Data in Brief最新文献_第6页

Irish potato imagery dataset for detection of early and late blight diseases 用于检测早、晚疫病的爱尔兰马铃薯图像数据集

IF 1

Data in Brief Pub Date : 2025-04-08 DOI: 10.1016/j.dib.2025.111549

Hudson Laizer, Neema Mduma

{"title":"Irish potato imagery dataset for detection of early and late blight diseases","authors":"Hudson Laizer, Neema Mduma","doi":"10.1016/j.dib.2025.111549","DOIUrl":"10.1016/j.dib.2025.111549","url":null,"abstract":"<div><div>This dataset comprises of 58,709 annotated images of irish potato leaves, categorized into three classes (healthy, early blight and late blight). The data was collected over six months from smallholder farms in Southern Highlands Tanzania, using Samsung Galaxy A03 smartphones with 8-megapixel camera. Researchers, farmers and agricultural extension officers were trained to capture images under diverse conditions, including varying lighting, angles and backgrounds to ensure the dataset is diverse and representative. Plant pathologists were used to validate the images to ensure and enhance the reliability of the labels. Pre-processing steps such as duplicate removal, filtering of irrelevant images, annotation and metadata integration were applied resulting in a high-quality dataset. The dataset is organized into three folders (healthy, early blight and late blight) and is freely available on the Zenodo repository to promote accessibility for researchers working in the field of plant diseases. This dataset holds significant potential for reuse in training machine learning models for crop disease detection, transfer learning and data augmentation studies. By enabling early detection and classification of potato diseases, the dataset supports the development of innovative agricultural tools aimed at reducing crop losses and enhancing food security in Sub-Saharan Africa. Its robust design and regional specificity make it a valuable resource for advancing research and innovation in sustainable farming practices.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111549"},"PeriodicalIF":1.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dataset on the life cycle assessment of the production of stabilized lactic acid bacteria 稳定乳酸菌生产的生命周期评估数据集

IF 1

Data in Brief Pub Date : 2025-04-08 DOI: 10.1016/j.dib.2025.111541

Maite Gagneten , Camille Quentier , Stéphanie Passot , Stéphanie Cenard , Fernanda Fonseca , Caroline Pénicaud

{"title":"Dataset on the life cycle assessment of the production of stabilized lactic acid bacteria","authors":"Maite Gagneten , Camille Quentier , Stéphanie Passot , Stéphanie Cenard , Fernanda Fonseca , Caroline Pénicaud","doi":"10.1016/j.dib.2025.111541","DOIUrl":"10.1016/j.dib.2025.111541","url":null,"abstract":"<div><div>Lactic acid bacteria are widely used in the food and pharmaceutical industries to produce fermented foods and probiotics. However, very little is known about the environmental impacts of their production processes. This dataset provides appropriate data related to the environmental assessment by Life Cycle Assessment of thirty scenarios of production processes to produce lactic acid bacteria concentrates at the pilot scale. Life Cycle Inventory (LCI) foreground data were collected during experiments performed in 2021 in Biosearch Life, a Kerry Group company (Granada, Spain). They were manually measured, registered with sensors (tap water, steam, compressed air, and electricity consumption), or found in the technical and scientific literature. Storage experiments and biological activity measurements were performed during 2021 and 2022 in AgroParisTech (Thiverval-Grignon, France). Background data came from the database Ecoinvent 3.9.1, completed by Agribalyse 3.0. LCI of the fructo-oligosaccharide (FOS) protectants' production was obtained from another data paper. Life Cycle Impact Assessments (LCIA) were computed with SimaPro v9.5 software (Pré consultant) with the “EF 3.0 Method (adapted) V1.00 / EF 3.0 normalization and weighting set” to obtain the midpoint indicators. The dataset contains all the inventory data (mass and energy flows, equipment) and the biological activity data. The Life Cycle Inventory data could be reused by scientists for future LCAs. The environmental impacts computed by Life Cycle Assessment could be reused by scientists or the food industry for eco-design or environmental labeling.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111541"},"PeriodicalIF":1.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comprehensive dataset on the physicochemical characteristics of agrowastes digestates from anaerobic digestion 厌氧消化沼液理化特性的综合数据集

