Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time web based Timing display Application for Test Range Applications

Web based applications are availabel since long time serving many needs of the people such as e-marketing, e-governance, telemedicine etc. but real-time web application technologies are quite new. Nowadays real-time web application is highly demanded in many areas such as stock marketing, industrial plants, Test Ranges etc. where realtime data has to be visualised. The present work is an effort in the same direction wherein the Count Down Time information generated by a hardware device combined with synchronised actual time is displayed in real-time using a web application. For development of real-time web application server side java scripting using node.j s framework has been done. The paper presents detailed architecture of Websocket and its successor socket.io. The implementation of frontend using HTML, CSS and backend server using node.js framework has been done. Finally the time delay analysis from server to clients which are remotely located from each other in the Range has been shown. This paper compares the time delay in traditional standalone application and new web based application. In this way this real-time web application for Time display is first of its kind in Test Range.
Design and seismic response of tall chevron panel buckling‐restrained braced steel frames

The numerical analysis of the seismic performance for tall chevron panel buckling‐restrained braced steel frames (PBRBFs) under small and strong earthquake excitations has been carried out to investigate a capacity design procedure for chevron PBRBFs and to examine the effects of axial strength distribution of braces along the height of buildings, vertical supports of braces for the braced beams and the overstrength of braces on the seismic response of PBRBFs. It revealed that the chevron braces that remained elastic can actually provide the vertical supports for the braced beams. Under severe earthquake excitations, the vertical supports deteriorated greatly after braces yielding. The PBRBFs designed by omitting vertical supports of braces for the braced beams and considering the overstrength of braces exhibited superior performance with smaller plastic deformations for braced beams and reduction in ductility demands for panel buckling‐restrained braces (PBRBs) as compared with the others. The distribution of yielding for PBRBs in 10‐story buildings verified that the participation from the higher modes is not very remarkable and that the capacity design based on the first‐mode response can be considered for multistory PBRBFs. Moreover, on the basis of the analysis results of the 30‐story PBRBF, the participation of the higher modes should be taken into account for high‐rise PBRBFs. Copyright © 2011 John Wiley & Sons, Ltd.
Research and Application of Key Technologies of BIM+GIS Virtual-reality Interaction for High-speed Railway Integration Test

Integration test is an important security guarantee for high-speed railway operation. Aiming at the problem of chimney construction of more than 20 professional systems, which are scattered and lack of linkage, key technologies such as BIM+GIS multi-source heterogeneous data fusion, dynamic loading and rendering and lightweight model are put forward, and the virtual-reality mapping and interaction in physical railway and virtual twin railway scenes are realized based on "One Screen, One Picture" in BIM+GIS vehicle-mounted integration platform. The platform further explores the data value, and provides reference and guidance for lossless transmission of full life circle data of multi-professional and multi-participant railway based on BIM+GIS model, collaborative linkage, visual expression, immersive experience and intelligent decision-making, and further improves the intelligent management level of overall research and judgment of integration test, collaborative command and scientific decision-making and promotes the development of intelligent joint debugging.
Automated Face Detection and Control System Using Computer Vision based Video Analytics to Avoid the Spreading of COVID-19

The classification of COVID-19 as global pandemic has led researchers and scientists to design solutions in order to reduce the fast spreading of the virus. This paper presents a novel detection and control system that utilizes Computer Vision based video analytics to help in reducing the speed of the spreading of the virus by recognizing people and detecting masks. The system uses the body temperature and other user biometrics to give access to a particular environement. The proposed system is able to identify a person who wants to access an environment and tracks his movement. The system can also control the door of the main entrance, the elevator, or any access zone, and generate audio notifications to alert user(s) to put their mask(s). The implementation results show that the proposed system has the advantages of a high sensitivity of 98.8% for front faces and 90.3% for turned faces, and ensure a safe environment while preserving the benefits of being modular and low cost.
Improved K-nearest neighbor algorithm for indoor positioning using 5G channel state information

As the demand for location-based services in indoor environments continues to grow, indoor positioning systems have attracted more and more attention. At present, the commonly used positioning system is based on the received signal strength of the WiFi network positioning algorithm. However, with the vigorous development of the fifth-generation(5G) mobile communication technology, the positioning accuracy can be greatly improved, and more accurate indoor positioning can be achieved. In order to improve the positioning accuracy, a positioning algorithm based on the channel state information reference signal is proposed. By using the smooth rank sequence (SRS) algorithm in the estimation of the number of received signal paths, the estimation accuracy of the angle of arrival(AoA) and the time of flight(ToF) can be improved. The combination of Gaussian Mixture Model(GMM) and the Expected Maximum(EM) algorithm further ensures the construction of offline fingerprint database. Besides, the online matching algorithm of fingerprint database is improved, and an improved k nearest neighbor algorithm is proposed. Compared with other matching algorithms, it proves that the proposed two-step k-nearest neighbor algorithm improves the positioning accuracy and reduces the amount of calculation for online matching.
Optoelectronic Methods for Non-invasive Analysis of Hematocrit Level

