Computational Intelligence
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The dataset aims to facilitate research in the optimization of the carbon footprint of recipes. Consisting of 30 Excel files processed through various Python scripts and Jupyter notebooks, the dataset serves as a versatile resource for both performance analysis and environmental impact assessment. The unique attribute of this dataset lies in its ability to calculate representative values of carbon footprint optimization through multiple algorithmic implementations.
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RITA (Resource for Italian Tests Assessment), is a new dataset of academic exam texts written in Italian by second-language learners for obtaining the CEFR certification of proficiency level.
In addition to the tests, RITA provides a variety of speech elements, annotations, and statistics, including phraseological units and their syntactic dependencies. The dataset consists of two corpora: one containing the task assignment and the other containing the texts elaborated by the learners in response to the assignment. This work describes the
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Please cite the following paper when using this dataset:
N. Thakur, K. A. Patel, I. Hall, Y. N. Duggal, and S. Cui, “A Dataset of Search Interests related to Disease X originating from different Geographic Regions”, Preprints 2023, 2023081701, DOI: https://doi.org/10.20944/preprints202308.1701.v1
Abstract:
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The dataset that we published in this data repository can be used to build neural networks-based inverse kinematics for NAO robot arms. This dataset is named ARKOMA. ARKOMA is an acronym for ARif eKO MAuridhi, all of whom are the creators of this dataset. This dataset contains input-output data pairs. In this dataset, the input data is the end-effector position and orientation, while the output data is a set of joint angular positions. For further applications, this dataset was split into the training dataset, validation dataset, and testing dataset.
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Most plant diseases have observable symptoms, and the widely used approach to detect plant leaf disease is by visually examining the affected plant leaves. A model which might carry out the feature extraction without any errors will process the classification task successfully. The technology currently faces certain limitations such as a large parameter count, slow detection speed, and inadequate performance in detecting small dense spots. These factors restrict the practical applications of the technology in the field of agriculture.
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This data collection focuses on capturing user-generated content from the popular social network Reddit during the year 2023. This dataset comprises 29 user-friendly CSV files collected from Reddit, containing textual data associated with various emotions and related concepts.
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Problems related to ventral hernia are very common, and evaluating them using computational methods can assist in selecting the most appropriate treatment. This study collected data from over 3500 patients from different European countries observed during last 11 years (2012-2022), which were collected by specialists in hernia surgery. The majority of patients underwent standard surgical procedures, with a growing trend towards robotic surgery. This paper focuses on statistically evaluating the treatment methods in relation to patient age, body mass index (BMI), and the type of repair.
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The e-nose device used in this study was constructed using a gas sensor array, LCD display, micro air pumps for inhalation and exhalation, a microcontroller, and a mini-PC. Gas samples from the sample chamber were periodically drawn into the device through a hose. Each sample underwent a 30-hour sampling process at room temperature (25°C). The sampling frequency was 15 times per hour, resulting in 60 records per sample.
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