Rank Full Journal Title Impact Factor 1 CA-A CANCER JOURNAL FOR

Total Page:16

File Type:pdf, Size:1020Kb

Rank Full Journal Title Impact Factor 1 CA-A CANCER JOURNAL FOR Journal Data Filtered By: Selected JCR Year: 2018 Selected Editions: SCIE,SSCI Selected Category Scheme: WoS Impact Rank Full Journal Title Total Cites Factor 1 CA-A CANCER JOURNAL FOR CLINICIANS 32,410 223.679 2 Nature Reviews Materials 7,901 74.449 3 NEW ENGLAND JOURNAL OF MEDICINE 344,581 70.670 4 LANCET 247,292 59.102 5 NATURE REVIEWS DRUG DISCOVERY 32,266 57.618 6 CHEMICAL REVIEWS 188,635 54.301 7 Nature Energy 11,113 54.000 8 NATURE REVIEWS CANCER 50,529 51.848 9 JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION 156,350 51.273 10 NATURE REVIEWS IMMUNOLOGY 41,499 44.019 11 NATURE REVIEWS GENETICS 36,697 43.704 12 NATURE REVIEWS MOLECULAR CELL BIOLOGY 45,869 43.351 13 NATURE 745,692 43.070 14 SCIENCE 680,994 41.037 15 CHEMICAL SOCIETY REVIEWS 139,751 40.443 16 NATURE MATERIALS 97,792 38.887 17 REVIEWS OF MODERN PHYSICS 50,151 38.296 18 CELL 242,829 36.216 19 LANCET ONCOLOGY 48,822 35.386 20 NATURE REVIEWS MICROBIOLOGY 29,637 34.648 21 Nature Reviews Clinical Oncology 9,626 34.106 22 World Psychiatry 5,426 34.024 22 World Psychiatry 5,426 34.024 24 Nature Nanotechnology 63,245 33.407 25 Energy & Environmental Science 81,176 33.250 26 NATURE REVIEWS NEUROSCIENCE 43,107 33.162 27 Annual Review of Astronomy and Astrophysics 11,821 33.069 28 Nature Reviews Disease Primers 4,339 32.274 29 NATURE BIOTECHNOLOGY 60,971 31.864 30 Nature Photonics 43,932 31.583 31 NATURE MEDICINE 79,243 30.641 32 Nature Reviews Chemistry 1,531 30.628 33 LANCET NEUROLOGY 30,748 28.755 34 NATURE METHODS 64,324 28.467 35 PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS 28,380 28.295 36 JOURNAL OF CLINICAL ONCOLOGY 154,029 28.245 37 Living Reviews in Relativity 2,819 27.778 38 BMJ-British Medical Journal 112,901 27.604 39 LANCET INFECTIOUS DISEASES 23,088 27.516 40 Annual Review of Biochemistry 20,344 26.922 41 PROGRESS IN ENERGY AND COMBUSTION SCIENCE 11,322 26.467 42 Cancer Discovery 13,715 26.370 43 ADVANCES IN PHYSICS 5,903 26.100 44 ADVANCED MATERIALS 229,186 25.809 45 NATURE GENETICS 93,920 25.455 46 Advanced Energy Materials 50,724 24.884 47 Nature Reviews Endocrinology 8,908 24.646 48 Lancet Diabetes & Endocrinology 7,961 24.540 49 PROGRESS IN POLYMER SCIENCE 26,152 24.505 50 Materials Today 12,566 24.372 51 PHYSIOLOGICAL REVIEWS 28,672 24.250 52 CANCER CELL 36,056 23.916 53 PROGRESS IN MATERIALS SCIENCE 14,580 23.725 54 Nature Reviews Gastroenterology & Hepatology 8,506 23.570 55 NATURE IMMUNOLOGY 44,298 23.530 56 EUROPEAN HEART JOURNAL 57,358 23.239 57 Nature Chemistry 32,858 23.193 58 CIRCULATION 166,484 23.054 59 Lancet Respiratory Medicine 7,600 22.992 60 IEEE Communications Surveys and Tutorials 16,408 22.973 61 JAMA Oncology 9,488 22.416 62 Cell Metabolism 34,829 22.415 63 MATERIALS SCIENCE & ENGINEERING R-REPORTS 7,206 22.250 63 