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Article Citation - WoS: 47Citation - Scopus: 67Deep Learning Based Fall Detection Using Smartwatches for Healthcare Applications(Elsevier Sci Ltd, 2022) Sengul, Gokhan; Karakaya, Murat; Misra, Sanjay; Abayomi-Alli, Olusola O.; Damasevicius, RobertasWe implement a smart watch-based system to predict fall detection. We differentiate fall detection from four common daily activities: sitting, squatting, running, and walking. Moreover, we separate falling into falling from a chair and falling from a standing position. We develop a mobile application that collects the acceleration and gyroscope sensor data and transfers them to the cloud. In the cloud, we implement a deep learning algorithm to classify the activity according to the given classes. To increase the number of data samples available for training, we use the Bica cubic Hermite interpolation, which allows us to improve the accuracy of the neural network. The 38 statistical data features were calculated using the rolling update approach and used as input to the classifier. For activity classification, we have adopted the bi-directional long short-term memory (BiLSTM) neural network. The results demonstrate that our system can detect falling with an accuracy of 99.59% (using leave-one-activityout cross-validation) and 97.35% (using leave-one-subject-out cross-validation) considering all activities. When considering only binary classification (falling vs. all other activities), perfect accuracy is achieved.Article Citation - WoS: 5Citation - Scopus: 6A Novel Deep Learning-Based Framework With Particle Swarm Optimisation for Intrusion Detection in Computer Networks(Public Library Science, 2025) Yilmaz, Abdullah AsimIntrusion detection plays a significant role in the provision of information security. The most critical element is the ability to precisely identify different types of intrusions into the network. However, the detection of intrusions poses a important challenge, as many new types of intrusion are now generated by cyber-attackers every day. A robust system is still elusive, despite the various strategies that have been proposed in recent years. Hence, a novel deep-learning-based architecture for detecting intrusions into a computer network is proposed in this paper. The aim is to construct a hybrid system that enhances the efficiency and accuracy of intrusion detection. The main contribution of our work is a novel deep learning-based hybrid architecture in which PSO is used for hyperparameter optimisation and three well-known pre-trained network models are combined in an optimised way. The suggested method involves six key stages: data gathering, pre-processing, deep neural network (DNN) architecture design, optimisation of hyperparameters, training, and evaluation of the trained DNN. To verify the superiority of the suggested method over alternative state-of-the-art schemes, it was evaluated on the KDDCUP'99, NSL-KDD and UNSW-NB15 datasets. Our empirical findings show that the proposed model successfully and correctly classifies different types of attacks with 82.44%, 90.42% and 93.55% accuracy values obtained on UNSW-B15, NSL-KDD and KDDCUP'99 datasets, respectively, and outperforms alternative schemes in the literature.Article Citation - WoS: 4Citation - Scopus: 4The Effect of Cerium Oxide (ceo2) on Ischemia-Reperfusion Injury in Skeletal Muscle in Mice With Streptozocin-Induced Diabetes(Mdpi, 2024) Ozer, Abdullah; Sengel, Necmiye; Kucuk, Ayseguel; Yigman, Zeynep; Ozdemir, Cagri; Kilic, Yigit; Arslan, MustafaObjective: Lower extremity ischemia-reperfusion injury (IRI) may occur with trauma-related vascular injury and various vascular diseases, during the use of a tourniquet, in temporary clamping of the aorta in aortic surgery, or following acute or bilateral acute femoral artery occlusion. Mitochondrial dysfunction and increased basal oxidative stress in diabetes may cause an increase in the effects of increased reactive oxygen species (ROS) and mitochondrial dysfunction due to IRI. It is of great importance to examine therapeutic approaches that can minimize the effects of IRI, especially for patient groups under chronic oxidative stress such as DM. Cerium oxide (CeO2) nanoparticles mimic antioxidant enzymes and act as a catalyst that scavenges ROS. In this study, it was aimed to investigate whether CeO2 has protective effects on skeletal muscles in lower extremity IRI in mice with streptozocin-induced diabetes. Methods: A total of 38 Swiss albino mice were divided into six groups as follows: control group (group C, n = 6), diabetes group (group D, n = 8), diabetes-CeO2 (group DCO, n = 8), diabetes-ischemia/reperfusion (group DIR, n = 8), and diabetes-ischemia/reperfusion-CeO2 (group DIRCO, n = 8). The DCO and DIRCO groups were given doses of CeO2 of 0.5 mg/kg intraperitoneally 30 min before the IR procedure. A 120 min ischemia-120 min reperfusion period with 100% O-2 was performed. At the end of the reperfusion period, muscle tissues were removed for histopathological