bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Ionospheric Irregularities and Phase Scintillation at Low and Middle Latitudes Based on Swarm Observations
Authors: Kuai Jiawei , Wang Kang , Zhong Jiahao , Wan Xin , Huang Fuqing , Sun Hao , Chen Jiawen , Song Xingyan , Han Hao
Published: September 2022

This study presents a statistical analysis of the ionospheric irregularities and topside ionospheric scintillation at low and middle latitudes by using in situ electron density and upward-looking total electron content data measured by the Swarm constellation during 2014–2021. The main purpose of this study is to determine whether the phase scintillation could present similar seasonal, longitudinal, latitudinal, local time, and solar activity features as the in situ ionospheric irregularities do at low and middle latitudes, and how the irregularities affect the phase scintillation. The results are summarized as follows: (1) At low latitudes, the occurrence rate of equatorial plasma irregularities (EPIs) at the equinoxes and December solstice peaks before midnight, but during the June solstice, the EPIs mainly occur after midnight. The occurrence rate of EPIs has a positive correlation with solar activity. The distribution of topside scintillation occurrence is relatively consistent with EPIs, but during the June solstice, the scintillation occurrence rate remains at a very low level. (2) The midlatitude irregularities mainly occur after midnight, and their occurrence rate is negatively correlated with solar activity. Midlatitude irregularities mainly occur during the solstices, concentrated over the Pacific region during the June solstice and over the Pacific American sector during the December solstice. Especially, the distribution of midlatitude irregularities has hemispheric asymmetry, with a higher occurrence rate in the winter hemisphere. However, the occurrence of midlatitude scintillation is comparable in both hemispheres during the June solstice, and it concentrates in the southern hemisphere during the December solstice. (3) The EPIs concentrate more at the altitudes of Swarm A, while the midlatitude irregularities mainly occur at the altitudes of Swarm B.
Precise Positioning Method of Moving Laser Point Cloud in Shield Tunnel Based on Bolt Hole Extraction
Authors: Ji Changqi , Sun Haili , Zhong Ruofei , Li Jincheng , Han Yulong
Published: September 2022

Mobile laser scanning technology used for deformation detection of shield tunnel is usually two-dimensional, which is expanded into three-dimensional (3D) through mileage, resulting in low positioning accuracy. This study proposes a 3D laser point cloud positioning method that is divided into rings in the mileage direction and blocks in the ring direction to improve the positional accuracy for shield tunnels. First, the cylindrical tunnel wall is expanded into a plane and the bolt holes are extracted using the self-adaptive parameter adjustment cloth simulation filter (CSF) algorithm combined with a density-based spatial clustering of applications with noise (DBSCAN) algorithm. Second, the mean-shift algorithm is used to obtain the center point of the bolt hole, and a model is designed to recognize the center point of different splicing blocks. Finally, the center point is combined with the standard straight-line equation to fit the straight-line positioning seam, achieving an accurate ring and block segmentation of a shield tunnel as a 3D laser point cloud. The proposed method is compared with existing methods to verify its feasibility and high accuracy using the seams located by the measured tunnel point cloud data and in the measured point cloud. The average differences between the circumferential seams positioned using the proposed method and those in the point cloud at the left waist, vault, and right waist were 3, 4, and 5 mm, respectively, and the average difference between the longitudinal seams was 3.4 mm The proposed research method provides important technical and theoretical support for tunnel safety monitoring and detection.
Energy Drinks Decrease Left Ventricular Efficiency in Healthy Children and Teenagers: A Randomized Trial
Authors: Oberhoffer Felix Sebastian , Li Pengzhu , Jakob André , Dalla-Pozza Robert , Haas Nikolaus Alexander , Mandilaras Guido
Published: September 2022

Background: Minors are considered the main consumer group of energy drinks (EDs). The aim of this study was to investigate the acute effects of ED consumption on left ventricular (LV) hemodynamics and efficiency in healthy children and teenagers. Methods: This study was a randomized, single-blind, placebo-controlled, crossover clinical trial. Study participants consumed a weight-adjusted amount of an ED or a placebo on two consecutive days. LV hemodynamics and efficiency parameters were evaluated non-invasively by generating LV pressure–volume loops (PVLs) through simultaneous echocardiography and blood pressure measurement. Results: A total of 24 children and teenagers (14.90 ± 2.27 years, 13 male) were included in the present study. Conventional echocardiographic parameters of LV function did not show significant differences between both beverage groups. The non-invasive generation of LV PVLs revealed a significantly lower cardiac efficiency 240 min after the ED consumption compared to the placebo intake (140.72 (133.21–149.73) mmHg vs. 135.60 (124.78–140.33) mmHg, p < 0.01). Conclusions: Acute ED consumption is associated with a significantly lower cardiac efficiency in healthy minors. The generation of non-invasive LV PVLs might be beneficial in the assessment of subtle changes in LV efficiency. Further studies need to investigate the influence of chronic ED consumption on LV function and morphology.
A Contemporary Design Process for Single-Phase Voltage Source Inverter Control Systems
Authors: Bernacki Krzysztof , Rymarski Zbigniew
Published: September 2022

