Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep hierarchical transformer for change detection in high-resolution remote sensing images

ABSTRACT Deep learning instantiated by convolutional neural networks has achieved great success in high-resolution remote-sensing image change detection. However, such networks have a limited receptive field, being unable to extract long-range dependencies in a scene. As the transformer model with self-attention can better describe long-range dependencies, we introduce a hierarchical transformer model to improve the precision of change detection in high-resolution remote sensing images. First, the hierarchical transformer extracts abstract features from multitemporal remote sensing images. To effectively minimize the model’s complexity and enhance the feature representation, we limit the self-attention calculation of each transformer layer to local windows with different sizes. Then, we combine the features extracted by the hierarchical transformer and input them into a nested U-Net to obtain the change detection results. Furthermore, a simple but effective model fusion strategy is adopted to improve the change detection accuracy. Extensive experiments are carried out on two large-scale data sets for change detection, LEVIR-CD and SYSU-CD. The quantitative and qualitative experimental results suggest that the proposed method outperforms the advanced methods in terms of detection performance.
On the Allocation of Treatments in Sequential Medical Trials

Summary Several allocation rules are compared by assessing their effectiveness in discovering which of two treatments has the higher probability of success. The number of observations needed to obtain a given level of precision can be minimized by using a fixed-sample rule, but this involves too many applications of the inferior treatment. It is demonstrated that sequential allocation rules can achieve a similar pattern of error probabilities for a small fraction of the expected cost to the volunteers employed in the experiment.
A Fast and Efficient Hybrid Fractal-Wavelet

The excellent visual quality and compression rate of fractal image coding have limited applications due to exhaustive inherent encoding time. This paper presents a new fast and effi- cient image coder that applies the speed of the wavelet transform to the image quality of the fractal compression. Fast fractal encoding using Fisher's domain classification is applied to the lowpass subband of wavelet transformed image and a modified set par- titioning in hierarchical trees (SPIHT) coding, on the remaining coefficients. Furthermore, image details and wavelet progressive transmission characteristics are maintained, no blocking effects from fractal techniques are introduced, and the encoding fidelity problem common in fractal-wavelet hybrid coders is solved. The proposed scheme promotes an average of 94% reduction in en- coding-decoding time comparing to the pure accelerated Fractal coding results. The simulations also compare the results to the SPIHT wavelet coding. In both cases, the new scheme improves the subjective quality of pictures for high-medium-low bitrates.
Computational aspects of a new multi‐scale dispersive gradient elasticity model with micro‐inertia

Computational aspects of a recently developed gradient elasticity model are discussed in this paper. This model includes the (Aifantis) strain gradient term along with two higher‐order acceleration terms (micro‐inertia contributions). It has been demonstrated that the presence of these three gradient terms enables one to capture the dispersive wave propagation with great accuracy. In this paper, the discretisation details of this model are thoroughly investigated, including both discretisation in time and in space. Firstly, the critical time step is derived that is relevant for conditionally stable time integrators. Secondly, recommendations on how to choose the numerical parameters, primarily the element size and time step, are given by comparing the dispersion behaviour of the original higher‐order continuum with that of the discretised medium. In so doing, the accuracy of the discretised model can be assessed a priori depending on the selected discretisation parameters for given length‐scales. A set of guidelines can therefore be established to select optimal discretisation parameters that balance computational efficiency and numerical accuracy. These guidelines are then verified numerically by examining the wave propagation in a one‐dimensional bar as well as in a two‐dimensional example. Copyright © 2016 John Wiley & Sons, Ltd.
Toward a Domain Description with CafeOBJ

In our work, we try to describe a domain description with CafeOBJ. A domain description means a document which describes observable phenomena of the domain. It also means the process of of domain capture, analysis and synhesis, and the document which result from that process[3]. We formalise the domain description in [2] in CafeOBJ. CafeOBJ is a formal specication language. By formalisation of domain description, we can avoid the ambiguities and inconsistency of the description, and can prove propertiess in a domain precisely.
Systematics of Periodic Windows in the Double-Diffusive Convection System

