Search results for: deep groundwater potential

Authors: S. Wagner, C. Boley, Y. Forouzandeh

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When digging excavations, groundwater bearing layers are often encountered. In order to allow anhydrous excavation, soil groutings are carried out, which form a water-impermeable layer. As it is injected into groundwater areas, the effects of the materials used on the environment must be known. Developing an eco-friendly, economical and low viscous acrylic gel which has a sealing effect on groundwater is therefore a significant task. At this point the study begins. Basic investigations with the rheometer and a reverse column experiment have been performed with different mixing ratios of an acrylic gel. A dynamic rheology study was conducted to determine the time at which the gel still can be processed and the maximum gel strength is reached. To examine the effect of acrylic gel grouting on determine the parameters pH value, turbidity, electric conductivity, and total organic carbon on groundwater, an acrylic gel was injected in saturated sand filled the column. The structure was rinsed with a constant flow and the eluate was subsequently examined. The results show small changes in pH values and turbidity but there is a dependency between electric conductivity and total organic carbon. The curves of the two parameters react at the same time, which means that the electrical conductivity in the eluate can be measured constantly until the maximum is reached and only then must total organic carbon (TOC) samples be taken.

Keywords: acrylic gel grouting, dynamic rheology study, electric conductivity, total organic carbon

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Authors: Noureddine Mohtaram, Jeremy Patrix, Jerome Verny

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As an enormous number of online services have been developed into web applications, security problems based on web applications are becoming more serious now. Most intrusion detection systems rely on each request to find the cyber-attack rather than on user behavior, and these systems can only protect web applications against known vulnerabilities rather than certain zero-day attacks. In order to detect new attacks, we analyze the HTTP protocols of web servers to divide them into two categories: normal attacks and malicious attacks. On the other hand, the quality of the results obtained by deep learning (DL) in various areas of big data has given an important motivation to apply it to cybersecurity. Deep learning for attack detection in cybersecurity has the potential to be a robust tool from small transformations to new attacks due to its capability to extract more high-level features. This research aims to take a new approach, deep learning to cybersecurity, to classify these two categories to eliminate attacks and protect web servers of the defense sector which encounters different web traffic compared to other sectors (such as e-commerce, web app, etc.). The result shows that by using a machine learning method, a higher accuracy rate, and a lower false alarm detection rate can be achieved.

Keywords: anomaly detection, HTTP protocol, logs, cyber attack, deep learning

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Authors: Marianne Miguet, Gaël Plantard, Yves Jaeger, Vincent Goetz

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The contamination of groundwater is a major concern. A common pollutant, the perchloroethylene, is the target contaminant. Water treatment process as Granular Activated Carbons are very efficient but requires pilot-scale testing to determine the full-scale GAC performance. First, the batch mode was used to get a reliable experimental method to estimate the adsorption capacity of a common volatile compound is settled. The Langmuir model is acceptable to fit the isotherms. Dynamic tests were performed with three columns and different operating conditions. A database of concentration profiles and breakthroughs were obtained. The resolution of the set of differential equations is acceptable to fit the dynamics tests and could be used for a full-scale adsorber.

Keywords: activated carbon, groundwater, perchloroethylene, full-scale

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Authors: Wondmyibza Tsegaye Bayou, Johannes C. Nonner, Joost Heijkers

