Article
Environmental Sciences
Arvind Yadav, Mohammad Kamrul Hasan, Devendra Joshi, Vinod Kumar, Azana Hafizah Mohd Aman, Hesham Alhumyani, Mohammed S. Alzaidi, Haripriya Mishra
Summary: This research aimed to develop a single hybrid artificial intelligence model for estimating the suspended sediment yield (SSY) in the Mahanadi River, India. The model combined data from 11-gauge stations into a hybrid generalized model using artificial neural network (ANN) and genetic algorithm (GA) optimization. The results showed that the proposed model outperformed the conventional approaches in terms of correlation and error, making it the most suitable model for estimating SSY in the MR Basin, particularly at the Tikarapara measuring station.
Article
Environmental Sciences
Arvind Yadav, Devendra Joshi, Vinod Kumar, Hitesh Mohapatra, Celestine Iwendi, Thippa Reddy Gadekallu
Summary: This article develops an artificial intelligence model based on genetic algorithm and artificial neural network for predicting suspended sediment yield (SSY) in the Godavari River Basin in India. The model shows the highest correlation coefficient and lowest error values compared to traditional models, making it a superior alternative for SSY prediction.
Article
Green & Sustainable Science & Technology
Ebenezer Boakye, F. O. K. Anyemedu, Emmanuel A. Donkor, Jonathan A. Quaye-Ballard
Summary: Accurate information on sediment yield in the Pra River Basin, Ghana is crucial for proper catchment and water resources management. This study found high sediment yields in the basin, with significant differences between contributing drainage basins. Rivers in galamsey prone basins had higher sediment pollution levels. The study highlights the importance of considering land use activities and catchment characteristics in predicting sediment yield variations.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2022)
Article
Chemistry, Multidisciplinary
Laszlo Vas, Eniko Anna Tamas
Summary: The study aims to find an effective method for monitoring suspended sediment transport in rivers. The currently used methods are not accurate enough, so the researchers tested an integrated surrogate method based on turbidity registration to determine the suspended sediment yield in the lower reach of the Danube River. The results of the tests show that the method has great potential, but further measurements are needed to refine the relationships.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Mohammad Ehteram, Ali Najah Ahmed, Sarmad Dashti Latif, Yuk Feng Huang, Meysam Alizamir, Ozgur Kisi, Cihan Mert, Ahmed El-Shafie
Summary: This study explored the effectiveness of artificial neural network (ANN) models in predicting suspended sediment load (SSL) and found that a hybrid ANN-WA model outperformed other ANN models, leading to improved accuracy in SSL prediction. An optimisation algorithm was introduced in a multi-objective framework to determine the best combination of inputs for predicting SSL, resulting in significant improvement in accuracy when hybridised with the ANN model and WA algorithm.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Multidisciplinary Sciences
Mahmoud Reza Ramezanpour, Mostafa Farajpour
Summary: The study introduced optimal concentrations of macro elements for greenhouse banana using ANOVA and two artificial neural networks, with the results showing that the GRNN model had better performance in modeling and predicting plant yield, fruit length, and number of rows per spike. This suggests that reducing chemical fertilizers based on the GRNN-GA hybrid model can achieve high yields compared to traditional methods.
Article
Environmental Sciences
Marzieh Fadaee, Amin Mahdavi-Meymand, Mohammad Zounemat-Kermani
Summary: This study investigates the application of two metaheuristic algorithms (BOA and GA) in the prediction of Suspended Sediment Load (SSL). The results show that the performances of all models are similar, and the metaheuristic algorithms can improve the accuracy of some models, with BOA outperforming GA.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
C. E. Renshaw, E. N. Dethier, J. D. Landis, J. M. Kaste
Summary: The input of organic matter into stream channels is an important energy source for headwater ecosystems and plays a crucial role in the global carbon cycle. The study focuses on quantifying the mobilization, transport, and storage of organic-rich fine sediment in a Strahler fourth-order stream during intermediate-sized storm events. It is found that the channel bed is consistently a source of suspended load to the channel margins, and the trapping of suspended load by riparian margins limits sediment transport distance and decouples the channel from local terrestrial organic matter exchange.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Arvind Yadav, Marwan Ali Albahar, Premkumar Chithaluru, Aman Singh, Abdullah Alammari, Gogulamudi Vijay Kumar, Yini Miro
Summary: The forecasting of sediment load (SL) is crucial for various purposes such as reservoir operations, water resource planning, and risk management. However, direct measurement of SL is challenging and expensive. In this study, a one-step-ahead SL forecasting model was developed for the Mahanadi River (MR) in India using artificial neural networks (ANN) and multi-objective genetic algorithm (ANN-MOGA) techniques. The performance of the proposed hybrid model was found to be significantly better compared to traditional regression models. The results suggest that the ANN-MOGA model is recommended for SL forecasting due to its superior performance and ease of application.
