Volume 13 | Issue 5 |

 Abstract

The Python ecosystem has experienced exponential growth with over 400,000 packages available on the Python Package Index (PyPI), creating unprecedented challenges in package distribution and management. Despite Python's popularity, existing package distribution tools often present obstacles for developers due to complex configuration requirements and inconsistent file inclusion mechanisms. We conducted an extensive analysis of setuptools' file control capabilities and developed a systematic framework for optimizing Python package distribution across diverse deployment environments. Our implementation employs setuptools' pattern matching algorithms for selective file inclusion and exclusion, utilizing both explicit manifest files and programmatic configurations through setup.cfg and pyproject.toml. Backend operations leverage setuptools' internal discovery mechanisms alongside custom hooks for pre-processing, transforming, and validating distribution contents before packaging. The frontend experience delivers modular declarative configuration options enabling developers to precisely define package boundaries through simple declarative syntax rather than complex procedural code. Evaluation determined system effectiveness through quantitative analysis of 150 popular Python packages on PyPI, measuring distribution size optimization, installation time improvement, and configuration complexity reduction. Results demonstrated an average 23% reduction in package size through optimized file selection, 17% faster installation times, and 42% decrease in configuration complexity as measured by lines of code and cognitive complexity metrics. Usability studies with 20 Python developers confirmed statistically significant improvements in task completion rates and satisfaction scores.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Python packaging, Setuptools, Distribution control, Package optimization, Manifest files, Dependency management, Software distribution, Configuration management, Automation tools, Developer productivity.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper examines the transformative role of social media in shaping modern political revolutions in India. As India stands as one of the largest democracies and one of the most digitally active nations in the world, the intersection between social media platforms and political activism has created new paradigms of citizen engagement, mobilization, and discourse. This study investigates how platforms like Twitter, Facebook, and WhatsApp have facilitated protest movements, challenged traditional political narratives, and redefined state-citizen communication. Focusing on key political events such as the 2011 India Against Corruption movement, the Citizenship Amendment Act (CAA) protests, and farmers' protests (2020-2021), this paper critically analyses the dual nature of social media--as a tool for empowerment and as a means for misinformation and polarization. Drawing on scholarly sources, news archives, and theoretical frameworks, the paper argues that while social media has democratized information and amplified dissenting voices, it also demands vigilant regulation to preserve the integrity of democratic processes in India.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

social media, political revolution, India, protest, digital activism, CAA, IAC movement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research paper presents the Detection of diseases in plants is a significant task that has be done in agriculture. The disease caused in plants due to various pathogens like viruses, fungi, and bacteria is liable for considerable monetary losses in the agriculture corporation across the world. The security of crops concerning quality and quantity is crucial to monitor disease in plants. Plant diseases pose a serious threat to global food security and agricultural productivity. Manual disease detection methods are often time-consuming and subjective, requiring expert knowledge. This research presents an automated leaf disease detection system using computer vision and deep learning, aimed at assisting farmers in early disease identification. The system leverages image preprocessing techniques and a Convolutional Neural Network (CNN) for feature extraction and classification. The results show high accuracy in detecting common leaf diseases. This solution is intended to be cost-effective, scalable, and applicable in real-world agricultural settings.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

- Plant disease detection, image processing, image acquisition, segmentation, feature extraction, classification.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The stock market is vital to the global economy due to its capability to enable wealth creation, resource allocation, and capital formation. The impact of various elements, such as macroeconomic metrics, market mood, geopolitical occurrences, and company-related announcements, has rendered stock price forecasting a challenging endeavor for an extended period. Time-series forecasting has utilized traditional statistical models like ARIMA, linear regression, and exponential smoothing; nonetheless, these models struggle to accurately represent the non-linear dynamics of financial markets. In recent times, machine learning (ML) methods have gained popularity due to their ability to effectively manage high-dimensional, non-linear data and reveal concealed patterns. This study evaluates the performance of five machine learning models -- Linear Regression, SVR, Random Forest, XGBoost, and LSTM -- using historical stock market data from India. The research presents a comparative examination to highlight the advantages and disadvantages of each model, aiming to assist in developing more precise and adaptable financial forecasting tools.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Stock Market, MachineLearning,Price Prediction, Linear Regression (LR), Support Vector Machine (SVM), Random Forest

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In these times, it has become apparent that creativity has an important bearing in career preferences. The focus of this study looks at how creativity influences school students' development of career choices. Schools mostly encourage students to the fields which they are going to follow and teachers and authorities as well as parents have to be clear about what drives the student career decisions. One of the many variables that accounts for amazing yet undetected ability to push a student to choose a career path is creativity. In this study, an association between students' creative thinking and their career preferences has been investigated. The central hypothesis is that, because they are more creative, students with higher levels of the creativity will be more inclined towards the careers that value innovation, artistic expression, unconventional problem solving and similar type of careers from the arts, design, media, entrepreneurship and scientific research rather than peers who might have more structured, conventional type of career.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Creative, Career Preference

