Volume 12 | Issue 2

 Abstract

This project introduces an Internet of Things (IoT) based pressure monitoring system utilizing the BMP085 sensor. The primary objective is to measure and monitor atmospheric pressure, offering real-time data visualization through the Blynk IoT platform. The Adafruit BMP085 sensor is employed for measuring temperature, pressure, and altitude, with an Arduino microcontroller and an ESP8266 Wi-Fi module facilitating wireless connectivity.The system leverages the Blynk library to establish a connection between the Arduino and the Blynk platform. Through the Blynk app, users gain remote access to pressure readings and receive alerts based on predefined thresholds. Additionally, the system controls an output pin, enabling the activation of a buzzer or external device in response to detected pressure levels.The implementation involves initializing the BMP085 sensor, configuring Wi-Fi credentials, and establishing a seamless connection with the Blynk platform. Sensor readings are then acquired and transmitted to the Blynk app, where they are visually displayed on a virtual terminal. Continuous monitoring of pressure levels provides visual feedback on both the Blynk app and the serial monitor.The proposed IoT-based pressure monitoring system boasts various advantages. It offers real-time data visualization, allowing users to remotely monitor atmospheric conditions. Integration with the Blynk platform enables the customization of alerts and notifications based on user-defined pressure thresholds. Moreover, the system exhibits flexibility for expansion, accommodating additional sensors or actuators to cater to more complex applications.

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 Keywords

Blood Pressure Monitoring System,Internet of Things(IoT),Blynk Platform,Data Visualization,Pressure Thresholds.

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This project is an effective technique to categorize data on specific requirements and conditions for the majority of marine species. To determine which species are all threatened or endangered, depending on the situation. Not only is the bulk of the data being classified here, but also the causes of and fixes for the classification of the data. The actual process of decision-making and branching based on the qualities of the data is carried out using a set of algorithms and tools. It facilitates the creation of efficient machine learning models that are capable of making precise predictions. Logistic regression is used to estimate discrete values (typically binary values like 0/1) from a collection of independent variables. The logic function is changed to match the data,It helps in estimating how likely an event is to occur. These algorithms function on this application well. Since there are just two outcomes in this project, logistic regression is employed as a binary classifier. It will also explain the causes and a fix for that here.

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 Keywords

Machine Learning Models,Logistic Regression,Logic Function,Binary Classifier,Precise Prediction

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Adult and pediatric populations have distinct medication pharmacokinetics and pharmacodynamics with the latter being more variable. While these variations in pharmacokinetics and pharmacodynamics support particular research, they also bring up a variety of moral and practical concerns. The invasiveness of the procedures and the barriers to patient recruitment are the main practical challenges to overcome while conducting clinical research in children. The Classical pharmacokinetic studies cannot often be performed on children due to the invasiveness associated with pain/anxiety and blood loss, especially in neonates and infants. Pharmacokinetic , pharmacodynamic modeling-based population techniques are especially attractive for pediatric populations due to their ability to handle sparse data. It has previously been highlighted how important population techniques are for examining dose-concentration-effect correlations and for qualitatively and quantitatively evaluating variables that could account for interindividual variability.

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 Keywords

Screening methods , Drug studies, In vivo-vitro studies, Animal cell culture Technique

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The Image Generation and Captioning Application project represents a groundbreaking fusion of artificial intelligence and creative expression, revolutionizing content creation. This innovative application leverages AI and computer vision to deliver a user-friendly platform for generating high-quality images with contextually relevant captions. Key objectives include developing resilient models, creating an intuitive interface, ensuring scalability, and maintaining ethical content generation. With applications spanning marketing, advertising, social media, and education, the project aims to redefine content creation by efficiently pairing compelling visuals with informative captions. The accompanying comprehensive review explores state-of-the-art techniques, emphasizing multimodal approaches, ethical considerations, and diverse applications. Addressing technical challenges and ethical guidelines, this project stands at the forefront of reshaping how we interact with visual information in the digital age.

