Data streams algorithms and applications
Muthukrishnan, S
2014-01-01
Data stream algorithms as an active research agenda emerged only over the past few years, even though the concept of making few passes over the data for performing computations has been around since the early days of Automata Theory. The data stream agenda now pervades many branches of Computer Science including databases, networking, knowledge discovery and data mining, and hardware systems. Industry is in synch too, with Data Stream Management Systems (DSMSs) and special hardware to deal with data speeds. Even beyond Computer Science, data stream concerns are emerging in physics, atmospheric
Streaming Algorithms for Line Simplification
Abam, Mohammad; de Berg, Mark; Hachenberger, Peter
2010-01-01
this problem in a streaming setting, where we only have a limited amount of storage, so that we cannot store all the points. We analyze the competitive ratio of our algorithms, allowing resource augmentation: we let our algorithm maintain a simplification with 2k (internal) points and compare the error of our...
Stream Deniable-Encryption Algorithms
N.A. Moldovyan
2016-04-01
Full Text Available A method for stream deniable encryption of secret message is proposed, which is computationally indistinguishable from the probabilistic encryption of some fake message. The method uses generation of two key streams with some secure block cipher. One of the key streams is generated depending on the secret key and the other one is generated depending on the fake key. The key streams are mixed with the secret and fake data streams so that the output ciphertext looks like the ciphertext produced by some probabilistic encryption algorithm applied to the fake message, while using the fake key. When the receiver or/and sender of the ciphertext are coerced to open the encryption key and the source message, they open the fake key and the fake message. To disclose their lie the coercer should demonstrate possibility of the alternative decryption of the ciphertext, however this is a computationally hard problem.
Overview of streaming-data algorithms
Madhulatha, T Soni
2012-01-01
Due to recent advances in data collection techniques, massive amounts of data are being collected at an extremely fast pace. Also, these data are potentially unbounded. Boundless streams of data collected from sensors, equipments, and other data sources are referred to as data streams. Various data mining tasks can be performed on data streams in search of interesting patterns. This paper studies a particular data mining task, clustering, which can be used as the first step in many knowledge discovery processes. By grouping data streams into homogeneous clusters, data miners can learn about data characteristics which can then be developed into classification models for new data or predictive models for unknown events. Recent research addresses the problem of data-stream mining to deal with applications that require processing huge amounts of data such as sensor data analysis and financial applications. For such analysis, single-pass algorithms that consume a small amount of memory are critical.
Overview Of Streaming-Data Algorithms
T. Soni Madhulatha
2011-12-01
Full Text Available Due to recent advances in data collection techniques, massive amounts of data are being collected at anextremely fast pace. Also, these data are potentially unbounded. Boundless streams of data collected fromsensors, equipments, and other data sources are referred to as data streams. Various data mining taskscan be performed on data streams in search of interesting patterns. This paper studies a particular datamining task, clustering, which can be used as the first step in many knowledge discovery processes. Bygrouping data streams into homogeneous clusters, data miners can learn about data characteristicswhich can then be developed into classification models for new data or predictive models for unknownevents. Recent research addresses the problem of data-stream mining to deal with applications thatrequire processing huge amounts of data such as sensor data analysis and financial applications. Forsuch analysis, single-pass algorithms that consume a small amount of memory are critical.
IMM Iterated Extended Particle Filter Algorithm
Yang Wan; Shouyong Wang; Xing Qin
2013-01-01
In order to solve the tracking problem of radar maneuvering target in nonlinear system model and non-Gaussian noise background, this paper puts forward one interacting multiple model (IMM) iterated extended particle filter algorithm (IMM-IEHPF). The algorithm makes use of multiple modes to model the target motion form to track any maneuvering target and each mode uses iterated extended particle filter (IEHPF) to deal with the state estimation problem of nonlinear non-Gaussian system. IEH...
Extended PGA for Range Migration Algorithms
Rossum, W.L. van; Otten, M.P.G.; Bree, R.J.P. van
2006-01-01
The Phase Gradient Autofocus (PGA) algorithm is extended to work for synthetic aperture radar (SAR) spotlight images processed with range migration (ω-k) algorithms. Several pre-processing steps are proposed for aligning the range-compressed phase-history data needed for successful autofocusing of
Extending value stream mapping through waste definition beyond customer perspective
Khurum, Mahvish; Petersen, Kai; Gorschek, Tony
2014-01-01
Value Stream Mapping is one of the several Lean practices, which has recently attracted interest in the software engineering community. In other contexts (such as military, health, production), Value Stream Mapping has achieved considerable improvements in processes and products. The goal is to also leverage on these benefits in the software intensive product development context. The primary contribution is that we are extending the definition of waste to fit in the software intensive product...
Segment-based traffic smoothing algorithm for VBR video stream
无
2006-01-01
Transmission of variable bit rate (VBR) video, because of the burstiness of VBR video traffic, has high fluctuation in bandwidth requirement. Traffic smoothing algorithm is very efficient in reducing burstiness of the VBR video stream by transmitting data in a series of fixed rates. We propose in this paper a novel segment-based bandwidth allocation algorithm which dynamically adjusts the segmentation boundary and changes the transmission rate at the latest possible point so that the video segment will be extended as long as possible and the number of rate changes can be as small as possible while keeping the peak rate low. Simulation results showed that our approach has small bandwidth requirement, high bandwidth utilization and low computation cost.
Optimal Rate Allocation Algorithm for Multiple Source Video Streaming
戢彦泓; 郭常杰; 钟玉琢; 孙立峰
2004-01-01
Video streaming is one of the most important applications used in the best-effort Internet.This paper presents a new scheme for multiple source video streaming in which the traditional fine granular scalable coding was rebuilt into a multiple sub-streams based transmission model.A peak signal to noise ratio based stream rate allocation algorithm was then developed based on the transmission model.In tests,the algorithm performance is about 1 dB higher than that of a uniform rate allocation algorithm.Therefore,this scheme can overcome bottlenecks along a single link and smooth jitter to achieve high quality and stable video.
Online Feature Extraction Algorithms for Data Streams
Ozawa, Seiichi
Along with the development of the network technology and high-performance small devices such as surveillance cameras and smart phones, various kinds of multimodal information (texts, images, sound, etc.) are captured real-time and shared among systems through networks. Such information is given to a system as a stream of data. In a person identification system based on face recognition, for example, image frames of a face are captured by a video camera and given to the system for an identification purpose. Those face images are considered as a stream of data. Therefore, in order to identify a person more accurately under realistic environments, a high-performance feature extraction method for streaming data, which can be autonomously adapted to the change of data distributions, is solicited. In this review paper, we discuss a recent trend on online feature extraction for streaming data. There have been proposed a variety of feature extraction methods for streaming data recently. Due to the space limitation, we here focus on the incremental principal component analysis.
The entity-to-algorithm allocation problem: Extending the analysis
Grobler, J
2014-12-01
Full Text Available This paper extends the investigation into the algorithm selection problem in hyper-heuristics, otherwise referred to as the entity-to-algorithm allocation problem, introduced by Grobler et al.. Two newly developed population-based portfolio...
Performance of a streaming mesh refinement algorithm.
Thompson, David C.; Pebay, Philippe Pierre
2004-08-01
In SAND report 2004-1617, we outline a method for edge-based tetrahedral subdivision that does not rely on saving state or communication to produce compatible tetrahedralizations. This report analyzes the performance of the technique by characterizing (a) mesh quality, (b) execution time, and (c) traits of the algorithm that could affect quality or execution time differently for different meshes. It also details the method used to debug the several hundred subdivision templates that the algorithm relies upon. Mesh quality is on par with other similar refinement schemes and throughput on modern hardware can exceed 600,000 output tetrahedra per second. But if you want to understand the traits of the algorithm, you have to read the report!
Algorithms for Constructing Overlay Networks For Live Streaming
Andreev, Konstantin; Meyerson, Adam; Saks, Jevan; Sitaraman, Ramesh K
2011-01-01
We present a polynomial time approximation algorithm for constructing an overlay multicast network for streaming live media events over the Internet. The class of overlay networks constructed by our algorithm include networks used by Akamai Technologies to deliver live media events to a global audience with high fidelity. We construct networks consisting of three stages of nodes. The nodes in the first stage are the entry points that act as sources for the live streams. Each source forwards each of its streams to one or more nodes in the second stage that are called reflectors. A reflector can split an incoming stream into multiple identical outgoing streams, which are then sent on to nodes in the third and final stage that act as sinks and are located in edge networks near end-users. As the packets in a stream travel from one stage to the next, some of them may be lost. A sink combines the packets from multiple instances of the same stream (by reordering packets and discarding duplicates) to form a single in...
An Extended Algorithm of Flexibility Analysis in Chemical Engineering Processes
无
2001-01-01
An extended algorithm of flexibility analysis with a local adjusting method for flexibility region of chemical processes, which is based on the active constraint strategy, is proposed, which fully exploits the flexibility region of the process system operation. The hyperrectangular flexibility region determined by the extended algorithm is larger than that calculated by the previous algorithms. The limitation of the proposed algorithm due to imperfect convexity and its corresponding verification measure are also discussed. Both numerical and actual chemical process examples are presented to demonstrate the effectiveness of the new algorithm.
A novel extended kernel recursive least squares algorithm.
Zhu, Pingping; Chen, Badong; Príncipe, José C
2012-08-01
In this paper, a novel extended kernel recursive least squares algorithm is proposed combining the kernel recursive least squares algorithm and the Kalman filter or its extensions to estimate or predict signals. Unlike the extended kernel recursive least squares (Ex-KRLS) algorithm proposed by Liu, the state model of our algorithm is still constructed in the original state space and the hidden state is estimated using the Kalman filter. The measurement model used in hidden state estimation is learned by the kernel recursive least squares algorithm (KRLS) in reproducing kernel Hilbert space (RKHS). The novel algorithm has more flexible state and noise models. We apply this algorithm to vehicle tracking and the nonlinear Rayleigh fading channel tracking, and compare the tracking performances with other existing algorithms.
An extended EM algorithm for subspace clustering
Lifei CHEN; Qingshan JIANG
2008-01-01
Clustering high dimensional data has become a challenge in data mining due to the curse of dimension-ality. To solve this problem, subspace clustering has been defined as an extension of traditional clustering that seeks to find clusters in subspaces spanned by different combinations of dimensions within a dataset. This paper presents a new subspace clustering algorithm that calcu-lates the local feature weights automatically in an EM-based clustering process. In the algorithm, the features are locally weighted by using a new unsupervised weight-ing method, as a means to minimize a proposed cluster-ing criterion that takes into account both the average intra-clusters compactness and the average inter-clusters separation for subspace clustering. For the purposes of capturing accurate subspace information, an additional outlier detection process is presented to identify the pos-sible local outliers of subspace clusters, and is embedded between the E-step and M-step of the algorithm. The method has been evaluated in clustering real-world gene expression data and high dimensional artificial data with outliers, and the experimental results have shown its effectiveness.
Image Encryption Using a Lightweight Stream Encryption Algorithm
Saeed Bahrami
2012-01-01
Full Text Available Security of the multimedia data including image and video is one of the basic requirements for the telecommunications and computer networks. In this paper, we consider a simple and lightweight stream encryption algorithm for image encryption, and a series of tests are performed to confirm suitability of the described encryption algorithm. These tests include visual test, histogram analysis, information entropy, encryption quality, correlation analysis, differential analysis, and performance analysis. Based on this analysis, it can be concluded that the present algorithm in comparison to A5/1 and W7 stream ciphers has the same security level, is better in terms of the speed of performance, and is used for real-time applications.
A note on extending decision algorithms by stable predicates
Alfredo Ferro
1988-11-01
Full Text Available A general mechanism to extend decision algorithms to deal with additional predicates is described. The only conditions imposed on the predicates is stability with respect to some transitive relations.
A potential reduction algorithm for an extended SDP problem
聂家旺; 袁亚湘
2000-01-01
An extended semi-definite programming, the SDP with an additional quadratic term in the objective function, is studied. Our generalization is similar to the generalization from linear programming to quadratic programming. Optimal conditions for this new class of problems are discussed and a potential reduction algorithm for solving QSDP problems is presented. The convergence properties of this algorithm are also given.
STEGANOGRAPHY FOR TWO AND THREE LSBs USING EXTENDED SUBSTITUTION ALGORITHM
R.S. Gutte
2013-03-01
Full Text Available The Security of data on internet has become a prior thing. Though any message is encrypted using a stronger cryptography algorithm, it cannot avoid the suspicion of intruder. This paper proposes an approach in such way that, data is encrypted using Extended Substitution Algorithm and then this cipher text is concealed at two or three LSB positions of the carrier image. This algorithm covers almost all type of symbols and alphabets. The encrypted text is concealed variably into the LSBs. Therefore, it is a stronger approach. The visible characteristics of the carrier image before and after concealment remained almost the same. The algorithm has been implemented using Matlab.
Extended SVM algorithms for multilevel trans-Z-source inverter
Aida Baghbany Oskouei
2016-03-01
Full Text Available This paper suggests extended algorithms for multilevel trans-Z-source inverter. These algorithms are based on space vector modulation (SVM, which works with high switching frequency and does not generate the mean value of the desired load voltage in every switching interval. In this topology the output voltage is not limited to dc voltage source similar to traditional cascaded multilevel inverter and can be increased with trans-Z-network shoot-through state control. Besides, it is more reliable against short circuit, and due to several number of dc sources in each phase of this topology, it is possible to use it in hybrid renewable energy. Proposed SVM algorithms include the following: Combined modulation algorithm (SVPWM and shoot-through implementation in dwell times of voltage vectors algorithm. These algorithms are compared from viewpoint of simplicity, accuracy, number of switching, and THD. Simulation and experimental results are presented to demonstrate the expected representations.
Resource Allocation in Public Cluster with Extended Optimization Algorithm
Akbar, Z.; Handoko, L. T.
2007-01-01
We introduce an optimization algorithm for resource allocation in the LIPI Public Cluster to optimize its usage according to incoming requests from users. The tool is an extended and modified genetic algorithm developed to match specific natures of public cluster. We present a detail analysis of optimization, and compare the results with the exact calculation. We show that it would be very useful and could realize an automatic decision making system for public clusters.
Extended Lyman-alpha emission from cold accretion streams
Rosdahl, J
2011-01-01
{Abridged} We investigate the observability of cold accretion streams at redshift 3 via Lyman-alpha radiation and the feasibility of cold accretion as the main driver behind giant Lya blobs (LABs). We run cosmological zoom simulations focusing on 3 halos spanning two orders of magnitude in mass, from 10^11 to 10^13 solar masses. We use a version of the AMR code Ramses that includes radiative transfer of UV photons, and we employ a refinement strategy that allows us to resolve accretion streams in their natural environment to an unprecedented level. For the first time, we self-consistently model self-shielding in the cold streams from the cosmological UV background, which enables us to accurately predict their temperatures, ionization states and Lya luminosities. We find the efficiency of gravitational heating in cold streams in a ~10^11 solar mass halo is around 10-20% throughout most of the halo but reaching much higher values close to the center. As a result most of the Lya luminosity comes from the circumg...
An Approximate L p Difference Algorithm for Massive Data Streams
Jessica H. Fong
2001-12-01
Full Text Available Several recent papers have shown how to approximate the difference ∑ i |a i-b i | or ∑|a i-b i | 2 between two functions, when the function values a i and b i are given in a data stream, and their order is chosen by an adversary. These algorithms use little space (much less than would be needed to store the entire stream and little time to process each item in the stream. They approximate with small relative error. Using different techniques, we show how to approximate the L p-difference ∑ i |a i-b i | p for any rational-valued p∈(0,2], with comparable efficiency and error. We also show how to approximate ∑ i |a i-b i | p for larger values of p but with a worse error guarantee. Our results fill in gaps left by recent work, by providing an algorithm that is precisely tunable for the application at hand. These results can be used to assess the difference between two chronologically or physically separated massive data sets, making one quick pass over each data set, without buffering the data or requiring the data source to pause. For example, one can use our techniques to judge whether the traffic on two remote network routers are similar without requiring either router to transmit a copy of its traffic. A web search engine could use such algorithms to construct a library of small ``sketches,'' one for each distinct page on the web; one can approximate the extent to which new web pages duplicate old ones by comparing the sketches of the web pages. Such techniques will become increasingly important as the enormous scale, distributional nature, and one-pass processing requirements of data sets become more commonplace.
An Index-Inspired Algorithm for Anytime Classification on Evolving Data Streams
Kranen, Phillip; Assent, Ira; Seidl, Thomas
2012-01-01
Due to the ever growing presence of data streams there has been a considerable amount of research on stream data mining over the past years. Anytime algorithms are particularly well suited for stream mining, since they flexibly use all available time on streams of varying data rates, and are also...
Burnett, L; Basten, A; Hensley, W J
1986-01-10
Most computer algorithms used for comparing or aligning nucleotide sequences rely on the premise that the best way to extend a homology between the two sequences is to select a match rather than a mismatch. We have tested this assumption and found that it is not always valid.
Validation of the Eclipse AAA algorithm at extended SSD.
Hussain, Amjad; Villarreal-Barajas, Eduardo; Brown, Derek; Dunscombe, Peter
2010-06-08
The accuracy of dose calculations at extended SSD is of significant importance in the dosimetric planning of total body irradiation (TBI). In a first step toward the implementation of electronic, multi-leaf collimator compensation for dose inhomogeneities and surface contour in TBI, we have evaluated the ability of the Eclipse AAA to accurately predict dose distributions in water at extended SSD. For this purpose, we use the Eclipse AAA algorithm, commissioned with machine-specific beam data for a 6 MV photon beam, at standard SSD (100 cm). The model was then used for dose distribution calculations at extended SSD (179.5 cm). Two sets of measurements were acquired for a 6 MV beam (from a Varian linear accelerator) in a water tank at extended SSD: i) open beam for 5 x 5, 10 x 10, 20 x 20 and 40 x 40 cm2 field sizes (defined at 179.5 cm SSD), and ii) identical field sizes but with a 1.3 cm thick acrylic spoiler placed 10 cm above the water surface. Dose profiles were acquired at 5 cm, 10 cm and 20 cm depths. Dose distributions for the two setups were calculated using the AAA algorithm in Eclipse. Confidence limits for comparisons between measured and calculated absolute depth dose curves and normalized dose profiles were determined as suggested by Venselaar et al. The confidence limits were within 2% and 2 mm for both setups. Extended SSD calculations were also performed using Eclipse AAA, commissioned with Varian Golden beam data at standard SSD. No significant difference between the custom commissioned and Golden Eclipse AAA was observed. In conclusion, Eclipse AAA commissioned at standard SSD can be used to accurately predict dose distributions in water at extended SSD for 6 MV open beams.
On Resource Aware Algorithms in Epidemic Live Streaming
Mathieu, Fabien
2009-01-01
Epidemic-style diffusion schemes have been previously proposed for achieving peer-to-peer live streaming. Their performance trade-offs have been deeply analyzed for homogeneous systems, where all peers have the same upload capacity. However, epidemic schemes designed for heterogeneous systems have not been completely understood yet. In this report we focus on the peer selection process and propose a generic model that encompasses a large class of algorithms. The process is modeled as a combination of two functions, an aware one and an agnostic one. By means of simulations, we analyze the awareness-agnostism trade-offs on the peer selection process and the impact of the source distribution policy in non-homogeneous networks. We highlight that the early diffusion of a given chunk is crucial for its overall diffusion performance, and a fairness trade-off arises between the performance of heterogeneous peers, as a function of the level of awareness.
The algorithm of measuring parameters of separate oil streams components
Kopteva, A. V.; Voytyuk, I. N.
2017-02-01
This paper describes a development in the area of non-contact measurement of moving flows, including mass flow, the number of components and their mass ratios in a multicomponent flow, as well as measurement of flows based on algorithms and functional developed for various industries and production processes. The paper demonstrates that at the core of the proposed systems, there is the physical information field created in the cross section of the moving flow by hard electromagnetic radiation. The substantiation and measurement of the information parameters are performed by the hardware and the software of the automatic measuring system. A new way of statistical pulsation measurements by the radioisotope technique is described, being alternative to the existing stream control methods and allowing improving accuracy of measurements. The basic formula fundamental for the method of calibration characteristics correction is shown.
Morikawa, Kyojiro; Kazoe, Yutaka; Mawatari, Kazuma; Tsukahara, Takehiko; Kitamori, Takehiko
2015-02-01
Understanding liquid structure and the electrical properties of liquids confined in extended nanospaces (10-1000 nm) is important for nanofluidics and nanochemistry. To understand these liquid properties requires determination of the dielectric constant of liquids confined in extended nanospaces. A novel dielectric constant measurement method has thus been developed for extended nanospaces using a streaming potential method. We focused on the nonsteady-state streaming potential in extended nanospaces and successfully measured the dielectric constant of liquids within them without the use of probe molecules. The dielectric constant of water was determined to be significantly reduced by about 3 times compared to that of the bulk. This result contributes key information toward further understanding of the chemistry and fluidics in extended nanospaces.
RStorm : Developing and testing streaming algorithms in R
Kaptein, M.C.
2014-01-01
Streaming data, consisting of indefinitely evolving sequences, are becoming ubiquitous in many branches of science and in various applications. Computer scientists have developed streaming applications such as Storm and the S4 distributed stream computing platform1 to deal with data streams. However
RStorm : Developing and testing streaming algorithms in R
Kaptein, M.C.
2014-01-01
Streaming data, consisting of indefinitely evolving sequences, are becoming ubiquitous in many branches of science and in various applications. Computer scientists have developed streaming applications such as Storm and the S4 distributed stream computing platform1 to deal with data streams.
RStorm: Developing and Testing Streaming Algorithms in R
Kaptein, M.C.
2014-01-01
Streaming data, consisting of indefinitely evolving sequences, are becoming ubiquitous in many branches of science and in various applications. Computer scientists have developed streaming applications such as Storm and the S4 distributed stream computing platform1 to deal with data streams.
RStorm: Developing and Testing Streaming Algorithms in R
Kaptein, M.C.
2014-01-01
Streaming data, consisting of indefinitely evolving sequences, are becoming ubiquitous in many branches of science and in various applications. Computer scientists have developed streaming applications such as Storm and the S4 distributed stream computing platform1 to deal with data streams. However
Streaming algorithms for recognizing nearly well-parenthesized expressions
Krebs, Andreas; Srinivasan, Srikanth
2012-01-01
We study the streaming complexity of the membership problem of 1-turn-Dyck2 and Dyck2 when there are a few errors in the input string. 1-turn-Dyck2 with errors: We prove that there exists a randomized one-pass algorithm that given x checks whether there exists a string x' in 1-turn-Dyck2 such that x is obtained by flipping at most $k$ locations of x' using: - O(k log n) space, O(k log n) randomness, and poly(k log n) time per item and with error at most 1/poly(n). - O(k^{1+epsilon} + log n) space for every 0 <= epsilon <= 1, O(log n) randomness, O(polylog(n) + poly(k)) time per item, with error at most 1/8. Here, we also prove that any randomized one-pass algorithm that makes error at most k/n requires at least Omega(k log(n/k)) space to accept strings which are exactly k-away from strings in 1-turn-Dyck2 and to reject strings which are exactly (k+2)-away from strings in 1-turn-Dyck2. Since 1-turn-Dyck2 and the Hamming Distance problem are closely related we also obtain new upper and lower bounds for th...
An Extended Clustering Algorithm for Statistical Language Models
Ueberla, J P
1994-01-01
Statistical language models frequently suffer from a lack of training data. This problem can be alleviated by clustering, because it reduces the number of free parameters that need to be trained. However, clustered models have the following drawback: if there is ``enough'' data to train an unclustered model, then the clustered variant may perform worse. On currently used language modeling corpora, e.g. the Wall Street Journal corpus, how do the performances of a clustered and an unclustered model compare? While trying to address this question, we develop the following two ideas. First, to get a clustering algorithm with potentially high performance, an existing algorithm is extended to deal with higher order N-grams. Second, to make it possible to cluster large amounts of training data more efficiently, a heuristic to speed up the algorithm is presented. The resulting clustering algorithm can be used to cluster trigrams on the Wall Street Journal corpus and the language models it produces can compete with exi...
Multiple extended target tracking algorithm based on Gaussian surface matrix
Jinlong Yang; Peng Li; Zhihua Li; Le Yang
2016-01-01
In this paper, we consider the problem of irregular shapes tracking for multiple extended targets by introducing the Gaussian surface matrix (GSM) into the framework of the random finite set (RFS) theory. The Gaussian surface function is constructed first by the measurements, and it is used to define the GSM via a mapping function. We then integrate the GSM with the probability hypothesis density (PHD) filter, the Bayesian recursion formulas of GSM-PHD are derived and the Gaussian mixture implementation is employed to obtain the closed-form solutions. Moreover, the estimated shapes are designed to guide the measurement set sub-partition, which can cope with the problem of the spatialy close target tracking. Simulation results show that the proposed algorithm can effectively estimate irregular target shapes and exhibit good robustness in cross extended target tracking.
EXTENDED MONTE CARLO LOCALIZATION ALGORITHM FOR MOBILE SENSOR NETWORKS
无
2008-01-01
A real-world localization system for wireless sensor networks that adapts for mobility and irregular radio propagation model is considered.The traditional range-based techniques and recent range-free localization schemes are not welt competent for localization in mobile sensor networks,while the probabilistic approach of Bayesian filtering with particle-based density representations provides a comprehensive solution to such localization problem.Monte Carlo localization is a Bayesian filtering method that approximates the mobile node’S location by a set of weighted particles.In this paper,an enhanced Monte Carlo localization algorithm-Extended Monte Carlo Localization (Ext-MCL) is suitable for the practical wireless network environment where the radio propagation model is irregular.Simulation results show the proposal gets better localization accuracy and higher localizable node number than previously proposed Monte Carlo localization schemes not only for ideal radio model,but also for irregular one.
MCMC with Strings and Branes: The Suburban Algorithm (Extended Version)
Heckman, Jonathan J; Vigoda, Ben
2016-01-01
Motivated by the physics of strings and branes, we develop a class of Markov chain Monte Carlo (MCMC) algorithms involving extended objects. Starting from a collection of parallel Metropolis-Hastings (MH) samplers, we place them on an auxiliary grid, and couple them together via nearest neighbor interactions. This leads to a class of "suburban samplers" (i.e., spread out Metropolis). Coupling the samplers in this way modifies the mixing rate and speed of convergence for the Markov chain, and can in many cases allow a sampler to more easily overcome free energy barriers in a target distribution. We test these general theoretical considerations by performing several numerical experiments. For suburban samplers with a fluctuating grid topology, performance is strongly correlated with the average number of neighbors. Increasing the average number of neighbors above zero initially leads to an increase in performance, though there is a critical connectivity with effective dimension d_eff ~ 1, above which "groupthin...
Extended Range Guided Munition Parameter Optimization Based on Genetic Algorithms
无
2005-01-01
Many factors influencing range of extended range guided munition (ERGM) are analyzed. The definition domain of the most important three parameters are ascertained by preparatory mathematical simulation, the optimized mathematical model of ERGM maximum range with boundary conditions is created, and parameter optimization based on genetic algorithm (GA) is adopted. In the GA design, three-point crossover is used and the best chromosome is kept so that the convergence speed becomes rapid. Simulation result shows that GA is feasible, the result is good and it can be easy to attain global optimization solution, especially when the objective function is not the convex one for independent variables and it is a multi-parameter problem.
PRESEE: an MDL/MML algorithm to time-series stream segmenting.
Xu, Kaikuo; Jiang, Yexi; Tang, Mingjie; Yuan, Changan; Tang, Changjie
2013-01-01
Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmenting mainly focused on the issue of ameliorating precision instead of paying much attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream.
Kristian M. Lien
1990-01-01
Full Text Available This paper presents a new algorithm based on the heuristic tearing algorithm by Gundersen and Hertzberg (1983. The basic idea in both the original and the proposed algorithm is sequential tearing of strong components which have been identified by an algorithm proposed by Targan (1972. The new algorithm has two alternative options for selection of tear streams, and alternative precedence orderings may be generated for the selected set of tear streams. The algorithm has been tested on several problems. It has identified minimal (optimal tear sets for all of them, including the four problems presented in Gundersen and Hertzberg (1983 where the original algorithm could not find a minimal tear set. A Lisp implementation of the algorithm is described, and example problems arc presented.
A Survey of latest Algorithms for Frequent Itemset Mining in Data Stream
U.Chandrasekhar
2013-03-01
Full Text Available Association rule mining and finding frequent patterns in data base has been a very old topic. With the advent of Big Data, the need for stream mining has increased. Hence the paper surveys various latest frequent pattern mining algorithms on data streams to understand various problems to be solved, their short comings and advantages over others.
Wu, Huayi; Guan, Xuefeng; Gong, Jianya
2011-09-01
This paper presents a robust parallel Delaunay triangulation algorithm called ParaStream for processing billions of points from nonoverlapped block LiDAR files. The algorithm targets ubiquitous multicore architectures. ParaStream integrates streaming computation with a traditional divide-and-conquer scheme, in which additional erase steps are implemented to reduce the runtime memory footprint. Furthermore, a kd-tree-based dynamic schedule strategy is also proposed to distribute triangulation and merging work onto the processor cores for improved load balance. ParaStream exploits most of the computing power of multicore platforms through parallel computing, demonstrating qualities of high data throughput as well as a low memory footprint. Experiments on a 2-Way-Quad-Core Intel Xeon platform show that ParaStream can triangulate approximately one billion LiDAR points (16.4 GB) in about 16 min with only 600 MB physical memory. The total speedup (including I/O time) is about 6.62 with 8 concurrent threads.
Extending Algorithm of RSA Algorithm%基于RSA算法的扩展算法
张延招
2011-01-01
The security of RSA is designed on the basis of the difficulty of large integer decomposition.In the RSA public key encryption system the public key n is the product of two large prime number,aiming at the large integer n decomposition of the form n=pq（in which p,q as large prime number）.The paper describes the encryption and decryption theory of extending RSA algorithm,aiming at the large integer n decomposition to the form n=p1,p2,…,pr（in which p1,p2,…,pr as large prime number）.The addition of prime number could enhance the security of RSA algorithm.Compared to RSA algorithm,the extending RSA algorithm could be applied to both digital encryption/decryption and digital signature.Digital signature algorithm based on extending RSA algorithm is also of high security and reliability.%RSA的安全性是依据大整数分解的困难性而设计的。RSA公开密钥加密体制中n为2个大素数的乘积,即针对n=pq（p,q为大素数）的大整数分解,这里介绍了RSA算法的扩展算法的加密和解密原理,即针对n=p1,p2,…,pr（p1,p2,…,pr为大素数）的大整数分解。通过扩展素因子的个数达到RSA算法的安全性。比较RSA算法,扩展的RSA算法不仅可用于数据加密解密,也可用于数字签名。利用扩展的RSA算法实现数字签名也具有较高的安全性和可靠性。
Extended Approach to Water Flow Algorithm for Text Line Segmentation
Darko Brodi(c)
2012-01-01
This paper proposes a new approach to the water flow algorithm for text line segmentation.In the basic method the hypothetical water flows under few specified angles which have been defined by water flow angle as parameter.It is applied to the document image frame from left to right and vice versa.As a result,the unwetted and wetted areas are established.Thesc areas separate text from non-text elements in each text line,respectively.Hence,they represent the control areas that are of major importance for text line segmentation.Primarily,an extended approach means extraction of the connected-components by bounding boxes ovcr text.By this way,each connected component is mutually separated.Hence,the water flow angle,which defines the unwetted areas,is determined adaptively.By choosing appropriate water flow angle,the unwetted areas are lengthening which leads to the better text line segmentation.Results of this approach are encouraging due to the text line segmentation improvement which is the most challenging step in document image processing.
An initial peer configuration algorithm for multi-streaming peer-to-peer networks
Ishii, Tomoyuki
2012-01-01
The growth of the Internet technology enables us to use network applications for streaming audio and video. Especially, real-time streaming services using peer-to-peer (P2P) technology are currently emerging. An important issue on P2P streaming is how to construct a logical network (overlay network) on a physical network (IP network). In this paper, we propose an initial peer configuration algorithm for a multi-streaming peer-to-peer network. The proposed algorithm is based on a mesh-pull approach where any node has multiple parent and child nodes as neighboring nodes, and content transmitted between these neighboring nodes depends on their parent-child relationships. Our simulation experiments show that the proposed algorithm improves the number of joining node and traffic load.
Algorithms for Deterministic Call Admission Control of Pre-stored VBR Video Streams
Christos Tryfonas
2009-08-01
Full Text Available We examine the problem of accepting a new request for a pre-stored VBR video stream that has been smoothed using any of the smoothing algorithms found in the literature. The output of these algorithms is a piecewise constant-rate schedule for a Variable Bit-Rate (VBR stream. The schedule guarantees that the decoder buffer does not overflow or underflow. The problem addressed in this paper is the determination of the minimal time displacement of each new requested VBR stream so that it can be accommodated by the network and/or the video server without overbooking the committed traffic. We prove that this call-admission control problem for multiple requested VBR streams is NP-complete and inapproximable within a constant factor, by reducing it from the VERTEX COLOR problem. We also present a deterministic morphology-sensitive algorithm that calculates the minimal time displacement of a VBR stream request. The complexity of the proposed algorithm along with the experimental results we provide indicate that the proposed algorithm is suitable for real-time determination of the time displacement parameter during the call admission phase.
Extended Approximate String Matching Algorithms To Detect Name Aliases
Shaikh, Muniba; Memon, Nasrullah; Wiil, Uffe Kock
2011-01-01
. An extension to widely used ASM algorithms is proposed to detect the name aliases that generate as a result of transliteration. This paper aims to improve the accuracy of the basic ASM algorithms in order to detect correct aliases. The experimental evaluation shows that proposed extension increases...
Solving for the RC4 stream cipher state register using a genetic algorithm
Benjamin Ferriman
2014-06-01
Full Text Available The RC4 stream cipher has shown to be quite resilient to cryptanalysis for the 26 years it has been around. The algorithm is still one of the most widely used methods of encryption over the Internet today being implemented through the Secure Socket Layer and Transport Layer Security protocols. Genetic algorithms are a sub-class of evolutionary algorithms that have been used to help solve many different problems of optimization in a variety of disciplines. In this paper we will examine the abilities of the genetic algorithm as a tool to help solve the permutation that is stored as the state register of the RC4 stream cipher. Finally, we will show that on average the genetic algorithm can solve 100% of the keystream in 2121:5 generations.
HYBRID CHRIPTOGRAPHY STREAM CIPHER AND RSA ALGORITHM WITH DIGITAL SIGNATURE AS A KEY
Grace Lamudur Arta Sihombing
2017-03-01
Full Text Available Confidentiality of data is very important in communication. Many cyber crimes that exploit security holes for entry and manipulation. To ensure the security and confidentiality of the data, required a certain technique to encrypt data or information called cryptography. It is one of the components that can not be ignored in building security. And this research aimed to analyze the hybrid cryptography with symmetric key by using a stream cipher algorithm and asymmetric key by using RSA (Rivest Shamir Adleman algorithm. The advantages of hybrid cryptography is the speed in processing data using a symmetric algorithm and easy transfer of key using asymmetric algorithm. This can increase the speed of transaction processing data. Stream Cipher Algorithm using the image digital signature as a keys, that will be secured by the RSA algorithm. So, the key for encryption and decryption are different. Blum Blum Shub methods used to generate keys for the value p, q on the RSA algorithm. It will be very difficult for a cryptanalyst to break the key. Analysis of hybrid cryptography stream cipher and RSA algorithms with digital signatures as a key, indicates that the size of the encrypted file is equal to the size of the plaintext, not to be larger or smaller so that the time required for encryption and decryption process is relatively fast.
A Multiplexing Algorithm of Multiple Elementary Streams Based on Virtual Buffer Control
YI Zhixiong; ZOU Xuecheng; LIU Weizhong; CHEN Weibing
2006-01-01
The paper presents a prototype of virtual decoder of the transport stream's system target decoder (T-STD).By connecting the coding model and decoding model, and feeding the overflow of decoding buffer back to control coding, we have got a self-adaptive coding model, and propose an algorithm of multiplexing multiple elementary streams to a transport stream based on the principle of virtual buffer controlling strategy. The transport stream (TS) which uses this method passes the test of software unzipping and set-top-box (STB) playing, and all of the analyzing parameters which are detected by code analyzer accord with the standard of MPEG-2. Some problems that playing time becomes longer and mu-tiple TS streaming can not be fit for all the players are also analyzed.
Qiguang Zhu
2014-05-01
Full Text Available To resolve the difficulty in establishing accurate priori noise model for the extended Kalman filtering algorithm, propose the fractional-order Darwinian particle swarm optimization (PSO algorithm has been proposed and introduced into the fuzzy adaptive extended Kalman filtering algorithm. The natural selection method has been adopted to improve the standard particle swarm optimization algorithm, which enhanced the diversity of particles and avoided the premature. In addition, the fractional calculus has been used to improve the evolution speed of particles. The PSO algorithm after improved has been applied to train fuzzy adaptive extended Kalman filter and achieve the simultaneous localization and mapping. The simulation results have shown that compared with the geese particle swarm optimization training of fuzzy adaptive extended Kalman filter localization and mapping algorithm, has been greatly improved in terms of localization and mapping.
AMJoin: An Advanced Join Algorithm for Multiple Data Streams Using a Bit-Vector Hash Table
Kwon, Tae-Hyung; Kim, Hyeon-Gyu; Kim, Myoung-Ho; Son, Jin-Hyun
A multiple stream join is one of the most important but high cost operations in ubiquitous streaming services. In this paper, we propose a newly improved and practical algorithm for joining multiple streams called AMJoin, which improves the multiple join performance by guaranteeing the detection of join failures in constant time. To achieve this goal, we first design a new data structure called BiHT (Bit-vector Hash Table) and present the overall behavior of AMJoin in detail. In addition, we show various experimental results and their analyses for clarifying its efficiency and practicability.
Call Admission Control Algorithm for pre-stored VBR video streams
Tryfonas, Christos; Mehler, Andrew; Skiena, Steven
2008-01-01
We examine the problem of accepting a new request for a pre-stored VBR video stream that has been smoothed using any of the smoothing algorithms found in the literature. The output of these algorithms is a piecewise constant-rate schedule for a Variable Bit-Rate (VBR) stream. The schedule guarantees that the decoder buffer does not overflow or underflow. The problem addressed in this paper is the determination of the minimal time displacement of each new requested VBR stream so that it can be accomodated by the network and/or the video server without overbooking the committed traffic. We prove that this call-admission control problem for multiple requested VBR streams is NP-complete and inapproximable within a constant factor, by reducing it from the VERTEX COLOR problem. We also present a deterministic morphology-sensitive algorithm that calculates the minimal time displacement of a VBR stream request. The complexity of the proposed algorithm make it suitable for real-time determination of the time displacem...
魏关锋; 姚平经; LUOXing; ROETZELWilfried
2004-01-01
The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one optimum and computational difficulty for traditional algorithms to find the global optimum. Compared with deterministic algorithms, evolutionary computation provides a promising approach to tackle this problem. In this paper, a mathematical model of multi-stream heat exchangers network synthesis problem is setup. Different from the assumption of isothermal mixing of stream splits and thus linearity constraints of Yee et al., non-isothermal mixing is supported. As a consequence, nonlinear constraints are resulted and nonconvexity of the objective function is added. To solve the mathematical model, an algorithm named GA/SA (parallel genetic/simulated annealing algorithm) is detailed for application to the multi-stream heat exchanger network synthesis problem. The performance of the proposed approach is demonstrated with three examples and the obtained solutions indicate the presented approach is effective for multi-stream HENS.
Structural Analysis Extended with Active Fault Isolation - Methods and Algorithms
Gelso, Esteban R.; Blanke, Mogens
2009-01-01
on system inputs can considerably enhance fault isolability. This paper investigates this possibility of active fault isolation from a structural point of view. While such extension of the structural analysis approach was suggested earlier, algorithms and case studies were needed to explore this theory....... The paper develops algorithms for investigation of the possibilities of active structural isolation and it offers illustrative examples and a larger case study to explore the properties of active structural isolability ideas....
Improved algorithms for approximate string matching (extended abstract
Papamichail Georgios
2009-01-01
Full Text Available Abstract Background The problem of approximate string matching is important in many different areas such as computational biology, text processing and pattern recognition. A great effort has been made to design efficient algorithms addressing several variants of the problem, including comparison of two strings, approximate pattern identification in a string or calculation of the longest common subsequence that two strings share. Results We designed an output sensitive algorithm solving the edit distance problem between two strings of lengths n and m respectively in time O((s - |n - m|·min(m, n, s + m + n and linear space, where s is the edit distance between the two strings. This worst-case time bound sets the quadratic factor of the algorithm independent of the longest string length and improves existing theoretical bounds for this problem. The implementation of our algorithm also excels in practice, especially in cases where the two strings compared differ significantly in length. Conclusion We have provided the design, analysis and implementation of a new algorithm for calculating the edit distance of two strings with both theoretical and practical implications. Source code of our algorithm is available online.
Extended seizure detection algorithm for intracranial EEG recordings
Kjaer, T. W.; Remvig, L. S.; Henriksen, J.
2010-01-01
Objective: We implemented and tested an existing seizure detection algorithm for scalp EEG (sEEG) with the purpose of improving it to intracranial EEG (iEEG) recordings. Method: iEEG was obtained from 16 patients with focal epilepsy undergoing work up for resective epilepsy surgery. Each patient...... had 4 or 5 recorded seizures and 24 hours of non-ictal data were used for evaluation. Data from three electrodes placed at the ictal focus were used for the analysis. A wavelet based feature extraction algorithm delivered input to a support vector machine (SVM) classifier for distinction between ictal...... the original implementation a sensitivity of 92.8% and a false positive ratio (FPR) of 0.93/h were obtained. Our extension of the algorithm rendered a 95.9% sensitivity and only 0.65 false detections per hour. Conclusion: Better seizure detection can be performed when the higher frequencies in the iEEG were...
A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances
Nicolas Normand
2014-09-01
Full Text Available We describe an algorithm that computes a “translated” 2D Neighborhood-Sequence Distance Transform (DT using a look up table approach. It requires a single raster scan of the input image and produces one line of output for every line of input. The neighborhood sequence is specified either by providing one period of some integer periodic sequence or by providing the rate of appearance of neighborhoods. The full algorithm optionally derives the regular (centered DT from the “translated” DT, providing the result image on-the-ﬂy, with a minimal delay, before the input image is fully processed. Its efficiency can benefit all applications that use neighborhood- sequence distances, particularly when pipelined processing architectures are involved, or when the size of objects in the source image is limited.
A genetic algorithm to reduce stream channel cross section data
Berenbrock, C.
2006-01-01
A genetic algorithm (GA) was used to reduce cross section data for a hypothetical example consisting of 41 data points and for 10 cross sections on the Kootenai River. The number of data points for the Kootenai River cross sections ranged from about 500 to more than 2,500. The GA was applied to reduce the number of data points to a manageable dataset because most models and other software require fewer than 100 data points for management, manipulation, and analysis. Results indicated that the program successfully reduced the data. Fitness values from the genetic algorithm were lower (better) than those in a previous study that used standard procedures of reducing the cross section data. On average, fitnesses were 29 percent lower, and several were about 50 percent lower. Results also showed that cross sections produced by the genetic algorithm were representative of the original section and that near-optimal results could be obtained in a single run, even for large problems. Other data also can be reduced in a method similar to that for cross section data.
Contrasting responses of the extended Gulf Stream to severe winter forcing
Jacobs, Z.; Grist, J. P.; Marsh, R.; Josey, S. A.; Sinha, B.
2015-12-01
Changes in the path and strength of the extended Gulf Stream, downstream of Cape Hatteras, and the North Atlantic Current (GSNAC), are associated with strong wintertime air-sea interactions that can further influence the atmospheric storm track. The GSNAC response to anomalous air-sea heat fluxes in particular is dependent on the location of excess heat loss, in turn related to meteorological circumstances. Outbreaks of cold continental air may lead to excess cooling over the Sargasso Sea, as in 1976-77. Under these circumstances, the Gulf Stream may intensify through a steepening of cross-stream density gradients. An alternative scenario prevailed during the cold outbreak of 2013-14 where excess cooling occurred over the central subpolar gyre and may have influenced the extreme storminess experienced in western Europe. An objectively-analysed temperature and salinity product (EN4) is used to investigate the variability of the GSNAC. Temperature and salinity profiles are used to obtain geostrophic transport at selected GSNAC transects, confirming strong horizontal temperature gradients and a positive geostrophic velocity anomaly at 70oW in spring 1977, the strongest spring transport seen in the 1970s at this location. In addition to observations, an eddy-resolving model hindcast spanning 1970-2013, is used to further characterise GSNAC transport variability, allowing a fuller assessment of the relationship between the winter surface heat flux, end-of-winter mixed layer depth, subtropical mode water volume and GSNAC transports. Preliminary results reveal a significant negative correlation between the winter surface heat flux over the Sargasso Sea and the GSNAC transport in the following spring.
A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream
Amineh Amini
2014-01-01
Full Text Available Data streams are continuously generated over time from Internet of Things (IoT devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.
A fast density-based clustering algorithm for real-time Internet of Things stream.
Amini, Amineh; Saboohi, Hadi; Wah, Teh Ying; Herawan, Tutut
2014-01-01
Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.
A Streaming Algorithm for Online Estimation of Temporal and Spatial Extent of Delays
Kittipong Hiriotappa
2017-01-01
Full Text Available Knowing traffic congestion and its impact on travel time in advance is vital for proactive travel planning as well as advanced traffic management. This paper proposes a streaming algorithm to estimate temporal and spatial extent of delays online which can be deployed with roadside sensors. First, the proposed algorithm uses streaming input from individual sensors to detect a deviation from normal traffic patterns, referred to as anomalies, which is used as an early indication of delay occurrence. Then, a group of consecutive sensors that detect anomalies are used to temporally and spatially estimate extent of delay associated with the detected anomalies. Performance evaluations are conducted using a real-world data set collected by roadside sensors in Bangkok, Thailand, and the NGSIM data set collected in California, USA. Using NGSIM data, it is shown qualitatively that the proposed algorithm can detect consecutive occurrences of shockwaves and estimate their associated delays. Then, using a data set from Thailand, it is shown quantitatively that the proposed algorithm can detect and estimate delays associated with both recurring congestion and incident-induced nonrecurring congestion. The proposed algorithm also outperforms the previously proposed streaming algorithm.
Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality
Sidick, Erkin
2008-01-01
Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.
2015-01-01
In this work the Benchmark Simulation Model No.2 is extended with processes for nitrous oxide production and for side-stream partial nitritation/Anammox (PN/A) treatment. For these extensions the Activated Sludge Model for Greenhouse gases No.1 was used to describe the main waterline, whereas...... the Complete Autotrophic Nitrogen Removal (CANR) model was used to describe the side-stream (PN/A) treatment. Comprehensive simulations were performed to assess the extended model. Steady-state simulation results revealed the following: (i) the implementation of a continuous CANR side-stream reactor has...... increased the total nitrogen removal by 10%; (ii) reduced the aeration demand by 16% compared to the base case, and (iii) the activity of ammonia-oxidizing bacteria is most influencing nitrous oxide emissions. The extended model provides a simulation platform to generate, test and compare novel control...
RESOLVE: A new algorithm for aperture synthesis imaging of extended emission in radio astronomy
Junklewitz, H.; Bell, M. R.; Selig, M.; Enßlin, T. A.
2016-02-01
We present resolve, a new algorithm for radio aperture synthesis imaging of extended and diffuse emission in total intensity. The algorithm is derived using Bayesian statistical inference techniques, estimating the surface brightness in the sky assuming a priori log-normal statistics. resolve estimates the measured sky brightness in total intensity, and the spatial correlation structure in the sky, which is used to guide the algorithm to an optimal reconstruction of extended and diffuse sources. During this process, the algorithm succeeds in deconvolving the effects of the radio interferometric point spread function. Additionally, resolve provides a map with an uncertainty estimate of the reconstructed surface brightness. Furthermore, with resolve we introduce a new, optimal visibility weighting scheme that can be viewed as an extension to robust weighting. In tests using simulated observations, the algorithm shows improved performance against two standard imaging approaches for extended sources, Multiscale-CLEAN and the Maximum Entropy Method.
