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Articles 1471 - 1500 of 10319
Full-Text Articles in Physical Sciences and Mathematics
Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie
Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie
Turkish Journal of Electrical Engineering and Computer Sciences
The most challenging objective in machine translation of sign language has been the machine?s inability tolearn interoccluding finger movements during an action process. This work addresses the problem of teaching a deeplearning model to recognize differently oriented skeletal data. The multi-view 2D skeletal sign language video data isobtained using 3D motion-captured system. A total of 9 signer views were used for training the proposed network andthe 6 for testing and validation. In order to obtain multi-view deep features for recognition, we proposed an end-to-endtrainable multistream convolutional neural network (CNN) with late feature fusion. The fused multiview features arethen inputted to …
Analytical Modeling And Study On Noise Characteristics Of Rotor Eccentric Spmsmwith Unequal Magnetic Poles Structure, Pengpeng Xia, Shenbo Yu, Rutong Dou, Fengchen Zhai
Analytical Modeling And Study On Noise Characteristics Of Rotor Eccentric Spmsmwith Unequal Magnetic Poles Structure, Pengpeng Xia, Shenbo Yu, Rutong Dou, Fengchen Zhai
Turkish Journal of Electrical Engineering and Computer Sciences
he establishment of the analytical model of the rotor eccentric surface-mounted permanent magnet syn-chronous motor (SPMSM) with unequal magnetic poles structure will be beneficial to calculating the magnetic field andstudying noise characteristics quickly. Based on the equivalent surface current (ESC) method and equivalent boundarymethod, the analytical model of the rotor eccentric SPMSM with unequal magnetic poles structure is proposed. Duringthe modeling process, the magnetic field produced by a permanent magnet (PM) is obtained using the ESC method, andthe effect on the air gap magnetic field, which arised from stator, is replaced with the concentric current sheet (CCS)magnetic field. And, the …
Dual Bit Control Low-Power Dynamic Content Addressable Memory Design For Iotapplications, V V Satyanarayana Satti, Sridevi Sriadibhatla
Dual Bit Control Low-Power Dynamic Content Addressable Memory Design For Iotapplications, V V Satyanarayana Satti, Sridevi Sriadibhatla
Turkish Journal of Electrical Engineering and Computer Sciences
The Internet of things (IoT) is an emerging area in the semiconductor industry for low-power and high-speedapplications. Many search engines of IoT applications require low power consumption and high-speed content addressablememory (CAM) devices for the transmission of data packets between servers and end devices. A CAM is a hardwaredevice used for transfer of packets in a network router with high speed at the cost of power consumption. In this paper,a new dual bit control precharge free (PF) dynamic content addressable memory (DCAM) has been introduced. Theproposed design uses a new charge control circuitry, which is used to control the dual …
Optimal Directional Overcurrent Relay Coordination Based On Computationalintelligence Technique: A Review, Suzana Pil Ramli, Muhammad Usama, Hazlie Mokhlis, Wei Ru Wong, Muhamad Hatta Hussain, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Optimal Directional Overcurrent Relay Coordination Based On Computationalintelligence Technique: A Review, Suzana Pil Ramli, Muhammad Usama, Hazlie Mokhlis, Wei Ru Wong, Muhamad Hatta Hussain, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Turkish Journal of Electrical Engineering and Computer Sciences
An exponential increase in diverse load demand in the last decade has influenced the integration of more power plants into the power system. This increases the fault current due to the bidirectional flow of current, resulting in unwanted tripping of the relays if not properly coordinated. Therefore, it is imperative to ensure the installation of relays in the grid being able to sense the fault current from any direction (i.e. upstream or downstream). This can be accomplished by introducing an optimal directional overcurrent relay (DOCR) coordination scheme into the system. This paper presents an in-depth review of the applications of …
