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Journal articles on the topic 'Storm sewers – Data processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Russo, Beniamino, David Sunyer, Marc Velasco, and Slobodan Djordjević. "Analysis of extreme flooding events through a calibrated 1D/2D coupled model: the case of Barcelona (Spain)." Journal of Hydroinformatics 17, no. 3 (2014): 473–91. http://dx.doi.org/10.2166/hydro.2014.063.

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This paper presents the results of a calibrated 1D/2D coupled model simulating surface and sewer flows in Barcelona. The model covers 44 km2 of the city land involving 241 km of sewers. It was developed in order to assess the flood hazard in the Raval district, historically affected by flooding during heavy rainfalls. Special attention was paid to the hydraulic characterization of the inlet systems (representing the interface between surface and underground flows), through experimental expressions used to estimate the effective runoff flows into the sewers in case of storms. A 2D unstructured

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Métadier, M., and J. L. Bertrand-Krajewski. "From mess to mass: a methodology for calculating storm event pollutant loads with their uncertainties, from continuous raw data time series." Water Science and Technology 63, no. 3 (2011): 369–76. http://dx.doi.org/10.2166/wst.2011.230.

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With the increasing implementation of continuous monitoring of both discharge and water quality in sewer systems, large data bases are now available. In order to manage large amounts of data and calculate various variables and indicators of interest it is necessary to apply automated methods for data processing. This paper deals with the processing of short time step turbidity time series to estimate TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) event loads in sewer systems during storm events and their associated uncertainties. The following steps are described: (i) sensor cal

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Gong, N., X. Ding, T. Denoeux, J. L. Bertrand-Krajewski, and M. Clément. "Stormnet: a connectionist model for dynamic management of wastewater treatment plants during storm events." Water Science and Technology 33, no. 1 (1996): 247–56. http://dx.doi.org/10.2166/wst.1996.0024.

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Models for solid transport in sewers during storm events are increasingly used. An important application of these models is the management of treatment plants during storm events so as to improve the quality of receiving waters. However, a major difficulty that prevents more general use of these tools is their calibration, which requires field data, accurate information about catchments and sewers, and a specific methodology. For that reason, a connectionist model called STORMNET has been designed to reproduce and replace usual conceptual and deterministic models. This model requires fewer dat

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Schilperoort, Rémy, Holger Hoppe, Cornelis de Haan, and Jeroen Langeveld. "Searching for storm water inflows in foul sewers using fibre-optic distributed temperature sensing." Water Science and Technology 68, no. 8 (2013): 1723–30. http://dx.doi.org/10.2166/wst.2013.419.

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A major drawback of separate sewer systems is the occurrence of illicit connections: unintended sewer cross-connections that connect foul water outlets from residential or industrial premises to the storm water system and/or storm water outlets to the foul sewer system. The amount of unwanted storm water in foul sewer systems can be significant, resulting in a number of detrimental effects on the performance of the wastewater system. Efficient removal of storm water inflows into foul sewers requires knowledge of the exact locations of the inflows. This paper presents the use of distributed tem

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Gong, Ning, Thierry Denoeux, and Jean-Luc Bertrand-Krajewski. "Neural networks for solid transport modelling in sewer systems during storm events." Water Science and Technology 33, no. 9 (1996): 85–92. http://dx.doi.org/10.2166/wst.1996.0183.

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Models for solid transport in sewers during storm events are increasingly used by engineers and operators to improve their systems and the quality of receiving waters. However, a major difficulty that prevents more general use of these models is their calibration, which requires field data, accurate information about catchments and sewers, and a specific methodology. Therefore, research has been carried out to assess the ability of connectionist models to reproduce and replace usual models for use by an operator. Such models require fewer data, are self-calibrated, and very easy to use. The fi

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Pan, Gang, Bao Wang, Shuai Guo, Wenming Zhang, and Stephen Edwini-Bonsu. "Statistical analysis of sewer odour based on 10-year complaint data." Water Science and Technology 81, no. 6 (2020): 1221–30. http://dx.doi.org/10.2166/wst.2020.217.