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This study aimed to identify and estimate dynamic groundwater seepage rates using four comparative methods; the Darcian approach, the water balance approach, the tracer method, and modeling. The theoretical background to these methods is put together in this study. The methodology was applied to a case study area at Zegveld following the advice of the Water Board Stichtse Rijnlanden. Data collection has been from various offices and a field campaign in the winter of 2008/09. In this complex confining layer of the study area, the location of the phreatic groundwater table is at a shallow depth compared to the piezometric water level. Data were available for the model years 1989 to 2000 and winter 2008/09. The higher groundwater table shows predominately-downward seepage in the study area. Results of the study indicated that net recharge to the groundwater table (precipitation excess) and the ditch system are the principal sources for seepage across the complex confining layer. Especially in the summer season, the contribution from the ditches is significant. Water is supplied from River Meije through a pumping system to meet the ditches' water demand. The groundwater seepage rate was distributed unevenly throughout the study area at the nature reserve averaging 0.60 mm/day for the model years 1989 to 2000 and 0.70 mm/day for winter 2008/09. Due to data restrictions, the seepage rates were mainly determined based on the Darcian method. Furthermore, the water balance approach and the tracer methods are applied to compute the flow exchange within the ditch system. The site had various validated groundwater levels and vertical flow resistance data sources. The phreatic groundwater level map compared with TNO-DINO groundwater level data values overestimated the groundwater level depth by 28 cm. The hydraulic resistance values obtained based on the 3D geological map compared with the TNO-DINO data agreed with the model values before calibration. On the other hand, the calibrated model significantly underestimated the downward seepage in the area compared with the field-based computations following the Darcian approach.

Keywords: groundwater seepage, phreatic water table, piezometric water level, nature reserve, Zegveld, The Netherlands

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Authors: Mohamed Ahmed, Ezat Korany, Abdelaziz Al Basam, Osama Kasem

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The arid climate, low rate of precipitations and population reflect the increasing of groundwater uses as the main source of water in Saudi Arabia. The Wajid Aquifer System represents a regional groundwater aquifer system along the edge of the crystalline Arabian Shield near the southwestern tip of the Arabian Peninsula. The aquifer extends across the border of Saudi Arabia and Yemen from the Asir –Yemen Highlands to the Rub al Khali Depression and possibly to the Gulf coast (at the southwestern tip). The present work is representing a hydrogeochemical investigation on the Wajid Aquifer System. The studied area is being classified into three zones. The 1st zone is West of Wadi Ad Dawasir (Northern part of the studied area), the 2nd is Najran-Asir Zone (southern part of the studied area), and the 3rd zone is the intermediate -central zone (occupying the central area between the last two zones). The groundwater samples were collected and chemically analyzed for physicochemical properties such as pH, electrical conductivity, total hardness (TH), alkalinity (pH), total dissolved solids (TDS), major ions (Ca2+, Mg2+, Na+, K+, HCO3-, SO42- and Cl-), and trace elements. Some parameters such as sodium adsorption ratio (SAR), soluble sodium percentage (Na%), potential salinity, residual sodium carbonate, Kelly's ratio, permeability index and Gibbs ratio, hydrochemical coefficients, hydrochemical formula, ion dominance, salt combinations and water types were also calculated in order to evaluate the quality of the groundwater resources in the selected areas for different purposes. The distribution of the chemical constituents and their interrelationships are illustrated by different hydrochemical graphs. Groundwater depths and the depth to water were measured to study the effect of discharge on both the water level and the salinity of the studied groundwater wells. A detailed comparison between the three studied zones according to the variations shown by the chemical and field investigations are discussed in detailed within the work.

Keywords: Najran-Asir, Wadi Ad Dawasir, Wajid Aquifer System, effect of discharge

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Authors: Ali Bakari Mohammed

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Transitioning is a continuous process of radical change in a society which involves co-evolution of institutional, technological, socio-cultural, and ecological developments at different scales and levels. Transition management model is a methodology that influences structural change of complex systems over a period (0-30 years) by experimenting and implementing new techniques. A transition management in the context of groundwater is a radical change from the current operate and control system to a next generation integrated and sustainable system that takes into account quality protection and sustained supply into the future. This study evaluates the transition management model in adopting it as a viable tool for the attainment of sustainable groundwater management. The outcome of the evaluation shows that there are three levels (strategic, tactical and operational) of operating the transition management model. At the strategic level, long-term goals for sustainable groundwater management are formulated, at the tactical level activities such as inter institutional networking, negotiation, planning and financing are carried out, and at the operational level, transition experiments and strategic niche management are carried out at the societal level. Overall, different actors and set of activities are required to partake at each management level. The outcome of this paper will provide basis for the implementation of the Sustainable Development Goal (SDG) 6 in Nigeria.

