bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated Solar PV Simulation System Supported by DC–DC Power Converters
Authors: Cordeiro Armando , Chaves Miguel , Gâmboa Paulo , Barata Filipe , Fonte Pedro , Lopes Hélio , Pires Vítor Fernão , Foito Daniel , Amaral Tito G. , Martins João Francisco
Published: March 2023

Solar photovoltaic simulators are valuable tools for the design and evaluation of several components of photovoltaic systems. They can also be used for several purposes, such as educational objectives regarding operation principles, control strategies, efficiency, maintenance, and other aspects. This paper presents an automated solar photovoltaic simulation system with the capability to generate automated tests considering different parameters of solar photovoltaic panels and different operation conditions. The proposed simulator is composed of three buck-boost DC–DC power converters controlled in such a way that will behave similarly to solar photovoltaic panels. It allows to introduce additional variable loads and maximum power point tracker algorithms similar to real systems. Some converters are controlled by a DSP microcontroller connected to a single programmable logic controller which generates the automated tests. Thus, using the presented solution, it is possible to implement the I-V and P-V characteristic curves of solar photovoltaic panels and evaluate different maximum power point tracker algorithms considering different meteorological conditions and load variations, being a useful tool to teach subjects related to renewable energy sources and related applications. Several simulation results using Matlab/Simulink and experimental results are presented to validate the operation of the proposed solution. Experimental results achieve a ripple between 2% and 5% of the desired average current in MPP conditions.
Hybrid Multilevel Thresholding Image Segmentation Approach for Brain MRI
Authors: Sharma Suvita Rani , Alshathri Samah , Singh Birmohan , Kaur Manpreet , Mostafa Reham R. , El-Shafai Walid
Published: March 2023

A brain tumor is an abnormal growth of tissues inside the skull that can interfere with the normal functioning of the neurological system and the body, and it is responsible for the deaths of many individuals every year. Magnetic Resonance Imaging (MRI) techniques are widely used for detection of brain cancers. Segmentation of brain MRI is a foundational process with numerous clinical applications in neurology, including quantitative analysis, operational planning, and functional imaging. The segmentation process classifies the pixel values of the image into different groups based on the intensity levels of the pixels and a selected threshold value. The quality of the medical image segmentation extensively depends on the method which selects the threshold values of the image for the segmentation process. The traditional multilevel thresholding methods are computationally expensive since these methods thoroughly search for the best threshold values to maximize the accuracy of the segmentation process. Metaheuristic optimization algorithms are widely used for solving such problems. However, these algorithms suffer from the problem of local optima stagnation and slow convergence speed. In this work, the original Bald Eagle Search (BES) algorithm problems are resolved in the proposed Dynamic Opposite Bald Eagle Search (DOBES) algorithm by employing Dynamic Opposition Learning (DOL) at the initial, as well as exploitation, phases. Using the DOBES algorithm, a hybrid multilevel thresholding image segmentation approach has been developed for MRI image segmentation. The hybrid approach is divided into two phases. In the first phase, the proposed DOBES optimization algorithm is used for the multilevel thresholding. After the selection of the thresholds for the image segmentation, the morphological operations have been utilized in the second phase to remove the unwanted area present in the segmented image. The performance efficiency of the proposed DOBES based multilevel thresholding algorithm with respect to BES has been verified using the five benchmark images. The proposed DOBES based multilevel thresholding algorithm attains higher Peak Signal-to-Noise ratio (PSNR) and Structured Similarity Index Measure (SSIM) value in comparison to the BES algorithm for the benchmark images. Additionally, the proposed hybrid multilevel thresholding segmentation approach has been compared with the existing segmentation algorithms to validate its significance. The results show that the proposed algorithm performs better for tumor segmentation in MRI images as the SSIM value attained using the proposed hybrid segmentation approach is nearer to 1 when compared with ground truth images.
Auditory Electrophysiological and Perceptual Measures in Student Musicians with High Sound Exposure
Authors: Washnik Nilesh J. , Bhatt Ishan Sunilkumar , Sergeev Alexander V. , Prabhu Prashanth , Suresh Chandan
Published: March 2023

This study aimed to determine (a) the influence of noise exposure background (NEB) on the peripheral and central auditory system functioning and (b) the influence of NEB on speech recognition in noise abilities in student musicians. Twenty non-musician students with self-reported low NEB and 18 student musicians with self-reported high NEB completed a battery of tests that consisted of physiological measures, including auditory brainstem responses (ABRs) at three different stimulus rates (11.3 Hz, 51.3 Hz, and 81.3 Hz), and P300, and behavioral measures including conventional and extended high-frequency audiometry, consonant–vowel nucleus–consonant (CNC) word test and AzBio sentence test for assessing speech perception in noise abilities at −9, −6, −3, 0, and +3 dB signal to noise ratios (SNRs). The NEB was negatively associated with performance on the CNC test at all five SNRs. A negative association was found between NEB and performance on the AzBio test at 0 dB SNR. No effect of NEB was found on the amplitude and latency of P300 and the ABR wave I amplitude. More investigations of larger datasets with different NEB and longitudinal measurements are needed to investigate the influence of NEB on word recognition in noise and to understand the specific cognitive processes contributing to the impact of NEB on word recognition in noise.
Impact of CT Photon-Counting Virtual Monoenergetic Imaging on Visualization of Abdominal Arterial Vessels
Authors: Dillinger Daniel , Overhoff Daniel , Booz Christian , Kaatsch Hanns L. , Piechotka Joel , Hagen Achim , Froelich Matthias F. , Vogl Thomas J. , Waldeck Stephan
Published: March 2023

