Artificial Intelligence
This is a subset of the original GDB-9-Ex_EOM-CCSD dataset at https://doi.org/10.13139/OLCF/2318313. It consists of 100 randomly selected molecules from the original dataset that consists of 80,593 molecules. This dataset contains data-intensive quantum chemical electronic structure calculations for organic molecules of the GDB-9-Ex dataset. Calculations were performed using the Equation of Motion Coupled Cluster (EOM-CCSD) first principles method using the ORCA software.
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This is a subset of the original GDB-9-Ex_TD-DFT-PBE0 dataset at https://doi.org/10.13139/OLCF/2318314. It consists of 100 randomly selected molecules from the original dataset that consists of 96,766 molecules. The dataset contains data-intensive quantum chemical electronic structure calculations for organic molecules of the GDB-9-Ex dataset. Calculations were performed using the Time Dependent Density Functional Theory (TDDFT) first principles method using the ORCA software.
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The Smart Home Device Dataset consists of 5000 samples collected at an hourly interval starting from January 2022, representing consumer electronics and IoT-enabled devices in a home automation environment. Each entry is associated with a unique device ID, ensuring identification of distinct devices. The dataset captures real-time sensor readings, including temperature variations (18°C to 30°C), power consumption levels (10W to 500W), and user activity states (Active, Idle, or Sleep), which provide contextual insights into device operation.
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The IARPA Space-Based Machine Automated Recognition Technique (SMART) program was one of the first large-scale research program to advance the state of the art for automatically detecting, characterizing, and monitoring large-scale anthropogenic activity in global scale, multi-source, heterogeneous satellite imagery. The program leveraged and advanced the latest techniques in artificial intelligence (AI), computer vision (CV), and machine learning (ML) applied to geospatial applications.
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This project contains data from four datasets used in the experiments of the paper: LIS, ExDark, ACDC, and DarkFace.
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The Dash Cam Video Dataset is a comprehensive collection of real-world road footage captured across various Indian roads, focusing on lane conditions and traffic dynamics. Indian roads are often characterized by inconsistent lane markings, unstructured traffic flow, and frequent obstructions, making lane detection and traffic identification a challenging task for autonomous vehicle systems.
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We construct the Thyroid Nodule Ultrasound (TNUS) dataset with thyroid nodule positions and puncture annotations, lacking in existing datasets. It supports future research in automating detection and diagnosis, enhancing diagnostic accuracy and clinical applications. The TNUS dataset is a curated collection of thyroid nodule ultrasound (US) images designed to support research in puncture position detection and nodule segmentation. It contains 4,376 images with puncture position annotations and 2,626 additional images with thyroid/nodule masks.
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ÛThis article examines Meta-AI's sociolinguistic challenges on WhatsApp through research-based analysis of its limitations in adapting lexicon and precise ethical practices in intercultural communication. The study demonstrates how Meta-AI system fails to read truncated vernacular speech patterns (“kenapa” → “enapa”) while missing customized slang (“puki”) used specifically in Maluku, North Maluku and East Nusa Tenggara regions to show fundamental limitations in error recognition capabilities and contextual understanding.
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This is the patent data we collected from USTPO. Its part of the paper that we used for our study. It contains patent data regarding financial, assistive, and artificial intelligence technology convergence. These patents are all registered in USPTO (united states patent and trademark office) from 2001 to 2020. These data were used for network analysis. Further details will be uploaded after paper acception.
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Dataset was created for the purposes of exploring time distortion with non-ideal near-field conditions. A 90 Hz square wave is played at 100dBA through a bookshelf speaker with the port removed. The recordings were captured at 5 separate axial distances (From 2" to 17", following inverse square law), and at three levels of resistive loading (No added resistance, 1.5 ohm, 3 ohm). The DC resistance of the speaker was measured at 6.9 ohms. To avoid overtraining, captures were recorded on a moving dynamic microphone.
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