Article
Environmental Sciences
L. Xiao, M. Robinson, M. O'Connor
Summary: This paper presents three independently conducted paired-catchment forestry studies in the UK and Ireland, showing that removal of coniferous evergreen trees can increase dry weather baseflow but have complex effects on peak flows.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Geosciences, Multidisciplinary
Yunfan Zhang, Lei Cheng, Lu Zhang, Shujing Qin, Liu Liu, Pan Liu, Yanghe Liu
Summary: This study explores the impact of multiyear drought on the rainfall-runoff relationship and the validity of vegetation change estimation methods. The results show that the traditional paired-catchment method (PCM) is still reliable under non-stationary conditions, while other methods (TTM and SBM) overestimate the impact of vegetation change on runoff. A new framework is proposed to better separate the effects of vegetation change, climate variability, and multiyear drought on runoff changes.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Biochemical Research Methods
P. Kavitha, G. Ayyappan, Prabhu Jayagopal, Sandeep Kumar Mathivanan, Saurav Mallik, Amal Al-Rasheed, Mohammed S. Alqahtani, Ben Othman Soufiene
Summary: This research investigates the use of advanced machine learning methods to enhance the detection accuracy of Melanoma skin cancer, and the results suggest that the Color Layout Filter model provides the best overall performance.
BMC BIOINFORMATICS
(2023)
Article
Chemistry, Analytical
Umm e Laila, Khalid Mahboob, Abdul Wahid Khan, Faheem Khan, Whangbo Taekeun
Summary: Diabetes is a long-lasting disease that can cause various health issues. Timely disease prediction can save lives and support healthcare decision making. In this study, ensemble learning technique was used to predict diabetes, with Random Forest showing the best performance.
Article
Multidisciplinary Sciences
Ravi Dandu, M. Vinayaka Murthy, Y. B. Ravi Kumar
Summary: Melanoma is a type of skin cancer that occurs primarily on sun-exposed areas of the skin, but can also develop in areas with less sun exposure. This study focuses on the segmentation and classification of melanoma skin cancer and highlights the use of biomedical imaging and analysis to address these issues. The research has achieved promising results with the selected attributes and the color layout filter model.
Article
Engineering, Environmental
Kai Lun Yeoh, How Tion Puay, Rozi Abdullah, Teh Sabariah Abd Manan
Summary: Short-term streamflow prediction plays a crucial role in flood early warning and water resources management. Data-driven approaches have gained popularity in recent decades due to the digital revolution. In this study, multiple linear regression (MLR) and random forest (RF) models were developed and evaluated for short-term streamflow prediction using hydrological datasets from the Kulim River catchment in Malaysia. The results showed that including more precedent streamflow events as predictors improved the performance of data-driven models, especially in predicting peak streamflow during high-flow events. The RF model outperformed the MLR model in overall prediction accuracy but showed decreased accuracy in predicting the arrival time and magnitude of peak streamflow with increasing lead-time length.
WATER SCIENCE AND TECHNOLOGY
(2023)
Article
Water Resources
Mark B. Green, Scott W. Bailey, John L. Campbell, Kevin J. McGuire, Amey S. Bailey, Timothy J. Fahey, Nina Lany, David Zietlow
Summary: Small catchments have served as indicators of forest ecosystem responses to changes in air quality and climate. The Hubbard Brook Experimental Forest has been monitoring water budgets and controls since 1956, showing a 30% increase in evapotranspiration starting in 2010. This increase was primarily due to increasing ET, as indicated by PET and subsurface storage indicators.
HYDROLOGICAL PROCESSES
(2021)
Article
Biochemistry & Molecular Biology
Abdul Quadir Md, Sanika Kulkarni, Christy Jackson Joshua, Tejas Vaichole, Senthilkumar Mohan, Celestine Iwendi
Summary: There is a global increase in liver disease, which is difficult to detect until its late stage due to limited symptoms. This study proposes a novel architecture based on ensemble learning and enhanced preprocessing to predict liver disease using the Indian Liver Patient Dataset (ILPD). Six ensemble learning algorithms are compared, and data preprocessing methods such as data balancing, feature scaling, and feature selection are applied to improve accuracy.
