bluuebunny/crossref_metadata_2025 huggingface dataset:
Turned Surface Monitoring Using a Confocal Sensor and the Tool Wear Process Optimization
Authors: Jurko Jozef , Miškiv-Pavlík Martin , Husár Jozef , Michalik Peter
Published: December 2022

Laser scanning technology has been used for several years. Nevertheless, no comprehensive study has been conducted to prove that the application of confocal chromatic sensor (CCHS) laser technology is effective and suitable to verify the integrity parameters of machined surfaces in terms of cutting tool damage. In this paper, the optimization and effects of five factors (cutting speed, feed, depth of cut, attachment length of the workpiece, and tip radius) on the roundness deviation measured by CCHS and, at the same time, on the amount of wear on the back side of the cutting part of the tool were studied according to ISO 3685, which was measured with a microscope. The results obtained were evaluated using the gray relational analysis method (GRA), in conjunction with the Taguchi method, and the significance of the factors was demonstrated using the analysis of variance (ANOVA) method.
A Truthful Mechanism for Multibase Station Resource Allocation in Metaverse Digital Twin Framework
Authors: Zhang Jixian , Zong Mingyi , Li Weidong
Published: December 2022

The concept of the metaverse has gained increasing attention in recent years, and the development of various new technologies, including digital twin technology, has made it possible to see the metaverse coming to pass. Many academics have begun to investigate various problems after realizing the importance of digital twin technology in building the metaverse. However, when utilizing digital twin technology to construct a metaverse, there remains limited research on how to allocate multibase station resources. This research translates a multibase station wireless resource allocation problem into an integer linear programming constraint model when virtual service providers construct a metaverse. In addition, the optimal VCG reverse auction (OPT-VCGRA) mechanism is designed to maximize social welfare and solve the problem of IoT devices competing for base station wireless resources. Specifically, the problem of the optimal allocation of wireless channel resources and payment rule based on the Vickrey–Clarke–Groves mechanism is solved to achieve optimal allocation and calculation of payment prices. Since the optimal allocation problem is NP-hard, this paper also designs a metaverse digital twin resource allocation and pricing (MDTRAP) mechanism based on monotonic allocation and key value theory. The mechanism sends the resource allocation results of multiple base stations to IoT devices and calculates the price payment when building a metaverse in the real world. This paper shows that both auction mechanisms have incentive compatibility and individual rationality properties. Through experiments, this paper compares the two mechanisms in terms of social welfare, the number of winners, and the overall payment. The MDTRAP mechanism performs similarly to the OPT-VCGRA mechanism in terms of social welfare, the number of winners, and channel utilization but is far superior to the OPT-VCGRA mechanism in terms of execution time and total payment. The trustful experiment also verified the truthfulness of the MDTRAP mechanism. The experimental results show that the MDTRAP mechanism can be used to solve the resource allocation problem of multiple base stations to IoT devices when building a metaverse in the real world and can effectively maximize social welfare.
Liver Transplantation from a Human Leukocyte Antigen-Matched Sibling Donor: Effectiveness of Direct-Acting Antiviral Therapy against Hepatitis C Virus Infection
Authors: Kanda Tatsuo , Matsumoto Naoki , Ishii Tomotaka , Arima Shuhei , Shibuya Shinji , Honda Masayuki , Sasaki-Tanaka Reina , Masuzaki Ryota , Kanezawa Shini , Ogawa Masahiro , Yamazaki Shintaro , Aramaki Osamu , Kogure Hirofumi , Okamura Yukiyasu
Published: December 2022

Through living-donor liver transplantation (LDLT) from a human leukocyte antigen (HLA)-matched sibling donor, it may be possible to stop the use of immunosuppressants. It is possible that acute antibody-mediated rejection and chronic active antibody-mediated rejection through the positivity of donor-specific anti-HLA antibodies and/or T cell-mediated rejection may affect the prognosis of liver transplantation. The etiologies of liver diseases of the recipient may also affect the post-transplantation course. Herein, we report on the successful re-treatment with direct-acting antiviral (DAA) therapy against hepatitis C virus (HCV) infection in a patient who underwent a LDLT from HLA-matched sibling donor. After liver transplantation for HCV-related liver diseases, it is easy for HCV to re-infect the graft liver under a lack of immunosuppressants. DAA therapy against HCV re-infection immediately after transplantation should be commenced, and it is important to eradicate HCV for better prognosis of the recipients in LDLT for HCV-related liver diseases.
An Empirical Analysis for the Determination of Risk Factors of Work-Related Accidents in the Maritime Transportation Sector
Authors: Zampeta Vicky , Chondrokoukis Gregory
Published: December 2022

