bluuebunny/crossref_metadata_2025 huggingface dataset:
The Profiles Based on Ridge and Valley Lines to Extract Shoulder Lines on the Loess Plateau
Authors: Yuan Shaoqing , Fan Wen , Jiang Chengcheng
Published: January 2023

The shoulder line is fundamental to geomorphic evolution and erosion monitoring research on the Loess Plateau, which represents the boundary between positive terrain (intergully) and negative terrain (inner gully). The existing extraction methods mainly suffer the problems of unclear geological significance, poor landform application, and low efficiency of algorithms. This paper proposes a new loess shoulder line automatic extraction method, in which topographic feature points (ridge and valley points) were used as endpoints to generate continuous profiles, and two parameters, analysis operator size (L) and filter threshold (σ), were created for shoulder point extraction from each profile. This method can be applied to complex landforms such as the continuous shoulder lines of terraces and extracts. Herein, three typical areas on the Dongzhi Plateau were selected to assess the performance of the method, and a digital elevation model (DEM) with a resolution of 5 m was used as source data. The accuracy assessment index was the Euclidean distance offset percentage (EDOP), and the original evaluation method was improved based on Structure from Motion–Multiview Stereo (SfM-MVS) technology. The experimental results showed that the average accuracy of the proposed method in the three test areas reached 89.3%, which is higher than that of the multidirectional hill-shading and P-N methods. Via testing in different areas, it could be concluded that the extraction efficiency was less affected by the area of the test region, and the approach exhibited a suitable robustness. Simultaneously, the optimal values of parameters L and σ were examined. This study increases the possibility of accurate shoulder line extraction in the large area of the Loess Plateau.
Measuring Urban Poverty Spatial by Remote Sensing and Social Sensing Data: A Fine-Scale Empirical Study from Zhengzhou
Authors: Wang Kun , Zhang Lijun , Cai Meng , Liu Lingbo , Wu Hao , Peng Zhenghong
Published: January 2023

Urban poverty is a major obstacle to the healthy development of urbanization. Identifying and mapping urban poverty is of great significance to sustainable urban development. Traditional data and methods cannot measure urban poverty at a fine scale. Besides, existing studies often ignore the impact of the built environment and fail to consider the equal importance of poverty indicators. The emerging multi-source big data provide new opportunities for accurately measuring and monitoring urban poverty. This study aims to map urban poverty spatial at a fine scale by using multi-source big data, including social sensing and remote sensing data. The urban core of Zhengzhou is selected as the study area. The characteristics of the community’s living environment are quantified by accessibility, block vitality, per unit rent, public service infrastructure, and socio-economic factors. The urban poverty spatial index (SI) model is constructed by using the multiplier index of the factors. The SOM clustering method is employed to identify urban poverty space based on the developed SI. The performance of the proposed SI model is evaluated at the neighborhood scale. The results show that the urban poverty spatial measurement method based on multi-source big data can capture spatial patterns of typical urban poverty with relatively high accuracy. Compared with the urban poverty space measured based on remote sensing data, it considers the built environment and socio-economic factors in the identification of the inner city poverty space, and avoids being affected by the texture information of the physical surface of the residential area and the external structure of the buildings. Overall, this study can provide a comprehensive, cost-effective, and efficient method for the refined management of urban poverty space and the improvement of built environment quality.
Geostationary Full-Spectrum Wide-Swath High-Fidelity Imaging Spectrometer: Optical Design and Prototype Development
Authors: Zhu Jiacheng , Zhao Zhicheng , Liu Quan , Chen Xinhua , Li Huan , Tang Shaofan , Shen Weimin
Published: January 2023

The optical system of an imaging spectrometer working on a geostationary earth orbit (GEO) covering a full optical spectrum of 0.3–12.5 μm is analyzed and designed. It enables a ground coverage of 400 × 400 km by internal scanning and achieves a high spatial resolution of 25 m. The full spectrum is divided into five sub-bands, and each band adopts four spectrometers to splice in the field of view to achieve the ultra-long slit required by the wide swath. The total length of the slit is up to 241.3 mm. This paper focuses on compact spectrometers with long slits that can meet the splicing requirements and points out that low spectral distortions, low stray light, high signal-to-noise ratio, and uniform spectral response are necessary for high-fidelity performance. The Offner and Wynne–Offner high-fidelity spectrometers based on convex blazed gratings are designed, and prototypes of each band are developed as well. The properties of long slits and convex blazed gratings are presented. The maximum length of a single slit is 61.44 mm. The groove density of gratings for five bands ranges from 8.8 lp/mm to 312.1 lp/mm, and the peak efficiency is up to 86.4%. The alignment and test of the spectrometers are introduced. Results show that the developed spectrometers have high fidelity and fulfill all requirements.
Solar Flare Effects Observed over Mexico during 30–31 March 2022
Authors: Sergeeva Maria A. , Maltseva Olga A. , Vesnin Artem M. , Blagoveshchensky Donat V. , Gatica-Acevedo Victor J. , Gonzalez-Esparza J. Americo , Chernov Aleksandr G. , Orrala-Legorreta Isaac D. , Melgarejo-Morales Angela , Gonzalez Luis Xavier , Rodriguez-Martinez Mario , Aguilar-Rodriguez Ernesto , Andrade-Mascote Ernesto , Villanueva Pablo
Published: January 2023

