Cited by Generating Headlines from Article Summaries Using Transformer Models

GTMicro—microservice identification approach based on deep NLP transformer model for greenfield developments DOI

Deepali Bajaj, Urmil Bharti, Isha Gupta

et al.

International Journal of Information Technology, Journal Year: 2024, Volume and Issue: 16(5), P. 2751 - 2761

Published: March 8, 2024

Language: Английский

Citations

Machine Learning based Phishing Website Detection DOI

Manav Kawale,

Bhavik Maru,

Sakshi Dagu

et al.

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Journal Year: 2024, Volume and Issue: unknown, P. 833 - 837

Published: Feb. 28, 2024

Phishing websites are those where a person can imitate legitimate website and trick an innocent user into thinking he is visiting while stealing sensitive information. Statistics from the Anti-Phishing Website Group (APWG) show that in second quarter of 2023, 1,286,208 phishing attacks were recorded. This was APWG's third-highest quarterly total ever. To address this issue, detection system made automatically detects notifies any website. The will be based on supervised learning wherein machine models such as k-nearest Neighbors, Logistic Regression, Support Vector Classifier, Naive Bayes, Decision Tree, Random Forest selected for training. found to have highest accuracy among them. As result, Randomforest chosen with 96.7 combination 32 features, which features like status bar customizing, forwarding, stats report, pop windows, server form handler uniquely identified implemented proposed improve overall model.

Language: Английский

Citations

A blockchain-based LLM-driven energy-efficient scheduling system towards distributed multi-agent manufacturing scenario of new energy vehicles within the circular economy DOI

Changchun Liu, Qingwei Nie

Computers & Industrial Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 110889 - 110889

Published: Jan. 1, 2025

Language: Английский

Citations

Mathematical Foundations and Applications of Generative AI Models DOI

Naru Venkata Pavan Saish,

J. Jayashree,

J. Vijayashree

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

Context-Aware Music Embedding in Silent Videos Leveraging Transformer Architectures: A Review DOI

Om Badhe,

Dr Kamal Sutaria,

Dr Vishal Shorthiya

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

Generative AI as a Tool for Personalized STEAM K-12 Education DOI

Abdesselam Bougdira,

Ghadah Al Murshidi

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 387 - 410

Published: March 13, 2025

This chapter delves into the transformative impact of generative AI on personalized STEAM education. It explores how technologies are integrated education to deliver learning experiences that cater individual student needs. The benefits highlighted, including enhanced engagement, improved outcomes, greater accessibility, and stimulation creativity innovation. also examines challenges deploying in education, such as resource limitations, data privacy concerns, algorithmic biases, need for educator training. Future trends explored, focusing advancements AI-driven virtual classrooms, adaptive technologies, ethical considerations. By harnessing AI, can be scaled a broader audience, delivering equitable, high-quality prepare students complexities contemporary society.

Language: Английский

Citations

Comparative study of low resource Digaru language using SMT and NMT DOI

Rushanti Kri, Koj Sambyo

International Journal of Information Technology, Journal Year: 2024, Volume and Issue: 16(4), P. 2015 - 2024

Published: March 7, 2024

Language: Английский

Citations

Interpretable Machine Learning Models for Credit Risk Assessment DOI

Md Al Mahedi Hassan,

Rakshit Govind T,

Usman Muhammad Mansur

et al.

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Journal Year: 2024, Volume and Issue: unknown, P. 361 - 365

Published: Feb. 28, 2024

For lending organizations, determining a borrower's creditworthiness is essential to their capacity repay loans. The prediction of credit scores using feature engineering and machine learning techniques the main emphasis this study. Using Kaggle Family Credit Default Risk dataset, AUC several models are compared. Modern techniques, including well-established methods like Random Forest Linear Support Vector Machines, can be effectively applied scoring. Ensemble models, such as LightGBM, offer advantages improved predictions increased stability, making them well-suited for specific use case. Combining from multiple often results in less noisy outcomes compared single model, outperforming other XGBoost, SVMs, logistic regression.

Language: Английский

Citations

Integrating Transformer-based Language Model for Drug Discovery DOI

Roshan R. Kotkondawar, Sanjay R. Sutar, Arvind W. Kiwelekar

et al.

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Journal Year: 2024, Volume and Issue: unknown, P. 1096 - 1101

Published: Feb. 28, 2024

The recent onset of the COVID-19 pandemic has made it crucial to accelerate creation potent drugs against new diseases for benefit global society. Traditional drug discovery methods require extensive time, skilled personnel, and huge financial resources testing molecules within chemical space. Computational Artificial Intelligence (AI) have elevated traditional framework higher levels in past decade. most development domain AI is dominated by Language Models (LM) which distinguish themselves with efficacy proficiency generating innovative ideas through assimilation knowledge from training datasets. LM can be effectively employed many activities like Drug-Target interaction prediction, Molecular similarity Compound property feeding an already known molecule a given target minimum reduce overall time project cost great extent. This work presents approach precise prediction molecular inhibit HIV replication leveraging BERT (Bidirectional Encoder Representations Transformers) language model standardized dataset based on SMILES (Simplified Input Line Entry System). Utilizing MoleculeNet-HIV dataset, integrated transformer-based architecture fine-tuned experiments, demonstrating superior accuracy generalization capabilities. proposed shows favorable outcomes capacity decrease both expenses procedure.

Language: Английский

Citations

Robotics and its Control Systems: Innovation Overview and Future Challenges DOI

Jasgurpreet Singh Chohan,

Gurinder Bawa,

Aqeel Hussain

et al.

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Journal Year: 2024, Volume and Issue: unknown, P. 524 - 528

Published: Feb. 28, 2024

The consequences of the recent breakthroughs in control systems and robotics span a wide range industries. study also discusses about possibilities challenges future research these areas, with focus on developing smarter, more resilient robotic systems. Research technological advancements over last several decades have allowed fields to make tremendous progress. This article aims give comprehensive review current developments fields. By outlining opportunities for research. Autonomous systems, sensing, acting are all parts technology. progress areas has creation ever complex robots capable carrying out activities that were hitherto considered impossible. There lot big need be overcome, like making it possible work alongside humans sure they safe when working unpredictable environments. demonstrates still long way go before reach their full potential open door intelligent, autonomous widely used across many different

Language: Английский

Citations