and biochemical examinations. Results: Total antioxidant status (TAS) levels were found to be significantly lower in group DIR compared with group D (p = 0.047 and p = 0.022, respectively). In group DIRCO, total oxidant status (TOS) levels were found to be significantly higher than in group DIR (p < 0.001). The oxidative stress index (OSI) was found to be significantly lower in group DIR compared with group DCO (p < 0.001). Paraoxanase (PON) enzyme activity was found to be significantly increased in group DIR compared with group DCO (p < 0.001). The disorganization and degeneration score for muscle cells, inflammatory cell infiltration score, and total injury score in group DIRCO were found to be significantly lower than in group DIR (p = 0.002, p = 0.034, and p = 0.001, respectively). Conclusions: Our results confirm that CeO2, with its antioxidative properties, reduces skeletal muscle damage in lower extremity IRI in diabetic mice.Article Citation - WoS: 17Citation - Scopus: 17Productivity and Growth in an Unstable Emerging Market Economy: the Case of Turkey, 1960-2004(Routledge Journals, Taylor & Francis Ltd, 2009) Ismihan, Mustafa; Metin-Ozcan, KivilcimThis paper explores sources of growth in the Turkish economy by performing growth accounting exercises over the 1960-2004 period and relevant subperiods. It also analyzes the role of a number of important policy-related factors, such as infrastructure investment, macroeconomic instability, and imports, on total factor productivity (TFP) by performing cointegration and impulse response analyses. The results suggest that both TFP and capital accumulation were crucial sources of growth during the sample period. Nevertheless, TFP growth displayed enormous variation from 1960 to 2004. The descriptive and empirical evidence suggests that TFP is positively affected by imports and public infrastructure investment and negatively affected by macroeconomic instability.Article Citation - WoS: 58Two-Dimensional Fluorinated Boron Sheets: Mechanical, Electronic, and Thermal Properties(Amer Chemical Soc, 2018) Pekoz, Rengin; Konuk, Mine; Kilic, M. Emin; Durgun, EnginThe synthesis of atomically thin boron sheets on a silver substrate opened a new area in the field of two-dimensional systems. Similar to hydrogenated and halogenated graphene, the uniform coating of borophene with fluorine atoms can lead to new derivatives of borophene with novel properties. In this respect, we explore the possible structures of fluorinated borophene for varying levels of coverage (BnF) by using first-principles methods. Following the structural optimizations, phonon spectrum analysis and ab initio molecular dynamics simulations are performed to reveal the stability of the obtained structures. Our results indicate that while fully fluorinated borophene (BF) cannot be obtained, stable configurations with lower coverage levels (B4F and B2F) can be attained. Unveiling the stable structures, we explore the mechanical, electronic, and thermal properties of (BnF). Fluorination significantly alters the mechanical properties of the system, and remarkable results, including direction-dependent variation of Young's modulus and a switch from a negative to positive Poisson's ratio, are obtained. However, the metallic character is preserved for low coverage levels, and metal to semiconductor transition is obtained for B2F. The heat capacity at a low temperature increases with an increasing F atom amount but converges to the same limiting value at high temperatures. The enhanced stability and unique properties of fluorinated borophene make it a promising material for various high-technology applications in reduced dimensions.Article Citation - WoS: 22Citation - Scopus: 21Principal and Nonprincipal Solutions of Impulsive Differential Equations With Applications(Elsevier Science inc, 2010) Ozbekler, A.; Zafer, A.We introduce the concept of principal and nonprincipal solutions for second order differential equations having fixed moments of impulse actions is obtained. The arguments are based on Polya and Trench factorizations as in non-impulsive differential equations, so we first establish these factorizations. Making use of the existence of nonprincipal solutions we also establish new oscillation criteria for nonhomogeneous impulsive differential equations. Examples are provided with numerical simulations to illustrate the relevance of the results. (C) 2010 Elsevier Inc. All rights reserved.Article Citation - WoS: 34Citation - Scopus: 34Friction Stir Processing of Dual Phase Steel: Microstructural Evolution and Mechanical Properties(Elsevier Science inc, 2019) Aktarer, S. M.; Kucukomeroglu, T.; Davut, K.The influence of friction stir processing (FSP) on the microstructure and mechanical properties of a DP 600 steel has been studied. The microstructure evolution during the FSP has been characterized using electron back scatter diffraction (EBSD) technique and scanning and transmission electron microscopes. Standard tension and hardness tests were used to characterize the mechanical