Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Large-Scale Datasets of Landsat-8 Satellite Image Based on LIBLINEAR Library

One of the most common machine learning approaches is linear classification. Multithreading used in LIBLINEAR Library has become an important research topic for processing large datasets. Working in a multithreaded environment accelerates the training of large datasets and increases classification accuracy. This study examines multiple linear support vector machine implementations for binary classification of Landsat-8 satellite image datasets to determine the optimal model. Four datasets have been created for different scenes in Iraq. Each dataset contains millions of pixels to be classified optimally. This article selects an appropriate algorithm for such a large dataset of current types in the LIBLINEAR library optimal for organizing large datasets using the linear SVM algorithm. Each dataset containing about 4.5 million samples was used to test the performance. The seven linear SVM techniques have statically examined the most effective SVM implementation method. Accuracy, F-Score, and Kappa are used as model assessment measures to evaluate and rank the models' performances. Based on the results, the LibLINEAR library with type 4 (LINLINEAR4) classifier was the best classifier for satellite image classification in remote sensing when applied to large datasets. The accuracy, Kappa, and f-score of the LIBLINEAR 4 classifier are as follows: (92.89 %), (73.53 %), and (77.77%) with dataset1, (96.25 %), (59.97 %), and (61.88%) with dataset2, (96.65%), (68.33%), and (70.03%), and (94.72%), (53.67%), and (56.25%), respectively, with dataset4.
A review of ground-based radar as a noncontact sensor for structural health monitoring of in-field wind turbines blades

Ground-based radar (GBR) are increasingly being used either as a vibration-based or as guided-wave-based structural health monitoring (SHM) sensors for monitoring of wind turbines blades. Despite various studies mentioning the use of radar as transducer for SHM, a singular exclusive review of GBR in blade monitoring may have been lacking. Various studies undertaken for SHM of blades using GBR have largely been laboratory-based or with actual wind turbines in parked positions or focussed on the extraction of only specific condition parameters like frequency or deflection with no validation with actual expected operating data. The present study provides quantitative data that relates in-field monitoring of wind turbines by GBR with actual design operating data. As such it helps the monitoring of blades during design, testing, and operation. Further, it supports the determination of fatigue damage for in-field wind turbine blades especially those made of composite materials by way of condition parameters residuals and deflection. A review of the two GBR-SHM approaches is thus undertaken. Additionally, a case study demonstrating its practical use as a vibration-based noncontact SHM sensors is also provided. The study contributes to the monitoring of blades during design, testing, and operation. Further, it supports the determination of damage detection for in-field wind turbine blades within a 3-tier SHM framework especially those made of composite materials by way of condition parameter residuals of extracted modal frequencies and deflection. © 2018 John Wiley & Sons, Ltd.
Analysis of Static and Dynamic Comprehensive Evaluation of Urban Low-Carbon Development Quality

In order to evaluate the quality of low-carbon development of each city in China more comprehensively, this paper innovatively introduces low-carbon innovation into the evaluation model and evaluates the quality of low-carbon development of each city in China using the dynamic evaluation method. Through the static evaluation model, it is obtained that the cities of Beijing, Shanghai Chongqing and Shenzhen are at the stage of high-quality low-carbon development; through the dynamic evaluation model, it is concluded that the cities of Shanghai and Shenzhen have higher potential for sustainable low-carbon development in the future.
Detection of Endosymbiont Candidatus Midichloria mitochondrii and Tickborne Pathogens in Humans Exposed to Tick Bites, Italy

During 2021, we collected blood and serum samples from 135 persons exposed to tick bites in southern Italy. We serologically and molecularly screened for zoonotic tickborne pathogens and only molecularly screened for Candidatus Midichloria mitochondrii. Overall, 62 (45.9%) persons tested positive for tickborne pathogens. Coxiella burnetii was detected most frequently (27.4%), along with Rickettsia spp. (21.5%) and Borrelia spp. (10.4%). We detected Candidatus M. mitochondrii DNA in 46 (34.1%) participants who had statistically significant associations to tickborne pathogens (p<0.0001). Phylogenetic analysis of Candidatus M. mitochondrii sequences revealed 5 clades and 8 human sequence types that correlated with vertebrates, Ixodes spp. ticks, and countries in Europe. These data demonstrated a high circulation of tickborne pathogens and Candidatus M. mitochondrii DNA in persons participating in outdoor activities in southern Italy. Our study shows how coordinated surveillance among patients, clinicians, and veterinarians could inform a One Health approach for monitoring and controlling the circulation of tickborne pathogens.
Techniques for Improved Speed and Accuracy in Layered Manufacturing

