Semi-supervised locally discriminant projection for classification and recognition

Semi-supervised dimensional reduction methods play an important role in pattern recognition, which are likely to be more suitable for plant leaf and palmprint classification, since labeling plant leaf and palmprint often requires expensive human labor, whereas unlabeled plant leaf and palmprint is far easier to obtain at very low cost. In this paper, we attempt to utilize the unlabeled data to aid plant leaf and palmprint classification task with the limited number of the labeled plant leaf or palmprint data, and propose a semi-supervised locally discriminant projection (SSLDP) algorithm for plant leaf and palmprint classification. By making use of both labeled and unlabeled data in learning a transformation for dimensionality reduction, the proposed method can overcome the small-sample-size (SSS) problem under the situation where labeled data are scant. In SSLDP, the labeled data points, combined with the unlabeled data ones, are used to construct the within-class and between-class weight matrices incorporating the neighborhood information of the data set. The experiments on plant leaf and palmprint databases demonstrate that SSLDP is effective and feasible for plant leaf and palmprint classification.     

Fuzzy measurable house of quality and quality function deployment for fuzzy regression estimation problem

In present competitive environment, it is necessary for companies to evaluate design time and effort at the early stage of product development. However, there is somewhat lacking in systemic analytical methods for product design time (PDT). For this end, this paper explores an intelligent method to evaluate the PDT. At the early development stage, designers are short of sufficient product information and have difficulty in determining PDT by subjective evaluation. Thus, a fuzzy measurable house of quality (FM-HOQ) model is proposed to provide measurable engineering information. Quality function deployment (QFD) is combined with a mapping pattern of “function → principle → structure” to extract product characteristics from customer demands. Then, a fuzzy support vector regression machine (FSVRM) model is built to fuse data and realize the estimation of PDT, which makes use of fuzzy comprehensive evaluation to simplify structure. In a word, the whole estimation method consists of four steps: time factors identification, product characteristics extraction by QFD and function mapping pattern, FSVRM learning, and PDT estimation. Finally, to illustrate the procedure of the estimation method, the case of injection mold design is studied. The results of experiments show that the fuzzy method is feasible and effective.     

基于形态学的蛇形机器人运动步态算法研究

基于蛇形机器人运动形态学,利用扩展Frenet-Serret分析了一种蛇形机器人运动的几何模型,并根据这种几何模型研究了一种确定蛇形机器人的运动步态规律的算法,称之为EFSA(extended frenet-serret algorithm)算法.用这种算法规划了无轮蛇形机器人的基本运动步态,而且重要的是实现了蛇形机器...     

Pseudo-Randomness of Certain Sequences of <Emphasis Type="Italic">k</Emphasis> Symbols with Length <Emphasis Type="Italic">pq</Emphasis>

The theory of finite pseudo-random binary sequences was built by C. Mauduit and A. Sárközy and later extended to sequences of k symbols (or k-ary sequences). Certain constructions of pseudo-random sequences of k symbols were presented over finite fields in the literature. In this paper, two families of sequences of k symbols are constructed by using the integers modulo pq for distinct odd primes p and q. The upper bounds on the well-distribution measure and the correlation measure of the families sequences are presented in terms of certain character sums over modulo pq residue class rings. And low bounds on the linear complexity profile are also estimated.     

应用于开关电源的CMOS电流控制振荡器

提出了一种结构简单的CMOS电流控制模式振荡器。该电路利用系统内部参考电压和外接电阻产生的电流信号对电容进行充放电,通过调节外接电阻大小,振荡器输出频率在660 kHz～4.15 MHz内可调。     

一种基于ECB模式的NSL协议改进方案

安全协议形式化方法大都在一个很高的抽象层次建立协议模型。但是协议的许多安全问题是在很低的抽象层次产生。本文分析了ECB工作模式下的NSL协议的安全问题,并通过破坏同态性的方法给出一种改进方案。通过扩展规则的BAN逻辑对NSL协议建模和分析,验证结果表明协议中存在着安全漏洞,新的改进方案可以避免这种攻击。     

Psychiatric document retrieval using a discourse-aware model

With the increased incidence of depression-related disorders, many psychiatric websites have been developed to provide huge amounts of educational documents along with rich self-help information. Psychiatric document retrieval aims to assist individuals to locate documents relevant to their depressive problems efficiently and effectively. By referring to relevant documents, individuals can understand how to alleviate their depression-related symptoms according to recommendations from health professionals. This work proposes the use of high-level discourse information extracted from queries and documents to improve the precision of retrieval results. The discourse information adopted herein includes negative life events, depressive symptoms and semantic relations between symptoms, which are beneficial for better understanding of users' queries. Experimental results show that the discourse-aware retrieval model achieves higher precision than the word-based retrieval models, namely the vector space model (VSM) and Okapi model, adopting word-level information alone.     

Model predictive control for systems with stochastic multiplicative uncertainty and probabilistic constraints

Robust predictive control handles constrained systems that are subject to stochastic uncertainty but propagating the effects of uncertainty over a prediction horizon can be computationally expensive and conservative. This paper overcomes these issues through an augmented autonomous prediction formulation, and provides a method of handling probabilistic constraints and ensuring closed loop stability through the use of an extension of the concept of invariance, namely invariance with probability p.     

On the diameter of geometric path graphs of points in convex position

For a set S of n points in convex position in the plane, let P(S) denote the set of all plane spanning paths of S. The geometric path graph of S, denoted by Gn, is the graph with P(S) as its vertex set and two vertices P,Q∈P(S) are adjacent if and only if P and Q can be transformed to each other by means of a single edge replacement. Recently, Akl et al. [S.G. Akl, K. Islam, H. Meijer, On planar path transformation, Inform. Process. Lett. 104 (2007) 59-64] showed that the diameter of Gn is at most 2n−5. In this note, we derive the exact diameter of Gn for n?3.     

Building a cost-constrained decision tree with multiple condition attributes

Costs are often an important part of the classification process. Cost factors have been taken into consideration in many previous studies regarding decision tree models. In this study, we also consider a cost-sensitive decision tree construction problem. We assume that there are test costs that must be paid to obtain the values of the decision attribute and that a record must be classified without exceeding the spending cost threshold. Unlike previous studies, however, in which records were classified with only a single condition attribute, in this study, we are able to simultaneously classify records with multiple condition attributes. An algorithm is developed to build a cost-constrained decision tree, which allows us to simultaneously classify multiple condition attributes. The experimental results show that our algorithm satisfactorily handles data with multiple condition attributes under different cost constraints.