Smart Book Hub: Empowering Literary Discovery Experience, Tailored Book Recommendations Using Mern and Lamp Stack
Abstract
Every new technology that comes out has some new features that meet the needs of users. A lot of innovations come and go from the market, but some have a big effect, make big improvements, and stay on top. The proposed online marketplace for used books and textbooks, which was made in PHP, includes user authentication, a strong system for uploading books with categories like business, sports, management, tourism, informatics, accounting, applied science, and more. It also includes important information like the ISBN, condition, price, and cover image. Users can browse the platform to see what books are available, add them to their shopping cart, and then go through a safe checkout process. The app has a user dashboard where you can manage your books, see your order history, and change your profile. To protect against any weaknesses, security procedures like input validation, using HTTPS, and storing passwords securely are put in place. You can add a payment gateway to the platform if you want to. In general, the system puts a responsive design first so that it works on all devices, and it comes with full documentation for future maintenance. We use the MERN (MongoDB, Express.js, React.js, Node.js) stack for temporary server functionality and the LAMP (Linux, Apache, MySQL, PHP) stack for home server operations. This gives us the best of both worlds.
References
L. Ang, C. Dubelaar, and B.-C. Lee, “To trust or not to trust? A model of internet trust from the customer’s point of view,” in Proceedings of the 14th Bled Electronic Commerce Conference, Bled, Slovenia, 2021.
S. Ba, “Establishing online trust through a community responsibility system,” Decision Support Systems, vol. 31, no. 3, pp. 323–336, 2021.
T. A. Hemphill, “Electronic commerce and consumer privacy: Establishing online trust in the US digital economy”, Business and Society Review, vol. 107, no. 2, pp. 221–239, 2022.
D. L. Hoffman, T. P. Novak, and M. Peralta, “Building consumer trust online,” Communications of the ACM, vol. 42, no. 4, pp. 80–85, 2023.
P. Pulivarthy, "Enhancing Data Integration in Oracle Databases: Leveraging Machine Learning for Automated Data Cleansing, Transformation, and Enrichment," International Journal of Holistic Management Perspectives, vol. 4, no. 4, pp. 1–18, Jun. 2023.
P. Pulivarthy, "Enhancing Database Query Efficiency: AI-Driven NLP Integration in Oracle," Transactions on Latest Trends in Artificial Intelligence, vol. 4, no. 4, pp. 1–25, Oct. 2023.
P. Pulivarthy, "Gen AI Impact on the Database Industry Innovations," International Journal of Advances in Engineering Research, vol. 28, no. 3, pp. 1–10, Sep. 2024.
M. Kommineni, "Develop New Techniques for Ensuring Fairness in Artificial Intelligence and ML Models to Promote Ethical and Unbiased Decision-Making," International Journal of Innovations in Applied Sciences & Engineering, vol. 10, Special Issue, pp. 13, Aug. 2024.
M. Kommineni, "Investigate Methods for Visualizing the Decision-Making Processes of a Complex AI System, Making Them More Understandable and Trustworthy in Financial Data Analysis," International Transactions in Artificial Intelligence, vol. 8, no. 8, pp. 1–21, Jan. 2024.
M. Kommineni, "Study High-Performance Computing Techniques for Optimizing and Accelerating AI Algorithms Using Quantum Computing and Specialized Hardware," International Journal of Innovations in Applied Sciences & Engineering, vol. 9, no. 1, pp. 48–59, Sep. 2023.
M. Kommineni, "Investigate Computational Intelligence Models Inspired by Natural Intelligence, Such as Evolutionary Algorithms and Artificial Neural Networks," Transactions on Latest Trends in Artificial Intelligence, vol. 4, no. 4, p. 30, Jun. 2023.
M. Kommineni, "Investigating High-Performance Computing Techniques for Optimizing and Accelerating AI Algorithms Using Quantum Computing and Specialized Hardware," International Journal of Innovations in Scientific Engineering, vol. 16, no. 1, pp. 66–80, Nov. 2022.
M. Kommineni, "Discover the Intersection Between AI and Robotics in Developing Autonomous Systems for Use in the Human World and Cloud Computing," International Numeric Journal of Machine Learning and Robots, vol. 6, no. 6, pp. 1–19, Sep. 2022.
