bluuebunny/crossref_metadata_2025 huggingface dataset:
Rainfall Consistency, Variability, and Concentration over the UAE: Satellite Precipitation Products vs. Rain Gauge Observations
Authors: Baig Faisal , Abrar Muhammad , Chen Haonan , Sherif Mohsen
Published: November 2022

Recent advancements in remote sensing have led to the development of several useful technologies that would significantly improve our understanding of atmospheric sciences. The ability to identify atmospheric conditions and determine the possibility and intensity of rainfall over a specific location represents one of the most important advantages. However, the use of remote sensing to measure precipitation in arid regions has revealed significant disparities due to a mixture of climatic and terrestrial factors. The objective of this study is to assess the precipitation consistency, variability, and concentration over the UAE using four multi-satellite remote sensing products, namely CHIRPS, CMORPH, GPM-IMERG, and the PERSIANN-CDR, considering daily rainfall data from 50 rain gauges for the period from 2004 through 2020. The study area is divided into various geomorphological regions to assess the accuracy of the products in different regions. Results reveal that the products with a finer spatial resolution such as CHIRPS and CMORPH are better in terms of annual and daily average values. CHIRPS and GPM-IMERG demonstrated better POD values of 0.80 and 0.78, respectively, while CMORPH and the PERSIANN-CDR showed POD values of 0.72 and 0.44, respectively. The correlation and error estimate analysis showed that the performance of different products varies in each region. The PERSIANN-CDR registered the highest correlation of 0.8 for the East Coast, while for other regions it could not correlate well. IMERG and CHIRPS were able to exhibit a good correlation value (up to 0.8) with the gauge observations. Precipitation concentration and variability analysis revealed that GPM-IMERG represents a better alternative to gauge data. It is concluded that multiple hydro-climatological measures should be utilized to assess the effectiveness of satellite products and select the best product for specific studies.
Physical-Based Spatial-Spectral Deep Fusion Network for Chlorophyll-a Estimation Using MODIS and Sentinel-2 MSI Data
Authors: He Yuting , Wu Penghai , Ma Xiaoshuang , Wang Jie , Wu Yanlan
Published: November 2022

Satellite-derived Chlorophyll-a (Chl-a) is an important environmental evaluation indicator for monitoring water environments. However, the available satellite images either have a coarse spatial or low spectral resolution, which restricts the applicability of Chl-a retrieval in coastal water (e.g., less than 1 km from the shoreline) for large- and medium-sized lakes/oceans. Considering Lake Chaohu as the study area, this paper proposes a physical-based spatial-spectral deep fusion network (PSSDFN) for Chl-a retrieval using Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 Multispectral Instrument (MSI) reflectance data. The PSSDFN combines residual connectivity and attention mechanisms to extract effective features, and introduces physical constraints, including spectral response functions and the physical degradation model, to reconcile spatial and spectral information. The fused and MSI data were used as input variables for collaborative retrieval, while only the MSI data were used as input variables for MSI retrieval. Combined with the Chl-a field data, a comparison between MSI and collaborative retrieval was conducted using four machine learning models. The results showed that collaborative retrieval can greatly improve the accuracy compared with MSI retrieval. This research illustrates that the PSSDFN can improve the estimated accuracy of Chl-a for coastal water (less than 1 km from the shoreline) in large- and medium-sized lakes/oceans.
Marine Heatwaves in the South China Sea: Tempo-Spatial Pattern and Its Association with Large-Scale Circulation
Authors: Li Yan , Ren Guoyu , Wang Qingyuan , Mu Lin , Niu Qianru
Published: November 2022

A marine heatwave (MHW) can significantly harm marine ecosystems and fisheries. Based on a remotely sensed sea surface temperature (SST) product, this study investigated MHWs behaviors in the South China Sea (SCS) throughout the warm season (May to September) from 1982 to 2020. The distributions of the three MHW indices used in this study showed significant latitudinal variations: more frequent, longer, and more intense MHWs appear in the northern SCS, and less frequent, shorter, and weaker MHWs appear in the southern SCS. Using the empirical orthogonal function (EOF) method, we found that the first leading modes of the three MHW indices account for more than half of the total variance. The first leading modes reveal uniform anomalies throughout the SCS, with the maximum in the deep central portion and its surroundings. Their corresponding time series showed significant interdecadal variations, with a turning point around 2009. Since 2010, the SCS has seen an increase in the frequency, length, and severity of MHWs. The incidence of MHWs has been linked to the presence of stable near-surface anticyclonic anomalies, which reduced cloud cover and increased solar radiation. This abnormal pattern was usually accompanied by the intensification and westward shift of the western North Pacific subtropical high (WNPSH). The findings imply that MHWs in the SCS may be predictable on interannual and decadal scales.
Investigating the Long-Term Variation Trends of Absorbing Aerosols over Asia by Using Multiple Satellites
Authors: Li Ding , Xue Yong , Qin Kai , Wang Han , Kang Hanshu , Wang Lizhang
Published: November 2022

