Search results for: online flood prediction system

Authors: Ankit Shah, R. K. Shrivastava

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Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

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Authors: Husni Mohd Radzi, Lilie Zahara Ramly, Sapora Sipon, Salhah Abdullah

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Malaysia have been experiencing series of huge floods all around the country for the past decades despide planned development done by local authorities. The floods incurred due to factors like natural climate change or man-made disaster. Floods have caused a lot of damages, destructions and losses in term of infrastructure, financial implications and physical health. However, other damaging aspect was not being given much attention are the psychological need of the flood victim. The traumatic impact from the natural disaster like floods may cause serious psychological and spiritual deterioration. Many flood relief shelters in the past did not provide counseling services for flood victims to consult, and as a result, it contributes to added stress among the flood victims, as the issue were not being addressed. Some studies indicates that flood victims did not look for counseling service being offered. A total of 257 flood victim was involved in this study. Main area of the study was Kg Bukit Changgang, Kg. Rancangan Tanah Belia, Kg. Labohan Dagang and Kg.Olak Lempit in Kuala Langat, Selangor. The flood victims have responded to the survey given and the data was analyze using SPSS for descriptive information and other measures. At least 13 victims were reported to have experienced moderate to severe level of stress and anxiety over the flood disaster incidents and a total of 88 respondents admitted to have at least thought and consider getting counseling service.

Keywords: perception, acceptance towards counseling, counseling service for flood victim, disaster

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Authors: Heny Hartono, Cecilia Titiek Murniati

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The pandemic has given teachers and students no other choice but having full online learning. In such an emergency situation as the time of the covid-19 pandemic, the application of LMS (Learner Management System) in higher education is the most reasonable solution for students and teachers. In fact, the online learning requires all elements of a higher education systems, including the human resources, infrastructure, and supporting systems such as the application, server, and stable internet connection. The readiness of the higher education institution in preparing the online system may secure those who are involved in the online learning process. It may also result in students’ self-efficacy in online learning. This research aimed to investigate how students perceive their self-efficacy in online English learning, especially in speaking classes which is considered as a productive language skill. This research collects qualitative data with narrative inquiry involving 25 students of speaking classes as the respondents. The results of this study show that students perceive their self-efficacy in speaking online classes as not very high.

Keywords: self-efficacy, online learning, speaking class, college students, e-learning

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Authors: Siti Hajar Ya’acob, Nor Sayzwani Sukri, Farah Khaliz Kedri, Rozidaini Mohd Ghazi, Nik Raihan Nik Yusoff, Aweng A/L Eh Rak

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Flood event that occurred in mid-December 2014 in East Coast of Peninsular Malaysia has driven attention from the public nationwide. Apart from loss and damage of properties and belongings, the massive flood event has introduced environmental disturbances on surface water resources in such flood affected area. A study has been conducted to measure the physical and chemical composition of Galas River and Pergau River prior to identification the flood impact towards environmental deterioration in surrounding area. Samples that have been collected were analyzed in-situ using YSI portable instrument and also in the laboratory for acid digestion and heavy metals analysis using Atomic Absorption Spectroscopy (AAS). Results showed that range of temperature (0C), DO (mg/L), Ec (µs/cm), TDS (mg/L), turbidity (NTU), pH, and salinity were 25.05-26.65, 1.51-5.85, 0.032-0.054, 0.022-0.035, 23.2-76.4, 3.46-7.31, and 0.01-0.02 respectively. The results from this study could be used as a primary database to evaluate the status of water quality of the respective river after the massive flood.

Keywords: flood, river, heavy metals, AAS

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Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

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Authors: Cedric Leong, Parth Desai, Parth Patel

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The purpose of this project was to develop a neural network based on qualitative team data to predict alliance scores to determine winners of matches in the FIRST Robotics Competition (FRC). The game for the competition changes every year with different objectives and game objects, however the idea was to create a prediction system which can be reused year by year using some of the statistics that are constant through different games, making our system adaptable to future games as well. Aerial Assist is the FRC game for 2014, and is played in alliances of 3 teams going against one another, namely the Red and Blue alliances. This application takes any 6 teams paired into 2 alliances of 3 teams and generates the prediction for the final score between them.

