Information cut for clustering using a gradient descent approach

We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between probability density functions. We propose to optimize the Information Cut using a gradient descent-based approach. Our algorithm has several advantages compared to many other graph-based methods in terms of determining an appropriate affinity measure, computational complexity, memory requirements and coping with different data scales. We show that our method may produce clustering and image segmentation results comparable or better than the state-of-the art graph-based methods.     

肉灌肠中淀粉测定的操作要点及改进

主要目的是重新认识淀粉测定中的操作要点，并结合实践经验加以改进和完善，提高化验结果的准确度，更好地指导和监督生产。     

裂解碳五选择性加氢研究

将裂解C5馏分资源经选择性加氢、醚化,合成了高辛烷值汽油调和组分。为满足醚化催化剂的要求,进行了蒸汽裂解C5双烯烃选择性加氢工艺研究,对裂解C5双烯烃选择性加氢催化剂进行了评价,考察了反应压力、空速、反应温度、氢烯摩尔比对双烯烃选择性加氢的影响,得出适宜工艺条件为:反应压力0.5～1.5 MPa,温度45～80℃,空速10～2．0 h-1 ,氢烯摩尔比大于1.1。     

瓶组气化站的建筑、结构设计要点

瓶组气化站的建筑，结构设计关系到安全，满足使用要求和投资的大小，本文根据多年的实践和最新的有关设计规范的要求，阐述瓶组气化站建筑，结构设计的要点。     

焊缝超声检测的基本特征及操作要点

通过对焊缝超声波检测原理和检测系统实施过程的分析,论述了检测系统的要素组成;总结了检测实施过程的基本特征与缺陷判定、焊缝质量评定的关系以及存在的主要问题;提出了提高焊缝超声波检测可靠性应控制检测实施过程诸要素的途径和方法.     

电力地理信息系统外业数据采集编码方案的探讨

本文介绍了配电电力地理信息系统外业数据采集编码的方法；其中包括线路编码、点编码、线路分界点编码、变电所的编码、开关的编码方法等。     

弱电工程施工和管理研究与探讨

弱电工程项目的质量控制的关键是对工程的设计、施工和管理过程进行严格的控制和把关,并按规范步骤进行操作和实施。通过工程的前期沟通、技术选择、需求确定、配置清单和施工图纸等措施可规范设计过程。通过施工前会议、施工要点、材料和设备采购、工程进度、方案设计等措施可规范施工过程。通过制定施工组织和协调管理等措施可规范施工管理。通过规范的设计、施工和管理可以提高工程质量和工程效益。     

Group codes on certain algebraic curves with many rational points

We construct a series of algebraic geometric codes using a class of curves which have many rational points. We obtain codes of lengthq ² over _q , whereq = 2q ₀ ² andq ₀ = 2 ⁿ , such that dimension + minimal distance q ² + 1 – q ₀ (q – 1). The codes are ideals in the group algebra _q [S], whereS is a Sylow-2-subgroup of orderq ² of the Suzuki-group of orderq ² (q ² + 1)(q – 1). The curves used for construction have in relation to their genera the maximal number of GF _q -rational points. This maximal number is determined by the explicit formulas of Weil and is effectively smaller than the Hasse—Weil bound.Supported by Deutsche Forschungsgemeinschaft while visiting Essen University     

Polynomial approximation of functions of matrices and applications

In solving a mathematical problem numerically, we frequently need to operate on a vector by an operator that can be expressed asf(A), whereA is anN ×N matrix [e.g., exp(A), sin(A), A^–-]. Except for very simple matrices, it is impractical to construct the matrixf (A) explicitly. Usually an approximation to it is used. This paper develops an algorithm based upon a polynomial approximation tof (A). First the problem is reduced to a problem of approximatingf (z) by a polynomial in z, where z belongs to a domainD in the complex plane that includes all the eigenvalues ofA. This approximation problem is treated by interpolatingf (z) in a certain set of points that is known to have some maximal properties. The approximation thus achieved is almost best. Implementing the algorithm to some practical problems is described. Since a solution to a linear systemAx=b isx=A ^–1 b, an iterative solution algorithm can be based upon a polynomial approximation tof (A)=A ^–1. We give special attention to this important problem.     

Continuous process control using neural networks

We present some adaptive control strategies based on neural networks that can be used for designing controllers for continuous process control problems. Specifically, a learning algorithm has been formulated based on reinforcement learning, a weakly supervised learning technique, to solve set-point control and control scheduling for continuous processes where the process cannot be modeled easily. It is shown how reinforcement learning can be used to learn the control strategy adaptively based on exploration of the control space without making assumptions about the process model. A new learning scheme, handicapped learning, was developed to learn a control schedule that specifies a schedule of set points. Applications studied include the control of a nonisothermal continuously stirred tank reactor at its unstable state and the learning of the daily time-temperature schedule for an environment controller. Experimental results demonstrate good learning performance, indicating that the learning algorithm can be used for solving transient startup and boundary value control problems.