Volume 12 | Issue 5 |

 Abstract

Emergency medical services are critical for saving lives, but instances of ambulance misuse, driven by factors such as commissions, can hinder timely responses. This project introduces a Smart Ambulance Routing System designed to mitigate such issues and optimize emergency response efforts. Leveraging real-time hospital information, GPS technology, and intelligent algorithms, the system guides ambulance drivers to the nearest hospitals, ensuring efficient and patient-centered emergency care. Two-way communication facilitates information exchange, and a user-friendly interface supports manual intervention. Continuous learning algorithms and privacy measures ensure system adaptability and data security. The system aims to revolutionize emergency response through AI-driven optimization and dynamic resource allocation. Ongoing collaboration and monitoring are essential for its effectiveness. The patient's biomedical parameters, such as heart rate, respiration, and body temperature, will be collected by the LSAI48266X Artificial Intelligence board. It will then use an algorithm to process the data and determine which category the patient falls into, i.e., oxygen bed support, ventilator support, or ICU support. The board will do this by utilizing Internet of Things to check the hospital's networked medical system availability. The hospital is informed to the ambulance driver via the Telegram app. The Smart Ambulance Routing System makes use of effective communication protocols, a cloud-based platform for hospital data storage, and NodeMCU for real-time GPS tracking. Hospital distances are dynamically calculated by cloud functions, and the best routes are determined by an onboard algorithm. An alert message is triggered when there is a major delay in the ambulance arrival.

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 Keywords

Emergency Medical Services, Real-time hospital information, cloud based platform, AI driven Optimization

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 Abstract

The bioaccumulation of arsenic in edible plants poses significant environmental and public health concerns, particularly in industrialized regions such as Hatti in Raichur, Karnataka. This study investigates arsenic contamination levels in various edible plants grown in the vicinity of the Hatti industrial area. Samples were collected from multiple locations around the industrial zone, and arsenic concentrations in plant tissues were analyzed using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). Results revealed elevated arsenic levels in plant samples, with variation observed among different plant species. Factors influencing arsenic uptake, including soil properties, plant species, and environmental conditions, were examined to elucidate bioaccumulation mechanisms. Specifically focusing on pigeon pea plants, suspicion of arsenic presence prompted extraction using an alkaline leaching method with temperature assistance, following a modified wet digestion approach. Initial chemical tests confirmed arsenic presence, with subsequent instrumental analysis via ICP-OES yielding the following observations (mg/kg): N1t (0.098), N2t (0.094), N3t (0.097), N4t (0.098), F1t (0.096), F2t (0.048), F3t (0.089), and F4t (0.092). Although arsenic concentrations in pigeon pea plants were below toxicity limits, ingestion of larger quantities could pose health risks. Acute oral ingestion of arsenic can result in gastrointestinal irritation, decreased blood cell production, abnormal heart rhythm, blood vessel damage, and impaired nerve function. Chronic exposure may lead to skin changes, skin cancer, and various internal cancers, along with potential impacts on diabetes, blood pressure, reproductive health, and cognitive function. This study contributes to understanding arsenic bioaccumulation in edible plants.

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 Keywords

Bioaccumulation , Alkaline Leaching method , Inductively Coupled Plasma Optical Emission Spectroscopy, Arsenic Uptake, Pigeon Pea plants, Gastrointestinal Irritation, Chronic Exposure.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Behaviour modification is a systematic approach to understanding and changing Behaviour through the application of principles derived from psychology, particularly Behaviourism. This paper explores the theoretical foundations, principles, techniques, and applications of Behaviour modification in various settings. Drawing on principles of operant conditioning, classical conditioning, social learning theory, and cognitive-Behavioural theory, Behaviour modification interventions aim to increase desired Behaviours and decrease undesired ones by manipulating environmental factors and consequences. The paper discusses the importance of functional Behavioural assessment (FBA) in identifying the underlying function of Behaviour and tailoring interventions accordingly. It also examines the role of reinforcement, punishment, shaping, prompting, modelling, and cognitive restructuring in Behaviour modification. Applications of Behaviour modification in clinical psychology, education, parenting, organizational management, and self-improvement programmes are explored, highlighting its effectiveness in addressing a wide range of Behavioural challenges and promoting positive Behaviour change. Finally, the paper discusses ethical considerations, limitations, and future directions in the field of behaviour modification.Behaviour modification is a systematic approach to understanding and changing Behaviour through the application of principles derived from psychology, particularly Behaviourism. It involves identifying target Behaviours, assessing their antecedents and consequences, and implementing interventions to increase desired Behaviours and decrease undesired ones. Key principles include operant conditioning, classical conditioning, social learning theory, and cognitive-behavioural theory. Techniques such as reinforcement, punishment, shaping, prompting, modelling, and cognitive restructuring are commonly used to modify behaviour. Behaviour modification is applied in various settings, including clinical psychology, education, parenting, organizational management, and self-improvement programmes, to address a wide range of behavioural challenges and promote positive behaviour change. Ethical considerations, limitations, and future directions in the field are also important aspects to consider when implementing behaviour modification interventions.

