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This paper focuses on making a comparing of GNSS/Levelling data and data obtained from global geopotential models. For comparison, geoid undulations obtained by GNSS/Levelling method and geoid undulations obtained from global geopotential models have been used. As global geopotential models, SGG-UGM-2, XGM2019e_2159, GO_CONS_GCF_2_TIM_R6e, ITSG-Grace2018s, EIGEN-GRGS.RL04.MEAN-FIELD, GOCO06s, GO_CONS_GCF_2_TIM_R6, GO_CONS_GCF_2_DIR_R6 GGMs are used. The data sets used in the improvements of the models are altimetry, satellite, location data and topography. The disparities between the geoid undulations obtained from the GNSS/Levelling method and geoid undulations obtained from global geoid models have been taken. Some statistical criteria for these differences have been calculated. These criteria, such as smallest, biggest, average, standard deviation, Root Mean Square RMS statistical values of deviations between GNSS/Levelling geoid and global geopotential models, are taken into consideration when comparing the models. According to the comparison, the global gravity field model that best fits the GNSS/Levelling is selected. https://issuu.com/kick-the-buddy-money-hack-ios https://issuu.com/ludo-club-money-hack-ios https://issuu.com/madout2-money-hack-ios https://issuu.com/asphalt-8-hack-ios-unlimited-money https://issuu.com/diamonds-mobile-legends-hack-ios https://issuu.com/coin-master-hack-ios-download https://issuu.com/goodnovel-free-coins-hack-ios https://issuu.com/pokemon-go-coins-hack-ios https://issuu.com/joi-free-coins-hack-ios https://issuu.com/livu-free-coins-hack-ios https://issuu.com/plato-hack-coins-ios https://issuu.com/ludo-star-coins-hack-ios https://issuu.com/coin-master-mod-ios-unlimited-spins https://issuu.com/dragon-city-gems-hack-ios https://issuu.com/episode-unlimited-gems-hack-ios https://issuu.com/shadow-fight-2-money-gems-hack-ios https://issuu.com/mario-kart-tour-ios-hack-rubies https://issuu.com/survival-city-builder-ios-hack-airdrops https://issuu.com/one-punch-man-the-strongest-ios-hack https://issuu.com/my-fantasy-ios-hack-unlimited-diamonds https://issuu.com/super-stylist-ios-hack https://issuu.com/block-craft-3d-ios-hack-gems

XR provides benefits in innovation, competitiveness and sustainability that offset disruptions in and enhances physical reality. The Caribbean’s metaverse evolution started before the pandemic with the development of XR projects and creatives’ NFTs. The physical isolation during the Covid-19 pandemic accelerated the Caribbean’s interest in the metaverse and XR. In 2020, only 83 participants from Trinidad and Tobago entered the CARIRI AR/VR Challenge to demonstrate their XR ideas. There is a need to encourage and accelerate regional XR development. The purpose of this research is to explore Caribbean XR developers’ experiences to provide an understanding of the factors affecting their XR development. This paper addresses the question: What factors of influence will encourage the development of XR projects in the Caribbean to advance their metaverse development? Online questionnaires issued to Caribbean XR developers from July to December 2021 obtained responses from 77 participants throughout 13 regional countries. The primary data were statistically insignificant and skewed towards two countries (Jamaica and Trinidad & Tobago). Comparative and inferential analyses identified factors of influence, industry sectors, and design foci. The originality of this research is an XR development strategy that incorporates the I4.0, UX, and financial strategies. It establishes the XR project design foci (the user, the purpose and the location). The factors of influence minimum criteria and the industry sector(s) influence each design focus. An initial reference list of industry sectors is education (the preferred option), healthcare, tourism, culture, manufacturing for export, construction, entertainment, game development, agriculture, and environmental protection. The strategy’s value is in enabling content creators to design XR applications to meet consumers’ needs and increase the regional adoption of XR. The impact of the research on the Caribbean is to facilitate a path to the regional metaverse evolution. This research identified the need for a regional XR development policy.

The main reason for technological developments is to make human life more comfortable. Bioclimatic comfort areas are areas where people feel the most comfortable and comfortable in terms of climate. As a result of global climate changes, the temperature in the world is increasing day by day moreover increase in terms of people living in our country and other countries which the need for comfortable and comfortable spaces increases in all seasons. Bioclimatic comfort areas are the most needed in the summer months. However, the average temperature increases day by day in all seasons due to climate change. For this reason, within the scope of this study, the most suitable bioclimatic comfort areas were calculated with the HEAT index by using the average temperature and humidity maps for the fall, winter, spring, and summer seasons of 2019. While creating temperature and humidity maps, a point database was created for the neighborhoods in Kocaeli Province, temperature and humidity data were combined in this database. The temperature and humidity map for each season was open-source code the Inverse Distance Weighted (IDW) interpolation method in the QGIS 3.16 software was transformed into a map in raster format. The heat index was created by using temperature and relative humidity maps in raster format. Then, the relationship between the created heat index maps and morphological factors was examined.

The need for accurate and up-to-date spatial data by decision-makers in public and private administrations is increasing gradually. In recent decades, in the management of disasters and smart cities, fast and accurate extraction of roads, especially in emergencies, is quite important in terms of transportation, logistics planning, and route determination. In this study, automatic road extraction analyses were carried out using the Unmanned Aerial Vehicle (UAV) data set, belonging to the Yildiz Technical University Davutpasa Campus road route. For this purpose, this paper presents a comparison between performance analysis of rule-based classification and U-Net deep learning method for solving automatic road extraction problems. Objects belonging to the road and road network were obtained with the rule-based classification method with overall accuracy of 95%, and with the deep learning method with an overall accuracy of 86%. On the other hand, the performance metrics including accuracy, recall, precision, and F1 score were utilized to evaluate the performance analysis of the two methods. These values were obtained from confusion matrices for 4 target classes consisting of road and road elements namely road, road line, sidewalk, and bicycle road. Finally, integration of classified image objects with ontology was realized. Ontology was developed by defining four target class results obtained as a result of the rule-based classification method, conceptual class definition and properties, rules, and axioms.

Classical outlier tests based on the least-squares (LS) have significant disadvantages in some situations. The adjustment computation and classical outlier tests deteriorate when observations include outliers. The robust techniques that are not sensitive to outliers have been developed to detect the outliers. Several methods use robust techniques such as M-estimators, L1- norm, the least trimmed squares etc. The least trimmed squares (LTS) among them have a high-breakdown point. After the theoretical explanation, the adjustment computation has been carried out in this study based on the least squares (LS) and the least trimmed squares (LTS). A certain polynomial with arbitrary values has been used for applications. In this way, the performances of these techniques have been investigated.

Nowadays, machine learning (ML) algorithms have been widely chosen for classifying satellite images for mapping Earth's surface. Support Vector Machine (SVM) and Random Forest (RF) stand out among these algorithms with their accurate results in the literature. The aim of this study is to analyze the performances of these algorithms on land use and land cover (LULC) classification, especially wetlands which have significant ecological functions. For this purpose, Sentinel-2 satellite image, which is freely provided by European Space Agency (ESA), was used to monitor not only the open surface water body but also around Marmara Lake. The performance evaluation was made with the increasing number of the training dataset. 3 different training datasets having 10, 15, and 20 areas of interest (AOI) per class, respectively were used for the classification of the satellite images acquired in 2015 and 2020. The most accurate results were obtained from the classification with RF algorithm and 20 AOIs. According to obtained results, the change detection analysis of Marmara Lake was investigated for possible reasons. Whereas the water body and wetland have decreased more than 50% between 2015 and 2020, crop sites have increased approximately 50%.

