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Article: An emergent addition for the optimal systemization of wastewater utilization plants using artificial intelligence.

Hasan, Mohd Abul

Water science and technology : a journal of the International Association on Water Pollution Research

2021 Volume 84, Issue 10-11, Page(s) 2805–2817

Abstract: The treatment of wastewater is an essential factor in preventing pollutants and promoting the quality of the water. The inherent complexity, influential impact and the solid waste infrastructure all lead to confusion and variance in the primary clarifier ...

Abstract	The treatment of wastewater is an essential factor in preventing pollutants and promoting the quality of the water. The inherent complexity, influential impact and the solid waste infrastructure all lead to confusion and variance in the primary clarifier for wastewater. These inconsistencies lead to variations in the purity and capacity constraints of wastewater and the existential impact of water receipt. Water treatment is a complicated task that has chemical, technical and biochemical aspects. A credible artificial neural network (ANN) method is necessary for another wastewater treatment plant to prevent the breakdown of the processes. Virtual reality seems to have become a strong solution for preventing waste management uncertainties and problems. This is not only due to extreme changes but also to significant external disturbances that water systems are subjected to when controlling challenges. Climate is among the most significant of such disturbances. Various environmental conditions actually include different influx frequencies and levels of substances. Water contamination has become one of the extremely serious growing concerns; sewage treatment plant identification is a key major issue here and the agencies enforce tighter requirements when operating wastewater software systems. This article plans to create models of achievement and prospects when possible future guidance of recent research borders for the use of artificial intelligence in wastewater treatment plants that concurrently deal with pollutants. This study has shown us that the composite ANN provides a greater level of competence in plant prediction and systemization.
MeSH term(s)	Artificial Intelligence ; Neural Networks, Computer ; Waste Disposal, Fluid ; Waste Water ; Water Pollutants, Chemical ; Water Purification
Chemical Substances	Waste Water ; Water Pollutants, Chemical
Language	English
Publishing date	2021-12-01
Publishing country	England
Document type	Journal Article
ZDB-ID	764273-8
ISSN	1996-9732 ; 0273-1223
ISSN (online)	1996-9732
ISSN	0273-1223
DOI	10.2166/wst.2021.203
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Article: Effects of Chemicals Exposure on the Durability of Geopolymer Concrete Incorporated with Silica Fumes and Nano-Sized Silica at Varying Curing Temperatures.

Paruthi, Sagar / Rahman, Ibadur / Husain, Asif / Hasan, Mohd Abul / Khan, Afzal Husain

Materials (Basel, Switzerland)

2023 Volume 16, Issue 18

Abstract: Durable concrete significantly reduces the spalling caused by chemical damage. The objective of current research is to substitute cement with supplementary such as fly ash (FA), ground granulated blast furnace slag (GGBS), and alccofine (AF). ... ...

Abstract	Durable concrete significantly reduces the spalling caused by chemical damage. The objective of current research is to substitute cement with supplementary such as fly ash (FA), ground granulated blast furnace slag (GGBS), and alccofine (AF). Additionally, the impact of nano-silica (NS) and silica fumes (SF) on the GPC durability when cured at various temperatures has been attempted. In order to perform this, GPC samples were produced by combining NS and SF at proportions of 0.5% NS + 5% SF, 1% NS + 10% SF, and 1.5% NS + 15% SF, and then cured at temperatures of 27 °C, 60 °C, 90 °C, and 120 °C, respectively. In this research, all concrete specimens were continuously immersed for twelve weeks under four different chemicals, i.e., HCl (2%), H
Language	English
Publishing date	2023-09-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2487261-1
ISSN	1996-1944
ISSN	1996-1944
DOI	10.3390/ma16186332
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Article: Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin

Meshram, Sarita Gajbhiye / Meshram, Chandrashekhar / Hasan, Mohd Abul / Khan, Muhammad Arshad / Islam, Saiful

Applied water science. 2022 July, v. 12, no. 7

2022

Abstract: Soil erosion is common and has a wide range of spatiotemporal variability. It is crucial in determining sediment output, which is essential for proper watershed management. In this research, we propose morphometric deterministic models (MDM) for ... ...

