Miracle-dz/UniFAR-FTUs huggingface dataset:
A Virtual Technology Aiding for Hand-Impaired Persons

Tremors are one of most common movement disorder symptoms, featured with the involuntary shaking of individual' body parts. They often occur hands and seriously reduce their functions. So that individuals with hand tremors difficultly perform much daily interactions with hands, for instance using tools for eating, touching computer/devices. Traditional approaches that helping trembling hands include "medical approaches", "mechanical approaches", "functional electric stimulation (FES) approaches", and "active approaches", but exist some limitations including body burden, muscle fatigues, and non-application of ordinary device. A way different from traditional approaches-virtual approach is introduced, which allows individuals with completely free trembling hands to preciously interact with ordinary devices meanwhile is no harm and no fatigue to user's hands. This paper reiterates over the scalability of the technology and discusses all hand impaired aided technologies.
An Origami Inspired Circularly-Polarized Folding Patch Antenna Array

This work investigates and develops the physical reconfiguration and deployment of a previously designed 2×2 corporate-fed microstrip patch antenna array. The physical reconfiguration of the antenna is achieved using a Miura-ori fold pattern due to its utilization for deployment. Increasing the fold angle impacts the input impedance and beamforming capabilities by changing the element spacing and orientation. The previous design experienced a graceful degradation in electromagnetic performance as the fold angle increased. Further optimization led to a more robust and functional antenna array system. The antenna is enhanced by designing the array with circularly polarized patch elements. The use of circular polarization eliminates the need to study the polarization changes during intermediate folding states and enables pattern reconfigurability. The performance of the circularly polarized array is evaluated over a comprehensive range of angles to evaluate the impact of physical reconfiguration. Results from a simulated circularly polarized array are provided for a 3GHz design.
Uncertainty Quantification of Vector Parabolic Equation based Wireless Channel Models Using Polynomial Chaos Expansion

Vector parabolic equation (VPE) methods have been widely applied to model wave propagation in guiding structures with high accuracy and computational efficiency. A detailed specification of the modeled environment is required. However, considerable uncertainty can exist in the description of the environment. This paper presents a non-intrusive formulation of polynomial chaos expansion (PCE) method to quantify the uncertainties in VPE-based channel models for tunnel environments. The performance is validated against Monte Carlo simulations and measurements.
Comparison of Sampling Methods for Imbalanced Data Classification in Random Forest

Imbalanced data classification is a serious and challenging task for most of the medical image diagnosis applications. They usually produce a larger number of false samples compared to the actual ones. That is the number of samples for the class of interest (minority) is significantly fewer than other types of class (majority). The classification performed using such data is called imbalanced data classification. As a consequence, the learning model bias towards the majority class and fails the classification of the minority class. Data sampling and ensemble methods are common ways to compensate for this issue. Random forest (RF), an ensemble of multiple decision trees, is very famous in both of the classification and regression problems because of its robust and accurate predictions. However, it also suffers class bias in the imbalanced data classification problems. This paper proposes and compares different sampling methods to solve the imbalanced data classification in RF.
Compact 2-D FDFD Analysis of Waveguide Structures with ARPACK

The compact 2-D FDFD method for waveguide is concluded as an sparse eigenvalue problem (EVP). ARPACK is an open software to compute a few eigenvalues and corresponding eigenvectors of large scale sparse EVPs. As we are just interested in the first few modes, ARPACK is very suitable for solving the EVP. In this paper, a method with ARPACK is proposed to solve the EVP, by which the first few eigenvalues of the waveguide EVP can be solved without the generation of spurious modes, and great efficiency is achieved.
Optimized Predictive Control and Equalization of Zero-States for a 27-level Cascade Asymmetric Multilevel Converter

