bluuebunny/crossref_metadata_2025 huggingface dataset:
NeXtNow: A Convolutional Deep Learning Model for the Prediction of Weather Radar Data for Nowcasting Purposes
Authors: Albu Alexandra-Ioana , Czibula Gabriela , Mihai Andrei , Czibula Istvan Gergely , Burcea Sorin , Mezghani Abdelkader
Published: August 2022

With the recent increase in the occurrence of severe weather phenomena, the development of accurate weather nowcasting is of paramount importance. Among the computational methods that are used to predict the evolution of weather, deep learning techniques offer a particularly appealing solution due to their capability for learning patterns from large amounts of data and their fast inference times. In this paper, we propose a convolutional network for weather forecasting that is based on radar product prediction. Our model (NeXtNow) adapts the ResNeXt architecture that has been proposed in the computer vision literature to solve the spatiotemporal prediction problem. NeXtNow consists of an encoder–decoder convolutional architecture, which maps radar measurements from the past onto radar measurements that are recorded in the future. The ResNeXt architecture was chosen as the basis for our network due to its flexibility, which allows for the design of models that can be customized for specific tasks by stacking multiple blocks of the same type. We validated our approach using radar data that were collected from the Romanian National Meteorological Administration (NMA) and the Norwegian Meteorological Institute (MET) and we empirically showed that the inclusion of multiple past radar measurements led to more accurate predictions further in the future. We also showed that NeXtNow could outperform XNow, which is a convolutional architecture that has previously been proposed for short-term radar data prediction and has a performance that is comparable to those of other similar approaches in the nowcasting literature. Compared to XNow, NeXtNow provided improvements to the critical success index that ranged from 1% to 17% and improvements to the root mean square error that ranged from 5% to 6%.
Estimating Global Anthropogenic CO2 Gridded Emissions Using a Data-Driven Stacked Random Forest Regression Model
Authors: Zhang Yucong , Liu Xinjie , Lei Liping , Liu Liangyun
Published: August 2022

The accurate estimation of anthropogenic carbon emissions is of great significance for understanding the global carbon cycle and guides the setting and implementation of global climate policy and CO2 emission-reduction goals. This study built a data-driven stacked random forest regression model for estimating gridded global fossil fuel CO2 emissions. The driving variables include the annual features of column-averaged CO2 dry-air mole fraction (XCO2) anomalies based on their ecofloristic zone, night-time light data from the Visible Infrared Imaging Radiometer Suite (VIIRS), terrestrial carbon fluxes, and vegetation parameters. A two-layer stacked random forest regression model was built to fit 1° gridded inventory of open-source data inventory for anthropogenic CO2 (ODIAC). Then, the model was trained using the 2014–2018 dataset to estimate emissions in 2019, which provided a higher accuracy compared with a single-layer model with an R2 of 0.766 and an RMSE of 0.359. The predicted gridded emissions are consistent with Global Carbon Grid at 1° scale with an R2 of 0.665, and the national total emissions provided a higher R2 at 0.977 with the Global Carbon Project (GCP) data, as compared to the ODIAC (R2 = 0.956) data, in European countries. This study demonstrates that data-driven random forest regression models are capable of estimating anthropogenic CO2 emissions at a grid scale.
Transmit Antenna Selection and Power Allocation for Joint Multi-Target Localization and Discrimination in MIMO Radar with Distributed Antennas under Deception Jamming
Authors: Li Zhengjie , Xie Junwei , Liu Weijian , Zhang Haowei , Xiang Houhong
Published: August 2022

In this paper, with the aim of performing joint multi-target localization and discrimination tasks, a performance-driven resource allocation scheme is proposed. In the first, by establishing the signal model under deception jamming and utilizing the maximum likelihood (ML) estimator, the estimation information of targets can be obtained. Secondly, the Cramer–Rao lower bound (CRLB) for the transmit antenna selection and power allocation is derived. Then, to fully utilize the difference in spatial distribution between true and false targets, a false target discriminator based on the CRLB of the distance deception parameter is utilized. By introducing the nondimensionalization mechanism, we build an optimal objective function of target localization error and discrimination probability. Subsequently, a joint multi-target localization and discrimination optimization model has been established, which is mathematically a non-smooth and non-convex problem. By introducing an auxiliary variable, we propose a three-step solution strategy for solving this problem. Simulation results demonstrate that the proposed algorithm can improve the performance of joint localization accuracy and discrimination ability (JLADA) by more than 30% compared with the algorithms only for localization or discrimination. Meanwhile, by utilizing the proposed algorithm, the composite indicators of JLADA can decrease more than 70% compared with the uniform allocation scheme.
A Novel Sparse Bayesian Space-Time Adaptive Processing Algorithm to Mitigate Off-Grid Effects
Authors: Liu Cheng , Wang Tong , Liu Kun , Zhang Xinying
Published: August 2022

