Volume 13 | Issue 1 |

 Abstract

This paper develops effective school-based career counseling and guidance programs that help students make informed choices about their future careers. The paper draws attention to integrating modern technologies such as decision-making algorithms, interactive quizzes, and web-based platforms in order to provide personalized career guidance. The proposed system uses academic performance data and aptitude assessments to give recommendations tailored to the needs of each student, ensuring that everyone in the system receives proper guidance for their career.

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CAREER COUNSELING, STUDENT GUIDANCE, DECISION TREE ALGORITHM, PERSONALIZED RECOMMENDATIONS, ACCESSIBILITY.

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Creative Commons Attribution 4.0 and The Open Definition

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???? ??????? ?????? ?????????????? ?????????, ???????? ??????? ??????? ???????????? ???????????? ???????????? ?????????. ??? ??? ???????????? ?????????????? ?????????????? ????????????? ??????????????????. ?????????, ?????????????????????? ?? ????????????? ??? ????????? ????? ????????? 17-?? ?????????? ??????????? ?????????????? ???????, ?????????? ??????????? ??????. ?? ??????????? ???????? ????????????? ??????? ??????????? ??? ??? ???? ??????????? ???????? ?????? ????? ?????????????????????? ???????? ????????? ????? ??????? ?????????? "????????????" ????????? ??????? ?????????? ???????????? ??????????????.

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Poetry plays an essential role in learning English literature by providing a rich avenue for linguistic, cognitive, and emotional exploration. As a unique form of expression, poetry challenges learners to engage with language in creative and multifaceted ways, enhancing both their understanding of the English language and their ability to interpret complex ideas. Through its rhythmic structure, figurative language, and compact yet profound expressions, poetry deepens vocabulary, cultivates critical thinking, and fosters a greater emotional connection to the themes explored. Beyond its linguistic value, poetry offers cultural and historical insights, enabling students to explore the socio-political contexts of different eras and cultures. The abstract nature of poetry encourages learners to develop interpretive skills and to engage in self-reflection, cultivating empathy and emotional intelligence. In essence, poetry enriches the study of English literature by promoting intellectual growth, emotional awareness, and a deeper understanding of human experience, making it a fundamental component of a well-rounded literary education

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Poetry, English literature, language development, cognitive skills, emotional intelligence, critical thinking, interpretation, vocabulary expansion, figurative language, cultural insight, historical context, empathy, self-expression, creativity, imagination, universal themes, identity, personal reflection, literary devices, rhythm, social issues, emotional connection, personal growth, engagement, poetic form, language play.

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The integration of artificial intelligence (AI) with optical biosensors has been an introduction to a new era in biomedical diagnostics, offering potential capabilities for the early detection of cancer, and precision and accurate retinal imaging. This review critically examines the transformative blend between AI algorithms and optical biosensing technologies, including surface plasmon resonance (SPR), fluorescence spectroscopy, and optical coherence tomography (OCT). These systems provide non-invasive, high-sensitivity diagnostic platforms capable of detecting subtle biomolecular interactions and imaging minute cellular structures, crucial for addressing the global burden of cancer and vision-related diseases. AI-powered optical biosensors enhance advanced computational techniques such as deep learning, convolutional neural networks (CNNs), and generative adversarial networks (GANs) to process complex datasets, optimize signal interpretation, and enhance diagnostic accuracy. SPR, known for its precision in detecting biomarker interactions, faces challenges like noise interference and high operational costs, which AI addresses by improving signal-to-noise ratios and automating data analysis. Similarly, fluorescence-based biosensors benefit from AI-driven algorithms to counteract limitations such as photobleaching, spectral overlap, and false positives. In retinal imaging, OCT achieves remarkable resolution, yet struggles with artifacts and restricted visualization scopes, which AI alleviates through real-time motion correction, enhanced depth resolution, and predictive imaging techniques. This review also compares the relative strengths and limitations of various AI-augmented optical biosensors, emphasizing their practical applications in clinical and research settings. Key challenges include the need for standardized datasets, the ethical implications of AI deployment, and barriers to widespread adoption due to cost and infrastructure requirements. Future innovations are anticipated to include hybrid biosensor platforms that integrate multiplexed detection capabilities, AI-enhanced multimodal imaging, and adaptive learning models capable of personalizing diagnostic outputs to individual patient profiles. In conclusion, AI-empowered optical biosensors represent a paradigm shift in diagnostic science, combining the precision of optics with the predictive power of AI to redefine early disease detection and management. Addressing current limitations through interdisciplinary collaboration and technological advancement will be pivotal in achieving scalable, cost-effective, and universally accessible solutions, thereby transforming healthcare delivery on a global scale.

