Delivering Sustainable Water Systems Using Kalman Filter and Statistical Approach

2017 ◽  
Vol 4 (1) ◽  
pp. 41-52
Author(s):  
Dedy Loebis
Keyword(s):  
Kalman Filtering ◽  
Statistical Approach ◽  
Water Systems ◽  
Data Sets ◽  
Pressure Data ◽  
Burst Event ◽  
Sample Data ◽  
Other Information ◽  
Supply Systems ◽  
Frequency Features

This paper presents the results of work undertaken to develop and test contrasting data analysis approaches for the detection of bursts/leaks and other anomalies within wate r supply systems at district meter area (DMA)level. This was conducted for Yorkshire Water (YW) sample data sets from the Harrogate and Dales (H&D), Yorkshire, United Kingdom water supply network as part of Project NEPTUNE EP/E003192/1 ). A data analysissystem based on Kalman filtering and statistical approach has been developed. The system has been applied to the analysis of flow and pressure data. The system was proved for one dataset case and have shown the ability to detect anomalies in flow and pres sure patterns, by correlating with other information. It will be shown that the Kalman/statistical approach is a promising approach at detecting subtle changes and higher frequency features, it has the potential to identify precursor features and smaller l eaks and hence could be useful for monitoring the development of leaks, prior to a large volume burst event.

Full-Coverage Film Cooling—Part II: Heat Transfer Data and Numerical Simulation

1980 ◽  
Vol 102 (4) ◽  
pp. 1006-1012 ◽  
Author(s):  
M. E. Crawford ◽  
W. M. Kays ◽  
R. J. Moffat
Keyword(s):  
Heat Transfer ◽  
Film Cooling ◽  
Numerical Procedure ◽  
Stanton Number ◽  
Data Sets ◽  
Blowing Ratio ◽  
Diameter Hole ◽  
Full Coverage ◽  
Sample Data ◽  
Length Data

Experimental research into heat transfer from full-coverage film-cooled surfaces with three injection geometries was described in Part I. This part has two objectives. The first is to present a simple numerical procedure for simulation of heat transfer with full-coverage film cooling. The second objective is to present some of the Stanton number data that was used in Part I of the paper. The data chosen for presentation are the low-Reynolds number, heated-starting-length data for the three injection geometries with five-diameter hole spacing. Sample data sets with high blowing ratio and with ten-diameter hole spacing are also presented. The numerical procedure has been successfully applied to the Stanton number data sets.

International standards for services activities relating to drinking water supply systems and wastewater systems: Implications for developing countries

2006 ◽  
Vol 53 (6) ◽  
pp. 75-82
Author(s):  
S. Lee ◽  
D. Cha ◽  
H. Park
Keyword(s):  
Developing Countries ◽  
Drinking Water ◽  
Water Systems ◽  
International Standards ◽  
Water Supply Systems ◽  
System Quality ◽  
Wastewater Systems ◽  
Service Standards ◽  
Supply Systems

In developing countries, the PPP (Public–Private–Partnerships) programs have been unsatisfied during the last decade. This study analyzed one of the main causes is low quality of the system. That is, no matter what supports developing countries may get through PPP, reforming water systems can be hardly successful without appropriate system quality. With this background, this study introduces service standards of ISO/TC 224 as an option to improve system quality of developing countries. To analyze its effects, system dynamic modeling was conducted. The results indicated that service standards, working with the PPP programs, can benefit all the stakeholders involved in the water systems in developing countries. Also this indicates further that this approach with service standards deserves more detailed study for improving the ailing water systems in developing countries.

Stamping Plant 4.0 – Basics for the Application of Data Mining Methods in Manufacturing Car Body Parts

2015 ◽  
Vol 639 ◽  
pp. 21-30 ◽  
Author(s):  
Stephan Purr ◽  
Josef Meinhardt ◽  
Arnulf Lipp ◽  
Axel Werner ◽  
Martin Ostermair ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Acquisition ◽  
Data Driven ◽  
Quality Analysis ◽  
Process Conditions ◽  
Data Sets ◽  
Body Parts ◽  
Car Body ◽  
Sample Data ◽  
Mining Methods

Data-driven quality evaluation in the stamping process of car body parts is quite promising because dependencies in the process have not yet been sufficiently researched. However, the application of data mining methods for the process in stamping plants would require a large number of sample data sets. Today, acquiring these data represents a major challenge, because the necessary data are inadequately measured, recorded or stored. Thus, the preconditions for the sample data acquisition must first be created before being able to investigate any correlations. In addition, the process conditions change over time due to wear mechanisms. Therefore, the results do not remain valid and a constant data acquisition is required. In this publication, the current situation in stamping plants regarding the process robustness will be first discussed and the need for data-driven methods will be shown. Subsequently, the state of technology regarding the possibility of collecting the sample data sets for quality analysis in producing car body parts will be researched. At the end of this work, an overview will be provided concerning how this data collection was implemented at BMW as well as what kind of potential can be expected.

scholarly journals Bayesian Classification of Microbial Communities Based on 16S rRNA Metagenomic Data

