Miracle-dz/UniFAR-FTUs huggingface dataset:
Topological Interference Management: Trade-off Between DoF and SIR for Cellular Systems

Topological interference management (TIM) allows studying the degrees of freedom (DoF) of partially connected linear interference communication networks, where the channel state information at the transmitters (CSIT) is restricted to the topology of the network, i.e., a knowledge of which interference links are weak and which are strong. In this paper, we consider TIM for an infinite downlink cellular network in the one-dimensional (1D) linear and the two-dimensional (2D) hexagonal models. We consider uniformly distributed users in each cellular cell, effectively creating a continuous distribution of users, aiming to study user classes based on different interference profiles rather than on actual individual users' positions. We also consider the construction of the TIM network topology by analyzing different interference thresholds. Unlike previous works, we use TIM at the user class level to find the system's DoF independent of the actual user position. Finally, after proposing a fractional coloring scheme that can achieve the optimal DoF solution, a trade-off between DoF and SIR is given.
A New Measurement System to Boost the IoMT for the Blood Pressure Monitoring

The paper presents an innovative system for the simultaneous noninvasive monitoring and synchronized storage of the photoplethysmographic (PPG) signals and blood pressure (BP) values. Because it is noninvasive, the proposed monitoring system will permit to achieve signals from both healthy and un-healthy patients and then to create a wide and heterogeneous base of knowledge to properly train automatic classifiers. The final aim is to permit the reliable BP evaluation through the umpteen IoT devices able to acquire the PPG signal, nowadays available on the market. This will permit the BP monitoring every time and every were and then the early diagnosis of several cardiovascular diseases.
Suppression Mechanism of TiO2 for the Partial Discharge of Oil-paper Insulation in Intensive Electric Field

With the rapid development of modern HVDC transmission technology, higher insulation properties are put forward on the oil-paper insulation system of the transformer, which determine the transformer service life to a certain extent. Traditional transformer oil-paper insulation is becoming increasingly difficult to meet the demands of insulation system with large capacity and miniaturization at ultra-high voltage level. In order to improve the insulation strength of oil-paper system, the insulation cellulose paper modified by TiO2 nanoparticles of different diameters (5 nm, 10 nm, 20 nm, 30 nm) were prepared, in addition, each of modified cellulose paper has different mass fraction of TiO2 nanoparticles (1%, 3%, 5%, 7% wt.). The partial discharge (PD) detection platform was established, and the partial discharge inception voltage (PDIV) values of the oil-paper insulation system with and without nanoparticles were measured. To investigate the PD characteristics, the PD waveforms and PD frequency spectrums of modified cellulose paper and the unmodified were obtained. The suppression mechanism of TiO2 nanoparticles on PD was explored through scanning electron microscope (SEM) observation. All the experiment results indicate that adding nano-TiO2 is beneficial to enhance the insulation properties of oil-paper insulation, and the optimum diameter and mass fraction of TiO2 nanoparticles to suppress oil-paper PD were obtained.
A gyroless adaptation of attitude complementary filtering

This article proposes a methodology for estimating the attitude of a rigid body from vector measurements only, i.e. without gyrometers. Classically, two vector measurements are enough to determine the attitude of a rigid body, through an algebraic calculation which is sometimes considered as computationally costly or tedious to implement. Instead, simple observers are often implemented such as the attitude complementary filter, using the feedback of a (possibly biased) gyrometer. What we show in this article is that the angular velocity can be simply estimated with the vector measurements, thus making the gyro redundant. We propose an adaptation of the complementary filter that is simple to implement and gyroless. A proof of convergence is given, and simulation and experimental results are provided.
Measurements with a Quad Band Field Monitor System for UMTS, LTE and WLAN Communications

In this paper, a field measurements monitor system is presented together with a set of measurements. The discussed methodology use an quad-band electric field probe implemented with an antenna. The field monitor is usually installed outdoor, it is equipped with an autonomous power unit and powered jointly by a rechargeable internal battery and directly by solar panels. Four frequency range are available for measurement in real time, day and night, and it covers EGSM, UMTS, LTE and WLAN bands. The presented system is compact in size, simple in design and from anywhere accessible via internet connection. The measured results are in good agreement with theoretical estimations.
The Decoupling Methods for Increasing the Isolation between Two Antennas

This paper presented the parasitic structure decoupling method and other related approaches to increase the isolation between two closely coupled antennas. The design parameters of the resultant decoupling structures based on the proposed methods can be precisely derived instead of fitted to achieve high antenna isolations. A two-element monopole array is employed as a benchmark to demonstrate the effectiveness of the proposed methods. The simulation results show that good impedance matching and high port isolation could be achieved simultaneously based on the proposed methods.
An Omnidirectionally Invisible Artificial Medium

