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Öğe Analysis and classification of the mobile molecular communication systems with deep learning(Springer Heidelberg, 2022) Isik, Ibrahim; Er, Mehmet Bilal; Isik, EsmeNano networks focused on communication between nano-sized devices (nanomachines) is a new communication concept which is known as molecular communication system (MCs) in literature. The researchers have generally used fixed transmitter and receiver for MCs models to analyze the fraction of received molecules and signal to interference rate etc. In this study, contrary to the literature, a mobile MC model has been used in a diffusion environment by using five bits. It is concluded that when the receiver and transmitter are mobile, distance between them changes and finally this affects the probability of the received molecules at the receiver. After the fraction of received molecules is obtained for different mobility values of Rx and Tx (Drx and Dtx), deep learning's bi-directional long short-term memory (Bi-LSTM) model is applied for the classification of Rx and Tx mobilities to find the best MC model with respect to fraction of received molecules. Finally it is obtained that when the mobilities of Rx and Tx increase, the fraction of received molecules also increases. Bi-LSTM model of Deep learning is used on a data set consisting of five classes. The suggested model's accuracy, precision, and sensitivity values are obtained as 98.05, 96.49, and 98.01 percent, respectively.Öğe Analysis and estimation of fading time from thermoluminescence glow curve by using artificial neural network(Taylor & Francis Ltd, 2021) Isik, Esme; Isik, Ibrahim; Toktamis, HuseyinThe artificial neural network (ANN) is an information processing technology inspired by the information processing technique of the human brain. The way the simple biological nervous system works is imitated with ANN. In this study, an ANN model is proposed to analyze and simulate TL intensity of experimental data of quartz crystals with respect to the fading. In this model, network type and transfer function are chosen as the feed-forward backpropagation algorithm and Tansig respectively for the training of the proposed ANN model. The optimization process is also chosen as Levenberg-Marquardt in this study. The performance criteria of the proposed method were evaluated according to the coefficient of determination (R-2) and mean-squared error (MSE) techniques. After simulation results are obtained, the TL glow curve of the prediction results of quartz crystal is obtained as a function of fading time irradiated with beta-source at 70 Gy for stored in 64 h at room temperature.Öğe Analysis of molecular communication model via diffusion with cumulative distribution functions(Gazi Univ, Fac Engineering Architecture, 2024) Isik, Ibrahim; Isik, Esme; Ates, AbdullahMolecular Communication (MOC), a novel communication method between nano-sized devices, has gained attention in recent literature. Numerous MOC models have been utilized to analyze factors such as the number of molecules reaching the receiver and the molecule-interference ratio. However, a common trend observed in the existing MOC models is the predominant use of the Normal distribution function to describe the movement of carrier molecules within the diffusion medium. In contrast to the existing literature, this study aims to thoroughly investigate alternative distribution functions for the diffusion of molecules in the medium, taking into consideration the number of received molecules, in order to identify the MOC model with optimal performance. In this study, the performance of various distribution functions including extreme value distribution (EVRND), normal distribution (NRND), t-distribution (TRND), generalized extreme value distribution (GEVRND), and generalized Pareto distribution (GPRND) were compared using different system parameters to identify the best MOC model. The analysis revealed that the GPRND distribution exhibited the highest performance, while the NRND distribution demonstrated the lowest performance. Given the prevalent use of the NRND distribution in analyzing MOC models within the literature, the significance of this study is further underscored.Öğe Analysis of the electronic integrate and fire neuron model(Elsevier, 2022) Isik, Ibrahim; Tagluk, Mehmet EminNano-scale devices are thought to intervene in natural life for a variety of responsibilities. For understanding the intrinsic communication of such nano-scale devices, software and hardware modalities have been introduced. Some of these models are of neuro-spike communication systems which employ spiking neuron circuits. In this study, the previously designed electronic integrate and fire circuit inspired by Hodgkin Huxley membrane model is analyzed and interrelated to the Izhikevich's systematic integrate and fire model. The generated action potentials with this model are very similar to the ones generated by real biophysical neurons which are thought as the inter-neuronal ionic transporters of information. The superiority of the analyzed model to the existing models is that it can show pulse trains whose characteristics are almost similar to those produced by nerve cells. The analytical, hardware and simulation results have shown that the model has the potential of employment in the smart nano-scale systems and medical treatment strategies. (c) 2022 Elsevier B.V. All rights reserved.