Volume 13 | Issue 5 |

 Abstract

One of the most central approaches to improving prosperity and responding to the challenge of supporting around 10 billion people in 2050 is agricultural development. The top threat to plant productivity in agriculture is plant diseases, which diminish plant quantity and diversity. Detection of such diseases at an early stage through computer-aided techniques based on deep learning could enhance food quality and reduce economic losses. Though today's models are very accurate for a particular species of plant, they generally demand good high-resolution images and are not good at low-resolution or poor-quality input. In order to overcome this issue, the work suggests using a pre-trained CNN model in such a way that it can efficiently identify plant diseases. Particularly, it aims to enhance the popular EfficientNetV2S model to achieve more robust detections under difficult conditions like low resolution, cluttered or deceptive backgrounds, leaf shadows, heterogeneous texture, and brightness changes. It employs the Plant Diseases Dataset, comprising 38 classes of both healthy and diseased leaves belonging to 38 crop species. In order to make the model stronger and reactive, the dataset was intentionally altered to contain noisy images, mimicking real-world scenarios. This alteration was done with the intention of making sure that the model can generalize and function effectively in uncontrolled situations. Overall, this measure reinforces the larger goal of enhancing plant disease detection under poor conditions and emphasizes the trailblazing role played by dataset optimization in deep learning for agriculture.

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 Keywords

CNN, Deep Learning, EfficientNetV2S, Classification, Plant Diseases.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study investigates the impact of health and safety measures on employee well-being, satisfaction, and productivity in a manufacturing organization where workers face various occupational risks. Using structured questionnaires, interviews, and company records, the research explores employees' awareness, understanding, and adherence to existing safety practices. While significant progress has been made in implementing health and safety protocols, gaps remain in training frequency, employee involvement, and communication. The study provides actionable recommendations to strengthen the safety culture, aiming to enhance compliance, reduce workplace incidents, and support sustainable organizational growth through improved employee welfare.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Health and Safety Measures, Safety Practices and Employee Welfare.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The advancements in artificial intelligence (AI) are reshaping healthcare by enabling smarter, data-driven solutions. This project focuses on developing an AI-powered smart dialysis machine aimed at enhancing patient care for individuals with chronic kidney disease (CKD). The proposed system leverages real-time data analytics, predictive modelling, and adaptive treatment protocols to customize dialysis sessions based on patients' unique health profiles. Key functionalities include automated monitoring of vital parameters, intelligent fluid management, predictive maintenance, and alert systems for critical conditions. By continuously learning from patient data, the system ensures optimal performance and personalized care. This innovative approach promises improved treatment accuracy, reduced operational costs, and better patient outcomes in renal healthcare management.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Smart Dialysis Machine, Personalized Healthcare, Chronic Kidney Disease (CKD), Predictive Analytics, Data-Driven Healthcare, Machine Learning, Renal Care Innovation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study investigates the application of unsupervised learning techniques, specifically K-means and hierarchical clustering, to classify individual player batting performance in the Indian Premier League (IPL). Leveraging match-level data from the 2008 to 2024 seasons, player performance was analyzed based on three distinct feature sets: runs scored, a combination of runs and strike rate, and a novel score metric (runs multiplied by strike rate). To ensure robust classification, only innings where a player faced at least 10 balls or was dismissed were considered. A total of six clustering experiments were conducted, and the resulting cluster quality was evaluated using the silhouette score. Comparative analysis revealed that K-means clustering, when applied to the score metric, yielded the most discernible and well-separated clusters of batting performance. This research demonstrates the potential of unsupervised learning in categorizing player batting performance in the high-stakes environment of the IPL, offering valuable insights for team management, player evaluation, and strategic decision-making.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

K-means, Hierarchical clustering, score metric, performance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Social media have become prominent part of life for many people today. Social networking sites provide a platform for the discussion on hot issues that have been overlooked in a day to day basis. The current study is conducted to monitor the impact of social media among common people. It is a survey-type research where for analyzing the effect of social media among the mass. The questionnaire is designed and by using simple random sampling, 250 respondents are selected from Idukki district. In this study it is observed that 76% of respondents agree that social media play a significant role in moulding their attitudes and behaviour of the users. This research also reveals that 79.2% of the respondents agree that social media affect the life of people. The outcomes of this work reveal that social networking sites have the positive impact among the people and it is suggested that both the government and every private institutions should have to work effectively uplift the productive activities of social media among the people.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Influence, Social media, Behaviour, Attitudes

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

After lung cancer, breast cancer is the most prevalent form of cancer in women globally and one of the leading causes of death. Chemotherapy or radiation therapy combined with surgery are the treatment methods for breast cancer. The use of nanotechnology in cancer treatments has received a lot of attention lately. The physical and biological characteristics of nanoparticles in medicinal application are the focus of nanotechnology. In relation to traditional chemotherapeutic medications, TNPs offer a higher loading capacity, lower toxicity, and more stable drug delivery. Breast cancer diagnosis, therapy, and prevention are just a few of the many uses for nanotechnology. The use of traditional treatment approaches for breast cancer leads to problems and numerous negative effects. A more focused strategy for treating breast cancer is provided by nanotechnology. By directing medications to tumors, producing high concentrations, releasing pharmaceuticals gradually, improving drug stability, and minimizing side effects, nanoparticles enhance chemotherapy. An overview of breast cancer, its existing treatment options, and the current application of nanotechnology in breast cancer treatment are all included in this paper.

