Miracle-dz/UniFAR-FTUs huggingface dataset:
Remapped Physical-Virtual Interfaces with Bimanual Haptic Retargeting

This paper proposes a novel interface for virtual reality in which physical interface components are mapped to multiple virtual counterparts using haptic retargeting illusions. This gives virtual reality interfaces the ability to have correct haptic sensations for many virtual buttons although in the physical space there is only one. This is a generic system that can be applied to areas including design, interaction tasks, product prototype development and interactive games in virtual reality. The system presented extends existing retargeting algorithms to support asymmetric bimanual interactions. A new warp technique, called interface warp, was developed to support remapped virtual reality user interfaces. Through an experimental user study, we explore the effects of bimanual retargeting and the interface warp technique on task response time, errors, presence, perceived manipulation compared to unimanual (single handed) retargeting and other existing warp techniques. The results demonstrated faster task response time and less errors for the interface warp technique and shows no significant effect of bimanual interactions.
Electron Self-Trapping in Vortex Rings in Superfluid Helium

The mobility of electrons injected in the majority of nonpolar dielectric liquids is a few orders of magnitude higher than the mobility of positive ions. However, the behavior of electrons in liquid helium is anomalous. The electron mobility is a few orders of magnitude lower than the value expected according to the classical Langevin theory and even a few times lower than the mobility of positive ions. The reason is that it is energetically favorable for an electron to be localized in nanobubble owing to a strong exchange repulsion from helium atoms. In addition to ordinary electron bubbles, two more types of negative charge carriers were discovered many years ago in superfluid helium: “fast” and “exotic” ions. The mobility of fast ions is approximately seven times higher than the mobility of electron bubbles, whereas the mobility of a family of exotic ions (more than ten members) lies between these two values. In the present work a model according to which fast and exotic negative ions in superfluid helium represent the localized states of electrons in vortex rings is presented. The quantization of radial and longitudinal motions of electrons inside the vortex core and the quantization of the vortex motion of liquid helium around the charged complex lead to the existence of a whole family of excited states of electron vortices with different radii and quanta of vorticity. The proposed simple model of autolocalization of injected electrons in vortex rings allows to understand the nature of fast and exotic ions in superfluid helium.
Ownership and Technological Intensities in Ugandan Manufacturing

This paper examines productivity, export-intensity and technological differences between foreign and local firms in metal engineering, food and beverages, and plastics firms in Uganda using an adapted version of the technological capability framework. Although the results were mixed, foreign firms enjoyed higher and statistically significant technological capabilities than local firms, and in its components of human resource, process technology and adaptive engineering. The relationship between labour productivity and export intensity, and technological intensity was stronger in foreign firms than in local firms. The relationship between foreign ownership and adaptive engineering was also positive and significant. Despite 25 per cent of the foreign firms enjoying no cross-border subsidiaries, foreign firms showed higher participation in adaptive engineering activities than local firms. (Please Puchase For Further Reading)
Efficient Modeling and Evaluation of Constraints in Path Planning for Multi-Legged Walking Robots

In this article, we propose a new method for constraints evaluation during the path planning of a multi-legged walking robot. We propose the application of Gaussian Mixtures (GM) to build constraint models. With the proposed analytical constraint function we can compute the gradient and move the robot out of the bound configuration. The proposed method allows checking self-collisions, and a workspace of the robot in a few microseconds and efficiently plan the motion of the robot. The proposed path planning method uses RRT-Connect framework. We show how to efficiently apply the constraints evaluation methods to optimize the posture of the robot, optimize the position of the feet during the swing phase and efficiently explore the search space. We compare the proposed method with the standard constraints evaluation algorithms. Finally, we present the results of path planning for the six-legged robot in various scenarios to show properties of the proposed motion planning algorithm with GM-based constraints evaluation.
Analysis of the Parasitic Parameters Influence on the Analog Filters Frequency Response

Modern tools for the synthesis of analog filters cannot automatically solve the problem of designing filters in the VHF range on concentrated non-tunable elements of minimal dimensions. The reason for this is unaccounted parasitic parameters that do not yet have a significant effect at lower frequencies, while at higher frequencies filters with distributed parameters become preferable. The article provides an assessment of the influence of various parasitic parameters on the frequency response of a bandpass filter.
Challenges of Junction Temperature Sensing in SiC Power MOSFETs