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Software quality assurance is one of the crucial factors for the success of software projects. Bug fixing has an essential role in software quality assurance, and bug localization (BL) is the first step of this process. BL is difficult and time-consuming since the developers should understand the flow, coding structure, and the logic of the program. Information retrieval-based bug localization (IRBL) uses the information of bug reports and source code to locate the section of code in which the bug occurs. It is difficult to apply other tools because of the diversity of software development languages, design patterns, and development …
Determination Of Pneumonia In X-Ray Chest Images By Using Convolutionalneural Network, Özlem Polat, Zümray Ölmez, Tamer Ölmez
Determination Of Pneumonia In X-Ray Chest Images By Using Convolutionalneural Network, Özlem Polat, Zümray Ölmez, Tamer Ölmez
Turkish Journal of Electrical Engineering and Computer Sciences
Pneumonia is one of the major diseases that cause a lot of deaths all over the world. Determining pneumonia from chest X-ray (CXR) images is an extremely difficult and important image processing problem. The discrimination of whether pneumonia is of bacterium or virus origin has also become more important during the pandemic. Automatic determination of the presence and origin of pneumonia is crucial for speeding up the treatment process and increasing the patient's survival rate. In this study, a convolutional neural network (CNN) framework is proposed for detection of pneumonia from CXR images. Two different binary CNNs and a triple …
New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan
New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, hyperchaotic system (HCSs) have been started to be used in engineering applications because they have complex dynamics, randomness, and high sensitivity. For this purpose, HCSs with different features have been introduced in the literature. In this work, a new HCS with a single discontinuous nonlinearity is introduced and analyzed. The proposed system has one saddle focus equilibrium. When the dynamic properties and bifurcation graphics of the system are analyzed, it is determined that the proposed system exhibits the complex phenomenon of multistability. Moreover, analog electronic circuit design of the proposed system is performed with positive second-generation current conveyor. In …
A Novel Hybrid Global Optimization Algorithm Having Training Strategy: Hybridtaguchi-Vortex Search Algorithm, Mustafa Saka, Meli̇h Çoban, İbrahi̇m Eke, Suleyman Sungur Tezcan, Müslüm Cengi̇z Taplamacioğlu
A Novel Hybrid Global Optimization Algorithm Having Training Strategy: Hybridtaguchi-Vortex Search Algorithm, Mustafa Saka, Meli̇h Çoban, İbrahi̇m Eke, Suleyman Sungur Tezcan, Müslüm Cengi̇z Taplamacioğlu
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search …
Field-Programmable Gate Array (Fpga) Hardware Design And Implementation Ofa New Area Efficient Elliptic Curve Crypto-Processor, Muhammad Kashif, İhsan Çi̇çek
Field-Programmable Gate Array (Fpga) Hardware Design And Implementation Ofa New Area Efficient Elliptic Curve Crypto-Processor, Muhammad Kashif, İhsan Çi̇çek
Turkish Journal of Electrical Engineering and Computer Sciences
Elliptic curve cryptography provides a widely recognized secure environment for information exchange in resource-constrained embedded system applications, such as Internet-of-Things, wireless sensor networks, and radio frequency identification. As the elliptic-curve cryptography (ECC) arithmetic is computationally very complex, there is a need for dedicated hardware for efficient computation of the ECC algorithm in which scalar point multiplication is the performance bottleneck. In this work, we present an ECC accelerator that computes the scalar point multiplication for the NIST recommended elliptic curves over Galois binary fields by using a polynomial basis. We used the Montgomery algorithm with projective coordinates for the scalar …
Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang
Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang
