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On functional equations of degenerate dilogarithm
Taekyun Kim,김대산,이현석,권종겸,YUNJAE KIM 장전수학회 2022 Proceedings of the Jangjeon mathematical society Vol.25 No.1
Recently, the degenerate polylogarithm is introduced by Kim-Kim as a degenerate version of the polylogarithm. In this note, we derive some interesting functional equations related to degenerate dilogarithm.
A NOTE ON DEGENERATE LAH-BELL POLYNOMIALS ARISING FROM DERIVATIVES
Xiangfan Piao,Yunjae Kim,Jongkyum Kwon 경남대학교 수학교육과 2021 Nonlinear Functional Analysis and Applications Vol.26 No.4
Recently, Kim-Kim introduced Lah-Bell polynomials and numbers, and investigated some properties and identities of these polynomials and numbers. Kim studied Lah-Bell polynomials and numbers of degenerate version. In this paper, we study degenerate Lah-Bell polynomials arising from differential equations. Moreover, we investigate the phenomenon of scattering of the zeros of these polynomials.
SOME IDENTITIES OF TYPE 2 DEGENERATE POLY-GENOCCHI NUMBERS AND POLYNOMIALS
YUNJAE KIM,SANGBEOM PARK,표성수,권종겸 장전수학회 2022 Advanced Studies in Contemporary Mathematics Vol.32 No.4
The purpose of this paper is to introduce a new version of the degenerate poly-Genocchi polynomials and numbers called the type 2 degenerate poly-Genocchi polynomials and numbers by the modification of degenerate polyexponential function in the generating function. To investigate the properties of the proposed polynomials and numbers, we derive several explicit expressions and identities induced from new generating function. Also, we present some relations between the type 2 degenerate poly-Genocchi polynomials and numbers and some other well-known special polynomials and numbers. In addition, we consider the higher-order type 2 degenerate Genocchi polynomials and show some interesting identities involving those polynomials and the type 2 higherorder Changhee polynomials.
Kim, Karam,Hwang, Sae Mi,Kim, Sung Min,Park, Sung Woo,Jung, Yunjae,Chung, Il Yup 한국조명·전기설비학회 2017 한국조명·전기설비학회 학술대회논문집 Vol. No.
<P>Neutrophils and eosinophils, 2 prominent granulocytes, are commonly derived from myelocytic progenitors through successive stages in the bone marrow. Our previous genome-wide transcriptomic data unexpectedly showed that genes encoding a multitude of neutrophil primary granule proteins (NPGPs) were markedly downregulated during the end period of eosinophilic terminal differentiation when cord blood (CB) cluster of differentiation (CD) 34<SUP>+</SUP> cells were induced to differentiate toward the eosinophil lineage during a 24-day culture period. Accordingly, this study aimed to examine whether NPGP genes were expressed on the way to eosinophil terminal differentiation stage and to compare their expression kinetics with that of genes encoding eosinophil-specific granule proteins (ESGPs). Transcripts of all NPGP genes examined, including proteinase 3, myeloperoxidase, cathepsin G (<I>CTSG</I>), and neutrophil elastase, reached a peak at day 12 and sharply declined thereafter, while transcript of ESGP genes including major basic protein 1 (<I>MBP1</I>) attained maximum expression at days 18 or 24. Growth factor independent 1 (<I>GFI1</I>) and CCAAT/enhancer-binding protein α (<I>C/EBPA</I>), transactivators for the NPGP genes, were expressed immediately before the NPGP genes, whereas expression of <I>C/EBPA</I>, <I>GATA1</I>, and <I>GATA2</I> kinetically paralleled that of eosinophil granule protein genes. The expression kinetics of NPGPs and ESGPs were duplicated upon differentiation of the eosinophilic leukemia cell line (EoL-1) immature eosinophilic cells. Importantly, confocal image analysis showed that CTSG was strongly coexpressed with MBP1 in differentiating CB eosinophils at days 12 and 18 and became barely detectable at day 24 and beyond. Our results suggest for the first time the presence of an immature stage where eosinophils coexpress NPGPs and ESGPs before final maturation.</P>
Deep Learning and Transfer Learning of Energy consumption forecasting for different Energy Domains
Yunjae Kim,Sanghyun Ryu,Jiwon Kim,Sukjun Lee,Hyeonjoon Moon 한국차세대컴퓨팅학회 2023 한국차세대컴퓨팅학회 학술대회 Vol.2023 No.12
As global energy consumption continues to rise, artificial intelligence-based models for efficient energy usage are emerging worldwide. Traditional learning approaches necessitate extensive datasets to create accurate models for predicting energy consumption. However, acquiring the vast amount of data required by these models has its limitations. Therefore, we propose a model for accurate energy consumption prediction using transfer learning, allowing effective modeling with smaller datasets. In this study, we present a deep learning model for energy consumption prediction, utilizing transfer learning on various energy domain datasets. We construct a base model using CNN-Seq2Seq with input variables such as heat consumption and meteorological data. For comparative evaluation, we employ SVR, XGBoost, LightGBM, Random Forest, LSTM, and Seq2Seq models, utilizing metrics like MAE, MSE, and R2 Score. We explore the impact of applying transfer learning on source domain data to four distinct target domain datasets, comparing results with and without transfer learning, as well as with other machine learning algorithm models. The findings demonstrate that applying transfer learning yields superior accuracy across all four target domain datasets. This suggests the potential of overcoming limitations in specific energy domains and obtaining meaningful results through the application of transfer learning.
SOME IDENTITIES OF CARLITZ'S TYPE DEGENERATE q-CHANGHEE POLYNOMIALS AND NUMBERS
Yunjae Kim,박진우,Jongkyum Kwon 장전수학회 2021 Proceedings of the Jangjeon mathematical society Vol.24 No.1
Recently several authors have studied the degenerate q-special polynomials related to Carlitz's degenerate polynomials. In this paper, we introduce the Carlitz's type degenerate q-Changhee numbers and polynomials. And, we study some explicit identities and properties for the Carlitz's type degenerate q-Changhee numbers and polynomials arising from p-adic q-integral on Zp.