bluuebunny/crossref_metadata_2025 huggingface dataset:
Vehicle Detection on Occupancy Grid Maps: Comparison of Five Detectors Regarding Real-Time Performance
Authors: Defauw Nils , Malfante Marielle , Antoni Olivier , Rakotovao Tiana , Lesecq Suzanne
Published: February 2023

Occupancy grid maps are widely used as an environment model that allows the fusion of different range sensor technologies in real-time for robotics applications. In an autonomous vehicle setting, occupancy grid maps are especially useful for their ability to accurately represent the position of surrounding obstacles while being robust to discrepancies between the fused sensors through the use of occupancy probabilities representing uncertainty. In this article, we propose to evaluate the applicability of real-time vehicle detection on occupancy grid maps. State of the art detectors in sensor-specific domains such as YOLOv2/YOLOv3 for images or PIXOR for LiDAR point clouds are modified to use occupancy grid maps as input and produce oriented bounding boxes enclosing vehicles as output. The five proposed detectors are trained on the Waymo Open automotive dataset and compared regarding the quality of their detections measured in terms of Average Precision (AP) and their real-time capabilities measured in Frames Per Second (FPS). Of the five detectors presented, one inspired from the PIXOR backbone reaches the highest AP0.7 of 0.82 and runs at 20 FPS. Comparatively, two other proposed detectors inspired from YOLOv2 achieve an almost as good, with a AP0.7 of 0.79 while running at 91 FPS. These results validate the feasibility of real-time vehicle detection on occupancy grids.
Linear and Non-Linear Heart Rate Variability Indexes from Heart-Induced Mechanical Signals Recorded with a Skin-Interfaced IMU
Authors: Milena Čukić , Romano Chiara , De Tommasi Francesca , Carassiti Massimiliano , Formica Domenico , Schena Emiliano , Massaroni Carlo
Published: February 2023

Heart rate variability (HRV) indexes are becoming useful in various applications, from better diagnosis and prevention of diseases to predicting stress levels. Typically, HRV indexes are retrieved from the heart’s electrical activity collected with an electrocardiographic signal (ECG). Heart-induced mechanical signals recorded from the body’s surface can be utilized to record the mechanical activity of the heart and, in turn, extract HRV indexes from interbeat intervals (IBIs). Among others, accelerometers and gyroscopes can be used to register IBIs from precordial accelerations and chest wall angular velocities. However, unlike electrical signals, the morphology of mechanical ones is strongly affected by body posture. In this paper, we investigated the feasibility of estimating the most common linear and non-linear HRV indexes from accelerometer and gyroscope data collected with a wearable skin-interfaced Inertial Measurement Unit (IMU) positioned at the xiphoid level. Data were collected from 21 healthy volunteers assuming two common postures (i.e., seated and lying). Results show that using the gyroscope signal in the lying posture allows accurate results in estimating IBIs, thus allowing extracting of linear and non-linear HRV parameters that are not statistically significantly different from those extracted from reference ECG.
WLiT: Windows and Linear Transformer for Video Action Recognition
Authors: Sun Ruoxi , Zhang Tianzhao , Wan Yong , Zhang Fuping , Wei Jianming
Published: February 2023

The emergence of Transformer has led to the rapid development of video understanding, but it also brings the problem of high computational complexity. Previously, there were methods to divide the feature maps into windows along the spatiotemporal dimensions and then calculate the attention. There are also methods to perform down-sampling during attention computation to reduce the spatiotemporal resolution of features. Although the complexity is effectively reduced, there is still room for further optimization. Thus, we present the Windows and Linear Transformer (WLiT) for efficient video action recognition, by combining Spatial-Windows attention with Linear attention. We first divide the feature maps into multiple windows along the spatial dimensions and calculate the attention separately inside the windows. Therefore, our model further reduces the computational complexity compared with previous methods. However, the perceptual field of Spatial-Windows attention is small, and global spatiotemporal information cannot be obtained. To address this problem, we then calculate Linear attention along the channel dimension so that the model can capture complete spatiotemporal information. Our method achieves better recognition accuracy with less computational complexity through this mechanism. We conduct extensive experiments on four public datasets, namely Something-Something V2 (SSV2), Kinetics400 (K400), UCF101, and HMDB51. On the SSV2 dataset, our method reduces the computational complexity by 28% and improves the recognition accuracy by 1.6% compared to the State-Of-The-Art (SOTA) method. On the K400 and two other datasets, our method achieves SOTA-level accuracy while reducing the complexity by about 49%.
Dielectric Characterization of Healthy Human Teeth from 0.5 to 18 GHz with an Open-Ended Coaxial Probe
Authors: Berezhanska Mariya , Godinho Daniela M. , Maló Paulo , Conceição Raquel C.
Published: February 2023

