bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Human Travel Correlation for Urban Transport Planning Based on Multisource Data
Authors: Chen Hua , Cai Ming , Xiong Chen
Published: December 2020

With the rapid development of positioning techniques, a large amount of human travel trajectory data is collected. These datasets have become an effective data resource for obtaining urban traffic patterns. However, many traffic analyses are only based on a single dataset. It is difficult to determine whether a single-dataset-based result can meet the requirement of urban transport planning. In response to this problem, we attempted to obtain traffic patterns and population distributions from the perspective of multisource traffic data using license plate recognition (LPR) data and cellular signaling (CS) data. Based on the two kinds of datasets, identification methods of residents’ travel stay point are proposed. For LPR data, it was identified based on different vehicle speed thresholds at different times. For CS data, a spatiotemporal clustering algorithm based on time allocation was proposed to recognize it. We then used the correlation coefficient r and the significance test p-values to analyze the correlations between the CS and LPR data in terms of the population distribution and traffic patterns. We studied two real-world datasets from five working days of human mobility data and found that they were significantly correlated for the stay and move population distributions. Then, the analysis scale was refined to hour level. We also found that they still maintain a significant correlation. Finally, the origin–destination (OD) matrices between traffic analysis zones (TAZs) were obtained. Except for a few TAZs with poor correlations due to the fewer LPR records, the correlations of the other TAZs remained high. It showed that the population distribution and traffic patterns computed by the two datasets were fairly similar. Our research provides a method to improve the analysis of complex travel patterns and behaviors and provides opportunities for travel demand modeling and urban transport planning. The findings can also help decision-makers understand urban human mobility and can serve as a guide for urban management and transport planning.
MAC Performance Analysis for Reliable Power-Line Communication Networks with ARQ Scheme
Authors: Hao Sheng , Zhang Huyin
Published: December 2020

Power-line communication (PLC) networks have been increasingly used for constructing industrial IoT (internet of things) and home networking systems due to their low-cost installation and broad coverage feature. To guarantee the transmission reliability, ARQ (automatic repeat request) scheme is introduced into the link layer of reliable PLC networks, which allows the retransmission of a data frame several times so that it has a higher probability to be correctly received. However, current studies of performance analysis for PLC MAC (medium access control) protocol (i.e., IEEE 1901) do not take into account of the impact of ARQ scheme. To resolve this problem, we propose an analytical model to investigate the MAC performance of IEEE 1901 protocol for reliable PLC networks with ARQ scheme. In the modeling process, we first establish a PLC channel model to reflect the impacts of PLC channel types (containing Rayleigh fading and Log-normal fading), additive non-Gaussian noise feature and ARQ scheme on data transmission at link layer. Next, we employ Renewal theory and Queueing dynamics to capture the transmission attempt behavior of executing IEEE 1901 protocol in the unsaturated environment with finite transit buffer size. On the basis of combining these two models, we derive the closed-form expressions of 1901 MAC metrics considering the influence of the ARQ scheme. Furthermore, we prove that the proposed analytical model has the convergence property. Finally, we evaluate the MAC performance of 1901 protocol for reliable PLC networks with ARQ scheme and verify the proposed analytical model.
Multi-Fading Factor and Updated Monitoring Strategy Adaptive Kalman Filter-Based Variational Bayesian
Authors: Shan Chenghao , Zhou Weidong , Yang Yefeng , Jiang Zihao
Published: December 2020

Aiming at the problem that the performance of adaptive Kalman filter estimation will be affected when the statistical characteristics of the process and measurement of the noise matrices are inaccurate and time-varying in the linear Gaussian state-space model, an algorithm of multi-fading factor and an updated monitoring strategy adaptive Kalman filter-based variational Bayesian is proposed. Inverse Wishart distribution is selected as the measurement noise model and the system state vector and measurement noise covariance matrix are estimated with the variational Bayesian method. The process noise covariance matrix is estimated by the maximum a posteriori principle, and the updated monitoring strategy with adjustment factors is used to maintain the positive semi-definite of the updated matrix. The above optimal estimation results are introduced as time-varying parameters into the multiple fading factors to improve the estimation accuracy of the one-step state predicted covariance matrix. The application of the proposed algorithm in target tracking is simulated. The results show that compared with the current filters, the proposed filtering algorithm has better accuracy and convergence performance, and realizes the simultaneous estimation of inaccurate time-varying process and measurement noise covariance matrices.
Driver Identification System Using Normalized Electrocardiogram Based on Adaptive Threshold Filter for Intelligent Vehicles
Authors: Choi Gyu Ho , Lim Kiho , Pan Sung Bum
Published: December 2020

