bluuebunny/crossref_metadata_2025 huggingface dataset:
3D Human Pose Estimation with a Catadioptric Sensor in Unconstrained Environments Using an Annealed Particle Filter
Authors: Ababsa Fakhreddine , Hadj-Abdelkader Hicham , Boui Marouane
Published: December 2020

The purpose of this paper is to investigate the problem of 3D human tracking in complex environments using a particle filter with images captured by a catadioptric vision system. This issue has been widely studied in the literature on RGB images acquired from conventional perspective cameras, while omnidirectional images have seldom been used and published research works in this field remains limited. In this study, the Riemannian varieties was considered in order to compute the gradient on spherical images and generate a robust descriptor used along with an SVM classifier for human detection. Original likelihood functions associated with the particle filter are proposed, using both geodesic distances and overlapping regions between the silhouette detected in the images and the projected 3D human model. Our approach was experimentally evaluated on real data and showed favorable results compared to machine learning based techniques about the 3D pose accuracy. Thus, the Root Mean Square Error (RMSE) was measured by comparing estimated 3D poses and truth data, resulting in a mean error of 0.065 m when walking action was applied.
Deep Learning Based Antenna Selection for MIMO SDR System
Authors: Zhong Shida , Feng Haogang , Zhang Peichang , Xu Jiajun , Luo Huancong , Zhang Jihong , Yuan Tao , Huang Lei
Published: December 2020

In this paper, we propose and implement a novel framework of deep learning based antenna selection (DLBAS)-aided multiple-input–multiple-output (MIMO) software defined radio (SDR) system. The system is constructed with the following three steps: (1) a MIMO SDR communication platform is first constructed, which is capable of achieving uplink communication from users to the base station via time division duplex (TDD); (2) we use the deep neural network (DNN) from our previous work to construct a deep learning decision server to assist the MIMO SDR platform for making intelligent decision for antenna selection, which transforms the optimization-driven decision making method into a data-driven decision making method; and (3) we set up the deep learning decision server as a multithreading server to improve the resource utilization ratio. To evaluate the performance of the DLBAS-aided MIMO SDR system, a norm-based antenna selection (NBAS) scheme is selected for comparison. The results show that the proposed DLBAS scheme performed equally to the NBAS scheme in real-time and out-performed the MIMO system without AS with up to 53% improvement on average channel capacity gain.
A Review on Map-Merging Methods for Typical Map Types in Multiple-Ground-Robot SLAM Solutions
Authors: Yu Shuien , Fu Chunyun , Gostar Amirali K. , Hu Minghui
Published: December 2020

When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the environment. Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM. This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps. These map-merging approaches are classified based on their working mechanism or the type of features they deal with. The concepts and characteristics of these map-merging methods are elaborated in this review. The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.
Biomedical Signal Acquisition Using Sensors under the Paradigm of Parallel Computing
Authors: Moreno Escobar Jesús Jaime , Morales Matamoros Oswaldo , Tejeida Padilla Ricardo , Chanona Hernández Liliana , Posadas Durán Juan Pablo Francisco , Pérez Martínez Ana Karen , Lina Reyes Ixchel , Quintana Espinosa Hugo
Published: December 2020

There are several pathologies attacking the central nervous system and diverse therapies for each specific disease. These therapies seek as far as possible to minimize or offset the consequences caused by these types of pathologies and disorders in the patient. Therefore, comprehensive neurological care has been performed by neurorehabilitation therapies, to improve the patients’ life quality and facilitating their performance in society. One way to know how the neurorehabilitation therapies contribute to help patients is by measuring changes in their brain activity by means of electroencephalograms (EEG). EEG data-processing applications have been used in neuroscience research to be highly computing- and data-intensive. Our proposal is an integrated system of Electroencephalographic, Electrocardiographic, Bioacoustic, and Digital Image Acquisition Analysis to provide neuroscience experts with tools to estimate the efficiency of a great variety of therapies. The three main axes of this proposal are: parallel or distributed capture, filtering and adaptation of biomedical signals, and synchronization in real epochs of sampling. Thus, the present proposal underlies a general system, whose main objective is to be a wireless benchmark in the field. In this way, this proposal could acquire and give some analysis tools for biomedical signals used for measuring brain interactions when it is stimulated by an external system during therapies, for example. Therefore, this system supports extreme environmental conditions, when necessary, which broadens the spectrum of its applications. In addition, in this proposal sensors could be added or eliminated depending on the needs of the research, generating a wide range of configuration limited by the number of CPU cores, i.e., the more biosensors, the more CPU cores will be required. To validate the proposed integrated system, it is used in a Dolphin-Assisted Therapy in patients with Infantile Cerebral Palsy and Obsessive–Compulsive Disorder, as well as with a neurotypical one. Event synchronization of sample periods helped isolate the same therapy stimulus and allowed it to be analyzed by tools such as the Power Spectrum or the Fractal Geometry.
Transfer Learning for Wireless Fingerprinting Localization Based on Optimal Transport
Authors: Bai Siqi , Luo Yongjie , Wan Qun
Published: December 2020

