Search results for: deep groundwater potential

Authors: Benjamin L. Freidman, Sally L. Gras, Ian Snape, Geoff W. Stevens, Kathryn A. Mumford

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Increasing transportation and storage of petroleum hydrocarbons in Antarctic and sub-Antarctic regions have resulted in frequent accidental spills. Migrating petroleum hydrocarbon spills can have a significant impact on terrestrial and marine ecosystems in cold regions, as harsh environmental conditions result in heightened sensitivity to pollution. This migration of contaminants has led to the development of Permeable Reactive Barriers (PRB) for application in cold regions. PRB’s are one of the most practical technologies for on-site or in-situ groundwater remediation in cold regions due to their minimal energy, monitoring and maintenance requirements. The Main Power House site has been used as a fuel storage and power generation area for the Macquarie Island research station since at least 1960. Soil analysis at the site has revealed Total Petroleum Hydrocarbon (TPH) (C9-C28) concentrations as high as 19,000 mg/kg soil. Groundwater TPH concentrations at this site can exceed 350 mg/L TPH. Ongoing migration of petroleum hydrocarbons into the neighbouring marine ecosystem resulted in the installation of a ‘funnel and gate’ PRB in November 2014. The ‘funnel and gate’ design successfully intercepted contaminated groundwater and analysis of TPH retention and biodegradation on PRB media are currently underway. Installation of the PRB facilitates research aimed at better understanding the contribution of particle attached biofilms to the remediation of groundwater systems. Bench-scale PRB system analysis at The University of Melbourne is currently examining the role biofilms play in petroleum hydrocarbon degradation, and how controlled release nutrient media can heighten the metabolic activity of biofilms in cold regions in the presence of low temperatures and low nutrient groundwater.

Keywords: groundwater, petroleum, Macquarie island, funnel and gate

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Authors: Newton Muhury, Armando A. Apan, Tek N. Marasani, Gebiaw T. Ayele

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The changing climate has degraded freshwater availability in Australia that influencing vegetation growth to a great extent. This study assessed the vegetation responses to groundwater using Terra’s moderate resolution imaging spectroradiometer (MODIS), Normalised Difference Vegetation Index (NDVI), and soil water content (SWC). A hydrological model, SWAT, has been set up in a southeast Australian river catchment for groundwater analysis. The model was calibrated and validated against monthly streamflow from 2001 to 2006 and 2007 to 2010, respectively. The SWAT simulated soil water content for 43 sub-basins and monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) were applied in the machine learning tool, Waikato Environment for Knowledge Analysis (WEKA), using two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The assessment shows that different types of vegetation response and soil water content vary in the dry and wet seasons. The WEKA model generated high positive relationships (r = 0.76, 0.73, and 0.81) between NDVI values of all vegetation in the sub-basins against soil water content (SWC), the groundwater flow (GW), and the combination of these two variables, respectively, during the dry season. However, these responses were reduced by 36.8% (r = 0.48) and 13.6% (r = 0.63) against GW and SWC, respectively, in the wet season. Although the rainfall pattern is highly variable in the study area, the summer rainfall is very effective for the growth of the grass vegetation type. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Khalifa Abdunaser, Salem Eljawashi

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Study area is threatened by numerous petroleum activities. The most important risk is associated with dramatic dangers of misuse and oil and gas pollutions, such as significant volumes of produced water, which refers to waste water generated during the production of oil and natural gas and disposed on the surface surrounded oil and gas fields. This work concerns the impact of oil exploration and production activities on the physical and environment fate of the area, focusing on the investigation and observation of crude oil migration as toxic fluid. Its penetration in groundwater resulted from the produced water impacted by oilfield operations disposed to the earth surface in Al Wahat area. Describing the areal distribution of the dominant groundwater quality constituents has been conducted to identify the major hydro-geochemical processes that affect the quality of water and to evaluate the relations between rock types and groundwater flow to the quality and geochemistry of water in Post-Eocene aquifer. The chemical and physical characteristics of produced water, where it is produced, and its potential impacts on the environment and on oil and gas operations have been discussed. Field work survey was conducted to identify and locate a large number of monitoring wells previously drilled throughout the study area. Groundwater samples were systematically collected in order to detect the fate of spills resulting from the various activities at the oil fields in the study area. Spatial distribution maps of the water quality parameters were built using Kriging methods of interpolation in ArcMap software. Thematic maps were generated using GIS and remote sensing techniques, which were applied to include all these data layers as an active database for the area for the purpose of identifying hot spots and prioritizing locations based on their environmental conditions as well as for monitoring plans.