Keywords: transition management, groundwater, sustainable management, tool, Nigeria

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Authors: Rajkumar Ghosh

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Climate change has led to decreased water availability in the Gomti Nagar area of Uttar Pradesh, India. Climate change has reduced the amount of precipitation and increased the rate of evaporation. The region is heavily reliant on surface water sources (Gomti river, Sharda Canal) and groundwater. Efficient management of groundwater resources is crucial for addressing water shortages. These may include: Exploring alternative water sources, such as wastewater recycling and desalination, can help augment water supply and reduce dependency on rainfall-dependent sources. Promoting the use of water-efficient technologies in industries, agriculture, and water-efficient infrastructure in urban areas can contribute to reducing water demand and optimizing water use. Incorporating climate change considerations into urban planning and infrastructure development can help ensure water security in the face of future climate uncertainties. Addressing water scarcity in the Gomti Nagar area requires a multi-pronged approach that combines sustainable groundwater management practices, climate change adaptation strategies, and integrated water resource management. By implementing these measures, the region can work towards ensuring a more sustainable and reliable water supply in the context of climate change. Water is the most important natural resource for the existence of living beings in the Earth's ecosystem. On Earth, 1.2 percent of the water is drinkable, but only 0.3 percent is usable by people. Water scarcity is a growing concern in India due to the impact of climate change and over-exploitation of water resources. Excess groundwater withdrawal causes regular declines in groundwater level. Due to city boundary expansion and growing urbanization, the recharge point for groundwater tables is decreasing. Rainwater infiltration into the subsoil is also reduced by unplanned, uneven settlements in urban change.

Keywords: climate change, water scarcity, groundwater, rainfall, water supply

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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Authors: Ziyad Abunada, Abir Al-tabbaa

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The current work is investigating the effectiveness of combined mixed materials mainly modified bentonites and organoclay in treating contaminated groundwater. Sodium bentonite was manufactured with a quaternary amine surfactant, dimethyl ammonium chloride to produce organoclay (OC). Inorgano-organo bentonite (IOB) was produced by intercalating alkylbenzyd-methyl-ammonium chloride surfactant into sodium bentonite and pillared with chlorohydrol pillaring agent. The materials efficiency was tested for both TEX compounds from model-contaminated water and a mixture of organic contaminants found in groundwater samples collected from a contaminated site in the United Kingdom. The sorption data was fitted well to both Langmuir and Freundlich adsorption models reflecting the double sorption model where the correlation coefficient was greater than 0.89 for all materials. The mixed materials showed higher sorptive capacity than individual material with a preference order of X> E> T and a maximum sorptive capacity of 21.8 mg/g was reported for IOB-OC materials for o-xylene. The mixed materials showed at least two times higher affinity towards a mixture of organic contaminants in groundwater samples. Other experimental parameters such as pH and contact time were also investigated. The pseudo-second-order rate equation was able to provide the best description of adsorption kinetics.

Keywords: modified bentobite, groundwater, adsorption, contaminats

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Authors: Babatunde Femi Bakare

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Groundwater quality was evaluated at a site for three years after the site was used for entrenchment of Ventilated Improved Pit (VIP) latrine sludge. Analysis performed on the soil characteristics at the entrenchment site indicated that, the soils at the entrenchment site are predominantly sandy. Depth of the water table at the entrenchment site was found to be approximately five meters. Five monitoring boreholes were dug along the perimeter of the sludge trenches and water samples taken from these monitoring boreholes were analyzed for pH, conductivity, sodium ions, chloride ions, phosphate, nitrate, ammonia, and bacteriological analysis. The results obtained from the analysis conducted were compared with the South African Bureau of Standards for drinking water and it was found that the parameters analyzed falls below the specified range. The data obtained from this study indicate that, given the relatively high sludge loading rates, poor soil quality, and the duration of the groundwater quality monitoring, it is unlikely that contamination of groundwater at the entrenchment site will be a major concern. However, caution is advised in extrapolating these results to other locations.