The article presents an overview of methods for studying blood corpuscles to select the most promising one and the possibility for its implementation. Through a preliminary experimental study of biological tissue, experimental results of the parameters of the Stokes vector and the polarization of radiation were obtained, which makes it possible to observe somatic deviations and shifts that can be caused both by therapeutic agents and by the presence of certain cardiovascular diseases in a patient. Based on the results of the preliminary experiment, the possibility of implementing the polarization method through an optoelectronic system was proposed for continuous monitoring of the rheological properties of blood, which in turn correlate with the level of hematocrit.
A vision system for automated crack detection in welds

The authors describe the development of a vision-based system for automated inspection of surface cracks in materials. The magnetic particle inspection method is used to reveal cracks in ferromagnetic materials. The vision system consists of an IBM AT compatible computer, a framestore and a camera. Details of the preparation procedure and the software algorithms for crack recognition are discussed. Results are presented for transverse and longitudinal cracks in welds used to fabricate structures.
Model Scale Analysis of a TLP Floating Offshore Wind Turbine

This paper discusses the experimental campaign conducted by CEHINAV-UPM research group as request of IBERDROLA within the OCEAN LIDER RD project framework. The purpose of the campaign has been the hydrodynamic performance of a tension leg platform to support a wind energy turbine (TLPWT). The turbine chosen in this study has been the 5MW reference WT of NREL, the location depth has been 80m and the operation area is Estaca de Bares in the north-west of Spain. Regular waves, operational, survival, failure and transport experiments have been conducted. All tests have been performed in CEHINAV (UPM) model basin, except survival tests performed in CEHIPAR ocean basin. This document presents the experimental setup and results from decay tests, regular wave motion RAOs, irregular wave responses, tendon loads and accelerations. Experimental results are compared with available in-house numerical simulations and other numerical and experimental results found in literature.Copyright © 2014 by ASME
Wearable Intelligent Textile Suits for Telemetry Monitoring in Pediatrics

The growing demand for opportunities for continuous online monitoring of biomedical signals leads to the rapid development of wearable technologies. The implementation of intelligent textile systems and materials in medical practice multiplies better results of the work of medical teams. With their help, diagnosis and treatment can be obtained anywhere, anytime, at an affordable price, without the need for patients to visit a medical center. When working with patients, especially in pediatric wards, the key issue is to preserve their ability to maintain daily activity within their habits, freedom of movement, movement, taking certain positions without interfering with the collection, recording and analysis. of biomedical signals. This would facilitate the process of accepting the monitoring and would lead to the provision of regularly received data on vital signs with the necessary quality for their diagnosis and treatment by the medical teams. Also, with the introduction of wearable technology, it is possible for a medical professional to take care of more patients, as well as to monitor their condition remotely, giving instructions to change treatment when necessary.
Design of a Compact and Low-Loss E-Band Filter Based on Multilayer Groove Gap Waveguide

This letter presents our study on a compact and low-loss E-band bandpass filter (BPF) based on multilayer groove gap waveguide (GGW). Different from other reported planar GGW filters and vertically stacked substrate integrated waveguide (SIW) filters, the proposed filter realizes a cross-coupled quadruplet topology by introducing a pair of unique circular capacitive holes across layers, innovative ridges (capacitive iris), and conventional inductive irises on the same layer, which reduces the insertion loss (IL) while having a smaller size. By tuning the dimensions of the coupling structures and cavities, the filter is optimized to exhibit a superior performance in simulation. The designed filter is fabricated using CNC machining and verified in experiment. The measured results agree with the simulated ones quite well, showing an average IL of 0.45 dB and an 8% relative 3-dB bandwidth at a center frequency of 73.65 GHz. Therefore, the proposed multilayer GGW structure opens a new avenue in designing high-performance filters in millimeter-wave bands.
The SSVEP tool as a marker of subjective visibility

