Volume 12 | Issue 12

 Abstract

The advent of digital financial technologies has offered a promising solution to bridge this gap and extend financial services to previously underserved populations, including street vendors. Mobile banking, electronic payments, and digital wallets have emerged as powerful tools to overcome the barriers of traditional banking, offering a convenient and accessible means for individuals to manage their finances, make payments, and access credit. By leveraging the widespread penetration of mobile phones and digital infrastructure, digital financial inclusion initiatives aim to empower marginalized groups like street vendors, enabling them to participate more fully in the formal economy and improve their financial well-being. However, the realization of digital financial inclusion for street vendors is not without its challenges. Despite the proliferation of digital financial services, adoption rates among marginalized communities remain uneven, influenced by a myriad of socio-economic, cultural, and institutional factors. Street vendors, in particular, face unique hurdles, including low literacy levels, limited access to smartphones and internet connectivity, and distrust of formal financial institutions. Moreover, the complex regulatory landscape governing digital finance introduces additional barriers, impeding the effective implementation of inclusive policies and programs.

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Changing lifestyle,Consumption pattern, Consumer Behavior, Market Segmentation.

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Anti-cancer drug treatment is seriously affected by various undesirable properties such as poor solubility,narrow the rapeutic index and efflux transporter specificity.

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Abstract: This article explores the role of artificial intelligence (AI) in medical imaging interpretation, focusing on its applications in radiology. Radiological image interpretation is fundamental to medical diagnostics, aiding in the detection, diagnosis, and management of various diseases. Traditional methods rely on human intuition, but the complexity of images can lead to errors and variability in outcomes. The evolution of AI in medical imaging has been significant, with advancements in technology and methodology over several decades. Current technologies, such as deep learning algorithms like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), offer solutions to longstanding challenges in image interpretation. Key studies demonstrate the transformative potential of AI in detecting abnormalities, segmenting anatomical structures, and aiding in treatment planning. However, challenges persist, including the need for standardization in data organization, policy considerations for data sharing, and concerns regarding model explainability and privacy. Achieving true "intelligence" at the human level remains a key consideration for the future of AI in medical imaging. Overall, this research highlights the critical importance of AI in advancing radiological interpretation, offering opportunities to improve diagnostic accuracy, efficiency, and patient outcomes.

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AI, CNNs, RNNs

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ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION

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ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION

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The discipline of pharmacogenetics examines how a medicinal intervention affects our genetic makeup. Nowadays, pharmacogenetics is generally heralded as having the potential to completely transform medicine. This quickly expanding discipline seeks to explain the genetic underpinnings of individual variations in drug response and to utilize that genetic data to forecast the safety, toxicity, and effectiveness of medications in either a single patient or a group of patients. It is also crucial for researching how several genes affect a drug's pharmacological function. In this we find and study about numerous components of the genes that affect the therapeutic of the drug. The majority of medications don't work as intended in the later phases. This could be because to an unforeseen side effect of the medication, which could be caused by different gene components. There are several phases of drug development where pharmacogenetic studies can be applied. Pharmacogenetics can be used in clinical research to stratify patients according to their genotype, which is correlated with their ability to metabolize. This promotes improved clinical trial results and the avoidance of numerous adverse medication reactions. In the global context, the advancement of pharmacogenetics and pharmacogenomics in Western Europe is extremely significant. Many research groups made up of basic and clinical researchers have been actively working in this subject for decades despite the typically minimal institutional backing. Their work had a global influence and cleared the path for additional research and pharmacy. In neurodegenerative illnesses, the use of genetic background as a predictor of therapeutic response is a relatively new and unexplored area. Even though sporadic degenerative illnesses have a complex etiopathogenesis, current understanding indicates that genetics is primarily responsible for directing the pathological events and even significantly altering the disease phenotype from patient to patient. Genes can function as regulatory factors that alter the strength and severity of pathogenic processes or the response to medication treatment, or they can work as susceptibility factors that raise the likelihood of disease development. Applying this knowledge to develop more targeted and efficient treatments and to customize therapy for each patient based on their genetic profile is the aim of pharmacogenomics.

