bluuebunny/crossref_metadata_2025 huggingface dataset:
Dual-Coupled CNN-GCN-Based Classification for Hyperspectral and LiDAR Data
Authors: Wang Lei , Wang Xili
Published: August 2022

Deep learning techniques have brought substantial performance gains to remote sensing image classification. Among them, convolutional neural networks (CNN) can extract rich spatial and spectral features from hyperspectral images in a short-range region, whereas graph convolutional networks (GCN) can model middle- and long-range spatial relations (or structural features) between samples on their graph structure. These different features make it possible to classify remote sensing images finely. In addition, hyperspectral images and light detection and ranging (LiDAR) images can provide spatial-spectral information and elevation information of targets on the Earth’s surface, respectively. These multi-source remote sensing data can further improve classification accuracy in complex scenes. This paper proposes a classification method for HS and LiDAR data based on a dual-coupled CNN-GCN structure. The model can be divided into a coupled CNN and a coupled GCN. The former employs a weight-sharing mechanism to structurally fuse and simplify the dual CNN models and extracting the spatial features from HS and LiDAR data. The latter first concatenates the HS and LiDAR data to construct a uniform graph structure. Then, the dual GCN models perform structural fusion by sharing the graph structures and weight matrices of some layers to extract their structural information, respectively. Finally, the final hybrid features are fed into a standard classifier for the pixel-level classification task under a unified feature fusion module. Extensive experiments on two real-world hyperspectral and LiDAR data demonstrate the effectiveness and superiority of the proposed method compared to other state-of-the-art baseline methods, such as two-branch CNN and context CNN. In particular, the overall accuracy (99.11%) on Trento achieves the best classification performance reported so far.
Chaos-Enhanced Adaptive Hybrid Butterfly Particle Swarm Optimization Algorithm for Passive Target Localization
Authors: Rosić Maja , Sedak Miloš , Simić Mirjana , Pejović Predrag
Published: August 2022

This paper considers the problem of finding the position of a passive target using noisy time difference of arrival (TDOA) measurements, obtained from multiple transmitters and a single receiver. The maximum likelihood (ML) estimator’s objective function is extremely nonlinear and non-convex, making it impossible to use traditional optimization techniques. In this regard, this paper proposes the chaos-enhanced adaptive hybrid butterfly particle swarm optimization algorithm, named CAHBPSO, as the hybridization of butterfly optimization (BOA) and particle swarm optimization (PSO) algorithms, to estimate passive target position. In the proposed algorithm, an adaptive strategy is employed to update the sensory fragrance of BOA algorithm, and chaos theory is incorporated into the inertia weight of PSO algorithm. Furthermore, an adaptive switch probability is employed to combine global and local search phases of BOA with the PSO algorithm. Additionally, the semidefinite programming is employed to convert the considered problem into a convex one. The statistical comparison on CEC2014 benchmark problems shows that the proposed algorithm provides a better performance compared to well-known algorithms. The CAHBPSO method surpasses the BOA, PSO and semidefinite programming (SDP) algorithms for a broad spectrum of noise, according to simulation findings, and achieves the Cramer–Rao lower bound (CRLB).
SMaTE: A Segment-Level Feature Mixing and Temporal Encoding Framework for Facial Expression Recognition
Authors: Kim Nayeon , Cho Sukhee , Bae Byungjun
Published: August 2022

Despite advanced machine learning methods, the implementation of emotion recognition systems based on real-world video content remains challenging. Videos may contain data such as images, audio, and text. However, the application of multimodal models using two or more types of data to real-world video media (CCTV, illegally filmed content, etc.) lacking sound or subtitles is difficult. Although facial expressions in image sequences can be utilized in emotion recognition, the diverse identities of individuals in real-world content limits computational models of relationships between facial expressions. This study proposed a transformation model which employed a video vision transformer to focus on facial expression sequences in videos. It effectively understood and extracted facial expression information from the identities of individuals, instead of fusing multimodal models. The design entailed capture of higher-quality facial expression information through mixed-token embedding facial expression sequences augmented via various methods into a single data representation, and comprised two modules: spatial and temporal encoders. Further, temporal position embedding, focusing on relationships between video frames, was proposed and subsequently applied to the temporal encoder module. The performance of the proposed algorithm was compared with that of conventional methods on two emotion recognition datasets of video content, with results demonstrating its superiority.
Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity
Authors: Ramamoorthi Yoghitha , Iwabuchi Masashi , Murakami Tomoki , Ogawa Tomoaki , Takatori Yasushi
Published: August 2022