Wireless fingerprinting localization (FL) systems identify locations by building radio fingerprint maps, aiming to provide satisfactory location solutions for the complex environment. However, the radio map is easy to change, and the cost of building a new one is high. One research focus is to transfer knowledge from the old radio maps to a new one. Feature-based transfer learning methods help by mapping the source fingerprint and the target fingerprint to a common hidden domain, then minimize the maximum mean difference (MMD) distance between the empirical distributions in the latent domain. In this paper, the optimal transport (OT)-based transfer learning is adopted to directly map the fingerprint from the source domain to the target domain by minimizing the Wasserstein distance so that the data distribution of the two domains can be better matched and the positioning performance in the target domain is improved. Two channel-models are used to simulate the transfer scenarios, and the public measured data test further verifies that the transfer learning based on OT has better accuracy and performance when the radio map changes in FL, indicating the importance of the method in this field.
Enhancing Classification Performance of fNIRS-BCI by Identifying Cortically Active Channels Using the z-Score Method
Authors: Nazeer Hammad , Naseer Noman , Mehboob Aakif , Khan Muhammad Jawad , Khan Rayyan Azam , Khan Umar Shahbaz , Ayaz Yasar
Published: December 2020

A state-of-the-art brain–computer interface (BCI) system includes brain signal acquisition, noise removal, channel selection, feature extraction, classification, and an application interface. In functional near-infrared spectroscopy-based BCI (fNIRS-BCI) channel selection may enhance classification performance by identifying suitable brain regions that contain brain activity. In this study, the z-score method for channel selection is proposed to improve fNIRS-BCI performance. The proposed method uses cross-correlation to match the similarity between desired and recorded brain activity signals, followed by forming a vector of each channel’s correlation coefficients’ maximum values. After that, the z-score is calculated for each value of that vector. A channel is selected based on a positive z-score value. The proposed method is applied to an open-access dataset containing mental arithmetic (MA) and motor imagery (MI) tasks for twenty-nine subjects. The proposed method is compared with the conventional t-value method and with no channel selected, i.e., using all channels. The z-score method yielded significantly improved (p < 0.0167) classification accuracies of 87.2 ± 7.0%, 88.4 ± 6.2%, and 88.1 ± 6.9% for left motor imagery (LMI) vs. rest, right motor imagery (RMI) vs. rest, and mental arithmetic (MA) vs. rest, respectively. The proposed method is also validated on an open-access database of 17 subjects, containing right-hand finger tapping (RFT), left-hand finger tapping (LFT), and dominant side foot tapping (FT) tasks.The study shows an enhanced performance of the z-score method over the t-value method as an advancement in efforts to improve state-of-the-art fNIRS-BCI systems’ performance.
Hierarchical Optimization of 3D Point Cloud Registration
Authors: Liu Huikai , Zhang Yue , Lei Linjian , Xie Hui , Li Yan , Sun Shengli
Published: December 2020

Rigid registration of 3D point clouds is the key technology in robotics and computer vision. Most commonly, the iterative closest point (ICP) and its variants are employed for this task. These methods assume that the closest point is the corresponding point and lead to sensitivity to the outlier and initial pose, while they have poor computational efficiency due to the closest point computation. Most implementations of the ICP algorithm attempt to deal with this issue by modifying correspondence or adding coarse registration. However, this leads to sacrificing the accuracy rate or adding the algorithm complexity. This paper proposes a hierarchical optimization approach that includes improved voxel filter and Multi-Scale Voxelized Generalized-ICP (MVGICP) for 3D point cloud registration. By combining traditional voxel sampling with point density, the outlier filtering and downsample are successfully realized. Through multi-scale iteration and avoiding closest point computation, MVGICP solves the local minimum problem and optimizes the operation efficiency. The experimental results demonstrate that the proposed algorithm is superior to the current algorithms in terms of outlier filtering and registration performance.
City Data Hub: Implementation of Standard-Based Smart City Data Platform for Interoperability
Authors: Jeong Seungmyeong , Kim Seongyun , Kim Jaeho
Published: December 2020

Like what happened to the Internet of Things (IoT), smart cities have become abundant in our lives as well. One of the smart city definitions commonly used is that smart cities solve city problems to enhance citizens’ life quality and make cities sustainable. From the perspective of information and communication technologies (ICT), we think this can be done by collecting and analyzing data to generate insights. The City Data Hub, which is a standard-based city data platform that has been developed, and a couple of problem-solving examples have been demonstrated. The key elements for smart city platforms have been chosen and they have been included in the core architecture principles and implemented as a platform. It has been proven that standard application programming interfaces (APIs) and common data models with data marketplaces, which are the keys, increase interoperability and guarantee ecosystem extensibility.
A Novel Broadband Monopole Antenna with T-Slot, CB-CPW, Parasitic Stripe and Heart-Shaped Slice for 5G Applications
Authors: Ding Zhendong , Wang Hao , Tao Shifei , Zhang Dan , Ma Chunyu , Zhong Yunxian
Published: December 2020

