bluuebunny/crossref_metadata_2025 huggingface dataset:
Monitoring Knee Contact Force with Force-Sensing Insoles
Authors: Spencer Alex , Samaan Michael , Noehren Brian
Published: May 2023

Numerous applications exist for monitoring knee contact force (KCF) throughout activities of daily living. However, the ability to estimate these forces is restricted to a laboratory setting. The purposes of this study are to develop KCF metric estimation models and explore the feasibility of monitoring KCF metrics via surrogate measures derived from force-sensing insole data. Nine healthy subjects (3F, age 27 ± 5 years, mass 74.8 ± 11.8 kg, height 1.7 ± 0.08 m) walked at multiple speeds (0.8–1.6 m/s) on an instrumented treadmill. Thirteen insole force features were calculated as potential predictors of peak KCF and KCF impulse per step, estimated with musculoskeletal modeling. The error was calculated with median symmetric accuracy. Pearson product-moment correlation coefficients defined the relationship between variables. Models develop per-limb demonstrated lower prediction error than those developed per-subject (KCF impulse: 2.2% vs 3.4%; peak KCF: 3.50% vs. 6.5%, respectively). Many insole features are moderately to strongly associated with peak KCF, but not KCF impulse across the group. We present methods to directly estimate and monitor changes in KCF using instrumented insoles. Our results carry promising implications for internal tissue loads monitoring outside of a laboratory with wearable sensors.
On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications
Authors: Rehman Abdul , Valentini Roberto , Cinque Elena , Di Marco Piergiuseppe , Santucci Fortunato
Published: May 2023

Developing radio access technologies that enable reliable and low-latency vehicular communications have become of the utmost importance with the rise of interest in autonomous vehicles. The Third Generation Partnership Project (3GPP) has developed Vehicle to Everything (V2X) specifications based on the 5G New Radio Air Interface (NR-V2X) to support connected and automated driving use cases, with strict requirements to fulfill the constantly evolving vehicular applications, communication, and service demands of connected vehicles, such as ultra-low latency and ultra-high reliability. This paper presents an analytical model for evaluating the performance of NR-V2X communications, with particular reference to the sensing-based semi-persistent scheduling operation defined in the NR-V2X Mode 2, in comparison with legacy sidelink V2X over LTE, specified as LTE-V2X Mode 4. We consider a vehicle platooning scenario and evaluate the impact of multiple access interference on the packet success probability, by varying the available resources, the number of interfering vehicles, and their relative positions. The average packet success probability is determined analytically for LTE-V2X and NR-V2X, taking into account the different physical layer specifications, and the Moment Matching Approximation (MMA) is used to approximate the statistics of the signal-to-interference-plus-noise ratio (SINR) under the assumption of a Nakagami-lognormal composite channel model. The analytical approximation is validated against extensive Matlab simulations that a show good accuracy. The results confirm a boost in performance with NR-V2X against LTE-V2X, particularly for high inter-vehicle distance and a large number of vehicles, providing a concise yet accurate modeling rationale for planning and adaptation of the configuration and parameter setup of vehicle platoons, without having to resort to extensive computer simulation or experimental measurements.
Design and Psychophysical Evaluation of a Novel Wearable Upper-Arm Tactile Display Device
Authors: Zhu Yongqing , Liu Peter Xiaoping , Gao Jinfeng
Published: May 2023

A novel wearable upper arm tactile display device, which can simultaneously provide three types of tactile stimuli (i.e., squeezing, stretching, and vibration) is presented. The squeezing and stretching stimulation of the skin is generated by two motors simultaneously driving the nylon belt in the opposite and the same direction, respectively. In addition, four evenly spaced vibration motors are fixed around the user’s arm by an elastic nylon band. There is also a unique structural design for assembling the control module and actuator, powered by two lithium batteries, making it portable and wearable. Psychophysical experiments are conducted to investigate the effect of interference on the perception of squeezing and stretching stimulation by this device. Results show that (1) different tactile stimuli actually interfere with the user’s perception compared to the case where only one stimulus is applied to the user; (2) the squeezing has a considerable impact on the stretch just noticeable difference (JND) values when both stimuli are exerted on the user, and when the squeezing is strong, while the impact of stretch on the squeezing JND values is negligible.
Target Recognition of Coal and Gangue Based on Improved YOLOv5s and Spectral Technology
Authors: Yan Pengcheng , Kan Xuyue , Zhang Heng , Zhang Xiaofei , Chen Fengxiang , Li Xinyue
Published: May 2023