This paper presents an improved predictive control for a 27-level asymmetric multilevel converter oriented to the injection of photovoltaic energy into the electrical grid. The improvement considers the reduction of commutations in the high power cell of the converter and the optimal of its zero states for an equitable distribution of conduction losses in the semiconductors devices. Simulations are carried out in order to prove the properness of the proposed control scheme.
Sparsity and Coherence in Inverse Problems - from 1 D to 2D Processing through Matrix Completion

Sparseness-promoting inversion strategies based on Bayesian formulations have recently emerged as powerful, robust, flexible, and accurate techniques to address a wide variety of problems arising in microwave imaging. The success of such paradigm is motivated by the capability of the resulting formulations to (i) handle sparse linear/linearized problems even when incoherence or restricted isometry properties (RIPs) are not guaranteed, and to (ii) provide self-computed “confidence level” estimations. Unfortunately, no methodology has been proposed in the state-of-the-art to actually exploit such confidence-level indexes and enhance the reconstructed profiles once the imaging reliability is self-detected to be poor (e.g., in harsh signal-to-noise-ratio scenarios, or when the RIP does not hold true). Moreover, the most popular BCS formulations handle the unknowns as 1D vectors, therefore neglecting the “matrix” nature of the associated physical problem (e.g., contrast retrieval). In this framework, this paper is aimed at illustrating the possibility to exploit a new class of methodologies based on rank-minimization formulations to overcome the above limitations and recover reliable reconstructions of the scattering scenario by fully exploiting the 2D matrix nature of the problem. Selected preliminary numerical results will be also discussed to validate the proposed paradigm.
Gain Improvement of Phased Array using Sub-Arrayed Microstrip Patch Antennas for Satellite Communication Applications

In this paper, a sub-array structure of a microstrip patch antennas is proposed as a phased array element to improve gain at low elevation angle for satellite communication. This subarray antenna has a radiation pattern with the conformation of two main lobes. Each 3dB beam-width coverage of beam pattern is ±17.7° to ±65.0°. The gain of the proposed phased array antenna was increased 2.67dB at theta 55°, compared to the conventional phased array antenna. The proposed antenna operates left-hand circularly polarization (LHCP) at 11.85GHz for satellite communication applications.
Trajectory Estimation and Crowdsourced Radio Map Establishment From Foot-Mounted IMUs, Wi-Fi Fingerprints, and GPS Positions

Trajectory estimation is a problem derived from a common indoor positioning scenario: the user is perceiving the environment while in motion. This paper focuses on an instance: the dead reckoning data of the user are provided by foot-mounted inertial positioning and the observations in the environment are position estimated from global positioning system (GPS) and Wi-Fi received signal strengths. An approach is proposed to merge the three types of data from multiple users using the graph-based SLAM framework. In constructing the graph, Wi-Fi-based edges are established adaptively and GPS-based edges are established as prior information for the corresponding positions from the dead reckoning generated trajectories. The users’ trajectories can be aligned and calibrated using the proposed graph construction strategies. Afterwards, a crowsourced Wi-Fi-based radio map (RM) can be established for other users who need the fingerprinting-based Wi-Fi indoor positioning service. The accuracy of the users’ trajectories and the crowdsourced RM are tested to validate the proposed approach.
Coding for Write Latency Reduction in a Multi-Level Cell (MLC) Phase Change Memory (PCM)

This paper presents a new write latency reduction scheme for a Phase Change Memory (PCM) made of Multi-Level Cells (MLCs). This scheme improves over an existing scheme found in the technical literature and known as CABS. The proposed scheme is based on the utilization of a new coding arrangement for the selection of candidate codewords. The code relies on the two-step feature found in the write operation of a MLC PCM and avoids the symbol that incurs in the largest latency at a higher rate than CABS. A detailed simulation based evaluation and comparison are also pursued; the proposed scheme accomplishes improvements in write latency (for parallel writing) as well as coding rate (16/17 for the proposed scheme versus 16/18 for CABS for 16 symbols or 32-bit word). As the proposed scheme utilizes novel selection criteria for the candidates, the design of the required circuitry (encoder and decoder) has also been changed with respect to CABS; in terms of hardware, the areas of the encoder and decoder for the proposed scheme are reduced by 73 and 56 percent respectively compared with CABS.
Recent Improvements in Asymptotic RCS Calculations of Large Complex Targets