The ability to improve the construction accuracy and/or the build speed for layered manufacturing techniques is demonstrated using a series of new techniques: (1) Parts can be decomposed into sections which are constructed in parallel and then assembled. This reduced the build time and material waste for a sheet foam process. (2) A more accurate interface based on direct slicing ofthe CAD model can be used to eliminate the need for the intermediary tessellation file. (3) The layer thickness can be adapted based on the part's geometric complexity to increase the surface quality, build speed, and z-axis accuracy.
A Modular Wearable Finger Interface for Cutaneous and Kinesthetic Interaction: Control and Evaluation

In this paper, we present a novel modular wearable interface for haptic interaction and robotic teleoperation. It is composed of a 3-degree-of-freedom (3-DoF) fingertip cutaneous device and a 1-DoF finger kinesthetic exoskeleton, which can be either used together as a single device or separately as two different devices. The 3-DoF fingertip device is composed of a static body and a mobile platform. The mobile platform is capable of making and breaking contact with the finger pulp and reangle to replicate contacts with arbitrarily oriented surfaces. The 1-DoF finger exoskeleton provides kinesthetic force to the proximal and distal interphalangeal finger articulations using one servo motor grounded on the proximal phalanx. This paper presents the wearable device as well as three different position, force, and compliance control schemes, together with their evaluations. We also present three human subjects experiments, enrolling a total of 40 different participants: the first experiment considered a curvature discrimination task, the second one a robot-assisted palpation task, and the third one an immersive experience in virtual reality. Results show that providing cutaneous and kinesthetic feedback through our device significantly improve the performance of all the considered tasks. Moreover, although cutaneous-only feedback shows promising performance, adding kinesthetic feedback improves most metrics. Finally, subjects rank our device as highly wearable, comfortable, and effective.
Blind ML JADE in Multipath Environments Using Differential Evolution

In this paper, we tackle the problem of joint angles and time delays estimation (JADE) in a non-data aided (NDA) scenario where no pilot symbols are available at the receiver. A differential evolution (DE) technique is proposed in the context of maximum likelihood (ML) estimation is proposed to solve the resulting multi-dimensional optimization problem. DE is a metaheuristic global optimization algorithm-based on population, that finds the optimum iteratively by trying to improve a candidate solution based on an evolutionary process. We introduce the improved DE using a pseudo-pdf for easier generation of individuals. Simulations results show that the proposed solution is significantly more efficient in terms of global convergence than the classic differential evolution algorithm (CDEA) as well in terms of RMSE. Moreover, due to a very useful approximation, we are able to reduce even further the computational complexity of the proposed technique without any significant performance loss. Computer simulations also show the distinct advantage of the new NDA-DE approach over the existing techniques. Most remarkably, it also approaches the Cramér-Rao lower bound (CRLB) at medium and high SNR levels.
The role of time-lag in the surface discharge inception under positive repetitive pulse voltage

Polyetheretherketone is used in the packaging of high voltage power electronics as a frame material, and the surface discharge behaviors of polyetheretherketone are the main concerns for the packaging design. Pulse width modulation voltage, which shows a variable duty cycle, is applied to polyetheretherketone at working conditions. The surface discharge behaviors of polyetheretherketone under a positive repetitive pulse voltage of 50 Hz with different duty cycles were investigated in this paper. It is generally considered that the surface discharge inception is mainly related to electric field distribution; however, the pulse width of voltage could significantly affect the surface discharge inception characteristics. In this study, the surface discharge inception voltage, time-integrated streamer images, and cumulative surface discharge patterns under a positive repetitive pulse voltage of 50 Hz were obtained. It was found that the surface discharge inception voltage decreased with the increase in the duty cycle. This relationship was explained by the role of time-lag. Time-lag distribution analysis was performed, and the time-lag distribution was mainly determined by stochastic time-lag. The mean stochastic time-lag was obtained by the Laue plot, and the relationship between the mean stochastic time-lag and applied voltage could be well fitted by the inverse power law. Furthermore, the relationship between the surface discharge inception voltage and duty cycle could be exactly fitted by the inverse power law, which was derived from the relationship between the stochastic mean time-lag and applied voltage. The closely related relationships demonstrate that time-lag plays a critical role in the surface discharge inception at different duty cycles.Polyetheretherketone is used in the packaging of high voltage power electronics as a frame material, and the surface discharge behaviors of polyetheretherketone are the main concerns for the packaging design. Pulse width modulation voltage, which shows a variable duty cycle, is applied to polyetheretherketone at working conditions. The surface discharge behaviors of polyetheretherketone under a positive repetitive pulse voltage of 50 Hz with different duty cycles were investigated in this paper. It is generally considered that the surface discharge inception is mainly related to electric field distribution; however, the pulse width of voltage could significantly affect the surface discharge inception characteristics. In this study, the surface discharge inception voltage, time-integrated streamer images, and cumulative surface discharge patterns under a positive repetitive pulse voltage of 50 Hz were obtained. It was found that the surface discharge inception voltage decreased with the increase in the dut.
Las patentes verdes como un eslabón para fomentar la innovación en las energías renovables

