Search results for: water prediction

Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: Hicham Maklache, Rajae Delhi, Fatiha Benzha, Mohamed Tahiri

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In Morocco, where semi-arid climate is dominant, the supply of industrial and drink water is provided primarily by surface water. Morocco has currently 118 multi-purpose dams. If the construction of these works was a necessity to ensure in all seasons, the water essential to our country, it is impartial to control and protect the quality of running water. -Most dam reservoir used are threatened by eutrophication due to increased terrigenous and anthropogenic pollutants, coming from an over-fertilization of water by phosphorus and nitrogen nutrients and accelerated by uncontrolled development of microalgae aging. It should also be noted that the daily practices of citizens with respect to the resource, an essential component involved in almost all human activities (agriculture, agro-industries, hydropower, ...), has contributed significantly to the deterioration of water quality despite its treatment in several plants. Therefore, the treated water, provides a legacy of bad tastes and odors unacceptable to the consumer. -The present work exhibits results of water quality watershed Oum Erbia used to supply drinking water to the whole terraced area connecting the city of Khenifra to the city of Azemmour. The area south west of Great Casablanca (metropolis of the kingdom with about 4 million inhabitants) supplied 50% of its water needs by sourcing Dam Sidi Said Maachou located, last anchor point of the watershed before the spill in the Atlantic Ocean. The results were performed in a spatio-temporal scale and helped to establish a history of monitoring water quality during the 2009-2011 cycles, the study also presents the development of quality according to the seasonal rhythmicity and rainfall. It gives also an overview on the concept of watershed stewardship.

Keywords: crude surface water quality, Oum Er Rbia hydraulic basin, spatio-temporal monitoring, Great Casablanca drink water quality, Morocco

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

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Authors: Dohwan Kim, Dongchoon Ryou, Pyungjong Yoo

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In public water facilities, drinking water distribution systems have played an important role along with water purification systems. The water distribution network is one of the most expensive components of water supply infrastructure systems. To improve the reliability for the drinking rate of tap water, advanced water treatment processes such as granular activated carbon and membrane filtration were used by water service providers in Korea. But, distrust of the people for tap water are still. Therefore, accurate diagnosis and condition assessment for water pipelines are required to supply the clean water. The internal corrosion of water pipe has increased as time passed. Also, the cross-sectional areas in pipe are reduced by the rust, deposits and tubercles. It is the water supply ability decreases as the increase of hydraulic pump capacity is required to supply an amount of water, such as the initial condition. If not, the poor area of water supply will be occurred by the decrease of water pressure. In order to solve these problems, water managers and engineers should be always checked for the current status of the water pipe, such as water leakage and damage of pipe. If problems occur, it should be able to respond rapidly and make an accurate estimate. In Korea, replacement and rehabilitation of aging drinking water pipes are carried out based on the circumstances of simply buried years. So, water distribution system management may not consider the entire water pipeline network. The long-term design and upgrading of a water distribution network should address economic, social, environmental, health, hydraulic, and other technical issues. This is a multi-objective problem with a high level of complexity. In this study, the thickness of the old water pipes, corrosion levels of the inner and outer surface for water pipes, basic data research (i.e. pipe types, buried years, accident record, embedded environment, etc.), specific resistance of soil, ultimate tensile strength and elongation of metal pipes, samples characteristics, and chemical composition analysis were performed about aging drinking water pipes. Samples of water pipes used in this study were cement mortar lining ductile cast iron pipe (CML-DCIP, diameter 100mm) and epoxy lining steel pipe (diameter 65 and 50mm). Buried years of CML-DCIP and epoxy lining steel pipe were respectively 32 and 23 years. The area of embedded environment was marine reclamation zone since 1940’s. The result of this study was that CML-DCIP needed replacement and epoxy lining steel pipe was still useful.

