Miracle-dz/UniFAR-FTUs huggingface dataset:
Human localization and tracking system based on multiple depth cameras in VR Scene

Reliable and accurate human localization and tracking systems is one of key technologies in virtual reality (VR). However, the traditional 2D object detection method is vulnerable to the changes in illumination, complex background, object occlusion, shadow interference and other factors, leading to poor robustness in the real world detections. To solve this problem, this paper proposes a human positioning and tracking system based on advanced multi-depth cameras. Multiple 3D TOF intelligent depth cameras are utilized to work coordinately, combining the Histograms of Oriented Depth (HOD), to extract human head and shoulder features. Then, a SVM classifier is used to achieve the target detection, followed by the improved Cam-shift algorithm for tracking real-time single target. Experimental results show that the system has high real-time performance and accuracy, providing a competitive solution for VR applications.
Registration of Color Point Cloud by Combining with Color Moments Information

With the development of RGB-D sensors, the highquality color point cloud can be obtained conveniently. Besides the geometrical information of point cloud, the color has great potential to assist the point cloud registration. In this paper, we propose a registration method by adaptively combining with color moment information to improve the registration accuracy. Firstly, three kinds of central moments are used to characterize the color distribution of two point clouds. And then, we build the correspondence between point clouds by dynamically combining the geometric feature and color moment feature of each point, hence the corresponding points satisfy both geometric similarity and color similarity. Finally, for the partial registration problem in practice, we apply the trimmed ICP algorithm framework to calculate the rigid transformation. Experimental results demonstrate that our algorithm is more robust and accurate in dealing with point cloud geometry defects, missing data and poor initial position.
Optimal sampling of multiple linear processes over a shared medium

In many emerging applications, multiple sensors transmit their measurements to a remote estimator over a shared medium. In such a system, the optimal sampling rates at each sensor depend on the nature of the stochastic process being observed as well as the available communication capacity. Our main contribution is to show that the problem of determining optimal sampling rates may be posed as a network utility maximization problem and solved using appropriate modifications of the standard dual decomposition algorithms for network utility maximization. We present two such algorithms, one synchronous and one asynchronous, and show that under mild technical conditions, both algorithms converge to the optimal rate allocation. We present a detailed simulation study to illustrate that the asynchronous algorithm is able to adapt the sampling rate to change in the number of sensors and the available channel capacity and is robust to packet drops.
Teaching Students About Machine Learning Through a Gamified Approach

The teaching of machine learning requires a range of tools and techniques to engage students and allow them to relate the processes involved to real world situations that they have previously experienced. One way to facilitate this learning process is to integrate the learning into a game situation, which is by definition fun to engage with and offers immediate rewards. This research shows that by collecting the student's behaviour and actions as they engage with well-known game software, the learning of key machine learning concepts can be enabled. It is also shown that customising of learning can be made possible by the use of gamification.
A Low-Cost Ka-Band Circularly Polarized Passive Phased-Array Antenna for Mobile Satellite Applications

This paper presents a low-profile, high-performance, and low-cost <italic>Ka</italic>-band circularly polarized (CP) passive phased-array antenna (PAA) system. A <inline-formula> <tex-math notation="LaTeX">$1\times 4$ </tex-math></inline-formula> passive subarray operating at the <italic>Ka</italic>-band frequency band is investigated, developed, and tested as a possible building block for mobile satellite communication systems. In particular, a CP antenna integrated with a high-performance passive phase shifter is presented and experimentally verified. A new low-cost and low-profile magnetic actuator is proposed to precisely control the phase state of the phase shifter. A 3-D printed polymer package is utilized to enclose the phase shifter and reduce the environmental effects. The proposed CP passive PAA achieves high-performance right-hand CP radiation with high cross-polarization discrimination over a wide scan angle from 0° to ±38° over the frequency band (29.5–30.5 GHz). An axial ratio (AR) < 3 dB is demonstrated over the entire scanning range. Moreover, the measured radiation efficiency is 60% at boresight. The gain drops by 1 dB at ±38° scanning angles.
Observer-Based Super-Twisting Sliding Mode Control with Fuzzy Variable Gains and its Application to Overactuated Quadrotors

