Data in Brief最新文献_第9页

ABRLog: a multi-device android bugreport log dataset for intelligent analysis ABRLog：用于智能分析的多设备android bug报告日志数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-07 DOI: 10.1016/j.dib.2026.113230

Ricardo Miranda Filho, João Alfredo Bessa, Rosiane de Freitas

{"title":"ABRLog: a multi-device android bugreport log dataset for intelligent analysis","authors":"Ricardo Miranda Filho, João Alfredo Bessa, Rosiane de Freitas","doi":"10.1016/j.dib.2026.113230","DOIUrl":"10.1016/j.dib.2026.113230","url":null,"abstract":"<div><div>Android devices generate a wealth of diagnostic data through their built-in logging subsystems, offering invaluable insights into application behavior, hardware performance, and operating system stability. However, the effective utilization of this data for intelligent analysis — particularly, for anomaly detection, failure diagnosis, and security monitoring — remains constrained by the scarcity of publicly available, well-structured, and multi-device log datasets. To address this gap, we introduce ABRLog (Android BugReport Log), a comprehensive multi-device log dataset derived from bug report captures collected across 15 distinct Android devices representing five major manufacturers (Samsung, Motorola, Google, Xiaomi, and Huawei) and spanning six Android versions, from 9 to 14. A total of 45 bugreport archives were systematically processed through two complementary extraction strategies: (i) line-by-line regular expression matching for granular event extraction; and (ii) section-based delimiter parsing for high-level block segmentation. This dual approach yielded 1012 structured log files, organized into 24 semantically coherent block types. The final dataset comprises approximately 10 million log lines (1.14 GiB), extracted from 6.34 GiB of raw bugreport data. By providing a systematically curated, multi-vendor, multi-version log corpus, ABRLog aims to serve as a foundational resource for the development and benchmarking of machine learning models for log-based anomaly detection, predictive maintenance, and intelligent system diagnostics on Android platforms.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113230"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149045888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental data from an open-source DC motor control educational kit for calibration, system identification, and controller validation 实验数据从一个开源的直流电机控制教育套件校准，系统识别，和控制器验证

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-17 DOI: 10.1016/j.dib.2026.113274

Alejandro Von Chong, Dorindo Cárdenas

{"title":"Experimental data from an open-source DC motor control educational kit for calibration, system identification, and controller validation","authors":"Alejandro Von Chong, Dorindo Cárdenas","doi":"10.1016/j.dib.2026.113274","DOIUrl":"10.1016/j.dib.2026.113274","url":null,"abstract":"<div><div>This data article presents raw and processed experimental data collected with the OpenMCT DC motor control educational kit. The dataset includes current-sense calibration data, static motor characterization data, system-identification logs at four sampling times, continuous PI controller validation at four loop periods, discrete controller validation for three controller designs, and an additional chirp-excitation characterization run. The raw acquisition files were exported from the OpenMCT Python/Qt graphical user interface as comma-separated text files containing reference commands, measured speed, loop interval, raw and filtered current-sense values, PWM command, and synchronized digital multimeter measurements. MATLAB scripts, processed files, model tables, screenshots, and exported figures are provided to reproduce the data organization and plots. The records can be used to prepare laboratory exercises in which students identify a motor model and compare its predicted response with experimental measurements. They also provide reference data for evaluating alternative identification and controller-validation methods.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113274"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149045889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Concrete400: A multi-task pixel-level crack dataset from urban infrastructure in Vietnam 混凝土400：来自越南城市基础设施的多任务像素级裂缝数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-09 DOI: 10.1016/j.dib.2026.113246

Le Hoai Nam, Nguyen Ngoc Lan, Vu Manh Trung, Nguyen Nam Son, Vu Quang Tuyen, Tran Ngoc Hoa