Keywords: drinking water distribution system, water supply, replacement, rehabilitation, water pipe

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Authors: Mohammed Hussein Eltoum Salih

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This study was conducted in four villages, namely: Jadeed, Alandraba, Um Gaar, and EL Shetabe in the White Nile State Sudan, to determine the ecological factors; water vegetations, physical and chemical properties of the water in Snails habitat. Bulinus truncatus, which act as an intermediate host for S. haematobium, were collected from water bodies adjacent to study villages where the residents were suspected to swim, and humans get in contact with water for various purposes. Water samples from the stretches were collected and then measured for parameters that are indicative of the quality of water and sustaining the survival of snails and would confirm even further if the contact between humans and water had taken place. The parameters measured included water conductivity, pH, dissolved oxygen, calcium, and magnesium content. Also, a single water sample from each contact site was collected for microbiological tests. The result revealed that the B. truncatus showed that these animals were fewer and free of infection and their sites of the collection were dense with different plant species making them suitable to harbor snails. Moreover, the results of microbial tests showed that there was higher bacterial contamination. Also, physical and chemical analysis of water sample of contact sites revealed that there were significant differences (p < 0.05) in water pH, calcium, and magnesium content between sites of study villages, and these were discussed in relation to factors suitable for the intermediate hosts and thus for the transmission of the S. haematobium disease.

Keywords: health, parasitology, Schistosoma, snails

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Authors: Franz Zirena Vilca, Nestor Cahui Galarza, Walter Alejandro Zamalloa Cuba, Edith Tello Palma, Teofilo Donaires Flores, Valdemar Luiz Tornisielo

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The production of rainbow trout in the Lake Titicaca represents an important economic activity for Peru. The city of Puno is responsible for 83% of this production, so the use of antibiotics within the aquaculture system is not alien to this reality. Meanwhile, the waters of Lake Titicaca represent an important source for the supply of drinking water for 80% of the population of the Puno city. In this paper, twelve antibiotics for veterinary use were monitored in water samples during two seasons: dry (July 2015) and rainy (February 2016), water samples from trout production systems, near the water catching point in the lake and drinking water in the city house of Puno were considered. The samples were analyzed using liquid chromatography coupled to mass spectrometry and solid online phase extraction (On-line SPE-LC-MS/MS), all samples analyzed showed concentrations of Ciprofloxacin up to 65.2 ng L⁻¹ at the rainy season. On the other hand, 63% of water samples from the dry season and 36 % from the rainy season showed Chlortetracycline up to 8.7 and 6.1 ng L⁻¹, respectively. The presence of residues of veterinary antibiotics in drinking water means a serious health risk for 80% of the population of Puno since all these people are supplied from this source.

Keywords: chromatography, DNA damage, environmental risk, water pollution

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Authors: I. O. Oyatayo, K. T. Oyatayo, B. Mamman

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This study was aimed at the assessment of heavy metal pollution of the water in river Benue along Ibi, Taraba State, Nigeria. Water samples were collected at ten sampling points over a distance of 100 meters each. The following water quality parameters were determined: TDS, copper, zinc, chromium, iron, mercury, nickel, and manganese, and the results were compared with the Nigerian Standard for Drinking Water Quality (NSDWQ) and WHO maximum permitted limits. The water quality analysis was conducted using the atomic absorption spectrophotometer (Model: 01-0960-00) at 510 nm. The mean value concentrations of copper, zinc, chromium, nickel, mercury, and mercury are within the permissible limits, while that of iron is above the limit. The summary of ANOVA single-factor statistics with a specified rejection level at α 0.05 is insignificant. The study concludes that the quality of water from river Benue along Ibi is deteriorating and unfit for human consumption. It was recommended that residents of the study area should be enlightened on the effects of indiscriminate dumping of waste and the proper handling and application of fertilizer and herbicides, as some of these end up in the river via surface runoff.