Keywords: boreholes, contamination, entrenchment, groundwater quality, VIP latrines

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Authors: Mohammad Tahsin Karimi Nezhad, Zaynab Shadbahr, Ali Gholami

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In recent years many attempts have been made to assess groundwater contamination by nitrates worldwide. The assessment of spatial and temporal variations of physico-chemical parameters of water is necessary to mange water quality. The objectives of the study were to evaluate spatial variability and temporal changes of hydrochemical factors by water sampling from 24 wells in the Shoush City suburb. The analysis was conducted for the whole area and for different land use and geological classes. In addition, nitrate concentration variability with descriptive parameters such as sampling depth, dissolved oxygen, and on ground nitrogen loadings was also investigated The results showed that nitrate concentrations did not exceed the standard limit (50 mg/l). EC of water samples, ranged from 900 to 1200 µs/cm, TDS from 775 to 830 mg/l and pH from 5.6 to 9.

Keywords: groundwater, GIS, water quality, Iran

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Authors: Radzuan Junin, Dayang Zulaika A. Hasbollah

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The increasing amount of greenhouse gasses in the atmosphere recently has become one of the discussed topics in relation with world’s concern on climate change. Developing countries’ emissions (such as Malaysia) are now seen to surpass developed country’s emissions due to rapid economic development growth in recent decades. This paper presents the potential storage sites suitability and storage capacity assessment for CO2 sequestration in sedimentary basins of Malaysia. This study is the first of its kind that made an identification of potential storage sites and assessment of CO2 storage capacity within the deep saline aquifers in the country. The CO2 storage capacity in saline formation assessment was conducted based on the method for quick assessment of CO2 storage capacity in closed, and semi-closed saline formations modified to suit the geology setting of Malaysia. Then, an integrated approach that involved geographic information systems (GIS) analysis and field data assessment was adopted to provide the potential storage sites and its capacity for CO2 sequestration. This study concentrated on the assessment of major sedimentary basins in Malaysia both onshore and offshore where potential geological formations which CO2 could be stored exist below 800 meters and where suitable sealing formations are present. Based on regional study and amount of data available, there are 14 sedimentary basins all around Malaysia that has been identified as potential CO2 storage. Meanwhile, from the screening and ranking exercises, it is obvious that Malay Basin, Central Luconia Province, West Baram Delta and Balingian Province are respectively ranked as the top four in the ranking system for CO2 storage. 27% of sedimentary basins in Malaysia were evaluated as high potential area for CO2 storage. This study should provide a basis for further work to reduce the uncertainty in these estimates and also provide support to policy makers on future planning of carbon capture and sequestration (CCS) projects in Malaysia.

Keywords: CO₂ storage, deep saline aquifer, GIS, sedimentary basin

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Authors: Nuntaporn Aukkanit

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The aim of this study was to determine the effect of oils on chemical, physical, and sensory properties of deep-fried dough stick. Five kinds of vegetable oil which were used for addition and frying consist of: palm oil, soybean oil, sunflower oil, rice bran oil, and canola oil. The results of this study showed that using different kinds of oil made significant difference in the quality of deep-fried dough stick. Deep-fried dough stick fried with the rice bran oil had the lowest moisture loss and oil absorption (p≤0.05), but it had some unsatisfactory physical properties (color, specific volume, density, and texture) and sensory characteristics. Nonetheless, deep-fried dough stick fried with the sunflower oil had moisture loss and oil absorption slightly more than the rice bran oil, but it had almost higher physical and sensory properties. Deep-fried dough sticks together with the sunflower oil did not have different sensory score from the palm oil, commonly used for production of deep-fried dough stick. These results indicated that addition and frying with the sunflower oil are appropriate for the production of deep-fried dough stick.

