Recent Articles

Dr. Bharati Bidikar, Karanam Sagar kiran  ·  International Journal of Technology & Emerging Research  ·  24 Jul 2025

Keratoconus is a progressive, non-inflammatory corneal disorder that can significantly impair vision if not detected and treated early. Accurate diagnosis of keratoconus, especially in its early stages, is crucial to prevent severe visual deterioration and reduce the need for invasive treatments such as corneal transplantation. This study proposes a machine learning-based approach for the diagnosis of keratoconus using topographic and tomographic features of the cornea. A large dataset containing 423 features was analyzed, and univariate feature selection was applied to identify the most discriminative attributes. Several supervised learning algorithms—including Random Forest, Support Vector Machines, k-Nearest Neighbors, and Logistic Regression—were trained and evaluated. The Random Forest classifier achieved the highest diagnostic accuracy of 95.8%, showcasing the potential of machine learning in aiding clinicians with accurate and early detection of keratoconus.

Budidha Samuel Ashish Kumar, Aluri Suguna Ratna Priya  ·  International Journal of Technology & Emerging Research  ·  24 Jul 2025

An advanced Automatic Question Answer (QA) Generation system that leverages DeepSeek R1 AI to address the limitations of traditional fine-tuning-based Natural Language Processing (NLP) models. Our approach eliminated the need for time-consuming fine-tuning and costly GPU infrastructure while supporting multiple input types, diverse QA pairs, and Bloom’s Taxonomy-based cognitive levels. We have evaluated the versatility of the model on a vast number of instructional materials and established its capability of generating great questions and answers in a variety of formats. To achieve this, we present a scalable and easily navigable framework for QA generation in educational and assessment technologies. Overall, our system exhibited emergent reasoning behaviors, utilizing the capability of reinforcement learning through DeepSeek R1, even in the absence of any supervised pre-training. The model is aligned with the educational goals and can be adjusted to accommodate different question types, including multiple-choice questions, short-answer questions, and descriptive questions. Besides, we further simplified reasoning strategies into smaller models for light deployments on non-GPU systems. Results of the experiments demonstrated that our method is resource-efficient and competes, performance-wise, with some of the most recent systems for real-world educational purposes.

Sanapala Joshika, Setti Sarika  ·  International Journal of Technology & Emerging Research  ·  24 Jul 2025

This paper presents an intelligent system for solving CAPTCHA challenges using Artificial Intelligence (AI) integrated with explainable frameworks. CAPTCHAs, designed to differentiate humans from bots, often pose accessibility and usability issues. To address this, we developed a deep learning model capable of accurately recognizing and solving both alphanumeric and math-based text CAPTCHAs. The model utilizes Convolutional Neural Networks (CNNs) for image-based text recognition, trained on synthetically generated CAPTCHA datasets. To enhance transparency and trust in AI predictions, the system incorporates LIME (Local Interpretable Model-agnostic Explanations), which visually explains each character prediction by highlighting important regions of the CAPTCHA image. This interpretability aids developers in validating the model's decisions and ensures robustness against adversarial inputs. The system aims to balance accuracy, security, and explainability, making it suitable for real-world applications where both user experience and AI accountability are critical.

Pasala Sanyasi Naidu, Pakerla Emmy Rathan  ·  International Journal of Technology & Emerging Research  ·  24 Jul 2025

Credit card fraud detection is a critical area of concern for financial institutions, as it aims to identify and prevent unauthorized transactions to safeguard consumers' financial assets. With the rapid growth of e-commerce and digital payments, fraudsters have increasingly employed sophisticated methods to exploit vulnerabilities in payment systems. This paper explores the various techniques used for credit card fraud detection, focusing on machine learning algorithms, statistical models, and hybrid approaches. We discuss the challenges in detecting fraud, such as the imbalance between legitimate and fraudulent transactions, the dynamic nature of fraud tactics, and the need for real-time detection. Additionally, we analyze the role of data preprocessing, feature engineering, and the use of advanced methods such as deep learning, ensemble methods, and anomaly detection to improve detection accuracy and reduce false positives. Finally, the paper reviews the impact of emerging technologies such as blockchain and AI on the future of fraud detection, providing a comprehensive overview of the current state and future directions in this field.

