Surface Reflectance Research Articles

Metamaterial-based Artificial magnetic conductor for efficient breast cancer diagnosis using a low-cost antenna array.

Breast cancer is the most common malignancy in women globally, stemming from gene mutations that prompt irregular cellular growth and subsequent tumor development. Early-stage detection of cancer cells results in a remarkable 99% survival rate. This research presents a microwave imaging technique for the non-invasive identification of tumors in the initial stages within the women's breast. A low-cost antenna array with an Artificial Magnetic Conductor (AMC) is proposed, featuring a compact structure size of 37.2 37.2 mm . The AMC, a metamaterial, acts as a reflective surface to enhance frequency selectivity, specifically at 8.48 GHz. The maximum gains reached 9.35 dBi in simulated results and 10.51 dBi in measured results. The fabricated antenna validates the simulated findings, and its operational efficiency has undergone experimental validation. Moreover, fidelity factors in face-to-face (FtF) and side-by-side (SbS) scenarios are delineated. The antenna, operating as a transceiver, is applied to a modeled breast phantom across five distinct cases for numerical simulations pertaining to cancer cell detection applications. The outcomes of this research bear considerable implications for advancing early-stage breast cancer detection methodologies.

Assessment of Tube–Fin Contact Materials in Heat Exchangers: Guidelines for Simulation and Experiments

This paper describes experiments on finned tube heat exchangers, focusing on reducing the thermal contact resistance at the contact between the pipe and the lamella. Various contact materials, such as solders and adhesives, were investigated. Several methods of establishing contact were tested, including blowtorch soldering, brazing, and furnace soldering. Thermal camera measurements were carried out to assess the performance of the contact materials. Moreover, finite element analysis was performed to evaluate the contact materials and establish guidelines in the fin–tube connection modeling by comparing simplified models with the realistic model. Blowtorch brazing tests were successful while soldering attempts failed. During the thermographic measurements, reflective surfaces could be measured after applying a thin layer of paint with high emissivity. These measurements did not provide valuable results; thus, the contact materials were assessed using a finite element analysis. The results from the finite element analysis showed that all the inspected contact materials provided better heat transfer than not using a contact material. The heat transfer rate of the tight-fit realistic model was found to be 33.65 for air and 34.9 for the Zn-22Al contact material. This finding could be utilized in developing heat exchangers with higher heat transfer with the same size.

Designing mouthwash formulations with innovative molecular components to control initial dental erosion in vivo.

This study aimed to examine and compare the efficacy of mouthwashes containing different proteins and peptide on the prevention of enamel erosion in vivo, as well as to evaluate the participants' satisfaction with the formulations. Twelve participants were selected and underwent five cross-over mouthwash phases: Water (control); 0.1mg/mL CaneCPI-5; 0.5mg/mL MaquiCPI-3; 0.1mg/mL CsinCPI-2; and 0.037mg/mL Stn15pSpS. After prophylaxis, the participants rinsed (1min), followed by the acquired enamel pellicle (AEP) formation (2h). An erosive challenge was made (biopsy, citric acid 1%, 15s) on the buccal surface of the central maxillary incisors. The Relative Surface Reflection Intensity (%SRI) was assessed and analyzed by ANOVA/Tukey's tests. The calcium release in acid was measured by the Arsenazo method and verified by Kruskal-Wallis/Dunn's tests. The Spearman's correlation was used between analyses. A questionnaire evaluated the satisfaction of participants. For both analyses, the results showed that mouthwashes containing the proteins or peptide were significantly more effective in preventing enamel erosion compared to deionized water, with no significant differences among the active ingredients (p < 0.05). Also, there was a significant negative correlation between %SRI and calcium released (r=-0.5754). The questionnaire revealed that the volunteers were satisfied with the taste of the products. In addition, the experimental procedures were well tolerable, and no side effects were reported. All mouthwashes containing proteins or peptide were acceptable and effective in protecting enamel against initial dental erosion in vivo. This study highlights the potential of these pioneer organic components for the development of mouthwashes designed for people with risk of erosive tooth wear.

