Search results for: Water demand forecast; Neural Networks model; water resources management; Saudi Arabia.

Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye

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In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.

Keywords: Robust exponential stability, delay-dependent stability, discrete-time neutral networks, time-varying delays.

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Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

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Average temperatures worldwide are expected to continue to rise. At the same time, major cities in developing countries are becoming increasingly populated and polluted. Governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of a model, which is able to estimate the occupant exposure to extreme temperatures and high air pollution within domestic buildings. Building physics simulations were performed using the EnergyPlus building physics software. An accurate metamodel is then formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) have been compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: Neural Networks, Radial Basis Functions, Metamodelling, Python machine learning libraries.

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Authors: P. M. Natarajan, Shambhu Kallolikar, S. Ganesh

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By size and volume of water, Ganges River basin is the biggest among the fourteen major river basins in India. By Hindu’s faith, it is the main ‘holy river’ in this nation. But, of late, the pollution load, both domestic and industrial sources are deteriorating the surface and groundwater as well as land resources and hence the environment of the Ganges River basin is under threat. Seeing this scenario, the Indian government began to reclaim this river by two Ganges Action Plans I and II since 1986 by spending Rs. 2,747.52 crores ($457.92 million). But the result was no improvement in the water quality of the river and groundwater and environment even after almost three decades of reclamation, and hence now the New Indian Government is taking extra care to rejuvenate this river and allotted Rs. 2,037 cores ($339.50 million) in 2014 and Rs. 20,000 crores ($3,333.33 million) in 2015. The reasons for the poor water quality and stinking environment even after three decades of reclamation of the river are either no treatment/partial treatment of the sewage. Hence, now the authors are suggesting a tertiary level treatment standard of sewages of all sources and origins of the Ganges River basin and recycling the entire treated water for nondomestic uses. At 20million litres per day (MLD) capacity of each sewage treatment plant (STP), this basin needs about 2020 plants to treat the entire sewage load. Cost of the STPs is Rs. 3,43,400 million ($5,723.33 million) and the annual maintenance cost is Rs. 15,352 million ($255.87 million). The advantages of the proposed exercise are: we can produce a volume of 1,769.52 million m³ of biogas. Since biogas is energy, can be used as a fuel, for any heating purpose, such as cooking. It can also be used in a gas engine to convert the energy in the gas into electricity and heat. It is possible to generate about 3,539.04 million kilowatt electricity per annum from the biogas generated in the process of wastewater treatment in Ganges basin. The income generation from electricity works out to Rs 10,617.12million ($176.95million). This power can be used to bridge the supply and demand gap of energy in the power hungry villages where 300million people are without electricity in India even today, and to run these STPs as well. The 664.18 million tonnes of sludge generated by the treatment plants per annum can be used in agriculture as manure with suitable amendments. By arresting the pollution load the 187.42 cubic kilometer (km³) of groundwater potential of the Ganges River basin could be protected from deterioration. Since we can recycle the sewage for non-domestic purposes, about 14.75km³ of fresh water per annum can be conserved for future use. The total value of the water saving per annum is Rs.22,11,916million ($36,865.27million) and each citizen of Ganges River basin can save Rs. 4,423.83/ ($73.73) per annum and Rs. 12.12 ($0.202) per day by recycling the treated water for nondomestic uses. Further the environment of this basin could be kept clean by arresting the foul smell as well as the 3% of greenhouse gages emission from the stinking waterways and land. These are the ways to reclaim the waterways of Ganges River basin from deterioration.

Keywords: Holy Ganges River, lifeline of India, wastewater treatment and management, making Ganges permanently holy.

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Authors: Abbas R. Ali, Safa H. Abdulrahman

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In this study, forty samples had been collected from water of Lesser Zab River and drinking water to determine fluoride concentration and show the impact of fluoride on general health of society of Kirkuk city. Estimation of fluoride concentration and determination of its proportion in water samples were performed attentively using a fluoride ion selective electrode. The fluoride concentrations in the Lesser Zab River samples were between 0.0265 ppm and 0.0863 ppm with an average of 0.0451 ppm, whereas the average fluoride concentration in drinking water samples was 0.102 ppm and ranged from 0.010 to 0.289 ppm. A comparison between results obtained with World Health Organization (WHO) show a low concentration of fluoride in the samples of the study. Thus, for health concerns we should increase the concentration of this ion in water of Kirkuk city at least to about (1.0 ppm) and this will take place after fluorination process.

Keywords: Fluoride concentration, Lesser Zab River, drinking water, health society, Kirkuk city.