Dental caries is a major oral health issue which compromises oral health, as it is the main cause of oral pain and tooth loss. Early caries detection is essential for effective clinical intervention. However, methods commonly employed for its diagnosis often fail to detect early caries lesions, which motivates the research for more effective diagnostic solutions. In this work, the relative permittivity of healthy permanent teeth, in caries-prone areas, was studied between 0.5 and 18 GHz. The reliability of such measurements is an important first step to, ultimately, evaluate the feasibility of a microwave device for caries detection. The open-ended coaxial probe technique was employed. Its performance showed to be compromised by the poor probe-tooth contact. We proposed a method based on applying coupling media to reduce this limitation. A decrease in the measured relative permittivity variability was observed when the space between the probe tip and tooth surface was filled by coupling media instead of air. The influence of the experimental conditions in the measurement result was found to be less than 5%. Measurements conducted in ex vivo teeth showed that the relative permittivity of the dental crown and root ranges between 10.0–11.0 and 8.0–9.5, respectively.
Reading Direct-Part Marking Data Matrix Code in the Context of Polymer-Based Additive Manufacturing
Authors: Matuszczyk Daniel , Weichert Frank
Published: February 2023

A novel approach to detect and decode direct-part-marked, low-contrast data matrix codes on polymer-based selective laser sintering manufactured parts, which is able to work on lightweight devices, is presented. Direct-part marking is a concept for labeling parts directly, which can be carried out during the additive manufacturing’s design process. Because of low contrast in polymer-based selective laser sintering manufactured parts, it is a challenging task to detect and read codes on unicolored parts. To achieve this, at first, codes are located using a deep-learning-based approach. Afterwards, the calculated regions of interest are passed into an image encoding network in order to compute readable standard data matrix codes. To enhance the training process, rendered images, improved with a generative adversarial network, are used. This process fulfills the traceability task in assembly line production and is suitable for running on mobile devices such as smartphones or cheap sensors placed in the assembly line. The results show that codes can be localized with 97.38% mean average precision, and a readability of 89.36% is achieved.
Electronically Tunable Memristor Emulator Implemented Using a Single Active Element and Its Application in Adaptive Learning
Authors: Tasneem Sadaf , Kumar Sharma Pankaj , Kumar Ranjan Rajeev , Khateb Fabian
Published: February 2023

In recent times, much-coveted memristor emulators have found their use in a variety of applications such as neuromorphic computing, analog computations, signal processing, etc. Thus, a 100 MHz flux-controlled memristor emulator is proposed in this research brief. The proposed memristor emulator is designed using a single differential voltage current conveyor (DVCC), three PMOS transistors, and one capacitor. Among three PMOS transistors, two transistors are used to implement an active resistor, and one transistor is used as the multiplier required for the necessary memristive behaviors. Through simple adjustment of the switch, the proposed emulator can be operated in incremental as well as decremental configurations. The simulations are performed using a 180 nm technology node to validate the proposed design and are experimentally verified using AD844AN and CD4007 ICs. The memristor states of the proposed emulator are perfectly retained even in the absence of external stimuli, thereby ascertaining the non-volatility behavior. The robustness of the design is further analyzed using the PVT and Monte Carlo simulations, which suggest that the circuit operation is not hindered by the mismatch and process variations. A simple neuromorphic adaptive learning circuit based on the proposed memristor is also designed as an application.
Data-Driven Supply Chain Operations—The Pilot Case of Postal Logistics and the Cross-Border Optimization Potential
Authors: Zdolsek Draksler Tanja , Cimperman Miha , Obrecht Matevž
Published: February 2023

According to the defined challenge of cross-border delivery, a pilot experiment based on the integration of new digital technologies to assess process optimization potential in the postal sector was designed. The specifics were investigated with events processing based on digital representation. Different events were simulated with scenario analysis with the integration of the Cognitive Advisor and supported by the monitoring of KPIs. The business environment is forcing logistics companies to optimize their delivery processes, integrate new technologies, improve their performance metrics, and move towards Logistics 4.0. Their main goals are to simultaneously reduce costs, environmental impact, delivery times, and route length, as well as to increase customer satisfaction. This pilot experiment demonstrates the integration of new digital technologies for process optimization in real time to manage intraday changes. Postal operators can increase flexibility, introduce new services, improve utilization by up to 50%, and reduce costs and route length by 12.21%. The Cognitive Advisor has shown great potential for the future of logistics by enabling a dynamic approach to managing supply chain disruptions using sophisticated data analytics for process optimization based on the existing delivery infrastructure and improving business processes. Research originality is identified with a novel approach of real-time simulation based on the integration of the Cognitive Advisor in postal delivery.
Development of Measurement Method for Temperature and Velocity Field with Optical Fiber Sensor
Authors: Sekine Masashi , Furuya Masahiro
Published: February 2023