The main objective of this study is to highlight the internal risk factors associated with maritime transportation accidents and the important role of presenting them in the dataset at the time of the incident. Since the study period involves a pre- and post-pandemic timeline, we refer to COVID-19, although it is not part of our analysis. The issue at hand is the appropriate statistical analysis and investigation of the possible correlations between the cause of the incident and internal factors/indicators that may affect the safety of crews on sea routes. We developed a comprehensive study based on advanced econometric modeling, utilizing multifactorial models of robust regression, structural equation modeling (SEM), and Gaussian/mixed-Markov graphical models (GGMs, MGMs) and applying them to a newly compiled dataset covering the 2014–2022 period. Our results bring to the fore important factors that can determine the causes of various accidents and injuries suffered by workers, ranging from work location to work activity and even the rank of the seafarers on board. We do not consider the external factors associated with a maritime transportation accident, as the risk of an accident in this sector due to external factors (i.e., weather conditions, defaults, failures, etc.) is limited. Reducing the number of injuries to seafarers will result not only in better seafarer health but also a reduction in the operating costs of shipping companies due to the reduced insurance premiums they will have to pay. It will also lead to a reduction in the amounts disbursed by Protection and Indemnity (P&I) Clubs to compensate seafarers. In future research, we will use external factors to determine seafaring risks related to, for example, weather conditions, the quality of ships, technology, safety measures, regulations, and more.
A Comprehensive Review of Vision-Based Robotic Applications: Current State, Components, Approaches, Barriers, and Potential Solutions
Authors: Shahria Md Tanzil , Sunny Md Samiul Haque , Zarif Md Ishrak Islam , Ghommam Jawhar , Ahamed Sheikh Iqbal , Rahman Mohammad H
Published: December 2022

Being an emerging technology, robotic manipulation has encountered tremendous advancements due to technological developments starting from using sensors to artificial intelligence. Over the decades, robotic manipulation has advanced in terms of the versatility and flexibility of mobile robot platforms. Thus, robots are now capable of interacting with the world around them. To interact with the real world, robots require various sensory inputs from their surroundings, and the use of vision is rapidly increasing nowadays, as vision is unquestionably a rich source of information for a robotic system. In recent years, robotic manipulators have made significant progress towards achieving human-like abilities. There is still a large gap between human and robot dexterity, especially when it comes to executing complex and long-lasting manipulations. This paper comprehensively investigates the state-of-the-art development of vision-based robotic application, which includes the current state, components, and approaches used along with the algorithms with respect to the control and application of robots. Furthermore, a comprehensive analysis of those vision-based applied algorithms, their effectiveness, and their complexity has been enlightened here. To conclude, there is a discussion over the constraints while performing the research and potential solutions to develop a robust and accurate vision-based robot manipulation.
Three-Dimensional Printing of Cylindrical Nozzle Elements of Bernoulli Gripping Devices for Industrial Robots
Authors: Mykhailyshyn Roman , Duchoň František , Mykhailyshyn Mykhailo , Majewicz Fey Ann
Published: December 2022

The application of additive technologies, namely, fused deposition modeling, is a new reality for prototyping gripping devices of industrial robots. However, during 3D printing of holes and nozzle elements, difficulties arise with reducing their diameter. Therefore, this article conducts a comprehensive study of the Bernoulli gripping device prototype with a cylindrical nozzle, manufactured by fused deposition modeling 3D printing. The three main reasons for reducing the diameter of the gripper nozzle after printing were due to the poor-quality model, excessive extrusion of plastic in the middle of the arc printing path, and linear shrinkage of printing material after cooling. The proposed methodology consisted of determining the three coefficients that allowed the determination of the diameter of the designed nozzle. The use of air pressure distributions on the surface of the manipulation object, and lifting forces of gripping devices with different 3D printing layer heights were found. It was experimentally determined that as the height of the printing layer increased, the lifting force decreased. This was due to the formation of swirls due to the increased roughness of the grip surface. It was proven that as the height between the manipulation object and the grip increased, the effect of surface roughness on the lifting force decreased, resulting in an increase in the lifting force. Determination of the rational operating parameters of gripping devices manufactured by 3D printing from the point of view of maximum lifting force, were determined.
Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S.
Authors: Ye Xinxin , Deshler Mina , Lyapustin Alexi , Wang Yujie , Kondragunta Shobha , Saide Pablo
Published: December 2022

Satellite remote sensing of aerosol optical depth (AOD) is essential for detection, characterization, and forecasting of wildfire smoke. In this work, we evaluate the AOD (550 nm) retrievals during the extreme wildfire events over the western U.S. in September 2020. Three products are analyzed, including the Moderate-resolution Imaging Spectroradiometers (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) product collections C6.0 and C6.1, and the NOAA-20 Visible Infrared Imaging Radiometer (VIIRS) AOD from the NOAA Enterprise Processing System (EPS) algorithm. Compared with the Aerosol Robotic Network (AERONET) data, all three products show strong linear correlations with MAIAC C6.1 and VIIRS presenting overall low bias (<0.06). The accuracy of MAIAC C6.1 is found to be substantially improved with respect to MAIAC C6.0 that drastically underestimated AOD over thick smoke, which validates the effectiveness of updates made in MAIAC C6.1 in terms of an improved representation of smoke aerosol optical properties. VIIRS AOD exhibits comparable uncertainty with MAIAC C6.1 with a slight tendency of increased positive bias over the AERONET AOD range of 0.5–3.0. Averaging coincident retrievals from MAIAC C6.1 and VIIRS provides a lower root mean square error and higher correlation than for the individual products, motivating the benefit of blending these datasets. MAIAC C6.1 and VIIRS are further compared to provide insights on their retrieval strategy. When gridded at 0.1° resolution, MAIAC C6.1 and VIIRS provide similar monthly AOD distribution patterns and the latter exhibits a slightly higher domain average. On daily scale, over thick plumes near fire sources, MAIAC C6.1 reports more valid retrievals where VIIRS tends to have retrievals designated as low or medium quality, which tends to be due to internal quality checks. Over transported smoke near scattered clouds, VIIRS provides better retrieval coverage than MAIAC C6.1 owing to its higher spatial resolution, pixel-level processing, and less strict cloud masking. These results can be used as a guide for applications of satellite AOD retrievals during wildfire events and provide insights on future improvement of retrieval algorithms under heavy smoke conditions.
Assessing Elevation-Based Forest Dynamics over Space and Time toward REDD+ MRV in Upland Myanmar
Authors: Lu Siqi , Zhang Chuanrong , Dong Jinwei , Adil Muhammad , Lu Heli
Published: December 2022

