Blood glucose level monitoring and control is of utmost importance to millions of people who have been diagnosed with diabetes or similar illnesses. One of the conventional tests for measuring how the human body breaks down glucose is IVGTT, the Intravenous Glucose Tolerance Test. The difficulty of computing the models of glucose-insulin interaction presents an issue when attempting to implement them in embedded hardware. The Metabolic P (MP), contrary to other models, does not require solving differential equations to compute, thus it could be an effective modelling approach for real-time applications. The present paper proves that MP system methodology-based IVGTT implementation in the Field Programmable Gate Arrays (FPGA) technology is reasonably precise and sufficiently flexible to be used effectively in multi-user scenarios. Presentation of the state-of-the-art focuses on glucose-insulin interaction models, glucose monitoring systems and MP system implementation techniques. Methods for MP system computations and techniques for their implementation on FPGA, together with the original unified MP system implementation technique, have been presented in this paper. The results of an elaborate investigation into the IVGTT MP systems, as well as their single and unified MP implementation techniques have also been considered. It is shown that the techniques developed are applicable to all known IVGTT MP systems, and can achieve RMSE not higher than 15% using a word length of at least 32 bits. The novel MP system combined quality metrics and its pictorial representation allow the analysis of various implementation characteristics. Compared to the unified pipelined IVGTT MP system implementation technique, the developed unified combinational technique ensures a 2‒3 times higher speed.
This work presents an outline of the history of scientists and the city where the world’s first relativistic CRM device, known today as a Gyrotron, was created. CRM can be explained as “a microwave source of stimulated radiation based on the cyclotron resonance phenomenon.”. The story begins in 1898 with the establishment of the Emperor Nicolas II Warsaw Polytechnic Institute and ends in 1964 with the launch of the world’s first Gyrotron at the Nizhegorodsky Polytechnical Institute (later Gorky). The principle of gyrotron operation is very briefly presented in the paper, but mainly, according to the idea of this work, a lot of space is devoted to people, scientists and organizers of science in Gorky, the first who created this device, and therefore the work is limited to presenting the events related to the creation of the Gyrotron in 1959‒1967.
The aim of the paper is to present the implementation of a PLC designed in the form of a System-on-a-Chip. The presented PLC is compatible with the IEC61131‒3 standard. More precisely, the Instruction List language is the native language of the designed CPU, so there is no need for multiple language transformations. In the proposed solution each instruction of the CPU program written in Instruction List is directly translated to machine code. The designed CPU is capable of performing logic operations up to 32-bit Boolean data types. However, the developed CPU is very flexible due to its architecture: data memory can be addressed as bit/byte/word/dword. Moreover, diverse blocks such as timers, counters, and hardware acceleration blocks, can be connected to the CPU by means of an APB AMBA bus. The designed PLC has been implemented in an FPGA device and can be used in cyber-physical systems and Industry 4.0.
In recent years, smog and poor air quality have become a growing environmental problem. There is a need to continuously monitor the quality of the air. The lack of selectivity is one of the most important problems limiting the use of gas sensors for this purpose. In this study, the selectivity of six amperometric gas sensors is investigated. First, the sensors were calibrated in order to find a correlation between the concentration level and sensor output. Afterwards, the responses of each sensor to single or multicomponent gas mixtures with concentrations from 50 ppb to 1 ppm were measured. The sensors were studied under controlled conditions, a constant gas flow rate of 100 mL/min and 50 % relative humidity. Single Gas Sensor Response Interpretation, Multiple Linear Regression, and Artificial Neural Network algorithms were used to predict the concentrations of SO2 and NO2. The main goal was to study different interactions between sensors and gases in multicomponent gas mixtures and show that it is insufficient to calibrate sensors in only a single gas.
