Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Aero-Acoustic Simulation of the HART II Rotor with the Compact Pade Scheme

One major diffculty in the design of quiet rotor blades is the correct numerical prediction of blade vortex interaction (BVI) noise in descent flight. Current second order spatial discretization schemes inherently have too much numerical dissipation to correctly conserve vorticity in the computational fluid dynamics (CFD) simulation. Higher order methods have proven their worthiness to alleviate this problem, yet are costly in terms of computational resources. In this paper, the 4th order implicit compact Pade scheme based on the finite difference formulation of the RANS equations is employed to convect the vortices in the simulation. The approach is paired with the classical finite volume approach with the Jameson-Schmidt-Turkel (JST) scheme. The robustness and flexibility of the JST scheme are exploited in the nearfield of the rotor blades and fuselage, while in the mid- and farfield the Pade scheme is utilized. This approach is validated against the experimental data of the HART II wind tunnel campaign. Different grid resolutions are examined as well as simulation strategies ranging from inviscid isolated rotor simulation up to viscous simulation including the fuselage. This hybrid simulation technique demonstrates the usefulness due to its high efficiency, while for design purposes the simplified physics yield an additional speed-up of the turn-around time.
Ensemble Learning for Breast Cancer Lesion Classification: A Pilot Validation Using Correlated Spectroscopic Imaging and Diffusion-Weighted Imaging

The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional echo-planar correlated spectroscopic imaging (5D EP-COSI) and diffusion-weighted imaging (DWI). Twenty-four different metabolite and lipid ratios with respect to diagonal fat peaks (1.4 ppm, 5.4 ppm) from 2D spectra, and water and fat peaks (4.7 ppm, 1.4 ppm) from one-dimensional non-water-suppressed (NWS) spectra were used as the features. Additionally, water fraction, fat fraction and water-to-fat ratios from NWS spectra and apparent diffusion coefficients (ADC) from DWI were included. The nine most important features were identified using recursive feature elimination, sequential forward selection and correlation analysis. XGBoost (AUC: 93.0%, Accuracy: 85.7%, F1-score: 88.9%, Precision: 88.2%, Sensitivity: 90.4%, Specificity: 84.6%) and GradientBoost (AUC: 94.3%, Accuracy: 89.3%, F1-score: 90.7%, Precision: 87.9%, Sensitivity: 94.2%, Specificity: 83.4%) were the best-performing models. Conventional biomarkers like choline, myo-Inositol, and glycine were statistically significant predictors. Key features contributing to the classification were ADC, 2D diagonal peaks at 0.9 ppm, 2.1 ppm, 3.5 ppm, and 5.4 ppm, cross peaks between 1.4 and 0.9 ppm, 4.3 and 4.1 ppm, 2.3 and 1.6 ppm, and the triglyceryl–fat cross peak. The results highlight the contribution of the 2D spectral peaks to the model, and they demonstrate the potential of 5D EP-COSI for early breast cancer detection.
Maximum power point tracking with constraint feedback linearization controller and modified incremental conductance algorithm

In this paper, a robust and constraint feedback linearization controller (FLC) with a modified incremental conductance (Inc.Cond) is proposed for maximum power point tracking (MPPT) in the photovoltaic (PV) systems and overall closed-loop internal stability is guaranteed. The proposed technique is independent with respect to load and is robust against disturbances in the load voltage. A boost chopper converter is utilized as an interface between the PV panel and load to control the system at the best operating point. A modified Inc.Cond method based on current orientation and without division equations is presented. The Inc.Cond method is utilized to generate the desired current for the FLC. The FLC navigates the PV panel to the maximum power point with high speed, whereas the control signal (duty cycle) constraints are monitored. Finally, the MPPT technique is validated through simulation and experimental results and two scenarios are defined to confirm controller robustness and modified Inc.Cond performance.
Vehicle Detection Based on Adaptive Multimodal Feature Fusion and Cross-Modal Vehicle Index Using RGB-T Images

