Miracle-dz/UniFAR-FTUs huggingface dataset:
Enabling End Users to Build Situational Collaborative Mashups at Runtime

—Web based collaboration gains importance in everyday life. However, users have to switch between dedicated collaboration tools that are not interoperable and do not satisfy the long tail of user needs. To overcome this, users would have to develop customized applications by themselves. Caused by a lack of support for users without programming experiences, existing approaches lack support for end user development (EUD) or cause high cognitive load leading to frustration. Therefore, we utilize the mashup paradigm to empower end users in conﬁguring their collaboration environment independently. To address arbitrary collaboration demands, we enable to synchronize collaborative and non collaborative components during an application’s runtime. In addition, users are able to share mashups as well as components, entirely or only in part, with an arbitrary number of collaboration partners. To further allow for individual user preferences, amongst others, we facilitate a semantic component description to synchronize different implementations of functionally similar applications.
Some New Inequalities for Dual Continuous g-Frames

In the present paper, we establish new inequalities for dual continuous generalized frames by adopting operator methods. The inequalities are parameterized by the parameter λ ∈ R . These results generalize those obtained by Balan, Casazza and Găvruţa and cover recently obtained results by Zhang and Li in [Zhang, W. ; Li, Y.Z. New inequalities and erasures for continuous g-frames. Math. Rep. 2018, 20, 263–278]. Moreover, we also give an upper bound of inequality for alternate continuous generalized frames in Hilbert spaces. It differs from previous results.
Automated Screening of Myocardial Infarction Based on Statistical Analysis of Photoplethysmographic Data

Integration of automated cardiac analysis techniques with the personal healthcare devices can aid in the timely diagnosis of myocardial infarction (MI) to reduce the risk of mortality. The use of electrocardiogram (ECG) along with advanced signal processing tools limits the application of the available techniques for such portable devices having limited processing ability. Here we propose a novel MI screening technique based on photoplethysmographic (PPG) data, which is the most widely monitored signal in everyday health monitoring. Two simple statistical features ideally reflecting the MI-induced variability in the PPG data are identified. To combat the noise sensitivity of the PPG acquisition process, the same statistical parameters are employed for eliminating the noise corrupted data segments. Classification of MI data is then performed using a simple threshold-based binary classification approach. The technique is evaluated with PPG records collected from 62 hospitalized MI patients and 65 healthy subjects. The robustness of the algorithm is cross-validated with both MI and non-MI records collected from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II database. The algorithm achieves an average detection accuracy of 96.25% with sensitivity and specificity of 96.36% and 96.15%, respectively. The promising results establish the utility of PPG as an alternate MI diagnosing tool. Apart from using the less obtrusive PPG signal, the proposed technique relies on simple feature extraction and classification tools, thus making it a promising alternative to the ECG based techniques for implementation on the personal healthcare devices.
Inverse Problems on Electrical Networks and in Photoacoustic Tomography

Author(s): Knox, Christina Grace | Advisor(s): Moradifam, Amir | Abstract: This dissertation investigates two inverse problems, one on electrical networks and another from photo acoustic tomography. First we consider the inverse problem of recovering the conductivities of an electrical network from theknowledge of the magnitude of the current along the edges coupled with either the voltage on the boundary of thenetwork or the current flowing in or out of the network. This problem corresponds to finding the minimizers of a l^1minimization problem. Additionally, we show that while the conductivities are not determined uniquely the flow of thecurrent is uniquely determined. We will also present a convergent numerical algorithm for solving these problems alongwith basic numerical simulations. Lastly, we will discuss some applications of this inverse problem.Next we consider the inverse problem of determining both the source of a wave and its speed inside a mediumfrom measurements of the solution of the wave equation on the boundary. This problem arises in photoacoustic andthermoacoustic tomography. We will present a brief overview of previous uniqueness results and then present our twooriginal uniqueness results. If the reciprocal of the wave speed squared is harmonic in a simply connected region andidentically one elsewhere then a wave speed satisfying a natural admissibility assumption can be uniquely determined from the solution of the wave equation on the boundary of domain without knowledge of the source. If the wave speed is known and only assumed tobe bounded, then, under the same admissibility assumption, the source of the wave can be uniquely determined fromboundary measurements.
Pengaruh pajak penghasilan badan terhadap permintaan tenaga kerja pada perusahaan manufaktur