Öğe Analysis of the Signal Reception in Mobile Molecular Communication System by Using Antenna(Ieee, 2021) Atamis, Furkan Burak; Isik, IbrahimMolecular communication is defined as the transmission and reception of biochemical information through molecules. Chemical signals are used to transfer information in molecular communication. In addition, carrier molecules are used to transmit and receive information between micro and nano machines. Molecular communication systems can be used in many subject such as Cancer Treatment, Drug Delivery. Molecular communication systems generally consist of a transmitter (Tx) and a receiver (Rx). Just like in digital communication, the transmitter transmits information through molecules, while the receiver receives and decodes the information encoded in the transmitter. In this study, a molecular communication model using mobile transmitters and transmitters is designed and analyzed in Matlab environment. In the designed model, the receptors on the receiver are considered as antennas and all calculations have been made accordingly. Contrary to the literature, comments have been made about how the communication quality will change with the change of distance between receiver and transmitter and diffusion constant of the nano machines in a mobile system. As a result, it has been observed that as the distance between the transmitter and receiver increases, the communication quality decreases.Öğe Analysis of thermoluminescence characteristics of a lithium disilicate glass ceramic using a nonlinear autoregressive with exogenous input model(Wiley, 2020) Isik, Esme; Toktamis, Huseyin; Isik, IbrahimDental ceramics because of their translucency exemplify the most biologically realistic restorative materials for aesthetic rehabilitation and can be used to estimate dose accumulated as a result of a nuclear accident or attack. In this study, lithium disilicate ceramic obtained from Vivadent Ivoclar, Turkey was studied for its thermoluminescence (TL) properties. The lithium disilicate glass ceramic was irradiated with a Sr-90-Y-90 beta-source from 10 Gy to 6.9 kGy and the results read on a Harshaw 3500 reader. The TL peak of lithium disilicate ceramic showed sublinearity in the range 12 Gy to 6 kGy. The area under the TL glow curve increased by about 25% by the end of 10th measurement cycle. Fading values were also considered after irradiation. Lithium disilicate ceramic samples underwent 37% fading after 1 h and 59% fading after 1 week. In addition to the experimental study, a software-based simulation study was also undertaken using a MATLAB system identification tool. Experimental studies are generally time consuming and some materials used for experiments are very expensive. In this study, experimental, and simulation results were compared and produced almost the same outcome with a similarity of more than 98%.Öğe Analyzing of Alzheimer's Disease Based on Biomedical and Socio-Economic Approach Using Molecular Communication, Artificial Neural Network, and Random Forest Models(Mdpi, 2022) Bayraktar, Yuksel; Isik, Esme; Isik, Ibrahim; Ozyilmaz, Ayfer; Toprak, Metin; Kahraman Guloglu, Fatma; Aydin, SerdarAlzheimer's disease will affect more people with increases in the elderly population, as the elderly population of countries everywhere generally rises significantly. However, other factors such as regional climates, environmental conditions and even eating and drinking habits may trigger Alzheimer's disease or affect the life quality of individuals already suffering from this disease. Today, the subject of biomedical engineering is being studied intensively by many researchers considering that it has the potential to produce solutions to various diseases such as Alzheimer's caused by problems in molecule or cell communication. In this study, firstly, a molecular communication model with the potential to be used in the treatment and/or diagnosis of Alzheimer's disease was proposed, and its results were analyzed with an artificial neural network model. Secondly, the ratio of people suffering from Alzheimer's disease to the total population, along with data of educational status, income inequality, poverty threshold, and the number of the poor in Turkey were subjected to detailed distribution analysis by using the random forest model statistically. As a result of the study, it was determined that a higher income level was causally associated with a lower risk of Alzheimer's disease.