This paper presents a novel broadband monopole antenna that was equipped with a bottom semicircle ground structure, a parasitic patch, a T-shaped slot, s transmission line, a parasitic strip, heart-shaped slices and a coplanar waveguide (CPW). The simulation results revealed that the proposed design had a relatively high return loss, a wide bandwidth and high efficiency. A prototype of the proposed antenna with an overall size of 0.94 λ0 × 0.94 λ0 × 0.02 λ0 (λ0 is the free-space wavelength) was fabricated and measured. The measurement results showed that the prototype had a bandwidth of 4.02 GHz (4.69–8.71 GHz) and a relative bandwidth of 60%. Besides, the maximum gain was 3.31 dBi and the maximum efficiency was 91.1% in the range of 5 to 8.5 GHz. Furthermore, it was found that the prototype almost achieved omnidirectional radiation. Its operating frequency band covered those of industrial scientific medical (ISM) (5.725–5.850 GHz), the radio frequency identification (RFID) (5.8 GHz) and the wireless local area network (WLAN) (5.15–5.25 GHz and 5.725–5.825 GHz).
Combining Artificial Neural Network and Ordinary Kriging to Predict Wetland Soil Organic Carbon Concentration in China’s Liao River Basin
Authors: Kang Yingdong , Li Xiaoyan , Mao Dehua , Wang Zongming , Liang Mingxuan
Published: December 2020

Accurate prediction of wetland soil organic carbon concentration and an understanding of its controlling factors are important for studying regional climate change and wetland carbon cycles; with that knowledge mechanisms can be put in place that are conducive to sustainable ecosystem management for environmental health. In this study, a hybrid approach combining an artificial neural network and ordinary kriging and 103 soil samples at three soil depth ranges (0–30, 30–60, and 60–100 cm) were used to predict wetland soil organic carbon concentration in China’s Liao River Basin. The model evaluation indicated that a combination of artificial neural network and ordinary kriging and limited soil samples achieved good performance in predicting wetland soil organic carbon concentration. Wetland soil organic carbon concentration in the Liao River Basin has apparent spatial and vertical heterogeneities with values decreasing from southeast to northwest and concentrates present mainly in the topsoil (0–30 cm). Mean wetland soil organic carbon concentration values at the three soil depths were 10.43 ± 0.38, 7.93 ± 0.25, and 7.61 ± 0.22 g/kg, respectively, which are smaller than those over other wetland regions in Northeast China. Terrain aspect contributed the most in predicting wetland soil organic carbon concentration at each of the three soil depths, followed by normalized difference vegetation index at 0–30 cm and mean annual precipitation at 30–60 and 60–100 cm. This study provides a framework method and baseline to quantify the soil organic carbon concentration dynamics in response to climatic and anthropogenic drivers.
Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence
Authors: Liu Zhansheng , Shi Guoliang , Zhang Anshan , Huang Chun
Published: December 2020

In this study, to address the problems of multiple dimensions, large scales, complex tension resource scheduling, and strict quality control requirements in the tensioning process of cables in prestressed steel structures, the technical characteristics of digital twins (DTs) and artificial intelligence (AI) are analyzed. An intelligent tensioning of prestressed cables method driven by the integration of DTs and AI is proposed. Based on the current research status of cable tensioning and DTs, combined with the goal of intelligent tensioning, a fusion mechanism for DTs and AI is established and their integration to drive intelligent tensioning of prestressed cables technology is analyzed. In addition, the key issues involved in the construction of an intelligent control center driven by the integration of DTs and AI are discussed. By considering the construction elements of space and time dimensions, the tensioning process is controlled at multiple levels, thereby realizing the intelligent tensioning of prestressed cables. Driven by intelligent tensioning methods, the safety performance evaluation of the intelligent tensioning process is analyzed. Combined with sensing equipment and intelligent algorithms, a high-fidelity twin model and three-dimensional integrated data model are constructed to realize closed-loop control of the intelligent tensioning safety evaluation. Through the study of digital twins and artificial intelligence fusion to drive the intelligent tensioning method for prestressed cables, this study focuses on the analysis of the intelligent evaluation of safety performance. This study provides a reference for fusion applications with DTs and AI in intelligent tensioning of prestressed cables.
Extraction of Land Information, Future Landscape Changes and Seismic Hazard Assessment: A Case Study of Tabriz, Iran
Authors: Mohammadi Ayub , Karimzadeh Sadra , Valizadeh Kamran Khalil , Matsuoka Masashi
Published: December 2020

