Predictive maintenance has become an important factor in improving the reliability and efficiency of industrial robots in the evolving environment of smart manufacturing. The proposed paper is a predictive maintenance framework based on AI to be implemented to multi-sensor industrial robots that will be used in a smart manufacturing setting. The po...

By Priya Vij, Ashu Nayak

This research investigates the Magnetohydrodynamic (MHD) flow of a Sutterby hybrid nanofluid over a convectively heated stretching sheet, specifically addressing the protection of human skin from solar thermal radiation. Utilizing Buongiorno’s nanomaterial model, the study evaluates the synergy of Cadmium Selenide (CdSe) and (𝐶6𝐻11𝑁𝑂4)𝑛&minus...

By P. Asaigeethan, M. Perumalsamy, M. Gnanakumar, J. Duraikannan, R. Saravanakumar, V. Subhashini, V. Jothi Francina, N. Deepa

The concept of monitoring conditions with the help of AI has become a significant aspect of Industry 4.0 that enhances machine reliability and provides predictive maintenance. However, the models of anomaly detection based on deep learning are not readily implemented because of their lack of interpretability. The article introduces a novel anomaly ...

By M. Mohamed Musthafa, A. Aafiya Thahaseen, R. Arulmozhi, S. Mohammed Ibrahim, S. Sangeetha, M. Rabiyathul Fathima, M. Gowthami, P. Esaiyazhini

The propagation faults are crippling the real-time streaming of content in learning environments with limited bandwidth, resulting in a small loss of packets that propagate into severe packet synchronization errors. The issue that is dealt with in this research is the preservation of continuity in streams through network conditions with throughput ...

By Ankita Sappa

The sophistication of the contemporary code has augmented defect prediction (SDP) with vital concerns like severe imbalance in classes, high redundancy of features and failure of conventional techniques to gain the rich semantic and structural context of a source code. The model suggested within the current paper is HDA-SE-GFF that has Semantic-Enr...

By P. Bhavani, N. Danapaquiame

Efficient document streaming requires robust preprocessing and semantic modeling to handle noise, redundancy, and morphological variations in large-scale text data. Existing stemming and document processing techniques often fail to preserve contextual relevance, leading to reduced classification and retrieval performance. In a bid to overcome this ...

By K. Ranjit Kumar, S. Thirumaran

Waste Foundry Sand (WFS) is the disposal that has been of great concern to the environment and this is as a result of high volumes generated in the process of metal casting. The building sector is developing eco-friendly alternatives to the natural aggregates in order to minimize environmental degradation and save natural resources. In this paper, ...

By John Sundarraj, Kesavan Govindaraj

Advancements in technology have increased demand for systems that continuously monitor the cardiovascular system in a non-invasive, energy-efficient way. Wearable sensors, in their current form, have many drawbacks: they require external power sources and are made of rigid components. This can impact the user experience, the system, the sensor's ab...

The speed of the electronic healthcare system, clinical information system, and biomedical sensing technologies has resulted in the creation of extremely huge high-dimensional and heterogeneous medical data. Such data have substantial potential to automatically diagnose diseases, but are difficult to use because they are feature redundant, nonlinea...

By Komal Saxena, M. Praneesh, S. Nancy Lima Christy, K. Nandhini, Tolib Rajabov, M. Nalini, Shalu Gupta

This paper discusses how data-based strategic and financial management can contribute to the competitive advantage of science and technology-based Small and Medium-sized Enterprises (SMEs). SMEs are challenged to use data to make better business decisions in an ever-dynamic and technology-driven market. This research combines data analytics into a ...

By Ravinder Sharma, Shyam Maurya