T. K. Lakshmi and J. Dheeba, "Classification and Segmentation of Periodontal Cyst for Digital Dental Diagnosis Using Deep Learning," Computer Assisted Methods in Engineering and Science, vol. 30, no. 2, pp. 131-149, 2023.
T. K. Lakshmi and J. Dheeba, "Digital Decision Making in Dentistry: Analysis and Prediction of Periodontitis Using Machine Learning Approach," International Journal of Next-Generation Computing, vol. 13, no. 3, 2022.
T. K. Lakshmi and J. Dheeba, "Digitalization in Dental Problem Diagnosis, Prediction and Analysis: A Machine Learning Perspective of Periodontitis," International Journal of Recent Technology and Engineering, vol. 8, no. 5, pp. 67-74, 2020.
S. K. Suvvari, "Ensuring security and compliance in agile cloud infrastructure projects," Int. J. Comput. Eng., vol. 6, no. 4, pp. 54–73, 2024.
S. K. Suvvari, "Building an architectural runway: Emergent practices in agile methodologies," Int. J. Sci. Res. (IJSR), vol. 13, no. 9, pp. 140–144, 2024.
S. K. Suvvari and V. D. Saxena, "Innovative approaches to project scheduling: Techniques and tools," Innov. Res. Thoughts, vol. 10, no. 2, pp. 133–143, 2024.
S. K. Suvvari, "The role of leadership in agile transformation: A case study," J. Adv. Manag. Stud., vol. 1, no. 2, pp. 31–41, 2024.
B. Albadawi and I. Alzeer, "The virtual museum VM as a tool of learning science from the perspective of learning disabled (LD) children and their parents," presented at the Sharjah International Conference on Education in Post-COVID-19, 2022.
B. Albadawi, "Emphasize inclusive education and vocational training for disability in Palestine," Journal of Positive Psychology and Wellbeing, vol. 6, no. 1, pp. 1138-1156, 2022.
B. Albadawi, "Introducing, applying, and elaborating the policies of inclusive education in Palestine," Turkish Online Journal of Qualitative Inquiry, vol. 12, no. 9, 2021.
B. Albadawi, "The virtual museum VM as a tool of science and technology literacy in informal environment," M.S. thesis, Al-Quds Univ., 2011. [Online]. Available: https://dspace.alquds.edu/handle/20.500.12213/3246.
B. I. Albadawi and M. O. Salha, "Comparing leadership models at Al-Quds University according to gender in light of leadership theory with love," Specialusis Ugdymas, vol. 1, no. 43, pp. 1739-1748, 2022.
B. I. Albadawi and M. O. Salha, "Role of knowledge management in ensuring quality of higher education in Al-Quds University from the academic staff's perspective," The Arab Journal for Quality Assurance in Higher Education, vol. 14, no. 47, pp. 1-30, 2021.
B. I. Albadawi, "Leadership change for the development policy of inclusive education: Leadership theories and models," in Comparative Research on Diversity in Virtual Learning: Eastern vs. Western Perspectives, IGI Global, 2023, pp. 201-214.
B. I. Albadawi, "The virtual museum VM as a tool for learning science in informal environment," Education in the Knowledge Society (EKS), vol. 22, 2021.
S. Banala, “The Future of IT Operations: Harnessing Cloud Automation for Enhanced Efficiency and The Role of Generative AI Operational Excellence,” International Journal of Machine Learning and Artificial Intelligence, vol. 5, no. 5, pp. 1–15, Jul. 2024.
S. Banala, "DevOps Essentials: Key Practices for Continuous Integration and Continuous Delivery," International Numeric Journal of Machine Learning and Robots, vol. 8, no. 8, pp. 1-14, 2024.
M. R. M. Reethu, L. N. R. Mudunuri, and S. Banala, “Exploring the Big Five Personality Traits of Employees in Corporates,” FMDB Transactions on Sustainable Management Letters, vol. 2, no. 1, pp. 1–13, 2024.
S. Banala, “The Future of Site Reliability: Integrating Generative AI into SRE Practices,” FMDB Transactions on Sustainable Computer Letters, vol. 2, no. 1, pp. 14–25, 2024.
S. Banala, Identity and Access Management in the Cloud, International Journal of Innovations in Applied Sciences & Engineering, vol. 10, no. 1S, pp. 60–69, 2024.