Abstract	Soil erosion is common and has a wide range of spatiotemporal variability. It is crucial in determining sediment output, which is essential for proper watershed management. In this research, we propose morphometric deterministic models (MDM) for prediction of sediment yield index using morphometric parameters of 49 watersheds from Upper Narmada Basin of Madhya Pradesh state, India. For this purpose, Shuttle Radar Topography Mission generated Digital Elevation Model was used to extract and analyze 12 morphometric parameters including linear, aerial, and relief parameters. Principle Component Analysis has been applied for the most effective parameter estimation. The linear and nonlinear MDM were discovered to be suitable for the field of sediment research due to the high value of R² (over 70%). The sediment yield forecasting is critical for taking the appropriate management measures in the watershed to reduce the sediment load in the reservoir and extend the life of the structure.
Keywords	basins ; deterministic models ; digital elevation models ; morphometry ; prediction ; principal component analysis ; radar ; sediment contamination ; sediment yield ; sediments ; soil erosion ; topography ; water ; watershed management ; watersheds ; India
Language	English
Dates of publication	2022-07
Size	p. 153.
Publishing place	Springer International Publishing
Document type	Article
ZDB-ID	2594789-8
ISSN	2190-5495 ; 2190-5487
ISSN (online)	2190-5495
ISSN	2190-5487
DOI	10.1007/s13201-022-01644-0
Database	NAL-Catalogue (AGRICOLA)

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Article: Sustainable landfill sites selection using geospatial information and AHP-GDM approach: A case study of Abha-Khamis in Saudi Arabia.

Arshad, Muhammad / Hasan, Mohd Abul / Al Mesfer, Mohammed K / Al Alwan, Basem Abdullah / Qureshi, Mohamed Noor / Eldirderi, Moutaz

Heliyon

2023 Volume 9, Issue 6, Page(s) e16432

Abstract: Social, environmental, and technical factors must be combined to solve the complex problem of ever-growing municipal solid waste (MSW) and minimize its negative impact on the environment. Saudi Arabia has launched a US$13 billion tourism strategy to ... ...

Abstract	Social, environmental, and technical factors must be combined to solve the complex problem of ever-growing municipal solid waste (MSW) and minimize its negative impact on the environment. Saudi Arabia has launched a US$13 billion tourism strategy to transform the Asir region into a year-round tourist destination and has pledged to welcome 10 million local and foreign visitors by 2030. The estimated share of Abha-Khamis will increase to 7.18 million tons of household waste per year. With a gross domestic product (GDP) of USD 820.00 billion by the end of 2022, Saudi Arabia can no longer afford to neglect the issue of waste production and its safe disposal. In this study, to account for all factors and evaluation criteria, a combination of remote sensing, geographic information systems and an analytical hierarchy process (AHP) was used to determine the best locations for municipal solid waste (MSW) disposal in Abha-Khamis. The analysis revealed that 60% of the study area consists of faults (14.28%), drainage networks (12.80%), urban (11.43%), land use (11.41%) and roads (8.35%), while 40% of the suitable area for landfill. Of these, a total of 20 sites ranging in size from 100 to 595 ha are distributed at reasonable distances from the cities of Abha-Khamis, which meet all the critical criteria for suitable landfill sites mentioned in the literature. Current research shows that the use of integrated remote sensing, GIS and the AHP-GDM approach significantly improves the identification of land suitability for MSW management.
Language	English
Publishing date	2023-06-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2023.e16432
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Assessing vulnerability to soil erosion based on fuzzy best worse multi-criteria decision-making method

Meshram, Sarita Gajbhiye / Hasan, Mohd Abul / Meshram, Chandrashekhar / Ilderomi, Ali Reza / Tirivarombo, Sithabile / Islam, Saiful

Applied water science. 2022 Sept., v. 12, no. 9

2022

Abstract: Soil wearing away or erosion is a chief agent of land loss in agricultural land and is regarded worldwide as a serious environmental hazard. This study performed watershed prioritization using morphometric parameters based on fuzzy best worse method (F- ... ...