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Artificial Intelligence, OCT, Biosensors, CNN's and GAN's, SPR, Fluorescence spectroscopy, optical interferometry

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Marketing encompasses all efforts a company makes to drive sales of its products and services. Advertising, a paid form of non-personal communication, is a key component of most marketing strategies. Technological advancements have significantly reshaped marketing approaches. With the internet deeply integrated into daily life and online shopping a common activity, companies increasingly advertise online to rapidly reach consumers. This surge in internet usage has created substantial opportunities for online retailers and, consequently, online advertising. This study examines the influence of internet advertising on online buying behavior, focusing specifically on 150 respondents in Irinjalakuda town.

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Creative Commons Attribution 4.0 and The Open Definition

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Internet advertising, Online buying, online retailers, marketing approaches

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Creative Commons Attribution 4.0 and The Open Definition

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?????? (Abstract) ??? ??????: ?????? ???????? ?? ????????? ?? ??????? ?? ??????: ????????????? ??????? ?? ??? ???? ?? ???????? ?????? ???????? ?? ??? ??????? ?? ?????? ?? ??? ?????????? ?? ???????? ???? ??? 1991 ??? ???? ??? ?????? ???????? ?? ?????? ?? ???, ?????????, ??????? ?? ???????? (LPG) ?? ???????? ?? ?????? ???? ?? ???????????? ??? ?????????? ????? ??? ???? ????? ??? ?? ??????? ?? ??? ?? ???????? ??????? ???????? ?? ???? ??? ???? ?? ?????? ????? ?????????, ?????? ??????, ?? ??????? ???????? ??? ???????? ?? ???????? ??? ??? ??? ??????? ?? ??? ?????????, ??????, ???? ?????, ?? ????????? ?? ???????? ??? ?????? ?? ????????? ?????? ?? ??? ??? ???????? ???? ??? ??, ???? ??????? ??????? ??? ????, ?????? ???? ????, ?? ???????? ??????? ?????? ?? ??? ??? ????????? ???????? ?? ?? ?????? ???? ??? ??? ??????? ?? ???? ??????? ?? ?????? ???????? ?? ???-??? ?????? ???? ??, ???? ???? ??????? ???? ?????? ?? ??? ????? ???, ???? ??????? ??????? ?? ?? ?? ????? ???????? ?? ?????? ?? ????? ???? ????? ??? ?? ??? ??? ?????? ???????, ????? ????????? ?? ??? ???????, ?? ????????? ?? ??????? ?????? ?? ??????? ?? ?? ??? ??? ??, ?? ?? ????? ???? ??? ?? ?? ????? ???????, ??????, ?? ???? ????? ?? ?? ????? ???? ?? ???????? ??, ???? ????? ???? ?? ?? ???????? ?? ?????? ?? ??? ?? ?????? ?????? ?? ??????????? ???? ?? ???? ??? ?? ???????? ?? ?? ?? ?????? ???????? ?? ??? ???? ??? ??????? ?? ?????? ??? ?????????? ????? ??? ??, ????? ???????, ?????????? ?? ?????????? ??????? ?? ???????? ?? ???? ??????? ?? ???? ???? ?? ??????? ??? ???? ?? ??? ???? ?? ????? ??? ??????? ?? ?????? ?? ??????? ?? ?????? ????? ????? ?? ???? ??? ?????????? ?????? ?????? ???? ??? ????? ????: ?????? ????????, ????? ?????????, ?????????, ?????? ??????, ???? ?????, ??????, ???? ?????, ????????? ???????, ??????? ?? ???? ???????, ????.

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????? ????: ?????? ????????, ????? ?????????, ?????????, ?????? ??????, ???? ?????, ??????, ???? ?????, ????????? ???????, ??????? ?? ???? ???????, ????.

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Mental health remains a pressing global issue, affecting individuals, families, and communities. Social workers play a pivotal role in addressing these challenges through advocacy, intervention, and prevention strategies. This paper examines the intersection of mental health and social work, exploring historical contexts, contemporary issues, and the future of collaborative care. The study emphasizes the importance of holistic approaches, effective methodologies, and evidence-based practices to enhance outcomes for individuals experiencing mental health challenges.