This study is part of a larger attempt to explore how the brain produces conscious experience. Our main objective here was to take advantage of a neural signature conveyed by the steady-state visual evoked potentials (SSVEP) technique (1) to explore the extent to which complex visual images can be processed in the absence of consciousness and (2) to determine whether this tool can be used to shed light on participants’ phenomenal experience of these images. To this end, we embedded faces within sequences of non-face stimuli and manipulated their contrast to create a subliminal condition. Our results were threefold. First, we show that a significant brain activation can be delineated with the SSVEP tool even when participants report being unable to see the stimuli. In this subliminal condition, the brain response was confined to the back of the scalp. Second, we observe that the face signal increases in magnitude and propagates bilaterally along a posterior-to-anterior axis as image contrast increases. Third, we suggest that SSVEP could be used as a novel instance of a no-report paradigm because it requires no overt behavioural response, and because at some contrast levels and electrodes, its outputs (signal magnitude and scalp topography) predict people’s self-reported phenomenal experience.
Properties Analysis of 2D PtSe2 Layers Grown by Thermally Assisted Conversion of Chemical Vapor Deposition

Platinum diselenide (PtSe2) as a part of 2D noble transition metal dichalcogenides (nTMDCs) offer diverse optoelectronic properties which can be effectively controlled as number of layers and engineered for novel applications. In this context, our study is focused on structural and compositional characteristics of large area synthesized PtSe2 ultrathin films. In addition, optical properties analysis as a way to track the quality of PtSe2 at different synthesized stages using thermal assisted conversion (TAC) of chemical vapor deposition (CVD) was performed.
Design and Implementation of Flow Visualization Software based on MATLAB

With the continuous development of scientific visualization, visualization has been applied to various fields. Flow field visualization is an important part of the visual field, by using computer graphics, computer vision, and image processing technology, it can use intuitive graphical images to describe the flow field structure of the complex, disorder, which makes the flow field visualization in the field of meteorology, aviation and geography have great application prospect. This paper uses MATLAB App Designer to design a flow field visualization software, which mainly displays the scalar or vector velocity field in two dimensions and three dimensions. The software has a powerful interactive function, can choose different flow field display modes, can choose a specific two-dimensional section for separate display. With this software, flow field data can be clearly, succinctly, and intuitively displayed, and key information such as flow field distribution, movement trend, and velocity change can be understood. In addition, the software uses MATLAB App Designer to encapsulate the form of desktop independent APP, which is simple and convenient to use.
Protective Effect Of Oral And Intranasal Bacterial Lysates In Mice

In this study albino mice were used to test the beneficial effect of bacterial lysates vaccination against lethal dose of Pseudomonas aeroginosa. Escherichia coli lysate, Pseudomonas aeroginosa lysate, Staphylococcus aureus lysate and mixed bacterial lysates were administered through the oral and the intranasal routes, both in the presence and absence of Freund’s adjuvant versus a placebo. Pseudomonas aeroginosa fifty percent lethal dose ( LD50 ) was injected intraperitonealy following intranasal and oral vaccination. The placebo and the four bacterial lysates were also used in association with Freund’s adjuvant. The results of the LD50 in intranasal vaccinated groups were 50%, 37.5%, 100%, 0% and 12.5%, and those with Freund’s adjuvant were 25%, 25% , 12.5%, 62.5%, 0% and 0% respectively. The results of LD50 in oral vaccination were 50%, 25%, 62.5% 0% and 37.5%, and those treated with Freund’s adjuvants were 12.5%, 12.5 %, 12.5%, 37.5 %, 0% and 25% respectively. The bacterial lysates vaccinated groups were studied for the total body weight (T), liver (L), spleen (S), thymus (Th) weights and the L+S+Th/T ratio. Besides, the peripheral blood and the peritoneal fluid total and differential leucocytic counts were determined and the bone marrow lymphocyte percentage. The serum immunoglobulins G and M were assessed using the immundiffusion plates. Our conclusion is: Bacterial lysates can play an important role as immunomodulators when used by oral or intranasal routes.
Optimal Precoding and Deployment of Millimeter-Wave Drone Base Stations

Due to their flexible deployment and line-of-sight channel conditions, drone base stations is a promising technology. Recent developments in Massive MIMO tranmission with millimeter-wave beamforming also enables high data rates and enables simultaneous transmission to multiple ground users. In this work we consider the problem of deployment (i.e. positioning) of drone base stations and analog MIMO beamforming that maximizes SINR. Simulation results reveal that careful K-Means clustering of ground users, together with DFT-based beamforming provides a promising performance.
Private Information Inference of Households from Electricity Consumption Data

The spread of smart home technologies not only brings convenience but also creates various security and privacy concerns among users. Electricity consumption data collected by smart meters is one of the sources of these concerns. The electricity consumption of the appliances working at home made it possible to have information about the private life of the household. This study is aimed to reveal a classification model by using the electricity consumption data obtained as a result of the study conducted in Ireland and the results of the survey study conducted with the households. While the first method in the study aims to access information about private life directly with electricity consumption data, the second method uses the predictions of one private information to improve the results of the prediction of another related information. As a result, it has been concluded that electricity consumption data can be used in the process of obtaining information about private life, and that the use of relationship between two information leads to an improvement in model performance. This study shows one of the obstacles that may occur in the spread of smart houses and has prepared the environment for studies that can be done on the subject of solution.
Finite-Time Fault-Tolerant Control for a Robotic Manipulator With Output Constraint and Uncertainties