The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS-assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an α-fair utility function, the joint resource allocation and the user scheduling of a RIS-assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. A heuristic is proposed to solve the formulated optimization problem with the derived optimal user scheduling time fractions. Exhaustive simulation results for coverage and throughput of the RIS-assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS-assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems.
Resolution Enhancement for Millimeter-Wave Radar ROI Image with Bayesian Compressive Sensing
Authors: Xie Pengfei , Wu Jianxin , Zhang Lei , Wang Guanyong , Jin Xue
Published: August 2022

For millimeter-wave (MMW) imaging security systems, the image resolution promisingly determines the performance of suspicious target detection and recognition. Conventional synthetic aperture radar (SAR) imaging algorithms only provide limited resolution in active MMW imaging, which is limited by the system. In terms of enhancing the resolution of a region of interest (ROI) image containing suspicious targets, super-resolution (SR) imaging is adopted via Bayesian compressive sensing (BCS) implemented by fast Fourier transform (FFT). The spatial sparsity of MMW ROI images is well exploited with BCS to achieve resolution enhancement without computational cost. Both simulated and measured experiments confirm that the proposed scheme effectively improves the resolution of ROI images.
Science and Hurling: A Review
Authors: Collins Kieran , Reilly Thomas , Malone Shane , Keane John , Doran Dominic
Published: August 2022

Hurling is one of the world’s fastest field sports. Since the last review of science and Gaelic sports in 2008, there has been an increase in sports science provisions across elite and sub-elite cohorts, resulting in increased hurling-specific literature equating to an additional 111 research investigations into the game across all sports science disciplines. The present review aims to provide an updated analysis of the current research on the game and propose recommendations for future research. Overall, intermittent aerobic fitness remains an important physical quality during competition, with a focus on games-based training methodologies within the literature. Within the current review, we provide updated normative data on the running demands, physiological responses, and anthropometric and performance profiles of hurling players. The increased literature across the sport has led to the development of a hurling-specific simulation, that can now be utilised practically in training and research processes for hurling cohorts. Furthermore, the monitoring of internal and external training loads across training and match environments, in addition to response variables such as well-being, appears to have become more prominent, allowing practitioners to design training regimes to achieve optimal dose and response characteristics. Analysing the game from a scientific perspective can allow for more efficient preparatory practices, to meet the specific requirements of players at all age levels. Collaborative research among the various sports science disciplines, is required to identify strategies to reduce the incidence of injury and enhance performance in hurling. The current review provides updated information to coaches and practitioners regarding position-specific physical qualities, and match-play demands that can concurrently support the training process within hurling.
Skills Measurement Strategic Leadership Based on Knowledge Analytics Management through the Design of an Instrument for Business Managers of Chilean Companies
Authors: Faúndez Mauricio Olivares , de la Fuente-Mella Hanns
Published: August 2022

The growth of business intelligence and analytics (BI&A) and technological advancement is having an impact on business dynamics, implying that executives need to adjust their management skills to create value and a sustainable competitive advantage in agile environments. In this research study, a model (LDM–BI&A) consisting of knowledge and skills domains for BI&A leadership has been proposed to measure strategic leadership skills for BI&A business managers in Chilean SMEs. The skills were studied according to their demand (role requirements) and supply (university curricula in Chile). Factorial validity was determined using Confirmatory Factor Analysis, showing that the model satisfactorily fit the data. The instrument proves reliable, showing solid psychometric properties, and contributes to the literature as it has the design and empirical validation of an instrument that measures skills linked to business managers in Chilean SMEs. This will provide support to Human Resources managers on how BI&A leadership skills can be diagnosed, maintained, and developed.
Predicting Pro-Environmental Behaviour amongst Citizens in African Countries: A Cross-National Study amongst Six African Countries
Authors: Ifegbesan Ayodeji P. , Rampedi Isaac T. , Ogunyemi Biodun , Modley Lee-Ann
Published: August 2022

The role of pro-environmental behaviour in environmental care and mitigation of environmental problems is widely recognised. However, most studies on pro-environmental behaviour have focused on populations living in Western and high-income countries and only a few studies are available in developing countries. In this paper, we explored and compared the determinants of pro-environmental behaviour of citizens in six African countries, namely Algeria, Egypt, Ghana, Nigeria, South Africa and Zimbabwe. We examined the relationship between socio-demographic variables and pro-environmental behaviour of citizens within and across these countries using secondary data collected through Wave 6 of the World Value Surveys. The results showed that there were differences and some similarities in pro-environmental behaviour across the selected countries. Factors such as gender, education, social class, membership of environmental organisations and employment status positively correlated with pro-environmental behaviour among the selected respondents. Based on the study findings, recommendations are made within to improve and increase pro-environmental behaviour in the selected countries.
Mountainous SAR Image Registration Using Image Simulation and an L2E Robust Estimator
Authors: Zhang Shuang , Sui Lichun , Zhou Rongrong , Xun Zhangyuan , Du Chengyan , Guo Xiao
Published: August 2022

