An evaluation of volumetric interest points

This paper presents the first performance evaluation of interest points on scalar volumetric data. Such data encodes 3D shape, a fundamental property of objects. The use of another such property, texture (i.e. 2D surface colouration), or appearance, for object detection, recognition and registration has been well studied; 3D shape less so. However, the increasing prevalence of depth sensors and the diminishing returns to be had from appearance alone have seen a surge in shape-based methods. In this work we investigate the performance of several detectors of interest points in volumetric data, in terms of repeatability, number and nature of interest points. Such methods form the first step in many shape-based applications. Our detailed comparison, with both quantitative and qualitative measures on synthetic and real 3D data, both point-based and volumetric, aids readers in selecting a method suitable for their application. © 2011 IEEE.

Smoke curing of mussels

Substantial quantities of green mussels are available on the Kerala coast particularly from Calicut to north. But these are not properly exploited at present. Simple and economic methods of processing like drying and smoking can go a long way towards market promotion and better returns to the fishermen. This paper reports the method of preparation of smoked mussels which have a great potential for export as well as local marketing.

Advanced applications of a computational design synthesis method

From modelling to manufacturing, computers have increasingly become partners in the design process, helping automate many phases once carried out by hand. In the creative phase, computational synthesis methods aim at facilitating designers' task through the automated generation of optimally directed design alternatives. Nevertheless, applications of these techniques are mainly academic and industrial design practice is still far from applying them routinely. This is due to the complex nature of many design tasks and to the difficulty of developing synthesis methods that can be easily adapted to multiple case studies and automated simulation. This work stems from the analysis of implementation issues and obstacles to the widespread use of these tools. The research investigates the possibility to remove these obstacles through the application of a novel technique to complex design tasks. The ability of this technique to scale-up without sacrificing accuracy is demonstrated. The successful results confirm the possibility to use synthesis methods in complex design tasks and spread their commercial and industrial application.

A performance evaluation of volumetric 3D interest point detectors

This paper presents the first performance evaluation of interest points on scalar volumetric data. Such data encodes 3D shape, a fundamental property of objects. The use of another such property, texture (i.e. 2D surface colouration), or appearance, for object detection, recognition and registration has been well studied; 3D shape less so. However, the increasing prevalence of 3D shape acquisition techniques and the diminishing returns to be had from appearance alone have seen a surge in 3D shape-based methods. In this work, we investigate the performance of several state of the art interest points detectors in volumetric data, in terms of repeatability, number and nature of interest points. Such methods form the first step in many shape-based applications. Our detailed comparison, with both quantitative and qualitative measures on synthetic and real 3D data, both point-based and volumetric, aids readers in selecting a method suitable for their application. © 2012 Springer Science+Business Media, LLC.

Comparison of Micro-Vortex generators in supersonic flows

An experimental comparison of several vortex generator geometries was conducted at Mach 1.5, 1.8, and 2.5 to better understand downstream vortex development as a function of device shape and Mach number. The devices had heights less than that of the boundary-layer ("micro"-vortex generators) and were either vane-shaped or of the alternative microramp geometry. LDV was used to measure two components of velocity at several stations downstream of the devices. The velocity data were then fitted to a vortex model so that vortex parameters such as circulation, core radius, and trajectory were estimated. Mach number dependence was seen for all parameters. Vortex height and core radius both tended to decrease slightly with increasing Mach number. A critical vane angle for maximum circulation was observed and also decreased with increasing Mach number. Circulation was seen to scale with wall-friction velocity for Mach 1.5 and 1.8 but not 2.5. © 2012 by W.R. Nolan and H. Babinsky.