S. Banala, "The FinOps Framework: Integrating Finance and Operations in the Cloud," International Journal of Advances in Engineering Research, vol. 26, no. 6, pp. 11–23, 2024.
S. Banala, "Artificial Creativity and Pioneering Intelligence: Harnessing Generative AI to Transform Cloud Operations and Environments," International Journal of Innovations in Applied Sciences and Engineering, vol. 8, no. 1, pp. 34–40, 2023.
S. Banala, Cloud Sentry: Innovations in Advanced Threat Detection for Comprehensive Cloud Security Management, International Journal of Innovations in Scientific Engineering, vol. 17, no. 1, pp. 24–35, 2023.
B. Senapati and B. S. Rawal, "Adopting a deep learning split-protocol based predictive maintenance management system for industrial manufacturing operations," in Big Data Intelligence and Computing. DataCom 2022, C. Hsu, M. Xu, H. Cao, H. Baghban, and A. B. M. Shawkat Ali, Eds., Lecture Notes in Computer Science, vol. 13864. Singapore: Springer, 2023, pp. 25–38.
B. Senapati and B. S. Rawal, "Quantum communication with RLP quantum resistant cryptography in industrial manufacturing," Cyber Security and Applications, vol. 1, 2023, Art. no. 100019.
D. Dayana, T. S. Shanthi, G. Wali, P. V. Pramila, T. Sumitha, and M. Sudhakar, “Enhancing usability and control in artificial intelligence of things environments (AIoT) through semantic web control models,” in Semantic Web Technologies and Applications in Artificial Intelligence of Things, F. Ortiz-Rodriguez, A. Leyva-Mederos, S. Tiwari, A. Hernandez-Quintana, and J. Martinez-Rodriguez, Eds., IGI Global, USA, 2024, pp. 186–206.
J. Tanwar, H. Sabrol, G. Wali, C. Bulla, R. K. Meenakshi, P. S. Tabeck, and B. Surjeet, “Integrating blockchain and deep learning for enhanced supply chain management in healthcare: A novel approach for Alzheimer’s and Parkinson’s disease prevention and control,” International Journal of Intelligent Systems and Applications in Engineering, vol. 12, no. 22s, pp. 524–539, 2024.
R. K. Meenakshi, R. S., G. Wali, C. Bulla, J. Tanwar, M. Rao, and B. Surjeet, “AI integrated approach for enhancing linguistic natural language processing (NLP) models for multilingual sentiment analysis,” Philological Investigations, vol. 23, no. 1, pp. 233–247, 2024.
G. Wali and C. Bulla, “Suspicious activity detection model in bank transactions using deep learning with fog computing infrastructure,” in Advances in Computer Science Research, 2024, pp. 292–302.
G. Wali, P. Sivathapandi, C. Bulla, and P. B. M. Ramakrishna, “Fog computing: Basics, key technologies, open issues, and future research directions,” African Journal of Biomedical Research, vol. 27, no. 9, pp. 748–770, 2024.
Wali, G., and C. Bulla, “Anomaly Detection in Fog Computing: State-of-the-Art Techniques, applications, Challenges, and Future Directions,” Library Progress International, vol. 44, no. 3, pp. 13967–13993, 2024.
P. P. Anand, U. K. Kanike, P. Paramasivan, S. S. Rajest, R. Regin, and S. S. Priscila, “Embracing Industry 5.0: Pioneering Next-Generation Technology for a Flourishing Human Experience and Societal Advancement,” FMDB Transactions on Sustainable Social Sciences Letters, vol.1, no. 1, pp. 43–55, 2023.
G. Gnanaguru, S. S. Priscila, M. Sakthivanitha, S. Radhakrishnan, S. S. Rajest, and S. Singh, “Thorough analysis of deep learning methods for diagnosis of COVID-19 CT images,” in Advances in Medical Technologies and Clinical Practice, IGI Global, pp. 46–65, 2024.
G. Gowthami and S. S. Priscila, “Tuna swarm optimisation-based feature selection and deep multimodal-sequential-hierarchical progressive network for network intrusion detection approach,” Int. J. Crit. Comput.-based Syst., vol. 10, no. 4, pp. 355–374, 2023.