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 Keywords

Image Generation, Captioning Application, User-Friendly Interface, Deep Learning, Generative Adversarial Networks (GANs)

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 Abstract

Schizophrenia is a psychiatric disorder affecting 1% of the population, characterized by a split mind disorder affecting emotions, thoughts, reasoning, and behaviour. It is a genetically influenced neurodevelopmental illness, with symptoms appearing after a 1-3% latency period. The disorder is characterized by delusions, hallucinations, illogical conclusions, and withdrawal from social interactions. The term "schizophrenia" was coined in 1908 by Swedish psychiatrist Eugen Bleuler, and its symptoms were first documented in Haslam and Pinel's 1809 publication. Mindfulness is a meta-cognitive exercise that involves focusing on the present moment while reducing emotional and cognitive reactivity. It originated from Buddhist vipassana meditation and has been applied to various health issues, particularly those with psychopathological profiles and somatic disorders. Mindfulness-based interventions (MBIs) have been shown to be effective in treating various mental health disorders. MBIs have shown moderate to strong effect sizes on depression and anxiety, and have been found to be beneficial during pregnancy. However, the benefits of mindfulness practices as stand-alone interventions are unclear. MBIs have also been found to improve insomnia and sleep quality, with effects lasting 3 months postintervention. They have also been found to have a positive effect on eating disorders, addiction, psychosis, post-traumatic stress disorder, and autism spectrum disorders. MBIs have also been shown to improve physical health outcomes for cancer patients, particularly in reducing cancer-related fatigue (CRF) scores. Furthermore, contemplative movement has been suggested to improve lung function and physical activity in COPD patients.

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Schizophrenia, Mindfulness-based interventions, addiction, psychosis, post-traumatic stress disorder, and autism spectrum disorders

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The fast-spreading infection of the retina is affecting persons of every age. There is photosensitive optic nerve material within a person's retina. The objective of the proposed approach is to gather a dataset of retinal illnesses so that the model can be trained on a range of images utilizing an open resume to enhance our standing. To identify the thing by analyzing the images and videos. From the smallest set of images if the retina, a machine learning technique based Deep Convolutional Neural Network (Deep CNN) will be used to determine the major retinal issues. The architecture consists of five layers, of which the second hidden layer and the third convolution layer are utilized to enhance and sharpen the images. The high as well as medium range characteristics are improved when the low-level characteristics are retrieved. Based on an experimental assessment, the suggested framework outperforms the others utilizing the multi-class Based on each stage's ability to recall, efficiency, and duration consumption, a complete assessment is being created. ss Kaggle dataset in terms of validity. On the Kaggle dataset, the recommended technique yielded a 97% accuracy rate.

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Machine Learning, Deep CNN, Convolutional Neural Network, CAT Boost Algorithm

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The aim of this investigation was to develop fast dissolving tablets containing Cyproheptadine Hydrochloride, with the goal of achieving a high onset of action. Fast dissolving tablet of Cyproheptadine hydrochloride was prepared by using direct compression method, there were nine batches were prepared of fast dissolving tablets, by using super disintegrant as crosspovidone ,croscarmellose and SSG. The fast dissolving tablets are evaluated for various parameters, the FDT of Cyproheptadine HCL containing crosspovidone showed faster disintegration time at concentrations 5% as compare to other. Hence from all nine formulation batch B3 showed better result like drug content, disintegrating time, drug release hence this is our optimized batch.Aalso, B3 was found stable during the stability study for 2 months. Hence prepared Fast dissolving tablet was stable in all conditions.

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Fast Dissolving Tablets, Cyproheptadine, Direct compression

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 Abstract

Neuroleptics, also known as antipsychotic medications, are used to treat and manage symptoms of many psychiatric disorders. They fall into two classes: first-generation or "typical" antipsychotics and second-generation or "atypical" antipsychotics. Both first and second-generation antipsychotics are used in various neuropsychiatric conditions. These include attention-deficit hyperactivity disorder (ADHD), behavioral disturbances in dementia, geriatric agitation, depression, eating disorders, personality disorders, insomnia, generalized anxiety disorder, obsessive-compulsive disorder, post-traumatic stress disorder (PTSD), and substance use and dependence disorders. For many of these conditions.