Abstract	Soil wearing away or erosion is a chief agent of land loss in agricultural land and is regarded worldwide as a serious environmental hazard. This study performed watershed prioritization using morphometric parameters based on fuzzy best worse method (F-BWM) and GIS integration for Gusru Watershed, India. This study prioritizes sub-watersheds of the study area from viewpoint of soil erosion using five major parameters i.e., stream frequency (Fₛ), relative relief (Rᵣ), length of overland flow (Lₒ), relief ratio (Rₕ) and drainage density (Dd). Fuzzy based Best Worse Multi-Criteria Decision-Making (F-BWM) Method was used to assigning weights to used criteria and combining them to achieve erosion susceptibility for each sub-watershed. Results showed that sub-watersheds 9, 14, and 5 were most susceptible to soil erosion and sub-watershed 3 was the least from the viewpoint of soil erosion ranking.
Keywords	agricultural land ; drainage ; environmental hazards ; morphometry ; multi-criteria decision making ; overland flow ; prioritization ; soil ; soil erosion ; streams ; subwatersheds ; water ; India
Language	English
Dates of publication	2022-09
Size	p. 219.
Publishing place	Springer International Publishing
Document type	Article
ZDB-ID	2594789-8
ISSN	2190-5495 ; 2190-5487
ISSN (online)	2190-5495
ISSN	2190-5487
DOI	10.1007/s13201-022-01714-3
Database	NAL-Catalogue (AGRICOLA)

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Article: Simplified sediment yield index incorporating parameter stream length

Meshram, Sarita Gajbhiye / Singh, Vijay P. / Meshram, Chandrashekhar / Hasan, Mohd Abul / Islam, Saiful

Environmental earth sciences. 2021 Sept., v. 80, no. 18

2021

Abstract: Sediment-Runoff process is highly variable and nonlinear in nature. In the present study an attempt has been made to develop a relationship between watershed stream length and Sediment Yield Index (SYI) and test it on Narmada watersheds, Madhya Pradesh, ... ...

Abstract	Sediment-Runoff process is highly variable and nonlinear in nature. In the present study an attempt has been made to develop a relationship between watershed stream length and Sediment Yield Index (SYI) and test it on Narmada watersheds, Madhya Pradesh, India. Area (A), Curve Number (CN) and stream length (SL) were utilized as input for model development. The three models (A model, CN model and simplified All India Soil and Land Use Survey (AISLUS) model including parameter SL) performed differently, with the coefficient of R² equal to 0.01, 0.02 and 0.71 (Shakkar watershed), 0.11, 0.23 and 0.91 (Bamhani watershed), 0.06, 0.001 and 0.80 (Manot watershed) and 0.40, 0.05 and 0.66 (Mohgaon watershed), respectively. The logarithmic simplified AISLUS model incorporating parameter SL resulted with the coefficient of R² as 0.76 (Shakkar watershed), 0.93 (Bamhani watershed), 0.84 (Manot watershed) and 0.66 (Mohgaon watershed). Therefore, the logarithm simplified AISLUS model was chosen as the best regression model for this study. It is observed that the simplified AISLUS model (logarithm form) incorporating parameter SL had a satisfactory efficiency as 76.35% (Shakkar watershed), 66.05% (Mohgaon watershed), 93.36% (Bamhani watershed), and 83.83% (Manot watershed) by Nash efficiency scale. The resulting higher Nash efficiency values support the versatility of the derived relationship and invoke assessment of SYI from the watershed stream length value. The prediction of SYI is important when adopting a suitable soil conservation measure in the watershed for minimizing soil erosion.
Keywords	land use ; models ; prediction ; regression analysis ; sediment yield ; soil ; soil conservation ; soil erosion ; streams ; surveys ; watersheds ; India
Language	English
Dates of publication	2021-09
Size	p. 631.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	2493699-6
ISSN	1866-6299 ; 1866-6280
ISSN (online)	1866-6299
ISSN	1866-6280
DOI	10.1007/s12665-021-09919-6
Database	NAL-Catalogue (AGRICOLA)

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Article: Comparative Overview of the Performance of Cementitious and Non-Cementitious Nanomaterials in Mortar at Normal and Elevated Temperatures.