Driver-centered infotainment and telematics services are provided for intelligent vehicles that improve driver convenience. Driver-centered services are performed after identification, and a biometrics system using bio-signals is applied. The electrocardiogram (ECG) signal acquired in the driving environment needs to be normalized because the intensity of noise is strong because the driver’s motion artifact is included. Existing time, frequency, and phase normalization methods have a problem of distorting P, QRS Complexes, and T waves, which are morphological features of an ECG, or normalizing to signals containing noise. In this paper, we propose an adaptive threshold filter-based driver identification system to solve the problem of distortion of the ECG morphological features when normalized and the motion artifact noise of the ECG that causes the identification performance deterioration in the driving environment. The experimental results show that the proposed method improved the average similarity compared to the results without normalization. The identification performance was also improved compared to the results before normalization.
Model-Free Lens Distortion Correction Based on Phase Analysis of Fringe-Patterns
Authors: Weng Jiawen , Zhou Weishuai , Ma Simin , Qi Pan , Zhong Jingang
Published: December 2020

The existing lens correction methods deal with the distortion correction by one or more specific image distortion models. However, distortion determination may fail when an unsuitable model is used. So, methods based on the distortion model would have some drawbacks. A model-free lens distortion correction based on the phase analysis of fringe-patterns is proposed in this paper. Firstly, the mathematical relationship of the distortion displacement and the modulated phase of the sinusoidal fringe-pattern are established in theory. By the phase demodulation analysis of the fringe-pattern, the distortion displacement map can be determined point by point for the whole distorted image. So, the image correction is achieved according to the distortion displacement map by a model-free approach. Furthermore, the distortion center, which is important in obtaining an optimal result, is measured by the instantaneous frequency distribution according to the character of distortion automatically. Numerical simulation and experiments performed by a wide-angle lens are carried out to validate the method.
Model of the Vibration Signal of the Vibrating Sieving Screen Suspension for Condition Monitoring Purposes
Authors: Michalak Anna , Wodecki Jacek , Drozda Michał , Wyłomańska Agnieszka , Zimroz Radosław
Published: December 2020

Diagnostics of industrial machinery is a topic related to the need for damage detection, but it also allows to understand the process itself. Proper knowledge about the operational process of the machine, as well as identification of the underlying components, is critical for its diagnostics. In this paper, we present a model of the signal, which describes vibrations of the sieving screen. This particular type is used in the mining industry for the classification of ore pieces in the material stream by size. The model describes the real vibration signal measured on the spring set being the suspension of this machine. This way, it is expected to help in better understanding how the overall motion of the machine can impact the efforts of diagnostics. The analysis of real vibration signals measured on the screen allowed to identify and parameterize the key signal components, which carry valuable information for the following stages of diagnostic process of that machine. In the proposed model we take into consideration deterministic components related to shaft rotation, stochastic Gaussian component related to external noise, stochastic α-stable component as a model of excitations caused by falling rocks pieces, and identified machine response to unitary excitations.
Human–Robot Interaction and Sexbots: A Systematic Literature Review
Authors: González-González Carina Soledad , Gil-Iranzo Rosa María , Paderewski-Rodríguez Patricia
Published: December 2020

At present, sexual robots have become a new paradigm of social robots. In this paper, we developed a systematic literature review about sexual robots (sexbots). To do this, we used the Scopus and WoS databases to answer different research questions regarding the design, interaction, and gender and ethical approaches from 1980 until 2020. In our review, we found a male bias in this discipline, and in recent years, articles have shown that user opinion has become more relevant. Some insights and recommendations on gender and ethics in designing sexual robots were also made.
Joint Optical and Wireless Resource Allocation for Cooperative Transmission in C-RAN
Authors: Yang Peng , Chen Liao , Zhang Hong , Yang Jing , Wang Ruyan , Li Zhidu
Published: December 2020

Cooperative multipoint transmission (CoMP) is one of the most promising paradigms for mitigating interference in cloud radio access networks (C-RAN). It allows multiple remote radio units (RRUs) to transmit the same data flow to a user to further improve the signal quality. However, CoMP may incur redundant data transmission over fronthaul network in the C-RAN. In a C-RAN employing CoMP, a key problem is how to coordinate heterogeneous resource allocation to maximize the cooperation gain while reducing the fronthaul load. In this paper, the cooperation transmission based on a multi-dimensional resource schedule (MRSCT) scheme, jointly considering user association, spectrum resource allocation, and wavelength resource allocation, is firstly envisioned in the underlying C-RAN integrating time and wavelength division multiplexing passive optical network (TWDM-PON) to maximize fronthaul efficiency. Then a two-timescale resource allocation framework including two sub-approaches is established. More specially, the first sub-approach mainly focuses on exploiting reinforcement learning to obtain a wavelength resource allocation strategy to relieve fronthaul traffic load. Moreover, the second sub-approach adopts the overlapping coalition formation game to establish a user-centric cooperative set, where spectrum resources are dynamically allocated to further alleviate the interference issue. The theoretical analysis and simulation results validate the performance of MRSCT scheme on the fronthaul efficiency, user experience, and system service capability.
Dynamic Characterisation of Fibre-Optic Temperature Sensors for Physiological Monitoring
Authors: Coote Joanna M. , Torii Ryo , Desjardins Adrien E.
Published: December 2020