Purpose: The novel photon-counting detector (PCD) technique acquires spectral data for virtual monoenergetic imaging (VMI) in every examination. The aim of this study was the evaluation of the impact of VMI of abdominal arterial vessels on quantitative and qualitative subjective image parameters. Methods: A total of 20 patients that underwent an arterial phase computed tomography (CT) scan of the abdomen with a novel PCD CT (Siemens NAEOTOM alpha) were analyzed regarding attenuation at different energy levels in virtual monoenergetic imaging. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated and compared between the different virtual monoenergetic (VME) levels with correlation to vessel diameter. In addition, subjective image parameters (overall subjective image quality, subjective image noise and vessel contrast) were evaluated. Results: Our research showed decreasing attenuation levels with increasing energy levels in virtual monoenergetic imaging regardless of vessel diameter. CNR showed best overall results at 60 keV, and SNR at 70 keV with no significant difference to 60 keV (p = 0.294). Subjective image quality was rated best at 70 keV for overall image quality, vessel contrast and noise. Conclusions: Our data suggest that VMI at 60–70 keV provides the best objective and subjective image quality concerning vessel contrast irrespective of vessel size.
Tear Film Dynamics between Low and High Contact Lens Dry Eye Disease Questionnaire (CLDEQ-8) Score with a Lehfilcon A Silicone Hydrogel Water Gradient Contact Lens: A Non-Invasive Methodology Approach
Authors: Capote-Puente Raúl , Bautista-Llamas María-José , Sánchez-González José-María
Published: March 2023

The purpose of this study is to evaluate the tear film dynamics between individuals with low and high Contact Lens Dry Eye Disease Questionnaire (CLDEQ-8) scores when wearing Lehfilcon A silicone hydrogel water gradient contact lenses. In this study, we implemented a longitudinal, single-location, self-comparison investigation. Variables measured included conjunctival redness, lipid layer thickness, tear meniscus height, first and mean non-invasive break-up time, CLDEQ-8, and standard patient evaluation of eye dryness (SPEED). In the second phase, participants were re-evaluated after 30 days of wearing the contact lenses to assess the tear film wearing the lenses. In a longitudinal comparison by group, we found that lipid layer thickness decreased 1.52 ± 1.38 (p < 0.01) and 0.70 ± 1.30 (p = 0.01) Guillon patterns degrees in the low and high CLDEQ-8 group, respectively. MNIBUT increased in 11.93 ± 17.93 (p < 0.01) and 7.06 ± 12.07 (p < 0.01) seconds. Finally, LOT increased in 22.19 ± 27.57 (p < 0.01) and 16.87 ± 25.09 (p < 0.01). In conclusion, this study demonstrates the effectiveness of Lehfilcon A silicone hydrogel water gradient contact lenses in improving tear film stability and reducing subjective dry eye symptoms in individuals with low and high CLDEQ-8 scores. However, it also led to an increase in conjunctival redness and a decrease in tear meniscus height.
Can Imaging Using Radiomics and Fat Fraction Analysis Detect Early Tissue Changes on Historical CT Scans in the Regions of the Pancreas Gland That Subsequently Develop Adenocarcinoma?
Authors: Korn Ronald Lee , Burkett Andre , Geschwind Jeff , Zygadlo Dominic , Brodie Taylor , Cridebring Derek , Von Hoff Daniel D. , Demeure Michael J.
Published: March 2023

Despite a growing number of effective therapeutic options for patients with pancreatic adenocarcinoma, the prognosis remains dismal mostly due to the late-stage presentation and spread of the cancer to other organs. Because a genomic analysis of pancreas tissue revealed that it may take years, if not decades, for pancreatic cancer to develop, we performed radiomics and fat fraction analysis on contrast-enhanced CT (CECT) scans of patients with historical scans showing no evidence of cancer but who subsequently went on to develop pancreas cancer years later, in an attempt to identify specific imaging features of the normal pancreas that may portend the subsequent development of the cancer. In this IRB-exempt, retrospective, single institution study, CECT chest, abdomen, and pelvis (CAP) scans of 22 patients who had evaluable historical imaging data were analyzed. The images from the “healthy” pancreas were obtained between 3.8 and 13.9 years before the diagnosis of pancreas cancer was established. Afterwards, the images were used to divide and draw seven regions of interest (ROIs) around the pancreas (uncinate, head, neck-genu, body (proximal, middle, and distal) and tail). Radiomic analysis on these pancreatic ROIs consisted of first order quantitative texture analysis features such as kurtosis, skewness, and fat quantification. Of all the variables tested, fat fraction in the pancreas tail (p = 0.029) and asymmetry of the histogram frequency curve (skewness) of pancreas tissue (p = 0.038) were identified as the most important imaging signatures for subsequent cancer development. Changes in the texture of the pancreas as measured on the CECT of patients who developed pancreas cancer years later could be identified, confirming the utility of radiomics-based imaging as a potential predictor of oncologic outcomes. Such findings may be potentially useful in the future to screen patients for pancreatic cancer, thereby helping detect pancreas cancer at an early stage and improving survival.
Direct Prosthetic Joint Infection Diagnosis from Sonication Fluid Inoculated in Blood Culture Bottles by Direct MALDI-TOF Mass Spectrometry
Authors: Beguiristain Iñaki , Henriquez Lucia , Sancho Ignacio , Martin Carmen , Hidalgo-Ovejero Angel , Ezpeleta Carmen , Portillo Maria Eugenia
Published: March 2023

