In a survey from August 2019, ** percent of global advertisers said they preferred short-term results of campaigns (such as increase in sales or engagement) to determine ROI, while the same was true for ** percent of agencies and ** percent of media companies.

The paper is now published in the recent Wearable Technology Journal, more detailed information on this dataset can be found there!

A human movement experiment with 12 young adults performing 13 daily movement trials (6 walking trials (speed: 0.9, 1.8, 2.7, 3.6, 4.5, 5.4 km/ h; 3 running trials (speed: 6.3, 8.8, 9.9 km/h); and four non-locomotion trials (vertical jump, squat, lunge, and single leg landing) was conducted with the ethic approved by the University of Twente (ET/A.21.19298, reference number 2021.57).

Six types of measurement devices were used to capture different information of participants’ movements. They can be divided into two systems: the wearable system and the conventional non-wearable system. In the wearable measurement system, eight IMUs (Xsens Link, Enschede, The Netherlands) were used to measure the kinematic movements of lower limbs and trunk. A pair of pressure insoles (Moticon, Munich, Germany) was used to measure the vertical GRF and CoPs. In the conventional system, an optical motion capture system (OMC) containing 8 infrared light cameras (6+ series, Qualisys, Gothenburg, Sweden) was used to measure body kinematics data using reflective markers. A split-belt instrumented treadmill (Motek-Forcelink B.V, Culemborg, The Netherlands) was used to measure the GRFs under each foot. Two video cameras were also included inside the conventional system to capture the RGB images of participants’ body postures at the sagittal and frontal planes (https://doi.org/10.5281/zenodo.6644593). In addition, nine electromyography sensors (EMGs) (Delsys Trigno, Delsys, USA) were included to record the activations of nine major muscles in the dominant leg ("soleus", "medial gastrocnemius", "lateral gastrocnemius", "tibialis anterior", " semimembranosus", " biceps femoris long head", "vastus lateral", "rectus femoris", "vastus medial").

In this shared data repository, both raw data (to be uploaded) and processed data (Processed_data.zip) are provided. The data processing pipeline can be found in this public GitHub repository: https://github.com/ET-BE/BioMechPro/tree/study/WearableSystemValidation. Guidelines for creating the same wearable system in the corresponding comparison study are shared in this GitHub repo: https://github.com/HuaweiWang/WearableMeasurementSystem.

[Note!] If you have unstable network that not able to download the huge data files, please check this version of dataset with small file sizes(2GB each)

• Raw data: https://doi.org/10.5281/zenodo.7422043
• Processed data: https://doi.org/10.5281/zenodo.7422031

Dataset structure descriptions:

Raw_data.rar: Raw dataset

• Subjxx: subject folder
  • Qualisys: Qualisys project folder of the recordings
  • Xsens: Xsens project folder of the recordings
  • Insoles: Pressure insole project folder of the recordings

Processed_data.rar: Processed dataset.

• allAverage.mat: the overall summarization data of all subject at all movement trials.
• dataValidation.m: the Matlab code to plot the summarization data by loading the allAverage.mat.
• subjs_info.txt: general information of all participants.
• ComparisonPlots: folder that contains the comparison plots between the laboratory-based system and the wearable measurement systems.
• Subjxx: processed data for participants xx
  • dynMVCvalue.mat: the dynamic Maximal Voluntary Contraction of measured muscles (highest value among all recorded movements)
  • MVCvalue.mat: the Maximal Voluntary Contraction of measured muscles (highest value in MVC recording trial only)
  • Subjxx_xxxx_xx.mat: the processed data (generated by the above mentioned processing pipeline) of current subject at specific movement trial.
  • Qualisys: The exported mat files from the Qualisys recordings, including markers, EMGs, GRFs.
  • Xsens: The exported .mvnx files from the Xsens MVN software reprocessing. This file can be directly loaded by Matlab without requiring the Xsens license.
  • Insole: Insole recorded data, parsed from the Moticon endpoint SDK output.
  • OS: The folder that contains the scaled OpenSim model and corresponding .xml and data files for IK and ID processing. Majority content in this folder is automatically generated by the processing pipeline
  • Figures: plots of the processed data, including joint angles, GRFs, joint torques, and EMGs. They are all generated in the last module of the processing pipeline.