Keywords: heavy, metal, pollution, river, Ibi

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Authors: Afrah Saad Mohsen Al-Mahfadi

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In rural areas of developing countries, participation of all stakeholders in water supply projects is an important step towards further development. As most of the beneficiaries are women, it is important that they should be involved to achieve successful and sustainable water supply projects. Women are responsible for the management of water both inside and outside home, and often spend more than six-hours a day fetching drinking water from distant water sources. The problem is that rural women play a role of little importance in the water supply projects’ phases in rural Yemen. Therefore, this research aimed at analyzing the different reasons of their lack of participation in projects and in what way a full participation -if achieved- could contribute to sustainable water supply projects in the rural mountainous areas in Yemen. Four water supply projects were selected as a case study in Al-Della'a Alaala sub-district in the Al-Mahweet governorate, two of them were implemented by the Social Fund and Development (SFD), while others were implemented by the General Authority for Rural Water Supply Projects (GARWSSP). Furthermore, the successful Al-Galba project, which is located in Badan district in Ibb governorate, was selected for comparison. The rural women's active participation in water projects have potential consequences including continuity and maintenance improvement, equipment security, and improvement in the overall health and education status of these areas. The majority of respondents taking part in GARWSSP projects estimated that there is no reason to involve women in the project activities. In the comparison project - in which a woman worked as a supervisor and implemented the project – all respondents indicated that the participation of women is vital for sustainability. Therefore, the results of this research are intended to stimulate rural women's participation in the mountainous areas of Yemen.

Keywords: assessment, rural woman, sustainability, water management

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Authors: Ekrem Canli, Thomas Glade

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The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

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Authors: Amin Khamoosh, Hamed Faramarzifar

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In the capital of Iran, Tehran, numerous buildings constructed when extreme climates were not prevalent now face the need for rehabilitation, typically within their first decade. Our data delves into the performance metrics and economic advantages of sustainable rehabilitation practices compared to traditional methods. With a focus on the scarcity of water resources, we specifically scrutinize water-efficient techniques throughout construction, rehabilitation, and usage. Examining design elements that optimize natural light while efficiently managing heat transmission is crucial, given the reliance on water for cooling devices in this region. The data aims to present a comprehensive strategy, addressing immediate structural concerns while harmonizing with Iran's unique environmental conditions.

Keywords: sustainable rehabilitation, concrete buildings, iran, solar energy, water-efficient techniques

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Authors: Zhenyu Yang, Qiunan Chen, Xiaocheng Huang

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Reliable prediction of tunnel collapse remains a prominent challenge in the field of civil engineering. In this study, leveraging the nonlinear Hoek-Brown failure criterion and the upper-bound theorem, an analytical solution for the collapse surface of shallowly buried circular tunnels was derived, taking into account the coupled effects of surface loads and pore water pressures. Initially, surface loads and pore water pressures were introduced as external force factors, equating the energy dissipation rate to the external force, yielding our objective function. Subsequently, the variational method was employed for optimization, and the outcomes were juxtaposed with previous research findings. Furthermore, we utilized the deduced equation set to systematically analyze the influence of various rock mass parameters on collapse shape and extent. To validate our analytical solutions, a comparison with prior studies was executed. The corroboration underscored the efficacy of our proposed methodology, offering invaluable insights for collapse risk assessment in practical engineering applications.

Keywords: tunnel roof stability, analytical solution, hoek–brown failure criterion, limit analysis

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Authors: Mehrdad Ebrahimi, Oliver Schmitz, Axel Schmidt, Peter Czermak

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“Produced water” (PW) is any fossil water that is brought to the surface along with crude oil or natural gas. By far, PW is the largest waste stream by volume associated with oil and gas production operations. Due to the increasing volume of waste all over the world in the current decade, the outcome and effect of discharging PW on the environment has lately become a significant issue of environmental concerns. Therefore, there is a need for new technologies for PW treatment due to increase focus on water conservation and environmental regulation. The use of membrane processes for treatment of PW has several advantages over many of the traditional separation techniques. In oilfield produced water treatment with ceramic membranes, process efficiency is characterized by the specific permeate flux and by the oil separation performance. Apart from the membrane properties, the permeate flux during filtration of oily wastewaters is known to be strongly dependent on the constituents of the feed solution, as well as on process conditions, e.g. trans-membrane pressure (TMP) and cross-flow velocity (CFV). The research project presented in these report describes the application of different ceramic membrane filtration technologies for the efficient treatment of oil-field produced water and different model oily solutions.