Space-time adaptive processing (STAP) algorithms based on sparse recovery (SR) have been researched because of their low requirement of training snapshots. However, once some portion of clutter is not located on the grids, i.e., off-grid problems, the performances of most SR-STAP algorithms degrade significantly. Reducing the grid interval can mitigate off-grid effects, but brings strong column coherence of the dictionary, heavy computational load, and heavy storage load. A sparse Bayesian learning approach is proposed to mitigate the off-grid effects in the paper. The algorithm employs an efficient sequential addition and deletion of dictionary atoms to estimate the clutter subspace, which means that strong column coherence has no effect on the performance of the proposed algorithm. Besides, the proposed algorithm does not require much computational load and storage load. Off-grid effects can be mitigated with the proposed algorithm when the grid-interval is sufficiently small. The excellent performance of the novel algorithm is demonstrated on the simulated data.
Quantitative Study of the T-AVIM-Based Simulated IMU Error in Polar Regions
Authors: Wen Zhe , Bian Hongwei , Wang Rongying , Ma Heng
Published: August 2022

For solving the problem of polar performance of the inertial navigation system (INS) at mid-low latitudes, the simulation test system constructed by the “attitude and velocity invariant method of trajectory transfer rule based on the transverse coordinate system (T-AVIM)” of the Earth sphere model is used. The test system structure, especially the IMU conversion formula from mid-low latitudes to polar region simulation test, is introduced, and it is proved that the IMU conversion error can be equivalently superimposed on the bias error of the polar simulated IMU. According to the marine estimation formula for the effect of the reference error on the IMU conversion error, the specific influence of the constant error component and the random error component of the reference system on the simulated IMU is analyzed. The calculation method of the simulated IMU error is given with examples and intuitively explained, and the correctness of the theory is verified through simulation experiments.
A Detection and Tracking Method Based on Heterogeneous Multi-Sensor Fusion for Unmanned Mining Trucks
Authors: Liu Haitao , Pan Wenbo , Hu Yunqing , Li Cheng , Yuan Xiwen , Long Teng
Published: August 2022

There exist many difficulties in environmental perception in transportation at open-pit mines, such as unpaved roads, dusty environments, and high requirements for the detection and tracking stability of small irregular obstacles. In order to solve the above problems, a new multi-target detection and tracking method is proposed based on the fusion of Lidar and millimeter-wave radar. It advances a secondary segmentation algorithm suitable for open-pit mine production scenarios to improve the detection distance and accuracy of small irregular obstacles on unpaved roads. In addition, the paper also proposes an adaptive heterogeneous multi-source fusion strategy of filtering dust, which can significantly improve the detection and tracking ability of the perception system for various targets in the dust environment by adaptively adjusting the confidence of the output target. Finally, the test results in the open-pit mine show that the method can stably detect obstacles with a size of 30–40 cm at 60 m in front of the mining truck, and effectively filter out false alarms of concentration dust, which proves the reliability of the method.
Study on Attenuation Characteristics of Acoustic Emission Signals with Different Frequencies in Wood
Authors: Mao Feilong , Fang Saiyin , Li Ming , Huang Changlin , Deng Tingting , Zhao Yue , Qin Gezhou
Published: August 2022

To study the effect of frequency on the attenuation characteristics of acoustic emission signals in wood, in this paper, two types of hard wood and soft wood were studied separately, and the energy attenuation model of the propagation process of AE sources with different frequencies was established. First, using the piezoelectric inverse effect of the AE sensor, an arbitrary waveform generator was used to generate frequency-tunable pulses in the range of 1 kHz to 150 kHz as the AE source, where the AE source energy could be regulated by the output voltage level. Then, five AE sensors were placed at equal intervals of 100 mm on the surface of the specimen to collect AE signals, and the sampling frequency was set to 500 kHz. Finally, the energy value of AE signal of each sensor was calculated based on the AC principle, and the energy attenuation model was established by exponential fitting. The results showed that both the amplitude and energy of the AE signals of different frequencies showed negative exponential decay with the increase of propagation distance, and, at the same frequency, the change of AE source energy level had no significant effect on its attenuation rate. Compared with hard wood, the energy attenuation of the AE signal of soft wood was more sensitive to the change of frequency, and, at the same frequency, the attenuation rate of soft wood was smaller than that of hard wood.
Adaptive Access Selection Algorithm for Large-Scale Satellite Networks Based on Dynamic Domain
Authors: Liu Gaosai , Jiang Xinglong , Li Huawang , Zhang Zhenhua , Sun Siyue , Liang Guang
Published: August 2022