Junction temperature sensing is an integral part of both on-line and off-line condition monitoring where direct access the bare die surface is not available. Given a defined power input, the junction temperature enables the estimation of the junction-to-case thermal resistance, which is a key indicator of packaging failure mechanisms like solder voiding and cracks. The use of temperature sensitive electrical parameters (TSEPs) has widely been proposed as a means of junction temperature sensing however, in SiC power devices there are certain challenges regarding the use of TSEPs. Bias Temperature Instability (BTI) from charge trapping in the gate dielectric causes threshold voltage drift, which in SiC affects some of the key TSEPs including ON-state resistance, body diode forward voltage as well as the turn-ON current commutation rate. This paper reviews the challenges of junction temperature sensing in SiC power devices, the impact of BTI on TSEPs and how different researchers have approached the issue of power cycling SiC power devices and modules.
Locating and Disregarding the Information from Compromised Sensors in a WSN

Security of wireless sensor networks and reliability of the data that they generate is very critical for the intended monitoring and control applications. The information received from a sensor may be compromised because of sensor malfunction, communication link failure, or jamming attacks. This paper proposes an algorithm for locating the compromised sensor within a network of cooperating sensors and disregarding the information it sends to the base station. Thus, the final decision regarding the information collected from the sensors is less affected by the compromised sensors. This helps prevent activating wrong response mechanisms based on the compromised received information. Simulation results show that the proposed algorithm effectively locates the compromised sensors and improves the reliability of the final decision at the base station.
Further reduction of Schottky barrier height of Hf-germanide/n-Ge(001) contacts by forming epitaxial HfGe2

For realizing high-performance Ge-channel metal-oxide-semiconductor field-effect transistor (MOSFET), the reduction of parasitic resistance is one of the most important issues [1] . However, it is generally difficult to reduce the contact resistivity at metal/ n -Ge interface because of its high Schottky barrier height (SBH) around 0.5–0.6 eV, in which the Fermi level of the metal is pinned at the valence band edge of Ge; well-known Fermi level pinning (FLP) phenomenon [2] , [3] . One of the considerable reasons for FLP is disorder-induced gap states owing to dangling bonds at the metal/Ge interface [4] . There are some reports in which an epitaxial metal/Ge interface alleviates FLP and the SBH can be lowered with Fe 3 Si/ n -Ge(111) [5] , Mn 3 Ge 5 / n -Ge(111) [6] , and NiGe/ n -Ge(110) contacts [7] .
IDA-PBC for Underactuated Mechanical Systems in Implicit Port-Hamiltonian Representation

Partial differential equations (PDEs) persist to be a stumbling block in Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC). Lately, for a class of mechanical systems an energy shaping controller has been investigated that avoids PDEs by exploiting implicit port-Hamiltonian representations. Following the same research line, in this paper we generalize the total energy shaping IDA-PBC for underactuated mechanical systems in the implicit framework and propose an algebraic solution for a class of systems. Besides, under some additional conditions we are also able to produce a respective output feedback. A reduction of the closed loop system in explicit coordinates is presented. We test our results on the inclined cart-pole system and portal crane.
Model reduction by moment matching: case study of a FIR system

We present two moment matching-based solutions to the problem of rational approximations of a finite-impulse response (FIR) system: a direct moment matching approximation performed on the FIR system and a sequential moment matching approximation performed on a block split model of a FIR system. Imposing moment matching conditions yields families of parametrized, low-order, rational approximations of the FIR filters, with guaranteed low frequency behavior. We show that the block rational implementation from [1], [2] is a particular case of the sequential moment matching result. The theory is illustrated with an example of a FIR system, where we select the free parameters such that the approximations are stable and more accurate. We compare the proposed approximations with existing rational implementations of the FIR system as well as with Loewner matrices-based approximations.
Solving the Inverse Problem in Spirometry with the Methods of Global and Local Estimation

Forced expiration is the most commonly applied lung function tests. The forward problem in spirometry was solved a few decades ago, nevertheless, a relatively small amount of work has been devoted to indirect measurements of lung properties based on spirometry data. Just recently, a reduced model for forced expiration was used to create and evaluate an artificial neural network approximating the inverse mapping (InvNN) between spirometric data and model parameters. The aim of this work was to evaluate the accuracy of an extended approach to this inverse problem, consisting of two stages: global estimation using the InvNN and then local estimation with the Levenberg-Marquardt algorithm (LM). To this end, 8000 synthetic spirometry results were generated. 6800 of them were used to train and validate the InvNN, and the remaining 1200 to test the entire method. The results show that the InvNN is not able to fit the model well enough to the data, and that the LM compensates this deficiency. The total estimation errors for particular model parameters are between 4 and 19 % in relation to their variability ranges. Higher errors mainly stem from the correlations between some of parameter estimators, as well as from noise present in the data. These outcomes encourage further analysis of the method using synthetic data generated by a more complex model and its application to the results of bronchial challenge tests.
Perceptually Lossless Compression for Mastcam Images

