Volume 14 | Issue 6 |

 Abstract

Navigating large academic campuses can be challenging for students, visitors, and staff due to complex layouts and the lack of intelligent real-time guidance systems. This paper presents the design and implementation of an intelligent campus navigation assistant that integrates speech recognition, natural language processing (NLP), and the A* pathfinding algorithm to provide efficient and user-friendly navigation support. The proposed system enables interaction through both voice and text inputs, allowing seamless and intuitive communication with the assistant. The speech recognition module converts spoken input into text, which is further processed using NLP techniques for intent detection and contextual understanding. Based on the interpreted input, the system is capable of both computing optimal navigation paths using the A* algorithm and handling general user queries related to the campus environment. This integrated approach enhances the system's functionality by combining navigation assistance with intelligent information retrieval.

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 Keywords

Intelligent Virtual Assistant, Campus Navigation, Speech Recognition, Natural Language Processing (NLP), A* Algorithm, Pathfinding

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Vocabulary is a fundamental component of language learning and plays a crucial role in developing students' reading, writing, listening, and speaking skills. Among the various approaches to vocabulary acquisition, developing regular reading habits is considered one of the most effective and natural methods. Reading exposes learners to new words in meaningful contexts, enabling them to understand, remember, and use vocabulary more effectively than through rote memorization. In recent years, however, the reading habits of school students have declined due to increased use of digital media, social networking platforms, and other forms of entertainment. This decline has adversely affected students' vocabulary development and overall language proficiency. The present study, "Improving English Vocabulary Through Reading Habits in School Students," was undertaken to examine the relationship between students' reading habits and their English vocabulary development. The specific objectives of the study were to investigate students' reading habits, identify the influence of regular reading on vocabulary acquisition, and suggest effective strategies to promote reading among school students. The study adopted the descriptive survey method. A sample of 30 school students from the researcher's tuition centre was selected using the convenience sampling technique. Data were collected using a self-prepared questionnaire consisting of items related to students' reading frequency, reading preferences, vocabulary learning strategies, and attitudes toward reading. The collected data were analysed using simple statistical techniques such as frequency and percentage. The findings of the study revealed that students who engaged in regular reading demonstrated better vocabulary knowledge, improved reading comprehension, and greater confidence in using English. The study also found that students who used strategies such as maintaining vocabulary notebooks, referring to dictionaries, and reading a variety of English materials showed higher levels of vocabulary acquisition. Furthermore, the findings indicated that encouragement from teachers and parents played a significant role in developing positive reading habits among students. The study concludes that regular reading is an effective and sustainable strategy for improving English vocabulary among school students. It recommends that schools, teachers, and parents encourage students to cultivate daily reading habits by providing access to suitable reading materials and creating a supportive reading environment. Such initiatives will not only enhance vocabulary development but also improve overall language proficiency, academic achievement, critical thinking, and lifelong learning skills.

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 Keywords

Reading Habits, English Vocabulary, Vocabulary Development, School Students, Language Learning, Reading Comprehension, English Language Teaching.

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This paper presents a comprehensive study of discrete sizing optimization of industrial steel truss structures using Genetic Algorithm (GA), Harmony Search (HS), Fully Constrained Design (FCD) and Mixed-Integer Non-linear Programming (MINLP), integrated with Finite Element Analysis (FEA) for structural response evaluation. The total structural weight is taken as the objective function, subject to member stress, Euler buckling and nodal displacement constraints as per IS 800:2007 and IS 875. The framework is implemented in MATLAB and validated against classical benchmark truss problems (10-bar, 25-bar, 72-bar), and is further applied to a 24 m span Pratt-type industrial factory roof truss. The GA achieves the best-known solutions on all benchmark problems and reduces the weight of the industrial truss from 847.3 kg to 634.8 kg, a reduction of 25.1%, corresponding to a cost saving of Rs. 31,238 per truss bay (22.4%). The results confirm GA as the most suitable method for discrete, nonlinear and discontinuous structural optimization problems encountered in Indian industrial steel truss design.

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 Keywords

Truss Optimization, Discrete Sizing, Genetic Algorithm, Harmony Search, Finite Element Analysis, MATLAB, IS 800:2007, Weight Minimization.

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Objective: To assess knowledge and practices among menopausal women regarding pelvic organ prolapse and urinary incontinence, and to evaluate the effectiveness of an educational intervention using the Prolapse and Incontinence Knowledge Questionnaire (PIKQ). Methods: An analytical study was conducted with 308 women aged 40-60 in Belagavi. Participants were randomly assigned to control and experimental groups. The intervention included pamphlets, a video module, and a pelvic model. Content validity (0.94 scale-level, 1 item-level) and reliability (0.859) were established. Data were collected pre- and post-intervention using PIKQ. Results & Conclusion: Significant improvements (p < 0.05) were observed post-intervention in both groups, with greater gains in the experimental group, indicating the intervention effectively enhanced knowledge and practices.

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 Keywords

Menopause; Educational Intervention; Urinary Incontinence; Pelvic Organ Prolapse; Knowledge.

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 Abstract

We give some necessary and sufficient condition for decomposing some special type of complete bipartite graph K_(m,n) into multi star subgraphs. In particular the condition for ? K_(t,?) with t=1,2,3,..., admits multi star decomposition exist. The graph of the form K_(1,?) has multi star decomposition if and only if ?=n(2n+1) for any natural number n. A Complete bipartite graph K_(t,?_t ) admits Multi star Decomposition (S_1,S_2,S_3,...,S_n) if and only if n=?Kt?^2 or 2n=?Kt?^2-1,t,K(?0)?N.We give some necessary and sufficient condition for decomposing some special type of complete bipartite graph K_(m,n) into multi star subgraphs. In particular the condition for ? K_(t,?) with t=1,2,3,..., admits multi star decomposition exist. The graph of the form K_(1,?) has multi star decomposition if and only if ?=n(2n+1) for any natural number n. A Complete bipartite graph K_(t,?_t ) admits Multi star Decomposition (S_1,S_2,S_3,...,S_n) if and only if n=?Kt?^2 or 2n=?Kt?^2-1,t,K(?0)?N.

