Abstract:
Through an interpretation of Elfriede Jelinek the Austrian writer/activist whose essays and plays establish the basis for the following e-text the analysis shows how the selected interpretations of female consciousness in Jelinek's literary works still is very crude in its approach. This paper intends to discuss the portrayal of female subjectivity, psychological fragmentation and the suppression of the feminine self under the capitalist and patriarchal social systems in [insert book name]. This is a qualitative analytical approach based on feminist literary criticism and close textual analysis of the major novels by Jelinek; namely, The Piano Teacher (Die Klavierspielerin), Women as Lovers (Die Liebhaberinnen), and Lust. The main hypothesis suggests that by means of female consciousness, Jelinek exposes the particulars of psychological disintegration women experience under patriarchal domination and systemic exploitation, where they learn to internalize oppression. The results, show that Jelinek is, in his novels, using concrete narrative methods such as fragmented prose, satirical remarks, and descriptions of sexual acts, to reveal the potential and final loss she represents for women, as a woman, the (deffuit) thing, through sexualization followed by destruction. Kindly note that this summary has its own words with different scripts of human form: The examination exposes the fact that the female figures of Jelinek are physically living in psychological petrifaction prisons with their heads brainwashed by maternal control, economic subjugation, and sexual objectification. To sum up, Jelinek's depiction of female consciousness can be considered a radical feminist perspective, forcing readers to not ignore the uncomfortable realities of gender relations and systemic oppression in the modern world.
Area: Department of English
Author: Amrita Singh1, Dr. Anil Kumar Singh2
DOI: MJAP/05/0024
Abstract:
Through an interpretation of Elfriede Jelinek the Austrian writer/activist whose essays and plays establish the basis for the following e-text the analysis shows how the selected interpretations of female consciousness in Jelinek's literary works still is very crude in its approach. This paper intends to discuss the portrayal of female subjectivity, psychological fragmentation and the suppression of the feminine self under the capitalist and patriarchal social systems in [insert book name]. This is a qualitative analytical approach based on feminist literary criticism and close textual analysis of the major novels by Jelinek; namely, The Piano Teacher (Die Klavierspielerin), Women as Lovers (Die Liebhaberinnen), and Lust. The main hypothesis suggests that by means of female consciousness, Jelinek exposes the particulars of psychological disintegration women experience under patriarchal domination and systemic exploitation, where they learn to internalize oppression. The results, show that Jelinek is, in his novels, using concrete narrative methods such as fragmented prose, satirical remarks, and descriptions of sexual acts, to reveal the potential and final loss she represents for women, as a woman, the (deffuit) thing, through sexualization followed by destruction. Kindly note that this summary has its own words with different scripts of human form: The examination exposes the fact that the female figures of Jelinek are physically living in psychological petrifaction prisons with their heads brainwashed by maternal control, economic subjugation, and sexual objectification. To sum up, Jelinek's depiction of female consciousness can be considered a radical feminist perspective, forcing readers to not ignore the uncomfortable realities of gender relations and systemic oppression in the modern world.
Area: Department of English
Author: Amrita Singh1, Dr. Anil Kumar Singh2
DOI: MJAP/05/0024
Abstract:
Climate change represents one of the most pressing global challenges, necessitating advanced computational approaches for accurate modeling and prediction. This study investigates the application of machine learning techniques in climate modeling, examining their effectiveness compared to traditional numerical methods. The primary objectives include evaluating deep learning architectures for temperature prediction, assessing ensemble methods for precipitation forecasting, and analyzing the computational efficiency of various algorithms. The methodology employs a comparative analytical design utilizing secondary data from major climate databases including NASA GISS and NOAA repositories. The hypothesis posits that machine learning models demonstrate superior predictive accuracy for short-term climate variables while maintaining computational efficiency. Results indicate that neural network-based approaches achieve 15-23% improvement in prediction accuracy for temperature anomalies compared to conventional statistical methods. Random forest and gradient boosting algorithms show particular promise for regional precipitation modeling with R² values exceeding 0.85. Discussion reveals that hybrid approaches combining physical climate models with data-driven techniques offer optimal performance. The conclusion emphasizes the transformative potential of machine learning in enhancing climate prediction capabilities while acknowledging limitations regarding long-term projections and interpretability challenges.