The method described in this work allows to determine the optimal distribution of pulses of digital signal as well as the non-linear mathematical model based on a multiple regression statistical analysis, which are specialized to an effective and low-cost testing of functional parameters in analog electronic circuits. The aim of this concept is to simplify the process of analog circuit specification validation and minimize hardware implementation, time and memory requirements during the testing stage. This strategy requires simulations of the analyzed analog electronic circuit; however, this effort is done only once – before the testing stage. Then, validation of circuit specification can be obtained after a quick, very low-cost procedure without time consuming computations and without expensive external measuring equipment usage. The analyzed test signature is a time response of the analog circuit to the stream of digital pulses for which distributions were determined during evolutionary optimization cycles. Besides, evolutionary computations assure determination of the optimal form and size of the non-linear mathematical formula used to estimate specific functional parameters. Generally, the obtained mathematical model has a structure similar to the polynomial one with terms calculated by means of multiple regression procedure. However, a higher ordered polynomial usage makes it possible to reach non-linear estimation model that improves accuracy of circuit parametric identification. It should be noted that all the evolutionary calculations are made only at the before test stage and the main computational effort, for the analog circuit specification test design, is necessary only once. Such diagnosing system is fully synchronized by a global digital signal clock that precisely determines time points of the slopes of input excitation pulses as well as acquired output signature samples. Efficiency of the proposed technique is confirmed by results obtained for examples based on analog circuits used in previous (and other) publications as test benchmarks.
In this paper, a new dynamic model was proposed for identifying the rock hardness during the process of roadway tunnelling, thereby regulating the speed of the driving motor and the torque of the cutting head. The presented identification model establishes a multi-information feature database containing vibration signals in the y-axis, acoustic emission signals, cutting current signals, and temperature signals. Subsequently, we obtain the membership functions (MFs) of the given multiple signals with the amount of feature samples according to the principle of minimum fuzzy entropy. Furthermore, a rock hardness identification model was established based on multi-sensor information fusion and Dempster-Shafer (D-S) evidence theory. To prove the accuracy of the proposed model, an identification experiment was carried out through the cutting of a poured mixed rock specimen with five grades of hardness. As a result, the proposed identification model recognizes the rock hardness accurately for fifteen sampling points, which indicates the significance of the method with regard to the dynamic identification of rock hardness during the process of roadway tunnelling, and further provides data support for adjusting the speed of the cutting head adaptively, thereby achieving high efficiency tunnelling.
Pot-cored coils are commonly used as probes in eddy current testing. In this paper, an analytical model of such a coil placed over a three-layer plate with a hole has been presented. The proposed solution enables the modelling of both magnetic and non-magnetic conductive plates that contain different types of hole, i.e. a through, a surface, an inner or a subsurface hole. The problem was solved by using the truncated region eigenfunction expansion (TREE) method. The analysis was carried out in a cylindrical coordinate system in which the solution domain was radially limited. With the employment of the filamentary coil, the expressions for the magnetic vector potential, and subsequently for the impedance of the cylindrical coil were obtained. The final formulas were presented in a closed form and then implemented in Matlab. The resistance and reactance values were compared with the results obtained in the experiment and using the finite element method in the Comsol Multiphysics package. In each of the cases, good agreement was obtained.
This paper presents equilibrium mechanics and a finite element model for analysing a scissor structure that contains pivots with zero bending stiffness representing structural instability. The pivot at the centre of each structural unit, which is a feature of scissor structures, can be used to transfer the displacement between the units. It cannot, however, transfer the rotation between these units, and the angular stiffness must be considered independently for each unit. To construct a general model of the scissor structure, a scissor unit was developed using the left and right boundary connections of adjacent units to simulate a periodically symmetric structure. The proposed method allows us to obtain an accurate distribution of the internal forces and deflections without the use of special elements to account for central pivots.
The article describes the results of combustion of a mixture of PCOME (purified cooking oil esters) and bioethanol in the compression ignition Perkins 1104C-44 engine. The engine was prepared for use with the classic type of fuel – diesel oil, not biofuels. That is why bioethanol was added to ester in tests so that the basic physicochemical properties of the obtained mixture were as close as possible to diesel fuel. Thanks to this, the use of such fuel in the future would not require reworking or adjusting the settings of selected elements of the engine power supply system. During this case study, the engine performance and heat release rate were analyzed. For comparison, tests were carried out while powering the engine with ester fuel, 10 and 20 per cent mixtures of bioethanol and PCOME. The speed and load characteristics for each fuel were determined. This article presents selected characteristics where the biggest differences were noticed.
