Miracle-dz/UniFAR-FTUs huggingface dataset:
High Performance Germanium n+/p Shallow Junction for nano-Scaled n-MOSFET

In this work, we study excimer laser annealing (ELA) on phosphorus-implanted germanium with implantation energies and doses of 30 keV, 5×10<sup>15</sup> cm<sup>-2</sup>, and 10 keV, 5×10<sup>14</sup> cm<sup>-2</sup>, respectively. A lower specific contact resistivity of Al/n<sup>+</sup>Ge and better performance of Ge n<sup>+</sup>/p diode than that obtained by rapid thermal annealing have been fulfilled. Moreover, by a combination of low temperature pre-annealing (LTPA) and ELA, we achieved a Ge n<sup>+</sup>/p diode with a rectification ratio of about 10<sup>7</sup> and decreased phosphorus diffusion in Ge during ELA. A increased activation concentration up to 6×10<sup>19</sup>cm<sup>-3</sup> with a high activation ratio about 85% of phosphorus have been achieved in a low ion implanted dose and energy.
Personality Traits Impacts in Virtual Reality’s User Experience

Psychological aspects of human beings, such as emotions and personality traits, have been investigated in order to improve computer applications and provide adequate responses to each individual. In Virtual Reality environments, specially when reproducing real situations, user experience can be impacted by the way his/her personality traits relates to the environment characteristics. By other hand, these environments are useful to simulate situations that may promote changes in user’s behavior. Although there is a considerable number of researches that establish relationships between personality traits and virtual reality environments, no compilation of them was presented until now. This article aims to fill this gap, presenting a systematic literature review about this theme. A total of 387 articles were retrieved, from which 20 were included in the review, after application of inclusion and exclusion criteria. The main results indicate that user personality traits can influence their user experience with RV environments in various directions, including the perception of immersion and decision making. Additionally, VR environments could be used to help treat people with social disorders.
Physiological Function Assessment Based on Kinect V2

This paper presented a framework based on fog computing for convenient and efficient Physiological Function Assessment, which consists of three parts: 1)measuring the degree of joint mobility; 2) investigating the abnormality of actions of upper limbs; and 3) abnormal gait detection for lower limbs. Especially, we introduced semi-automatic Rapid Upper Limb Assessment (RULA) using Kinect v2 for the upper limb motion evaluation. Since a specific action can be described by action sequences of different length, we used dynamic time warping (DTW) to find the similarity between action sequences with different length. Traditional DTW algorithm does not work well when the action sequences are long and complex. To address this problem, we improved the DTW method by modifying the mapping relationship and limiting the computation space. Our modified DTW algorithm was evaluated on a standard 3D action dataset (SYSU 3D HOI) and Human Upper Action dataset (HUA), achieving the accuracy of 83.75%, 89.50%, respectively. The result is significantly better than the traditional DTW and the reported methods. In our previous work, we described the framework and how to make physiological function assessment. The goal of this paper is to 1) enrich the experiments of previous work and 2) introduce the framework of using RULA for physiological function assessment. All the tests have been done in this framework based on fog computing.
Automatic psoriasis assessment methods: current scenario and perspectives from a metrologic point of view

The assessment of the psoriasis severity in a quantitative way is essential to address the therapy choice as well as to monitor its effectiveness over time. The Psoriasis Area Severity Index (PASI) is currently the most used parameter to assess severity and to define treatment response, however it presents some limitations as, for example, the subjective nature of its assessment relying on a visual examination. The paper presents an overview of the limitations on psoriasis assessment by means of electronic instrumentation and the solutions proposed by research, in these last years.
Performance Analysis of the Revisited Tone Mapped Quality Index for Tone Mapped HDR Images Evaluation

