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  • Online Resource  (70)
  • MDPI AG  (70)
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  • 1
    Online Resource
    Online Resource
    Deep Learning Models for Long-Term Solar Radiation Forecasting Considering Microgrid Installation: A Comparative Study
    MDPI AG ; 2019
    In:  Energies Vol. 13, No. 1 ( 2019-12-27), p. 147-
    Details
    In: Energies, MDPI AG, Vol. 13, No. 1 ( 2019-12-27), p. 147-
    Abstract: Microgrid is becoming an essential part of the power grid regarding reliability, economy, and environment. Renewable energies are main sources of energy in microgrids. Long-term solar generation forecasting is an important issue in microgrid planning and design from an engineering point of view. Solar generation forecasting mainly depends on solar radiation forecasting. Long-term solar radiation forecasting can also be used for estimating the degradation-rate-influenced energy potentials of photovoltaic (PV) panel. In this paper, a comparative study of different deep learning approaches is carried out for forecasting one year ahead hourly and daily solar radiation. In the proposed method, state of the art deep learning and machine learning architectures like gated recurrent units (GRUs), long short term memory (LSTM), recurrent neural network (RNN), feed forward neural network (FFNN), and support vector regression (SVR) models are compared. The proposed method uses historical solar radiation data and clear sky global horizontal irradiance (GHI). Even though all the models performed well, GRU performed relatively better compared to the other models. The proposed models are also compared with traditional state of the art methods for long-term solar radiation forecasting, i.e., random forest regression (RFR). The proposed models outperformed the traditional method, hence proving their efficiency.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en13010147
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2437446-5
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  • 2
    Online Resource
    Online Resource
    AE-LSTM Based Deep Learning Model for Degradation Rate Influenced Energy Estimation of a PV System
    MDPI AG ; 2020
    In:  Energies Vol. 13, No. 17 ( 2020-08-24), p. 4373-
    Details
    In: Energies, MDPI AG, Vol. 13, No. 17 ( 2020-08-24), p. 4373-
    Abstract: With the increase in penetration of photovoltaics (PV) into the power system, the correct prediction of return on investment requires accurate prediction of decrease in power output over time. Degradation rates and corresponding degraded energy estimation must be known in order to predict power delivery accurately. Solar radiation plays a key role in long-term solar energy predictions. A combination of auto-encoder and long short-term memory (AE-LSTM) based deep learning approach is adopted for long-term solar radiation forecasting. First, the auto-encoder (AE) is trained for the feature extraction, and then fine-tuning with long short-term memory (LSTM) is done to get the final prediction. The input data consist of clear sky global horizontal irradiance (GHI) and historical solar radiation. After forecasting the solar radiation for three years, the corresponding degradation rate (DR) influenced energy potentials of an a-Si PV system is estimated. The estimated energy is useful economically for planning and installation of energy systems like microgrids, etc. The method of solar radiation forecasting and DR influenced energy estimation is compared with the traditional methods to show the efficiency of the proposed method.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en13174373
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2437446-5
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  • 3
    Online Resource
    Online Resource
    Comprehensive Design of DC Shipboard Power Systems for Pure Electric Propulsion Ship Based on Battery Energy Storage System
    MDPI AG ; 2021
    In:  Energies Vol. 14, No. 17 ( 2021-08-25), p. 5264-
    Details
    In: Energies, MDPI AG, Vol. 14, No. 17 ( 2021-08-25), p. 5264-
    Abstract: With the strengthening of international environmental regulations, many studies on the integrated electric propulsion systems applicable to eco-friendly ship are being conducted. However, few studies have been performed to establish a guide line for the overall pure electric propulsion ship design. Therefore, this paper introduces the comprehensive design of DC shipboard power system for pure electric propulsion ship based on battery energy storage system (BESS). To design and configure the pure electric propulsion ship, 2 MW propulsion car ferry was assumed and adopted to be the target vessel in this paper. In order to design the overall system, a series of design processes, such as the decision of the ship operation profile, BESS capacity selection, configuration of the power conversion systems for propulsion, battery charging/discharging procedures, classification of system operation modes, and analysis of the efficiency, were considered. The proposed efficient design and analysis of the pure electric propulsion ship was qualitatively and quantitatively validated by MATLAB Simulink tool. The methodology presented in this paper can help design real ships before the system commissioning.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en14175264
