BIOCONVECTIVE MHD SUTTERBY HYBRID NANOFLUID FLOW WITH FUZZY VOLUME FRACTION OVER A CONVECTIVELY HEATED STRETCHING SHEET
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
FRAGMENTATION-ENABLED VM MIGRATION AND ENHANCED DATA SEARCHING IN BIG DATA SERVER ENVIRONMENT
The proposed research paper suggests a hybrid system to improve speed and data extraction in a large data server setup, but the focus will be on how to maximize the use of resources and provide actionable information on the unstructured data. The architecture also incorporates fragmentation-enabled virtual machine (VM) migration and high-end data s...
By G.S. Manjula, T. Meyyappan
EXPERIMENTAL INVESTIGATION ON MECHANICAL AND FLEXURAL BEHAVIOUR OF CONCRETE WITH FOUNDRY SAND AS PARTIAL FINE AGGREGATE REPLACEMENT
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
RULE-BASED ITERATIVE PREPROCESSING WITH DEEP SIAMESE GRU–BILSTM FOR EFFICIENT DOCUMENT STREAMING
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
A ROBUST FEATURE ENGINEERING ARCHITECTURE INCORPORATING HYBRID SAMPLING AND SEMANTIC-STRUCTURAL CODE AUGMENTATION
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
MITIGATING PROPAGATION FAULTS IN REAL-TIME CONTENT STREAMING FOR LOW-BANDWIDTH LEARNING ENVIRONMENTS
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
AI DRIVEN PREDICTIVE MAINTENANCE FRAMEWORK FOR MULTI-SENSOR INDUSTRIAL ROBOTS IN SMART MANUFACTURING
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
EXPLORING THE IMPACT OF INNOVATION ON INDIA'S SCIENTIFIC EQUIPMENT INDUSTRY THROUGH GLOBAL PARTNERSHIPS
The paper discusses the importance of innovation in revolutionizing the scientific equipment market in India with a lot of focus on how it has changed supplier firms and its end consumers particularly the pharmaceutical industry. It underscores the use of new technologies and models of business with regard to improved operational performance and ef...
By Dinakar Lingam, Syed Jaffer
INTERPRETABLE TRANSFORMER-BASED VIBRATION ANALYSIS FOR ANOMALY DETECTION IN INDUSTRIAL SYSTEMS
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
SOFT WEARABLE TRIBOELECTRIC SENSORS FOR CONTINUOUS CARDIOVASCULAR MONITORING AND ANOMALY PREDICTION
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...