Aiming at the problems of long detection time and low detection accuracy in the existing coal gangue recognition, this paper proposes a method to collect the multispectral images of coal gangue using spectral technology and match with the improved YOLOv5s (You Only Look Once Version-5s) neural network model to apply it to coal gangue target recognition and detection, which can effectively reduce the detection time and improve the detection accuracy and recognition effect of coal gangue. In order to take the coverage area, center point distance and aspect ratio into account at the same time, the improved YOLOv5s neural network replaces the original GIou Loss loss function with CIou Loss loss function. At the same time, DIou NMS replaces the original NMS, which can effectively detect overlapping targets and small targets. In the experiment, 490 sets of multispectral data were obtained through the multispectral data acquisition system. Using the random forest algorithm and the correlation analysis of bands, the spectral images of the sixth, twelfth and eighteenth bands from twenty-five bands were selected to form a pseudo RGB image. A total of 974 original sample images of coal and gangue were obtained. Through two image noise reduction methods, namely, Gaussian filtering algorithm and non-local average noise reduction, 1948 images of coal gangue were obtained after preprocessing the dataset. This was divided into a training set and test set according to an 8:2 ratio and trained in the original YOLOv5s neural network, improved YOLOv5s neural network and SSD neural network. By identifying and detecting the three neural network models obtained after training, the results can be obtained, the loss value of the improved YOLOv5s neural network model is smaller than the original YOLOv5s neural network and SSD neural network, the recall rate is closer to 1 than the original YOLOv5s neural network and SSD neural network, the detection time is the shortest, the recall rate is 100% and the average detection accuracy of coal and gangue is the highest. The average precision of the training set is increased to 0.995, which shows that the improved YOLOv5s neural network has a better effect on the detection and recognition of coal gangue. The detection accuracy of the improved YOLOv5s neural network model test set is increased from 0.73 to 0.98, and all overlapping targets can also be accurately detected without false detection or missed detection. At the same time, the size of the improved YOLOv5s neural network model after training is reduced by 0.8 MB, which is conducive to hardware transplantation.
Concurrent Validity and Test–Retest Reliability of Pressure-Detecting Insoles for Static and Dynamic Movements in Healthy Young Adults
Authors: Lambrich Johanna , Hagen Marco , Schwiertz Gerrit , Muehlbauer Thomas
Published: May 2023

Compared to force-plates, pressure-detecting insoles have the advantage that vertical ground reaction force (vGRF) can be estimated under field rather than laboratory conditions. However, the question arises whether insoles also provide valid and reliable results compared to a force-plate (i.e., the gold standard). The study aimed to investigate the concurrent validity and test–retest reliability of pressure-detecting insoles during static and dynamic movements. Twenty-two healthy young adults (12 females) performed standing, walking, running, and jumping movements while simultaneously collecting pressure (GP MobilData WiFi, GeBioM mbH, Münster, Germany) and force (Kistler®) data twice, 10 days apart. Concerning validity, ICC values showed excellent agreement (ICC > 0.75), irrespective of the test condition. Further, the insoles underestimated (mean bias: −4.41 to −37.15%) most of the vGRF variables. Concerning reliability, ICC values for nearly all test conditions also showed excellent agreement, and the SEM was rather low. Lastly, most of the MDC95% values were low (≤5%). The predominantly excellent ICC values for between-devices (i.e., concurrent validity) and between-visits (i.e., test–retest reliability) comparisons suggest that the tested pressure-detecting insoles can be used under field-based conditions for a valid and reliable estimation of relevant vGRF variables during standing, walking, running, and jumping.
A Novel Approach for Efficient Solar Panel Fault Classification Using Coupled UDenseNet
Authors: Pamungkas Radityo Fajar , Utama Ida Bagus Krishna Yoga , Jang Yeong Min
Published: May 2023

Photovoltaic (PV) systems have immense potential to generate clean energy, and their adoption has grown significantly in recent years. A PV fault is a condition of a PV module that is unable to produce optimal power due to environmental factors, such as shading, hot spots, cracks, and other defects. The occurrence of faults in PV systems can present safety risks, shorten system lifespans, and result in waste. Therefore, this paper discusses the importance of accurately classifying faults in PV systems to maintain optimal operating efficiency, thereby increasing the financial return. Previous studies in this area have largely relied on deep learning models, such as transfer learning, with high computational requirements, which are limited by their inability to handle complex image features and unbalanced datasets. The proposed lightweight coupled UdenseNet model shows significant improvements for PV fault classification compared to previous studies, achieving an accuracy of 99.39%, 96.65%, and 95.72% for 2-class, 11-class, and 12-class output, respectively, while also demonstrating greater efficiency in terms of parameter counts, which is particularly important for real-time analysis of large-scale solar farms. Furthermore, geometric transformation and generative adversarial networks (GAN) image augmentation techniques improved the model’s performance on unbalanced datasets.
Direction-of-Arrival Estimation Method Based on Neural Network with Temporal Structure for Underwater Acoustic Vector Sensor Array
Authors: Xie Yangyang , Wang Biao
Published: May 2023