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2437446-5
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  • 4
    Online Resource
    Online Resource
    The Role of Interventional Radiology and Management of an Angiography Suite in the Treatment of COVID-19 Patients: Single-Center, 2-Year Experience
    MDPI AG ; 2023
    In:  Medicina Vol. 59, No. 2 ( 2023-01-17), p. 188-
    Details
    In: Medicina, MDPI AG, Vol. 59, No. 2 ( 2023-01-17), p. 188-
    Abstract: Background and Objectives: Hospital angiography suites with negative-pressure ventilation facilities are challenging to equip. During the COVID-19 pandemic, we aimed to introduce interventional radiology procedures performed on COVID-19 patients and understand management of the angiography suite without a negative-pressure ventilation facility before and after the procedures to prevent the spread of infection. Materials and Methods: Between December 2020 and November 2022, 52 COVID-19 patients underwent interventional radiology procedures in an angiography suite, where no negative-pressure ventilation facility was installed. During the procedure, all staff members wore full personal protection equipment, and after the procedure for the COVID-19-positive patient was completed, the angiography suite was disinfected and entry to the angiography suite was prohibited for 1–3 h. In this angiography suite, procedures for COVID-19 patients and non-COVID-19 patients were performed. Results: A total of 61 interventional radiology procedures were performed in 52 patients with COVID-19. Of 52 patients, 21 underwent procedures under intubation and mechanical ventilation. All procedures were performed according to the guidelines set by the Infection Control Committee of our hospital. No major or minor complications were associated with the procedures. There were no cases of infection among staff members or other non-COVID-19 patients related to procedures on COVID-19 patients. Conclusions: Interventional radiology can play an important role in solving the complications of COVID-19 and the problems caused by patients’ underlying diseases. In addition, if accurate guidelines are followed, both COVID-19 and non-COVID-19 patients can undergo procedures in an angiography room without negative-pressure ventilation while preventing infection.
    Type of Medium: Online Resource
    ISSN: 1648-9144
    URL: Article
    DOI: 10.3390/medicina59020188
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2088820-X
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  • 5
    Online Resource
    Online Resource
    Cook with Different Pots, but Similar Taste? Comparison of Phase Angle Using Bioelectrical Impedance Analysis According to Device Type and Examination Posture
    MDPI AG ; 2023
    In:  Life Vol. 13, No. 5 ( 2023-04-30), p. 1119-
    Details
    In: Life, MDPI AG, Vol. 13, No. 5 ( 2023-04-30), p. 1119-
    Abstract: Bioelectrical impedance analysis (BIA) is gaining popularity as a tool for body composition assessment. Although BIA has been studied and validated in different populations, age groups, and clinical settings, including critically ill patients, there are concerns about BIA reproducibility and reliability for different device types and postures. This study aimed to evaluate the reliability of BIA using different devices, postures, and lead types. Cross-sectional observational data were collected from 74 healthy volunteers (32 women, 42 men). We used two types of devices, three types of postures (standing, sitting, and lying), and two lead types (clamp lead and adhesive lead) to measure the whole-body phase angle (phA) at a single frequency of 50 kHz. The measurements were validated using the intraclass correlation coefficient (ICC) and Bland–Altman plot analysis. All phA measurements recorded using the two types of devices, three different postures, and two types of leads were equivalent (mean ICC = 0.9932, 95% confidence interval (CI) 0.9905–0.0053, p 〈 0.001). The average mean difference in phA was 0.31 (95% CI 0.16–0.46). The largest phA value was measured using BWA with an adhesive-type lead in the supine position. There were no differences between the standing and sitting positions. We compared the consistency and reliability of phA using two devices, two lead types, and three postures. Seven different phA were interchangeable in healthy volunteers.
