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Journal of Agricultural Science and Technology(A) 2017年第8期7卷 546-551页

作者： ilker kepenekci Onur Dura Sami Dura Department of Plant Protection Faculty of Agriculture Gaziosmanpasa University Tashciftlik Tokat 60250 Turkey Atatiirk Central Horticultural Research Institute Merkez Yalova 77100 Turkey ROTAM Lifesciences Kimyasal Tartm Tic. Ltd. Sti Pasaport lzmir 35210 Turkey

The aim of this study was to determine the nematicidal effects of some biopesticides againist root-knot nematodes （RKNs）（Meloidogyne incognita） on Bruno type kiwifruit seedlings. Research was conducted in the Atattirk Central Horticultural Research Institute （ACHRI, Yalova, Turkey） greenhouse during 2013-2014. Biopesticides observed in this study were： sesame oil （Devalone EC）, castor oil （Ricinus communis）, Myrothecium verrucaria （M. verrucaria strain AARC-0255, Inferno DF）, Glomus spp. （Endomycorrhizal fungi, Endo Roots Soluble SP） and Paecilomyces lilacinus （Entomopathogenic fungi, P. lilacinus strain PL1, Bionematon SL）. Nematicide Nemacur EC 400 （fenamiphos） was used as treated control （TC） and trials were set up as randomized parcel design （RPD） with seven characters and 10 replicates. Reproduction ratio was determined according to scale values in trial applications and second stage juvenile （J2） populations of M. incognita in soil. The results showed that the best nematicidal effects against RKNs were determined in castor oil （77.92% in 2013 and 73.61% in 2014） and P. lilacinus （61.03% in 2013 and 55.55% in 2014）.

关键词： Root-knot nematodes Meloidogyne incognita sesame oil castor oil Myrothecium verrucaria Glomus Paecilomyceslilacinus kiwifruit.

Modelling height-diameter relationships in complex tropical rain forest ecosystems using deep learning algorithm

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Journal of Forestry Research 2022年第3期33卷 883-898页

作者： Friday Nwabueze Ogana ilker Ercanli Department of Social and Environmental Forestry Faculty of Renewable Natural ResourcesUniversity of IbadanIbadanOyo200284Nigeria Department of Forest Engineering Faculty of ForestryÇankiri Karatekin UniversityÇankiri18200Turkey

Modelling tree height-diameter relationships in complex tropical rain forest ecosystems remains a challenge because of characteristics of multi-species, multi-layers, and indeterminate age composition. Effective modelling of such complex systems required innovative techniques to improve prediction of tree heights for use for aboveground biomass estimations. Therefore, in this study, deep learning algorithm (DLA) models based on artificial intelligence were trained for predicting tree heights in a tropical rain forest of Nigeria. The data consisted of 1736 individual trees representing 116 species, and measured from 52 0.25 ha sample plots. A K-means clustering was used to classify the species into three groups based on height-diameter ratios. The DLA models were trained for each species-group in which diameter at beast height, quadratic mean diameter and number of trees per ha were used as input variables. Predictions by the DLA models were compared with those developed by nonlinear least squares (NLS) and nonlinear mixed-effects (NLME) using different evaluation statistics and equivalence test. In addition, the predicted heights by the models were used to estimate aboveground biomass. The results showed that the DLA models with 100 neurons in 6 hidden layers, 100 neurons in 9 hidden layers and 100 neurons in 7 hidden layers for groups 1, 2, and 3, respectively, outperformed the NLS and NLME models. The root mean square error for the DLA models ranged from 1.939 to 3.887 m. The results also showed that using height predicted by the DLA models for aboveground biomass estimation brought about more than 30% reduction in error relative to NLS and NLME. Consequently, minimal errors were created in aboveground biomass estimation compared to those of the classical methods.

关键词： Artificial intelligence Height-diameter model Mixed-effects Nonlinear least squares Tropical mixed forest

Innovative deep learning artificial intelligence applications for predicting relationships between individual tree height and diameter at breast height

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Forest Ecosystems 2020年第2期7卷 141-158页

作者： ilker Ercanli Cankiri Karatekin University Faculty of Forestry18200ÇankırıTurkey