properties. The results show that the FSP produced a refined microstructure composed of ferrite, bainite, martensite, and tempered martensite which in turn increased the hardness and strength magnitudes by a factor of 1.5. The initially 2.83 mu m average grain size of ferrite has decreased to 0.79 mu m in the pin effected zone of (PE-SZ-I) of the processed region. Both EBSD and TEM observations showed regions with high dislocation density and sub-structures region in the processed zone. The grain size became coarser, the density of both dislocations and low-angle grain boundaries decrease, away from the processed zone. Moreover, phase fractions and hardness values were predicted using CALPHAD thermodynamic based software based on commercial material properties. Although the prediction does not take into consideration the influence of severe plastic deformation, the results were within 10% uncertainties of the experimental findings. The present study demonstrates that an ultra-fine grained structure can be obtained through the thickness of a 1.5 mm thick D P600 steel sheet via FSP. FSP can produce a range of different hardness and strength values; which can also be predicted successfully by inputting the composition and local temperatures reached during the FSP.Article Citation - WoS: 9Citation - Scopus: 15Therapeutic Efficacy of Boric Acid Treatment on Brain Tissue and Cognitive Functions in Rats With Experimental Alzheimer's Disease(Dove Medical Press Ltd, 2023) Ozdemir, Cagri; Arslan, Mustafa; Kucuk, Aysegul; Yigman, Zeynep; Dursun, Ali DoganIntroduction: Oxidative stress has an important role in the pathophysiology of Alzheimer's disease (AD), the most common type of dementia. Boric acid (BA) contributes significantly to the protection of the brain by reducing lipid peroxidation and supporting antioxidant defense. We aimed to evaluate the therapeutic potential of BA treatment in AD rats. Materials and Methods: Four groups were formed as Control (C), Alzheimer's (A), Alzheimer's + Boric acid (ABA), Boric acid (BA). Intracerebroventricular injection of Streptozotocin (STZ) was preferred to create an AD. After 4 weeks, BA was applied 3 times every other day. The Radial Arm Maze Test (RAMT) was used to evaluate memory and learning abilities. Biochemical and histopathological evaluations were made in the hippocampus. Results: Initial RAMT inlet/outlet (I/O) numbers were similar. Two weeks after STZ injection, I/O numbers decreased in group A and ABA compared to group C and BA (p<0.05). After the second BA application, I/O numbers increased in the ABA group compared to the A group (p<0.05). In group A, PON-1, TOS and OSI levels were higher and TAS levels were lower than in groups BA and C. After BA treatment, PON-1 and OSI levels were lower in the ABA group than in the A group (p<0.05). Although there was an increase in TAS value and a decrease in TOS, this did not make a statistical difference. The thickness of the pyramidal cell in CA1 and the granular cell layers in the dentate gyrus, and the number of intact and degenerated neurons in the pyramidal cell layer were similar between the groups. Discussion: Significant improvement in learning and memory abilities after BA application is promising for AD. Conclusion: These results show that BA application positively affects learning and memory abilities, and reduces oxidative stress. More extensive studies are required to evaluate histopathological efficacy.Article Citation - WoS: 25Citation - Scopus: 27Robust stability of 2-D digital filters employing saturation(Ieee-inst Electrical Electronics Engineers inc, 2005) Singh, VA computationally tractable, i.e., linear matrix inequality (LMI)-based criterion for the global asymptotic stability of uncertain two-dimensional digital filters described by the Fornasini-Marchesini second local state-space model with saturation overflow arithmetic is presented. The criterion is compared with an earlier LMI-based criterion.Article Citation - WoS: 36Citation - Scopus: 58A Suite of Object Oriented Cognitive Complexity Metrics(Ieee-inst Electrical Electronics Engineers inc, 2018) Misra, Sanjay; Adewumi, Adewole; Fernandez-Sanz, Luis; Damasevicius, RobertasObject orientation has gained a wide adoption in the software development community. To this end, different metrics that can be utilized in measuring and improving the quality of object-oriented (OO) software have been proposed, by providing insight into the maintainability and reliability of the system. Some of these software metrics are based on cognitive weight and are referred to as cognitive complexity metrics. It is our objective in this paper to present a suite of cognitive complexity metrics that can be used to evaluate OO software projects. The present suite of metrics includes method complexity, message complexity, attribute complexity, weighted class complexity, and code complexity. The metrics suite was evaluated theoretically using measurement theory and Weyuker's properties, practically using Kaner's framework and empirically using thirty projects.