    Type of Medium: Online Resource
    ISSN: 2075-1729
    URL: Article
    DOI: 10.3390/life13051119
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662250-6
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  • 6
    Online Resource
    Online Resource
    Surface Transformation of Spin-on-Carbon Film via Forming Carbon Iron Complex for Remarkably Enhanced Polishing Rate
    MDPI AG ; 2022
    In:  Nanomaterials Vol. 12, No. 6 ( 2022-03-15), p. 969-
    Details
    In: Nanomaterials, MDPI AG, Vol. 12, No. 6 ( 2022-03-15), p. 969-
    Abstract: To scale down semiconductor devices to a size less than the design rule of 10 nm, lithography using a carbon polymer hard-mask was applied, e.g., spin-on-carbon (SOC) film. Spin coating of the SOC film produces a high surface topography induced by pattern density, requiring chemical–mechanical planarization (CMP) for removing such high surface topography. To achieve a relatively high polishing rate of the SOC film surface, the CMP principally requires a carbon–carbon (C-C) bond breakage on the SOC film surface. A new design of CMP slurry evidently accomplished C-C bond breakage via transformation from a hard surface with strong C-C covalent bonds into a soft surface with a metal carbon complex (i.e., C=Fe=C bonds) during CMP, resulting in a remarkable increase in the rate of the SOC film surface transformation with an increase in ferric catalyst concentration. However, this surface transformation on the SOC film surface resulted in a noticeable increase in the absorption degree (i.e., hydrophilicity) of the SOC film CMP slurry on the polished SOC film surface during CMP. The polishing rate of the SOC film surface decreased notably with increasing ferric catalyst concentration. Therefore, the maximum polishing rate of the SOC film surface (i.e., 272.3 nm/min) could be achieved with a specific ferric catalyst concentration (0.05 wt%), which was around seven times higher than the me-chanical-only CMP.
    Type of Medium: Online Resource
    ISSN: 2079-4991
    URL: Article
    DOI: 10.3390/nano12060969
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662255-5
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  • 7
    Online Resource
    Online Resource
    Scavenger with Protonated Phosphite Ions for Incredible Nanoscale ZrO2-Abrasive Dispersant Stability Enhancement and Related Tungsten-Film Surface Chemical–Mechanical Planarization
    MDPI AG ; 2021
    In:  Nanomaterials Vol. 11, No. 12 ( 2021-12-04), p. 3296-
    Details
    In: Nanomaterials, MDPI AG, Vol. 11, No. 12 ( 2021-12-04), p. 3296-
    Abstract: For scaling-down advanced nanoscale semiconductor devices, tungsten (W)-film surface chemical mechanical planarization (CMP) has rapidly evolved to increase the W-film surface polishing rate via Fenton-reaction acceleration and enhance nanoscale-abrasive (i.e., ZrO2) dispersant stability in the CMP slurry by adding a scavenger to suppress the Fenton reaction. To enhance the ZrO2 abrasive dispersant stability, a scavenger with protonate-phosphite ions was designed to suppress the time-dependent Fenton reaction. The ZrO2 abrasive dispersant stability (i.e., lower H2O2 decomposition rate and longer H2O2 pot lifetime) linearly and significantly increased with scavenger concentration. However, the corrosion magnitude on the W-film surface during CMP increased significantly with scavenger concentration. By adding a scavenger to the CMP slurry, the radical amount reduction via Fenton-reaction suppression in the CMP slurry and the corrosion enhancement on the W-film surface during CMP performed that the W-film surface polishing rate decreased linearly and notably with increasing scavenger concentration via a chemical-dominant CMP mechanism. Otherwise, the SiO2-film surface polishing rate peaked at a specific scavenger concentration via a chemical and mechanical-dominant CMP mechanism. The addition of a corrosion inhibitor with a protonate-amine functional group to the W-film surface CMP slurry completely suppressed the corrosion generation on the W-film surface during CMP without a decrease in the W- and SiO2-film surface polishing rate.