This paper proposed a finite-time backstepping control for a robotic manipulator under the presence of actuator fault, saturation constraints, output constraints, and external disturbance to obtain requirements about the robustness, fast convergence, and high accuracy tracking performance. To manage the above challenges, the proposed control is designed on a transformed model with the backstepping approach and extended state observer. The transformed model is resulted from converting a constrained system based on a transformation technique. So, it provides an ability for the proposed control to obtain the prescribed performance of the output response. Additionally, an extended state observer is conducted to deal with the lumped uncertainties in the system. The essential characteristic of the proposed control is no required knowledge of the actuator faults and external disturbance to be available. Furthermore, fractional-order terms are added in the control laws to enhance the rate of output responses. To demonstrate the advantages of the proposed control in terms of global asymptotic stability, the Lyapunov approach is used to verify the whole controlled system in theory. The proposed control is applied to a 2-degree of freedom (DOF) manipulator and simulated by MATLAB Simulink. Its simulation results are compared to other state-of-the-art methods to exhibit the effectiveness of the proposed control.
A Prediction Model of Humidity Sensor Response

Many modern algorithms that process sensor information need both current sensor output values and some prediction of these values in future moments. In the current work, an approach to building a predictive low order model of the SHT31-DIS humidity sensor is discussed. Assuming that the sensor can be presented with a standard first-order output error model plus delay, it is shown that the measurements obtained from the sensor can be predicted one step ahead with an error of less than 5%RH. When estimating the parameters of the model, a mean square criterion and measurements traceable to the standard relative humidity scale OIML R 121 were used.
A Selective Soft Error Protection Method for COTS Processor-based Systems

This paper proposes a framework that dynamically monitors a program's registers and analyzes their interaction with the memory at run-time. This information is used to implement the Selective-Swift-R fault tolerance technique, which enables us to selectively identify and protect vulnerable registers and achieve fault tolerance against soft errors. Being a pure software-implemented framework and error detection techniques, this research is suitable for commercial off-the-shelf processors. The evaluation based on number of Silent Data Corruptions and code size overhead has been evaluated for four different case studies compared to the unprotected program.
Controlled Islanding Based on the Coherency of Generators and Minimum Electrical Distance

Inter-area oscillations and cascading failures are the most significant threats to power system security. In case of unstable inter-area oscillation or progressive cascading failure, the system will be faced uncontrolled islanding. The establishment of uncontrolled islands with a deficiency in load-generation balance is the main reason for system blackout. In this respect, for reducing the risk of blackout, controlled islanding has been considered as a preventive strategy. In this paper, based on the coherency and nearest electrical distances between loads and coherent groups of generators, a new algorithm for applying the strategy of controlled islanding is proposed. In this method, first based on the correlation coefficients between generators and the DBSCAN clustering algorithm, coherent generators as the main core for controlled islands are identified. Then by using mixed-integer linear-programming around each coherent group, the sub-networks are established. Then, non-linear programming is used to construct the stable sub-networks associated with islands satisfying load-generation balance, voltage limits, and transmission limits. The proposed scheme is implemented on the IEEE 39-bus system as a small system and Iran power network as a large-scale realistic power system. The results show the ability of the proposed method for implementation in a real power system.
Short-Term Wind Speed and Temperature Forecasting Model Based on Gated Recurrent Unit Neural Networks

Wind energy generation fluctuations and intermittency issues create inefficiency and instability in power management. The recurrent neural networks (RNNs) prediction approaches are an essential technology that can improve wind power generation and assist in energy management and power systems’ performance. In this paper, a prediction model based on Gated Recurrent Unit (GRU) neural networks is proposed to predict wind speed and temperature values one week ahead in the future at hourly intervals. The GRU prediction model automatically learnt the features, used fewer training parameters, and required a shorter time to train compared to other types of RNNs. The GRU model was designed to predict 169 hours ahead as a short-term period of wind speed and temperature values based on 36 years of hourly historical data (1 January 1985 to 6 June 2021) collected from Dumat al-Jandal city. The findings notably indicate that the GRU model has promising performance with significant prediction accuracies in terms of overfitting, reliability, resolution, efficiency, and generalizable processes. The GRU model is characterized by its good performance and influential evaluation error metrics for wind speed and temperature values.