A New Extended Projection-Based Image Registration Algorithm
CHENHuafu; YAODezhong
2005-01-01
In the presence of fixed -pattern noise, the projection-based image registration technique is effective but its implementation is only confined to translation registration. Presented in this paper is an extended projectionbased image registration technique in which, by rearranging the projections of images, the image registration is implemented in two steps: rotation and translation, to accomplish two-dimensional (2-D) image registration. Thisapproach transforms the general 2-D optimization procedure into an 1-D projection optimization, thus considerably reducing the amount of computation. The validity ofthe new method is testified by simulation experiment.
The analysis of the number of fixed points in the key extending algorithm of RC4
2008-01-01
The probabilities of the state transitions of the initial value So in the S table of RC4 are described by a kind of bistochastic matrices, and then a computational formula for such bistochastic matrices is given, by which the mathematical expectation of the number of fixed points in the key extending algorithm of RC4 is obtained. As a result, a statistical weakness of the key extending algorithm of RC4 is presented.
Transmission Algorithm with QoS Considerations for a Sustainable MPEG Streaming Service
Sang-Hyong Kim
2017-03-01
Full Text Available With the proliferation of heterogeneous networks, there is a need to provide multimedia stream services in a sustainable manner. It is especially critical to maintain the Quality of Service (QoS standards. Existing multimedia streaming services have been studied to guarantee QoS on the receiving side. QoS has not been ensured due to the fact that the loss of streaming data to be transmitted has not been considered in network conditions. With an algorithm that considers the QoS and can reduce the overhead of the network, it will be possible to reduce the transmission error and wastage of communication network resources. In this paper, we propose a scheme that improves the reliability of multimedia transmissions by using an adaptive algorithm that switches between UDP (User Datagram Protocol and TCP (Transmission Control Protocol based on the size of the data. In addition, we present a method that retransmits essential portions of the multimedia data, thus improving transmission efficiency. We simulate an MPEG (Moving Picture Experts Group stream service and evaluate the performance of the proposed adaptive MPEG stream service.
Linked-Tree: An Aggregate Query Algorithm Based on Sliding Window over Data Stream
YU Yaxin; WANG Guoren; SU Dong; ZHU Xinhua
2006-01-01
How to process aggregate queries over data streams efficiently and effectively have been becoming hot research topics in both academic community and industrial community. Aiming at the issues, a novel Linked-tree algorithm based on sliding window is proposed in this paper. Due to the proposal of concept area, the Linked-tree algorithm reuses many primary results in last window and then avoids lots of unnecessary repeated comparison operations between two successive windows. As a result, execution efficiency of MAX query is improved dramatically. In addition, since the size of memory is relevant to the number of areas but irrelevant to the size of sliding window, memory is economized greatly. The extensive experimental results show that the performance of Linked-tree algorithm has significant improvement gains over the traditional SC (Simple Compared) algorithm and Ranked-tree algorithm.
Fast and Faster: A Comparison of Two Streamed Matrix Decomposition Algorithms
Řeh{\\ru}řek, Radim
2011-01-01
With the explosion of the size of digital dataset, the limiting factor for decomposition algorithms is the \\emph{number of passes} over the input, as the input is often stored out-of-core or even off-site. Moreover, we're only interested in algorithms that operate in \\emph{constant memory} w.r.t. to the input size, so that arbitrarily large input can be processed. In this paper, we present a practical comparison of two such algorithms: a distributed method that operates in a single pass over the input vs. a streamed two-pass stochastic algorithm. The experiments track the effect of distributed computing, oversampling and memory trade-offs on the accuracy and performance of the two algorithms. To ensure meaningful results, we choose the input to be a real dataset, namely the whole of the English Wikipedia, in the application settings of Latent Semantic Analysis.
Lelu, Alain; Cuxac, Pascal
2008-01-01
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, independent from any initial conditions and ordering of the data-vectors stream, 2) the cognitive challenge: we have implemented a stringent selection process of association rules between clusters at time t-1 and time t for directly generating the main conclusions about the dynamics of a data-stream. We illustrate these points with an application to a two years and 2600 documents scientific information database.
A Novel High Dimensional and High Speed Data Streams Algorithm: HSDStream
Irshad Ahmed
2016-09-01
Full Text Available This paper presents a novel high speed clustering scheme for high-dimensional data stream. Data stream clustering has gained importance in different applications, for example, network monitoring, intrusion detection, and real-time sensing. High dimensional stream data is inherently more complex when used for clustering because the evolving nature of the stream data and high dimensionality make it non-trivial. In order to tackle this problem, projected subspace within the high dimensions and limited window sized data per unit of time are used for clustering purpose. We propose a High Speed and Dimensions data stream clustering scheme (HSDStream which employs exponential mov-ing averages to reduce the size of the memory and speed up the processing of projected subspace data stream. It works in three steps: i initialization, ii real-time maintenance of core and outlier micro-clusters, and iii on-demand offline generation of the final clusters. The proposed algorithm is tested against high dimensional density-based projected clustering (HDDStream for cluster purity, memory usage, and the cluster sensitivity. Experi-mental results are obtained for corrected KDD intrusion detection dataset. These results show that HSDStream outperforms the HDDStream in all performance metrics, especially, the memory usage and the processing speed.
Türkay Gökgöz
2015-10-01
Full Text Available Multi-representation databases (MRDBs are used in several geographical information system applications for different purposes. MRDBs are mainly obtained through model and cartographic generalizations. Simplification is the essential operator of cartographic generalization, and streams and lakes are essential features in hydrography. In this study, a new algorithm was developed for the simplification of streams and lakes. In this algorithm, deviation angles and error bands are used to determine the characteristic vertices and the planimetric accuracy of the features, respectively. The algorithm was tested using a high-resolution national hydrography dataset of Pomme de Terre, a sub-basin in the USA. To assess the performance of the new algorithm, the Bend Simplify and Douglas-Peucker algorithms, the medium-resolution hydrography dataset of the sub-basin, and Töpfer’s radical law were used. For quantitative analysis, the vertex numbers, the lengths, and the sinuosity values were computed. Consequently, it was shown that the new algorithm was able to meet the main requirements (i.e., accuracy, legibility and aesthetics, and storage.
RESOLVE: A new algorithm for aperture synthesis imaging of extended emission in radio astronomy
Junklewitz, H; Selig, M; Enßlin, T A
2013-01-01
We present RESOLVE, a new algorithm for radio aperture synthesis imaging of extended and diffuse emission in total intensity. The algorithm is derived using Bayesian statistical inference techniques, estimating the surface brightness in the sky assuming a priori log-normal statistics. RESOLVE not only estimates the measured sky brightness in total intensity, but also its spatial correlation structure, which is used to guide the algorithm to an optimal reconstruction of extended and diffuse sources. For a radio interferometer, it succeeds in deconvolving the effects of the instrumental point spread function during this process. Additionally, RESOLVE provides a map with an uncertainty estimate of the reconstructed surface brightness. Furthermore, with RESOLVE we introduce a new, optimal visibility weighting scheme that can be viewed as an extension to robust weighting. In tests using simulated observations, the algorithm shows improved performance against two standard imaging approaches for extended sources, Mu...
The extended halo of Centaurus A: uncovering satellites, streams and substructures
Crnojević, D; Spekkens, K; Caldwell, N; Guhathakurta, P; McLeod, B; Seth, A; Simon, J; Strader, J; Toloba, E
2015-01-01
We present the widest-field resolved stellar map to date of the closest ($D\\sim3.8$ Mpc) massive elliptical galaxy NGC 5128 (Centaurus A; Cen A), extending out to a projected galactocentric radius of $\\sim150$ kpc. The dataset is part of our ongoing Panoramic Imaging Survey of Centaurus and Sculptor (PISCeS) utilizing the Magellan/Megacam imager. We resolve a population of old red giant branch stars down to $\\sim1.5$ mag below the tip of the red giant branch, reaching surface brightness limits as low as $\\mu_{V,0}\\sim32$ mag arcsec$^{-2}$. The resulting spatial stellar density map highlights a plethora of previously unknown streams, shells, and satellites, including the first tidally disrupting dwarf around Cen A, which underline its active accretion history. We report 13 previously unknown dwarf satellite candidates, of which 9 are confirmed to be at the distance of Cen A (the remaining 4 are not resolved into stars), with magnitudes in the range $M_V=-7.2$ to $-13.0$, central surface brightness values of $\\...
Memory Copy Optimization for Streaming Gateway Transco ding：Mo dels and Algorithms
LI Mingzhe; WANG Jinlin; CHEN Xiao; YE Xiaozhou
2016-01-01
Repeated memory copy during proto-col translation inhibits capacity of a streaming media gateway. Unlike existing optimization techniques that rely on platform-specific features, this paper investigates algorithm-level platform-independent strategies. A math-ematical concept of the buf-string is proposed to model the protocol transcoding process. Based on this model three payload extraction algorithms that can reduce mem-ory copy are presented. The streaming gateway used in the Next-generation broadcasting (NGB) and the Next-generation on-demand (NGOD) system is taken as an ex-ample to demonstrate and evaluate our strategies. Experi-mental results from an x86 host and an embedded system prove that our strategies can reduce CPU overhead by 15%to 45%, and optimize the linear space complexity to a con-stant one.
Becker, Stefan; Scherer-Negenborn, Norbert; Thakkar, Pooja; Hübner, Wolfgang; Arens, Michael
2016-10-01
This paper is a continuation of the work of Becker et al.1 In their work, they analyzed the robustness of various background subtraction algorithms on fused video streams originating from visible and infrared cameras. In order to cover a broader range of background subtraction applications, we show the effects of fusing infrared-visible video streams from vibrating cameras on a large set of background subtraction algorithms. The effectiveness is quantitatively analyzed on recorded data of a typical outdoor sequence with a fine-grained and accurate annotation of the images. Thereby, we identify approaches which can benefit from fused sensor signals with camera jitter. Finally conclusions on what fusion strategies should be preferred under such conditions are given.
Performance Evaluation of Multipath Discovery Algorithms for VoD Streaming in Wireless Mesh Network
Praful C. Ramteke
2014-07-01
Full Text Available Transmission and routing of video data over wireless network is a challenging task because of wireless interferences. To improve the performance of video on demand transmission over wireless networks multipath algorithms are used. IPD/S (Iterative path discovery/ selection PPD/S (Parallel Path discovery/selection are two algorithms which is used for discovering maximum number of edge disjoint paths from source to destination, for each VoD request by considering the effects of wireless interferences. In this paper performance evaluation of these multipath discovery algorithms for VoD (Video on demand streaming in wireless mesh network is presented. These algorithms are evaluated on the bases of Number of Path discovers, Packet drop ratio. Simulation result shows that PPD/S works batter as compared to IPD/S because it’s able to discover more paths than IPD/S under same circumstances
XUEGuangtao; SHIHua; YOUJinyuan; YAOWensheng
2003-01-01
Mobile peer-to-peer media streaming systems are expected to become as popular as the peer-to-peer file sharing systems. In this paper, we study two key problems arising from mobile peer-to-peer media streaming: the stability of interconnection between supplying peers and requesting peers in mobile peer-to-peer streaming system; and fast capacity amplification of the entire mobile peer-to-peer streaming system. We use the Stable group algorithm to characterize user mobility in mobile ad hoc networks. Based on the stable group, we then propose a distributed Stable-group differentiated admission control algorithm (SGDACp2p), which leads to fast amplifying the system's total streaming capacity using its self-growing. At last, the extensive simulation results are presented to compare between the SGDACp2p and traditional methods to prove the superiority of the algorithm.
Shrestha, Kalyan; Mompean, Gilmar; Calzavarini, Enrico
2016-02-01
A finite-volume (FV) discretization method for the lattice Boltzmann (LB) equation, which combines high accuracy with limited computational cost is presented. In order to assess the performance of the FV method we carry out a systematic comparison, focused on accuracy and computational performances, with the standard streaming lattice Boltzmann equation algorithm. In particular we aim at clarifying whether and in which conditions the proposed algorithm, and more generally any FV algorithm, can be taken as the method of choice in fluid-dynamics LB simulations. For this reason the comparative analysis is further extended to the case of realistic flows, in particular thermally driven flows in turbulent conditions. We report the successful simulation of high-Rayleigh number convective flow performed by a lattice Boltzmann FV-based algorithm with wall grid refinement.
An extended ANN-based high speed accurate distance protection algorithm
Sanaye-Pasand, M. [University of Tehran, Tehran (Iran). School of Electrical and Computer Engineering; Khorashadi-Zadeh, H. [University of Birjand, Birjand (Iran). Department of Electrical Engineering
2006-07-15
This paper presents a new neural network based transmission line distance protection module. The proposed module uses samples of voltage and current signals to learn the hidden relationship existing in the input patterns. Simulation studies are preformed and influence of changing system parameters such as fault resistance and source impedance is studied. Details of the design procedure and the results of performance studies with the proposed relay are given in the paper. In addition, an extended ANN-based technique which, uses the proposed neural network distance relay as its basis is described. The extended technique uses neutral current as its new input. Since, this technique adds a new dimension to the input decision space, the accuracy of the algorithm is increased. Various simulation studies are performed and capabilities of the extended algorithm are investigated. Performance studies results show that the proposed algorithm is fast and accurate. Some of the simulation studies are presented in the paper. (author)
The Extended Halo of Centaurus A: Uncovering Satellites, Streams, and Substructures
Crnojević, D.; Sand, D. J.; Spekkens, K.; Caldwell, N.; Guhathakurta, P.; McLeod, B.; Seth, A.; Simon, J. D.; Strader, J.; Toloba, E.
2016-05-01
We present the widest-field resolved stellar map to date of the closest (D˜ 3.8 Mpc) massive elliptical galaxy NGC 5128 (Centaurus A; Cen A), extending out to a projected galactocentric radius of ˜150 kpc. The data set is part of our ongoing Panoramic Imaging Survey of Centaurus and Sculptor (PISCeS) utilizing the Magellan/Megacam imager. We resolve a population of old red giant branch (RGB) stars down to ˜1.5 mag below the tip of the RGB, reaching surface brightness limits as low as {μ }V,0˜ 32 mag arcsec-2. The resulting spatial stellar density map highlights a plethora of previously unknown streams, shells, and satellites, including the first tidally disrupting dwarf around Cen A (CenA-MM-Dw3), which underline its active accretion history. We report 13 previously unknown dwarf satellite candidates, of which 9 are confirmed to be at the distance of Cen A (the remaining 4 are not resolved into stars), with magnitudes in the range {M}V=-7.2 to -13.0, central surface brightness values of {μ }V,0=25.4{--}26.9 mag arcsec-2, and half-light radii of {r}h=0.22{--}2.92 {{kpc}}. These values are in line with Local Group dwarfs but also lie at the faint/diffuse end of their distribution; interestingly, CenA-MM-Dw3 has similar properties to the recently discovered ultradiffuse galaxies in Virgo and Coma. Most of the new dwarfs are fainter than the previously known Cen A satellites. The newly discovered dwarfs and halo substructures are discussed in light of their stellar populations, and they are compared to those discovered by the PAndAS survey of M31. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.
Extended-Maxima Transform Watershed Segmentation Algorithm for Touching Corn Kernels
Yibo Qin
2013-01-01
Full Text Available Touching corn kernels are usually oversegmented by the traditional watershed algorithm. This paper proposes a modified watershed segmentation algorithm based on the extended-maxima transform. Firstly, a distance-transformed image is processed by the extended-maxima transform in the range of the optimized threshold value. Secondly, the binary image obtained by the preceding process is run through the watershed segmentation algorithm, and watershed ridge lines are superimposed on the original image, so that touching corn kernels are separated into segments. Fifty images which all contain 400 corn kernels were tested. Experimental results showed that the effect of segmentation is satisfactory by the improved algorithm, and the accuracy of segmentation is as high as 99.87%.
Yuanlong Cao
2012-01-01
Full Text Available The content-rich multimedia streaming will be the most attractive services in the next-generation networks. With function of distribute data across multipath end-to-end paths based on SCTP's multihoming feature, concurrent multipath transfer SCTP (CMT-SCTP has been regarded as the most promising technology for the efficient multimedia streaming transmission. However, the current researches on CMT-SCTP mainly focus on the algorithms related to the data delivery performance while they seldom consider the background traffic factors. Actually, background traffic of realistic network environments has an important impact on the performance of CMT-SCTP. In this paper, we firstly investigate the effect of background traffic on the performance of CMT-SCTP based on a close realistic simulation topology with reasonable background traffic in NS2, and then based on the localness nature of background flow, a further improved retransmission algorithm, named RTX_CSI, is proposed to reach more benefits in terms of average throughput and achieve high users' experience of quality for multimedia streaming services.
Compressed domain moving object extraction algorithm for MPEG-2 video stream
Yang, Gaobo; Wang, Xiaojing; Zhang, Zhaoyang
2007-11-01
In this paper, a compressed domain moving object extraction algorithm is proposed for MPEG-2 video stream. It is mainly based on the histogram analysis of motion vectors, which can be easily obtained by partially decoding the MPEG-2 video stream. The whole algorithm framework can be divided into three key steps: motion vector pre-processing, histogram analysis of motion vector and motion vector similarity based region growing for final mask generation. A piecewise cubic hermit interpolation is utilized to form a dense motion field. The outputs of region growing algorithm based on similarity matching are the final segmentation results of moving object. These final segmentation results are further smoothed and interpolated by B-spline curve estimation. Experimental results on several test sequences demonstrate that desirable segmentation results are obtained. The accuracy of segmentation results is improved obviously, nearly to pixel level accuracy because of B-spline curve representation of segmented object. For segmentation efficiency, the processing speed is about 30ms per frame, which can meet the requirements of real time applications.
Extending the Stream Reasoning in DyKnow with Spatial Reasoning in RCC-8
Lazarovski, Daniel
2012-01-01
Autonomous systems require a lot of information about the environment in which they operate in order to perform different high-level tasks. The information is made available through various sources, such as remote and on-board sensors, databases, GIS, the Internet, etc. The sensory input especially is incrementally available to the systems and can be represented as streams. High-level tasks often require some sort of reasoning over the input data, however raw streaming input is often not suit...
On the sequences ri, si, ti ∈ ℤ related to extended Euclidean algorithm and continued fractions
Muhammad, Khairun Nisak; Kamarulhaili, Hailiza
2016-06-01
The extended Euclidean Algorithm is a practical technique used in many cryptographic applications, where it computes the sequences ri, si, ti ∈ ℤ that always satisfy ri = si a+ tib. The integer ri is the remainder in the ith sequences. The sequences si and ti arising from the extended Euclidean algorithm are equal, up to sign, to the convergents of the continued fraction expansion of a/b. The values of (ri, si, ti) satisfy various properties which are used to solve the shortest vector problem in representing point multiplications in elliptic curves cryptography, namely the GLV (Gallant, Lambert & Vanstone) integer decomposition method and the ISD (integer sub decomposition) method. This paper is to extend the proof for each of the existing properties on (ri, si, ti). We also generate new properties which are relevant to the sequences ri, si, ti ∈ ℤ. The concepts of Euclidean algorithm, extended Euclidean algorithm and continued fractions are intertwined and the properties related to these concepts are proved. These properties together with the existing properties of the sequence (ri, si, ti) are regarded as part and parcel of the building blocks of a new generation of an efficient cryptographic protocol.
Extended Mixed-Efects Item Response Models with the MH-RM Algorithm
Chalmers, R. Philip
2015-01-01
A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…
Fast Adapting Ensemble: A New Algorithm for Mining Data Streams with Concept Drift
Agustín Ortíz Díaz
2015-01-01
Full Text Available The treatment of large data streams in the presence of concept drifts is one of the main challenges in the field of data mining, particularly when the algorithms have to deal with concepts that disappear and then reappear. This paper presents a new algorithm, called Fast Adapting Ensemble (FAE, which adapts very quickly to both abrupt and gradual concept drifts, and has been specifically designed to deal with recurring concepts. FAE processes the learning examples in blocks of the same size, but it does not have to wait for the batch to be complete in order to adapt its base classification mechanism. FAE incorporates a drift detector to improve the handling of abrupt concept drifts and stores a set of inactive classifiers that represent old concepts, which are activated very quickly when these concepts reappear. We compare our new algorithm with various well-known learning algorithms, taking into account, common benchmark datasets. The experiments show promising results from the proposed algorithm (regarding accuracy and runtime, handling different types of concept drifts.
GLOBAL OPTIMIZATION OF PUMP CONFIGURATION PROBLEM USING EXTENDED CROWDING GENETIC ALGORITHM
Zhang Guijun; Wu Tihua; Ye Rong
2004-01-01
An extended crowding genetic algorithm (ECGA) is introduced for solving optimal pump configuration problem,which was presented by T.Westerlund in 1994.This problem has been found to be non-convex,and the objective function contained several local optima and global optimality could not be ensured by all the traditional MINLP optimization method.The concepts of species conserving and composite encoding are introduced to crowding genetic algorithm (CGA) for maintain the diversity of population more effectively and coping with the continuous and/or discrete variables in MINLP problem.The solution of three-levels pump configuration got from DICOPT++ software (OA algorithm) is also given.By comparing with the solutions obtained from DICOPT++,ECP method,and MIN-MIN method,the ECGA algorithm proved to be very effective in finding the global optimal solution of multi-levels pump configuration via using the problem-specific information.
Nourelfath, M.; Nahas, N.; Montreuil, B.
2007-12-01
This article uses a hybrid optimization approach to solve the discrete facility layout problem (FLP), modelled as a quadratic assignment problem (QAP). The idea of this approach design is inspired by the ant colony meta-heuristic optimization method, combined with the extended great deluge (EGD) local search technique. Comparative computational experiments are carried out on benchmarks taken from the QAP-library and from real life problems. The performance of the proposed algorithm is compared to construction and improvement heuristics such as H63, HC63-66, CRAFT and Bubble Search, as well as other existing meta-heuristics developed in the literature based on simulated annealing (SA), tabu search and genetic algorithms (GAs). This algorithm is compared also to other ant colony implementations for QAP. The experimental results show that the proposed ant colony optimization/extended great deluge (ACO/EGD) performs significantly better than the existing construction and improvement algorithms. The experimental results indicate also that the ACO/EGD heuristic methodology offers advantages over other algorithms based on meta-heuristics in terms of solution quality.
Guo Jiao
2014-08-01
Full Text Available A system impulse response with low sidelobes is critical in synthetic aperture radar (SAR images because sidelobes contribute to noise and interfere with nearby scatterers. However, the conventional tricks of sidelobe suppression are unable to be exactly applied to the case of spaceborne sliding spotlight SAR due to great azimuth shifts in both time and frequency domains. In this paper, an extended chirp scaling algorithm is presented for spaceborne sliding spotlight SAR data imaging. The proposed algorithm firstly uses the spectral analysis (SPECAN technique to avoid the azimuth spectrum folding effect and then employs the chirp scaling (CS algorithm to achieve data focusing, i.e., the so-called two-step approach. To suppress the sidelobe level, an efficient strategy for the azimuth spectral weighting which only involves matrix multiplications and short fast Fourier transformations (FFTs is proposed, which is a post-process executed on the focused SAR image and particularly simple to be implemented. The SAR image processed by the proposed extended CS algorithm is very precise and perfectly phase-preserving. In the end, computer simulation results verify the analysis and confirm the validity of the proposed algorithm.
Guo Jiao; Xu Youshuan; Fu Longsheng
2014-01-01
A system impulse response with low sidelobes is critical in synthetic aperture radar (SAR) images because sidelobes contribute to noise and interfere with nearby scatterers. However, the conventional tricks of sidelobe suppression are unable to be exactly applied to the case of space-borne sliding spotlight SAR due to great azimuth shifts in both time and frequency domains. In this paper, an extended chirp scaling algorithm is presented for spaceborne sliding spotlight SAR data imaging. The proposed algorithm firstly uses the spectral analysis (SPECAN) technique to avoid the azimuth spectrum folding effect and then employs the chirp scaling (CS) algorithm to achieve data focusing, i.e., the so-called two-step approach. To suppress the sidelobe level, an efficient strategy for the azimuth spectral weighting which only involves matrix multiplications and short fast Fourier transformations (FFTs) is proposed, which is a post-process executed on the focused SAR image and particularly simple to be implemented. The SAR image processed by the proposed extended CS algorithm is very precise and perfectly phase-preserving. In the end, computer simulation results verify the analysis and confirm the validity of the proposed algorithm.
Extended models of gravity in SNIa cosmological data using genetic algorithms
López-Corona, O
2015-01-01
In this talk I explained briefly the advantages of using genetic algorithms on any measured data but specially astronomical ones. This kind of algorithms are not only a better computational paradigm, but they also allow for a more profound data treatment enhancing theoretical developments. As an example, I will use the SNIa cosmological data to fit the extended metric theories of gravity of Carranza et al. (2013, 2014) showing that the best parameters combination deviate from theoretical predicted ones by a minimal amount. This means that these kind of gravitational extensions are statistically robust and show that no dark matter and/or energy is required to explain the observations.
Extended models of gravity in SNIa cosmological data using genetic algorithms
López-Corona, O.
2015-04-01
In this talk I explained briefly the advantages of using genetic algorithms on any measured data but specially astronomical ones. This kind of algorithms are not only a better computational paradigm, but they also allow for a more profound data treatment enhancing theoretical developments. As an example, I will use the SNIa cosmological data to fit the extended metric theories of gravity of Carranza et al. (2013, 2014) showing that the best parameters combination deviate from theoretical predicted ones by a minimal amount. This means that these kind of gravitational extensions are statistically robust and show that no dark matter and/or energy is required to explain the observations.
Islanding Detection for Microgrid Based on Frequency Tracking Using Extended Kalman Filter Algorithm
Bin Li
2014-01-01
Full Text Available Islanding detection is essential for secure and reliable operation of microgrids. Considering the relationship between the power generation and the load in microgrids, frequency may vary with time when islanding occurs. As a common approach, frequency measurement is widely used to detect islanding condition. In this paper, a novel frequency calculation algorithm based on extended Kalman filter was proposed to track dynamic frequency of the microgrid. Taylor series expansion was introduced to solve nonlinear state equations. In addition, a typical microgrid model was built using MATLAB/SIMULINK. Simulation results demonstrated that the proposed algorithm achieved great stability and strong robustness in of tracking dynamic frequency.
A DIGITAL CALIBRATION ALGORITHM WITH VARIABLE-AMPLITUDE DITHERING FOR DOMAIN-EXTENDED PIPELINE ADCS
Ting Li
2014-02-01
Full Text Available The pseudorandom noise dither (PN dither technique is used to measure domain-extended pipeline analog-to-digital converter (ADC gain errors and to calibrate them digitally, while the digital error correction technique is used to correct the comparator offsets through the use of redundancy bits. However, both these techniques suffer from three disadvantages: slow convergence speed, deduction of the amplitude of the transmitting signal, and deduction of the redundancy space. A digital calibration algorithm with variable-amplitude dithering for domain-extended pipeline ADCs is used in this research to overcome these disadvantages. The proposed algorithm is implemented in a 12-bit, 100 MS/s sample-rate pipeline ADC. The simulation results illustrate both static and dynamic performance improvement after calibration. Moreover, the convergence speed is much faster.
ANN-based Control of a Wheeled Inverted Pendulum System Using an Extended DBD Learning Algorithm
David Cruz
2016-05-01
Full Text Available This paper presents a dynamic model for a self-balancing vehicle using the Euler-Lagrange approach. The design and deployment of an artificial neuronal network (ANN in a closed-loop control is described. The ANN is characterized by integration of the extended delta bar-delta algorithm (DBD, which accelerates the adjustment of synaptic weights. The results of the control strategy in the dynamic model of the robot are also presented.
ANN-Based Control of a Wheeled Inverted Pendulum System Using an Extended DBD Learning Algorithm
David Cruz
2016-05-01
Full Text Available This paper presents a dynamic model for a self-balancing vehicle using the Euler-Lagrange approach. The design and deployment of an artificial neuronal network (ANN in a closed-loop control is described. The ANN is characterized by integration of the extended delta-bar-delta algorithm (DBD, which accelerates the adjustment of synaptic weights. The results of the control strategy in the dynamic model of the robot are also presented.
2011-01-01
Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data. Some adaptation algorithms for fuzzy system based on extended Kalman filter are presented in this paper, which allows obtaining accurate models without renounce the computational efficiency that characterizes the Kalman filter, and allows ...
Low-cost attitude determination system using an extended Kalman filter (EKF) algorithm
Esteves, Fernando M.; Nehmetallah, Georges; Abot, Jandro L.
2016-05-01
Attitude determination is one of the most important subsystems in spacecraft, satellite, or scientific balloon mission s, since it can be combined with actuators to provide rate stabilization and pointing accuracy for payloads. In this paper, a low-cost attitude determination system with a precision in the order of arc-seconds that uses low-cost commercial sensors is presented including a set of uncorrelated MEMS gyroscopes, two clinometers, and a magnetometer in a hierarchical manner. The faster and less precise sensors are updated by the slower, but more precise ones through an Extended Kalman Filter (EKF)-based data fusion algorithm. A revision of the EKF algorithm fundamentals and its implementation to the current application, are presented along with an analysis of sensors noise. Finally, the results from the data fusion algorithm implementation are discussed in detail.
An optimal algorithm based on extended kalman filter and the data fusion for infrared touch overlay
Zhou, AiGuo; Cheng, ShuYi; Pan, Qiang Biao; Sun, Dong Yu
2016-01-01
Current infrared touch overlay has problems on the touch point recognition which bring some burrs on the touch trajectory. This paper uses the target tracking algorithm to improve the recognition and smoothness of infrared touch overlay. In order to deal with the nonlinear state estimate problem for touch point tracking, we use the extended Kalman filter in the target tracking algorithm. And we also use the data fusion algorithm to match the estimate value with the original target trajectory. The experimental results of the infrared touch overlay demonstrate that the proposed target tracking approach can improve the touch point recognition of the infrared touch overlay and achieve much smoother tracking trajectory than the existing tracking approach.
Godsk, Mikkel
This paper presents a flexible model, ‘STREAM’, for transforming higher science education into blended and online learning. The model is inspired by ideas of active and collaborative learning and builds on feedback strategies well-known from Just-in-Time Teaching, Flipped Classroom, and Peer...... Instruction. The aim of the model is to provide both a concrete and comprehensible design toolkit for adopting and implementing educational technologies in higher science teaching practice and at the same time comply with diverse ambitions. As opposed to the above-mentioned feedback strategies, the STREAM...
Fiorino, Steven T.; Elmore, Brannon; Schmidt, Jaclyn; Matchefts, Elizabeth; Burley, Jarred L.
2016-05-01
Properly accounting for multiple scattering effects can have important implications for remote sensing and possibly directed energy applications. For example, increasing path radiance can affect signal noise. This study describes the implementation of a fast-calculating two-stream-like multiple scattering algorithm that captures azimuthal and elevation variations into the Laser Environmental Effects Definition and Reference (LEEDR) atmospheric characterization and radiative transfer code. The multiple scattering algorithm fully solves for molecular, aerosol, cloud, and precipitation single-scatter layer effects with a Mie algorithm at every calculation point/layer rather than an interpolated value from a pre-calculated look-up-table. This top-down cumulative diffusivity method first considers the incident solar radiance contribution to a given layer accounting for solid angle and elevation, and it then measures the contribution of diffused energy from previous layers based on the transmission of the current level to produce a cumulative radiance that is reflected from a surface and measured at the aperture at the observer. Then a unique set of asymmetry and backscattering phase function parameter calculations are made which account for the radiance loss due to the molecular and aerosol constituent reflectivity within a level and allows for a more accurate characterization of diffuse layers that contribute to multiple scattered radiances in inhomogeneous atmospheres. The code logic is valid for spectral bands between 200 nm and radio wavelengths, and the accuracy is demonstrated by comparing the results from LEEDR to observed sky radiance data.
A Fast Algorithm for Finding Point Sources in the Fermi Data Stream: FermiFAST
Ashathaman, Asha; Heyl, Jeremy S
2016-01-01
This paper presents a new and efficient algorithm for finding point sources in the photon event data stream from the Fermi Gamma-Ray Space Telescope. It can rapidly construct about most significant half of the Fermi Third Point Source catalogue (3FGL) with nearly 80% purity from the four years of data used to construct the catalogue. If a higher purity sample is desirable, one can achieve a sample that includes the most significant third of the Fermi 3FGL with only five percent of the sources unassociated with Fermi sources. Outside the galaxy plane, the contamination is essentially negligible. This software allows for rapid exploration of the Fermi data, simulation of the source detection to calculate the selection function of various sources and the errors in the obtained parameters of the sources detected.
Beirle, Steffen; Hörmann, Christoph; Jöckel, Patrick; Liu, Song; Penning de Vries, Marloes; Pozzer, Andrea; Sihler, Holger; Valks, Pieter; Wagner, Thomas
2016-07-01
The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1-0.2 × 1015 molecules cm-2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study.
Extended reactance domain algorithms for DoA estimation onto an ESPAR antennas
Harabi, F.; Akkar, S.; Gharsallah, A.
2016-07-01
Based on an extended reactance domain (RD) covariance matrix, this article proposes new alternatives for directions of arrival (DoAs) estimation of narrowband sources through an electronically steerable parasitic array radiator (ESPAR) antennas. Because of the centro symmetry of the classic ESPAR antennas, an unitary transformation is applied to the collected data that allow an important reduction in both computational cost and processing time and, also, an enhancement of the resolution capabilities of the proposed algorithms. Moreover, this article proposes a new approach for eigenvalues estimation through only some linear operations. The developed DoAs estimation algorithms based on this new approach has illustrated a good behaviour with less calculation cost and processing time as compared to other schemes based on the classic eigenvalues approach. The conducted simulations demonstrate that high-precision and high-resolution DoAs estimation can be reached especially in very closely sources situation and low sources power as compared to the RD-MUSIC algorithm and the RD-PM algorithm. The asymptotic behaviours of the proposed DoAs estimators are analysed in various scenarios and compared with the Cramer-Rao bound (CRB). The conducted simulations testify the high-resolution of the developed algorithms and prove the efficiently of the proposed approach.
V.Sinthu Janita Prakash
2012-10-01
Full Text Available Wireless links are characterized by high error rates and intermittent connectivity. TCP congestion control has been developed on the assumption that network congestion is the only cause for packet loss. Upon detecting a packet loss, TCP drops its transmit window resulting in an unnecessary reduction of end-to-end throughput which results in suboptimal performance.The sender has to be made aware by some feedback mechanism that some of the losses reported are not due to congestion. The Active Queue Management algorithms (AQM are used to reduce congestion, and in this paper, we have analysed four AQM algorithms, Random Early Deduction (RED, Wireless Explicit Congestion Notification (WECN, Queue Management Backward Congestion Control Algorithm (QMBCCA and its enhanced version Extended Queue Management Backward Congestion Control Algorithm (EQMBCCA. WECN, QMBCCA & EQMBCCA algorithms make use of feedback mechanisms. WECN gives feedback using the CE bit. QMBCCA and EQMBCCA make use of ISQ notifications and also the CE bit whenever the average queue size crosses minimum threshold value. EQMBCCA reduces the reverse ISQ traffic by introducing a configurable intermediate threshold value IntThres. The comparison is made in terms of Delay, HTTP packet loss percentage and fairness for FTP flows in a wireless environment. It is found that the performance of EQMBCCA is almost equal to that of QMBCCA and better than RED and WECN.
PERFORMANCE IMPROVEMENT OF AN AS-FRIENDLY PEER SELECTION ALGORITHM FOR P2P LIVE STREAMING
Yukinobu Fukushima
2016-01-01
Full Text Available Minimum Physical Hop (MPH has been proposed as a peer selection algorithm for decreasing inter-AS (Autonomous System traffic volume in P2P live streaming. In MPH, a newly joining peer selects a peer whose physical hop count (i.e., the number of ASes traversed on the content delivery path from it is the minimum as its providing peer. However, MPH shows high inter-AS traffic volume when the number of joining peers is large. In this paper, we propose IMPH that tries to further decrease the inter-AS traffic volume by distributing peers with one logical hop count (i.e., the number of peers or origin streaming servers (OSSes traversed on the content delivery path from an OSS to the peer to many ASes and encouraging the following peers to find their providing peers within the same AS. Numerical examples show that IMPH achieves at the maximum of 64% lower inter-AS traffic volume than MPH.
Use of NTRIP for Optimizing the Decoding Algorithm for Real-Time Data Streams
Zhanke He
2014-10-01
Full Text Available As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS Augmentation systems, such as Continuous Operational Reference System (CORS, Wide Area Augmentation System (WAAS and Satellite Based Augmentation Systems (SBAS. With the deployment of BeiDou Navigation Satellite system(BDS to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.
Use of NTRIP for Optimizing the Decoding Algorithm for Real-Time Data Streams
He, Zhanke; Tang, Wenda; Yang, Xuhai; Wang, Liming; Liu, Jihua
2014-01-01
As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (CORS), Wide Area Augmentation System (WAAS) and Satellite Based Augmentation Systems (SBAS). With the deployment of BeiDou Navigation Satellite system (BDS) to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG) NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX) format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China. PMID:25310474
Hybrid ants-like search algorithms for P2P media streaming distribution in ad hoc networks
无
2007-01-01
Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions, potential high loss rate and the decentralized architecture. To support long and high-quality streams, one viable approach is that a media stream is partitioned into segments, and then the segments are replicated in a network and served in a peer-to-peer (P2P)fashion. However, the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm (HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks, such as low transmitting latency, less jitter times, and low unnecessary traffic. We quantify the performance of our scheme in terms of response time, jitter times, and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.
Chen, Ying-ping; Chen, Chao-Hong
2010-01-01
An adaptive discretization method, called split-on-demand (SoD), enables estimation of distribution algorithms (EDAs) for discrete variables to solve continuous optimization problems. SoD randomly splits a continuous interval if the number of search points within the interval exceeds a threshold, which is decreased at every iteration. After the split operation, the nonempty intervals are assigned integer codes, and the search points are discretized accordingly. As an example of using SoD with EDAs, the integration of SoD and the extended compact genetic algorithm (ECGA) is presented and numerically examined. In this integration, we adopt a local search mechanism as an optional component of our back end optimization engine. As a result, the proposed framework can be considered as a memetic algorithm, and SoD can potentially be applied to other memetic algorithms. The numerical experiments consist of two parts: (1) a set of benchmark functions on which ECGA with SoD and ECGA with two well-known discretization methods: the fixed-height histogram (FHH) and the fixed-width histogram (FWH) are compared; (2) a real-world application, the economic dispatch problem, on which ECGA with SoD is compared to other methods. The experimental results indicate that SoD is a better discretization method to work with ECGA. Moreover, ECGA with SoD works quite well on the economic dispatch problem and delivers solutions better than the best known results obtained by other methods in existence.
SVD-TLS extending Prony algorithm for extracting UWB radar target feature
Liu Donghong; Hu Wenlong; Chen Zhijie
2008-01-01
A now method, SVD-TLS extending Prony algorithm, is introduced for extracting UWB radar target features. The method is a modified classical Prony method based on singular value decomposition and total least squares that can improve robust for spectrum estimation. Simulation results show that poles and residuum of target echo can be extracted effectively using this method, and at the same time, random noises can be restrained to some degree. It is applicable for target feature extraction such as UWB radar or other high resolution range radars.
A. Alfaro
2006-01-01
Full Text Available Determining the method by which a protein thermodynamically folds and unfolds in three-dimension is one of the most complex and least understood problems in modern biochemistry. Misfolded proteins have been recently linked to diseases including Amyotrophic Lateral Sclerosis and Alzheimer's disease. Because of the large number of parameters involved in defining the tertiary structure of proteins, based on free energy global minimisation, we have developed a new Divide and Conquer (DAC Extended Genetic Algorithm. The approach was applied to explore and verify the energy landscape of protein chymotrypsin inhibitor-2.
Pyragas, Viktoras; Pyragas, Kestutis
2015-08-01
In a recent paper [Phys. Rev. E 91, 012920 (2015)] Olyaei and Wu have proposed a new chaos control method in which a target periodic orbit is approximated by a system of harmonic oscillators. We consider an application of such a controller to single-input single-output systems in the limit of an infinite number of oscillators. By evaluating the transfer function in this limit, we show that this controller transforms into the known extended time-delayed feedback controller. This finding gives rise to an approximate finite-dimensional theory of the extended time-delayed feedback control algorithm, which provides a simple method for estimating the leading Floquet exponents of controlled orbits. Numerical demonstrations are presented for the chaotic Rössler, Duffing, and Lorenz systems as well as the normal form of the Hopf bifurcation.
Pyragas, Viktoras; Pyragas, Kestutis
2015-08-01
In a recent paper [Phys. Rev. E 91, 012920 (2015), 10.1103/PhysRevE.91.012920] Olyaei and Wu have proposed a new chaos control method in which a target periodic orbit is approximated by a system of harmonic oscillators. We consider an application of such a controller to single-input single-output systems in the limit of an infinite number of oscillators. By evaluating the transfer function in this limit, we show that this controller transforms into the known extended time-delayed feedback controller. This finding gives rise to an approximate finite-dimensional theory of the extended time-delayed feedback control algorithm, which provides a simple method for estimating the leading Floquet exponents of controlled orbits. Numerical demonstrations are presented for the chaotic Rössler, Duffing, and Lorenz systems as well as the normal form of the Hopf bifurcation.
Cui, Laizhong; Jiang, Yong; Wu, Jianping; Xia, Shutao
Most large-scale Peer-to-Peer (P2P) live streaming systems are constructed as a mesh structure, which can provide robustness in the dynamic P2P environment. The pull scheduling algorithm is widely used in this mesh structure, which degrades the performance of the entire system. Recently, network coding was introduced in mesh P2P streaming systems to improve the performance, which makes the push strategy feasible. One of the most famous scheduling algorithms based on network coding is R2, with a random push strategy. Although R2 has achieved some success, the push scheduling strategy still lacks a theoretical model and optimal solution. In this paper, we propose a novel optimal pull-push scheduling algorithm based on network coding, which consists of two stages: the initial pull stage and the push stage. The main contributions of this paper are: 1) we put forward a theoretical analysis model that considers the scarcity and timeliness of segments; 2) we formulate the push scheduling problem to be a global optimization problem and decompose it into local optimization problems on individual peers; 3) we introduce some rules to transform the local optimization problem into a classical min-cost optimization problem for solving it; 4) We combine the pull strategy with the push strategy and systematically realize our scheduling algorithm. Simulation results demonstrate that decode delay, decode ratio and redundant fraction of the P2P streaming system with our algorithm can be significantly improved, without losing throughput and increasing overhead.
Kampf, Sabine
2010-01-01
This paper presents a method to determine a set of basis polynomials from the extended Euclidean algorithm that allows Generalized Minimum Distance decoding of Reed-Solomon codes with a complexity of O(nd).
Simon Fong
2015-01-01
Full Text Available Human motion sensing technology gains tremendous popularity nowadays with practical applications such as video surveillance for security, hand signing, and smart-home and gaming. These applications capture human motions in real-time from video sensors, the data patterns are nonstationary and ever changing. While the hardware technology of such motion sensing devices as well as their data collection process become relatively mature, the computational challenge lies in the real-time analysis of these live feeds. In this paper we argue that traditional data mining methods run short of accurately analyzing the human activity patterns from the sensor data stream. The shortcoming is due to the algorithmic design which is not adaptive to the dynamic changes in the dynamic gesture motions. The successor of these algorithms which is known as data stream mining is evaluated versus traditional data mining, through a case of gesture recognition over motion data by using Microsoft Kinect sensors. Three different subjects were asked to read three comic strips and to tell the stories in front of the sensor. The data stream contains coordinates of articulation points and various positions of the parts of the human body corresponding to the actions that the user performs. In particular, a novel technique of feature selection using swarm search and accelerated PSO is proposed for enabling fast preprocessing for inducing an improved classification model in real-time. Superior result is shown in the experiment that runs on this empirical data stream. The contribution of this paper is on a comparative study between using traditional and data stream mining algorithms and incorporation of the novel improved feature selection technique with a scenario where different gesture patterns are to be recognized from streaming sensor data.
LI Xing-mei; ZHANG Li-hui; QI Jian-xun; ZHANG Su-fang
2008-01-01
In order to study the problem that particle swarm optimization (PSO) algorithm can easily trap into local mechanism when analyzing the high dimensional complex optimization problems, the optimization calculation using the information in the iterative process of more particles was analyzed and the optimal system of particle swarm algorithm was improved. The extended particle swarm optimization algorithm (EPSO) was proposed. The coarse-grained and free-grained criteria that can control the selection were given to ensure the convergence of the algorithm. The two criteria considered the parameter selection mechanism under the situation of random probability. By adopting MATLAB7.1, the extended particle swarm optimization algorithm was demonstrated in the resource leveling of power project scheduling. EPSO was compared with genetic algorithm (GA) and common PSO, the result indicates that the variance of the objective function of resource leveling is decreased by 7.9%, 18.2%, respectively, certifying thee effectiveness and stronger global convergence ability of the EPSO.
Janssen, O.T.A.; Van Haver, S.; Janssen, A.J.E.M.; Braat, J.J.M.; Urbach, H.P.; Pereira, S.F.
2008-01-01
Results are presented of mask imaging using the Extended Nijboer-Zernike (ENZ) theory of diffraction. We show that the efficiency of a mask imaging algorithm, derived from this theory, can be increased. By adjusting the basic Finite Difference Time Domain (FDTD) algorithm, we can calculate the near
A fast algorithm for finding point sources in the Fermi data stream: FermiFAST
Asvathaman, Asha; Omand, Conor; Barton, Alistair; Heyl, Jeremy S.
2017-04-01
We present a new and efficient algorithm for finding point sources in the photon event data stream from the Fermi Gamma-Ray Space Telescope, FermiFAST. The key advantage of FermiFAST is that it constructs a catalogue of potential sources very fast by arranging the photon data in a hierarchical data structure. Using this structure, FermiFAST rapidly finds the photons that could have originated from a potential gamma-ray source. It calculates a likelihood ratio for the contribution of the potential source using the angular distribution of the photons within the region of interest. It can find within a few minutes the most significant half of the Fermi Third Point Source catalogue (3FGL) with nearly 80 per cent purity from the 4 yr of data used to construct the catalogue. If a higher purity sample is desirable, one can achieve a sample that includes the most significant third of the Fermi 3FGL with only 5 per cent of the sources unassociated with Fermi sources. Outside the Galactic plane, all but eight of the 580 FermiFAST detections are associated with 3FGL sources. And of these eight, six yield significant detections of greater than 5σ when a further binned likelihood analysis is performed. This software allows for rapid exploration of the Fermi data, simulation of the source detection to calculate the selection function of various sources and the errors in the obtained parameters of the sources detected.
Syed Bilal Hussain Shah
2017-01-01
Full Text Available In Wireless Sensors Networks (WSNs, researcher’s main focus is on energy preservation and prolonging network lifetime. More energy resources are required in case of remote applications of WSNs, where some of the nodes die early that shorten the lifetime and decrease the stability of the network. It is mainly caused due to the non-optimal Cluster Heads (CHs selection based on single criterion and uneven distribution of energy. We propose a new clustering protocol for both homogeneous and heterogeneous environments, named as Optimized Path planning algorithm with Energy efficiency and Extending Network lifetime in WSN (OPEN. In the proposed protocol, timer value concept is used for CH selection based on multiple criteria. Simulation results prove that OPEN performs better than the existing protocols in terms of the network lifetime, throughput and stability. The results explicitly explain the cluster head selection of OPEN protocol and efficient solution of uneven energy distribution problem.
Eberhardt, D. S.; Baganoff, D.; Stevens, K.
1984-01-01
Implicit approximate-factored algorithms have certain properties that are suitable for parallel processing. A particular computational fluid dynamics (CFD) code, using this algorithm, is mapped onto a multiple-instruction/multiple-data-stream (MIMD) computer architecture. An explanation of this mapping procedure is presented, as well as some of the difficulties encountered when trying to run the code concurrently. Timing results are given for runs on the Ames Research Center's MIMD test facility which consists of two VAX 11/780's with a common MA780 multi-ported memory. Speedups exceeding 1.9 for characteristic CFD runs were indicated by the timing results.