Structure of the Subjxx_xxxx_xx.mat:

Subjxx_xxxx_xx.mat:

• Info: the general information of the participant and corresponding processing steps.
• Marker: Marker data from Qualisys
• Force: GRFs data from Qualisys
• EMG: EMG data from Qualisys
• IMU: Motion data from Xsens IMU system (from .mvnx)
• Insole: The recorded pressure insole data
• Resample: This data structure that contains the resampled data of the above mentioned sensor data
  • FrameRate: the sampling rate for all resampled sensor data
  • Marker: Resampled marker data
  • Force: resampled force data
  • EMG: resampled EMG data
  • IMU: resampled IMU data
  • Insole: resampled Insole data
  • CoM: resampled center of mass data from Xsens IMU system
  • Sych: this data structure contains the IK & ID data of two measurement systems. They are also synchronized by calculate the highest correlation coefficient.
    • DeltaT: the time differences between the laboratory-based system and the wearable measurement system.
    • IKAngData: the joint angle data from marker data inverse kinematics
    • ForcePlateGFRData: the ground reaction force data from instrumented treadmill
    • IDTrqData: the joint torque data from laboratory measurement system (optical + treadmill)
    • IMUAngData: the joint angle data from Xsens MVN software
    • InsoleGRFData: the ground reaction force data from pressure insoles
    • IDTrqData_portable: the joint torque data from the wearable system inverse dynamics
    • EMG: synchronized EMG data
    • CoM: synchronized CoM data
    • xxxxxLabel: the labels of each data column of corresponding data matrix
    • Average: this data structure contains the averaged gait/moment cycles
      • hsMatrix_right: The heel strike data points of the right leg
      • hsMatrix_left: the heel strike data points of the left leg
      • EMGAvedynNorFlag: whether dynamic MVC normalization is applied on EMG.
      • EMGAveNorFlag: whether MVC normalization is applied on EMG.
      • xxxx: The averaged data of corresponding variables
      • ForcePlateGRFDataInCalCn: transferred treadmill GRF data from the treadmill global coordinate to the local Calcaneus coordinate of the scaled OpenSim model.

This classification contains the codes for the different types of measurement. To create this classification we have used the proposal used by Google, in its standard Dataset Publishing Language (DSPL).

During a global October 2023 survey among communications specialists, almost **** out of five (or ** percent) of respondents said they used engagement data such as comments, views, shares and likes, to measure the individual success of each influencer marketing campaign. Around ** percent of interviewees mentioned product sales, while ** turned to impressions as a metric for success rate.

Market Overview:

The global inner diameter measurement system market is projected to grow at a CAGR of 6.5% from 2022 to 2030. The market growth is attributed to the increasing demand for inner diameter measurement systems in various applications such as automotive, manufacturing, pharmaceuticals & healthcare, construction and others. In terms of type, the optical method segment is expected to lead the global inner diameter measurement system market during the forecast period owing to its advantages such as accuracy and precision.

Product Definition:

The inner diameter measurement system is a type of measurement system that uses a helical or spiral groove to measure the inside diameter of objects. This system has several advantages over other types of measurement systems, including its ability to accurately measure small diameters and its low cost. Additionally, the inner diameter measurement system is often used in conjunction with other measurement systems, such as the outside diameter measurement system, to create a complete description of an object's dimensions.

Optical Method:

The optical method is a non-destructive testing technology that uses light to measure the internal diameter of tubes and pipes. It provides highly accurate results in a short period as compared to other conventional methods. The optical method can be used for both, thin-walled as well as thick-walled tubes and pipes.