Khan, M Arsalan / Imam, M Khalid / Irshad, Kashif / Ali, Hafiz Muhammad / Hasan, Mohd Abul / Islam, Saiful

Nanomaterials (Basel, Switzerland)

2021 Volume 11, Issue 4

Abstract: Nanotechnology has emerged as a field with promising applications in building materials. Nanotechnology-based mortars are examples of such building materials that have widespread applications in the construction industry. The main nanomaterials used in ... ...

Abstract	Nanotechnology has emerged as a field with promising applications in building materials. Nanotechnology-based mortars are examples of such building materials that have widespread applications in the construction industry. The main nanomaterials used in mortars include nano-silica, nano-magnesium oxide, nano-alumina, nano-titanium oxide, nano-zinc oxide, nano-clay, and nano-carbon. This review paper presents a summary of the properties and effects of these nanomaterials on cement mortar in terms of its fresh-state and hard-state properties. The fresh-state properties include the setting time, consistency, and workability, while the hard-state properties include mechanical properties such as compressive, flexural, tensile strengths, as well as the elasticity modulus, in addition to durability properties such as water absorption, shrinkage strain, strength loss due to freeze-thaw cycles, and chloride penetration, among others. Different nanomaterials cause different physical and chemical alterations within the microstructures of cement mortar. Therefore, the microstructural characterization and densification of mortar are discussed in detail at varying temperatures. In general, the involvement of nanomaterials in cement mortar influences the fresh-state properties, enhances the mechanical properties, and impacts the durability properties, while reducing the porosity present in the mortar matrix. Cementitious nanomaterials can create a pathway for the easy injection of binding materials into the internal microstructures of a hydration gel to impact the hydration process at different rates, whereas their non-cementitious counterparts can act as fillers. Furthermore, the research gaps and future outlook regarding the application of nanomaterials in mortar are discussed.
Language	English
Publishing date	2021-04-02
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2662255-5
ISSN	2079-4991
ISSN	2079-4991
DOI	10.3390/nano11040911
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Toxic metal ions contamination in the groundwater, Kingdom of Saudi Arabia

Ali, Imran / Hasan, Mohd Abul / Alharbi, Omar M. L.

Journal of Taibah University for Science. 2020 Jan. 01, v. 14, no. 1 p.1571-1579

2020

Abstract: The Kingdom of Saudi Arabia (KSA) is one of the rising countries in the Gulf region but always scared of water; being present in the arid desert. Among some water resources groundwater is one of the most significant ones in this country but unfortunately ...

Abstract	The Kingdom of Saudi Arabia (KSA) is one of the rising countries in the Gulf region but always scared of water; being present in the arid desert. Among some water resources groundwater is one of the most significant ones in this country but unfortunately is being contaminated by the toxic metal ions. The present article describes the status of groundwater contamination by toxic metal ions. The meal ions analysed in the groundwater of KSA are Al, Cr, As, Cd, Ba, Co, Cu, Fe, Li, Hg, Mn, Ni, Se, Pb, V and Zn. This article describes the different groundwater resources in KSA, toxicities of the metal ions, metal ions contamination in the groundwater and sources of metal ions pollution. Besides, efforts are made to discuss the future challenges and the remediation measures; needed to protect the groundwater resources. This article will be important to the academicians, researchers, industry persons and the regulatory authorities.
Keywords	groundwater ; groundwater contamination ; industry ; remediation ; toxicity ; Saudi Arabia ; Contamination ; future challenges and the remediation ; pollution sources ; toxic metal ions
Language	English
Dates of publication	2020-0101
Size	p. 1571-1579.
Publishing place	Taylor & Francis
Document type	Article ; Online
ZDB-ID	2834710-9
ISSN	1658-3655
ISSN	1658-3655
DOI	10.1080/16583655.2020.1847807
Database	NAL-Catalogue (AGRICOLA)

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Article: Green synthesis of metalloid nanoparticles and its biological applications: A review.

