Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptation of extrapolation techniques in the proximal gradient algorithm and an iteratively reweighted l₁ algorithm

Many areas like engineering, statistics and computing et.al involve solving optimization models. The proximal gradient algorithm is a popular kind of algorithm for solving these problems. This algorithm, though simple and widely used, can be slow in practice; see for example [64, 90, 95]. To accelerate the proximal gradient algorithm, various approaches such as extrapolation techniques or line-search have been adopted. In this thesis, we first present some existing convergence results of the proximal gradient algorithm such as the global complexity. Then, we focus on the adaptation of the extrapolation techniques which is usually easier to implement in practice and leads to provably better iteration complexity for a large class of convex problems. We review this latter fact concerning iteration complexity and also present some existing convergence properties of the proximal gradient algorithm with extrapolation. Another popular kind of first-order algorithms is the iteratively reweighted algorithm. For this class of algorithms, the line-search techniques have also been adopted for acceleration while the extrapolation techniques have not. In view of the success in accelerating the proximal gradient algorithm empirically via extrapolations, in the last section of this thesis, we investigate how extrapolation techniques can be suitably incorporated into an iteratively reweighted `1 algorithm. We specifically consider extrapolation techniques motivated from three popular optimal first-order methods: the fast iterative soft-thresholding algorithm (FISTA) [10,68], the method
Validation of ATL Transformation to Generate a Reliable MVC2 Web Models

Technologies are constantly evolving. In order to benefit from technological advances, it is necessary to adapt the applications to these technologies. This operation is expensive for companies because it is often necessary to rewrite the code entirely. Where there is no capitalization of application functions and development is generally based on source code, the separation of concerns appears to be the necessary solution to the problem. Thus, functional specifications and technical specifications are taken into account separately by MDA approach. In this paper we present a new method of transformation validation and then we implement a new model transformation process based on MDA approach to generate an MVC2 Web model from Struts 2. This transformation begins by the validation of different transformation rules by applying the developed method of transformation validation. KeywordsMDA; Validation of transformation; Struts; ATL transformation; MVC2 architecture.
Lung Tumor Classification on Human Chest X-Ray Using Statistical Modelling Approach

Lung tumor is a group of abnormal cells that are formed from the process of excessive and uncoordinated cell division in the lung or known as a neoplasia. Neoplasia refers to the growth of new cells that are different from the growth of cells around it. The Tumor can formed to be benign tumors that not cause cancer and malignant tumors that can cause cancer. Chest X-ray is the most technique that used for detecting a lung tumor. Image processing is done by mean for distinguishing the classification lung tumor. Based on previous research the most used method is the mathematical method, but the result obtained are not maximal. Therefore, in this study we propose methods to classify lung tumor by using statistical modelling approach with logit link function based on parametric model, and nonparametric model using penalized spline estimator. Based on the proposed method, we get the classification accuracy of 80% for parametric model approach and 85% for nonparametric model approach, it means that the nonparametric model approach is better than the parametric model approach.
xtspj: A command for split-panel jackknife estimation

In this article, we present a new command, xtspj, that corrects for incidental parameter bias in panel-data models with fixed effects. The correction removes the first-order bias term of the maximum likelihood estimate using the split-panel jackknife method. Two variants are implemented: the jackknifed maximum-likelihood estimate and the jackknifed log-likelihood function (with corresponding maximizer). The model may be nonlinear or dynamic, and the covariates may be predetermined instead of strictly exogenous. xtspj implements the split-panel jackknife for fixed-effects versions of linear, probit, logit, Poisson, exponential, gamma, Weibull, and negbin2 regressions. It also accommodates other models if the user specifies the log-likelihood function (and, possibly but not necessarily, the score function and the Hessian). xtspj is fast and memory efficient, and it allows large datasets. The data may be unbalanced. xtspj can also be used to compute uncorrected maximum-likelihood estimates of fixed-effects models for which no other xt (see [XT] xt) command exists.
Optimal Design of Structural Parameters of Binocular Stereo Visual Sensor

