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This paper aims to address the challenges in hydroacoustic signal detection, signal distortion and target localization caused by baseline drift. The authors propose a combined algorithm that integrates short-time Fourier transform (STFT) detection, smoothness priors approach (SPA), attitude calibration and direction of arrival (DOA) estimation for micro-electro-mechanical system vector hydrophones.

Initially, STFT method screens target signals with baseline drift in low signal-to-noise ratio environments, facilitating easier subsequent processing. Next, SPA is applied to the screened target signal, effectively removing the baseline drift, and combined with filtering to improve the signal-to-noise ratio. Then, vector channel amplitudes are corrected using attitude correction with 2D compass data. Finally, the absolute target azimuth is estimated using the minimum variance distortion-free response beamformer.

Simulation and experimental results demonstrate that the SPA outperforms high-pass filtering in removing baseline drift and is comparable to the effectiveness of variational mode decomposition, with significantly shorter processing times, making it more suitable for real-time applications. The detection performance of the STFT method is superior to instantaneous correlation detection and sample entropy methods. The final DOA estimation achieves an accuracy within 2°, enabling precise target azimuth estimation.

To the best of the authors’ knowledge, this study is the first to apply SPA to baseline drift removal in hydroacoustic signals, significantly enhancing the efficiency and accuracy of signal processing. It demonstrates the method’s outstanding performance in the field of underwater signal processing. In addition, it confirms the reliability and feasibility of STFT for signal detection in the presence of baseline drift.

Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.

Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.

The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.

This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

Using typical structure of asphalt pavement in Harbin area of China, and the formula of generalized friction coefficient between base and surface layers of asphalt pavement in cold area is established.

Through structural characteristics analysis of asphalt pavement in cold area, the generalized formula of friction coefficient between base and surface layers of asphalt pavement in cold area is derived. The formula can quickly calculate the friction coefficient between layers of asphalt pavement.

Based on quantitative analysis to the contacting state between layers of asphalt pavement in cold area, the relationships between generalized friction coefficient and resilient modulus of asphalt mixtures, temperature shrinkage coefficient and temperature have been established.

The findings can enrich the description methods about the contacting state between layers of asphalt pavement, and have a certain theoretical and practical value. Through the application of the formula of generalized friction coefficient between layers, it can provide a technical basis for the asphalt pavement design, construction and maintenance in cold area.

This study aims to clarify the influence mechanism of polishing solution type on the glazing evolution of fixed abrasive pad under different interfacial pressure conditions.

The tribological experiments were carried out on the friction and wear machinery with W3-5 diamond fixed abrasive pad and quartz glass workpiece under three polishing solution types of five pressure conditions. The changes of surface morphology, porosity and hardness of fixed abrasive pad were detected by white light interferometer, optical microscope and shore hardness tester.

The results showed that the glazed phenomenon of fixed abrasive pad is occurred after a certain time, which is more obvious with the increasing of interfacial pressures. The polishing solution type has a significant effect on the glazing time, although the glazed phenomenon is inevitable. The mechanism of it is that the micro-convex peaks on the surface of the fixed abrasive pad are easily wear, and the pores are blocked by the accumulation of waste debris generated during the experiment process. Thus, a smooth and high-density hard layer is formed on the surface of the fixed abrasive pad which induces the decreasing of the friction coefficient and surface roughness value. For selected polishing solution types, the wear rate of micro-convex peaks is different due to the corrosion action difference with polishing pad surface.

The main contribution of this work is to provide a new investigating method for further understanding the glazing evolution mechanism of fixed abrasive pad.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0257/

Honey peaches are rich in a variety of vitamins and are well known in China as the queen of fruit. However, as highly climacteric fruit, peach is too easy to affect its economic value. In this paper, a new passive modified atmosphere packaging system was proposed to solve the lack of water vapour removal capacity – which is still the technical bottleneck of passive modified atmosphere packaging. This paper aims to address this issue.

Under the conditions of relative humidity 85−90% and temperature 28°C−38°C, the influence of new passive modified atmosphere packaging on the shelf life and quality of 70% ripe peaches was studied in the paper. The effect of the new passive modified atmosphere packaging (PMAP) on fruit appearance, colour, taste, flavour, soluble solids, Vitamin C and titratable acid was investigated.

Regardless of whether 1-Methylcyclopropene is added or not, the research results show that the new PMAP has a significant effect on extending the shelf life and maintaining the quality of peaches. Compared with the control group, the shelf life of peaches treated with modified atmosphere packaging and 1-Methylcyclopropene was prolonged by 7 and 11 days, increasing the retailer's revenue by 44 and 75%.

