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This paper proposes the usage of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the Demand Response program. In contrast with other related studies, this research recognizes both randomness and fuzziness in appliance usage. Moreover, the input data for usage prediction consists of nodal price values (which represent the actual power system conditions), appliance operation time, and time of day. The case study of residential power consumer behavior modeling was implemented to show the functionality of the proposed methodology. The results of applying the suggested algorithm are presented as colored 3D control surfaces. In addition, the performance of the model was verified using R squared coefficient and root mean square error. The conducted studies show that the proposed approach can be used to predict when the selected appliances can be used under specific circumstances. Research of this type may be useful for evaluation of the demand response programs and support residential load forecasting. [ABSTRACT FROM AUTHOR]

Object tracking based on Siamese networks has achieved great success in recent years, but increasingly advanced trackers are also becoming cumbersome, which will severely limit deployment on resource-constrained devices. To solve the above problems, we designed a network with the same or higher tracking performance as other lightweight models based on the SiamFC lightweight tracking model. At the same time, for the problems that the SiamFC tracking network is poor in processing similar semantic information, deformation, illumination change, and scale change, we propose a global attention module and different scale training and testing strategies to solve them. To verify the effectiveness of the proposed algorithm, this paper has done comparative experiments on the ILSVRC, OTB100, VOT2018 datasets. The experimental results show that the method proposed in this paper can significantly improve the performance of the benchmark algorithm. [ABSTRACT FROM AUTHOR]

Time invariant linear operators are the building blocks of signal processing. Weighted circular convolution and signal processing framework in a generalized Fourier domain are introduced by Jorge Martinez. In this paper, we prove that under this new signal processing framework, weighted circular convolution also has a generalized time invariant property. We also give an application of this property to algorithm of continuous wavelet transform (CWT). Specifically, we have previously studied the algorithm of CWT based on generalized Fourier transform with parameter 1. In this paper, we prove that the parameter can take any complex number. Numerical experiments are presented to further demonstrate our analyses. [ABSTRACT FROM AUTHOR]

An iterative neural network framework is proposed in this paper for the human-induced Ground Reaction Forces (GRF) replication with an inertial electrodynamic mass actuator (APS 400). This is the first approach to the systematization of dynamic load tests on structures on a purely objective, repeatable and pedestrian-independent basis. Therefore, an inversion-free offline algorithm based on Machine Learning techniques has been applied for the first time on an electrodynamic shaker, without requiring its inverse model to tackle the inverse problem of successful force reconstruction. The proposed approach aims to obtain the optimal drive signal to minimize the error between the experimental shaker output and the reference force signal, measured with a pair of instrumented insoles (Loadsol©) for human bouncing at different frequencies and amplitudes. The optimal performance, stability and convergence of the system are verified through experimental tests, achieving excellent results in both time and frequency domain. [ABSTRACT FROM AUTHOR]

This paper proposes an autonomous obstacle avoidance method combining improved A-star (A*) and improved artificial potential field (APF) to solve the planning and tracking problems of autonomous vehicles in a road environment. The A*APF algorithm performs path planning tasks, and based on the longitudinal braking distance model, a dynamically changing obstacle influence range is designed. When there is no obstacle affecting the controlled vehicle, the improved A* algorithm with angle constraint combined with steering cost can quickly generate the optimal route and reduce turning points. If the controlled vehicle enters the influence domain of the obstacle, the improved artificial potential field algorithm will generate lane-changing paths and optimize the local optimal locations based on simulated annealing. Pondering the influence of surrounding participants, the four-mode obstacle avoidance process is established, and the corresponding safe distance condition is analyzed. A particular index is introduced to comprehensively evaluate speed, risk warning, and safe distance factors, so the proposed method is designed based on the fuzzy control theory. In the tracking task, a model predictive controller in the light of the kinematics model is devised to make the longitudinal and lateral process of lane-changing meet comfort requirements, generating a feasible autonomous lane-change path. Finally, the simulation was performed in the Matlab/Simulink and Carsim combined environment. The proposed fusion path generation algorithm can overcome the shortcomings of the traditional single method and better adapt to the dynamic environment. The feasibility of the obstacle avoidance algorithm is verified in the three-lane simulation scenario to meet safety and comfort requirements. [ABSTRACT FROM AUTHOR]