Bu çalışmada, esas olarak mikrodenetleyici tabanlı çok kanallı ve kanal genişliği ayarlanabilen bir dijital geçikmeli darbe üreteci (DGDÜ) tasarımı gerçekleştirilmiştir. Bu sistemde mikrodenetleyici (PIC18F4550), kristal osilatör (8 MHz) ve 4 giriş 16 çıkışlı kodlayıcı/kodçözücü entegresi (74LS154) kullanarak 1µs-1s arasında 25 farklı genişlikte zaman-taban sinyalleri üretilmiştir. Tetikleme sinyalinden sonra seçilen zaman-taban genişliğinde ardışık olarak 32 kanallı zaman-geçiktirme dijital darbe sinyalleri elde edilmiştir. DGDÜ sistemi, ilk olarak genlik-zaman bağımlılığı bilinen referans üçgensel sinyalin bir tam periyodu içinde seçilen iki zaman pencere değerine karşı gelen sinyal genlik değerlerinin 2-kanallı örnekle-tut devresinin de bulunduğu Sinyal Analiz Birimi (SAB) ile test edilmiştir. Elde edilen sonuçların bilinen gerçek değerler ile karşılaştırılması yapılmıştır. Sonuçların uyumlu olduğu gözlenmiştir. Daha sonra ticari bir ürün olan ve ışığa duyarlı bir direnç (LDR) için oda sıcaklığında, kesikli aydınlatma ile oluşan foto-akımın zamanla matematiksel formunun belirlenmesi için kullanılmıştır. Sonuç olarak, bu yeni mikrodenetleyici tabanlı çok kanallı DGDÜ ve SAB ile hızlı, işlevsel ve esnek özellikleri olan bir otomatik veri toplama sistemi gerçekleştirilmiştir. Ayrıca derin seviyeli transient spektroskopi (DLTS), foto-uyarımlı akım transiyent spektroskopisi (PICTS) gibi yarıiletken mazlemelerin karakterizasyonları için kullanımı kolay ve ticari çift-örnekleme sistemlerine göre daha ucuz olması nedeniyle tercih edilebilir bir sistemdir., In this study, a multi-channel digital delayed pulse generator (DDPG) with adjustable channel width, mainly based on microcontroller, has been designed. In this system, 25 different time-base signals were generated between 1µs-1s by using microcontroller (PIC18F4550), crystal oscillator (8 MHz) and 4 input 16 output encoder/decoder IC (74LS154). After the trigger signal, 32-channel time-delayed digital pulse signals are obtained sequentially at the selected time-base width. The DDPG system was first tested with the Signal Analysis Unit (SAU), which also includes a 2-channel sample-and-hold circuit of the signal amplitude values corresponding to two selected time window values within one full period of the reference triangular signal whose amplitude-time dependence is known. The obtained results were compared with the known real values. It was observed that the results were compatible. It was then used to determine the mathematical form of the photocurrent over time, which is produced by pulsed illumination at room temperature for a light-sensitive resistor (LDR), which is a commercial product. As a result, an automatic data acquisition system with fast, functional and flexible features has been realized with this new microcontroller-based multi-channel DDPG and SAU. In addition, deep-level transient spectroscopy (DLTS) is a preferable system for the characterization of semiconductor materials such as photo-excited current transient spectroscopy (PICTS) because it is easy to use and cheaper than commercial double-sampling systems.

Kullanım ömrü sona eren ürünlerin çeşitli işlemlerden sonra yeniden kullanılabilir hale getirilmesi çevresel, ekonomik ve sosyal alanlarda insanoğluna birçok fayda sağlar. Çevrenin korunması, hammadde ihtiyacının azalması, kaynakların ekonomik kullanımı ve kirliliğin azaltılması gibi faydaları nedeniyle de geri dönüşüm sektörünün önemi dünya çapında giderek artmaktadır. Bu çalışmada, geri dönüşüm sürecini içeren bulanık bir stok modeli önerilmiştir. İlk olarak, Dobos ve Richter (2003) tarafından geliştirilen sabit talep ve geri dönüş oranlarına sahip genişletilmiş bir üretim/geri dönüşüm modeli atıkların yok edilme süreci ve oluşacak stok düzeyi bakımından yeniden düzenlenmiştir. Ardından talep, marjinal geri alma ve marjinal kullanım oranı parametreleri yamuk bulanık sayı olarak kabul edilip model bulanıklaştırılmıştır. Durulaştırma işlemi için kademeli ortalama entegrasyon temsil yöntemi kullanılmıştır. Böylece birim zamandaki toplam maliyet ve optimal çevrim süresi deterministik değerler olarak ifade edilmiştir. Çözülen problemin sonuçları değerlendirildiğinde, önerilen bulanık stok modelinin temel alınan deterministik stok modeline kıyasla çevrim süresi bakımından daha iyi sonuçlar verdiği gözlemlenmiştir., Making products that have reached the end of their lifespan reusable after several processes provide many benefits to human beings in environmental, economic, and social areas. The importance of the recycling industry is increasing worldwide due to its benefits such as environmental protection, reduction of raw material needs, economical use of resources, and reduction of pollution. In this study, a fuzzy inventory model including the recycling process is proposed. Firstly, an expanded production/recycling model with fixed demand and return rates developed by Dobos and Richter (2003) is rearranged in terms of the waste disposal process and the level of stock to be created. Then, the model is fuzzified by taking the demand, marginal recovery, and marginal utilization rate parameters as trapezoidal fuzzy numbers. The graded mean integration representation method was used for the defuzzification process. Thus, the total cost per unit time and the optimal cycle time are expressed as deterministic values. When the results of the solved problem are evaluated, it is observed that the proposed fuzzy stock model gives better results for cycle times compared to the deterministic stock model based on.

Food security has become a significant issue due to the growing human population. In this case, a significant role is played by agriculture. The essential foods are obtained mainly from plants. Plant diseases can, however, decrease both food production and its quality. Therefore, it is substantial to comprehend the dynamics of plant diseases as they can provide insightful information about the dispersal of plant diseases. In order to investigate the dynamics of plant disease and analyze the effects of strategies of disease control, a mathematical model can be applied. We show that this model provides the non-negative solutions that population dynamics requires. The model was investigated by using the Atangana-Baleanu in Caputo sense (ABC) operator which is symmetrical to the Caputo-Fabrizio (CF) operator with a different function. Whereas the ABC operator uses the generalized Mittag-Leffler function while the CF operator employs the exponential kernel. For the proposed model, we have displayed the local and global stability of a nonendemic and an endemic equilibrium, existence and uniqueness theorems. By applying the fractional Adams-Bashforth-Moulton method, we have implemented numerical solutions to illustrate the theoretical analysis.

In many applications, free surface flow through rigid porous media has to be modeled. Examples refer to coastal engineering applications as well as geotechnical or biomedical applications. Albeit the frequent applications, slight inconsistencies in the formulation of the governing equations can be found in the literature. The main goal of this paper is to identify these differences and provide a quantitative assessment of different approaches. Following a review of the different formulations, simulation results obtained from three alternative formulations are compared with experimental and numerical data. Results obtained by 2D and 3D test cases indicate that the predictive differences returned by the different formulations remain small for most applications, in particular for small porous Reynolds number ReP < 5000. Thus it seems justified to select a simplified formulation that supports an efficient algorithm and coding structure in a computational fluid dynamics environment. An estimated accuracy depending on the porous Reynolds number or the mean grain diameter is given for the simplified formulation.