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Abstract The City of Edmonton has been suffering from sewer odour problem for many years. Ten years of odour complaints data from 2008 to 2017 were statistically analyzed to identify major factors that relate to the odour problem. Spatial and temporal distributions of odour complaints in the city were first presented. Then relationships between the complaints and physical attributes of the sewer systems were analyzed by introducing a parameter of risk index. It was found that the snowmelt and storm events could possibly reduce odour complaints. Old sewer pipes and large drop structures are sta

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Ruan, Mingchaun, and Jan B. M. Wiggers. "Application of time-series analysis to urban storm drainage." Water Science and Technology 36, no. 5 (1997): 125–31. http://dx.doi.org/10.2166/wst.1997.0180.

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In urban storm drainage, deterministic models, such as SWMM, HydroWorks and MOUSE are commonly used. However, comprehensive research programmes, including field surveys, have indicated that most processes related to urban storm drainage have stochastic characteristic, like the occurrence of rainfall events, the processes of rainfall-runoff and flow routing in sewer networks3etc.. Particularly, sediments found in sewers either in suspension or in deposition, cannot be considered as having a unique entity. Inhomogeneity and randomness are just the nature of sewer sediment behaviour. Most data re

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Coghlan, Brian P., Richard M. Ashley, and George M. Smith. "Empirical equations for solids transport in combined sewers." Water Science and Technology 33, no. 9 (1996): 77–84. http://dx.doi.org/10.2166/wst.1996.0181.

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An investigation of the transport of solids in combined sewers during both dry weather flow (DWF) periods and storms is described. The study was based on data obtained from a number of sites in the combined sewer system of Dundee, Scotland. The relationship between hydraulic conditions in a combined sewer and the transport of solids in suspension was examined. The aim was to arrive at a methodology by which an appropriate model could be selected or developed which would predict solids transport rates given information on hydraulic conditions. It was found that for individual sites, site-specif

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Arthur, S., and R. M. Ashley. "The influence of near bed solids transport on first foul flush in combined sewers." Water Science and Technology 37, no. 1 (1998): 131–38. http://dx.doi.org/10.2166/wst.1998.0032.

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The problems associated with deposited sediments in sewers, and their transport through sewer systems have been the subject of detailed fieldwork programmes in the UK, and elsewhere in Europe. Existing laboratory, and some field based research exercises have focused on the relatively small, discrete particles. It is clear, however, that combined sewer systems have inputs which comprise of a significant proportion of large organic solids (faecal and food wastes), as well as the finer range of particle sizes. The increased concern regarding CSO spills into the environment has fuelled the recent

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Delleur, J. W., and Y. Gyasi-Agyei. "Prediction of Suspended Solids in Urban Sewers by Transfer Function Model." Water Science and Technology 29, no. 1-2 (1994): 171–79. http://dx.doi.org/10.2166/wst.1994.0663.

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There is increasing concern about the sediments transported in urban storm sewers. Progress has been made on the measurement of suspended solids, and telemetry systems have been installed that permit remote access to flow, temperature and suspended solids concentration data. Using observations obtained in the main trunk sewer in Brussels, Belgium, a transfer function model for the prediction of suspended load concentration from temperature and discharge measurements was developed. This model is based on the transfer function methodology developed by Box and Jenkins. It is shown that the transf

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Murodov, P., O. Amirov, and P. Khuzhaev. "Cleaning the Kafirnigan River From Sewage Pollution." Bulletin of Science and Practice 6, no. 11 (2020): 126–31. http://dx.doi.org/10.33619/2414-2948/60/13.

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The influence of the discharged treated wastewater on the ecology of the Kafirnigan River is considered. The data on the current state of sewage treatment facilities in the city of Dushanbe are given and an assessment of the environmental efficiency of these treatment facilities is given. Preliminary calculations of costs for the construction of a new sewage treatment plant in Dushanbe have been made. The article is devoted to the current problem of cleaning storm sewers. It should be noted that storm water drainage, like wastewater, has a negative impact on the environment. Before the wastewa

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Yuan, Shao Guang, Yong Li Zhu, Guo Liang Zhou, and Ming Kun Wang. "Research on Dynamic Scheduling of Grid Monitoring Data Processing Tasks Based Storm." Applied Mechanics and Materials 651-653 (September 2014): 1051–55. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1051.

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Development of smart grid spawned the big data in electric power industry, the cloud computing platform provided the solution for the big data in electric power industry, it has a significant effect for batch jobs, but its real-time is not guaranteed. For the real-time problem of cloud computing platform, the Storm platform will be introduced to monitor the grid power. This paper studies the fair share scheduling algorithm under the Storm platform. It introduced the concept of Storm framework briefly, then, proposed the fair share scheduling algorithm according to the lack of current Storm sch

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Daliakopoulos, Ioannis N., and Ioannis K. Tsanis. "A weather radar data processing module for storm analysis." Journal of Hydroinformatics 14, no. 2 (2011): 332–44. http://dx.doi.org/10.2166/hydro.2011.118.