Article
Engineering, Civil
Teresa Serra, Marianna Soler, Aina Barcelona, Jordi Colomer
Summary: Sediment-replenished artificial flooding results in a more balanced suspended sediment transport compared to non-sediment-replenishment cases, with higher sedimentation rates during flood events.
JOURNAL OF HYDROLOGY
(2022)
Article
Water Resources
Mario Bentivenga, Joris de Vente, Salvatore Ivo Giano, Giacomo Prosser, Marco Piccarreta
Summary: This paper investigates the impact of hydrological drought on suspended sediment yield (SSY) in the Ofanto River basin and its sub-basins in southern Italy from 1951 to 1989. The study utilizes the Standardized Precipitation Evaporation Index (SPEI12) to assess hydrological drought and analyzes the correlations between dry/wet cycles, streamflow, and SSY using various factors such as Qmean, Qmax, rainfall erosivity, and rainfall intensity. The results show a significant correlation between Qmean, Qmax, and SSY, while SPEI12 and rainfall intensity do not have a strong correlation with SSY. Additionally, the analysis indicates higher SSY estimations during wet periods following a drought or during drought periods.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Engineering, Civil
Cong Xiao, Xiao-Hua Zhu, Chuanzheng Zhang, Ze-Nan Zhu, Yun Long Ma, Ji Wen Zhong, Li Xin Wei
Summary: This study successfully estimated the cross-section averaged suspended sediment concentration (SSC) and suspended sediment discharge (SSD) in the Yangtze River using Coastal Acoustic Tomography (CAT). The results showed that SSD was primarily driven by water discharge, with values ranging from 204 kg/s during the dry season to a maximum of 36,299 kg/s during flood events. This method offers the advantage of continuous real-time monitoring of transect river flow, SSC, and SSD.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Multidisciplinary
Nannan Zhao, Alireza Ghaemi, Chengwen Wu, Shahab S. Band, Kwok-Wing Chau, Atef Zaguia, Majdi Mafarja, Amir H. Mosavi
Summary: Estimation of suspended sediment load (SSL) is crucial for water resources management, with the ITD-EPR method proving to be the most accurate in predicting SSL at the Sarighamish and Varand Stations in Iran. This method outperformed other approaches like MT and SRC, showcasing its superior predictive capabilities.
ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS
(2021)
Article
Computer Science, Artificial Intelligence
Li Wang, Yikang Guo, Biren Dalip, Yan Xiao, Richard D. Urman, Yingzi Lin
Summary: The study proposed an objective method for pain level assessment using pupillary response and machine learning algorithms. By utilizing genetic algorithm to select optimal features subset for artificial neural network, the accuracy reached 81.0%, indicating promising application potential.
APPLIED INTELLIGENCE
(2022)
Article
Geosciences, Multidisciplinary
Paolo Billi, Velibor Spalevic
Summary: This study utilized suspended sediment yield field data measured by the national and regional hydrological services to investigate the factors influencing sediment yield in Italy. The research found a wide variation in sediment yield and attributed the marked decrease in sediment yield in Italy to factors such as reduced annual precipitation and forest expansion.
Article
Environmental Sciences
Shaheen Akhtar, Sk Md Equeenuddin, Priyadarsi D. Roy
Summary: The study analyzed the multi-element composition of rare earth elements (REE) in surface sediment from the Devi river estuary on the eastern coast of India. The sediments are primarily derived from the Eastern Ghat Group of rocks and are influenced by intrinsic physicochemical parameters, mainly salinity and redox conditions.