Synthetic Aperture Radar (SAR) is one of the most widely utilized methods to extract elevation information and identify large-scale deformations in mountainous areas. Homologous points in stereo SAR image pairs are difficult to identify due to complex geometric and radiometric distortions. In this paper, a new approach for mountainous area images is suggested. Firstly, a simulated SAR image and a look-up table based on DEM data are generated by a range-Doppler model and an empirical formula. Then, a point matching RPM-L2E algorithm is used to match images obtained by the simulation and in real-time to indirectly obtain the feature points of the real SAR images. Finally, the accurate registration of mountainous areas in the SAR images is achieved by a polynomial transform. Experimental verification is performed by using the data of mountainous SAR images from the same sensor and different sensors. When the registration accuracy of the method is compared with that of two state-of-the-art image registration algorithms, better outcomes are experimentally shown. The suggested approach can effectively solve the registration problem of SAR images of mountainous areas, and can overcome the disadvantages of poor adaptability and low accuracy of traditional SAR image registration methods for mountainous areas.
Exploring the Key Priority Development Projects of Smart Transportation for Sustainability: Using Kano Model
Authors: Lu Ming-Tsang , Lu Hsi-Peng , Chen Chiao-Shan
Published: August 2022

Many smart transport programs are being carried out despite the fact that new smart transport programs technologies are not yet mature and people’s needs are not fully understood. As a result, many smart transport projects fall into chaos and fail to operate successfully, and can even impede socioeconomic development for sustainability. Therefore, this study suggests that cities should consider first the perceptions of people toward smart transport before they actively implement smart transport projects; this is an indispensable, key step to the smooth development of smart transport. Based on exploratory research, the study explores the procedure of constructing a kano model of smart transportation. A six-stage procedure is developed as primary collected 50 smart transport cases worldwide and then extracted 24 smart transport items. We designed questionnaire contents within the theoretical framework of the kano model, and eventually collected 369 completed questionnaires to determine how smart transport items can be classified under appropriate need attributes. Additionally, we use the customer satisfaction coefficient method to further prioritize the smart transport items, and four methods to prioritize them. Decision-makers can consider prioritization results from using different rules and methods, and reduce the gap between technologies implementation and actual needs.
Analyzing Street Crime Hotspots and Their Associated Factors in Chittagong City, Bangladesh
Authors: Haider Mohammad Ali , Iamtrakul Pawinee
Published: August 2022

Urban street crime (USC) hotspots severely affect the residential and business neighborhood (RBN) areas of any urban center. This study analyzes USC hotspots and identifies the associated risk factors of becoming a USC hotspot in the residential and business neighborhood areas of Chittagong city. Primary and secondary data sources were used, but primary data played a primary role in this study. It was found that male, married, landlord, and middle-income groups of people are more likely to be victimized than the female, unmarried, renters, rich, and no-income groups. More street crime hotspots were found in the residential than in the business neighborhood. The statistical analysis of the logistic regression model for street crime victimization, a hotspot analysis model of a contour map, and a spatial autocorrelation map identified vulnerable locations in the residential and business neighborhood areas where people are frequently victimized by street crime. Qualitative and statistical analysis results show social, economic, geographical, governance, and planning and urban design factors play a vital role in developing USC hotspots in Chittagong city. The study outcomes need to be considered for an integrated approach to monitor and reduce street crime hotspots by policymakers, urban local government, and community leaders in Chittagong city.
Regional Niche and Spatial Distribution of Foreign Investment in China from 2012 to 2021
Authors: Ding Ling , Wu Jinxi , Ma Ziyou , Mai Jialu
Published: August 2022

Strategic positioning is the core issue of strategic management, and regional niche is the core of strategic positioning. Regional niche has important implications in sustainability transition. In this study, the regional niche and spatial distribution of foreign investment in 31 provinces of China from 2012 to 2021 are explored regarding sustainability transition. The results show that: (1) Low fierce competition is important for foreign-investment resources in sustainability transition in general. (2) The gradient of niche-evolution momentum is considerable in sustainability transformation. (3) The spatial echelon distribution of foreign investment is obvious in sustainability transition with a positive spatial-geography correlation. Therefore, in view of the overall space–time development and political layout of foreign investment in emerging industrialized countries such as China in the future, this study has important practical significance. It proposes countermeasures for policy-makers and managers to promote the expansion, evolution, and coordination of foreign investment in regional resources. The conclusion is helpful for China and other emerging industrial countries to successfully realize the space–time layout of regional niche, through foreign investment, and improve their open capabilities of global sustainable development.
Long-Term COVID: Case Report and Methodological Proposals for Return to Work
Authors: Malta Ginevra , Cirrincione Luigi , Plescia Fulvio , Campagna Marcello , Montagnini Claudia , Cannizzaro Emanuele
Published: August 2022