Keywords: Sirt Basin, produced water, Al Wahat area, Ground water

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Authors: Rajkumar Ghosh

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Water scarcity is a pressing issue in urban areas, even in smart cities where efficient resource management is a priority. This scarcity is mainly caused by factors such as lifestyle changes, excessive groundwater extraction, over-usage of water, rapid urbanization, and uncontrolled population growth. In the specific case of Gomti Nagar, Lucknow, Uttar Pradesh, India, the depletion of groundwater resources is particularly severe, leading to a water imbalance and posing a significant challenge for the region's sustainable development. The aim of this study is to address the water shortage in the Gomti Nagar region by focusing on the implementation of artificial groundwater recharge methods. Specifically, the research aims to investigate the effectiveness of rainwater collection through rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to reduce aquifer depletion and bridge the gap between groundwater recharge and extraction. The research methodology for this study involves the utilization of RTRWHs as the main method for collecting rainwater. This approach is considered effective in managing and conserving water resources in a sustainable manner. The focus is on implementing RTRWHs in residential and commercial buildings to maximize the collection of rainwater and its subsequent utilization for various purposes in the Gomti Nagar region. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage (0.04%) of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance of 24519 ML/yr in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. The findings of this study can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis. The data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. Statistical analysis and modelling techniques were employed to quantify the water imbalance and evaluate the effectiveness of RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. The study highlights the need for widespread adoption of RTRWHs in all buildings and emphasizes the importance of integrating such systems into the urban planning and development process. By doing so, smart cities like Gomti Nagar can achieve efficient water management, ensuring a better future with improved water availability for its residents.

Keywords: rooftop rainwater harvesting, rainwater, water management, aquifer

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Authors: M. O. Eyankware, D. O. Ufomata

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Groundwater samples were collected from Otovwodo-Ughelli and Environ with the aim of assessing groundwater quality of the area. Twenty (20) water samples from Boreholes (BH) (six) and Hand Dug Wells (HDW) (fourteen) were randomly sampled and were analysed for different physiochemical and bacteriological parameters. The following 16 parameters have been considered viz: pH, electrical conductivity, temperature, total hardness, total dissolved solids, dissolved oxygen, biological oxygen demand, phosphate, sulphate, chloride, nitrate, calcium, sodium, chloride, magnesium, and total suspended solids. On comparing the results against drinking quality standards laid by World Health Organization and Nigeria industrial standard, it was found that the water quality parameters were not above the (WHO, 2011 and NIS, 2007) permissible limit. Microbial analysis reveals the presence of coliform and E.coli in two hand-dug well (HDW7 and 13) and one borehole well (BH20). These contaminations are perhaps traceable to have originated from human activities (septic tanks, latrines, dumpsites) and have affected the quality of groundwater in Otovwodo-Ughelli. From the piper trilinear diagram, the dominant ionic species is alkali bicarbonate water type, with bicarbonate as the predominant ion (Na+ + K+)-HCO3.

Keywords: groundwater, surface water, Ughelli, Nigeria industrial standard, who standard

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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Authors: Mohammad Shameel, Peter K. K. Loh, James H. Ng

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Cybercrime is a new category of crime which poses a different challenge for crime investigators and incident responders. Attackers can mask their identities using a suite of tools and with the help of the deep web, which makes them difficult to track down. Scouring the deep web manually takes time and is inefficient. There is a growing need for a tool to scour the deep web to obtain useful evidence or intel automatically. In this paper, we will explain the background and motivation behind the research, present a survey of existing research on related tools, describe the design of our own crime/threat intelligence hunting tool prototype, demonstrate its capability with some test cases and lastly, conclude with proposals for future enhancements.