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 Keywords

Behaviour therapy, Applied Behaviour analysis, Operant conditioning, Target Behaviours, Antecedents, Consequences, Reinforcement, Punishment, Shaping, Modelling, Cognitive restructuring, Positive reinforcement, Negative reinforcement, Extinction, Behavioural interventions

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Local Train commuters in Mumbai face a tremendous amount of crowd while travelling in rush hours of the day, which usually leads to many commuters standing for the entire duration of travel in a cramped space or sitting in awkward postures, for a long time that over a course of period inevitably leads to musculoskeletal pain in some form or another. Objective: To find the joints and areas involved most commonly in local train commuters using Nordic Musculoskeletal Questionnaire and to have a gender biased discrimination on the joints involved. Methods: A cross sectional survey was conducted on 384 local train commuters in Mumbai. Dadar and Thane railway stations were targeted for recruitment of participants. Convenience sampling was used for the same. Both male and female participants above the age of 18, who had been travelling for more than a year and had a single travel route of an hour or more were included in the study. Nordic Musculoskeletal Questionnaire was used to collect the data. Results: A total of 384 responses were collected from local train commuters, amongst which 60% were female and 40% were male participants. 86% commuters experienced pain while 14% did not. Neck was the most affected area (37%) while elbow was the least affected (2%). The gender biased study pointed towards females having more cases of pain in each involved joint. Conclusion: The present study indicates that 86% Mumbai local train commuters have experienced a degree of musculoskeletal pain from travelling.

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 Keywords

Musculoskeletal pain, Mumbai local train commuters

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 Abstract

Machine learning methods have transformed healthcare by enabling precise and prompt disease prediction. Predicting multiple diseases simultaneously can greatly enhance early detection and treatment,improving patient outcomes and lowering healthcare expenses. This system examines the use of machine learning algorithms in predicting multiple diseases, addressing their advantages, obstacles, and future prospects.It provides an overview of various machine learning models and data sources commonly employed for diseaseprediction, emphasizing the significance of feature selection, model assessment, and the fusion of multiple datatypes for improved disease prediction. Research findings underscore the promise of machine learning in multi-disease prediction and its potential to advance public health.

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Machine learning,Emphasizing

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Institutions annually witness a significant number of graduating students requiring clearance from various departments, a process traditionally executed through physical visits to different offices. However, this conventional method is marred by inefficiencies including time consumption, staff unavailability, and data management issues. To address these shortcomings, an online clearance system was developed, utilizing modern web technologies. The system, developed with Angular for the frontend and Node.js for the backend, along with MongoDb for database design, revolutionizes the clearance process. Incorporating Angular for the frontend enhances user experience with its dynamic and responsive interface, while Node.js ensures efficient data processing and server-side operations. Evaluation involving 500 students and 60 staff members yielded promising results, with approximately 90.1%, 92.8%, and 95.3% affirming its usability, service delivery convenience, and accessibility, respectively. This research underscores the system's efficacy in facilitating efficient and effective clearance procedures, enhancing the institution's administrative workflow.

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 Keywords

virtual clearance gateway, Angular, Node.js, Accessibility

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

E-resources are valuable resources for 21st century learners. In the digital age, ICT is regarded as the backbone of entire teaching learning process. The main objective of the study is to study the awareness and usability of E-resources for undergraduate students. The study was conducted by following survey method, in which a sample of 60 students were selected through convenience sampling. Self -developed tool was used for data collection. The findings of the study highlight that students of non-govt. aided institutions are moderately aware about E-Books, E-Journals and their usability. So, E-resources has significant implications for enhancing the potentialities of the learners.

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 Keywords

ICT, E-resources, awareness, availability, usability and undergraduate students.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This abstract presents a novel method that makes use of drones and image processing tools to identify medicinal plants in distant forest areas. With the help of the Jupyter IDE and Python programming language, the study uses the Vgg19 Convolutional Neural Network (CNN) to accurately identify plants. Drones can be used to explore inaccessible areas, which improves conservation and biodiversity monitoring initiatives. Real-time analysis is made possible by the integration of image processing techniques, which helps researchers and conservationists make decisions quickly. In the end, our approach promises to transform the identification and monitoring of medicinal plants, supporting biodiversity preservation and sustainable resource management.

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 Keywords

Image processing , Vgg19 , Areal drone detection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract- The emergence of electric cars (EVs) in India has positive implications for the future of the transportation business. India is one of the globe's marketplaces for automobiles that are expanding at a rapid pace, and the adoption of electric vehicles (EVs) there could have a major impact on the economics, environment, and energy security of the entire country. India dominates the world in EV usage for many causes. By 2030, the Indian government wants to electrify 30% of all vehicles on the road. The government has made several pronouncements to that effect, including tax rebates, financial aid, and expenditures in infrastructure for charging. In addition, EVs offer a number of benefits over conventional internal combustion engine (ICE) cars, including reduced operating costs, fewer pollutants, and increased energy efficiency. These benefits are particularly important in India, where fuel costs fluctuate and air pollution is a serious public health issue. The introduction of EVs in India still encounters a number of issues. They involve a dearth of infrastructure for charging, a small variety of EV models, and expensive initial expenses for EVs. The Indian government continues to attempt to boost the nation's charging infrastructure, encourage indigenous EV production, and offer incentives for EV usage to resolve these problems. In conclusion, India's increasing adoption of electric vehicles has the potential to completely transform the country's transportation sector and clear the way for a more flourishing and environmentally friendly future. Even though there are still issues to be resolved, the Indian government's commitment to electric transportation and consumers' growing interest in EVs indicate that the technology has a promising future. The introduction of EVs in India still encounters a number of issues. They involve a dearth of infrastructure for charging, a small variety of EV models, and expensive initial expenses for EVs. The Indian government continues to attempt to boost the nation's charging infrastructure, encourage indigenous EV production, and offer incentives for EV usage to solve issues.

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 Keywords

EV

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Phytochemical Analysis, DPPH, ABTS, Free Radical Scavenging, Anti Pyretic Activity

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Creative Commons Attribution 4.0 and The Open Definition