An accurate and fast microbiological diagnosis is key for a proper management and results when facing prosthetic joint infection (PJI). The purpose of this study is to assess the role of direct Matrix-assisted laser desorption ionization time of flight (MALDI-TOF) mass spectrometry (MS) for early identification of the pathogens causing PJI from sonication fluid inoculated in blood culture bottles (BCB-SF). This prospective multicentric study included 107 consecutive patients from February 2016 to February 2017. Among them, 71 prosthetic joint revision surgeries were undergone for aseptic and 36 for septic reasons. Prostheses were sonicated and the resulting fluid inoculated into blood culture bottles, regardless the suspicion for infection. We assessed the diagnostic performance of direct MALDI-TOF MS identification of the pathogens in BCB-SF and compared it with periprosthetic tissue and conventional sonication fluid cultures. The sensitivity of direct MALDI-TOF MS of BCB-SF (69%) was higher compared to conventional sonication fluid (69% vs. 64%, p > 0.05) or intraoperative tissue cultures (69% vs. 53%, p = 0.04), especially for patients receiving antimicrobial treatment. This approach also reduced the time for identification but the specificity was compromised (100% vs. 94%) and polymicrobial infections were missed. In conclusion, BCB-SF improves the sensitivity and reduces the time of PJI diagnosis when used in combination with conventional cultures under strict sterility conditions.
Vancomycin and Linezolid-Resistant Enterococcus Isolates from a Tertiary Care Center in India
Authors: Sengupta Mallika , Sarkar Riya , Sarkar Soma , Sengupta Manideepa , Ghosh Sougata , Banerjee Parthajit
Published: March 2023

Introduction: There is increasing development of antibiotic resistance among the Enterococcus species. Objectives: This study was performed to determine prevalence and characterize the vancomycin-resistant and linezolid-resistant enterococcus isolates from a tertiary care center. Moreover, the antimicrobial susceptibility pattern of these isolates was also determined. Materials and Methods: A prospective study was performed in Medical College, Kolkata, India, over a period of two years (from January 2018 to December 2019). After obtaining clearance from the Institutional Ethics Committee, Enterococcus isolates from various samples were included in the present investigation. In addition to the various conventional biochemical tests, the VITEK 2 Compact system was used to identify the Enterococcus species. The isolates were tested for antimicrobial susceptibility to different antibiotics using the Kirby–Bauer disk diffusion method and VITEK 2 Compact to determine the minimum inhibitory concentration (MIC). The Clinical and Laboratory Standards Institute (CLSI) 2017 guidelines were used to interpret susceptibility. Multiplex PCR was performed for genetic characterization of the vancomycin-resistant Enterococcus isolates and sequencing was performed for characterization of the linezolid-resistant Enterococcus isolates. Results: During the period of two years, 371 isolates of Enterococcus spp. were obtained from 4934 clinical isolates showing a prevalence of 7.52%. Among these isolates, 239 (64.42%) were Enterococcus faecalis, 114 (30.72%) Enterococcus faecium, and others were Enterococcus durans, Enterococcus casseliflavus, Enterococcus gallinarum, and Enterococcus avium. Among these, 24 (6.47%) were VRE (Vancomycin-Resistant Enterococcus) of which 18 isolates were Van A type and six isolates of Enterococcus casseliflavus and Enterococcus gallinarum were resistant VanC type. There were two linezolid-resistant Enterococcus, and they were found to have the G2576T mutation. Among the 371 isolates, 252 (67.92%) were multi-drug resistant. Conclusion: This study found an increasing prevalence of vancomycin-resistant Enterococcus isolates. There is also an alarming prevalence of multidrug resistance among these isolates.
Effectiveness of mHealth Interventions in Medication Adherence among Patients with Cardiovascular Diseases: A Systematic Review
Authors: Arshed Muhammad , Mahmud Aidalina Binti , Minhat Halimatus Sakdiah , Ying Lim Poh , Umer Muhammad Farooq
Published: March 2023

mHealth interventions have been reported to improve adherence to long-term therapies in chronic conditions. Therefore, this study aimed at determining the effectiveness of mHealth interventions in medication adherence among patients with cardiovascular diseases (CVDs), a leading cause of mortality globally. Relying on our inclusion criteria and the PRISMA recommendations, a literature search was carried out in the PubMed, Medline, and ProQuest databases for primary studies that investigated the impact of mHealth on medication adherence for cardiovascular disease (CVD) between 2000–2021. A total of 23 randomized controlled trials with 34,915 participants matched the selection criteria. The mHealth interventions used included text messages, mobile phone applications, and voice calls, which were used either as a single intervention or combined. Additionally, studies on enhancing drug adherence had contradictory findings: most of the studies elaborated positive results; however, six studies were unable to reveal any significant effect. Finally, a risk bias analysis revealed varying outcomes across all studies. This review, as a whole, supported the notion that mHealth interventions can be effective in improving adherence to CVD medication even though they could not improve adherence to all CVD medications when compared with controls. Further trials with more refined designs integrated with comprehensive interventions are needed to produce better health outcomes.
Chewing Efficiency Test in Subjects with Clear Aligners
Authors: Levrini Luca , Bocchieri Salvatore , Mauceri Federico , Saran Stefano , Carganico Andrea , Zecca Piero Antonio , Segù Marzia
Published: March 2023

