Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring Polarization of the Cosmic Microwave Background with the South Pole Telescope Polarization Experiment

The South Pole Telescope Polarization experiment (SPTpol) is a camera consisting of 180 (588) pixels observing bands centered at 90 (150) GHz, installed on the South Pole Telescope in December 2012. It is a high-resolution, high-sensitivity instrument for mapping the polarized component of the Cosmic Microwave Background. In this thesis, we describe the development, testing, and deployment of transition edge sensor (TES) bolometers that make up the camera pixels, as well as the data analysis pipeline used to generate power spectra of the CMB. The tests used to measure various detector properties are described and their results displayed, and details of the analysis routines are explained. We conclude with preliminary results from SPTpol and a discussion of future directions for the experiment.
A Statistical Identification Model (SIM) For Textural Images

The extraction of Textural Images Properties and its Identification relative to one of textural Images groups was and still the main concern for many researchers and studies in many application fields that because of the wide applicability for such kind of studies on many applications. This research came for building a application model to determine Identification textural pieces to belong to one of proposed textural groups or not belong to any textural Images in the Experiment based on statistical model parameters for determine the range of convergence or divergence for each texture thoughtful, also research included percentages to the range of determining to belong to random piece textural to one of the textural images of the study. Discrimination process depend on the parameters of the proposed model. Experimental data representation as (24) textural images divided into (3) main groups. Experimental results showing the ability of textural features for identify and discriminate of textural part to belong to main textural images with difference identification ratio depending on (textural kinds , textural features). The proposed model can be adopted for many images application such as (MRI, Remote Sensing).
Robust topology optimization of phononic crystals with random field uncertainty

The uncertain spatial variation of material properties can remarkably affect the band gap characteristics of phononic crystals (PnCs). It is necessary to consider this issue when designing and manufacturing PnC materials/structures. This paper investigates a robust topology optimization method for designing the microstructures of PnCs by considering random‐field material properties. Herein, the spatial distribution of the material properties is first represented by a random field and then discretized into uncorrelated stochastic variables with the expansion optimal linear estimation method; stochastic band gap analysis is then conducted with polynomial chaos expansion. Furthermore, a robust topology optimization formulation of PnCs is proposed on the basis of the relative elemental density, where a weighted objective function handles the compromise of the mean value and standard deviation of the PnC band gap. The band gap response is analyzed, employing the finite element method for each sample of polynomial chaos expansion. In this context, the sensitivities of the stochastic band gap behaviors to the design variables are also derived. Numerical examples demonstrate that the proposed method can generate meaningful optimal topologies of PnCs with a relatively large width and less sensitive band gap. Additionally, the effects of the weight factors in the objective function and the variation coefficient of material properties are discussed.
Influence of Fraud Triangle Framework on the Fraud Prevention and Detection Programs in PT. XX

Given the significant variability of fraud instances in businesses of all sizes, it is captivating that despite their complexity, the fraud triangle's three elements can be used to explain all of them. As a result, the researcher was compelled to examine the impact of this framework on fraud programs. This report aims to thoroughly analyze the fraud triangle's influence on fraud prevention and detection programs, particularly at PT. XX. This qualitative research data collection comprises two main target population sources, the internal auditor team and the company's management, through a semi-structured interview approach where data is later processed using the in vivo and pattern coding technique. It is found from the study that each dimension of the fraud triangle which are pressure, opportunity, and rationalization, has a direct causal link to a fraud program described in the company's fraud SOP. The analysis concluded that the internal auditor team used the fraud triangle framework to identify patterns in fraud justifications and then developed several preventive fraud programs that management and users will implement to reduce the amount of fraud occurring in PT. XX. Further findings included the mutually reinforcing roles undertaken by the two divisions under study in creating the SOP and carrying out the company's fraud programs, which the study contends have already been effectively executed.
The Design of a Virtual Prototyping System for Authoring Interactive Virtual Reality Environments From Real-World Scans