IF 1

Data in Brief Pub Date : 2025-04-08 DOI: 10.1016/j.dib.2025.111550

Lucille Caradec , Aurélia Michaud , Mariana Moreira , Ivan Desneulin , Sylvaine Berger , Dominique Patureau , Sabine Houot , Florent Levavasseur , Antoine Savoie , Julie Jimenez

{"title":"Comprehensive dataset on the physicochemical characteristics of agrowastes digestates from anaerobic digestion","authors":"Lucille Caradec , Aurélia Michaud , Mariana Moreira , Ivan Desneulin , Sylvaine Berger , Dominique Patureau , Sabine Houot , Florent Levavasseur , Antoine Savoie , Julie Jimenez","doi":"10.1016/j.dib.2025.111550","DOIUrl":"10.1016/j.dib.2025.111550","url":null,"abstract":"<div><div>The established database represents one of the largest and most diverse collections of digestates compositions, with a total of 806 digestates derived from two main collections: (i) 608 digestates from French agricultural anaerobic digestion (AD) plants, which include detailed physicochemical characterization, trace metal elements and organic contaminants concentrations, and potential C and N mineralization during soil incubation in controlled conditions as agronomic indicators, and (ii) 198 digestates collected from an international literature review, with physicochemical characterization and some trace metal elements concentrations. An additional dataset of process metadata was also set-up, including feedstock compositions, operational conditions and post-treatments descriptions. A preliminary description of both collections is provided using descriptive statistics. This dataset can help to better understand the variability in digestates quality based on feedstock compositions, operational conditions and post-treatments, thereby improving their agronomic benefits.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111550"},"PeriodicalIF":1.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A labeled synthetic mobile money transaction dataset 标记合成移动货币交易数据集

IF 1

Data in Brief Pub Date : 2025-04-07 DOI: 10.1016/j.dib.2025.111534

Denish Azamuke, Marriette Katarahweire, Engineer Bainomugisha

{"title":"A labeled synthetic mobile money transaction dataset","authors":"Denish Azamuke, Marriette Katarahweire, Engineer Bainomugisha","doi":"10.1016/j.dib.2025.111534","DOIUrl":"10.1016/j.dib.2025.111534","url":null,"abstract":"<div><div>This data article introduces a labeled synthetic mobile money transaction dataset created using MoMTSim, a multi-agent-based simulation platform designed and validated specifically for mobile money transactions. MoMTSim toolkit simulates mobile money interactions, ensuring that the generated synthetic dataset closely mimics the statistical properties of real transaction data. This dataset encapsulates a wide range of transaction features, such as timestamps (step), transaction amounts, the initial and new account balances of both the initiator and recipient, participant IDs, and the types of transactions conducted. The included transaction types span deposits, withdrawals, transfers, payments, and debits. Each record in the dataset also carries a label that identifies whether the transaction is legitimate or fraudulent. The synthesis of this dataset using MoMTSim is described in this article and its structure and summary statistics are also presented. The dataset is particularly suitable for training and testing machine learning algorithms to detect financial fraud. Additionally, it holds the potential for benchmarking fraud detection algorithms and systems and validating synthetic data generation methodologies.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111534"},"PeriodicalIF":1.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dataset of the representatives elected in France during the fifth republic 第五共和国期间在法国选出的代表的数据集

IF 1

Data in Brief Pub Date : 2025-04-07 DOI: 10.1016/j.dib.2025.111542

Noémie Févrat , Vincent Labatut , Émilie Volpi , Guillaume Marrel

引用次数: 0

A comprehensive Malabar Spinach dataset for diseases classification 用于疾病分类的马拉巴尔菠菜综合数据集