Three-dimensional reconstruction of a light field based on phase restoration for highly reflective surfaces

This paper proposes, a novel, to our knowledge, phase-restoration-based light field method to achieve 3D reconstruction of highly reflective surfaces. First, a focused light field camera whose angular and spatial resolutions can be adjusted according to the needs has been designed and fabricated to capture 4D light field information. Then, according to the pixel offsets between different sub-aperture images, a phase restoration method based on multi-view complementary information is proposed to restore the missing absolute phase information caused by highlights. Finally, a cubic B-spline curve method is used to directly fit the relationship between absolute phase and coordinates to achieve 3D reconstruction of highly reflective surfaces. The experimental results demonstrate that the proposed method effectively utilizes the multi-view information from the light field to restore missing absolute phase data in the phase unwrapping, ensuring accurate 3D reconstruction of highly reflective surfaces. What is more, our method requires no additional hardware, camera angle calibration, or point cloud fusion, which significantly reduces both hardware complexity and computational demands.

Research on the Method of Depth-Sensing Optical System Based on Multi-Layer Interface Reflection

In this paper, a depth-sensing method employing active irradiation of a semi-annular beam is proposed for observing the multi-layered reflective surfaces of transparent samples with higher resolutions and lower interference. To obtain the focusing resolution of the semi-annular aperture diaphragm system, a model for computing the diffracted optical energy distribution of an asymmetric aperture diaphragm is constructed, and mathematical formulas are deduced for determining the system resolution based on the position of the first dark ring of the amplitude distribution. Optical simulations were performed under specific conditions; the lateral resolution δr of the depth-sensing system was determined to be 0.68 μm, and the focusing accuracy δz was determined to be 0.60 μm. An experimental platform was established under the same conditions, and the results were in accord with those of the simulation results, which validated the correctness of the formula for calculating the amplitude distribution of the diffracted light from the asymmetric aperture diaphragm.

Buildings in Hot Climate Zones—Quantification of Energy and CO2 Reduction Potential for Different Architecture and Building Services Measures

Reducing energy and associated greenhouse gas emissions in buildings is one of the key aspects of climate change on a global level. To put the building sector on a low carbon development path, policies and adequate financing play a crucial role in each region. In the global South, policies and regulations related to the decarbonization of the building stock are increasingly being implemented. For policy and decision makers, adequate data on the status quo of the building stock, as well as the quantification of energy reduction measures, are essential to make informed decisions on the building regulatory and funding framework. The objective of this study is to provide data-driven insights into the potential for energy and CO2 reduction in buildings across various hot climate zones in the Global South. A simulation-based approach was employed to model five different building types, ranging from residential homes to office buildings, under a variety of architectural and building services scenarios. The simulations were conducted using the dynamic building energy simulation tool EnergyPlus, which assessed the impact of various energy-saving measures under both current and projected future climate conditions. This study concludes that optimizing passive design features, such as improved windows, solar shading, and reflective surfaces, in conjunction with active systems like decentralized cooling units and renewable energy integration, can result in a notable reduction in energy demand and emissions. Our findings provide a robust basis for policymakers to develop targeted energy efficiency strategies for buildings in hot climate zones, which will play a crucial role in achieving climate goals in the Global South.

Evaluation of Himawari-8/AHI land surface reflectance at mid-latitudes using LEO sensors with off-nadir observation