Keywords: cybercrime, deep web, threat intelligence, web crawler

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Hana' Al-Ghanim, Mu'tasim Abdel-Jaber, Maha Alqam

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This experimental investigation deals with shear strengthening of reinforced concrete (RC) deep beams using the externally bonded carbon fiber-reinforced polymer (CFRP) composites. The current study, therefore, evaluates the effectiveness of four various configurations for shear strengthening of deep beams with two different types of CFRP materials including sheets and laminates. For this purpose, a total of 10 specimens of deep beams were cast and tested. The shear performance of the strengthened beams is assessed with respect to the cracks’ formation, modes of failure, ultimate strength and the overall stiffness. The obtained results demonstrate the effectiveness of using the CFRP technique on enhancing the shear capacity of deep beams; however, the efficiency varies depending on the material used and the strengthening scheme adopted. Among the four investigated schemes, the highest increase in the ultimate strength is recorded by using the continuous wrap of two layers of CFRP sheets, exceeding a value of 86%, whereas an enhancement of about 36% is achieved by the inclined CFRP laminates.

Keywords: deep beams, laminates, shear strengthening, sheets

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Authors: Olumuyiwa Olusola Falowo

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One of the objectives of the Millennium Development Goals is to have sustainable access to safe drinking water and basic sanitation. In line with this objective, an assessment of groundwater quality was carried out in Odigbo Local Government Area of Ondo State in November – February, 2019 to assess the drinking, domestic and irrigation uses of the water. Samples from 30 randomly selected ground water sources; 16 shallow wells and 14 from boreholes and analyzed using American Public Health Association method for the examination of water and wastewater. Water quality index calculation, and diagrams such as Piper diagram, Gibbs diagram and Wilcox diagram have been used to assess the groundwater in conjunction with irrigation indices such as % sodium, sodium absorption ratio, permeability index, magnesium ratio, Kelly ratio, and electrical conductivity. In addition statistical Principal component analysis were used to determine the homogeneity and source(s) influencing the chemistry of the groundwater. The results show that all the parameters are within the permissible limit of World Health Organization. The physico-chemical analysis of groundwater samples indicates that the dominant major cations are in decreasing order of Na+, Ca2+, Mg2+, K+ and the dominant anions are HCO-3, Cl-, SO-24, NO-3. The values of water quality index varies suggest a Good water (WQI of 50-75) accounts for 70% of the study area. The dominant groundwater facies revealed in this study are the non-carbonate alkali (primary salinity) exceeds 50% (zone 7); and transition zone with no one cation-anion pair exceeds 50% (zone 9), while evaporation; rock–water interaction, and precipitation; and silicate weathering process are the dominant processes in the hydrogeochemical evolution of the groundwater. The study indicates that waters were found within the permissible limits of irrigation indices adopted, and plot on excellent category on Wilcox plot. In conclusion, the water in the study area are good/suitable for drinking, domestic and irrigation purposes with low equivalent salinity concentrate and moderate electrical conductivity.

Keywords: equivalent salinity concentration, groundwater quality, hydrochemical facies, principal component analysis, water-rock interaction

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Authors: Akhtar Malik Muhammad, Agha Mirwais

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Dams are considered to recharge aquifers by raising the water table, especially the ones near wells. The present study investigates the impact of dams on groundwater recharge in Jilga, Pakistan. The comparative analysis of changes in the groundwater table of the year 2012 and 2019 was carried out using ArcGIS 10.5 through the kriging method and remote sensing techniques to evaluate the mini dam's impact on the upstream area. Arc Info Spatial Analyze extension was used to find static water level maps of the years. The water table was observed minimum 67.08 feet and maximum 130.09 feet in 2012 whereas in 2019 the minimum water table level 49.89 feet and maximum 115.85 feet. Groundwater recharge with different ratio was noted, but the most significant was at Rabbani dam with 26ft due to supported lithology conditions and the lowest recharge was found at Garang dam14ft. The overall positive trend indicates the rehabilitation of dead karez and agriculture activities by increasing 36% the vegetation area in 2019. An over 6% increase in human settlement indicates socioeconomic development. Thus, it highlights the need for preferential focus on the construction of the dam so that the water level could be sustained to cater to the agricultural and domestic needs of the local population around the year