We present a new 2.5D model for predicting the concentration of nitrogen dioxide (NO2) at street level in an urban area. This work develops the first prototype of a tool that should provide fast quantitative answers to help decision-making on the suitability of implementing traffic restrictions during air pollution episodes. The model first solves the wind flow over the city streets ignoring vorticity and turbulence. The obtained velocity field is used to transport the pollutant via a semi-Lagrangian model, combining the particle finite element method of second generation (PFEM2) with the finite element method. A variable absorption term is used to account for the part of the contaminant entering and leaving the calculation plane. The NO2 emissions are estimated from the historical traffic data. The model has been tested during four air pollution episodes in the city of Barcelona (Spain), two in summer and two in winter. A comparison against experimental measurements has been performed at seven different locations throughout the city with promising results.

Granular flow is common in many industrial applications, and involves heat generation from frictional contacts and inelastic collisions between particles. The self-heating process is still poorly understood despite being intrinsic to many processes. This work, for the first time, explores this problem experimentally by quantifying the temperature rise of granular flows in a rotating drum with a robust methodology based on infrared thermography. Particles of four different materials (lead, steel, plastic and glass) are used in the experiments, at various rotation speeds and drum fill ratios. To assess the mechanical behaviour, the flow regime of every experiment was determined. It was inferred that particles with higher density tend to generate more heat. It was also revealed that increasing the rotation speed favours the temperature rise. At the same time, the fill ratio had the least influence on the thermal response of the particulate systems considered. his project is funded through Marie SKŁODOWSKA-CURIE Innovative Training Network MATHEGRAM, the People Programme (Marie SKŁODOWSKA-CURIE Actions) of the European Union's Horizon 2020 Programme H2020 under REA grant agreement No. 813202. Dr. Franci acknowledges the support from MCIN/AEI/10.13039/501100011033 and FEDER Una manera de hacer Europa for funding his work via project PID2021-122676NB-I00. Prof. Oñate acknowledges the Severo Ochoa Programme through the Grant CEX2018-000797-S funded by MCIN/AEI/10.13039/501100011033.

We present a general framework for the analysis and modelling of frictional contact involving composite materials. The study has focused on composite materials formed by a matrix of rubber and synthetic or metallic fibres, which is the case of standard tires. We detail the numerical treatment of incompressibility at large deformations that rubber can experience, as well as the stiffening effect that properly oriented fibres will induce within the rubber. To solve the frictional contact between solids, a Dual Augmented Lagrangian Multiplier Method is used together with the Mortar method. This ensures a variationally consistent estimation of the contact forces. A modified Serial-Parallel Rule of Mixtures is employed to model the behaviour of composite materials. This is a simple and novel methodology that allows the blending of constitutive behaviours as diverse as rubber (very low stiffness and incompressible behaviour) and steel (high stiffness and compressible behaviour) taking into account the orientation of the fibres within the material. The locking due to the incompressibility constraint in the rubber material has been overcome by using Total Lagrangian mixed displacement-pressure elements. A collection of numerical examples is provided to show the accuracy and consistency of the methodology presented when solving frictional contact, incompressibility and composite materials under finite strains.

In this study, the microstructure and mechanical properties of Al 2024 powder, the prominent type of Al 2XXX series aluminum alloys widely used in the aerospace industry, and TiO2 and ZrO2 reinforcement elements used to improve material properties were investigated. Each reinforcement element is included in the material at the rate of 10%. For hybrid composite sample production, 10% hybrid composite material was procured by adding each reinforcing element equally. For each sample, powders were mixed in a 3D mixer to ensure an equal distribution of matrix powder and reinforcement elements in the samples. The samples were churned out by subjecting the two-stage them to a one-way hot press process. The furnace temperature was kept at 600 o C to preserve samples. Density and microstructure analyses were performed on the formed samples, and the results were evaluated. After all, the Archimedean density measurement method was used to obtain final densities, these samples were taken to bakelite for optical images, then scanning electron microscope (SEM) and Brinell hardness of the samples was measured. The cross-fracture strength test was completed to analyze each sample’s microstructural behavior. Finally, the theoretical radiation shielding properties of each sample were investigated. The Phy-X/PSD program was used to examine the radiation permeability properties. According to the test and analysis results, the effect of reinforcement elements on the material was determined. As a result, the highest hardness value measured was 97.5 HB at the 10% ZrO2 -reinforced MMCs. However, the relative density of the hybrid composite is better than ZrO2-reinforced MMCs. Thus, the best cross-fracture strength measured was 635 MPa in 10% hybrid MMCs. The radiation shielding parameters showed that the 10% ZrO2 -reinforced MMCs are best for shielding. Therefore, the second reasonable material for radiation shielding is hybrid reinforced materials. In the final decision, hybrid composite materials became prominent because the distinctive features of each material enhanced the samples.

This paper discusses the immediate deflection calculation of reinforced concrete beams and their consistency with the experimental results. For this purpose, a total of six T-beams with low, medium, and high reinforcement ratios were tested and then, deflection behavior was compared with the well-known Branson (1965) and Bischoff (2005) approaches. Although both approaches could yield close results for the low reinforcement at service loads by using a constant modulus of elasticity, they underestimated the deflections of medium and highly reinforced beams. Thus, the nonlinear behavior of concrete that changes with stress was also considered in the subsequent analyzes. As a result, the developed new approach could predict the experimental deformations very accurately, especially at the level of service loads.

Porous NiAl parts were formed by using Ni and Al elemental powders, preformed NiAl as diluent and NaCl particles as space holder (SH). The aim of utilizing preformed NiAl (30%-40%) as a diluent was to preserve the shape of the products. The amounts of the SH NaCl particles in NiAl were 25-50-75 vol.% and their sizes were in 300-500 µm range. Porous NiAl samples were prepared by volume combustion synthesis (VCS). The adiabatic temperatures of the Ni+Al mixtures having 30 and 40% diluent NiAl were calculated as 1638.9 and 1460.8°C, respectively. Formation of NiAl phase was verified by XRD analyses. In the green pellets, the total porosity amount was higher than the added NaCl amount. Also it was slightly higher in the product pellets than in the green pellets before VCS. Compressive strength and microhardness values of the samples which contained 30% diluent NiAl were higher than the samples which contained 40% diluent. Average compressive strength values of the products that were obtained by 25% NaCl and 30 and 40% diluent NiAl additions were 112.0±29.5 and 66.0±20.5 MPa, respectively.