Absorbing aerosols, consisting of smoke (black carbon (BC) and other organics) and dust (from windblown sources), can have a strong warming effect on the climate and impact atmospheric circulation due to localized heating. To investigate the spatiotemporal and vertical changes of absorbing aerosols across Asia, collocation data from OMI, MODIS, and CALIPSO were used to compare two periods: 2006–2013 and 2014–2021. This study revealed a significant temporal and spatial contrast of aerosol loading over the study region, with a drop in total aerosol concentration and anthropogenic smoke concentration recorded across the Eastern China region (all seasons) and a concurrent increase in the Indian sub-continent region (especially in autumn). The range of aerosol diffusion is affected by the height of the smoke and aerosol plumes, as well as the wind force, and is dispersed eastwards because of the Hadley circulation patterns in the Northern Hemisphere. Smoke from Southeast Asia typically rises to a height of 3 km and affects the largest area in contrast to other popular anthropogenic zones, where it is found to be around 1.5–2 km. The dust in Inner Mongolia had the lowest plume height of 2 km (typically in spring) compared to other locations across the study region where it reached 2–5 km in the summer. This study showed, by comparison with AERONET measurements, that combining data from MODIS and OMI generates more accuracy in detecting aerosol AOD from smoke than using the instruments singularly. This study has provided a comprehensive assessment of absorbing aerosol in Asia by utilizing multiplatform remote-sensed data and has summarized long-term changes in the spatiotemporal distribution and vertical structure of absorbing aerosols.
Environmental Conditions in Middle Eastern Megacities: A Comparative Spatiotemporal Analysis Using Remote Sensing Time Series
Authors: Mohammadi Shahin , Saber Mohsen , Amini Saeid , Mostafavi Mir Abolfazl , McArdle Gavin , Rabiei-Dastjerdi Hamidreza
Published: November 2022

Rapid and timely evaluation and monitoring of the urban environment has gained significant importance in understanding the state of urban sustainability in metropolises. Multi-source remote sensing (RS) data are a valuable source for a comprehensive understanding of urban environmental changes in developing countries. However, in the Middle East, a region with several developing countries, limited study has been conducted to understand urban environmental changes. In this study, to evaluate the changes in the urban environment, 32 metropolises in the Middle East were studied between 2000 and 2019. For this purpose, a comprehensive environmental index (CEI) integrated with Google Earth Engine (GEE) platform for processing and analysis is introduced. The results show degraded environmental conditions in 19 metropolises based on a significant increasing trend in the time series of the CEI index. The highest increasing trend in the value of the CEI was observed in the cities of Makkah, Jeddah, Basra, Riyadh, and Sana’a. The results also show that the percentage of urban areas in all 32 cities that falls into the degraded class varies from 5% to 75% between 2005 and 2018. The results of CEI changes in megacities, such as Ajman, Tehran, Jeddah, Makkah, Riyadh, Karaj, and Sana’a show that these cities have increasingly suffered from the degradation of environmental conditions since 2001. According to the results, it is recommended to pay more attention to environmental issues regarding the future of urban development in these cities. The proposed approach in this study can be implemented for environmental assessment in other regions.
Characteristics of Summer Hailstorms Observed by Radar and Himawari-8 in Beijing, China
Authors: Jing Yingying , Chen Yichen , Ma Xincheng , Ma Jianli , Li Xia , Ma Ningkun , Bi Kai
Published: November 2022

Severe hailstorms frequently occurred in Beijing between May and August 2021, leading to extensive hail damage. These hailstorms were observed by radar and satellite data, and reported by surface observers. In this study, the spectral and cloud microphysical characteristics of typical Beijing events in 2021 were analyzed using Himawari-8 satellite products and ground-based S-band weather radar data obtained from the Beijing Meteorological Bureau. The relationship between Himawari-8 brightness temperature differences (BTD) and radar reflectivity was also investigated. The results revealed that the significant spectral depression of brightness temperatures (BTs) in hail clouds was observed by a satellite. Furthermore, the stronger the radar reflectivity was, the more rapidly BTD decreased, with a nonlinear relationship between them. The results of cloud physical characteristics show that, for cloud-top heights above 10 km, the cloud effective radius was about 25 μm, with a cloud-top temperature of 225 K during these hail events. By means of Gaussian fitting, the BT threshold value (11.2 μm) was determined by satellite at 230 K, with a BTD focused on 1.9 K when hailstorms occurred. These results will help us better understand the characteristics of hailstorms, while also providing information for future hail suppression in Beijing.
Finite Element Model Updating of RC Bridge Structure with Static Load Testing: A Case Study of Vietnamese ThiThac Bridge in Coastal and Marine Environment
Authors: Nguyen Duc Cong , Salamak Marek , Katunin Andrzej , Gerges Michael
Published: November 2022

