*.csv

The attached zip contains both data and analysis scripts for the first two particle-in-cell examples in the associated paper. In particular,
(1) The BeamExpansion folder contains output z vs r phase space data from the quasi-Helmholtz FEMPIC code used in the paper at 3 ns (fempic.csv), as well as the equivalent data from an XOOPIC simulation (xoopic.txt). The analysis is done in the ipython notebook file in the folder. All of the plots in the paper was generated using this same script.
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The recent developments in the field of the Internet of Things (IoT) bring alongside them quite a few advantages. Examples include real-time condition monitoring, remote control and operation and sometimes even remote fault remediation. Still, despite bringing invaluable benefits, IoT-enriched entities inherently suffer from security and privacy issues. This is partially due to the utilization of insecure communication protocols such as the Open Charge Point Protocol (OCPP) 1.6. OCPP 1.6 is an application-layer communication protocol used for managing electric vehicle chargers.
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An integrated analysis using association rule mining and network pharmacology to identify therapeutic combinations of herbal materials and compounds in traditional medicine.
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Legal analysis utilizing natural language processing and machine learning technologies is a difficult undertaking that has recently sparked the interest of many academics and industries. Using a human-annotated dataset summarized into colloquial Thai from Supreme Court decisions, this work investigates a different combination of NLP, ML, and rule-based techniques for accurate legal case analysis as per Thai law, especially property-related offences, with the intuition to imitate the lawyer's cognitive process.
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We curated and release a real-world medical clinical dataset, namely MedCD, in the context of building generative artificial intelligence (AI) applications in the clinical setting. The MedCD dataset is one of the accomplishments from our longitudinal applied AI research and deployment in a tertiary care hospital in China. First, the dataset is real and comprehensive, in that it was sourced from real-world electronic health records (EHRs), clinical notes, lab examination reports and more.
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Race track dataset for a mobile fun racer. Used for the evaluation of a not yet published journal paper. Specific reference will be added here once the paper has been accepted and published.
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In this study, we analyzed the data on MLB pitchers data, using datasets derived from Statcast. Introduced in 2015, Statcast is an advanced tracking technology capable of capturing detailed information on pitch tracking, bat tracking, etc. in every MLB game. Currently, all 30 MLB ballparks are equipped with Statcast systems, and since the introduction of the Hawk-Eye technology in 2020, this system has achieved an impressive tracking rate of 99\% for batted balls.
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This dataset from the Ateneo Experience Sampling App (AESapp) contains 618 records assessing student emotional states (happiness, engagement, anger, anxiety, sadness) and contextual factors (online status, online activity, location, activity, companionship). Of these, 454 responses are complete. Each entry includes a timestamp, user ID, and response status. The dataset enables analysis of within-person and between-person variations in well-being, examining how situational factors influence emotions over time.
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This dataset contains results and scripts from experiments evaluating the resilience of the QUIC protocol against handshake flooding attacks. It aims to support researchers and developers in analyzing the performance of QUIC against handshake flooding attacks. The experiments utilize three prominent QUIC implementations: aioquic, quic-go, and picoquic, providing a comprehensive comparison of their resilience. Additionally, to benchmark the performance and resilience of QUIC, SYN flood attacks were conducted against TCP with SYN cookies.
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