Turkish Journal of Electrical Engineering and Computer Sciences
This study develops the deep Q-network (DQN)-based noise suppression for robust speech recognition purposes under ambient noise. We thus design a reinforcement algorithm that combines DQN training with a deep neural networks (DNN) to let reinforcement learning (RL) work for complex and high dimensional environments like speech recognition. For this, we elaborate on the DQN training to choose the best action that is the quantized noise suppression gain by the observation of noisy speech signal with the rewards of DQN including both the word error rate (WER) and objective speech quality measure. Experiments demonstrate that the proposed algorithm improves speech …
An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding
An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding
Turkish Journal of Electrical Engineering and Computer Sciences
Edge computing is a new paradigm that provides data processing capabilities at the network edge. In view of the uneven data distribution and the constrained onboard resource, an edge device often needs to call for a number of neighboring devices as followers to cooperate on data analysis tasks. However, these followers may be rational and selfish, having their private optimization objectives such as energy efficiency. Therefore, the leader device needs to incentivize the followers to achieve a certain global objective, e.g., maximizing task accomplishment, rather than their own objectives. In this paper, we model the aforementioned challenges in edge computing …
Privacy Preserving Hybrid Recommender System Based On Deep Learning, Sangeetha Selvaraj, Sudha Sadasivam Gangadharan
Privacy Preserving Hybrid Recommender System Based On Deep Learning, Sangeetha Selvaraj, Sudha Sadasivam Gangadharan
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning models are widely being used to provide relevant recommendations in hybrid recommender systems. These hybrid systems combine the advantages of both content based and collaborative filtering approaches. However, these learning systems hamper the user privacy and disclose sensitive information. This paper proposes a privacy preserving deep learning based hybrid recommender system. In hybrid deep neural network, user?s side information such as age, location, occupation, zip code along with user rating is embedded and provided as input. These embedding?s pose a severe threat to individual privacy. In order to eliminate this breach of privacy, we have proposed a private …
Robust And Efficient Ebg-Backed Wearable Antenna For Ism Applications, Ayesha Saeed, Asma Ejaz, Humayun Shahid, Yasar Amin, Hannu Tenhunen
Robust And Efficient Ebg-Backed Wearable Antenna For Ism Applications, Ayesha Saeed, Asma Ejaz, Humayun Shahid, Yasar Amin, Hannu Tenhunen
Turkish Journal of Electrical Engineering and Computer Sciences
A structurally compact, semiflexible wearable antenna composed of a distinctively miniaturized electromagnetic band gap (EBG) structure is presented in this work. Designed for body-centric applications in the 5.8 GHz band, the design draws heavily from a novel planar geometry realized on Rogers RT/duroid 5880 laminate with a compact physical footprint spanning lateral dimensions of $0.6$$\lambda$$_0$$\times$$0.06$$\lambda$$_0$. Incorporating a 2$\times$2 EBG structure at the rear of the proposed design ensures sufficient isolation between the body and the antenna, doing away with the performance degradation associated with high permittivity of the tissue layer. The peculiar antenna geometry allows for reduced backward radiation and …
Improved Online Sequential Extreme Learning Machine: Os-Celm, Olcay Tosun, Recep Eryi̇ği̇t
Improved Online Sequential Extreme Learning Machine: Os-Celm, Olcay Tosun, Recep Eryi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
Online learning methods (OLM) have been gaining traction as a solution to classification problems because of rapid renewal and fast growth in volume of available data. ELM-based sequential learning (OS-ELM) is one of the most frequently used online learning methodologies partly due to fast training algorithm but suffers from inefficient use of its hidden layers due to the random assignment of the parameters of those layers. In this study, we propose an improved online learning model called online sequential constrained extreme learning machine (OS-CELM), which replaces the random assignment of those parameters with better generalization performance using the CELM method …
