Scalable Video Streaming in Wireless Mesh Networks for Education

Science.gov (United States)

Liu, Yan; Wang, Xinheng; Zhao, Liqiang

2011-01-01

In this paper, a video streaming system for education based on a wireless mesh network is proposed. A wireless mesh network is a self-organizing, self-managing and reliable intelligent network, which allows educators to deploy a network quickly. Video streaming plays an important role in this system for multimedia data transmission. This new…

A stream temperature model for the Peace-Athabasca River basin

Science.gov (United States)

Morales-Marin, L. A.; Rokaya, P.; Wheater, H. S.; Lindenschmidt, K. E.

2017-12-01

Water temperature plays a fundamental role in water ecosystem functioning. Because it regulates flow energy and metabolic rates in organism productivity over a broad spectrum of space and time scales, water temperature constitutes an important indicator of aquatic ecosystems health. In cold region basins, stream water temperature modelling is also fundamental to predict ice freeze-up and break-up events in order to improve flood management. Multiple model approaches such as linear and multivariable regression methods, neural network and thermal energy budged models have been developed and implemented to simulate stream water temperature. Most of these models have been applied to specific stream reaches and trained using observed data, but very little has been done to simulate water temperature in large catchment river networks. We present the coupling of RBM model, a semi-Lagrangian water temperature model for advection-dominated river system, and MESH, a semi-distributed hydrological model, to simulate stream water temperature in river catchments. The coupled models are implemented in the Peace-Athabasca River basin in order to analyze the variation in stream temperature regimes under changing hydrological and meteorological conditions. Uncertainty of stream temperature simulations is also assessed in order to determine the degree of reliability of the estimates.

Analysis of sound data streamed over the network

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2013-01-01

Full Text Available In this paper we inspect a difference between original sound recording and signal captured after streaming this original recording over a network loaded with a heavy traffic. There are several kinds of failures occurring in the captured recording caused by network congestion. We try to find a method how to evaluate correctness of streamed audio. Usually there are metrics based on a human perception of a signal such as “signal is clear, without audible failures”, “signal is having some failures but it is understandable”, or “signal is inarticulate”. These approaches need to be statistically evaluated on a broad set of respondents, which is time and resource consuming. We try to propose some metrics based on signal properties allowing us to compare the original and captured recording. We use algorithm called Dynamic Time Warping (Müller, 2007 commonly used for time series comparison in this paper. Some other time series exploration approaches can be found in (Fejfar, 2011 and (Fejfar, 2012. The data was acquired in our network laboratory simulating network traffic by downloading files, streaming audio and video simultaneously. Our former experiment inspected Quality of Service (QoS and its impact on failures of received audio data stream. This experiment is focused on the comparison of sound recordings rather than network mechanism.We focus, in this paper, on a real time audio stream such as a telephone call, where it is not possible to stream audio in advance to a “pool”. Instead it is necessary to achieve as small delay as possible (between speaker voice recording and listener voice replay. We are using RTP protocol for streaming audio.

In-stream Nitrogen Processing and Dilution in an Agricultural Stream Network

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Prior, K.; Ward, A. S.; Davis, C. A.; Burgin, A. J.; Loecke, T.; Riveros-Iregui, D. A.; Thomas, S. A.; St Clair, M. A.

2014-12-01

The interaction of agricultural fertilizer use and extremes in drought and flood conditions in 2012-2013 set up conditions for a natural experiment on watershed-scale nutrient dynamics. The region-wide drought in 2012 left surface soils disconnected from stream networks and restricted nutrient use by crops, resulting in an unusually large nitrogen pool in soil columns through the winter. When wet conditions returned to the Midwest in 2013, the unused fertilizer was mobilized, resulting in a six-week period of extremely high in-stream nutrient concentrations. This study analyses three synoptic samples from the Iowa-Cedar River Basin in 2013 to quantify patterns in nitrogen dynamics. We use multiple conservative ions as tracers to estimate dilution by lateral inflows. We also estimate nutrient spiraling metrics by treating the fertilizer pulse as a constant rate nutrient addition across the watershed—a scale on which these processes are increasingly modeled numerically, but on which standard nutrient addition experiments are simply not feasible. Results of this study compare patterns in dilution and uptake across spatial and temporal scales, and bound feasible explanations for each reach of the network.

Intelligent Packet Shaper to Avoid Network Congestion for Improved Streaming Video Quality at Clients

DEFF Research Database (Denmark)

Kaul, Manohar; Khosla, Rajiv; Mitsukura, Y

2003-01-01

of this intelligent traffic-shaping algorithm on the underlying network real time packet traffic and the eradication of unwanted abruption in the streaming video qualiy. This paper concluded from the end results of the simulation that neural networks are a very superior means of modeling real-time traffic......This paper proposes a traffic shaping algorithm based on neural networks, which adapts to a network over which streaming video is being transmitted. The purpose of this intelligent shaper is to eradicate all traffic congestion and improve the end-user's video quality. It possesses the capability...

Wireless network interface energy consumption implications of popular streaming formats

Science.gov (United States)

Chandra, Surendar

2001-12-01

With the proliferation of mobile streaming multimedia, available battery capacity constrains the end-user experience. Since streaming applications tend to be long running, wireless network interface card's (WNIC) energy consumption is particularly an acute problem. In this work, we explore the WNIC energy consumption implications of popular multimedia streaming formats from Microsoft (Windows media), Real (Real media) and Apple (Quick Time). We investigate the energy consumption under varying stream bandwidth and network loss rates. We also explore history-based client-side strategies to reduce the energy consumed by transitioning the WNICs to a lower power consuming sleep state. We show that Microsoft media tends to transmit packets at regular intervals; streams optimized for 28.8 Kbps can save over 80% in energy consumption with 2% data loss. A high bandwidth stream (768 Kbps) can still save 57% in energy consumption with less than 0.3% data loss. For high bandwidth streams, Microsoft media exploits network-level packet fragmentation, which can lead to excessive packet loss (and wasted energy) in a lossy network. Real stream packets tend to be sent closer to each other, especially at higher bandwidths. Quicktime packets sometimes arrive in quick succession; most likely an application level fragmentation mechanism. Such packets are harder to predict at the network level without understanding the packet semantics.

Two-Stream Transformer Networks for Video-based Face Alignment.

Science.gov (United States)

Liu, Hao; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a two-stream transformer networks (TSTN) approach for video-based face alignment. Unlike conventional image-based face alignment approaches which cannot explicitly model the temporal dependency in videos and motivated by the fact that consistent movements of facial landmarks usually occur across consecutive frames, our TSTN aims to capture the complementary information of both the spatial appearance on still frames and the temporal consistency information across frames. To achieve this, we develop a two-stream architecture, which decomposes the video-based face alignment into spatial and temporal streams accordingly. Specifically, the spatial stream aims to transform the facial image to the landmark positions by preserving the holistic facial shape structure. Accordingly, the temporal stream encodes the video input as active appearance codes, where the temporal consistency information across frames is captured to help shape refinements. Experimental results on the benchmarking video-based face alignment datasets show very competitive performance of our method in comparisons to the state-of-the-arts.

Development of Land Segmentation, Stream-Reach Network, and Watersheds in Support of Hydrological Simulation Program-Fortran (HSPF) Modeling, Chesapeake Bay Watershed, and Adjacent Parts of Maryland, Delaware, and Virginia

Science.gov (United States)

Martucci, Sarah K.; Krstolic, Jennifer L.; Raffensperger, Jeff P.; Hopkins, Katherine J.

2006-01-01

The U.S. Geological Survey, U.S. Environmental Protection Agency Chesapeake Bay Program Office, Interstate Commission on the Potomac River Basin, Maryland Department of the Environment, Virginia Department of Conservation and Recreation, Virginia Department of Environmental Quality, and the University of Maryland Center for Environmental Science are collaborating on the Chesapeake Bay Regional Watershed Model, using Hydrological Simulation Program - FORTRAN to simulate streamflow and concentrations and loads of nutrients and sediment to Chesapeake Bay. The model will be used to provide information for resource managers. In order to establish a framework for model simulation, digital spatial datasets were created defining the discretization of the model region (including the Chesapeake Bay watershed, as well as the adjacent parts of Maryland, Delaware, and Virginia outside the watershed) into land segments, a stream-reach network, and associated watersheds. Land segmentation was based on county boundaries represented by a 1:100,000-scale digital dataset. Fifty of the 254 counties and incorporated cities in the model region were divided on the basis of physiography and topography, producing a total of 309 land segments. The stream-reach network for the Chesapeake Bay watershed part of the model region was based on the U.S. Geological Survey Chesapeake Bay SPARROW (SPAtially Referenced Regressions On Watershed attributes) model stream-reach network. Because that network was created only for the Chesapeake Bay watershed, the rest of the model region uses a 1:500,000-scale stream-reach network. Streams with mean annual streamflow of less than 100 cubic feet per second were excluded based on attributes from the dataset. Additional changes were made to enhance the data and to allow for inclusion of stream reaches with monitoring data that were not part of the original network. Thirty-meter-resolution Digital Elevation Model data were used to delineate watersheds for each

Optimal Traffic Allocation for Multi-Stream Aggregation in Heterogeneous Networks

DEFF Research Database (Denmark)

Popovska Avramova, Andrijana; Iversen, Villy Bæk

2015-01-01

nature of radio access networks are considered as important factors for performance improvement by multi-stream aggregation. Therefore, in our model, the networks are represented by different queueing systems in order to indicate networks with opposite quality of service provisioning, capacity and delay...... variations. Furthermore, services with different traffic characteristics in terms of quality of service requirements are considered. The simulation results show the advantages of our scheme with respect to efficient increase in data rate and delay performance compared to traditional schemes....

A bipartite fitness model for online music streaming services

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Pongnumkul, Suchit; Motohashi, Kazuyuki

2018-01-01

This paper proposes an evolution model and an analysis of the behavior of music consumers on online music streaming services. While previous studies have observed power-law degree distributions of usage in online music streaming services, the underlying behavior of users has not been well understood. Users and songs can be described using a bipartite network where an edge exists between a user node and a song node when the user has listened that song. The growth mechanism of bipartite networks has been used to understand the evolution of online bipartite networks Zhang et al. (2013). Existing bipartite models are based on a preferential attachment mechanism László Barabási and Albert (1999) in which the probability that a user listens to a song is proportional to its current popularity. This mechanism does not allow for two types of real world phenomena. First, a newly released song with high quality sometimes quickly gains popularity. Second, the popularity of songs normally decreases as time goes by. Therefore, this paper proposes a new model that is more suitable for online music services by adding fitness and aging functions to the song nodes of the bipartite network proposed by Zhang et al. (2013). Theoretical analyses are performed for the degree distribution of songs. Empirical data from an online streaming service, Last.fm, are used to confirm the degree distribution of the object nodes. Simulation results show improvements from a previous model. Finally, to illustrate the application of the proposed model, a simplified royalty cost model for online music services is used to demonstrate how the changes in the proposed parameters can affect the costs for online music streaming providers. Managerial implications are also discussed.

Evidence for fish dispersal from spatial analysis of stream network topology

Science.gov (United States)

Hitt, N.P.; Angermeier, P.L.

2008-01-01

Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.

Use of neural networks for monitoring surface water quality changes in a neotropical urban stream.

Science.gov (United States)

da Costa, Andréa Oliveira Souza; Silva, Priscila Ferreira; Sabará, Millôr Godoy; da Costa, Esly Ferreira

2009-08-01

This paper reports the using of neural networks for water quality analysis in a tropical urban stream before (2002) and after sewerage building and the completion of point-source control-based sanitation program (2003). Mathematical modeling divided water quality data in two categories: (a) input of some in situ water quality variables (temperature, pH, O2 concentration, O2 saturation and electrical conductivity) and (b) water chemical composition (N-NO2(-); N-NO3(-); N-NH4(+) Total-N; P-PO4(3-); K+; Ca2+; Mg+2; Cu2+; Zn2+ and Fe+3) as the output from tested models. Stream water data come from fortnightly sampling in five points along the Ipanema stream (Southeast Brazil, Minas Gerais state) plus two points downstream and upstream Ipanema discharge into Doce River. Once the best models are consistent with variables behavior we suggest that neural networking shows potential as a methodology to enhance guidelines for urban streams restoration, conservation and management.

Real-time video streaming in mobile cloud over heterogeneous wireless networks

Science.gov (United States)

Abdallah-Saleh, Saleh; Wang, Qi; Grecos, Christos

2012-06-01

Recently, the concept of Mobile Cloud Computing (MCC) has been proposed to offload the resource requirements in computational capabilities, storage and security from mobile devices into the cloud. Internet video applications such as real-time streaming are expected to be ubiquitously deployed and supported over the cloud for mobile users, who typically encounter a range of wireless networks of diverse radio access technologies during their roaming. However, real-time video streaming for mobile cloud users across heterogeneous wireless networks presents multiple challenges. The network-layer quality of service (QoS) provision to support high-quality mobile video delivery in this demanding scenario remains an open research question, and this in turn affects the application-level visual quality and impedes mobile users' perceived quality of experience (QoE). In this paper, we devise a framework to support real-time video streaming in this new mobile video networking paradigm and evaluate the performance of the proposed framework empirically through a lab-based yet realistic testing platform. One particular issue we focus on is the effect of users' mobility on the QoS of video streaming over the cloud. We design and implement a hybrid platform comprising of a test-bed and an emulator, on which our concept of mobile cloud computing, video streaming and heterogeneous wireless networks are implemented and integrated to allow the testing of our framework. As representative heterogeneous wireless networks, the popular WLAN (Wi-Fi) and MAN (WiMAX) networks are incorporated in order to evaluate effects of handovers between these different radio access technologies. The H.264/AVC (Advanced Video Coding) standard is employed for real-time video streaming from a server to mobile users (client nodes) in the networks. Mobility support is introduced to enable continuous streaming experience for a mobile user across the heterogeneous wireless network. Real-time video stream packets

Comparisons of Spatial Predictions of Conductivity on a Stream Network in an Appalachian Watershed

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We made spatial predictions of specific conductance based on spatial stream network (SSN) modeling to compare conductivity measurements of components of the network, such as headwaters, tributaries, and mainstem, which have different spatial extents in a study Appalachian watersh...

IPTV based on IP network and streaming media service station

Science.gov (United States)

Sun, Jifeng; Gao, Songbo

2007-11-01

IPTV can be a new service performed on the Internet in that network transmission and streaming media technologies are getting mature. In this paper, IPTV system infrastructure of UTStarcom, key technologies deployed, and applications will be discussed and evaluated. The key technologies to achieve IPTV services include 1) codec and compression; 2) streaming media; and 3) broadband networks and access to such networks. The implementation of Media Switch IPTV system in Harbin CNC city network is also discussed.

Value shaping in networked business modeling : Case studies of sustainability-oriented innovations

NARCIS (Netherlands)

Oskam, I.F.; Bossink, Bart; de Man, Ard-Pieter

2018-01-01

A stream of literature is emerging where network development and business modeling intersect. Various authors emphasize that networks influence business models. This paper extends this stream of literature by studying two cases in which we analyze how business modeling and networking interact over

In-Network Adaptation of Video Streams Using Network Processors

Directory of Open Access Journals (Sweden)

Mohammad Shorfuzzaman

2009-01-01

problem can be addressed, near the network edge, by applying dynamic, in-network adaptation (e.g., transcoding of video streams to meet available connection bandwidth, machine characteristics, and client preferences. In this paper, we extrapolate from earlier work of Shorfuzzaman et al. 2006 in which we implemented and assessed an MPEG-1 transcoding system on the Intel IXP1200 network processor to consider the feasibility of in-network transcoding for other video formats and network processor architectures. The use of “on-the-fly” video adaptation near the edge of the network offers the promise of simpler support for a wide range of end devices with different display, and so forth, characteristics that can be used in different types of environments.

Stream Intermittency Sensors Monitor the Onset and Duration of Stream Flow Along a Channel Network During Storms

Science.gov (United States)

Jensen, C.; McGuire, K. J.

2017-12-01

Headwater streams are spatially extensive, accounting for a majority of global stream length, and supply downstream water bodies with water, sediment, organic matter, and pollutants. Much of this transmission occurs episodically during storms when stream flow and connectivity are high. Many headwaters are temporary streams that expand and contract in length in response to storms and seasonality. Understanding where and when streams carry flow is critical for conserving headwaters and protecting downstream water quality, but storm events are difficult to study in small catchments. The rise and fall of stream flow occurs rapidly in headwaters, making observation of the entire stream network difficult. Stream intermittency sensors that detect the presence or absence of water can reveal wetting and drying patterns over short time scales. We installed 50 intermittency sensors along the channel network of a small catchment (35 ha) in the Valley and Ridge of southwest Virginia. Previous work shows stream length is highly variable in this shale catchment, as the drainage density spans two orders of magnitude. The sensors record data every 15 minutes for one year to capture different seasons, antecedent moisture conditions, and precipitation rates. We seek to determine whether hysteresis between stream flow and network length occurs on the rising and falling limbs of events and if reach-scale characteristics such as valley width explain spatial patterns of flow duration. Our results indicate reaches with a wide, sediment-filled valley floor carry water for shorter periods of time than confined channel segments with steep valley side slopes. During earlier field mapping surveys, we only observed flow in a few of the tributaries for the wettest conditions mapped. The sensors now show that these tributaries flow more frequently during much smaller storms, but only for brief periods of time (hour). The high temporal sampling resolution of the sensors permits a more realistic

Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA

Science.gov (United States)

Clayton, J.A.; Kean, J.W.

2010-01-01

Investigating the routing of streamflow through a large drainage basin requires the determination of discharge at numerous locations in the channel network. Establishing a dense network of stream gages using conventional methods is both cost-prohibitive and functionally impractical for many research projects. We employ herein a previously tested, fluid-mechanically based model for generating rating curves to establish a stream gaging network in the Whitewater River basin in south-central Kansas. The model was developed for the type of channels typically found in this watershed, meaning that it is designed to handle deep, narrow geomorphically stable channels with irregular planforms, and can model overbank flow over a vegetated floodplain. We applied the model to ten previously ungaged stream reaches in the basin, ranging from third- to sixth-order channels. At each site, detailed field measurements of the channel and floodplain morphology, bed and bank roughness, and vegetation characteristics were used to quantify the roughness for a range of flow stages, from low flow to overbank flooding. Rating curves that relate stage to discharge were developed for all ten sites. Both fieldwork and modeling were completed in less than 2 years during an anomalously dry period in the region, which underscores an advantage of using theoretically based (as opposed to empirically based) discharge estimation techniques. ?? 2010 Springer Science+Business Media B.V.

Geostatistical prediction of microbial water quality throughout a stream network using meteorology, land cover, and spatiotemporal autocorrelation.

Science.gov (United States)

Holcomb, David Andrew; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

2018-06-11

Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modelled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was >90%, 10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

Documentation of a daily mean stream temperature module—An enhancement to the Precipitation-Runoff Modeling System

Science.gov (United States)

Sanders, Michael J.; Markstrom, Steven L.; Regan, R. Steven; Atkinson, R. Dwight

2017-09-15

A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.

Streaming layered video over P2P networks

NARCIS (Netherlands)

Alhaisoni, M.; Ghanbari, M.; Liotta, A.

2009-01-01

Peer-to-Peer streaming has been increasingly deployed recently. This comes out from its ability to convey the stream over the IP network to a large number of end-users (or peers). However, due to the heterogeneous nature among the peers, some of them will not be capable to relay or upload the

Hybrid Multicast-Unicast Video Streaming over Heterogeneous Cellular Networks

OpenAIRE

Almowuena, Saleh Abdullah

2016-01-01

The demand for multimedia streaming over mobile networks has been steadily increasing in the past several years. For instance, it has become common for mobile users to stream full TV episodes, sports events, and movies while on the go. Unfortunately, this growth in demand has strained the wireless networks despite the significant increase in their capacities with recent generations. It has also caused a significant increase in the energy consumption at mobile terminals. To overcome these chal...

Retrieval of Sentence Sequences for an Image Stream via Coherence Recurrent Convolutional Networks.

Science.gov (United States)

Park, Cesc Chunseong; Kim, Youngjin; Kim, Gunhee

2018-04-01

We propose an approach for retrieving a sequence of natural sentences for an image stream. Since general users often take a series of pictures on their experiences, much online visual information exists in the form of image streams, for which it would better take into consideration of the whole image stream to produce natural language descriptions. While almost all previous studies have dealt with the relation between a single image and a single natural sentence, our work extends both input and output dimension to a sequence of images and a sequence of sentences. For retrieving a coherent flow of multiple sentences for a photo stream, we propose a multimodal neural architecture called coherence recurrent convolutional network (CRCN), which consists of convolutional neural networks, bidirectional long short-term memory (LSTM) networks, and an entity-based local coherence model. Our approach directly learns from vast user-generated resource of blog posts as text-image parallel training data. We collect more than 22 K unique blog posts with 170 K associated images for the travel topics of NYC, Disneyland , Australia, and Hawaii. We demonstrate that our approach outperforms other state-of-the-art image captioning methods for text sequence generation, using both quantitative measures and user studies via Amazon Mechanical Turk.

Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change

Science.gov (United States)

Elliott, Caroline M.; Jacobson, Robert B.; Freeman, Mary C.

2014-01-01

A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the

Effects of stream topology on ecological community results from neutral models

Science.gov (United States)

While neutral theory and models have stimulated considerable literature, less well investigated is the effect of topology on neutral metacommunity model simulations. We implemented a neutral metacommunity model using two different stream network topologies, a widely branched netw...

A model for evaluating stream temperature response to climate change in Wisconsin

Science.gov (United States)

Stewart, Jana S.; Westenbroek, Stephen M.; Mitro, Matthew G.; Lyons, John D.; Kammel, Leah E.; Buchwald, Cheryl A.

2015-01-01

Expected climatic changes in air temperature and precipitation patterns across the State of Wisconsin may alter future stream temperature and flow regimes. As a consequence of flow and temperature changes, the composition and distribution of fish species assemblages are expected to change. In an effort to gain a better understanding of how climatic changes may affect stream temperature, an approach was developed to predict and project daily summertime stream temperature under current and future climate conditions for 94,341 stream kilometers across Wisconsin. The approach uses a combination of static landscape characteristics and dynamic time-series climatic variables as input for an Artificial Neural Network (ANN) Model integrated with a Soil-Water-Balance (SWB) Model. Future climate scenarios are based on output from downscaled General Circulation Models (GCMs). The SWB model provided a means to estimate the temporal variability in groundwater recharge and provided a mechanism to evaluate the effect of changing air temperature and precipitation on groundwater recharge and soil moisture. The Integrated Soil-Water-Balance and Artificial Neural Network version 1 (SWB-ANNv1) Model was used to simulate daily summertime stream temperature under current (1990–2008) climate and explained 76 percent of the variation in the daily mean based on validation at 67 independent sites. Results were summarized as July mean water temperature, and individual stream segments were classified by thermal class (cold, cold transition, warm transition, and warm) for comparison of current (1990–2008) with future climate conditions.

Performance Evaluation of Concurrent Multipath Video Streaming in Multihomed Mobile Networks

Directory of Open Access Journals (Sweden)

James Nightingale

2013-01-01

Full Text Available High-quality real-time video streaming to users in mobile networks is challenging due to the dynamically changing nature of the network paths, particularly the limited bandwidth and varying end-to-end delay. In this paper, we empirically investigate the performance of multipath streaming in the context of multihomed mobile networks. Existing schemes that make use of the aggregated bandwidth of multiple paths can overcome bandwidth limitations on a single path but suffer an efficiency penalty caused by retransmission of lost packets in reliable transport schemes or path switching overheads in unreliable transport schemes. This work focuses on the evaluation of schemes to permit concurrent use of multiple paths to deliver video streams. A comprehensive streaming framework for concurrent multipath video streaming is proposed and experimentally evaluated, using current state-of-the-art H.264 Scalable Video Coding (H.264/SVC and the next generation High Efficiency Video Coding (HEVC standards. It provides a valuable insight into the benefit of using such schemes in conjunction with encoder specific packet prioritisation mechanisms for quality-aware packet scheduling and scalable streaming. The remaining obstacles to deployment of concurrent multipath schemes are identified, and the challenges in realising HEVC based concurrent multipath streaming are highlighted.

The interaction between network ties and business modeling : Case studies of sustainability-oriented innovations

NARCIS (Netherlands)

Oskam, Inge; Bossink, Bart; de Man, Ard Pieter

2018-01-01

A stream of literature is emerging where network development and business modeling intersect. Various authors emphasize that networks influence business models. This paper extends this stream of literature by studying two cases in which we analyze how business modeling and networking interact over

The Interaction between network ties and business modeling : case studies of sustainability-oriented innovations

NARCIS (Netherlands)

Oskam, Inge; Bossink, Bart; de Man, Ard-Pieter

2018-01-01

A stream of literature is emerging where network development and business modeling intersect. Various authors emphasize that networks influence business models. This paper extends this stream of literature by studying two cases in which we analyze how business modeling and networking interact over

Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks.

Science.gov (United States)

Duda, Piotr; Jaworski, Maciej; Rutkowski, Leszek

2018-03-01

One of the greatest challenges in data mining is related to processing and analysis of massive data streams. Contrary to traditional static data mining problems, data streams require that each element is processed only once, the amount of allocated memory is constant and the models incorporate changes of investigated streams. A vast majority of available methods have been developed for data stream classification and only a few of them attempted to solve regression problems, using various heuristic approaches. In this paper, we develop mathematically justified regression models working in a time-varying environment. More specifically, we study incremental versions of generalized regression neural networks, called IGRNNs, and we prove their tracking properties - weak (in probability) and strong (with probability one) convergence assuming various concept drift scenarios. First, we present the IGRNNs, based on the Parzen kernels, for modeling stationary systems under nonstationary noise. Next, we extend our approach to modeling time-varying systems under nonstationary noise. We present several types of concept drifts to be handled by our approach in such a way that weak and strong convergence holds under certain conditions. Finally, in the series of simulations, we compare our method with commonly used heuristic approaches, based on forgetting mechanism or sliding windows, to deal with concept drift. Finally, we apply our concept in a real life scenario solving the problem of currency exchange rates prediction.

Use of multiple dispersal pathways facilitates amphibian persistence in stream networks

Science.gov (United States)

Campbell, Grant E.H.; Nichols, J.D.; Lowe, W.H.; Fagan, W.F.

2010-01-01

Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

Use of multiple dispersal pathways facilitates amphibian persistence in stream networks.

Science.gov (United States)

Campbell Grant, Evan H; Nichols, James D; Lowe, Winsor H; Fagan, William F

2010-04-13

Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

Directory of Open Access Journals (Sweden)

Benjamin H. Letcher

2016-02-01

Full Text Available Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C, identified a clear warming trend (0.63 °C decade−1 and a widening of the synchronized period (29 d decade−1. We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data. Missing all data for a year decreased performance (∼0.6 °C jump in RMSE, but this decrease was moderated when data were available from other streams in the network.

Using Streaming Analytics for Effective Real Time Network Visibility -

Science.gov (United States)

on in your network right now. Certainly the other thing that we talked about on the big data side was [inaudible] data. So now we'll drill into - so this is all the traffic from the internal network to the taking a streaming analytics approach to network traffic analysis. So we can go to the next - there we go

Fragmentation alters stream fish community structure in dendritic ecological networks.

Science.gov (United States)

Perkin, Joshuah S; Gido, Keith B

2012-12-01

Effects of fragmentation on the ecology of organisms occupying dendritic ecological networks (DENs) have recently been described through both conceptual and mathematical models, but few hypotheses have been tested in complex, real-world ecosystems. Stream fishes provide a model system for assessing effects of fragmentation on the structure of communities occurring within DENs, including how fragmentation alters metacommunity dynamics and biodiversity. A recently developed habitat-availability measure, the "dendritic connectivity index" (DCI), allows for assigning quantitative measures of connectivity in DENs regardless of network extent or complexity, and might be used to predict fish community response to fragmentation. We characterized stream fish community structure in 12 DENs in the Great Plains, USA, during periods of dynamic (summer) and muted (fall) discharge regimes to test the DCI as a predictive model of fish community response to fragmentation imposed by road crossings. Results indicated that fish communities in stream segments isolated by road crossings had reduced species richness (alpha diversity) relative to communities that maintained connectivity with the surrounding DEN during summer and fall. Furthermore, isolated communities had greater dissimilarity (beta diversity) to downstream sites notisolated by road crossings during summer and fall. Finally, dissimilarity among communities within DENs decreased as a function of increased habitat connectivity (measured using the DCI) for summer and fall, suggesting that communities within highly connected DENs tend to be more homogeneous. Our results indicate that the DCI is sensitive to community effects of fragmentation in riverscapes and might be used by managers to predict ecological responses to changes in habitat connectivity. Moreover, our findings illustrate that relating structural connectivity of riverscapes to functional connectivity among communities might aid in maintaining metacommunity

Network Monitoring as a Streaming Analytics Problem

KAUST Repository

Gupta, Arpit; Birkner, Rü diger; Canini, Marco; Feamster, Nick; Mac-Stoker, Chris; Willinger, Walter

2016-01-01

, processing such network monitoring queries at high traffic rates requires both the switches and the stream processors to filter the traffic iteratively and adaptively so as to extract only that traffic that is of interest to the query at hand. Others have

Fast algorithm for automatically computing Strahler stream order

Science.gov (United States)

Lanfear, Kenneth J.

1990-01-01

An efficient algorithm was developed to determine Strahler stream order for segments of stream networks represented in a Geographic Information System (GIS). The algorithm correctly assigns Strahler stream order in topologically complex situations such as braided streams and multiple drainage outlets. Execution time varies nearly linearly with the number of stream segments in the network. This technique is expected to be particularly useful for studying the topology of dense stream networks derived from digital elevation model data.

Testing a Cloud Provider Network for Hybrid P2P and Cloud Streaming Architectures

OpenAIRE

Cerviño Arriba, Javier; Rodríguez, Pedro; Trajkovska, Irena; Mozo Velasco, Alberto; Salvachúa Rodríguez, Joaquín

2011-01-01

The number of online real-time streaming services deployed over network topologies like P2P or centralized ones has remarkably increased in the recent years. This has revealed the lack of networks that are well prepared to respond to this kind of traffic. A hybrid distribution network can be an efficient solution for real-time streaming services. This paper contains the experimental results of streaming distribution in a hybrid architecture that consist of mixed connections among P2P and Clou...

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

Science.gov (United States)

Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Douglas S.

2004-01-01

Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

Network Structure as a Modulator of Disturbance Impacts in Streams

Science.gov (United States)

Warner, S.; Tullos, D. D.

2017-12-01

This study examines how river network structure affects the propagation of geomorphic and anthropogenic disturbances through streams. Geomorphic processes such as debris flows can alter channel morphology and modify habitat for aquatic biota. Anthropogenic disturbances such as road construction can interact with the geomorphology and hydrology of forested watersheds to change sediment and water inputs to streams. It was hypothesized that the network structure of streams within forested watersheds would influence the location and magnitude of the impacts of debris flows and road construction on sediment size and channel width. Longitudinal surveys were conducted every 50 meters for 11 kilometers of third-to-fifth order streams in the H.J. Andrews Experimental Forest in the Western Cascade Range of Oregon. Particle counts and channel geometry measurements were collected to characterize the geomorphic impacts of road crossings and debris flows as disturbances. Sediment size distributions and width measurements were plotted against the distance of survey locations through the network to identify variations in longitudinal trends of channel characteristics. Thresholds for the background variation in sediment size and channel width, based on the standard deviations of sample points, were developed for sampled stream segments characterized by location as well as geomorphic and land use history. Survey locations were classified as "disturbed" when they deviated beyond the reference thresholds in expected sediment sizes and channel widths, as well as flow-connected proximity to debris flows and road crossings. River network structure was quantified by drainage density and centrality of nodes upstream of survey locations. Drainage density and node centrality were compared between survey locations with similar channel characteristic classifications. Cluster analysis was used to assess the significance of survey location, proximity of survey location to debris flows and road

Encrypted data stream identification using randomness sparse representation and fuzzy Gaussian mixture model

Science.gov (United States)

Zhang, Hong; Hou, Rui; Yi, Lei; Meng, Juan; Pan, Zhisong; Zhou, Yuhuan

2016-07-01

The accurate identification of encrypted data stream helps to regulate illegal data, detect network attacks and protect users' information. In this paper, a novel encrypted data stream identification algorithm is introduced. The proposed method is based on randomness characteristics of encrypted data stream. We use a l1-norm regularized logistic regression to improve sparse representation of randomness features and Fuzzy Gaussian Mixture Model (FGMM) to improve identification accuracy. Experimental results demonstrate that the method can be adopted as an effective technique for encrypted data stream identification.

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

Energy Technology Data Exchange (ETDEWEB)

Rossi, R; Gallagher, B; Neville, J; Henderson, K

2011-11-11

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied our model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.

A Context-Aware Adaptive Streaming Media Distribution System in a Heterogeneous Network with Multiple Terminals

Directory of Open Access Journals (Sweden)

Yepeng Ni

2016-01-01

Full Text Available We consider the problem of streaming media transmission in a heterogeneous network from a multisource server to home multiple terminals. In wired network, the transmission performance is limited by network state (e.g., the bandwidth variation, jitter, and packet loss. In wireless network, the multiple user terminals can cause bandwidth competition. Thus, the streaming media distribution in a heterogeneous network becomes a severe challenge which is critical for QoS guarantee. In this paper, we propose a context-aware adaptive streaming media distribution system (CAASS, which implements the context-aware module to perceive the environment parameters and use the strategy analysis (SA module to deduce the most suitable service level. This approach is able to improve the video quality for guarantying streaming QoS. We formulate the optimization problem of QoS relationship with the environment parameters based on the QoS testing algorithm for IPTV in ITU-T G.1070. We evaluate the performance of the proposed CAASS through 12 types of experimental environments using a prototype system. Experimental results show that CAASS can dynamically adjust the service level according to the environment variation (e.g., network state and terminal performances and outperforms the existing streaming approaches in adaptive streaming media distribution according to peak signal-to-noise ratio (PSNR.

Association rule extraction from XML stream data for wireless sensor networks.

Science.gov (United States)

Paik, Juryon; Nam, Junghyun; Kim, Ung Mo; Won, Dongho

2014-07-18

With the advances of wireless sensor networks, they yield massive volumes of disparate, dynamic and geographically-distributed and heterogeneous data. The data mining community has attempted to extract knowledge from the huge amount of data that they generate. However, previous mining work in WSNs has focused on supporting simple relational data structures, like one table per network, while there is a need for more complex data structures. This deficiency motivates XML, which is the current de facto format for the data exchange and modeling of a wide variety of data sources over the web, to be used in WSNs in order to encourage the interchangeability of heterogeneous types of sensors and systems. However, mining XML data for WSNs has two challenging issues: one is the endless data flow; and the other is the complex tree structure. In this paper, we present several new definitions and techniques related to association rule mining over XML data streams in WSNs. To the best of our knowledge, this work provides the first approach to mining XML stream data that generates frequent tree items without any redundancy.

Spatial Statistical Network Models for Stream and River Temperatures in the Chesapeake Bay Watershed

Science.gov (United States)

Numerous metrics have been proposed to describe stream/river thermal regimes, and researchers are still struggling with the need to describe thermal regimes in a parsimonious fashion. Regional temperature models are needed for characterizing and mapping current stream thermal re...

Retrofit of heat exchanger networks with pressure recovery of process streams at sub-ambient conditions

International Nuclear Information System (INIS)

Onishi, Viviani C.; Ravagnani, Mauro A.S.S.; Caballero, José A.

2015-01-01

Highlights: • New mathematical model for heat exchanger networks retrofit with pressure recovery. • Optimal heat and work integration applied to the retrofit of sub-ambient processes. • Streams pressure manipulation is used to enhance heat integration of the system. • Compressors and turbines can act on a coupling shaft and/or as stand-alone equipment. • Use of smaller amount of cold utilities, reducing significantly the operational costs. - Abstract: This paper presents a new mathematical programming model for the retrofit of heat exchanger networks (HENs), wherein the pressure recovery of process streams is conducted to enhance heat integration. Particularly applied to cryogenic processes, HENs retrofit with combined heat and work integration is mainly aimed at reducing the use of expensive cold services. The proposed multi-stage superstructure allows the increment of the existing heat transfer area, as well as the use of new equipment for both heat exchange and pressure manipulation. The pressure recovery of streams is carried out simultaneously with the HEN design, such that the process conditions (streams pressure and temperature) are variables of optimization. The mathematical model is formulated using generalized disjunctive programming (GDP) and is optimized via mixed-integer nonlinear programming (MINLP), through the minimization of the retrofit total annualized cost, considering the turbine and compressor coupling with a helper motor. Three case studies are performed to assess the accuracy of the developed approach, including a real industrial example related to liquefied natural gas (LNG) production. The results show that the pressure recovery of streams is efficient for energy savings and, consequently, for decreasing the HEN retrofit total cost especially in sub-ambient processes

Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming

International Nuclear Information System (INIS)

Ibrahimy, Abdullah Faruq Ibn; Rafiqul, Islam Md; Anwar, Farhat; Ibrahimy, Muhammad Ibn

2013-01-01

The live video data is streaming usually in a tree-based overlay network or in a mesh-based overlay network. In case of departure of a peer with additional upload bandwidth, the overlay network becomes very vulnerable to churn. In this paper, a two dimensional array-based overlay network is proposed for streaming the live video stream data. As there is always a peer or a live video streaming server to upload the live video stream data, so the overlay network is very stable and very robust to churn. Peers are placed according to their upload and download bandwidth, which enhances the balance of load and performance. The overlay network utilizes the additional upload bandwidth of peers to minimize chunk delivery delay and to maximize balance of load. The procedure, which is used for distributing the additional upload bandwidth of the peers, distributes the additional upload bandwidth to the heterogeneous strength peers in a fair treat distribution approach and to the homogeneous strength peers in a uniform distribution approach. The proposed overlay network has been simulated by Qualnet from Scalable Network Technologies and results are presented in this paper

Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming

Science.gov (United States)

Faruq Ibn Ibrahimy, Abdullah; Rafiqul, Islam Md; Anwar, Farhat; Ibn Ibrahimy, Muhammad

2013-12-01

The live video data is streaming usually in a tree-based overlay network or in a mesh-based overlay network. In case of departure of a peer with additional upload bandwidth, the overlay network becomes very vulnerable to churn. In this paper, a two dimensional array-based overlay network is proposed for streaming the live video stream data. As there is always a peer or a live video streaming server to upload the live video stream data, so the overlay network is very stable and very robust to churn. Peers are placed according to their upload and download bandwidth, which enhances the balance of load and performance. The overlay network utilizes the additional upload bandwidth of peers to minimize chunk delivery delay and to maximize balance of load. The procedure, which is used for distributing the additional upload bandwidth of the peers, distributes the additional upload bandwidth to the heterogeneous strength peers in a fair treat distribution approach and to the homogeneous strength peers in a uniform distribution approach. The proposed overlay network has been simulated by Qualnet from Scalable Network Technologies and results are presented in this paper.

