Search

Your search keyword '"Khan, Shahnawaz"' showing total 484 results
Start Over Author "Khan, Shahnawaz"
484 results on '"Khan, Shahnawaz"'

1. A Blockchain and Artificial Intelligence based System for Halal Food Traceability

Author

Alourani, Abdulla and Khan, Shahnawaz

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence
Abstract

The demand of the halal food products is increasing rapidly around the world. The consumption of halal food product is just not among the Muslims but also among non-Muslims, due to the purity of the halal food products. However, there are several challenges that are faced by the halal food consumers. The challenges raise a doubt among the halal food consumers about the authenticity of the product being halal. Therefore, a solution that can address these issues and can establish trust between consumers and producers. Blockchain technology can provide a distributed ledger of an immutable record of the information. Artificial intelligence supports developing a solution for pattern identification. The proposed research utilizes blockchain an artificial intelligence-based system for developing a system that ensure the authenticity of the halal food products by providing the traceability related to all the operations and processes of the supply chain and sourcing the raw material. The proposed system has been tested with a local supermarket. The results and tests of the developed solution seemed effective and the testers expressed interest in real-world implementation of the proposed system., Comment: 13 pages

Published
2024

5. International Roughness Index Prediction Using Various Machine Learning Techniques on Flexible Pavements

Author

Pandit, Wasique Haleem, Sharma, Krishna Pal, Sharma, Nonita, Tomar, Priyanka, Khan, Shahnawaz, Chakrabarti, Amlan, Series Editor, Becker, Jürgen, Editorial Board Member, Hu, Yu-Chen, Editorial Board Member, Chattopadhyay, Anupam, Editorial Board Member, Tribedi, Gaurav, Editorial Board Member, Saha, Sriparna, Editorial Board Member, Goswami, Saptarsi, Editorial Board Member, Sharma, Nonita, editor, Mangla, Monika, editor, and Shinde, Subhash K., editor

Published
2024
Full Text
View/download PDF

18. Ethical Concerns in Artificial Intelligence (AI): The Role of RegTech and Islamic Finance

Author

Rabbani, Mustafa Raza, Sarea, Adel, Khan, Shahnawaz, Abdullah, Yomna, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, and Musleh Al-Sartawi, Abdalmuttaleb M. A., editor

Published
2022
Full Text
View/download PDF

25. Reddit social media text analysis for depression prediction: using logistic regression with enhanced term frequency-inverse document frequency features.

Author

Ayyalasomayajula, Madan Mohan Tito, Agarwal, Akshay, and Khan, Shahnawaz

Subjects
SOCIAL media, LINGUISTIC analysis, PROGRAMMING languages, MENTAL illness, PERSONALITY
Abstract

Language provides significant insights into an individual's emotional state, social status, and personality traits. This research aims to enhance depression detection through the analysis of linguistic features and various dataset attributes. The dataset, sourced from the social networking platform Reddit, comprises posts and comments from individuals diagnosed with depression. Logistic regression with term frequency-inverse document frequency (TFIDF) is employed as the primary model for text classification. To improve model performance, a novel feature--the average time interval between consecutive posts or comments--is introduced, contributing to a marginal but noteworthy improvement in accuracy. The proposed model demonstrates superior F1 scores compared to other models applied to the same dataset. Given the increasing recognition of mental health's significance, accurately diagnosing mental disorders is of paramount importance. This study underscores the potential of leveraging linguistic analysis and advanced machine learning techniques to identify depressive symptoms, thereby contributing to more effective mental health diagnostics and interventions. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

26. A Performance Evaluation of SO2 Gas and SO2/CO2 Gas Mixture as Potential SF 6 Gas Alternatives in Power Transmission and Distribution System

Author

Pandey, Akhilesh Kumar, Singh, Pushpendra, Singh, Jitendra Kumar, Khan, Shahnawaz, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Gupta, Om Hari, editor, and Sood, Vijay Kumar, editor

Published
2021
Full Text
View/download PDF

27. Intracranial Hemorrhage Detection Using Deep Convolutional Neural Network

Author

Thirunavukkarasu, K., Gupta, Anmol, Abimannan, Satheesh, Khan, Shahnawaz, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Saini, H. S., editor, Sayal, Rishi, editor, Govardhan, A., editor, and Buyya, Rajkumar, editor

Published
2021
Full Text
View/download PDF

37. Improving sustainability of precast concrete sandwich wall panels through stone waste aggregates and supplementary.

Author

Kumar, Pushpender, Kumar, Rajesh, Nighot, Nikhil Sanjay, Sharma, Surabhi, Rahman, Mohd Reyazur, Chidambaram, R. Siva, and Khan, Shahnawaz

Subjects
SANDWICH construction (Materials), LIGHTWEIGHT concrete, SELF-consolidating concrete, STONE, STEEL wastes, PRECAST concrete
Abstract

Precast concrete sandwich wall panels offer advantages such as design flexibility, ease of installation, cost-effectiveness, and energy efficiency due to the incorporated insulation layer, but regular concrete production has sustainability issues. This study aims to improve the sustainability of these panels by utilizing stone waste aggregates as a replacement for natural aggregates and supplementary cementitious materials as a partial replacement for cement. The panels were made with two concrete wythes reinforced with steel fibers and joined using basalt fiber-reinforced polymer (BFRP) connectors, with high-density expanded polystyrene (EPS) insulation (30 kg/m3) in between. Self-compacting concrete mixes with varying proportions of stone waste aggregates and supplementary cementitious materials were used. Full-scale wall panels were cast and subjected to flexural tests per ASTM standards, analyzing loaddisplacement curves, ultimate bearing capacity, and failure modes. The incorporation of steel fibers and stone waste aggregates resulted in substantial increases in failure load and flexural strength compared to controlled concrete panels, with the stone waste steel fiber panels exhibiting significantly higher maximum cracking loads and improved energy absorption and ductility. The inclusion of these sustainable materials, along with basalt fiber connectors and grooves in the EPS layer for mechanical interlock, prevented brittle failure modes and enhanced the composite action, leading to more ductile behavior under flexural loading. Utilizing sustainable materials like stone waste aggregates (100% replacement) and supplementary cementitious materials (30% replacement) in these panels can contribute to eco-friendly and efficient construction practices while maintaining adequate structural performance, paving the way for more sustainable building systems. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

43. Islamic FinTech

Author

Atif, Mohammad, primary, Hassan, M. Kabir, additional, Raza Rabbani, Mustafa, additional, and Khan, Shahnawaz, additional

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results