This paper presents an overview of contemporary voltage source inverter control system design. Design begins with the theoretical considerations that lead to the creation of the system’s differential control law. This stage does not include scaling coefficients for the output voltage, output current, and filter inductor current. Following this, the inverter is modelled in MATLAB’s Simulink environment with an appropriate load and control system. If the resultant simulation provides satisfactory results, a hybrid system consisting of MATLAB’s Simulink and dSpace libraries with the MicroLabBox device is used to interface the simulation with an experimental hardware model in real-time. This allows the hardware plant and measuring traces to be validated. ControlDesk is used to scale the relevant coefficients. During the final stage of the design process, a microprocessor is programmed to control the inverter according to the dSpace simulation results. This requires new scaling values. Throughout every stage of the design process, too high a value of the modulation index disables the reduction of output voltage distortions. This paper details the entire design process for both single-input and multi-input control systems, explaining the scaling process and the required software. Such a modern design process ensures the shortest time between conceptualization and the final product.
Cooperative Anti-Deception Jamming in a Distributed Multiple-Radar System under Registration Errors
Authors: Zhao Shanshan , Yi Minju , Liu Ziwei
Published: September 2022

A distributed multiple-radar system has natural advantages in anti-deception jamming. However, most of the anti-jamming methods are proposed in full spatial registration. In practice, the registration error is difficult to eliminate, which will seriously degrade the performance of cooperative anti-jamming. Therefore, it is of great significance to consider the problem of cooperative anti-deception jamming under registration error. In this paper, the cooperative anti-deception jamming method is proposed in a distributed multiple-radar system under registration errors. On the premise of the known registration error, target received signal vectors are estimated from an uncertainty region in each channel by maximum likelihood (ML) algorithm. With the estimated received signal vectors, a target discrimination algorithm is introduced based on the difference in target spatial scattering characteristics, which calculate the correlation coefficient between different target received signal vectors and discriminate a false target with a designed threshold. Furthermore, since the registration error depends on the radar site errors, theoretical derivation for the registration error is given as a function of the transmitter and receiver site errors. Finally, simulation results verify the feasibility of the proposed discrimination method, and its performance due to the influence of the jamming-to-noise ratio (JNR), the registration error, the target size, and the discrimination threshold are considered.
A Design of Analog Front-End with DBPSK Demodulator for Magnetic Field Wireless Network Sensors
Authors: Asl S. Ali Hosseini , Rikan Behnam S. , Hejazi Arash , Pu YoungGun , Huh Hyungki , Jung Yeonjae , Hwang Keum Cheol , Yang Youngoo , Lee Kang-Yoon
Published: September 2022

This paper presents an on-chip fully integrated analog front-end (AFE) with a non-coherent digital binary phase-shift keying (DBPSK) demodulator suitable for short-range magnetic field wireless communication applications. The proposed non-coherent DBPSK demodulator is designed based on using comparators to digitize the received differential analog BPSK signal. The DBPSK demodulator does not need any phase-lock loop (PLL) to detect the data and recover the clock. Moreover, the proposed demodulator provides the detected data and the recovered clock simultaneously. Even though previous studies have offered the basic structure of the AFEs, this work tries to amplify and generate the required differential BPSK signal without missing data and clock throughout the AFE, while a low voltage level signal is received at the input of the AFE. A DC-offset cancellation (DCOC), a cascaded variable gain amplifier (VGA), and a single-to-differential (STOD) converter are employed to construct the implemented AFE. The simulation results indicate that the AFE provides a dynamic range of 0 dB to 40 dB power gain with 2 dB resolution. Measurement results show the minimum detectable voltage at the input of AFE is obtained at 20 mV peak-to-peak. The AFE and the proposed DBSPK demodulator are analyzed and fabricated in a 130 nm Bipolar-CMOS-DMOS (BCD) technology to recover the maximum data rate of 32 kbps where the carrier frequency is 128 kHz. The implemented DCOC, cascaded VGA, STOD, and the demodulator occupy 0.15 mm2, 0.063 mm2, 0.045 mm2, and 0.03 mm2 of area, respectively. The AFE and the demodulator consume 2.9 mA and 0.15 mA of current from an external 5 V power supply, respectively.
Test Structure Design for Defect Detection during Active Thermal Cycling
Authors: Florea Ciprian , Simon Dan , Bojiță Adrian , Purcar Marius , Boianceanu Cristian , Țopa Vasile
Published: September 2022