Almost two years after the beginning of the SARS-CoV-2 pandemic, the knowledge of which in the infectious and therapeutic spheres is constantly evolving, attention paid to the medicolegal aspects linked to this emergency phenomenon has mainly focused on the liability implications falling on healthcare personnel. With regard to the medicolegal assessment of the outcomes of COVID-19 illness, although it is a procedure that is commonly used, and although references in the assessment tables in force have been adhered to, a specific assessment protocol has not been standardized that takes into account, from an objective point of view, the degree of severity of the long-term residual outcomes and their impact on the social and working lives of subjects. This shortcoming appears to be attributable to the immediate need to categorize the results of COVID-19, but, in our opinion, it deserves an in-depth study and protocols to enable evaluation committees to draw up an assessment as precisely as possible and that is free of gaps, which could be the subject of legal disputes. The aim of the present work, in light of a worldwide problem, is to arrive at specific and univocal evaluation criteria for COVID-19 disease outcomes, applicable in different operational contexts of reemployment.
The Impact of High-Speed Rail and Central Cities on Enterprise Financing Costs
Authors: Luo Shuai , Yang Xinhua , Li Qicheng
Published: August 2022

The study of the impact of the high-speed railway (HSR) on enterprise financing costs (EFCs) contributes to understanding the economic impact of transportation facilities, by analyzing the coordinated development of the regional economy and studying the influencing factors in enterprise operation. By using data of Chinese listed companies from 2008 to 2019, this paper analyzes the impact of HSR on EFCs and examines the role of central cities (CCs) in the whole process through methods of the DID model, panel threshold model, PSM-DID, parallel trend test and so on. The research results are as follows: first, HSR led to a significant decrease in the level of corporate debt financing. The regression coefficient of HSR is −0.002, which is significant at a 5% level. Second, there exists a heterogeneous effect of HSR on CCs. Mid-region enterprises suffered more than small enterprises, low-growth enterprises and enterprises with a low return on assets. Third, HSR affects EFCs, which leads to the diffusion effect of CCs, resulting in an increase in EFCs in CCs and a decrease in non-CCs. It was found that there is a single threshold of the panel threshold regression based on per capita GDP, and the regression coefficient of HSR below the threshold is −0.001, which is significant at the 5% level. Additionally, the regression coefficient of HSR above the threshold is 0.002, which is significant at the 1% level. The interaction term and group regression both also confirm the above conclusion. Fourth, the impact of HSR on EFCs is limited by geographic distance. When the geographic distance between a non-CC and a single CC is greater than 500 km, and the total distance between a non-CC and four CCs is greater than 3500 km, the effect of HSR is remarkable. The above conclusions prove the significant impact of HSR on EFCs and reveal the role of CCs and geographic distance in this process. These provide new ideas and evidence for corporate financing management as well as planning for urban development and the HSR network.
Paving the Way to Green Status for Nuclear Power
Authors: Pershukov Viacheslav , Artisyuk Vladimir , Kashirsky Andrey
Published: August 2022

The paper considers a way to bring nuclear power into the category of “green” energy technologies; thus advertising its critical role in achieving the sustainable development goals adopted by the UN in 2015, and presents an option of nuclear power development based on a new technological platform (NTP) with two pillars: closed nuclear fuel cycle (CNFC), and fast reactors (FR). Provisions are formulated to break through the skepticism of nuclear power opponents. The “PRORYV” (the Russian equivalent for “break-through”) project is focused on proving the industrial feasibility of the closed fuel cycle on-site of the NPP with fast reactor, thus giving the technological opportunity to establish nuclear energy systems environmentally friendly and free from the risk of proliferation of nuclear weapons. Such a nuclear energy system could contribute significantly in combating both looming energy crises and climate change.
Permeability of Waterfronts—Contemporary Approach in Designing Urban Blue Spaces
Authors: Dubinina Anastasiia , Wawrzyńska Aleksandra , Krośnicka Karolina A.
Published: August 2022