The impact of structural parameters of binocular stereo visual sensor on the measurement accuracy of the sensor was studied based on 311-A optimum regression design.According to the experiment results,a regressive equation was established to set the relationship between measurement accuracy of binocular stereo visual sensor and its structural parameters.By resolving optimal model,the optimal combination of the parameters was got.The experiment results show that the proposed method is effective to improve the accuracy of binocular stereo visual sensor.
Simulation & testing of a multichannel sytem for 3D sound localization

Three-dimensional (3D) audio involves the ability to localize sound anywhere in a three-dimensional space. 3D audio can be used to provide the listener with the perception of moving sounds and can provide a realistic listening experience for applications such as gaming, video conferencing, movies, and concerts. The purpose of this research is to simulate and test 3D audio by incorporating auditory localization techniques in a multi-channel speaker system. The objective is to develop an algorithm that can place an audio event in a desired location by calculating and controlling the gain factors of each speaker. A MATLAB simulation displays the location of the speakers and perceived sound, which is verified through experimentation. The scenario in which the listener is not equidistant from each of the speakers is also investigated and simulated. This research is envisioned to lead to a better understanding of human localization of sound, and will contribute to a more realistic listening experience.
THE IMPACT OF E-LEARNING ON IMPROVING IRANIAN EFL LEARNERS’ LANGUAGE SKILLS: DECREASING LEARNING ANXIETY

Multimedia materials in the English classroom play a novel role in language learning. The report presents the advantages of the e-learning and its role in enhancing “English Foreign language” (EFL) students’ language skills and independent learning. An already running and established virtual learning environment, namely the e-learning, was used successfully in the Azad University in Iran. Participants in this study were of EFL (English as a Foreign language) university students majoring in computer engineering and IT (information technology). A pretest and posttest included listening, reading comprehension and grammatical points contain multiple choices, fill in the blank, substitution, written form. Two classes were randomly selected as a control group and experimental group in the study. The different activities and resources that were provided by e-learning have been described with an analysis of how they can be used to develop EFL students’ language proficiency and independent learning. The purpose of this study was to expose a group of Iranian students to an e-learning program and find out the effects of this exposure on their learning skills. The study conducted claims to identify and understand the relationship between multimedia techniques in language teaching and learners’ language learning. Its results also suggest that a multimedia environment can reduce student anxiety and provide a less stressful classroom environment. Put otherwise, multimedia tools enable English teachers to help students to both improve their English performance and lower their language anxiety. Keywords: CALL; E-Learning; English as a Foreign Language ( EFL ); Scaffolding
KEPIMPINAN DISTRIBUTIF, KEADAAN DALAM SEKOLAH, DAN KOMITMEN GURU UNTUK BERUBAH: SATU ANALISA PARTIAL LEAST SQUARES[DISTRIBUTIVE LEADERSHIP, IN-SCHOOL CONDITION, AND TEACHERS’ COMMITMENT TO CHANGE: A PARTIAL LEAST SQUARES ANALYSIS]