Manifestations of two solar flares of March 2022 were studied over Mexico. The flare effects in the lower ionosphere had a ~3 min delay from the X1.3-flare onset and ~5 min from the M9.6-flare onset. The maximal impact on the HF signal amplitude was ~(14–15) min after the onset of both flares. The X1.3-flare provoked the shortwave fadeout during ~6 min. The effects in the lower ionosphere lasted longer than the flares and the effects at the F2 region and higher altitudes only during the flares. The interpretation of results showed the following. (1) Based on the absorption level estimated with minimum frequency and signal amplitude on ionograms, the major role of X-ray radiation in the electron concentration increase in the lower ionosphere was confirmed. At the same time, the EUV radiation impact on the lower ionosphere cannot be totally discarded. The lower ionosphere recovery began before and lasted after the X1.3-flare end, being more rapid at Eglin than in Mexico. During M9.6-flare, the responses at the two observation points were rather synchronized due to the more similar illumination conditions at the two meridians. (2) According to the dI variations characterizing the F2 region and higher, the M9.6-flare provoked medium-scale and the X1.3-flare provoked both medium- and small-scale ionospheric irregularities. The response duration corresponded to the dI series filtered with (10–20) min windows. The dI curve during the flares was characterized by the И-form and depended more on the active region position and the flare class than on the solar zenith angle. The available data do not allow us to unambiguously identify the reason for the negative dI: the applied filtering procedure or the physical effect. (3) During both flares, the major EUV impact on the lower ionosphere was by the flux at 133.5 nm and on the F2 region and higher altitudes at 25.6 nm. In addition, during the M9.6-flare, EUV 28.4, 30.4 and 121.6 nm spectral bands also played an important role in the F2 response. During the X1.3-flare, the EUV 25.6 nm flux and X-ray flux impacts on the F2 region were of the same level. The weakest impact was caused by the emission in the EUV 28.4 nm spectral band on the absorption in the lower ionosphere during both flares and on the electron density in the F2 region and higher during the X1.3-flare.
The Effect of Key Anthropometric and Biomechanics Variables Affecting the Lower Back Forces of Healthcare Workers
Authors: Ji Xiaoxu , Littman Alexa , Hettiarachchige Ranuki Onara , Piovesan Davide
Published: January 2023

Wearable devices are becoming ubiquitous and can be used to better estimate postures and movements to reduce the risk of injuries. Thirty-three participants were recruited in this study to perform two daily repetitive patient transfer tasks while the full body movements were acquired using a set of magneto-inertial wearable devices. The use of wearable devices allowed for the estimation of the forces provoked on the lower back during the entire task performance. In postures where the forces exceeded the warning threshold found in the literature, healthcare workers were considered to have a greater risk of injury. Additionally, the maximum force exerted by each hand to avoid injury to the spinal column was also estimated. Knowing the key anthropometric variables associated with musculoskeletal disorders (MSDs) will enable engineers and researchers to design better assistive devices and injury prevention programs in diverse workplaces.
Sensor-Model-Based Trajectory Optimization for UAVs to Enhance Detection Performance: An Optimal Control Approach and Experimental Results
Authors: Zwick Markus , Gerdts Matthias , Stütz Peter
Published: January 2023

UAVs are widely used for aerial reconnaissance with imaging sensors. For this, a high detection performance (accuracy of object detection) is desired in order to increase mission success. However, different environmental conditions (negatively) affect sensory data acquisition and automated object detection. For this reason, we present an innovative concept that maps the influence of selected environmental conditions on detection performance utilizing sensor performance models. These models are used in sensor-model-based trajectory optimization to generate optimized reference flight trajectories with aligned sensor control for a fixed-wing UAV in order to increase detection performance. These reference trajectories are calculated using nonlinear model predictive control as well as dynamic programming, both in combination with a newly developed sensor performance model, which is described in this work. To the best of our knowledge, this is the first sensor performance model to be used in unmanned aerial reconnaissance that maps the detection performance for a perception chain with a deep learning-based object detector with respect to selected environmental states. The reference trajectory determines the spatial and temporal positioning of the UAV and its imaging sensor with respect to the reconnaissance object on the ground. The trajectory optimization aims to influence sensor data acquisition by adjusting the sensor position, as part of the environmental states, in such a way that the subsequent automated object detection yields enhanced detection performance. Different constraints derived from perceptual, platform-specific, environmental, and mission-relevant requirements are incorporated into the optimization process. We evaluate the capabilities of the sensor performance model and our approach to sensor-model-based trajectory optimization by a series of simulated aerial reconnaissance tasks for ground vehicle detection. Compared to a variety of benchmark trajectories, our approach achieves an increase in detection performance of 4.48% on average for trajectory optimization with nonlinear model predictive control. With dynamic programming, we achieve even higher performance values that are equal to or close to the theoretical maximum detection performance values.
Video Sequence Segmentation Based on K-Means in Air-Gap Data Transmission for a Cluttered Environment
Authors: Mazurek Przemyslaw , Bak Dawid
Published: January 2023

