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Background The assessment of diaphragm function is crucial for effective clinical management and the prevention of complications associated with diaphragmatic dysfunction. However, current measurement methodologies rely on manual techniques that are susceptible to human error: How does the performance of an automatic diaphragm measurement system based on a segmentation neural network focusing on diaphragm thickness and excursion compare with existing methodologies? Methods The proposed system integrates segmentation and parameter measurement, leveraging a newly established ultrasound diaphragm dataset. This dataset comprises B-mode ultrasound images and videos for diaphragm thickness assessment, as well as M-mode images and videos for movement measurement. We introduce a novel deep learning-based segmentation network, the Multi-ratio Dilated U-Net (MDRU-Net), to enable accurate diaphragm measurements. The system additionally incorporates a comprehensive implementation plan for automated measurement. Results Automatic measurement results are compared against manual assessments conducted by clinicians, revealing an average error of 8.12% in diaphragm thickening fraction measurements and a mere 4.3% average relative error in diaphragm excursion measurements. The results indicate overall minor discrepancies and enhanced potential for clinical detection of diaphragmatic conditions. Additionally, we design a user-friendly automatic measurement system for assessing diaphragm parameters and an accompanying method for measuring ultrasound-derived diaphragm parameters. Conclusions In this paper, we constructed a diaphragm ultrasound dataset of thickness and excursion. Based on the U-Net architecture, we developed an automatic diaphragm segmentation algorithm and designed an automatic parameter measurement scheme. A comparative error analysis was conducted against manual measurements. Overall, the proposed diaphragm ultrasound segmentation algorithm demonstrated high segmentation performance and efficiency. The automatic measurement scheme based on this algorithm exhibited high accuracy, eliminating subjective influence and enhancing the automation of diaphragm ultrasound parameter assessment, thereby providing new possibilities for diaphragm evaluation.

A range of motion (ROM) has been measured using several indices to judge the progress of ankylosing spondylitis (AS). However, measuring and calculating the ROM is time-consuming & labor-intensive and it would be even difficult to measure accurately. Thus, an automated measurement system (AMS) is proposed & developed to measure the ROM more easily without any restraint sensor, and to recognize changes in the ROM more constantly with the same standard of measurement. The measurement items are neck cervical rotation, cervical lateral flexion, finger-to-floor distance, intermalleolar distance, and lumbar side flexion. Data from 30 healthy subjects were collected by the AMS and their motions were recorded simultaneously by installed webcams to acquire gold-standard data compared with the measurement value of the AMS. The accuracy was determined by calculating the standard error of estimation (SEE) and a possibility of replacement of measurement obtained by a physician using a protractor & ruler has been assessed by pattern recognition of Bland-Airman plots. These statistical results exhibit a significant degree of agreement with the novel AMS. The total measurement time for the 5 items using the proposed AMS was less than 5 min, which is faster than manual measurement. However, the measurement was conducted against only healthy subjects; therefore additional tests with AS patients will be required for utilization in clinical practice.

The present paper focuses on the analysis of the possibilities of using integral transforms for measuring and evaluating the differences of compared images (car silhouettes) with the purpose of a correct car body categorization. Approaches such as the light intensities frequency change, the application of discrete integral transforms without the use of further supplementary information enabling automated data processing using the Fourier-Mellin transforms are used within this work. The calculation of the several metrics was verified through different combinations that implied using and not using the Hamming window and a low-pass filter. The paper introduced a method for measuring and evaluating the differences in the compared images (car silhouettes). The proposed method relies on the fact that the integral transforms have their own transformants in the case of translation, scaling and rotation, in the frequency area. Besides, the Fourier-Mellin transform was to offer image transformation that is resistant to the translation, rotation and scale.

An automatic measurement system used on deviation measurement of the cable crane tower has been designed, and the development ideas and the key codes have also been given. Then by experiment, it has been improved that the system has overcame the shortcomings of low efficiency and high labor intensity existed in the previous manual targeting, and measurement errors have also been reduced by the automatic measurement system. Based on the above advantages, the system has a high application value and promotion prospects.

During the production of the low-pressure casting aluminumwheel hub, the head face deformation and axial deformation of the casting blank are always happened due to various factors.The casting wheels beyond tolerance are considered as waste products with no need for further machining. Traditionally, the measurement of the deformation is usually static and by handwork,which limits the accuracy and reliability. This paper introduces anon-line automatic measuring system for casting wheels based on laser measuring technology. The configuration of the system and measuring method are presented in detail. Test results showed that the system could meet the measurement requirements: the whole measurement process operated quickly with the total time of 30s; the dimensional accuracy reached 0.02mm while the measurement error of the deformation was within 0.04mm. The system achieves better repeatability and reliability compared to the manual measurement.

In industrial machining of timber, the method in which the operator visually inspects both wear and chippings of router bits after stopping the machine is generally adopted. However, many working hours are lost in this method and productivity suffers. Therefore, the development of a system that can automatically measure wear or chippings without stopping the machine is desirable. In this study, a laser measuring instrument was installed in a computerized numerically controlled (CNC) router, and an automatic measurement system for the cutting edge profile of throw-away-type straight bits with single-edged blades was developed. The main results are summarized as follows: (1) an automatic measurement system for the cutting edge profile of the bit was constructed; (2) this system was composed of a laser measuring instrument, a control personal computer (PC) for the CNC router, and a monitoring PC to control some devices and collect sampling data; (3) the system could measure the cutting edge profile of the bit without stopping the CNC router.

An automatic sampling and measurement system was developed to take water samples efficiently during rain events. The system consisted of an automatic sampler, a rain gauge and a data logger as well as sensors for pH, electrical conductivity (EC), and both water and air temperature. The system was tested in a stream in a forested watershed (5.8 km2) located in the middle of Hyogo prefecture, Japan. The sampling program has been improved gradually. For several rain events of 30 to 157 mm, most water samples were in agreement with the hydrograph from the beginning of each rainfall until the rain had stopped and the water level had begun to fall. The fluctuations in water quality in the samples taken by the automatic sampler during those rain events showed patterns similar to those of water samples taken by hand. There were also no problems with the water level or the EC sensor during the investigation periods, but the pH values were lower than those in the laboratory. The results showed that the system is suitable for taking water samples from mountainous streams during rain events.

Nowadays, acid rain is generally noticed as a global environmental problem. While acid rain has very much to do with the air pollutants, the relation between air pollution and chemical constituents in precipitation is not understood clearly yet. It is important to measure a variation of ion concentration in precipitation in short term for understanding the formation mechanism of acid rain. Therefore, an automatic continuous measurement system of chemical constituents in precipitation was developed and put into practical use in this study. The developed system was able to collect automatically every 1mm of precipitation and analyze major ions within 20 minutes.

\"Big Data\" is on the covers ofScience, Nature, theEconomist, andWiredmagazines, on the front pages of theWall Street Journaland theNew York Times.But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines.Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six \"provocations\" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.

* Covers all aspects of the data acquisition system from design and specification to programming, installation and configuration * Gives both the novice and experienced user a solid understanding of interfacing the PC and standalone instruments to real-world signals from the laboratory to the industrial plant * Provides a thorough grasp of PC data.