Evaluation Of Cable And Busbar System In Multiconductor Distribution Systems Interms Of Current And Magnetic Field Distributions, Yunus Berat Demi̇rol, Mehmet Aytaç Çinar, Bora Alboyaci
Evaluation Of Cable And Busbar System In Multiconductor Distribution Systems Interms Of Current And Magnetic Field Distributions, Yunus Berat Demi̇rol, Mehmet Aytaç Çinar, Bora Alboyaci
Turkish Journal of Electrical Engineering and Computer Sciences
The selection of power distribution components is of great importance in electrical facilities. Cable and busbar systems are widely used applications, such as electric vehicle charge stations, microgrids and energy storage systems, for power distribution in the distribution grid. In this study, the current distribution on the parallel conductors and magnetic field distributions around cable and busbar structures is evaluated for studied application where the power is distributed using a cable system between a converter transformer and a converter. All modeling and analyzes are conducted using ANSYS Electronics Suite software, by applying balanced and pure sinusoidal current excitation. Obtained results …
Hc-Fft: Highly Configurable And Efficient Fft Implementation On Fpga, Paki̇ze Ergül, H. Fati̇h Uğurdağ, Doğancan Davutoğlu
Hc-Fft: Highly Configurable And Efficient Fft Implementation On Fpga, Paki̇ze Ergül, H. Fati̇h Uğurdağ, Doğancan Davutoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
FFT is one of the basic building blocks in many applications such as sensors, radars, communications. For some applications, e.g., real-time spectral monitoring and analysis, FFT needs to be "run-time configurable" so that the system is real-time. When examining the previous work on configurable real-time (FPGA-based) FFT implementations, we see that the degree of configurability is less than what is desired. In this paper, a new FFT architecture is proposed, which has a high degree of run-time configurability and yet does not compromise area or throughput. The configurable parameters of this design are the number of FFT points (up to …
Opinion Dynamics Of Stubborn Agents Under The Presence Of A Troll Asdifferential Game, Aykut Yildiz, Ari̇f Bülent Özgüler
Opinion Dynamics Of Stubborn Agents Under The Presence Of A Troll Asdifferential Game, Aykut Yildiz, Ari̇f Bülent Özgüler
Turkish Journal of Electrical Engineering and Computer Sciences
The question of whether opinions of stubborn agents result in Nash equilibrium under the presence of troll is investigated in this study. The opinion dynamics is modelled as a differential game played by n agents during a finite time horizon. Two types of agents, ordinary agents and troll, are considered in this game. Troll is treated as a malicious stubborn content maker who disagrees with every other agent. On the other hand, ordinary agents maintain cooperative communication with other ordinary agents and they disagree with the troll. Under this scenario, explicit expressions of opinion trajectories are obtained by applying Pontryagin?s …
Brain Tumor Detection From Mri Images With Using Proposed Deep Learningmodel: The Partial Correlation-Based Channel Selection, Atinç Yilmaz
Brain Tumor Detection From Mri Images With Using Proposed Deep Learningmodel: The Partial Correlation-Based Channel Selection, Atinç Yilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
A brain tumor is an abnormal growth of a mass or cell in the brain. Early diagnosis of the tumor significantly increases the chances of successful treatment. Artificial intelligence-based systems can detect the tumor in early stages. In this way, it could be possible to detect a tumor and resolve this problem that may endanger human life early. In the study, the partial correlation-based channel selection formula was presented that allowed the selection of the most prominent feature that differs from the other studies in the literature. Additionally, the multi-channel convolution structure was proposed for the feature network phase of …
