基于BP神经网络的手势识别系统

给出了采用ADXL335加速度传感器来采集五个手指和手背的加速度三轴信息,并通过ZigBee无线网络传输来提取手势特征量,同时利用BP神经网络算法进行误差分析来实现手势识别的设计方法。最后,通过Matlab验证,结果表明,该系统在测试中识别率较高,系统稳定。     

A grid-based clustering algorithm for wild bird distribution

Advanced satellite tracking technologies provide biologists with long-term location sequence data to understand movement of wild birds then to find explicit correlation between dynamics of migratory birds and the spread of avian influenza. In this paper, we propose a hierarchical clustering algorithm based on a recursive grid partition and kernel density estimation (KDE) to hierarchically identify wild bird habitats with different densities. We hierarchically cluster the GPS data by taking into account the following observations: 1) the habitat variation on a variety of geospatial scales; 2) the spatial variation of the activity patterns of birds in different stages of the migration cycle. In addition, we measure the site fidelity of wild birds based on clustering. To assess effectiveness, we have evaluated our system using a large-scale GPS dataset collected from 59 birds over three years. As a result, our approach can identify the hierarchical habitats and distribution of wild birds more efficiently than several commonly used algorithms such as DBSCAN and DENCLUE.     

校园网安全防护的研究

目的:探讨校园网组建起来后,所面临的各种问题,并提供有效的解决方案。方法:从网络的结构性,网络的可靠性,网络的安全性三个方面进行分析,并提出相应的优化策略。结果:提高了校园网运行的可靠性、安全性和效率。结论:采用路径分析、关联规则待方法对网络进行优化,可以提高校园网的运行效率以及安全性。     

A distributed collaborative product design environment based on semantic norm model and role-based access control

With the boom of Internet Technology, it becomes possible to combine designers from different disciplines into one team to support product design globally. In this paper, a distributed collaborative product design environment is presented to support top-down process oriented product design. In conceptual design stage, the artifact is managed by semantic norm model (SNM). In SNM, the designers can define virtual components at early design stage and instantiate those components at later detailed design stage. By role-based access control (RBAC), different roles with corresponding permissions could be assigned to distributed designers, and the designers could concurrently modify different components of the product relevant to his or her roles. Based on the SNM and RBAC system, a distributed collaborative product design environment is developed and the top-down oriented product design process is demonstrated.     

How does organisational absorptive capacity matter in the assimilation of enterprise information systems?

Extant literature offers two mostly distinct perspectives on enterprise systems assimilation – driven either by internal expertise and learning capability or by external institutional pressures. This study combines the two perspectives and subscribes to the view that organisations’ learning capability moderates their acquiescence to institutional pressures. The study then anchors organisational learning capability to the concept of absorptive capacity and proposes that its two dimensions – potential absorptive capacity (PACAP) and realised absorptive capacity (RACAP) – affect enterprise systems assimilation through different pathways. Our survey‐based empirical study of Enterprise Resource Planning (ERP) systems in the post‐implementation stage reveals that while both PACAP and RACAP have a positive direct impact on assimilation, PACAP positively moderates the impact of mimetic (institutional) pressures, but not normative (institutional) pressures, on assimilation; whereas RACAP positively moderates the impact of normative pressures, but not mimetic pressures, on assimilation. Thus, our theoretical contribution lies in understanding the distinct ways in which PACAP and RACAP moderate the influence of external institutional pressures on enterprise systems assimilation.     

Dynamic-cost-reward connection admission control for maximizing system reward in 4G wireless multihop relaying networks

The 3GPP Long Term Evolution (LTE) Advanced and IEEE 802.16j specifications adopt the mobile multi-hop relaying (MMR) mechanism for enlarging service area and improving wireless transmission quality simultaneously. By deploying different types of Relay Stations (RSs), MMR can bring some advantages: (1) the signal fading and wireless interference of a single long wireless link is improved obviously; (2) the ranges of wireless access and relay area are extended, etc. MMR can offer a high data rate transmission for packet services and can increase system capacity. Note that MMR can be applied to the public transportation system, e.g., equipped a mobile RS on a high-speed train. A mobile RS handoff initializes a multiple handoff requests of different types of traffics. It becomes as a critical handoff issue in 4G MMR. Thus, the MMR handoff needs a new efficient Connection Admission Control (CAC) to guarantee qualities for various types of traffics and to increase system revenue. However, traditional CACs are difficult to fulfill the objectives. This paper thus proposes the Dynamic Cost-Reward-based (DCR) CAC that consists of two key mechanisms: (1) adopting a Markov decision process-based (MDP) cost function and (2) providing different reward functions for different types of nodes and various types of connection. Additionally, a mathematical analytical Markov chain is modeled for DCR. The simulation results are very close to the analysis results, which justifies the correctness of the analytical model. Numerical results demonstrate that DCA outperforms the compared CACs in the probabilities of new blocking, MS-handoff, and RS-handoff dropping, FRL, GoS, and system reward.     

