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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: 10Citation - Scopus: 15Toughening Mechanism Analysis of Recycled Rubber-Based Composites Reinforced With Glass Bubbles, Glass Fibers and Alumina Fibers(Mdpi, 2021) Kabakci, Gamze Cakir; Aslan, Ozgur; Bayraktar, EminRecycling of materials attracts considerable attention around the world due to environmental and economic concerns. Recycled rubber is one of the most commonly used recyclable materials in a number of industries, including automotive and aeronautic because of their low weight and cost efficiency. In this research, devulcanized recycled rubber-based composites are designed with glass bubble microsphere, short glass fiber, aluminum chip and fine gamma alumina fiber (gamma-Al2O3) reinforcements. After the determination of the reinforcements with matrix, bending strength and fracture characteristics of the composite are investigated by three-point bending (3PB) tests. Halpin-Tsai homogenization model is adapted to the rubber-based composites to estimate the moduli of the composites. Furthermore, the relevant toughening mechanisms for the most suitable reinforcements are analyzed and stress intensity factor, K-Ic and critical energy release rate, G(Ic) in mode I are determined by 3PB test with single edge notch specimens. In addition, 3PB tests are simulated by finite element analysis and the results are compared with the experimental results. Microstructural and fracture surfaces analysis are carried out by means of scanning electron microscopy (SEM). Mechanical test results show that the reinforcement with glass bubbles, aluminum oxide ceramic fibers and aluminum chips generally increase the fracture toughness of the composites.Article Citation - WoS: 17Citation - Scopus: 24Iot Platform for Seafood Farmers and Consumers(Mdpi, 2020) Jaeger, Bjorn; Mishra, Alok; Jæger, BjørnThere has been a strong growth in aquatic products supported by the global seafood industry. Consumers demand information transparency to support informed decisions and to verify nutrition, food safety, and sustainable operations. Supporting these needs rests on the existence of interoperable Internet of Things (IoT) platforms for traceability that goes beyond the minimum "one up, one down" scheme required by regulators. Seafood farmers, being the source of both food and food-information, are critical to achieving the needed transparency. Traditionally, seafood farmers carry the costs of providing information, while downstream actors reap the benefits, causing limited provision of information. Now, global standards for labelling, data from IoT devices, and the reciprocity of utility from collecting data while sharing them represent great potential for farmers to generate value from traceability systems. To enable this, farmers need an IoT platform integrated with other IoT platforms in the value network. This paper presents a case study of an enterprise-level IoT platform for seafood farmers that satisfies consumers' end-to-end traceability needs while extracting data from requests for information from downstream actors.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: 10Citation - Scopus: 20A Comparison of the Ballistic Performances of Various Microstructures in Mil-A Armor Steel(Mdpi, 2020) Konca, ErkanDue to their advantageous properties, there is a growing interest in developing armor steels containing fully or partially bainitic microstructures. In this study, bainitic and martensitic microstructures were obtained in rolled homogeneous armor (RHA) steel samples and their ballistic protection performances were investigated. RHA (MIL-A-12560) steel samples were subjected to isothermal heat treatments at three different temperatures, where one temperature (360 degrees C) was above the martensite formation start (Ms) temperature of 336 degrees C while the other two (320 degrees C and 270 degrees C) were below. For the assessment of the ballistic protection performance, the kinetic energy losses of the 12.7 mm bullets fired at the test samples were determined. The promising nature of the bainite microstructure was confirmed as the sample isothermally treated at 360 degrees C provided approximately 10% higher ballistic protection as compared to the regular RHA sample of tempered martensite microstructure. However, the ballistic performances of the isothermally treated samples decreased as the treatment temperature went below the Ms temperature. Following the ballistic tests, hardness measurements, impact tests at -40 degrees C, and macro- and microstructural examinations of the samples were performed. No correlation was found between the hardness and impact energies of the samples and their ballistic performances.Article Citation - WoS: 18Citation - Scopus: 35Distributed Centrality Analysis of Social Network Data Using Mapreduce(Mdpi, 2019) Behera, Ranjan Kumar; Rath, Santanu Kumar; Misra, Sanjay; Damasevicius, Robertas; Maskeliunas, RytisAnalyzing the structure of a social network helps in gaining insights into interactions and relationships among users while revealing the patterns of their online behavior. Network centrality is a metric of importance of a network node in a network, which allows revealing the structural patterns and morphology of networks. We propose a distributed computing approach for the calculation of network centrality value for each user using the MapReduce approach in the Hadoop platform, which allows faster and more efficient computation as compared to the conventional implementation. A distributed approach is scalable and helps in efficient computations of large-scale datasets, such as social network data. The proposed approach improves the calculation performance of degree centrality by 39.8%, closeness centrality by 40.7% and eigenvalue centrality by 41.1% using a Twitter dataset.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.
