| Volume 27, Issue 3 | |
| Arrhythmia Classification Based on Adaptive Refined Composite Multiscale Fluctuation Dispersion Entropy | 121-138 |
| Changsheng Zhang, Xin Ding, Changping Tian, Wei Peng | |
| doi: 10.7546/ijba.2023.27.3.000895 | |
| [ +/- how to cite ][ +/- abstract ][ full text ] | |
| Changsheng Zhang, Xin Ding, Changping Tian, Wei Peng (2023) Arrhythmia Classification Based on Adaptive Refined Composite Multiscale Fluctuation Dispersion Entropy, Int J Bioautomation, 27 (3), 121-138, doi: 10.7546/ijba.2023.27.3.000895 | |
| Abstract: To improve the accuracy of electrocardiography (ECG) signal classification and identify abnormal heart rhythms, an arrhythmia classification algorithm based on adaptive refined composite multiscale fluctuation dispersion entropy (ARCMFDE) is proposed. First, an improved QRS complex detection algorithm named the improved Pan-Tompkins algorithm (IPTA) is used. The QRS wave is detected, and the waveform is further processed; then, the signal is decomposed into multiple modal components using variational mode decomposition with the optimized number of decomposition layers (K). Subsequently, the RCMFDE is extracted from the different modal components as a classification feature. Finally, differential evolution (DE) and grey wolf optimization (GWO) are combined to form the hybrid differential evolution-grey wolf pack optimization (DE-GWO) algorithm to optimize the penalty factor c and the kernel function parameter g of the support vector machine for performing pattern recognition. Experimental results show that compared with other methods such as variational mode decomposition (VMD), fluctuation dispersion entropy (FDE), genetic algorithms (GA), and support vector machine (SVM). The proposed classification model has superior performance, with an average accuracy of 96.1%, a sensitivity of 95.9%, and a specificity of 98.7% for four types of heart rhythm recognition. Thus, accurate classification of ECG signals can be achieved using the proposed ARCMFDE-based DE-GWO method.
Keywords: Arrhythmia classification, Variational mode decomposition, Adaptive refined composite multiscale fluctuation dispersion entropy, Differential evolution – Grey wolf optimization – Support vector machines | |
| Application of Queuing Theory to Analysis of Waiting Time in the Hospital | 139-146 |
| Manish Kumar Pandey, Dharmendra Kumar Gangeshwer | |
| doi: 10.7546/ijba.2023.27.3.000904 | |
| [ +/- how to cite ][ +/- abstract ][ full text ] | |
| Manish Kumar Pandey, Dharmendra Kumar Gangeshwer (2023) Application of Queuing Theory to Analysis of Waiting Time in the Hospital, Int J Bioautomation, 27 (3), 139-146, doi: 10.7546/ijba.2023.27.3.000904 | |
| Abstract: The main problem that healthcare workers face in many hospitals is how long it takes patients to receive services. This tendency is becoming more prevalent, posing a threat to healthcare services. The repercussions of keeping people in a long line for medical care can result in a variety of issues, including death. The many server queuing models were utilized to examine the government hospital's service efficiency in this study. Over two weeks, primary data was collected at the hospital using observation and questionnaire methods to find the queuing model that minimizes patient waiting time. The findings revealed that most of the patients were dissatisfied with the hospital's queue management tactics.
Keywords: Queuing theory, Hospital, Queue management, Waiting line | |
| Adaptive Fed-batch Control of Escherichia coli Fermentation for Protein Production | 147-160 |
| Velislava Lyubenova, Anastasiya Zlatkova, Maya Ignatova | |
| doi: 10.7546/ijba.2023.27.3.000930 | |
| [ +/- how to cite ][ +/- abstract ][ full text ] | |
| Velislava Lyubenova, Anastasiya Zlatkova, Maya Ignatova (2023) Adaptive Fed-batch Control of Escherichia coli Fermentation for Protein Production, Int J Bioautomation, 27 (3), 147-160, doi: 10.7546/ijba.2023.27.3.000930 | |
| Abstract: A new adaptive linearizing control algorithm that stabilizes the carbon source concentration in a desired value is proposed. This algorithm is applied to recombinant protein production by Escherichia coli. A model for control of the investigated process is derived. The model identification is made based on experimental data of the batch phase of the process. The operating model includes two sub-models. Each of them describes one of the two physiological states through which the process passes. Switching from one model to another depends on the sign of a key parameter obtained from the acetate measurements. A cascade scheme of software sensors for the estimation of two biomass growth rates included in the structure of the proposed control algorithm is derived. Simulation studies of the developed closed system have been carried out. The results of the impact of an open-loop control system on the same object are compared.
Keywords: Fermentation, Adaptive control, Glucose, Acetate, Recombinant proteins | |
| In silico Analysis Predicts that Mir-6770-5p Can Target the X Gene of All Hepatitis B Virus Genotypes | 161-176 |
| Amrizal Muchtar, Ramdhani M. Natsir, Minarty M. Natsir, Andi Sitti Fahirah Arsal, Hisashi Iizasa, Hironori Yoshiyama | |
| doi: 10.7546/ijba.2023.27.3.000915 | |
| [ +/- how to cite ][ +/- abstract ][ full text ] | |
| Amrizal Muchtar, Ramdhani M. Natsir, Minarty M. Natsir, Andi Sitti Fahirah Arsal, Hisashi Iizasa, Hironori Yoshiyama (2023) In silico Analysis Predicts that Mir-6770-5p Can Target the X Gene of All Hepatitis B Virus Genotypes, Int J Bioautomation, 27 (3), 161-176, doi: 10.7546/ijba.2023.27.3.000915 | |
| Abstract: To date, effective medication against hepatitis B virus (HBV) has not been developed. MicroRNAs (miRNAs) comprise a promising therapeutic approach to inhibit the virus. In this study, 1917 miRNAs in the miRBase database were screened using bioinformatics software to obtain candidates that can target HBV genotype B. Two parameters, namely pairing pattern and minimum free energy were used to select the qualifying miRNAs. Three miRNAs targeting the X gene and one miRNA targeting the C gene were identified out of 39 initial candidates. Uniquely, miR-6770-5p was the only candidate that could target the X gene of all HBV genotypes, with a higher potency of inhibition compared to other candidates. The three other candidates also showed good potency for some genotypes; thus, the identified candidates show promise as therapeutics for hepatitis infection.
Keywords: Human miRNAs, HBV, X gene, in silico analysis |
Sponsored by National Science Fund of Bulgaria, Grant No KP-06-NP4-25, 2023
© 2023, BAS, Institute of Biophysics and Biomedical Engineering