Daily Archives: July 30, 2025

Authors: Neha Dongre, Dr.SunilSugandhi

Abstract: Soil stabilization can be explained as the alteration of the soil properties by chemical or physical means in order to enhance the engineering quality of the soil. The main objectives of the soil stabilization is to increase the bearing capacity of the clay soil, it’s resistance to weathering process and soil permeability. The long-term performance of any construction project depends on the soundness of the underlying soils. Unstable clay soils can create significant problems for pavements or structures, Therefore soil stabilization techniques are necessary to ensure the good stability of clay soil so that it can successfully sustain the load of the superstructure especially in case of clay soil which are highly active, also it saves a lot of time and millions of money when compared to the method of cutting out and replacing the unstable soil. This paper deals with the complete analysis of the improvement of clay soil properties and its stabilization using industrial waste sand and lime. The experimentation is carried out keeping 20% of lime as constant and industrial waste sand 10%, 20%and 30%. Disposal of these waste materials is essential as these are causing hazardous effects on the environment. With the same intention literature review is undertaken on utilization of solid waste materials for the stabilization of soils and their performance is discussed

 

 

Published by: vikaspatanker

Authors: Maurya Kiran M, Gadekar Mayuri N, Davkhar Kalyani U, Kadbhane Ashwini S

 

Abstract: This study investigated antibacterial activity of two medicinal plants: Tridax procumbens, and Lantana camara; they are common weeds often found in cultivated areas and wastelands, and hold significant importance in traditional Indian medicine. These plants are rich in a diverse array of secondary metabolites, including tannins, flavonoids, alkaloids, saponins, phenols, steroids, anthocyanins, proteins, and carbohydrates. These secondary metabolites are extracted using Soxhlet’s method and ethanol as a solvent. Screening of plants' phytochemicals is done as per standard protocol. In vitro, antimicrobial activity was assessed using the well diffusion method. The antibacterial activity of Ethanol extracts of these two plant leaves was evaluated against disease-causing bacteria, including Staphylococcus aureus., Escherichia coli, Pseudomonas aeruginosa, Streptococcus sp., and Klebsiella pneumoniae Combined ethanolic plant extracts exhibited maximum antibacterial activity compared to the individual plant extracts.

DOI:

 

Published by: vikaspatanker

Authors: Rajnandanikoshti, Assistant professor Anubhav Rai

Abstract: The Calibration and testing of light weight structure are very important part for building design. However proposed work is belongs for a different types of steel structure analysis. In this proposed steel structures main focus to reduce of total weight and easily design. Now these research work identification of best light weight structures using staad pro software. The main object of this work design a steel frames and compare both structures

 

 

Published by: vikaspatanker

Authors: S.Radha Krishnan, Assistant Professor,M.Aishwarya, Dr.R.Natarajan

Abstract: Fault detection in industrial systems is crucial for ensuring operational safety, minimizing downtime, and reducing maintenance costs. This work proposes a hybrid deep learning model combining Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU) to detect and classify machine faults from time-series data. The CNN layers extract spatial features, while GRU layers model temporal depen,dencies in the data. The architecture incorporates residual connections to enhance gradient flow and improve learning efficiency. The model is evaluated on multi­ class fault detection datasets, achieving robust performance with high accuracy, precision, recall, and F1-score. Advanced metrics, including ROC-AUC, logarithmic loss, Cohen's Kappa, and Matthews Correlation Coefficient, demonstrate the model's reliability. Visualization of confusion matrices and detailed performance metrics validates its effectiveness in detecting anomalies and classifying fault types. This approach can be generalized for real-time monitoring systems in various industrial applications, ensuring predictive maintenance and operational excellence.

 

 

Published by: vikaspatanker