Voltage and frequency dependent of capacitance and conductivity versus voltage (C&G/ω–V) qualifications of Al/(ZnFe2O4-PVA)/p-Si structure was compared and examined at lower and higher frequencies as 10 kHz and 1 MHz, respectively. The negative capacitance (NC) is a phenomenon that occurs at low frequencies and is primarily caused by minority carrier injection, series resistance (Rs), and surface states (Nss). Because of the specific density distribution and relaxation times of Nss, NC acts different behavior at lower and higher frequency levels and loses its effectiveness with increasing frequency. Also, the fluctuations in C and G/ω were ascribed to doping concentration, surface states loss charges, and interlayer thickness. Nss was acquired using the low-high frequency capacitance method (CLF-CHF), and the forward biased C−2 vs V graphs (at 10 kHz to 1 MHz) were used to determine the Fermi level (EF), barrier height (ΦB), and concentration of doped acceptor atoms (NA). Accordingly, it has been detected that C and G/ω are highly dependence on biases and frequencies. Then again, the polarizations and surface states effect are barely perceptible at extremely higher frequency levels. Thus, polarization and Rs stand out as important parameters that should be taken into account when examining the basic parameters of electronic devices.

A sudden slope failure occurred in Manisa possibly due to the effect of water infiltration because of a slightly damaged sewage pipe. Considering that there was no other evidence such as rainfall or any loading conditions to trigger the slope failure, a laboratory investigation on the soil’s unsaturated hydro-mechanical properties was initiated. Slopes are naturally unsaturated soils, and they may lose their stability with increased saturation degrees with water infiltration. Thus, for a proper investigation, the unsaturated hydro-mechanical properties of soils should be determined. The results presented in this study are focused on determining the key parameters to evaluate the slope failure for unsaturated soil conditions. In this regard, hydraulic conductivity and suction characteristics and the shear strength parameters were determined as well as the classical geotechnical properties of the soil. Classification of soil was determined as silty sand which is known to have slight to moderate suction stresses and mostly affected suddenly by water infiltration. A flexible-wall permeability test was run with a falling head procedure and the saturated hydraulic conductivity of the soil sample was measured as 1x10-7 m/s. Suction characteristics were detected by filter paper method, besides, the soil water retention curve of the soil was constructed. The maximum matric suction of the soil was measured as 2887 kPa for an air-dried sample. Following, the shear strength parameters were measured by conventional direct shear test for both dry and soaked conditions. Finally, the friction angle due to suction was calculated to be 1.7 degrees from the results of dry and saturated shear strength parameters.

The aim of this study is to establish an effective protocol for in vitro micropropagation from node explants of the 'Paradox' (Juglans regia x J. hindsii) rootstock. In the first stage of the study, the node explants were cultured in semi-solid media after being exposed to different sterilization methods. The most effective sterilization method was observed as ST2 with the lowest darkening rate (4 %). According to the results, SP4 medium provided the highest number of shoots per unit explant (1.05 shoots/explant) and 100 % shoot formation, SP2 medium provided the best mean shoot length (1.6 cm) and the mean number of nodes per unit explant (7.95 nodes/explant). Best root induction was provided from ½ Modified MS medium containing 4 mg/L IBA with 30 g/L sucrose. For root induction explants were retained under dark conditions for 7 days at 24±2oC. In order to ensure root formation and elongation, shoot explants with root induction cultured in a 16-hour photoperiod (3500 lux) for 21 days in different nutrient media containing 2.4 mg/L Gelrite, hormone-free and mixed with vermiculite (1:1 v/v) and was rooting rate is 45.45 % in ¼DFe medium.

Using the gamma spectroscopy system, it can be determined whether environmental samples or standard radioactive sources are radioactive, and from which elements their radioactivity originates. The purpose of Monte Carlo (MC) simulation is to model a real-life system with its inputs and evaluate the outputs with real results. This study calculates the experimental efficiency of a p-type HPGe detector using a 0.5 g/cc Epoxy Matrix Marinelli beaker and compares these results with GESPECOR and PHITS MC Simulation programs. Thus, the thickness of the dead layer, which thickens over time and affects the detector efficiency, was determined from the most compatible result of the MC calculations made repeatedly at various alternative thicknesses to the experimental results. For 1.5 mm dead layer thickness, less than 2 % error was found between the test and MC results, especially at energies above 165 keV. As a result, it was determined that the dead layer thickness of the detector reached 1.5 mm with an increase of 114 % after its production. The current value of the dead layer thickness of each detector should be checked, as the efficiency affects the determination of the activity.

Utilization of wood waste particles (WWP) is important for environmental and economic concern. This study focuses on the behavior of mortars having WWP with various amounts. Incorporation of WWP brings about the advantages such as decrease in the mass and cost of the mortar. In the present study, the proportions of the wood waste particles replacing the crushed sand in the mortars by volume were 0, 10, 20, 30 and 40 %. Physical, mechanical and capillary absorption properties have been investigated. In addition, microstructure of the mortars has been examined with optical microscope. As compared to control specimen, dry bulk density decreased from 2.2 to 1.5 kg/m3, apparent porosity increased about 2 folds, and water absorption increased about 4 folds, for sample in which 40 % of crushed sand was replaced with WWP. Mechanical values reduced with increasing WWP amount. On the other hand, during compressive and flexural strength tests, samples containing WWP presented a gradual decrease in strength, thus they exhibited a more ductile behavior.

Combustion of conventional energy sources produces pollutants such as SOx, NOx, and CO; the use of hydrogen and methane can eliminate these harmful emissions. In fuel cell technology and other uses, hydrogen must be refined by extracting methane from the methane/hydrogen combination, produced via dry or steam reforming. This study investigates the adsorption and separation capabilities of recently discovered zeolite-templated carbons (ZTCs) for binary mixtures consisting of hydrogen and methane. To assess the adsorption and separation performances of these carbon-based nanostructures, grand canonical Monte Carlo (GCMC) simulations were used. The simulation results revealed that AFY (|(C6H15N)3(H2O)7|[Co3Al5P8O32]) and RWY (|(C6H18N4)16| [Ga32Ge16S96]) structures could be viable alternatives for applications involving adsorptive gas separation based on selectivity and the CH4 uptake capacity. The selectivity of AFY was calculated to be 176, while its capacity to uptake CH4 was found to be 2.57 mmol/g, the selectivity of RWY was calculated to be 132, and its CH4 uptake was 3.49 mmol/g.

The aim of this study is to fabricate in-situ TiC particle reinforced Fe matrix composites via volume combustion synthesis (VCS) through heating by two different sources. One group of reactant pellets was ignited by heating in an induction furnace (IF). The other group was ignited via heating by using a tungsten inert gas (TIG) torch. Thus, the differences in the microhardness and microstructure of the obtained composites could be compared. Fe, C and Ti elemental powders were used to obtain composites that contained 50 vol. % TiC in the Fe matrix. In the repeated experiments, the ignition temperatures of the IF pellets were found to be in 1164-1184 oC range. The formation of composites was verified by X-ray diffraction (XRD) analyses, where it was seen that the products were composed of TiC and Fe with trace impurity phase. Scanning electron microscope (SEM) examinations showed that the in-situ formed TiC particles were regularly distributed in matrix in both series. The TiC particles obtained by TIG heating were about 5 times larger than the particles obtained by induction heating. Microhardness values of the samples were higher in IF series as compared to TIG series. It was shown that 50 vol. % TiC particle reinforced Fe matrix composites could be obtained by both heating methods. TIG was found to be a much practical method, when compared to conducting VCS in a furnace.