Triangulation Method:

The Triangulation method is used to measure the inner diameter of a pipe or tube. It uses three points to determine the size of an object. The method can be used for any shape and is not limited to round objects only. It measures the largest point on one side, then the middle point and finally measures from that point on the other side using the Law of Cosines property which gives you an angle measurement to calculate the inner diameter.

Spectral Interference Method:

The spectral interference method is a type of inner diameter measurement system that uses the principle of interference to determine the size of an object. This system is advantageous because it is relatively easy to use and can be used in a variety of environments. Additionally, this method is accurate and can be used to measure objects of a variety of shapes and sizes.

Application Insights:

The automotive application segment accounted for the largest share of over 30.0% in 2019 and is expected to continue its dominance over the forecast period. The system is widely used in vehicle manufacturing facilities, engine production, body shops and others to measure the dimensional accuracy of various components such as gears, shafts, bearings etc., which are critical to ensure a safe and reliable functioning of a component or an entire assembly.

The pharmaceutical & healthcare application segment accounted for nearly 19.0% share in 2019 owing to high demand from medical device manufacturers who require consistent quality standards across all processes involved with product development & manufacturing including raw material procurement & distribution as well as component fabrication activities at different levels throughout the supply chain network. In addition, stringent regulatory requirements related to patient safety along with rising awareness among end-users regarding process reliability are further anticipated to propel the market growth during the forecast period.

Regional Analysis:

The Asia Pacific dominated the global inner diameter measurement system sales in 2015 and is expected to continue its dominance over the forecast period. This can be attributed to increasing automotive production, high manufacturing volume of electronics products, rapid urbanization and infrastructure development in this region. The growing construction industry due to the rising population is also anticipated to drive product demand over the next eight years.

North America accounted for a significant share of global market revenue owing to early adoption by manufacturers in this region coupled with high R&D investments by universities & research institutes for developing innovative sensors technology. Europe accounted for the second-largest share of global market revenue owing to the presence of major automobile manufacturers such as Daimler AG; BMW Group; Fiat Chrysler Automobiles N.V.; Ferrari S.pA.; Mercedes-Benz AMG GmbH; Porsche AG etc., which are continuously investing in new technologies such as lightweight materials, electric motors and batteries, etc.

In this paper, we generalize the notion of measurement error on deterministic sample datasets to accommodate sample data that are random-variable-valued. This leads to the formulation of two distinct kinds of measurement error: intrinsic measurement error, and incidental measurement error. Incidental measurement error will be recognized as the traditional kind that arises from a set of deterministic sample measurements, and upon which the traditional measurement error modelling literature is based, while intrinsic measurement error reflects some subjective quality of either the measurement tool or the measurand itself. We define calibrating conditions that generalize common and classical types of measurement error models to this broader measurement domain, and explain how the notion of generalized Berkson error in particular mathematicizes what it means to be an expert assessor or rater for a measurement process. We then explore how classical point estimation, inference, and likelihood theory can be generalized to accommodate sample data composed of generic random-variable-valued measurements.

Home Health Care Agency Ratings

Quality Measurements, Types of Services and More

By US Open Data Portal, data.gov [source]

About this dataset

This dataset provides a list of all Home Health Agencies registered with Medicare. Contained within this dataset is information on each agency's address, phone number, type of ownership, quality measure ratings and other associated data points. With this valuable insight into the operations of each Home Health Care Agency, you can make informed decisions about your care needs. Learn more about the services offered at each agency and how they are rated according to their quality measure ratings. From dedicated nursing care services to speech pathology to medical social services - get all the information you need with this comprehensive look at U.S.-based Home Health Care Agencies!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

Are you looking to learn more about Home Health Care Agencies registered with Medicare? This dataset can provide quality measure ratings, addresses, phone numbers, types of services offered and other information that may be helpful when researching Home Health Care Agencies.

This guide will explain how to use the data in this dataset to gain a better understanding of Home Health Care Agencies registered with Medicare.