Supporting Dynamic Adaptive Streaming over HTTP in Wireless Meshed Networks using Random Linear Network Coding

DEFF Research Database (Denmark)

Hundebøll, Martin; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani

2014-01-01

This work studies the potential and impact of the FRANC network coding protocol for delivering high quality Dynamic Adaptive Streaming over HTTP (DASH) in wireless networks. Although DASH aims to tailor the video quality rate based on the available throughput to the destination, it relies...

STARS: An ArcGIS Toolset Used to Calculate the Spatial Information Needed to Fit Spatial Statistical Models to Stream Network Data

Directory of Open Access Journals (Sweden)

Erin Peterson

2014-01-01

Full Text Available This paper describes the STARS ArcGIS geoprocessing toolset, which is used to calcu- late the spatial information needed to fit spatial statistical models to stream network data using the SSN package. The STARS toolset is designed for use with a landscape network (LSN, which is a topological data model produced by the FLoWS ArcGIS geoprocessing toolset. An overview of the FLoWS LSN structure and a few particularly useful tools is also provided so that users will have a clear understanding of the underlying data struc- ture that the STARS toolset depends on. This document may be used as an introduction to new users. The methods used to calculate the spatial information and format the final .ssn object are also explicitly described so that users may create their own .ssn object using other data models and software.

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks.

Science.gov (United States)

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN).

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

Science.gov (United States)

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN). PMID:27907113

Ecohydrological and subsurface controls on drought-induced contraction and disconnection of stream networks

Science.gov (United States)

Godsey, S.; Kirchner, J. W.; Whiting, J. A.

2016-12-01

Temporary headwater streams - both intermittent and ephemeral waterways - supply water to approximately 1/3 of the US population, and 60% of streams used for drinking water are temporary. Stream ecologists increasingly recognize that a gradient of processes across the drying continuum affect ecosystems at dynamic terrestrial-aquatic interfaces. Understanding the hydrological controls across that gradient of drying may improve management of these sensitive systems. One possible control on surface flows includes transpiration losses from either the riparian zone or the entire watershed. We mapped several stream networks under extreme low flow conditions brought on by severe drought in central Idaho and California in 2015. Compared to previous low-flow stream length estimates, the active drainage network had generally decreased by a very small amount across these sites, perhaps because stored water buffered the precipitation decrease, or because flowing channel heads are fixed by focused groundwater flow emerging at springs. We also examined the apparent sources of water for both riparian and hillslope trees using isotopic techniques. During drought conditions, we hypothesized that riparian trees - but not those far from flowing streams - would be sustained by streamflow recharging riparian aquifers, and thus would transpire water that was isotopically similar to streamflow because little soil water would remain available below the wilting point and stream water would be sustain those trees. We found a more complex pattern, but in most places stream water and water transpired by trees were isotopically distinct regardless of flow intermittency or tree location. We also found that hillslope trees outside of the riparian zone appeared to be using different waters from those used by riparian trees. Finally, we explore subsurface controls on network extent, showing that bedrock characteristics can influence network stability and contraction patterns.

System architecture for ubiquitous live video streaming in university network environment

CSIR Research Space (South Africa)

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...

Streaming Multimedia via Overlay Networks using Wi-Fi Peer-to-Peer Connections

DEFF Research Database (Denmark)

Poderys, Justas; Soler, José

2017-01-01

Short range ad-hoc wireless networks can be used to deliver streaming multimedia for information, entertainment and advertisement purposes. To enable short-range communication between various devices, the Wi-Fi Alliance proposed an extension to the IEEE802.11 Wi-Fi standard called Wi-Fi Peer......-to-Peer (P2P). It allows compliant devices to form ad-hoc communication groups without interrupting conventional access point-based Wi-Fi communication. This paper proposes to use Wi-Fi P2P connectivity to distribute streaming multimedia in ah-hoc formed user groups. The exchange of multimedia data...... is performed by forming an overlay network using Peer-to-Peer Streaming Peer Protocol (PPSPP). In order to make PPSPP function over WiFi P2P connections, this paper proposes a number of changes to the protocol. The performance of the proposed system is evaluated using a computer networks emulator...

Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

Science.gov (United States)

Brennan, Sean R.; Torgersen, Christian E.; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K.; Schindler, Daniel E.

2016-05-01

A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called "isoscapes," form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

Dynamical modeling of tidal streams

International Nuclear Information System (INIS)

Bovy, Jo

2014-01-01

I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

Association Rule Extraction from XML Stream Data for Wireless Sensor Networks

Science.gov (United States)

Paik, Juryon; Nam, Junghyun; Kim, Ung Mo; Won, Dongho

2014-01-01

With the advances of wireless sensor networks, they yield massive volumes of disparate, dynamic and geographically-distributed and heterogeneous data. The data mining community has attempted to extract knowledge from the huge amount of data that they generate. However, previous mining work in WSNs has focused on supporting simple relational data structures, like one table per network, while there is a need for more complex data structures. This deficiency motivates XML, which is the current de facto format for the data exchange and modeling of a wide variety of data sources over the web, to be used in WSNs in order to encourage the interchangeability of heterogeneous types of sensors and systems. However, mining XML data for WSNs has two challenging issues: one is the endless data flow; and the other is the complex tree structure. In this paper, we present several new definitions and techniques related to association rule mining over XML data streams in WSNs. To the best of our knowledge, this work provides the first approach to mining XML stream data that generates frequent tree items without any redundancy. PMID:25046017

Fine-Grained Rate Shaping for Video Streaming over Wireless Networks

Directory of Open Access Journals (Sweden)

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.

A GIS-based groundwater travel time model to evaluate stream nitrate concentration reductions from land use change

Science.gov (United States)

Schilling, K.E.; Wolter, C.F.

2007-01-01

Excessive nitrate-nitrogen (nitrate) loss from agricultural watersheds is an environmental concern. A common conservation practice to improve stream water quality is to retire vulnerable row croplands to grass. In this paper, a groundwater travel time model based on a geographic information system (GIS) analysis of readily available soil and topographic variables was used to evaluate the time needed to observe stream nitrate concentration reductions from conversion of row crop land to native prairie in Walnut Creek watershed, Iowa. Average linear groundwater velocity in 5-m cells was estimated by overlaying GIS layers of soil permeability, land slope (surrogates for hydraulic conductivity and gradient, respectively) and porosity. Cells were summed backwards from the stream network to watershed divide to develop a travel time distribution map. Results suggested that groundwater from half of the land planted in prairie has reached the stream network during the 10 years of ongoing water quality monitoring. The mean travel time for the watershed was estimated to be 10.1 years, consistent with results from a simple analytical model. The proportion of land in the watershed and subbasins with prairie groundwater reaching the stream (10-22%) was similar to the measured reduction of stream nitrate (11-36%). Results provide encouragement that additional nitrate reductions in Walnut Creek are probable in the future as reduced nitrate groundwater from distal locations discharges to the stream network in the coming years. The high spatial resolution of the model (5-m cells) and its simplicity may make it potentially applicable for land managers interested in communicating lag time issues to the public, particularly related to nitrate concentration reductions over time. ?? 2007 Springer-Verlag.

Streaming-aware channel utilization improvement for wireless home networks

NARCIS (Netherlands)

Aslam, W.; Lukkien, J.J.

2012-01-01

A wireless network of consumer electronic (CE) devices in a modern home, is typically running streaming services with heterogeneous bandwidth demands. Satisfying these demands offers the challenge of mapping them efficiently onto scarce wireless channel bandwidth. This mapping is supported by the

A Wave-guide Model for Packetized Media Streaming in Lossless Networks

NARCIS (Netherlands)

Konstantas, D.; Widya, I.A.

2002-01-01

Optimal operation of network based multimedia applications requires a precise specification of the network parameters. Different models have been used in the past in calculating the behavior of the network and defining parameters like throughput and delays of packets, using among others fluid

Energy from streaming current and potential

NARCIS (Netherlands)

Olthuis, Wouter; Schippers, Bob; Eijkel, Jan C.T.; van den Berg, Albert

2005-01-01

It is investigated how much energy can be delivered by a streaming current source. A streaming current and subsequent streaming potential originate when double layer charge is transported by hydrodynamic flow. Theory and a network model of such a source is presented and initial experimental results

Convolutional Codes with Maximum Column Sum Rank for Network Streaming

OpenAIRE

Mahmood, Rafid; Badr, Ahmed; Khisti, Ashish

2015-01-01

The column Hamming distance of a convolutional code determines the error correction capability when streaming over a class of packet erasure channels. We introduce a metric known as the column sum rank, that parallels column Hamming distance when streaming over a network with link failures. We prove rank analogues of several known column Hamming distance properties and introduce a new family of convolutional codes that maximize the column sum rank up to the code memory. Our construction invol...

InSTREAM: the individual-based stream trout research and environmental assessment model

Science.gov (United States)

Steven F. Railsback; Bret C. Harvey; Stephen K. Jackson; Roland H. Lamberson

2009-01-01

This report documents Version 4.2 of InSTREAM, including its formulation, software, and application to research and management problems. InSTREAM is a simulation model designed to understand how stream and river salmonid populations respond to habitat alteration, including altered flow, temperature, and turbidity regimes and changes in channel morphology. The model...

Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

KAUST Repository

Alsibyani, Hassan M.

2018-05-15

Cloud computing usage is increasing and a common concern is the privacy and security of the data and computation. Third party cloud environments are not considered fit for processing private information because the data will be revealed to the cloud provider. However, Trusted Execution Environments (TEEs), such as Intel SGX, provide a way for applications to run privately and securely on untrusted platforms. Nonetheless, using a TEE by itself for stream processing systems is not sufficient since network communication patterns may leak properties of the data under processing. This work addresses leaky topology structures and suggests mitigation techniques for each of these. We create specific metrics to evaluate leaks occurring from the network patterns; the metrics measure information leaked when the stream processing system is running. We consider routing techniques for inter-stage communication in a streaming application to mitigate this data leakage. We consider a dynamic policy to change the mitigation technique depending on how much information is currently leaking. Additionally, we consider techniques to hide irregularities resulting from a filtering stage in a topology. We also consider leakages resulting from applications containing cycles. For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing system.

New metrics for evaluating channel networks extracted in grid digital elevation models

Science.gov (United States)

Orlandini, S.; Moretti, G.

2017-12-01

Channel networks are critical components of drainage basins and delta regions. Despite the important role played by these systems in hydrology and geomorphology, there are at present no well-defined methods to evaluate numerically how two complex channel networks are geometrically far apart. The present study introduces new metrics for evaluating numerically channel networks extracted in grid digital elevation models with respect to a reference channel network (see the figure below). Streams of the evaluated network (EN) are delineated as in the Horton ordering system and examined through a priority climbing algorithm based on the triple index (ID1,ID2,ID3), where ID1 is a stream identifier that increases as the elevation of lower end of the stream increases, ID2 indicates the ID1 of the draining stream, and ID3 is the ID1 of the corresponding stream in the reference network (RN). Streams of the RN are identified by the double index (ID1,ID2). Streams of the EN are processed in the order of increasing ID1 (plots a-l in the figure below). For each processed stream of the EN, the closest stream of the RN is sought by considering all the streams of the RN sharing the same ID2. This ID2 in the RN is equal in the EN to the ID3 of the stream draining the processed stream, the one having ID1 equal to the ID2 of the processed stream. The mean stream planar distance (MSPD) and the mean stream elevation drop (MSED) are computed as the mean distance and drop, respectively, between corresponding streams. The MSPD is shown to be useful for evaluating slope direction methods and thresholds for channel initiation, whereas the MSED is shown to indicate the ability of grid coarsening strategies to retain the profiles of observed channels. The developed metrics fill a gap in the existing literature by allowing hydrologists and geomorphologists to compare descriptions of a fixed physical system obtained by using different terrain analysis methods, or different physical systems

Potential interaction between transport and stream networks over the lowland rivers in Eastern India.

Science.gov (United States)

Roy, Suvendu; Sahu, Abhay Sankar

2017-07-15

Extension of transport networks supports good accessibility and associated with the development of a region. However, transport lines have fragmented the regional landscape and disturbed the natural interplay between rivers and their floodplains. Spatial analysis using multiple buffers provides information about the potential interaction between road and stream networks and their impact on channel morphology of a small watershed in the Lower Gangetic Plain. Present study is tried to understand the lateral and longitudinal disconnection in headwater stream by rural roads with the integration of geoinformatics and field survey. Significant (p development, delineation of stream corridor, regular monitoring and engineering efficiency for the construction of road and road-stream crossing might be effective in managing river geomorphology and riverine landscape. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cooperative Coding and Caching for Streaming Data in Multihop Wireless Networks

Directory of Open Access Journals (Sweden)

Liu Jiangchuan

2010-01-01

Full Text Available This paper studies the distributed caching managements for the current flourish of the streaming applications in multihop wireless networks. Many caching managements to date use randomized network coding approach, which provides an elegant solution for ubiquitous data accesses in such systems. However, the encoding, essentially a combination operation, makes the coded data difficult to be changed. In particular, to accommodate new data, the system may have to first decode all the combined data segments, remove some unimportant ones, and then reencode the data segments again. This procedure is clearly expensive for continuously evolving data storage. As such, we introduce a novel Cooperative Coding and Caching ( scheme, which allows decoding-free data removal through a triangle-like codeword organization. Its decoding performance is very close to the conventional network coding with only a sublinear overhead. Our scheme offers a promising solution to the caching management for streaming data.

Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks

KAUST Repository

Wang, Wei; Guyet, Thomas; Quiniou, René ; Cordier, Marie-Odile; Masseglia, Florent; Zhang, Xiangliang

2014-01-01

In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.

Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks

KAUST Repository

Wang, Wei

2014-06-22

In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.

Performance Evaluation of UML2-Modeled Embedded Streaming Applications with System-Level Simulation

Directory of Open Access Journals (Sweden)

Arpinen Tero

2009-01-01

Full Text Available This article presents an efficient method to capture abstract performance model of streaming data real-time embedded systems (RTESs. Unified Modeling Language version 2 (UML2 is used for the performance modeling and as a front-end for a tool framework that enables simulation-based performance evaluation and design-space exploration. The adopted application meta-model in UML resembles the Kahn Process Network (KPN model and it is targeted at simulation-based performance evaluation. The application workload modeling is done using UML2 activity diagrams, and platform is described with structural UML2 diagrams and model elements. These concepts are defined using a subset of the profile for Modeling and Analysis of Realtime and Embedded (MARTE systems from OMG and custom stereotype extensions. The goal of the performance modeling and simulation is to achieve early estimates on task response times, processing element, memory, and on-chip network utilizations, among other information that is used for design-space exploration. As a case study, a video codec application on multiple processors is modeled, evaluated, and explored. In comparison to related work, this is the first proposal that defines transformation between UML activity diagrams and streaming data application workload meta models and successfully adopts it for RTES performance evaluation.

Cooperative Coding and Caching for Streaming Data in Multihop Wireless Networks

Directory of Open Access Journals (Sweden)

Dan Wang

2010-01-01

Full Text Available This paper studies the distributed caching managements for the current flourish of the streaming applications in multihop wireless networks. Many caching managements to date use randomized network coding approach, which provides an elegant solution for ubiquitous data accesses in such systems. However, the encoding, essentially a combination operation, makes the coded data difficult to be changed. In particular, to accommodate new data, the system may have to first decode all the combined data segments, remove some unimportant ones, and then reencode the data segments again. This procedure is clearly expensive for continuously evolving data storage. As such, we introduce a novel Cooperative Coding and Caching (C3 scheme, which allows decoding-free data removal through a triangle-like codeword organization. Its decoding performance is very close to the conventional network coding with only a sublinear overhead. Our scheme offers a promising solution to the caching management for streaming data.

Rotenone persistence model for montane streams

Science.gov (United States)

Brown, Peter J.; Zale, Alexander V.

2012-01-01

The efficient and effective use of rotenone is hindered by its unknown persistence in streams. Environmental conditions degrade rotenone, but current label instructions suggest fortifying the chemical along a stream based on linear distance or travel time rather than environmental conditions. Our objective was to develop models that use measurements of environmental conditions to predict rotenone persistence in streams. Detailed measurements of ultraviolet radiation, water temperature, dissolved oxygen, total dissolved solids (TDS), conductivity, pH, oxidation–reduction potential (ORP), substrate composition, amount of organic matter, channel slope, and travel time were made along stream segments located between rotenone treatment stations and cages containing bioassay fish in six streams. The amount of fine organic matter, biofilm, sand, gravel, cobble, rubble, small boulders, slope, pH, TDS, ORP, light reaching the stream, energy dissipated, discharge, and cumulative travel time were each significantly correlated with fish death. By using logistic regression, measurements of environmental conditions were paired with the responses of bioassay fish to develop a model that predicted the persistence of rotenone toxicity in streams. This model was validated with data from two additional stream treatment reaches. Rotenone persistence was predicted by a model that used travel time, rubble, and ORP. When this model predicts a probability of less than 0.95, those who apply rotenone can expect incomplete eradication and should plan on fortifying rotenone concentrations. The significance of travel time has been previously identified and is currently used to predict rotenone persistence. However, rubble substrate, which may be associated with the degradation of rotenone by adsorption and volatilization in turbulent environments, was not previously considered.

Scalable and Media Aware Adaptive Video Streaming over Wireless Networks

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Béatrice Pesquet-Popescu

2008-07-01

Full Text Available This paper proposes an advanced video streaming system based on scalable video coding in order to optimize resource utilization in wireless networks with retransmission mechanisms at radio protocol level. The key component of this system is a packet scheduling algorithm which operates on the different substreams of a main scalable video stream and which is implemented in a so-called media aware network element. The concerned type of transport channel is a dedicated channel subject to parameters (bitrate, loss rate variations on the long run. Moreover, we propose a combined scalability approach in which common temporal and SNR scalability features can be used jointly with a partitioning of the image into regions of interest. Simulation results show that our approach provides substantial quality gain compared to classical packet transmission methods and they demonstrate how ROI coding combined with SNR scalability allows to improve again the visual quality.

Potential stream density in Mid-Atlantic US watersheds.

Science.gov (United States)

Elmore, Andrew J; Julian, Jason P; Guinn, Steven M; Fitzpatrick, Matthew C

2013-01-01

Stream network density exerts a strong influence on ecohydrologic processes in watersheds, yet existing stream maps fail to capture most headwater streams and therefore underestimate stream density. Furthermore, discrepancies between mapped and actual stream length vary between watersheds, confounding efforts to understand the impacts of land use on stream ecosystems. Here we report on research that predicts stream presence from coupled field observations of headwater stream channels and terrain variables that were calculated both locally and as an average across the watershed upstream of any location on the landscape. Our approach used maximum entropy modeling (MaxEnt), a robust method commonly implemented to model species distributions that requires information only on the presence of the entity of interest. In validation, the method correctly predicts the presence of 86% of all 10-m stream segments and errors are low (stream density and compare our results with the National Hydrography Dataset (NHD). We find that NHD underestimates stream density by up to 250%, with errors being greatest in the densely urbanized cities of Washington, DC and Baltimore, MD and in regions where the NHD has never been updated from its original, coarse-grain mapping. This work is the most ambitious attempt yet to map stream networks over a large region and will have lasting implications for modeling and conservation efforts.

A time-varying subjective quality model for mobile streaming videos with stalling events

Science.gov (United States)

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C.

2015-09-01

Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.

Data Centric Sensor Stream Reduction for Real-Time Applications in Wireless Sensor Networks

Science.gov (United States)

Aquino, Andre Luiz Lins; Nakamura, Eduardo Freire

2009-01-01

This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness. PMID:22303145

Landscape control on the hydrogeochemistry of As, Co and Pb in a boreal stream network

Science.gov (United States)

Wällstedt, Teresia; Björkvald, Louise; Laudon, Hjalmar; Borg, Hans; Mörth, Carl-Magnus

2017-08-01

In a boreal stream network, stream water concentrations of As, Co and Pb (filtered, 30% wetland), which was suggested to be controlled by atmospheric deposition in combination with high DOC release from the wetlands. For Co, the highest concentrations were found in the forest dominated sites (>98% forest), which were attributed to the weathering of minerogenic sources. Contrasting response to runoff events could also be related to landscape type; during the spring flood, decreasing concentrations of As, Co and Pb were observed in the wetland dominated catchments due to dilution, while increasing concentrations during spring flood were observed in the mixed catchments (2-30% wetland) and to some degree in the forested catchments, probably due to flushing of the organic-rich riparian sources. Further, metal speciation was calculated using the geochemical equilibrium model Visual MINTEQ. This suggests that dissolved inorganic species of As and Co dominated in headwater streams with low pH while DOC had a major influencing role for Pb. In the larger mixed streams where pH was higher and precipitation of e.g. colloidal Fe and Mn (hydr)oxides was favoured, the major influencing factor was instead adsorption to colloidal Fe for As and Pb, while association to organic matter and colloids of e.g. Mn influenced the concentrations of Co. We thus conclude that landscape type and the magnitude of the runoff events are of great importance for the spatial and temporal variations of As, Co and Pb in this boreal stream network. Projected climate change, with increasing runoff, may therefore influence riverine concentrations and fluxes differently, depending on the prevailing landscape type.

ER network homeostasis is critical for plant endosome streaming and endocytosis

Science.gov (United States)

Stefano, Giovanni; Renna, Luciana; Lai, YaShiuan; Slabaugh, Erin; Mannino, Nicole; Buono, Rafael A; Otegui, Marisa S; Brandizzi, Federica

2015-01-01

Eukaryotic cells internalize cargo at the plasma membrane via endocytosis, a vital process that is accomplished through a complex network of endosomal organelles. In mammalian cells, the ER is in close association with endosomes and regulates their fission. Nonetheless, the physiological role of such interaction on endocytosis is yet unexplored. Here, we probed the existence of ER–endosome association in plant cells and assayed its physiological role in endocytosis. Through live-cell imaging and electron microscopy studies, we established that endosomes are extensively associated with the plant ER, supporting conservation of interaction between heterotypic organelles in evolutionarily distant kingdoms. Furthermore, by analyzing ER–endosome dynamics in genetic backgrounds with defects in ER structure and movement, we also established that the ER network integrity is necessary for homeostasis of the distribution and streaming of various endosome populations as well as for efficient endocytosis. These results support a novel model that endocytosis homeostasis depends on a spatiotemporal control of the endosome dynamics dictated by the ER membrane network. PMID:27462431

Synchronized Multimedia Streaming on the iPhone Platform with Network Coding

DEFF Research Database (Denmark)

Vingelmann, Peter; Fitzek, Frank; Pedersen, Morten Videbæk

2011-01-01

on the iPhone that use point-to-point architectures. After acknowledging their limitations, we propose a solution based on network coding to efficiently and reliably deliver the multimedia content to many devices in a synchronized manner. Then we introduce an application that implements this technique......This work presents the implementation of synchronized multimedia streaming for the Apple iPhone platform. The idea is to stream multimedia content from a single source to multiple receivers with direct or multihop connections to the source. First we look into existing solutions for video streaming...... on the iPhone. We also present our testbed, which consists of 16 iPod Touch devices to showcase the capabilities of our application....

Estimation of Total Nitrogen and Phosphorus in New England Streams Using Spatially Referenced Regression Models

Science.gov (United States)

Moore, Richard Bridge; Johnston, Craig M.; Robinson, Keith W.; Deacon, Jeffrey R.

2004-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA) and the New England Interstate Water Pollution Control Commission (NEIWPCC), has developed a water-quality model, called SPARROW (Spatially Referenced Regressions on Watershed Attributes), to assist in regional total maximum daily load (TMDL) and nutrient-criteria activities in New England. SPARROW is a spatially detailed, statistical model that uses regression equations to relate total nitrogen and phosphorus (nutrient) stream loads to nutrient sources and watershed characteristics. The statistical relations in these equations are then used to predict nutrient loads in unmonitored streams. The New England SPARROW models are built using a hydrologic network of 42,000 stream reaches and associated watersheds. Watershed boundaries are defined for each stream reach in the network through the use of a digital elevation model and existing digitized watershed divides. Nutrient source data is from permitted wastewater discharge data from USEPA's Permit Compliance System (PCS), various land-use sources, and atmospheric deposition. Physical watershed characteristics include drainage area, land use, streamflow, time-of-travel, stream density, percent wetlands, slope of the land surface, and soil permeability. The New England SPARROW models for total nitrogen and total phosphorus have R-squared values of 0.95 and 0.94, with mean square errors of 0.16 and 0.23, respectively. Variables that were statistically significant in the total nitrogen model include permitted municipal-wastewater discharges, atmospheric deposition, agricultural area, and developed land area. Total nitrogen stream-loss rates were significant only in streams with average annual flows less than or equal to 2.83 cubic meters per second. In streams larger than this, there is nondetectable in-stream loss of annual total nitrogen in New England. Variables that were statistically significant in the total

Design of Optimized Multimedia Data Streaming Management Using OMDSM over Mobile Networks

Directory of Open Access Journals (Sweden)

Byungjoo Park

2017-01-01

Full Text Available Mobility management is an essential challenge for supporting reliable multimedia data streaming over wireless and mobile networks in the Internet of Things (IoT for location-based mobile marketing applications. The communications among mobile nodes for IoT need to have a seamless handover for delivering high quality multimedia services. The Internet Engineering Task Force (IETF mobility management schemes are the proposals for handling the routing of IPv6 packets to mobile nodes that have moved away from their home network. However, the standard mobility management scheme cannot prevent packet losses due to longer handover latency. In this article, a new enhanced data streaming route optimization scheme is introduced that uses an optimized Transmission Control Protocol (TCP realignment algorithm in order to prevent the packet disordering problem whenever the nodes in the IoT environment are communicating with each other. With the proposed scheme, data packets sequence realignment can be prevented, the packet traffic speed can be controlled, and the TCP performance can be improved. The experimental results show that managing the packet order in proposed new scheme remarkably increases the overall TCP performance over mobile networks within the IoT environment thus ensuring the high quality of service (QoS for multimedia data streaming in location-based mobile marketing applications.

Beyond the edge: Linking agricultural landscapes, stream networks, and best management practices

Science.gov (United States)

Kreiling, Rebecca M.; Thoms, Martin C.; Richardson, William B.

2018-01-01

Despite much research and investment into understanding and managing nutrients across agricultural landscapes, nutrient runoff to freshwater ecosystems is still a major concern. We argue there is currently a disconnect between the management of watershed surfaces (agricultural landscape) and river networks (riverine landscape). These landscapes are commonly managed separately, but there is limited cohesiveness between agricultural landscape-focused research and river science, despite similar end goals. Interdisciplinary research into stream networks that drain agricultural landscapes is expanding but is fraught with problems. Conceptual frameworks are useful tools to order phenomena, reveal patterns and processes, and in interdisciplinary river science, enable the joining of multiple areas of understanding into a single conceptual–empirical structure. We present a framework for the interdisciplinary study and management of agricultural and riverine landscapes. The framework includes components of an ecosystems approach to the study of catchment–stream networks, resilience thinking, and strategic adaptive management. Application of the framework is illustrated through a study of the Fox Basin in Wisconsin, USA. To fully realize the goal of nutrient reduction in the basin, we suggest that greater emphasis is needed on where best management practices (BMPs) are used within the spatial context of the combined watershed–stream network system, including BMPs within the river channel. Targeted placement of BMPs throughout the riverine landscape would increase the overall buffering capacity of the system to nutrient runoff and thus its resilience to current and future disturbances.

A Statistical Method to Predict Flow Permanence in Dryland Streams from Time Series of Stream Temperature

Directory of Open Access Journals (Sweden)

Ivan Arismendi

2017-12-01

Full Text Available Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs, to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels between April and August (2015–2016. We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%, but a portion of them showed one or more shifts among states (17%. We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.

A statistical method to predict flow permanence in dryland streams from time series of stream temperature

Science.gov (United States)

Arismendi, Ivan; Dunham, Jason B.; Heck, Michael; Schultz, Luke; Hockman-Wert, David

2017-01-01

Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.

Random linear network coding for streams with unequally sized packets

DEFF Research Database (Denmark)

Taghouti, Maroua; Roetter, Daniel Enrique Lucani; Pedersen, Morten Videbæk

2016-01-01

State of the art Random Linear Network Coding (RLNC) schemes assume that data streams generate packets with equal sizes. This is an assumption that results in the highest efficiency gains for RLNC. A typical solution for managing unequal packet sizes is to zero-pad the smallest packets. However, ...

Automated identification of stream-channel geomorphic features from high‑resolution digital elevation models in West Tennessee watersheds

Science.gov (United States)

Cartwright, Jennifer M.; Diehl, Timothy H.

2017-01-17

High-resolution digital elevation models (DEMs) derived from light detection and ranging (lidar) enable investigations of stream-channel geomorphology with much greater precision than previously possible. The U.S. Geological Survey has developed the DEM Geomorphology Toolbox, containing seven tools to automate the identification of sites of geomorphic instability that may represent sediment sources and sinks in stream-channel networks. These tools can be used to modify input DEMs on the basis of known locations of stormwater infrastructure, derive flow networks at user-specified resolutions, and identify possible sites of geomorphic instability including steep banks, abrupt changes in channel slope, or areas of rough terrain. Field verification of tool outputs identified several tool limitations but also demonstrated their overall usefulness in highlighting likely sediment sources and sinks within channel networks. In particular, spatial clusters of outputs from multiple tools can be used to prioritize field efforts to assess and restore eroding stream reaches.

Content-Adaptive Packetization and Streaming of Wavelet Video over IP Networks

Directory of Open Access Journals (Sweden)

Chien-Peng Ho

2007-03-01

Full Text Available This paper presents a framework of content-adaptive packetization scheme for streaming of 3D wavelet-based video content over lossy IP networks. The tradeoff between rate and distortion is controlled by jointly adapting scalable source coding rate and level of forward error correction (FEC protection. A content dependent packetization mechanism with data-interleaving and Reed-Solomon protection for wavelet-based video codecs is proposed to provide unequal error protection. This paper also tries to answer an important question for scalable video streaming systems: given extra bandwidth, should one increase the level of channel protection for the most important packets, or transmit more scalable source data? Experimental results show that the proposed framework achieves good balance between quality of the received video and level of error protection under bandwidth-varying lossy IP networks.

Intrinsic properties of channel network structure and the hierarchical classification approach for stream-limits delineation

Energy Technology Data Exchange (ETDEWEB)

Afana, A.; Barrio, G. del

2009-07-01

Delineation of drainage networks is an essential task in hydrological and geomorphologic analysis. Manual channel definition depends on topographic contrast and is highly subjective, leading to important errors at high resolutions. different automatic methods have proposed the use of a constant threshold of up sole contributing are to define channel initiation. Actually, these are the most commonly used for the automatic-channel network extraction from Digital Models (DEMs). However, these methods fall to detect and appropriate threshold when the basin is made up to heterogeneous sub-zones, as they only work either lumped or locally. In this study, the critical threshold area for channel delineation has been defined through the analysis of dominant geometric and topologic properties of stream network formation. (Author) 5 refs.

Multiscale Models for the Two-Stream Instability

Science.gov (United States)

Joseph, Ilon; Dimits, Andris; Banks, Jeffrey; Berger, Richard; Brunner, Stephan; Chapman, Thomas

2017-10-01

Interpenetrating streams of plasma found in many important scenarios in nature and in the laboratory can develop kinetic two-stream instabilities that exchange momentum and energy between the streams. A quasilinear model for the electrostatic two-stream instability is under development as a component of a multiscale model that couples fluid simulations to kinetic theory. Parameters of the model will be validated with comparison to full kinetic simulations using LOKI and efficient strategies for numerical solution of the quasilinear model and for coupling to the fluid model will be discussed. Extending the kinetic models into the collisional regime requires an efficient treatment of the collision operator. Useful reductions of the collision operator relative to the full multi-species Landau-Fokker-Plank operator are being explored. These are further motivated both by careful consideration of the parameter orderings relevant to two-stream scenarios and by the particular 2D+2V phase space used in the LOKI code. Prepared for US DOE by LLNL under Contract DE-AC52-07NA27344 and LDRD project 17- ERD-081.

A random spatial network model based on elementary postulates

Science.gov (United States)

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

Modelling dendritic ecological networks in space: An integrated network perspective

Science.gov (United States)

Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

Science.gov (United States)

Gomez-Velez, Jesus D.; Harvey, Judson W.

2014-09-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.

A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

Science.gov (United States)

Gomez-Velez, Jesus D.; Harvey, Judson

2014-01-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.

Modelling and predicting biogeographical patterns in river networks

Directory of Open Access Journals (Sweden)

Sabela Lois

2016-04-01

Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

Cross-Layer Techniques for Adaptive Video Streaming over Wireless Networks

Directory of Open Access Journals (Sweden)

Yufeng Shan

2005-02-01

Full Text Available Real-time streaming media over wireless networks is a challenging proposition due to the characteristics of video data and wireless channels. In this paper, we propose a set of cross-layer techniques for adaptive real-time video streaming over wireless networks. The adaptation is done with respect to both channel and data. The proposed novel packetization scheme constructs the application layer packet in such a way that it is decomposed exactly into an integer number of equal-sized radio link protocol (RLP packets. FEC codes are applied within an application packet at the RLP packet level rather than across different application packets and thus reduce delay at the receiver. A priority-based ARQ, together with a scheduling algorithm, is applied at the application layer to retransmit only the corrupted RLP packets within an application layer packet. Our approach combines the flexibility and programmability of application layer adaptations, with low delay and bandwidth efficiency of link layer techniques. Socket-level simulations are presented to verify the effectiveness of our approach.

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics.

Science.gov (United States)

Kotevska, Olivera; Kusne, A Gilad; Samarov, Daniel V; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today's cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County.

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics

Science.gov (United States)

Kotevska, Olivera; Kusne, A. Gilad; Samarov, Daniel V.; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today’s cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County. PMID:29250476

Restoring Wood-Rich Hotspots in Mountain Stream Networks

Science.gov (United States)

Wohl, E.; Scott, D.

2016-12-01

Mountain streams commonly include substantial longitudinal variability in valley and channel geometry, alternating repeatedly between steep, narrow and relatively wide, low gradient segments. Segments that are wider and lower gradient than neighboring steeper sections are hotspots with respect to: retention of large wood (LW) and finer sediment and organic matter; uptake of nutrients; and biomass and biodiversity of aquatic and riparian organisms. These segments are also more likely to be transport-limited with respect to floodplain and instream LW. Management designed to protect and restore riverine LW and the physical and ecological processes facilitated by the presence of LW is likely to be most effective if focused on relatively low-gradient stream segments. These segments can be identified using a simple, reach-scale gradient analysis based on high-resolution DEMs, with field visits to identify factors that potentially limit or facilitate LW recruitment and retention, such as forest disturbance history or land use. Drawing on field data from the western US, this presentation outlines a procedure for mapping relatively low-gradient segments in a stream network and for identifying those segments where LW reintroduction or retention is most likely to balance maximizing environmental benefits derived from the presence of LW while minimizing hazards associated with LW.

Modeling and clustering users with evolving profiles in usage streams

KAUST Repository

Zhang, Chongsheng; Masseglia, Florent; Zhang, Xiangliang

2012-01-01

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.

Modeling and clustering users with evolving profiles in usage streams

KAUST Repository

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.

Numeric Analysis for Relationship-Aware Scalable Streaming Scheme

Directory of Open Access Journals (Sweden)

Heung Ki Lee

2014-01-01

Full Text Available Frequent packet loss of media data is a critical problem that degrades the quality of streaming services over mobile networks. Packet loss invalidates frames containing lost packets and other related frames at the same time. Indirect loss caused by losing packets decreases the quality of streaming. A scalable streaming service can decrease the amount of dropped multimedia resulting from a single packet loss. Content providers typically divide one large media stream into several layers through a scalable streaming service and then provide each scalable layer to the user depending on the mobile network. Also, a scalable streaming service makes it possible to decode partial multimedia data depending on the relationship between frames and layers. Therefore, a scalable streaming service provides a way to decrease the wasted multimedia data when one packet is lost. However, the hierarchical structure between frames and layers of scalable streams determines the service quality of the scalable streaming service. Even if whole packets of layers are transmitted successfully, they cannot be decoded as a result of the absence of reference frames and layers. Therefore, the complicated relationship between frames and layers in a scalable stream increases the volume of abandoned layers. For providing a high-quality scalable streaming service, we choose a proper relationship between scalable layers as well as the amount of transmitted multimedia data depending on the network situation. We prove that a simple scalable scheme outperforms a complicated scheme in an error-prone network. We suggest an adaptive set-top box (AdaptiveSTB to lower the dependency between scalable layers in a scalable stream. Also, we provide a numerical model to obtain the indirect loss of multimedia data and apply it to various multimedia streams. Our AdaptiveSTB enhances the quality of a scalable streaming service by removing indirect loss.