Fast, miniature temperature sensors are required for various biomedical applications. Fibre-optics are particularly suited to minimally invasive procedures, and many types of fibre-optic temperature sensors have been demonstrated. In applications where rapidly varying temperatures are present, a fast and well-known response time is important; however, in many cases, the dynamic behaviour of the sensor is not well-known. In this article, we investigate the dynamic response of a polymer-based interferometric temperature sensor, using both an experimental technique employing optical heating with a pulsed laser, and a computational heat transfer model based on the finite element method. Our results show that the sensor has a time constant on the order of milliseconds and a −6 dB bandwidth of up to 178 Hz, indicating its suitability for applications such as flow measurement by thermal techniques, photothermal spectroscopy, and monitoring of thermal treatments.
A Novel Gesture Recognition System Based on CSI Extracted from a Smartphone with Nexmon Firmware
Authors: Li Tao , Shi Chenqi , Li Peihao , Chen Pengpeng
Published: December 2020

In this paper, we propose a novel gesture recognition system based on a smartphone. Due to the limitation of Channel State Information (CSI) extraction equipment, existing WiFi-based gesture recognition is limited to the microcomputer terminal equipped with Intel 5300 or Atheros 9580 network cards. Therefore, accurate gesture recognition can only be performed in an area relatively fixed to the transceiver link. The new gesture recognition system proposed by us breaks this limitation. First, we use nexmon firmware to obtain 256 CSI subcarriers from the bottom layer of the smartphone in IEEE 802.11ac mode on 80 MHz bandwidth to realize the gesture recognition system’s mobility. Second, we adopt the cross-correlation method to integrate the extracted CSI features in the time and frequency domain to reduce the influence of changes in the smartphone location. Third, we use a new improved DTW algorithm to classify and recognize gestures. We implemented vast experiments to verify the system’s recognition accuracy at different distances in different directions and environments. The results show that the system can effectively improve the recognition accuracy.
A Cloud-Based IoT Platform for Precision Control of Soilless Greenhouse Cultivation
Authors: Sagheer Alaa , Mohammed Maged , Riad Khaled , Alhajhoj Mohammed
Published: December 2020

Food security has become an increasingly important challenge for all countries globally, particularly as the world population continues to grow and arable lands are diminishing due to urbanization. Water scarcity and lack of labor add extra negative influence on traditional agriculture and food production. The problem is getting worse in countries with arid lands and harsh climate, which exacerbates the food gap in these countries. Therefore, smart and practical solutions to promote cultivation and combat food production challenges are highly needed. As a controllable environment, greenhouses are the perfect environment to improve crops’ production and quality in harsh climate regions. Monitoring and controlling greenhouse microclimate is a real problem where growers have to deal with various parameters to ensure the optimal growth of crops. This paper shows our research in which we established a multi-tier cloud-based Internet of Things (IoT) platform to enhance the greenhouse microclimate. As a case study, we applied the IoT platform on cucumber cultivation in a soilless medium inside a commercial-sized greenhouse. The established platform connected all sensors, controllers, and actuators placed in the greenhouse to provide long-distance communication to monitor, control, and manage the greenhouse. The implemented platform increased the cucumber yield and enhanced its quality. Moreover, the platform improved water use efficiency and decreased consumption of electrical energy. Based on the positive impact on water use efficiency and enhancement on cucumber fruit yield and quality, the established platform seems quite suitable for the soilless greenhouse cultivation in arid regions.
The Family System of Sexuality Communication: Extended Family Perceptions of Adolescent–Family Talk about Sex, with Sibling and Non-Sibling Comparison
Authors: Grossman Jennifer M. , Pearce Nora , Richer Amanda M.
Published: December 2020

Talk with parents and extended family about sex and relationships can support adolescents’ sexual health. However, few studies explore how parent and extended family communication with adolescents intersect. This study used thematic analysis to assess family roles in talk with teens about sex and relationships among a sample of 39 adult extended family members (such as aunts and uncles, and older siblings and cousins) in the United States. Analyses identified four themes in sexuality communication that address: why adolescents talk to extended family about sex and relationships, family engagement in these conversations, consistency of family messages, and family communication about adolescents. Findings identify variation in how family members interact with adolescents and one another regarding talk about sex and relationships. For example, some participants described family coordination of sexual messages to the teen, while others reported no family communication about this topic. Results also showed similarities and differences in how sibling and non-sibling extended family describe these processes. These findings identify the need to examine family talk about sex and relationships in the context of a larger family system, rather than only within dyadic relationships, and suggests possibilities for family-based interventions to support adolescents’ sexual health.
Peak Traffic Flow Predictions: Exploiting Toll Data from Large Expressway Networks
Authors: Shen Ling , Lu Jian , Geng Dongdong , Deng Ling
Published: December 2020