Integrated power ICs acting as smart power switches for automotive or industrial applications are often subjected to active thermal cycling. Consequently, they undergo significant self-heating and are prone to various failure mechanisms related to the electro-thermo-mechanical phenomena that take place in the device metallization. In this article a test structure consisting of a lateral DMOS transistor equipped with several integrated sensors is proposed for metallization fatigue assessment. The design of the test structure is presented in detail, alongside with design considerations drawn from the literature and from simulation results. The testing procedure is then described, and experimental results are discussed. The experimental data provided by the integrated sensors correlated with the electro-thermal simulation results indicate the emergence of a failure mechanism and this is later confirmed by failure analysis. Conclusions are further drawn regarding the feasibility of using the proposed integrated sensors for monitoring defects in power ICs.
MulTNet: A Multi-Scale Transformer Network for Marine Image Segmentation toward Fishing
Authors: Xu Xi , Qin Yi , Xi Dejun , Ming Ruotong , Xia Jie
Published: September 2022

Image segmentation plays an important role in the sensing systems of autonomous underwater vehicles for fishing. Via accurately perceiving the marine organisms and surrounding environment, the automatic catch of marine products can be implemented. However, existing segmentation methods cannot precisely segment marine animals due to the low quality and complex shapes of collected marine images in the underwater situation. A novel multi-scale transformer network (MulTNet) is proposed for improving the segmentation accuracy of marine animals, and it simultaneously possesses the merits of a convolutional neural network (CNN) and a transformer. To alleviate the computational burden of the proposed network, a dimensionality reduction CNN module (DRCM) based on progressive downsampling is first designed to fully extract the low-level features, and then they are fed into a proposed multi-scale transformer module (MTM). For capturing the rich contextural information from different subregions and scales, four parallel small-scale encoder layers with different heads are constructed, and then they are combined with a large-scale transformer layer to form a multi-scale transformer module. The comparative results demonstrate MulTNet outperforms the existing advanced image segmentation networks, with MIOU improvements of 0.76% in the marine animal dataset and 0.29% in the ISIC 2018 dataset. Consequently, the proposed method has important application value for segmenting underwater images.
Ultrasonic Monitoring of the Water Content in Concentrated Water–Petroleum Emulsions Using the Slope of the Phase Spectrum
Authors: Franco Ediguer E. , Reyna Carlos A. B. , Durán Alberto L. , Buiochi Flávio
Published: September 2022

This work proposes the slope of the phase spectrum as a signal processing parameter for the ultrasonic monitoring of the water content of water-in-crude oil emulsions. Experimental measurements, with water volume fractions from 0 to 0.48 and test temperatures of 20 °C, 25 °C, and 30 °C, were carried out using ultrasonic measurement devices operating in transmission–reception and backscattering modes. The results show the phase slope depends on the water volume fraction and, to a lesser extent, on the size of the emulsion droplets, leading to a stable behavior over time. Conversely, the behavior of the phase slope as a function of the volume fraction is monotonic with low dispersion. Fitting a power function to the experimental data provides calibration curves that can be used to determine the water content with percentage relative error up to 70% for a water volume fraction of 0.06, but less than 10% for water volume fractions greater than 0.06. Furthermore, the methodology works over a wide range of volume fractions.
Enhanced Ambient Sensing Environment—A New Method for Calibrating Low-Cost Gas Sensors
Authors: Russell Hugo Savill , Frederickson Louise Bøge , Kwiatkowski Szymon , Emygdio Ana Paula Mendes , Kumar Prashant , Schmidt Johan Albrecht , Hertel Ole , Johnson Matthew Stanley
Published: September 2022

Accurate calibration of low-cost gas sensors is, at present, a time consuming and difficult process. Laboratory calibration and field calibration methods are currently used, but laboratory calibration is generally discounted due to poor transferability, and field methods requiring several weeks are standard. The Enhanced Ambient Sensing Environment (EASE) method described in this article, is a hybrid of the two, combining the advantages of a laboratory calibration with the increased accuracy of a field calibration. It involves calibrating sensors inside a duct, drawing in ambient air with similar properties to the site where the sensors will operate, but with the added feature of being able to artificially increases or decrease pollutant levels, thus condensing the calibration period required. Calibration of both metal-oxide (MOx) and electrochemical (EC) gas sensors for the measurement of NO2 and O3 (0–120 ppb) were conducted in EASE, laboratory and field environments, and validated in field environments. The EC sensors performed marginally better than MOx sensors for NO2 measurement and sensor performance was similar for O3 measurement, but the EC sensor nodes had less node inter-node variability and were more robust. For both gasses and sensor types the EASE calibration outperformed the laboratory calibration, and performed similarly to or better than the field calibration, whilst requiring a fraction of the time.
Domain Adaptation for In-Line Allergen Classification of Agri-Food Powders Using Near-Infrared Spectroscopy
Authors: Bowler Alexander Lewis , Ozturk Samet , Rady Ahmed , Watson Nicholas
Published: September 2022