Improving Watershed-Scale Hydrodynamic Models by Incorporating Synthetic 3D River Bathymetry Network

Science.gov (United States)

Dey, S.; Saksena, S.; Merwade, V.

2017-12-01

Digital Elevation Models (DEMs) have an incomplete representation of river bathymetry, which is critical for simulating river hydrodynamics in flood modeling. Generally, DEMs are augmented with field collected bathymetry data, but such data are available only at individual reaches. Creating a hydrodynamic model covering an entire stream network in the basin requires bathymetry for all streams. This study extends a conceptual bathymetry model, River Channel Morphology Model (RCMM), to estimate the bathymetry for an entire stream network for application in hydrodynamic modeling using a DEM. It is implemented at two large watersheds with different relief and land use characterizations: coastal Guadalupe River basin in Texas with flat terrain and a relatively urban White River basin in Indiana with more relief. After bathymetry incorporation, both watersheds are modeled using HEC-RAS (1D hydraulic model) and Interconnected Pond and Channel Routing (ICPR), a 2-D integrated hydrologic and hydraulic model. A comparison of the streamflow estimated by ICPR at the outlet of the basins indicates that incorporating bathymetry influences streamflow estimates. The inundation maps show that bathymetry has a higher impact on flat terrains of Guadalupe River basin when compared to the White River basin.

Foundations for Streaming Model Transformations by Complex Event Processing.

Science.gov (United States)

Dávid, István; Ráth, István; Varró, Dániel

2018-01-01

Streaming model transformations represent a novel class of transformations to manipulate models whose elements are continuously produced or modified in high volume and with rapid rate of change. Executing streaming transformations requires efficient techniques to recognize activated transformation rules over a live model and a potentially infinite stream of events. In this paper, we propose foundations of streaming model transformations by innovatively integrating incremental model query, complex event processing (CEP) and reactive (event-driven) transformation techniques. Complex event processing allows to identify relevant patterns and sequences of events over an event stream. Our approach enables event streams to include model change events which are automatically and continuously populated by incremental model queries. Furthermore, a reactive rule engine carries out transformations on identified complex event patterns. We provide an integrated domain-specific language with precise semantics for capturing complex event patterns and streaming transformations together with an execution engine, all of which is now part of the Viatra reactive transformation framework. We demonstrate the feasibility of our approach with two case studies: one in an advanced model engineering workflow; and one in the context of on-the-fly gesture recognition.

Comprehensive model-based prediction of micropollutants from diffuse sources in the Swiss river network

Science.gov (United States)

Strahm, Ivo; Munz, Nicole; Braun, Christian; Gälli, René; Leu, Christian; Stamm, Christian

2014-05-01

Water quality in the Swiss river network is affected by many micropollutants from a variety of diffuse sources. This study compares, for the first time, in a comprehensive manner the diffuse sources and the substance groups that contribute the most to water contamination in Swiss streams and highlights the major regions for water pollution. For this a simple but comprehensive model was developed to estimate emission from diffuse sources for the entire Swiss river network of 65 000 km. Based on emission factors the model calculates catchment specific losses to streams for more than 15 diffuse sources (such as crop lands, grassland, vineyards, fruit orchards, roads, railways, facades, roofs, green space in urban areas, landfills, etc.) and more than 130 different substances from 5 different substance groups (pesticides, biocides, heavy metals, human drugs, animal drugs). For more than 180 000 stream sections estimates of mean annual pollutant loads and mean annual concentration levels were modeled. This data was validated with a set of monitoring data and evaluated based on annual average environmental quality standards (AA-EQS). Model validation showed that the estimated mean annual concentration levels are within the range of measured data. Therefore simulations were considered as adequately robust for identifying the major sources of diffuse pollution. The analysis depicted that in Switzerland widespread pollution of streams can be expected. Along more than 18 000 km of the river network one or more simulated substances has a concentration exceeding the AA-EQS. In single stream sections it could be more than 50 different substances. Moreover, the simulations showed that in two-thirds of small streams (Strahler order 1 and 2) at least one AA-EQS is always exceeded. The highest number of substances exceeding the AA-EQS are in areas with large fractions of arable cropping, vineyards and fruit orchards. Urban areas are also of concern even without considering

Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

KAUST Repository

Alsibyani, Hassan M.

2018-01-01

. For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing

Streaming Weak Submodularity: Interpreting Neural Networks on the Fly

OpenAIRE

Elenberg, Ethan R.; Dimakis, Alexandros G.; Feldman, Moran; Karbasi, Amin

2017-01-01

In many machine learning applications, it is important to explain the predictions of a black-box classifier. For example, why does a deep neural network assign an image to a particular class? We cast interpretability of black-box classifiers as a combinatorial maximization problem and propose an efficient streaming algorithm to solve it subject to cardinality constraints. By extending ideas from Badanidiyuru et al. [2014], we provide a constant factor approximation guarantee for our algorithm...

Review of analytical models to stream depletion induced by pumping: Guide to model selection

Science.gov (United States)

Huang, Ching-Sheng; Yang, Tao; Yeh, Hund-Der

2018-06-01

Stream depletion due to groundwater extraction by wells may cause impact on aquatic ecosystem in streams, conflict over water rights, and contamination of water from irrigation wells near polluted streams. A variety of studies have been devoted to addressing the issue of stream depletion, but a fundamental framework for analytical modeling developed from aquifer viewpoint has not yet been found. This review shows key differences in existing models regarding the stream depletion problem and provides some guidelines for choosing a proper analytical model in solving the problem of concern. We introduce commonly used models composed of flow equations, boundary conditions, well representations and stream treatments for confined, unconfined, and leaky aquifers. They are briefly evaluated and classified according to six categories of aquifer type, flow dimension, aquifer domain, stream representation, stream channel geometry, and well type. Finally, we recommend promising analytical approaches that can solve stream depletion problem in reality with aquifer heterogeneity and irregular geometry of stream channel. Several unsolved stream depletion problems are also recommended.

Performance of the air2stream model that relates air and stream water temperatures depends on the calibration method

Science.gov (United States)

Piotrowski, Adam P.; Napiorkowski, Jaroslaw J.

2018-06-01

A number of physical or data-driven models have been proposed to evaluate stream water temperatures based on hydrological and meteorological observations. However, physical models require a large amount of information that is frequently unavailable, while data-based models ignore the physical processes. Recently the air2stream model has been proposed as an intermediate alternative that is based on physical heat budget processes, but it is so simplified that the model may be applied like data-driven ones. However, the price for simplicity is the need to calibrate eight parameters that, although have some physical meaning, cannot be measured or evaluated a priori. As a result, applicability and performance of the air2stream model for a particular stream relies on the efficiency of the calibration method. The original air2stream model uses an inefficient 20-year old approach called Particle Swarm Optimization with inertia weight. This study aims at finding an effective and robust calibration method for the air2stream model. Twelve different optimization algorithms are examined on six different streams from northern USA (states of Washington, Oregon and New York), Poland and Switzerland, located in both high mountains, hilly and lowland areas. It is found that the performance of the air2stream model depends significantly on the calibration method. Two algorithms lead to the best results for each considered stream. The air2stream model, calibrated with the chosen optimization methods, performs favorably against classical streamwater temperature models. The MATLAB code of the air2stream model and the chosen calibration procedure (CoBiDE) are available as Supplementary Material on the Journal of Hydrology web page.

Intelligent Stale-Frame Discards for Real-Time Video Streaming over Wireless Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Sheu Tsang-Ling

2009-01-01

Full Text Available Abstract This paper presents intelligent early packet discards (I-EPD for real-time video streaming over a multihop wireless ad hoc network. In a multihop wireless ad hoc network, the quality of transferring real-time video streams could be seriously degraded, since every intermediate node (IN functionally like relay device does not possess large buffer and sufficient bandwidth. Even worse, a selected relay node could leave or power off unexpectedly, which breaks the route to destination. Thus, a stale video frame is useless even if it can reach destination after network traffic becomes smooth or failed route is reconfigured. In the proposed I-EPD, an IN can intelligently determine whether a buffered video packet should be early discarded. For the purpose of validation, we implement the I-EPD on Linux-based embedded systems. Via the comparisons of performance metrics (packet/frame discards ratios, PSNR, etc., we demonstrate that video quality over a wireless ad hoc network can be substantially improved and unnecessary bandwidth wastage is greatly reduced.

PROXY-BASED PATCHING STREAM TRANSMISSION STRATEGY IN MOBILE STREAMING MEDIA SYSTEM

Institute of Scientific and Technical Information of China (English)

Liao Jianxin; Lei Zhengxiong; Ma Xutao; Zhu Xiaomin

2006-01-01

A mobile transmission strategy, PMPatching (Proxy-based Mobile Patching) transmission strategy is proposed, it applies to the proxy-based mobile streaming media system in Wideband Code Division Multiple Access (WCDMA) network. Performance of the whole system can be improved by using patching stream to transmit anterior part of the suffix that had been played back, and by batching all the demands for the suffix arrived in prefix period and patching stream transmission threshold period. Experimental results show that this strategy can efficiently reduce average network transmission cost and number of channels consumed in central streaming media server.

Horton Ratios Link Self-Similarity with Maximum Entropy of Eco-Geomorphological Properties in Stream Networks

Directory of Open Access Journals (Sweden)

Bruce T. Milne

2017-05-01

Full Text Available Stream networks are branched structures wherein water and energy move between land and atmosphere, modulated by evapotranspiration and its interaction with the gravitational dissipation of potential energy as runoff. These actions vary among climates characterized by Budyko theory, yet have not been integrated with Horton scaling, the ubiquitous pattern of eco-hydrological variation among Strahler streams that populate river basins. From Budyko theory, we reveal optimum entropy coincident with high biodiversity. Basins on either side of optimum respond in opposite ways to precipitation, which we evaluated for the classic Hubbard Brook experiment in New Hampshire and for the Whitewater River basin in Kansas. We demonstrate that Horton ratios are equivalent to Lagrange multipliers used in the extremum function leading to Shannon information entropy being maximal, subject to constraints. Properties of stream networks vary with constraints and inter-annual variation in water balance that challenge vegetation to match expected resource supply throughout the network. The entropy-Horton framework informs questions of biodiversity, resilience to perturbations in water supply, changes in potential evapotranspiration, and land use changes that move ecosystems away from optimal entropy with concomitant loss of productivity and biodiversity.

Interactive collision detection for deformable models using streaming AABBs.

Science.gov (United States)

Zhang, Xinyu; Kim, Young J

2007-01-01

We present an interactive and accurate collision detection algorithm for deformable, polygonal objects based on the streaming computational model. Our algorithm can detect all possible pairwise primitive-level intersections between two severely deforming models at highly interactive rates. In our streaming computational model, we consider a set of axis aligned bounding boxes (AABBs) that bound each of the given deformable objects as an input stream and perform massively-parallel pairwise, overlapping tests onto the incoming streams. As a result, we are able to prevent performance stalls in the streaming pipeline that can be caused by expensive indexing mechanism required by bounding volume hierarchy-based streaming algorithms. At runtime, as the underlying models deform over time, we employ a novel, streaming algorithm to update the geometric changes in the AABB streams. Moreover, in order to get only the computed result (i.e., collision results between AABBs) without reading back the entire output streams, we propose a streaming en/decoding strategy that can be performed in a hierarchical fashion. After determining overlapped AABBs, we perform a primitive-level (e.g., triangle) intersection checking on a serial computational model such as CPUs. We implemented the entire pipeline of our algorithm using off-the-shelf graphics processors (GPUs), such as nVIDIA GeForce 7800 GTX, for streaming computations, and Intel Dual Core 3.4G processors for serial computations. We benchmarked our algorithm with different models of varying complexities, ranging from 15K up to 50K triangles, under various deformation motions, and the timings were obtained as 30 approximately 100 FPS depending on the complexity of models and their relative configurations. Finally, we made comparisons with a well-known GPU-based collision detection algorithm, CULLIDE [4] and observed about three times performance improvement over the earlier approach. We also made comparisons with a SW-based AABB

From bottles to stream reaches and networks: Consequences of scale in how we interpret the function of freshwaters in the carbon cycle

Science.gov (United States)

Hotchkiss, E. R.

2017-12-01

Freshwater biological processes can alter the quantity and quality of organic carbon (OC) inputs from land before they are transported downstream, but the relative role of hydrologic transport and in-stream processing is still not well quantified at the scale of fluvial networks. Despite much research on the role of biology and hydrology in governing the form and fate of C in inland waters, conclusions about the function of freshwater ecosystems in modifying OC still largely depend on where we draw our ecosystem boundaries, i.e., the spatial scale of measurements used to assess OC transformations. Here I review freshwater OC uptake rates derived from bioassay incubations, synoptic modeling, reach-scale experiments, and ecosystem OC spiraling estimates. Median OC uptake velocities from standard bioassay incubations (0.02 m/d) and synoptic modeling (0.04 m/d) are 1-2 orders of magnitude lower than reach-scale experimental DOC additions and ecosystem OC spiraling estimates (2.2 and 0.27 m/d, respectively) in streams and rivers. Together, ecosystem metabolism and OC fluxes can be used to estimate the distance OC travels before being consumed and respired as CO2 through biological processes (i.e., OC spiraling), allowing for a more mechanistic understanding of the role of ecosystem processes and hydrologic fluxes in modifying downstream OC transport. Beyond the reach scale, data from stream network and stream-lake-river modeling simulations show how we may use linked sampling sites within networks to better understand the integrated sources and fate of OC in freshwaters. We currently underestimate the role of upstream processes in contributing to downstream fluxes: moving from single-ecosystem comparisons to linked-ecosystem simulations increases the contribution of in situ OC processing to CO2 emissions from 30% to >40%. Insights from literature reviews, ecosystem process measurements, and model simulations provide a framework for future considerations of integrated C

MODEL OF FUNCTIONING OF TELECOMMUNICATION EQUIPMENT FOR SOFTWARE-CONFIGURATED NETWORKS

Directory of Open Access Journals (Sweden)

Konstantin E. Samouylov

2018-03-01

Full Text Available A mathematical model of the functioning of the switch of a software defined networks is constructed in the form of a queuing network consisting of two queuing systems: the first simulates an input data buffer and a device for reading information from the header of the packet; the second is a table for addressing the switch of a software defined networks. The receipt of data in software defined networks has a probabilistic character in their deterministic processing in communication channels and switching nodes. Therefore, this mathematical model of the functioning of the switch of a software defined networks was built on the basis of queuing systems and networks. The stream of requests flowing into the network was divided into two Poisson streams of various types of applications, the first of which corresponded to the packets that came to the control port of the switch (from the controller, and the second flow to the remaining packets arriving on the switch. The flow corresponding to the packets arriving at the switch from the controller has a relative priority over the flow from the remaining arriving packets As a result, formulas were obtained for calculating the performance indicators of this telecommunications equipment such as average waiting queues for priority and non-priority applications, the probability of loss of applications for each phase of the switch. Based on the received quality of service indicators for this telecommunications equipment, it is possible to assess the stability of switches in software defined networks for various information impacts.

Inference of Stream Network Fragmentation Patterns from Ground Water - Surface Water Interactions on the High Plains Aquifer

Science.gov (United States)

Chandler, D. G.; Yang, X.; Steward, D. R.; Gido, K.

2007-12-01

Stream networks in the Great Plains integrate fluxes from precipitation as surface runoff in discrete events and groundwater as base flow. Changes in land cover and agronomic practices and development of ground water resources to support irrigated agriculture have resulted in profound changes in the occurrence and magnitude of stream flows, especially near the Ogallala aquifer, where precipitation is low. These changes have demonstrably altered the aquatic habitat of western Kansas, with documented changes in fish populations, riparian communities and groundwater quality due to stream transmission losses. Forecasting future changes in aquatic and riparian ecology and groundwater quality requires a large scale spatially explicit model of groundwater- surface water interaction. In this study, we combine historical data on land use, stream flow, production well development and groundwater level observations with groundwater elevation modeling to support a geospatial framework for assessing changes in refugia for aquatic species in four rivers in western Kansas between 1965 and 2005. Decreased frequency and duration of streamflow occurred in all rivers, but the extent of change depended on the geomorphology of the river basin and the extent of groundwater development. In the absence of streamflow, refugia for aquatic species were defined as the stream reaches below the phreatic surface of the regional aquifer. Changes in extent, location and degree of fragmentation of gaining reaches was found to be a strong predictor of surface water occurrence during drought and a robust hydrological template for the analysis of changes in recharge to alluvial and regional aquifers and riparian and aquatic habitat.

Modelling dendritic ecological networks in space: anintegrated network perspective

Science.gov (United States)

Peterson, Erin E.; Ver Hoef, Jay M.; Isaak, Dan J.; Falke, Jeffrey A.; Fortin, Marie-Josée; Jordon, Chris E.; McNyset, Kristina; Monestiez, Pascal; Ruesch, Aaron S.; Sengupta, Aritra; Som, Nicholas; Steel, E. Ashley; Theobald, David M.; Torgersen, Christian E.; Wenger, Seth J.

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within

Modeling of immision from power plants using stream-diffusion model

International Nuclear Information System (INIS)

Kanevce, Lj.; Kanevce, G.; Markoski, A.

1996-01-01

Analyses of simple empirical and integral immision models, comparing with complex three dimensional differential models is given. Complex differential models needs huge computer power, so they can't be useful for practical engineering calculations. In this paper immision modeling, using stream-diffusion approach is presented. Process of dispersion is divided into two parts. First part is called stream part, it's near the source of the pollutants, and it's presented with defected turbulent jet in wind field. This part finished when the velocity of stream (jet) becomes equal with wind speed. Boundary conditions in the end of the first part, are initial for the second, called diffusion part, which is modeling with tri dimensional diffusion equation. Gradient of temperature, wind speed profile and coefficient of diffusion in this model must not be constants, they can change with the height. Presented model is much simpler than the complete meteorological differential models which calculates whole fields of meteorological parameters. Also, it is more complex and gives more valuable results for dispersion of pollutants from widely used integral and empirical models

Ultrasound-driven Viscous Streaming, Modelled via Momentum Injection

Directory of Open Access Journals (Sweden)

James PACKER

2008-12-01

Full Text Available Microfluidic devices can use steady streaming caused by the ultrasonic oscillation of one or many gas bubbles in a liquid to drive small scale flow. Such streaming flows are difficult to evaluate, as analytic solutions are not available for any but the simplest cases, and direct computational fluid dynamics models are unsatisfactory due to the large difference in flow velocity between the steady streaming and the leading order oscillatory motion. We develop a numerical technique which uses a two-stage multiscale computational fluid dynamics approach to find the streaming flow as a steady problem, and validate this model against experimental results.

Reverse stream flow routing by using Muskingum models

Indian Academy of Sciences (India)

Reverse stream flow routing is a procedure that determines the upstream hydrograph given the downstream hydrograph. This paper presents the development of methodology for Muskingum models parameter estimation for reverse stream flow routing. The standard application of the Muskingum models involves calibration ...

Routing Optimization of AVB Streams in TSN Networks

DEFF Research Database (Denmark)

Laursen, Sune Mølgaard; Pop, Paul; Steiner, Wilfried

2016-01-01

In this paper we are interested in safety-critical real-time applications implemented on distributed architectures using the Time-Sensitive Networking (TSN) standard. The ongoing standardization of TSN is an IEEE effort to bring deterministic real-time capabilities into the IEEE 802.1 Ethernet...... standard supporting safety-critical systems and guaranteed Quality-of-Service. TSN will support Time-Triggered (TT) communication based on schedule tables, Audio-Video-Bridging (AVB) streams with bounded end-to-end latency as well as Best-Effort messages. We consider that we know the topology...... Procedure (GRASP)-based heuristic for this routing optimization problem. The proposed approaches has been evaluated using several test cases....

Duplication of Key Frames of Video Streams in Wireless Networks

OpenAIRE

Sagatov, Evgeny S.; Sukhov, Andrei M.

2011-01-01

In this paper technological solutions for improving the quality of video transfer along wireless networks are investigated. Tools have been developed to allow packets to be duplicated with key frames data. In the paper we tested video streams with duplication of all frames, with duplication of key frames, and without duplication. The experiments showed that the best results are obtained by duplication of packages which contain key frames. The paper also provides an overview of the coefficient...

Continuous Online Sequence Learning with an Unsupervised Neural Network Model.

Science.gov (United States)

Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff

2016-09-14

The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.

Learning a Continuous-Time Streaming Video QoE Model.

Science.gov (United States)

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C

2018-05-01

Over-the-top adaptive video streaming services are frequently impacted by fluctuating network conditions that can lead to rebuffering events (stalling events) and sudden bitrate changes. These events visually impact video consumers' quality of experience (QoE) and can lead to consumer churn. The development of models that can accurately predict viewers' instantaneous subjective QoE under such volatile network conditions could potentially enable the more efficient design of quality-control protocols for media-driven services, such as YouTube, Amazon, Netflix, and so on. However, most existing models only predict a single overall QoE score on a given video and are based on simple global video features, without accounting for relevant aspects of human perception and behavior. We have created a QoE evaluator, called the time-varying QoE Indexer, that accounts for interactions between stalling events, analyzes the spatial and temporal content of a video, predicts the perceptual video quality, models the state of the client-side data buffer, and consequently predicts continuous-time quality scores that agree quite well with human opinion scores. The new QoE predictor also embeds the impact of relevant human cognitive factors, such as memory and recency, and their complex interactions with the video content being viewed. We evaluated the proposed model on three different video databases and attained standout QoE prediction performance.

Two-stream Convolutional Neural Network for Methane Emissions Quantification

Science.gov (United States)

Wang, J.; Ravikumar, A. P.; McGuire, M.; Bell, C.; Tchapmi, L. P.; Brandt, A. R.

2017-12-01

Methane, a key component of natural gas, has a 25x higher global warming potential than carbon dioxide on a 100-year basis. Accurately monitoring and mitigating methane emissions require cost-effective detection and quantification technologies. Optical gas imaging, one of the most commonly used leak detection technology, adopted by Environmental Protection Agency, cannot estimate leak-sizes. In this work, we harness advances in computer science to allow for rapid and automatic leak quantification. Particularly, we utilize two-stream deep Convolutional Networks (ConvNets) to estimate leak-size by capturing complementary spatial information from still plume frames, and temporal information from plume motion between frames. We build large leak datasets for training and evaluating purposes by collecting about 20 videos (i.e. 397,400 frames) of leaks. The videos were recorded at six distances from the source, covering 10 -60 ft. Leak sources included natural gas well-heads, separators, and tanks. All frames were labeled with a true leak size, which has eight levels ranging from 0 to 140 MCFH. Preliminary analysis shows that two-stream ConvNets provides significant accuracy advantage over single steam ConvNets. Spatial stream ConvNet can achieve an accuracy of 65.2%, by extracting important features, including texture, plume area, and pattern. Temporal stream, fed by the results of optical flow analysis, results in an accuracy of 58.3%. The integration of the two-stream ConvNets gives a combined accuracy of 77.6%. For future work, we will split the training and testing datasets in distinct ways in order to test the generalization of the algorithm for different leak sources. Several analytic metrics, including confusion matrix and visualization of key features, will be used to understand accuracy rates and occurrences of false positives. The quantification algorithm can help to find and fix super-emitters, and improve the cost-effectiveness of leak detection and repair

Benthic invertebrate fauna, small streams

Science.gov (United States)

J. Bruce Wallace; S.L. Eggert

2009-01-01

Small streams (first- through third-order streams) make up >98% of the total number of stream segments and >86% of stream length in many drainage networks. Small streams occur over a wide array of climates, geology, and biomes, which influence temperature, hydrologic regimes, water chemistry, light, substrate, stream permanence, a basin's terrestrial plant...

Robust estimates of environmental effects on population vital rates: an integrated capture–recapture model of seasonal brook trout growth, survival and movement in a stream network

Science.gov (United States)

Letcher, Benjamin H.; Schueller, Paul; Bassar, Ronald D.; Nislow, Keith H.; Coombs, Jason A.; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B.; Whiteley, Andrew R.; O'Donnell, Matthew J.; Dubreuil, Todd L.

2015-01-01

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses.We developed an integrated capture–recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival.We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature.Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative

A national optimisation model for energy wood streams; Energiapuuvirtojen valtakunnallinen optimointimalli

Energy Technology Data Exchange (ETDEWEB)

Iikkanen, P.; Keskinen, S.; Korpilahti, A.; Raesaenen, T.; Sirkiae, A.

2011-07-01

In 2010 a total of 12,5 terawatt hours of forest energy was used in Finland's heat and power plants. According to studies by Metsaeteho and Poeyry, use of energy wood will nearly double to 21.6 terawatt hours by 2020. There are also plans to use energy wood as a raw material for biofuel plants. The techno-ecological supply potential of energy wood in 2020 is estimated at 42.9 terawatt hours. Energy wood has been transported almost entirely by road. The situation is changing, however, because growing demand for energy wood will expand raw wood procurement areas and lengthen transport distances. A cost-effective transport system therefore also requires the use of rail and waterway transports. In Finland, however, there is almost a complete absence of the terminals required for the use of rail and waterway transports; where energy wood is chipped, temporarily stored and loaded onto railway wagons and vessels for further transport. A national optimisation model for energy wood has been developed to serve transport system planning in particular. The linear optimisation model optimises, on a national level, goods streams between supply points and usage points based on forest energy procurement costs. The model simultaneously covers deliveries of forest chips, stumps and small-sized thinning wood. The procurement costs used in the optimisation include the costs of the energy wood's roadside price, chipping, transport and terminal handling. The transport system described in the optimisation model consists of wood supply points (2007 municipality precision), wood usage points, railway terminals and the connections between them along the main road and rail network. Elements required for the examination of waterway transports can also be easily added to the model. The optimisation model can be used to examine, for example, the effects of changes of energy wood demand and supply as well as transport costs on energy wood goods streams, the relative use of different

Research on quality metrics of wireless adaptive video streaming

Science.gov (United States)

Li, Xuefei

2018-04-01

With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

Analytic Strategies of Streaming Data for eHealth.

Science.gov (United States)

Yoon, Sunmoo

2016-01-01

New analytic strategies for streaming big data from wearable devices and social media are emerging in ehealth. We face challenges to find meaningful patterns from big data because researchers face difficulties to process big volume of streaming data using traditional processing applications.1 This introductory 180 minutes tutorial offers hand-on instruction on analytics2 (e.g., topic modeling, social network analysis) of streaming data. This tutorial aims to provide practical strategies of information on reducing dimensionality using examples of big data. This tutorial will highlight strategies of incorporating domain experts and a comprehensive approach to streaming social media data.

The national stream quality accounting network: A flux-basedapproach to monitoring the water quality of large rivers

Science.gov (United States)

Hooper, R.P.; Aulenbach, Brent T.; Kelly, V.J.

2001-01-01

Estimating the annual mass flux at a network of fixed stations is one approach to characterizing water quality of large rivers. The interpretive context provided by annual flux includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean. Since 1995, the US Geological Survey's National Stream Quality Accounting Network (NASQAN) has employed this approach at a network of 39 stations in four of the largest river basins of the USA: The Mississippi, the Columbia, the Colorado and the Rio Grande. In this paper, the design of NASQAN is described and its effectiveness at characterizing the water quality of these rivers is evaluated using data from the first 3 years of operation. A broad range of constituents was measured by NASQAN, including trace organic and inorganic chemicals, major ions, sediment and nutrients. Where possible, a regression model relating concentration to discharge and season was used to interpolate between chemical observations for flux estimation. For water-quality network design, the most important finding from NASQAN was the importance of having a specific objective (that is, estimating annual mass flux) and, from that, an explicitly stated data analysis strategy, namely the use of regression models to interpolate between observations. The use of such models aided in the design of sampling strategy and provided a context for data review. The regression models essentially form null hypotheses for concentration variation that can be evaluated by the observed data. The feedback between network operation and data collection established by the hypothesis tests places the water-quality network on a firm scientific footing.

Modelling animal waste pathogen transport from agricultural land to streams

International Nuclear Information System (INIS)

Pandey, Pramod K; Soupir, Michelle L; Ikenberry, Charles

2014-01-01

The transport of animal waste pathogens from crop land to streams can potentially elevate pathogen levels in stream water. Applying animal manure into crop land as fertilizers is a common practice in developing as well as in developed countries. Manure application into the crop land, however, can cause potential human health. To control pathogen levels in ambient water bodies such as streams, improving our understanding of pathogen transport at farm scale as well as at watershed scale is required. To understand the impacts of crop land receiving animal waste as fertilizers on stream's pathogen levels, here we investigate pathogen indicator transport at watershed scale. We exploited watershed scale hydrological model to estimate the transport of pathogens from the crop land to streams. Pathogen indicator levels (i.e., E. coli levels) in the stream water were predicted. With certain assumptions, model results are reasonable. This study can be used as guidelines for developing the models for calculating the impacts of crop land's animal manure on stream water

Mining Frequent Item Sets in Asynchronous Transactional Data Streams over Time Sensitive Sliding Windows Model

International Nuclear Information System (INIS)

Javaid, Q.; Memon, F.; Talpur, S.; Arif, M.; Awan, M.D.

2016-01-01

EPs (Extracting Frequent Patterns) from the continuous transactional data streams is a challenging and critical task in some of the applications, such as web mining, data analysis and retail market, prediction and network monitoring, or analysis of stock market exchange data. Many algorithms have been developed previously for mining FPs (Frequent Patterns) from a data stream. Such algorithms are currently highly required to develop new solutions and approaches to the precise handling of data streams. New techniques, solutions, or approaches are developed to address unbounded, ordered, and continuous sequences of data and for the generation of data at a rapid speed from data streams. Hence, extracting FPs using fresh or recent data involves the high-level analysis of data streams. We have suggested an efficient technique for the window sliding model; this technique extracts new and fresh FPs from high-speed data streams. In this study, a CPILT (Compacted Tree Compact Pattern Tree) is developed to capture the latest contents in the stream and to efficiently remove outdated contents from the data stream. The main concept introduced in this work on CPILT is the dynamic restructuring of a tree, which is helpful in producing a compacted tree and the frequency descending structure of a tree on runtime. With the help of the mining technique of FP growth, a complete list of new and fresh FPs is obtained from a CPILT using an existing window. The memory usage and time complexity of the latest FPs in high-speed data streams can efficiently be determined through proper experimentation and analysis. (author)

Three-dimensional model of corotating streams in the solar wind 3. Magnetohydrodynamic streams

International Nuclear Information System (INIS)

Pizzo, V.J.

1982-01-01

The focus of this paper is two-fold: (1) to examine how the presence of the spiral magnetic field affects the evolution of interplanetary corotating solar wind streams, and (2) to ascertain the nature of secondary large-scale phenomena likely to be associated with streams having a pronounced three-dimensional (3-D) structure. The dynamics are presumed to be governed by the nonlinear polytropic, single-fluid, 3-D MHD equations. Solutions are obtained with an explicit, Eulerian, finite differences technique that makes use of a simple form of artificial diffusion for handling shocks. For smooth axisymmetric flows, the picture of magnetically induced meridional motions previously established by linear models requires only minor correction. In the case of broad 3-D streams input near the sun, inclusion of the magnetic field is found to retard the kinematic steepening at the stream front substantially but to produce little deviation from planar flow. For the more realistic case of initially sharply bounded streams, however, it becomes essential to account for magnetic effects in the formulation. Whether a full 3-D treatment is required depends upon the latitudinal geometry of the stream

A model for the origin of solar wind stream interfaces

International Nuclear Information System (INIS)

Hundhausen, A.J.; Burlaga, L.F.

1975-01-01

The basic variations in solar wind properties that have been observed at 'stream interfaces' near 1 AU are explained by a gas dynamic model in which a radially propagating stream, produced by a temperature variation in the solar envelope, steepens nonlinearly while moving through interplanetary space. The region thus identified with the stream interface separates the ambient solar wind from the fresh hot material originally in the stream. However, the interface regions given by the present model are thicker than most stream interfaces observed in the solar wind, a fact suggesting that some additional physical process may be important in determining that thickness. Variations in the density, speed, or Alfven pressure alone appear not to produce streams with such an interface

Animal models for auditory streaming

Science.gov (United States)

Itatani, Naoya

2017-01-01

Sounds in the natural environment need to be assigned to acoustic sources to evaluate complex auditory scenes. Separating sources will affect the analysis of auditory features of sounds. As the benefits of assigning sounds to specific sources accrue to all species communicating acoustically, the ability for auditory scene analysis is widespread among different animals. Animal studies allow for a deeper insight into the neuronal mechanisms underlying auditory scene analysis. Here, we will review the paradigms applied in the study of auditory scene analysis and streaming of sequential sounds in animal models. We will compare the psychophysical results from the animal studies to the evidence obtained in human psychophysics of auditory streaming, i.e. in a task commonly used for measuring the capability for auditory scene analysis. Furthermore, the neuronal correlates of auditory streaming will be reviewed in different animal models and the observations of the neurons’ response measures will be related to perception. The across-species comparison will reveal whether similar demands in the analysis of acoustic scenes have resulted in similar perceptual and neuronal processing mechanisms in the wide range of species being capable of auditory scene analysis. This article is part of the themed issue ‘Auditory and visual scene analysis’. PMID:28044022

Efficient Delivery of Scalable Video Using a Streaming Class Model

Directory of Open Access Journals (Sweden)

Jason J. Quinlan

2018-03-01

Full Text Available When we couple the rise in video streaming with the growing number of portable devices (smart phones, tablets, laptops, we see an ever-increasing demand for high-definition video online while on the move. Wireless networks are inherently characterised by restricted shared bandwidth and relatively high error loss rates, thus presenting a challenge for the efficient delivery of high quality video. Additionally, mobile devices can support/demand a range of video resolutions and qualities. This demand for mobile streaming highlights the need for adaptive video streaming schemes that can adjust to available bandwidth and heterogeneity, and can provide a graceful changes in video quality, all while respecting viewing satisfaction. In this context, the use of well-known scalable/layered media streaming techniques, commonly known as scalable video coding (SVC, is an attractive solution. SVC encodes a number of video quality levels within a single media stream. This has been shown to be an especially effective and efficient solution, but it fares badly in the presence of datagram losses. While multiple description coding (MDC can reduce the effects of packet loss on scalable video delivery, the increased delivery cost is counterproductive for constrained networks. This situation is accentuated in cases where only the lower quality level is required. In this paper, we assess these issues and propose a new approach called Streaming Classes (SC through which we can define a key set of quality levels, each of which can be delivered in a self-contained manner. This facilitates efficient delivery, yielding reduced transmission byte-cost for devices requiring lower quality, relative to MDC and Adaptive Layer Distribution (ALD (42% and 76% respective reduction for layer 2, while also maintaining high levels of consistent quality. We also illustrate how selective packetisation technique can further reduce the effects of packet loss on viewable quality by

Joint Optimized CPU and Networking Control Scheme for Improved Energy Efficiency in Video Streaming on Mobile Devices

Directory of Open Access Journals (Sweden)

Sung-Woong Jo

2017-01-01

Full Text Available Video streaming service is one of the most popular applications for mobile users. However, mobile video streaming services consume a lot of energy, resulting in a reduced battery life. This is a critical problem that results in a degraded user’s quality of experience (QoE. Therefore, in this paper, a joint optimization scheme that controls both the central processing unit (CPU and wireless networking of the video streaming process for improved energy efficiency on mobile devices is proposed. For this purpose, the energy consumption of the network interface and CPU is analyzed, and based on the energy consumption profile a joint optimization problem is formulated to maximize the energy efficiency of the mobile device. The proposed algorithm adaptively adjusts the number of chunks to be downloaded and decoded in each packet. Simulation results show that the proposed algorithm can effectively improve the energy efficiency when compared with the existing algorithms.

Dynamic modeling of nitrogen losses in river networks unravels the coupled effects of hydrological and biogeochemical processes

Science.gov (United States)

Alexander, Richard B.; Böhlke, John Karl; Boyer, Elizabeth W.; David, Mark B.; Harvey, Judson W.; Mulholland, Patrick J.; Seitzinger, Sybil P.; Tobias, Craig R.; Tonitto, Christina; Wollheim, Wilfred M.

2009-01-01

The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly

Low latency adaptive streaming of HD H.264 video over 802.11 wireless networks with cross-layer feedback

Science.gov (United States)

Patti, Andrew; Tan, Wai-tian; Shen, Bo

2007-09-01

Streaming video in consumer homes over wireless IEEE 802.11 networks is becoming commonplace. Wireless 802.11 networks pose unique difficulties for streaming high definition (HD), low latency video due to their error-prone physical layer and media access procedures which were not designed for real-time traffic. HD video streaming, even with sophisticated H.264 encoding, is particularly challenging due to the large number of packet fragments per slice. Cross-layer design strategies have been proposed to address the issues of video streaming over 802.11. These designs increase streaming robustness by imposing some degree of monitoring and control over 802.11 parameters from application level, or by making the 802.11 layer media-aware. Important contributions are made, but none of the existing approaches directly take the 802.11 queuing into account. In this paper we take a different approach and propose a cross-layer design allowing direct, expedient control over the wireless packet queue, while obtaining timely feedback on transmission status for each packet in a media flow. This method can be fully implemented on a media sender with no explicit support or changes required to the media client. We assume that due to congestion or deteriorating signal-to-noise levels, the available throughput may drop substantially for extended periods of time, and thus propose video source adaptation methods that allow matching the bit-rate to available throughput. A particular H.264 slice encoding is presented to enable seamless stream switching between streams at multiple bit-rates, and we explore using new computationally efficient transcoding methods when only a high bit-rate stream is available.