Smock, Brandon; Wilson, Joseph
2012-06-01
In landmine detection using vehicle-mounted ground-penetrating radar (GPR) systems, ground tracking has proven to be an eective pre-processing step. Identifying the ground can aid in the correction of distortions in downtrack radar data, which can result in the reduction of false alarms due to ground anomalies. However, the air-ground interface is not the only layer boundary detectable by GPR systems. Multiple layers can exist within the ground, and these layers are of particular importance because they give rise to anomalous signatures below the ground surface, where target signatures will typically reside. In this paper, an ecient method is proposed for performing multiple ground layer-identication in GPR data. The method is an extension of the dynamic programming-based Viterbi algorithm, nding not only the globally optimal path, which can be associated with the ground surface, but also locally optimal paths that can be associated with distinct layer boundaries within the ground. In contrast with the Viterbi algorithm, this extended method is uniquely suited to detecting not only multiple layers that span the entire antenna array, but also layers that span only a subset of the channels of the array. Furthermore, it is able to accomplish this while retaining the ecient nature of the original Viterbi scheme.
Herman, Matthew R; Nejadhashemi, A Pouyan; Daneshvar, Fariborz; Abouali, Mohammad; Ross, Dennis M; Woznicki, Sean A; Zhang, Zhen
2016-10-01
The emission of greenhouse gases continues to amplify the impacts of global climate change. This has led to the increased focus on using renewable energy sources, such as biofuels, due to their lower impact on the environment. However, the production of biofuels can still have negative impacts on water resources. This study introduces a new strategy to optimize bioenergy landscapes while improving stream health for the region. To accomplish this, several hydrological models including the Soil and Water Assessment Tool, Hydrologic Integrity Tool, and Adaptive Neruro Fuzzy Inference System, were linked to develop stream health predictor models. These models are capable of estimating stream health scores based on the Index of Biological Integrity. The coupling of the aforementioned models was used to guide a genetic algorithm to design watershed-scale bioenergy landscapes. Thirteen bioenergy managements were considered based on the high probability of adaptation by farmers in the study area. Results from two thousand runs identified an optimum bioenergy crops placement that maximized the stream health for the Flint River Watershed in Michigan. The final overall stream health score was 50.93, which was improved from the current stream health score of 48.19. This was shown to be a significant improvement at the 1% significant level. For this final bioenergy landscape the most often used management was miscanthus (27.07%), followed by corn-soybean-rye (19.00%), corn stover-soybean (18.09%), and corn-soybean (16.43%). The technique introduced in this study can be successfully modified for use in different regions and can be used by stakeholders and decision makers to develop bioenergy landscapes that maximize stream health in the area of interest.
Chèze, Guillaume
2010-01-01
The extended L\\"uroth's Theorem says that if the transcendence degree of $\\KK(\\mathsf{f}_1,\\dots,\\mathsf{f}_m)/\\KK$ is 1 then there exists $f \\in \\KK(\\underline{X})$ such that $\\KK(\\mathsf{f}_1,\\dots,\\mathsf{f}_m)$ is equal to $\\KK(f)$. In this paper we show how to compute $f$ with a probabilistic algorithm. We also describe a probabilistic and a deterministic algorithm for the decomposition of multivariate rational functions. The probabilistic algorithms proposed in this paper are softly optimal when $n$ is fixed and $d$ tends to infinity. We also give an indecomposability test based on gcd computations and Newton's polytope. In the last section, we show that we get a polynomial time algorithm, with a minor modification in the exponential time decomposition algorithm proposed by Gutierez-Rubio-Sevilla in 2001.
Yu-Bao Liu; Jia-Rong Cai; Jian Yin; Ada Wai-Chee Fu
2008-01-01
Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organization and topic detection and tracing etc. However, most methods are similarity-based approaches and only use the TF*IDF scheme to represent the semantics of text data and often lead to poor clustering quality. Recently, researchers argue that semantic smoothing model is more efficient than the existing TF.IDF scheme for improving text clustering quality. However, the existing semantic smoothing model is not suitable for dynamic text data context. In this paper, we extend the semantic smoothing model into text data streams context firstly. Based on the extended model, we then present two online clustering algorithms OCTS and OCTSM for the clustering of massive text data streams. In both algorithms, we also present a new cluster statistics structure named cluster profile which can capture the semantics of text data streams dynamically and at the same time speed up the clustering process. Some efficient implementations for our algorithms are also given. Finally, we present a series of experimental results illustrating the effectiveness of our technique.
A Huge Dimension Table Join Algorithm for Construction of StreamCube%一种构建StreamCube的超大维表连接算法
甘亮; 贾焰; 李爱平; 金鑫
2011-01-01
表连接是关系数据库中最重要的操作之一,在数据流管理系统中同样重要.构建StreamCube的聚集查询时,数据流与超大维表(如IPaddress维表)作表连接将耗费大量有限的计算资源和内存.超大维表需划分为多个块,分块读入内存,造成磁盘I/O频繁.根据维表及其连接键层的特性,降低维表与数据流连接的连接键冗余,将维表无损压缩为可装入内存的连接键范围维表(RJ-DT),引出数据流上非等值连接问题;并提出一种超大维表多表连接算法--多动态索引嵌套循环连接算法(multi dynamic index nested-loop join),该算法实现数据流与压缩维表高效的非等值连接,并拓展为多表连接.理论分析及实验结果表明,该算法可使超大维表连接性能明显改善,最高可达到一个数量级的加速并具有很强的实用性.%Join is one of the most important operations in relational database, and is also important in data stream management system. In group-bys which construct StreamCube, join will be done before them, and join between data stream and huge dimension tables (such as IPaddress table) would consume limited power of CPU and capacity of memory. Generally, a huge dimension table must be partitioned into small tables and each partition table is loaded into memory in turn that causes frequent disk I/O. To avoid this shortage, it compress huge dimension tables losslessly by taking characters of dimension tables and their join-key layer into account and finding join-key redundancies in those tables. So, one dimension table with n concept columns is compressed into n ranged join-key dimension tables (RJ-DT) by reducing join-key redundancies and using decomposed of storage model of column-store. Each RJ-DT is composed of start and end columns and several concept columns.However, a new issue that non-equijoin called range join between data stream and RJ-DT is brought out. Then, it proposes a multi-join algorithm of huge
An extended validation test for data input into parameterized retrieval algorithms
Schaale, Michael; Schroeder, Thomas
2013-05-01
The retrieval of environmental data from multi-spectral remotely sensed data is very often based on the (partial) inversion of extensive radiative transfer simulations (RTS). The inversion can be utilized in different ways, e.g. through the usage of polynomials or artificial neural networks. The inversion algorithms (IA) usually contain numerous parameters, which have to be adapted by regression schemes in a training phase with the help of the RTS data. The subsequent processing of real remotely sensed data by an adapted IA requires a validity test (VT) of the input data (usually a vector consisting of TOA radiances, environmental and geometric data) before inputting them into the IA. This test ensures that these or similar data were included in the training phase of the IA and thus helps to avoid unpredictable extrapolation effects. In standard procedures these "out-of-scope" data are identified by a simple convexity test (CT). CT means that each element of the input vector is tested to lie between the minimum and maximum values of the corresponding element used in the training data set. This assumption is rather crude as it assumes a homogeneously filled data space. But in general the data are not distributed homogeneously and thus a CT is an incomplete and unsatisfactory check. This paper proposes a solution to the problem sketched above by the development and implementation of an enhanced VT (eVT), which is based on a density map of the data space. The density map itself is approximated by an extended neuronal vector quantization method. The newly developed eVT algorithm is tested with known distributions of artificial data. Although the eVT is not limited to a specific retrieval/inversion scheme it is finally applied to an existing retrieval scheme for coastal water constituents from satellite data (MERIS) acquired over coastal regions in Europe (here: FUB/WeW water processor for VISAT-BEAM). A comparison against the data filtered by a simple CT further
Liu, Rengli; Wang, Yanfei
2016-04-01
An extended nonlinear chirp scaling (NLCS) algorithm is proposed to process data of highly squinted, high-resolution, missile-borne synthetic aperture radar (SAR) diving with a constant acceleration. Due to the complex diving movement, the traditional signal model and focusing algorithm are no longer suited for missile-borne SAR signal processing. Therefore, an accurate range equation is presented, named as the equivalent hyperbolic range model (EHRM), which is more accurate and concise compared with the conventional fourth-order polynomial range equation. Based on the EHRM, a two-dimensional point target reference spectrum is derived, and an extended NLCS algorithm for missile-borne SAR image formation is developed. In the algorithm, a linear range walk correction is used to significantly remove the range-azimuth cross coupling, and an azimuth NLCS processing is adopted to solve the azimuth space variant focusing problem. Moreover, the operations of the proposed algorithm are carried out without any interpolation, thus having small computational loads. Finally, the simulation results and real-data processing results validate the proposed focusing algorithm.
National Aeronautics and Space Administration — This paper considers the problem of change detection using local distributed eigen monitoring algorithms for next generation of astronomy petascale data pipelines...
A QoE Aware Fairness Bi-level Resource Allocation Algorithm for Multiple Video Streaming in WLAN
Hu Zhou
2015-11-01
Full Text Available With the increasing of smart devices such as mobile phones and tablets, the scenario of multiple video users watching video streaming simultaneously in one wireless local area network (WLAN becomes more and more popular. However, the quality of experience (QoE and the fairness among multiple users are seriously impacted by the limited bandwidth and shared resources of WLAN. In this paper, we propose a novel bi-level resource allocation algorithm. To maximize the total throughput of the network, the WLAN is firstly tuned to the optimal operation point. Then the wireless resource is carefully allocated at the first level, i.e., between AP and uplink background traffic users, and the second level, i.e., among downlink video users. The simulation results show that the proposed algorithm can guarantee the QoE and the fairness for all the video users, and there is little impact on the average throughput of the background traffic users.
Danovich, Mark; Hahn, Oliver; Ceverino, Daniel; Primack, Joel
2014-01-01
We study the buildup of angular momentum (AM) in high-z galaxies using zoom-in hydro-cosmological simulations. The disc AM originates in a few co-planar streams of cold gas and merging galaxies tracing filaments of the cosmic web and undergo 4 phases of evolution. In phase I, outside the halo virial radius (Rv), the elongated streams gain AM by tidal torques with a specific AM (sAM) ~1.7 times that of the dark matter (DM) due to the gas' higher quadrupole moment. This AM is expressed as stream impact parameters, from ~0.3Rv to occasional counter rotation. In phase II, in the outer halo, while the incoming DM mixes with the existing halo of lower sAM to a spin $\\lambda_{\\rm dm}\\sim0.04$, the cold streams transport the AM to the inner halo such that their spin in the halo is $\\sim3\\lambda_{\\rm dm}$. In phase III, near pericenter, the streams dissipate and form a non-uniform, rotating ring extending to ~0.3Rv and tilted relative to the inner disc. Torques exerted partly by the disc make the gas ring lose AM, spi...
Unison as a Self-Stabilizing Wave Stream Algorithm in Asynchronous Anonymous Networks
Boulinier, Christian
2007-01-01
How to pass from local to global scales in anonymous networks? How to organize a selfstabilizing propagation of information with feedback. From the Angluin impossibility results, we cannot elect a leader in a general anonymous network. Thus, it is impossible to build a rooted spanning tree. Many problems can only be solved by probabilistic methods. In this paper we show how to use Unison to design a self-stabilizing barrier synchronization in an anonymous network. We show that the commuication structure of this barrier synchronization designs a self-stabilizing wave-stream, or pipelining wave, in anonymous networks. We introduce two variants of Wave: the strong waves and the wavelets. A strong wave can be used to solve the idempotent r-operator parametrized computation problem. A wavelet deals with k-distance computation. We show how to use Unison to design a self-stabilizing wave stream, a self-stabilizing strong wave stream and a self-stabilizing wavelet stream.
Cao, Minh Duc; Ganesamoorthy, Devika; Elliott, Alysha G; Zhang, Huihui; Cooper, Matthew A; Coin, Lachlan J M
2016-07-26
The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This has great potential to shorten the sample-to-results time and is likely to have benefits such as rapid diagnosis of bacterial infection and identification of drug resistance. However, there are few tools available for streaming analysis of real-time sequencing data. Here, we present a framework for streaming analysis of MinION real-time sequence data, together with probabilistic streaming algorithms for species typing, strain typing and antibiotic resistance profile identification. Using four culture isolate samples, as well as a mixed-species sample, we demonstrate that bacterial species and strain information can be obtained within 30 min of sequencing and using about 500 reads, initial drug-resistance profiles within two hours, and complete resistance profiles within 10 h. While strain identification with multi-locus sequence typing required more than 15x coverage to generate confident assignments, our novel gene-presence typing could detect the presence of a known strain with 0.5x coverage. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer.
Li, Baojun; Deng, Junjun; Lonn, Albert H; Hsieh, Jiang
2012-10-01
To further improve the image quality, in particularly, to suppress the boundary artifacts, in the extended scan field-of-view (SFOV) reconstruction. To combat projection truncation artifacts and to restore truncated objects outside the SFOV, an algorithm has previously been proposed based on fitting a partial water cylinder at the site of the truncation. Previous studies have shown this algorithm can simultaneously eliminate the truncation artifacts inside the SFOV and preserve the total amount of attenuation, owing to its emphasis on consistency conditions of the total attenuation in the parallel sampling geometry. Unfortunately, the water cylinder fitting parameters of this 2D algorithm are inclined to high noise fluctuation in the projection samples from image to image, causing anatomy boundaries artifacts, especially during helical scans with higher pitch (≥1.0). To suppress the boundary artifacts and further improve the image quality, the authors propose to use a roughness penalty function, based on the Huber regularization function, to reinforce the z-dimensional boundary consistency. Extensive phantom and clinical tests have been conducted to test the accuracy and robustness of the enhanced algorithm. Significant reduction in the boundary artifacts is observed in both phantom and clinical cases with the enhanced algorithm. The proposed algorithm also reduces the percent difference error between the horizontal and vertical diameters to well below 1%. It is also noticeable that the algorithm has improved CT number uniformity outside the SFOV compared to the original algorithm. The proposed algorithm is capable of suppressing boundary artifacts and improving the CT number uniformity outside the SFOV.
Introduction to stream: An Extensible Framework for Data Stream Clustering Research with R
Michael Hahsler
2017-02-01
Full Text Available In recent years, data streams have become an increasingly important area of research for the computer science, database and statistics communities. Data streams are ordered and potentially unbounded sequences of data points created by a typically non-stationary data generating process. Common data mining tasks associated with data streams include clustering, classification and frequent pattern mining. New algorithms for these types of data are proposed regularly and it is important to evaluate them thoroughly under standardized conditions. In this paper we introduce stream, a research tool that includes modeling and simulating data streams as well as an extensible framework for implementing, interfacing and experimenting with algorithms for various data stream mining tasks. The main advantage of stream is that it seamlessly integrates with the large existing infrastructure provided by R. In addition to data handling, plotting and easy scripting capabilities, R also provides many existing algorithms and enables users to interface code written in many programming languages popular among data mining researchers (e.g., C/C++, Java and Python. In this paper we describe the architecture of stream and focus on its use for data stream clustering research. stream was implemented with extensibility in mind and will be extended in the future to cover additional data stream mining tasks like classification and frequent pattern mining.
SHARPEN-Systematic Hierarchical Algorithms for Rotamers and Proteins on an Extended Network
Loksha, Ilya V.
2009-04-30
Algorithms for discrete optimization of proteins play a central role in recent advances in protein structure prediction and design. We wish to improve the resources available for computational biologists to rapidly prototype such algorithms and to easily scale these algorithms to many processors. To that end, we describe the implementation and use of two new open source resources, citing potential benefits over existing software. We discuss CHOMP, a new object-oriented library for macromolecular optimization, and SHARPEN, a framework for scaling CHOMP scripts to many computers. These tools allow users to develop new algorithms for a variety of applications including protein repacking, protein-protein docking, loop rebuilding, or homology model remediation. Particular care was taken to allow modular energy function design; protein conformations may currently be scored using either the OPLSaa molecular mechanical energy function or an all-atom semiempirical energy function employed by Rosetta. © 2009 Wiley Periodicals, Inc.
Towards Improving the NIST Fingerprint Image Quality (NFIQ) Algorithm (Extended Version)
Merkle, Johannes; Bausinger, Oliver; Breitenstein, Marco; Elwart, Kristina; Nuppeney, Markus
2010-01-01
The NIST Fingerprint Image Quality (NFIQ) algorithm has become a standard method to assess fingerprint image quality. However, in many applications a more accurate and reliable assessment is desirable. In this publication, we report on our efforts to optimize the NFIQ algorithm by a re-training of the underlying neural network based on a large fingerprint image database. Although we only achieved a marginal improvement, our work has revealed several areas for potential optimization.
Salmon, BP
2012-07-01
Full Text Available In this paper the Bias Variance Search Algorithm is proposed as an algorithm to optimize a candidate set of initial parameters for an Extended Kalman filter (EKF). The search algorithm operates on a Bias Variance Equilibrium Point criterion...
A Bi-Criteria Active Learning Algorithm for Dynamic Data Streams.
Mohamad, Saad; Bouchachia, Abdelhamid; Sayed-Mouchaweh, Moamar
2016-10-21
Active learning (AL) is a promising way to efficiently build up training sets with minimal supervision. A learner deliberately queries specific instances to tune the classifier's model using as few labels as possible. The challenge for streaming is that the data distribution may evolve over time, and therefore the model must adapt. Another challenge is the sampling bias where the sampled training set does not reflect the underlying data distribution. In the presence of concept drift, sampling bias is more likely to occur as the training set needs to represent the whole evolving data. To tackle these challenges, we propose a novel bi-criteria AL (BAL) approach that relies on two selection criteria, namely, label uncertainty criterion and density-based criterion. While the first criterion selects instances that are the most uncertain in terms of class membership, the latter dynamically curbs the sampling bias by weighting the samples to reflect on the true underlying distribution. To design and implement these two criteria for learning from streams, BAL adopts a Bayesian online learning approach and combines online classification and online clustering through the use of online logistic regression and online growing Gaussian mixture models, respectively. Empirical results obtained on standard synthetic and real-world benchmarks show the high performance of the proposed BAL method compared with the state-of-the-art AL methods.
Tataw, Oben Moses
2013-01-01
Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…
Tataw, Oben Moses
2013-01-01
Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…
Lau Nguyen Dinh
2016-01-01
Full Text Available The problem of finding maximum flow in network graph is extremely interesting and practically applicable in many fields in our daily life, especially in transportation. Therefore, a lot of researchers have been studying this problem in various methods. Especially in 2013, we has developed a new algorithm namely, postflow-pull algorithm to find the maximum flow on traditional networks. In this paper, we revised postflow-push methods to solve this problem of finding maximum flow on extended mixed network. In addition, to take more advantage of multi-core architecture of the parallel computing system, we build this parallel algorithm. This is a completely new method not being announced in the world. The results of this paper are basically systematized and proven. The idea of this algorithm is using multi processors to work in parallel by postflow_push algorithm. Among these processors, there is one main processor managing data, sending data to the sub processors, receiving data from the sub-processors. The sub-processors simultaneously execute their work and send their data to the main processor until the job is finished, the main processor will show the results of the problem.
L-Tree Match: A New Data Extraction Model and Algorithm for Huge Text Stream with Noises
Xu-Bin Deng; Yang-Yong Zhu
2005-01-01
In this paper, a new method, named as L-tree match, is presented for extracting data from complex data sources. Firstly, based on data extraction logic presented in this work, a new data extraction model is constructed in which model components are structurally correlated via a generalized template. Secondly, a database-populating mechanism is built, along with some object-manipulating operations needed for flexible database design, to support data extraction from huge text stream. Thirdly, top-down and bottom-up strategies are combined to design a new extraction algorithm that can extract data from data sources with optional, unordered, nested, and/or noisy components. Lastly, this method is applied to extract accurate data from biological documents amounting to 100GB for the first online integrated biological data warehouse of China.
DOA estimation of coherent wideband signals based on extended TOPS algorithm
Guo, Rui; Li, Weixing; Zhang, Yue; Chen, Zengping
2015-12-01
In this paper, we present a new direction of arrival (DOA) estimation algorithm for coherent wideband signals. This algorithm is based on the test of orthogonality of projected subspaces (TOPS) method which will fail to work in real environments where signals are highly correlated or coherent due to multipath propagation. In order to overcome the disadvantage, we combine spatial smoothing techniques with TOPS method so that the rank of covariance matrix is equal to the number of signal sources even signals received are coherent. Unlike other coherent wideband methods, such as the coherent signal subspace method (CSSM) and WAVES, the new method does not require any initial DOA estimation, thus avoiding errors brought by incorrect initial values. Simulations on computer and experiments in the anechoic chamber based on an 8-elements digital array radar test-bed operating at L & S band are carried out. Simulation and experimental results validate the effectiveness of proposed algorithm.
Borui Li
2014-04-01
Full Text Available Traditional object tracking technology usually regards the target as a point source object. However, this approximation is no longer appropriate for tracking extended objects such as large targets and closely spaced group objects. Bayesian extended object tracking (EOT using a random symmetrical positive definite (SPD matrix is a very effective method to jointly estimate the kinematic state and physical extension of the target. The key issue in the application of this random matrix-based EOT approach is to model the physical extension and measurement noise accurately. Model parameter adaptive approaches for both extension dynamic and measurement noise are proposed in this study based on the properties of the SPD matrix to improve the performance of extension estimation. An interacting multi-model algorithm based on model parameter adaptive filter using random matrix is also presented. Simulation results demonstrate the effectiveness of the proposed adaptive approaches and multi-model algorithm. The estimation performance of physical extension is better than the other algorithms, especially when the target maneuvers. The kinematic state estimation error is lower than the others as well.
Abdel-Rehim, A M; Stathopoulos, Andreas; Orginos, Kostas
2014-08-01
The technique that was used to build the EigCG algorithm for sparse symmetric linear systems is extended to the nonsymmetric case using the BiCG algorithm. We show that, similarly to the symmetric case, we can build an algorithm that is capable of computing a few smallest magnitude eigenvalues and their corresponding left and right eigenvectors of a nonsymmetric matrix using only a small window of the BiCG residuals while simultaneously solving a linear system with that matrix. For a system with multiple right-hand sides, we give an algorithm that computes incrementally more eigenvalues while solving the first few systems and then uses the computed eigenvectors to deflate BiCGStab for the remaining systems. Our experiments on various test problems, including Lattice QCD, show the remarkable ability of EigBiCG to compute spectral approximations with accuracy comparable to that of the unrestarted, nonsymmetric Lanczos. Furthermore, our incremental EigBiCG followed by appropriately restarted and deflated BiCGStab provides a competitive method for systems with multiple right-hand sides.
P. Li
2017-06-01
Full Text Available Use of the Gaussian inverse Wishart probability hypothesis density (GIW-PHD filter has demonstrated promise as an approach to track an unknown number of extended targets. However, when targets of various sizes are spaced closely together and performing maneuvers, estimation errors will occur because measurement partitioning algorithms fail to provide the correct partitions. Specifically, the sub-partitioning algorithm fails to handle cases in which targets are of different sizes, while other partitioning approaches are sensitive to target maneuvers. This paper presents an improved partitioning algorithm for a GIW-PHD filter in order to solve the above problems. The sub-partitioning algorithm is improved by considering target extension information and by employing Mahalanobis distances to distinguish among measurement cells of different sizes. Thus, the improved approach is not sensitive to either differences in target sizes or target maneuvering. Simulation results show that the use of the proposed partitioning approach can improve the tracking performance of a GIW-PHD filter when target are spaced closely together.
DAI Chao-Qing; MENG Jian-Ping; ZHANG Jie-Fang
2005-01-01
The Jacobian elliptic function expansion method for nonlinear differential-different equations and its algorithm are presented by using some relations among ten Jacobian elliptic functions and successfully construct more new exact doubly-periodic solutions of the integrable discrete nonlinear Schrodinger equation. When the modulous m → 1or 0, doubly-periodic solutions degenerate to solitonic solutions including bright soliton, dark soliton, new solitons as well as trigonometric function solutions.
Zhao, Jing; Li, Peng
2017-05-01
In this paper, we propose a car-following model to explore the influences of V2V communication on the driving behavior at un-signalized intersections with two crossing streams and to explore how the speed guidance strategy affects the operation efficiency. The numerical results illustrate that the benefits of the guidance strategy could be enhanced by lengthening the guiding space range and increasing the maximum speed limitation, and that the guidance strategy is more suitable under low to medium traffic density and small safety interval condition.
Ma, Zhanshan (Sam)
Competition, cooperation and communication are the three fundamental relationships upon which natural selection acts in the evolution of life. Evolutionary game theory (EGT) is a 'marriage' between game theory and Darwin's evolution theory; it gains additional modeling power and flexibility by adopting population dynamics theory. In EGT, natural selection acts as optimization agents and produces inherent strategies, which eliminates some essential assumptions in traditional game theory such as rationality and allows more realistic modeling of many problems. Prisoner's Dilemma (PD) and Sir Philip Sidney (SPS) games are two well-known examples of EGT, which are formulated to study cooperation and communication, respectively. Despite its huge success, EGT exposes a certain degree of weakness in dealing with time-, space- and covariate-dependent (i.e., dynamic) uncertainty, vulnerability and deception. In this paper, I propose to extend EGT in two ways to overcome the weakness. First, I introduce survival analysis modeling to describe the lifetime or fitness of game players. This extension allows more flexible and powerful modeling of the dynamic uncertainty and vulnerability (collectively equivalent to the dynamic frailty in survival analysis). Secondly, I introduce agreement algorithms, which can be the Agreement algorithms in distributed computing (e.g., Byzantine Generals Problem [6][8], Dynamic Hybrid Fault Models [12]) or any algorithms that set and enforce the rules for players to determine their consensus. The second extension is particularly useful for modeling dynamic deception (e.g., asymmetric faults in fault tolerance and deception in animal communication). From a computational perspective, the extended evolutionary game theory (EEGT) modeling, when implemented in simulation, is equivalent to an optimization methodology that is similar to evolutionary computing approaches such as Genetic algorithms with dynamic populations [15][17].
基于GPU的视频流拼接算法研究%Research of video stream splicing algorithm based on GPU
张燕; 赵新灿; 谭同德
2012-01-01
To solve the stability and real-time of video stream splicing, combined with the powerful graphics processor GPU's parallel computing capabilities, a design method of stream splicing algorithm based on GPU is presented Extracting video stream frame image, then image stitching which contains feature extraction and matching is implemented on the GPU using SIFT (scale invariant feature transform) algorithm, to realize the stable and real-time video stream splicing. The SIFT algorithm based on the GPU makes full use of the GPU's parallel processing capability, which accelerates the implementation of video streaming stitching algorithm and realizes the fast and stable video stream splicing with quite different but a public vision.%为解决视频流的稳定实时拼接,结合图形处理器GPU强大的并行计算能力,提出了一种基于GPU的视频流拼接算法.提取视频流的帧图像,利用尺度不变特征变换(scale invariant feature transform,SIFT)算法在GPU上实现帧图像的特征提取与匹配,实现图像拼接,进而实现视频流的稳定实时拼接.基于GPU的SIFT算法充分利用了GPU的并行处理能力,加快了视频流拼接算法执行的速度,真正意义上实现了几个差异较大但具有公共视野的视频流快速稳定的拼接.
Qingbo Li
2013-01-01
Full Text Available In order to improve the predictive accuracy of human blood glucose quantitative analysis model with fourier transform infrared (FT-IR spectroscopy, this paper uses a method named improved extended multiplicative scatter correction (Im-EMSC, which can effectively eliminate the scattering effects caused by human body strong scattering. The principal components of the differential spectra are used instead of the pure spectra of the analytes in this algorithm. Calibrate the unwanted physical characteristic through the shape of the curve of principal components, and extract the original glucose concentration information. Im-EMSC can efficiently remove most of the pathlength difference and baseline shift influences. Firstly, Im-EMSC is used as a preprocessing method, and then partial least squares (PLS regression method is adopted to establish a quantitative analysis model. In this paper, the result of Im-EMSC is compared with those popular scattering correction algorithms of multiplicative scatter correction (MSC and extended multiplicative scatter correction (EMSC preprocessing methods. Experimental results show that the prediction accuracy has been greatly improved with Im-EMSC method, which is helpful for human noninvasive glucose concentration detection technology.
Stein, Simon Christoph; Thiart, Jan
2016-11-25
Super-resolution localization microscopy and single particle tracking are important tools for fluorescence microscopy. Both rely on detecting, and tracking, a large number of fluorescent markers using increasingly sophisticated computer algorithms. However, this rise in complexity makes it difficult to fine-tune parameters and detect inconsistencies, improve existing routines, or develop new approaches founded on established principles. We present an open-source MATLAB framework for single molecule localization, tracking and super-resolution applications. The purpose of this software is to facilitate the development, distribution, and comparison of methods in the community by providing a unique, easily extendable plugin-based system and combining it with a novel visualization system. This graphical interface incorporates possibilities for quick inspection of localization and tracking results, giving direct feedback of the quality achieved with the chosen algorithms and parameter values, as well as possible sources for errors. This is of great importance in practical applications and even more so when developing new techniques. The plugin system greatly simplifies the development of new methods as well as adapting and tailoring routines towards any research problem's individual requirements. We demonstrate its high speed and accuracy with plugins implementing state-of-the-art algorithms and show two biological applications.
Irondi, Iheanyi; Wang, Qi; Grecos, Christos
2016-04-01
Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next
Iman Aghayan
2012-11-01
Full Text Available This paper compares two fuzzy clustering algorithms – fuzzy subtractive clustering and fuzzy C-means clustering – to a multi-layer perceptron neural network for their ability to predict the severity of crash injuries and to estimate the response time on the traffic crash data. Four clustering algorithms – hierarchical, K-means, subtractive clustering, and fuzzy C-means clustering – were used to obtain the optimum number of clusters based on the mean silhouette coefficient and R-value before applying the fuzzy clustering algorithms. The best-fit algorithms were selected according to two criteria: precision (root mean square, R-value, mean absolute errors, and sum of square error and response time (t. The highest R-value was obtained for the multi-layer perceptron (0.89, demonstrating that the multi-layer perceptron had a high precision in traffic crash prediction among the prediction models, and that it was stable even in the presence of outliers and overlapping data. Meanwhile, in comparison with other prediction models, fuzzy subtractive clustering provided the lowest value for response time (0.284 second, 9.28 times faster than the time of multi-layer perceptron, meaning that it could lead to developing an on-line system for processing data from detectors and/or a real-time traffic database. The model can be extended through improvements based on additional data through induction procedure.
Fu, Haohao; Shao, Xueguang; Chipot, Christophe; Cai, Wensheng
2016-08-09
Proper use of the adaptive biasing force (ABF) algorithm in free-energy calculations needs certain prerequisites to be met, namely, that the Jacobian for the metric transformation and its first derivative be available and the coarse variables be independent and fully decoupled from any holonomic constraint or geometric restraint, thereby limiting singularly the field of application of the approach. The extended ABF (eABF) algorithm circumvents these intrinsic limitations by applying the time-dependent bias onto a fictitious particle coupled to the coarse variable of interest by means of a stiff spring. However, with the current implementation of eABF in the popular molecular dynamics engine NAMD, a trajectory-based post-treatment is necessary to derive the underlying free-energy change. Usually, such a posthoc analysis leads to a decrease in the reliability of the free-energy estimates due to the inevitable loss of information, as well as to a drop in efficiency, which stems from substantial read-write accesses to file systems. We have developed a user-friendly, on-the-fly code for performing eABF simulations within NAMD. In the present contribution, this code is probed in eight illustrative examples. The performance of the algorithm is compared with traditional ABF, on the one hand, and the original eABF implementation combined with a posthoc analysis, on the other hand. Our results indicate that the on-the-fly eABF algorithm (i) supplies the correct free-energy landscape in those critical cases where the coarse variables at play are coupled to either each other or to geometric restraints or holonomic constraints, (ii) greatly improves the reliability of the free-energy change, compared to the outcome of a posthoc analysis, and (iii) represents a negligible additional computational effort compared to regular ABF. Moreover, in the proposed implementation, guidelines for choosing two parameters of the eABF algorithm, namely the stiffness of the spring and the mass
Fallahi, Kia; Raoufi, Reza; Khoshbin, Hossein
2008-07-01
In recent years chaotic secure communication and chaos synchronization have received ever increasing attention. In this paper a chaotic communication method using extended Kalman filter is presented. The chaotic synchronization is implemented by EKF design in the presence of channel additive noise and processing noise. Encoding chaotic communication is used to achieve a satisfactory, typical secure communication scheme. In the proposed system, a multi-shift cipher algorithm is also used to enhance the security and the key cipher is chosen as one of the chaos states. The key estimate is employed to recover the primary data. To illustrate the effectiveness of the proposed scheme, a numerical example based on Chen dynamical system is presented and the results are compared to two other chaotic systems.
Xin Li
2016-02-01
Full Text Available Wireless signal strength is susceptible to the phenomena of interference, jumping, and instability, which often appear in the positioning results based on Wi-Fi field strength fingerprint database technology for indoor positioning. Therefore, a Wi-Fi and PDR (pedestrian dead reckoning real-time fusion scheme is proposed in this paper to perform fusing calculation by adaptively determining the dynamic noise of a filtering system according to pedestrian movement (straight or turning, which can effectively restrain the jumping or accumulation phenomena of wireless positioning and the PDR error accumulation problem. Wi-Fi fingerprint matching typically requires a quite high computational burden: To reduce the computational complexity of this step, the affinity propagation clustering algorithm is adopted to cluster the fingerprint database and integrate the information of the position domain and signal domain of respective points. An experiment performed in a fourth-floor corridor at the School of Environment and Spatial Informatics, China University of Mining and Technology, shows that the traverse points of the clustered positioning system decrease by 65%–80%, which greatly improves the time efficiency. In terms of positioning accuracy, the average error is 4.09 m through the Wi-Fi positioning method. However, the positioning error can be reduced to 2.32 m after integration of the PDR algorithm with the adaptive noise extended Kalman filter (EKF.
Distributed Parallel Algorithm of Mining Frequent Pattern on Data Stream%分布式并行化数据流频繁模式挖掘算法
马可; 李玲娟; 孙杜靖
2016-01-01
为了提高数据流频繁模式挖掘的效率,文中基于经典的数据流频繁模式挖掘算法FP-Stream和分布式并行计算原理,设计了一种分布式并行化数据流频繁模式挖掘算法—DPFP-Stream ( Distributed Parallel Algorithm of Mining Frequent Pattern on Data Stream)。该算法将建立频繁模式树的任务分为local和global两部分,并设置了参数“当前时间”；将到达的流数据平均分配到多个不同的local节点,各local节点使用FP-Growth算法产生该单位时间内本节点的候选频繁项集,并按照单位时间将候选频繁项集及其支持度计数打包发送至global节点；global节点按“当前时间”合并各local节点的中间结果并更新模式树Pattern-Tree。在分布式数据流计算平台Storm上进行的算法实现和性能测试结果表明,DPFP-Stream算法的计算效率能够随着local节点或local bolt线程的增加而提高,适用于高效挖掘数据流中的频繁模式。%In order to improve the efficiency of mining frequent pattern on data stream,a Distributed Parallel Algorithm of Mining Fre-quent Pattern on Data Stream,named DPFP-Stream,is designed in this paper based on the ideas of classical FP-Stream and the distribu-ted parallel computing. It divides the task of building frequent pattern tree into two parts:local and global,and introduces a new parameter“current time”. The arrival data will be equally distributed into different local nodes. Then every local node uses FP-Growth algorithm to produce candidate frequent items,and packages them with relevant support count according to unit time,and sends them to the global node. The global node combines the results produced by local nodes according to the“current time” and updates the global Pattern-Tree. The results of implementing DPFP-Stream algorithm and testing its performance on Storm,a distribution data stream computing platform, show that the computing efficiency of DPFP-Stream can
面向子流的低延迟数据调度算法%A Novel Sub-Stream-Oriented Low-Delay Scheduling Algorithm
吴国福; 窦强; 吴吉庆; 窦文华
2012-01-01
Peer-to-Peer streaming is an effectual and promising way to distribute media content. In this paper, we present a novel sub-stream-oriented low-delay scheduling strategy under the push-pull hybrid framework. First the sub-stream scheduling problem is transformed into the matching problem of the weighted bipartite graph. Then the well-known Hungarian Algorithm is ameliorated, and a minimum delay, maximum matching algorithm is presented. Not only maximum matching is reserved by the new improved algorithm, but also the transmitting delay of each sub-stream is as low as possible. The simulation results show that our method can greatly reduce the transmission delay.%P2P流媒体是分发流媒体数据的高效方式,而数据传输延迟是决定P2P流媒体系统性能的重要参数.在分析“拉”模式数据调度模式传输延迟的基础上,本文在“推”、“拉”混合的调度模式下提出一种新的面向子流的低延迟数据调度算法.首先子流的调度问题被转换成等价的带权二部图匹配问题,其次针对转换后的二部图改进匈牙利算法,提出最小延迟、最大匹配的启发式匹配算法.该算法在保证最大匹配的同时使得每条子流的延迟尽可能地低.模拟实验表明本文的算法能够极大降低数据传输延迟.
Extended Fuzzy Clustering Algorithms
U. Kaymak (Uzay); M. Setnes
2000-01-01
textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applied successfully in various fields including finance and marketing. Despite the successful applications, there are a number of issues that must be dealt with in practical applications of fuz
Data Stream Clustering Algorithm Based on Neighborhood Covering%一种领域覆盖的数据流聚类算法
章季阳; 王伦文
2012-01-01
Data stream clustering analysis is one of the key techniques in data stream mining. To meet the requirement of evolution and high-speed processing, a data stream clustering algorithm based on Neighborhood Covering is proposed, namely NCStream. By building Neighborhood Covering model, the proposed algorithm for the evolving procedure of data stream is defined and analyzed at length, including the adjustment, creation, deletion and mergence of covering cluster, and simultaneously maintain the cluster feature online. Compared with the similar clustering method, NCStream has no assignment in the number of cluster in advance, which avoids the disadvantage of clustering result due to parameter setting. Moreover, NCStream benefits the establishment of spatial index. Hence, the evolution of data stream is more effectively reflected. The experimental results on real wireless monitor data sets demonstrate that NCStream is of better performance in clustering shape, quality and processing time.%数据流聚类分析是数据流挖掘的重要手段之一.为满足数据流不断演化及高速处理的要求,提出一种领域覆盖的数据流聚类算法NCStream( Stream clustering algorithm based on Neighborhood Covering).该算法通过建立领域覆盖模型,详细定义和分析了数据流演化过程中覆盖簇调整、创建、删除和合并的行为操作,并同时对覆盖簇的聚类特征予以在线维护.与同类算法相比,NCStream算法无需事先指定聚类簇数,避免参数设置对聚类结果造成的影响,而且易于建立空间索引,因此能够更加有效地反映数据流的演化情况.实验采用无线电实际监测数据集构造数据流,实验结果表明NCStream算法在聚类形状、聚类质量以及处理时间方面具有更好的性能.
Productivity of Stream Definitions
Endrullis, Jörg; Grabmayer, Clemens; Hendriks, Dimitri; Isihara, Ariya; Klop, Jan
2007-01-01
We give an algorithm for deciding productivity of a large and natural class of recursive stream definitions. A stream definition is called ‘productive’ if it can be evaluated continuously in such a way that a uniquely determined stream is obtained as the limit. Whereas productivity is undecidable
Productivity of stream definitions
Endrullis, J.; Grabmayer, C.A.; Hendriks, D.; Isihara, A.; Klop, J.W.
2008-01-01
We give an algorithm for deciding productivity of a large and natural class of recursive stream definitions. A stream definition is called ‘productive’ if it can be evaluated continually in such a way that a uniquely determined stream in constructor normal form is obtained as the limit. Whereas prod
Lary, David J.; Mussa, Yussuf
2004-01-01
In this study a new extended Kalman filter (EKF) learning algorithm for feed-forward neural networks (FFN) is used. With the EKF approach, the training of the FFN can be seen as state estimation for a non-linear stationary process. The EKF method gives excellent convergence performances provided that there is enough computer core memory and that the machine precision is high. Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). The neural network was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9997. The neural network Fortran code used is available for download.
D. J. Lary
2004-06-01
Full Text Available In this study a new extended Kalman filter (EKF learning algorithm for feed-forward neural networks (FFN is used. With the EKF approach, the training of the FFN can be seen as state estimation for a non-linear stationary process. The EKF method gives excellent convergence performances provided that there is enough computer core memory and that the machine precision is high. Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH_{4}-N_{2}O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH_{4} volume mixing ratio (v.m.r.. The neural network was able to reproduce the CH_{4}-N_{2}O correlation with a correlation coefficient between simulated and training values of 0.9997. The neural network Fortran code used is available for download.
Bo, Yang
2010-01-01
A data stream management system (DSMS) is similar to a database management system (DBMS) but can search data directly in on-line streams. Using its mediator-wrapper approach, the extensible database system, Amos II, allows different kinds of distributed data resource to be queried. It has been extended with a stream datatype to query possibly infinite streams, which provides DSMS functionality. Nowadays, more and more web applications start to offer their services in JSON format which is a te...
Nelson, T. P.; Lachmar, T. E.
2013-09-01
Marx Creek is a groundwater-fed, artificial salmon-spawning stream near Hyder, Alaska. The purpose of this project was to develop a groundwater flow model to predict baseflow to a proposed 450-m extension of Marx Creek. To accomplish this purpose, water levels were monitored in 20 monitor wells and discharge measurements were recorded from Marx Creek. These data were used to create a three-dimensional groundwater flow model using Visual MODFLOW. Three predictive simulations were run after the model was calibrated to groundwater levels and stream discharge measurements. The proposed extension was added to the calibrated model during the first simulation, resulting in simulated baseflow to the extension stream exceeding simulated baseflow to the existing Marx Creek by 39 %. Sections of Marx Creek were removed from the model during the second simulation, resulting in a 5 % increase in simulated baseflow to the extension stream. A 32-cm reduction in the water table was simulated during the third simulation, resulting in an 18 % decrease in simulated baseflow to the extension stream. These modeling results were used by Tongass National Forest personnel to determine that baseflow to the proposed extension would likely be sufficient to provide habitat conducive to salmon spawning. The extension stream was constructed and portions of Marx Creek were decommissioned during the summer of 2008. It was observed that there is comparable or greater discharge in the extension stream than there was in the decommissioned sections of Marx Creek, although neither discharge nor stream stage measurements have yet been collected.
Data stream sliding window clustering algorithm applied in IDS%滑动窗口数据流聚类算法在IDS中的应用
朱琳; 朱参世
2014-01-01
Aimming at the traditional intrusion detection system is difficult to adapt to the increasing amount of data demand for real-time processing capability, this paper uses of sliding window and the data stream clustering technology to design a clustering algorithm based on sliding window data streams, and build the IDS network security defense model based on the algorithm. The validation of model simulation proves that the network security defense model is able to adapt to the high-speed network intrusion detection requirements.%针对传统入侵检测系统难于适应日益增长数据量对实时处理能力的需求问题，运用滑动窗口、数据流聚类技术，设计了基于滑动窗口数据流聚类算法，并构建了基于该算法的IDS网络安全防御模型。通过对该模型仿真验证，证明该网络安全防御模型能较好地适应高速网络的入侵检测需求。
Huang, Chung-Yuan
A new formulation of the stream function based on a stream function coordinate (SFC) concept for inviscid flow field calculations is presented. In addition, a new method is developed not only to accelerate, but also to stabilize the iterative schemes for steady and unsteady, linear and non-linear, scalar and system of coupled, partial differential equations. With this theory, the limitation on the time step size of an explicit scheme for solving unsteady problems and the limitation on the relaxation factors of an iterative scheme for solving steady state problems could be analytically determined. Moreover, this theory allows the determination of the optimal time steps for explicit time-stepping schemes and the optimal values of the acceleration factors for iterative schemes, if the transient behavior is immaterial.
A note on Padé approximant in extended euclidean algorithm%浅析Padé逼近的扩展欧几里德方法
李志刚; 陈佘喜
2012-01-01
介绍Padé逼近的一般理论,通过引入扩展欧几里德算法给出对任何形式幂级数(n,m)阶Padé逼近的一种计算方法；还给出该方法求Padé逼近的一个应用实例.%The general theory about Pade approximants was introduced, and a new way of computations was provided, that with extended Euclidean algorithm of an (m,n)-Pade approximant to a formal power series. In addiotions, an application example was given by applying Extended Euclidean Algorithm to obtain Pade approximation.
Derrouich, Salah; Izumida, Kiichiro; Murao, Kenji; Shiiya, Kazuhisa
The implementation of autonomous mobile robots in real life environments still has numerous challenges to face. The most crucial problem is real-time decision-making, using appropriate methods with the right hardware. Recovering the three-dimension scene geometry and detecting moving targets simultaneously from a stream of images are important tasks and have wide applicability in the creation of autonomous mobile robots, such as persistent choice of a safe route free of obstacles, targeting objects to avoid collisions, autonomous navigation and robot manipulation. In the present work, we focus on exploiting the robustness of the analogic-array-processing-aspect introduced by the Cellular Nonlinear Network paradigm to develop a real time tracking method for a stream of general signals coming from space-distributed sources for monocular autonomous mobile robots. The motivation for developing the new tracking method is from one hand the matching operation has to be performed in real-time, while from the other hand a 32 bit floating point accuracy is not often required, which, together with a vertical rectification, as an intermediate process to minimize the token relative displacements between two frames, can lead to a robust real-time object tracking system. The technique has been successfully applied to several indoor sequences of images. The results of the simulations are presented and discussed.
一种基于FEC-MDC的多用户码流快速分割算法%A FEC-MDC Based Fast Multiuser Stream Partition Algorithm
赵明; 胡栋; 范德一
2011-01-01
基于前向纠错的多描述编码(FEC-MDC)是一种在包丢失严重的信道中传输可分级图像和视频数据的有效方法.本文针对单一信源多用户的网络应用模型,研究了在描述数N固定的情况下,根据各信道传输码率的不同,通过调整发送包的长度L实现最佳码流传输的问题,提出了一种码流快速优化分割的改进算法.该算法基于已计算出的参考信道码流分割方案,在期望失真最小的准则下,首先通过在各个目标码率的邻域进行搜索计算,将搜索域分割为低码率部分和高码率部分,然后在高码率部分进行粗的二次搜索,得到最终码流分割,这不仅减少了搜索次数,降低了计算的复杂度,而且保证搜索到在该码率情况下的最佳分割.实验结果表明,本文提出的改进算法与之前的方法相比能够得到相同的平均PSNR,但是总的运算时间减少了近40%.%FEC-based multiple description coding ( FEC-MDC) is an effective approach for sending scalable image and video dato over packet-loss networks. For the scenario where different clients access the server via separate links, we envestigate best stream transmission by adjusting packet length with fixed descriptions N, according to the channel rates, and propose a modified fast, nearly optimal stream partition algorithm. Based on the already computed optimal partition of a reference channel, the algorithm calculate the expected distortion in searching area of each target rate, devides the searching areas into low rate part and high rate part, and then, carries coarse secondary search, obtaines best stream partition afterwards. In this way, not only the searching time being saved, computational conmplexity being decreased, the optimal stream partitions are guaranteed for each channel rate. Experimental results show, the proposed algorithm holds comparable performance to known algorithms , while the total computation time are decreased to approximately 40％.
Russell, Alex M
2016-01-01
We have generalized the Nanbu collision algorithm to accommodate arbitrary collision rates, enabling accurate kinetic modeling of short range particle interactions in non-Spitzerian systems. With this extension, we explore the effect of different collision models on the simulation of how ultra-intense lasers first begin to heat a target. The effect of collisions on plasma evolution is crucial for treating particle slowing, energy transport, and thermalization. The widely used Nanbu collision algorithm provides a fast and computationally efficient method to include the effects of collisions between charged particles in kinetic simulations without requiring that the particles already be in local thermal equilibrium. However, it is "hardwired" to use Spitzer collision rates appropriate for hot, relatively dilute plasmas. This restriction prevents the Nanbu collision algorithm from accurately describing the initial heating of a cold target, a key problem for the study of laser damage or the generation of the warm...
