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3,202 results for “maintenance”
Data from: Prophage maintenance is determined by environment-dependent selective sweeps rather than mutational availability
<p>Prophages, viral sequences integrated into bacterial genomes, can confer fitness benefits and costs. Despite the risk of prophage activation and subsequent bacterial death, active prophages are present in most bacterial genomes. However, our understanding about the selective forces that maintain prophages in bacterial populations is scarce. Combining experimental evolution with stochastic modelling we found that prophage maintenance and loss are primarily determined by environmental conditions that amplify the net fitness effect of the prophage. Whole genome sequencing revealed that prophage loss occurs through environment-specific sequences of selective sweeps, leading to rapid prophage loss when prophages are costly. However, conflicting selection pressures that select against the prophage but for a prophage-encoded accessory gene can prolong prophage maintenance. The extent of prolonged maintenance depends on the sociality of this accessory gene. Selection for non-cooperative genes is more effective for prophage maintenance as cooperative genes allow for protection of phage-free 'cheaters' that may emerge if prophage costs outweigh their benefits. Our mathematical model suggests that environmental variation plays a larger role than mutation rates in determining prophage maintenance. This challenges our understanding of the role of random chance events relative to environmental factors in shaping the evolutionary trajectory of bacterial populations.</p>
Predictive Maintenance Literature Review Framework
<p>This dataset contains information collected during a literature review in the domain of Predictive Maintenance in Industry 4.0. It consists of Two Tables:</p><ol><li>Paper references and their contribution to individual topics</li><li>Types of Neural Networks that have been used in the Papers</li></ol>
Big data analytics in support of the under-rail maintenance management at Vitória – Minas Railway
<p>This video describes an ongoing study using data collected by an instrumented ore car on Vitória–Minas Railway, operated by Vale in Brazil. The research uses big data analysis methods over collected data by the instrumented car during its voyages. Railway geometry issues can cause undesirable movements on the wagons that can cause discomfort for passengers or instability for the cargo. In the worst scenario, derailments can occur. Each second, several sensors installed on the instrumented car collect data about velocity, acceleration, and movements on the wagon. The volume of collected data is impressive since the railway has about 2,000 km of extension. That volume compels us to use big data analytics methods. As the result of the research, the team aims to establish some levels of operational conditions, named as severity indexes, which can indicate to the maintenance teams the necessity of intervention on the railway.</p>
Resource Guide for State DOT's Maintenance Equipment Fleet Management Decisions
<p>This research created a guide for state Departments of Transportation fleet management on utilizing equipment fleet management system data to make informed fleet management decisions. The research team took the historical equipment fleet data from the Oklahoma Department of Transportation and developed workflows, algorithms, and examples to demonstrate the use of historical equipment data for equipment decisions. Specifically, the research team demonstrated 1) the use of life cycle analysis and dynamic programming models for equipment replacement decisions; 2) developed algorithms to calculate equipment rental rates that can be used by the Department to forecast and allocate equipment operational budget among field districts and central office, 3) developed a procedure to make own-rent/lease decisions based on historical equipment management data. Using the two class codes of equipment (Class Code 5355 – 2 Yd. front-end loaders and Class Code 5385 – 1/2-ton fleetside pickup trucks) as examples, the research team presented the result of the equipment replacement models using both life cycle analysis and dynamic programming approaches and discussed the difference of those two methods. In addition, the impact of model input parameters (specifically depreciation cost estimation using both straight line and double declining balance depreciation calculation methods) on equipment replacement outcomes is discussed. The framework for deciding between on renting or owning for the two class codes of equipment was developed. Also, the equipment rental rates for the most frequently used equipment by ODOT were updated per class code.</p>
Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks
<p>Seed dispersal by animals is one of the most important ecological processes in tropical forests, entailing millions of years of evolutionary adaptations of plants and frugivorous animals forming networks of interactions that, ultimately, contribute to the resilience of such forests. We analyze 29 seed dispersal networks in the threatened Atlantic Forest biodiversity hotspot, with data on the frequency of feeding visits by birds to fruiting plants to answer: (1) which are the effects of forest cover and landscape connectivity on the maintenance of phylogenetic diversity (PD) of interacting birds and plants and the evolutionary distinctiveness of the interactions (EDi) between them; and (2) how EDi and plant/bird PD affects the robustness of the interaction networks? We found that forest cover positively influences both plant and bird PD and EDi. Landscape connectivity is an important predictor of bird PD, but not plant PD, suggesting that the spatial arrangement of forest remnants is essential for guaranteeing bird movement among forest fragments. Furthermore, interaction networks of areas with higher PD and EDi had great robustness to the simulated extinction of species, which underscore the importance of larger forest blocks for conserving evolutionary information and, consequently, the health and natural resistance of seed dispersal networks against environmental change.</p>
Maintenance and Restriping Strategies for Pavement Markings on Asphalt Pavements in Louisiana
<p>In Louisiana, most districts restripe their roadways using waterborne paints every other year; this strategy is questionable in terms of efficiency and economy. Meanwhile, previous studies showed substantial variability in the paint service life throughout the United States ranging between 0.25 and 6.2 years. Shortcomings in modeling the retroreflectivity of waterborne paints appear to significantly contribute to these variations as several studies predicted these values using degradation curves with a coefficient of determination (R2) as low as 0.1. Therefore, the objective of this study was to (i) develop new cost-effective restriping strategies using 4-inch (15-mil thickness) and 6-inch (25-mil thickness) wide waterborne paints when applied on asphalt pavements in hot and humid climates, and (ii) employ an advanced machinelearning algorithm to develop performance prediction models for waterborne paints considering the variables that are believed to affect their performance. To achieve these objectives, National Transportation Product Evaluation Program (NTPEP) data were collected and analyzed to evaluate the field performance of waterborne paints commonly used in Southern United States. Results indicated that 4-inch wide standard paints exhibited service life up to four years depending on the line color, traffic and initial retroreflectivity, while 4-inch wide high-build paints had a service life of at least three years. Based on a life-cycle cost analysis, it was concluded that LaDOTD could restripe their district roads every three years instead of the current two-year period using the same product (4-inch or 6-inch wide) saving about $20 or $2 million, respectively, every year when restriping a 5,000-mile network. Additionally two machine-learning models were developed with an acceptable level of accuracy, and that can predict the skip and wheel retroreflectivity of waterborne paints for up to three years using only the initial measured retroreflectivity and the anticipated project conditions over the intended prediction horizon, such as line color, traffic, air temperature, etc. These models could be used by transportation agencies throughout the United States to (1) compare between different products and select the best product for a specific project, and (2) determine the expected service life of a specific product based on a specified threshold retroreflectivity to plan for future restriping activities.</p>
Data from: Maintenance of local adaptation despite gene flow in a coastal songbird
