bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Impact of Different Port Governances on Smart Port Development Strategy in Taiwan and Spain
Authors: Lin Sheng-Che , Chang Hsien-Kuo , Chung Ying-Feng
Published: July 2022

With the rapid development of new technologies, such as automation, big data, and artificial intelligence, a port that utilizes these technologies can significantly improve its operational efficiency and make it economically more competitive. Despite its increasing importance, there is no standard definition of a smart port, resulting in each country having its own smart port development strategy. In this study, we explore how varied port governance of port authorities may impact the smart port development strategy. First, we established a set of evaluation criteria, using the Borda count and fuzzy analytic hierarchy process, to obtain the key indicators for the development of smart ports in Taiwan. Then, we compared the preferred indicators of Taiwan’s smart port development strategy with those of Spanish ports. An obvious difference in this ranking comparison is found. This indicates that Taiwan’s strategy focuses on optimizing maritime safety, while Spain’s strategy focuses on improving operational economics. Finally, we analyzed the differences between the smart port development strategies of these two countries using the latest port governance classification table. The results of the above analysis are also verified by comparing the differences in port legislation between them. It turns out that the private sector is deeply involved in the operation of ports in Taiwan compared with Spain. Our main contribution lies in providing a clear pathway for developing a smart port in Taiwan in the future and investigating the reasons for different smart port development strategies in different countries.
Natural Language Processing Methods for Scoring Sustainability Reports—A Study of Nordic Listed Companies
Authors: Gutierrez-Bustamante Marcelo , Espinosa-Leal Leonardo
Published: July 2022

This paper aims to evaluate the degree of affinity that Nordic companies’ reports published under the Global Reporting Initiatives (GRI) framework have. Several natural language processing and text-mining techniques were implemented and tested to achieve this goal. We extracted strings, corpus, and hybrid semantic similarities from the reports and evaluated the models through the intrinsic assessment methodology. A quantitative ranking score based on index matching was developed to complement the semantic valuation. The final results show that Latent Semantic Analysis (LSA) and Global Vectors for word representation (GloVE) are the best methods for our study. Our findings will open the door to the automatic evaluation of sustainability reports which could have a substantial impact on the environment.
State-Level Urban Agglomeration and Enterprise Innovation: A Quasi-Natural Experiment
Authors: Zhao Kai , Huang Huahua , Wu Wanshu
Published: July 2022

Based on the data of listed enterprises in China from 2007 to 2019, this study uses the quasi-natural experiment method (staggered DID) to explore the actual impact of the establishment of state-level urban agglomeration on the innovation activities of enterprises and the heterogeneous impact caused by regional differences. It is found that state-level urban agglomerations play the role of “incubator” for enterprise innovation, and the establishment of urban agglomerations can not only effectively encourage enterprises to increase R&D investment, but also greatly increase the quantity of innovation output of enterprises. It is worthwhile to note that the establishment of state-level urban agglomerations has no significant impact on R&D investment and the innovation output of enterprises in the eastern region. As far as the western region is concerned, the incentive effect of the establishment of urban agglomeration on the innovation output of enterprises is significantly positive at 1% significance level, while the incentive effect on the R&D investment of enterprises is positive but not statistically significant.
The Influence of Environmental and Non-Environmental Factors on Tourist Satisfaction in Halal Tourism Destinations in West Sumatra, Indonesia
Authors: Zulvianti Nora , Aimon Hasdi , Abror Abror
Published: July 2022

This study aims to investigate the influence of environmental and non-environmental factors on tourist satisfaction in halal tourism destinations in West Sumatra. The environmental factor is perceived environmental value. Meanwhile, non-environmental factors are halal-friendly destination performance, sustainability tourism development, and halal destination image. The survey was conducted by distributing questionnaires to 690 respondents who visited halal tourism destinations in West Sumatra. It was analyzed by using the Structural Equation Modeling (SEM)—Partial Least Square (PLS). The results indicate environmental factors (perceived environmental values) and non-environmental factors (halal-friendly destination performance, sustainable tourism development, and halal destination image influence tourist satisfaction. Moreover, sustainability tourism development mediates the effect of perceived environmental value on tourist satisfaction. However, sustainability tourism development does not mediate the effect of halal-friendly destination performance on tourist satisfaction. Meanwhile, the halal destination image does not moderate the effect of sustainability tourism development on satisfaction. Thus, our research can be used as a reference for tourist destination managers to increase tourist satisfaction by maintaining and managing the tourist destination environment properly.
Evaluation of the Suitability of Smart Health Products for Aging Based on the IIVAHP-CRITIC Model: A Case Study of Smart Health Kiosk
Authors: Lu Ning , Li Yefei , Xu Bochu
Published: July 2022