Background:Deep Learning Algorithms(DLA)have become prominent as an application of Artificial Intelligence(Al)Techniques since *** paper introduces the DLA to predict the relationships between individual tree height(ITH)and the diameter at breast height(DBH).Methods:A set of 2024 pairs of individual height and diameter at breast height measurements,originating from 150 sample plots located in stands of even aged and pure Anatolian Crimean Pine(Pinus nigra *** ***(Lamb.)Holmboe)in Konya Forest *** present study primarily investigated the capability and usability of DLA models for predicting the relationships between the ITH and the DBH sampled from some stands with different growth *** 80 different DLA models,which involve different the alternatives for the numbers of hidden layers and neuron,have been trained and compared to determine optimum and best predictive DLAs network ***:It was determined that the DLA model with 9 layers and 100 neurons has been the best predictive network model compared as those by other different DLA,Artificial Neural Network,Nonlinear Regression and Nonlinear Mixed Effect *** alternative of 100#neurons and 9#hidden layers in deep learning algorithms resulted in best predictive ITH values with root mean squared error(RMSE,0.5575),percent of the root mean squared error(RMSE%,4.9504%),Akaike information criterion(AIC,-998.9540),Bayesian information criterion(BIC,884.6591),fit index(Fl,0.9436),average absolute error(AAE,0.4077),maximum absolute error(***,2.5106),Bias(0.0057)and percent Bias(Bias%,0.0502%).In addition,these predictive results with DLAs were further validated by the Equivalence tests that showed the DLA models successfully predicted the tree height in the independent ***:This study has emphasized the capability of the DLA models,novel artificial intelligence technique,for predicting the relationships between individual tree height and the diame

关键词： Artificial intelligence Prediction Deep learning algorithms Individual tree height

Investigation of Heat Transfer Augmentation between the Ribbed Plates via Taguchi Approach and Computational Fluid Dynamics

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Journal of Thermal Science 2020年第3期29卷 647-666页

作者： GOKTEPELI ilker ATMACA Ulas CAKAN Abdullah Department of Mechanical Engineering Faculty of Engineering and Natural SciencesKonya Technical UniversityKonya 42075Turkey

Heat transfer and turbulent flow characteristics between the ribbed plates have been numerically studied in the present *** ribs with the rectangular cross-section have been placed on the top and the bottom plates of the duct,*** is assumed that the fluid at 300 K has entered the system while the walls kept at 400 *** numerical analyses have been performed by k-ωShear Stress Transport(SST)turbulence model for Re=10000,15000 and *** the fixed rib width,the dimensionless height and the dimensionless spacing have been respectively varied as 0.1≤h’≤0.3 and 0.5≤S’≤1,and the results have been compared with the ones of the smooth *** though there are twenty-seven cases obtained as a result of parametric combinations,the number of various cases has been reduced from twenty-seven to only nine different variations by applying the Taguchi ***,the effects of all the considered parameters on the heat transfer and flow characteristics have been determined in terms of the influence *** optimum parameters for Nusselt number and pressure loss have been ascertained *** is more,the almost exact values for Nusselt number and pressure loss have also been attained by the confirmation test having an error percentage of 6%.The most dominant factor has been determined as the rib height due to its effect on both heat transfer and flow ***,with respect to the numerical results,increasing the rib height,the rib spacing and Reynolds number has separately increased Nusselt ***,symmetrical flow structure has been disturbed as a result of ascending the rib height as clearly seen for h’=0.3 from the *** the meantime,pressure loss has been augmented owing to the increment of the geometrical parameters and also Reynolds number.h’=0.1 with S’=0.5 at Re=10000,h’=0.2 with S’=0.5 at Re=15000 and h’=0.1 with S’=0.75 at Re=15000 can be suggested for the heat transfer enhancement since the press

关键词： CFD heat transfer Nusselt number parallel plate Reynolds number rib Taguchi approach turbulent flow

Experimental analysis on the nonlinear behavior of DC barrier discharge plasmas

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Plasma Science and Technology 2017年第1期19卷 44-50页

作者： Dogan MANSUROGLU ilker Umit UZUN-KAYMAK Physics Department CanakkaleOnsekiz Mart University Canakkale 17100 Turkey Physics Department Middle East Technical University Ankara 06800 Turkey

Nonlinear behavior of glow discharge plasmas is experimentally *** glow is generated between a barrier semiconductor electrode,Chromium doped namely Gallium Arsenide（Ga As：Cr）,as a cathode and an Indium–Tin Oxide（ITO） coated glass electrode as an anode,in reverse *** planar nature of electrodes provides symmetry in spatial *** discharge behaves oscillatory in the time domain,with single and sometimes multiperiodicities in plasma current and voltage *** this paper,harmonic frequency generation and transition to chaotic behavior is *** observed current–voltage characteristics of the discharge are discussed in detail.