Land-surface reflectance (LSR) is a basic physical retrieval in terrestrial monitoring. The potential for high-frequency surface product estimation was evident in third-generation Geostationary Earth Orbit (3rd-GEO) satellites, substantially improving spectral, spatial, and temporal resolutions. Intercomparisons with LSR products from Low Earth Orbit (LEO) satellites have been employed as a common way to evaluate the LSRs of GEO satellites. However, in mid-latitude regions, comparing the LSR between two satellites is challenging due to constraints in the sun–target–sensor geometries. In this study, we proposed a method to obtain observations with consistent viewing and illumination conditions aligned with those of the Himawari-8/Advanced Himawari Imager (AHI) at mid-latitudes, by utilizing forward and backward viewing cameras from LEO sensors, such as Terra/Multi-angle Imaging SpectroRadiometer (MISR). The reflectance intercomparison revealed that the estimated AHI LSR closely matched the LSR from MISR in the red and near-infrared (NIR) bands at latitudes higher than 30°N/S during 2018–2019, with correlation coefficient (r) greater than 0.8 and a relative root mean square error (RRMSE) below 25 %. The data accuracy in the NIR bands was higher than in the red band, as indicated by a lower RRMSE. The correlation was also stronger in non-forested regions compared to forested areas, with higher r values. Additionally, screening observation pairs based on the relative azimuth angle (RAA), which assumes rotational symmetry in LSR, was examined and proved effective for GEO–LEO intercomparisons. This RAA-matching criterion enables reflectance intercomparisons across a wide longitude range at mid-latitudes, including areas like mainland China and New Zealand, where ray-matching is not applicable. The reflectance consistency demonstrated by RAA matches was comparable to that of ray matches, although the RAA-matching is constrained by timing due to the solar location. The findings from this study have potential applications for other satellites.

Custom chromatic confocal microscope for surface profilometry

In this work, a surface profiling system is introduced, employing a custom-designed chromatic confocal (CC) distance sensor. Today’s commercial sensors based on the CC principle have a major drawback of effectively coupling light from the illumination source into the optical imaging system, mainly due to etendue mismatch. Consequently, a substantial amount of light is lost, significantly reducing the overall SNR of the system. This limitation restricts its applicability primarily to highly reflective surfaces. To address this issue, an etendue-matched optical system is proposed, that incorporates an innovative superluminescent light source. Through this approach, the system achieves 4 orders of magnitudes higher illumination intensity concentrated within the focus spot compared to existing devices in the current market.

Multi-task deep learning for quantifying methane emissions from 2-D plume imagery with Low Signal-to-Noise Ratio

ABSTRACT Methane is the second most significant greenhouse gas after carbon dioxide. As global warming intensifies, the quantification of methane point sources is becoming increasingly crucial. However, retrieving high-quality methane signals from remote sensing data remains challenging due to various factors, including surface reflectance, atmospheric interference, sensor noise, wind speed, and sensor sensitivity. In real-world scenarios, methane remote sensing quantification often encounters unfavourable conditions that lead to low signal-to-noise ratio (SNR) signals, resulting in reduced quantification accuracy. To address these challenges, we introduce a novel multi-task learning-based approach. Specifically, we incorporate a denoising auxiliary task into the quantification network by introducing an additional denoising branch that recovers clean plume column concentration maps. The network is trained with supervision using both denoising and quantification losses, which enables it to acquire robust feature representations to noise and benefits the quantification of low SNR images. During the inference phase, the denoising branch is removed, resulting in an efficient and robust single quantification network with reduced inferring time, supporting onboard computation. We construct a low SNR database based on the AVIRIS-NG sensor and evaluate the generalization ability of our method. DQNet achieves the highest RMSE, MAPE, and R of 16.478 kg/h, 15.296%, and 95.167% respectively on the synthetic dataset. Across the entire range of SNR, DQNet exhibits a greater relative advantage as SNR decreases. However, our approach is not limited to AVIRIS-NG and can be easily extended to various multispectral and hyperspectral satellites.

Research on Airborne Ground-Penetrating Radar Imaging Technology in Complex Terrain

The integration of ground-penetrating radar (GPR) with unmanned aerial vehicles (UAVs) enables efficient non-contact detection, performing exceptionally well in complex terrains and extreme environments. However, challenges in data processing and interpretation remain significant obstacles to fully utilizing this technology. To mitigate the effects of numerical dispersion, this paper develops a high-order finite-difference time-domain (FDTD(2,4)) three-dimensional code suitable for airborne GPR numerical simulations. The simulation results are compared with traditional FDTD methods, validating the accuracy of the proposed approach. Additionally, a Kirchhoff migration algorithm that considers the influence of the air layer is developed for airborne GPR. Different processing strategies are applied to flat and undulating terrain models, significantly improving the identification of shallowly buried targets. Particularly under undulating terrain conditions, the energy ratio method is introduced, effectively suppressing the interference of surface reflections caused by terrain variations. This innovative approach offers a new technical pathway for efficient GPR data processing in complex terrains. The study provides new insights and methods for the practical application of airborne GPR.