In this paper, we propose an observer-based super-twisting sliding mode control with fuzzy variable gains (OST-FVG) for general second-order nonlinear systems. First, the super-twisting observer with fuzzy variable gains is designed for state estimation, for which we show finite-time convergence of the estimation error to zero under the bounded disturbance. Then, together with the proposed observer, the sliding mode control with fuzzy variable gains is designed to ensure precise tracking control performance and to alleviate the chattering phenomenon. We apply the OSTFVG to the overactuated quadrotor modeled by the second-order nonlinear system within the quaternion framework, which resolves underactuation and singularity problems appeared in standard quadrotors. In simulation results of attitude and position control, the fuzzy mechanism implemented in the OSTFVG guarantees faster convergence of the quadrotor to the desired position and more precision tracking performance compared to the standard observer-based super-twisting sliding mode control.
Distributed Robust Dynamic Average Consensus with Dynamic Event-Triggered Communication

This paper presents the formulation and analysis of a fully distributed dynamic event-triggered communication based robust dynamic average consensus algorithm. Dynamic average consensus problem involves a networked set of agents estimating the time-varying average of dynamic reference signals locally available to individual agents. We propose an asymptotically stable solution to the dynamic average consensus problem that is robust to network disruptions. Since this robust algorithm requires continuous communication among agents, we introduce a novel dynamic event-triggered communication scheme to reduce the overall inter-agent communications. It is shown that the event-triggered algorithm is asymptotically stable and free of Zeno behavior. Numerical simulations are provided to illustrate the effectiveness of the proposed algorithm.
Development of new flexible dry electrode for myoelectric sensor using conductive silicone

This paper reports the development of a new electromyography (EMG) sensor for the myoelectric prosthetic hand. The myoelectric prosthetic hand is controlled by EMG which is detected from the surface of human skin. Our study focuses on the dry type sensor with flexible adhesion material to fit to the skin surface instead of metal electrodes. The developed electrode consisted of silicone and conductive silicone blended with conductive carbon black. These electrodes were mounted on myoelectric prosthetic hands that were applied to perform the Pick and Place Tasks to test the total performance of the control system. The results showed that the developed material obtained a thinner sensor than the conventional ones, which enabled it to naturally trace to the subject’s forearm shape without burden on the skin.
Smart Mirror - a Secured Application of Artificial Intelligence Recognizing Human Face and Voice

Smart mirrors are a brand new addition to the IoT product family that has been obtaining a great deal of attention in recent years by each industrial makers and hobbyists. This paper describes the planning associated implementation of a voice controlled wall mirror, referred to as “Magic Mirror” with Artificial Intelligence for the home environment. It is a mirror, which can display real time content like time, date, weather and news at the same time. The Magic Mirror consists of functionalities like real time information and data updates, voice commands, face recognition. The user can control the magic mirror by voice commands.
Object Detection in Aerial Images Based on Cascaded CNN

—Object detection in aerial images is widely used for military applications, such as reconnaissance, target surveillance, battle damage assessment, et al. However, the tasks are very challenging due to a lot of factors, such as illumination variance, scene complexity, and platform motion. To deal with these problems, a new cascaded convolutional neural network (CNN) model for object detection from airborne videos is proposed. The proposed framework adopts a cascaded structure with three levels of deep CNNs that predict objects in a coarse-to-fine manner. The experimental results showed that the proposed method can achieve better performance.
Via-Less Waveguide to Microstrip Line Transition with Tolerance to Misalignment of Circuit Patterns

