Dimension Expansion Research Articles

Dimension changes induced by phase transformation behaviors in Ni-Mn-Cu alloys

The phase transformation behaviors, microstructural evolutions and dimension changes of Ni50-xCuxMn50 (x=8, 10, 12) (at%) were investigated. The results show that the phase transformation sequence of Ni50-xCuxMn50 alloys obtained by quenching from 900°C during heating and cooling is: γ(fcc) → non-martensite L10 phase→14M martensite↔B2↔γ(fcc). As these alloys are annealed under a variety of temperatures between 500°C and 900°C, different microstructural evolutions occur. The interesting changes that occurred during the heating and cooling of the above phase transformation are observed in Ni50-xCuxMn50 alloys. Due to the transformations of non-martensite L10 phase→14M martensite→B2, two consecutive dimension expansions are observed during heating for the alloys quenched from 900°C. The largest dimension expansion can reach to 2.2% in Ni40Cu10Mn50 alloy. The reversible transformation behaviors of 14M martensite↔B2 and B2↔γ result in the reversible dimension changes. During cycling or as the alloys quench from 700°C, the irreversible phase transformation behaviors and the corresponding dimension changes gradually recede and even disappear.

Modeling nonstationarity in space and time.

We propose to model a spatio-temporal random field that has nonstationary covariance structure in both space and time domains by applying the concept of the dimension expansion method in Bornn et al. (2012). Simulations are conducted for both separable and nonseparable space-time covariance models, and the model is also illustrated with a streamflow dataset. Both simulation and data analyses show that modeling nonstationarity in both space and time can improve the predictive performance over stationary covariance models or models that are nonstationary in space but stationary in time.

Indoor Localization Using Semi-Supervised Manifold Alignment with Dimension Expansion

Location estimation plays a crucial role in Location-Based Services (LBSs) with satisfactory user experience. The Wireless Local Area Network (WLAN) localization approach is preferred as a cost-efficient solution to indoor localization on account of the widely-deployed WLAN infrastructures. In this paper, we propose a new WLAN Received Signal Strength (RSS)-based indoor localization approach using the semi-supervised manifold alignment with dimension expansion. In concrete terms, we first construct an innovative objective function based on the augmented physical coordinates and the corresponding WLAN RSS measurements. Second, the closed-form solution to the objective function is derived out according to the Lagrange multiplier equation, which results in the manifold in physical coordinate space. Third, the target location is estimated by matching the transformed newly-collected RSS against the manifold. The localization performance with noise perturbation is analyzed upon the constructed objective function, and meanwhile, the closed-form solution to the objective function with respect to multiple types of measurements is also derived out for the sake of leveraging all of the potential measurements for indoor localization. The extensive testing results show that the proposed approach performs well in localization accuracy even at low calibration load, and its performance can be further improved by using multiple types of measurements for localization.

Performance improvement for GPS single frequency kinematic relative positioning under poor satellite visibility.

Reliable ambiguity resolution in difficult environments such as during setting/rising events of satellites or during limited satellite visibility is a significant challenge for GPS single frequency kinematic relative positioning. Here, a recursive estimation method combining both code and carrier phase measurements was developed that can tolerate recurrent satellite setting/rising and accelerate initialization in motion. We propose an ambiguity dimension expansion method by utilizing the partial ambiguity relevance of previous and current observations. In essence, this method attempts to integrate all useful information into the recursive estimation equation and performs a better least squares adjustment. Using this method, the success rate of the extended ambiguity estimation is independent of the satellite setting and shows robust performance despite poor satellite visibility. Our model allows integration of other useful information into the recursive process. Actual experiments in urban environments demonstrate that the proposed algorithm can improve the reliability and availability of relative positioning.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure.

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods.

Cost-effective utilization of mineral-based raw materials for preparation of porous mullite ceramic membranes via in-situ reaction method

Porous mullite ceramic membranes were prepared via in-situ synthesis method using abundant natural minerals including coarse bauxite and fine kaolin powders. Thermal sintering behavior of the green sample shows that a unique dimension expansion appears during the sintering process due to the anisotropic growth of mullite crystals. The XRD analysis suggests the ceramic membrane is mainly composed of mullite phase when sintering above 1450°C. The SEM images confirm that with an increase in sintering temperature, mullitization reaction firstly occurs in kaolin agglomerations, and then bauxite-derived alumina reacts with silica-containing phase by a solution-precipitation mechanism to form an interlocked framework of elongated secondary mullite. Both maximum and average pore sizes increase with increasing sintering temperature. The growth of mullite whiskers has a positive impact on the improvement of porosity and mechanical strength of ceramic membranes. Even after sintering at 1500°C, the sample shows the highest open porosity of 31.6% and good biaxial flexural strength of 100.2MPa.