Acoustic vector sensor (AVS) is a kind of sensor widely used in underwater detection. Traditional methods use the covariance matrix of the received signal to estimate the direction-of-arrival (DOA), which not only loses the timing structure of the signal but also has the problem of weak anti-noise ability. Therefore, this paper proposes two DOA estimation methods for underwater AVS arrays, one based on a long short-term memory network and attention mechanism (LSTM-ATT), and the other based on Transformer. These two methods can capture the contextual information of sequence signals and extract features with important semantic information. The simulation results show that the two proposed methods perform much better than the multiple signal classification (MUSIC) method, especially in the case of low signal-to-noise ratio (SNR), the DOA estimation accuracy has been greatly improved. The accuracy of the DOA estimation method based on Transformer is comparable to that of the DOA estimation method based on LSTM-ATT, but the computational efficiency is obviously better than that of the DOA estimation method based on LSTM-ATT. Therefore, the DOA estimation method based on Transformer proposed in this paper can provide a reference for fast and effective DOA estimation under low SNR.
Obstacle Detection Method Based on RSU and Vehicle Camera Fusion
Authors: Ding Shaohong , Xu Yi , Zhang Qian , Yu Jinxin , Sun Teng , Ni Juan , Shi Shuyue , Kong Xiangcun , Zhu Ruoyu , Wang Liming , Wang Pengwei
Published: May 2023

Road obstacle detection is an important component of intelligent assisted driving technology. Existing obstacle detection methods ignore the important direction of generalized obstacle detection. This paper proposes an obstacle detection method based on the fusion of roadside units and vehicle mounted cameras and illustrates the feasibility of a combined monocular camera inertial measurement unit (IMU) and roadside unit (RSU) detection method. A generalized obstacle detection method based on vision IMU is combined with a roadside unit obstacle detection method based on a background difference method to achieve generalized obstacle classification while reducing the spatial complexity of the detection area. In the generalized obstacle recognition stage, a VIDAR (Vision-IMU based identification and ranging) -based generalized obstacle recognition method is proposed. The problem of the low accuracy of obstacle information acquisition in the driving environment where generalized obstacles exist is solved. For generalized obstacles that cannot be detected by the roadside unit, VIDAR obstacle detection is performed on the target generalized obstacles through the vehicle terminal camera, and the detection result information is transmitted to the roadside device terminal through the UDP (User Data Protocol) protocol to achieve obstacle recognition and pseudo-obstacle removal, thereby reducing the error recognition rate of generalized obstacles. In this paper, pseudo-obstacles, obstacles with a certain height less than the maximum passing height of the vehicle, and obstacles with a height greater than the maximum passing height of the vehicle are defined as generalized obstacles. Pseudo-obstacles refer to non-height objects that appear to be “patches” on the imaging interface obtained by visual sensors and obstacles with a height less than the maximum passing height of the vehicle. VIDAR is a vision-IMU-based detection and ranging method. IMU is used to obtain the distance and pose of the camera movement, and through the inverse perspective transformation, it can calculate the height of the object in the image. The VIDAR-based obstacle detection method, the roadside unit-based obstacle detection method, YOLOv5 (You Only Look Once version 5), and the method proposed in this paper were applied to outdoor comparison experiments. The results show that the accuracy of the method is improved by 2.3%, 17.4%, and 1.8%, respectively, compared with the other four methods. Compared with the roadside unit obstacle detection method, the speed of obstacle detection is improved by 1.1%. The experimental results show that the method can expand the detection range of road vehicles based on the vehicle obstacle detection method and can quickly and effectively eliminate false obstacle information on the road.
Gearbox Fault Diagnosis Method Based on Multidomain Information Fusion
Authors: Xie Fengyun , Wang Gan , Shang Jiandong , Liu Hui , Xiao Qian , Xie Sanmao
Published: May 2023

Traditional methods of gearbox fault diagnosis rely heavily on manual experience. To address this problem, our study proposes a gearbox fault diagnosis method based on multidomain information fusion. An experimental platform consisting of a JZQ250 fixed-axis gearbox was built. An acceleration sensor was used to obtain the vibration signal of the gearbox. Singular value decomposition (SVD) was used to preprocess the signal in order to reduce noise, and the processed vibration signal was subjected to short-time Fourier transform to obtain a two-dimensional time–frequency map. A multidomain information fusion convolutional neural network (CNN) model was constructed. Channel 1 was a one-dimensional convolutional neural network (1DCNN) model that input a one-dimensional vibration signal, and channel 2 was a two-dimensional convolutional neural network (2DCNN) model that input short-time Fourier transform (STFT) time–frequency images. The feature vectors extracted using the two channels were then fused into feature vectors for input into the classification model. Finally, support vector machines (SVM) were used to identify and classify the fault types. The model training performance used multiple methods: training set, verification set, loss curve, accuracy curve and t-SNE visualization (t-SNE). Through experimental verification, the method proposed in this paper was compared with FFT-2DCNN, 1DCNN-SVM and 2DCNN-SVM in terms of gearbox fault recognition performance. The model proposed in this paper had the highest fault recognition accuracy (98.08%).
Alleviating the Bauxite Maritime Supply Chain Risks through Resilient Strategies: QFD-MCDM with Intuitionistic Fuzzy Decision Approach
Authors: Sun Jiachen , Wang Haiyan , Cui Zhimin
Published: May 2023

