Miracle-dz/UniFAR-FTUs huggingface dataset:
T–S fuzzy‐based multi‐LAE approach for sensor linearisation

Most sensors exhibit a non-linear input–output relationship. Sensor linearity is essential for the true representation of measurand in modern instrumentation systems. Although several linearisation techniques (LTs) have been proposed in recent years, they incur common problems of scalability, reliability, flexibility, complexity and cost. Hence, an effective software lineariser is needed to overcome these difficulties. This study presents a Takagi–Sugeno (T–S) fuzzy-based sensor LT using piecewise linearisation. The non-linear static relationship splits into ‘N’ multiple linear algebraic equations, which are combined using T–S fuzzy logic to ensure a smooth transfer from one region to another. The linearity (mean square error) of 0.1663 is obtained for negative temperature coefficient thermistor in simulation over a temperature range of 307 to 373 K, and of 0.0255 is achieved for infrared sensor in real time over a distance range of 12–30 cm. The performance of the proposed LT is compared with popular curve fitting, a look-up table and soft computing approaches. The results show that the proposed LT outperforms other approaches regarding performance indices. This technique eliminates hardware complexity rendering better accuracy over the span of measurement.
A Complex Brain Learning Skeleton Comprising Enriched Pattern Neural Network System for Next Era Internet of Things

The Internet of Things (IoT) is now growing dramatically on various levels and helps to digitize various vital industries quickly. The most difficult obstacle for BCIs to overcome is the fact that not everyone has the same brain. Every new session requires the BCI to learn from the user’s brain, which is accomplished via the use of machine learning. However, this learning process is time-consuming. Calibration time refers to the amount of time it takes for the BCI to adapt to the user’s brain in order to properly categorize their thoughts and determine their meaning. The patient has had to wait an arduous and tiresome length of time for the system to be completely functioning up until now because of this calibration, which may take up to 20–30 minutes. The aim of this paper was to find a way to decrease the amount of time required for calibration to the smallest amount feasible. In the first section of this paper, a first effort is made to determine the optimum number of features required for the BCI to operate reasonably, taking into consideration all of the calibration data provided. When the results were averaged across five participants, the percentage of properly identified thoughts was just 67.15 percent. Transfer learning was used in order to improve the performance of the BCI while simultaneously decreasing the calibration time. It is feasible to decrease the amount of calibration required for the categorization of thoughts coming from a new target subject by using knowledge collected from previously recorded subjects to the greatest extent possible in transfer learning. It was determined that existing methods were superior, and a new methodology was created that required just 24 seconds of calibration data while accurately identifying 86.8% of the thoughts. In order to alleviate mental stress and anger, the system suggested fits effectively with a deep learning network. This paper proposes a brain learning framework that uses a neural network model that is complex in nature and uses IoT for data collection from various wearable devices, and the same can be used for modelling the brain functions. Aside from the fact that categorization performance is assessed, a more relevant metric is the number of letters per minute that a user transmits. In addition to evaluating classification performance, there are methods that evaluate the amount of time necessary to complete specified tasks.
The characteristic function of rough Heston models

It has been recently shown that rough volatility models, where the volatility is driven by a fractional Brownian motion with small Hurst parameter, provide very relevant dynamics in order to reproduce the behavior of both historical and implied volatilities. However, due to the non‐Markovian nature of the fractional Brownian motion, they raise new issues when it comes to derivatives pricing. Using an original link between nearly unstable Hawkes processes and fractional volatility models, we compute the characteristic function of the log‐price in rough Heston models. In the classical Heston model, the characteristic function is expressed in terms of the solution of a Riccati equation. Here, we show that rough Heston models exhibit quite a similar structure, the Riccati equation being replaced by a fractional Riccati equation.
CDMerge: Semantically Sound Merging of Class Diagrams for Software Component Integration

Abstraction, refinement and (de-)composition are fundamental techniques for engineering large software systems. In the context of Model Driven Development (MDD), these techniques are primarily applied to models. Our goal is to integrate automated composition of data models into the development process. We focus primarily on Class Diagrams (CDs) which are widely used to model object-oriented systems. In particular, we consider the variant of UML/P CDs which are equipped with a formal semantics for both the closed-world and open-world assumptions and allow for underspecified associations. A sound merge of CDs must include precisely the information of its components and preserve their semantic implications. In this paper we introduce a merge operator for CDs that considers both formal and implementation-oriented soundness requirements. The operator is able to support a divide-and-conquer approach for modeling and code-generation of large object-oriented software systems. We clarify why we deem an open-world approach necessary and outline merge conflicts and variants. Finally, we discuss integration of automated merging into the development process and provide an outlook on run-time data integration.
Taylor–Couette–Poiseuille flow with a weakly permeable inner cylinder: absolute instabilities and selection of global modes

