A Disturbance Suppression Micro-Newton Force Sensor Based on Shadow Method

<div>The precision of micro-force measurement is determined by the sensitivity of force sensors and the magnitude of environmental disturbances. Damping, a process that converts vibrational energy into heat, is one of the most effective methods of suppressing disturbances. Inspired by the shadow formed at a pond when water striders walked on the water, a bionic viscoelastic-polymer micro-force (VPMF) sensor with a high damping ratio based on the shadow method was developed. In the VPMF sensor, the surface of the polymer was deformed by the contact of a cylindrical flat punch when the sensor was subjected to a normal force. A shadow with a bright edge was formed due to the refraction that parallel light went through the deformed surface. The force was in proportion to the change of the shadow diameter. The sensor optimal sensitivity was 2.15 μN/pixel and the measurement range was 0.981 mN. The damping ratio of the VPMF sensor was 0.22 on account of viscoelasticity, which could suppress disturbances effectively. The VPMF sensor could reduce the influence of disturbances by about 96.23% compared to the cantilever. The present study suggests that the VPMF sensor is hopefully applied to the reliable measurement of micro force under complex environments.</div>

A Disturbance Suppression Micro-Newton Force Sensor Based on Shadow Method

<div>The precision of micro-force measurement is determined by the sensitivity of force sensors and the magnitude of environmental disturbances. Damping, a process that converts vibrational energy into heat, is one of the most effective methods of suppressing disturbances. Inspired by the shadow formed at a pond when water striders walked on the water, a bionic viscoelastic-polymer micro-force (VPMF) sensor with a high damping ratio based on the shadow method was developed. In the VPMF sensor, the surface of the polymer was deformed by the contact of a cylindrical flat punch when the sensor was subjected to a normal force. A shadow with a bright edge was formed due to the refraction that parallel light went through the deformed surface. The force was in proportion to the change of the shadow diameter. The sensor optimal sensitivity was 2.15 μN/pixel and the measurement range was 0.981 mN. The damping ratio of the VPMF sensor was 0.22 on account of viscoelasticity, which could suppress disturbances effectively. The VPMF sensor could reduce the influence of disturbances by about 96.23% compared to the cantilever. The present study suggests that the VPMF sensor is hopefully applied to the reliable measurement of micro force under complex environments.</div>

Development of Car Tyre Air Pressure System (CTAPMS) Using Node MCU ESP8266 Board

CTAPMS is an electronic system designed in this work to monitor the air pressure inside pneumatic tyres on various types of vehicles. A crucial issue in monitoring air pressures of a tyre was most users are too lazy and do not check their car tyre condition daily or before starting a journey. As an assist device for the user to monitor their car air tyre pressure daily, this project has developed the CTAPMS using a BMP180 sensor and Node MCU 8266 microcontroller board. Based on the system, the measured car air tyre pressure can be visualized from the ThingSpeak IoT platform through a smartphone. The performance of the developed system has been validated through a series of experimental works. The result indicates a reliable measurement with an error of less than 10% as compare to the existing system. Further, this product will be commercialized for future use.

Application of Electrical Tomography Imaging Using Machine Learning Methods for the Monitoring of Flood Embankments Leaks

This paper presents an application for the monitoring of leaks in flood embankments by reconstructing images in electrical tomography using logistic regression machine learning methods with elastic net regularisation, PCA and wave preprocessing. The main advantage of this solution is to obtain a more accurate spatial conductivity distribution inside the studied object. The described method assumes a learning system consisting of multiple equations working in parallel, where each equation creates a single point in the output image. This enables the efficient reconstruction of spatial images. The research focused on preparing, developing, and comparing algorithms and models for data analysis and reconstruction using a proprietary electrical tomography solution. A reliable measurement solution with sensors and machine learning methods makes it possible to analyse damage and leaks, leading to effective information and the eventual prevention of risks. The applied methods enable the improved resolution of the reconstructed images and the possibility to obtain them in real-time, which is their distinguishing feature compared to other methods. The use of electrical tomography in combination with specific methods for image reconstruction allows for an accurate spatial assessment of leaks and damage to dikes.

