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
AGILE PROJECT MANAGEMENT STRATEGIES FOR OPTIMIZING CROSS-FUNCTIONAL OPERATIONS AND MARKET ADAPTATION IN HIGH-TECH SUPPLY CHAINS
An environment that is characterised by a high rate of technological change, short product life cycle, and fluctuating market demand demands a high level of technology, and therefore, the conventional project management approaches may no longer be effective. This paper analyzes how agile project management strategies can be used to support cross-fu...
By M.N. Prabadevi, P.A. Mary Auxilia, B. Jeyaprabha, N. Zeenath Zarina, M. Menaka
HYBRID SOLAR-WIND INTEGRATION USING AN ADAPTIVE NETWORK RECONFIGURATION METHOD AND CONTROLLING FOR UNCERTAINTY-AWARE SMART GRID BY OPTIMIZATION ALGORITHM
In this work, a new optimization approach for the exploitation and smooth integration of hybrid renewable sources (HRs), including PV solar/wind turbines in addition to a dynamic reconfiguration process of electricity distribution microgrids, is proposed. A crucial novelty of this work is the definition of a multi-scenario optimization framewo...
By Ghaith M. Fadhil, Saeid Ghassem Zadeh
DATA-DRIVEN SUPPLY CHAIN AND FINANCIAL MANAGEMENT FRAMEWORK FOR RISK OPTIMIZATION IN HIGH-TECHNOLOGY MANUFACTURING INDUSTRIES
In the dynamic environment of the high-technology production, the supply chain and financial risks management have become more important to maintain the continuity of the operations and profitability. Although a large amount of data is available, most industries continue to struggle to use this data to optimize all risks holistically. In this paper...
By Priya Sethuraman, M. Kalaivani, K. Latha, B. Kiruthiga
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
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...
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
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