Exact land cover inventory data should be extracted for future landscape prediction and seismic hazard assessment. This paper presents a comprehensive study towards the sustainable development of Tabriz City (NW Iran) including land cover change detection, future potential landscape, seismic hazard assessment and municipal performance evaluation. Landsat data using maximum likelihood (ML) and Markov chain algorithms were used to evaluate changes in land cover in the study area. The urbanization pattern taking place in the city was also studied via synthetic aperture radar (SAR) data of Sentinel-1 ground range detected (GRD) and single look complex (SLC). The age of buildings was extracted by using built-up areas of all classified maps. The logistic regression (LR) model was used for creating a seismic hazard assessment map. From the results, it can be concluded that the land cover (especially built-up areas) has seen considerable changes from 1989 to 2020. The overall accuracy (OA) values of the produced maps for the years 1989, 2005, 2011 and 2020 are 96%, 96%, 93% and 94%, respectively. The future potential landscape of the city showed that the land cover prediction by using the Markov chain model provided a promising finding. Four images of 1989, 2005, 2011 and 2020, were employed for built-up areas’ land information trends, from which it was indicated that most of the built-up areas had been constructed before 2011. The seismic hazard assessment map indicated that municipal zones of 1 and 9 were the least susceptible areas to an earthquake; conversely, municipal zones of 4, 6, 7 and 8 were located in the most susceptible regions to an earthquake in the future. More findings showed that municipal zones 1 and 4 demonstrated the best and worst performance among all zones, respectively.
Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method
Authors: Xiao Feng , Li Fei , Zhang Shengkai , Li Jiaxing , Geng Tong , Xuan Yue
Published: December 2020

Satellite altimeters can be used to derive long-term and large-scale sea ice thickness changes. Sea ice thickness retrieval is based on measurements of freeboard, and the conversion of freeboard to thickness requires knowledge of the snow depth and snow, sea ice, and sea water densities. However, these parameters are difficult to be observed concurrently with altimeter measurements. The uncertainties in these parameters inevitably cause uncertainties in sea ice thickness estimations. This paper introduces a new method based on least squares adjustment (LSA) to estimate Arctic sea ice thickness with CryoSat-2 measurements. A model between the sea ice freeboard and thickness is established within a 5 km × 5 km grid, and the model coefficients and sea ice thickness are calculated using the LSA method. Based on the newly developed method, we are able to derive estimates of the Arctic sea ice thickness for 2010 through 2019 using CryoSat-2 altimetry data. Spatial and temporal variations of the Arctic sea ice thickness are analyzed, and comparisons between sea ice thickness estimates using the LSA method and three CryoSat-2 sea ice thickness products (Alfred Wegener Institute (AWI), Centre for Polar Observation and Modelling (CPOM), and NASA Goddard Space Flight Centre (GSFC)) are performed for the 2018–2019 Arctic sea ice growth season. The overall differences of sea ice thickness estimated in this study between AWI, CPOM, and GSFC are 0.025 ± 0.640 m, 0.143 ± 0.640 m, and −0.274 ± 0.628 m, respectively. Large differences between the LSA and three products tend to appear in areas covered with thin ice due to the limited accuracy of CryoSat-2 over thin ice. Spatiotemporally coincident Operation IceBridge (OIB) thickness values are also used for validation. Good agreement with a difference of 0.065 ± 0.187 m is found between our estimates and the OIB results.
A Routing Algorithm Based on Real-Time Information Traffic in Sparse Environment for VANETs
Authors: Liu Jianhang , Bai Fan , Weng Haonan , Li Shibao , Cui Xuerong , Zhang Yucheng
Published: December 2020

Because of the specific characteristics, like high vehicular mobility, unstable topology, and interruption of inter-vehicle wireless communication, it is hard to make a perfect decision on packet forwarding in highly dynamic topology VANETs. Especially in a sparse urban environment, the poor connectivity of nodes will mostly cause problems such as data packet loss and routing redundancy. Therefore, how to choose the best relay node becomes a key challenge in the design of fast and reliable routing protocols. This paper presents real-time effective information traffic routing (RTEIT), which provides an optimal route for forwarding the data packets toward their destination when choosing the relay node. RTEIT introduces a new network parameter named effective information traffic which can estimate the connectivity of nodes by the path that has been successfully created. Moreover, for avoiding unexpected communication interruption, we propose a new formula to evaluate the status of the links via considering the speed, direction, and location information. Finally, the node utility, as the criterion of routing decision, is calculated by effective information traffic and link status. We use the simulator of SUMO and NS-3 platform to evaluate RTEIT, and the results are compared with GPSR MOPR, and MM-GPSR. The evaluation results demonstrate that RTEIT outperforms in terms of packet loss rate, end-to-end delay, and network yield.
Mechanical Flexibility of DNA: A Quintessential Tool for DNA Nanotechnology
Authors: Saran Runjhun , Wang Yong , Li Isaac T. S.
Published: December 2020