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 Keywords

breast cancer; chemotherapy; nanoparticles; nanotechnology; tumor.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Haryana, a state located in northern India, has been making considerable progress in many sectors like education, healthcare, and infrastructure. However, disabled individuals in the state continue to face significant socio-economic challenges that hinder their participation in the society and economy. These challenges often result from inadequate infrastructure, limited access to education and employment, societal stigma, and a lack of comprehensive support systems. This study aims to identify the socio-economic problems faced by disabled persons in Haryana, understand the barriers to their full integration, and propose solutions for their inclusion in mainstream society. Through questionnaires, personal interviews, and secondary research, this study investigates

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Study on Socio-Economic Problems of Disabled Persons in Haryana

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the design and implementation of a mobile, AI-driven personal assistant robot that integrates intelligent movement, natural interaction, and seamless connectivity using Wi-Fi. The robot is built on a lightweight 3D-printed PLA chassis and powered by servo motors--DS3230 for the lower body and MG995 for the upper body--offering a practical and cost-effective mobility platform. Locomotion is managed by Central Pattern Generators (CPGs), enabling smooth and stable bipedal walking, even with payloads close to the robot's own weight (~6-7 kg). The robot understands voice commands using the Cohere API for natural language processing and detects human presence and gestures using the YOLO object detection model. User interaction is made intuitive through real-time speech and visual input. IoT functionality is handled over Wi-Fi, allowing the robot to interact with smart home devices and services. In lab tests, the robot achieved reliable path following with an average positional error of ~3 cm, responsive gesture recognition within 30 ms, and accurate voice understanding in varied conditions. This work demonstrates the feasibility of building accessible, human-centric assistant robots using modern AI tools and common hardware. Future development will focus on enhancing real-world adaptability, social interaction, and long-term usability in home environments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Personal Assistant Robot, Bipedal Locomotion, Human-Robot Interaction, Internet of Things (IoT), Modular Robot Design, Smart Home Automation, Artificial Intelligence.

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Creative Commons Attribution 4.0 and The Open Definition

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The new age trends in the recruitment industry has indicated new ways to follow the hiring process. When we talk about hiring and managing talent, it becomes quite difficult to understand the hiring process and recruit the new age talents. In this paper, I have tried to understand the ways through which some of the Indian companies hire, recruit and retain the talents. As recruitment and talent management are broader terms, we will delve into the core aspects of the hiring and retaining process. We will understand the different perspectives of the industry people towards hiring talent and understand the gaps which need to be filled up.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Recruitment, Hiring, Talent management, Selection, Hiring process

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract The present study focuses on the formulation and evaluation of a herbal shampoo using natural ingredients known for their hair care benefits. The primary objective is to develop an effective, eco- friendly, and safe alternative to synthetic shampoos by incorporating plant-based components such as Shikakai (Acacia concinna), Reetha (Sapindus mukorossi), Amla (Phyllanthus emblica), Neem (Azadirachta indica), and Aloe vera. These herbs were selected based on their traditional use and scientifically recognized properties, including cleansing, antimicrobial, anti-dandruff, and conditioning effects. The formulated shampoo was evaluated for physicochemical parameters such as pH, foaming ability, viscosity, and dirt dispersion capacity. Results indicate that the herbal shampoo met standard quality parameters and showed promising cleansing and conditioning properties, making it a suitable natural alternative for regular hair care. This formulation contributes to the growing demand for sustainable and chemical-free personal care products. The increasing demand for natural and chemical- free personal care products has led to a surge in the development of herbal cosmetics, particularly in hair care. This study presents the formulation and evaluation of a herbal shampoo using a combination of traditionally used medicinal plants known for their beneficial effects on scalp health and hair maintenance. The aim was to create a mild, non-toxic, biodegradable shampoo that offers cleansing, conditioning, and therapeutic benefits without the adverse effects associated with synthetic surfactants and preservatives. The formulation included extracts of Shikakai (Acacia concinna), Reetha (Sapindus mukorossi), Amla (Phyllanthus emblica), Neem (Azadirachta indica), and Aloe vera. These herbs were chosen based on their rich saponin content, antimicrobial properties, anti-inflammatory effects, and proven role in promoting hair growth and scalp health. The preparation involved aqueous extraction of the plant materials, followed by blending in specific proportions to achieve desired viscosity, foamability, and cleansing power. Physicochemical evaluations were conducted to assess pH, surface tension, solid content, foaming index, dirt dispersion, and stability over time. The shampoo maintained an ideal pH (4.5-5.5), exhibited adequate foaming, good cleansing efficiency, and was free from synthetic additives. Microbial testing ensured the absence of contamination, and user trials indicated favorable acceptance in terms of texture, fragrance, and after-use feel.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Herbal shampoo, Reetha, Shikakai, Amla, Neem, Aloe vera, natural formulation, hair care, sustainable cosmetics, phytochemicals

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Creative Commons Attribution 4.0 and The Open Definition