Keywords: deep-fried dough stick, palm oil, sunflower oil, rice bran oil

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: K. Mirudhula, R. Saravanan

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Bhavani basin is the fourth largest Sub Basin in the Cauvery basin. The entire command area of all three major canals that takes off from the Bhavani river falls within the Erode District i.e. Lower Bhavani Project (LBP), Kodiveri and Kalingarayan canals. The LBP canal is a major source of irrigation in Erode District. Many of these canals are unlined and leakage takes place from them. Thus the seepage from the canal helps in recharging the wells in the area, enabling to get adequate water supply for the crops when water was not released from Bhavanisagar Dam. In this study, the groundwater recharge is determined by groundwater flow modeling using Visual MODFLOW model. For this purpose, three major natural sources of groundwater recharge are taken into consideration such as rainfall infiltration, canal seepage and return flow of irrigation. The model was run and ZONEBUDGET gives an idea about the amount of recharge from lined/unlined canal to the field. Unlined canal helps to recharge the groundwater about 20% more than the lined canal. The analysis reveals that the annual rainfall also has rapidly changed in this region. In the LBP canal Head reach meets their requirement with available quantity of water from the canal system. Tail end reach does not receive the required quantity of water because of seepage loss and conveyance loss. Hence the lined canal can be provided for full length of the main canal. Branch canals and minor distributaries are suggested to maintain the canals with unlined canal system.

Keywords: lower Bhavani basin, erode, groundwater flow modeling, irrigation practice, lined canal system

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Authors: Alok Saini, Rajkumar Ghosh

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Water is nature's important resource for survival of all living things, but freshwater scarcity exists in some parts of world. This study has predicted that Gomti Nagar area (49.2 sq. km.) will harvest about 91110 ML of rainwater till 2051 (assuming constant and present annual rainfall). But 17.71 ML of rainwater was harvested from only 53 buildings in Gomti Nagar area in the year 2021. Water level will be increased (rise) by 13 cm in Gomti Nagar from such groundwater recharge. The total annual groundwater abstraction from Gomti Nagar area was 35332 ML (in 2021). Due to hydrogeological constraints and lower annual rainfall, groundwater recharge is less than groundwater abstraction. The recent scenario is only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. Gomti Nagar is situated in 'Zone–A' (water distribution area) and groundwater is the primary source of freshwater supply. Current scenario indicates only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. In Gomti Nagar, the difference between groundwater abstraction and recharge will be 735570 ML in 30 yrs. Statistically, all buildings at Gomti Nagar (new and renovated) could harvest 3037 ML of rainwater through RTRWHs annually. The most recent monsoonal recharge in Gomti Nagar was 10813 ML/yr. Harvested rainwater collected from RTRWHs can be used for rooftop irrigation, and residential kitchen and gardens (home grown fruit and vegetables). According to bylaws, RTRWH installations are required in both newly constructed and existing buildings plot areas of 300 sq. m or above. Harvested rainwater is of higher quality than contaminated groundwater. Harvested rainwater from RTRWHs can be considered water self-sufficient. Rooftop Rainwater Harvesting Systems (RTRWHs) are least expensive, eco-friendly, most sustainable, and alternative water resource for artificial recharge. This study also predicts about 3.9 m of water level rise in Gomti Nagar area till 2051, only when all buildings will install RTRWHs and harvest for groundwater recharging. As a result, this current study responds to an impact assessment study of RTRWHs implementation for the water scarcity problem in the Gomti Nagar area (1.36 sq.km.). This study suggests that common storage tanks (recharge wells) should be built for a group of at least ten (10) households and optimal amount of harvested rainwater will be stored annually. Artificial recharge from alternative water sources will be required to improve the declining water level trend and balance the groundwater table in this area. This over-exploitation of groundwater may lead to land subsidence, and development of vertical cracks.

Keywords: aquifer, aquitard, artificial recharge, bylaws, groundwater, monsoon, rainfall, rooftop rainwater harvesting system, RTRWHs water table, water level

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Authors: Yu-Chen Chang, Yen-Ping Peng, Wei-Yu Chen, Ku-Fan Chen

