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

Sustainable practice and automation in the field of mining engineering are becoming a fundamental component of educating the future engineers to respond to the challenges facing a changing mining industry. As mining operators are increasingly being pressured to utilize more environmentally sustainable practices and to adopt new automation technolog...

By Kamala Kodirova, Ozodbek Nematov, Anastasia Seitasmanova, Sarvinoz Qodirova, Feruza Sapaeva, Fotima Babajanova, Bakhtiyor Polvonov, Abduraim Adilov

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

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

The fast development of digital technologies has transformed the organization and work relations, and the process of the digitalization of Human Resource Management (HRM) has become significant in optimizing the performance of the organization. In this paper, I am going to examine how Artificial Intelligence (AI), flexible work environments, and st...

By E. Pavithra, K. Sathishkumar, G. Kowsalya, M. Ramalingam, Pardaev Jamshid, Jyoti Prasad Kalita, S.D. Vijayakumar

Efficient document streaming requires robust preprocessing and semantic modeling to handle noise, redundancy, and morphological variations in large-scale text data. Existing stemming and document processing techniques often fail to preserve contextual relevance, leading to reduced classification and retrieval performance. In a bid to overcome this ...

By K. Ranjit Kumar, S. Thirumaran