The dynamics of truncated double-diffusive convection system on a parameter axis is studied with symbolic dynamics. It is found that the systematics of periodic windows interspersed in chaotic region for its one-dimensional (1D) return maps (to be defined in the text) can be fitted into the universal form for the 1D mappings with two critical points and the antisymetric property.
Absorption/Scattering of Massless Dirac Wave from Black Hole Spacetimes with Cosmic String

In this paper we investigate the scattering of massless Dirac wave from several different black hole spacetimes (i.e. the Schwarzschild black hole, the RN extremal black hole, the Schwarzschild de Sitter black hole, and the extremal Schwarzschild de Sitter black hole) which are influenced by the cosmic string, respectively. All these cases show us that the total absorption cross sections oscillate around the geometric-optical limit and decrease with linear mass density μ of the cosmic string. All of the total scattering cross sections exhibit that the main scattering angle becomes narrower for the high partial frequency wave. Due to the influence of cosmic string, the glory peak becomes wider for larger values of linear mass density μ of the cosmic string.
Presupposition without Common Ground

In this paper, I review a number of arguments in favor of treating many of the central cases of presupposition as the result of conversational inference, rather than as lexically specified properties of particular expressions. I then argue that, despite the standard assumption to the contrary, the view of presupposition as constraints on the common ground is not consistent with the provision of a conversational account of particular instances of presupposition. The argument revolves crucially around the workings of accommodation. I then offer an alternative view of the phenomenon of presupposition, which is compatible with a variety of sources for presuppositions. On the view offered here, presupposition is seen as a property of utterances. I argue that the presuppositions of an utterance are those propositions which an interpreter must take the speaker to accept in order to take the speaker to be fully cooperative, in a broadly Gricean sense.
Solving constrained path problem based on improved recurrent neural network

In order to find the global optimal solution of the loop-free path with constraints, to solve the problems of low efficiency, and only local optimum in the traditional segmented splicing algorithm, an optimal calculation of the path with constraints based on an improved recurrent neural network is proposed. The embedded graph attention network structure, by specifying different attention weights for neighbor nodes, learns the graph embedding features of different constructed network topologies, and uses the learned graph features as the internal state of the recurrent neural network to predict according to the recurrent time sequence, the optimal order of the constraint segmentation is obtained, and finally the segmentation path is obtained according to the constraint segmentation, and the global optimal path is obtained by splicing. The experimental results show that, compared with the traditional segmentation splicing algorithm, the calculation amount of the algorithm in this paper is significantly reduced, the operating efficiency is significantly improved, and the global optimal solution can be obtained, and the generalization ability of the unknown network topology is extremely strong. In practical engineering applications It has very high practical value.
Research on industrial internet intrusion detection model based on optimized BI-GRU

The intrusion detection model based on deep learning has become a research hotspot in the field of network security, aiming at the high FPR and low DR of current intrusion detection systems, this paper proposes an anomaly detection model based on deep learning. The system is first optimized by particle swarm optimization. Data feature extraction, and then through the fusion of MLP's bidirectional GRU model to better mine the information contained in the data set and its correlation, and improve the efficiency and quality of feature extraction. Finally, experiments show that the model has good performance, with a detection readiness rate of 98.74%, a false positive rate of 0.029, and a detection rate of 98.42%. The results show that the detection effect of PSO+BI-GRU+MLP is better than other algorithm models.
Effects of Composition and Compression Pressure on the Ferroelectricity of a Novel Eco-Friendly Nanocomposite Based on a Molecular Ferroelectric of Tris-Sarcosine Calcium Chloride Filled with Cellulose Nanoparticles

