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Effectiveness of Classroom Interaction on English Language Production in Tamil Medium Schools in Coimbatore
The research study emphasized the importance of classroom interaction (CI) in English language classes for language learning among second language learners of English based on the interaction approach to language learning. The present study attempted to address the problem of students entering the tertiary level of education with dissimilar levels of English language proficiency due to the inequity in English language education among various types of schools in India. newlineThe main purpose of the study was to facilitate classroom interaction (CI) for newlineEnglish language learning in the context through the development of an Interactive Hour module and thereby providing opportunities for disadvantaged learners to be exposed to a graded target language and enabling them to produce the target language inside classroom spaces with corrective feedback on language use. The research was carried out in two phases using mixed methods research design in government-aided Tamil medium schools in the district of Coimbatore, newlineTamil Nadu, India. Phase I of the study, which was majorly qualitative in nature, was conducted to establish the need for the study in the context. It was aimed to Systematically present the actual teaching and learning scenario of English language classrooms in government-aided schools in Tamil Nadu in comparison to what is mentioned newlinein the national and state education policy notes and official documents related to newlineEnglish language teaching. The major objectives of phase I of the study were to newlineunderstand the pedagogic goals of English language teachers and their classroom newlineinteractional awareness and to observe and evaluate the nature and extent of classroom interaction in English language classes in the context of language policy and planning. -
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Synergistic effects of CuO/TiO2-chitosan-farnesol nanocomposites: Synthesis, characterization, antimicrobial, and anticancer activities on melanoma cells SK-MEL-3
The current investigation focuses on synthesizing copper oxide (CuO)-titanium oxide (TiO2)-chitosan-farnesol nanocomposites with potential antibacterial, antifungal, and anticancer properties against Melanoma cells (melanoma cells [SK-MEL-3]). The nanocomposites were synthesized using the standard acetic acid method and subsequently characterized using an X-ray diffractometer, scanning electron microscope, transmission electron microscopy, and Fourier transform infrared spectroscopy. The results from the antibacterial tests against Streptococcus pneumoniae and Stapylococcus aureus demonstrated significant antibacterial efficacy. Additionally, the antifungal studies using Candida albicans through the agar diffusion method displayed a considerable antifungal effect. For evaluating the anticancer activity, various assays such as MTT assay, acridine orange/ethidium bromide dual staining assay, reactive oxygen species (ROS) generation assay, and mitochondrial membrane potential (MMP) analysis were conducted on SK-MEL-3 cells. The nanocomposites exhibited the ability to induce ROS generation, decrease MMP levels, and trigger apoptosis in SK-MEL-3 cells. Collectively, the findings demonstrated a distinct pattern for the synthesized bimetallic nanocomposites. Furthermore, these nanocomposites also displayed significant (p < 0.05) antibacterial, antifungal, and anticancer effects when tested on the SK-MEL-3 cell line. 2023 Wiley-VCH GmbH. -
Nanostructured ZnCo2S4@metal organic frameworks composite for supercapacitor by ultrasonication supported hydrothermal reaction
Electrode materials for supercapacitors, sensors, and battery applications were frequently manufactured using the chemistry of metal organic framework nanostructured materials. These materials have three-dimensional networks between organic linkers and metal precursors thanks to diverse chemical alterations. Due to their enhanced surface characteristics, porous nature, and strong connecting organic molecules for numerous possible applications, MOFs have a wide range of uses. In this study, we used a sonicated enhanced hydrothermal reaction to fabricate ZnCo2S4 and ZnCo2S4 on the metal organic framework composite materials. Raman, FTIR, XRD, XPS, SEM, and SEM-EDS tests were utilized to confirm the composite's structural and morphological features. With 1 M KOH electrolyte, composite electrodes for supercapacitor fabrication were produced. The composite electrodes have a stability under cycles count of 5000 and a capacitance of 550 F/g at a density of 1 A/g. 2024 Elsevier B.V. -
Calcination process of porous metalorganic frameworks derived from nickel sulfide composites for supercapacitor and computer vision for investigating the porosity-electrochemical correlation
The utilization of metalorganic framework nanostructured electrode materials in supercapacitors and sensor applications is achieved by various chemical methods. In this study, we create NiS and NiS@MOF-BDC by employing nickel precursors and benzene dicarboxylic acid (BDC) as chelating organic linkers through a thermal reduction procedure at a temperature of 400 C to produce the composite. The composite heterostructure enhanced the conductivity, porous characteristics, and diverse potential morphological qualities. The production of composite electrodes demonstrates a specific capacity of 260F/g (104C/g) when subjected to a current density of 1A/g. Additionally, these electrodes exhibit exceptional cyclic stability, enduring 5000 cycles, when used with a 2 M KOH electrolyte. Moreover, the synthesized composite HR-TEM images were analyzed using computer vision and AI techniques for estimating the porosity and investigating the enhanced electrochemical correlation. 2024 Elsevier B.V. -