Recent studies have paid particular attention to polymer-nanoparticle composite materials considering they have a number of interesting properties, which include optical, thermal, electrical, and others (Reyna-Gonzalez et al., 2009; Yakuphanoglu et al., 2010). In this study, a free radical polymerization process was used to create a copolymer of N-vinylcarbazole (NVC) and benzyl methacrylate (BZMA) at 25–75 mol% each. The procedure was conducted at 70°C with azobisisobutyronitrile (AIBN) acting as the initiator. Nano zinc oxide powders were then added to composites at three different ratios of 5%, 10%, and 15% weight of the copolymer. In order to better understand the structures of the P(NVC-co-BZMA) and its composites, FT-IR, 1H NMR, and UV spectroscopic techniques were also implemented. The optical characteristics of both the pure copolymer and its composites were examined. In the visible region, the composite containing 15% nano ZnO had the highest optical absorbance value. Additionally, the thermal behaviours of the composites and copolymers were analysed.

Accurate estimation of streamflow has an important role in water resources management, disaster preparedness and early warning, reservoir operation, and sizing of water structures. In this study, Extreme gradient boosting (XGBoost) and K-Nearest Neighbours (KNN) algorithms are used for the estimation of streamflow. In order to reveal the appropriate model, the raw model and models with optimized parameters were evaluated while the models were being built. In the setup of the models, various training test rates were also tried, and it was investigated which data division showed more effective results. For this purpose, the data were divided into ratios such as 60-40, 70-30, 80-20, and 90-10, respectively, and the model results were compared. Various statistical indicators such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R2) were used when comparing the models. As a result of the analysis, it was determined that the most suitable model for monthly streamflow estimation was obtained by using the optimized Xgboost algorithm and 60-40% data division. The obtained outputs constitute a vital resource for decision-makers regarding water resources planning and flood and drought management., Accurate estimation of stream flow has an important role in water resources management, disaster preparedness and early warning, reservoir operation, and sizing of water structures. In this study, Extreme gradient boosting (XGBoost) and K-Nearest Neighbours (KNN) algorithms are used for modeling river flows. In order to reveal the appropriate model, the raw model and models with optimized parameters were evaluated while the models were being built. In the setup of the models, various training test rates were also tried, and it was investigated which data division showed more effective results. For this purpose, the data were divided into ratios such as 60-40, 70-30, 80-20, and 90-10, respectively, and the model results were compared. Various statistical indicators such as root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) were used when comparing the models. As a result of the analysis, it was determined that the most suitable model for monthly flow estimation was obtained by using the optimized Xgboost algorithm and 60-40% data division. The obtained outputs constitute a vital resource for decision-makers regarding water resources planning and flood and drought management.

Half-metallic properties of NbAl2F4 spinel and semiconductor characteristics of TcAl2F4 spinel were investigated with the help of the WIEN2k program. NbAl2F4 spinel shows a metallic character in the up-electron states, while it has a semiconductor nature in the down-electron states. In NbAl2F4 spinel, the Eg bandgaps were calculated in GGA and GGA+mBJ 1.551 eV and 1.622 eV, respectively. The EHM half-metallic bandgaps were obtained 0.410 eV and 0.422 eV, respectively. In the up-spin states of TcAl2F4 spinel, Eg values were obtained 1.199 eV and 1.447 eV for the GGA and GGA+mBJ methods, respectively, while they were obtained 1.281 eV and 1.519 eV in the down-spin states, respectively. When GGA+mBJ is used, it is easily observed that the semiconductor characters increase. Total magnetic moments of NbAl2F4 and TcAl2F4 spinels were calculated 6.00 µB/cell and 10.0 µB/cell, respectively. When both electronic and magnetic moment values are carefully examined, NbAl2F4 and TcAl2F4 spinels can be used as alternative compounds in spintronic applications.

The Uniaxial compressive strength (UCS) is an important geotechnical property of rock used in tunnel design, rock mass classification and other surface and underground mining projects. It is the Key parameter of rock mass rating (RMR) and the RMR is the basic of all the slope stability analyses methods. This key parameter of slope stability analyses and tunneling can be determine easily by axial and diametral point load test (PLI/Is50). In the past irregular lumps PLI is also correlated with UCS but the data is limited particularly the rocks along Karakoram High Way (KKH), North Pakistan. In this study the diametral, axial and the irregular lumps PLI is correlated with UCS using dimension stones of tectonic regions along KKH. A methodology of size correction of irregular lumps have been set. Using regression analyses the PLI of cores and lumps have been correlated with UCS. The significance of the correlation were developed by correlations coefficients. It is found that the Is(50) of irregular lump of white marble is 1.8MPa. For pink and white granite the Is(50) value is recorded as 3.2MPa and 2.4MPa respectively. In the size correction factor (F) the power n for irregular lump is corrected as 0.8 for marble lumps and the n value for pink and white granite is 0.9 and 1.4 respectively. For diametral and axial PLI the power n is used as 0.45. The correction factor F=(De/50)0.8 is suggested for marble irregular lumps while for axial and diametral specimens of marble the correction factor is F=(De/50)0.45 is recommended. In the case of pink and white granite the correction factors are F=(De/50)0.9 and F=(De/50)1.4 respectively.

Effects of the pregnancy and the following lactation periods on the lifespan entropy of the women has been evaluated. In the case of singleton pregnancy, a wealthy woman may generate 1.5% and in the case of twin pregnancy 2.1% of the total lifespan entropy of a non-pregnant wealthy women. In the case of a poor woman the singleton pregnancy, may generate 1.8% and in case of the twin pregnancy 2.1% of the total lifespan entropy generated by the non-pregnant wealthy woman. Results of the diet-based thermodynamic calculations for the poor women are compared with the demographic data collected across pre-industrial Europe and a good agreement was found.

A high level of cancer awareness may contribute to early diagnosis and improve cancer survival. This study is aimed to assess the level of awareness of occupational cancer among airline pilots. To the best of the authors’ knowledge, this study has examined pilots’ occupational cancer awareness levels for the first time. A brand-new cancer awareness survey was used to examine the awareness level of airline pilots on cancer. The analysis of variance (ANOVA) method was employed to analyze the survey results. The response rate was % 43.6. Data had been collected from 523 individuals, 48 of whom were female pilots. Of the participants 67.3% were long-haul pilots. Female airline pilots were much more aware of cancer in comparison to male airline pilots. Pilots flying 81-90 hours per month were much more aware of cancer in comparison to other participants. Academic articles, magazines and social media were sources of knowledge for 64.6 % of pilots whereas 39.5% of pilots were informed by e-learnings and recurrent trainings regarding the occupational cancer. According to the findings of this study, there is a need for training and media-based interventions to raise awareness and instil safe and healthy lifestyle practices at the workplace in the airline industry.

GLONASS system; It has become the second system operating on a global scale after the GPS system in the world, after completing the satellite constellation and using it at full capacity as of 8 December 2011. Due to the increasing need for high accuracy and precision real-time location information, CORS networks have become widespread in the world. In Turkey, it was established as CORS-TR and opened for use in December 2008. Comprehensive studies investigating the effects of Network-Based RTK techniques (VRS, FKP, and MAC) in the CORS-TR network are very limited due to the fact that the GLONASS system has been used at full capacity recently. In this paper, it is aimed to determine the effect of measurements derived from the Network-Based RTK techniques in the CORS-TR network of the GLONASS system on the location accuracy, and thus to make a business plan according to the accuracy and precision requirements of all civil and military users. For this purpose, simultaneous measurements were made with 6 GNSS receiver devices of the same brand and model. A total of 308,908 epoch data (northing value, easting value, and ellipsoidal height: projection coordinates (ITRF96 Datum, 2005.00 Reference Epoch)) were collected at one-second intervals in each technique and for seven days of measurements. As a result of the evaluation and analysis of the data sets obtained with the measurements; It has been observed that the GLONASS system has a positive effect on position accuracy, but in some cases, it also has disruptive effects. It has been observed that the most important contribution is to increase the number of visible satellites and to enable measurements with GLONASS satellites in cases where GPS satellites alone are not sufficient, especially in areas where the satellite elevation angle is narrowed, such as city centers, and forest areas.

