Miracle-dz/UniFAR-FTUs huggingface dataset:
Finite time state tracking control based on prescribed performance for a class of constrained nonlinear systems

In this article, a finite time prescribed performance controller is designed for a class of constrained nonlinear systems with external disturbances. A homeomorphic mapping is used for error conversion to establish the equivalent error model of the system. A robust stability controller is designed when the initial state is in the initial stability region. A finite time optimization controller is designed to make the state reach the initial stability region when the initial state is outside the initial stability region. Based on Lyapunov stability theory, it is proved that the system can realize state tracking in a limited time and meet the prescribed performance conditions. The effectiveness of the proposed method is testified by two simulation examples.
Multi-sensor data fusion method based on PSO algorithm to optimize RBF neural network

Aiming at the uncertainty of data collected in multi-sensor networks, a multi-sensor fusion technique based on the PSO algorithm is suggested to optimize the RBF neural network with the aim of reducing the uncertainty of data gathered in multi-sensor networks. The RBF neural network's weight and threshold parameters are modeled as moving particles, with vectors used to describe their positions. The PSO algorithm chooses the proper values for the parameters. The ideal parameter values of the RBF neural network are ultimately established following iterative training. It has been demonstrated that the PSO algorithm-based RBF neural network multi-sensor data fusion algorithm has higher fusion accuracy and shorter running times.
Characterization of OSIRIS NAC filters for the interpretation of multispectral data of comet 67P/Churyumov-Gerasimenko

Context. We interpret multicolor data from OSIRIS NAC for the remote-sensing exploration of comet 67P/Churyumov-Gerasimenko. Aims. We determine the most meaningful definition of color maps for the characterization of surface variegation with filters available on OSIRIS NAC. Methods. We analyzed laboratory spectra of selected minerals and olivine-pyroxene mixtures seen through OSIRIS NAC filters, with spectral methods existing in the literature: reflectance ratios, minimum band wavelength, spectral slopes, band tilt, band curvature, and visible tilt. Results. We emphasize the importance of reflectance ratios and particularly the relation of visible tilt vs. band tilt. This technique provides a reliable diagnostic of the presence of silicates. Color maps constructed by red-green-blue colors defined with the green, orange, red, IR, and Fe2O3 filters let us define regions that may significantly differ in composition.
APPLICATION OF H* ROBUST TECHNIQUE FOR CONTROL OF UNCERTAIN WAVE EQUATIONS

Application of H^ robust technique for control of one-dimensional uncertain wave equations by a distributed force is studied in this paper. The wave equation may contain uncertainties in the coefficients multiplying various derivatives and viscous damping terms. Linear //«, robust controller is known to stabilize systems with certain types of bounded uncertainties; it is employed in this study to control the wave equation with positive or negative bounded damping coefficients, as well as the time-varying coefficients. It is shown that the robust control gain obtained from the solution of a partial differential Riccati equation can be used to stabilize the uncertain wave systems. Numerical simulation results illustrate the potential of the proposed method.
Exploring the Joint Potential of Blockchain and AI for Securing Internet of Things

—The emergence of the Internet of Things (IoT) has revolutionized the way we interact with the physical world. The rapid growth of IoT devices has led to a pressing need for robust security measures. Two promising approaches that can enhance IoT security are blockchain and artificial intelligence (AI). Blockchain can offer a decentralized and tamper-proof framework, ensuring the confidentiality and integrity of IoT data. AI can analyze large volumes of real-time data and detect anomalies in response to security threats in the IoT ecosystem. This paper explores the potential of these technologies and how they complement each other to provide a secured IoT system. Our main argument is that combining blockchain with AI can provide a robust solution for securing IoT networks and safeguarding the privacy of IoT users. This survey paper aims to provide a comprehensive understanding of the potential of these technologies for securing IoT networks and discuss the challenges and opportunities associated with their integration. It also provides a discussion on the current state of research on this topic and presents future research directions in this area.
Multiscale Cross-Modal Homogeneity Enhancement and Confidence-Aware Fusion for Multispectral Pedestrian Detection

Multispectral pedestrian detection has shown many advantages in a variety of environments, particularly poor illumination conditions, by leveraging visible-thermal modalities. However, in-depth insight into distinguishing the complementary content of multimodal data and exploring the extent of multimodal feature fusion is still lacking. In this paper, we propose a novel multispectral pedestrian detector with multiscale cross-modal homogeneity enhancement and confidence-aware feature fusion. RGB and thermal streams are constructed to extract features and generate candidate proposals. During feature extraction, multiscale cross-modal homogeneity enhancement is proposed to enhance single-modal features using the separated homogeneous features via modal interactions. Homogeneity features encode the semantic information of the scene and are extracted from the RGB-thermal pairs by employing a channel attention mechanism. Proposals from two modalities are united to obtain multimodal proposals. Then, confidence measurement fusion is proposed to achieve multispectral feature fusion in each proposal by measuring the internal confidence of each modality and the interaction confidence between modalities. In addition, a confidence transfer loss function is designed to focus more on hard-to-detect samples during training. Experimental results on two challenging datasets demonstrate that the proposed method achieves better performance compared to existing methods.
Signal Parameter Estimation Using 1-Bit