A C-type lectin associated and translocated with cortical granules during oocyte maturation and egg fertilization in fish

Oocyte maturation and egg fertilization in both vertebrates and invertebrates are marked by orchestrated cytoplasmic translocation of secretory vesicles known as cortical granules. It is thought that such redistribution of cellular content is critical for asymmetrical cell division during early development, but the mechanism and regulation of the process is poorly understood. Here we report the identification, purification and cDNA cloning of a C-type lectin from oocytes of a freshwater fish species gibel carp (Carassius auratus gibelio). The purified protein has been demonstrated to have lectin activity and to be a Ca2+-dependent C-type lectin by hemagglutination activity assay. Immunocytochemistry revealed that the lectin is associated with cortical granules, gradually translocated to the cell surface during oocyte maturation, and discharged to the egg envelope upon fertilization. Interestingly, the lectin becomes phosphorylated on threonine residues upon induction of exocytosis by fertilization and returns to its original state after morula stage of embryonic development, suggesting that this posttranslational modification may represent a critical molecular switch for early embryonic development. (C) 2003 Elsevier Inc. All rights reserved.

一种个体软件过程能力度量方法

个体软件过程(PSP)是由卡内基×梅隆大学软件工程研究所的Humphrey领导开发的.它是一种可用于控制、管理和改进个人工作方式的自我持续改进过程.随着工业界对软件过程改进需求的日益增长,PSP成为了软件组织为达成完全(从宏观到微观)量化过程管理研究中的一个热点课题.软件过程研究表明,高水平的个体软件过程能力是软件项目成功的关键,如何进行有效的个体软件过程能力度量是PSP中的一个核心问题.现有方法不能同时有效处理个体软件过程能力度量中的可变规模收益、多变量输入/输出以及决策者偏好问题.提出了一种综合了数据包络分析(DEA)和层次分析法(AHP)的个体软件过程能力评价方法--PSPADA,介绍了PSPADA的个体软件过程能力评价模型和核心算法(集成决策者偏好和估计规模收益).实验结果显示,PSPADA能够在考虑决策者偏好的同时,有效地进行多指标、规模收益可变的量化评估.

Optical image processing using the photoinduced anisotropy of pyrrylfulgide

A synthesized photochromic compound-pyrrylfulgide-is prepared as a thin film doped in a polymethylmethacrylate (PMMA) matrix. Under irradiation by UV light, the film converts from the bleached state into a colored state that has a maximum absorption at 635 nm and is thermally stable at room temperature. When the colored state is irradiated by a linearly polarized 650 nm laser, the film returns to the bleached state; photoinduced anisotropy is produced during this process. Application of optical image processing methods using the photoinduced anisotropy of the pyrrylfulgide/PMMA film is described. Examples in non-Fourier optical image processing, such as contrast reversal and image subtraction and summation, as well as in Fourier optical image processing, such as low-pass filtering and edge enhancement, are presented. (c) 2006 Optical Society of America.

Effects of convection and solid wall on the diffusion in microscale convection flows

The diffusive transport properties in microscale convection flows are studied by using the direct simulation Monte Carlo method. The effective diffusion coefficient D is computed from the mean square displacements of simulated molecules based on the Einstein diffusion equation D = x2 t /2t. Two typical convection flows, namely, thermal creep convection and Rayleigh– Bénard convection, are investigated. The thermal creep convection in our simulation is in the noncontinuum regime, with the characteristic scale of the vortex varying from 1 to 100 molecular mean free paths. The diffusion is shown to be enhanced only when the vortex scale exceeds a certain critical value, while the diffusion is reduced when the vortex scale is less than the critical value. The reason for phenomenon of diffusion reduction in the noncontinuum regime is that the reduction effect due to solid wall is dominant while the enhancement effect due to convection is negligible. A molecule will lose its memory of macroscopic velocity when it collides with the walls, and thus molecules are hard to diffuse away if they are confined between very close walls. The Rayleigh– Bénard convection in our simulation is in the continuum regime, with the characteristic length of 1000 molecular mean free paths. Under such condition, the effect of solid wall on diffusion is negligible. The diffusion enhancement due to convection is shown to scale as the square root of the Péclet number in the steady convection regime, which is in agreement with previous theoretical and experimental results. In the oscillation convection regime, the diffusion is more strongly enhanced because the molecules can easily advect from one roll to its neighbor due to an oscillation mechanism. © 2010 American Institute of Physics. doi:10.1063/1.3528310

