Volume 14 | Issue 5 |

 Abstract

The cabin floor is one of the most important structural components in a commercial vehicle Body-in-White (BIW), contributing significantly to global stiffness, vibration control, and passenger comfort. Due to its large and thin sheet metal geometry, the cabin floor is highly susceptible to low-frequency vibration and structural resonance, which negatively affect Noise, Vibration, and Harshness (NVH) performance. Traditional stiffness improvement methods such as thickness increase and additional reinforcements often lead to increased vehicle mass and manufacturing cost. To overcome these limitations, topography optimization has emerged as an efficient Computer-Aided Engineering (CAE) technique for improving stiffness through optimized bead generation without adding extra material. This review paper presents a comprehensive study of topography optimization methods applied to automotive floor structures, focusing on stiffness enhancement, natural frequency improvement, and NVH performance. Various research studies, optimization methodologies, design constraints, and commercial software tools used in topography optimization are reviewed. The study also identifies current research gaps related to commercial vehicle cabin floor applications and highlights future opportunities in vehicle-level optimization.

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 Keywords

Optistruct, Hypermesh, Catia, Topography Optimization

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 Abstract

Driver drowsiness is one of the major causes of road accidents worldwide, leading to serious injuries and loss of life. Detecting driver fatigue at an early stage can significantly reduce the risk of accidents. This paper presents a real-time Driver Drowsiness Detection and Alert System using Machine Learning and Computer Vision techniques. The proposed system continuously monitors the driver's facial expressions using a camera and analyzes eye movements, blinking patterns, and yawning behavior. Facial landmark detection and Eye Aspect Ratio (EAR) are used to identify signs of drowsiness. A Support Vector Machine (SVM) classifier is employed to classify the driver's state as alert or drowsy. When drowsiness is detected, the system triggers an alarm to alert the driver and can also send the vehicle's live location to a registered contact for emergency assistance. The proposed system is cost-effective, reliable, and suitable for both personal and commercial vehicles. Experimental results demonstrate an accuracy of 83.25% in detecting changes in facial expressions under varying lighting conditions.

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 Keywords

Driver drowsiness, Machine Learning, Facial Landmark Detection, Support Vector Machine, OpenCV, Eye Aspect Ratio

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Measurable signs known as biomarkers are used to diagnose illnesses, track their development, and assess the efficacy of therapies. Important biomarkers for kidney stone disease, diabetes, and cancer--three major global health issues--are covered in this review. Circular RNAs, survivin, protein markers, circulating tumour DNA, and exosomes are examples of biomarkers in cancer that help in early identification, outcome prediction, and targeted therapy guidance. Serum indicators, cardiac markers, HbA1c, circular microRNAs, and glycated albumin are examples of diabetes biomarkers that can evaluate glucose control, identify problems early, and enhance diagnosis. Calcium oxalate-binding proteins and metabolic markers are examples of kidney stone biomarkers that help in early stone risk assessment and improved recurrence treatment. These biomarkers are crucial instruments for contemporary clinical practice since they enhance diagnosis, tracking, and individualised treatment.

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Biomarkers,Precision medicine , Cancer biomarkers ,Diabetes biomarkers ,Kidney stone disease HbA1c ,microRNA

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 Abstract

Herbal tea is gaining wide acceptance as a natural and healthy beverage because of its therapeutic value and refreshing nature. These beverages, also known as tisanes, are prepared using different medicinal plants, herbs, spices, flowers, and roots that possess beneficial biological properties. Herbal teas have been traditionally consumed in many cultures as part of daily lifestyle practices and social gatherings. They are believed to help improve immunity, reduce stress, promote relaxation, and maintain overall health and well-being. Since most herbal teas are naturally caffeine-free, they are considered a suitable alternative to conventional tea and other stimulant beverages. Herbal teas are generally prepared by infusion or decoction of selected herbal ingredients soaked or boiled in water to obtain the required extract. Herbal teas contain several naturally occurring phytochemicals such as flavonoids, phenolic compounds, tannins, alkaloids, terpenoids, and saponins contributing to their antioxidant and medicinal activities. In herbal teas, these bioactive compounds may possess antimicrobial, anti-inflammatory, digestive and immunity enhancing properties. Various herbal ingredients such as ginger, peppermint, tulsi, chamomile, cinnamon and lemongrass are used either alone or in combination to enhance the flavor and therapeutic efficacy. The present study deals with formulation and evaluation of herbal tea prepared from selected medicinal herbs. The study was aimed at developing a flavorful, safe and health promoting beverage with acceptable sensory characteristics and beneficial pharmacological properties.