Jashmita Boyina, Prof. Ch Satyananda Reddy  ·  International Journal of Technology & Emerging Research  ·  23 Jul 2025

In today's competitive job market, understanding hiring trends and job posting patterns is crucial for job seekers, recruiters, and analysts alike. Traditional job portals often lack insights into evolving skill demands and recruitment behavior [2]. This paper introduces a comprehensive analysis system for LinkedIn Job Postings and Hiring Trends, leveraging data visualization and business intelligence techniques [4]. Using a cleaned dataset of scraped LinkedIn job postings, the system identifies top in demand roles, frequently required skills, salary patterns, experience levels, and regional hiring dynamics [1]. The solution utilizes Power BI for interactive dashboards, enriched with DAX measures to uncover hidden patterns and relationships ([3]). Additionally, Python and Excel were used for data preprocessing, ensuring data quality and consistency. The resulting dashboards support multi-angle exploration—industry-wise hiring, job level analysis, function vs. experience mapping, and skill gaps— providing actionable insights for career planning and workforce development. This data-driven approach empowers stakeholders with a deeper understanding of the professional landscape and future hiring trajectories.

Dr. Challa Narasimham , Dudi Sai Sri Sneha  ·  International Journal of Technology & Emerging Research  ·  23 Jul 2025

This project focuses on improving the digital shopping experience for footwear through an interactive virtual try-on system. Many users struggle to find the perfect shoe size or fit when shopping online, which often leads to returns, dissatisfaction, or hesitation in purchasing.To solve this, we developed a web-based platform that helps users see how a shoe would look on their foot before buying it. The user can scan their foot and then choose from a variety of shoe models displayed in the catalog. Once selected, the shoe is overlaid onto the scanned foot image, giving a real-time try-on effect.The idea behind this project is to make online shoe shopping easier, more reliable, and user-friendly. It aims to build trust between brands and customers by showing how a product might actually look when worn. This helps users make more confident purchase decisions.Our system also includes links to real websites where the shoes are sold, so users can directly buy the products after trying them virtually. In addition, details such as price, fit type, and foot compatibility are clearly shown to guide buyers.This method saves time, reduces return rates, and provides a unique shopping experience. We believe such digital tools can shape the future of online shopping, especially in the fashion and retail industry.

Dr. Bharati Bidikar, Gorremuchu Jayasri  ·  International Journal of Technology & Emerging Research  ·  23 Jul 2025

The interaction with the computers by utilizing a revolutionary gesture-based mouse control system has many applications in a variety of sectors, including virtual reality, media management, productivity tools, and gaming. This technology makes use of hand motions tracked by a regular webcam or depth camera to navigate and manage the computer interface, rather than relying on physical mouse devices. The system uses computer vision algorithms to recognize, track, and understand hand gestures in real time in order to execute mouse actions like cursor movement, clicking, and scrolling. The system's key components include hand detection, gesture recognition, and cursor mapping, all of which collaborate to create a seamless and user-friendly interface. The system tackles issues like gesture accuracy and user adaptability via ongoing improvement and feedback integration. Because it provides a more accessible and inclusive mode of interaction, it is particularly helpful for those with motor impairments. This solution, at its heart, illustrates how cutting-edge computer vision and pattern recognition can facilitate smooth and intuitive human-computer interaction, paving the way for intelligent, touchless interfaces.

Dr. Kalpana Thakur  ·  International Journal of Technology & Emerging Research  ·  22 Jul 2025

This paper explores the intersection of human rights and the lived realities of rape victims, emphasizing the urgent need for legal, social, and institutional reforms to uphold victims’ dignity, justice, and recovery. It begins by examining the theoretical and historical foundations of human rights, tracing their evolution from ancient civilizations to contemporary international frameworks. Particular attention is given to how these rights apply to victims of rape, with an analysis of legal obligations and societal responsibilities to prevent sexual violence, prosecute offenders, and support survivors. Despite advancements in international law, challenges such as stigma, victim-blaming, inadequate access to justice, and cultural barriers persist. Through a comprehensive review of international treaties, declarations, and human rights instruments, this article underscores the moral and legal imperatives for states and societies to protect the rights of rape victims. It concludes by advocating for a holistic, rights-based approach centered on prevention, protection, prosecution, and empowerment.