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Neuroleptics, classification, Types, Advantages, Disadvantages, Advers effects Neuroleptic Malignant Syndrome, Treatment

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Tuberculosis (TB), one of today's most deadly diseases, is caused by Mycobacterium tuberculosis and primarily affects the lungs, often exploiting weakened immune systems. TB poses a significant threat, with mortality rates escalating if left undetected. To address this challenge, various computer-assisted diagnostic methods have emerged, leveraging machine learning, particularly deep learning, in image processing. By analyzing chest X-rays, these techniques aim to provide more accurate, timely, and reliable diagnoses. Recent studies suggest that machine learning-based approaches can outperform manual diagnosis, offering superior accuracy. Notably, Digital image processing (DIP) is gaining prominence in biomedical research. Leveraging image processing, Support Vector Machine (SVM) models can effectively classify lung abnormalities indicative of TB. The primary focus of this study is to detect tuberculosis through the implementation of machine learning models trained on chest X-ray images.

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Mycobacterium Tuberculosis, Digital Image Processing (DIP), Machine Learning, Deep Learning, Support Vector Machine (SVM)

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This paper provides an overview of the concept of carbon credit and carbon taxation, highlighting their potential to incentivize emission reductions and promote sustainable development. It explores the current state of the electricity and heat sector in India, emphasizing the need for comprehensive measures to curb carbon emissions and transition towards a low-carbon economy. It also addresses the critical issue of sustainable development in the electricity and heat sector in India through the implementation of carbon credit and carbon taxation mechanisms. India, as one of the world's fastest-growing economies, faces the dual challenge of meeting its increasing energy demands while also combating climate change and reducing carbon emissions. The electricity and heat sector, being one of the major contributors to carbon emissions, requires innovative policies and strategies to promote sustainability and reduce its environmental impact. It also identify the challenges and barriers associated with the implementation of carbon credit and taxation in India, including the need for robust monitoring, reporting, and verification mechanisms, as well as the importance of ensuring equity and mitigating potential economic impacts. It emphasizes the significance of carbon credit and carbon taxation as essential tools for promoting sustainable development in India's electricity and heat sector. It advocates for a comprehensive policy framework that integrates these mechanisms into the country's energy strategy, while also considering the unique socio-economic and environmental context of India.

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Carbon Credit, Carbon Taxation, Carbon Accounting, Green Credit Programme, Sustainable Development, Decarbonizing, Renewable energy integration.

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This paper aims at enriching the debate on aesthetics properties on the Chhau-Na?cha (dance) of Odisha. This traditional Chhau- Na?cha mostly based on the Ra?sa theory i.e., Vira (Heroic); and its old age tradition belonging to canons of Na?tyas?a?stra in rhythmic way. Man requires artistic skill to express his thought but proper modulation of artistic representation is necessary to make expressed thought precise and distinct. One performer could represent him/her in the way of demonstrate in the form of art i.e., dance or Na?cha/Na?ta. Dance consists of certain movements, certain prescribed gestures and postures of the body which are more capable of giving expression to human thought, than even language. Communication of thought through dance is even a better guide of human thought than through language. In Odisha the performance dance its related music, dramatic thought, is as old like its history. Numerous forms of histrionic arts which are deeply and intimately associated with the life of the people were evolved, natured and put into practice and then left to the posterity either to retain or forget. Through the passage of time many terms are must have perished away. All the form of art can survive only proper patronage but these are not possible every time and space. Chhau dance is basically a virile dance which demonstrates vim and vigour. It reflects a culture of strength with aesthetics.

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region, trend, practises, ritual, folk dance, anthropological methods, theory of Rasa

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Abstract: A wide variety of forecasting techniques are in use. In many respects they are quite different from each other. Forecasting techniques assume that the same underlying casual system that existed in the past will continue to exist in the future. 1. Forecasts are not perfect, actual results differ from predicted values; the presence of randomness precludes a perfect forecast. Allowances should be made for forecast errors. 2. Forecast accuracy decreases as the time period covered by the forecast-the time horizon-increases. Generally speaking, short range forecasts must be content with fewer uncertainties than longer-range forecasts, so they tend to be more accurate.

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Time Series Graphs, Supply Chain, Forecasting Error, Minitab, Power Bi

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Disposal of waste material (plastic) is a major problem. Plastic waste is a non-biodegradable. Burning of these waste plastic bags causes highly environmental pollution. It mainly consists of low-density polyethylene. To use of waste material in Bituminous Road construction really impressive job, this material dumped into land leads to wastage of land. In this study use of Aggregate as a filler material bituminous concrete and waste plastic as coating material. Find its utility in bituminous mixes for road construction. Improvement in properties of bituminous mix provides the solution for disposal in a useful way.

