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Article
Optics
D. Venu et al.
Summary: The latest advancements in fiber optic communication technology have attracted significant attention due to the benefits of high data rate, acceptable cost, bandwidth, and low attenuation. While fiber optic networks are commonly used for data transfer, security remains a challenge. This paper introduces a new Low Complexity Compression Then Encryption using Optimal Homomorphic Encryption (LCCE-OHE) technique for secure fiber optic communication, which achieves efficient and secure data transmission through compression and encryption processes.
Review
Environmental Sciences
Nawal Taoufik et al.
Summary: In recent years, significant progress has been made in the application of machine learning in chemical engineering, enhancing prediction quality for complex variables and addressing various challenges. Research in this field aims to analyze physicochemical processes utilizing machine learning for organic and inorganic pollutant removal, while also highlighting future research needs.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Chemistry, Multidisciplinary
Mohammed Al-Yaari et al.
Summary: In this study, a new artificial neural network (ANN) model was developed using different architectures of an adaptive network-based fuzzy inference system (ANFIS) to predict the adsorption efficiency of arsenate (As(III)) from polluted water. The results showed that the ANFIS model had high prediction accuracy and identified the dominant factors affecting the adsorption process efficiency.
APPLIED SCIENCES-BASEL
(2022)
Article
Environmental Sciences
Xiaolei Zheng et al.
Summary: This study introduces a robust artificial intelligent model for predicting heavy metal removal efficiency in biochar systems. Through evaluating 22 types of biomass feedstock in 353 experiments, a highly accurate artificial neural network model was developed.
Article
Environmental Sciences
P. Asha et al.
Summary: In the past decades, rapid industrial and technological development has led to unsustainable utilization of non-renewable resources, prompting significant attention to the impact of toxic chemicals on human health in the environmental toxicology field. As a result, there is a need for an automated air pollution monitoring system to improve human health.
ENVIRONMENTAL RESEARCH
(2022)
Article
Environmental Sciences
Ying Zhao et al.
Summary: In this study, the Kriging and polyparameter linear free energy relationship model were used to predict the adsorption capacity of organic pollutants by biochar and resin. The results showed that the Kriging-LFER model had better accuracy and predictive performance compared to the published NN-LFER model. Local sensitivity analysis and uncertainty analysis methods were also applied to evaluate the influence of variables and analyze data uncertainty. The study highlights the significance of the Kriging-LFER model in understanding parameter importance, reducing experimental efforts, and evaluating pollutant fate.
ENVIRONMENTAL RESEARCH
(2022)
Article
Engineering, Chemical
Muhammad Raziq Rahimi Kooh et al.
Summary: This study models the adsorption of methylene blue dye using the aquatic plant Azolla pinnata and applies various supervised machine learning algorithms to accurately predict the adsorption capacity under different experimental conditions. The SVR-RBF algorithm performs the best, achieving the highest correlation coefficient and the lowest error.
JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS
(2022)
Article
Engineering, Multidisciplinary
Hu Hao et al.
Summary: This paper proposes a fault diagnosis method for planetary gearbox based on deep belief networks, which improves the diagnostic accuracy through automatic feature extraction and fault recognition.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2022)
Article
Optics
Harinder Singh et al.
Summary: This paper presents a novel AI-based cognitive QoT prediction (AI-CQoT) model for optical communication networks. The proposed model aims to predict the QoT for the quality of service (QoS) link setup using AI techniques and synthetic data generation based on transmission equations. The LW-ELM model is used for the prediction process, and the parameters are optimized using the SSO algorithm to improve predictive performance.
Article
Mathematics
Qingxin Liu et al.
Summary: Image segmentation is a crucial stage in image processing, and the multi-level thresholding technique is a popular and efficient method. However, existing meta-heuristic algorithms have some issues in determining the threshold values. Therefore, this study proposes a modified remora optimization algorithm (MROA) to address global optimization and image segmentation tasks.
Article
Engineering, Environmental
Keivan Rahmani et al.
Summary: Determining the long-term performance of adsorbents is crucial for air treatment system design. Machine learning algorithms, such as XGBoost and neural network, were used to predict cyclic heel buildup on activated carbons. The neural network algorithm showed better performance in predicting heel buildup compared to XGBoost. Partial dependency plots were generated to analyze the interaction between heel buildup and different factors. These ML-based prediction methods can help optimize adsorption/desorption conditions and screen efficient adsorbents.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Environmental Sciences
Ali El Hanandeh et al.
Summary: Biochar is effective for removing heavy metals from wastewater, with operational conditions affecting the treatment process. This study introduces a multi-input multi-output model to predict heavy metals adsorption capacity of biochar in single and multi-solute systems, using machine learning models. Results show highly accurate predictions, with the generalized regression network model providing the best match to experimental data.
ENVIRONMENTAL RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Jie Li et al.
Summary: Hydrothermal carbonization is a promising technology for recovering valuable resources from high-moisture wastes, while machine learning tools can accelerate experiments and improve product preparation efficiency.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Environmental
Hongrui Yang et al.
Summary: The research team developed machine learning models to predict the adsorption of six heavy metals in different soils and found that the gradient boosting decision tree model performed the best overall. By analyzing feature importance and effects, they successfully built six independent models, improving the model performance.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Heming Jia et al.
Summary: The Remora Optimization Algorithm (ROA) is proposed in this paper, inspired by the parasitic behavior of remora. ROA mimics the behavior of remora by updating different hosts globally or locally, providing a new idea for memetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Environmental Sciences
Bo Ke et al.
Summary: Heavy metals in water and wastewater are a significant environmental issue affecting human health. The use of biochar systems can help remove heavy metals, but the efficiency depends on biochar characteristics, metal sources, and environmental conditions. Artificial intelligence models can accurately predict heavy metal sorption onto biochar.
Article
Environmental Sciences
Divya Lakshmi et al.
Summary: The use of biochar for heavy metal removal has gained traction in recent years due to its cost-effectiveness and efficiency compared to conventional methods. Research shows that utilizing biochar for the removal of harmful heavy metals is an effective method, with the type and preparation process of biochar also affecting the removal efficiency.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Environmental Sciences
Bo Ke et al.
Summary: The FCM-BPNN model showed promising results in predicting the sorption efficiency of heavy metals onto biochar, outperforming the BPNN model alone. The FCM algorithm significantly improved the performance of the BPNN model in this study.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Environmental Sciences
Noor Hafsa et al.
Article
Engineering, Environmental
Xinzhe Zhu et al.
JOURNAL OF HAZARDOUS MATERIALS
(2019)
Article
Engineering, Chemical
Mingrun Li et al.
SEPARATION AND PURIFICATION TECHNOLOGY
(2019)