Diagnostic load testing refers to the use of the measured historical responses of the structure in the field data to better understand its dynamic and static structural behaviours. It is important and necessary to predict the health state, load capacity, and aging of the structure by updating the finite element (FE) model, which can give useful information to aid the design of retrofits and the maintenance of the existing bridge in the future. The paper presents an update of the full-scale FE model for the reinforced concrete (RC) bridge structure over the seawater river based on the experimental strains under the static load testing in which the representative FE model of the actual structure is determined from the optimisation procedures. The optimisation variables are applied, including the cross-sectional properties and concrete material calibrated through the genetic algorithm (GA) optimisation in the MATLAB software, which interfaces with the FE modelling in the scripting of the SOFISTIK TEDDY software automatically. The bending moments at the mid-span of the RC girders are determined in the FE modelling to compute stresses, which are compared with the measured stresses through optimisation scenarios with a percentage error of the objective function less than 10%. The measured data of concrete strains are recorded from reusable strain transducers installed on the mid-span girders for every bridge span, which are used to calibrate the bridge model in static load testing. The novelty of the solution is to implement innovative techniques using field data as an improved approach for calibrating automatically the analytical FE model parameters of all RC spans of the bridge until its static behaviours are very similar to those of the actual bridge. The final updated FE modelling is used to apply truck load configurations according to bridge design standards such as the AASHTO specifications, which can predict the load limits of the existing bridge structure more accurately and reliably. These proposed approaches can be applied to large bridges as well as complex structures with supporting FE analysis software and data processing software.
Geohash-Based Rapid Query Method of Regional Transactions in Blockchain for Internet of Vehicles
Authors: Zhou Chang , Lu Huimei , Xiang Yong , Wu Jingbang , Wang Feng
Published: November 2022

Many researchers have introduced blockchain into the Internet of Vehicles (IoV) to support trading or other authentication applications between vehicles. However, the traditional blockchain cannot well support the query of transactions that occur in a specified area which is important for vehicle users since they are bound to the geolocations. Therefore, the querying efficiency of the geolocation attribute of transactions is vital for blockchain-based applications. Existing work does not well handle the geolocation of vehicles in the blockchain, and thus the querying efficiency is questionable. In this paper, we design a rapid query method of regional transactions in blockchain for IoV, including data structures and query algorithms. The main idea is to utilize the Geohash code to represent the area and serve as the key for transaction indexing and querying, and the geolocation is marked as one of the attributes of transactions in the blockchain. To further verify and evaluate the proposed design, on the basis of the implementation of Ethereum, which is a well-known blockchain, the results show that the proposed design achieves significantly better-querying speed than Ethereum.
Rules-Based Real-Time Gait Event Detection Algorithm for Lower-Limb Prosthesis Users during Level-Ground and Ramp Walking
Authors: Gouda Aliaa , Andrysek Jan
Published: November 2022

Real-time gait event detection (GED) using inertial sensors is important for applications such as remote gait assessments, intelligent assistive devices including microprocessor-based prostheses or exoskeletons, and gait training systems. GED algorithms using acceleration and/or angular velocity signals achieve reasonable performance; however, most are not suited for real-time applications involving clinical populations walking in free-living environments. The aim of this study was to develop and evaluate a real-time rules-based GED algorithm with low latency and high accuracy and sensitivity across different walking states and participant groups. The algorithm was evaluated using gait data collected from seven able-bodied (AB) and seven lower-limb prosthesis user (LLPU) participants for three walking states (level-ground walking (LGW), ramp ascent (RA), ramp descent (RD)). The performance (sensitivity and temporal error) was compared to a validated motion capture system. The overall sensitivity was 98.87% for AB and 97.05% and 93.51% for LLPU intact and prosthetic sides, respectively, across all walking states (LGW, RA, RD). The overall temporal error (in milliseconds) for both FS and FO was 10 (0, 20) for AB and 10 (0, 25) and 10 (0, 20) for the LLPU intact and prosthetic sides, respectively, across all walking states. Finally, the overall error (as a percentage of gait cycle) was 0.96 (0, 1.92) for AB and 0.83 (0, 2.08) and 0.83 (0, 1.66) for the LLPU intact and prosthetic sides, respectively, across all walking states. Compared to other studies and algorithms, the herein-developed algorithm concurrently achieves high sensitivity and low temporal error with near real-time detection of gait in both typical and clinical populations walking over a variety of terrains.
Research on the Derated Power Data Identification Method of a Wind Turbine Based on a Multi-Gaussian–Discrete Joint Probability Model
Authors: Ma Yuanchi , Liu Yongqian , Yang Zhiling , Yan Jie , Tao Tao , Infield David
Published: November 2022

This paper focuses on how to identify normal, derated power and abnormal data in operation data, which is key to intelligent operation and maintenance applications such as wind turbine condition diagnosis and performance evaluation. Existing identification methods can distinguish normal data from the original data, but usually remove power curtailment data as outliers. A multi-Gaussian–discrete probability distribution model was used to characterize the joint probability distribution of wind speed and power from wind turbine SCADA data, taking the derated power of the wind turbine as a hidden random variable. The maximum expectation algorithm (EM), an iterative algorithm derived from model parameters estimation, was applied to achieve the maximum likelihood estimation of the proposed probability model. According to the posterior probability of the wind-power scatter points, the normal, derated power and abnormal data in the wind turbine SCADA data were identified. The validity of the proposed method was verified by three wind turbine operational data sets with different distribution characteristics. The results are that the proposed method has a degree of universality with regard to derated power operational data with different distribution characteristics, and in particular, it is able to identify the operating data with clustered distribution effectively.
Data Collection in IoT Using UAV Based on Multi-Objective Spotted Hyena Optimizer
Authors: Al-Khafaji Hamza Mohammed Ridha
Published: November 2022