Keywords: ceramic membrane, membrane fouling, oil rejection, produced water treatment

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Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

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Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

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Authors: Qiying Zhang, Panpan Xu, Hui Qian

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Groundwater is an important water resource in the world, especially in arid and semi-arid regions. In the present study, 141 groundwater samples were collected and analyzed for various physicochemical parameters to assess the irrigation water quality using six indicators (sodium percentage (Na%), sodium adsorption ratio (SAR), magnesium hazard (MH), residual sodium carbonate (RSC), permeability index (PI), and potential salinity (PS)). The results show that the patterns for the average cation and anion concentrations were in decreasing orders of Na^＋ > Mg^2＋ > Ca^2＋ > K^＋and SO₄^2－ > HCO₃^－ > Cl^－ > NO₃^－ > CO₃^2－ > F^－, respectively. The values of Na%, MH, and PS show that most of the groundwater samples are not suitable for irrigation. The same conclusion is drawn from the USSL and Wilcox diagrams. PS values indicate that Cl^－and SO₄^2－have a great influence on irrigation water in Jiaokou Irrigation District. RSC and PI values indicate that more than half of groundwater samples are suitable for irrigation. The finding is beneficial for the policymakers for future water management schemes to achieve a sustainable development goal.

Keywords: groundwater chemistry, Guanzhong Basin, irrigation water quality evaluation, Jiaokou Irrigation District

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Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Muhammad Saiful Islam Khan, Yun Ji Kim

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Organophosphorus pesticides (OPPs) have been widely used to replace more persistent organochlorine pesticides because OPPs are more soluble in water and decompose rapidly in aquatic systems. Extensive uses of OPPs in modern agriculture are the major cause of the contamination of surface water. Regardless of the advantages gained by the application of pesticides in modern agriculture, they are a threat to the public health environment. With the aim of reducing possible health threats, several physical and chemical treatment processes have been studied to eliminate biological and chemical poisons from food stuff. In the present study, a micro-plasma device was used to reduce pesticides from the surface of food stuff. Pesticide free food items chosen in this study were perilla leaf, tomato, broccoli and blueberry. To evaluate the removal efficiency of pesticides, different washing methods were followed such as soaking with water, washing with bubbling water, washing with plasma-treated water and washing with chlorine water. 2 mL of 2000 ppm pesticide samples, namely, diazinone and chlorpyrifos were individuality inoculated on food surface and was air dried for 2 hours before treated with plasma. Plasma treated water was used in two different manners one is plasma treated water with bubbling the other one is aerosolized plasma treated water. The removal efficiency of pesticides from food surface was studied using HPLC. Washing with plasma treated water, aerosolized plasma treated water and chlorine water shows minimum 72% to maximum 87 % reduction for 4 min treatment irrespective to the types of food items and the types of pesticides sample, in case of soaking and bubbling the reduction is 8% to 48%. Washing with plasma treated water, aerosolized plasma treated water and chlorine water shows somewhat similar reduction ability which is significantly higher comparing to the soaking and bubbling washing system. The temperature effect of the washing systems was also evaluated; three different temperatures were set for the experiment, such as 22°C, 10°C and 4°C. Decreasing temperature from 22°C to 10°C shows a higher reduction in the case of washing with plasma and aerosolized plasma treated water, whereas an opposite trend was observed for the washing with chlorine water. Further temperature reduction from 10°C to 4°C does not show any significant reduction of pesticides, except for the washing with chlorine water. Chlorine water treatment shows lesser pesticide reduction with the decrease in temperature. The color changes of the treated sample were measured immediately and after one week to evaluate if there is any effect of washing with plasma treated water and with chlorine water. No significant color changes were observed for either of the washing systems, except for broccoli washing with chlorine water.