Paszkowicz, Wojciech [Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, PL-02-668 Warsaw (Poland)]. E-mail: paszk@ifpan.edu.pl
2006-04-27
Genetic algorithms represent a powerful global-optimisation tool applicable in solving tasks of high complexity in science, technology, medicine, communication, etc. The usual genetic-algorithm calculation scheme is extended here by introduction of a quadratic self-learning operator, which performs a partial local search for randomly selected representatives of the population. This operator is aimed as a minor deterministic contribution to the (stochastic) genetic search. The population representing the trial solutions is split into two equal subpopulations allowed to exhibit different mutation rates (so called asymmetric mutation). The convergence is studied in detail exploiting a crystallographic-test example of indexing of powder diffraction data of orthorhombic lithium copper oxide, varying such parameters as mutation rates and the learning rate. It is shown through the averaged (over the subpopulation) fitness behaviour, how the genetic diversity in the population depends on the mutation rate of the given subpopulation. Conditions and algorithm parameter values favourable for convergence in the framework of proposed approach are discussed using the results for the mentioned example. Further data are studied with a somewhat modified algorithm using periodically varying mutation rates and a problem-specific operator. The chance of finding the global optimum and the convergence speed are observed to be strongly influenced by the effective mutation level and on the self-learning level. The optimal values of these two parameters are about 6 and 5%, respectively. The periodic changes of mutation rate are found to improve the explorative abilities of the algorithm. The results of the study confirm that the applied methodology leads to improvement of the classical genetic algorithm and, therefore, it is expected to be helpful in constructing of algorithms permitting to solve similar tasks of higher complexity.
Mahmoud Mohammed A
2009-05-01
Full Text Available Abstract Aim This study investigated the nosocomial blood stream infection (BSI in the adult ICUs in Assiut university hospitals to evaluate the rate of infection in different ICUs, causative microorganisms, antimicrobial resistance, outcome of infection, risk factors, prevalence of extended spectrum B-lactamase producing organisms and molecular typing of Klebsiella pneumoniae strains to highlight the role of environment as a potential source of nosocomial BSI. Methods This study was conducted over a period of 12 months from January 2006 to December 2006. All Patients admitted to the different adult ICUs were monitored daily by attending physicians for subsequent development of nosocomial BSI. Blood cultures were collected from suspected patients to detect the causative organisms. After antimicrobial susceptibility testing, detection of ESBLs was conducted among gram negative isolates. Klebsiella pneumoniae isolates were tested by PCR to determine the most common group of B-lactamase genes responsible for resistance. Klebsiella pneumoniae isolates from infected patients and those isolated from the environment were typed by RAPD technique to investigate the role of environment in transmission of infection. Results The study included 2095 patients who were admitted to different ICUs at Assiut University Hospitals from January 2006 to December 2006. Blood samples were collected from infected patients for blood cultures. The colonies were identified and antibiotic sensitivities were performed. This study showed that the rate of nosocomial BSI was 75 per 1000 ICU admissions with the highest percentages in Trauma ICU (17%. Out of 159 patients with primary bloodstream infection, 61 patients died representing a crude mortality rate of 38%. Analysis of the organisms causing BSI showed that Gram positive organisms were reported in 69.1% (n = 121; MRSA was the most prevalent (18.9%, followed by methicillin resistant coagulase negative Staphylococci (16
A. Yu. Popov
2015-01-01
Full Text Available Bauman Moscow State Technical University is implementing a project to develop operating principles of computer system having radically new architecture. A developed working model of the system allowed us to evaluate an efficiency of developed hardware and software. The experimental results presented in previous studies, as well as the analysis of operating principles of new computer system permit to draw conclusions regarding its efficiency in solving discrete optimization problems related to processing of sets.The new architecture is based on a direct hardware support of operations of discrete mathematics, which is reflected in using the special facilities for processing of sets and data structures. Within the framework of the project a special device was designed, i.e. a structure processor (SP, which improved the performance, without limiting the scope of applications of such a computer system.The previous works presented the basic principles of the computational process organization in MISD (Multiple Instructions, Single Data system, showed the structure and features of the structure processor and the general principles to solve discrete optimization problems on graphs.This paper examines two search algorithms of the minimum spanning tree, namely Kruskal's and Prim's algorithms. It studies the implementations of algorithms for two SP operation modes: coprocessor mode and MISD one. The paper presents results of experimental comparison of MISD system performance in coprocessor mode with mainframes.
S. HASHEMI; H. AHMADIAN; S. MOHAMMADI
2015-01-01
Thermo-mechanical coupling in shape memory alloys is a very complicated phenomenon. The heat generation/absorption during forward/reverse transformation can lead to temperature-dependent variation of its mechanical behavior in the forms of superelasticity and shape memory effect. However, unlike the usual assumption, slow loading rate cannot guarantee an isothermal process. A two-dimensional thermo-mechanically coupled algorithm is proposed based on the original model of Lagoudas to efficiently model both superelasticity and shape memory effects and the influence of various strain rates, aspect ratios and boundary conditions. To implement the coupled model into a finite element code, a numerical staggered algorithm is employed. A number of simulations are performed to verify the proposed approach with available experimental and numerical data and to assess its efficiency in solving complex SMA problems.
Rius, Jordi; Frontera, Carles
2008-11-01
Some years ago the direct-methods origin-free modulus sum function (S) was adapted to the processing of intensity data from density functions with positive and negative peaks [Rius, Miravitlles & Allmann (1996). Acta Cryst. A52, 634-639]. That implementation used phase relationships explicitly. Although successfully applied to different situations where the number of reflections was small, its generalization to larger problems required avoiding the time-consuming manipulation of quartet terms. To circumvent this limitation, a modification of the recently introduced S-FFT algorithm (that maximizes S with only Fourier transforms) is presented here. The resulting S2-FFT algorithm is highly effective for crystal structures with at least one moderate scatterer in the unit cell. Test calculations have been performed on conventional single-crystal X-ray diffraction data, on neutron diffraction data of compounds with negative scatterers and on intensities of superstructure reflections to solve difference structures.
Streaming for Functional Data-Parallel Languages
Madsen, Frederik Meisner
, and the limited memory in these architectures, severely constrains the data sets that can be processed. Moreover, the language-integrated cost semantics for nested data parallelism pioneered by NESL depends on a parallelism-flattening execution strategy that only exacerbates the problem. This is because...... machine without any changes in the specification. We expose streams as sequences in the frontend languages to provide the programmer with high-level information and control over streamable and non-streamable computations. In particular, we can extend NESL's intuitive and high-level work–depth model......Rank algorithm and a MD5 dictionary attack algorithm. For Streaming NESL we show that for several examples of simple, but not trivially parallelizable, text-processing tasks, we obtain single-core performance on par with off-the-shelf GNU Coreutils code, and near-linear speedups for multiple cores...
Extending raw materials ordering policy with genetic algorithm%用遗传算法拓展原材料的采购策略
余玉刚; 梁樑; 王志强
2004-01-01
A fractional-integral multiple ordering method was proposed to improve the integral multiple ordering method in material procurements. To illustrate the improvement effect, a new model considering a fractional-integral multiple ordering method was presented to extend the model proposed by Woo, Hsu, and Wu (2001), and a genetic algorithm was developed to resolve the modified model. Finally a numerical study based on the example used by Woo, Hsu, and Wu was presented to illustrate that the proposed model provided a lower or equal joint total relevant cost compared with Woo, Hsu, and Wu's model.
基于自适应渐消 EKF 的 FastSLAM 算法%FastSLAM algorithm based on adaptive fading extended Kalman filter
刘丹; 段建民; 于宏啸
2016-01-01
快速同时定位与建图（fast simultaneous localization and mapping，FastSLAM）算法的采样过程会带来粒子退化问题，为了改进算法的性能，提高估计精度，从研究粒子滤波的建议分布函数出发，提出基于自适应渐消扩展卡尔曼滤波（adaptive fading extended Kalman filter，AFEKF）的 FastSLAM 算法。该算法基于 FastSLAM的基本框架，利用 AFEKF 产生一种参数可自适应调节的建议分布函数，使其更接近移动机器人的后验位姿概率分布，减缓粒子集的退化。因此在同等粒子数的情况下，该算法有效提高了 SLAM 精度，以此减少所使用的粒子数，降低算法的复杂度。基于模拟器和标准数据集的实验仿真结果验证了该算法的有效性。%Sampling process often causes particle degradation in fast simultaneous localization and mapping (FastSLAM).From the point view of the proposal distribution function,a method named the FastSLAM based on adaptive fading extended Kalman filter is proposed to improve the performance of the algorithm and increase estimation accuracy.It uses the adaptive fading extended Kalman filter (AFEKF)to compute proposal distribu-tion based on the basic framework of FastSLAM,then this proposal distribution is more close to the posterior position of the mobile robot and the degree of particle degradation is reduced.In the case of the same number of particles,the algorithm can effectively improve the accuracy of SLAM.Hence it can reduce the number of parti-cles used in the algorithm and the complexity of the algorithm.The validity of the proposed algorithm is verified by the experimental simulation results based on the simulator and the standard data set.
Bergamino, Maurizio; Barletta, Laura; Castellan, Lucio; Mancardi, Gianluigi; Roccatagliata, Luca
2015-12-01
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a well-established technique for studying blood-brain barrier (BBB) permeability that allows measurements to be made for a wide range of brain pathologies, including multiple sclerosis and brain tumors (BT). This latter application is particularly interesting, because high-grade gliomas are characterized by increased microvascular permeability and a loss of BBB function due to the structural abnormalities of the endothelial layer. In this study, we compared the extended Tofts-Kety (ETK) model and an extended derivate class from phenomenological universalities called EU1 in 30 adult patients with different BT grades. A total of 75 regions of interest were manually drawn on the MRI and subsequently analyzed using the ETK and EU1 algorithms. Significant linear correlations were found among the parameters obtained by these two algorithms. The means of R (2) obtained using ETK and EU1 models for high-grade tumors were 0.81 and 0.91, while those for low-grade tumors were 0.82 and 0.85, respectively; therefore, these two models are equivalent. In conclusion, we can confirm that the application of the EU1 model to the DCE-MRI experimental data might be a useful alternative to pharmacokinetic models in the study of BT, because the analytic results can be generated more quickly and easily than with the ETK model.
New image encryption algorithm of extended logistic equation%一种改进logistic方程的图像加密新算法
蒋梦轩; 射可夫
2012-01-01
提出了改进的logistic混沌方程和新的图像加密算法.改进的混沌方程对比logistic混沌方程具有更大的密钥空间,而且所生成的混沌序列的互相关性、敏感性等密码特性更好.新的图像加密算法是运用密码学原理设计的随机加密算法,理论上安全空间非常大.理论分析和计算机仿真实验表明该方程和该算法结合的加密机制具有更好的加密效果和安全性,能有效抵抗暴力攻击、已知明文攻击和统计分析.%An extended logistic equation and new image encryption algorithm is proposed. Compared with the logistic equation, the improved chaotic equation has larger key space, and the generated chaotic sequences has excellent performance such as cross correlation and sensitivity. The algorithm is designed based on cryptography theory and safety space is huge. Theoretical analyses and computer simulation show that the equation and the algorithm has more efficiency and security, it can resist violence attack, known-plaintext attack and statistical analysis effectively.
Improved Ontology Concept Classification Algorithm Based on Extend Tag%基于扩展标记的改进本体概念分类算法
吕素刚; 郑洪源
2011-01-01
研究Pellet系统本体概念分类算法及其优化技术,在此基础上给出一种基于扩展标记的改进算法.该算法通过概念间已知的包含关系,控制分类过程中遍历时概念加入的顺序,并最大程度地双向传播这些关系,从而有效地降低概念包含测试的次数.验证结果表明,该算法的概念分类性能平均提高约22%.%Based on research of Pellet concept of ontology classification algorithm and some optimization techniques, this paper presents a method based on extend tag improvement. The method is mainly through the use of the inclusion relations concept between the known, taking control of the classification process of inclusion of the traversal order, and the maximum two-way dissemination of these relationships, thus effectively reducing the number of concept subsumption test. Algorithm verification results show that the refined algorithm improves the performance on average by about 22% when carrying out the concept classification.
曹红; 郑鑫
2014-01-01
许多现实应用中，由于数据流的特性，使人们难以获得全部数据的类标签。为了解决类标签不完整数据流的分类问题，本文首先分析了有标签数据集对基于聚类假设半监督分类算法分类误差的影响；然后，利用分类误差影响分析以及数据流的特点，提出一种基于聚类假设半监督数据流集成分类器算法（semi-supervised data stream ensemble classifiers under the cluster assumption, SSDSEC），并针对个体分类器的权值设定进行了探讨；最后，利用仿真实验验证本文算法的有效性。%In many real-world applications, due to the characteristics of the data stream, makes it difficult to get the class labels of all data. This paper first analyzes in order to solve the problem of the class label incomplete data stream classification, labeled data set based on clustering assuming semi-supervised classification algorithms classification error; then use classification errors affect the analysis as well as the characteristics of the data stream is proposed semi-supervised data stream the integrated classifier algorithm (Semi-supervised data stream ensemble classifiers under the cluster assumption, SSDSEC), and assigning weights for individual classifier based clustering assumptions; Finally, the simulation results verify the proposed algorithm effectiveness.
Streams with Strahler Stream Order
Minnesota Department of Natural Resources — Stream segments with Strahler stream order values assigned. As of 01/08/08 the linework is from the DNR24K stream coverages and will not match the updated...
K. C. Kaku
2014-03-01
Full Text Available The Spectral Deconvolution Algorithm (SDA and SDA+ (extended SDA methodologies can be employed to separate the fine and coarse mode extinction coefficients from measured total aerosol extinction coefficients, but their common use is currently limited to AERONET Aerosol Optical Depth (AOD. Here we provide the verification of the SDA+ methodology on a non-AERONET aerosol product, by applying it to fine and coarse mode nephelometer and Particle Soot Absorption Photometer (PSAP data sets collected in the marine boundary layer. Using datasets collected on research vessels by NOAA PMEL, we demonstrate that with accurate input, SDA+ is able to predict the fine and coarse mode scattering and extinction coefficient partition in global data sets representing a range of aerosol regimes. However, in low-extinction regimes commonly found in the clean marine boundary layer, SDA+ output accuracy is sensitive to instrumental calibration errors. This work was extended to the calculation of coarse and fine mode scattering coefficients with similar success. This effort not only verifies the application of the SDA+ method to in situ data, but by inference verifies the method as a whole for a host of applications, including AERONET. Study results open the door to much more extensive use of nephelometers and PSAPs, with the ability to calculate fine and coarse mode scattering and extinction coefficients in field campaigns that do not have the resources to explicitly measure these values.
Merz, E.; Thode, C.; Eiben, B.; Wellek, S.
2016-01-01
Aim: Both previous versions of the German PRC algorithm developed by our group for routine first-trimester screening relied on the assumption that maternal blood sampling and fetal ultrasonography are performed at the same visit of a pregnant women. In this paper we present an extension of our method allowing also for constellations where this synchronization is abandoned through preponing blood sampling to dates before 11 weeks of gestation. Methods: In contrast to the directly measured concentrations of the serum parameters PAPP-A and free ß-hCG, the logarithmically transformed values could be shown to admit the construction of reference bands covering the whole range from 16 to 84 mm CRL [corresponding to 63 to 98 days of gestation]. Prior to determining reference limits from which the DoEs for each individual patient had to be calculated, the log concentrations of all PAPP-A and free ß-hCG values were transformed once more using the calibration approach established in 1 for the elimination of the influence of maternal weight. Results: Although that part of the database which was available for estimating the reference bands for blood sampling times prior to 11 weeks of gestation was comparatively sparse (898 out of 186 215 pregnancies with euploid outcome), the key statistical characteristics of the extended risk-calculation procedure turned out to be very satisfactory. Using the same cutoff value of 1:150 for the posterior risks of trisomy 21 and 13/18, the overall FPR (false positive rate) for diagnosing a T21 was found to be 3.42%. The corresponding DTR (detection rate) was obtained to be 86.8% and thus exceeded the DTR attained by PRC 2.0 for trisomy 21. For trisomies 13 and 18, the proportions of patients with calculated posterior risks exceeding the cutoff value of 1:150 were obtained to be 1.60% (=FPR) and 86.4% (=DTR). Conclusion: Transforming the measured concentrations of PAPP-A and free ß-hCG to the logarithmic scale allows one to extend the Do
The many streams of the Magellanic Stream
Stanimirovic, Snezana; Heiles, Carl; Douglas, Kevin A; Putman, Mary; Peek, Joshua E G
2008-01-01
We present results from neutral hydrogen (HI) observations of the tip of the Magellanic Stream (MS), obtained with the Arecibo telescope as a part of the on-going survey by the Consortium for Galactic studies with the Arecibo L-band Feed Array. We find four large-scale, coherent HI streams, extending continously over a length of 20 degrees, each stream possessing different morphology and velocity gradients. The newly discovered streams provide strong support for the tidal model of the MS formation by Connors et al. (2006), which suggested a spatial and kinematic bifurcation of the MS. The observed morphology and kinematics suggest that three of these streams could be interpreted as a 3-way splitting of the main MS filament, while the fourth stream appears much younger and may have originated from the Magellanic Bridge. We find an extensive population of HI clouds at the tip of the MS. Two thirds of clouds have an angular size in the range 3.5'--10'. We interpret this as being due to thermal instability, which...
上下文感知的自适应P2P流媒体数据调度算法%CONTEXT-AWARE ADAPTIVE DATA SCHEDULING ALGORITHM FOR P2P STREAMING MEDIA
李伟; 郑烇
2012-01-01
In mesh-based peer-to-peer streaming media systems, media contents are usually divided into different data segments. Among them, the scheduling algorithm in charge of coordinating the data segments from multiple sending peers is the key factor of video quality affecting users' perception. In order to improve overall performance of streaming media system, the context-aware adaptive (CAA) streaming media data scheduling algorithm is proposed in this paper. In this algorithm, the priority of data segments is defined based on the context information, and the bandwidth of networks between neighbours' nodes is dynamically evaluated. Also, the algorithm calculates the order and direction requested by data segments according to context information such as priority of segments, assessment of sending peers quality and network capacity. Simulation results show that the proposed CAA scheduling algorithm requires smaller buffering delays. What' s more, it achieves higher peer throughput and more balanced load distribution across peers than the conventional P2P streaming media scheduling algorithms. Meanwhile, it also improves the continuity index of peers.%在网格型P2P流媒体系统中,媒体内容通常分成不同的数据块.其中,负责协调来自多个发送节点的数据块的调度算法,是影响用户感知的视频质量的重要因素.为了提高流媒体系统的整体性能,提出一种上下文感知的自适应(CAA)流媒体数据调度算法.算法根据上下文信息定义了数据块的优先级,并动态估计与邻居节点间的网络带宽,根据数据块的优先级、发送节点质量的评估和网络容量等上下文信息计算数据块请求的次序和方向.仿真结果表明,CAA调度算法具有较小的缓冲延迟,在节点吞吐量和系统负载均衡方面比传统的P2P流媒体调度算法有所提高,同时节点连续性指标也得到了改进.
叶剑虹; 叶双
2013-01-01
A hybrid content delivery network combining complementary advantages of CDN and P2P called HyCDN for streaming media was presented. The CVCR4P2P (Comprehensive Value Cache Replacement Algorithm for P2P) algorithm was proposed for the peers inside domain, which considers bytes benefit of prefix data, transmission cost and access rate of streaming media. Another algorithm,DSA4ProxyC (Dynamic Scheduling Algorithm for Proxy Caching), which joints the proxy caching and server scheduling strategies for proxies between domain was also shown. It employs the scheme of cache allocation based on the current batching interval that has non-zero requests, which can be updated periodically according to the popularity of streaming media object The principle is obeyed that the data cached for each streaming media object are in proportion to their popularity at the proxy server. Theoretical analysis and simulation results show that the hybrid dynamic scheduling can effectively reduce server and network bandwidth usage,and also has a very good adaptability for the variety of the request arrival rate.%介绍了一种结合了CDN和P2P互补优势的流媒体混合内容分发网络(HyCDN).针对HyCDN不同区域提出了相应的缓存算法,域内用户端综合考虑了流媒体前缀字节的有用性、文件的传输代价及点播热度,在此基础上提出缓存替换算法(Comprehensive Value Cache Replacement Algorithm for P2P,CVCR4P2P)；对域间边缘服务器采用补丁预取与调度算法(Dynamic Scheduling Algorithm for Proxy Caching,DSA4ProxyC),通过基于用户访问情况自适应伸缩缓存的分配方案,使流媒体后缀部分在边缘服务器中缓存的数据段与其流行度成正比.理论分析及实验结果表明,混合流媒体缓存调度策略的实施能有效地降低骨干网络带宽资源消耗,对用户请求到达速率的变化具有良好的适应性.
许颖梅
2014-01-01
Sliding window is one kind of approximation methods on recent data in data streams .This paper proposes an optimization algorithm SWStream which processes data over sliding window .In the online component , the sliding window tree is introduced to store the important statistical information of data streams , and adjust the sizes of sliding windows .Optimized algorithm can promptly eliminate expired tuple , and the new tuples arrive continuously in real-time processing , which can achieve more accurate results .In the offline component, by employing the mean value of the macro-clusters, generate the final clustering results .Com-pared with clustering algorithm CluStream , this algorithm is more efficient on data processing and memory sav-ing.%滑动窗口是数据流中一种关注近期数据的近似方法，提出一种采用滑动窗口处理数据的优化算法SWStream。在线阶段利用滑动窗口树存储概要结构，动态调整窗口大小。优化后的算法能及时淘汰过期元组，同时对新到达的元组不断进行实时处理，可以获得更准确的分析结果。而在离线阶段对上一阶段的结果进行宏聚类，得到最后的结果。与聚类算法CluS-tream相比，此算法处理数据的效率更高，也相对节约内存。
杨静; 李文平; 张健沛
2012-01-01
现存的多维数据流典型相关分析(Canonical Correlation Analysis,简称CCA)算法主要是基于近似技术的求解方法,本质上并不是持续更新的精确算法.为了能在时变的环境中持续、快速而精确地跟踪数据流之间的相关性,本文提出一种多维数据流典型相关跟踪算法TCCA.该算法基于秩2更新理论,通过并行方式持续更新样本协方差矩阵的特征子空间,进而实现多维数据流典型相关的快速跟踪.理论分析及仿真实验结果表明,TCCA具有较好的稳定性、较高的计算效率和精度,可以作为基本工具应用于数据流相关性检测、特征融合、数据降维等数据流挖掘领域.%Existing algorithms for canonical correlation analysis(CCA) of multidimensional data streams are mostly based on approximate techniques,but are not the precise algorithms for updates in essence. In this study,a novel canonical correlation analysis algorithm, called TCCA( Tracking CCA) ,is proposed for tracking the correlations rapidly and accurately between two multidimensional data streams in the time-varying environments. By introducing the technique of rank two modifications to update the eigen-subspace of the sample covariance matrix in parallel,TCCA can rapidly track the correlations of data streams. Theoretical analysis and experimental results indicate that the TCCA algorithm has better stability, high computational efficiency and accuracy. It could be presented as a basic tool for correlation detection on data streams, feature fusion, dimension reduction and other areas of data streams mining.
Daniela J. López-Araujo
2013-01-01
Full Text Available In this work, an output‐feedback adaptive SP‐SD‐type control scheme for the global position stabilization of robot manipulators with bounded inputs is proposed. Compared with the output‐feedback adaptive approaches previously developed in a bounded‐ input context, the proposed velocity‐free feedback controller guarantees the adaptive regulation objective globally (i.e. for any initial condition, avoiding discontinuities throughout the scheme, preventing the inputs from reaching their natural saturation bounds and imposing no saturation-avoidance restrictions on the choice of the P and D control gains. Moreover, through its extended structure, the adaptation algorithm may be configured to evolve either in parallel (independently or interconnected to the velocity estimation (motion dissipation auxiliary dynamics, giving an additional degree of design flexibility. Furthermore, the proposed scheme is not restricted to the use of a specific saturation function to achieve the required boundedness, but may involve any one within a set of smooth and non‐smooth (Lipschitz‐continuous bounded passive functions that include the hyperbolic tangent and the conventional saturation as particular cases. Experimental results on a 3‐ degree‐of‐freedom manipulator corroborate the efficiency of the proposed scheme.
DuPont, Bryony; Cagan, Jonathan; Moriarty, Patrick
2016-07-01
This paper presents a system of modeling advances that can be applied in the computational optimization of wind plants. These modeling advances include accurate cost and power modeling, partial wake interaction, and the effects of varying atmospheric stability. To validate the use of this advanced modeling system, it is employed within an Extended Pattern Search (EPS)-Multi-Agent System (MAS) optimization approach for multiple wind scenarios. The wind farm layout optimization problem involves optimizing the position and size of wind turbines such that the aerodynamic effects of upstream turbines are reduced, which increases the effective wind speed and resultant power at each turbine. The EPS-MAS optimization algorithm employs a profit objective, and an overarching search determines individual turbine positions, with a concurrent EPS-MAS determining the optimal hub height and rotor diameter for each turbine. Two wind cases are considered: (1) constant, unidirectional wind, and (2) three discrete wind speeds and varying wind directions, each of which have a probability of occurrence. Results show the advantages of applying the series of advanced models compared to previous application of an EPS with less advanced models to wind farm layout optimization, and imply best practices for computational optimization of wind farms with improved accuracy.
Bieniasz, Leslaw K.; Østerby, Ole; Britz, Dieter
1995-01-01
We extend the analysis of the stepwise numerical stability of the classic explicit, fully implicit and Crank-Nicolson finite difference algorithms for electrochemical kinetic simulations, to the multipoint gradient approximations at the electrode. The discussion is based on the matrix method...... of stability analysis....
Rousseau, Yannick Y.; Van de Wiel, Marco J.; Biron, Pascale M.
2017-10-01
Meandering river channels are often associated with cohesive banks. Yet only a few river modelling packages include geotechnical and plant effects. Existing packages are solely compatible with single-threaded channels, require a specific mesh structure, derive lateral migration rates from hydraulic properties, determine stability based on friction angle, rely on nonphysical assumptions to describe cutoffs, or exclude floodplain processes and vegetation. In this paper, we evaluate the accuracy of a new geotechnical module that was developed and coupled with Telemac-Mascaret to address these limitations. Innovatively, the newly developed module relies on a fully configurable, universal genetic algorithm with tournament selection that permits it (1) to assess geotechnical stability along potentially unstable slope profiles intersecting liquid-solid boundaries, and (2) to predict the shape and extent of slump blocks while considering mechanical plant effects, bank hydrology, and the hydrostatic pressure caused by flow. The profiles of unstable banks are altered while ensuring mass conservation. Importantly, the new stability module is independent of mesh structure and can operate efficiently along multithreaded channels, cutoffs, and islands. Data collected along a 1.5-km-long reach of the semialluvial Medway Creek, Canada, over a period of 3.5 years are used to evaluate the capacity of the coupled model to accurately predict bank retreat in meandering river channels and to evaluate the extent to which the new model can be applied to a natural river reach located in a complex environment. Our results indicate that key geotechnical parameters can indeed be adjusted to fit observations, even with a minimal calibration effort, and that the model correctly identifies the location of the most severely eroded bank regions. The combined use of genetic and spatial analysis algorithms, in particular for the evaluation of geotechnical stability independently of the hydrodynamic
洪月华
2013-01-01
This paper mainly studied data stream frequent itemsets mining problem of wireless sensor network. Aiming at the characteristics of sensor networks that centralized static data stream frequent itemset mining method cannot be directly used in sensor network,a frequent itemset mining algorithm FIMDS based on distributed data stream of sensor network was proposed. Based on FP-tree, the algorithm can fast mine the single data stream local frequent Itemsets of sensor nodes,and then through the routing, the local frequent itemsets are uploaded and combined layer-by-layer, and last local frequent itemsets collected on the sink node and global frequent itemsets are got by the top-down efficient pruning strategy. The experimental results show that the algorithm can effectively and greatly reduce candidate item-sets, and reduces the amount of communication traffic in wireless sensor networks, so the algorithm has good performance in time and space.%研究无线传感器网络中数据流频繁项集挖掘问题.针对集中式的静态数据流频繁项集挖掘方法不能在传感器网络中直接使用这一特点,提出基于传感器网络的分布式数据流的频繁项集挖掘算法FIMDS.该算法基于FP-tree快速挖掘出传感器节点上单一数据流的局部频繁项集,然后通过路由将其在无线传感器网络里逐层上传合并,在Sink节点上汇聚后,采用自顶向下的高效剪枝策略挖掘出全局频繁项集.实验结果表明,该算法能有效地大幅度减少候选项集,降低无线传感器网络中的通信量,并有较高的时间和空间效率.
Class Incremental Learning Algorithm for P2P Streaming Media Identification%用于P2P流媒体识别的类增量学习算法
李进; 张鑫; 王晖
2011-01-01
针对P2P流媒体流量识别中的类增量学习问题,提出一种基于“一对一”支持向量机多分类器的类增量学习算法CIOOL.充分利用原有多分类器知识,在不打破原有分类器体系的前提下加入新增类样本知识,以构造出新的多分类器.实验结果表明,CIOOL算法能在保证识别精度的同时减少训练时间和内存消耗,是一种解决P2P流媒体流量识别中类增量问题的有效方法.%This paper studies class incremental learning of P2P streaming traffic identification by using one-against-one Support VectorMachine(SVM) multi-classification. A new SVM class incremental learning algorithm--Class Incremental One-against-One Learning(CIOOL) ispresented. CIOOL can adequately use former knowledge to construct a new multi-classifier without training over again. Experimental results indicate that CIOOL can decrease the time of training and memory consuming, and it is an effective algorithm to solve the problem of class incremental learning in P2P streaming traffic identification.
Nightingale, James; Wang, Qi; Grecos, Christos
2011-03-01
Users of the next generation wireless paradigm known as multihomed mobile networks expect satisfactory quality of service (QoS) when accessing streamed multimedia content. The recent H.264 Scalable Video Coding (SVC) extension to the Advanced Video Coding standard (AVC), offers the facility to adapt real-time video streams in response to the dynamic conditions of multiple network paths encountered in multihomed wireless mobile networks. Nevertheless, preexisting streaming algorithms were mainly proposed for AVC delivery over multipath wired networks and were evaluated by software simulation. This paper introduces a practical, hardware-based testbed upon which we implement and evaluate real-time H.264 SVC streaming algorithms in a realistic multihomed wireless mobile networks environment. We propose an optimised streaming algorithm with multi-fold technical contributions. Firstly, we extended the AVC packet prioritisation schemes to reflect the three-dimensional granularity of SVC. Secondly, we designed a mechanism for evaluating the effects of different streamer 'read ahead window' sizes on real-time performance. Thirdly, we took account of the previously unconsidered path switching and mobile networks tunnelling overheads encountered in real-world deployments. Finally, we implemented a path condition monitoring and reporting scheme to facilitate the intelligent path switching. The proposed system has been experimentally shown to offer a significant improvement in PSNR of the received stream compared with representative existing algorithms.
韩玉艳; 巩敦卫; 张勇
2015-01-01
For the blocking lot-streaming flow shop scheduling problem with stochastic processing time,a method is proposed to transform it into a determinate one using Monte Carlo sampling method.An improved artificial bee colony algorithm is developed, in which a harmony search and local search based on insertion operators are adopted to balance the algorithm’s capability in explo-ration and exploitation.The proposed algorithm is applied to 24 instances of blocking lot-streaming flow shop scheduling prob-lem.The experimental results show that the improved algorithm can generate solutions with high quality and reduce the influence resulting from uncertainties.%针对含有随机加工时间的阻塞批量流水线调度问题，利用蒙特卡洛采样方法，将不确定加工时间的阻塞批量流水线调度问题转化为确定加工时间的阻塞批量调度问题。采用改进的人工蜂群算法，对上述转化后的调度问题进行求解。算法中加入了和声搜索和基于插入操作的局部搜索算子，以改进全局探索和局部开发能力，并将改进的算法应用到阻塞批量调度的24个算例中。仿真实验结果表明，改进的人工蜂群算法能够降低调度中的不确定因素带来的影响，产生高质量的解。
Akl, Selim G
1985-01-01
Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the
Pair Triplet Association Rule Generation in Streams
Manisha Thool
2013-08-01
Full Text Available Many applications involve the generation and analysis of a new kind of data, called stream data, where data flows in and out of an observation platform or window dynamically. Such data streams have the unique features such as huge or possibly infinite volume, dynamically changing, flowing in or out in a fixed order, allowing only one or a small number of scans. An important problem in data stream mining is that of finding frequent items in the stream. This problem finds application across several domains such as financial systems, web traffic monitoring, internet advertising, retail and e-business. This raises new issues that need to be considered when developing association rule mining technique for stream data. The Space-Saving algorithm reports both frequent and top-k elements with tight guarantees on errors. We also develop the notion of association rules in streams of elements. The Streaming-Rules algorithm is integrated with Space-Saving algorithm to report 1-1 association rules with tight guarantees on errors, using minimal space, and limited processing per element and we are using Apriori algorithm for static datasets and generation of association rules and implement Streaming-Rules algorithm for pair, triplet association rules. We compare the top- rules of static datasets with output of stream datasets and find percentage of error.
A stream cipher algorithm based on composite chaotic dynamical systems%一种基于复合混沌动力系统的序列密码算法
王丽燕; 李永华; 贾思齐; 刚家泰
2012-01-01
A new stream cipher algorithm is designed based on 2-D Logistic map and piecewise linear chaotic map, which uses the output of 2-D Logistic map as the piecewise parameter P of piecewise linear chaotic map. The encryption algorithm is constructed by piecewise linear chaotic map with P. The simulation experiments and security analyses are conducted for this algorithm, and the random properties and the sensitivity to initial value of stream generated by these two maps are studied. The analytical results of security indicate that this algorithm is effective in encryption, the key, plaintext and cipher text form complex and sensitive nonlinear relations, and the correlation between plaintext and cipher text is very small, which makes the algorithm effectively defend statistic analysis. The leaking of key and plaintext information from cipher text can also be effectively prevented.%基于二维Logistic映射和分段线性混沌映射，提出了一种新的序列密码算法．该算法用二维Logistic映射的输出作为分段线性映射的分段参数P．再用带有参数P的分段线性混沌映射构造加密算法．对算法进行了仿真实验和安全性分析，并对由二维Logistic映射和分段线性混沌映射产生的序列的随机性、初值敏感性等性质进行了研究．安全性分析表明，该算法加密效果良好，密钥、明文与密文之间关系均十分敏感，而且密文和明文的相关度也很小，可以有效地抵御统计分析，防止密文对密钥和明文信息的泄露．
Visual analytics of anomaly detection in large data streams
Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.; Sharma, Ratnesh K.; Mehta, Abhay
2009-01-01
Most data streams usually are multi-dimensional, high-speed, and contain massive volumes of continuous information. They are seen in daily applications, such as telephone calls, retail sales, data center performance, and oil production operations. Many analysts want insight into the behavior of this data. They want to catch the exceptions in flight to reveal the causes of the anomalies and to take immediate action. To guide the user in finding the anomalies in the large data stream quickly, we derive a new automated neighborhood threshold marking technique, called AnomalyMarker. This technique is built on cell-based data streams and user-defined thresholds. We extend the scope of the data points around the threshold to include the surrounding areas. The idea is to define a focus area (marked area) which enables users to (1) visually group the interesting data points related to the anomalies (i.e., problems that occur persistently or occasionally) for observing their behavior; (2) discover the factors related to the anomaly by visualizing the correlations between the problem attribute with the attributes of the nearby data items from the entire multi-dimensional data stream. Mining results are quickly presented in graphical representations (i.e., tooltip) for the user to zoom into the problem regions. Different algorithms are introduced which try to optimize the size and extent of the anomaly markers. We have successfully applied this technique to detect data stream anomalies in large real-world enterprise server performance and data center energy management.
Research of P2P Live Streaming Scheduling Algorithm in Heterogeneous Environment%异构环境下P2P直播流媒体调度算法研究
陈华; 宋建新
2012-01-01
In this paper, the scheduling algorithm of P2P live streaming media system in heterogeneous environment is investigated, including the system model and the relevant identification, data block scheduling algorithm research based on bandwidth perception, and performance evaluation. It shows that exploiting the heterogeneity effectively when designing the data scheduling algorithm, favoring the high uplink bandwidth peer, can reduce the average chunk transmission delay effectively.%对节点上行带宽异构环境下的P2P流媒体系统数据块调度算法进行了研究,具体包括系统模型及相关标识,基于带宽感知的数据块调度算法研究和性能评价.通过研究发现,在设计数据块调度算法时充分利用带宽异构性,优先选择高上行带宽的节点,能有效地降低平均块延时.
STREAM2016: Streaming Requirements, Experience, Applications and Middleware Workshop
Fox, Geoffrey [Indiana Univ., Bloomington, IN (United States); Jha, Shantenu [Rutgers Univ., New Brunswick, NJ (United States); Ramakrishnan, Lavanya [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2016-10-01
discusses four research directions driven by current and future application requirements reflecting the areas identified as important by STREAM2016. These include (i) Algorithms, (ii) Programming Models, Languages and Runtime Systems (iii) Human-in-the-loop and Steering in Scientific Workflow and (iv) Facilities.
Kansas Data Access and Support Center — Digital representation of the map accompanying the "Kansas stream and river fishery resource evaluation" (R.E. Moss and K. Brunson, 1981.U.S. Fish and Wildlife...
Kummel, Miro; Bruder, Andrea; Powell, Jim; Kohler, Brynja; Lewis, Matt
2016-01-01
Dead leaves, ping-pong balls or plastic golf balls are floated down a small stream. The number of leaves/balls passing recording stations along the stream are tallied. Students are then challenged to develop a transport model for the resulting data. From this exercise students gain greater understanding of PDE modeling, conservation laws, parameter estimation as well as mass and momentum transport processes.
Pattern Discovery and Change Detection of Online Music Query Streams
Li, Hua-Fu
In this paper, an efficient stream mining algorithm, called FTP-stream (Frequent Temporal Pattern mining of streams), is proposed to find the frequent temporal patterns over melody sequence streams. In the framework of our proposed algorithm, an effective bit-sequence representation is used to reduce the time and memory needed to slide the windows. The FTP-stream algorithm can calculate the support threshold in only a single pass based on the concept of bit-sequence representation. It takes the advantage of "left" and "and" operations of the representation. Experiments show that the proposed algorithm only scans the music query stream once, and runs significant faster and consumes less memory than existing algorithms, such as SWFI-stream and Moment.
詹长书; 陈勇汛
2013-01-01
文章首先介绍了物流领域中经典的车辆路径问题(VRP),以及解决该问题的算法,然后论述了遗传算法在解决VRP上的应用,并详细地叙述ExtendSim仿真软件如何对某一VRP进行建模优化,最后得出最优方案.验证了这一仿真优化方法是解决VRP的一种有效途径.
冯雪丽; 颜伏伍; 胡杰
2016-01-01
Dynamic velocity determination had to meet the higher requirement from the vehicle electronic control system. The algorithm combining finite⁃difference algorithm with extended Kalman filtering algorithm has higher accuracy in GPS veloci⁃ty determination than GPS location difference velocity determination method,but there is a larger measuring error during the fast turning of car. The finite⁃difference operation is adopted to achieve the priori error covariance matrix and the posterior error cova⁃riance matrix of filtering to enhance the convergence of the filtering process,and then the finite⁃difference extended Kalman fil⁃tering algorithm is used to calculate car’s real⁃time location,so as to get the real⁃time speed of the vehicle. The experiment re⁃sults show that the improved algorithm has higher measuring accuracy than that of the extended Kalman filtering velocity determi⁃nation algorithm.%汽车电子控制系统对动态测速提出较高的要求，使用位差法和扩展卡尔曼滤波融合算法用于GPS测速比GPS位置差分测速方法具有更高的精度，但在汽车快速转弯时误差较大。为此通过有限差分运算获取滤波验前、验后误差协方差矩阵，增强滤波过程的收敛性，再以有限差分扩展卡尔曼滤波算法对汽车实时位置进行运算以获取实时车速。实验结果表明，相比扩展卡尔曼滤波GPS测速方法，该文算法具有更高的测速精度。
Iba, Yukito
2000-01-01
``Extended Ensemble Monte Carlo''is a generic term that indicates a set of algorithms which are now popular in a variety of fields in physics and statistical information processing. Exchange Monte Carlo (Metropolis-Coupled Chain, Parallel Tempering), Simulated Tempering (Expanded Ensemble Monte Carlo), and Multicanonical Monte Carlo (Adaptive Umbrella Sampling) are typical members of this family. Here we give a cross-disciplinary survey of these algorithms with special emphasis on the great f...
stream-stream: Stellar and dark-matter streams interactions
Bovy, Jo
2017-02-01
Stream-stream analyzes the interaction between a stellar stream and a disrupting dark-matter halo. It requires galpy (ascl:1411.008), NEMO (ascl:1010.051), and the usual common scientific Python packages.
杨棉绒
2015-01-01
提出一种针对网络环境中流媒体传播与数据调度策略的改进方案，充分利用对等节点网络中子节点的资源来减轻服务器负载压力。基于遗传算法建立一种资源寻优策略，对服务器和对等网络节点中的数据资源进行更加优化的分配与调度。通过实验验证了算法的有效性。%The paper put forward an improved program focusing on strategies for streaming media transmission and data scheduling in network environment. The program aimed to reduce server’s load pressure by using the resources of sub-nodes in P2P network. On the basis of genetic algorithm, the paper proposed a resource optimization strategy which could better the matching and scheduling of data resources in the server and P2P network. Finally, the paper verified the validity of algorithm through the experimental data.
基于连续数据流的动态手势识别算法%Algorithm based on continuous data stream for dynamic gesture recognition
郑鞲; 沈旭昆
2012-01-01
For the purpose of recognizing the sequence of dynamic gesture made by operator, a method was presented based on continuous data streams sampled from data glove, which used singular value decompo- sition （SVD） to eliminating noise and extracting features. The characteristics of physiology about joint bend was applied making user-dependent information be culled. A set of gesture template which across different us- ers was set up. The template which gives a complete description of gesture＇ s feature and generalizes it is therefore user-independent. Based on Hill Climbing heuristic, these streams were separated into action se- quences, then a similarity measurement using Euclidian distance was adopted in real time between all seg- ments and templates on a hierarchy search tree built in advance. The sequences segmented by this method are accuracy and suitable for multi users. The effectiveness of this approach for identifying dynamic＇gesture was verified by two empirical experiments which using 5 DT data glove.%为识别用户做出的动态手势序列，基于数据手套采集的连续数据流，运用奇异值分解消除数据噪点，提取手势的特征信息，并利用关节弯曲的生理学特性与用户解耦合，将各种动作片段抽象成用户无关的手势模板，从而唯一定义手势特征并屏蔽不同用户的手势差异，再基于Hill Climbing思想把连续数据流分割成有序的动作序列，并按时序对所有片段在预先构造的层次树上实时搜索，根据欧式距离度量序列与手势模板的相似性，该算法对手势序列的分割准确，对多用户具有良好的适应性，其有效性在使用5DT数据手套搭建的两组动态手势识别的实验中得以验证。
Chunk Scheduling Algorithm of P2P Live Streaming in Single-rate%单码流场景下P2P流媒体直播数据调度方法
常国锋
2013-01-01
由于具有较高应对节点动态性的能力和较强的扩展性,Mesh-Pull P2P流媒体直播分发方法赢得了学术界和工业界的广泛青睐.提出了传统互联网单码流场景下Mesh-Pull P2P流媒体直播的数据调度算法.该算法采用TOPSIS方法来解决调度算法中数据块优先级的量化这一多属性决策问题,以降低节点的启动延迟.仿真实验表明,本算法可以在保证高视频播放质量的情况下降低用户观看视频的延迟.%Due to the higher ability to cope with node dynamics and strong scalability,Mesh-Pull P2P live streaming distribution method won academia and industry for most cities.In this paper,a chunk scheduling algorithm in the traditional single-rate environment is proposed.The algorithm uses TOPSIS methods to solve scheduling priority data block quantify this multi-attribute decision making problems to reduce the startup delay nodes.Simulation results show that the scheduling algorithm could improve the delay performance under the guarantee of high quality video.
Dynamic Clustering Of High Speed Data Streams
J. Chandrika
2012-03-01
Full Text Available We consider the problem of clustering data streams. A data stream can roughly be thought of as a transient, continuously increasing sequence of time-stamped data. In order to maintain an up-to-date clustering structure, it is necessary to analyze the incoming data in an online manner, tolerating but a constant time delay. The purpose of this study is to analyze the working of popular algorithms on clustering data streams and make a comparative analysis.
Parikh Matching in the Streaming Model
Lee, Lap-Kei; Lewenstein, Moshe; Zhang, Qin
2012-01-01
|-length count vector. In the streaming model one seeks space-efficient algorithms for problems in which there is one pass over the data. We consider Parikh matching in the streaming model. To make this viable we search for substrings whose Parikh-mappings approximately match the input vector. In this paper we...... present upper and lower bounds on the problem of approximate Parikh matching in the streaming model....
Hand Recognition in Live-Streaming Video
Mikhail, Belov
2011-01-01
The article describes the algorithmic component of the pattern recognition method for extracting hand patterns from a video stream. Methods removing excess information from frames, localizing fragments with a hand and extracting hand contours to classify them are described.
Efficient architectures for streaming applications
Smit, Gerard J.M.; Kokkeler, André B.J.; Wolkotte, Pascal T.; Burgwal, van de Marcel D.; Heysters, Paul M.; Athanas, P.; Becker, J.; Brebner, G.; Teich, J.
2006-01-01
This presentation will focus on algorithms and reconfigurable tiled architectures for streaming DSP applications. The tile concept will not only be applied on chip level but also on board-level and system-level. The tile concept has a number of advantages: (1) depending on the requirements more or l
Modified Streaming Format for Direct Access Triangular Data Structures
Khaled Abid
2014-01-01
Full Text Available We define in this paper an extended solution to improve an Out-of-Core data structure which is the streaming format, by adding new information allowing to reduce file access cost, reducing the neighborhood access delay to constant time. The original streaming format is conceived to manipulate huge triangular meshes. It assumes that the whole mesh cannot be loaded entirely into the main memory. That's why the authors did not include the neighborhood in the file structure. However, almost all of the applications need the neighborhood information in the triangular structures. Using the original streaming format does not allow us to extract the neighborhood information easily. By adding the neighbor indices to the file in the same way as the original format, we can benefit from the streaming format, and at the same time, guarantee a constant time access to the neighborhood. We have adapted our new structure so that it can allow us to apply our direct access algorithm to different parts of the structure without having to go through the entire file.
Huang, Haoqian; Chen, Xiyuan; Zhou, Zhikai; Xu, Yuan; Lv, Caiping
2014-12-03
High accuracy attitude and position determination is very important for underwater gliders. The cross-coupling among three attitude angles (heading angle, pitch angle and roll angle) becomes more serious when pitch or roll motion occurs. This cross-coupling makes attitude angles inaccurate or even erroneous. Therefore, the high accuracy attitude and position determination becomes a difficult problem for a practical underwater glider. To solve this problem, this paper proposes backing decoupling and adaptive extended Kalman filter (EKF) based on the quaternion expanded to the state variable (BD-AEKF). The backtracking decoupling can eliminate effectively the cross-coupling among the three attitudes when pitch or roll motion occurs. After decoupling, the adaptive extended Kalman filter (AEKF) based on quaternion expanded to the state variable further smoothes the filtering output to improve the accuracy and stability of attitude and position determination. In order to evaluate the performance of the proposed BD-AEKF method, the pitch and roll motion are simulated and the proposed method performance is analyzed and compared with the traditional method. Simulation results demonstrate the proposed BD-AEKF performs better. Furthermore, for further verification, a new underwater navigation system is designed, and the three-axis non-magnetic turn table experiments and the vehicle experiments are done. The results show that the proposed BD-AEKF is effective in eliminating cross-coupling and reducing the errors compared with the conventional method.
Morshed, Mohammad Sarwar; Kamal, Mostafa Mashnoon; Khan, Somaiya Islam
2016-07-01
Inventory has been a major concern in supply chain and numerous researches have been done lately on inventory control which brought forth a number of methods that efficiently manage inventory and related overheads by reducing cost of replenishment. This research is aimed towards providing a better replenishment policy in case of multi-product, single supplier situations for chemical raw materials of textile industries in Bangladesh. It is assumed that industries currently pursue individual replenishment system. The purpose is to find out the optimum ideal cycle time and individual replenishment cycle time of each product for replenishment that will cause lowest annual holding and ordering cost, and also find the optimum ordering quantity. In this paper indirect grouping strategy has been used. It is suggested that indirect grouping Strategy outperforms direct grouping strategy when major cost is high. An algorithm by Kaspi and Rosenblatt (1991) called RAND is exercised for its simplicity and ease of application. RAND provides an ideal cycle time (T) for replenishment and integer multiplier (ki) for individual items. Thus the replenishment cycle time for each product is found as T×ki. Firstly, based on data, a comparison between currently prevailing (individual) process and RAND is provided that uses the actual demands which presents 49% improvement in total cost of replenishment. Secondly, discrepancies in demand is corrected by using Holt's method. However, demands can only be forecasted one or two months into the future because of the demand pattern of the industry under consideration. Evidently, application of RAND with corrected demand display even greater improvement. The results of this study demonstrates that cost of replenishment can be significantly reduced by applying RAND algorithm and exponential smoothing models.