The communication channel between Mars and Earth is bandwidth limited. In such bandwidth scarce applications, lossless compression of Mastcam images may be unnecessary, as only two to three times of compression can be achieved. Currently, NASA is using JPEG codec, a technology invented in the 90’s, to compress the Mastcam images. An alternative way to save bandwidth is to adopt perceptually lossless compression, which can attain eight times or more compression without loss of important information. In this research, our main objective is to compare and select the best compression algorithm in the literature to achieve 8:1 or more compression ratio with perceptually lossless compression for Mastcam images. We have clearly achieved the above objectives using real Mastcam images.
Online k-step model identification with directional forgetting

We propose a k-step ahead prediction recursive algorithm for online adaptive identification of slowly time-varying nonlinear systems based on polynomial NARX models to be used in model predictive control (MPC). In view of the possible mismatch between level of excitation and number of model parameters during online operation, we propose to initialize the model by an offline identification with sufficient excitation and then to use directional forgetting to update its parameters in closed loop under insufficient excitation in order to avoid estimator windup. We show the effectiveness and robustness with respect to disturbance properties such as noise color of the presented recursive algorithm by simulation examples in open and closed loop.
TL-FALL: Contactless Indoor Fall Detection Using Transfer Learning from a Pretrained Model

A new radar-based fall detection method is proposed using the recent advances in deep neural networks. An ultrawideband radar is used to monitor human daily activities and identify the occurrence of falls. A transfer learning approach is employed based on a pre-trained model on ImageNet dataset to realize a robust feature extraction from radar data. The architecture and depth of the model are fine-tuned to radar time-frequency representations. From the results, it is observed that the proposed transfer learning based method can achieve a detection accuracy for fall incidents higher that those of the other methods.
ε-Approximate Output Regulation of Linear Stochastic Systems: a Hybrid Approach

The problem of output regulation for linear stochastic systems is addressed. The controlled system belongs to a general class of linear systems, namely the state, the control input and the exogenous input appear in both the drift and diffusion terms of the differential equations. Building upon the solution of the ideal, non-causal, stochastic regulator problem, we define an approximate full-information problem. By means of measurements of the state vector, we provide a way to compute a sequence of scalars approximating a posteriori the variations of the Brownian motion. Then, we propose a hybrid control architecture which solves the approximate problem. The continuous-time part of the controller is deterministic, whereas the discrete-time part has the function of “correcting” the control action by means of the approximate discrete-time Brownian motion. The solution of the ideal stochastic regulator problem is recovered as the sampling time tends to zero. We illustrate the results by means of a numerical example and conclude the paper with some final remarks: the proposed control architecture is the first causal solution of the full-information output regulation problem and is an essential intermediate step for the solution of the error-feedback problem.
Company-Internal ELF Communication: The Case of Email Requests between Professionals

The email medium plays a prevalent role in globalised professional communication. Where English as a Lingua Franca is the language of choice, challenges may arise based on differing assumptions about the appropriate degree of directness, in particular with face-threatening speech acts such as requests. Given the frequency of email requests between colleagues, they are investigated here with the aim of identifying common practices in diverse speaker groups. Requests for information and requests for action were analysed with respect to request perspective and realisation strategy. The results indicate that these request types differ on both measures. The former are primarily realised as impersonal questions, focusing on the content rather than highlighting the requestive character. The latter make use of different realisation strategies and perspectives, one of them being the most direct strategy in hearer perspective, i.e. placing emphasis on the requestive illocutionary force. Direct requests are common in business (email) requests, but are less in line with both native and L2 English speakers’ preferred choices outside this context. We urge for raising awareness of ELF language use in language policies and instruction on business communication.
A Cleaning Robot for Solar Panels

Many types of Solar Panel Cleaning Robots are used in many countries, such as Solar Frames Connected Robot. Developing the Solar Panel Cleaning Robots can be used to work instead human especially it is not necessary to have a supervisor for working control and reduce a risk of damage from moving a robot. However, Solar Frames Connected Robot still has defect which limited size of solar panel and not easy to move. This research aims to design and develop the Solar Panel Cleaning Robots by studying Solar Panel Cleaning Robots movement which work suitable in Thailand, Wireless Joystick, Sensor Sonar using Gear Motor and ARDUINO microcontroller. The robot will clean a solar cell by using a rotary brush with water spray to improve cleaning system. Result of studying Solar Panel Cleaning Robots movement by using Gear Motor can operate at a surface level of 0–30 degrees Celsius and cleaning system by using rotary brush can be clean 80% of solar panel.
Practical Decoding Scheme for Doubly Irregular Sparse Code Multiple Access

