Rotational and translational domains of beta precipitate in aged binary Mg-Ce alloys

The structural evolution fromβ_(1)(Mg_(3)Ce)toβ(Mg_(12)Ce)precipitates,which takes place at the over-aged stage of binary Mg-Ce alloys,are investigated by high-angle annular dark-field scanning transmission electron microscopy.The structural transformation mainly occurs in the{111}_(β1)crystallographic planes,where the newly formedβlattices exhibit two categories of domain structures,namely rotational and translational domains.The rotational domain is composed of threeβdomains(β_(RA),β_(RB)andβ_(RC)),which are related by a 120°rotation with respect to each other around the 111_(β1)axis of theirβ_(1)parent phase.The{111}_(β1)crystallographic planes can provide four sets of sublattices with the same orientation for an initial nucleation ofβlattice.It leads to the formation of four translationalβdomains(β_(TA),β_(TB),β_(TC)andβ_(TD)),among which any two differ by a vector of 1/6112_(β1).We deduce theoretically that there exist twenty-fourβdomains during this transition.However,considering the interfacial misfit,only one-third of domains can grow up and eventually formsβribbon.Furthermore,a majority ofβribbons overlap partiallyβ_(1)plate,which is beneficial to relax interfacial strain amongβ,β_(1)andα-Mg matrix(α/β/β_(1)).The configuration of multipleβdomains can effectively regulate interfacial misfit ofα/βandβ/β_(1),which are responsible for enhancing the hardness and strength of Mg-Ce alloy.Additionally,this study aims to provide some clues to improve the over-aged performance of magnesium alloys by constructingβdomains and optimizing theα/β/β_(1)interface.

Image Reconstruction from Fan-Beam Projections without Back-Projection Weight in a 2-D Dynamic CT: Compensation of Time-Dependent Rotational, Uniform Scaling and Translational Deformations

In a dynamic CT, the acquired projections are corrupted due to strong dynamic nature of the object, for example: lungs, heart etc. In this paper, we present fan-beam reconstruction algorithm without position-dependent backprojection weight which compensates for the time-dependent translational, uniform scaling and rotational deformations occurring in the object of interest during the data acquisition process. We shall also compare the computational cost of the proposed reconstruction algorithm with the existing one which has position-dependent weight. To accomplish the objective listed above, we first formulate admissibility conditions on deformations that is required to exactly reconstruct the object from acquired sequential deformed projections and then derive the reconstruction algorithm to compensate the above listed deformations satisfying the admissibility conditions. For this, 2-D time-dependent deformation model is incorporated in the fan-beam FBP reconstruction algorithm with no backprojection weight, assuming the motion parameters being known. Finally the proposed reconstruction algorithm is evaluated with the motion corrupted projection data simulated on the computer.

Upper bound seismic rotational stability analysis of gravity retaining walls considering embedment depth

Stability analysis of gravity retaining wall was currently based on the assumption that the wall had no embedment depth. The effect of earth berm was usually neglected. The present work highlighted the importance of embedment depth when assessing the seismic stability of gravity retaining walls with the pattern of pure rotation. In the framework of upper bound theorem of limit analysis, pseudo-static method was applied into two groups of parallel rigid soil slices methods in order to account for the effect of embedment depth on evaluating the critical acceleration of wall-soil system. The present analytical solution is identical to the results obtained from using limit equilibrium method, and the two methods are based on different theory backgrounds. Parameter analysis indicates that the critical acceleration increases slowly when the ratio of the embedment depth to the total height of the wall is from 0 to 0.15 and increases drastically when the ratio exceeds 0.15.

Upper bound analysis for deep tunnel face with joined failure mechanism of translation and rotation

A joined failure mechanism of translation and rotation was proposed for the stability analysis of deep tunnel face, and the upper bound solution of supporting force of deep tunnel was calculated under pore water pressure. The calculations were based on limit analysis method of upper bound theory, with the employment of non-associated Mohr-Coulomb flow rule. Nonlinear failure criterion was adopted. Optimized analysis was conducted for the effects of the tunnel depth, pore water pressure coefficient, the initial cohesive force and nonlinear coefficient on supporting force. The upper bound solutions are obtained by optimum method. Results are listed and compared with the previously published solutions for the verification of correctness and effectiveness. The failure shapes are presented, and results are discussed for different pore water pressure coefficients and nonlinear coefficients of tunnel face.