Today, the use of information and communication technology is very important in making the internet of things (IoT) elements distributable around the earth. With the development of IoT topics, today unmanned aerial vehicles (UAV) are utilized as a platform for gathering data from various IoT devices located worldwide. Determining the number and optimal locations of drones can minimize energy consumption in this data-collection system in the IoT. Using a promising multi-objective optimization algorithm (MOA) can achieve this goal. In this research, a bio-inspired MOA, termed the multi-objective spotted hyena optimizer (MOSHO), is employed on the data-collection platform for a group of IoT devices in a geographical area. The results of this method have been compared with other evolutionary MOAs. The analysis of the results shows that the MOSHO has a noteworthy consequence on the process of optimal energy consumption in this system, in addition to a high convergence associated with better diversity and robustness. The results of this research can be used to identify the optimization parameters in this system.
Sensor-Based Motion Tracking System Evaluation for RULA in Assembly Task
Authors: Senjaya Wenny Franciska , Yahya Bernardo Nugroho , Lee Seok-Lyong
Published: November 2022

Industries need a mechanism to monitor the workers’ safety and to prevent Work-related Musculoskeletal Disorders (WMSDs). The development of ergonomics assessment tools helps the industry evaluate workplace design and worker posture. Many studies proposed the automated ergonomics assessment method to replace the manual; however, it only focused on calculating body angle and assessing the wrist section manually. This study aims to (a) propose a wrist kinematics measurement based on unobtrusive sensors, (b) detect potential WMSDs related to wrist posture, and (c) compare the wrist posture of subjects while performing assembly tasks to achieve a comprehensive and personalized ergonomic assessment. The wrist posture measurement is combined with the body posture measurement to provide a comprehensive ergonomics assessment based on RULA. Data were collected from subjects who performed the assembly process to evaluate our method. We compared the risk score assessed by the ergonomist and the risk score generated by our method. All body segments achieved more than an 80% similarity score, enhancing the scores for wrist position and wrist twist by 6.8% and 0.3%, respectively. A hypothesis analysis was conducted to evaluate the difference across the subjects. The results indicate that every subject performs tasks differently and has different potential risks regarding wrist posture.
Soybean Seedling Root Segmentation Using Improved U-Net Network
Authors: Xu Xiuying , Qiu Jinkai , Zhang Wei , Zhou Zheng , Kang Ye
Published: November 2022

Soybean seedling root morphology is important to genetic breeding. Root segmentation is a key technique for identifying root morphological characteristics. This paper proposed a semantic segmentation model of soybean seedling root images based on an improved U-Net network to address the problems of the over-segmentation phenomenon, unsmooth root edges and root disconnection, which are easily caused by background interference such as water stains and noise, as well as inconspicuous contrast in soybean seedling images. Soybean seedling root images in the hydroponic environment were collected for annotation and augmentation. A double attention mechanism was introduced in the downsampling process, and an Attention Gate mechanism was added in the skip connection part to enhance the weight of the root region and suppress the interference of background and noise. Then, the model prediction process was visually interpreted using feature maps and class activation mapping maps. The remaining background noise was removed by connected component analysis. The experimental results showed that the Accuracy, Precision, Recall, F1-Score and Intersection over Union of the model were 0.9962, 0.9883, 0.9794, 0.9837 and 0.9683, respectively. The processing time of an individual image was 0.153 s. A segmentation experiment on soybean root images was performed in the soil-culturing environment. The results showed that this proposed model could extract more complete detail information and had strong generalization ability. It can achieve accurate root segmentation in soybean seedlings and provide a theoretical basis and technical support for the quantitative evaluation of the root morphological characteristics in soybean seedlings.
Improving Actuator Wearing Using Noise Filtering
Authors: Domański Paweł D.
Published: November 2022

Actuator, mostly valve, wearing is an important factor of the overall industrial control system operational cost. Actuator operational wear strongly depends on its operation. Highly utilized elements have a tendency to degrade faster. Therefore, the maintenance teams prefer to minimize their moves. In contrary, control engineers need the actuators to actively operate in their control loops to mitigate disturbances and follow the desired trajectories. Higher control performance is often achieved with an active use of actuators. Control loop quality depends on the controller setup and loop auxiliary functionality. Properly designed filtering not only facilitates controller action, but also impacts actuator operational wear. Industrial control templates are built using the blockware that is embedded in the existing control system. Distributed control system (DCS) and programmable logic controller (PLC) have a limited number of control algorithms. An engineer has to design the control structure and the associated sensor noise filtering using available functionality. This paper evaluates and measures the impact of noise filtering on the loop performance and on the actuator weariness. Relations between noise filtering time constant, loop performance and valve travel deliver recommendations for control engineers.
HeriLedger—A New Generation of Blockchains for Cultural Heritage Preservation
Authors: Trček Denis
Published: November 2022