The traditional satellite access selection algorithm, which is used in large-scale satellite networks, has some disadvantages, such as frequent link switching, high interrupt probability, and unable to adapt to a dynamic environment. According to the periodicity of the large-scale satellite network and the prior knowledge provided by acknowledgment packages, a dynamic domain-based adaptive access algorithm (DAA) is proposed in this paper. Firstly, this algorithm divides the large-scale satellite network into different domains according to the minimum elevation angle of the Earth station (ES) and the predictable characteristics of the trajectory of the satellite. Then, the ES selects the access satellites according to the relationship between the traffic volume and the satellites’ coverage time. Finally, the ES selects the backup access satellite based on the satellites’ coverage time, the traffic volume of the ES, satellite status provided by prior knowledge, and other information. When the access satellite cannot satisfy the communication demand, the ES adaptively switches the earth-satellite link to the backup access satellite. The ES first choice of access satellite does not require interaction with the satellites, reducing the consumption of communication resources. The selection strategy of backup access satellite and the concept of virtual destination address proposed in this paper can reduce the routing overhead after switching. Through theoretical analysis and simulation results in the StarLink constellation, it is proved that this paper improves the coverage time utilization of accessing satellites and reduces the switching probability compared with the traditional access algorithm, which is more suitable for ES to access large-scale satellite networks.
Use of Polar Heliostats to Improve Levels of Natural Lighting inside Buildings with Little Access to Sunlight
Authors: Fernández-Ahumada Luis Manuel , Osuna-Mérida Maximiliano , López-Sánchez Jesús , Gómez-Uceda Francisco Javier , López-Luque Rafael , Varo-Martínez Marta
Published: August 2022

The growing need to increase environmental and energy sustainability in buildings (housing, offices, warehouses, etc.) requires the use of solar radiation as a renewable source of energy that can help to lower carbon footprint, making buildings more efficient and thereby contributing to a more sustainable planet, while enhancing the health and wellbeing of its occupants. One of the technologies deployed in the use of solar energy in buildings is heliostats. In this context, this paper presents an analysis of the performance of a heliostat illuminator to improve illumination in a classroom at the Campus of Rabanales of the University of Cordoba (Spain). A design of a system in charge of monitoring and measuring daylighting variables using Arduino hardware technology and free software is shown. This equipment develops the communications, programming and collection of lighting data. In parallel, installation of an artificial lighting system complementary to the natural lighting system is implemented. Finally, an analysis of the impact of the proposed solution on the improvement of energy efficiency is presented. Specifically, it is estimated that up to 64% of savings in artificial lighting can be achieved in spaces with heliostatic illuminators compared to those without them.
Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform
Authors: Brown Nicholas E. , Rojas Johan F. , Goberville Nicholas A. , Alzubi Hamzeh , AlRousan Qusay , Wang Chieh (Ross) , Huff Shean , Rios-Torres Jackeline , Ekti Ali Riza , LaClair Tim J. , Meyer Richard , Asher Zachary D.
Published: August 2022

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.
Image Recognition of Wind Turbine Blade Defects Using Attention-Based MobileNetv1-YOLOv4 and Transfer Learning
Authors: Zhang Chen , Yang Tao , Yang Jing
Published: August 2022

Recently, the machine-vision-based blades surface damage detection technique has received great attention for its low cost, easy operation, and lack of a need for prior knowledge. The rapid progress of deep learning has contributed to the promotion of this technology with automatic feature extraction, a broader scope of application, and stronger expansibility. An image recognition method of wind turbine blade defects using attention-based MobileNetv1-YOLOv4 and transfer learning is proposed in this paper. The backbone convolution neural network of YOLOv4 is replaced by the lightweight MobileNetv1 for feature extraction to reduce complexity and computation. Attention-based feature refinement with three distinctive modules, SENet, ECANet, and CBAM, is introduced to realize adaptive feature optimization. To solve the problem of slow network convergence and low detection accuracy caused by insufficient data, a two-stage transfer learning approach is introduced to fine-tune the pre-trained network. Comparative experiments verify the efficacy of the proposed model, with higher detection accuracy but a significantly faster response speed and less computational complexity, compared with other state-of-the-art networks by using images of the wind turbine blades taken by an unmanned aerial vehicle (UAV). A sensitivity study is also conducted to present the effects of different training dataset sizes on the model performance.
Perceptions of Trust in the Context of Social Cohesion in Selected Rural Communities of South Africa
Authors: Khaile Fundiswa T. , Roman Nicolette V. , October Kezia R. , Van Staden Maria , Balogun Tolulope V.
Published: August 2022