{"title":"Concrete400: A multi-task pixel-level crack dataset from urban infrastructure in Vietnam","authors":"Le Hoai Nam, Nguyen Ngoc Lan, Vu Manh Trung, Nguyen Nam Son, Vu Quang Tuyen, Tran Ngoc Hoa","doi":"10.1016/j.dib.2026.113246","DOIUrl":"10.1016/j.dib.2026.113246","url":null,"abstract":"<div><div>Concrete400 is a multi-task concrete crack dataset for visual infrastructure inspection. It contains 379 RGB photographs of building surfaces and concrete pavements in Hanoi, Vietnam, with manually prepared pixel-level crack masks and corresponding text files containing crack region bounding box annotations. The release also includes 1502 labelled image patches for binary crack classification, comprising 633 crack patches and 869 no-crack patches. The collection preserves field variability in illumination, concrete texture, surface condition, background clutter, and acquisition time. The released segmentation and object detection images, masks, and box coordinates are standardised to 512 <span><math><mo>×</mo></math></span> 512 pixels, while the classification patches are provided at 256 <span><math><mo>×</mo></math></span> 256 pixels. The accompanying reproducible protocol defines 303 training and 76 validation image–mask pairs. After masks are binarised at an intensity threshold of 127, crack pixels represent 3.08% of image pixels on average. Concrete400 can therefore support patch-level crack classification, semantic crack segmentation, instance-style crack region segmentation, object detection, semi-supervised and self-supervised learning, and crack image generation under realistic inspection conditions.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113246"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149045947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of floating waste and river vegetation images collected from turbid rivers in Banjarmasin, Indonesia 从印度尼西亚班加马辛的浑浊河流中收集的漂浮废物和河流植被图像数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-16 DOI: 10.1016/j.dib.2026.113265

Iphan F. Radam, Yuslena Sari, Muhammad Ryan Rizky Rahmadi, Muhammad Alkaff, Irham Maulani A․G, Mohammad Zaki Firmansah, Natalie Grace Katiandagho, Zainil Musthofa Radam, Fatih Alfayruz, Nashry Akbar

{"title":"A dataset of floating waste and river vegetation images collected from turbid rivers in Banjarmasin, Indonesia","authors":"Iphan F. Radam, Yuslena Sari, Muhammad Ryan Rizky Rahmadi, Muhammad Alkaff, Irham Maulani A․G, Mohammad Zaki Firmansah, Natalie Grace Katiandagho, Zainil Musthofa Radam, Fatih Alfayruz, Nashry Akbar","doi":"10.1016/j.dib.2026.113265","DOIUrl":"10.1016/j.dib.2026.113265","url":null,"abstract":"<div><div>This dataset contains images of floating waste and river vegetation collected from several turbid river locations in Banjarmasin, South Kalimantan, Indonesia. The dataset combines still photographs and image frames extracted from video recordings, with video frames extracted at approximately one frame per second. The collected images were manually screened to remove images that did not contain relevant objects before annotation. The final dataset consists of 1,577 unique RGB images containing two object categories, namely floating waste and river vegetation. Each image was manually annotated using bounding boxes and stored in YOLO annotation format with object class identifiers and normalized bounding box coordinates. The dataset contains 5,792 annotated object instances, comprising 3,718 floating waste instances and 2,074 river vegetation instances. The dataset is partitioned into training, validation, and testing subsets containing 1,104, 315, and 158 images, respectively. The partitioning was performed using a group-aware strategy to ensure that images originating from the same video source were kept within the same subset. The dataset is intended to support computer vision, object detection, and environmental monitoring research under challenging turbid river conditions.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113265"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149046333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gridded sea surface hydrographic data along two Salish Sea passenger ferry routes, 2001–2025 2001-2025年两条萨利希海客轮航线的网格化海面水文数据

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-21 DOI: 10.1016/j.dib.2026.113279