Abstract For the first time, to our knowledge, an eco-friendly nanocomposite based on a classical molecular ferroelectric of Tris-sarcosine calcium chloride (TSCC) with an addition of cellulose nanoparticles (CNPs) was synthesized. The samples containing different cellulose concentrations were compressed under various pressures from 0.1 to 0.7 GPa to investigate the effects of composition and compression pressure on the ferroelectricity of the composites. Experiments were conducted on samples in the fresh state and after 200 h under normal conditions. The results obtained demonstrated higher phase transition temperatures in the composites than those of pure TSCC. Besides, a deformation of the dielectric hysteresis loops with changing cellulose content was detected. Importantly, an increase in compression pressure applied on the samples led to the movement of the phase transition point toward higher temperatures. The results also revealed an instability of the ferroelectric properties in the composites with high content of cellulose.
Rosa davurica Inhibited Allergic Mediators by Regulating Calcium and Histamine Signaling Pathways

Rosa davurica Pall. exhibits antioxidant, antiviral, and anti-inflammatory properties; however, its pharmacological mechanism in allergy is yet to be understood. This study confirmed the effects of R. davurica Pall. leaf extract (RLE) on allergy as a new promising material. To evaluate the therapeutic potential of RLE against allergy, we investigated the effects of RLE on the regulatory β-hexosaminidase, histamine, histidine decarboxylase (HDC), Ca2+ influx, nitric oxide (NO), and cytokines induced by lipopolysaccharide (LPS) and DNP-IgE/BSA in Raw 264.7 and RBL-2H3 cells. Furthermore, we examined the effects of RLE on the signaling pathways of mitogen-activated protein kinase (MAPK) and Ca2+ pathways. After stimulating Raw 264.7 cells with LPS, RLE reduced the release of inflammatory mediators, such as NO, cyclooxygenase (COX)-2, inducible nitric oxygen synthase (iNOS), interleukin (IL)-1β, -6, and tumor necrosis factor (TNF)-α. Also, RLE reduced the β-hexosaminidase, histamine, HDC, Ca2+ influx, Ca2+ pathways, and phosphorylation of MAPK in DNP-IgE/BSA-stimulated RBL-2H3 cells. Our studies indicated that RLE is a valuable ingredient for treating allergic diseases by regulating cytokine release from macrophages and mast cell degranulation. Consequently, these results suggested that RLE may serve as a possible alternative promising material for treating allergies.
Durable Response after Repeat Cytoreductive Surgery (CRS) and Hyperthermic Intraperitoneal Chemotherapy (HIPEC) in a Patient with Extensive Mucinous Adenocarcinoma of the Appendix

Mucinous adenocarcinoma of the appendix is a rare form of lower gastrointestinal (GI) tract cancer. These cancers have a high tendency to progress towards peritoneal metastasis and their response to systemic treatment is typically low. Together, cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) have become an established form of therapy used to prolong the survival of patients with this disease. Repeat CRS and HIPEC have been shown to be feasible in selected patients with GI peritoneal carcinomatosis (PC), among which those with appendix cancer receive the greatest benefit. The peritoneal cancer index (PCI) and completeness of cytoreduction have been shown to be important predictors of outcomes. However, repeat cytoreduction in patients with a high-volume peritoneal tumor burden (peritoneal cancer index (PCI) > 30) is not typically performed due to concerns regarding morbidity and mortality. Herein, we describe a case of repeat CRS and HIPEC for extensive appendiceal mucinous peritoneal carcinomatosis after initial incomplete cytoreduction and durable remission of 28 months without adjuvant chemotherapy. In appendiceal mucinous cancers, repeat CRS can achieve a durable response despite an initial failed CRS and high-volume disease.
A Line Mapping Based Automatic Registration Algorithm of Infrared and Visible Images