关键词： DC glow discharges nonlinear behavior digital signal analysis

Analysis of EST-SSRs in silver birch(Betula pendula Roth.)

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Journal of Forestry Research 2016年第3期27卷 639-646页

作者： Ertugrul Filiz Ilhan Dogan Ibrahim ilker Ozyigit Department of Crop and Animal Production Cilimli Vocational SchoolDuzce University Department of Molecular Biology and Genetics Izmir Institute of Technology Department of Biology Faculty of ScienceRahatlayadururken Manas University Department of Biology Faculty of Science and ArtsMarmara University

Simple sequence repeats（SSRs） defined as sequence repeat units between 1 and 6 bp occur abundantly in both coding and non-coding regions in eukaryotic genomes and these repeats can affect gene expression. In this study, ESTs（expressed sequence tags） of Betula pendula（silver birch） were analyzed for in silico mining of ESTSSRs, protein annotation, open reading frames（ORFs）,designing primers, and identifying codon repetitions. In ***, the frequency of ESTs containing SSRs was 7.8 %with an average of 1SSR/4. 78 kb of EST sequences. A total of 188 SSRs was identified by using MISA software and dinucleotide SSR motifs（65.9 %） were found to be the most abundant type of repeat motif followed by tri-（27.1 %）,tetra-（4.8 %）, and penta-（2.2 %） motifs. Based on ORF analysis, 175 of 178 sequences were predicted as ORFs and the most frequent SSRs were detected in 50 UTR（58.43 %）,followed by in ORF（31.46 %） and in 30UTR（8.43 %）. 102 of 178 ESTs were annotated as ribosomal protein, transport protein, membrane protein, carrier protein, binding protein,and transferase protein. For a total of 102 SSRs（57.3 %）with significant matches, a set of 102 primers（100 %） with forward and reverse strands was designed by using Primer 3 software. Serine（Ser, 19.6 %） was predominant in putative encoded amino acids and most of amino acids showed nonpolar（35.3 %） nature. Our data provide resources for *** and can be useful for in silico comparative analyses of Betulaceae species, including SSR mining.

关键词： Silver birch (Betula pendula) Betulaceae -EST-SSR SSR mining In silico analysis

Weak Vertical Diffusion Allows Maintenance of Cold Halocline in the Central Arctic

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Atmospheric and Oceanic Science Letters 2009年第3期2卷 148-152页

作者： ilker FER Geophysical Institute University of Bergen & Bjerknes Centre for Climate ResearchBergen Norway

In spring preceding the record minimum summer ice cover detailed microstructure measurements were made from drifting pack ice in the Arctic Ocean, 110 km from the North Pole. Profiles of hydrography, shear, and temperature microstructure collected in the upper water column covering the core of the Atlantic Water are analyzed to determine the diapycnal eddy diffusivity, the eddy diffusivity for heat, and the turbulent flux of heat. Turbulence in the bulk of the cold halocline layer was not strong enough to generate significant buoyancy flux and mixing. Resulting turbulent heat flux across the upper cold halocline was not significantly different than zero. The results show that the low levels of eddy diffusivity in the upper cold halocline lead to small vertical turbulent transport of heat, thereby allowing the maintenance of the cold halocline in the central Arctic.

关键词： Arctic Ocean cold halocline layer turbulence mixing heat flux Atlantic Water

Artificial neural network models predicting the leaf area index:a case study in pure even-aged Crimean pine forests from Turkey

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Forest Ecosystems 2018年第4期5卷 400-411页

作者： ilker Ercanli Alkan Gunlu Muammer Senyurt Sedat Keles Faculty of Forestry Cankin Karatekin University18200 CankiriTurkey

Background: Leaf Area Index(LAI) is an important parameter used in monitoring and modeling of forest ecosystems. The aim of this study was to evaluate performance of the artificial neural network(ANN) models to predict the LAI by comparing the regression analysis models as the classical method in these pure and even-aged Crimean pine forest ***: One hundred eight temporary sample plots were collected from Crimean pine forest stands to estimate stand parameters. Each sample plot was imaged with hemispherical photographs to detect the LAI. The partial correlation analysis was used to assess the relationships between the stand LAI values and stand parameters, and the multivariate linear regression analysis was used to predict the LAI from stand parameters. Different artificial neural network models comprising different number of neuron and transfer functions were trained and used to predict the LAI of forest ***: The correlation coefficients between LAI and stand parameters(stand number of trees, basal area, the quadratic mean diameter, stand density and stand age) were significant at the level of 0.01. The stand age, number of trees, site index, and basal area were independent parameters in the most successful regression model predicted LAI values using stand parameters(R_(adj)~2=0.5431). As corresponding method to predict the interactions between the stand LAI values and stand parameters, the neural network architecture based on the RBF 4-19-1 with Gaussian activation function in hidden layer and the identity activation function in output layer performed better in predicting LAI(SSE(12.1040), MSE(0.1223), RMSE(0.3497), AIC(0.1040), BIC(-77.7310) and R^2(0.6392)) compared to the other studied ***: The ANN outperformed the multivariate regression techniques in predicting LAI from stand parameters. The ANN models, developed in this study, may aid in making forest management planning in study forest stands.