The aim of this study was to evaluate the masticatory function of subjects with clear aligners and to propose a simple and repeatable method for the clinical and experimental evaluation of masticatory function. For the testing we used almonds, a natural substance that can be easily found and stored, has intermediate consistency and hardness, is insoluble in saliva, and has the ability easily lose the moisture absorbed in the mouth. Thirty-four subjects using the Invisalign® (Align Technology, Santa Clara, CA, USA) protocol were randomly selected. This was an “intercontrol test”, i.e., all subjects under the same conditions acted as controls but also as cases whilst wearing the clear aligners. Patients were asked to chew an almond for 20 s, once with aligners and once without aligners. The material was then dried, sieved, and weighted. Statistical analysis was performed to investigate any significative differences. In all our subjects, the efficiency of chewing with clear aligners was found to be comparable to the efficiency of chewing without clear aligners. In detail, the average weight after drying was 0.62 g without aligners and 0.69 g with aligners, while after sieving at 1 mm, the average weight was 0.08 g without aligners and 0.06 g with aligners. The average variation after drying was of 12%, and after sieving at 1 mm, it was 25%. In summary, there was no substantial difference between chewing with or without clear aligners. Despite some discomfort in chewing, the clear aligners were well tolerated by most subjects, who wore them without difficulty even during meals.
A 23-Year Observational Follow-Up Clinical Evaluation of Direct Posterior Composite Restorations
Authors: von Gehren Marie O. , Rüttermann Stefan , Romanos Georgios E. , Herrmann Eva , Gerhardt-Szép Susanne
Published: March 2023

The purpose of this observational follow-up clinical study was to observe the quality of posterior composite restorations more than 23 years after application. A total of 22 patients, 13 male and 9 female (mean age 66.1 years, range 50–84), with a total of 42 restorations attended the first and second follow-up examinations. The restorations were examined by one operator using modified FDI criteria. Statistical analysis was performed with the Wilcoxon Mann–Whitney U test and Wilcoxon exact matched-pairs test with a significance level of p = 0.05. Bonferroni–Holm with an adjusted significance level of alpha = 0.05 was applied. With the exception of approximal anatomical form, significantly worse scores were seen for six out of seven criteria at the second follow-up evaluation. There was no significant difference in the first and second follow-up evaluations in the grades of the restorations with regard to having been placed in the maxilla or mandible, as well as for one-surface or multiple-surface restorations. The approximal anatomical form showed significantly worse grades at the second follow-up when having been placed in molars. In conclusion, the study results show that significant differences regarding FDI criteria in posterior composite restorations occur after more than 23 years of service. Further studies with extended follow-up time and at regular and short time intervals are recommended.
Classifying Children’s Behaviour at the Dentist—What about ‘Burnout’?
Authors: Donnell Christopher C.
Published: March 2023

In children and young people, complex and prolonged dental treatment can sometimes be met with resistance despite previously successful treatment appointments. While this has traditionally been referred to as a ‘loss of cooperation’ or ‘non-compliance’, these children may actually be experiencing ‘burnout’, of which many may have the potential to recover and complete their course of treatment. Burnout has been defined as “the extinction of motivation or incentive, especially where one’s devotion to a cause or relationship fails to produce the desired results”. Traditionally, burnout is experienced by those who deliver services rather than be in receipt of a service; however, the burnout concept proposed in this paper explores it as an alternative perspective to other dentally relevant psychosocial conditions and should be considered when employing appropriate behaviour management techniques and coping strategies for paediatric patients. The intention of this paper is not to establish firm grounds for this new concept in healthcare, but to start a discussion and motivate further theoretical and empirical research. The introduction of the ‘burnout triad model’ and the importance of communication aims to highlight the tripartite influence of patients, parents and professionals engaged in the central ‘care experience’ and underlines the belief that early recognition and management of potential signs of burnout may help reduce the likelihood of those involved developing the condition.
Large-Scale Simulation of Full Three-Dimensional Flow and Combustion of an Aero-Turbofan Engine on Sunway TaihuLight Supercomputer
Authors: Xu Quanyong , Ren Hu , Gu Hanfeng , Wu Jie , Wang Jingyuan , Xie Zhifeng , Yang Guangwen
Published: March 2023