2018 ◽  
Author(s):  
Arghavan Bahadorinejad ◽  
Ivan Ivanov ◽  
Johanna W Lampe ◽  
Meredith AJ Hullar ◽  
Robert S Chapkin ◽  
...  
Keyword(s):  
16S Rrna ◽  
Sample Size ◽  
Microbial Communities ◽  
State Of The Art ◽  
Metagenomic Data ◽  
Data Sets ◽  
Sequencing Data ◽  
Sample Data

AbstractWe propose a Bayesian method for the classification of 16S rRNA metagenomic profiles of bacterial abundance, by introducing a Poisson-Dirichlet-Multinomial hierarchical model for the sequencing data, constructing a prior distribution from sample data, calculating the posterior distribution in closed form; and deriving an Optimal Bayesian Classifier (OBC). The proposed algorithm is compared to state-of-the-art classification methods for 16S rRNA metagenomic data, including Random Forests and the phylogeny-based Metaphyl algorithm, for varying sample size, classification difficulty, and dimensionality (number of OTUs), using both synthetic and real metagenomic data sets. The results demonstrate that the proposed OBC method, with either noninformative or constructed priors, is competitive or superior to the other methods. In particular, in the case where the ratio of sample size to dimensionality is small, it was observed that the proposed method can vastly outperform the others.Author summaryRecent studies have highlighted the interplay between host genetics, gut microbes, and colorectal tumor initiation/progression. The characterization of microbial communities using metagenomic profiling has therefore received renewed interest. In this paper, we propose a method for classification, i.e., prediction of different outcomes, based on 16S rRNA metagenomic data. The proposed method employs a Bayesian approach, which is suitable for data sets with small ration of number of available instances to the dimensionality. Results using both synthetic and real metagenomic data show that the proposed method can outperform other state-of-the-art metagenomic classification algorithms.

scholarly journals What Your Tweets Tell Us About You: Identity, Ownership and Privacy of Twitter Data

2012 ◽  
Vol 7 (1) ◽  
pp. 174-197 ◽  
Author(s):  
Heather Small ◽  
Kristine Kasianovitz ◽  
Ronald Blanford ◽  
Ina Celaya
Keyword(s):  
Social Media ◽  
Social Networking Sites ◽  
Data Sets ◽  
Data Set ◽  
Social Media Data ◽  
Twitter Data ◽  
Other Information ◽  
Rich Data ◽  
Additional Value ◽  
Media Data

Social networking sites and other social media have enabled new forms of collaborative communication and participation for users, and created additional value as rich data sets for research. Research based on accessing, mining, and analyzing social media data has risen steadily over the last several years and is increasingly multidisciplinary; researchers from the social sciences, humanities, computer science and other domains have used social media data as the basis of their studies. The broad use of this form of data has implications for how curators address preservation, access and reuse for an audience with divergent disciplinary norms related to privacy, ownership, authenticity and reliability.In this paper, we explore how the characteristics of the Twitter platform, coupled with an ambiguous and evolving understanding of privacy in networked communication, and divergent disciplinary understandings of the resulting data, combine to create complex issues for curators trying to ensure broad-based and ethical reuse of Twitter data. We provide a case study of a specific data set to illustrate how data curators can engage with the topics and questions raised in the paper. While some initial suggestions are offered to librarians and other information professionals who are beginning to receive social media data from researchers, our larger goal is to stimulate discussion and prompt additional research on the curation and preservation of social media data.

scholarly journals First reported isolation of an emerging opportunistic pathogen (Elizabethkingia anophelis) from hospital water systems in Greece

2017 ◽  
Vol 16 (1) ◽  
pp. 164-170 ◽  
Author(s):  
Maria A. Kyritsi ◽  
Varvara A. Mouchtouri ◽  
Spyros Pournaras ◽  
Christos Hadjichristodoulou
Keyword(s):  
Water Supply ◽  
Water Samples ◽  
Opportunistic Pathogen ◽  
Water Systems ◽  
Water Supply Systems ◽  
Northern Greece ◽  
Active Search ◽  
Three Samples ◽  
Supply Systems

Abstract After the Elizabethkingia anophelis outbreak in Wisconsin, USA, an active search for the detection of the microorganism in hospital water systems from Central and Northern Greece was performed from June to December 2016. In total, 457 water samples from 11 hospitals were analyzed. Elizabethkingia spp. was detected in three samples collected from two hospitals, both of which are located in Northern Greece. Two of the three isolated strains were identified as Elizabethkingia anophelis. No cases of Elizabethkingia infection were reported in either hospital during 2016. This is the first reported isolation of the pathogen in water supply systems in Greece.

scholarly journals Highly accurate long-read HiFi sequencing data for five complex genomes

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Ting Hon ◽  
Kristin Mars ◽  
Greg Young ◽  
Yu-Chih Tsai ◽  
Joseph W. Karalius ◽  
...  
Keyword(s):  
Sequence Data ◽  
Genome Structure ◽  
Data Sets ◽  
Sequencing Data ◽  
Complex Samples ◽  
Bioinformatic Tools ◽  
Long Reads ◽  
Sequencing Method ◽  
Sample Data ◽  
Long Read

AbstractThe PacBio® HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10–25 kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomes Mus musculus and Zea mays, as well as two complex genomes, octoploid Fragaria × ananassa and the diploid anuran Rana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System.

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