Domain users (DUs) with a knowledge base in specialized fields are frequently excluded from authoring Virtual Reality (VR)-based applications in corresponding fields. This is largely due to the requirement of VR programming expertise needed to author these applications. To address this concern, we developed VRFromX, a system workflow design to make the virtual content creation process accessible to DUs irrespective of their programming skills and experience. VRFromX provides an in-situ process of content creation in VR that (a) allows users to select regions of interest in scanned point clouds or sketch in mid-air using a brush tool to retrieve virtual models, and (b) then attach behavioral properties to those objects. Using a welding use case, we performed a usability evaluation of VRFromX with 20 DUs from which 12 were novices in VR programming. Study results indicated positive user ratings for the system features with no significant differences across users with or without VR programming expertise. Based on the qualitative feedback, we also implemented two other use cases to demonstrate potential applications. We envision that the solution can facilitate the adoption of the immersive technology to create meaningful virtual environments.
An Ensemble-Based Parallel Deep Learning Classifier With PSO-BP Optimization for Malware Detection

Digital networks and systems are susceptible to malicious software (malware) attacks. Deep learning (DL) models have recently emerged as effective methods to classify and detect malware. However, DL models often relies on gradient descent optimization in learning, i.e., the Back-Propagation (BP) algorithm; therefore, their training and optimization procedures suffer from several limitations, such as high computational cost and local suboptimal solutions. On the other hand, ensemble methods overcome the shortcomings of individual models by consolidating their strengths to increase performance. In this paper, we propose an ensemble-based parallel DL classifier for malware detection. In particular, a stacked ensemble learning method is developed, which leverages five DL base models and a neural network as a meta model. The DL models are trained and optimized with a hybrid optimization method based on BP and Particle Swarm Optimization (PSO) algorithms. To improve scalability and efficiency of the ensemble method, a parallel computing framework is exploited. The proposed ensemble method is evaluated using five malware datasets (namely, Drebin, NTAM, TOP-PE, DikeDataset, and ML_Android), and high accuracy rates of 99.2%, 99.3%, 98.7%, 100%, and 100% have been achieved, respectively. Its parallel implementation also significantly enhances the computational speed by a factor up to 6.75 times. These results ascertain that the proposed ensemble method is effective, efficient, and scalable, outperforming many other compared methods in malware detection.
An effective online data monitoring and saving strategy for large-scale climate simulations

Abstract Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk, the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This paper proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.
Joint geometric and photometric direct image registration based on Lie algebra parameterization

In this paper, we consider direct image registration problem which estimate the geometric and photometric transformations between two images. The efficient second-order minimization method (ESM) is based on a second-order Taylor series of image differences without computing the Hessian under brightness constancy assumption. This can be done due to the fact that the considered geometric transformations is Lie group and can be parameterized by its Lie algebra. In order to deal with lighting changes, we extend ESM to the compositional dual efficient second-order minimization method (CDESM). In our approach, the photometric transformations is parameterized by its Lie algebra with compositional operation, which is similar to that of geometric transformations. Our algorithm can give a second-order approximation of image differences with respect to geometric and photometric parameters. The geometric and photometric parameters are simultaneously obtained by non-linear least-square optimization. Our algorithm preserves the advantages of the original ESM method which has high convergence rate and large capture radius. Experimental results show that our algorithm is more robust to lighting changes and has higher registration accuracy compared to previous algorithms.
Meandering Evolution and Width Variations: A Physics‐Statistics‐Based Modeling Approach

Many models have been so far proposed to simulate and understand the long‐term evolution of meandering rivers. Nevertheless, some modeling problems still need to be solved, for example, the physical soundness of long‐term simulations when width variations are accounted for. The present work proposes the use of statistical tools to capture the spatiotemporal variations of channel width and to embed their effect into a physics‐statistics‐based model that simulates the river bank evolution. Erosion and deposition processes are assumed to act independently, with a specific shear stress threshold for each of them. In addition, the width evolution is linked with a river‐specific probability density function. The analysis of a representative sample of meandering configurations, extracted from Landsat images, indicates that in many cases a generalized extreme value distribution nicely describes the along‐channel distribution of cross‐section width. For a given river, the parameters of this distribution keep almost constant in time. Significant variations are observed only after cutoff events that shorten the length of the river. The constraint of the river width based on the assumption of a generalized extreme value distribution ensures physically plausible configurations as the river moves throughout the floodplain, adapting continuously its local width. The application of the model to a reach of the Ucayali River appears to reasonably reproduce the planform river morphodynamics and yields realistic values of the cross‐section widths.
Self-adjointness of sound-proof models for magnetic buoyancy