First, you will need to become familiar with the columns in the dataset. A list of all columns and their associated descriptions is provided above for your reference. Once you understand each column’s purpose, it will be easier for you to decide what metrics or variables are most important for your own research.

Next, use this data to compare various facets between different Home Health Care Agencies such as type of ownership, services offered and quality measure ratings like star rating or CMS certification number (from 0-5 stars). Collecting information from multiple sources such as public reviews or customer feedback can help supplement these numerical metrics in order to paint a more accurate picture about each agency's performance and customer satisfaction level.

Finally once you have collected enough data points on one particular agency or a comparison between multiple agencies then conduct more analysis using statistical methods like correlation matrices in order to determine any patterns that exist within the data set which may reveal valuable insights into topic of research at hand

Research Ideas

• Using the data to compare quality of care ratings between agencies, so people can make better informed decisions about which agency to hire for home health services.
• Analyzing the costs associated with different types of home health care services, such as nursing care and physical therapy, in order to determine where money could be saved in health care budgets.
• Evaluating the performance of certain agencies by analyzing the number of episodes billed to Medicare compared to their national averages, allowing agencies with lower numbers of billing episodes to be identified and monitored more closely if necessary

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: csv-1.csv | Column name | Description | |:----------------------------------------...

Roundness Measuring Machine Market Outlook

The global roundness measuring machine market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 2.5 billion by 2032, with a compound annual growth rate (CAGR) of 8.5%. The market's growth is driven by the increasing demand for precision engineering, particularly in high-precision industries such as automotive and aerospace, where the accuracy of components is critical.

One of the key growth factors for the roundness measuring machine market is the continuous advancement in manufacturing technologies. Industries are increasingly adopting automation and precision engineering to enhance the quality and efficiency of their production processes. The need for highly accurate measurements has made roundness measuring machines indispensable in quality control processes. Additionally, the integration of advanced software solutions with these machines has improved their functionality, making them more user-friendly and efficient.

Another significant growth driver is the rising demand in the automotive sector. With the automotive industry constantly evolving to meet stringent emission norms and safety standards, the need for precision-engineered components is higher than ever. Roundness measuring machines play a crucial role in ensuring the accuracy of these components, thus bolstering their adoption in the sector. Moreover, the increasing production of electric vehicles, which require high precision in components, is expected to further drive market growth.

The aerospace industry also contributes significantly to the market's expansion. The sector's high demand for precision and reliability in components makes roundness measuring machines essential. As aerospace manufacturers strive to meet the high standards of safety and performance, the adoption of these machines is expected to surge. Additionally, the growing emphasis on reducing waste and improving material efficiency in aerospace manufacturing processes further supports market growth.

Regionally, the Asia Pacific region is expected to witness substantial growth in the roundness measuring machine market. The region's robust manufacturing base, particularly in countries like China, Japan, and South Korea, drives the demand for advanced measurement solutions. Additionally, the increasing investments in the automotive and aerospace sectors in these countries contribute to market expansion. North America and Europe also present significant growth opportunities due to the presence of established automotive and aerospace industries and the continuous advancements in manufacturing technologies.

Product Type Analysis

When analyzing the roundness measuring machine market by product type, it is essential to consider the two main categories: contact type and non-contact type. Contact-type roundness measuring machines utilize tactile probes to measure the roundness of an object by physically touching it. These machines are highly accurate and are widely used in applications where high precision is required. Their reliability and ease of use make them a popular choice in various industries, including automotive and aerospace.

Non-contact type roundness measuring machines, on the other hand, employ optical or laser-based systems to measure the roundness of objects without physically touching them. These machines are advantageous in situations where the object being measured is delicate or has a surface that could be damaged by contact. Non-contact measurements are also faster and can be more suitable for high-volume production environments. The advancement in laser and optical technologies has significantly improved the accuracy and reliability of non-contact measuring machines, making them increasingly popular in industrial manufacturing and medical applications.

