Miracle-dz/UniFAR-FTUs huggingface dataset:
Aggregating and Searching frame in Video Using Semantic Analysis

The idea of Video content reclamation is a youthful field that has its genetics grounded forebears instinctive intelligence, numerical signal rectification, statistics, natural language understanding, If researchers are concentrating all these fast growing fields so none of these parental fields alone antiquated able to directly solve the retrieval problem. In this paper shows the path towards a step by step mechanism of CBVR i.e. analysis of entire video, video segmentation, key frames mining, feature extraction mining for retrieving the video from large video datasets. The proposed system inclination focuses on performing key frame mining using adaptive thresholding algorithm and canny mechanism for feature extraction purpose. In order to legalize this claim, content based video reclamation systems were furnished using color histogram, features extraction and different approaches are applied for the supervision of the semantic temperament of each frame in the video.
A Brief Review on Ground Vehicles Aerodynamics due to the Presence of Streamwise Vortices

Flow past any solid bodies often generates three-dimensional trailing, swirling vortices. Such structures affect the aerodynamic performance of vehicles in motion. The presence of vortices changes the aerodynamic forces that are directly related to fuel consumption, maneuverability, and safety of the vehicles. In this manuscript, a brief review on the presence of three-dimensional vortices and their effects on the aerodynamic performances of the ground vehicles is presented. Specifically, the discussions cover the drag mechanism in passenger cars, heavy trucks, and motorbikes, which is highly affected by the presence of such three-dimensional vortices. Some attempts to reduce drag, both in conceptual prototypes and commercial cars are provided in this paper as well. One of the drag reduction methods, that is, by means of a vortex generator, is often installed in the racing cars and heavy trucks. Qualitative smoke-wire visualization of simple vortex generators on a flat plate is also included in this manuscript.
Gaussian Process Learning for Distributed Sensor Networks under False Data Injection Attacks

Distributed sensor networks are the backbone of many modern intelligent systems. The collected sensor data are fused and processed to learn the underlying model (such as the Gaussian process) of interested physical process, which serves as critical knowledge for the further decision making process. On the other hand, the distributed and heterogeneous nature of connected devices makes them vulnerable to cybersecurity attacks. One common type of attacks is the false data injection attack, which is implemented by hijacking nodes and modifying sensor measurements. In this work, we study the problem of Gaussian process learning for distributed sensor networks under false data injection attacks. The proposed algorithm is based on formulating consensus for the unknown hyper-parameters of the Gaussian process over the network, where statistical measures of the reliability of the local maximum likelihood estimates are used as the weights in the consensus formulation. Furthermore, we investigate the impact of choosing different subset of nodes to deploy the FDIA, based on the topological properties of the subset of nodes. The simulation result shows that extra effort must be invested to protect the integrity of data from nodes with high centrality, due to their critical positions in the information flow over the network.
Research on Intelligent Monitoring and Analysis of Physical Fitness Based on the Internet of Things

In the process of physical fitness training, it is an important subject of scientific physical fitness training to adjust and control the physical load intensity in real-time, accurately and effectively according to the physiological load inside the human body so as to make it consistent with the predetermined goal of the training plan. Aiming at the current demand of smartphone popularization and athlete training monitoring, this paper designs an intelligent monitoring system of physical fitness based on the Internet of Things technology. By selecting such factors as vertical jump, fast leg raising, sitting forward, height, chest circumference, percentage of body constitution, YOYO intermittent endurance running and so on, using RFID technology to mark different athletes, and after using the particle swarm optimization method of BP network to establish the evaluation model of the athletes’ physical condition. Through simulation, the physical condition of athletes is accurately predicted, which provides a new scientific and technological means to improve the efficiency of physical training and make physical training scientific.
Comprehensive Computational Modelling Approach for Graphene FETs

Graphene has shown a great scope beyond the bulk silicon devices for future transistor applications. Even though it has undergone intensive investigations through experimental approach, there are no easy and time efficient computational approaches for analysing the graphene transistors. In this paper we provide methodology for simulating graphene transistors using conventional TCAD tools with appropriate model calibration. We demonstrate the calibration methodology along with few graphene FET simulations with the calibrated set-up.
Simple Beam Scanning SIW Cavity-Backed Slot Antenna Using Postloaded Varactor