Most high-pressure fuel pumps for compression-ignition engines manufactured today are cam driven. These pumps have numerous advantages, such as low energy consumption and limited production costs. However, a problem arising from the nature of the cam mechanism is an unfavorable distribution of forces in the camshaft-plunger-cylinder system of a delivery section. The authors have proposed an innovative pump design that eliminates most of the problems present in conventional solutions. The pump utilizes a gear-based hypocycloid drive. This paper focuses mainly on the strength analysis of the two critical components (countershaft and mount) of the subassembly under the highest load – simulations were carried out for different critical load states. The following procedure of estimating fatigue life was adopted for computations: the operational evolution of stresses will be systematized to the set of amplitude stresses and mean stresses by means of the “Rainflow” method. The results obtained in the work showed that the main factor determining change of stresses was the presence of clearances in the pump mechanism. It has been proved that the values of clearances have a negative influence on the power transmission in particular – their presence results in loads being carried by the countershaft and not by the support inter-operating with it. This may cause frictional wear of teeth, leading to the improper operation of the transmission. The analysis showed that the mount was designed correctly. This facilitates the use of less demanding constructional materials.
In this paper, quanizted multisine inputs for a maneuver with simultaneous elevator, aileron and rudder deflections are presented. The inputs were designed for 9 quantization levels. A nonlinear aircraft model was exited with the designed inputs and its stability and control derivatives were identified. Time domain output error method with maximum likelihood principle and a linear aircraft model were used to perform parameter estimation. Visual match and relative standard deviations of the estimates were used to validate the results for each quantization level for clean signals and signals with measurement noise present in the data. The noise was included into both output and input signals. It was shown that it is possible to obtain accurate results when simultaneous flight controls deflections are quantized and noise is present in the data.
The problems of mathematical modelling of vibration signal for bearings with specific geometrical structure or defect is important insofar as there are no model bearings (to facilitate carrying out a calibration procedure for industrial measurement systems). It is even more so that there are no precise reference systems to which we would compare the results. This article presents a general outline of the most important studies on modelling of vibrations in rolling bearings. Papers constituting the basis for the most recent studies and a review of articles from the past few years have been considered here. Five different models have been analyzed in detail in order to show the directions of the latest studies. Completed analysis presents different viewpoints on the issue of modelling a rolling bearing operation. This overview article makes it possible to derive the final conclusion that in order to include all factors affecting bearing vibrations, even those ignored in the most recent models, it is necessary to carry out practical statistical research including the principles of multicriteria statistics. This approach will facilitate developing a versatile model, also applicable to predicting vibrations of a new bearing just manufactured in a factory.
The main drawback of vibration-based energy harvesting is its poor efficiency due to small amplitudes of vibration and low sensitivity at frequencies far from resonant frequency. The performance of electromagnetic energy harvester can be improved by using mechanical enhancements such as mechanical amplifiers or spring bumpers. The mechanical amplifiers increase range of movement and velocity, improving also significantly harvester efficiency for the same level of excitation. As a result of this amplitude of motion is much larger comparing to the size of the electromagnetic coil. This in turn imposes the need for modelling of electromagnetic circuit parameters as the function of the moving magnet displacement. Moreover, high velocities achieved by the moving magnet reveal nonlinear dynamics in the electromagnetic circuit of the energy harvester. Another source of nonlinearity is the collision effect between magnet and spring bumpers. It has been shown that this effect should be carefully considered during design process of the energy harvesting device. The present paper investigates the influence of the above-mentioned nonlinearities on power level generated by the energy harvester. A rigorous model of the electromagnetic circuit, derived with aid of the Hamilton’s principle of the least action, has been proposed. It includes inductance of the electromagnetic coil as the function of the moving magnet position. Additionally, nonlinear behaviour of the overall electromagnetic device has been tested numerically for the case of energy harvester attached to the quarter car model moving on random road profiles. Such a source of excitation provides wide band of excitation frequencies, which occur in variety of real-life applications.
The present work focuses on the fabrication of glass fiber and multifilament discarded fishnet nylon fiber polymer composites with four different fiber compositions. Composites are molded by means of simple hand lay-up methodology with dissimilar layers of the fiber mat. The mechanical characterization (tensile and impact) and thermal analysis of composites have to be investigated. Among the different patterns, hybrid composites reflected better tensile and impact properties as compared to the conventional materials. Morphological characterization was carried out to figure out the de-bonding of fiber/matrix adhesion characteristics of fractured face of tensile testing samples. The result suggests the potential for reuse of discarded fishnet, which constitutes a better alternative for structural work and for possible applications to be used to develop added-value products.