This paper discusses the appropriate choice of the Tone Mapped Quality Index (TMQI) parameters. The TMQI metric has been developed to evaluate and compare the visual quality of the Tone Mapped (TM) High Dynamic Range (HDR) images. However, the parameters of this metric have been adjusted on a specific and reduced set of Tone Mapping Operators (TMO) and a restricted base of HDR images. The visual rendering evaluation of the TM images is then no longer consistent with the metric when new TMO (excluded from the initial training process) are used. To better adjust these parameters, discussions and experiments have been conducted on a large extension of the initial TMOs set and tone mapped HDR images dataset. The new parameters show a strong correlation between the revisited metric and the Mean Opinion Score (MOS).
The Shannon Capacity of Linear Dynamical Networks

Understanding the fundamental mechanisms enabling fast and reliable communication in the brain is one of the outstanding key challenges in neuroscience. In this work, we address this problem from a systems and information theoretic perspective. Specifically, we first develop a simple and tractable framework to model information transmission in networks driven by linear dynamics. We then resort to the notion of Shannon capacity to quantify the information transfer performance of these networks. Building on this framework, we show that it is possible to increase Shannon capacity via two fundamentally different mechanisms: either by decreasing the degree of stability of the network adjacency matrix, or by increasing its degree of non-normality. We illustrate and validate our findings by means of simple, insightful examples.
Experimental Investigation of Millimeter-Wave MIMO Channel Characteristics in Tunnel

A 28 GHz millimeter-wave (mm-wave) propagation measurement campaign was performed to predict the multiple-input multiple-output (MIMO) channel performance in a tunnel environment. Two kinds of polarization configurations were studied in this paper. In order to overcome the serious path loss (PL) of mm-wave propagation, a high gain directional horn antenna was used in the measurements of tunnel environment. The measurement results and simulation results at same specific locations are compared. The result of comparison indicates that the simulation model matches the measurement well. Then the MIMO capacity at other locations of the tunnel can be predicted by the simulation model. Further-more, it is inferred that the antenna array elements of horizontally polarized configuration have higher capacity than the vertically polarized under the constant signal-to-noise ratio (SNR).
Partial Discharge Measurements on Dibenzyltoluene for High Temperature Encapsulant Application up to 350°C

Partial discharges characterization on ceramic substrates and dielectric liquids under high temperature up to $350^{\circ}\mathrm{C}$ is investigated. Aluminum nitride (AlN) and alumina (Al2O3 substrates, and a high temperature non-polar dibenzyltoluene (DBT) liquid are used. Several complementary measurements are also done in a synthetic ester liquid. PD measurements on AlN substrates embedded in DBT show a good behavior up to $300^{\circ}\mathrm{C}$, and up to $350^{\circ}\mathrm{C}$ with Alumina. This shows that high temperature insulating liquid may constitute a good alternative to silicone gels for the encapsulation of power electronics circuits at high temperature and high voltage. The comparison between PD characteristics in the liquid alone and with substrates show that PDs mostly occur within the ceramic material at temperatures up to $300^{\circ}\mathrm{C}$.
Cooling Performance Of Different Dielectric Fluids Containing Nanoparticles in a Transformer Winding

This work presents a study where the thermal performance of different nanofluids is tested in a transformer winding model. A 2D axisymmetric non-isothermal CFD model has been used to compare temperature and velocity distribution of the proposed fluids. The fluids tested consists of eight different mixtures manufactured from two different nanoparticles and two different concentrations, using a mineral oil and a natural ester as base liquids. The comparison has been carried out between each nanofluid and their base fluid to observe the thermal impact of nanoparticles. The temperature dependent properties have been determined to include them in the simulation model. Two different inlet velocities were selected as inlet conditions, representing Oil Natural and Oil Directed Cooling. The analysis has been carried out using ANSYS Fluent® in a two pass winding model. The average and maximum disc temperatures and mass flow distributions are obtained for all the cases. The results obtained show that the temperature in the seven discs of the considered winding increases when the nanoparticles are added to the natural ester, between 3 and 7%. On the other hand, in the case of mineral oil, the addition of nanoparticles reduces the temperature in the discs between 0.3 and 3%.
Quantized Massive MIMO Networks Under Channel Correlation and CSI Mismatch