The immense success of Bitcoin has also highlighted the hidden potential of blockchains and distributed ledgers in general. However, most blockchains are based on the so-called Proof-of-Work principle, which requires significant resources, making them unsuitable for the growing number of Internet of Things devices, not to mention other problems such as ensuring privacy and resistance to quantum computing. This paper, therefore, analyses current approaches in the field of ledgers with applications for the Internet of Things. Based on this, it presents a new ledger architecture for cultural heritage preservation that is energy sustainable and tailored to smartphones while pushing the deployment boundaries closer to the rest of the Internet of Things world. It is also resistant to quantum computing and provides privacy with accountability. Moreover, the developed solution considers not only the core technological structure but also its broader social (business) context, i.e., links to the tourism sector. This is performed by incorporating the relevant business model, as business models are important for the successful adoption of new technologies.
4th Order LC-Based Sigma Delta Modulators
Authors: Lima Evelyn Cristina de Oliveira , Soares Antonio Wallace Antunes , Belfort Diomadson Rodrigues
Published: November 2022

Due to the characteristic of narrow band conversion around a central radio frequency, the Sigma Delta Modulator (ΣΔM) based on LC resonators is a suitable option for use in Software-Defined Radio (SDR). However, some aspects of the topologies described in the state-of-the-art, such as noise and nonlinear sources, affect the performance of ΣΔM. This paper presents the design methodology of three high-order LC-Based single-block Sigma Delta Modulators. The method is based on the equivalence between continuous time and discrete time loop gain using a Finite Impulse Response Digital-to-Analog Converter (FIRDAC) through a numerical approach to defining the coefficients. The continuous bandpass LC ΣΔM simulations are performed at a center frequency of 432 MHz and a sampling frequency of 1.72 GHz. To the proposed modulators a maximum Signal-to-Noise Ratio (SNR) of 51.39 dB, 48.48 dB, and 46.50 dB in a 4 MHz bandwidth was achieved to respectively 4th Order Gm-LC ΣΔM, 4th Order Magnetically Coupled ΣΔM and 4th Order Capacitively Coupled ΣΔM.
LiDAR-Only Crop Navigation for Symmetrical Robot
Authors: Guyonneau Rémy , Mercier Franck , Oliveira Freitas Gabriel Freitas
Published: November 2022

This paper presents a navigation approach for autonomous agricultural robots based on LiDAR data. This navigation approach is divided into two parts: a line finding algorithm and a control algorithm. The paper proposes several line finding algorithms (based on PEARL/Ruby approach) that extract lines from a LiDAR data set. Once the lines have been processed from the data set, a control algorithm filters these lines and, using a fuzzy controller, generates the wheel speed commands to move the robot among the crop rows. This navigation approach was tested using a simulator built on ROS middle-ware and Gazebo (the source codes of the simulation are available on GitHub). The results of the simulated experiments show that the proposed approach performs well for a large range of crop configurations (with or without considering weeds, with or without holes in the crop rows…).
Optimal Greedy Control in Reinforcement Learning
Authors: Gorobtsov Alexander , Sychev Oleg , Orlova Yulia , Smirnov Evgeniy , Grigoreva Olga , Bochkin Alexander , Andreeva Marina
Published: November 2022

We consider the problem of dimensionality reduction of state space in the variational approach to the optimal control problem, in particular, in the reinforcement learning method. The control problem is described by differential algebraic equations consisting of nonlinear differential equations and algebraic constraint equations interconnected with Lagrange multipliers. The proposed method is based on changing the Lagrange multipliers of one subset based on the Lagrange multipliers of another subset. We present examples of the application of the proposed method in robotics and vibration isolation in transport vehicles. The method is implemented in FRUND—a multibody system dynamics software package.
Pixel-Guided Association for Multi-Object Tracking
Authors: Boragule Abhijeet , Jang Hyunsung , Ha Namkoo , Jeon Moongu
Published: November 2022

Propagation and association tasks in Multi-Object Tracking (MOT) play a pivotal role in accurately linking the trajectories of moving objects. Recently, modern deep learning models have been addressing these tasks by introducing fragmented solutions for each different problem such as appearance modeling, motion modeling, and object associations. To bring unification in the MOT task, we introduce a pixel-guided approach to efficiently build the joint-detection and tracking framework for multi-object tracking. Specifically, the up-sampled multi-scale features from consecutive frames are queued to detect the object locations by using a transformer–decoder, and per-pixel distributions are utilized to compute the association matrix according to object queries. Additionally, we introduce a long-term appearance association on track features to learn the long-term association of tracks against detections to compute the similarity matrix. Finally, a similarity matrix is jointly integrated with the Byte-Tracker resulting in a state-of-the-art MOT performance. The experiments with the standard MOT15 and MOT17 benchmarks show that our approach achieves significant tracking performance.
A New Intraoral Six-Degrees-of-Freedom Jaw Movement Tracking Method Using Magnetic Fingerprints
Authors: Morikawa Kinta , Isogai Ryosuke , Nonaka Junya , Yoshida Yoshifumi , Haga Shugo , Maki Koutaro
Published: November 2022