Although nuances around the definitions and contextualization of social cohesion subsist, this paper views social cohesion through the lens of social cooperation and togetherness within a collective in geopolitical terms, expressed in the attitudes and behaviours of its members. In many countries, including South Africa, social cohesion remains an ideal to strive for and achieve. Extant studies suggest that trust is one of the key factors in building social cohesion. As such, this paper aims to explore trust in the context of social cohesion. This study attempts to address the knowledge gaps regarding the views, feelings, and experiences around trust and also make a contribution to the qualitative inquiry of trust in the context of social cohesion in rural communities of South Africa. Accordingly, the perceptions and experiences of people in two rural communities (Lambert’s Bay and Philippolis) regarding trust in the context of social cohesion were explored. A qualitative methodology was employed in order to gain a deeper understanding of the perceptions of trust. A total of 19 participants were interviewed, comprising of community stakeholders and parents. A semi-structured interview schedule was used to collect data in face-to-face interviews with participants. Data collected were analysed using Braun and Clark’s thematic analysis. The study found that trust among community members in both Lambert’s Bay and Philippolis was limited. In instances where there was trust, it was mainly amongst participants who know each other compared to individuals who do not know each other. Thus, in both communities, generalised trust continues to be a challenge.
Importance of Skills Development for Ensuring Graduates Employability: The Case of Bangladesh
Authors: Alam Md Jahangir , Ogawa Keiichi , Islam Sheikh Rashid Bin
Published: August 2022

Graduate employability is a multifaceted concept considering the Sustainable Development Goals. Graduate employability and skills development are also significant determinants for future career success. Graduate employability has seen more sweeping emphasis and concerns in national and global job markets, due to the ever-rising number of unemployed people, which has increased even more due to COVID-19. Due to its importance, this study investigates the current state of skill development initiatives in Bangladesh and the perceptions of university graduates regarding skill development for their future employability. This study uses mixed-method research. Data was collected through surveys and in-depth interviews; various probabilistic and non-probabilistic sample selection methods were used. A total of 437 participants responded to this study. After analysis, the data was shown descriptively. The empirical findings of this study demonstrated that university graduates are well-aware of the skill development requirements for their future employability. However, university graduates face many obstacles in acquiring these necessary skill development opportunities. Therefore, the government and relevant stakeholders must work together to alleviate the obstacles. Furthermore, this study includes recommendations that can assist in developing a model for skill development programs and initiatives in the country for university graduates to ensure their future employability.
Models and Methods of Formation of the Foresight-Controlling Mechanism
Authors: Alabugin Anatoliy , Aliukov Sergei , Khudyakova Tatyana
Published: August 2022

The necessity of mechanisms for long-term forecasting and regulation of high-tech enterprise development strategies has been determined. This paper discusses how managers and designers can create models and methods for sustainability management mechanisms. The elements of novelty of this study and contribution to the existing theory of managing objects of socio-economic systems are: the development of the principle of a single mechanism of foresight-controlling, which made it possible to increase the efficiency and sustainability of the organizational behavior of objects; the development of theoretical and methodological models for the formation of a foresight-controlling management mechanism; the improvement of the management mechanism based on the combined application of mechanical and organic models of organizational behavior of socio-economic systems; the development of methods for regulating the management mechanism according to stability criteria in accordance with the characteristics of the enterprise’s innovation cycle; finally, the modernization of mathematical models and methods for studying the processes of functioning of the control mechanism. The following results of the implementation of the methods at the enterprise-object of research were obtained: the assessment and adjustment of planned and target indicators of the quality of management were carried out on the basis of an examination of the parameters of the quality of regulation; recommendations were developed for adjusting the planned and target indicators of the quality of the formation of development strategies, taking into account the factors of the knowledge economy. The results’ validations were implemented in projects and plans for the innovative development of the facility based on the transformation factors of the 5–6th modes of the economy.
The Influence of Content Presentation on Users’ Intention to Adopt mHealth Applications: Based on the S-O-R Theoretical Model
Authors: Liu Yizhi , Lu Xuan , Li Chengjiang , Zhao Gang
Published: August 2022

The development of internet technology enables mobile medical health (mHealth) applications (Apps) to provide users with health services. The content presentation of apps is an important factor affecting users’ adoption of mHealth Apps. This study aims to examine the effect of the content presentation of mHealth Apps on users’ adoption intention, using the stimulus-organism-response (S-O-R) theory as the theoretical framework. A model of the effect of the content presentation of mHealth Apps on users’ intention to adopt, integrating perceived value and trust, was constructed. Furthermore, a quantitative study using a questionnaire survey was carried out to test the model. The analysis shows that platform information presentation, guidance information presentation, and relational information presentation indirectly have a significant positive effect on willingness toward participation and recommendation through the mediating effect of perceived value or trust. All three presentations have a significant positive effect on perceived value. Platform information presentation has a significant positive effect on trust in contrast to the other two presentations. In addition, the results reveal that perceived value and trust have a significant positive effect on willingness toward participation and recommendation, respectively. However, the effect of perceived value on trust is not significant. This work could provide measures and suggestions to improve users’ intention to adopt mHealth Apps as well as help researchers, developers, service providers, and app users to use and improve this modern mobile medical service.
A Factor Exploration and Empirical Study on the Influence of the Fourth Industrial Revolution on Employment: Focus on Korean Sample
Authors: Ahn Jongchang , Jang Yirang , Rhee Yoonki
Published: August 2022