Computational fluid dynamics- (CFD-) based component-level numerical simulation technology has been widely used in the design of aeroengines. However, due to the strong coupling effects between components, the numerical simulation of the whole engine considering the full three-dimensional flow and multi-component chemical reaction is still very difficult at present. Aimed at this problem, an efficient implicit solver, ‘sprayDyMFoam’ for an unstructured mesh, is developed in this paper based on the Sunway TaihuLight supercomputer. This sprayDyMFoam solver improves the PIMPLE algorithm in the solution of aerodynamic force and adjusts the existing droplet atomization model in the solution of the combustion process so as to meet the matching situation between components and the combustion chamber in the solution process. Meanwhile, the parallel communication mechanism of AMI boundary processing is optimized based on the hardware environment of the Sunway supercomputer. The sprayDyMFoam solver is used to simulate a typical double-rotor turbofan engine: the calculation capacity and efficiency meet the use requirements, and the obtained compressor performance can form a good match with the test. The research proposed in this paper has strong application value in high-confidence computing, complex phenomenon capturing, and time and cost reduction for aeroengine development.
Epidemic Waves and Exact Solutions of a Sequence of Nonlinear Differential Equations Connected to the SIR Model of Epidemics
Authors: Vitanov Nikolay K. , Vitanov Kaloyan N.
Published: March 2023

The SIR model of epidemic spreading can be reduced to a nonlinear differential equation with an exponential nonlinearity. This differential equation can be approximated by a sequence of nonlinear differential equations with polynomial nonlinearities. The equations from the obtained sequence are treated by the Simple Equations Method (SEsM). This allows us to obtain exact solutions to some of these equations. We discuss several of these solutions. Some (but not all) of the obtained exact solutions can be used for the description of the evolution of epidemic waves. We discuss this connection. In addition, we use two of the obtained solutions to study the evolution of two of the COVID-19 epidemic waves in Bulgaria by a comparison of the solutions with the available data for the infected individuals.
WGM-dSAGA: Federated Learning Strategies with Byzantine Robustness Based on Weighted Geometric Median
Authors: Wang Xiaoxue , Zhang Hongqi , Bilal Anas , Long Haixia , Liu Xiaowen
Published: March 2023

Federated learning techniques accomplish federated modeling and share global models without sharing data. Federated learning offers a good answer to complex data and privacy security issues. Although there are many ways to target federated learning, Byzantine attacks are the ones we concentrate on. Byzantine attacks primarily impede learning by tampering with the local model parameters provided by a client to the master node throughout the federation learning process, leading to a final global model that diverges from the optimal solution. To address this problem, we combine aggregation rules with Byzantine robustness using a gradient descent optimization algorithm based on variance reduction. We propose a WGM-dSAGA method with Byzantine robustness, called weighted geometric median-based distributed SAGA. We replace the original mean aggregation strategy in the distributed SAGA with a robust aggregation rule based on weighted geometric median. When less than half of the clients experience Byzantine attacks, the experimental results demonstrate that our proposed WGM-dSAGA approach is highly robust to different Byzantine attacks. Our proposed WGM-dSAGA algorithm provides the optimal gap and variance under a Byzantine attack scenario.
Cascaded AC-DC Power Conversion Interface for Charging Battery
Authors: Wu Jinn-Chang , Jou Hurng-Liahng , Chen Fu-Zen , Li Jung-Peng
Published: March 2023

This paper develops a cascaded AC-DC power conversion interface (CADPCI) to convert AC power to charge the battery set. The proposed CADPCI is composed of a cascaded converter (CC) and a dual-input buck converter (DIBC). The CC is formed by connecting a full-bridge converter (FBC) and a bridgeless rectifier (BLR) in series. The CADPCI generates an 11-level input voltage and performs unity power factor correction. The switching loss is reduced because only the FBC with a lower DC port voltage is switched at a high frequency. The DIBC uses a buck converter and a selection switch set to generate a two-level DC voltage on the DC port of the BLR. By controlling the DC input voltage of the buck converter, the injected power of the BLR can match the input power of the utility. Therefore, the FBC does not require to handle the real power, saving an isolated converter for regulating the DC port voltage of the FBC, thus simplifying the power circuit of the CC. The buck converter also acts as a DC active filter to filter out low-frequency ripples of the charging current. A prototype is constructed to verify the performance of the proposed CADPCI.
Determinants of Bank Closures: What Ensures Sustainable Profitability in Mobile Banking?
Authors: Cho Soohyung , Lee Zoonky , Hwang Sewoong , Kim Jonghyuk
Published: March 2023

Owing to the recent increase in mobile banking customers, studies exploring self-service channels and customer responses as distribution channels in the retail banking industry are also rapidly expanding. Moreover, with the emergence of big data and a series of artificial intelligence (AI) technologies, customer pattern analysis using deep learning, insurance fraud prevention, software development and various types of blockchain-based FinTech technologies, offline banks are disappearing. Accordingly, many commercial banks are attempting to find technological alternatives. However, maintaining a profitable bank branch is a crucial factor in the relationship between service quality and customer satisfaction because excellent service quality prevents existing customers from leaving. This study sought to quantitatively prove the change in customer service quality and profit due to the introduction of technology in the financial industry. We microscopically compared the effects between bank branch closures and changes in net profit using a time-series analysis. Specifically, we quantitatively analyzed actual customer attrition behavior with a time-series analysis across the three quarters before and after the closure of 88 branches of major commercial banks in South Korea in the Seoul metropolitan area and nearby cities. The findings prove that branch closures and multi-channel effects in the financial sector are gradually being resolved through immediate technology acceptance, contrary to popular concern.
Detection of Vulnerabilities by Incorrect Use of Variable Using Machine Learning
Authors: Park Jihyun , Shin Jaeyoung , Choi Byoungju
Published: March 2023