Cross-layer ultrasound video streaming over mobile WiMAX and HSUPA networks.

Science.gov (United States)

Alinejad, Ali; Philip, Nada Y; Istepanian, Robert S H

2012-01-01

It is well known that the evolution of 4G-based mobile multimedia network systems will contribute significantly to future mobile healthcare (m-health) applications that require high bandwidth and fast data rates. Central to the success of such emerging applications is the compatibility of broadband networks, such as mobile Worldwide Interoperability For Microwave Access (WiMAX) and High-Speed Uplink Packet Access (HSUPA), and especially their rate adaption issues combined with the acceptable real-time medical quality of service requirements. In this paper, we address the relevant challenges of cross-layer design requirements for real-time rate adaptation of ultrasound video streaming in mobile WiMAX and HSUPA networks. A comparative performance analysis of such approach is validated in two experimental m-health test bed systems for both mobile WiMAX and HSUPA networks. The experimental results have shown an improved performance of mobile WiMAX compared to the HSUPA using the same cross-layer optimization approach.

Geometry of river networks. III. Characterization of component connectivity

International Nuclear Information System (INIS)

Dodds, Peter Sheridan; Rothman, Daniel H.

2001-01-01

Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we explore the presence of randomness in river network structure and the details of its consequences. We first show that an averaged view of network architecture is provided by a proposed self-similarity statement about the scaling of drainage density, a local measure of stream concentration. This scaling of drainage density is shown to imply Tokunaga's law, a description of the scaling of side branch abundance along a given stream, as well as a scaling law for stream lengths. We then consider fluctuations in drainage density and consequently the numbers of side branches. Data are analyzed for the Mississippi River basin and a model of random directed networks. Numbers of side streams are found to follow exponential distributions, as are intertributary distances along streams. Finally, we derive a joint variation of side stream abundance with stream length, affording a full description of fluctuations in network structure. Fluctuations in side stream numbers are shown to be a direct result of fluctuations in stream lengths. This is the last paper in a series of three on the geometry of river networks

Network Degradation Effects on Different Codec Types and Characteristics of Video Streaming

Directory of Open Access Journals (Sweden)

Jaroslav Frnda

2014-01-01

Full Text Available Nowadays, there is a quickly growing demand for the transmission of voice, video and data over an IP based network. Multimedia, whether we are talking about broadcast, audio and video transmission and others, from a global perspective is growing exponentially with time. With incoming requests from users, new technologies for data transfer are continually developing. Data must be delivered reliably and with the fewest losses at such high speed. Video quality as part of multimedia technology has a very important role nowadays. It is influenced by several factors, where each of them can have many forms and processing. Network performance is the major degradation effect that influences the quality of resulting image. Poor network performance (lack of link capacity, high network load… causes data packet losses or different delivery time for each packet. This work focuses exactly on these network phenomena. It examines the impact of different delays and packet losses on the quality parameters of triple play services, to evaluate the results using objective methods. The aim of this work is to bring a detailed view on the performance of video streaming over IP-based networks.

Learning From Short Text Streams With Topic Drifts.

Science.gov (United States)

Li, Peipei; He, Lu; Wang, Haiyan; Hu, Xuegang; Zhang, Yuhong; Li, Lei; Wu, Xindong

2017-09-18

Short text streams such as search snippets and micro blogs have been popular on the Web with the emergence of social media. Unlike traditional normal text streams, these data present the characteristics of short length, weak signal, high volume, high velocity, topic drift, etc. Short text stream classification is hence a very challenging and significant task. However, this challenge has received little attention from the research community. Therefore, a new feature extension approach is proposed for short text stream classification with the help of a large-scale semantic network obtained from a Web corpus. It is built on an incremental ensemble classification model for efficiency. First, more semantic contexts based on the senses of terms in short texts are introduced to make up of the data sparsity using the open semantic network, in which all terms are disambiguated by their semantics to reduce the noise impact. Second, a concept cluster-based topic drifting detection method is proposed to effectively track hidden topic drifts. Finally, extensive studies demonstrate that as compared to several well-known concept drifting detection methods in data stream, our approach can detect topic drifts effectively, and it enables handling short text streams effectively while maintaining the efficiency as compared to several state-of-the-art short text classification approaches.

Keystone Business Models for Network Security Processors

Directory of Open Access Journals (Sweden)

Arthur Low

2013-07-01

Full Text Available Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor” models nor the silicon intellectual-property licensing (“IP-licensing” models allow small technology companies to successfully compete. This article describes an alternative approach that produces an ongoing stream of novel network security processors for niche markets through continuous innovation by both large and small companies. This approach, referred to here as the "business ecosystem model for network security processors", includes a flexible and reconfigurable technology platform, a “keystone” business model for the company that maintains the platform architecture, and an extended ecosystem of companies that both contribute and share in the value created by innovation. New opportunities for business model innovation by participating companies are made possible by the ecosystem model. This ecosystem model builds on: i the lessons learned from the experience of the first author as a senior integrated circuit architect for providers of public-key cryptography solutions and as the owner of a semiconductor startup, and ii the latest scholarly research on technology entrepreneurship, business models, platforms, and business ecosystems. This article will be of interest to all technology entrepreneurs, but it will be of particular interest to owners of small companies that provide security solutions and to specialized security professionals seeking to launch their own companies.

Longitudinal structure in temperate stream fish communities: evaluating conceptual models with temporal data

Science.gov (United States)

Roberts, James H.; Hitt, Nathaniel P.

2010-01-01

Five conceptual models of longitudinal fish community organization in streams were examined: (1) niche diversity model (NDM), (2) stream continuum model (SCM), (3) immigrant accessibility model (IAM), (4) environmental stability model (ESM), and (5) adventitious stream model (ASM). We used differences among models in their predictions about temporal species turnover, along with five spatiotemporal fish community data sets, to evaluate model applicability. Models were similar in predicting a positive species richness–stream size relationship and longitudinal species nestedness, but differed in predicting either similar temporal species turnover throughout the stream continuum (NDM, SCM), higher turnover upstream (IAM, ESM), or higher turnover downstream (ASM). We calculated measures of spatial and temporal variation from spatiotemporal fish data in five wadeable streams in central and eastern North America spanning 34–68 years (French Creek [New York], Piasa Creek [Illinois], Spruce Run [Virginia], Little Stony Creek [Virginia], and Sinking Creek [Virginia]). All streams exhibited substantial species turnover (i.e., at least 27% turnover in stream-scale species pools), in contrast to the predictions of the SCM. Furthermore, community change was greater in downstream than upstream reaches in four of five streams. This result is most consistent with the ASM and suggests that downstream communities are strongly influenced by migrants to and from species pools outside the focal stream. In Sinking Creek, which is isolated from external species pools, temporal species turnover (via increased richness) was higher upstream than downstream, which is a pattern most consistent with the IAM or ESM. These results corroborate the hypothesis that temperate stream habitats and fish communities are temporally dynamic and that fish migration and environmental disturbances play fundamental roles in stream fish community organization.

Variable selection for modelling effects of eutrophication on stream and river ecosystems

NARCIS (Netherlands)

Nijboer, R.C.; Verdonschot, P.F.M.

2004-01-01

Models are needed for forecasting the effects of eutrophication on stream and river ecosystems. Most of the current models do not include differences in local stream characteristics and effects on the biota. To define the most important variables that should be used in a stream eutrophication model,

Modelling of stormwater infiltration for stream restoration. Beder (Aarhus) case study

DEFF Research Database (Denmark)

Locatelli, Luca; Bockhorn, Britta; Klint, K. E.

to assess the impact of stormwater runoff infiltration on (1) the water balance; (2) stream flow of the local stream Hovedgrøften; and (3) the risk of polluting the primary aquifer. The hydrogeological model was developed in a deterministic groundwater model (MIKE SHE) which was coupled dynamically...... carried out by developing a hydrogeological model of the Beder area in Aarhus, Denmark. The model area is characterized by the presence of a secondary unconfined aquifer that partly contributes baseflow to the local streams and partly to recharge to the underlying primary aquifer. The model was applied...... to a hydrodynamic 1-D river model (MIKE 11). Geological data based on spear mapping, geophysical data and lithology from local boreholes were used to set up the geological model. Groundwater observation and stream flow measurements were used for model calibration and validation.Different scenarios were analyzed...

Beaver dams maintain fish biodiversity by increasing habitat heterogeneity throughout a low-gradient stream network

Science.gov (United States)

Smith, Joseph M.; Mather, Martha E.

2013-01-01

Understanding the relationship between heterogeneity and biodiversity is an active focus of ecological research. Although habitat heterogeneity is conceptually linked to biodiversity, the amount and configuration of heterogeneity that maintains biodiversity within ecosystems is not well understood, especially for an entire stream network.

Modelling climate change impacts on stream habitat conditions

DEFF Research Database (Denmark)

Boegh, Eva; Conallin, John; Karthikeyan, Matheswaran

Impact from groundwater abstraction on freshwater resources and ecosystems is an issue of sincere concern in Denmark and many other countries worldwide. In addition, climate change projections add complexity to the existing conflict between water demands to satisfy human needs and water demands...... required to conserve streams as biologically diverse and healthy ecosystems. Solutions to this intensifying conflict require a holistic approach whereby stream biota is related to their physical environment at catchment scale, as also demanded by the EU Water Framework Directive. In the present study......, climate impacts on stream ecological conditions were quantified by combining a heat and mass stream flow with a habitat suitability modelling approach. Habitat suitability indices were developed for stream velocity, water depth, water temperature and substrate. Generally, water depth was found...

Modeling transient streaming potentials in falling-head permeameter tests.

Science.gov (United States)

Malama, Bwalya; Revil, André

2014-01-01

We present transient streaming potential data collected during falling-head permeameter tests performed on samples of two sands with different physical and chemical properties. The objective of the work is to estimate hydraulic conductivity (K) and the electrokinetic coupling coefficient (Cl ) of the sand samples. A semi-empirical model based on the falling-head permeameter flow model and electrokinetic coupling is used to analyze the streaming potential data and to estimate K and Cl . The values of K estimated from head data are used to validate the streaming potential method. Estimates of K from streaming potential data closely match those obtained from the associated head data, with less than 10% deviation. The electrokinetic coupling coefficient was estimated from streaming potential vs. (1) time and (2) head data for both sands. The results indicate that, within limits of experimental error, the values of Cl estimated by the two methods are essentially the same. The results of this work demonstrate that a temporal record of the streaming potential response in falling-head permeameter tests can be used to estimate both K and Cl . They further indicate the potential for using transient streaming potential data as a proxy for hydraulic head in hydrogeology applications. © 2013, National Ground Water Association.

STRIP: stream learning of influence probabilities

DEFF Research Database (Denmark)

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...

Urban Stream Burial Increases Watershed-Scale Nitrate Export.

Directory of Open Access Journals (Sweden)

Jake J Beaulieu

Full Text Available Nitrogen (N uptake in streams is an important ecosystem service that reduces nutrient loading to downstream ecosystems. Here we synthesize studies that investigated the effects of urban stream burial on N-uptake in two metropolitan areas and use simulation modeling to scale our measurements to the broader watershed scale. We report that nitrate travels on average 18 times farther downstream in buried than in open streams before being removed from the water column, indicating that burial substantially reduces N uptake in streams. Simulation modeling suggests that as burial expands throughout a river network, N uptake rates increase in the remaining open reaches which somewhat offsets reduced N uptake in buried reaches. This is particularly true at low levels of stream burial. At higher levels of stream burial, however, open reaches become rare and cumulative N uptake across all open reaches in the watershed rapidly declines. As a result, watershed-scale N export increases slowly at low levels of stream burial, after which increases in export become more pronounced. Stream burial in the lower, more urbanized portions of the watershed had a greater effect on N export than an equivalent amount of stream burial in the upper watershed. We suggest that stream daylighting (i.e., uncovering buried streams can increase watershed-scale N retention.

Key Management Schemes for Peer-to-Peer Multimedia Streaming Overlay Networks

Science.gov (United States)

Naranjo, J. A. M.; López-Ramos, J. A.; Casado, L. G.

Key distribution for multimedia live streaming peer-to-peer overlay networks is a field still in its childhood stage. A scheme designed for networks of this kind must seek security and efficiency while keeping in mind the following restrictions: limited bandwidth, continuous playing, great audience size and clients churn. This paper introduces two novel schemes that allow a trade-off between security and efficiency by allowing to dynamically vary the number of levels used in the key hierarchy. These changes are motivated by great variations in audience size, and initiated by decision of the Key Server. Additionally, a comparative study of both is presented, focusing on security and audience size. Results show that larger key hierarchies can supply bigger audiences, but offer less security against statistical attacks. The opposite happens for shorter key hierarchies.

Continental hydrosystem modelling: the concept of nested stream-aquifer interfaces

Science.gov (United States)

Flipo, N.; Mouhri, A.; Labarthe, B.; Biancamaria, S.; Rivière, A.; Weill, P.

2014-08-01

Coupled hydrological-hydrogeological models, emphasising the importance of the stream-aquifer interface, are more and more used in hydrological sciences for pluri-disciplinary studies aiming at investigating environmental issues. Based on an extensive literature review, stream-aquifer interfaces are described at five different scales: local [10 cm-~10 m], intermediate [~10 m-~1 km], watershed [10 km2-~1000 km2], regional [10 000 km2-~1 M km2] and continental scales [>10 M km2]. This led us to develop the concept of nested stream-aquifer interfaces, which extends the well-known vision of nested groundwater pathways towards the surface, where the mixing of low frequency processes and high frequency processes coupled with the complexity of geomorphological features and heterogeneities creates hydrological spiralling. This conceptual framework allows the identification of a hierarchical order of the multi-scale control factors of stream-aquifer hydrological exchanges, from the larger scale to the finer scale. The hyporheic corridor, which couples the river to its 3-D hyporheic zone, is then identified as the key component for scaling hydrological processes occurring at the interface. The identification of the hyporheic corridor as the support of the hydrological processes scaling is an important step for the development of regional studies, which is one of the main concerns for water practitioners and resources managers. In a second part, the modelling of the stream-aquifer interface at various scales is investigated with the help of the conductance model. Although the usage of the temperature as a tracer of the flow is a robust method for the assessment of stream-aquifer exchanges at the local scale, there is a crucial need to develop innovative methodologies for assessing stream-aquifer exchanges at the regional scale. After formulating the conductance model at the regional and intermediate scales, we address this challenging issue with the development of an

Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes

Science.gov (United States)

Mollenhauer, Robert; Mouser, Joshua B.; Brewer, Shannon K.

2018-01-01

Temporal and spatial variability in streams result in heterogeneous gear capture probability (i.e., the proportion of available individuals identified) that confounds interpretation of data used to monitor fish abundance. We modeled tow-barge electrofishing capture probability at multiple spatial scales for nine Ozark Highland stream fishes. In addition to fish size, we identified seven reach-scale environmental characteristics associated with variable capture probability: stream discharge, water depth, conductivity, water clarity, emergent vegetation, wetted width–depth ratio, and proportion of riffle habitat. The magnitude of the relationship between capture probability and both discharge and depth varied among stream fishes. We also identified lithological characteristics among stream segments as a coarse-scale source of variable capture probability. The resulting capture probability model can be used to adjust catch data and derive reach-scale absolute abundance estimates across a wide range of sampling conditions with similar effort as used in more traditional fisheries surveys (i.e., catch per unit effort). Adjusting catch data based on variable capture probability improves the comparability of data sets, thus promoting both well-informed conservation and management decisions and advances in stream-fish ecology.

Optimizing Reservoir-Stream-Aquifer Interactions for Conjunctive Use and Hydropower Production

Directory of Open Access Journals (Sweden)

Hala Fayad

2012-01-01

Full Text Available Conjunctive management of water resources involves coordinating use of surface water and groundwater resources. Very few simulation/optimization (S-O models for stream-aquifer system management have included detailed interactions between groundwater, streams, and reservoir storage. This paper presents an S-O model doing that via artificial neural network simulators and genetic algorithm optimizer for multiobjective conjunctive water use problems. The model simultaneously addresses all significant flows including reservoir-stream-diversion-aquifer interactions in a more detailed manner than previous models. The model simultaneously maximizes total water provided and hydropower production. A penalty function implicitly poses constraints on state variables. The model effectively finds feasible optimal solutions and the Pareto optimum. Illustrated is application for planning water resource and minihydropower system development.

How and Why Does Stream Water Temperature Vary at Small Spatial Scales in a Headwater Stream?

Science.gov (United States)

Morgan, J. C.; Gannon, J. P.; Kelleher, C.

2017-12-01

The temperature of stream water is controlled by climatic variables, runoff/baseflow generation, and hyporheic exchange. Hydrologic conditions such as gaining/losing reaches and sources of inflow can vary dramatically along a stream on a small spatial scale. In this work, we attempt to discern the extent that the factors of air temperature, groundwater inflow, and precipitation influence stream temperature at small spatial scales along the length of a stream. To address this question, we measured stream temperature along the perennial stream network in a 43 ha catchment with a complex land use history in Cullowhee, NC. Two water temperature sensors were placed along the stream network on opposite sides of the stream at 100-meter intervals and at several locations of interest (i.e. stream junctions). The forty total sensors recorded the temperature every 10 minutes for one month in the spring and one month in the summer. A subset of sampling locations where stream temperature was consistent or varied from one side of the stream to the other were explored with a thermal imaging camera to obtain a more detailed representation of the spatial variation in temperature at those sites. These thermal surveys were compared with descriptions of the contributing area at the sample sites in an effort to discern specific causes of differing flow paths. Preliminary results suggest that on some branches of the stream stormflow has less influence than regular hyporheic exchange, while other tributaries can change dramatically with stormflow conditions. We anticipate this work will lead to a better understanding of temperature patterns in stream water networks. A better understanding of the importance of small-scale differences in flow paths to water temperature may be able to inform watershed management decisions in the future.

Stream Tracker: Crowd sourcing and remote sensing to monitor stream flow intermittence

Science.gov (United States)

Puntenney, K.; Kampf, S. K.; Newman, G.; Lefsky, M. A.; Weber, R.; Gerlich, J.

2017-12-01

Streams that do not flow continuously in time and space support diverse aquatic life and can be critical contributors to downstream water supply. However, these intermittent streams are rarely monitored and poorly mapped. Stream Tracker is a community powered stream monitoring project that pairs citizen contributed observations of streamflow presence or absence with a network of streamflow sensors and remotely sensed data from satellites to track when and where water is flowing in intermittent stream channels. Citizens can visit sites on roads and trails to track flow and contribute their observations to the project site hosted by CitSci.org. Data can be entered using either a mobile application with offline capabilities or an online data entry portal. The sensor network provides a consistent record of streamflow and flow presence/absence across a range of elevations and drainage areas. Capacitance, resistance, and laser sensors have been deployed to determine the most reliable, low cost sensor that could be mass distributed to track streamflow intermittence over a larger number of sites. Streamflow presence or absence observations from the citizen and sensor networks are then compared to satellite imagery to improve flow detection algorithms using remotely sensed data from Landsat. In the first two months of this project, 1,287 observations have been made at 241 sites by 24 project members across northern and western Colorado.

Application of Genetic Programing to Develop a Modular Model for the Simulation of Stream Flow Time Series

Science.gov (United States)

Meshgi, A.; Babovic, V.; Chui, T. F. M.; Schmitter, P.

2014-12-01

Developing reliable methods to estimate stream flow has been a subject of interest due to its importance in planning, design and management of water resources within a basin. Machine learning tools such as Artificial Neural Network (ANN) and Genetic Programming (GP) have been widely applied for rainfall-runoff modeling as they require less computational time as compared to physically-based models. As GP is able to generate a function with understandable structure, it may offer advantages over other data driven techniques and therefore has been used in different studies to generate rainfall-runoff functions. However, to date, proposed formulations only contain rainfall and/or streamflow data and consequently are local and cannot be generalized and adopted in other catchments which have different physical characteristics. This study investigated the capability of GP in developing a physically interpretable model with understandable structure to simulate stream flow based on hydrological parameters (e.g. precipitation) and catchment conditions (e.g., initial groundwater table elevation and area of the catchment) by following a modular approach. The modular model resulted in two sub-models where the baseflow was first predicted and the direct runoff was then estimated for a semi-urban catchment in Singapore. The simulated results matched very well with observed data in both the training and the testing of data sets, giving NSEs of 0.97 and 0.96 respectively demonstrated the successful estimation of stream flow using the modular model derived in this study. The results of this study indicate that GP is an effective tool in developing a physically interpretable model with understandable structure to simulate stream flow that can be transferred to other catchments.

Encryption for confidentiality of the network and influence of this to the quality of streaming video through network

Science.gov (United States)

Sevcik, L.; Uhrin, D.; Frnda, J.; Voznak, M.; Toral-Cruz, Homer; Mikulec, M.; Jakovlev, Sergej

2015-05-01

Nowadays, the interest in real-time services, like audio and video, is growing. These services are mostly transmitted over packet networks, which are based on IP protocol. It leads to analyses of these services and their behavior in such networks which are becoming more frequent. Video has become the significant part of all data traffic sent via IP networks. In general, a video service is one-way service (except e.g. video calls) and network delay is not such an important factor as in a voice service. Dominant network factors that influence the final video quality are especially packet loss, delay variation and the capacity of the transmission links. Analysis of video quality concentrates on the resistance of video codecs to packet loss in the network, which causes artefacts in the video. IPsec provides confidentiality in terms of safety, integrity and non-repudiation (using HMAC-SHA1 and 3DES encryption for confidentiality and AES in CBC mode) with an authentication header and ESP (Encapsulating Security Payload). The paper brings a detailed view of the performance of video streaming over an IP-based network. We compared quality of video with packet loss and encryption as well. The measured results demonstrated the relation between the video codec type and bitrate to the final video quality.

Implementation of a subcanopy solar radiation model on a forested headwater basin in the Southern Appalachians to estimate riparian canopy density and stream insolation for stream temperature models

Science.gov (United States)

Belica, L.; Petras, V.; Iiames, J. S., Jr.; Caldwell, P.; Mitasova, H.; Nelson, S. A. C.

2016-12-01

Water temperature is a key aspect of water quality and understanding how the thermal regimes of forested headwater streams may change in response to climatic and land cover changes is increasingly important to scientists and resource managers. In recent years, the forested mountain watersheds of the Southeastern U.S. have experienced changing climatic patterns as well as the loss of a keystone riparian tree species and anticipated hydrologic responses include lower summer stream flows and decreased stream shading. Solar radiation is the main source of thermal energy to streams and a key parameter in heat-budget models of stream temperature; a decrease in flow volume combined with a reduction in stream shading during summer have the potential to increase stream temperatures. The high spatial variability of forest canopies and the high spatio-temporal variability in sky conditions make estimating the solar radiation reaching small forested headwater streams difficult. The Subcanopy Solar Radiation Model (SSR) (Bode et al. 2014) is a GIS model that generates high resolution, spatially explicit estimates of solar radiation by incorporating topographic and vegetative shading with a light penetration index derived from leaf-on airborne LIDAR data. To evaluate the potential of the SSR model to provide estimates of stream insolation to parameterize heat-budget models, it was applied to the Coweeta Basin in the Southern Appalachians using airborne LIDAR (NCALM 2009, 1m resolution). The LIDAR derived canopy characteristics were compared to current hyperspectral images of the canopy for changes and the SSR estimates of solar radiation were compared with pyranometer measurements of solar radiation at several subcanopy sites during the summer of 2016. Preliminary results indicate the SSR model was effective in identifying variations in canopy density and light penetration, especially in areas associated with road and stream corridors and tree mortality. Current LIDAR data and

Heat transfer entropy resistance for the analyses of two-stream heat exchangers and two-stream heat exchanger networks

International Nuclear Information System (INIS)

Cheng, XueTao; Liang, XinGang

2013-01-01

The entropy generation minimization method is often used to analyze heat transfer processes from the thermodynamic viewpoint. In this paper, we analyze common heat transfer processes with the concept of entropy generation, and propose the concept of heat transfer entropy resistance. It is found that smaller heat transfer entropy resistance leads to smaller equivalent thermodynamic force difference with prescribed heat transfer rate and larger heat transfer rate with prescribed equivalent thermodynamic force difference. With the concept of heat transfer entropy resistance, the performance of two-stream heat exchangers (THEs) and two-stream heat exchanger networks (THENs) is analyzed. For the cases discussed in this paper, it is found that smaller heat transfer entropy resistance always leads to better heat transfer performance for THEs and THENs, while smaller values of the entropy generation, entropy generation numbers and revised entropy generation number do not always. -- Highlights: • The concept of entropy resistance is defined. • The minimum entropy resistance principle is developed. • Smaller entropy resistance leads to better heat transfer

An Analysis of Quality of Service (QoS In Live Video Streaming Using Evolved HSPA Network Media

Directory of Open Access Journals (Sweden)

Achmad Zakaria Azhar

2016-10-01

Full Text Available Evolved High Speed Packet Access (HSPA+ is a mobile telecommunication system technology and the evolution of HSPA technology. This technology has a packet data based service with downlink speeds up to 21.1 Mbps and uplink speed up to 11.5 Mbps on the bandwidth 5MHz. This technology is expected to fulfill and support the needs for information that involves all aspects of multimedia such as video and audio, especially live video streaming. By utilizing this technology it will facilitate communicating the information, for example to monitoring the situation of the house, the news coverage at some certain area, and other events in real time. This thesis aims to identify and test the Quality of Service (QoS performance on the network that is used for live video streaming with the parameters of throughput, delay, jitter and packet loss. The software used for monitoring the data traffic of the live video streaming network is wireshark network analyzer. From the test results it is obtained that the average throughput of provider B is 5,295 Kbps bigger than the provider A, the average delay of provider B is 0.618 ms smaller than the provider A, the average jitter of provider B is 0.420 ms smaller than the provider A and the average packet loss of provider B is 0.451% smaller than the provider A.

Stream network geomorphology mediates predicted vulnerability of anadromous fish habitat to hydrologic change in southeast Alaska.

Science.gov (United States)

Sloat, Matthew R; Reeves, Gordon H; Christiansen, Kelly R

2017-02-01

In rivers supporting Pacific salmon in southeast Alaska, USA, regional trends toward a warmer, wetter climate are predicted to increase mid- and late-21st-century mean annual flood size by 17% and 28%, respectively. Increased flood size could alter stream habitats used by Pacific salmon for reproduction, with negative consequences for the substantial economic, cultural, and ecosystem services these fish provide. We combined field measurements and model simulations to estimate the potential influence of future flood disturbance on geomorphic processes controlling the quality and extent of coho, chum, and pink salmon spawning habitat in over 800 southeast Alaska watersheds. Spawning habitat responses varied widely across watersheds and among salmon species. Little variation among watersheds in potential spawning habitat change was explained by predicted increases in mean annual flood size. Watershed response diversity was mediated primarily by topographic controls on stream channel confinement, reach-scale geomorphic associations with spawning habitat preferences, and complexity in the pace and mode of geomorphic channel responses to altered flood size. Potential spawning habitat loss was highest for coho salmon, which spawn over a wide range of geomorphic settings, including steeper, confined stream reaches that are more susceptible to streambed scour during high flows. We estimated that 9-10% and 13-16% of the spawning habitat for coho salmon could be lost by the 2040s and 2080s, respectively, with losses occurring primarily in confined, higher-gradient streams that provide only moderate-quality habitat. Estimated effects were lower for pink and chum salmon, which primarily spawn in unconfined floodplain streams. Our results illustrate the importance of accounting for valley and reach-scale geomorphic features in watershed assessments of climate vulnerability, especially in topographically complex regions. Failure to consider the geomorphic context of stream

Habitat hydraulic models - a tool for Danish stream quality assessment?

DEFF Research Database (Denmark)

Olsen, Martin

and hydromorphological and chemical characteristics has to be enlightened (EUROPA, 2005). This study links catchment hydrology, stream discharge and physical habitat in a small Danish stream, the stream Ledreborg, and discusses the utility of habitat hydraulic models in relation to the present criteria and methods used......).  Hydromorphological conditions in the stream are measured through field study, using a habitat mapping approach and modelled using a habitat hydraulic model (RHYHABSIM). Using RHYHABSIM and both "site-specific" and general HSI's, Weighted Usable Area (WUA) for the trout population at different discharges is assessed...... and differences between simulated WUA using "site-specific" and general habitat preferences are discussed. In RHYHABSIM it is possible to use two different approaches to investigate the hydromorphological conditions in a river, the habitat mapping approach used in this project and the representative reach...

Maximization Network Throughput Based on Improved Genetic Algorithm and Network Coding for Optical Multicast Networks

Science.gov (United States)

Wei, Chengying; Xiong, Cuilian; Liu, Huanlin

2017-12-01

Maximal multicast stream algorithm based on network coding (NC) can improve the network's throughput for wavelength-division multiplexing (WDM) networks, which however is far less than the network's maximal throughput in terms of theory. And the existing multicast stream algorithms do not give the information distribution pattern and routing in the meantime. In the paper, an improved genetic algorithm is brought forward to maximize the optical multicast throughput by NC and to determine the multicast stream distribution by hybrid chromosomes construction for multicast with single source and multiple destinations. The proposed hybrid chromosomes are constructed by the binary chromosomes and integer chromosomes, while the binary chromosomes represent optical multicast routing and the integer chromosomes indicate the multicast stream distribution. A fitness function is designed to guarantee that each destination can receive the maximum number of decoding multicast streams. The simulation results showed that the proposed method is far superior over the typical maximal multicast stream algorithms based on NC in terms of network throughput in WDM networks.

Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models

Directory of Open Access Journals (Sweden)

Sungwon Kim

2015-06-01

Full Text Available The objective of this study is to develop artificial neural network (ANN models, including multilayer perceptron (MLP and Kohonen self-organizing feature map (KSOFM, for spatial disaggregation of areal rainfall in the Wi-stream catchment, an International Hydrological Program (IHP representative catchment, in South Korea. A three-layer MLP model, using three training algorithms, was used to estimate areal rainfall. The Levenberg–Marquardt training algorithm was found to be more sensitive to the number of hidden nodes than were the conjugate gradient and quickprop training algorithms using the MLP model. Results showed that the networks structures of 11-5-1 (conjugate gradient and quickprop and 11-3-1 (Levenberg-Marquardt were the best for estimating areal rainfall using the MLP model. The networks structures of 1-5-11 (conjugate gradient and quickprop and 1-3-11 (Levenberg–Marquardt, which are the inverse networks for estimating areal rainfall using the best MLP model, were identified for spatial disaggregation of areal rainfall using the MLP model. The KSOFM model was compared with the MLP model for spatial disaggregation of areal rainfall. The MLP and KSOFM models could disaggregate areal rainfall into individual point rainfall with spatial concepts.

Stream isotherm shifts from climate change and implications for distributions of ectothermic organisms

Science.gov (United States)

Daniel J. Isaak; Bruce E. Rieman

2013-01-01

Stream ecosystems are especially vulnerable to climate warming because most aquatic organisms are ectothermic and live in dendritic networks that are easily fragmented. Many bioclimatic models predict significant range contractions in stream biotas, but subsequent biological assessments have rarely been done to determine the accuracy of these predictions. Assessments...

Application of two-stream model to solar radiation of rice canopy

International Nuclear Information System (INIS)

Kawakata, T.

2005-01-01

The amount of solar radiation absorbed by a crop canopy is correlated with crop production, and thus it is necessary to estimate both transmission and reflection around the canopy for crop growth models. The 'forward and backward streams' representation of radiation has been refined to account for both transmission and reflection in the crop canopy. However, this model has not been applied to a rice canopy through the growing period. The purpose of this study is to examine whether the two-stream model is applicable to the rice canopy, and to investigate the parameters of the model. The values for both transmittance below the rice canopy and reflectance above it that were derived from the two-stream model represent the observed values throughout the growing period. The inclination factor of leaves (F), which is used in the two-stream model, was almost equivalent to the extinction coefficient of transmittance in the case of the rice canopy

An initial SPARROW model of land use and in-stream controls on total organic carbon in streams of the conterminous United States

Science.gov (United States)

Shih, Jhih-Shyang; Alexander, Richard B.; Smith, Richard A.; Boyer, Elizabeth W.; Shwarz, Grogory E.; Chung, Susie

2010-01-01

Watersheds play many important roles in the carbon cycle: (1) they are a site for both terrestrial and aquatic carbon dioxide (CO2) removal through photosynthesis; (2) they transport living and decomposing organic carbon in streams and groundwater; and (3) they store organic carbon for widely varying lengths of time as a function of many biogeochemical factors. Using the U.S. Geological Survey (USGS) Spatially Referenced Regression on Watershed Attributes (SPARROW) model, along with long-term monitoring data on total organic carbon (TOC), this research quantitatively estimates the sources, transport, and fate of the long-term mean annual load of TOC in streams of the conterminous United States. The model simulations use surrogate measures of the major terrestrial and aquatic sources of organic carbon to estimate the long-term mean annual load of TOC in streams. The estimated carbon sources in the model are associated with four land uses (urban, cultivated, forest, and wetlands) and autochthonous fixation of carbon (stream photosynthesis). Stream photosynthesis is determined by reach-level application of an empirical model of stream chlorophyll based on total phosphorus concentration, and a mechanistic model of photosynthetic rate based on chlorophyll, average daily solar irradiance, water column light attenuation, and reach dimensions. It was found that the estimate of in-stream photosynthesis is a major contributor to the mean annual TOC load per unit of drainage area (that is, yield) in large streams, with a median share of about 60 percent of the total mean annual carbon load in streams with mean flows above 500 cubic feet per second. The interquartile range of the model predictions of TOC from in-stream photosynthesis is from 0.1 to 0.4 grams (g) carbon (C) per square meter (m-2) per day (day-1) for the approximately 62,000 stream reaches in the continental United States, which compares favorably with the reported literature range for net carbon fixation by

Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding

Science.gov (United States)

Cui, Laizhong; Lu, Nan; Chen, Fu

2014-01-01

Most large-scale peer-to-peer (P2P) live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments. PMID:25114968

Models of Tidally Induced Gas Filaments in the Magellanic Stream

Science.gov (United States)

Pardy, Stephen A.; D’Onghia, Elena; Fox, Andrew J.

2018-04-01

The Magellanic Stream and Leading Arm of H I that stretches from the Large and Small Magellanic Clouds (LMC and SMC) and over 200° of the Southern sky is thought to be formed from multiple encounters between the LMC and SMC. In this scenario, most of the gas in the Stream and Leading Arm is stripped from the SMC, yet recent observations have shown a bifurcation of the Trailing Arm that reveals LMC origins for some of the gas. Absorption measurements in the Stream also reveal an order of magnitude more gas than in current tidal models. We present hydrodynamical simulations of the multiple encounters between the LMC and SMC at their first pass around the Milky Way, assuming that the Clouds were more extended and gas-rich in the past. Our models create filamentary structures of gas in the Trailing Stream from both the LMC and SMC. While the SMC trailing filament matches the observed Stream location, the LMC filament is offset. In addition, the total observed mass of the Stream in these models is underestimated by a factor of four when the ionized component is accounted for. Our results suggest that there should also be gas stripped from both the LMC and SMC in the Leading Arm, mirroring the bifurcation in the Trailing Stream. This prediction is consistent with recent measurements of spatial variation in chemical abundances in the Leading Arm, which show that gas from multiple sources is present, although its nature is still uncertain.

A modelling study of hyporheic exchange pattern and the sequence, size, and spacing of stream bedforms in mountain stream networks, Oregon, USA.

Science.gov (United States)

Michael N. Gooseff; Justin K. Anderson; Steven M. Wondzell; Justin LaNier; Roy. Haggerty

2005-01-01

Studies of hyporheic exchange flows have identified physical features of channels that control exchange flow at the channel unit scale, namely slope breaks in the longitudinal profile of streams that generate subsurface head distributions. We recently completed a field study that suggested channel unit spacing in stream longitudinal profiles can be used to predict the...

Anomaly Detection in Dynamic Networks

Energy Technology Data Exchange (ETDEWEB)

Turcotte, Melissa [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2014-10-14

Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. A second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the

The significance of small streams

Science.gov (United States)

Wohl, Ellen

2017-09-01

Headwaters, defined here as first- and secondorder streams, make up 70%‒80% of the total channel length of river networks. These small streams exert a critical influence on downstream portions of the river network by: retaining or transmitting sediment and nutrients; providing habitat and refuge for diverse aquatic and riparian organisms; creating migration corridors; and governing connectivity at the watershed-scale. The upstream-most extent of the channel network and the longitudinal continuity and lateral extent of headwaters can be difficult to delineate, however, and people are less likely to recognize the importance of headwaters relative to other portions of a river network. Consequently, headwaters commonly lack the legal protections accorded to other portions of a river network and are more likely to be significantly altered or completely obliterated by land use.

Mapping a lateralisation gradient within the ventral stream for auditory speech perception

OpenAIRE

Karsten eSpecht

2013-01-01

Recent models on speech perception propose a dual stream processing network, with a dorsal stream, extending from the posterior temporal lobe of the left hemisphere through inferior parietal areas into the left inferior frontal gyrus, and a ventral stream that is assumed to originate in the primary auditory cortex in the upper posterior part of the temporal lobe and to extend towards the anterior part of the temporal lobe, where it may connect to the ventral part of the inferior frontal gyrus...

Mapping a lateralization gradient within the ventral stream for auditory speech perception

OpenAIRE

Specht, Karsten

2013-01-01

Recent models on speech perception propose a dual-stream processing network, with a dorsal stream, extending from the posterior temporal lobe of the left hemisphere through inferior parietal areas into the left inferior frontal gyrus, and a ventral stream that is assumed to originate in the primary auditory cortex in the upper posterior part of the temporal lobe and to extend toward the anterior part of the temporal lobe, where it may connect to the ventral part of the inferior frontal gyrus....

