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2020

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Effects Of Sliding Mode Control Antiretroviral Drug On Hiv-1 Viral Load, Musharif Ahmed, Saad Zafar, Muhammad Aamer Saleem, Muhammad Zubair, Ijaz Mansoor Qureshi Jan 2020

Effects Of Sliding Mode Control Antiretroviral Drug On Hiv-1 Viral Load, Musharif Ahmed, Saad Zafar, Muhammad Aamer Saleem, Muhammad Zubair, Ijaz Mansoor Qureshi

Turkish Journal of Electrical Engineering and Computer Sciences

Human immunodeficiency virus (HIV) has devastating effects on human society. Researchers have proposed many models for the decay of CD4+T cells, the growth of infected cells, and viral load. In this paper, four first-order nonlinear coupled differential equations have been considered. Four variables are CD4+T cells, which are healthy, less infected cells,more infected cells capable of producing virus,and finally the viralload. Apart from the two drug therapies, protease inhibitor (PI) and reverse transcriptase inhibitor (RTI), which have already been considered in the literature, we have proposed antiretroviral drug (ARD) that works as sliding mode controller. We have used numerical methods …

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An Intelligent Diagnostic Method Based On Optimizing B-Cell Pool Clonal Selection Classification Algorithm, Chao Lan, Hongli Zhang, Xin Sun, Zhongyuan Ren Jan 2020

An Intelligent Diagnostic Method Based On Optimizing B-Cell Pool Clonal Selection Classification Algorithm, Chao Lan, Hongli Zhang, Xin Sun, Zhongyuan Ren

Turkish Journal of Electrical Engineering and Computer Sciences

The trend of intellectualization and complication of mechanical equipment makes the demand for intelligent diagnostic methods more and more intense in industry. In view of the difficulty of obtaining mechanical fault samples and the requirement of clear and reliable diagnosis results, intelligent diagnosis methods need to adapt to the learning of small samples and have the interpretability of white box model. In this paper, inspired by biological immunity, an intelligent fault diagnosis method was proposed-optimizing b-cell pool clonal selection classification algorithm (OBPCSCA). The OBPCSCA provides a method to construct unique B-cell pools corresponding to specific antigen pools, and uses greedy …

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Automated Labeling Of Terms In Medical Reports In Serbian, Aldina Avdic, Ulfeta Marovac, Dragan Jankovic Jan 2020

Automated Labeling Of Terms In Medical Reports In Serbian, Aldina Avdic, Ulfeta Marovac, Dragan Jankovic

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, many electronic health reports (EHRs) are stored daily. They consist of the structured part and of an unstructured section written in natural language. Due to the limited time for medical examination, EHRs are short reports which often contain errors and abbreviations. Therefore it is a challenge to process an EHR and extract knowledge from this part of the text for different purposes. This paper compares the results of three proposed methods for automatic labeling of medical terms in unstructured parts of EHRs. All words are categorized as words within the medical domain (symptoms, diagnoses, therapies, anatomy, specialties etc.) and …

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Existence Results For $\Psi $-Caputo Fractional Neutral Functional Integro-Differential Equations With Finite Delay, Abdellatif Boutiara, Mohamed S. Abdo, Maamar Benbachir Jan 2020

Existence Results For $\Psi $-Caputo Fractional Neutral Functional Integro-Differential Equations With Finite Delay, Abdellatif Boutiara, Mohamed S. Abdo, Maamar Benbachir

Turkish Journal of Mathematics

This research article deals with novel two species of initial value problems, one of them, the fractional neutral functional integrodifferential equations, and the other one, the coupled system of fractional neutral functional integrodifferential equations, with finite delay and involving a $\psi$-Caputo fractional operator. The existence and uniqueness results are studied through Banach's contraction principle and Krasnoselskii's fixed point theorem. We also establish two various kinds of Ulam stability results for the proposed problems. Further, two pertinent examples are presented to demonstrate the reported results.