Öğe Classification of Diffusion Constants of Transmitter and Receiver and Distance Between Them Using Mobile Molecular Communication via Diffusion Model(Springer Heidelberg, 2024) Er, Mehmet Bilal; Isik, Ibrahim; Kuran, Umut; Isik, EsmeMolecular communication (MC) holds promise for enabling communication in scenarios where traditional wireless methods may be impractical or ineffective, offering unique capabilities for a range of applications in both natural and engineered systems. In this research, a novel approach to MC is explored, diverging from the standard use of stationary transmitter and receiver models typically found in the field. The study introduces a dynamic MC model, where both the transmitter and receiver are mobile within a diffusion environment. This model operates using a 5-bit system. The key finding is that the mobility of these nanodevices alters their distance, which in turn impacts the likelihood of molecule reception at the receiver. The study employs deep learning techniques, specifically a combination of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, to categorize the mobility patterns of the receiver (Rx) and transmitter (Tx). By analyzing various mobility rates (Drx and Dtx) and distances between the Tx and Rx, the research successfully identifies the most efficient mobile MC model in terms of molecule reception rates. The use of Linear Support Vector Machine alongside the CNN and LSTM hybrid feature vector resulted in an 87.68% accuracy in predicting diffusion coefficients. Moreover, using a Cubic Support Vector with the same hybrid feature vector, the study achieved an 88.09% accuracy in estimating the distance between the transmitter and receiver. The study concludes that an increase in the mobilities of Rx and Tx correlates with a higher rate of molecule reception.Öğe Communication in nano devices: Electronic based biophysical model of a neuron(Elsevier Science Bv, 2019) Tagluk, M. Emin; Isik, IbrahimInvestigating new strategies and signaling techniques for nano-devices and systems is quite challenging. The communication systems considered to be feasible in nano-devices are inspired from biophysical systems which communicate with electro-chemical signals organized with respect to excitation. While the electrical pulses transmitted along with the cell membrane the chemical signal transmitted in the synaptic cleft. Developing new chemical signal based communication which termed as the molecular communication with minimum error is now the central deal for the researchers. Strategic approaches to the issue in variety of perspective such as systematic, experimental and electronic circuitry viable for chip based robotic and nano-device design are now available in the literature. Biological signaling pathways, in accordance with the action potentials generated in pre-synaptic neuron some chemical substances called neurotransmitters released into the synaptic cleft and hence the post-synaptic neuron is accordingly triggered. In this way the information transmitted from one cell to another by electro chemical signal carriers. About this process some electronic neuron models have also been introduced to simulate dynamic behavior of neuronal cells. In this study, a novel simple electronic integrate and fire model which has been designed previously was further developed and used to simulate and analyze the communication of neurons. The proposed electronic model not only simulates the neuronal cell's behavior and also can transmit the information to the following neuron. The rate of correct transmission depends on the synaptic channel model. The characteristics of the used semiconductor components with overall structure of the proposed electronic model are very close to the biophysical nature of neuron and can be designed on semiconductor chips which is the advantage of the model. (C) 2019 Elsevier B.V. All rights reserved.Öğe Comparison of HDL Coder and System Generator Tools in terms of QPSK Analysis(Ieee, 2017) Isik, Ibrahim; Tagluk, Mehmet EminBER (bit error rate) measurement is an important criterion to analyze digital communication systems. In literature this measurement generally performed through simulation programs like Matlab/Simulink. It is considered that the simulation programs may not represent a real communication system and also they are quite time consuming and expensive. However, modeling communication systems with parallel processing and fast modules such as FPGA (Field Programmable Gate Arrays) using VHDL (Very High Speed Integrated Circuit Hardware Description Language) and performing BER measurements on this modules is much faster, closer to the reality. The main interest of this study is to demonstrate the performance of FPGA based models in communication systems and show their advantages and disadvantages compared to the simulator models. Despite the simple structure of FPGA it sometimes restricts a complete design of the system because of comprising only gates, logic operators, register etc. Simulator models such as the ones designed with Matlab have a huge library which provides flexibility in the design and analysis of the system. Software and hardware developers try to develop new ways such as HDL Coder and System Generator tools to get over these restrictions. But both methods still have some restrictions to design a better communication system. In this paper also this restrictions are investigated detailed. As an example, QPSK (Quadrature Phase Shift Keying) modulation is shown by using System Generator tool in this paper.