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\"The fifth edition of this market leading book provides mechanical engineers with the most up to date coverage of mechanical measurements. Sound theory is highlighted by rich and current practical examples. New chapter opening learning objectives and outcomes explore the critical concepts that will be discussed. New and revised examples and problems clearly show how the information is applied in the field. Expanded discussions are included on measurements, equipment, and basic metrology. The DFT concept presentation is now simplified. More pictures have also been added to make the material easier to learn. Mechanical engineers will then better understand the elements for the design of measurement systems and measurement test plans.\"--Publisher's website.

The topic of engagement has been attracting increasing amounts of attention in the field of e-learning. Research shows that multifarious benefits occur when students are engaged in their own learning, including increased motivation and achievement. Previous studies have proposed many scales for measuring student engagement. However, very few have been developed to measure engagement in e-learning environments. Thus, developing an instrument for measuring student engagement in e-learning environments is the purpose of this study. The participants of this study were 737 Korean online university students. Initial items were designed based on the literature. The instrument items were reduced from an initial 48 to 24 items after obtaining expert opinion and then validity and reliability analysis. Exploratory and confirmatory factor analyses were also conducted. Six factors, including psychological motivation, peer collaboration, cognitive problem solving, interaction with instructors, community support, and learning management emerged in the 24-item scale. This scale is expected to help instructors and curriculum designers to find conditions to improve student engagement in e-learning environments, and ultimately prevent students from dropping out of online courses.

Reviews the basics of rulers and observe them being used by scientists as well as by professionals in the working world.

This paper gives an elaboration on the source of uncertainty, general class and its difference with error, followed by detailed analysis and verification of a real case of measurement uncertainty. Taking a multi-function three-phase electrical measuring instrument calibration device as an example, the paper describes how to evaluate the uncertainty in measurement result of indication errors in mathematical model.

Presents information about measuring containers scientists use for their own science experiments.

Metrology is the science and study of providing accurate measurements. It has relevance to mechanical, industrial, electrical, and quality engineering and is a foundational concept for the manufacturing industry, where the accurate calibration of measurements can have direct impact on a product's end quality and production cost. While metrology has historical roots that date back to the late-18th century, its modern applications remain relevant to the Industry 4.0 technologies of today.

The appropriate period of collocation of a low-cost air sensor (LCS) with reference measurements is often unknown. Previous LCS studies have shown that due to sensor ageing and seasonality of environmental interferences periodical sensor calibration needs to be performed to guarantee sufficient data quality. While the limitations are well-established it is still unclear how often a recalibration of a sensor needs to be carried out. In this study, we demonstrate how widely used air sensors (OX-B431 and SPS30) for the relevant air pollutants ozone (O.sub.3) and fine particulate matter (PM.sub.2.5) by two manufacturers (Alphasense and Sensirion) should be recalibrated for real-world monitoring applications. Sensor calibration functions were built using Multiple Linear Regression, Ridge Regression, Random Forest and Extreme Gradient Boosting. We use multiple novel test protocols for air sensors provided by the United States Environmental Protection Agency and the European Committee for Standardization for evaluative guidance and to identify possible applications for OX-B431 and SPS30 sensors. We conducted a yearlong collocation campaign at an urban background air and climate monitoring station next to the University Hospital Augsburg, Germany. LCSs were exposed to a wide range of environmental conditions, with air temperatures between -10 and 36 °C, relative air humidity between 19 % and 96 % and air pressure between 937 and 983 hPa. The ambient concentration ranges for O.sub.3 and PM.sub.2.5 were up to 82 ppb and 153 µg m.sup.-3, respectively. For the baseline single training of 5 months, the calibrated O.sub.3 and PM.sub.2.5 sensors were able to reflect the hourly reference data well during the training (R.sup.2 : O.sub.3 = 0.92-1.00; PM.sub.2.5 = 0.93-0.97) and the following test period (R.sup.2 : O.sub.3 = 0.93-0.98; PM.sub.2.5 = 0.84-0.93). Additionally, the sensor errors were generally acceptable during the training (RMSE: O.sub.3 = 0.80-4.35 ppb; PM.sub.2.5 = 1.45-2.51 µg m.sup.-3) and the following test period (RMSE: O.sub.3 = 3.62-5.84 ppb; PM.sub.2.5 = 2.04-3.02 µg m.sup.-3). We investigated different recalibration cycles using a pairwise calibration strategy, which is an uncommon method for recurrent LCS calibration. Our results indicate that a regular in-season recalibration is required to obtain the highest quantitative validity and broadest range of applications (indicative and non-regulatory supplemental measurements) for the analysed LCSs. Monthly recalibrations are observed to be the most suitable approach. The measurement uncertainties of the calibrated O.sub.3 LCSs and PM.sub.2.5 LCSs were able to meet the data quality objective for indicative measurements for different calibration models. In-season recalibration, rather than reliance on a single pre-deployment calibration, should be adopted by end-user communities. This approach is required for certain real-world applications to be performed reliably by LCSs and to achieve sufficient information content.

This article presents the results of an LMM-R-2019 interlaboratory comparison. Such comparisons of different families of measuring instruments are one of the activities conducted among the calibration laboratories to maintain their ISO 17025 accreditation. Given that the study of surface roughness is becoming increasingly important in the field of dimensional metrology, the comparison focused on determining the Ra parameter on a pseudorandom metallic roughness standard using two types of measuring instruments: physical contact (stylus instruments) and optical (confocal microscopes). Among the aspects studied was whether the roughness measurements obtained using calibrated confocal microscopes could be compared with those using traditional methods since optical instruments obtain measurements more quickly and responsively than do stylus instruments. The results showed that roughness measurements using confocal microscopes are comparable with those from a traditional stylus instrument.

Lightning strikes can cause significant damage to critical infrastructure and pose a serious threat to public safety. To ensure the safety of facilities and investigate the causes of lightning accidents, we propose a cost-effective design method for a lightning current measuring instrument that uses a Rogowski coil and dual signal conditioning circuits to detect a wide range of lightning currents, ranging from hundreds of A to hundreds of kA. To implement the proposed lightning current measuring instrument, we design signal conditioning circuits and software capable of detecting and analyzing lightning currents from ±500 A to ±100 kA. By employing dual signal conditioning circuits, it offers the advantage of detecting a wide range of lightning currents compared to existing lightning current measuring instruments. The proposed instrument has the following features: First, the peak current, polarity, T1 (front time), T2 (time to half value), and Q (amount of energy of the lightning current) can be analyzed and measured with a fast sampling time of 380 ns. Second, it can distinguish whether a lightning current is induced or direct. Third, a built-in SD card is provided to save the detected lightning data. Finally, it provides Ethernet communication capability for remote monitoring. The performance of the proposed instrument is evaluated and validated by applying induced and direct lightning using a lightning current generator.