The choice between contact type and non-contact type roundness measuring machines often depends on the specific requirements of the application. For instance, in the automotive industry, where components such as engine parts and transmission gears require high precision, contact type machines are preferred for their accuracy. In contrast, non-contact machines are more suitable for measuring medical devices and components that are sensitive to physical contact.

Overall, both product types are expected to witness significant growth during the forecast period. The continuous advancements in measurement technologies and the increasing demand for high-precision components across various ind

1. Introduction

The file “gen_dd_channel.zip” is a package of a wideband multiple-input multiple-output (MIMO) stored radio channel model at 140 GHz in indoor hall, outdoor suburban, residential and urban scenarios. The package consists of 1) measured wideband double-directional multipath data sets estimated from radio channel sounding and processed through measurement-based ray-launching and 2) MATLAB code sets that allows users to generate wideband MIMO radio channels with various antenna array types, e.g., uniform planar and circular arrays at link ends.

2. What does this package do?

Outputs of the channel model

The MATLAB file “ChannelGeneratorDD_hexax.m” gives the following variables, among others. The .m file also gives optional figures illustrating antennas and radio channel responses.

Inputs to the channel model

In order for the MATLAB file “ChannelGeneratorDD_hexax.m” to run properly, the following inputs are required.

User’s parameters

When using “ChannelGeneratorDD_hexax.m”, the following choices are available.

List of files in the dataset

MATLAB codes that implement the channel model

The MATLAB files consist of the following files.

Measured multipath data

The directory "data_030123_double_directional_paths" in the package contains the following files.

References

Details of the data set are available in the following two documents:

The stored channel models

A. Nimr (ed.), "Hexa-X Deliverable D2.3 Radio models and enabling techniques towards ultra-high data rate links and capacity in 6G," April 2023, available: https://hexa-x.eu/deliverables/

@misc{Hexa-XD23,
author = {{A. Nimr (ed.)}},
title = {{Hexa-X Deliverable D2.3 Radio models and enabling techniques towards ultra-high data rate links and capacity in 6G}},
year = {2023},
month = {Apr.},
howpublished = {https://hexa-x.eu/deliverables/},
}

Derivation of the data, i.e., radio channel sounding and measurement-based ray-launching

M. F. De Guzman and K. Haneda, "Analysis of wave-interacting objects in indoor and outdoor environments at 142 GHz," IEEE Transactions on Antennas and Propagation, vol. 71, no. 12, pp. 9838-9848, Dec. 2023, doi: 10.1109/TAP.2023.3318861

@ARTICLE{DeGuzman23_TAP,
author={De Guzman, Mar Francis and Haneda, Katsuyuki},
journal={IEEE Transactions on Antennas and Propagation},
title={Analysis of Wave-Interacting Objects in Indoor and Outdoor Environments at 142 {GHz}},
year={2023},
volume={71},
number={12},
pages={9838-9848},
}

Finally, the code “randl.m” are from the following MATLAB Central File Exchange.

Hristo Zhivomirov (2023). Generation of Random Numbers with Laplace Distribution (https://www.mathworks.com/matlabcentral/fileexchange/53397-generation-of-random-numbers-with-laplace-distribution), MATLAB Central File Exchange. Retrieved February 15, 2023.

Data usage terms

Any usage of the data must be upon consent on the following conditions:

• The file “ChannelGeneratorDD_hexax.m” is owned by OUL. Contact: Dr. Pekka Kyösti, Pekka.Kyosti@oulu.fi.
• The other files and those in the directories, except for “randl.m”, are owned by AAU. Contact: Mr. Mar Francis de Guzman, francis.deguzman@aalto.fi.
• When a scientific paper is published that exploits the data and code, please cite this data set; the citation can be downloaded from the zenodo page of this data set.

Body Measurements Dataset

The dataset consists of a compilation of people's photos along with their corresponding body measurements. It is designed to provide information and insights into the physical appearances and body characteristics of individuals. The dataset includes a diverse range of subjects representing different age groups, genders, and ethnicities. The photos are captured in a standardized manner, depicting individuals in a front and side positions. The images aim to… See the full description on the dataset page: https://huggingface.co/datasets/TrainingDataPro/body-measurements-dataset.