We have developed a new method for measuring temperature and velocity at a high spatial resolution (minimum 2.56 mm pitch along an optical fiber). The developed method uses the same principle as a hot wire anemometer, where the velocity perpendicular to an optical fiber is estimated as a function of the cooling curve of a gold-coated layer on the optical fiber Joule-heated intermittently. The developed optical fiber sensor demonstrated the ability to acquire a transient velocity profile in airflow experiments with high repeatability and accuracy. This paper describes optical fiber-based velocity measurement in the velocity range of approximately 0–7 m/s with an error of approximately 10% compared to a hot wire anemometer and a new method for simultaneous temperature and velocity measurements. Applicability to velocity distribution measurements and seconds transient velocity changes are also described.
Vibration Measurements on a Six-Axis Collaborative Robotic Arm—Part I
Authors: Cernohlavek Vit , Klimenda Frantisek , Houska Pavel , Suszyński Marcin
Published: February 2023

This article deals with the design of a methodology for vibration and noise measurement on a six-axis collaborative robotic arm. A vibration and noise measurement methodology is proposed for six robot positions. In each position, measurements were performed under defined equal boundary conditions. The boundary conditions were related to the velocities of the joints and the load on the robotic arm. The second part of the article is an evaluation of the initial experimental results. So far, only the acceleration of the sixth joint of the robotic arm—Wrist 3—has been measured. The aim of the measurements was to verify if the methodology presented can be used for vibration measurements. From the evaluation of the experimental measurements, it was determined that the given methodology can be used for vibration measurements. It was also found that the acceleration is transmitted in the axes other than the axis of motion of the robotic arm. In future experiments, the vibration at the other joints of the robotic arm will be measured and the noise of the robotic arm will be measured to confirm whether the proposed methodology is indeed functional.
One-Year Seismic Survey of the Tectonic CO2-Rich Site of Mefite d’Ansanto (Southern Italy): Preliminary Insights in the Seismic Noise Wavefield
Authors: Morabito Simona , Cusano Paola , Galluzzo Danilo , Gaudiosi Guido , Nardone Lucia , Del Gaudio Pierdomenico , Gervasi Anna , La Rocca Mario , Milano Girolamo , Petrosino Simona , Zuccarello Luciano , Manzo Roberto , Buonocunto Ciro , Di Luccio Francesca
Published: February 2023

A passive seismic experiment is carried out at the non-volcanic highly degassing site of Mefite d’Ansanto located at the northern tip of the Irpinia region (southern Italy), where the 1980 MS 6.9 destructive earthquake occurred. Between 2020 and 2021, background seismic noise was recorded by deploying a broadband seismic station and a seismic array composed of seven 1 Hz three-component sensors. Using two different array configurations, we were allowed to explore in detail the 1–20 Hz frequency band of the seismic noise wavefield as well as Rayleigh wave phase velocities in the 400–800 m/s range. Spectral analyses and array techniques were applied to one year of data showing that the frequency content of the signal is very stable in time. High frequency peaks are likely linked to the emission source, whereas at low frequencies seismic noise is clearly correlated to meteorological parameters. The results of this study show that small aperture seismic arrays probe the subsurface of tectonic CO2-rich emission areas and contribute to the understanding of the link between fluid circulation and seismogenesis in seismically active regions.
Micro-Three-Coil Sensor with Dual Excitation Signals Use Asymmetric Magnetic Fields to Distinguish between Non-Ferrous Metals
Authors: Hong Jiaju , Xie Yucai , Zhang Shuyao , Shi Haotian , Liu Yu , Zhang Hongpeng , Sun Yuqing
Published: February 2023

Intelligent operation and maintenance technology for vessels can ensure the safety of the entire system, especially for the development of intelligent and unmanned marine technology. The material properties of metal abrasive particles in oil could demonstrate the wear areas of the marine mechanical system because different components consist of different materials. However, most sensors can only roughly separate metallic contaminants into ferromagnetic and non-ferromagnetic particles but cannot differentiate them in greater detail. A micro-three-coil sensor is designed in this paper; the device applies different excitation signals to two excitation coils to differentiate materials, based on the different effects of different material particles in the asymmetric magnetic field. Therefore, a particle’s material can be judged by the shape of the induction electromotive force output signal from the induction coil, while the particle size can be judged by the amplitude of the signal. Experimental results show that the material differentiation of four different types of particles can be achieved, namely, of aluminum, iron, 304 stainless steel, and carbon steel. This newly designed sensor provides a new research prospect for the realization of an inductive detection method to distinguish non-ferrous metals and a reference for the subsequent detection of metal contaminants in oil and other liquids.
At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives
Authors: Bourechak Amira , Zedadra Ouarda , Kouahla Mohamed Nadjib , Guerrieri Antonio , Seridi Hamid , Fortino Giancarlo
Published: February 2023

