This paper examines the effectiveness of Generative AI (GenAI) as a socio-pragmatic aid that can improve Cross-Cultural Communicative Competence (CCCC) in advanced language learners (N = 80). Although such learners may be highly proficient in their language, A so-called pragmatic gap may also be faced in attempts to negotiate complex social interac...

By Temur Irmuxamedov, Jahongirmirzo Maxmudov, Gulshan Ibragimova, Aziza Muminova, Alevtina Muradova, Fotima Safarova, Bayramdurdi Sapaev

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

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

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

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