Penelitian ini bertujuan untuk mengetahui pengaruh pajak penghasilan (PPh) Badan terhadap permintaan tenaga kerja pada industri manufaktur di Indonesia. Penelitian dilakukan dengan unit analisis perusahaan menggunakan data survei industri besar dan sedang dari Badan Pusat Statistik. Estimasi dilakukan dengan teknik model unbalanced panel fixed effect . Secara umum hasil estimasi menunjukkan PPh Badan mempunyai hubungan negatif terhadap permintaan tenaga kerja yang berarti bahwa modal dan tenaga kerja di industri manufaktur bersifat komplemen. Tetapi secara statistik, PPh Badan tidak memiliki pengaruh yang signifikan terhadap permintaan tenaga kerja. Hal tersebut mengindikasikan bahwa pajak penghasilan (PPh) Badan bukan merupakan pertimbangan penting bagi perusahaan dalam menentukan jumlah tenaga kerjanya.
Semiparametric bayesian analysis of transformation spatial mixed models for large datasets

In spatial mixed models (SMMs), it is commonly assumed that stationary spatial process and random errors independently follow the Gassian distribution. However, in some applications, this assumption may be inappropriate. To this end, this paper proposes a transformation spatial mixed models (TSMMs) to accommodate large dataset that follows the non-Gaussian distribution. With the help of Gibbs sampler algorithm, a semiparametric Bayesian approach is developed to make inference on TSMMs by using Bayesian P-splines to approximate transformation function, and a ﬁxed number of known but not necessarily orthogonal spatial basis functions with multi-resolution analysis method to approximate nonstationary spatial process. Instead of Wishart distribution assumption for the prior of precision matrix of random eﬀects, we consider Cholesky decomposition of the precision matrix, and specify the priors for unknown components in low unit triangular matrix and diagonal matrix. Simulation studies and an example are used to illustrate the proposed methodologies.
A Bayesian semiparametric factor analysis model for subtype identification

Abstract: Disease subtype identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to infer disease subtypes, which often lead to biologically meaningful insights into disease. Despite many successes, existing clustering methods may not perform well when genes are highly correlated and many uninformative genes are included for clustering due to the high dimensionality. In this article, we introduce a novel subtype identification method in the Bayesian setting based on gene expression profiles. This method, called BCSub, adopts an innovative semiparametric Bayesian factor analysis model to reduce the dimension of the data to a few factor scores for clustering. Specifically, the factor scores are assumed to follow the Dirichlet process mixture model in order to induce clustering. Through extensive simulation studies, we show that BCSub has improved performance over commonly used clustering methods. When applied to two gene expression datasets, our model is able to identify subtypes that are clinically more relevant than those identified from the existing methods.
Two-Dimensional Fourier-Based Modeling of Electric Machines—An Overview

An increasing need for fast and reliable models has led to a continuous development of Fourier-based (FB) analytical modeling. This paper presents an overview of the techniques that are currently available in FB modeling for electric machines. By coupling that overview to the most relevant literature related to the subject, an interesting starting point is provided for anyone who wants to use or improve FB models. The following seven aspects of FB models are discussed in detail: 1) the magnetic potential (scalar or vector potential); 2) the coordinate system and the solution of the partial-differential equations for each magnetic potential and for each coordinate system; 3) the way in which time dependence is accounted for; 4) the implementation of the source terms; 5) the possibilities to account for slotted structures; 6) the modeling of eccentricity; and 7) the post-processing computation of physical quantities, such as flux density, electromotive force, torque, losses, and eddy currents in conductive objects. Furthermore, this paper gives the closed form solution of the Laplace, Poisson, and Helmholtz equations in each coordinate system. In addition, this paper tackles other important features of FB models such as computational time reduction and coupling the machine model to an electric circuit.
Evidence for spatial variation of the fine structure constant