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 Keywords

Complete bipartite graph, Arithmetic Decomposition, Multi decomposition, Multi-Star Decomposition

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents the implementation of Skill-Bridge, an AI-powered smart learning and career guidance platform designed to assist students in skill development and career preparation. The system integrates multiple AI-based modules such as course generation, quiz generation, roadmap planning, resume analysis, and Ai resource generation. The platform uses modern web technologies and AI APIs to generate personalized learning paths and provide real-time feedback. The system architecture, module implementation, and functionality of each component are discussed. The proposed system aims to bridge the gap between academic learning and career readiness by providing an integrated ecosystem for learning, assessment, and professional development.

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 Keywords

Artificial Intelligence (AI), Smart Learning Platform, Career Guidance System, Generative AI, Personalized Learning, Course Generation, Resume Analysis, Career Roadmap Generation, AI Chatbot, Educational Technology, Skill Development

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Creative Commons Attribution 4.0 and The Open Definition

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This study examines the emotional and psychological representations of female characters in selected global literary texts and films, with a comparative focus on human women and artificial female figures. Drawing on feminist theory, post-humanism, affect theory, and trauma studies, the research analyzes how emotions function as central tools in constructing gendered identity, agency, and subjectivity. Through close reading and discourse analysis of works such as Margaret Atwood's The Handmaid's Tale (1985), Buchi Emecheta's The Joys of Motherhood (1979), Chitra Banerjee Divakaruni's The Palace of Illusions (2008), Philip K. Dick's Do Androids Dream of Electric Sheep? (1968), and films including Black Swan (2010), Frida (2002), Ghost in the Shell (1995), and Ex Machina (2014), the study explores how emotional depth shapes autonomy and resistance in human female characters, and how emotional simulation complicates identity in artificial beings. The findings suggest that emotional representation is not merely a personal trait but a cultural and political construct that influences societal perceptions of femininity. While many narratives reinforce traditional stereotypes of women as nurturing, vulnerable, or emotionally excessive, others present emotional self- awareness and psychological resilience as forms of empowerment. The analysis of artificial femininity reveals that programmed emotions often reproduce gender norms, yet these figures also challenge the human machine divide by asserting agency. By integrating literary analysis with discussions of emotional artificial intelligence, the study contributes to ongoing debates in gender and technology studies and highlights the need to critically examine how emotion continues to define identity in an increasingly technological world.

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emotional representation, gender identity, post-humanism, artificial intelligence, feminist theory,affect theory.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this paper, we study some distance based topological indices, such as Wiener Index(W), Hyper-Wiener Index (WW), Harary Index (H), Reciprocal Complementary Wiener Index (RCW), Sum Connectivity Index (SCI), Batschelet Index (B), Reverse Wiener Index ?(G), Reciprocal Reverse Wiener Index R ? (G) of K_m ? C_n.

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 Keywords

Wiener index, Hyper-Wiener Index, Harary Index, Reciprocal Complementary Wiener Index, Sum Connectivity Index, Batschelet Index, Reverse Wiener Index, Reciprocal Reverse Wiener Index and Corona Product.

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Creative Commons Attribution 4.0 and The Open Definition

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Vataja Kasa is a commonly encountered respiratory disorder in peadiatric age groups characterized by dry cough, hoarseness of voice, chest pain, and scanty sputum. Ayurveda recommends the use of Vata-shamaka and kasa-hara drugs for its management. Rasna (Pluchea lanceolata) is a well-known ayurvedic drug indicated in Vata-kapha dominant disorders including Kasa and Shwasa. The present review compiles classical Ayurvedic references, pharmacological properties, and modern scientific evidence highlighting the role of Rasna in the management of Vataja Kasa. Special emphasis is given to its pharmacological action on respiratory pathways and its relevance in pediatric formulations. Although Rasna is widely used in traditional practice and is a component of several classical and contemporary formulations for respiratory disorders, the available information is scattered across Ayurvedic texts, pharmacological studies, and experimental research articles. There is a lack of a focused, critically analyzed review highlighting the role of Rasna specifically in Vataja Kasa, particularly with relevance to pediatric age groups. Furthermore, recent scientific studies demonstrating its action on airway inflammation, bronchial smooth muscle, and cough reflex receptors have not been adequately correlated with Ayurvedic concepts such as rasapanchaka, dosha karma, and samprapti vighatana. Therefore, this review is needed to bridge classical Ayurvedic knowledge with modern scientific understanding and support evidence-based Ayurvedic practice.

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 Keywords

Rasna, Vataja Kasa, pediatric cough, Kasa-hara dravya, Ayurveda

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 Abstract

Chronic low back pain (CLBP) can be described as pain for more than three months and is a major cause of reduced quality of life and disability worldwide, particularly in the working population. Conventional management strategies have been directed toward biomechanical and tissue-related factors. Nonetheless, the multidimensional aspects of chronic pain demand more comprehensive interventions. Pain Neuroscience Education (PNE) focuses on enhancing individual's knowledge of the neurophysiology of pain by explaining how neural processes, together with cognitive, emotional, and behavioural influences, affect pain perception and related outcomes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pain Neuroscience Education (PNE), Traditional Patient Education (TPE), Chronic Low Back Pain (CLBP), Kinesiophobia, Catastrophizing, Chronic Non-Specific Low Back Pain (CNSLBP).

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Creative Commons Attribution 4.0 and The Open Definition