Ian T. Black, Alice O.V. Bui, Bennit L. Mueller, Kohen W. Bauer

{"title":"Gridded sea surface hydrographic data along two Salish Sea passenger ferry routes, 2001–2025","authors":"Ian T. Black, Alice O.V. Bui, Bennit L. Mueller, Kohen W. Bauer","doi":"10.1016/j.dib.2026.113279","DOIUrl":"10.1016/j.dib.2026.113279","url":null,"abstract":"<div><div>Since 2001, several passenger ferries connecting Vancouver Island and mainland British Columbia, Canada have collected sea surface hydrographic data within the Salish Sea. Originally part of two separate monitoring projects in the early 2000s and now maintained by Ocean Networks Canada (ONC), archived and real-time data from these vessels are open to the public. To date, several vessels with scientific underway systems have collected data between Tsawwassen-Nanaimo (TWS-NNO, ∼70 km) and Tsawwassen-Swartz Bay (TWS-SWB, ∼44 km), sometimes up to 8 times per day. This data article describes how the original time-series were obtained, the performance of additional quality assessment, and the steps for creating curated datasets consisting of spatially binned (0.01°) transits of surface ocean water properties in the Salish Sea between 2001–2025. During this period, 30,000+ transits along both routes collected sea surface temperature, practical salinity, and dissolved oxygen; providing dense coverage for a variety of inter-seasonal and inter-annual analyses. Pathways for uncertainty estimation and validation are discussed. Python 3 example code is provided for compiling and processing new data collected after 2025 to enable users to extend this dataset for future analyses.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113279"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149156483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The complete chloroplast genome data of Bergera glabra (Guillaumin) F.J.Mou, a potential aromatic plant endemic to Vietnam 越南潜在特有芳香植物大花柏草（Bergera glabra (Guillaumin) F.J.Mou）叶绿体全基因组数据

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-10-06 DOI: 10.1016/j.dib.2026.113313

Nhat Nam Nguyen

{"title":"The complete chloroplast genome data of Bergera glabra (Guillaumin) F.J.Mou, a potential aromatic plant endemic to Vietnam","authors":"Nhat Nam Nguyen","doi":"10.1016/j.dib.2026.113313","DOIUrl":"10.1016/j.dib.2026.113313","url":null,"abstract":"<div><div>The genus <em>Bergera</em> J.Koenig is renowned for the curry tree (<em>Bergera koenigii</em> L.) and related aromatic species. However, most available genomic data for this genus have focused on <em>B. koenigii</em> because of its widespread use as a spice. In this study, we sequence and report the complete chloroplast genome of <em>Bergera glabra</em> (Guillaumin) F.J.Mou, a species endemic to Vietnam. The reported genome has a quadripartite structure, comprising a large single-copy region (87,759 bp and 37.1% GC), a small single-copy region (18,075 bp and 33.7% GC), and two inverted repeat regions (27,112 bp and 43% GC each). Additionally, the genome contains 79 protein-coding genes, 30 transfer RNA genes, and four ribosomal RNA genes. Phylogenetic analysis indicated the monophyly of the genus <em>Bergera</em> and a close relationship between <em>B. glabra</em> and <em>Bergera euchrestifolia</em> (Hayata) F.J.Mou<em>.</em> This study expands the genomic data of the genus <em>Bergera</em> and provides useful information for further genomic studies examining population genetics and molecular markers for <em>B. glabra</em> and other related <em>Bergera</em> taxa.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113313"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149202024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An RGB-D time-series dataset of white button mushroom growth for instance segmentation 一种用于实例分割的RGB-D白纽扣蘑菇生长时序数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-07-22 DOI: 10.1016/j.dib.2026.113085

Namrata Dutt, Daeun Choi

{"title":"An RGB-D time-series dataset of white button mushroom growth for instance segmentation","authors":"Namrata Dutt, Daeun Choi","doi":"10.1016/j.dib.2026.113085","DOIUrl":"10.1016/j.dib.2026.113085","url":null,"abstract":"<div><div>Accurate detection and segmentation of individual mushroom caps in densely populated cultivation beds remain key challenges for robotic harvesting of white button mushrooms (<em>Agaricus bisporus</em>), where precise boundary delineation is required for size estimation, grasp planning, and collision-free manipulation. The data was developed to support research on computer vision-based perception systems for autonomous mushroom harvesting. The dataset comprises of 129 time-series RGB and depth images of mushrooms from a top-view perspective, representing mushroom growth and spatial distribution under an indoor mushroom production environment. Each sample includes an RGB image, a corresponding depth image, and pixel-level segmentation annotations of individual mushrooms in COCO JSON format. The inclusion of depth information enables the extraction of geometric features such as cap height, curvature, and relative positioning between neighboring mushrooms. This dataset provides a resource for training and benchmarking algorithms in instance segmentation, growth analysis, and perception for agricultural robotics, with particular relevance to automated harvesting and RGB–D scene understanding in complex, densely populated agricultural settings.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113085"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148646503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Point cloud dataset of mature pecan trees (Carya illinoinensis) obtained with a low-cost mobile terrestrial LiDAR 利用低成本移动地面激光雷达获取成熟山核桃（Carya illinensis）点云数据集。

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-07-13 DOI: 10.1016/j.dib.2026.113076