We propose a via-less waveguide to microstrip line transitions for automotive millimeter wave radar modules. Multi-stage impedance transformers are adopted for impedance matching and suppression of undesired radiation. In order to overcome output amplitude and phase error due to misalignment of circuit patterns, we add just one pair of stubs to the transition. We demonstrate the proposed transition with the stubs drastically stabilizes output amplitude and phase.
A Discontinuous Charging Technique with Programmable Duty-Cycle for Switched-Capacitor Based Energy Harvesting Circuits in IoT Applications

This paper presents a discontinuous charging technique for switched-capacitor (SC) converters that delivers current in bursts to the load. The purpose of the proposed approach is to improve power conversion efficiency(PCE) at low ambient input power in energy harvesting circuits for Internet of Things applications. Current is delivered to the load only during non-overlap time $\pmb{(\text{t}_{\text{NOL}})}$. The $\pmb{\text{t}_{\text{NOL}}}$ time, and consequently the clock duty cycle, are programmed to control the average power delivered to the load based on ambient power levels, as opposed to battery voltage level in existing chargers. This allows the system to tune the maximum PCE to the expected, application-specific, ambient power levels. The circuit is modelled and designed in 90nm CMOS process. For a given 40k! Ω load, the proposed discontinuous system achieves 71.5% peak power conversion efficiency at 6.87uW input power when operating at 258KHz with 10% $\mathbf{t}_{\pmb{\text{NOL}}}$. Compared to continuous SC charging, the proposed design achieves the same peak power conversion efficiency at 78% less input power.
Corner Truncated Patch Circularly Polarized Antenna for UHF RFID Applications

This paper presents a design of corner truncated patch circularly polarized antenna for UHF RFID applications. The corner truncated patch antenna is proposed for circularly polarized radiation for UHF RFID applications. The corner truncated patch circularly polarized antenna is 20cm, 20cm and 1.327cm in width (W), length (L) and height (ha), respectively, to propagate the UHF RFID frequency band of 920-925MHz. The radiating patch and ground plane was designed form single sided PCBs with exposed FR-4 substrate. The corner truncated patch and ground plane were placed parallel to each other using air as an intermediary. Antenna simulation results are used to determine the optimal proposed antenna parameters and a circularly polarized antenna are fabricated and exhaustively tested, respectively. The simulated and measured antenna gains are 8. 49dBi and 7. 68dBi, respectively. The simulated and measured HPBW in the XZ-plane and YZ-planes are greater than 65°. And the axial ratio $(AR)\le 3dB$ cover the operating frequency band. The results of simulated compared with the measured are show good agreement. In addition, the proposed antenna is suitable for UHF RFID reader applications.
Design and analysis of a biomolecular positive-feedback oscillator

Nonlinear relaxation oscillators in engineering rely on positive feedback to operate. One category of relaxation oscillators is given by astable multivibrators, that include a bistable component at the core of their architecture. Here we describe a molecular network motif that operates as an astable multivibrator, and relies on a bistable switch (the classical Gardner and Collins genetic switch) that is toggled between its stable steady states by a persistent input. We show that oscillations arise in the presence of two negative feedback loops that process the persistent input and influence the production of the molecular species forming the bistable subsystem. We perform a thorough stability analysis of this motif obtaining closed-form practical conditions for the emergence of oscillations, and we examine the sensitivity of the system to parameter variations.
Analytical Survey on Wearable Sensors in Monitoring Physiological Responses and Vital Signs

Remarkable achievements in medical sciences have led to a considerable improvement in the quality of life. Moreover, innovative opportunities have come to light due to the combined effect of miniaturized sensor technologies, wearable electronics, and big data analysis which, in turn, have paved the way for a better healthcare. In this revision paper, efforts of authors have been made in order to discuss unparalleled accomplishments and new technological advancements on wearable sensors. These sensors which operate without a need for direct wire or power and can be mounted on the skin, pupil, and teeth have been reviewed in this research. Finally, this paper have fully evaluated the wearable biocompatible materials that can monitor body temperature, heart rate, brain activity, muscle dynamics and other important vital signs of the patient and their current restrictions.
Preparation of TiO2/Single Layer Grapgene Composite Photoanodes for Dye-Sensitized Solar Cells