In the global situation of an aging population, the evaluation of the suitability of smart health products for aging is very important in order to achieve sustainable development goals. However, few evaluation methods have been adopted for smart health products for older individuals. An objective and comprehensive evaluation system and evaluation methods need to be established to guide the design of smart health products. In this study, a Smart Health Kiosk (SHK) was used as an example, and an index system was established for the evaluation of the suitability for aging based on the influencing factors from four dimensions. To address the problem that it is difficult to quantify the subjective and objective weights in the evaluation, this study proposes a method of evaluating suitability for aging based on the combination of the Improved Interval-Valued Analytic Hierarchy Process and the Criteria Importance Though Intercrieria Correlation (IIVAHP-CRITIC) method. The results show that the method integrates the influence of subjective and objective weights on the evaluation and avoids the limitations of a single evaluation. It takes into account the relationship between the various levels of indicators and the subjective and objective indicators. Weights calculated by the IIVAHP-CRITIC method help to better assess the objectivity and validity of the design solutions. This evaluation method can effectively reflect the related attributes of each element in the aging-suitability design stage of smart health products. The evaluation results help to improve the quality and ergonomic comfort of aging products, and can effectively reduce the occurrence of design problems.
Types, Modes and Influencing Factors of Urban Shrinkage: Evidence from the Yellow River Basin, China
Authors: Ding Xiaoming , Yu Shangkun , Miao Yi , Wang Chengxin , Jin Zhenxing
Published: July 2022

Following the appearance of urban shrinkage in Western countries, scholars have taken note of increasing amounts of urban shrinkage with significant regional characteristics in China in recent years. Focusing on the Yellow River Basin, this study comprehensively measured prefecture-level and county-level city shrinkage based on China’s fifth, sixth and seventh national census data. Furthermore, the spatiotemporal patterns, types and modes of urban shrinkage were analyzed, and the factors influencing urban shrinkage were explored using a multiple linear regression model and a sorting model. The study results show that the number of shrinking cities and the shrinking degree significantly increased at the prefecture and county levels in the last 20 years. The identified shrinking cities are concentrated in the upper and middle reaches of the river basin, spatially configured around major cities and along the high-speed railway line. The regional pattern shows a typical “core–periphery” characteristic. Peripheral shrinkage is the main mode in which cities shrink. The strength and speed of economic development and industrial transformation positively affect urban shrinkage; the ageing degree, high-speed railway opening and other factors negatively affect urban shrinkage.
A Research Framework for Sustainable Digital Innovation: Case Studies of Japanese Firms
Authors: Park Young Won , Hong Paul
Published: July 2022

Today’s competitive and highly volatile environment calls for a new kind of flexibility and adaptability. Limited studies are available that examine how firms achieve both speed and creativity requirements in this digital era. In view of the rare empirical studies on real-world cases that apply rigorous research methods for sustainable digital innovation (SDI), this research investigates the key strategic requirements of organizational agility and flexibility for SDI. The research framework defines four types of innovators. This study used the benchmark tool to assess the status of their innovation effectiveness. This research framework is useful for firms to classify, assess, and evaluate their innovation type. The study’s findings also suggest the road map for future strategic goals. This theoretical framework illustrates the causal relationship between Japanese-style digital innovation and the firms’ sustainable competitive advantage. This model might be extended to other firms in different contexts (e.g., Korea, India, USA, Brazil, and a host of other countries). The theoretical and practical implications are discussed for future research.
Multinomial Cross-Sectional Regression Models to Estimate and Predict the Determinants of Academic Performance: The Case of Auditor Accountant of the Pontifical Catholic University of Valparaíso
Authors: de la Fuente-Mella Hanns , Campos-Espinoza Ricardo , Lay-Raby Nelson , Lamelés-Corvalán Omar , Pino-Moya Mario , Ramírez-Molina Reynier
Published: July 2022

The debate on the primary cross-curricular skills or fundamental competencies that must be improved in higher education has increased in the last few years. This is especially important in the new distant learning environments, which bring new challenges to the educational process. Econometric models have been designed to explain the students’ academic performance, which has been measured using their qualifications average, the number of failed subjects, passed subjects, and withdrawn subjects, and the level of progress, among other indicators, to try to understand the influence of variables such as students’ self-esteem, reading comprehension, English proficiency level, and performance in a mathematics-related subject on the students of accountant auditor program from Pontificia Universidad Católica de Valparaiso. Students were asked to fill in a questionnaire to collect data on the psychological and pedagogical variables, while the socio-economic and socio-demographic data were collected from the university. The results have shown that the most significant variables in the development level of this skill type are socio-demographic and socio-economic characteristics. Some of the psychological and pedagogical variables that have, to a lesser degree, some influences are self-regulation in the learning process and the self-perception of anxiety levels. Lastly, some recommendations to intervene in the students’ learning process are presented with the objective of achieving a higher level of development in this type of competences.
An Analysis of the Learning Effects and Differences of College Students Using English Vocabulary APP
Authors: Guo Haiyan , Li Zhigang
Published: July 2022