An ideal magneto-hydrodynamic fluid, whether fully compressible or incompressible, is a Hamiltonian system. This implies that the equations describing perturbations to any static state are self-adjoint, a fact that is useful in obtaining stability criteria. To describe weakly compressible flows, there are a number of “sound-proof” models that eliminate sound waves by making approximations to the governing equations. However, such approximations may violate the Hamiltonian structure of the system. In a recent work, we have introduced a very general sound-proof model and determined conditions under which it closely approximates the linear regime of magneto-buoyancy instability, motivated by conditions in the solar interior. In the present work, we take a complementary approach, by deriving constraints under which the linearised sound-proof system is self-adjoint. We show that there is a unique set of self-adjoint sound-proof equations that conserves the same energy as the fully compressible system.
impact of domestic violence on cognitive and psychological development of children: A scoping review

Background: Domestic violence is an incident that affects all family members, including children. The impact of domestic violence needs to be identified from the beginning, so that early treatment can be given. The purpose of this study was to describe the impact of domestic violence on child development. Purpose: The purpose of this study was to explore the coping strategies of adolescents with divorced parents.Methods: This study used the Scoping Review method. Literature were sourced from CINAHL, PubMed, and Scopus. The keywords are “domestic violence” AND “child” AND “impact”. The criteria for articles in this study are full text, free access, English language, and the publication period of the last 10 years (2013-2022). Results: Nine articles were found discussing the impact of domestic violence on children's development, namely the psychological impact, social impact, and the impact on school life. Several samples from UK ranged from 8-336 respondents. These impacts occur due to trauma events in children that are not treated immediately. The impact will be even worse if there is no immediate intervention to reduce the impact of domestic violence. Conclusions: Domestic violence can cause disturbances to the development of children including psychological impacts, social impacts, and impacts on school life.
The singleton-geminate distinction can be rate dependent: Evidence from Maltese

Many languages distinguish short and long consonants, or singletons and geminates. The primary acoustic correlate of this distinction is the duration of the consonants. Given that the absolute duration of speech sounds varies with speech rate, the question rises to what extent the category boundary between singletons and geminates is sensitive to the overall speech rate (i.e., rate normalization). Next to rate normalization, there are two other possible explanations how singletons and geminates might be distinguished. First, it has been suggested that despite variation in absolute duration, the two categories remain distinct; that is, even in fast speech, geminates seldom take on durations that would be typical of singletons at slow speech rates. Second, it has been suggested that, with higher speech rate, both the duration of consonants and vowels shrink, so that the duration ratio of consonant and adjacent vowel is a rate independent cue for the singleton-geminate distinction. Using production and perception data from Maltese, we show that, first, the singleton-geminate distinction is endangered by speech-rate variation and, second, consequently undergoes speech-rate normalization.
Reassessing the Empirical Relationship between Health Expenditure, Governance and Economic Growth in Africa: Analysis of Nigerian Data

As an aspect of human capital, a positive association exists amongst health, productivity, and growth in output per capita. On the other hand, social infrastructure defined by the institution of governance has a direct effect on the environment upon which productive activities take place to determine outcomes. Nigeria like most African countries is bedevilled by the high prevalence of inadequate health financing and poor governance. Health financing for Nigeria consistently has fallen short of the AU health funding commitment of 15% of annual budgetary allocation to the health sector. Secondly, poor governance conditions available resources and shape the state of infrastructure, particularly health infrastructure and socioeconomic conditions. In turn, this determines individuals’ level of exposure to health risks and their capacity to actively contribute to productive activity for growth stimulation and sustainability. Against this backdrop, this study added to the existing literature in the context of Nigeria, by theoretically applying the Solow augmented Mankiw-Romer-Weil structural model in the examination of the impact of government size and governance quality in the health sector, on economic growth. Autoregressive Distributed Lag (ARDL) model was adopted in the estimation. Findings show that governance quality adversely affects growth and this reduces the capacity of health spending to stimulate growth by an almost equal margin. As a result, this study recommends legislative backing to the AU health funding commitment in Nigeria.
Observed Emotional Availability (EA) in the Early Months and Adolescence and Self-Reported EA at Any Age: A Narrative Review

