Volume 13 | Issue 2 |

 Abstract

In metropolitan areas, traffic congestion at intersections presents a major challenge to both efficiency and safety. This study proposes a real-time traffic management system that leverages computer vision and artificial intelligence to optimize traffic signal timings based on dynamic vehicle density analysis. The system employs four strategically placed cameras at a crossroad, capturing live video feeds from each approach. Real-time vehicle detection and tracking are performed using OpenCV, a widely adopted computer vision library. By analysing vehicles within predefined regions of interest (ROIs) in each camera feed, the system calculates vehicle densities for all approaches. An AI-driven algorithm integrates the data from all cameras to dynamically adjust traffic signal timings, prioritizing green light durations for roads with higher vehicle densities. The primary objective is to enhance traffic flow, minimize congestion, and improve overall intersection efficiency. Experimental results demonstrate the system's effectiveness and feasibility, highlighting its potential for practical implementation in smart city infrastructures.

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 Keywords

Computer Vision, Real time vehicle detection, Data analysis, Region of Interest, Smart city infrastructure

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This research explores the impact of advertisement on consumer behavior, focusing on the psychological, emotional, and social influences that advertisements have on purchasing decisions. As advertising plays an essential role in the marketing strategies of companies, it is crucial to understand how consumers react to different advertising techniques. The paper examines various types of advertisements--such as television, digital, print, and social media--and evaluates their effectiveness in shaping consumer attitudes, brand perception, and purchasing behavior. The study employs a mixed-methods approach, combining quantitative surveys and qualitative interviews to assess the relationship between advertising exposure and consumer decision-making processes.

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 Keywords

Advertisement, Consumer behavior, Brand perception, consumer decision making, exposure

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 Abstract

This study presents a closed-form solution for a triangular porous fin, incorporating factors such as power law-dependent heat transfer coefficient, internal heat generation, surface emissivity, and external magnetic and electric fields. Darcy's model is used to simulate flow within the fin under insulated boundary conditions. The governing equation is solved using the Modified Adomian Decomposition Method (MADM), with results compared to the Finite Difference Method (FDM) for validation. The analysis shows that the fin temperature increases with higher power law parameters, and both the Hartmann number (magnetic field effect) and porosity improve fin efficiency.

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 Keywords

variable area; porosity; magnetic effect; modified differential operator

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 Abstract

Decalcification is an essential step in the histological preparation of tissues containing decalcification is to remove calcium salts, primarily hydroxyapatite, which are embedded in the tissue, making it too hard to be sectioned into thin slices for microscopic analysis. While this step is crucial for successful tissue processing, it presents several challenges that can affect the quality and accuracy of histological results. This review highlights the mechanisms, techniques, and considerations in decalcifying tooth tissue, providing insights into optimizing the process for accurate dental histopathology.

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 Keywords

Decalcification, Mineralised structures, Histopathology

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Creative Commons Attribution 4.0 and The Open Definition

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The detection of fitness for duty (FFD) is crucial for ensuring safety in industries requiring high levels of mental and physical alertness, such as transportation, construction, and healthcare. Traditional FFD assessment methods are often invasive, time-consuming, or subjective, limiting their applicability in real-time scenarios. This paper explores a hybrid deep learning approach leveraging CNN-ResNet50 architectures combined with temporal and spatial feature extraction techniques using Near-Infrared (NIR) iris images. By analyzing iris and periocular features, the model classifies individuals as fit or unfit under conditions induced by alcohol, drugs, and sleep deprivation. The survey synthesizes findings from state-of-the-art studies, addressing segmentation, feature extraction, transfer learning, and classification methods. Additionally, the survey highlights the challenges, dataset constraints, and performance metrics related to the proposed approach. The findings emphasize the potential of integrating advanced deep learning models with non-invasive imaging for robust, real-time FFD evaluation.