    Type of Medium: Online Resource
    ISSN: 2079-4991
    URL: Article
    DOI: 10.3390/nano11123296
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
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  • 8
    Online Resource
    Online Resource
    Impact of Cardiac Troponin Elevation on Mortality of Patients with Acute Heart Failure: Insights from the Korea Acute Heart Failure (KorAHF) Registry
    MDPI AG ; 2022
    In:  Journal of Clinical Medicine Vol. 11, No. 10 ( 2022-05-16), p. 2800-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 11, No. 10 ( 2022-05-16), p. 2800-
    Abstract: We aimed to conduct the largest study evaluating the impact of cardiac troponin (TnI) status on mid- and long-term mortality in patients admitted for acute heart failure (AHF) as compared between patients with ischemic (IHF) vs. non-ischemic heart failure (non-IHF). Among 5625 patients from the Korea Acute Heart Failure (KorAHF) registry, 4396 eligible patients with TnI measurement were analyzed. The patients were included on admission with the diagnosis of AHF, and TnI level was measured on the day of admission. A TnI value of 〈 0.05 ng/mL was considered normal. The patients were divided into four groups according to the etiology of heart failure and the status of TnI: non-IHF with normal TnI (n = 1009) vs. non-IHF with elevated TnI (n = 1665) vs. IHF with normal TnI (n = 258) vs. IHF with elevated TnI (n = 1464). The primary outcome was death from all causes according to the etiology (non-IHF vs. IHF) and TnI elevation during the entire follow-up period of 784 days (IQR 446–1116). Elevation of TnI was observed in 71.2% of all patients with AHF. Patients with IHF had higher all-cause mortality compared to those with non-IHF. Elevated TnI was associated with higher 90-day and post-90-day mortality in the non-IHF group. IHF as compared to non-IHF and elevation of TnI were independent predictors of mortality also in the adjustment analysis. In the IHF group, however, elevated TnI had a higher mortality with only 90-day follow-up (18.6% vs. 25.9%, log-rank p 〈 0.001), not in the post-90-day follow-up (31.1% vs. 32.5%, log-rank p = 0.799). In conclusion, elevated TnI in patients with heart failure is associated with increased all-cause mortality regardless of the etiology of HF. Elevation of TnI was associated to a higher post-90 day mortality in patients with non-IHF but not in patients with IHF.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm11102800
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662592-1
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  • 9
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    Online Resource
    Probiotic Potential of a Novel Vitamin B2-Overproducing Lactobacillus plantarum Strain, HY7715, Isolated from Kimchi
    MDPI AG ; 2021
    In:  Applied Sciences Vol. 11, No. 13 ( 2021-06-22), p. 5765-
    Details
    In: Applied Sciences, MDPI AG, Vol. 11, No. 13 ( 2021-06-22), p. 5765-
    Abstract: Vitamin B2, also known as riboflavin, is essential for maintaining human health. The purpose of this study was to isolate novel lactic acid bacteria that overproduce vitamin B2 and to validate their potential as probiotics. In this study, Lactobacillus plantarum HY7715 (HY7715) was selected among lactic acid bacteria isolated from Kimchi. HY7715 showed a very high riboflavin-producing ability compared to the control strain due to the high expression of ribA, ribB, ribC, ribH, and ribG genes. HY7715 produced 34.5 ± 2.41 mg/L of riboflavin for 24 h without consuming riboflavin in the medium under optimal growth conditions. It was able to produce riboflavin in an in vitro model of the intestinal environment. In addition, when riboflavin deficiency was induced in mice through nutritional restriction, higher levels of riboflavin were detected in plasma and urine in the HY7715 administration group than in the control group. HY7715 showed high survival rate in simulated gastrointestinal conditions and had antibiotic resistance below the cutoff MIC value suggested by the European Food Safety Authority; moreover, it did not cause hemolysis. In conclusion, HY7715 could be considered a beneficial probiotic strain for human and animal applications, suggesting that it could be a new alternative to address riboflavin deficiency.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app11135765
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704225-X
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  • 10
    Online Resource
    Online Resource
    Early Detection of Bacteraemia Using Ten Clinical Variables with an Artificial Neural Network Approach
    MDPI AG ; 2019
    In:  Journal of Clinical Medicine Vol. 8, No. 10 ( 2019-10-02), p. 1592-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 8, No. 10 ( 2019-10-02), p. 1592-
    Abstract: An adequate model for predicting bacteraemia has not yet been developed. This study aimed to evaluate the performance of an artificial neural network (ANN)-based prediction model in comparison with previous statistical models. The performance of multi-layer perceptron (MLP), a representative ANN model, was verified via comparison with a non-neural network model. A total of 1260 bacteraemia episodes were identified in 13,402 patients. In MLP with 128 hidden layer nodes, the area under the receiver operating characteristic curve (AUC) of the prediction performance was 0.729 (95% confidence interval [CI]; 0.712–0.728), while in MLP with 256 hidden layer nodes, it was 0.727 (95% CI; 0.713–0.727). In a conventional Bayesian statistical method, the AUC was 0.7. The aforementioned two MLP models exhibited the highest sensitivity (0.810). The ranking of clinical variables was used to describe the influential power of the prediction. Serum alkaline phosphatase was one of the most influential clinical variables, and one-out search was the best ranking method for measuring the influence of the clinical variables. Furthermore, adding variables beyond the 10 top-ranking ones did not significantly affect the prediction of bacteraemia. The ANN model is not inferior to conventional statistical approaches. Bacteraemia can be predicted using only the top 10 clinical variables determined by a ranking method, and the model can be used in clinical practice by applying real-time monitoring.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm8101592
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2662592-1
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