Article
Water Resources
Robert Szczepanek
Summary: Streamflow forecasting in mountainous catchments is an important hydrological task. This study compares the performance of three gradient boosting models (XGBoost, LightGBM, and CatBoost) for daily streamflow forecasting in mountainous catchments. The results show that all three models achieve satisfactory forecast accuracy, with advantages of simplicity, fast computation, and robustness. These models allow for easy interpretation of predictor significance compared to deep machine learning models.
Article
Ecology
Alitzel Guzman-Hama, Lyssette Elena Munoz-Villers
Summary: This study examined the hydrological behavior of the Los Gavilanes river catchment, which supplies 90% of water to the city of Coatepec, Mexico. The study found high annual rainfall and streamflow, with a large proportion of baseflow contributing to the streamflow throughout the year. The forest cover in the catchment plays a key role in maintaining water sources for the region.
Article
Water Resources
Kenton L. Sena, Tanja N. Williamson, Christopher D. Barton
Summary: The University of Kentucky has conducted environmental experiments in Robinson Forest since 1923. Recently, data on precipitation and stream information from the forest have been compiled and made available for research use through a partnership with the U.S. Geological Survey. This data set serves as a valuable resource for studying water quality in minimally affected forests in the region.
HYDROLOGICAL PROCESSES
(2021)
Article
Water Resources
L'udmila Macejna, Andrea Zacharova, Hana Ollerova, Jana Skvareninova, Jaroslav Skvarenina
Summary: The study revealed high levels of mercury deposition in both a mining area and a protected primary forest, with throughfall being a significant contributor to THg input into forest soil. The forest ecosystem has the ability to capture atmospheric mercury and introduce new sources of mercury inputs into the soil through throughfall and litterfall.
JOURNAL OF HYDROLOGY AND HYDROMECHANICS
(2021)
Article
Computer Science, Artificial Intelligence
Parves Mohammed, S. Jabeen Begum
Summary: This paper presents an integrated model for heart disease diagnosis using advanced data mining techniques such as decision tree algorithm, naive Bayes classification, and ensemble classifiers. The model aims to enhance the classification accuracy of patient data and comparative analysis shows its effectiveness compared to existing models.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Raniel Gomes da Silva, Jailson de Oliveira Liberato Magalhaes, Iago Richard Rodrigues Silva, Roberta A. de A. Fagundes, Emerson A. de O. Lima, Alexandre M. Alexandre Maciel
Summary: This study analyzed applications using KNN and Random Forest techniques to predict application ratings, with Random Forest outperforming KNN.
IEEE LATIN AMERICA TRANSACTIONS
(2021)
Proceedings Paper
Automation & Control Systems
Akalbir Singh Chadha, Ajitkumar Shitole
Summary: This study attempts to predict the outcome of H-1B visa using machine learning models and create a fusion model to enhance the results. It also emphasizes on finding patterns between different features and the status of the case. The proposed model achieved high accuracy, F1-Score, and AUC.
2021 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL, CONTROL AND INSTRUMENTATION ENGINEERING (IEEE ICECIE'2021)
(2021)
Article
Water Resources
Sam G. Westerhof, Martijn J. Booij, Marcel C. J. Van den Berg, Ric J. M. Huting, Jord J. Warmink
Summary: This study aims to quantify the uncertainty of risk-based flood safety standards for a Dutch riverine case study and found that the Dutch flood safety standards are highly uncertain, especially in terms of damage functions and evacuation uncertainty.