Synthesis and characterization of 4-nitro benzaldehyde with ZnO-based nanoparticles for biomedical applications
Globally, cancer is the leading cause of death and morbidity, and skin cancer is the most common cancer diagnosis. Skin problems can be treated with nanoparticles (NPs), particularly with zinc oxide (ZnO) NPs, which have antioxidant, antibacterial, anti-inflammatory, and anticancer properties. An antibacterial activity of zinc oxide nanoparticles prepared in the presence of 4-nitrobenzaldehyde (4NB) was also tested in the present study. In addition, the influence of synthesized NPs on cell apoptosis, cell viability, mitochondrial membrane potential (MMP), endogenous reactive oxygen species (ROS) production, apoptosis, and cell adhesion was also examined. The synthesized 4-nitro benzaldehyde with ZnO (4NBZnO) NPs were confirmed via characterization techniques. 4NBZnO NPs showed superior antibacterial properties against the pathogens tested in antibacterial investigations. As a result of dose-based treatment with 4NBZnO NPs, cell viability, and MMP activity of melanoma cells (SK-MEL-3) cells were suppressed. A dose-dependent accumulation of ROS was observed in cells exposed to 4NBZnO NPs. As a result of exposure to 4NBZnO NPs in a dose-dependent manner, viable cells declined and apoptotic cells increased. This indicates that apoptotic cell death was higher. The cell adhesion test revealed that 4NBZnO NPs reduced cell adhesion and may promote apoptosis of cancer cells because of enhanced ROS levels. 2023 Wiley-VCH GmbH. -
Phytoextract-mediated synthesis of Cu doped NiO nanoparticle using cullon tomentosum plant extract with efficient antibacterial and anticancer property
In the present study, nickel oxide (NiO) and copper-doped nickel oxide (NiCuO) nanoparticles (NPs) were successfully synthesized using Cullen tomentosum plant extract with the co-precipitation method. This work focuses on the Phyto-mediated synthesis and characterization of NPs for their biological applications. Phytochemicals that exist in the plant extract acts as reducing and capping agent. The successful formation of the NPs was validated by various analysis as XRD, FESEM, EDAX, FT-IR, UVVis, and Photoluminescence. According to XRD studies, the average crystallite size of NiO and NiCuO NPs is 36 nm and 31 nm, respectively. The river stone and nanoflower like morphology for NiO and NiCuO NPs are confirmed by FESEM image. Furthermore, the synthesized NPs were tested against Gram-positive (Bacillus subtilis, Streptococcus pneumoniae) and Gram-negative (Klebsiella pneumoniae, Escherichia coli) bacteria, which showed enhanced antibacterial activity of NiCuO NPs. The cytotoxicity of NPs was investigated against human breast cancer cells (MDA-MB-231) and fibroblast L929 cell lines. Also, the IC50 value for human breast cancer cells is 11.8 ?g/mL. According to these findings, NiCuO NPs are potential nanomaterials with advanced healthcare uses. 2023 -
Bridging Digital Divide in India: Positive Outlook Amid COVID-19
The digital divide is described as the gap in access to, knowledge of, use of, or ability to comprehend information and communication technology (ICT) between different societal groups. The digital divide can often give way to an upsurge in social inequalities. This study intended to comprehend the extent of the rural-urban digital divide in India regarding access to the internet and to analyze the increase or decrease in the same due to the global coronavirus pandemic. The analysis of the paper was primarily based on secondary data collected from the report on The Indian Telecom Services Performance Indicators issued by the Telecom Regulatory Authority of India for June 2019 and June 2020. Percentage analysis was employed to comprehend the trend of the digital divide in terms of access for the years 2019 and 2020. The results disclosed that there was an increase in internet access in the rural population during the time frame of COVID-19, and this increase has led to a decrease in the digital divide in terms of access to the internet. Moreover, the study revealed that COVID-19, to some extent, has resulted in bridging the rural-urban digital divide in India in terms of access. The study further highlighted the importance of digital literacy and access to ICT, and suggested ways to improve digital literacy in India. 2022, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Artificial Intelligence and Machine Learning Applications in Threat Detection