Öğe Effect of receiver shape and volume on the Alzheimer disease for molecular communication via diffusion(Inst Engineering Technology-Iet, 2020) Isik, Ibrahim; Yilmaz, H. Birkan; Demirkol, Ilker; Tagluk, Mehmet EminNano-devices are featured to communicate via molecular interaction, the so-called molecular communication (MC). In MC systems, the information is carried by molecules where the amount of molecules constitutes the level of the signal. In this study, an MC-based system was analysed with different receiver topology and related parameters, such as size, shape, and orientation of receptors on the receiver. Also in the concept of nano-medicine, the effect of amyloid-beta (A(beta)), which is believed as the main cause of Alzheimer disease, on the successful reception ratio of molecules with the proposed receiver models was investigated. It was demonstrated that the cubic receiver model is superior to sphere one in terms of the correct reception ratio of the molecular signal. A cubic model where its edge (not rotated around the centre) is placed across the transmitter demonstrated a better performance in reducing the effect of A(beta) as compared to the sphere model while a cubic model where its corner (rotated around the centre) is placed across the transmitter demonstrated a worse performance than the spherical model. From this expression, it may be concluded that with the adjustment of topological system parameters the probability of successful reception ratio in MC may be possible.Öğe Effects of Sensor Size, Surface Material, and Contact Area on Pressure Measurements in Thin-Film Pressure Sensors(Ieee-Inst Electrical Electronics Engineers Inc, 2024) Talu, Burcu; Isik, Ibrahim; Candiri, Busra; Candiri, Yunus; Yapalikan, Remziye BetulThe existing studies on foot pressure measurement have primarily focused on sensor placement and the number of sensors instead of sensor size and the ground above the sensor; moreover, there is limited research available on the use of different materials in pressure measurement devices manufactured by various companies. This study, therefore, aimed to address these gaps by investigating the measurement accuracy in standard loading conditions, considering different sensor sizes, contact areas, and ground surfaces. Pressure was applied within the sensing diameter of the sensor, and a microcontroller was used to calculate the reciprocal resistance. The results of the study indicated that the coating of sensors with different materials and the shape of the contact surface of the object applying pressure significantly influenced the measurements of the pressure sensors. When comparing the difference according to the sensor sizes, medium-size sensor (18.3 mm); according to surfaces, thin-thick plastazote; according to loading conditions, oval contact areas gave more sensitive values. Future research can further build upon these findings to enhance the design and development of pressure measurement devices, ultimately benefiting scientific research and clinical applications.Öğe Enhancing the performance of TiO2 nanotube-based hydrogen sensors through crystal structure and metal electrode(Pergamon-Elsevier Science Ltd, 2024) Tasyurek, Lutfi Bilal; Isik, Esme; Isik, Ibrahim; Kilinc, NecmettinIn this research, the effect of metal electrodes and crystalline phase on gas detection of titanium dioxide (TiO2) nanotube-based hydrogen (H2) sensors was investigated. TiO2 nanotubes were produced using glycerol-based electrolyte and annealed at 300 degrees C and 700 degrees C to change the anatase and rutile crystalline phases, respectively. TiO2 nanotubes were coated by platinum (Pt), palladium (Pd), gold (Au) and silver (Ag) electrodes to fabricate metal/TiO2 nanotubes Ti H2 sensor devices and then the current-voltage (I-V) characteristics were investigated at room temperature. The structural properties of TiO2 nanotubes were characterized by SEM, FE-SEM, XRD, and Raman techniques. The H2 detection properties of the sensors were examined at the 1000 ppm - 5% H2 concentration range. The crystal structure and metal electrodes are the main factors that affect the H2 sensing properties of TiO2 nanotube-based sensors. The effect of crystal forms on sensitivity was not the same as for metal electrodes. The underlying sensing mechanisms for different types of metal electrodes and crystal structures are discussed and the relevance of their sensing performance to nanotubes and electronic properties is investigated. In addition, discussion of each metal electrode and crystal structure will make important contributions to the development of H2 sensors. The Pd-coated device annealed at 700 degrees C showed the best detection performance.