Keywords: artifical neural network, prediction system, qualitative team data, FIRST Robotics Competition (FRC)

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Authors: Freddy Houndekindo

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A study was carried out to evaluate the flood risk in the district of Malanville located along the Niger River. The knowledge produce by this study is useful in the implementation of adaptation and/or mitigation measures to alleviate the impact of the flooding on the populations, the economy and the environment. Over the course of the study, the lack of data in the area of interest has been one of the main challenges encountered. Therefore, in the analysis of the flood hazard different sources of remotely sensed data were used. Moreover, the flood hazard was analysed by applying a 1D hydraulic model: HEC-RAS. After setting up the model for the study area, the different flood scenarios considered were simulated and mapped using ArcGIS and the HEC-GEORAS extension. The result of the simulation gave information about the inundated areas and the water depths at each location. From the analysis of the flood hazard, it was found that between 47% and 50% of the total area of the district of Malanville would be flooded in the different flood scenarios considered, and the water depth varies between 1 and 7 m. The townships of Malanville most at risk of flooding are Momkassa and Galiel, located in a high-risk and very high-risk zone, respectively. Furthermore, the assessment of the flood risk showed that the most vulnerable sector to the inundations is the agricultural sector. Indeed, the cultivated floodplains were the most affected areas by the floodwater in every flood scenarios. Knowing that a high proportion of the population of the district relies on their farmlands in these floodplains for their livelihood, the floods pose a challenge not only to the food security in the area but also to its development.

Keywords: flood risk management, Niger, remote sensing, vulnerability

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Larry Wang

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The aim of this paper is to demonstrate how an online homework system is integrated in teaching and learning mathematics and how it improves the student success rates in some gateway mathematics courses. WeBWork provided by the Mathematical Association of America is adopted as the online homework system. During the period of 2010-2015, the system was implemented in classes of precalculus, calculus, probability and statistics, discrete mathematics, linear algebra, and differential equations. As a result, the passing rates of the sections with WeBWork are well above other sections without WeBWork (about 7-10% higher). The paper also shows how the WeBWork system was used.

Keywords: gateway mathematics, online grading, pass rate, WeBWorK

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Authors: Kefaya Qaddoum

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The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

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Authors: Malani Herath, Sohan Wijesekera, Jagath Munasingha

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The impact of recent floods become significant, and the extraordinary flood events cause considerable damage to lives, properties, environment and negatively affect the whole development of Colombo urban region. Even though the Colombo urban region experiences recurrent flood impacts, several spatial planning interventions have been taken from time to time since early 20th century. All past plans have adopted a traditional approach to flood management, using infrastructural measures to reduce the chance of flooding together with rigid planning regulations. The existing flood risk management practices do not operate to be acceptable by the local community particular the urban poor. Researchers have constantly reported the differences in estimations of flood risk, priorities, concerns of experts and the local community. Risk-based decision making in flood management is not only a matter of technical facts; it has a significant bearing on how flood risk is viewed by local community and individuals. Moreover, sustainable flood management is an integrated approach, which highlights joint actions of experts and community. This indicates the necessity of further societal discussion on the acceptable level of flood risk indicators to prioritize and identify the appropriate flood management measures in Colombo. The understanding and evaluation of flood risk by local people are important to integrate in the decision-making process. This research questioned about the gap between the acceptable level of flood risk to spatial planners and to the local communities in Colombo. A comprehensive literature review was conducted to prepare a framework to analyze the public perception in Colombo. This research work identifies the factors that affect the variation of flood risk and acceptable levels to both local community and planning authorities.

Keywords: Colombo basin, public perception, urban flood risk, multi-criteria analysis

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Authors: Reini S. Ilmiaty, Muhammad B. Al Amin, Sarino, Muzamil Jariski

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Kedukan River is an artificial river which serves as a Watershed Boang drainage channel in Palembang. The river has upstream and downstream connected to Musi River, that often overflowing and flooding caused by the huge runoff discharge and high tide water level of Musi River. This study aimed to analyze the flood water surface profile on Kedukan River continued with flood inundation simulation to determine flooding prone areas in research area. The analysis starts from the peak runoff discharge calculations using rational method followed by water surface profile analysis using HEC-RAS program controlled by manual calculations using standard stages. The analysis followed by running flood inundation simulation using ArcGIS program that has been integrated with HEC-GeoRAS. Flood inundation simulation on Kedukan River creates inundation characteristic maps with depth, area, and circumference of inundation as the parameters. The inundation maps are very useful in providing an overview of flood prone areas in Kedukan River.