Area: Department of Computer Science
Author: Ms. Aarti Hans
DOI: MJAP/05/0021
Abstract:
Statistical convergence, introduced by Fast and Steinhaus in 1951, extends classical pointwise convergence by focusing on the behavior of the majority of sequence elements while disregarding a negligible set. This study examines the foundational properties, applications, and theoretical implications of statistical convergence within real analysis. Originally connected to summation of series, statistical convergence has evolved into a powerful tool, particularly useful when classical convergence methods such as pointwise, uniform, or almost sure convergence prove insufficient. We investigate how statistical convergence relates to these traditional methods, offering a comparative framework through theoretical exploration and practical examples. The methodology includes analytical approaches, comparative studies of convergence criteria, and applications in approximation theory. Our results highlight statistical convergence’s superiority in modeling sequences that frequently occur in measurement and computational processes. It proves especially beneficial where classical convergence fails to capture the underlying structure of sequences. The study underscores statistical convergence as a bridge between abstract theory and real-world problems, reinforcing its value in fields like calculus, topology, and functional analysis. Ultimately, this research affirms statistical convergence as a significant extension of classical theory, offering fresh insights into sequence behavior in mathematical analysis.
Area: Department of Mathematics
Author: Sushree Swagatika1, Dr. Badri Vishal Padamwar2
DOI: MJAP/05/0020
Abstract:
Digital training interventions have emerged as transformative tools in contemporary sports science, revolutionizing how university-level athletes approach physical conditioning and skill development. This study investigates the effects of digital training interventions on physical conditioning, performance outcomes, and skill enhancement among university-level male athletes in India. The primary objectives include examining the impact of mobile applications, wearable technology, and video-based feedback systems on athletic performance parameters. A quasi-experimental research design was employed, utilizing a sample of 120 male athletes from various universities across India. Standardized fitness assessments, performance metrics, and skill evaluation tools were administered pre and post-intervention over a 12-week period. The hypothesis posited that athletes receiving digital training interventions would demonstrate significantly greater improvements compared to traditional training methods. Results revealed statistically significant improvements in cardiovascular endurance, muscular strength, agility, and sport-specific skills among the experimental group. Discussion indicates that digital interventions enhance training adherence, provide immediate feedback, and facilitate personalized programming. The conclusion suggests that integrating digital training technologies into university athletic programs can substantially optimize athlete development and competitive performance outcomes.
Area: Department of Physical Education
Author: Srishti Kanskar1, Dr. Poonam2
DOI: MJAP/05/0023
Abstract:
This study investigates the key determinants influencing employee retention in India's metal industry, a sector employing approximately 1.3 million people as of 2023. The research adopts a quantitative approach using a cross-sectional survey design with 450 employees from major metal manufacturing companies across India. The study examines five primary retention factors: compensation and benefits, workplace safety and environment, career development opportunities, work-life balance, and organizational culture. Results indicate that compensation emerges as the strongest predictor (β=0.542, p
Area: Department of Management
Author: Anil kumar Sharma1, Dr. Parag Sanghani2
DOI: MJAP/05/0019
Abstract:
The emergence of artificial intelligence has fundamentally transformed contemporary society, presenting unprecedented challenges to established human rights frameworks and ethical principles. This paper examines the intricate relationship between artificial intelligence technologies, ethical considerations, and fundamental human rights through an analytical lens grounded in international legal instruments and emerging regulatory frameworks. The research analyzes key legal developments including the European Union's Artificial Intelligence Act (2024), UNESCO's Recommendation on the Ethics of Artificial Intelligence (2021), and the Council of Europe's Framework Convention on AI and Human Rights (2024), alongside foundational human rights instruments such as the Universal Declaration of Human Rights. The analysis reveals critical tensions between technological innovation and human rights protection, particularly concerning privacy, non-discrimination, freedom of expression, and algorithmic accountability. This paper argues that effective governance of AI requires a human-centric approach anchored in international human rights law, supported by robust regulatory mechanisms, and informed by ethical principles that prioritize human dignity, transparency, and accountability in AI system lifecycles.