This study examines the performance of the multi-user multiple-input-multiple-output (massive MIMO) systems with 1-bit, 2-bit and 3-bit analogue to digital converters (ADCs) under channel correlation and channel state information (CSI) errors. The OFDM modulated uplink with QPSK, 16QAM and 32QAM schemes are considered for the communication between the base station (BS) and the user equipment (UEs). The BS antenna array is assumed to be uniform linear (1D) or uniform rectangular (2D) arrays. Zero-Forcing (ZF) receiver has been employed by the BS due to its simplicity and superior performance over other linear receivers. Furthermore, we consider the square root raised cosine filter (SRRC) to enhance the performance of the low-resolution ADC systems. The results show that the resolution of ADCs mainly determines the modulation scheme and having a high-level channel correlation or CSI mismatch requires a higher resolution ADCs. Furthermore, it has been shown that the SRRC filter enhances the system performance even with low-resolution ADCs.
Rod-shaped payload transportation using multiple quadrotors

Aiming to address and contribute to the topic of load transportation using aerial vehicles, this work presents a cooperative system using two quadrotors to carry a rod-shaped load. The problem is dealt with as a virtual-structure formation, considering the load and quadrotor as a line formation that needs to be accomplished. The load is carried as a cable-suspended one, and a nonlinear controller based on feedback linearization is employed to fulfill the mission requests while minimizing the load oscillations. Experiments were conducted using two AR.Drone 2.0 quadrotors, carrying an aluminum rod. The paper presents the results of such experiments in illustrations and videos, showing the good performance of the proposed algorithms, thus validating them.
Trajectory-tracking of a Heterogeneous Formation Using Null Space-Based Control

This work discusses a trajectory tracking task accomplished by a formation of two heterogeneous robots, namely a Pioneer 3-DX (UGV) and an AR.Drone 2.0 quadcopter (UAV). The control paradigm considers the formation as a virtual structure, here represented by a 3D straight line linking the two agents. The formation is characterized by the distance between the two robots and two angles, measured between the linking-line and the YZ and XZ planes. In this approach, the formation position coincides with the UGV position. The transformation between the robot to formation variables allows characterizing the motion and shape of the formation starting from the movement of the robots, or vice-versa. Then, a controller guides the formation and manages two conflicting subtasks (reach the desired robot position or keep the formation shape), whose priority is defined by the null space-based approach. Finally, real experiments validate the proposed approach during trajectory-tracking tasks for three scenarios, one assigning the highest priority to the formation position, another to the formation shape, and a last one, without any priority. In addition, we evaluated the formation behavior in failure situations in one of the robots.
vProVal: Introspection based Process Validation for Detecting Malware in KVM-based Cloud Environment

In the modern era of computing, Cloud security is of paramount importance. Most of the research mainly focused on In-Virtual Machine (VM) security techniques for detecting malware affecting virtual domains running in the Cloud. In-VM security techniques are deployed inside the VM and hence they are very much prone to subversion attacks. In this paper, an-VM monitoring approach based on introspection, called vProVal, is proposed. The vProVal is designed to detect the hidden processes and rootkits that disable the security tool, running in the monitored VM in Kernel VM (KVM)-based cloud environment. It performs the malware detection from outside the VM at the KVM-layer and hence more robust to attacks. The introspection technique used is to extract the low-level details of a running VM from hypervisor by viewing its memory, trapping on hardware events, and accessing the vCPU registers. A preliminary analysis has been performed and the approach is found to be promising.
Trajectory Optimization and Orbital Stabilization of Underactuated Euler-Lagrange Systems with Impacts