The constant struggle with rising sea levels and flood hazards has resulted in the change of the paradigm in shaping urban waterfronts towards increasing their permeability and creation of urban blue spaces. The aim of the paper was to indicate a new approach in designing public spaces at the sea–land interface by presenting a comparative study of the design solutions used in case of the four selected case studies: the Sea Organs in Zadar (Croatia), Norwegian National Opera and Ballet in Oslo (Norway), the Coastal Public Sauna in Helsinki (Finland) and Tel Aviv’s Central Promenade (Israel). The studied examples take into account the permeability of waterfronts (understood as a feature of the edge between water–land consisting of being soft and permeable). The authors decided to use the case study method as the main approach, analyzing such elements as: the site’s location and urban context, features of urban and architectural design (with usage of graphic methods and a qualitative description), and the land–water edge type (defined according the existing typologies). The study proved, that in recent years the designers have started to replace the vertical quay walls, which create a “rigid” water–land border, with multi-level solutions having a high degree of permeability for water.
Research on the Strategy of Industrial Structure Optimization Driven by Green Credit Distribution
Authors: Ding Guoping , Hua Jingqian , Duan Juntao , Deng Sixia , Zhang Wenyu , Gong Yifan , Sun Huaping
Published: August 2022

Credit is an important means to promote economic development, while green credit is conducive to the sustainable development of industry. This paper aims to build a multiple linear regression model and a dynamic panel data GMM estimation model to analyze the important factors that affect the optimization of the industrial structure. We then use an analytic hierarchy process to explore the relationship between green credit and industrial optimization. We compare this with the optimization rate of the industrial structure according to the real data, and then obtain the effectiveness of the hierarchical analysis of the three major industries in the eastern, central and western regions. Finally, neural networks are used to forecast the total amount and distribution of green credit in 2021. The final results show that there are regional and industrial differences in the influence of green credit on industrial structure optimization, and in the process of using green credit to promote the optimization and upgrading of industrial structure.
Significance of Thermal Phenomena and Mechanisms of Heat Transfer through the Dynamics of Second-Grade Micropolar Nanofluids
Authors: Awan Aziz Ullah , Ahammad N. Ameer , Ali Bagh , Tag-ElDin ElSayed M. , Guedri Kamel , Gamaoun Fehmi
Published: August 2022

Due to their unique microstructures, micropolar fluids have attracted enormous attention due to their potential for industrial application, including convective heat and mass transfer polymer production and the rigid and random cooling of particles for metallic sheets. In this context, a micropolar second-grade fluid flow over a vertical Riga plate is investigated for hidden microstructures. The novelty of the flow model allows us to explore the significance of Brownian motion and thermophoresis on the dynamics of non-Newtonian fluid. A mathematical model is developed under the flow assumptions for micropolar second-grade fluid over a vertical Riga plate of PDEs, reducing them into ODEs by invoking similarity techniques. The acquired system of non-linear ODEs is elucidated numerically using bvp4c methodology. Furthermore, comparative tables are generated to confirm the bvp4c technique, ensuring the accuracy of our numerical approach. This rheological study of micropolar second-grade fluid suggests that temperature distribution increases due to variations in the micropolar parameter (K), Eckert number (Ec), and the thermophoresis parameter (Nt), and the concentration distribution (Φ(η)) keeps rising against the boosting values of Brownian motion (Nb); however, the inverse trend is noted against thermophoresis (Nt).
Building Carbon Emission Scenario Prediction Using STIRPAT and GA-BP Neural Network Model
Authors: Zhang Sensen , Huo Zhenggang , Zhai Chencheng
Published: August 2022

As a major province of energy consumption and carbon emission, Jiangsu Province is also a major province of the construction industry, which is a key region and potential area for carbon emission reduction in China. The research and prediction of carbon emission in the construction industry is of great significance for the development of low-carbon policies in the construction industry of other cities. The purpose of this paper is to study the influencing factors of the whole life cycle carbon emissions of buildings in Jiangsu Province, and to predict the carbon emissions of buildings in Jiangsu Province based on the main influencing factors. This paper uses the energy balance sheet splitting method, STIRPAT model, gray correlation method and GA-BP neural network model to study and predict the carbon emissions of construction industry in Jiangsu Province. The research results show that the resident population, urbanization rate, steel production, average distance of road transportation, and labor productivity of construction enterprises have a catalytic effect on construction carbon emissions; GDP per capita and added value of tertiary industry have a suppressive effect; construction carbon emissions reached the historical peak in 2012; the prediction results show that the future construction carbon emissions in Jiangsu province generally show a decreasing trend. The research results of this paper provide a possibility to refine the study of construction carbon emission, and also provide a basis and guidance for subsequent research on construction carbon emission.
Objective and Perceived Risk in Seismic Vulnerability Assessment at an Urban Scale
Authors: Fischer Eliana , Biondo Alessio Emanuele , Greco Annalisa , Martinico Francesco , Pluchino Alessandro , Rapisarda Andrea
Published: August 2022