Dr. Boyillapalli Venkata Rao, Imlinenla Longkumer, Dr. Prerna Mukhia  ·  International Journal of Technology & Emerging Research  ·  21 Jul 2025

This study aimed to assess secondary school teachers' awareness of digital initiatives and evaluate digital infrastructure availability in secondary schools of Nagaland. A survey research design was employed, involving 200 tribal teachers from 20 secondary schools in Kohima district. A self-developed survey questionnaire, Digital Initiatives Awareness and Digital Infrastructure (DADI), was validated through content and face validity. The findings revealed a significant gap in digital infrastructure, with poor internet connectivity and inadequate classroom infrastructure. While some digital initiatives like DIKSHA, e-Pathasala, and SWAYAM MOOCS had high awareness levels, others like National Test Abhyaas and NATIONAL DIGITAL LIBRARY had low awareness levels. The study also found that smartphones with internet connectivity and electricity were widely available in schools. The study suggests that more promotion and awareness are needed to achieve the intended goals of digital initiatives. The findings highlight the need for increased investment in digital infrastructure and targeted initiatives to bridge the digital divide and enhance teaching-learning processes. The results can inform policymakers and educators in developing strategies to promote the effective integration of ICT tools and enhance learning outcomes.

Dr. Sarla Raigar, Dr. Gurusharan Kaur, Dr. Kirti Kumar Jain  ·  International Journal of Technology & Emerging Research  ·  19 Jul 2025

This article describes how to use Graph Theory and LPP approaches to identify solutions to minimize transportation expenses. This paper's goal is to apply several strategies that have been created in the literature to address transportation-related issues and lower costs. This paper demonstrates the connection between the transportation problem and graph theory and starts the process of looking for different sorts of solutions. For this reason, we have employed a novel approach in conjunction with graph theory, LCM, VAM, NWCM, and Linear Programming Model. Which technique has a lower transportation cost is shown via comparison.

Prof. (Dr.) Pushpendra Yaduvanshi, Damini Pareta  ·  International Journal of Technology & Emerging Research  ·  10 Jul 2025

The terms "shin pain," "shin splints," and "Medial Tibial Stress Syndrome" (MTSS) are commonly used to refer to pain and discomfort in the lower leg. It might impact recreational and competitive athletes equally, particularly distance runners, endurance sports players, dancers, and the military, proving that this injury is strongly linked to higher physical demands (overload). Medial Tibial Stress Syndrome (MTSS) is a common overuse injury of the lower extremity. It typically occurs in runners and other athletes that are exposed to intensive weight-bearing activities such as jumpers, most common injuries sustained by military personnel, associated with MTSS impact from loading activities such as marching.

Prof. (Dr.) Pushpendra Yaduvanshi, ANMOL PATIDAR  ·  International Journal of Technology & Emerging Research  ·  10 Jul 2025

Cervicogenic headache (CGH), a type of secondary headache stemming from cervical spine dysfunction, is often misdiagnosed due to its similarity to primary headaches. Given the high levels of physical and mental strain in medical education, this study set out to explore how common CGH is among medical students. We initially screened 117 students using three validated tools: the Cervicogenic Headache Questionnaire (CGH), the Neck Disability Index (NDI), and the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS). Of those, 56 students met the criteria for further evaluation. Surprisingly, only one participant (1.78%) showed signs consistent with CGH. Average scores on the assessment tools suggested minimal cervical-related symptoms or disability (CGH: 26.76, NDI: 8.11, LANSS: 3.31). These findings indicate that CGH is not a common issue among medical students, challenging the assumption that their academic lifestyle puts them at high risk. While factors like stress, posture, and screen use may still cause general discomfort, they do not seem to significantly contribute to CGH in this population.