This paper investigates the improvement in accuracy and efficiency of the ray-launching geometrical optics method, as implemented in different versions of FEKO, and shooting-and-bouncing-rays with physical optics method, as implemented in SigmaHat, to calculate the radar cross section (RCS) of a large complex model airframe. A scale model Boeing 707 (106λ) and accurately scanned CAD model is utilized for this study. The investigation is conducted by comparing the calculated RCS to measured data, obtained in a compact range, using angular RCS graphs and ISAR imaging. Interesting results are obtained and some clear improvements can be observed in the accuracy as well as efficiency of the methods.
A Convergence result for the Euler-Maruyama method of one-dimensional stochastic differential equations involving the local time of the unknown process at zero

In this paper, we study the strong rate of convergence for the Euler-Maruyama approximation of a class of one-dimensional stochastic differential equations involving the local time (SDELT) of the unknown process, corresponding to divergence form operator with a discontinuous coefficients at zero. We use a space transform in order to remove the local time $L_{t}^{0}$ from the stochastic differential equation of type, \begin{equation*} dX_{t}=\sigma(X_{t})dB_{t}+\psi(X_{t})dt+\beta dL_{t}^{0}(X). \end{equation*} Here $B$ is a standard one-dimensional Brownian motion. $\sigma$ and $\psi$ are a bounded measurable functions, and $\beta\in(-1,1)$. We provide the approximation of Euler-Maruyama for the stochastic differential equation without local time. After that the approximation can be transformed back, giving an approximation of Euler-Maruyama $X_{t}^{n}$ to the solution of the original SDELT, and we provide the rate of strong convergence Error $=\mathbb{E}[\vert X_{T}^{\mathrm{n}}-X_{T}\vert]$.
Design of PMSM for EMA Employed in Secondary Flight Control Systems

The more electric aircraft (MEA) initiative aims to improve weight, fuel consumption and maintenance costs of the aircraft, by increasing the use of electric power in actuation systems. Considering this scenario, electromechanical actuators (EMAs) for flight control (FC) systems represent a key technology in future aircraft. The paper presents a linear geared EMA for secondary FC systems, where the safety and availability requirements are fulfilled by duplicating the electric drive acting on the EMA drive-train (i.e. two power converters feeding as many electrical machines coupled to the same mechanical system). The design of the permanent magnet synchronous machine (PMSM) integrated into the EMA is addressed. Preliminary results on the PMSM prototype are also provided and compared to the finite element (FE) outcomes obtained at the design stage. The EMA performance at system-level is evaluated in Dymola environment, analyzing three operating modes, such as active-active, active-standby and active-shorted. Finally, some thermal considerations regarding the active-shorted configuration are outlined.
A Secure Testing Based Approach for Mapreduce Frameworks

MapReduce framework was built as a parallel distributed programming model. It has emerged over the past few years as the most popular framework to process large-scale datasets efficiently. However, the execution of such model on large clusters can be more complex and could produce several failures due to bugs or hardware problems since several workers with different functionalities are running together. Moreover, security of data and MapReduce computations are essential concerns when a MapReduce computation is executed in public. In this paper, we present a novel secure architecture-Based Conformance Testing in order to check not only if the behavior of a Mapreduce Implementation Under Test (MR-IUT) is conform to its specification but also if MR-IUT respects some security policies. The proposed approach shows how to cope with problems encountered in Mapreduce distributed testing using distributed testing rules. Afterwards, we propose the use of a rule based system to model our approach for testing the MR-IUT implementation.
Hierarchical Regularization of Building Boundaries in Noisy Aerial Laser Scanning and Photogrammetric Point Clouds