El artículo caracteriza el panorama de las energías renovables en el mundo, destacando el papel de la investigación y el desarrollo apalancada en las patentes como una solución a tener muy en el ámbito de la innovación ambiental. Como objetivo propuesto, se busca caracterizar el rol de las patentes verdes como un factor determinante en el ámbito público y empresarial para fomentar la innovación y el desarrollo en el ámbito de las energías renovables. La metodología escogida es de análisis documental, apoyada en una interpretación sistemática de los hallazgos bibliográficas obtenidos luego de realizar una revisión sistemática de fuentes especializadas entre los años 2000 y 2021, tales como artículos, libros de investigación, informes, políticas y normas vigentes en la materia. Como resultados, se llevan a cabo una serie de reflexiones sobre las dificultades y oportunidades que estas aproximaciones y experiencias traen las patentes en materia de innovación ambiental y energías renovables. El aporte del artículo se da en el alcance de las reflexiones planteadas, las cuales se apoyan en aproximaciones teóricas y estudios, entre estos el Informe Awake sobre patentamiento de energías renovables en el mundo. Se concluye, por último, que, si en países en vías de desarrollo como Colombia se incentivan las patentes verdes en la investigación y el desarrollo en energías renovables, se logrará avanzar a grandes pasos hasta situarse a la par de países desarrollados.
Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference

We provide a critical review on calibration methods developed in three different areas: survey sampling, missing data analysis and causal inference. We highlight the connections and variations of calibration techniques used in missing data analysis and causal inference to conventional calibration weighting and estimation in survey sampling and provide a common framework through model‐calibration and empirical likelihood to unify different calibration methods proposed in recent literature. The goal is to demonstrate the success and effectiveness of calibration methods in achieving some highly desired properties for missing data analysis and causal inference.
Cyber Physical System applied in poultry production

a use case of poultry counting on a production line in Portugal is presented as a first step for Industry 4.0 application. Along the poultry production line there are several transformation and translation steps in which the fowls are subjected to, and their quantity in the line may change; some are removed or fall out and others are recovered and inserted in precise places of the line. Those changes can be used as an indicator of the status of the production line at that may influence the improvement of its efficiency. This paper presents a working solution of five wireless devices along a poultry production line and the complete system where data is stored locally for maintenance and supervisor decisions, and also data is stored at a remote database for management purposes which can be accessed by a mobile application.
Research on Processing Error of Special Machine Tool for VH-CATT Cylindrical Gear

The variable hyperbolic circular arc tooth trace (VH-CATT) cylindrical gear is a new gear suitable for heavy loads and high speed. The special structure of the gear provides excellent mechanical properties but also increases the processing difficulty. The special machine tool for VH-CATT gear provides a prerequisite for mass production, but the machining accuracy remains to be improved. Therefore, this paper proposes a Kriging model based on the glowworm swarm optimization algorithm of scene understanding (SGSO) to study the relationship between input parameters and output precision. Then, the SGSO algorithm is used to optimize the parameters of the Gaussian mutation function in the Kriging model to improve its fitting accuracy. When solving four groups of tooth profile and tooth direction errors, the key precision index, R2, of SGSO-Kriging all exceed 0.95. Additionally, the feasibility of the model is verified by the residual diagram and the box diagram. The contour diagram and error results show that reducing the feeding velocity, vf, can improve accuracy most efficiently, and the increase of rotational speed, n, is more conducive to the accuracy of the tooth surface than the acceleration of the coolant, vQ. The above research provides an optimization strategy of gear machining accuracy and a theoretical basis for the promotion of the VH-CATT gear.
Mutual-Feed Learning for Super-Resolution and Object Detection in Degraded Aerial Imagery

The resolution degradation poses a huge challenge for object detection (OD) in aerial imagery. The existing methods use super-resolution (SR) based on generative adversarial network (GAN) to restore texture details in degraded images. However, constrained detection results are still acquired due to object feature difference between restored and clear images. Therefore, we propose a simple yet effective learning method called mutual-feed learning (MFL) to solve the problem in this article. A closed-loop structure is designed via building the feedback connection based on the feedforward connection between the two tasks. It effectively delivers the object spatial and feature information from OD to SR and provides restoration-enhanced images from SR to OD. Specifically, a feedback of region of interest (FROI) module is introduced to realize a region-level discrimination under the guidance of object information. It guides the discrimination process of SR. Furthermore, a multiscale object information (MSOI) module is developed to implement a feature-level restoration by narrowing the differences in object-related features. It improves the generation process of SR. Then OD can be performed in restoration-enhanced images to obtain more accurate results. Extensive experiments over Northwestern Polytechnical University (NWPU) Very High Resolution (VHR)-10, Cars Overhead With Context (COWC), and Fine-grained Object Recognition (FAIR)1M datasets show that the method can achieve state-of-the-art results.
Vortex channeling and the voltage–current characteristics of YBa2Cu3O7 low-angle grain boundaries