Variations in the local stability of the flow in a Taylor–Couette cell can be imposed by adding an axial Poiseuille flow and a radial flow associated with one or both of the cylinders being permeable. At a given rotation rate of the inner cylinder, this results in adjacent regions of the flow that can be simultaneously stable, convectively unstable, and absolutely unstable, making this system fit for studying global modes of instability. To this end, building on the existing stability analysis in absolute modes developing over axially invariant base flows, we consider the case of axially varying base flows in systems for which the outer cylinder is impermeable, and the inner cylinder is a weakly permeable membrane through which the radial flow is governed by Darcy’s law. The frameworks of linear and nonlinear global modes are used to describe the instabilities and assess the results of direct numerical simulations using a dedicated pseudospectral method. Three different axially evolving set-ups are considered. In the first, fluid injection occurs along the full inner cylinder. In the second, fluid extraction occurs along the full inner cylinder. Besides its fundamental interest, this set-up is relevant to filtration devices. In the third, fluid flux through the inner cylinder evolves from extraction to injection as cross-flow reversal occurs. In agreement with the global mode analyses, the numerical simulations develop centrifugal instabilities above the predicted critical rotation rates and downstream of the predicted axial locations. The global mode analyses do not fully explain, however, that the instabilities observed in the numerical simulations take the form of axial stacks of wavepackets characterized by jumps of the temporal frequency.
Three-lead in vivo measurement method for determining the skin-electrode impedance of textile electrodes

The rise of interest in wearable sensing of bioelectrical signals conducted via smart textile systems over the past decades has resulted in many investigations on how to develop and evaluate such systems. All measurements of bioelectrical signals are done by way of electrodes. The most critical parameter for an electrode is the skin-electrode impedance. A common method for measuring skin-electrode impedance is the two-lead method, but it has limitations because it relies on assumptions of symmetries of the body impedance in different parts of the body as well as of the skin-electrode impedances. To address this, in this paper we present an easy-to-use and reliable three-lead in vivo method as a more accurate alternative. We aim to show that the in vivo three-lead method overcomes all such limitations. We aim at raising the awareness regarding the possibility to characterize textile electrodes using a correct, accurate and robust method rather than limited and sometimes inadequate and uninformative methods. The three-lead in vivo method eliminates the effect of body impedance as well as all other contact impedances during measurements. The method is direct and measures only the skin-electrode impedance. This method is suitable for characterization of skin-electrode interface of textile electrodes intended for both bioelectrical signals as well as for electrostimulation of the human body. We foresee that the utilization of the three-lead in vivo method has the potential to impact the further development of wearable sensing by enabling more accurate and reliable measurement of bioelectrical signals.
ASAS J083241+2332.4: A NEW EXTREME LOW MASS RATIO OVERCONTACT BINARY SYSTEM

We present the R- and V-band CCD photometry and Hα line studies of an overcontact binary ASAS J083241+2332.4. The light curves exhibit totality along with a trace of the O’Connell effect. The photometric solution indicates that this system falls into the category of extreme low-mass ratio overcontact binaries with a mass ratio, q ∼ 0.06. Although a trace of the O’ Connell effect is observed, constancy of the Hα line along various phases suggest that a relatively higher magnetic activity is needed for it to show a prominent fill-in effect. The study of O–C variations reveals that the period of the binary shows a secular increase at the rate of dP/dt ∼ 0.0765 s years−1, which is superimposed by a low, but significant, sinusoidal modulation with a period of ∼8.25 years. Assuming that the sinusoidal variation is due to the presence of a third body, orbital elements have been derived. There exist three other similar systems, SX Crv, V857 Her, and E53, which have extremely low mass ratios and we conclude that ASAS J083241+2332.4 resembles SX Crv in many respects. Theoretical studies indicate that at a critical mass ratio range, qcritical = 0.07–0.09, overcontact binaries should merge and form a fast rotating star, but it has been suggested that qcritical can continue to fall up to 0.05 depending on the primary's mass and structure. Moreover, the obtained fill-out factors (50%–70%) indicate that mass loss is considerable and hydrodynamical simulations advocate that mass loss from L2 is mandatory for a successful merging process. Comprehensively, the results indicate that ASAS J083241+2332.4 is at a stage of merger. The pivotal role played by the subtle nature of the derived mass ratio in forming a rapidly rotating star has been discussed.
Capacity Bounds and Spectral Constraints for Transceivers With Finite Resolution Quantizers