An Experimental Study on the Effect of Nano Zinc Oxide on Reflective Coatings and Building Roof Temperatures

Most roofs on Earth are made of dark materials. Dark roof surfaces can retain heat better than light ones; in Iraq, summer time temperatures on the roofs of dark buildings reached 70–80 degrees Celsius in July and August. The effects of this temperature rise are detrimental to cooling and energy consumption. To lessen heat transfer into the building, use reflective surfaces that can reflect infrared radiation waves. Cool roofs have both short-term and long-term advantages. They can reduce a building's annual air conditioning energy consumption by up to 15%, extend the life of the roof and its service life, improve the energy efficiency of roofs particularly those with inadequate insulation at the front of the roof improve thermal comfort in buildings without air conditioning, and lower greenhouse gas emissions and air pollution. Solar heat is one of the main factors affecting the durability of roofing membranes, according to research and real-world experience with the deterioration of these materials over time. High solar reflectance materials can reflect more sunlight and maintain their coolness in the sun. This study examines a low-cost composite cool coating that uses 60% calcium carbonate and demonstrates a 15°C drop in surface concrete temperature for roof buildings when compared to an uncoated surface. Additionally, compared to 30%wt CaCO3, the effect of 60%CaCO3 in composite coating reduces adhesion strength. According to the study, the weight of CaCO3 in the composite coating increases while adhesion strength, surface roughness, and particle homogeneity distribution decrease. Conversely, the maximum weight of CaCO360% weight percent exhibits good IR reflectance and less tribological properties. While preserving good infrared reflectance, adding 10% ZnO to the coating solution (60% CaCO3/PVac) improves tribological properties. The adhesion strength of the 60% calcium carbonate polymer composite paint increased from 10.9 MPa to 40.2 MPa when the nanomaterial was present, while this material maintained the superior optical qualities of infrared reflection. The coefficient of thermal expansion varies between concrete and coating solutions. For instance, the coating that has 10% weight added ZnO has a peel resistance coefficient of 8*10-6 1/K. The 60%CaCO3/10%ZnO/PVac coating effectively lowers the temperature by 15–12 °C when applied to a building roof.

Investigation of impact of community environment factors on the residents’ visiting rate to outdoor venues in South China

Understanding the activity patterns of urban residents is crucial for urban community design and urban energy forecasting. Predicting the visitation rates of different types of locations is a important issue because urban residents can only be in one place at a time. Achieving accurate predictions of outdoor public space visitation rates is equivalent to predicting the upper limit of the number of visitors to other buildings. Previous similar studies usually rely on survey methods such as questionnaires and GPS positioning. These methods have some drawbacks, such as small sample sizes and inaccurate data. In this paper, we used mobile signaling to investigate the park visit rates of residents in different communities in Guangzhou. In accordance with Chinese tradition, we define a community as a residential community, which consists of multiple residential units and a set of basic service facilities and management structures that are sufficient to meet the daily needs of residents. We found that the park visit rate of a community is closely related to the characteristics of the community itself. The park visit rate is positively correlated with the average LST (land surface temperature) of the communities, the average distance between the community and the large park, and the building coverage rate, while it is negatively correlated with the vegetation coverage rate, the average surface reflection rate, the convenience of transportation, and the per capita green space area. Given the different travel habits of urban residents on weekdays and weekends, we also used multiple linear regression to establish prediction models for community park visitation rates on weekdays and weekends.

Structurally Colored Photonic Crystal Biomimetic Microstructures for Daytime Radiative Cooling.

