Miracle-dz/UniFAR-FTUs huggingface dataset:
Opportunistic localization using LEO signals

Accurate positioning, navigation, and timing (PNT) is taking a centre stage due to enhanced requirements in safety critical systems, emergence of autonomous systems as well as the use of sensor networks in disaster management. While Global Navigation Satellite System (GNSS) has been a prime source for enabling PNT, the aforementioned use cases would need a complementary solution in case GNSS signals are unavailable, unreliable or unusable. This work, builds on the existing literature, and considers the use of signals from low Earth orbit (LEO) satellites due to the higher spatial and temporal resolution offered by the evolving and emerging megaconstellations. It builds on the existing LEO PNT works and considers the feasibility of LEO PNT from a system perspective and parameter estimation aspects. It then presents the tracking algorithm fusing information from multiple satellites while incorporating errors in their locations into the state model. Performance evaluation for representative scenario is undertaken.
Decoding a Neurofeedback-Modulated Performance State in Presence of a Time-Varying Process Noise Variance

Everyday life actuators such as music can be used as neurofeedback to improve quality of life and performance. To track one's performance, we develop a performance decoder that captures the time-varying nature of the process noise. We first design a performance state-space model within an autoregressive conditional heteroskedasticity (ARCH) framework to enable adaptive performance state estimation. Then, we design an expectation-maximization algorithm to decode a hidden performance state and estimate the model parameters. Particularly, by considering the sequence of responses and the corresponding reaction times as the observation vector, we employ particle-filtering to track the hidden performance state. We investigate the decoder's performance on experimental data. The estimated performance state is aligned with different task difficulty levels. During the experiment, music was used as neurofeedback to regulate the arousal. Our results indicate music can be utilized to regulate arousal and modulate performance in smart environments. Adaptive performance estimation in varying environments in presence of neurofeedback is a key step for improving performance in real-world settings. Envisioned cyber-physical systems applications include improving productivity in smart workplaces and enhancing learning in online educational systems.
Fairness-aware Graph Attention Networks

Graphs can facilitate modeling of various complex systems and the analyses of the underlying relations within them, such as gene networks and power grids. Hence, learning over graphs has attracted increasing attention recently. Specifically, graph neural networks (GNNs) have been demonstrated to achieve state-of-the-art for various learning tasks over graphs. However, it is also shown that the use of graph structures in GNNs results in the amplification of algorithmic bias. Hence, fairness is an essential problem in GNNs. Motivated by this, this study proposes a novel fairness-aware graph attention network (GAT) design. Conventional GAT is one of the most popular and widely utilized GNN structure. Specifically, the present study first carries out a theoretical analysis in order to demonstrate the sources of algorithmic bias in GAT-based learning. Then, a novel fairness-aware GAT design is developed based the theoretical findings. Experimental results on real-world social networks show that the proposed fairness-aware GAT design can improve group fairness measures together with comparable classification accuracy to the conventional GAT for node classification.
A Brief Overview of the Respiratory Sound Based Detection of Chronic Obstructive Pulmonary Disease(COPD)

Lung sound reflects the lung morphology. Changes in behavior of respiratory sound could be the direct indicator of changes in the lung morphology due to pulmonary diseases. Computerized lung sound analysis is one of the cost effective as well as the non-invasive tool to analyze respiratory diseases. Chronic Obstructive Pulmonary Disease (COPD) is one of the chronic lung diseases whose correct diagnosis is very difficult as well as whose health cost is very high. Researchers have proposed several interesting methodologies in diagnosing such disease based on LS. However, it is essential to identify the available lung sound (LS) based diagnostic system which could be able to effectively detect COPD in a better way. This study is all about to identify the exact LS based diagnostic procedure which could be a considerable and effective one for diagnosing COPD. In comparison to all of the existing LS based methodologies, one study produced the highest classification accuracy of 99.7%. In that the study the LS recordings were effectively denoised using EMD and DWT, followed by feature extraction in various domains. Next to this, feature selection was conducted using the back elimination method to identify the best features. Those selected features were then given input to quadratic discriminant classifier to diagnose COPD. This LS based diagnostic procedure outperformed with classification accuracy of 99.7% It is concluded that this study has successfully identified the most effective automated LS based procedure to correctly detect COPD. This methodology can even be recommended clinically as to support physicians for diagnosing COPD. However, existing studies have not included the LS data of COPD patients having other comorbidities. The future endeavor of this study is to implement such a LS based diagnostic system which could detect COPD even in COPD patients with other comorbidities.
A Compound Quantitative Structure-activity Relationship Model was Introduced with a Meta-heuristic Algorithm