Rotation,Translation and Scale Invariant Sign Word Recognition Using Deep Learning

Communication between people with disabilities and people who do not understand sign language is a growing social need and can be a tedious task.One of the main functions of sign language is to communicate with each other through hand gestures.Recognition of hand gestures has become an important challenge for the recognition of sign language.There are many existing models that can produce a good accuracy,but if the model test with rotated or translated images,they may face some difficulties to make good performance accuracy.To resolve these challenges of hand gesture recognition,we proposed a Rotation,Translation and Scale-invariant sign word recognition system using a convolu-tional neural network(CNN).We have followed three steps in our work:rotated,translated and scaled(RTS)version dataset generation,gesture segmentation,and sign word classification.Firstly,we have enlarged a benchmark dataset of 20 sign words by making different amounts of Rotation,Translation and Scale of the ori-ginal images to create the RTS version dataset.Then we have applied the gesture segmentation technique.The segmentation consists of three levels,i)Otsu Thresholding with YCbCr,ii)Morphological analysis:dilation through opening morphology and iii)Watershed algorithm.Finally,our designed CNN model has been trained to classify the hand gesture as well as the sign word.Our model has been evaluated using the twenty sign word dataset,five sign word dataset and the RTS version of these datasets.We achieved 99.30%accuracy from the twenty sign word dataset evaluation,99.10%accuracy from the RTS version of the twenty sign word evolution,100%accuracy from thefive sign word dataset evaluation,and 98.00%accuracy from the RTS versionfive sign word dataset evolution.Furthermore,the influence of our model exists in competitive results with state-of-the-art methods in sign word recognition.

NCCT for Micropolar Solid and Fluid Media Based on Internal Rotations and Rotation Rates with Rotational Inertial Physics: Model Problem Studies

This paper presents model problem studies for micropolar thermoviscoelastic solids without memory and micropolar thermoviscous fluid using micropolar non-classical continuum theories (NCCT) based on internal rotations and rotation rates in which rotational inertial physics is considered in the derivation of the conservation and balance laws (CBL). The dissipation mechanism is due to strain rates as well as rotation rates. Model problems are designed to demonstrate and illustrate various significant aspects of the micropolar NCCT with rotational inertial physics considered in this paper. In case of micropolar solids, the translational and rotational waves are shown to coexist. In the absence of microconstituents (classical continuum theory, CCT) the internal rotations are a free field, hence have no influence on CCT. Absence of gradients of displacements and strains in micropolar thermoviscous fluid medium prohibits existence of translational waves as well as rotational waves even though the appearance of the mathematical model is analogous to the solids, but in terms of strain rates. It is shown that in case of micropolar thermoviscous fluids the BAM behaves more like time dependent diffusion equation i.e., like heat conduction equation in Lagrangian description. The influence of rotational inertial physics is demonstrated using BLM as well as BAM in the model problem studies.

A Cone Rotating in a Fluid Translates

When a solid cone with smooth surfaces rotates at a constant rate about its long axis in still water, it will experience no friction, as announced earlier [1] and documented further here. However, if not restrained, it will translate along the axis base first and apex last, which is caused by a variation of pressure on its side: low near the base and high at the apex. This translation needs to be verified experimentally. Friction will occur during translation but an opposite reaction force will also take place related to the front to back asymmetry of the body [2]. Whether or not these two oppositely directed forces can cancel each other out by an appropriate choice of variable magnitudes is not known, but if true, it would lead to an extended translation. Also the translation path could be lengthened by slightly modifying the front face of the cone such that the translation itself produces rotation. One idea for such a modification is suggested. Observations in the future would be very beneficial.

