Less Amount Of Computation Research Articles

A Certificateless Signcryption Mechanism Based on Blockchain for Edge Computing

The emergence of edge computing makes it possible to realize new technologies such as virtual reality and augmented reality. However, a large number of devices and more messages at the edge bring more security problems. Therefore, it is an important research topic to provide users with faster network services while ensuring confidentiality and authentication of data transmission. Because signcryption can encrypt and sign messages at the same time, it has become a new cryptographic primitive. In the meantime, certificateless signcryption guarantees data confidentiality and authentication and addresses traditional single point failure problems based on the trust center and the problem of relying on a trusted third party. Therefore, certificateless signcryption has attracted great attention from academia and industry. But certificateless signcryption also faces two types of attacks. In order to more effectively resist these two types of attacks, we propose a certificateless signcryption mechanism based on blockchain. This mechanism can make good use of the nontamperable feature of blockchain, prevent illegal users from substituting public key of the user, and guarantee signature non-repudiation. And our scheme is investigated in a comparative study with eight schemes. Comparative analysis outcomes demonstrate our scheme has achieved better results in efficiency and security. The process of signcryption and unsigncryption consumes the least amount of computation, which is very suitable for the edge computing environment.

Wiener filter and wavelet transform of noisy image analysis based on MATLAB

In recent years, how to filter noise more effectively has been a topic of great interest, and improvements have been made based on various filtering algorithms in the hope of obtaining the most optimal filtering effect with the least amount of computation. However, there is a considerable research gap in how to achieve this goal. This article is based on this research. The motif of this study paper is the analysis of images containing Gaussian noise based on Wiener filter and wavelet transform, and an attempt to improve the filtering algorithm. The SNR and PSNR obtained by applying Wiener filtering analysis are 46.7864 and 76.0247, respectively, and the SNR and PSNR results of wavelet transform are 14.0851 and 49.7426. this article implements Wiener filtering based on Wiener method, and the results are almost consistent with the function of invoked system. It is found that the Wiener filter is more suitable for handling processing Gaussian noise. The SNR and PSNR values of both sets of experimental Wiener filter are larger than those of wavelet transform, then it indicates that Wiener filter is more beneficial to suppress Gaussian noise under the same condition.

Application of Bispectrum Dimensionality Reduction Method in Ultrasonic Echo Signal Processing

Processing ultrasonic echo signals to obtain high-precision residual thickness information of the pipeline wall is the key to nondestructive testing of corrosion of a long-distance pipeline. The traditional power spectrum estimation method assumes that an analyzed echo signal is Gaussian, and the useful information is insufficiently extracted, which leads to errors in the processing results. In this paper, to solve this problem, the bispectrum, which requires the least amount of computation in higher-order spectral estimation, is proposed to process an echo signal with a non-minimum phase and non-Gaussian characteristics. The bispectrum is projected onto a one-dimensional frequency space using the dimensionality reduction method, and one-dimensional diagonal slices of the bispectrum are extracted to analyze the characteristics of the echo signal, which significantly improves the intuitiveness of data processing. The experimental results show that the bispectrum dimensionality reduction method has high accuracy in processing ultrasonic echo signals, and the relative error of the residua wall thickness is below 2%. A C-scan image displaying the shape, size, depth, and other characteristics of pipeline corrosion obtained by the proposed method is much better than that using the traditional power spectrum estimation method. Therefore, the proposed method is suitable for nondestructive testing of corrosion of long-distance pipelines.

Dual Attention with the Self-Attention Alignment for Efficient Video Super-resolution

By selectively enhancing the features extracted from convolution networks, the attention mechanism has shown its effectiveness for low-level visual tasks, especially for image super-resolution (SR). However, due to the spatiotemporal continuity of video sequences, simply applying image attention to a video does not seem to obtain good SR results. At present, there is still a lack of suitable attention structure to achieve efficient video SR. In this work, building upon the dual attention, i.e., position attention and channel attention, we proposed deep dual attention, underpinned by self-attention alignment (DASAA), for video SR. Specifically, we start by constructing a dual attention module (DAM) to strengthen the acquired spatiotemporal features and adopt a self-attention structure with the morphological mask to achieve attention alignment. Then, on top of the attention features, we utilize the up-sampling operation to reconstruct the super-resolved video images and introduce the LSTM (long short-time memory) network to guarantee the coherent consistency of the generated video frames both temporally and spatially. Experimental results and comparisons on the actual Youku-VESR dataset and the typical benchmark dataset-Vimeo-90 k demonstrate that our proposed approach achieves the best video SR effect while taking the least amount of computation. Specifically, in the Youku-VESR dataset, our proposed approach achieves a test PSNR of 35.290db and a SSIM of 0.939, respectively. In the Vimeo-90 k dataset, the PSNR/SSIM indexes of our approach are 32.878db and 0.774. Moreover, the FLOPS (float-point operations per second) of our approach is as low as 6.39G. The proposed DASAA method surpasses all video SR algorithms in the comparison. It is also revealed that there is no linear relationship between positional attention and channel attention. It suggests that our DASAA with LSTM coherent consistency architecture may have great potential for many low-level vision video applications.

