无线传感器网络整合时钟同步方案

针对多数无线传感器网络时钟同步方案存在的仅纠正时钟偏移问题,提出一种新的解决方案,整合时钟偏移同步和时钟速率同步,通过3个连续的消息传输实现单跳同步,采用分层的生成树实现多跳同步。仿真实验结果表明,与现有的同步方案比较,该方案的同步错误更小,能够获得更长的再同步周期。     

Optimal replacement policy for a two-dissimilar-component cold standby system with different repair actions

In this paper, a cold standby repairable system consisting of two dissimilar components and one repairman is studied. When failures occur, the repair of both component 1 and component 2 are not ‘as good as new’. The consecutive operating times of component 1 after repair constitute a decreasing geometric process, while the repair times of component 1 are independent and identically distributed. For component 2, its failure is rectified by minimal repair, and the repair time is negligible. Component 1 has priority in use when both components are good. The replacement policy N is based on the failure number of component 1. Under policy N, we derive the explicit expression of the long-run average cost rate C(N) as well as the average number of repairs of component 2 before the system replaced. The optimal replacement policy N*, which minimises the long-run average cost rate C(N), is obtained theoretically. If the failure rate r(t) of component 2 is increasing, the existence and uniqueness of the optimal policy N* is also proved. Finally, a numerical example is given to validate the developed theoretical model. Some sensitivity analyses are provided to show the influence of some parameters, such as the costs for replacement and repair, and the parameters of the lifetime and repair time distributions of both components, to the optimal replacement policy N* and corresponding average cost rate C(N*).     

Creating the Enabling Environment for More Transparent and Better-resourced Local Governments: A Case of E-taxation in the Philippines

This research joins the growing body of literature that advocates for the use of information and communication technology (ICT) in local governance more particularly in public financial management. Using a case study in Bohol, a province in the Philippines, this paper discusses the impact of ICT on local revenue generation by analyzing both quantitative and qualitative data from 15 municipalities which used e-taxation. This paper argues that the use of ICT can make possible more transparent and accountable revenue generation systems to benefit both government and taxpayers. However, these results are differentiated depending on the level of political leadership, the nature of articulation of the demand for ICT use, the ratio of benefit against cost, and the availability of technical skills and resources at the sub-national level. It is within this context that an eco-system analysis is argued to be useful in analyzing how ICT can be adopted, scaled, and used by sub-national governments to achieve better governance.     

On detecting active worms with varying scan rate

Active worms have posed a major security threat to the Internet and many research efforts have focused on them. However, defending against them remains challenging due to their continuous evolution. In this paper, we study a new class of defense-oriented evolved worms, the Varying Scan Rate worm (the VSR worm in short). In order to circumvent detection by existing worm detection schemes, the VSR worm deliberately varies its scan rate according to these schemes’ weaknesses. To counteract the VSR worm, we design a new worm-detection scheme, the attack-target Distribution Entropy-based Dynamic detection scheme (DED detection for short). DED detection utilizes the attack-target distribution and robust statistical feature in conjunction with dynamic decision adaptation to distinguish worm-scan traffic from non-worm-scan traffic. We present a comparatively complete space of detection schemes and conduct extensive performance evaluations on the DED detection scheme compared with other schemes, using real-world Internet traces as background scan traffic. Our data clearly demonstrate the effectiveness of the DED detection scheme in detecting both the VSR worm and the traditional worm.     

On the estimation of adequate test set size using fault failure rates

Test set size in terms of the number of test cases is an important consideration when testing software systems. Using too few test cases might result in poor fault detection and using too many might be very expensive and suffer from redundancy. We define the failure rate of a program as the fraction of test cases in an available test pool that result in execution failure on that program. This paper investigates the relationship between failure rates and the number of test cases required to detect the faults. Our experiments based on 11 sets of C programs suggest that an accurate estimation of failure rates of potential fault(s) in a program can provide a reliable estimate of adequate test set size with respect to fault detection and should therefore be one of the factors kept in mind during test set construction. Furthermore, the model proposed herein is fairly robust to incorrect estimations in failure rates and can still provide good predictive quality. Experiments are also performed to observe the relationship between multiple faults present in the same program using the concept of a failure rate. When predicting the effectiveness against a program with multiple faults, results indicate that not knowing the number of faults in the program is not a significant concern, as the predictive quality is typically not affected adversely.     

A Complex View of Barycentric Mappings

Barycentric coordinates are very popular for interpolating data values on polyhedral domains. It has been recently shown that expressing them as complex functions has various advantages when interpolating two‐dimensional data in the plane, and in particular for holomorphic maps. We extend and generalize these results by investigating the complex representation of real‐valued barycentric coordinates, when applied to planar domains. We show how the construction for generating real‐valued barycentric coordinates from a given weight function can be applied to generating complex‐valued coordinates, thus deriving complex expressions for the classical barycentric coordinates: Wachspress, mean value, and discrete harmonic. Furthermore, we show that a complex barycentric map admits the intuitive interpretation as a complex‐weighted combination of edge‐to‐edge similarity transformations, allowing the design of “home‐made” barycentric maps with desirable properties. Thus, using the tools of complex analysis, we provide a methodology for analyzing existing barycentric mappings, as well as designing new ones.     

On the implication problem for cardinality constraints and functional dependencies

In database design, integrity constraints are used to express database semantics. They specify the way by that the elements of a database are associated to each other. The implication problem asks whether a given set of constraints entails further constraints. In this paper, we study the finite implication problem for cardinality constraints. Our main result is a complete characterization of closed sets of cardinality constraints. Similar results are obtained for constraint sets containing cardinality constraints, but also key and functional dependencies. Moreover, we construct Armstrong databases for these constraint sets, which are of special interest for example-based deduction in database design.     

A Constraint-Based Approach for Deriving 3-D Structures of Cyclic Polypeptides

This paper presents an hybrid algorithm for deriving 3-D structures of cyclic polypeptides. The algorithm combines constraint-based techniques with the most widely used methods for non-cyclic polypeptides. The empirical results demonstrate that the proposed hybrid algorithm outperforms traditional methods especially with respect to running times.     

我国GNP的单位根不确定性研究

对于一个实际的时间序列数据,我们并不知道其真正的数据生成过程,只能通过假设和基于假设的统计推断来确定。本文利用蒙特卡罗模拟进行有限样本的ADF检验。结果表明,当原假设是存在单位根,备择假设是趋势稳定时,ADF检验的势很低。这意味着,我国GNP存在单位根是不确定的。     

Towards the next generation of artificial neural networks for civil engineering

The purpose of this paper is to stimulate interest within the civil engineering research community for developing the next generation of applied artificial neural networks. In particular, it identifies what the next generation of these devices needs to achieve, and provides direction in terms of how their development may proceed. An analysis of the current situation indicates that progress in the development of artificial neural network applications has largely stagnated. Suggestions are made for advancing the field to the next level of sophistication and application, using genetic algorithms and related techniques. It is shown that this approach will require the design of some very sophisticated genetic coding mechanisms in order to develop the required higher-order network structures, and will utilize development mechanisms observed in nature such as growth, self-organization, and multi-stage objective functions. The capabilities of such an approach and the way in which they can be achieved are explored with reference to the problems of: (a) determining truck attributes from the strain envelopes they induce in structural members when crossing a bridge, and; (b) developing a decision support system for dynamic control of industrialized manufacturing of houses.