基于FPGA的同步时钟报文检测电路的设计

时钟同步技术是解决基于网络的分布式测控系统完成同步测控任务的关键技术,IEEE-1588协议是一种应用于分布式测量和控制系统中的精准时钟同步协议.提出了一种基于IEEE-1588协议在以太网物理层和MAC层之间的介质无关接口(MII/RMII)处检测同步报文的策略和实现精确时间标记方案[1],在此硬件支持方案和方法的基础之上,充分利用FPGA宏模块资源采用较为简便实用的方法设计实现了同步报文检测电路,该部分电路的设计是采用硬件时间标记方案实现IEEE1588高精度时钟同步的基础.在QuartsII 7.2平台下对设计电路进行优化综合和时序仿真,通过在线实时检测验证了电路设计的正确性.初步验证结果表明设计达到课题要求,应用性能良好.     

基于模式映射的GML文档存储

随着地理信息系统GIS(Geography Markup Language)的广泛应用,GML己经成为事实上的空间数据编码、传输、共享和发布的一种国际标准。近年来,大量GML数据以文档形式出现,对如何高效地存储和管理GML数据提出了新的挑战。根据GML文档的特点,提出了一种基于模式映射的存储方法。首先,根据映射规则将GML模式生成对象-关系数据库模式;其次,解析GML文档并根据映射信息构造相应的SQL语句,将数据存储于数据库。实验表明,提出的存储方法是可行、高效的。     

Pricing and inventory management in a system with multiple competing retailers under (r, Q) policies

We consider a multi-retailer system operated on an infinite horizon, in which each retailer faces stochastic demand following a Poisson process and adopts a continuous-review (r, Q) policy for replenishing inventory to satisfy customer demand. The system involves decisions of pricing and inventory management with the goal of maximizing profit, which equals the sales revenue minus the purchase and inventory costs. Taking Cournot competition into account, models are formulated to optimize simultaneously the expected sales volumes and (r, Q) policies of all retailers. An efficient approach is proposed to calculate the approximate inventory cost. Based on this approach, solution methods for centralized and decentralized scenarios are developed. A great number of numerical computations are provided to evaluate the efficiency of the solution methods, and their performance in the two scenarios. Moreover, system performance under sequential decisions (first pricing and then inventory management) is also investigated.     

Identifying mislabeled training data with the aid of unlabeled data

This paper presents a new approach for identifying and eliminating mislabeled training instances for supervised learning algorithms. The novelty of this approach lies in the using of unlabeled instances to aid the detection of mislabeled training instances. This is in contrast with existing methods which rely upon only the labeled training instances. Our approach is straightforward and can be applied to many existing noise detection methods with only marginal modifications on them as required. To assess the benefit of our approach, we choose two popular noise detection methods: majority filtering (MF) and consensus filtering (CF). MFAUD/CFAUD is the new proposed variant of MF/CF which relies on our approach and denotes majority/consensus filtering with the aid of unlabeled data. Empirical study validates the superiority of our approach and shows that MFAUD and CFAUD can significantly improve the performances of MF and CF under different noise ratios and labeled ratios. In addition, the improvement is more remarkable when the noise ratio is greater.     

Advancements in technology and design of NEMS vector hydrophone

This paper reports on recent developments to improve the performance of hair vector hydrophone by means of several technological advancements in the fabrication procedures and corresponding sensor design. With fish’s lateral line organs as prototypes, NEMS (Nano-Electromechanical System) vector hydrophone with directivity has been designed. This paper describes the meso-piezoresistance effect of resonant tunneling thin-film, and the NEMS hydrophone based on this effect is highly sensitive and small size. The application of bionics structure may improve the low-frequency sensitivity of hydrophone. The calibration test shows that NEMS vector hydrophone’s receiving sensitivity is up to −170 dB (0dB = 1 V/μPa), has a good directional pattern in the form of “8” shape. The sea test shows that the direction of target can be detected by single NEMS vector hydrophone. In the anechoic tank, it has been verified that NEMS vector hydrophone can track the trajectory of the moving target.     

Embedded simulation on a multiprocessor job scheduling system with inspection

This paper first develops architecture for a multiprocessor job scheduling system with an embedded simulation technique. The architecture provides a shell for applications that are characterized by two scheduling policies, a heuristic algorithm policy and a First-In-First-Out (FIFO) policy. These policies are implemented in the simulation model by using the embedded technique. The paper evaluates these two policies using the queue length, waiting time and flow time as the criteria to compare the performance of these two scheduling policies. Next we designed two simulation situations using two different real world applications. The purpose is to examine the performances of multiprocessor systems with and without inspection operations and two different scheduling policies. The two applications, berth allocation for the container terminal operations and production scheduling arrangement in an Original Equipment Manufacturer (OEM) power supply factory, are studied. The final results show that a proper scheduling policy will perform better than the traditional FIFO approach for a multiprocessor system. Our study also provides guidelines on balancing a system with the addition of a final inspection activity.     

