Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Utility of Vague Concept for Uncertainty and Hesitation Management

In the realistic situation, there are many areas which contain imprecisely specified data. This imprecise data indicates the presence of vagueness, incompleteness and uncertainty which causes the problem during important decision-making task. The present paper focuses on the problem of mining important inference from supermarket basket data (in the presence of vagueness). The paper specifically studies the usefulness of vague set theory for the exploration of hesitation information and vague association rules. The hesitation information of an item plays a vital role in making selling strategies for the exhilaration of business. For this purpose, the vague set concept can be used as an important tool which can assist in the identification of hesitated item. The vague set theory with its two membership function provides more intuitive way to interact with the vague situation that causes the hesitation for any item. The effectiveness of the hesitated pattern and rule provide advanced decision-making capabilities that transform ‘almost sold’ items to ‘sold items’.
Multi-scan smoothing for tracking manoeuvering target trajectory in heavy cluttered environment

An automatic target tracking algorithm must be capable of dealing with an unknown number of targets and their trajectory behaviour inside the surveillance region. However, due to target motion uncertainties, heavily populated clutter measurements and low detection probabilities of targets, the smoothing algorithms often fail to detect the true number of target trajectories. In this study, the authors discussed some deficiencies and insignificances of existing smoothing algorithms and proposed a new smoothing data association based algorithm called fixed-interval integrated track splitting smoothing (ITS-S). The proposed algorithm employ smoothing data association algorithm and compared with existing smoothing algorithms outperform in terms of target trajectory accuracy and false-track discrimination (FTD). However, existing algorithms fail to generate smoothed target trajectory and provides insignificant FTD performance in such difficult environments as illustrated in this simulation study. The ITS-S shows improved smoothing performance compared with that of existing algorithms for a manoeuvering target tracking in a heavily populated cluttered environment and low detection probabilities.
Conformally natural extensions of continuous circle maps

Conformally natural and continuous extensions were originally introduced by Douady and Earle for circle homeomorphisms, and later by Abikoff, Earle and Mitra for continuous degree ±1 monotone circle maps. The first main result of this thesis shows that conformally natural and continuous extensions exist for all continuous circle maps. The second main result shows that if f is a continuous circle map and is M-quasisymmetric on some arc on the unit circle S1, then such an extension of f is locally K-quasiconformal on a neighborhood of the arc in the open unit disk D, where the neighborhood and K depend only on M.
Plasma plume expansion dynamics in nanosecond Nd:YAG laserosteotome

In minimal invasive laser osteotomy precise information about the ablation process can be obtained with LIBS in order to avoid carbonization, or cutting of wrong types of tissue. Therefore, the collecting fiber for LIBS needs to be optimally placed in narrow cavities in the endoscope. To determine this optimal placement, the plasma plume expansion dynamics in ablation of bone tissue by the second harmonic of a nanosecond Nd:YAG laser at 532 nm has been studied. The laserinduced plasma plume was monitored in different time delays, from one nanosecond up to one hundred microseconds. Measurements were performed using high-speed gated illumination imaging. The expansion features were studied using illumination of the overall visible emission by using a gated intensified charged coupled device (ICCD). The camera was capable of having a minimum gate width (Optical FWHM) of 3 ns and the timing resolution (minimum temporal shift of the gate) of 10 ps. The imaging data were used to generate position–time data of the luminous plasma-front. Moreover, the velocity of the plasma plume expansion was studied based on the time-resolved intensity data. By knowing the plasma plume profile over time, the optimum position (axial distance from the laser spot) of the collecting fiber and optimal time delay (to have the best signal to noise ratio) in spatial-resolved and time-resolved laser-induced breakdown spectroscopy (LIBS) can be determined. Additionally, the function of plasma plume expansion could be used to study the shock wave of the plasma plume.
Delft University of Technology Experimental assessment of the influence of welding process parameters on Lamb wave transmission across ultrasonically welded thermoplastic composite joints