Psychological Science in the Public Interest 1,437 22.250 65 Nature Climate Change 23,544 21.722 65 Nature Climate Change 23,544 21.722 67 ACCOUNTS OF CHEMICAL RESEARCH 69,687 21.661 68 IMMUNITY 51,051 21.522 69 Cell Stem Cell 24,628 21.464 70 Annual Review of Immunology 17,013 21.429 71 Nature Reviews Neurology 9,548 21.155 72 NATURE NEUROSCIENCE 63,390 21.126 73 INTERNATIONAL MATERIALS REVIEWS 5,262 21.086 74 JAMA Internal Medicine 15,215 20.768 75 Nature Physics 36,156 20.113 76 Annual Review of Psychology 20,230 19.755 76 Annual Review of Psychology 20,230 19.755 78 Nature Reviews Nephrology 5,767 19.684 79 Science Robotics 898 19.400 80 ANNALS OF INTERNAL MEDICINE 57,057 19.315 81 GASTROENTEROLOGY 74,469 19.233 82 INTENSIVE CARE MEDICINE 22,631 18.967 83 JOURNAL OF HEPATOLOGY 40,643 18.946 84 Annual Review of Plant Biology 19,024 18.918 85 PHARMACOLOGICAL REVIEWS 12,653 18.886 86 JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY 100,986 18.639 87 Nature Reviews Rheumatology 7,761 18.545 88 Lancet Psychiatry 4,887 18.329 88 Lancet Psychiatry 4,887 18.329 90 Chem 3,493 18.205 91 ACTA NEUROPATHOLOGICA 20,206 18.174 92 GUT 43,400 17.943 93 Annual Review of Physiology 9,562 17.902 94 CELL RESEARCH 15,131 17.848 95 CLINICAL MICROBIOLOGY REVIEWS 19,194 17.750 96 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 55,828 17.730 97 NATURE CELL BIOLOGY 40,615 17.728 98 Nature Reviews Cardiology 6,301 17.420 99 EUROPEAN UROLOGY 30,782 17.298 100 Annual Review of Fluid Mechanics 12,706 17.214 101 BEHAVIORAL AND BRAIN SCIENCES 9,377 17.194 101 BEHAVIORAL AND BRAIN SCIENCES 9,377 17.194 103 Science Translational Medicine 30,485 17.161 104 Nature Biomedical Engineering 1,540 17.135 105 TRENDS IN BIOCHEMICAL SCIENCES 17,448 16.889 106 Annual Review of Materials Research 8,086 16.816 107 REVIEWS OF GEOPHYSICS 11,762 16.725 108 REPORTS ON PROGRESS IN PHYSICS 18,176 16.620 109 TRENDS IN CELL BIOLOGY 14,380 16.588 110 Nano Today 7,980 16.582 111 BLOOD 161,827 16.562 112 AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE 63,074 16.494 113 PSYCHOLOGICAL BULLETIN 50,710 16.405 113 PSYCHOLOGICAL BULLETIN 50,710 16.405 115 ACS Energy Letters 10,134 16.331 116 TRENDS IN COGNITIVE SCIENCES 27,095 16.173 116 TRENDS IN COGNITIVE SCIENCES 27,095 16.173 118 JAMA Psychiatry 10,894 15.916 118 JAMA Psychiatry 10,894 15.916 120 Lancet Global Health 6,109 15.873 120 Lancet Global Health 6,109 15.873 122 CIRCULATION RESEARCH 52,988 15.862 123 Advanced Science 8,129 15.804 124 Cell Host & Microbe 17,787 15.753 125 ADVANCED FUNCTIONAL MATERIALS 95,431 15.621 126 FUNGAL DIVERSITY 4,234 15.596 127 Annual Review of Condensed Matter Physics 2,763 15.588 128 Nano Energy 37,106 15.548 129 ADVANCED DRUG DELIVERY REVIEWS 36,350 15.519 130 DIABETES CARE 71,305 15.270 131 MICROBIOLOGY AND MOLECULAR BIOLOGY REVIEWS 11,790 15.255 132 TRENDS IN ECOLOGY & EVOLUTION 36,697 15.236 133 Annual Review of Marine Science 3,870 15.225 134 JOURNAL OF PINEAL