With the gradual popularization of mobile learning, it has become a trend for college students to use learning applications (APPs) for learning, but the learning effect has always been a concern. Since college students have different learning purposes, strategies, skills, and habits, responses to these differences have been an urgent problem. This paper takes college students using an English vocabulary APP to study as the survey object. It sets up the influencing factors model of the English vocabulary learning effect based on UTAUT2. Then, we analyzed the factors influencing the learning effect of using an English vocabulary APP and studied its mechanism. The results show that on the one hand, the influence degree of influencing factors is habit, facilitation condition, price value, effort expectancy, and performance expectancy from high to low, and all the above factors have a significant positive impact on the learning effect of college students using English vocabulary APP. On the other hand, gender, grade, and major have a moderating effect on English vocabulary learning, and there are differences among different genders, grades, and majors. Finally, suggestions are put forward from the perspective of APP construction and students’ differences to enhance and improve the learning effect of English vocabulary.
Integration of Solar Photovoltaic Systems into Power Networks: A Scientific Evolution Analysis
Authors: Elomari Youssef , Norouzi Masoud , Marín-Genescà Marc , Fernández Alberto , Boer Dieter
Published: July 2022

Solar photovoltaic (PV) systems have drawn significant attention over the last decade. One of the most critical obstacles that must be overcome is distributed energy generation. This paper presents a comprehensive quantitative bibliometric study to identify the new trends and call attention to the evolution within the research landscape concerning the integration of solar PV in power networks. The research is based on 7146 documents that were authored between 2000–2021 and downloaded from the Web of Science database. Using an in-house bibliometric tool, Bibliometrix R-package, and the open-source tool VOSviewer we obtained bibliometric indicators, mapped the network analysis, and performed a multivariate statistical analysis. The works that were based on solar photovoltaics into power networks presented rapid growth, especially in India. The co-occurrence analysis showed that the five main clusters, classified according to dimensions and significance, are (i) power quality issues that are caused by the solar photovoltaic penetration in power networks; (ii) algorithms for energy storage, demand response, and energy management in the smart grid; (iii) optimization, techno-economic analysis, sensitivity analysis, and energy cost analysis for an optimal hybrid power system; (iv) renewable energy integration, self-consumption, energy efficiency, and sustainable development; and (v) modeling, simulation, and control of battery energy storage systems. The results revealed that researchers pay close attention to “renewable energy”, “microgrid”, “energy storage”, “optimization”, and “smart grid”, as the top five keywords in the past four years. The results also suggested that (i) power quality; (ii) voltage and frequency fluctuation problems; (iii) optimal design and energy management; and (iv) technical-economic analysis, are the most recent investigative foci that might be appraised as having the most budding research prospects.
Applying Green Human Resource Practices toward Sustainable Workplace: A Moderated Mediation Analysis
Authors: Chreif Maya , Farmanesh Panteha
Published: July 2022

The significant need to achieve business sustainability calls for a new business perspective grounded on leaders’ abilities and the effective execution of green human resource management (GHRM). This study aims to emphasize the role of ethical leadership and GHRM in moving organizations toward sustainability. GHRM supports companies to match their corporate strategies to the environment mainly in the presence of ethical leaders who can walk the talk and the provision of adequate practices and training by HRM to foster a working environment, where employees can exhibit creativity, passion, and positive behaviors towards sustainability. Specifically, this research studies the impact of ethical leaders via GHRM and harmonious environmental passion on employees’ green behaviors using a quantitative method in which a dyadic approach (supervisor–employee) was employed to collect data from two sources through a structured questionnaire from non-profit organizations in Lebanon. The research hypotheses were tested using Partial Least-Squares–Structural Equation Modeling (PLS-SEM). The results showed a significant impact of ethical leadership on employees’ green behaviors. In addition, GHRM and harmonious environmental passion mediated the relationship between ethical leadership and employees’ green behaviors. Besides, it was noticed that green creativity strengthened the association between ethical leadership and GHRM, while a psychological green climate strengthened the association between GHRM and employees’ green behaviors. The study has practical implications for leaders and policymakers who are apprehensive about business sustainability.
Performance of Poly(caprolactone) (PCL) as an Impact Modifier for Polystyrene (PS): Effect of Functionalized Compatibilizers with Maleic Anhydride and Glycidyl Methacrylate
Authors: de Souza Morais Dayanne Diniz , Luna Carlos Bruno Barreto , Bezerra Elieber Barros , de França Danyelle Campos , Araújo Edcleide Maria , do Nascimento Emanuel Pereira , de Oliveira Amanda Dantas , de Mélo Tomás Jefferson Alves
Published: July 2022