Survey Attention and Self-Reported Political Behavior

Survey research methodology is evolving rapidly, as new technologies provide new opportunities. One of the areas of innovation regards the development of online interview best practices, and the advancement of methods that allow researchers to measure the attention that subjects are devoting to the survey task. Reliable measurement of subject attention can yield important information about the quality of the survey response. In this paper, we take advantage of an innovative survey we conducted in 2018, in which we directly connect survey responses to administrative data, allowing us to directly assess the association between survey attention and response quality. We show that attentive survey subjects are more likely to provide accurate survey responses regarding a number of behaviors and attributes that we can validate with our administrative data. The best strategy to deal with inattentive respondents, however, depends on the correlation between respondent attention and the outcome of interest.

Method for determining uncertainty and error in the process of ophthalmic lens calibration

In the present investigation, a scientific procedure was developed, and a mathematical model was proposed, with the objective of determining, under standard conditions, the uncertainty, and the measurement of dioptric power in ophthalmic lenses. The methodology of the scientific procedure is based on the fundamentals of geometric optics, this process guarantees and establishes a standardized uncertainty measure in repeatable and reproducible processes. The methodology is complemented with a proposed mathematical model based on the guide for the expression of uncertainty in measurement - GUM. This model can be applied to lenses used for calibrating eye care equipment (such as lensometers, which are used to diagnose myopia and farsightedness) by evaluating the lenses without having direct contact with patients. When the proposed mathematical model was applied, its experimental result was a maximum expanded uncertainty of ± 0.0079 diopters in a 0.5-diopter lens. This is optimal compared to the result of other authors this article, who reported a maximum expanded uncertainty of ± 0.0086 diopters. In conclusion, the application of this scientific procedure provides manufacturers and users of this type of lenses with a reliable measurement thanks to a calibration process based on geometrical optics and centered on patient safety.

Nature Interest Scale – Development and Evaluation of a Measurement Instrument for Individual Interest in Nature

Interest is an important factor for successful learning that has been the subject of intensive research for decades. Although interest in nature is of great importance for environmental education, to date there is no valid and reliable measurement tool. Therefore, the purpose of this study was to develop and test a scale for interest in nature, the Nature Interest Scale (NIS). In study 1, nine items were selected based on the three dimensions of the psychological interest construct to represent interest in nature. The factor structure of this new measurement instrument, was tested using confirmatory factor analyses. The results show that the instrument represents the three dimensions of the interest construct well. In study 2 the validity (discriminant and convergent validity) as well as the reliability (internal consistency, composite reliability, test-retest reliability) of the NIS were demonstrated. In study 3, the applicability of the NIS was tested with a different target group, students with learning disabilities. The results of this factor analysis also confirm the factor structure of the scale. Thus, this study provides a valid and reliable measurement tool for individual interest in nature that can be used for future research.

T-DSES: A Blockchain-powered Trusted Decentralized Service Eco-System

Existing Web service eco-systems are typically managed in a centralized manner, which hinders their further development due to inherent disadvantages such as trust issues, interest disputes, value separation and so on. The recently emerged blockchains provide distributed ledgers that enable parties who do not fully trust each other to maintain a set of global states, which provide a natural solution. Based on the INKchain, which is an open-source permissioned blockchain mechanism extending the Hyperledger Fabric, this paper proposes Trusted Decentralized Service Eco-System (T-DSES). T-DSES achieves not only fundamental functionalities of conventional systems, but also offers mechanisms to stimulate participants to bring trustworthiness to the whole system. The trustworthiness of T-DSES is realized by three strategies: reliable information of services and mashups, reliable records of participants’ rights, and reliable measurement of participants’ contributions. A customized token “SToken” is created to act as the media of value circulation. In this paper, the overall framework and detailed design of T-DSES are presented, especially including how to utilize Kubernetes to establish a cloud-based environment. A tailored Web front-end ensures the usability of operations. Over real-world data from ProgrammableWeb.com, analyses and experiments have been conducted to verify the feasibility and effectiveness of the presented approach.

Novel Measurement Approaches Are Needed In The Pre-Hospital Setting To Prevent Accidental Hypothermia.

Accidental hypothermia can be fatal if not recognised early, and effective management relies on the accurate recording of core body temperature. The focus of this critique - a recent study by Podsiado et al. (2019) – highlighted the need for reliable measurement of core body temperature in the pre-hospital and austere setting. An esophageal temperature probe may prove to be a reliable, and best practice approach for measuring core body temperature in critically unwell, unconscious patients suffering accidental hypothermia.