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Advancing Neurodegenerative Disorder Treatment through Pharmacogenetics: A Personalized Medicine Approach

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This study presents a comparative analysis of fuzzy logic and traditional statistical methods for evaluating academic performance, focusing on the application of fuzzy membership functions. In traditional methods, such as the use of weighted averages, student performance is assessed based on fixed boundaries, often leading to rigid and sometimes unrealistic evaluations. In contrast, fuzzy logic provides a flexible framework that allows for the modeling of uncertainty and partial truth by employing membership functions that categorize performance levels like "Poor," "Average," "Good," and "Excellent" with varying degrees of membership. Using a case study of students' test and project scores, this research demonstrates how fuzzy logic-based evaluations can offer more nuanced and context-sensitive assessments compared to conventional statistical approaches. By analyzing the impact of different fuzzy rules and membership function shapes on the overall performance scores, the study highlights the advantages of fuzzy logic in capturing the complexities of academic performance. The results show that fuzzy logic provides a more adaptable and informative evaluation, especially when dealing with ambiguous or borderline cases, thereby offering a more realistic alternative to traditional methods.

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Fuzzy logic, statistical methods, academic performance evaluation, fuzzy membership functions, comparative analysis, test scores, project scores, partial truth, rule-based decision-making

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Physicists such as Sir Isaac Newton through the prism experiment, Rayleigh through the gas tube experiment, Tyndall through the scattering of light by particles in a colloidal solution experiment, C.V.Raman through the solution mixed water tube experiment have given explanations that due to the scattering and refraction of the light as it flows through the medium, the colors in the light are seen separately at different wavelengths. But according to this, there is no explanation for the fact that natural blue color in the sky appears to be much more diffused in space above the clouds and the sun, the colors yellow orange red are seen only on the clouds, the green color is not visible and many other information about the colors are not clear. The scattering and refraction of light described by physicists are some information related to the flow of light. But because the particles in the medium have different densities and the light passing through these particles has different intensities, the transparency translucency and opacity in the particles of the medium are the information about the effect of light. This report provides information on scientific explanations and experimental explanations of prism using black-and-white strips which confirms that the colors are indirectly arising because of the optical effects of white color when light passes through particles of mediums having different densities exposed to light and dark black colors when light intensity is low.

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Light & Dark, Inverse square law of light, Light Medium, Atmosphere Particles, Density of Medium, Intensity of Light, Light Effect, Optical effect, Transparent Prism, Total Internal Reflection/Critical angle, Spectrum, Primary -Secondary color wheel.

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This study aimed to study the effect of Ethnomathematical Teaching on Numerical Ability of Secondary level students. To study the effect the Quasi-Experimental method was used. A sample of 60 students of class VIII from a School of Thiruvarur(Dt.), Tamil Nadu was selected through purposive sampling. The researcher has used lesson plans based on Ethnomathematical Teaching and for the collection of Data; the researcher constructed a tool to check the numerical ability of the students, named Numerical Ability Test. The statistical techniques used to find the effect was t-test and found there exists a significant effect of Ethnomathematical Teaching on Numerical Ability of Secondary Students.

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Ethnomathematical Teaching, Numerical Ability, Secondary Students.

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The nation's first female educator and social reformer, Savitribai Phule, imparted this lesson. Savitribai made significant contributions to women's literacy and education. Despite the harsh obstacles presented by patriarchy and conservatism, she paved numerous new avenues for women's empowerment. She brought women's consciousness to a new level and established new avenues for independence. She is renowned for encouraging education among Dalits as well. In the 19th century, she spoke out against the restrictive social structure that dominated Pune, Maharashtra. Her contribution focused on human causes like equality, truth, and humanity as well as rationality. Savitribai Phule was a trailblazing advocate for women's rights and social transformation.

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Social Reformer, Women's education and rights , Value Education .

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H.A. Roberts made significant contributions to homeopathic repertory through meticulous research and compilation of symptoms and remedies. His work focused on enhancing the accuracy and utility of repertory tools, thereby aiding homeopaths in selecting appropriate remedies based on individual symptoms. Roberts' systematic approach and comprehensive understanding of Materia medica enriched the field, laying a foundation for effective homeopathic practice and education.

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Homoeopathy, H. A. Robert, Repertory

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Lung cancer is one of the most killer diseases in the developing countries and the detection of the cancer at the early stage is a challenge. Analysis and cure of lung malignancy have been one of the greatest difficulties faced by humans over the most recent couple of decades. Early identification of tumor would facilitate in sparing a huge number of lives over the globe consistently. This paper presents an approach which utilizes a Convolutional Neural Network (CNN) to classify the tumors found in lung as malignant or benign. The accuracy obtained by means of CNN is 96%, which is more efficient when compared to accuracy obtained by the traditional neural network systems.