The addition of incorrect agri-food powders to a production line due to human error is a large safety concern in food and drink manufacturing, owing to incorporation of allergens in the final product. This work combines near-infrared spectroscopy with machine-learning models for early detection of this problem. Specifically, domain adaptation is used to transfer models from spectra acquired under stationary conditions to moving samples, thereby minimizing the volume of labelled data required to collect on a production line. Two deep-learning domain-adaptation methodologies are used: domain-adversarial neural networks and semisupervised generative adversarial neural networks. Overall, accuracy of up to 96.0% was achieved using no labelled data from the target domain moving spectra, and up to 99.68% was achieved when incorporating a single labelled data instance for each material into model training. Using both domain-adaptation methodologies together achieved the highest prediction accuracies on average, as did combining measurements from two near-infrared spectroscopy sensors with different wavelength ranges. Ensemble methods were used to further increase model accuracy and provide quantification of model uncertainty, and a feature-permutation method was used for global interpretability of the models.
Development of a Mobile Sensory Device to Trace Treatment Conditions for Various Medical Plasma Source Devices
Authors: Chaerony Siffa Ihda , Gerling Torsten , Masur Kai , Eschenburg Christian , Starkowski Frank , Emmert Steffen
Published: September 2022

The emerging use of low-temperature plasma in medicine, especially in wound treatment, calls for a better way of documenting the treatment parameters. This paper describes the development of a mobile sensory device (referred to as MSD) that can be used during the treatment to ease the documentation of important parameters in a streamlined process. These parameters include the patient’s general information, plasma source device used in the treatment, plasma treatment time, ambient humidity and temperature. MSD was developed as a standalone Raspberry Pi-based version and attachable module version for laptops and tablets. Both versions feature a user-friendly GUI, temperature–humidity sensor, microphone, treatment report generation and export. For the logging of plasma treatment time, a sound-based plasma detection system was developed, initially for three medically certified plasma source devices: kINPen® MED, plasma care®, and PlasmaDerm® Flex. Experimental validation of the developed detection system shows accurate and reliable detection is achievable at 5 cm measurement distance in quiet and noisy environments for all devices. All in all, the developed tool is a first step to a more automated, integrated, and streamlined approach of plasma treatment documentation that can help prevent user variability.
Path Planning and Formation Control for UAV-Enabled Mobile Edge Computing Network
Authors: Choutri Kheireddine , Lagha Mohand , Meshoul Souham , Fadloun Samiha
Published: September 2022

Recent developments in unmanned aerial vehicles (UAVs) have led to the introduction of a wide variety of innovative applications, especially in the Mobile Edge Computing (MEC) field. UAV swarms are suggested as a promising solution to cope with the issues that may arise when connecting Internet of Things (IoT) applications to a fog platform. We are interested in a crucial aspect of designing a swarm of UAVs in this work, which is the coordination of swarm agents in complicated and unknown environments. Centralized leader–follower formations are one of the most prevalent architectural designs in the literature. In the event of a failed leader, however, the entire mission is canceled. This paper proposes a framework to enable the use of UAVs under different MEC architectures, overcomes the drawbacks of centralized architectures, and improves their overall performance. The most significant contribution of this research is the combination of distributed formation control, online leader election, and collaborative obstacle avoidance. For the initial phase, the optimal path between departure and arrival points is generated, avoiding obstacles and agent collisions. Next, a quaternion-based sliding mode controller is designed for formation control and trajectory tracking. Moreover, in the event of a failed leader, the leader election phase allows agents to select the most qualified leader for the formation. Multiple possible scenarios simulating real-time applications are used to evaluate the framework. The obtained results demonstrate the capability of UAVs to adapt to different MEC architectures under different constraints. Lastly, a comparison is made with existing structures to demonstrate the effectiveness, safety, and durability of the designed framework.
Use of DSLR and Sonic Cameras to Detect and Locate High-Voltage Corona Discharges
Authors: Riba Jordi-Roger , Bas-Calopa Pau
Published: September 2022

Corona discharges are a concern in high-voltage applications. It is of utmost importance to detect and locate the discharges at an early stage using simple methods for this purpose. This paper evaluates and compares the sensitivity of two methods for detecting and locating the source of discharges, which are based on a digital single-lens reflex (DSLR) camera and a portable wideband sonic camera incorporating a matrix of micro-electromechanical systems (MEMS) microphones. Both cameras can generate an image of the studied area where the discharge sites are identified. The study is carried out with different electrode geometries, 50 Hz alternating current (ac) and positive and negative direct current (dc) supplies, and the effect of the distance between the sensor and the discharge sites is also analyzed. The presented results show that the sonic camera enables fast, simple, and sensitive detection and localization of the source of corona discharges even at a very early stage in daylight conditions, regardless of the type of power supply, that is, ac or positive/negative dc, and at distance of several meters from the discharge source.
FBG Spectrum Regeneration by Ni-Coating and High-Temperature Treatment
Authors: Lupi Carla , Vendittozzi Cristian , Ciro Erwin , Felli Ferdinando
Published: September 2022