Artificial intelligence (AI) and machine mastering (ML) have emerged as progressive breakthroughs in medical prognosis, especially in the area of early most cancers diagnosis. These trendy gadgets significantly enhance the accuracy and performance of tumor detection. By analyzing huge records units, synthetic intelligence structures can identify small styles and anomalies in medical imaging, which lets in malignant tumors to be recognized earlier and greater appropriately than traditional methods. AI and ML are needed to accelerate tumor analysis and category in the context of most cancers remedy. These technologies assist doctors quickly perceive any abnormalities in radiological pictures inclusive of X-rays, MRIs and CT scans. Artificial intelligence reduces the workload of clinical specialists through automating this manner, enabling faster and greater correct analysis. In addition, AI can assist tailor remedy packages contemplating a patient's specific records, maximizing treatments and predicting remedy outcomes. In addition to improving the performance and speed of diagnosis, the aggregate of AI and ML in tumor detection suggests the capability to boom the general effectiveness of cancer treatment and in the end enhance affected person consequences. 2025 Scrivener Publishing LLC. -
Design, Analysis and Validation of Electric Vehicle Control and Safety for Different Path Profiles and Braking Conditions
Energy conservation and Environmental pollution are two major challenges today for our society. Currently, utilization of the latest technology, to reduce energy consumption and harmful emissions from vehicles, is gaining significance in the contexts related to automobile, energy and power industries. Considerations of these contexts enable us to form a more realistic newlineperspective and a need for developing fuel efficient, comfortable and affordable electric vehicles. The importance of design and development of electric vehicle (EV) is better perceived when, there is a major impact on our future society due to (i) the energy saving aspect from newlineboth the customer side on individual expenditure as well as from the national economy viewpoint and (ii) the huge benefit due to reduction of emissions from internal combustion engines using fossil fuels. EV offers the best solution which not only avoids emissions but overcome the dependency on petroleum resources as well. Due to fewer moving parts, monitoring and controlling of EV are also smooth and relatively much easier. The embedded control techniques used in EV also contribute for a better controllable, observable, predictable newlineand efficient vehicle drive. This current research work focuses mainly on Electric Vehicle Mobility and Control aspects for a deeper study. This research work addresses topics related to mathematical modelling and simulation studies for design and analysis of EV control and safety. Validations of the several case studies done during this research are supported by software tools namely MATLAB/Simulink and IPG Carmaker Virtual Driving Simulation Platform. Starting from modelling, throughout the various stages of this work, realistic vehicle parameters and specifications are considered. The newlinedifferent levels of testing, validation and trial runs of the model-based designs are also validated by software in loop and hardware in loop approaches. Automotive Safety Integrity Level B/C hardware was used for the implementation purpose. -
AI for Optimization of Farming Resources and their Management
The chapter explores the incorporation of artificial intelligence (AI) into framework strategies aimed at addressing the dynamic challenges confronting the agricultural industry. It focuses on issues like resource depletion, escalating labor costs, and the impacts of climate change, emphasizing the necessity for inventive solutions. The proposed framework adopts a comprehensive approach that integrates farm-to-fork strategies, smart agricultural practices, and advanced crop planning. Its primary objectives are to enhance crop yields, establish transparent supply chains, and optimize resource allocation. The chapter underscores the potential synergies associated with contextual understanding, efficient communication, and personalized user experiences, anticipating a transformative impact on agriculture. The integration of AI is anticipated to yield unprecedented benefits, paving the way for a more technologically advanced, sustainable, and productive future. Despite these promising prospects, challenges emerge during the integration process, manifesting as regulatory hurdles, infrastructure deficiencies, and inherent complexities. The chapter acknowledges these obstacles and asserts that overcoming them is crucial for realizing the full transformative potential of AI in agriculture. Looking ahead, the convergence of AI and framing strategies is poised to revolutionize the agricultural landscape, ushering in increased efficiency and sustainability. This innovative partnership holds the promise of building a resilient foundation for agriculture, ensuring its adaptability to changing needs and contributing to a greener and more productive future. 2025 selection and editorial matter, Sirisha Potluri, Suneeta Satpathy, Santi Swarup Basa, and Antonio Zuorro; individual chapters, the contributors. All rights reserved. -
Electric Vehicle Control and Driving Safety Systems: A Review
The relevance of Electric Vehicles (EVs) and the overall market demands of the respective control units is in a never before leap all around the globe as seen from the news, business studies, research trends and technological innovations today. Compared to earlier years, the relevance of driving safety in EVs also gains special attention due to the unforeseen surge in promoting EVs by National, State and City administrations for better environment and societal changes in future. For EV, the scenario broadens to a wider landscape beyond the earlier passive safety design features, to a highly comfortable and safer possible road travel. Safety enhancements can be experimented and implemented on EVs in a reliable way with higher end control of the dynamics, stability and optimised utilisation of individual vehicle characteristics and driver behaviours. In this paper, an attempt is made to scrutinise different control design approaches and possible solution paths experimented upon in the past and currently for EV as seen in the published literature. The quest is also to explore optimisation strategies in an organised way to ensure best possible driving safety along with passenger safety in EVs. 2023 IETE. -