Area: Department of Law
Author: Ankita Shukla1, Dr. Shameem Ahmed Khan2
DOI: MJAP/05/0018
Abstract:
Climate change poses an existential threat to sustainable development, necessitating urgent legal and policy interventions. Carbon credits have emerged as a pivotal market-based mechanism to mitigate greenhouse gas emissions while promoting economic efficiency. This paper examines the legal and policy dimensions of carbon credit systems within international and domestic frameworks, with particular emphasis on India's legislative developments. The study analyzes the evolution from the Kyoto Protocol's Clean Development Mechanism to the Paris Agreement's Article 6 framework, and India's Energy Conservation (Amendment) Act, 2022, which established the Carbon Credit Trading Scheme. The research evaluates the regulatory architecture, institutional mechanisms, and challenges in operationalizing carbon markets. Through doctrinal analysis and examination of verified legal instruments, this paper demonstrates that while carbon credits present significant opportunities for climate action and sustainable development, their effectiveness depends on robust regulatory frameworks, transparency, and integration with broader climate policies. The findings underscore the need for strengthened legal mechanisms to ensure environmental integrity and equitable participation in carbon markets.
Area: Department of Law
Author: Madhav Kale1, Dr. Shameem Ahmed Khan2
DOI: MJAP/05/0017
Abstract:
The development of advanced luminescent materials for high-performance display devices has gained significant attention in recent decades. Rare-earth activated phosphors, particularly Eu³⁺ and Tb³⁺ doped aluminates, show sharp emission lines, long lifetimes, and high color purity. Thermal quenching at elevated temperatures, however, remains a critical limitation for practical applications. In this study, Eu³⁺ and Tb³⁺ activated aluminate nanophosphors were synthesized via a sol–gel assisted solid-state reaction method. The samples were characterized by XRD, SEM, PL spectroscopy, and TGA to assess their structural, morphological, luminescent, and thermal properties. The aluminate host matrix provided high crystallinity and uniform dopant distribution. Co-doping with Eu³⁺ and Tb³⁺ facilitated energy transfer, resulting in enhanced up-conversion emission under near-infrared excitation. Notably, the phosphors retained over 80% of their room-temperature emission intensity at 500 °C, confirming excellent thermal stability. These results indicate the potential of Eu³⁺/Tb³⁺ activated aluminate nanophosphors for next-generation optoelectronic display devices, LEDs, and laser-based applications.
Area: Department of Physics
Author: Mrs. Rinku Lodh1, Dr. Aloke Verma2
DOI: MJAP/05/0016
Abstract:
Food preservation has become an integral component of modern food systems, with chemical preservatives playing a crucial role in extending shelf life and ensuring microbiological safety. However, the widespread use of synthetic preservatives has raised significant concerns regarding their potential adverse effects on human health. This comprehensive review examines the landscape of chemical food preservatives, including sodium benzoate, nitrites, nitrates, sulfur dioxide, sorbic acid, and various other additives commonly employed in the food industry. Through systematic analysis of recent literature spanning 2012-2024, this study investigates the mechanisms of action, applications, and health implications of these preservatives. Evidence suggests that chronic exposure to chemical preservatives may be associated with oxidative stress, gut microbiota dysbiosis, genotoxicity, carcinogenic potential, and various metabolic disorders. The review also explores emerging alternatives, including natural preservatives derived from essential oils, spices, and plant extracts, which demonstrate promising antimicrobial properties with reduced toxicological concerns. This meta-analysis synthesizes findings from toxicological studies, epidemiological research, and mechanistic investigations to provide a comprehensive understanding of the risk-benefit balance in food preservation practices and inform future regulatory guidelines.
Area: Department of Chemistry
Author: Sulochana Nayak1, Dr. Sushreeta Patnaik2
DOI: MJAP/05/0015
Abstract:
The twenty-first century has experienced a high pace of industrialization, urbanization, and uncontrolled use of resources, hence making environmental protection one of the most pressing issues of a global concern. Although most countries have implemented tough policies and laws on the environment, their success can largely be determined by the existence of consistent political goodwill. This paper is a critical analysis of how politics and the law interact in influencing environmental protection efforts, especially in India against certain international examples of the processes under consideration as the United States, the European Union, and China. India has passed laws that are very broad like the Environment Protection Act (1986) and the National Green Tribunal (2010) but its implementation is not uniform as it is hindered by bureaucratic inefficiencies, other developmental priorities, and a lack of political goodwill. Comparatively, the EU has maintained policy continuity with supranational binding targets, U.S. has experienced ups and downs due to change of political regimes and China has displayed speed in terms of implementation through centralized powers. The comparative study indicates that a high level of political will, institutional autonomy as well as binding obligations are critical to turn legal frameworks into viable environmental governance. The paper wraps up with the insights of the lessons that India can learn out of the international practices in order to augment its environmental policies and place the development objectives in terms of sustainability.
