An algorithm for predicting the NMR shielding of protons over substituted benzene rings

In a strong magnetic field, hydrogen nuclei located over an aromatic ring experience a reduced magnetic field as a result of the induced magnetic field associated with circulating pi electrons. We used GIAO-SCF, an ab initio subroutine in Gaussian 94 to calculate isotropic shielding values and to determine the proton nuclear magnetic resonance (NMR) shielding increment for a simple model system: methane held at various positions over a substituted benzene ring. The NMR shielding increments experienced by the proximal protons of methane have been mapped as a function of their position X, Y, and Z relative to the center of aniline and, separately, nitrobenzene. A mathematical function of the same form has been fit to the three-dimensional shielding increment surface at each of five distances from the face of each aromatic ring. In addition, a single mathematical equation has been developed for predicting the shielding caused by either substituted aromatic ring. The chemical shifts predicted by using the results of this equation in conjunction with additive substituent increments are compared to observed values.     

An iterative phase correction program for nuclear magnetic resonance (NMR) spectra

An iterative algorithm is given to correct for the zeroth and first order phase errors in NMR spectroscopy. A FORTRAN computer program is listed and two sample runs exemplified. No a priori knowledge of the existing phase errors is required. The parameters are optimised iteratively under the assumption that when the spectrum is correctly phased the ratio of the area above the spectrum to that below it is a maximum.     

磁共振成像重建的新算法

提出了一种高效的磁共振成像重建算法,将磁共振成像重建看作标准的线性求逆问题,基于变量分离技术重新建立线性求逆问题的目标函数,用交替最小化方法处理新目标函数的优化问题.新目标函数的优化包含两个交替的过程:一个凸的光滑函数的优化和一个凸的非光滑函数的优化.为处理非光滑函数的优化问题,引入投影算法对其求解.实验结果表明了该磁共振成像重建算法的有效性,与同类算法性比,重建的磁共振图像的均方误差(MSE)最小,重建的速度最快.     

核磁共振陀螺仪研究进展

核磁共振陀螺仪(NMRG)是基于量子原理的、目前世界上体积最小的导航级陀螺仪,具有加速度不敏感、抗干扰能力强且没有运动部件等优势,有望在与微机电陀螺仪同等体积、成本下达到光学陀螺仪的精度,受到了国内外广泛关注.介绍了核磁共振陀螺仪基于核磁共振技术的基本工作原理,然后回顾了核磁共振陀螺仪自20世纪60年代起的发展历史,重点分析了21世纪以来国内外研究机构在核磁共振陀螺领域取得的重大研究成果,并对国内外核磁共振陀螺仪的最新研究进展进行了跟踪,美国Northrop Grumman公司已经率先研制出了面向军事领域的微小型导航级核磁共振陀螺仪.最后对核磁共振陀螺仪未来发展的方向进行展望,将进一步向高精度、低成本和小体积方向发展,同时分析了核磁共振陀螺可能应用前景,将广泛应用于民用领域以及军用领域.     

基于深度学习的心脏核磁共振图像自动分割算法

心脏核磁共振成像技术由于其无电离辐射的优点已成为医疗诊断中的主要手段。对左心室、右心室以及左心肌进行准确的分割与识别是心脏手术前的重要一步,手动分割心脏结构耗时且易出错,因此自动分割双心室与心肌至关重要。提出了一种能充分利用心脏图像信息的多尺度特征融合U型神经网络MFF U-Net。首先,选择以U-Net++作为网络基本框架。其次,为了提高特征复用率,解决网络深度增加导致的过拟合问题,在U-Net++的编码部分提出了密集残差模块,使得网络在下采样过程中学习到更多有用特征。此外,在解码部分,为了使网络的分割结果更加符合目标器官之间的物理特征,用多个卷积核来扩大感受野并利用长距离依赖模块共享全局上下文信息,使得网络在编码还原的过程中尽可能地获取到目标器官之间的关系信息,从而使得分割结果更为精准。最后,考虑到双心室与左心肌的连贯性与唯一性,还添加了获取最大连通域与填充细小孔洞的后处理操作。采用的实验数据为ACDC心脏分割挑战数据集,其包含150位志愿者收缩期末期与舒张期末期的短轴心脏磁共振图像。在该数据集的测试集上进行验证,并通过在线提交的方式获取实验结果。实验结果表明,相较于其他算法,所提出的算法能够有效地分割目标器官,特别是舒张期末期的Dice系数分别达到了左心室0.96、右心室0.94和左心肌0.89,收缩期末期的分割精度达到了0.87,0.86和0.89。     

Comparison of reconstruction algorithm for compressive sensing magnetic resonance imaging

Multimedia Tools and Applications - Compressed sensing can reconstruct the undersampled image. The combination of compressed sensing and magnetic resonance imaging is a potential future fast...     