Implementation of a measuring, reporting, and verifying (MRV) framework is essential for reducing emissions from deforestation and forest degradation (REDD+). According to the United Nations Framework Convention on Climate Change, MRV can be regarded as an important mechanism to mitigate global warming. Upland Myanmar, with an elevation of ~80–2600 m, is experiencing tropical deforestation, which is commonly explained by the expansion of shifting cultivation. The vegetation change tracker algorithm, with its high-automation and wild-adaptation features, and the enhanced integrated forest z-score were applied in this elevation-based study of time series deforestation monitoring in upland Myanmar using data from 2003 to 2015. Four spatial patterns of deforestation, namely stripes, adjacent, filled, and staggered, were found in the research area. Moreover, our work showed that the center of elevation of deforestation was ~1000 m. Further analysis revealed that this center tended to shift to a higher elevation over time; a “golden cross”/changeover could be deciphered at ~1000 m, indicating that the scale and intensity of shifting cultivation continue to expand vertically. The results suggest the need to track the elevation-based signature of vegetation clearings to help achieve the goals of REDD+ at the regional level in tropical rainforest countries.
Studies and Analysis of Combining BDS-3/GNSS Ultra-Rapid Orbit Products from Different IGS Analysis Centers
Authors: Hou Yangfei , Wang Hu , Wang Jiexian , Ma Hongyang , Ren Yingying , Li Pengyuan , Wang Yafeng
Published: December 2022

The third generation of China’s BeiDou Navigation Satellite System (BDS-3) began to provide global service at the end of 2018, and the completion of BDS was announced in July 2020, which includes GEO (Geostationary Earth Orbit), IGSO (Inclined Geosynchronous orbit), and MEO (Medium Earth Orbit) satellites. The resulting BDS orbits vary due to the inconsistent alignment strategies used by different analysis centers. Therefore, it is necessary to study the method of determining the BDS-3 orbit products combined from different analysis centers. In this research, the accuracy of the combined orbits for BDS-3 and other GNSS systems is evaluated and analyzed. To verify the reliability of the orbit combination method proposed in this paper, the GPS orbit is first selected for verification. Compared to the analysis centers, the mean Signal in Space User Ranging Error (SISURE) for GPS combined orbits is significantly reduced, and the mean SISURE of combined orbits for Block IIF, Block IIR, and Block III is 4.15 mm, 5.43 mm, and 5.63 mm, respectively. This demonstrates the effectiveness of the orbit combination method in this research. Besides, the accuracy of the combined orbits is improved by the ERP correction, and the mean RMS of the without Earth rotation Parameters (ERP) correction orbits and with ERP correction orbits is 4.78 mm and 4.53 mm, respectively. This demonstrates that orbit consistency corrections should be considered when performing orbit combinations. Compared to the GFZ orbits, the accuracy of the combined orbits has improved for GPS, GLONASS, GALILEO, and BDS is 8.2%, 9.9%, 9.9%, and 5.5%, respectively. It shows that the orbit combination method improves the orbital accuracy compared to the individual analysis center orbits. The mean RMS of the combined orbits for GPS, GLONASS, GALILEO, BDS MEO, and BDS IGSO is 1.7 cm, 2.61 cm, 2.52 cm, 2.59 cm, and 4.90 cm, respectively. The results demonstrate that the accuracy of the combined orbit for the BDS-3 MEO satellite is already similar to other systems; an orbit combination also available for the BDS-3 satellite.
Integrating Spatial Heterogeneity to Identify the Urban Fringe Area Based on NPP/VIIRS Nighttime Light Data and Dual Spatial Clustering
Authors: Zhu Jie , Lang Ziqi , Yang Jing , Wang Meihui , Zheng Jiazhu , Na Jiaming
Published: December 2022