Motivated by the estimation of spatio-temporal events with cheap, simple sensors, we consider the problem of estimation of a parameter of a signal corrupted by noise assuming that only 1-bit precision dithered quantized samples are available. An estimate that does not require the knowledge of the dither signal and the noise distribution is proposed, and it is analyzed in detail under variety of nonidealities. The consistency and asymptotic normality of the estimate is established for deter- ministic and random sampling, imprecise knowledge of sampling locations, Gaussian and non-Gaussian noise (with possibly infinite variance), a wide class of dither distributions, and under erroneous transmission of the binary observations via binary-symmetric channels (BSCs). It is also shown that if approximation to the log-likelihood equation in the full precision case yields a good estimate, then there is a corresponding good estimate based on 1-bit dithered samples. The proposed estimate requires no more computation than the maximum-likelihood estimate for the full precision case and suffers only a logarithmic rate loss compared to the full precision case when uniform dithering is used. It is shown that uniform dithering leads to the best rate among a broad class of dither distributions. A condition under which no dithering leads to a better estimate is also given.
Applied Statistical Decision Theory.

In general, this book is concerned with capital budgeting and decision theory. Specifically, it centers around a singular uncertainty decision the decision by oil and gas operators to drill, or not to drill, a well. Actually, a sequence of decisions must precede this final action, but each one of these preliminary decisions is principally directed toward the final payoff question: Should we invest money in this well? If so, how much should we risk, and how much of the risk should we share with others? The objective of this book is twofold. The first objective is to describe the nature of decision problems in drilling for gas and oil, a business situation where uncertainties are exceptionally great, and to describe how businessmen actually make drilling decisions in the face of these uncertainties. This descriptive section, of great interest in its own right, then provides the foundation for the second objective, which is to explore the possibilities of applying "decision theories" to such decisions. This second objective is normative or prescriptive in its attempt to provide the driller with better guides to consistent action to meet his own goals. The presentation of the applications of mathematical theories is kept clear and simple, and the methods suggested for dealing with these problems can be understood by a reader with only a working knowledge of arithmetic and high school algebra. This book should be of interest to several audiences, among whom are the following: ( 1 ) people in the oil industry; (2) people in other industries who are actively interessed in finding ways of making better decisions in situations of risk and uncertainty; and (3) people whose interests are perhaps inore academic and who are concerned with both theory and practice in the area of decision making. xmlui.dri2xhtml. METS1.0. item-descriptionmiscellaneous 380 p., graph. Search all I-Revues This Collection
Ferroelectric Switching by the Grounded Scanning Probe Microscopy Tip

The process of polarization reversal by the tip of scanning probe microscope was intensively studied for last two decades. Number of the abnormal switching phenomena was reported by the scientific groups worldwide. In particularly it was experimentally and theoretically shown that slow dynamics of the surface screening controls kinetics of the ferroelectric switching, backswitching and relaxation and presence of the charges carriers on the sample surface and in the sample bulk significantly change polarization reversal dynamics. Here we experimentally demonstrated practical possibility of the history dependent polarization reversal by the grounded SPM tip. This phenomenon was attributed to induction of the slowly dissipating charges into the surface of the grounded tip that enables polarization reversal under the action of the produced electric field. Analytical and numerical electrostatic calculations allow additional insight into nontrivial abnormal switching phenomena reported earlier.
Quantum resonance catastrophe for conductance through a periodically driven barrier

We consider the quantum transport in a tight-binding chain with a locally applied potential which is oscillating in time. The steady state for such a driven impurity can be calculated exactly for any energy and applied potential using the Floquet formalism. The resulting transmission has a non-trivial, non-monotonic behavior depending on incoming momentum, driving frequency, and the strength of the applied periodic potential. Hence there is an abundance of tuning possibilities, which allows to find resonances of total reflection for any choice of incoming momentum and periodic potential. Remarkably, this implies that even for an arbitrarily small infinitesimal impurity potential it is always possible to find a resonance frequency at which there is a catastrophic breakdown of the transmission T=0. The points of zero transmission are closely related to the phenomenon of Fano resonances at dynamically created bound states in the continuum. The results are relevant for a variety of one-dimensional systems where local AC driving is possible, such as quantum nanodot arrays, ultracold gases in optical lattices, photonic crystals, or molecular electronics.
A scattering phase function for ice cloud: Tests of applicability using aircraft and satellite multi‐angle multi‐wavelength radiance measurements of cirrus

