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Eliminations of sulphur and fluoride from contaminated water by the applications of various types of biosorbents materials

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Water-Energy Nexus 2025年 8卷 73-92页

作者： Dey, Subhashish Veerendra, G.T.N. Phani Manoj, A.V. Anjaneya Babu, P.S.S. Jagadeesh, Gogineni Venkata Swarup Kumar, J.N.V.R. Civil Engineering Department Gudlavalleru Engineering College Andhra Pradesh Gudlavalleru India Mechanical Engineering Department Gudlavalleru Engineering College Andhra Pradesh Gudlavalleru India Computer Science Engineering Department Gitam University Andhra Pradesh Vishakapatnam India

Industrial and human waste releases sulphur and fluoride metals into the water sources, polluting them and endangering humans and the environment. There are various methods available for removals of the pollutants from the water. The membrane filtering and Chemical precipitation are more expensive, useless at low metal concentrations, and produce vast amounts of sludge and toxic by products that must be disposed of when treating big volumes of water. Alternative the wastewater treatment using the biosorption technology is environmentally friendly method. These methods are cheaper, more accessible, and reusable than traditional ones. Biomass can be treated physically and chemically treated before usage. The other parameters included the contact time, agitation speed, adsorbent dosage, pH, and temperature also affects the biosorption performances. After the removal of sulphur and fluorides from water, the bio-sorbent can be regenerated and reused to save money. Wastewater pollution removal using adsorption method is generally accepted. In the present scenario, the magnetic biosorbents and nanoparticles biosorbents are used for wastewater treatment have been developed. The magnetic biosorbents are attractive because to their various active sites, large specific surface area, easy separation, and lower cost. Chemical activations like acid, alkali, and salt improve biosorbents adsorption. In this observe, the various biosorbents have been developed for their better performance on defluoridation and desulphuridation. Due to different scientific barriers in the biosorption procedures those obstruct its commercialization;there has been a gradually rising consideration in this area of study. Of late more consideration is being paid in the formation of cost-effective adsorbents using various agricultural wastes, plant biomass, bacteria, algae and fungi. This review article highlights the applications of different biosorbents, sorption isotherm, and kinetics. In addition, the

关键词： Wastewater treatment

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Automatic segmentation, classification, and prediction of pelvic bone tumors using deep learning techniques

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Journal of engineering and Applied science 2024年第1期71卷 1-22页

作者： Shouman, Mona Rahouma, Kamel Hussein Hamed, Hesham F. A. Computer and System Engineering Department Faculty of Engineering Minia University Minia Egypt Faculty of Engineering Minia University Minia Egypt College of Artificial Intelligence Russian University Cairo Egypt

MRI and CT images are widely utilized for detecting tumors in internal organs. However, accurately distinguishing tumors using these images only, poses a challenge. This demands human expertise to effectively mark tumors in a given MRI or CT image, which is time-consuming. In this study, MONAI Label and MONAI Dynamic U-Net (DynU-Net) were used to segment tumors in any given 3D CT image of the pelvic bone, aiming to assist radiologists further. This method helps to run the model without needing a GPU which is better than traditional approaches. In addition, a convolutional neural network (CNN) was used to classify the tumors as benign or malignant and to predict three grades of tumors (low, medium, and high). The use of CNN in classification and prediction gives higher results than other studies. A dataset of 178 3D CT picture images was employed to feed the networks with the help of Adam optimizer and Categorical cross-entropy. We employ a set of 3D CT scans because of their greater contrast and spatial resolution which is better used for pelvic bone tumors. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) have been used to perform calculations in segmentation. The results show a DSC of 0.7660280 and an HD of 16.75480. A range of performance metrics, such as sensitivity, specification, and F1-score for classification and prediction methods, are used to evaluate the accuracy of the proposed system. The system has accuracy (99.4%) for classification and (97.8%) for prediction. These findings indicate that MONAI Label is effective for automatic segmentation of tumors in a given CT scan;with high accuracy. Moreover, CNN is useful for classification and prediction systems with high accuracy. However, achieving better results is possible with an abundance of training samples. © The Author(s) 2024.