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Authors: G. Jelic Mrcelic, M. Sliskovic

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In Croatia, the majority of cultured marine fish species are reared in net cages. The intensive production of the fish in net cages may generate the considerable amount of bio waste and change water quality especially in enclosed and semi-enclosed coastal areas. The aim of this paper is to assess the potential impact of sea bass (Dicentrarchus labrax L.) cage farm on water quality. The weak relationship between food supply and water quality parameters (nutrient content and phytoplankton biomass) was found, but significant changes in oxygen saturation was observed in the cages during the warmer period of a year especially in the morning (occasionally it dropped below 70 %). Despite of, satisfactory results of water quality parameters, it is necessary to establish comprehensive monitoring process, especially to include quality assessment of fouling communities.

Keywords: Mariculture, monitoring, fish cages, water quality parameters.

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Authors: L. Salhi, M. Talbi, A. Cherif

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This paper presents a new strategy of identification and classification of pathological voices using the hybrid method based on wavelet transform and neural networks. After speech acquisition from a patient, the speech signal is analysed in order to extract the acoustic parameters such as the pitch, the formants, Jitter, and shimmer. Obtained results will be compared to those normal and standard values thanks to a programmable database. Sounds are collected from normal people and patients, and then classified into two different categories. Speech data base is consists of several pathological and normal voices collected from the national hospital “Rabta-Tunis". Speech processing algorithm is conducted in a supervised mode for discrimination of normal and pathology voices and then for classification between neural and vocal pathologies (Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation results will be presented in function of the disease and will be compared with the clinical diagnosis in order to have an objective evaluation of the developed tool.

Keywords: Formants, Neural Networks, Pathological Voices, Pitch, Wavelet Transform.

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Authors: S. Sadhishkumar, T. Balusamy

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A single-phase closed thermosyphon has been fabricated and experimented to utilize solar energy for water heating. The working fluid of the closed thermosyphon is heated at the flatplate collector and the hot water goes to the water tank due to density gradient caused by temperature differences. This experimental work was done using insulated water tank and insulated connecting pipe between the tank and the flat-plate collector. From the collected data, performance parameters such as instantaneous collector efficiency and heat removal factor are calculated. In this study, the effects of glazing were also observed. The water temperature rise and the maximum instantaneous efficiency obtained from this experiment with glazing using insulated water tank and insulated connecting pipe are 17°C in a period of 5 hours and 60% respectively. Whereas the water temperature rise and the maximum instantaneous efficiency obtained from this experiment with glazing using non-insulated water tank and non-insulated connecting pipe are 14°C in a period of 5 hours and 39% respectively.

Keywords: Solar water heating systems, Single-phase thermosyphon, Flat-plate collector, Insulated tank and pipe.

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Authors: Roy J. Issa

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Spray chilling using air-mist nozzles has received much attention in the food processing industry because of the benefits it has shown over forced air convection. These benefits include an increase in the heat transfer coefficient and a reduction in the water loss by the product during cooling. However, few studies have simulated the heat transfer and aerodynamics phenomena of the air-mist chilling process for optimal operating conditions. The study provides insight into the optimal conditions for spray impaction, heat transfer efficiency and control of surface flooding. A computational fluid dynamics model using a two-phase flow composed of water droplets injected with air is developed to simulate the air-mist chilling of food products. The model takes into consideration droplet-to-surface interaction, water-film accumulation and surface runoff. The results of this study lead to a better understanding of the heat transfer enhancement, water conservation, and to a clear direction for the optimal design of air-mist chilling systems that can be used in commercial applications in the food and meat processing industries.

Keywords: Droplets impaction efficiency, Droplet size, Heat transfer enhancement factor, Water runoff.

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Authors: Hadi Veisi, Mansour Jamzad

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In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

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Authors: Chokri Slim

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The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

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Authors: Zahra Yazdani Paraii, Zohreh Yazdani Paraei

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Many urban designers and planners have been involved in the design of environmentally friendly or nature adaptable urban development models due to increase in urban populations in the recent century, limitation on natural resources, climate change, and lack of enough water and food. Ecological city is one of the latest models proposed to accomplish the latter goal. In this work, the existing establishing indicators of the ecological city are used regarding energy, water, land use and transportation issues. The model is used to compare the function of traditional settlements of Iran. The result of investigation shows that the specifications and functions of the traditional settlements of Iran fit well into the ecological city model. It is found that the inhabitants of the old cities and villages in Iran had founded ecological cities based on their knowledge of the environment and its natural opportunities and limitations.