(c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Öğe Heart Disease Prediction with Feature Selection Based on Metaheuristic Optimization Algorithms and Electronic Filter Model(Springer Heidelberg, 2023) Isik, IbrahimIt is known that manually detecting heart conditions is often costly and time-consuming and any study regarding diagnose these conditions has a great importance. In this study, a metaheuristic optimization model has been developed to automate the detection of heart diseases with artificial intelligence compatible methods. In the proposed model, the feature set is selected to represent the best heart sound signals and heart disease diagnoses using machine learning algorithms with these feature sets. The proposed method has been tested on the Pascal dataset which consists of four classes. Firstly, an electronic-based filter model is used as low-pass filter and has great potential to use as a filtering for heart sound signals to decrease noise. Secondly, the statistical and acoustic feature vector extracted from the audio signals in the Pascal dataset is passed through particle swarm optimization (PSO), firefly algorithm (FA) and cuckoo search algorithm (CSA), and the most suitable feature vector is selected. After obtaining the most suitable feature vector with metaheuristic optimization algorithms and filtering method, heart disease diagnosis is performed using random forest (RF), K-nearest neighbor (K-NN), support vector machine (SVM) and Naive Bayes machine learning algorithms.Öğe How mobility of transmitter and receiver affects the communication quality(Aip Publishing, 2022) Isik, IbrahimNano-networks focused on communication of nano-sized devices (nanomachines) are a new communication concept, which is known as Molecular Communication (MC) in the literature. In this study, on the contrary to the literature, a mobile MC model is proposed in a diffusion environment by using 5 bits because it is known that besides the molecules, which transport information between the transmitter and receiver, the transmitter and receiver parts of the biological cells are mobile in the blood or any other fluid media. In this study, both the transmitter and the receiver can be chosen as mobile and/or fixed for some specific duties, such as drug delivery systems. Their mobility values can also be regulated separately for the proposed mobile MC model. The proposed model is analyzed for the different situations of the transmitter and receiver (fixed and/or mobile) by considering the fraction of the received molecules. Finally, the number of bits, the time step, and the bit duration are analyzed to find the best MC model. It is concluded that when the receiver and the transmitter are mobile, the distance between them changes, and finally, this affects the probability of the received molecules at the receiver. (c) 2022 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Öğe Interference and molecule reception probability analysis in nano/micro scale communication systems using Fick's diffusion law(Gazi Univ, Fac Engineering Architecture, 2022) Isik, Ibrahim; Tagluk, Mehmet Emin; Isik, EsmeRecently, too much afford has been conducted toward development of novel communication techniques (biological inspired) for implementing in nano and micro scale systems inspired from electro-chemical communication systems that naturally used by living beings. One of these techniques is known as nano/micro scale communication (NMSC) in which chemical signals are used as carriers for transmission of information through fluid media. The information carrier particles used in such communication systems consist of biological components such as DNA and protein components. Studies regarding NMSC are considered to highly contribute to the developments in the field of nano-technology which can be used to detect and treatment of the some unsolved illness yet. Therefore, in this study, software based a new NMSC model that could potentially be used in nano-scale systems were developed and analysed in terms of communication performance. Firstly, Diffusion constant which affect the communication performance of the software based NMSC model is derived using some Physics laws such as Fick's. Secondly, different forms of receivers such as sphere, cube and rectangular prism topologies have been tried for increasing the rate of molecule reception and reducing the inter symbol interference of the receiver. It was observed that the signal transmission rate increased and the interference decreased with the use of a cube receiver model. The results obtained from the proposed NMSC model encourages one to think that such receiver models might have the potential for Alzheimer and many illness which cause missing and/or wrong communication of the cells.