关键词： computerized tomography

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Global Perspective of Natural Fibre Reinforced Composites: Properties, and Applications

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Journal of The Institution of Engineers (India): Series C 2024年第5期105卷 1335-1350页

作者： Tyagi, Ankit Punia, Upender Dadhich, Abhishek Meena, S.L. Department of Mechanical Engineering Poornima College of Engineering Rajasthan Jaipur India Department of Mechanical Engineering DCRUST Haryana Murthal Sonipat India Department of Computer Science Engineering Poornima Institute of Engineering and Technology Rajasthan Jaipur India Department of Mechanical Engineering RTU Kota Rajasthan Kota India

The primary promoters for the advancement of NFRCs (Natural fibre reinforced composites) in many industries are the imperative need to decrease energy consumption and mitigate environmental consequences. Natural fibres provide several advantages in terms of affordability, biodegradability, lightweight nature, superior life-cycle performance, and good mechanical qualities. The present paper initially provides an overview of the different types, benefits and challenges of NFRCs with a brief description. Then after, the article briefly discussed the about DMA (Dynamic mechanical analysis), mechanical behavior, as well as thermal behavior characteristic of NFRCs. Finally, we shortly introduce natural fibres applications in the field of construction work, structures and buildings, automobiles industry, biomedical and pharmaceutical industries, furniture and architecture and in various other industries. Nonetheless, the intrinsic characteristics of natural fibres derived from plants have posed difficulties in the advancement and utilization of NFRCs. These challenges include inconsistent fibre quality, inadequate thermal stability, restricted mechanical properties, susceptibility to water absorption, and a tendency to clump together. © The Institution of Engineers (India) 2024.

关键词： Natural fibers

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Enhancing mechanical durability and flame retardancy in Bamboo-Polypropylene composites with nAl2O3 fillers

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Interactions 2024年第1期245卷 1-17页

作者： Sahare, Shilpa B. Seenivasan, S. Satishkumar, P. Lajurkar, Sangita Pravin Saminathan, Rajasekaran Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Maharashtra Nagpur India Department of Mechanical Engineering Rathinam Technical Campus Tamilnadu Coimbatore India Department of Civil Engineering Acharya Shrimannarayan Polytechnic Maharashtra Pipri Wardha India Department of Mechanical Engineering College of Engineering and Computer Science Jazan University Jazan Saudi Arabia

Natural fiber-based nanocomposite is an innovative material created recently, widely used in various industries for its exceptional strength-to-weight ratio and lightweight properties. The study examined the impact of titanium nanoparticles on the mechanical properties, moisture absorption, flammability, and dynamic mechanical characteristics of polypropylene (PP)/Bamboo fiber. Composite materials consisting of PP, Bamboo fiber, and alumina were manufactured using injection molding. The hybrids’ elongation at break (1.70%), tensile strength (TS), and modulus of elasticity (2124 MPa, 43.1 MPa, and 9%, respectively), were enhanced by adding 9% nano aluminum oxide (nAl2O3) nanoparticles to the mix. The clean PP/Bamboo had a modulus of 2189 MPa and bending strength of 39.6 MPa. The PP/Bamboo/Al2O3 composite material showed a modulus of 2805 MPa and a bending strength of 56.7 MPa, an increase of 28.46%. Raised nanoparticle concentration resulted in a significant reduction in water absorption (9.1%) and swelling thickness (2.03%). The n-Al2O3 was incorporated into composites to improve their dynamic mechanical properties, resulting in a loss modulus of 5.02 MPa and a storage modulus of 12.92 MPa. Additionally, it enhanced fire resistance, leading to a combustion rate of 18 mm min-1 and a char residue of 30%. The endurance of the char barrier is greatly affected by the chemical composition and distribution pattern of the mixture. Char shields with increased nAl2O3 content are designed to resist burning and require greater temperatures to break down. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Tensile strength