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Contamination of soil and groundwater has become a serious and widespread environmental problem. In this study, sustained-release persulfate tablets were developed using persulfate powder and a modified cellulose binder for organic-contaminated groundwater remediation. Conventional cement-based persulfate-releasing materials were also synthesized for the comparison. The main objectives of this study were to: (1) evaluate the release rates of the remedial tablets; (2) obtain the optimal formulas of the tablets; and (3) evaluate the effects of the tablets on the subsurface environment. The results of batch experiments show that the optimal parameter for the preparation of the persulfate-releasing tablet was persulfate:cellulose = 1:1 (wt:wt) with a 5,000 kg F/cm2 of pressure application. The cellulose-based persulfate tablet was able to release 2,030 mg/L of persulfate per day for 10 days. Compared to cement-based persulfate-releasing materials, the persulfate release rates of the cellulose-based persulfate tablets were much more stable. Moreover, since the tablets are soluble in water, no waste will be produced in the subsurface. The results of column tests show that groundwater flow would shorten the release time of the tablets. This study successfully developed unique persulfate tablets based on green remediation perspective. The efficacy of the persulfate-releasing tablets on the removal of organic pollutants needs to be further evaluated. The persulfate tablets are expected to be applied for site remediation in the future.

Keywords: sustained-release persulfate tablet, modified cellulose, green remediation, groundwater

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Authors: S. Nagheli, N. Samani, D. A. Barry

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In this paper, the velocity potential and stream function of capture zone for a well field in an aquifer bounded by two parallel streams with or without a uniform regional flow of any directions are presented. The well field includes any number of extraction or injection wells or a combination of both types with any pumping rates. To delineate the capture envelope, the potential and streamlines equations are derived by conformal mapping method. This method can help us to release constrains of other methods. The equations can be applied as useful tools to design in-situ groundwater remediation systems, to evaluate the surface–subsurface water interaction and to manage the water resources.

Keywords: complex potential, conformal mapping, image well theory, Laplace’s equation, superposition principle

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Authors: Joy Cao, Min Zhou

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Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

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Authors: Kazuhisa Koda, Tsutomu Kobayashi, Rebecca Lorennji, Alington Robert, Halston DeBrum, Julious Lucky, Paul Paul

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Atolls are low-lying small islands with highly permeable ground that does not allow rivers and lakes to develop. As the water resources on these atolls basically rely on precipitation, groundwater becomes a very important water resource during droughts. Freshwater lenses develop as groundwater on relatively large atoll islands and play a key role in the stable water supply. Atoll islands in the Pacific Ocean sometimes suffer from drought due to El Nino. The global warming effects are noticeable, particularly on atoll islands. The Republic of the Marshall Islands in Oceania is burdened with the problems common to atoll islands. About half of its population lives in the capital, Majuro, and securing water resources for these people is a crucial issue. There is a freshwater lens on the largest, Laura Island, which serves as a water source for the downtown area. A serious drought that occurred in 1998 resulted in excessive water intake from the freshwater lens on Laura Island causing up-coning. Up-coning mixes saltwater into groundwater pumped from water-intake wells. Because up-coning makes the freshwater lens unusable, there was a need to investigate the freshwater lens on Laura Island. In this study, we observed the electrical conductivities of the groundwater at different depths in existing monitoring wells to determine the total storage volume of the freshwater lens on Laura Island from 2010 to 2013. Our results indicated that most of the groundwater that seeped into the freshwater lens had flowed out into the sea.

Keywords: Atoll islands, drought, El-Nino, freshwater lens, groundwater observation

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Authors: Christopher Baiyegunhi, Oswald Gwavava

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The location/source of the Beattie magnetic anomaly (BMA) and interconnectivity of geologic structures at depth have been a topic of investigation for over 30 years. Up to now, no relationship between geological structures (interconnectivity of dolerite intrusions) at depth has been established. Therefore, the environmental impact of fracking the Karoo for shale gas could not be assessed despite the fact that dolerite dykes are groundwater localizers in the Karoo. In this paper, we shed more light to the unanswered questions concerning the possible location of the source of the BMA, the connectivity of geologic structures like dolerite dykes and sills at depth and this relationship needs to be established before the tectonic evolution of the Karoo basin can be fully understood and related to fracking of the Karoo for shale gas. The result of the magnetic investigation and modelling of four gravity profiles that crosses the BMA in the study area reveals that the anomaly, which is part of the Beattie magnetic anomaly tends to divide into two anomalies and continue to trend in an NE-SW direction, the dominant gravity signatures is of long wavelength that is due to a deep source/interface inland and shallows towards the coast, the average depth to the top of the shallow and deep magnetic sources was estimated to be approximately 0.6 km and 15 km, respectively. The BMA become stronger with depth which could be an indication that the source(s) is deep possibly a buried body in the basement. The bean-shaped anomaly also behaves in a similar manner like the BMA thus it could possibly share the same source(s) with the BMA.