Kajian ini bertujuan untuk mengkaji hubungan antara kepimpinan distributif terhadap komitmen guru untuk berubah dengan keadaan dalam sekolah sebagai mediator. Kajian ini menggunakan reka bentuk kajian kuantitatif dengan kaedah tinjauan. Sampel kajian terdiri daripada 357 orang guru-guru sekolah menengah yang dipilih secara rawak daripada 20 buah sekolah di Daerah Seberang Perai Utara dan Seberang Perai Tengah di Pulau Pinang, Malaysia. Pendekatan Partial Least Squares Structural Equation Modeling (PLS-SEM) dengan perisian SmartPLS 3.2. 7 digunakan untuk penganalisaan data. Dapatan kajian ini menunjukkan bahawa kepimpinan distributif mempunyai hubungan positif yang signifikan dengan komitmen guru untuk berubah secara langsung (β=0.472, p<.05). Keadaan dalam sekolah mempunyai kesan pengantaraan yang signifikan dalam hubungan antara kepimpinan distributif dan komitmen guru untuk berubah (β=0.228, p<.05). Dapatan kajian memberi implikasi terhadap pihak pembuat polisi dan pentadbir sekolah bahawa kepimpinan distributif dan keadaan dalam sekolah merupakan elemen yang penting untuk meningkatkan komitmen guru untuk berubah dalam pengajaran abad ke-21.Kata kunci: Keadaan dalam sekolah, kepimpinan distributif, komitmen guru untuk berubah, Partial Least Squares Structural Equation Modeling (PLS-SEM), pembuat polisi.ABSTRACTThis study aims to investigate the relationships between distributed leadership and teachers’ commitment to change with in-school condition as the mediator. This study employed quantitative survey research design. Data consisted of 357 secondary teachers who were selected randomly from 20 schools in northern and central districts in Seberang Prai in Penang, Malaysia. Partial Least Squares Structural Equation Modeling (PLS-SEM) approach with SmartPLS 3.2. 7 software was used for data analysis. Findings revealed significant and positive direct relationship between distributed leadership and teachers’ commitment to change (β=0.472, p<.05). In-school condition has significant mediating effects between distributed leadership and teachers’ commitment to change (β=0.228, p<.05). Findings informed implications for policymakers that distributed leadership and in-school condition are two ultimate elements to enhance teachers’ commitment to change in the teaching of 21st century.Keywords: Distributed leadership, in-school condition, Partial Least Squares Structural Equation Modeling (PLS-SEM), policymakers, teachers’ commitment to changeCite as: Thien, L. M. & Tan, M. Y. (2019). Kepimpinan distributif, keadaan dalam sekolah, dan komitmen guru untuk berubah: Satu analisa partial least squares. Journal of Nusantara Studies, 4(1), 159-185. http://dx.doi. org/10.24200/jonus.vol4iss1pp159-185
Study of V/Q Non-Linearity in Scientific CMOS Sensor

Scientific CMOS sensor usually manifests V/Q non-linearity in charge-to-voltage conversion. Starting from the mechanism underlying this non-linearity, we build the V/Q non-linearity model to study the influence of modulation transfer function (MTF) and signal-to-noise ratio (SNR). Meanwhile, simulation verification is carried out. The results show that V/Q non-linearity improves SNR but causes the decrease of MTF of the electronic device. We propose the combination of video response curve with photo response non-uniformity (PRNU) noise curve to locate V/Q non-linearity. The validity of this method is proved by simulation verification and physical experiment. The present study provides reference for design optimization and compensation for non-linearity in scientific CMOS sensor.
Gaussian Mixture Message Passing for Blind Known Interference Cancellation

This paper proposes a Gaussian mixture message passing (GMMP) scheme to implement the blind known-interference cancellation (BKIC). Being aware of interference data as a priori information, the BKIC aims at canceling the interference without estimating the interference channel. Since the target signals are represented by continuous real-valued variables, the previous BKIC scheme is constructed as a real-valued belief propagation (RBP) for implementing message passing on the factor graph that represents the corresponding signal model. To implement the RBP-BKIC, the real-valued variables are actually quantized into vectors of discrete values. As such, the quantized RBP-BKIC has some drawbacks: 1) its performance is determined by the quantization step size and 2) it can only be applied to real signaling with 1-D PAM modulations. To overcome these drawbacks, we propose a GMMP scheme for the BKIC. First, we reveal that all messages passing over the factor graph of BKIC systems can be exactly represented by the mixtures of weighted Gaussian probability density functions. Superior to the quantized RBP-BKIC, we further show that the proposed GMMP scheme is an exact and efficient solution to the BKIC. In particular, it can approach performances of point-to-point communication systems with complex QAM modulations at the cost of affordable computational complexities. Moreover, we put forth a message passing framework that combines the GMMP-BKIC and the channel decoding into an iterative message passing scheme.
Leucine-rich Repeat Kinase 2 (LRRK2) Phosphorylates Rab10 in Glia and Neurons

InAm Neuroscience Research Center, Sanbon Medical Center, College of Medicine, Wonkwang University, Gyeonggido 15865, Korea Paik Institute for Clinical Research, Inje University College of Medicine, Busan 47392, Korea Department of Convergence Biomedical Science, Inje University College of Medicine, Busan 47392, Korea Department of Neurology, Sanbon Medical Center, College of Medicine, Wonkwang University, Gyeonggido 15865, Korea
Analysis and Design of Interior Permanent Magnet Synchronous Motor Using a Sequential-Stage Magnetic Equivalent Circuit