Rotating Translating Cones

A first attempt has been made to confirm experimentally a theoretical concept, recently published, involving a rigid cone rotating about its long axis under still water: it should tend to translate along that axis blunt end leading and apex trailing. Two identical hollow cones, neutrally buoyant, with equal weights attached to the apexes, were released simultaneously at the surface of a swimming pool. One cone had a thin light weight spiral vane vertically attached to the cone’s outside surface in order to cause it to rotate as it sank. Several trial runs were made in the shallow and deep ends of the pool, and in every case, the non-rotating cone without a vane hit the bottom of the pool first. These comparisons qualitatively and indirectly validate the prediction.

Translation Elongation by Rotation in a Still Fluid of a Solid Cone with a Spiral Vane

Within the field of physics, the idea of perpetual motion is not allowed in most references. However, in a still fluid, one potential perpetual motion example is offered: a hollow solid cone rotating about its long axis at a constant rate.

Hierarchical path planning for multi-arm spacecraft with general translational and rotational locomotion mode

On-orbit construction and maintenance technology will play a significant role in future space exploration.The dexterous multifunctional spacecraft equipped with multi-arm,for instance,Spider Fab Bot,has attracted a great deal of focus due to its versatility in completing these missions.In such engineering practice,point-to-point moving in a complex environment is the fundamental issue.This paper investigates the three-dimensional point-to-point path planning problem,and a hierarchical path planning architecture is developed to give the trajectory of the multi-arm spacecraft effectively and efficiently.In the proposed 3-level architecture,the high-level planner generates the global constrained centric trajectory of the spacecraft with a rigid envelop assumption;the middle-level planner contributes the action sequence,a combination of the newly developed general translational and rotational locomotion mode,to cope with the relative position and attitude of the arms about the centroid of the spacecraft;the low-level planner maps the position/attitude of the end-effector of each arm from the operational space to the joint space optimally.Finally,the simulation experiment is carried out,and the results verify the effectiveness of the proposed three-layer architecture path planning strategy.

Rigid-Liquid-Flexible Dynamic Formulation for a Two-Dimensional Tank Undergoing Translational and Rotational Motion

Considering rigid-liquid-flexible coupling effect, dynamic formulation for a two-dimensional rectangular tank with liquid sloshing connected to a flexible beam is proposed. Differing from the traditional formulation which considered either the rotational motion or the translational motion of the tank, this formulation can be applied for rigid-liquid-flexible coupling dynamic analysis of tank undergoing translational and rotational motion based on the theorem of momentum and the theorem of moment of momentum. Furthermore, stiffening terms are included in the dynamics equations of the flexible beam. Firstly, the dynamic equations of the rigid-liquid coupling system and the flexible beam are derived, respectively, and then by introducing the Lagrange-multipliers,the rigid-liquid-flexible coupling equations can be combined with acceleration constraint equations. Finally, the mix differential-algebraic equations are solved to investigate the rigid-liquid-flexible coupling dynamic performance of the system.

Translation of English Language into Urdu Language Using LSTM Model

English to Urdu machine translation is still in its beginning and lacks simple translation methods to provide motivating and adequate English to Urdu translation.In order tomake knowledge available to the masses,there should be mechanisms and tools in place to make things understandable by translating from source language to target language in an automated fashion.Machine translation has achieved this goal with encouraging results.When decoding the source text into the target language,the translator checks all the characteristics of the text.To achieve machine translation,rule-based,computational,hybrid and neural machine translation approaches have been proposed to automate the work.In this research work,a neural machine translation approach is employed to translate English text into Urdu.Long Short Term Short Model(LSTM)Encoder Decoder is used to translate English to Urdu.The various steps required to perform translation tasks include preprocessing,tokenization,grammar and sentence structure analysis,word embeddings,training data preparation,encoder-decoder models,and output text generation.The results show that the model used in the research work shows better performance in translation.The results were evaluated using bilingual research metrics and showed that the test and training data yielded the highest score sequences with an effective length of ten(10).