A parametrization of the Henyey‐Greenstein scattering phase function is presented for application to aircraft and satellite remote sensing of cirrus‐cloud bulk and microphysical properties at non‐absorbing and absorbing wavelengths. The phase function is based initially around a non‐absorbing laboratory‐measured phase function between scattering angles of 30° and 180°, although at scattering angles greater than 95° the phase function is made constant with scattering angle. This ‘analytic’ phase function has an asymmetry parameter value of 0.80 at non‐absorbing wavelengths. This analytic phase function is tested using aircraft‐based transmission radiance measurements at the wavelengths of 0.55 μm, 0.87 μm, 1.6 μm and 3.7 μm between scattering angles of 10° and 120°, and satellite retrievals of cirrus‐cloud spherical albedo at the wavelength of 0.67 μm between scattering angles of 60° and 180°. The analytic phase function reproduces both aircraft and satellite measurements well, and is shown to be a distinct improvement over single‐crystal model phase functions representing both small and large crystals in terms of angular scattering pattern and retrieved optical thickness.
THE MODELLING OF THE DYNAMICS OF HAIRPIN VORTEX PACKETS IN WALL TURBULENCE

The talk addresses the experimental, analytical and numerical modelling of the dynamics of concentrated vortex packets over a rigid smooth plane. To answer the principal question why and how does fluid in outer region of the turbulent boundary layer organize itself into hairpin streamwise vortex packets with low-speed convective velocity we developed the vortex filament model of hierarchy of hairpin packets.
Utilization of Plastic Waste for Developing Composite Bricks and Enhancing Mechanical Properties: A Review on Challenges and Opportunities

The population increases demand for plastic in every sector along with single-use plastic rapidly increasing, but it still has a low recycling rate. The use of plastic in the form of brick is challenging and overall has a better impact on the ecosystem, economy, and industrial revolution. In this paper, a study has been done of the available research work on plastic bricks from different plastic waste materials. It discusses the processes used to make bricks from plastic waste materials, the possibility of contamination from the waste materials utilized, the lack of pertinent standards, and the public adoption of waste materials-based bricks. Furthermore, it focused on research and development required for the widespread production and use of bricks made from waste materials, not only in terms of technical, economic, and environmental considerations but also in terms of standardization, governmental policy, and public awareness of waste recycling and sustainable development. It has been observed from the study that PET has mostly recycled plastic with greater efficiency compared to other plastics. However, worldwide global production is followed by PE, PVC, and PP. PET has only 5% contribution to the global recycling of plastics.
Estimation of genetic variance components including mutation and epistasis using Bayesian approach in a selection experiment on body weight in mice

Selection experiment was performed for body weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets containing standard and severely reduced protein level (19.3 and 5.1 % crude protein respectively). Within each diet three lines were selected upwards, three lines were selected downwards and the other three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods introduced by Wray (1990). DIC was used to compare the model fit. Models with mutation effect have better fit compared to the model with only additive genetic effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance.
Ship trajectory prediction model based on transformer

To improve the prediction accuracy of ship trajectory, the Transformer model is applied to predict ship trajectory. The pre-processed AIS data are used for the training and testing of Transformer model, and the AIS data from port area of Ningbo Zhoushan are used for validation. The results prove that the Transformer model is suitable for ship trajectory prediction, and the mean absolute error and mean square error of the Transformer model prediction results are smaller than those of other prediction models. The prediction results show that it is feasible to use Transformer model for ship trajectory prediction, and it also provides a kind of data preparation for collision avoidance warning for ships.
Delaunay Triangulation in 3D

The Delaunay triangulation is one of the most popular and most often used methods in problems related to the generation of meshes. A lot of the optimal properties of Delaunay triangulation are known in 2D, where it has been intensively studied during the last twenty years, although the fundamentals were formulated early in the twentieth century (Voronoi, 1908 and Delaunay, 1934). This thesis presents Delaunay triangulation without addition or displacement of points in 3D space. It focuses on its properties and on a summarization of existing sequential algorithms. Also our experience with the implementation of the incremental insertion algorithm is presented and observed features are discussed. The properties of Delaunay triangulation in 3D (or generally in higher dimensions) are not as good as in 2D and different kinds of methods are used mainly to remove the tetrahedra of undesirable shape. Although this area of research was not within our main scope, we present an existing simple method for tetrahedra shape improvement. We have implemented this method and our results are presented and discussed. In the implementation of algorithms, which have to deal with inprecise floating-point arithmetic on real computers, the question of numerical stability becomes very important for the proper function of the implementation. We introduce several existing approaches for increasing the numerical stability of algorithms, two of them for an exact evaluation of geometric predicates are presented in more details. We made a comparison of them and we mention the results of incorporating one of them in our implementation.
A new HNO3 digestion procedure for Re–Os isotope analysis and its implications for organic‐rich sedimentary rocks and mafic rocks

