Volume 12 | Issue 3

 Abstract

The escalating prevalence of diabetes globally has positioned it as a significant contributor to mortality rates. Elevated blood glucose levels and insulin resistance are implicated in a spectrum of health complications, encompassing cardiovascular diseases, renal dysfunction, neuropathies, and diabetic retinopathy--a debilitating condition marked by vision impairment. Early detection serves as a pivotal determinant in mitigating the progression of diabetic retinopathy and averting irreversible visual impairment. Consequently, the imperative for a robust screening methodology becomes apparent. To this end, a comprehensive investigation into deep learning strategies has been undertaken. Leveraging publicly available datasets, our research ends have focused on the acquisition and reprocessing of data pertaining to diabetic individuals. Furthermore, the development of sophisticated machine learning algorithms, including deep neural networks such as Convolutional Neural Networks (CNNs), has been instrumental in refining our screening approach. The culmination of these efforts has yielded promising outcomes, as evidenced by the system's proficiency in accurately discerning normal retinal images from those indicative of aberrant pathology with a remarkable degree of certainty. In conclusion, the integration of advanced technologies, such as deep learning and machine learning, holds considerable promise in revolutionizing diabetic retinopathy screening protocols. By harnessing the power of these methodologies, we can enhance early detection, facilitate timely intervention, and ultimately ameliorate the burden of diabetic retinopathy on global visual health outcomes

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Diabetic Retinopathy, Deep Learning, KNN, CNN

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In today's globalized world, effective cross-cultural communication is essential for success in various personal, academic, and professional endeavors. English language proficiency plays a significant role in facilitating communication across cultural boundaries. This paper explores the impact of English language proficiency on cross-cultural communication success, examining its influence on interpersonal interactions, academic achievements, and professional opportunities. By analyzing research findings and real-world examples, this paper highlights the importance of English language proficiency as a key determinant of success in cross-cultural communication.

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English language proficiency, cross-cultural communication, globalization, interpersonal interactions, academic achievements, professional opportunities.

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Image manipulation and forgery present significant challenges across various domains, including forensics, security, and media authentication. This is a novel approach that integrates Error Level Analysis (ELA) with Convolutional Neural Networks (CNNs) to differentiate between authentic and tampered images. Using the Cassia v2 dataset containing both real and fake instances, diverse data augmentation techniques, such as flattening, resizing, and converting images to ELA format, are applied to enhance model robustness. The dataset is partitioned into 80% training and 20% validation sets to facilitate comprehensive model training and evaluation. Utilizing Keras, a Sequential model is developed, incorporating Conv2D, MaxPooling2D, Dropout, Flatten, and Dense layers for effective feature extraction and classification. Training utilizes the Adam optimizer for parameter optimization. Evaluation metrics, including loss, accuracy, and a confusion matrix, are employed to assess model performance. Results demonstrate promising accuracy, with the model achieving 98.8% training and 92.8% validation accuracy, showcasing the efficacy of the proposed methodology in accurately distinguishing between real and fake images. This approach holds potential for applications in image forensics, security, and authentication domains.

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 Keywords

Fake images, ELA, CNN, Sequential model, Adam optimizer

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Social media nowadays is the 'best possibilities available' to an item to get in touch with potential customers directly. Community social networking sites are the method which is widely used to interact socially. In most cases, these new media won the belief and trust of customers by linking with them at a deeper level. Social media marketing is the new mantra for many manufacturers, wholesalers and retailers since early a season ago. Promoters are considering many various social media possibilities and arising with new social projects at a better frequency than ever before. Social media marketing and the companies that utilize it have become more intensified. The boom of social media trend is as amazing as that and the speed at which it is improving is incredible. International companies have identified social media marketing as a potential promotion system and began to use them with enhancements to power their marketing with social media promotion. This paper discusses about the awareness level of e-consumers in social media sites and the impact of social media advertisements on e-consumers. It also presents an outline on social media marketing in Coimbatore.

