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The purpose of this paper is to design and fabricate a three-dimensional (3D) bionic airflow sensing array made of two multi-electrode piezoelectric metal-core fibers (MPMFs), inspired by the structure of a cricket’s highly sensitive airflow receptor (consisting of two cerci).

A metal core was positioned at the center of an MPMF and surrounded by a hollow piezoceramic cylinder. Four thin metal films were spray-coated symmetrically on the surface of the fiber that could be used as two pairs of sensor electrodes.

In 3D space, four output signals of the two MPMFs arrays can form three “8”-shaped spheres. Similarly, the sensing signals for the same airflow are located on a spherical surface.

Two MPMF arrays are sufficient to detect the speed and direction of airflow in all three dimensions.

This paper aims to solve the typical thermal airflow sensor's high power consumption and integration difficulties, based on the FS5 thermal element and constant temperature measurement method, a flow sensor is developed with high measurement accuracy, low power consumption, small size, low cost and easy system integration.

A small wind tunnel was used to test and assess the sensor's measurement range, reaction time, stability, repeatability, measurement accuracy and multi-temperature calibration was performed in the temperature range of −10°C to 30°C. The effect of ambient temperature on the sensor's measurement data is investigated, and the coefficient correction method of power function was investigated to implement the sensor's software temperature compensation function.

The results show that the sensor is stable and repeatable, the output voltage has a power function relationship with the airflow rate, the flow rate measurement range is 0–18 m/s, the response time is less than 3 s, the measurement accuracy at high flow rates is within 0.4 m/s and the temperature-corrected airflow rate measurement error is less than 5%. Setting the temperature calibration interval to 2°C and 5°C has the same temperature compensation effect, reducing the sensor's calibration effort significantly.

This paper demonstrates that a thermostatic method is used to construct a thermal wind speed sensor that delivers accurate measurements in the wind speed measuring range of 0–18 m/s under test conditions. In addition, the sensor's performance is evaluated, and calibration tests for a wide range of temperatures are done. Finally, based on the power function correction method, a temperature compensation algorithm is proposed.

This study aims to propose optimised function-based evolutionary algorithms in this research to effectively replace the traditional electronic circuitry used in linearising constant temperature anemometer (CTA) and Microbridge mass flow sensor AWM 5000.

The proposed linearisation technique effectively uses the ratiometric function for the linearisation of CTA and Microbridge mass flow sensor AWM 5000. In addition, the well-known transfer relation, namely, the King’s Law is used for the linearisation of CTA and successfully implemented using LabVIEW 7.1.

Investigational results unveil that the proposed evolutionary optimised linearisation technique performs better in linearisation of both CTA and Mass flow sensors, and hence finds applications for computer-based flow measurement/control systems.

The evolutionary optimisation algorithms such as the real-coded genetic algorithm, particle swarm optimisation algorithm, differential evolution algorithm and covariance matrix adopted evolutionary strategy algorithm are used to determine the optimal values of the parameters present in the proposed ratiometric function. The performance measures, namely, the full-scale error and mean square error are used to analyse the overall performance of the proposed approach is compared to a state of art techniques available in the literature.

The purpose of this paper is to describe the use and benefits of thermal mass flow sensing on a new Chinese power plant.

The rationale behind the use and application of thermal mass flow sensors on a coal‐fired power plant is described and the benefits derived are identified.

Use of thermal mass airflow sensors have allowed improved control of the plant's combustion process, leading to greater efficiency, reduced emissions and lower maintenance requirements.

This paper illustrates how close measurement and control of the airflow led to improved operation of a coal‐fired power plant.

This paper seeks to pursue the research of different types of sensors suitable for positioning edge accuracy of textile material.

A measuring device is used to install different types of sensors on the slide holders and to change their interspace as well as the space between the sensors and textile fabric.

The new measuring equipment has been established.

Only the results of woven fabric measurement are analyzed in this paper, while the results of knitted and nonwoven fabric measurement will be elaborated in the future papers.

The measuring equipment is original.

The aim of this paper is to investigate the behavior of a new nanometric particle NTC thermistor paste and thick films obtained by screen printing.