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PWM-Plastic Waste Modified, TGA-Thermo-Gravimetric Analysis.

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This study delves into the satisfaction level of employees within public and private sector banks in Kottayam district regarding the incentives and fringe benefits provided by their respective institutions. The research aims to effectively analyze the impact of these incentives and benefits on employee motivation and retention, asserting that employee satisfaction significantly contributes to organizational goals. Employing a descriptive research approach, convenient sampling was utilized. "The study underscores the pivotal role of incentives and fringe benefits in enhancing individual performance, with employees expressing satisfaction with current schemes".

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Employee satisfaction, Incentives, Fringe benefits, Motivation.

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Digital transformation is the key to the success of any business today. Unlike the conventional approach, modern advertising media allows customers to interact with the web at a much more personal and intimate level thereby collecting consumer data - likes, dislikes, interests, and preferences. One of the main reasons for the high effectiveness of personalized online advertising is the use of emerging IT solutions which have been playing a major role in crafting impressive commercials, making it easier for marketers to target users at a very personalized level. Objective of the study: The objective of this research paper is to review and assess the role of Information Technology in delivering highly targeted personalized ads to the consumers by understanding the concept of personalization. Research Methodology: The research is basically qualitative in nature. This field has evolved over a period of time. So, it is an exploratory study. The research is based on an analysis of various research papers and an extensive literature review is used. It is based upon review and analysis of papers to arrive at a framework of adoption of these technologies in personalized advertisement.

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Advertisement, Digital Transformation, Consumers, Information Technology

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Pharmacovigilance definition given by WHO, it is "The science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other possible drug-related problems.The volume of data handled has increased in tandem with the number of reported Adverse Drug Reactions (ADRs). Standardising the process of risk management and signal detection in the context of clinical trials and post-marketing pharmacovigilance is a difficult task. Nonetheless, there is a pressing need to comprehend and apply pharmacovigilance given the increased number of clinical trials and clinical research activities being carried out in India, as well as the phase of clinical trials and pharmaco epidemiologic studies.

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Pharmaco epidemiologic studies, adverse drug reaction,clinical trials, post-marketing surveillance

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To ensure system stability and security, the rapid growth of Internet of Things (IoT) networks has prompted the development of effective anomaly detection systems. In this study, we give a thorough investigation of anomaly detection in IoT networks, with a particular emphasis on the incorporation of machine learning approaches. While bridging the gap between technical difficulties and popular comprehension, we explore into several machine learning approaches such as supervised, semi-supervised, and unsupervised learning. Our goal is to encourage more technological study and appreciation in the ever-changing IoT ecosystem. We also discuss the practical impacts of anomaly detection in sectors like the field of cyber security, healthcare, and industrial applications. As IoT systems evolve, so will the necessity for effective anomaly detection solutions.

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Anomaly detection, machine learning, security and privacy protection, Internet of Things (IoT), smart devices.

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The Wandergram assignment goals are to alternate how humans plan and discover vacations. It gives records and guidance to assist humans in making the most of their journey testimonies. This present-day tour website uses interactive factors and vicinity-based absolute services to provide a plethora of revel-in facts, travel tips, websites of interest, and nearby espresso stores, ingesting places, and hangout locations. Wandergram's main motive is to cater to a wide variety of user pastimes and offer customers the ability to find hidden areas, discover places, and plan extraordinary tours unexpectedly. In order to gather information about attractions while taking user preferences and behavior into account, restricted Boltzmann machines (RBMs) were employed in the study. Furthermore, we use collaborative-based filtering using K-means clustering to provide restaurants, accommodations, and an upgraded restaurant recommendation system, respectively. A chatbot that serves as a virtual travel helper is also a part of Wandergram. A chatbot that serves as a virtual travel helper is also a part of Wandergram. This integration marks the beginning of a new generation in which the tour transcends every day and will become an unforgettable journey. As Wandergram matures, it transforms how vacationers put together and revel in their trips. Wandergram ensures that each trip can be transformed into a unique experience that allows visitors to immerse themselves in the neighborhood's way of life and discover new ways. Travelers are taken on tours by Wandergram, where every interaction is specifically catered to their preferences and areas of interest. The proposed system shows an accuracy of 95%

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Restricted Boltzmann Machines (RBMs), Collaborative Filtering, Recommender System, Location-Based Recommendation, Rating Prediction, and Feature Learning.

