Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiclass Classification Application using SVM Kernel to Classify Chest X-ray Images Based on Nodule Location in Lung Zones

Support Vector Machine (SVM) has long been known as an excellent approach for image classification. While many studies have reported on its achievement, yet it still weak to handle multiclass classification problem because it is originally designed as a binary classification technique. It is challenging task to transform SVM to solve multiclass problems like classifying chest X-ray images based on the lung zone location. Classified X-ray images improved image retrieval hence reducing time taken to assessed back the images. Realizing this difficulties, therefore, we proposed an application method for multiclass classification using SVM kernel to classify chest X-ray images based on nodule location in lung zones. The multiclass classification experiment is performed using four popular SVM kernels namely linear, polynomial, radial based function (RBF) and sigmoid. Overall, we obtained high classification accuracy (>90%) for three classifiers that are RBF, polynomial and linear kernel while sigmoid kernel classifier is only moderately good at 82.7% accuracy. Besides, values in the confusion matrices revealed that the RBF and polynomial classifiers managed to classify test data into all classification classes. Conversely, classifiers based on linear and sigmoid kernel have missed at least one classification class. Since each classifier work differently based on their kernel types, we noticed that it is better to view them as a complimentary rather than treating them as competing options. This condition also revealed that we can modify the original SVM classification method to handle multiclass classification problem.
Bird Species Database Of Egg Volumes And Surface Areas

The computer-based analysis of 13458 photographs of avian eggs belonging to 257 species of 19 orders provided empirical data for the coefficients of egg volume and surface area calculation using the dimensions of length and breadth. The calculated species-specific and order-specific coefficients are given. The method of estimation of egg volume and surface by means of taking digital photographs with further computer calculation may be used to study the intrapopulation variability and to estimate incubation efficiency.
Quasi solution of a backward space fractional diffusion equation

Abstract In this paper, based on a quasi solution approach, i.e., a methodology involving minimization of a least squares cost functional, we study a backward space fractional diffusion equation. To this end, we give existence and uniqueness theorems of a quasi solution in an appropriate class of admissible initial data. In addition, in order to approximate the quasi solution, the finite element method is used. Since the obtained system of linear equations is ill-posed, we apply TSVD regularization. Finally, three numerical examples are given. Numerical results reveal the efficiency and applicability of the proposed method.
On reversible cascades in scale-free and Erd\H{o}s-R\'enyi random graphs

Consider the following cascading process on a simple undirected graph $G(V,E)$ with diameter $\Delta$. In round zero, a set $S\subseteq V$ of vertices, called the seeds, are active. In round $i+1,$ $i\in\mathbb{N},$ a non-isolated vertex is activated if at least a $\rho\in(\,0,1\,]$ fraction of its neighbors are active in round $i$; it is deactivated otherwise. For $k\in\mathbb{N},$ let $\text{min-seed}^{(k)}(G,\rho)$ be the minimum number of seeds needed to activate all vertices in or before round $k$. This paper derives upper bounds on $\text{min-seed}^{(k)}(G,\rho)$. In particular, if $G$ is connected and there exist constants $C>0$ and $\gamma>2$ such that the fraction of degree-$k$ vertices in $G$ is at most $C/k^\gamma$ for all $k\in\mathbb{Z}^+,$ then $\text{min-seed}^{(\Delta)}(G,\rho)=O(\lceil\rho^{\gamma-1}\,|\,V\,|\rceil)$. Furthermore, for $n\in\mathbb{Z}^+,$ $p=\Omega((\ln{(e/\rho)})/(\rho n))$ and with probability $1-\exp{(-n^{\Omega(1)})}$ over the Erd\H{o}s-R\'enyi random graphs $G(n,p),$ $\text{min-seed}^{(1)}(G(n,p),\rho)=O(\rho n)$.
A Review of Intrinsic Optical Imaging Serial Blockface Histology (ICI-SBH) for Whole Rodent Brain Imaging

