Search Results (7)

Cover crop mixes play an important role in enhancing soil health, nutrient turnover, and ecosystem resilience; yet, maintaining even seed dispersion and planting uniformity is difficult due to significant variances in seed physical and aerodynamic properties. These discrepancies produce non-uniform seeding and species separation in drill hoppers, which has an impact on stand establishment and biomass stability. The thousand-grain weight is an important measure for determining cover crop seed quality and yield since it represents the weight of 1000 seeds in grams. Accurate seed counting is thus a key factor in calculating thousand-grain weight. Accurate mixed-seed identification is also helpful in breeding, phenotypic assessment, and the detection of moldy or damaged grains. However, in real-world conditions, the overlap and thickness of adhesion of mixed seeds make precise counting difficult, necessitating current research into powerful seed detection. This study addresses these issues by integrating deep learning-based computer vision algorithms for multi-seed detection and counting in cover crop mixes. The Canon LP-E6N R6 5D Mark IV camera was used to capture high-resolution photos of flax, hairy vetch, red clover, radish, and rye seeds. The dataset was annotated, augmented, and preprocessed on RoboFlow, split into train, validation, and test splits. Two top models, YOLOv5 and YOLOv7, were tested for multi-seed detection accuracy. The results showed that YOLOv7 outperformed YOLOv5 with 98.5% accuracy, 98.7% recall, and a mean Average Precision (mAP 0–95) of 76.0%. The results show that deep learning-based models can accurately recognize and count mixed seeds using automated methods, which has practical applications in seed drill calibration, thousand-grain weight estimation, and fair cover crop establishment. Full article

Urban green spaces (UGSs) play a significant role in promoting public health by facilitating outdoor activities, but issues of spatial and socioeconomic inequality within UGSs have drawn increasing attention. However, current methods for assessing UGS inequality still face challenges such as data acquisition difficulties and low identification accuracy. Taking Harbin as a case study, this research employs various advanced technologies, including Python data scraping, drone imagery collection, and Amap API, to gather a diverse range of data on UGSs, including photos, high-resolution images, and AOI boundaries. Firstly, elements related to physical activity within UGSs are integrated into a supply adjustment index (SAI), based on which UGSs are classified into three categories. Then, a supply–demand improved two-step floating catchment area (SD2SFCA) method is employed to more accurately measure the accessibility of these three types of UGSs. Finally, using multiple linear regression analysis and Mann–Whitney U tests, socioeconomic inequalities in UGS accessibility are explored. The results indicate that (1) significant differentiation exists in the types of UGS services available in various urban areas, with a severe lack of small-scale, low-supply UGSs; (2) accessibility of all types of UGSs is significantly positively associated with housing prices, with higher-priced areas demonstrating notably higher accessibility compared to lower-priced ones; (3) children may be at a disadvantage in accessing UGSs with medium-supply levels. Future planning efforts need to enhance attention to vulnerable groups. This study underscores the importance of considering different types of UGSs in inequality assessments and proposes a method that could serve as a valuable tool for accurately assessing UGS inequality. Full article

This study focuses on enhancing the tunable sensitivity of a photo irradiance sensor (PIS) operating in the near-ultraviolet to visible to near-infrared (NUV-VIS-NIR) spectrum using an indium tin oxide-aluminum oxide-zirconia aluminum oxide-silicon oxide-silicon capacitor (hereafter IAZAOS). Unlike other PIS designs such as reverse-biased metal–insulator–semiconductor (MIS) and tunneling MIS, the IAZAOS PIS measures changes in inversion capacitance under strong forward bias with light irradiation. The IAZAOS PIS offers several key advantages over alternative designs. It exhibits high sensitivity, weak bias dependence, low dark current, tunable sensitivity, low power consumption, CMOS process compatibility, simple low-cost manufacturing, and good gate oxide reliability. Under 1 mW/cm² irradiation at 1 kHz, the inversion carrier concentration reaches approximately 70% saturation. The resolution achieved is 10 nW/cm² at 1 kHz, with a sensing range spanning from 10 nW/cm² to 1 W/cm² across frequencies from 1 kHz to 100 kHz. These performance characteristics surpass those reported for other PIS technologies. Furthermore, the IAZAOS PIS demonstrates a quantum efficiency of about 60% at 405 nm, which surpasses the quantum efficiency of general silicon-based p(i)n diodes. Post-deposition annealing techniques are employed to enhance the sensor’s performance. Dielectric annealing improves the ZrAlO_x interface trap and permittivity properties, while conducting oxide annealing enhances indium tin oxide transmission and resistivity. The combination of these treatments results in a high-speed, high-sensitivity, high-resolution, and reliable NUV-VIS-NIR sensing capability for the IAZAOS capacitor-based PIS. Full article