A reconfigurable beam-scanning substrate integrated waveguide (SIW) cavity-backed slot antenna (CBSA) is presented. By adopting three transverse radiating slots and inserting four pairs of postloaded varactors, the field distributing in the SIW cavity can be moderately perturbed. To be specific, two pairs of varactors, flanked by the adjacent slots, are placed in the vicinity of the cavity longitudinal centerline; while the other two pairs are symmetrically embedded at two end parts of the bilateral slots. As such, manipulating biasing voltage applied to each pair of varactors independently could offer very fine control of the amplitude and phase of every single-slot element. Accordingly, the main beam direction of the proposed antenna is electronically controlled. A prototype was designed and fabricated to validate the proposed method. Measured results demonstrate the proposed CBSA with a beam scanning from –30° to 41° and a gain varying between 6.4 and 9.2 dBi.
The Processing of the Results of Deformation Measurements Using Empirical Mode Decomposition

The study of the deformations of the Earth’s crust and rocks allows filling the lack of information about earthquake precursors in the absence of reliable methods for their prediction. In the area of the Baikal rift zone, the insufficient technical equipment of the existing geodynamic polygons is particularly strongly felt. It is not possible to achieve sufficiently reliable results for the detection of earthquake precursors. Creating an automated, highly reliable measuring equipment is extremely important. Laser displacement meters are most effective for these purposes. They allow measuring of deformations of the Earth’s crust, which allows registering and identifying early harbingers of earthquakes. The processing of the results of these measurements is also important for solving applied problems of engineering seismology. The paper discusses the possibility of using the empirical mode decomposition method for processing data obtained because of using a laser rock strain gauge developed by the Institute of Laser Physics of the SB RAS and used at the Talaya Observatory in the Baikal rift zone. The results of applying this method to real data are given.
Scatter Phy: A Physical Layer for the DARPA Spectrum Collaboration Challenge

DARPA has started the Spectrum Collaboration Challenge with the aim to encourage research and development of coexistence and collaboration techniques of heterogeneous networks in the same wireless spectrum bands. Team SCATTER has participated in the challenge from its beginning and is currently preparing for the final phase of the competition. SCATTER’s physical layer (SCATTER PHY) has been developed as a standalone application, with the ability to communicate with higher layers of SCATTER’s system via ZeroMQ, and uses USRP X310 software-defined radio devices to send and receive wireless signals. SCATTER PHY relies on USRP’s ability to schedule timed commands, uses both physical interfaces of the radio devices, utilizes the radio’s internal FPGA board to implement custom high-performance filtering blocks in order to increase its spectral efficiency as well as enable reliable usage of neighboring spectrum bands. This paper describes the design and main features of SCATTER PHY and showcases the experiments performed to verify the achieved benefits.
First Time User Experience Assessment on Web based Online Examination

An examination is an important task in the education system to measure the level of students’ understanding of teaching material. Replacing paper-based with an online system not only increases the efficiency of its process by reducing the consumption of papers, but also the amount of time spent marking and grading. However, a massive changing in exam operation happens on test participant. This research aims to reveal the user experience in the implementation of a website-based exam system. In particular, to study the first-time user experience, including their attempt to understand how to use the application. The user experience is measured by User Experience Questionnaire (UEQ). 40 respondent participated in this research. All the respondent use the exam system for the first time without any prior training. According to the user responses, the first-time user rates the overall system in a good score in good and above average compared to the benchmark. However, the novelty and perspicuity dimension obtain the lowest score. Interviews confirm this value, and some respondents put attention to the alternative of the interface in more modern technology such as mobile phone apps. The current interface also needs great improvement, such as font size and question grouping.
Energy Efficient Stationary Application Supplied with Solar - Wind Hybrid Energy

Decreasing the use of conventional energy resources, increasing efficiency of stationary applications, reducing greenhouse emissions are topics of great interest worldwide. Hybrid energy is the combined use of two or more forms of energy, ensuring in a more efficient overall result. In general, hybrid energy systems can significantly reduce classic energy consumption, impact on the environment and cost of supply to end users. This article addresses two innovative concepts that underpin the sustainability elements in stationary applications: energy efficient building and hybrid energy generation system with the role of completely eliminating traditional energy consumption. The case study presents a solution for integrating renewable energy sources (sun and wind) with a special role in decarbonising of buildings sector. The study, the simulations and analyzes performed aim to demonstrate the applicability of hybrid energy systems and highlighting their energy, ecological and economic performances in supplying with alternative hybrid energies for stationary applications.
Hybrid System of Convolutional Neural Networks and SVM for Multi-class MIEEG Classification