One of the advantages of thermoplastic composites relative to their thermoset counterparts is the possibility of assembling components through welding. Ultrasonic welding in particular is very promising for industrialization. However, uncertainty in the fatigue and fracture behaviour of composites is still an obstacle to the full utilisation of these materials. Health monitoring is then of vital importance, and Lamb wave techniques have been widely recognised as some of the most promising approaches for that end. This paper presents the first experimental study about the influence of welding travel on the transmission of Lamb waves across ultrasonically welded thermoplastic composite joints in single-lap configuration. The main aim of this research is to start to understand how guided waves interact with the internal structure of ultrasonic welds, so that benign, manufacturing-related structural features can be distinguished from damaging ones in signal interpretation. The power transmission coefficient and the correlation coefficient proved to be suitable for analysing the wave propagation phenomena, allowing quantitative identification of small variations of weld-line thickness and intermolecular diffusion at the weld interface. The conclusions are used to develop a tentative damage detection criterion which can later on assist the design of a Lamb wave based structural health monitoring system for thermoplastic composite structures. The Lamb wave test results are backed up by phased-array inspections, which also provide some extra insight on the internal structure of ultrasonic welds.
Target Tracking based on Improved Unscented Particle Filter with Markov Chain Monte Carlo

ABSTRACT In this paper, a target-tracking algorithm based on improved unscented particle filter with the Markov chain Monte Carlo (MCMC) is proposed. In the proposed method, the improved unscented Kalman filter (UKF) is used to generate the proposal distribution, and particle swarm optimization (PSO) integrates into the UKF proposal. Moreover, the sample impoverishment created by resampling step is restrained with MCMC move step after the resampling. Experiments are presented to evaluate the performance of the proposed algorithm. The results show that the proposed algorithm has more significant advantages in tracking accuracy than other classical algorithms.
New Patterns of the Two-Dimensional Rogue Waves: (2+1)-Dimensional Maccari System

The ocean rogue wave is one kind of puzzled destructive phenomenon that has not been understood thoroughly so far. The two-dimensional nature of this wave has inspired the vast endeavors on the recognizing new patterns of the rogue waves based on the dynamical equations with two-spatial variables and one-temporal variable, which is a very crucial step to prevent this disaster event at the earliest stage. Along this issue, we present twelve new patterns of the two-dimensional rogue waves, which are reduced from a rational and explicit formula of the solutions for a (2+1)-dimensional Maccari system. The extreme points (lines) of the first-order lumps (rogue waves) are discussed according to their analytical formulas. For the lower-order rogue waves, we show clearly in formula that parameter b 2 plays a significant role to control these patterns.
Composite Stackelberg Strategy for Singularly Perturbed Bilinear Quadratic Systems

Abstract Based on singularly perturbed bilinear quadratic problems, this paper proposes to decompose the full-order system into two subsystems of a slow-time and fast-time scale. Utilizing the fixed point iterative algorithm to solve cross-coupled algebraic Riccati equations, equilibrium strategies of the two subsystems can be obtained, and further the composite strategy of the original full-order system. It was proved that such a composite strategy formed an o(ε) (near) Stackelberg equilibrium, and a numerical result of the algorithm was presented in the end.
Digital Hardware Architectures for Exact and Approximate DCT Computation Using Number Theoretic Techniques

The discrete cosine transform (DCT) is a key tool in many image and video coding applications. Therefore significant effort is been made to realize DCT computation utilizing minimum resources in terms of hardware, at acceptable accuracy. This thesis explores the use of number theoretic techniques such as algebraic integer (AI) encoding and expansion factor methods for exact and approximate DCT computation. Novel digital hardware architectures that utilize these techniques to obtain, a) improvements in accuracy b) reductions in area and power consumption, are proposed. Review of the utilized number theoretic techniques, mathematical derivations of the proposed architectures and digital hardware implementations are provided. All designs are implemented and tested on-chip using field programmable gate array (FPGA) technology and also simulated up to synthesis level for application specific integrated circuits (ASICs). Obtained accuracy and hardware metrics are presented and compared with the current state-of-the-art. Performance of AI based DCT computation algorithms in next generation video codecs are also analysed by integrating the proposed algorithms into high efficiency video coding standard (HEVC). The proposed digital architectures have potential applications in multimedia, automatic surveillance, geospatial remote sensing, and automotive industry. iii
Inducing Suprasegmental Structure without Constituency: a Case Study on Southern French