We have performed (voltage–current) V–I measurements on a thin film YBa2Cu3O7 4° [001] tilt low-angle grain boundary over an extensive range of temperatures and fields, verifying the presence of a linear characteristic. We report on the occurrence of the linear characteristic in its basic form and on the observation of V–I kinking into several, and in some cases numerous, linear segments. We interpret these findings in terms of a variation in the dissipative width at the grain boundary. Kinking from one linear V–I section to another of different gradient is described in terms of a change in the number of vortex rows being viscously channeled along the boundary.
Fault Isolation Strategy of Cascaded H-bridge Rectifier in Power Electronic Traction Transformer

As the input stage of the power electronic traction transformer (PETT), the cascaded H-bridge rectifier (CHBR) is responsible for converting the high-voltage alternating current into direct current for the next-stage DC/DC conversion. It is of great significance to study the fault isolation strategy of cascaded H-bridge rectifiers for the safe running of trains. The basic principles and control strategies of single-phase H-bridge rectifiers and CHBR are introduced. A control strategy of CHBR based on the differential voltage balance strategy (DVBS) is proposed and its effectiveness is verified. A fault isolation strategy of CHBR based on DVBS is proposed, and the effect of this strategy to isolate faults and restore the stability of CHBR is verified by simulation.
Design of a Maximally Permissive Liveness‐enforcing Supervisor with Reduced Complexity for Automated Manufacturing Systems

This paper deals with the problems of computational and structural complexity in designing maximally permissive liveness‐enforcing supervisors for a class of Petri nets called Systems of Simple Sequential Processes with Resources (S3PR) without ξ‐resources. The supervisor consists of two parts: the first part proposes an algorithm to extract a desired emptied strict minimal siphon (SMS) from a given emptied siphon based on loop resource subsets. This is faster than the existing ones. The second part proposes a siphon‐based deadlock prevention policy, which can obtain a maximally permissive liveness‐enforcing supervisor with reduced structural complexity and no weighted monitors, owing to the contribution of the first part, which can compute a desired SMS such that one with the smallest number of resource places is selected first for control. Several flexible manufacturing systems are used to show the proposed method and its superior performance over the previous ones.
IRS-UAV Relaying Networks for Spectrum and Energy Efficiency Maximization

In this paper, an integrated intelligent reflecting surface (IRS)-unmanned aerial vehicle (UAV) communication scheme is proposed where the IRS is mounted on the UAV as a mobile relay between the base station (BS) and the ground user. We present two schemes to maximize the spectrum efficiency (SE) and the energy efficiency (EE) of the system by jointly optimizing the active beamforming, passive beamforming and UAV trajectory. First, to tackle the SE maximization problem, we divide it into three sub-problems to optimize the variables iteratively. For the active and passive beamforming, the closed-form solutions can be directly derived. The suboptimal trajectory design can be obtained by utilizing the successive convex approximation (SCA). Furthermore, considering the limited on-broad energy of UAV, a scheme to maximize the EE is proposed. The optimal active beamforming and the passive beamforming can be similarly obtained. For the non-convex fractional programing of trajectory optimization, it can be solved via the Dinkelbach’s method. Numerical results demonstrate that the effectiveness of the proposed algorithms.
Modeling Population Exposures to Pollutants Emitted from Natural Gas Cooking Burners

We developed a physics-based data-supported model to investigate indoor pollutant exposure distributions resulting from use of natural gas cooking appliances across households in California. The model was applied to calculate time-resolved indoor concentrations of CO, NO2 and formaldehyde resulting from cooking burners and entry with outdoor air. Exposure metrics include 1-week average concentrations and frequency of exceeding ambient air quality standards. We present model results for Southern California (SoCal) using two air-exchange scenarios in winter: (1) infiltration-only, and (2) air exchange rate (AER) sampled from lognormal distributions derived from measurements. In roughly 40percent of homes in the SoCal cohort (N=6634) the 1-hour USEPA NO2 standard (190 ? g/m3) was exceeded at least once. The frequency of exceeding this standard was largely independent of AER assumption, and related primarily to building volume, emission rate and amount of burner use. As expected, AER had a more substantial impact on one-week average concentrations.