A numerical framework for finding and stabilizing periodic trajectories of underactuated mechanical systems with impacts is presented. By parameterizing a trajectory by a set of synchronization functions, whose parameters we search for, the dynamical constraints arising due to underactuation can be reduced to a single equation on integral form. This allows for the discretization of the planning problem into a parametric nonlinear programming problem by Gauss-Legendre quadratures. A convenient set of candidates for transverse coordinates are then introduced. The origin of these coordinates correspond to the target motion, along which their dynamics can be analytically linearized. This allows for the design of an orbitally stabilizing feedback controller, which is also applicable for degrees of underactuation higher than one.
Three-dimensional Multiple Signal Classification (3D-MUSIC) for Super-resolution FMCW Radar Detection

Three-dimensional multiple signal classification (3DMUSIC) algorithm is introduced to implement super-resolution detection in azimuth, elevation, and range directions. In implementing this algorithm, 3D spatial smoothing is applied to solve the deficient rank of the covariance matrix due to coherent echoes. Performance of this algorithm is numerically investigated based on a uniform area FMCW radar array. Simulation results show that, this 3D-MUSIC algorithm achieves super-resolution detection and performs much better than the digital beamforming (DBF) method. Based on this 3D-MUSIC algorithm, a potential application for target recognition is also demonstrated.
Comparison in Depth Perception between Virtual Reality and Augmented Reality Systems

The virtual reality (VR) and augmented reality (AR) applications have been widely used in a variety of fields; one of the key requirements in a VR or AR system is to understand how users perceive depth in the virtual environment and augmented reality. This paper conducts an experiment to compare users' performance of depth perception in VR and AR system using an optical see-through head-mounted display (HMD). The result shows that the accuracy of depth estimation in AR is higher than in VR. Besides, the matching error increases as the distance becomes farther.
Energy-Efficient Resource Allocation With Hybrid TDMA–NOMA for Cellular-Enabled Machine-to-Machine Communications

Machine-to-machine (M2M) communications, which are considered as an integral part of the Internet of Things (IoT), are being more and more ubiquitous. Meanwhile, due to the advantages of cellular networks (e.g., excellent coverage and mobility/roaming support), cellular-enabled M2M communication is a promising solution for M2M-based applications. However, there are significant challenges in cellular-enabled M2M communications due to the special features of M2M-based applications [e.g., massive concurrent uplink transmissions, small bursty traffic, and the high requirements of energy efficiency (EE)]. On the other hand, non-orthogonal multiple access (NOMA) can simultaneously serve multiple users at the same frequency and time by splitting different users in the power domain and thus increase the number of concurrent connections. In this paper, we propose an energy-efficient resource allocation scheme with hybrid time division multiple access (TDMA)–non-orthogonal multiple access (NOMA) for cellular-enabled M2M networks. First, we configure the user equipments (UEs) as the machine type communication gateways (MTCGs). Then, we propose our time sharing scheme. Next, we formulate the resource allocation problems as a noncooperative game. Finally, in order to obtain the optimal EE of machine type communication devices (MTCDs) and UEs in the game to confirm the power allocation, we transform each non-convex optimization problem into the convex form by using nonlinear fractional programming and solve the transformed problem by Dinkelbach’s method and Lagrangian duality theory. The simulation results show that our scheme can dramatically shorten the total transmission time at the cost of a little more total energy when compared to the existing works.
New results on the eigenstructure assignment in the computation of reachability output nulling subspaces

This paper provides a system theoretic investigation of the building blocks of the supremal output-nulling, reachability and stabilizability subspaces that are obtained from the eigenstructure assignment approach based on projecting the bases of the null-spaces of the Rosenbrock matrix pencil on the state space. In particular, we show that the use of a certain set of eigenvalues to build such bases guarantees that their span is the largest output-nulling subspace of the system such that the closed-loop mapping restricted to it has exactly these eigenvalues, and that all the output-nulling subspaces constructed in this way share the same reachability subspace. This paper also casts some light onto the fact that, even if these building blocks depend on the values of the indeterminate used to compute the kernels of the Rosenbrock matrix, the dimension of their sums for different values is independent of the specific values of the indeterminate.
Collaborative Beamforming for Cognitive UAV Relaying System Coexisting with Satellite Networks