In recent years, multiple serial histology techniques were developed to enable whole rodent brain imaging in 3-D. The main driving forces behind the emergence of these imaging techniques were the genome-wide atlas of gene expression in the mouse brain, the pursuit of the mouse brain connectome, and the BigBrain project. These projects rely on the use of optical imaging to target neuronal structures with histological stains or fluorescent dyes that are either expressed by transgenic mice or injected at specific locations in the brain. Efforts to adapt the serial histology acquisition scheme to use intrinsic contrast imaging (ICI) were also put forward, thus leveraging the natural contrast of neuronal tissue. This review focuses on these efforts. First, the origin of optical contrast in brain tissue is discussed with emphasis on the various imaging modalities exploiting these contrast mechanisms. Serial blockface histology (SBH) systems using ICI modalities are then reported, followed by a review of some of their applications. These include validation studies and the creation of multimodal brain atlases at a micrometer resolution. The paper concludes with a perspective of future developments, calling for a consolidation of the SBH research and development efforts around the world. The goal would be to offer the neuroscience community a single standardized open-source SBH solution, including optical design, acquisition automation, reconstruction algorithms, and analysis pipelines.
Natural Language Processing on Ambiguous Sentence Using NLP Tools: Core NLP, Apertium and PRAAT

Natural Language Processing (NLP) is the computerized approach to analyzing text that is based on both set of theories and a set of technologies. It can take the input in any form like text, audio and in any language. Pattern modules help us in understanding the natural language processes and how easily we can use it. In this paper, we are focusing on three NLP tools Core NLP, Apertium and PRAAT and using them on single ambiguous sentence.
Design and Development of an Inexpensive Sub-Nanosecond Gaussian Pulse Transmitter

A design of a hybrid Gaussian pulse transmitter using a transistor-based pulse generator and two pulse-shaping networks, a shorted stub delay circuit and a 90° hybrid coupler, is presented. A transistor-based pulse generator drives the pulse-forming network to achieve a sub-nanosecond pulsewidth. The shorted stub delay line was modified to optimize the frequency response and phase linearity. The transistor-based pulse generator is an inexpensive way of producing a square pulse of sharp rise time; this design achieved 280-ps rise time. A Schottky diode was used to eliminate the negative part of the output pulse as well as to reduce the ringing. Multiple simulations and measurements were performed to study the circuit behavior. The measurement results demonstrated a pulsewidth as sharp as 153 ps with 0.83-V amplitude and a low ringing on the order of 10%. The Gaussian monopulse was obtained by feeding the Gaussian pulse to a broadband 90° hybrid, which acts as a differentiator in the time domain. The pulse has a width on the order of 100 ps. The transmitter circuit was completed by connecting the monopulse circuit with an antenna. The measured radiated pulse in the far field of the transmitter is a second derivative Gaussian pulse with 85 ps of pulsewidth.
Half-inverse Sturm–Liouville problem on a time scale

In this paper, we consider a half-inverse Sturm–Liouville problem on a time scale which is the union of an interval and another time scale such as . We give a Hochstadt–Lieberman-type theorem for a Sturm–Liouville dynamic equation with Robin boundary conditions and investigate some special cases of this theorem.
Assessment of PLS-SEM Path Model for Coefficient of Determination and Predictive Relevance of Consumer Trust on Organic Cosmetics

