南韓

Stochastic gradient descent (SGD) is one of the preferred online optimization algorithms. However, one of its major drawbacks is its predisposition to forgetting previous data when optimizing through a data stream, also known as catastrophic interference. In this project, we attempt to mitigate this drawback by proposing a new low-cost approach which incorporates backward queried images with SGD during online training. Under this new approach, we propose that for every new training sample through the data stream, the neural network is optimized using the corresponding backward queried image from the initial dataset. After compiling the accuracy of the proposed method and SGD under a data-stream of 50,000 training cases with 10,000 test cases and comparing our algorithm to SGD, we see substantial improvements in the performance of the neural network with two different MNIST datasets (Fashion and Kuzushiji), classifying the MNIST datasets at a high accuracy for the mean, minimum, lower quartile, median, and upper quartile, while maintaining lower standard deviation in performance, demonstrating that our proposed algorithm can be a potential alternative to online SGD.

The equation of an ellipse and quadratic residues are well-known concepts in elementary geometry and number theory, respectively. While the properties of ellipse equations in Euclidean space have been extensively studied, many characteristics of quadratic residues, such as consecutive quadratic residues, have also been explored in past research. In this study, we discovered the characteristic polynomial of the equation of an ellipse over finite fields Fp, a single-variable polynomial that shares the same roots as the ellipse. Furthermore, by examining the parallels between the equation of an ellipse and the pairs of residues and nonresidues, we derived a characteristic polynomial for this concept and demonstrated its connection to the Catalan number, a significant sequence in combinatorics. This research was conducted through the following steps. First, the power sums of the roots of the ellipse in Fp were calculated using the Legendre symbol and Euler’s criterion. Next, the characteristic polynomial of the ellipse was determined using Newton’s identity, generating functions, and Vieta’s theorem. Finally, leveraging the equivalence between the equation of the ellipse and the pairs of residues and nonresidues, we established the main results connecting these two concepts with Catalan numbers.

Carbon capture and storage technology (CCS) has tremendous potential to enable the use of fossil fuels while reducing the emissions of CO2 into the atmosphere, and consequently combating climate change. CCS faces several challenges such as energy consumption, cost, low practical applications and environmentally friendliness. This research presents the first carbon capture device capable of capturing CO2 while generating green energy. By integrating advanced materials science with sustainable energy principles, the device addresses the dual challenges of CO2 mitigation and renewable energy production in a single, cost-effective platform. Beyond its technical innovations, this research highlights the device’s scalability and potential to revolutionize carbon capture deployment. The device can be integrated into industrial emissions systems, transportation systems, urban infrastructure, or even wearable technologies, providing versatile applications across different sectors. Furthermore, the device’s lightweight and flexible form factor ensures accessibility as it improves the applicability of CCS technology in remote or developing regions. This study demonstrated a novel approach to carbon capture by implementing carbon capture into a thin-film moisture electricity generator. The developed thin-film supercapacitor successfully demonstrated the capacity for supercapacitive swing adsorption of CO2, which is a relatively novel approach to CCS that is cheap, environmentally friendly, and efficient while generating green energy from ambient humidity.

The following issues associated with soil affected by wildfires were identified: First, there was a significant decline in the populations of anaerobic and aerobic soil bacteria, which play a critical role in the decomposition and cycling of organic matter. This decline resulted in reduced water retention capacity and porosity of the soil, leading to poor moisture retention and increased evaporation compared to unaffected soil. Moreover, the organic matter content in the soil was significantly depleted, inhibiting plant growth. Additionally, there was a notable proliferation of methane-producing bacteria, which contribute to the greenhouse effect. It was further observed that fire-damaged soils exhibit limited natural recovery, even over prolonged periods. .An investigation into the underlying causes of these problems revealed that actinomycetes, the primary microorganisms responsible for producing watersoluble aromatic compounds in soil, are particularly sensitive to heat compared to other bacterial species. Research demonstrated that the population and diversity of actinomycetes are significantly diminished in soils exposed to wildfires. To mitigate these issues, water-soluble aromatic compounds produced by actinomycetes were extracted and introduced into wildfire-affected soil. This intervention promoted the restoration of actinomycetes populations, enabling their normal growth in the affected soil. Consequently, various wildfire-induced soil problems were effectively resolved. These outcomes were confirmed through the study...Key Words: Actinomycetes, anaerobic and aerobic soil bacteria, methane-producing bacteria, wildfires, water-soluble aromatic compounds.