Buckling Properties of Water-Drop-Shaped Pressure Hulls with Various Shape Indices Under Hydrostatic External Pressure

The water-drop-shaped pressure hull has a good streamline,which has good application prospect in the underwater observatory.Therefore,this study conducted analytical,experimental and numerical investigation of the buckling properties of water-drop-shaped pressure hulls under hydrostatic pressure.A water-drop experiment was conducted to design water-drop-shaped pressure hulls with various shape indices.The critical loads for the water-drop-shaped pressure hulls were resolved by using Mushtari’s formula.Several numerical simulations including linear buckling analysis and nonlinear buckling analysis including eigenmode imperfections were performed.The results indicated that the critical loads resolved by Mushtari's formula were in good agreement with the linear buckling loads from the numerical simulations.This formula can be extended to estimate the buckling capacity of water-drop-shaped pressure hulls.In addition,three groups of pressure hulls were fabricated by using stereolithography,a rapid prototyping technique.Subsequently,three groups of the pressure hulls were subjected to ultrasonic measurements,optical scanning,hydrostatic testing and numerical analysis.The experimental results were consistent with the numerical results.The results indicate that the sharp end of the water-drop-shaped pressure hulls exhibited instability compared with the blunt end.This paper provides a new solution to the limitations of experimental studies on the water-drop-shaped pressure hulls as well as a new configuration and evaluation method for underwater observatories.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

CONVEXITY OF THE FREE BOUNDARY FOR AN AXISYMMETRIC INCOMPRESSIBLE IMPINGING JET

This paper is devoted to the study of the shape of the free boundary for a threedimensional axisymmetric incompressible impinging jet.To be more precise,we will show that the free boundary is convex to the fluid,provided that the uneven ground is concave to the fluid.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives

We are investigating the distributed optimization problem,where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions.Since nodes exchange optimization parameters through the wireless network,large-scale training models can create communication bottlenecks,resulting in slower training times.To address this issue,CHOCO-SGD was proposed,which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective functions.Nevertheless,most convex functions are not strongly convex(such as logistic regression or Lasso),which raises the question of whether this algorithm can be applied to non-strongly convex functions.In this paper,we provide the first theoretical analysis of the convergence rate of CHOCO-SGD on non-strongly convex objectives.We derive a sufficient condition,which limits the fidelity of compression,to guarantee convergence.Moreover,our analysis demonstrates that within the fidelity threshold,this algorithm can significantly reduce transmission burden while maintaining the same convergence rate order as its no-compression equivalent.Numerical experiments further validate the theoretical findings by demonstrating that CHOCO-SGD improves communication efficiency and keeps the same convergence rate order simultaneously.And experiments also show that the algorithm fails to converge with low compression fidelity and in time-varying topologies.Overall,our study offers valuable insights into the potential applicability of CHOCO-SGD for non-strongly convex objectives.Additionally,we provide practical guidelines for researchers seeking to utilize this algorithm in real-world scenarios.

Relaxed Stability Criteria for Time-Delay Systems:A Novel Quadratic Function Convex Approximation Approach

This paper develops a quadratic function convex approximation approach to deal with the negative definite problem of the quadratic function induced by stability analysis of linear systems with time-varying delays.By introducing two adjustable parameters and two free variables,a novel convex function greater than or equal to the quadratic function is constructed,regardless of the sign of the coefficient in the quadratic term.The developed lemma can also be degenerated into the existing quadratic function negative-determination(QFND)lemma and relaxed QFND lemma respectively,by setting two adjustable parameters and two free variables as some particular values.Moreover,for a linear system with time-varying delays,a relaxed stability criterion is established via our developed lemma,together with the quivalent reciprocal combination technique and the Bessel-Legendre inequality.As a result,the conservatism can be reduced via the proposed approach in the context of constructing Lyapunov-Krasovskii functionals for the stability analysis of linear time-varying delay systems.Finally,the superiority of our results is illustrated through three numerical examples.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

Optimized Adsorption of Small and Medium Molecules by a Biosorbent Based on Hevea Hulls

In the context of the recovery of agricultural waste, many researches have focused on the preparation of adsorbents from natural waste from fruit trees, egg shells, palm waste or sawdust. This work aims to optimize the preparation of a biosorbent from rubber hulls by studying its ability to adsorb small and medium molecules. The influence of parameters such as drying temperature (X1), particle size (X2), stirring time (X3) and sodium hypochloride mass (X4) was studied. The results indicate that the model used for biosorbent optimization on methylene blue and iodine index is significant. In addition, this model has greater adsorption capabilities on small molecules than with large molecules. Statistical analysis of the data shows that temperature is the most influential factor in the adsorption of small molecules. On the other hand, particle size has a significant influence on the adsorption of large molecules. The optimum biosorbent preparation values are 1.0 for drying temperature (X1), −1.0 for biosorbent grain size (X2), 1.0 for stirring time (X3) and 1.0 for sodium hypochloride mass (X4).