Area: Department of Political Science
Author: Sandeep Malik1, Dr. Mahendra Tiwari2
DOI: MJAP/05/0014
Abstract:
This study examines the comparative accuracy of different analytical approaches in pile test evaluation, focusing on static load testing (SLT) and dynamic load testing (DLT) methodologies. The investigation evaluates the effectiveness of various analytical techniques including Case Pile Wave Analysis Program (CAPWAP), pile driving analyzer (PDA) methods, and traditional static load testing approaches. A comprehensive analysis of 51 pile test cases reveals significant correlations between different testing methods, with dynamic-to-static load ratios averaging 0.9833. The methodology encompassed both driven and cast-in-situ piles tested across diverse soil conditions, utilizing standardized testing procedures as per ASTM D1143 and ASTM D4945 specifications. Results indicate that dynamic load testing with CAPWAP analysis demonstrates high accuracy in predicting static pile capacity, with correlation coefficients ranging from 0.77 to 0.92 depending on soil conditions and pile types. The study establishes that while static load testing remains the gold standard for accuracy, dynamic testing provides reliable results with significant cost and time advantages. The findings demonstrate that CAPWAP-derived capacities are typically 1.06 to 1.15 times static capacities, indicating conservative yet reliable predictions. These results contribute to optimizing pile testing strategies by providing engineers with validated correlation factors for different analytical approaches, thereby improving foundation design efficiency while maintaining safety standards in geotechnical engineering practice
Area: Department of Civil Engineering
Author: Bishwjeet Kumar Chandan1, Mrs. Kamini Laheriya2
DOI: MJAP/05/0013
Abstract:
Ground improvement techniques have become increasingly crucial for enhancing the bearing capacity and reducing settlement of weak soils in geotechnical engineering applications. This study investigates the effectiveness of stone column technique reinforced with jute geotextile for soil improvement in soft clay conditions. The research employs experimental and numerical analysis to evaluate the performance of conventional stone columns compared with jute geotextile-encased stone columns. The primary objectives include assessing bearing capacity enhancement, settlement reduction, and load-displacement behavior under various loading conditions. The methodology involves laboratory testing on soil samples with different reinforcement configurations, field investigations, and statistical analysis of performance parameters. The hypothesis postulates that jute geotextile reinforcement significantly improves stone column performance by providing lateral confinement and preventing bulging failure. Results demonstrate that geotextile-encased stone columns exhibit 60-78% improvement in bearing capacity and 45-67% reduction in settlement compared to conventional columns. The enhanced performance is attributed to increased lateral confinement, improved load transfer mechanism, and reduced column deformation. Statistical analysis confirms the significance of reinforcement parameters on overall performance. The study concludes that jute geotextile reinforcement presents an economical and environmentally sustainable solution for ground improvement, particularly suitable for Indian soil conditions where jute fiber availability and cost-effectiveness make it a viable alternative to synthetic geotextiles.