We designed two new samplers for monitoring airborne particulates, including fungal and fern spores and plant pollen, that rely on natural wind currents (Passive Environmental Sampler) or a battery operated fan (Active Environmental Sampler). Both samplers are modeled after commercial devices such as the Rotorod® and the Burkard® samplers, but are more economical and require less maintenance than commercial devices. We compared our two new samplers to Rotorod® samplers using Xyleborus spp. boring dust (frass) known to contain fungi responsible for Rapid Ohia Death. The comparison was done in a large outdoor field cage to determine relative effectiveness of the three samplers for capturing windblown boring dust. The dataset contains measurements of boring dust particles that were captured by the three types of samples over the course of twelve trials.

The National Measurement Office provides a range of type approval services designed to enable manufacturers gain access to European and global markets for weighing and other regulated measuring instruments. Where a manufacture's instrument complies with the regulation, European Directives and International Recommendations (OIML), a certificate of conformity is issued. These data sets show which companies have been issued a certificate and which product it relates to.

Horizontal Measuring Instrument Market Outlook

The global Horizontal Measuring Instrument market size was valued at USD 3.2 billion in 2023 and is expected to reach USD 5.6 billion by 2032, growing at a CAGR of 6.3% during the forecast period. The growth of this market is driven by the increasing demand for precision measurement tools in various industries, technological advancements, and the growing adoption of automated systems in manufacturing processes.

One of the significant factors propelling the growth of the Horizontal Measuring Instrument market is the rapid industrialization and the subsequent need for precise and accurate measurement tools. Industries such as manufacturing, automotive, and aerospace require high precision in their operations to ensure quality and efficiency. The use of advanced horizontal measuring instruments, such as digital calipers and micrometers, enables these industries to achieve the necessary precision, thereby driving the market growth. Moreover, the increasing emphasis on quality control and assurance in manufacturing processes further amplifies the demand for these instruments.

The ongoing advancements in measurement technology are another critical factor contributing to the market growth. Modern horizontal measuring instruments are equipped with digital displays, wireless connectivity, and enhanced accuracy features, making them more efficient and user-friendly. These technological advancements not only improve the performance of the instruments but also expand their application scope across various industries. Furthermore, the integration of software solutions with measuring instruments for data analysis and management is expected to boost the market growth significantly over the forecast period.

Additionally, the growing adoption of automation in manufacturing and construction processes is creating a favorable environment for the Horizontal Measuring Instrument market. Automated measuring systems are increasingly being used to enhance productivity, reduce human errors, and ensure consistent quality. The rising awareness about the benefits of automation, coupled with the increasing investments in automated systems, is expected to drive the demand for horizontal measuring instruments. This trend is particularly prominent in regions with advanced industrial infrastructure, such as North America and Europe.

From a regional perspective, the Asia Pacific region is anticipated to witness substantial growth in the Horizontal Measuring Instrument market during the forecast period. This growth can be attributed to the increasing industrial activities, rapid urbanization, and the expanding construction industry in countries such as China, India, and Japan. The presence of a large number of manufacturing facilities and the growing automotive industry in this region are also contributing to the market expansion. Moreover, favorable government initiatives to promote industrial development and technological innovation are expected to further boost the market growth in Asia Pacific.

Product Type Analysis

The Horizontal Measuring Instrument market is segmented by product type into calipers, micrometers, gauges, levels, and others. Each of these product types serves distinct measurement needs across various industries and applications. Calipers, for instance, are widely used for measuring the distance between two opposite sides of an object. They are available in different forms, such as vernier, dial, and digital calipers, each offering varying degrees of precision and ease of use. The demand for digital calipers is particularly high due to their accuracy, ease of reading measurements, and integration with data recording systems.