Deep learning methods are used in the field of brain–computer interface (BCI). We propose a model that combines convolution neural networks (CNNs) and support vector machines (SVMs) for multi-classification based on the use of motor imagery technique. The Stockwell transform is used to transform signals into feature maps covering different frequency ranges. Here, the feature map is input into CNN for conducting feature extraction, and the SVM is used as a classifier to classify the feature secondary training extracted by the CNN to form a complete MI processing framework. Batch normalization and drop layer are added to the CNN network to improve the over-fitting phenomenon that may occur. The sliding Gaussian time window enhances the data samples to improve the classification performance of the network. The superiority of the model is demonstrated through the results of the tests conducted on the BCI Competition IV dataset 2a. The average cross-validation accuracy rates of CNN and CNN-SVM are 82% and 84.1%, and the Kappa values are 0.76 and 0.79, respectively. The accuracy rate and Kappa value of CNN-SVM increased by 2.1% and 0.03, respectively. Experimental results show that the classification performance of CNN-SVM is higher than that of CNN and most existing classification algorithms.
Design of a Low Profile Flexible Tri-Band Frequency Surface Applied in X-Band, K-Band and Millimeter-Band

A low profile flexible miniaturized tri-band frequency surface is proposed by cascading three layers of periodic arrays. The top and bottom layers have the same square patch structure embedded in the bending gap, whereas the middle layer has an interlaced metal grid structure. The medium between each layer is made of flexible polyimide material with a thickness of only about 0.2mm. The coupling of the three metal layers gives rise to a first X-band passband, with a central frequency of 10.6 GHz. The interlaced metal grid structure generates a second K-band passband, with a central frequency of 24.1GHz. The two-layer symmetrical planar cascade structure produces double-peak resonances at 39.4 GHz and 46.2 GHz, forming a third millimeter-wave passband. Compared with the traditional tri-band FSSs, due to the combination of bending technology and multi-screen cascade technology, the reported structure generates the first and second passbands with miniaturization and good angle stability, and the third passband with rectangular filtering characteristics. Besides fabrication and tests, the corresponding equivalent circuit model is also established in order to analyze the transmission characteristics. The test results are well compatible with the simulation results.
Open Complementary Split Ring Resonator Based RF Sensor with Improved Sensitivity for Detection and Estimation of Adulteration in Edible Oils

In this paper, a non destructive approach for detection of adulteration in edible oils using an open complementary split ring resonator (OCSRR) structure is presented. The pro-posed OCSRR based RF sensor is designed on a 1.6 mm thick FR4 substrate ($\epsilon _{r}$=4.4) to operate at 3.6 GHz. The adulteration analysis in this study is carried out for various samples of mustard, coconut, olive and sunflower oils. A sample holder is placed such that the oil sample under test is in direct contact with the manufactured OCSRR sensor. The shift in the resonant frequency of the OCSRR is observed and the permittivity values of the oil samples are extracted from the simulation results and practical measurements. In addition, the percentage of adulterant in an oil sample is estimated by studying the dielectric properties of the sample under test. About 50% of adulteration in edible oils can be detected using this procedure and the numerical sensitivity (NS) of the proposed sensor lies in between 11.67% -18.33% for different oil samples.
Narrow-Linewidth Photonic Microwave Generation Based on an Optically Injected Semiconductor Laser Subject to Subharmonic Modulation

We propose and experimentally demonstrate a scheme to acquire a narrow-linewidth photonic microwave based on an optically injected semiconductor laser (OISL) modulated by a subharmonic microwave from an optoelectronic oscillation (OEO). The microwave frequency generated by the OEO is 7.62 GHz, and the period-one (P1) oscillation frequency of the OISL is close to twice of it. Through modulating the OISL by a 1/2 subharmonic microwave generated by the OEO, the photonic microwave is locked at 15.24 GHz with a 3-dB linewidth about 1 kHz and a SSB phase noise of -94 dBc/Hz at offset frequency 10 kHz.
Femtosecond Soliton Erbium-Doped Fiber Laser With a Symmetrical GIMF–SIMF–GIMF Saturable Absorber