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 Keywords

Fitness-for-Duty (FFD), Iris Image Analysis, Biometric System, Alcohol Influence Detection, Drug Influence Detection, Sleep Deprivation Analysis, Near-Infrared (NIR) Imaging, Convolutional Neural Network (CNN), ResNet50 Architecture, Occupational Safety, Physiological Impairment Detection, Deep Learning in Biometrics

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Hypothyroidism is a common endocrine disorder that affects a significant portion of the global population, particularly in women. This study aimed to investigate the levels of Tumor Necrosis Factor-alpha (TNF-?), oxidative stress markers, and selected biochemical parameters in patients with hypothyroidism. A total of 50 hypothyroid patients and 50 age- and sex-matched healthy controls were included in the study. Blood samples were collected to measure TNF-?, oxidative stress biomarkers (such as malondialdehyde and antioxidant enzyme levels), and biochemical parameters including serum TSH, T3, T4, lipid profile, and liver enzymes. The study found significantly elevated levels of TNF-? and oxidative stress in hypothyroid patients compared to the controls. These findings suggest that inflammation and oxidative stress play a role in the pathophysiology of hypothyroidism and may contribute to its complications. The results underscore the importance of monitoring oxidative stress and inflammatory markers in hypothyroid patients.

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 Keywords

Hypothyroidism, TNF-?, Oxidative Stress, Biochemical Parameters, Inflammation, Malondialdehyde, Antioxidant Enzymes, Lipid Profile, TSH, T3, T4.

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Thyroid dysfunction is a common endocrine disorder that affects a large segment of the population worldwide, with a significant burden in India. This hospital-based study aims to assess the prevalence of thyroid dysfunction in Indore district and understand the demographic patterns. A total of 1,000 patients visiting a tertiary care hospital in Indore were screened for thyroid function tests (TFTs). The study found that approximately 15% of patients exhibited thyroid dysfunction, with hypothyroidism being the most common disorder. Gender, age, and socio-economic status were found to be key contributing factors. The results highlight the need for routine screening, particularly in high-risk groups.

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 Keywords

Prevalence Thyroid dysfunction Hypothyroidism Hyperthyroidism Sub clinical Hypothyroidism Subclinical Hyperthyroidism Secondary hypothyroidism

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The College Placement System (CPS) is a web-based platform designed to streamline campus recruitment. Traditional placement processes rely on manual data management, leading to inefficiencies and errors. This system, developed using Python and Django, offers a centralized solution for student registration, job postings, resume uploads, and event management. CPS provides role-based access, ensuring seamless interaction between students, recruiters, and placement officers. Automation enhances efficiency, reducing manual work while improving transparency and security

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 Keywords

College Placement System, Campus Recruitment, Web-Based Platform, Manual Data Management, Python, Django, Centralized Solution, Student Registration, Job Postings, Resume Uploads

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Creative Commons Attribution 4.0 and The Open Definition

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Simulation-based education has gained recognition as a critical tool in nursing education to enhance clinical skills and critical thinking. This study aims to explore the effects of simulation training on the clinical skills and critical thinking abilities of nursing students in Indore. A sample of 100 nursing students from multiple nursing schools in Indore will participate in the study. The intervention will consist of simulation training sessions focusing on patient care scenarios and decision-making skills. Pre- and post-assessments will be conducted to evaluate changes in clinical skills and critical thinking abilities. The results are expected to demonstrate that simulation-based training significantly enhances both clinical proficiency and critical thinking in nursing students, preparing them for real-life healthcare challenges.

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 Keywords

Simulation training, clinical skills, critical thinking, nursing students, nursing education, decision-making, Indore, healthcare simulation, skills enhancement.

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The healthcare industry, especially in nursing, faces high levels of stress, which significantly affects the physical and mental well-being of nurses and the quality of patient care. Mindfulness-based interventions (MBIs) have been proven to alleviate stress and improve emotional well-being across various settings. This study aims to explore the effectiveness of MBIs in reducing nurse stress levels and improving patient care outcomes in Indore, India. A sample of 100 nurses working in various healthcare institutions in Indore will participate in the study. Data will be collected using pre- and post-intervention assessments, including questionnaires on stress levels, job satisfaction, and perceived patient care quality. This study will assess the feasibility, acceptability, and outcomes of mindfulness practices among nurses in the context of Indian healthcare. Results will offer valuable insights into how MBIs can be integrated into nursing practice to promote better mental health and improve patient care.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mindfulness-based interventions (MBIs), nurse stress, patient care, job satisfaction, emotional well-being, healthcare, nursing, intervention study, Indore, mental health, nurse retention.

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Creative Commons Attribution 4.0 and The Open Definition