RESEARCH 10,695 15.221 135 ENDOCRINE REVIEWS 13,381 15.167 136 ASTRONOMY AND ASTROPHYSICS REVIEW 1,788 15.143 137 HEPATOLOGY 65,892 14.971 138 MMWR-MORBIDITY AND MORTALITY WEEKLY REPORT 26,534 14.874 139 SURFACE SCIENCE REPORTS 4,655 14.824 140 MOLECULAR BIOLOGY AND EVOLUTION 46,915 14.797 141 Lancet HIV 2,417 14.753 142 JOURNAL OF THE AMERICAN CHEMICAL SOCIETY 550,343 14.695 143 Living Reviews in Solar Physics 1,071 14.625 144 MOLECULAR CELL 62,812 14.548 145 Nature Geoscience 24,174 14.480 146 Alzheimers & Dementia 13,341 14.423 147 NEURON 95,348 14.403 148 Materials Horizons 4,587 14.356 149 Nature Microbiology 4,996 14.300 150 ANNALS OF THE RHEUMATIC DISEASES 44,754 14.299 151 APPLIED CATALYSIS B-ENVIRONMENTAL 74,797 14.229 152 ANNALS OF ONCOLOGY 40,751 14.196 153 JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY 51,978 14.110 154 Annual Review of Clinical Psychology 5,555 14.098 154 Annual Review of Clinical Psychology 5,555 14.098 156 GENOME BIOLOGY 38,920 14.028 157 TRENDS IN PLANT SCIENCE 21,520 14.006 158 Light-Science & Applications 5,894 14.000 159 EUROPEAN JOURNAL OF HEART FAILURE 13,107 13.965 160 Advances in Optics and Photonics 2,494 13.963 161 ACS Nano 152,659 13.903 162 Annual Review of Pathology-Mechanisms of Disease 4,585 13.833 163 TRENDS IN BIOTECHNOLOGY 15,857 13.747 164 PSYCHOTHERAPY AND PSYCHOSOMATICS 3,892 13.744 164 PSYCHOTHERAPY AND PSYCHOSOMATICS 3,892 13.744 166 AMERICAN JOURNAL OF PSYCHIATRY 43,025 13.655 166 AMERICAN JOURNAL OF PSYCHIATRY 43,025 13.655 168 COORDINATION CHEMISTRY REVIEWS 32,760 13.476 169 Nature Plants 3,979 13.297 170 IEEE Industrial Electronics Magazine 1,884 13.241 171 National Science Review 1,842 13.222 172 TRENDS IN IMMUNOLOGY 12,153 13.000 173 HUMAN REPRODUCTION UPDATE 9,206 12.878 174 Lancet Gastroenterology & Hepatology 1,649 12.856 175 ACS Central Science 4,160 12.837 176 BIOTECHNOLOGY ADVANCES 18,021 12.831 177 Science Advances 21,901 12.804 178 Applied Physics Reviews 2,404 12.750 179 PROGRESS IN LIPID RESEARCH 5,839 12.540 180 Journal of Thoracic Oncology 16,601 12.460 181 JAMA Neurology 8,683 12.321 182 TRENDS IN NEUROSCIENCES 20,163 12.314 183 Academy of Management Annals 3,693 12.289 184 JOURNAL OF CLINICAL INVESTIGATION 108,879 12.282 185 NANO LETTERS 163,570 12.279 186 ANGEWANDTE CHEMIE-INTERNATIONAL EDITION 327,734 12.257 186 Annual Review of Biomedical Engineering 4,634 12.257 188 ACS Catalysis 55,465 12.221 189 Physical Review X 13,462 12.211 190 Annual Review of Biophysics 2,878 12.175 191 Nature Chemical Biology 21,428 12.154 192 NATURE STRUCTURAL & MOLECULAR BIOLOGY 27,166 12.109 193 Annual Review of Pharmacology and Toxicology 7,820 12.103 194 Annual Review of Neuroscience 14,042 12.043 195 JAMA Pediatrics 8,016 12.004 196 Lancet Haematology 1,934 11.990 197 Annual Review of Physical Chemistry 8,622 11.982 198 TRENDS IN MICROBIOLOGY 12,514 11.974 199 MOLECULAR PSYCHIATRY 20,353 11.973 200 Nature Communications 243,793 11.878 201 