In this work, the copolymers ethylene-glycidyl methacrylate (E-GMA), ethylene methyl methacrylate-glycidyl methacrylate (EMA-GMA), and styrene-(ethylene-butylene)-styrene grafted with maleic anhydride (SEBS-g-MA) were used to compatibilize polystyrene (PS)/poly(caprolactone) (PCL) blends. The blends were processed in a co-rotating twin-screw extruder and injection molded. Samples were investigated by torque rheometry, capillary rheometry, impact strength, tensile strength, heat deflection temperature (HDT), dynamic-mechanical thermal analysis (DMTA), thermogravimetry (TG), and scanning electron microscopy (SEM). Torque rheometry indicated that glycidyl methacrylate functional groups and maleic anhydride groups interact with PCL. Capillary rheometry evidenced that at shear rates lower than 10,000 s−1, the PS/PCL/SEBS-g-MA blends presented the highest apparent viscosity among the blends. Such behavior was possibly due to the good interaction between SEBS-g-MA and the PS and PCL phases. Consequently, the properties of impact strength, elongation at break, tensile strength, and elastic modulus were improved by 30%, 109%, 33.8%, and 13.7%, respectively, compared with the non-compatibilized PS/PCL system. There was a reduction in the HDT of all blends compared with neat PS, given the elastomeric characteristics of PCL and compatibilizers. The DMTA results revealed two independent peaks in the blends (one around −53 °C concerning the PCL phase and another at 107 °C related to PS), confirming their immiscibility. The PS/PCL/SEBS-g-MA blends showed higher morphological stability, confirming their good mechanical properties.
A Hybrid Forecast Model for Household Electric Power by Fusing Landmark-Based Spectral Clustering and Deep Learning
Authors: Shi Jiarong , Wang Zhiteng
Published: July 2022

Household power load forecasting plays an important role in the operation and planning of power grids. To address the prediction issue of household power consumption in power grids, this paper chooses a time series of historical power consumption as the feature variables and uses landmark-based spectral clustering (LSC) and a deep learning model to cluster and predict the power consumption dataset, respectively. Firstly, the investigated data are reshaped into a matrix and all missing entries are recovered by matrix completion. Secondly, the data samples are divided into three clusters by the LSC method according to the periodicity and regularity of power consumption. Then, all samples in each cluster are expanded via bootstrap aggregating technique. Subsequently, a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) is employed to predict power consumption. The goal of CNN is to extract the features from input data in sequence learning, and LSTM aims to train and predict the power consumption. Finally, the forecasting performance of the LSC–CNN–LSTM is compared with several other deep learning models to verify its reliability and effectiveness in the field of household power load. The experimental results show that the proposed hybrid method is superior to other state-of-the-art deep learning techniques in forecasting performance.
Predicting Leaf Nitrogen Content in Cotton with UAV RGB Images
Authors: Kou Jinmei , Duan Long , Yin Caixia , Ma Lulu , Chen Xiangyu , Gao Pan , Lv Xin
Published: July 2022

Rapid and accurate prediction of crop nitrogen content is of great significance for guiding precise fertilization. In this study, an unmanned aerial vehicle (UAV) digital camera was used to collect cotton canopy RGB images at 20 m height, and two cotton varieties and six nitrogen gradients were used to predict nitrogen content in the cotton canopy. After image-preprocessing, 46 hand features were extracted, and deep features were extracted by convolutional neural network (CNN). Partial least squares and Pearson were used for feature dimensionality reduction, respectively. Linear regression, support vector machine, and one-dimensional CNN regression models were constructed with manual features as input, and the deep features were used as inputs to construct a two-dimensional CNN regression model to achieve accurate prediction of cotton canopy nitrogen. It was verified that the manual feature and deep feature models constructed from UAV RGB images had good prediction effects. R2 = 0.80 and RMSE = 1.67 g kg−1 of the Xinluzao 45 optimal model, and R2 = 0.42 and RMSE = 3.13 g kg−1 of the Xinluzao 53 optimal model. The results show that the UAV RGB image and machine learning technology can be used to predict the nitrogen content of large-scale cotton, but due to insufficient data samples, the accuracy and stability of the prediction model still need to be improved.
Assessment of the Common Agricultural Policy 2014–2020 in Supporting Agroecological Transitions: A Comparative Study of 15 Cases across Europe
Authors: Linares Quero Alba , Iragui Yoldi Uxue , Gava Oriana , Schwarz Gerald , Povellato Andrea , Astrain Carlos
Published: July 2022

This article is aimed at analyzing the potential that CAP 2014–2020-related instruments have on supporting agroecological transitions in Europe by focusing on the strengths and weaknesses of key instruments. Through a stepwise participatory research methodology, 105 key stakeholders (farmers, advisors, academics, environment experts, administration representatives, and professionals from food chains) in 15 countries in Europe were engaged in the discussion of the potential of current CAP instruments to solve the barriers that constrain agroecological farming systems in their particular regions. The results of this comparative study show which CAP instruments are valued with a high potential to support transitions to agroecology. The analysis of the stakeholders’ perceptions contributes to an enhanced understanding of why CAP instruments have failed or succeeded to promote agroecological transitions.
A Note on the Design of Waste Management System Using QR Code for Radioactive Waste
Authors: Lee Jin-Woo , Jeong Ji-Young , Kim Jong-Jin , Park Hee-Seoung , Chae San
Published: July 2022

