In this study, the performance of an organic dye obtained from the bark of the red pine (Pinus brutia) tree growing in Muğla/Turkey as an interface layer in the Au/n-Si Schottky diode (SD) structure was evaluated. For this purpose, at first, the optimized molecular structure, the highest occupied molecular orbital (HOMO), and the lowest unoccupied molecular orbital (LUMO) simulations of the organic dye were calculated by the Gauss program and it was theoretically proven that the dye exhibits semiconducting properties. Then, the electrical and photodiode variables such as ideality factor, effective barrier height, series resistance, interface states density distribution, photosensitivity, and photo responsivity were evaluated employing current-voltage measurements under dark and different illumination densities. Additionally, C-V measurements were used to demonstrate that the fabricated device has capacitive features and this capability varies as a function of the frequency. Under these measurements, the possible conduction mechanism for the organic dye-based Au/n-Si device was investigated and the results showed that Au/Pinus brutia/n-Si may be a good candidate for optoelectronic applications. Full article

Building extraction from remote sensing (RS) images is a fundamental task for geospatial applications, aiming to obtain morphology, location, and other information about buildings from RS images, which is significant for geographic monitoring and construction of human activity areas. In recent years, deep learning (DL) technology has made remarkable progress and breakthroughs in the field of RS and also become a central and state-of-the-art method for building extraction. This paper provides an overview over the developed DL-based building extraction methods from RS images. Firstly, we describe the DL technologies of this field as well as the loss function over semantic segmentation. Next, a description of important publicly available datasets and evaluation metrics directly related to the problem follows. Then, the main DL methods are reviewed, highlighting contributions and significance in the field. After that, comparative results on several publicly available datasets are given for the described methods, following up with a discussion. Finally, we point out a set of promising future works and draw our conclusions about building extraction based on DL techniques. Full article

This work has developed and evaluated a microemulsion-based drilling fluid formulation with characteristics to be applied in oil wells. The microemulsion was formulated with a solution of water/glycerol, pine oil, and Tween 80, a nonionic and biodegradable surfactant. The physical and chemical properties of the drilling fluid obtained in this work were investigated through rheology and filtration analysis, solids content, aging, lubricity, toxicity, and thermal degradation. A non-toxic microemulsion-based drilling fluid oil-in-water (O/W) with high lubricity (0.07638) and thermal stability was obtained with suitable viscosity, gel strength and low fluid loss (4.0 mL), low solids content (6%), stability in a wide range of salinity conditions, and the possibility of high water content (above 85% in mass fraction). The fluid presented a pseudoplastic behavior, and statistically significant Herschel–Bulkley parameters were obtained. Full article

Doubly-fed induction generators (DFIGs) participate in the system frequency regulation using a fixed-coefficient droop control scheme. Nevertheless, the frequency-supporting capability of this control scheme with fixed gain is limited for different disturbances. This paper suggests an improved droop control scheme for a DFIG that can both alleviate the frequency nadir and maximum rate of change of frequency (ROCOF) during the frequency regulation. To achieve this, an adaptive droop control coefficient based on the ROCOF is suggested. The proposed droop control coefficient is a linear function of the ROCOF. Therefore, the proposed scheme can adjust the control coefficient according to the varying ROCOF. Simulation results clearly demonstrate that the proposed droop control scheme shows better effectiveness in improving the maximum ROCOF and frequency nadir under various sizes of disturbance, even in a varying wind speed. Full article

Appropriate driving technique, in compliance with eco-driving principles, remains an effective method to reduce fuel consumption. The selection of the correct gear is one of the pertinent factors when driving a car with a manual gearbox. In this study we have analyzed fuel overconsumption based on data recorded in real traffic conditions for vehicles driven by experienced drivers, using a black-box model. It was found that the total share of trip time with a lower than optimal gear selected amounted to from c.a. 3% for motorway driving up to 28% on rural roads. The mean fuel consumption reduction factor (following selection of the next gear up) amounted to from c.a. 2% up to 20%, depending on the selected gear and type of driving. Unfortunately, the potential for reduction of fuel consumption is not evenly distributed over the entire operating area of the engine. Thus, the cumulative reduction of fuel consumption, due to selection of the optimal gear, amounted to from c.a. 0.2% for motorway driving up to 3–6%, for urban and rural driving. It was shown that due to the selection of the appropriate gear, there still exists a real possibility of reduction of fuel consumption, even in the case of experienced drivers. Full article