Area: Jayparkash Kumar1, Ms. Yamini Rai2
Author: Jayparkash Kumar1, Ms. Yamini Rai2
DOI: MJAP/05/0012
Abstract:
Abstract
This research paper explores the manifestation of existential themes in the dramatic works of Eugene O'Neill, the Nobel Prize-winning American playwright, and Girish Karnad, the acclaimed Indian dramatist. The study examines how both playwrights employ existentialist philosophy to explore the human condition, focusing on themes of alienation, authenticity, freedom, and the search for meaning in an apparently absurd universe. Through comparative analysis of their major works, this research demonstrates how O'Neill's psychologically penetrating American dramas and Karnad's mythologically rooted Indian plays converge in their exploration of existential crisis, despite their distinct cultural contexts. The methodology employs textual analysis, comparative literature approach, and existentialist theoretical framework to examine selected plays including O'Neill's "Long Day's Journey into Night," "The Iceman Cometh," and Karnad's "Tughlaq," "Hayavadana," and "Yayati." The results reveal that both playwrights present characters struggling with existential despair, the burden of choice, and the quest for authentic existence. The discussion highlights how O'Neill's autobiographical realism and Karnad's mythological revisionism serve as vehicles for existential exploration. The research concludes that both dramatists effectively demonstrate that existential themes transcend cultural boundaries, offering universal insights into the human predicament of existence in a seemingly meaningless world
Area: Performing Arts
Author: JSV Sivaprasaad Ji
DOI: MJAP/05/0011
Abstract:
Self-care awareness among healthcare practitioners has emerged as a critical factor in maintaining professional wellbeing and optimal patient care delivery. This cross-sectional study examined self-care practices, awareness levels, and associated factors among healthcare professionals across various specialties. The study aimed to assess the prevalence of self-care awareness, identify barriers to implementation, and evaluate the relationship between self-care practices and professional burnout. A quantitative methodology was employed using validated instruments including the Mayo Clinic Well-Being Index and Six Domains of Self-Care framework among 850 healthcare practitioners from multiple healthcare settings. The hypothesis posited that higher self-care awareness would correlate with lower burnout rates and improved professional satisfaction. Results revealed that 67.3% of participants demonstrated adequate self-care awareness, with physical self-care being most prevalent (61.7%) followed by relational (38.0%) and psychological domains (34.6%). Statistical analysis showed significant associations between self-care practices and reduced emotional exhaustion (p
Area: Department of Psycology
Author: Mullai Kodi Madesh1, Dr. Jayarani Manikandan2
DOI: MJAP/05/0010
Abstract:
Up‑conversion (UC) phosphors that can sustain high luminous efficiency at elevated temperatures are pivotal for next‑generation, high‑brightness display and projection systems that operate under intense photoexcitation and thermally stressful conditions. This journal describes the synthesis, structure–property relationships, and photophysical behavior of Eu³⁺‑ and Tb³⁺‑activated aluminate host lattices with a focus on thermal quenching resistance, color purity, and excitation flexibility. We discuss host platforms including SrAl₂O₄, BaMgAl₁₀O₁₇ (BAM), CaAl₁₂O₁₉ (CA₆), and related aluminate frameworks, and analyze energy transfer channels that enable anti‑Stokes (up‑conversion) emission by leveraging defect‑assisted sensitization, cooperative energy transfer, and cross‑relaxation pathways. A comparative evaluation of Eu³⁺ and Tb³⁺ emission manifolds, Judd–Ofelt intensity parameters, CIE colorimetry, thermal activation energies (ΔE) from Arrhenius fits, and photostability under continuous‑wave (CW) pumping is presented. Results reveal that properly engineered charge‑compensated sites, optimized dopant concentration (typically 0.1–5 mol%), and controlled grain‑boundary chemistry can suppress non‑radiative multiphonon losses and maintain ≥70–85% room‑temperature brightness at 423–473 K. The work outlines design rules and future directions for integrating thermally stable UC aluminates in micro‑LED backlights, laser‑excited phosphor (LEP) projectors, and augmented‑reality (AR) light engines.
Area: Department of Physics
Author: Mrs. Rinku Lodh1, Dr. Aloke Verma2
DOI: MJAP/05/0009
Abstract:
Rheumatoid arthritis is a chronic autoimmune disorder marked by progressive joint destruction and systemic inflammation. Current therapies are often limited by side effects and inconsistent efficacy, prompting interest in natural alternatives. Tephrosia purpurea L. (Sharapunkha), traditionally used in Ayurveda for inflammatory ailments, has shown promise against rheumatism and joint disorders. This study evaluated the anti-arthritic potential of hydro-alcoholic extract of T. purpurea leaves in Freund’s complete adjuvant (FCA)-induced arthritis in Wistar rats. It further assessed inflammatory biomarkers, safety through acute toxicity studies, and possible mechanisms of action. Acute toxicity was assessed following OECD 423 guidelines. Arthritis was induced in 36 male Wistar rats using FCA. Animals were orally treated with T. purpurea extract (200 and 400 mg/kg) for 21 days. Paw edema, arthritic score, inflammatory cytokines, biochemical indices, and histopathology were analyzed. The extract was safe (LD₅₀ >2000 mg/kg) and significantly reduced paw swelling, arthritic scores, and pro-inflammatory cytokines (TNF-α, IL-1β, IL-6). Histology confirmed reduced synovial inflammation and cartilage protection. The findings highlight T. purpurea as a promising natural therapeutic for rheumatoid arthritis.