<p class="MsoNormal">Adaptation to local environments is common in widespread species and the basis of ecological speciation. The song sparrow (<em>Melospiza melodia</em>) is a widespread, polytypic passerine that occurs in shrubland habitats throughout North America. We examined the population structure of two parapatric subspecies that inhabit different environments: the Atlantic song sparrow (<em>M. m. atlantica</em>), a coastal specialist; and the eastern song sparrow (<em>M. m. melodia</em>), a shrubland generalist. These populations lacked clear mitochondrial population structure, yet coastal birds formed a distinct nuclear genetic cluster. We found weak overall genomic differentiation between these subspecies, suggesting either recent divergence, extensive gene flow, or a combination thereof. There was a steep genetic cline at the transition to coastal habitats, consistent with isolation by environment (IBE), not isolation by distance (IBD). A phenotype under divergent selection, bill size, varied with the amount of coastal ancestry in transitional areas, but larger bill size was maintained in coastal habitats regardless of ancestry, further supporting a role for selection in the maintenance of these subspecies. Demographic modeling suggested a divergence history of limited gene flow followed by secondary contact, which has emerged as a common theme in adaptive divergence across taxa.</p>
Age-specific activation patterns and inter-subject similarity during verbal working-memory maintenance and Cognitive Reserve
<p>Cognitive Reserve, according to a recent consensus definition of the NIH-funded Reserve and Resilience collaboratory (<a href="https://reserveandresilience.com/">https://reserveandresilience.com/</a>), is constituted by any mechanism contributing to cognitive performance beyond, or interacting with, brain structure in the widest sense. To identity multivariate activation patterns fulfilling this postulate, we investigated a verbal Sternberg fMRI task and imaged 181 people with age coverage in the ranges 20-30 (44 participants) and 55-70 (137 participants). Beyond task performance, participants were characterized in terms of demographics, and neuropsychological assessments of vocabulary, episodic memory, perceptual speed, and abstract fluid reasoning. Participants studied an array of either 1, 3, or 6 upper-case letters for 3 seconds (=encoding phase), then a blank fixation screen was presented for 7 seconds (=maintenance phase), to be probed with a lower-case letter to which they responded with a differential button press whether the letter was part of the studied array or not (=retrieval phase). We focused on identifying maintenance-related activation patterns showing memory-load increases in pattern score on an individual-participant level for both age groups. We found such a pattern that increased with memory load for all but one person in the young participants (p<0.001), and such a pattern for all participants in the older group (p<0.001). Both patterns showed broad topographic similarities; however, relationships to task performance and neuropsychological characteristics were markedly different and point to individual differences in Cognitive Reserve. Beyond the derivation of group-level activation patterns, we also investigated the inter-subject spatial similarity of individual working-memory rehearsal patterns in the older participants' group as a function of neuropsychological and task performance, education and mean cortical thickness. Higher task accuracy and neuropsychological function was reliably associated with higher inter-subject similarity of individual-level activation patterns in older participants.</p>
Research Artifact: Dockerfile Meta-Maintenance for Updating Multiple Version-Pinned Packages
<p>This is a research artifact for the paper "Dockerfile Meta-Maintenance for Updating Multiple Version-Pinned Packages". This artifact is a data repository including a list of studied 7,914 repositories on GitHub, 17,139 dockerfiles, 363 repositories containing comparable package sets, and 335 repositories that provide the packages included in the identified 385 package sets.</p>
Supplementary materials of the paper entitled: "Metamorphic Testing Meets Regression Testing: A Case Study of Scientific Software Maintenance"