ALTDSE: An Arnoldi–Lanczos program to solve the time-dependent Schrödinger equation

We describe a general ab initio and non-perturbative method to solve the time-dependent Schrödinger equation (TDSE) for the interaction of a strong attosecond laser pulse with a general atom. While the field-free Hamiltonian and the dipole matrices may be generated using an arbitrary primitive basis, they are assumed to have been transformed to the eigenbasis of the problem before the solution of the TDSE is propagated in time using the Arnoldi–Lanczos method. Probabilities for survival of the ground state, excitation, and single ionization can be extracted from the propagated wavefunction.

Program summary

Program title: ALTDSECatalogue identifier: AEDM_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDM_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 2154No. of bytes in distributed program, including test data, etc.: 30 827Distribution format: tar.gzProgramming language: Fortran 95. [A Fortran 2003 call to “flush” is used to simplify monitoring the output file during execution. If this function is not available, these statements should be commented out.].Computer: Shared-memory machinesOperating system: Linux, OpenMPHas the code been vectorized or parallelized?: YesRAM: Several Gb, depending on matrix size and number of processorsSupplementary material: To facilitate the execution of the program, Hamiltonian field-free and dipole matrix files are provided.Classification: 2.5External routines: LAPACK, BLASNature of problem: We describe a computer program for a general ab initio and non-perturbative method to solve the time-dependent Schrödinger equation (TDSE) for the interaction of a strong attosecond laser pulse with a general atom [1,2]. The probabilities for survival of the initial state, excitation of discrete states, and single ionization due to multi-photon processes can be obtained.Solution method: The solution of the TDSE is propagated in time using the Arnoldi–Lanczos method. The field-free Hamiltonian and the dipole matrices, originally generated in an arbitrary basis (e.g., the flexible B-spline R-matrix (BSR) method with non-orthogonal orbitals [3]), must be provided in the eigenbasis of the problem as input.Restrictions: The present program is restricted to a ¹S^e initial state and linearly polarized light. This is the most common situation experimentally, but a generalization is straightforward.Running time: Several hours, depending on the number of threads used.References: [1] X. Guan, O. Zatsarinny, K. Bartschat, B.I. Schneider, J. Feist, C.J. Noble, Phys. Rev. A 76 (2007) 053411. [2] X. Guan, C.J. Noble, O. Zatsarinny, K. Bartschat, B.I. Schneider, Phys. Rev. A 78 (2008) 053402. [3] O. Zatsarinny, Comput. Phys. Comm. 174 (2006) 273.     

Nearest neighbor editing aided by unlabeled data

This paper proposes a novel method for nearest neighbor editing. Nearest neighbor editing aims to increase the classifier’s generalization ability by removing noisy instances from the training set. Traditionally nearest neighbor editing edits (removes/retains) each instance by the voting of the instances in the training set (labeled instances). However, motivated by semi-supervised learning, we propose a novel editing methodology which edits each training instance by the voting of all the available instances (both labeled and unlabeled instances). We expect that the editing performance could be boosted by appropriately using unlabeled data. Our idea relies on the fact that in many applications, in addition to the training instances, many unlabeled instances are also available since they do not need human annotation effort. Three popular data editing methods, including edited nearest neighbor, repeated edited nearest neighbor and All k-NN are adopted to verify our idea. They are tested on a set of UCI data sets. Experimental results indicate that all the three editing methods can achieve improved performance with the aid of unlabeled data. Moreover, the improvement is more remarkable when the ratio of training data to unlabeled data is small.     

Automatic face detection in video sequences using local normalization and optimal adaptive correlation techniques

Automatic human face detection from video sequences is an important component of intelligent human computer interaction systems for video surveillance, face recognition, emotion recognition and face database management. This paper proposes an automatic and robust method to detect human faces from video sequences that combines feature extraction and face detection based on local normalization, Gabor wavelets transform and Adaboost algorithm. The key step and the main contribution of this work is the incorporation of a normalization technique based on local histograms with optimal adaptive correlation (OAC) technique to alleviate a common problem in conventional face detection methods: inconsistent performance due to sensitivity to variation illuminations such as local shadowing, noise and occlusion. The approach uses a cascade of classifiers to adopt a coarse-to-fine strategy for achieving higher detection rates with lower false positives. The experimental results demonstrate a significant performance improvement gains and achieved by local normalization over methods without normalizations in real video sequences with a wide range of facial variations in color, position, scale, and varying lighting conditions.     

Design and implementation of light-weight mobile multicast for fast MIPv6

Mobile multicast is a research hotspot and can provide many applications. Some mobile multicast schemes have been proposed, but most of them introduce new entities and study construction algorithms of the dynamic multicast delivery structure which is heavyweight for wireless devices. In this paper, we propose a light-weight mobile multicast (LMM) scheme for Fast Mobile IPv6 which reduces the redundant operational overhead by simplifying multicast listener discovery (MLD) proxying. The LMM scheme implements simplified MLD proxying function on home agent to reduce the complicated multicast routing protocol and modifies MLD host part function on mobile node to reduce the multicast membership messages interaction. In order to solve the tunnel convergence problem, LMM also introduces a multicast tunnel combination and reconstruction algorithm. We set up a test-bed to evaluate the performance of LMM, and compare it with other mobile multicast schemes. The experimental results show that LMM reduces the multicast disruption time at handover. Based on the experimental results, we analyze the cost of LMM, and the results show that it has lower protocol cost than other schemes.