Common Weakness Enumeration (CWE) refers to a list of faults caused from software or hardware. The CWE includes the faults related to programming language and security. We propose a technique to detect the vulnerabilities from incorrect use of a variable in C language. There are various static/dynamic methods to detect the variable vulnerabilities. However, when analyzing the vulnerabilities, a static technique causes a lot of false alarms, meaning that there is no fault in the actual implementation. When monitoring the variable via the static analysis, there is a great overhead during execution, so its application is not easy in a real environment. In this paper, we propose a method to reduce false alarms and detect vulnerabilities by performing static analysis and dynamic verification using machine learning. Our method extracts information on variables through static analysis and detects defects through static analysis results and execution monitoring of the variables. In this process, it is determined whether the currently used variable values are valid and whether the variables are used in the correct order by learning the initial values and permissible range of the variables using machine learning techniques. We implemented our method as VVDUM (Variable Vulnerability Detector Using Machine learning). We conducted the comparative experiment with the existing static/dynamic analysis tools. As a result, compared with other tools with the rate of variable vulnerability detection between 9.17~18.5%, ours had that of 89.5%. In particular, VVDUM detects ‘defects out of the range of valid’ that are difficult to detect with existing methods, and the overhead due to defect detection is small. In addition, there were a few overheads at run time that were caused during data collection for detection of a fault.
Enhanced Embedding Capacity for Data Hiding Approach Based on Pixel Value Differencing and Pixel Shifting Technology
Authors: Huang Cheng-Ta , Shongwe Njabulo Sinethemba , Weng Chi-Yao
Published: March 2023

Data hiding algorithms can achieve the issue of information security when secret data are transmitted via the public network. This paper proposes a novel data-hiding scheme based on pixel value differencing and pixel shifting to increase embedding capacity and visual quality. In the proposed method, the cover image is first divided into nonoverlapping blocks, and eight groups of different values are generated with the center pixel as the reference pixel to embed the secret message. The pixel shifting strategy is applied to adjust the stego image to improve its quality. Experimental results show that the proposed method has an embedding capacity of 740,000 bits with a peak signal-to-noise ratio value greater than 35 dB. Therefore, it is undetected by the human eye. Other compared state-of-the-art schemes have embedding capacities of 51,219 bits, 70,217 bits, and 104,055 bits, which are lower than the proposed methods’ 740,000 bits. The RS, chi-square, and rotation attack analyses prove that the proposed method can withstand security attacks. Thus, the proposed method performs better than other state-of-the-art methods with respect to embedding capacity and ability to withstand attacks.
Intelligent Decision Support System for Differential Diagnosis of Chronic Odontogenic Rhinosinusitis Based on U-Net Segmentation
Authors: Alekseeva Victoria , Nechyporenko Alina , Frohme Marcus , Gargin Vitaliy , Meniailov Ievgen , Chumachenko Dmytro
Published: March 2023

The share of chronic odontogenic rhinosinusitis is 40% among all chronic rhinosinusitis. Using automated information systems for differential diagnosis will improve the efficiency of decision-making by doctors in diagnosing chronic odontogenic rhinosinusitis. Therefore, this study aimed to develop an intelligent decision support system for the differential diagnosis of chronic odontogenic rhinosinusitis based on computer vision methods. A dataset was collected and processed, including 162 MSCT images. A deep learning model for image segmentation was developed. A 23 convolutional layer U-Net network architecture has been used for the segmentation of multi-spiral computed tomography (MSCT) data with odontogenic maxillary sinusitis. The proposed model is implemented in such a way that each pair of repeated 3 × 3 convolutions layers is followed by an Exponential Linear Unit instead of a Rectified Linear Unit as an activation function. The model showed an accuracy of 90.09%. To develop a decision support system, an intelligent chatbot allows the user to conduct an automated patient survey and collect patient examination data from several doctors of various profiles. The intelligent information system proposed in this study made it possible to combine an image processing model with a patient interview and examination data, improving physician decision-making efficiency in the differential diagnosis of Chronic Odontogenic Rhinosinusitis. The proposed solution is the first comprehensive solution in this area.
Improvement of Municipal Solid Waste Syngas Premixed Flame with Cellular Structure on a Flat Burner
Authors: Kaewpradap Amornrat , Sarmarnjit Paweenuch , Korkeatkangwan Pisit , Sawatnuchart Kritchaniphat , Jugjai Sumrerng
Published: March 2023

