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Search-based software testing (SBST) is now a mature area, with numerous techniques developed to tackle the challenging task of software testing. SBST techniques have shown promising results and have been successfully applied in the industry to automatically generate test cases for large and complex software systems. Their effectiveness, however, has been shown to be problem dependent.
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A contiguous area cartogram is a geographic map in which the area of each region is proportional to numerical data (e.g., population size) while keeping neighboring regions connected. In this study, we investigated whether value-to-area legends (square symbols next to the values represented by the squares' areas) and grid lines aid map readers in making better area judgments. We conducted an experiment to determine the accuracy, speed, and confidence with which readers infer numerical data values for the mapped regions.
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This dataset file is used for the study of imbalanced data and contains 6 imbalanced datasets
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This dataset includes real-world time-series statistics from network traffic on real commercial LTE networks in Greece. The purpose of this dataset is to capture the QoS/QoE of three COTS UEs interacting with three edge applications. Specifically, the following features are included: Throughput and Jitter for each UE-Application and Channel Quality Indicator (CQI) for each UE. The interactions were generated from a realistic network behavior in an office by developing multiple network traffic scenarios.
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This study reports the properties and the sensing mechanism of Pd nanoparticles (PdNPs) decorated n+/n-/n+ double-junction silicon nanobelt (SNB) device as hydrogen (H2) gas sensor. The SNB devices are prepared via CMOS process. Plasma-enhanced atomic layer deposition (PEALD) is adopted for PdNPs deposition as sensing material on the Al2O3 dielectric of SNB devices. The PdNPs-decorated SNB devices working at room temperature are characterizedat H2 concentration ranging from 10 to 1000 ppm.
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For the purpose of experimentation, the historical stock prices of three petroleum companies: Pakistan State Oil (PSO), Hascol, and Attock Petroleum Limited (APL), are extracted from the Pakistan Stock Exchange (PSX) website through a web scrapper for the last four years. Different attributes related to the stocks of each of these companies are extracted for each day. Along with this, for each of these companies, Twitter data for sentiment analysis is also extracted using Twint.
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A mobile sensor can be described as a kind of smart technology that can capture minor or major changes in an environment and can respond by performing a particular task. The scope of the dataset is for forensic purposes that will help segregate day-to-day activities from criminal actions. Smartphones supplied with sensors can be utilised for monitoring and recording simple daily activities such as walking, climbing stairs, eating and more. For the generation of this dataset, we have collected data for 13 classes of daily life activities, which has been done by a single individual.
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Using Python. we crawl a total of 18, 793 diabetes related Q&A between Jun. 1, 2016 and Sept. 1, 2020 on xywy.com, a famous Chinese Online Medical Community. Each data contains four parts of the question detail page: Title, Problem Description, User ID and Question Time, and three parts of the doctor’s answer page: Doctor ID, Answer Content and Answer Time. After preprocessing such as cleaning and deduplication, we finally obtain 18,521 valid data.
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COVIDSentiRO contains 19319 Romanian tweets extracted in the time-frame 01.01.2021 - 28.02.2022 using query words related to COVID-19 vaccination. Each tweet has its timestamp associated and is labelled with positive, negative and neutral, using the SART dataset for sentiment analysis.
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