Structural changes occurring in the crude oil market have stimulated the emergence of hypotheses suggesting that the relationship between prices of this raw material and the US dollar exchange rate can gradually become similar to that observed between oil prices and exchange rates of the currencies of the countries whose revenues from the export of this resource are a significant part of their current account balance. The purpose of this study was to determine and evaluate the time-varying dependence between oil prices and the exchange rate of the US dollar in the context of the same relationship for the Chinese, European, Japanese, Saudi, and Russian currencies. The results of our analyses implicate that a negative correlation between the variables in question grows stronger in time periods preceding global shocks and during thereof. The dominance of the USD in the crude oil market is reflected in similar characteristics of the correlations of the currencies of other countries, such as China, countries of the Euro area, or Japan. As for countries exporting crude oil, the situation varies. The results of our research suggest the lack of a stable relationships between prices of crude oil and currency exchange rates. It is also impossible to observe a long-term, unequivocal tendency of the currencies of oil exporting countries being positively correlated with oil prices. Russia was the closest to this situation. In Saudi Arabia, a positive correlation emerged during moments of crisis. Full article

Energy storage is currently one of the most significant technological challenges globally, and supercapacitor is a prominent candidate over batteries due to its ability for fast charging and long lifetime. Supercapacitors typically use porous carbon as electrodes, because of both the high conductivity and surface area of the material. However, the state-of-the-art porous carbon described in the literature uses toxic chemicals and complex procedures that enhance costs and pollute the environment. Thus, a more sustainable procedure to produce porous carbon is highly desirable. In this context, xerogel-like carbons were prepared by a new, cheap, simple route to polymerization reactions of tannin-formaldehyde in a bio-oil by-product. Using bio-oil in its natural pH allowed a cost reduction and avoided using new reactants to change the reactional medium. Textural properties and electrochemical performances were improved by fast activating the material per 20 min. The non-activated carbon xerogel presented a capacitance of 92 F/g, while the activated one had 132 F/g, given that 77% of the components used are eco-friendly. These results demonstrate that renewable materials may find applications as carbon electrodes for supercapacitors. Overhauling the synthesis route with a different pH or replacing formaldehyde may enhance performance or provide a 100% sustainable carbon electrode. Full article

The application of laser ignition in the aerospace field has promising prospects. Based on the constant volume combustion chamber, the laser ignition of CH₄/O₂/N₂ mixture with different initial pressure, different laser energy, different equivalence ratio and different oxygen content has been carried out. The development characteristics of the flame kernel and shock wave under different conditions are analyzed. In addition, the Taylor model and Jones model are also used to simulate the development process of the shock wave, and a new modified model is proposed based on the Jones model. The experimental results show that under pure oxygen conditions, the chemical reaction rate of the mixture is too fast, which makes it difficult for the flame kernel to form the ring and third-lobe structure. However, the ring structure is easier to form with the pressure and laser energy degraded; the flame kernel morphology is easier to maintain at a rich equivalence ratio, which is caused by the influence of the movement of hot air flow and a clearer boundary between the ring and the third-lobe. The decrease of the initial pressure or the increase of the laser energy leads to the increase in shock wave velocity, while the change of the equivalence ratio and oxygen content has less influence on the shock wave. Full article