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 Keywords

Herbal Tea, Camellia sinensis, Phytochemicals, Antioxidant, Medicinal Herbs, Tisanes

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 Abstract

Health is defined by the World Health Organization (WHO) as a state of complete physical, mental, and social well-being, not merely the absence of disease or infirmity. It involves maintaining balance across these areas, including emotional health, to function well in daily life. Well-being on the other hand is a positive state that individuals and societies experience, influenced by social, economic, and environmental factors. It's a resource for daily life, encompassing quality of life and the ability to contribute meaningfully. Focusing on well-being promotes equitable resource distribution, sustainability, and thriving. A society's well-being is reflected in its resilience, capacity for action, and ability to overcome challenges

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THE PROBLEM AND ITS BACKGROUND

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For the reconstruction of economic, social, political and cultural aspects of our nation the self-reliance of every village is a pre-requisite condition. The father of the nation mahatma Gandhi always insisted the concept of grama swaraj and believed that the soul of our nation lies in the villages. To realise the dreams of mahatma Gandhi and to achieve the concept of grama swaraj, the parliament had enacted the 73rd constitutional amendment in the year 1993 and there by accorded the constitutional status to the concept of 'Grama Swaraj'. Accordingly a Three-Tier-Panchayati Raj was introduced. The institutions of rural local bodies were accorded constitutional status.

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Significance of 73rd Constitutional Amendment Act - 1992:

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Opportunities and Challenges of Artificial Intelligence in Higher Education - A Study

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Artificial Intelligence (AI), Higher Education, Opportunities, Challenges.

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The research work is "To focus on the formulation and evolution of the herbal Anti diabetic tablet containing insulin, neem and aloe vera for potential therapeutic application. The tablets were prepared using the suitable excipients by wet granulation method. Preformation study such as bulk density, tapped density and angle of repose were carried out to evaluate the flow properties of the powder blend. The prepared tablets were evaluated for various parameter including hardness, friability disintegration time and dissolution time. The result indicate that all the evaluation parameters were within the acceptable limits as per the standard guidelines. The formulated tablets showed the satisfactory physical characteristics and their suitability for the studies". The study conclude that the formulated herbal tablet possesses promising antidiabetic potential and can be considered as a safe and alternative for diabetes management.

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 Keywords

Introduction, Diabetic, Antidiabetic drug.

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The growing use of lithium-ion batteries in electric vehicles, renewable energy systems, and portable electronics has increased the need for efficient Battery Management Systems (BMS). Lithium-ion batteries are highly sensitive to voltage, current, and temperature variations, which can affect performance, safety, and lifespan. Hence, accurate monitoring and estimation of battery parameters are essential for safe and reliable operation. This project presents the design and development of a real-time Battery Management System for lithium-ion batteries with State of Charge (SOC) and State of Health (SOH) estimation using the Extended Kalman Filter (EKF). The system continuously monitors battery voltage, current, and temperature using a voltage sensor, INA219 current sensor, and Dallas DS18B20 temperature sensor interfaced with an Arduino Uno microcontroller. The EKF algorithm is implemented to estimate SOC accurately under dynamic conditions. Compared to conventional methods such as Coulomb counting and voltage-based estimation, EKF reduces errors caused by sensor noise, drift, and nonlinear battery behavior. SOH is determined based on battery capacity degradation, which helps analyze battery aging and health condition. To ensure battery safety, MOSFETs are used to control charging and discharging operations. The system automatically disconnects the battery during abnormal conditions such as overvoltage, undervoltage. A DC motor is used as a load to simulate discharge conditions. The measured and estimated parameters are stored in an SQLite database and displayed through a Flask-based web dashboard for real-time monitoring and visualization. Experimental results show that the developed system provides stable SOC and SOH estimation, reliable monitoring, and improved battery safety. The proposed system is cost- effective, scalable, and suitable for battery management applications in electric vehicles and renewable energy storage systems

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 Keywords

Battery Model, State of Charge, State of Health, Kalman Filter, Battery Management System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Six Sigma methodology, particularly the DMAIC (Define, Measure, Analyze, Improve, Control) approach, is a systematic process for continuous improvement in production processes. It focuses on reducing defects, increasing efficiency, and enhancing customer satisfaction. The methodology involves defining the problem, measuring the process, analyzing the data, improving the process, and controlling the results to achieve a state of perfection. Lean Six Sigma integrates these methodologies to address waste and improve productivity. It emphasizes the importance of value stream mapping, process cycle efficiency, and Kaizen initiatives to optimize production processes. The application of Six Sigma in production has been shown to lead to significant improvements in productivity, reduction of manufacturing waste and enhancement of customer satisfaction.

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Six Sigma, Pressure Die Casting, ADC12 Alloy, Quality Improvement, DMAIC.

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