Keywords: water table, GIS, land cover, mini dams, agriculture

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Authors: Akbar Khodavirdizadeh, Ali Nemati Babaylou, Hassan Moomivand

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The history of human access to water technique has been one of the factors in the formation of human civilizations in the ancient world. The technique that makes surface water and groundwater accessible to humans on the ground has been a clever technique in human life to reach the water. In this study, while examining the water technique of ancient Iran using the Qanats technique, the water supply system of different regions of the ancient world were also studied and compared. Six groups of the ancient region of ancient Greece (Archaic 480-750 BC and Classical 223-480 BC), Urartu in Tuspa (600-850 BC), Petra (106-168 BC), Ancient Rome (265 BC), and the ancient United States (1450 BC) and ancient Iranian water technologies were studied under water supply systems. Past water technologies in these areas: water transmission systems in primary urban centers, use of water structures in water control, use of bridges in water transfer, construction of waterways for water transfer, storage of rainfall, construction of various types of pottery- ceramic, lead, wood and stone pipes have been used in water transfer, flood control, water reservoirs, dams, channel, wells, and Qanat. The central plateau of Iran is one of the arid and desert regions. Archaeological, geomorphological, and paleontological studies of the central region of the Iranian plateau showed that without the use of Qanats, the possibility of urban civilization in this region was difficult and even impossible. Zarch aqueduct is the most important aqueduct in Yazd region. Qanat of Zarch is a plain Qanat with a gallery length of 80 km; its mother well is 85 m deep and has 2115 well shafts. The main purpose of building the Qanat of Zārch was to access the groundwater source and transfer it to the surface of the ground. Regarding the structure of the aqueduct and the technique of transferring water from the groundwater source to the surface, it has a great impact on being different from other water techniques in the ancient world. The results show that the use of water technologies in ancient is very important to understand the history of humanity in the use of hydraulic techniques.

Keywords: ancient water technologies, groundwaters, qanat, human history, Ancient Iran

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Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

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Authors: Modreck Gomo

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Although the dolomite and calcite carbonates can neutralize Acid Mine Drainage (AMD) and prevent leaching of metals, salinity still remains a huge problem. The study presents a conceptual discussion of geochemical controls of salinity in a typical calcite and dolomite AMD neutralised groundwater systems. Thereafter field evidence is presented to support the conceptual discussions. 1020 field data sets of from a groundwater system reported to be under circumneutral conditions from the neutralization effect of calcite and dolomite is analysed using correlation analysis and bivariate plots. Field evidence indicates that sulphate, calcium and magnesium are strongly and positively correlated to Total Dissolved Solids (TDS) which is used as measure of salinity. In this, a hydrogeochemical system, the dissolution of sulphate, calcium and magnesium form AMD neutralization process contributed 50%, 10% and 5% of the salinity.

Keywords: acid mine drainage, carbonates, neutralization, salinity

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Authors: Moayyad Shawaqfah, Ibtehal Alqdah, Amjad Adaileh