The precise recognition of urban fringes is vital to monitor urban sprawl and map urban management planning. The spatial clustering method is a prevalent way to identify urban fringes due to its objectivity and convenience. However, previous studies had problems with ignoring spatial heterogeneity, which could overestimate or underestimate the recognition results. Nighttime light can reflect the transitional urban–rural regions’ regional spatial characteristics and can be used to identify urban fringes. Accordingly, a new model has been established for urban fringe identification by combining spatial continuous wavelet transform (SCWT) and dual spatial clustering. Then, Nanjing City, China, as a case study, is employed to validate the model through the NPP/VIIRS nighttime light data. The identification of mutated points across the urban–rural gradient is conducted by utilizing the SCWT. By using dual spatial clustering in the urban fringe identification, it transmits the mutation points’ spatial patterns to the homogeneous spatially neighboring clusters effectively, which measures the similarity between mutation points regarding spatial and attribute domains. A comparison of the identified results by various spatial clustering approaches revealed that our method could be more suitable for the impacts of mutation points’ local spatial patterns on different density values over the whole density surface, thus leading to more accurate spatial boundaries featured by differentiating actual differences of mutation points between adjacent clusters.
Aerosol Optical Properties above Productive Waters of Gorky Reservoir for Atmospheric Correction of Sentinel-3/OLCI Images
Authors: Fedorov Sergei , Molkov Aleksandr , Kalinskaya Daria
Published: December 2022

The main challenge that one has to face during the atmospheric correction (AC) of productive inland waters is the inability to correctly separate aerosol radiance from water-leaving radiance in the near-infrared range (NIR) bands. This leads both to incorrect estimates of the aerosol parameters and the remote-sensing reflectance (Rrs). For the Gorky Reservoir, where we are developing regional bio-optical models, the situation is complicated by the lack of field measurements of aerosol optical properties due to the significant remoteness of AERONET stations. The standard AC algorithms, as shown earlier, greatly overestimated the aerosol radiance in all spectral bands up to red bands during the period of intense cyanobacteria blooms, while the algorithm with a fixed aerosol optical depth (AOD) obtained in a clean water area gave encouraging results. Therefore, it was important to investigate the characteristics of the atmosphere above the reservoir and validate the proposed approach for regular use of Sentinel-3 imagery of the Gorky Reservoir. To solve these issues, regular in situ aerosol measurements using the handheld sun photometer SPM were performed. The measured AOD and the Angstrom exponent were compared with the estimates of these parameters from two Sentinel-3/OLCI Level-2 products, namely, Synergy (SYN) and Water Full Resolution products (OL_2_WFR). It was found that AOD and the Angstrom exponent from these standard products were overestimated by 2–3 times and almost 2 times in all cases. Atmospheric correction with fixed AOD, defined by measurements, allows us to completely get rid of negative Rrs, and its shapes and values became typical for the Gorky Reservoir. Despite the overestimation of AOD in traditional AC and its large variations in general, it was found that the minimum AOD spectrum is close to the measured spectrum. Therefore, the AOD spectra, which correspond to the two percentiles of the distribution, can be used for preliminary AC with a fixed AOD of the Sentinel-3/OLCI imaginary. The relative errors of the Rrs retrievals using the two percentile AOD compared to the measured AOD were 3–35% in the green and red bands of Sentinel-3/OLCI.
Linearized Single-Scattering Property Database for Hexagonal Prism Ice Particles
Authors: Gao Chenxu , Liang Dongbin , Sun Bingqiang , Liu Jian , Liu Zhaoyuan
Published: December 2022

Accurate description of the single scattering properties of atmospheric particles can be an essential factor influencing the remote sensing of atmospheric microphysics. In this paper, a database for the linearized single scattering properties of ice particles was developed in the visible to infrared spectral region of 0.4–15 μm and for size parameters ranging from 0.5 to 500. The linearized invariant imbedding T-matrix method and linearized physical-geometric optics method were jointly applied. A full set of integral scattering properties including extinction efficiency, single scattering albedo, asymmetry factors, and differential scattering properties, including six phase matrix elements, were the basic scattering parameters in the database. Furthermore, the Jacobians of these regular scattering properties with respect to refractive index (real and imaginary parts) and effective radius were also included and used for sensitivity determinations. The spectral and size-dependent variations and changing rates of the derivative characteristics with actual application values, such as backscattering depolarization ratios, were also discussed.
Reconstruction of High-Resolution Sea Surface Salinity over 2003–2020 in the South China Sea Using the Machine Learning Algorithm LightGBM Model
Authors: Wang Zhixuan , Wang Guizhi , Guo Xianghui , Hu Jianyu , Dai Minhan
Published: December 2022

Salinity, as one of the essential physical properties of seawater, is a common tracer differentiating water masses in the ocean, which often require relatively high-resolution datasets. Limited by the coverage of direct observations, however, high-resolution spatial and temporal salinity data are not always available, which hinders the fine application of salinity data in discerning ocean processes and improved modeling of ocean physics and biogeochemistry. To supplement the salinity database, we reconstructed sea surface salinity (SSS) with reasonably high spatial resolution (0.05° × 0.05°) over 2003–2020 in the South China Sea (SCS) with a machine learning algorithm based on a combination of MODIS-Aqua remote sensing data and a large cruise observation-based dataset. The reconstructed SSS has a mean absolute error (MAE) of 0.2 when compared with our underway observations with a corresponding root mean square error (RMSE) of 0.3. The MAE between station-based observations and our reconstruction was 0.5, and the RMSE was 0.7. These validations strongly suggest that our reconstruction is highly adequate, representing at most a quarter of the identified discrepancies compared to the remote sensing SSS or two other prevalent model-derived datasets. Based on our reconstruction, the SSS in the SCS is relatively low in coastal waters, but high in the ocean basin, with a seasonal pattern with a minimum in the summer and a maximum in the winter. This spatio-temporal distribution is well consistent with the observations and is affected by the Pearl River plume, sea surface circulation, and precipitation. Using our reconstructed SSS, we were able to successfully characterize the spreading of the Pearl River and Mekong River plumes and the intrusion of the Kuroshio Current from the Pacific Ocean into the SCS.
A Study of Autonomous Small Satellite Constellations for Disaster Management and Deep Space Strategy
Authors: Rashed Mohammed Irfan , Bang Hyochoong
Published: December 2022