This paper deals with research on the magnetic bearing control systems for a high-speed rotating machine. Theoretical and experimental characteristics of the control systems with the model algorithmic control (MAC) algorithm and the proportional-derivative (PD) algorithm are presented. The MAC algorithm is the non-parametric predictive control method that uses an impulse response model. A laboratory model of the rotor-bearing unit under study consists of two active radial magnetic bearings and one active axial (thrust) magnetic bearing. The control system of the rotor position in air gaps consists of the fast prototyping control unit with a signal processor, the input and output modules, power amplifiers, contactless eddy current sensors and the host PC with dedicated software. Rotor displacement and control current signals were registered during investigations using a data acquisition (DAQ) system. In addition, measurements were performed for various rotor speeds, control algorithms and disturbance signals generated by the control system. Finally, the obtained time histories were presented, analyzed and discussed in this paper. [ABSTRACT FROM AUTHOR]

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives. One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process. Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the necessary minimum. In the paper, the problem of delivering components to a production area using trains and appropriately laid-out carriages was described. It is a milk run stop locations problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms. Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors. In this paper, the applicability of three algorithms -- tabu search, genetic algorithm, and simulated annealing -- was explored. [ABSTRACT FROM AUTHOR]

This issue is a typical NP-hard problem for an unrelated parallel machine scheduling problem with makespan minimization as the goal and no sequence-related preparation time. Based on the idea of tabu search (TS), this paper improves the iterative greedy algorithm (IG) and proposes an IG-TS algorithm with deconstruction, reconstruction, and neighborhood search operations as the main optimization process. This algorithm has the characteristics of the strong capability of global search and fast speed of convergence. The warp knitting workshop scheduling problem in the textile industry, which has the complex characteristics of a large scale, nonlinearity, uncertainty, and strong coupling, is a typical unrelated parallel machine scheduling problem. The IG-TS algorithm is applied to solve it, and three commonly used scheduling algorithms are set as a comparison, namely the GA-TS algorithm, ABC-TS algorithm, and PSO-TS algorithm. The outcome shows that the scheduling results of the IG-TS algorithm have the shortest manufacturing time and good robustness. In addition, the production comparison between the IG-TS algorithm scheduling scheme and the artificial experience scheduling scheme for the small-scale example problem shows that the IG-TS algorithm scheduling is slightly superior to the artificial experience scheduling in both planning and actual production. Experiments show that the IG-TS algorithm is feasible in warp knitting workshop scheduling problems, effectively realizing the reduction of energy and the increase in efficiency of a digital workshop in the textile industry. [ABSTRACT FROM AUTHOR]

Most of the basic control methods of the grid-connected converter (GCC) are defined to work with a sine wave grid voltage. In that case if the grid voltage is distorted by higher harmonics, the grid current may be distorted too, which, in consequence, may increase the value of the THD of the grid voltage. The paper deals with an improved finite control set model predictive control (FCS-MPC) method of an LCL-filtered GCC operating under distorted grid conditions. The proposed method utilizes supplementary grid current feedback to calculate the reference converter current. The introduced signal allows to effectively improve the operation when the grid is subject to harmonic distortion. The paper shows a simulation analysis of the proposed control scheme operating with and without additional feedback under grid distortions. To validate the practical feasibility of the proposed method an algorithm was implemented on a 32-bit microcontroller STM32F7 with a floating point unit to control a 10 kW GCC. The laboratory test setup provided experimental results showing properties of the introduced control scheme. [ABSTRACT FROM AUTHOR]