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Coridoor area (400 km2) lies to the north – east of Amman (60 km). It lies between 285-305 E longitude and 165-185 N latitude (according to Palestine Grid). It been subjected to exploitation of groundwater from new eleven wells since the 1999 with a total discharge of 11 MCM in addition to the previous discharge rate from the well field 14.7 MCM. Consequently, the aquifer balance is disturbed and a major decline in water level. Therefore, suitable groundwater resources management is required to overcome the problems of over pumping and its effect on groundwater quality. Three–dimensional groundwater flow model Processing Modeflow for Windows Pro (PMWIN PRO, 2003) has been used in order to calculate the groundwater budget, aquifer characteristics, and to predict the aquifer response under different stresses for the next 20 years (2035). The model was calibrated for steady state conditions by trial and error calibration. The calibration was performed by matching observed and calculated initial heads for year 2001. Drawdown data for period 2001-2010 were used to calibrate transient model by matching calculated with observed one, after that, the transient model was validated by using the drawdown data for the period 2011-2014. The hydraulic conductivities of the Basalt- A7/B2 aquifer System are ranging between 1.0 and 8.0 m/day. The low conductivity value was found at the north-west and south-western parts of the study area, the high conductivity value was found at north-western corner of the study area and the average storage coefficient is about 0.025. The water balance for the Basalt and B2/A7 formation at steady state condition with a discrepancy of 0.003%. The major inflows come from Jebal Al Arab through the basalt and through the limestone aquifer (B2/A7 12.28 MCMY aquifer and from excess rainfall is about 0.68 MCM/a. While the major outflows from the Basalt-B2/A7 aquifer system are toward Azraq basin with about 5.03 MCMY and leakage to A1/6 aquitard with 7.89 MCMY. Four scenarios have been performed to predict aquifer system responses under different conditions. Scenario no.2 was found to be the best one which indicates that the reduction the abstraction rates by 50% of current withdrawal rate (25.08 MCMY) to 12.54 MCMY. The maximum drawdowns were decreased to reach about, 7.67 and 8.38m in the years 2025 and 2035 respectively.

Keywords: Amman/Zarqa Basin, Jordan, groundwater management, groundwater modeling, modflow

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Authors: Mahmud Gungor, Ali Aydin, Erdal Akyol, Suat Tasdelen

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The understanding of geotechnical characteristics of near-surface material and the effects of the groundwater is very important problem in such as site studies. For showing the relations between seismic data and groundwater we selected about 25 km2 as the study area. It has been presented which is a detailed work of seismic data and groundwater depths of Gokpinar Damp area. Seismic waves velocity (Vp and Vs) are very important parameters showing the soil properties. The seismic records were used the method of the multichannel analysis of surface waves near area of Gokpinar Damp area. Sixty sites in this area have been investigated with survey lines about 60 m in length. MASW (Multichannel analysis of surface wave) method has been used to generate one-dimensional shear wave velocity profile at locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 2 and 5 m intervals up to a depth of 45 m. Levels of equivalent shear wave velocity of soil are used the classified of the study area. After the results of the study, it must be considered as components of urban planning and building design of Gokpinar Damp area, Denizli and the application and use of these results should be required and enforced by municipal authorities.

Keywords: seismic data, Gokpinar Damp, urban planning, Denizli

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Authors: Xuewei Li, Jingfeng Yuan, Jianliang Zhou

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The 21st century has been called the century of human exploitation of underground space. Due to the characteristics of large quantity, tight schedule, low safety reserve and high uncertainty of deep foundation pit engineering, accidents frequently occur in deep foundation pit engineering, causing huge economic losses and casualties. With the successful application of information technology in the construction industry, building information modeling has become a research hotspot in the field of architectural engineering. Therefore, the application of building information modeling (BIM) and other information communication technologies (ICTs) in construction safety management is of great significance to improve the level of safety management. This research summed up the mechanism of the deep foundation pit engineering accident through the fault tree analysis to find the control factors of deep foundation pit engineering safety management, the deficiency existing in the traditional deep foundation pit construction site safety management. According to the accident cause mechanism and the specific process of deep foundation pit construction, the hazard information of deep foundation pit engineering construction site was identified, and the hazard list was obtained, including early warning information. After that, the system framework was constructed by analyzing the early warning information demand and early warning function demand of the safety management system of deep foundation pit. Finally, the safety management system of deep foundation pit construction site based on BIM through combing the database and Web-BIM technology was developed, so as to realize the three functions of real-time positioning of construction site personnel, automatic warning of entering a dangerous area, real-time monitoring of deep foundation pit structure deformation and automatic warning. This study can initially improve the current situation of safety management in the construction site of deep foundation pit. Additionally, the active control before the occurrence of deep foundation pit accidents and the whole process dynamic control in the construction process can be realized so as to prevent and control the occurrence of safety accidents in the construction of deep foundation pit engineering.