An air gap is a technique that increases the security of information systems. The use of unconventional communication channels allows for obtaining communication that is of interest to the attacker as well as to cybersecurity engineers. One of the very dangerous forms of attack is the use of computer screen brightness modulation, which is not visible to the user but can be observed from a distance by the attacker. Once infected, the computer can transmit data over long distances. Even in the absence of direct screen visibility, transmission can be realized by analyzing the modulated reflection of the monitor’s afterglow. The paper presents a new method for the automatic segmentation of video sequences to retrieve the transmitted data that does not have the drawbacks of the heretofore known method of growth (filling) based on an analysis of adjacent pixels. A fast camera operating at 380 fps was used for image acquisition. The method uses the characteristics of the amplitude spectrum for individual pixels, which is specific to the light sources in the room, and clustering with the k-means algorithm to group pixels into larger areas. Then, using the averaging of values for individual areas, it is possible to recover the 2-PAM (pulse-amplitude modulation) signal even at a 1000 times greater level of interference in the area to the transmitted signal, as shown in the experiments. The method does not require high-quality lenses.
Performance Evaluation and Cyberattack Mitigation in a Blockchain-Enabled Peer-to-Peer Energy Trading Framework
Authors: Pradhan Nihar Ranjan , Singh Akhilendra Pratap , Sudha S. V. , Reddy K Hemanth Kumar , Roy Diptendu Sinha
Published: January 2023

With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT)-based solutions are gaining prominence, and innovative peer-to-peer (P2P) energy trading at a micro level is being deployed. Such advancement, however, leaves traditional security models vulnerable and paves the path for blockchain, a distributed ledger technology (DLT), with its decentralized, open, and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, most of the prototype resilience regarding cybersecurity attack, performance and scalability of transaction broadcasting, and its direct impact on overall performances and attacks are required to be supported, which becomes a performance bottleneck with existing blockchain solutions such as Hyperledger, Ethereum, and so on. In this paper, we design a novel permissioned Corda framework for P2P energy trading peers that not only mitigates a new class of cyberattacks, i.e., delay trading (or discard), but also disseminates the transactions in a optimized propagation time, resulting in a fair transaction distribution. Sharing transactions in a permissioned R3 Corda blockchain framework is handled by the Advanced Message Queuing Protocol (AMQP) and transport layer security (TLS). The unique contribution of this paper lies in the use of an optimized CPU and JVM heap memory scenario analysis with P2P metric in addition to a far more realistic multihosted testbed for the performance analysis. The average latencies measured are 22 ms and 51 ms for sending and receiving messages. We compare the throughput by varying different types of flow such as energy request, request + pay, transfer, multiple notary, sender, receiver, and single notary. In the proposed framework, request is an energy asset that is based on payment state and contract in the P2P energy trading module, so in request flow, only one node with no notary appears on the vault of the node.Energy request + pay flow interaction deals with two nodes, such as producer and consumer, to deal with request and transfer of asset ownership with the help of a notary. Request + repeated pay flow request, on node A and repeatedly transfers a fraction of energy asset state to another node, B, through a notary.
Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System
Authors: Borzelli Daniele , Pastorelli Stefano , d’Avella Andrea , Gastaldi Laura
Published: January 2023

In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The “virtual stiffness” method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations.
Emerging Methods in Biosensing of Immunoglobin G—A Review
Authors: Azam Tehmina , Bukhari Syed Hassan , Liaqat Usman , Miran Waheed
Published: January 2023

Human antibodies are produced due to the activation of immune system components upon exposure to an external agent or antigen. Human antibody G, or immunoglobin G (IgG), accounts for 75% of total serum antibody content. IgG controls several infections by eradicating disease-causing pathogens from the body through complementary interactions with toxins. Additionally, IgG is an important diagnostic tool for certain pathological conditions, such as autoimmune hepatitis, hepatitis B virus (HBV), chickenpox and MMR (measles, mumps, and rubella), and coronavirus-induced disease 19 (COVID-19). As an important biomarker, IgG has sparked interest in conducting research to produce robust, sensitive, selective, and economical biosensors for its detection. To date, researchers have used different strategies and explored various materials from macro- to nanoscale to be used in IgG biosensing. In this review, emerging biosensors for IgG detection have been reviewed along with their detection limits, especially electrochemical biosensors that, when coupled with nanomaterials, can help to achieve the characteristics of a reliable IgG biosensor. Furthermore, this review can assist scientists in developing strategies for future research not only for IgG biosensors but also for the development of other biosensing systems for diverse targets.
Influence of the Long-Range Transport of Siberian Biomass Burnings on Air Quality in Northeast China in June 2017
Authors: Sun Li , Yang Lei , Wang Dongdong , Zhang Tiening
Published: January 2023