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Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp Jan 2020

Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp

Turkish Journal of Electrical Engineering and Computer Sciences

Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold …

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Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation, Orhan Kesemen, Özge Tezel, Eda Özkul, Buğra Kaan Ti̇ryaki̇ Jan 2020

Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation, Orhan Kesemen, Özge Tezel, Eda Özkul, Buğra Kaan Ti̇ryaki̇

Turkish Journal of Electrical Engineering and Computer Sciences

Cluster analysis is widely used in data analysis. Statistical data analysis is generally performed on the linear data. If the data has directional structure, classical statistical methods cannot be applied directly to it. This study aims to improve a new directional clustering algorithm which is based on trigonometric approximation. The trigonometric approximation is used for both descriptive statistics and clustering of directional data. In this paper, the fuzzy clustering algorithms (FCD and FCM4DD) improved for directional data and the proposed method are carried out on some numerical and real data examples, and the simulation results are presented. Consequently, these results …

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Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik Jan 2020

Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer's disease is a brain disease that causes impaired cognitive abilities in memory, concentration, planning, and speaking. Alzheimer's disease is defined as the most common cause of dementia and changes different parts of the brain. Neuroimaging, cerebrospinal fluid, and some protein abnormalities are commonly used as clinical diagnostic biomarkers. In this study, neuroimaging biomarkers were applied for the diagnosis of Alzheimer's disease and dementia as a noninvasive method. Structural magnetic resonance (MR) brain images were used as input of the predictive model. T1 weighted volumetric MR images were reduced to two-dimensional space by several preprocessing methods for three different projections. …

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Automatic Characterization Of Copy Number Polymorphism Using High Throughput Sequencing, Can Alkan Jan 2020

Automatic Characterization Of Copy Number Polymorphism Using High Throughput Sequencing, Can Alkan

Turkish Journal of Electrical Engineering and Computer Sciences

Genome structural variation, broadly defined as alterations longer than 50 bp, are important sources for genetic variation among humans, including those that cause complex diseases such as autism, developmental delay, and schizophrenia. Although there has been considerable progress in characterizing structural variation since the beginnings of the 1000 Genomes Project, one form of structural variation called segmental duplications (SDs) remained largely understudied in large cohorts. This is mostly because SDs cannot be accurately discovered using the alignment files generated with standard read mapping tools. Instead, they can only be found when multiple map locations are considered. There is still a …

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Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya Jan 2020

Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Lung cancer is one of the deadly cancer types, and almost 85 % of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation of two subtypes of NSCLC, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). The major advances in understanding the effects of therapy agents suggest that future targeted therapies will be increasingly subtype specific. We obtained positron emission tomography (PET) images of 93 patients with NSCLC, 39 of which had ADC while the rest had SqCC. Random walk segmentation was applied to delineate three-dimensional tumor …

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Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak Jan 2020

Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak

Turkish Journal of Electrical Engineering and Computer Sciences

Understanding human activities is a newly emerging paradigm that is greatly involved in developing ubiquitous health care (u-Health) systems. The aim of these systems is to seamlessly gather knowledge about the patient?s health and, after collecting knowledge, make suggestions to the patient according to his/her health profile. For this purpose, one of the most important ubiquitous communication trends is the smartphone, which has drawn the attention of both professionals and caregivers for monitoring the aging population, childcare, fall detection, and cognitive impairment. Recognizing human actions in a ubiquitous environment is very challenging and researchers have extensively investigated different methods to …

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A Modified Relay-Race Algorithm For Floorplanning In Pcb And Ic Design, Mert Vatansever, İsmai̇l Fai̇k Başkaya Jan 2020

A Modified Relay-Race Algorithm For Floorplanning In Pcb And Ic Design, Mert Vatansever, İsmai̇l Fai̇k Başkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Floorplanning is a fundamental design step in the physical design of printed circuit boards (PCBs) and integrated circuits (ICs), as it handles the complexity of layout design. From a computational point of view, the floorplanning problem is an NP hard problem, and the size of the search space grows exponentially with increasing numbers of modules. Thus, the algorithm used is an essential factor for speed and quality of the floorplanning process. Although polynomial-time floorplanning algorithms can be implemented when solution space is limited to slicing floorplans, optimal solutions often exist only in the nonslicing floorplan search space. Various stochastic algorithms …

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Geographic Variation And Ethnicity In Diabetic Retinopathy Detection Via Deeplearning, Ali Serener, Sertan Serte Jan 2020

Geographic Variation And Ethnicity In Diabetic Retinopathy Detection Via Deeplearning, Ali Serener, Sertan Serte

Turkish Journal of Electrical Engineering and Computer Sciences

The prevalence of diabetes is on the rise steadily around the globe. Diabetic retinopathy (DR) is a result of damage to the blood vessels in the retina due to diabetes and its fast treatment is crucial for preventing possible blindness. The diagnosis of DR is done mostly using a comprehensive eye exam, where the eye is dilated for better inspection. Analysis by an ophthalmologist is prone to human error and thus automatic and highly accurate detection of DR is preferred for an earlier and better diagnosis. It is important, however, that automatic detection be accurate for all data collected from …