Raúl Porras, Gilberto Rivera, Vicente García, Rogelio Florencia, Patricia Sánchez-Solís

{"title":"Point cloud dataset of mature pecan trees (Carya illinoinensis) obtained with a low-cost mobile terrestrial LiDAR","authors":"Raúl Porras, Gilberto Rivera, Vicente García, Rogelio Florencia, Patricia Sánchez-Solís","doi":"10.1016/j.dib.2026.113076","DOIUrl":"10.1016/j.dib.2026.113076","url":null,"abstract":"<div><div>This article describes a comprehensive point cloud dataset representing the 3D structures of 33 mature pecan trees (<em>Carya illinoinensis</em>, cv. 'Western'), which was acquired <em>in situ</em> within commercial orchards in Chihuahua, Mexico. The data were obtained using a low-cost mobile terrestrial laser scanner, consisting of an iPad Pro (11-inch, M1 processor). A pedestrian-based kinematic scanning protocol was applied, based on the EveryPoint application, which leverages the device’s integrated LiDAR sensor and its 12-megapixel Wide camera. The dataset contains point clouds at several stages of processing, ranging from raw acquisitions containing inherent sensor noise and positional artifacts (the “noise dome”) to definitively filtered, ready-to-use spatial geometries. Data processing was carried out using programmatic preprocessing, which involved geometric filtering based on local volume density and Gaussian curvature thresholds, in order to systematically remove outliers near the woody branching architecture. The dataset is available in standard .ply and .las formats, and is accompanied by <em>in situ</em> photographic reference images. It may be used to develop and benchmark denoising methods for low-cost LiDAR data, or to support non-destructive phenotyping and pruning-related decision support applications in pecan orchards.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"67 ","pages":"Article 113076"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393651/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148577426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transcriptome datasets of salicylic acid-treated tomato plant cultures under normal and stress conditions 水杨酸处理番茄植株在正常和胁迫条件下的转录组数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-07-28 DOI: 10.1016/j.dib.2026.113108

Kincső Decsi, Mostafa Ahmed, Zoltán Tóth

{"title":"Transcriptome datasets of salicylic acid-treated tomato plant cultures under normal and stress conditions","authors":"Kincső Decsi, Mostafa Ahmed, Zoltán Tóth","doi":"10.1016/j.dib.2026.113108","DOIUrl":"10.1016/j.dib.2026.113108","url":null,"abstract":"<div><div>Extreme weather events pose a significant challenge to agricultural systems, as they induce various abiotic stress responses in plants. Preventive crop protection strategies that aim to enhance plant resistance in advance are gaining increasing importance to mitigate these stress effects. Priming treatments based on the activation of the immune response allow plants to be prepared for stress by triggering some of the defense mechanisms before the actual stress occurs.</div><div>In the study, healthy, young tomato plants were pre-treated with a foliar spray containing salicylic acid and then subjected to drought stress during the vegetation period. NGS-based shallow RNA sequencing was used to examine the samples at the molecular level. Following bioinformatic processing and evaluation of the obtained sequence data, it was possible to analyse the putative stimulatory effects of salicylic acid treatment and to monitor the development of long-term adaptation processes induced by priming, such as the development of plant stress memory under stress conditions.</div><div>The sequencing data were submitted in the NCBI database in the form of four forward SRA data sets, in three biological replicates, providing a total of 12 SRA data sets. Furthermore, a de novo transcriptome assembly (TSA) file generated from the quality-controlled reads, along with a read count table obtained from from RNA-seq analysis, was deposited in the Mendeley Data repository. Since Kecskeméti 549 is a special local tomato variety, no reference genome is available in public databases; therefore, the de novo assembly method was chosen for the reconstruction of the transcriptome.</div><div>The created datasets provide an opportunity for future studies to explore the short-term (priming effect) and prolonged (during stress exposure) molecular consequences of the treatments. The data can also be used to identify and monitor plant biochemical processes induced by salicylic acid, with particular attention to changes in gene expression patterns.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113108"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148733647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generating synthetic journal entries for audit analytics: Method and dataset 为审计分析生成合成日记账：方法和数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-11 DOI: 10.1016/j.dib.2026.113257

Jan Gronewald, Sebastian Stephan, Alexander Rombach, Peter Fettke

引用次数: 0