A novel image similarity called implicit linesegment similarity( ILS),and a registration algorithm of infrared and visible images based on ILS,are proposed.Essentially,the algorithm achieves image registration by aligning the corresponding line segment features in two images.First,line segment features are extraced and their coordinate positions in one of the images are recorded.These line segment features are mapped into the second image,in which the geometric mapping relationship are caculated by maximizing the degree of similarity between the line segment features and correspondence regions in the second image.The advantage of this method is that it eliminates the need to directly measure the grey similarity between the two images.A multiresolution analysis method is used to calculate the model parameters from coarse to fine on Gaussian scale space.The geometric transformation parameters are finally obtained by the improved Powell algorithm.Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images.It significantly improves computational efficiency and anti-noise ability beyond previously proposed algorithms.
Pauli Crystals: hidden geometric structures of the quantum statistics

We predict existence of Pauli crystals -- so far undiscovered form of matter organization on the microscopic level. The predicted crystalline structure is present in a non-interacting system of a few quantum particles, only because of the Fermi-Dirac statistics. This finding touches one of the most fundamental principles of Quantum Theory, namely the Pauli exclusion principle and shows its role from a geometric perspective.
Problems and Solutions of Low Frequency PWM Inverters—an Overview

To increase output power of medium voltage inverters, the switching frequency has to be decreased, that causes high harmonic problem. For solving the problem, it is better to adopt synchronized and symmetrical optimal PWM strategies. Two of them, CHM-PWM and SHE-PWM, and their approximate simplified algorithms,were introduced.The optimal strategies can not be used to high performance system directly, that will make system out-off work during transient. The system, stator flux trajectory control, which can both decrease harmonics and have fast response, was investigated, it is based on the optimal PWM and has the function of revising switching angles. For solving the cross-coupling problem caused by low switching frequency a new closed-loop variable speed control system which is based on flux trajectory control and different from vector control was introduced.
A Unified Statistical Approach to Modeling the Shape of Human Hyoid Bones in CT Images

We present a unified statistical approach to modeling 3D anatomical objects extracted from medical images. Due to image acquisition and preprocessing noises, it is expected the imaging data is noisy. Using the Laplace-Beltrami (LB) eigenfunctions, we smooth out noisy data and perform statistical analysis. The method is applied in characterizing the 3D growth pattern of human hyoid bone between ages 0 and 20 obtained from computed tomography (CT). We detected a significant age effect on localized parts of the hyoid bone.
Image encryption with an improved cryptosystem based on a matrix approach

This paper carries out the image encryption with a revised and modified cryptosystem based on a rule-90 cellular automaton. For this purpose, we used an appropriate and convenient matrix approach to implement the main components of the encryption system, two indexed families of permutations and a pseudo-random bit generator. Furthermore, we modify the encryption scheme for improving its security. This makes our encryption proposal resist some common attacks, e.g. chosen plain-text attack, and the encryption and decryption processes are performed in a flexible way. Also, some security aspects of the cryptosystem are evaluated with a series of statistical tests exhibiting good results. It is believed that this proposal fits naturally in the present digital technology and is capable of achieving high levels of performance.
New method for time-lapse seismic matching based on SVD

The conventional match filter in time-lapse seismic cross-equalization is discussed. In order to reduce the influence of noise, new matching filter formula is derived and the method based on SVD is proposed. The effectiveness of the method is tested though theoretical and real data. The result indicates that new method is better than conventional one.
A Geometric Rectification Method for Lens Camera

Images with severe geometrical distortions,which are induced by camera lens and position, must be corrected before extracting quantitative m easurements.In this paper,we present a geometric calibration method for lens c amera by applying polynomial warping and bilinear interpolation,and discusses t he selection pattern of control points.First,we implement a general polynomial warping algorithm and a bilinear interpolation algorithm in Visual C ++ 5 0,then we demonstrate that,for common optical lens,images with geometric dist ortions can be rectified with cubic polynomial warping method using only a few c ontrol points.This method is simple and practical,and can be used in camera-f ixed situations,such as operating table and on-line industry inspection,to ac quire lossless images.Practical application in lottery printing quality inspect ion shows that the method is reliable and valid.
Interactive Modeling of Architectural and Regional Design Based on Augmented Reality (AR)