FBG sensors are used in many scientific and industrial fields for assessing the structural integrity of mechanical components and in very high (above 600 °C) or very low (cryogenic) temperature applications. The main concerns with the use of such sensors in applications involving extreme temperatures are related partly to the instability of the reflected spectrum, which tends to dissolve into the noise floor, and partly to the degradation of the mechanical properties of the optical fiber, which tends to worsen the inherent brittleness. All of this raises the need for a robust nickel protective coating to ensure the grating’s integrity in high-temperature environments. In addition, the inherent brittleness of fiber-optic gratings leaves one to wonder whether it is possible to recover a broken, seemingly unusable sensor. In this way, a single-peak commercial FBG was intentionally broken in the middle of the grating length and re-spliced, inducing a strongly asymmetric chirped-like spectrum; then, a nickel coating was electrodeposited on its surface. The most important outcome achieved by this work is the regeneration of a highly distorted reflected spectrum through three thermal cycles performed from room temperature up to 500, 750, and 800 °C, respectively. After reaching a temperature of at least 700 °C, the spectrum, which has been drastically altered by splicing, becomes stable and restores its single peak shape. A further stabilization cycle carried out at 800 °C for 80 min led to an estimation of the stabilizing time of the new single-peak reflected spectrum.
Characterization of Thermal Gradient Effects on a Quartz Crystal Microbalance
Authors: Magni Marianna , Scaccabarozzi Diego , Palomba Ernesto , Zampetti Emiliano , Saggin Bortolino
Published: September 2022

Quartz crystal microbalances are widely used sensors with applications for the detection of very-low-mass deposition in many different fields, from contamination monitoring in the high vacuum of deep space missions to the monitoring of biological activity or pollution using specifically designed active substrates. These sensors are very stable over time; nevertheless, their sensitivity to the temperature is well known, and different implementations have been devised to correct it, e.g., through compensation with a dual crystal. This paper deals with the effects of temperature on QCM but separates the case of uniform crystal temperature from the case of in-plane temperature gradients considering a QCM based on quartz crystals with deposited film resistors used as both RTDs and heaters. This configuration allows both an accurate temperature measurement and efficient thermal control, allowing the achievement of crystals temperatures in the order of 400 °C higher than the environment with a low power dissipation of the order of 1 W. The film resistors deposited around the electrodes allow directly measuring the average crystal temperature and directly delivering power to the crystal for thermal control. The localized delivery of the heat nevertheless also determines uncommon temperature fields on the crystal, and thus, an analysis of both the effects of temperature on the new microbalance was performed. The temperature gradient has strong effects on the frequency; therefore, along with the temperature, the thermal gradients have tobe compensated. The calibration of the QCM thermometers and the assessment of the achievable measurement accuracy were performed, as well as the determination of the frequency–temperature relationship. The comparison between frequency changes in the case of uniform temperature and those observed while using crystal heaters proved that temperature gradients have a strong effect on the crystal frequency. To identify the temperature field on the crystal surface of a QCM crystal, the gold coating of the deposited films was removed to achieve an emissivity acceptable for thermal imaging with an IR camera. Moreover, image processing for emissivity correction was developed. In order to correlate the temperature gradient with the frequency variation, a test campaign was performed to measure the frequency changes derived from different power levels delivered to the crystal heaters. From this test campaign and thermal analysis, the effect of the thermal gradient was assessed.
The Numerical Investigation of the Performance of a Newly Designed Sediment Trap for Horizontal Transport Flux
Authors: Wang Cheng , Guo Lei , Zhang Shaotong , Fei Zihang , Xue Gang , Yang Xiuqing , Zhang Jiarui
Published: September 2022

Marine sediment transport is closely related to seafloor topography, material transport, marine engineering safety, etc. With a developed time-series vector observation device, the sediment capture and transport process can be observed. The structure of the capture tube and the internal filter screen can significantly affect the flow field during the actual observation, further influencing the sediment transport observation and particle capture process. This paper presents a numerical model for investigating the effect of device structure on seawater flow to study the processes of marine sediment transport observation and sediment particle capture. The model is based on the solution of both porous media and the Realizable k-ε turbulence in Fluent software. The flow velocity distribution inside and outside the capture tube with different screen pore sizes (0.300, 0.150, and 0.075 mm) is analyzed. To enhance the reliability of the numerical simulation, the simulation calculation results are compared with the test results and have good coincidence. Finally, by analyzing the motion law of sediment in the capture tube, the accurate capture of sediment particles is achieved, and the optimal capture efficiency of the sediment trap is obtained.
A Classification Model of EEG Signals Based on RNN-LSTM for Diagnosing Focal and Generalized Epilepsy
Authors: Najafi Tahereh , Jaafar Rosmina , Remli Rabani , Wan Zaidi Wan Asyraf
Published: September 2022