Given its advantages in low latency, fast response, context-aware services, mobility, and privacy preservation, edge computing has emerged as the key support for intelligent applications and 5G/6G Internet of things (IoT) networks. This technology extends the cloud by providing intermediate services at the edge of the network and improving the quality of service for latency-sensitive applications. Many AI-based solutions with machine learning, deep learning, and swarm intelligence have exhibited the high potential to perform intelligent cognitive sensing, intelligent network management, big data analytics, and security enhancement for edge-based smart applications. Despite its many benefits, there are still concerns about the required capabilities of intelligent edge computing to deal with the computational complexity of machine learning techniques for big IoT data analytics. Resource constraints of edge computing, distributed computing, efficient orchestration, and synchronization of resources are all factors that require attention for quality of service improvement and cost-effective development of edge-based smart applications. In this context, this paper aims to explore the confluence of AI and edge in many application domains in order to leverage the potential of the existing research around these factors and identify new perspectives. The confluence of edge computing and AI improves the quality of user experience in emergency situations, such as in the Internet of vehicles, where critical inaccuracies or delays can lead to damage and accidents. These are the same factors that most studies have used to evaluate the success of an edge-based application. In this review, we first provide an in-depth analysis of the state of the art of AI in edge-based applications with a focus on eight application areas: smart agriculture, smart environment, smart grid, smart healthcare, smart industry, smart education, smart transportation, and security and privacy. Then, we present a qualitative comparison that emphasizes the main objective of the confluence, the roles and the use of artificial intelligence at the network edge, and the key enabling technologies for edge analytics. Then, open challenges, future research directions, and perspectives are identified and discussed. Finally, some conclusions are drawn.
Editorial for the Special Issue on Electronics for Sensors II
Authors: Ferri Giuseppe , Barile Gianluca , Leoni Alfiero
Published: February 2023

Sensor signals are physical, chemical, or biological quantities that evolve over time [...]
The Measure of Motion Similarity for Robotics Application
Authors: Zielinska Teresa , Coba Gabriel
Published: February 2023

A new measure of motion similarity has been proposed. The formulation of this measure is presented and its logical basis is described. Unlike in most of other methods, the measure enables easy determination of the instantaneous synergies of the motion of body parts. To demonstrate how to use the measure, the data describing human movement is used. The movement is recorded using a professional motion capture system. Two different cases of non-periodic movements are discussed: stepping forward and backward, and returning to a stable posture after an unexpected thrust to the side (hands free or tied). This choice enables the identification of synergies in slow dynamics (stepping) and in fast dynamics (push recovery). The trajectories of motion similarity measures are obtained for point masses of the human body. The interpretation of these trajectories in relation to motion events is discussed. In addition, ordinary motion trajectories and footprints are shown in order to better illustrate the specificity of the discussed examples. The article ends with a discussion and conclusions.
Fault Diagnosing of Cycloidal Gear Reducer Using Statistical Features of Vibration Signal and Multifractal Spectra
Authors: Komorska Iwona , Olejarczyk Krzysztof , Puchalski Andrzej , Wikło Marcin , Wołczyński Zbigniew
Published: February 2023

The article presents a method for diagnosing cycloidal gear damage on a laboratory stand. The damage was simulated by removing the sliding sleeves from two adjacent external pins of the cycloidal gearbox. Damage to the sliding sleeves may occur under operating conditions and can lead to the destruction of the gear unit. Hence, early detection is essential. Signals from torque sensors, rotational speed sensors and vibration acceleration sensors of input and output shafts for various rotational speeds and transmission loads were recorded. The frequency analysis of these signals was carried out. Due to the fluctuation of the rotational speed, the frequency spectrum gives an approximate picture and is not useful in detecting this type of damage. The statistical characteristics of the signal were determined. However, only statistical moments of higher orders, such as kurtosis, are sensitive to the tested damage. Therefore, the use of multifractal analysis of the vibration signal using the wavelet leader method (WLMF) was considered. Then log-cumulants of the multifractal spectrum were selected as the new signal features.
Effective Electrical Properties and Fault Diagnosis of Insulating Oil Using the 2D Cell Method and NSGA-II Genetic Algorithm
Authors: Monzón-Verona José Miguel , González-Domínguez Pablo , García-Alonso Santiago
Published: February 2023

In this paper, an experimental analysis of the quality of electrical insulating oils is performed using a combination of dielectric loss and capacitance measurement tests. The transformer oil corresponds to a fresh oil sample. The paper follows the ASTM D 924-15 standard (standard test method for dissipation factor and relative permittivity of electrical insulating liquids). Effective electrical parameters, including the tan δ of the oil, were obtained in this non-destructive test. Subsequently, a numerical method is proposed to accurately determine the effective electrical resistivity, σ, and effective electrical permittivity, ε, of an insulating mineral oil from the data obtained in the experimental analysis. These two parameters are not obtained in the ASTM standard. We used the cell method and the multi-objective non-dominated sorting in genetic algorithm II (NSGA-II) for this purpose. In this paper, a new numerical tool to accurately obtain the effective electrical parameters of transformer insulating oils is therefore provided for fault detection and diagnosis. The results show improved accuracy compared to the existing analytical equations. In addition, as the experimental data are collected in a high-voltage domain, wireless sensors are used to measure, transmit, and monitor the electrical and thermal quantities.
Synthesis and Characterization of Mesoporous Silica Modified with Purpald and Its Application in the Preconcentration of Cu2+ and Cd2+ from Aqueous Samples through Solid-Phase Extraction
Authors: Wondracek Marcos Henrique Pereira , Jorgetto Alexandre de Oliveira , da Silva Adrielli Cristina Peres , Schneider José Fabián , Pedrosa Valber de Albuquerque , Saeki Margarida Juri , de Castro Gustavo Rocha
Published: February 2023