We proposed a novel jaw movement tracking method that can measure in six degrees of freedom. The magnetic field generated by a permanent magnet paired with a small, low-power-consumption Hall effect magnetic sensor is used to estimate the relative distance between two objects—in this instance, the lower and upper jaws. By installing a microelectromechanical system (MEMS) orientation sensor in the device, we developed a mouthpiece-type sensing device that can measure voluntary mandibular movements in three-dimensional orientation and position. An evaluation of individuals wearing this device demonstrated its ability to measure mandibular movement with an accuracy of approximately 3 mm. Using the movement recording feature with six degrees of freedom also enabled the evaluation of an individual’s jaw movements over time in three dimensions. In this method, all sensors are built onto the mouthpiece and the sensing is completed in the oral cavity. It does not require the fixation of a large-scale device to the head or of a jig to the teeth, unlike existing mandibular movement tracking devices. These novel features are expected to increase the accessibility of routine measurements of natural jaw movement, unrestricted by an individual’s physiological movement and posture.
A Software and Hardware Cooperation Method for Full Nyquist Rate Transmission Symbol Synchronization at E-Band Wireless Communication
Authors: Wang Fei , Cheng Zhiqun , Li Hang , Zhu Dan
Published: November 2022

Compared with the conventional pulse-shaping transmission system, the full Nyquist rate transmission system with large bandwidth is sensitive to the sampling phase. It has only one sample available in one symbol period and is easily interfered by the channel, which does not allow the traditional symbol synchronization methods to be used directly. Another challenge is that the resource utilization for sampling data processing needs to be minimized due to the excessive consumption of the high data throughput in hardware resources. To solve these issues, we propose a symbol synchronization method based on the combination of software and hardware, which mainly includes two processes: Obtaining the initial phase by using Chirp signal and MOE criterion before communication; tracking the real-time phase using an on-line gradient table and frequency domain analysis of known data during communication. Both processes are proceeded with a phase adjustable clock. Through hardware verification, the sampling phase can be kept close to the optimal phase, thus ensuring the accuracy of the sampling data, and improving the system BER performance.
Near Field Models of Spatially-Fed Planar Arrays and Their Application to Multi-Frequency Direct Layout Optimization for mm-Wave 5G New Radio Indoor Network Coverage
Authors: Prado Daniel R.
Published: November 2022

Two near field models for the analysis of spatially fed planar array antennas are presented, compared and applied to a multi-frequency wideband direct layout optimization for mm-Wave 5G new radio (NR) indoor network coverage. One model is based on the direct application of the radiation equations directly derived from the A and F vector potentials. The second model is based on the superposition of far field contributions of all array elements, which are modelled as rectangular apertures with constant field. Despite the different assumptions made to develop both models, the degree of agreement between them in the computation of the radiated near field is very high. The relative error between the models is equal or lower than 3.2% at a plane 13λ from the array, and it decreases as the near field is computed further away from the array. Then, the faster model is employed in a general direct layout optimization procedure to shape the electromagnetic near field for application in an indoor femtocell to provide coverage with constant power in a private office. Results show that a magnitude ripple better than 1.5 dB can be achieved in an enlarged coverage area covering the whole n257 band of the 5G NR, corresponding to a 10.7% relative bandwidth.
Formulation of the Alpha Sliding Innovation Filter: A Robust Linear Estimation Strategy
Authors: AlShabi Mohammad , Gadsden Stephen Andrew
Published: November 2022

In this paper, a new filter referred to as the alpha sliding innovation filter (ASIF) is presented. The sliding innovation filter (SIF) is a newly developed estimation strategy that uses innovation or measurement error as a switching hyperplane. It is a sub-optimal filter that provides a robust and stable estimate. In this paper, the SIF is reformulated by including a forgetting factor, which significantly improves estimation performance. The proposed ASIF is applied to several systems including a first-order thermometer, a second-order spring-mass-damper, and a third-order electrohydrostatic actuator (EHA) that was built for experimentation. The proposed ASIF provides an improvement in estimation accuracy while maintaining robustness to modeling uncertainties and disturbances.
Energy-Efficient Routing Protocol for Selecting Relay Nodes in Underwater Sensor Networks Based on Fuzzy Analytical Hierarchy Process
Authors: Pabani Jitander Kumar , Luque-Nieto Miguel-Ángel , Hyder Waheeduddin , Ariza Alfonso
Published: November 2022

The use of underwater sensor networks (UWSNs) offers great advantages in many automatic observation services such as water monitoring (ocean, sea, etc.) and registering of geological events (landslides, earthquakes). However, UWSNs have many more limitations than terrestrial sensor networks (smaller bandwidth, higher delays, etc.) with new requirements such as low power consumption by nodes or being able to select appropriate routes in a dynamic topology due to water currents and movements. To cope with these problems, the use of a routing protocol is very important. In this paper we propose a routing technique that adapts to changes in the network topology, avoiding multiple retransmissions that would affect its overall performance. This protocol is energy-efficient and is implemented using a fuzzy analytical hierarchical process (FAHP) under multi-criteria decision making (MCDM) to make an intelligent routing decision based on objectives, criteria and alternatives. To select the next node on the route, several comparison matrices are used: number of hops, distances to the sink node, and number of neighbors. The results show that the proposed setup behaves similarly to other existing underwater sensor network routing schemes using fuzzy schemes such as SPRINT.
The Dynamic Target Motion Perception Mechanism of Tactile-Assisted Vision in MR Environments
Authors: Wang Wei , Xu Ning , Liu Haiping , Qu Jue , Dang Sina , Hong Xuefeng
Published: November 2022