Due to the characteristics of color vegetation canopy images which have multiple details and Gaussion noise interference, the adaptive mean filtering (AMF) algorithm is used to perform the denoising experiments on noised images in RGB and YUV color space. Based on the single color characteristics of color vegetation canopy images, a simplified AMF algorithm is proposed in this paper to shorten the overall running time of the denoising algorithm by simplifying the adaptive denoising processing of the component V, which contains less image details. Experimental results show that this method can effectively reduce the running time of the algorithm while maintaining a good denoising effect. [ABSTRACT FROM AUTHOR]

In this paper three algorithms of motion planning for two-input, one-chained nonholonomic systems are presented. The classical Murray-Sastry algorithm is compared with two original algorithms aimed at optimizing energy of controls. Based on the generalized CampbellBaker-Hausdorff-Dynkin formula applied to the systems, some observations are made concerning the optimal relationship between amplitudes and phases of harmonic controls. The observations help to optimize a selection of controls and to design new algorithms for planning a suboptimal trajectory between given boundary configurations. It was also shown that for those particular systems the generalized C-B-H-D formula is valid not only locally (as in a typical case) but also globally. Simulations performed on the five-dimensional chain system facilitate distinguishing the proposed algorithms from the Murray-Sastry algorithm and to illustrate their features. Systems in a chained form are important from a practical point of view as they are canonical for a class of systems transformable into this form. The most prominent among them are mobile robots with or without trailers. [ABSTRACT FROM AUTHOR]

Developing novel methods, approaches and computational techniques is essential for solving efficiently more and more demanding up-to-date engineering problems. Designing durable, light and eco-friendly structures starts at the conceptual stage, where new efficient design and optimization tools need to be implemented. Nowadays, apart from the traditional gradient-based methods applied to optimal structural and material design, innovative techniques based on versatile heuristic concepts, like for example Cellular Automata, are implemented. Cellular Automata are built to represent mechanical systems where the special local update rules are implemented to mimic the performance of complex systems. This paper presents a novel concept of flexible Cellular Automata rules and their implementation into topology optimization process. Despite a few decades of development, topology optimization still remains one of the most important research fields within the area of structural and material design. One can notice novel ideas and formulations as well as new fields of their implementation. What stimulates that progress is that the researcher community continuously works on innovative and efficient topology optimization methods and algorithms. The proposed algorithm combined with an efficient analysis system ANSYS offers a fast convergence of the topology generation process and allows obtaining well-defined final topologies. [ABSTRACT FROM AUTHOR]

This paper investigates an algorithm for finding steady-states in electromechanical systems for the cases of their periodic nature. The algorithm enables to specify the steady-state solution identified directly in time domain. The basis for such an algorithm is a discrete differential operator that specifies the values of the first derivative of the periodic function in the selected set of points on the basis of the values of that function in the same set of points. It creates algebraic equations describing the steady-state solution for the nonlinear differential equations describing electromechanical systems. In this paper, the direct time-domain approach is tested for the simple converter considering. The algorithm used in this paper is competitive with respect to the one known in literature an approach based on the harmonic balance method operated in frequency domain. [ABSTRACT FROM AUTHOR]

The goal of the paper was to shorten the calculation time by realising all used signal processing algorithms in the form of stack filters. The architecture of these filters allows us to process signals using the advantages of hardware processing and simultaneous signal processing. This paper elaborated on the synthesis of stack filters which realise median, averaging, opening and closing operations. The novel achievement was to develop the binary box method which allows us to obtain stack filters for more complex algorithms. This method consists of two stages and requires that we construct a spatial structure of the data. This structure allows us to examine the stacking property in two steps. Obtained in this way architecture of the function is predisposed to VLSI implementation. The authors devised this method transforming the averaging filter into stack filter; however, the invented binary box method allows us to synthesise stack filter which realises more complex signal processing algorithms. The only assumption which limits the class of acceptable algorithms is the fact that the algorithm has to satisfy the stacking property at each stage of the signal processing. The proposed approach allows us to convert well-known signal processing algorithms into realisation which guarantees significantly greater speeds of signal processing. [ABSTRACT FROM AUTHOR]

