*.bib; *.xlsx;
Cyberbullying is a growing problem on social media. This dataset helps detect cyberbullying in Bangla by collecting comments from YouTube, Facebook, Instagram, and TikTok. The data is categorized into two types: bullying and non-bullying. It includes various abusive and harmful texts, along with normal conversations. This dataset will help researchers and developers train AI models to automatically identify cyberbullying in Bangla text. The goal is to create better tools to keep online spaces safe for Bangla-speaking users.
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This repository contains the code and documentation for a computational framework that leverages machine learning techniques to enable accurate classification of bacterial species, even closely related strains.
The framework integrates genomic analysis methods, such as motif screening and single nucleotide polymorphism (SNP) extraction, to derive informative features from bacterial genomes. These genomic insights are then fed into machine learning models, which are trained to reliably differentiate between bacterial species based on their distinctive patterns and characteristics.
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Self-Reconfigurable Modular robotic Systems (SRMSs) can physically connect and form a variety of morphologies without the need for external intervention. The morphology transformation problem of an underwater SRMS is critical to various functionalities. Morphology decomposition and reconnections are reduced by clustering some modules together. The file includes the x and y coordinates of modules in a self-reconfigurable robotic system.
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This dataset offers a comprehensive collection of financial data associated with the development of medical software, providing insights into the various cost components involved in creating and maintaining such systems. It encompasses expenses from the initial concept and design phase through to development, testing, deployment, and ongoing maintenance. The data has been meticulously gathered from a variety of completed and ongoing medical software projects, highlighting both typical and outlier cost scenarios.
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Spectroscopic ellipsometry measurements were conducted to determine optical constants of CdSexTe1-x (CST) compounds deposited through co-evaporation, with the composition parameter (x) ranging from 0 to 1. The dielectric function spectra obtained from these thin films were interpolated using an energy-shift algorithm to develop a comprehensive optical library for the CST compound with x ranging from 0 to 1 with a 0.001 step.
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The dataset includes 22 projects and 1680 user stories, with the aim of classifying these stories into those suitable for AI implementation and those not recommended for AI implementation. The labeling was done in a group, reaching a consensus on each user story in each project, determining whether it is susceptible to being developed with AI. Thus, each user story was evaluated and assigned a value of 1 if it was considered suitable for AI implementation (this label was named AI), and a value of 0 if it was not (this label was named not-AI).
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We investigate whether hypothesis testing can be improved by a simple prompt to ‘think in opposites’, a strategy suggested by a growing body of literature as being beneficial in various reasoning and problem-solving contexts.
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The study investigates the relationship between people’s personality and the types of hats they like and would be willing to wear. The question is of interest for the psychology of personality and aesthetic preferences, empirical aesthetics, and potentially also for marketing studies. 539 Italian adults completed an on-line questionnaire showing black and white images of 34 iconic types of hat (set 1) and 8 types of baseball caps (set 2) one at a time. For each hat, they were asked to rate how much they liked it and how likely it was that they would wear it.
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Precise modeling of dynamical systems can be crucial for engineering applications. Traditional analytical models often struggle when capturing real-world complexities due to challenges in system nonlinearity representation and model parameter determination. Data-driven models, such as deep neural networks (DNNs), offer better accuracy and generalization but require large quantities of high-quality data.
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159 Views
Each sheet in this document meticulously details the electrical parameters of the grounding networks. Among all these parameters, touch voltage stands out as the most critical factor to consider in each evaluated conductor configuration.
The determination of these physical configurations is based on meticulous measurement of the distances between conductors on one side of the grid. It's important to note that in this context, square grids are being employed for grounding, which implies a specific arrangement of conductors.
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