Target detection is a critical task in interpreting aerial images. Small target detection, such as vehicles, is challenging. Different lighting conditions affect the accuracy of vehicle detection. For example, vehicles are difficult to distinguish from the background in red, green, blue (RGB) images under low illumination conditions. In contrast, under high-illumination conditions, the color and texture of vehicles are not significantly different in thermal infrared (TIR) images. To improve the accuracy of vehicle detection under various illumination conditions, we propose an adaptive multimodal feature fusion and cross-modal vehicle index (AFFCM) model for vehicle detection. Based on the single-stage object detection model, AFFCM uses RGB and TIR images. It comprises three parts: 1) the softpooling channel attention (SCA) mechanism calculates the cross-modal feature weights of the RGB and TIR features using a fully connected layer during global weighted pooling; 2) we design a multimodal adaptive feature fusion (MAFF) module based on the cross-modal feature weights derived from the SCA mechanism; the MAFF selects features with high weight, compresses redundant features with low weight, and performs adaptive fusion using a multiscale feature pyramid; and 3) a cross-modal vehicle index is established to extract the target area, suppress complex background information, and minimize false alarms in vehicle detection. The mean average precision (mAP) on the Drone Vehicle dataset is 14.44% and 5.02% higher than that obtained using only RGB or TIR images. The mAP is 2.63% higher than that of state-of-the-art methods that utilize RGB and TIR images.
GAMMA MIXTURE MODELED WITH "SECOND KIND STATISTICS" : APPLICATION TO SAR IMAGE PROCESSING

SAR images are classically analyzed with the help of Goodman approach and multiplicative noise. By this way, speckle is modeled by a Gamma law (for intensity images). A new approach based on “second kind statistics” [l] identifies multiplicative noise as a “Mellin convolution” [Z] yielding oversimple expression when texture is not homogeneous. In this article, we propose to use this new approach for solving the problem of binary additive mixture of Gamma law[3] and to apply the results to SAR image processing.
Unlocking The Secret to Arabic Fluency: Exploring The Critical Role of Language Environment in Maximizing Arabic-Speaking Outcomes

Maximizing Arabic-speaking learning outcomes for MAN 1 Sungai Penuh students has been a significant goal. However, many students struggle to become proficient in the language despite this. This study aims to understand the underlying issues better. The research utilized a case study approach, incorporating interviews, observations, and documentation as data collection methods. Data reduction, display, and conclusion were employed as data analysis techniques. The results of this study indicate that the lack of a language-rich environment has hindered students' ability to develop Arabic speaking skills. The findings highlight the critical role of an immersive language environment in facilitating Arabic language learning. In conclusion, this research underscores the need for a language-rich environment for effective Arabic language learning. By providing an environment that encourages and supports Arabic language use, students at MAN 1 Sungai Penuh may be better equipped to acquire the language skills they need to succeed.
Workarounds and shadow IT – balancing innovation and risk

A significant amount of research has been carried out into the way in which employees use workarounds and shadow IT to cope with the complexity of enterprise applications. There is a similar situation in the use of clinical record applications. However neither qualitative or quantitative survey techniques give any indication of the scale of the adoption of workarounds. In both enterprise and clinical settings workarounds can either introduce a substantial element of corporate risk or provide a basis for process innovation. The research that has been carried out primarily focuses on data-rich processes and little attention has been given to workarounds in a digital workplace where the processes may be significantly more complex that in enterprise data processes
Microbiota Composition during Fermentation of Broomcorn Millet Huangjiu and Their Effects on Flavor Quality

Broomcorn millet Huangjiu brewing is usually divided into primary fermentation and post-fermentation. Microbial succession is the major factor influencing the development of the typical Huangjiu flavor. Here, we report the changes in flavor substances and microbial community during the primary fermentation of broomcorn millet Huangjiu. Results indicated that a total of 161 volatile flavor compounds were measured during primary fermentation, and estragole was detected for the first time in broomcorn millet Huangjiu. A total of 82 bacteria genera were identified. Pediococcus, Pantoea, and Weissella were the dominant genera. Saccharomyces and Rhizopus were dominant among the 30 fungal genera. Correlation analysis showed that 102 microorganisms were involved in major flavor substance production during primary fermentation, Lactobacillus, Photobacterium, Hyphodontia, Aquicella, Erysipelothrix, Idiomarina, Paraphaeosphaeria, and Sulfuritalea were most associated with flavoring substances. Four bacteria, Lactobacillus (R1), Photobacterium (R2), Idiomarina (R3), and Pediococcus (R4), were isolated and identified from wheat Qu, which were added to wine Qu to prepare four kinds of fortified Qu (QR1, QR2, QR3, QR4). QR1 and QR2 fermentation can enhance the quality of Huangjiu. This work reveals the correlation between microorganisms and volatile flavor compounds and is beneficial for regulating the micro-ecosystem and flavor of the broomcorn millet Huangjiu.
Exploring the anti‐corruption abilities of e‐procurement in Ghanaian mining companies