Due to the effective management of radioactive waste in the Republic of Korea (South Korea) and around the world as well as the introduction of radioactive waste certification programs, an integrated radioactive waste management system has been developed and applied. An integrated radioactive waste management system can improve waste management by providing an automatic identification and waste certification program (WCP) of radioactive waste. In this paper, we propose the development of a methodology that can manage radioactive waste from generation to treatment and a system for tracking radioactive waste using a QR code system with real-time management. A QR code is designed for mobile phones as an Android application and allows users to view, sort, and learn about radioactive waste in real time. This enables the smoother and more systematic management of radioactive waste.
How to Assess Generic Competencies: From Sustainable Development Needs among Engineering Graduates in Industry
Authors: Yu Tianzuo , Shang Weiwei , Liu Shaoxue , Zhu Jiabin
Published: July 2022

Achieving many of the UN’s 17 Sustainable Development Goals requires the active contribution of skilled engineers. Globally, however, there appears to be a mismatch between the sustainable competencies that engineering graduates possess and those required by industry. Closing this gap requires a reliable and valid means of establishing which competencies are of greatest importance to engineering practitioners. In this research, we developed a model of generic engineering competency and designed a scale comprising 55 skills in total. This instrument was then used to survey two samples of engineering graduates working in the Chinese industry, with 746 in the first round of surveys, and 1183 in the second. Using exploratory factor analysis (EFA), seven subscales were extracted from the data: (1) leadership, (2) engineering design, (3) professionalism, (4) problem solving, (5) lifelong learning, (6) technical theory, and (7) communication. Confirmatory factor analysis (CFA) demonstrated that the total number of generic engineering competencies was represented by a second-order, single-factor model that adequately fitted the data. Further, the Cronbach’s alpha values and composite reliability of the scale indicate its reliability. Overall, the evidence shows that the instrument offers a valid and reliable means of researching and assessing engineering education practices.
Primary Growth Effect of Salix viminalis L. CV. Inger and Tordis in Controlled Conditions by Exploring Optimum Cutting Lengths and Rhizogenesis Treatments
Authors: Vâtcă Sorin Daniel , Gâdea Ștefania , Vidican Roxana , Șandor Mignon , Stoian Vlad , Vâtcă Anamaria , Horvath Adrian , Stoian Valentina Ancuța
Published: July 2022

The major disadvantage of setting up a willow coppice is the low survival rate, which reduces economic efficiency and crop sustainability. The aim of this research was to test, under controlled conditions, the impact of water, gibberellic acid A3 (0.05%), and humic acid (0.2%) on the growth and development of two willow clones. Under humic acid treatment, 20 cm cuttings of the Tordis clone developed up to 15 roots, and 25 cm cuttings developed more than 23. In comparison, water stimulated more than 15 roots for both 20 and 25 cm cuttings. Gibberellins acted as an inhibitor, especially on the roots, and the cuttings dried out from the top to the middle, with weak development of shoots and callus formation. For both clones, the highest number of active buds was observed on 20 and 25 cm cuttings grown in water, with more than four for Inger and more than seven for Tordis. Root development of the Inger clone had a maximum of eight for 25 cm cuttings grown in water; it was three times lower in the same variant of Tordis and two times lower for the Tordis clone with humic acid treatment. In general, Inger cuttings of 15 and 25 cm highlighted a delayed root formation when humic acids and gibberellins were applied. In controlled condition experiments, the Tordis clone was more suitable owing to its higher development and increased growth stability.
Grain Security in Light of the Current Geopolitical Background and Agricultural Policy in the Democratic People’s Republic of Korea
Authors: Jiang Luguang , Liu Ye
Published: July 2022

Grain problems in the Democratic People’s Republic of Korea (DPRK) have been the focus of global attention for many years. In this context, scientific evaluations of grain supply and consumption are very important as a component of agricultural cooperation between China and the DPRK and will also promote a stable development of the society across Northeast Asia. The results of this analysis showed that DPRK grain production in 2019 was equivalent to that seen in 1975. Dominant grain-producing areas within the DPRK include the plains in the west and southwest encompassing North Phyongan, South Phyongan, Pyongyang, North Hwanghae, and South Hwanghae. The data showed that the DPRK was basically grain self-sufficient prior to 1995 but subsequently has been unable to meet the demand, even given reliance on imports and international assistance. The cultivated land area within the DPRK includes large proportions of slope farmland, an important factor that influences the grain production. The DPRK also boasts good irrigation infrastructure that provides a good basis for grain production. This means that, under normal circumstances, 56.59% of cultivated land can be effectively irrigated. Chemical fertilizer supplies have, however, been unable to meet the agricultural production demands, currently remaining at the 1970s levels. It is clear that the DPRK needs to increase chemical and organic fertilizer inputs in order to ensure soil fertility. As the southern region of the DPRK has sufficient water and is hot enough, the implementation of multi-cropping farming systems will ensure an increase of at least 4.9 million tons in grain production and will guarantee supply for at least 1.88 million people.
Using Clean Energy Satellites to Interpret Imagery: A Satellite IoT Oriented Lightweight Object Detection Framework for SAR Ship Detection
Authors: Xie Fang , Luo Hao , Li Shaoqian , Liu Yingchun , Lin Baojun
Published: July 2022

