Modeling real-time communication systems: Practices and experiences in Motorola

Visual modeling languages and techniques have been increasingly adopted for software specification, design, development, and testing. With the major improvements of UML 2.0 and tools support, visual modeling technologies have significant potential for simplifying design, facilitating collaborations, and reducing development cost. In this paper, we describe our practices and experiences of applying visual modeling techniques to the design and development of real-time wireless communication systems within Motorola. A model-driven engineering approach of integrating visual modeling with development and validation is described. Results, issues, and our viewpoints are also discussed.     

Cuckoo search: recent advances and applications

Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and the same has been found to be efficient in solving global optimization problems. In this paper, we review the fundamental ideas of cuckoo search and the latest developments as well as its applications. We analyze the algorithm and gain insight into its search mechanisms and find out why it is efficient. We also discuss the essence of algorithms and its link to self-organizing systems, and finally, we propose some important topics for further research.     

A new method for texture fields synthesis: some applications to the study of human vision

We present a general method to synthesize a stochastic process from its a priori given second-order statistics. Some new results, including a new conjecture dealing with visual discrimination of stochastic texture fields, are also given.     

Industrial geometry: recent advances and applications in CAD

Industrial Geometry aims at unifying existing and developing new methods and algorithms for a variety of application areas with a strong geometric component. These include CAD, CAM, Geometric Modelling, Robotics, Computer Vision and Image Processing, Computer Graphics and Scientific Visualization. In this paper, Industrial Geometry is illustrated via the fruitful interplay of the areas indicated above in the context of novel solutions of CAD related, geometric optimization problems involving distance functions: approximation with general B-spline curves and surfaces or with subdivision surfaces, approximation with special surfaces for applications in architecture or manufacturing, approximate conversion from implicit to parametric (NURBS) representation, and registration problems for industrial inspection and 3D model generation from measurement data. Moreover, we describe a ‘feature sensitive’ metric on surfaces, whose definition relies on the concept of an image manifold, introduced into Computer Vision and Image Processing by Kimmel, Malladi and Sochen. This metric is sensitive to features such as smoothed edges, which are characterized by a significant deviation of the two principal curvatures. We illustrate its applications at hand of feature sensitive curve design on surfaces and local neighborhood definition and region growing as an aid in the segmentation process for reverse engineering of geometric objects.     

Nanotechnology advances and applications in information storage

A brief review of some applications of nanotechnology to information storage is given with the focus on self-assembled nanoporous alumina templates for patterned media.Ordered nanoporous alumina templates were fabricated by self-assembly technology. A two-step anodization process was also carried out to obtain templates with pores perpendicular to the substrate without removing the aluminum and barrier layer. Polycrystalline structure was observed with a grain size of about 2 μm in which the pores were almost perfect hexagonally ordered. The pore arrays exhibit different orientation along the boundaries of neighboring grains. Nanopatterning implemented by electron-beam lithography demonstrates the ability to write pores forming concentric circles with pore diameter as small as 50 nm.     

实时数据流聚类的研究新进展

实时数据流聚类是目前国际数据库和数据管理领域的新兴研究热点.综述了实时数据流聚类的最新研究进展,在介绍实时数据流聚类的相关理论和常用技术的基础上,对现有各种代表性算法的优势和不足进行了系统地分析,从处理速度、聚类形状、演化分析、高维性及噪声健壮性5个方面对算法的性能进行了比较.探讨了基于聚类的实时数据流演化分析方法及其局限性.最后展望了将来可能的研究方向.     

Recent advances in simultaneous localization and map-building using computer vision

Simultaneous localization and map-building (SLAM) continues to draw considerable attention in the robotics community due to the advantages it can offer in building autonomous robots. It examines the ability of an autonomous robot starting in an unknown environment to incrementally build an environment map and simultaneously localize itself within this map. Recent advances in computer vision have contributed a whole class of solutions for the challenge of SLAM. This paper surveys contemporary progress in SLAM algorithms, especially those using computer vision as main sensing means, i.e., visual SLAM. We categorize and introduce these visual SLAM techniques with four main frameworks: Kalman filter (KF)-based, particle filter (PF)-based, expectation-maximization (EM)-based and set membership-based schemes. Important topics of SLAM involving different frameworks are also presented. This article complements other surveys in this field by being current as well as reviewing a large body of research in the area of vision-based SLAM, which has not been covered. It clearly identifies the inherent relationship between the state estimation via the KF versus PF and EM techniques, all of which are derivations of Bayes rule. In addition to the probabilistic methods in other surveys, non-probabilistic approaches are also covered.     

