Vision-Inspection System for Residue Monitoring of Ready-Mixed Concrete Trucks

The objective of this study is to propose a vision-inspection system that improves the quality management for ready-mixed concrete (RMC). The proposed system can serve as an alternative to the current visual inspection method for the detection of residues in agitator drum of RMC truck. To propose the system, concept development and the system-level design should be executed. The design considerations of the system are derived from the hardware properties of RMC truck and the conditions of RMC factory, and then 6 major components of the system are selected in the stage of system level design. The prototype of system was applied to a real RMC plant and tested for verification of its utility and efficiency. It is expected that the proposed system can be employed as a practical means to increase the efficiency of quality management for RMC

Optimizing the Mixing Proportion with Neural Networks Based on Genetic Algorithms for Recycled Aggregate Concrete

This research aims to optimize the mixing proportion of recycled aggregate concrete (RAC) using neural networks (NNs) based on genetic algorithms (GAs) for increasing the use of recycled aggregate (RA). NN and GA were used to predict the compressive strength of the concrete at 28 days. And sensitivity analysis of the NN based on GA was used to find the mixing ratio of RAC. The mixing criteria for RAC were determined and the replacement ratio of RAs was identified. This research reveal that the proposed method, which is NN based on GA, is proper for optimizing appropriate mixing proportion of RAC. Also, this method would help the construction engineers to utilize the recycled aggregate and reduce the concrete waste in construction process

Privacy Protection for Personal Health Device Communication and Healthcare Building Applications

This paper proposes a new method for protecting patient privacy when communicating with a gateway which collects bioinformation through using personal health devices, a type of biosensor for telemedicine, at home and in other buildings. As the suggested method is designed to conform with ISO/IEEE 11073-20601, which is the international standard, interoperability with various health devices was considered. We believe it will be a highly valuable resource for dealing with basic data because it suggests an additional standard for security with the Continua Health Alliance or related international groups in the future

Electronic structures of hexagonal RMnO3 (R = Gd, Tb, Dy, and Ho) thin films

We investigated the electronic structure of multiferroic hexagonal RMnO3 (R = Gd, Tb, Dy, and Ho) thin films using both optical spectroscopy and first-principles calculations. Using artificially stabilized hexagonal RMnO3, we extended the optical spectroscopic studies on the hexagonal multiferroic manganite system. We observed two optical transitions located near 1.7 eV and 2.3 eV, in addition to the predominant absorption above 5 eV. With the help of first-principles calculations, we attribute the low-lying optical absorption peaks to inter-site transitions from the oxygen states hybridized strongly with different Mn orbital symmetries to the Mn 3d3z2-r2 state. As the ionic radius of the rare earth ion increased, the lowest peak showed a systematic increase in its peak position. We explained this systematic change in terms of a flattening of the MnO5 triangular bipyramid

First-time comparison between NO2 vertical columns from GEMS and Pandora measurements

The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV&ndash;visible spectrometer onboard the GEO-KOMPSAT-2B satellite launched into geostationary orbit in February 2020. To evaluate GEMS NO2 column data, comparison was carried out using NO2 vertical column density (VCD) measured using direct-sunlight observations by the Pandora spectrometer system at four sites in Seosan, South Korea, during November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO2 data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7 &times; 1015 molec. cm-2 to 5.5 &times; 1015 molec. cm-2 for cloud fraction (CF) &lt; 0.7. Higher correlation coefficients of 0.62&ndash;0.78 with lower RMSEs from 3.3 &times; 1015 molec. cm-2 to 4.3 &times; 1015 molec. cm-2 were found with CF &lt; 0.3, indicating the higher sensitivity of GEMS to atmospheric NO2 in less-cloudy conditions. Overall, GEMS NO2 column data tend to be lower than those of Pandora due to differences in representative spatial coverage, with a large negative bias under high-CF conditions. With correction for horizontal representativeness in Pandora measurement coverage, the correlation coefficients range from 0.69 to 0.81 with RMSEs from 3.2 &times; 1015 molec. cm-2 to 4.9 &times; 1015 molec. cm-2 were achieved for CF &lt; 0.3, showing the better correlation with the correction than that without the correction.</p

First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements

The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV-visible (UV-Vis) spectrometer on board the GEO-KOMPSAT-2B (Geostationary Korea Multi-Purpose Satellite 2B) satellite launched into a geostationary orbit in February 2020. To evaluate the GEMS NO2 total column data, a comparison was carried out using the NO2 vertical column density (VCD) that measured direct sunlight using the Pandora spectrometer system at four sites in Seosan, South Korea, from November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO2 data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7×1015 to 5.5×1015 molec. cm−2 for a cloud fraction (CF) &lt;0.7. Higher correlation coefficients of 0.62–0.78 with lower RMSEs from 3.3×1015 to 5.0×1015 molec. cm−2 were found with CF &lt;0.3, indicating the higher sensitivity of GEMS to atmospheric NO2 in less cloudy conditions. Overall, the GEMS NO2 total column data tended to be lower than the Pandora data, owing to differences in the representative spatial coverage, with a large negative bias under high CF conditions. With a correction for horizontal representativeness in the Pandora measurement coverage, correlation coefficients ranging from 0.69 to 0.81, with RMSEs from 3.2×1015 to 4.9×1015 molec. cm−2, were achieved for CF &lt;0.3, showing a better correlation with the correction than without the correction.</p

Implementation of Personal Health Device Communication Protocol Applying ISO/IEEE 11073-20601

In 2010, IEEE and ISO announced the exchange protocol standard (ISO/IEEE 11073-20601), optimized to secure mutual compatibility between all sorts of PHDs and the gateways for collecting bioinformation from the devices and activating related services. This international standard is the first official document that has dealt with communication related to the healthcare device. This paper is about implementing communication protocols between a weight sensor, a kind of personal health devices (PHDs) used in homes, and a gateway collecting a variety of biometric information from multiple sensors, applying international standard ISO/IEEE 11073-20601 for interoperability between medical devices. Moreover, security is enhanced by applying the international symmetric key encryption standard, advanced encryption standard (AES), for secure data transmission from the weight sensor to gateway. When the cipher algorithm was applied, we confirmed that the implementation took about 0.008 second on average than the previous