Biomass burning (BB) emits a large volume of trace gases and aerosols into the atmosphere, which can significantly affect the earth’s radiative balance and climate and has negative impacts on air quality and even human health. In late June 2017, an intense BB case, dominated by forest and savanna fires, occurred in Siberia, and it affected the air quality of Northeast China through long-range transport. Here, multisatellite remote-sensing products and ground-based PM2.5 measurements are used to evaluate the influence of the Siberian smoky plume on Northeast China. The results show that the BB was intense at the early stage when the daily fire count and average fire radiative power exceeded 300 and 200 MW, respectively. The maximum daily fire count reached 1350 in Siberia, and the peak value of instantaneous fire radiative power was as high as 3091.5 MW. High concentrations of CO and aerosols were emitted into the atmosphere by the BB in Siberia. The maximum daily mean values of the CO column concentration and aerosol optical depth (AOD) increased by 3 × 1017 molec·cm2 and 0.5 compared with that during the initial BB stage. In addition, the BB released a large number of absorptive aerosols into the atmosphere, and the UV aerosol index (UVAI) increased by five times at the peak of the event in Siberia. Under the appropriate synoptic conditions and, combined with pyroconvection, the smoky plume was lifted into the upper air and transported to Northeast China, affecting the air quality of Northeast China. The daily mean values of CO concentration, AOD, and UVAI in Northeast China increased by 6 × 1017 molec·cm2, 0.5, and 1.4, respectively, after being affected. Moreover, the concentration of the surface PM2.5 in Northeast China approximately doubled after being affected by the plume. The results of this study indicate that the air quality of Northeast China can be significantly affected by Siberian BBs under favorable conditions.
Impact of Glass Irradiation on Laser-Induced Breakdown Spectroscopy Data Analysis
Authors: Garrett Londrea J. , Morgan Bryan W. , Burger Miloš , Lee Yunu , Kim Hyeongbin , Sabharwall Piyush , Choi Sungyeol , Jovanovic Igor
Published: January 2023

Increased absorption of optical materials arising from exposure to ionizing radiation must be accounted for to accurately analyze laser-induced breakdown spectroscopy (LIBS) data retrieved from high-radiation environments. We evaluate this effect on two examples that mimic the diagnostics placed within novel nuclear reactor designs. The analysis is performed on LIBS data measured with 1% Xe gas in an ambient He environment and 1% Eu in a molten LiCl-KCl matrix, along with the measured optical absorption from the gamma- and neutron-irradiated low-OH fused silica and sapphire glasses. Significant changes in the number of laser shots required to reach a 3σ detection level are observed for the Eu data, increasing by two orders of magnitude after exposure to a 1.7 × 1017 n/cm2 neutron fluence. For all cases examined, the spectral dependence of absorption results in the introduction of systematic errors. Moreover, if lines from different spectral regions are used to create Boltzmann plots, this attenuation leads to statistically significant changes in the temperatures calculated from the Xe II lines and Eu II lines, lowering them from 8000 ± 610 K to 6900 ± 810 K and from 15,800 ± 400 K to 7200 ± 800 K, respectively, for exposure to the 1.7 × 1017 n/cm2 fluence. The temperature range required for a 95% confidence interval for the calculated temperature is also broadened. In the case of measuring the Xe spectrum, these effects may be mitigated using only the longer-wavelength spectral region, where radiation attenuation is relatively small, or through analysis using the iterative Saha–Boltzmann method.
Research on the Pose Error Compensation Technology for the Mass and Centroid Measurement of Large-Sized Aircraft Based on Kinematics
Authors: Yu Hang , Zhang Xiaolin , Wang Zanqin , Tang Wenyan , Wang Jun
Published: January 2023

The accurate measurement of mass and centroid is indispensable for accurate control of aircraft. In order to eliminate the influence of assembly error and product pose error on the measurement results, a multi-station measurement idea that can self-compensate for the geometric parameter error is proposed in this paper based on. At the same time, the kinematic model of the mechanical structure of the measurement equipment is established to prove the effectiveness of the structure in error compensation theoretically, and the experimental verification of the standard part and aircraft is carried out. The test results show that the measurement results using the idea of the multi-station compensation measurement are significantly better than those of the more common methods, with the mass measurement accuracy of 0.03% and the centroid error within ±0.15 mm, meeting the requirement of high precision measurement for the mass properties.
Accurate Detection and Localization of Water Pipe Leaks through Model-Based TDR Inversion
Authors: Scarpetta Marco , Cataldo Andrea , Spadavecchia Maurizio , Piuzzi Emanuele , Masciullo Antonio , Giaquinto Nicola
Published: January 2023