Dye-sensitized solar cells (DSSCs) are low-cost, simple process and promising solar cells. Single Layer Graphene(G) have good electrical conductivity, mechanical and thermal stability, and can be used as the photoanode material for DSSCs. In this study, the DSSCs were fabricated byTiO2/G composites, and compared with the properties of DSSCs which fabricated by different concentrations of Single Layer Graphene. Then the Single Layer Graphene were dispersed and fabricated into the DSSCs, compared with the DSSCs which fabricated by undispersed Single Layer Graphene. Finally, theTiO2 film and theTiO2/G film were mixed coating, and analyzed the effect of different coating sequences on DSSCs. The results indicate that Single Layer Graphene can provide a direct transmission pathway for electrons, which can enhance the transmission speed of electron and reduce the electron/hole recombination. The DSSCs fabricated by theTiO2 film and theTiO2/G film had the highest efficiency 3.6%. The DSSCs prepared by mixing theTiO2/G film with theTiO2 film can slightly improve the efficiency of the dye-sensitized battery. Compared with the DSSCs prepared fromTiO2 film, the efficiency increases slightly and the efficiency is 3.36%.
Prevention of Timing Attack in Software Defined Named Data Network with VANETs

Software Defined Network (SDN) is getting popularity both from academic and industry. Lot of researches have been made to combine SDN with future Internet paradigms to manage and control networks efficiently. SDN provides better management and control in a network through decoupling of data and control plane. Named Data Networking (NDN) is a future Internet technique with aim to replace IPv4 addressing problems. In NDN, communication between different nodes done on the basis of content names rather than IP addresses. Vehicular Ad-hoc Network (VANET) is a subtype of MANET which is also considered as a hot area for future applications. Different vehicles communicate with each other to form a network known as VANET. Communication between VANET can be done in two ways (i) Vehicle to Vehicle (V2V) (ii) Vehicle to Infrastructure (V2I). Combination of SDN and NDN techniques in future Internet can solve lot of problems which were hard to answer by considering a single technique. Security in VANET is always challenging due to unstable topology of VANET. In this paper, we merge future Internet techniques and propose a new scheme to answer timing attack problem in VANETs named as Timing Attack Prevention (TAP) protocol. Proposed scheme is evaluated through simulations which shows the superiority of proposed protocol regarding detection and mitigation of attacker vehicles as compared to normal timing attack scenario in NDN based VANET.
Optimized Parameters on Enhanced Precision of Image Matching in UAS Photogrammetry

Due to the improvement of computer processing efficiency, the UAS aerial mapping map can simultaneously acquire a large amount of three-dimensional dense point cloud data, and has gradually replaced the traditional mapping efforts of a large number of manpower and material resources with a total station in recent year. The general UAS aerial surveying is used the multi-view image processing technology combined with the Structure from Motion algorithm, which aligning the multiple photos into a true orthomosaic through image processing. However, several parameters that need to be set during the processing, and these parameter settings affect the accuracy of the subsequent processing of image results more or less. In the past, a better precision result obtaining by trying error, it often wasted a lot of time and resources.In order to overcome the above problems, this study uses Agisoft Photoscan software as the image processing software. The Taguchi method with 23 control factors was introduced to the pre-process at obtaining the accuracy report for deriving the optimized setting of those parameters. According to the characteristics of each factor select 2 or 3 levels, through the 211X312 orthogonal table for 36 experiments. Each experiment was processed by PhotoScan software and the quality and accuracy of the two checkpoints were evaluated based on the level and vertical accuracy of the output. The results show that, the first three items among the 23 factors that affect the accuracy control are Disable Cameras Quality below, AGL and Align Photos-Advanced Tie Point limitation, respectively. The less affect the accuracy of control point has 6 items. This research can provide the basis for parameter setting during subsequent image preprocessing.
Nash Equilibrium Seeking with Second-Order Dynamic Agents