Light weight model for intra mode selection in HEVC

The High Efficiency Video Coding (HEVC) efficiently reduces the size of the multimedia contents, but at the cost of high computation complexity. In order to make it work for the real time applications, a study is conducted in this article to speed up the intra mode decision of HEVC. Firstly, a novel early termination mechanism is proposed that is based on the duration problem. This model is designed such that it requires the least amount of computation and dynamically adjusts to the current best option. Secondly, a dynamic threshold is proposed that outperformed majority of the thresholds in-terms of computation and adjustment with-respect-to the current best option. Experimental results proved that when the proposed methods are incorporated in HEVC, they reduced the encoding time by 34.1% on average, with a minor bit-rate (BD-BR) increase of 1.4% on average.

Ladder network parameters identification of an isolated winding by combining the intelligent optimisation algorithm and GNIA

The ladder network parameter identification for transformer winding is crucial for the interpretation of the frequency response function data. The traditional identification method, mainly based on intelligent optimisation algorithm, is generally very time-consuming due to a large amount of computation. This study proposes to combine the intelligent algorithm and Gauss-Newton iteration algorithm (GNIA) to improve the optimisation efficiency notably with a sharply dropped calculation workload. These two methods are well-complementary since the intelligent algorithm holds excellent global search ability while the search of the GNIA is directional and quantitative. This study solves three key problems for the combined algorithms. The first problem is the calculation of the least-square correction solution to the network parameters in the iteration algorithm. The treatment of the ill-conditioned Jacobian matrix in the iteration algorithm is the second challenge. Another issue is the determination of the network parameter with zero sensitivity. The identification results on an isolated winding show that the combined algorithms can obtain a more precise solution with far less amount of computation.

A Novel Fifth-Degree Cubature Kalman Filter Approaching the Lower Bound on the Number of Cubature Points

In this paper, a novel fifth-degree cubature Kalman filter, which approaches the lower bound on the number of cubature points, is proposed to reduce the computational complexity while maintaining the fifth-degree filtering accuracy. The Gaussian weighted integral of a nonlinear function is approximated using a numerical cubature rule, whose number of cubature points needed is only one more than the theoretical lower bound, and the filter is deduced under the Bayesian filtering framework by this rule. Furthermore, a square-root version of the proposed fifth-degree cubature Kalman filter is given, and it acquires higher computational efficiency and ensures the numerical stability of the filter. Three numerical simulations are taken, and the results show that the proposed filters maintain the fifth-degree filtering accuracy, while needing the least amount of computation and achieving the best real-time performance.

A Fast Algorithm for Analysis of Molecular Communication in Artificial Synapse.

In this paper, we analyze molecular communications (MCs) in a proposed artificial synapse (AS), whose main difference from biological synapses (BSs) is that it is closed, i.e., transmitter molecules cannot diffuse out from AS. Such a setup has both advantages and disadvantages. Besides higher structural stability, being closed, AS never runs out of transmitters. Thus, MC in AS is disconnected from outer environment, which is very desirable for possible intra-body applications. On the other hand, clearance of transmitters from AS has to be achieved by transporter molecules on the presynaptic membrane of AS. Except from these differences, rest of AS content is taken to be similar to that of a glutamatergic BS. Furthermore, in place of commonly used Monte Carlo-based random walk experiments, we derive a deterministic algorithm that attacks for expected values of desired parameters such as evolution of receptor states. To assess validity of our algorithm, we compare its results with average results of an ensemble of Monte Carlo experiments, which shows near exact match. Moreover, our approach requires significantly less amount of computation compared with Monte Carlo approach, making it useful for parameter space exploration necessary for optimization in design of possible MC devices, including but not limited to AS. Results of our algorithm are presented in case of single quantal release only, and they support that MC in closed AS with elevated uptake has similar properties to that in BS. In particular, similar to glutamatergic BSs, the quantal size and the density of receptors are found to be main sources of synaptic plasticity. On the other hand, the proposed model of AS is found to have slower decaying transients of receptor states than BSs, especially desensitized ones, which is due to prolonged clearance of transmitters from AS.

