Crop classification in South Korea for multitemporal PlanetScope imagery using SFC-DenseNet-AM

In this manuscript, a new methodology based on a deep learning model using a Siamese network and attention module was proposed to classify crop cultivation areas, such as onion and garlic, from multitemporal PlanetScope images in South Korea. To consider the seasonal characteristics of crops in the model, training data were constructed from multitemporal satellite images. It was generated using PlanetScope satellite imagery from January and April, corresponding to the seasonal growth period of onion and garlic, in South Korea. Image patches were generated by considering the ratio of crops to minimize the influence of imbalanced data in the training process. Siamese FC-DenseNet with an attention module model (SFC-DenseNet-AM) is proposed, and the attention module is used to classify cultivated crop areas. Based on the proposed network, we extract cultivated crop areas using preliminary cultivation information. The results of the experiment using PlanetScope images indicate that image classification for cultivated areas was effectively performed using the proposed deep learning model. The model\u27s performance, with F1-scores of 0.823 (garlic) and 0.774 (onion), was verified through an ablation study

A 118.6fJ/Conversion-Step Two-Step Time-Domain RC-to-Digital Converter With 33nF/10MΩ Range and 53aFrmsResolution

Sensor readout ICs for internet-of-things (IoT) systems require not only high energy efficiency and resolution but also a wide input range to cover a variety of sensors with different output types and characteristics [1], [2]. Readout methods based on delta-sigma modulation (DSM) [3], [4] and two-step conversion (successive approximation + time-domain (TD) DSM) [5] have been proposed to achieve high resolution and energy efficiency, but these structures suffer from limited input ranges as they convert the sensor output to voltage, whose range is strictly constrained by the given supply rails. Alternatively, a TD readout method converts the sensor output into a TD signal, eliminating the range constraint [1], [2], [6]. However, its resolution is limited by the jitter performance of the oscillator of the counting clock [1]. This resolution issue can be addressed together with a wide input range by a dual-oscillator-based structure utilizing a large oversampling ratio (OSR) [2]. However, a power-hungry high-frequency reference oscillator (R-OSC) should continuously operate to reduce the quantization noise (Q-noise), degrading energy efficiency greatly. Although this structure can reduce both the Q-noise and random noise by sacrificing the readout time, the signal-to-noise ratio (SNR) per energy efficiency is limited by the performance of the oscillator itself. Here, we present a TD 2-stepconversion readout IC achieving a wide input range, high resolution, and high energy efficiency altogether. © 2022 IEEE

Effect of Surface Roughness and Electroless Ni–P Plating on the Bonding Strength of Bi–Te-based Thermoelectric Modules

In this study, electroless-plating of a nickel-phosphor (Ni–P) thin film on surface-controlled thermoelectric elements was developed to significantly increase the bonding strength between Bi–Te materials and copper (Cu) electrodes in thermoelectric modules. Without electroless Ni–P plating, the effect of surface roughness on the bonding strength was negligible. Brittle SnTe intermetallic compounds were formed at the bonding interface of the thermoelectric elements and defects such as pores were generated at the bonding interface owing to poor wettability with the solder. However, defects were not present at the bonding interface of the specimen subjected to electroless Ni–P plating, and the electroless Ni–P plating layer acted as a diffusion barrier toward Sn and Te. The bonding strength was higher when the specimen was subjected to Ni–P plating compared with that without Ni–P plating, and it improved with increasing surface roughness. As electroless Ni–P plating improved the wettability with molten solder, the increase in bonding strength was attributed to the formation of a thicker solder reaction layer below the bonding interface owing to an increase in the bonding interface with the solder at higher surface roughness

Evaluation of Xylooligosaccharides Production for a Specific Degree of Polymerization by Liquid Hot Water Treatment of Tropical Hardwood

Eucalyptus pellita is known as attractive biomass, and it has been utilized for eucalyptus oil, furniture, and pulp and paper production that causes a significant amount of byproducts. Liquid hot water treatment depending on combined severity factor (CSF) was subjected to isolate hemicellulose fraction from E. pellita and to produce xylooligosaccharides (XOS). The xylan extraction ratio based on the initial xylan content of the feedstock was maximized up to 77.6% at 170 °C for 50 min condition (CSF: 1.0), which had accounted for XOS purity of 76.5% based on the total sugar content of the liquid hydrolysate. In this condition, the sum of xylobiose, xylotriose, and xylotetraose which has a low degree of polymerization (DP) of 2 to 4 was determined as 80.6% of the total XOS. The highest XOS production score established using parameters including the xylan extraction ratio, XOS purity, and low DP XOS ratio was 5.7 at CSF 1.0 condition. XOS production score evaluated using the CSF is expected to be used as a productivity indicator of XOS in the industry (R-squared value: 0.92).Forestry, Faculty ofNon UBCWood Science, Department ofReviewedFacultyResearche

Simultaneous Lignin Extraction and Fibrillation: A Novel Approach for a Continuous Biorefinery

A simultaneous lignin extraction and fibrillation (SEF) process combined with hydrothermal treatment is proposed, which provides an advanced lignin extraction prospect for a continuous biorefinery. Lignin was extracted during refining using a hydrothermally treated solid residue, which loosened the cell wall structure of biomass. The SEF process was controlled according to alcohol concentration without applying heat, pressure, and catalyst, increasing the lignin extraction rate by 2.1 times compared to the unpretreated biomass. The SEF process shortened the time from 96 to 48 h to reach a steady-state yield by improving the initial enzymatic hydrolysis rate with a significant increase in the final glucose conversion rate from 73.8 to 78.0%. Furthermore, the SEF process can produce lignin with a low molecular weight and a narrow polydispersity, benefiting the subsequent purification process by reducing the concentration of phenolic compounds and enzyme proteins in the enzymatic hydrolysate by 1/4 and 1/2, respectively