Öğe A New Chaotic System with Chaos Entanglement(Ieee, 2015) Hamamci, Serdar Ethem; Gogebakan, Veysel; Isik, IbrahimIn this paper, a new chaotic system is proposed by using chaos entanglement method. Chaos entanglement method is based on obtaining the new chaotic systems adding some nonlinear elements to sub-equations of a third order linear system. It is shown from analysis of the new system that it produces a rich chaotic behavior sequence. Furthermore, the proposed chaotic system is controlled by a simple constant controller and its chaotic behavior is converted to periodic or stable behaviours. The analysis results are confirmed by the figures.Öğe Parameter Optimization for Molecular Communication via Diffusion Model using Equilibrium and Enhanced Equilibrium Algorithms(Springer Heidelberg, 2023) Isik, IbrahimMolecular communication (MOC), which is proposed as a new communication method between nano-sized devices (nanomachines), holds the potential to be used for diagnosing and treating diseases such as Alzheimer's, Spinal Cord, and Parkinson's in the future. Several methods for analyzing MOC models can be found in the literature. However, many of them propose using constant transmitters and receivers in a diffusion environment. In contrast to the existing literature, this study proposes a MOC model that considers the transmitter, receiver, and molecule as mobile entities in the diffusion environment. Furthermore, the system's performance has been improved by identifying optimal parameters, such as the diffusion coefficient that controls mobility and the receptor radius that directly affects the system's performance, using the equilibrium optimization (EO) algorithm and enhanced equilibrium optimization (E-2 O) algorithms. All optimized results are presented with mean and standard deviation values, demonstrating the reproducibility and consistency of the findings. In conclusion, solving the stochastic MOC problem with deterministic approaches such as the E O and (EO)-O-2 algorithms offers several advantages.Öğe Parkinson's detection based on combined CNN and LSTM using enhanced speech signals with Variational mode decomposition(Elsevier Sci Ltd, 2021) Er, Mehmet Bilal; Isik, Esme; Isik, IbrahimParkinson's disease (PD) can cause many non-motor and motor symptoms such as speech and smell. One of the difficulties that Parkinson's patients can experience is a change in speech or speaking difficulties. Therefore, the right diagnosis in the early period is important in reducing the possible effects of speech disorders caused by the disease. Speech signal of Parkinson patients shows major differences compared to normal people. In this study, a new approach based on pre-trained deep networks and Long short-term memory (LSTM) by using melspectrograms obtained from denoised speech signals with Variational Mode Decomposition (VMD) for detecting PD from speech sounds is proposed. The proposed model consists of four steps. In the first step, the noise is removed by applying VMD to the signals. In the second step, mel-spectrograms are extracted from the enhanced sound signals with VMD. In the third step, pre-trained deep networks are preferred to extract deep features from the mel-spectrograms. For this purpose, ResNet-18, ResNet-50 and ResNet-101 models are used as pre-trained deep network architecture. In the last step, the classification process is occurred by giving these features as input to the LSTM model, which is designed to define sequential information from the extracted features. Experiments are performed with the PC-GITA dataset, which consists of two classes and is widely used in the literature. The results obtained from the proposed method are compared with the latest methods in the literature, it is seen that it has a better performance in terms of classification performance.Öğe A Preliminary Investigation of Receiver Models in Molecular Communication via Diffusion(Ieee, 2017) Isik, Ibrahim; Yilmaz, H. Birkan; Tagluk, Mehmet EminMolecular Communication (MC) is a new multidisciplinary subject concerning medicine, biology, and communication engineering. MC concept is introduced for modeling of communication of nano/micro scale devices. In MC systems, chemical signals carrying information in gaseous or liquid media are used. Similar to other communication systems, in MC sending information from transmitter to receiver with minimum error is one of the most important goals. In MC systems due to physical characteristics of medium, higher rates of inter symbol interference (ISI) and noise increase error probability. Figures of receiver mechanisms and signal detection techniques are therefore the main factors to be tuned for decreasing error probability. In this view, so far, many receiver models such as reversible adsorption and desorption (A&D), protrusion method, ligand receptor, and linear catalytic or CAT receiver models have been introduced. In this study, these models and the results obtained through their implementation are investigated and briefly reviewed.