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An efficient integrity based multi-user blockchain framework for heterogeneous supply chain management applications

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International Journal of computers and Applications 2023年第4期45卷 337-351页

作者： Karumanchi, Mani Deep Sheeba, J.I. Devaneyan, S. Pradeep Department of Computer Science and Engineering Bapatla Engineering College Bapatla India Department of Computer Science and Engineering Puducherry Technological University Puducherry India Department of Mechanical Engineering Sri Venkateshwaraa College of Engineering and Technology Puducherry India

Most of the traditional cloud-based applications are insecure and difficult to compute the data integrity with variable hash size on heterogeneous supply chain datasets. Also, cloud storage systems are independent of integrity computational and data security due to structured data and computational memory. As the size of the cloud data files is increasing in the public and private cloud servers, it is difficult to provide strong data security due to file format and high dimensionality. The computational time and storage space of the conventional attribute-based encryption and decryption models are high during the data integrity verification in the traditional blockchain frameworks. This paper implements a hybrid variable size data integrity algorithm on the heterogeneous cloud supply chain data files for the strong data encryption and decryption process. This work implements an optimized blockchain framework using the advanced heterogeneous integrity computation approach and integrity policy-based attribute encryption and decryption approach for better cloud data security. Experimental results proved that the proposed integrity-based encryption model has better efficiency than the traditional integrity-based encryption frameworks on cloud heterogeneous data types. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Blockchain

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Revolutionizing Healthcare: AI-Powered Solutions, Technological Integration for Accessible and Effective Medical Service

Revolutionizing Healthcare: AI-Powered Solutions, Technologi...

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2024 International Conference on Advances in Computing Research on science engineering and Technology, ACROSET 2024

作者： Shaikh, Almas Jafar Takbhate, Sakshi Bharat Gawai, Shailesh Limbore, Altaf Mainoddin Patil, Vaidehi Avinash JSPM's Rajarshi Shahu College of Engineering Department of Computer Science and Business System Tathawade India

ISBN: (纸本)9798350388800

The main characteristics of the healthcare platform that this study suggests for rural areas are User ID or image-based recognition, Options for consultation, Disease Prediction, Integration with Aasha Workers, Technical considerations and Project Objectives. User ID or image-based recognition are used for a secure login process. Options for Consultation is to select from medical chatbots or video consultations with physicians. Disease Prediction is to make recommendations for possible disease diagnosis, real-time image analysis (such as reviewing uploaded photos) and machine learning are used. Risk assessment: Machine learning algorithms evaluate risks for different health disorders based on user-provided data (age, medical history, etc.). Integration with Aasha Workers is a platform establishes a connection with Aasha workers, who can provide medication as required following consultations. Technical considerations are a platform can be built using web development frameworks such as Flask or Django. Strong privacy and data security protocols are necessary. Project Objectives: Expand access to healthcare in remote locations. Give patients knowledge and tools for self-evaluation to empower them. Improve interaction and cooperation between medical professionals, patients, and Asha employees. © 2024 IEEE.

关键词： Adversarial machine learning

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Unlocking new possibilities in ionic thermoelectric materials: a machine learning perspective

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National science Review 2025年第1期12卷 195-206页

作者： Yidan Wu Dongxing Song Meng An Cheng Chi Chunyu Zhao Bing Yao Weigang Ma Xing Zhang Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Engineering Mechanics Tsinghua University Key Laboratory of Process Heat Transfer and Energy Saving of Henan Province School of Mechanics and Safety Engineering Zhengzhou University College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Key Laboratory of Power Station Energy Transfer Conversion and System of Ministry of Education School of Energy Power and Mechanical Engineering North China Electric Power University School of Materials and Chemical Engineering Xuzhou University of Technology