Breast cancer, for which no effective cure has been found to date, is known as one of the more deadly cancers. Currently, in drug development, the method of building predictive models of compound activity is commonly used for convenience and efficiency.The 20 most correlated features were first obtained by combining Pearson and Spearman correlation coefficients. These 20 characteristics were then used to model the predictions and cross-validate the models to ensure the reasonableness of the model predictions. Finally, the regression models were compared with MAPE indicators for the IC50 and pIC50 predictions, and the Bagging regression model was identified as the optimal model.
Assessing Inter-Annotator Agreement for Medical Image Segmentation

Artificial Intelligence (AI)-based medical computer vision algorithm training and evaluations depend on annotations and labeling. However, variability between expert annotators introduces noise in training data that can adversely impact the performance of AI algorithms. This study aims to assess, illustrate and interpret the inter-annotator agreement among multiple expert annotators when segmenting the same lesion(s)/abnormalities on medical images. We propose the use of three metrics for the qualitative and quantitative assessment of inter-annotator agreement: 1) use of a common agreement heatmap and a ranking agreement heatmap; 2) use of the extended Cohen’s kappa and Fleiss’ kappa coefficients for a quantitative evaluation and interpretation of inter-annotator reliability; and 3) use of the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm, as a parallel step, to generate ground truth for training AI models and compute Intersection over Union (IoU), sensitivity, and specificity to assess the inter-annotator reliability and variability. Experiments are performed on two datasets, namely cervical colposcopy images from 30 patients and chest X-ray images from 336 tuberculosis (TB) patients, to demonstrate the consistency of inter-annotator reliability assessment and the importance of combining different metrics to avoid bias assessment.
The development trends and research fronts in orbital angular momentum technology: A bibliometric analysis

Orbital angular momentum (OAM) technology, refers to Laguerre-Gaussian (LG) beams, twisted beams, vector/vortex beams, acoustic vortex beams and fractional vortex beams. It is an emerging and promising technology to improve the communication capacity, spectral efficiency, and anti-jamming capability due to its helical phase fronts and infinite orthogonal states. Although the OAM research began in the 1990s, the developing trends, current status, issues and characteristics through a systematic observation have not yet been performed. This paper presents a knowledge-based evolution of OAM research published in the Web of Science (WoS) from 2011 to 2021 using bibliometric analysis in Citepspace. The results demonstrate that the bandwidth, efficiency, gain, divergence, phase quantization, bulky and complex feeding structures, misalignment, distortion, interferences atmospheric turbulence and diffraction were the key issues found in the OAM technology. The main research hotspots and categories, influential authors, leading journals, best institutions of OAM show a strong bias in favor of their functions and technology developments. The research on OAM was mainly performed by the counties that have developed the 5G and now moving towards 6G communications like China, USA and South Korea. This study would serve as an inclusive guide on the future research trends and status especially for the OAM researchers.
Analysis Influencing Factors of Consumer Satisfaction of Men's Sweaters Based on Online Reviews

In order to explore the main factors influencing the satisfaction of online shopping consumers of men's woolen sweaters. The binary Logistic model was used to conduct data mining and analysis of online comments on JD. The results showed that the factors influencing customer satisfaction include the intrinsic quality of woolen sweaters, marketing strategy, logistics and customer service, a total of 12 factors. Among them, the product's perceived experience, fabric, technology, style, color, brand, price, activity, delivery speed and pre-sale service have a significant positive impact on satisfaction. Consumers are more satisfied with the perceived experience and style, but less satisfied with the brand and after-sale service.
Affine-Projection q-Rényi Algorithm for Channel Estimation Under Different Vehicle Velocities and Impulsive Interference

An adaptive estimation algorithm based on <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula>-Rényi kernel function and affine project scheme is proposed, analyzed and simulated for channel estimation in the impulsive noise environment, which is named as affine-projection <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula>-Rényi (APQR) algorithm. APQR algorithm is implemented via minimizing the <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula>-Rényi kernel function with past errors to achieve robustness for impulsive noise and improve convergence speed when the input signal is colored. The step-size boundary and steady-state analysis are presented. Simulation results verify the correctness of theoretical analysis and the superiority of the proposed algorithm under the conditions of colored input and impulsive noise.
Pre-connect Handover Management for 5G Networks