Game with second-order dynamic agents is explored for the case where the payoff function of each agent is concave and continuously differentiable. Several control laws that seek the Nash equilibrium by utilizing only the knowledge of each agent's payoff function are proposed. We use the results from a convex optimization framework to derive our control laws. We illustrate our approach with a numerical example.
Cloud-Supported Self-Triggered Control for Multi-Agent Circumnavigation

In this paper, we propose a cloud-supported control framework for multi-agent circumnavigation missions. We consider a network of planar autonomous agents. Our objective is for the agents to circumnavigate a target with a desired angular speed, while forming a regular polygon around the target. We propose self-triggered rules to schedule the bearing measurements and the cloud accesses for each agent.
Beamforming mmWave MIMO: Impact of Nonideal Hardware and Channel State Information

In this paper, we analyzed the impact of residual hardware impairments on the performance of different beamforming millimeter wave (mmWave) Multiple-Input Multiple-Output (MIMO) architectures. By modeling the residual impairments as a additional distortion noise, expression for the capacity for both hybrid beamforming and analog RF beamforming mmWave MIMO is obtained. For the analog RF beamforming, an analytical upper bound is derived. Additionally, the effect of nonideal channel state information is investigated. Performance of the beamforming mmWave MIMO are assessed through Monte Carlo simulations. Results confirm that hardware impairments are limiting the systems performance.
Sparse Bayesian Learning Based Space-Time Adaptive Processing Against Unknown Mutual Coupling for Airborne Radar Using Middle Subarray

Sparse-recovery-based space–time adaptive processing (STAP) methods can exhibit superior clutter suppression performance with limited training data. However, the clutter suppression performance seriously degrades when the mutual coupling is present in the STAP array elements. In this paper, a sparse Bayesian learning (SBL)-based STAP method against the mutual coupling by using the middle subarray is proposed. Specifically, the mutual coupling matrix (MCM) of the STAP uniform linear array is approximately described as a banded symmetric Toeplitz matrix since the effect of mutual coupling between two array elements is inversely related to their distance and can be negligible when their distance is larger than a few wavelengths. Utilizing this specific structure of the MCM, a mutual coupling mitigation method is developed for STAP by rearranging the received snapshots with the designed spatial–temporal selection matrix. Then, to efficiently recover the clutter angle-Doppler profile, the modified fast converging SBL (FCSBL) named adaptive FCSBL algorithm and its multiple measurement vector case adaptive MFCSBL algorithm are developed with only partial hyper-parameters being updated in a single iteration. The proposed method not only achieves the superior clutter suppression performance in the presence of unknown mutual coupling, but also has low computational load. The simulation results are implemented to validate the effectiveness of the proposed methods.
Uni-directional Antenna using a Probe-Fed Open Waveguide with Two-Stacked-Coupling Aperture

This paper presents a design of symmetrically unidirectional beam antenna implemented by a probe-feed open waveguide with two-stacked-coupling aperture as a primary feed for parabolic reflector. This proposed antenna is able to rectify the asymmetry bi-directional beam and also achieves a symmetrically uni-directional beam through the influence of two-stacked-coupling aperture. The antenna geometry is composed of a radiating rectangular waveguide vertically jointed to the two open-end waveguides of an identical widthwise (i.e., an open-end waveguide stacked on top and the other underneath) the radiating section to induce the radiation beamwidth. The radiating rectangular waveguide is excited by a linearly probe with an attached circular disc. To design the antenna, its parameters are investigated by using an electromagnetic microwave simulator. In the analysis, the probefeed open waveguide without and with stacked-coupling-aperture are demonstrated. Apparently, this antenna operates the WLAN frequency band of 2.4--2.5 GHz with the magnitude of S11 better than -10 dB. The simulated half-power beamwidths in both the ${E-} $ and H-planes are equal 70° with the maximum gain of 7.1 dBi. The results will be reported and discussed in the paper.