The problem of water scarcity affects many areas of the world due to water mismanagement and overconsumption and, more recently, to climate change. Monitoring the integrity of distribution systems is, therefore, increasingly important to avoid the waste of clean water. This paper presents a new signal processing technique for enhancing the performance of the methodology of leak detection in water distribution pipes based on time domain reflectometry (TDR). The new technique is based on a particular kind of TDR inversion (spatial TDR) based on a “gray-box” lumped parameter model of the system. The model does not include, e.g., radiative phenomena, non-TEM (transverse electromagnetic) modes etc. but is capable of reproducing accurately the complicated reflectograms obtained by a TDR leak detection system assuming a proper profile of capacitance per unit length along the sensing element. Even more importantly, the model is identified using only the reflectograms taken by the system with very little prior information about the system components. The developed technique is able to estimate with good accuracy, from reflectograms with unclear or ambiguous interpretation, the position and the extension of a region where water is located. The measurement is obtained without prior electromagnetic characterization of the TDR system components and without the need of modeling or quantifying a number of electromagnetic effects typical of on-site measurements.
Development and Practice of Sports-Related Public Welfare Platform Based on Multi-Sensor Technology
Authors: He Quantao , Hu Tongchang , Zhong Yong , Li Wenjuan , Sun Ren
Published: January 2023

Today, more and more Internet public media platforms allowing people to make donations or seek help are being founded in China. However, there are few specialized sports-related public welfare platforms. In this paper, a sports-related public welfare platform that aims to help people who were disabled due to participation in sports and those who are disabled but want to participate in sports was developed based on multi-sensor technology. A multi-sensor data fusion algorithm was developed, and its estimation performance was verified by comparing it with the existing Kalman consistent filtering algorithm in terms of average estimation and average consistency errors. Experimental results prove that the speed of the data collection and analysis of the sports-related public welfare platform using the algorithm established in this paper was greatly improved. Relevant data on how users used this platform showed that various factors affected users’ practical satisfaction with sports-related public welfare media platforms. It is suggested that a sports-related public welfare media platform should pay attention to the aid effect, and specific efforts should be devoted to improving the reliability and timeliness of public welfare aid information, and ensuring the stability of the platform system.
Terahertz Time-of-Flight Ranging with Adaptive Clock Asynchronous Optical Sampling
Authors: Li Min , Liu Zheng , Xia Yu , He Mingyang , Yang Kangwen , Yuan Shuai , Yan Ming , Huang Kun , Zeng Heping
Published: January 2023

We propose and implement a terahertz time-of-flight ranging system based on adaptive clock asynchronous optical sampling, where the timing jitter is corrected in real time to recover the depth information in the acquired interferograms after compensating for laser instabilities using electronic signal processing. Consequently, the involved measurement uncertainties caused by the timing jitter during the terahertz sampling process and the noise intensity of the terahertz electric field have been reduced by the utilization of the adaptive clock. The achieved uncertainty range is about 2.5 μm at a 5 cm distance after averaging the acquisition time of 1876 ms 5000 times, showing a significant improvement compared with the asynchronous optical sampling using a constant clock. The implemented terahertz ranging system only uses free-running mode-locked lasers without any phase-locked electronics, and this favors simple and robust operations for subsequent applications that extend beyond the laboratory conditions.
Comprehensive Numerical Analysis of Temperature Sensitivity of Spherical Microresonators Based on Silica and Soft Glasses
Authors: Marisova Maria P. , Andrianov Alexey V. , Anashkina Elena A.
Published: January 2023

In recent years, the use of optical methods for temperature measurements has been attracting increased attention. High-performance miniature sensors can be based on glass microspheres with whispering gallery modes (WGMs), as their resonant frequencies shift in response to the ambient parameter variations. In this work, we present a systematic comprehensive numerical analysis of temperature microsensors with a realistic design based on standard silica fibers, as well as commercially available special soft glass fibers (GeO2, tellurite, As2S3, and As2Se3). Possible experimental implementation and some practical recommendations are discussed in detail. We developed a realistic numerical model that takes into account the spectral and temperature dependence of basic glass characteristics in a wide parameter range. To the best of our knowledge, spherical temperature microsensors based on the majority of the considered glass fibers have been investigated for the first time. The highest sensitivity dλ/dT was obtained for the chalcogenide As2Se3 and As2S3 microspheres: for measurements at room temperature conditions at a wavelength of λ = 1.55 μm, it was as high as 57 pm/K and 36 pm/K, correspondingly, which is several times larger than for common silica glass (9.4 pm/K). Importantly, dλ/dT was almost independent of microresonator size, WGM polarization and structure; this is a practically crucial feature showing the robustness of the sensing devices of the proposed design.
Sow Farrowing Early Warning and Supervision for Embedded Board Implementations
Authors: Chen Jinxin , Zhou Jie , Liu Longshen , Shu Cuini , Shen Mingxia , Yao Wen
Published: January 2023