Eychenne, Julien. 2013. Inducing Suprasegmental Structure without Constituency: a Case Study on Southern French. The Journal of Studies in Language 29.1, 97-128. This paper provides a connectionist analysis of the prosodic structure of a non-standard variety of French, using the framework of Dynamic Computational Networks. I develop a corpus-based analysis of schwa in this variety and propose that its behaviour stems from its inability to project from the syllabic to the metrical level. The model shows that a significant portion of the lexical prosodic structure of southern French can be learned from data without needing prosodic constituency. (Hankuk University of Foreign Studies)
Heat and mass transfer characteristics of MHD three-dimensional flow over a stretching sheet filled with water-based alumina nanofluid

Purpose To know the influence of velocity slip, nanoparticle volume fraction, chemical reaction and non-linear thermal radiation on MHD three-dimensional heat and mass transfer boundary layer flow over a stretching sheet filled with water – based alumina nanofluid is analyzed in this paper. To get more meaningful results we have taken nonlinear thermal radiation in the heat transfer process Design/methodology/approach The suitable similarity variables are introduced to convert governing partial differential equations into the set of ordinary differential equations and are solved numerically using a versatile, extensively validated finite element method with Galerkin’s weighted residual simulation. The velocity, temperature, concentration profiles of nanoparticles as well as skin friction coefficient, Nusselt number and Sherwood number for different non-dimensional parameters such as volume fraction parameter, magnetic parameter, Prandtl number, radiation parameter, velocity slip parameter are examined and.
Galaxy cluster cosmology from X-ray surveys of the hot and energetic Universe

Abstract We discuss recent advances and prospects in our understanding of the formation of structures on cosmic scales based on surveys of galaxy clusters in the X-ray bands. We highlight the interaction between observations and numerical simulations of the X-ray sky. We show how future surveys will unveil the nature of the dark energy and study its evolution with time.
On the behaviour of impinging zero-net-mass-flux jets

This paper reports on an experimental study of the influence of the Strouhal number (0.011, 0.022 and 0.044) and orifice-to-plate distances (2, 4 and 6 orifice diameters) on the flow field of an impinging zero-net-mass-flux jet at a Reynolds number equal to 35 000. These jets are generated by a reciprocating piston that oscillates in a cavity behind a circular orifice. Instantaneous two-dimensional in-plane velocity fields are measured in a plane containing the orifice axis using multigrid/multipass cross-correlation digital particle image velocimetry. These measurements have been used to investigate the mean flow quantities and turbulent statistics of the impinging zero-net-mass-flux jets. In addition, the vortex ring behaviour is analysed via its trajectory and azimuthal vorticity as well as the saddle point excursion, the flow rate and entrainment. The behaviour of all these quantities depends on the Strouhal number and the orifice-to-plate distance because the former governs the presence and the relative importance of the vortex ring and the trailing jet on the flow field and the latter delimits the downstream evolution of these structures.
Control of Topological Magnetic Textures by Magnetic and Electric Fields in Magnetoelectric Helimagnet Cu₂OSeO₃