In this paper the researchers investigated the coefficient of determination R-Square and predictive relevance (Q2) through Blindfolding. To fulfil the aim of the study, a structured quantitative research survey has been conducted with 640 sample size. The results emerged from the research survey shows that the R-Square has moderate strength for the endogenous latent variable trust and substantial strength or effect for the endogenous latent variables integrity, ability and benevolence. After calculating Q2 for the endogenous latent variable ability, benevolence, integrity and trust it was found that the model has predictive relevance for these constructs. The path coefficient threshold values for measuring between indicators namely, cause purview and emotional benefits, cause consequential and trust, cause rubric and trust, cause span and emotional benefits, emotional benefits and trust, functional benefits and trust, ability and trust, benevolence and trust and also for integrity and trust are above the threshold value of 1.96 substantiate the hypothesis and exerts direct relationship between two * Research Scholar, Jain University, Bangalore and Assistant ProfessorSelection Grade, School of Management, Manipal Institute of Technology, Manipal University, Manipal, Karnataka, India † Corresponding Author, Dean, Justice K S Hegde Institute of Management, Nitte University, Karkala, Udupi District, Karnataka, India; apmanipal@gmail.com Ushus JBMgt 15, 4 (2016) ISSN 0975-3311 2 variables. But the path coefficient threshold values between indicators namely, Cause purview and trust, cause consequential and trust, cause rubric and emotional benefits, cause span and trust, and also self-expressive and trust are below the threshold value of 1.96 does not substantiate the hypothesis and also does not exerts direct relationship between two variables. At the end of the paper, the author highlights the results, along with implications and limitations.
Robust Regression Methods for Solving Non-Spherical Problem in Linear Regression

ABSTRACT This study investigated the effects of non-spherical disturbance on the model parameters of some classical regression models. The aim was to examine the impacts of multicollinearity on the efficiency of classical Ordinary least squares (OLS) relative to the ridge regression (RR) and principal component regression (PCR) models. Data were simulated from a multivariate normal distribution with mean zero and variance-covariance matrix at various sample sizes 25, 50, 100, 200, 500 and 1000. To assess the asymptotic efficiency and consistency of these regression models in the presence of multicollinearity, the evaluation criteria used were the Variance, Absolute bias, Mean Square Error (MSE) and Mean Square Error of Prediction (MSEP). Results from this work showed that the RR model had smaller variance, absolute bias and MSE when it was compared with OLS. Also, the ridge estimator had the least MSEP when compared to both the OLS and PCR models. Hence, it can be concluded that the ridge estimator performed better than the OLS and PCR when explanatory variables are highly correlated.
X-ray emission from a metal depleted accretion shock onto the classical T Tauri star TW Hya

We present the X-ray spectrum of TW Hya observed at high and intermediate spectral resolution with the Reflection Grating Spectrometer (RGS) and the European Photon Imaging Camera (EPIC) onboard the XMM-Newton satellite. TW Hya is the first classical T Tauri star for which simultaneous X-ray data with both high spectral resolution and high sensitivity were obtained, thus allowing to probe the X-ray emission properties of stars in the early pre-main sequence phase. Despite TW Hya's high X-ray luminosity in excess of 10 30 erg/s its X-ray spectrum is dominated by emission lines from rather cool plasma ($T \approx 3$ MK), and only little emission measure is present at high temperatures ($T \approx 10$ MK). We determine photon fluxes for the emission lines in the high resolution spectrum, confirming the earlier result from Chandra that the predominant emission is from neon and oxygen, with comparatively weak iron lines. Further, the line ratios of He-like triplets of nitrogen, oxygen and neon require densities of $n_{\rm e} \sim 10^{13}\,{\rm cm^{-3}}$, about two orders of magnitude higher than for any other star observed so far at high spectral resolution. Finally, we find that nearly all metals are underabundant with respect to solar abundances, while the abundances of nitrogen and neon are enhanced. The high plasma density, the (comparatively) low temperature, and peculiar chemical abundances in the X-ray emitting region on TW Hya are untypical for stellar coronae. An alternative X-ray production mechanism is therefore called for and a natural explanation is an accretion column depleted of grain forming elements. The metal depletion could be either due to the original molecular cloud that formed TW Hya or due to a settling of dust in the circumstellar disk of TW Hya.
Linguistic Perception and second language acquisition