This research paper discusses the friction and wear behaviour of Al-12Si alloy reinforced with B4C prepared through Powder Metallurgy (P/M) method by varying the weight percentage of reinforcement (x = 2, 4, 6, 8, and 10) content. The samples were prepared by using die and punch assembly and the lubricant used to eject the sample from the die was molybdenum disulfide. The compaction was done by using a compression testing machine by applying a pressure of 800 MPa. The dry sliding friction and wear behaviour of the sample was conducted on a Pin-on-Disc machine and the experimental values of friction and wear were calibrated. The Taguchi design experiment was done by applying an L25 orthogonal array for 3 factors at 5 levels for the response parameter Coefficient of Friction (CoF) and wear loss. The SEM images show the shape, size and EDX confirm the existence of Al, Si, B4C particles in the composites. Analysis of Variance (ANOVA) for CoF of S/N ratio, shows that the reinforcement having 34.92% influence towards the S/N ratio of CoF, ANOVA for wear loss of S/N ratio shows that the sliding distance having 46.76% influence towards the S/N ratio of wear loss, when compared to that of the other two input parameters. The interaction line plot and the 2Dsurface plot for CoF and wear loss show that the increase in B4C content decreases the wear loss and CoF. The worn surface shows that the B4C addition will increase the wear resistance.
Metal matrix composites (MMC) are finding application in many fields such as aerospace and automobile industries. This is due to their advantages such as light weight and low cost. Among all the available non-traditional machining processes, wire electric discharge machining (WEDM) is found to be a suitable method for producing complex or intricate shapes in composite materials. In this study, an aluminum metal matrix composite (AMMC) with 6% and 8% weight (wt) fraction of Al2O3 is prepared through the stir casting process. The fabricated AMMC specimen is machined using WEDM, considering various process parameters such as wt % of reinforcement, gap voltage (Vg), peak current (IP) wire tension (WT) and dielectric pressure (Pd). Output responses such as the machining rate (MR) and surface roughness (Ra) of the slots are analyzed by conducting L18 mixed orthogonal array (OA) experiments. The experiments are analyzed using techniques for order preference by similarity to ideal solution (TOPSIS) and analysis of variance (ANOVA). Based on the analyses, the optimum combination of process parameters for better MR and Ra is as follows: wt % = 6 gm, Vg = 53 V, Ip = 8 A, WT = 11 g, Pd = 13 bar. The optimum level of process parameters for MR and Ra are 1.5 mm/min and 3.648 µm, respectively. Based on ANOVA, the peak current is found to have a significant influence on MR and Ra. Moreover, based on a scanning electron microscope (SEM) image, the presence of micro-ridges, reinforcement, micro-craters, micro-cracks, recast layers and oxide formation are all analyzed on the surface being machined.
Industries that rely on additive manufacturing of metallic parts, especially biomedical companies, require material science-based knowledge of how process parameters and methods affect the properties of manufactured elements, but such phenomena are incompletely understood. In this study, we investigated the influence of selective laser melting (SLM) process parameters and additional heat treatment on mechanical properties. The research included structural analysis of residual stress, microstructure, and scleronomic hardness in low-depth measurements. Tensile tests with specimen deformation analysis using digital image correlation (DIC) were performed as well. Experiment results showed it was possible to observe the porosity growth mechanism and its influence on the material strength. Specimens manufactured with 20% lower energy density had almost half the elongation, which was directly connected with the porosity growth during energy density reduction. Hot isostatic pressing (HIP) treatment allowed for a significant reduction of porosity and helped achieve properties similar to specimens manufactured using different levels of energy density.