Inhibitors and motivators for telework: some Finnish experiences

Nordic countries have traditionally been the forerunners in both usage of telecommunication and restructuring of working life. Both elements are strongly involved in telework so there might be a lesson to be learnt from Nordic telework projects. In this article four Finnish telework initiatives are studied. The reasons for starting them are sought and their results are evaluated. Further factors making the daily telework easier or more difficult are explicated. Conclusions are drawn from the cases, and their characteristics are compared with those of other European telework initiatives.     

Principles and applications of high-speed single-pixel imaging technology

Single-pixel imaging (SPI) technology has garnered great interest within the last decade because of its ability to record high-resolution images using a single-pixel detector. It has been applied to diverse fields, such as magnetic resonance imaging (MRI), aerospace remote sensing, terahertz photography, and hyperspectral imaging. Compared with conventional silicon-based cameras, single-pixel cameras (SPCs) can achieve image compression and operate over a much broader spectral range. However, the imaging speed of SPCs is governed by the response time of digital micromirror devices (DMDs) and the amount of compression of acquired images, leading to low (ms-level) temporal resolution. Consequently, it is particularly challenging for SPCs to investigate fast dynamic phenomena, which is required commonly in microscopy. Recently, a unique approach based on photonic time stretch (PTS) to achieve high-speed SPI has been reported. It achieves a frame rate far beyond that can be reached with conventional SPCs. In this paper, we first introduce the principles and applications of the PTS technique. Then the basic architecture of the high-speed SPI system is presented, and an imaging flow cytometer with high speed and high throughput is demonstrated experimentally. Finally, the limitations and potential applications of high-speed SPI are discussed.     

高速CMOS图像存储与实时显示系统设计

针对遥测系统图像单元存在数据量大、速度快、无法直接存储显示等问题,设计了一种高速图像存储与实时显示系统。系统以Spartan 6系列现场可编程门阵列(FPGA)作为核心处理器,使用Full模式Camera Link接口采集CMOS相机输出的图像数据,利用DDR3乒乓缓存技术将图像数据写入由SATA控制器组成的磁盘阵列中,并且通过千兆以太网接口将处理后的数据上传至计算机;图像数据采用抽帧以及降低分辨率的形式,将其转换为1 024×768像素的VGA分辨率格式,最后通过VGA接口对图像进行实时显示。实验结果表明,该系统能够对分辨率为2 048×2 048像素、帧频为150 f/s的高速图像数据进行长时间存储与实时显示。     

Context modeling in computer vision: techniques,implications, and applications

In recent years there has been a surge of interest in context modeling for numerous applications in computer vision. The basic motivation behind these diverse efforts is generally the same—attempting to enhance current image analysis technologies by incorporating information from outside the target object, including scene analysis as well as metadata. However, many different approaches and applications have been proposed, leading to a somewhat inchoate literature that can be difficult to navigate. The current paper provides a ‘roadmap’ of this new research, including a discussion of the basic motivation behind context-modeling, an overview of the most representative techniques, and a discussion of specific applications in which contextual modeling has been incorporated. This review is intended to introduce researchers in computer vision and image analysis to this increasingly important field as well as provide a reference for those who may wish to incorporate context modeling in their own work.     

Recent advances in feature selection and its applications

Feature selection is one of the key problems for machine learning and data mining. In this review paper, a brief historical background of the field is given, followed by a selection of challenges which are of particular current interests, such as feature selection for high-dimensional small sample size data, large-scale data, and secure feature selection. Along with these challenges, some hot topics for feature selection have emerged, e.g., stable feature selection, multi-view feature selection, distributed feature selection, multi-label feature selection, online feature selection, and adversarial feature selection. Then, the recent advances of these topics are surveyed in this paper. For each topic, the existing problems are analyzed, and then, current solutions to these problems are presented and discussed. Besides the topics, some representative applications of feature selection are also introduced, such as applications in bioinformatics, social media, and multimedia retrieval.     

基于FPGA和多DSP的高速视觉测量系统的研究

针对高速视觉测量系统数据处理速度快、数据处理量大的特点,将FPGA技术与DSP技术相结合,研究了一种基于FPGA和多DSP的多通道并行处理的高速视觉测量系统。详细介绍了FPGA技术与多DSP技术在数字图像处理过程中的不同应用、高速视觉测量系统的总体结构以及各部分的工作原理。     

面向实时应用的时态数据库系统体系结构

提出了面向实时应用的时态数据库系统 Agilor-TDB,详细介绍了系统的体系结构。针对实时应用 ,实现了实时任务调度。在数据存储方面介绍了基于时间区间的多级文件索引结构和高效的内存数据管理机制 ;在数据查询方面提出了高速查询缓存优化策略。此外 ,用 PN模型对系统并发控制进行了详细描述。