In the mixed reality (MR) environment, the task of target motion perception is usually undertaken by vision. This approach suffers from poor discrimination and high cognitive load when the tasks are complex. This cannot meet the needs of the air traffic control field for rapid capture and precise positioning of the dynamic targets in the air. Based on this problem, we conducted a multimodal optimization study on target motion perception judgment by controlling the hand tactile sensor to achieve the use of tactile sensation to assist vision in MR environment. This allows it to adapt to the requirements of future development-led interactive tasks under the mixed reality holographic aviation tower. Motion perception tasks are usually divided into urgency sensing for multiple targets and precise position tracking for single targets according to the number of targets and task division. Therefore, in this paper, we designed experiments to investigate the correlation between tactile intensity-velocity correspondence and target urgency, and the correlation between the PRS (position, rhythm, sequence) tactile indication scheme and position tracking. We also evaluated it through comprehensive experiment. We obtained the following conclusions: (1) high, higher, medium, lower, and low tactile intensities would bias human visual cognitive induction to fast, faster, medium, slower, and slow motion targets. Additionally, this correspondence can significantly improve the efficiency of the participants’ judgment of target urgency; (2) under the PRS tactile indication scheme, position-based rhythm and sequence cues can improve the judgment effect of human tracking target dynamic position, and the effect of adding rhythm cues is better. However, when adding rhythm and sequence cues at the same time, it can cause clutter; (3) tactile assisted vision has a good improvement effect on the comprehensive perception of dynamic target movement. The above findings are useful for the study of target motion perception in MR environments and provide a theoretical basis for subsequent research on the cognitive mechanism and quantitative of tactile indication in MR environment.
Distress Detection in Subway Tunnel Images via Data Augmentation Based on Selective Image Cropping and Patching
Authors: Maeda Keisuke , Takada Saya , Haruyama Tomoki , Togo Ren , Ogawa Takahiro , Haseyama Miki
Published: November 2022

Distresses, such as cracks, directly reflect the structural integrity of subway tunnels. Therefore, the detection of subway tunnel distress is an essential task in tunnel structure maintenance. This paper presents the performance improvement of deep learning-based distress detection to support the maintenance of subway tunnels through a new data augmentation method, selective image cropping and patching (SICAP). Specifically, we generate effective data for training the distress detection model by focusing on the distressed regions via SICAP. After the data augmentation, we train a distress detection model using the expanded training data. The new image generated based on SICAP does not change the pixel values of the original image. Thus, there is little loss of information, and the generated images are effective in constructing a robust model for various subway tunnel lines. We conducted experiments with some comparative methods. The experimental results show that the detection performance can be improved by our data augmentation.
Compact Eight-Element MIMO Antenna with Reduced Mutual Coupling and Beam-Scanning Performance
Authors: Ahmad Ashfaq , Choi Dong-you
Published: November 2022

In this study, a multiple-input multiple-output (MIMO) antenna for wide scanning is designed. By adding slits to the patches, each element is intended to strengthen the isolation between the radiating elements. The proposed high isolation and wide scanning antenna combine to achieve the desired phased-array antenna. The array has a main beam pointing to the desired scanning region and a minimum side lobe level (SLL) in the undesired direction. A compact and linear eight-element array with an interelement spacing of λ/2 is designed and analyzed for beam scanning in the E-plane. Considering the worst case, the proposed array has a very low mutual coupling of (S21 = −24 dB), and it realizes a gain of 9.3 dBi and an SLL of 11 dB at a scanning angle of 70∘. The antenna performance was studied in terms of the S-parameter, radiation patterns, beam-scanning performance, envelope correlation coefficient (ECC), diversity gain (DG), peak gain, and efficiency. A close agreement was observed between the simulated and measured results.
Elastomeric Core/Conductive Sheath Fibers for Tensile and Torsional Strain Sensors
Authors: Kim Jeeeun , Choi Changsoon
Published: November 2022

Motion sensing, aimed at detecting and monitoring mechanical deformation, has received significant attention in various industrial and research fields. In particular, fiber-structured mechanical strain sensors with carbon-based materials have emerged as promising alternatives for wearable applications owing to their wearability and adaptability to the human body. Various materials, structures, sensing mechanisms, and fabrication methods have been used to fabricate high-performance fiber strain sensors. Nevertheless, developing multi-modal strain sensors that can monitor multiple deformations remains to be accomplished. This study established core/sheath fiber multi-modal strain sensors using polymer and carbon nanotubes (CNTs). Specifically, a flexible and conductive CNT sheet was wrapped onto the elastomeric core fiber at a certain angle. This wrapping angle allowed the CNTs to mechanically deform under tensile and torsional deformations without fatal structural damage. The CNTs could sense both tensile and torsional strains through reversible structural changes during deformations. The fiber strain sensor exhibited an increase of 124.9% and 9.6% in the resistance during tensile and torsional deformations of 100% and 1250 rad/m, respectively.
Fixed-Time Coverage Control of Mobile Robot Networks Considering the Time Cost Metric
Authors: Sun Qihai , Liao Tianjun , Liu Zhi-Wei , Chi Ming , He Dingxin
Published: November 2022