Keywords: chlorpyrifos, diazinone, pesticides, micro plasma

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Authors: Feng Huang, Carlos G. Ochoa, Haitao Zhao

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Poyang Lake, the largest freshwater lake in China, is located at the middle-lower reaches of the Yangtze River basin. It has great value in socioeconomic development and is internationally recognized as an important lacustrine and wetland ecosystem with abundant biodiversity. Impacted by ongoing climate change and anthropogenic activities, especially the regulation of the Three Gorges Reservoir since 2003, Poyang Lake has experienced significant water regime evolution, resulting in challenges for the management of water resources and the environment. Quantifying the contribution of hydrologic and topographic changes to water regime alteration is necessary for policymakers to design effective adaption strategies. Long term hydrologic data were collected and the back-propagation neural networks were constructed to simulate the lake water level. The impacts of hydrologic and topographic changes were differentiated through scenario analysis that considered pre-impact and post-impact hydrologic and topographic scenarios. The lake water regime was characterized by hydrologic indicators that describe monthly water level fluctuations, hydrologic features during flood and drought seasons, and frequency and rate of hydrologic variations. The results revealed different contributions of hydrologic and topographic changes to different features of the lake water regime.Noticeable changes were that the water level declined dramatically during the period of reservoir impoundment, and the drought was enhanced during the dry season. The hydrologic and topographic changes exerted a synergistic effect or antagonistic effect on different lake water regime features. The findings provide scientific reference for lacustrine and wetland ecological protection associated with water regime alterations.

Keywords: back-propagation neural network, scenario analysis, water regime, Poyang Lake

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Authors: Rajoo Balaji, Omar Yaakob

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The Ballast Water Convention requires less than 5% of the world tonnage for ratification. Consequently, ships will have to comply with the requirements. Compliance evaluation and enforcement will become mandatory. Ship owners have to invest in treatment systems and shipboard personnel have to operate them and ensure compliance. The monitoring and enforcement will be the responsibilities of the Administrations. Herein, a review of the current status of the Ballast Water Management and the issues faced by these are projected. Issues range from efficacy and economics of the treatment systems to sampling and testing. Health issues of chemical systems, paucity of data for decision support etc., are other issues. It is emphasized that management of ballast water must be extended to ashore and sustainable solutions must be researched upon. An exemplar treatment system based on ship’s waste heat is also suggested.

Keywords: Ballast Water Management, compliance evaluation, compliance enforcement, sustainability

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Authors: Fawad Ali, Muhammad Ateeq, Ikhtiar Khan

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Ground water, a major source of drinking water supply in Peshawar has been severely contaminated by leather tanning industry. Effluents from the tanneries contain high concentration of chromium besides several other chemical species. Release of untreated effluents from the tanning industry has severely damaged surface and ground water, agriculture soil as well as vegetables and crops. Chromium is a well-known carcinogenic and mutagenic agent. Once in the human food chain, it causes multiple problems to the exposed population including various types of cancer, skin dermatitis, and DNA damage. In order to assess the extent of chromium and other heavy metals contamination, water samples were analyzed for heavy metals using Graphite Furnace Atomic Absorption Spectrometer (GFAAS, Analyst 700, Perkin Elmer). Total concentration of chromium was above the permissible limit (0.048 mg/l) in 85% of the groundwater (drinking water) samples. The concentration of cobalt, manganese, cadmium, nickel, lead, zinc and iron was also determined in the ground water, surface water, agriculture soil, and vegetables samples from the affected area.