Sow farrowing is an important part of pig breeding. The accurate and effective early warning of sow behaviors in farrowing helps breeders determine whether it is necessary to intervene with the farrowing process in a timely manner and is thus essential for increasing the survival rate of piglets and the profits of pig farms. For large pig farms, human resources and costs are important considerations in farrowing supervision. The existing method, which uses cloud computing-based deep learning to supervise sow farrowing, has a high equipment cost and requires uploading all data to a cloud data center, requiring a large network bandwidth. Thus, this paper proposes an approach for the early warning and supervision of farrowing behaviors based on the embedded artificial-intelligence computing platform (NVIDIA Jetson Nano). This lightweight deep learning method allows the rapid processing of sow farrowing video data at edge nodes, reducing the bandwidth requirement and ensuring data security in the network transmission. Experiments indicated that after the model was migrated to the Jetson Nano, its precision of sow postures and newborn piglets detection was 93.5%, with a recall rate of 92.2%, and the detection speed was increased by a factor larger than 8. The early warning of 18 approaching farrowing (5 h) sows were tested. The mean error of warning was 1.02 h.
A Simple Way to Reduce 3D Model Deformation in Smartphone Photogrammetry
Authors: Jasińska Aleksandra , Pyka Krystian , Pastucha Elżbieta , Midtiby Henrik Skov
Published: January 2023

Recently, the term smartphone photogrammetry gained popularity. This suggests that photogrammetry may become a simple measurement tool by virtually every smartphone user. The research was undertaken to clarify whether it is appropriate to use the Structure from Motion—Multi Stereo View (SfM-MVS) procedure with self-calibration as it is done in Uncrewed Aerial Vehicle photogrammetry. First, the geometric stability of smartphone cameras was tested. Fourteen smartphones were calibrated on the checkerboard test field. The process was repeated multiple times. These observations were found: (1) most smartphone cameras have lower stability of the internal orientation parameters than a Digital Single-Lens Reflex (DSLR) camera, and (2) the principal distance and position of the principal point are constantly changing. Then, based on images from two selected smartphones, 3D models of a small sculpture were developed. The SfM-MVS method was used, with self-calibration and pre-calibration variants. By comparing the resultant models with the reference DSLR-created model it was shown that introducing calibration obtained in the test field instead of self-calibration improves the geometry of 3D models. In particular, deformations of local concavities and convexities decreased. In conclusion, there is real potential in smartphone photogrammetry, but it also has its limits.
Automatic Verification and Execution of Cyber Attack on IoT Devices
Authors: Færøy Fartein , Yamin Muhammad , Shukla Ankur , Katt Basel
Published: January 2023

Internet of Things (IoT) devices are becoming a part of our daily life; from health monitors to critical infrastructure, they are used everywhere. This makes them ideal targets for malicious actors to exploit for nefarious purposes. Recent attacks like the Mirai botnet are just examples in which default credentials were used to exploit thousands of devices. This raises major concerns about IoT device security. In this work, we aimed to investigate security of IoT devices through performing automatic penetration test on IoT devices. A penetration test is a way of detecting security problems, but manually testing billions of IoT devices is infeasible. This work has therefore examined autonomous penetration testing on IoT devices. In recent studies, automated attack execution models were developed for modeling automated attacks in cyber ranges. We have (1) investigated how such models can be applied for performing autonomous IoT penetration testing. Furthermore, we have (2) investigated if some well known and severe Wi-Fi related vulnerabilities still exist in IoT devices. Through a case study, we have shown that the such models can be used to model and design autonomous penetration testing agents for IoT devices. In addition, we have demonstrated that well-known vulnerabilities are present in deployed and currently sold products used in IoT devices, and that they can be both autonomously revealed through our developed system.
Very Compact Waveguide Orthomode Transducer in the K-Band for Broadband Communication Satellite Array Antennas
Authors: Fonseca Nelson J. G.
Published: January 2023