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Online shopping cart

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This paper provides a discourse on the crucial role played by folk songs in the transmission and preservation of cultural history and identity within the context of Nagaland. It is rooted in the pressing need and significance of safeguarding the extensive and meaningful folk songs that serve not only as musical compositions but also as potent agents of history and identity. These folk songs serve as invaluable repositories of cultural narratives, offering profound insights into the cultural heritage and way of life of the Naga people. The renowned Angami folk song "AvuNei Hu" is selected as the focal point of analysis in this paper to shed light on the intricate interplay between tradition, identity, and storytelling through music. This paper aims to highlight the enduring significance of folk music as a vital component of cultural heritage, emphasizing its role as a conduit for preserving and transmitting the rich cultural history and identity of Nagaland for generations to come.

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Oral Tradition, Folk Songs, Cultural Narratives

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Tuberculosis (TB) remains a pressing global health concern, demanding accurate diagnostic tools for timely intervention. This study introduces a ground breaking machine learning framework for TB detection, leveraging the K-Nearest Neighbors (KNN) algorithm. Utilizing a comprehensive dataset sourced from Kaggle, encompassing diverse demographic and clinical attributes of individuals suspected of TB, our research focuses on refining the KNN model to precisely classify TB-positive and TB-negative cases. Notably, our approach achieves an impressive accuracy of 95.12%, highlighting the robustness and efficacy of the proposed methodology. Through meticulous experimentation and rigorous evaluation, including cross-validation and independent test set analysis, we ascertain the reliability and generalizability of our model. Furthermore, our investigation delves into the impact of varying KNN parameters on performance, offering invaluable insights into parameter tuning strategies for improved TB detection. This study signifies a significant leap forward in TB diagnostics, demonstrating the potential of machine learning techniques to complement existing methodologies and enhance patient outcomes. The study's findings reveal the algorithm's potential as a significant advancement in medical imaging analysis, offering a promising tool for healthcare professionals in the early detection of TB. The integration of KNN into TB detection workflows could revolutionize the diagnostic process, leading to improved patient outcomes and a reduction in the global TB burden.

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 Keywords

Detection of Tuberculosis, Machine Learning (ML), K-Nearest Neighbors (KNN) algorithm, Image Classification.

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Water scarcity is a serious challenge for agriculture, which heavily relies on insufficient monsoon rains. To address this issue, an Internet of Things (IoT) and Machine Learning (ML) based smart irrigation system is proposed. This system predicts irrigation requirements using environmental parameters and weather forecasting, optimized by an ensemble ML method. The system reduces water, labour, and plant nutrient usage with a low-cost prototype achieving above 90% accuracy. A flexible IoT platform is designed to enable developers to easily integrate IoT and ML components for customized analytical methods in precision irrigation. This platform benefits both IoT specialists and farmers by reducing water waste, lowering costs, and ensuring safer crop yields. An intelligent irrigation system is implemented using an IoT-enabled ML-trained system for optimal water consumption. IoT sensors capture real-time ground and environmental data, which is analyzed by ML to provide irrigation minimizing human intervention.

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IOT, Smart Irrigation, Machine learning, Ensembling, Agriculture.

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Crime fiction has fascinated readers through the ages. This paper explores the changing portrayal of female characters in crime fiction. Early works often relegated women to stereotypical roles: the victim, the femme fatale, or the sidekick. Characters like Miss Marple and Miss Loveday Brooke offered glimpses of more complex heroines, but it was not until the mid-20th century that authors like Dorothy L. Sayers and Patricia Highsmith challenged gender norms with characters like Harriet Vane and Tom Ripley. The Silent Patient by Alex Michaelides serves as a case study. While Alicia Berenson, the accused murderer, displays psychological complexity, she remains somewhat limited. Kathy Faber, Theo Faber's wife, embodies a different stereotype - the cheating spouse. In contrast, Clarice Starling from Thomas Harris' The Silence of the Lambs exemplifies a more modern heroine. Intelligent, resourceful, and haunted by her past, Clarice navigates a male-dominated world with both strength and vulnerability. By analysing both characters through Eysenck's PEN model, the paper highlights the enduring influence of past portrayals while celebrating the emergence of multifaceted female characters who challenge expectations and drive the genre forward.