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A pre- and post-processing weather radar data module was developed in the Matlab suite of software with GIS data exchange abilities for storm event analysis. During pre-processing, each radar sweep is converted from spherical to Cartesian coordinates in the desired temporal and spatial resolution. The module's functionality in post processing includes radar data display, geo-referencing over GIS maps, data filtering with the Wiener filter and single or multiple sweep processing. The user can perform individual storm cell detection and tracking, resulting in the storm's average velocity and tra

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Hansen, R., T. Thøgersen, and F. Rogalla. "Comparing cost and process performance of activated sludge (AS) and biological aerated filters (BAF) over ten years of full sale operation." Water Science and Technology 55, no. 8-9 (2007): 99–106. http://dx.doi.org/10.2166/wst.2007.247.

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In the early 1990s, the Wastewater Treatment Plant (WWTP) of Frederikshavn, Denmark, was extended to meet new requirements for nutrient removal (8 mg/L TN, 1.5 mg TP/L) as well as to increase its average daily flow to 16,500 m3/d (4.5 MGD). As the most economical upgrade of the existing activated sludge (AS) plant, a parallel biological aerated filter (BAF) was selected, and started up in 1995. Running two full scale processes in parallel for over ten years on the same wastewater and treatment objectives enabled a direct comparison in relation to operating performance, costs and experience. Co

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Kim, Youngkuk, Siwoon Son, and Yang-Sae Moon. "SPMgr: Dynamic workflow manager for sampling and filtering data streams over Apache Storm." International Journal of Distributed Sensor Networks 15, no. 7 (2019): 155014771986220. http://dx.doi.org/10.1177/1550147719862206.

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In this article, we address dynamic workflow management for sampling and filtering data streams in Apache Storm. As many sensors generate data streams continuously, we often use sampling to choose some representative data or filtering to remove unnecessary data. Apache Storm is a real-time distributed processing platform suitable for handling large data streams. Storm, however, must stop the entire work when it changes the input data structure or processing algorithm as it needs to modify, redistribute, and restart the programs. In addition, for effective data processing, we often use Storm wi

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Zakšek, K., K. Čotar, T. Veljanovski, P. Pehani, and K. Oštir. "Topographic Correction Module at Storm (TC@Storm)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 721–28. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-721-2015.

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Different solar position in combination with terrain slope and aspect result in different illumination of inclined surfaces. Therefore, the retrieved satellite data cannot be accurately transformed to the spectral reflectance, which depends only on the land cover. The topographic correction should remove this effect and enable further automatic processing of higher level products. The topographic correction TC@STORM was developed as a module within the SPACE-SI automatic near-real-time image processing chain STORM. It combines physical approach with the standard Minnaert method. The total irra

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Mcllhatton, T. D., R. Sakrabani, R. M. Ashley, and R. Burrows. "Erosion mechanisms in combined sewers and the potential for pollutant release to receiving waters and water treatment plants." Water Science and Technology 45, no. 3 (2002): 61–69. http://dx.doi.org/10.2166/wst.2002.0055.

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The problems associated with solids in sewerage systems result in common difficulties such as blockages and flooding and the subsequent maintenance requirements have been well documented. Concerns regarding pollutant release have also been demonstrated, with the contribution from in-sewer solids to the quality of the flow during a storm event being especially significant. These events known as “foul flushes” in combined sewers typically occur in the initial period of storm flows, when the concentration of suspended sediments and other pollutants are significantly higher than at other times. Tr

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Lv, Jia-Ke, Yang Li, and Xuan Wang. "Log Data Real Time Analysis Using Big Data Analytic Framework with Storm and Hadoop." MATEC Web of Conferences 246 (2018): 03009. http://dx.doi.org/10.1051/matecconf/201824603009.

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The log data real-time processing platform which is built using Storm On YARN integrated MapReduce and Storm that use MapReduce to complete large-scale off-line data global knowledge extraction, sudden knowledge extraction of small-scale data in Kafka buffers through Storm, and continuous real-time calculation of streaming data in combination with global knowledge. We tested our technique with the well-known KDD99 CUP data set. The experimentation results prove the system to be effective and efficient.

