技术防范电信欠费

电信用户欠费是当今电信业者面临的日益严峻的问题,本文主要阐述如何利用电信企业拥有的数据仓库,依靠技术手段分析追踪和预防用户异常行为,达到防范电信欠费的效果。     

An energy-efficient real-time scheduling scheme on dual-channel networks

The recent evolution of wireless sensor networks have yielded a demand to improve energy-efficient scheduling algorithms and energy-efficient medium access protocols. This paper proposes an energy-efficient real-time scheduling scheme that reduces power consumption and network errors on dual channel networks. The proposed scheme is based on a dynamic modulation scaling scheme which can scale the number of bits per symbol and a switching scheme which can swap the polling schedule between channels. Built on top of EDF scheduling policy, the proposed scheme enhances the power performance without violating the constraints of real-time streams. The simulation results show that the proposed scheme enhances fault-tolerance and reduces power consumption.     

基于动态贝叶斯网络的社交圈归属匹配模型

为了帮助社交网中新成员寻找与之最为合适的社交圈,尝试采用动态贝叶斯网（DBN）理论解决社交网分析应用中成员（节点）与社交圈（集合）的匹配问题。将圈内成员个人的多项兴趣爱好程度作为描述社交圈基本属性的特征向量,对每一类圈子建立了带有辅助信息形式的DBN模型,求解最大输出概率即为最佳匹配对象。结果表明,在客观测试和主观评价两方面,该模型都收到了较为满意的结果。     

Dynamic response of Kevlar®29/epoxy laminates under projectile impact-experimental investigation

This authors of this article investigated the dynamic response of woven Kevlar®29/epoxy laminates subjected to the impact loading. The cylindrical aluminum foam projectile and steel projectile were used to exert the impulse on the laminates. Deformation/failure modes, deflections, strain histories, and failure mechanisms were obtained and discussed. The results showed that with the high toughness of Kevlar fiber, the deformation modes of the laminates exhibited some characteristics similar to the metal panel, such as large global deformation. The failure mechanisms like matrix failure, fiber splitting, and fibrillation were observed. These micron failures led to the macroscopic delamination and fracture of the laminates.     

Erosion coupled dynamic mesh analysis for location of maximum erosion in 90-degree bends for gas-solid flows

The progressive change in the surface geometry of the component due to erosive wear affects the correct estimation of erosive wear performance and service life of the components handling particulate flows. The current study focuses on determining the change in the location of higher erosion on the bend surface during the pneumatic conveying of solids with continuous geometric modification due to erosive wear. Computational fluid dynamics (CFD) based erosion-coupled dynamic mesh methodology is adopted to simulate the time-dependent surface modification of the 90° bend geometry due to erosive wear. Available experimental data are used to validate the numerical results. Further, the erosion distribution and the location of the maximum erosion for different flow velocities, particle sizes, and bend radius ratios with the increase in solid throughput are investigated. It has been found that the modification in the bend geometry due to erosion influences the location of the maximum erosion. The increase in thickness loss due to erosion increases the variation in the location of the maximum erosion. Furthermore, an equation for predicting the location of maximum erosion of bend geometry is obtained based on the bend radius ratio and the thickness loss.     

An improved method for voice pathology detection by means of a HMM-based feature space transformation

This paper presents new a feature transformation technique applied to improve the screening accuracy for the automatic detection of pathological voices. The statistical transformation is based on Hidden Markov Models, obtaining a transformation and classification stage simultaneously and adjusting the parameters of the model with a criterion that minimizes the classification error. The original feature vectors are built up using classic short-term noise parameters and mel-frequency cepstral coefficients. With respect to conventional approaches found in the literature of automatic detection of pathological voices, the proposed feature space transformation technique demonstrates a significant improvement of the performance with no addition of new features to the original input space. In view of the results, it is expected that this technique could provide good results in other areas such as speaker verification and/or identification.     