A new integrated structure, which is composed of two types of films with high oxygen and high water vapour permeability was designed for the retail of peaches at room temperature. The former was mainly responsible for regulating the concentration of O₂ and CO₂, while the latter was for removing water vapour and regulating the relative humidity in PMAP.

Behaviour in virtual learning environments (VLE), including travel, gaze, manipulate, gesture and conversation, offer considerable information about the user's implicit interest. The purpose of this study is to find an approach for user interest mining via behaviour analysis in a VLE.

According to research in psychology, any interaction in a VLE has implications for the user's implicit interest. In order to mine a user's implicit interest, an explicit interaction‐interest model needs to be established. This paper presents findings from the concept classification of behaviour in a VLE. Based on this classification, the paper proposes a hierarchical interaction model. In this model the relation between interaction and user interest can be described and used to improve system performance.

In the experimental prototype the authors found that user‐implicit interest could be mined via stages of web mining, i.e. capture the user's original gesture signal, data pre‐process, pattern discovery, interaction goal and interest mining. The mined user's interest information can be used to update the state of local interest, leading to a reduction in network traffic and promotion of better system performance.

This is an original study using behaviour analysis for interest mining in e‐learning. Research on interest mining in e‐learning focused on content mining or search engine and usage mining in web courses. The paper provides valuable clues regarding user interest mining in a VLE, in which the context is different from usual web courses. The research output can be implemented widely, including online learning, and especially in the VLE.

Over the last two decades, green supply chain management (GSCM) has enabled businesses to operate in an environmentally friendly manner. The present review examines 234 research articles and proposes a methodical literature review on GSCM, focusing on the aspects of sustainable development.

The work examines conceptual, analytical, empirical and non-empirical research articles, analyzing at all levels of the organization, such as firm, dyad, supply chain and network. The objective of the review is to provide insights into the state and scope of existing research in the domain of GSCM, to identify the prevalence of GSCM and to consolidate the trend of future research. The literature review follows a systematic methodology for analyzing the literature.

The findings can support researchers in identifying research areas with significant impact and streamline research on GSCM in the future. Practitioners can utilize this structured classification to strategize their green initiatives in their firms.

The work contributes to providing literature that explores a detailed review in GSCM. The proposed literature review captures critical aspects in the domain of GSCM and offers future research directions.

Defining and measuring competitiveness has been a major focus in the business and competition literature over the past decades. The paper aims to use data-driven principal component analysis (PCA) to measure firm competitiveness.

A “3Ps” (performance, potential, and process) firm competitiveness indicator system is structured for indicator selection. Data-driven PCA is proposed to measure competitiveness by reducing the dimensionality of indicators and assigning weights according to the endogenous structure of a dataset. To illustrate and validate the method, a case study applying to Chinese international construction companies (CICCs) was conducted.

In the case study, 4 principal components were derived from 11 indicators through PCA. The principal components were labeled as “performance” and “capability” under the two respective super-components of “profitability” and “solvency” of a company. Weights of 11 indicators were then generated and competitiveness of CICCs was finally calculated by composite indexes.

This study offers a systematic indicator framework for firm competitiveness. The study also provides an alternative approach to better solve the problem of firm competitiveness measurement that has long plagued researchers.

The data-driven PCA approach alleviates the difficulties of dimensionality and subjectivity in measuring firm competitiveness and offers an alternative choice for companies and researchers to evaluate business success in future studies.

Despite the abundant renewable energy potential in the Nigeria, the power-sector stakeholder has not paid attention to the prospect of the natural resources that can be accrued when it is properly harnessed. Although a very negligible fraction of the population has invested in solar photovoltaics (PVs) for home solution, the initiative was only made public commercialised under the public-private partnership (PPP) and the objectives of the Power Sector Reform Act. 2005. It is, therefore, aimed to investigate the causes and insight of the barriers that are responsible for the slow implementation of the solar energy initiative in the Nigeria.

An empirical study was performed in the Nigeria. The study was conducted qualitatively, through semi-structured face-to-face interviews of 25 participants. The interviews were recorded, transcribed, interpreted, coded, categorised into themes and analysed by content analysis.

The study reveals technological, financial, political and social barriers have been the reason for slowing down solar energy development in Nigeria. While the technical barrier is a challenge to the solar energy implementation, socio-cultural issues have also been an obstacle to the implementation process. It is suggested that, the stakeholders of the initiative endeavour to proffer sustainable policies to enable public and private promoters to be able to generate and distribute electricity through solar PV and to complement the inadequate conventional electricity sources from the grids.

The paper provides a richer insight into the understanding and awareness of barriers for implementing solar energy strategies in Nigeria.