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Zhang, Ziyu, Zitan Liu, Qingcai Jiang, Junshi Chen, and Hong An. "RDMA-Based Apache Storm for High-Performance Stream Data Processing." International Journal of Parallel Programming 49, no. 5 (2021): 671–84. http://dx.doi.org/10.1007/s10766-021-00696-0.

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Frehmann, T., T. Mietzel, R. Kutzner, B. Spengler, and W. F. Geiger. "Monitoring in inline storage sewers for stormwater treatment to determine efficiencies." Water Science and Technology 50, no. 11 (2004): 89–96. http://dx.doi.org/10.2166/wst.2004.0675.

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A special structure of combined sewer overflow tanks is the inline storage sewer with downstream discharge (SKU). This layout has the advantage that besides the sewer system, no other structures are required for storm water treatment. Consequently only very little space is required and compared to combined sewer overflow tanks, there is an enormous potential in reducing costs during construction. To investigate the efficiency of an inline storage sewer, a monitoring station was established in Dortmund-Scharnhorst, Germany. The monitoring station was in operation for a period of 2.5 years. With

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Cao, Huiyan, Chase Q. Wu, Liang Bao, Aiqin Hou, and Wei Shen. "Throughput optimization for Storm-based processing of stream data on clouds." Future Generation Computer Systems 112 (November 2020): 567–79. http://dx.doi.org/10.1016/j.future.2020.06.009.

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García, Juan T., and Joseph R. Harrington. "Fine Sediment Modeling During Storm-Based Events in the River Bandon, Ireland." Water 11, no. 7 (2019): 1523. http://dx.doi.org/10.3390/w11071523.

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The River Bandon located in County Cork (Ireland) has been time-continuously monitored by turbidity probes, as well as automatic and manual suspended sediment sampling. The current work evaluates three different models used to estimate the fine sediment concentration during storm-based events over a period of one year. The modeled suspended sediment concentration is compared with that measured at an event scale. Uncertainty indices are calculated and compared with those presented in the bibliography. An empirically-based model was used as a reference, as this model has been previously applied

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Hu, Xiling. "An Analysis on Task Migration Strategy of Big Data Streaming Storm Computing Framework for Distributed Processing." International Journal of Information System Modeling and Design 11, no. 4 (2020): 18–35. http://dx.doi.org/10.4018/ijismd.2020100102.

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In this modern era, a large volume of data is generated regularly, which needs to be processed for gaining profits of latent information. The processing of big data is composed of a challenge termed as communication overhead. In order to minimize communication overhead on the premise of various resource constraints, a task migration strategy under heterogeneous storm environment is proposed. The proposed strategy is based on the establishment and demonstration of storm resource constraint model, optimal communication overhead model, and task migration model. Where the source node selection alg

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Zhao, Jindong, Shouke Wei, Xuebin Wen, and Xiuqin Qiu. "Analysis and prediction of big stream data in real-time water quality monitoring system." Journal of Ambient Intelligence and Smart Environments 12, no. 5 (2020): 393–406. http://dx.doi.org/10.3233/ais-200571.

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Large scale real-time water quality monitoring system usually produces vast amounts of high frequency data, and it is difficult for traditional water quality monitoring system to process such large and high frequency data generated by wireless sensor network. A real-time processing and early warning system framework is proposed to solve this problem, Apache Storm is used as the big data processing platform, and Kafka message queue is applied to classify the sample data into several data streams so as to reserve the time series data property of a sensor. In storm platform, Daubechies Wavelet is

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Xiao, F., G. Y. K. Shea, M. S. Wong, and J. Campbell. "An automated and integrated framework for dust storm detection based on ogc web processing services." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2 (November 11, 2014): 151–56. http://dx.doi.org/10.5194/isprsarchives-xl-2-151-2014.

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Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing f

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Choi, Dojin, Hyeonwook Jeon, Jongtae Lim, Kyoungsoo Bok, and Jaesoo Yoo. "Dynamic Task Scheduling Scheme for Processing Real-Time Stream Data in Storm Environments." Applied Sciences 11, no. 17 (2021): 7942. http://dx.doi.org/10.3390/app11177942.