Magnetic skyrmions, topologically non-trivial chiral whirl-like spin configurations, have been under massive investigations in both fundamental and application aspects. In some special compounds, these quasi-particles can formtriangular skrymion lattice (SkL) exhibiting abundant unique properties. This thesis presents my comprehensive studies on the SkL in the magnetoelectric (ME) coupling helimagnet Cu2OSeO3. Starting from measurements on single crystal bulk Cu2OSeO3 samples, including dc magnetization, magnetoelectric susceptibility and neutron scattering, so as to get the general understanding of this system, the main work of this thesis focused on the investigation of quasi-two dimensional thin slab samples by the state-of-the-art Lorentz electron transmission electron microscopy (LTEM). Variousmagnetic textures including the spin helices and skyrmions were observed and analyzed. What separates the work presented here from literatures is the special emphasis on the dynamics of the SkL under various excitations in real space and real time, such as thermal fluctuation, magnetic field and electric field. Specifically, the magnetic field induced melting of the SkL in Cu2OSeO3 was, for the first time, observed and analyzed quantitatively. Two-step melting process was observed and demonstrated to follow the Kosterlitz-Thouless-Halperin-Nelson-Young (KTHNY) theory. The application of electric field can not only rotate the SkL, but also create skyrmions fromthe helical phase. My studies, especially those focused on the emergent properties induced by external fields, are intended to provide deeper insight into the fundamental knowledge of the SkL in Cu2OSeO3 and to promote the the development of skyrmion based spintronic applications.
On Aspects of Holographic Thermal QCD in the MQGP Limit

In the context of [1]’s string theoretic dual of thermal QCD-like theories at finite gauge/string coupling (as part of the ‘MQGP’ limit of [2]), we obtain the QCD deconfinement temperature compatible with lattice results for the right number of light flavors Nf = 3, number of colors N ∼ O(10) and the correct mass scale of the light (first generation) quarks. The type IIB background of [1] is also shown to be thermodynamically stable. Further, we show that the temperature dependence of DC electrical conductivity mimicks a one-dimensional Luttinger liquid. These results arise due to the non-Kahlerity and non-conformality of the type IIB background. On the geometrical side we quantify the former (non-Kahlerity) by evaluating the SU(3)/G2-structure torsion classes of the local type IIA mirror/M-theory uplift. Analogous to what was shown for the type IIB background in [3], we first show that the type IIA delocalized SYZ mirror (after fine tuning) can also be approximately supersymmetric. We then work out the G2-structure torsion classes of the local M-theory uplift of the mirror type IIA metric in the MQGP limit G2 structure approaches G2 holonomy. e-mail: aalokfph@iitr.ac. in e-mail: krusldph@iitr.ac. in
Extreme Multi-Label Skill Extraction Training using Large Language Models

Online job ads serve as a valuable source of information for skill requirements, playing a crucial role in labor market analysis and e-recruitment processes. Since such ads are typically formatted in free text, natural language processing (NLP) technologies are required to automatically process them. We specifically focus on the task of detecting skills (mentioned literally, or implicitly described) and linking them to a large skill ontology, making it a challenging case of extreme multi-label classification (XMLC). Given that there is no sizable labeled (training) dataset are available for this specific XMLC task, we propose techniques to leverage general Large Language Models (LLMs). We describe a cost-effective approach to generate an accurate, fully synthetic labeled dataset for skill extraction, and present a contrastive learning strategy that proves effective in the task. Our results across three skill extraction benchmarks show a consistent increase of between 15 to 25 percentage points in \textit{R-Precision@5} compared to previously published results that relied solely on distant supervision through literal matches.
$\Lambda_{\rm s}$CDM model: A promising scenario for alleviation of cosmological tensions

We present a comprehensive analysis of the $\Lambda_{\rm s}$CDM model, which explores the recent conjecture suggesting a rapid transition of the Universe from anti-de Sitter vacua to de Sitter vacua (viz., the cosmological constant switches sign from negative to positive) at redshift ${z_\dagger\sim 2}$, inspired by the graduated dark energy (gDE) model. Our analysis shows that, predicting $z_\dagger\approx1.7$, $\Lambda_{\rm s}$CDM simultaneously addresses the major cosmological tensions of the standard $\Lambda$CDM model, viz., the Hubble constant $H_0$, the Type Ia Supernovae absolute magnitude $M_{\rm B}$, and the growth parameter $S_8$ tensions, along with other less significant tensions such as the BAO Lyman-$\alpha$ discrepancy.
Nonlinear Meta-Learning Can Guarantee Faster Rates