Big data from toll stations provides reliable and accurate origin-destination (OD) pair information of expressway networks. However, although the short-term traffic prediction model based on big data is being constantly improved, the volatility and nonlinearity of peak traffic flow restricts the accuracy of the prediction results. Therefore, this research attempts to solve this problem through three contributions, firstly, proposing the use the Pauta criterion from statistics as the standard for defining the anomaly criteria of expressway traffic flows. Through comparison with the common local outlier factor (LOF) method, the rationality and advantages of the Pauta criterion were expounded. Secondly, adding week attributes to data, and splitting the data based on the similarity characteristics of traffic flow time series in order to improve the accuracy and efficiency of data input. Thirdly, by introducing empirical mode decomposition (EMD) to decompose the signal before autoregressive integrated moving average (ARIMA) model training is carried out. The first two contributions are for efficiency, the third is to deal with the volatility and nonlinearity of the abnormal peak training data. Finally, the model is analyzed, based on the expressway toll data of the Jiangsu Province. The results show that the EMD-ARIMA model has more advantages than the ARIMA model when dealing with fluctuating data.
Evaluation of Allelopathic Potentials from Medicinal Plant Species in Phnom Kulen National Park, Cambodia by the Sandwich Method
Authors: Sothearith Yourk , Appiah Kwame Sarpong , Motobayashi Takashi , Watanabe Izumi , Somaly Chan , Sugiyama Akifumi , Fujii Yoshiharu
Published: December 2020

Phnom Kulen National Park, in north-western Cambodia, has huge richness in biodiversity and medicinal value. One hundred and ninety-five (195) medicinal plant species were collected from the national park to examine allelopathic potentials by using the sandwich method, a specific bioassay for the evaluation of leachates from plants. The study found 58 out of 195 medicinal plant species showed significant inhibitory effects on lettuce radicle elongation as evaluated by standard deviation variance based on the normal distribution. Three species including Iris pallida (4% of control), Parabarium micranthum (7.5% of control), and Peliosanthes teta (8.2% of control) showed strong inhibition of lettuce radicle elongation less than 10% of the control. The results presented could present as a benchmark for isolation and identification of allelochemicals among medicinal plants used in Cambodia.
Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry
Authors: Chen Wen-Kuo , Riantama Dalianus , Chen Long-Sheng
Published: December 2020

Due to the COVID-19 pandemic, the sales of fast-food businesses have dropped sharply. Customer satisfaction has always been one of the key factors for the sustainable development of enterprises. However, in the fast-food restaurant business, gaining the knowledge of customer satisfaction is one of the critical tasks. Moreover, text reviews in social media have become one of important reference sources for customers’ decisions in buying services and products. Therefore, the main purpose of this study is to explore whether customer voices from social media reviews are different during the COVID-19 outbreak and to propose a new method to reduce interpersonal contact when collecting data. A text mining scheme which includes least absolute shrinkage and selection operator (LASSO) and decision trees (DT) are presented to discover the essential factors for customers to increase their satisfaction from unstructured online customer reviews. Finally, three real world review sets were employed to validate the effectiveness of the presented text mining scheme. Experimental results can help companies to properly adapt to similar epidemic situations in the future and facilitate their sustainable development.
Evaluation of Pacific Whiteleg Shrimp and Three Halophytic Plants in Marine Aquaponic Systems under Three Salinities
Authors: Chu Yu-Ting , Brown Paul B.
Published: December 2020

The effect of salinity on the growth performance of whiteleg shrimp (Litopenaeus vannamei) and three halophyte plants, red orache (Atriplex hortensis), okahijiki (Salsola komarovii), and minutina (Plantago coronopus), in a marine aquaponic system with biofloc was evaluated in this study. The experiment was conducted for 4 weeks, and the three treatments were 10, 15, or 20 ppt (parts per thousand). The growth performance of the shrimp and the three halophytes were affected by the salinity. Compared to the shrimp reared in 10 ppt, those reared in 15 and 20 ppt had higher final weight, weight gain rate (WGR), and specific growth rate (SGR), and lower feed conversion ratio (FCR). The results from shrimp raised in 15 ppt were 2.0 ± 0.1 g, 89.9 ± 2.2%, 2.3 ± 0.0%, and 1.5 ± 0.0, respectively, and those in 20 ppt were 2.0 ± 0.1 g, 93.9 ± 5.4%, 2.4 ± 0.1%, and 1.4 ± 0.1, respectively. On the other hand, the growth performance and nutrient content in halophyte plants decreased with the increasing salinity. In general, the three halophyte plants had better results in the 10 and 15 ppt treatments than those in 20 ppt. Therefore, the salinity of 15 ppt was suggested as the optimal condition for the integrated cultivation of whiteleg shrimp and the three halophytes in marine aquaponics. Additionally, they are compatible species for the development of marine aquaponics.
The Bike-Sharing Rebalancing Problem Considering Multi-Energy Mixed Fleets and Traffic Restrictions
Authors: Jia Yongji , Zeng Wang , Xing Yanting , Yang Dong , Li Jia
Published: December 2020