Mr. Nagaraju Vassey, Mr. Manne Naga VJ Manikanth, Mr. MANTHRI GANESH RAO  ·  International Journal of Technology & Emerging Research  ·  09 Jul 2025

This paper presents an Innovative AI-Bot Mock Interviewer system designed to assist job seeker’s by providing real-time, intelligent feedback on virtual interviews. The system integrates advanced language models via OpenAI APIs within a secure Next.js, Drizzle ORM, and Clerk for secure user authentication. A key feature is its intelligent real time interview feedback mechanism. The frontend, built with Next.js, offers a smooth and interactive user experience. Evaluation results show the system delivers over 90% accurate and relevant feedback, with average response times under 2 seconds. This solution supports people by providing virtual mock interviews while preserving human oversight, ultimately enhancing interview quality and accelerating job seeker’s confidence

Dr. Kailas Tehare, Vikas Mogadpalli, Nikhil Raj Gupta, Snehal Takalkar, Mamta Patil  ·  International Journal of Technology & Emerging Research  ·  07 Jul 2025

Python has emerged as one of the most popular and versatile programming languages inthe field of data science and big data. Here we try explores role of Python programming language indata is analysis, manipulated, and visualized. We highlighted its relevance in the growing age of bigdata, focusing on key libraries, frameworks, and tools due to this Python widely popular used by datascientists and analysts. Moreover, in present article we investigate Python language with big datatools such Hadoop and Spark with its capacity to process large-scale datasets. In present study wealso focus on advantages of Python programming language and challenges in the perspective of bigdata analytics.

Dr. Pankaj Mishra  ·  International Journal of Technology & Emerging Research  ·  03 Jul 2025

The Pradhan Mantri Jan Dhan Yojana (PMJDY) was launched on 28th August 2014 by Prime MinisterNarendra Modi with the aim of promoting financial inclusion by offering banking facilities to every householdIndian. Prior to this scheme, a large segment of India’s population, especially in rural areas, remained unbankedand thus outside the formal economic system. This limited their access to credit, insurance, pension, andemployment-linked benefits. With over 50 crore accounts opened as of March 2024, the PMJDY has created aplatform for direct benefit transfers (DBT), micro-finance, and employment-oriented government schemes likeMGNREGA, PMEGP, and Start-Up India. The availability of bank accounts has allowed beneficiaries to receivewages and subsidies directly, ensuring transparency and reducing leakages. Studies have shown thatentrepreneurial activity, rural employment, and women participation in the labor market have seen measurablegrowth post-implementation. This research paper seeks to explore how PMJDY has played a catalytic role inincreasing employment opportunities, facilitating job linkages, and creating a more transparent wage-paymentsystem across various employment-generating schemes in India.

Ms. Kolli Karishma, Dr. Suvarna Kumar Gogula  ·  International Journal of Technology & Emerging Research  ·  30 Jun 2025

In today's digital world, securing online identities is very important. Password-based authentication systems are increasingly vulnerable to phishing, brute-force, and social engineering attacks. To address these issues, this paper introduces "Secure Morph," a secure login system using visual puzzle-based authentication. Users register with their email ID and multiple personal images. During login, one of these uploaded images is randomly selected and displayed alongside AI-generated visually similar decoy images. Users are need to identify the correct image within three (3) attempts. Upon successful selection, a puzzle based on that image must be solved within a time limit. Failure to authenticate within the given constraints results in temporary account lockout. This multi-factor, cognitive-image-based authentication approach enhances resistance to automated attacks while preserving user experience. Secure Morph leverages HTML, CSS, JavaScript for frontend, Python Flask for backend, and utilizes image generation APIs from Hugging Face and Stability AI.

Dr. M Murugesan, Mrs. J Sherrin Banu, M. Kokilavani, S Nirmal Kumar  ·  International Journal of Technology & Emerging Research  ·  25 Jun 2025

In the smart city, advanced monitoring systems are implemented to optimize various aspects of urban life. These systems include sensors that detect sunlight levels to adjust street lighting accordingly, ensuring efficient energy usage and safety. Parking alert systems utilize real-time data to guide drivers to available parking spaces, reducing congestion and emissions. Hill station roadways are equipped with vehicle monitoring technology linked to signal lights, facilitating smoother traffic flow and enhancing safety on steep terrain. Information updates are displayed on LCD screens across the city, providing residents with timely updates on traffic conditions and other relevant news. The city leverages solar energy sources to power these systems, demonstrating a commitment to sustainability and environmental stewardship.