The assessment of seismic risk in urban areas with high seismicity is certainly one of the most important problems that territorial managers have to face. A reliable evaluation of this risk is the basis for the design of both specific seismic improvement interventions and emergency management plans. Inappropriate seismic risk assessments may provide misleading results and induce bad decisions with relevant economic and social impacts. The seismic risk in urban areas is mainly linked to three factors, namely, “hazard”, “exposure” and “vulnerability”. Hazard measures the potential of an earthquake to produce harm; exposure evaluates the size of the population exposed to harm; and vulnerability represents the proneness of considered buildings to suffer damages in case of an earthquake. Estimates of such factors may not always coincide with the perceived risk of the resident population. The propensity to implement structural seismic improvement interventions aimed at reducing the vulnerability of buildings depends significantly on the perceived risk. This paper investigates the difference between objective and perceived risk and highlights some critical issues. The aim of the study is to calibrate opportune policies, which allow addressing the most appropriate seismic risk mitigation options with reference to current levels of perceived risk. We propose the introduction of a Seismic Policy Prevention index (SPPi). This methodology is applied to a case-study focused on a densely populated district of the city of Catania (Italy).
Study on Low-Carbon Technology Innovation Strategies through Government–University–Enterprise Cooperation under Carbon Trading Policy
Authors: Wang Junwu , Song Yinghui , Li Mao , Yuan Cong , Guo Feng
Published: August 2022

This paper focuses on developing low-carbon technology (LCT) innovation in traditional enterprises under carbon trading policies. The Hamilton–Jacobi–Berman equation quantitatively investigates the coordination mechanism and optimal strategy of LCT innovation systems in conventional industries. A three-way dynamic differential game model is constructed to analyze three cases: the Nash disequilibrium game; the Stackelberg master–slave game; and the cooperative game with the optimal effort of universities, traditional enterprises, and local government, the optimal benefits of the three parties, the region, and the regional LCT level. The results are as follows: (1) by changing the government subsidy factor, carbon trading price, and carbon trading tax rate, the optimal effort of universities and traditional enterprises can be significantly increased; (2) cost-sharing contracts do not change the level of effort of local government to manage the environment, and the use of cost-sharing agreements can change the status of action of universities and enterprises; (3) the optimal effort, optimal benefit, and total system benefit of the three parties and the level of LCT of the industry in the cooperative game are better than those in the non-cooperative case. The combined game achieves the Pareto optimum of the system. The study will contribute to both sustainable business development and environmental sustainability.
Automation of Negative Infrastructural Externalities Assessment Methods to Determine the Cost of Land Resources Based on the Development of a “Thin Client” Model
Authors: Bykowa Elena , Skachkova Maria , Raguzin Ivan , Dyachkova Irina , Boltov Maxim
Published: August 2022

This article discusses the need to transform real estate valuation methods. It is associated with the problems of obtaining unreliable results affecting the subsequent adoption of management decisions. As an important element of land plots assessment, the authors define the Negative Infrastructural Externalities arising from the presence of infrastructure and other regime-forming facilities. These externalities represent the loss of title holders due to the encumbrances arising from the use of land plots. The world community (and the authors as part of it) sees one of the transformation methods in the automation of the evaluation process. Therefore, the purpose of this study is to develop a mechanism of automating the Negative Infrastructural Externalities assessment process in the conditions of a non-existent and weak market activity of land relations. Modern trends dictate the saving of hardware, labor and money resources; in this connection, the methods of Negative Infrastructural Externalities assessment are implemented on the basis of the “thin client” technology. The research is based on the following methods: the analytical method is used to perform a critical analysis of the problem area and to substantiate the research topic’s relevance; methods of object-oriented programming and methods of modular programming (Cowan’s axiom of modularity) are used as tools for developing the web application logic, as well as the interaction of its individual elements; the attribute-driven design approach is used in the creation of software architectures. The result of the study is the developed and substantiated architecture of a web application for assessing negative infrastructural external factors in determining the land value, the implemented modular structure of the specified web application and the developed conceptual model of the database. The practical implementation of the listed proposals is made by means of the Python programming language. The advantage of the created automated system is the possibility of multi-disciplinary use of the expert assessment approach when changing the settings.
Exploring Determinants of Tourists’ Ethical Behavior Intention for Sustainable Tourism: The Role of Both Pursuit of Happiness and Normative Goal Framing
Authors: Ko Eunhee Erica , Cho Minho
Published: August 2022