Weigend, Florian, E-mail: florian.weigend@kit.edu [Institut für Physikalische Chemie, Abteilung für Theoretische Chemie, Karlsruher Institut für Technologie, Fritz-Haber-Weg 2, 76131 Karlsruhe, Germany and Institut für Nanotechnologie, Karlsruher Institut für Technologie, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen (Germany)
2014-10-07
Energy surfaces of metal clusters usually show a large variety of local minima. For homo-metallic species the energetically lowest can be found reliably with genetic algorithms, in combination with density functional theory without system-specific parameters. For mixed-metallic clusters this is much more difficult, as for a given arrangement of nuclei one has to find additionally the best of many possibilities of assigning different metal types to the individual positions. In the framework of electronic structure methods this second issue is treatable at comparably low cost at least for elements with similar atomic number by means of first-order perturbation theory, as shown previously [F. Weigend, C. Schrodt, and R. Ahlrichs, J. Chem. Phys. 121, 10380 (2004)]. In the present contribution the extension of a genetic algorithm with the re-assignment of atom types to atom sites is proposed and tested for the search of the global minima of PtHf{sub 12} and [LaPb{sub 7}Bi{sub 7}]{sup 4−}. For both cases the (putative) global minimum is reliably found with the extended technique, which is not the case for the “pure” genetic algorithm.
Weigend, Florian
2014-10-07
Energy surfaces of metal clusters usually show a large variety of local minima. For homo-metallic species the energetically lowest can be found reliably with genetic algorithms, in combination with density functional theory without system-specific parameters. For mixed-metallic clusters this is much more difficult, as for a given arrangement of nuclei one has to find additionally the best of many possibilities of assigning different metal types to the individual positions. In the framework of electronic structure methods this second issue is treatable at comparably low cost at least for elements with similar atomic number by means of first-order perturbation theory, as shown previously [F. Weigend, C. Schrodt, and R. Ahlrichs, J. Chem. Phys. 121, 10380 (2004)]. In the present contribution the extension of a genetic algorithm with the re-assignment of atom types to atom sites is proposed and tested for the search of the global minima of PtHf12 and [LaPb7Bi7](4-). For both cases the (putative) global minimum is reliably found with the extended technique, which is not the case for the "pure" genetic algorithm.
The Gulf Stream: Inertia and friction
ASSAF, GAD
2011-01-01
The inertial theory of the Gulf Stream (Charney, 1955) is extended to include vertical friction in the cyclonic shear zone (the western side) of the stream. The vertical friction is assumed to be controlled by local Froude conditions.DOI: 10.1111/j.2153-3490.1977.tb00717.x
王静; 郁梅; 李文锋; 骆挺
2016-01-01
针对 HEVC 的视频流版权问题，提出了一种抗量化转码的零水印算法。首先，经过统计发现量化转码后编码单元(CU)深度具有很强的稳定性，部分深度会发生转移且主要往相邻深度转移；然后，为增加深度特征的顽健性，对 CU 深度进行分组，并映射成二值信息；最后，将加密后的特征信息同混沌置乱后的版权信息异或，与时间戳作为最终注册的零水印。实验结果表明，该算法对量化参数在一定变化范围内的重量化转码攻击以及常见的信号攻击具有很强的鲁棒性。%For the video stream copyright issues of high efficiency video coding (HEVC), a new zero-watermarking algorithm with robustness to re-quantization transcoding is proposed. Firstly, from statistics analysis about re-quantization transcoding, it is found that Coding Unit (CU) depths have strong stability and only a fraction of the depths would shift and almost shift to adjacent depths. Then, in order to increase the robustness of the depth characteristic, the CU depths are divided into two groups and mapped into two values ‘0’ and ‘1’. Finally, ‘xor’ operation is performed between the binary information encrypted and the copyright information scrambled by using the chaotic algorithm, the outcome with the timestamp acts as the ultimate registered zero-watermarking. Experimental results show that the proposed algorithm has strong robustness to re-quantization transcoding and other common signal attacks.
基于两个离散混沌动力系统的序列密码算法%A stream cipher algorithm based on two discrete chaotic dynamical systems
王丽燕; 许佳佳; 李海燕
2014-01-01
A new stream cipher algorithm is designed based on two discrete chaotic dynamical systems.The algorithm uses the front output of the piecewise nonlinear map as the next input of the piecewise nonlinear map,and the iterative sequences are transformed into 0-1 sequence with discrete operator,and then,the 0-1 sequence is used to select the piecewise nonlinear maps of the two chaotic dynamical systems.The simulation test and security analysis are conducted to study the randomness, the initial value sensitivity and other properties of sequences generated by the map.The experimental results show that the algorithm has the characteristics of the high sensitivity of secret key,plaintext and ciphertext,and the small correlation between ciphertext and plaintext.These peculiarities can efficiently prevent ciphertext to leak the information of secret key and plaintext.%基于两个离散混沌动力系统提出了一种新的序列密码算法。该算法用分段非线性映射的上一次迭代的输出作为分段非线性映射的下一次迭代的输入，并将迭代序列通过离散化算子转化为0-1序列，由0-1序列来选择两个混沌动力系统中的分段非线性映射。对算法进行了仿真实验和安全性分析，并对该映射产生的序列的随机性、初始值敏感性及其他性质进行了研究。研究结果表明，算法呈现出密钥、明文与密文之间高度的敏感性，密文和明文之间的相关度极小等特点，从而起到有效防止密文对密钥和明文信息泄露的作用。
CLUSTERING ANALYSIS OF DEBRIS-FLOW STREAMS
Yuan-Fan TSAI; Huai-Kuang TSAI; Cheng-Yan KAO
2004-01-01
The Chi-Chi earthquake in 1999 caused disastrous landslides, which triggered numerous debris flows and killed hundreds of people. A critical rainfall intensity line for each debris-flow stream is studied to prevent such a disaster. However, setting rainfall lines from incomplete data is difficult, so this study considered eight critical factors to group streams, such that streams within a cluster have similar rainfall lines. A genetic algorithm is applied to group 377 debris-flow streams selected from the center of an area affected by the Chi-Chi earthquake. These streams are grouped into seven clusters with different characteristics. The results reveal that the proposed method effectively groups debris-flow streams.
Sentiment Knowledge Discovery in Twitter Streaming Data
Bifet, Albert; Frank, Eibe
Micro-blogs are a challenging new source of information for data mining techniques. Twitter is a micro-blogging service built to discover what is happening at any moment in time, anywhere in the world. Twitter messages are short, and generated constantly, and well suited for knowledge discovery using data stream mining. We briefly discuss the challenges that Twitter data streams pose, focusing on classification problems, and then consider these streams for opinion mining and sentiment analysis. To deal with streaming unbalanced classes, we propose a sliding window Kappa statistic for evaluation in time-changing data streams. Using this statistic we perform a study on Twitter data using learning algorithms for data streams.
Triangle Counting in Dynamic Graph Streams
Bulteau, Laurent; Froese, Vincent; Pagh, Rasmus
2015-01-01
, with a few exceptions, the algorithms have considered insert-only streams. We present a new algorithm estimating the number of triangles in dynamic graph streams where edges can be both inserted and deleted. We show that our algorithm achieves better time and space complexity than previous solutions......Estimating the number of triangles in graph streams using a limited amount of memory has become a popular topic in the last decade. Different variations of the problem have been studied, depending on whether the graph edges are provided in an arbitrary order or as incidence lists. However...... for various graph classes, for example sparse graphs with a relatively small number of triangles. Also, for graphs with constant transitivity coefficient, a common situation in real graphs, this is the first algorithm achieving constant processing time per edge. The result is achieved by a novel approach...
Extended scaling in high dimensions
Berche, B.; Chatelain, C.; Dhall, C.; Kenna, R.; Low, R.; Walter, J.-C.
2008-11-01
We apply and test the recently proposed 'extended scaling' scheme in an analysis of the magnetic susceptibility of Ising systems above the upper critical dimension. The data are obtained by Monte Carlo simulations using both the conventional Wolff cluster algorithm and the Prokof'ev-Svistunov worm algorithm. As already observed for other models, extended scaling is shown to extend the high-temperature critical scaling regime over a range of temperatures much wider than that achieved conventionally. It allows for an accurate determination of leading and sub-leading scaling indices, critical temperatures and amplitudes of the confluent corrections.
Online feature selection with streaming features.
Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan
2013-05-01
We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.
陈亮; 顾雪平; 贾京华
2014-01-01
To ensure the safe recovery of the black-start system and well synthesize the quick search and local search of multi-objective optimization method, an extended black-start multi-objective optimization method based on virus evolution improved NSGA-II algorithm considering power support and restoration security margin comprehensively is proposed. The optimization goals are designed to maximize the total weighted power generation output (MWh) of the black-start system, to maximize voltage stability margin and to maintain bus voltage at a satisfactory level. Biological virus mechanism and the infection-based operation are introduced into the chromosome of the fast and elitist non-dominated sorting genetic algorithm (NSGA-II). Horizontal infection of the virus is applied to improve local search capability in solution space and avoid the frontier degradation. The virus evolution improved NSGA-II algorithm and the Dijkstra algorithm are employed to solve the Pareto-optimal solutions of the extended black-start schemes. The effectiveness of the proposed method is validated by the optimization results on the New England 10-unit 39-bus power system and the southern power system of Hebei province. The method can provide decision-makers with greater choice of space and guarantee the extended initial black-start power system to recover more power generation output safely and reliably.%为了保证黑启动小系统的安全恢复和合理兼顾多目标优化方法的快速搜索与局部搜索，提出基于病毒进化改进NSGA-II算法的综合功率支持和恢复安全裕度的扩展黑启动方案多目标优化方法。以初期阶段内发电量加权和最大化、电压稳定裕度最大化和维持节点电压在满意水平为目标建立多目标优化模型。在快速非支配排序遗传算法（NSGA-II）的染色体中引入生物病毒机制和病毒感染操作，利用病毒的横向感染对解空间进行局部搜索，避免强化全局寻优时的前
Krueger, Joel; Szanto, Thomas
2016-01-01
Until recently, philosophers and psychologists conceived of emotions as brain- and body-bound affairs. But researchers have started to challenge this internalist and individualist orthodoxy. A rapidly growing body of work suggests that some emotions incorporate external resources and thus extend...... beyond the neurophysiological confines of organisms; some even argue that emotions can be socially extended and shared by multiple agents. Call this the extended emotions thesis (ExE). In this article, we consider different ways of understanding ExE in philosophy, psychology, and the cognitive sciences....... First, we outline the background of the debate and discuss different argumentative strategies for ExE. In particular, we distinguish ExE from cognate but more moderate claims about the embodied and situated nature of cognition and emotion (Section 1). We then dwell upon two dimensions of ExE: emotions...
Müller, Ingo
1993-01-01
Physicists firmly believe that the differential equations of nature should be hyperbolic so as to exclude action at a distance; yet the equations of irreversible thermodynamics - those of Navier-Stokes and Fourier - are parabolic. This incompatibility between the expectation of physicists and the classical laws of thermodynamics has prompted the formulation of extended thermodynamics. After describing the motifs and early evolution of this new branch of irreversible thermodynamics, the authors apply the theory to mon-atomic gases, mixtures of gases, relativistic gases, and "gases" of phonons and photons. The discussion brings into perspective the various phenomena called second sound, such as heat propagation, propagation of shear stress and concentration, and the second sound in liquid helium. The formal mathematical structure of extended thermodynamics is exposed and the theory is shown to be fully compatible with the kinetic theory of gases. The study closes with the testing of extended thermodynamics thro...
Stream Execution on Embedded Wide-Issue Clustered VLIW Architectures
Shan Yan
2009-02-01
Full Text Available Very long instruction word- (VLIW- based processors have become widely adopted as a basic building block in modern System-on-Chip designs. Advances in clustered VLIW architectures have extended the scalability of the VLIW architecture paradigm to a large number of functional units and very-wide-issue widths. A central challenge with wide-issue clustered VLIW architecture is the availability of programming and automated compiler methods that can fully utilize the available computational resources. Existing compilation approaches for clustered-VLIW architectures are based on extensions of previously developed scheduling algorithms that primarily focus on the maximization of instruction-level parallelism (ILP. However, many applications do not have sufficient ILP to fully utilize a large number of functional units. On the other hand, many applications in digital communications and multimedia processing exhibit enormous amounts of data-level parallelism (DLP. For these applications, the streaming programming paradigm has been developed to explicitly expose coarse-grained data-level parallelism as well as the locality of communication between coarse-grained computation kernels. In this paper, we investigate the mapping of stream programs to wide-issue clustered VLIW processors. Our work enables designers to leverage their existing investments in VLIW-based architecture platforms to harness the advantages of the stream programming paradigm.
Stream Execution on Embedded Wide-Issue Clustered VLIW Architectures
Yan Shan
2008-01-01
Full Text Available Abstract Very long instruction word- (VLIW- based processors have become widely adopted as a basic building block in modern System-on-Chip designs. Advances in clustered VLIW architectures have extended the scalability of the VLIW architecture paradigm to a large number of functional units and very-wide-issue widths. A central challenge with wide-issue clustered VLIW architecture is the availability of programming and automated compiler methods that can fully utilize the available computational resources. Existing compilation approaches for clustered-VLIW architectures are based on extensions of previously developed scheduling algorithms that primarily focus on the maximization of instruction-level parallelism (ILP. However, many applications do not have sufficient ILP to fully utilize a large number of functional units. On the other hand, many applications in digital communications and multimedia processing exhibit enormous amounts of data-level parallelism (DLP. For these applications, the streaming programming paradigm has been developed to explicitly expose coarse-grained data-level parallelism as well as the locality of communication between coarse-grained computation kernels. In this paper, we investigate the mapping of stream programs to wide-issue clustered VLIW processors. Our work enables designers to leverage their existing investments in VLIW-based architecture platforms to harness the advantages of the stream programming paradigm.
赵学良; 肖永松
2011-01-01
For mnltiple-input single-output (MISO) output-error systems, estimates from the conventional recursive least squares parameter identification method are biased. In order to euhanlce accuracy and speed of convergence for stochastic gradient identification algorithm, an auxiliary model based multi-innovation extended stochastic gradient (AM-MI-ESG) algorithm is presented by replacing the unknown unmeasurable variables in the information vector with the outputs of the auxiliary model, and introducing the innovation length and expanding the scalar innovation to an innovation vector. The AM-M1-ESG algorithm uses not only the current data and innovation but also the past data and innovation at each iteration, thus the parameter estimation accuracy and convergence rate can be improved. The simulation results show that the proposed algorithm is effective.%对于有色噪声干扰的输出误差多输入单输出(MISO)系统,常规的递推最小二乘辨识方法给出的参数估计是有偏的.为了提高随机梯度辨识方法的收敛精度和速度,用辅助模型的输出代替辨识模型信息向量中的未知不可测变量,推导出其辅助模型增广随机梯度辨识算法;再引入新息长度扩展标量新息为新息向量,提出了基于辅助模型的MISO系统多新息增广随机梯度辨识算法.所得算法在每一次的迭代中不仅使用了当前数据和新息,而且使用了过去数据和新息,提高了参数估计精度和收敛速度.仿真例子验证了算法的有效性.
Streaming Compression of Hexahedral Meshes
Isenburg, M; Courbet, C
2010-02-03
We describe a method for streaming compression of hexahedral meshes. Given an interleaved stream of vertices and hexahedral our coder incrementally compresses the mesh in the presented order. Our coder is extremely memory efficient when the input stream documents when vertices are referenced for the last time (i.e. when it contains topological finalization tags). Our coder then continuously releases and reuses data structures that no longer contribute to compressing the remainder of the stream. This means in practice that our coder has only a small fraction of the whole mesh in memory at any time. We can therefore compress very large meshes - even meshes that do not file in memory. Compared to traditional, non-streaming approaches that load the entire mesh and globally reorder it during compression, our algorithm trades a less compact compressed representation for significant gains in speed, memory, and I/O efficiency. For example, on the 456k hexahedra 'blade' mesh, our coder is twice as fast and uses 88 times less memory (only 3.1 MB) with the compressed file increasing about 3% in size. We also present the first scheme for predictive compression of properties associated with hexahedral cells.
StreamMap: Smooth Dynamic Visualization of High-Density Streaming Points.
Li, Chenhui; Baciu, George; Yu, Han
2017-02-13
Interactive visualization of streaming points for real-time scatterplots and linear blending of correlation patterns is increasingly becoming the dominant mode of visual analytics for both big data and streaming data from active sensors and broadcasting media. To better visualize and interact with inter-stream patterns, it is generally necessary to smooth out gaps or distortions in the streaming data. Previous approaches either animate the points directly or present a sampled static heatmap. We propose a new approach, called StreamMap, to smoothly blend high-density streaming points and create a visual flow that emphasizes the density pattern distributions. In essence, we present three new contributions for the visualization of high-density streaming points. The first contribution is a density-based method called super kernel density estimation that aggregates streaming points using an adaptive kernel to solve the overlapping problem. The second contribution is a robust density morphing algorithm that generates several smooth intermediate frames for a given pair of frames. The third contribution is a trend representation design that can help convey the flow directions of the streaming points. The experimental results on three datasets demonstrate the effectiveness of StreamMap when dynamic visualization and visual analysis of trend patterns on streaming points are required.
Stream Processing Using Grammars and Regular Expressions
Rasmussen, Ulrik Terp
Kleenex, a language for expressing high-performance streaming string processing programs as regular grammars with embedded semantic actions, and its compilation to streaming string transducers with worst-case linear-time performance. Its underlying theory is based on transducer decomposition into oracle...... is based on a bottom-up tabulation algorithm reformulated using least fixed points and evaluated using an instance of the chaotic iteration scheme by Cousot and Cousot....
ENCORE: An extended contractor renormalization algorithm.
Albuquerque, A Fabricio; Katzgraber, Helmut G; Troyer, Matthias
2009-04-01
Contractor renormalization (CORE) is a real-space renormalization-group method to derive effective Hamiltionians for microscopic models. The original CORE method is based on a real-space decomposition of the lattice into small blocks and the effective degrees of freedom on the lattice are tensor products of those on the small blocks. We present an extension of the CORE method that overcomes this restriction. Our generalization allows the application of CORE to derive arbitrary effective models whose Hilbert space is not just a tensor product of local degrees of freedom. The method is especially well suited to search for microscopic models to emulate low-energy exotic models and can guide the design of quantum devices.
姜蕴珈; 宋珂; 章桐
2014-01-01
A Multiple Input Single Output(MISO) fuzzy logic controller is designed for the energy distribution of a fuel cell Extended-Range Electric Vehicle(E-REV) on basis of Genetic Algorithm(GA). By using battery SoC and transient power demand at the load bus as inputs, the fuzzy controller can calculate the optimal output power of the fuel cell extended range, which promotes a rational distribution of energy resources. Genetic algorithm optimizes the fuzzy membership function and rules of the controller, so the human knowledge or experience for parameter settings of the controller can be avoided. The validation is achieved by the simulation of ADVISOR and the experiment of car roller bench. The results demonstrate that the proposed fuzzy controller can improve the energy management strategy to attain a better economic performance.%针对燃料电池增程式电动汽车动力系统双能量源间的分配问题，设计基于遗传算法的多输入单输出(MISO)模糊控制器。控制器将动力蓄电池SOC和负载总线实时需求功率作为输入变量，求解燃料电池增程器的最佳输出功率，从而获得蓄电池和燃料电池的输出功率分配关系，以此实现不同功率需求下车载多能量源间的合理分配。为克服传统模糊控制器的参数设置仅依靠专家经验设定的局限性，采用遗传算法对模糊控制器的隶属函数和控制规则参数进行优化设计。通过ADVISOR软件仿真和转鼓实验台实车验证，结果证明，与传统能量控制策略相比，优化设计后的模糊控制能量管理策略能够明显提高增程式电动汽车的燃料经济性，并表现出较好的工况适应能力。
Franceschi, Alessandro
2014-01-01
This book is a clear, detailed and practical guide to learn about designing and deploying you puppet architecture, with informative examples to highlight and explain concepts in a focused manner. This book is designed for users who already have good experience with Puppet, and will surprise experienced users with innovative topics that explore how to design, implement, adapt, and deploy a Puppet architecture. The key to extending Puppet is the development of types and providers, for which you must be familiar with Ruby.
Data Stream Clustering With Affinity Propagation
Zhang, Xiangliang
2014-07-09
Data stream clustering provides insights into the underlying patterns of data flows. This paper focuses on selecting the best representatives from clusters of streaming data. There are two main challenges: how to cluster with the best representatives and how to handle the evolving patterns that are important characteristics of streaming data with dynamic distributions. We employ the Affinity Propagation (AP) algorithm presented in 2007 by Frey and Dueck for the first challenge, as it offers good guarantees of clustering optimality for selecting exemplars. The second challenging problem is solved by change detection. The presented StrAP algorithm combines AP with a statistical change point detection test; the clustering model is rebuilt whenever the test detects a change in the underlying data distribution. Besides the validation on two benchmark data sets, the presented algorithm is validated on a real-world application, monitoring the data flow of jobs submitted to the EGEE grid.
Max-Weight Scheduling and Quality-Aware Streaming for Device-to-Device Video Delivery
Kim, Joongheon; Molisch, Andreas F.; Caire, Giuseppe
2014-01-01
We propose and analyze centralized and distributed algorithms for device-to-device video scheduling and streaming. The proposed algorithms address jointly the problems of device-to-device link scheduling and video quality adaptation in streaming. Our simulations show that the proposed algorithms significantly outperform conventional separated approaches that treat these two problems independently.
A computer game's player is experiencing not only the game as a designer-made artefact, but also a multitude of social and cultural practices and contexts of both computer game play and everyday life. As a truly multidisciplinary anthology, Extending Experiences sheds new light on the mesh...... of possibilities and influences the player engages with. Part one, Experiential Structures of Play, considers some of the key concepts commonly used to address the experience of a computer game player. The second part, Bordering Play, discusses conceptual and practical overlaps of games and everyday life...
STRIP: stream learning of influence probabilities
Kutzkov, Konstantin
2013-01-01
cascades, and developing applications such as viral marketing. Motivated by modern microblogging platforms, such as twitter, in this paper we study the problem of learning influence probabilities in a data-stream scenario, in which the network topology is relatively stable and the challenge of a learning...... algorithm is to keep up with a continuous stream of tweets using a small amount of time and memory. Our contribution is a number of randomized approximation algorithms, categorized according to the available space (superlinear, linear, and sublinear in the number of nodes n) and according to dierent models...
Detection of Acoustic Change-Points in Audio Streams and Signal Segmentation
J. Zdansky
2005-04-01
Full Text Available This contribution proposes an efficient method for the detection ofrelevant changes in continuous stream of sound. The detectedchange-points can then serve for the segmentation of long audiorecordings into shorter and more or less homogenous sections. First, wediscuss the task of a single change-point detection using the Bayesdecision theory. We show that it leads to a quite simple andcomputationally efficient solution based on the Bayesian InformationCriterion. Next, we extend this approach to formulate the algorithm forthe detection of multiple change-points. Finally, the proposedalgorithm is applied for the segmentation of broadcast newsaudio-streams into parts belonging to different speakers or differentacoustic conditions. Such segmentation is necessary as the first stepin the automatic speech-to-text transcription of TV or radio news.
Carrara-Augustenborg, Claudia
2012-01-01
There is no consensus yet regarding a conceptualization of consciousness able to accommodate all the features of such complex phenomenon. Different theoretical and empirical models lend strength to both the occurrence of a non-accessible informational broadcast, and to the mobilization of specific...... brain areas responsible for the emergence of the individual´s explicit and variable access to given segments of such broadcast. Rather than advocating one model over others, this chapter proposes to broaden the conceptualization of consciousness by letting it embrace both mechanisms. Within...... such extended framework, I propose conceptual and functional distinctions between consciousness (global broadcast of information), awareness (individual´s ability to access the content of such broadcast) and unconsciousness (focally isolated neural activations). My hypothesis is that a demarcation in terms...
Stretch-minimising stream surfaces
Barton, Michael
2015-05-01
We study the problem of finding stretch-minimising stream surfaces in a divergence-free vector field. These surfaces are generated by motions of seed curves that propagate through the field in a stretch minimising manner, i.e., they move without stretching or shrinking, preserving the length of their arbitrary arc. In general fields, such curves may not exist. How-ever, the divergence-free constraint gives rise to these \\'stretch-free\\' curves that are locally arc-length preserving when infinitesimally propagated. Several families of stretch-free curves are identified and used as initial guesses for stream surface generation. These surfaces are subsequently globally optimised to obtain the best stretch-minimising stream surfaces in a given divergence-free vector field. Our algorithm was tested on benchmark datasets, proving its applicability to incompressible fluid flow simulations, where our stretch-minimising stream surfaces realistically reflect the flow of a flexible univariate object. © 2015 Elsevier Inc. All rights reserved.
Modeling and clustering users with evolving profiles in usage streams
Zhang, Chongsheng
2012-09-01
Today, there is an increasing need of data stream mining technology to discover important patterns on the fly. Existing data stream models and algorithms commonly assume that users\\' records or profiles in data streams will not be updated or revised once they arrive. Nevertheless, in various applications such asWeb usage, the records/profiles of the users can evolve along time. This kind of streaming data evolves in two forms, the streaming of tuples or transactions as in the case of traditional data streams, and more importantly, the evolving of user records/profiles inside the streams. Such data streams bring difficulties on modeling and clustering for exploring users\\' behaviors. In this paper, we propose three models to summarize this kind of data streams, which are the batch model, the Evolving Objects (EO) model and the Dynamic Data Stream (DDS) model. Through creating, updating and deleting user profiles, these models summarize the behaviors of each user as a profile object. Based upon these models, clustering algorithms are employed to discover interesting user groups from the profile objects. We have evaluated all the proposed models on a large real-world data set, showing that the DDS model summarizes the data streams with evolving tuples more efficiently and effectively, and provides better basis for clustering users than the other two models. © 2012 IEEE.
Markham, Annette
layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also......This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....
Brax, Philippe
2015-01-01
We extend the chameleon models by considering Scalar-Fluid theories where the coupling between matter and the scalar field can be represented by a quadratic effective potential with density-dependent minimum and mass. In this context, we study the effects of the scalar field on Solar System tests of gravity and show that models passing these stringent constraints can still induce large modifications of Newton's law on galactic scales. On these scales we analyse models which could lead to a percent deviation of Newton's law outside the virial radius. We then model the dark matter halo as a Navarro-Frenk-White profile and explicitly find that the fifth force can give large contributions around the galactic core in a particular model where the scalar field mass is constant and the minimum of its potential varies linearly with the matter density. At cosmological distances, we find that this model does not alter the growth of large scale structures and therefore would be best tested on galactic scales, where inter...
Federated Stream Processing Support for Real-Time Business Intelligence Applications
Botan, Irina; Cho, Younggoo; Derakhshan, Roozbeh; Dindar, Nihal; Haas, Laura; Kim, Kihong; Tatbul, Nesime
In this paper, we describe the MaxStream federated stream processing architecture to support real-time business intelligence applications. MaxStream builds on and extends the SAP MaxDB relational database system in order to provide a federator over multiple underlying stream processing engines and databases. We show preliminary results on usefulness and performance of the MaxStream architecture on the SAP Sales and Distribution Benchmark.
AMIDST: Analysis of MassIve Data STreams
Masegosa, Andres; Martinez, Ana Maria; Borchani, Hanen
2015-01-01
The Analysis of MassIve Data STreams (AMIDST) Java toolbox provides a collection of scalable and parallel algorithms for inference and learning of hybrid Bayesian networks from data streams. The toolbox, available at http://amidst.github.io/toolbox/ under the Apache Software License version 2...
Mining Building Metadata by Data Stream Comparison
Holmegaard, Emil; Kjærgaard, Mikkel Baun
2016-01-01
to handle data streams with only slightly similar patterns. We have evaluated Metafier with points and data from one building located in Denmark. We have evaluated Metafier with 903 points, and the overall accuracy, with only 3 known examples, was 94.71%. Furthermore we found that using DTW for mining...... ways to annotate sensor and actuation points. This makes it difficult to create intuitive queries for retrieving data streams from points. Another problem is the amount of insufficient or missing metadata. We introduce Metafier, a tool for extracting metadata from comparing data streams. Metafier...... enables a semi-automatic labeling of metadata to building instrumentation. Metafier annotates points with metadata by comparing the data from a set of validated points with unvalidated points. Metafier has three different algorithms to compare points with based on their data. The three algorithms...
Mining Building Metadata by Data Stream Comparison
Holmegaard, Emil; Kjærgaard, Mikkel Baun
2017-01-01
to handle data streams with only slightly similar patterns. We have evaluated Metafier with points and data from one building located in Denmark. We have evaluated Metafier with 903 points, and the overall accuracy, with only 3 known examples, was 94.71%. Furthermore we found that using DTW for mining...... ways to annotate sensor and actuation points. This makes it difficult to create intuitive queries for retrieving data streams from points. Another problem is the amount of insufficient or missing metadata. We introduce Metafier, a tool for extracting metadata from comparing data streams. Metafier...... enables a semi-automatic labeling of metadata to building instrumentation. Metafier annotates points with metadata by comparing the data from a set of validated points with unvalidated points. Metafier has three different algorithms to compare points with based on their data. The three algorithms...
Self-Adaptive Anytime Stream Clustering
Kranen, Philipp; Assent, Ira; Baldauf, Corinna
2009-01-01
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited. Clustering has to be performed in a single pass over the incoming data and within the possibly varying inter......-arrival times of the stream. Likewise, memory is limited, making it impossible to store all data. For clustering, we are faced with the challenge of maintaining a current result that can be presented to the user at any given time. In this work, we propose a parameter free algorithm that automatically adapts...... to the speed of the data stream. It makes best use of the time available under the current constraints to provide a clustering of the objects seen up to that point. Our approach incorporates the age of the objects to reflect the greater importance of more recent data. Moreover, we are capable of detecting...
Temporal Segmentation of MPEG Video Streams
Janko Calic
2002-06-01
Full Text Available Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.
Multi-core Architectures and Streaming Applications
Smit, Gerard J.M.; Kokkeler, André B.J.; Wolkotte, Pascal T.; Burgwal, van de Marcel D.; Mandoiu, I.; Kennings, A.
2008-01-01
In this paper we focus on algorithms and reconfigurable multi-core architectures for streaming digital signal processing (DSP) applications. The multi-core concept has a number of advantages: (1) depending on the requirements more or fewer cores can be switched on/off, (2) the multi-core structure f
Fine-Grained Rate Shaping for Video Streaming over Wireless Networks
Chen Tsuhan
2004-01-01
Full Text Available Video streaming over wireless networks faces challenges of time-varying packet loss rate and fluctuating bandwidth. In this paper, we focus on streaming precoded video that is both source and channel coded. Dynamic rate shaping has been proposed to shape the precompressed video to adapt to the fluctuating bandwidth. In our earlier work, rate shaping was extended to shape the channel coded precompressed video, and to take into account the time-varying packet loss rate as well as the fluctuating bandwidth of the wireless networks. However, prior work on rate shaping can only adjust the rate oarsely. In this paper, we propose fine-grained rate shaping (FGRS to allow for bandwidth adaptation over a wide range of bandwidth and packet loss rate in fine granularities. The video is precoded with fine granularity scalability (FGS followed by channel coding. Utilizing the fine granularity property of FGS and channel coding, FGRS selectively drops part of the precoded video and still yields decodable bit-stream at the decoder. Moreover, FGRS optimizes video streaming rather than achieves heuristic objectives as conventional methods. A two-stage rate-distortion (RD optimization algorithm is proposed for FGRS. Promising results of FGRS are shown.
Prioritized Contact Transport Stream
Hunt, Walter Lee, Jr. (Inventor)
2015-01-01
A detection process, contact recognition process, classification process, and identification process are applied to raw sensor data to produce an identified contact record set containing one or more identified contact records. A prioritization process is applied to the identified contact record set to assign a contact priority to each contact record in the identified contact record set. Data are removed from the contact records in the identified contact record set based on the contact priorities assigned to those contact records. A first contact stream is produced from the resulting contact records. The first contact stream is streamed in a contact transport stream. The contact transport stream may include and stream additional contact streams. The contact transport stream may be varied dynamically over time based on parameters such as available bandwidth, contact priority, presence/absence of contacts, system state, and configuration parameters.
U.S. Environmental Protection Agency — The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the...
姚玲玲; 张霄宇; 江彬彬
2016-01-01
针对静止海洋水色传感器（GOCI）2．1μm 短波红外通道缺失和高太阳天顶角的特点，采用二流式算法，并考虑气溶胶的折射率、地球曲率等因素，重新计算地表反射率、表观反射率以及反演 GOCI 气溶胶光学厚度（AOT ）．结果表明：参数重新计算后的 GOCI＼AOT 反演精度明显增高；根据目前广泛使用的实测 AOT （440 nm）＞1．00霾判定阈值，采用线性内插方法，建议 GOCI＼AOT 以 AOT （555 nm）＞0．81作为霾判定阈值；中分辨率成像光谱仪（MODIS）是业务化的极轨卫星，GOCI＼AOT 整体略大于 MODIS ＼AOT ，拟合精度 R2＝0．82．以2015年11月27日至同年12月2日华北地区发生的霾事件为例，结合具有大范围观测能力的 MODIS 卫星，多源遥感监测方法有效地反映了该霾事件的动态发展过程．%Aerosol optical thickness (AOT ) of geostationary ocean color imager (GOCI ) was retrieved based on the two-stream approximate algorithm considering aerosol refractive index and earth curvature and other causations ,aiming at the lackage of 2 .1 μm short wave infrared band and the high solar zenith angle of GOCI . As specified , the retrieval precision of GOCI \\AOT gets improved after parameters recalculation .According to the widely used groundbase haze threshold of AOT (440 nm) > 1 .00 ,GOCI\\AOT (555 nm) > 0 .81 is proposed as the haze determination threshold based on the linear interpolation method . Moderate resolution imaging spectroradiometer (MODIS ) is an operational polar orbiting satellite ,GOCI \\AOT is slightly higher than MODIS \\AOT with R2 of 0 .82 . The haze event from November 27 to December 2 ,2015 was selected as one case and MODIS satellite was combined to realize real-time dynamic monitoring of haze events over North China ,which indicates that the multi satellites remote sensing monitoring method can reflect the dynamic process of haze event effectively .
A dynamically reconfigurable data stream processing system
Nogiec, J.M.; Trombly-Freytag, K.; /Fermilab
2004-11-01
This paper describes a component-based framework for data stream processing that allows for configuration, tailoring, and runtime system reconfiguration. The system's architecture is based on a pipes and filters pattern, where data is passed through routes between components. A network of pipes and filters can be dynamically reconfigured in response to a preplanned sequence of processing steps, operator intervention, or a change in one or more data streams. This framework provides several mechanisms supporting dynamic reconfiguration and can be used to build static data stream processing applications such as monitoring or data acquisition systems, as well as self-adjusting systems that can adapt their processing algorithm, presentation layer, or data persistency layer in response to changes in input data streams.
Can dust coagulation trigger streaming instability?
Drazkowska, Joanna
2014-01-01
Streaming instability can be a very efficient way of overcoming growth and drift barriers to planetesimal formation. However, it was shown that strong clumping, which leads to planetesimal formation, requires a considerable number of large grains. State-of-the-art streaming instability models do not take into account realistic size distributions resulting from the collisional evolution of dust. We investigate whether a sufficient quantity of large aggregates can be produced by sticking and what the interplay of dust coagulation and planetesimal formation is. We develop a semi-analytical prescription of planetesimal formation by streaming instability and implement it in our dust coagulation code based on the Monte Carlo algorithm with the representative particles approach. We find that planetesimal formation by streaming instability may preferentially work outside the snow line, where sticky icy aggregates are present. The efficiency of the process depends strongly on local dust abundance and radial pressure g...
2013-10-03
This package assists in genome assembly. extendFromReads takes as input a set of Illumina (eg, MiSeq) DNA sequencing reads, a query seed sequence and a direction to extend the seed. The algorithm collects all seed--]matching reads (flipping reverse--]orientation hits), trims off the seed and additional sequence in the other direction, sorts the remaining sequences alphabetically, and prints them aligned without gaps from the point of seed trimming. This produces a visual display distinguishing the flanks of multi-]copy seeds. A companion script hitMates.pl collects the mates of seed--]hi]ng reads, whose alignment reveals longer extensions from the seed. The collect/trim/sort strategy was made iterative and scaled up in the script denovo.pl, for de novo contig assembly. An index is pre--]built using indexReads.pl that for each unique 21--]mer found in all the reads, records its gfateh of extension (whether extendable, blocked by low coverage, or blocked by branching after a duplicated sequence) and other characteristics. Importantly, denovo.pl records all branchings that follow a branching contig endpoint, providing contig-]extension information
Dynamical Modelling of Meteoroid Streams
Clark, David; Wiegert, P. A.
2012-10-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required questionable assumptions and significant simplifications. Extending on the approach of Vaubaillon et al. (2005)1, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of frequency based on model parameter changes. To assist in model analysis we are developing interactive software to permit the “turning of knobs” of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. With this tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity. The software uses a single model definition and implementation throughout model verification, sample particle bin generation and integration, and analysis. It supports the adjustment with feedback of both independent and independent model values, with the intent of providing an interface supporting multivariate analysis. Propagations of measurement uncertainties and model parameter precisions are tracked rigorously throughout. We maintain a separation of the model itself from the abstract concepts of model definition, parameter manipulation, and real-time analysis and visualization. Therefore we are able to quickly adapt to fundamental model changes. It is hoped the tool will also be of use in other solar system dynamics problems. 1 Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. Astronomy and
Joint Stream-Wise THP Transceiver Design for the Multiuser MIMO Downlink
Miao, Wei; Chen, Xiang; Zhao, Ming; Zhou, Shidong; Wang, Jing
This paper addresses the problem of joint transceiver design for Tomlinson-Harashima Precoding (THP) in the multiuser multiple-input-multiple-output (MIMO) downlink under both perfect and imperfect channel state information at the transmitter (CSIT). For the case of perfect CSIT, we differ from the previous work by performing stream-wise (both inter-user and intra-user) interference pre-cancelation at the transmitter. A minimum total mean square error (MT-MSE) criterion is used to formulate our optimization problem. By some convex analysis of the problem, we obtain the necessary conditions for the optimal solution. An iterative algorithm is proposed to handle this problem and its convergence is proved. Then we extend our designed algorithm to the robust version by minimizing the conditional expectation of the T-MSE under imperfect CSIT. Simulation results are given to verify the efficacy of our proposed schemes and to show their superiorities over existing MMSE-based THP schemes.
Logistic Regression for Evolving Data Streams Classification
YIN Zhi-wu; HUANG Shang-teng; XUE Gui-rong
2007-01-01
Logistic regression is a fast classifier and can achieve higher accuracy on small training data. Moreover,it can work on both discrete and continuous attributes with nonlinear patterns. Based on these properties of logistic regression, this paper proposed an algorithm, called evolutionary logistical regression classifier (ELRClass), to solve the classification of evolving data streams. This algorithm applies logistic regression repeatedly to a sliding window of samples in order to update the existing classifier, to keep this classifier if its performance is deteriorated by the reason of bursting noise, or to construct a new classifier if a major concept drift is detected. The intensive experimental results demonstrate the effectiveness of this algorithm.
An extended grammar system for learning and recognizing complex visual events.
Zhang, Zhang; Tan, Tieniu; Huang, Kaiqi
2011-02-01
For a grammar-based approach to the recognition of visual events, there are two major limitations that prevent it from real application. One is that the event rules are predefined by domain experts, which means huge manual cost. The other is that the commonly used grammar can only handle sequential relations between subevents, which is inadequate to recognize more complex events involving parallel subevents. To solve these problems, we propose an extended grammar approach to modeling and recognizing complex visual events. First, motion trajectories as original features are transformed into a set of basic motion patterns of a single moving object, namely, primitives (terminals) in the grammar system. Then, a Minimum Description Length (MDL) based rule induction algorithm is performed to discover the hidden temporal structures in primitive stream, where Stochastic Context-Free Grammar (SCFG) is extended by Allen's temporal logic to model the complex temporal relations between subevents. Finally, a Multithread Parsing (MTP) algorithm is adopted to recognize interesting complex events in a given primitive stream, where a Viterbi-like error recovery strategy is also proposed to handle large-scale errors, e.g., insertion and deletion errors. Extensive experiments, including gymnastic exercises, traffic light events, and multi-agent interactions, have been executed to validate the effectiveness of the proposed approach.
黄坤; 韩飞; 杨月全; 王正群; 张天平
2012-01-01
首先给出了通过矩形块与三角像素特征块相结合所构造的八种用于眼睛检测的扩展三角特征原型块．考虑扫描块在人脸背景中遍历时眼睛样本图像块数量远少于非眼睛样本块数的实际，提出了一种结合Haar特征和三角特征的AdaBoost快速眼睛检测算法．通过级联分类器的前几层强分类器完成排除大部分非眼睛样本；然后，通过后续强分类器进行判断大部分的眼睛图像块和少量非眼睛图像块．检测时间消耗有所下降，这样可以保证整体的检测速度．实验结果进一步表明该算法具有更好的检测性能，与仅使用Haar特征相比正检率有一定程度提高．%Eight extended feature prototypes were presented by combining rectangular feature blocks and triangular feature blocks. In consideration of the fact that the amount of eye image blocks is far less than that of non-eye image blocks during a scanning block passing through face images, a fast eye location detection scheme based on AdaBoost algorithm combining rectangular feature blocks and triangular feature blocks was proposed. After most of non-eye blocks are excluded through the foregoing strong classifiers, most eye image blocks and a few of non-eye image blocks are detected through the rear parts of the cascade classifier, which can reduce the detection time and boost the detection speed. The experiments further show that the scheme has better detection performance and positive detection rate compared to the case only employed Haar features.
Hilley, David; Ramachandran, Umakishore
Distributed continuous live stream analysis applications are increasingly common. Video-based surveillance, emergency response, disaster recovery, and critical infrastructure protection are all examples of such applications. They are characterized by a variety of high- and low-bandwidth streams as well as a need for analyzing both live and archived streams. We present a system called Persistent Temporal Streams (PTS) that supports a higher-level, domain-targeted programming abstraction for such applications. PTS provides a simple but expressive stream abstraction encompassing transport, manipulation and storage of streaming data. In this paper, we present a system architecture for implementing PTS. We provide an experimental evaluation which shows the system-level primitives can be implemented in a lightweight and high-performance manner, and an application-based evaluation designed to show that a representative high-bandwidth stream analysis application can be implemented relatively simply and with good performance.
Entropy Message Passing Algorithm
Ilic, Velimir M; Branimir, Todorovic T
2009-01-01
Message passing over factor graph can be considered as generalization of many well known algorithms for efficient marginalization of multivariate function. A specific instance of the algorithm is obtained by choosing an appropriate commutative semiring for the range of the function to be marginalized. Some examples are Viterbi algorithm, obtained on max-product semiring and forward-backward algorithm obtained on sum-product semiring. In this paper, Entropy Message Passing algorithm (EMP) is developed. It operates over entropy semiring, previously introduced in automata theory. It is shown how EMP extends the use of message passing over factor graphs to probabilistic model algorithms such as Expectation Maximization algorithm, gradient methods and computation of model entropy, unifying the work of different authors.
Mining Frequent Itemsets from Online Data Streams: Comparative Study
HebaTallah Mohamed Nabil
2013-08-01
Full Text Available Online mining of data streams poses many new challenges more than mining static databases. In addition to the one-scan nature, the unbounded memory requirement, the high data arrival rate of data streams and the combinatorial explosion of itemsets exacerbate the mining task. The high complexity of the frequent itemsets mining problem hinders the application of the stream mining techniques. In this review, we present a comparative study among almost all, as we are acquainted, the algorithms for mining frequent itemsets from online data streams. All those techniques immolate with the accuracy of the results due to the relatively limited storage, leading, at all times, to approximated results.
Stream Temperature Estimation From Thermal Infrared Images
Handcock, R. N.; Kay, J. E.; Gillespie, A.; Naveh, N.; Cherkauer, K. A.; Burges, S. J.; Booth, D. B.
2001-12-01
data for atmospheric effects we combine radiosonde profiles with a physically based radiative transfer model (MODTRAN) and an in-scene relative correction adapted from the ISAC algorithm. Laboratory values for water emissivities are used as a baseline estimate of stream emissivities. Emitted radiance reflected by trees in the stream near-bank environment is estimated from the height and canopy temperature, using a radiosity model.
Schedule-extended synchronous dataflow graphs
Damavandpeyma, M.; Stuijk, S.; Basten, T.; Geilen, M.; Corporaal, H.
2013-01-01
Synchronous dataflow graphs (SDFGs) are used extensively to model streaming applications. An SDFG can be extended with scheduling decisions, allowing SDFG analysis to obtain properties, such as throughput or buffer sizes for the scheduled graphs. Analysis times depend strongly on the size of the
Computation of unirational fields (extended abstract)
Gutierrez, Jaime
2008-01-01
In this paper we present an algorithm for computing all algebraic intermediate subfields in a separably generated unirational field extension (which in particular includes the zero characteristic case). One of the main tools is Groebner bases theory. Our algorithm also requires computing computing primitive elements and factoring over algebraic extensions. Moreover, the method can be extended to finitely generated K-algebras.
Q-Method Extended Kalman Filter
Zanetti, Renato; Ainscough, Thomas; Christian, John; Spanos, Pol D.
2012-01-01
A new algorithm is proposed that smoothly integrates non-linear estimation of the attitude quaternion using Davenport s q-method and estimation of non-attitude states through an extended Kalman filter. The new method is compared to a similar existing algorithm showing its similarities and differences. The validity of the proposed approach is confirmed through numerical simulations.
