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

Water efficiency in agriculture is a crucial measure of how effectively farmers use their most vital resource. In practical terms, it reveals how much applied water actually nourishes crops versus being lost to evaporation or runoff. In the Bundelkhand region of Uttar Pradesh, India, where water is incredibly scarce, making every drop count is cruc...

By Aakanksha Rawat, Mukul Kulshrestha

New smart museums, integrating technologies like augmented reality (AR), virtual reality (VR), interactive kiosks, Internet of Things (IoT) devices, and AI tools, mark a departure from treating industrial history as a passive archival medium. The incorporation of these technologies allows for a shift from passive learning to actively experiencing h...

By Umidbek Abdalov, Nilufar Rajabova, Rufat Karimov, Zafar Khasanov, Rukiya Ashurbayeva, Mamlakat Xonnazarova, Dilshod Khamidov, Dilfuza Abdullayeva

The nature of software engineering is ever-changing and needs smart, intelligent, and innovation-enhancing solutions for talent management. In this paper, we describe our statistically validated dynamic Talented Innovative ecosystem (DTIE) that aims to improve innovation scaling in software engineering through AI-enabled analytics, data-driven recr...

By S. Krishnadas, Ramya Thiyagarajan

Diagnosing critical conditions like Acute Liver Failure (ALF), Methanol Toxicity (MT), Alcohol Poisoning (AP), and Diabetic Ketoacidosis (DKA) is difficult due to similar symptoms and complex interdependent metabolism, often resulting in delayed and incorrect diagnoses in historic clinical practice. We present a hybrid machine learning framework in...

By S. Ramadoss, A. Kumaravel

In fast-developing Indian cities, congestion is a significant concern, as travel times are much longer, the environment is negatively affected, and infrastructure is overstretched. Conventional traffic management systems tend to be ineffective at addressing such problems because they rely on fixed traffic lights and lack data inputs. This paper pre...

By Anjali Goswami, Anjali Krushna Kadao

Manufacturing systems that are technology-intensive have high interdependencies between financial decisions on investments, the change in production capacity, and operational efficiency. Traditional methods tend to look at financial and operational planning in isolation, resulting in poor performance of the system and poor use of resources. In orde...

By Megala Rajendran, Yokubbaeva Umida Abduvakhob kizi, Kosimov Khusniddin Badriddinovich, Ergashev Rasulbek Sokhib ugli, Iplina Antonina Aleksandrovna

This study looks into how artificial intelligence (AI), especially machine learning (ML), might improve workplace satisfaction and employee engagement among mid-level IT professionals in Bangalore. The report examines the strategic uses of AI in digital trust systems, employee profiling, and predictive analytics, based on a structured survey of 434...

By Amthul Naseeb, S. Ramesh Babu, Jalaja Anilkumar, Mounica Vallabhaneni, Indumathi, N. Venkatarathnam, S. Mahabub Basha

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

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