An invisible solid medium in free space requires itself neither reflects nor refracts lights for all incident angles, which has not been found in nature. In this paper, we show that such a medium can be artificially achieved by constructing a mesoscopic building block with independently controllable electrical and magnetic resonances. By precise dispersion engineering, this building block could have both effective unity permittivity and permeability at a specific frequency. Composites consisting of either loosely or densely arranged such blocks can exhibit omnidirectional invisibility in free space, regardless of the shape. 3D sculpture technology was used to fabricate an electrically large aircraft sample for experimental verification. The measured results show that this artificial medium macroscopically exhibits an air-like electromagnetic response at around 5 GHz. The proposed medium can improve mechanical stability, electrical conduction, and heat dissipation of a system, without disturbing the electro-magnetic design.
Capacitorless memory devices using virtual junctions

Electrostatic doping (ED) offers an alternative to chemical doping in nanometer-scale devices. Recent works have shown the applicability of ED in a host of devices based on different materials ranging from Si and ultrahin fully depleted Silicon-on-Insulator layers to carbon nanotubes, graphene, and other 2D semiconductors, specially transition metal dichalcogenides (TMDs) [1] . In this work, we will demonstrate the application of electrostatic doping to form virtual junctions in an undoped ultrathin Silicon on Insulator layer, which can be operated as a memory device.
A Semi-Supervised Synthetic Aperture Radar (SAR) Image Recognition Algorithm Based on an Attention Mechanism and Bias-Variance Decomposition

Synthetic Aperture Radar (SAR) target recognition is an important research direction of SAR image interpretation. In recent years, most of machine learning methods applied to SAR target recognition are supervised learning which requires a large number of labeled SAR images. However, labeling SAR images is expensive and time-consuming. We hereby propose an end-to-end semi-supervised recognition method based on an attention mechanism and bias-variance decomposition, which focuses on the unlabeled data screening and pseudo-labels assignment. Different from other learning methods, the training set in each iteration is determined by a module that we here propose, called dataset attention module (DAM). Through DAM, the contributing unlabeled data will have more possibilities to be added into the training set, while the non-contributing and hard-to-learn unlabeled data will receive less attention. During the training process, each unlabeled data will be input into the network for prediction. The pseudo-label of the unlabeled data is considered to be the most probable classification in the multiple predictions, which reduces the risk of the single prediction. We calculate the prediction bias-and-variance of all the unlabeled data and use the result as the criteria to screen the unlabeled data in DAM. In this paper, we carry out semi-supervised learning experiments under different unlabeled rates on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset. The recognition accuracy of our method is better than several state of the art semi-supervised learning algorithms.
A Survey on LoRa for IoT: Integrating Edge Computing

Increased automation and intelligence in computer systems have revealed limitations of Cloud-based computing such as unpredicted latency in safety-critical and performance-sensitive applications. The amount of data generated from ubiquitous sensors has reached a degree where it becomes impractical to always store and process in the Cloud. Edge computing brings computation and storage to the Edge of the network near to where the data originates yielding reduced network load and better performance of services. In parallel, new wireless communication technologies have appeared to facilitate the expansion of Internet of Things (IoT). Instead of seeking higher data rates, low-power wide-area network aims at battery-powered sensor nodes and devices which require reliable communication for a prolonged period of time. Recently, Long Range (LoRa) has become a popular choice for IoT-based solutions. In this paper, we explore and analyze different application fields and related works which use LoRa and investigate potential improvement opportunities and considerations. Furthermore, we propose a generic architecture to integrate Edge computation capability in IoT-based applications for enhanced performance.
Haptic Compass: Active Vibrotactile Feedback of Physical Object for Path Guidance*

Haptic guidance is an essential research topic of haptic interaction technology. In some conditions, haptic guidance devices could be better at assisting navigation. We developed Haptic Compass, a prototype with active vibrotactile feedback by attaching vibration motors to a cylinder-shaped physical object, to provide directional cues for haptic guidance. To validate the prototype, we conducted two user studies. The first study investigated if users could identify the vibrotactile feedback from the prototype. The results showed that participants could effectively recognize and judge the vibration direction. In the second study, we evaluated the task completion time and the movement error among the Visual-only, Haptic-Only and Haptic-Visual feedback conditions in a typical path-guiding task. We found that, together with visual feedback, haptic feedback could enhance task performance and user experience for direct path guidance. Performance of the two studies demonstrated that our prototype has the potential to be an alternative for applications where non-wearable haptic feedback is desired.
Studying the Mental Effort in Virtual Versus Real Environments

