Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–² Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-2691 Peer reviewed articles 2017 Mostafa Abdulghafoor MOHAMMED, Nicolae ŢĂPUŞ A Novel Approach of Reducing Energy Consumption by Utilizing Enthalpy in Mobile Cloud Computing Studies in Informatics and Control 10.24846/v26i4y201706 Simulation & Modeling River Basins No abstract available 690900
publications-2692 Peer reviewed articles 2018 George-Alexandru Musat, MÇŽdÇŽlin Colezea, Florin Pop, Catalin Negru, Mariana Mocanu, Christian Esposito, Aniello Castiglione Advanced services for efficient management of smart farms Journal of Parallel and Distributed Computing 10.1016/j.jpdc.2017.10.017 Simulation & Modeling Irrigation Systems No abstract available 690900
publications-2693 Peer reviewed articles 2017 Radu-Ioan Ciobanu, Radu-Corneliu Marin, Ciprian Dobre, Valentin Cristea Trust and reputation management for opportunistic dissemination Pervasive and Mobile Computing 10.1016/j.pmcj.2016.09.016 Uncategorized River Basins No abstract available 690900
publications-2694 Peer reviewed articles 2017 Cristian Chilipirea, Andreea-Cristina Petre, Loredana-Marsilia Groza, Ciprian Dobre, Florin Pop An integrated architecture for future studies in data processing for smart cities Microprocessors and Microsystems 10.1016/j.micpro.2017.03.004 Simulation & Modeling Precipitation & Ecological Systems No abstract available 690900
publications-2695 Peer reviewed articles 2018 Cosmin Dragomir, Lucian Mogosanu, Mihai Carabas, Razvan Deaconescu, Nicolae Tapus <i>µ</i>QC: a property-based testing framework for L4 microkernels International Journal of Critical Computer-Based Systems 10.1504/IJCCBS.2018.091826 Data Management & Analytics River Basins No abstract available 690900
publications-2696 Peer reviewed articles 2018 Alexandru Iulian Orhean, Florin Pop, Ioan Raicu New scheduling approach using reinforcement learning for heterogeneous distributed systems Journal of Parallel and Distributed Computing 10.1016/j.jpdc.2017.05.001 Simulation & Modeling Groundwater No abstract available 690900
publications-2697 Peer reviewed articles 2017 George IORDACHE, Adrian PASCHKE, Mariana MOCANU, Cătălin NEGRU Service Level Agreement Characteristics of Monitoring Wireless Sensor Networks for Water Resource Management (SLAs4Water) Studies in Informatics and Control 10.24846/v26i4y201701 Control Systems River Basins No abstract available 690900
publications-2698 Peer reviewed articles 2017 Dan Popescu, Loretta Ichim, Florin Stoican Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing Sensors 10.3390/s17030446 Data Management & Analytics Wastewater Treatment Plants Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication. The aerial component contains mobile nodes—fixed wing type UAVs. In order to evaluate flood damage, two tasks must be accomplished by the network: area coverage and image processing. The second novelty of the paper consists of texture analysis in a deep neural network, taking into account new criteria for feature selection and patch classification. Color and spatial information extracted from chromatic co-occurrence matrix and mass fractal dimension were used as well. Finally, the experimental results in a real mission demonstrate the validity of the proposed methodologies and the performances of the algorithms. 690900
publications-2699 Peer reviewed articles 2016 Ciolofan, Sorin N.; Pop, Florin; Mocanu, Mariana; Cristea Valentin Rapid Parallel Detection of Distance-based Outliers in Time Series using MapReduce CONTROL ENGINEERING AND APPLIED INFORMATICS journal Data Management & Analytics River Basins No abstract available 690900
publications-2700 Peer reviewed articles 2019 Mohammad Gharesifard, Uta Wehn, Pieter van der Zaag What influences the establishment and functioning of community-based monitoring initiatives of water and environment? A conceptual framework Journal of Hydrology 10.1016/j.jhydrol.2019.124033 Uncategorized Uncategorized No abstract available 689744