The effect of laser processing on the structure, microstructure and hardness of high-speed steel produced by powder metallurgy was investigated. The samples were surfaces remelted with impulse CO2 laser radiation under different operation conditions. In the remelted layer, the presence of full remelting, partial remelting and heat affected zones was detected. As a result of concentrated laser beam treatment, microstructures characteristic of the rapid crystallization process were observed. The microstructure in the full remelting zone was characterized by a fine microdendritic structure with the average distance between the secondary axes of dendrites below 1 µm and the dissolution of primary carbides. Retained austenite was found in the remelted samples, the amounts of which depended on the treatment parameters and grew with an increase in the speed of the laser beam movement. There was no unequivocal effect of the distance of the irradiated surface from the focus of the beam focusing system on the content of retained austenite. Due to the presence of retained austenite in the remelted part, the hardness decreased by about 23% compared to the hardness of the material before the treatment. On the other hand, laser processing leads to strong refinement of the microstructure and eliminates the residual porosity of powder steels, which can increase the toughness and cutting performance of steel. The research also showed the possibility of shaping the geometry of the remelting zone by the appropriate selection of machining parameters
The main objective of this work is to present an innovative method of numerical modeling of anchored piles system acting as a road protection against landslide, called the “2D/3D method”. Firstly, short description of the problem and “state of the art” review are included. An effective methodology of the design supported by the numerical analysis, solving the problem of interaction of a periodic system of piles and the unstable soil mass is presented, for which some detailed information about proposed numerical approach is given. The key idea of 2D/3D method is to join the pile with the 2D plane strain continuum by fictitious connectors of Winkler type with P-Y properties identified during the analysis of a subsidiary 3D problem. Practical example of usage of proposed approach to a real case of a road endangered by a landslide then protected by the piles system is presented. On the base of this example, a discussion about important design issues like internal forces in piles (mainly bending moments) and anchors (tensile forces) or overall stability of the soil-structure system is done.
Several recent earthquakes have indicated that the design and construction of bridges based on former seismic design provisions are susceptible to fatal collapse triggered by the failure of reinforced concrete columns. This paper incorporates an experimental investigation into the seismic response of nonductile bridge piers strengthened with low-cost glass fiber reinforced polymers (LC-GFRP). Three full-scale bridge piers were tested under lateral cyclic loading. A control bridge pier was tested in the as-built condition and the other two bridge piers were experimentally tested after strengthening them with LC-GFRP jacketing. The LC-GFRP strengthening was performed using two different configurations. The control bridge pier showed poor seismic response with the progress of significant cracks at very low drift levels. Test results indicated the efficiency of the tested strengthening configurations to improve the performance of the strengthened bridge piers including crack pattern, yield, and ultimate cyclic load capacities, ductility ratio, dissipated energy capacity, initial stiffness degradation, and fracture mode.
The subject matter of the research pertains to the improvement of rheological properties of petroleum bitumens by their modification with SBS (styrene-butadiene-styrene) copolymer. The authors have determined selected rheological properties characterising the durability of modified bitumens used in road pavements. The bitumens were modified in laboratory conditions with modified bitumen concentrate of a known SBS copolymer content of 9%. The result was a binder containing the known percentage of the SBS copolymer of 3%, 4.5% and 6%. Rheological properties of the tested bitumens were determined by the use of a DSR dynamic shear rheometer (in a wide temperature range from 40°C to 100°C) and a ductilometer at 5°C. DSR was used for performing MSCR test to determine the resistance of the asphalt mixture with the SBS-modified binder to permanent deformations in the high temperature range (from 40°C to 82°C). The comparison of the values of the dynamic shear modulus |G*| of all the bitumens tested shows that with a growing content of the SBS copolymer in the tested binder the value of |G*| increases, which may indicate greater resistance to permanent deformation of the asphalt pavement. The MSCR test has shown that the increased use of the SBS copolymer addition in the bitumen translates to decreasing values of the non-recoverable creep compliance Jnr. The SBS copolymer accelerates stress relaxation in the bitumen sample, thus increasing pavement resistance to low-temperature cracks. Furthermore, modification reduces the negative impact of ageing on the properties of the binder, manifested by its stiffening and slowdown of relaxation.
We propose an approach to indirectly learn the Web Ontology Language OWL 2 property characteristics as an explanation for a deep recurrent neural network (RNN). The input is a knowledge graph represented in Resource Description Framework (RDF) and the output are scored axioms representing the characteristics. The proposed method is capable of learning all the characteristics included in OWL 2: functional, inverse functional, reflexive and irreflexive, symmetric and asymmetric, transitive. We report and discuss experimental evaluation on DBpedia 2016-10, showing that the proposed approach has advantages over a simple counting baseline.
The paper proposes an adaptation of mathematical models derived from the theory of deterministic chaos to short-term power forecasts of wind turbines. The operation of wind power plants and the generated power depend mainly on the wind speed at a given location. It is a stochastic process dependent on many factors and very difficult to predict. Classical forecasting models are often unable to find the existing relationships between the factors influencing wind power output. Therefore, we decided to refer to fractal geometry. Two models based on self-similar processes (M-CO) and (M-COP) and the (M-HUR) model were built. The accuracy of these models was compared with other short-term forecasting models. The modified model of power curve adjusted to local conditions (M-PC) and Canonical Distribution of the Vector of Random Variables Model (CDVRM). Examples of applications confirm the valuable properties of the proposed approaches.