This study aims to analyze whether technological changes in the fourth industrial revolution (4IR), as independent variables, can influence employment, a dependent variable. It categorizes scientific technology changes in the 4IR based on related research, and identifies six factors and corresponding research hypotheses. The paths for the six hypotheses were analyzed using 275 effective samples. Results show that life-convenience technology and blockchain technology variables significantly influenced employment (p < 0.001). Additionally, innovation technology, interface technology, human life technology, and 3D technology variables significantly influenced employment (p < 0.01). The power of the total variance explanation (69.596%) for the employment influence was very high. Seven items—self-driving cars, decision-making using big data, Internet of Things, Wearable Internet, Designer Beings, 3D printing technology and human health, and Bitcoin and blockchain—were statistically significant for the employment effect. The study obtained effective paths for the employment influence of fundamental technologies and derived the demographic variable presenting a meaningful difference among groups. This research seeks a policy direction that enables preparation for 4IR deployment. It also contributes to the academic sphere in meaningfully and empirically classifying the technology factors of the 4IR.
The Effect of Safety Attitudes on Coal Miners’ Human Errors: A Moderated Mediation Model
Authors: Niu Lixia , Zhao Rui
Published: August 2022

With the advancement of digital technology, the operation scenarios and work of miners have changed. Although the rate of accidents caused by unsafe conditions is decreasing year by year, the rate of accidents caused by human errors is still high. To investigate the influencing factors of miners’ human errors in the context of smart mines, based on the attitude–behavior model, this paper introduced two variables, situational awareness and task complexity, and established a moderated mediation model to explore the path of safety attitudes on human errors. Using time-lagged data from 246 full-time miners working at smart mines, we found that miners’ safety attitudes were effective in reducing human errors, miners’ safety attitudes reduced human errors through the mediation of situational awareness, and task complexity enhanced the positive relationship between safety attitudes and situational awareness, thus positively moderating the indirect relationship between safety attitudes and human errors. The findings advance a new understanding of how safety attitudes can reduce miners’ human errors. They also provide practical implications on the importance of leadership and finding ways to promote situational awareness as well as maintaining good safety attitudes.
Decentralisation and Resilience: A Multidimensional Approach
Authors: Arcidiacono Alessia , Torrisi Gianpiero
Published: August 2022

Multidimensional wellbeing is gaining momentum as a measure of socio-economic performance. Departing from common practice using income and employment, we investigate the resilience of 22 European countries on the occasion of the 2007 economic crisis in terms of multidimensional wellbeing. The potential effects of fiscal federalism-as measured by decentralised expenditure- on the ability to recover from the economic shock at the sectoral level are taken into account using data from the IMF’s Fiscal Decentralisation dataset. Methodologically, using panel data from 2009 to 2017 the empirical analysis adopts a pooled regression (POLS) approach with Driscoll–Kraay standard errors to consider very general forms of cross-sectional/spatial and temporal dependence. The analysis shows that (i) the results in terms of multidimensional resilience along the so-called 4R (i.e., Resilience, Recovery, Reorientation, and Renewal) are rather sector-specific and (ii) generally speaking, the level of fiscal decentralisation mitigates the shocks. Although based on the 2007 financial crisis, we argue that the lessons learned from the current analysis could provide a stimulus for research and interesting general insights applicable to other shocks, including the current COVID-19 pandemic. Indeed, our novel approach based on multidimensional wellbeing provides a piece of robust evidence making the spatial unevenness of economic shocks more apparent. As a consequence, from a scholarship perspective, it questions the mainstream approach based on mainstream measures, such as GDP and employment, calling for a more granular approach to economic resilience; furthermore, from a policymaking perspective, it prompts policymakers and practitioners to pay higher attention to sector-specific effects of decentralised policies.
Participatory Approach to Wetland Governance: The Case of The Memorandum of Understanding of the Sečovlje Salina Nature Park
Authors: Polajnar Horvat Katarina , Gašperič Primož , Leban Kim , Tičar Jure , Smrekar Aleš
Published: August 2022