Micrometers, another critical segment, are precision instruments used to measure small distances with high accuracy. They are commonly used in mechanical engineering, machining, and manufacturing industries. Micrometers are available in different types, including outside, inside, and depth micrometers, catering to various measurement requirements. The increasing need for precise measurements in manufacturing processes is driving the demand for micrometers, particularly digital micrometers that offer enhanced readability and data recording capabilities.

Gauges are also an essential category within the horizontal measuring instruments market. They are used for measuring or checking the size, shape, and other dimensional attributes of manufactured parts. Gauges come in various forms, such as ring gauges, plug gauges, and snap gauges, each designed for specific measurement ta

The dataset is presented in the paper:

Building and analysing a labelled Measure While Drilling dataset from 15 hard rock tunnels in Norway, by T.F. Hansen, Z. Liu, J. Torressen

The paper has a preprint on SSRN: http://dx.doi.org/10.2139/ssrn.4729646 and is under review in a peer-reviewed journal.

The dataset is utilised in a machine learning analysis in the paper:

Predicting rock type from MWD tunnel data using a reproducible ML-modelling process, by T.F. Hansen, Z. Liu, J. Torressen

The paper is published in the journal Tunnelling and Underground Space Technology:

https://doi.org/10.1016/j.tust.2024.105843

Description of the dataset:

Measure While Drilling (MWD) is a technique in rock drilling, mainly used in drill and blast tunnelling, where data about the rock mass is registered by sensors while drilling. The extensive and geologically diversified dataset contains corresponding MWD-data and rock mass mappings for 5205 blasting rounds from 15 hard rock tunnels in Norway. MWD-data are presented as tabular data. 10 different rocktypes are the corresponding labels.

Four files are given:

A csv-file of the training dataset - with outliers removed

A csv-file of the testing dataset (split train/test 0.75/0.25) - with outliers removed

A csv-file with the full unsplitted dataset, cleaned and with outliers removed

A csv-file with the raw dataset, before cleaning, processing and outlier removal

The author gratefully acknowledge the tunnel software/hardware company Bever Control, which have facilitated data from the clients Bane NOR, Statens Vegvesen, Nye Veier, and the contractor AF-Gruppen.

NOTE: The dataset is only available for research, no commercial use.

The AMLEs and MGLEs for the slope parameter in the model Y|X ∼ N(βX, σ2) using the toy dataset on four sample measurements for the given measurement protocols for X and Y, and different RVVMs for ρX(ω1) and ρX(ω2).

Global Moving Platform Video Measureing Machine Market is expanding from US$ 1638.6 Million in 2023 to US$ 3630.01 Million by 2032 with a CAGR of 9.24%.

The global pneumatic measuring instrument market is experiencing robust growth, driven by increasing automation across diverse industries like mechanical manufacturing, electronics, and chemicals. The market's expansion is fueled by the inherent advantages of pneumatic instruments, including their robustness, reliability in harsh environments, and cost-effectiveness compared to other measuring technologies. The rising demand for precision measurement in manufacturing processes, particularly in quality control and process optimization, is a key factor bolstering market growth. Technological advancements, such as the integration of smart sensors and digital communication protocols (like IIoT), are further enhancing the capabilities and appeal of pneumatic measuring instruments, driving adoption across various applications. While the market faces challenges like the increasing prevalence of alternative technologies (e.g., optical and laser-based sensors) and the potential impact of economic fluctuations, the overall growth trajectory remains positive, particularly in emerging economies with expanding manufacturing sectors. The segment encompassing pressure pneumatic measuring instruments holds a significant market share, reflecting its widespread use in industrial applications requiring precise pressure measurement. Market segmentation reveals strong growth in the electronic and chemical sectors, attributed to their increased demand for high-precision measurements in quality control and process monitoring. The buoy-type pneumatic measuring instruments are also witnessing substantial growth, particularly in applications requiring non-contact measurement. While North America and Europe currently dominate the market, the Asia-Pacific region, led by China and India, exhibits significant potential for growth due to rapid industrialization and infrastructure development. Companies like Endress+Hauser, Emerson, and Yokogawa are key players, leveraging their established technological expertise and global distribution networks to maintain a competitive edge. Continued investment in research and development, strategic partnerships, and expansion into emerging markets will be crucial factors driving future growth in this dynamic market. We estimate the market size will experience a substantial rise over the forecast period.