Roy, Arpita / Datta, Shreeja / Luthra, Ritika / Khan, Muhammad Arshad / Gacem, Amel / Hasan, Mohd Abul / Yadav, Krishna Kumar / Ahn, Yongtae / Jeon, Byong-Hun

Frontiers in chemistry

2022 Volume 10, Page(s) 994724

Abstract: Synthesis of metalloid nanoparticles using biological-based fabrication has become an efficient alternative surpassing the existing physical and chemical approaches because there is a need for developing safer, more reliable, cleaner, and more eco- ... ...

Abstract	Synthesis of metalloid nanoparticles using biological-based fabrication has become an efficient alternative surpassing the existing physical and chemical approaches because there is a need for developing safer, more reliable, cleaner, and more eco-friendly methods for their preparation. Over the last few years, the biosynthesis of metalloid nanoparticles using biological materials has received increased attention due to its pharmaceutical, biomedical, and environmental applications. Biosynthesis using bacterial, fungal, and plant agents has appeared as a faster developing domain in bio-based nanotechnology globally along with other biological entities, thus posing as an option for conventional physical as well as chemical methods. These agents can efficiently produce environment-friendly nanoparticles with the desired composition, morphology (shape as well as size), and stability, along with homogeneity. Besides this, metalloid nanoparticles possess various applications like antibacterial by damaging bacterial cell membranes, anticancer due to damaging tumour sites, targeted drug delivery, drug testing, and diagnostic roles. This review summarizes the various studies associated with the biosynthesis of metalloid particles, namely, tellurium, arsenic, silicon, boron, and antimony, along with their therapeutic, pharmaceutical and environmental applications.
Language	English
Publishing date	2022-09-26
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2711776-5
ISSN	2296-2646
ISSN	2296-2646
DOI	10.3389/fchem.2022.994724
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Article ; Online: Imputation of missing monthly rainfall data using machine learning and spatial interpolation approaches in Thale Sap Songkhla River Basin, Thailand.

Pinthong, Sirimon / Ditthakit, Pakorn / Salaeh, Nureehan / Hasan, Mohd Abul / Son, Cao Truong / Linh, Nguyen Thi Thuy / Islam, Saiful / Yadav, Krishna Kumar

Environmental science and pollution research international

2022

Abstract: Missing rainfall data has been a prevalent issue and primarily interested in hydrology and meteorology. This research aimed to examine the capability of machine learning (ML) and spatial interpolation (SI) methods to estimate missing monthly rainfall ... ...

Abstract	Missing rainfall data has been a prevalent issue and primarily interested in hydrology and meteorology. This research aimed to examine the capability of machine learning (ML) and spatial interpolation (SI) methods to estimate missing monthly rainfall data. Six ML algorithms (i.e. multiple linear regression (MLR), M5 model tree (M5), random forest (RF), support vector regression (SVR), multilayer perceptron (MLP), genetic programming (GP)) and four SI methods (i.e. arithmetic average (AA), inverse distance weighting (IDW), correlation coefficient weighted (CCW), normal ratio (NR)) were investigated and compared in their performance. The twelve rainfall stations, located in the Thale Sap Songkhla river basin and nearby basins, were considered as a study case. Tuning hyper-parameters for each ML method was conducted to get the most suitable model for the data sets considered. Three performance criteria matrices (i.e. NSE, OI, and r) were chosen, and the sum of those three performance criteria matrices was introduced for methods' performance comparison. The experimental results pointed out that selecting neighbouring stations were essential when applying SI methods, but not for the ML method. The overall performance showed ML better imputed missing monthly rainfall than SI due to overcoming spatial constraints. GP provided the highest performance by giving NSE = 0.825, OI = 0.877, and r = 0.909 for the training stage. Those values for the testing stage were 0.796, 0.852, and 0.902, respectively. It was followed by SVR-rbf, SVR-poly, and RF. NR provided the best performance among four SI methods, followed by CCW, AA, and IDW. When applying SI methods, it should contemplate a correlation between the target and neighbouring stations greater than 0.80.
Language	English
Publishing date	2022-09-29
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-022-23022-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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