Keywords: flood modelling, HEC-GeoRAS, HEC-RAS, inundation map

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Authors: R. W. Brown, P. J. Blignaut

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An online performance management system was evaluated, and recommendations were made to improve the system. The study shows the effects of not adhering to the established web design principles and conventions. Furthermore, the study indicates that if the online performance management system is not well designed, it may have negative effects on the overall usability of the system and these negative effects will have consequences for both the employer and employees. The evaluation was done in terms of the usability metrics of effectiveness, efficiency and user satisfaction. Effectiveness was measured in terms of the success rate with which users could execute prescribed tasks in a sandbox system. Efficiency was expressed in terms of the time it took participants to understand what is expected of them and to execute the tasks. Post-test questionnaires were used in order to determine the satisfaction of the participants. Recommendations were made to improve the usability of the online performance management system.

Keywords: eye tracking, human resource management, performance management, usability

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Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map

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Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

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Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km², and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: watershed simulation, WetSpa, stream flow, flood prediction

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Authors: Moudi Almousa

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This research paper explores Saudi Arabian female consumers’ experiences using 3D body scanning technology and their level of acceptance of possible market applications of this technology to adopt for apparel online shopping. Data was collected for 82 women after being scanned then viewed a short video explaining three possible scenarios of 3D body scanning applications, which include size prediction, customization, and virtual try-on, before completing the survey questionnaire. Although respondents have strong positive responses towards the scanning experience, the majority were concerned about their privacy during the scanning process. The results indicated that size prediction and virtual try on had greater market application potential and a higher chance of crossing the gap based on consumer interest. The results of the study also indicated a strong positive correlation between respondents’ concern with inability to try on apparel products in online environments and their willingness to use the 3D possible market applications.

Keywords: 3D body scanning, market applications, online, apparel fit

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Authors: Thomas Ruppert, Shana Jones, J. Scott Pippin

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State and federal government agencies within the United States have recently invested substantial resources into studies of future flood risk conditions associated with climate change and sea-level rise. A review of numerous case studies has uncovered several key themes that speak to an overall incoherence within current flood risk assessment procedures in the U.S. context. First, there are substantial local differences in the quality of available information about basic infrastructure, particularly with regard to local stormwater features and essential facilities that are fundamental components of effective flood hazard planning and mitigation. Second, there can be substantial mismatch between regulatory Flood Insurance Rate Maps (FIRMs) as produced by the National Flood Insurance Program (NFIP) and other 'current condition' flood assessment approaches. This is of particular concern in areas where FIRMs already seem to underestimate extant flood risk, which can only be expected to become a greater concern if future FIRMs do not appropriately account for changing climate conditions. Moreover, while there are incentives within the NFIP’s Community Rating System (CRS) to develop enhanced assessments that include future flood risk projections from climate change, the incentive structures seem to have counterintuitive implications that would tend to promote moral hazard. In particular, a technical finding of higher future risk seems to make it easier for a community to qualify for flood insurance savings, with much of these prospective savings applied to individual properties that have the most physical risk of flooding. However, there is at least some case study evidence to indicate that recognition of these issues is prompting broader discussion about the need to move beyond FIRMs as a standalone local flood planning standard. The paper concludes with approaches for developing climate adaptation and flood resilience strategies in the U.S. that move away from the social welfare model being applied through NFIP and toward more of an informed risk approach that transfers much of the investment responsibility over to individual private property owners.

Keywords: climate change adaptation, flood risk, moral hazard, sea-level rise

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Authors: Lumindu Dilumka, Ranaweera I. D., Sudusinghe S. P., Sanduni Kanchana A. M. K.

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This study was motivated by the challenges experienced by parents and guardians in ensuring the safety of children in cyberspace. In the last two or three years, online education has become very popular all over the world due to the Covid 19 pandemic. Therefore, parents, guardians and teachers must ensure the safety of children in cyberspace. Children are more likely to go astray and there are plenty of online programs are waiting to get them on the wrong track and also, children who are engaging in the online education can be distracted at any moment. Therefore, parents should keep a close check on their children's online activity. Apart from that, due to the unawareness of children, they tempt to share their sensitive information, causing a chance of being a victim of phishing attacks from outsiders. These problems can be overcome through the proposed web-based system. We use feature extraction, web tracking and analysis mechanisms, image processing and name entity recognition to implement this web-based system.

