artificial intelligence
Internet-of-Things (IoT) technology such as Surveillance cameras are becoming a widespread feature of citizens' life. At the same time, the fear of crime in public spaces (e.g., terrorism) is ever-present and increasing but currently only a small number of studies researched automatic recognition of criminal incidents featuring artificial intelligence (AI), e.g., based on deep learning and computer vision. This is due to the fact that little to none real data is available due to legal and privacy regulations. Consequently, it is not possible to train and test deep learning models.
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This dataset comprises data created during research on AI-generated code, with a focus on software engineering use-cases. The purpose of the research was to investigate how AI should be integrated into university software engineering curricula.
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Overview
The dataset under consideration is a comprehensive compilation of code snippets, function descriptions, and their respective binary representations aimed at fostering research in software engineering. It contains a variety of code functionalities and serves as a valuable resource for understanding the behavior and characteristics of C programs. This data is sourced from the AnghaBench repository, a well-documented collection of C programs available on GitHub.
Columns and Data Types
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The Narrative question answering (QA) problem involves generating accurate, relevant, and human-like answers to questions based on the comprehension of a story consisting of logically connected paragraphs. However, this problem remains unexplored for the Arabic language because of the lack of Arabic narrative datasets. To address this gap, we present the Arabic-NarrativeQA dataset, which is the first dataset specifically designed for machine-reading comprehension of Arabic stories.
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This research introduces the Open Seizure Database and Toolkit as a novel, publicly accessible resource designed to advance non-electroencephalogram seizure detection research. This paper highlights the scarcity of resources in the non-electroencephalogram domain and establishes the Open Seizure Database as the first openly accessible database containing multimodal sensor data from 49 participants in real-world, in-home environments.
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290 Views
Sentiment analysis, which aims to identify the positive or negative tone of a given text, has seen a surge in interest over the past two decades, making it one of the most studied areas of study in the fields of Natural Language Processing and Information Extraction. Due to the ambiguous nature of sarcasm, however, sarcasm detection is an essential part of sentiment analysis. The task becomes exceedingly challenging when applied to a language with a more intricate morphology and a lack of available resources, such as Telugu.
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Gorakhpur is a city located in the north-eastern region of
Uttar Pradesh state of India. It is a sub-part of Purvanchal
region of Uttar Pradesh and Bihar. In the south-western
part, Gorakhpur periphery spreads along Rapti river. In
the north-western region, Gorakhpur shares its periphery
with Chillua Tal. In the southern part, Ramgarh Tal with a
perimeter of 18 km is located.
Water Bodies:
+ Ramgarh Tal is a historically important heritage site and
is also a tourist attraction; spread over 700 hectares of
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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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937 Views
This is the full ChatGPT transcript for the IEEE Power Engineering Letter "On the Potential of ChatGPT to Generate Distribution Systems for Load Flow Studies using OpenDSS". The abstract for the letter is as follows:
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415 Views
FormAI is a novel AI-generated dataset comprising 112,000 compilable and independent C programs. All the programs in the dataset were generated by GPT-3.5-turbo using dynamic zero-shot prompting technique and comprises programs with varying levels of complexity. Some programs handle complicated tasks such as network management, table games, or encryption, while others deal with simpler tasks like string manipulation. Each program is labelled based on vulnerabilities present in the code using a formal verification method based on the Efficient SMT-based Bounded Model Checker (ESBMC).
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