Data in Brief最新文献_第9页

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

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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

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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

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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

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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

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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

A multi-class driver behavior dataset for real-time detection and road safety enhancement 用于实时检测和增强道路安全的多类别驾驶员行为数据集

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Data in Brief Pub Date : 2025-04-04 DOI: 10.1016/j.dib.2025.111529

Arafat Sahin Afridi, Arafath Kafy, Ms. Nazmun Nessa Moon, Md. Shahriar Shakil

引用次数: 0

Reflected Light Microscopic Iron ore image dataset for iron ore characterization 用于铁矿石表征的反射光显微铁矿石图像数据集

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Data in Brief Pub Date : 2025-04-03 DOI: 10.1016/j.dib.2025.111540

Shama Firdaus , Shamama Anwar , Subrajeet Mohapatra , Prabodha Ranjan Sahoo

引用次数: 0

Holy Quran Kurdish Sorani translation dataset for language modelling 用于语言建模的《古兰经》库尔德语索拉尼语翻译数据集

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Data in Brief Pub Date : 2025-04-03 DOI: 10.1016/j.dib.2025.111533

Muhammad Bamoki , Shakhawan Hares Wady , Soran Badawi

{"title":"Holy Quran Kurdish Sorani translation dataset for language modelling","authors":"Muhammad Bamoki , Shakhawan Hares Wady , Soran Badawi","doi":"10.1016/j.dib.2025.111533","DOIUrl":"10.1016/j.dib.2025.111533","url":null,"abstract":"<div><div>The Holy Quran serves as a foundational text in Islamic theology and has been translated into numerous languages across the globe. This paper introduces a manual translation of the Holy Quran into the Kurdish language, specifically designed to aid natural language processing (NLP) research and linguistic analysis. The translation process employed a thorough methodology that combined advanced linguistic tools with the expertise of bilingual religious scholars, translators, and professional proofreaders over several years. Careful attention was given to maintaining both semantic accuracy and theological precision, ensuring a faithful representation of the original Arabic text. The dataset comprises two primary files: a raw translation and a refined linguistic version. We performed various statistical analyses, including the identification of the top 20 most frequent words, a comparative analysis of verse lengths between the Kurdish and Arabic versions, and an evaluation of unique word distributions in both the raw and processed texts. This Kurdish Quran translation dataset represents a significant resource for computational linguistics, particularly in the development of neural machine translation models and in linguistic research focused on under-resourced languages.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111533"},"PeriodicalIF":1.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843347","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 creation of thermal images of pomegranate for internal defect detection 创建用于内部缺陷检测的石榴热图像数据集

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Data in Brief Pub Date : 2025-04-03 DOI: 10.1016/j.dib.2025.111538

Ashvini Gaikwad, Manoj Deshpande, Varsha Bhole

{"title":"Dataset creation of thermal images of pomegranate for internal defect detection","authors":"Ashvini Gaikwad, Manoj Deshpande, Varsha Bhole","doi":"10.1016/j.dib.2025.111538","DOIUrl":"10.1016/j.dib.2025.111538","url":null,"abstract":"<div><div>Datasets are crucial in various fields, especially in the context of machine learning, data science and research. Datasets are used to train machine learning models. A model learns patterns and relationships from the data it is exposed to. The dataset used for training a machine learning model shall be diversified and consist sufficient samples of desired categories. This paper presents various steps and its outcome in preparing the dataset of digital and thermal images of pomegranate for recognising internal defects. The defects in fruits are often categorised as surface defects and internal defects. The surface defects are recognised with digital RGB image but fails to give insight about the internal structure of the fruit in which we are often interested. The thermal images can be used to detect the internal defects in fruits. When a fruit is subjected to temperature difference as compared to the surrounding, the thermal emissions from fruit captured through a thermal camera (thermal image) gives the key information about the internal damages in the fruit. The internal defects are reflected in thermal image as variations in temperature of adjacent pixels. The k-mean segmentation is applied for identifying internal defects with thermal images in pomegranates to categorize them viz. No defect, major defect and minor defect. This information is useful for training a machine learning algorithms that are intended for bulk processing in the field of fruit defect detection and classification.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111538"},"PeriodicalIF":1.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833619","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