This paper studies the lightweight deep learning object detection algorithm to detect ship targets in SAR images that can be deployed on-orbit and accessed in the space-based IoT. Traditionally, remote sensing data must be transferred to the ground for processing. With the vigorous development of the commercial aerospace industry, computing, and high-speed laser inter-satellite link technologies, the interconnection of everything in the intelligent world has become an irreversible trend. Satellite remote sensing has entered the era of a big data link with IoT. On-orbit interpretation gives remote sensing images expanse application space. However, implementing on-orbit high-performance computing (HPC) is difficult; it is limited by the power and computer resource consumption of the satellite platform. Facing this challenge, building a processing algorithm with less computational complexity, less parameter quantity, high precision, and low computational power consumption is a key issue. In this paper, we propose a lightweight end-to-end SAR ship detector fused with the vision transformer encoder: YOLO−ViTSS. The experiment shows that YOLO−ViTSS has lightweight features, the model size is only 1.31 MB; it has anti-noise capability is suitable for processing SAR remote sensing images with native noise, and it also has high performance and low training energy consumption with 96.6 mAP on the SSDD dataset. These characteristics make YOLO−ViTSS suitable for porting to satellites for on-orbit processing and online learning. Furthermore, the ideas proposed in this paper help to build a cleaner and a more efficient new paradigm for remote sensing image interpretation. Migrating HPC tasks performed on the ground to on-orbit satellites and using solar energy to complete computing tasks is a more environmentally friendly option. This environmental advantage will gradually increase with the current construction of large-scale satellite constellations. The scheme proposed in this paper helps to build a novel real-time, eco-friendly, and sustainable SAR image interpretation mode.
A Model of Motivational and Technological Factors Influencing Massive Open Online Courses’ Continuous Intention to Use
Authors: Al-shami Samer Ali , Aldahmani Salem , Kamalrudin Massila , Al-Kumaim Nabil Hasan , Al Mamun Abdullah , Al-shami Mohammed , Jaber Mustafa Musa
Published: July 2022

Massive open online courses have been regarded as effective technological innovations that improve educational systems in the era of digitalisation. However, only 10% of the registered students complete their courses. This study aims to examine the motivational and technological factors and contextual features on students’ continuous intention to use. A questionnaire was gathered from 315 of students in the UAE and revealed that social motivational and technological factors driven by the technology acceptance model and technology task fit theory significantly influenced the students’ continuance intention to use. This study also revealed that contextual features including language use and course accreditation are important indicators determining students’ behaviours toward the use. Hence, this study proposed an integrative model to explain ways to improve continuance intention to use. This study contributes to the sustainable use of massive open online courses in developing countries through an integrative model.
Regional Flood Frequency Analysis of the Sava River in South-Eastern Europe
Authors: Leščešen Igor , Šraj Mojca , Basarin Biljana , Pavić Dragoslav , Mesaroš Minučer , Mudelsee Manfred
Published: July 2022

Regional flood frequency analysis (RFFA) is a powerful method for interrogating hydrological series since it combines observational time series from several sites within a region to estimate risk-relevant statistical parameters with higher accuracy than from single-site series. Since RFFA extreme value estimates depend on the shape of the selected distribution of the data-generating stochastic process, there is need for a suitable goodness-of-distributional-fit measure in order to optimally utilize given data. Here we present a novel, least-squares-based measure to select the optimal fit from a set of five distributions, namely Generalized Extreme Value (GEV), Generalized Logistic, Gumbel, Log-Normal Type III and Log-Pearson Type III. The fit metric is applied to annual maximum discharge series from six hydrological stations along the Sava River in South-eastern Europe, spanning the years 1961 to 2020. Results reveal that (1) the Sava River basin can be assessed as hydrologically homogeneous and (2) the GEV distribution provides typically the best fit. We offer hydrological-meteorological insights into the differences among the six stations. For the period studied, almost all stations exhibit statistically insignificant trends, which renders the conclusions about flood risk as relevant for hydrological sciences and the design of regional flood protection infrastructure.
Can Green Finance Policies Stimulate Technological Innovation and Financial Performance? Evidence from Chinese Listed Green Enterprises
Authors: Du Mo , Zhang Ruirui , Chai Shanglei , Li Qiang , Sun Ruixuan , Chu Wenjun
Published: July 2022

The impact of China’s green finance policies on renewable energy, clean energy, and other green companies is a hot topic of concern. This study uses the difference-in-differences (DID) model to examine the incentive effect of the Green Credit Guidelines (GCG) on the technological innovation and financial performance of Chinese listed green enterprises. The heterogeneity analysis is carried out from the level of digital finance, green development, and marketization. This study finds that: (1) Green finance is conducive to stimulating the technological innovation and financial performance of green enterprises. (2) Green enterprises in areas with high digital finance levels have a more significant incentive effect on green finance policies, compared to areas with less-developed digital finance. (3) Green enterprises in areas with high levels of green development are more significantly positively affected by green finance policies, compared to areas with less-developed digital finance. (4) The incentive effect of green credit policies on green enterprises in areas with a high degree of marketization is more significant, compared with regions with a lower level of green development. Finally, some policy implications are proposed to provide a reference for China to improve the green financial system to facilitate the financing of green enterprises.
Research on Mine Water Dispatching Mode Based on Maximization of Reuse Rate
Authors: Liu Yang , Liu Ping , Bo Lei , Li Qingshan , Quan Gefei , Zhuo Yuanjing , Han Yuqi , Wang Yiying
Published: July 2022

