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Article Citation - WoS: 13Citation - Scopus: 13Comparison of Physicochemical Properties of Two Types of Polyepichlorohydrin-Based Anion Exchange Membranes for Reverse Electrodialysis(Mdpi, 2022) Karakoc, Ezgi; Guler, EnverThe development of the most effective, suitable and economic ion-exchange membranes is crucial for reverse electrodialysis (RED)-the most widely studied process to harvest salinity gradient energy from mixing seawater and river water. RED utilizes two types of membranes as core elements, namely cation exchange membranes (CEM) and anion exchange membranes (AEM). Since the preparation of AEMs is more complex compared to CEMs, the design and development of anion exchange membranes have been the focus in this study. Homogeneous AEMs based on two types of polyepichlorohydrin (PECH) with different chlorine amounts (PECH-H, 37 wt% and PECH-C, 25 wt%) were synthesized, and first-time benchmarking of the membrane properties was conducted. In addition to physicochemical membrane properties, some instrumental analyses such as SEM, FTIR and DSC were investigated to characterize these anion-exchange membranes. Based on the results, although the PECH-H-type membrane had enhanced ion-exchange properties, PECH-C-based anion-exchange membranes exhibited a higher power density of 0.316 W/m(2) in a lab-scale RED system. Evidently, there is room for the development of new types of PECH-C-based AEMs with great potential for energy generation in the RED process.Article Citation - WoS: 4Citation - Scopus: 4Effects of Cerium Oxide on Kidney and Liver Tissue Damage in an Experimental Myocardial Ischemia-Reperfusion Model of Distant Organ Damage(Mdpi, 2024) Gunes, Isin; Dursun, Ali Dogan; Ozdemir, Cagri; Kucuk, Aysegul; Sezen, Saban Cem; Arslan, Mustafa; Ozer, AbdullahBackground and Objectives: Ischemia-reperfusion (I/R) injury is a process in which impaired perfusion is restored by restoring blood flow and tissue recirculation. Nanomedicine uses cutting-edge technologies that emerge from interdisciplinary influences. In the literature, there are very few in vivo and in vitro studies on how cerium oxide (CeO2) affects systemic anti-inflammatory response and inflammation. Therefore, in our study, we aimed to investigate whether CeO2 administration has a protective effect against myocardial I/R injury in the liver and kidneys. Materials and Methods: Twenty-four rats were randomly divided into four groups after obtaining approval from an ethics committee. A control (group C), cerium oxide (group CO), IR (group IR), and Cerium oxide-IR (CO-IR group) groups were formed. Intraperitoneal CeO2 was administered at a dose of 0.5 mg/kg 30 min before left thoracotomy and left main coronary (LAD) ligation, and myocardial muscle ischemia was induced for 30 min. After LAD ligation was removed, reperfusion was performed for 120 min. All rats were euthanized using ketamine, and blood was collected. Liver and kidney tissue samples were evaluated histopathologically. Serum AST (aspartate aminotransferase), ALT (alanine aminotransaminase), GGT (gamma-glutamyl transferase), glucose, TOS (Total Oxidant Status), and TAS (Total Antioxidant Status) levels were also measured. Results: Necrotic cell and mononuclear cell infiltration in the liver parenchyma of rats in the IR group was observed to be significantly increased compared to the other groups. Hepatocyte degeneration was greater in the IR group compared to groups C and CO. Vascular vacuolization and hypertrophy, tubular degeneration, and necrosis were increased in the kidney tissue of the IR group compared to the other groups. Tubular dilatation was significantly higher in the IR group than in the C and CO groups. TOS was significantly higher in all groups than in the IR group (p < 0.0001, p < 0.0001, and p = 0.006, respectively). However, TAS level was lower in the IR group than in the other groups (p = 0.002, p = 0.020, and p = 0.031, respectively). Renal and liver histopathological findings decreased significantly in the CO-IR group compared to the IR group. A decrease in the TOS level and an increase in the TAS level were found compared to the IR group. The AST, ALT, GGT, and Glucose levels are shown. Conclusions: CeO2 administered before ischemia-reperfusion reduced oxidative stress and ameliorated IR-induced damage in distant organs. We suggest that CeO2 exerts protective effects in the myocardial IR model.Article Citation - WoS: 8Citation - Scopus: 9Propagation Measurements for Iqrf Network in an Urban Environment(Mdpi, 2022) Bouzidi, Mohammed; Dalveren, Yaser; Mohamed, Marshed; Dalveren, Yaser; Moldsvor, Arild; Cheikh, Faouzi Alaya; Derawi, Mohammad; Dalveren, Yaser; Department of Electrical & Electronics Engineering; Department of Electrical & Electronics EngineeringRecently, IQRF has emerged as a promising technology for the Internet of Things (IoT), owing to its ability to support short- and medium-range low-power communications. However, real world deployment of IQRF-based wireless sensor networks (WSNs) requires accurate path loss modelling to estimate network coverage and other performances. In the existing literature, extensive research on propagation modelling for IQRF network deployment in urban environments has not been provided yet. Therefore, this study proposes an empirical path loss model for the deployment of IQRF networks in a peer-to-peer configured system where the IQRF sensor