Wetlands are defined as dynamic ecosystems that combine the characteristics of aquatic and terrestrial ecosystems and are important from ecological as well as social and economic perspectives. In response to the intense degradation and alteration of wetlands, communities have developed various management strategies. One of the ways to achieve more effective participatory wetland management is to introduce the concept of a Wetland Contract, a voluntary agreement that ensures sustainable management and development of wetlands. This study on the Sečovlje Salina Nature Park in Slovenia follows the methodology of the preparation (legal framework, scientific description and stakeholder analysis) and implementation (organization of Territorial Labs, scenario planning and development) stages of the Wetland Contract concept. Of approximately 200 potential stakeholders, 34 participated in the Territorial Labs, and 16 stakeholders signed the less binding type of Wetland Contract, called the Memorandum of Understanding. The Memorandum of Understanding and its implementation process, which included systematic cross-sectoral participation, successfully overcame conflicts between stakeholders with different interests. The methodology used has shown great potential for further applications in wetlands of common interest.
The Spatial Network Structure of Tourism Efficiency and Its Influencing Factors in China: A Social Network Analysis
Authors: Yang Guangming , Yang Yunrui , Gong Guofang , Gui Qingqing
Published: August 2022

Although tourism has gradually become a popular form of leisure and entertainment in China, the quality of China’s tourism development remains unclear. Through the panel data of 30 provinces in China, an SBM-DEA model and a social network analysis are used to explore the quality of tourism development, and a spatial econometric regression is used to identify the relevant factors affecting tourism efficiency. The study found that the level of tourism efficiency in Southwest China is high and stable. The northwest region has a low level of tourism efficiency, but a slow growth trend. The rest of the regions show fluctuating trends of tourism efficiencies. The spatial correlation network of provincial tourism efficiency is gradually complicated. Regarding influencing factors, the number of patents granted, traffic levels, financial development, and government macro-control all have positive effects on tourism efficiency. The study uncovered some useful management insights and implications for the travel industry.
Coordinated Development of Urban Agglomeration in Central Shanxi
Authors: Cao Yongjian , Zhang Zhongwu , Fu Jie , Li Huimin
Published: August 2022

Central Shanxi is one of the nine urban agglomerations proposed in China’s latest national planning, which has great development potential and represents a major opportunity for Shanxi Province to rise in central China. How to determine the existing problems and promote better-coordinated development is the goal of this article. Therefore, an improved gravity model, industrial structure similarity coefficient and population–economic growth elasticity method were used to analyze and study the coordinated development of urban agglomerations in central Shanxi from the perspectives of economy, industry and population–economy. The research conclusion is that there are three problems: a low level of coordinated economic development, strong dependence on coal resources, and uncoordinated population development and economic growth. Therefore, this paper discusses and puts forward the main strategies for the government to strengthen economic planning, improve the level of economic development, optimize and upgrade the industrial structure, end dependence on coal resources and strengthen regional ties, and improve the level of population and economy coordination so that the urban agglomeration in central Shanxi becomes the growth pole and important support point of regional economic and social development.
Spatiotemporal Evolution and Socioeconomic Impacts of Rainstorms and Droughts in Contiguous Poverty-Stricken Areas of China
Authors: Li Aiwei , Gao Shuyuan , Gao Miaoni , Wang Xueqing , Zhang Hongling , Jiang Tong , Yang Jing
Published: August 2022

To consolidate the achievements in the elimination of absolute poverty in China and prevent rural populations from returning to poverty as a result of meteorological disasters, this study analyzed the spatiotemporal characteristics of rainstorms and droughts and their socioeconomic impacts on China’s contiguous poverty-stricken areas (CPSAs) from 1984 to 2019. The annual number of rainstorms and drought days in CPSAs of China reached approximately 1.9 days/year and 44.6 days/year, respectively. It gradually decreased from southeast to northwest. Rainstorms showed a significant increasing trend of 0.075 days/decade, while there is no significant trend in drought days. Due to rainstorms and droughts, the average annual number of people affected and direct economic losses in CPSAs reached 34 million people/year and 29 billion Chinese yuan/year, accounting for 22.9% and 12.6% of China’s total amounts, respectively. The average annual loss rate due to disasters in this region reached 1.6%, which is 0.6% higher than the national level. Furthermore, the distinct features and socioeconomic impacts of rainstorms and droughts were identified on the southeastern and northwestern sides of the population density line (PDL) along Tengchong-Aihui in China. Droughts have often impacted the regions located along the PDL, while rainstorms and droughts have occurred more frequently in the regions to the southeast of the PDL than in the regions to the northwest of the PDL. As a result, the affected population and direct economic losses due to rainstorms and droughts in the regions to the southeast of the PDL were 8.8 and 9.2 times and 3.3 and 7.4 times higher, respectively, than those in the regions on the other side of the PDL. Although the losses were greater, the disaster resistance capabilities were significantly improved in these regions. In contrast, the regions to the northwest side of the PDL exhibited a significant increasing trend in losses with a relatively low disaster resistance capabilities. This study revealed that it is necessary to improve the capability of meteorological disaster prevention and reduction in China’s CPSAs, especially in the regions to the west of the PDL, which could further contribute to the realization of United Nations Sustainable Development Goals.
Spatial Multi-Criteria Analysis for Road Segment Cycling Suitability Assessment
Authors: Santos Bertha , Passos Sílvia , Gonçalves Jorge , Matias Isabel
Published: August 2022