Low-resolution digital-to-analog and analog-to-digital converters (DACs and ADCs) have attracted considerable attention in efforts to reduce power consumption in millimeter wave (mmWave) and massive MIMO systems. This paper presents an information-theoretic analysis with capacity bounds for classes of linear transceivers with finite quantization. The transmitter modulates symbols via a unitary transform followed by a DAC and the receiver employs an ADC followed by the inverse unitary transform. If the unitary transform is set to a discrete Fourier transform (DFT) matrix, the model naturally captures filtering and spectral constraints. In particular, this model allows studying the impact of quantization on out-of-band (OOB) emission constraints. The out-of-band emission constraints are defined using a “spectrum mask” in practical wireless systems. All transmissions need to meet the OOB constraint to allow other services and technologies to operate in adjacent bands.In the limit of a large random unitary transform, it is shown that the effect of quantization can be precisely described via an additive Gaussian noise model. This model in turn leads to simple and intuitive expressions for the power spectrum of the transmitted signal and a lower bound to the capacity with quantization. Comparison with non-quantized capacity and a capacity upper bound that does not make linearity assumptions suggests that while low resolution quantization has minimal impact on the achievable rate at typical parameters in 5G systems, satisfying OOB emissions is potentially much more of a challenge.
Chronic Intermittent Hypoxia-Induced Diaphragm Muscle Weakness Is NADPH Oxidase-2 Dependent

Chronic intermittent hypoxia (CIH)-induced redox alterations underlie diaphragm muscle dysfunction. We sought to establish if NADPH oxidase 2 (NOX2)-derived reactive oxygen species (ROS) underpin CIH-induced changes in diaphragm muscle, which manifest as impaired muscle performance. Adult male mice (C57BL/6J) were assigned to one of three groups: normoxic controls (sham); chronic intermittent hypoxia-exposed (CIH, 12 cycles/hour, 8 h/day for 14 days); and CIH + apocynin (NOX2 inhibitor, 2 mM) administered in the drinking water throughout exposure to CIH. In separate studies, we examined sham and CIH-exposed NOX2-null mice (B6.129S-CybbTM1Din/J). Apocynin co-treatment or NOX2 deletion proved efficacious in entirely preventing diaphragm muscle dysfunction following exposure to CIH. Exposure to CIH had no effect on NOX2 expression. However, NOX4 mRNA expression was increased following exposure to CIH in wild-type and NOX2 null mice. There was no evidence of overt CIH-induced oxidative stress. A NOX2-dependent increase in genes related to muscle regeneration, antioxidant capacity, and autophagy and atrophy was evident following exposure to CIH. We suggest that NOX-dependent CIH-induced diaphragm muscle weakness has the potential to affect ventilatory and non-ventilatory performance of the respiratory system. Therapeutic strategies employing NOX2 blockade may function as an adjunct therapy to improve diaphragm muscle performance and reduce disease burden in diseases characterised by exposure to CIH, such as obstructive sleep apnoea.
What are the Determinants of Attitudes Towards Immigrants in Turkey? Evidence from the World Values Survey

In this study, I aim to find the impact of social values and demographic characteristics on attitudes toward immigrants in Turkey. For the empirical analysis, wave 7 data from the World Values Survey (WVS) is used. Individual-level data from 2018 shows that religion and nationalism play a key role in increasing negative attitudes toward immigrants. As individuals' social class improves, their anti-immigrant sentiments tend to decrease. However, when there is concern about potential competition for scarce jobs in the labor market, social class jumps result in discrimination against immigrants. The logit regression coefficients for political opinion, education, age and marital status do not show robust results in different models using different measures of negative attitudes. Thus, demographic characteristics do not systematically influence opinions toward immigration in Turkey. Rather, values and socioeconomic position in society have an impact on opinions toward immigrants.
A Comparative Study of the SIMPLE and Fractional Step Time Integration Methods for Transient Incompressible Flows

Time integration methods are necessary for the solution of transient flow problems. In recent years, interest in transient flow problems has increased, leading to a need for better understanding of the costs and benefits of various time integration schemes. The present work investigates two common time integration schemes, namely the Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) and the Fractional Step (FS) method. Three two-dimensional, transient, incompressible flow problems are solved using a cell centered, finite volume code. The three test cases are laminar flow in a liddriven skewed cavity, laminar flow over a square cylinder, and turbulent flow over a square cylinder. Turbulence is modeled using wall functions and the k−ε turbulence model with the modifications suggested by Kato and Launder. Solution efficiency as measured by the effort carried out by the flow equation solver and CPU time is examined. Accuracy of the results, generated using the SIMPLE and FS time integration schemes, is analyzed through a comparison of the results with existing experimental and/or numerical solutions. Both the SIMPLE and FS algorithms are shown to be capable of solving benchmark flow problems with reasonable accuracy. The two schemes differ slightly in their prediction of flow evolution over time, especially when simulating very slowly changing flows. As the time step size decreases, the SIMPLE algorithm computational cost (CPU time) per time step remains approximately constant, while the FS method experiences a reduction in cost per time step. Also, the SIMPLE algorithm is numerically stable for time steps approaching infinity, while the FS scheme suffers from numerical instability if the time step size is too large. As a result, the SIMPLE algorithm is recommended to be used for transient simulations with large time steps or steady state problems while the FS scheme is better suited for small time step solutions, although both time-stepping schemes are found to be most efficient when their time steps are at their maximum stable value.
Simulation of SAXS patterns of hexa-n-alkoxy-2,3,6,7,10,11-triphenylene mesophase