Nowadays, as a low-carbon and sustainable transport mode bike-sharing systems are increasingly popular all over the world, as they can reduce road congestion and decrease greenhouse gas emissions. Aiming at the problem of the mismatch of bike supply and user demand, the operators have to transfer bikes from surplus stations to deficiency stations to redistribute them among stations by vehicles. In this paper, we consider a mixed fleet of electric vehicles and internal combustion vehicles as well as the traffic restrictions to the traditional vehicles in some metropolises. The mixed integer programming model is firstly established with the objective of minimizing the total rebalancing cost of the mixed fleet. Then, a simulated annealing algorithm enhanced with variable neighborhood structures is designed and applied to a set of randomly generated test instances. The computational results and sensitivity analysis indicate that the proposed algorithm can effectively reduce the total cost of rebalancing.
Impact of the COVID-19 Pandemic on the Romanian Labor Market
Authors: Radulescu Carmen Valentina , Ladaru Georgiana-Raluca , Burlacu Sorin , Constantin Florentina , Ioanăș Corina , Petre Ionut Laurentiu
Published: December 2020

The present research aims to establish the impact that the current crisis situation the planet is facing, namely the COVID-19 pandemic, has had so far on the Romanian labor force market. In this context, given the lack of information and information regarding this pandemic and its effects, the administration of a questionnaire among the population was considered to identify the research results. The method of semantic differential and the method of ordering the ranks were used for the interpretation of the results. With the help of this questionnaire, it will be possible to answer the question of the research in this study: What are the main effects of the COVID-19 pandemic on the Romanian labor market? The main results showed that the COVID-19 pandemic affected the Romanian workforce; the respondents of the applied questionnaire claimed that they obtained better results and maintained a similar income, but the health crisis also influenced the mentality of employees, with respondents stating that in the event of changing jobs, they would consider it very important for the new employer to ensure the conditions for preventing and combating COVID-19, as well as complex health insurance. However, analyzing at the macroeconomic level, it was found that the COVID-19 pandemic induced an increase in the number of unemployed people in the Romanian labor market.
Confidence in Local, National, and International Scientists on Climate Change
Authors: Sparks Aaron C. , Hodges Heather , Oliver Sarah , Smith Eric R. A. N.
Published: December 2020

In many public policy areas, such as climate change, news media reports about scientific research play an important role. In presenting their research, scientists are providing guidance to the public regarding public policy choices. How do people decide which scientists and scientific claims to believe? This is a question we address by drawing on the psychology of persuasion. We propose the hypothesis that people are more likely to believe local scientists than national or international scientists. We test this hypothesis with an experiment embedded in a national Internet survey. Our experiment yielded null findings, showing that people do not discount or ignore research findings on climate change if they come from Europe instead of Washington-based scientists or a leading university in a respondent’s home state. This reinforces evidence that climate change beliefs are relatively stable, based on party affiliation, and not malleable based on the source of the scientific report.
Measuring Green Creativity for Employees in Green Enterprises: Scale Development and Validation
Authors: Jiang Hui , Wang Kaichao , Lu Zhibin , Liu Yifei , Wang Yu , Li Gang
Published: December 2020

Although employee green creativity is recognized as the key to the innovation in green enterprises, few studies explores the measurement of green creativity for employees. To address the gap, the present study identifies the major dimensions of employee green creativity and develops a comprehensive, reliable, and valid measurement instrument. According to the 4P’s model of creativity, four core dimensions of employee green creativity are identified, namely, green creative motivation, thinking, behavior, and outcome. Strictly adhering to the process of scale development, employee green creativity scale (EGCS) is constructed and validated. We first develop the items of employee green creativity based on literature review and expertise from academics and practitioners. Next, we examine the validation of EGCS through exploratory and confirmatory factor analysis using a sample from three large-scale green enterprises (N = 460). Further, we also check the nomological validity of EGCS by testing the effects of determinants (e.g., green transformational leadership, shared vision, and green self-efficacy) on employee green creativity using a new sample from another two green enterprises (N = 169). Results reveal that EGCS is a reliable and valid instrument for capturing employee green creativity in multiple contexts. Theoretical and practical implications are discussed.
Assessment of Solar Dehumidification Systems in a Hot Climate
Authors: Tabet Aoul Kheira Anissa , Hasan Ahmad , Dakheel Joud Al
Published: December 2020