Transient solid–fluid interactions in rat brain tissue under combined translational shear and fixed compression

An external mechanical insult to the brain may create internal deformation waves, which have shear and longitudinal components that induce combined shear and compression of the brain tissue. To isolate such interactions and to investigate the role of the extracellular fluid (ECF) in the transient mechanical response, translational shear stretch up to 1.25 under either 0 or 33% fixed normal compression is applied without preconditioning to heterogeneous sagittal slices which are nearly the full length of the rat brain cerebrum.The normal stress contribution is estimated by separate unconfined compression stress–stretch curves at 0.0667/s and 1/s engineering strain rates to 33% strain. Unconfined compression deformation causes lateral dimension expansion less than that predicted for an incompressible material under large deformation and often a visible loss of internal fluid from the specimen so that the bulk brain tissue is not incompressible in vitro, as sometimes assumed for mathematical modeling.The response to both slow 0.001/s and moderate 1/s shear translational stretch rates is deformation rate dependent and hardening under no compression but under 33% compression is nearly linear perhaps because of increased solid–solid friction. Both shear and normal stress relaxation are faster after the fast rate deformation possibly because higher deformation rates produce higher ECF hydrostatic pressure that primarily drives stress relaxation.The experimental results on ECF behavior guide the form of our nonlinear viscoelastic mathematical model. Our data are closely fit by non-equilibrium evolution equations that involve at most three specimen-specific empirical parameters and that are based on the idea that stretch of axons and glial processes resists load-induced ECF pressure.

EELS modelling of graphitisation

The impact of graphitisation-type processes on the carbon K-edge ELNES is explored for model systems using the CASTEP density functional theory code. For c lattice direction expansion, contraction of spectral peaks occurs between 20 and 27 eV above the edge onset, for a/b lattice dimension expansion spectral peaks are heavily compressed in terms of energy separation and are shifted towards the edge-onset, consistent with a 1/a2 relationship. For a nanotube model system, it is shown that for higher curvature, an additional feature was observed in the spectrum ~5 eV, arguably consistent with 'fullerene'-type character.

Exact Linearization Algorithm of Tight Coupling Nonlinear System Based on Differential Manifold

Dealt with the short precision the traditional Taylor series expansion induced and shortage that the system mechanics is hard to match with the exact linearization conditions, a novel exact linearization algorithm of tight coupling nonlinear system based on differential manifold to the missile attitude control system is proposed. A dimension expansion method is proposed, the method solves the problem that the input and output dimensions can not meet the exact linearization conditions; the algorithm application range is widened. Using the principle of the differential manifold, the missile velocity and height information are selected as the measure output, the exact linearization of the missile attitude system is derived based on the diffeomorphism transformations. The simulations are performed on the missile attitude control system. Simulation results show that the effectiveness of the algorithm proposed.

Conformal blocks in the large D limit

We derive conformal blocks in an inverse spacetime dimension expansion. In this large D limit, the blocks are naturally written in terms of a new combination of conformal cross-ratios. We comment on the implications for the conformal bootstrap at large D.

A Direct Method for Searching Power System Second Order Resonance Point

The dynamic characteristics of the power system will be a sharp deterioration near the second order resonance point. In-depth study of the Power system dynamic characteristics near the second order resonance point, and then how to cause the dynamic characteristics of the system worse at the second order resonance point near the stable boundary, need to quickly search system of second order resonance point. Based on the principle of minimal expansion system method, this paper presents the direct method for search the second order resonance point in power system. For the N dimensions differential dynamic system was established in the 4N+4 dimension expansion equations. The power system second order resonance point search is changed into expanding equation fixed point solution. Significantly reduce computational load, improve the search accuracy for solving second order resonance point calculation. For in-depth study of power system dynamic characteristics near the second order resonance point have a certain value.

Dimension expansion and customized spring potentials for sensor localization

The spring model algorithm is an important distributed algorithm for solving wireless sensor network (WSN) localization problems. This article proposes several improvements on the spring model algorithm for solving WSN localization problems with anchors. First, the two-dimensional (2D) localization problem is solved in a three-dimensional (3D) space. This “dimension expansion” technique can effectively prevent the spring model algorithm from falling into local minima, which is verified both theoretically and empirically. Second, the Hooke spring force, or quadratic potential function, is generalized into L p potential functions. The optimality of different values of p is considered under different noise environments. Third, a customized spring force function, which has larger strength when the estimated distance between two sensors is close to the true length of the spring, is proposed to increase the speed of convergence. These techniques can significantly improve the robustness and efficiency of the spring model algorithm, as demonstrated by multiple simulations. They are particularly effective in a scenario with anchor points of longer broadcasting radius than other sensors.