The hyperspectral images have so far been widely utilized in monitoring and detecting the changes in a broad range of environmentally related matters. The hyperspectral image analysis yields maps that show spatial dispersion of physical and ecological characteristics of the terrain. Within the scope of the current study, an integrated Fuzzy-MCDM in a Geographic Information Systems (GIS) platform was used to map the health condition of Ramsar forest. Spectral indices can provide different methods for identifying vegetation coverings. For forest health analysis, spectral indices such as NDWI, CRI1, PSRI, PRI, and NDVI were used to infer the causative factors of forest health. The findings highlight the suitability of the used methodology in identifying potential forest statuses, where forest health protection measures can be taken in advance. The results also suggest that the southern and the western aspects of the study area are of “very low” to “low” forest health. Furthermore, the results indicate a high potentiality for applying the spatial MCDM techniques as an effective tool for the forest health investigation.

Recently, three-dimensional visualization of soil characteristics has been widely used in geotechnical engineering applications. In this study, the 3-D visualization of Tepebaşı area soils, the province of Eskişehir, is prepared using SPT data, soil classes through Environmental Visualization System-Mining Visualization System (EVS-MVS) programs. Moreover, the local soil conditions were classified according to the Turkish Earthquake Code 2018 and digitized using Geographical Information Systems (GIS) and the data observed by the field and laboratory tests. The local soil conditions are observed utilizing the map classified according to the Turkish Earthquake Code 2018. By taking these 3D visuals and maps into consideration, it is determined that soil is alluvial. The ground water level is high, especially in the city center; the local soil type is ZD, ZE and ZF, according to the Turkish Earthquake Code (2018). Examination of the 3D visuals and maps reveal soil’s the changing soil profile with a gradual gradation from fine grain soil (clayey and silty) at the surface; to coarse grain soil (sandy and gravelly). Therefore, the 3D visuals and maps established in the scope of this study may provide preliminary information to the researchers and pragmatists in the area.

GNSS observation intervals can be tuned from low rate to high rates (such as 300 to 1 s) for the specific applications. In this study, the effect of sampling intervals of 1, 5, 15, and 30 s on the convergence time and positioning accuracy of static precise point positioning is investigated using high-rate data from 26 IGS (International GNSS Service)-MGEX (Multi-GNSS Experiment) stations over a three-week period in 2020. Six different GNSS constellations – namely, GPS-only, GLONASS-only, Galileo-only, BeiDou-2-only, BeiDou-3-only, and multi-GNSS (GPS+GLONASS+Galileo+BeiDou-2+BeiDou-3) – are processed for static PPP. The results show that the use of higher rate of observation intervals significantly reduces the PPP convergence time for each GNSS constellation. Maximum improvements between 30 s and 1 s are found to be 55%, 60%, and 55% for north, east, and up components, respectively, for Galileo PPP. However, the results of positioning accuracy indicates that the use of higher rate of observation intervals slightly degrades the PPP converged positioning accuracy for each GNSS constellation except for BDS-3 and multi-GNSS PPP modes. The results demonstrate that the satellite clock interpolation error is mainly responsible for the degradation in accuracy at the higher rate of observation intervals compared with the orbit interpolation error.

The amount of chlorophyll in a plant useful to indicate its physiological activity and then changes in chlorophyll content have been used as a good indicator of disease as well as nutritional and environmental stresses on plants. Chlorophyll content estimation is one of the most applications of hyperspectral remote sensing data. The aim of this study is to evaluate dimensionality reduction for estimating chlorophyll contents from hyperspectral reflectance. Random Forest (RF) has been applied to assess biochemical properties such as chlorophyll content from remote sensing data; however, an approach integrating with dimensionality reduction techniques has not been fully evaluated. A total of 200 Zizania latifolia leaves with 5 treatments from Shizuoka University field were measured for reflectance and chlorophyll content. then, the regression models were generated based on RF with three dimensionality reduction methods including principal component analysis, kernel principal component analysis and independent component analysis. This research clarified that PCA is the best method for dimensionality reduction for estimating chlorophyll content in Zizania Latifolia with a RMSE value of 5.65 ± 0.58 μg cm-2.

Road extraction plays an important role in urban planning and city extension issues, as well as in road monitoring, traffic management and map updating. Technological advances may offer a wealth of data and techniques that could be implemented in road delineation and extraction, as well as in change detection projects. Among the various methods that have been developed for this purpose, remote sensing techniques and especially digital processing of satellite data could contribute significantly in this direction. This paper presents the study of a road network which concerns the city of Kastoria located in northwestern Greece and its surrounding area. The special character of the road network is closely related to the city’s cultural value which is depicted in its structure. Satellite images of various spatial resolutions were employed for digital processing. Landsat 8 imagery was used in order to detect and delineate the linear features through spatial enhancement, while Landsat 5 images were used to detect changes over time through visual interpretation. Semi-automatic techniques were applied to SPOTmaps products to extract the road network, while an object-oriented approach was applied to QuickBird imagery in order to combine the spatial components with spectral properties. Through semi-automatic digitization and object-oriented workflows, the export of the studied part of the road network in vector format was achieved, thus facilitating the process and reducing the required time. The resulted data are efficient in road network delineation and could be combined with other data for road maintenance and extension, change detection issues, as well as for cultural and touristic purposes.

In this paper, an effective method for the classification process simulation in 75¬mm hydrocyclone is considered. The simulation results and computational time are compared using Reynolds stress model (RSM) and different large eddy simulation (LES) subgrid-scale models as turbulence models, and the volume of fluid model (VOF) as a multiphase model. The Lagrangian discrete phase model (DPM) is used to simulate the classification process of particles. As the experimental result for comparison of simulation results, Hsieh's experimental data are used. When the different LES subgrid-scale models are used, the solution converges stably by various solution convergence methods without increasing the grid numbers or reducing the size of time steps than RSM model. As a result, it is confirmed that when an appropriate simulation method is applied with the LES-WMLES S-Omega model, more accurate axial water flow velocity distribution and particle classification simulation results can be obtained at a computational cost similar to that of using the RSM model.

The household and industrial use, as well as mining of coal, pose various environmental and health risks including lung and kidney diseases such as Balkan Endemic Nephropathy (BEN). BEN is a kidney disease and it is geographically confined to Balkan countries where extensive lignite deposits are located. The most accepted cause of BEN is the use of untreated waters contaminated by lignite-derived organic contaminants. Afşin-Elbistan basin contains approximately 50 % of the lignite reserves of Turkey which makes it an ideal location for the current study. In this work, water samples were taken from 10 different locations in the Afşin-Elbistan basin and they were analyzed for organic and inorganic contaminants. Results showed that none of the water samples were contaminated with inorganic contaminants and indeed met the Turkish drinking water standards. GC-MS analyses of the water samples revealed similar chromatograms. Briefly, all the water samples have similar organic compound types such as n-alkanes, chlorophyll-derived phytols, and plant- and animal-derived acids (i.e. palmitic acid). On the other hand, none of the samples were contaminated with carcinogenic and/or nephrotoxic organic compounds such as polyaromatic hydrocarbons and aromatic amines, which is contrary to many, but not all of the previous works conducted in Balkan countries. All these results may indicate that the influence of coal deposits on the groundwaters is minimal.