We previously reported observations of quasar spectra from the Keck telescope suggesting a smaller value of the fine structure constant, α, at high redshift. A new sample of 153 measurements from the ESO Very Large Telescope (VLT), probing a different direction in the universe, also depends on redshift, but in the opposite sense, that is, α appears on average to be larger in the past. The combined dataset is well represented by a spatial dipole, significant at the 4. 1σ level, in the direction right ascension 17.3 ± 0.6 hours, declination −61 ± 9 degrees. A detailed analysis for systematics, using observations duplicated at both telescopes, reveals none which are likely to emulate this result.
Independence Polynomials of Molecular Graphs

In the 1980’s, it was noticed by molecular chemists that the stability and boiling point of certain molecules were related to the number of independent vertex sets in the molecular graphs of those chemicals. This led to the definition of the Merrifield-Simmons index of a graph G as the number of independent vertex sets in G. This parameter was extended by graph theorists, who counted independent sets of different sizes and defined the independence polynomial FG(x) of a graph G to be ∑ k Fk(G)x k where for each k, Fk(G) is the number of independent sets of k vertices. This thesis is an investigation of independence polynomials of several classes of graphs, some directly related to molecules of hydrocarbons. In particular, for the graphs of alkanes, alkenes, and cycloalkanes, we have determined the Merrifield-Simmons index, the independence polynomial, and, in some cases, the generating function for the independence polynomial. These parameters are also determined in several classes of graphs which are natural generalizations of the hydrocarbons. The proof techniques used in studying the hydrocarbons have led to some possibly interesting results concerning the coefficients of independence polynomials of regular graphs with large girth.
Quintessence and the rest of the world

A nearly-massless, slowly-rolling scalar field φ may provide most of the energy density of the current universe. One potential difficulty with this idea is that couplings to ordinary matter, even if suppressed by the Planck scale, should lead to observable long-range forces and time dependence of the constants of nature. I explore the possibility that an approximate global symmetry serves to suppress such couplings even further. Such a symmetry would allow a coupling of φ to the pseudoscalar FμνFμν of electromagnetism, which would rotate the polarization state of radiation from distant sources. This effect is fairly well constrained, but it is conceivable that future improvements could lead to a detection of a cosmological scalar field. (Based closely on astro-ph/9806099 [1].)
Arquitectura neuronal apoyada en señales reconstruidas con Wavelets para predicción de series de tiempo caóticas

RESUMEN En el presente trabajo se describe una nueva arquitectura neuronal inspirada en la red recurrente conocida como red híbrida compleja (HCNN por sus siglas en inglés) para predicción a mediano plazo de series de tiempo. El modelo propuesto mostró un mejor desempeño que una red neuronal totalmente recurrente y una feedforward en la predicción de 56 valores de 11 series de un conjunto utilizado para concursos de predicción de series económicas y financieras, conocido como NN5.
Avaliação de bens tangíveis: uma aplicação do método de preços hedônicos para avaliar atributos raros de peças filatélicas na construção de carteiras eficientes

Este trabalho faz uma aplicacao dos resultados obtidos com a estimacao de modelos de precos hedonicos na construcao de carteiras eficientes de ativos implicitos. Para tanto, utiliza-se o metodo dos precos hedonicos e a analise de carteiras eficientes de Markowitz. Os precos implicitos estimados sao utilizados para calcular os inputs (retornos medios e matriz de variâncias-covariâncias) necessarios a construcao das carteiras eficientes. Essa sequencia de procedimentos e aplicada a avaliacao das caracteristicas das pecas filatelicas do periodo imperial brasileiro (1843-1889), tomando-se as series temporais das cotacoes dessas pecas no periodo de 1954 a 1988. As evidencias encontradas mostram que carteiras eficientes sao formadas por um reduzido numero de selos.
FORWARD MODELING OF EMISSION IN SOLAR DYNAMICS OBSERVATORY/ATMOSPHERIC IMAGING ASSEMBLY PASSBANDS FROM DYNAMIC THREE-DIMENSIONAL SIMULATIONS