The shift to low-emission mobility, embedded in a growing need for sustainable development, makes soft modes a highly promoted transport alternative in national and international mobility policies. Soft mobility modes, especially cycling, is an alternative capable of reversing the trend of private car use in urban areas, being one of the main strategies of Sustainable Urban Mobility Plans (SUMP). Several factors can influence travel mode choice, between them, demographic, economic, land use, travel distance and time, and climatic and physical factors are the most reported in the literature. This study presents a framework of the main European cycling strategies and focuses on the development of a methodological approach to assess the cycling suitability of existing road networks. The approach is based on a spatial multi-criteria analysis that combines population density, trip generation points service areas and road characteristics (hierarchy and slope). Consideration of the topography was particularly relevant in the cycling suitability model definition. The model was tested in the hillside city of Covilhã (Portugal) and compared with the recently planned and implemented city cycling network. The main conclusions point to the adequacy, flexibility, and applicability of the proposed model by municipalities, contributing to a more sustainable urban environment and healthier communities. Results obtained in the Covilhã case study also denote the possibility of implementing cycling mobility in hillside cities, especially using e-bikes. For future works, an expansion of the approach is proposed to include a detailed and sustained cycling network definition model and a process to assess cycling routes hierarchy/solutions.
Analysis of a Teleworking Technology Adoption Case: An Agent-Based Model
Authors: Arbelaez-Velasquez Carlos A. , Giraldo Diana , Quintero Santiago
Published: August 2022

An agent-based model for teleworking technology adoption is presented, including the risk of office closure in the event of a lockdown. It analyzes an adoption case using simulations and can be adapted to other cases and teleworking promotion strategies to contribute to sustainability. Simulations produce smooth sigmoidal curves that reasonably fit to real adoption curves. The simulation results suggest that the main reason for the observed increase in the adoption rate is the increase in the risk of office closures, the consequent increase in the usefulness of teleworking technology, and the increase in external influence that motivates them.
Methane Emissions from Livestock Slurry: Effects of Storage Temperature and Changes in Chemical Composition
Authors: Hilgert Julio E. , Amon Barbara , Amon Thomas , Belik Vitaly , Dragoni Federico , Ammon Christian , Cárdenas Aura , Petersen Søren O. , Herrmann Christiane
Published: August 2022

Livestock production contributes to releasing methane into the atmosphere. Liquid manure management offers significant opportunities to reduce these emissions. A better understanding of the factors controlling methane emissions from manure is necessary to select effective mitigation strategies. Our study aimed to identify the influence of storage temperature and the associated change in chemical composition on methane emissions from dairy and fattening pig manure. Storage temperature affects microbial activity and induces changes in chemical composition that are key influences in methane emissions. Dairy and fattening pig manure samples were stored at five different temperatures (5–25 °C) for 90 days in a laboratory-scale experiment to measure the methane production. The chemical composition of the slurry samples was analyzed, and the biochemical methane potential (BMP) tests were performed before and after storage. For pig manure stored at 25 °C and 20 °C, methane emissions accounted for 69.3% and 50.3% of the BMP, respectively. Maximum methane emissions for dairy slurry were observed at 25 °C but remained at a low level. Analyses of the accumulation of volatile fatty acids (VFAs) during storage are presented in few studies, this work revealed a potential inhibition of methane production, where the accumulation of VFAs was most elevated in samples stored at 20 °C and 25 °C. This partly counteracted the increase in methane emissions expected from the higher temperatures. The degree of VFA and dissociated fatty acids accumulation in dairy cattle slurry should be assessed for more accurate estimations of methane emissions from slurry stores.
The Impact of ‘Compulsory’ Shifting to Use e-Services during COVID-19 Pandemic Restrictions Period on e-Services Users’ Future Attitude and Intention “Case Study of Central European Countries/Visegrád Group (V4)”
Authors: Alassaf Pierre , Szalay Zsigmond Gábor
Published: August 2022

This study takes advantage of COVID-19 experience in regards of ‘compulsory’ shifting toward using e-services to evaluate Central European countries’ citizens’ future attitude and intention to keep using e-services after COVID-19 pandemic precautionary measures end regarding the case study of Visegrád Group (V4) countries: Czech, Hungary, Poland and Slovakia, considering the impact of users’ satisfaction with e-services during that period, taking age and gender as control variables. Total of 354 survey responses used in analyzing distributed questionnaire answers. The study found 84% of V4 countries’ users between 18–35 years old were satisfied and willing to keep using e-services, whereas only 44.5% of 46–55-year-old users have this future willingness, the vast majority of oldest respondents between 56–65 don’t intend to keep using e-services after COVID-19 pandemic precautionary measures end, while only 16.6% having the intention to do so. Moreover, this research finds no impact of gender on e-services satisfaction, attitude and intention in regard to the study. One of the main contributions of this study is raising attention to the decreasing intentions to keep using e-services among users above 35 as their age increases, addressing this weakness is very important to involve older generations in future digitizing-projects and successful e-government implementation.
Assessing the Economic Energy Level of the Chengdu–Chongqing Economic Circle: An Integrative Perspective of “Field Source” and “Field”
Authors: Wang Chengfu , Song Lijun , Lu Haoqi , Zheng Shuxin , Huang Chengfeng
Published: August 2022