Sharing visual features for multiclass and multiview object detection

We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifiers to the image, at multiple locations and scales. This can be slow and can require a lot of training data, since each classifier requires the computation of many different image features. In particular, for independently trained detectors, the (run-time) computational complexity, and the (training-time) sample complexity, scales linearly with the number of classes to be detected. It seems unlikely that such an approach will scale up to allow recognition of hundreds or thousands of objects. We present a multi-class boosting procedure (joint boosting) that reduces the computational and sample complexity, by finding common features that can be shared across the classes (and/or views). The detectors for each class are trained jointly, rather than independently. For a given performance level, the total number of features required, and therefore the computational cost, is observed to scale approximately logarithmically with the number of classes. The features selected jointly are closer to edges and generic features typical of many natural structures instead of finding specific object parts. Those generic features generalize better and reduce considerably the computational cost of an algorithm for multi-class object detection.

In Comes I: Performance, Memory and Landscape

Pearson, Mike, In Comes I: Performance, Memory and Landscape (Exeter: University of Exeter Press, 2007) RAE2008

Lares de Infância e Juventude

Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Serviço Social.

Improving the Performance of Overlay Routing and P2P File Sharing using Selfish Neighbor Selection

A foundational issue underlying many overlay network applications ranging from routing to P2P file sharing is that of connectivity management, i.e., folding new arrivals into the existing mesh and re-wiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for specific applications designed to work well in real deployments, and providing abstractions for the underlying problem that are tractable to address via theoretical analyses, especially game-theoretic analysis. Our work unifies these two thrusts first by distilling insights gleaned from clean theoretical models, notably that under natural resource constraints, selfish players can select neighbors so as to efficiently reach near-equilibria that also provide high global performance. Using Egoist, a prototype overlay routing system we implemented on PlanetLab, we demonstrate that our neighbor selection primitives significantly outperform existing heuristics on a variety of performance metrics; that Egoist is competitive with an optimal, but unscalable full-mesh approach; and that it remains highly effective under significant churn. We also describe variants of Egoist's current design that would enable it to scale to overlays of much larger scale and allow it to cater effectively to applications, such as P2P file sharing in unstructured overlays, based on the use of primitives such as scoped-flooding rather than routing.

Recognition of Human Action Using Moment-Based Feature

The performance of different classification approaches is evaluated using a view-based approach for motion representation. The view-based approach uses computer vision and image processing techniques to register and process the video sequence. Two motion representations called Motion Energy Images and Motion History Image are then constructed. These representations collapse the temporal component in a way that no explicit temporal analysis or sequence matching is needed. Statistical descriptions are then computed using moment-based features and dimensionality reduction techniques. For these tests, we used 7 Hu moments, which are invariant to scale and translation. Principal Components Analysis is used to reduce the dimensionality of this representation. The system is trained using different subjects performing a set of examples of every action to be recognized. Given these samples, K-nearest neighbor, Gaussian, and Gaussian mixture classifiers are used to recognize new actions. Experiments are conducted using instances of eight human actions (i.e., eight classes) performed by seven different subjects. Comparisons in the performance among these classifiers under different conditions are analyzed and reported. Our main goals are to test this dimensionality-reduced representation of actions, and more importantly to use this representation to compare the advantages of different classification approaches in this recognition task.

A Fully Distributed Location Management Scheme for Large PCS

In [previous papers] we presented the design, specification and proof of correctness of a fully distributed location management scheme for PCS networks and argued that fully replicating location information is both appropriate and efficient for small PCS networks. In this paper, we analyze the performance of this scheme. Then, we extend the scheme in a hierarchical environment so as to scale to large PCS networks. Through extensive numerical results, we show the superiority of our scheme compared to the current IS-41 standard.