The mechanical properties of DNA have enabled it to be a structural and sensory element in many nanotechnology applications. While specific base-pairing interactions and secondary structure formation have been the most widely utilized mechanism in designing DNA nanodevices and biosensors, the intrinsic mechanical rigidity and flexibility are often overlooked. In this article, we will discuss the biochemical and biophysical origin of double-stranded DNA rigidity and how environmental and intrinsic factors such as salt, temperature, sequence, and small molecules influence it. We will then take a critical look at three areas of applications of DNA bending rigidity. First, we will discuss how DNA’s bending rigidity has been utilized to create molecular springs that regulate the activities of biomolecules and cellular processes. Second, we will discuss how the nanomechanical response induced by DNA rigidity has been used to create conformational changes as sensors for molecular force, pH, metal ions, small molecules, and protein interactions. Lastly, we will discuss how DNA’s rigidity enabled its application in creating DNA-based nanostructures from DNA origami to nanomachines.
Safety Evaluation and Experimental Study of a New Bionic Muscle Cable-Driven Lower Limb Rehabilitation Robot
Authors: Wang Yan Lin , Wang Ke Yi , Wang Kui Cheng , Mo Zong Jun
Published: December 2020

Safety is a significant evaluation index of rehabilitation medical devices and a significant precondition for practical application. However, the safety evaluation of cable-driven rehabilitation robots has not been reported, so this work aims to study the safety evaluation methods and evaluation index of cable-driven rehabilitation robots. A bionic muscle cable (BM cable) is proposed to construct a bionic muscle cable-driven lower limb rehabilitation robot (BM-CDLR). The working principle of the BM-CDLR is introduced. The safety performance factors are defined based on the mechanical analysis of the BM-CDLR. The structural safety evaluation index and the use safety evaluation index of the BM-CDLR are given by comprehensively considering the safety performance factors and a proposed speed influence function. The effect of the structural parameters of the elastic elements in the BM cable on the safety performance factors and safety of the BM-CDLR is analyzed and verified by numerical simulations and experimental studies. The results provide the basis for further study of the compliance control strategy and experiments of the human-machine interaction of the BM-CDLR.
Numerical Analysis of MIM-Based Log-Spiral Rectennas for Efficient Infrared Energy Harvesting
Authors: Yahyaoui Ali , Elsharabasy Ahmed , Yousaf Jawad , Rmili Hatem
Published: December 2020

This work presents the design and analysis of a metal-insulator-metal (MIM)-based optical log spiral rectenna for efficient energy harvesting at 28.3 THz. To maximize the benefits of the enhanced field of the proposed nano-antenna in the rectification process, the proposed design considers the antenna arms (Au) as the electrodes of the rectifying diode and the insulator is placed between the electrode terminals for the compact design of the horizontal MIM rectenna. The rectifier insulator, Al2O3, was inserted at the hotspot located in the gap between the antennas. A detailed analysis of the effect of different symmetric and asymmetric MIM-configurations (Au-Al2O3-Ag, Au-Al2O3-Al, Au-Al2O3-Cr, Au-Al2O3-Cu, and Au-Al2O3-Ti) was conducted. The results of the study suggested that the asymmetric configuration of Au-Al2O3-Ag provides optimal results. The proposed design benefits from the captured E-field intensity, I-V, resistivity, and responsivity and results in a rectenna that performs efficiently.
Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration
Authors: Rawa Muhyaddin , Abusorrah Abdullah , Al-Turki Yusuf , Mekhilef Saad , Mostafa Mostafa H. , Ali Ziad M. , Aleem Shady H. E. Abdel
Published: December 2020

Recent advances in using renewable energy resources make them more accessible and prevalent in microgrids (MGs) and nano grids (NGs) applications. Accordingly, much attention has been paid during the past few years to design and operate MGs with high renewable energy sources (RESs) penetration. Energy storage (ES) is the crucial enabler for reliable MG operation to help MGs become more resistant to disruptions, particularly with the increased penetration of RESs. In this regard, this paper formulates a two-stage optimization framework to improve a grid-connected MG performance. Firstly, the optimal allocation decisions of the battery ES systems (BESSs) are provided to enhance the self-consumption rate of the RESs and the hosting capacity (HC) of the MG. Secondly, an operation strategy with the results (number, location, and capacity) of the BESSs obtained from the first stage is handled as an objective function to minimize the MG’s total operation cost. The IEEE 33-bus radial system is modified to act as the MG with high RESs penetration. The problem is solved using a recent swarm intelligence optimization algorithm called the Harris hawks optimization (HHO) algorithm. The proposed optimal operation strategy considers numerous constraints, such as the charge-discharge balance, number and capacity limitations of the BESSs, and the different technical performance constraints of the MG. The results obtained verify the proposed optimization framework’s effectiveness for grid-connected MGs and validate the benefits gained from the appropriate allocation of BESSs. The results also indicate that oversized storage or using many unneeded storage units may adversely influence the MG’s total power losses.
Valuation of FinTech Innovation Based on Patent Applications
Authors: Kabulova Jelena , Stankevičienė Jelena
Published: December 2020

