arXiv subjects

Sanghoon Shin

Publications and source records attributed to Sanghoon Shin.

3 recordsLinked to original sources

arXiv2023

Nepal Himalaya Offers Considerable Potential for Pumped Storage Hydropower

There is a pressing need for a transition from fossil fuel to renewable energy to meet the increasing energy demands and reduce greenhouse gas (GHG) emissions. The Himalayas possess substantial renewable energy potential that can be harnessed through hydropower projects due to its peculiar topographic characteristics and abundant water resources. However, the current exploitation rate is low owing to the predominance of run-of-river hydropower systems to support the power system. The utility-scale storage facility is crucial in the load scenario of an integrated power system to manage diurnal variation, peak demand, and penetration of intermittent energy sources. In this study, we first identify the potential of pumped storage hydropower across Nepal (a central Himalayan country) under multiple configurations by pairing lakes, hydropower projects, rivers, and available flat terrains. We then identify technically feasible pairs from those of potential locations. Infrastructural, environmental, operational, and other technical constraints govern the choice of feasible locations. We find the flat land-to-river configuration most promising than other configurations. Our results provide insight into the potential of pumped storage hydropower and are of practical importance in planning sustainable power systems in the Himalayas and beyond.

stat.AP↗

arXiv2022

Machine learning based lens-free imaging technique for field-portable cytometry

Lens-free Shadow Imaging Technique (LSIT) is a well-established technique for the characterization of microparticles and biological cells. Due to its simplicity and cost-effectiveness, various low-cost solutions have been evolved, such as automatic analysis of complete blood count (CBC), cell viability, 2D cell morphology, 3D cell tomography, etc. The developed auto characterization algorithm so far for this custom-developed LSIT cytometer was based on the hand-crafted features of the cell diffraction patterns from the LSIT cytometer, that were determined from our empirical findings on thousands of samples of individual cell types, which limit the system in terms of induction of a new cell type for auto classification or characterization. Further, its performance is suffering from poor image (cell diffraction pattern) signatures due to its small signal or background noise. In this work, we address these issues by leveraging the artificial intelligence-powered auto signal enhancing scheme such as denoising autoencoder and adaptive cell characterization technique based on the transfer of learning in deep neural networks. The performance of our proposed method shows an increase in accuracy >98% along with the signal enhancement of >5 dB for most of the cell types, such as Red Blood Cell (RBC) and White Blood Cell (WBC). Furthermore, the model is adaptive to learn new type of samples within a few learning iterations and able to successfully classify the newly introduced sample along with the existing other sample types.

eess.IV↗

arXiv2016

Three Dimensional Measurements by Deflectometry and Double Hilbert Transform

An improved phase retrieval method based Hilbert transform is introduced to quantitatively calculate the phase distribution from distorted fringe pattern. Also phase measurement deflectomety are widely used in specular type samples. The background noise or bias should be suppressed prior to apply Hilbert transform. A method for suppression background noise double Hilbert transform is presented, which requires only one image. The method is easy to implement, and it is able to conducting automated fast measurements. We have demonstrated the double Hilbert transform method to retrieve the phase and background suppression by computer simulation and experiment in phase measuring deflectometry method.

physics.ins-det↗