OTSU AND KAPUR ENTROPY BASED OPTIMAL MULTILEVEL IMAGE THRESHOLDING USING JAYA AND STOCHASTIC FRACTAL SEARCH ALGORITHMS FOR ENHANCED IMAGE SEGMENTATION
Image segmentation plays an important role in medical diagnosis and recognition, but the traditional methods of multilevel thresholding have exponential computation complexity with the number of thresholds. The study corresponds to the necessity to have a computationally effective parameter-free optimization to support fast clinical decision-making...
By S. Anbazhagan, M. Karthika, S. Ramkumar, P. Nammalvar, P. Anbarasan, V. Krishnakumar
DRIVING SCM AND HR TRANSFORMATION WITH AI THROUGH THE ROLE OF LEADERSHIP AND INNOVATION AS MEDIATORS
Due to the fast adoption of digital technologies and artificial intelligence (AI), the operations of enterprises, especially in the context of supply chain management (SCM) and human resource (HR) practises, are being fundamentally reorganised by allowing data-driven decision-making, automating processes, and enhancing agility to organisational cha...
By Sureshkumar Somanathan, R. Harsha, Sherzod Khalilov, Anvar Khudoyarov, Samariddin Makhmudov, Pallapati Ravi Kumar, Rajinder Kumar
SUPPLY CHAIN INTEGRATION AND CLOUD BASED OPERATIONS MANAGEMENT FOR RESILIENT SMART MANUFACTURING SYSTEMS
The research introduces Cloud-SCIM (Supply Chain Integration and Cloud-Based Operations Management to Resilient Smart Manufacturing) model, which aims to solve the problems of the modern manufacturing system. The model leverages cloud computing, IoT, and AI analytics to harmonize supply chain operations, boosting efficiency, flexibility, and resili...
By Lalit Sachdeva, Utkarsh Anand
DATA DRIVEN STRATEGIC AND FINANCIAL MANAGEMENT FOR ENHANCING COMPETITIVE ADVANTAGE IN SCIENCE AND TECHNOLOGY-BASED SMES
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
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 HYBRID MACHINE LEARNING AND DEEP LEARNING ARCHITECTURE FOR AUTOMATED MEDICAL DIAGNOSIS USING HIGH-DIMENSIONAL CLINICAL AND BIOMEDICAL DATA
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
GEOTECHNICAL APPROACHES FOR BUILDING EARTHQUAKE-RESILIENT INFRASTRUCTURE IN URBAN ENVIRONMENTS
The seismic nature of the soil in urban spheres is very susceptible to seismic ground failures caused by intricate soil conditions, extensive development, and outdated construction methods. However, structural solutions have always played the most important role in seismic design; growing evidence points to the importance of geotechnical engineerin...
By Jainish Roy, Rajesh Sehgal
AN ADVANCED MULTIMODAL AI FRAMEWORK FOR EARLY BRAIN STROKE DETECTION USING HYBRID FEATURE SELECTION, ENSEMBLE MODELS, AND REINFORCEMENT LEARNING
The detection of stroke is vital since any delay in diagnosis may lead to significant disability or the loss of life. The existing predictive models fail to capture stroke symptoms with accuracy because of low complexity, and the ability to be used in the real-time situation in the clinical setting. In the following paper, an AI-based system of ear...
By D. Ushasree, A.V. Praveen Krishna, Ch. Mallikarjuna Rao, D.V. Lalita Parameswari
PRECISION STOCK MARKET TREND ANALYSIS WITH HYBRID SMOOTH SVM AND WEIGHED VULTURE OPTIMIZATION
Accurate prediction of stock market trends remains a challenging task due to high volatility, non-linearity, and the dynamic nature of financial time series data. Conventional statistical and machine learning typically do not provide consistent performance due to the fixed hyperparameter settings and the inability to adapt to a shifting market situ...
By N. Subalakshmi, M. Jeyakarthic, V. Mohanaselvam
BUILDING INFORMATION MODELING AND ITS ROLE IN ADVANCING SUSTAINABLE CONSTRUCTION PRACTICES
The global construction industry accounts for approximately 37% of energy-related carbon dioxide emissions and nearly one-third of global waste, necessitating a rapid shift toward sustainable practices. Building Information Modeling (BIM) has become a transition catalyst, going beyond simple 3D visualization that has incorporated environmental inte...
By Deepti Patnaik, Rakshak Bharti