Kohler, Susanna
2016-01-01
Dwarf galaxies or globular clusters orbiting the Milky Way can be pulled apart by tidal forces, leaving behind a trail of stars known as a stellar stream. One such trail, the Ophiuchus stream, has posed a serious dynamical puzzle since its discovery. But a recent study has identified four stars that might help resolve this streams mystery.Conflicting TimescalesThe stellar stream Ophiuchus was discovered around our galaxy in 2014. Based on its length, which appears to be 1.6 kpc, we can calculate the time that has passed since its progenitor was disrupted and the stream was created: ~250 Myr. But the stars within it are ~12 Gyr old, and the stream orbits the galaxy with a period of ~350 Myr.Given these numbers, we can assume that Ophiuchuss progenitor completed many orbits of the Milky Way in its lifetime. So why would it only have been disrupted 250 million years ago?Fanning StreamLed by Branimir Sesar (Max Planck Institute for Astronomy), a team of scientists has proposed an idea that might help solve this puzzle. If the Ophiuchus stellar stream is on a chaotic orbit common in triaxial potentials, which the Milky Ways may be then the stream ends can fan out, with stars spreading in position and velocity.The fanned part of the stream, however, would be difficult to detect because of its low surface brightness. As a result, the Ophiuchus stellar stream could actually be longer than originally measured, implying that it was disrupted longer ago than was believed.Search for Fan StarsTo test this idea, Sesar and collaborators performed a search around the ends of the stream, looking for stars thatare of the right type to match the stream,are at the predicted distance of the stream,are located near the stream ends, andhave velocities that match the stream and dont match the background halo stars.Histogram of the heliocentric velocities of the 43 target stars. Six stars have velocities matching the stream velocity. Two of these are located in the main stream; the other
胡云云; 肖武; 贺高红
2012-01-01
the design of plate-fin heat exchanger. In the traditional plate-fin heat exchanger design, the passage arrangement is usually designed at a single maximum load operation point, which ignores the impact of heat transfer when the operation point changes very much. But in fact the operation conditions change along with seasons, raw materials and production circumstances, which usually lows the plate-fin heat exchanger's heat transfer when it works at these operation points. The number of the passage arrangement increases exponentially with the increase of fluid number in the plate-fin heat exchanger, so the passage arrangement is determined according to the experiential rule, which needs designers spend a lot of time in repeatedly improving the heat exchanger's passage arrangement to comply with the design requirements, and achieve superior heat transfer effect. To overcome this shortcoming, a novel flexible design method was presented in the paper based on flexible design of passage arrangement for multi-stream plate-fin heat exchanger in various conditions. The objective function was the minimum mean-square deviation of accumulative heat load of the passage arrangement, and genetic algorithm (GA) was adopted to attain the optimal passage arrangement. Specific steps: 1) GA was used to achieve the best passage arrangement at every operation point; 2) Flexible design was used to combine the different best passage arrangements to get flexible design passage arrangement which can worked well at all operation points; 3) Fine-tuning strategy was used to improve flexible design channel arrangement to get the final optimal passage arrangement by reducing the mean-square deviation of accumulative heat load. Finally an illustrative example was presented to demonstrate the validity and advantages of the proposed approach, the final passage arrangement's average mean-square deviation of accumulative heat load of three different operation points was 3632.48 W, which was lower than
A Stellar Stream Surrounds the Whale Galaxy
Kohler, Susanna
2015-10-01
The -cold dark matter cosmological model predicts that galaxies are assembled through the disruption and absorption of small satellite dwarf galaxies by their larger hosts. A recent study argues that NGC 4631, otherwise known as the Whale galaxy, shows evidence of such a recent merger in the form of an enormous stellar stream extending from it.Stream SignaturesAccording to the -CDM model, stellar tidal streams should be a ubiquitous feature among galaxies. When satellite dwarf galaxies are torn apart, they spread out into such streams before ultimately feeding the host galaxy. Unfortunately, these streams are very faint, so were only recently starting to detect these features.Stellar tidal streams have been discovered around the Milky Way and Andromeda, providing evidence of these galaxies growth via recent (within the last 8 Gyr) mergers. But discovering stellar streams around other Milky Way-like galaxies would help us to determine if the model of hierarchical galaxy assembly applies generally.To this end, the Stellar Tidal Stream Survey, led by PI David Martnez-Delgado (Center for Astronomy of Heidelberg University), is carrying out the first systematic survey of stellar tidal streams. In a recent study, Martnez-Delgado and collaborators present their detection of a giant (85 kpc long!) stellar tidal stream extending into the halo of NGC 4631, the Whale galaxy.Modeling a SatelliteThe top image is a snapshot from an N-body simulation of a single dwarf satellite, 3.5 Gyr after it started interacting with the Whale galaxy. The satellite has been torn apart and spread into a stream that reproduces observations, which are shown in the lower image (scale is not the same). [Martnez-Delgado et al. 2015]The Whale galaxy is a nearby edge-on spiral galaxy interacting with a second spiral, NGC 4656. But the authors dont believe that the Whale galaxys giant tidal stellar stream is caused by its interactions with NGC 4656. Instead, based on their observations, they believe
Constrained Stochastic Extended Redundancy Analysis.
DeSarbo, Wayne S; Hwang, Heungsun; Stadler Blank, Ashley; Kappe, Eelco
2015-06-01
We devise a new statistical methodology called constrained stochastic extended redundancy analysis (CSERA) to examine the comparative impact of various conceptual factors, or drivers, as well as the specific predictor variables that contribute to each driver on designated dependent variable(s). The technical details of the proposed methodology, the maximum likelihood estimation algorithm, and model selection heuristics are discussed. A sports marketing consumer psychology application is provided in a Major League Baseball (MLB) context where the effects of six conceptual drivers of game attendance and their defining predictor variables are estimated. Results compare favorably to those obtained using traditional extended redundancy analysis (ERA).
Rehan, Waqas; Fischer, Stefan; Rehan, Maaz
2016-01-01
, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC) outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption) for accommodating stream-based communication in multichannel WSNs. PMID:27626429
Waqas Rehan
2016-09-01
. In the end, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption for accommodating stream-based communication in multichannel WSNs.
Rehan, Waqas; Fischer, Stefan; Rehan, Maaz
2016-09-12
, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC) outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption) for accommodating stream-based communication in multichannel WSNs.
Lewis, G F; Ferguson, A M N; Ibata, R A; Irwin, M J; McConnachie, A W; Tanvir, N
2004-01-01
The existence of a stream of tidally stripped stars from the Sagittarius Dwarf galaxy demonstrates that the Milky Way is still in the process of accreting mass. More recently, an extensive stream of stars has been uncovered in the halo of the Andromeda galaxy (M31), revealing that it too is cannibalizing a small companion. This paper reports the recent observations of this stream, determining it spatial and kinematic properties, and tracing its three-dimensional structure, as well as describing future observations and what we may learn about the Andromeda galaxy from this giant tidal stream.
Hydrography - Streams and Shorelines
California Department of Resources — The hydrography layer consists of flowing waters (rivers and streams), standing waters (lakes and ponds), and wetlands -- both natural and manmade. Two separate...
Natalia Mironova
2014-01-01
.... Cassidy, the safety coordinator at the Airline Pilots Association, says Levine and others advocating for live data streaming are oversimplifying the issue and overlooking the logistical concerns...
Inventory of miscellaneous streams
Lueck, K.J.
1995-09-01
On December 23, 1991, the US Department of Energy, Richland Operations Office (RL) and the Washington State Department of Ecology (Ecology) agreed to adhere to the provisions of the Department of Ecology Consent Order. The Consent Order lists the regulatory milestones for liquid effluent streams at the Hanford Site to comply with the permitting requirements of Washington Administrative Code. The RL provided the US Congress a Plan and Schedule to discontinue disposal of contaminated liquid effluent into the soil column on the Hanford Site. The plan and schedule document contained a strategy for the implementation of alternative treatment and disposal systems. This strategy included prioritizing the streams into two phases. The Phase 1 streams were considered to be higher priority than the Phase 2 streams. The actions recommended for the Phase 1 and 2 streams in the two reports were incorporated in the Hanford Federal Facility Agreement and Consent Order. Miscellaneous Streams are those liquid effluents streams identified within the Consent Order that are discharged to the ground but are not categorized as Phase 1 or Phase 2 Streams. This document consists of an inventory of the liquid effluent streams being discharged into the Hanford soil column.
The Magellanic Stream: Circumnavigating the Galaxy
D'Onghia, Elena; Fox, Andrew J.
2016-09-01
The Magellanic Clouds are surrounded by an extended network of gaseous structures. Chief among these is the Magellanic Stream, an interwoven tail of filaments trailing the Clouds in their orbit around the Milky Way. When considered in tandem with its Leading Arm, the Stream stretches over 200° on the sky. The Stream is thought to represent the result of tidal interactions between the Clouds and ram-pressure forces exerted by the Galactic corona, and its kinematic properties reflect the dynamical history of the pair of dwarf galaxies closest to the Milky Way. The Stream is a benchmark for hydrodynamical simulations of accreting gas and cloud/corona interactions. If the Stream survives these interactions and arrives safely in the Galactic disk, its cargo of over a billion solar masses of gas has the potential to maintain or elevate the Galactic star-formation rate. In this article, we review the current state of knowledge of the Stream, including its chemical composition, physical conditions, origin, and fate. We also review the dynamics of the Magellanic System, including the proper motions and orbital history of the Large and Small Magellanic Clouds, the first-passage and second-passage scenarios, and the evidence for a Magellanic Group of galaxies.
An Extended Particle Swarm Optimizer
XU Jun-jie; XIN Zhan-hong
2005-01-01
An Extended Particle Swarm Optimizer (EPSO) is proposed in this paper. In this new algorithm, not only the local but also the global best position will impact the particle's velocity updating process. EPSO is an integration of Local Best paradigm (LBEST) and Global Best paradigm (GBEST) and it significantly enhances the performance of the conventional particle swarm optimizers. The experiment results have proved that EPSO deserves to be investigated.
A unified self-stabilizing neural network algorithm for principal and minor components extraction.
Kong, Xiangyu; Hu, Changhua; Ma, Hongguang; Han, Chongzhao
2012-02-01
Recently, many unified learning algorithms have been developed for principal component analysis and minor component analysis. These unified algorithms can be used to extract principal components and, if altered simply by the sign, can also serve as a minor component extractor. This is of practical significance in the implementations of algorithms. This paper proposes a unified self-stabilizing neural network learning algorithm for principal and minor components extraction, and studies the stability of the proposed unified algorithm via the fixed-point analysis method. The proposed unified self-stabilizing algorithm for principal and minor components extraction is extended for tracking the principal subspace (PS) and minor subspace (MS). The averaging differential equation and the energy function associated with the unified algorithm for tracking PS and MS are given. It is shown that the averaging differential equation will globally asymptotically converge to an invariance set, and the corresponding energy function exhibit a unique global minimum attained if and only if its state matrices span the PS or MS of the autocorrelation matrix of a vector data stream. It is concluded that the proposed unified algorithm for tracking PS and MS can efficiently track an orthonormal basis of the PS or MS. Simulations are carried out to further illustrate the theoretical results achieved.
Labeling algorithm and its fairness analysis for autonomous system
Han Guodong; Wang Hui; Wu Jiangxing
2005-01-01
A kind of packet labeling algorithm for autonomous system is introduced. The fairness of the algorithm for each traffic stream in the integrated-services is analyzed. It is shown that the rate of each stream in the integrated-services would converge to a stable value if the transmitting or forwarding rates converge to that of the receiving exponentially.
Løgstrup Bjerg, Poul; Sonne, Anne T.; Rønde, Vinni; McKnight, Ursula S.
2016-04-01
elevated concentrations of chlorinated ethenes, benzene and site specific pharmaceuticals in both the hyporheic zone and the stream water. Observed stream water vinyl chloride concentrations (up to 6 μg/L) are far above the Danish EQS (0.05 μg/L) for several km downstream of the discharge area. For heavy metals, comparison with EQS in stream water, the hyporheic zone and streambed showed concentrations around or above the threshold values for barium, copper, lead, nickel and zinc. The calculated TU was generally similar along the stream, but for arsenic and nickel higher values were observed where the groundwater plume discharges into the stream. Also, log TU sum values for organic contaminants were elevated in both the hyporheic zone and stream. Thus, the overall chemical stress in the main discharge area is much higher than upstream, while it gradually decreases downstream. In conclusion, this work clearly shows that groundwater contaminant plumes can impact stream water quality significantly in discharge areas, and extend far downstream. A surprisingly high impact of heavy metals with diffuse and/or biogenic origin on stream quality was identified. This work highlights the importance of a holistic assessment of stream water quality to identify and quantify the main contaminant sources and resulting chemical stream stressors leading to potential ecological impacts.
Learning Extended Finite State Machines
Cassel, Sofia; Howar, Falk; Jonsson, Bengt; Steffen, Bernhard
2014-01-01
We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior. Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.
Efficient iterative adaptive pole placement algorithm
李俊民; 李靖; 杨磊
2004-01-01
An iterative adaptive pole placement algorithm is presented. The stability and the convergence of the algorithm are respectively established. Since one-step iterative formulation in computing controller's parameters is used, the on-line computation cost is greatly reduced with respected to the traditional algorithm. The algorithm with the feed-forward can follow arbitrarily bounded output. The algorithm is also extended to multivariate case. Simulation examples show the efficiency and robustness of the algorithm.
钟敏; 张凯; 黄湘宁; 殷琳; 刘鑫; 喻华; 黄文芳; 唐荣珍; 奉婷
2016-01-01
Objective To investigate the incidences, risk factors, genotypes and epidemiology of community-acquired blood stream infection caused by extended spectrum β-lactamases (ESBLs)-producing Escherichia coli and Klebsiella pneumonia strains and to analyze the sensitivity of those ESBLs producing strains to commonly used antibiotics. Methods Forty-two patients who were diagnosed with community-ac-quired blood stream infection caused by Escherichia coli or Klebsiella pneumonia strains in Sichuan Provincial People′s Hospital were recruited in this study. Disc diffusion method was used for the phenotypic confirmato-ry test of ESBLs. Agar dilution method was performed to measure the antimicrobial susceptibility of the ESBLs-producing strains to 13 clinically commonly used antibiotics. Genotypes of the ESBLs-producing strains were identified by polymerase chain reaction (PCR). Multilocus sequence typing (MLST) was used to analyze the epidemiology of ESBLs-producing strains. Logistic regression analysis was performed to analyze the risk factors for community-acquired blood stream infection. Results The ESBLs-producing Escherichia coli strains accounted for 56. 3% (18 / 32) and the ESBLs-producing Klebsiella pneumoniae strains accounted for 20% (2 / 10). All of the 20 ESBLs-producing strains were sensitive to imipenem, meropenem, ertapen-em, nitrofurantoin and moxalactam. The ESBLs-producing strains sensitive to amikacin, piperacillin-tazobactam and fosfomycin accounted for 95% , 90% and 85% , respectively. Drug resistance rates of the 20 strains to cefotaxime, levofloxacin, ciprofloxacin and cefepime were relatively high accounting for 100% , 80% , 80% and 75% , respectively. Among the 20 ESBLs-producing strains, 7 strains only carried the CTM gene, while the other 13 strains were all positive for two genotypes of ESBLs, mainly identified as TEM+CTM-M-14 and TEM+CTM-15 genotypes. The 18 Escherichia coli strains were classified into 10 ST types, most of which were ST131
Simon Fong
2013-01-01
Full Text Available Earlier on, a conceptual design on the real-time clinical decision support system (rt-CDSS with data stream mining was proposed and published. The new system is introduced that can analyze medical data streams and can make real-time prediction. This system is based on a stream mining algorithm called VFDT. The VFDT is extended with the capability of using pointers to allow the decision tree to remember the mapping relationship between leaf nodes and the history records. In this paper, which is a sequel to the rt-CDSS design, several popular machine learning algorithms are investigated for their suitability to be a candidate in the implementation of classifier at the rt-CDSS. A classifier essentially needs to accurately map the events inputted to the system into one of the several predefined classes of assessments, such that the rt-CDSS can follow up with the prescribed remedies being recommended to the clinicians. For a real-time system like rt-CDSS, the major technological challenges lie in the capability of the classifier to process, analyze and classify the dynamic input data, quickly and upmost reliably. An experimental comparison is conducted. This paper contributes to the insight of choosing and embedding a stream mining classifier into rt-CDSS with a case study of diabetes therapy.
Nonlinear projective filtering in a data stream
Schreiber, T; Schreiber, Thomas; Richter, Marcus
1998-01-01
We introduce a modified algorithm to perform nonlinear filtering of a time series by locally linear phase space projections. Unlike previous implementations, the algorithm can be used not only for a posteriori processing but includes the possibility to perform real time filtering in a data stream. The data base that represents the phase space structure generated by the data is updated dynamically. This also allows filtering of non-stationary signals and dynamic parameter adjustment. We discuss exemplary applications, including the real time extraction of the fetal electrocardiogram from abdominal recordings.
Percent Agriculture Adjacent to Streams
U.S. Environmental Protection Agency — The type of vegetation along a stream influences the water quality in the stream. Intact buffer strips of natural vegetation along streams tend to intercept...
Percent Forest Adjacent to Streams
U.S. Environmental Protection Agency — The type of vegetation along a stream influences the water quality in the stream. Intact buffer strips of natural vegetation along streams tend to intercept...
A Formalization and Proof of the Extended Church-Turing Thesis -Extended Abstract-
Nachum Dershowitz
2012-07-01
Full Text Available We prove the Extended Church-Turing Thesis: Every effective algorithm can be efficiently simulated by a Turing machine. This is accomplished by emulating an effective algorithm via an abstract state machine, and simulating such an abstract state machine by a random access machine, representing data as a minimal term graph.
A Streaming Language Implementation of the Discontinuous Galerkin Method
Barth, Timothy; Knight, Timothy
2005-01-01
We present a Brook streaming language implementation of the 3-D discontinuous Galerkin method for compressible fluid flow on tetrahedral meshes. Efficient implementation of the discontinuous Galerkin method using the streaming model of computation introduces several algorithmic design challenges. Using a cycle-accurate simulator, performance characteristics have been obtained for the Stanford Merrimac stream processor. The current Merrimac design achieves 128 Gflops per chip and the desktop board is populated with 16 chips yielding a peak performance of 2 Teraflops. Total parts cost for the desktop board is less than $20K. Current cycle-accurate simulations for discretizations of the 3-D compressible flow equations yield approximately 40-50% of the peak performance of the Merrimac streaming processor chip. Ongoing work includes the assessment of the performance of the same algorithm on the 2 Teraflop desktop board with a target goal of achieving 1 Teraflop performance.
Falaschi, Alessandro; Mønster, Dan; Doležal, Ivan;
2004-01-01
The TF-NETCAST task force was active from March 2003 to March 2004, and during this time the mem- bers worked on various aspects of streaming media related to the ultimate goal of setting up common services and infrastructures to enable netcasting of high quality content to the academic community...... in Europe. We report on a survey of the use of streaming media in the academic community in Europe, an open source content delivery network, and a portal for announcing live streaming events to the global academic community....
Vertical Handover and Video Streaming Over Cloud in 4G Heterogeneous Overlay Wireless Networks
Dr.P.Vetrivelan
2015-10-01
Full Text Available 4G enables the integration and interworking of all wireless systems. The users always think of seamless streaming of multimedia over various networks. The proposed technique focus on providing “non-terminating” video streaming for mobile users while moving over various networks, the adaptive mobile streaming over mobile networks helps to provide streaming of video . The streaming delays can be reduced by constructing private agents using cloud to provide adaptive video streaming to mobile devices, some algorithm like SVC H.264f is used to reduce buffering during streaming and also in switching over one network to another network. Vertical Handover is carried out in order to reduce handoff by constructing MDP based algorithms using the QoS parameters such as bandwidth, delay, jitter, bit error rate and cost.
Finding Recently Frequent Items over Online Data Streams
YIN Zhi-wu; HUANG Shang-teng
2006-01-01
In this paper, a new algorithm HCOUNT + is proposed to find frequent items over data stream based on the HCOUNT algorithm. The new algorithm adopts aided measures to improve the precision of HCOUNT greatly. In addition,HCOUNT + is introduced to time critical applications and a novel sliding windows-based algorithm SL-HCOUNT + is proposed to mine the most frequent items occurring recently.This algorithm uses limited memory (nB · (1 +α) · e/ε·In(-M/lnρ)(α＜1) counters), requires constant processing time per packet (only (1+α) · ln(-M/lnρ(α＜1)) counters are updated), makes only one pass over the streaming data,and is shown to work well in the experimental results.
PGG: An Online Pattern Based Approach for Stream Variation Management
Lu-An Tang; Bin Cui; Hong-Yan Li; Gao-Shan Miao; Dong-Qing Yang; Xin-Biao Zhou
2008-01-01
Many database applications require efficient processing of data streams with value variations and fiuctuant sampling frequency. The variations typically imply fundamental features of the stream and important domain knowledge of underlying objects. In some data streams, successive events seem to recur in a certain time interval, but the data indeed evolves with tiny differences as time elapses. This feature, so called pseudo periodicity, poses a new challenge to stream variation management. This study focuses on the online management for variations over such streams. The idea can be applied to many scenarios such as patient vital signal monitoring in medical applications. This paper proposes a new method named Pattern Growth Graph (PGG) to detect and manage variations over evolving streams with following features: 1) adopts the wave-pattern to capture the major information of data evolution and represent them compactly;2) detects the variations in a single pass over the stream with the help of wave-pattern matching algorithm; 3) only stores different segments of the pattern for incoming stream, and hence substantially compresses the data without losing important information; 4) distinguishes meaningful data changes from noise and reconstructs the stream with acceptable accuracy.Extensive experiments on real datasets containing millions of data items, as well as a prototype system, are carried out to demonstrate the feasibility and effectiveness of the proposed scheme.
Software for simulating dichromatic perception of video streams
2013-01-01
We have designed a configurable stand-alone Matlab-based software to simulate dichromatic perception of video streams. The algorithm used is an extension for video streams of the “corresponding pair algorithm” by Capilla and coworkers for simulation of dichromatic perception of images. The software allows the user to upload a video sequence and to process it using different dichromatic color vision models and viewing conditions. The output video may be generated in different spatial and tempo...
The Magellanic Stream: Circumnavigating the Galaxy
D'Onghia, Elena
2015-01-01
The Magellanic Clouds are surrounded by an extended network of gaseous structures. Chief among these is the Magellanic Stream, an interwoven tail of filaments trailing the Clouds in their orbit around the Milky Way. When considered in tandem with its Leading Arm, the Stream stretches over 200 degrees on the sky. Thought to represent the result of tidal interactions between the Clouds and ram-pressure forces exerted by the Galactic corona, its kinematic properties reflect the dynamical history of the closest pair of dwarf galaxies to the Milky Way. The Stream is a benchmark for hydrodynamical simulations of accreting gas and cloud/corona interactions. If the Stream survives these interactions and arrives safely in the Galactic disk, its cargo of over a billion solar masses of gas has the potential to maintain or elevate the Galactic star formation rate. In this article, we review the current state of knowledge of the Stream, including its chemical composition, physical conditions, origin, and fate. We also rev...
Trout Stream Special Regulations
Minnesota Department of Natural Resources — This layer shows Minnesota trout streams that have a special regulation as described in the 2006 Minnesota Fishing Regulations. Road crossings were determined using...
Iowa State University GIS Support and Research Facility — This draft dataset consists of all ditches or channelized pieces of stream that could be identified using three input datasets; namely the1:24,000 National...
Shigeta, M.; Sato, T.; Dasgupta, B.
1985-01-01
The magnetohydrodynamic stability of streaming tearing mode is investigated numerically. A bulk plasma flow parallel to the antiparallel magnetic field lines and localized in the neutral sheet excites a streaming tearing mode more strongly than the usual tearing mode, particularly for the wavelength of the order of the neutral sheet width (or smaller), which is stable for the usual tearing mode. Interestingly, examination of the eigenfunctions of the velocity perturbation and the magnetic field perturbation indicates that the streaming tearing mode carries more energy in terms of the kinetic energy rather than the magnetic energy. This suggests that the streaming tearing mode instability can be a more feasible mechanism of plasma acceleration than the usual tearing mode instability.
Mack, Steve
2002-01-01
This book "tells you everything you need to know to produce professional-quality streaming media for the Internet, from an overview of the available systems and tools to high-end techniques for top quality results...
U.S. Environmental Protection Agency — Roads are a source of auto related pollutants (e.g. gasoline, oil and other engine fluids). When roads are near streams, rain can wash these pollutants directly into...
U.S. Environmental Protection Agency — Roads are a source of auto related pollutants (e.g. gasoline, oil and other engine fluids). When roads are near streams, rain can wash these pollutants directly into...
Minnesota Department of Natural Resources — 1:24,000 scale streams captured from USGS seven and one-half minute quadrangle maps, with perennial vs. intermittent classification, and connectivity through lakes,...
Shigeta, M.; Sato, T.; Dasgupta, B.
1985-01-01
The magnetohydrodynamic stability of streaming tearing mode is investigated numerically. A bulk plasma flow parallel to the antiparallel magnetic field lines and localized in the neutral sheet excites a streaming tearing mode more strongly than the usual tearing mode, particularly for the wavelength of the order of the neutral sheet width (or smaller), which is stable for the usual tearing mode. Interestingly, examination of the eigenfunctions of the velocity perturbation and the magnetic field perturbation indicates that the streaming tearing mode carries more energy in terms of the kinetic energy rather than the magnetic energy. This suggests that the streaming tearing mode instability can be a more feasible mechanism of plasma acceleration than the usual tearing mode instability.
Streaming Virtual Reality Content
El-Ganainy, Tarek; Hefeeda, Mohamed
2016-01-01
The recent rise of interest in Virtual Reality (VR) came with the availability of commodity commercial VR prod- ucts, such as the Head Mounted Displays (HMD) created by Oculus and other vendors. To accelerate the user adoption of VR headsets, content providers should focus on producing high quality immersive content for these devices. Similarly, multimedia streaming service providers should enable the means to stream 360 VR content on their platforms. In this study, we try to cover different ...
Reincarnation of Streaming Applications
2009-10-01
AFRL-RY-WP-TR-2009-1033 REINCARNATION OF STREAMING APPLICATIONS Saman Amarsinghe, Robert Miller, and Michael Ernst Massachusetts...2007 – 31 December 2008 4. TITLE AND SUBTITLE REINCARNATION OF STREAMING APPLICATIONS 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA8650-07-C-7737 5c...Program Reincarnation , using a simple prototype. A Program Reincarnation tool will assist the programmer in replacing the program’s code (the body
王让定; 朱洪留; 徐达文
2011-01-01
提出一种基于脆弱水印的视频流完整性认证方法,在H.264压缩比特流中,首先根据I_Slice中4×4块的编码模式生成认证码,然后通过调制某些运动子块的VLC码字将其嵌入B_Slice和P_Slice的视频流中.这种调制是基于VLC码字和待嵌入比特之间的映射规则进行的.映射后的码字与原码字具有很好的相似性,即码字长度不变,码字表示的编码元素值相似.该算法可以实现水印的快速提取,满足视频实时处理的要求.实验仿真结果表明,本算法具有较小的视频失真,并能有效地对视频帧进行完整性认证.%An integrity authentication scheme for video bit-stream based on the fragile watermarking is proposed in this paper.In the compressed bit-stream of H.264, The authentication cedeword are generated according to the mode of intra_4 × 4 in I_Slice firstly, and then embedded into B_Slice and P_Slice by modulating some VLC codeword of sub-block.This modulation is based on the mapping rule between the VLC cedeword and the bit to be embedded.The mapped codeword is very similar to the original codeword, namely, the length of cedeword is same and the value of coding element is similar.This scheme could detect the watermarking rapidly, which meets the requirement of the real-time processing of video.Experimental results show that it has less influence on the quality of video, and can effectively carry out the integral certification of video frame.
Gulf stream separation dynamics
Schoonover, Joseph
Climate models currently struggle with the more traditional, coarse ( O(100 km) ) representation of the ocean. In these coarse ocean simulations, western boundary currents are notoriously difficult to model accurately. The modeled Gulf Stream is typically seen exhibiting a mean pathway that is north of observations, and is linked to a warm sea-surface temperature bias in the Mid-Atlantic Bight. Although increased resolution ( O(10 km) ) improves the modeled Gulf Stream position, there is no clean recipe for obtaining the proper pathway. The 70 year history of literature on the Gulf Stream separation suggests that we have not reached a resolution on the dynamics that control the current's pathway just south of the Mid-Atlantic Bight. Without a concrete knowledge on the separation dynamics, we cannot provide a clean recipe for accurately modeling the Gulf Stream at increased resolutions. Further, any reliable parameterization that yields a realistic Gulf Stream path must express the proper physics of separation. The goal of this dissertation is to determine what controls the Gulf Stream separation. To do so, we examine the results of a model intercomparison study and a set of numerical regional terraforming experiments. It is argued that the separation is governed by local dynamics that are most sensitive to the steepening of the continental shelf, consistent with the topographic wave arrest hypothesis of Stern (1998). A linear extension of Stern's theory is provided, which illustrates that wave arrest is possible for a continuously stratified fluid.
Streaming Pool: reuse, combine and create reactive streams with pleasure
CERN. Geneva
2017-01-01
When connecting together heterogeneous and complex systems, it is not easy to exchange data between components. Streams of data are successfully used in industry in order to overcome this problem, especially in the case of "live" data. Streams are a specialization of the Observer design pattern and they provide asynchronous and non-blocking data flow. The ongoing effort of the ReactiveX initiative is one example that demonstrates how demanding this technology is even for big companies. Bridging the discrepancies of different technologies with common interfaces is already done by the Reactive Streams initiative and, in the JVM world, via reactive-streams-jvm interfaces. Streaming Pool is a framework for providing and discovering reactive streams. Through the mechanism of dependency injection provided by the Spring Framework, Streaming Pool provides a so called Discovery Service. This object can discover and chain streams of data that are technologically agnostic, through the use of Stream IDs. The stream to ...
The influence of the Gulf Stream on wintertime European blocking
O'Reilly, Christopher H.; Minobe, Shoshiro; Kuwano-Yoshida, Akira
2016-09-01
Wintertime blocking is responsible for extended periods of anomalously cold and dry weather over Europe. In this study, the influence of the Gulf Stream sea surface temperature (SST) front on wintertime European blocking is investigated using a reanalysis dataset and a pair of atmospheric general circulation model (AGCM) simulations. The AGCM is forced with realistic and smoothed Gulf Stream SST, and blocking frequency over Europe is found to depend crucially on the Gulf Stream SST front. In the absence of the sharp SST gradient European blocking is significantly reduced and occurs further downstream. The Gulf Stream is found to significantly influence the surface temperature anomalies during blocking periods and the occurrence of associated cold spells. In particular the cold spell peak, located in central Europe, disappears in the absence of the Gulf Stream SST front. The nature of the Gulf Stream influence on European blocking development is then investigated using composite analysis. The presence of the Gulf Stream SST front is important in capturing the observed quasi-stationary development of European blocking. The development is characterised by increased lower-tropospheric meridional eddy heat transport in the Gulf Stream region and increased eddy kinetic energy at upper-levels, which acts to reinforce the quasi-stationary jet. When the Gulf Stream SST is smoothed the storm track activity is weaker, the development is less consistent and European blocking occurs less frequently.
An Active Queue Management Algorithm: CRED
LI Shi-ning; SUN En-chang; QIN Zheng
2006-01-01
By applying the method of average and variance, a new queue management algorithm named the Classified-Random Early Detection (CRED) algorithm is presented which can identify the media streaming, TCP traffic and other UDP traffic at the edge routers. The algorithm discriminates the slow start and the congestion control phase of the TCP traffic and combines the TCP congestion control with the IP congestion control to alleviate the congestion effectively. Simulation shows that CRED can not only make the media streaming obtain the resources needed but also protect the TCP traffic transmitted effectively and reliably.
Hybrid Peer-to-peer Streaming System for Mobile Peers with Transcoding
Shuai Zeng
2015-08-01
Full Text Available In this paper, we study in hybrid peer-to-peer (P2P streaming system, which includes fixed peers and mobile peers in the same network, and propose a flow rate allocation algorithm to optimize the streaming system. In the proposed algorithm, based on transcoding technique, we describe how to exchange original and transcoded data among video source server, fixed and mobile peers. The purpose of our algorithm is to reduce the bandwidth demand of video source server, while ensuring the flow rate of video data sending to any peer no less than its video coding rate. We compare the performance of P2P streaming system using our algorithm with traditional design in various situations in the simulation experiment, and test how much benefit the system can get from the new algorithm. The results show that, if the flow rate of video data is allocated appropriately, better performance of streaming system can be achieved.
Data Stream Classification Based on the Gamma Classifier
Abril Valeria Uriarte-Arcia
2015-01-01
Full Text Available The ever increasing data generation confronts us with the problem of handling online massive amounts of information. One of the biggest challenges is how to extract valuable information from these massive continuous data streams during single scanning. In a data stream context, data arrive continuously at high speed; therefore the algorithms developed to address this context must be efficient regarding memory and time management and capable of detecting changes over time in the underlying distribution that generated the data. This work describes a novel method for the task of pattern classification over a continuous data stream based on an associative model. The proposed method is based on the Gamma classifier, which is inspired by the Alpha-Beta associative memories, which are both supervised pattern recognition models. The proposed method is capable of handling the space and time constrain inherent to data stream scenarios. The Data Streaming Gamma classifier (DS-Gamma classifier implements a sliding window approach to provide concept drift detection and a forgetting mechanism. In order to test the classifier, several experiments were performed using different data stream scenarios with real and synthetic data streams. The experimental results show that the method exhibits competitive performance when compared to other state-of-the-art algorithms.
A Distributed Flocking Approach for Information Stream Clustering Analysis
Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL
2006-01-01
Intelligence analysts are currently overwhelmed with the amount of information streams generated everyday. There is a lack of comprehensive tool that can real-time analyze the information streams. Document clustering analysis plays an important role in improving the accuracy of information retrieval. However, most clustering technologies can only be applied for analyzing the static document collection because they normally require a large amount of computation resource and long time to get accurate result. It is very difficult to cluster a dynamic changed text information streams on an individual computer. Our early research has resulted in a dynamic reactive flock clustering algorithm which can continually refine the clustering result and quickly react to the change of document contents. This character makes the algorithm suitable for cluster analyzing dynamic changed document information, such as text information stream. Because of the decentralized character of this algorithm, a distributed approach is a very natural way to increase the clustering speed of the algorithm. In this paper, we present a distributed multi-agent flocking approach for the text information stream clustering and discuss the decentralized architectures and communication schemes for load balance and status information synchronization in this approach.
Streams and their future inhabitants
Sand-Jensen, K.; Friberg, N.
2006-01-01
In this fi nal chapter we look ahead and address four questions: How do we improve stream management? What are the likely developments in the biological quality of streams? In which areas is knowledge on stream ecology insuffi cient? What can streams offer children of today and adults of tomorrow?...
On generalized extending modules
ZENG Qing-yi
2007-01-01
A module M is called generalized extending if for any submodule N of M, there is a direct summand K of M such that N≤K and K/N is singular. Any extending module and any singular module are generalized extending. Any homomorphic image of a generalized extending module is generalized extending. Any direct sum of a singular (uniform) module and a semi-simple module is generalized extending. A ring R is a right Co-H-ring ifand only ifall right R modules are generalized extending modules.
Kleinberg, Jon
2006-01-01
Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
The WHAM Hα Magellanic Stream Survey: Progress and Early Results
Smart, Brianna; Haffner, L. Matthew; Barger, Kat; Krishnarao, Dhanesh
2017-01-01
We present early analysis of the Hα survey of the Magellanic Stream using the Wisconsin H-Alpha Mapper (WHAM). The neutral component of the Stream extends some 200° across the sky (Nidever et al. 2010). However, the full extent of the ionized gas has not been mapped in detail. Previous studies (e.g., Putman et al. 2003; Weiner & Williams 1996) suggest that ionized gas is likely to be found all along the length of the Stream, and may extend beyond the current neutral boundaries as traced by 21 cm. Barger et al. (2013) used WHAM to map ionized gas throughout the Magellanic Bridge between the Magellanic Clouds. Although ionized emission tracks the neutral emission for the most part, it often spans a few degrees away from the H I at slightly offset velocities. Additionally, Fox et al. (2014) find evidence in an absorption line study that the tidal debris in the Magellanic System contains twice as much ionized gas as neutral material and may extend 30° away from 21-cm sensitivity boundaries. We are now compiling the first comprehensive picture of the ionized component of the Magellanic Stream using WHAM's unprecedented sensitivity to trace diffuse emission (~tens of mR), its velocity resolution (12 km/s) to separate the Stream from the Milky Way, and its multiwavelength capabilities (e.g., [S II] and [N II]) to examine the physical conditions of the gas. Much of the data along the primary axis of the Stream has been collected for the first phase of this extensive study, a complete kinematic Hα survey of the Stream. We present survey progress, challenges in extracting Stream emission, and first-look kinematic maps at select positions along the Stream.
Stellar Streams and Clouds in the Galactic Halo
Grillmair, Carl J
2016-01-01
Recent years have seen the discovery of an ever growing number of stellar debris streams and clouds. These structures are typically detected as extended and often curvilinear overdensities of metal-poor stars that stand out from the foreground disk population. The streams typically stretch tens of degrees or more across the sky, even encircling the Galaxy, and range in heliocentric distance from 3 to 100 kpc. This chapter summarizes the techniques used for finding such streams and provides tables giving positions, distances, velocities, and metallicities, where available, for all major streams and clouds that have been detected as of January 2015. Sky maps of the streams are also provided. Properties of individual tidal debris structures are discussed.
Artificial viscosity in the transonic stream function formulation
徐建中; 杜建一; 沈浩; 刘海涛
1995-01-01
The artificial density method which has been applied widely in the transonic potential calculation and the current transonic stream function calculation is investigated theoretically. The analysis shows that in the stream function formulation the artificial density is not equivalent to the artificial viscosity and cannot be used, and a correct expression of the artificial viscosity in the stream function method is then derived. The principal equation of the stream function, the density equation converted from one of the momentum equations and the present artificial viscosity scheme constitute the complete transonic stream function formulation. The numerical practice demonstrates that the range of Mach number computed by this approach is extended and the shock location is close to the experimental result.
Tau reconstruction and identification algorithm
Raman Khurana
2012-11-01
CMS has developed sophisticated tau identification algorithms for tau hadronic decay modes. Production of tau lepton decaying to hadrons are studied at 7 TeV centre-of-mass energy with 2011 collision data collected by CMS detector and has been used to measure the performance of tau identification algorithms by measuring identification efficiency and misidentification rates from electrons, muons and hadronic jets. These algorithms enable extended reach for the searches for MSSM Higgs, and other exotic particles.
Algorithm for Compressing Time-Series Data
Hawkins, S. Edward, III; Darlington, Edward Hugo
2012-01-01
An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").
2016-04-05
About this volumeMontana StreamStats is a Web-based geographic information system (http://water.usgs.gov/osw/streamstats/) application that provides users with access to basin and streamflow characteristics for gaged and ungaged streams in Montana. Montana StreamStats was developed by the U.S. Geological Survey (USGS) in cooperation with the Montana Departments of Transportation, Environmental Quality, and Natural Resources and Conservation. The USGS Scientific Investigations Report consists of seven independent but complementary chapters dealing with various aspects of this effort.Chapter A describes the Montana StreamStats application, the basin and streamflow datasets, and provides a brief overview of the streamflow characteristics and regression equations used in the study. Chapters B through E document the datasets, methods, and results of analyses to determine streamflow characteristics, such as peak-flow frequencies, low-flow frequencies, and monthly and annual characteristics, for USGS streamflow-gaging stations in and near Montana. The StreamStats analytical toolsets that allow users to delineate drainage basins and solve regression equations to estimate streamflow characteristics at ungaged sites in Montana are described in Chapters F and G.
Sound stream segregation: a neuromorphic approach to solve the ‘cocktail party problem’ in real-time
Chetan Singh Thakur
2015-09-01
Full Text Available The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the ‘cocktail party effect’. It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA. This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR of the segregated stream (90, 77 and 55 dB for simple tone, complex tone and speech, respectively as compared to the SNR of the mixture waveform (0 dB. This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for
Newberg, Heidi Jo
Dwarf galaxies that come too close to larger galaxies suffer tidal disruption; the differential gravitational force between one side of the galaxy and the other serves to rip the stars from the dwarf galaxy so that they instead orbit the larger galaxy. This process produces "tidal streams" of stars, which can be found in the stellar halo of the Milky Way, as well as in halos of other galaxies. This chapter provides a general introduction to tidal streams, including the mechanism through which the streams are created, the history of how they were discovered, and the observational techniques by which they can be detected. In addition, their use in unraveling galaxy formation histories and the distribution of dark matter in galaxies is discussed, as is the interaction between these dwarf galaxy satellites and the disk of the larger galaxy.
Continuous Outlier Monitoring on Uncertain Data Streams
曹科研; 王国仁; 韩东红; 丁国辉; 王爱侠; 石凌旭
2014-01-01
Outlier detection on data streams is an important task in data mining. The challenges become even larger when considering uncertain data. This paper studies the problem of outlier detection on uncertain data streams. We propose Continuous Uncertain Outlier Detection (CUOD), which can quickly determine the nature of the uncertain elements by pruning to improve the efficiency. Furthermore, we propose a pruning approach - Probability Pruning for Continuous Uncertain Outlier Detection (PCUOD) to reduce the detection cost. It is an estimated outlier probability method which can effectively reduce the amount of calculations. The cost of PCUOD incremental algorithm can satisfy the demand of uncertain data streams. Finally, a new method for parameter variable queries to CUOD is proposed, enabling the concurrent execution of different queries. To the best of our knowledge, this paper is the first work to perform outlier detection on uncertain data streams which can handle parameter variable queries simultaneously. Our methods are verified using both real data and synthetic data. The results show that they are able to reduce the required storage and running time.
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Mining Frequent Itemsets with Weights over Data Stream Using Inverted Matrix
Long Nguyen Hung
2016-10-01
Full Text Available In recent years, the mining research over data stream has been prominent as they can be applied in many alternative areas in the real worlds. In this paper, we have proposed an algorithm called MFIWDSIM for mining frequent itemsets with weights over a data stream using Inverted Matrix [10]. The main idea is moving data stream to an inverted matrix saved in the computer disks so that the algorithms can mine on it many times with different support thresholds as well as alternative minimum weights. Moreover, this inverted matrix can be accessed to mine in different times for user’s requirements without recalculation. By analyzing and evaluating, the MFIWDSIM can be seen as the better algorithm compared to WSWFP-stream [9] for mining frequent itemsets with weights over data stream.
Classifying Uncertain and Evolving Data Streams with Distributed Extreme Learning Machine
韩东红; 张昕; 王国仁
2015-01-01
Conventional classification algorithms are not well suited for the inherent uncertainty, potential concept drift, volume, and velocity of streaming data. Specialized algorithms are needed to obtain eﬃcient and accurate classifiers for uncertain data streams. In this paper, we first introduce Distributed Extreme Learning Machine (DELM), an optimization of ELM for large matrix operations over large datasets. We then present Weighted Ensemble Classifier Based on Distributed ELM (WE-DELM), an online and one-pass algorithm for eﬃciently classifying uncertain streaming data with concept drift. A probability world model is built to transform uncertain streaming data into certain streaming data. Base classifiers are learned using DELM. The weights of the base classifiers are updated dynamically according to classification results. WE-DELM improves both the eﬃciency in learning the model and the accuracy in performing classification. Experimental results show that WE-DELM achieves better performance on different evaluation criteria, including eﬃciency, accuracy, and speedup.
Cao, Pan; Jorswieck, Eduard A.; Shi, Shuying
2013-10-01
We consider a multiple-input multiple-output (MIMO) interference channel (IC), where a single data stream per user is transmitted and each receiver treats interference as noise. The paper focuses on the open problem of computing the outermost boundary (so-called Pareto boundary-PB) of the achievable rate region under linear transceiver design. The Pareto boundary consists of the strict PB and non-strict PB. For the two user case, we compute the non-strict PB and the two ending points of the strict PB exactly. For the strict PB, we formulate the problem to maximize one rate while the other rate is fixed such that a strict PB point is reached. To solve this non-convex optimization problem which results from the hard-coupled two transmit beamformers, we propose an alternating optimization algorithm. Furthermore, we extend the algorithm to the multi-user scenario and show convergence. Numerical simulations illustrate that the proposed algorithm computes a sequence of well-distributed operating points that serve as a reasonable and complete inner bound of the strict PB compared with existing methods.
StreamSqueeze: a dynamic stream visualization for monitoring of event data
Mansmann, Florian; Krstajic, Milos; Fischer, Fabian; Bertini, Enrico
2012-01-01
While in clear-cut situations automated analytical solution for data streams are already in place, only few visual approaches have been proposed in the literature for exploratory analysis tasks on dynamic information. However, due to the competitive or security-related advantages that real-time information gives in domains such as finance, business or networking, we are convinced that there is a need for exploratory visualization tools for data streams. Under the conditions that new events have higher relevance and that smooth transitions enable traceability of items, we propose a novel dynamic stream visualization called StreamSqueeze. In this technique the degree of interest of recent items is expressed through an increase in size and thus recent events can be shown with more details. The technique has two main benefits: First, the layout algorithm arranges items in several lists of various sizes and optimizes the positions within each list so that the transition of an item from one list to the other triggers least visual changes. Second, the animation scheme ensures that for 50 percent of the time an item has a static screen position where reading is most effective and then continuously shrinks and moves to the its next static position in the subsequent list. To demonstrate the capability of our technique, we apply it to large and high-frequency news and syslog streams and show how it maintains optimal stability of the layout under the conditions given above.
张金玲; 万文钢; 郑占奇; 甘曦; 朱兴宇
2015-01-01
提出了一种改进型自适应遗传算法,该算法用logistic函数拟合交叉概率和变异概率,以赌轮盘选择和精英保留相结合的方式,在全局寻找最优解.与经典遗传算法相比,改进型自适应遗传算法可以大大提高算法的求解质量.本文基于改进的自适应遗传算法研究设计了−3 dB范围为0◦—12◦,−10 dB波束宽度为65◦,波束覆盖为65◦,天线频带范围为8.5—9.8 GHz,中心频率为9.05 GHz的X波段微带余割平方扩展波束天线阵.研究结果表明改进型自适应遗传算法对方向图的拟合程度具有较大提高,适应度值可以从0.07以下提升到0.09以上.%Synthesis of desired radiation patterns without an optimization algorithm is usually time consuming and ineﬃcient. To achieve a desired radiation pattern such as cosecant squared beam and contoured beam, different evolutionary algorithms such as genetic algorithm (GA), particle swarm optimization algorithm, and invasive weed optimization algorithm have been used to find the excitation of radiation elements. Adaptive genetic algorithm (AGA) optimizer is a robust, stochastic search method, modeled on the principles and concepts of natural selection and evolution. As an optimizer, the powerful heuristic of the AGA is effective for solving complex and related problems. An improved AGA is proposed, in allusion to the characteristics of optimizing designs of antenna arrays which have many parameters and complicated structures. This algorithm constructs an adjustble formula to produce the crossover rate and mutation rate based on a logistic curve equation. In the way of combining roulette wheel selection and elitist strategy, this algorithm searches for the optimal solution in the global space, and is compared with the classical GA; the improved AGA has a better performance in seeking the solution. Taking the mutual coupling between the elements into account, we design the X band extended cosecant squared beam
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
Streaming for Functional Data-Parallel Languages
Madsen, Frederik Meisner
In this thesis, we investigate streaming as a general solution to the space inefficiency commonly found in functional data-parallel programming languages. The data-parallel paradigm maps well to parallel SIMD-style hardware. However, the traditional fully materializing execution strategy, and the......In this thesis, we investigate streaming as a general solution to the space inefficiency commonly found in functional data-parallel programming languages. The data-parallel paradigm maps well to parallel SIMD-style hardware. However, the traditional fully materializing execution strategy...... flattening necessitates all sub-computations to materialize at the same time. For example, naive n by n matrix multiplication requires n^3 space in NESL because the algorithm contains n^3 independent scalar multiplications. For large values of n, this is completely unacceptable. We address the problem...
Numerical Modelling of Streams
Vestergaard, Kristian
In recent years there has been a sharp increase in the use of numerical water quality models. Numeric water quality modeling can be divided into three steps: Hydrodynamic modeling for the determination of stream flow and water levels. Modelling of transport and dispersion of a conservative...
Falaschi, Alessandro; Mønster, Dan; Doležal, Ivan
2004-01-01
The TF-NETCAST task force was active from March 2003 to March 2004, and during this time the mem- bers worked on various aspects of streaming media related to the ultimate goal of setting up common services and infrastructures to enable netcasting of high quality content to the academic community...
Pedersen, Rasmus Rex
This report analyses how a ’per user’ settlement model differs from the ‘pro rata’ model currently used. The analysis is based on data for all streams by WiMP users in Denmark during August 2013. The analysis has been conducted in collaboration with Christian Schlelein from Koda on the basis...
Boesgaard, Martin; Vesterager, Mette; Zenner, Erik
2008-01-01
The stream cipher Rabbit was first presented at FSE 2003, and no attacks against it have been published until now. With a measured encryption/decryption speed of 3.7 clock cycles per byte on a Pentium III processor, Rabbit does also provide very high performance. This paper gives a concise...... description of the Rabbit design and some of the cryptanalytic results available....
Stream Automata Are Coalgebras
Ciancia, V.; Venema, Y.
2012-01-01
Stream automata (also called ω-automata) and ω-regular languages are of paramount importance in Computer Science and Logic. A coalgebraic treatment of these structures has not been given yet. We study a simple two-sorted setting where deterministic Muller automata can be cast as coalgebras, so that
U.S. Environmental Protection Agency — QUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987).
Grønkjær, Poul
2004-01-01
E-learning Lab på Aalborg Universitet har i forbindelse med forskningsprojektet Virtuelle Læringsformer og Læringsmiljøer foretaget en række praktiske eksperimenter med streaming-video produktioner. Hensigten med denne artikel er at formidle disse erfaringer. Artiklen beskriver hele produktionsf...... E-learning Lab på Aalborg Universitet har i forbindelse med forskningsprojektet Virtuelle Læringsformer og Læringsmiljøer foretaget en række praktiske eksperimenter med streaming-video produktioner. Hensigten med denne artikel er at formidle disse erfaringer. Artiklen beskriver hele...... produktionsforløbet: fra ide til færdigt produkt, forskellige typer af præsentationer, dramaturgiske overvejelser samt en konceptskitse. Streaming-video teknologien er nu så udviklet med et så tilfredsstillende audiovisuelt udtryk at vi kan begynde at fokusere på, hvilket indhold der er velegnet til at blive gjort...... tilgængeligt uafhængigt af tid og sted. Afslutningsvis er der en række kildehenvisninger, blandt andet en oversigt over de streaming-video produktioner, som denne artikel bygger på....