一类有向双环网络的最优单播路由算法

有向双环网络G(N;1,h)(N是节点数,1和h是步长)是重要的互联网络结构。给出了有向双环网络G(N;1,h)的若干性质。作为这些性质的两个应用,给出一类有向双环网络的直径公式,以及这类有向双环网络的单播路由算法,这个算法是简单且最优的。     

Algorithm 34 An algorithm for the automatic integration over a triangle

Numerical integration over an arbitrary triangular domain is considered. An adaptive algorithm with round-off error guard is described. A FORTRAN IV implementation is given and numerical results are reported.     

An optimal control algorithm for nuclear reactor load cycling

An optimal control algorithm for reactor reactivity controls during CANDU4 nuclear station load cycling is presented. The minimized performance index is reactor operating cost during a load cycling interval. The algorithm is developed using Pontryagin's Maximum principle. A novel non-iterative technique for determining the adjoint multiplier initial values in the resulting two point boundary value problem is used. The analysis considers standard fuel, booster fuel, moderator poison and liquid zone controllers as available reactivity control devices.     

An algorithm for controlling hybrid magnetic bearings using the magnetic field pattern

A novel algorithm and a way of controlling the rotor position in hybrid magnetic bearings based on the pattern of the external magnetic field is presented. A mathematical apparatus for the practical implementation of the proposed control method and algorithm is developed, and computer simulation using Ansys and Maxwell is carried out. Results of experimental verification of theoretical conclusions are presented.     

Distance metric-based time-efficient fuzzy algorithm for abnormal magnetic resonance brain image segmentation

Image segmentation is one of the significant computational applications of the biomedical field. Automated computational methodologies are highly preferred for medical image segmentation since these techniques are immune to human perception error. Artificial intelligence (AI)-based techniques are often used for this process since they are superior to other automated techniques in terms of accuracy and convergence time period. Fuzzy systems hold a significant position among the AI techniques because of their high accuracy. Even though these systems are exceptionally accurate, the time period required for convergence is exceedingly high. In this work, a novel distance metric-based fuzzy C-means (FCM) algorithm is proposed to tackle the low-convergence-rate problem of the conventional fuzzy systems. This modified approach involves the concept of distance-based dimensionality reduction of the input vector space that substantially reduces the iterative time period of the conventional FCM algorithm. The effectiveness of the modified FCM algorithm is explored in the context of magnetic resonance brain tumor image segmentation. Experimental results show promising results for the proposed approach in terms of convergence time period and segmentation efficiency. Thus, this algorithm proves to be highly feasible for time-oriented real-time applications.     

基于Moreau-包络的近似平滑迭代磁共振图像重建算法

针对基于压缩感知（CS）的磁共振成像（MRI）稀疏重建中存在的两个非平滑正则项问题,提出了一种基于Moreau包络的近似平滑迭代算法（PSIA）。基于CS的经典MRI稀疏重建是求解一个由最小二乘保真项、小波变换稀疏正则项和总变分（TV）正则项线性组合成的目标函数最小化问题。首先,对目标函数中的小波变换正则项作平滑近似;然后,将数据保真项与平滑近似后的小波正则项的线性组合看成一个新的可以连续求导的凸函数;最后,采用PSIA对新的优化问题进行求解。该算法不仅可以同时处理优化问题中的两个正则约束项,还避免了固定权重带来的算法鲁棒性问题。仿真得到的体模图像及真实磁共振图像的实验结果表明,所提算法与四种经典的稀疏重建算法：共轭梯度（CG）下降算法、TV1范数压缩MRI（TVCMRI）算法、部分k空间重建算法（RecPF）和快速复合分离算法（FCSA）相比,在图像信噪比、相对误差和结构相似性指数上具有更好的重建结果,且在算法复杂度上与现有最快重建算法即FCSA相当。     

