Frequency domain analysis of the mirror-modified filtered-x least mean squares algorithm with low ambient noise

The mirror-modified filtered-x least mean squares (MMFxLMS ) algorithm is a variation of the FxLMS algorithm with online secondary path modeling that cannot diverge due to secondary path modeling errors. However, problems may occur when the ambient noise is not limited due to insufficient modeling power. This work shows that under a frequency domain analysis without ambient noise, the MMFxLMS algorithm is always stable, and expressions for the maximum residual noise level at any given time are obtained. It is also shown that, under the same context, convergence to the minimum residual noise is guaranteed. Still, convergence can be much slower for high secondary path modeling errors than that of the LMS or MFxLMS algorithms. Simulations confirm these results.     

Coagulation process in Manchega sheep milk from Spain: A path analysis approach

Characteristics of sheep milk are of great interest for the dairy industry, as almost the totality of production is intended for cheesemaking. However, the existing relationships between these variables are complex. This study assessed composition, hygienic quality, coagulation properties, and curd yield of 1,200 individual Manchega sheep milk samples. The aim was to compare the effect of composition and hygienic quality on coagulation and curdling, and to evaluate the relationship between curd yields and the coagulation process and the effect of other features by using path analysis methodologies. Outcomes proved path analysis to be a useful and effective tool to assess these relationships through direct and indirect paths within the same model. Results showed that the factors that had a direct influence on milk coagulation were lactose concentration, casein content, and initial pH of milk. Contrastingly, somatic cells did not seem to have any effect (direct or indirect) on the coagulation process. Factors that directly affected curd yield were fat content, lactose concentration, casein content, and curd moisture. However, technological parameters showed little effect over curd yield.     

基于协同多目标算法的多机器人路径规划

多机器人路径规划是群体机器人协同工作的前提,其特点是在防碰撞与避障的前提下追求多方面资源的最小消耗.针对这一特点,提出协同非支配排序遗传算法,解决具有多个优化目标的多机器人路径规划问题;运用改进的多目标优化算法,克服多目标优化取权值的不足,同时考虑机器人能源与时间两大资源,以多机器人的路径总长度、总平滑度、总耗时为规划目标.同时引入合作型协同算法框架,将难以求解的多变量问题分组求解.每个机器人的路径视为子种群,子种群通过带精英策略的非支配排序遗传算法,进化并筛选出子种群的部分进入协同进化,每次迭代更新外部的精英解集,最终生成一组非支配路径解.仿真结果表明,在栅格地图环境下,本文算法可有效实现多移动机器人的多优化目标路径规划.     

超级计算机网络引导技术研究与分析

针对超级计算机系统中网络引导时间开销大的问题，提出网络引导分布算法是影响网络引导性能的主要因素之一，是优化网络引导性能的主要方向的观点。首先，分析了影响大规模网络引导性能的主要因素；其次，结合一种典型超级计算机系统，分析了超节点循环分布算法（SCDA）和插件循环分布算法（BCDA）的网络引导数据流拓扑结构；最后，量化分析了这两种算法对各个网络路径段的压力和可获得的网络性能，发现BCDA性能是SCDA性能的1~20倍。通过理论分析和模型推导发现，在计算节点和引导服务器之间使用更细粒度的映射算法可以在引导部分资源时使用尽量多的引导服务器，减少对局部网络资源的过早竞争，提升网络引导性能。     

Local toolpath smoothing for five-axis machine tools

When five axis CNC machine tools follow series linear toolpath segments, the drives experience velocity, acceleration and jerk discontinuities at the block transition points. The discontinuities result in fluctuations on machine tool motions which lead to poor surface quality. This paper proposes to insert quintic and septic micro-splines for the tool tip and tool-orientation, respectively, at the adjacent linear toolpath segments. Optimal control points are calculated for position and orientation splines to achieve C³ continuity at the junctions while respecting user-defined tolerance limits. The geometrically smoothed corners are traveled at a smoothly varying feed with cubic acceleration trajectory profile. The proposed method is experimentally demonstrated to show improvements in motion smoothness and tracking accuracy in five-axis machining of free-form surfaces found in dies, molds and aerospace parts.     

Buckling and post-buckling behaviour of elastic seven-layered cylindrical shells – FEM study

The paper is devoted to buckling and post-buckling problems of an elastic seven-layered cylindrical shell under uniformly distributed pressure. The shell is an untypical sandwich structure composed of main corrugated core and two three-layer faces. Numerical FEM model for the shell has been elaborated. The calculations have been performed with the use of the ANSYS code for elastic shells of different dimensions. The linear and non-linear analyses of the shells have been performed with the use of the finite elements method. Critical pressure and equilibrium paths for the family of seven-layered shells subjected to uniformly distributed external pressure are calculated. The influence of corrugation pitch of main core and the length of the shell on the critical pressure has been determined. The results of these investigations are presented on the graphs.     