Keywords: Beattie magnetic anomaly, magnetic sources, modelling, Karoo Basin

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Authors: Tamale Vincent

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Groundwater investigation is the investigation of underground formations to understand the hydrologic cycle, known groundwater occurrences, and identify the nature and types of aquifers. There are different groundwater investigation methods and surface geophysical method is one of the groundwater investigation more especially the Geoelectrical resistivity Schlumberger configuration method which provides valuable information regarding the lateral and vertical successions of subsurface geomaterials in terms of their individual thickness and corresponding resistivity values besides using surface geophysical method, hydrogeological and geological investigation methods are also incorporated to aid in preliminary groundwater investigation. Investigation for groundwater in lwantonde district has been implemented. The area project is located cattle corridor and the dry seasonal troubles the communities in lwantonde district of which 99% of people living there are farmers, thus making agriculture difficult and local government to provide social services to its people. The investigation was done using the Geoelectrical resistivity Schlumberger configuration method. The measurement point is located in the three sub-counties, with a total of 17 measurement points. The study location is at 0025S, 3110E, and covers an area of 160 square kilometers. Based on the results of the Geoelectrical information data, it was found two types of aquifers, which are open aquifers in depth ranging from six meters to twenty-two meters and a confined aquifer in depth ranging from forty-five meters to eighty meters. In addition to the Geoelectrical information data, drilling was done at an accessible point by heavy equipment in the Lwakagura village, Kabura sub-county. At the drilling point, artesian wells were obtained at a depth of eighty meters and can rise to two meters above the soil surface. The discovery of artesian well is then used by residents to meet the needs of clean water and for irrigation considering that in this area most wells contain iron content.

Keywords: artesian well, geoelectrical, lwantonde, Schlumberger

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Authors: Uma Maheshwari V., Rajanikanth Aluvalu, Kumar Gautam

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The COVID-19 disease is a highly contagious viral infection with major worldwide health implications. The global economy suffers as a result of COVID. The spread of this pandemic disease can be slowed if positive patients are found early. COVID-19 disease prediction is beneficial for identifying patients' health problems that are at risk for COVID. Deep learning and machine learning algorithms for COVID prediction using X-rays have the potential to be extremely useful in solving the scarcity of doctors and clinicians in remote places. In this paper, a convolutional neural network (CNN) with deep layers is presented for recognizing COVID-19 patients using real-world datasets. We gathered around 6000 X-ray scan images from various sources and split them into two categories: normal and COVID-impacted. Our model examines chest X-ray images to recognize such patients. Because X-rays are commonly available and affordable, our findings show that X-ray analysis is effective in COVID diagnosis. The predictions performed well, with an average accuracy of 99% on training photographs and 88% on X-ray test images.

Keywords: deep CNN, COVID–19 analysis, feature extraction, feature map, accuracy

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Authors: Ehsan Heidaryan

Abstract:

Gas hydrate sediments are ice like permafrost in deep see and oceans. Methane production in sequestration process and reducing atmospheric carbon dioxide, a main source of greenhouse gas, has been accentuated recently. One focus is capture, separation, and sequestration of industrial carbon dioxide. As a hydrate former, carbon dioxide forms hydrates at moderate temperatures and pressures. This phenomenon could be utilized to capture and separate carbon dioxide from flue gases, and also has the potential to sequester carbon dioxide in the deep seabeds. This research investigated the effect of synthetic surfactants on carbon dioxide hydrate formation, catalysis and consequently, methane production from hydrate permafrosts in sediments. It investigated the sequestration potential of carbon dioxide hydrates in ocean sediments. Also, the catalytic effect of biosurfactants in these processes was investigated.