This study explored variables that determine outbound Korean tourists’ ethical behavior intention during their visits of Southeast Asian countries and analyzed the influencing relationship between them in an integrated manner. The results from the partial least squares path modeling of the R statistical program demonstrate that the pursuit of hedonic and eudaimonic motives plays a positive role in activating normative goal framing which supports tourists’ ethical behavior intention. This study therefore empirically proved the important roles of both the pursuit of happiness in daily life and normative goal framing as motivators that enhance ethical behavior intention at tourist destinations to achieve the goal of sustainable tourism after the pandemic.
Revaluation of Local Waste through an Ecotechnologies Strategic Plan: A Case Study with Digesters
Authors: Flores-Nieves Mariana Montserrat , Soto-Zarazúa Genaro M. , Rico-García Enrique , Zamora-Castro Sergio , Macías-Bobadilla Gonzalo , Hernández-López Ma Sandra , Sánchez-Gutiérrez Arantza Elena
Published: August 2022

In Mexico, the accelerated and unplanned growth of population causes the increment in informal facilities, complicating access to essential services such as adequate sanitation and organic waste management, where the most affected are usually the vulnerable population. The Mexican government has implemented programs and support to encourage the use of ecotechnologies and thus provide alternatives to improve their living conditions by taking advantage of local resources and waste. However, these programs and supports lack planning, creating little interest from users. This research proposes an acceptance strategy for the integration of ecotechnologies that adapt to the lifestyle of populations that need an alternative for their method of sanitation and organic waste management. The strategy is mainly based on a course of action that operates with four main lines of intervention. It was executed as a practical exercise with biodigesters, in the Mexican community of La Trinidad, in the municipality of Tequisquiapan, Querétaro. With the help of the strategy, important factors for the end-user were identified that must be considered when integrating one ecotechnology into the population. In general terms, the strategy showed an improvement in sanitation and organic waste management and a greater acceptance of biodigesters as an alternative of use.
Investigating the Effect of Network Traffic Signal Timing Strategy with Dynamic Variable Guidance Lanes
Authors: Zhao Fei , Fu Liping , Pan Xiaofeng , Kwon Tae J. , Zhong Ming
Published: August 2022

This paper aims to investigate the effect of network signal timing strategy with dynamic variable guidance lanes based on a two-step approach, where the first step is an interactive traffic signal optimization model for each single interaction (e.g., lane allocation plans, cycle length) in the network, and the second refers to network signal control (e.g., split, off-sets). The optimization problem in the first step is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-ΙΙ), and the network signal control problem in the second step is solved through SYNCHRO. To verify the effect of dynamic variable guidance lanes and also the reliability and validity of the proposed approach, a numerical case study is carried out. The results show that the average vehicle delay in the entire road network was reduced by 25.06% after optimization using the proposed model. Moreover, the sensitivity of influencing factors of the proposed model is also analyzed. The results show that when the traffic flow is increased by 60% of the original traffic flow, the optimization effect of the model is more significant. However, when the lane capacity is more than 1300 pcu/h, the vehicle delay will increase slowly. To sum up, this method can improve the regional traffic efficiency of the traffic-stressed lanes and further promote the full utilization of space-time resources of the road network.
Slope Instability Analysis in Permafrost Regions by Shear Strength Parameters and Numerical Simulation
Authors: Zhou Bao , Zhang Yingli , Wei Sailajia , Wang Zhongfu , Zhu Wenfeng , Xue Zhijia
Published: August 2022

With the onset of global warming, the environment has profoundly changed. The melting of ice and slope instability were widely observed in the permafrost regions of the Qinghai–Tibet Plateau, which has destroyed infrastructure and threatened people’s safety. For this study, we conducted a direct shear test, monitored field temperature, and performed a numerical simulation to explore the mechanism of slope instability in the permafrost regions of the Qinghai. The results show that the shear strength of the permafrost soil decreased with the increases in water content and thawing condition. Moreover, the thawing depth of the slopes increased with the rising temperature. From the temperature monitoring data and field observations, cracks and slope instability phenomena were observed in the Qinghai and occurred with the thawing of the permafrost soil. The safety of slopes in the permafrost regions decreased with increases in the temperature, slope gradient, and pore water pressure and with decreases in the shear strength parameters. In addition, the sliding interface had a direct correlation with the freeze–thaw interface, which is a migrated interface of water in liquid form. Therefore, the thawing of the permafrost soil causes the shear strength to decrease and pore water pressure to increase, which leads to slope instability in the permafrost regions of the Qinghai.
Effects of Individual and Block Freezing on the Quality of Pacific Oyster (Crassostrea gigas) during Storage under Different Pretreatment Conditions
Authors: Tsai Hsin-Shan , Hsiao Yu-Tien , Weng Yih-Ming
Published: August 2022