The anti‐corruption capabilities of e‐procurement have not gotten any attention in Ghana, although the success factors of e‐procurement adoption have been thoroughly researched. The study's main objective is to assess how e‐procurement may reduce procurement fraud and corruption in Ghanaian mining enterprises. A self‐administered questionnaire was used to gather information on the extent to which e‐procurement anti‐corruption factors outlined in the literature reduced procurement fraud and corruption in Ghanaian mining firms from the perspectives of sector practitioners. The data was then analyzed using factor analysis. The study revealed the breaking of the monopoly of power, transparency and accountability, and breaking of information asymmetry, as e‐procurement anti‐corruption variables that combat procurement fraud and corruption in the mining companies. The most effective e‐procurement factor for preventing procurement fraud and corruption is the breaking of the monopoly of power, followed by transparency and accountability, and the least is the breaking of information asymmetry. To reduce procurement fraud and corruption, the government and organizations that manage procurement activities will now have a better understanding of the e‐procurement anti‐corruption activities and be guided as such.
Design aspects of rating scales in questionnaires

Since their introduction by Thurstone (1929) and Likert (1932), rating scales have been determinant in questionnaires. A rating scale usually defines the graduations out of a continuum such as agreement, intensity, frequency, or satisfaction. Respondents evaluate questions and items by marking the appropriate category, which usually concerns personal characteristics, opinions, and behavior Parducci (1983) defines responses as functions of the continuum of a rating scale. They range between the end poles and depend on the graduation of the scale; however, their quality should not be influenced by the characteristics of the rating scale. Menold and Bogner (2016) review characteristics of rating scales as follows: total number of categories, usage of middle and “do not know” options, category labeling, scale orientation (starting with a negative or a positive value, or a lower or a higher value), scale polarity (usage of verbal opposites), and visual presentation. The best design of rating scales remains controversial. Moreover, characteristics of rating scales can affect the quality of measurement (Krosnick and Fabrigar, 1997). Menold and Tausch (2016) demonstrate that different total numbers of categories have different psychometric properties and that verbalisation affects measurement. Data can no longer be compared if they have been produced from different rating scales. Graduations used in rating scales involve metric properties, because they are supposed to correspond to equal differences between categories. Orth (1982) and Westermann (1985) criticized this assumption of equidistance. The socalled “visual design” (Christian and Dillman, 2004; Tourangeau et al., 2007) was introduced to make out the influence of the graphical presentation of rating scales on response. Responses could, conciously or not, be biased by the graphical features. According to Schaefer and Dykema (2011: 912), “although past research often allows us to predict how a marginal distribution will be affected . we are too often unable to say which version of a question is more reliable or valid. ” That is why the reliability and validity of rating scales constitute an issue. This special
Lattice modes and plasmonic linewidth engineering in gold and aluminum nanoparticle arrays

Metallic nanoparticles arranged in arrays have been shown to support both localized surface plasmons (LSPs) and diffractive grating behavior, related to the inter-particle period. By selecting both the period and particle size, it is possible to generate lattice modes that are caused by interference of the LSP and the grating Rayleigh anomaly. These hybrid modes show a Fano-like lineshape with reduced linewidth relative to the LSP mode. In this paper, we study the lattice modes supported by gold and aluminum nanoparticle arrays in the visible and UV, both experimentally and theoretically. The measured and simulated dispersion curves allow us to comprehensively analyze the details of the LSP coupling in the array. We show that when the spectral position of the Rayleigh anomaly, dependent on the period of the array, is slightly blue-shifted with respect to the LSP resonance, the quality factor of the lattice mode is significantly increased. We also provide evidence that the formation of the lattice modes critically depends on the incident light polarization, with maximum coupling efficiency between LSPs and the in-plane scattered light when the polarization direction is perpendicular to the propagation direction of the grazing wave. The results obtained provide design rules for high quality factor resonances throughout the visible and ultraviolet spectral ranges.
Reduced-parameter motion estimation in PET using respiratory motion models