Keywords: Web-BIM, safety management, deep foundation pit, construction

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Authors: Usama Massoud, Abeer A. Kenawy, El-Said A. Ragab, Abbas M. Abbas, Heba M. El-Kosery

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Vertical Electrical Sounding (VES) and Transient Electro Magnetic (TEM) survey have been applied for characterizing the groundwater aquifers at El Sadat industrial area. El-Sadat city is one of the most important industrial cities in Egypt. It has been constructed more than three decades ago at about 80 km northwest of Cairo along the Cairo–Alexandria desert road. Groundwater is the main source of water supplies required for domestic, municipal, and industrial activities in this area due to the lack of surface water sources. So, it is important to maintain this vital resource in order to sustain the development plans of this city. In this study, VES and TEM data were identically measured at 24 stations along three profiles trending NE–SW with the elongation of the study area. The measuring points were arranged in a grid like pattern with both inter-station spacing and line–line distance of about 2 km. After performing the necessary processing steps, the VES and TEM data sets were inverted individually to multi-layer models, followed by a joint inversion of both data sets. Joint inversion process has succeeded to overcome the model-equivalence problem encountered in the inversion of individual data set. Then, the joint models were used for the construction of a number of cross sections and contour maps showing the lateral and vertical distribution of the geo-electrical parameters in the subsurface medium. Interpretation of the obtained results and correlation with the available geological and hydrogeological information revealed TWO aquifer systems in the area. The shallow Pleistocene aquifer consists of sand and gravel saturated with fresh water and exhibits large thickness exceeding 200 m. The deep Pliocene aquifer is composed of clay and sand and shows low resistivity values. The water bearing layer of the Pleistocene aquifer and the upper surface of Pliocene aquifer are continuous and no structural features have cut this continuity through the investigated area.

Keywords: El Sadat city, joint inversion, VES, TEM

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Authors: Joseph Uzuazomaro Oju

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The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

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Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu

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Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.

Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: S. M. Javad Davoodi, Mojtaba Shourian

Abstract:

Groundwater table close to the ground surface causes major problems in construction and mining operation. One of the methods to control groundwater in such cases is using pumping wells. These pumping wells remove excess water from the site project and lower the water table to a desirable value. Although the efficiency of this method is acceptable, it needs high expenses to apply. It means even small improvement in a design of pumping wells can lead to substantial cost savings. In order to minimize the total cost in the method of pumping wells, a simulation-optimization approach is applied. The proposed model integrates MODFLOW as the simulation model with Firefly as the optimization algorithm. In fact, MODFLOW computes the drawdown due to pumping in an aquifer and the Firefly algorithm defines the optimum value of design parameters which are numbers, pumping rates and layout of the designing wells. The developed Firefly-MODFLOW model is applied to minimize the cost of the dewatering project for the ancient mosque of Kerman city in Iran. Repetitive runs of the Firefly-MODFLOW model indicates that drilling two wells with the total rate of pumping 5503 m3/day is the result of the minimization problem. Results show that implementing the proposed solution leads to at least 1.5 m drawdown in the aquifer beneath mosque region. Also, the subsidence due to groundwater depletion is less than 80 mm. Sensitivity analyses indicate that desirable groundwater depletion has an enormous impact on total cost of the project. Besides, in a hypothetical aquifer decreasing the hydraulic conductivity contributes to decrease in total water extraction for dewatering.