Emotional availability (EA) is a relational construct that encompasses the ability of a dyad to share an emotionally connected, safe relationship. EA is operationalized by the multidimensional framework, which includes the observational EA Scales, the observational emotional attachment zones (EA-Z), as well as the EA Self-Report (EA-SR). The observational EA Scales measure the mutual interactive influences a child and parent may have on one another through observation of their affect and behavior and consist of 4 adult dimensions (sensitivity, structuring, nonintrusiveness, and nonhostility) and 2 child dimensions (responsiveness and involvement of the adult). The EA-Z refers to “emotional attachment styles” and is based on the summary of the observational EA Scales, assigned separately to adult and child (Emotionally Available, Complicated, Detached, Problematic/Disturbed/Traumatized or Traumatizing), with the potential that the emotional attachment perspective of the adult and child may not be the same. The EA-SR is about parental perceptions rather than observations, which should be taken into account in interpreting its findings. Collectively, these different measurements are referred to as the EA System. In this review, we focus on the EA-SR at any age, as well as EA observations, in the earliest months and adolescence.
Analysis of emerging trends and hot spots in respiratory biomechanics from 2003 to 2022 based on CiteSpace

Introduction: With the global prevalence of coronavirus disease 2019 (COVID-19), an increasing number of people are experiencing respiratory discomfort. Respiratory biomechanics can monitor breathing patterns and respiratory movements and it is easier to prevent, diagnose, treat or rehabilitate. However, there is still a lack of global knowledge structure in the field of respiratory biomechanics. With the help of CiteSpace software, we aim to help researchers identify potential collaborators and collaborating institutions, hotspots and research frontiers in respiratory biomechanics. Methods: Articles on respiratory biomechanics from 2003 to 2022 were retrieved from the Web of Science Core Collection by using a specific strategy, resulting a total of 2,850 publications. We used CiteSpace 6.1. R6 to analyze the year of publication, journal/journals cited, country, institution, author/authors cited, references, keywords and research trends. Co-citation maps were created to visually observe research hot spots and knowledge structures. Results and discussion: The number of annual publications gradually increased over the past 20 years. Medical Physics published the most articles and had the most citations in this study. The United States was the most influential country, with the highest number and centrality of publications. The most productive and influential institution was Harvard University in the United States. Keall PJ was the most productive author and MCCLELLAND JR was the most cited authors The article by Keall PJ (2006) article (cocitation counts: 55) and the article by McClelland JR (2013) were the most representative and symbolic references, with the highest cocitation number and centrality, respectively. The top keywords were “radiotherapy”, “volume”, and “ventilation”. The top Frontier keywords were “organ motion,” “deep inspiration,” and “deep learning”. The keywords were clustered to form seven labels. Currently, the main area of research in respiratory biomechanics is respiratory motion related to imaging techniques. Future research may focus on respiratory assistance techniques and respiratory detection techniques. At the same time, in the future, we will pay attention to personalized medicine and precision medicine, so that people can monitor their health status anytime and anywhere.
Optimal decisions for a dual-channel supply chain under information asymmetry

We discuss the optimal pricing and production decisions in a channel supply chain under symmetric and asymmetric information cases. We compare the optimum policies between the asymmetric information and the full information cases. We analyze the effect of the reseller's cost information on the profits of the partners. We find that information asymmetry is beneficial to the reseller, but is inefficient to the manufacturer and the whole supply chain. The information value increases with uncertainties arising from the reseller's cost structure. The dual-channel supply chain can share information and achieve coordination, if the lump-sum side payment from the manufacturer can make up the loss of the reseller due to sharing information. Finally, the effectiveness of the proposed models is verified by numerical examples.
Existence and orbital stability of normalized solutions for nonlinear Schrödinger equations

Dans cette these nous etudions l’existence et la stabilite orbitale de solutions ayant une norme prescrite pour deux types d’equations Schrodinger non lineaires dans , a savoir, une classe de systemes non lineaires couples de Schrodinger dans et une classe d’equations non lineaires de Schrodinger du quatrieme ordre dans . Ces deux types d’equations non lineaires de Schrodinger surviennent dans de nombreuses applications en mathematiques et physique, et sont devenus une grande attention dans les annees recentes. D’un point de vue physique, de telles solutions sont souvent referees comme des solutions normalisees, qui sont obtenues comme points critiques d’energie fonctionnelle associee sous contrainte avec une norme. Les elements cles de nos preuves sont les methodes variationnelles.