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evidence-based practices

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INTRODUCTION-Chronic non-specific low back pain (CNSLBP) brought on by acute or chronic lumbar diseases can affect the way the body is built and how it moves and functions, resulting in decreased mobility, endurance, and muscle strength. CNSLBP can affect balance and proprioception which eventually can have a huge impact on quality of life as well as fear of fall in the patients. So, it is necessary to assess these components in patients having chronic non-specific low back pain using appropriate method. AIMS AND OBJECTIVES: To determine the association of balance and lumbar proprioception with quality of life and fear of fall in patients with chronic non-specific low back pain. METHODOLOGY: In the present correlational study, total 46 patients with chronic non-specific low back pain with age between 20-45 years were included. Sample size calculated was 42, with a drop out chances of 10%, the total sample size was 46. Patients were evaluated for static balance (EO and EC), anticipatory balance and dynamic balance using Unipedal Stance Test (UPST), Functional Reach Test (FRT) and Five Times Sit To Stand Test (FTSTS Test) respectively. Lumbar proprioception was assessed by Joint Repositioning Error method (JRE). Quality of life and fear of fall were assessed using 12- item Short Form Survey questionnaire and Fall Efficacy Scale- International (FES - I) questionnaire respectively. Statistical analysis was done by using SPSS 26.0 version. Significance level was set at p<=0.05. RESULT: The study was conducted on 46 subjects with 23 male and 23 female having chronic non-specific low back pain. The data were ensured for their normal distribution using the Shapiro-Wilk Test. Pearson Correlation test as the parametric test was performed to see the relationship between all the variables and it showed that there were significant correlation i.e. either negative or positive correlation present between all the variables. There was a positive correlation present between balance and quality of life as well as with fear of fall. Whereas, there was a negative correlation present between lumbar proprioception with quality of life but positive correlation with fear of fall. CONCLUSION: So, study concluded that there was significant association found between balance with quality of life and fear of fall, signifying more the balance score less will be the fear of fall and improved quality of life. Also, lumbar proprioception was associated with quality of life and fear of fall showing that less the pelvic tilt, less there will be the risk of fall and hence, improved quality of life.

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chronic non-specific lbp, lumbar proprioception, quality of life

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Customer segmentation and behavior prediction play pivotal roles in enhancing business strategies, personalizing marketing campaigns, and optimizing inventory management in E-commerce platforms. This research focuses on analyzing a comprehensive E-commerce dataset containing transactions of ~4,000 customers over one year to uncover purchasing patterns, classify customer types, and anticipate future buying behaviors. Data preprocessing involved handling missing values, removing duplicates, and identifying order cancellations to ensure clean and reliable data for analysis.A detailed exploratory data analysis (EDA) was conducted to investigate product categories, customer attributes, and purchase trends. Advanced clustering techniques, including k-Means, were employed to segment customers into meaningful groups based on purchase frequency, spending patterns, and preferences. Machine learning models, such as Support Vector Machines (SVM), Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, and k-Nearest Neighbors (k-NN), were utilized to classify customers into predefined categories, achieving moderate to high precision scores.To enhance predictive accuracy, deep learning models were incorporated. A Convolutional Neural Network (CNN) achieved the highest precision of 94.94%, leveraging its capability to extract complex patterns and relationships from high-dimensional data. An Artificial Neural Network (ANN) also demonstrated strong performance with a precision of 91.62%. Comparative analyses revealed the superiority of CNN and ANN over traditional machine learning models in handling complex datasets.This study introduces a novel approach to predicting customer behavior based on their first transaction. By integrating insights from clustering, classification models, and deep learning techniques, this research provides a robust framework for understanding customer dynamics and forecasting future purchases. The proposed methods empower businesses to optimize decision-making, improve customer satisfaction, and achieve sustainable growth in competitive E-commerce environments.

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Deep Learning,Machine Learning,Imaging,Disease Classification,Research Publications

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In India, the intersection of climate change and human rights presents complex challenges, particularly for marginalized and vulnerable communities. Climate change exacerbates existing socio-economic inequalities, impacting the most disadvantaged groups, such as indigenous populations, rural farmers, women, and low-income urban dwellers. This paper examines the concept of climate justice in the Indian context, emphasizing how climate change threatens fundamental human rights, including the rights to food, water, shelter, and livelihood. Through an analysis of India's climate policies, legal frameworks, and case studies, the paper critiques the adequacy of current responses and explores the gaps in addressing human rights concerns related to climate change. It highlights the need for a rights-based approach to climate action that integrates human rights considerations into policy frameworks, strengthens the legal protection of vulnerable communities, and promotes inclusive, participatory governance. Furthermore, the paper proposes recommendations aimed at empowering marginalized communities, addressing gender disparities, improving public awareness, and enhancing climate resilience through better social protection mechanisms and international cooperation. Ultimately, this research emphasizes the ethical and legal imperatives of safeguarding human rights in the face of a changing climate in India and globally.

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Climate Justice, Human Rights, Legal Protection, Social Protection, Environmental Justice

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Creative Commons Attribution 4.0 and The Open Definition