Monolithic Convex Limiting for Legendre-Gauss-Lobatto Discontinuous Galerkin Spectral-Element Methods

We extend the monolithic convex limiting(MCL)methodology to nodal discontinuous Galerkin spectral-element methods(DGSEMS).The use of Legendre-Gauss-Lobatto(LGL)quadrature endows collocated DGSEM space discretizations of nonlinear hyperbolic problems with properties that greatly simplify the design of invariant domain-preserving high-resolution schemes.Compared to many other continuous and discontinuous Galerkin method variants,a particular advantage of the LGL spectral operator is the availability of a natural decomposition into a compatible subcellflux discretization.Representing a highorder spatial semi-discretization in terms of intermediate states,we performflux limiting in a manner that keeps these states and the results of Runge-Kutta stages in convex invariant domains.In addition,local bounds may be imposed on scalar quantities of interest.In contrast to limiting approaches based on predictor-corrector algorithms,our MCL procedure for LGL-DGSEM yields nonlinearflux approximations that are independent of the time-step size and can be further modified to enforce entropy stability.To demonstrate the robustness of MCL/DGSEM schemes for the compressible Euler equations,we run simulations for challenging setups featuring strong shocks,steep density gradients,and vortex dominatedflows.

无线传感器网络中基于Convexhull的能量空洞避免路由算法

提供了一种绕过无线传感器网络"能量空洞"的方法(CHA方法),可以用来找到绕过能量空洞的最优节点路由路径。在数据包从源节点传递到目的节点的过程中,通过遇到能量空洞,先勾勒出空洞范围,再基于凸壳(Convex hull)找到绕过能量空洞的最优节点路由路径。仿真结果表明,该算法优化了能量空洞绕洞路由路径,有效提高了无线传感器网络传输效率,减少了无线传感器能量损耗和信息传递的延迟。

A new algorithm for computing the convex hull of a planar point set

When the edges of a convex polygon are traversed along one direction,the interior of the convex polygon is always on the same side of the edges. Based on this characteristic of convex polygons,a new algorithm for computing the convex hull of a simple polygon is proposed in this paper,which is then extended to a new algorithm for computing the convex hull of a planar point set. First,the extreme points of the planar point set are found,and the subsets of point candidate for vertex of the convex hull between extreme points are obtained. Then,the ordered convex hull point sequences between extreme points are constructed separately and concatenated by removing redundant extreme points to get the convex hull. The time complexity of the new planar convex hull algorithm is O(nlogh) ,which is equal to the time complexity of the best output-sensitive planar convex hull algorithms. Compared with the algorithm having the same complexity,the new algorithm is much faster.

A novel method for virtual clearance computation of high-speed train based on model integration and convex hull

The 3D clearance of a high-speed train(HST) is critical to ensure the safety of railway transportation. Many studies have been conducted on the inspection of the clearance profile in railway operation based on the vision system, but few researchers have focused on the computation of the 3D clearance in the design phase of an HST. This paper summarizes the virtual 3D clearance computation of an HST based on model integration and the convex hull method. First, both the aerodynamic and kinetic analysis models of the HST are constructed. The two models are then integrated according to the corresponding relationship map, and an array of transformation matrixes of the HST is created to drive the designed model simulating the physical railway motion. Furthermore, the convex hull method is adopted to compute the 3D envelope of the moving train. Finally, the Hausdorff metric is involved in the measurement of the minimum clearance model and the 3D envelope model. In addition, the color map of the Hausdorff distance is established to verify that the designed shape of the HST meets the national standards. This paper provides an effective method to accurately calculate the 3D clearance for the shape design of an HST, which greatly reduces the development cost by minimizing the physical prototype that must be built.

On Constructing Approximate Convex Hull

The algorithms of convex hull have been extensively studied in literature, principally because of their wide range of applications in different areas. This article presents an efficient algorithm to construct approximate convex hull from a set of n points in the plane in O(n+k) time, where k is the approximation error control parameter. The proposed algorithm is suitable for applications preferred to reduce the computation time in exchange of accuracy level such as animation and interaction in computer graphics where rapid and real-time graphics rendering is indispensable.

Group Target Tracking in WSN Based on Convex Hulls Merging

When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group target. In order to decrease the amount of energy spent on active sensing and communications, a flexible boundary detecting model for group target tracking in WSN is proposed, in which, the number of sensors involved in target tracking is adjustable. Unlike traditional one or multiple individual targets, the group target usually occupies a large area. To obtain global estimated position of group target, a divide-merge algorithm using convex hull is designed. In this algorithm, group target’s boundary is divided into several small pieces, and each one is enclosed by a convex hull which is constructed by a cluster of boundary sensors. Then, the information of these small convex hulls is sent back to a sink. Finally, big convex hull merged from these small ones is considered as the group target’s contour. According to our metric of precision evaluation, the simulation experiments confirm the efficiency and accuracy of this algorithm.