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The present paper explores the presence of Kabir, an early modern North Indian saint poet, among the Muslims of Maghar and examines how he has become part of their cultural, religious and social life. The previous studies give just passing references to Muslims' attachment to Kabir at Maghar in the context of their visit to the Kabir Mazar (shrine). However, no scholar has paid any attention to the Muslims of Maghar town (which itself consists of Kabir's shrines at its east periphery) in terms of their relationship with Kabir. During the course of my fieldwork at Maghar from 2016 to the early months of 2022, I found that the Muslims of Maghar look up to Kabir as one of their own. They perceive him as a Sufi or Pir or Wali and address him as Kabiruddin Shah. They frequently visit Kabir's shrine, offer fatiha (prayer), recognize and claim Kabir to be their own. For their faith in Kabir, they claim to reject the propagation of the orthodox Deobandi and Wahhabi Islamic groups, which give a strong emphasis on purifying Islam of the non-Islamic elements. It is significant to note that in the increasing fire of communalism when religious leaders impose strict segregational codes on their followers shunning mixed religious practices, the Muslims of Maghar have not only preserved the tradition of their attachment to Kabir but also foster this syncretic tradition for the future generations.

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Maghar, Muslims, Kabir Mazar, Deobandi and Wahhabi Islamic groups, syncretic tradition

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 Abstract

Background: Mental health can be described as a healthy mind. Mental illness is a state of dysfunction in overall health of an individual. Misconception and stigma is closely related to mental illness since human civilization. Though the perception on mental health and mental illness keeps on changing but the misconception and stigma is still somewhere associated with it. The present study was undertaken to assess the misconception and stigma regarding mental illness among adults in a rural community of Sonapur, Kamrup (Metro), Assam. The study was aimed to assess misconception and stigma regarding mental illness and find out the association of misconception and stigma regarding mental illness and sociodemographic variables. Methods: Two hundred and seventy subjects were selected from six selected villages of Sonapur, Kamrup (metro), Assam, by using multistage sampling technique. Structured tool was developed to assess the misconception and stigma regarding mental illness among adults and the data were analyzed by using the software package, SPSS 20 version. Results: Majority of the adults i.e., 115 (42.6%) had moderate misconception regarding mental illness, 80 (29.6%) of the adults had low misconception and remaining 75 (27.8%) had high misconception regarding mental illness. With regard to subareas, highest misconception of the adults was observed in the recovery (Mean%=95.25) followed by symptoms (Mean%=92.75), causes (Mean%=75.45) and lowest misconception was recorded in treatment (Mean%=74.36). Majority of the adults i.e., 178 (65.9%) had moderate stigma regarding mental illness, 62 (23%) of the adults had low stigma and remaining 30 (11.1%) had high stigma regarding mental illness. With regard to subareas, highest stigma of the adults was observed in the vi prejudice (Mean%=66.58) followed by discrimination (Mean=64.08) and lowest stigma was recorded in stereotype (Mean=51.63). The calculated value of correlation coefficient, 'r' has found to be 0.653, P value <.001, which is significant at 0.001 level of significance, which signifies that there is a strong correlation between the misconception and stigma regarding mental illness among adults. Respondent's misconception regarding mental illness was insignificantly associated with all the sociodemographic variables i.e., age, sex, education, occupation, monthly family income, marital status, religion, type of family and family history of mental ilness. Respondent"s stigma regarding mental illness was also insignificantly associated with all the selected sociodemographic variables. Interpretation and Conclusion: The findings clearly suggest that majority of the adults had misconception and stigma on mental illness. Therefore appropriate measures should be adopted based on the need of the people in the community setting to eliminate the existing misconception thereby to remove stigma in order to bring a drastic change in the perception of people towards mental illness in the near future.

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"A study to assess the misconception and stigma regarding mental illness among adults in a rural community of Sonapur, Kamrup (Metro), Assam."

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