Keywords: carbon dioxide, hydrate, sequestration, surfactant

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Authors: Rouighi Mustapha, Bouzid Laghaa Souad, Rouighi Tahar

Abstract:

Due to rain Shortage and the increase of population in the last years, wells excavation and groundwater use for different purposes had been increased without any planning. This is a great challenge for our country. Moreover, this scarcity of water resources in this region is unfortunately combined with rapid fresh water resources quality deterioration, due to salinity and contamination processes. Therefore, it is necessary to conduct the studies about groundwater quality in Algeria. In this work consists in the identification of the factors which influence the water quality parameters in Laghouat region by using statistical analysis Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and geographic information system (GIS) in an attempt to discriminate the sources of the variation of water quality variations. The results of PCA technique indicate that variables responsible for water quality composition are mainly related to soluble salts variables; natural processes and the nature of the rock which modifies significantly the water chemistry. Inferred from the positive correlation between K+ and NO3-, NO3- is believed to be human induced rather than naturally originated. In this study, the multivariate statistical analysis and GIS allows the hydrogeologist to have supplementary tools in the characterization and evaluating of aquifers.

Keywords: cluster, analysis, GIS, groundwater, laghouat, quality

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Authors: Ashutosh Mishra, Nikhil Goyal

Abstract:

A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: Shri Devi

Abstract:

This paper was conducted to see the ground water potential zones in Paramakudi taluk, Ramanathapuram,Tamilnadu India with a total areal extent of 745 sq. km. The various thematic map have been prepared for the study such as soil, geology, geomorphology, drainage, land use of the particular study area using the Toposheet of 1: 50000. The digital elevation model (DEM) has been generated from contour interval of 10m and also the slope was prepared. The ground water potential zone of the region was obtained using the weighted overlay analysis for which all the thematic maps were overlayed in arc gis 10.2. For the particular output the ranking has been given for all the parameters of each thematic layer with different weightage such as 25% was given to soil, 25% to geomorphology and land use land cover also 25%, slope 15%, lineament with 5% and drainage streams with 5 percentage. Using these entire potential zone maps was prepared which was overlayed with the village map to check the region which has good, moderate and low groundwater potential zone.

Keywords: GIS, ground water, Paramakudi, weighted overlay analysis

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Authors: Debneil Saha Roy

Abstract:

Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

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Authors: Priyanka Yadav, Rajkumar Ghosh, Alok Saini

Abstract:

Human civilization cannot exist and thrive in the absence of adequate water. As a result, even in smart cities, water plays an important role in human existence. The key causes of this catastrophic water scarcity crisis are lifestyle changes, over-exploitation of groundwater, water over usage, rapid urbanization, and uncontrolled population growth. Furthermore, salty water seeps into deeper aquifers, causing land subsidence. The purpose of this study on artificial groundwater recharge is to address the water shortage in Gomti Nagar, Lucknow. Submersibles are the most common methods of collecting freshwater from groundwater in Gomti Nagar neighbourhood of Lucknow. Gomti Nagar area has a groundwater depletion rate of 1968 m3/day/km2 and is categorized as Zone-A (very high levels) based on the existing groundwater abstraction pattern - A to D. Harvesting rainwater using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water management system. Rainwater collecting using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water conservation system. Due to a water imbalance of 24519 ML/yr, the Gomti Nagar region is facing severe groundwater depletion. According to the Lucknow Development Authority (LDA), the impact of installed RTRWHs (plot area 300 sq. m.) is 0.04 percent of rainfall collected through RTRWHs in Gomti Nagar region of Lucknow. When RTRWHs are deployed in all buildings, their influence will be greater. Bye-laws in India have mandated the installation of RTRWHs on plots greater than 300 sq.m. A better India without any water problem is a pipe dream that may be realized by installing residential and commercial rooftop rainwater collecting systems in every structure. According to the current study, RTRWHs should be used as an alternate source of water to bridge the gap between groundwater recharge and extraction in smart city viz. Gomti Nagar, Lucknow, India.

Keywords: groundwater recharge, RTRWHs, harvested rainwater, rainfall, water extraction

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Authors: Abe D. Desta

Abstract:

This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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