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Lung cancer, Computed Tomography, Chest CT image, Neural Network, Deep Learning, Convolutional Neural Network

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Forensic Odontology is a branch of Forensic Sciences, which deals with identification of individuals through their dental as well as their palatal structure as it is unique for each individual. Forensic Odontology plays an integral role in the identification of individuals especially in the cases of mass disasters and crimes against humans. The recent advancements in technology as well as Artificial Intelligence have been playing a huge role in the process of identification of individuals through Forensic Odontology. These advancements in the field of Forensic Odontology have not only made the process of identification of individuals much easier and faster but has also been helpful in the faster disposal of cases in criminal trials. This paper deals in detail with the recent technological advancements that have made the process of identification of individuals through the process of forensic odontology easier and quicker as compared to the manual and traditional methods as well as analyses how these technological advancements have made it easier for the courts to identify the offenders and award them the punishment accordingly. This paper also highlights the various cases in India which have used Forensic Odontology for the identification of offenders as well as cases where the evidence received through the different methods used in Forensic Odontology have been admitted as well as used by the courts in India for the faster disposal of cases and the nature and scope of Forensic odontology in India.

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Forensic Odontology, Technological Advancements, Artificial Intelligence, Criminal Trials, Dental Structure

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Virtual reality (VR) is a technology which allows a user to interact with a computer-simulated environment, whether that environment is a simulation of the real world or an imaginary world. This paper explores the transformative role of Virtual Reality (VR) in the fashion and retail sectors, highlighting its potential to reshape consumer engagement, sales strategies, and operational efficiencies. Virtual reality offers immersive experiences, enabling customers to virtually try on clothing, accessories, and even participate in runway shows from anywhere in the world. VR-powered virtual try-ons address key challenges, such as improving fit accuracy and reducing product returns, while enhancing personalization and convenience in both online and in-store shopping experiences. This technology allows customers to see how garments appear and fit in real-time, bridging the gap between digital and physical retail. Furthermore, VR empowers fashion brands with virtual showrooms, creating unique opportunities for showcasing collections and storytelling, and expands the boundaries of creativity with digital-only fashion. However, the adoption of VR presents challenges, including high development costs and accessibility barriers for certain consumers. This paper evaluates the impact of VR on brand-consumer interaction, compares its efficacy against traditional retail methods, and examines emerging trends in virtual commerce, such as NFTs and digital influencers. Through case studies, data analysis, and expert perspectives, the research concludes with recommendations for leveraging VR technologies in sustainable, cost-effective ways to enhance customer satisfaction and competitive advantage within the fashion and retail landscape.

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Virtual Reality (VR), Fashion and Retail, Immersive Experiences, Virtual Try-ons, Personalization, Virtual Showrooms, Sustainability

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This study explores the utilization of advanced data analytics techniques to extract actionable insights from large-scale educational datasets, aimed at informing decision-making and facilitating personalized learning interventions. Through the analysis of diverse data sources including student performance metrics, demographic information, and learning behaviors, this research seeks to uncover patterns, trends, and correlations that can enhance educational practices. The study investigates the development and validation of predictive models for forecasting student performance, as well as the ethical and privacy considerations associated with data analytics in education. By synthesizing existing literature and empirical research, this study provides insights into the potential of data analytics to transform education, fostering a culture of evidence-based decision-making and supporting the implementation of tailored interventions to meet the diverse needs of learners. Ultimately, this research contributes to the ongoing discourse on leveraging technology and data-driven approaches to promote educational equity, improve student outcomes, and advance teaching and learning practices

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Data analytics, Learning behaviors, Digital learning, educational datasets