Many recent theoretical works on \emph{meta-learning} aim to achieve guarantees in leveraging similar representational structures from related tasks towards simplifying a target task. Importantly, the main aim in theory works on the subject is to understand the extent to which convergence rates -- in learning a common representation -- \emph{may scale with the number $N$ of tasks} (as well as the number of samples per task). First steps in this setting demonstrate this property when both the shared representation amongst tasks, and task-specific regression functions, are linear. This linear setting readily reveals the benefits of aggregating tasks, e.g., via averaging arguments. In practice, however, the representation is often highly nonlinear, introducing nontrivial biases in each task that cannot easily be averaged out as in the linear case. In the present work, we derive theoretical guarantees for meta-learning with nonlinear representations. In particular, assuming the shared nonlinearity maps to an infinite-dimensional RKHS, we show that additional biases can be mitigated with careful regularization that leverages the smoothness of task-specific regression functions,
Battle Ground: Data Collection and Labeling of CTF Games to Understand Human Cyber Operators

Industry standard frameworks are now widespread for labeling the high-level stages and granular actions of attacker and defender behavior in cyberspace. While these labels are used for atomic actions, and to some extent for sequences of actions, there remains a need for labeled data from realistic full-scale attacks. This data is valuable for better understanding human actors’ decisions, behaviors, and individual attributes. The analysis could lead to more effective attribution and disruption of attackers. We present a methodological approach and exploratory case study for systematically analyzing human behavior during a cyber offense/defense capture-the-flag (CTF) game. We describe the data collection and analysis to derive a metric called keystroke accuracy. After collecting players’ commands, we label them using the MITRE ATT&CK framework using a new tool called Pathfinder. We present results from preliminary analysis of participants’ keystroke accuracy and its relation to score outcome in CTF games. We describe frequency of action classification within the MITRE ATT&CK framework and discuss some of the mathematical trends suggested by our observations. We conclude with a discussion of extensions for the methodology, including performance evaluation during games and the potential use of this methodology for training artificial intelligence.
Empirical Evaluation of a Live Environment for Extract Method Refactoring

Complex software can be hard to read, adapt, and maintain. Refactoring it can create cleaner and self-explanatory code. Refactoring tools try to guide developers towards better code, with more quality. However, most of them take too long to provide feedback, support, and guidance on how developers should improve their software. To reduce this problem, we explored the concept of Live Refactoring, focusing on visually suggesting and applying refactorings, in real-time. With this in mind, we developed a Live Refactoring Environment that visually identifies, recommends, and applies Extract Method refactorings. To validate it, we conducted an empirical experiment. Early results showed that our approach improved several code quality metrics. Besides, we also concluded that our results were significantly different and better than the ones from refactoring the code manually without further help.
Learning Discriminative Visual-Text Representation for Polyp Re-Identification

Colonoscopic Polyp Re-Identification aims to match a specific polyp in a large gallery with different cameras and views, which plays a key role for the prevention and treatment of colorectal cancer in the computer-aided diagnosis. However, traditional methods mainly focus on the visual representation learning, while neglect to explore the potential of semantic features during training, which may easily leads to poor generalization capability when adapted the pretrained model into the new scenarios. To relieve this dilemma, we propose a simple but effective training method named VT-ReID, which can remarkably enrich the representation of polyp videos with the interchange of high-level semantic information. Moreover, we elaborately design a novel clustering mechanism to introduce prior knowledge from textual data, which leverages contrastive learning to promote better separation from abundant unlabeled text data. To the best of our knowledge, this is the first attempt to employ the visual-text feature with clustering mechanism for the colonoscopic polyp re-identification. Empirical results show that our method significantly outperforms current state-of-the art methods with a clear margin.