In this work, we studied the area coverage control problem (ACCP) based on the time cost metric of a robot network with an input disturbance in a dynamic environment, which was modeled by a time-varying risk density function. A coverage control method based on the time cost metric was proposed. The area coverage task that considers the time cost consists of two phases: the robot network is driven to cover the task area with a time-optimal effect in the first phase; the second phase is when the accident occurs and the robot is driven to the accident site at maximum speed. Considering that there were movable objects in the task area, a time-varying risk density function was used to describe the risk degree at different locations in the task area. In the presence of the input disturbance, a robust controller was designed to drive each robot, with different maximum control input values, to the position that locally minimized the time cost metric function in a fixed time, and the conditions for maximum control input were obtained. Finally, simulation results and comparison result are presented in this paper.
Development of an HPLC-DAD Method for the Extraction and Quantification of 5-Fluorouracil, Uracil, and 5-Fluorodeoxyuridin Monophosphate in Cells and Culture Media of Lactococcus lactis
Authors: Mavromatis Petros , Stampouli Kyriaki , Vliora Angeliki , Mayilyan Anna , Samanidou Victoria , Touraki Maria
Published: November 2022

The drug 5-fluorouracil (5-FU) is a common cancer chemotherapeutic, presenting toxicity. Mild toxicity is treated with administration of probiotics. The interaction of these probiotics with the drug may have a crucial effect on its therapeutic efficacy. In the present work, a method for the quantification of uracil, 5-FU, and its active metabolite 5-fluorodeoxyuridin monophosphate in cells and culture medium of the probiotic L. lactis is presented. Extraction using H2O containing 0.05% v/v formic acid (1:5 v/v) was followed by ammonium sulphate protein precipitation and SPE. Analysis was conducted in a Nucleosil column using a gradient of water, formic acid, and acetonitrile. Calibration curves were constructed for 5-FU (5–100 μg/mL), uracil (5–20 μg/mL), and 5-fluorodeoxyuridin monophosphate (5–20 μg/mL) using 5-bromouracil as the internal standard (R2 ≥ 0.999). The photodegradation of 5-FU amounted to 36.2% at 96 h. An administration experiment in the dark revealed a decline in 5-FU concentration in the culture media (88.3%) and uptake by the cells, while the uracil and FdUMP levels increased in the cells. The inactive metabolite 5,6 dihydrofluorouracil was detected in the medium. Our results demonstrate that uptake and metabolism of 5-FU in L. lactis cells leads to a decline in the drug levels and in the formation of both the active and the inactive metabolites of the drug.
Establishing and Verifying a Robust Liquid Chromatography-Tandem Mass Spectrometry Method to Simultaneously Measure Seven Androgens Present in Plasma Samples
Authors: Yu Songlin , Zou Yutong , Yin Yicong , Yu Jialei , Li Qianqian , Xie Shaowei , Luo Wei , Ma Xiaoli , Wang Danchen , Qiu Ling
Published: November 2022

Objectives: To develop a robust liquid chromatography-tandem mass spectrometry (LC–MS/MS) method to simultaneously measure seven human plasma androgens, namely testosterone (T), dihydrotestosterone (DHT), androstenedione (A4), dehydroepiandrosterone sulfate (DHEAS), dehydroepiandrosterone (DHEA), 11-ketotestosterone (11-KetoT), and 11β-hydroxytestosterone (11β-OHT). Design and Methods: Plasma was extracted via a solid phase extraction method, and the analytical performance of the assay was validated according to the Clinical & Laboratory Standards Institute guidelines. Overall, 73 apparently healthy volunteers were recruited to evaluate the distribution of these seven androgens; their levels in 25 females with acne and 33 obese females were also evaluated. Results: The developed method exhibited a good precision, with the total coefficient variations (CV) and the intra-assay CVs being within 10%. Furthermore, the recoveries of T, DHT, A4, DHEA, DHEAS, 11-KetoT, and 11β-OHT were 90.3–105.8, 88.7–98.1, 92.4–102.5, 90.5–106.7, 87.6–99.9, 93.3–105.3, and 90.2–104.4%, respectively, and no significant matrix effect was observed after internal standard correction (<20%). Moreover, the limits of quantification were 0.01, 0.01, 0.01, 0.10, 5.00, 0.02, and 0.02 ng/mL for T, DHT, A4, DHEA, DHEAS, 11-KetoT, and 11β-OHT, respectively, which are adequate for their accurate measurement in human plasma samples. It was also determined that patients diagnosed with acne had significantly higher levels of DHT, A4, and DHEAS, while those suffering from obesity had significantly higher levels of T and A4 but lower levels of DHT. Conclusions: A robust LC-MS/MS method for the simultaneous determination of seven androgens in plasma samples was successfully established and validated, which plays important roles in clinical application.