Epilepsy is a chronic neurological disorder caused by abnormal neuronal activity that is diagnosed visually by analyzing electroencephalography (EEG) signals. Background: Surgical operations are the only option for epilepsy treatment when patients are refractory to treatment, which highlights the role of classifying focal and generalized epilepsy syndrome. Therefore, developing a model to be used for diagnosing focal and generalized epilepsy automatically is important. Methods: A classification model based on longitudinal bipolar montage (LB), discrete wavelet transform (DWT), feature extraction techniques, and statistical analysis in feature selection for RNN combined with long short-term memory (LSTM) is proposed in this work for identifying epilepsy. Initially, normal and epileptic LB channels were decomposed into three levels, and 15 various features were extracted. The selected features were extracted from each segment of the signals and fed into LSTM for the classification approach. Results: The proposed algorithm achieved a 96.1% accuracy, a 96.8% sensitivity, and a 97.4% specificity in distinguishing normal subjects from subjects with epilepsy. This optimal model was used to analyze the channels of subjects with focal and generalized epilepsy for diagnosing purposes, relying on statistical parameters. Conclusions: The proposed approach is promising, as it can be used to detect epilepsy with satisfactory classification performance and diagnose focal and generalized epilepsy.
Optical Monitoring of Breathing Patterns and Tissue Oxygenation: A Potential Application in COVID-19 Screening and Monitoring
Authors: Mah Aaron James , Nguyen Thien , Ghazi Zadeh Leili , Shadgan Atrina , Khaksari Kosar , Nourizadeh Mehdi , Zaidi Ali , Park Soongho , Gandjbakhche Amir H. , Shadgan Babak
Published: September 2022

The worldwide outbreak of the novel Coronavirus (COVID-19) has highlighted the need for a screening and monitoring system for infectious respiratory diseases in the acute and chronic phase. The purpose of this study was to examine the feasibility of using a wearable near-infrared spectroscopy (NIRS) sensor to collect respiratory signals and distinguish between normal and simulated pathological breathing. Twenty-one healthy adults participated in an experiment that examined five separate breathing conditions. Respiratory signals were collected with a continuous-wave NIRS sensor (PortaLite, Artinis Medical Systems) affixed over the sternal manubrium. Following a three-minute baseline, participants began five minutes of imposed difficult breathing using a respiratory trainer. After a five minute recovery period, participants began five minutes of imposed rapid and shallow breathing. The study concluded with five additional minutes of regular breathing. NIRS signals were analyzed using a machine learning model to distinguish between normal and simulated pathological breathing. Three features: breathing interval, breathing depth, and O2Hb signal amplitude were extracted from the NIRS data and, when used together, resulted in a weighted average accuracy of 0.87. This study demonstrated that a wearable NIRS sensor can monitor respiratory patterns continuously and non-invasively and we identified three respiratory features that can distinguish between normal and simulated pathological breathing.
Volunteer Food Handlers’ Safety Knowledge and Practices in Implementing National School Nutrition Programme in Gauteng North District, South Africa
Authors: Chelule Paul K. , Ranwedzi Mavis
Published: September 2022

Volunteer food handlers (VFHs) working in school feeding programmes contribute immensely to the safety of food served to the school learners. However, their level of knowledge and practice of safe food handling is questionable. This study investigated food safety knowledge and practices of VFHs working for the National School Nutrition Programme (NSNP) in Gauteng North District, South Africa. This was a descriptive quantitative study in which data were obtained using a standard structured questionnaire. A total of 115 VFHs participated in the study. Most of the VFHs (n = 84, 73.0%) had secondary education with working experience of between 1 to 12 months. Although a high level of knowledge on food safety was demonstrated by the VFHs, this did not fully translate into safe food handling practices. The new VFH recruits were 66% more likely to wear protective clothing than the rest (OR: 0.34, 95%CI: 0.12–0.91, p = 0.033). Women were 90% more likely to wear aprons than men (OR = 0.11; 95 CI: 0.03–0.45; p = 0.002). In this study, VFHs demonstrated adequate levels of knowledge on food safety. Lack of facilities contributed to VFH non-compliance to safe food handling practices. Thus, there is a need to further support VFHs to comply with recommended safe food handling practices.
Tensor Rank Regularization with Bias Compensation for Millimeter Wave Channel Estimation
Authors: He Fei , Harms Andrew , Yang Lamar Yaoqing
Published: September 2022

This paper presents a novel method of tensor rank regularization with bias compensation for channel estimation in a hybrid millimeter wave MIMO-OFDM system. Channel estimation is challenging due to the unknown number of multipath components that determines the channel rank. In general, finding the intrinsic rank of a tensor is a non-deterministic polynomial-time (NP) hard problem. However, by leveraging the sparse characteristics of millimeter wave channels, we propose a modified CANDECOMP/PARAFAC (CP) decomposition-based method that jointly estimates the tensor rank and channel component matrices. Our approach differs from most existing works that assume the number of channel paths is known and the proposed method is able to estimate channel parameters accurately without the prior knowledge of number of multipaths. The objective of this work is to estimate the tensor rank by a novel sparsity-promoting prior that is incorporated into a standard alternating least squares (ALS) function. We introduce a weighting parameter to control the impact of the previous estimate and the tensor rank estimation bias compensation in the regularized ALS. The channel information is then extracted from the estimated component matrices. Simulation results show that the proposed scheme outperforms the baseline l1 strategy in terms of accuracy and robustness. It also shows that this method significantly improves rank estimation success at the expense of slightly more iterations.
Empirical Formal Methods: Guidelines for Performing Empirical Studies on Formal Methods
Authors: ter Beek Maurice H. , Ferrari Alessio
Published: September 2022