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Background: The World Health Organization classifies young people as 10-24 years old with adolescence (10-19yrs) and (15-24yrs). The adolescent period is a time for developing independence. It is a transitional stage of physical and psychological development that usually occurs during the period from puberty to adulthood. The adolescent's behavior varies within the time period that defines the stage of development and differs by sex and setting. The behavior are influenced by a range of factors including individuals self-esteem, skill, knowledge, beliefs, caregiver, peers and teachers, schools, economic status, folk's beliefs. Perception of sights, sense of future, and the media. Aim: "A study to evaluate the effectiveness of structured teaching program on knowledge regarding management and prevention of selected behavioral problems of adolescents among students studying in a selected nursing college in Mangalore". Objectives: 1. To assess the students' knowledge regarding management and prevention of selected behavioral problems in adolescence. 2. To evaluate the effectiveness of structured teaching program on management and prevention of behavioral problem in adolescents among nursing students. 3. To find out association between pretest knowledge score of students regarding management of adolescent behavioral problem with selected demographic variables Such as age in year, gender, religion, education status of parents, occupation of parents, monthly income of the family, type of family, Source of information on management and prevention of behavioral problems, Area of residence. Methodology: A quantitative research approach and comparative research design were used .A total of 60 adolescent boys and girls were chosen from the selected college of Srinivas Institute of Nursing Sciences by convenient sampling technique. A pre and post questionnaire was used to assess the behavioral problems and 81.7% of adolescent had poor knowledge and in posttest 3.3% of adolescent's had poor knowledge in selected behavioral problems. Results: Among 60 adolescents 49. (81.7%) of adolescent had poor knowledge in pre-test , 11 (18.3%) had moderate knowledge and none of the adolescents had good knowledge of selected behavioural problems whereas in post-test had mode 49(81.7%) rare knowledge and 22 (36.7%) had good knowledge, It was concluded that there was an improvement in knowledge regarding management and prevention of selected behavioural problems and none of the adolescent. Conclusion: The study concludes that adolescents studying in college were having behavioral problems. Substance abuse was found to be the least common behavioral problems among adolescent boys and girls.

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Behavioral problems, Adolescent boys and girls, college.

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Agriculture is the process of growing food to feed the masses. In modern day, agricultural practices have been trying to adopt technologies that can give a better yield, predict returns and also mitigate losses. Farmers are adopting trends and are trying to catch up with the growing market requirements. Supply chains have to improve the nutrient content. Data acquisition and processing form the important challenges to improve productivity, resource utilization. The lands are generally enormous and communication can get tricky since there are costs involved. However wireless technologies such as LoRa, Zigbee etc are showing promise. This paper tries to understand the advancements made in agriculture in the recent times and the best practices that are giving good results.

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Agriculture, Wireless sensor networks, Security, AI/ML, Internet of Things (IoT).

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For small sigma asymptotic approach due to Kadane and Shukla studies he properties of two families of estimators considered by Srivastava and Chandra from the idea of concentration probabilities of estimators around the two unknown parameters stochastically restricted a linear regression model. To analyses the properties of more generalized classes of estimators by Sing et.al (1995) from concentration probabilities theme choice of an estimator.

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Quadratic Risk Criterion, Stochastic, Regression, Exact linear constraints, Coefficient vector.

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Due to their numerous advantages, people have recently started to show increased interest in herbal medicines.

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Herb , Extraction, chromatographic methods , standardization.

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This study examines the impact of karaoke singing, specifically retro melodies, as a form of music therapy on mental health, anxiety, cognitive function, and social well-being. Using a mixed-methods approach, the research evaluates how engaging in karaoke influences stress levels, mood, anxiety, and cognitive performance. The findings reveal that karaoke singing significantly alleviates symptoms of anxiety and depression while enhancing mood and cognitive function. The study also explores the role of karaoke as a therapeutic tool for individuals with dementia and Alzheimer's disease, showing its potential to stimulate memory recall and support emotional well-being. Furthermore, the social benefits of karaoke--through fostering social interaction and community building--are highlighted, demonstrating how it can reduce feelings of loneliness and promote a sense of belonging. By connecting music, nostalgia, and therapy, this paper emphasizes the potential of karaoke singing as an accessible and enjoyable intervention to enhance mental health and overall well-being.

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Karaoke singing, music therapy, retro melodies, mental health, anxiety reduction, mood enhancement, cognitive function, social well-being, dementia, Alzheimer's disease, nostalgia, community building, therapeutic intervention.

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This study assessed the knowledge of higher secondary students in Hajo Block, Kamrup, Assam, regarding the harmful effects of cigarette smoking. A descriptive research design and purposive sampling were used to include 60 students from two schools, with data collected using a structured questionnaire. Most participants (86.7%) were aged 16-18, 91.7% were male, and 60% were Muslim. The majority had average knowledge (85%) about the harmful effects of smoking, with no significant associations found between knowledge levels and demographic variables. The findings highlight the need for targeted awareness programs to improve understanding and reduce smoking-related risks among youth.

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ASSESSMENT OF KNOWLEDGE REGARDING HARMFUL EFFECTS OF CIGARETTE SMOKING AMONG THE HIGHER SECONDARY STUDENTS OF HAJO BLOCK, KAMRUP ASSAM.

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