NATURAL PRODUCT REPORTS 11,039 11.876 202 JAMA Cardiology 3,280 11.866 203 BRAIN 52,970 11.814 204 EUROPEAN RESPIRATORY JOURNAL 38,502 11.807 205 Annual Review of Entomology 12,624 11.796 206 QUARTERLY JOURNAL OF ECONOMICS 28,500 11.775 207 PROGRESS IN RETINAL AND EYE RESEARCH 6,284 11.768 208 DRUG RESISTANCE UPDATES 2,856 11.708 209 IEEE Transactions on Neural Networks and Learning Systems 27,444 11.683 210 Journal of Statistical Software 20,164 11.655 211 BRITISH JOURNAL OF SPORTS MEDICINE 21,929 11.645 212 Lancet Public Health 799 11.600 212 Lancet Public Health 799 11.600 214 FEMS MICROBIOLOGY REVIEWS 12,528 11.524 215 TRENDS IN PHARMACOLOGICAL SCIENCES 12,317 11.523 216 BIOLOGICAL PSYCHIATRY 43,122 11.501 217 Nature Protocols 40,341 11.334 218 IMMUNOLOGICAL REVIEWS 15,517 11.292 219 EMBO JOURNAL 65,212 11.227 220 NUCLEIC ACIDS RESEARCH 181,592 11.147 221 Autophagy 16,161 11.059 222 PLOS MEDICINE 30,689
Recommended publications
  • Practical Hydroinformatics
    Water Science and Technology Library 68 Practical Hydroinformatics Computational Intelligence and Technological Developments in Water Applications Bearbeitet von Robert J Abrahart, Linda M See, Dimitri P Solomatine 1. Auflage 2008. Buch. xvi, 506 S. Hardcover ISBN 978 3 540 79880 4 Format (B x L): 15,5 x 23,5 cm Gewicht: 944 g Weitere Fachgebiete > Geologie, Geographie, Klima, Umwelt > Geologie > Hydrologie, Hydrogeologie Zu Inhaltsverzeichnis schnell und portofrei erhältlich bei Die Online-Fachbuchhandlung beck-shop.de ist spezialisiert auf Fachbücher, insbesondere Recht, Steuern und Wirtschaft. Im Sortiment finden Sie alle Medien (Bücher, Zeitschriften, CDs, eBooks, etc.) aller Verlage. Ergänzt wird das Programm durch Services wie Neuerscheinungsdienst oder Zusammenstellungen von Büchern zu Sonderpreisen. Der Shop führt mehr als 8 Millionen Produkte. Chapter 2 Data-Driven Modelling: Concepts, Approaches and Experiences D. Solomatine, L.M. See and R.J. Abrahart Abstract Data-driven modelling is the area of hydroinformatics undergoing fast development. This chapter reviews the main concepts and approaches of data-driven modelling, which is based on computational intelligence and machine-learning methods. A brief overview of the main methods – neural networks, fuzzy rule-based systems and genetic algorithms, and their combination via committee approaches – is provided along with hydrological examples and references to the rest of the book. Keywords Data-driven modelling · data mining · computational intelligence · fuzzy rule-based systems · genetic algorithms · committee approaches · hydrology 2.1 Introduction Hydrological models can be characterised as physical, mathematical (including lumped conceptual and distributed physically based models) and empirical. The lat- ter class of models, in contrast to the first two, involves mathematical equations that are not derived from physical processes in the catchment but from analysis of time series data.