Empirical studies on formal methods and tools are rare. In this paper, we provide guidelines for such studies. We mention their main ingredients and then define nine different study strategies (usability testing, laboratory experiments with software and human subjects, case studies, qualitative studies, surveys, judgement studies, systematic literature reviews, and systematic mapping studies) and discuss for each of them their crucial characteristics, the difficulties of applying them to formal methods and tools, typical threats to validity, their maturity in formal methods, pointers to external guidelines, and pointers to studies in other fields. We conclude with a number of challenges for empirical formal methods.
Measuring Concentrated Solar Radiation Flux in a Linear Fresnel-Type Solar Collector
Authors: Fernández-Reche Jesús , Valenzuela Loreto , Pulido-Iparraguirre Diego
Published: September 2022

Linear Fresnel solar collectors are a promising and emerging solution to contribute to renewable heat supply in industrial processes with thermal energy demand in the medium temperature range (<250 °C). An innovative linear Fresnel collector (LFC) prototype has been designed, patented, and built at the Plataforma Solar de Almería (PSA), Spain. This work presents the applied methodology, experimental device, and results obtained in the measurement of the flux density of concentrated solar radiation in the focal plane of the solar collector. The experimental results confirm that an average flux density of (9.8 ± 0.6) kW/m2 was obtained with a direct normal solar irradiance of (870 ± 10) W/m2 in tests performed in May 2002, which is a result similar to that obtained in optical simulations of the system.
Quantitative Evaluation of Complex Degree of Geological Structure in Yangquan Mining Area
Authors: Pu Yang , Yang Zhihua
Published: September 2022

The study and analysis of tectonic activities on regional structures is of great significance to mine prospecting and production safety in mine work. We take the No. 3 coal seam in the Yangquan mining area as the object of study. The methods of fractal dimension, structural curvature and trend surface analysis are applied to quantitatively evaluate and predict the mine structure. The folded meso-plane analysis is also carried out. The results show that the trend surface reflects that the monoclinic structure is high in the NE direction and low in the SW direction. The dip angle is small, and the overall structure is characterized by an NNE−NE trend. The curvature value of the coal seam in the mining area is generally small. The northwest structure is relatively simple. The eastern fracture is more developed. The southern structure is relatively simple. A large nearly EW direction Taohe syncline is developed in the middle and south. Several large fractures in the NE direction are developed in the southwest. The capacity dimension of fractures in the mine field is mostly between 0.6 and 1.6. It indicates that the complexity of the fracture structure in the mine field has obvious heterogeneity. The neutral surface of the mine is in the third section of Taiyuan formation, and the No. 3 coal seam is above it. The research results have reference significance for the evaluation and prediction of safe mining and gas outburst danger zones in mining areas.
Multicultural Education Policies and Connected Ways of Living during COVID-19: Role of Educators as Cultural Transformers
Authors: Kirac Necla İzbul , Altinay Fahriye , Dagli Gokmen , Altinay Zehra , Sharma Ramesh , Shadiev Rustam , Celebi Menil
Published: September 2022

Multicultural education plays a significant role in eliminating prejudices and developing concepts such as tolerance, understanding, respect for differences, and empathy. The northern part of Cyprus exhibits the characteristics of a society that has received increasing numbers of immigrants in recent years, and where the experiences of living together with individuals from different cultures begin to differ rapidly. As a result of increasing immigration to the northern part of Cyprus in recent years and the changing lives based on digitalization, students from different cultures have started to receive education in schools. The aim of this research is to evaluate the multicultural education policies to contribute to the creation and implementation of multicultural education policies according to the results of the evaluation of the role of digital educators in transforming cultures. In addition, the qualitative research model was adopted, and the Case Study pattern was used. The interview technique was used for data collection. The research universe consisted of 31 participants, including teacher training faculty members, administrators, and teachers working in public schools in the 2020–2021 academic year in the northern part of Cyprus. Educators participating in the research expressed more positive views on multiculturalism, multicultural education, and multicultural education.
Air Quality and Thermal Environment of Primary School Classrooms with Sustainable Structures in Northern Shaanxi, China: A Numerical Study
Authors: Lan Kun , Chen Yang
Published: September 2022

