http://nopr.niscpr.res.in/handle/123456789/65359 2026-10-10T13:29:11Z http://nopr.niscpr.res.in/handle/123456789/65369 Title: Life Cycle Energy Assessment of Rajasthan’s Marble Processing Plant for Sustainable Environment Planning Authors: Singh Sodha, Dharmanshu; Singh Mali, Harlal; Kumar Singh, Amit Abstract: The construction sector plays a vital role in achieving sustainability; therefore, monitoring and continuous improvement in energy and environmental performance in this sector are crucial. The Rajasthan state of India contains 64% of Indian marble resources, and approximately 90% of the marble is being processed in Rajasthan alone. In past decades, the production of marble stones has been in very high volume, leading to high energy consumption. Since the processing of marble worldwide is performed by Small-to-Medium Enterprises (SMEs), these industries lack technology, leading to low efficiency and more expensive production with significant waste generation. The objective of this study is to assess the energy consumption and environmental impacts of typical marble processing SMEs in Rajasthan and to propose strategies for enhancing production efficiency and reducing the ecological footprint. Through site surveys, power rating data were collected to quantify electrical energy usage across various operations of marble production, and further, each operating scenario's energy consumption was compiled. Environmental impacts, particularly CO2 emissions, were quantified using the GaBi® sustainability software. This study presents a consolidate index for assessing the economic and environmental performance of different operating scenarios and for ranking processing lines for One Square Feet (ft2) of processed marble stone, providing a comprehensive sustainability performance assessment. The findings highlight the potential for substantial environmental advantages by implementing energy-efficient practices and critical technological advancements to improve the marble processing industries' sustainability and operational efficiency, potentially assisting broader regional environmental initiatives. Eventually, the findings aim to contribute to the development of greener production practices in the sector, promoting both economic and environmental sustainability. Page(s): 123-135 2025-02-01T00:00:00Z http://nopr.niscpr.res.in/handle/123456789/65368 Title: Physicochemical Properties of Soil and Plant Geometry in Oil Yield, Quality and Economics of Lemongrass in Rainfed Bundelkhand Region, India Authors: Jeet, Sabha; Verma, Ravindra; Bhagat, Sonali; Bhanwaria, Rajendra; Tabassum, Shahina; Kumar Yadav, Gajendra Abstract: Keeping in mind the significance of sustainable production practices and greater resource use efficiency, a study was led to access five levels of Plant Geometry (PG)/spacing of lemongrass variety CKP–25 (Cymbopogon khasianus × pendulous) tested with three levels of Soil Types (ST) on the performance of essential oil (EO) yield, secondary metabolites (SM) and economic returns (ER) in rainfed Bundelkhand region. The results of the analysis of variance data were recorded for two consecutive years (2020–21 and 2021–22). On an average EO content was found to be highest (0.77%) in Mar Soil (MS). The interaction MS along with PG1 [62,500 plants/ha (40×40 cm)] observed the highest EO content (0.79%). The highest EO yield (228.23, 319.92 kg/ha) was obtained in MS along with PG3 [76,923 plants/ha (45×30 cm)] in 1st and 2nd years, respectively. The lemongrass variety, showed excellent performance in terms of achieving higher net income and benefit˗cost (B:C) ratio, in respect of MS with PG3. The significantly highest Net Return (NR) (Rs. 1,70,995 and 3,02,984 /ha) and B:C ratio (2.66 and 4.74) were recorded in MS along with PG3 in the 1st and 2nd year, respectively. However, in terms of secondary metabolites, Neral (cis˗citral) or citral B (40.13 ± 3.92%, 37.36 ± 4.63) and trans citral or citral A (47.97 ± 5.51%, 45.83 ± 5.54%) was noted to be highest in MS in both the year. On average, the total citral was found to be highest in MS (84.95 ± 5.36%, 83.19 ± 4.85%) in 1st and 2nd years, respectively. Page(s): 136-147 2025-02-01T00:00:00Z http://nopr.niscpr.res.in/handle/123456789/65367 Title: GAN-CNN based Structure-Preserving Mixed Noise Removal Model for Enhancing Medical Image Authors: H Shah, Vishal; Parimita Dash, Prajna Abstract: The current era of the Internet of Medical Things (IoMT) and Medical Artificial Intelligence (MAI) makes medical imaging a prominent mode of providing effective solutions in diagnosis and prognosis. The main issue with these images is the presence of noise that requires enhancement through effective edge preservation and noise reduction. The proposed work introduces a two-stage Deep Learning (DL) model, utilizing Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNN) for jointly reducing speckle, impulse, and Gaussian noise while preserving edge information in noisy medical images. The work also explores the probabilistic evaluation of generators and discriminators for compensating lossy patches to ensure image quality. The performance of the proposed model is investigated by considering three different performance metrics, namely, PSNR, FSIM, and SSIM. Moreover, non-parametric statistical tests like the Sign test, Wilcoxon Signed rank tests and Friedman tests are also conducted to assess the dominance of the proposed model over other state-of-the-art approaches. Two-stage GAN-based models generate realistic, high-quality images by effectively suppressing inherently present spurious noise in medical images and simultaneously preserving the edge information. Page(s): 148-161 2025-02-01T00:00:00Z http://nopr.niscpr.res.in/handle/123456789/65366 Title: Simulative Performance Investigation of OFDM & f-OFDM for Optical Wireless Communication System Authors: Upadhyay, Kritika; Bharti, Manisha Abstract: Internet of Things (IoT) is a fast-growing technology that requires innovative solutions and technologies to realize its vision efficiently. Optical Wireless Communication (OWC) technology is one of the emerging connectivity technologies that could benefit this IoT deployment. Orthogonal Frequency Division Multiplexing (OFDM) is regarded as a technique of encoding data on multiple carriers as it promises high data rates and lays down the foundation for many standards of wireless communication such as 5G network. However, large OOBE (Out-Of-Band Emission) and large Peak to Average Power Ratio (PAPR) in OFDM makes it less potent to meet demand of high data rate. Therefore, Filtered-OFDM (f-OFDM) act as promising candidate for future wireless generation networks. The motivation of this paper is to analyze the applicative aspect of Multicarrier Modulation schemes (OFDM and f-OFDM) in implementation of OWC technology within the IoT. The parameters used for evaluating the robustness of the designed system are namely- Bit error Rate (BER), Signal to noise ratio (SNR) Peak to average power ratio (PAPR) and Power Spectral Density (PSD).The investigation reveals an increment of 25% SNR and decrement of 16% occurrences of error during transmission for f-OFDM. Further, Quadrature Amplitude Modulation (QAM) modulation scheme increase this SNR to 30% (approx.), thus promising the designed system as suitable contender for upcoming linked OWC and wireless networks like IoT. Page(s): 162-169 2025-02-01T00:00:00Z