nodes operate in the 868 MHz band. For this purpose, extensive measurement campaigns are conducted outdoor in an urban environment for Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) links. Furthermore, in order to evaluate the prediction accuracy of well-known empirical path loss models for urban environments, the measurements are compared with the predicted path loss values. The results show that the COST-231 Walfisch-Ikegami model has higher prediction accuracy and can be used for IQRF network planning in LoS links, while the COST-231 Hata model has better accuracy in NLoS links. On the other hand, the effects of antennas on the performance of IQRF transceivers (TRs) for LoS and NLoS links are also scrutinized. The use of IQRF TRs with a Straight-Line Dipole Antenna (SLDA) antenna is found to offer more stable results when compared to IQRF (TRs) with Meander Line Antenna (MLA) antenna. Therefore, it is believed that the findings presented in this article could offer useful insights for researchers interested in the development of IoT-based smart city applications.Article Citation - WoS: 4Citation - Scopus: 8Real-Time Learning and Monitoring System in Fighting Against Sars-Cov in a Private Indoor Environment(Mdpi, 2022) Erisen, SerdarThe SARS-CoV-2 virus has posed formidable challenges that must be tackled through scientific and technological investigations on each environmental scale. This research aims to learn and report about the current state of user activities, in real-time, in a specially designed private indoor environment with sensors in infection transmission control of SARS-CoV-2. Thus, a real-time learning system that evolves and updates with each incoming piece of data from the environment is developed to predict user activities categorized for remote monitoring. Accordingly, various experiments are conducted in the private indoor space. Multiple sensors, with their inputs, are analyzed through the experiments. The experiment environment, installed with microgrids and Internet of Things (IoT) devices, has provided correlating data of various sensors from that special care context during the pandemic. The data is applied to classify user activities and develop a real-time learning and monitoring system to predict the IoT data. The microgrids were operated with the real-time learning system developed by comprehensive experiments on classification learning, regression learning, Error-Correcting Output Codes (ECOC), and deep learning models. With the help of machine learning experiments, data optimization, and the multilayered-tandem organization of the developed neural networks, the efficiency of this real-time monitoring system increases in learning the activity of users and predicting their actions, which are reported as feedback on the monitoring interfaces. The developed learning system predicts the real-time IoT data, accurately, in less than 5 milliseconds and generates big data that can be deployed for different usages in larger-scale facilities, networks, and e-health services.Review Citation - WoS: 67Citation - Scopus: 77Atmospheric Pressure Plasma Surface Treatment of Polymers and Influence on Cell Cultivation(Mdpi, 2021) Sasmazel, Hilal Turkoglu; Alazzawi, Marwa; Alsahib, Nabeel Kadim AbidAtmospheric plasma treatment is an effective and economical surface treatment technique. The main advantage of this technique is that the bulk properties of the material remain unchanged while the surface properties and biocompatibility are enhanced. Polymers are used in many biomedical applications; such as implants, because of their variable bulk properties. On the other hand, their surface properties are inadequate which demands certain surface treatments including atmospheric pressure plasma treatment. In biomedical applications, surface treatment is important to promote good cell adhesion, proliferation, and growth. This article aim is to give an overview of different atmospheric pressure plasma treatments of polymer surface, and their influence on cell-material interaction with different cell lines.Article Citation - WoS: 20Citation - Scopus: 24A Novel Hybrid Machine Learning Based System To Classify Shoulder Implant Manufacturers(Mdpi, 2022) Sivari, Esra; Guzel, Mehmet Serdar; Bostanci, Erkan; Mishra, AlokIt is necessary to know the manufacturer and model of a previously implanted shoulder prosthesis before performing Total Shoulder Arthroplasty operations, which may need to be performed repeatedly in accordance with the need for repair or replacement. In cases where the patient's previous records cannot be found, where the records are not clear, or the surgery was conducted abroad, the specialist should identify the implant manufacturer and model during preoperative X-ray controls. In this study, an auxiliary expert system is proposed for classifying manufacturers of shoulder implants on the basis of X-ray images that is automated, objective, and based on hybrid machine learning models. In the proposed system, ten different hybrid models consisting of a combination of deep learning and machine learning algorithms were created and statistically tested. According to the experimental results, an accuracy of 95.07% was achieved using the DenseNet201 + Logistic Regression model, one of the proposed hybrid machine learning models (p < 0.05). The proposed hybrid machine learning algorithms achieve the goal of low cost and high performance compared to other studies