This research was conducted to study the flame instability of syngas derived from raw municipal solid waste (MSW) and its potential as a natural gas (NG) replacement in power generation. MSW syngas is a mixture of various components such as methane (CH4), nitrogen (N2), oxygen (O2), and hydrogen (H2), whereas NG is mainly composed of CH4 (>70%) and CO2 (>10%). The flame characteristics of these two gases are quite different thus a direct replacement of NG with MSW syngas is impossible. Improvements to MSW syngas combustion are needed through the augmentation of the gas with CH4 and H2 active additives at various ratios so that its flame characteristics are comparable to those of NG. A typical MSW syngas composed of 16.2% methane (CH4), 13.5% hydrogen (H2), 69.1% nitrogen (N2), and 0.6% oxygen (O2) (by vol.) is available in Thailand with great potential for use as an NG replacement. In this study, this gas is used as a representative fuel for improvement and is referred to as simulated Syngas 1. Its premixed flame was studied using a McKenna flat burner to understand its flame instability. Various percentages of CH4 and H2 were added to Syngas 1. Its flame characteristics were measured and compared to those of NG. These characteristics included the cellular flame, cell size, flat flame, flammability limit, and flame temperature. The results showed that the flame instability of Syngas 1 was significantly suppressed by adding minimal amounts of CH4 and H2. The new composition of Syngas 1 consisted of 19.3% methane (CH4), 19.0% hydrogen (H2), 61.2% nitrogen (N2), and 0.5% oxygen (O2) (by vol.). It yielded flame characteristics that were comparable to those of an NG flame. This study shows that MSW syngas can potentially replace NG in power generation.
Investment and Innovation Activity of Renewable Energy Sources in the Electric Power Industry in the South-Eastern Region of Ukraine
Authors: Sala Dariusz , Bashynska Iryna , Pavlova Olena , Pavlov Kostiantyn , Chorna Nelia , Chornyi Roman
Published: March 2023

Nowadays, the Ukrainian electricity industry is experiencing difficult conditions, as it is operating in a mode of depletion of its production potential. At the same time, the transition to sustainable and renewable energy is the necessary basis for the country’s welfare and for ensuring its energy security. Therefore, today we cannot do without the additional attraction of sources of funding from investors. The purpose of the survey is to study the pattern and effectiveness of investments and identify links and dependencies between key technical and economic parameters and investments in renewable energy sources. To achieve this goal, the authors divided the study into four successive stages, which made it possible to study the subject of the study comprehensively. As a result of the study, results have been obtained that complement the existing theoretical, methodological, and practical developments. Mathematical calculations (using the example of the largest wind power plants in the south-eastern region) revealed transparent relationships and dependencies between the critical technical and economic parameters of the WPP of South-Eastern Ukraine and investments in the wind energy sector. Among them: the installation of 1 MW of additional WPP generating capacity requires an average of EUR 1.51 million of investment resources, and the production of one additional kWh of electricity requires an investment EUR 0.42 euros; therefore, providing an additional thousand households with WPP electricity is possible with an investment of EUR 1.345 million.
Induced Navier’s Slip with CNTS on a Stretching/Shrinking Sheet under the Combined Effect of Inclined MHD and Radiation
Authors: Shettar Mahabaleshwar Ulavathi. , Rudraiah Mahesh , Bragard Jean , Laroze David
Published: March 2023

The present article investigates viscous fluid flow’s heat and mass transfers over a stretching/shrinking sheet using the single and multi-wall carbon nanotube models. The analysis considers the effects of thermal radiation, induced slip, mass transpiration, and inclined magnetic force. The effect of the carbon nanotube model on fluid flow has not been considered in previous studies. By exploiting the similarity variable, the governing nonlinear partial differential equations are converted into nonlinear ordinary differential equation. The derived equations are solved analytically, and we obtained an exact solution for the velocity and energy conservation equation. The physical parameters of interest such as induced slip parameter, suction/injection, magnetic field, thermal radiation, and shear stress are analyzed and presented graphically. In particular, we show that the fluid flow in a single wall carbon nanotube transfers more energy than the multivalued nanotubes.
Prevention of Wildfires Using an AI-Based Open Conductor Fault Detection Method on Overhead Line
Authors: Che Junsoo , Kim Taehun , Pyo Suhan , Park Jaedeok , An Byeonghyeon , Park Taesik
Published: March 2023

Overhead lines that are exposed to the outdoors are susceptible to faults such as open conductors on weak points and disconnection caused by external factors such as typhoons. Arcs that occur during disconnection generate energy at a high heat of over 10,000 °C, requiring swift fault shut-off. However, most conventional fault detection methods to protect electrical power systems detect an overcurrent; thus, they can only detect faults after the line is disconnected and the cross-section of the line that generates the arc discharge makes contact with another line or the ground, causing a high risk of fire. Furthermore, in the case of ground faults owing to the disconnection of overhead lines, the load and the grounding impedance are not parallel. Therefore, in the case of the fault current not exceeding the threshold or a high impedance fault due to the high grounding impedance of the surrounding environment, such as grass or trees, it is difficult to determine overhead line faults with conventional fault detection methods. To solve these issues, this paper proposes an AI-based open conductor fault detection method on overhead lines that can clear the fault before the falling open conductor line comes into contact with the ground’s surface so as to prevent fire. The falling time according to the height and span of the overhead line was calculated using a falling conductor model for the overhead line, to which the pendulum motion was applied. The optimal input data cycle that enables fault detection before a line–ground fault occurs was derived. For artificial intelligence learning to prevent wildfires, the voltage and current signals were collected through a total of 432 fault simulations and were wavelet-transformed with a deep neural network to verify the method. The proposed total scheme was simulated and verified with MATLAB.
Aerodynamic Drag Reduction by the Trapezoid Spanwise Groove Inspired by Pigeon Feathers
Authors: Wang Yanqing , Wei Yuju , Weng Ding , Wang Jiadao
Published: March 2023