INTERNATIONAL JOURNAL OF RIVER BASIN MANAGEMENT
(2023)
Article
Engineering, Environmental
Hakan Tongal, Martijn J. Booij
Summary: Streamflow simulation in a snow dominated basin is complex. Long short-term memory (LSTM) and artificial neural network (ANN) models were used for rainfall-runoff simulation in the Carson River basin in the US. The LSTM model outperformed the ANN model in representing flow dynamics, while the ANN model showed good performance in rainfall-runoff modeling. The proposed methodology enhances the learning capabilities of machine learning models in rainfall-runoff simulation.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Engineering, Environmental
Hamid Kazemi, Rabar H. Faraj, Wrya Abdullah, Shahriar Shahbazpanahi, Amir Mosavi
Summary: This research investigates the feasibility of using Medium-density fiberboard waste ash (MDFWA) in concrete as a substitute for cement. The results show that the compressive strength of the concrete is increased and the microstructure is improved when a certain proportion of MDFWA is used.
JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION
(2023)
Article
Green & Sustainable Science & Technology
Ishita Afreen Ahmed, Swapan Talukdar, Mohd Waseem Naikoo, Shahfahad, Ayesha Parvez, Swades Pal, Shakeel Ahmed, Atiqur Rahman, Abu Reza Md Towfiqul Islam, Amir H. Mosavi
Summary: This study aimed to identify the most suitable soil-water conservation areas in Guwahati through a coupling coordination mechanism. Principal component analysis and revised universal soil loss equation were used to determine the suitability models for current and future scenarios. The findings of this study are significant for environmental protection and land-water resource management in urban watersheds.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Mohd Sayeed Ul Hasan, Mufti Mohammad Saif, Nehal Ahmad, Abhishek Kumar Rai, Mohammad Amir Khan, Ali Aldrees, Wahaj Ahmad Khan, Mustafa K. A. Mohammed, Zaher Mundher Yaseen
Summary: This study evaluates the climatological conditions of terrestrial water storage anomalies (TWSAs) in India, one of the most populous countries in the world. The analysis of RL06 mascon data from the GRACE and GRACE-FO satellite missions reveals seasonal and interannual changes in terrestrial water storage. Statistical tests are conducted to determine the homogeneity of the data, and trends and magnitudes are analyzed using various methods. The findings suggest significant declining trends in certain regions, with implications for water resource management and long-term planning in India.
Article
Green & Sustainable Science & Technology
Iman Ahmadianfar, Bijay Halder, Salim Heddam, Leonardo Goliatt, Mou Leong Tan, Zulfaqar Sa'adi, Zainab Al-Khafaji, Raad Z. Homod, Tarik A. Rashid, Zaher Mundher Yaseen
Summary: This paper proposes an enhanced multioperator Runge-Kutta optimization (EMRUN) algorithm to accurately solve different types of water engineering problems. Experimental results show that EMRUN outperforms advanced optimization methods and has the ability to converge to the global solution up to 99.99%. The suggested method is deemed competitive and important in optimizing water engineering problems.
Article
Mathematics, Applied
Kamran Sabahi, Chunwei Zhang, Nasreen Kausar, Ardashir Mohammadzadeh, Dragan Pamucar, Amir H. Mosavi
Summary: This paper proposes a method for tuning the input-output scaling factor of an interval type-2 fuzzy PID controller using a multi-objective optimization technique. The suggested controller is applied to the frequency regulation problem in microgrids, considering the effect of variations in renewable energy schemes and minimizing overshoot and achieving the desired settling/rising time.
Article
Environmental Sciences
Elika Safaie Ghamsary, Mehrdad Karimimoshaver, Armin Akhavan, Zahra Afzali Goruh, Farshid Aram, Amir Mosavi
Summary: This study compared land use and accessibility as two main factors affecting the selection of appropriate locations for pocket parks. The results indicated that the effects of location greatly outweighed the effects of accessibility. It was also found that different types of commercial land use were more closely associated with people's attendance. These findings will assist urban planners and authorities in making better decisions regarding pocket park locations.