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Short Unsegmented Pcg Classification Based On Ensemble Classifier, Sinam Ajitkumar Singh, Swanirbhar Majumder Jan 2020

Short Unsegmented Pcg Classification Based On Ensemble Classifier, Sinam Ajitkumar Singh, Swanirbhar Majumder

Turkish Journal of Electrical Engineering and Computer Sciences

Diseases associated with the heart are one of the main reasons of death worldwide. Hence, early examination of the heart is important. For analysis of cardiac disorders, a study of heart sounds is a crucial and beneficial approach. Still, automated classification of heart sounds is a challenging task that mainly depends on segmentation of heart sounds and derivation of features using segmented samples. In the literature available for PCG classification provided by PhysioNet/CinC Challenge 2016, most of the research has focused on enhancing the accuracy of the classification model based on complicated segmentation processes and has failed to improve the …

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Dynamic Software Rejuvenation In Web Services: A Whale Optimizationalgorithm-Based Approach, Kimia Rezaei Kalantari, Ali Ebrahimnejad, Homayun Motameni Jan 2020

Dynamic Software Rejuvenation In Web Services: A Whale Optimizationalgorithm-Based Approach, Kimia Rezaei Kalantari, Ali Ebrahimnejad, Homayun Motameni

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we suggest a method for determining the restarting time for web services to increase availability, known as rejuvenation. We consider different parameters such as number of users, maximum service request number, response time, and throughput of a web service to determine its restarting time. Software rejuvenation is an effective technique to counteract software aging in continuously running applications such as web service-based systems. In these systems, web services are allocated based on the needs of the receivers and facilities of servers. One of the challenges while assigning web services is selecting the appropriate server to reduce faults. …

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An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath Jan 2020

An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath

Turkish Journal of Electrical Engineering and Computer Sciences

Many eye diseases like cataracts, trachoma, or corneal ulcer can cause vision problems. Progression of these eye diseases can only be prevented if they are recognized accurately at the early stage. Visually observable symptoms differ a lot among these eye diseases. However, a wide variety of symptoms is necessary to be analyzed for the accurate detection of eye diseases. In this paper, we propose a novel approach to provide an automated eye disease recognition system using visually observable symptoms applying digital image processing techniques and machine learning techniques such as deep convolution neural network (DCNN) and support vector machine (SVM). …

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Accurate Indoor Positioning With Ultra-Wide Band Sensors, Taner Arsan Jan 2020

Accurate Indoor Positioning With Ultra-Wide Band Sensors, Taner Arsan

Turkish Journal of Electrical Engineering and Computer Sciences

Ultra-wide band is one of the emerging indoor positioning technologies. In the application phase, accuracy and interference are important criteria of indoor positioning systems. Not only the method used in positioning, but also the algorithms used in improving the accuracy is a key factor. In this paper, we tried to eliminate the effects of off-set and noise in the data of the ultra-wide band sensor-based indoor positioning system. For this purpose, optimization algorithms and filters have been applied to the raw data, and the accuracy has been improved. A test bed with the dimensions of 7.35 m × 5.41 m …

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Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇ Jan 2020

Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, railway transport has been preferred intensively in local and intercity freight and passenger transport. For this reason, it is of utmost importance that railway lines are operated in an uninterrupted and safe manner. In order to carry out continuous operation, all systems must continue to operate with maximum availability. In this study, data were collected from switch motors, which are the important equipment of railways, and the related equipment and these data were evaluated with sector experience and the results related to the failure status of the switch points were revealed. The obtained results were processed with …

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Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç Jan 2020

Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we have proposed an alternative approach for sentence modeling problem. The difficulty of the choice of answer, the semantically related questions and the lack of syntactic closeness of the answers give rise to the difficulty of selecting the answer. The deep learning field has recently achieved a pivotal success in semantic analysis, machine translation, and text summaries. The essence of this work, inspired by the human orthographic processing mechanism and using multiple convolution filters with pre-rendered 2-Dimension (2D) representations of sentences, input or output size is to learn the basic features of the language without concerns. For …

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An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil, Can Bariş Top Jan 2020