ABSTRACT Small-angle X-ray scattering (SAXS) experiments and molecular dynamic modelling of the mesomorphic organisation of hexa-n-pentoxy-2,3,6,7,10,11-triphenylene are reported. Simulated SAXS patterns extracted from molecular dynamic simulations account for the fact that despite a perfect organisation of the columns in a 2D hexagonal array, in most case, SAXS patterns show only the fundamental diffraction peak with a limited number of higher order reflections. GRAPHICAL ABSTRACT
Hybrid Indoor Positioning Method of BLE and Monocular VINS-Based Smartphone

The visual simultaneous localization and mapping (VSLAM) method has a significant advantage in indoor positioning methods. Visual–inertial navigation system (VINS)-Mono is one of the state-of-the-art works widely used in many augmented reality (AR)/virtual reality (VR) applications on a smartphone. However, in indoor positioning based on a smartphone, the low accuracy of the inertial measurement unit (IMU) leads to a disappointing estimate of the initialization scale of VINS-Mono, which makes the assignable error in subsequent positioning. In addition, the time consumption of the loop detection module in VINS-Mono is high, which can be replaced if there are other global measurements based on smartphone sensors, for example, Bluetooth low energy (BLE) broadcast frame. Indoor positioning methods based on BLE have been implemented in Wechat mini program because of the lightweight performance in memory and complexity. However, almost all related methods process BLE information in a synchronous way for triangulation or fingerprint positioning. Such processing does not consider the ranging error caused by the asynchronous reception of the BLE broadcast frame, which leads to nonnegligible positioning errors. Therefore, we propose a lightweight VINS-Mono-BLE framework using only the smartphone’s monocular vision, low-precision IMU, and BLE. We design the BLE back-propagation algorithm to eliminate the influence of asynchronous reception and then fuse it with the vision and IMU measurements. Furthermore, we use BLE as a global observation instead of the loop detection module to improve the accuracy of VINS-Mono and reduce the time cost of the algorithm. Meanwhile, we have conducted experiments in the laboratory and commercial scenarios, respectively. The experimental results show that our proposed BLE back-propagation algorithm can effectively reduce the ranging error and improve the positioning accuracy of the fusion algorithm.
Method for determining pump flow without the use of traditional sensors

The method of determining the flow rate of the pump without using a conventional sensor, comprising the steps of: means for creating a calibration curve in the power valve is closed under certain conditions of rotational speed; a ratio of the normalized power curves based on the power of the pump calculation coefficient; and a flow rate for the solution of the current operating point of the power polynomial equation. Can create a calibration curve of power from the minimum speed to maximum speed is incremented by the pump operation in a case where the relief valve closed when the rotational speed of the pump. This data is used to correct the published performance and power off the power of the best efficiency point at rated speed, to determine the power ratio of the pump. It is also used to accurately determine the power valve is closed when the current operating speed. Power polynomial equations include, for example, may use a third-order polynomial equation from a power normalization coefficient of the flow curve is formed, and the speed can be corrected, and the specific gravity of the hydraulic efficiency of power polynomial equation.
Asymptotic normality of estimators for parameters of a multivariate skew-normal distribution

ABSTRACT In this paper, asymptotic normality is established for the parameters of the multivariate skew-normal distribution under two parametrizations. Also, an analytic expression and an asymptotic normal law are derived for the skewness vector of the skew-normal distribution. The estimates are derived using the method of moments. Convergence to the asymptotic distributions is examined both computationally and in a simulation experiment.
Imaging static Fourier transform spectrometry: impact of trajectory perturbations on the hyperspectral images

Imaging static Fourier transform spectrometry (isFTS) may be used for pushbroom air- or spaceborne hyperspectral remote sensing. In isFTS, the spectral information is multiplexed over several instantaneous images, and numerical reconstruction is needed to recover the full spectrum for each pixel. The registration of instantaneous images is a crucial step. Unsufficient precision leads to artefacts on the images and degradation of the estimated spectra. We developed a simulation program of the entire processing chain of an isFTS system that can reproduce the degradations of actual isFTS images. Using this program we studied spatial and spectral effects of temporally correlated and uncorrelated trajectory perturbations. We also performed a theoretical study to quantify these degradations. We demonstrated that the most significant degradations occur in the regions of high radiance gradient.