This paper describes practical issues related to control of the active power buffer (APB) developed for a 2 kVA single-phase inverter. The buffer is designed using the latest GaN HEMTs controlled with triangular current mode to reduce switching losses, however, the switching frequency should be limited to 1 MHz. In the case of the presented analogue-digital controller, frequency is influenced by a reference current of the APB and circuit. Therefore, the operation at start-up and shut-down is especially challenging. A modified control algorithm that also includes pre-charging and discharging process of the energy buffer is presented and experimentally verified by series of tests of the 2 kVA GaN based inverter with the APB. [ABSTRACT FROM AUTHOR]

The paper proposes to apply an algorithm for predicting the minimum level of the state of charge (SoC) of stationary supercapacitor energy storage system operating in a DC traction substation, and for changing it over time. This is done to insure maximum energy recovery for trains while braking. The model of a supercapacitor energy storage system, its algorithms of operation and prediction of the minimum state of charge are described in detail; the main formulae, graphs and results of simulation are also provided. It is proposed to divide the SoC curve into equal periods of time during which the minimum states of charge remain constant. To predict the SoC level for the subsequent period, the learning algorithm based on the neural network could be used. Then, the minimum SoC could be based on two basic types of data: the first one is the time profile of the energy storage load during the previous period with the constant minimum SoC retained, while the second one relies on the trains' locations and speed values in the previous period. It is proved that the use of variable minimum SoC ensures an increase of the energy volume recovered by approximately 10%. Optimum architecture and activation function of the neural network are also found. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach to building network cluster structures, based on the modified LEACH algorithm. The proposed solution takes into account the multitasking of the network infrastructure, resulting from various functions performed by individual nodes. Therefore, instead of a single head, dedicated to a given cluster, a set of heads is selected, the number of which corresponds to the number of performed functions. Outcomes of simulations, comparing the classical and the multifunctional approach, are presented. The obtained results confirm that both algorithms deliver similar levels of energy consumption, as well as efficiency in terms of the number of individual nodes discharged. [ABSTRACT FROM AUTHOR]

Parallel realizations of discrete transforms (DTs) computation algorithms (DTCAs) performed on graphics processing units (GPUs) play a significant role in many modern data processing methods utilized in numerous areas of human activity. In this paper the authors propose a novel execution time prediction model, which allows for accurate and rapid estimation of execution times of various kinds of structurally different DTCAs performed on GPUs of distinct architectures, without the necessity of conducting the actual experiments on physical hardware. The model can serve as a guide for the system analyst in making the optimal choice of the GPU hardware solution for a given computational task involving particular DT calculation, or can help in choosing the best appropriate parallel implementation of the selected DT, given the limitations imposed by available hardware. Restricting the model to exhaustively adhere only to the key common features of DTCAs enables the authors to significantly simplify its structure, leading consequently to its design as a hybrid, analytically-simulational method, exploiting jointly the main advantages of both of the mentioned techniques, namely: time-effectiveness and high prediction accuracy, while, at the same time, causing mutual elimination of the major weaknesses of both of the specified approaches within the proposed solution. The model is validated experimentally on two structurally different parallel methods of discrete wavelet transform (DWT) computation, i.e. the direct convolutionbased and lattice structure-based schemes, by comparing its prediction results with the actual measurements taken for 6 different graphics cards, representing a fairly broad spectrum of GPUs compute architectures. Experimental results reveal the overall average execution time and prediction accuracy of the model to be at a level of 97.2%, with global maximum prediction error of 14.5%, recorded throughout all the conducted experiments, maintaining at the same time high average evaluation speed of 3.5 ms for single simulation duration. The results facilitate inferring the model generality and possibility of extrapolation to other DTCAs and different GPU architectures, which along with the proposed model straightforwardness, time-effectiveness and ease of practical application, makes it, in the authors' opinion, a very interesting alternative to the related existing solutions. [ABSTRACT FROM AUTHOR]