Aerial laser scanning or photogrammetric point clouds are often noisy at building boundaries. In order to produce regularized polygons from such noisy point clouds, this study proposes a hierarchical regularization method for the boundary points. Beginning with detected planar structures from raw point clouds, two stages of regularization are employed. In the first stage, the boundary points of an individual plane are consolidated locally by shifting them along their refined normal vector to resist noise, and then grouped into piecewise smooth segments. In the second stage, global regularities among different segments from different planes are softly enforced through a labeling process, in which the same label represents parallel or orthogonal segments. This is formulated as a Markov random field and solved efficiently via graph cut. The performance of the proposed method is evaluated for extracting 2D footprints and 3D polygons of buildings in metropolitan area. The results reveal that the proposed method is superior to the state-of-art methods both qualitatively and quantitatively in compactness. The simplified polygons could fit the original boundary points with an average residuals of 0.2 m, and in the meantime reduce up to 90% complexities of the edges. The satisfactory performances of the proposed method show a promising potential for 3D reconstruction of polygonal models from noisy point clouds.
An Investigation on the Development of Informatization Ability of Teachers by Applying the Technology Acceptance Model

This study applies the Technology Acceptance Model (TAM) as basic theoretical framework to analysis the informatization ability of teachers in No.53 Middle School of Changchun. And the study applies the six factors (external variables, adjustment variables, perceived usefulness, perceived ease of use, attitude towards using and behavioral intention) of the TAM model to evaluate the development of informatization ability of teachers. Each factors are evaluated through interviews of the teachers in No.53 Middle School of Changchun. The results of the interviews and the investigation identify three solutions applied by No.53 Middle School conform to the TAM model: Firstly, the method of making up study groups of young and old teachers conforms to individual differences of external variables in the TAM model; Secondly, information technology training in No.53 Middle School is a convenient condition of external factors in the TAM model. Thirdly, Micro-curriculum competition conforms to experience factors of adjustment variables. These three solutions have positive effect on teachers' perceived usefulness and perceived ease of use, and then the three solutions have a positive impetus to the development of informatization ability of teachers. The investigation also identifies two solutions don't conform to the TAM model: Firstly, teachers use free resource platform; Secondly, recruit more information technology teachers.
Modeling Space-Terrestrial Integrated Networks with Smart Collaborative Theory

Driven by the requirements of space exploration and terrestrial investigation, interplanetary network merging has been widely focused on by academia, industry, and the military. Although system architecture and layered workflow are updated endlessly, the pervasive methodology is still urgently needed to provide a unified solution for heterogeneous elements. In this article, we propose a modeling scheme named generalized logical sphere (GLS) for space-terrestrial networks based on smart collaborative theory. First, the coverage range, transmission mechanism, and practice guideline of integration evolution are fully analyzed via three phases to guarantee the comprehensive combinations. Then the specific approach as well as the advanced characteristics of GLS (i.e., load balancing, smart routing, cognitive healing, and hierarchical shielding) are presented and discussed. Finally, a prototype platform is established to validate the correctness. The results of two scenarios illustrate the functionality and practicability of our model.
A Domain Decomposition Method Based on Simplified Volume-Surface Integral Equation

A novel non-overlapping and non-conforming domain decomposition method (DDM) based on simplified volume-surface integral equation (S-VSIE) is proposed for the electromagnetic analysis of composite very thin dielectric/complex finite array objects. In this scheme, such composite objects are decomposed into multiple composite subdomains. To model efficiently subdomains involving very thin dielectric, the VSIE with simplified prism vector (SPV) basis functions, called as S-VSIE, is applied. Further, a discontinuous Galerkin volume integral equation method based on the SPV basis functions (DG-S-VIE) is proposed for conformal as well as non-conformal volume discretizations. Moreover, a additive non-overlapping DD preconditioner is designed for the fast iterative solution.
TX-RX K/Ka Band Polarizer Based on a SIW Polarization Twister

