Effective feature selection based HOBS pruned- ELM model for tomato plant leaf disease classification.

Tomato cultivation is expanding rapidly, but the tomato sector faces significant challenges from various sources, including environmental (abiotic stress) and biological (biotic stress or disease) threats, which adversely impact the crop's growth, reproduction, and overall yield potential. The objective of this work is to build deep learning based lightweight convolutional neural network (CNN) architecture for the real-time classification of biotic stress in tomato plant leaves. This model proposes to address the drawbacks of conventional CNNs, which are resource-intensive and time-consuming, by using optimization methods that reduce processing complexity and enhance classification accuracy.

Fuzzy logic-based health risk assessment of fluoride in groundwater used as drinking source in Sira region, Tumkur, India.

Fluoride contamination in drinking water is a serious public health concern across the world, and more than 90 million people in India are affected by health risks associated with fluoride. Though the fatality due to fluoride chronic toxicity is uncommon, the exposure to fluoride at different concentration levels shows various adverse health effects such as dental and skeletal fluorosis, multiorgan failure, cognitive and behavioural effects. Hence, the objectives of the present study are to understand the hydrogeochemistry and drinking water suitability of groundwater of the Sira region, Karnataka, India, and to understand the occurrence of fluoride and its health risks using the United State Environmental Protection Agency (US EPA) method and fuzzy logic concepts.

Simultaneous production of renewable biohydrogen, biobutanol and biopolymer from phytogenic CoNPs-assisted Clostridial fermentation for sustainable energy and environment.

Considering the environmental impacts, rapid fossil fuel depletion and production costs, sustainable production of clean biofuels from alternative sources is required to meet the increasing demand for energy while avoiding environmental pollution. In this study, phytogenic cobalt nanoparticles (CoNPs)-assisted dark fermentation process was developed for the simultaneous production of biohydrogen, biobutanol and biopolymer from glucose using Clostridium acetobutylicum NCIM 2337. The maximum biohydrogen yield of 2.

Chloride-salinity as indicator of the chemical composition of groundwater: empirical predictive model based on aquifers in Southern Quebec, Canada.

The present study first describes the variations in concentrations of 12 chemical elements in groundwater relative to salinity levels in Southern Quebec (Canada) groundwater systems, and then uses this data to develop an empirical predictive model for evaluating groundwater chemical composition relative to salinity levels. Data is drawn from a large groundwater chemistry database containing 2608 samples. Eight salinity classes were established from lowest to highest chloride (Cl) concentrations.

SCB-HC-ECC-Based Privacy Safeguard Protocol for Secure Cloud Storage of Smart Card-Based Health Care System.

The advent of the internet has brought an era of unprecedented connectivity between networked devices, making one distributed computing, called cloud computing, and popular. This has also resulted in a dire need for remote authentication schemes for transferring files of a sensitive nature, especially health-related information between patients, smart health cards, and cloud servers smart health card solution providers. In this article, we elaborate on our proposed approach for such a system and accomplish an informal analysis to demonstrate the claim that this scheme provides sufficient security while maintaining usability.