Diagnosis Of Paroxysmal Atrial Fibrillation From Thirty-Minute Heart Ratevariability Data Using Convolutional Neural Networks, Murat Sürücü, Yalçin İşler, Resul Kara
Diagnosis Of Paroxysmal Atrial Fibrillation From Thirty-Minute Heart Ratevariability Data Using Convolutional Neural Networks, Murat Sürücü, Yalçin İşler, Resul Kara
Turkish Journal of Electrical Engineering and Computer Sciences
Paroxysmal atrial fibrillation (PAF) is the initial stage of atrial fibrillation, one of the most common arrhythmia types. PAF worsens with time and affects the patient?s life quality negatively. In this study, we aimed to diagnose PAF early, so patients can start taking precautions before this disease gets worse. We used the atrial fibrillation prediction database, an open data from Physionet and constructed our approach using convolutional neural networks. Heart rate variability (HRV) features are calculated from time-domain measures, frequency-domain measures using power spectral density estimations (fast Fourier transform, Lomb-Scargle, and Welch periodogram), time-frequencydomain measures using wavelet transform, and nonlinear …
Attention Augmented Residual Network For Tomato Disease Detection Andclassification, Getinet Yilma Abawatew, Seid Belay, Kumie Gedamu, Maregu Assefa, Melese Ayalew, Ariyo Oluwasanmi, Zhiguang Qin
Attention Augmented Residual Network For Tomato Disease Detection Andclassification, Getinet Yilma Abawatew, Seid Belay, Kumie Gedamu, Maregu Assefa, Melese Ayalew, Ariyo Oluwasanmi, Zhiguang Qin
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning techniques help agronomists efficiently identify, analyze, and monitor tomato health. CNN (convolutional neural network) locality constraint and existing small train sample adversely influenced disease recognition performance. To alleviate these challenges, we proposed a discriminative feature learning attention augmented residual (AAR) network. The AAR network contains a stacked pre-activated residual block that learns deep coarse level features with locality context, whereas the attention block captures salient feature sets while maintaining the global relationship in data points, attention features augment the learning of the residual block. We used conditional variational generative adversarial network (CVGAN) image reconstruction network and augmentation techniques …
New Chlorogenic Acid Derivatives And Triterpenoids From Scorzonera Aucheriana, İshak Eri̇k, Kami̇l Çoşkunçelebi̇, Serdar Makbul, Nuretti̇n Yayli
New Chlorogenic Acid Derivatives And Triterpenoids From Scorzonera Aucheriana, İshak Eri̇k, Kami̇l Çoşkunçelebi̇, Serdar Makbul, Nuretti̇n Yayli
Turkish Journal of Chemistry
Chromatographic separation of n-hexane and ethyl acetate fraction of a crude methanol extract obtained from aerial parts of the Scorzonera aucheriana DC collected from Sivas province of Turkey yielded nine natural compounds; two new 3-caffeoyl-quinic acid analogs (1-2), one new taraxasterol oleate (3), and six known triterpenoids taraxasterol (4), taraxasterol acetate (5), ptiloepoxide (6), lupeol (7), lupeol acetate (8), and β-sitosterol (9) were characterized. The structures of the isolated compounds were elucidated on the basis of NMR (1H, 13C, COSY, HMBC, HSQC, and TOCSY), UV, FT-IR and LC-Q-TOF-MS spectrometric data.
Microwave Assisted, Sequential Two-Step, One-Pot Synthesis Of Novel Imidazo[1,2-A]Pyrimidine Containing Tri/Tetrasubstituted Imidazole Derivatives, Tuğba Güngör
Turkish Journal of Chemistry
A series of novel imidazo[1,2-a]pyrimidine containing tri/tetrasubstituted imidazole derivatives (1-10) has been synthesized via sequential two-step, one-pot, multicomponent reaction using imidazo[1,2-a]pyrimidine-2-carbaldehyde, benzil, primary amines, and ammonium acetate catalyzed by p-toluenesulfonic acid under microwave-assisted conditions. The results showed that target compounds can be obtained from a wide range of primary amines bearing different functional groups with moderate to good yields (46%-80%) under optimum reaction conditions. This method provides a green protocol for imidazo[1,2-a]pyrimidine containing tri/ tetrasubstituted imidazole derivatives due to ethyl alcohol as a green solvent, microwave irradiation as a greener heating method and one-pot multicomponent reaction as a green technique. …