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Crime fiction, The Silent Patient, The Silence of the Lambs, Eysenck's PEN model

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In Gudiyatham Taluk, out of total population, 180,971 were engaged in work activities. 83.5% of workers describe their work as Main Work (Employment or Earning more than 6 Months) while 16.5% were involved in Marginal activity providing livelihood for less than 6 months. Of 180,971 workers engaged in Main Work, 10,209 were cultivators (owner or co-owner) while 27,078 were Agricultural labourers.

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Atthi, Rural Clinic

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In recent years, there has been a growing recognition of, open jails or open correctional institutions, as a potential solution to these challenges. This research paper aims to examine the necessity and viability of open prisons in India, by exploring their potential benefits, legal frameworks, and socio-economic implications. This research paper attempts to provide a comprehensive analysis of the need for open prisons in India, as They have the potential to address the issue of overcrowding, promote rehabilitation and reduce recidivism rates. However, their implementation needs to be accompanied by a strong regulatory framework and supportive policies to overcome the associated challenges. As the country moves towards a more progressive criminal justice system, open prisons can play a crucial role in making rehabilitation and reintegration a reality for inmates. Further research in this area can help refine and improve the efficacy of open prison systems in India.

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Open prisons, Prison reform , Rights of accused

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A study was conducted to identify the reasons for people avoidance of seeking medical care and to classify these reasons into conceptually distinct categories reflecting underlying factors contributing to avoidance. The aim of the study is to identify the factors contributing towards delay in seeking medical care among people residing in selected areas of district Mohali, Punjab. A quantitative research approach with descriptive research design was adopted. By using convenient sampling technique, 250 people were selected. Study showed majority of people's age i.e. 32% were in the age group of 28-37 years. Gender distribution of sample revealed that majority of samples were male i.e. 57%. 30% have educational qualification of graduation and above followed by 29.6% having up to senior secondary. Most of the people i.e. 30.8% were government employee. 55.6% were unmarried. Sample consisted of people who were not diagnosed with any disease by physician and avoided visiting doctor or seeking medical care when they suspect they should. Factors for delay in seeking medical care were identified and were categorized into personal, financial, transportation, psychological, perceptional, medical, traditional and cultural factors. Frequency and percentage distribution of these factors were calculated and they have been presented with help of figures.

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, factors, delay, seeking medical care, people .

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The incorporation of Social Commerce (S-commerce) into the domain of Educational Technology (EdTech) has precipitated substantial changes in the manner in which learners, educators, and students engage with digital educational platforms. By leveraging the social and collaborative aspects of learning, S-commerce in EdTech enhances the educational experience through the use of user-generated content, peer recommendations, and social engagement. Furthermore, this paradigm shift carries significant ramifications for the intention to use the product. It is crucial to analyse utilization intention in the context of S-commerce in EdTech to comprehend how social and collaborative dynamics influence the adoption and efficacy of educational technology. This publication provides valuable perspectives on the dynamic nature of digital education and its influence on the goals of both instructors and students. Usage Adoption and Usage Purchase Intention both appear to influence usage intention, according to the findings of the present study. However, the hypothesis that usage information influences usage intention is refuted. The results may have been affected by constraints in our data acquisition methodologies or the particular measures employed for Information Factors. Upon integrating the aforementioned data, it becomes evident that although informational factors may not have a direct impact on usage intention, user-centric factors that contribute to the adoption of usage and factors associated with price and products/services significantly influence the overall user intentions in e-commerce. The implications of these disclosures for platform designers and practitioners are substantial. Ensuring competitive pricing and high-quality products/services, prioritizing user-friendly design, and accentuating platform usability are critical strategies for enhancing user engagement and, consequently, increasing students' overall intention to utilize S commerce platforms.