An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil, Can Bariş Top

Turkish Journal of Electrical Engineering and Computer Sciences

Magnetic nanoparticles (MNPs) have a wide range of clinical applications for imaging, therapy, and biosensing. Superparamagnetic MNPs can be directly visualized with high spatiotemporal resolution using the magnetic particle imaging (MPI) modality. The image resolution of MPI depends on the relaxation properties of the MNPs. Therefore, characterization of MNP response under alternating magnetic field excitation is necessary to predict MPI imaging performance and develop optimized MNPs. Biosensing applications also make use of the change in the relaxation response of MNPs after binding to a target agent. As MNP relaxation properties change with temperature and viscosity, noninvasive probing of these microenvironmental …

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On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya Jan 2020

On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya

Turkish Journal of Electrical Engineering and Computer Sciences

In game-theoretic settings the key notion of analysis is an equilibrium, which is a profile of agent strategies such that no viable coalition of agents can improve upon their coalitional welfare by jointly changing their strategies. A Nash equilibrium, where viable coalitions are only singletons, and a super strong equilibrium, where every coalition is deemed viable, are two extreme scenarios in regard to coalition formation. A recent trend in the literature is to consider equilibrium notions that allow for coalition formation in between these two extremes and which are suitable to model social coalition structures that arise in various real-life …

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A New Semiempirical Model Determining The Dielectric Characteristics Of Citrusleaves For The Remote Sensing At C Band, Abdullah Genç, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t Jan 2020

A New Semiempirical Model Determining The Dielectric Characteristics Of Citrusleaves For The Remote Sensing At C Band, Abdullah Genç, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t

Turkish Journal of Electrical Engineering and Computer Sciences

Dielectric parameters (i.e. permittivity) are fundamental to the simulation, design, modeling, and developing of microwave applications. For targeted objects, the complex permittivity is an essential parameter that affects its characteristics of scattering and microwave radiation. Thus, in microwave remote sensing applications, the knowledge of the dielectric property of vegetable materials is used not only to detect planting areas for monitoring and to able to specify the growth stage of them in seasonal variations, but also to determine the water requirement of the plant for controlling (water stress). This paper focuses on determining the dielectric parameters of orange and lemon leaves, …

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Passenger Scoring For Free-Pass Promotion In Public Transportation, Ufuk Demi̇r Alan, Derya Bi̇rant Jan 2020

Passenger Scoring For Free-Pass Promotion In Public Transportation, Ufuk Demi̇r Alan, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

The focus of promotions targeted to increase the use of public transportation concentrates on increasing the attractiveness of it, particularly by decreasing transportation fares. To serve that purpose, this paper proposes a novel passenger scoring model, namely RFLT (recency, frequency, loyalty, and time), for offering a free-pass promotion in public transportation. It presents the comparison results of RFLT and wRFLT (weighted version) using a real-world dataset obtained by a near field communication (NFC) mobile payment application. The experimental results show that the w-RFLT model provides a more balanced score distribution than the RFLT model, and the frequency parameter (F), among …

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A Random Subspace Based Conic Functions Ensemble Classifier, Emre Çi̇men Jan 2020

A Random Subspace Based Conic Functions Ensemble Classifier, Emre Çi̇men

Turkish Journal of Electrical Engineering and Computer Sciences

Classifiers overfit when the data dimensionality ratio to the number of samples is high in a dataset. This problem makes a classification model unreliable. When the overfitting problem occurs, one can achieve high accuracy in the training; however, test accuracy occurs significantly less than training accuracy. The random subspace method is a practical approach to overcome the overfitting problem. In random subspace methods, the classification algorithm selects a random subset of the features and trains a classifier function trained with the selected features. The classification algorithm repeats the process multiple times, and eventually obtains an ensemble of classifier functions. Conic …

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Net-Lda: A Novel Topic Modeling Method Based On Semantic Document Similarity, Eki̇n Eki̇nci̇, Sevi̇nç İlhan Omurca Jan 2020

Net-Lda: A Novel Topic Modeling Method Based On Semantic Document Similarity, Eki̇n Eki̇nci̇, Sevi̇nç İlhan Omurca

Turkish Journal of Electrical Engineering and Computer Sciences

Topic models, such as latent Dirichlet allocation (LDA), allow us to categorize each document based on the topics. It builds a document as a mixture of topics and a topic is modeled as a probability distribution over words. However, the key drawback of the traditional topic model is that it cannot handle the semantic knowledge hidden in the documents. Therefore, semantically related, coherent and meaningful topics cannot be obtained. However, semantic inference plays a significant role in topic modeling as well as in other text mining tasks. In this paper, in order to tackle this problem, a novel NET-LDA model …

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Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath Jan 2020

Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath

Turkish Journal of Electrical Engineering and Computer Sciences

Recent developments in deep networks allow us to train networks with more parameters by yielding better performance given sufficient amount of data. However, we are still restricted with the availability of labelled data in medical image segmentation, where the problem is exacerbated with high intra- and intervariability of anatomical structures. In order to bypass this problem without compromising network performance, this study introduces a PERINet, which promises to achieve higher performance while being with smaller parameter count such as on the order of 0.8 million than its counterparts. The network benefits from rich features generated by our versions of inception …

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Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya Jan 2020

Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Real-time response, low cost, sensitive and easy setup fiber optic chemical sensors were fabricated by etching a part of single mode fiber in hydrofluoric (HF) acid solution and tested in different water samples such as tap water, DI water, salty and sugar water with different concentrations to record ringdown time (RDT) differences between media due to refractive index differences by employing the fiber loop ringdown (FLRD) spectroscopy technique. Baseline stability of 0.63 % and the minimum detectable RDT of $5.05$ $\mu$s for this kind of fiber optic chemical sensors were obtained. Fabricated sensors were coated with N,N-Diethyl-p-phenylenediamine for the first …

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The Role Of Badh Gene In Oxidative, Salt, And Drought Stress Tolerances Of White Clover, Gürkan Demi̇rkol Jan 2020

The Role Of Badh Gene In Oxidative, Salt, And Drought Stress Tolerances Of White Clover, Gürkan Demi̇rkol

Turkish Journal of Botany

The aim of this study was to confirm the presence of BADH gene and control whether it plays an important role to protect white clover (Trifolium repens L.) against oxidative, salt, and drought stresses. Three genotypes possessing BADH and 1 genotype lacking BADH were selected, considering the expression levels of BADH in response to methyl viologen mediated oxidative stress. The genotypes possessing BADH displayed significantly less ion leakage under oxidative stress treatment, compared to that lacking BADH . In order to test salinity tolerance, the plants were treated with 300 mM NaCl for 2 weeks, and to mimic drought conditions, …

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Karyotype Evolution And New Chromosomal Data In Erodium: Chromosome Alteration, Polyploidy, Dysploidy, And Symmetrical Karyotypes, Esra Marti̇n, Ahmet Kahraman, Tuncay Di̇rmenci̇, Havva Bozkurt, Hali̇l Erhan Eroğlu Jan 2020

Karyotype Evolution And New Chromosomal Data In Erodium: Chromosome Alteration, Polyploidy, Dysploidy, And Symmetrical Karyotypes, Esra Marti̇n, Ahmet Kahraman, Tuncay Di̇rmenci̇, Havva Bozkurt, Hali̇l Erhan Eroğlu

Turkish Journal of Botany

Chromosomal data are valuable and very useful for revealing evolution and speciation processes. Due to its wide distribution throughout the world, morphological differences, and chromosomal alterations, Erodium L?Hér. is an important genus for investigating the relationship between chromosomal alterations and karyotype evolution. In the present study, the chromosome records of 15 taxa are provided; three are reported here for the first time (E.birandianum, E. gaillardotii, and E.hendrikii), seven present new chromosome numbers, and five are in agreement with previous reports. Karyotype evolution is summarized in the light of this data, and four different genomes are presented in the genus. Millions …

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Transcriptomic Insights Into The Molecular Aspects Of Salt Stress Responses In Kandelia Candel Roots, Jianhong Xing, Dezhuo Pan, Lingxia Wang, Fanglin Tan, Wei Chen Jan 2020

Transcriptomic Insights Into The Molecular Aspects Of Salt Stress Responses In Kandelia Candel Roots, Jianhong Xing, Dezhuo Pan, Lingxia Wang, Fanglin Tan, Wei Chen

Turkish Journal of Botany

The mangrove plant Kandelia candel is a type of woody halophyte that grows in tropical and subtropical ocean intertidal zones and exhibits a high salt tolerance. In this study, 61,970 unigenes were obtained from the roots of 60-day-old K. candel seedlings treated with 0 (control), 200, 400, and 600 mM NaCl for 3 days with an N50 of 1510 bp. Moreover, 454, 311, and 2663 genes were differentially expressed under 200, 400, and 600 mM NaCl treatments, respectively. These differentially expressed genes were primarily involved in plant hormone signal transduction, carbohydrate and energy metabolism, amino acid metabolism, stress response, and …

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Cover And Contents Jan 2020

Cover And Contents

Turkish Journal of Botany

No abstract provided.

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