TRANSIENT SOLUTION FOR LOSSY TRANSMISSION LINE BY MEANS OF ORTHOGONAL PROJECTION METHOD

A novel electromagnetic transient analysis technique by means of the orthogonal projection method for lossy transmission line is proposed. By employing the proposed method, the traveling waves propagating from one terminal to another can be quickly obtained with less amount of computation at considerably large steps. First of all, the difierential function to variable time can be approximated to be the convolution with a flxed vector relates to a certain set of orthogonal basis, e.g., Daubechies' basis. The partial difierential telegraph equations related to both variable time t and distance x are then transformed to be difierential equations only related to x. The solution of such equations can be obtained accordingly. The discrete coe-cients of propagation function for lossy line are obtained as well, by which the propagating traveling waves can be calculated precisely at considerably large sampling periods with less amount of computation.

Factors affecting the production of verb inflections in Greek aphasia

Verb inflection errors are commonly observed in the speech of aphasic individuals, but the errors are selective and not evenly distributed across different functional categories (e.g., Friedman & Grodzinsky, 1997). An investigation of verb inflection errors in seven Greek aphasic individuals showed more errors in aspect and tense than in agreement (Varlokosta et al., 2006). Moreover, the productions revealed a large proportion of repetition and lexical errors in addition to pure inflectional errors. The presence of different types of errors raises the question of the nature of the underlying deficit in the production of the functional categories. An erroneous production of a verb may involve an error in morphological suffixation, preserving the verb stem; an error in lexical selection, preserving the inflection; and a mixed error, involving both the morphological suffixation and the verb stem. Because all verbs in Greek are affixed, a bare stem is not a possibility as it would result in an illegal word. According to Levelt’s (1999) model of word production, morphological suffixation errors indicate a breakdown at the level of diacritical (lexical–semantic) features, whereas lexical and mixed lexical–morphological errors reflect additional difficulty in lexical selection. Repetition errors involve the least amount of computation and thus may indicate a difficulty in affixation during phonological encoding. To address the above question, we re-examined the productions of the Greek speaking aphasic individuals studied by Varlokosta et al. (2006) by re-classifying the errors as morphological, lexical, or mixed. A second aim was to examine the contributions of severity of spoken language impairment, verb familiarity, regularity, and presence of consonant cluster to the performance per functional category.

Image Magnification by a Compact Method with Preservation of Preferential Components

Bicubic interpolation is one of the standard approaches for image magnification since it can be easily computed and does not require a priori knowledge nor a complicated model. In spite of such convenience, the images enlarged by bicubic interpolation are blurry, in particular for large magnification factors. This may be explained by four constraints of bicubic interpolation. Hence, by relaxing or replacing the constraints, we propose a new magnification method, which performs better than bicubic interpolation, but retains its compactness. One of the constraints is about criterion, which we replace by a criterion requiring that all pixel values are reproduced and preferential components in input images are perfectly reconstructed. We show that, by choosing the low frequency components or edge enhancement components in the DCT basis as the preferential components, the proposed method performs better than bicubic interpolation, with the same, or even less amount of computation.

On Approximating the Individual Risk Model

Error bounds are developed for Kornya-Presman–type approximations to the individual risk model. In particular, error bounds are given for the compound Poisson approximation, with the Poisson parameter equal to the expected number of claims. The approximations considered are a modification by Hipp of an approximation originally developed by Kornya, as well as Kornya’s original approximation. The error bounds are similar in concept to Hipp’s original error bounds using concentration–functions, as refined by Čekanavičius, Roos, and others. Computation of the bounds, however, is considerably simplified. In particular, concentration function type bounds called width-norm bounds are calculated directly from the values of the approximation, avoiding completely the need for calculating a special auxiliary compound Poisson distribution. Two examples are given. Depending on the portfolio parameters, the width-norm error bounds may or may not be sharper than the Hipp-Roos error bounds. In any event, it is recommended that the simpler widthnorm calculation, possibly together with an increase in the order of the approximation, be considered in practical applications if the goal is to achieve a specified accuracy with the least amount of computation. For large portfolios, where the maximum claim on any one policy is relatively small compared to the expected aggregate claims, the width-norm error bounds compare quite favorably with error bounds developed by De Pril and by Dhaene.

Finite element analysis of contact–impact between a shell of revolution and a rigid wall

AbstractIn this paper an attempt is made to use a shell theory that includes transverse normal stresses to study the contact–impact behaviour involving thick shells. The problem is solved using the finite element method. The contact criterion is imposed by means of displacement and force constraints. The Lagrangian multipliers technique is used to impose these constraints. The case of a spherical shell impacting a rigid wall with a constant velocity is considered for the analysis. It is shown that the method produces accurate results with less amount of computation than the usual three‐dimensional analyses. The effects of the thickness of shell, velocity of impact and modulus of the material are studied.