<p>Supplementary materials of the paper entitled:</p> <p>“Metamorphic Testing Meets Regression Testing: A Case Study of Scientific Software Maintenance”</p> <p>file01 - source code for detecting and comparing output relations of a given metamorphic relation<br> file02 - interview transcripts and qualitative coding results<br> file03 - system script for compiling SWMM, creating sSWMM simulation outputs, and logging execution time<br> file04 - source code for SWMM 5.1.014<br> file05 - source code for SWMM 5.1.015<br> file06 - a suite of 40 regression tests (40 .inp files)<br> file07 - result table for 760 cases (19 MRs × 40 .inp files)<br> file08 - 491 automatically generated follow-up .inp files via reuse<br> file09 - result table for mutation analysis<br> file10 - output files for mutation analysis with metamorphic testing:<br> a. Original source output<br> b. Original follow-up output<br> c. Mutant source output<br> d. Mutant follow-up output</p>
Numerical analysis of working paper "Joint integrated production-maintenance policy of a deteriorating equipment considering random yield and maintenance delay"
<p>This is the numerical analysis code using in the working paper "Joint integrated production-maintenance policy of a</p> <p>deteriorating equipment considering random yield and maintenance delay"</p>
Frequency, types, and factors associated with Complementary and Alternative Medicine use among patients on Maintenance Haemodialysis
<p><strong>Objective</strong>: This study aims to determine the prevalence, types, indications, and factors associated with CAM use by patients on maintenance haemodialysis (MHD) in Cameroon.</p> <p> </p>
Data from: The role of conflict in the formation and maintenance of variant sex chromosome systems in mammals
<p>The XX/XY sex chromosome system is deeply conserved in therian mammals, as is the role of <em>Sry</em> in testis determination, giving the impression of stasis relative to other taxa. However, the long tradition of cytogenetic studies in mammals documents sex chromosome karyotypes that break this norm in myriad ways, ranging from fusions between sex chromosomes and autosomes to Y chromosome loss. Evolutionary conflict, in the form of sexual antagonism or meiotic drive, is the primary predicted driver of sex chromosome transformation and turnover. Yet conflict-based hypotheses are less considered in mammals, perhaps because of the perceived stability of the sex chromosome system. To address this gap, we catalogue and characterize all described sex chromosome variants in mammals, test for family-specific rates of accumulation, and consider the role of conflict between the sexes or within the genome in the evolution of these systems. We identify 152 species with sex chromosomes that differ from the ancestral state and find evidence for different rates of ancestral to derived transitions among families. Sex chromosome-autosome fusions account for 80% of all variants whereas documented sex chromosome fissions are limited to three species. We propose that meiotic drive and drive suppression provide viable explanations for the evolution of many of these variant systems, particularly those involving autosomal fusions. We highlight taxa particularly worthy of further study and provide experimental predictions for testing the role of conflict and its alternatives in generating observed sex chromosome diversity.</p>
Data from: Experimental increase in fecundity causes upregulation of fecundity and body maintenance genes in the fat body of ant queens
<p>In most organisms, fecundity and longevity are negatively associated and the molecular regulation of these two life history traits is highly interconnected. In addition, nutrient intake often has opposing effects on lifespan and reproduction. In contrast to solitary insects, the main reproductive individual of social hymenopterans, the queen, is also the most long-lived. During development, queen larvae are well-nourished, but we are only beginning to understand the impact of nutrition on the queens' adult life and the molecular regulation and connectivity of fecundity and longevity. Here, we used two experimental manipulations to alter queen fecundity in the ant <em>Temnothorax rugatulus</em> and investigated associated changes in fat body gene expression. Egg removal triggered a fecundity increase, leading to expression changes in genes with functions in fecundity such as oogenesis and body maintenance. Dietary restriction lowered the egg production of queens and altered the expression of genes linked to autophagy, Toll signalling, cellular homeostasis, and immunity. Our study reveals that an experimental increase in fecundity causes the co-activation of reproduction and body maintenance mechanisms, shedding light on the molecular regulation of the link between longevity and fecundity in social insects.</p>