In the interior permanent magnet synchronous motor (IPMSM) design for the traction motor of fuel cell electric vehicles (FCEVs), it is necessary to analyze the nonlinear characteristics including saturation due to the requirement of a high torque density. The finite element method (FEM) is the most widely used technique for electric machine designs because complicated computations can be taken into account. However, a large amount of analysis over the entire design is a computationally large burden. To address this problem, this paper proposes a fast and accurate analysis method, sequential-stage magnetic equivalent circuit (SSMEC). The proposed method consists of no-load, q-axis circuit analysis, d-axis circuit analysis, and motor characteristic calculation. Because the proposed method can quickly and accurately analyze the complex shapes of an IPMSM, it can be used effectively throughout the entire motor design process. The effectiveness of the proposed SSMEC was verified in comparing with experimental results.
Final report for grant DE-FG02-06ER64182: "Evaluation and Improvement of the Cloud Resolving Model Component of the Multi-Scale Modeling Framework"

The overall aim of the larger collaborative effort of which this project was part was to evaluate and improve the cloud system resolving model (CSRM) at the heart of the multi-scale modeling framework (MMF). Our task at the University of Colorado our effort was to develop methods that would let us evaluate the performance of cloud-scale models at the ARM SGP site using ARM remote sensing products.
A Binary Array Asynchronous Sorting Algorithm with Using Petri Nets

Nowadays the tasks of computations speed-up and/or their optimization are actual. Among the approaches on how to solve these tasks, a method applying approaches of parallelization and asynchronization to a sorting algorithm is considered in the paper. The sorting methods are ones of elementary methods and they are used in a huge amount of different applications. In the paper, we offer a method of an array sorting that based on a division into a set of independent adjacent pairs of numbers and their parallel and asynchronous comparison. And this one distinguishes the offered method from the traditional sorting algorithms (like quick sorting, merge sorting, insertion sorting and others). The algorithm is implemented with the use of Petri nets, like the most suitable tool for an asynchronous systems description.
Structure et élasticité des films moussés : Effets de la distribution des tailles des bulles

L’objet de ce travail experimental est l’etude de la mecanique de films de mousses dont la structure est confinee par leur faible epaisseur. A partir d’une methode de moussage de dispersion de particules de polyurethane, nous sommes parvenus a controler, de facon independante, la fraction d’air (ou la densite) de ces films, leur epaisseur e et la distribution des tailles de leurs pores (de diametre moyen D _b). Pour ce dernier parametre, nous nous sommes interesses au cas de distributions monodisperse, bidisperse et polydisperses. Les differentes structures obtenues ont ete etudiees par tomographie aux rayons X, de maniere a quantifier l’ordre induit par le confinement (profils de densite, position des centres de pores, tailles des elements structuraux,…). Nous nous sommes interesses a la mecanique de ces films de mousse en tension (dans le plan du film) et en compression (dans le plan orthogonal au film). Un travail specifique mene sur la matrice de polymere nous a permis de determiner des grandeurs adimensionnees (modules et contraintes caracteristiques) permettant une comparaison avec les donnees et les modeles de la litterature. Nous montrons qu’en plus de l’effet classique de la densite, le nombre moyen de bulles a travers l’epaisseur, i.e. e⁄D _b , est un parametre determinant pour les deux directions de sollicitation. En elongation, les couches parietales contribuent a augmenter le module elastique des films par rapport a une mousse non-confinee. Ce renforcement est d’autant plus important (jusqu’a deux fois) lorsque e⁄D _b est faible, quel que soit le type de distribution des tailles de pores. En compression, les couches parietales ne contribuent pas directement, mais le confinement joue egalement un role important, avec cette fois-ci un impact determinant de la distribution des tailles de pores. Ainsi, un film de mousse monodisperse est ordonne comme un polycristal et presente des caracteristiques mecaniques nettement plus elevees qu’un film de mousse polydisperse, comportant de nombreuses zones de faiblesse mecanique engendrees par les defauts d’empilement des bulles initiales. Les films de mousse bidisperses ont une reponse mecanique qui se rapproche soit des mousses monodisperses, pour de relativement grands rapports e⁄D _b , soit des mousses polydisperses, pour de relativement petits rapports( e)⁄D _b
Mutual Information Based Tracking With Mobile Sensors