Solar thermal-powered desiccant dehumidification systems are attracting attention for cooling load-dominated climates. However, their performance varies substantially from place to place depending on climatic conditions, which therefore warrants a tailored design and specification at each geographical location. The current article attempted to investigate the feasibility of extending an existing solar thermal system in a school building in Abu Dhabi to provide dehumidification for the existing air condition system through a desiccant system. The system performance was predicted through a Transient System (TRNSYS) Simulation model to determine the energy savings achieved by the solar-assisted dehumidification system. The current articles determined the effect of fluid flow rate, solar radiation concentration, and heat exchanger effectiveness at the dehumidification of the fresh air as well as energy saved by the proposed system. It was concluded that the system can remove 35% moisture from the air, simultaneously saving 10% of the building’s energy. The system cost and benefit analysis revealed a payback period of 7.5 years, considered slightly higher for an attractive investment in such systems.
Research on the Spatial Differentiation and Driving Forces of Eco-Efficiency of Regional Tourism in China
Authors: Wang Rui , Xia Bing , Dong Suocheng , Li Yu , Li Zehong , Ba Duoxun , Zhang Wenbiao
Published: December 2020

Tourism eco-efficiency is an important indicator that has often been applied to measure the quality of green tourism development. This paper takes the 31 provinces of China as examples to analyze regional tourism eco-efficiency. By constructing multiple input and output indicator systems for regional tourism, we estimated the eco-efficiency of 31 provinces in 1997–2016 using an undesirable output model of a slack-based model (undesirable-SBM) for data envelopment analysis (DEA). Then, we analyzed the spatial–temporal evolutionary trends and patterns of the eco-efficiency over 20 years by using the Hot Spot Model and Spatial Center of Gravity Model. Finally, we explored the driving forces internal and external to the tourism eco-economic system using the Panel Tobit Regression Model and Geodetector Model, respectively. The results show that: In the last 20 years, the tourism eco-efficiency of provinces in China declined, though tourism has experienced rapid but extensive development. The western regions of China, which have better eco-environmental conditions, and the southeastern coastal regions, which have higher levels of economic development, have higher tourism eco-efficiency. Regions with lower tourism eco-efficiency show diffusion trends, while regions with higher tourism eco-efficiency are characterized by a lack of obvious space spillover effects. Technology is the core driving force of regional tourism eco-efficiency, while traffic conditions and social civilization levels are key external influence factors leading to improvement of tourism eco-efficiency. The research results reveal the great significance of laws for sustainable green tourism development with different economic levels in the different regions. Our work could provide a reference for similar countries and regions in the world with the rapid growth of tourism or obvious spatial differentiation in socioeconomic development.
Critical Success Factors of the Project Management in Relation to Industry 4.0 for Sustainability of Projects
Authors: Vrchota Jaroslav , Řehoř Petr , Maříková Monika , Pech Martin
Published: December 2020

Sustainability has recently become a phenomenon; small and medium-sized enterprises (SMEs) are increasingly emphasizing the principles of sustainability in their corporate governance. They implement these changes through project management. The purpose of the paper is to determine the critical success factors in project management, as seen by the managers of Czech manufacturing enterprises, related to the most to the successful completion of the projects. We aim to analyze the relation of these success factors to Industry 4.0, Human Resources, and sustainability. We determined the possible interconnectedness of the critical success factors using correlation coefficients. Then, we compared them using the Mann-Whitney test with new corporate management trends. The results show that companies consider Leadership and Experiences, and Employees and Flexibility to be key factors in project management’s success. The most important critical factor for the sustainability of projects focused on Industry 4.0 is the finances that decide the implementation of projects. The benefits of Industry 4.0 concerning sustainability have been identified in projects aimed at implementing new energy sources. In addition to the results obtained, the development of a methodology for evaluating Industry 4.0 projects’ success concerning sustainability may be based on critical success factors in the future.
Increasing Profitability and Monitoring Environmental Performance: A Case Study in the Agri-Food Industry through an Edge-IoT Platform
Authors: Pérez-Pons María E. , Plaza-Hernández Marta , Alonso Ricardo S. , Parra-Domínguez Javier , Prieto Javier
Published: December 2020