    [Show full text]
  • Applications of Social Media in Hydroinformatics: a Survey
    Applications of Social Media in Hydroinformatics: A Survey Yufeng Yu, Yuelong Zhu, Dingsheng Wan,Qun Zhao [email protected] College of Computer and Information Hohai University Nanjing, Jiangsu, China Kai Shu, Huan Liu [email protected] School of Computing, Informatics, and Decision Systems Engineering Arizona State University Tempe, Arizona, U.S.A Abstract Floods of research and practical applications employ social media data for a wide range of public applications, including environmental monitoring, water resource managing, disaster and emergency response, etc. Hydroinformatics can benefit from the social media technologies with newly emerged data, techniques and analytical tools to handle large datasets, from which creative ideas and new values could be mined. This paper first proposes a 4W (What, Why, When, hoW) model and a methodological structure to better understand and represent the application of social media to hydroinformatics, then provides an overview of academic research of applying social media to hydroinformatics such as water environment, water resources, flood, drought and water Scarcity management. At last,some advanced topics and suggestions of water-related social media applications from data collection, data quality management, fake news detection, privacy issues , algorithms and platforms was present to hydroinformatics managers and researchers based on previous discussion. Keywords: Social Media, Big Data, Hydroinformatics, Social Media Mining, Water Resource, Data Quality, Fake News 1 Introduction In the past two
    [Show full text]
  • Hydroinformatics and Its Applications at Delft Hydraulics Arthur E
    83 © IWA Publishing 1999 Journal of Hydroinformatics | 01.2 | 1999 Hydroinformatics and its applications at Delft Hydraulics Arthur E. Mynett ABSTRACT Hydroinformatics concerns applications of advanced information technologies in the fields Arthur E. Mynett Department of Strategic Research and of hydro-sciences and engineering. The rapid advancement and indeed the very success of Development, hydroinformatics is directly associated with these applications. The aim of this paper is to provide Delft Hydraulics, Postbus 177, Rotterdamseweg 185, 2600 MH Delft, an overview of some recent advances and to illustrate the practical implications of hydroinformatics The Netherlands technologies. A selection of characteristic examples on various topics is presented here, demonstrating the practical use at Delft Hydraulics. Most surely they will be elaborated upon in a more detailed way in forthcoming issues of this Journal. First, a very brief historical background is outlined to characterise the emergence and evolution of hydroinformatics in hydraulic and environmental engineering practice. Recent advances in computational hydraulics are discussed next. Numerical methods are outlined whose main advantages lie in their efficiency and applicability to a very wide range of practical problems. The numerical scheme has to adhere only to the velocity Courant number and is based upon a staggered grid arrangement. Therefore the method is efficient for most free surface flows, including complex networks of rivers and canals, as well as overland flows. Examples are presented for dam break problems and inundation of polders. The latter results are presented within the setting of a Geographical Information System. In general, computational modelling can be viewed as a class of techniques very much based on, and indeed quite well described by, mathematical equations.
    [Show full text]
  • Time Series Scenario Composition Framework in Hydroinformatics Systems
    Time Series Scenario Composition Framework in Hydroinformatics Systems Von der Fakultät für Umweltwissenschaften und Verfahrenstechnik der Brandenburgischen Technischen Universität Cottbus-Senftenberg zur Erlangung des akademischen Grades eines Doktor-Ingenieurs genehmigte Dissertation vorgelegt von Master of Science Chi-Yu LI aus Taipeh, TAIWAN Gutachter: apl. Prof. Dr.-Ing. Frank Molkenthin Gutachter: Prof. Dr.-Ing. Reinhard Hinkelmann Tag der mündliche Prüfung: 04. Dezember 2014 Cottbus 2014 Declaration I, Chi-Yu Li, hereby declare that this thesis entitled "Time Series Composition Framework in Hydroinformatics Systems" was carried out and written independently, unless where clearly stated otherwise. I have used only the sources, the figures and the data that are clearly stated. This thesis has not been published elsewhere. Cottbus, June 25, 2014 Chi-Yu Li ii Abstract Since Z3, the first automatic, programmable and operational computer, emerged in 1941, computers have become an unshakable tool in varieties of engineering researches, studies and applications. In the field of hydroinformatics, there exist a number of tools focusing on data collection and management, data analysis, numerical simulations, model coupling, post-processing, etc. in different time and space scales. However, one crucial process is still missing — filling the gap between available mass raw data and simulation tools. In this research work, a general software framework for time series scenario composition is proposed to improve this issue. The design of this framework is aimed at facilitating simulation tasks by providing input data sets, e.g. Boundary Conditions (BCs), generated for user-specified what-if scenarios. These scenarios are based on the available raw data of different sources, such as field and laboratory measurements and simulation results.
