445 research outputs found

    Government Regulations on Rural Water Safety-Ghana

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    Portable water accessibility remains one of the key issues in development. A survey from the United Nations, 2010 indicates that about 783 million people (11% of the global population) remain without access to an improved source of drinking water. The Government of Ghana has come out with numerous water projects in some poor communities in the Northern, Upper East and Upper West regions, yet unhygienic water and water pollution seems to still be a challenge facing citizens of this communities. It is therefore against this background that this research was conducted to find out about the impact of Government regulatory practices on water safety in the Wa Municipality which is in the upper west region. The study was guided by these questions: Does Government regulations on service assessment affect water safety? Does monitoring and control practice have a productive result on water safety? Do management plan on water safety has a direct impact on water safety? Does government released funds on water safety embarked upon as planned?  The study employed the good governance theory, social capital theory, and the institutional change theory. The study did an empirical review of related literatures to answer the various research questions. It was revealed from the empirical review that service assessment, monitoring and control, effective management plan and government released funds intended for their right purposes have a significant positive effect on water safety.  The study therefore recommended an implementation of a working and effective service assessment systems and monitoring and control mechanisms over water projects to ensure the provision of portable water to the intended communities in the municipality. Also, there is the need for the implementation of an effective management plan for water projects, as well as the timely provision and the right usage of project fund. Keywords: Government Regulations, Monitoring and Control, Service Assessment, Rural Water Safety