in the literature. The results lead the authors to believe that the proposed system could be used in hospitals as an automatic and objective system for assisting orthopedists in the rapid and effective determination of shoulder implant types before performing revision surgery.Article Citation - WoS: 5Citation - Scopus: 8A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification(Mdpi, 2024) Kadhim, Yezi Ali; Guzel, Mehmet Serdar; Mishra, AlokMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep learning techniques, which were based on a convolutional neural network (CNN) or autoencoder, to extract features and combine them with the next step of the meta-heuristic algorithm in order to select optimal features using the particle swarm optimization (PSO) algorithm. This combination sought to reduce the dimensionality of the datasets while maintaining the original performance of the data. This is considered an innovative method and ensures highly accurate classification results across various medical datasets. Several classifiers were employed to predict the diseases. The COVID-19 dataset found that the highest accuracy was 99.76% using the combination of CNN-PSO-SVM. In comparison, the brain tumor dataset obtained 99.51% accuracy, the highest accuracy derived using the combination method of autoencoder-PSO-KNN.Article Citation - WoS: 6Citation - Scopus: 6Further Development of Polyepichlorohydrin Based Anion Exchange Membranes for Reverse Electrodialysis by Tuning Cast Solution Properties(Mdpi, 2022) Eti, Mine; Cihanoglu, Aydin; Guler, Enver; Gomez-Coma, Lucia; Altiok, Esra; Arda, Muserref; Kabay, NalanRecently, there have been several studies done regarding anion exchange membranes (AEMs) based on polyepichlorohydrin (PECH), an attractive polymer enabling safe membrane fabrication due to its inherent chloromethyl groups. However, there are still undiscovered properties of these membranes emerging from different compositions of cast solutions. Thus, it is vital to explore new membrane properties for sustainable energy generation by reverse electrodialysis (RED). In this study, the cast solution composition was easily tuned by varying the ratio of active polymer (i.e., blend ratio) and quaternary agent (i.e., excess diamine ratio) in the range of 1.07-2.00, and 1.00-4.00, respectively. The membrane synthesized with excess diamine ratio of 4.00 and blend ratio of 1.07 provided the best results in terms of ion exchange capacity, 3.47 mmol/g, with satisfactory conductive properties (area resistance: 2.4 omega center dot cm(2), electrical conductivity: 6.44 mS/cm) and high hydrophilicity. RED tests were performed by AEMs coupled with the commercially available Neosepta CMX cation exchange membrane (CEMs).Article Citation - WoS: 4Citation - Scopus: 6A Conceptual Design of Smart Management System for Flooding Disaster(Mdpi, 2021) Ibrahim, Thaer; Mishra, AlokDisasters pose a real threat to the lives and property of citizens; therefore, it is necessary to reduce their impact to the minimum possible. In order to achieve this goal, a framework for enhancing the current disaster management system was proposed, called the smart disaster management system. The smart aspect of this system is due to the application of the principles of information and communication technology, especially the Internet of Things. All participants and activities of the proposed system were clarified by preparing a conceptual design by using The Unified Modeling Language diagrams. This effort was made to overcome the lack of citizens' readiness towards the use of information and communication technology as well as increase their readiness towards disasters. This study aims to develop conceptual design that can facilitate in development of smart management system for flooding disaster. This will assist in the design process of the Internet of Things systems in this regard.Article Citation - WoS: 36Citation - Scopus: 68Cybersecurity Enterprises Policies: a Comparative Study(Mdpi, 2022) Mishra, Alok; Alzoubi, Yehia Ibrahim; Gill, Asif Qumer; Anwar, Memoona JaveriaCybersecurity is a critical issue that must be prioritized not just by enterprises of all kinds, but also by national security. To safeguard an organization's cyberenvironments, information, and communication technologies, many enterprises are investing substantially in cybersecurity these days. One part of the cyberdefense mechanism is building an enterprises' security policies library, for consistent implementation of security controls. Significant and common cybersecurity policies of various enterprises are compared and explored in this study to provide robust and comprehensive cybersecurity knowledge that can be used in various enterprises. Several significant common security policies were identified and discussed in this comprehensive study. This study identified 10 common cybersecurity policy aspects in five enterprises: healthcare, finance, education, aviation, and e-commerce. We aimed to build a strong infrastructure in each business, and investigate the security laws and policies that apply to all businesses in each sector. Furthermore, the findings of this study reveal that the importance of cybersecurity requirements differ across multiple organizations. The choice and applicability of cybersecurity policies are determined by the type of information under control and the security requirements of organizations in relation to these policies.