In this paper, we study a cognitive unmanned aerial vehicle (UAV) relaying system (CURS) which shares the downlink frequency of a satellite network. Specifically, we propose a collaborative beamforming (CBF) scheme that maximizes the signal-to-interference plus noise ratio (SINR) of CURS, subjects to the SINR requirements of the satellite network and the individual transmit power constraints of UAV relays. Since the original optimization problem is non-convex and mathematically intractable, we first transform it into an approximate convex one by means of the Charnes-Cooper transformation and the penalty function method as well as the difference of two-convex functions (D.C.) approach. Then a convergence proven iterative algorithm is designed to find the optimal CBF solution. Simulation results are provided to demonstrate the effectiveness of the proposed scheme and the impact of UAV transmit power and satellite network SINR requirements on the CURS.
A Review of Human- and Computer-Facing URL Phishing Features

When detecting phishing websites, both humans and computers rely on aspects of the website (features) to aid in their decision making. In this work, we conduct a review of URL-based phishing features that appear in publications targeting human-facing and automated anti-phishing approaches. We focus on both humans and computers to obtain a more comprehensive feature list and create a cross-community foundation for future research. We reviewed 94 papers and categorise their features into: lexical, host, rank, redirection, certificate, search engine, and black\textbackslash white lists. We find that research on automation has used all feature categories but several, such as host-based features (e.g. DNS), are minimally explored in human-facing anti-phishing research.
Multi-Ray Jumping: Comprehensible Group Navigation for Collocated Users in Immersive Virtual Reality

The collaborative exploration of virtual environments benefits from joint group navigation capabilities. In this paper, we focus on the design and evaluation of a short-range teleportation technique (jumping) for a group of collocated users wearing head-mounted displays. In a pilot study with expert users, we tested three naïve group jumping approaches and derived the requirements for comprehensible group jumping. We propose a novel Multi-Ray Jumping technique to meet these requirements and report results of two formal user studies, one exploring the effects of passive jumping on simulator sickness symptoms $(N=20)$ and a second one investigating the advantages of our novel technique compared to naïve group jumping $(N=22)$. The results indicate that Multi-Ray Jumping decreases spatial confusion for passengers, increases planning accuracy for navigators, and reduces cognitive load for both.
Towards a Weather Analysis Software Framework to Improve UAS Operational Safety

Unmanned Aerial Systems (UAS) operations are evolving towards autonomous flight beyond visual line of sight (BVLOS), which requires moving assessments normally conducted by the remote pilot to the autonomous software. An important assessment currently conducted by the remote pilot is whether the current weather conditions pose a safety risk to the flight. This work deals with the development of a software framework for analysing weather data. The developed framework is capable of providing a weather analysis report to a remote supervisor or to an autonomous decision-making software. The software framework has been tested using historical weather data for a full calendar year provided by IBM. The weather data was applied to four different UAS ranging from small UAS to a passenger UAS. The results obtained show that during a full year, flight was possible from 53.9 % to 95.8 % of the time depending on the UAS. We consider the software framework an important step towards improving the operational safety for autonomous UAS operations under BVLOS conditions.
Observer-based Diagnosis in Chemical Reaction Networks

This paper proposes a method to diagnose unexpected changes in the dynamic behavior of Chemical Reaction Network models. It is considered that the disturbances can induce changes in the reaction rate coefficients of chemical reactions. Conditions for the estimation of such disturbances are formulated. Using the algebraic properties of kinetic models, on-line observers are designed to monitor the disturbance-generated modifications in the reaction rate coefficients. An extended disturbance observer is also introduced for such cases when not all the states of the Chemical Reaction Network are measurable. The applicability of the developed method is shown through simulation studies.