Keywords: heavy metals, soil, groundwater, tannery effluents, food chain

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Authors: Saad S. Alrwashdeh, Henning Markötter, Handri Ammari, Jan Haußmann, Tobias Arlt, Joachim Scholta, Ingo Manke

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In this investigation, synchrotron X-ray imaging is used to study water transport inside polymer electrolyte membrane fuel cells. Two measurement techniques are used, namely in-situ radiography and quasi-in-situ tomography combining together in order to reveal the relationship between the structures of the microporous layers (MPLs) and the gas diffusion layers (GDLs), the operation temperature and the water flow. The developed cell is equipped with a thick GDL and a high back pressure MPL. It is found that these modifications strongly influence the overall water transport in the whole adjacent GDM.

Keywords: polymer electrolyte membrane fuel cell, microporous layer, water transport, radiography, tomography

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Authors: Hocini Yousra, Medjnoun Amal, Khiatine Mohamed, Bahar Ramdane

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The development of the regions of southern Algeria require the construction of numerous road, rail, and airport infrastructures. However, this development is very expensive given the very severe climatic conditions, the difficulty of reusing local materials, and the unavailability of water on the project sites; these regions are characterized by an arid or semi-arid climate, which means that water sources are very limited. The climatic conditions and the scarcity of water make soil compaction work very difficult and excessively expensive. These constraints related to the supply of water for irrigation of these construction sites make it necessary to examine the solution of compaction with low water content. This work studies the possibility of improving the compaction with a low water content of the soils of southern Algeria and this by using natural or recycled ecological materials. Local soils are first subjected to a series of laboratory characterization tests, then mixed with varying amounts of natural additives. The new materials are, in turn, subjected to road tests.

Keywords: compaction, low water content, sand, natural materials

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Authors: E. Ebru Demirci, Remzi Şahin

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The purpose of this study is to compare Self Compacting Concrete (SCC) and Conventional Concrete (CC) in terms of their capillary water absorption. During the comparison of SCC and CC, the effects of two different factors were also investigated: concrete strength class and curing condition. In the study, both SCC and CC were produced in three different concrete classes (C25, C50 and C70) and the other parameter (i.e curing condition) was determined as two levels: moisture and air curing. It was observed that, for both curing environments and all strength classes of concrete, SCCs had lower capillary water absorption values than that of CCs. It was also detected that, for both SCC and CC, capillary water absorption values of samples kept in moisture curing were significantly lower than that of samples stored in air curing. Additionally, it was determined that capillary water absorption values for both SCC and CC decrease with increasing strength class of concrete for both curing environments.

Keywords: capillary water absorption, curing condition, reinforced concrete beam, self-compacting concrete

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Authors: Ismail Tas, Yusuf Ersoy Yildirim, Yavuz Fatih Fidantemiz, Aysegul Boyacioglu, Demet Uygan, Ozgur Ates, Erdinc Savasli, Oguz Onder, Murat Tugrul

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The biggest input of agricultural production is irrigation, water and energy. Although it varies according to the conditions in drip and sprinkler irrigation systems compared to surface irrigation systems, there is a significant amount of energy expenditure. However, this expense not only increases the user's control over the irrigation water but also provides an increase in water savings and water application efficiency. Thus, while irrigation water is used more effectively, it also contributes to reducing production costs. The Mobile Drip Irrigation System (MDIS) is a system in which new technologies are used, and it is one of the systems that are thought to play an important role in increasing the irrigation water utilization rate of plants and reducing water losses, as well as using irrigation water effectively. MDIS is currently considered the most effective method for irrigation, with the development of both linear and central motion systems. MDIS is potentially more advantageous than sprinkler irrigation systems in terms of reducing wind-induced water losses and reducing evaporation losses on the soil and plant surface. Another feature of MDIS is that the sprinkler heads on the systems (such as the liner and center pivot) can remain operational even when the drip irrigation system is installed. This allows the user to use both irrigation methods. In this study, the effect of MDIS and linear sprinkler irrigation method on sugar beet yield at different irrigation water levels will be revealed.