The complex and dynamic space environment is both exciting and challenging in this NewSpace era. In particular, Low-Earth Orbits are being realigned and reinvented for various purposes using suitable technological advancement. This paper is focused on the major parameters that can be analyzed to attain orbit control and autonomy of small-satellite constellations for real-time applications. By applying industry experience to graduate research, this work addresses the related concerns in a realistic manner. Currently, global small-satellite constellation solutions are too expensive and inaccessible for many nations to help in their data reception requirements. This issue was addressed, and some of the main aspects relating to low-cost and high-benefit technical synthesis, in addition to utilization for deep-space missions, were also discussed in detail. In conclusion, this paper demonstrated a strategic approach to optimize the coverage and performance, and reduce the cost of small-satellite constellations, compared with present day constellations, allowing the data to be relayed faster and with precision. This will benefit the industry in the development of low-cost constellations, and effectively assist in disaster management and deep-space communication relays. Autonomous orbit selection and navigation can be established for better path alignment for satellites to efficiently propagate and deliver the required data.
Seismo-Lineaments in Egypt: Analysis and Implications for Active Tectonic Structures and Earthquake Magnitudes
Authors: Moustafa Sayed S. R. , Abdalzaher Mohamed S. , Abdelhafiez H. E.
Published: December 2022

Quiescent faults may be capable of creating catastrophic earthquakes in locations with moderate and/or low seismic activity, such as Egypt. This study combines structural, remote sensing (RS), geophysical, and seismic activity data to examine and analyze the relationship between tectonic structures and seismotectonic activity in Egypt. In a new seismo-lineaments map of Egypt, tectonic lineaments of the Egyptian mainland were delineated and classified. The database contains 8000 lineaments that were divided into distinct geographical zones using statistical analysis and general features. Delineated lineaments were integrated with digitized geological and geophysical surface and subsurface faults and geographic information systems (GIS) processing techniques were applied to produce 4249 faults. The spatial distribution of seismic activity was determined to extract 1968 competent faults out of 4249 capable faults (i.e., greater than 10 km and suitably orientated concerning the existing stress field). Maximum expected magnitudes (Mmax) were calculated for distinct seismogenic locations in Egypt, taking into account the nature of the regional rupture. At the national scale, empirical scaling relations between fault lengths and earthquake magnitude were employed for all mapped faults in Egypt. The findings concerning the faults were highly consistent with traditional geological information. The results suggest that our technique for estimating the highest predicted magnitudes produces similar values and might be used to evaluate Egypt’s possible future seismic hazard. The results were compared to seismic databases. The similarity of our results with those reported in the catalogs lends confidence to the proposed scheme.
Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural Systems
Authors: Park Seonyoung , Lee Jaese , Yeom Jongmin , Seo Eunkyo , Im Jungho
Published: December 2022

Drought affects a region’s economy intensively and its severity is based on the level of infrastructure present in the affected region. Therefore, it is important not only to reflect on the conventional environmental properties of drought, but also on the infrastructure of the target region for adequate assessment and mitigation. Various drought indices are available to interpret the distinctive meteorological, agricultural, and hydrological characteristics of droughts. However, these drought indices do not consider the effective assessment of damage of drought impact. In this study, we evaluated the applicability of satellite-based drought indices over North Korea and South Korea, which have substantially different agricultural infrastructure systems to understand their characteristics. We compared satellite-based drought indices to in situ-based drought indices, standardized precipitation index (SPI), and rice yield over the Korean Peninsula. Moderate resolution imaging spectroradiometer (MODIS), tropical rainfall measuring mission (TRMM), and global land data assimilation system (GLDAS) data from 2001 to 2018 were used to calculate drought indices. The correlations of the indices in terms of monitoring meteorological and agricultural droughts in rice showed opposite correlation patterns between the two countries. The difference in the prevailing agricultural systems including irrigation resulted in different impacts of drought. Vegetation condition index (VCI) and evaporative stress index (ESI) are best suited to assess agricultural drought under well-irrigated regions as in South Korea. In contrast, most of the drought indices except for temperature condition index (TCI) are suitable for regions with poor agricultural infrastructure as in North Korea.
Recent Advances in Modelling Geodetic Time Series and Applications for Earth Science and Environmental Monitoring
Authors: He Xiaoxing , Montillet Jean-Philippe , Li Zhao , Kermarrec Gaël , Fernandes Rui , Zhou Feng
Published: December 2022