The Maintenance of Long-Lived Concentric Eyewall in Simulated Typhoon Lekima (2019)
<p>The model-simulated data used in this study are uploaded here. Due to the large number, the original simulation data are available on request (qnn_nancy@yahoo.com).</p>
359,569 commits with source code density; 1149 commits of which have software maintenance activity labels (adaptive, corrective, perfective)
<p>This dataset comes as SQL-importable file and is compatible with the widely available MariaDB- and MySQL-databases.</p> <p>It is based on (and incorporates/extends) the dataset "<em>1151 commits with software maintenance activity labels (corrective,perfective,adaptive)</em>" by Levin and Yehudai (<a href="https://doi.org/10.5281/zenodo.835534">https://doi.org/10.5281/zenodo.835534</a>).</p> <p>The extensions to this dataset were obtained using <em>Git-Tools</em>, a tool that is included in the <strong>Git-Density</strong> (<a href="https://doi.org/10.5281/zenodo.2565238">https://doi.org/10.5281/zenodo.2565238</a>) suite. For each of the projects in the original dataset, Git-Tools was run in <em>extended</em> mode.</p> <p>The dataset contains these tables:</p> <ul> <li><strong>x1151</strong>: The original dataset from Levin and Yehudai. <ul> <li>despite its name, this dataset has only 1,149 commits, as two commits were duplicates in the original dataset.</li> <li>This dataset spanned 11 projects, each of which had between 99 and 114 commits</li> <li>This dataset has <strong>71</strong> features and spans the projects <em>RxJava, hbase, elasticsearch, intellij-community, hadoop, drools, Kotlin, restlet-framework-java, orientdb, camel</em> and <em>spring-framework</em>.</li> </ul> </li> <li><strong>gtools_ex</strong> (short for <em>Git-Tools, extended</em>) <ul> <li>Contains <strong>359,569</strong> commits, analyzed using Git-Tools in extended mode</li> <li>It spans all commits and projects from the x1151 dataset as well.</li> <li>All 11 projects were analyzed, from the initial commit until the end of January 2019. For the projects <em>Intellij</em> and <em>Kotlin</em>, the first 35,000 resp. 30,000 commits were analyzed.</li> <li>This dataset introduces <strong>35 new</strong> features (see list below), 22 of which are <em><strong>size</strong></em>- or <em><strong>density</strong></em>-related.</li> </ul> </li> </ul> <p>The dataset contains these views:</p> <ul> <li><strong>geX_L</strong> (short for Git-<em>tools, extended, with labels</em>) <ul> <li>Joins the commits' labels from <em>x1151</em> with the extended attributes from <em>gtools_ex</em>, using the commits' hashes.</li> </ul> </li> <li><strong>jeX_L</strong> (short for <em>joined, extended, with labels</em>) <ul> <li>Joins the datasets <em>x1151</em> and <em>gtools_ex</em> entirely, based on the commits' hashes.</li> </ul> </li> </ul> <p> </p> <p>Features of the <strong>gtools_ex</strong> dataset:</p> <ul> <li><strong>SHA1</strong></li> <li><strong>RepoPathOrUrl</strong></li> <li><strong>AuthorName</strong></li> <li><strong>CommitterName</strong></li> <li><strong>AuthorTime </strong>(UTC)</li> <li><strong>CommitterTime </strong>(UTC)</li> <li><strong>MinutesSincePreviousCommit</strong>: Double, describing the amount of minutes that passed since the previous commit. Previous refers to the <strong>parent</strong> commit, not the previous in time.</li> <li><strong>Message</strong>: The commit's message/comment</li> <li><strong>AuthorEmail</strong></li> <li><strong>CommitterEmail</strong></li> <li><strong>AuthorNominalLabel</strong>: All authors of a repository are analyzed and merged by Git-Density using some heuristic, even if they do not always use the same email address or name. This label is a unique string that helps identifying the same author across commits, even if the author did not always use the exact same identity.</li> <li><strong>CommitterNominalLabel</strong>: The same as <em>AuthorNominalLabel</em>, but for the committer this time.</li> <li><strong>IsInitialCommit</strong>: A boolean indicating, whether a commit is preceded by a parent or not.</li> <li><strong>IsMergeCommit</strong>: A boolean indicating whether a commit has more than one parent.</li> <li><strong>NumberOfParentCommits</strong></li> <li><strong>ParentCommitSHA1s</strong>: A comma-concatenated string of the parents' SHA1 IDs</li> <li><strong>NumberOfFilesAdded</strong></li> <li><strong>NumberOfFilesAddedNet</strong>: Like the previous property, but if the net-size of all changes of an added file is zero (i.e. when adding a file that is empty/whitespace or does not contain code), then this property does not count the file.