittance enterprises and the native place and overseas networks of property owners.

This study reveals that the spatial distribution of the remittance enterprises was determined by the native place origins of local property owners, and that the inflow of overseas Chinese capital contributed to real estate development in Shantou.

Despite the limited access to Chinese official archives, this paper manages to identify several building blocks and neighbors in Shantou for spatial analysis.

This study is the first attempt to use the geographical information system (GIS) method in Chinese urban history research and hopes to establish a larger historical database of Shantou as a sample for comparison.

This investigation advances the spatial study of urban history and overseas Chinese remittances in the maritime society of South China.

This systematic review, following preferred reporting items for systematic reviews and meta-analysis guidelines, rigorously investigates the emergent role of virtual reality (VR) technology in human movement training. The purpose of this study is to explore the effectiveness and evolution of VR in enhancing movement training experiences.

Acknowledging its pivotal role in diverse applications, such as sports and rehabilitation, human movement training is currently experiencing accelerated evolution, facilitated by the proliferation of wearable devices and mobile applications. This review conducted an exhaustive search across five different electronic databases, such as Web of Science, PubMed and ProQuest, resulting in the selection of 69 eligible articles published within the past five years. It also integrates 40 studies into a narrative summary, categorized based on the level of immersion offered by respective VR systems.

Enhanced immersion in VR potentially augments the effectiveness of movement training by engendering more realistic and captivating experiences for users. The immersive and interactive environments provided by VR technology enable tailored training experiences accompanied by precise, objective feedback. This review highlights the benefits of VR in human movement training and its potential to revolutionize the way training is conducted.

This systematic review contributes significantly to the existing literature by providing a comprehensive examination of the efficacy and evolution of VR in human movement training. By organizing the findings based on the level of immersion offered by VR systems, it provides valuable insights into the importance of immersion in enhancing training outcomes. In addition, this study identifies the need for future research focusing on the impacts of VR on learning and performance, as well as strategies to optimize its effectiveness and improve accessibility.