Coal mining not only produces a large amount of mine water but also may cause water pollution. Therefore, economic treatment and efficient reuse of mine water are the main research directions of the mine area at present, and the realization of optimal dispatching and efficient reuse of mine water is an urgent problem to be solved. Based on the Na Lin mining area as an example, based on maximizing the reuse rate of mine water, summarizes the mine water level fractionation utilization pathway and classification of mine water dispatching mode, build the Na Lin mining area water supply dispatching model, analyzed the Na Lin River No. 2 mining area water supply dispatching model and the space-time change of water dispatching, through comparing with traditional dispatching model, the results showed that: The constructed water dispatching model can significantly improve the mine water recycling rate in Na Lin river mine area, which provides a certain theoretical basis for the study of efficient utilization of mine water.
The Stability of a Hydrodynamic Bravais Lattice
Authors: Couchman Miles M. P. , Evans Davis J. , Bush John W. M.
Published: July 2022

We present the results of a theoretical investigation of the stability and collective vibrations of a two-dimensional hydrodynamic lattice comprised of millimetric droplets bouncing on the surface of a vibrating liquid bath. We derive the linearized equations of motion describing the dynamics of a generic Bravais lattice, as encompasses all possible tilings of parallelograms in an infinite plane-filling array. Focusing on square and triangular lattice geometries, we demonstrate that for relatively low driving accelerations of the bath, only a subset of inter-drop spacings exist for which stable lattices may be achieved. The range of stable spacings is prescribed by the structure of the underlying wavefield. As the driving acceleration is increased progressively, the initially stationary lattices destabilize into coherent oscillatory motion. Our analysis yields both the instability threshold and the wavevector and polarization of the most unstable vibrational mode. The non-Markovian nature of the droplet dynamics renders the stability analysis of the hydrodynamic lattice more rich and subtle than that of its solid state counterpart.
A Novel Real Coded Genetic Algorithm for Software Mutation Testing
Authors: Mishra Deepti Bala , Acharya Biswaranjan , Rath Dharashree , Gerogiannis Vassilis C. , Kanavos Andreas
Published: July 2022

Information Technology has rapidly developed in recent years and software systems can play a critical role in the symmetry of the technology. Regarding the field of software testing, white-box unit-level testing constitutes the backbone of all other testing techniques, as testing can be entirely implemented by considering the source code of each System Under Test (SUT). In unit-level white-box testing, mutants can be used; these mutants are artificially generated faults seeded in each SUT that behave similarly to the realistic ones. Executing test cases against mutants results in the adequacy (mutation) score of each test case. Efficient Genetic Algorithm (GA)-based methods have been proposed to address different problems in white-box unit testing and, in particular, issues of mutation testing techniques. In this research paper, a new approach, which integrates the path coverage-based testing method with the novel idea of tracing a Fault Detection Matrix (FDM) to achieve maximum mutation coverage, is proposed. The proposed real coded GA for mutation testing is designed to achieve the highest Mutation Score, and it is thus named RGA-MS. The approach is implemented in two phases: path coverage-based test data are initially generated and stored in an optimized test suite. In the next phase, the test suite is executed to kill the mutants present in the SUT. The proposed method aims to achieve the minimum test dataset, having at the same time the highest Mutation Score by removing duplicate test data covering the same mutants. The proposed approach is implemented on the same SUTs as these have been used for path testing. We proved that the RGA-MS approach can cover maximum mutants with a minimum number of test cases. Furthermore, the proposed method can generate a maximum path coverage-based test suite with minimum test data generation compared to other algorithms. In addition, all mutants in the SUT can be covered by less number of test data with no duplicates. Ultimately, the generated optimal test suite is trained to achieve the highest Mutation Score. GA is used to find the maximum mutation coverage as well as to delete the redundant test cases.
On Fractional Newton Inequalities via Coordinated Convex Functions
Authors: Kösem Pınar , Kara Hasan , Budak Hüseyin , Ali Muhammad Aamir , Nonlaopon Kamsing
Published: July 2022

In this paper, firstly, we present an integral identity for functions of two variables via Riemann–Liouville fractional integrals. Then, a Newton-type inequality via partially differentiable coordinated convex mappings is derived by taking the absolute value of the obtained identity. Moreover, several inequalities are obtained with the aid of the Hölder and power mean inequality. In addition, we investigate some Newton-type inequalities utilizing mappings of two variables with bounded variation. Finally, we gave some mathematical examples and their graphical behavior to validate the obtained inequalities.
Numerical Investigation of the Fredholm Integral Equations with Oscillatory Kernels Based on Compactly Supported Radial Basis Functions
Authors: Khan Suliman , Alhazmi Sharifah E. , Alqahtani Aisha M. , Ahmed Ahmed EI-Sayed , Yaseen Mansour F. , Tag-Eldin Elsayed M. , Qaiser Dania
Published: July 2022

