Efficient application identification and the temporal and spatial stability of classification schema

Motivated by the importance of accurate identification for a range of applications, this paper compares and contrasts the effective and efficient classification of network-based applications using behavioral observations of network-traffic and those using deep-packet inspection.Importantly, throughout our work we are able to make comparison with data possessing an accurate, independently determined ground-truth that describes the actual applications causing the network-traffic observed.In a unique study in both the spatial-domain: comparing across different network-locations and in the temporal-domain: comparing across a number of years of data, we illustrate the decay in classification accuracy across a range of application–classification mechanisms. Further, we document the accuracy of spatial classification without training data possessing spatial diversity.Finally, we illustrate the classification of UDP traffic. We use the same classification approach for both stateful flows (TCP) and stateless flows based upon UDP. Importantly, we demonstrate high levels of accuracy: greater than 92% for the worst circumstance regardless of the application.     

The influence of attentional engagement and spatial characteristics on time perception in virtual reality

Virtual Reality - Virtual reality (VR) is a simulation tool that is being used extensively to study the effects of training and perception. However, several studies have shown that some aspects of...     

Neural-network method applied to the stereo image correspondence problem in three-component particle image velocimetry

The successful application of a recurrent neural network of the Hopfield type to the solution of the stereo image-pair reconciliation problem in stereoscopic particle image velocimetry (PIV) in the tracking mode is described. The results of applying the network to both virtual-flow and physical-flow PIV data sets are presented, and the usefulness of this novel approach to PIV stereo image analysis is demonstrated. A partner-particle image-pair density (PPID) parameter is defined as the average number of potential particle image-pair candidates in the search window in the second view corresponding to a single image pair in the first view. A quantitative assessment of the performance of the method is then made from groups of 100 synthetic flow images at various values of the PPID. The successful pairing of complementary image points is shown to vary from 100% at a PPID of 1 and to remain greater than 97% successful for PPID's up to 5. The application of the method to a hydraulic flow is also described, with in-line stereo images presented, and the application of the neural-matching method is demonstrated for a typical data set.     

Evolution of carbohydrate metabolic pathways

Current studies of hyperthermophilic archaea and bacteria, the phylogenetically deepest-rooted and slowest-evolving extant organisms known, are allowing new insights into the nature of presumably ancient metabolic pathways. The apparent common occurrence of modified non-phosphorylated Entner-Doudoroff (ED) pathways among saccharolytic archaea and the absence of the conventional Embden-Meyerhof-Parnas (EMP) mode of glycolysis indicate that the ED pathway is the older route of carbohydrate dissimilation. However, gluconeogenesis via the "reversed" EMP route has been found in archaea. Thus, the EMP pathway was probably an anabolic pathway to begin with; its catabolic role came later, with the evolution of fructose phosphate kinases, using ATP, ADP or pyrophosphate as phosphate donors. Similarly, the presence of reductive reactions of the citric acid cycle in anaerobic archaea and the most deeply rooted bacteria, including autotrophs, indicates that the citric acid cycle was originally a reductive biosynthetic pathway.     

Two is better than one: A diploid genotype for neural networks

In nature the genotype of many organisms exhibits diploidy, i.e., it includes two copies of every gene. In this paper we describe the results of simulations comparing the behavior of haploid and diploid populations of ecological neural networks living in both fixed and changing environments. We show that diploid genotypes create more variability in fitness in the population than haploid genotypes and buffer better environmental change; as a consequence, if one wants to obtain good results for both average and peak fitness in a single population one should choose a diploid population with an appropriate mutation rate. Some results of our simulations parallel biological findings.     

The labeled maximum matching problem

Given a graph G where a label is associated with each edge, we address the problem of looking for a maximum matching of G using the minimum number of different labels, namely the labeled maximum matching problem. It is a relatively new problem whose application is related to the timetabling problem. We prove it is NP-complete and present four different mathematical formulations. Moreover, we propose an exact algorithm based on a branch-and-bound approach to solve it. We evaluate the performance of our algorithm on a wide set of instances and compare our computational times with the ones required by CPLEX to solve the proposed mathematical formulations. Test results show the effectiveness of our procedure, that hugely outperforms the solver.     

Cubic B样条旋转曲面的自由绘制技术

随着基于样条曲线的模型逐渐成为CAGD的主要研究对象,进一步带动了高度自由曲面建模技术的发展.本文描述一个新颖、直观的旋转曲面绘制技术,它支持三次B样条的自由输入作为轮廓线,并通过提取的样点矢量以及最小方差逼近方法形成旋转轴,利用轴上测量点的切线方向确定各个圆平面,从而建立了平面上旋转坐标矩阵,最终插值空间球面样点生成双三次B样条曲面.实验结果有效地验证了此技术的高效性.     

Monitoring activities from multiple video streams: establishing acommon coordinate frame

Monitoring of large sites requires coordination between multiple cameras, which in turn requires methods for relating events between distributed cameras. This paper tackles the problem of automatic external calibration of multiple cameras in an extended scene, that is, full recovery of their 3D relative positions and orientations. Because the cameras are placed far apart, brightness or proximity constraints cannot be used to match static features, so we instead apply planar geometric constraints to moving objects tracked throughout the scene. By robustly matching and fitting tracked objects to a planar model, we align the scene's ground plane across multiple views and decompose the planar alignment matrix to recover the 3D relative camera and ground plane positions. We demonstrate this technique in both a controlled lab setting where we test the effects of errors in the intrinsic camera parameters, and in an uncontrolled, outdoor setting. In the latter, we do not assume synchronized cameras and we show that enforcing geometric constraints enables us to align the tracking data in time. In spite of noise in the intrinsic camera parameters and in the image data, the system successfully transforms multiple views of the scene's ground plane to an overhead view and recovers the relative 3D camera and ground plane positions     

An Integrated Assessment of the Impacts of Changing Climate Variability on Agricultural Productivity and Profitability in an Irrigated Mediterranean Catchment

Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ET_N), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ET_N may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.