A Fundamental Study on Electric Vehicle Model for Longitudinal Control
Stricter emission norms need to drift toward being environment friendly have shifted the concentration in the automobile sector toward electric vehicles. This research article highlights the fundamental modeling steps required for an electric vehicle control system design following a simulation approach using MATLAB/Simulink software. From an electric vehicle design perspective, this approach offers an excellent solution to give insights into EV research involving multidisciplinary engineering aspects. The study presents longitudinal control technique, relevant observations and results to bring out the differences in open-loop and closed-loop case studies. It also intends to provide better understanding toward the need for a feedback, realization of an expected path profile for students and researchers in this field of interest. The steps involved in transforming the mathematical model into a simulation model and analysis of the simulation results are detailed in this article. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Simulations of electric vehicle model for insights into pre-planned trajectory profiles
Electric vehicles are slowly gaining its significance in the automobile sector due to stringent emission norms. This research article highlights the fundamental modeling steps required for an electric vehicle designing following a simulation approach using MATLAB/Simulink software. It gives a clear and concise way to interpret vehicle model from a simple to complex modelling approach. Unlike other research works, this paper helps to thoroughly perceive the fundamentals involved in modeling an electric vehicle with different trajectory profiles. The vehicles behavior when subjected to different external forces, steering characteristics under different path profiles are analyzed in a systematic way. This research work highlights the significance of identifying and solving issues faced in the safety sub-system of an EV. 2020 SERSC. -
Design and performance analysis of braking system in an electric vehicle using adaptive neural networks
Research article emphasizes on the impact of braking concepts considering regenerative braking system and energy consumption aspects in electric vehicles through a new perspective. The electric vehicle system is modeled and simulated using the MATLAB/Simulink software. A dataset is developed using the virtual simulation environment created by co-simulation using the MATLAB/Simulink and the IPG Carmaker software. This dataset is also used in a neural network model based on adaptive neuro fuzzy logic and the system performance is analyzed. Parameters considered for training the neural network are the brake pedal displacement, braking change rate and the need for brake application. The highlight of this study is the focus on a front wheel driven electric vehicle, which uses a standard drive cycle input to validate the model. The significant parameters evaluated in this study include the braking effects, kinetic energy, regenerative braking torque, battery state of the charge and the motor torque. The torque generation and its intended braking force requirements based on the acceleration, deceleration and braking conditions are the notable observations. The regenerative capability of this proposed system design is also illustrated along with the surface plots based on the training dataset. Investigation and analysis reveal that, the battery state of charge could be revived throughout the drive with a steady and stable increase. Transitions of motor torques between tractive and regenerative phases are also illustrated and explained for clarity and brevity. 2023 Elsevier Ltd -
A Study on Machine Learning Techniques for Internet of Things in Societal Applications
Until recent years, monitoring and analysing system inputs, responses were merely based on Sensor Systems. Gradually, Embedded Systems and other Data Resources including Remote Monitoring Units started gaining momentum. But, with advent of Internet of Things (IoT), the outlook and expectations are broadened. IoT introduced incredible volumes of structured and unstructured data of different formats. There is a need to investigate, the underlying concepts of Machine Learning, Internet of Things (IoT) and Embedded Systems. These domains grow and expand its frontiers at a very fast pace. This paper attempts to throw light on possibilities of combining different technological domains, for design and development of Smarter and Context Aware Intelligent Electronics Systems for Societal Utility. Effective implementation and realization of such systems by suitable fusion of essential inter-disciplinary concepts is expected to have considerable potential for societal impact in the years to come. 2019 IEEE. -
Simulations of electric vehicle model for insights into pre-planned trajectory profiles