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s-commerce, usage intention, usage information, EdTech

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The crankshaft is one of the essential components of an internal combustion engine, in which the reciprocating motion of the piston is converted into rotary motion through the connecting rod. The current work consists of two types of analysis. In the first part of the study, strength analysis on a single cylinder four stroke diesel engine crankshafts. The best combination of parameters like Von Mises stress, deformation and weight reduction for crankshaft is carried out. In the second part of the study, two materials namely structural steel and aluminium alloy are selected for analysis and comparison of these two materials properties such as Von-Mises stress, strain and total deformation were determined and results were compared. Crankshaft needs to be checked carefully to ensure that the design is fully optimized for that optimization of the crankshaft is studied and changing the geometry and shape of the existing crankshaft. In the present work CAD model of the crankshaft has been designed in the AUTOCAD 2016 software and then finite element analysis (FEA) has been carried out by using ANSYS 15.0 workbench software. Static analysis of crankshaft is done to find the maximum stress and deformation point.

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Structural Steel, Crankshaft, ANSYS, Finite Element Analysis.

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The pharmaceutical enterprise, an imperative pillar of world healthcare, confronts a complicated and pressing mission at the intersection of fitness, environment, and economics: sustainable waste control. This complete examination embarks on a problematic adventure to discover and deal with the multifaceted facets of this urgent trouble inside the pharmaceutical region. We delve deep into the labyrinth of pharmaceutical waste, scrutinizing the numerous categories and myriad sources. With a meticulous lens, we assess the environmental toll, quantifying the industry's impact on international sustainability. Financial repercussions loom massive as we delve into the price dynamics and regulatory intricacies that form waste management practices. Amid this backdrop, we cast our gaze upon innovation, examining contemporary waste answers and the transformative strength of generation. They have a look at traversing borders to get to the bottom of the pharmaceutical industry's position in international sustainability tasks and the forging of impactful go-region collaborations. But we do not forestall at evaluation; we confront demanding situations head-on. Regulatory complexities, supply chain collaboration, and the economics of sustainability are laid bare. Through real-global case studies, we unearth practical insights that exemplify fulfillment tales and highlight training found out. The study culminates in a compendium of hints and fine practices, paving the course toward greater ecologically conscious and socially accountable pharmaceutical waste management.

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Pharmaceutical industry, Waste management, Sustainability, Environmental impact, Technological advancements, Global initiatives

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In recent years, there has been a steady rise in the number of road accidents in India, resulting in a rise in injuries and fatalities. Particularly, the failure of motorcyclists to wear helmets is one of the significant contributors to severe injuries and casualties in road accidents. The rise in population and the growing number of motorcyclists on the road have made police patrolling challenging and labor-intensive. The proposed system aims to address this issue by developing a specialized computing model designed to identify motorcyclists not wearing helmets. Upon successful detection, the system promptly retrieves the vehicle's number plate and transmits this vital information to relevant authorities for necessary action. This involves issuing an automated challan to the violator and stating the reason for the fine. The application utilizes the YOLO (You Only Look Once) computer vision algorithm, known for its efficiency in real-time object detection and classification. Recently, a new version of the YOLOv8 algorithm has been developed by Ultralytics, taking into account the limitations of its predecessor models. With a focus on speed, accuracy, and user-friendly design, YOLOv8 is a robust choice for various computer vision tasks. Its capabilities extend to object detection and tracking, instance segmentation, and image classification, demonstrating a flexible and high-performance solution for diverse applications. This integration of technology tackles the critical issue of helmetless driving, thereby promoting road safety by enhancing stricter measures. By automating the identification and penalty processes, the proposed system aims to optimize enforcement efforts, ensuring a safer environment for all commuters.

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Road accidents, injuries, fatalities, helmet non-compliance, computer model, YOLOv8, real-time object detection, automated challan, road safety, enforcement automation.

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Ophthalmic problem is becoming very common globally over 2 billion people suffer from vision impairment. Eye drop are the most inexpensive ophthalmic formulation. Dry eye syndrome is one of the prevalent cause for irritant feeling in eyes. Dry eye syndrome is an interpalpebral ocular surface problem also called as Keratoconjuctivitis sicca, which cause damage to interpalpebral eye surface due to deficiency of tear or uncontrolled evaporation. Resulting in the damage to the ocular surface which is getting worsen day by day. There are several preparation of eye drop for dry eye condition. There are several studies which are currently being explored with much focus on adjusting the formulation of eye drop to enhance the retention time in the eye. Castor oil is used for its anti inflammatory and lubricant effects, it has been found that it helps in maintaining the lipid layer of tears called as tear film lipid thickness and helps in increasing tear film lipid layer stability. My review objective is the preparation of eye drop containing castor oil as the active ingredient, excipents and preservatives from preventing the microbial growth. the evaluation parameter such as ph, clarity, sterility, viscosity, surface tension were studied to identify the stability of the eye formulation.