On Meteoroid Streams Identification
Klacka, J
1999-01-01
Criterion for the membership of individual meteors to meteoroid streams presented by Valsecchi {\\it et. al.} (1999) and Jopek {\\it et. al.} (1999) is discussed. The authors characterize and use their criterion as a distance function. However, it is not a distance function. Some practical aspects are also discussed. Correct criterion is presented.
Abrams, D.; Williams, C.
1999-01-01
This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases for which all know classical algorithms require exponential time.
Tel, G.
1993-01-01
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of distri
K. Selvi
2014-12-01
Full Text Available Pattern recognition, envisaging supervised and unsupervised method, optimization, associative memory and control process are some of the diversified troubles that can be resolved by artificial neural networks. Problem identified: Of late, discovering the required information in massive quantity of data is the challenging tasks. The model of similarity evaluation is the central element in accomplishing a perceptive of variables and perception that encourage behavior and mediate concern. This study proposes Artificial Neural Networks algorithms to resolve similarity measures. In order to apply singular value decomposition the frequency of word pair is established in the given document. (1 Tokenization: The splitting up of a stream of text into words, phrases, signs, or other significant parts is called tokenization. (2 Stop words: Preceding or succeeding to processing natural language data, the words that are segregated is called stop words. (3 Porter stemming: The main utilization of this algorithm is as part of a phrase normalization development that is characteristically completed while setting up in rank recovery technique. (4 WordNet: The compilation of lexical data base for the English language is called as WordNet Based on Artificial Neural Networks, the core part of this study work extends n-gram proposed algorithm. All the phonemes, syllables, letters, words or base pair corresponds in accordance to the application. Future work extends the application of this same similarity measures in various other neural network algorithms to accomplish improved results.
楼晓春
2011-01-01
针对移动机器人的同步定位与建图（SLAM）问题,提出了一种基于改进的扩展Kalman滤波算法的同步定位与建图方法。通过建立基于直线特征提取的机器人观测模型,推导了SLAM建图的预测和更新算式,设计了基于特征点数目的SLAM预测与更新率算子,实现了移动机器人的同步定位与建图。实验结果表明该方法有效、可行。%For mobile robot simultaneous localization and mapping（SLAM） key issues,an improved SLAM method based on extended Kalman filter was presented.Through the establishment of the observation model based on line features,the prediction and state-updating of the SLAM were formulated,the computing cycles were designed based on the number of feature points and the simultaneous localization and mapping were realized.Experimental results show that the method is effective and feasible.
吴林煌; 苏凯雄; 郭里婷; 吴子静
2016-01-01
针对强记忆功放的非线性问题,提出一种基于自适应扩展卡尔曼滤波与神经网络的高功放(High power amplifier,HPA)预失真算法.采用实数固定延时神经网络(Real-valued focused time-delay neural network,RVFTDNN)对间接学习结构预失真系统中的预失真器和逆估计器进行建模,扩展卡尔曼滤波(Extended Kalman filter,EKF)算法训练神经网络,从理论上指出Levenberg-Marquardt (LM)算法是EKF算法的特殊情况,并用李亚普诺夫稳定性理论分析EKF算法的稳定收敛条件,推导出测量误差矩阵的自适应迭代公式.结果表明:自适应EKF算法的训练误差和泛化误差均比LM算法更低,预失真后的邻道功率比(Adjacent channel power ratio,ACPR)比LM算法改善了2dB.
An Efficient Framework for Generating Storyline Visualizations from Streaming Data.
Tanahashi, Yuzuru; Hsueh, Chien-Hsin; Ma, Kwan-Liu
2015-06-01
This paper presents a novel framework for applying storyline visualizations to streaming data. The framework includes three components: a new data management scheme for processing and storing the incoming data, a layout construction algorithm specifically designed for incrementally generating storylines from streaming data, and a layout refinement algorithm for improving the legibility of the visualization. By dividing the layout computation to two separate components, one for constructing and another for refining, our framework effectively provides the users with the ability to follow and reason dynamic data. The evaluation studies of our storyline visualization framework demonstrate its efficacy to present streaming data as well as its superior performance over existing methods in terms of both computational efficiency and visual clarity.
Computing Strongly Connected Components in the Streaming Model
Laura, Luigi; Santaroni, Federico
In this paper we present the first algorithm to compute the Strongly Connected Components of a graph in the datastream model (W-Stream), where the graph is represented by a stream of edges and we are allowed to produce intermediate output streams. The algorithm is simple, effective, and can be implemented with few lines of code: it looks at each edge in the stream, and selects the appropriate action with respect to a tree T, representing the graph connectivity seen so far. We analyze the theoretical properties of the algorithm: correctness, memory occupation (O(n logn)), per item processing time (bounded by the current height of T), and number of passes (bounded by the maximal height of T). We conclude by presenting a brief experimental evaluation of the algorithm against massive synthetic and real graphs that confirms its effectiveness: with graphs with up to 100M nodes and 4G edges, only few passes are needed, and millions of edges per second are processed.
SRF Coloring: Stream Register File Allocation via Graph Coloring
Xue-Jun Yang; Yu Deng; Li Wang; Xiao-Bo Yan; Jing Du; Ying Zhang; Gui-Bin Wang; Tao Tang
2009-01-01
Stream Register File (SRF) is a large on-chip memory of the stream processor and its efficient management is essential for good performance. Current stream programming languages expose the management of SRF to the programmer, incurring heavy burden on the programmer and bringing difficulties to inheriting the legacy codes. SF95 is the language developed for FT64 which is the first 64-bit stream processor designed for scientific applications. SF95 conceals SRF from the programmer and leaves the management of SRF to its compiler. In this paper, we present a compiler approach named SRF Coloring to manage SRF automatically. The novelties of this paper are: first, it is the first time to use the graph coloring-based algorithm for the SRF management; second, an algorithm framework for SRF Coloring that is well suited to the FT64 architecture is proposed -- this framework is based on a well-understood graph coloring algorithm for register allocation, together with some modifications to deal with the unusual aspects of SRF problem; third, the SRF Coloring algorithm is implemented in SF95Compiler, a compiler designed for FT64 and SF95. The experimental results show that our approach represents a practical and promising solution to SRF allocation.
Chaos-Based Encryption Algorithm for Compressed Video
袁春; 钟玉琢; 贺玉文
2003-01-01
Encryption for compressed video streams has attracted increasing attention with the exponential growth of digital multimedia delivery and consumption. However, most algorithms proposed in the literature do not effectively address the peculiarities of security and performance requirements. This paper presents a chaos-based encryption algorithm called the chaotic selective encryption of compressed video (CSECV) which exploits the characteristics of the compressed video. The encryption has three separate layers that can be selected according to the security needs of the application and the processing capability of the client computer. The chaotic pseudo-random sequence generator used to generate the key-sequence to randomize the important fields in the compressed video stream has its parameters encrypted by an asymmetric cipher and placed into the stream. The resulting stream is still a valid video stream. CSECV has significant advantages over existing algorithms for security, decryption speed, implementation flexibility, and error preservation.
Lightweight query authentication on streams
2014-01-01
We consider a stream outsourcing setting, where a data owner delegates the management of a set of disjoint data streams to an untrusted server. The owner authenticates his streams via signatures. The server processes continuous queries on the union of the streams for clients trusted by the owner. Along with the results, the server sends proofs of result correctness derived from the owner's signatures, which are easily verifiable by the clients. We design novel constructions for a collection o...
Battling memory requirements of array programming through streaming
Kristensen, Mads Ruben Burgdorff; Avery, James Emil; Blum, Troels;
2016-01-01
A barrier to efficient array programming, for example in Python/NumPy, is that algorithms written as pure array operations completely without loops, while most efficient on small input, can lead to explosions in memory use. The present paper presents a solution to this problem using array streaming......, implemented in the automatic parallelization high-performance framework Bohrium. This makes it possible to use array programming in Python/NumPy code directly, even when the apparent memory requirement exceeds the machine capacity, since the automatic streaming eliminates the temporary memory overhead...... streaming, yielding corresponding improvements in speed and utilization of GPGPU-cores. The streaming-enabled Bohrium effortlessly runs programs on input sizes much beyond sizes that crash on pure NumPy due to exhausting system memory....
An analytical framework for data stream mining techniques based on challenges and requirements
Kholghi, Mahnoosh
2011-01-01
A growing number of applications that generate massive streams of data need intelligent data processing and online analysis. Real-time surveillance systems, telecommunication systems, sensor networks and other dynamic environments are such examples. The imminent need for turning such data into useful information and knowledge augments the development of systems, algorithms and frameworks that address streaming challenges. The storage, querying and mining of such data sets are highly computationally challenging tasks. Mining data streams is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information. Generally, two main challenges are designing fast mining methods for data streams and need to promptly detect changing concepts and data distribution because of highly dynamic nature of data streams. The goal of this article is to analyze and classify the application of diverse data mining techniques in different challenges of data stream mining. In this...
A. Liss
2016-06-01
Full Text Available Regional climate is a critical factor in public health research, adaptation studies, climate change burden analysis, and decision support frameworks. Existing climate regionalization schemes are not well suited for these tasks as they rarely take population density into account. In this work, we are extending our recently developed method for automated climate regionalization (LKN-method to incorporate the spatial features of target population. The LKN method consists of the data limiting step (L-step to reduce dimensionality by applying principal component analysis, a classification step (K-step to produce hierarchical candidate regions using k-means unsupervised classification algorithm, and a nomination step (N-step to determine the number of candidate climate regions using cluster validity indexes. LKN method uses a comprehensive set of multiple satellite data streams, arranged as time series, and allows us to define homogeneous climate regions. The proposed approach extends the LKN method to include regularization terms reflecting the spatial distribution of target population. Such tailoring allows us to determine the optimal number and spatial distribution of climate regions and thus, to ensure more uniform population coverage across selected climate categories. We demonstrate how the extended LKN method produces climate regionalization can be better tailored to epidemiological research in the context of decision support framework.
Liss, Alexander; Gel, Yulia R.; Kulinkina, Alexandra; Naumova, Elena N.
2016-06-01
Regional climate is a critical factor in public health research, adaptation studies, climate change burden analysis, and decision support frameworks. Existing climate regionalization schemes are not well suited for these tasks as they rarely take population density into account. In this work, we are extending our recently developed method for automated climate regionalization (LKN-method) to incorporate the spatial features of target population. The LKN method consists of the data limiting step (L-step) to reduce dimensionality by applying principal component analysis, a classification step (K-step) to produce hierarchical candidate regions using k-means unsupervised classification algorithm, and a nomination step (N-step) to determine the number of candidate climate regions using cluster validity indexes. LKN method uses a comprehensive set of multiple satellite data streams, arranged as time series, and allows us to define homogeneous climate regions. The proposed approach extends the LKN method to include regularization terms reflecting the spatial distribution of target population. Such tailoring allows us to determine the optimal number and spatial distribution of climate regions and thus, to ensure more uniform population coverage across selected climate categories. We demonstrate how the extended LKN method produces climate regionalization can be better tailored to epidemiological research in the context of decision support framework.
宗长富; 潘钊; 胡丹; 郑宏宇; 徐颖; 董益亮
2009-01-01
车辆行驶中某些状态参量不易准确测得或测量成本较高,而这些变量的准确获取对车辆底盘控制有着重要的意义.为以较低成本获取重要的车辆运动状态,建立包括横摆、侧向和纵向3自由度的非线性车辆模型,利用扩展Kalman滤波(Extended Kalman filtering, EKF)理论建立了信息融合算法,给出车辆状态变量最小方差意义下的融合结果,利用少量的易测车辆状态信息(转向盘转角、车辆纵、侧向加速度)融合得出所需的难测车辆状态(横摆角速度、质心侧偏角).并在Matlab/Simulink环境下利用实车场地试验数据进行了离线仿真.多种工况下的场地试验结果表明,该算法在估计汽车横摆角速度、质心侧偏角、纵向速度时具有一定的准确性,特别是对横摆角速度的估计,即使在车辆非线性区也表现出良好性能.同时该融合算法简单、稳定及所需融合输入较少的特点使该算法在实际中的应用成为可能.
常晓丽; 付巍; 梁慧; 李锦荣; 闫文博
2015-01-01
In the process of there-phase induction motor speed and torque estimation,the data collec-tion is vulnerable to the outside interference easily,which leads to large deviations.Speed and torque es-timation method of there-phase induction motor based on central difference extended Kalman filter was proposed.At first,deduced there-phase induction motor state equations and output equations in theα-βcoordinate system with three-phase induction motor stator and rotor currents as state variables.Then u-sing central difference extended kalman filter algorithm for three-phase induction motor speed and torque estimation.The simulation results show that,compares with extended kalman filter,central difference extended kalman filter algorithm has better follow-up performance when motor running state changes, and has faster rate of convergence.Thus speed and torque of there-phase induction motor can be esti-mated precisely.%针对三相感应电机在转速和转矩测试过程中，存在采集数据易受外界干扰而导致转速和转矩等估计值出现较大偏差的问题，提出采用中心差心扩展卡尔曼滤波算法实现对三相感应电机转速和转矩的估计。首先，以三相感应电机的定子和转子电流作为状态变量，推导出了三相感应电机在α-β坐标系下的状态方程和输出方程。然后，采用中心差分扩展卡尔曼滤波算法实现对三相感应电机转速和转矩的解算。仿真结果表明，与扩展卡尔曼滤波算法相比，中心差分扩展卡尔曼滤波算法对电机运行状态的变化具有更好的跟随性能及更快的收敛速度，能够准确的估计三相感应电机的转速和转矩。
Triangle Counting in Dynamic Graph Streams
Bulteau, Laurent; Froese, Vincent; Pagh, Rasmus;
2015-01-01
Estimating the number of triangles in graph streams using a limited amount of memory has become a popular topic in the last decade. Different variations of the problem have been studied, depending on whether the graph edges are provided in an arbitrary order or as incidence lists. However...... combining sampling of vertex triples and sparsification of the input graph. In the course of the analysis of the algorithm we present a lower bound on the number of pairwise independent 2-paths in general graphs which might be of independent interest. At the end of the paper we discuss lower bounds...
Analysis of hydraulic characteristics for stream diversion in small stream
Ahn, Sang-Jin; Jun, Kye-Won [Chungbuk National University, Cheongju(Korea)
2001-10-31
This study is the analysis of hydraulic characteristics for stream diversion reach by numerical model test. Through it we can provide the basis data in flood, and in grasping stream flow characteristics. Analysis of hydraulic characteristics in Seoknam stream were implemented by using computer model HEC-RAS(one-dimensional model) and RMA2(two-dimensional finite element model). As a result we became to know that RMA2 to simulate left, main channel, right in stream is more effective method in analysing flow in channel bends, steep slope, complex bed form effect stream flow characteristics, than HEC-RAS. (author). 13 refs., 3 tabs., 5 figs.
2016-06-06
ELC – Extended Life Coolant SCA – Supplemental Coolant Additive SOW – Scope of Work SwRI – Southwest Research Institute TARDEC – Tank Automotive...ethylene or propylene glycol and 35% extended life coolant #1 (ELC1) with a balance of water. At a higher ELC1 content of 45% or 50%, the mass loss...UNCLASSIFIED TABLE OF CONTENTS EXTENDED LIFE COOLANT TESTING INTERIM REPORT TFLRF No. 478 by Gregory A. T. Hansen Edwin A
Extended icosahedral structures
Jaric, Marko V
1989-01-01
Extended Icosahedral Structures discusses the concepts about crystal structures with extended icosahedral symmetry. This book is organized into six chapters that focus on actual modeling of extended icosahedral crystal structures. This text first presents a tiling approach to the modeling of icosahedral quasiperiodic crystals. It then describes the models for icosahedral alloys based on random connections between icosahedral units, with particular emphasis on diffraction properties. Other chapters examine the glassy structures with only icosahedral orientational order and the extent of tra
Big Data Mining: Tools & Algorithms
Adeel Shiraz Hashmi
2016-03-01
Full Text Available We are now in Big Data era, and there is a growing demand for tools which can process and analyze it. Big data analytics deals with extracting valuable information from that complex data which can’t be handled by traditional data mining tools. This paper surveys the available tools which can handle large volumes of data as well as evolving data streams. The data mining tools and algorithms which can handle big data have also been summarized, and one of the tools has been used for mining of large datasets using distributed algorithms.
Hill climbing algorithms and trivium
Borghoff, Julia; Knudsen, Lars Ramkilde; Matusiewicz, Krystian
2011-01-01
This paper proposes a new method to solve certain classes of systems of multivariate equations over the binary field and its cryptanalytical applications. We show how heuristic optimization methods such as hill climbing algorithms can be relevant to solving systems of multivariate equations....... A characteristic of equation systems that may be efficiently solvable by the means of such algorithms is provided. As an example, we investigate equation systems induced by the problem of recovering the internal state of the stream cipher Trivium. We propose an improved variant of the simulated annealing method...
Hill climbing algorithms and trivium
Borghoff, Julia; Knudsen, Lars Ramkilde; Matusiewicz, Krystian
2011-01-01
This paper proposes a new method to solve certain classes of systems of multivariate equations over the binary field and its cryptanalytical applications. We show how heuristic optimization methods such as hill climbing algorithms can be relevant to solving systems of multivariate equations....... A characteristic of equation systems that may be efficiently solvable by the means of such algorithms is provided. As an example, we investigate equation systems induced by the problem of recovering the internal state of the stream cipher Trivium. We propose an improved variant of the simulated annealing method...
Meteor Stream Membership Criteria
Klacka, J
2000-01-01
Criteria for the membership of individual meteors in meteor streams are discussed from the point of view of their mathematical and also physical properties. Discussion is also devoted to the motivation. It is shown that standardly used criteria (mainly D-criterion of Southworth and Hawkins, 1963) have unusual mathematical properties in the sense of a term ``distance'', between points in a phase space, and, physical motivation and realization for the purpose of obtaining their final form is not natural and correct, and, moreover, they lead also to at least surprising astrophysical results. General properties of possible criteria are discussed. A new criterion for the membership in meteor streams is suggested. It is based on probability theory. Finally, a problem of meteor orbit determination for known parent body is discussed.
Parallel Algorithms for Computer Vision.
1989-01-01
developed algorithms for sev- stage at which they are used, for example by a eral early vision processes, such as edge detection, stere - navigation...system operates by receiving a stream of instructions from its front end computer. A microcontroller receives the instructions, expands each of them...instructions flow into the Connection Machine hardware from the front end. These I macro-instructions are sent to a microcontroller , which expands them
An Adaptive Algorithm for Finding Frequent Sets in Landmark Windows
Dang, Xuan-Hong; Ong, Kok-Leong; Lee, Vincent
2012-01-01
We consider a CPU constrained environment for finding approximation of frequent sets in data streams using the landmark window. Our algorithm can detect overload situations, i.e., breaching the CPU capacity, and sheds data in the stream to “keep up”. This is done within a controlled error thresho...
System architecture for ubiquitous live video streaming in university network environment
Dludla, AG
2013-09-01
Full Text Available an architecture which supports ubiquitous live streaming for university or campus networks using a modified bluetooth inquiry mechanism with extended ID, integrated end-user device usage and adaptation to heterogeneous networks. Riding on that architecture...
Heuristic for Critical Machine Based a Lot Streaming for Two-Stage Hybrid Production Environment
Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.
2017-03-01
Lot streaming in Hybrid flowshop [HFS] is encountered in many real world problems. This paper deals with a heuristic approach for Lot streaming based on critical machine consideration for a two stage Hybrid Flowshop. The first stage has two identical parallel machines and the second stage has only one machine. In the second stage machine is considered as a critical by valid reasons these kind of problems is known as NP hard. A mathematical model developed for the selected problem. The simulation modelling and analysis were carried out in Extend V6 software. The heuristic developed for obtaining optimal lot streaming schedule. The eleven cases of lot streaming were considered. The proposed heuristic was verified and validated by real time simulation experiments. All possible lot streaming strategies and possible sequence under each lot streaming strategy were simulated and examined. The heuristic consistently yielded optimal schedule consistently in all eleven cases. The identification procedure for select best lot streaming strategy was suggested.
Puig, A.
2016-07-01
The LHCb experiment will record an unprecedented dataset of beauty and charm hadron decays during Run II of the LHC, set to take place between 2015 and 2018. A key computing challenge is to store and process this data, which limits the maximum output rate of the LHCb trigger. So far, LHCb has written out a few kHz of events containing the full raw sub-detector data, which are passed through a full offline event reconstruction before being considered for physics analysis. Charm physics in particular is limited by trigger output rate constraints. A new streaming strategy includes the possibility to perform the physics analysis with candidates reconstructed in the trigger, thus bypassing the offline reconstruction. In the Turbo stream the trigger will write out a compact summary of physics objects containing all information necessary for analyses. This will allow an increased output rate and thus higher average efficiencies and smaller selection biases. This idea will be commissioned and developed during 2015 with a selection of physics analyses. It is anticipated that the turbo stream will be adopted by an increasing number of analyses during the remainder of LHC Run II (2015-2018) and ultimately in Run III (starting in 2020) with the upgraded LHCb detector.
Bossart, S.J.; Cicero, D.C.; Zeh, C.M.; Bedick, R.C.
1990-08-01
This report describes the current status and recent accomplishments of gas stream cleanup (GSCU) projects sponsored by the Morgantown Energy Technology Center (METC) of the US Department of Energy (DOE). The primary goal of the Gas Stream Cleanup Program is to develop contaminant control strategies that meet environmental regulations and protect equipment in advanced coal conversion systems. Contaminant control systems are being developed for integration into seven advanced coal conversion processes: Pressurized fludized-bed combustion (PFBC), Direct coal-fueled turbine (DCFT), Intergrated gasification combined-cycle (IGCC), Gasification/molten carbonate fuel cell (MCFC), Gasification/solid oxide fuel cell (SOFC), Coal-fueled diesel (CFD), and Mild gasification (MG). These advanced coal conversion systems present a significant challenge for development of contaminant control systems because they generate multi-contaminant gas streams at high-pressures and high temperatures. Each of the seven advanced coal conversion systems incorporates distinct contaminant control strategies because each has different contaminant tolerance limits and operating conditions. 59 refs., 17 figs., 5 tabs.
Bossart, S.J.; Cicero, D.C.; Zeh, C.M.; Bedick, R.C.
1990-08-01
This report describes the current status and recent accomplishments of gas stream cleanup (GSCU) projects sponsored by the Morgantown Energy Technology Center (METC) of the US Department of Energy (DOE). The primary goal of the Gas Stream Cleanup Program is to develop contaminant control strategies that meet environmental regulations and protect equipment in advanced coal conversion systems. Contaminant control systems are being developed for integration into seven advanced coal conversion processes: Pressurized fludized-bed combustion (PFBC), Direct coal-fueled turbine (DCFT), Intergrated gasification combined-cycle (IGCC), Gasification/molten carbonate fuel cell (MCFC), Gasification/solid oxide fuel cell (SOFC), Coal-fueled diesel (CFD), and Mild gasification (MG). These advanced coal conversion systems present a significant challenge for development of contaminant control systems because they generate multi-contaminant gas streams at high-pressures and high temperatures. Each of the seven advanced coal conversion systems incorporates distinct contaminant control strategies because each has different contaminant tolerance limits and operating conditions. 59 refs., 17 figs., 5 tabs.
Puig, A., E-mail: albert.puig@cern.ch
2016-07-11
The LHCb experiment will record an unprecedented dataset of beauty and charm hadron decays during Run II of the LHC, set to take place between 2015 and 2018. A key computing challenge is to store and process this data, which limits the maximum output rate of the LHCb trigger. So far, LHCb has written out a few kHz of events containing the full raw sub-detector data, which are passed through a full offline event reconstruction before being considered for physics analysis. Charm physics in particular is limited by trigger output rate constraints. A new streaming strategy includes the possibility to perform the physics analysis with candidates reconstructed in the trigger, thus bypassing the offline reconstruction. In the Turbo stream the trigger will write out a compact summary of physics objects containing all information necessary for analyses. This will allow an increased output rate and thus higher average efficiencies and smaller selection biases. This idea will be commissioned and developed during 2015 with a selection of physics analyses. It is anticipated that the turbo stream will be adopted by an increasing number of analyses during the remainder of LHC Run II (2015–2018) and ultimately in Run III (starting in 2020) with the upgraded LHCb detector.
Poul Grønkjær
2004-05-01
Full Text Available
Første gang publiceret i UNEV nr. 3: Internet Video: Teknik og pædagogik mødes på nettet, april - juni 2004, red. Jens Dørup. ISSN 1603-5518.
E-learning Lab på Aalborg Universitet har i forbindelse med forskningsprojektet Virtuelle Læringsformer og Læringsmiljøer foretaget en række praktiske eksperimenter med streaming-video produktioner. Hensigten med denne artikel er at formidle disse erfaringer. Artiklen beskriver hele produktionsforløbet: fra ide til færdigt produkt, forskellige typer af præsentationer, dramaturgiske overvejelser samt en konceptskitse. Streaming-video teknologien er nu så udviklet med et så tilfredsstillende audiovisuelt udtryk at vi kan begynde at fokusere på, hvilket indhold der er velegnet til at blive gjort tilgængeligt uafhængigt af tid og sted. Afslutningsvis er der en række kildehenvisninger, blandt andet en oversigt over de streaming-video produktioner, som denne artikel bygger på.
Ecoenzymatic Stoichiometry of Stream Sediments with Comparison to Terrestrial Soils
In this study, we extend the development of ecoenzymatic stoichiometry to the surface sediments of stream ecosystems using data collected in a nationwide survey. The data set is larger and more comprehensive than those used in our previous studies. The data include the first broa...
Ecoenzymatic Stoichiometry of Stream Sediments with Comparison to Terrestrial Soils
In this study, we extend the development of ecoenzymatic stoichiometry to the surface sediments of stream ecosystems using data collected in a nationwide survey. The data set is larger and more comprehensive than those used in our previous studies. The data include the first broa...
The Nature and Orbit of the Ophiuchus Stream
Sesar, B; Bernard, E J; Caldwell, N; Cohen, J G; Fouesneau, M; Johnson, C I; Ness, M; Ferguson, A M N; Martin, N F; Rix, H -W; Schlafly, E F; Burgett, W S; Chambers, K C; Flewelling, H; Hodapp, K W; Kaiser, N; Magnier, E A; Platais, I; Tonry, J L; Waters, C; Wyse, R F G
2015-01-01
The Ophiuchus stream is the most recently discovered stellar tidal stream in the Milky Way (Bernard et al. 2014). We present high-quality spectroscopic data for 14 stream member stars obtained using the Keck and MMT telescopes. We confirm the stream as a fast moving ($v_{los}\\sim290$ km s$^{-1}$), kinematically-cold group ($\\sigma_{v_{los}}\\lesssim1$ km s$^{-1}$) of $\\alpha-$enhanced and metal-poor stars (${\\rm [\\alpha/Fe]\\sim0.4}$ dex, ${\\rm [Fe/H]\\sim-2.0}$ dex). Using a probabilistic technique, we model the stream simultaneously in line-of-sight velocity, color-magnitude, coordinate, and proper motion space, and so determine its distribution in 6D phase-space. We find that that the stream extends in distance from 8 to 9.5 kpc from the Sun; it is 50 times longer than wide, merely appearing highly foreshortened in projection. The analysis of the stellar population contained in the stream suggests that it is $\\sim13$ Gyr old, and that its initial stellar mass was $\\sim2\\times10^4$ $M_\\sun$ (or at least $\\ga4\\...
Mass streams for spacecraft propulsion and energy generation
Hammer, J H
2005-08-31
A speculative propulsion concept is presented, based on accelerating a spacecraft by impact of a stream of matter in relative motion with respect to the spacecraft. To accelerate the stream to the needed velocity the stream mass is contained in a transit vehicle, launched at low velocity and hence low energy cost, and then sent on a trajectory with near encounters of the planets for gravitational assist. The mass arrives at Earth or wherever the propellant is needed at much higher velocity and kinetic energy, where it is released into an extended stream suitable for propulsion. The stream, moving at a relative velocity in the range of 10 to 30km/s, should be capable of both high thrust and high specific impulse. Means of limiting the transverse expansion of the stream during release and for the {approx}1000 seconds duration of impact are a critical requirement for practicality of the concept. The scheme could potentially lead to a virtually unlimited energy source. One can imagine using a portion of one stream to launch another, larger payload on a similar trajectory. This creates, in effect, an energy amplifier extracting energy from the orbital motions of the planets. The gain of the energy amplifier is only limited by the capacity to prepare mass in transit vehicles.
Destabilization of the Northeast Greenland Ice Stream
Korsgaard, N. J.; Khan, Shfaqat Abbas; Kjaer, K. H.
. Here, we reveal that the Northeast Greenland Ice Stream (NEGIS), which extends more than 600 km into the interior of the ice sheet, is now undergoing dynamic thinning after more than a quarter of a century of stability. This sector of the GrIS is of particular interest in sea level projections, because...... the glacier flows into a large submarine basin with a negative bed slope near the grounding line. Our findings unfold the next step in mass loss of the GrIS as we show a heightened risk of rapid sustained loss from Northeast Greenland on top of the thinning in Southeast and Northwestern Greenland....
Clustering Time Series Data Stream - A Literature Survey
Kavitha, V
2010-01-01
Mining Time Series data has a tremendous growth of interest in today's world. To provide an indication various implementations are studied and summarized to identify the different problems in existing applications. Clustering time series is a trouble that has applications in an extensive assortment of fields and has recently attracted a large amount of research. Time series data are frequently large and may contain outliers. In addition, time series are a special type of data set where elements have a temporal ordering. Therefore clustering of such data stream is an important issue in the data mining process. Numerous techniques and clustering algorithms have been proposed earlier to assist clustering of time series data streams. The clustering algorithms and its effectiveness on various applications are compared to develop a new method to solve the existing problem. This paper presents a survey on various clustering algorithms available for time series datasets. Moreover, the distinctiveness and restriction ...
Solvability of Extended General Strongly Mixed Variational Inequalities
Balwant Singh Thakur
2013-10-01
Full Text Available In this paper, a new class of extended general strongly mixed variational inequalities is introduced and studied in Hilbert spaces. An existence theorem of solution is established and using resolvent operator technique, a new iterative algorithm for solving the extended general strongly mixed variational inequality is suggested. A convergence result for the iterative sequence generated by the new algorithm is also established.
Design and Implementation of Streaming Media Server Cluster Based on FFMpeg
Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao
2015-01-01
Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system. PMID:25734187
Design and implementation of streaming media server cluster based on FFMpeg.
Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao
2015-01-01
Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system.
Dynamically Computing Approximate Frequency Counts in Sliding Window over Data Stream
无
2006-01-01
This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constructs sub-windows and deletes expired sub-windows periodically in sliding window, and each sub-window maintains a summary data structure. The first algorithm outputs at most 1/ε + 1 elements for frequency queries over the most recent N elements. The second algorithm adapts multiple levels method to deal with data stream. Once the sketch of the most recent N elements has been constructed, the second algorithm can provides the answers to the frequency queries over the most recent n(n≤N) elements. The second algorithm outputs at most 1/ε+2 elements. The analytical and experimental results show that our algorithms are accurate and effective.
Extended Logistic Chaotic Sequence and Its Performance Analysis
ZHANG Xuefeng; FAN Jiulun
2007-01-01
In order to improve performance and security of image encryption algorithm effectively based on chaotic sequences, an extended chaotic sequence generating method is presented based on logistic chaotic system using Bernstein form Bezier curve generating algorithm. In order to test the pseudorandom performance of the extended chaotic sequence, we also analyze random performance, autocorrelation performance, and balance performance of the extended chaotic sequence. Simulation results show that the extended chaotic sequence generated using our method is pseudorandom and its correlation performance and balance performance are good. As an application, we apply the extended chaotic sequence in image encryption algorithm, the simulation results show that the performance of the encrypted image using our method is better than that using logistic chaotic sequence.
Quantum Extended Supersymmetries
Grigore, D R; Grigore, Dan Radu; Scharf, Gunter
2003-01-01
We analyse some quantum multiplets associated with extended supersymmetries. We study in detail the general form of the causal (anti)commutation relations. The condition of positivity of the scalar product imposes severe restrictions on the (quantum) model. It is problematic if one can find out quantum extensions of the standard model with extended supersymmetries.
Synthetic Aperture Radar Raw Signals Simulation of Extended Scenes
Sun Jin-yao; Sun Hong
2004-01-01
A synthetic aperture radar (SAR) raw signal simulation algorithm for extended scenes is presented. This algorithm is based on the SAR two-dimensional system transform function (STF). To cope with range-variant nature of SAR STF and increase the speed of this algorithm, new formulas for range-variant phase corrections in range Doppler (RD) domain are developed. In this way, many azimuth lines can be simulated with the same SAR STF. It only needs twodimensional fast Fourier transform code and complex multiplications. Comparing with time-domain simulation algorithm, it is very simple and thus efficient. Simulation results have shown that this algorithm is accurate and efficient.
Generalized fairing algorithm of parametric cubic splines
WANG Yuan-jun; CAO Yuan
2006-01-01
Kjellander has reported an algorithm for fairing uniform parametric cubic splines. Poliakoff extended Kjellander's algorithm to non-uniform case. However, they merely changed the bad point's position, and neglected the smoothing of tangent at bad point. In this paper, we present a fairing algorithm that both changed point's position and its corresponding tangent vector. The new algorithm possesses the minimum property of energy. We also proved Poliakoff's fairing algorithm is a deduction of our fairing algorithm. Several fairing examples are given in this paper.
Extended Theories of Gravitation
Fatibene Lorenzo
2013-09-01
Full Text Available Extended theories of gravitation are naturally singled out by an analysis inspired by the Ehelers-Pirani-Schild framework. In this framework the structure of spacetime is described by a Weyl geometry which is enforced by dynamics. Standard General Relativity is just one possible theory within the class of extended theories of gravitation. Also all Palatini f(R theories are shown to be extended theories of gravitation. This more general setting allows a more general interpretation scheme and more general possible couplings between gravity and matter. The definitions and constructions of extended theories will be reviewed. A general interpretation scheme will be considered for extended theories and some examples will be considered.
Streaming Compression of Tetrahedral Volume Meshes
Isenburg, M; Lindstrom, P; Gumhold, S; Shewchuk, J
2005-11-21
Geometry processing algorithms have traditionally assumed that the input data is entirely in main memory and available for random access. This assumption does not scale to large data sets, as exhausting the physical memory typically leads to IO-inefficient thrashing. Recent works advocate processing geometry in a 'streaming' manner, where computation and output begin as soon as possible. Streaming is suitable for tasks that require only local neighbor information and batch process an entire data set. We describe a streaming compression scheme for tetrahedral volume meshes that encodes vertices and tetrahedra in the order they are written. To keep the memory footprint low, the compressor is informed when vertices are referenced for the last time (i.e. are finalized). The compression achieved depends on how coherent the input order is and how many tetrahedra are buffered for local reordering. For reasonably coherent orderings and a buffer of 10,000 tetrahedra, we achieve compression rates that are only 25 to 40 percent above the state-of-the-art, while requiring drastically less memory resources and less than half the processing time.
Audio Video Compression Stream Synthesis and Implementation
徐燕凌; 方向忠; 周源华
2004-01-01
Multiplex of digital streams is one of the key technologies in audio video communication, and determines audio-video quality. A design scheme for an MPEG2 compliant digital television system including audio-video encoding and multiplexing was implemented. The principles and elements of system layer stream synthesis were analyzed. The key technologies of video and audio PES packetization were discussed, such as stream structure,scheduling matching, audio-video synchronization, data flow and buffering. DSP and FPGA are combined to construct header information and packet structure. The substitution of traditional RAM or PLD results in high operational efficiency and saves memory space. A scheduling algorithm was introduced for PES coding, using the monitor information of PES buffers. DTS is generated by multiplexer to guarantee synchronization. The system is not only simple but also stable, and maintains synchronization constraints of the standard. It supports both analogy and digital audio-video source input, and provides real-time MPEG2 compliant TS/PS output. It has perfect performance and meets the national broadcasting requirements.
Conventional to Cloud: Detailed survey and comparative study of multimedia streaming rate Adaptation
Selvaraj Kesavan
2014-06-01
Full Text Available Infotainment and telecommunication industry is fast evolving towards personalized network connectivity and newer applications services ranging from music playback to ever changing telephony applications. Streaming is the key services which enables the users to view real time multimedia content on-the-go anywhere and everywhere. In streaming, quality of service is a major concern in the increasing network traffic and high user demand. Rate adaptation is crucial process to dynamically evaluate, select and control the media rate based on the network deviation, processing capability and to ensure the best class of service, user experience to the consumer. In this paper, we focuses on the comprehensive survey of existing rate adaptation algorithms used in conventional, adaptive, cloud assisted streaming methods and lists the merits ,limitations of the algorithms. With an experiment setup, we also evaluate and analyze the rate adaptation behavior of the streaming techniques using streaming client.
Remembering the Important Things: Semantic Importance in Stream Reasoning
Yan, Rui; Greaves, Mark T.; Smith, William P.; McGuinness, Deborah L.
2016-11-04
Reasoning and querying over data streams rely on the abil- ity to deliver a sequence of stream snapshots to the processing algo- rithms. These snapshots are typically provided using windows as views into streams and associated window management strategies. Generally, the goal of any window management strategy is to preserve the most im- portant data in the current window and preferentially evict the rest, so that the retained data can continue to be exploited. A simple timestamp- based strategy is rst-in-rst-out (FIFO), in which items are replaced in strict order of arrival. All timestamp-based strategies implicitly assume that a temporal ordering reliably re ects importance to the processing task at hand, and thus that window management using timestamps will maximize the ability of the processing algorithms to deliver accurate interpretations of the stream. In this work, we explore a general no- tion of semantic importance that can be used for window management for streams of RDF data using semantically-aware processing algorithms like deduction or semantic query. Semantic importance exploits the infor- mation carried in RDF and surrounding ontologies for ranking window data in terms of its likely contribution to the processing algorithms. We explore the general semantic categories of query contribution, prove- nance, and trustworthiness, as well as the contribution of domain-specic ontologies. We describe how these categories behave using several con- crete examples. Finally, we consider how a stream window management strategy based on semantic importance could improve overall processing performance, especially as available window sizes decrease.
Fast compressed domain motion detection in H.264 video streams for video surveillance applications
Szczerba, Krzysztof; Forchhammer, Søren; Støttrup-Andersen, Jesper;
2009-01-01
This paper presents a novel approach to fast motion detection in H.264/MPEG-4 advanced video coding (AVC) compressed video streams for IP video surveillance systems. The goal is to develop algorithms which may be useful in a real-life industrial perspective by facilitating the processing of large...... numbers of video streams on a single server. The focus of the work is on using the information in coded video streams to reduce the computational complexity and memory requirements, which translates into reduced hardware requirements and costs. The devised algorithm detects and segments activity based...... on motion vectors embedded in the video stream without requiring a full decoding and reconstruction of video frames. To improve the robustness to noise, a confidence measure based on temporal and spatial clues is introduced to increase the probability of correct detection. The algorithm was tested on indoor...
The Orbit of the Orphan Stream
Newberg, Heidi Jo; Willett, Benjamin A.; Yanny, Brian; Xu, Yan
2010-01-01
and correspondingly larger halo masses. Distinguishing between different classes of models requires data over a larger range of distances. The Orphan Stream is projected to extend to 90 kpc from the Galactic center, and measurements of these distant parts of the stream would be a powerful probe of the mass of the Milky Way.
Stellar streams around the Magellanic Clouds
Belokurov, Vasily
2015-01-01
Using Blue Horizontal Branch stars identified in the Dark Energy Survey Year 1 data, we report the detection of an extended and lumpy stellar debris distribution around the Magellanic Clouds. At the heliocentric distance of the Clouds, overdensities of BHBs are seen to reach at least to ~30 degrees, and perhaps as far as ~50 degrees from the LMC. In 3D, the stellar halo is traceable to between 25 and 50 kpc from the LMC. We catalogue the most significant of the stellar sub-structures revealed, and announce the discovery of a number of narrow streams and diffuse debris clouds. Two narrow streams appear approximately aligned with the Magellanic Clouds' proper motion. Moreover, one of these overlaps with the gaseous Magellanic Stream on the sky. Curiously, two diffuse BHB agglomerations seem coincident with several of the recently discovered DES satellites. Given the enormous size and the conspicuous lumpiness of the LMC's stellar halo, we speculate that the dwarf could easily have been more massive than previou...
ALGORITHM FOR IMAGE MIXING AND ENCRYPTION
Ayman M. Abdalla
2013-04-01
Full Text Available This new algorithm mixes two or more images of different types and sizes by employing a shuffling procedure combined with S-box substitution to perform lossless image encryption. This combines stream cipher with block cipher, on the byte level, in mixing the images. When this algorithm was implemented, empirical analysis using test images of different types and sizes showed that it is effective and resistant to attacks.
The dialogically extended mind
Fusaroli, Riccardo; Gangopadhyay, Nivedita; Tylén, Kristian
2014-01-01
A growing conceptual and empirical literature is advancing the idea that language extends our cognitive skills. One of the most influential positions holds that language – qua material symbols – facilitates individual thought processes by virtue of its material properties. Extending upon this model......, we argue that language enhances our cognitive capabilities in a much more radical way: The skilful engagement of public material symbols facilitates evolutionarily unprecedented modes of collective perception, action and reasoning (interpersonal synergies) creating dialogically extended minds. We...... relate our approach to other ideas about collective minds and review a number of empirical studies to identify the mechanisms enabling the constitution of interpersonal cognitive systems....
The Extended Enterprise concept
Larsen, Lars Bjørn; Vesterager, Johan; Gobbi, Chiara
1999-01-01
This paper provides an overview of the work that has been done regarding the Extended Enterprise concept in the Common Concept team of Globeman 21 including references to results deliverables concerning the development of the Extended Enterprise concept. The first section presents the basic concept...... picture from Globeman21, which illustrates the Globeman21 way of realising the Extended Enterprise concept. The second section presents the Globeman21 EE concept in a life cycle perspective, which to a large extent is based on the thoughts and ideas behind GERAM (ISO/DIS 15704)....
Streaming-based verification of XML signatures in SOAP messages
Somorovsky, Juraj; Jensen, Meiko; Schwenk, Jörg
2010-01-01
WS-Security is a standard providing message-level security in Web Services. Therewith, it ensures their integrity, confidentiality, and authenticity. However, using sophisticated security algorithms can lead to high memory consumptions and long evaluation times. In combination with the standard DOM...... approach for XML processing, the Web Services servers easily become a target of Denial-of-Service attacks. We present a solution for these problems: an external streaming-based WS-Security Gateway. Our implementation is capable of processing XML Signatures in SOAP messages using a streaming-based approach...
Realization of a Quantum Scheduling Algorithm Using Nuclear Magnetic Resonance
ZHANG Jing-Fu; DENG Zhi-Wei; PAN Yan-Na; LU Zhi-Heng
2004-01-01
The quantum scheduling algorithm proposed by Grover is generalized to extend its scope of applications. The generalized algorithm proposed here is realized on a nuclear magnetic resonance quantum computer. The experimental results show that the generalized algorithm can work efficiently in the case that Grover's scheduling algorithm is completely invalid, and represent the quantum advantages when qubits replace classical bits.
The California stream quality assessment
Van Metre, Peter C.; Egler, Amanda L.; May, Jason T.
2017-03-06
In 2017, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project is assessing stream quality in coastal California, United States. The USGS California Stream Quality Assessment (CSQA) will sample streams over most of the Central California Foothills and Coastal Mountains ecoregion (modified from Griffith and others, 2016), where rapid urban growth and intensive agriculture in the larger river valleys are raising concerns that stream health is being degraded. Findings will provide the public and policy-makers with information regarding which human and natural factors are the most critical in affecting stream quality and, thus, provide insights about possible approaches to protect the health of streams in the region.
The Southeast Stream Quality Assessment
Van Metre, Peter C.; Journey, Celeste
2014-01-01
In 2014, the U.S. Geological Survey (USGS) National Water-Quality Assessment Program (NAWQA) is assessing stream quality across the Piedmont and southern Appalachian Mountains in the southeastern United States. The goal of the Southeast Stream Quality Assessment (SESQA) is to characterize multiple water-quality factors that are stressors to aquatic life—contaminants, nutrients, sediment, and streamflow alteration—and the relation of these stressors to ecological conditions in streams throughout the region. Findings will provide communities and policymakers with information on which human and environmental factors are the most critical in controlling stream quality and, thus, provide insights about possible approaches to protect or improve stream quality. The SESQA study will be the second regional study by the NAWQA program, and it will be of similar design and scope as the Midwest Stream Quality Assessment conducted in 2013 (Van Metre and others, 2012).
Using electronic conductivity and hardness data for rapid assessment of stream water quality.
Thompson, Michael Y; Brandes, David; Kney, Arthur D
2012-08-15
A graphical screening method was previously developed by Kney and Brandes (2007) for assessing stream water quality data using electronic conductivity (EC) and alkalinity data. The method was aimed at providing citizen scientists involved in stream monitoring programs with a relatively simple way to interpret EC data. The method utilizes a plot of EC against concurrent alkalinity data, and is used to distinguish EC values for impacted or degraded streams from those that can be considered background values in a particular geologic setting. The method performs well in areas underlain by carbonate bedrock, as streams in those areas characteristically have EC values that are strongly correlated with alkalinity. However, in areas of low stream alkalinity (less than approximately 50 mg/L as CaCO(3)), the Kney and Brandes (2007) method was found to be much less effective in identifying impacted streams. This paper extends the graphical screening approach to streams with low alkalinity, specifically regions underlain by clastic sedimentary or crystalline bedrock, by using the strong correlation between EC and total hardness (TH). A baseline relationship of EC vs. TH is developed using surface water chemistry data from Hydrologic Benchmark Network streams (deemed as having minimal anthropogenic impacts) and regional groundwater quality data. The usefulness of the method is demonstrated by application to publicly available stream chemistry data and to field data collected from streams of eastern Pennsylvania under baseflow conditions. Results demonstrate that for streams with alkalinity alkalinity-based method of Kney and Brandes (2007).
Rational extended thermodynamics
Müller, Ingo
1998-01-01
Ordinary thermodynamics provides reliable results when the thermodynamic fields are smooth, in the sense that there are no steep gradients and no rapid changes. In fluids and gases this is the domain of the equations of Navier-Stokes and Fourier. Extended thermodynamics becomes relevant for rapidly varying and strongly inhomogeneous processes. Thus the propagation of high frequency waves, and the shape of shock waves, and the regression of small-scale fluctuation are governed by extended thermodynamics. The field equations of ordinary thermodynamics are parabolic while extended thermodynamics is governed by hyperbolic systems. The main ingredients of extended thermodynamics are • field equations of balance type, • constitutive quantities depending on the present local state and • entropy as a concave function of the state variables. This set of assumptions leads to first order quasi-linear symmetric hyperbolic systems of field equations; it guarantees the well-posedness of initial value problems and f...
Gaspa, M. C.; De La Cruz, R. M.; Olfindo, N. T.; Borlongan, N. J. B.; Perez, A. M. C.
2016-10-01
Stream network delineation based on LiDAR-derived digital terrain model (DTM) may produce stream segments that are inexistent or incomplete because of limitations imposed by extraction procedure, terrain and data. The applicability of a common threshold value in defining streams such as those implemented through the D8 algorithm also remains in question because the threshold varies depending on the geomorphology of the area. Flat areas and improper hydrologic conditioning produce erratic stream network. To counteract these limitations, this study proposes a workflow that improves the stream network produced by the D8 algorithm. It incorporates user-defined channel initiation points as inputs to a tool developed to automatically trace the flow of water into the next actual stream segment. Spurious streams along digital dams and flat areas are also manually reshaped. The proposed workflow is implemented in Iligan River Basin, Philippines using LiDARderived DTM of 1-meter resolution. The Flow Path Tracing (FPT) method counteracts the limits imposed by extraction procedure, terrain and data. It is applicable to different typologies of watersheds by eliminating the need to use site-specific threshold in determining streams. FPT is implemented as a Phyton script to automate the tracing of the streams using the flow direction raster. The FPT method is compared to the blue line digitization and the D8 method using morphometric parameters, such as stream number, stream order and stream length, to assess its performance. Results show that streams derived from the FPT method has higher stream order, number and length. An accuracy of 93.5% produced from field validation of the FPT method's streams strengthens the findings that integrating manual channel head initiation and flow path tracing can be used for nationwide extraction of streams using LiDAR-derived-DTM in the Philippines.