The author introduces the L2 Linguistic Perception (L2LP) model, a new formal and comprehensive proposal which integrates, synthesizes, and improves on previous studies, and therefore constitutes the most explanatorily adequate account of the whole process of L2 sound acquisition. More specifically, it proposes that the description of optimal L1 and L2 perception allows us to predict and explain the initial state, the learning task, and the end state that are involved in the acquisition process. It advances the hypothesis of Full Copying which constitutes a formal linguistic explanation for the prediction that learners will initially manifest an L2 perception that matches their optimal L1 perception. It also predicts that the degree of mismatch between perception grammars will define the number and nature of the learning tasks. With respect to L2 development, it posits that learners will either need to create new perceptual mappings and categories, or else adjust any existing mappings through the same learning mechanisms that operate in L1 acquisition. Finally, the model’s hypotheses of separate perception grammars and language activation predict that learners will achieve optimal L2 perception while preserving their optimal L1 perception.
Solving inverse problems using data-driven models

Recent research in inverse problems seeks to develop a mathematically coherent foundation for combining data-driven models, and in particular those based on deep learning, with domain-specific knowledge contained in physical–analytical models. The focus is on solving ill-posed inverse problems that are at the core of many challenging applications in the natural sciences, medicine and life sciences, as well as in engineering and industrial applications. This survey paper aims to give an account of some of the main contributions in data-driven inverse problems.
Multiple Quantum Phase Transitions at the superconducting LaTiO3/SrTiO3 interface

We study the magnetic field driven Quantum Phase Transition (QPT) in electrostatically gated superconducting LaTiO3/SrTiO3 interfaces. Through finite size scaling analysis, we show that it belongs to the (2+1)D XY model universality class. The system can be described as a disordered array of superconducting islands coupled by a two dimensional electron gas (2DEG). Depending on the 2DEG conductance tuned by the gate voltage, the QPT is single (corresponding to the long range phase coherence in the whole array) or double (one related to local phase coherence, the other one to the array). By retrieving the coherence length critical exponent \nu, we show that the QPT can be "clean" or "dirty" according to the Harris criteria, depending on whether the phase coherence length is smaller or larger than the island size. The overall behaviour is well described by a theoretical approach of Spivak et al., in the framework of the fermionic scenario of 2D superconducting QPT.
Adaptation-like effects in body weight attractiveness are not simply norm based

Perceptions of body weight attractiveness can be manipulated through visual exposure to bodies at one weight extreme. This implies that body weight is coded relative to a central ‘norm’ or prototype. Cross-cultural research, however, shows differences between groups’ perceptions of body weight attractiveness in terms of preferences for specific weight ranges as well as overall differences in the perceived ‘ideal’ weight. Here we test for the first time whether visual exposure to body weight extremes can induce such localised changes in preferences within individuals. British and Chinese participants in Studies 1 and 3 rated 23 bodies of known BMI for attractiveness, before and after viewing underweight or overweight/obese bodies. Results of Study 1 and a combined analysis of Studies 1 and 3 together showed no evidence of significant changes in participants’ ‘ideal’ weight, but the groups which viewed obese bodies during adaptation rated bodies of BMI 30kg/m2 significantly more positively at post-test than those who had viewed underweight bodies. In Study 2, participants viewed 48 bodies of known BMI in a randomised order. Proportion of obese bodies viewed in the preceding 10 trials predicted more positive ratings of overweight/obese bodies, but not any other weight category. Together, these data strongly suggest that we can induce ‘local’ changes in body ideals through exposure but do not support a strict norm-based approach.
New Integrating Methods for Time-Varying Linear Systems and Lie-Group Computations

In many engineering applications the Lie group calculation is very important. With this in mind, the subject of this paper is for an in-depth investigation of time-varying linear systems, and its accompanied Lie group calculations. In terms of system matrix A in Eq. (11) and a one-order lower fundamental solution matrix associated with the sub-state matrix function As, we propose two methods to nilpotentlize the timevarying linear systems. As a consequence, we obtain two different calculations of the general linear group. Then, the nilpotent systems are further transformed to a unique new system Ż(t) = B(t)Z(t), which having a special simple B(t) ∈ sl(n + 1,R) with Bs and B 0 0 vanishing. Correspondingly, we get a third calculation of the general linear group. By using the nilpotent property we can develop quite simple numerical scheme of nilpotent type to calculate the state transition matrix. We also develop a Lie-group solver in terms of the exponential mapping of B. Several numerical examples were employed to assess the performance of proposed schemes. Especially, the new Lie-group solver is very stable and highly accurate. Keyword: Lie-group solver, Nilpotent matrix, Time-varying linear system, Quadratic invariant
Gold nanoparticle-pentacene memory-transistors