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Keratoconjuctivitis Sicca, Castor Oil, Lubricant, Eye Drop

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The purpose of this paper, is to introduce and study the micro binary topological spaces. The notions of Micro Binary open sets, Micro Binary closed sets, Micro Binary interior, and Micro Binary closure are introduced and their basic properties are discussed with suitable examples.

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Micro Binary Topology, Micro Binary open sets, Micro Binary closed sets, Micro Binary interior, Micro Binary closure, and Micro Binary Continuity.

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LearnUp stands as a virtual sanctuary where students and professors convene to form a vibrant and enriching online community dedicated to the pursuit of knowledge and academic excellence. This innovative platform reimagines traditional learning by seamlessly integrating technology, fostering collaboration, and facilitating the exchange of ideas among its members. The creation of an online community tailored for students and professors in academia is underway. Our platform aims to cultivate an environment that encourages substantial discussions while integrating AI-assisted virtual mentors to enrich the learning experience. By harnessing cutting-edge technologies, we aspire to craft an interactive and vibrant space that fosters collaboration and knowledge sharing. Our focus remains on creating an ecosystem that empowers academic growth, providing a unique and innovative avenue for mentorship and exchange among the academic community

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none

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The National Policy on Education, 1986 which states that Continuous and Comprehensive Evaluation (CCE) should include both scholastic-based and non-scholastic aspects of the evaluation a full classroom assessment system should put in place at National Curriculum Framework of 2005. The CCE refers to a school-based assessment which covers aspects related to student's development. It emphasizes the two-fold objectives such as continuity of evaluation and assessment of learning outcomes in a comprehensive manner. The CCE is an assessment procedure mandated by the RTE Act, 2009. An effort to reduce the stress and fear of the examination, Continuous and Comprehensive Evaluation (CCE) has been recommended by different policy documents from time-to-time at the national level. The Right of Children to Free and Compulsory RTE Act 2009 provided hope and vision to this Section 29(2) of the RTE Act-2009 requires that the guidelines of curriculum and evaluation procedures are laid down by the appropriate academic authorities. The CCE system was introduced in 2009 by the Central Board of Secondary Education (CBSE) with the enactment of the RTE Act, 2009 in order to achieve holistic development among students and helps teachers to systematize their strategies for effective teaching.

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NPE, CCE, CBSE, RTE Act, NCF, Curriculum, Assessment, Formatives Assessment, Summative Assessment, Grades, Competencies, Responses, Project work, Academic Standards

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In the 21st century the word 'trauma' is not only used as a homogenous medical concept but also considered as a multidimensional psychological and moral idea. Earlier it meant the physical injuries caused by the 'shocking event'. From that perspective, it was referring to only 'shock', letting the people paralyze in response. That's what is implanted in the common people - 'trauma' means 'shock'. The change did not take place until the emergence of Freud's psychological study of hysteria and unconsciousness in the 1920s. Following him, this stereotypical illusion gets vagued with further analysis of 'trauma' by different distinguished theorists such as Cathy Caruth, Michael Alexander, Dominick LaCapra, etc. The study of psychological trauma steers at high speed especially after the Second World War. The journey does not even stop here. Parallelly it glides into its transitional moral phase after the 1970s. Here it extends its wing in any protest and violence, be it regional racial or religious, or communal. The ethical values fade away and moral judgment gets challenged. Thus, this paper aims at presenting all of these transitional phases including the discussion of socio-cultural-political dimensions. The 'mobility' in this field galvanizes the connection of different discourses simultaneously. It also focuses on the interconnection of diverse genres and generations with their heterogeneous lenses and temperaments.

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 Keywords

Trauma Studies, Medical, Psychological, Moral, Multidimensional, Multidisciplinary, Multigenerational

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