The synthesis of an organofunctionalized mesoporous silica was accomplished by a two-step process involving (1) the co-condensation of a silylant agent at the surface of silica, followed by (2) the immobilization of Purpald (ligand) at the organic termination of the silytant agent. The characterization of the organofunctionalized material indicated the presence of NH2 groups, and the immobilization of the ligand was confirmed by 29Si- and 13C-nuclear magnetic resonance. The material’s surface area was determined as 370 m2 g−1. Batch adsorption experiments enabled the determination of optimum pH conditions for the adsorption of Cu(II) and Cd(II). Under optimal pH, the pseudo-second-order kinetic model and Langmuir model provided the best correlations to describe the materials adsorption behavior, suggesting a chemisorption mechanism. When tested in continuous-flow preconcentration experiments, the flow rate and eluent concentration demonstrated to affect the removal of Cu(II) and Cd(II), while the buffer concentration had an effect only over the adsorption of Cu(II). Under optimized preconcentration conditions, it was possible both to determine the concentrations of Cu(II) and Cd(II) in samples such as mineral water, ground water, tap water and river water. Ions commonly found in drinking and natural waters (Na+, K+, Ca2+, Mg2+, Fe3+, Ba2+, Cl−, SO42−, HCO3−, and H2PO4−) did not affect the preconcentration of any of the studied analytes. Reutilization experiments indicated that the adsorbent material can withstand at least 40 adsorption/desorption preconcentration cycles with no efficiency loss.
The Evaluation in the Urban Projects Planning: A Logical-Deductive Model for the Definition of “Warning Areas” in the Esquilino District in the City of Rome (Italy)
Authors: Morano Pierluigi , Tajani Francesco , Di Liddo Felicia , La Spina Ivana
Published: February 2023

With reference to the current focus on urban redevelopment issue, the evaluation of the projects plays a central role for the definition of effective urban development policies. In the present research, a logical-deductive model for the identification of “warning areas” is proposed. Given an urban area to be renovated, the developed methodological approach starts from the detection of the main existing architectural, historical and environmental emergencies in order to investigate the appreciation of the reference market for the higher or lower proximity to each considered urban pole. Thus, an econometric technique is implemented to examine the influence of each locational factor on selling prices, by assuming the property asset price increase as a proxy of the benefits generated by the urban redevelopment intervention for local communities. Furthermore, the proposed methodology is applied to the Esquilino district in the city of Rome (Italy), for which a relevant urge of urban regeneration is found, to orient the selection phases of the areas that need more attention from public entities.
Local Calibration of TDR Measurements for Determining Water and Organic Carbon Contents of Peaty Soils
Authors: Nielsen Claudia Kalla , Thomsen Anton Gårde
Published: February 2023

Time domain reflectometry (TDR) measurements of the volumetric water content (θ) of soils are based on the dielectric permittivity (ε), relating ε to θ, using an empirical calibration function. Accurate determination of θ for peaty soils is vital but complicated by the complexity of organic soils and the lack of a general calibration model. Site-specific calibration models were developed to determine θ from TDR measurements for a heterogenous peatland across gradients of peat decomposition and organic carbon (OC) content; derived by soil organic matter conversion. The possibility of predicting OC contents based on the corrected θ (θcor); ε; electrical impedance (Ζ); and a categorical predictor variable was explored. The application of plot-specific and local area calibration models resulted in similar results. Compared to common calibrations, the threshold for accurate determination of θ was at ε = 5; with higher ε underestimating θ by up to 25%. Including the von Post degree of peat humification as a bioindicator, the OC content could be modelled across the area and the full range of θ with an accuracy of ±1.2% for 496 measurements. In conclusion, a strong indication was found for determining OC in peatlands in situ using TDR and a site-specific calibration model for θ together with indices of peat decomposition.
Use of Plant Regulators for Activation of Antioxidant Enzymes in Basil Plants under Water Deficit Conditions
Authors: Carvalho Beatriz Lívero , Aires Eduardo Santana , Rodrigues João Domingos , Ono Elizabeth Orika
Published: February 2023