Vortex-Assisted Magnetic Solid Phase Extraction Of Pb And Cu In Some Herb Samples On Magnetic Multiwalled Carbon Nanotubes, Di̇lek Kamaş, Aslihan Karatepe, Mustafa Soylak
Vortex-Assisted Magnetic Solid Phase Extraction Of Pb And Cu In Some Herb Samples On Magnetic Multiwalled Carbon Nanotubes, Di̇lek Kamaş, Aslihan Karatepe, Mustafa Soylak
Turkish Journal of Chemistry
This study is the development of a new solid phase extraction method based on using magnetic multiwalled carbon nanotubes impregnated with 1-(2-pyridylazo)2-naphthol (PAN) for separation, preconcentration, and flame atomic absorption spectrometric determination of Pb(II) and Cu(II). Optimization of the method was done by investigating pH effect, amount of magnetic multiwalled carbon nanotubes impregnated with PAN, eluent type and volume, matrix effects, and volume of the sample. The optimum adsorbent amount was found to be 75 mg and the optimum pH value was found as 5.5. The detection limits were 16.6 μg L-1 for Pb(II) and 18.9 μg L-1 for Cu(II). …
Co2 Hydrogenation To Methanol And Dimethyl Ether At Atmospheric Pressure Using Cu-Ho-Ga/Γ-Al2o3 And Cu-Ho-Ga/Zsm-5: Experimental Study And Thermodynamic Analysis, Cansu Tuygun, Bahar İpek
Co2 Hydrogenation To Methanol And Dimethyl Ether At Atmospheric Pressure Using Cu-Ho-Ga/Γ-Al2o3 And Cu-Ho-Ga/Zsm-5: Experimental Study And Thermodynamic Analysis, Cansu Tuygun, Bahar İpek
Turkish Journal of Chemistry
CO2 valorization through chemical reactions attracts significant attention due to the mitigation of greenhouse gas effects. This article covers the catalytic hydrogenation of CO2 to methanol and dimethyl ether using Cu-Ho-Ga containing ZSM-5 and γ-Al2O3 at atmospheric pressure and at temperatures of 210 °C and 260 °C using a CO2:H2 feed ratio of 1:3 and 1:9. In addition, the thermodynamic limitations of methanol and DME formation from CO2 was investigated at a temperature range of 100?400 °C. Cu-Ho-Ga/γ-Al2O3 catalyst shows the highest formation rate of methanol (90.3 μmolCH3OH/gcat/h ) and DME (13.2 μmolDME/gcat/h) as well as the highest selectivity towards …
Formation And Characterization Of Mechanochemically Generated Free Lignin Radicalsfrom Olive Seeds, Fatma Demi̇r
Formation And Characterization Of Mechanochemically Generated Free Lignin Radicalsfrom Olive Seeds, Fatma Demi̇r
Turkish Journal of Chemistry
In this study, formation and quantification of mechanochemically generated free radicals of lignin were evaluated after the extraction of lignin from olive seeds and detailed lignin characterization was performed. Lignin was extracted from crushed olive seeds as an insoluble solid using Klason method. Isolated lignin was mechanochemically grinded under cryo conditions using Cryomill and particlesizes were determined by using Zeta Sizer, structural changes were followed by XRD and FTIR-ATR; thermal stabilities were tracked by TGA and DSC. In order to enable solubility demanding studies (such as 1H-NMR and GPC), acylation of lignin was accomplished. ESR measurements were completed to prove …
Enhanced Ethanol Sensing Properties Of Wo$_{3}$ Modified Tio$_{2}$ Nanorods, Bekzat Abdikadyr, Alp Kiliç, Onur Alev, Serkan Büyükköse, Zafer Zi̇ya Öztürk
Enhanced Ethanol Sensing Properties Of Wo$_{3}$ Modified Tio$_{2}$ Nanorods, Bekzat Abdikadyr, Alp Kiliç, Onur Alev, Serkan Büyükköse, Zafer Zi̇ya Öztürk
Turkish Journal of Chemistry
Pristine and WO$_{3}$ decorated TiO$_{2}$ nanorods (NRs) were synthesised to investigate n-n-type heterojunction gas sensing properties. TiO$_{2}$ NRs were fabricated via hydrothermal method on fluorine-doped tin oxide coated glass (FTO) substrates. Then, tungsten was sputtered on the TiO$_{2}$ NRs and thermally oxidised to obtain WO$_{3}$ nanoparticles. The heterostructure was characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX) spectroscopy. Fabricated sensor devices were exposed to VOCs such as toluene, xylene, acetone and ethanol, and humidity at different operation temperatures. Experimental results demonstrated that the heterostructure has better sensor response toward ethanol at 200 °C. Enhanced sensing …