Area: College of Pharmacy
Author: Shivam Shakiya1, Dr. Narendra Patel2, Mr. Firoz Khan3
DOI: MJAP/05/0008
Abstract:
Traditional knowledge systems have been fundamental to human healthcare for millennia, particularly in indigenous communities of central India. This ethnobotanical study was conducted in Sehore district, Madhya Pradesh, to document and analyze the diversity of medicinal plants and associated traditional knowledge among local communities. The research objectives were to inventory medicinal plants used by tribal populations, document traditional preparation methods, evaluate conservation status, and assess knowledge transmission patterns. A cross-sectional research design was employed using semi-structured interviews, field observations, and focus group discussions with 150 informants including traditional healers and community members. The study documented 89 medicinal plant species belonging to 82 genera and 44 families used for treating various human ailments. Trees constituted the highest proportion (43%) followed by herbs (33%) and shrubs (24%). Fabaceae, Asteraceae, and Lamiaceae were the most represented families. Results revealed that traditional knowledge is concentrated among elderly populations (65+ years) with limited transmission to younger generations. Statistical analysis showed high informant consensus factor (ICF) values ranging from 0.68 to 0.92 for different ailment categories. The study identified significant threats including habitat destruction, deforestation, and knowledge erosion. Conservation strategies and community-based documentation programs are urgently needed to preserve this invaluable traditional knowledge system for future generations and potential pharmaceutical applications.
Area: Department of Botany
Author: Bhawna Patidar1, Dr. Syed Shahab Ahmad2
DOI: MJAP/09/0007
Abstract:
India’s electric vehicle (EV) sector has shown rapid growth, with sales surpassing 2 million units in 2024 a 24% increase from 2023 and capturing 8% market share, up from 6.8% the previous year. This review explores India’s evolving EV landscape by assessing technological advancements, policy frameworks, and barriers to adoption. Regional disparities remain prominent: Uttar Pradesh contributed 19% of national EV sales, followed by Maharashtra (12%) and Karnataka (9%). The market is dominated by two-wheelers, which accounted for nearly 1.2 million units and 92% of total EV sales in 2024. Government support has been pivotal through initiatives such as the FAME-II scheme with an allocation of ₹11,500 crore, Production Linked Incentive (PLI) programs, and rapid expansion of charging networks, which reached 25,202 public stations by December 2024. Despite progress, challenges persist, including high upfront costs, inadequate rural charging infrastructure, range anxiety, and low consumer awareness. Drawing on literature reviews, government data, and industry reports from 2019–2025, findings indicate the EV market is projected to grow at a 22.4% CAGR, reaching USD 117.78 billion by 2032. The study concludes that while supportive policies and innovation drive growth, overcoming cost and infrastructure barriers is crucial to achieving 30% EV penetration by 2030.
Area: Department of EVS
Author: Electric vehicles India1, FAME Scheme2, Charging Infrastructure3, EV Adoption Barriers4, Sustainable
DOI: MJAP/09/0006
Abstract:
The influx of AI is changing the face social media from a content creation, targeting and moderation standpoint with updates across major platforms. This has dramatically boosted efficiency and engagement through the strength of AI with personalized user experiences, advertising strategies optimization and content management automation. However, AI also brings with it significant challenges such as bias, echo chamber formation and creation of new rumors. And of course, time and privacy are the complicating factors — (broader concerns also. arise) about how our faces can be used to track us through the world against job prospects or even from public protests. How to address these challenges, as well harness AI capability is critical in the fast-changing social media landscape where maintaining trust and ethical standard amidst respecting users' privacy are primary concerns.