Basil is susceptible to biotic or abiotic stress, negatively interfering with growth and production. Thus, the objective of this work was to evaluate the physiological effects of the application of plant regulators in basil plants that suffer from water deficit. The experiment was conducted in a randomized block design (RBD) in a 2 × 4 factorial scheme, including plants that were subjected to water stress and those that were not. In addition, plants also received five doses of Stimulate® composed of indolylbutyric acid (IBA) + gibberellic acid (GA3) + kinetin (Kt) with four repetitions each. The experiment was evaluated through the biochemical analyses of superoxide dismutase (SOD), catalase (CAT), peroxidase (POD) and lipid peroxidation performed 20, 35, and 50 days after transplanting (DAT). The mixture of plant regulators attenuateds the effects through the increasing activities of these enzymes. The plants that received the highest dosages (9 and 12 mL L−1) offered the best protetion. Parameters of growth measures such as number of leaves and leaf area also showed significant responses regarding the application of the plant growth regulators. The use of a mixture of plant regulators, despite satisfactory results, does not make basil economically viable because it presents inaccurate results regarding its use.
A Dual DIC System for Analysis of Dynamic Mechanical Properties of Large Sandstone under Uniaxial Compression Load
Authors: Zhong Yichen , Chen Fanxiu , Gao Xinya , Guo Zhanwei , Sun Jie , Zhang Liming , Wang Yuan , Liu Yuxin , Li Changtai
Published: February 2023

In this paper, an experiment is carried out to acquire the dynamic mechanical properties of a simulated sandstone tunnel by a dual DIC system. The sandstone tunnel is simulated by large sandstone with a prefabricated hole in the center. The speckle size required by DIC system was evaluated, and the results showed that for large specimens a marker pen could be used to spot speckles and make sure that the diameters of speckle points in an image should be ranged from three to five pixels. The dual DIC system is composed of a low-speed camera and a high-speed camera. The low-speed camera is used to record the speckle patterns of the sandstone in one side during the whole process of compression load, and the high-speed camera is placed in the other side to record speckle patterns for 11.5 seconds before and after failure. It is realized that monitoring whole process of deformation and instantaneous failure in two directions is required. Measurement results are effectively analyzed. The results are shown as follows: At the initial stage of loading the sandstone is in an elastic stage without macroscopic cracks. With the increase in compression load the sandstone has several small stress releases and several obvious macroscopic cracks. In the final stage of loading, the distribution of normal stress and shear stress are almost the same, and cracks are subjected to the coupling effect of normal stress and shear stress. The two ends of the prefabricated hole perpendicular to the applied load direction are prone to cracks parallel to the applied load direction.
Battery Power Control Strategy for Intermittent Renewable Energy Integrated Modular Multilevel Converter-Based High-Voltage Direct Current Network
Authors: Hossain Md Ismail , Shafiullah Md , Abido Mohammad A.
Published: February 2023

Modular multilevel converters (MMC) play a dominant role in integrating remotely located renewable energy resources (RER) over the high-voltage direct current (HVDC) transmission network. The fault ride-through capabilities of the MMC-HVDC network during low-voltage faults and the power fluctuation due to RER intermittency are the major obstacles to the effective integration of renewable energy. In response, this article proposes a local voltage-based combined battery energy control scheme for a PV-wind-battery connected MMC-HVDC system to regulate the HVDC-link voltage during low-voltage faults at the point of common coupling of alternating current grids and to reduce the intermittent RER power fluctuation. The proposed technique removes the dynamic braking resistor from the HVDC-link and smoothly integrates the RER without active power reduction of renewable energy under low-voltage faults. Symmetrical and unsymmetrical low-voltage faults have been conducted to validate the effectiveness of the proposed control scheme for the battery in mitigating surplus energy in the HVDC-link. Additionally, wind speed, solar radiation, and temperature have been changed to confirm the improved performance of the battery energy management system. The complete systems have been simulated and tested in a real-time digital simulator (RTDS) and using dSPACE-based controller hardware in a loop setup.
Center-Aware 3D Object Detection with Attention Mechanism Based on Roadside LiDAR
Authors: Shi Haobo , Hou Dezao , Li Xiyao
Published: February 2023

Infrastructure 3D Object Detection is a pivotal component of Vehicle-Infrastructure Cooperated Autonomous Driving (VICAD). As turning objects account for a high proportion of traffic at intersections, anchor-free representation in the bird’s-eye view (BEV) is more suitable for roadside 3D detection. In this work, we propose CetrRoad, a simple yet effective center-aware detector with transformer-based detection head for roadside 3D object detection with single LiDAR (Light Detection and Ranging). CetrRoad firstly utilizes a voxel-based roadside LiDAR feature encoder module that voxelizes and projects the raw point cloud into BEV with dense feature representation, following a one-stage center proposal module that initializes center candidates of objects based on the top N points in the BEV target heatmap with unnormalized 2D Gaussian. Then, taking attending center proposals as query embedding, a detection head with multi-head self-attention and multi-scale multi-head deformable cross attention can refine and predict 3D bounding boxes for different classes moving/parked at the intersection. Extensive experiments and analyses demonstrate that our method achieves state-of-the-art performance on the DAIR-V2X-I benchmark with an acceptable training time cost, especially for Car and Cyclist. CetrRoad also reaches comparable results with the multi-modal fusion method for Pedestrian. An ablation study demonstrates that center-aware query as input can provide denser supervision than a purified feature map in the attention-based detection head. Moreover, we were able to intuitively observe that in complex traffic environment, our proposed model could produce more accurate 3D detection results than other compared methods with fewer false positives, which is helpful for other downstream VICAD tasks.
Will Off-Balance-Sheet Business Innovation Affect Bank Risk-Taking under the Background of Financial Technology?
Authors: Gao Shuiwen , Gu Haifeng , Buitrago Guillermo Andres , Halepoto Habiba
Published: February 2023