    [Show full text]
  • Hydroinformatics Support to Flood Forecasting and Flood Management
    Water in Celtic Countries: Quantity, Quality and Climate Variability (Proceedings of the Fourth InterCeltic 23 Colloquium on Hydrology and Management of Water Resources, Guimarães, Portugal, July 2005). IAHS Publ. 310, 2007. Hydroinformatics support to flood forecasting and flood management ADRI VERWEY WL | Delft Hydraulics, Delft, The Netherlands [email protected] Abstract This keynote paper describes state-of-the-art hydroinformatics support to the water sector. A few examples are worked out in some detail, whereas for other examples the reader is guided to recent literature. The focus is on flood forecasting and flood management, with a brief description of the potential of changing technologies that support studies and facilities in this area. Examples are: new data collection methods; data mining from these extensive new sources of information, e.g. the use of genetic programming; data driven modelling techniques, e.g. artificial neural networks; decision support systems; and the provision of a hydroinformatics platform for flood forecasting. Particular attention is given to advances in numerical flood modelling. Over recent years the robustness of numerical models has increased substantially, solving for example, the flooding and drying problem of flood plains and the computation of supercritical flows. In addition, the emergence of hybrid 1D2D models is discussed with their different options for linking model components of flood prone areas. Key words data mining; flood forecasting; flood management; flow resistance; flood
    [Show full text]
  • Hydroinformatics for Hydrology: Data-Driven and Hybrid Techniques
    Hydroinformatics for hydrology: data-driven and hybrid techniques Dimitri P. Solomatine UNESCO-IHE Institute for Water Education Hydroinformatics Chair Outline of the course Notion of data-driven modelling (DDM) Data Introduction to some methods Combining models - hybrid models Demonstration of applications – Rainfall-runoff modelling – Reservoir optimization D.P. Solomatine. Data-driven modelling (part 1). 2 •1 Quick start: rainfallrainfall--runoffrunoff modelling FLOW1: effective rainfall and discharge data Discharge [m3/s] Eff.rainfall [mm] 800 0 2 700 4 600 Effective rainfall [mm] 6 500 8 400 10 Discharge [m3/s] 12 300 14 200 16 100 18 0 20 0 500 1000 1500 2000 2500 Time [hrs] D.P. Solomatine. Data-driven modelling. Applications. 3 Quick start: how to calculate runoff one step ahead? SF – Snow RF – Rain EA – Evapotranspiration SP – Snow cover SF RF IN – Infiltration EA R – Recharge A. Lumped conceptual model SM – Soil moisture CFLUX – Capillary transport SP UZ – Storage in upper reservoir IN PERC – Percolation SM LZ – Storage in lower reservoir R CFLUX Qo – Fast runoff component Q0 Q1 – Slow runoff component UZ Q – Total runoff PERC Q1 Q=Q0+Q1 Transform LZ function B. Data-driven (regression) model, based on past data: Q (t+1) = f (REt, REt-1, REt-2, REt-3, REt-4, REt-5, Qt, Qt-1, Qt-2) FLOW1: effective rainfall and discharge data Discharge [m3/s] where f is a non-linear function Eff.rainfall [mm] 800 0 2 700 4 600 Effective rainfall [mm] 6 500 8 400 10 Discharge [m3/s] 12 300 14 200 16 100 18 0 20 0 500 1000 1500 2000 2500 4 D.P.