    Real-time early warning system design for pluvial flash floods - A review

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    [EN] Pluvial flash floods in urban areas are becoming increasingly frequent due to climate change and human actions, negatively impacting the life, work, production and infrastructure of a population. Pluvial flooding occurs when intense rainfall overflows the limits of urban drainage and water accumulation causes hazardous flash floods. Although flash floods are hard to predict given their rapid formation, Early Warning Systems (EWS) are used to minimize casualties. We performed a systematic review to define the basic structure of an EWS for rain flash floods. The structure of the review is as follows: first, Section 2 describes the most important factors that affect the intensity of pluvial flash floods during rainfall events. Section 3 defines the key elements and actors involved in an effective EWS. Section 4 reviews different EWS architectures for pluvial flash floods implemented worldwide. It was identified that the reviewed projects did not follow guidelines to design early warning systems, neglecting important aspects that must be taken into account in their implementation. Therefore, this manuscript proposes a basic structure for an effective EWS for pluvial flash floods that guarantees the forecasting process and alerts dissemination during rainfall events.Administrative Department of Science, Technology and Innovation of the presidency of the Republic of Colombia (COLCIENCIAS) #728.Acosta-Coll, M.; Ballester Merelo, FJ.; MartĂ­nez PeirĂł, MA.; De La Hoz-Franco, E. (2018). Real-time early warning system design for pluvial flash floods - A review. Sensors. 18(7). https://doi.org/10.3390/s18072255S187Kundzewicz, Z. W. (2002). Non-structural Flood Protection and Sustainability. Water International, 27(1), 3-13. doi:10.1080/02508060208686972Singh, P., Sinha, V. S. P., Vijhani, A., & Pahuja, N. (2018). Vulnerability assessment of urban road network from urban flood. International Journal of Disaster Risk Reduction, 28, 237-250. doi:10.1016/j.ijdrr.2018.03.017Birkmann, J., & von Teichman, K. (2010). Integrating disaster risk reduction and climate change adaptation: key challenges—scales, knowledge, and norms. Sustainability Science, 5(2), 171-184. doi:10.1007/s11625-010-0108-yEmerging Challenges for Early Warning Systems in context of Climate Change and Urbanizationhttp://www.preventionweb.net/ files/15689_ewsincontextofccandurbanization.pdfChaumillon, E., Bertin, X., Fortunato, A. B., Bajo, M., Schneider, J.-L., Dezileau, L., 
 Pedreros, R. (2017). Storm-induced marine flooding: Lessons from a multidisciplinary approach. Earth-Science Reviews, 165, 151-184. doi:10.1016/j.earscirev.2016.12.005Alfieri, L., Cohen, S., Galantowicz, J., Schumann, G. J.-P., Trigg, M. A., Zsoter, E., 
 Salamon, P. (2018). A global network for operational flood risk reduction. Environmental Science & Policy, 84, 149-158. doi:10.1016/j.envsci.2018.03.014Maggioni, V., & Massari, C. (2018). On the performance of satellite precipitation products in riverine flood modeling: A review. Journal of Hydrology, 558, 214-224. doi:10.1016/j.jhydrol.2018.01.039Jiang, Y., Zevenbergen, C., & Ma, Y. (2018). Urban pluvial flooding and stormwater management: A contemporary review of China’s challenges and «sponge cities» strategy. Environmental Science & Policy, 80, 132-143. doi:10.1016/j.envsci.2017.11.016Veldhuis, J. A. E. (2011). How the choice of flood damage metrics influences urban flood risk assessment. Journal of Flood Risk Management, 4(4), 281-287. doi:10.1111/j.1753-318x.2011.01112.xGlobal Approach to Address Flash Floodshttp://www.hrc-lab.org/publicbenefit/downloads/wmo-flashflood.pdfChen, Y., Zhou, H., Zhang, H., Du, G., & Zhou, J. (2015). Urban flood risk warning under rapid urbanization. Environmental Research, 139, 3-10. doi:10.1016/j.envres.2015.02.028Guerreiro, S., Glenis, V., Dawson, R., & Kilsby, C. (2017). Pluvial Flooding in European Cities—A Continental Approach to Urban Flood Modelling. Water, 9(4), 296. doi:10.3390/w9040296Bhattarai, R., Yoshimura, K., Seto, S., Nakamura, S., & Oki, T. (2016). Statistical model for economic damage from pluvial floods in Japan using rainfall data and socioeconomic parameters. Natural Hazards and Earth System Sciences, 16(5), 1063-1077. doi:10.5194/nhess-16-1063-2016Acosta-Coll, M., Ballester-Merelo, F., & MartĂ­nez-PeirĂł, M. (2018). Early warning system for detection of urban pluvial flooding hazard levels in an ungauged basin. Natural Hazards, 92(2), 