In this work, the synthesis of a phosphorylated polyvinyl alcohol (p-PVA)/polyoxometalate (tungsto-phosphate) membrane for the BioGenerator, a bio-electrochemical energy storage technology, is reported. It was shown that bonding of lacunary tungsto-phosphate ions to the carbon skeleton of a polymer matrix results in an increase in proton conductivity of up to 2.7 times, compared to previously studied phosphorylated PVA membranes. Testing of the membrane in an actual Fe³⁺/H₂ electrochemical cell showed that it performs significantly better (0.28 W·cm⁻² at 0.79 A·cm⁻²) than the previously used commercial Selemion HSF (Japan) membrane (0.18 W·cm⁻² at 0.60 A·cm⁻²). Full article

Advanced Driver-Assistance Systems (ADASs) are currently gaining particular attention in the automotive field, as enablers for vehicle energy consumption, safety, and comfort enhancement. Compelling evidence is in fact provided by the variety of related studies that are to be found in the literature. Moreover, considering the actual technology readiness, larger opportunities might stem from the combination of ADASs and vehicle connectivity. Nevertheless, the definition of a suitable control system is not often trivial, especially when dealing with multiple-objective problems and dynamics complexity. In this scenario, even though diverse strategies are possible (e.g., Equivalent Consumption Minimization Strategy, Rule-based strategy, etc.), the Model Predictive Control (MPC) turned out to be among the most effective ones in fulfilling the aforementioned tasks. Hence, the proposed study is meant to produce a comprehensive review of MPCs applied to scenarios where ADASs are exploited and aims at providing the guidelines to select the appropriate strategy. More precisely, particular attention is paid to the prediction phase, the objective function formulation and the constraints. Subsequently, the interest is shifted to the combination of ADASs and vehicle connectivity to assess for how such information is handled by the MPC. The main results from the literature are presented and discussed, along with the integration of MPC in the optimal management of higher level connection and automation. Current gaps and challenges are addressed to, so as to possibly provide hints on future developments. Full article

The article is an overview of various methods of braking and controlling the movement of the piston rod under various load conditions. The purpose of this review is to systematize the state of the art in terms of efficiency, energy consumption and limitations of each method. The article discusses systems with different types of hydraulic actuators, operating under passive, active and variable load during the duty cycle of the piston rod. The existing literature was analysed in terms of applicability, reduction of energy consumption of the systems and even the possibility of energy return. Attention was paid to the costs and the need for additional power sources, as well as the problems and limitations of the presented methods. Based on the simulation model, energy consumption tests were carried out in systems with an actuator loaded with a variable force. There is a comparison of all methods in terms of actuator type, load, energy consumption and the possibility of energy recovery. Full article

Transition to turbulence and changes in the fluid flow structure are subjects of continuous analysis and research, especially for unique fields of research such as the thermo-magnetic convection of weakly magnetic fluids. Therefore, an experimental and numerical research of the influence of an external magnetic field on a natural convection’s fluid flow was conducted in the presented research. The experimental part was performed for an enclosure with a 0.5 aspect ratio, which was filled with a paramagnetic fluid and placed in a superconducting magnet in a position granting the enhancement of the flow. The process was recorded as temperature signals from the thermocouples placed in the analyzed fluid. The numerical research enabled an investigation based not only on temperature, but velocities as well. Experimental and numerical data were analyzed with the application of extended fast Fourier transform and wavelet analysis. The obtained results allowed the determination of changes in the nature of the flow and visualization of the influence of an imposed strong magnetic field on a magnetic fluid. It is proved that an applied magnetic field actuates the flow in Rayleigh-Benard convection and causes the change from laminar to turbulent flow for fairly low magnetic field inductions (2T and 3T for ΔT = 5 and 11 °C respectively). Fast Fourier transform allowed the definition of characteristic frequencies for oscillatory states in the flow, as well as an observation that the high values of magnetic field elongate the inertial range of the flow on the power spectrum density. Temperature maps obtained during numerical simulations granted visualizations of thermal plume formation and behavior with increasing magnetic field. Full article

