Energy supply is one of the most significant issues in modern society. So, energy saving becomes important in systems used frequently in daily life. Due to these energy saving concerns, there are numerous studies in literature to make supermarket refrigeration systems consume less energy. Among these studies, CO2 booster refrigeration system with flooded evaporators and parallel compressor (BFP) seems as an energy-saving and nature-friendly choice.
In this study, BFP was selected as the system of concern and the Bees Algorithm optimization was applied to get minimum power consumption (maximum COP). Gas cooler pressure (Pgc), intermediate pressure(Pint), and medium temperature (MT) level evaporator outlet quality(x14) were chosen as optimization parameters. According to the optimization results, the Bees Algorithm converged well, and these three parameters were found worthy to optimize as they brought significant energy saving in total (up to 8.7% in comparison with constant intermediate pressure and MT evaporator outlet quality).
As a result of this analysis, the optimal Pgc values were found to be between 7600 kPa and 12000 kPa at ambient temperatures ranging from 28 to 46°C. The optimal Pint values were found to be around 3500 kPa below ambient temperature of 14 °C and around 4500 kPa above this temperature. The optimal values for x14 ranged between 0.62 and 0.69.
Additionally, annual energy consumption (AEC) and total equivalent emission (TEE) for 15 years were calculated for four different climate types. The highest AEC and TEE were obtained at tropical climate with 728.56 MWh and over 10000 tons, respectively. The lowest AEC and TEE were found at continental conditions as 380.01 MWh and almost 6000 tons of emission.

PCL has limited use in drug delivery systems and tissue engineering due to its slow biodegradability. Studies are continuing on the degradation process of PCL. This study was carried out to determine the effects of graphene derivative filler on the structural and biodegradability properties of PCL composite films. PCL composite films filled with the same content (0.5 wt%) of graphene oxide (GO), reduced graphene oxide (RGO), and graphene nanoplatelets (GNP) were prepared by the liquid-phase ultrasonic mixing method. Characterization studies of the films were analyzed by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), optical microscopy (OM), and surface roughness tests. All fillers were homogeneously distributed in the polymer matrix, and polymer-filler interactions were achieved. Graphene derivatives showed different effects on nucleation, and the PCL/RGO film had the finest grain structure. The highest weight loss occurred in PCL/GO film, which had the highest porosity (23.49%) and surface roughness value of 12.33 µm. This study proposes the addition of graphene derivatives (GO and RGO) with oxygen-containing functional groups to the PCL matrix as a viable way to control the degradation process of PCL.

In the present study, a quarter vehicle active suspension model with one degree of freedom designed considering only vertical forces were examined. LQG-based closed-loop suspension control was used to minimize the response of the system according to different road profiles. Sensor noises were added for the realistic simulations of the designed control system and a Kalman filter was used to filter these noises. The active suspension system was analyzed with the MATLAB simulation software package. The feedback signal and sensor location which used for the control system were determined using the system's Gramian matrix with the new approach. The LQG control system was compared to the conventional passive suspension system, according to the obtained results. In this study, three different road inputs were applied to active and passive suspension systems modeled according to several feedback signals. Although the LQG control was exposed to sensor noise, its damping ability against different road inputs was determined to be better than the passive suspension system.

Reusing waste heat is one of the techniques for increasing energy efficiency, which is a highly emphasized issue today. The organic Rankine cycle, also known as ORC, is increasingly recognized as a promising technique for converting low-temperature heat into electricity. ORCs are designed to operate without human intervention and require minimal maintenance. Although basic ORC is increasingly accepted by the industry, there is still a need to improve cost effectiveness. For the purpose of this review, calculations of the ORC system were made for the purpose of generating electricity by utilizing the recovery of heat energy at low temperatures for companies that discharge waste heat into the environment. EES program was used to investigate the relationship between efficiency rates as well as fluid properties to be used in the ORC system. Among the various fluids used in this system, cyclohexane, R123 and R290 were determined to have the highest efficiency rates. Estimated efficiencies for these fluids are 26%, 18.28% and 8% respectively. Condenser and turbine powers were calculated and compared to determine which fluid had the optimum efficiency rate and waste heat capacity. It has been noted that as the temperature of the condenser increases, the power output of the turbine decreases. The most effective fluids for turbine power generation are cyclohexane and R123.

In this study, the designs with suitable combinations of a microstrip patch antenna and mushroom like EBG structures having different via locations are presented. The performance of the reference antenna is improved with the designs having removed and/or offset via configuration. It has been experienced with different designs that the vias removed and/or shifted from the first row of EBG structures, which are closest to the radiating patch of the antenna, have a significant effect on antenna performance. With the proposed designs, up to 32% bandwidth enhancement and up to 2.9 dBi gain increment are achieved according to the reference antenna. Moreover, the front to back ratio (F/B) of the reference antenna is enhanced to values between 26 and 29 dB from the 16.9 dB by the presented designs. In addition, while the simple single layer designs of the presented antennas facilitate their manufacturing, they also achieve a good thin profile merit (h/λo, λo is the free-space wavelength at the centre frequency) with a value of 0.05.