Is there an effect of Virtual Reality (VR) Head-Mounted Display (HMD) on the user's mental effort? In this paper, we compare the mental effort in VR versus in real environments. An experiment $(\mathrm{N}=27)$ was conducted to assess the effect of being immersed in a virtual environment (VE) using an HMD on the user's mental effort while performing a standardized cognitive task (the well-known N-back task, with three levels of difficulty, $N\in\{1,2,3\})$. In addition to test the effect of the environment (i.e., virtual versus real), we also explored the impact of performing a dual task (i.e., sitting versus walking) in both environments on mental effort. The mental effort was assessed through self-report, task performance, behavioural and physiological measures. In a nutshell, the analysis of all measurements revealed no significant effect of being immersed in the VE on the users' mental effort. In contrast, natural walking significantly increased the users' mental effort. Taken together, our results support the fact there is no specific additional mental effort related to the immersion in a VE using a VR HMD.
Design Methodology of Bidirectional Flyback Converter for Differential Power Processing Modules in PV Applications

A bidirectional flyback converter is a suitable topology for a PV-to-bus differential power processing (DPP) module in PV applications because of its electrical isolation capability, bidirectional power transfer, high step-up ratio, and simple circuit structure. Bidirectional flyback converters differ from the conventional flyback converters, which has power switches and snubber circuits on both the primary and secondary sides for bi-directional operations. The poor reverse recovery characteristics of the anti-parallel diode of the secondary (output) side power switch increase the switching loss and reduce the reliability. This paper proposes the design methodology of the bidirectional flyback converter for operating under the boundary conduction mode (BCM), which can show low power loss from the reverse recovery issue. The suitable magnetizing inductance is obtained by calculating the power losses in the bidirectional operation at the rated load. The validity of the proposed design methodology is verified using a 25.6-W bidirectional flyback converter prototype.
Monocular SLAM Position Scale Estimation for Quadrotor Autonomous Navigation

Monocular Simultaneous Localization and Mapping (SLAM) provides a position estimation with an unknown scale factor. The scale factor depends on the initial conditions of the SLAM algorithm so that it is always different. This paper presents a scale factor estimator based on the Immersion and Invariance technique for quadrotor autonomous navigation. The estimator assumes that the quadrotor’s linear velocity, attitude and the applied total thrust are measurable. The estimator performance is validated using numerical simulations and experiments.
Dual-Mode Large-Mode-Area Multicore Fiber With Air-Hole Structure

A novel dual-mode large-mode-area multicore fiber with air-hole structure, which is a quasi-37 core structured fiber with 20 air holes and 17 cores, is proposed in this paper. This fiber can realize strict dual-mode operation, that is, the fundamental mode HE11 and the second-order mode HE21 operation. The air-hole structure makes the second-order modes TE01 and TM01 cut off. Effects of structural parameters on effective refractive index and effective area of fundamental mode are investigated systematically. By optimizing the structural parameters of the fiber, effective area of fundamental mode is up to 1557.91 μm2 and maintaining a low bending loss (less than 10−4 dB/m at R > 0.47 m) while keeping dual-mode operation. The fiber can be used for large-mode-area high-power optical fiber laser, amplifier, FTTH and so on.
Colored-Noise Tracking of Floating Objects using UAVs with Thermal Cameras

Tracking of floating objects using a fixed-wing UAV equipped with a thermal camera requires precise knowledge about the position and attitude of the UAV. Errors in the navigation estimates reduce the accuracy of the tracking system. Navigation errors are usually correlated in time and can propagate colored noise into the tracking filter. This work analyzes two approaches that seek to mitigate colored noise and they are compared experimentally with a third approach which assumes that the noise in the tracking system is purely white. Two independent flight experiments have been carried out where a small marine vessel was used as target. Thermal images of the target were captured and the position and velocity of the target have been estimated in an Earth-fixed coordinate system only using the images. The results show that objects can be tracked with an accuracy of a few meters when measurements are available, and that the estimates do not drift significantly in periods without measurements. Moreover, the results demonstrate that colored noise need to be accounted for in the measurement model to estimate the covariance precisely and maintain filter consistency, which is critical in multi-target tracking.
A UAV-Mountable Flat Array Antenna System

In this paper, we suggest a method to design a small antenna system apt for the attachment to the drone with multi-propellers. Since each of multi-propellers is part of a branch connected to the center of the drone, a flat radial power divider is designed to feed antennas adhering to the propellers, instead of the Wilkinson power divider. For the frequency of 2.4 GHz to build a wireless link between the quadcopter and the ground, the 4-way radial power divider and 4 antennas are designed for the same frequency and light weight.
A Tutorial on Detecting Security Attacks on Cyber-Physical Systems