Computing Diameter in the Streaming and Sliding-Window Models (Preprint)

National Research Council Canada - National Science Library

Feigenbaum, Joan; Kannan, Sampath; Zhang, Jian

2002-01-01

We investigate the diameter problem in the streaming and sliding-window models. We show that, for a stream of n points or a sliding window of size n, any exact algorithm for diameter requires Omega(n) bits of space...

Effective Quality-of-Service Renegotiating Schemes for Streaming Video

Directory of Open Access Journals (Sweden)

Song Hwangjun

2004-01-01

Full Text Available This paper presents effective quality-of-service renegotiating schemes for streaming video. The conventional network supporting quality of service generally allows a negotiation at a call setup. However, it is not efficient for the video application since the compressed video traffic is statistically nonstationary. Thus, we consider the network supporting quality-of-service renegotiations during the data transmission and study effective quality-of-service renegotiating schemes for streaming video. The token bucket model, whose parameters are token filling rate and token bucket size, is adopted for the video traffic model. The renegotiating time instants and the parameters are determined by analyzing the statistical information of compressed video traffic. In this paper, two renegotiating approaches, that is, fixed renegotiating interval case and variable renegotiating interval case, are examined. Finally, the experimental results are provided to show the performance of the proposed schemes.

Tracing disturbance impacts on water quantity and quality through a stream network

Science.gov (United States)

Ross, Matthew; Nippgen, Fabian; McGlynn, Brian; Bernhardt, Emily

2017-04-01

By dismantling and redistributing 100s of meters of bedrock to mine coal from the surface, mountaintop mining with valley fills has dramatically changed catchment hydrology and biogeochemistry over more than 5,000 km2 in Central Appalachia. Throughout this expansive coal region, mining operators deposit tens of millions of m3 of crushed bedrock into headwater valleys, creating valley fills, which have substantial subsurface water storage potential. Streams draining mines have reduced peakflows, elevated baseflows, and lower event runoff ratios on average. The water stored in and percolating through valley fills drives the dissolution and oxidation of pyrite into sulfuric acid which reacts with carbonate-rich materials to rapidly weather out a suite of elements including Ca2+, Mg2+, K+, SO42-, HCO3-, and the pollutant Selenium. Together these ions increase the average specific conductance of mined streams from 60 to 1,500 µS/cm, 25-times higher than unmined streams, exporting 45-times more total dissolved solids. Together, the increased catchment storage, consequent elevated baseflow, and elevated weathering rates from mining have the potential to lower water quality throughout river networks in Central Appalachia, especially during the summer low flow period. To better understand the water quality impacts of mining at the river network scale, we used the paired catchment approach. Working in the Mud River, West Virginia, we instrumented a 4th order catchment 35 km2, that was 46% mined. Within the large catchment we instrumented 8 additional 1st-3rd order sub-catchments that varied in catchment size, mining cover, mine size, and mine age. At each site we measured stream discharge and specific conductance (SC). Using SC as a trace for mining we did simple hydrograph separations at our largest catchments, partitioning the hydrograph between mined and unmined water. Our results suggest that on an annual scale, mine water contributes a disproportionate percentage of

Analysis of radionuclide migration through fractures using the stream tube approach

International Nuclear Information System (INIS)

Jong Soon Song; Kun Jai Lee

1988-01-01

An analytical solution for the radionuclide migration in the heterogeneous geologic media is developed by using the Green's function techniques. To take into account the non-homogeneous geologic formation and non-uniform groundwater flow field effectively, a combined fracture/porous media model (in series network) is introduced. The stream tube approach is suggested as an efficient method to analyze groundwater hydrology occurring primarily along the fractures. With this approach, three-dimensional heterogeneous media may be approximated as a network of one-dimensional flow paths (fractures) and the corresponding subsurface transport equations can be solved more easily and efficiently by using the Green's function technique within each unit stream tubes. Also a method of combining the corresponding separate Green's functions to derive an overall Green's function for the flow path network is developed. Analytical solutions with various time-dependent radionuclide release modes for heterogeneous geologic media are obtained and sample calculations are performed for the parametric studies. Comparison with other model shows the validity of the present model. 22 refs.; 11 figs.; 5 tabs

NLP model and stochastic multi-start optimization approach for heat exchanger networks

International Nuclear Information System (INIS)

Núñez-Serna, Rosa I.; Zamora, Juan M.

2016-01-01

Highlights: • An NLP model for the optimal design of heat exchanger networks is proposed. • The NLP model is developed from a stage-wise grid diagram representation. • A two-phase stochastic multi-start optimization methodology is utilized. • Improved network designs are obtained with different heat load distributions. • Structural changes and reductions in the number of heat exchangers are produced. - Abstract: Heat exchanger network synthesis methodologies frequently identify good network structures, which nevertheless, might be accompanied by suboptimal values of design variables. The objective of this work is to develop a nonlinear programming (NLP) model and an optimization approach that aim at identifying the best values for intermediate temperatures, sub-stream flow rate fractions, heat loads and areas for a given heat exchanger network topology. The NLP model that minimizes the total annual cost of the network is constructed based on a stage-wise grid diagram representation. To improve the possibilities of obtaining global optimal designs, a two-phase stochastic multi-start optimization algorithm is utilized for the solution of the developed model. The effectiveness of the proposed optimization approach is illustrated with the optimization of two network designs proposed in the literature for two well-known benchmark problems. Results show that from the addressed base network topologies it is possible to achieve improved network designs, with redistributions in exchanger heat loads that lead to reductions in total annual costs. The results also show that the optimization of a given network design sometimes leads to structural simplifications and reductions in the total number of heat exchangers of the network, thereby exposing alternative viable network topologies initially not anticipated.

Accessing Wireless Sensor Networks Via Dynamically Reconfigurable Interaction Models

Directory of Open Access Journals (Sweden)

Maria Cecília Gomes

2012-12-01

Full Text Available The Wireless Sensor Networks (WSNs technology is already perceived as fundamental for science across many domains, since it provides a low cost solution for environment monitoring. WSNs representation via the service concept and its inclusion in Web environments, e.g. through Web services, supports particularly their open/standard access and integration. Although such Web enabled WSNs simplify data access, network parameterization and aggregation, the existing interaction models and run-time adaptation mechanisms available to clients are still scarce. Nevertheless, applications increasingly demand richer and more flexible accesses besides the traditional client/server. For instance, applications may require a streaming model in order to avoid sequential data requests, or the asynchronous notification of subscribed data through the publish/subscriber. Moreover, the possibility to automatically switch between such models at runtime allows applications to define flexible context-based data acquisition. To this extent, this paper discusses the relevance of the session and pattern abstractions on the design of a middleware prototype providing richer and dynamically reconfigurable interaction models to Web enabled WSNs.

Semantic Network Adaptation Based on QoS Pattern Recognition for Multimedia Streams

Science.gov (United States)

Exposito, Ernesto; Gineste, Mathieu; Lamolle, Myriam; Gomez, Jorge

This article proposes an ontology based pattern recognition methodology to compute and represent common QoS properties of the Application Data Units (ADU) of multimedia streams. The use of this ontology by mechanisms located at different layers of the communication architecture will allow implementing fine per-packet self-optimization of communication services regarding the actual application requirements. A case study showing how this methodology is used by error control mechanisms in the context of wireless networks is presented in order to demonstrate the feasibility and advantages of this approach.

Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

KAUST Repository

Afify, Laila H.

2016-10-11

This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

KAUST Repository

Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2016-01-01

This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

Network analysis applications in hydrology

Science.gov (United States)

Price, Katie

2017-04-01

Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

Dynamic network expansion, contraction, and connectivity in the river corridor of mountain stream network

Science.gov (United States)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.

2017-12-01

River networks are broadly recognized to expand and contract in response to hydrologic forcing. Additionally, the individual controls on river corridor dynamics of hydrologic forcing and geologic setting are well recognized. However, we currently lack tools to integrate our understanding of process dynamics in the river corridor and make predictions at the scale of river networks. In this study, we develop a perceptual model of the river corridor in mountain river networks, translate this into a reduced-complexity mechanistic model, and implement the model in a well-studied headwater catchment. We found that the river network was most sensitive to hydrologic dynamics under the lowest discharges (Qgauge managers of water resources who need to estimate connectivity and flow initiation location along the river corridor over broad, unstudied catchments.

Analysis of hydraulic characteristics for stream diversion in small stream

Energy Technology Data Exchange (ETDEWEB)

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.

Impact of river stage prediction methods on stream-aquifer exchanges in a hydro(geo)logical model at the regional scale

Science.gov (United States)

Saleh, F.; Flipo, N.; de Fouquet, C.

2012-04-01

The main objective of this study is to provide a realistic simulation of river stage in regional river networks in order to improve the quantification of stream-aquifer exchanges and better assess the associated aquifer responses that are often impacted by the magnitude and the frequency of the river stage fluctuations. The study focuses on the Oise basin (17 000 km2, part of the 65 000 km2 Seine basin in Northern France) where stream-aquifer exchanges cannot be assessed directly by experimental methods. Nowadays numerical methods are the most appropriate approaches for assessing stream-aquifer exchanges at this scale. A regional distributed process-based hydro(geo)logical model, Eau-Dyssée, is used, which aims at the integrated modeling of the hydrosystem to manage the various elements involved in the quantitative and qualitative aspects of water resources. Eau-Dyssée simulates pseudo 3D flow in aquifer systems solving the diffusivity equation with a finite difference numerical scheme. River flow is simulated with a Muskingum model. In addition to the in-stream discharge, a river stage estimate is needed to calculate the water exchange at the stream-aquifer interface using the Darcy law. Three methods for assessing in-stream river stages are explored to determine the most appropriate representation at regional scale over 25 years (1980-2005). The first method consists in defining rating curves for each cell of a 1D Saint-Venant hydraulic model. The second method consists in interpolating observed rating curves (at gauging stations) onto the river cells of the hydro(geo)logical model. The interpolation technique is based on geostatistics. The last method assesses river stage using Manning equation with a simplified rectangular cross-section (water depth equals the hydraulic radius). Compared to observations, the geostatistical and the Manning methodologies lead to slightly less accurate (but still acceptable) results offering a low computational cost opportunity

Artificial intelligence based models for stream-flow forecasting: 2000-2015

Science.gov (United States)

Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

2015-11-01

The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Waqas Rehan

2016-09-01

Full Text Available Wireless sensor networks (WSNs have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM, that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI and the average of the link quality indicator (LQI of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC algorithm in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC algorithm, that can perform channel quality estimation on the basis of both current and past values of channel rank estimation

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

Science.gov (United States)

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-09-12

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end

Design tradeoffs in long-term research for stream salamanders

Science.gov (United States)

Brand, Adrianne B,; Grant, Evan H. Campbell

2017-01-01

Long-term research programs can benefit from early and periodic evaluation of their ability to meet stated objectives. In particular, consideration of the spatial allocation of effort is key. We sampled 4 species of stream salamanders intensively for 2 years (2010–2011) in the Chesapeake and Ohio Canal National Historical Park, Maryland, USA to evaluate alternative distributions of sampling locations within stream networks, and then evaluated via simulation the ability of multiple survey designs to detect declines in occupancy and to estimate dynamic parameters (colonization, extinction) over 5 years for 2 species. We expected that fine-scale microhabitat variables (e.g., cobble, detritus) would be the strongest determinants of occupancy for each of the 4 species; however, we found greater support for all species for models including variables describing position within the stream network, stream size, or stream microhabitat. A monitoring design focused on headwater sections had greater power to detect changes in occupancy and the dynamic parameters in each of 3 scenarios for the dusky salamander (Desmognathus fuscus) and red salamander (Pseudotriton ruber). Results for transect length were more variable, but across all species and scenarios, 25-m transects are most suitable as a balance between maximizing detection probability and describing colonization and extinction. These results inform sampling design and provide a general framework for setting appropriate goals, effort, and duration in the initial planning stages of research programs on stream salamanders in the eastern United States.

Comparing stream-specific to generalized temperature models to guide salmonid management in a changing climate

Science.gov (United States)

Andrew K. Carlson,; William W. Taylor,; Hartikainen, Kelsey M.; Dana M. Infante,; Beard, Douglas; Lynch, Abigail

2017-01-01

Global climate change is predicted to increase air and stream temperatures and alter thermal habitat suitability for growth and survival of coldwater fishes, including brook charr (Salvelinus fontinalis), brown trout (Salmo trutta), and rainbow trout (Oncorhynchus mykiss). In a changing climate, accurate stream temperature modeling is increasingly important for sustainable salmonid management throughout the world. However, finite resource availability (e.g. funding, personnel) drives a tradeoff between thermal model accuracy and efficiency (i.e. cost-effective applicability at management-relevant spatial extents). Using different projected climate change scenarios, we compared the accuracy and efficiency of stream-specific and generalized (i.e. region-specific) temperature models for coldwater salmonids within and outside the State of Michigan, USA, a region with long-term stream temperature data and productive coldwater fisheries. Projected stream temperature warming between 2016 and 2056 ranged from 0.1 to 3.8 °C in groundwater-dominated streams and 0.2–6.8 °C in surface-runoff dominated systems in the State of Michigan. Despite their generally lower accuracy in predicting exact stream temperatures, generalized models accurately projected salmonid thermal habitat suitability in 82% of groundwater-dominated streams, including those with brook charr (80% accuracy), brown trout (89% accuracy), and rainbow trout (75% accuracy). In contrast, generalized models predicted thermal habitat suitability in runoff-dominated streams with much lower accuracy (54%). These results suggest that, amidst climate change and constraints in resource availability, generalized models are appropriate to forecast thermal conditions in groundwater-dominated streams within and outside Michigan and inform regional-level salmonid management strategies that are practical for coldwater fisheries managers, policy makers, and the public. We recommend fisheries professionals reserve resource

ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

Directory of Open Access Journals (Sweden)

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

The Stream-Catchment (StreamCat) and Lake-Catchment ...

Science.gov (United States)

Background/Question/MethodsLake and stream conditions respond to both natural and human-related landscape features. Characterizing these features within contributing areas (i.e., delineated watersheds) of streams and lakes could improve our understanding of how biological conditions vary spatially and improve the use, management, and restoration of these aquatic resources. However, the specialized geospatial techniques required to define and characterize stream and lake watersheds has limited their widespread use in both scientific and management efforts at large spatial scales. We developed the StreamCat and LakeCat Datasets to model, predict, and map the probable biological conditions of streams and lakes across the conterminous US (CONUS). Both StreamCat and LakeCat contain watershed-level characterizations of several hundred natural (e.g., soils, geology, climate, and land cover) and anthropogenic (e.g., urbanization, agriculture, mining, and forest management) landscape features for ca. 2.6 million stream segments and 376,000 lakes across the CONUS, respectively. These datasets can be paired with field samples to provide independent variables for modeling and other analyses. We paired 1,380 stream and 1,073 lake samples from the USEPAs National Aquatic Resource Surveys with StreamCat and LakeCat and used random forest (RF) to model and then map an invertebrate condition index and chlorophyll a concentration, respectively. Results/ConclusionsThe invertebrate

Social Sensor Analytics: Making Sense of Network Models in Social Media

Energy Technology Data Exchange (ETDEWEB)

Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.; Sego, Landon H.; Corley, Courtney D.

2015-07-27

Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013 and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.

Adaptive Media Streaming to Mobile Devices: Challenges, Enhancements, and Recommendations

OpenAIRE

Evensen, Kristian; Kupka, Tomas; Riiser, Haakon; Ni, Pengpeng; Eg, Ragnhild; Griwodz, Carsten; Halvorsen, Pål

2014-01-01

Video streaming is predicted to become the dominating traffic in mobile broadband networks. At the same time, adaptive HTTP streaming is developing into the preferred way of streaming media over the Internet. In this paper, we evaluate how different components of a streaming system can be optimized when serving content to mobile devices in particular. We first analyze the media traffic from a Norwegian network and media provider. Based on our findings, we outline benefits and chal...

Comparison of Three Model Concepts for Streaming Potential in Unsaturated Porous Media

Science.gov (United States)

Huisman, J. A.; Satenahalli, P.; Zimmermann, E.; Vereecken, H.

2017-12-01

Streaming potential is the electric potential generated by fluid flow in a charged porous medium. Although streaming potential in saturated conditions is well understood, there still is considerable debate about the adequate modelling of streaming potential signals in unsaturated soil because different concepts are available to estimate the effective excess charge in unsaturated conditions. In particular, some studies have relied on the volumetric excess charge, whereas others proposed to use the flux-averaged excess charge derived from the water retention or relative permeability function. The aim of this study is to compare measured and modelled streaming potential signals for two different flow experiments with sand. The first experiment is a primary gravity drainage of a long column equipped with non-polarizing electrodes and tensiometers, as presented in several previous studies. Expected differences between the three concepts for the effective excess charge are only moderate for this set-up. The second experiment is a primary drainage of a short soil column equipped with non-polarizing electrodes and tensiometers using applied pressure, where differences between the three concepts are expected to be larger. A comparison of the experimental results with a coupled model of streaming potential for 1D flow problems will provide insights in the ability of the three model concepts for effective excess charge to describe observed streaming potentials.

A novel WDM passive optical network architecture supporting two independent multicast data streams

Science.gov (United States)

Qiu, Yang; Chan, Chun-Kit

2012-01-01

We propose a novel scheme to perform optical multicast overlay of two independent multicast data streams on a wavelength-division-multiplexed (WDM) passive optical network. By controlling a sinusoidal clock signal and shifting the wavelength at the optical line terminal (OLT), the delivery of the two multicast data, being carried by the generated optical tones, can be independently and flexibly controlled. Simultaneous transmission of 10-Gb/s unicast downstream and upstream data as well as two independent 10-Gb/s multicast data was successfully demonstrated.

Flow-Through Stream Modeling with MODFLOW and MT3D: Certainties and Limitations.

Science.gov (United States)

Ben Simon, Rose; Bernard, Stéphane; Meurville, Charles; Rebour, Vincent

2015-01-01

This paper aims to assess MODFLOW and MT3D capabilities for simulating the spread of contaminants from a river exhibiting an unusual relationship with an alluvial aquifer, with the groundwater head higher than the river head on one side and lower on the other (flow-through stream). A series of simulation tests is conducted using a simple hypothetical model so as to characterize and quantify these limitations. Simulation results show that the expected contaminant spread could be achieved with a specific configuration composed of two sets of parameters: (1) modeled object parameters (hydraulic groundwater gradient, hydraulic conductivity values of aquifer and streambed), and (2) modeling parameters (vertical discretization of aquifer, horizontal refinement of stream modeled with River [RIV] package). The influence of these various parameters on simulation results is investigated, and potential complications and errors are identified. Contaminant spread from stream to aquifer is not always reproduced by MT3D due to the RIV package's inability to simulate lateral exchange fluxes between stream and aquifer. This paper identifies the need for a MODFLOW streamflow package allowing lateral stream-aquifer interactions and streamflow routine calculations. Such developments could be of particular interest for modeling contaminated flow-through streams. © 2015, National Ground Water Association.

A regional neural network model for predicting mean daily river water temperature

Science.gov (United States)

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate

A spatially referenced regression model (SPARROW) for suspended sediment in streams of the conterminous U.S.

Science.gov (United States)

Schwarz, Gregory E.; Smith, Richard A.; Alexander, Richard B.; Gray, John R.

2001-01-01

identified as potential sediment sinks. Other, non-anthropogenic sources and sinks are identified using soil information from the State Soil Survey Geographic (STATSGO) data base (Schwarz and Alexander, 1995) and spatial coverages representing surficial rock type and vegetative cover. The SPARROW model empirically relates these diverse spatial datasets to estimates of long-term, mean annual sediment flux computed from concentration and flow measurements collected over the period 1985-95 from more than 400 monitoring stations maintained by the National Stream Quality Accounting Network (Alexander and others, 1998), the National Water Quality Assessment Program, and U.S. Geological Survey District offices (Turcios and Gray, in press). The calibrated model is used to estimate sediment flux for over 60,000 stream segments included in the River Reach File 1 (RF1) stream network (Alexander and others, 1999).SPARROW uses statistical methods to calibrate a simple, structural model of riverine water quality, one that imposes mass balance in accounting for changes in contaminant flux. As applied here, the mass-balance approach facilitates the interpretation of model results in terms of physical processes affecting sediment transport, and makes possible the estimation of various rates of sediment generation and loss associated with stream channels and features of the landscape. The statistical approach provides a basis for assessing the error of these inferred rates and of the error in extrapolated estimates of sediment flux made for streams in the RF1 network.An important implication of the holistic modeling approach adopted in this analysis is that estimates of sediment production and loss are based on, and therefore consistent with, measurements of in-stream flux. Other ancillary information, such as direct measurements of long-term sediment storage and release from reservoirs (Steffen, 1996), is incorporated into the analysis by specifying additional equations explaining these

Landscape attributes and life history variability shape genetic structure of trout populations in a stream network

Science.gov (United States)

Neville, H.M.; Dunham, J.B.; Peacock, M.M.

2006-01-01

Spatial and temporal landscape patterns have long been recognized to influence biological processes, but these processes often operate at scales that are difficult to study by conventional means. Inferences from genetic markers can overcome some of these limitations. We used a landscape genetics approach to test hypotheses concerning landscape processes influencing the demography of Lahontan cutthroat trout in a complex stream network in the Great Basin desert of the western US. Predictions were tested with population- and individual-based analyses of microsatellite DNA variation, reflecting patterns of dispersal, population stability, and local effective population sizes. Complementary genetic inferences suggested samples from migratory corridors housed a mixture of fish from tributaries, as predicted based on assumed migratory life histories in those habitats. Also as predicted, populations presumed to have greater proportions of migratory fish or from physically connected, large, or high quality habitats had higher genetic variability and reduced genetic differentiation from other populations. Populations thought to contain largely non-migratory individuals generally showed the opposite pattern, suggesting behavioral isolation. Estimated effective sizes were small, and we identified significant and severe genetic bottlenecks in several populations that were isolated, recently founded, or that inhabit streams that desiccate frequently. Overall, this work suggested that Lahontan cutthroat trout populations in stream networks are affected by a combination of landscape and metapopulation processes. Results also demonstrated that genetic patterns can reveal unexpected processes, even within a system that is well studied from a conventional ecological perspective. ?? Springer 2006.

Scaling measurements of metabolism in stream ecosystems: challenges and approaches to estimating reaeration

Science.gov (United States)

Bowden, W. B.; Parker, S.; Song, C.

2016-12-01

Stream ecologists have used various formulations of an oxygen budget approach as a surrogate to measure "whole-stream metabolism" (WSM) of carbon in rivers and streams. Improvements in sensor technologies that provide reliable, high-frequency measurements of dissolved oxygen concentrations in adverse field conditions has made it much easier to acquire the basic data needed to estimate WSM in remote locations over long periods (weeks to months). However, accurate estimates of WSM require reliable measurements or estimates of the reaeration coefficient (k). Small errors in estimates of k can lead to large errors in estimates of gross ecosystem production and ecosystem respiration and so the magnitude of the biological flux of CO2 to or from streams. This is an especially challenging problem in unproductive, oligotrophic streams. Unfortunately, current methods to measure reaeration directly (gas evasion) are expensive, labor-intensive, and time-consuming. As a consequence, there is a substantial mismatch between the time steps at which we can measure reaeration versus most of the other variables required to calculate WSM. As a part of the NSF Arctic Long-Term Ecological Research Project we have refined methods to measure WSM in Arctic streams and found a good relationship between measured k values and those calculated by the Energy Dissipation Model (EDM). Other researchers have also noted that this equation works well for both low- and high-order streams. The EDM is dependent on stream slope (relatively constant) and velocity (which is related to discharge or stage). These variables are easy to measure and can be used to estimate k a high frequency (minutes) over large areas (river networks). As a key part of the NSF MacroSystems Biology SCALER project we calculated WSM for multiple reaches in nested stream networks in six biomes across the United States and Australia. We calculated k by EDM and fitted k via a Bayesian model for WSM. The relationships between

Stream Width Dynamics in a Small Headwater Catchment

Science.gov (United States)

Barefoot, E. A.; Pavelsky, T.; Allen, G. H.; Zimmer, M. A.; McGlynn, B. L.

2016-12-01

Changing streamflow conditions cause small, ephemeral and intermittent stream networks to expand and contract, while simultaneously driving widening and narrowing of streams. The resulting dynamic surface area of ephemeral streams impacts critical hydrological and biogeochemical processes, including air-water gas exchange, solute transport, and sediment transport. Despite the importance of these dynamics, to our knowledge there exists no complete study of how stream widths vary throughout an entire catchment in response to changing streamflow conditions. Here we present the first characterization of how variable hydrologic conditions impact the distribution of stream widths in a 48 ha headwater catchment in the Stony Creek Research Watershed, NC, USA. We surveyed stream widths longitudinally every 5 m on 12 occasions over a range of stream discharge from 7 L/s to 128 L/s at the catchment outlet. We hypothesize that the shape and location of the stream width distribution are driven by the action of two interrelated mechanisms, network extension and at-a-station widening, both of which increase with discharge. We observe that during very low flow conditions, network extension more significantly influences distribution location, and during high flow conditions stream widening is the dominant driver. During moderate flows, we observe an approximately 1 cm rightward shift in the distribution peak with every additional 10 L/s of increased discharge, which we attribute to a greater impact of at-a-station widening on distribution location. Aside from this small shift, the qualitative location and shape of the stream width distribution are largely invariant with changing streamflow. We suggest that the basic characteristics of stream width distributions constitute an equilibrium between the two described mechanisms across variable hydrologic conditions.

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin

Energy Technology Data Exchange (ETDEWEB)

Selbig, William R., E-mail: wrselbig@usgs.gov

2015-07-15

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2 °C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery. - Highlights: • A stream temperature model was calibrated for three streams in northern Wisconsin. • The effect of climate change on stream temperature was simulated in each stream. • Annual average stream temperature was projected to rise from 1 to 3 °C by 2100. • Forecasts of stream temperature exceeded optimal ranges for brook trout.

Simulating temporal variations of nitrogen losses in river networks with a dynamic transport model unravels the coupled effects of hydrological and biogeochemical processes

Energy Technology Data Exchange (ETDEWEB)

Mulholland, Patrick J [ORNL; Alexander, Richard [U.S. Geological Survey; Bohlke, John [U.S. Geological Survey; Boyer, Elizabeth [Pennsylvania State University; Harvey, Judson [U.S. Geological Survey; Seitzinger, Sybil [Rutgers University; Tobias, Craig [University of North Carolina, Wilmington; Tonitto, Christina [Cornell University; Wollheim, Wilfred [University of New Hampshire

2009-01-01

The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly

MATIN: a random network coding based framework for high quality peer-to-peer live video streaming.

Science.gov (United States)

Barekatain, Behrang; Khezrimotlagh, Dariush; Aizaini Maarof, Mohd; Ghaeini, Hamid Reza; Salleh, Shaharuddin; Quintana, Alfonso Ariza; Akbari, Behzad; Cabrera, Alicia Triviño

2013-01-01

In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.

Modeling the citation network by network cosmology.

Science.gov (United States)

Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

2015-01-01

Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

Data streams: algorithms and applications

National Research Council Canada - National Science Library

Muthukrishnan, S

2005-01-01

... massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges. This article is an overview and survey of data stream algorithmics and is an updated version of [175]. S. Muthukrishnan Rutgers University, New Brunswick, NJ, USA, muthu@cs...

Can Low-Resolution Airborne Laser Scanning Data Be Used to Model Stream Rating Curves?

Directory of Open Access Journals (Sweden)

Steve W. Lyon

2015-03-01

Full Text Available This pilot study explores the potential of using low-resolution (0.2 points/m2 airborne laser scanning (ALS-derived elevation data to model stream rating curves. Rating curves, which allow the functional translation of stream water depth into discharge, making them integral to water resource monitoring efforts, were modeled using a physics-based approach that captures basic geometric measurements to establish flow resistance due to implicit channel roughness. We tested synthetically thinned high-resolution (more than 2 points/m2 ALS data as a proxy for low-resolution data at a point density equivalent to that obtained within most national-scale ALS strategies. Our results show that the errors incurred due to the effect of low-resolution versus high-resolution ALS data were less than those due to flow measurement and empirical rating curve fitting uncertainties. As such, although there likely are scale and technical limitations to consider, it is theoretically possible to generate rating curves in a river network from ALS data of the resolution anticipated within national-scale ALS schemes (at least for rivers with relatively simple geometries. This is promising, since generating rating curves from ALS scans would greatly enhance our ability to monitor streamflow by simplifying the overall effort required.

Can low-resolution airborne laser scanning data be used to model stream rating curves?

Science.gov (United States)

Lyon, Steve; Nathanson, Marcus; Lam, Norris; Dahlke, Helen; Rutzinger, Martin; Kean, Jason W.; Laudon, Hjalmar

2015-01-01

This pilot study explores the potential of using low-resolution (0.2 points/m2) airborne laser scanning (ALS)-derived elevation data to model stream rating curves. Rating curves, which allow the functional translation of stream water depth into discharge, making them integral to water resource monitoring efforts, were modeled using a physics-based approach that captures basic geometric measurements to establish flow resistance due to implicit channel roughness. We tested synthetically thinned high-resolution (more than 2 points/m2) ALS data as a proxy for low-resolution data at a point density equivalent to that obtained within most national-scale ALS strategies. Our results show that the errors incurred due to the effect of low-resolution versus high-resolution ALS data were less than those due to flow measurement and empirical rating curve fitting uncertainties. As such, although there likely are scale and technical limitations to consider, it is theoretically possible to generate rating curves in a river network from ALS data of the resolution anticipated within national-scale ALS schemes (at least for rivers with relatively simple geometries). This is promising, since generating rating curves from ALS scans would greatly enhance our ability to monitor streamflow by simplifying the overall effort required.

A Simple FSPN Model of P2P Live Video Streaming System

OpenAIRE

Kotevski, Zoran; Mitrevski, Pece

2011-01-01

Peer to Peer (P2P) live streaming is relatively new paradigm that aims at streaming live video to large number of clients at low cost. Many such applications already exist in the market, but, prior to creating such system it is necessary to analyze its performance via representative model that can provide good insight in the system’s behavior. Modeling and performance analysis of P2P live video streaming systems is challenging task which requires addressing many properties and issues of P2P s...

Progressive Conversion from B-rep to BSP for Streaming Geometric Modeling.

Science.gov (United States)

Bajaj, Chandrajit; Paoluzzi, Alberto; Scorzelli, Giorgio

2006-01-01

We introduce a novel progressive approach to generate a Binary Space Partition (BSP) tree and a convex cell decomposition for any input triangles boundary representation (B-rep), by utilizing a fast calculation of the surface inertia. We also generate a solid model at progressive levels of detail. This approach relies on a variation of standard BSP tree generation, allowing for labeling cells as in, out and fuzzy, and which permits a comprehensive representation of a solid as the Hasse diagram of a cell complex. Our new algorithm is embedded in a streaming computational framework, using four types of dataflow processes that continuously produce, transform, combine or consume subsets of cells depending on their number or input/output stream. A varied collection of geometric modeling techniques are integrated in this streaming framework, including polygonal, spline, solid and heterogeneous modeling with boundary and decompositive representations, Boolean set operations, Cartesian products and adaptive refinement. The real-time B-rep to BSP streaming results we report in this paper are a large step forward in the ultimate unification of rapid conceptual and detailed shape design methodologies.

A CONTEXT AWARE BASED PRE-HANDOFF SUPPORT APPROACH TO PROVIDE OPTIMAL QOS FOR STREAMING APPLICATIONS OVER VEHICULAR AD HOC NETWORKS – HOSA

Directory of Open Access Journals (Sweden)

K. RAMESH BABU

2015-06-01

Full Text Available Large variations in network Quality of Service (QoS such as bandwidth, latency, jitter, and reliability may occur during media transfer over vehicular ad hoc networks (VANET. Usage of VANET over mobile and wireless computing applications experience “bursty” QoS behavior during the execution over distributed network scenarios. Applications such as streaming media services need to adapt their functionalities to any change in network status. Moreover, an enhanced software platform is necessary to provide adaptive network management services to upper software components. HOSA, a handoff service broker based architecture for QoS adaptation over VANET supports in providing awareness. HOSA is structured as a middleware platform both to provide QoS awareness to streaming applications as well to manage dynamic ad hoc network resources with support over handoff in an adaptive fashion. HOSA is well analyzed over routing schemes such as TIBSCRPH, SIP and ABSRP where performance of HOSA was measured using throughput, traffic intensity and end to end delay. HOSA has been analyzed using JXTA development toolkit over C++ implemented classes to demonstrate its performance over varying node mobility established using vehicular mobility based conference application.

Maximizing Resource Utilization in Video Streaming Systems

Science.gov (United States)

Alsmirat, Mohammad Abdullah

2013-01-01

Video streaming has recently grown dramatically in popularity over the Internet, Cable TV, and wire-less networks. Because of the resource demanding nature of video streaming applications, maximizing resource utilization in any video streaming system is a key factor to increase the scalability and decrease the cost of the system. Resources to…

Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling

Science.gov (United States)

Brakebill, J.W.; Wolock, D.M.; Terziotti, S.E.

2011-01-01

Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

The role of the hyporheic zone across stream networks

Science.gov (United States)

Steven M. Wondzell

2011-01-01

Many hyporheic papers state that the hyporheic zone is a critical component of stream ecosystems, and many of these papers focus on the biogeochemical effects of the hyporheic zone on stream solute loads. However, efforts to show such relationships have proven elusive, prompting several questions: Are the effects of the hyporheic zone on stream ecosystems so highly...

Evaluation of neutron streaming in fast breeder reactor fuel assembly by double heterogeneous modelling

International Nuclear Information System (INIS)

Unesaki, Hironobu; Takeda, Toshikazu

1988-01-01

Neutron streaming in a fast breeder reactor fuel assembly caused by the double heterogeneity structure is estimated by double heterogeneous modelling. The conventional pin cell model, a two-region subassembly model and the exact pin cluster model are used to take into account the streaming effect caused by the pin cell structure and the surrounding wrapper tube structure. The heterogeneity of wrapper tube and its surrounding sodium is explicitly considered. The streaming effect is evaluated based on Benoist's diffusion coefficient. The total streaming effect caused by the double heterogeneity structure of a fuel subassembly is found to be -0.2 % dk/kk' for k eff , which is almost twice that obtained from the conventional pin cell model of -0.1 % dk/kk'. (author)

Reducing equifinality using isotopes in a process-based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams

Science.gov (United States)

Ford, William I.; Fox, James F.; Pollock, Erik

2017-08-01

The fate of bioavailable nitrogen species transported through agricultural landscapes remains highly uncertain given complexities of measuring fluxes impacting the fluvial N cycle. We present and test a new numerical model named Technology for Removable Annual Nitrogen in Streams For Ecosystem Restoration (TRANSFER), which aims to reduce model uncertainty due to erroneous parameterization, i.e., equifinality, in stream nitrogen cycle assessment and quantify the significance of transient and permanent removal pathways. TRANSFER couples nitrogen elemental and stable isotope mass-balance equations with existing hydrologic, hydraulic, sediment transport, algal biomass, and sediment organic matter mass-balance subroutines and a robust GLUE-like uncertainty analysis. We test the model in an agriculturally impacted, third-order stream reach located in the Bluegrass Region of Central Kentucky. Results of the multiobjective model evaluation for the model application highlight the ability of sediment nitrogen fingerprints including elemental concentrations and stable N isotope signatures to reduce equifinality of the stream N model. Advancements in the numerical simulations allow for illumination of the significance of algal sloughing fluxes for the first time in relation to denitrification. Broadly, model estimates suggest that denitrification is slightly greater than algal N sloughing (10.7% and 6.3% of dissolved N load on average), highlighting the potential for overestimation of denitrification by 37%. We highlight the significance of the transient N pool given the potential for the N store to be regenerated to the water column in downstream reaches, leading to harmful and nuisance algal bloom development.

Modelling computer networks

International Nuclear Information System (INIS)

Max, G

2011-01-01

Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

Science.gov (United States)

Kashuba, Roxolana; McMahon, Gerard; Cuffney, Thomas F.; Qian, Song; Reckhow, Kenneth; Gerritsen, Jeroen; Davies, Susan

2012-01-01

Urban development alters important physical, chemical, and biological processes that define urban stream ecosystems. An approach was developed for quantifying the effects of these processes on aquatic biota, and then linking those effects to endpoints that can be used for environmental management. These complex, interacting systems are challenging to model from a scientific standpoint. A desirable model clearly shows the system, simulates the interactions, and ultimately predicts results of management actions. Traditional regression techniques that calculate empirical relations between pairs of environmental factors do not capture the interconnected web of multiple stressors, but urban development effects are not yet understood at the detailed scales required to make mechanistic modeling approaches feasible. Therefore, in contrast to a fully deterministic or fully statistical modeling approach, a Bayesian network model provides a hybrid approach that can be used to represent known general associations between variables while acknowledging uncertainty in predicted outcomes. It does so by quantifying an expert-elicited network of probabilistic relations between variables. Advantages of this modeling approach include (1) flexibility in accommodating many model specifications and information types; (2) efficiency in storing and manipulating complex information, and to parameterize; and (3) transparency in describing the relations using nodes and arrows and in describing uncertainties with discrete probability distributions for each variable.

SST: Single-Stream Temporal Action Proposals

KAUST Repository

Buch, Shyamal; Escorcia, Victor; Shen, Chuanqi; Ghanem, Bernard; Niebles, Juan Carlos

2017-01-01

Our paper presents a new approach for temporal detection of human actions in long, untrimmed video sequences. We introduce Single-Stream Temporal Action Proposals (SST), a new effective and efficient deep architecture for the generation of temporal action proposals. Our network can run continuously in a single stream over very long input video sequences, without the need to divide input into short overlapping clips or temporal windows for batch processing. We demonstrate empirically that our model outperforms the state-of-the-art on the task of temporal action proposal generation, while achieving some of the fastest processing speeds in the literature. Finally, we demonstrate that using SST proposals in conjunction with existing action classifiers results in improved state-of-the-art temporal action detection performance.