Toxicity Remission Of Paes On Multireceptors After Molecular Modification Through A3d-Qsar Pharmacophore Model Coupled With A Gray Interconnect Degree Method, Xinyi Chen, Yu Li
Toxicity Remission Of Paes On Multireceptors After Molecular Modification Through A3d-Qsar Pharmacophore Model Coupled With A Gray Interconnect Degree Method, Xinyi Chen, Yu Li
Turkish Journal of Chemistry
In the proposed model, the gray interconnect degree method was employed to process the acute toxicity values of phthalate acid esters (PAEs) to green algae, daphnia, mysid, and fish (predicted by EPI Suite software) and to obtain the comprehensive characterization value of the multireceptor toxicity effect (MTE) of PAEs. The 3D-QSAR pharmacophore model indicated that hydrophobic groups significantly affected the MTE of PAEs. Based on this, 16 PAEs derivative molecules with significantly decreased comprehensive characterization value (more than 10%) of the toxic effects of multireceptors were designed. Among them, 13 PAEs derivative molecules reduced the toxicity values (predicted by the …
Electrophoretic Deposition And Characterization Of Self-Doped Srtio$_{3}$ Thin Films, Naeimeh Sadat Peighambardoust, Umut Aydemi̇r
Electrophoretic Deposition And Characterization Of Self-Doped Srtio$_{3}$ Thin Films, Naeimeh Sadat Peighambardoust, Umut Aydemi̇r
Turkish Journal of Chemistry
Herein, titanium (Ti$^{3+}$) self-doped strontium titanate (SrTiO$_{3}$), so-called blue SrTiO$_{3}$, with a bandgap of 2.6 eV and favorable photocatalytic characteristics was fabricated through a facile and effective method. For electrochemical investigations, the electrophoretic deposition was applied to produce SrTiO$_{3}$ thin films on (fluorine-doped tin oxide) FTO conductive substrates. The electrophoretic voltage of 20 V and a process duration of 10 min were optimized to reach transparent and uniform coatings on FTO. The blue SrTiO$_{3}$ reveals lower resistance (charge transfer resistance of 6.38 Ω cm$^{-2}$) and higher electron mobility (current density value of 0.25 mA cm?2) compared to a pure SrTiO$_{3}$ …
Efficiency Enhancement With Chloride To Iodide Ion Exchange Of Benzimidazolium Salt Asa Redox Mediator, Serkan Dayan, Mert Olgun Karataş, Bülent Alici, Ni̇lgün Kalaycioğlu Özpozan
Efficiency Enhancement With Chloride To Iodide Ion Exchange Of Benzimidazolium Salt Asa Redox Mediator, Serkan Dayan, Mert Olgun Karataş, Bülent Alici, Ni̇lgün Kalaycioğlu Özpozan
Turkish Journal of Chemistry
The new benzimidazolium derivative (SM-1) salt with ion exchange from the (SM-0) was fabricated and characterized by protonnuclear magnetic resonance (1H-NMR), carbon-nuclear magnetic resonance (13C-NMR), Fourier-transform infrared spectroscopy (FTIR), electrospray ionization (EIS-MS), thermal analysis (TG), cyclic voltammetry (CV), and ultraviolet-visible spectroscopy (UV-vis), for electrolytes (liquid or dried) in the DSSC charge transportation mechanism. Also, the influence of ion exchange from chloride to iodine in the synthesized electrolytes, compared to other electrolytes (conventional or commercial), was investigated about DSSC performance efficiency. When using as a liquid electrolyte (SM-1), the power conversion efficiency (η) of the working DSSC device was recorded as …
Reusability And Regeneration Of Solid Catalysts Used In Ultrasound Assisted Biodieselproduction, Mahmut Rahi̇m Bayramoğlu, İbrahi̇m Korkut, Başak Temur Ergan
Reusability And Regeneration Of Solid Catalysts Used In Ultrasound Assisted Biodieselproduction, Mahmut Rahi̇m Bayramoğlu, İbrahi̇m Korkut, Başak Temur Ergan
Turkish Journal of Chemistry
Reusability of two heterogeneous catalysts in ultrasound (US) assisted biodiesel production was investigated in comparison to each other. An ultrasound (US) generator (200 W, 20 kHz) equipped with a horn type probe (19 mm) was used. Regeneration experiments were planned according to second order central composite design (CCD) method. After the eighth use of the catalysts, biodiesel yield decreased from 99.1% to 90.4% for calcined calcite (CaO) and from 98.8% to 89.8% for calcined dolomite (CaO.MgO). Furthermore, regeneration of spent catalysts by calcination was investigated; optimum temperature and time were found as 750 °C and 90 min, lower than fresh …