With the development of the global economy and energy supply chain, the uncertainty and complexity of the bauxite maritime supply chain (BMSC) has been further increased. Determining the crucial risks and improving the supply chain’s resilient capacity based on operation objectives has become important, in order to ensure the sustainability and competitiveness of the BMSC. This paper combines quality function deployment (QFD), a multi-criteria decision method (MCDM), and intuitionistic fuzzy set (IFS); an integrated methodology is developed to achieve efficient design of BMSC resilient strategies (RESs), taking into account both customer requirements (CRs) and risk factors (RFs). A combined weighting method is employed to determine each CR’s importance. A decision-making trial and evaluation laboratory (DEMATEL) method is adopted to determine the RFs’ interrelationships. The results obtained with the MCDM are incorporated into QFD to construct a two-stage house of quality (HoQ) model, which transforms CRs into RFs, and then into RESs. The real case of the Guinea–China bauxite import supply chain is studied to demonstrate the applicability and validity of the proposed framework. Research results reveal that the most important CR is ‘stability’. ‘Information sharing asymmetry’, ‘poor ship stability or obsolete equipment performance’, and ‘lack of coordination between shipping and ports’ are the most severe risks impacting the operation of supply chain. Furthermore, ‘constructing strategic alliances’ contributes to alleviating potential risks, optimizing the allocation of resources, and finally, improving the resilience of the BMSC significantly. This paper will help managers to understand how to achieve sustainable development of the supply chain through resilient strategies, and will aid rational decision-making in the management and operation of a resilient BMSC for alleviating risk.
Analysis and Verification of Load–Deformation Response for Rocking Self-Centering Bridge Piers
Authors: Wang Shijie , Sun Zhiguo , Wang Dongsheng
Published: May 2023

Rocking self-centering (RSC) bridge piers were proposed based on the bridge seismic resilience design theory, pushing the development of bridge sustainability. To develop a seismic design method for RSC bridge piers, a clear understanding of their behavior under earthquakes is essential. This study analyzed the whole lateral force–displacement response of RSC piers, taking into account both rotational and flexural deformation, which resulted in a clearer understanding of their behavior under seismic actions. In this study, the whole loading process was simplified into three statuses, and a calculation method was developed to determine the relationship between lateral force and displacement of both single-column and double-column RSC bridge piers. The accuracy of the proposed method was verified by comparing the calculated results with experimental data for six single-column and two double-column RSC bridge piers. The results show that the proposed calculation method predicts the initial stiffness, yield and peak loads, and yield and peak displacements well for RSC bridge piers. The method offers valuable insights into the seismic response of RSC bridge piers, which can serve as a reference for future research, promoting the safety and stability of these structures.
Study on Skywell Shape in Huizhou Traditional Architecture Based on Outdoor Wind Environment Simulation
Authors: Fang Huanhuan , Ji Xiang , Chu Yun , Nie Lufeng , Wang Jianyuan
Published: May 2023

This study was conducted in the context of the latest Chinese policy on “double carbon”. First, we obtained building skywell and meteorological data parameters through a site survey and measurements. We applied the PHOENICS software to simulate and analyze the wind environment of a traditional building skywell. Secondly, the outdoor wind environment of typical building skywells could be simulated and evaluated one by one. Finally, using the method of controlling the variables and by combining typical buildings and skywell-scale layouts, the study summarized and compared the wind environment of the skywell under different scale combinations from three aspects: building skywell shape, skywell scale ratio, and skywell door opening. The following conclusions were drawn: (1) Among the four skywell shapes, the wind environment inside of the skywell was best in the HUI shape. (2) The wind environment inside of the skywell was best in the simulated skywell width-to-height ratio D/H values of 0.2–0.6; the AO shape D/H value was equal to 0.3; and the best wind environment in the skywell occurred when the D/H value of the HUI shape was equal to 0.4. (3) The wind environment in the skywell was best in the range of 1–1.5 for the aspect ratio W/L in the HUI-shaped building skywell (when the width-to-height D/H ratio was 0.4). (4) The opening of the door of the residential building had a great impact on the wind environment of the skywell.
Evolution of Urban Ecosystem Service Value and a Scenario Analysis Based on Land Utilization Changes: A Case Study of Hangzhou, China
Authors: Wu Yizhou , Huang Zichun , Han Dan , Qiu Xiaoli , Pan Yaxin
Published: May 2023