A very compact waveguide orthomode transducer (OMT) is described in this paper. The design is characterized with a twofold rotationally symmetric cross-section in the probing area, adapted from a side-coupling OMT design, simultaneously enabling low port-to-port coupling and high cross-polarization discrimination (XPD) over a fractional bandwidth of about 15–20%. Compared to previously reported compact waveguide OMTs, the proposed design is simpler, thus facilitating its manufacture at millimeter-wave frequencies. The concept is demonstrated with a design in the K-band for a broadband communication satellite downlink over the frequency band of 17.3–20.2 GHz. For test purposes, transitions to standard waveguide WR42 are included, and the OMT is assembled with a conical horn antenna. The measured reflection and coupling coefficients are below −19.5 dB and −22.9 dB, respectively, over the nominal bandwidth, and they are in good agreement with the simulation’s results. The on-axis XPD, measured in an anechoic chamber, is better than 30 dB over the nominal bandwidth, which is also in line with simulations. The proposed waveguide OMT may be designed to fit in a lattice below one wavelength at the highest operating frequency, which is desirable for dual-polarized closely spaced array antennas in low and medium Earth orbit communication satellite systems. The simple mechanical design of the proposed OMT makes it particularly appealing for additive manufacturing techniques, as demonstrated with a variant of the design having folded single-mode waveguides, which preserves the RF properties of the original design.
A Comprehensive Survey on MIMO Visible Light Communication: Current Research, Machine Learning and Future Trends
Authors: Sejan Mohammad Abrar Shakil , Rahman Md Habibur , Aziz Md Abdul , Kim Dong-Sun , You Young-Hwan , Song Hyoung-Kyu
Published: January 2023

Visible light communication (VLC) has contributed new unused spectrum in addition to the traditional radio frequency communication and can play a significant role in wireless communication. The adaptation of VLC technology enhances wireless connectivity both in indoor and outdoor environments. Multiple-input multiple-output (MIMO) communication has been an efficient technique for increasing wireless communications system capacity and performance. With the advantages of MIMO techniques, VLC can achieve an additional degree of freedom. In this paper, we systematically perform a survey of the existing work based on MIMO VLC. We categorize the types of different MIMO techniques, and a brief description is given. Different problem-solving approaches are given in the subsequent sections. In addition, machine learning approaches are also discussed in sufficient detail. Finally, we identify the future study direction for MIMO-based communication in VLC.
Multi-Robot Task Scheduling with Ant Colony Optimization in Antarctic Environments
Authors: Kim Seokyoung , Lee Heoncheol
Published: January 2023

This paper addresses the problem of multi-robot task scheduling in Antarctic environments. There are various algorithms for multi-robot task scheduling, but there is a risk in robot operation when applied in Antarctic environments. This paper proposes a practical multi-robot scheduling method using ant colony optimization in Antarctic environments. The proposed method was tested in both simulated and real Antarctic environments, and it was analyzed and compared with other existing algorithms. The improved performance of the proposed method was verified by finding more efficiently scheduled multiple paths with lower costs than the other algorithms.
The Dependence of the Burning Process and Ignition Temperature of a Lithium Cell on Its State of Charge
Authors: Erd Andrzej , Ciszewski Tomasz
Published: January 2023

Batteries and energy stores built with lithium-ion cells are potentially dangerous and can cause fires that are difficult to extinguish. Reducing the intensity of the fires and extending the time of their development may be of great importance for improving safety. The aim of this work is to examine the influence of the state of charge (SOC) of a cell on susceptibility to ignition, and to analyze the course of the burning process. For this purpose, a special measuring station was built, where ignition was initiated and the course of combustion was observed. During the measurements, energy was supplied by heating a cell from the outside with a resistance heater while at the same time thermally insulating the cell from the environment. The measures of the course of the fire were the amount of energy supplied to the cell before ignition and the temperature changes during the fire. The tests proved the existence of significant differences in the amount of energy causing the ignition of cells. These differences result from changes in the SOC. Quantitative results are presented. The existence of differences in susceptibility to ignition can be used to change the construction of control algorithms for battery management systems (BMSs).
SSA-VMD for UWB Radar Sensor Vital Sign Extraction
Authors: Yu Huimin , Huang Wenjun , Du Baoqiang
Published: January 2023

The combination of advanced radar sensor technology and smart grid has broad prospects. It is meaningful to monitor the respiration and heartbeat of grid employees under resting state through radar sensors to ensure that they are in a healthy working state. Ultra-wideband (UWB) radar sensor is suitable for this application because of its strong penetration ability, high range resolution and low average power consumption. However, due to weak heartbeat amplitude and measurement noise, the accurate measurement of the target heart rate is a challenge. In this paper, singular spectrum analysis (SSA) is proposed to reconstruct the eigenvalues of noisy vital signs to eliminate noise peaks around the heartbeat rate; combined with the variational modal decomposition (VMD), the target vital signs can be extracted with high accuracy. The experiment confirmed that the target vital sign information can be extracted with high accuracy from ten subjects at different distances, which can play an important role in short distance human detection and vital sign monitoring.
Yield and Composition Variations of the Milk from Different Camel Breeds in Saudi Arabia
Authors: El-Hanafy Amr A. , Saad Yasser M. , Alkarim Saleh A. , Almehdar Hussein A. , Alzahrani Fuad M. , Almatry Mohammed A. , Uversky Vladimir N. , Redwan Elrashdy M.
Published: January 2023