An algorithm for non-linear space—Time nuclear reactor control

A novel multivariable control algorithm for non-linear space-time nuclear reactor dynamics is proposed in this paper. The multivariable control algorithm is based on a mathematical model of the nuclear reactor which includes: a single energy group of neutrons, delayed neutron precursors, iodine, xenon and thermal-hydraulic feedback. The multivariable control algorithm is composed of non-linear time-varying feedforward and feedback control signals, a reference model of the nuclear reactor and a dynamic observer. The non-linear proportional plus integral feedback controller forces the nuclear reactor to follow the response of the reference model. The dynamic observer estimates the unmeasurable state variables. The feedforward and feedback control signals are determined in a novel approach by specifying the form of the closed-loop response of the neutron density variables. By virtue of the multivariable control algorithm the closed-loop differential equations are linear and time-varying. A linear stability analysis for base-load and load-cycle operation indicates that the closed-loop system is stable provided that the thermal-hydraulic subsystem is inherently stable. The simulated dynamic response indicates that the multivariable control algorithm provides excellent response characteristics.     

Modeling glasses using the reverse Monte Carlo algorithm: addition of nuclear magnetic resonance and expanded coordination number constraints

In simple oxide glasses the coordination number and oxidation state of the glass-forming element can be predicted directly from the “8 − n” rule. Tellurite glasses, however, are unusual in that the coordination number of oxygen around tellurium varies without a corresponding change in the oxidation state of tellurium. To model sodium tellurite glasses successfully using the reverse Monte Carlo algorithm several new constraints have been added. Changes include extending the original coordination constraint to allow multiple coordination numbers, and the addition of a new coordination constraint to keep the oxidation state of tellurium constant by limiting the number of bridging and nonbridging oxygens bonded to each tellurium atom. In addition, the second moment of the distribution of dipolar couplings for sodium atoms obtained from a spin-echo NMR experiment was added as a new constraint. The resulting real-space models are presented and the effectiveness of the new constraints is discussed.     

An optimized ANN model based on genetic algorithm for predicting ripping production

Due to the environmental constraints and the limitations on blasting, ripping as a ground loosening and breaking method has become more popular in both mining and civil engineering applications. As a result, a more applicable rippability model is required to predict ripping production (Q) before conducting such tests. In this research, a hybrid genetic algorithm (GA) optimized by artificial neural network (ANN) was developed to predict ripping production results obtained from three sites in Johor state, Malaysia. It should be noted that the mentioned hybrid model was first time applied in this field. In this regard, 74 ripping tests were investigated in the studied areas and the relevant parameters were also measured. A series of GA–ANN models were conducted in order to propose a hybrid model with a higher accuracy level. To demonstrate the performance capacity of the hybrid GA–ANN model, a pre-developed ANN model was also proposed and results of predictive models were compared using several performance indices. The results revealed higher accuracy of the proposed hybrid GA–ANN model in estimating Q compared to ANN technique. As an example, root-mean-square error values of 0.092 and 0.131 for testing datasets of GA–ANN and ANN techniques, respectively, express the superiority of the newly developed model in predicting ripping production.

     

Automatic magnetic resonance image segmentation by fuzzy intercluster hostility index based genetic algorithm: An application

Segmentation of magnetic resonance (MR) images plays an important role in the medical science or clinical research. In this article, an application of a genetic algorithm (GA) based segmentation algorithm is presented for automatic grouping of unlabeled pixels of the MR images into different homogeneous clusters. Before the segmentation, the information about the optimal number of segments as well as the underlying pixel distribution of an image is not required in this method. The centroid of different segments is demarcated as active/inactive centroid by the fuzzy intercluster hostility index. After that, the test images are segmented by the selected active centroids. The optimal number of segments and their respective centroids are determined by this method. A performance comparison is manifested between the fuzzy intercluster hostility index based GA method and the well-known automatic clustering using differential evolution (ACDE) algorithm and one genetic algorithm based non-automatic algorithm with the help of two real life MR images. The comparison depicted the superiority of the GA based automatic image segmentation method with the help of fuzzy intercluster hostility index over other two algorithms.