Article
Environmental Sciences
Arvind Yadav, Mohammad Kamrul Hasan, Devendra Joshi, Vinod Kumar, Azana Hafizah Mohd Aman, Hesham Alhumyani, Mohammed S. Alzaidi, Haripriya Mishra
Summary: This research aimed to develop a single hybrid artificial intelligence model for estimating the suspended sediment yield (SSY) in the Mahanadi River, India. The model combined data from 11-gauge stations into a hybrid generalized model using artificial neural network (ANN) and genetic algorithm (GA) optimization. The results showed that the proposed model outperformed the conventional approaches in terms of correlation and error, making it the most suitable model for estimating SSY in the MR Basin, particularly at the Tikarapara measuring station.
Article
Computer Science, Information Systems
Manoj Diwakar, Prabhishek Singh, Girija Rani Karetla, Preeti Narooka, Arvind Yadav, Rajesh Kumar Maurya, Reena Gupta, Jose Luis Arias-Gonzales, Mukund Pratap Singh, Dasharathraj K. Shetty, Rahul Paul, Nithesh Naik
Summary: Computed tomography (CT) plays a crucial role in medical imaging during the COVID-19 outbreak. This study proposes a novel denoising methodology for low-dose COVID-19 CT images using a convolution neural network (CNN) and batch normalization, achieving significant noise reduction and improved image accuracy.
Article
Energy & Fuels
Adel Oubelaid, Nabil Taib, Toufik Rekioua, Mohit Bajaj, Arvind Yadav, Mokhtar Shouran, Salah Kamel
Summary: A secure power management strategy has been developed for a fuel cell-supercapacitor hybrid electric vehicle to enhance reliability and comfort. The strategy detects failures, isolates the faulty source, and reconfigures the control scheme to ensure voltage stability and vehicle traction. The use of a particle swarm optimization algorithm enables simultaneous tuning of vehicle speed and torque controllers, minimizing torque and speed ripples.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Environmental Sciences
Shaheen Akhtar, Sk. Md. Equeenuddin
Summary: The major ions and nutrient chemistry of surface water from the Devi river estuary in eastern India were studied to understand the biogeochemical processes. The concentration of certain ions increased with higher salinity, while others decreased. The concentrations of major ions were highest in summer and lowest in monsoon season, except for NO3 and dissolved silica. The study also found that the nutrient stoichiometric ratios varied spatially and seasonally due to different geochemical processes in the freshwater and marine environment.
ENVIRONMENTAL EARTH SCIENCES
(2023)
Article
Environmental Sciences
Arvind Yadav, Premkumar Chithaluru, Aman Singh, Devendra Joshi, Dalia H. Elkamchouchi, Cristina Mazas Perez-Oleaga, Divya Anand
Summary: Estimation of suspended sediment yield (SSY) is essential for river basin management, and a developed artificial neural network (ANN) model showed superior accuracy and generalizability for SSY prediction in the Mahanadi River basin.
Article
Environmental Sciences
Arvind Yadav, Marwan Ali Albahar, Premkumar Chithaluru, Aman Singh, Abdullah Alammari, Gogulamudi Vijay Kumar, Yini Miro
Summary: The forecasting of sediment load (SL) is crucial for various purposes such as reservoir operations, water resource planning, and risk management. However, direct measurement of SL is challenging and expensive. In this study, a one-step-ahead SL forecasting model was developed for the Mahanadi River (MR) in India using artificial neural networks (ANN) and multi-objective genetic algorithm (ANN-MOGA) techniques. The performance of the proposed hybrid model was found to be significantly better compared to traditional regression models. The results suggest that the ANN-MOGA model is recommended for SL forecasting due to its superior performance and ease of application.
Article
Mathematics
Devendra Joshi, Marwan Ali Albahar, Premkumar Chithaluru, Aman Singh, Arvind Yadav, Yini Miro
Summary: This study utilizes a minimum-cut network flow algorithm to optimize open-pit mine design and production scheduling, increasing the chances of meeting predicted production targets by considering uncertainties.