This paper presents a deep learning-based image texture recognition system. The methodology taken in this solution is formed in a bottom-up manner. It means we swipe a moving window through the image in order to categorize if a given region belongs to one of the classes seen in the training process. This categorization is done based on the Deep Neural Network (DNN) of fixed architecture. The training process is fully automated regarding the training data preparation, investigation of the best training algorithm, and its hyper-parameters. The only human input to the system is the definition of the categories for further recognition and generation of the samples (region markings) in the external application chosen by the user. The system is tested on road surface images where its task is to categorize image regions to a different road category (e.g. curb, road surface damage, etc.) and is featured with 90% and above accuracy.
Necessary and sufficient conditions for the pointwise completeness and the pointwise degeneracy of linear discrete-time different fractional order systems are established. It is shown that if the fractional system is pointwise complete in one step (q = 1), then it is also pointwise complete for q = 2, 3…
In this paper, an advanced study covering the comparison between two classes of generalized inverses is conducted. Two sets of instances, strictly derived from the recently introduced nonunique S- and σ-inverse, are analyzed, especially in terms of degrees of freedom-oriented interchangeable application in different engineering tasks. Henceforth, the respective collections of right and left inverses can be combined in order to achieve a complex tool for robustification of a plethora of real processes. The great potential of two S- and σ-inverse, in particular in robust control and signal recovery as well as complex optimal tasks, is confirmed in the manuscript and supported by the recently carried out research investigations.
In this work, we present a failure detection system in sensors of any robot. It is based on the k-fold cross-validation approach and built from N neural networks, where N is the number of signals read from sensors. Our tests were carried out using an unmanned aerial vehicle (UAV, quadrocopter), where signals were read from three sensors: accelerometer, magnetometer and gyroscope. Artificial neural network was used to determine Euler angles, based on signals from these sensors. The presented system is an extension of the system that we proposed in one of our previous papers. The improvement shown in this work took place on two levels. The first one was related to improvement of a neural network՚s reproduction quality – we have replaced a recurrent neural network with a convolutional one. The second level was associated with the improvement of the validation process, i.e. with adding some new criteria to check the values of Euler՚s angles determined by the convolutional neural network in subsequent time steps. To highlight the proposed system improvement we present a number of indicators such as RMSE, NRMSE and NDR (Normalized Detection Ratio).
This paper presents the concept of using algorithms for reducing the dimensions of finite-difference equations of two-dimensional (2D) problems, for second-order partial differential equations. Solutions are predicted as two-variable functions over the rectangular domain, which are periodic with respect to each variable and which repeat outside the domain. Novel finite-difference operators, of both the first and second orders, are developed for such functions. These operators relate the value of derivatives at each point to the values of the function at all points distributed uniformly over the function domain. A specific feature of the novel operators follows from the arrangement of the function values as well as the values of derivatives, which are rectangular matrices instead of vectors. This significantly reduces the dimensions of the finite-difference operators to the numbers of points in each direction of the 2D area. The finite-difference equations are created exemplary elliptic equations. An original iterative algorithm is proposed for reducing the process of solving finite-difference equations to the multiplication of matrices.
Hybrid Power Sources/Systems (HPS) are generally treated as local prosumer supplies. The paper presents a new approach to the strategy of electricity contracting from HPS, considering hybrid systems as a new type of quasi-centrally dispatched power units operating in Polish market conditions. The possibilities of contracting electricity from HPS, consisting of three electricity generation technologies: biogas plant, wind power plant and solar power plant, are presented. The opportunity to obtain additional income from the electricity trading on the balancing market was used. Proposals for a new mathematical description of HPS topology were also presented, including a feasibility function, which can be used for technical and economic analyses. The obtained results can be used as a direction of development in the field of optimization of hybrid source operation in cooperation with the power grid. Based on the conducted analyses, it can be observed that electricity sales contracts concluded for each hour of the day may bring additional profit for the investor. However, the strong dependence of the proposed strategy on the situation on the balancing market or other local electricity markets similar in their operations should be emphasized.
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