Neural Machine Translation Models with Attention-Based Dropout Layer

In bilingual translation,attention-based Neural Machine Translation(NMT)models are used to achieve synchrony between input and output sequences and the notion of alignment.NMT model has obtained state-of-the-art performance for several language pairs.However,there has been little work exploring useful architectures for Urdu-to-English machine translation.We conducted extensive Urdu-to-English translation experiments using Long short-term memory(LSTM)/Bidirectional recurrent neural networks(Bi-RNN)/Statistical recurrent unit(SRU)/Gated recurrent unit(GRU)/Convolutional neural network(CNN)and Transformer.Experimental results show that Bi-RNN and LSTM with attention mechanism trained iteratively,with a scalable data set,make precise predictions on unseen data.The trained models yielded competitive results by achieving 62.6%and 61%accuracy and 49.67 and 47.14 BLEU scores,respectively.From a qualitative perspective,the translation of the test sets was examined manually,and it was observed that trained models tend to produce repetitive output more frequently.The attention score produced by Bi-RNN and LSTM produced clear alignment,while GRU showed incorrect translation for words,poor alignment and lack of a clear structure.Therefore,we considered refining the attention-based models by defining an additional attention-based dropout layer.Attention dropout fixes alignment errors and minimizes translation errors at the word level.After empirical demonstration and comparison with their counterparts,we found improvement in the quality of the resulting translation system and a decrease in the perplexity and over-translation score.The ability of the proposed model was evaluated using Arabic-English and Persian-English datasets as well.We empirically concluded that adding an attention-based dropout layer helps improve GRU,SRU,and Transformer translation and is considerably more efficient in translation quality and speed.

Decomposition of Molecular Motions into Translational, Rotational, and Intramolecular Parts by a Projection Operator Technique

The motion of the atoms in a molecule may be described as a superposition of translational motion of the molecular center-of-mass,rotational motion about the principal molecular axes,and an intramolecular motion that may be associated with vibrations and librations as well as molecular conformational changes.We have constructed projection operators that use the atomic coordinates and velocities at any two times,t=0 and a later time t,to determine the molecular center-of-mass,rotational,and intramolecular motions in a molecular dynamics simulation.This model-independent technique facilitates characterization of the atomic motions within a system of complex molecules and is important for the interpretation of experiments that rely on time correlation functions of atomic and molecular positions and velocities.The application of the projection operator technique is illustrated for the inelastic neutron scattering functions and for the translational and rotational velocity autocorrelation functions.

Spectral Element Simulation of Rotating Particle in Viscous Flow

Spectral element methods (SEM) are superior to general finite element methods (FEM) in achieving high order accuracy through p-type refinement. Owing to orthogonal polynomials in both expansion and test functions, the discretization errors in SEM could be reduced exponentially to machine zero so that the spectral convergence rate can be achieved. Inherited the advantage of FEM, SEM can enhance resolution via both h-type and p-type mesh-refinement. A penalty method was utilized to compute force fields in particulate flows involving freely moving rigid particles. Results were analyzed and comparisons were made;therefore, this penalty-implemented SEM was proven to be a viable method for two-phase flow problems.

Multi-Barycenter Mechanics, N-Body Problem and Rotation of Galaxies and Stars

In the present paper, the establishment of a systematic multi-barycenter mechanics is based on the multi-particle mechanics. The new theory perfects the basic theoretical system of classical mechanics, which finds the law of mutual interaction between particle groups, reveals the limitations of Newton’s third law, discovers the principle of the intrinsic relationship between gravity and tidal force, reasonably interprets the origin and change laws for the rotation angular momentum of galaxies and stars and so on. By applying new theory, the multi-body problem can be transformed into a special two-body problem and for which an approximate solution method is proposed, the motion law of each particle can be roughly obtained.