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Owing to the recent advancements in Internet of Things technology, social media, and mobile devices, real-time stream balancing processing systems are commonly used to process vast amounts of data generated in various media. In this paper, we propose a dynamic task scheduling scheme considering task deadlines and node resources. The proposed scheme performs dynamic scheduling using a heterogeneous cluster consisting of various nodes with different performances. Additionally, the loads of the nodes considering the task deadlines are balanced by different task scheduling based on three defined l

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Lacour, C., C. Joannis, M. C. Gromaire, and G. Chebbo. "Potential of turbidity monitoring for real time control of pollutant discharge in sewers during rainfall events." Water Science and Technology 59, no. 8 (2009): 1471–78. http://dx.doi.org/10.2166/wst.2009.169.

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Turbidity sensors can be used to continuously monitor the evolution of pollutant mass discharge. For two sites within the Paris combined sewer system, continuous turbidity, conductivity and flow data were recorded at one-minute time intervals over a one-year period. This paper is intended to highlight the variability in turbidity dynamics during wet weather. For each storm event, turbidity response aspects were analysed through different classifications. The correlation between classification and common parameters, such as the antecedent dry weather period, total event volume per impervious he

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Jafari, H., and A. A. Alesheikh. "DEVELOPING A SPATIAL PROCESSING SERVICE FOR AUTOMATIC CALCULATION OF STORM INUNDATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W4 (September 27, 2017): 389–94. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w4-389-2017.

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With the increase in urbanization, the surface of earth and its climate are changing. These changes resulted in more frequent floodingand storm inundation in urban areas. The challenges of flooding can be addressed through several computational procedures. Due to its numerous advantages, accessible web services can be chosen as a proper format for determining the storm inundation. Web services have facilitated the integration and interactivity of the web applications. Such services made the interaction between machines more feasible. Web services enable the heterogeneous software systems to co

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Li, Xiang, Beth Plale, Nithya Vijayakumar, Rahul Ramachandran, Sara Graves, and Helen Conover. "Real-time storm detection and weather forecast activation through data mining and events processing." Earth Science Informatics 1, no. 2 (2008): 49–57. http://dx.doi.org/10.1007/s12145-008-0010-7.

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Kahar, Gertrudis V., Abdul Wahid, and Hadi Imam Sutaji. "ANALISIS KEJADIAN BADAI MAGNETIK BERDASARKAN DATA VARIASI HARIAN MAGNETIK DI KOTA KUPANG." Jurnal Fisika : Fisika Sains dan Aplikasinya 3, no. 1 (2018): 12–20. http://dx.doi.org/10.35508/fisa.v3i1.589.

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ABSTRAK Telah dilakukan penelitian analisis kejadian badai magnetik di Kota Kupang bulan Oktober 2014 sampai bulan September 2016. Penelitian ini bertujuan untuk menentukan karateristik kejadian badai magnetik serta menentukan periode kemunculan badai magnetik di Kota Kupang. Pengolahan data dengan menggunakan Software Microsoft Excel untuk dibuat grafik data komponen magnet bumi terhadap waktu dan Software Matlab 2011 untuk penentuan periodesitas kejadian badai magnetik menggunakan transformasi fourier cepat (FFT). Berdasarkan hasil pengolahan data, karateristik kejadian badai magnetik

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Fais, Alessandra, Giuseppe Lettieri, Gregorio Procissi, Stefano Giordano, and Francesco Oppedisano. "Data Stream Processing for Packet-Level Analytics." Sensors 21, no. 5 (2021): 1735. http://dx.doi.org/10.3390/s21051735.

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One of the most challenging tasks for network operators is implementing accurate per-packet monitoring, looking for signs of performance degradation, security threats, and so on. Upon critical event detection, corrective actions must be taken to keep the network running smoothly. Implementing this mechanism requires the analysis of packet streams in a real-time (or close to) fashion. In a softwarized network context, Stream Processing Systems (SPSs) can be adopted for this purpose. Recent solutions based on traditional SPSs, such as Storm and Flink, can support the definition of general comple

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Scaratos, P. D. "Computer modeling of fecal coliform contamination of an urban estuarine system." Water Science and Technology 44, no. 7 (2001): 9–16. http://dx.doi.org/10.2166/wst.2001.0378.