With its development, artificial intelligence has formed the basis for many studies aimed at facilitating people's lives. More successful results have been tried to be obtained with the increasing data and developing equipment in these studies. It is seen that these developments in artificial intelligence are reflected in the studies related to sign language conversion. In this study, a data set belonging to the letters in the Turkish Sign Language Alphabet was created, and the classification process was carried out with both the deep learning model we created and VGG16, Inceptionv3, Resnet, and Mobilnet models, which are frequently used in image classification. In addition, an open-source data set containing the letters in the American Sign Language Alphabet was organized similar to the data set containing the letters in the Turkish Sign Language Alphabet we created, and Deep Learning models were used to classify the letters in the American Sign Language Alphabet by using this data set. Performance evaluations of the classifications made by Deep Learning Models using both data sets were made. With this study, the results obtained from training Deep Learning methods with different data sets were compared. In addition, it is thought that the study will be useful in determining both the data set and the deep learning method to be used for the studies on the recognition of Sign Language Letters.

In this work, metal-semiconductor photodiodes with organic interlayers were produced, and their electrical properties were investigated under different light intensities. CongoRed was used as interlayer and grown as a thin film using spin coating technique on p-type silicon substrates cleaned by different chemical methods. The changes in electrical parameters of completed Al/CongoRed/p-Si/Al diodes were investigated under dark and different light intensity. From results obtained, it has been seen that the fabricated devices show photodiode properties, and as a result, they can be employed in opto-electronic applications.

The purpose of this article is to show the adaptation of the Kantorovich type integral to the Dunkl operator. This article gives a sequence of operators to get an approximation result. The variant of the operator which is the Kantorovich type integral has been given and examined the approximation ratio by the first and second order modulus of continuity. The approximation order of the operators is shown by the first order modulus of continuity and the Lipschitz class functions.

With the increasing interest in outdoor recreation activities, the demand for national parks and natural parks also increases. Natural parks are natural parts with vegetation and wildlife features, suitable for public recreation and entertainment in the integrity of the landscape. Unlike National Parks, they are natural parts that have protection, recreation and tourism areas with only natural resource values that are rare nationally and internationally. Today, natural park areas are visited by many people who come for recreation activities. For this reason, recreational activities in natural parks gain importance and take an important place in tourism activities. Kadınçayırı Natural Park, which is the research area, is located between Çankırı and Kastamonu provinces. It has aimed to reveal the recreational potential by evaluating user trends and expert preferences with the surveys conducted in the field. Analytical Hierarchy Process (AHP) analysis has been applied to the obtained data arranged in line with Gülez Method features and it has been determined that the recreational service and potential of the Kadınçayırı Natural Park showed enrichment and there are some criteria that affect the recreational activities in the area and in this context, suggestions have been developed in terms of the Landscape Architecture professional discipline.

The authors consider the problem of reducing the dredge performance when operating at subzero air temperatures. This problem is particularly relevant for deposits located in the Far North, where the dredging season is limited by climatic conditions. During the period of subzero air temperatures dredge performance decreases significantly due to the icing of dredge structure. In consequence, dredging operations are terminated until the occurrence of favorable conditions for work. In this regard, the authors propose a method for isolating the open-pit mine with a hangar made of contemporary construction materials. Cellular polycarbonate, which has several advantages, was chosen as the most promising material for insulating dredging works. The article offers the technical and technological solutions for the proposed method of extending the dredging season. The costs of a dredge hangar for dredges of different sizes and the annual cost of its movement are calculated. A method has been developed for determining the optimal maneuvering angle of the dredge and the width of the single face, whose values depend on the type of dredge and the gold content in the sand. The areas of dredge hangars are determined by the graphical-analytic method. The article presents an example of the air temperature dynamics in a dredge hangar during the year, as well as determines the duration of the mining season., Yazarlar, sıfırın altındaki hava sıcaklıklarında çalışırken tarama performansını düşürme problemini göz önünde bulundururlar. Bu sorun özellikle, tarama mevsiminin iklim koşullarıyla sınırlı olduğu Uzak Kuzey'de bulunan yataklar için geçerlidir. Sıfırın altındaki hava sıcaklıkları döneminde, tarama yapısının buzlanması nedeniyle tarama performansı önemli ölçüde azalır. Sonuç olarak, çalışma için uygun koşullar oluşana kadar tarama işlemleri sonlandırılır. Bu bağlamda, yazarlar, çağdaş inşaat malzemelerinden yapılmış bir hangar ile açık ocak madeni izole etmek için bir yöntem önermektedir. Çeşitli avantajlara sahip hücresel polikarbonat, yalıtkan tarama çalışmaları için en umut verici malzeme olarak seçilmiştir. Makale, tarama mevsimini uzatmak için önerilen yöntem için teknik ve teknolojik çözümler sunmaktadır. Farklı büyüklükteki taramalar için bir tarama hangarının maliyeti ve hareketinin yıllık maliyeti hesaplanır. Değerleri tarama tipine ve kumdaki altın içeriğine bağlı olan, taramanın optimal manevra açısını ve tek yüzün genişliğini belirlemek için bir yöntem geliştirilmiştir. Tarama hangarlarının alanları grafik-analitik yöntemle belirlenir. Makale, yıl boyunca bir tarama hangarındaki hava sıcaklığı dinamiklerinin bir örneğini sunmakta ve madencilik sezonunun süresini belirlemektedir.

With the growing interest in renewable energy systems, studies on the sustainability of small-scale wind turbines have been published in recent years. A literature review was conducted in this study to compile scientific studies conducted to evaluate the environmental effects of medium and small-sized wind energy systems using the life cycle assessment. Life cycle assessment is a method of evaluating the environmental sustainability of a product, process, or system that is becoming more important in the context of decisions and policies in the energy sector. The environmental effects of medium and small-sized wind turbines on the life cycle size have been investigated in this study, which looked at studies conducted since 2004. The vast majority of these studies conducted environmental sustainability assessments based solely on a few environmental impact indicators such as global warming potential. There are only a few studies that consider a wider range of environmental effects. The collection and analysis of studies examining the life cycle environmental sustainability of medium and small-scale wind turbines are important for determining the future vision of small-scale energy production systems., Son yıllarda yenilenebilir enerji sistemlerine olan ilginin artmasıyla birlikte küçük ölçekli rüzgâr türbinlerinin sürdürülebilirliği konusunda çalışmalar yayınlanmıştır. Bu çalışmada, yaşam döngüsü analizi yöntemi kapsamında orta ve küçük ölçekli rüzgâr enerji sistemlerinin çevresel etkilerinin değerlendirilmesine yönelik yapılan bilimsel çalışmaların derlenmesi amacıyla bir literatür çalışması yapılmıştır. Yaşam döngüsü analizi enerji sistemlerinin çevresel sürdürülebilirliğini değerlendirmek ve bu alandaki kararlar ve politikalar bağlamında giderek daha önemli hale gelen bir yöntemdir. Bu araştırmada öncelikle orta ve küçük ölçekli rüzgâr türbinlerinin yaşam döngüsü boyutunda çevresel etkileri konularında 2004 yılından bu yana yapılmış olan çalışmalar taranmıştır. Bu çalışmaların çoğunluğu yalnızca dar bir gösterge aralığı göz önüne alınarak çevresel değerlendirmeler gerçekleştirmiştir. Daha geniş bir çevresel etki yelpazesini dikkate alan az sayıda çalışma vardır. Orta ve küçük ölçekli rüzgâr türbinlerinin yaşam döngüsü çevresel sürdürülebilirliklerini analiz eden çalışmaların derlenerek irdelenmesi küçük ölçekli enerji üretim sistemlerinin gelecek vizyonun belirlenmesi açısından büyük önem taşımaktadır.