SST: Single-Stream Temporal Action Proposals

KAUST Repository

Buch, Shyamal

2017-11-09

Our paper presents a new approach for temporal detection of human actions in long, untrimmed video sequences. We introduce Single-Stream Temporal Action Proposals (SST), a new effective and efficient deep architecture for the generation of temporal action proposals. Our network can run continuously in a single stream over very long input video sequences, without the need to divide input into short overlapping clips or temporal windows for batch processing. We demonstrate empirically that our model outperforms the state-of-the-art on the task of temporal action proposal generation, while achieving some of the fastest processing speeds in the literature. Finally, we demonstrate that using SST proposals in conjunction with existing action classifiers results in improved state-of-the-art temporal action detection performance.

A spatially referenced regression model (SPARROW) for suspended sediment in streams of the Conterminous U.S.

Science.gov (United States)

Schwarz, Gregory E.; Smith, Richard A.; Alexander, Richard B.; Gray, John R.

2001-01-01

Corps of Engin eers, 1996) are identified as pot ential sediment sinks. Other, non-anthropogenic sources and sinks are identified using soil in formation from the State Soil Survey Geographic (STATSGO) data base (Schwarz and Alexander, 1995) and spatial coverages representing surficial rock t ype and vegetative cover. The SPA RROW model empirically relates these diverse spatial datasets to estimates of long-term, mean annual sediment flux computed from concentration and flow measurements co llected over the period 1985 -95 from more than 400 monitoring stations maintained by the Na tional Stream Quality Accounting Network (Alexander and others, 1998), the National Wa ter Quality Assessment Program, and U.S. Geological Survey District offices (Turcios and Gray, in press). Th e calibrated model is used to estimate sediment flux for over 60,000 stream segments included in the River Reach File 1 (RF1) stream network (Alexander and others, 1999). SPARROW uses statis tical methods to calibrate a simple, structural model of riverine water quality, one that imposes mass ba lance in accounting for changes in contaminant flux. As applied here, the mass-balance approach facilitates the interpretation of model results in terms of physical processes affecting sediment transport, and makes possible the estimation of various rates of sediment generation and loss associated with stream channels and features of the landscape. The statistical approach provides a basi s for assessing the error of these inferred rates and of the error in extrapolated estimates of sediment flux made for streams in the RF1 network. An important implication of the holistic modeling approach adopted in this analysis is that estimates of sediment production and loss ar e based on, and therefore consistent with, measurements of in-stream flux. Other ancillary information, such as direct measurements of long-term sediment storage and release from rese rvoirs (Steffen, 1996), is incorporated into the analysis by

A Multivariant Stream Analysis Approach to Detect and Mitigate DDoS Attacks in Vehicular Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Raenu Kolandaisamy

2018-01-01

Full Text Available Vehicular Ad Hoc Networks (VANETs are rapidly gaining attention due to the diversity of services that they can potentially offer. However, VANET communication is vulnerable to numerous security threats such as Distributed Denial of Service (DDoS attacks. Dealing with these attacks in VANET is a challenging problem. Most of the existing DDoS detection techniques suffer from poor accuracy and high computational overhead. To cope with these problems, we present a novel Multivariant Stream Analysis (MVSA approach. The proposed MVSA approach maintains the multiple stages for detection DDoS attack in network. The Multivariant Stream Analysis gives unique result based on the Vehicle-to-Vehicle communication through Road Side Unit. The approach observes the traffic in different situations and time frames and maintains different rules for various traffic classes in various time windows. The performance of the MVSA is evaluated using an NS2 simulator. Simulation results demonstrate the effectiveness and efficiency of the MVSA regarding detection accuracy and reducing the impact on VANET communication.

Drug perfusion enhancement in tissue model by steady streaming induced by oscillating microbubbles.

Science.gov (United States)

Oh, Jin Sun; Kwon, Yong Seok; Lee, Kyung Ho; Jeong, Woowon; Chung, Sang Kug; Rhee, Kyehan

2014-01-01

Drug delivery into neurological tissue is challenging because of the low tissue permeability. Ultrasound incorporating microbubbles has been applied to enhance drug delivery into these tissues, but the effects of a streaming flow by microbubble oscillation on drug perfusion have not been elucidated. In order to clarify the physical effects of steady streaming on drug delivery, an experimental study on dye perfusion into a tissue model was performed using microbubbles excited by acoustic waves. The surface concentration and penetration length of the drug were increased by 12% and 13%, respectively, with streaming flow. The mass of dye perfused into a tissue phantom for 30s was increased by about 20% in the phantom with oscillating bubbles. A computational model that considers fluid structure interaction for streaming flow fields induced by oscillating bubbles was developed, and mass transfer of the drug into the porous tissue model was analyzed. The computed flow fields agreed with the theoretical solutions, and the dye concentration distribution in the tissue agreed well with the experimental data. The computational results showed that steady streaming with a streaming velocity of a few millimeters per second promotes mass transfer into a tissue. © 2013 Published by Elsevier Ltd.

MATIN: a random network coding based framework for high quality peer-to-peer live video streaming.

Directory of Open Access Journals (Sweden)

Behrang Barekatain

Full Text Available In recent years, Random Network Coding (RNC has emerged as a promising solution for efficient Peer-to-Peer (P2P video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.

Modeling nutrient in-stream processes at the watershed scale using Nutrient Spiralling metrics

Science.gov (United States)

Marcé, R.; Armengol, J.

2009-07-01

One of the fundamental problems of using large-scale biogeochemical models is the uncertainty involved in aggregating the components of fine-scale deterministic models in watershed applications, and in extrapolating the results of field-scale measurements to larger spatial scales. Although spatial or temporal lumping may reduce the problem, information obtained during fine-scale research may not apply to lumped categories. Thus, the use of knowledge gained through fine-scale studies to predict coarse-scale phenomena is not straightforward. In this study, we used the nutrient uptake metrics defined in the Nutrient Spiralling concept to formulate the equations governing total phosphorus in-stream fate in a deterministic, watershed-scale biogeochemical model. Once the model was calibrated, fitted phosphorus retention metrics where put in context of global patterns of phosphorus retention variability. For this purpose, we calculated power regressions between phosphorus retention metrics, streamflow, and phosphorus concentration in water using published data from 66 streams worldwide, including both pristine and nutrient enriched streams. Performance of the calibrated model confirmed that the Nutrient Spiralling formulation is a convenient simplification of the biogeochemical transformations involved in total phosphorus in-stream fate. Thus, this approach may be helpful even for customary deterministic applications working at short time steps. The calibrated phosphorus retention metrics were comparable to field estimates from the study watershed, and showed high coherence with global patterns of retention metrics from streams of the world. In this sense, the fitted phosphorus retention metrics were similar to field values measured in other nutrient enriched streams. Analysis of the bibliographical data supports the view that nutrient enriched streams have lower phosphorus retention efficiency than pristine streams, and that this efficiency loss is maintained in a wide

Spatial patterns of some trace elements in four Swedish stream networks

Directory of Open Access Journals (Sweden)

J. Temnerud

2013-03-01

Full Text Available Four river basins in southern Sweden, with catchment sizes from 0.3 to 127 km2 (median 1.9, were sampled in October~2007. The 243 samples were analysed for 26 trace elements (Ag, As, Au, Ba, Be, Bi, Cd, Co, Cr, Cu, Ga, Ge, In, La, Li, Mo, Ni, Pb, Sb, Se, Sn, Tl, Ti, U, V and Zn to identify spatial patterns within drainage networks. The range and median of each element were defined for different stream orders, and relationships to catchment characteristics, including deposition history, were explored. The sampling design made it possible to compare the differences along 40 stream reaches, above and below 53 stream junctions with 107 tributaries and between the 77 inlets and outlets of 36 lakes. The largest concentration differences (at reaches, junctions and lakes were observed for lakes, with outlets usually having lower concentration compared to the inlets for As, Ba, Be, Bi, Cd, Co, Cr, Ga, Ge, Ni, Pb, Sn, Ti, Tl, U, V and Zn. Significantly lower concentrations were observed for Cd and Co when comparing headwaters with downstream sites in each catchment. Common factor analysis (FA revealed that As, Bi, Cr, Ga, Ge, Tl and V co-vary positively with Al, Fe and total organic carbon (TOC and negatively with La, Li and pH. The strong removal of a large number of trace elements when passing through lakes is evident though in the FA, where lake surface coverage plots opposite to many of those elements. Forest volume does not respond in a similar systematic fashion and, surprisingly, the amount of wetland does not relate strongly to either Fe or TOC at any of the rivers. A better understanding of the quantitative removal of organic carbon and iron will aid in understanding trace element fluxes from landscapes rich in organic matter and iron.

Using spatial-stream-network models and long-term data to understand and predict dynamics of faecal contamination in a mixed land-use catchment.

Science.gov (United States)

Neill, Aaron James; Tetzlaff, Doerthe; Strachan, Norval James Colin; Hough, Rupert Lloyd; Avery, Lisa Marie; Watson, Helen; Soulsby, Chris

2018-01-15

An 11year dataset of concentrations of E. coli at 10 spatially-distributed sites in a mixed land-use catchment in NE Scotland (52km 2 ) revealed that concentrations were not clearly associated with flow or season. The lack of a clear flow-concentration relationship may have been due to greater water fluxes from less-contaminated headwaters during high flows diluting downstream concentrations, the importance of persistent point sources of E. coli both anthropogenic and agricultural, and possibly the temporal resolution of the dataset. Point sources and year-round grazing of livestock probably obscured clear seasonality in concentrations. Multiple linear regression models identified potential for contamination by anthropogenic point sources as a significant predictor of long-term spatial patterns of low, average and high concentrations of E. coli. Neither arable nor pasture land was significant, even when accounting for hydrological connectivity with a topographic-index method. However, this may have reflected coarse-scale land-cover data inadequately representing "point sources" of agricultural contamination (e.g. direct defecation of livestock into the stream) and temporal changes in availability of E. coli from diffuse sources. Spatial-stream-network models (SSNMs) were applied in a novel context, and had value in making more robust catchment-scale predictions of concentrations of E. coli with estimates of uncertainty, and in enabling identification of potential "hot spots" of faecal contamination. Successfully managing faecal contamination of surface waters is vital for safeguarding public health. Our finding that concentrations of E. coli could not clearly be associated with flow or season may suggest that management strategies should not necessarily target only high flow events or summer when faecal contamination risk is often assumed to be greatest. Furthermore, we identified SSNMs as valuable tools for identifying possible "hot spots" of contamination which

A method to assess longitudinal riverine connectivity in tropical streams dominated by migratory biota

Science.gov (United States)

Crook, K.E.; Pringle, C.M.; Freeman, Mary C.

2009-01-01

1. One way in which dams affect ecosystem function is by altering the distribution and abundance of aquatic species. 2. Previous studies indicate that migratory shrimps have significant effects on ecosystem processes in Puerto Rican streams, but are vulnerable to impediments to upstream or downstream passage, such as dams and associated water intakes where stream water is withdrawn for human water supplies. Ecological effects of dams and water withdrawals from streams depend on spatial context and temporal variability of flow in relation to the amount of water withdrawn. 3. This paper presents a conceptual model for estimating the probability that an individual shrimp is able to migrate from a stream's headwaters to the estuary as a larva, and then return to the headwaters as a juvenile, given a set of dams and water withdrawals in the stream network. The model is applied to flow and withdrawal data for a set of dams and water withdrawals in the Caribbean National Forest (CNF) in Puerto Rico. 4. The index of longitudinal riverine connectivity (ILRC), is used to classify 17 water intakes in streams draining the CNF as having low, moderate, or high connectivity in terms of shrimp migration in both directions. An in-depth comparison of two streams showed that the stream characterized by higher water withdrawal had low connectivity, even during wet periods. Severity of effects is illustrated by a drought year, where the most downstream intake caused 100% larval shrimp mortality 78% of the year. 5. The ranking system provided by the index can be used as a tool for conservation ecologists and water resource managers to evaluate the relative vulnerability of migratory biota in streams, across different scales (reach-network), to seasonally low flows and extended drought. This information can be used to help evaluate the environmental tradeoffs of future water withdrawals. ?? 2008 John Wiley & Sons, Ltd.

Network user's guide

International Nuclear Information System (INIS)

McGrady, P.W.

1994-12-01

NETWORK is a FORTRAN code used to model process flow systems in the gaseous diffusion plants at Portsmouth, Ohio and Paducah, Kentucky, operated by the United States Enrichment Corporation. It can handle a wide range of components and several different types of controllers. NETWORK can be run in either a steady-state mode or a transient mode. In the transient mode many different types of perturbations may be modeled. It is currently being used to model taking a cell off-stream in a gaseous diffusion plant. A brief description of the code is given, and process equipment models and input data are discussed

Modelling stream aquifer seepage in an alluvial aquifer: an improved loosing-stream package for MODFLOW

Science.gov (United States)

Osman, Yassin Z.; Bruen, Michael P.

2002-07-01

Seepage from a stream, which partially penetrates an unconfined alluvial aquifer, is studied for the case when the water table falls below the streambed level. Inadequacies are identified in current modelling approaches to this situation. A simple and improved method of incorporating such seepage into groundwater models is presented. This considers the effect on seepage flow of suction in the unsaturated part of the aquifer below a disconnected stream and allows for the variation of seepage with water table fluctuations. The suggested technique is incorporated into the saturated code MODFLOW and is tested by comparing its predictions with those of a widely used variably saturated model, SWMS_2D simulating water flow and solute transport in two-dimensional variably saturated media. Comparisons are made of both seepage flows and local mounding of the water table. The suggested technique compares very well with the results of variably saturated model simulations. Most currently used approaches are shown to underestimate the seepage and associated local water table mounding, sometimes substantially. The proposed method is simple, easy to implement and requires only a small amount of additional data about the aquifer hydraulic properties.

Endoplasmic-reticulum-mediated microtubule alignment governs cytoplasmic streaming.

Science.gov (United States)

Kimura, Kenji; Mamane, Alexandre; Sasaki, Tohru; Sato, Kohta; Takagi, Jun; Niwayama, Ritsuya; Hufnagel, Lars; Shimamoto, Yuta; Joanny, Jean-François; Uchida, Seiichi; Kimura, Akatsuki

2017-04-01

Cytoplasmic streaming refers to a collective movement of cytoplasm observed in many cell types. The mechanism of meiotic cytoplasmic streaming (MeiCS) in Caenorhabditis elegans zygotes is puzzling as the direction of the flow is not predefined by cell polarity and occasionally reverses. Here, we demonstrate that the endoplasmic reticulum (ER) network structure is required for the collective flow. Using a combination of RNAi, microscopy and image processing of C. elegans zygotes, we devise a theoretical model, which reproduces and predicts the emergence and reversal of the flow. We propose a positive-feedback mechanism, where a local flow generated along a microtubule is transmitted to neighbouring regions through the ER. This, in turn, aligns microtubules over a broader area to self-organize the collective flow. The proposed model could be applicable to various cytoplasmic streaming phenomena in the absence of predefined polarity. The increased mobility of cortical granules by MeiCS correlates with the efficient exocytosis of the granules to protect the zygotes from osmotic and mechanical stresses.

Knowledge discovery from data streams

CERN Document Server

Gama, Joao

2010-01-01

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams.The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks,

Multi-stream CNN: Learning representations based on human-related regions for action recognition

NARCIS (Netherlands)

Tu, Zhigang; Xie, Wei; Qin, Qianqing; Poppe, R.W.; Veltkamp, R.C.; Li, Baoxin; Yuan, Junsong

2018-01-01

The most successful video-based human action recognition methods rely on feature representations extracted using Convolutional Neural Networks (CNNs). Inspired by the two-stream network (TS-Net), we propose a multi-stream Convolutional Neural Network (CNN) architecture to recognize human actions. We

Brain Network Modelling

DEFF Research Database (Denmark)

Andersen, Kasper Winther

Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

Modeling the effects of LID practices on streams health at watershed scale

Science.gov (United States)

Shannak, S.; Jaber, F. H.

2013-12-01

Increasing impervious covers due to urbanization will lead to an increase in runoff volumes, and eventually increase flooding. Stream channels adjust by widening and eroding stream bank which would impact downstream property negatively (Chin and Gregory, 2001). Also, urban runoff drains in sediment bank areas in what's known as riparian zones and constricts stream channels (Walsh, 2009). Both physical and chemical factors associated with urbanization such as high peak flows and low water quality further stress aquatic life and contribute to overall biological condition of urban streams (Maxted et al., 1995). While LID practices have been mentioned and studied in literature for stormwater management, they have not been studied in respect to reducing potential impact on stream health. To evaluate the performance and the effectiveness of LID practices at a watershed scale, sustainable detention pond, bioretention, and permeable pavement will be modeled at watershed scale. These measures affect the storm peak flows and base flow patterns over long periods, and there is a need to characterize their effect on stream bank and bed erosion, and aquatic life. These measures will create a linkage between urban watershed development and stream conditions specifically biological health. The first phase of this study is to design and construct LID practices at the Texas A&M AgriLife Research and Extension Center-Dallas, TX to collect field data about the performance of these practices on a smaller scale. The second phase consists of simulating the performance of LID practices on a watershed scale. This simulation presents a long term model (23 years) using SWAT to evaluate the potential impacts of these practices on; potential stream bank and bed erosion, and potential impact on aquatic life in the Blunn Watershed located in Austin, TX. Sub-daily time step model simulations will be developed to simulate the effectiveness of the three LID practices with respect to reducing

A Network Model of Observation and Imitation of Speech

Science.gov (United States)

Mashal, Nira; Solodkin, Ana; Dick, Anthony Steven; Chen, E. Elinor; Small, Steven L.

2012-01-01

Much evidence has now accumulated demonstrating and quantifying the extent of shared regional brain activation for observation and execution of speech. However, the nature of the actual networks that implement these functions, i.e., both the brain regions and the connections among them, and the similarities and differences across these networks has not been elucidated. The current study aims to characterize formally a network for observation and imitation of syllables in the healthy adult brain and to compare their structure and effective connectivity. Eleven healthy participants observed or imitated audiovisual syllables spoken by a human actor. We constructed four structural equation models to characterize the networks for observation and imitation in each of the two hemispheres. Our results show that the network models for observation and imitation comprise the same essential structure but differ in important ways from each other (in both hemispheres) based on connectivity. In particular, our results show that the connections from posterior superior temporal gyrus and sulcus to ventral premotor, ventral premotor to dorsal premotor, and dorsal premotor to primary motor cortex in the left hemisphere are stronger during imitation than during observation. The first two connections are implicated in a putative dorsal stream of speech perception, thought to involve translating auditory speech signals into motor representations. Thus, the current results suggest that flow of information during imitation, starting at the posterior superior temporal cortex and ending in the motor cortex, enhances input to the motor cortex in the service of speech execution. PMID:22470360

Pollutant Dispersion Modeling in Natural Streams Using the Transmission Line Matrix Method

Directory of Open Access Journals (Sweden)

Safia Meddah

2015-09-01

Full Text Available Numerical modeling has become an indispensable tool for solving various physical problems. In this context, we present a model of pollutant dispersion in natural streams for the far field case where dispersion is considered longitudinal and one-dimensional in the flow direction. The Transmission Line Matrix (TLM, which has earned a reputation as powerful and efficient numerical method, is used. The presented one-dimensional TLM model requires a minimum input data and provides a significant gain in computing time. To validate our model, the results are compared with observations and experimental data from the river Severn (UK. The results show a good agreement with experimental data. The model can be used to predict the spatiotemporal evolution of a pollutant in natural streams for effective and rapid decision-making in a case of emergency, such as accidental discharges in a stream with a dynamic similar to that of the river Severn (UK.

Verification of high-speed solar wind stream forecasts using operational solar wind models

DEFF Research Database (Denmark)

Reiss, Martin A.; Temmer, Manuela; Veronig, Astrid M.

2016-01-01

and the background solar wind conditions. We found that both solar wind models are capable of predicting the large-scale features of the observed solar wind speed (root-mean-square error, RMSE ≈100 km/s) but tend to either overestimate (ESWF) or underestimate (WSA) the number of high-speed solar wind streams (threat......High-speed solar wind streams emanating from coronal holes are frequently impinging on the Earth's magnetosphere causing recurrent, medium-level geomagnetic storm activity. Modeling high-speed solar wind streams is thus an essential element of successful space weather forecasting. Here we evaluate...... high-speed stream forecasts made by the empirical solar wind forecast (ESWF) and the semiempirical Wang-Sheeley-Arge (WSA) model based on the in situ plasma measurements from the Advanced Composition Explorer (ACE) spacecraft for the years 2011 to 2014. While the ESWF makes use of an empirical relation...

Grid refinement model in lattice Boltzmann method for stream function-vorticity formulations

Energy Technology Data Exchange (ETDEWEB)

Shin, Myung Seob [Dept. of Mechanical Engineering, Dongyang Mirae University, Seoul (Korea, Republic of)

2015-03-15

In this study, we present a grid refinement model in the lattice Boltzmann method (LBM) for two-dimensional incompressible fluid flow. That is, the model combines the desirable features of the lattice Boltzmann method and stream function-vorticity formulations. In order to obtain an accurate result, very fine grid (or lattice) is required near the solid boundary. Therefore, the grid refinement model is used in the lattice Boltzmann method for stream function-vorticity formulation. This approach is more efficient in that it can obtain the same accurate solution as that in single-block approach even if few lattices are used for computation. In order to validate the grid refinement approach for the stream function-vorticity formulation, the numerical simulations of lid-driven cavity flows were performed and good results were obtained.

Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Science.gov (United States)

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

Incorporation of the equilibrium temperature approach in a Soil and Water Assessment Tool hydroclimatological stream temperature model

Science.gov (United States)

Du, Xinzhong; Shrestha, Narayan Kumar; Ficklin, Darren L.; Wang, Junye

2018-04-01

Stream temperature is an important indicator for biodiversity and sustainability in aquatic ecosystems. The stream temperature model currently in the Soil and Water Assessment Tool (SWAT) only considers the impact of air temperature on stream temperature, while the hydroclimatological stream temperature model developed within the SWAT model considers hydrology and the impact of air temperature in simulating the water-air heat transfer process. In this study, we modified the hydroclimatological model by including the equilibrium temperature approach to model heat transfer processes at the water-air interface, which reflects the influences of air temperature, solar radiation, wind speed and streamflow conditions on the heat transfer process. The thermal capacity of the streamflow is modeled by the variation of the stream water depth. An advantage of this equilibrium temperature model is the simple parameterization, with only two parameters added to model the heat transfer processes. The equilibrium temperature model proposed in this study is applied and tested in the Athabasca River basin (ARB) in Alberta, Canada. The model is calibrated and validated at five stations throughout different parts of the ARB, where close to monthly samplings of stream temperatures are available. The results indicate that the equilibrium temperature model proposed in this study provided better and more consistent performances for the different regions of the ARB with the values of the Nash-Sutcliffe Efficiency coefficient (NSE) greater than those of the original SWAT model and the hydroclimatological model. To test the model performance for different hydrological and environmental conditions, the equilibrium temperature model was also applied to the North Fork Tolt River Watershed in Washington, United States. The results indicate a reasonable simulation of stream temperature using the model proposed in this study, with minimum relative error values compared to the other two models

Java parallel secure stream for grid computing

International Nuclear Information System (INIS)

Chen, J.; Akers, W.; Chen, Y.; Watson, W.

2001-01-01

The emergence of high speed wide area networks makes grid computing a reality. However grid applications that need reliable data transfer still have difficulties to achieve optimal TCP performance due to network tuning of TCP window size to improve the bandwidth and to reduce latency on a high speed wide area network. The authors present a pure Java package called JPARSS (Java Parallel Secure Stream) that divides data into partitions that are sent over several parallel Java streams simultaneously and allows Java or Web applications to achieve optimal TCP performance in a gird environment without the necessity of tuning the TCP window size. Several experimental results are provided to show that using parallel stream is more effective than tuning TCP window size. In addition X.509 certificate based single sign-on mechanism and SSL based connection establishment are integrated into this package. Finally a few applications using this package will be discussed

SP@CE - An SP-based programming model for consumer electronics streaming applications

NARCIS (Netherlands)

Varbanescu, Ana Lucia; Nijhuis, Maik; Escribano, Arturo González; Sips, Henk; Bos, Herbert; Bal, Henri

2007-01-01

Efficient programming of multimedia streaming applications for Consumer Electronics (CE) devices is not trivial. As a solution for this problem, we present SP@CE, a novel programming model designed to balance the specific requirements of CE streaming applications with the simplicity and efficiency

MAC-Layer Active Dropping for Real-Time Video Streaming in 4G Access Networks

KAUST Repository

She, James

2010-12-01

This paper introduces a MAC-layer active dropping scheme to achieve effective resource utilization, which can satisfy the application-layer delay for real-time video streaming in time division multiple access based 4G broadband wireless access networks. When a video frame is not likely to be reconstructed within the application-layer delay bound at a receiver for the minimum decoding requirement, the MAC-layer protocol data units of such video frame will be proactively dropped before the transmission. An analytical model is developed to evaluate how confident a video frame can be delivered within its application-layer delay bound by jointly considering the effects of time-varying wireless channel, minimum decoding requirement of each video frame, data retransmission, and playback buffer. Extensive simulations with video traces are conducted to prove the effectiveness of the proposed scheme. When compared to conventional cross-layer schemes using prioritized-transmission/retransmission, the proposed scheme is practically implementable for more effective resource utilization, avoiding delay propagation, and achieving better video qualities under certain conditions.

Mapping a lateralisation gradient within the ventral stream for auditory speech perception

Directory of Open Access Journals (Sweden)

Karsten eSpecht

2013-10-01

Full Text Available Recent models on speech perception propose a dual stream processing network, with a dorsal stream, extending from the posterior temporal lobe of the left hemisphere through inferior parietal areas into the left inferior frontal gyrus, and a ventral stream that is assumed to originate in the primary auditory cortex in the upper posterior part of the temporal lobe and to extend towards the anterior part of the temporal lobe, where it may connect to the ventral part of the inferior frontal gyrus. This article describes and reviews the results from a series of complementary functional magnetic imaging (fMRI studies that aimed to trace the hierarchical processing network for speech comprehension within the left and right hemisphere with a particular focus on the temporal lobe and the ventral stream. As hypothesised, the results demonstrate a bilateral involvement of the temporal lobes in the processing of speech signals. However, an increasing leftward asymmetry was detected from auditory-phonetic to lexico-semantic processing and along the posterior-anterior axis, thus forming a lateralisation gradient. This increasing leftward lateralisation was particularly evident for the left superior temporal sulcus (STS and more anterior parts of the temporal lobe.

Mapping a lateralization gradient within the ventral stream for auditory speech perception.

Science.gov (United States)

Specht, Karsten

2013-01-01

Recent models on speech perception propose a dual-stream processing network, with a dorsal stream, extending from the posterior temporal lobe of the left hemisphere through inferior parietal areas into the left inferior frontal gyrus, and a ventral stream that is assumed to originate in the primary auditory cortex in the upper posterior part of the temporal lobe and to extend toward the anterior part of the temporal lobe, where it may connect to the ventral part of the inferior frontal gyrus. This article describes and reviews the results from a series of complementary functional magnetic resonance imaging studies that aimed to trace the hierarchical processing network for speech comprehension within the left and right hemisphere with a particular focus on the temporal lobe and the ventral stream. As hypothesized, the results demonstrate a bilateral involvement of the temporal lobes in the processing of speech signals. However, an increasing leftward asymmetry was detected from auditory-phonetic to lexico-semantic processing and along the posterior-anterior axis, thus forming a "lateralization" gradient. This increasing leftward lateralization was particularly evident for the left superior temporal sulcus and more anterior parts of the temporal lobe.

The development of stream temperature model in a mountainous river of Taiwan.

Science.gov (United States)

Tung, Ching-Pin; Lee, Tsung-Yu; Huang, Jr-Chuang; Perng, Po-Wen; Kao, Shih-Ji; Liao, Lin-Yen

2014-11-01

Formosan landlocked salmon is an endangered species and is very sensitive to stream temperature change. This study attempts to improve a former stream temperature model (STM) which was developed for the salmon's habitat to simulate stream temperature more realistically. Two modules, solar radiation modification (SRM) and surface/subsurface runoff mixing (RM), were incorporated to overcome the limitation of STM designed only for clear-sky conditions. It was found that daily temperature difference is related to cloud cover and can be used to adjust the effects of cloud cover on incident solar radiation to the ground level. The modified model (STM + SRM) improved the simulation during a baseflow period in both winter and summer with the Nash-Sutcliffe efficiency coefficient improved from 0.37 (by STM only) to 0.71 for the winter and from -0.18 to 0.70 for the summer. On the days with surface/subsurface runoff, the incorporation of the two new modules together (STM + SRM + RM) improved the Nash-Sutcliffe efficiency coefficient from 0.00 to 0.65 and from 0.29 to 0.83 in the winter and the summer, respectively. Meanwhile, the contributions of major thermal sources to stream temperature changes were identified. Groundwater is a major controlling factor for regulating seasonal changes of stream temperature while solar radiation is the primary factor controlling daily stream temperature variations. This study advanced our understanding on short-term stream temperature variation, which could be useful for the authorities to restore the salmon's habitat.

A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

Energy Technology Data Exchange (ETDEWEB)

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr [TECHNOLOGICAL RESEARCH INSTITUTE SYSTEMX (France); Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr [UPE/IFSTTAR-COSYS-GRETTIA (France)

2015-03-10

We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap scheme is introduced to numerically approximate the model’s flow equations.

Adding Live-Streaming to Recorded Lectures in a Non-Distributed Pre-Clerkship Medical Education Model.

Science.gov (United States)

Sandhu, Amanjot; Fliker, Aviva; Leitao, Darren; Jones, Jodi; Gooi, Adrian

2017-01-01

Live-streaming video has had increasing uses in medical education, especially in distributed education models. The literature on the impact of live-streaming in non-distributed education models, however, is scarce. To determine the attitudes towards live-streaming and recorded lectures as a resource to pre-clerkship medical students in a non-distributed medical education model. First and second year medical students were sent a voluntary cross-sectional survey by email, and were asked questions on live-streaming, recorded lectures and in person lectures using a 5-point Likert and open answers. Of the 118 responses (54% response rate), the data suggested that both watching recorded lectures (Likert 4.55) and live-streaming lectures (4.09) were perceived to be more educationally valuable than face-to-face attendance of lectures (3.60). While responses indicated a statistically significant increase in anticipated classroom attendance if both live-streaming and recorded lectures were removed (from 63% attendance to 76%, p =0.002), there was no significant difference in attendance if live-streaming lectures were removed but recorded lectures were maintained (from 63% to 66%, p=0.76). The addition of live-streaming lectures in the pre-clerkship setting was perceived to be value added to the students. The data also suggests that the removal of live-streaming lectures would not lead to a statistically significant increase in classroom attendance by pre-clerkship students.

Fate of acetone in an outdoor model stream with a nitrate supplement, southern Mississippi, U.S.A.

Science.gov (United States)

Rathbun, R.E.; Stephens, D.W.; Tai, D.Y.

1991-01-01

The fate of acetone in an outdoor model stream to which nitrate was added as a nutrient supplement was determined. The stream, in southern Mississippi, U.S.A. was 234 m long. Water was supplied to the stream by an artesian well at about 1.21 s-1, resulting in a mean water velocity of about 0.5 m min-1. Acetone was injected continuously for 26 days resulting in concentrations of 20-40 mg l-1. A nitrate solution was injected for 21 days resulting in an instream concentration of about 1.7 mg l-1 at the upstream end of the stream. Rhodamine-WT dye was used to determine the travel time and dispersion characteristics of the stream, and t-butyl alcohol was used to determine the volatilization characteristics. Volatilization controlled the fate of acetone in the model stream. The lack of substantial bacterial degradation of acetone was contrary to expectations based on the results of laboratory degradation studies using model stream water enriched with nitrate. A possible explanation for the lack of significant degradation in the model stream may be the limited 6-h residence time of the acetone in the stream. ?? 1991.

Predictive Models of the Hydrological Regime of Unregulated Streams in Arizona

Science.gov (United States)

Anning, David W.; Parker, John T.C.

2009-01-01

Three statistical models were developed by the U.S. Geological Survey in cooperation with the Arizona Department of Environmental Quality to improve the predictability of flow occurrence in unregulated streams throughout Arizona. The models can be used to predict the probabilities of the hydrological regime being one of four categories developed by this investigation: perennial, which has streamflow year-round; nearly perennial, which has streamflow 90 to 99.9 percent of the year; weakly perennial, which has streamflow 80 to 90 percent of the year; or nonperennial, which has streamflow less than 80 percent of the year. The models were developed to assist the Arizona Department of Environmental Quality in selecting sites for participation in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program. One model was developed for each of the three hydrologic provinces in Arizona - the Plateau Uplands, the Central Highlands, and the Basin and Range Lowlands. The models for predicting the hydrological regime were calibrated using statistical methods and explanatory variables of discharge, drainage-area, altitude, and location data for selected U.S. Geological Survey streamflow-gaging stations and a climate index derived from annual precipitation data. Models were calibrated on the basis of streamflow data from 46 stations for the Plateau Uplands province, 82 stations for the Central Highlands province, and 90 stations for the Basin and Range Lowlands province. The models were developed using classification trees that facilitated the analysis of mixed numeric and factor variables. In all three models, a threshold stream discharge was the initial variable to be considered within the classification tree and was the single most important explanatory variable. If a stream discharge value at a station was below the threshold, then the station record was determined as being nonperennial. If, however, the stream discharge was above the threshold

A simple prioritization tool to diagnose impairment of stream temperature for coldwater fishes in the Great Basin

Science.gov (United States)

Falke, Jeffrey A.; Dunham, Jason B.; Hockman-Wert, David; Pahl, Randy

2016-01-01

We provide a simple framework for diagnosing the impairment of stream water temperature for coldwater fishes across broad spatial extents based on a weight-of-evidence approach that integrates biological criteria, species distribution models, and geostatistical models of stream temperature. As a test case, we applied our approach to identify stream reaches most likely to be thermally impaired for Lahontan Cutthroat Trout Oncorhynchus clarkii henshawi in the upper Reese River, located in the northern Great Basin, Nevada. We first evaluated the capability of stream thermal regime descriptors to explain variation across 170 sites, and we found that the 7-d moving average of daily maximum stream temperatures (7DADM) provided minimal among-descriptor redundancy and, based on an upper threshold of 20°C, was also a good indicator of acute and chronic thermal stress. Next, we quantified the range of Lahontan Cutthroat Trout within our study area using a geographic distribution model. Finally, we used a geostatistical model to assess spatial variation in 7DADM and predict potential thermal impairment at the stream reach scale. We found that whereas 38% of reaches in our study area exceeded a 7DADM of 20°C and 35% were significantly warmer than predicted, only 17% both exceeded the biological criterion and were significantly warmer than predicted. This filtering allowed us to identify locations where physical and biological impairment were most likely within the network and that would represent the highest management priorities. Although our approach lacks the precision of more comprehensive approaches, it provides a broader context for diagnosing impairment and is a useful means of identifying priorities for more detailed evaluations across broad and heterogeneous stream networks.

Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.

Science.gov (United States)

Gopalakrishnan, Ravichandran C; Karunakaran, Manivannan

2014-01-01

Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

OPTIMAL CAMERA NETWORK DESIGN FOR 3D MODELING OF CULTURAL HERITAGE

Directory of Open Access Journals (Sweden)

B. S. Alsadik

2012-07-01

Full Text Available Digital cultural heritage documentation in 3D is subject to research and practical applications nowadays. Image-based modeling is a technique to create 3D models, which starts with the basic task of designing the camera network. This task is – however – quite crucial in practical applications because it needs a thorough planning and a certain level of expertise and experience. Bearing in mind todays computational (mobile power we think that the optimal camera network should be designed in the field, and, therefore, making the preprocessing and planning dispensable. The optimal camera network is designed when certain accuracy demands are fulfilled with a reasonable effort, namely keeping the number of camera shots at a minimum. In this study, we report on the development of an automatic method to design the optimum camera network for a given object of interest, focusing currently on buildings and statues. Starting from a rough point cloud derived from a video stream of object images, the initial configuration of the camera network assuming a high-resolution state-of-the-art non-metric camera is designed. To improve the image coverage and accuracy, we use a mathematical penalty method of optimization with constraints. From the experimental test, we found that, after optimization, the maximum coverage is attained beside a significant improvement of positional accuracy. Currently, we are working on a guiding system, to ensure, that the operator actually takes the desired images. Further next steps will include a reliable and detailed modeling of the object applying sophisticated dense matching techniques.

River longitudinal profiles and bedrock incision models: Stream power and the influence of sediment supply

Science.gov (United States)

Sklar, Leonard; Dietrich, William E.

The simplicity and apparent mechanistic basis of the stream power river incision law have led to its wide use in empirical and theoretical studies. Here we identify constraints on its calibration and application, and present a mechanistic theory for the effects of sediment supply on incision rates which spotlights additional limitations on the applicability of the stream power law. On channels steeper than about 20%, incision is probably dominated by episodic debris flows, and on sufficiently gentle slopes, sediment may bury the bedrock and prevent erosion. These two limits bound the application of the stream power law and strongly constrain the possible combination of parameters in the law. In order to avoid infinite slopes at the drainage divide in numerical models of river profiles using the stream power law it is commonly assumed that the first grid cell is unchanneled. We show, however, that the size of the grid may strongly influence the calculated equilibrium relief. Analysis of slope-drainage area relationships for a river network in a Northern California watershed using digital elevation data and review of data previously reported by Hack reveal that non-equilibrium profiles may produce well defined slope-area relationships (as expected in equilibrium channels), but large differences between tributaries may point to disequilibrium conditions. To explore the role of variations in sediment supply and transport capacity in bedrock incision we introduce a mechanistic model for abrasion of bedrock by saltating bedload. The model predicts that incision rates reach a maximum at intermediate levels of sediment supply and transport capacity. Incision rates decline away from the maximum with either decreasing supply (due to a shortage of tools) or increasing supply (due to gradual bed alluviation), and with either decreasing transport capacity (due to less energetic particle movement) or increasing transport capacity (due less frequent particle impacts per unit bed

Hydraulic modeling of thermal discharges into shallow, tidal affected streams

International Nuclear Information System (INIS)

Copp, H.W.; Shashidhara, N.S.