Inspired by pigeon feathers, the drag-reducing contribution of spanwise grooves was studied. Surface topography of the wing feather was scanned by an instrument of white light interference. Three types of grooves of triangle, rectangle, and trapezoid were adopted based on the unsymmetric microstructures found on the feather surface. Numerical simulations were conducted to analyze drag-reducing mechanisms. According to the simulation results, the rectangular groove reduced the wall shear stress more efficiently but with greater additional pressure drag, while the triangular groove was the opposite. For the trapezoidal groove similar to the feather structure, drag reduction was the best out of the three. Wind tunnel experiments for the trapezoidal groove were performed by using a cylindrical model and large-area plate. Drag reduction was confirmed from the cylindrical model at a series of velocities from 15 m/s to 90 m/s (about 16% at velocity of 30 m/s and about 8.5% at velocity of 60 m/s). Drag reduction was also obtained from the plate model at a velocity range of 30 m/s to 75 m/s (about 19% at the velocity of 60 m/s), which worked for a wide range of velocity and was more meaningful for the application.
The Maximum Power Point Tracking (MPPT) of a Partially Shaded PV Array for Optimization Using the Antlion Algorithm
Authors: Abbass Muhammad Jamshed , Lis Robert , Saleem Faisal
Published: March 2023

The antlion optimizer (ALO) algorithm is used in this article for maximum power point tracking (MPPT) of a solar array. The solar array consists of a single module, while there are 20 cells in the module. The voltage and current ratings of each cell are 2 V and 2.5 A, making a 100 W array in ideal condition. However, the voltage and current characteristics of the PV cell are unable to achieve maximum power. Therefore, the ALO was used for MPPT. The results of the ALO are compared with the traditional metaheuristic approaches, perturb and observe (P&O) and flower pollination (FP) algorithms. Comparison of the ALO with the stated algorithms is conducted for two cases: when solar irradiance is 1000 W/m2 and when it drops to 200 W/m2 at first then reaches 1000 W/m2. The change of irradiance is performed to simulate the partial shading condition. The simulation results depict that maximum power for the first case using the ALO reaches 91.3 W in just 0.05 s, while the P&O and PFA reach 90 W after 0.64 and 2 s, respectively. For the case of partial shading, maximum power using the ALO drops to 55 W when irradiance decreases to 200 W/m2 and then increases with the increase in irradiance reaching 91.3 W which clearly shows that the ALO outperforms the P&O and FPA.
Experiments and Modeling of Solid–Solid Phase Change Material-Loaded Plaster to Enhance Building Energy Efficiency
Authors: Farulla Girolama Airò , Brancato Vincenza , Palomba Valeria , Zhang Yannan , Dino Giuseppe E. , Frazzica Andrea
Published: March 2023

In this paper, cement mortar IN200 integrated with solid–solid PlusIce X25 commercial PCM was fully characterized for the first time via experimental tests and numerical simulations. An experimental setup was designed and built to evaluate the thermal performance of the composite. Experimental results confirmed the expected advantages of the PCM-loaded plaster in terms of inner surface temperature, inbound heat flux reduction, and the enhanced damping effect on the average temperature. The experimental results were used to validate and calibrate a finite element model implemented in COMSOL Multiphysics® 5.6. The model was adopted to carry out a parametric analysis assessing the influence of PCM mass fraction, phase transition temperature, and PCM mortar thickness. The composite thickness was the most influential parameter, resulting in an energy saving increase from 3.29% to 72.72% as it was increased from 10 mm to 30 mm. Moreover, the model was used in a set of dynamic simulations, reproducing real Mediterranean climatic conditions to capture the transition process for a long period in buildings. The PCM mortar located on the interior side exhibited the highest reduction in both heat flux and inner surface temperature, representing a simple approach to achieving the best thermal comfort conditions.
Drilling in Gas Hydrates: Managing Gas Appearance Risks
Authors: Gizatullin Ruslan , Dvoynikov Mikhail , Romanova Natalya , Nikitin Victor
Published: March 2023

This article provides a detailed analysis of issues related to the complications while drilling in hydrate-bearing rocks of permafrost areas. The goal of the paper is to develop recommendations for preventing gas occurrence while drilling gas hydrate deposits and to eliminate gas leakiness of the intercasing space of the well. The results of modeling the effect of drilling mud injection on the temperature field of the well are presented. It is revealed that the most significant role is played by the injection rate of drilling mud and its temperature. The recommended flow rate of the process fluid should be within 0.30–0.45 m3/s, and its temperature should not exceed 20 °C. Controlling the parameters of drilling mud and its flow rate allows for avoiding intensive gas occurrence while drilling in gas hydrates. The presence of gas hydrates may be the cause of gas leakiness of the intercasing space in the permafrost area. One of the ways to eliminate leakiness is colmatation (clogging). A method of preventing leaks in the intercasing space of the gas well is the use of colmatating solution. An aqueous solution of sodium silicate with the addition of 2% polymer is used as a colmatating composition.