A. J. Obaid, S. Suman Rajest, S. Silvia Priscila, T. Shynu, and S. A. Ettyem, “Dense convolution neural network for lung cancer classification and staging of the diseases using NSCLC images,” in Proceedings of Data Analytics and Management, Singapore; Singapore: Springer Nature, pp. 361–372, 2023.
S. S. Priscila and A. Jayanthiladevi, “A study on different hybrid deep learning approaches to forecast air pollution concentration of particulate matter,” in 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2023.
S. S. Priscila, S. S. Rajest, R. Regin, and T. Shynu, “Classification of Satellite Photographs Utilizing the K-Nearest Neighbor Algorithm,” Central Asian Journal of Mathematical Theory and Computer Sciences, vol. 4, no. 6, pp. 53–71, 2023.
S. S. Priscila and S. S. Rajest, “An Improvised Virtual Queue Algorithm to Manipulate the Congestion in High-Speed Network”,” Central Asian Journal of Medical and Natural Science, vol. 3, no. 6, pp. 343–360, 2022.
S. S. Priscila, S. S. Rajest, S. N. Tadiboina, R. Regin, and S. András, “Analysis of Machine Learning and Deep Learning Methods for Superstore Sales Prediction,” FMDB Transactions on Sustainable Computer Letters, vol. 1, no. 1, pp. 1–11, 2023.
R. Regin, Shynu, S. R. George, M. Bhattacharya, D. Datta, and S. S. Priscila, “Development of predictive model of diabetic using supervised machine learning classification algorithm of ensemble voting,” Int. J. Bioinform. Res. Appl., vol. 19, no. 3, 2023.
S. Silvia Priscila, S. Rajest, R. Regin, T. Shynu, and R. Steffi, “Classification of Satellite Photographs Utilizing the K-Nearest Neighbor Algorithm,” Central Asian Journal of Mathematical Theory and Computer Sciences, vol. 4, no. 6, pp. 53–71, 2023.
S. S. Rajest, S. Silvia Priscila, R. Regin, T. Shynu, and R. Steffi, “Application of Machine Learning to the Process of Crop Selection Based on Land Dataset,” International Journal on Orange Technologies, vol. 5, no. 6, pp. 91–112, 2023.
T. Shynu, A. J. Singh, B. Rajest, S. S. Regin, and R. Priscila, “Sustainable intelligent outbreak with self-directed learning system and feature extraction approach in technology,” International Journal of Intelligent Engineering Informatics, vol. 10, no. 6, pp.484-503, 2022.
S. S. Priscila, D. Celin Pappa, M. S. Banu, E. S. Soji, A. T. A. Christus, and V. S. Kumar, “Technological frontier on hybrid deep learning paradigm for global air quality intelligence,” in Cross-Industry AI Applications, IGI Global, pp. 144–162, 2024.
S. S. Priscila, E. S. Soji, N. Hossó, P. Paramasivan, and S. Suman Rajest, “Digital Realms and Mental Health: Examining the Influence of Online Learning Systems on Students,” FMDB Transactions on Sustainable Techno Learning, vol. 1, no. 3, pp. 156–164, 2023.
S. R. S. Steffi, R. Rajest, T. Shynu, and S. S. Priscila, “Analysis of an Interview Based on Emotion Detection Using Convolutional Neural Networks,” Central Asian Journal of Theoretical and Applied Science, vol. 4, no. 6, pp. 78–102, 2023.
Wali, G., and C. Bulla, “A Data Driven Risk Assessment in Fractional Investment in Commercial Real Estate using Deep Learning Model and Fog Computing Infrastructure,” Library Progress International, vol. 44, no. 3, pp. 4128–4141, 2024.
S. Temara, “Maximizing Penetration Testing Success with Effective Reconnaissance Techniques Using ChatGPT”, Asian Journal of Research in Computer Science, vol. 17, no. 5, pp. 19–29, 2024.
S. Temara, “The Ransomware Epidemic: Recent Cybersecurity Incidents Demystified”, Asian Journal of Advanced Research and Reports, vol. 18, no. 3, pp. 1–16, Feb. 2024.
S. Temara, “Harnessing the power of artificial intelligence to enhance next-generation cybersecurity,” World Journal of Advanced Research and Reviews, vol. 23, no. 2, pp. 797–811,2024.