Simulating the change in ecosystem service values (ESVs) caused by land use changes in metropolitan areas under multiple scenarios is of great significance to ensure regional ecological security and sustainable urban development. This study assessed the variations in land use and ESV in the main urban area of Hangzhou, China, from 2000 to 2020. A total of four future land use scenarios for 2030 were created using the cellular automata–Markov prediction model and ESVs were calculated for four future scenarios. The results are as follows: (1) Arable land and construction land were the most drastic types of land use changes in the main urban area of Hangzhou during the study period. From 2000 to 2020, construction land in the main urban area of Hangzhou expanded rapidly, with an increase of 46,916.82 hm2, while the cultivated land area decreased significantly by 38,396.43 hm2. (2) The ESV in the study area continuously declined from 2000 to 2020, with high-value ecosystem service areas predominantly found in forest areas and water areas. (3) The values of ecosystem services under the simulated future scenarios of natural development, rapid development, planned development, and ecological development were CNY 15.053, 14.525, 16.690, and 16.799 billion, respectively. The planned development and ecological development scenarios effectively ensure a high ESV. The results indicated that balancing various types of land use is essential to guarantee ecological security in urban development. Moreover, urban development and construction should be undertaken in areas with a low ESV. This forecasting study can serve as a key reference for policy makers regarding the urban landscape sustainability of Hangzhou City. The integrated simulation method of land use and ESV proposed in this study can shed light on the urban spatial layout and spatial regulation in urban land use planning.
Spatio-Temporal Assessment of Manganese Contamination in Relation to River Morphology: A Study of the Boac and Mogpog Rivers in Marinduque, Philippines
Authors: Monjardin Cris Edward F. , Power Christopher , Senoro Delia B.
Published: May 2023

This study investigates the contribution of river morphology towards the occurrence of manganese (Mn) in both sediment and surface water (SW), considering the temporal climatic and spatial conditions. The Boac and Mogpog rivers on the island province of Marinduque, Philippines, were examined in this study. These rivers are downstream of the two abandoned open mine pits at San Antonio and Tapian, where mining disasters occurred in 1993 and 1996, respectively. Field sampling programs were conducted in 2019, 2021 and 2022 to measure the Mn concentrations in sediment and SW, and the physicochemical parameters in SW during the same sampling event. Geographic Information System (GIS) tools were employed to characterize the morphology of each river, specifically river slope, river bends, sinuosity, and channel width and length. The Boac and Mogpog rivers were divided into 22 and 15 river segments, respectively, to account for spatial heterogeneity of all parameters. Correlation (r) analysis on the average Mn concentration and river morphology within each segment was performed and indicated that river bends (Boac r = 0.421, Mogpog r = 0.356) and sinuosity (Boac r = 0.403, Mogpog r = 0.352) had the highest correlation with Mn concentrations in sediment. While river slope (Boac r = 0.716, Mogpog r = 0.282) and sinuosity (Boac r = 0.505, Mogpog r = 0.257) were the highest for Mn in SW. This confirmed that the planform of the river affected the accumulation of Mn due to its effect on sediment deposition along the river and its potential to adsorb and/or desorb metals. Furthermore, the pH of SW also directly correlated with sediment Mn (r = 0.293), and inversely correlated with SW Mn (r = −0.465), which was expected as acidic water promotes the release of metals from sediments to SW. The results from this study will aid local government, environmental engineers and managers in their mitigation program through identification of the areas and segments in the river that contain the highest and the least contamination. This is to optimize financial and human resources during river system remediation and monitoring. Data and information extracted from this study are useful in other areas of similar condition.
A Traceability Framework to Enable Circularity in the Built Environment
Authors: Davari Saman , Jaberi Meisam , Yousfi Adam , Poirier Erik
Published: May 2023

The transition towards a Circular Economy (CE) has been receiving an increasing amount of attention in the built asset industry. One of the key aspects of CE is traceability, which can enable the identification and tracking of materials, products, and their associated value throughout their entire lifecycle. However, achieving traceability has been challenging in the built asset industry due to the complex nature of construction projects and a lack of awareness about the benefits of traceability in achieving the circularity of building products and materials. Despite recent studies and efforts, a limited number of frameworks or guidelines exist to support traceability in the built asset industry. In many cases, several of the existing traceability standards, strategies, and guidelines must be identified and framed to support development and implementation of theories and models applicable within the built asset domain. This paper proposes a traceability framework consisting of five key components covering: the main purposes of traceability enabling CE principles, the role of traceability across asset lifecycle stages, the type of data needed to support traceability, the value of collaboration and coordination among industry stakeholders, and key enablers and drivers of traceability from technological and organizational perspectives. The proposed framework developed in this paper contributes to the effort aimed at framing the knowledge domain of CE through the traceability of products and materials in the built environment.
COVID-19 Pandemic, Climate Change, and Conflicts on Agriculture: A Trio of Challenges to Global Food Security
Authors: Paudel Devendra , Neupane Ram Chandra , Sigdel Sailesh , Poudel Pradip , Khanal Aditya R.
Published: May 2023