Article
Mathematics
Arvind Yadav, Premkumar Chithaluru, Aman Singh, Marwan Ali Albahar, Anca Jurcut, Roberto Marcelo Alvarez, Ramesh Kumar Mojjada, Devendra Joshi
Summary: Rivers are important for ecosystems and society, and the forecasting of suspended sediment yield (SSY) is crucial for river basin systems. Traditional methods struggle with the complexity of SSY, but artificial intelligence techniques offer a promising solution. This study developed a hybrid intelligent model combining artificial neural networks (ANN) and genetic algorithms (GA) to forecast SSY in the Mahanadi River. The GA optimized the ANN parameters, and the model outperformed other models in terms of accuracy and simplicity.
Article
Mathematics
Devendra Joshi, Premkumar Chithaluru, Aman Singh, Arvind Yadav, Dalia H. Elkamchouchi, Jose Brenosa, Divya Anand
Summary: This study aims to determine the duration of providing necessary materials to a cement plant from a limestone mine, and explore the feasibility of combining limestone from a nearby mine with the study mine limestone. By calculating the maximum net profit and production sequencing, the issues were resolved. The findings show that the study mine can exclusively serve the cement plant for 15 years, but the addition of limestone from the neighboring mine significantly increases the mine's lifespan, and the proposed method generates higher profits compared to the current production planning formulation.
Review
Chemistry, Multidisciplinary
Abhishek Guru, Bhabendu Kumar Mohanta, Hitesh Mohapatra, Fadi Al-Turjman, Chadi Altrjman, Arvind Yadav
Summary: In the current era, blockchain has a wide range of consensus algorithms and employs encryption methods such as ECC and Merkle hash tree. Researchers also explore PKI cryptography to enhance blockchain data security. However, there is a need to address the security vulnerabilities, including attacks from ARP, DDoS, and sharding in permission-less blockchains. The presence of a byzantine adversary poses a serious threat. Therefore, it is important to conduct informative surveys and research to understand and mitigate these consensus protocol attacks on blockchain.
APPLIED SCIENCES-BASEL
(2023)
Article
Social Sciences, Interdisciplinary
Devendra Joshi, Premkumar Chithaluru, Aman Singh, Arvind Yadav, Dalia H. Elkamchouchi, Cristina Mazas Perez-Oleaga, Divya Anand
Summary: Traditional optimization of open pit mine design is essential in the mining industry, with geological uncertainty being the key factor. This study proposes a minimum cut algorithm to generate optimal pit limits and pushback designs, and applies Gaussian simulation-based smoothing spline technique to analyze an iron ore mining project in India, demonstrating higher metal production and net present value when uncertainty is considered.
Article
Medicine, General & Internal
Monika Nandkumar Chavan, Jayashree Ganu, Sangita Jadkar, Arvind Yadav, Anup N. Nillawar
Summary: The study revealed a significant decrease in NO levels and increase in MDA levels in the PTL group, along with decreases in TP, albumin, calcium, and inorganic phosphorus levels, suggesting these parameters may play a role in the diagnosis and prevention of preterm labor.
JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH
(2022)
Proceedings Paper
Energy & Fuels
Arvind Yadav, Mohit Bajaj, Francisco Jurado, Salah Kamel
Summary: This paper investigates the power conversion of quasi-z-source inverter and mitigates the effect of PV array output voltage variation through closed loop control, finding an effective method to maintain a consistent dc-link voltage and regulate the shoot-through duty ratio and modulation index.
2022 IEEE 4TH GLOBAL POWER, ENERGY AND COMMUNICATION CONFERENCE (IEEE GPECOM2022)
(2022)
Proceedings Paper
Energy & Fuels
Subhash Chandra, Arvind Yadav, Mohit Bajaj, Naveen Kumar Sharma, Francisco Jurado, Salah Kamel
Summary: This study compares the actual greenhouse gas emissions reduction of a 50kWp solar PV system with diesel generation. The results show that compared to diesel, the solar PV system reduces CO2 emissions by 78.4%, SO2 emissions by 80%, and NOx emissions by 97.67%.
2022 IEEE 4TH GLOBAL POWER, ENERGY AND COMMUNICATION CONFERENCE (IEEE GPECOM2022)
(2022)