Handover is an essential and significant component of mobility management in cellular networks. Handover management is more challenging in Fifth Generation (5G) networks because of ultra-reliable low latency communications (URLLC) requirements. This paper proposes a handover enhancement mechanism, namely pre-connect handover (PHO), for user equipment (UE) to support seamless and reliable handover management for 5G networks. PHO was designed for UEs to start the pre-connection process earlier than the 3GPP baseline handover to meet the strict low latency requirements, while satisfying the quality of service (QoS) demands. Specifically, the radio resources including a capacity-adjustable buffer are pre-allocated at the candidate target cell(s) in advance. The feasibility of PHO has been investigated by considering various scenarios and validated extensively via Network Simulator 3 (NS-3). The empirical results demonstrated that the proposed PHO can successfully achieve pre-connect handovers and support QoS without packet loss.
New transformer model including joint air gaps and lamination anisotropy

A new three phase transformer model is presented in this paper, taking into account air gaps, saturation, core losses, and lamination anisotropy. The flux distribution in a straight overlap joint has been investigated using a lumped circuit model. It is shown that the actual air gap varies largely between an upper and a lower limit as a function of core saturation. Therefore, mitered joints have been modeled using a new concept of an equivalent variable air gap. This consists of defining the length of an equivalent air gap as a function of the instantaneous value of the flux in the laminations. A new approach to the core loss modeling is highlighted. It is characterized by a nonlinear conductance placed in parallel with the saturated magnetizing inductance. Furthermore, transformer yokes and limbs have been divided into longitudinal elements according to the rolling direction to take into account the lamination anisotropy effects. The transient and steady state behaviors of the transformer model have been tested. A good agreement is obtained between computed and measured results.
Design and implementation of secure and reliable information interaction architecture for digital twins

In order to improve the comprehensive defense capability of data security in digital twins (DTs), an information security interaction architecture is proposed in this paper to solve the inadequacy of data protection and transmission mechanism at present. Firstly, based on the advanced encryption standard (AES) encryption, we use the keystore to expand the traditional key, and use the digital pointer to avoid the key transmission in a wireless channel. Secondly, the identity authentication technology is adopted to ensure the data integrity, and an automatic retransmission mechanism is added for the endogenous properties of the wireless channel. Finally, the software defined radio (SDR) platform composed of universal software radio peripheral (USRP) and GNU radio is used to simulate the data interaction between the physical entity and the virtual entity. The numerical results show that the DTs architecture can guarantee the encrypted data transmitted completely and decrypted accurately with high efficiency and reliability, thus providing a basis for intelligent and secure information interaction for DTs in the future.
Conformal transformation of photonic crystal structures

In this paper we present an algorithm that maps a reference diffracting structure along an arbitrarily curved boundary. The proposed algorithm produces deformed photonic crystal lattice patches with minimal angular distortion of its unit cells, thus realizing a discrete quasi-conformal transformation of the dielectric map. We then investigate the field confinement characteristics of some curved waveguide devices realized by such structures.
The Factors affect Customer interest in using Mobile Banking in Indonesia

Banking has taken the lead in providing technology-based delivery channels such as ATMs, internet banking, and one of them is mobile banking. This research study uses a technology adoption model. According to the findings, perceived usefulness and perceived ease of use, social influence, and trust tendencies are the underlying factors that influence a person's behavioral intention to use mobile banking services. Mobile banking is attractive because it is a convenient way to perform remote banking transactions; however, the application of mobile banking is currently less secure. Perceived usefulness, perceived ease of use, social influence, trustworthiness tendency, convenience, and security are variables in this study. The methodology of this research is questionnaire, made using Google forms and disseminated from April to June. The survey was conducted on 400 respondents who of course use mobile banking in several cities in Indonesia. The collected data is processed and calculated using SmartPLS application with PLS and Bootstrapping calculations. After conducting convergent and discriminant tests and path coefficients, it is known that from a total of 6 hypothesis there are 2 hypothesis that are rejected, and 4 hypothesis are accepted. From this study, there are also limitations which include samples and variables.
A problem-independent limiter for high-order Runge—Kutta discontinuous Galerkin methods

Abstract This paper is devoted to the use of discontinuous Galerkin methods to solve hyperbolic conservation laws. The emphasis is laid on the elaboration of slope limiters to enforce nonlinear stability for shock-capturing. The objectives are to derive problem-independent methods that maintain high-order of accuracy in regions where the solution is smooth, and in the neighborhood of shock waves. The aim is also to define a way of taking into account high-order space discretization in limiting process, to make use of all the expansion terms of the approximate solution. A new slope limiter is first presented for one-dimensional problems and any order of approximation. Next, it is extended to bidimensional problems, for unstructured triangular meshes. The new method is totally free of problem-dependence. Numerical experiments show its capacity to preserve the accuracy of discontinuous Galerkin method in smooth regions, and to capture strong shocks.
An Alternative to the Bessel K form Distribution