关键词： Leaf area index Multivariate linear regression model Artificial neural network modeling Crimean pine Stand parameters

N_(2)and Ar dilution on the premixed biogas jet flame under external acoustic enforcement

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Propulsion and Power Research 2023年第4期12卷 486-504页

作者： Bugrahan Alabas ilker Yılmaz YakupÇam Department of Aeronautical Engineering Faculty of Aeronautics and AstronauticsErciyes UniversityKayseri 38039Turkey Department of Energy Systems Engineering Faculty of TechnologyGazi UniversityAnkara 06560Turkey Department of Aircraft Maintenance and Repair Faculty of Aeronautics and AstronauticsErciyes UniversityKayseri 38039Turkey

In this study,combustion instabilities and flue gas emission changes under different dilutions of N_(2)(nitrogen)and Ar(argon)of a promising biogas mixture(70%CH4-30%CO_(2))in the fight against greenhouse gas emissions were *** the experiments,additions were made from 0%to 50%at intervals of 10%for both *** order to detect the instability of the flame,external acoustic enforcements at different frequencies was applied through the speakers placed in the combustion chamber *** dynamic pressure fluctuation values were *** results showed that low dilution ratios were effective in reducing flame instability for both inert ***,as the dilution ratio increased,the fuel/air mixture became leaner and blowoff *** the case of comparing two different gases,it has been observed that the effect of argon gas on reducing dynamic pressure fluctuation is *** outlet temperature and brightness values of the flame decreased in both Ar and N_(2)*** and NOx emissions increased with increasing diluent volume for all dilution *** the emissions of the two diluent gases are compared,the CO emission,which was 3134 ppm in the undiluted condition,increased up to 4949 ppm in 50%Ar dilution,while it increased to 4521 ppm in 50%N_(2)dilution.

关键词： Biogas Combustion instabilities Pollutant emissions Gas turbine combustor Dilution

Surface charging activated mechanism change: A computational study of O, CO, and CO2 interactions on Ag electrodes

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Journal of Energy Chemistry 2020年第11期29卷 307-313页

作者： ilker Tezsevin Mauritius C.M.van de Sanden Suleyman Er DIFFER-Dutch Institute for Fundamental Energy Research De Zaale 20Eindhoven 5612 AJThe Netherlands CCER-Center for Computational Energy Research DIFFER-Dutch Institute for Fundamental Energy ResearchDe Zaale 20Eindhoven 5612 AJThe Netherlands Department of Applied Physics Eindhoven University of TechnologyEindhoven 5600 MBThe Netherlands

Electrocatalytic and plasma-activated processes receive increasing attention in catalysis. Density functional theory(DFT) calculations are state-of-the-art tools for the fundamental study of reaction mechanisms and predicting the performance of catalytic materials. Proper application of DFT-based methods is crucial when investigating charge-doped electrode surfaces during electrocatalytic and plasma-activated reactions. Here, as a model electrode for plasma-activated CO2 splitting, we studied the interactions of O, CO, and CO2 with the neutral and progressively charged Ag(111) metal surfaces. We show that the application of correction procedures is necessary to obtain accurate adsorption energy profiles of O atoms,CO and CO2 molecules on Ag surfaces that are under the influence of additional electrons. Interestingly,the oxidation of CO is found to shift from a Langmuir–Hinshelwood mechanism on a neutral electrode to an Eley–Rideal mechanism on charged electrodes. Furthermore, we show that the surface charging of Ag(111) electrodes increase their CO2 reduction performance by enhancing the adsorption of O atoms and desorption of CO molecules. A further increase in the absolute charge-state of the electrode surface is expected to waive the thermodynamic barriers for the CO2 splitting reaction.

关键词： Density functional theory CO2 reduction Silver electrode Surface charge