Given the rapid development of financial technology, the off-balance-sheet business innovations of banks may potentially impact bank risk-taking. This issue is of great importance to commercial banks and financial regulators. This paper analyzed the relationship between off-balance-sheet business innovation (OBI) and Bank Risk-Taking (BRT) in Chinese commercial banks, as well as the mediation role of the Bank Agency Cost (BAC), the impact of a bank’s Internal Control Quality (ICQ) on this relationship, and the moderating role of Bank Competition (BCMP) by analyzing panel data from a sample of 130 Chinese commercial banks from 2009 to 2019. The results of this empirical exercise showed that (1) OBI has a significant negative correlation with BRT, evidencing that off-balance-sheet business innovation can improve bank risk management processes and enhance the bank’s operating performance, thereby reducing their willingness to transfer risks, restraining the BRT level. Compared with state-owned and joint-stock banks, OBI has a more significant inhibitory effect on BRT in urban and rural commercial banks. (2) BAC showed a mediation role in the relationship between OBI and BRT levels. Bank OBI can inhibit BRT levels by BAC reduction, demonstrating an effective mediation channel. (3) The degree of BCMP displayed a positive moderation effect on the relationship between the explained and explanatory variables, which means that, at higher BCMP levels, the inhibitory effect of OBI on BRT levels becomes more significant. (4) Additionally, this exercise also found that a bank’s ICQ can enhance the impact of OBI on BRT. The research contributions of this paper constitute an important theoretical significance and reference value for researchers exploring mechanisms that can improve innovation in the commercial banking industry and give importance to financial supervision and financial system risk control.
Application of Environmental Isotopes and Hydrochemistry to Identify the Groundwater Recharge in Wadi Qanunah Basin, Saudi Arabia
Authors: Masoud Milad , El Osta Maged , Alqarawy Abdulaziz , Ezzeldin Hesham
Published: February 2023

The current study focuses on the Wadi Qanunah basin, which is considered one of Makkah Al-Mukarramah’s most important watersheds. It is located in the southwestern part of the Al Qunfudhah governorate. The identification and characterization of the recharging sources for the quaternary aquifer is one of the most important goals of this study. In this context, different methods will be applied for the identification of the different factors impacting groundwater. Such methods will be based on the integration of geographic information system (GIS) and modern hydrochemical methods ranging from graphical plots, bivariate and multivariate analysis to geochemical modeling. The salinity of the groundwater studied varied from fresh to brackish, according to the seasonal influx of dilute runoff and the dissolution of the weathered rocks, as well as the cementing materials within the aquifers’ matrix. Ionic ratios indicated that ion exchange, silicate weathering and evaporation played a significant role in the enrichment of the groundwater with major constituents including calcium, sodium, magnesium, sulphate and chloride. Furthermore, four factors accounted for 73.92% of the total variance, calculated using SPSS’s statistical program. These factors accounted for leaching and dissolution, silicate and carbonate weathering, anthropogenic effects and evaporation. The δ18O vs. δD, TDS vs. δ18O and δ18O vs. d-excess relationships revealed that local rainfall is the main recharging source for groundwater; some samples were affected by evaporated rainfall, while others with lower salinity (<1000 mg/L) were diluted through seepage from the underlying fractured basement aquifer. Netpath geochemical modeling was applied to calculate the amount of evaporation or dilution which had affected an initial body of water as it moves from the upstream to downstream. The output of this program is consistent with what has been proved by stable isotopes, where the groundwater extracted from the final water is a mixture of an enriched recent precipitation with depleted older water. This study is an attempt to shed light on the assessment of groundwater and the extent at which it is affected by various factors in order to benefit from it in a way that ensures its sustainability.
Moderating Impacts of Education Levels in the Energy–Growth–Environment Nexus
Authors: Osuntuyi Busayo Victor , Lean Hooi Hooi
Published: February 2023