Photovoltaic systems are one of the renewable energy systems that convert solar radiation directly into electricity. The relationship between current and voltage of PV system is nonlinear and it has only one point where power efficiency is greatest. Power efficiency mainly depends on atmospheric conditions such as irradiance and temperature. Therefore, various maximum power point tracking algorithms have been proposed in the literature to obtain maximum efficiency. The proposed traditional methods show high performance for maximum power point tracking under uniform irradiance and constant temperature. But another situation that affects the power efficiency is the partial shading condition and there are more maximum points on the output power curve in the partial shading conditions. For this reason, traditional methods are insufficient to reach global maximum power points. Metaheuristic algorithms have been proposed to solve this problem. In this paper, particle swarm optimization, gray wolf optimization and whale optimization algorithms were selected among the metaheuristic algorithms and comparative performance analysis were made in terms of convergence rate and efficiency under partial shading conditions. Obtained results were compared both graphically and numerically.

The concept of Compressive Sensing (CS), which emerged in the 2000s, is about the existence of sparse states of signals in a transformation area other than the time axis or the axis they exist. Primary data organized in accordance with the purpose or secondary data collected in accordance with the purpose can be expressed sparsely in a size appropriate to the data structure. The CS method, which is applied to randomly collected data from the sparse form created as a result of the transformation, provides an advantage in cases where sample collection from the signal is difficult, incomplete and costly. When the total amount that can be taken is defined as 100%, the reconstruction algorithm is applied to the amount taken below this amount and called the measurement, and a signal close to the original of the signal is obtained. This study is about CS method to Frequency Modulated Continuous Wave Radars (FMCWR) based on Discrete Fractional Fourier Transform (DFrFT). The degree of FrFT is estimated with the first few scans of the FMCWR and the signal is randomly received in the amount of 25% in the next scans. In the reconstruction phase, the l1 norm of convex optimization is applied and its success is tested. When the most appropriate degree is determined as a result of degree estimation and the method is applied to 25% of the randomly collected signal; It can be seen that even when 75% of the signal is not received, very high performance is achieved in reconstructing the signal. This performance was compared with other fraction degrees and the results were expressed in a table.

In this study, we consider the Generalized Classical (GC) method based on the differential Taylor (DT) transform method for the analysis of transient regimes in simple electrical circuits. The approximate solution of nonlinear differential equations of electrical circuits with variable coefficients is found by using the GC method. It is shown that, if the solution is decomposed as steady-state and the temporary components, the use of the GC method can become more advantageous, and the transient differential equation of the circuits can be analyzed without a fully solving process. The efficiency of the considered method is illustrated by compared with the results obtained from similar problems in the literature. The results reveal that the proposed method is very effective and simple and can be applied to the analysis of both linear and nonlinear problems in physical systems. The short history and real status of the DT transform method are mentioned briefly.

Panoramic dental radiography is a common imaging technique used to diagnose dental problems. However, the resolution of panoramic dental radiographs taken with this imaging method is relatively low. As a result, dental problems may be missed. Against this background, this study proposes a method involving image preprocessing techniques and a convolutional neural network (CNN) for tooth segmentation in computer-aided clinical decision support systems using panoramic dental radiographs. The performance of the proposed method is evaluated using the dataset of the Southwest Bahia State University (UESB). First, the U-Net, SegNet and DeepLabv3+ architectures are trained and then tested on the UESB dataset. Then, pre-processing methods such as Histogram Equalisation (HE), Contrast Stretching (CS), and Contrast Limited Adaptive Histogram Equalisation (CLAHE) are applied to the UESB dataset. To evaluate the impact of these pre-processing methods on the performance, the pre-processed datasets are retrained and tested on the U-Net, SegNet and DeepLabv3+ architectures. Based on the test results obtained, it is evident that CS is the preprocessing method that significantly improves the performance of the DeepLabv3+ and SegNet architectures compared to the other preprocessing methods used in this study. The best performance is achieved by the SegNet architecture trained on the CS preprocessed dataset and is subsequently proposed for tooth segmentation. The comparative performance analysis shows that CS has a performance-enhancing effect on both panoramic dental images and ESA architectures. Furthermore, the results obtained from the proposed method are compared with previous studies on the UESB dataset and this method is one of the methods that performs remarkably well compared to similar state-of-the-art methods in the literature. In conclusion, the proposed method can be used as a powerful tool in computer-aided decision support systems that can be developed for tooth segmentation.