In this study, a series of pretreatments, including ice-glazing, polyphosphate impregnated, and both ice-glazing and polyphosphate impregnated, were employed to pretreat shucked oysters in order to explore the optimal processing conditions for long-time storage. The effect of repeated freezing-thawing cycles on the quality of oysters was evaluated. Several quality indicators were used to investigate the effects of pretreatment. For the VBN (volatile salt-based nitrogen) value, the lowest value was 9.1 ± 0.2 of BPG (block oyster with polyphosphate impregnated and ice-glazing), which was significantly lower than 9.6 ± 0.2 of IPG (individual oyster with polyphosphate impregnated and ice-glazing). In terms of drip loss, there was no significant difference between the IPG (21.0 ± 0.2%) and the BPG (20.8 ± 0.2%). In addition, the highest WHC% (water holding capacity) was IPG (65.5 ± 0.5%) which was slightly lower than BPG (67.6 ± 0.6%). As compared to the experimental control, the IPG and BPG had the best appearance and color. In terms of TAPC (total aerobic plate count), with the increase of freezing storage time, each group showed a slight downward trend, but the difference was not statistically significant. After repeated freezing-thawing of block frozen oysters, there were significant differences in drip loss, WHC, and cooked taste with the increasing number of times, and there was a trend of deterioration (p < 0.05). Repeated freezing and thawing can seriously degrade the quality of oysters, so individual freezing (especially IPG) should be the most appropriate processing method.
Nonlinear Impact of Circulation-Industry Intelligentization on the Urban–Rural Income Gap: Evidence from China
Authors: Meng Haoyun , Deng Peidong , Zhang Jinbo
Published: August 2022

Integrating informatization into the circulation industry has led to the concept of circulation-industry intelligence. By reducing transportation costs and increasing total factor productivity, the incomes of rural-area residents can be improved; a new pattern of regional economy can be established; urban, rural, social, and economic development can become more coordinated; and social sustainable development can be promoted. In this study, we used China’s provincial panel data corresponding to the 2007–2019 period to measure the intelligence index of the circulation industry in each region and determine the factors that affect the urban–rural income gap; thereafter, we conducted comparative analyses. Further, a fixed-effects model was established based on the theory of agglomeration and diffusion effects to analyze the relationship between these two variables. Our analysis identified innovation investment as a significant intermediary mechanism. The robustness of this finding was verified by substituting variables and controlling for endogeneity. Thus, the effect was shown to be regionally heterogeneous. This study innovatively integrated informatization into the circulation industry, and the results obtained provide a reference for formulating transportation infrastructure as well as informatization strategies for promoting urban–rural coordination and sustainable development globally.
Study on Comparing the Performance of Fully Automated Container Terminals during the COVID-19 Pandemic
Authors: Kim Bokyung , Kim Geunsub , Kang Moohong
Published: August 2022

Major ports worldwide suffered from various problems such as labor shortage, port congestion, and global supply chain disruptions during COVID-19. To ensure stable operations of ports in such scenarios, one option is to adopt fully automated terminals. This study aimed at evaluating the performance of fully automated terminals compared with that of non-fully automated ones during the disrupted logistics due to coronavirus. Four ports that simultaneously operate both fully and non-fully automated terminals were selected. The performance of the target terminals was measured based on quantitative factors: throughput, number of ship arrivals, and berthing time. The results showed that the fully automated container terminals present better operational performance than the non-fully automated terminals. The former achieved large increments in the throughput, small decreases in the berthing time per ship, and increases in the number of ship arrivals. Moreover, there were economic benefits, revealing that the total terminal profit at the fully automated terminals was significantly increased, whereas that at the non-fully automated ones decreased based on berthing times. Therefore, fully automated terminals can be considered as alternatives for responding flexibly and stably during crises such as COVID-19.
Numerical Simulation of Fracture Propagation during Refracturing
Authors: Wang Daobing , Dahi Taleghani Arash , Yu Bo , Wang Meng , He Chunming
Published: August 2022

Hydraulic fracturing is repeated in some unconventional wells after production since the initial fracturing treatment. Due to prior production, the stress field around the existing fractures possibly rotates, and this impacts the refracturing operation. In this study, an extended finite element model (XFEM) including junction enrichments of intersecting fractures was proposed to simulate fracture propagation during refracturing in the cemented fractured reservoirs. In the XFEM model, a lubrication equation coupling both tangential and normal flow in hydraulic fractures (HFs) was used to describe the fluid flow behavior within the fractured elements, and the Newton-Raphson method was used to solve the nonlinear fluid–solid coupling system of the refracturing model. The effects of approaching angle, stress anisotropy, and production time were discussed. The results showed that the effects of these factors on improvement of fracture complexity during refracturing depend on the reservoir parameters and the stress field. The characteristics of the injection pressure curves during refracturing were analyzed.