A K/Ka band polarizer obtained stacking a SIW polarization rotator and a meander-lines polarizer is presented. The rotator is realized with SIW cavities that selectively twist the polarization of the incident wave. In this way, incident 30GHz horizontally polarized waves are converted in RHCP signals, while incident 20GHz waves with the same polarization are converted in LHCP signals. The proposed polarizer may be used with linearly polarized aperture antennas and, for this reason, it can be considered as an after-market add-on that does not affect the performance parameters of the antenna itself.
Characterization of Colloidal Silica by Optical Fiber Sensor

The assessment of colloidal silica properties by an optical fiber sensor is reported. The effect of particles concentration and size was analyzed by dynamic light scattering, making it possible to estimate the sample properties from the decay rate. Moreover, the nanofluids were subjected to heating, so the thermal conductivity and refractive index variations could be inferred from reflected intensity and autocorrelation signals.
Identifying Mangrove Species Using Field Close-Range Snapshot Hyperspectral Imaging and Machine-Learning Techniques

Investigating mangrove species composition is a basic and important topic in wetland management and conservation. This study aims to explore the potential of close-range hyperspectral imaging with a snapshot hyperspectral sensor for identifying mangrove species under field conditions. Specifically, we assessed the data pre-processing and transformation, waveband selection and machine-learning techniques to develop an optimal classification scheme for eight mangrove species in Qi'ao Island of Zhuhai, Guangdong, China. After data pre-processing and transformation, five spectral datasets, which included the reflectance spectra R and its first-order derivative d(R), the logarithm of the reflectance spectra log(R) and its first-order derivative d[log(R)], and hyperspectral vegetation indices (VIs), were used as the input data for each classifier. Consequently, three waveband selection methods, including the stepwise discriminant analysis (SDA), correlation-based feature selection (CFS), and successive projections algorithm (SPA) were used to reduce dimensionality and select the effective wavebands for identifying mangrove species. Furthermore, we evaluated the performance of mangrove species classification using four classifiers, including linear discriminant analysis (LDA), k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). Application of the four considered classifiers on the reflectance spectra of all wavebands yielded overall classification accuracies of the eight mangrove species higher than 80%, with SVM having the highest accuracy of 93.54% (Kappa=0.9256). Using the selected wavebands derived from SPA, the accuracy of SVM reached 93.13% (Kappa=0.9208). The addition of hyperspectral VIs and d[log(R)] spectral datasets further improves the accuracies to 93.54% (Kappa=0.9253) and 96.46% (Kappa=0.9591), respectively. These results suggest that it is highly effective to apply field close-range snapshot hyperspectral images and machine-learning classifiers to classify mangrove species.
Sea Surface Temperature Retrieval from the First Korean Geostationary Satellite COMS Data: Validation and Error Assessment

Korea’s first geostationary satellite, the “Communication, Ocean, and Meteorological Satellite” (COMS), has been operating since 2010. The Meteorological Imager (MI), an sensor on-board the COMS, has observed sea-surface radiances for the estimation of sea surface temperature (SST) in the western Pacific Ocean and eastern Indian Ocean. To derive the SST coefficients of COMS, quality-controlled surface drifting buoy data were collected for the period of April 2011 to March 2015. A collocation procedure between COMS/MI data and the surface drifter data produced a matchup database for 4 years from 2011 to 2015. The coefficients for the COMS/MI SST were derived by applying appropriate algorithms, i.e., the Multi-channel SST (MCSST) and Non-linear SST (NLSST) algorithms, for daytime and nighttime data using a regression method. Validation results suggest the possibility of the continuous use of the coefficients as representative SST coefficients of COMS. The estimated SSTs near the edge of a full disk with high satellite zenith angles over 60° revealed relatively large errors compared to drifter temperatures. Most of NLSST formulations exhibited overestimation of SSTs at low SSTs (<10 °C). This study suggests an approach by which SST can be measured accurately in order to contribute to tracking climate change.