In a world with limited resources, it is crucial for individuals to utilise shared systems and develop strategies to optimise their usage. To cope with this, 'servicizing' has emerged as a rapidly growing promising solution, especially in car-sharing systems. These systems can be split into two: station-based and free-floating. The latter introduces more flexibility to the customers as free-floating systems allow users to pick up and drop off vehicles anywhere within predetermined operational zones. This flexibility may come with an additional cost by bringing a potential imbalance between demand and supply. This imbalance can harm the company's profitability and customer satisfaction. In this study, the imbalance problem of the system of free-floating car sharing is considered. A mixed integer linear programming model is developed and tested with real data for free floating car sharing systems to solve this problem. The proposed system consists of four modules: clustering, forecasting, optimization model, and relocation strategy. According to the results, it is observed that the system is more balanced with satisfying 9% more demand and more profitable with earning 6% more. The study was conducted on a car-sharing company that is based in Istanbul, but the results can be applied to any free-floating car-sharing system. This ensures customer satisfaction by meeting demand and balancing the system.

Serious environmental challenges such as global warming and climate change have captured a growing amount of public awareness in the last decade. Besides monetary incentives, the drive for environmental preservation and the pursuit of a sustainable energy source have contributed to an increased recognition of energy usage within the industrial sector. Meanwhile, the challenge of energy efficiency stands out as a major focal point for researchers and manufacturers alike. Efficient assembly line balancing plays a vital role in enhancing production effectiveness. The robotic two-sided assembly line balancing problem (RTALBP) commonly arises in manufacturing facilities that produce large-sized products in high volumes. In this scenario, multiple robots are placed at each assembly line station to manufacture the product. The utilization of robots is extensive within two-sided assembly lines, primarily driven by elevated labour expenses. However, this adoption has resulted in the challenge of increasing energy consumption. Therefore, in this study, a new hybrid genetic algorithm is introduced, incorporating an adaptive local search mechanism. for the mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. This algorithm has two main objectives: minimizing cycle time (time-based approach) and overall energy consumption (energy-based approach). Depending on managerial priorities, either the time-based or energy-based model can be chosen for different production timeframes.

Recent earthquakes have shown that urban transformation has become a necessity for many cities in Turkey to achieve livable conditions and to ensure the safety of life and property of the citizens. In order to fulfill the need for urban transformation in the country, "General Directorate of Infrastructure and Urban Transformation Services" has been established under the Ministry of Environment, Urbanization and Climate Change since 2013, and building-based and area-based urban transformation has been carried out. activities are coordinated by this institution. Within the framework of area-based Urban Transformation planning, areas with high-risk buildings in terms of earthquake hazard are determined by using the First Stage Evaluation Method included in the annex of the Law No. 6306 Enforcement Regulation. It was observed that the method was insufficient to determine the risk situations of buildings and was not very compatible with the detailed analysis results. In this study, new parameters to be used in addition to the parameters used for the "First Stage Evaluation Method" were studied and it was aimed to determine the risk situation in the determined region more appropriately. In this context, 402 buildings, whose risk status was determined by static analyzes from the database of the Ministry of Environment, Urbanization and Climate Change, were used. To achieve this, the parameters that may cause the buildings that are determined to be risky to be risky are determined in the database and the contributions of these determined parameters to the risky of the building are ranked from the most effective to the least using the following methods: SPSS statistical analysis software. In addition, the parameters used in the "First Stage Evaluation Method" were interpreted.

Middle-Late Carboniferous granitic rocks are widely observed in larger outcrops in the Eastern Pontide orogenic belt of the Eastern Sakarya Zone. This tectonic belt is an important part of the Anatolian plate in terms of containing igneous rocks with a wide age and composition range. This study presents new petrochemical-petrological data on Carboniferous granites in the Güneydere and surrounding area of Bayburt (NE Turkey). The granitic rocks, which include an area of approximately 5 km, represent the pre-Jurassic basement in the study area. Besides, they are unconformably overlain by Early - Middle Jurassic volcano-clastics units and Late Jurassic - Early Cretaceous limestones. They mainly consist of granite, granite porphyry and aplite, to a lesser extent granodiorite and quartz monzonite. Rocks have high SiO2 contents (60.43-75.51%) and high K calc-alkali to shoshonitic affinities and have been derived from an I-type source. The granitic rocks are metalumine-peralumine in character and are similar to post-collisional volcanic arc granitoids. Whole-rocks major and trace element trends show that plagioclase, hornblende, biotite, apatite, and Fe-Ti oxide mineral fractionations play an important role in the formation of the rocks. It has been revealed that fractional crystallization and assimilation±magma mixing processes play a role in the development of granites. Also, the saturation temperatures calculated from the whole-rock zircon values reflect lower initial magma temperatures. All results obtained indicate that parental magma of studied granitic rocks have evolved from lower/middle crust-derived melts as a result of partial melting and differentiated and emplaced in the continental magma chamber.