Positron emission tomography (PET) is a modality with high temporal resolution but long acquisition times. This can result in blurred images due to subject motion. Respiratory motion in particular is an unavoidable source of degradation, which can cause issues with quantification and clinical interpretation. An important characteristic of respiratory motion is its pseudo-cyclic nature, which has previously been exploited to form mathematical models which describe the motion, driven by a small number of parameters. The aim of this project is to use this form of motion modelling to estimate motion using information acquired from both dynamic magnetic resonance (MR) scans and from the acquired PET data itself to correct for the effects of motion. The use of motion models in this way can overcome the high levels of noise which otherwise characterise the estimation problem. First the feasibility of using motion models is investigated using synthetic data consisting of individual PET gates simulated using real motion information. The PET gates are registered using constraints provided by a motion model derived from MR images. A novelty of this approach is that this is the first time PET data have been used to indirectly drive a parameterised motion model. The next part of the project attempts to formalise the motion estimation process by incorporating the reduced-parameter motion model into the PET image reconstruction. An analytical gradient for a single motion parameter that drives the model is derived from the same objective function used to estimate the image. This results in significant noise averaging, providing robustness to the high level of noise typically found in PET data acquired over short time frames. This is shown to improve robustness to noise well enough that the number of gates can be increased and overall motion correction performance improved. Finally, the formulation is extended further to also model photon attenuation effects. This is shown to improve the performance of the algorithm when dealing with synthetic data that includes attenuation.
Frames, polarity and causation

A polarity-sensitive item (PSI), as traditionally defined, is an expression that is restricted to either an affirmative or negative context. PSIs like ‘lift a finger’ and ‘all the time in the world’ sub-serve discourse routines like understatement and emphasis. Lexical–semantic classes are increasingly invoked in descriptions of the properties of PSIs. Here, we use English corpus data and the tools of Frame Semantics (Fillmore, 1982, 1985) to explore Israel's (2011) observation that the semantic role of a PSI determines how the expression fits into a contextually constructed scalar model. We focus on a class of exceptions implied by Israel's model: cases in which a given PSI displays two countervailing patterns of polarity sensitivity, with attendant differences in scalar entailments. We offer a set of case studies of polarity-sensitive expressions – including verbs of attraction and aversion like ‘can live without’, monetary units like ‘a red cent’, comparative adjectives and time-span adverbials – that .
Pre-nebular Light Curves of SNe I

We compare analytic predictions of supernova light curves with recent high-quality data from SN2011fe (Ia), KSN2011b (Ia), and the Palomar Transient Factory and the La Silla-QUEST variability survey (LSQ) (Ia). Because of the steady, fast cadence of observations, KSN2011b provides unique new information on SNe Ia: the smoothness of the light curve, which is consistent with significant large-scale mixing during the explosion, possibly due to 3D effects (e.g., Rayleigh–Taylor instabilities), and provides support for a slowly varying leakage (mean opacity). For a more complex light curve (SN2008D, SN Ib), we separate the luminosity due to multiple causes and indicate the possibility of a radioactive plume. The early rise in luminosity is shown to be affected by the opacity (leakage rate) for thermal and non-thermal radiation. A general derivation of Arnett’s rule again shows that it depends upon all processes heating the plasma, not just radioactive ones, so that SNe Ia will differ from SNe Ibc if the latter have multiple heating processes.
Development of a Variable Stiffness Function for a New Multifunctional Wire Driven Joint Mechanism

A mechanical variable stiffness can adapt to external forces beyond the control cycle, such as overturning of walking robots, which can help solve problems such as actuator and joint destruction. In this research, we will clarify the structure of a two-input, one-output joint mechanism that can realize three functions: normal motion, instantaneous motion, and variable stiffness function. As part of the development of the variable stiffness function, a mathematical model is derived and simulated for the relationship between the joint angle of the output link and the disturbance torque when a disturbance torque is applied to the output link of the proposed mechanism
FEASIBILITY OF PREFABRICATED BUILDING STRUCTURES IN BHUTAN

Studies and research on the arena of prefabrication have prodigiously reported faster project delivery, improved quality and safer working conditions. More prominently, reduction in waste materials at project sites without any implications to environmental aspects has been a major breakthrough. Prefabricated building structures have been progressively recognized as a substitute to the conventional methods of construction at a rapid rate, however, there is a knowledge vacuum and inadequate data on the adoption of prefabrication in Bhutan. Hence, in the current study, the feasibility of Prefabricated Buildings in Bhutan with a case study was carried out. The study focused on the benefits, constraints and way forward of prefabrication works in Bhutan through field survey and questionnaire survey. In addition, economic, environmental assessments and insulation performance were carried on a Pre-Engineered building with prefabricated materials and subsequently compared to a conventional building. From the study, the major benefit found to be ease of construction whereas the constraints pertaining to the design and planning phase of the project were deemed to be the major constraint. In particular for prefabricated construction, the cost was found to be 24.18% higher but the duration of the project can be reduced by 25-31% and the environmental impact was found to be 20.81% less than for the conventional building. Therefore, adopting prefabricated construction will depend on the requirements of a particular project, the availability of funds and environmental standards to be followed. However, the use and acceptance of prefabrication in the construction industry can be improved by better advocacy and public awareness.