Keywords: groundwater dewatering, pumping wells, simulation-optimization, MODFLOW, firefly algorithm

Procedia PDF Downloads 246

Authors: Yongrong Li, Ralf Domroes

Abstract:

Due to significant energy savings, enablement of higher machining speed as well as environmentally friendly features, Minimum Quantity Lubrication (MQL) has been used for many machining processes efficiently. However, in the deep hole drilling field (small tool diameter D < 5 mm) and long tool (length L > 25xD) it is always a bottle neck for a single channel MQL system. The single channel MQL, based on the Venturi principle, faces a lack of enough oil quantity caused by dropped pressure difference during the deep hole drilling process. In this paper, a system concept based on a bypass design has explored its possibility to dynamically reach the required pressure difference between the air inlet and the inside of aerosol generator, so that the deep hole drilling demanded volume of oil can be generated and delivered to tool tips. The system concept has been investigated in static and dynamic laboratory testing. In the static test, the oil volume with and without bypass control were measured. This shows an oil quantity increasing potential up to 1000%. A spray pattern test has demonstrated the differences of aerosol particle size, aerosol distribution and reaction time between single channel and bypass controlled single channel MQL systems. A dynamic trial machining test of deep hole drilling (drill tool D=4.5mm, L= 40xD) has been carried out with the proposed system on a difficult machining material AlSi7Mg. The tool wear along a 100 meter drilling was tracked and analyzed. The result shows that the single channel MQL with a bypass control can overcome the limitation and enhance deep hole drilling with a small tool. The optimized combination of inlet air pressure and bypass control results in a high quality oil delivery to tool tips with a uniform and continuous aerosol flow.

Keywords: deep hole drilling, green production, Minimum Quantity Lubrication (MQL), near dry machining

Procedia PDF Downloads 171

Authors: Khawar Naeem, Adel Elomri, Adel Zghibi

Abstract:

Contamination leakage from municipal solid waste (MSW) landfills is a serious environmental challenge that poses a threat to interconnected ecosystems. It not only contaminates the soil of the saturated zone, but it also percolates down the earth and contaminates the groundwater (GW). In this concise literature review, an effort is made to understand the environmental hazards posed by this contamination to the soil and groundwater, the type of contamination, and possible solutions proposed in the literature. In the study’s second phase, the MSW management practices are explored as the landfill site dump rate and type of MSW into the landfill site directly depend on the MSW management strategies. Case studies from multiple developed and underdeveloped countries are presented, and the complex MSW management system is investigated from an operational perspective to minimize the contamination of GW. One of the significant tools used in the literature was found to be Systems Dynamic Modeling (SDM), which is a simulation-based approach to study the stakeholder’s approach. By employing the SDM approach, the risk of GW contamination can be reduced by devising effective MSW management policies, ultimately resulting in water resource sustainability and regional sustainable development.

Keywords: groundwater contamination, environmental risk, municipal solid waste management, system dynamic modeling, water resource sustainability, sustainable development

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Authors: Rupas Kumar M., Saravana Kumar M., Amarendra Kumar S., Likhita Komal V., Sree Deepthi M.

Abstract:

The demand for water is increasing at an alarming rate due to rapid urbanization and increase in population. Due to freshwater scarcity, Groundwater became the necessary source of potable water to major parts of the world. This problem of freshwater scarcity and groundwater dependency is very severe particularly in developing countries and overpopulated regions like India. The present study aimed at evaluating the Ground Water Quality Index (GWQI), which represents overall quality of water at certain location and time based on water quality parameters. To evaluate the GWQI, sixteen water quality parameters have been considered viz. colour, pH, electrical conductivity, total dissolved solids, turbidity, total hardness, alkalinity, calcium, magnesium, sodium, chloride, nitrate, sulphate, iron, manganese and fluorides. The groundwater samples are collected from Kadapa City in Andhra Pradesh, India and subjected to comprehensive physicochemical analysis. The high value of GWQI has been found to be mainly from higher values of total dissolved solids, electrical conductivity, turbidity, alkalinity, hardness, and fluorides. in the present study, citrus limetta (sweet lemon) peel powder has used as a coagulant and GWQI values are recorded in different concentrations to improve GWQI. Sensitivity analysis is also carried out to determine the effect of coagulant dosage, mixing speed and stirring time on GWQI. The research found the maximum percentage improvement in GWQI values are obtained when the coagulant dosage is 100ppm, mixing speed is 100 rpm and stirring time is 10 mins. Alum is also used as a coagulant aid and the optimal ratio of citrus limetta and alum is identified as 3:2 which resulted in best GWQI value. The present study proposes Citrus limetta peel powder as a potential natural coagulant to treat Groundwater and to improve GWQI.