Keywords: online education, cyber bullying, social media, face recognition, web tracker, privacy data

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Authors: Siti Murniningsih, Evi Anggraheni

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Various infrastructures such as dams, flood control dams and reservoirs have been developed in the 19th century until the 20th century. These infrastructures are very effective in controlling the river flows and in preventing inundation in the urban area prone to flooding. Flooding in the urban area often brings large impact, affecting every aspect of life and also environment. Ciliwung is one of the rivers allegedly contributes to the flooding problems in Jakarta; various engineering work has been done in Ciliwung river to help controlling the flooding. One of the engineering work is to build Ciawi Dam and Sukamahi Dam. In this research, author is doing the flood calculation with Nakayasu Method, while the previous flooding in that case study is computed using Level Pool Routine. The effectiveness of these dams can be identified by using flood simulation of existing condition and compare it to the flood simulation after the dam construction. The final goal of this study is to determine the effectiveness of flood mitigation infrastructure located at upstream area in reducing the volume of flooding in Jakarta.

Keywords: effectiveness, flood simulation, infrastructure flooding, level pool routine

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Authors: Suresh Hettiarachchi, Conrad Wasko, Ashish Sharma

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The ever changing and expanding urban landscape increases the stress on urban systems to support and maintain safe and functional living spaces. Flooding presents one of the more serious threats to this safety, putting a larger number of people in harm’s way in congested urban settings. Climate change is adding to this stress by creating a dichotomy in the urban flood response. On the one hand, climate change is causing storms to intensify, resulting in more destructive, rarer floods, while on the other hand, longer dry periods are decreasing the severity of more frequent, less intense floods. This variability is creating a need to be more agile and innovative in how we design for and manage urban flooding. Here, we argue that to cope with this challenge climate change brings, we need to move towards urban flood management through resilience rather than flood prevention. We also argue that dealing with the larger variation in flood response to climate change means that we need to look at flooding from all aspects rather than the single-dimensional focus of flood depths and extents. In essence, we need to rethink how we manage flooding in the urban space. This change in our thought process and approach to flood management requires a practical way to assess and quantify resilience that is built into the urban landscape so that informed decision-making can support the required changes in planning and infrastructure design. Towards that end, we propose a Simple Urban Flood Resilience Index (SUFRI) based on a robust definition of resilience as a tool to assess flood resilience. The application of a simple resilience index such as the SUFRI can provide a practical tool that considers urban flood management in a multi-dimensional way and can present solutions that were not previously considered. When such an index is grounded on a clear and relevant definition of resilience, it can be a reliable and defensible way to assess and assist the process of adapting to the increasing challenges in urban flood management with climate change.

Keywords: urban flood resilience, climate change, flood management, flood modelling

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Authors: S. Channgam, A. Sae-Tang, T. Termsaithong

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In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions.

Keywords: Bak-Tang-Wiesenfeld sandpile model, cross-correlation, avalanches, prediction method

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Authors: Ahmed S. Afifi, Ahmed Magdy

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Satellite monitoring is an essential tool to study, understand, and map large-scale environmental changes that affect humans, climate, and biodiversity. The Sentinel-1 Synthetic Aperture Radar (SAR) instrument provides a high collection of data in all-weather, short revisit time, and high spatial resolution that can be used effectively in flood management. Floods occur when an overflow of water submerges dry land that requires to be distinguished from flooded areas. In this study, we use global flood mapper (GFM), a new google earth engine application that allows users to quickly map floods using Sentinel-1 SAR. The GFM enables the users to adjust manually the flood map parameters, e.g., the threshold for Z-value for VV and VH bands and the elevation and slope mask threshold. The composite R:G:B image results by coupling the bands of Sentinel-1 (VH:VV:VH) reduces false classification to a large extent compared to using one separate band (e.g., VH polarization band). The flood mapping algorithm in the GFM and the Otsu thresholding are compared with Sentinel-2 optical data. And the results show that the GFM algorithm can overcome the misclassification of a flooded area in An Giang, Vietnam.

Keywords: SAR backscattering, Sentinel-1, flood mapping, disaster

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

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Authors: Hafiz Muhammad Tayyab Bhatti, Munazza Usmani

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One of nature's most destructive occurrences, floods do immense damage to communities and economic losses. Nigeria country, specifically southern Nigeria, is known for being prone to flooding. Even though periodic flooding occurs in Nigeria frequently, the floods of 2022 were the worst since those in 2012. Flood vulnerability analysis and mapping are still lacking in this region due to the very limited historical hydrological measurements and surveys on the effects of floods, which makes it difficult to develop and put into practice efficient flood protection measures. Remote sensing and Geographic Information Systems (GIS) are useful approaches to detecting, determining, and estimating the flood extent and its impacts. In this study, NOAA VIIR has been used to extract the flood extent using the flood water fraction data and afterward fused with GIS data for some zonal statistical analysis. The estimated possible flooding areas are validated using satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). The goal is to map and studied flood extent, flood hazards, and their effects on the population, schools, and health facilities for each state of Nigeria. The resulting flood hazard maps show areas with high-risk levels clearly and serve as an important reference for planning and implementing future flood mitigation and control strategies. Overall, the study demonstrated the viability of using the chosen GIS and remote sensing approaches to detect possible risk regions to secure local populations and enhance disaster response capabilities during natural disasters.