The present manuscript deals with some certain finite sums and identities pertaining to some special numbers. Using generating functions methods, some relations and identities involving the Apostol type Euler and combinatorial numbers, and also the Fubini type numbers and polynomials, are given. Then, by using some certain classes of special finite sums involving the following rational sum which is defined by Simsek (2021b): y(r,ϑ)=∑_(b=0)^r▒〖(-1)^r/((1+b) ϑ^(b+1) 〖(ϑ-1)〗^(r-b+1) ),〗many new certain finite sums and formulas related to the Leibnitz, Harmonic, Changhee, and Daehee numbers are obtained. Moreover, some applications of these results are presented.

In the last decades, global warming has changed the temperature. It caused an increasing the wildfire in everywhere. Wildfires affect people's social lives, animal lives, and countries' economies. Therefore, new prevention and control mechanisms are required for forest fires. Artificial intelligence and neural networks(NN) have been benefited from in the management of forest fires since the 1990s. Since that time, machine learning (ML) methods have been used in environmental science in various subjects. This study aims to present a performance comparison of ML algorithms applied to predict burned area size. In this paper, different ML algorithms were used to forecast fire size based on various characteristics such as temperature, wind, humidity and precipitation, using records of 512 wildfires that took place in a national park in Northern Portugal. These algorithms are Multilayer perceptron(MLP), Linear regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree and Stacking methods. All algorithms have been implemented on the WEKA environment. The results showed that the SVM method has the best predictive ability among all models according to the Mean Absolute Error (MAE) metric. Son on yılda, küresel ısınma sıcaklığı değiştirdi. Orman yangınlarının her yerde artmasına neden oldu. Orman yangınları insanların sosyal yaşamlarını, hayvan yaşamlarını ve ülke ekonomilerini etkiler. Bu nedenle orman yangınları için yeni önleme ve kontrol mekanizmalarına ihtiyaç duyulmaktadır. 1990'lı yıllardan itibaren orman yangınlarının yönetiminde yapay zeka ve sinir ağlarından yararlanılmaktadır. O zamandan beri, çevre biliminde çeşitli konularda makine öğrenmesi (ML) yöntemleri kullanılmıştır. Bu çalışma, yanan alan boyutunu tahmin etmek için uygulanan ML algoritmalarının performans karşılaştırmasını sunmayı amaçlamaktadır. Bu yazıda, Kuzey Portekiz'deki bir milli parkta meydana gelen 512 orman yangınının kayıtları kullanılarak sıcaklık, rüzgar, nem ve yağış gibi çeşitli özelliklere dayalı olarak yangın boyutunu tahmin etmek için farklı ML algoritmaları kullanılmıştır. Bu algoritmalar Lineer regresyon, Destek Vektör Makineleri (SVM), Çok Katmanlı Algılayıcı, KEn Yakın Komşular (KNN), Karar Ağacı ve Yığınlama yöntemleridir. Tüm algoritmalar WEKA ortamında gerçeklenmiştir. Sonuçlar, Ortalama Mutlak Hata (MAE) metriğine göre tüm modeller arasında SVM yönteminin en iyi tahmin yeteneğine sahip olduğunu göstermiştir.

Potato is an industrial plant that is produced and consumed globally due to its cheapness, high yield in the unit area, high nutritional values. It is used in many different fields. It has been stated that wild species with various characteristics can be used in studies to increase productivity because they have greater rate of genetic variation than their domesticated relatives. One of the wild species of potato found in nature is S. commersonii Dunal. It is more resistant to many stresses than cultivated potato S. tuberosum L. Also, its tuber has better quality due to the fact that it contains a higher proportion of dry matter. With the aim of determining the effects of miRNAs in tuber production and root characteristics relation we aimed to detect miRNAs in two transcriptome libraries of S. commersonii. In this study miRNAs were evaluated for the first time in the wild potato transcriptome data using in silico analysis. A number of miRNAs were identified, and their potential roles in tuber were discussed.

The amount and conformation of bovine serum albumin upon adsorption on titanium (Ti) surfaces containing nanotubes with different pore sizes were investigated. Nanotubes were created on the surfaces via anodization. Protein adsorption behavior on anodized surfaces were compared with the adsorption behavior on smooth and sanded Ti surfaces. The conformational changes in surface adsorbed proteins were evaluated using the second derivative and curve fitting methods applied to the Fourier transform infrared spectra of the surfaces. Results showed that the amount of protein adsorbed on the surfaces increased significantly with increasing surface roughness and a significant change in the conformation of the adsorbed protein occurred on every surface albeit in a different fashion. When anodized samples were considered, it was observed that the changes in the secondary structure seemed to be correlated with to the pore size of the nanotubes rather than the surface roughness.

Çin’in Wuhan kentinde ortaya çıkan COVID-19 virüsü, dünya genelinde yayılarak artmaya devam etmektedir. Virüsün hızla yayılmasından en çok etkilenen sektör, sağlık sektörü olmuştur. Çalışma alanları itibariyle en riskli ortamda olan sağlık çalışanları, gerekli koruyucu ekipmanları kullansalar dahi uzun süreli ve dengeli düzenlenmemiş çalışma saatlerine bağlı olarak, virüse yakalanma riskini minimize edememektedirler. Aynı zamanda sağlık çalışanlarının koronavirüse yakalanma riski, hastanelerde açılan korona servisi birimleriyle de doğrudan etkileşim içerisindedir. Yapılan çalışmada, belirli varsayımlar üzerine kurulmuş simülasyon modelinden alınan veriler doğrultusunda korona servisi birimleri ile doktor ve hemşirelerin virüse yakalanma riskini minimize edecek bir tam sayılı doğrusal programlama (TDP) modeli önerilmiştir. Planlama ufku 14 gün olarak belirlenmiş ve model sonucunda korona servisi birimleri için virüs taşıma riskinin minimum olduğu vardiya çizelgeleri oluşturulmuştur., The COVID-19 virus, which originated in Wuhan, China, continues to spread around the world. The health sector has been the most affected by the rapid spread of the virus. Healthcare workers who are in the riskiest environment due to their working areas, long-term and unbalanced working hours, cannot minimize the risk of contracting the virus even if they use the necessary protective equipment. At the same time, the risk of COVID-19 infections among healthcare workers interacts directly with corona service units opened in hospitals. In this study, an integer linear programming (ILP) model was proposed to minimize the risk of doctors and nurses contracting the virus with corona service units, in line with the data obtained from the simulation model based on certain assumptions. The planning horizon was set to 14 days, and as a result of the proposed model, shift schedules which minimize the risk of contracting the virus were created for each corona service unit.