1237-1265. doi:10.1007/s11069-018-3249-4Yin, J., Ye, M., Yin, Z., & Xu, S. (2014). A review of advances in urban flood risk analysis over China. Stochastic Environmental Research and Risk Assessment, 29(3), 1063-1070. doi:10.1007/s00477-014-0939-7Azam, M., Kim, H. S., & Maeng, S. J. (2017). Development of flood alert application in Mushim stream watershed Korea. International Journal of Disaster Risk Reduction, 21, 11-26. doi:10.1016/j.ijdrr.2016.11.008Creutin, J. D., Borga, M., Gruntfest, E., Lutoff, C., Zoccatelli, D., & Ruin, I. (2013). A space and time framework for analyzing human anticipation of flash floods. Journal of Hydrology, 482, 14-24. doi:10.1016/j.jhydrol.2012.11.009Yin, J., Yu, D., Yin, Z., Liu, M., & He, Q. (2016). Evaluating the impact and risk of pluvial flash flood on intra-urban road network: A case study in the city center of Shanghai, China. Journal of Hydrology, 537, 138-145. doi:10.1016/j.jhydrol.2016.03.037UNISDR Terminology on Disaster Risk Reductionhttps://www.unisdr.org/we/inform/publications/657Einfalt, T., Hatzfeld, F., Wagner, A., Seltmann, J., Castro, D., & Frerichs, S. (2009). URBAS: forecasting and management of flash floods in urban areas. Urban Water Journal, 6(5), 369-374. doi:10.1080/15730620902934819Lam, R. P. K., Leung, L. P., Balsari, S., Hsiao, K., Newnham, E., Patrick, K., 
 Leaning, J. (2017). Urban disaster preparedness of Hong Kong residents: A territory-wide survey. International Journal of Disaster Risk Reduction, 23, 62-69. doi:10.1016/j.ijdrr.2017.04.008Bouwer, L. M., Papyrakis, E., Poussin, J., Pfurtscheller, C., & Thieken, A. H. (2014). The Costing of Measures for Natural Hazard Mitigation in Europe. Natural Hazards Review, 15(4), 04014010. doi:10.1061/(asce)nh.1527-6996.0000133Praskievicz, S., & Chang, H. (2009). A review of hydrological modelling of basin-scale climate change and urban development impacts. Progress in Physical Geography: Earth and Environment, 33(5), 650-671. doi:10.1177/0309133309348098Hunt, A., & Watkiss, P. (2010). Climate change impacts and adaptation in cities: a review of the literature. Climatic Change, 104(1), 13-49. doi:10.1007/s10584-010-9975-6Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., 
 Sherstyukov, B. (2013). Flood risk and climate change: global and regional perspectives. Hydrological Sciences Journal, 59(1), 1-28. doi:10.1080/02626667.2013.857411You, Q., Kang, S., Aguilar, E., Pepin, N., FlĂŒgel, W.-A., Yan, Y., 
 Huang, J. (2010). Changes in daily climate extremes in China and their connection to the large scale atmospheric circulation during 1961–2003. Climate Dynamics, 36(11-12), 2399-2417. doi:10.1007/s00382-009-0735-0Miller, J. D., & Hutchins, M. (2017). The impacts of urbanisation and climate change on urban flooding and urban water quality: A review of the evidence concerning the United Kingdom. Journal of Hydrology: Regional Studies, 12, 345-362. doi:10.1016/j.ejrh.2017.06.006Borga, M., Anagnostou, E. N., Blöschl, G., & Creutin, J.-D. (2011). Flash flood forecasting, warning and risk management: the HYDRATE project. Environmental Science & Policy, 14(7), 834-844. doi:10.1016/j.envsci.2011.05.017Grillakis, M. G., Koutroulis, A. G., Komma, J., Tsanis, I. K., Wagner, W., & Blöschl, G. (2016). Initial soil moisture effects on flash flood generation – A comparison between basins of contrasting hydro-climatic conditions. Journal of Hydrology, 541, 206-217. doi:10.1016/j.jhydrol.2016.03.007Zhang, J., Yu, Z., Yu, T., Si, J., Feng, Q., & Cao, S. (2018). Transforming flash floods into resources in arid China. Land Use Policy, 76, 746-753. doi:10.1016/j.landusepol.2018.03.002Spiekermann, R., Kienberger, S., Norton, J., Briones, F., & Weichselgartner, J. (2015). The Disaster-Knowledge Matrix – Reframing and evaluating the knowledge challenges in disaster risk reduction. International Journal of Disaster Risk Reduction, 13, 96-108. doi:10.1016/j.ijdrr.2015.05.002Weichselgartner, J., & Pigeon, P. (2015). The Role of Knowledge in Disaster Risk Reduction. International Journal of Disaster Risk Science, 6(2), 107-116. doi:10.1007/s13753-015-0052-7Hunt, D. P. (2003). The concept of knowledge and how to measure it. Journal of Intellectual Capital, 4(1), 100-113. doi:10.1108/14691930310455414Strengthening Capacities for Disaster Risk Reduction, A Primerhttps://www.preventionweb.net/files/globalplatform/entry_bg_paper~strengtheningcapacityfordrraprimerfullreport.pdfSurjan, A., Sharma, A., & Shaw, R. (2011). Chapter 2 Understanding Urban Resilience. Community, Environment and Disaster Risk Management, 17-45. doi:10.1108/s2040-7262(2011)0000006008Fakhruddin, S. H. M., Kawasaki, A., & Babel, M. S. (2015). Community responses to flood early warning system: Case study in Kaijuri Union, Bangladesh. International Journal of Disaster Risk Reduction, 14, 323-331. doi:10.1016/j.ijdrr.2015.08.004Balis, B., Kasztelnik, M., Bubak, M., Bartynski, T., GubaƂa, T., Nowakowski, P., & Broekhuijsen, J. (2011). The UrbanFlood Common Information Space for Early Warning Systems. Procedia Computer Science, 4, 96-105. doi:10.1016/j.procs.2011.04.011Krzhizhanovskaya, V. V., Shirshov, G. S., Melnikova, N. B., Belleman, R. G., Rusadi, F. I., Broekhuijsen, B. J., 