Daytime radiative cooling offers a novel solution to the energy crisis, enabling green and efficient thermal management in space. High reflectance in the solar spectrum is essential for passive radiative cooling, rendering dye coloring and similar methods unsuitable for colored coolers. This paper presents a structurally colored photonic crystal biomimetic microstructured radiative cooler. Inspired by natural biological systems, this cooler features a dual-layered microtruncated-cone array structure on the surface and bottom membrane layers. The silver reflector and 3D micrograting surface structure produce continuous iridescent colors through multiple interference effects. Optimized lithographic process enable the fabrication of the ordered dual-layer surface microstructure arrays with precise angular combinations. The dual-layered microtruncated-cone introduces a gradient refractive index, reducing impedance mismatch at the interface. As a result, the radiative cooler achieves high solar spectral reflectance (0.95) and high mid-infrared emissivity (0.95). Notably, the net theoretical cooling power and the subambient temperature drop are 106.9 W m-2 and 7.4 °C, respectively, at an ambient temperature of 40 °C, with a measured average temperature reduction of 6.1 °C under direct sunlight. This performance matches that of advanced radiative coolers, striking a balance between aesthetics and radiative cooling capability.

Investigation on the integrated characteristics of n-decane/air rotating detonation combustor and supersonic turbine

In this study, the two-dimensional numerical simulations are conducted to study the flow field characteristics, turbine performance and loss mechanism of integrated system of rotating detonation combustor and supersonic turbine under two different directions of detonation wave propagation. The results indicate that the propagation direction of RDW affects the incident angle between OSW and guide vanes, resulting in different operating modes for aligned and unaligned modes. OSW in the turbine cascade undergoes the leading-edge shock, blade surface reflection and trailing edge diffraction. The backward-propagating rake-type shock envelope is formed due to leading-edge shock of the rotor. In misaligned mode, the stator has higher damping of both pressure and temperature. The stator significantly improves the circumferential uniformity of both velocity and pressure, particularly when operating in aligned mode. The total pressure loss in aligned mode is less, therefore the turbine achieves higher rim work and efficiency. The viscosity is one of the main sources of loss in the flow field. The reflected shock waves at the leading edge of the rotor and in the stator cascade are the primary factors contributing to the leading-edge vortices on the stator vanes.

Machine vision-based detection of surface defects in cylindrical battery cases

Automotive 21700 series lithium batteries are prone to surface defects during production and transportation, thus affecting their performance, so we propose a full-surface defect detection method for battery cases based on the synthesis of traditional image processing and deep learning to address this problem. First, the mechanism of surface defects on a battery case is analysed, and the types of surface defects are summarized. A suitable platform for image acquisition is designed for the severely reflective surface. Since there is no publicly available defect dataset for cylindrical battery cases, a defect dataset is established, and the dataset is augmented and expanded via the traditional method and the ACGAN model. For the defects on the top of the battery case, a traditional image processing algorithm is used to combine the roundness and the area of the area pixels to make a comprehensive judgement. For the defects on the bottom and side of the battery case, after comparing and analysing a variety of deep learning networks, the YOLOv7 model is selected to address the data characteristics of the large experimental inputs and the small targeted defects. To improve the accuracy of the model to meet the needs of real-time detection in industry, the CA attention mechanism, the DYHEAD dynamic detector head, and the slicing-assisted super inference (SAHI) method are used, with a final map accuracy reaching 98.1 %, which is 2.7 % higher than that of the initial model. Compared with mainstream target detection algorithms, the algorithm in this paper has good detection performance for cylindrical battery case defect detection and can be better applied to real-time detection in industry.