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This study is focused on the investigation of the sources, distribution and fate of fecal coliform populations in the North Fork of the New River that flows through the City of Fort Lauderdale, Florida, USA. The dynamics of this brackish river are driven by weak tides, regulated freshwater discharges, overland runoff, storm water drainage from sewers, and groundwater exchange. Extensive field studies failed to document any alleged source(s) of contamination, including birds, domesticated and undomesticated mammals, humans, septic tank leakage, urban runoff, non-point discharges from agricultur

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Curtis, David C. "Use of Weather Surveillance Radars—88 Doppler Data in Hydrologic Modeling." Transportation Research Record: Journal of the Transportation Research Board 1647, no. 1 (1998): 61–66. http://dx.doi.org/10.3141/1647-08.

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Successful hydrologic modeling depends heavily on high-quality rainfall data sets. If hydrologists cannot determine what is coming into a watershed, there is little chance that any hydrologic model will accurately estimate what is coming out on a consistent basis. Hydrologists are frequently forced to use rainfall data sets derived from sparse rain gauge networks that poorly resolve critical rainfall features, leading to inadequate model results. Over the past several years, the modernizing National Weather Service, the Federal Aviation Administration, and the Department of Defense have instal

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Liu, Di, Ying Wang, and Lian Guang Liu. "Discussion on Power Grid Magnetic Storm Disaster Monitoring System Based on Cloud Computing." Advanced Materials Research 341-342 (September 2011): 641–45. http://dx.doi.org/10.4028/www.scientific.net/amr.341-342.641.

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The power grid storm disaster monitoring system involves power system data，geomagnetic data, satellite data and other earth space observation data. To solve such problems as the system's large quantity of data, storage and processing difficulties, using cloud computing in the system is putting forward. The basic concepts and the services of cloud computing are introduced first. From the aspects of the front-end data collection and communication methods to the background software data processing, the GIC (geomagnetically-induced current) monitoring system is showed. Then the issues of the conti

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Wu, Sheng Hang, Zhe Wang, Ming Yuan He, and Huai Lin Dong. "Large-Scale Text Clustering Based on Improved K-Means Algorithm in the Storm Platform." Applied Mechanics and Materials 543-547 (March 2014): 1913–16. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1913.

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With the web information dramatically increases, Distributed processing of mass data through a cluster have been the focus of research field. An efficient distributed algorithm is the determinant of the scalability and performance in data analyses. This dissertation firstly studies the operation mechanism of Storm, which is a simplified distributed and real-time computation platform. Based on the Storm platform, an improved K-Means algorithm which could be used for data intensive computing is designed and implemented. Finally, the experience results show that the K-Means clustering algorithm b

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Cho, Wonhyeong, Myeong-Seon Gil, Mi-Jung Choi, and Yang-Sae Moon. "Storm-based distributed sampling system for multi-source stream environment." International Journal of Distributed Sensor Networks 14, no. 11 (2018): 155014771881269. http://dx.doi.org/10.1177/1550147718812698.

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As a large amount of data streams occur rapidly in many recent applications such as social network service, Internet of Things, and smart factory, sampling techniques have attracted many attentions to handle such data streams efficiently. In this article, we address the performance improvement of binary Bernoulli sampling in the multi-source stream environment. Binary Bernoulli sampling has the n:1 structure where n sites transmit data to 1 coordinator. However, as the number of sites increases or the input stream explosively increases, the binary Bernoulli sampling may cause a severe bottlene

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Oštir, K., K. Čotar, A. Marsetič, et al. "Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 669–76. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-669-2015.

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In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. <br><br> Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model an

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Gad, M. A., and I. K. Tsanis. "A GIS methodology for the analysis of weather radar precipitation data." Journal of Hydroinformatics 5, no. 2 (2003): 113–26. http://dx.doi.org/10.2166/hydro.2003.0009.

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A GIS multi-component module was developed within the ArcView GIS environment for processing and analysing weather radar precipitation data. The module is capable of: (a) reading geo-reference radar data and comparing it with rain-gauge network data, (b) estimating the kinematics of rainfall patterns, such as the storm speed and direction, and (c) accumulating radar-derived rainfall depths. By bringing the spatial capabilities of GIS to bear this module can accurately locate rainfall on the ground and can overlay the animated storm on different geographical features of the study area, making t

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Podladchikova, Tatiana, Anatoly Petrukovich, and Yuri Yermolaev. "Geomagnetic storm forecasting service StormFocus: 5 years online." Journal of Space Weather and Space Climate 8 (2018): A22. http://dx.doi.org/10.1051/swsc/2018017.