As a densely overlapping area under the national overarching development strategy, the Chengdu–Chongqing Economic Circle (CCEC) possesses a significant strategic location. However, compared with the other three growth pillars, the economic energy of the CCEC is still at a low level and in urgent need of improvement, which has to be implemented step by step in a systematic manner. At present, the focus remains on the two central cities—Chengdu and Chongqing. In contrast to the traditional evaluation of the regional economic energy level (EEL) solely from the “internal comprehensive development level”, this paper takes an angle on the interdependence and co-existence of “field source” and “field” to construct a preliminary index system which accounts for the “external economic connection level” as well. We then calibrate and validate the proposed model from both statistical and empirical angles. Finally, by optimizing the model, this paper evaluates the EELs of the Chengdu–Chongqing twin cities by fuzzy integrals of comprehensive weights. The results show the following: (1) From the perspective of overall indicators, the EELs of Chengdu and Chongqing have been rising from 2000 to 2018. In 2019, due to deglobalization and the Sino-US trade war, both cities appeared to reach an inflection point. (2) In terms of horizontal comparison, the EELs of the two cities basically coincide with each other, in line with the positioning of Chengdu–Chongqing as the two leading cities in Western China. However, their EELs have been lagging behind those of Beijing, indicating more room for further improvement. (3) From the point of view of sub-indexes, Chongqing has the advantage in the “external economic connection level” while Chengdu has the advantage in the “internal comprehensive development level”. The dislocation and complementarity of Chongqing and Chengdu has become an opportunity to break away from the stiff competition and jointly improve their EELs. (4) By comparing our evaluation with the traditional assessment, we note that the EEL tends to be misestimated if comprehensive factors regarding the “external economic connection level” are not taken into account.
A Study of Evaluation Method for Turbocharger Turbine Based on Joint Operation Curve
Authors: Yin Sheng , Ni Jimin , Fan Houchuan , Shi Xiuyong , Huang Rong
Published: August 2022

Turbochargers have evolved with the advancement of engine technology. In this study, we pro-posed a concept of joint operation, based on the operating characteristics of the compressor and turbine. Furthermore, a turbine evaluation method was proposed based on this concept, and an optimization application study of the turbine impeller blade number and turbine casing was con-ducted and verified. The results showed that the performance evaluation method based on the joint point could predict the optimization trend of turbine performance more accurately, the turbine output power optimized based on our new method evidently had advantages over the original turbine, and the joint point showed better overall performance. The original single-entry turbine could be optimized into a 9-blade twin-entry turbine having better response characteristics. The maximum torque of the optimized engine was 5.4% higher than that of the original engine, and the minimum brake specific fuel consumption (BSFC) was reduced by 2.1%. In the low and medium speed operating region, engine torque was increased by up to 3.2% and BSFC was reduced by up to 1.1% compared to the turbine optimized by conventional methods. Hence, the optimization effect of our new method was proven.
An Integrated Fuzzy-Based Sustainability Framework for Post-Secondary Educational Buildings: A User-Perspective Approach
Authors: Alfalah Ghasan , Al-Sakkaf Abobakr , Mohammed Abdelkader Eslam , Zayed Tarek
Published: August 2022

Decreasing the impact of educational buildings on the environment is a primary concern of the sustainable building movement. However, limited research has centered on improving educational building sustainability from users’ perspectives. This study aims to determine an overall user perspective satisfaction scale (OUPS) for post-secondary educational buildings, determine the factors and sub-factors that affect users’ perspectives, and create a building sustainability platform for evaluating user satisfaction. The main goal of the developed model is to offer facility managers the current users’ perspectives on post-secondary educational buildings to improve sustainability from users’ perspectives. The results revealed a significant influence of thermal comfort (40%) and aesthetics (22%) on users’ perspectives. The developed model was validated by experts working in the facility management field and they acknowledged it as having good potential. This work first utilized the Fuzzy Analytic Network Process (FANP) modelling technique to determine weights for each factor and sub-factor and then employed the fuzzy expert system to develop an OUPS. Questionnaire responses and interviews with facility managers and users were used to develop these models for a case study of the M.B. building at Concordia University in Montreal, Quebec.