Taken a toll control in development alludes to the progressing prepare of overseeing costs– commerce costs such as materials, work, overhead, and alter orders–associated with an extend in arrange to move forward benefit.

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Welding is a process a two-material crystallization and non-crystallization bonding process. GTAW by a shielding gas (helium, argon and nitrogen). GTAW techniques one of the major process ASS and FSS fabrication process. Tungsten arc welding mostly helpful use environment a helium and argon gas therefore protect welding area, maintain stale arc welding due to low ionization potential. Aluminium react to affect a corrosion resistance in the mechanical property. GTAW process ASS and FSS result of the finding have confirmed that depending one of the heat inputs which can controlled by welding parameters welding speed, AC current and voltage. Aluminium is light and weight material for use best performance industry, automobile mechanical, defense and others. AC power supply is preferring to use for Aluminium as compare to DC power supply because of its low melting point Aluminium melt at low temperature. Welding process partially heat affected zone HAZs it can undergo mechanical failure.

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The Internet of Things (IoT) is revolutionizing business operations by connecting devices, systems, and processes in unprecedented ways. This comprehensive study explores the multifaceted applications of IoT in enhancing business efficiency. By integrating IoT technologies, businesses can streamline operations, reduce costs, and improve decision-making through real-time data analytics and automated processes. The paper examines various IoT implementations across industries such as manufacturing, retail, logistics, and healthcare, highlighting how IoT enables predictive maintenance, inventory management, and personalized customer experiences. Case studies illustrate the tangible benefits of IoT adoption, including increased productivity, reduced downtime, and enhanced customer satisfaction. The research also addresses the challenges and risks associated with IoT deployment, such as data security, privacy concerns, and the need for robust infrastructure. Furthermore, the study outlines best practices for businesses to effectively implement IoT solutions, emphasizing the importance of strategic planning, cross-functional collaboration, and continuous innovation. By providing a detailed analysis of the current state and future potential of IoT in business, this paper aims to offer valuable insights for organizations seeking to leverage IoT technologies to achieve operational excellence and competitive advantage.

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The major problem faced by electricity consumers is more consumption of electricity and high paying electricity bill. Many people cannot even pay for calculated electricity bill from authority and due to this they have to face power cuts/power outage. In remedy to reduces electricity bill of consumer, suggested modification in this paper may help to achieve minimum consumption of electricity and they have to pay less amount for the electricity, and they don't have to face power outage. This modification facilitates regeneration of electricity by mechanical coupling which is discussed in detailed in this paper. Modification of ceiling fan to regenerate energy can be done with the help of mechanical coupling by which transmission of rotational energy is possible from main shaft to shaft of magnetic housing, as it starts to rotate rotating magnetic field will be developed around the conductors and emf will get induced in conductor. We can use this energy whenever required and deal with power cuts/power outage.

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Covid-19 was declared as a global pandemic in March 2020 (WHO, 2020). It led to the closure of schools and universities and this closure put a considerable burden on the academic institution to cope with the unprecedented shift from traditional to online learning. This study focused on school students and teacher's perceptions and preference towards the online learning. The research approach that is conducted for the study is Quantitative Descriptive survey type and random sampling technique has been adopted for the study. The primary data is collected from Students (100) and teachers (50) through structured questionnaire. Results of this study indicate that flexible schedule and convenience was ranked as the main benefits of the online learning. Online education offers students, the opportunity to study at their own space and time of their convenience. This study also reveals that online learning hamper students – teacher's relationship, it also create problem in understanding the language and social science and also math subjects among students. So, though this study, it can be said that online learning just an alternative of face to face mode of learning during Covid-19 to continue learning process.

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The current methods for oil spill detection face limitations in coverage, real-time processing, and accuracy, hindering effective response to environmental hazards. These challenges include limited accessibility to remote areas, reliance on human intervention, difficulties in detecting small spills, and constraints in processing large-scale data. Addressing these issues requires advanced AI-driven solutions that enhance detection accuracy, enable real-time monitoring, and optimize resource utilization for cost-effective deployment. This research presents a novel approach to detecting oil spills using an enhanced deep learning model, integrating YOLO-V3 with MobileNet architecture. The primary objective was to improve the detection accuracy and speed of oil spill identification in satellite imagery. The model was trained and evaluated using a diverse dataset that included varying sea states, weather conditions, and oil spill sizes. The experimental results demonstrated significant improvements in precision, recall, F1-score, and mean average precision (mAP) compared to the standard YOLO-V3 model. Additionally, the model achieved superior detection speed, making it highly suitable for real-time applications. Comparative analysis with other state-of-the-art models further validated the effectiveness of the proposed approach. The scenario-based testing underscored the model's robustness in diverse operational conditions, showcasing its potential for practical deployment in oil spill monitoring systems.

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Based on the proposed design methodology of ICBP, a design chart and design software were also developed. Based on the proposed deflection prediction model, a design methodology was developed in accordance with IRC 37 (2018). Rutting and deflection were the two failure criteria considered while designing ICBP. For the assumed ICBP layer thickness, the actual and allowed values for deflection and rutting criteria were determined. The actual and allowable rutting were calculated as per IRC 37 (2018) guidelines. The Shell equation was used to compute allowable rutting and the IIT PAVE software was used to calculate the actual rutting. Similarly, the actual deflection was measured using the proposed deflection model and the permissible deflection was calculated using Sun's rutting equation (1996). A design methodology is developed based on the failure criteria. A design chart is generated based on the design methodology for various sub grade strength sand traffic in the wider range. A designs of tware called NITT-BLOCKPAVE was established to explore the ICBP section for various CBR and traffic conditions. It was recommended to provide zigzag shaped blocks with herringbone pattern. The NITT-BLOCKPAVE aids in attaining the ICBP section which satisfies the design criteria.

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