1981-01-01

A two-unit nuclear fired power plant is being constructed in western Washington state. Blowdown water from cooling towers will be discharged into the Chehalis River nearby. The location of a diffuser is some 21 miles upriver from Grays Harbor on the Pacific Ocean. Because the Chehalis River is classified as an excellent stream from the standpoint of water quality, State regulatory agencies required demonstration that thermal discharges would maintain water quality standards within fairly strict limits. A hydraulic model investigation used a 1:12 scale, undistorted model of a 1300-foot river reach in the vicinity of the diffuser. The model scale was selected to insure fully turbulent flows both in the stream and from the diffuser (Reynolds similitude). Model operation followed the densimetric Froude similitude. Thermistors were employed to measure temperatures in the model; measurements were taken by computer command and such measurements at some 250 positions were effected in about 2.5 seconds

A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems

Directory of Open Access Journals (Sweden)

Chen Homer H

2007-01-01

Full Text Available The paradigm shift of network design from performance-centric to constraint-centric has called for new signal processing techniques to deal with various aspects of resource-constrained communication and networking. In this paper, we consider the computational constraints of a multimedia communication system and propose a video adaptation mechanism for live video streaming of multiple channels. The video adaptation mechanism includes three salient features. First, it adjusts the computational resource of the streaming server block by block to provide a fine control of the encoding complexity. Second, as far as we know, it is the first mechanism to allocate the computational resource to multiple channels. Third, it utilizes a complexity-distortion model to determine the optimal coding parameter values to achieve global optimization. These techniques constitute the basic building blocks for a successful application of wireless and Internet video to digital home, surveillance, IPTV, and online games.

A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems

Science.gov (United States)

Lu, Meng-Ting; Yao, Jason J.; Chen, Homer H.

2007-12-01

The paradigm shift of network design from performance-centric to constraint-centric has called for new signal processing techniques to deal with various aspects of resource-constrained communication and networking. In this paper, we consider the computational constraints of a multimedia communication system and propose a video adaptation mechanism for live video streaming of multiple channels. The video adaptation mechanism includes three salient features. First, it adjusts the computational resource of the streaming server block by block to provide a fine control of the encoding complexity. Second, as far as we know, it is the first mechanism to allocate the computational resource to multiple channels. Third, it utilizes a complexity-distortion model to determine the optimal coding parameter values to achieve global optimization. These techniques constitute the basic building blocks for a successful application of wireless and Internet video to digital home, surveillance, IPTV, and online games.

The Effect of Model Grid Resolution on the Distributed Hydrologic Simulations for Forecasting Stream Flows and Reservoir Storage

Science.gov (United States)

Turnbull, S. J.

2017-12-01

Within the US Army Corps of Engineers (USACE), reservoirs are typically operated according to a rule curve that specifies target water levels based on the time of year. The rule curve is intended to maximize flood protection by specifying releases of water before the dominant rainfall period for a region. While some operating allowances are permissible, generally the rule curve elevations must be maintained. While this operational approach provides for the required flood control purpose, it may not result in optimal reservoir operations for multi-use impoundments. In the Russian River Valley of California a multi-agency research effort called Forecast-Informed Reservoir Operations (FIRO) is assessing the application of forecast weather and streamflow predictions to potentially enhance the operation of reservoirs in the watershed. The focus of the study has been on Lake Mendocino, a USACE project important for flood control, water supply, power generation and ecological flows. As part of this effort the Engineer Research and Development Center is assessing the ability of utilizing the physics based, distributed watershed model Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to simulate stream flows, reservoir stages, and discharges while being driven by weather forecast products. A key question in this application is the effect of watershed model resolution on forecasted stream flows. To help resolve this question, GSSHA models of multiple grid resolutions, 30, 50, and 270m, were developed for the upper Russian River, which includes Lake Mendocino. The models were derived from common inputs: DEM, soils, land use, stream network, reservoir characteristics, and specified inflows and discharges. All the models were calibrated in both event and continuous simulation mode using measured precipitation gages and then driven with the West-WRF atmospheric model in prediction mode to assess the ability of the model to function in short term, less than one week

Collaborative networks: Reference modeling

NARCIS (Netherlands)

Camarinha-Matos, L.M.; Afsarmanesh, H.

2008-01-01

Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

The four facets of multimedia streaming (Chapter 7)

NARCIS (Netherlands)

Agboma, F.; Liotta, A.; Pierre, S.

2010-01-01

Recent advances in media coding techniques and network access technologies have made multimedia streaming practicable and affordable in both fixed and mobile environments. Multimedia streaming services from anywhere and at anytime is fast becoming a reality. This chapter provides a snapshot of the

Stochastic Modelling of Shiroro River Stream flow Process

OpenAIRE

Musa, J. J

2013-01-01

Economists, social scientists and engineers provide insights into the drivers of anthropogenic climate change and the options for adaptation and mitigation, and yet other scientists, including geographers and biologists, study the impacts of climate change. This project concentrates mainly on the discharge from the Shiroro River. A stochastic approach is presented for modeling a time series by an Autoregressive Moving Average model (ARMA). The development and use of a stochastic stream flow m...

Stochastic ice stream dynamics.

Science.gov (United States)

Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca

2016-08-09

Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

rEMM: Extensible Markov Model for Data Stream Clustering in R

Directory of Open Access Journals (Sweden)

Michael Hahsler

2010-10-01

Full Text Available Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream is not only characterized by the proximity of data points which is used by clustering, but also by a temporal component. The extensible Markov model (EMM adds the temporal component to data stream clustering by superimposing a dynamically adapting Markov chain. In this paper we introduce the implementation of the R extension package rEMM which implements EMM and we discuss some examples and applications.

Determining hyporheic storage using the rSAS model in urban restored streams.

Science.gov (United States)

Stoll, E.; Putnam, S. M.; Cosans, C.; Harman, C. J.

2017-12-01

One aim of stream restoration is to increase the connectivity of the stream with the hyporheic zone, which is important for processes like denitrification. This study analyzed transects of different restoration techniques in an urban stream, Stony Run in Baltimore, Maryland. The extent of the hyporheic zone was determined using a combination of salt slug injection tracer studies to determine the breakthrough curves and the rank StorAge Selection (rSAS) model. Previous studies using salt tracer injections have often focused on the shape of the breakthrough curve and the transit time distributions of streams to infer indicies correlated with hyporheic zone storage. This study uses the rSAS model to determine the volume of storage that must be turning over to produce the breakthrough curve. This study looked at transects of two different restoration techniques, one with floodplain rehabilitation and one without. Both transects had cross vanes and pool and riffle systems and only differed in the steepness of the banks surrounding the stream. The utility and accuracy of rSAS method was found to be heavily dependent on accurate flow rates. To avoid potential skew in the results, normalized, relatively flow rate-independent metric of storage were compared among transects to reduce error resulting from the flow rate. The results suggested that stream water was retained for longer in a larger storage volume in the transect that did not have floodplain rehabilitation. When compared to the storage of a natural stream with similar geomorphologic characteristics, the restored transect without floodplain rehabilitation had a larger storage volume than the natural stream. The restored transect with floodplain rehabilitation not only had a smaller storage volume than the restored section without rehabilitation, but also had a smaller storage volume than the natural stream with similar bank slopes. This suggests that the floodplain restoration does not significantly contribute to

Effect of morphology and discharge on hyporheic exchange flows in two small streams in the Cascade Mountains of Oregon, USA.

Science.gov (United States)

Steven M. Wondzell

2006-01-01

Stream-tracer injections were used to examine the effect of channel morphology and changing stream discharge on hyporheic exchange flows. Direct observations were made from well networks to follow tracer movement through the hyporheic zone. The reach-integrated influence of hyporheic exchange was evaluated using the transient storage model (TSM) OTIS-P. Transient...

Questioning the Faith - Models and Prediction in Stream Restoration (Invited)

Science.gov (United States)

Wilcock, P.

2013-12-01

River management and restoration demand prediction at and beyond our present ability. Management questions, framed appropriately, can motivate fundamental advances in science, although the connection between research and application is not always easy, useful, or robust. Why is that? This presentation considers the connection between models and management, a connection that requires critical and creative thought on both sides. Essential challenges for managers include clearly defining project objectives and accommodating uncertainty in any model prediction. Essential challenges for the research community include matching the appropriate model to project duration, space, funding, information, and social constraints and clearly presenting answers that are actually useful to managers. Better models do not lead to better management decisions or better designs if the predictions are not relevant to and accepted by managers. In fact, any prediction may be irrelevant if the need for prediction is not recognized. The predictive target must be developed in an active dialog between managers and modelers. This relationship, like any other, can take time to develop. For example, large segments of stream restoration practice have remained resistant to models and prediction because the foundational tenet - that channels built to a certain template will be able to transport the supplied sediment with the available flow - has no essential physical connection between cause and effect. Stream restoration practice can be steered in a predictive direction in which project objectives are defined as predictable attributes and testable hypotheses. If stream restoration design is defined in terms of the desired performance of the channel (static or dynamic, sediment surplus or deficit), then channel properties that provide these attributes can be predicted and a basis exists for testing approximations, models, and predictions.

Long-term patterns of chironomid assemblages in a high elevation stream/lake network (Switzerland – Implications to global change

Directory of Open Access Journals (Sweden)

Brigitte Lods-Crozet

2012-10-01

Full Text Available A long-term monitoring program was initiated in 2002 on running and standing waters in a high elevation cirque landscape (Macun in the Swiss National Park. The region comprises contrasting basins with different water sources, a glacier-fed basin and two precipitation-fed basins. Sampling of 26 permanent and temporary ponds (or small lakes and of interconnecting streams (10 sites was conducted from 2002 to 2010. Pond macroinvertebrate assemblages were dominated by chironomids with 42 taxa. The Orthocladiinae were the dominant subfamily in richness and abundance with 22 taxa. The greatest diversity was found in ponds located in the south and outlet basins. The inter-year variability for the same pond is high, but no clear temporal trend was noticed in ponds frequently monitored ponds. The Orthocladiinae subfamily was also the richest in the stream sites where 33 taxa were collected. The north and south basins were separated on the basis of chironomid assemblages. The chironomid assemblages in the stream network shows a temporal trend from 2002 but it cannot be linked to any clear change at the community structure level. The higher richness and abundance in stream sites and ponds of the south basin could be related to a greater heterogeneity in water physico-chemistry and substrata, and by the presence of Bryophyta. The understanding of the environmental factors that influence faunal assemblages is crucial for the protection of this sensitive alpine pond network where a relatively high overall regional diversity (49 taxa is detected. From the literature, temperature is recognized as the driving force on changes in chironomid assemblages in alpine systems. Our results support the use of chironomids as flagship indicators in the assessment of climatic change in alpine landscapes.doi: 10.5324/fn.v31i0.1361.Published online: 17 October 2012.

A daily salt balance model for stream salinity generation processes following partial clearing from forest to pasture

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M. A. Bari

2006-01-01

Full Text Available We developed a coupled salt and water balance model to represent the stream salinity generation process following land use changes. The conceptual model consists of three main components with five stores: (i Dry, Wet and Subsurface Stores, (ii a saturated Groundwater Store and (iii a transient Stream zone Store. The Dry and Wet Stores represent the salt and water movement in the unsaturated zone and also the near-stream dynamic saturated areas, responsible for the generation of salt flux associated with surface runoff and interflow. The unsaturated Subsurface Store represents the salt bulge and the salt fluxes. The Groundwater Store comes into play when the groundwater level is at or above the stream invert and quantifies the salt fluxes to the Stream zone Store. In the stream zone module, we consider a 'free mixing' between the salt brought about by surface runoff, interflow and groundwater flow. Salt accumulation on the surface due to evaporation and its flushing by initial winter flow is also incorporated in the Stream zone Store. The salt balance model was calibrated sequentially following successful application of the water balance model. Initial salt stores were estimated from measured salt profile data. We incorporated two lumped parameters to represent the complex chemical processes like diffusion-dilution-dispersion and salt fluxes due to preferential flow. The model has performed very well in simulating stream salinity generation processes observed at Ernies and Lemon experimental catchments in south west of Western Australia. The simulated and observed stream salinity and salt loads compare very well throughout the study period with NSE of 0.7 and 0.4 for Ernies and Lemon catchment respectively. The model slightly over predicted annual stream salt load by 6.2% and 6.8%.

Parallel computing and networking; Heiretsu keisanki to network

Energy Technology Data Exchange (ETDEWEB)

Asakawa, E; Tsuru, T [Japan National Oil Corp., Tokyo (Japan); Matsuoka, T [Japan Petroleum Exploration Co. Ltd., Tokyo (Japan)

1996-05-01

This paper describes the trend of parallel computers used in geophysical exploration. Around 1993 was the early days when the parallel computers began to be used for geophysical exploration. Classification of these computers those days was mainly MIMD (multiple instruction stream, multiple data stream), SIMD (single instruction stream, multiple data stream) and the like. Parallel computers were publicized in the 1994 meeting of the Geophysical Exploration Society as a `high precision imaging technology`. Concerning the library of parallel computers, there was a shift to PVM (parallel virtual machine) in 1993 and to MPI (message passing interface) in 1995. In addition, the compiler of FORTRAN90 was released with support implemented for data parallel and vector computers. In 1993, networks used were Ethernet, FDDI, CDDI and HIPPI. In 1995, the OC-3 products under ATM began to propagate. However, ATM remains to be an interoffice high speed network because the ATM service has not spread yet for the public network. 1 ref.

In-network adaptation of SHVC video in software-defined networks

Science.gov (United States)

Awobuluyi, Olatunde; Nightingale, James; Wang, Qi; Alcaraz Calero, Jose Maria; Grecos, Christos

2016-04-01

Software Defined Networks (SDN), when combined with Network Function Virtualization (NFV) represents a paradigm shift in how future networks will behave and be managed. SDN's are expected to provide the underpinning technologies for future innovations such as 5G mobile networks and the Internet of Everything. The SDN architecture offers features that facilitate an abstracted and centralized global network view in which packet forwarding or dropping decisions are based on application flows. Software Defined Networks facilitate a wide range of network management tasks, including the adaptation of real-time video streams as they traverse the network. SHVC, the scalable extension to the recent H.265 standard is a new video encoding standard that supports ultra-high definition video streams with spatial resolutions of up to 7680×4320 and frame rates of 60fps or more. The massive increase in bandwidth required to deliver these U-HD video streams dwarfs the bandwidth requirements of current high definition (HD) video. Such large bandwidth increases pose very significant challenges for network operators. In this paper we go substantially beyond the limited number of existing implementations and proposals for video streaming in SDN's all of which have primarily focused on traffic engineering solutions such as load balancing. By implementing and empirically evaluating an SDN enabled Media Adaptation Network Entity (MANE) we provide a valuable empirical insight into the benefits and limitations of SDN enabled video adaptation for real time video applications. The SDN-MANE is the video adaptation component of our Video Quality Assurance Manager (VQAM) SDN control plane application, which also includes an SDN monitoring component to acquire network metrics and a decision making engine using algorithms to determine the optimum adaptation strategy for any real time video application flow given the current network conditions. Our proposed VQAM application has been implemented and

Evasion of CO2 from streams - the dominant component of the carbon export through the aquatic conduit in a boreal landscape.

Science.gov (United States)

Wallin, Marcus B; Grabs, Thomas; Buffam, Ishi; Laudon, Hjalmar; Agren, Ånneli; Öquist, Mats G; Bishop, Kevin

2013-03-01

Evasion of gaseous carbon (C) from streams is often poorly quantified in landscape C budgets. Even though the potential importance of the capillary network of streams as C conduits across the land-water-atmosphere interfaces is sometimes mentioned, low-order streams are often left out of budget estimates due to being poorly characterized in terms of gas exchange and even areal surface coverage. We show that evasion of C is greater than all the total dissolved C (both organic and inorganic) exported downstream in the waters of a boreal landscape. In this study evasion of carbon dioxide (CO2 ) from running waters within a 67 km(2) boreal catchment was studied. During a 4 year period (2006-2009) 13 streams were sampled on 104 different occasions for dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC). From a locally determined model of gas exchange properties, we estimated the daily CO2 evasion with a high-resolution (5 × 5 m) grid-based stream evasion model comprising the entire ~100 km stream network. Despite the low areal coverage of stream surface, the evasion of CO2 from the stream network constituted 53% (5.0 (±1.8) g C m(-2)  yr(-1) ) of the entire stream C flux (9.6 (±2.4) g C m(-2)  yr(-1) ) (lateral as DIC, DOC, and vertical as CO2 ). In addition, 72% of the total CO2 loss took place already in the first- and second-order streams. This study demonstrates the importance of including CO2 evasion from low-order boreal streams into landscape C budgets as it more than doubled the magnitude of the aquatic conduit for C from this landscape. Neglecting this term will consequently result in an overestimation of the terrestrial C sink strength in the boreal landscape. © 2012 Blackwell Publishing Ltd.

Artificial Neural Network Modelling of the Energy Content of Municipal Solid Wastes in Northern Nigeria

Directory of Open Access Journals (Sweden)

M. B. Oumarou

2017-12-01

Full Text Available The study presents an application of the artificial neural network model using the back propagation learning algorithm to predict the actual calorific value of the municipal solid waste in major cities of the northern part of Nigeria, with high population densities and intense industrial activities. These cities are: Kano, Damaturu, Dutse, Bauchi, Birnin Kebbi, Gusau, Maiduguri, Katsina and Sokoto. Experimental data of the energy content and the physical characterization of the municipal solid waste serve as the input parameter in nature of wood, grass, metal, plastic, food remnants, leaves, glass and paper. Comparative studies were made by using the developed model, the experimental results and a correlation which was earlier developed by the authors to predict the energy content. While predicting the actual calorific value, the maximum error was 0.94% for the artificial neural network model and 5.20% by the statistical correlation. The network with eight neurons and an R2 = 0.96881 in the hidden layer results in a stable and optimum network. This study showed that the artificial neural network approach could successfully be used for energy content predictions from the municipal solid wastes in Northern Nigeria and other areas of similar waste stream and composition.

Transmission Algorithm with QoS Considerations for a Sustainable MPEG Streaming Service

Directory of Open Access Journals (Sweden)

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.

Building a High-Precision 2D Hydrodynamic Flood Model Using UAV Photogrammetry and Sensor Network Monitoring

Directory of Open Access Journals (Sweden)

Jakub Langhammer

2017-11-01

Full Text Available This paper explores the potential of the joint application of unmanned aerial vehicle (UAV-based photogrammetry and an automated sensor network for building a hydrodynamic flood model of a montane stream. UAV-based imagery was used for three-dimensional (3D photogrammetric reconstruction of the stream channel, achieving a resolution of 1.5 cm/pixel. Automated ultrasonic water level gauges, operating with a 10 min interval, were used as a source of hydrological data for the model calibration, and the MIKE 21 hydrodynamic model was used for building the flood model. Three different horizontal schematizations of the channel—an orthogonal grid, curvilinear grid, and flexible mesh—were used to evaluate the effect of spatial discretization on the results. The research was performed on Javori Brook, a montane stream in the Sumava (Bohemian Forest Mountains, Czech Republic, Central Europe, featuring a fast runoff response to precipitation events and that is located in a core zone of frequent flooding. The studied catchments have been, since 2007, equipped with automated water level gauges and, since 2013, under repeated UAV monitoring. The study revealed the high potential of these data sources for applications in hydrodynamic modeling. In addition to the ultra-high levels of spatial and temporal resolution, the major contribution is in the method’s high operability, enabling the building of highly detailed flood models even in remote areas lacking conventional monitoring. The testing of the data sources and model setup indicated the limitations of the UAV reconstruction of the stream bathymetry, which was completed by the geodetic-grade global navigation satellite system (GNSS measurements. The testing of the different model domain schematizations did not indicate the substantial differences that are typical for conventional low-resolution data, proving the high reliability of the tested modeling workflow.

Modeling wood dynamics, jam formation, and sediment storage in a gravel-bed stream

Science.gov (United States)

Eaton, B. C.; Hassan, M. A.; Davidson, S. L.

2012-12-01

In small and intermediate sized streams, the interaction between wood and bed material transport often determines the nature of the physical habitat, which in turn influences the health of the stream's ecosystem. We present a stochastic model that can be used to simulate the effects on physical habitat of forest fires, climate change, and other environmental disturbances that alter wood recruitment. The model predicts large wood (LW) loads in a stream as well as the volume of sediment stored by the wood; while it is parameterized to describe gravel bed streams similar to a well-studied field prototype, Fishtrap Creek, British Columbia, it can be calibrated to other systems as well. In the model, LW pieces are produced and modified over time as a result of random tree-fall, LW breakage, LW movement, and piece interaction to form LW jams. Each LW piece traps a portion of the annual bed material transport entering the reach and releases the stored sediment when the LW piece is entrained and moved. The equations governing sediment storage are based on a set of flume experiments also scaled to the field prototype. The model predicts wood loads ranging from 70 m3/ha to more than 300 m3/ha, with a mean value of 178 m3/ha: both the range and the mean value are consistent with field data from streams with similar riparian forest types and climate. The model also predicts an LW jam spacing that is consistent with field data. Furthermore, our modeling results demonstrate that the high spatial and temporal variability in sediment storage, sediment transport, and channel morphology associated with LW-dominated streams occurs only when LW pieces interact and form jams. Model runs that do not include jam formation are much less variable. These results suggest that river restoration efforts using engineered LW pieces that are fixed in place and not permitted to interact will be less successful at restoring the geomorphic processes responsible for producing diverse, productive

The Midwest Stream Quality Assessment—Influences of human activities on streams

Science.gov (United States)

Van Metre, Peter C.; Mahler, Barbara J.; Carlisle, Daren M.; Coles, James F.

2018-04-16

Healthy streams and the fish and other organisms that live in them contribute to our quality of life. Extensive modification of the landscape in the Midwestern United States, however, has profoundly affected the condition of streams. Row crops and pavement have replaced grasslands and woodlands, streams have been straightened, and wetlands and fields have been drained. Runoff from agricultural and urban land brings sediment and chemicals to streams. What is the chemical, physical, and biological condition of Midwestern streams? Which physical and chemical stressors are adversely affecting biological communities, what are their origins, and how might we lessen or avoid their adverse effects?In 2013, the U.S. Geological Survey (USGS) conducted the Midwest Stream Quality Assessment to evaluate how human activities affect the biological condition of Midwestern streams. In collaboration with the U.S. Environmental Protection Agency National Rivers and Streams Assessment, the USGS sampled 100 streams, chosen to be representative of the different types of watersheds in the region. Biological condition was evaluated based on the number and diversity of fish, algae, and invertebrates in the streams. Changes to the physical habitat and chemical characteristics of the streams—“stressors”—were assessed, and their relation to landscape factors and biological condition was explored by using mathematical models. The data and models help us to better understand how the human activities on the landscape are affecting streams in the region.

Quality models for audiovisual streaming

Science.gov (United States)

Thang, Truong Cong; Kim, Young Suk; Kim, Cheon Seog; Ro, Yong Man

2006-01-01

Quality is an essential factor in multimedia communication, especially in compression and adaptation. Quality metrics can be divided into three categories: within-modality quality, cross-modality quality, and multi-modality quality. Most research has so far focused on within-modality quality. Moreover, quality is normally just considered from the perceptual perspective. In practice, content may be drastically adapted, even converted to another modality. In this case, we should consider the quality from semantic perspective as well. In this work, we investigate the multi-modality quality from the semantic perspective. To model the semantic quality, we apply the concept of "conceptual graph", which consists of semantic nodes and relations between the nodes. As an typical of multi-modality example, we focus on audiovisual streaming service. Specifically, we evaluate the amount of information conveyed by a audiovisual content where both video and audio channels may be strongly degraded, even audio are converted to text. In the experiments, we also consider the perceptual quality model of audiovisual content, so as to see the difference with semantic quality model.

Solar wind stream evolution at large heliocentric distances - Experimental demonstration and the test of a model

Science.gov (United States)

Gosling, J. T.; Hundhausen, A. J.; Bame, S. J.

1976-01-01

A stream propagation model which neglects all dissipation effects except those occurring at shock interfaces, was used to compare Pioneer-10 solar wind speed observations, during the time when Pioneer 10, the earth, and the sun were coaligned, with near-earth Imp-7 observations of the solar wind structure, and with the theoretical predictions of the solar wind structure at Pioneer 10 derived from the Imp-7 measurements, using the model. The comparison provides a graphic illustration of the phenomenon of stream steepening in the solar wind with the attendant formation of forward-reverse shock pairs and the gradual decay of stream amplitudes with increasing heliocentric distance. The comparison also provides a qualitative test of the stream propagation model.

Modelling the fate of six common pharmaceuticals in a small stream: quantification of attenuation and retention in different stream-specific environments

Science.gov (United States)

Riml, Joakim; Wörman, Anders; Kunkel, Uwe; Radke, Michael

2013-04-01

Detection of pharmaceutical residues in streaming waters is common in urbanized areas. Although the occurrence and source of these micropollutants is known, their behavior in these aquatic ecosystems is still only partly understood. Specifically, quantitative information of biogeochemical processes in stream-specific environments where predominant reactions occur is often missing. In an attempt to address this knowledge gap, we performed simultaneous tracer tests in Säva Brook, Sweden, with bezafibrate, clofibric acid, diclofenac, ibuprofen, metoprolol and naproxen, as well as with the more inert solutes uranine and Rhodamine WT. The breakthrough curves at five successive sampling stations along a 16 km long stream reach were evaluated using a coupled physical-biogeochemical model framework containing surface water transport together with a representation of transient storage in slow/immobile zones of the stream. The multi-tracer experiment opens for decoupling of hydrological and biogeochemical contribution to the fate, and by linking impact and sensitivity analyses to relative significance of model parameters the most important processes for each contaminant were elucidated. Specifically for Säva Brook, the proposed methodology revealed that the pharmaceutical-contaminated stream water remained in the storage zones for times corresponding to 5-25% of the flow time of the stream. Furthermore, the results indicate a great variability in terms of predominant biogeochemical processes between the different contaminants. Rapid reactions occurring in the transient storage zone attenuated both ibuprofen and clofibric acid, and we conclude that a major degradation pathway for these contaminants was biodegradation in the hyporheic zone. In contrast, bezafibrate, metoprolol, and naproxen were mainly affected by sorption both in the storage zone and the main channel, while diclofenac displayed negligible effects of biogeochemical reactions.

Nonlinear forecasting of stream flows using a chaotic approach and artificial neural networks

Directory of Open Access Journals (Sweden)

Hakan Tongal

2013-07-01

Full Text Available This paper evaluates the forecasting performance of two nonlinear models, k-nearest neighbor (kNN and feed-forward neural networks (FFNN, using stream flow data of the Kızılırmak River, the longest river in Turkey. For the kNN model, the required parameters are delay time, number of nearest neigh- bors and embedding dimension. The optimal delay time was obtained with the mutual information function; the number of nearest neighbors was obtained with the optimization process that minimi- zes RMSE as a function of the neighbor number and the embedding dimension was obtained with the correlation dimension method. The correlation dimension of the Kızılırmak River was d = 2.702, which was used in forming the input structure of the FFNN. The nearest integer above the correlation dimension (i.e., 3 provided the minimal number of required variables to characterize the system, and the maximum number of required variables was obtained with the nearest integer above the value 2d + 1 (Takens, 1981 (i.e., 7. Two FFNN models were developed that incorporate 3 and 7 lagged discharge values and the predicted performance compared to that of the kNN model. The results showed that the kNN model was superior to the FFNN model in stream flow forecasting. However, as a result from the kNN model structure, the model failed in the prediction of peak values. Additionally, it was found that the correlation dimension (if it existed could successfully be used in time series where the determina- tion of the input structure is difficult because of high inter-dependency, as in stream flow time series.  Resumen Este trabajo evalúa el desempeño de pronóstico de dos modelos no lineares, de método de clasificación no paramétrico kNN y de redes neuronales con alimentación avanzada (FNNN, usando datos de flujo del río Kizilirmak, el mayor de Turquía. Para el modelo kNN, los parámetros requeridos son tiempo de retraso, número de vecindarios cercanos y dimensión de

Application of the Hydroecological Integrity Assessment Process for Missouri Streams

Science.gov (United States)

Kennen, Jonathan G.; Henriksen, James A.; Heasley, John; Cade, Brian S.; Terrell, James W.

2009-01-01

Natural flow regime concepts and theories have established the justification for maintaining or restoring the range of natural hydrologic variability so that physiochemical processes, native biodiversity, and the evolutionary potential of aquatic and riparian assemblages can be sustained. A synthesis of recent research advances in hydroecology, coupled with stream classification using hydroecologically relevant indices, has produced the Hydroecological Integrity Assessment Process (HIP). HIP consists of (1) a regional classification of streams into hydrologic stream types based on flow data from long-term gaging-station records for relatively unmodified streams, (2) an identification of stream-type specific indices that address 11 subcomponents of the flow regime, (3) an ability to establish environmental flow standards, (4) an evaluation of hydrologic alteration, and (5) a capacity to conduct alternative analyses. The process starts with the identification of a hydrologic baseline (reference condition) for selected locations, uses flow data from a stream-gage network, and proceeds to classify streams into hydrologic stream types. Concurrently, the analysis identifies a set of non-redundant and ecologically relevant hydrologic indices for 11 subcomponents of flow for each stream type. Furthermore, regional hydrologic models for synthesizing flow conditions across a region and the development of flow-ecology response relations for each stream type can be added to further enhance the process. The application of HIP to Missouri streams identified five stream types ((1) intermittent, (2) perennial runoff-flashy, (3) perennial runoff-moderate baseflow, (4) perennial groundwater-stable, and (5) perennial groundwater-super stable). Two Missouri-specific computer software programs were developed: (1) a Missouri Hydrologic Assessment Tool (MOHAT) which is used to establish a hydrologic baseline, provide options for setting environmental flow standards, and compare past and

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Progress and lessons learned from water-quality monitoring networks

Science.gov (United States)

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

Quantifying geomorphic change at ephemeral stream restoration sites using a coupled-model approach

Science.gov (United States)

Norman, Laura M.; Sankey, Joel B.; Dean, David; Caster, Joshua J.; DeLong, Stephen B.; Henderson-DeLong, Whitney; Pelletier, Jon D.

2017-01-01

Rock-detention structures are used as restoration treatments to engineer ephemeral stream channels of southeast Arizona, USA, to reduce streamflow velocity, limit erosion, retain sediment, and promote surface-water infiltration. Structures are intended to aggrade incised stream channels, yet little quantified evidence of efficacy is available. The goal of this 3-year study was to characterize the geomorphic impacts of rock-detention structures used as a restoration strategy and develop a methodology to predict the associated changes. We studied reaches of two ephemeral streams with different watershed management histories: one where thousands of loose-rock check dams were installed 30 years prior to our study, and one with structures constructed at the beginning of our study. The methods used included runoff, sediment transport, and geomorphic modelling and repeat terrestrial laser scanner (TLS) surveys to map landscape change. Where discharge data were not available, event-based runoff was estimated using KINEROS2, a one-dimensional kinematic-wave runoff and erosion model. Discharge measurements and estimates were used as input to a two-dimensional unsteady flow-and-sedimentation model (Nays2DH) that combined a gridded flow, transport, and bed and bank simulation with geomorphic change. Through comparison of consecutive DEMs, the potential to substitute uncalibrated models to analyze stream restoration is introduced. We demonstrate a new approach to assess hydraulics and associated patterns of aggradation and degradation resulting from the construction of check-dams and other transverse structures. Notably, we find that stream restoration using rock-detention structures is effective across vastly different timescales.

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.

Science.gov (United States)

Güçlü, Umut; van Gerven, Marcel A J

2015-07-08

Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream. Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0.

Increased functional connectivity in the ventral and dorsal streams during retrieval of novel words in professional musicians.

Science.gov (United States)

Dittinger, Eva; Valizadeh, Seyed Abolfazl; Jäncke, Lutz; Besson, Mireille; Elmer, Stefan

2018-02-01

Current models of speech and language processing postulate the involvement of two parallel processing streams (the dual stream model): a ventral stream involved in mapping sensory and phonological representations onto lexical and conceptual representations and a dorsal stream contributing to sound-to-motor mapping, articulation, and to how verbal information is encoded and manipulated in memory. Based on previous evidence showing that music training has an influence on language processing, cognitive functions, and word learning, we examined EEG-based intracranial functional connectivity in the ventral and dorsal streams while musicians and nonmusicians learned the meaning of novel words through picture-word associations. In accordance with the dual stream model, word learning was generally associated with increased beta functional connectivity in the ventral stream compared to the dorsal stream. In addition, in the linguistically most demanding "semantic task," musicians outperformed nonmusicians, and this behavioral advantage was accompanied by increased left-hemispheric theta connectivity in both streams. Moreover, theta coherence in the left dorsal pathway was positively correlated with the number of years of music training. These results provide evidence for a complex interplay within a network of brain regions involved in semantic processing and verbal memory functions, and suggest that intensive music training can modify its functional architecture leading to advantages in novel word learning. © 2017 Wiley Periodicals, Inc.

Where and why hyporheic exchange is important: Inferences from a parsimonious, physically-based river network model

Science.gov (United States)

Gomez-Velez, J. D.; Harvey, J. W.

2014-12-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data as well as models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically-based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). At the core of NEXSS is a characterization of the channel geometry, geomorphic features, and related hydraulic drivers based on scaling equations from the literature and readily accessible information such as river discharge, bankfull width, median grain size, sinuosity, channel slope, and regional groundwater gradients. Multi-scale hyporheic flow is computed based on combining simple but powerful analytical and numerical expressions that have been previously published. We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bedforms dominates hyporheic fluxes and turnover rates along the river corridor. Moreover, the hyporheic zone's potential for biogeochemical transformations is comparable across stream orders, but the abundance of lower-order channels results in a considerably higher cumulative effect for low-order streams. Thus, vertical exchange beneath submerged bedforms has more potential for biogeochemical transformations than lateral exchange beneath banks, although lateral exchange through meanders may be important in large rivers. These results have implications for predicting outcomes of river and basin management practices.

A feedback model of figure-ground assignment.

Science.gov (United States)

Domijan, Drazen; Setić, Mia

2008-05-30

A computational model is proposed in order to explain how bottom-up and top-down signals are combined into a unified perception of figure and background. The model is based on the interaction between the ventral and the dorsal stream. The dorsal stream computes saliency based on boundary signals provided by the simple and the complex cortical cells. Output from the dorsal stream is projected to the surface network which serves as a blackboard on which the surface representation is formed. The surface network is a recurrent network which segregates different surfaces by assigning different firing rates to them. The figure is labeled by the maximal firing rate. Computer simulations showed that the model correctly assigns figural status to the surface with a smaller size, a greater contrast, convexity, surroundedness, horizontal-vertical orientation and a higher spatial frequency content. The simple gradient of activity in the dorsal stream enables the simulation of the new principles of the lower region and the top-bottom polarity. The model also explains how the exogenous attention and the endogenous attention may reverse the figural assignment. Due to the local excitation in the surface network, neural activity at the cued region will spread over the whole surface representation. Therefore, the model implements the object-based attentional selection.

Quantifying in-stream retention of nitrate at catchment scales using a practical mass balance approach.

Science.gov (United States)

Schwientek, Marc; Selle, Benny

2016-02-01

As field data on in-stream nitrate retention is scarce at catchment scales, this study aimed at quantifying net retention of nitrate within the entire river network of a fourth-order stream. For this purpose, a practical mass balance approach combined with a Lagrangian sampling scheme was applied and seasonally repeated to estimate daily in-stream net retention of nitrate for a 17.4 km long, agriculturally influenced, segment of the Steinlach River in southwestern Germany. This river segment represents approximately 70% of the length of the main stem and about 32% of the streambed area of the entire river network. Sampling days in spring and summer were biogeochemically more active than in autumn and winter. Results obtained for the main stem of Steinlach River were subsequently extrapolated to the stream network in the catchment. It was demonstrated that, for baseflow conditions in spring and summer, in-stream nitrate retention could sum up to a relevant term of the catchment's nitrogen balance if the entire stream network was considered.

A neighbourhood evolving network model

International Nuclear Information System (INIS)

Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

2006-01-01

Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

The ecology and biogeochemistry of stream biofilms.

Science.gov (United States)

Battin, Tom J; Besemer, Katharina; Bengtsson, Mia M; Romani, Anna M; Packmann, Aaron I

2016-04-01

Streams and rivers form dense networks, shape the Earth's surface and, in their sediments, provide an immensely large surface area for microbial growth. Biofilms dominate microbial life in streams and rivers, drive crucial ecosystem processes and contribute substantially to global biogeochemical fluxes. In turn, water flow and related deliveries of nutrients and organic matter to biofilms constitute major constraints on microbial life. In this Review, we describe the ecology and biogeochemistry of stream biofilms and highlight the influence of physical and ecological processes on their structure and function. Recent advances in the study of biofilm ecology may pave the way towards a mechanistic understanding of the effects of climate and environmental change on stream biofilms and the biogeochemistry of stream ecosystems.

Symbol-stream Combiner: Description and Demonstration Plans

Science.gov (United States)

Hurd, W. J.; Reder, L. J.; Russell, M. D.