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Forecasting geomagnetic storms is highly important for many space weather applications. In this study, we review performance of the geomagnetic storm forecasting service StormFocus during 2011–2016. The service was implemented in 2011 at SpaceWeather.Ru and predicts the expected strength of geomagnetic storms as measured by Dst index several hours ahead. The forecast is based on L1 solar wind and IMF measurements and is updated every hour. The solar maximum of cycle 24 is weak, so most of the statistics are on rather moderate storms. We verify quality of selection criteria, as well as reliabil

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BELOKI, ZUHAITZ, XABIER ARTOLA, and AITOR SOROA. "A scalable architecture for data-intensive natural language processing." Natural Language Engineering 23, no. 5 (2017): 709–31. http://dx.doi.org/10.1017/s1351324917000092.

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AbstractComputational power needs have greatly increased during the last years, and this is also the case in the Natural Language Processing (NLP) area, where thousands of documents must be processed, i.e., linguistically analyzed, in a reasonable time frame. These computing needs have implied a radical change in the computing architectures and big-scale text processing techniques used in NLP. In this paper, we present a scalable architecture for distributed language processing. The architecture uses Storm to combine diverse NLP modules into a processing chain, which carries out the linguistic

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Li, Guang Di, Guo Yin Wang, Xue Rui Zhang, Wei Hui Deng, and Fan Zhang. "Forest Cover Types Classification Based on Online Machine Learning on Distributed Cloud Computing Platforms of Storm and SAMOA." Advanced Materials Research 955-959 (June 2014): 3803–12. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.3803.

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Storm is the most popular realtime stream processing platform, which can be used to deal with online machine learning. Similar to how Hadoop provides a set of general primitives for doing batch processing, Storm provides a set of general primitives for doing realtime computation. SAMOA includes distributed algorithms for the most common machine learning tasks like Mahout for Hadoop. SAMOA is both a platform and a library. In this paper, Forest cover types, a large benchmaking dataset available at the UCI KDD Archive is used as the data stream source. Vertical Hoeffding Tree, a parallelizing st

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Wan, Jin Chang, and Tao Cheng. "Research on Multi-Agent and Storm-Hadoop Based on Cooperative Sensing Framework for Multiple Intelligent Manufacturing Agent." Applied Mechanics and Materials 864 (April 2017): 192–201. http://dx.doi.org/10.4028/www.scientific.net/amm.864.192.

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With the bottlenecks of traditional manufacturing technology becoming increasingly prominent, manufacturing industry need to adjust and upgrade the industrial structure, and intelligent manufacturing is the future development direction of manufacturing industry. According to the characteristics of complex, open system hierarchy structure and distributed multi agent of intelligent manufacturing, in order to solve the problem of information integration and collaborative processing of the organic elements of intelligent manufacturing collaborative perception process, it is necessary to give the a

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Rinas, Martin, Jens Tränckner, and Thilo Koegst. "Sediment Transport in Sewage Pressure Pipes, Part I: Continuous Determination of Settling and Erosion Characteristics by In-Situ TSS Monitoring Inside a Pressure Pipe in Northern Germany." Water 11, no. 10 (2019): 2125. http://dx.doi.org/10.3390/w11102125.

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Continuous measurement systems are widely spread in sewers, especially in non-pressure systems. Due to its relatively low costs, turbidity sensors are often used as a surrogate for other indicators (solids, heavy metals, organic compounds). However, little effort is spent to turbidity sensors in pressurized systems so far. This work presents the results of one year in-situ turbidity/total suspended solids (TSS) monitoring inside a pressure pipe (600 mm diameter) in an urban region in northern Germany. The high-resolution sensor data (5 s interval) are used for the determination of solids sedim

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Tscheikner-Gratl, Franz, Peter Zeisl, Carolina Kinzel, et al. "Lost in calibration: why people still do not calibrate their models, and why they still should – a case study from urban drainage modelling." Water Science and Technology 74, no. 10 (2016): 2337–48. http://dx.doi.org/10.2166/wst.2016.395.

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From a scientific point of view, it is unquestioned that numerical models for technical systems need to be calibrated. However, in sufficiently calibrated models are still used in engineering practice. Case studies in the scientific literature that deal with urban water management are mostly large cities, while little attention is paid to the differing boundary conditions of smaller municipalities. Consequently, the aim of this paper is to discuss the calibration of a hydrodynamic model of a small municipality (15,000 inhabitants). To represent the spatial distribution of precipitation, three

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Moura, P., S. Barraud, and M. Baptista. "Multicriteria procedure for the design and the management of infiltration systems." Water Science and Technology 55, no. 4 (2007): 145–53. http://dx.doi.org/10.2166/wst.2007.104.