The need for therapeutic aromatic herbs is expanding as a result of the emergence of worldwide antibiotic resistance. The literature on the advantages of using infusions or essential oils from these plants is growing. For decades, thyme, sage, and lavender have been popular sources of essential oils and are commonly employed in modern medicine. The goal was to create a cream formulation to facilitate the application of these oils, with the hope that it would be favored in terms of dosage and sensory acceptability. In this case, Lavender, Sage, and Thyme oils were incorporated into cream formulations in advance. Antimicrobial and antifungal actions of essential oils at 5% and 10% ratios were tested for this purpose, and then they were added to the cream formulation, and the same study was repeated. This study also considered stability and consumer acceptance. The findings revealed that lavender essential oil had no impact at any dosage, while sage and thyme essential oils exhibited a selective effect. Lavender and sage showed little heterogeneity in terms of stability in cream formulations; however, thyme oil was deemed unacceptable not only in terms of texture but also in sensory aspects. Clearly, the search for new medications continues, and antimicrobial resistance caused by each new formulation is a global issue. Although resistance to essential oils has not yet been recorded, research is being conducted with the hope that they might offer a solution to global resistance-related illnesses. In this context, the findings of this study, encompassing not only a cream formulation but also data on the use of essential oils with a guiding methodology in the literature, are amenable to clinical investigation.

Ansys Fluent can be used in chemical engineering to draw velocity profiles, temperature profiles inside pipes and columns and determine pressure losses, making 2D and 3D simulations of mass separation processes using user defined functions. Computational fluid dynamics (CFD) software can be applied for the analysis of photoreactors, which initiate and sustain chemical reactions through the application of light energy. Photoreactors can be used in a variety of industries and their performance can significantly impact the efficiency of the chemical processes they support. In this study, Ansys Fluent flow simulation was applied in order to improve the design of proposed photoreactor. Firstly, base photoreactor models were simulated via Ansys Fluent CFD software. Accordingly, these base models were further developed in order to obtain high fluid velocity and homogenous flow by adding baffles and nozzles. The effects of baffle height and spacing on the total velocity and flow homogeneity were also investigated. All models were analysed with the total fluid velocity on selected points and standard deviation between the velocity data. Optimal photoreactor design with the highest fluid velocity and homogenous flow distribution was developed.

In order to evaluate kidney bean husks, extraction of pectin from this waste was carried out under hot acid and ultrasonic assisted extraction methods. Dilute solutions of different organic and inorganic acids were used as extraction solutions, and their effects on the yields and properties of the extracted pectins were investigated by making changes in extraction conditions including temperature and time. Increasing extraction temperature, longer extraction time and decreasing the pH of the medium increased the pectin yields for both methods. Pectin yields were higher when inorganic acids were used as extraction media under ultrasonic assisted extraction method. All extracted pectins are in the class of high ester pectin. The FTIR spectra of the extracted pectins and commercial pectin were very similar to each other and gave similar vibration bands.

Two new salts (4 and 5) obtained between 2-methoxy-5-sulfamoylbenzoic acid (1) and 2-aminopyridine (2) or 2-amino-4-methylpyridine (3), and their Cu(II) complexes (6 and 7) have been obtained. The structures of the salts (4 and 5) were suggested by elemental analysis, NMR, FT-IR and UV-Vis, while the structures of Cu(II) complexes (6 and 7) were suggested by elemental analysis, AAS, UV-Vis and magnetic susceptibility techniques. While the acid: base ratio was 2: 1 for 4 and 1: 1 for 5 salts, the metal: acid: base ratio was 1: 2: 2 for 6 and 7. According to the results of spectroscopic analysis, the structures of 6 and 7 compounds were proposed as octahedral. Additionally, antimicrobial activities of all compounds were studied against Pseudomonas aeruginosa (ATCC 27853), Staphylococcus aureus (NRRL B-767), Bacillus subtilis, Enterococcus faecalis (ATCC 29212), Escherichia coli (ATCC25922) and Listeria monocytogenes (ATCC 7644) bacteria and Candida albicans (F89) yeast. The results were comparisoned with the antibiotics (Fluconazole, Vancomycin, Cefepime and Levofloxacin). All compounds showed activity against bacteria and yeasts. Compounds Cu(OAc)2.2H2O (31.25 µg/mL) for C. Albicans, 1 and 7 (31.25 µg/mL) for L. monocytogens, all compounds (except 6) (7.60 µg/mL) for B. subtilis, 2 (31.25 µg/mL) for E. Coli, 7 (15.60 µg/mL) for S. aureus, 7 (31.25 µg/mL) for E. Faecalis, and 3 (15.60 µg/mL) for P. aeruginoa have the best activity.