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Review Citation - WoS: 75Citation - Scopus: 122Hybrid Blockchain Platforms for the Internet of Things (iot): a Systematic Literature Review(Mdpi, 2022) Alkhateeb, Ahmed; Catal, Cagatay; Kar, Gorkem; Mishra, AlokIn recent years, research into blockchain technology and the Internet of Things (IoT) has grown rapidly due to an increase in media coverage. Many different blockchain applications and platforms have been developed for different purposes, such as food safety monitoring, cryptocurrency exchange, and secure medical data sharing. However, blockchain platforms cannot store all the generated data. Therefore, they are supported with data warehouses, which in turn is called a hybrid blockchain platform. While several systems have been developed based on this idea, a current state-of-the-art systematic overview on the use of hybrid blockchain platforms is lacking. Therefore, a systematic literature review (SLR) study has been carried out by us to investigate the motivations for adopting them, the domains at which they were used, the adopted technologies that made this integration effective, and, finally, the challenges and possible solutions. This study shows that security, transparency, and efficiency are the top three motivations for adopting these platforms. The energy, agriculture, health, construction, manufacturing, and supply chain domains are the top domains. The most adopted technologies are cloud computing, fog computing, telecommunications, and edge computing. While there are several benefits of using hybrid blockchains, there are also several challenges reported in this study.Article Citation - Scopus: 2The Effects of Paddy Cultivation and Microbiota Members on Arsenic Accumulation in Rice Grain(Mdpi, 2023) Ersoy Omeroglu, Esra; Bayer, Asli; Sudagidan, Mert; Ozalp, Veli Cengiz; Yasa, IhsanAccess to safe food is one of the most important issues. In this context, rice plays a prominent role. Because high levels of arsenic in rice grain are a potential concern for human health, in this study, we determined the amounts of arsenic in water and soil used in the rice development stage, changes in the arsC and mcrA genes using qRT-PCR, and the abundance and diversity (with metabarcoding) of the dominant microbiota. When the rice grain and husk samples were evaluated in terms of arsenic accumulation, the highest values (1.62 ppm) were obtained from areas where groundwater was used as irrigation water, whereas the lowest values (0.21 ppm) occurred in samples from the stream. It was observed that the abundance of the Comamonadaceae family and Limnohabitans genus members was at the highest level in groundwater during grain formation. As rice development progressed, arsenic accumulated in the roots, shoots, and rice grain. Although the highest arsC values were reached in the field where groundwater was used, methane production increased in areas where surface water sources were used. In order to provide arsenic-free rice consumption, the preferred soil, water source, microbiota members, rice type, and anthropogenic inputs for use on agricultural land should be evaluated rigorously.Article Citation - WoS: 3Citation - Scopus: 3Paper-Based Aptasensor Assay for Detection of Food Adulterant Sildenafil(Mdpi, 2024) Kavruk, Murat; Ozalp, Veli CengizSildenafil is used to treat erectile dysfunction and pulmonary arterial hypertension but is often illicitly added to energy drinks and chocolates. This study introduces a lateral flow strip test using aptamers specific to sildenafil for detecting its illegal presence in food. The process involved using graphene oxide SELEX to identify high-affinity aptamers, which were then converted into molecular gate structures on mesoporous silica nanoparticles, creating a unique signaling system. This system was integrated into lateral flow chromatography strips and tested on buffers and chocolate samples containing sildenafil. The method simplifies the lateral flow assay (LFA) for small molecules and provides a tool for signal amplification. The detection limit for these strips was found to be 68.2 nM (31.8 mu g/kg) in spiked food samples.