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Infiltration systems are frequently used as an option to manage urban storm drainage. By reducing flows and volumes in downstream sewers or in surface waters, they decrease the overflows and make it possible to recharge groundwater. They come in various forms with different uses; therefore, their performance is diverse and integrates multiple aspects. Consequently, a multicriteria approach was developed in order to quantify the performance of these systems and to help in decision making problems. For that purpose, a list of performance indicators integrating technical, economical, environmenta

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Wu, Kehe, Yayun Zhu, Quan Li, and Ziwei Wu. "A distributed real-time data prediction framework for large-scale time-series data using stream processing." International Journal of Intelligent Computing and Cybernetics 10, no. 2 (2017): 145–65. http://dx.doi.org/10.1108/ijicc-09-2016-0033.

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Purpose The purpose of this paper is to propose a data prediction framework for scenarios which require forecasting demand for large-scale data sources, e.g., sensor networks, securities exchange, electric power secondary system, etc. Concretely, the proposed framework should handle several difficult requirements including the management of gigantic data sources, the need for a fast self-adaptive algorithm, the relatively accurate prediction of multiple time series, and the real-time demand. Design/methodology/approach First, the autoregressive integrated moving average-based prediction algori

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Brown, Tanya M., William H. Pogorzelski, and Ian M. Giammanco. "Evaluating Hail Damage Using Property Insurance Claims Data." Weather, Climate, and Society 7, no. 3 (2015): 197–210. http://dx.doi.org/10.1175/wcas-d-15-0011.1.

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Abstract A series of thunderstorms on 24 May 2011 produced significant hail in the Dallas–Fort Worth (DFW) metroplex, resulting in an estimated $876.8 million (U.S. dollars) in insured losses to property and automobiles, according to the Texas Department of Insurance. Insurance claims and policy-in-force data were obtained from five insurance companies for more than 67 000 residential properties located in 20 ZIP codes. The methodology for selecting the 20 ZIP codes is described. This study evaluates roofing material type with regard to resiliency to hailstone impacts and relative damage costs

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Bartolini, Ilaria, and Marco Patella. "Real-Time Stream Processing in Social Networks with RAM3S." Future Internet 11, no. 12 (2019): 249. http://dx.doi.org/10.3390/fi11120249.

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The avalanche of (both user- and device-generated) multimedia data published in online social networks poses serious challenges to researchers seeking to analyze such data for many different tasks, like recommendation, event recognition, and so on. For some such tasks, the classical “batch” approach of big data analysis is not suitable, due to constraints of real-time or near-real-time processing. This led to the rise of stream processing big data platforms, like Storm and Flink, that are able to process data with a very low latency. However, this complicates the task of data analysis since an

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Wang, Wenjuan, and Hongchun Yuan. "A Tidal Level Prediction Approach Based on BP Neural Network and Cubic B-Spline Curve with Knot Insertion Algorithm." Mathematical Problems in Engineering 2018 (July 11, 2018): 1–9. http://dx.doi.org/10.1155/2018/9835079.

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Tide levels depend on both long-term astronomical effects that are mainly affected by moon and sun and short-term meteorological effects generated by severe weather conditions like storm surge. Storm surge caused by typhoons will impose serious security risks and threats on the coastal residents’ safety in production, property, and life. Due to the challenges of nonperiodic and incontinuous tidal level record data and the influence of multimeteorological factors, the existing methods cannot predict the tide levels affected by typhoons precisely. This paper targets to explore a more advanced me

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Yovan Felix, A., G. S. S. Vinay, and G. Akhik. "K-Means Cluster Using Rainfall and Storm Prediction in Machine Learning Technique." Journal of Computational and Theoretical Nanoscience 16, no. 8 (2019): 3265–69. http://dx.doi.org/10.1166/jctn.2019.8174.

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Data Mining involves extracting meaningful information from the available data in a user understandable manner. Its role is to analyze voluminous data that is being often assembled. Using the approach of Data mining techniques various business related queries can be attended which formerly were extremely time-consuming to answer. There exist uncontrollable natural disasters that critically hampers and costs human life, environment and revenue material. Natural calamities like heavy rainfall and floods cannot be well predicted until it happens, also it’s beyond one’s power to control them. The

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