    [Show full text]
  • The Water Informatics in Science and Engineering (WISE) Centre for Doctoral Training
    Hydrol. Earth Syst. Sci., 25, 2721–2738, 2021 https://doi.org/10.5194/hess-25-2721-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Hydroinformatics education – the Water Informatics in Science and Engineering (WISE) Centre for Doctoral Training Thorsten Wagener1,2,9, Dragan Savic3,4, David Butler4, Reza Ahmadian5, Tom Arnot6, Jonathan Dawes7, Slobodan Djordjevic4, Roger Falconer5, Raziyeh Farmani4, Debbie Ford4, Jan Hofman3,6, Zoran Kapelan4,8, Shunqi Pan5, and Ross Woods1,2 1Department of Civil Engineering, University of Bristol, Bristol, UK 2Cabot Institute, University of Bristol, Bristol, UK 3KWR Water Research Institute, Nieuwegein, the Netherlands 4Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK 5Hydro-environmental Research Centre, School of Engineering, Cardiff University, Cardiff, UK 6Water Innovation and Research Centre, Department of Chemical Engineering, University of Bath, Bath, UK 7Institute for Mathematical Innovation and Department of Mathematical Sciences, University of Bath, Bath, UK 8Department of Water Management, Delft University of Technology, Delft, the Netherlands 9Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany Correspondence: Thorsten Wagener ([email protected]) Received: 15 September 2020 – Discussion started: 5 October 2020 Revised: 17 April 2021 – Accepted: 23 April 2021 – Published: 20 May 2021 Abstract. The Water Informatics in Science and Engineer- 1 Introduction ing Centre for Doctoral Training (WISE CDT) offers a post- graduate programme that fosters enhanced levels of innova- tion and collaboration by training a cohort of engineers and The global water cycle consists of a complex web of interact- scientists at the boundary of water informatics, science and ing physical, biogeochemical, ecological and human systems engineering.
    [Show full text]
  • Building an Intelligent Hydroinformatics Integration Platform for Regional Flood Inundation Warning Systems
    water Editorial Building an Intelligent Hydroinformatics Integration Platform for Regional Flood Inundation Warning Systems Li-Chiu Chang 1,*, Fi-John Chang 2 , Shun-Nien Yang 1, I-Feng Kao 2, Ying-Yu Ku 1, Chun-Ling Kuo 3 and Ir. Mohd Zaki bin Mat Amin 4 1 Department of Water Resources and Environmental Engineering, Tamkang University, New Taipei City 25137, Taiwan; [email protected] (S.-N.Y.); [email protected] (Y.-Y.K.) 2 Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan; [email protected] (F.-J.C.); [email protected] (I.-F.K.) 3 Water Resources Agency, Ministry of Economic Affairs, Taipei 10617, Taiwan; [email protected] 4 Water Resources and Climatic Change Research Centre, National Hydraulic Research Institute of Malaysia, 43300 Selangor, Malaysia; [email protected] * Corresponding author: [email protected]; Tel.: +886-2-26258523 Received: 30 November 2018; Accepted: 19 December 2018; Published: 21 December 2018 Abstract: Flood disasters have had a great impact on city development. Early flood warning systems (EFWS) are promising countermeasures against flood hazards and losses. Machine learning (ML) is the kernel for building a satisfactory EFWS. This paper first summarizes the ML methods proposed in this special issue for flood forecasts and their significant advantages. Then, it develops an intelligent hydroinformatics integration platform (IHIP) to derive a user-friendly web interface system through the state-of-the-art machine learning, visualization and system developing techniques for improving online forecast capability and flood risk management. The holistic framework of the IHIP includes five layers (data access, data integration, servicer, functional subsystem, and end-user application) and one database for effectively dealing with flood disasters.
    [Show full text]
  • AETA-Computational-Engineering.Pdf
    Computational Engineering A Agent-based computational economics Algorithmic art Artificial intelligence Astroinformatics Author profiling B Biodiversity informatics Biological computation C Cellular automaton Chaos theory Cheminformatics Code stylometry Community informatics Computable topology Computational aeroacoustics Computational archaeology Computational astrophysics Computational auditory scene analysis Computational biology Computational chemistry Computational cognition Computational complexity theory Computational creativity Computational criminology Computational economics Computational electromagnetics Computational epigenetics Computational epistemology Computational finance Computational fluid dynamics Computational genomics Computational geometry Computational geophysics Computational group theory Computational humor Computational immunology Computational journalism Computational law Computational learning theory Computational lexicology Computational linguistics Computational lithography Computational logic Computational magnetohydrodynamics Computational Materials Science Computational mechanics Computational musicology Computational neurogenetic modeling Computational neuroscience Computational number theory Computational particle physics Computational photography Computational physics Computational science Computational engineering Computational scientist Computational semantics Computational semiotics Computational social science Computational sociology Computational