Keywords: alum, Citrus limetta, ground water quality index, physicochemical analysis

Procedia PDF Downloads 197

Authors: Rajkumar Ghosh

Abstract:

Rapid urbanization, rising population, changing lifestyles and in-migration, Lucknow is groundwater over-exploited area, with an abstract rate of 1968 m3/day/km2 in Gomti Nagar. The groundwater situation in Gomti Nagar is deteriorating day-by-day. According to the work, the calculated annual water deficiency in Gomti Nagar area will be 28061 Million Litre (ML) in 2022. Within 30 yrs., the water deficiency will be 735570 ML (till 2051). The calculated groundwater recharge in Gomti Nagar was 10813 ML/y (in 2022). The annual groundwater abstraction from Gomti Nagar area was 35332 ML/yr. (in 2022). Bye-laws (≥ 300 sq.m) existing RTRWHs can recharge 17.71 ML/yr. in Gomti Nagar area. The existing RTRWHs are contributing 0.07% for recharging groundwater table. In Gomti Nagar, the water level is dropping at a rate of 1.0 metre per year, and the depth of the water table is less than 30 metre below ground level (mbgl). Natural groundwater recharge is affected by the geomorphological conditions of the surrounding area. Gomti Nagar is located on the erosional terrace (Te) and depositional terrace (d) of the Gomti River. The flood plain in Lucknow city is less active due to the embankments on the both sides of the Gomti River. The alluvium is composed of clay sandy up to a depth of 30m, and the alignment of the Gomti River reveals the presence of sandy soil at shallow depths. Aquifer depth 120 metre. Recharge as in Gomti Nagar (it may vary) 0 – 150 metre. Infiltration rates in alluvial floodplains range from 0.8 to 74 cm/hr. Geologically and Geomorphologically support rapid percolation of rainwater through alluvium in Gomti Nagar, Lucknow city, Uttar Pradesh. Over-exploitation of groundwater causes natural hazards viz. land subsidence, development of cracks on roads and buildings, development of vacuum and compactness of soil/clay which leads towards land subsidence, devastating effects on natural stream flow. Gomti River already transitioning phase from ‘effluent’ to ‘influent’, and saline intrusion in Aquifer –II (among Five aquifers in Lucknow city). A 250 m long crack developed in 2007 due to groundwater depletion in Dullu Khera and Vader Khera village of Kakori, Uttar Pradesh. The groundwater table of Lucknow is declining and water table imbalance occurs due to 17 times less recharge than groundwater exploitation. Uttar Pradesh along with four states have extracted 49% of groundwater in the entire country. In Gomti Nagar area, 27305 no of houses are present and available build up area 3.8 sq. km (60% of plot area) based on Lucknow Development Authority (LDA) Master plan 2031. If RTRWHs would install in all the houses, then 12% harvested rainwater contribute to the water table in Gomti Nagar area. Till 2051, Gomti Nagar area will harvest 91110 ML of rainwater. There are minimalistic chances that any incidence of flood can occur due to RTRWH. Thus, it can conclud that RTRWH is not related to flood happening in urban areas viz. Gomti Nagar.

Keywords: RTRWH, aquifer, groundwater table, rainwater, infiltration

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Authors: Romisaa Ali

Abstract:

The Policy Gradient approach is one of the deep reinforcement learning families that combines deep neural networks (DNN) with reinforcement learning RL to discover the optimum of the control problem through experience gained from the interaction between the robot and its surroundings. In contrast to earlier policy gradient algorithms, which were unable to handle these two types of error because of over-or under-estimation introduced by the deep neural network model, this article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: deep neural networks, deep reinforcement learning, proximal policy optimization, state-of-the-art, trust region policy optimization

Procedia PDF Downloads 136