Globalization has led to a new paradigm where the traditional industries, such as agriculture, employ vanguard technologies to broaden its possibilities into what is known as smart farming and the agri-food industry 4.0. This industry needs to adapt to the current market through an efficient use of resources while being environmentally friendly. The most commonly used approaches for analyzing efficiency and sustainability on farms are production efficiency based analyses, such as Data Envelopment Analysis and Stochastic Frontier Analysis, since they allow to see how efficient the outputs are generated regardless of the units of measurement of the inputs. This work presents a real scenario for making farms more profitable and sustainable through the analysis of the Data Envelopment Analysis and the application of the Internet of Things and Edge Computing. What makes this model interesting is that it allows monitoring the ambient conditions with real-time data from the different sensors that have been installed on the farm, minimizing costs and gaining robustness in the transmission of the data to the cloud with Edge Computing, and then to have a complete overview in terms of monthly resource efficiency through the Data Envelopment Analysis. The results show that including the costs of edge and non-edge data transfer have an impact on the efficiency. This small-scale study set the basis for a future test with many farms simultaneously.
New Bis-Pyrazole-Bis-Acetate Based Coordination Complexes: Influence of Counter-Anions and Metal Ions on the Supramolecular Structures
Authors: Oulmidi Afaf , Radi Smaail , Miras Haralampos N. , Adarsh Nayarassery N. , Garcia Yann
Published: December 2020

A new flexible bis-pyrazol-bis-acetate ligand, diethyl 2,2’-(pyridine-2,6-diylbis (5-methyl-1H-pyrazole-3,1-diyl))diacetate (L), has been synthesised, and three coordination complexes, namely, [Zn(L)2](BF4)2 (1), [MnLCl2] (2) and [CdLCl2] (3) have been obtained. All ligands and complexes were characterised by IR, mass spectroscopy, thermogravimetric analysis and single-crystal X-ray diffraction. Single crystal X-ray diffraction experiment revealed that the primary supramolecular building block of 1 is a hexagonal chair shaped 0D hydrogen bonded synthon (stabilised by C–H∙∙∙O hydrogen bonding and C=O∙∙∙π interactions), which further built into a 2D corrugated sheet-like architecture having a 3-c net honeycomb topology, and finally extended to a 3D hydrogen bonded network structure having a five nodal 1,3,3,3,7-c net, through C–H∙∙∙F interactions. On the other hand, the two crystallographically independent molecules of 2 exhibited two distinct supramolecular structures such as 2D hydrogen bonded sheet structure and 1D zigzag hydrogen bonded chain, sustained by C–H∙O and C–H∙∙∙Cl interactions, which are further self-assembled into a 3,4-c network structure, and 3 showed a 2D hydrogen bonded sheet structure. The supramolecular structural diversity in these complexes is due to the different conformations adopted by the ligands, which are mainly induced by different metal ions with coordination environments controlled by different anions. Hirshfeld surface analysis was explored for the qualitative and quantitative analysis of the supramolecular interactions.
Cybersecurity Policy and the Legislative Context of the Water and Wastewater Sector in South Africa
Authors: Malatji Masike , Marnewick Annlizé L. , von Solms Suné
Published: December 2020

The water and wastewater sector is an important lifeline upon which other economic sectors depend. Securing the sector’s critical infrastructure is therefore important for any country’s economy. Like many other nations, South Africa has an overarching national cybersecurity strategy aimed at addressing cyber terrorism, cybercriminal activities, cyber vandalism, and cyber sabotage. The aim of this study is to contextualise the water and wastewater sector’s cybersecurity responsibilities within the national cybersecurity legislative and policy environment. This is achieved by conducting a detailed analysis of the international, national and sector cybersecurity stakeholders; legislation and policies; and challenges pertaining to the protection of the water and wastewater sector. The study found some concerning challenges and improvement gaps regarding the complex manner in which the national government is implementing the cybersecurity strategy. The study also found that, along with the National Cybersecurity Policy Framework (the national cybersecurity strategy of South Africa), the Electronic Communications and Transactions Act, Critical Infrastructure Protection Act, and other supporting legislation and policies make provision for the water and wastewater sector’s computer security incidents response team to be established without the need to propose any new laws or amend existing ones. This is conducive for the immediate development of the sector-specific cybersecurity governance framework and resilience strategy to protect the water and wastewater assets.
The Role of Green and Blue Hydrogen in the Energy Transition—A Technological and Geopolitical Perspective
Authors: Noussan Michel , Raimondi Pier Paolo , Scita Rossana , Hafner Manfred
Published: December 2020

Hydrogen is currently enjoying a renewed and widespread momentum in many national and international climate strategies. This review paper is focused on analysing the challenges and opportunities that are related to green and blue hydrogen, which are at the basis of different perspectives of a potential hydrogen society. While many governments and private companies are putting significant resources on the development of hydrogen technologies, there still remains a high number of unsolved issues, including technical challenges, economic and geopolitical implications. The hydrogen supply chain includes a large number of steps, resulting in additional energy losses, and while much focus is put on hydrogen generation costs, its transport and storage should not be neglected. A low-carbon hydrogen economy offers promising opportunities not only to fight climate change, but also to enhance energy security and develop local industries in many countries. However, to face the huge challenges of a transition towards a zero-carbon energy system, all available technologies should be allowed to contribute based on measurable indicators, which require a strong international consensus based on transparent standards and targets.
Decision Support in Selecting Airfield Pavement Design Alternatives Using Life Cycle Assessment: Case Study of Nashville Airport
Authors: Butt Ali Azhar , Harvey John , Saboori Arash , Ostovar Maryam , Bejarano Manuel , Garg Navneet
Published: December 2020