In northern Shaanxi, China, the air quality and thermal insulation properties of primary school classrooms should be given more attention due to the relatively low temperatures in the winter, which are significant to the learning processes of students in classrooms. Some sustainable building measures have been designed and constructed to improve the air quality and thermal comfort of classrooms in this region; however, is still unclear how these measures influence air quality and temperature. This study investigated the indoor air quality and thermal environment of a typical primary school classroom in Yulin city, Shaanxi Province, China. The classroom was characterized by sustainable structures, including double-sided corridors and an underground ventilation pipe, for better thermal insulation. By conducting on-site monitoring in the classroom and performing various numerical simulations based on finite element software, the variations in the indoor air quality (carbon dioxide, water vapor concentration) and temperature over time, and under different conditions, were investigated. Moreover, influences (i.e., of corridors, ventilation pipes, window areas, classroom areas, and the number of students) on the air quality and temperature were analyzed. It was proven that double-sided corridors, underground ventilation pipes, and windows with heights/widths equaling 1 could provide energy-efficient and livable building structures for primary school classrooms in the northern Shaanxi region of China.
Research on Financial Early Warning Based on Combination Forecasting Model
Authors: Kuang Jin , Chang Tse-Chen , Chu Chia-Wei
Published: September 2022

Since entering the 21st century, “economic globalization” has become a hot topic. Under the impact of “economic globalization”, the competition of the Chinese domestic market continues to intensify, and Chinese enterprises are facing enormous pressure for survival and development. Among them, there are many cases of poor business operation caused by financial crisis which have directly put these companies in trouble, even causing them to go bankrupt. Therefore, it is very practical to establish a scientific data model to analyze and predict the financial data of enterprises. It can not only monitor the financial status of the enterprise in real time, but also play an effective financial early warning role. This research focuses on using the combined forecasting method to establish a more comprehensive financial early warning model to solve the related financial crisis forecasting problem. Specifically, two different forecasting methods are first adopted in this study to conduct financial early warning research. The first is time series forecasting. It is a dynamic data processing statistical method, which is often used in forecasting research in the business field. The second is the BP neural network algorithm (referred to as BP), which is an error back-propagation learning algorithm, which is often used in the field of artificial intelligence. Then, the prediction error values of the two methods are compared and they are applied to the combined prediction method. Finally, a new error prediction formula is obtained. The result shows that the BP method provides the best performance over others, while the combinational forecasting method offers better performance than any single method.
Modeling Urban Freeway Rear-End Collision Risk Using Machine Learning Algorithms
Authors: Ma Xiaolong , Yu Qiang , Liu Jianbei
Published: September 2022

A large amount of traffic crash investigations have shown that rear-end collisions are the main type collisions on the freeway. The purpose of this study is to investigate the rear-end collision risk on the freeway. Firstly, a new framework was proposed to develop the rear-end collision probability (RCP) model between two vehicles based on Generalized Pareto Distribution (GPD). Secondly, the freeway rear-end collision risk (F-RCR) was defined as the sum of the rear-end collision probability of each vehicle and divided into three levels which was high, median, and low rear-end collision risk. Then, different machine learning algorithms were used to model F-RCR under the condition of an unbalanced dataset. The result of the RCP model showed continuous change and can identify the dangerous condition quickly compared to the traditional models even when the speed of the leading vehicle is faster than the following vehicle. When the vehicle distribution was unbalanced on road and the speed difference between adjacent lanes and the traffic volume was large, F-RCR will increase. Multi-Layer Perceptron (MLP) was found to be more suitable for modeling F-RCR. The framework provided in this research was transferrable and can be used in the freeway proactive traffic safety management system.
Ecosystem Services of Mangroves: A Systematic Review and Synthesis of Contemporary Scientific Literature
Authors: Bimrah Kanika , Dasgupta Rajarshi , Hashimoto Shizuka , Saizen Izuru , Dhyani Shalini
Published: September 2022

The paper narrates a systematic literature review on ‘’mangrove ecosystem services’’ to identify their typology, distribution, and utilization within the contemporary scientific literature. We performed a systematic review of 76 research articles derived from the Scopus database, and the dataset was scrutinized and classified against the four major categories of ecosystem services, namely provisioning, regulating, cultural, and supporting services, as per the Millennium Ecosystem Assessment (2005). We attempted to determine the existing state of the interconnectedness of mangrove ecosystem services by mapping the potential synergies and trade-offs. Further, an attempt was made to understand the critical linkages between mangrove ecosystem services and their contribution to the localization/achievement of the Sustainable Development Goals (SDGs). The results suggest disproportionate distribution of scientific literature, where nearly 56 of the studies were concentrated in Asia. The recognition of regulating the services of mangroves, particularly in carbon storage and disaster risk reduction, outnumbered the other types of ecosystem services. In particular, studies related to mangroves’ cultural ecosystem services remain underrepresented. The results show a strong correlation in terms of synergies between the coastal protection ecosystem services and the high carbon sequestration ability of mangroves; and the trade-off between facilitating water transport services and the provision of fresh water. Of the 17 SDGs, three SDGs, namely, SDG 12 (responsible consumption and production), SDG 13 (climate action), and SDG 14 and 15 (life below water and life on land) showed close interrelationships with the existing database. As such, the results are beneficial for coastal planners to better integrate and mainstream mangrove ecosystem services into coastal and regional planning, by maximizing synergies, encouraging the involvement of coastal communities as well as elaborating ameliorative adaptive measures.