VMPlanner: Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers

In recent years, the power costs of cloud data centers have become a practical concern and have attracted significant attention from both industry and academia. Most of the early works on data center energy efficiency have focused on the biggest power consumers (i.e., computer servers and cooling systems), yet without taking the networking part into consideration. However, recent studies have revealed that the network elements consume 10–20% of the total power in the data center, which poses a great challenge to effectively reducing network power cost without adversely affecting overall network performance. Based on the analysis on topology characteristics and traffic patterns of data centers, this paper presents a novel approach, called VMPlanner, for network power reduction in the virtualization-based data centers. The basic idea of VMPlanner is to optimize both virtual machine placement and traffic flow routing so as to turn off as many unneeded network elements as possible for power saving. We formulate the optimization problem, analyze its hardness, and solve it by designing VMPlanner as a stepwise optimization approach with three approximation algorithms. VMPlanner is implemented and evaluated in a simulated environment with traffic traces collected from a data center test-bed, and the experiment results illustrate the efficacy and efficiency of this approach.     

Transductive multi-distance learning for video search

Graph-based semi-supervised learning approaches have been proven effective and efficient in solving the problem of the inefficiency of labeled training data in many real-world application areas, such as video annotation. As a significant factor of these algorithms, however, pair-wise similarity metric of samples has not been fully investigated. Specifically, for existing approaches, the estimation of pair-wise similarity between two samples relies on the spatial property of video data. On the other hand, temporal property, an essential characteristic of video data, is not embedded into the pair-wise similarity measure. Accordingly, in this paper, a novel framework for video annotation, called Joint Spatio-Temporal Correlation Learning (JSTCL) is proposed. This framework is characterized by simultaneously taking into account both the spatial and temporal property of video data to improve the estimation of pair-wise similarity. We apply the proposed framework to video annotation and report superior performance compared to key existing approaches over the benchmark TRECVID data set.     

Effect of Ce(3+) on soluble microbial products production in anaerobic granular sludge digestion

Upflow anaerobic sludge bed reactors fed on glucose were used to investigate the effects of Ce(3+) on soluble microbial products (SMP) production, which is the majority of the residual chemical oxygen demand present in the effluent. It was found that Ce(3+) concentration of 0.05 mg/L had no significant effect on the amount of SMP production, whereas that of 1 mg/L led to the increase in SMP production. The molecular-weight distribution and carbohydrate analysis indicated that an increase in SMP production may be partly attributed to the release of extracellular polymeric substances (EPS) into the bulk solution resulted from cerium toxicity, and the nucleic acids analysis suggested that increased cell lysis also contributed to SMP accumulation in the presence of Ce(3+). The increase in SMP production in the presence of Ce(3+) is possibly a consequence of the release of EPS and increased cell lysis due to cerium toxicity.     

Effective degradation of para-chloronitrobenzene through a sequential treatment using zero-valent iron reduction and Fenton oxidation

In this study, zero-valent iron (ZVI) was used to pretreat para-chloronitrobenzene (p-CNB), and the major product was para-chloroaniline (p-CAN). By adding H(2)O(2) directly, further p-CAN degradation can be attributed to Fenton oxidation because ferrous ions (Fe(2+)) released during the ZVI corrosion could be used as an activator for H(2)O(2) decomposition. In the reduction process, the reduction efficiency of p-CNB as well as Fe(2+) concentration increased with increasing iron dosage and decreasing solution pH. Under the optimal conditions, 25 mg L(-1) of p-CNB could be transformed in 3 h when initial solution pH was 3.0 and ZVI dosage was 2.0 g L(-1). A sufficient amount of Fe(2+) (50.4 mg L(-1)) was obtained after the above reaction to activate H(2)O(2). In the Fenton process, the oxidization of p-CAN was also more effective in acidic conditions and it increased with increasing H(2)O(2) concentration. The control experiments showed that the sequential treatment was more effective than Fenton oxidation alone in treating p-CNB wastewater since the removal rate of total organic carbon (TOC) was improved by about 34%. It suggested that the amino function group is more susceptible to oxidative radical attack than the nitro function group. Therefore, sequential treatment using zero-valent iron reduction followed by Fenton oxidation is a promising method for p-CNB degradation.