Doubly irregular sparse code multiple access (DI-SCMA) is a type of sparse code multiple access (SCMA) with irregular degree distributions both in resource node (RN) and user node (UN) to increase the overloading factor. This paper proposes a practical decoding scheme for DI-SCMA having low computational complexity based on using peeling decoding algorithm. We also use mother constellation capable of detecting 4 users simultaneously based on binary shift keying (BPSK)-like mapping leading to a total constellation similar to the 8 phase shift keying (8-PSK). We evaluate the decoding behaviour of the proposed DI-SCMA using extrinsic information transfer (EXIT) chart and computer simulations. Our results confirm the validity of achievable overloading factor using the practical decoding technique with better bit error rate (BER) performances compared to performances of 8-PSK modulations.
Advancing Ethical Decision Making in Virtual Reality

Virtual reality (VR) has been widely utilized for training and education purposes because of pedagogical, safety, and economic benefits. The investigation of moral judgment is a particularly interesting VR application, related to training. For this study, we designed a within-subject experiment manipulating the role of study participants in a Trolley Dilemma scenario: either victim or driver. We conducted a pilot study with four participants and describe preliminary results and implications in this poster.
Consensus in the presence of communication faults

In this paper we investigate the edge disconnection problem for a discrete-time multi-agent consensus network. We first show that if the communication network is symmetric, an edge disconnection that does not affect the connectedness of the whole network does not even affect the final consensus value. On the contrary, if the communication network is not symmetric, then, in general, an edge disconnection that preserves the strong connectedness of the communication graph nonetheless may lead to a consensus value that is different from the original one. Discernibility of the faulty network from the original one is investigated both in case the states of all the agents are available and in case only the states of a subset of the agents are available. Several equivalent conditions are derived and it is proved that the necessary and sufficient conditions for discernibility and for discernibility from the observation of a subset of agents are exactly the same and can be checked on the original state matrix and on its eigenvectors.
Method of Sea Wave Extraction and Matching from Images Based on Convolutional Neural Network

Tsunami is known as one of the most destructive natural disasters. Aiming to measure Tsunami, our laboratory proposed a method based on binocular stereo vision. As we calculate the 3D coordinates of sea waves, the sea surface height in surveillance area can be measured in real time. Sea wave extraction and sea wave matching are two key steps in the above method. By conventional image processing methods, the effects of sea wave extraction and sea wave matching are not satisfactory because of uneven illuminance and different filming angles. In this paper, we propose a method of sea wave extraction and sea wave matching based on Convolutional Neural Network (CNN). Firstly, we take photos of the sea surface with two cameras. Given the raw photos, we divide them into small blocks of waves. According to the wave quantity in each block, we can build databases for sea wave extraction. And databases for sea wave matching can be built according to the matching situation of two blocks from left and right photos. Then we make use of the open-source software library Tensorflow to establish two CNN frameworks. After being trained by training databases, experiments on the test database show that the two CNN systems can separately extract and match sea waves from photos with considerable accuracy within several seconds. Besides, our network is self-adaptive to different sea wave images as well as to different camera settings.
Prebreakdown and Breakdown in Liquid Nitrogen under Pulsed Heating for Superconducting

An experimental study of breakdown and pre-breakdown phenomena in liquid nitrogen (LN2) is performed in this work, aiming to provide useful knowledge for the design of high voltage superconducting systems. A metallic tape subjected to pulsed heating is used as ground electrode to properly simulate the operating conditions of a quenching superconducting apparatus. Measurements of breakdown voltages between the tape and a plane electrode tied to high voltage show the strong influence of tape polarity, LN2 temperature, and delay between heating and voltage application. Various measurements obtained with either a highspeed camera or an intensified camera allow to characterize the sequence of pre-breakdown events (i.e. liquid boiling, vapor bubble development, and streamer propagation) leading to breakdown.
Spatial Presence in Real and Remote Immersive Environments

This paper presents an experiment assessing the feeling of spatial presence in both real and remote environments (respectively the socalled “natural presence” and “telepresence”). Twenty-eight (28) participants performed a 3D-pointing task while being located in a real office and the same office remotely rendered over HMD. The spatial presence was evaluated by means of the ITC-SOPI questionnaire and users' behaviour analysis (trajectories of head during the task). The analysis also included the effect of different levels of immersion of the system - visual-only versus visual and audio - rendering in such environments. The results show a higher sense of spatial presence for the remote condition, regardless of the degree of immersion, and for the “visual and audio” condition regardless of the environment. Additionally, trajectory analysis of users' heads reveals that participants behaved similarly in both environments.