Keywords: flood hazards, remote sensing, damage assessment, GIS, geospatial analysis

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Authors: Han Bing, Yin Zhenjie

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In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

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Authors: Sameen Masood, Muhammad Ali Jibran

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The frequent flood history in Pakistan has pronounced the need for disaster risk management. Various policies are formulated and steps are being taken by the government in order to cope with the flood effects. However, a much promising pro-active approach that is globally acknowledged is educating the masses regarding living with risk and uncertainty. Unfortunately, majority of the flood victims in Pakistan are poor and illiterate which also transpires as a significant cause of their distress. An illiterate population is not risk averse or equipped intellectually regarding how to prepare and protect against natural disasters. The current research utilizes a cross-disciplinary approach where the role of education (both formal and informal) and indigenous knowledge is explored with reference to disaster preparedness. The data was collected from the flood prone rural areas of Punjab. In the absence of disaster curriculum taught in formal schools, informal education disseminated by NGOs and relief and rehabilitation agencies was the only education given to the flood victims. However the educational attainment of flood victims highly correlated with their awareness regarding flood management and disaster preparedness. Moreover, lessons learned from past flood experience generated indigenous knowledge on the basis of which flood victims prepared themselves for any uncertainty. If the future policy regarding disaster preparation integrates indigenous knowledge and then delivers education on the basis of that, it is anticipated that the flood devastations can be much reduced. Education can play a vital role in amplifying perception of risk and taking precautionary measures for disaster. The findings of the current research will provide practical strategies where disaster preparedness through education has not yet been applied.

Keywords: education, disaster preparedness, illiterate population, risk management

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Authors: Oussama Derdous, Lakhdar Djemili, Hamza Bouchehed

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The potential risks associated with dam break flooding could be considerable and result in major damage, including loss of life and property destruction. In the past, Algeria experienced such flood disasters; let’s recall the failure of Fergoug dam in 1881, this accident cost 200 lives, many houses and bridges were destroyed by the flooding. Recently the Algerian government have obligated to dam owners the development of detailed dam break Emergency Action Plans for its 64 major dams. The research presented here was conducted within this framework, Zardezas dam which is located in the city of Skikda in the North East of Algeria was the case of study. The model HEC-RAS was used for the hydrodynamic routing of the dam break flood wave. In addition, Geographic Information System (GIS) was used to create inundation maps and produce a visualization of the flood propagation in the Saf-Saf River.The simulation results that demonstrate the significance of Zardezas dam break flooding; constitute a real tool for developing emergency response plans and assisting territorial communities in land use planning.

Keywords: dam break, HEC-RAS, GIS, inundation maps, Emergency Action Plan

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Authors: Bikramjit Goswami, Manoranjan Kalita

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Active microwave remote sensing is useful in remote sensing applications in cloud-covered regions in the world. Because of high spatial resolution, the spatial variations of land cover can be monitored in greater detail using synthetic aperture radar (SAR). Inundation is studied using the SAR images obtained from Sentinel-1A in both VH and VV polarizations in the present experimental study. The temporal variation of the SAR scattering coefficient values for the area gives a good indication of flood and its boundary. The study area is the district of Morigaon in the state of Assam in India. The period of flood monitoring study is the monsoon season of the year 2017, during which high flood occurred in the state of Assam. The variation of microwave scattering value shows a distinctive indication of flood from the non-flooded period. Frequent monitoring of flood in a large area (10 km x 10 km) using passive microwave sensing and pin-pointing the actual flooded portions (5 m x 5 m) within the flooded area using active microwave sensing, can be a highly useful combination, as revealed by the present experimental results.

Keywords: active remote sensing, flood monitoring, microwave remote sensing, synthetic aperture radar

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Authors: Alvaro Figueira, Bruno Cabral

Abstract:

Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

Procedia PDF Downloads 98

Authors: K. Roushanger, A. Soleymanzadeh

Abstract:

Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs.

Keywords: discharge coefficient, genetic expression programming, trapezoidal weir

Procedia PDF Downloads 362