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.Article Citation - WoS: 7Citation - Scopus: 8Finite Element Analysis of Frames With Reinforced Concrete Encased Steel Composite Columns(Mdpi, 2022) Tunc, Gokhan; Othman, Mohammed Moatasem; Mertol, Halit CenanStructural frame systems that consists of concrete-encased-steel-embedded composite columns and reinforced concrete beams are typically used in mid-rise to tall buildings. In order to understand their overall structural behavior, a total of 12 frame models with high and low ductility features were constructed and analyzed using LS-DYNA software. Two of these models were validated using the results of previously tested frames. The remaining 10 models were studied to predict the behavior of frames with varying concrete strengths, reinforcement configurations, and structural steel sections under vertical and lateral loads. The results were investigated in terms of cracks and failure patterns, load-deflection relationships, energy dissipation, and stiffness degradation. The analytical results indicated that the high ductile frame models showed slightly better lateral load carrying performances compared to low ductility frame models. Moreover, the analytical studies demonstrated that the existence of structural steel in a column, regardless of its cross-sectional shape, was the most important parameter in improving the lateral load carrying capacity of a frame.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: 5Space Efficiency in Tall Hotel Towers(Mdpi, 2024) Aslantamer, Ozlem Nur; Ilgin, Huseyin EmreMaximizing spatial utilization within tall buildings stands as a paramount planning consideration for ensuring project feasibility, particularly accentuated ins the context of hotel constructions. To date, no comprehensive study has addressed this issue while considering crucial architectural and structural planning factors. This article fills this gap by using a case study method based on data from 31 contemporary tall hotel towers. The findings revealed several key points: (i) central core typology was mostly utilized; (ii) prismatic buildings were the most prevalent forms; (iii) shear-walled frame systems were predominantly employed; (iv) concrete was the preferred choice for hotel construction; (v) the average space efficiency and the ratio of core area to gross floor area (GFA) averaged 81.2% and 16%, respectively; (vi) the range changed from a minimum of 70% to 4% to a maximum of 94% to 28%; and (vii) space efficiency showed an inverse relationship with the height of the building. It is anticipated that this paper will assist architects and structural engineers as well as builders involved in the planning of hotel developments.Article Citation - WoS: 7Citation - Scopus: 6Optimized Porous Carbon Particles From Sucrose and Their Polyethyleneimine Modifications for Enhanced Co2 Capture(Mdpi, 2024) Ari, Betul; Inger, Erk; Sunol, Aydin K.; Sahiner, NurettinCarbon dioxide (CO2), one of the primary greenhouse gases, plays a key role in global warming and is one of the culprits in the climate change crisis. Therefore, the use of appropriate CO2 capture and storage technologies is of significant importance for the future of planet Earth due to atmospheric, climate, and environmental concerns. A cleaner and more sustainable approach to CO2 capture and storage using porous materials, membranes, and amine-based sorbents could offer excellent possibilities. Here, sucrose-derived porous carbon particles (PCPs) were synthesized as adsorbents for CO2 capture. Next, these PCPs were modified with branched- and linear-polyethyleneimine (B-PEI and L-PEI) as B-PEI-PCP and L-PEI-PCP, respectively. These PCPs and their PEI-modified forms were then used to prepare metal nanoparticles such as Co, Cu, and Ni in situ as M@PCP and M@L/B-PEI-PCP (M: Ni, Co, and Cu). The presence of PEI on the PCP surface enables new amine functional groups, known for high CO2 capture ability. The presence of metal nanoparticles in the structure may be used as a catalyst to convert the captured CO2 into useful products, e.g., fuels or other chemical compounds, at high temperatures. It was found that B-PEI-PCP has a larger surface area and higher CO2 capture capacity with a surface area of 32.84 m(2)/g and a CO2 capture capacity of 1.05 mmol CO2/g adsorbent compared to L-PEI-PCP. Amongst metal-nanoparticle-embedded PEI-PCPs (M@PEI-PCPs, M: Ni, Co, Cu), Ni@L-PEI-PCP was found to have higher CO2 capture capacity, 0.81 mmol CO2/g adsorbent, and a surface area of 225 m(2)/g. These data are significant as they will steer future studies for the conversion of captured CO2 into useful fuels/chemicals.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.