This paper presents the improved methodology for the direct calculation of steady-state periodic solutions for electromagnetic devices, as described by nonlinear differential equations, in the time domain. A novel differential operator is developed for periodic functions and the iterative algorithm determining periodic steady-state solutions in a selected set of time instants is identified. Its application to steady-state analysis is verified by an elementary example. The modified algorithm reduces the complexity of steady-state analysis, particularly for electromagnetic devices described by high-dimensional nonlinear differential equations. [ABSTRACT FROM AUTHOR]

Hybridization of meta-heuristic algorithms plays a major role in the optimization problem. In this paper, a new hybrid meta-heuristic algorithm called hybrid pathfinder algorithm (HPFA) is proposed to solve the optimal reactive power dispatch (ORPD) problem. The superiority of the Differential Evolution (DE) algorithm is the fast convergence speed, a mutation operator in the DE algorithm incorporates into the pathfinder algorithm (PFA). The main objective of this research is to minimize the real power losses and subject to equality and inequality constraints. The HPFA is used to find optimal control variables such as generator voltage magnitude, transformer tap settings and capacitor banks. The proposed HPFA is implemented through several simulation cases on the IEEE 118-bus system and IEEE 300-bus power system. Results show the superiority of the proposed algorithm with good quality of optimal solutions over existing optimization techniques, and hence confirm its potential to solve the ORPD problem. [ABSTRACT FROM AUTHOR]

The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature. [ABSTRACT FROM AUTHOR]

The paper presents the new optimal real-time control algorithm of the power source. The minimum of the square-instantaneous current was assumed as an optimal criterion, with an additional constraint on source instantaneous power. The mathematical model of a multiphase source was applied as a voltage-current convolution in the discrete time domain. The resulting control algorithm was the recursive digital filter with infinite recursion. [ABSTRACT FROM AUTHOR]

The paper presents a novel model predictive flux control (MPFC) scheme for three-level inverter-fed sensorless induction motor drive operated in a wide speed region, including field weakening. The novelty of the proposed drive lies in combining in one system a number of new solutions providing important features, among which are: very high dynamics, constant switching frequency, no need to adjust weighting factors in the predictive cost function, adaptive speed and parameter (stator resistance, main inductance) estimation. The theoretical principles of the optimal switching sequence predictive stator flux control (OSS-MPFC) method used are also discussed. The method guarantees constant switching frequency operation of a three-level inverter. For speed estimation, a compensated model reference adaptive system (C-MRAS) was adopted while for IM parameters estimation a Q-MRAS was developed. Simulation and experimental results measured on a 50 kW drive that illustrates operation and performances of the system are presented. The proposed novel solution of a predictive controlled IM drive presents an attractive and complete algorithm/system which only requires the knowledge of nominal IM parameters for proper operation. [ABSTRACT FROM AUTHOR]

This paper investigates whether a quantum computer can efficiently simulate the non-elastic scattering of the Schrödinger particle on a stationary excitable shield. The return of the shield to the ground state is caused by photon emission. An algorithm is presented for simulating the time evolution of such a process, implemented on standard two-input gates. The algorithm is used for the computation of elastic and non-elastic scattering probabilities. The results obtained by our algorithm are compared with those obtained using the standard Cayley's method. [ABSTRACT FROM AUTHOR]