The precision of available Re–Os isotope analysis for organic‐rich sedimentary (ORS) rocks is influenced by the coexisting clastic and organic components and the considerable differences between Re and Os mass fractions in such rocks. Here, we present a new method to analyse Re–Os isotopes of organic‐rich sedimentary (ORS) rocks by thermal ionization mass spectrometry. Nitric acid (HNO3) was used as the single digestion medium, and this method mainly relies on HNO3 at the optimum digestion condition, which can both equilibrate Os isotope between spike and sample and prevent the dissolving of clastic particles as many as possible especially the non‐aqueous elements inside. After a series of condition experiments, our data demonstrate that digestion temperatures and durations play important roles not only on the equilibrium between sample and spike, but also on the dissolving‐out quantity of non‐aqueous Re and Os elements. The optimum condition of 24 h and 230°C (the obtained Re and Os concentrations for the oil shale reference material SGR‐1b, and the 187Os/188Os ratios are 33.44 ± 0.09 ng/g, 0.4452 ± 0.0107 ng/g and 1.7822 ± 0.0439, n = 3, 1SD) can produce the Re–Os isotopic ratios of ORS at a precise level, and restrain the liberation of clastic Re and Os. This method at the digestion condition of 24 h and 230°C, therefore, will increase the accuracy of Re–Os isotope analysis of ORS on the basis of low blank and high efficiency. When this method is used for olivine tholeiite reference materials (BIR‐1a), the result demonstrates that the Os isotopes of mafic rocks do not produce fractionation when the temperature is higher than 200°C during the HNO3 digestion.
Childhood Bacterial Meningitis Surveillance in Southern Vietnam: Trends and Vaccination Implications From 2012 to 2021

Abstract Background This retrospective hospital-based surveillance aimed to assess the epidemiology, causative pathogens trend, and serotypes distribution of pneumococcal meningitis among children aged under 5 years with bacterial meningitis in Southern Vietnam after the introduction of pentavalent vaccine in the Expanded Program on Immunization (EPI). Methods From 2012 to 2021, cerebrospinal fluid samples were collected from children aged under 5 years with suspected bacterial meningitis at Children's Hospitals 1 and 2 in Ho Chi Minh City. Probable bacterial meningitis (PBM) cases were identified using biochemistry and cytology. Real-time polymerase chain reaction was used to confirm cases of confirmed bacterial meningitis (CBM) caused by Streptococcus pneumoniae, Haemophilus influenzae, or Neisseria meningitidis. Streptococcus pneumoniae serotyping was performed. Results Of the 2560 PBM cases, 158 (6.2%) were laboratory-confirmed. The CBM proportion decreased during the 10-year study and was associated with age, seasonality, and permanent residence. Streptococcus pneumoniae was the most common pathogen causing bacterial meningitis (86.1%), followed by H influenzae (7.6%) and N meningitidis (6.3%). The case-fatality rate was 8.2% (95% confidence interval, 4.2%–12.2%). Pneumococcal serotypes 6A/B, 19F, 14, and 23F were the most prevalent, and the proportion of pneumococcal meningitis cases caused by the 10-valent pneumococcal conjugate vaccine (PCV) serotypes decreased from 96.2% to 57.1% during the PCV eras. Conclusions Streptococcus pneumoniae is the most frequent causative agent of bacterial meningitis in children aged under 5 years in Southern Vietnam over the last decade. Policymakers may need to consider introducing PCVs into the EPI to effectively prevent and control bacterial meningitis.
A Simple Integrated Interferometer for Salinity and Temperature Measurement

A simple integrated interferometer with an open cavity for salinity and temperature measurement is theoretically analyzed and verified in the article. The sensing probe consists of a small segment of hollow core fiber (HCF) embedded in a pair of multimode fibers (MMFs) and is spliced to the light-guiding single-mode fiber (SMF), that is, the SMF–MMF–HCF–MMF–SMF (SMHMS) structure. The existence of the opening cavity makes it possible for Mach–Zehnder (MZ) and Fabry–Perot (FP) interference spectra to coexist in a single compact structure. The interferometer not only maintains the high sensitivity in salinity measurement with the MZ interferometer (MZI) but also obtains the spectrums of the MZI and FP interferometer (FPI) simultaneously, which is adequate to make a more precise measurement. In the experiment, the sensitivity of salinity can reach −3.2 nm/ ‰ in the salinity range of 0 $\unicode{0x2030}-40\,\,\unicode{0x2030}$ , at the same time, that of temperature can reach 1.64 nm/°C within 5 °C–30 °C. According to the different responses of two interferometers in one compact structure to salinity and temperature, the problem of cross-sensitivity can be solved. In addition, the proposed sensing probe has advantages in size, sensitivity, and multiparameter sensing.