Modeling Nonstationary Processes Through Dimension Expansion

In this article, we propose a novel approach to modeling nonstationary spatial fields. The proposed method works by expanding the geographic plane over which these processes evolve into higher-dimensional spaces, transforming and clarifying complex patterns in the physical plane. By combining aspects of multidimensional scaling, group lasso, and latent variable models, a dimensionally sparse projection is found in which the originally nonstationary field exhibits stationarity. Following a comparison with existing methods in a simulated environment, dimension expansion is studied on a classic test-bed dataset historically used to study nonstationary models. Following this, we explore the use of dimension expansion in modeling air pollution in the United Kingdom, a process known to be strongly influenced by rural/urban effects, amongst others, which gives rise to a nonstationary field.

From Simple to Complex: Topological Evolution and Luminescence Variation in a Copper(I) Pyridylpyrazolate System Tuned via Second Ligating Spacers

By systematically varying the geometric length and electronic properties of the second ligating ligands of halogen (Cl(-), Br(-), and I(-)) and pseudohalogen (CN(-), SCN(-), and N(3)(-)) anions, we synthesized 11 isomeric/isostructural copper(I) complexes: [Cu(2)(L3-3)I](n) (1), [Cu(2)(L4-4)Br](n) (2-Br), [Cu(2)(L4-4)Cl](n) (2-Cl), [Cu(2)(L3-4)(CN)](n) (3), [Cu(2)(L3-3)(CN)](n) (4), [Cu(3)(L4-4)(CN)(2)](n) (5), {[Cu(2)(L4-4)Br](2)·CuBr}(n) (6-Br), {[Cu(2)(L4-4)Cl](2)·CuCl}(n) (6-Cl), [Cu(2)(L4-4)(SCN)](n) (7α-SCN), [Cu(2)(L4-4)(SCN)](n) (7β-SCN), and [Cu(2)(L4-4)(N(3))](n) (7α-N(3)). These structures are based on a series of isomeric pyridylpyrazole ligands, namely, 3,5-bis(3-pyridyl)-1H-pyrazole (HL3-3), 3-(3-pyridyl)-5-(4-pyridyl)-1H-pyrazole (HL3-4), and 3,5-bis(4-pyridyl)-1H-pyrazole (HL4-4), and their structural features range from 1-D (1), 2-D (2), and 3-D noninterpenetration (3), to 3-D 2-fold interpenetration (4 and 5), to 3-D self-catenation (6 and 7), exhibiting a trend from simple to complex with dimension expansion and an interpenetrating degree increase. The five most complex structures (6 and 7) with self-catenated networks are based on 2-fold interpenetrated networks linked via appropriate second ligating spacers (Cl(-), Br(-), SCN(-), and N(3)(-)), representing a strategy to construct self-catenated coordination polymers through cross-linking interpenetrated frameworks. Moreover, these complexes exhibit strong photoluminescence, which is mainly ascribed to Cu(I)-related charge transfers (MLCT, MC, and MMLCT) regulated by the electronic properties of halogen or pseudohalogen. The topological evolution and luminescence variation presented in this work open an avenue to understanding the luminescence origin and the structure-property relationship of luminescent coordination polymers.

Towards dimension expanders over finite fields

In this paper we study the problem of explicitly constructing a dimension expander raised by [3]: Let $\mathbb{F}^n $ be the n dimensional linear space over the field $\mathbb{F}$. Find a small (ideally constant) set of linear transformations from $\mathbb{F}^n $ to itself {A i }i∈I such that for every linear subspace V ⊂ $\mathbb{F}^n $ of dimension dim(V) 0 is some constant. In other words, the dimension of the subspace spanned by {A i (V)}i∈I should be at least (1+α)·dim(V). For fields of characteristic zero Lubotzky and Zelmanov [10] completely solved the problem by exhibiting a set of matrices, of size independent of n, having the dimension expansion property. In this paper we consider the finite field version of the problem and obtain the following results. We give a constant number of matrices that expand the dimension of every subspace of dimension d<n/2 by a factor of (1+1/logn). We give a set of O 0. Our constructions are algebraic in nature and rely on expanding Cayley graphs for the group ℤ=ℤn and small-diameter Cayley graphs for the group SL2(p).