ENVIRONMENTAL AND SUSTAINABILITY INDICATORS
(2023)
Article
Green & Sustainable Science & Technology
Bijay Halder, Subhadip Barman, Papiya Banik, Puja Das, Jatisankar Bandyopadhyay, Fredolin Tangang, Shamsuddin Shahid, Chaitanya B. Pande, Baqer Al-Ramadan, Zaher Mundher Yaseen
Summary: Currently, natural hazards, such as floods, landslides, droughts, and deforestation, are amplified by climate change and human activities, leading to increased vulnerability, environmental degradation, and loss of life. This study used the Google Earth Engine platform and satellite data to analyze the extent of flood inundation and deforestation in Assam state, India in 2022. The findings revealed significant vegetation loss and flood inundation in several districts, emphasizing the importance of satellite-based information for effective hazard and disaster management strategies.
Article
Multidisciplinary Sciences
Sabaa Sattar, Yaser Alaiwi, Nabaa Sattar Radhi, Zainab Al-Khafaji, Osamah Al-Hashimi, Hassan Alzahrani, Zaher Mundher Yaseen
Summary: The study aims to reduce hot corrosion in steam turbines for Al-Mussaib thermal power stations. Experimental tests were conducted to identify the alloy composition and prepare samples with the same composition. Coating the samples with different ratios of TiO2 and SiO2 resulted in increased thickness, hardness, and reduced wear.
JOURNAL OF KING SAUD UNIVERSITY SCIENCE
(2023)
Article
Horticulture
Mohamed A. Sharaf-Eldin, Zaher Mundher Yaseen, Adel H. Elmetwalli, Salah Elsayed, Miklas Scholz, Zainab Al-Khafaji, Genesia F. Omar
Summary: Global warming is the most significant issue caused by climate change, having negative impacts on crop production. Modifying cultivation systems in arid regions is crucial to cope with heat stress. A study showed that using solar energy to operate fogging and evaporative cooling systems in shaded net tunnels successfully improved the microclimate and increased tomato yield.
Article
Energy & Fuels
Hamed Tabrizchi, Jafar Razmara, Amir Mosavi
Summary: The fast advancement of technology and developers' utilization of data centers have significantly increased energy usage in today's society. Thermal control is a critical issue in hyper-scale cloud data centers, and accurate estimation of host temperatures plays a crucial role in optimal resource management. Existing temperature estimating algorithms are ineffective, but this research proposes an efficient temperature prediction model using a combination of CNN and BiLSTM. The experiments demonstrate that the model successfully anticipates temperature with high accuracy, outperforming other methods.
Article
Horticulture
Mohamed A. Sharaf-Eldin, Salah Elsayed, Adel H. Elmetwalli, Zaher Mundher Yaseen, Farahat S. Moghanm, Mohssen Elbagory, Sahar El-Nahrawy, Alaa El-Dein Omara, Andrew N. Tyler, Osama Elsherbiny
Summary: Moisture and potassium deficiency are limiting variables for squash crop performance. Proximal hyperspectral remotely sensed data can be used to predict squash traits. The newly constructed three-band spectral index values based on VIS, NIR, and red-edge wavelengths were sensitive enough to measure the four tested parameters of squash.
Article
Computer Science, Information Systems
Muhammad Sheeraz, Muhammad Arsalan Paracha, Mansoor Ul Haque, Muhammad Hanif Durad, Syed Muhammad Mohsin, Shahab S. Band, Amir Mosavi
Summary: The internet's unprecedented advances have made it essential for every organization, but the rising popularity also brings security threats. To address this, organizations must continuously monitor their security status and protect their infrastructure using SIEM systems. This research paper proposes a comprehensive and modular architecture for SIEM systems, allowing developers to extend functionality without compromising performance, and aiding users in making better decisions.
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
(2023)
Article
Energy & Fuels
Raad Z. Homod, Hayder Ibrahim Mohammed, Aissa Abderrahmane, Omer A. Alawi, Osamah Ibrahim Khalaf, Jasim M. Mahdi, Kamel Guedri, Nabeel S. Dhaidan, A. S. Albahri, Abdellatif M. Sadeq, Zaher Mundher Yaseen
Summary: This study proposes a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adds a pre-cooling coil in the air handling unit (AHU) to alleviate the coupling issue in HVAC systems. The DCLTML algorithm shows promising results in controlling HVAC systems, with significant energy savings and improved environmental comfort.