1984-01-01

A system is described and demonstration plans presented for antenna arraying by symbol stream combining. This system is used to enhance the signal-to-noise ratio of a spacecraft signals by combining the detected symbol streams from two or more receiving stations. Symbol stream combining has both cost and performance advantages over other arraying methods. Demonstrations are planned on Voyager 2 both prior to and during Uranus encounter. Operational use is possible for interagency arraying of non-Deep Space Network stations at Neptune encounter.

Method and means for filtering polychlorinated biphenyls from a gas stream

International Nuclear Information System (INIS)

Sowinski, R.F.

1992-01-01

This patent describes a method of filtering, adjacent to an end user-customer's residence or business in which at least a single gas appliance is located, a natural gas stream in which polychlorinated biphenyls (PCB's) and degraded PCB products have been concentrated at sufficient levels to be a health threat in a natural gas gathering and distributing network. It comprises: introducing the natural gas stream to a filter selected from a group that includes impingement, absorbing and adsorbing media whereby PCB's and degraded PCB products concentrated in the gas stream at sufficient levels to be a health threat by a periodic loading of the natural gas within the gathering and distributing network, are filtered from the gas stream and captured irrespective of mode of transport, passing the filtered natural gas stream to the customer's gas appliance wherein safe use of the energy associated with the stream occurs; periodically and safely removing the filter, inserting a new filter in place of the removed filter

Stream temperature investigations: field and analytic methods

Science.gov (United States)

Bartholow, J.M.

1989-01-01

This document provides guidance to the user of the U.S. Fish and Wildlife Service’s Stream Network Temperature Model (SNTEMP). Planning a temperature study is discussed in terms of understanding the management objectives and ensuring that the questions will be accurately answered with the modeling approach being used. A sensitivity analysis of SNTEMP is presented to illustrate which input variables are most important in predicting stream temperatures. This information helps prioritize data collection activities, highlights the need for quality control, focuses on which parameters can be estimated rather than measured, and offers a broader perspective on management options in terms of knowing where the biggest temperature response will be felt. All of the major input variables for stream geometry, meteorology, and hydrology are discussed in detail. Each variable is defined, with guidance given on how to measure it, what kind of equipment to use, where to obtain it from another agency, and how to calculate it if the data are in a form other than that required by SNTEMP. Examples are presented for the various forms in which water temperature, discharge, and meteorological data are commonly found. Ranges of values for certain input variables that are difficult to measure of estimate are given. Particular attention is given to those variables not commonly understood by field biologists likely to be involved in a stream temperature study. Pertinent literature is cited for each variable, with emphasis on how other people have treated particular problems and on results they have found.

Telecommunications network modelling, planning and design

CERN Document Server

Evans, Sharon

2003-01-01

Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.

Kinesthetic working memory and action control within the dorsal stream.

Science.gov (United States)

Fiehler, Katja; Burke, Michael; Engel, Annerose; Bien, Siegfried; Rösler, Frank

2008-02-01

There is wide agreement that the "dorsal (action) stream" processes visual information for movement control. However, movements depend not only on vision but also on tactile and kinesthetic information (=haptics). Using functional magnetic resonance imaging, the present study investigates to what extent networks within the dorsal stream are also utilized for kinesthetic action control and whether they are also involved in kinesthetic working memory. Fourteen blindfolded participants performed a delayed-recognition task in which right-handed movements had to be encoded, maintained, and later recognized without any visual feedback. Encoding of hand movements activated somatosensory areas, superior parietal lobe (dorsodorsal stream), anterior intraparietal sulcus (aIPS) and adjoining areas (ventrodorsal stream), premotor cortex, and occipitotemporal cortex (ventral stream). Short-term maintenance of kinesthetic information elicited load-dependent activity in the aIPS and adjacent anterior portion of the superior parietal lobe (ventrodorsal stream) of the left hemisphere. We propose that the action representation system of the dorsodorsal and ventrodorsal stream is utilized not only for visual but also for kinesthetic action control. Moreover, the present findings demonstrate that networks within the ventrodorsal stream, in particular the left aIPS and closely adjacent areas, are also engaged in working memory maintenance of kinesthetic information.

Multiobjective heat exchanger network synthesis based on grouping of process streams

Energy Technology Data Exchange (ETDEWEB)

Laukkanen, T.P.

2012-06-15

Heat exchanger network synthesis (HENS) is an important process synthesis problem and different tools and methods have been presented to solve this synthesis problem. This is mainly due to its importance in achieving energy savings in industrial processes in a cost-efficient way. The problem is also hard to solve and has been proven NP-hard (Nondeterministic Polynomial-time) and hence it is not known if a computationally efficient (polynomial) algorithm to solve the problem exists. Thus methods that provide good approximate solutions with reasonable computational requirements are useful. The objective of this thesis is to present new HENS approaches that are able to generate good solutions for HENS problems in a computationally efficient way so that all the objectives of HENS are optimized simultaneously. The main approach in accomplishing this objective is by grouping process streams. This is done either on the basis of the fact that in reality the process streams belong to a specific group or these groups are artificially developed. In the latter approach the idea is to decompose the set of binary variables i.e., the variables that define the existence of heat exchanger matches, into two separate problems. In this way the number of different options to connect the streams decreases compared to the situation where no decomposition is present. This causes the solution time to decrease and provides options for solving larger HENS problems. In this work the multiobjective HENS problem is solved either with the traditional weighting method or with an interactive multiobjective optimization method. In the weighting method the weights are the annual costs of the different objectives. In the interactive multiobjective optimization method the Decision Maker (DM) controls the decision-making process by classifying the objectives at each iteration. This multiobjective approach provides the benefit of using interactive multiobjective optimization, so that it is possible to

Cross-Layer Measurement on an IEEE 802.11g Wireless Network Supporting MPEG-2 Video Streaming Applications in the Presence of Interference

Directory of Open Access Journals (Sweden)

Alessandro Sona

2010-01-01

Full Text Available The performance of wireless local area networks supporting video streaming applications, based on MPEG-2 video codec, in the presence of interference is here dealt with. IEEE 802.11g standard wireless networks, that do not support QoS in according with IEEE 802.11e standard, are, in particular, accounted for and Bluetooth signals, additive white Gaussian noise, and competitive data traffic are considered as sources of interference. The goal is twofold: from one side, experimentally assessing and correlating the values that some performance metrics assume at the same time at different layers of an IEEE 802.11g WLAN delivering video streaming in the presence of in-channel interference; from the other side, deducing helpful and practical hints for designers and technicians, in order to efficiently assess and enhance the performance of an IEEE 802.11g WLAN supporting video streaming in some suitable setup conditions and in the presence of interference. To this purpose, an experimental analysis is planned following a cross-layer measurement approach, and a proper testbed within a semianechoic chamber is used. Valuable results are obtained in terms of signal-to-interference ratio, packet loss ratio, jitter, video quality, and interference data rate; helpful hints for designers and technicians are finally gained.

Modelling the Emergence and Dynamics of Perceptual Organisation in Auditory Streaming

Science.gov (United States)

Mill, Robert W.; Bőhm, Tamás M.; Bendixen, Alexandra; Winkler, István; Denham, Susan L.

2013-01-01

Many sound sources can only be recognised from the pattern of sounds they emit, and not from the individual sound events that make up their emission sequences. Auditory scene analysis addresses the difficult task of interpreting the sound world in terms of an unknown number of discrete sound sources (causes) with possibly overlapping signals, and therefore of associating each event with the appropriate source. There are potentially many different ways in which incoming events can be assigned to different causes, which means that the auditory system has to choose between them. This problem has been studied for many years using the auditory streaming paradigm, and recently it has become apparent that instead of making one fixed perceptual decision, given sufficient time, auditory perception switches back and forth between the alternatives—a phenomenon known as perceptual bi- or multi-stability. We propose a new model of auditory scene analysis at the core of which is a process that seeks to discover predictable patterns in the ongoing sound sequence. Representations of predictable fragments are created on the fly, and are maintained, strengthened or weakened on the basis of their predictive success, and conflict with other representations. Auditory perceptual organisation emerges spontaneously from the nature of the competition between these representations. We present detailed comparisons between the model simulations and data from an auditory streaming experiment, and show that the model accounts for many important findings, including: the emergence of, and switching between, alternative organisations; the influence of stimulus parameters on perceptual dominance, switching rate and perceptual phase durations; and the build-up of auditory streaming. The principal contribution of the model is to show that a two-stage process of pattern discovery and competition between incompatible patterns can account for both the contents (perceptual organisations) and the

Coldwater fish in wadeable streams [Chapter 8

Science.gov (United States)

Jason B. Dunham; Amanda E. Rosenberger; Russell F. Thurow; C. Andrew Dolloff; Philip J. Howell

2009-01-01

Small, wadeable streams comprise the majority of habitats available to fishes in fluvial networks. Wadeable streams are generally less than 1 m deep, and fish can be sampled without the use of water craft. Cold waters are defined as having mean 7-d summer maximum water temperatures of less than 20°C and providing habitat for coldwater fishes.

AMIDST: Analysis of MassIve Data STreams

DEFF Research Database (Denmark)

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.......0, also efficiently leverages existing functionalities and algorithms by interfacing to software tools such as HUGIN and MOA....

The role of headwater streams in downstream water quality

Science.gov (United States)

Alexander, R.B.; Boyer, E.W.; Smith, R.A.; Schwarz, G.E.; Moore, R.B.

2007-01-01

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and

Application of HEC-RAS water quality model to estimate contaminant spreading in small stream

Energy Technology Data Exchange (ETDEWEB)

Halaj, Peter; Bárek, Viliam; Halajová, Anna Báreková; Halajová, Denisa [Slovak University of Agriculture in Nitra, Nitra (Slovakia)

2013-07-01

The paper presents study of some aspects of HEC-RAS water quality model connected to simulation of contaminant transport in small stream. Authors mainly focused on one of the key tasks in process of pollutant transport modelling in streams - determination of the dispersion characteristics represented by longitudinal dispersion coefficient D. Different theoretical and empirical formulas have been proposed for D value determination and they have revealed that the coefficient is variable parameter that depends on hydraulic and morphometric characteristics of the stream reaches. Authors compare the results of several methods of coefficient D assessment, assuming experimental data obtained by tracer studies and compare them with results optimized by HEC-RAS water quality model. The analyses of tracer study and computation outputs allow us to outline the important aspects of longitudinal dispersion coefficient set up in process of the HEC-RAS model use. Key words: longitudinal dispersion coefficient, HEC-RAS, water quality modeling.

Layer-based buffer aware rate adaptation design for SHVC video streaming

Science.gov (United States)

Gudumasu, Srinivas; Hamza, Ahmed; Asbun, Eduardo; He, Yong; Ye, Yan

2016-09-01

This paper proposes a layer based buffer aware rate adaptation design which is able to avoid abrupt video quality fluctuation, reduce re-buffering latency and improve bandwidth utilization when compared to a conventional simulcast based adaptive streaming system. The proposed adaptation design schedules DASH segment requests based on the estimated bandwidth, dependencies among video layers and layer buffer fullness. Scalable HEVC video coding is the latest state-of-art video coding technique that can alleviate various issues caused by simulcast based adaptive video streaming. With scalable coded video streams, the video is encoded once into a number of layers representing different qualities and/or resolutions: a base layer (BL) and one or more enhancement layers (EL), each incrementally enhancing the quality of the lower layers. Such layer based coding structure allows fine granularity rate adaptation for the video streaming applications. Two video streaming use cases are presented in this paper. The first use case is to stream HD SHVC video over a wireless network where available bandwidth varies, and the performance comparison between proposed layer-based streaming approach and conventional simulcast streaming approach is provided. The second use case is to stream 4K/UHD SHVC video over a hybrid access network that consists of a 5G millimeter wave high-speed wireless link and a conventional wired or WiFi network. The simulation results verify that the proposed layer based rate adaptation approach is able to utilize the bandwidth more efficiently. As a result, a more consistent viewing experience with higher quality video content and minimal video quality fluctuations can be presented to the user.

Analytical Models of Exoplanetary Atmospheres. IV. Improved Two-stream Radiative Transfer for the Treatment of Aerosols

International Nuclear Information System (INIS)

Heng, Kevin; Kitzmann, Daniel

2017-01-01

We present a novel generalization of the two-stream method of radiative transfer, which allows for the accurate treatment of radiative transfer in the presence of strong infrared scattering by aerosols. We prove that this generalization involves only a simple modification of the coupling coefficients and transmission functions in the hemispheric two-stream method. This modification originates from allowing the ratio of the first Eddington coefficients to depart from unity. At the heart of the method is the fact that this ratio may be computed once and for all over the entire range of values of the single-scattering albedo and scattering asymmetry factor. We benchmark our improved two-stream method by calculating the fraction of flux reflected by a single atmospheric layer (the reflectivity) and comparing these calculations to those performed using a 32-stream discrete-ordinates method. We further compare our improved two-stream method to the two-stream source function (16 streams) and delta-Eddington methods, demonstrating that it is often more accurate at the order-of-magnitude level. Finally, we illustrate its accuracy using a toy model of the early Martian atmosphere hosting a cloud layer composed of carbon dioxide ice particles. The simplicity of implementation and accuracy of our improved two-stream method renders it suitable for implementation in three-dimensional general circulation models. In other words, our improved two-stream method has the ease of implementation of a standard two-stream method, but the accuracy of a 32-stream method.

Analytical Models of Exoplanetary Atmospheres. IV. Improved Two-stream Radiative Transfer for the Treatment of Aerosols

Energy Technology Data Exchange (ETDEWEB)

Heng, Kevin; Kitzmann, Daniel, E-mail: kevin.heng@csh.unibe.ch, E-mail: daniel.kitzmann@csh.unibe.ch [University of Bern, Center for Space and Habitability, Gesellschaftsstrasse 6, CH-3012, Bern (Switzerland)

2017-10-01

We present a novel generalization of the two-stream method of radiative transfer, which allows for the accurate treatment of radiative transfer in the presence of strong infrared scattering by aerosols. We prove that this generalization involves only a simple modification of the coupling coefficients and transmission functions in the hemispheric two-stream method. This modification originates from allowing the ratio of the first Eddington coefficients to depart from unity. At the heart of the method is the fact that this ratio may be computed once and for all over the entire range of values of the single-scattering albedo and scattering asymmetry factor. We benchmark our improved two-stream method by calculating the fraction of flux reflected by a single atmospheric layer (the reflectivity) and comparing these calculations to those performed using a 32-stream discrete-ordinates method. We further compare our improved two-stream method to the two-stream source function (16 streams) and delta-Eddington methods, demonstrating that it is often more accurate at the order-of-magnitude level. Finally, we illustrate its accuracy using a toy model of the early Martian atmosphere hosting a cloud layer composed of carbon dioxide ice particles. The simplicity of implementation and accuracy of our improved two-stream method renders it suitable for implementation in three-dimensional general circulation models. In other words, our improved two-stream method has the ease of implementation of a standard two-stream method, but the accuracy of a 32-stream method.

Biotic Responses of Headwater Streams to Geophysical Alteration and Disturbance Related to Climate Change

Science.gov (United States)

Gresswell, R. E.; Sedell, E. R.; Cannon, S.; Hostetler, S. W.; Williams, J. E.; Haak, A. L.; Kershner, J. L.

2009-12-01

Climate change will potentially alter physical habitat availability for trout species (both native and nonnative) in the western USA, and ultimately affect population distribution and abundance in watersheds across the region. To understand the biological consequences of habitat alteration associated with climate change, we have developed models linking contemporary patterns of occurrence and abundance to geomorphic variables (e.g., aspect, elevation, and slope) and stream conditions derived from the habitat (e.g., temperature, discharge, and flood regimes). Because headwater streams may be especially susceptible to catastrophic disturbances in the form of debris flow torrents that have the potential to radically alter the physical structure of channels and sometimes extirpate local fish populations, we are focusing fine-scale spatial analyses in the high elevation systems. Risks of such disturbances increase exponentially in landscapes that have experienced recent wildfires when high-intensity precipitation or runoff events occur. Although predicting the timing, extent, and severity of future wildfires or subsequent precipitation and runoff events is difficult, it is possible to identify channels within stream networks that may be prone to debris flows. These channels can be identified using models based on characteristic storm and burn scenarios and geographic information describing topographic, soil, and vegetation characteristics. At-risk channels are being mapped throughout the stream networks within the study areas in the headwaters of the Colorado River to provide information about the potential for catastrophic population disturbance in response to variety of wildfire and post-wildfire storm scenarios.

Coevolutionary modeling in network formation

KAUST Repository

Al-Shyoukh, Ibrahim

2014-12-03

Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

Coevolutionary modeling in network formation

KAUST Repository

Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.

2014-01-01

Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

Modeling Climate and Management Change Impacts on Water Quality and In-Stream Processes in the Elbe River Basin

Directory of Open Access Journals (Sweden)

Cornelia Hesse

2016-01-01

Full Text Available Eco-hydrological water quality modeling for integrated water resources management of river basins should include all necessary landscape and in-stream nutrient processes as well as possible changes in boundary conditions and driving forces for nutrient behavior in watersheds. The study aims to assess possible impacts of the changing climate (ENSEMBLES climate scenarios and/or land use conditions on resulting river water quantity and quality in the large-scale Elbe river basin by applying a semi-distributed watershed model of intermediate complexity (SWIM with implemented in-stream nutrient (N+P turnover and algal growth processes. The calibration and validation results revealed the ability of SWIM to satisfactorily simulate nutrient behavior at the watershed scale. Analysis of 19 climate scenarios for the whole Elbe river basin showed a projected increase in temperature (+3 °C and precipitation (+57 mm on average until the end of the century, causing diverse changes in river discharge (+20%, nutrient loads (NO3-N: −5%; NH4-N: −24%; PO4-P: +5%, phytoplankton biomass (−4% and dissolved oxygen concentration (−5% in the watershed. In addition, some changes in land use and nutrient management were tested in order to reduce nutrient emissions to the river network.

On the Validity of the Streaming Model for the Redshift-Space Correlation Function in the Linear Regime

Science.gov (United States)

Fisher, Karl B.

1995-08-01

The relation between the galaxy correlation functions in real-space and redshift-space is derived in the linear regime by an appropriate averaging of the joint probability distribution of density and velocity. The derivation recovers the familiar linear theory result on large scales but has the advantage of clearly revealing the dependence of the redshift distortions on the underlying peculiar velocity field; streaming motions give rise to distortions of θ(Ω0.6/b) while variations in the anisotropic velocity dispersion yield terms of order θ(Ω1.2/b2). This probabilistic derivation of the redshift-space correlation function is similar in spirit to the derivation of the commonly used "streaming" model, in which the distortions are given by a convolution of the real-space correlation function with a velocity distribution function. The streaming model is often used to model the redshift-space correlation function on small, highly nonlinear, scales. There have been claims in the literature, however, that the streaming model is not valid in the linear regime. Our analysis confirms this claim, but we show that the streaming model can be made consistent with linear theory provided that the model for the streaming has the functional form predicted by linear theory and that the velocity distribution is chosen to be a Gaussian with the correct linear theory dispersion.

A New Streamflow-Routing (SFR1) Package to Simulate Stream-Aquifer Interaction with MODFLOW-2000

Science.gov (United States)

Prudic, David E.; Konikow, Leonard F.; Banta, Edward R.

2004-01-01

The increasing concern for water and its quality require improved methods to evaluate the interaction between streams and aquifers and the strong influence that streams can have on the flow and transport of contaminants through many aquifers. For this reason, a new Streamflow-Routing (SFR1) Package was written for use with the U.S. Geological Survey's MODFLOW-2000 ground-water flow model. The SFR1 Package is linked to the Lake (LAK3) Package, and both have been integrated with the Ground-Water Transport (GWT) Process of MODFLOW-2000 (MODFLOW-GWT). SFR1 replaces the previous Stream (STR1) Package, with the most important difference being that stream depth is computed at the midpoint of each reach instead of at the beginning of each reach, as was done in the original Stream Package. This approach allows for the addition and subtraction of water from runoff, precipitation, and evapotranspiration within each reach. Because the SFR1 Package computes stream depth differently than that for the original package, a different name was used to distinguish it from the original Stream (STR1) Package. The SFR1 Package has five options for simulating stream depth and four options for computing diversions from a stream. The options for computing stream depth are: a specified value; Manning's equation (using a wide rectangular channel or an eight-point cross section); a power equation; or a table of values that relate flow to depth and width. Each stream segment can have a different option. Outflow from lakes can be computed using the same options. Because the wetted perimeter is computed for the eight-point cross section and width is computed for the power equation and table of values, the streambed conductance term no longer needs to be calculated externally whenever the area of streambed changes as a function of flow. The concentration of solute is computed in a stream network when MODFLOW-GWT is used in conjunction with the SFR1 Package. The concentration of a solute in a

Residence-time framework for modeling multicomponent reactive transport in stream hyporheic zones

Science.gov (United States)

Painter, S. L.; Coon, E. T.; Brooks, S. C.

2017-12-01

Process-based models for transport and transformation of nutrients and contaminants in streams require tractable representations of solute exchange between the stream channel and biogeochemically active hyporheic zones. Residence-time based formulations provide an alternative to detailed three-dimensional simulations and have had good success in representing hyporheic exchange of non-reacting solutes. We extend the residence-time formulation for hyporheic transport to accommodate general multicomponent reactive transport. To that end, the integro-differential form of previous residence time models is replaced by an equivalent formulation based on a one-dimensional advection dispersion equation along the channel coupled at each channel location to a one-dimensional transport model in Lagrangian travel-time form. With the channel discretized for numerical solution, the associated Lagrangian model becomes a subgrid model representing an ensemble of streamlines that are diverted into the hyporheic zone before returning to the channel. In contrast to the previous integro-differential forms of the residence-time based models, the hyporheic flowpaths have semi-explicit spatial representation (parameterized by travel time), thus allowing coupling to general biogeochemical models. The approach has been implemented as a stream-corridor subgrid model in the open-source integrated surface/subsurface modeling software ATS. We use bedform-driven flow coupled to a biogeochemical model with explicit microbial biomass dynamics as an example to show that the subgrid representation is able to represent redox zonation in sediments and resulting effects on metal biogeochemical dynamics in a tractable manner that can be scaled to reach scales.

A Coupled Model of the 1D River Network and 3D Estuary Based on Hydrodynamics and Suspended Sediment Simulation

Directory of Open Access Journals (Sweden)

Wei Zhang

2014-01-01

Full Text Available River networks and estuaries are very common in coastal areas. Runoff from the upper stream interacts with tidal current from open sea in these two systems, leading to a complex hydrodynamics process. Therefore, it is necessary to consider the two systems as a whole to study the flow and suspended sediment transport. Firstly, a 1D model is established in the Pearl River network and a 3D model is applied in its estuary. As sufficient mass exchanges between the river network and its estuary, a strict mathematical relationship of water level at the interfaces can be adopted to couple the 1D model with the 3D model. By doing so, the coupled model does not need to have common nested grids. The river network exchanges the suspended sediment with its estuary by adding the continuity conditions at the interfaces. The coupled model is, respectively, calibrated in the dry season and the wet season. The results demonstrate that the coupled model works excellently in simulating water level and discharge. Although there are more errors in simulating suspended sediment concentration due to some reasons, the coupled model is still good enough to evaluate the suspended sediment transport in river network and estuary systems.

Modeling online social signed networks

Science.gov (United States)

Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

2018-04-01

People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

MEKANISME SEGMENTASI LAJU BIT PADA DYNAMIC ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

Directory of Open Access Journals (Sweden)

Muhammad Audy Bazly

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

Modelling of a vanishing Hawaiin stream with DHSVM

NARCIS (Netherlands)

Verger, R.P.; Augustijn, Dionysius C.M.; Booij, Martijn J.; Fares, A.; Erdbrink, C.D.; van Os, A.G.

2008-01-01

Several Hawaiian streams show downward trends in stream flow. In this study Makaha Stream is investigated as an example. Three possible reasons are commonly mentioned for the discharge reduction: groundwater pumping, decreasing rainfall, and changes in vegetation. The effect of these factors on

Multi-scale streambed topographic and discharge effects on hyporheic at the stream network scale in confined streams

Science.gov (United States)

Alessandra Marzadri; Daniele Tonina; James A. McKean; Matthew G. Tiedemann; Rohan M. Benjankar

2014-01-01

The hyporheic zone is the volume of the streambed sediment mostly saturated with stream water. It is the transitional zone between stream and shallow-ground waters and an important ecotone for benthic species, including macro-invertebrates, microorganisms, and some fish species that dwell in the hyporheic zone for parts of their lives. Most hyporheic analyses are...

Bandwidth Estimation in Wireless Lans for Multimedia Streaming Services

Directory of Open Access Journals (Sweden)

Heung Ki Lee

2007-01-01

Full Text Available The popularity of multimedia streaming services via wireless networks presents major challenges in the management of network bandwidth. One challenge is to quickly and precisely estimate the available bandwidth for the decision of streaming rates of layered and scalable multimedia services. Previous studies based on wired networks are too burdensome to be applied to multimedia applications in wireless networks. In this paper, a new method, IdleGap, is suggested to estimate the available bandwidth of a wireless LAN based on the information from a low layer in the protocol stack. We use a network simulation tool, NS-2, to evaluate our new method with various ranges of cross-traffic and observation times. Our simulation results show that IdleGap accurately estimates the available bandwidth for all ranges of cross-traffic (100 Kbps ∼ 1 Mbps with a very short observation time of 10 seconds.

Thermodynamic analysis of an open cycle solid desiccant cooling system using Artificial Neural Network

International Nuclear Information System (INIS)

Koronaki, I.P.; Rogdakis, E.; Kakatsiou, T.

2012-01-01

Highlights: ► A neural network model based on experimental data was developed. ► Description of the experimental setup. ► Prediction of the state conditions of air at the process and regeneration stream. ► Sensitivity Analysis performed on these predicted results. ► Predicted output values in line with correlation model based on data from industry. - Abstract: This paper examines the performance of an installed open cycle air-conditioning system with a silica gel desiccant wheel which uses a conventional heat pump and heat exchangers for the improvement of the outlet air of the system. A neural network model based on the training of a black box model with experimental data was developed as a method based on experimental results predicting the state conditions of air at the process and regeneration stream. The model development was followed by a Sensitivity Analysis performed on these predicted results. The key parameters were the thermodynamic condition of process and regeneration air streams, the sensible heat factor of the room, and the mass air flow ratio of the regeneration and process streams. The results of this analysis revealed that all investigated parameters influenced the performance of the desiccant unit. Predicted output values of the proposed Neural Network Model for Desiccant Systems are in line with results from other correlation models based on the interpolation of experimental data obtained from industrial air conditioning installations.

Groundwater data improve modelling of headwater stream CO2 outgassing with a stable DIC isotope approach

Science.gov (United States)

Marx, Anne; Conrad, Marcus; Aizinger, Vadym; Prechtel, Alexander; van Geldern, Robert; Barth, Johannes A. C.

2018-05-01

A large portion of terrestrially derived carbon outgasses as carbon dioxide (CO2) from streams and rivers to the atmosphere. Particularly, the amount of CO2 outgassing from small headwater streams is highly uncertain. Conservative estimates suggest that they contribute 36 % (i.e. 0.93 petagrams (Pg) C yr-1) of total CO2 outgassing from all fluvial ecosystems on the globe. In this study, stream pCO2, dissolved inorganic carbon (DIC), and δ13CDIC data were used to determine CO2 outgassing from an acidic headwater stream in the Uhlířská catchment (Czech Republic). This stream drains a catchment with silicate bedrock. The applied stable isotope model is based on the principle that the 13C / 12C ratio of its sources and the intensity of CO2 outgassing control the isotope ratio of DIC in stream water. It avoids the use of the gas transfer velocity parameter (k), which is highly variable and mostly difficult to constrain. Model results indicate that CO2 outgassing contributed more than 80 % to the annual stream inorganic carbon loss in the Uhlířská catchment. This translated to a CO2 outgassing rate from the stream of 34.9 kg C m-2 yr-1 when normalised to the stream surface area. Large temporal variations with maximum values shortly before spring snowmelt and in summer emphasise the need for investigations at higher temporal resolution. We improved the model uncertainty by incorporating groundwater data to better constrain the isotope compositions of initial DIC. Due to the large global abundance of acidic, humic-rich headwaters, we underline the importance of this integral approach for global applications.

Streaming potential modeling in fractured rock: Insights into the identification of hydraulically active fractures

Science.gov (United States)

Roubinet, D.; Linde, N.; Jougnot, D.; Irving, J.

2016-05-01

Numerous field experiments suggest that the self-potential (SP) geophysical method may allow for the detection of hydraulically active fractures and provide information about fracture properties. However, a lack of suitable numerical tools for modeling streaming potentials in fractured media prevents quantitative interpretation and limits our understanding of how the SP method can be used in this regard. To address this issue, we present a highly efficient two-dimensional discrete-dual-porosity approach for solving the fluid flow and associated self-potential problems in fractured rock. Our approach is specifically designed for complex fracture networks that cannot be investigated using standard numerical methods. We then simulate SP signals associated with pumping conditions for a number of examples to show that (i) accounting for matrix fluid flow is essential for accurate SP modeling and (ii) the sensitivity of SP to hydraulically active fractures is intimately linked with fracture-matrix fluid interactions. This implies that fractures associated with strong SP amplitudes are likely to be hydraulically conductive, attracting fluid flow from the surrounding matrix.

Fate of acetone in an outdoor model stream in southern Mississippi, U.S.A.

Science.gov (United States)

Rathbun, R.E.; Stephens, D.W.; Shultz, D.J.; Tai, D.Y.

1988-01-01

The fate of acetone in water was investigated in an outdoor model stream located in southern Mississippi, U.S.A. Acetone was injected continuously for 32 days resulting in small milligram-perliter concentrations in the stream. Rhodamine-WT dye was injected at the beginning and at the end of the study to determine the time-of-travel and dispersion characteristics of the stream. A 12-h injection of t-butyl alcohol (TBA) was used to determine the volatilization characteristics of the stream. Volatilization controlled the acetone concentration in the stream. Significant bacterial degradation of acetone did not occur, contrary to expectations based on previous laboratory studies. Attempts to induce degradation of the acetone by injecting glucose and a nutrient solution containing bacteria acclimated to acetone were unsuccessful. Possible explanations for the lack of bacterial degradation included a nitrate limitation and a limited residence time in the stream system. ?? 1988.

Maximizing the model for Discounted Stream of Utility from ...

African Journals Online (AJOL)

Osagiede et al. (2009) considered an analytic model for maximizing discounted stream of utility from consumption when the rate of production is linear. A solution was provided to a level where methods of solving order differential equations will be applied, but they left off there, as a result of the mathematical complexity ...

Large-scale environmental controls on microbial biofilms in high-alpine streams

Directory of Open Access Journals (Sweden)

T. J. Battin

2004-01-01

Full Text Available Glaciers are highly responsive to global warming and important agents of landscape heterogeneity. While it is well established that glacial ablation and snowmelt regulate stream discharge, linkage among streams and streamwater geochemistry, the controls of these factors on stream microbial biofilms remain insufficiently understood. We investigated glacial (metakryal, hypokryal, groundwater-fed (krenal and snow-fed (rhithral streams - all of them representative for alpine stream networks - and present evidence that these hydrologic and hydrogeochemical factors differentially affect sediment microbial biofilms. Average microbial biomass and bacterial carbon production were low in the glacial streams, whereas bacterial cell size, biomass, and carbon production were higher in the tributaries, most notably in the krenal stream. Whole-cell in situ fluorescence hybridization revealed reduced detection rates of the Eubacteria and higher abundance of α-Proteobacteria in the glacial stream, a pattern that most probably reflects the trophic status of this ecosystem. Our data suggest low flow during the onset of snowmelt and autumn as a short period (hot moment of favorable environmental conditions with pulsed inputs of allochthonous nitrate and dissolved organic carbon, and with disproportionately high microbial growth. Tributaries are relatively more constant and favorable environments than kryal streams, and serve as possible sources of microbes and organic matter to the main glacial channel during periods (e.g., snowmelt of elevated hydrologic linkage among streams. Ice and snow dynamics - and their impact on the amount and composition of dissolved organic matter - have a crucial impact on stream biofilms, and we thus need to consider microbes and critical hydrological episodes in future models of alpine stream communities.

A simple metric to predict stream water quality from storm runoff in an urban watershed.

Science.gov (United States)

Easton, Zachary M; Sullivan, Patrick J; Walter, M Todd; Fuka, Daniel R; Petrovic, A Martin; Steenhuis, Tammo S

2010-01-01

The contribution of runoff from various land uses to stream channels in a watershed is often speculated and used to underpin many model predictions. However, these contributions, often based on little or no measurements in the watershed, fail to appropriately consider the influence of the hydrologic location of a particular landscape unit in relation to the stream network. A simple model was developed to predict storm runoff and the phosphorus (P) status of a perennial stream in an urban watershed in New York State using the covariance structure of runoff from different landscape units in the watershed to predict runoff in time. One hundred and twenty-seven storm events were divided into parameterization (n = 85) and forecasting (n = 42) data sets. Runoff, dissolved P (DP), and total P (TP) were measured at nine sites distributed among three land uses (high maintenance, unmaintained, wooded), three positions in the watershed (near the outlet, midwatershed, upper watershed), and in the stream at the watershed outlet. The autocorrelation among runoff and P concentrations from the watershed landscape units (n = 9) and the covariance between measurements from the landscape units and measurements from the stream were calculated and used to predict the stream response. Models, validated using leave-one-out cross-validation and a forecasting method, were able to correctly capture temporal trends in streamflow and stream P chemistry (Nash-Sutcliffe efficiencies, 0.49-0.88). The analysis suggests that the covariance structure was consistent for all models, indicating that the physical processes governing runoff and P loss from these landscape units were stationary in time and that landscapes located in hydraulically active areas have a direct hydraulic link to the stream. This methodology provides insight into the impact of various urban landscape units on stream water quantity and quality.

Microbial and Organic Fine Particle Transport Dynamics in Streams - a Combined Experimental and Stochastic Modeling Approach

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Drummond, Jen; Davies-Colley, Rob; Stott, Rebecca; Sukias, James; Nagels, John; Sharp, Alice; Packman, Aaron

2014-05-01

Transport dynamics of microbial cells and organic fine particles are important to stream ecology and biogeochemistry. Cells and particles continuously deposit and resuspend during downstream transport owing to a variety of processes including gravitational settling, interactions with in-stream structures or biofilms at the sediment-water interface, and hyporheic exchange and filtration within underlying sediments. Deposited cells and particles are also resuspended following increases in streamflow. Fine particle retention influences biogeochemical processing of substrates and nutrients (C, N, P), while remobilization of pathogenic microbes during flood events presents a hazard to downstream uses such as water supplies and recreation. We are conducting studies to gain insights into the dynamics of fine particles and microbes in streams, with a campaign of experiments and modeling. The results improve understanding of fine sediment transport, carbon cycling, nutrient spiraling, and microbial hazards in streams. We developed a stochastic model to describe the transport and retention of fine particles and microbes in rivers that accounts for hyporheic exchange and transport through porewaters, reversible filtration within the streambed, and microbial inactivation in the water column and subsurface. This model framework is an advance over previous work in that it incorporates detailed transport and retention processes that are amenable to measurement. Solute, particle, and microbial transport were observed both locally within sediment and at the whole-stream scale. A multi-tracer whole-stream injection experiment compared the transport and retention of a conservative solute, fluorescent fine particles, and the fecal indicator bacterium Escherichia coli. Retention occurred within both the underlying sediment bed and stands of submerged macrophytes. The results demonstrate that the combination of local measurements, whole-stream tracer experiments, and advanced modeling

Artificial Neural Network Models for Long Lead Streamflow Forecasts using Climate Information

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Kumar, J.; Devineni, N.

2007-12-01

Information on season ahead stream flow forecasts is very beneficial for the operation and management of water supply systems. Daily streamflow conditions at any particular reservoir primarily depend on atmospheric and land surface conditions including the soil moisture and snow pack. On the other hand recent studies suggest that developing long lead streamflow forecasts (3 months ahead) typically depends on exogenous climatic conditions particularly Sea Surface Temperature conditions (SST) in the tropical oceans. Examples of some oceanic variables are El Nino Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Identification of such conditions that influence the moisture transport into a given basin poses many challenges given the nonlinear dependency between the predictors (SST) and predictand (stream flows). In this study, we apply both linear and nonlinear dependency measures to identify the predictors that influence the winter flows into the Neuse basin. The predictor identification approach here adopted uses simple correlation coefficients to spearman rank correlation measures for detecting nonlinear dependency. All these dependency measures are employed with a lag 3 time series of the high flow season (January - February - March) using 75 years (1928-2002) of stream flows recorded in to the Falls Lake, Neuse River Basin. Developing streamflow forecasts contingent on these exogenous predictors will play an important role towards improved water supply planning and management. Recently, the soft computing techniques, such as artificial neural networks (ANNs) have provided an alternative method to solve complex problems efficiently. ANNs are data driven models which trains on the examples given to it. The ANNs functions as universal approximators and are non linear in nature. This paper presents a study aiming towards using climatic predictors for 3 month lead time streamflow forecast. ANN models representing the physical process of the system are

Statistical Models for Social Networks

NARCIS (Netherlands)

Snijders, Tom A. B.; Cook, KS; Massey, DS

2011-01-01

Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

Agent-based modeling and network dynamics

CERN Document Server

Namatame, Akira

2016-01-01

The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

Modeling Epidemic Network Failures

DEFF Research Database (Denmark)

Ruepp, Sarah Renée; Fagertun, Anna Manolova

2013-01-01

This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

Integrating the pulse of the riverscape and landscape: modelling stream metabolism using continuous dissolved oxygen measurements

Science.gov (United States)