In recent years, the most popular methods for determining coastline course are geodetic, satellite, and tacheometric techniques. None of the above-mentioned measurement methods allows marking out the shoreline both in an accurate way and with high coverage of the terrain with surveys. For this reason, intensive works are currently underway to find alternative solutions that could accurately, extensively, and quickly determine coastline course. Based on a review of the literature regarding shoreline measurements, it can be concluded that the photogrammetric method, based on low-altitude images taken by an Unmanned Aerial Vehicle (UAV), has the greatest potential. The aim of this publication is to present and validate a method for determining coastline course based on low-altitude photos taken by a drone. Shoreline measurements were carried out using the DJI Matrice 300 RTK UAV in the coastal zone at the public beach in Gdynia (Poland) in 2023. In addition, the coastline course was marked out using high-resolution satellite imagery (0.3–0.5 m). In order to calculate the accuracy of determining the shoreline by photogrammetric and satellite methods, it was decided to relate them to the coastline marked out using a Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) receiver with an accuracy of 2.4 cm Distance Root Mean Square (DRMS). Studies have shown that accuracies of determining coastline course using a UAV are 0.47 m (p = 0.95) for the orthophotomosaic method and 0.70 m (p = 0.95) for the Digital Surface Model (DSM), and are much more accurate than the satellite method, which amounted to 6.37 m (p = 0.95) for the Pléiades Neo satellite and 9.24 m (p = 0.95) for the Hexagon Europe satellite. Based on the obtained test results, it can be stated that the photogrammetric method using a UAV meets the accuracy requirements laid down for the most stringent International Hydrographic Organization (IHO) order, i.e., Exclusive Order (Total Horizontal Uncertainty (THU) of 5 m with a confidence level of 95%), which they relate to coastline measurements. Full article

We investigated characteristics of highly flexible and stretchable electrodes consisting of Galinstan (i.e., a gallium-based liquid metal alloy) under various conditions including sub-zero temperature (i.e., <0 °C) and demonstrated solar-blind photodetection via the spontaneous oxidation of Galinstan. For this work, a simple and rapid method was introduced to fabricate the Galinstan electrodes with precise patterns and to exfoliate their surface oxide layers. Thin conductive films possessing flexibility and stretchability can be easily prepared on flexible substrates with large areas through compression of a dried suspension of Galinstan microdroplets. Furthermore, a laser marking machine was employed to facilitate patterning of the Galinstan films at a high resolution of 20 μm. The patterned Galinstan films were used as flexible and stretchable electrodes. The electrical conductivity of these electrodes was measured to be ~1.3 × 10⁶ S m⁻¹, which were still electrically conductive even if the stretching ratio increased up to 130% below 0 °C. In addition, the surface oxide (i.e., Ga₂O₃) layers possessing photo-responsive properties were spontaneously formed on the Galinstan surfaces under ambient conditions, which could be solely exfoliated using elastomeric stamps. By combining Galinstan and its surface oxide layers, solar-blind photodetectors were successfully fabricated on flexible substrates, exhibiting a distinct increase of up to 14.7% in output current under deep ultraviolet irradiation (254 nm wavelength) with an extremely low light intensity of 0.1 mW cm⁻², whereas no significant change was observed under visible light irradiation. Full article

In situ measurements of sagebrush have traditionally been expensive and time consuming. Currently, improvements in small Unmanned Aerial Systems (sUAS) technology can be used to quantify sagebrush morphology and community structure with high resolution imagery on western rangelands, especially in sensitive habitat of the Greater sage-grouse (Centrocercus urophasianus). The emergence of photogrammetry algorithms to generate 3D point clouds from true color imagery can potentially increase the efficiency and accuracy of measuring shrub height in sage-grouse habitat. Our objective was to determine optimal parameters for measuring sagebrush height including flight altitude, single- vs. double- pass, and continuous vs. pause features. We acquired imagery using a DJI Mavic Pro 2 multi-rotor Unmanned Aerial Vehicle (UAV) equipped with an RGB camera, flown at 30.5, 45, 75, and 120 m and implementing single-pass and double-pass methods, using continuous flight and paused flight for each photo method. We generated a Digital Surface Model (DSM) from which we derived plant height, and then performed an accuracy assessment using on the ground measurements taken at the time of flight. We found high correlation between field measured heights and estimated heights, with a mean difference of approximately 10 cm (SE = 0.4 cm) and little variability in accuracy between flights with different heights and other parameters after statistical correction using linear regression. We conclude that higher altitude flights using a single-pass method are optimal to measure sagebrush height due to lower requirements in data storage and processing time. Full article

This article presents a color light detection system integrated in 130 nm CMOS technology. The sensors and corresponding electronics detect light in a CIE XYZ color luminosity space using on-chip integrated sensors without any additional process steps, high-resolution analog-to-digital converter, and dedicated DSP algorithm. The sensor consists of a set of laterally arranged integrated photodiodes that are partly covered by metal, where color separation between the photodiodes is achieved by lateral carrier diffusion together with wavelength-dependent absorption. A high resolution, hybrid, ∑∆ ADC converts each photo diode’s current into a 22-bit digital result, canceling the dark current of the photo diodes. The digital results are further processed by the DSP, which calculates normalized XYZ or RGB color and intensity parameters using linear transformations of the three photo diode responses by multiplication of the data with a transformation matrix, where the coefficients are extracted by training in combination with a pseudo-inverse operation and the least-mean square approximation. The sensor system detects the color light parameters with 22-bit accuracy, consumes less than 60 μA on average at 10 readings per second, and occupies approx. 0.8 mm² of silicon area (including three photodiodes and the analog part of the ADC). The DSP is currently implemented on FPGA. Full article