ANALYZING AND PRIORITIZING HEALTHCARE SERVICE PERFORMANCE IN HOSPITALS USING SERQUAL MODEL
Health care is essential for both public welfare and national growth. Nevertheless, the number of hospitals has increased; patients still face many problems highlighting the need for better healthcare services. The Present study aims to analyze the quality of healthcare services in view of patients’ fulfillment and identify their requirements...
By Abdul Z. Hameed, R. Balamurugan, Ali Rizwan, Muhammad Atif Shahzad
NONLINEAR STATIC ANALYSIS OF RCC SPACE FRAME ON SLOPING GROUNDS INCORPORATING SSI
This paper presents a comprehensive investigation into the seismic performance of a G+5 reinforced concrete spaceframe subjected to pushover analysis. The analysis incorporates the critical influence of soil-structure interaction on varying slope inclinations. A nonlinear static pushover method is utilized to examine the lateral loading streng...
By Tushar Golait, Neeraj Tiwari, Manjeet Singh Hora
BATTERY MANAGEMENT SYSTEM FOR ELECTRIC VEHICLE USING ARTIFICIAL INTELLIGENCE AND IOT TECHNOLOGY
With the rapid advancement in electric vehicle (EV) technology, efficient battery management has become crucial for enhancing performance, safety, and longevity. This research integrates Internet of Things (IoT) and artificial intelligence (AI) technology to provide a revolutionary solution to battery management in electric vehicles. Our suggested ...
By R. Ramya, V. Ramya, J. Jaganpradeep, M. Balamurugan, P. Murugesan
EXPLORING ABG IMBALANCES IN ICU PATIENTS USING MACHINE LEARNING SUPERVISED ALGORITHMS
Arterial Blood Gas (ABG) analysis is an important diagnostic tool in intensive care unit (ICU) settings that provides valuable information about the patient's respiratory and metabolic status. However, in the absence of predictive information, when testing is over-utilized or not planned, it can cause discomfort to the patient, costs to the healthc...
By S. Ramadoss, A. Kumaravel
A COMPARATIVE STRATIFICATION OF FISH SPECIES USING TRANSFER LEARNING ON PRE-TRAINED DEEP LEARNING NETWORKS JUXTAPOSED WITH SHUFFLERES – A HYBRID DEEP NETWORK CLASSIFIER
The marine ecoculture is an evolving realm that necessitates thorough scrutiny of the diverse species it comprises, along with the explicit identification of the species classes that form, to be crucial for aquaculture and the ecological conservation of fish diversity. The stratification through image classification is a well-studied area of resear...
By R.P. Selvam, R. Devi
ENTREPRENEURIAL MARKETING AND INNOVATION CAPABILITIES IN HIGH TECHNOLOGY STARTUPS IN EMERGING ECONOMIES
Emerging economies have a dynamic and challenging business environment, which requires entrepreneurial marketing and innovation capabilities of the high-tech startups. Such startups are usually faced with issues of lack of resources, regulation and lack of proper infrastructure. In this regard, it is important to combine entrepreneurial marketing p...
By Jainish Roy, Rajesh Sehgal
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
LEVERAGING NANOMATERIALS IN CHEMICAL ENGINEERING TO OPTIMIZE EFFICIENCY AND SUSTAINABILITY ACROSS MODERN INDUSTRIAL PROCESSES
Nanomaterials have distinct physicochemical characteristics of high surface area, controllable surface chemistry, and size-dependent reactivity, which can be used to fine-tune industrial chemical reactions to maximize efficiency and sustainability. The paper examines the incorporation of the following nanomaterials, namely carbon nanotubes, graphen...
By Sandeep Soni, Rajvir Saini
IMPROVING MICRO-EXPRESSION RECOGNITION WITH AN ENHANCED DESCRIPTOR COMBINING GW-LBP, TGMH, AND WT
Micro-expressions (MEs) are involuntary facial expressions, short-lived (usually between 1/5 and 1/25 seconds), and important in the application of security, psychological tests, and forensics. The MEs are however difficult to identify because it occur quickly and also involve little movement of the muscles. The paper presents an Enhanced Micro-Exp...
By P. Surekha, P. Vidya Sagar, G. Ramesh
BIG DATA PROCESSING AND CORRELATION ANALYSIS OF ELECTRIC POWER MARKETING BASED ON IMPROVED APRIORI ALGORITHM AND RDD MODEL
To solve the problems of traditional Apriori algorithm in power marketing big data processing, such as candidate item set redundancy, low single-machine computing efficiency, and difficulty in adapting to multi-dimensional time series data, this study proposes an improved Apriori algorithm that integrates Resilient Distributed Dataset (RDD) distrib...
By Fan Pan, Lingen Zhou, Lu Gan, Wei Kang, Xiaolei Li