Geodesy is the science of accurately measuring the topography of the earth (geometric shape and size), its orientation in space, and its gravity field. With the advances in our knowledge and technology, this scientific field has extended to the understanding of geodynamical phenomena such as crustal motion, tides, and polar motion. This Special Issue is dedicated to the recent advances in modelling geodetic time series recorded using various instruments. Due to the stochastic noise properties inherent in each of the time series, careful modelling is necessary in order to extract accurate geophysical information with realistic associated uncertainties (statistically sufficient). The analyzed data have been recorded with various space missions or ground-based instruments. It is impossible to be comprehensive in the vast and dynamic field that is Geodesy, particularly so-called “Environmental Geodesy”, which intends to understand the Earth’s geodynamics by monitoring any changes in our environment. This field has gained much attention in the past two decades due to the need by the international community to understand how climate change modifies our environment. Therefore, this Special Issue collects some articles which emphasize the recent development of specific algorithms or methodologies to study particular natural phenomena related to the geodynamics of the earth’s crust and climate change.
A QoS-Adaptive Interference Alignment Technique for In-Band Full-Duplex Multi-Antenna Cellular Networks
Authors: Lee Ki-Hun , Park Gyudong , Jung Bang Chul
Published: December 2022

In this paper, we propose a novel interference alignment (IA) technique for an in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) cellular network where a base station (BS) and user equipment (UE) are equipped with multiple antennas, and the local channel state information (CSI) is available at all nodes. Considering a practical IBFD MIMO cellular network, it is assumed that only the BS operates with full-duplex (FD) communication while UE operate in half-duplex (HD) mode. These IBFD networks introduce a new type of interference called cross-link interference (CLI), in which uplink UE affects downlink UE. The proposed IA technique consists of two symmetric IA schemes according to the number of antennas in the uplink and downlink UE, and both schemes effectively mitigate CLI in the IBFD MIMO network. It is worth noting that both IA schemes are adaptively applicable according to the network’s quality-of-service (QoS) requirements, such as uplink and downlink traffic demands. Furthermore, we theoretically characterize and prove the achievable sum-degrees-of-freedom (DoF) of the proposed IA technique. Simulation results show that the proposed IA technique significantly improves the sum rate performance compared to conventional HD communications (multi-user MIMO) while achieving the same achievable DoF as the interference-free IBFD MIMO network.
Prediction of IGS RTS Orbit Correction Using LSTM Network at the Time of IOD Change
Authors: Kim Beomsoo , Kim Jeongrae
Published: December 2022

The international GNSS service (IGS) real-time service (RTS) provides orbit and clock corrections for the global navigation satellite system (GNSS) via the internet. RTS is widely used for real-time, precise positioning and its data is transmitted via the internet. Intermittent data loss can occur and cause positioning accuracy degradation. RTS data has a discontinuity when the issue of data (IOD) changes every two hours. If the signal loss occurs immediately after the IOD change, then the performance of the RTS prediction degrades significantly. We propose an adjustment method to make the RTS data across the IOD change, which makes it possible to use long RTS data for building a prediction model. The proposed adjustment method is combined with a long-short-term memory (LSTM) network to improve long-period prediction accuracy. Experiments with GPS and RTS were performed to evaluate the RTS orbit prediction accuracy. The LSTM with the IOD adjustment outperforms other polynomial prediction methods, and the positioning accuracy with the predicted RTS orbit correction shows a significant improvement.
Physical Simulation of Ultrasonic Imaging Logging Response
Authors: Lu Junqiang , Han Jiyong , Wu Jinping , Che Xiaohua , Qiao Wenxiao , Wang Jiale , Chen Xu
Published: December 2022

Ultrasonic imaging logging can visually identify the location, shape, dip angle and orientation of fractures and holes. The method has not been effectively applied in the field; one of the prime reasons is that the results of physical simulation experiments are insufficient. The physical simulation of fracture and hole response in the laboratory can provide a reference for the identification and evaluation of the underground geological structure. In this work, ultrasonic scanning experiments are conducted on a grooved sandstone plate and a simulated borehole and the influence of different fractures and holes on ultrasonic pulse echo is studied. Experimental results show that the combination of ultrasonic echo amplitude imaging and arrival time imaging can be used to identify the fracture location, width, depth and orientation, along with accurately calculating the fracture dip angle. The evaluated fracture parameters are similar to those in the physical simulation model. The identification accuracy of the ultrasonic measurement is related to the diameter of the radiation beam of the ultrasonic transducer. A single fracture with width larger than or equal to the radiation beam diameter of the ultrasonic transducer and multiple fractures with spacing longer than or equal to the radiation beam diameter can be effectively identified.
The Validity and Reliability of a New Intelligent Three-Dimensional Gait Analysis System in Healthy Subjects and Patients with Post-Stroke
Authors: Wang Yingpeng , Tang Ran , Wang Hujun , Yu Xin , Li Yingqi , Wang Congxiao , Wang Luyi , Qie Shuyan
Published: December 2022