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Here we propose a savvy climate revealing framework over the web. Our proposed framework considers climate parameter detailing over the drug shipment which causes degradation of medicines in the healthcare industry. Drug deterioration is a major issue these days. As, during transportation of drugs it poses a serious complication for the healthcare providers who are the health professionals in the pharmaceutical industry which leads to decreased efficacy, health risks, and pecuniary losses, and special damages. This article introduces Enviro Net, a smart system that is based on Internet of Things that uses weather data to modify storage conditions in real-time, preventing medication stagnation. Enviro Net senses and controls temperature, humidity, and other various physical, chemical, and biological characteristics of a specific environment that influence the distribution, abundance, and activity, within medication transport containers using the concept of interconnected devices using sensors, microcontrollers, and communication technologies to gather and transmit data. The technology actively regulates storage conditions to ensure optimal temperature control throughout the transportation phase by fusing historical climatic data with real-time weather forecasts or current weather outlook, or updated weather report. It is impossible to overestimate Enviro Net's promise to improve the safety, efficacy, and dependability of medicine delivery; this article describes its development, implementation, and evaluation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

-Internet of Things; cloud; mobile application; sensor network; environmental monitoring

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial Intelligence (AI) has revolutionized various industries, and its impact on the recruitment process has been profound. AI-driven hiring systems enhance efficiency, candidate experience, and data-driven decision-making, offering organizations the ability to streamline talent acquisition. AI facilitates automation in resume screening, interview scheduling, and candidate assessments, reducing biases and improving hiring outcomes. However, the integration of AI in recruitment also brings ethical concerns, particularly regarding data privacy, algorithmic bias, and transparency. This paper explores AI's role in recruitment, the benefits it offers, ethical concerns, and its future potential, supported by academic research and real-world applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence (AI), Recruitment, Hiring, Talent Management, Screening, Predictive Analytics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

For a country like India, where democracy is the bedrock of all governing systems, governance must be inclusive and heavily influenced by citizen participation. In a democracy like ours, an accountable and transparent governing system necessitates the participation of citizens at all levels. People's participation, on the one hand, can assist the government in formulating better policies that can then be communicated to the public and implemented effectively. Citizens will be more likely to participate in the mainstream political process if government policies are inclusive and people-friendly. As a result, whether people participate directly, such as by running for office, or indirectly, such as by voting or being a part of the election process, the government is strengthened and more people-friendly policies are implemented. As a result, good governance must be viewed as a two-way process: on the one hand, the government must ensure that good governance values such as accountability and transparency are considered when formulating policies, and on the other hand, citizens must participate in the governance process in order to improve it. Election is the process by which we elect our representatives for forming government. India is the biggest democracy in the world. A free and fair election is the backbone of a healthy democracy. Malpractices in the elections distort the political, social, and economic outcomes in addition to distorting the quality of representation. Elections are an important part of democracy, and excellent elections increase the political legitimacy of the leadership. This is emphasized in the Inter-Parliamentary Council's (IPC) 'Declaration on Criteria for Free and Fair Elections,' which begins: "The government's authority can only come from the people's will, expressed in authentic, free, and fair elections held at regular intervals on the basis of universal, equal, and secret suffrage."

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Democracy, Good-governance, Inter-Parliamentary, Malpractices

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

e-commerce,user,product sentiment,reviews ui,modeling, encoder , customer

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Women's safety in public spaces should not calculate on chance or introductory security styles traditional tools like CCTV cameras and details generally respond after an incident happens they do not stop problems from being these styles constantly warrant the capability to predict risks in real time this creates a big gap in safety plans that concentrate only on replying as technologies like artificial intelligence machine knowledge computer vision and the internet of goods meliorate snappily were moving toward smarter security systems these new systems can snappily spot possible troubles notice unusual conduct and automatically start safety procedures using these tools makes safety measures more flexible and quick to respond they can advise police and other askers right down indeed helping to avoid detriment before it occurs this composition introduces the a powered women's safety analytics system this system is designed to learn from its surroundings understand gets patterns and take fast safety conduct a pivotal part of this system is its capability to fete gender through deep knowledge this helps descry strange trends like a woman alone in a busy area or an unlooked-for crowd forming which could gesture a safety concern the system also uses special discovery styles like autoencoders and one- class SVMs along with disguise estimation tools analogous as open disguise and disguise net these tools anatomize how people move and stand they can identify movements that might mean someone is in trouble or feeling uncomfortable allowing for quick help unlike aged systems that need people to oversee them all the time this ai predicated system improves trouble discovery and waves up contact with police it also has a new point gesture grounded SOS signals sometimes women in pitfall can not press a fear button or make a call the system can recognize specific moves body signals or voice cues that show torture deep knowledge algorithms trained to descry urgency in speech can shoot cautions automatically indeed without physical contact this provides a quick and hands-free way to call for help the system also uses prophecy tools that anatomize formerly crime data cover current situations and produce heatmaps of risks this helps authorities see implicit troubles before problems be insulation and fairness are truly important particular data is kept safe with encryption and the system is erected to avoid bias its thing is to meliorate safety without violating individual rights or insulation.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sentiment analysis, partitioning dataset, parallel processing, combining results.

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Creative Commons Attribution 4.0 and The Open Definition