 Meijer, R. J. (2011). Flood early warning system: design, implementation and computational modules. Procedia Computer Science, 4, 106-115. doi:10.1016/j.procs.2011.04.012Chang, C. L., & Lin, T.-C. (2015). The role of organizational culture in the knowledge management process. Journal of Knowledge Management, 19(3), 433-455. doi:10.1108/jkm-08-2014-0353MARK, O., WEESAKUL, S., APIRUMANEKUL, C., AROONNET, S., & DJORDJEVIC, S. (2004). Potential and limitations of 1D modelling of urban flooding. Journal of Hydrology, 299(3-4), 284-299. doi:10.1016/s0022-1694(04)00373-7Henonin, J., Russo, B., Mark, O., & Gourbesville, P. (2013). Real-time urban flood forecasting and modelling – a state of the art. Journal of Hydroinformatics, 15(3), 717-736. doi:10.2166/hydro.2013.132Mayhorn, C. B., & McLaughlin, A. C. (2014). Warning the world of extreme events: A global perspective on risk communication for natural and technological disaster. Safety Science, 61, 43-50. doi:10.1016/j.ssci.2012.04.014Cools, J., Innocenti, D., & O’Brien, S. (2016). Lessons from flood early warning systems. Environmental Science & Policy, 58, 117-122. doi:10.1016/j.envsci.2016.01.006Plate, E. J. (2007). Early warning and flood forecasting for large rivers with the lower Mekong as example. Journal of Hydro-environment Research, 1(2), 80-94. doi:10.1016/j.jher.2007.10.002Altay, N., & Green, W. G. (2006). OR/MS research in disaster operations management. European Journal of Operational Research, 175(1), 475-493. doi:10.1016/j.ejor.2005.05.016Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., & Pappenberger, F. (2013). GloFAS – global ensemble streamflow forecasting and flood early warning. Hydrology and Earth System Sciences, 17(3), 1161-1175. doi:10.5194/hess-17-1161-2013Morss, R. E., Mulder, K. J., Lazo, J. K., & Demuth, J. L. (2016). How do people perceive, understand, and anticipate responding to flash flood risks and warnings? Results from a public survey in Boulder, Colorado, USA. Journal of Hydrology, 541, 649-664. doi:10.1016/j.jhydrol.2015.11.047Cama-Pinto, A., Acosta-Coll, M., Piñeres-Espitia, G., Caicedo-Ortiz, J., Zamora-Musa, R., & Sepulveda-Ojeda, J. (2016). Diseño de una red de sensores inalĂĄmbricos para la monitorizaciĂłn de inundaciones repentinas en la ciudad de Barranquilla, Colombia. Ingeniare. Revista chilena de ingenierĂ­a, 24(4), 581-599. doi:10.4067/s0718-33052016000400005Espitia, G. P. (2014). Plataformas tecnolĂłgicas aplicadas al monitoreo climĂĄtico. Prospectiva, 11(2), 78. doi:10.15665/rp.v11i2.42Caicedo Ortiz, J. G. (2015). Modelo de despliegue de una WSN para la mediciĂłn de las variables climĂĄticas que causan fuertes precipitaciones. Prospectiva, 13(1), 106. doi:10.15665/rp.v13i1.365Marshall, J. S., & Palmer, W. M. K. (1948). THE DISTRIBUTION OF RAINDROPS WITH SIZE. Journal of Meteorology, 5(4), 165-166. doi:10.1175/1520-0469(1948)0052.0.co;2Liquid-Level Monitoring Using a Pressure Sensorhttp://www.ti.com/lit/an/snaa127/snaa127.pdfUltrasonic Transmitters vshttps://www.flo-corp.com/wp-content/uploads/2017/01/LTT1_UltrasonicTransmitters_GuidedWaveRadar_LevelMeasurement_whitepaper.pdfPanda, K. G., Agrawal, D., Nshimiyimana, A., & Hossain, A. (2016). Effects of environment on accuracy of ultrasonic sensor operates in millimetre range. Perspectives in Science, 8, 574-576. doi:10.1016/j.pisc.2016.06.024Saad, C., Mostafa, B., Ahmadi, E., & Abderrahmane, H. (2014). Comparative Performance Analysis of Wireless Communication Protocols for Intelligent Sensors and Their Applications. International Journal of Advanced Computer Science and Applications, 5(4). doi:10.14569/ijacsa.2014.050413FloodCitiSense: Early Warning Service for Urban Pluvial Floods for and by Citizens and City Authoritieshttp://www.iiasa.ac.at/web/home/research/researchPrograms/EcosystemsServicesandManagement/FloodCitiSense.htmlParker, D. J. (2017). Flood Warning Systems and Their Performance. Oxford Research Encyclopedia of Natural Hazard Science. doi:10.1093/acrefore/9780199389407.013.8

