KPR Institute of Engineering and Technology

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

Purpose Enhancing construction site productivity (CSP) is essential, as the industry's growth is closely linked to the economy's development. Prior research on CSP has demonstrated its role, including enhancing project planning and execution. However, existing research has not investigated factors impacting CSP in India. Therefore, this study aims to develop and validate a CSP model for the Indian construction industry. Design/methodology/approach Structural equation modeling (SEM) was employed to analyze the relationships among latent variables and test the proposed theoretical framework. In this study, 8 latent constructs operationalized through 28 indicators were examined to assess their impact on CSP. A total of 204 valid responses were obtained and subjected to rigorous statistical examination. The analytical procedures comprised reliability assessment, chi-square testing, correlation analysis, confirmatory factor analysis and SEM to validate the proposed model. Findings The SEM analysis revealed that site management (SM) (ß = 0.38, p < 0.001) and safety and quality procurement (ß = 0.32, p < 0.001) exerted the strongest significant impact on CSP. These findings indicate that standardized safety and quality measures are critical determinants of site productivity. Additionally, three indicators emerged as particularly important: workforce stability, skill development and working conditions. Research limitations/implications These findings furnish construction practitioners with empirical evidence regarding the hierarchical impact of factors impacting CSP. Critically, the results establish a framework for analyzing site operations and administrative processes, thereby enhancing evidence-based decision-making in project management. Moreover, this study advances construction performance management theory by empirically validating that site-level managerial capabilities and human resource dimensions constitute the primary determinants of productivity in developing economies. Originality/value This study contributes to the productivity management body of knowledge by developing and validating a CSP model in the context of developing economies. By establishing SM as a strong influencing factor, this study provides evidence that calls for further research on management practices and their mechanisms for enhancing productivity at construction sites.

With increased Internet of Things (IoT) devices, complexity and protection are more challenging. Lightweight cryptographic algorithms are secure and suitable for limited-resource environments; however, their hash functions provide encrypted data but not integrity. Strong security features are available, but setup is difficult and expensive. Network security mechanisms increase power consumption and latency. As IoT networks grow, managing cryptographic keys and securely authenticating large numbers of devices become complex tasks. Efficient key management strategies are required to ensure the scalability required. Existing state-of-the-art solutions lack standardization, scalability, complex and costly. Thus, this research proposes a secure solution for IoT resource-constrained devices, combining strong data integrity and lightweight encryption, and is thus named a hybrid. This hybrid approach integrates SHA-512 and the present cipher in our proposed approach and thus ensuring higher security than state-of-the-art models. This intelligent combination not only enhances the algorithm’s resistance against cryptographic attacks but also improves its processing speed. The proposed approach is used to reduce the processing time for encryption in the IoT platform and to preserve the trade-off between security and efficiency. In terms of memory use, execution time, and precision, the proposed approach is compared with recent state-of-the-art research. The experimental results indicate that our approach is efficient using the avalanche, authentication success rate, collision events, and execution time. The efficiency is 53% to 65%, and the avalanche effect indicates sensitivity to input variations, suggesting moderate-to-considerable reactivity to small data changes. The experimental tests conducted across 10,000 and 80,000 runs reveal no collisions and found that the proposed approach is resilient in managing unique IDs. Moreover, our approach performs consistently, with an average execution time of 0.088246 s, ranging from 0.075954 to 0.094583 s. Finally, our approach provides a practical and scalable solution for securing IoT devices in resource-constrained environments, addressing practical problems for IoT devices.

This study investigates the development of a carbonate-based eutectic phase change material (PCM) and evaluates the hot corrosion behavior of containment alloys for high-temperature concentrated solar power (CSP) applications. A eutectic mixture of sodium carbonate (55 wt%) and diatomite (45 wt%) was thermally characterized using DSC, TGA, and FTIR through which confirming its stability up to 800 °C with an exothermic peak at 849.1 °C and an enthalpy change of 48.1 J/g. Hot corrosion tests were conducted at 800 °C for exposure durations up to 500 h on Inconel 686, Hastelloy C2000, Inconel 59, and SS316 in the eutectic PCM environment. Amongst, Inconel 59 exhibited superior corrosion resistance, with the corrosion rate decreasing significantly from 627.15 μm/year at 100 h to 25.09 μm/year at 500 h, indicating the formation of a stable and protective oxide scale. In contrast, SS316 showed severe degradation, with corrosion rates increasing from 1756.01 μm/year to 3706.44 μm/year due to the formation of non-protective iron oxides and chromium depletion. XRD, SEM, and EDS analyses revealed the dominant formation of NiO and Cr 2 O 3 protective layers in Ni-based alloys, while SS316 exhibited porous Fe 2 O 3 and FeCr 2 O 4 phases. Based on the experimental corrosion data, machine learning models were applied to predict corrosion behavior, with the stochastic gradient descent (SGD) algorithm demonstrating reliable performance (R 2 = 0.923). The results revealed that Inconel 59 is a promising containment material for carbonate-based thermal energy storage systems and demonstrate the potential of machine learning approaches for corrosion prediction in CSP environments.

The field of biomimetic and bioinspired materials has progressed rapidly by drawing inspiration from nature's intricate structures and multifunctional systems in order to address pressing challenges in modern engineering. This review critically examines the mechanical performance of these materials, focusing on their hierarchical design principles, synthesis strategies, and versatility of application. Natural exemplars such as nacre, spider silk, and bone are emphasized, as their structural efficiency and functional adaptability have informed the development of synthetic analogues with superior strength, toughness, flexibility, and lightweight characteristics. The review also highlights advanced fabrication methods, such as additive manufacturing and precision chemical synthesis, which have enabled researchers to replicate the complexity of nature with ever-greater accuracy. Key case studies demonstrate how bioinspired strategies have been translated into high-performance materials for use in the aerospace, construction, and biomedical sectors. The review also discusses challenges related to scalability, reproducibility, and industrial integration. Finally, the review outlines emerging interdisciplinary approaches that are set to further enhance the mechanical properties and practical relevance of biomimetic materials, establishing them as transformative solutions for the next generation of engineering systems.