Volume 12 | Issue 4 |

 Abstract

Research introduces "EtherDrug," a decentralized Pharmaceutical Supply Chain Management System leveraging Ethereum blockchain technology to combat counterfeit drugs and pharmaceutical trafficking. By utilizing a technology stack comprising Ethereum, MetaMask, Ganache, Truffle, Solidity, HTML, and CSS, the project orchestrates a systematic approach, beginning with node registration and order placement with Medicine ID and quantity specifications. The system meticulously controls each transaction, allowing individual nodes to accept or reject orders, while real-time tracking provides precise updates on the location and timestamp of medicines within the supply chain. This innovative solution not only addresses the immediate need for transparency and security in drug supply chains but also contributes to the broader discourse on blockchain's application in ensuring pharmaceutical quality, safety, and efficacy, offering a practical solution to industry-wide challenges.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

EtherDrug, Ethereum Blockchain Technology, Counterfeit Drugs, Pharmaceutical Trafficking.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Now day's people are searching for something creative and smart technologies for the various events and also for the entertainment purpose, so we are creating our project on the pyro machine or the automatic fire blast machine.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

smart pyro machine, fire blast, automatic, creative

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A brain stroke is a medical disorder where the brain is damaged due to a burst in the blood vessels in the brain. These symptoms occur if the supply of blood or any other nutritional resources to the brain are interrupted. The studies indicate that brain stroke is the primary cause of death and disability worldwide. Timely detection of strokes is essential for effective treatment. Current stroke detection techniques include machine learning, but they struggle with complex patterns in medical imaging and need human-designed features. These approaches cause slower diagnosis and erroneous outcomes. To estimate the probability of early-stage brain strokes, the paper experiments using various algorithms, including VGG16, XGBoost, GNN, and EfficientNetB3 architectures. To determine the effectiveness of the algorithms, a reliable dataset for stroke detection was taken from Kaggle website. Several classification models, including XGBoost, VGG-16, EfficientNetB3, and GNN were used. By training the model on a large dataset and classifying using different algorithms the XGBoost has produced the highest accuracy of 97.94% than the GNN, VGG-16, and EffiientNetB3 which produced an accuracy of 73.68%, 87.26%, 75.28% accuracy. This paper showed that XGBoost performed better compared to other algorithms.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Extreme Gradient Boosting, Visual Geometric Group 16 (VGG 16), Graph Neural Network ( GNN), Stroke detection XG Boost.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

English as a Second Language (ESL), is an educational curriculum designed to help non-native speakers improve their English language skills. In today's increasingly interconnected and diverse world, having proficiency in English is a threshold to global opportunities. ESL students face a number of challenges as they venture down the path of learning the English language, hence the role of English teachers is substantial in helping students face and overcome the challenges. This paper focuses on the variety of learning difficulties the ESL students face in the classroom, which could negatively impact the student's learning progress, and features the valuable insights to effectively support students in overcoming them.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: ESL, learning, challenges, skills, strategies, understanding

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Paper begins with the Introduction of the title and on which thesis will develop upon. The paper will give deep explanation to the concept of feminism dividing it in different section such as definitions, characteristics and waves of feminism so that it will be clear to the readers who are not aware of the term feminism, the detailed information will be given on writer's ideology on feminism, with it the concept of identity will also be introduced to the readers by giving its definition, importance and how it is related with the novel The Golden Notebook and The Grass is Singing and how the writer have shown both Feminism and identity in her novel. The Golden Notebook and The Grass is singing will be shown how it is meant to be a feminist Novel as other feminist works. Second a brief introduction of the novel will be given with its background, thematic concerns and the character sketch of protagonist which will give idea and hint to the readers.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

The Quest for identity and Feminist approach in Doris Lessing's The Golden Notebook and The Grass is Singing

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Digital platforms can connect people, organizations, and resources to facilitate the core interactions between businesses and consumers To facilitate the essential interactions between businesses and consumers and ensure increased efficiency for company management, digital platforms can connect people, organizations, and resources. As a result, the foundation of new company concepts, like creative start-ups, is built on creativity, scalability, and connections with the surrounding community. The objective is to identify important organizations that support startups in their establishment and growth, pinpoint regions in which startups receive assistance from the social networks of their key members and/or founders, and examine the correlation between the kinds of contacts and support offered. These networks comprise friends and business partners in terms of their use rates, important roles, and level of support, as well as business angels in terms of finance and advice on technology and marketing. Certain weak ties have different uses (both positively and adversely) than they have importance. Although business incubators assisted 50% of businesses, the incubators' assistance in creating networks and connections with the outside world appears to be underappreciated. Our findings suggest that networking initiatives with outside parties should be part of startup support programs