In order to utilize mobile sensor nodes in a sensing and estimation problem, one must carefully consider the optimal placement of those sensor nodes and simultaneously account for the cost incurred in moving the sensor nodes. We present an approximate dynamic programming approach to a tracking problem with mobile sensor nodes. We utilize mutual information as the objective for optimal sensor placement. We show how a constrained dynamic programming approach allows us to balance estimation quality against mobility costs. However this constrained optimization problem is NP -hard. We present a set of approximations that allow this dynamic program to be solved with polynomial complexity in the number of sensors. We present a greedy multiple time step planning algorithm that greedily selects the most informative paths over a fixed planning horizon. These approximation algorithms are verified via simulation to give a comparative analysis of estimate quality and mobility costs. Thesis Supervisor: Daniela Rus Title: Professor Thesis Supervisor: John Fisher Title: Principal Research Scientist
An Exact Solution for Transient Anisotropic Heat Conduction in Composite Cylindrical Shells

In this study, an analytical solution is proposed for the problem of transient anisotropic conductive heat transfer in composite cylindrical shells. The composite shells are considered to have directional heat transfer properties, which is due to the existence of fibers which can be winded in any direction. The composite shells usually show high conductivity in the direction parallel to fiber direction and low conductivity in other two orthogonal directions. To solve the heat transfer partial differential equation, finite Fourier transform and separation of variables method are used. The present solution is used to find the temperature distribution in a composite cylindrical vessel for which the composite material is graphite/epoxy and the vessel is prone to an external heat flux and also ambient flow. The analytical solution is verified perfectly by the data obtained from a second-order finite difference solution. The solution is used to investigate the effects of values of fiber angle and material conductivity coefficients on temperature distribution of the composite cylindrical vessel. The results show the important role of fiber angle values on the temperature distribution of vessel.
Lights in Dark Places: Inferring the Milky Way Mass Profile using Galactic Satellites and Hierarchical Bayes

Despite valiant effort by astronomers, the mass of the Milky Way (MW) Galaxy is poorly constrained, with estimates varying by a factor of two. A range of techniques have been developed and different types of data have been used to estimate the MW’s mass. One of the most promising and popular techniques is to use the velocity and position information of satellite objects orbiting the Galaxy to infer the gravitational potential, and thus the total mass. Using these satellites, or Galactic tracers, presents a number of challenges: 1) much of the tracer velocity data are incomplete (i.e. only line-of-sight velocities have been measured), 2) our position in the Galaxy complicates how we quantify measurement uncertainties of mass estimates, and 3) the amount of available tracer data at large distances, where the dark matter halo dominates, is small. The latter challenge will improve with current and upcoming observational programs such as Gaia and the Large Synoptic Survey Telescope (LSST ), but to properly prepare for these data sets we must overcome the former two. In this thesis work, we have created a hierarchical Bayesian framework to estimate the Galactic mass profile. The method includes incomplete and complete data simultaneously, and incorporates measurement uncertainties through a measurement model. The physical model relies on a distribution function for the tracers that allows the tracer and dark matter to have different spatial density v Ph.D. Thesis Gwendolyn M. Eadie McMaster University Physics & Astronomy profiles. When the hierarchical Bayesian model is confronted with the kinematic data from satellites, a posterior distribution is acquired and used to infer the mass and mass profile of the Galaxy. This thesis walks through the incremental steps that led to the development of the hierarchical Bayesian method, and presents MW mass estimates when the method is applied to the MW’s globular cluster population. Our best estimate of the MW’s virial mass is Mvir = 0.87 (0.67, 1.09)×10M . We also present preliminary results from a blind test on hydrodynamical, cosmological computer-simulated MW-type galaxies from the McMaster Unbiased Galaxy Simulations. These results suggest our method may be able to reliably recover the virial mass of the Galaxy.