A femtosecond soliton erbium-doped fiber ring laser with the symmetrical saturable absorber (SA) of graded index multimode fiber-step index multimode fiber-graded index multimode fiber (GIMF-SIMF-GIMF) is proposed and proved. Based on the nonlinear multimode interference (NL-MMI) effect of SA, the fiber laser achieved femtosecond soliton mode-locking operation and repetition rate tuning. The duration of soliton was 364 fs at 1562.5 nm and repetition rate was tunable from 10.29 MHz to 763.36 MHz. In the structure of SA, a short step index multimode fiber (SIMF) was inserted between two graded index multimode fibers (GIMFs) to generate more high-order modes, adjust the self-focusing length, and improve operation stability of mode-locked fiber laser. The SA also has the advantages of immunity to the external environment variation, high damage threshold and inoxidizability, which make the laser operate stably for a long time.
Active Steering and Driving/Braking Coupled Control Based on Flatness Theory and a Novel Reference Calculation Method

Vehicle handing stability under the combined acceleration steering and braking steering conditions has a great impact on the vehicle safety. Therefore, the coupled steering and driving/braking stability control is essential. Thus, a novel controller based on differential flatness and vehicle stability region is proposed. First, the reference vehicle state variables are calculated and the vehicle stability region is established based on vehicle dynamics and bifurcation analysis. Then, the flatness-based controller is designed which can ensure the vehicle handing stability by controlling the vehicle states approaching their references. Based on the driver preview model, the vehicle can keep good path tracking effect by tracking the lateral deviation. The simulation results of the double lane change tests show that the proposed control method can ensure both the vehicle handing stability and the path tracking effect. Compared to vehicle equipped with the integration of active front steering and direct yaw moment control, vehicle controlled by flatness-based controller performs better in both handing stability and path tracking.
Design of Miniaturized Diamond Shaped Substrate Integrated Waveguide CSRR Band Pass Filter for X Band Applications

In this paper, compact substrate integrated waveguide (SIW) band pass filters (BPFs) incorporated with novel diamond shaped complementary split ring resonator (CSRR) are proposed and analyzed using simulation software HFSS. First single stage SIW BPF is analyzed with face to face orientation of outer ring. Thereafter, a two stage filter is analyzed with similar type of orientation. The filters are simulated using substrate material RT Duroid 5880 with relative permittivity of 2.2 and height 0.508 mm. The proposed two stage SIW BPF exhibits highly selective pass band with center frequency of 8.86 GHz with 3-dB bandwidth of 0.74 GHz. It also exhibits one stop band with rejection peak below −60 dB in close proximity to two transmission poles in the pass band. The two stage SIW filter has better selectivity, bandwidth and stop band performance.
Broadband absorption in Au nanoparticle-decorated chlorophyll b for biophotonic applications

This paper reports a broadband absorption of gold nanoparticle-decorated chlorophyll b. Chlorophyll b was extracted from spinach. Au nanoparticles were synthesized by chemical method. Structural and optical characterization of chlorophyll-b and Au nano-particles were also studied. Current-voltage characteristics of chlorophyll-b and Au nanoparticle-decorated chlorophyll b were also studied by fabricating devices using etched ITO glass. Chlorophyll-b has a strong absorption in the blue region at 435 nm and in the red region at 665 nm, whereas Au nanoparticle has its plasmonic peak at 535 nm. Au nanoparticle-decorated chlorophyll b gives a broad absorption spectrum ranging from 315 nm to 1025 nm due to the interaction between chlorophyll b molecules with Au nano-particles.
Weighted Robust Sage-Husa Adaptive Kalman Filtering for Angular Velocity Estimation

An inexpensive Microelectromechanical systems (MEMS) gyroscope smartphone sensor in a smartphone is considered for angular velocity estimation. The performance of the MEMS gyroscope is substandard due to random errors associated with it. Kalman and adaptive Kalman filters are applied to improve the performance of the MEMS gyroscope estimation. In this paper, a Sage-Husa adaptive Kalman filter (SHAKF) is extented to residual-based estimation of the measurement noise covariance matrix to ensure its positive definiteness. It is complemented by an innovation-based estimation of the process noise covariance matrix to provide numerical stability of the resulting SHAKF. In addition, a Mahalanobis distance-based judging index is proposed within the framework of the SHAKF to reduce the impact of the outliers on the recursive estimation of the angular velocity estimates. Estimation results obtained from measured smartphone data and simulations reveal that the proposed weighted robust Sage-Husa adaptive Kalman filter (WRSHAKF) clearly outperforms the SHAKF in terms of the achievable Allan and standard deviations with low computational complexity.