Nanometric powder of NTC thermistors based on complex spinel was made by calcination of an oxide mixture and ultra fast ball milling. Characterization of the new powder was done on compacts sintered in different conditions. Segmented thermistors were screen printed on alumina substrata, dried and fired in a conveyor furnace at 850°C/10 min. Segmented thermistors were indirectly heated by a glass sealed heater placed between them in the middle. The system was put in a tube with a regulated air flow to serve as a volume thermistor sensor based on heat loss.

The sintered thick film samples and NTC powder compacts measurements could help in choosing the optimal technology conditions during the production of NTC devices. The NTC segmented thermistors were suitable both for heated sensors and self heated sensors.

Low temperature thick film thermistor pastes based on nanometer powder of complex spinel are of interest due to their importance in sensor applications.

This work predicts that high temperature pastes of the same material can be realized with characteristics superior to those of low temperature paste such as NTC 3K3 or similar.

The purpose of this paper is to describe a multi‐robot solution to the problem of chemical source localization, in which a team of inexpensive, simple vehicles with short‐range, low‐power sensing, communication, and processing capabilities trace a chemical plume to its source emitter

The source localization problem is analyzed using computational fluid dynamics simulations of airborne chemical plumes. The analysis is divided into two parts consisting of two large experiments each: the first part focuses on the issues of collaborative control, and the second part demonstrates how task performance is affected by the number of collaborating robots. Each experiment tests a key aspect of the problem, e.g. effects of obstacles, and defines performance metrics that help capture important characteristics of each solution.

The new empirical simulations confirmed previous theoretical predictions: a physics‐based approach is more effective than the biologically inspired methods in meeting the objectives of the plume‐tracing mission. This gain in performance is consistent across a variety of plume and environmental conditions. This work shows that high success rate can be achieved by robots using strictly local information and a fully decentralized, fault‐tolerant, and reactive control algorithm.

This is the first paper to compare a physics‐based approach against the leading alternatives for chemical plume tracing under a wide variety of fluid conditions and performance metrics. This is also the first presentation of the algorithms showing the specific mechanisms employed to achieve superior performance, including the underlying fluid and other physics principles and their numerical implementation, and the mechanisms that allow the practitioner to duplicate the outstanding performance of this approach under conditions of many robots navigating through obstacle‐dense environments.

In the COVID-19 outbreak periods, people's life has been deranged, leading to disrupt the world. Firstly, the number of deaths is growing and has the potential to surpass the highest level at any time. Secondly, the pandemic broke many countries' fortified lines of epidemic prevention and gave people a more honest view of its seriousness. Finally, the pandemic has an impact on life, and the economy led to a shortage in medical, including a lack of clinicians, facilities and medical equipment. One of those, a simple ventilator is a necessary piece of medical equipment since it might be useful for a COVID-19 patient's treatment. In some cases, the COVID-19 patients require to be treated by modern ventilators to reduce lung damage. Therefore, the addition of simple ventilators is a necessity to relieve high work pressure on medical bureaucracies. Some low-income countries aim to build a simple ventilator for primary care and palliative care using locally accessible and low-cost components. One of the simple principles for producing airflow is to squeeze an artificial manual breathing unit (AMBU) iterative with grippers, which imitates the motion of human fingers. Unfortunately, the squeezing angle of grippers is not proportional to the exhaust air volume from the AMBU bag. This paper aims to model the AMBU bag by a mathematical equation that enables to implement on a simple controller to operate a bag-valve-mask (BVM) ventilator with high accuracy performance.

This paper provides a curvature function to estimate the air volume exhausting from the AMBU bag. Since the determination of the curvature function is sophisticated, the coefficients of the curvature function are approximated by a quadratic function through the experimental identification method. To obtain the high accuracy performance, a linear regression model and a least square method are employed to investigate the characteristic of the BVM ventilator's grippers angle with respect to the airflow volume produced by the AMBU bag.

This paper investigates the correlation between the exhausting airflow of the AMBU bag and the grippers angle of the BVM ventilator.

The experimental results validated that the regression model of the characteristic of the exhausting airflow of the AMBU bag with respect to the grippers' angle has been fitted with a coefficient over 98% within the range of 350–750 ml.

Allen‐Bradley recently announced a new addition to the company's CVIM vision input module offering. The Allen‐Bradley optical character recognition package, OCR‐PAK, allows the CVIM module to read character strings within an image for product identification.