Drug discrimination of Near Infrared spectroscopy based on the scaled convex hull classifier

Near Infrared spectroscopy(NIRS)has been widely used in the discrimination(classification)of pharmaceutical drugs.In real applications,however,the class imbalance of the drug samples,i.e.,the number of one drug sample may be much larger than the number of the other drugs,deceasesdrastically the discrimination performance of the classification models.To address this classimbalance problem,a new computational method--the scaled convex hull(SCH)-basedmaximum margin classifier is proposed in this paper.By a suitable selection of the reductionfactor of the SCHs generated by the two classes of drug samples,respectively,the maximalmargin classifier bet ween SCHs can be constructed which can obtain good classification per-formance.With an optimization of the parameters involved in the modeling by Cuckoo Search,a satisfied model is achieved for the classification of the drug.The experiments on spectra samplesproduced by a pharmaceutical company show that the proposed method is more effective androbust than the existing ones.

Experimental and numerical analysis on suitability of S-Glass-Carbon fiber reinforced polymer composites for submarine hull

Suitability of S-Glass/carbon fiber reinforced polymer composite for submarine hull subjected to hydrostatic pressure has been investigated in the present study.Metallic materials have raised concerns owing to their decomposition due to low resistance towards salinity and hence polymer composites have been explored to showcase their mechanical stability to withstand transverse and impact loads.To this end,the mechanical properties of S-Glass/carbon fiber reinforced polymer composite were experimentally investigated and higher specific strength and stiffness of the composite in comparison to many metallic materials used for submarine hull were reported.The obtained experimental values were used for the static and dynamic crash analysis of the bow,stern and foil through Finite Element Analysis(FEA);where depth of travel was varied from sea surface level of 0-7000 m.Submarine assembly was later developed with the optimum shape and thickness of each part.We also report the nonlinear crash analysis upon impact at velocity ranging from 3 to 21 m/s.Besides,kinetic energy,acceleration peak and internal energy in struck submarine revealed that travel depth 1750 m and 3500 m is recommendable,more particularly,crash safety factor of the submarine is found to be within limit when submarine encounters crash at 1750 m.

Relaxed Stability Criteria for Delayed Generalized Neural Networks via a Novel Reciprocally Convex Combination

Dear Editor,This letter examines the stability issue of generalized neural networks(GNNs) with time-varying delay based on a novel reciprocally convex combination(RCC). By considering a new matrix polynomial, the proposed novel reciprocally convex method leads to a tight bound for integral inequality combination and encompasses several existing approaches as special cases.

Secure planar convex hull protocol for large-scaled point sets in semi-honest model

Efficiency and scalability are still the bottleneck for secure multi-party computation geometry （SMCG）. In this work a secure planar convex hull （SPCH） protocol for large-scaled point sets in semi-honest model has been proposed efficiently to solve the above problems. Firstly, a novel priva- cy-preserving point-inclusion （PPPI） protocol is designed based on the classic homomorphic encryp- tion and secure cross product protocol, and it is demonstrated that the complexity of PPPI protocol is independent of the vertex size of the input convex hull. And then on the basis of the novel PPPI pro- tocol, an effective SPCH protocol is presented. Analysis shows that this SPCH protocol has a good performance for large-scaled point sets compared with previous solutions. Moreover, analysis finds that the complexity of our SPCH protocol relies on the size of the points on the outermost layer of the input point sets only.

Novel Gluten-Free Amaranth and Oat Flour Cookies Fortified with Soybean Hulls

Soybean hulls, an abundant byproduct of soybean processing, contain rich phytochemicals, fibers, proteins, and minerals. Currently soybean hulls are primarily used as animal feeds. For value-added soybean hull utilization, 25% soybean hulls were substituted for amaranth or whole oat flour (WOF) in novel gluten-free cookies. Composition, nutritional values, water-holding capacities, correlation between properties, and pasting and rheological properties of soybean hulls, amaranth, and WOF were appraised in comparison to wheat flour. Water loss, cookie texture, and geometrical properties of the cookies were examined. The results disclosed that soybean hulls, amaranth and WOF contain higher protein content, minerals, fiber, special amino acids, and critical vitamins (C and K) than wheat flour. Considerably higher total amino acid content was found in soybean hulls (18.33%) than wheat flour (12.77%). Water-holding capacities increased by replacing amaranth and WOF with soybean hulls. Soybean hulls exhibited higher rheological elastic properties than amaranth, WOF and wheat flours. The soybean hulls utilized in amaranth or WOF cookies greatly improved their nutritional value, the water retention and moisture content along with acceptable physical properties when compared to wheat flour cookies. This study explored the feasibility and potential of utilizing soybean hulls with amaranth and WOF in gluten-free bakery products and other food applications.

基于机器视觉的芯片字符区域分割和定位算法

芯片表面的字符对分选具有重要意义,对字符的定位是分选工作的关键步骤。为了提高分选工作定位效率和定位精度,提出了一种基于改进的区域生长算法和凸包检测算法分割和定位芯片表面字符区域方法。首先,对采集图像进行预处理操作,利用改进的Canny算法获取无干扰图像边缘,将图像边缘作为区域生长法的种子点并以图像自适应阈值作为生长准则分割图像,使用最大内接矩形算法粗定位字符区域;其次,采用Harris角点检测算法获取字符角点分布位置;最后,筛选角点并提取关键点,利用一种改进的凸包检测算法定位字符区域。经过实验验证,所设计的算法能够完整的分割和定位芯片表面字符区域,定位精度和效率较原有方法提升5.3%和15.4%,满足实际工业生产的要求。