Pub Date : 2023-02-23DOI: 10.1142/s021947752350030x
Juraj Curpek
This paper investigates a progress of the maturity of the Czech intraday electricity market during the COVID-19 pandemic by employing the multifractal analysis. Our results indicate that since intraday electricity returns display multifractal property originating both from long-range correlations and fat-tailed distribution, a sole use of the Hurst exponent is not sufficient, and multifractality characteristics should be used. The quantities describing a multifractal behavior indicate in some periods higher stage of market development operating on short temporal scales compared to the larger temporal scales, especially the MLM index. In some periods, they are in close agreement with the Hurst approach (e.g., July 2020). Moreover, the ADL models indicate a positive association of the Hurst exponent on short temporal scales with its lagged values and new cases of the COVID-19. On short temporal scales, the rate of new COVID-19 cases was positively related to the strength of multifractality, i.e., smaller degree of maturity, both by singularity spectrum width and MLM index. We found a nonlinear relationship between the government stringent policy and the Hurst exponent on long temporal scales, singularity spectrum width and the MLM index on short temporal scales, indicating that the loose anti-COVID policies are associated with more mature market and vice versa. On the contrary, on its long counterpart, the relationships are weaker and opposite in signs.
{"title":"Analysis of the Czech intraday electricity market during Covid-19 pandemic from the multifractal perspective","authors":"Juraj Curpek","doi":"10.1142/s021947752350030x","DOIUrl":"https://doi.org/10.1142/s021947752350030x","url":null,"abstract":"This paper investigates a progress of the maturity of the Czech intraday electricity market during the COVID-19 pandemic by employing the multifractal analysis. Our results indicate that since intraday electricity returns display multifractal property originating both from long-range correlations and fat-tailed distribution, a sole use of the Hurst exponent is not sufficient, and multifractality characteristics should be used. The quantities describing a multifractal behavior indicate in some periods higher stage of market development operating on short temporal scales compared to the larger temporal scales, especially the MLM index. In some periods, they are in close agreement with the Hurst approach (e.g., July 2020). Moreover, the ADL models indicate a positive association of the Hurst exponent on short temporal scales with its lagged values and new cases of the COVID-19. On short temporal scales, the rate of new COVID-19 cases was positively related to the strength of multifractality, i.e., smaller degree of maturity, both by singularity spectrum width and MLM index. We found a nonlinear relationship between the government stringent policy and the Hurst exponent on long temporal scales, singularity spectrum width and the MLM index on short temporal scales, indicating that the loose anti-COVID policies are associated with more mature market and vice versa. On the contrary, on its long counterpart, the relationships are weaker and opposite in signs.","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49255435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-16DOI: 10.1142/s0219477523500268
T. Jayachandran, S. Kavitha
{"title":"A development and analysis of colour image new blind watermarking based on dwt-svd swapping and 3-dimensional cryptography technique","authors":"T. Jayachandran, S. Kavitha","doi":"10.1142/s0219477523500268","DOIUrl":"https://doi.org/10.1142/s0219477523500268","url":null,"abstract":"","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43574256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01Epub Date: 2023-04-06DOI: 10.1117/12.2653715
Ling Ma, Jeremy Sherey, Doreen Palsgrove, Baowei Fei
Hyperspectral imaging (HSI) has been demonstrated in various digital pathology applications. However, the intrinsic high dimensionality of hyperspectral images makes it difficult for pathologists to visualize the information. The aim of this study is to develop a method to transform hyperspectral images of hemoxylin & eosin (H&E)-stained slides to natural-color RGB histologic images for easy visualization. Hyperspectral images were obtained at 40× magnification with an automated microscopic imaging system and downsampled by various factors to generate data equivalent to different magnifications. High-resolution digital histologic RGB images were cropped and registered to the corresponding hyperspectral images as the ground truth. A conditional generative adversarial network (cGAN) was trained to output natural color RGB images of the histological tissue samples. The generated synthetic RGBs have similar color and sharpness to real RGBs. Image classification was implemented using the real and synthetic RGBs, respectively, with a pretrained network. The classification of tumor and normal tissue using the HSI-synthesized RGBs yielded a comparable but slightly higher accuracy and AUC than the real RGBs. The proposed method can reduce the acquisition time of two imaging modalities while giving pathologists access to the high information density of HSI and the quality visualization of RGBs. This study demonstrated that HSI may provide a potentially better alternative to current RGB-based pathologic imaging and thus make HSI a viable tool for histopathological diagnosis.