The Measurement Infrastructure Gap Analysis in Utah’s Great Salt Lake Basin was a comprehensive inventory and analysis of existing diversion and stream measurement infrastructure along 19 primary river systems, as well as a preliminary investigation of measurement infrastructure gaps around Great Salt Lake proper. The purpose of this “Gap Analysis” was to develop methods to identify and prioritize areas throughout the Great Salt Lake basin where new or updated measurement infrastructure is needed to serve diverse objectives. The following gaps were identified: (1) existing measurement infrastructure quality and completeness gaps, (2) stakeholder identified gaps, and (3) potential spatial gaps in hydrologic understanding. By adapting the prioritization schema originally presented in the Colorado River Metering and Gaging and Gap Analysis to equally weight these three gap types at the HUC12 scale, a flexible framework for prioritizing new or updated measurement infrastructure in areas with large cumulative measurement gaps was developed, and high, medium, and low priority HUC12s were identified.

Results showed that 250 diversion and 28 stream measurement devices along primary systems had at least one quality and/or completeness gap. The most common quality and completeness gaps were insufficient device types, lack of telemetry, and data record interval. Stakeholders suggested 50 instances of new or updated diversion measurement infrastructure, 95 instances of new or updated stream measurement infrastructure, and 39 recommendations for continued funding of existing measurement infrastructure—totaling 185 stakeholder-identified gaps. To provide a spatially consistent approach to identifying potential gaps in hydrologic understanding, geospatial datasets describing features or attributes that can impact local hydrology were used to identify measurement gaps at the HUC12 scale. Among HUC12s that overlapped with the river systems included in this analysis, HUC12s with the greatest number of potential spatial gaps were in the Bear River sub-basin and near reservoirs in the Weber River sub-basin.

Based on the prioritization schema applied to synthesize these three gap types, there were 52 HUC12s along primary systems classified as high priority for measurement improvement. Of the 250 existing diversion and 28 stream measurement devices with at least one quality and/or completeness gap, 217 and 10 devices, respectively, were located within high priority HUC12s. Most stakeholder-identified gaps identified in the Weber and Jordan River sub-basins also fell within high-priority HUCs. Eighteen unique agencies suggested new or updated measurement infrastructure or continued funding of existing measurement infrastructure in high-priority HUC12s, demonstrating some consensus regarding measurement gaps in critical areas. There were 6 high priority HUC12s with no existing measurement infrastructure quality and completeness gaps, and 11 high priority HUC12s with no stakeholder-identified gaps. High priority HUC12s highlighted only due to potential spatial gaps may warrant additional investigation to further understand potential measurement gaps in these HUC12s.

Because the prioritization schema applied equally weighted all three gap types, it likely does not fully represent the diverse missions and priorities of different stakeholder groups. To facilitate an adaptable approach to prioritize measurement gaps within the Great Salt Lake basin, raw data for each of the three gap types are provided to allow varied prioritization schemes to be developed by weighting gap types differently or considering subsets of data. These data provide the basis for stakeholders within the Great Salt Lake basin to collectively prioritize future investments in gaging infrastructure and better manage water throughout the Great Salt Lake basin.

This dataset includes data from 43 hospitalized patients with type 2 diabetes mellitus. Dexcom G5 and Dexcom G6 mobile continuous glucose measurement (CGM) devices were used to measure continuous blood glucose levels. The data collection period is from April 2019 to January 2022. We selected 43 patients whose records with a more extended recording period of more than seven days. Data was collected for 7 to 10 days at 5-minute intervals. This data can be used for glucose level prediction or hypoglycemia occurrence prediction for patient with type 2 diabetes mellitus.