Keywords: Ecological city, traditional city, urban design, environment.

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Authors: Alaa Hussein Wadi

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The principal objective of a water treatment plant is to produce water that satisfies a set of drinking water quality standards at a reasonable price to the consumers. The gravel-bed flocculator provide a simple and inexpensive design for flocculation in small water treatment plants (less than 5000 m3/day capacity). The packed bed of gravel provides ideal conditions for the formation of compact settleable flocs because of continuous recontact provided by the sinuous flow of water through the interstices formed by the gravel. The field data which were obtained from the operation of the water supply treatment unit cover the physical, chemical and biological water qualities of the raw and settled water as obtained by the operation of the treatment unit. The experiments were carried out with the aim of assessing the efficiency of the gravel filter in removing the turbidity, pathogenic bacteria, from the raw water. The water treatment plant, which was constructed for the treatment of river water, was in principle a rapid sand filter. The results show that the average value of the turbidity level of the settled water was 4.83 NTU with a standard deviation of turbidity 2.893 NTU. This indicated that the removal efficiency of the sedimentation tank (gravel filter) was about 67.8 %. for pH values fluctuated between 7.75 and 8.15, indicating the alkaline nature of the raw water of the river Shatt Al-Hilla, as expected. Raw water pH is depressed slightly following alum coagulation. The pH of the settled water ranged from 7.75 to a maximum of 8.05. The bacteriological tests which were carried out on the water samples were: total coliform test, E-coli test, and the plate count test. In each test the procedure used was as outlined in the Standard Methods for the Examination of Water and Wastewater (APHA, AWWA, and WPCF, 1985). The gravel filter exhibit a low performance in removing bacterial load. The percentage bacterial removal, which is maximum for total plate count (19%) and minimum for total coliform (16.82%).

Keywords: Gravel bed flocculator, turbidity, total coliform.

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Authors: Sangbum Park, Namki Lee, Youngjoon Han, Hernsoo Hahn

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In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.

Keywords: accumulated histogram, water level detection, band pass filter.

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Authors: Jie Zhao, Meng Su

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Image recognition enables machine-like robotics to understand a scene and plays an important role in computer vision applications. Computer vision platforms as physical infrastructure, supporting Neural Networks for image recognition, are deterministic to leverage the performance of different Neural Networks. In this paper, three different computer vision platforms – edge AI (Jetson Nano, with 4GB), a standalone laptop (with RTX 3000s, using CUDA), and a web-based device (Google Colab, using GPU) are investigated. In the case study, four prominent neural network architectures (including AlexNet, VGG16, GoogleNet, and ResNet (34/50)), are deployed. By using public ImageNets (Cifar-10), our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: AlexNet, VGG, GoogleNet, ResNet, ImageNet, Cifar-10, Edge AI, Jetson Nano, CUDA, GPU.

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: F. Behrouzi, A. Maimun, M. Nakisa

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The growth of population, rising fossil fuel prices (limited and decreasing day by day), pollution problem due to use of fossil fuels and increasing electrical demand are important factors that encourage the use of green and renewable energy technologies. Among the different renewable energy technologies, hydro power generation (large and small scale) is the prime choice in terms of contribution to the world's electricity generation by using water current turbines. Currently, researchers mainly focused on design and development of different kind of turbines to capture hydropower to generate electricity as clean and reliable energy. This paper is a review of the status of research on water current turbines carried out to generate electricity from hydrokinetic energy especially in places where there is no electricity, but there is access to flowing water.

Keywords: Turbines, Renewable Energy, Hydropower.

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Authors: Hazem M. El-Bakry

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In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.

Keywords: Boolean functions, simplification, Karnough map, implementation of logic functions, modular neural networks.

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Authors: H. M. Kelash, H. M. Faheem, M. Amoon

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The demand for autonomous resource management for distributed systems has increased in recent years. Distributed systems require an efficient and powerful communication mechanism between applications running on different hosts and networks. The use of mobile agent technology to distribute and delegate management tasks promises to overcome the scalability and flexibility limitations of the currently used centralized management approach. This work proposes a multiagent system that adopts mobile agents as a technology for tasks distribution, results collection, and management of resources in large-scale distributed systems. A new mobile agent-based approach for collecting results from distributed system elements is presented. The technique of artificial intelligence based on intelligent agents giving the system a proactive behavior. The presented results are based on a design example of an application operating in a mobile environment.