Cyber-physical systems (CPSs) have become targets for malicious adversaries, creating new challenges for attaining reliable CPS performance. Achieving CPS security requires tools which extend beyond what is offered in state of the art software and cyber security. In this tutorial, we consider a science of CPS security which combines tools from both cyber security and system theory to defend against adversarial behavior. We discuss realistic and intelligent attack models from an adversarial perspective and then present mechanisms for defenders to achieve resilience by recognizing and responding to such malicious behavior. The focus of this tutorial is particularly on the recognition and detection of attacks, which is the first and foremost step in achieving resilience and is a necessary prerequisite to any active response.
A Review on State-of-the-Art Violence Detection Techniques

With the rapid growth of surveillance cameras to monitor the human activity demands such system which recognize the violence and suspicious events automatically. Abnormal and violence action detection has become an active research area of computer vision and image processing to attract new researchers. The relevant literature presents different techniques for detection of such activities from the video proposed in the recent years. This paper reviews various state-of-the-art techniques of violence detection. In this paper, the methods of detection are divided into three categories that is based on classification techniques used: violence detection using traditional machine learning, using support vector machine (SVM), and using deep learning. The feature extraction techniques and object detection techniques of the each single method are also presented. Moreover, datasets and video features that used in the techniques, which play a vital role in recognition process are also discussed. For better understanding, the steps of the research approaches have been presented in an architecture diagram. The overall research findings have been discussed which may be helpful for finding the potential future work in this research domain.
Acute Effect of the Virtual Reality Stimulus in the Performance of Swimmers: A Pilot Study

Virtual reality (VR) consists of the union between an individual and an integrated software and hardware system, where it is virtually transported to a simulated environment. Researches indicates that this technology changes variables related to the individual visual perception and motor capacity. Thus, there are a number of potential explanations for the positive effects encountered by the use of virtual reality in sports that need to be considered. In addition, when VR is used in conjunction with the Motor Imagery (MI) technique, it allows the triggering of a region of the brain responsible for motor activity, even though the action is not actually happening, thus making motor learning possible. This premise was used for developing an application in VR, where an athlete swims in a pool of approximately 20 meters. This application was used to train swimmers. Nine volunteers were divided into two groups, an experimental group (EG) consisting of 5 participants and a control group (CG) consisting of 4 participants. The CG is the group that will provide a standard for evaluation, while the EG is the group that will receive the experiment to be evaluated. EG swimmers received a stimulus through the virtual reality equipment, which increased the number of strokes required to perform the 20 meters front crawl in 10%. On the other hand, the CG witnessed in the VR a stimulus similar to the situation (travel time and number of strokes) of its original performance. Both groups received the same amount of VR stimulus time. After the VR stimulus, it was expected that only the EG obtained changes in the stimulated variables, which did not occur. It was observed that both groups achieved a change in the frequency and in their stroke cycle, but without significant change in their velocity. Although the result was not exactly the expected one, we were able to show that the MI technique in conjunction with VR had an influence on the athlete's performance.
A Miniaturized SIW Triplexer Based on a Triple-Mode Resonator with Slot Perturbation

A miniaturized substrate integrated waveguide (SIW) triplexer with a common triple-mode resonator has been proposed in this paper. The common triple-mode resonator is perturbed by centered cross-shaped slots etched on the top surface of a square SIW cavity. By investigation of surface current distributions on the slot perturbed triple-mode square cavity, the first and second higher-order spurious resonant frequencies can be respectively controlled by each slot, and the fundamental mode frequency is not affected. Meanwhile, the triple-mode resonator has merit of compact size due to slot perturbation. Besides, bandwidths of the three filter channels can be flexibly controlled without extra matching network. Based on systematic analysis of resonant characteristic of the perturbed triple-mode SIW resonator, a triplexer with second-order Chebyshev frequency response at each channel is synthesized and designed. Furthermore, a compact circuit occupation of only approximately 1. 79λg × 1. 19λg has been obtained. The synthesized, simulated and measured results show a good agreement.
Closed-loop Control of a Nonprehensile Manipulation System Inspired by the Pizza-Peel Mechanism

A nonprehensile manipulation system consisting of a dexterous plate (e.g., a peel) which is intended to induce a rotating movement on a disk (e.g., a pizza) is studied. A dynamic model based on the Euler-Lagrange equations is first derived. Then, a controllability analysis of this model is carried out, which shows some intrinsic limitations of the proposed system. Later, a closed-loop control strategy is proposed to induce the desired rotating speed in the disk, while maintaining the position of both the disk and the plate as close to zero as possible. A stability analysis is performed to show the boundedness of all the states, the oscillatory response of all of them, and the maximum amplitude of these oscillations. A numerical simulation is employed to verify the proposed controller and the predicted behavior found in the stability analysis.