Keywords: MDIS, linear sprinkler, sugar beet, irrigation efficiency

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Authors: Banu Aytül Ekmekçi

Abstract:

Salinity stress has negative effects on agricultural yield throughout the world, affecting production whether it is for subsistence or economic gain. This study investigates the inductive role of vitamin C and its application mode in mitigating the detrimental effects of irrigation with diluted (10, 20 and 30 %) NaCl + water on carthamus tinctorius plants. The results show that 10% of salt water exhibited insignificant changes, while the higher levels impaired growth by reducing seed germination, dry weights of shoot and root, water status and chlorophyll contents. However, irrigation with salt water enhanced carotenoids and antioxidant enzyme activities. The detrimental effects of salt water were ameliorated by application of 100 ppm ascorbic acid (vitamin C). The inductive role of vitamin was associated with the improvement of seed germination, growth, plant water status, carotenoids, endogenous ascorbic acid and antioxidant enzyme activities. Moreover, vitamin C alone or in combination with 30% NaCl water increased the intensity of protein bands as well as synthesized additional new proteins with molecular weights of 205, 87, 84, 65 and 45 kDa. This could increase tolerance mechanisms of treated plants towards water salinity.

Keywords: salinity, stress, vitamin c, antioxidant, NaCl, enzyme

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Authors: Lizhou Chen, Abdelhamid Belgaid, Assem Elsayed, Xiaoming Yang

Abstract:

Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations.

Keywords: compression index, clay, settlement, consolidation, secondary compression index, soil parameter

Procedia PDF Downloads 144

Authors: Luis C. Parra

Abstract:

The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Ihsanullah, Muataz Ali Atieh

Abstract:

In this study, a low-cost adsorbent carbon fly ash (CFA) was used for the removal of Phenol from the water. The adsorbent characteristics were observed by the Thermogravimetric Analysis (TGA), BET specific surface area analyzer, Zeta Potential and Field Emission Scanning Electron Microscopy (FE-SEM). The effect of pH, agitation speed, contact time, adsorbent dosage, and initial concentration of phenol were studied on the removal of phenol from the water. The optimum values of these variables for maximum removal of phenol were also determined. Both Freundlich and Langmuir isotherm models were successfully applied to describe the experimental data. Results showed that low-cost adsorbent phenol can be successfully applied for the removal of Phenol from the water.

Keywords: phenol, fly ash, adsorption, carbon adsorbents

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Authors: Mohammad Ahmad, Sander Gersen, Erwin Wilbers

Abstract:

Carbon capture, transport and underground storage have become a major solution to reduce CO2 emissions from power plants and other large CO2 sources. A big part of this captured CO2 stream is transported at high pressure dense phase conditions and stored in offshore underground depleted oil and gas fields. CO2 is also transported in offshore pipelines to be used for enhanced oil and gas recovery. The captured CO2 stream with impurities may contain water that causes severe corrosion problems, flow assurance failure and might damage valves and instrumentations. Thus, free water formation should be strictly prevented. The purpose of this work is to study the solubility of water in pure CO2 and in CO2 mixtures under real pipeline pressure (90-150 bar) and temperature operation conditions (5-35°C). A set up was constructed to generate experimental data. The results show the solubility of water in CO2 mixtures increasing with the increase of the temperature or/and with the increase in pressure. A drop in water solubility in CO2 is observed in the presence of impurities. The data generated were then used to assess the capabilities of two mixture models: the GERG-2008 model and the EOS-CG model. By generating the solubility data, this study contributes to determine the maximum allowable water content in CO2 pipelines.

Keywords: carbon capture and storage, water solubility, equation of states, fluids engineering

Procedia PDF Downloads 276