Keywords: distributed management, distributed systems, efficiency, mobile agent, multiagent, response time

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Authors: Kasthurirangan Gopalakrishnan, Anshu Manik

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Subgrade moisture content varies with environmental and soil conditions and has significant influence on pavement performance. Therefore, it is important to establish realistic estimates of expected subgrade moisture contents to account for the effects of this variable on predicted pavement performance during the design stage properly. The initial boundary soil suction profile for a given pavement is a critical factor in determining expected moisture variations in the subgrade for given pavement and climatic and soil conditions. Several numerical models have been developed for predicting water and solute transport in saturated and unsaturated subgrade soils. Soil hydraulic properties are required for quantitatively describing water and chemical transport processes in soils by the numerical models. The required hydraulic properties are hydraulic conductivity, water diffusivity, and specific water capacity. The objective of this paper was to determine isothermal moisture profiles in a soil fill and predict the soil moisture movement above the ground water table using a simple one-dimensional finite difference model.

Keywords: Fill, Hydraulic Conductivity, Pavement, Subgrade.

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Authors: Seong-Pil Kang, Ho-Jung Ryu, Yongwon Seo

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Hydrate phase equilibria for the binary CO2+water and CH4+water mixtures in silica gel pore of nominal diameters 6, 30, and 100 nm were measured and compared with the calculated results based on van der Waals and Platteeuw model. At a specific temperature, three-phase hydrate-water-vapor (HLV) equilibrium curves for pore hydrates were shifted to the higher-pressure condition depending on pore sizes when compared with those of bulk hydrates. Notably, hydrate phase equilibria for the case of 100 nominal nm pore size were nearly identical with those of bulk hydrates. The activities of water in porous silica gels were modified to account for capillary effect, and the calculation results were generally in good agreement with the experimental data. The structural characteristics of gas hydrates in silica gel pores were investigated through NMR spectroscopy.

Keywords: CO2, CH4, gas hydrate, equilibria.

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Authors: Bahar Razavi, Mansour Parehkar, Ali Gholami

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Pore water pressure is normally because of consolidation, compaction and water level fluctuation on reservoir. Measuring, controlling and analyzing of pore water pressure have significant importance in both of construction and operation period. Since end of 2002, (dam start up) nature of KARKHEH dam has been analyzed by using the gathered information from instrumentation system of dam. In this lecture dam condition after start up have been analyzed by using the gathered data from located piezometers in core of dam. According to TERZAGHI equation and records of piezometers, consolidation lasted around five years during early years of construction stage, and current pore water pressure in core of dam is caused by water level fluctuation in reservoir. Although there is time lag between water level fluctuation and results of piezometers. These time lags have been checked and the results clearly show that one of the most important causes of it is distance between piezometer and reservoir.

Keywords: Earth dam, Reservoir, Piezometer, Terzaghi, Consolidation

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Authors: Shaival H. Nagarsheth, Utpal Pandya, Hemant J. Nagarsheth

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Cross flow water tube heat exchanger can be designed and made operational using methods of model building and simulation of the system. This paper projects the design and development of a model of cross flow water tube heat-exchanger system, simulation and validation of control analysis of different tuning methods. Feedback and override control system is developed using inputs acquired with the help of sensory system. A mathematical model is formulated for analysis of system behaviour. The temperature is regulated at the desired set point automatically.

Keywords: Heat Exchanger, Feedback, Override, Temperature, PID.

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.

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Authors: Satean Tunyasrirut, Tianchai Suksri, Arjin Numsomran, Supan Gulpanich, Kitti Tirasesth

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This paper presents the approach to design the Auto- Tuning PID controller for interactive Water Level Process using integral step response. The Integral Step Response (ISR) is the method to model a dynamic process which can be done easily, conveniently and very efficiently. Therefore this method is advantage for design the auto tune PID controller. Our scheme uses the root locus technique to design PID controller. In this paper MATLAB is used for modeling and testing of the control system. The experimental results of the interacting water level process can be satisfyingly illustrated the transient response and the steady state response.

Keywords: Coupled-Tank, Interacting water level process, PIDController, Auto-tuning.