</li> <li><strong>NumberOfLinesAddedByAddedFiles</strong></li> <li><strong>NumberOfLinesAddedByAddedFilesNet</strong>: Like the previous property, but counts the net-lines</li> <li><strong>NumberOfFilesDeleted</strong></li> <li><strong>NumberOfFilesDeletedNet</strong>: Like the previous property, but considers only files that had net-changes</li> <li><strong>NumberOfLinesDeletedByDeletedFiles</strong></li> <li><strong>NumberOfLinesDeletedByDeletedFilesNet</strong>: Like the previous property, but counts the net-lines</li> <li><strong>NumberOfFilesModified</strong></li> <li><strong>NumberOfFilesModifiedNet</strong>: Like the previous property, but considers only files that had net-changes</li> <li><strong>NumberOfFilesRenamed</strong></li> <li><strong>NumberOfFilesRenamedNet</strong>: Like the previous property, but considers only files that had net-changes</li> <li><strong>NumberOfLinesAddedByModifiedFiles</strong></li> <li><strong>NumberOfLinesAddedByModifiedFilesNet</strong>: Like the previous property, but counts the net-lines</li> <li><strong>NumberOfLinesDeletedByModifiedFiles</strong></li> <li><strong>NumberOfLinesDeletedByModifiedFilesNet</strong>: Like the previous property, but counts the net-lines</li> <li><strong>NumberOfLinesAddedByRenamedFiles</strong></li> <li><strong>NumberOfLinesAddedByRenamedFilesNet</strong>: Like the previous property, but counts the net-lines</li> <li><strong>NumberOfLinesDeletedByRenamedFiles</strong></li> <li><strong>NumberOfLinesDeletedByRenamedFilesNet</strong>: Like the previous property, but counts the net-lines</li> <li><strong>Density</strong>: The ratio between the two sums of all lines added+deleted+modified+renamed and their resp. gross-version. A density of zero means that the sum of net-lines is zero (i.e. all lines changes were just whitespace, comments etc.). A density of of 1 means that all changed net-lines contribute to the gross-size of the commit (i.e. no useless lines with e.g. only comments or whitespace).</li> <li><strong>AffectedFilesRatioNet</strong>: The ratio between the sums of <em>NumberOfFilesXXX</em> and <em>NumberOfFilesXXXNet</em></li> </ul> <p> </p> <p>This dataset is supporting the paper <strong>"<em>Importance and Aptitude of Source code Density for Commit Classification into Maintenance Activities</em></strong><strong>"</strong>, as submitted to the <em>QRS2019</em> conference (The 19th IEEE International Conference on Software Quality, Reliability, and Security). Citation: Hönel, S., Ericsson, M., Löwe, W. and Wingkvist, A., 2019. Importance and Aptitude of Source code Density for Commit Classification into Maintenance Activities. In <em>The 19th IEEE International Conference on Software Quality, Reliability, and Security</em>.</p>
Replication Package: Reducing the Maintenance Effort for Parameterization of Representative Load Tests Using Annotations
<p>This is the replication package for the publication <em>Reducing the Maintenance Effort for Parameterization of Representative Load Tests Using Annotations</em>, Journal of Software Testing, Verification and Reliability (STVR), Special Issue on Testing Extra-Functional Properties. It contains the JSON/YAML schema of the Input Data and Properties Annotation (IDPA) as well as the experiment artifacts, the experiment results, and the R-scripts we used for the analysis.</p> <p>The README.md (or README.pdf) contains further descriptions and instructions.</p>
Sustainable and Equitable Financing for Pedestrian Infrastructure Maintenance
<p>Corresponding data set for Tran-SET Project No. 17PPUNM01. Abstract of the final report is stated below for reference:</p> <p>"In many communities, pedestrian infrastructure is discontinuous, inaccessible to those with physical disabilities, and poorly maintained. Correcting these problems would be a first step in providing infrastructure to achieve the active travel and related transportation goals of many communities. One nearly universal challenge to maintaining sidewalks in a state of good repair and addressing environmental justice concerns is an adequate, sustainable, and equitable source of funding. Municipal governments across the country maintain and repair their streets and roadways; however, most require residents to maintain and repair public sidewalks adjacent to their property. These policies are