{"title":"Conditional Generative Adversarial Network (cGAN) for Synthesis of Digital Histologic Images from Hyperspectral Images.","authors":"Ling Ma, Jeremy Sherey, Doreen Palsgrove, Baowei Fei","doi":"10.1117/12.2653715","DOIUrl":"10.1117/12.2653715","url":null,"abstract":"<p><p>Hyperspectral imaging (HSI) has been demonstrated in various digital pathology applications. However, the intrinsic high dimensionality of hyperspectral images makes it difficult for pathologists to visualize the information. The aim of this study is to develop a method to transform hyperspectral images of hemoxylin & eosin (H&E)-stained slides to natural-color RGB histologic images for easy visualization. Hyperspectral images were obtained at 40× magnification with an automated microscopic imaging system and downsampled by various factors to generate data equivalent to different magnifications. High-resolution digital histologic RGB images were cropped and registered to the corresponding hyperspectral images as the ground truth. A conditional generative adversarial network (cGAN) was trained to output natural color RGB images of the histological tissue samples. The generated synthetic RGBs have similar color and sharpness to real RGBs. Image classification was implemented using the real and synthetic RGBs, respectively, with a pretrained network. The classification of tumor and normal tissue using the HSI-synthesized RGBs yielded a comparable but slightly higher accuracy and AUC than the real RGBs. The proposed method can reduce the acquisition time of two imaging modalities while giving pathologists access to the high information density of HSI and the quality visualization of RGBs. This study demonstrated that HSI may provide a potentially better alternative to current RGB-based pathologic imaging and thus make HSI a viable tool for histopathological diagnosis.</p>","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":"11 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10942653/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86534875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-27DOI: 10.1142/s0219477523400059
J. Álvarez-Ramírez
We considered the daily price dynamics of the US Bitcoin market in the period from 2015 to 2022. In the first step, we used a singular value decomposition (SVD) entropy method for assessing time-varying informational efficiency over different time scales, from weeks to quarters. It was shown that the US Bitcoin market has been informationally efficient most of the time, except for some isolated periods where the returns exhibited deviations from the random behavior. The COVID-19 pandemic has not impacted the informational efficiency. This suggests that the Bitcoin market is unpredictable, and no reliable predictions can be obtained. A further analysis was carried out by considering the recurrence intervals for different positive and negative returns. We found that the distribution of recurrence intervals for positive and negative returns is asymmetric, with mean values higher for negative returns. We found that the distribution of recurrence intervals can be described by a stretching exponential distribution, such that the empirical and analytical hazard probabilities as functions of the elapsed time show good agreement. [ FROM AUTHOR] Copyright of Fluctuation & Noise Letters is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
{"title":"Recurrence interval analysis of the US Bitcoin market","authors":"J. Álvarez-Ramírez","doi":"10.1142/s0219477523400059","DOIUrl":"https://doi.org/10.1142/s0219477523400059","url":null,"abstract":"We considered the daily price dynamics of the US Bitcoin market in the period from 2015 to 2022. In the first step, we used a singular value decomposition (SVD) entropy method for assessing time-varying informational efficiency over different time scales, from weeks to quarters. It was shown that the US Bitcoin market has been informationally efficient most of the time, except for some isolated periods where the returns exhibited deviations from the random behavior. The COVID-19 pandemic has not impacted the informational efficiency. This suggests that the Bitcoin market is unpredictable, and no reliable predictions can be obtained. A further analysis was carried out by considering the recurrence intervals for different positive and negative returns. We found that the distribution of recurrence intervals for positive and negative returns is asymmetric, with mean values higher for negative returns. We found that the distribution of recurrence intervals can be described by a stretching exponential distribution, such that the empirical and analytical hazard probabilities as functions of the elapsed time show good agreement. [ FROM AUTHOR] Copyright of Fluctuation & Noise Letters is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47775852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-27DOI: 10.1142/s0219477523500244
Pengfei Zhu, Yong Tang, Tuantuan Lu
{"title":"How connected is crude oil to stock sectors before and after the COVID-19 outbreak? Evidence from a novel network method","authors":"Pengfei Zhu, Yong Tang, Tuantuan Lu","doi":"10.1142/s0219477523500244","DOIUrl":"https://doi.org/10.1142/s0219477523500244","url":null,"abstract":"","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42059378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-27DOI: 10.1142/s0219477523500232
Sange Li, Pengjian Shang
{"title":"Characterizing nonlinear time series via sliding-window amplitude based dispersion entropy","authors":"Sange Li, Pengjian Shang","doi":"10.1142/s0219477523500232","DOIUrl":"https://doi.org/10.1142/s0219477523500232","url":null,"abstract":"","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45188795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-20DOI: 10.1142/s0219477523500219
Guangxi Cao, Wenhao Xie
{"title":"Statistical test of detrended multiple moving average cross-correlation analysis and its application in financial market","authors":"Guangxi Cao, Wenhao Xie","doi":"10.1142/s0219477523500219","DOIUrl":"https://doi.org/10.1142/s0219477523500219","url":null,"abstract":"","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49114294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-20DOI: 10.1142/s0219477523500207
Sridhar K. Venkata, Kumar T. Kishore
{"title":"Wavelet-based weighted low-rank sparse decomposition model for speech enhancement using gammatone filter bank under low snr conditions","authors":"Sridhar K. Venkata, Kumar T. Kishore","doi":"10.1142/s0219477523500207","DOIUrl":"https://doi.org/10.1142/s0219477523500207","url":null,"abstract":"","PeriodicalId":55155,"journal":{"name":"Fluctuation and Noise Letters","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49600419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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