A smooth curve evolution approach to the feedrate planning on five-axis toolpath with geometric and kinematic constraints

Feedrate planning with geometric and kinematic constraints is crucial for sculptured surface machining. Due to the non-linear relationship between the Cartesian space and the joint space, the feedrate planning method for a given five-axis toolpath is very limited compared with that in three-axis machining. To achieve the exact control of the chord error and the kinematic characteristics of cutter and machine tool, this paper presents a new feedrate planning method for five-axis parametric path using a smooth curve evolution strategy. The constraints in feedrate planning are first classified as two types of neighbor-independent (NI) constraints and neighbor-dependent (ND) constraints. Then for constraint violated region, the detailed formulas of determining the update feedrates of violated sampling points are given using a decoupled manner. As a result, NI and ND constraints are satisfied respectively with one step and multi-step smooth curve evolution technique, which can smoothly deform the target feedrate profile to the desired update positions. Simulations and experiments are performed on the given tool path to validate the effectiveness of the proposed feed planning method. The results show that the proposed method is robust and effective in the exact control of constraints in the feedrate planning on complex five-axis toolpath.     

Expression of RCAS1 Correlates with Urothelial Bladder Cancer Malignancy

RCAS1 is a protein that participates in regulation of the tumor microenvironment and its immune responses, all in order to evade the immune system. The aim of this study was to analyze RCAS1 expression in urothelial bladder cancer cells (and in fibroblasts and macrophages of the tumor stroma) and its relationship with the histological pattern of malignancy. Eighty-three postcystectomy patients were enrolled. We analyzed the histological maturity (grade), progress (pT stage), tissue invasion type (TIT), nonclassic differentiation number (NDN), and the ability to metastasize (pN). The expression of RCAS1 protein was analyzed by immunohistochemistry. Indicators of histological malignancy were observed solely in association with the RCAS1 expression in cells in the border parts (BPs) of the tumor. Histological malignancy of the tumor, indicated by the pT and pN, and metastasis-free survival time, correlated significantly with RCAS1 expression in tumor neoplastic cells, whereas malignancy determined by grade, TIT, and NDN correlated with RCAS1 expression in fibroblasts and macrophages in the tumor microenvironment. These findings suggest that the increased RCAS1 expression depends on its cellular source and that RCAS1 expression itself is a component of various signaling pathways. The immune escape occurs within the tumor BPs, where the increase in the RCAS1 expression occurs within tumor cells and stromal cells in its microenvironment. We conclude that the histological pattern of tumor malignancy, indicated by grade, TIT, NDN, pT, and pN is a morphological indicator of immune escape.     

A Dijkstra-like method computing all extreme supported non-dominated solutions of the biobjective shortest path problem

We address the problem of determining all extreme supported solutions of the biobjective shortest path problem. A novel Dijkstra-like method generalizing Dijkstra׳s algorithm to this biobjective case is proposed. The algorithm runs in O(N(m+n log n)) time to solve one-to-one and one-to-all biobjective shortest path problems determining all extreme supported non-dominated points in the outcome space and one supported efficient path associated with each one of them. Here n is the number of nodes, m is the number of arcs and N is the number of extreme supported points in outcome space for the one-to-all biobjective shortest path problem. The memory space required by the algorithm is O(n+m) for the one-to-one problem and O(N+m) for the one-to-all problem. A computational experiment comparing the performance of the proposed methods and state-of-the-art methods is included.     

A physically-based model for global collision avoidance in 5-axis point milling

Although 5-axis free form surface machining is commonly proposed in CAD/CAM software, several issues still need to be addressed and especially collision avoidance between the tool and the part. Indeed, advanced user skills are often required to define smooth tool axis orientations along the tool path in high speed machining. In the literature, the problem of collision avoidance is mainly treated as an iterative process based on local and global collision tests with a geometrical method. In this paper, an innovative method based on physical modeling is used to generate 5-axis collision-free smooth tool paths. In the proposed approach, the ball-end tool is considered as a rigid body moving in the 3D space on which repulsive forces, deriving from a scalar potential field attached to the check surfaces, and attractive forces are acting. A study of the check surface tessellation is carried out to ensure smooth variations of the tool axis orientation. The proposed algorithm is applied to open pocket parts such as an impeller to emphasize the effectiveness of this method to avoid collision.