Electric vehicles are slowly gaining its significance in the automobile sector due to stringent emission norms. This research article highlights the fundamental modeling steps required for an electric vehicle designing following a simulation approach using MATLAB/Simulink software. It gives a clear and concise way to interpret vehicle model from a simple to complex modelling approach. Unlike other research works, this paper helps to thoroughly perceive the fundamentals involved in modeling an electric vehicle with different trajectory profiles. The vehicles behavior when subjected to different external forces, steering characteristics under different path profiles are analyzed in a systematic way. This research work highlights the significance of identifying and solving issues faced in the safety sub-system of an EV. 2020 SERSC. -
FloodWatch: Suggesting an IoT-Driven Flood Monitoring and Early Warning System for the Flood-Prone Cuddalore District in the Indian State of Tamilnadu
Floods continue to pose significant threats to communities worldwide, causing loss of life, property damage, and disruption of vital services. Timely and accurate flood monitoring and early warning systems play a critical role in mitigating these impacts. This chapter presents FloodWatch, an innovative IoT-based flood monitoring and early warning system designed to enhance community resilience and response capabilities for the Cuddalore district, classified as one of the multi-hazard-prone districts of Tamilnadu. The Cuddalore district has a coastal line of 68 km, hence it is vulnerable to cyclones, and heavy rainfall, in turn causing floods. FloodWatch leverages the power of the Internet of Things (IoT) technology and provides real-time data collection, analysis, and dissemination for flood-related parameters. FloodWatch integrates a network of smart sensors strategically deployed in flood-prone areas, including rivers, streams, and urban drainage systems. These sensors continuously measure key variables, such as water level, rainfall intensity, weather conditions, and soil moisture content. The collected data is transmitted to a centralized cloud-based platform, where advanced data analytics and machine learning algorithms are employed to process and analyze the information. FloodWatch utilizes historical data and predictive modeling to assess the risk of flooding and generate accurate early warnings. Through intuitive interfaces and mobile applications, relevant stakeholders, including local authorities, emergency responders, and residents, receive real-time alerts and notifications, enabling timely decision-making and appropriate response actions. Key features of FloodWatch include its scalability, adaptability, and user-friendliness. The system can be easily customized to cater to different geographical and environmental conditions, ensuring its applicability in diverse regions. Additionally, FloodWatchs intuitive interfaces provide actionable insights in a visually comprehensible manner, facilitating effective communication and community engagement. The implementation of FloodWatch offers several notable benefits, including improved flood preparedness, reduced response time, and enhanced disaster management. By equipping communities with the tools to monitor, predict, and respond to floods, FloodWatch contributes to minimizing the impact of flood-related disasters, ultimately fostering greater resilience and safeguarding lives and property. FloodWatch represents a significant advancement in flood monitoring and early warning systems, harnessing IoT technology to provide accurate and timely information to communities at risk. This chapter highlights the architecture, functionality, and advantages of FloodWatch, underscoring its potential to enhance resilience and contribute to more effective flood management strategies on a global scale. 2025 selection and editorial matter, A. Daniel, Srinivasan Sriramulu, N. Partheeban, and Santhosh Jayagopalan; individual chapters, the contributors. -
Digital twin technologies for automated vehicles in smart healthcare systems
The idea of being comfortable seems appealing to a vast majority of people, from the start humans were always dependent on something. First the tools were invented and with the help of the tools, amazing things were built. From the invention of the wheel to the steam-powered machines and now the introduction of electronic automation, digitization and making intelligent production processes is the need for todays industry. Industry 4.0 is now the standard by which businesses must measure their progress. It enables businesses to reinvent themselves. Manufacturing systems go beyond simple connections here, communicating, analyzing, and using data to drive more intelligent activities. It combines Internet of Things (IoT), analytics, additive manufacturing, robots, artificial intelligence, sophisticated materials, and augmented reality. The autonomous vehicle (AV) is one of the applications of Industry 4.0. AVs can make passenger transfers more efficient. Furthermore, smart sensors, when combined with cognitive computing and IoT, portray an AV as a cyber-physical system where data from all relevant viewpoints is closely monitored and synced between physical devices and the cyber computational realm. By utilizing sophisticated information analytics, AVs will be able to work more effectively, collaboratively, and resiliently. As a result, AVs might be able to work with Industry 4.0 systems. 2023 Elsevier Inc. All rights reserved.