    Implementation of Middleware for Internet of Things in Asset Tracking Applications: In-lining Approach

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    ThesisInternet of Things (IoT) is a concept that involves giving objects a digital identity and limited artificial intelligence, which helps the objects to be interactive, process data, make decisions, communicate and react to events virtually with minimum human intervention. IoT is intensified by advancements in hardware and software engineering and promises to close the gap that exists between the physical and digital worlds. IoT is paving ways to address complex phenomena, through designing and implementation of intelligent systems that can monitor phenomena, perform real-time data interpretation, react to events, and swiftly communicate observations. The primary goal of IoT is ubiquitous computing using wireless sensors and communication protocols such as Bluetooth, Wireless Fidelity (Wi-Fi), ZigBee and General Packet Radio Service (GPRS). Insecurity, of assets and lives, is a problem around the world. One application area of IoT is tracking and monitoring; it could therefore be used to solve asset insecurity. A preliminary investigation revealed that security systems in place at Central University of Technology, Free State (CUT) are disjointed; they do not instantaneously and intelligently conscientize security personnel about security breaches using real time messages. As a result, many assets have been stolen, particularly laptops. The main objective of this research was to prove that a real-life application built over a generic IoT architecture that innovatively and intelligently integrates: (1) wireless sensors; (2) radio frequency identification (RFID) tags and readers; (3) fingerprint readers; and (4) mobile phones, can be used to dispel laptop theft. To achieve this, the researcher developed a system, using the heterogeneous devices mentioned above and a middleware that harnessed their unique capabilities to bring out the full potential of IoT in intelligently curbing laptop theft. The resulting system has the ability to: (1) monitor the presence of a laptop using RFID reader that pro-actively interrogates a passive tag attached to the laptop; (2) detect unauthorized removal of a laptop under monitoring; (3) instantly communicate security violations via cell phones; and (4) use Windows location sensors to track the position of a laptop using Googlemaps. The system also manages administrative tasks such as laptop registration, assignment and withdrawal which used to be handled manually. Experiments conducted using the resulting system prototype proved the hypothesis outlined for this research

    Study on the impact of regulation (EC) No 1/2005 on the protec-tion of animals during transport

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    The objective of the findings of an evaluation of Regulation (EC) 1/2005 was to provide a detailed assessment of the implementation of the Regulation (EC) and its impact on the animals being transported and on operators, with special reference to trade flows, navigation systems and the socio‐economic and regional implications

    The state of climate information services for agriculture and food security in West African countries

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    Wireless Sensor Networks for Condition Monitoring in the Railway Industry : a Survey

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    In recent years, the range of sensing technologies has expanded rapidly, whereas sensor devices have become cheaper. This has led to a rapid expansion in condition monitoring of systems, structures, vehicles, and machinery using sensors. Key factors are the recent advances in networking technologies such as wireless communication and mobile adhoc networking coupled with the technology to integrate devices. Wireless sensor networks (WSNs) can be used for monitoring the railway infrastructure such as bridges, rail tracks, track beds, and track equipment along with vehicle health monitoring such as chassis, bogies, wheels, and wagons. Condition monitoring reduces human inspection requirements through automated monitoring, reduces maintenance through detecting faults before they escalate, and improves safety and reliability. This is vital for the development, upgrading, and expansion of railway networks. This paper surveys these wireless sensors network technology for monitoring in the railway industry for analyzing systems, structures, vehicles, and machinery. This paper focuses on practical engineering solutions, principally,which sensor devices are used and what they are used for; and the identification of sensor configurations and network topologies. It identifies their respective motivations and distinguishes their advantages and disadvantages in a comparative review
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