IF 1

Data in Brief Pub Date : 2025-04-06 DOI: 10.1016/j.dib.2025.111532

Mushfiqur Rahman, Md Al Mamun

{"title":"A comprehensive Malabar Spinach dataset for diseases classification","authors":"Mushfiqur Rahman, Md Al Mamun","doi":"10.1016/j.dib.2025.111532","DOIUrl":"10.1016/j.dib.2025.111532","url":null,"abstract":"<div><div>This study focuses on the urgent need to increase detection of diseases in Malabar Spinach, a valuable leaf vegetable crop which is at risk from several disease types including Anthracous leaf spot and Straw mite infestation. There is still a lack of research focused on Malabar spinach, although advances in machine vision have considerably increased the detection of largescale crop diseases. By developing and evaluating machine vision algorithms specifically designed for accurate detection of diseases in Malabar spinach, this research aims to fill this gap. To achieve this, a comprehensive dataset comprising images of both healthy and diseased Malabar Spinach plants is utilized for training, testing, and validation purposes. This study seeks to develop reliable disease detection models through the examination of different image processing techniques and deep learning algorithms such as ResNet50. In particular, the performance of these models is rigorously evaluated on the basis of a set of standardized evaluation metrics which aim to achieve an overall test accuracy of 94%. The results of this research will have a major impact on the cultivation of Malabar spinach in terms of precision farming techniques and effective crop management practices. This study will contribute to the wider objectives of agricultural sustainability and food security, through increasing crop productivity and reducing yield losses. In the end, it is intended to strengthen the resilience of farming communities dependent on Malabar Spinach crops by providing farmers and experts with efficient tools for detecting diseases.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111532"},"PeriodicalIF":1.0,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven thermal analysis of indoor cooling for a thermoelectric radiant panel system 热电辐射板系统室内制冷的数据驱动热分析

IF 1

Data in Brief Pub Date : 2025-04-06 DOI: 10.1016/j.dib.2025.111547

Muhammad ‘Amir Roslan, Farah Liana Mohd Redzuan

{"title":"Data-driven thermal analysis of indoor cooling for a thermoelectric radiant panel system","authors":"Muhammad ‘Amir Roslan, Farah Liana Mohd Redzuan","doi":"10.1016/j.dib.2025.111547","DOIUrl":"10.1016/j.dib.2025.111547","url":null,"abstract":"<div><div>A thermal analysis of a thermoelectric radiant panel (TERP) system was conducted to evaluate its cooling effectiveness in maintaining indoor comfort within the temperature range recommended by ASHRAE Standard 55 and Malaysian Standard (MS) 1525 under tropical climate conditions. The study utilized ANSYS software, incorporating computational fluid dynamics (CFD) tools for detailed heat transfer simulations. The analysis examined the impact of outdoor temperature variations on indoor conditions and TERP system panel temperatures by considering heat transfer mechanisms, boundary conditions, and material properties to ensure accuracy. By accounting for these factors, the simulation provided a realistic representation of the thermal environment in a tropical climate. The simulation results were visualized as 3D thermal profiles, with color contours illustrating temperature distributions across the panel surface and the indoor environment. The collected data was then simplified into graph form for easier interpretation and analysis, including an evaluation of compliance with thermal comfort standards such as ASHRAE Standard 55 and MS 1525. The findings serve as a benchmark for assessing thermoelectric cooling performance in tropical buildings and offer valuable insights for optimizing thermoelectric cooling systems in similar climates. This study contributes to the development of sustainable cooling solutions and supports further research in thermoelectric cooling applications.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111547"},"PeriodicalIF":1.0,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A text dataset of fire door defects for pre-delivery inspections of apartments during the construction stage 用于施工阶段公寓交付前检查的防火门缺陷文本数据集