It is typically assumed that emission in the passbands of the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) is dominated by single or several strong lines from ions that under equilibrium conditions are formed in a narrow range of temperatures. However, most SDO/AIA channels also contain contributions from lines of ions that have formation temperatures that are significantly different from the “dominant” ion(s). We investigate the importance of these lines by forward modeling the emission in the SDO/AIA channels with three-dimensional radiative MHD simulations of a model that spans the upper layer of the convection zone to the low corona. The model is highly dynamic. In addition, we pump a steadily increasing magnetic flux into the corona, in order to increase the coronal temperature through the dissipation of magnetic stresses. As a consequence, the model covers different ranges of coronal temperatures as time progresses. The model covers coronal temperatures that are representative of plasma conditions in coronal holes and quiet Sun. The 131, 171, and 304 Å AIA passbands are found to be the least influenced by the so-called non-dominant ions, and the emission observed in these channels comes mostly from plasma at temperatures near the formation temperature of the dominant ion(s). On the other hand, the other channels are strongly influenced by the non-dominant ions, and therefore significant emission in these channels comes from plasma at temperatures that are different from the “canonical” values. We have also studied the influence of non-dominant ions on the AIA passbands when different element abundances are assumed (photospheric and coronal), and when the effects of the electron density on the contribution function are taken into account.
A new drive modulation applied to an L-band EER transmitter

This paper shows a novel drive modulation technique applied to a high power, high efficiency, linear Envelope Elimination and Restoration (EER) amplifier for L-Band. It comprises a mixed-mode suboptimum Class-E / Class-A wideband RF amplifier based on a dual GaN HEMT for RF carrier amplification and a high efficiency, high switching frequency, multi-phase, buck power converter based on Silicon LDMOS transistors to work as a modulator (or envelope amplifier). The linearity and power gain for this EER amplifier is improved by means of a new digital drive modulation technique and digital predistortion (DPD) to achieve linearity performances equivalent or better than Class-AB amplifiers of similar output power level and frequency band but exhibiting much higher efficiency. This EER amplifier provides 120W peak output power at the L-band without any adjustment. In a two tone test, measured third and fifth-order intermodulation products were -45 dBc and -49 dBc, respectively, reaching 67.5 % maximum PAE.
Ultra‐wideband crossover with a reversed polarity channel designed with normalized Euclid distance for fast pulse transmission

An ultra‐wideband pulse crossover with a reversed polarity channel is proposed, and a time‐domain analysis is utilized to design the crossover and estimate its performance. Two crossed channels are designed based on post‐wall slotline (PWS) and conventional slotline, and one of the two channels provides an output with reversed polarity. At the overlapping region, the PWS degrades to slotline on single layer to improve isolation between channels. Normalized Euclid distance of short pulses is utilized to evaluate the isolating and polarity reversing features of the crossover, and the matrices of normalized Euclid distance are then obtained and applied to the design procedure. The proposed crossover are modeled and fabricated for simulation and measurement, and the simulated and measured results agree well. Minimum of return loss and isolation is more than 12 dB within an ultra‐wide bandwidth from DC to 8.5 GHz. Moreover, in time domain, the proposed crossover shows good performance in pulse transmission, including high fidelity and amplitude ratio of input and output signals. The characteristics of the crossover indicate the practicability in short pulse application, and rectangular pulse transmission performance is evaluated to verify the ability.
MAGIC studies of the Crab Pulsar and Nebula spectra for energies above 20 GeV

The Crab Nebula is the most studied object in the gamma-ray sky. Yet there are many important unanswered questions on the interrelation between the gamma-ray emission from the Pulsar and the Nebula. We present the results of 112 hours of observations conducted with the MAGIC Telescopes by using the stereoscopic Sum-Trigger-II, a novel trigger system essentially halving the lower energy threshold of the telescopes. In order to process the data, a dedicated analysis aiming for the lowest energies is applied. From these observations, we detect pulsed gamma-ray emission down to 27 GeV, which allows us to perform a detailed spectral study. Due to the sound statistical basis, we perform short-time variability studies of the Pulsar and test possible correlations with the nebular flares detected by Fermi-LAT.
Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites

The ability to make devices that mimic the human brain has been a subject of great interest in scientific research in recent years. Current artificial intelligence algorithms are primarily executed on the von Neumann hardware. This causes a bottleneck in processing speeds and is not energy efficient. In this work, we have demonstrated a synaptic element based on a magnetic domain wall device. The domain wall motion was controlled with the use of synthetic pinning sites, which were introduced by boron (B+) ion-implantation for local modification of the magnetic properties. The magnetization switching process of a Co/Pd multilayer structure with perpendicular magnetic anisotropy was observed by using MagVision Kerr microscopy system. The B+ implantation depth was controlled by varying the thickness of a Ta overcoat layer. The Kerr microscopy results correlate with the electrical measurements of the wire which show multiple resistive states. The control of the domain wall motion with the synthetic pinning sites is demonstrated to be a reliable technique for neuromorphic applications.
Control directo de par predictivo para motores de inducción aplicado a tracción de vehículos eléctricos

Resulta esencial el estudio de los sistemas de control de los motores electricos, de forma que se pueda mejorar su rendimiento, a la par que se impulsa las prestaciones que ofrecen. De esta forma, este trabajo fin de grado se desarrolla en la Unidad Docente de Maquinas electricas de la ETSII UPM y, concretamente, en la bancada docente dedicada a la traccion de vehiculos electricos. Consta de dos motores acoplados en el mismo eje; un motor de induccion de jaula y uno de imanes permanentes superficiales alimentados desde sendos inversores trifasicos y controlados por un microprocesador. Se dispone de un armario que recoge todos los dispositivos necesarios para medida, proteccion y control, asi como de una interfaz que permite visualizar en tiempo real las magnitudes de interes. Informacion detallada de la bancada, asi como del procedimiento de conexion y desconexion se pueden encontrar en TFGs anteriores, incluidos en la bibliografia de este trabajo. Paralelamente a la labor presencial en el laboratorio se trabaja con la herramienta de simulacion MATLAB Simulink.
CTDroid: Leveraging a Corpus of Technical Blogs for Android Malware Analysis

The rapid growth of Android malware results in a large body of approaches devoted to malware analysis by leveraging machine learning algorithms. However, the effectiveness of these approaches primarily depends on the manual feature engineering process, which is time-consuming and labor-intensive based on expert knowledge and intuition. In this paper, we propose an automatic approach that engineers informative features from a corpus of Android malware related technical blogs, which are written in a way that mirrors the human feature engineering process. However, there are two main challenges. First, it is difficult to recognize useful knowledge in the magnanimity information of thousands of blogs. To this end, we leverage natural language processing techniques to process the blogs and extract a set of sensitive behaviors that might do harmful activities to users potentially. Second, there exists a semantic gap between the extracted sensitive behaviors and the programming language. To this end, we propose two semantic matching rules to match the behaviors with concrete code snippets such that the apps can be tested experimentally. We design and implement a system called CTDroid for malware analysis, including malware detection (MD) and familial classification (FC). After the evaluation of CTDroid on a large scale of real malware and benign apps, the experimental results demonstrate that CTDroid can achieve 95.8% true positive rate with only 1% false positive rate for MD and 97.9% accuracy for FC. Furthermore, our proposed features are more informative than those of state-of-the-art approaches.
Application of GA package in functional packaging

The approach to application program for the task of configuration of the elements of the commutation circuit for design of the radio-electronic equipment on the basis of the genetic algorithm is offered. The efficiency of the used approach for commutation circuits with different characteristics for computer-aided design on radio-electronic manufacturing is shown. The prototype of the computer-aided design subsystem on the basis of a package GA for R with a set of the general functions for optimization of multivariate models is programmed.