The financial services sector, perhaps more than any other, is being disrupted by advances in technology. The purpose of this study is to provide comprehensive data and evidence on value of the FinTech innovation event. First, a text-based filtering method for identifying FinTech patent applications is provided. Using machine learning applications, innovations are classified into major technology groups. The methodology for valuation of FinTech innovation is based on data of stock price changes. To assess the value impact, Poisson flow rates and stock price movements were combined. Further, to evaluate the effect of FinTech patents on the company’s value, a combination of CAR of patent application and Poisson intensities were used. Research findings provide evidence that FinTech innovations bring significant value for innovators and Blockchain being especially valuable. Such innovations as blockchain, robo-advising and mobile transactions are the most valuable for the financial sector. On one side of the spectrum, the financial industry can be affected more negatively by the innovation of nonfinancial startups that carry disruptive technology at their core. However, on the other side of the spectrum, market leaders who make significant investments in their innovations can evade most of these negative effects. This helped to form an overall view of FinTech innovations.
A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network
Authors: Amin Adil , Tareen Wajahat Ullah Khan , Usman Muhammad , Ali Haider , Bari Inam , Horan Ben , Mekhilef Saad , Asif Muhammad , Ahmed Saeed , Mahmood Anzar
Published: December 2020

This study summarizes a critical review on EVs’ optimal charging and scheduling under dynamic pricing schemes. A detailed comparison of these schemes, namely, Real Time Pricing (RTP), Time of Use (ToU), Critical Peak Pricing (CPP), and Peak Time Rebates (PTR), is presented. Globally, the intention is to reduce the carbon emissions (CO2) has motivated the extensive practice of Electric Vehicles (EVs). The uncoordinated charging and uncontrolled integration however of EVs to the distribution network deteriorates the system performance in terms of power quality issues. Therefore, the EVs’ charging activity can be coordinated by dynamic electricity pricing, which can influence the charging activities of the EVs customers by offering flexible pricing at different demands. Recently, with developments in technology and control schemes, the RTP scheme offers more promise compared to the other types of tariff because of the greater flexibility for EVs’ customers to adjust their demands. It however involves higher degree of billing instability, which may influence the customer’s confidence. In addition, the RTP scheme needs a robust intelligent automation system to improve the customer’s feedback to time varying prices. In addition, the review covers the main optimization methods employed in a dynamic pricing environment to achieve objectives such as power loss and electricity cost minimization, peak load reduction, voltage regulation, distribution infrastructure overloading minimization, etc.
Sustainability of Portuguese Courts: Citizen Satisfaction and Loyalty as Key Factors
Authors: Pereira Sandra Patrícia Marques , Correia Pedro Miguel Alves Ribeiro
Published: December 2020

This paper aims to describe the satisfaction and loyalty of citizens towards the sustainability of Portuguese courts. This research was carried out under the Portuguese justice agenda named “Justice + Closer” between the years of 2017, 2018, and 2019. The methodological approach adopted was quantitative. Based on the literature review, a structural model of the relationships between the dimensions that directly and indirectly influence citizen satisfaction and loyalty was adapted from the arbitration centers to the court’s reality. Data collection was carried out during the three years mentioned—in person at the Portuguese Campus of Justice and also through questionnaires applied online. In the course of the three years, 3276 observations were collected. Through structural equation modeling, it was possible to measure positive relations produced between seven established dimensions. The results of this study contribute generally to applied research in the field of justice administration and to the understanding of this topic by those in the academic sector where it has been superficially addressed. Related future investigations might include a comparative study between the satisfaction and loyalty of citizens with (i) the formal adjudication processes and case outcomes of the Portuguese courts and (ii) alternative dispute-resolution processes and case outcome means reached by recognized arbitration and mediation centers, judges of peace, and related ADR services.
Energy Expenditure and Physical Activity in a University Population in the Coastal Region of Ecuador
Authors: Hernández-Gallardo Damaris , Arencibia-Moreno Ricardo , Linares-Girela Daniel , Saca-Plua Iván Jesús , Linares-Manrique Marta
Published: December 2020

Background: Variations in physical activity greatly affect total energy expenditure, and therefore its examination contributes to the prevention of systemic disease. We sought to evaluate energy expenditure and physical activity within a university population from the coastal region of Ecuador. Methods: A descriptive and observational research study was developed to compare 1038 university students. Weight, height, resting metabolic rate and estimated energy needs were estimated. A 24 h recall questionnaire was administered to examine the relationship between total energy expenditure and physical activity. The “IPAQ” (international physical activity questionnaire) was employed to classify the type of physical activity performed and weekly metabolic equivalent (MET) minutes were calculated. Results: Male and female participants showed total energy expenditures of 2571.26 ± 321.26 and 1924.75 ± 112.78 kcal/day, respectively, with resting metabolic rates of 1864.12 ± 206.67 and 1373.96 ± 178.28 kcal/day, respectively. A total of 81.88% of the population reported being sedentary. With regards to time distribution between activities, insignificant time was dedicated to sport and health-related activities. Weekly MET minute expenditure was classified as low in 45.37% of individuals, moderate in 52.2%, and high in 3% of individuals. Conclusions: We conclude that the studied population led a notably sedentary lifestyle, which was contingent on voluntary behavioural states including the avoidance of certain exercises. Such tendencies are harmful to health.
Green Procurement Practices in Romania: Evidence from a Survey at the Level of Local Authorities
Authors: Ciumara Tudor , Lupu Iulia
Published: December 2020