B. Senapati et al., "Wrist crack classification using deep learning and X-ray imaging," in Proceedings of the Second International Conference on Advances in Computing Research (ACR’24), K. Daimi and A. Al Sadoon, Eds., Lecture Notes in Networks and Systems, vol. 956. Cham: Springer, 2024, pp. 72–85.
S. Banala, Exploring the Cloudscape - A Comprehensive Roadmap for Transforming IT Infrastructure from On-Premises to Cloud-Based Solutions, International Journal of Universal Science and Engineering, vol. 8, no. 1, pp. 35–44, 2022.
B. I. Albadawi, "Virtual reality in process for children with autism disability," in Comparative Research on Diversity in Virtual Learning: Eastern vs. Western Perspectives, IGI Global, 2023, pp. 88-104.
B. I. M. Albadawi, "An analytical study of the Palestinian inclusive education policy and its application in reality: Toward developing a visionary model in light of international criteria and local experiences," Ph.D. dissertation, Arab American Univ. Palestine, 2023.
M. O. Salha and B. I. Albadawi, "Organizational culture and knowledge management at Al-Quds University," Journal of Positive School Psychology, vol. 6, no. 3, pp. 7770-7781, 2022.
N. Dakhlallah and B. Albadawi, "The Illinois scale for examining psycho-linguistic abilities, learning disabilities, and verification of its validity and persistence in kindergartens in the suburbs of Jerusalem," 2021.
S. K. Suvvari, "The role of emotional intelligence in project leadership: A study," Innov. Res. Thoughts, vol. 10, no. 1, pp. 157–171, 2024.
S. K. Suvvari and V. D. Saxena, "Stakeholder management in projects: Strategies for effective communication," Innov. Res. Thoughts, vol. 9, no. 5, pp. 188–201, 2023.
T. K. Lakshmi and J. Dheeba, "Predictive Analysis of Periodontal Disease Progression Using Machine Learning: Enhancing Oral Health Assessment and Treatment Planning," International Journal of Intelligent Systems and Applications in Engineering, vol. 11, no. 10s, pp. 660–671, 2023.
M. Kommineni, "Explore Scalable and Cost-Effective AI Deployments, Including Distributed Training, Model Serving, and Real-Time Inference on Human Tasks," International Journal of Advances in Engineering Research, vol. 24, no. 1, pp. 07–27, Jul. 2022.
M. Kommineni, "Explore Knowledge Representation, Reasoning, and Planning Techniques for Building Robust and Efficient Intelligent Systems," International Journal of Inventions in Engineering & Science Technology, vol. 7, no. 2, pp. 105–114, 2021.
P. Pulivarthy, "Semiconductor Industry Innovations: Database Management in the Era of Wafer Manufacturing," FMDB Transactions on Sustainable Intelligent Networks, vol. 1, no. 1, pp. 15–26, Mar. 2024.
P. Pulivarthy, "Enhancing Dynamic Behaviour in Vehicular Ad Hoc Networks through Game Theory and Machine Learning for Reliable Routing," International Journal of Machine Learning and Artificial Intelligence, vol. 4, no. 4, pp. 1–13, Dec. 2023.
P. Pulivarthy, "Performance Tuning: AI Analyse Historical Performance Data, Identify Patterns, and Predict Future Resource Needs," International Journal of Innovations in Applied Sciences and Engineering, vol. 8, no. 2, pp. 139–155, Nov. 2022.
M. A. Yassin et al., “Advancing SDGs : Predicting Future Shifts in Saudi Arabia ’ s Terrestrial Water Storage Using Multi-Step-Ahead Machine Learning Based on GRACE Data,” 2024.
M. A. Yassin, A. G. Usman, S. I. Abba, D. U. Ozsahin, and I. H. Aljundi, “Intelligent learning algorithms integrated with feature engineering for sustainable groundwater salinization modelling: Eastern Province of Saudi Arabia,” Results Eng., vol. 20, p. 101434, 2023.
B. Senapati and B. S. Rawal, “Adopting a deep learning split-protocol based predictive maintenance management system for industrial manufacturing operations,” in Lecture Notes in Computer Science, Singapore: Springer Nature Singapore, pp. 22–39, 2023.
B. Senapati and B. S. Rawal, “Quantum communication with RLP quantum resistant cryptography in industrial manufacturing,” Cyber Security and Applications, vol. 1, no. 12, p. 100019, 2023.