Abstract We study an alternative to the Bessel K form (BKF) distribution that results when instead of gamma, the scale random variable in the Gaussian scale mixture (GSM) parameterization follows a generalized exponential distribution. The new distribution is expressed as a sum of simpler Laplace densities. Some properties of this distribution are provided. We investigate parameter estimation under the additive Gaussian noise model using simple cascades of estimators. Exact and approximate Bayesian estimators are derived for the generalized K form (GKF) in the spherically contoured case that make use of the generalized incomplete Gamma function.
A-weighted equivalent sound level as a predictor of the annoyance caused by road traffic consisting of various proportions of light and heavy vehicles

A laboratory study was conducted to examine the relationship between noise annoyance and the proportion of heavy vehicles in a mixture of trucks and passenger cars. Twenty normal-hearing subjects were asked to judge the annoyance caused by the sounds from a continuous stream of vehicles, assuming they were exposed to it at home on a regular basis. The number of passby events as well as the A- weighted equivalent sound level were kept constant. Results showed that in such conditions, the annoyance is virtually independent of the proportion of heavy vehicles. (E)
Automated Aerotriangulation Using Multiple Image Multipoint Matching

This paper deals with automating the aerotriangulation procedure using digital image processing methods and images available exclusively in digital format. A conceptual system has been developed and implemented which allows for the automatic determination of exterior orientation parameters and positions of selected points in object space using a minimal number of assumptions. In direct analogy to the preparation phase of the conventional approach, a photomosaic is automatically generated to describe the interrelationship of all photos within the available block. This photomosaic is subsequently used for the automatic extraction of approximate conjugate image coordinates. A multiple image multipoint matching strategy has been developed to identify and precisely match conjugate points in the triple, quadruple, or multiple overlapping areas of the block. By taking into account the geometric relationship between conjugate points as expressed by their corresponding image-forming rays, and using image coordinates rather than the widely used local template coordinates, matching and block adjustment can be combined in a unique way. Thus, the mensuration and adjustment phases of classical aerotriangulation are substituted by a single digital process which allows automation of the complete procedure.
Intermediate-band photometry of late-type stars VIII. Nonvariable stars in the halo population near the sun.

From a discussion of a complete sample of high-velocity stars, the following criteria are suggested for identification of halo population objects: (1) all stars having less than about 25% of the solar metal abundance; (2) if only the space motion is available, those giving e>0.42; (3) for e<0.42, vertical-barWvertical-bar larger than about 60 km s/sup -1/ (or Z greater than about 1 kpc). The available data for the halo stars indicate that the whole range of halo metal abundance is present in the region of 10 to 20 kpc from the galactic center, but this range narrows beyond 20 kpc, and the upper limit, beyond 30 kpc, is near 3% of the solar abundance.
Transient performance degradation of the LMS, RLS, sign, signed regressor, and sign-sign algorithms with data correlation

The transient performance degradation, for correlated input data, is studied for various adaptive algorithms. The algorithms are least mean square (LMS), recursive least squares (RLS), sign (SA), signed regressor (SRA), and sign-sign (SSA). Analysis is performed for adaptive plant identification with stationary Gaussian inputs. A closed-form expression for the mean convergence time is derived for each algorithm. The degradation measure used is the ratio of convergence time for correlated data to the convergence time for white data. The LMS and SRA degradations are the same. The SA and SSA degradations are also the same. The smallest degradation occurs for RLS, the largest for LMS and SRA. The SRA, RLS, and LMS degradations are independent of plant-noise variance. The SA and SSA degradations increase with increased noise variance. The LMS and SRA degradations do not depend upon the weight initialization, RLS (SA and SSA) depends weakly (significantly) upon the weight initialization. The analytical results are supported by simulations.
Is the seismic moment–frequency relation universal?

SUMMARY We evaluate the seismic moment‐frequency relation for the Harvard catalogue in the period 1977‐1994. This catalogue is composed of about 12 000 earthquakes. After selection of events in terms of depth and energy, we retain about 8000 data points. We estimate two parameters of the seismic moment distribution: the power exponent b and the cut-oV value M m . The method used is a least-squares linear fit on a log‐log scale performed over a range selected on the basis of the standard deviation from the histogram. The analysis is carried out for diVerent subdivisions of the Earth in square grids of diVerent sizes. Neither parameter exhibits a dependence on cell size, suggesting the universality of their values and the interpretation of the existence of a cut-oV as a finite size eVect linked to a finite catalogue length. The variations of the parameters are investigated as a function of time (duration of the catalogue) and versus the number of events used for building up the distribution. Again, b and M m do not depend on time, but M m depends on the number of events, reaching a stable value for N#1000. The only significant change in the parameters is observed for diVerent values of M 0upper in the catalogue, revealing the existence of universality classes.