Public procurement is considered an important driver of an economy and has a considerable power in orienting the market, including toward environmental protection policies and strategies. This study examines the green public procurement practiced at the level of local Romanian authorities with the aim of understanding the real context by highlighting the mix between what is required and/or expected from local authorities and what is actually happening in terms of green public procurement. The research is based on the results of an online survey conducted from 16 August 2019 to 18 September 2019. The research results show that green procurement is not a subject approached in many administrative units; however, it appears that environmental protection in the context of public procurement is considered important. In line with other research, our results enrich the current knowledge on green procurement practices at the local government level and indicate that increased regulatory pressure for green public procurement may lead to market development and innovation for green goods and services.
Does Gender Diversity Affect the Environmental Performance of Banks?
Authors: Gallego-Sosa Clara , Fernández-Torres Yakira , Gutiérrez-Fernández Milagros
Published: December 2020

Climate change is one of the greatest challenges facing humanity today. Therefore, all segments of society must act together to stop the deterioration of the planet and the depletion of its resources. The business sector must play an active role in acting responsibly toward the environment. Given the importance of this issue, major efforts have been made to analyze the environmental performance of the most polluting sectors. In contrast, other sectors that are also of great interest due to their contribution to sustainable development, such as the banking sector, have been overlooked. Notable factors conditioning performance include aspects of corporate governance such as gender diversity. However, the empirical evidence reveals a lack of consensus regarding the influence of women directors on corporate environmental performance. This background motivates the study of the commitment of the banking sector to reducing their environmental impact and the analysis the influence of board gender diversity on environmental performance. Data for the period 2009 to 2018 on 52 banks from the most polluting Western regions were studied using descriptive statistics and fixed effects econometric estimation to test the relationship between a selection of relevant variables. The key conclusions are that banks are committed to protecting the environment and that there are no significant differences between banks’ commitment to the planet on the basis of board gender diversity.
Joint Ventures and Sustainable Development. A Bibliometric Analysis
Authors: Muñoz de Prat Javier , Escriva-Beltran María , Gómez-Calvet Roberto
Published: December 2020

One of the most common business strategies in companies’ growth and internationalization is the Joint Venture (JV) strategy. This type of entry mode in the global market has contributed to building a more sustainable international market. This type of collaborative business normally happens between firms located either in the same country or located in different countries with different levels of development. This paper presents a thorough cross-bibliometric analysis of studies examining the relation between joint ventures and sustainability published in academic journals during the period from 1997 to 2020 and available in the Scopus Collection. This mapping of the field on the one hand graphically illustrates the publications’ evolution over time, and on the other hand, the use of bibliometric methodology shows a picture that clusters the academic research of the relationships among these two topics according to the following criteria: JV type, sustainability criteria, host country groups and activity sectors. In addition, the public or private JVs’ nature shows a relation to the type of sustainability, and mainly development and management sustainability. The paper reveals the knowledge gap regarding the connection of these two fields, JV and sustainability, and provides a robust roadmap for further investigation in this field.
Environmental Regulation and Financial Performance in China: An Integrated View of the Porter Hypothesis and Institutional Theory
Authors: Lee Eunmi
Published: December 2020

The link between environmental regulations and financial performance has long been studied, but whether command and control environmental regulation or voluntary instruments induce better results is an unsettled question. By drawing on the Porter Hypothesis, this paper examines whether both approaches to environmental protection boost forms of environmental protection regulations that have positive impacts on financial performance. By integrating institutional theory, this study also examines whether ownership structures moderate the relationship between environmental regulation and financial performance. The results from data on 183 firms listed on the Shanghai and Shenzhen Stock Exchanges confirmed that both command and control environmental regulation and voluntary instruments positively affect financial performance. This paper also found that ownership structure strengthens the relationship between command and control environmental regulation and financial performance. The findings enrich the Porter Hypothesis and contribute to environmental research by revealing that properly designed environmental regulations have positive impacts on financial performance. By drawing on institutional theory, this study further contributes to business and management studies by confirming that the specific moderator, China’s state-owned enterprises, is a crucial contributor in achieving robust financial results.
Agricultural Water Use Efficiency—A Case Study of Inland-River Basins in Northwest China
Authors: Qu Wei , Tan Yanmei , Li Zhentao , Aarnoudse Eefje , Tu Qin
Published: December 2020