Dr. Kumaraswamy Mora  ·  International Journal of Technology & Emerging Research  ·  23 Jun 2025

Psychological factors significantly influence consumer satisfaction, including motivation to reduce costs, perception of brand attractiveness, attitudes and beliefs toward goods or services, age and educational qualifications among residents at Inavolu area in Hanamkonda district. This study examines the psychological aspects concerning the purchase of groceries. A structured questionnaire was administered with a convenience sample of 200 respondents from Inavolu area of Hanamkonda district. Data were analysed with One-way Anova in SPSS software to assess the average consumer satisfaction with quality, discounts and brand loyalty for purchase of groceries at 5 percent significance level. The findings reveal significant difference among average consumer satisfaction with educational qualifications and age of.

Prof. Ruth Lalhmingthang, Ms. Catherine Lalremruati, Ms. Chawngzikpuii, Ms. Christy Lalruatfeli, Ms. Lalrinmawii, Ms. R Lalrammuansangi, Ms. Lallianpuii, Ms. A Lalawmpuii  ·  International Journal of Technology & Emerging Research  ·  07 Jun 2025

ABSTRACT BACKGROUND Stroke is a common neurological disorder which has a significant impact on patients. Hypertension is said to be the most common risk factor of stroke associated with hemiplegia and paralysis and the warning signals that mostly noted in stroke are numbness, weakness and slurred speech. There is lack of knowledge in the community regarding warning signs, risk factors and the prevention of stroke. Therefore, awareness is needed on the importance of stroke prevention and seeking health care. OBJECTIVES The purpose of this study is to assess the knowledge regarding warning signs and prevention of stroke among selected urban community. METHODS: The research approach adopted for the study was quantitative research approach, one group pre- test design. The study was conducted among 60 samples of age group of above 50 years by convenient sampling technique in Tlangnuam Community, Aizawl, Mizoram. The tools used for the study was self-administered structured knowledge questionnair RESULTS : The data was tabulated, analyzed and interpreted using descriptive and inferential statistics. Findings reveal that that majority (40%) of participants were between the age group 50-59 years, (33.33%) were the age group of 60-69 years, (16.67%) were 70-79 years and the remaining (10%) were above 80 years. Further result depicts that majority (50%) of respondents had inadequate knowledge, (26.67%) of respondents had moderate knowledge and remaining (23.33%) of respondents had adequate knowledge. The result indicates the need to update knowledge regarding warning signs and prevention of stroke. CONCLUSION From this study, there was a clear knowledge gap regarding stroke and associated symptoms in the urban community of Tlangnuam Community

Dr. Pavitra Krishna, Ms. Akshara T  ·  International Journal of Technology & Emerging Research  ·  30 May 2025

The Vegan milk jigarthanda , recognized for its innovative and nutritional benefits Jigarthanda is a famous Madurai drink , which is developed with the different ingredients which can be adapted by the lactose – intolerance and which also comes with the ability to treat insomnia patients. Lactose intolerance - is an inability to digest lactose, a sugar found in milk and milk products. This condition often runs in families and can affect both children and adults. Lactose intolerance is most common in Asian Americans, African Americans, Mexican Americans and Native Americans. Insomnia Insomnia - is a sleep disorder in which you have trouble falling asleep, staying asleep, or waking up too early. the condition can be short term (acute) or can last a long time (chronic) . The vegan milk jigarthanda which deals with both the disorders and helps in the improvement of the disorders and the ingredients incorporated in the jigarthanda are Badam , cashew , poppy seeds and cotton seeds , which is prepared by processing the mixture of the vegan milk altogether. The addition of these product creates a unique kind of a product with the different taste and the ideal product , which gives a innovative and nutritional based food product to the food products , These products cater to ethical, environmental, and health-conscious consumers who follow a plant-based lifestyle. As the vegan food industry grows, research is expanding into several key areas to improve product quality, nutrition, and sustainability. This study highlights the necessity for further research into the health benefits and applications of vegan milk in functional foods, potentially leading to new dietary strategies and interventions aimed at improving public health outcomes. The integration of vegan milk incorporation in the Jigarthanda represents a promising advancement in functional foods, with significant relevance to therapeutic and personalized nutrition. The findings provide a foundation for further research and validation of vegan milk Jigarthanda as a valuable ingredient is a health-promoting food products.