The Federal Aviation Administration (FAA) has taken measures to improve safety, reduce costs, increase resilience, and improve the sustainability of the United States (U.S.) airfield infrastructure by using a life-cycle cost analysis methodology to increase the efficient use of economic resources needed for expanding and preserving the airfield system. However, a life-cycle assessment (LCA) approach for evaluating the environmental impacts of decisions regarding airfield infrastructure has yet to be fully developed and applied. The objective of this study is to demonstrate the use of the airfield LCA framework that was developed for the FAA and can be used by U.S. airports. The comparison of alternative pavement designs at Nashville International Airport (BNA) is presented. The scope of the study was from cradle to laid; materials, materials transportation, and construction stages of the pavement life cycle are considered, and the maintenance, use and end of life stages are not considered. Primary data were acquired from BNA and secondary data were used in situations of unavailability of primary data. The case study showed that performing LCA provides opportunities for airports to consider energy use and environment-related impacts in the decision-making process.
Does CSR Help to Retain Customers in a Service Company?
Authors: Fandos-Roig Juan Carlos , Sánchez-García Javier , Tena-Monferrer Sandra , Callarisa-Fiol Luis José
Published: December 2020

The main aim of this paper is to analyze the influence of service companies’ corporate social responsibility (CSR) actions on final customer’s loyalty. A theoretical model of loyalty formation based on CSR was proposed and a sample of 1125 final customers of financial services in Spain was studied. Structural equation models were used to verify the hypothesized relationships. Based on the CSR theory oriented to stakeholders, this work justifies the direct and positive relationship between the perception of CSR actions in the shopping experience and customer trust. We also verified a positive indirect influence on loyalty. The services industry was chosen to conduct this research due to its own particularities (intangibility, inseparability, heterogeneity and perishability). As it is impossible to evaluate a service before its consumption, a high level of trust in the supplier will be necessary to motivate the purchase decision. We conclude that CSR becomes a key strategic asset for determining trust and loyalty among consumers. As major findings, we have verified the special importance of CSR in the services market. CSR improves customer trust in the service provider. Thus, this paper has significant managerial implications. Through CSR strategies, both the perception of the customer’s purchasing experience and trust can be enhanced, resulting in more loyal customers. As a limitation, this research was carried out among financial services. Further research should test the model across different industries and countries in order to determine the generalizability and consistency of the findings of this study.
Understanding China’s National Emergency Command System from the Perspective of Power and Responsibility Allocation
Authors: Kong Feng
Published: December 2020

The structure between the Party and the government is the core and soul of China’s emergency management, and the allocation of power and responsibility is the core of China’s national emergency command system (NECS). The allocation of power and responsibility between the Party and the government, as well as between departments, is the main aspect of the allocation of power and responsibility in China, and is also an important component of the NECS. This paper mainly introduces the characteristics of power and responsibility allocation between the Party and the government, as well as between departments in China’s NECS, and analyzes the above-mentioned power and responsibility allocation, based on the prevention and control of SARS (severe acute respiratory syndrome) and COVID-19 (coronavirus disease 2019), and analyzes their development, changes, and unchanged characteristics. Through the above analysis, we found that the Party’s leadership style in dealing with emergencies has changed from indirect leadership to direct leadership. The joint defense and control mechanism has replaced the national headquarters of emergency management as the common mode.
Place-Based Citizen Science for Assessing Risk Perception and Coping Capacity of Households Affected by Multiple Hazards
Authors: Alves Priscila Barros Ramalho , Cordão Maria José de Sousa , Djordjević Slobodan , Javadi Akbar A.
Published: December 2020

Since hazards act upon vulnerability and exposure to become disasters, the understanding of societal challenges is key for disaster risk reduction. This condition is even more critical when more than one hazard is in place. Taking the case of flooding and water shortage, this study is built upon the premise that disasters are a social phenomenon; therefore, it is essential to comprehend the social context in which they occur. Particularly, this study aims to evaluate the similarities and differences in risk perception and the coping capacity of residents in the multiple-hazard context. For this, a place-based citizen science approach was developed in this study in Campina Grande, a semiarid region of Brazil, with the collaboration of 199 participants. Risk perception and coping capacity were analysed through the citizens’ participation, while combining subjective and objective methods. The results indicate that even though residents have experienced severe flooding and water shortages in the past, they still have low coping capacity. The findings highlight the need to combine a triad of societal challenges, namely information, trust, and incentives, to improve coping capacity in the future and increase resilience. This study underlines the need to understand multiple hazards according to social, spatial, and temporal scales in a socio-spatial perspective.