Puig Navarro, Albert
2016-01-01
The LHCb experiment will record an unprecedented dataset of beauty and charm hadron decays during Run II of the LHC, set to take place between 2015 and 2018. A key computing challenge is to store and process this data, which limits the maximum output rate of the LHCb trigger. So far, LHCb has written out a few kHz of events containing the full raw sub-detector data, which are passed through a full offline event reconstruction before being considered for physics analysis. Charm physics in particular is limited by trigger output rate constraints. A new streaming strategy includes the possibility to perform the physics analysis with candidates reconstructed in the trigger, thus bypassing the offline reconstruction. In the Turbo stream the trigger will write out a compact summary of physics objects containing all information necessary for analyses. This will allow an increased output rate and thus higher average efficiencies and smaller selection biases. This idea will be commissioned and developed during 2015 wi...
Benson, Sean; Vesterinen, Mika Anton; Williams, John Michael
2015-01-01
The LHCb experiment will record an unprecedented dataset of beauty and charm hadron decays during Run II of the LHC, set to take place between 2015 and 2018. A key computing challenge is to store and process this data, which limits the maximum output rate of the LHCb trigger. So far, LHCb has written out a few kHz of events containing the full raw sub-detector data, which are passed through a full offline event reconstruction before being considered for physics analysis. Charm physics in particular is limited by trigger output rate constraints. A new streaming strategy includes the possibility to perform the physics analysis with candidates reconstructed in the trigger, thus bypassing the offline reconstruction and discarding the raw event. In the Turbo stream the trigger will write out a compact summary of physics objects containing all information necessary for analyses, and this will allow an increased output rate and thus higher average efficiencies and smaller selection biases. This idea will be commissi...
Benson, Sean
2015-01-01
The LHCb experiment will record an unprecedented dataset of beauty and charm hadron decays during Run II of the LHC, set to take place between 2015 and 2018. A key computing challenge is to store and process this data, which limits the maximum output rate of the LHCb trigger. So far, LHCb has written out a few kHz of events containing the full raw sub-detector data, which are passed through a full offline event reconstruction before being considered for physics analysis. Charm physics in particular is limited by trigger output rate constraints. A new streaming strategy includes the possibility to perform the physics analysis with candidates reconstructed in the trigger, thus bypassing the offline reconstruction. In the "turbo stream" the trigger will write out a compact summary of "physics" objects containing all information necessary for analyses, and this will allow an increased output rate and thus higher average efficiencies and smaller selection biases. This idea will be commissioned and developed during...
Symmetric Extended Ockham Algebras
T.S. Blyth; Jie Fang
2003-01-01
The variety eO of extended Ockham algebras consists of those algealgebra with an additional endomorphism k such that the unary operations f and k commute. Here, we consider the cO-algebras which have a property of symmetry. We show that there are thirty two non-isomorphic subdirectly irreducible symmetric extended MS-algebras and give a complete description of them.2000 Mathematics Subject Classification: 06D15, 06D30
Algorithms and estimators for summarization of unaggregated data streams
Cohen, Edith; Duffield, Nick; Kaplan, Haim
2014-01-01
Abstract Statistical summaries of IP traffic are at the heart of network operation and are used to recover aggregate information on subpopulations of flows. It is therefore of great importance to collect the most accurate and informative summaries given the router's resource constraints. A summar......Abstract Statistical summaries of IP traffic are at the heart of network operation and are used to recover aggregate information on subpopulations of flows. It is therefore of great importance to collect the most accurate and informative summaries given the router's resource constraints...
X-Graphs: Language and Algorithms for Heterogeneous Graph Streams
2017-09-01
IN ACCORDANCE WITH ASSIGNED DISTRIBUTION STATEMENT. FOR THE CHIEF ENGINEER: / S / / S / JOHN SPINA MICHAEL J. WESSING Work Unit Manager Deputy...OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON JOHN SPINA a. REPORT U b. ABSTRACT U c. THIS PAGE U...ISCA : 43rd International Symposium on Computer Architecture, June 2016. 5. R. Prabhakar, D. Koeplinger, K. J. Brown , H. Lee, C. De Sa, C
Mining developer communication data streams
Connor, Andy M.; Jacqui Finlay; Russel Pears
2014-01-01
This paper explores the concepts of modelling a sof tware development project as a process that results in the creation of a continuous stream of d ata. In terms of the Jazz repository used in this research, one aspect of that stream of data would b e developer communication. Such data can be used to create an evolving social network charac terized by a range of metrics. This paper presents the application of data stream mining tech ni...
Acoustic streaming with heat exchange
Gubaidullin, A. A.; Pyatkova, A. V.
2016-10-01
Acoustic streaming in a cylindrical cavity with heat exchange is numerically investigated. The cavity is filled with air. The boundaries of the cavity are maintained at constant temperature. The features of acoustic streaming manifesting with the decrease in the frequency of vibration in comparison with the resonant frequency are determined. The influence of the nonlinearity of process on acoustic streaming is shown. The nonlinearity is caused by the increase of the vibration amplitude.
The Phoenix Stream: A Cold Stream in the Southern Hemisphere
Balbinot, E.; Yanny, B.; Li, T. S.; Santiago, B.; Marshall, J. L.; Finley, D. A.; Pieres, A.; Abbott, T. M. C.; Abdalla, F. B.; Allam, S.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Brooks, D.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Cunha, C. E.; da Costa, L. N.; DePoy, D. L.; Desai, S.; Diehl, H. T.; Doel, P.; Estrada, J.; Flaugher, B.; Frieman, J.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Honscheid, K.; James, D. J.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; March, M.; Martini, P.; Miquel, R.; Nichol, R. C.; Ogando, R.; Romer, A. K.; Sanchez, E.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Tarle, G.; Thomas, D.; Tucker, D.; Walker, A. R.; DES Collaboration
2016-03-01
We report the discovery of a stellar stream in the Dark Energy Survey Year 1 (Y1A1) data. The discovery was made through simple color-magnitude filters and visual inspection of the Y1A1 data. We refer to this new object as the Phoenix stream, after its resident constellation. After subtraction of the background stellar population we detect a clear signal of a simple stellar population. By fitting the ridge line of the stream in color-magnitude space, we find that a stellar population with age τ = 11.5 ± 0.5 Gyr and [Fe/H] < -1.6, located 17.5 ± 0.9 kpc from the Sun, gives an adequate description of the stream stellar population. The stream is detected over an extension of 8.°1 (2.5 kpc) and has a width of ˜54 pc assuming a Gaussian profile, indicating that a globular cluster (GC) is a probable progenitor. There is no known GC within 5 kpc that is compatible with being the progenitor of the stream, assuming that the stream traces its orbit. We examined overdensities (ODs) along the stream, however, no obvious counterpart-bound stellar system is visible in the coadded images. We also find ODs along the stream that appear to be symmetrically distributed—consistent with the epicyclic OD scenario for the formation of cold streams—as well as a misalignment between the northern and southern part of stream. Despite the close proximity we find no evidence that this stream and the halo cluster NGC 1261 have a common accretion origin linked to the recently found EriPhe OD.
A New Filtering Algorithm Utilizing Radial Velocity Measurement
LIU Yan-feng; DU Zi-cheng; PAN Quan
2005-01-01
Pulse Doppler radar measurements consist of range, azimuth, elevation and radial velocity. Most of the radar tracking algorithms in engineering only utilize position measurement. The extended Kalman filter with radial velocity measureneut is presented, then a new filtering algorithm utilizing radial velocity measurement is proposed to improve tracking results and the theoretical analysis is also given. Simulation results of the new algorithm, converted measurement Kalman filter, extended Kalman filter are compared. The effectiveness of the new algorithm is verified by simulation results.
Stream Productivity by Outermost Termination
Zantema, Hans; 10.4204/EPTCS.15.7
2010-01-01
Streams are infinite sequences over a given data type. A stream specification is a set of equations intended to define a stream. A core property is productivity: unfolding the equations produces the intended stream in the limit. In this paper we show that productivity is equivalent to termination with respect to the balanced outermost strategy of a TRS obtained by adding an additional rule. For specifications not involving branching symbols balancedness is obtained for free, by which tools for proving outermost termination can be used to prove productivity fully automatically.
Stream Productivity by Outermost Termination
Hans Zantema
2010-01-01
Full Text Available Streams are infinite sequences over a given data type. A stream specification is a set of equations intended to define a stream. A core property is productivity: unfolding the equations produces the intended stream in the limit. In this paper we show that productivity is equivalent to termination with respect to the balanced outermost strategy of a TRS obtained by adding an additional rule. For specifications not involving branching symbols balancedness is obtained for free, by which tools for proving outermost termination can be used to prove productivity fully automatically.
Stream Kriging: Incremental and recursive ordinary Kriging over spatiotemporal data streams
Zhong, Xu; Kealy, Allison; Duckham, Matt
2016-05-01
Ordinary Kriging is widely used for geospatial interpolation and estimation. Due to the O (n3) time complexity of solving the system of linear equations, ordinary Kriging for a large set of source points is computationally intensive. Conducting real-time Kriging interpolation over continuously varying spatiotemporal data streams can therefore be especially challenging. This paper develops and tests two new strategies for improving the performance of an ordinary Kriging interpolator adapted to a stream-processing environment. These strategies rely on the expectation that, over time, source data points will frequently refer to the same spatial locations (for example, where static sensor nodes are generating repeated observations of a dynamic field). First, an incremental strategy improves efficiency in cases where a relatively small proportion of previously processed spatial locations are absent from the source points at any given iteration. Second, a recursive strategy improves efficiency in cases where there is substantial set overlap between the sets of spatial locations of source points at the current and previous iterations. These two strategies are evaluated in terms of their computational efficiency in comparison to ordinary Kriging algorithm. The results show that these two strategies can reduce the time taken to perform the interpolation by up to 90%, and approach average-case time complexity of O (n2) when most but not all source points refer to the same locations over time. By combining the approaches developed in this paper with existing heuristic ordinary Kriging algorithms, the conclusions indicate how further efficiency gains could potentially be accrued. The work ultimately contributes to the development of online ordinary Kriging interpolation algorithms, capable of real-time spatial interpolation with large streaming data sets.
Theory of semi-feasible algorithms
Hemaspaandra, L.A.; Torenvliet, L.
2010-01-01
This book presents a consolidated survey of the vibrant field of research known as the theory of semi-feasible algorithms. This research stream perfectly showcases the richness of, and contrasts between, the central notions of complexity: running time, nonuniform complexity, lowness, and NP-hardness
Detecting Danger: The Dendritic Cell Algorithm
Greensmith, Julie; Cayzer, Steve
2010-01-01
The Dendritic Cell Algorithm (DCA) is inspired by the function of the dendritic cells of the human immune system. In nature, dendritic cells are the intrusion detection agents of the human body, policing the tissue and organs for potential invaders in the form of pathogens. In this research, and abstract model of DC behaviour is developed and subsequently used to form an algorithm, the DCA. The abstraction process was facilitated through close collaboration with laboratory- based immunologists, who performed bespoke experiments, the results of which are used as an integral part of this algorithm. The DCA is a population based algorithm, with each agent in the system represented as an 'artificial DC'. Each DC has the ability to combine multiple data streams and can add context to data suspected as anomalous. In this chapter the abstraction process and details of the resultant algorithm are given. The algorithm is applied to numerous intrusion detection problems in computer security including the detection of p...
Maruyama, Kazunori; NIKAIDO, Mitsuru; Hara, Yoshinori; Tanizaki, Yoshie
2012-01-01
Both streaming potential and accumulated charge of water flowed out were measured simultaneously using a sandwich-type cell. The voltages generated in divided sections along flow direction satisfied additivity. The sign of streaming potential agreed with that of streaming electrification. The relation between streaming potential and streaming electrification was explained from a viewpoint of electrical double layer in glass-water interface.
Maruyama, Kazunori; NIKAIDO, Mitsuru; Hara, Yoshinori; Tanizaki, Yoshie
2012-01-01
Both streaming potential and accumulated charge of water flowed out were measured simultaneously using a sandwich-type cell. The voltages generated in divided sections along flow direction satisfied additivity. The sign of streaming potential agreed with that of streaming electrification. The relation between streaming potential and streaming electrification was explained from a viewpoint of electrical double layer in glass-water interface.
Influence of the Gulf Stream on the troposphere.
Minobe, Shoshiro; Kuwano-Yoshida, Akira; Komori, Nobumasa; Xie, Shang-Ping; Small, Richard Justin
2008-03-13
The Gulf Stream transports large amounts of heat from the tropics to middle and high latitudes, and thereby affects weather phenomena such as cyclogenesis and low cloud formation. But its climatic influence, on monthly and longer timescales, remains poorly understood. In particular, it is unclear how the warm current affects the free atmosphere above the marine atmospheric boundary layer. Here we consider the Gulf Stream's influence on the troposphere, using a combination of operational weather analyses, satellite observations and an atmospheric general circulation model. Our results reveal that the Gulf Stream affects the entire troposphere. In the marine boundary layer, atmospheric pressure adjustments to sharp sea surface temperature gradients lead to surface wind convergence, which anchors a narrow band of precipitation along the Gulf Stream. In this rain band, upward motion and cloud formation extend into the upper troposphere, as corroborated by the frequent occurrence of very low cloud-top temperatures. These mechanisms provide a pathway by which the Gulf Stream can affect the atmosphere locally, and possibly also in remote regions by forcing planetary waves. The identification of this pathway may have implications for our understanding of the processes involved in climate change, because the Gulf Stream is the upper limb of the Atlantic meridional overturning circulation, which has varied in strength in the past and is predicted to weaken in response to human-induced global warming in the future.
Analyzing indicators of stream health for Minnesota streams
Singh, U.; Kocian, M.; Wilson, B.; Bolton, A.; Nieber, J.; Vondracek, B.; Perry, J.; Magner, J.
2005-01-01
Recent research has emphasized the importance of using physical, chemical, and biological indicators of stream health for diagnosing impaired watersheds and their receiving water bodies. A multidisciplinary team at the University of Minnesota is carrying out research to develop a stream classification system for Total Maximum Daily Load (TMDL) assessment. Funding for this research is provided by the United States Environmental Protection Agency and the Minnesota Pollution Control Agency. One objective of the research study involves investigating the relationships between indicators of stream health and localized stream characteristics. Measured data from Minnesota streams collected by various government and non-government agencies and research institutions have been obtained for the research study. Innovative Geographic Information Systems tools developed by the Environmental Science Research Institute and the University of Texas are being utilized to combine and organize the data. Simple linear relationships between index of biological integrity (IBI) and channel slope, two-year stream flow, and drainage area are presented for the Redwood River and the Snake River Basins. Results suggest that more rigorous techniques are needed to successfully capture trends in IBI scores. Additional analyses will be done using multiple regression, principal component analysis, and clustering techniques. Uncovering key independent variables and understanding how they fit together to influence stream health are critical in the development of a stream classification for TMDL assessment.
ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING
I Made Oka Widyantara
2015-12-01
Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG-DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views
Hromkovic, Juraj
2009-01-01
Explores the science of computing. This book starts with the development of computer science, algorithms and programming, and then explains and shows how to exploit the concepts of infinity, computability, computational complexity, nondeterminism and randomness.
Extending DUNE: The dune-xt modules
Leibner, Tobias; Milk, René; Schindler, Felix
2016-01-01
We present our effort to extend and complement the core modules of the Distributed and Unified Numerics Environment DUNE (http://dune-project.org) by a well tested and structured collection of utilities and concepts. We describe key elements of our four modules dune-xt-common, dune-xt-grid, dune-xt-la and dune-xt-functions, which aim at further enabling the programming of generic algorithms within DUNE as well as adding an extra layer of usability and convenience.
Investigation of acoustic streaming patterns around oscillating sharp edges
Nama, Nitesh; Huang, Tony Jun; Costanzo, Francesco
2014-01-01
Oscillating sharp edges have been employed to achieve rapid and homogeneous mixing in microchannels using acoustic streaming. Here we use a perturbation approach to study the flow around oscillating sharp edges in a microchannel. This work extends prior experimental studies to numerically characterize the effect of various parameters on the acoustically induced flow. Our numerical results match well with the experimental results. We investigated multiple device parameters such as the tip angle, oscillation amplitude, and channel dimensions. Our results indicate that, due to the inherent nonlinearity of acoustic streaming, the channel dimensions could significantly impact the flow patterns and device performance.
Kernel Extended Real-Valued Negative Selection Algorithm (KERNSA)
2013-06-01
from Moya and Hush [58], but it is also referred to as outlier/anomaly detection [67], novelty detection [7], concept learning [41], or data domain...Communications of the ACM, 42 (11):30–36, 1999. [58] Mary M Moya and Don R Hush . Network constraints and multi-objective optimization for one-class
Wild Bearing Analysis. EAAF (Extended Algorithm Analysis Family).
1985-07-10
Systems Section fense Information Systems Program C), .. ;l LLU CJET PROPULSION LABORATORY California Institute of Technology Pasadena, California JPL D...1Avaailiy codes Dit vail and Ior DitN~ ,9’ UNCLASSIFIED rr JET PROPULSIONH LABOATOR Califonia Intie ofn TecNology
Human impacts to mountain streams
Wohl, Ellen
2006-09-01
Mountain streams are here defined as channel networks within mountainous regions of the world. This definition encompasses tremendous diversity of physical and biological conditions, as well as history of land use. Human effects on mountain streams may result from activities undertaken within the stream channel that directly alter channel geometry, the dynamics of water and sediment movement, contaminants in the stream, or aquatic and riparian communities. Examples include channelization, construction of grade-control structures or check dams, removal of beavers, and placer mining. Human effects can also result from activities within the watershed that indirectly affect streams by altering the movement of water, sediment, and contaminants into the channel. Deforestation, cropping, grazing, land drainage, and urbanization are among the land uses that indirectly alter stream processes. An overview of the relative intensity of human impacts to mountain streams is provided by a table summarizing human effects on each of the major mountainous regions with respect to five categories: flow regulation, biotic integrity, water pollution, channel alteration, and land use. This table indicates that very few mountains have streams not at least moderately affected by land use. The least affected mountainous regions are those at very high or very low latitudes, although our scientific ignorance of conditions in low-latitude mountains in particular means that streams in these mountains might be more altered than is widely recognized. Four case studies from northern Sweden (arctic region), Colorado Front Range (semiarid temperate region), Swiss Alps (humid temperate region), and Papua New Guinea (humid tropics) are also used to explore in detail the history and effects on rivers of human activities in mountainous regions. The overview and case studies indicate that mountain streams must be managed with particular attention to upstream/downstream connections, hillslope
Towards Cache-Enabled, Order-Aware, Ontology-Based Stream Reasoning Framework
Yan, Rui; Praggastis, Brenda L.; Smith, William P.; McGuinness, Deborah L.
2016-08-16
While streaming data have become increasingly more popular in business and research communities, semantic models and processing software for streaming data have not kept pace. Traditional semantic solutions have not addressed transient data streams. Semantic web languages (e.g., RDF, OWL) have typically addressed static data settings and linked data approaches have predominantly addressed static or growing data repositories. Streaming data settings have some fundamental differences; in particular, data are consumed on the fly and data may expire. Stream reasoning, a combination of stream processing and semantic reasoning, has emerged with the vision of providing "smart" processing of streaming data. C-SPARQL is a prominent stream reasoning system that handles semantic (RDF) data streams. Many stream reasoning systems including C-SPARQL use a sliding window and use data arrival time to evict data. For data streams that include expiration times, a simple arrival time scheme is inadequate if the window size does not match the expiration period. In this paper, we propose a cache-enabled, order-aware, ontology-based stream reasoning framework. This framework consumes RDF streams with expiration timestamps assigned by the streaming source. Our framework utilizes both arrival and expiration timestamps in its cache eviction policies. In addition, we introduce the notion of "semantic importance" which aims to address the relevance of data to the expected reasoning, thus enabling the eviction algorithms to be more context- and reasoning-aware when choosing what data to maintain for question answering. We evaluate this framework by implementing three different prototypes and utilizing five metrics. The trade-offs of deploying the proposed framework are also discussed.
Japyassú, Hilton F; Laland, Kevin N
2017-05-01
There is a tension between the conception of cognition as a central nervous system (CNS) process and a view of cognition as extending towards the body or the contiguous environment. The centralised conception requires large or complex nervous systems to cope with complex environments. Conversely, the extended conception involves the outsourcing of information processing to the body or environment, thus making fewer demands on the processing power of the CNS. The evolution of extended cognition should be particularly favoured among small, generalist predators such as spiders, and here, we review the literature to evaluate the fit of empirical data with these contrasting models of cognition. Spiders do not seem to be cognitively limited, displaying a large diversity of learning processes, from habituation to contextual learning, including a sense of numerosity. To tease apart the central from the extended cognition, we apply the mutual manipulability criterion, testing the existence of reciprocal causal links between the putative elements of the system. We conclude that the web threads and configurations are integral parts of the cognitive systems. The extension of cognition to the web helps to explain some puzzling features of spider behaviour and seems to promote evolvability within the group, enhancing innovation through cognitive connectivity to variable habitat features. Graded changes in relative brain size could also be explained by outsourcing information processing to environmental features. More generally, niche-constructed structures emerge as prime candidates for extending animal cognition, generating the selective pressures that help to shape the evolving cognitive system.
Ševkušić-Mandić Slavica G.
2002-01-01
Full Text Available The paper presents the results of a pilot project evaluation, carried out as an action investigation whose aim was to provide a better quality extended day for primary school students. The project included the training of teachers involved in extended day program, designing of special activities performed by teachers with children once a week as well as changes and equipping of premises where children stay. The aims of the program were conception and performance of activities in a less formal way than during regular instructional days, linking of learning at school and acquired knowledge to everyday experiences, and work on contents contributing to the development of child's interests and creativity. The program was accomplished in a Belgrade primary school during the 2001/2002 academic year, comprising students of 1st and 2nd grades (N=77. The effects of the program were monitored throughout the academic year (observation and teachers' reports on accomplished workshops and at the end of the academic year (teachers and students' opinions of the program, academic achievement and creativity of students attending the extended day program compared with students not attending it. Findings about positive effects of the program on students' broadening of interests and willingness to express themselves creatively, indicate unequivocally that there is a need for developing special extended day programs. The extended day program is an opportunity for school to exert greater educational influence that has yet to be tapped.
The mass of the Geminid meteoroid stream
Ryabova, G. O.
2017-09-01
This paper describes a method for calculation of the mass of a meteoroid stream. The idea of the proposed method is simple: comparing observed meteor showers of the stream with their model. If we have a mathematical model for the stream, we know the total number of particles in the model stream and the number of particles registered at the Earth. We also know the mass distributions in the model stream and the model shower. Assuming that relations for the model stream are valid for the real stream, we calculate the real stream mass. The Geminid stream mass estimated on radar and visual observations is found to be 1016-1018 g.
Reasoning about Cardinal Directions between Extended Objects
Zhang, Xiaotong; Li, Sanjiang; Ying, Mingsheng
2009-01-01
Direction relations between extended spatial objects are important commonsense knowledge. Recently, Goyal and Egenhofer proposed a formal model, known as Cardinal Direction Calculus (CDC), for representing direction relations between connected plane regions. CDC is perhaps the most expressive qualitative calculus for directional information, and has attracted increasing interest from areas such as artificial intelligence, geographical information science, and image retrieval. Given a network of CDC constraints, the consistency problem is deciding if the network is realizable by connected regions in the real plane. This paper provides a cubic algorithm for checking consistency of basic CDC constraint networks, and proves that reasoning with CDC is in general an NP-Complete problem. For a consistent network of basic CDC constraints, our algorithm also returns a 'canonical' solution in cubic time. This cubic algorithm is also adapted to cope with cardinal directions between possibly disconnected regions, in whic...
Discovering Patterns in Symbolic Streams%符号流中的模式发现
李刚; 童铑
2000-01-01
The idea of discovering patterns in data seems to be essential for decision making in our social activities. This paper presents a simple algorithm which can be used to detect such patterns in elementary sequences of symbols. It adopts a data compression algorithm to seek for interesting patterns, which is important in understanding the way that the input symbol stream repeats itself. In this paper, the algorithm and related data structures are described in detail, and an illustrative example is given.
Discovering Patterns in Symbolic Streams%符号流中的模式发现
李刚; 童頫
2001-01-01
The idea of discovering patterns in data seems to be essential for decision making in our social activities. This paper presents a simple algorithm which can be used to detect such patterns in elementary sequences of symbols. It adopts a data compression algorithm to seek for interesting patterns, which is important in understanding the way that the input symbol stream repeats itself. In this paper, the algorithm and related data structures are described in detail, and an illustrative example is given.
CIFAR10-DVS: An Event-Stream Dataset for Object Classification.
Li, Hongmin; Liu, Hanchao; Ji, Xiangyang; Li, Guoqi; Shi, Luping
2017-01-01
Neuromorphic vision research requires high-quality and appropriately challenging event-stream datasets to support continuous improvement of algorithms and methods. However, creating event-stream datasets is a time-consuming task, which needs to be recorded using the neuromorphic cameras. Currently, there are limited event-stream datasets available. In this work, by utilizing the popular computer vision dataset CIFAR-10, we converted 10,000 frame-based images into 10,000 event streams using a dynamic vision sensor (DVS), providing an event-stream dataset of intermediate difficulty in 10 different classes, named as "CIFAR10-DVS." The conversion of event-stream dataset was implemented by a repeated closed-loop smooth (RCLS) movement of frame-based images. Unlike the conversion of frame-based images by moving the camera, the image movement is more realistic in respect of its practical applications. The repeated closed-loop image movement generates rich local intensity changes in continuous time which are quantized by each pixel of the DVS camera to generate events. Furthermore, a performance benchmark in event-driven object classification is provided based on state-of-the-art classification algorithms. This work provides a large event-stream dataset and an initial benchmark for comparison, which may boost algorithm developments in even-driven pattern recognition and object classification.
Bosch, Carl; Degirmenci, Soysal; Barlow, Jason; Mesika, Assaf; Politte, David G.; O'Sullivan, Joseph A.
2016-05-01
X-ray computed tomography reconstruction for medical, security and industrial applications has evolved through 40 years of experience with rotating gantry scanners using analytic reconstruction techniques such as filtered back projection (FBP). In parallel, research into statistical iterative reconstruction algorithms has evolved to apply to sparse view scanners in nuclear medicine, low data rate scanners in Positron Emission Tomography (PET) [5, 7, 10] and more recently to reduce exposure to ionizing radiation in conventional X-ray CT scanners. Multiple approaches to statistical iterative reconstruction have been developed based primarily on variations of expectation maximization (EM) algorithms. The primary benefit of EM algorithms is the guarantee of convergence that is maintained when iterative corrections are made within the limits of convergent algorithms. The primary disadvantage, however is that strict adherence to correction limits of convergent algorithms extends the number of iterations and ultimate timeline to complete a 3D volumetric reconstruction. Researchers have studied methods to accelerate convergence through more aggressive corrections [1], ordered subsets [1, 3, 4, 9] and spatially variant image updates. In this paper we describe the development of an AM reconstruction algorithm with accelerated convergence for use in a real-time explosive detection application for aviation security. By judiciously applying multiple acceleration techniques and advanced GPU processing architectures, we are able to perform 3D reconstruction of scanned passenger baggage at a rate of 75 slices per second. Analysis of the results on stream of commerce passenger bags demonstrates accelerated convergence by factors of 8 to 15, when comparing images from accelerated and strictly convergent algorithms.
Estimating Stream Surface Flow Velocities from Video Clips
Weijs, S. V.; Brauchli, T.; Chen, Z.; Huwald, H.
2014-12-01
Measuring surface flow velocities in streams can provide important information on discharge. This information is independent of water level, the most commonly used proxy for discharge and therefore has significant potential to reduce uncertainties. Advances in cheap and commonly used imaging devices (e.g. smartphone cameras) and image processing techniques offer new opportunities to get velocity information. Short video clips of streams can be used in combination with optical flow algorithms to get proxies for stream surface velocities. Here some initial results are presented and the main challenges are discussed, especially in view of using these techniques in a citizen science context (specifically the "WeSenseIt" project, a citizen observatory of water), where we try to minimize the need for site preparation and additional equipment needed to take measurements.
Situation-Aware Adaptive Processing (SAAP) of Data Streams
Haghighi, Pari Delir; Gaber, Mohamed Medhat; Krishnaswamy, Shonali; Zaslavsky, Arkady
The growth and proliferation of technologies in the field of sensor networking and mobile computing have led to the emergence of diverse applications that process and analyze sensory data on mobile devices such as a smart phone. However, the real power to make a significant impact on the area of developing these applications rests not merely on deploying the technologies, but on the ability to perform real-time, intelligent analysis of the data streams that are generated by the various sensors. In this chapter, we present a novel approach for Situation-Aware Adaptive Processing (SAAP) of data streams for pervasive computing environments. This approach uses fuzzy logic principles for modelling and reasoning about uncertain situations, and performs gradual adaptation of parameters of data stream mining algorithms in real-time according to availability of resources and the occurring situations.
Save Our Streams and Waterways.
Indiana State Dept. of Education, Indianapolis. Center for School Improvement and Performance.
Protection of existing water supplies is critical to ensuring good health for people and animals alike. This program is aligned with the Izaak Walton League of American's Save Our Streams program which is based on the concept that students can greatly improve the quality of a nearby stream, pond, or river by regular visits and monitoring. The…
Technology & Learning, 2008
2008-01-01
More than ever, teachers are using digital video to enhance their lessons. In fact, the number of schools using video streaming increased from 30 percent to 45 percent between 2004 and 2006, according to Market Data Retrieval. Why the popularity? For starters, video-streaming products are easy to use. They allow teachers to punctuate lessons with…
Nonnegative Matrix Factorization-Based Spatial-Temporal Clustering for Multiple Sensor Data Streams
Di-Hua Sun
2014-01-01
Full Text Available Cyber physical systems have grown exponentially and have been attracting a lot of attention over the last few years. To retrieve and mine the useful information from massive amounts of sensor data streams with spatial, temporal, and other multidimensional information has become an active research area. Moreover, recent research has shown that clusters of streams change with a comprehensive spatial-temporal viewpoint in real applications. In this paper, we propose a spatial-temporal clustering algorithm (STClu based on nonnegative matrix trifactorization by utilizing time-series observational data streams and geospatial relationship for clustering multiple sensor data streams. Instead of directly clustering multiple data streams periodically, STClu incorporates the spatial relationship between two sensors in proximity and integrates the historical information into consideration. Furthermore, we develop an iterative updating optimization algorithm STClu. The effectiveness and efficiency of the algorithm STClu are both demonstrated in experiments on real and synthetic data sets. The results show that the proposed STClu algorithm outperforms existing methods for clustering sensor data streams.
A Versatile Chip Set For Image Processing Algorithms
Krishnan, M. S.
1988-02-01
This paper presents a versatile chip set that can realize signal/image processing algorithms used in several important image processing applications, including template-processing, spatial filtering and image scaling. This chip set architecture is superior in versatility, programmability and modularity to several schemes proposed in the literature. The first chip, called the Template Processor, can perform a variety of template functions on a pixel stream using a set of threshold matrices that can be modified or switched in real-time as a function of the image being processed. This chip can also be used to perform data scaling and image biasing. The second chip, called the Filter/Scaler chip, can perform two major functions. The first is a transversal filter function where the number of sample points is modularly extendable and the coefficients are programmable. The second major function performed by this chip is the interpolation function. Linear or cubic B-spline interpolation algorithms can be implemented by programming the coefficients appropriately. The essential features of these two basic building block processors and their significance in template-based computations, filtering, data-scaling and half-tone applications are discussed. Structured, testable implementations of these processors in VLSI technology and extensions to higher performance systems are presented.
Extending Critical Performativity
Spicer, André; Alvesson, Mats; Kärreman, Dan
2016-01-01
In this article we extend the debate about critical performativity. We begin by outlining the basic tenets of critical performativity and how this has been applied in the study of management and organization. We then address recent critiques of critical performance. We note these arguments suffer...... from an undue focus on intra-academic debates; engage in author-itarian theoretical policing; feign relevance through symbolic radicalism; and repackage common sense. We take these critiques as an opportunity to offer an extended model of critical performativity that involves focusing on issues...
Parallel algorithms for numerical linear algebra
van der Vorst, H
1990-01-01
This is the first in a new series of books presenting research results and developments concerning the theory and applications of parallel computers, including vector, pipeline, array, fifth/future generation computers, and neural computers.All aspects of high-speed computing fall within the scope of the series, e.g. algorithm design, applications, software engineering, networking, taxonomy, models and architectural trends, performance, peripheral devices.Papers in Volume One cover the main streams of parallel linear algebra: systolic array algorithms, message-passing systems, algorithms for p
Bat Algorithm for Multi-objective Optimisation
Yang, Xin-She
2012-01-01
Engineering optimization is typically multiobjective and multidisciplinary with complex constraints, and the solution of such complex problems requires efficient optimization algorithms. Recently, Xin-She Yang proposed a bat-inspired algorithm for solving nonlinear, global optimisation problems. In this paper, we extend this algorithm to solve multiobjective optimisation problems. The proposed multiobjective bat algorithm (MOBA) is first validated against a subset of test functions, and then applied to solve multiobjective design problems such as welded beam design. Simulation results suggest that the proposed algorithm works efficiently.
Final Report: Sampling-Based Algorithms for Estimating Structure in Big Data.
Matulef, Kevin Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-02-01
The purpose of this project was to develop sampling-based algorithms to discover hidden struc- ture in massive data sets. Inferring structure in large data sets is an increasingly common task in many critical national security applications. These data sets come from myriad sources, such as network traffic, sensor data, and data generated by large-scale simulations. They are often so large that traditional data mining techniques are time consuming or even infeasible. To address this problem, we focus on a class of algorithms that do not compute an exact answer, but instead use sampling to compute an approximate answer using fewer resources. The particular class of algorithms that we focus on are streaming algorithms , so called because they are designed to handle high-throughput streams of data. Streaming algorithms have only a small amount of working storage - much less than the size of the full data stream - so they must necessarily use sampling to approximate the correct answer. We present two results: * A streaming algorithm called HyperHeadTail , that estimates the degree distribution of a graph (i.e., the distribution of the number of connections for each node in a network). The degree distribution is a fundamental graph property, but prior work on estimating the degree distribution in a streaming setting was impractical for many real-world application. We improve upon prior work by developing an algorithm that can handle streams with repeated edges, and graph structures that evolve over time. * An algorithm for the task of maintaining a weighted subsample of items in a stream, when the items must be sampled according to their weight, and the weights are dynamically changing. To our knowledge, this is the first such algorithm designed for dynamically evolving weights. We expect it may be useful as a building block for other streaming algorithms on dynamic data sets.
Stream-profile analysis and stream-gradient index
Hack, John T.
1973-01-01
The generally regular three-dimensional geometry of drainage networks is the basis for a simple method of terrain analysis providing clues to bedrock conditions and other factors that determine topographic forms. On a reach of any stream, a gradient-index value can be obtained which allows meaningful comparisons of channel slope on streams of different sizes. The index is believed to reflect stream power or competence and is simply the product of the channel slope at a point and channel length measured along the longest stream above the pointwhere the calculation is made. In an adjusted topography, changes in gradient-index values along a stream generally correspond to differences in bedrock or introduced load. In any landscape the gradient index of a stream is related to total relief and stream regimen. Thus, climate, tectonic events, and geomorphic history must be considered in using the gradient index. Gradient-index values can be obtained quickly by simple measurements on topographic maps, or they can be obtained by more sophisticated photogrammetric measurements that involve simple computer calculations from x, y, z coordinates.
The Phoenix stream: a cold stream in the Southern hemisphere
Balbinot, E; Li, T S; Santiago, B; Marshall, J L; Finley, D A; Pieres, A; Abbott, T M C; Abdalla, F B; Allam, S; Benoit-Lévy, A; Bernstein, G M; Bertin, E; Brooks, D; Burke, D L; Rosell, A Carnero; Kind, M Carrasco; Carretero, J; Cunha, C E; da Costa, L N; DePoy, D L; Desai, S; Diehl, H T; Doel, P; Estrada, J; Flaugher, B; Frieman, J; Gerdes, D W; Gruen, D; Gruendl, R A; Honscheid, K; James, D J; Kuehn, K; Kuropatkin, N; Lahav, O; March, M; Martini, P; Miquel, R; Nichol, R C; Ogando, R; Romer, A K; Sanchez, E; Schubnell, M; Sevilla-Noarbe, I; Smith, R C; Soares-Santos, M; Sobreira, F; Suchyta, E; Tarle, G; Thomas, D; Tucker, D; Walker, A R
2015-01-01
We report the discovery of a stellar stream in the Dark Energy Survey (DES) Year 1 (Y1A1) data. The discovery was made through simple color-magnitude filters and visual inspection of the Y1A1 data. We refer to this new object as the Phoenix stream, after its residing constellation. Through the subtraction of the background stellar population we detect a clear signal of a simple stellar population. By fitting the ridge line of the stream in color-magnitude space, we find that a stellar population with age $\\tau=11.5\\pm0.5$ Gyr and ${\\rm [Fe/H]}<-1.6$ located 17.5$\\pm$0.9 kpc from the Sun gives an adequate description of the stream stellar population. The stream is detected over an extension of 8$^{\\circ}$.1 (2.5 kpc) and has a width of $\\sim$54 pc assuming a Gaussian profile, indicating that a globular cluster is a probable progenitor. There is no known globular cluster within 5 kpc compatible with being the progenitor of the stream, assuming that the stream traces its orbit. We examined overdensities along...
Simulation and reconstruction of free-streaming data in CBM
Friese, Volker
2011-12-01
The CBM experiment will investigate heavy-ion reactions at the FAIR facility at unprecedented interaction rates. This implies a novel read-out and data acquisition concept with self-triggered front-end electronics and free-streaming data. Event association must be performed in software on-line, and may require four-dimensional reconstruction routines. In order to study the problem of event association and to develop proper algorithms, simulations must be performed which go beyond the normal event-by-event processing as available from most experimental simulation frameworks. In this article, we discuss the challenges and concepts for the reconstruction of such free-streaming data and present first steps for a time-based simulation which is necessary for the development and validation of the reconstruction algorithms, and which requires modifications to the current software framework FAIRROOT as well as to the data model.
Evaluation of packet loss impairment on streaming video
RUI Hua-xia; LI Chong-rong; QIU Sheng-ke
2006-01-01
Video compression technologies are essential in video streaming application because they could save a great amount of network resources. However compressed videos are also extremely sensitive to packet loss which is inevitable in today's best effort IP network. Therefore we think accurate evaluation of packet loss impairment on compressed video is very important. In this work, we develop an analytic model to describe these impairments without the reference of the original video (NR) and propose an impairment metric based on the model, which takes into account both impairment length and impairment strength. To evaluate an impaired frame or video, we design a detection and evaluation algorithm (DE algorithm) to compute the above metric value. The DE algorithm has low computational complexity and is currently being implemented in the real-time monitoring module of our HDTV over IP system. The impairment metric and DE algorithm could also be used in adaptive system or be used to compare diffeient error concealment strategies.
Intuitionistic fuzzy hierarchical clustering algorithms
Xu Zeshui
2009-01-01
Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.
A statistical learning algorithm for word segmentation
Van Aken, Jerry R
2011-01-01
In natural speech, the speaker does not pause between words, yet a human listener somehow perceives this continuous stream of phonemes as a series of distinct words. The detection of boundaries between spoken words is an instance of a general capability of the human neocortex to remember and to recognize recurring sequences. This paper describes a computer algorithm that is designed to solve the problem of locating word boundaries in blocks of English text from which the spaces have been removed. This problem avoids the complexities of processing speech but requires similar capabilities for detecting recurring sequences. The algorithm that is described in this paper relies entirely on statistical relationships between letters in the input stream to infer the locations of word boundaries. The source code for a C++ version of this algorithm is presented in an appendix.
Parameterization of extended systems
Niemann, Hans Henrik
2006-01-01
The YJBK parameterization (of all stabilizing controllers) is extended to handle systems with additional sensors and/or actuators. It is shown that the closed loop transfer function is still an affine function in the YJBK parameters in the nominal case. Further, some closed-loop stability results...
Coping with handover effects in video streaming over cellular networks
BOUAZIZI Imed; HANNUKSELA Miska M.; RAUF Usama
2006-01-01
The 3rd generation partnership project (3GPP) has defined the protocols and codecs for implementing media streaming services over packet-switched 3G mobile networks. The specification is based on IETF RFCs on audio/video transport.It also adds new features to achieve better adaptation to the mobile network environment. In this paper, we propose an algorithm for handover detection and fast buffer refill that is based on the existing feedback and signaling mechanisms. The proposed algorithm refills the receiver buffer at a faster pace during a limited time frame after a hard handover is detected in order to achieve higher video quality.
Dynamic Mode Decomposition for Large and Streaming Datasets
Hemati, Maziar S; Rowley, Clarence W
2014-01-01
We formulate a low-storage method for performing dynamic mode decomposition that can be updated inexpensively as new data become available; this formulation allows dynamical information to be extracted from large datasets and data streams. We present two algorithms: the first is mathematically equivalent to a standard "batch-processed" formulation; the second introduces a compression step that maintains computational efficiency, while enhancing the ability to isolate pertinent dynamical information from noisy measurements. Both algorithms reliably capture dominant fluid dynamic behaviors, as demonstrated on cylinder wake data collected from both direct numerical simulations and particle image velocimetry experiments
Maeda Batista dos Anjos
Full Text Available Small streams are important components of the landscape in terra firme forests in central Amazonia and harbor a large number of fish species. Nevertheless, the lack of a common sampling protocol in studies of this ichthyofauna hinders comparisons among available results. This study evaluates how the length of stream reach sampled affects estimates of local fish species density in 1st, 2nd, and 3rd order streams, and proposes a mean minimum sampling length that best approximates the absolute number of species in a given stream segment. We sampled three streams in the Biological Dynamics of Forest Fragments Project's study sites, between May and August 2004. At each stream, one 1st order, one 2nd order, and one 3rd order segment was sampled. We sampled five 20-m reaches in each stream segment. Three to four people collected along each reach for 45 to 60 minutes. We used Jaccard's coefficient to estimate the similarity of species composition among stream reaches and segments. Estimates of species richness were obtained with Jackknife 1 and Bootstrap algorithms and species accumulation curves. We used simple linear regressions to look for relationships between species density and fish abundance and between species density and the volume of 100-m stream segments. Species density in 1st order stream reaches was slightly higher than in 2nd and 3rd order stream reaches, whereas fish abundance was apparently higher in 3rd order reaches. Similarity in fish species composition between 20-m reaches was low for all studied streams. Species density values in pooled 100-m stream segments represented 71.4% to 94.1% of the estimated values for these streams. Species density showed a direct relationship both with volume of the sampled stream segment and fish abundance. It seems plausible that larger streams contain a higher number of microhabitat types, which allow for the presence of more fish species per stream length. Based on the values of asymptotes and
A Clustal Alignment Improver Using Evolutionary Algorithms
Thomsen, Rene; Fogel, Gary B.; Krink, Thimo
2002-01-01
Multiple sequence alignment (MSA) is a crucial task in bioinformatics. In this paper we extended previous work with evolutionary algorithms (EA) by using MSA solutions obtained from the wellknown Clustal V algorithm as a candidate solution seed of the initial EA population. Our results clearly show...
Percent Agriculture Adjacent to Streams (Future)
U.S. Environmental Protection Agency — The type of vegetation along a stream influences the water quality in the stream. Intact buffer strips of natural vegetation along streams tend to intercept...
Stream Habitat Reach Summary - NCWAP [ds158
California Department of Resources — The Stream Habitat - NCWAP - Reach Summary [ds158] shapefile contains in-stream habitat survey data summarized to the stream reach level. It is a derivative of the...
Major Kansas Perennial Streams : 1961 and 2009
US Fish and Wildlife Service, Department of the Interior — Map of major perennial streams in Kansas for the years 1961 and 2009. The map shows a decrease in streams regarded as perennial in 1961, compared to stream regarded...
Percent Forest Adjacent to Streams (Future)
U.S. Environmental Protection Agency — The type of vegetation along a stream influences the water quality in the stream. Intact buffer strips of natural vegetation along streams tend to intercept...
Reclamation of potable water from mixed gas streams
Judkins, Roddie R.; Bischoff, Brian L.; Debusk, Melanie Moses; Narula, Chaitanya
2016-07-19
An apparatus for separating a liquid from a mixed gas stream can include a wall, a mixed gas stream passageway, and a liquid collection assembly. The wall can include a first surface, a second surface, and a plurality of capillary condensation pores. The capillary condensation pores extend through the wall, and have a first opening on the first surface of the wall, and a second opening on the second surface of the wall. The pore size of the pores can be between about 2 nm to about 100 nm. The mixed gas stream passageway can be in fluid communication with the first opening. The liquid collection assembly can collect liquid from the plurality of pores.
Lambda-perceptron: an adaptive classifier for data-streams
Pavlidis, N.; Tasoulis, Dimitrios; Adams, N.M.; Hand, D J
2011-01-01
Streaming data introduce challenges mainly due to changing data distributions (population drift). To accommodate population drift we develop a novel linear adaptive online classification method motivated by ideas from adaptive filtering. Our approach allows the impact of past data on parameter estimates to be gradually removed, a process termed forgetting, yielding completely online adaptive algorithms. Extensive experimental results show that this approach adjusts the forgetting mechanism to...
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
Streaming patterns in Faraday waves
Périnet, Nicolas; Urra, Héctor; Mujica, Nicolás; Gordillo, Leonardo
2016-01-01
Waves patterns in the Faraday instability have been studied for decades. Besides the rich dynamics that can be observed on the waves at the interface, Faraday waves hide beneath them an elusive range of flow patterns --or streaming patterns-- which have not been studied in detail until now. The streaming patterns are responsible for a net circulation in the flow which are reminiscent of convection cells. In this article, we analyse these streaming flows by conducting experiments in a Faraday-wave setup. To visualize the flows, tracers are used to generate both trajectory maps and to probe the streaming velocity field via Particle Image Velocimetry (PIV). We identify three types of patterns and experimentally show that identical Faraday waves can mask streaming patterns that are qualitatively very different. Next we propose a three-dimensional model that explains streaming flows in quasi-inviscid fluids. We show that the streaming inside the fluid arises from a complex coupling between the bulk and the boundar...
Extending Wireless Rechargeable Sensor Network Life without Full Knowledge
Najeeb W. Najeeb
2017-07-01
Full Text Available When extending the life of Wireless Rechargeable Sensor Networks (WRSN, one challenge is charging networks as they grow larger. Overcoming this limitation will render a WRSN more practical and highly adaptable to growth in the real world. Most charging algorithms require a priori full knowledge of sensor nodes’ power levels in order to determine the nodes that require charging. In this work, we present a probabilistic algorithm that extends the life of scalable WRSN without a priori power knowledge and without full network exploration. We develop a probability bound on the power level of the sensor nodes and utilize this bound to make decisions while exploring a WRSN. We verify the algorithm by simulating a wireless power transfer unmanned aerial vehicle, and charging a WRSN to extend its life. Our results show that, without knowledge, our proposed algorithm extends the life of a WRSN on average 90% of what an optimal full knowledge algorithm can achieve. This means that the charging robot does not need to explore the whole network, which enables the scaling of WRSN. We analyze the impact of network parameters on our algorithm and show that it is insensitive to a large range of parameter values.
Recognizing well-parenthesized expressions in the streaming model
Magniez, F; Nayak, A
2009-01-01
Motivated by a concrete problem and with the goal of understanding the sense in which the complexity of streaming algorithms is related to the complexity of formal languages, we investigate the problem Dyck(s) of checking matching parentheses, with $s$ different types of parenthesis. We present a one-pass randomized streaming algorithm for Dyck(2) with space $\\Order(\\sqrt{n}\\log n)$, time per letter $\\polylog (n)$, and one-sided error. We prove that this one-pass algorithm is optimal, up to a $\\polylog n$ factor, even when two-sided error is allowed. For the lower bound, we prove a direct sum result on hard instances by following the "information cost" approach, but with a few twists. Indeed, we play a subtle game between public and private coins. This mixture between public and private coins results from a balancing act between the direct sum result and a combinatorial lower bound for the base case. Surprisingly, the space requirement shrinks drastically if we have access to the input stream in reverse. We p...