Reconstruction of 3-D binary tree-like structures from three mutually orthogonal projections

A method is developed to generate the 3D binary representation for a tree-like object from three mutually orthogonal projections. This is done by first backprojecting the binarized images from three directions and then iteratively removing artifacts in the backprojection. Three different algorithms have been developed: the Lagrange multiplier algorithm, the conjugate gradient algorithm, and the minimum-voxel representation algorithm (MRA). The performance of these algorithms under noise-free conditions is evaluated using mathematically projected images of a 3D tree structure. While all three algorithms are capable of producing a relatively accurate reconstruction, the MRA is superior not only because it requires the least amount of computation but also because it uses binary instead of gray-scale information in the input images. Reconstruction of 3D coronary arterial structures using MRA is further verified with X-ray images of a human chest phantom and shows a satisfactory performance. The result of this study should be valuable for 3D imaging of blood vessels. >

A periodically time‐varying digital filter containing a discrete fourier transformer

AbstractSo far, three periodically time‐varying models have been proposed in the research on periodically time‐varying digital filters. They are the coefficients time‐varying model, the output sampling polyphase model, and the input sampling polyphase model. Analyses of these models have also been completed by the authors.This paper proposes new models to solve a problem which the three conventional models cannot solve. It is known that a periodically time‐varying digital filter can be used to implement a spectrum scrambler. However, when these models are to be used to implement a spectrum scrambler, time‐invariant filters in these models are restricted to FIR filters.This paper proposes and analyzes an output sampling polyphase model and an input sampling polyphase model, both of which contain a discrete Fourier transformer. Relationships between the newly proposed models and the conventional coefficients time‐varying model are established.By making use of the newly proposed periodically time‐varying models, we can design a spectrum scrambler employing not only FIR time‐invariant filters but IIR time‐invariant filters as well. Furthermore, compared to the conventional models, the newly proposed periodically time‐varying models are shown to have an advantage of less amount of computation when they are used to implement a spectrum scrambler.

Composite Hydroelectric Energy System State Estimation

The feasibility and performance of a combined eiectrical-mechanical-hydraulic, static-dynamic hierarchical state estimator is investigated. A central tracking electric power system static state estimator co-ordinates ‘local’ voltage and phase information to a series of ‘local’ dynamic hydro turbine state estimators at regular intervals, after each ‘global’ measurement scan. Also present are ‘local’ dynamic hydro canal state estimators. The open channel hydro canal and hydro turbine Kalman filters use a ‘linearized’ approach which involves the least amount of computation yet is stable and capable of tracking changes. The Kalman filter gain matrix of the hydro canal state estimator is relatively insensitive to changes in flow conditions and has a sparse band-like structure.

亜音速非定常揚力面理論に現われる核関数の改善された数値計算法

An integral function B(X, r, k) appears in the kernel function for subsonic lifting surface theory. UEDA presented an effcient evaluation method of B. We, however, found that there are some points to be improved. It is seen first that the case "X<0 and k=1" is of fundamental importance. Secondly the least amount of computation should be carried out for a specified accuracy. Some devices for this are presented. Third, the near-field formulationis considerably improved; infinite series expansions are used as restrictedly as possible, and three component blocks are constructed so that they vanish individually for r→∞ and X=0. Fourth, a tentative criterion for the truncation error is introduced in the far-field expression. Eventually an overall computation program of B is presented. It may require the least amount of cornputation in order to attain a specified accuracy. It utilizes the near-field expression provided that the function H is obtainable through a series within a specified number of terms. Some numerical results are quite encouraging.

Direct solutions for Poisson's equation in three dimensions

Two-dimensional Poisson problems are commonly solved by one of three direct methods: cyclic reduction (CR), Fourier analysis (FA), or a combination of FA and CR (FACR). It has been shown that FACR requires the least amount of computation and CR the most. All of these methods employ one-dimensional solvers embedded in the algorithms for solving the two-dimensional problem. These methods can be used to solve three-dimensional systems if the one-dimensional solver is replaced with a two-dimensional solver. In three dimensions FACR and FA require almost the same number of operations if the two-dimensional solver is FACR. Further, the three-dimensional CR using CR to solve the two-dimensional systems requires a much larger number of operations in comparison with any of the other approaches considered. This information is illustrated using a staggered grid with Neumann boundary conditions. The operation counts for this problem are derived so that they are applicable even if the number of mesh points in any direction is small. The FFT algorithm required when using FA is presented. The FA algorithm is simpler to code than FACR. A comparison of run times between CR and FA (using CR to solve the two-dimensional systems) is given for several mesh sizes. The results agree with the operation count comparisons. Some input-output considerations for coding problems which require auxiliary storage are also discussed.