difficult to enforce and may be at least partly responsible for the poor condition of many sidewalks. They may also place a relatively high cost on low-income households. We evaluate three alternative options for financing the maintenance of public sidewalks in Albuquerque, New Mexico: increasing the gross receipts tax (GRT), the gasoline excise tax, or the property tax. These are broad-based taxes that many municipalities already levy to pay for public infrastructure, including streets. We conclude that any of the alternatives would perform better than policies that require adjacent property owners to maintain public sidewalks. They are generally less regressive, cost less on average, and would allow municipalities to more effectively manage sidewalk assets. The differences between the alternatives are relatively minor compared to their benefits. Additional considerations should include how the revenue from each tax may change over time."</p>
Channel State Information (CSI) analysis for predictive maintenance using Convolutional Neural Network (CNN)
<p>Dataset manual:</p> <p>This dataset contains CSI amplitude values for rotating motors in an office environment. Details of the experiments may be found in the corresponding paper published in the DATA'19 workshop, SenSys (<a href="https://doi.org/10.1145/3359427.3361917">https://doi.org/10.1145/3359427.3361917</a>). </p> <p>Folder structure:<br> The folders for servo motor and stepper motor contains separate folders for network reconnection conditions (w_recc: with reconnections, wo_recc: without recconnections) and load conditions (w_load: with load and wo_load: without load). The data is stores as Matlab files with .mat extentions. </p> <p>File structure:<br> In each file name, the digits after the '_' at the end of the file name correspond to the speed of the motor. In case of stepper motor these numbers could be directly interpreted as rpm. Ex: table_inj_with_load_5_0.mat corresponds to stationary motor (0 rpm) and table_inj_with_load_5_250.mat corresponds to motor rotating with 250 rpm speed. In the case of servo motor these numbers should be mapped with the following table in order to get the speeds.</p> <p>0: 0 rpm<br> 50: 14.45 rpm<br> 100: 8.02 rpm<br> 150: 5.38 rpm<br> 200: 4.05 rpm<br> 250: 3.26 rpm<br> 300: 2.67 rpm<br> Ex: table_inj_with_load_50.mat corresponds to motor running with 14.45 rpm.</p> <p>Each file has 3 columns, each corresponding to CSI value, labels (speed/last digits in the file name) and the data sample number (not in sequence as a result of packer loss) respectively. CSI values are typically a matrix of size 3000*180 (3000 CSI samples for 3sec data @1kHz sampling rate and 180 channels for 6 antenna pairs @ 30 subcarrier data per antenna).</p>
Decision-Making Tool for Road Preventive Maintenance Using Vehicle Vibration Data
<p>Corresponding data set for Tran-SET Project No. 18PLSU08. Abstract of the final report is stated below for reference:</p> <p>"Automated and timely road pavement damage inspection is critical to the preventive maintenance and the long-term sustainability and resilience of roads in Region 6. Current road inspection practices rely heavily on a manual process. Sensor-based methods (e.g., LiDAR scanning) are promising but can be too expensive for a wider adoption. This study employs a crowdsourcing approach of using the vibration patterns of regular vehicles in inferring specific types of road damages. A cloud-based smart phone app and system was developed to collect real-time vehicle vibrations, location data, and road damage images for training the detection model. However, there is a great challenge in using classic classification methods with crowdsourced vibration data containing high level of noises, as vehicle vibrations are greatly affected by the types and conditions of the vehicles, as well the varying driving behaviors of drivers. The study thus employed the recent developments in Deep Learning methods, including a Self-Taught Learning (STL) algorithm and Sparse Coding to tackle with the low-quality issues of collected data. A total of 310 miles of road-induced vehicle vibration data was collected in Texas and Louisiana, and the road damage detection model was trained on Texas A&M University (TAMU) supercomputing server. The results show that the features generated from Sparse Coding greatly contribute to enhancing detection performances, by addressing low-quality data issues."</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.