A Wideband High-Gain Multilinear Polarization-Reconfigurable Antenna Integrated With Nonuniform Partially Reflective Surface

A Wideband High-Gain Multilinear Polarization-Reconfigurable Antenna Integrated With Nonuniform Partially Reflective Surface

Optimum Beamforming and Grating-Lobe Mitigation for Intelligent Reflecting Surfaces

Optimum Beamforming and Grating-Lobe Mitigation for Intelligent Reflecting Surfaces

Cost-Effective Dust Detection on Solar PV Panels through Deep Learning: A Step towards Automated Maintenance Systems

Abstract: Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy it produces. Detecting and mitigating dust accumulation is therefore crucial for optimizing solar energy production. While various techniques exist for detecting dust to schedule cleaning, many of these methods uses licensed software like MATLAB, which can be financially burdensome. This study proposes the use of modified pre-trained ResNet-50 model architecture with an adjusted fully connected layer for binary classification. An experimental setup was installed utilizing a single 75 Wp panel with an inclination maintained at 30-degree angle. The fine dirt particles were artificially introduced and datasets of images of clean and dusty panels were collected from five different sides were taken, to compensate for the surface reflectance from the PV panel due to camera angles. Those datasets were used to train and test the model and the accuracy achieved was 90%. The model's ability to detect dust with minimal false positives ensures more efficient maintenance scheduling. This research demonstrates the potential of AI-driven dust detection systems to enhance the operational efficiency of solar PV installations.

Evaluation of Surface Reflectance and Vegetation Indices Measured by Sentinel-2 Satellite Using Drone Considering Crop Type and Surface Heterogeneity

Evaluation of Surface Reflectance and Vegetation Indices Measured by Sentinel-2 Satellite Using Drone Considering Crop Type and Surface Heterogeneity

Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements

Abstract. Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation in important air pollutants such as nitrogen dioxide (NO2). The South Korean instrument GEMS (Geostationary Environmental Monitoring Spectrometer), launched in February 2020, is the first geostationary instrument that is able to observe the diurnal variation in NO2. The measurements have a spatial resolution of 3.5 km × 8 km and cover a large part of Asia. This study compares 1 year of tropospheric NO2 vertical column density (VCD) observations from the operational GEMS L2 product, the scientific GEMS IUP-UB (Institute of Environmental Physics at the University of Bremen) product, the operational TROPOspheric Monitoring Instrument (TROPOMI) product, and ground-based differential optical absorption spectroscopy (DOAS) measurements in South Korea. The GEMS L2 tropospheric NO2 VCDs overestimate the ground-based tropospheric NO2 VCDs with a median relative difference of +61 % and a correlation coefficient of 0.76. The median relative difference is −2 % for the GEMS IUP-UB product and −16 % for the TROPOMI product, with correlation coefficients of 0.83 and 0.89, respectively. The scatter in the GEMS products can be reduced when observations are limited to the TROPOMI overpass time. Diurnal variations in tropospheric NO2 VCDs differ by the pollution level of the analyzed site but with good agreement between the GEMS IUP-UB and ground-based observations. Low-pollution sites show weak or almost no diurnal variation. In summer, the polluted sites show a minimum around noon, indicating the large influence of photochemical loss. Most variation is seen in spring and autumn, with increasing NO2 in the morning, a maximum close to noon, and a decrease towards the afternoon. Winter observations show rather flat or slightly decreasing NO2 throughout the day. Winter observations under low-wind-speed conditions at high-pollution sites show enhancements of NO2 throughout the day. This indicates that under calm conditions, dilution and the less effective chemical loss in winter do not balance the accumulating emissions. Diurnal variation observed at a low-pollution site follows seasonal wind patterns. A weekday–weekend effect analysis shows good agreement between the different products. However, the GEMS L2 product, while agreeing with the other data sets on weekdays, shows significantly less reduction on weekends. The influence of the stratospheric contribution and the surface reflectivity product on the satellite tropospheric NO2 VCD products is investigated. While the TM5 model's stratospheric VCDs, used in the TROPOMI product, are too high, resulting in tropospheric NO2 VCDs that are too low and even negative, when used in the GEMS IUP-UB retrieval, the GEMS L2 stratospheric VCD is too low. Surface reflectivity comparisons indicate that the GEMS L2 reflectivity makes a large contribution to the observed overestimation and scatter.