The Green Deal of the European Union defines extremely ambitious climate targets for 2030 (−55% emissions compared to 1990) and 2050 (−100%), which go far beyond the current goals that the EU member states have agreed on thus far. The question of which sectors contribute how much has already been discussed, but is far from decided, while the question of which countries shoulder how much of the tightened reduction targets has hardly been discussed. We want to contribute significantly to answering these policy questions by analysing the necessary burden sharing within the EU from both an energy system and an overall macroeconomic perspective. For this purpose, we use the energy system model TIMES PanEU and the computational general equilibrium model NEWAGE. Our results show that excessively strong targets for the Emission Trading System (ETS) in 2030 are not system-optimal for achieving the 55% overall target, reductions should be made in such a way that an emissions budget ratio of 39 (ETS sector) to 61 (Non-ETS sector) results. Economically weaker regions would have to reduce their CO₂ emissions until 2030 by up to 33% on top of the currently decided targets in the Effort Sharing Regulation, which leads to higher energy system costs as well as losses in gross domestic product (GDP). Depending on the policy scenario applied, GDP losses in the range of −0.79% and −1.95% relative to baseline can be found for single EU regions. In the long-term, an equally strict mitigation regime for all countries in 2050 is not optimal from a system perspective; total system costs would be higher by 1.5%. Instead, some countries should generate negative net emissions to compensate for non-mitigable residual emissions from other countries. Full article

Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, novel hybrid machine learning approaches that exploit auxiliary numerical data are proposed. The proposed hybrid methods invoke different machine learning paradigms, including feature selection, classification, and regression. Additionally, numerical weather prediction (NWP) models are used in the proposed hybrid models. Feature selection is used for feature space dimension reduction to reduce the large number of recorded parameters that affect estimation and prediction processes. The rough set theory is applied for attribute reduction and the dependency degree is used as a fitness function. The effect of the attribute reduction process is investigated using thirty different classification and prediction models in addition to the proposed hybrid model. Then, different machine learning models are constructed based on classification and regression techniques to predict solar radiation. Moreover, other hybrid prediction models are formulated to use the output of the numerical model of Weather Research and Forecasting (WRF) as learning elements in order to improve the prediction accuracy. The proposed methodologies are evaluated using a data set that is collected from different regions in Saudi Arabia. The feature-reduction has achieved higher classification rates up to 8.5% for the best classifiers and up to 15% for other classifiers, for the different data collection regions. Additionally, in the regression, it achieved improvements of average root mean square error up to $5.6\%$ and in mean absolute error values up to 8.3%. The hybrid models could reduce the root mean square errors by 70.2% and 4.3% than the numerical and machine learning models, respectively, when these models are applied to some dataset. For some reduced feature data, the hybrid models could reduce the root mean square errors by 47.3% and 14.4% than the numerical and machine learning models, respectively. Full article

The global maximum power point tracking of a PV array under partial shading represents a global optimization problem. Conventional maximum power point tracking algorithms fail to track the global maximum power point, and global optimization algorithms do not provide global maximum power point in real-time mode due to a slow convergence process. This paper presents an intelligent reconfigurable photovoltaic system on the basis of a modified fuzzy neural net that includes a convolutional block, recurrent networks, and fuzzy units. We tune the modified fuzzy neural net based on modified multi-dimension particle swarm optimization. Based on the processing of the sensors’ signals and the photovoltaic array’s image, the tuned modified fuzzy neural net generates an electrical interconnection matrix of a photovoltaic total-cross-tied array, which reaches the global maximum power point under non-homogeneous insolation. Thus, the intelligent reconfigurable photovoltaic system represents an effective machine learning application in a photovoltaic system. We demonstrate the advantages of the created intelligent reconfigurable photovoltaic system by simulations. The simulation results reveal robustness against photovoltaic system uncertainties and better performance and control speed of the proposed intelligent reconfigurable photovoltaic system under non-homogeneous insolation as compared to a GA-based reconfiguration total-cross-tied photovoltaic system. Full article