Augmented-Reality is a technology that presents the virtual world into the dimensions of the real world that can be controlled through implicit user interactions with virtual objects. With the rapid development of AR to date, many aspects of technology support the visualization of virtual objects to offer various services to meet the needs of each sector. Although augmented reality applications are used in many areas, AR technology is still relatively new in its use for the advancement of architectural applications. With the current AR technology, the physical form of the mock-up can be replaced by presenting the building design virtually to the real world and providing a different visual accentuation because the mock-up is present in a virtual entity. using the markerless augmented reality method. This method can be used to display 3-dimensional designs without having to use markers or markers so that they can place three-dimensional designs in various fields. In this study, the model that will be used is in the form of a reconstruction of the design of the Gajah Mada Denpasar Heritage Area which is then processed to be visualized interactively through an AR prototype.Heading/Introduction.
Analysis of Surface Texture and Roughness in Composites Stiffening Ribs Formed by SPIF Process

Studying roughness parameters and the topography of stiffening ribs in composite sandwich structures is important for understanding these materials’ surface quality and mechanical properties. The roughness parameters describe the micro-geometry of the surface, including the average height deviation, roughness depth, and waviness. The topography of the surface refers to the spatial arrangement and distribution of features such as bumps, ridges, and valleys. The study investigated the roughness parameters under three scenarios based on two SPIF process parameters: tool rotational speed(N) and feed rate (f). The vertical step was held constant at 0.4 mm across all scenarios. In scenario A, the process parameters were set at f = 300 mm/min and n = 300 rpm; in scenario B, f = 1500 mm/min and n = 3000 rpm; and in scenario C, f = 1500 mm/min and n = 300 rpm. The experimental research topography analyses revealed that the surface roughness of the stiffened ribs was highly dependent on the SPIF process parameters. The highest feed rate and tool rotational speed produced the smoothest surface texture with the lowest maximum height (Sz) value. In contrast, the lowest feed rate and tool rotational speed resulted in a rougher surface texture with a higher maximum height (Sz) value. Furthermore, the contour plots generated from the topography analyses provided a good visual representation of the surface texture and roughness, allowing for a more comprehensive analysis of the SPIF process parameters. This study emphasizes optimizing the SPIF process parameters to achieve the desired surface quality and texture of stiffened ribs formed in Litecor® panel sheets.
Energy bounds for a moving boundary initial boundary value problem for the semi-linear wave equation

The context of the paper is an initial boundary value problem for the semi-linear wave equation in a straight-line region with assigned moving boundaries, upon which time-dependent Dirichlet conditions are specified. Assuming smooth solutions, bounds, in terms of data, are obtained for the energy when the boundary motions are suitably restricted, and their sharpness (in a technical sense) is established (i.e. circumstances in which the bounds become equalities are obtained). It is shown how point-wise, upper bounds for the solution follow in the case of upper bounds for the energy. The means by which a generalization of the energy bounds to a three-dimensional context may be obtained is outlined briefly.
Braking due to non-resonant magnetic perturbations and comparison with neoclassical toroidal viscosity torque in EXTRAP T2R

The non-resonant magnetic perturbation (MP) braking is studied in the EXTRAP T2R reversed-field pinch (RFP) and the experimental braking torque is compared with the torque expected by the neoclassical toroidal viscosity (NTV) theory. The EXTRAP T2R active coils can apply magnetic perturbations with a single harmonic, either resonant or non-resonant. The non-resonant MP produces velocity braking with an experimental torque that affects a large part of the core region. The experimental torque is clearly related to the plasma displacement, consistent with a quadratic dependence as expected by the NTV theory. The work show a good qualitative agreement between the experimental torque in a RFP machine and NTV torque concerning both the torque density radial profile and the dependence on the non-resonant MP harmonic.