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital platforms, Startups, Community connections, Business partners, Startup support programs.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this era where every aspect of our day-to-day life is gadget-oriented, there is a huge volume of data that has been emanating from various digital sources. Today there are millions of data sources that generate data at a very rapid rate. Data analytics uses analytic techniques to examine data, thus obtaining and find out information like hidden patterns. The agriculture industry has witnessed a remarkable transformation in recent years, thanks to the integration of Big Data and advanced technologies such as machine learning(ML) and Internet of Things(IoT). Big Data analytics has opened up new possibilities for optimizing farming practices, increasing yields, and ensuring food security. This paper will explore how Big Data has revolutionizing agriculture and provided some applications. Big Data contribute to making timely recommendations to farmers with regard to smart agricultural techniques. One purpose of current research is to get a better knowledge of the present state of Big Data processing in Agriculture and even to uncover underlying challenges that need to be addressed.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Big Data, Data Analytics, smart agriculture, Machine Learning(ML), IoT

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The unique strategy to tracking and monitoring mental health that this paper presents makes use of data science and artificial intelligence/machine learning (AI/ML) approaches. The project's goal is to produce a complete mental health tracker system that can analyze various data sources and offer chances for early intervention and individualized insights. The system integrates information from several sources, including wearable technology, social media activity, calendar events, and self-reported mood assessments, by utilizing AI/ML algorithms. The tracker uses sophisticated data analysis and predictive modelling to find patterns, trends, and possible risk factors related to variations in mental health. In addition, the system makes use of feedback mechanisms and real-time monitoring to enable people to take proactive measures to maintain their mental health. The project offers a scalable and easily available solution for ongoing mental health monitoring and support, helping to close the gap between conventional mental health evaluation techniques and cutting-edge technologies.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

logistic regression, K-nearest neighbors (KNN), behavioral analysis.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The paper "Examining the Adoption and User Experience of Mobile Payment Solutions in the Era of Fintech Revolution" delves into the evolving landscape of financial technology, focusing particularly on the rise of mobile payment options. With the fintech revolution reshaping traditional banking practices, mobile payment systems have emerged as convenient, secure, and efficient alternatives to cash and cards. The research aims to understand the factors influencing user adoption and experience with these technologies, spanning across demographic, cultural, regulatory, and technological dimensions. Despite their potential to promote financial inclusion and streamline transactions for individuals and businesses alike, mobile payment systems face challenges such as digital divides, technological biases, and regulatory differences. By exploring these complexities and limitations, the study seeks to provide valuable insights for policymakers, businesses, and researchers navigating the dynamic landscape of mobile payments in the digital age.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fintech, Mobile Payment Solutions, User Experience

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A macrobenthic study was carried out at different ghats of Yamuna river at Mathura after falling down Drain effluents. 7 Ghats (Gau ghat, Swami ghat, Askunda ghat, Vishram ghat, Bangali ghat, Dhruv ghat, Mahadev ghat) were used as sampling stations for sampling of Macrobenthos from (March 2021 to April 2022). Macrobenthos from three types of phylum Arthropoda, Annelida, Mollusca were recorded. Among these three phylum, Maximum species of phylum Arthropoda were recorded at every station in summer. Maximum species density of Molluscs and Annelids were recorded at Gau ghat & Dhruv ghat may be due to shallow clean water and river soil having highest organic carbon and Minimum at Mahadev ghat and Askunda ghat may be due to dirty water, because of falling drain effluents. Annelid's species Namalyastis sp. and Mollusc's species Pila sp. were present at maximum stations from others. Arthropoda community were observed dominated from Annelids and Molluscs. Arthropodal species Caenis sp. and Chironomial sp. were dominant at maximum stations from others. Following results were determined as species richness from classes - Insecta - Arthropoda at polluted ghats (station -3,7) Oligochaeta & Hirudinea - Annelida at (station-1,6) and Gastropoda &Bivalvia - Mollusca at less polluted site (station-1,2,6).

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Macrobenthos, Drain effluents, Gastropods, Species richness.

  License

Creative Commons Attribution 4.0 and The Open Definition