Global food security is a worldwide concern. Food insecurity is a significant threat to poverty and hunger eradication goals. Agriculture is one of the focal points in the global policy agenda. Increases in agricultural productivity through the incorporation of technological advances or expansion of cultivable land areas have been pushed forward. However, production growth has slowed in many parts of the world due to various endemic challenges, such as decreased investment in agricultural research, lack of infrastructure in rural areas, and increasing water scarcity. Climate change adversities in agriculture and food security are increasing. Recently, the COVID-19 pandemic has severely affected global food supply chains. Economic and social instability from the pandemic contribute to long-term disturbances. Additionally, conflicts such as war directly affect agriculture by environmental degradation, violence, and breaches of national and international trade agreements. A combination of food security and climate change challenges along with increased conflicts among nations and post-COVID-19 social and economic issues bring bigger and more serious threats to agriculture. This necessitates the strategic design of policies through multifaceted fields regarding food systems. In this comprehensive review, we explore how these three challenging factors, COVID-19, climate change, and conflicts, are interrelated, and how they affect food security. We discuss the impact of these issues on the agricultural sector, plus possible ways of preventing or overcoming such adverse effects.
Exploring Perceptions of the Adoption of Prefabricated Construction Technology in Pakistan Using the Technology Acceptance Model
Authors: Hamza Muhammad , Azfar Rai Waqas , Mazher Khwaja Mateen , Sultan Basel , Maqsoom Ahsen , Khahro Shabir Hussain , Memon Zubair Ahmed
Published: May 2023

Prefabricated construction is being pursued globally as a critically important sustainable construction technology. Prefabricated construction technology (PCT) provides opportunities to effectively manage construction waste and offers venues to address the poor productivity and lackluster performance of construction projects, which are often expected to miss their budget and schedule constraints. Despite the significant benefits inherent in the adoption of PCT, research has shown an unimpressive exploitation of this technology in the building sector. A modified version of the popular technology acceptance model (TAM) was used to understand Pakistan’s building construction industry stakeholder’s acceptance of PCT and the factors that influence its usage. Data were collected from 250 building construction experts in the industry to test the hypotheses derived from the proposed model. Data analysis using covariance-based structural equation modeling revealed that construction industry stakeholders’ perceptions of perceived ease-of-use, perceived usefulness, trust, and satisfaction all strongly influenced PCT acceptance behavior. Moreover, results also confirmed the total direct and indirect effects of the perceived usefulness and perceived ease-of-use of behavioral intention toward using PCT, with trust and user satisfaction as mediators. The results of this research are expected to serve as a guide for the construction industry stakeholders to effectively plan, strategize, encourage, and increase the adoption of PCT to achieve sustainable construction outcomes in the building construction sector.
Indoor Air Quality Perception in Built Cultural Heritage in Times of Climate Change
Authors: Ilies Dorina Camelia , Herman Grigore Vasile , Safarov Bahodirhon , Ilies Alexandru , Blaga Lucian , Caciora Tudor , Peres Ana Cornelia , Grama Vasile , Bambang Sigit Widodo , Brou Telesphore , Taglioni Francois , Hassan Thowayeb H. , Hossain Mallik Akram
Published: May 2023

Low quality in a museum’s internal microclimate can induce both the deterioration of the exhibit collections, as well as affecting the health of visitors, employees and restorers. Starting from this premise, the present study aims to study the perception of visitors and employees of Darvas-La Roche Museum House (Romania) in relation to the air quality in the exhibition spaces. Their opinions were analyzed based on a questionnaire comprising 11 items aimed at understanding the influence of the indoor environment on the health of individuals, the degree of disturbance induced by the indoor air, if they experienced symptoms of illness after visiting the museum, etc. The obtained data were analyzed statistically in the SPSS 28 program, using tests such as coefficient, analysis of variance (ANOVA) and model summary, in order to obtain correlations between the sets of variables. The results obtained indicate that the majority of respondents perceived the indoor air quality as good, but there were also exceptions (approximately 20% of the respondents), which indicated different symptoms induced by the indoor air. Most of those (%) affected stated that they had pre-existing conditions, wear contact lenses or are smokers. In their case, the statistical-mathematical analyses indicated strong correlations between the ailments they suffer from and the appearance of certain discomforts (caused by too low or too high temperature, dust or dry air, etc.) and disease symptoms (nasal congestion, eye and skin irritations, coughs, migraines, frequent colds, etc.).
Study on the Effect of External Air Supply and Temperature Control on Coal Spontaneous Combustion Characteristics
Authors: Lei Changkui , Shi Xueqiang , Jiang Lijuan , Deng Cunbao , Nian Jun , Gao Yabin
Published: May 2023

Coal spontaneous combustion in underground mine goaf has a great impact on coal mining. The temperature-programmed experiment is a commonly used and effective method for studying the characteristics of coal spontaneous combustion. Aiming at the problem that the numerical simulation of coal spontaneous combustion characteristics under the condition of external air supply and temperature control in a temperature-programmed experiment is insufficient, a multi-physical field coupling numerical model of coal spontaneous combustion in the temperature-programmed experiment is established. The variation characteristics of coal temperature, oxygen, and oxidation products under external air supply and temperature control were studied. The results show that the numerical simulation results are consistent with the experimental results. With the increase in temperature, the volume fractions of oxygen and carbon dioxide decrease and increase, respectively. As the air supply volume increases, the oxygen volume fraction at the outlet increases, and the peak value of the oxygen volume fraction change rate exhibits a “hysteresis” feature, and the time corresponding to the peak value increases. Moreover, the temperature change rate increases. With the increase in the heating rate, the peak value of the oxygen volume fraction change rate increases and shows an “early appearance” characteristic, at the same time, the maximum coal temperature displays a linear increase trend.
Research on the Regulation of Algorithmic Price Discrimination Behaviour of E-Commerce Platform Based on Tripartite Evolutionary Game
Authors: Li Jianjun , Xu Xiaodi , Yang Yu
Published: May 2023