The high thermopower of ionic thermoelectric(i-TE) materials holds promise for miniaturized waste-heat recovery devices and thermal sensors. However, progress is hampered by laborious trial-and-error experimentations, which lack theoretical underpinning. Herein, by introducing the simplified molecular-input line-entry system, we have addressed the challenge posed by the inconsistency of i-TE material types, and present a machine learning model that evaluates the Seebeck coefficient with an R2of0.98 on the test dataset. Using this tool, we experimentally identify a waterborne polyurethane/potassium iodide ionogel with a Seebeck coefficient of 41.39 m V/K. Furthermore, interpretable analysis reveals that the number of rotatable bonds and the octanol-water partition coefficient of ions negatively affect Seebeck coefficients, which is corroborated by molecular dynamics simulations. This machine learning-assisted framework represents a pioneering effort in the i-TE field, offering significant promise for accelerating the discovery and development of high-performance i-TE materials.

关键词： thermoelectric conversion ionic thermoelectric materials machine learning interpretable analysis

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Fuzzy Adaptive State Estimation of Distributed Drive Electric Vehicles with Random Missing Measurements and Unknown Process Noise

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Chinese Journal of mechanical engineering 2024年第5期37卷 543-554页

作者： Zhiguo Zhang Guodong Yin Chao Huang Jingyu Hu Xing Xu Chengyue Jiang Yan Wang School of Mechanical Engineering Southeast UniversityNanjing 211189China Department of Industrial and System Engineering The Hong Kong Polytechnical UniversityHong KongChina Department of Automotive Engineering Research Institute Jiangsu UniversityZhenjiang 225009China College of Vehicle Engineering Chongqing University of TechnologyChongqing 400054China

Accurate estimation of sideslip angle and vehicle velocity is crucial for effective control of distributed drive electric ***,as these states are not directly measured,Kalman-based approaches utilizing in-vehicle sensors have been developed to estimate ***,existing methods tend to ignore the impact of data loss on estimation ***,the process noise,which changes dynamically due to varying driving conditions,is not adequately *** response to these constraints,we propose a novel method called the fuzzy adaptive fault-tolerant extended Kalman filter(FAFTEKF).Initially,a fault-tolerant EKF is devised to handle missing ***,a fuzzy logic system that dynamically updates the process noise matrix,is built to improve estimation accuracy under different driving *** experimental results validate the superiority of the FAFTEKF over the traditional EKF across various scenarios with different degrees of data loss.

关键词： Distributed drive electric vehicles State estimation Fault-tolerant EKF Fuzzy logic system

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Strength-ductility synergy in Mg-Gd-Y-Zr alloys via texture engineering in bi-directional forging

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Journal of Magnesium and Alloys 2024年第11期12卷 4709-4721页

作者： Jingli Li Quanfeng Han Xiuzhu Han Xin Yi Institute for Advanced Materials North China Electric Power UniversityBeijing 102206China Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China Beijing Institute of Spacecraft System Engineering Beijing 100094China

In this work,we successfully fabricate an ultra-high strength Mg-11Gd-3Y-0.5Zr alloy with ultimate tensile strength of 523 MPa and enhanced ductility via cost-effective bi-directional forging (BDF) and subsequent annealing heat *** elucidate the role of BDF and gain a fundamental understanding of the remarkable simultaneous increase of strength and ductility,systematic microstructure characterization and analysis are *** is revealed that the double-peak basal texture,with basal poles located at the center of two mutually perpendicular forging directions,serves as an essential factor for the strength-ductility synergy of the Mg-11Gd-3Y-0.5Zr alloy processed with *** of the double-peak basal texture in overcoming the strength-ductility trade-off include promoting non-basal slip,increasing ductility,and enlarging the Hall-Petch effect along the sample elongation direction while reducing the extent of anisotropy in critical resolved shear stresses of different slip *** study demonstrates that texture engineering is a powerful strategy to control magnesium alloy performance and BDF is a promising processing technique for enhancing mechanical properties of magnesium alloys.

关键词： Bi-directional forging(BDF) Magnesium alloys High strength Texture Anisotropy

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