B. Senapati et al., “Wrist crack classification using deep learning and X-ray imaging,” in Proceedings of the Second International Conference on Advances in Computing Research (ACR’24), Cham: Springer Nature Switzerland, pp. 60–69, 2024.
A. B. Naeem et al., “Heart disease detection using feature extraction and artificial neural networks: A sensor-based approach,” IEEE Access, vol. 12, no.3, pp. 37349–37362, 2024.
R. Tsarev et al., “Automatic generation of an algebraic expression for a Boolean function in the basis ∧, ∨, ¬,” in Data Analytics in System Engineering, Cham: Springer International Publishing, Switzerland, pp. 128–136, 2024.
R. Tsarev, B. Senapati, S. H. Alshahrani, A. Mirzagitova, S. Irgasheva, and J. Ascencio, “Evaluating the effectiveness of flipped classrooms using linear regression,” in Data Analytics in System Engineering, Cham: Springer International Publishing, Switzerland, pp. 418–427, 2024.
S. I. Abba, A. G. Usman, and S. IŞIK, “Simulation for response surface in the HPLC optimization method development using artificial intelligence models: A data-driven approach,” Chemom. Intell. Lab. Syst., vol. 201, no. April, 2020.
A. G. Usman et al., “Environmental modelling of CO concentration using AI-based approach supported with filters feature extraction: A direct and inverse chemometrics-based simulation,” Sustain. Chem. Environ., vol. 2, p. 100011, 2023.
Gbadamosi et al., “New-generation machine learning models as prediction tools for modeling interfacial tension of hydrogen-brine system,” Int. J. Hydrogen Energy, vol. 50, pp. 1326–1337, 2024.
Abdulazeez, S. I. Abba, J. Usman, A. G. Usman, and I. H. Aljundi, “Recovery of Brine Resources Through Crown-Passivated Graphene, Silicene, and Boron Nitride Nanosheets Based on Machine-Learning Structural Predictions,” ACS Appl. Nano Mater., 2023.
S. Alotaibi et al., “Sustainable Green Building Awareness: A Case Study of Kano Integrated with a Representative Comparison of Saudi Arabian Green Construction,” Buildings, vol. 13, no. 9, 2023, : 10.3390/buildings13092387.
K. Sharma and R. Tripathi, “4 Intuitionistic fuzzy trigonometric distance and similarity measure and their properties,” in Soft Computing, De Gruyter, Berlin, Germany, pp. 53–66, 2020.
K. Sharma, B. Singh, M. Anam, R. Regin, D. Athikesavan, and M. Kalyan Chakravarthi, “Applications of two separate methods to deal with a small dataset and a high risk of generalization,” in 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, 2021.
K. Sharma, B. Singh, M. Anam, K. O. Villalba-Condori, A. K. Gupta, and G. K. Ali, “Slotting learning rate in deep neural networks to build stronger models,” in 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, 2021.
Kaliyaperumal, A. Rahim, D. K. Sharma, R. Regin, S. Vashisht, and K. Phasinam, “Rainfall prediction using deep mining strategy for detection,” in 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, 2021.
Nallathambi, R. Ramar, D. A. Pustokhin, I. V. Pustokhina, D. K. Sharma, and S. Sengan, “Prediction of influencing atmospheric conditions for explosion Avoidance in fireworks manufacturing Industry-A network approach,” Environ. Pollut., vol. 304, no. 7, p. 119182, 2022.
S. I. Abba et al., “Integrated Modeling of Hybrid Nanofiltration/Reverse Osmosis Desalination Plant Using Deep Learning-Based Crow Search Optimization Algorithm,” Water (Switzerland), vol. 15, no. 19, 2023.
S. I. Abba, J. Usman, and I. Abdulazeez, “Enhancing Li + recovery in brine mining : integrating next-gen emotional AI and explainable ML to predict adsorption energy in crown ether-based hierarchical nanomaterials,” pp. 15129–15142, 2024.
Usman, S. I. Abba, N. Baig, N. Abu-Zahra, S. W. Hasan, and I. H. Aljundi, “Design and Machine Learning Prediction of In Situ Grown PDA-Stabilized MOF (UiO-66-NH2) Membrane for Low-Pressure Separation of Emulsified Oily Wastewater,” ACS Appl. Mater. Interfaces, Mar. 2024.