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Authors: E. A. Kiridi, A. O. Ogunlela

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Pollutants from aquacultural practices constitute environmental problems and phytoremediation could offer cheaper environmentally sustainable alternative since equipment using advanced treatment for fish tank effluent is expensive to import, install, operate and maintain, especially in developing countries. The main objective of this research was, therefore, to develop a mathematical model for phytoremediation by aquatic plants in aquaculture wastewater. Other objectives were to evaluate the retention times on phytoremediation rates using the model and to measure the nutrient level of the aquaculture effluent and phytoremediation rates of three aquatic macrophytes, namely; water hyacinth (Eichornia crassippes), water lettuce (Pistial stratoites) and morning glory (Ipomea asarifolia). A completely randomized experimental design was used in the study. Approximately 100 g of each macrophyte were introduced into the hydroponic units and phytoremediation indices monitored at 8 different intervals from the first to the 28^th day. The water quality parameters measured were pH and electrical conductivity (EC). Others were concentration of ammonium–nitrogen (NH4⁺ -N), nitrite- nitrogen (NO₂^- -N), nitrate- nitrogen (NO₃^- -N), phosphate –phosphorus (PO₄^3- -P), and biomass value. The biomass produced by water hyacinth was 438.2 g, 600.7 g, 688.2 g and 725.7 g at four 7–day intervals. The corresponding values for water lettuce were 361.2 g, 498.7 g, 561.2 g and 623.7 g and for morning glory were 417.0 g, 567.0 g, 642.0 g and 679.5g. Coefficient of determination was greater than 80% for EC, TDS, NO₂^- -N, NO₃^- -N and 70% for NH₄⁺ -N using any of the macrophytes and the predicted values were within the 95% confidence interval of measured values. Therefore, the model is valuable in the design and operation of phytoremediation systems for aquaculture effluent.

Keywords: Phytoremediation, macrophytes, hydroponic unit, aquaculture effluent, mathematical model.

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Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

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Over the past decade, the non-elective admissions in the UK have increased significantly. Taking into account limited resources (i.e. beds), the related service managers are obliged to manage their resources effectively due to the non-elective admissions which are mostly admitted to inpatient specialities via A&E departments. Geriatric medicine is one of specialities that have long length of stay for the non-elective admissions. This study aims to develop a discrete event simulation model to understand how possible increases on non-elective demand over the next 12 months affect the bed occupancy rate and to determine required number of beds in a geriatric medicine speciality in a UK hospital. In our validated simulation model, we take into account observed frequency distributions which are derived from a big data covering the period April, 2009 to January, 2013, for the non-elective admission and the length of stay. An experimental analysis, which consists of 16 experiments, is carried out to better understand possible effects of case studies and scenarios related to increase on demand and number of bed. As a result, the speciality does not achieve the target level in the base model although the bed occupancy rate decreases from 125.94% to 96.41% by increasing the number of beds by 30%. In addition, the number of required beds is more than the number of beds considered in the scenario analysis in order to meet the bed requirement. This paper sheds light on bed management for service managers in geriatric medicine specialities.

Keywords: Bed management, bed occupancy rate, discrete event simulation, geriatric medicine, non-elective admission.

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Authors: Felix Dobslaw

Abstract:

In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their successful application to concrete problems requires the finding of a good initial parameter setting, which is a tedious and time consuming task. Recent research reveals the lack of approach when it comes to this so called parameter-tuning process. In the majority of publications, researchers do have a weak motivation for their respective choices, if any. Because initial parameter settings have a significant impact on the solutions quality, this course of action could lead to suboptimal experimental results, and thereby a fraudulent basis for the drawing of conclusions.

Keywords: Parameter-Tuning, Metaheuristics, Design of Experiments, Artificial Neural Networks.

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Authors: Bhausaheb L. Pangarkar, M.G. Sane

Abstract:

Membrane distillation (MD) is a rising technology for seawater or brine desalination process. In this work, an air gap membrane distillation (AGMD) performance was investigated for aqueous NaCl solution along with natural ground water and seawater. In order to enhance the performance of the AGMD process in desalination, that is, to get more flux, it is necessary to study the effect of operating parameters on the yield of distillate water. The influence of operational parameters such as feed flow rate, feed temperature, feed salt concentration, coolant temperature and air gap thickness on the membrane distillation (MD) permeation flux have been investigated for low and high salt solution. the natural application of ground water and seawater over 90 h continuous operation, scale deposits observed on the membrane surface and reduction in flux represents 23% for ground water and 60% for seawater, in 90 h. This reduction was eliminated (less than 14 %) by acidification of feed water. Hence, promote the research attention in apply of AGMD for the ground water as well as seawater desalination over today-s conventional RO operation.

Keywords: MD, ground water, seawater, AGMD.

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

Abstract:

Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R color component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: Chromaticity, Feature Extraction, Remote Sensing, Spectral library, Water Index.

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

Abstract:

In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: Hydrological characteristic, land and climate, runoff discharge, streamflow.

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