Water resources play a vital role in the process of economic development, especially in arid and semi-arid regions. Improving the efficiency of water use is an effective way to solve the shortage of water resources. In this paper, influencing factors of water utilization efficiency in three inland river basins (Shiyang, Heihe, and Shule river) in Gansu Province, Northwest China, are investigated. Using survey data of 306 households, results of the multiple linear regression analysis show that management capacity and its strictness in a different basin, irrigation technology and facility conditions, and farmers’ self-government are key factors affecting farmers’ irrigation efficiency. Additionally, factors at the farmer and family level, as well as the differences in natural conditions and economic and social development in different regions, also have a significant impact on water use efficiency.
TRIMIS: Modular Development of an Integrated Policy-Support Tool for Forward-Oriented Transport Research and Innovation Analysis
Authors: Tsakalidis Anastasios , Gkoumas Konstantinos , Grosso Monica , Pekár Ferenc
Published: December 2020

The European Commission’s Strategic Transport Research and Innovation Agenda (STRIA) outlines future transport research and innovation (R&I) priorities towards the decarbonization of European transport. Seven STRIA roadmaps focus on crosscutting research areas. In order to support and monitor their implementation, the Transport Research and Innovation Monitoring and Information System (TRIMIS) was developed. It is an integrated transport policy-support tool with a modular design, serving as a knowledge management system that offers open-access information, as well as an inventory of transport technologies and innovations. TRIMIS provides a holistic assessment of current and emerging technologies and trends and R&I capacities in the European transport sector incorporating foresight capabilities based on transport R&I data collection, innovation capacity mapping, technological status assessment, horizon scanning, and identification of new and emerging technologies and trends. This paper presents an overview of TRIMIS and its benefits as an integrated analytical tool that provides support to sustainable transport governance and decision-making. Moreover, it provides insights on current technology trends in the road transport domain with a focus on smart innovation and identifies emerging trends with a potential future impact through a dedicated case study, combining a techno-economic assessment with findings of a horizon scanning exercise.
A Mixed Approach on Resilience of Spanish Dwellings and Households during COVID-19 Lockdown
Authors: Cuerdo-Vilches Teresa , Navas-Martín Miguel Ángel , Oteiza Ignacio
Published: December 2020

The confinement by COVID-19 has meant a re-reading of housing for Spanish households, resulting in the only available and safe space to carry out daily activity. This complex phenomenon has generated a completely different way of inhabiting it, as well as of relating to domestic spaces. For this reason, the home perception and its characteristics must be evaluated, highlighting those perceived as deficiencies, or as preferences in such an unusual context as lockdown, where the experience was different depending on the dwelling characteristics, and the family in question. To deepen in this double perception home-dwelling, a mixed method was used, with two online forms. The first is a quantitative questionnaire, while the second asks the participants for photographs and narratives about such images. More than 1800 surveys and 785 qualitative responses were obtained. From both approaches, the joint discourse arose, allowing an exploratory analysis of the current situation of the Spanish residential park, and the resilience demonstrated in this period by both households and their usual dwellings. This study should facilitate the development of new proposals on housing in contexts similar to the COVID-19 pandemic.
The Effect of Trust on the Various Dimensions of Climate Change Attitudes
Authors: Bodor Ákos , Varjú Viktor , Grünhut Zoltán
Published: December 2020

The struggle against climate change will not be successful without a sufficient level of collective action. However, a necessary precondition for this is the existence of trust between people. The literature on trust and attitudes to climate change is displaying a growing tendency, and today the results of numerous empirical studies are available. Although, for the time being, on the basis of these studies, we only have a fragmented picture from which it appears that trust is having a significant effect on attitudes to climate change at both the micro and macro levels. The current paper tries to progress on this path and reveal the role of trust in various dimensions of the attitude to climate change using the data of the European Social Survey originating from 22 countries. The results show that while climate change beliefs and climate concern display no relationship with trust, neither on the individual or national level, trust does have a clear effect on the feeling of individual responsibility in connection with climate change and on support for the various policy measures. In addition, it is also investigated whether the effect of trust can be shown to exist in the relationships between climate concern and the feeling of individual responsibility, and climate concern and policy support. The results show that in both cases the relationship is stronger in those countries characterized by a higher level of social trust.
An Analysis of the Determinants of Sport Expenditure in Sports Centers in Spain
Authors: Elasri-Ejjaberi Amal , Aparicio-Chueca Pilar , Triadó-Ivern Xavier M.
Published: December 2020

The sports center sector is undergoing a complete transformation. Knowing users’ behavior regarding sport expenditure is needed to be able to act in terms of the future of the sector. This study analyzes the expenditure of people in Spain who are members of sports centers. Adult members were asked about their sport expenditure in several defined categories. An analysis of variance (ANOVA) and a multiple logistic regression analysis were carried out. The results show that the variables of time of participation, federation membership, and income have predictive value in terms of sport expenditure. Age and educational level also explain the significant differences in sport expenditure in its different categories. This study suggests the importance of identifying the behavior of sports center users with reference to sport expenditure as an essential component of the future strategy of the sector.