Effect of Gaussian Noise Amplitude on Translation Error Estimated Using Double-Wayland Algorithm

The Wayland algorithm has been improved in order to evaluate the degree of visible determinism for dynamical systems that generate time series. The objective of this study is to show that the Double-Wayland algorithm can distinguish between time series generated by a deterministic process and those generated by a stochastic process. The authors conducted numerical analysis of the van der Pol equation and a stochastic differential equation as a deterministic process and a Ganssian stochastic process, respectively. In case of large S/N ratios, the noise term did not affect the translation error derived from time series data, but affected that from the temporal differences of time series. In case of larger noise amplitudes, the translation error from the differences was calculated to be approximately 1 using the Double-Wayland algorithm, and it did not vary in magnitude. Furthermore, the translation error derived from the differenced sequences was considered stable against noise. This novel algorithm was applied to the detection of anomalous signals in some fields of engineering, such as the analysis of railway systems and bio-signals.

Simulation of the Scattered EM Field of a Rotating Conducting Cylinder Using Static Data

The effect of the rotation of a very good conducting cylinder on the backscattered field will be investigated where the incident wave is considered as a plane wave in both polarizations （E-wave and H-wave）. Previous work has explained that rotation or vibration of the object may induce phase changes of the scattered signal. Modulation during rotation or vibration is referred to as micro-Doppler effect. Also, the effect of the rotation of a conducting cylinder was investigated by many researchers in the past using the Galilean transformation. These analyses conclude that the effect of rotation does not exist in the case of a perfectly conducting cylinder in both polarizations. In this work, the Franklin transformation is used instead of the Galilean transformation to analyze scattering of both types of electromagnetic waves （H-wave and E-wave） by rotating a very good circular conducting cylinder. This work shows that the scattered field is affected by the rotation of a very good conducting cylinder, especially in the case of H-wave （TE-mode）. Finally, the model that will be presented is used to simulate rotation using static backscattered field data of an arbitrary object.

考虑轴力与底板约束的埋入式钢柱脚刚度模型

为准确预测埋入式(特别是浅埋)钢柱脚节点的初始转动刚度,将柱脚的埋入段简化为地基梁,基于初参数法完善考虑轴力影响的Winkler地基上的Timoshenko梁理论,提出受锚栓和混凝土约束的柱脚底板转动刚度的计算方法,进而建立可以综合反映柱脚埋深、埋入段剪切变形、钢柱轴力、底板约束影响的埋入式钢柱脚转动刚度模型。基于已验证的有限元模型进行参数分析,研究埋深比、轴力和锚栓布置对柱脚转动刚度的影响。与有限元结果的对比表明,提出的刚度模型较过往文献中理论模型具有更高的精度和更好的适用性,尤其是对于埋深比为0.5~1.5的浅埋柱脚节点。理论与有限元结果表明:埋深比较小时,柱脚转动刚度随埋深比的增加快速增大,而埋深比增加到一定程度后,其对转动刚度几乎无影响;柱脚转动刚度随钢柱轴压力增加呈增大的趋势;对于浅埋柱脚节点,底板约束对其转动刚度的影响较大,而随着埋深的增大,其影响逐渐减小;底板转动约束对埋深比小于1.5的节点刚度具有显著影响,当埋深比增大至2.5,其影响可以忽略。

基于三维空间旋转平移的自适应知识表示方法

现有知识图谱表示学习研究中普遍存在忽视特定关系的语义空间、难以建模非单射复杂关系或多种关系模式等问题,尤其是在不可交换的组合以及子关系两种关系模式上表现不佳。针对该问题,在对实体自适应投影的基础上,利用罗德里格斯旋转公式将旋转操作从二维空间拓展到三维空间并进行平移优化,提出一种新的具有强表征能力的模型ATR3DKRL。通过理论推导可以证明该模型能够建模非单射复杂关系以及多种关系模式。在多个通用数据集上的实验结果表明,该模型可以有效提高链接预测精度,在数据集DB100K与FB15K-237中四个指标上领先现有基线模型,其中在DB100K上评价指标MRR和H@1相较于基线模型RotatE分别大幅提高了3.3%以及6.5%。