The integral equations with oscillatory kernels are of great concern in applied sciences and computational engineering, particularly for large-scale data points and high frequencies. Therefore, the interest of this work is to develop an accurate, efficient, and stable algorithm for the computation of the Fredholm integral equations (FIEs) with the oscillatory kernel. The oscillatory part of the FIEs is evaluated by the Levin quadrature coupled with a compactly supported radial basis function (CS-RBF). The algorithm exhibits sparse and well-conditioned matrix even for large-scale data points, as compared to its counterpart, multi-quadric radial basis function (MQ-RBF) coupled with the Levin quadrature. Usually, the RBFs behave with spherical symmetry about the centers, known as radial. The comparison of convergence and stability analysis of both types of RBFs are performed and numerically verified. The proposed algorithm is tested with benchmark problems and compared with the counterpart methods in the literature. It is concluded that the algorithm in this work is accurate, robust, and stable than the existing methods in the literature based on MQ-RBF and the Chebyshev interpolation matrix.
Vibration Analysis of a Finite Lightweight Locally Resonant Beam Suspended with Periodic Force-Moment-Type Resonators inside Using an Exact Wave-Based Approach
Authors: Lv Hangyuan , Li Shangjie , Huang Xianzhen , Yu Zhongliang
Published: July 2022

This paper employs and develops the exact wave-based vibration analysis approach to investigate the propagation properties of a designed finite lightweight locally resonant (LR) beam with two-degree-of-freedom (2-DOF) force-moment-type resonators attached periodically inside. By deriving the propagation, reflection, and transmission matrices of the structural discontinuities, the vibration of the LR beam can be described as structural waves. By assembling wave relations into the beam, the approach shows high efficiency because the forced vibration problem of the lightweight LR structure is turned to be the solution to a related set of matrix equations. The accuracy of the developed approach is validated with two examples carried out using the finite element method. In addition, the influence of the main parameters of the LR beam is studied and we found that the increase in the mass of the resonator and the stiffness of the spring are more sensitive in broadening the width and increasing the center frequency of the band gap of the designed lightweight LR beam. The proposed structure and analysis approach in this paper may provide an exact and efficient means for the design and analysis of structures in which damping and lightweight properties are required, such as space-arm and the framework of antennas in the field of aerospace.
Computational Study of H2 Catalytic Combustion on Pd38 Cluster Model and Pd(111) Slab Model
Authors: Qi Dabin , Luo Xudong , Yao Yulong , Qi Na , Lu Xiaojun , Chen Hao , Shi Hongqi
Published: July 2022

Hydrogen is one of the exhaust gases produced by nuclear power stations. Due to the potential danger of incomplete combustion and the emission of hydrogen, hydrogen catalytic combustion is introduced to ensure the safety of nuclear power stations. Palladium is a widely used catalyst for hydrogen catalytic combustion. H2 catalytic combustion on a Pd(111) slab model and Pd38 cluster model were simulated using density functional theory (DFT), in order to analyze the H2 oxidation mechanism on the catalyst surface.
Preserving Classes of Meromorphic Functions through Integral Operators
Authors: Totoi Elisabeta-Alina , Cotîrlă Luminiţa-Ioana
Published: July 2022

We consider three new classes of meromorphic functions defined by an extension of the Wanas operator and two integral operators, in order to study some preservation properties of the classes. The purpose of the paper is to find the conditions such that, when we apply the integral operator Jp,γ to some function from the new defined classes ΣSp,qn(α,δ), respectively ΣSp,qn(α), we obtain also a function from the same class. We also define a new integral operator on the class of meromorphic functions, denoted by Jp,γ,h, where h is a normalized analytic function on the unit disc. We study some basic properties of this operator. Then we look for the conditions which allow this operator to preserve a particular subclass of the classes mentioned above.
Capture in Regime of a Trapped Motion with Further Inelastic Collision for Finite-Sized Asteroid in ER3BP
Authors: Ershkov Sergey , Leshchenko Dmytro , Rachinskaya Alla
Published: July 2022

The application of a modern solving algorithm or method of resolving dynamical equations for small projectile of finite sizes orbiting to be captured in a trapped zigzaging oscillations on orbit around the another large asteroid and in a further inelastic colliding scenario with him (using a formulation of the elliptic restricted three-body problem, ER3BP) is studied semi-analytically. Herein, two primaries MSun and mp (mp < MSun) revolve around their barycenter on Keplerian orbits with low eccentricities. A smaller body (projectile for attacking a large asteroid) is supposed to be a solid, almost symmetric ellipsoid, having the gravitational potential of the MacCullagh type. Our aim is to develop a previously introduced solving procedure and to investigate the updated dynamics of the projectile captured to a trapped dynamical resonance, thereby having the inelastic collision of a small projectile orbiting on quasi-stable elliptic orbits around the large asteroid, mp.