Odonate is a new, intelligent three-dimensional gait analysis system based on binocular depth cameras and neural networks, but its accuracy has not been validated. Twenty-six healthy subjects and sixteen patients with post-stroke were recruited to investigate the validity and reliability of Odonate for gait analysis and examine its ability to discriminate abnormal gait patterns. The repeatability tests of different raters and different days showed great consistency. Compared with the results measured by Vicon, gait velocity, cadence, step length, cycle time, and sagittal hip and knee joint angles measured by Odonate showed high consistency, while the consistency of the gait phase division and the sagittal ankle joint angle was slightly lower. In addition, the stages with statistical differences between healthy subjects and patients during a gait cycle measured by the two systems were consistent. In conclusion, Odonate has excellent inter/intra-rater reliability, and has strong validity in measuring some spatiotemporal parameters and the sagittal joint angles, except the gait phase division and the ankle joint angle. Odonate is comparable to Vicon in its ability to identify abnormal gait patterns in patients with post-stroke. Therefore, Odonate has the potential to provide accessible and objective measurements for clinical gait assessment.
Graphene-Enhanced Polydimethylsiloxane Patch for Wearable Body Temperature Remote Monitoring Application
Authors: Huang Jie , Huang Daqing
Published: December 2022

In this work, we designed and implemented a wearable body temperature monitoring device, which was constructed by a graphene-enhanced polydimethylsiloxane patch and a temperature measurement chip. The body temperature patch adopts a completely flexible solution in combination with near field communication component, which provides the advantages of passive wireless, overall flexibility, and being comfortable to wear. The whole device can be bent and stretched in conformal contact with skin. In order to improve the temperature conduction ability of the patch and make the patch data more accurate, we adopted graphene nanoplates to improve the thermal conductivity of polydimethylsiloxane patch with a significant thermal conductivity increase of 23.8%. With the combination of hollow sandwich structure and small dimension. it will reduce the uncomfortable situation of wearing the device for extended periods and can be served to monitor the human body temperature for a long time. Ultimately, this device is combined with a reading software for analyzing and processing on a smart mobile terminal. The real-time and past temperature range can be a pre-warning; meanwhile, the historical data can be traced and analyzed. Therefore, this device can be utilized in multiple human body temperature measurement scenarios and complex public health situations.
Anomaly Detection Based on Time Series Data of Hydraulic Accumulator
Authors: Park Min-Ho , Chakraborty Sabyasachi , Vuong Quang Dao , Noh Dong-Hyeon , Lee Ji-Woong , Lee Jae-Ung , Choi Jae-Hyuk , Lee Won-Ju
Published: December 2022

Although hydraulic accumulators play a vital role in the hydraulic system, they face the challenges of being broken by continuous abnormal pulsating pressure which occurs due to the malfunction of hydraulic systems. Hence, this study develops anomaly detection algorithms to detect abnormalities of pulsating pressure for hydraulic accumulators. A digital pressure sensor was installed in a hydraulic accumulator to acquire the pulsating pressure data. Six anomaly detection algorithms were developed based on the acquired data. A threshold averaging algorithm over a period based on the averaged maximum/minimum thresholds detected anomalies 2.5 h before the hydraulic accumulator failure. In the support vector machine (SVM) and XGBoost model that distinguish normal and abnormal pulsating pressure data, the SVM model had an accuracy of 0.8571 on the test set and the XGBoost model had an accuracy of 0.8857. In a convolutional neural network (CNN) and CNN autoencoder model trained with normal and abnormal pulsating pressure images, the CNN model had an accuracy of 0.9714, and the CNN autoencoder model correctly detected the 8 abnormal images out of 11 abnormal images. The long short-term memory (LSTM) autoencoder model detected 36 abnormal data points in the test set.
Sensing Method Using Dielectric Loss Factor to Evaluate Surface Conditions on Polluted Porcelain Insulator
Authors: Šárpataky Ľuboš , Dolník Bystrík , Zbojovský Ján , Schichler Uwe , Pischler Oliver , Schober Bernhard
Published: December 2022

Insulator diagnostics is still a topical issue. No one has yet found out how to accurately determine the condition of all insulators and decide when replacement or maintenance is required. Insulators are one of the main components of a transmission and distribution system and must withstand high voltages in all weather conditions. Moisture and dirt are the main factors influencing the insulating properties of insulators. This article deals with the effect of pollution on a porcelain insulator. An Omicron MI 600 measuring system monitors the changes in the dielectric loss factor and leakage current in a wide frequency range (10 Hz to 1 kHz) to evaluate the contamination level. We applied three high voltage levels (5 kV, 7.5 kV, and 10 kV) to the porcelain insulator to monitor changes in the mentioned quantities with various frequencies. The measurement results confirmed the usability of the dielectric loss factor and leakage current for the diagnosis of insulator pollution. The dielectric loss factor showed more promising results than the leakage current.
Manufacture of Three-Dimensional Optofluidic Spot-Size Converters in Fused Silica Using Hybrid Laser Microfabrication
Authors: Yu Jianping , Xu Jian , Zhang Aodong , Song Yunpeng , Qi Jia , Dong Qiaonan , Chen Jianfang , Liu Zhaoxiang , Chen Wei , Cheng Ya
Published: December 2022