IF 1

Data in Brief Pub Date : 2025-04-05 DOI: 10.1016/j.dib.2025.111536

Seunghyeon Wang , Sungkon Moon , Ikchul Eum , Dongjin Hwang , Jaejun Kim

{"title":"A text dataset of fire door defects for pre-delivery inspections of apartments during the construction stage","authors":"Seunghyeon Wang , Sungkon Moon , Ikchul Eum , Dongjin Hwang , Jaejun Kim","doi":"10.1016/j.dib.2025.111536","DOIUrl":"10.1016/j.dib.2025.111536","url":null,"abstract":"<div><div>Defect classification from text descriptions written by inspectors during the construction stage can be highly beneficial, offering advantages such as cost savings and improved reputation of apartment complexes by allowing early identification and resolution of issues. Combining automated methods with textual data can facilitate the rapid identification and diagnosis of faults. To develop such automated methods, this research constructed a dataset from real-world data collected from three apartment complexes. This study classifies fire door defects into eight categories: frame gap, door closer adjustment defect, contamination, dent, scratch, sealing components, mechanical operation components, and others. The level of detail in this classification ensures a comprehensive understanding of fire door issues. The main contributions of this dataset to the field are twofold. First, it represents a unique dataset based on real-world fire door defect descriptions, which is currently non-existent in this domain. Second, the dataset's expert labeling adds significant value by ensuring accurate fault classification. We hope this dataset will encourage the development of robust text classification techniques suitable for real-world applications by providing a reliable benchmark.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111536"},"PeriodicalIF":1.0,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EMG features dataset for arm activity recognition 肌电图特征数据集用于手臂活动识别

IF 1

Data in Brief Pub Date : 2025-04-04 DOI: 10.1016/j.dib.2025.111519

Koundinya Challa, Issa W. AlHmoud, Chandra Jaiswal, Anish C. Turlapaty, Balakrishna Gokaraju

引用次数: 0

Dataset of lithium-ion cell degradation under randomized current profiles for NMC, NCA, and LFP chemistries NMC、NCA和LFP化学下随机电流分布下锂离子电池降解数据集

IF 1

Data in Brief Pub Date : 2025-04-04 DOI: 10.1016/j.dib.2025.111531

Mohsen Heydarzadeh, Teemu Toivola, Victor Vega-Garita, Eero Immonen

{"title":"Dataset of lithium-ion cell degradation under randomized current profiles for NMC, NCA, and LFP chemistries","authors":"Mohsen Heydarzadeh, Teemu Toivola, Victor Vega-Garita, Eero Immonen","doi":"10.1016/j.dib.2025.111531","DOIUrl":"10.1016/j.dib.2025.111531","url":null,"abstract":"<div><div>This paper describes an experimental dataset of lithium-ion cells subjected to a randomized usage profile and periodically characterized through diagnostic tests. The study involved testing eight cells from three types of chemistries (NMC, NCA, LFP) over more than 600 full charge–discharge cycles. The dataset captures the cell's degradation process, including capacity fade and power loss. The experimental procedure comprised an initial full charge/discharge cycle to activate the cells, followed by repeated cycles at varying discharging current rates ranging from 0.5C to 2C/5C. Periodic Hybrid Dynamic Pulse Power Characterization (HPPC) and Constant Current∼ (CC) discharging profiles were executed as reference performance testing (RPT) to monitor transient dynamics and overall performance changes. Furthermore, the Constant Current–Constant Voltage (CC–CV) charging protocol was implemented at 1C charging rates. The experiment entailed the collection of data on voltage, current, cell temperature, ambient temperature, and time, with a 1 Hz sampling rate, utilizing specialized equipment, Chroma 1107 system and temperature sensors. The dataset facilitates the characterization of cell aging under various usage patterns, thereby enabling the development of models and management strategies for different applications. The data was collected at the New Energy Research Center at Turku University of Applied Sciences (TUAS), Finland.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111531"},"PeriodicalIF":1.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0