We demonstrate an organic memory-transistor device based on a pentacene-gold nanoparticles active layer. Gold (Au) nanoparticles are immobilized on the gate dielectric (silicon dioxide) of a pentacene transistor by an amino-terminated self-assembled monolayer. Under the application of writing and erasing pulses on the gate, large threshold voltage shift (22V) and on/off drain current ratio of ∼3×104 are obtained. The hole field-effect mobility of the transistor is similar in the on and off states (less than a factor of 2). Charge retention times up to 4500s are observed. The memory effect is mainly attributed to the Au nanoparticles.
Investigations on Z-Source Based Cascaded Five Level Inverter

The Z source inverter is a novel power conversion topology that can buck and boost the given input voltage. Voltage source inverter (VSI) and current source inverter (CSI) have some common problems. The proposed work eliminates the limitations of both voltage source inverter and current source inverter by replacing multilevel inverter. This paper presents the new inverter topology based on combination of Z Source Inverter (ZSI) and Multi Level Inverter (MLI). The Z source inverter employs a unique impedance network to couple the main circuit to the power source. The basic structure includes one DC voltage source, Z network and multilevel inverter. Thus providing unique features that cannot be provided in both traditional voltage source and current source inverter. The cascaded MLI composed of eight switches to generating five voltage levels. The presence of multilevel inverters provide high output voltages with low harmonics without the use of transformers. The Z source concept can be applied to ac-dc, dc-ac, ac-ac and dc-dc power conversions. This work observes the rms (Root Mean Square) output voltage and presence of THD (Total Harmonic Distortion) in the output waveform by simulating the Z source based multilevel inverter using MATLAB/simulink.
Modeling of interlayer contact and contact pressure during fused filament fabrication

An in-line rheometer and data acquisition system are used to monitor the melt pressure, melt temperature, and environmental temperatures while producing parts via fused filament fabrication (FFF). Melt pressures are observed to increase when printing parts with small layer heights, which is attributed to the confined space created between the nozzle and the previous layer (i.e., an exit pressure). These exit pressures (referred to as contact pressure) and the resulting interlayer contact areas are analyzed for 2863 layers created at 21 different processing conditions. The measured contact pressure was found to directly influence the shape of the layers and the resulting interlayer contact. An intimate contact model based on contact pressure is combined with a wetting model to accurately predict the interlayer contact of FFF parts. This pressure-driven intimate contact model for FFF shows strong agreement with the observed interlayer contact. No theoretical model has previously existed for predicting interlayer contact, so this research provides a critical component for developing a comprehensive part strength model. Both the measurements and proposed model are sufficiently simple and accurate for real-time analysis of FFF quality, so the described in-line sensors provide valuable quality insights and are recommended for future researchers, printer manufacturers, and end-users.An in-line rheometer and data acquisition system are used to monitor the melt pressure, melt temperature, and environmental temperatures while producing parts via fused filament fabrication (FFF). Melt pressures are observed to increase when printing parts with small layer heights, which is attributed to the confined space created between the nozzle and the previous layer (i.e., an exit pressure). These exit pressures (referred to as contact pressure) and the resulting interlayer contact areas are analyzed for 2863 layers created at 21 different processing conditions. The measured contact pressure was found to directly influence the shape of the layers and the resulting interlayer contact. An intimate contact model based on contact pressure is combined with a wetting model to accurately predict the interlayer contact of FFF parts. This pressure-driven intimate contact model for FFF shows strong agreement with the observed interlayer contact. No theoretical model has previously existed for predicting inter.