An improved smart card based password authentication scheme with provable security

Password authentication has been adopted as one of the most commonly used solutions in network environment to protect resources from unauthorized access. Recently, Lee–Kim–Yoo [S.W. Lee, H.S. Kim, K.Y. Yoo, Improvement of Chien et al.'s remote user authentication scheme using smart cards, Computer Standards & Interfaces 27 (2) (2005) 181–183] and Lee-Chiu [N.Y. Lee, Y.C. Chiu, Improved remote authentication scheme with smart card, Computer Standards & Interfaces 27 (2) (2005) 177–180] respectively proposed a smart card based password authentication scheme. We show that these two schemes are both subject to forgery attacks provided that the information stored in the smart card is disclosed by the adversary. We also propose an improved scheme with formal security proof.     

Energy efficient redundant configurations for real-time parallel reliable servers

Modular redundancy and temporal redundancy are traditional techniques to increase system reliability. In addition to being used as temporal redundancy, with technology advancements, slack time in a system can also be used by energy management schemes to save energy. In this paper, we consider the combination of modular and temporal redundancy to achieve energy efficient reliable real-time service provided by multiple servers. We first propose an efficient adaptive parallel recovery scheme that appropriately processes service requests in parallel to increase the number of faults that can be tolerated and thus system reliability. Then we explore schemes to determine the optimal redundant configurations of the parallel servers to minimize system energy consumption for a given reliability goal or to maximize system reliability for a given energy budget. Our analysis results show that small requests, optimistic approaches, and parallel recovery favor lower levels of modular redundancy, while large requests, pessimistic approaches and restricted serial recovery favor higher levels of modular redundancy.

Micro/nanoporous membrane based gas–water separation in microchannel

In this paper, a method coupling micro/nanoporous membranes with microchannels for the gas/water separation in microscale has been demonstrated. The principle of separation is based on the basic properties of membranes—wetted micro/nanoporous hydrophilic membranes can block gas due to a large water surface tension in the entrance of micro/nano pores to withstand the gas pressure, while it allows water to permeate with overcoming the flow resistance of pores; in contrast, hydrophobic membranes permit gas to penetrate but prevent water flow. These two kinds of membranes coupled with microchannels in cross-flow mode or dead-end mode can separate gas/water in microscale. The separation in cross-flow mode can achieve relative high water permeate flow rate, while the separation in dead-end mode can completely separate gas/water segments in a single operation step. The membrane-based separation method has low cost, easy integration into microfludics channels, design flexibility with two configuration modes (cross-flow and dead-end).     

TSVM-HMM: Transductive SVM based hidden Markov model for automatic image annotation

Automatic image annotation (AIA) is an effective technology to improve the performance of image retrieval. In this paper, we propose a novel AIA scheme based on hidden Markov model (HMM). Compared with the previous HMM-based annotation methods, SVM based semi-supervised learning, i.e. transductive SVM (TSVM), is triggered out for remarkably boosting the reliability of HMM with less users’ labeling effort involved (denoted by TSVM-HMM). This guarantees that the proposed TSVM-HMM based annotation scheme integrates the discriminative classification with the generative model to mutually complete their advantages. In addition, not only the relevance model between the visual content of images and the textual keywords but also the property of keyword correlation is exploited in the proposed AIA scheme. Particularly, to establish an enhanced correlation network among keywords, both co-occurrence based and WordNet based correlation techniques are well fused and are able to be helpful for benefiting from each other. The final experimental results reveal that the better annotation performance can be achieved at less labeled training images.     

Rough set-based heuristic hybrid recognizer and its application in fault diagnosis

Rough set theory (RS) has been a topic of general interest in the field of knowledge discovery and pattern recognition. Machine learning algorithms are known to degrade in performance when faced with many features (sometimes attributes) that are not necessary for rule discovery. Many methods for selecting a subset of features have been proposed. However, only one method cannot handle the complex system with many attributes or features, so a hybrid mechanism is proposed based on rough set integrating artificial neural network (Rough-ANN) for feature selection in pattern recognition. RS-based attributes reduction as the preprocessor can decrease the inputs of the NN and improve the speed of training. So the sensitivity of rough set to noise can be avoided and the system’s robustness is to be improved. A RS-based heuristic algorithm is proposed for feature selection. The approach can select an optimal subset of features quickly and effectively from a large database with a lot of features. Moreover, the validity of the proposed hybrid recognizer and solution is verified by the application of practical experiments and fault diagnosis in industrial process.     

数字式涡街流量计应用中关键问题的研究

对基于谱分析的数字式涡街流量计在应用中响应速度比较慢及其在小流量或小口径时流量计输出波动两个问题进行了深入分析.采用设置门限值的方法提高了系统响应速度.对频谱分析结果进行多次为0判断,解决了系统输出断续问题.通过对频谱分析结果的限幅,在平均时去掉超过标准差的频率值,并去掉最大值和最小值,对平均结果进行第二次平均的方法减小了系统输出的波动,提高了流量计输出稳定性.     

直角式智能弯管流量计的实验研究及开发

研究并开发了一种新型的流量测量直角弯头结构,探索其用作差压流量仪表差压发生器的可能性.在实验室模拟条件下,研究了不同参数条件下流量与压差的关系,并拟合了曲线和回归方程,同时研究了雷诺数和流量系数的关系.设计了数据单片机采集和处理系统,实现了流量仪表的智能化,具有工程实用价值.     

新型智能照明控制系统的设计与验证

针对当今照明控制系统对环境照度变化响应比较慢的问题,提出了一种新型的智能照明控制系统。该系统采用可视光通信技术,并在照明设备和照度传感器之间建立直接通信,用来加快环境照度调节的速度。为了使该系统的控制更加精准,又采用了基于相关性系数的自适应邻域算法,对新的环境照度进行智能推断。实验结果表明,该系统可以在短时间内将测试地点的照度达到新的目标值。     

基于模式驱动和模糊查询的模式发现方法

在蛋白质序列的比对研究中,拥有相似模式的蛋白质常常具有相似的功能.通过已知的蛋白质序列模式可以很方便地对新蛋白质序列的功能结构进行研究和确认.蛋白质序列的发现已成为一个很有意义的题目.对基于模式驱动Pratt算法进行改进以提高其效率,在原来基础上引入模糊查询方法,能够更为快捷地从互不相关的蛋白质序列集合中找出最具代表性的蛋白质模式.