With the increasing interest in the identification of differences between camel breeds over the last decade, this study was conducted to estimate the variability of milk production and composition of four Saudi camel breeds during different seasons. Milk records were taken two days per week from females of Majahem, Safra, Wadha, and Hamra breeds distributed over Saudi Arabia. The milk yield during winter indicated that the weekly average of the Wadha breed was significantly lower (27.13 kg/week) than Majahem and Hamra breeds. The Safra breed had the lowest milk yield (30.7 kg/week) during summer. During winter, the Hamra breed had a lower content of all analyzed milk components except proteins and was characterized by a lower pH than the milk of the other breeds. However, the Hamra breed had significantly higher contents of milk fat and lactose than the other breeds during summer, with the corresponding values of 3.87 and 4.86%, respectively. Milk collected during winter from Majahem, Safra, and Wadha breeds was characterized by a significant increase in all milk components and milk pH. Finally, the isoelectric focusing analysis revealed noticeable variability of casein purified from camel milk within the different Saudi breeds, with the highest significant value of 2.29 g per 100 mL recorded for the Wadha breed.
Two Stability Indicating Chromatographic Methods: TLC Densitometric versus HPLC Method for the Simultaneous Determination of Brinzolamide and Timolol Maleate in Ophthalmic Formulation in the Presence of Probable Carcinogenic Oxidative Degradation Product of Timolol Maleate
Authors: Mandour Asmaa A. , Nabil Nada , Zaazaa Hala E. , Ibrahim Munjed M. , Ibrahim Mohamed A.
Published: January 2023

A comparative study between two stability-indicating chromatographic methods for the assay of brinzolamide and timolol maleate in the co-existence of the probable carcinogenic oxidative degradation product of timolol maleate in their ophthalmic formulation was demonstrated. The first method established the thin-layer chromatography coupled with the densitometric determination of the analyzed spots, using silica gel TLC aluminum plates F254 and a developing system of chloroform: methanol: ammonia (6:1:0.1, in volumes) at room temperature to give good separation for the three investigated components, where retardation factors for the oxidative degradation product of timolol maleate, brinzolamide and timolol maleate were (Rf 0.21), (Rf 0.46), and (Rf 0.55), respectively. The linear ranges were 2–10 and 3–16 μg/band for brinzolamide and timolol maleate, respectively. In the second method, high performance liquid chromatography (HPLC), photo diode array detection was used on a Eurospher 5 µm C18 100 Å (4.6 × 250 mm) column, using triethylamine pH 3.5, adjusted by glacial acetic acid: acetonitrile (20:80, v/v) at a rate of 0.5 mL per minute. An acceptable separation was achieved, where the retention times for timolol maleate, the oxidative degradation product of timolol maleate and brinzolamide, were (Rt 3.6), (Rt 4.7), and (Rt 5.6), respectively. Linearity covered a range of 20–120 μg/mL for both drugs. It has been proved previously that timolol maleate is liable to oxidation, giving a high-probability carcinogenic product in female mice. The validation for the new proposed stability-indicating methods was optimized in line with the ICH guidelines with good outcomes. It is worth noting that the HPLC-DAD method showed superior separation, economic and time-saving results, while TLC method was more sensitive.
Low-Cost Implementation of an Adaptive Neural Network Controller for a Drive with an Elastic Shaft
Authors: Malarczyk Mateusz , Zychlewicz Mateusz , Stanislawski Radoslaw , Kaminski Marcin
Published: January 2023

This paper deals with the implementation of an adaptive speed controller applied for two electrical machines coupled by a long shaft. The two main parts of the study are the synthesis of the neural adaptive controller and hardware implementation using a low-cost system based on an STM Discovery board. The framework between the control system, the power converters, and the motors is established with an ARM device. A radial basis function neural network (RBFNN) is used as an adaptive speed controller. The net coefficients are updated (online mode) to ensure high dynamics of the system and correct work under disturbance. The results contain transients achieved in simulations and experimental tests.
Analyzing the Influence of Philanthropy on Eco-Efficiency in 108 Countries
Authors: Belucio Matheus , Guarini Giulio
Published: January 2023

This paper analyzes philanthropy’s influence on countries’ eco-efficiency. The hypothesis to be verified is that philanthropy can favour the eco-efficiency. A data panel was built with statistical information from 2009 to 2018. Two methods were applied. First, a Data Envelopment Analysis model output oriented was estimated to identify the situation of overall efficiency in countries. We consider the relationship between Gross Domestic Product per capita and carbon dioxide per capita as our desirable and undesirable products, respectively. The second estimated method was a Stochastic Frontier, through which it was possible to assess the impact of philanthropy on eco-efficiency (rank of overall efficiency from DEA). Assessing the average eco-efficiency of countries around the world, it is possible to state that the results are worrying, since they reveal a fall in the average eco-efficiency of the countries over the years. Moreover, according to the second econometric model, the philanthropy index positively impacts on eco-efficiency. These empirical results fill a gap in the literature on donations’ effect on countries’ eco-efficiency. They allow policymakers to see how philanthropy can be one more tool to help countries improve their eco-efficiency. However, there is a warning that some attention is needed (control and regulation) for the best use of donations.