With the development of the digital economy, the algorithms and big data technologies of e-commerce platforms have gradually turned into double-edged swords. While realising personalised recommendations, they also provide information technology support for the use of algorithmic prices to discriminate and extract residual value from consumers. Consumers frequently use Black Cat and third-party media to complain, resulting in a significant negative impact. Therefore, in order to regulate algorithmic price discrimination, using e-commerce platforms, local governments and consumers act as game subjects, taking an evolutionary game approach. We analyse the impact of different situations and factors on the system’s evolutionary stability strategy and conduct its verification via simulation experiments. This study shows that several measures, such as increasing cooperation with the media; establishing clear regulatory rules to reduce the extent of algorithmic price discrimination and the grey revenue of e-commerce platforms; establishing a long-term mechanism for consumer feedback; improving rewards and punishments to increase the probability of successful regulation and penalties by local governments; sharing information to reduce the cost of consumer regulation; and setting reasonable bonus thresholds based on government revenue and consumer regulation costs, can effectively regulate algorithmic price discrimination and promote the sustainable development of e-commerce platforms.
Converting Seasonal Measurements to Monthly Groundwater Levels through GRACE Data Fusion
Authors: Ali Muhammad Zeeshan , Chu Hone-Jay , Tatas Tatas
Published: May 2023

Groundwater depletion occurs when the extraction exceeds its recharge and further impacts water resource management around the world, especially in developing countries. In India, most groundwater level observations are only available on a seasonal scale, i.e., January (late post-monsoon), May (pre-monsoon), August (monsoon), and November (early post-monsoon). The Gravity Recovery and Climate Experiment (GRACE) data are available to estimate the monthly variation in groundwater storage (GWS) by subtracting precipitation runoff, canopy water, soil moisture, and solid water (snow and ice) from the GLDAS model. Considering GRACE-based GWS data, the data fusion is further used to estimate monthly spatial maps of groundwater levels using time-varying spatial regression. Seasonal groundwater monitoring data are used in the training stage to identify spatial relations between groundwater level and GWS changes. Estimation of unknown groundwater levels through data fusion is accomplished by utilizing spatial coefficients that remain consistent with the nearest observed months. Monthly groundwater level maps show that the lowest groundwater level is 50 to 55 m below the earth’s surface in the state of Rajasthan. The accuracy of the estimated groundwater level is validated against observations, yielding an average RMSE of 2.37 m. The use of the GWS information enables identification of monthly spatial patterns of groundwater levels. The results will be employed to identify hotspots of groundwater depletion in India, facilitating efforts to mitigate the adverse effects of excessive groundwater extraction.
Recent Trends, Developments, and Emerging Technologies towards Sustainable Intelligent Machining: A Critical Review, Perspectives and Future Directions
Authors: Asif Muhammad , Shen Hang , Zhou Chunlin , Guo Yuandong , Yuan Yibo , Shao Pu , Xie Lan , Bhutta Muhammad Shoaib
Published: May 2023

Intelligent manufacturing is considered among the most important elements of the modern industrial revolution, which includes digitalization, networking, and the development of the intelligent manufacturing industry. With the progressive development of modern information technology, particularly the new generation of artificial intelligence (AI) technology, many new opportunities are coming into existence for intelligent machine tool (IMT) development. Intelligent machine tools offer diverse advantages, including learning and optimizing machining processes, error compensation, energy savings, and failure prevention. The paper focuses on the machine tool market in terms of global production, the leading machine tool-producing countries, and the leading countries’ market share in machine tool production. Moreover, the usage of various artificial intelligence techniques in intelligent machining operations is also considered in this comprehensive review, including machining parameter optimization, tool condition monitoring (TCM), and chatter vibration management of intelligent machine tools. Furthermore, future challenges for the machine tool industry are also highlighted.
A Quantitative Framework for Propagation Paths of Natech Domino Effects in Chemical Industrial Parks: Part II—Risk Assessment and Mitigation System
Authors: Yang Yunfeng , Chen Guohua , Zhao Yuanfei
Published: May 2023