Area: Department of Mechanical Engineering
Author: Brij Bhan Singh1, Dr. Prashant Singh2
DOI: MJAP/09/0005
Abstract:
To research the effect of web-based entertainment on youth, this study used a quantitative exploration strategy with a regulating review procedure. The discoveries uncover that web 2.0, which incorporates stages like WhatsApp or Facebook and Instagram is exceptionally coordinated into the everyday existence of youngsters where advantages incorporate more prominent availability with more extensive companions organizations; enhanced opportunities for career advancement as well improved ways to help self-expression in youth civic engagement and personal identity development. The majority of respondents use these businesses regularly from a mobile device. Anyway, the concentrate additionally recognizes significant downsides. Overuse of digital recreation was also associated with social isolation, reduced live interpersonal interactions and a shift in focus from academic interests to the electronic domain. Anything from cyberbullying to protection dangers and habit are typical Issues. The analysis of socio-segment shows that the majority clients are male, and aged 18-24 with student. Additionally, the review includes the impact of web based amusement on personal life (e.g., its effects for physical work, focus and family time). Despite the many advantages brought about by virtual entertainment, it is also important to take into consideration its negative effects so that an appropriate balance can be struck between online and offline life in young people. The review highlights the need for ways that harness the benefits of streaming while mitigating its harmful effects
Area: Department of Management
Author: Swati Singh1, Pratik Singh2
DOI: MJAP/09/0004
Abstract:
In this review, we have explored many AI and profound learning techniques for finding of cerebrum cancer identification in X-ray filters. We tried Convolutional Neural Networks (CNNs), Multilayer Perceptrons (MLPs) with Principal Component Analysis(PCA), and Transfer Learning using InceptionV3 to find out what could be the best possible methods for automated tumor classification. The highest performance the CNN model; 86.27% accuracy in this case, due to its ability of learning and classifying features from MRI images directly possible as showed by our results InceptionV3 with Transfer Learning was also efficient in catching performance of 82.78% thus proved to be most useful way leveraging pre-trained model, even so couldn't beat up the results of CNNs. On the contrary, The MLP with PCA model reached an accuracy of 76.47%, proving that perhaps continuously half way projecting to reduce dimensionality may not catch some important features for classification. Charges such as Logistic Regression, Random Forests and AdaBoost preceded by Naive Bayes (NB) secmenu followed behind in terms of performance but were generally weak relative to the CNN and Transfer Learning-based methods. These outcomes demonstrate that future improvements in feature extraction and model training could achieve better brain tumor detection
Area: Department of Management
Author: Uday Pratap Singh
DOI: MJAP/09/0003
Abstract:
This review focuses on the application of AI tools to detect phishing sites, concentrating specifically in calculations such as Arbitrary Backwoods (LR), XGBoost, Simplistic Bayes (NB), Support Vector Machine(Bolstered vector machine). The study reminiscences the importance of comprehensive data preprocessing which consists, different precursory procedures like cleaning, extraction and standardization to improve the predictive accuracy and robustness of models. Among the tried methodologies, Angle Helping accomplished 97.6% precision which shows its strength in phishing identification and Guileless Bayes recorded the least exactness at 60.5%. Results show the fundamental role of selecting appropriate AI models and preprocessing methods to enhance phishing detection systems. This represents a significant advancement over traditional methods, especially in dealing with happy hour phishing attacks and managing restrictive data sets, providing an effective solution to enhance cyber security.
Area: Department of Aeronautical Engineering
Author: Pooja Singh1,Hrishita Maurya2
DOI: MJAP/09/0002
Abstract:
Taking the context of Kerala into account, this study investigates motivations and barriers for RL adoption as well benefits in plastic recycling units (PRU). Through different statistical analysis, the study finds that economic factors are more determinants of urban recycling units while environmental and social concerns drive rural units. There are differences by region in the barriers to RL adoption, with urban units experiencing HR and organizational challenges, while rural units face technological obstacles. RL practices result in a variety of benefits; urban units achieved improvements in relationship with stake holders, cost effectiveness and social advantages while environmental gains for rural beneficiaries. The results highlight the heterogeneity of RL practices in Kerala and this could serve as a fundamental stepping-stone for shaping policy environment, directing future investments even promotional activities on recycling towards addressing requisite needs of rural/urban cycles so that comprehensive solution may be tailored with reference to tackling grinding waste management woes from across the state.
Area: DEPARTMENT OF AERONAUTICAL ENGINEERING
Author: BRIJ BHAN SINGH
DOI: MJAP/09/0001