We propose a hybrid laser microfabrication approach for the manufacture of three-dimensional (3D) optofluidic spot-size converters in fused silica glass by a combination of femtosecond (fs) laser microfabrication and carbon dioxide laser irradiation. Spatially shaped fs laser-assisted chemical etching was first performed to form 3D hollow microchannels in glass, which were composed of embedded straight channels, tapered channels, and vertical channels connected to the glass surface. Then, carbon dioxide laser-induced thermal reflow was carried out for the internal polishing of the whole microchannels and sealing parts of the vertical channels. Finally, 3D optofluidic spot-size converters (SSC) were formed by filling a liquid-core waveguide solution into laser-polished microchannels. With a fabricated SSC structure, the mode spot size of the optofluidic waveguide was expanded from ~8 μm to ~23 μm with a conversion efficiency of ~84.1%. Further measurement of the waveguide-to-waveguide coupling devices in the glass showed that the total insertion loss of two symmetric SSC structures through two ~50 μm-diameter coupling ports was ~6.73 dB at 1310 nm, which was only about half that of non-SSC structures with diameters of ~9 μm at the same coupling distance. The proposed approach holds great potential for developing novel 3D fluid-based photonic devices for mode conversion, optical manipulation, and lab-on-a-chip sensing.
Multi-Target PIR Indoor Localization and Tracking System with Artificial Intelligence
Authors: Chen Xuan-Ying , Wen Chih-Yu , Sethares William A.
Published: December 2022

Pyroelectric infrared (PIR) sensors are low-cost, low-power, and highly reliable sensors that have been widely used in smart environments. Indoor localization systems may be wearable or non-wearable, where the latter are also known as device-free localization systems. Since binary PIR sensors detect only the presence of a subject’s motion in their field of view (FOV) without other information about the actual location, information from overlapping FOVs of multiple sensors can be useful for localization. This study introduces the PIRILS (pyroelectric infrared indoor localization system), in which the sensing signal processing algorithms are augmented by deep learning algorithms that are designed based on the operational characteristics of the PIR sensor. Expanding to the detection of multiple targets, the PIRILS develops a quantized scheme that exploits the behavior of an artificial neural network (ANN) model to demonstrate localization performance in tracking multiple targets. To further improve the localization performance, the PIRILS incorporates a data augmentation strategy that enhances the training data diversity of the target’s motion. Experimental results indicate system stability, improved positioning accuracy, and expanded applicability, thus providing an improved indoor multi-target localization framework.
High Spectral Sensitivity of Strongly Coupled Hybrid Tamm-Plasmonic Resonances for Biosensing Application
Authors: Anulytė Justina , Bužavaitė-Vertelienė Ernesta , Stankevičius Evaldas , Vilkevičius Kernius , Balevičius Zigmas
Published: December 2022

In this study, the sensitivity to the refractive index changes of the ambient was studied on the uniform gold film (~50 nm) with a 1D photonic crystal (PC) from periodic five TiO2 (~110 nm)/SiO2 (~200 nm) bilayers and gold nano-bumps array produced by direct laser writing on the same sample. The optical signal sensitivity of hybrid plasmonic resonances was compared with traditional surface plasmon resonance (SPR) on a single gold layer. The influence of the strong coupling regime between Tamm plasmon polariton (TPP) and propagated plasmon polaritons in the hybrid plasmonic modes on the sensitivity of the optical was discussed. Recent studies have shown very high hybrid plasmonic mode sensitivity SHSPP ≈ 26,000 nm/RIU to the refractive index on the uniform gold layer; meanwhile, the introduction of gold lattice reduces the signal sensitivity, but increases the Q-factor of the plasmonic resonances. Despite this, the sensitivity to the ellipsometric parameters Ψ and Δ on the gold lattice was rather high due to the increased Q-factor of the resonances. The comparison of plasmonic resonance sensitivity to the refractive index changes of hybrid TPP-SPP mode on the uniform gold layer and traditional SPR have shown that hybrid plasmonic mode, due to a strong coupling effect, overcomes the SPR by about 27%.
Data Freshness and End-to-End Delay in Cross-Layer Two-Tier Linear IoT Networks
Authors: Cheikh Imane , Sabir Essaid , Aouami Rachid , Roy Sébastien , Sadik Mohamed
Published: December 2022

The operational and technological structures of radio access networks have undergone tremendous changes in recent years. A displacement of priority from capacity–coverage optimization (to ensure data freshness) has emerged. Multiple radio access technology (multi-RAT) is a solution that addresses the exponential growth of traffic demands, providing degrees of freedom in meeting various performance goals, including energy efficiencies in IoT networks. The purpose of the present study was to investigate the possibility of leveraging multi-RAT to reduce each user’s transmission delay while preserving the requisite quality of service (QoS) and maintaining the freshness of the received information via the age of information (AoI) metric. First, we investigated the coordination between a multi-hop network and a cellular network. Each IoT device served as an information source that generated packets (transmitting them toward the base station) and a relay (for packets generated upstream). We created a queuing system that included the network and MAC layers. We propose a framework comprised of various models and tools for forecasting network performances in terms of the end-to-end delay of ongoing flows and AoI. Finally, to highlight the benefits of our framework, we performed comprehensive simulations. In discussing these numerical results, insights regarding various aspects and metrics (parameter tuning, expected QoS, and performance) are made apparent.