The world’s environment has deteriorated significantly over the years. Pollution’s impact on the ecosystem is undeniably alarming. Many factors have been found in the literature to impact environmental pollution. However, there is a dearth of literature on the impacts of education levels on environmental pollution. This study, therefore, examines the effects of education levels and their moderating impacts on the energy–growth–environment nexus. Fundamentally, the study investigates the effects of economic growth, natural resources, and the marginal effects of energy consumption on environmental pollution at various levels of education in Africa from 1990 to 2017. The cross-sectional dependence test, unit root test, cointegration test, fixed effect estimation, Driscoll–Kraay standard errors, fully modified least ordinary least square estimator and dynamic ordinary least square estimator are employed for the analyses. The findings reveal that education increases environmental pollution and that the marginal impacts of energy consumption at various education levels adversely impact environmental pollution, implying that increased school enrollments exacerbate the adverse effects of energy consumption. The findings also show that economic growth, population, and trade openness degrade the environment, whereas natural resources promote environmental sustainability. We deduce several policy implications to improve environmental quality in Africa based on the findings.
Impacts and Response Strategies of the COVID-19 Pandemic on the Construction Industry Using Structural Equation Modeling
Authors: Kassem Mukhtar A. , Radzi Afiqah R. , Pradeep Asankha , Algahtany Mohammed , Rahman Rahimi A.
Published: February 2023

The COVID-19 pandemic is one of the most serious global health crises. It has had a massive impact on the global workforce and workplaces, causing enormous changes in the working environment and raising concerns among organizations. Due to the pandemic, the construction industry has faced more challenges in delivering projects on time and within budget. This study aims to determine the relationship between the impacts and response strategies of COVID-19 in Sri Lankan construction projects. A systematic literature review and semi-structured interviews with industry professionals identified twelve COVID-19 impacts and twenty-two response strategies needed to mitigate the impacts. A structured questionnaire survey was then conducted with Sri Lankan construction professionals. The gathered data were analyzed using the Kruskal–Wallis test, exploratory factor analysis (EFA), and partial least-squares structural equation modeling (PLS-SEM). A model and six hypotheses were developed to explain the impact and strategy. The results revealed that it is necessary to focus on the impacts related to the project, develop the necessary strategies from a financial point of view, and supply the necessary materials and equipment. During COVID-19, organizational management and information exchange should be enhanced, along with a project’s workforce and its provision. The study findings could aid industry professionals and policymakers in comprehending the pandemic and developing strategies to mitigate the effects of COVID-19 on Sri Lankan construction projects.
Response of Contrasting Nutrient Management Regimes on Soil Aggregation, Aggregate-Associated Carbon and Macronutrients in a 43-Year Long-Term Experiment
Authors: Choudhary Mahipal , Sinha Nishant K. , Mohanty Monoranjan , Jayaraman Somasundaram , Kumari Nikul , Jyoti Bikram , Srivastava Ankur , Thakur Jyoti K. , Kumar Nirmal , Jha Pramod , Kumar Dhiraj , Kumar Jitendra , Mishra Rahul , Wanjari Ravi H. , Chaudhary Ranjeet S. , Hati Kuntal M. , Bisht Jaideep K. , Pattanayak Arunava
Published: February 2023

The present investigation evaluated the effect of continuous application (>43 years) of organic and inorganic fertilisers on soil aggregate stability, aggregate size distribution, aggregate-associated carbon and its fractions, and total macro-nutrient content under the soybean–wheat cropping system in vertisols of the semi-arid region. Seven contrasting treatments consisted of T1 (50% NPK), T2 (100% NPK), T3 (150% NPK), T4 (100% NP), T5 (100% N), T6 (100% NPK + FYM) and T7 Control (crop raised without addition of any nutrient). The highest and lowest percentage of large macroaggregates (11.3%) was found in T6 and T7 treatments. The NPK + FYM (T6) treatments substantially increased the proportion of the macroaggregate fractions (>2 mm and 2–0.25 mm) than other treatments. However, different manure and fertilisation treatments did not affect the proportion of silt + clay aggregates. Long-term application of 100% NPK + FYM increased mean weight diameter (MWD) and stable water aggregates (WSA) by 35.7 and 6.01% over control. The aggregate-associated SOC followed the trend of large macroaggregates > microaggregates > small macroaggregates > silt + clay fractions. Application of long-term manure plus inorganic fertiliser (T6) has also increased Walkley Black soil organic carbon (WBSC), permanganate oxidisable carbon (KMnO4-C), soil microbial biomass carbon (SMBC), carbon mineralisation (CM), total soil carbon (TSC), total soil N (TSN), total soil phosphorus (TSP) and total soil potassium (STK) by 82.1, 71.6, 182, 42.4, 23.9, 41.6, 117 and 18.4%, respectively, over control (T7). The lowest metabolic quotient (MetQ) value of 5.13 mg CO2–C mg−1 MBC h−1 was obtained in the control treatment (T7). The lowest MetQ was recorded in the integrated application of manure + inorganic fertiliser, i.e., 100% NPK + FYM (T6). Similarly, microbial quotient (MiQ) was also higher in treatment T6 (100% NPK + FYM) and lower in T7 (control). It is concluded that the application of inorganic fertiliser alone is insufficient to maintain soil health and sustainability so, combined application of manure plus inorganic fertilisation is the most important nutrient management practice for long-term soil sustainability because it maintains SOC levels in soils for long periods and ultimately ensures the soil health of soybean–wheat cropping systems in the vertisols of semi-arid regions.