    [Show full text]
  • MH106748 Physiology-Based Virtual Reality Training for Social Skills In
    MH106748 Physiology-based virtual reality training for social skills in schizophrenia 11/30/2018 PROTOCOL We will implement the adaptive social VR game and determine the optimal dose. After we construct each subject’s affective model with the machine-learning algorithm, we will test the effects of the adaptive VR games in 40 medicated outpatients with schizophrenia (SZ). Demographically matched control (CO) subjects (n=16) will only participate in the affective modeling and social and cognitive assessments but not in VR training (see Human Subjects section for details). To determine the optimal dose of VR training, it is necessary to conduct a valid assessment for social functioning pre- and post- treatment. Details of assessments are outlined below. Optimal dose of physiology-based, adaptive VR intervention is unknown but Tsang & Man53 reported that just ten 30-minute sessions of conventional, non-adaptive VR training was sufficient to obtain an improvement in SZ. In our study, we will examine the effects of social VR training on social and cognitive measures, pre- and post-treatment. At baseline (t1), the PI’s will use stratified randomization to assign SZ to two dose conditions: high vs. low. Stratified randomization is used to ensure that potential confounding factors (e.g. age, gender) are evenly distributed between groups. If possible, we will try to match the two groups on IQ, and the Social Functioning Scale79, a broad measure of social functioning, but if it cannot be done, we will statistically adjust for them when we test for treatment effects. Everybody will train twice a week but the low dose group will train for 30 mins and the high dose group for 2 x 30 mins per visit.
    [Show full text]
  • Urban Hydroinformatics: Past, Present and Future
    water Review Urban Hydroinformatics: Past, Present and Future C. Makropoulos 1,2,3 and D. A. Savi´c 1,4,* 1 KWR, Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, The Netherlands; [email protected] 2 Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, Iroon Politechniou 5, 157 80 Zografou, Athens, Greece 3 Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway 4 Centre for Water Systems, University of Exeter, Exeter EX44QF, UK * Correspondence: [email protected] Received: 20 May 2019; Accepted: 10 September 2019; Published: 20 September 2019 Abstract: Hydroinformatics, as an interdisciplinary domain that blurs boundaries between water science, data science and computer science, is constantly evolving and reinventing itself. At the heart of this evolution, lies a continuous process of critical (self) appraisal of the discipline’s past, present and potential for further evolution, that creates a positive feedback loop between legacy, reality and aspirations. The power of this process is attested by the successful story of hydroinformatics thus far, which has arguably been able to mobilize wide ranging research and development and get the water sector more in tune with the digital revolution of the past 30 years. In this context, this paper attempts to trace the evolution of the discipline, from its computational hydraulics origins to its present focus on the complete socio-technical system, by providing at the same time, a functional framework to improve the understanding and highlight the links between different strands of the state-of-art hydroinformatic research and innovation.
    [Show full text]
  • New Skills in the Time of Hydroinformatics
    Blokker, 8 nov 2018 1 New skills in the time of hydroinformatics drinking water quality conference 2018 KWR invests in strong links with Building the knowledge base valuable partners, in order to needed to provide drinking water build a solid knowledge base of world class quality. realise high quality reference projects 40 years of collective research covering source to tap, create marketable products institutional memory for the drinking water sector KWR Watercycle Research Institute Knowledge institute of and for Dutch & Flemish drinking water companies Blokker, 8 nov 2018 3 Hydroinformatics Hydroinformatics (…) concentrates on the application of ICTs in addressing the increasingly serious problems of the equitable and efficient use of water for many different purposes. (Wikipedia) ➔ More data ➔ More information ➔ More knowledge (?) Blokker, 8 nov 2018 4 New skills Computer skills? • Genetic algorithms • Artificial intelligence • Datamining • … Human skills? • Problem definition • System understanding • … Blokker, 8 nov 2018 5 Some examples in drinking water distribution OPTIMAL NETWORK DESIGN SENSORED NETWORK + REAL TIME MODELLING Janke, R., Uber, J., Hattchett, S., A. Gibbons, D. and Y. Wang, H. (2015). "Enhancements to the EPANET-RTX (Real-Time Analytics) Software Libraries-2015. ." Blokker, 8 nov 2018 6 van Thienen, P., Vertommen, I. and van Laarhoven, K. (2018). "Practical application of optimization techniques Optimal network design to drinking water distribution problems." Hydroinformatics International Conference, Palermo, Italy.
    [Show full text]