This is the second part of the quantitative framework for the propagation paths of Natech domino effects in chemical industrial parks, which focuses on risk assessment and a mitigation system based on the propagation path probabilities obtained from Part I. In this paper, the risk assessment model for the propagation paths of the domino effects induced by natural disasters are developed, and the risk level is quantitatively analyzed using individual risk and social risk indexes and compared with the risk acceptance standard to determine whether the risk in the plant area is at the risk acceptance level. Furthermore, the chain-cutting disaster mitigation model for domino effects induced by Natech events and the full-life-cycle mitigation system are proposed, and the effectiveness of mitigation measures is also evaluated. The case analysis results show that Natech events and multi-level domino effects can increase the risk to an unacceptable level, and taking corresponding mitigation measures could reduce the risk to an acceptable level.
An Empirical Research: Incorporation of User Innovativeness into TAM and UTAUT in Adopting a Golf App
Authors: Kim Ji-Hye , Kang Eungoo
Published: May 2023

This current empirical study aims at investigating the incorporation of consumer innovativeness in TAM and UTAUT in the development of a golf app and how these influence consumer behavioral intentions in adopting the golf app. These models help illustrate consumer adoption of particular technologies and relate to the concept of innovation diffusion theory. Our research has obtained 394 responses and participants of the questionnaire were evenly divided by gender and age to reach the purpose of the current research. The main statistical methodology used the structural equation modeling (SEM) to evaluate the connection among user’s innovativeness regarding the golf application, technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT), behavioral intention, and word of mouth. In contrast to correlation assessments, SEM can measure the strength of the linear causative relationships between factors. Finally, this research concludes that TAM and UTAUT components determine the consumer’s attitude towards accepting and using new technology. Consumers who are open to innovations are more likely to accept emerging technology products and use them with the least resistance.
Impact of Major Function-Oriented Zone Planning on Spatial and Temporal Evolution of “Three Zone Space” in China
Authors: Xu Xinliang , Na Rigala , Shen Zhicheng , Deng Xiaojuan
Published: May 2023

Major function-oriented zone (MFOZ) planning is an important blueprint for the spatial development and protection of the Chinese national territory. The “Three Zone Space” (TZS) perspective, including agricultural space, ecological space, and urban space, is an important principle and method for the transformation and diffusion of MFOZ planning to implement territory planning from the central government to local branches. More than ten years have passed since the release of the MFOZ plan in 2010 in China, but there is still a lack of comprehensive and systematic analysis of the dynamic characteristics of the TZS under the impact of MFOZ planning. Therefore, based on high-resolution remote sensing land use data from 2010 to 2020, this paper systematically analyzes the changing characteristics of the TZS on the national scale by reasonably determining TZS areas in China. The main results are as follows: in 2020, the proportions of ecological space, agricultural space, and urban space in China were 78.635%, 20.083%, and 1.282%, respectively. The TZS areas reflected the spatial pattern of MFOZs in China. From 2010 to 2020, the spatial heterogeneity of the TZS changes was significant. In China, agricultural space and ecological space as a whole showed a decreasing trend, with dynamic degrees of −0.05% and −0.04%, respectively, while urban space showed a significant expansion trend, with a dynamic degree of 4.69%. The temporal change processes of the TZS in the periods of 2010–2015 and 2015–2020 were noticeably different. The agricultural space first showed an increasing trend and then a decreasing trend. The ecological space showed a decreasing trend in the two periods, while the urban space showed a significant expansion trend in the two periods. From 2010 to 2020, the urban spatial structure of the optimized development zones tended to be stable, and the ecological space reduction in the key ecological function zones has gradually been curbed, but the agricultural space in the main agricultural production zones has shown a slight decline. On the whole, the dynamic changes in the TZS from 2010 to 2020 in China are basically in line with the governance objectives of territorial space. The reasonable allocation and development of the “three zone space” is of great significance for protecting the natural and ecological environment.
Analyzing and Prioritizing the Barriers and Solutions of Sustainable Agriculture for Promoting Sustainable Development Goals in China
Authors: Cao Jiangning , Solangi Yasir Ahmed
Published: May 2023

Sustainable agriculture is crucial to the United Nations’ efforts to promote the Sustainable Development Goals (SDGs). However, to develop successful policies and strategies, it is necessary to assess the many obstacles to implementing sustainable agriculture. This study uses Multi-Criteria Decision Making (MCDM) techniques to analyze the challenges and opportunities facing sustainable agriculture in China’s economy, particularly in advancing the SDGs. Three enormous obstacles are found in the study, along with fifteen smaller ones that are broken down into economic, social, and environmental categories. The weights of the obstacles and sub-barriers are determined, and the solutions for sustainable agriculture are ranked using the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methodologies. According to the AHP approach, economic issues are China’s most significant obstacles to sustainable agriculture, followed by environmental and social concerns. Climate change and a lack of financial incentives are the two highest-ranked sub-barriers. On the other hand, the SAW approach suggests that the best ways to achieve the SDGs through sustainable agriculture are through international cooperation, financial investments in sustainable agriculture, and alternative agricultural methods. In order to advance sustainable agriculture and the SDGs in China, the report advises policymakers to focus on strengthening institutional support, increasing public awareness, and making technological investments.