Slave System Dimension Expansion Approach for Robust Synchronization of Chaotic Systems with Unknown Phase Difference

A technique which increased the dimension of slave system is adopted for robust synchronization of chaotic systems with unknown phase difference. The phase difference plays a great role in variation of dynamic behavior of the coupled systems. The phase difference of the sinusoidal forcing term is always assumed to be known in the majority of the existing literature. However, unknown parameter error value has always existed in real problems. This method uses the properties of the triangular function and increases the number of dimensions in the slave system to match the phase of forcing term in the master system. Numerical simulations show that the flexible control variable we first investigated is very important. We expect our results to be of some broader applicabilities.

High-rate groupwise STBC using low-complexity SIC based receiver

In this paper, using diagonal signal repetition with Alamouti code employed as building blocks, we propose a high-rate groupwise space-time block code (GSTBC) which can be effectively decoded by a low-complexity successive interference cancellation (SIC) based receiver. The proposed GSTBC and SIC based receiver are jointly designed such that the diversity repetition in a GSTBC can induce the dimension expansion to suppress interfering signals as well as to obtain diversity gain. Our proposed scheme can be easily applied to the case of large number of antennas while keeping a reasonably low complexity at the receiver. It is found that the required minimum number of receive antennas is only two for the SIC based receiver to avoid the error floor in performance. The simulation results show that the proposed GSTBC with SIC based receiver obtains a near maximum likelihood (ML) performance while having a significant performance gain over other codes equipped with linear decoders.

Coronary occlusion by balloon to instruct swine acute myocardial infarction and following ventricualr remodeling model

Objective To investigate the effects of established swine acute myocardial infarction and following ventricular remodeling model by occluding Coronary with balloon. Methods Ten healthy Domestic swine are enrolled. Each swine's left anterior descending coronary artery was occluded for three hours by dilated balloon, and then reperfusion was performed. During the whole course of operation, the electro-cardiogram was monitored. B-ultrasound and single -photon emission computed tomography examination (SPECT) were performed to detect left ventricular end diastolic dimension, left ventricular tip wall thickness, left ventricular end diastolic volume and left ventricula ejection fraction before operation and one week, three month, six month after acute myocardial infarction. Results Five swine died during the period of opera-tion for lack of experience, the remains survived. Electrocardiogram revealed significant ST-elevation and Q-wave formation. B-untrasound and SPECT witnessed deteriorating left ventricular end diastolic dimension expansion, left ventricular tip wall thickness thinning, left ventricular end diastolic volume expansion and left ventricular ejection fraction depression. Conclusions Coronary artery occlusion by balloon can successfully establish acute myocardial infarction and following left ventricular remodeling models. Key words: Angioplasty, transluminal, pereutaneous coronary ; Disease models, animal ; Myocardial infarction ; Swine

Joint Design of Groupwise STBC and SIC Based Receiver

In this letter, we propose a simple groupwise space-time block code (GSTBC) which can be easily applied to a large number of transmit antennas and be effectively decoded by a low complexity successive interference cancellation (SIC) based receiver. The proposed GSTBC and SIC based receiver are jointly designed and the diversity repetition in GSTBC is used to induce the dimension expansion that can be exploited by the SIC based receiver to suppress interfering signals as well as to obtain diversity gain. Our proposed scheme provides a near maximum likelihood (ML) performance while keeping a reasonably low complexity at the receiver.

Speech Analysis in a Model of the Central Auditory System

Recently, there is a significant increase in research interest in the area of biologically inspired systems, which, in the context of speech communications, attempt to learn from human's auditory perception and cognition capabilities so as to derive the knowledge and benefits currently unavailable in practice. One particular pursuit is to understand why the human auditory system generally performs with much more robustness than an engineering system, say a state-of-the-art automatic speech recognizer. In this study, we adopt a computational model of the mammalian central auditory system and develop a methodology to analyze and interpret its behavior for an enhanced understanding of its end product, which is a data-redundant, dimension-expanded representation of neural firing rates in the primary auditory cortex (A1). Our first approach is to reinterpret the well-known Mel-frequency cepstral coefficients (MFCCs) in the context of the auditory model. We then present a framework for interpreting the cortical response as a place-coding of speech information, and identify some key advantages of the model's dimension expansion. The framework consists of a model of ldquosourcerdquo-invariance that predicts how speech information is encoded in a class-dependent manner, and a model of ldquoenvironmentrdquo-invariance that predicts the noise-robustness of class-dependent signal-respondent neurons. The validity of these ideas are experimentally assessed under existing recognition framework by selecting features that demonstrate their effects and applying them in a conventional phoneme classification task. The results are quantitatively and qualitatively discussed, and our insights inspire future research on category-dependent features and speech classification using the auditory model.