Discussions of worker ants’ rule-based CHC dealing with changing environments

Contrary to popular belief, biologists discovered that worker ants are really not all hardworking. It has been found that in three separate 30-strong colonies of black Japanese ants (Myrmecina nipponica), about 20% of worker ants are diligent, 60% are ordinary, and 20% are lazy. That is called 20:60:20 rule. Though they are lazy, biologists suggested that lazy worker ants could be contributing something to the colony that is yet to be determined. In our last research, we used CHC (cross generational elitist selection, heterogeneous recombination, and cataclysmic mutation) with the worker ants’ rule (WACHC) aiming at solving optimization problems in changing environments. CHC is a nontraditional genetic algorithm (GA) which combines a conservative selection strategy that always preserves the best individuals found so far with a radical (highly disruptive) recombination operator. In our last research, we verified that WACHC performs better than CHC in only one case of fully changing environment. In this paper, we further discuss our proposed WACHC dealing with changing environment problems with varying degree of difficulty, compare our proposal with hypermutation GA which is also proposed for dealing with changing environment problems, and discuss the difference between our proposal and ant colony optimization algorithms.     

Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports

The problem of transporting patients or elderly people has been widely studied in literature and is usually modeled as a dial-a-ride problem (DARP). In this paper we analyze the corresponding problem arising in the daily operation of the Austrian Red Cross. This nongovernmental organization is the largest organization performing patient transportation in Austria. The aim is to design vehicle routes to serve partially dynamic transportation requests using a fixed vehicle fleet. Each request requires transportation from a patient's home location to a hospital (outbound request) or back home from the hospital (inbound request). Some of these requests are known in advance. Some requests are dynamic in the sense that they appear during the day without any prior information. Finally, some inbound requests are stochastic. More precisely, with a certain probability each outbound request causes a corresponding inbound request on the same day. Some stochastic information about these return transports is available from historical data. The purpose of this study is to investigate, whether using this information in designing the routes has a significant positive effect on the solution quality. The problem is modeled as a dynamic stochastic dial-a-ride problem with expected return transports. We propose four different modifications of metaheuristic solution approaches for this problem. In detail, we test dynamic versions of variable neighborhood search (VNS) and stochastic VNS (S-VNS) as well as modified versions of the multiple plan approach (MPA) and the multiple scenario approach (MSA). Tests are performed using 12 sets of test instances based on a real road network. Various demand scenarios are generated based on the available real data. Results show that using the stochastic information on return transports leads to average improvements of around 15%. Moreover, improvements of up to 41% can be achieved for some test instances.     

Solving single-product economic lot-sizing problem with non-increasing setup cost,constant capacity and convex inventory cost in O(N log N) time

This paper considers an economic lot sizing model with constant capacity, non-increasing setup cost, and convex inventory cost function. Algorithms with computational time of O(N×TD_N)have been developed for solving the model, where N is the number of planning periods and TD_N is the total demand. This study partially characterizes the optimal planning structure of the model. A new efficient algorithm with computational time of O(N log N) has also been developed based on the partial optimal structure. Moreover, computational study demonstrates that the new algorithm is efficient.     

A comparative study on the performance of dissortative mating and immigrants-based strategies for evolutionary dynamic optimization

Traditional Genetic Algorithms (GAs) mating schemes select individuals for crossover independently of their genotypic or phenotypic similarities. In Nature, this behavior is known as random mating. However, non-random protocols, in which individuals mate according to their kinship or likeness, are more common in natural species. Previous studies indicate that when applied to GAs, dissortative mating - a type of non-random mating in which individuals are chosen according to their similarities - may improve their performance (on both speed and reliability). Dissortative mating maintains genetic diversity at a higher level during the run, a fact that is frequently observed as a possible cause of dissortative GAs’ ability to escape local optima. Dynamic optimization demands a special attention when designing and tuning a GA, since diversity plays an even more crucial role than it does when tackling static ones. This paper investigates the behavior of the Adaptive Dissortative Mating GA (ADMGA) in dynamic problems and compares it to GAs based on random immigrants. ADMGA selects parents according to their Hamming distance, via a self-adjustable threshold value. The method, by keeping population diversity during the run, provides an effective means to deal with dynamic problems. Tests conducted with dynamic trap functions and dynamic versions of Road Royal and knapsack problems indicate that ADMGA is able to outperform other GAs on a wide range of tests, being particularly effective when the frequency of changes is low. Specifically, ADMGA outperforms two state-of-the-art algorithms on many dynamic scenarios. In addition, and unlike preceding dissortative mating GAs and other evolutionary techniques for dynamic optimization, ADMGA self-regulates the intensity of the mating restrictions and does not increase the set of parameters in GAs, thus being easier to tune.