Digital system algorithms such as FFT algorithms, convolution, image processing algorithm, etc. deploy Multiply and Accumulate (MAC) unit as an evaluative component. The efficiency of a MAC typically relies on the speed of operation, power dissipation, and chip area along with the complexity level of the circuit. In this research paper, a power-delay-efficient signed-floating-point MAC (SFMAC) is proposed using Universal Compressor based Multiplier (UCM). Instead of having a complex design architecture, a simple multiplexer-based circuit is used to achieve a signed-floating output. The 8£8 SFMAC can take 8-bit mantissa and 3-bit exponent and therefore, the input to the SFMAC can be in the range of - (7.96875)10 to +(7.96875)10. The design and implementation of the proposed architecture is executed on the Cadence Spectre tool in GPDK 90 nm and TSMC 130 nm CMOS, which proves as power and delay efficient. [ABSTRACT FROM AUTHOR]

Target manoeuvre is one of the key factors affecting guidance accuracy. To intercept highly maneuverable targets, a second-order sliding-mode guidance law, which is based on the super-twisting algorithm, is designed without depending on any information about the target motion. In the designed guidance system, the target estimator plays an essential role. Besides the existing higher-order sliding-mode observer (HOSMO), a first-order linear observer (FOLO) is also proposed to estimate the target manoeuvre, and this is the major contribution of this paper. The closed-loop guidance system can be guaranteed to be uniformly ultimately bounded (UUB) in the presence of the FOLO. The comparative simulations are carried out to investigate the overall performance resulting from these two categories of observers. The results show that the guidance law with the proposed linear observer can achieve better comprehensive criteria for the amplitude of normalised acceleration and elevator deflection requirements. The reasons for the different levels of performance of these two observer-based methods are thoroughly investigated. [ABSTRACT FROM AUTHOR]

Generators of finite cyclic groups play important role in many cryptographic algorithms like public key ciphers, digital signatures, entity identification and key agreement algorithms. The above kinds of cryptographic algorithms are crucial for all secure communication in computer networks and secure information processing (in particular in mobile services, banking and electronic administration). In the paper, proofs of correctness of two probabilistic algorithms (for finding generators of finite cyclic groups and primitive roots) are given along with assessment of their average time computational complexity. [ABSTRACT FROM AUTHOR]

In electric drive with a synchronous motor with permanent magnets, having a complex mechanical structure and changeable parameters. Several research cases of the control system with a neural controller are presented, focusing on the change of object parameters. Also, the influence of the system critic behaviour is researched, where the critic is a function of control error and energy cost. It ensures long term performance stability without the need of switching off the adaptation algorithm. Numerous simulation tests were carried out and confirmed on a real stand.out the need of switching off the adaptation algorithm. Numerous simulation tests were carried out and confirmed on a real stand. [ABSTRACT FROM AUTHOR]

This paper presets the specification and implementation of the control system of the mobile platform Rex. The presented system structure and the description of its functioning result from the application of a formal method of designing such systems. This formalism is based on the concept of an embodied agent. The behaviours of its subsystems are specified in terms of transition functions that compute, out of the variables contained in the internal memory and the input buffers, the values that are inserted into the output buffers and the internal memory. The transition functions are the parameters of elementary actions, which in turn are used in behaviour patterns which are the building blocks of the subsystems of the designed control system. Rex is a skid steering platform, with four independently actuated wheels. It is represented by a single agent that implements the locomotion functionality. The agent consists of a control subsystem, a virtual effector and a virtual receptor. Each of those subsystems is discussed in details. Both the data structures and the transition functions defining their behaviours are described. The locomotion agent is a part of the control system of the autonomous exploration and rescue robot developed within the RobREx project. [ABSTRACT FROM AUTHOR]

The problem of performing software tests using Testing-as-a-Service cloud environment is considered and formulated as an~online cluster scheduling on parallel machines with total flowtime criterion. A mathematical model is proposed. Several properties of the problem, including solution feasibility and connection to the classic scheduling on parallel machines are discussed. A family of algorithms based on a new priority rule called the Smallest Remaining Load (SRL) is proposed. We prove that algorithms from that family are not competitive relative to each other. Computer experiment using real-life data indicated that the SRL algorithm using the longest job sub-strategy is the best in performance. This algorithm is then compared with the Simulated Annealing metaheuristic. Results indicate that the metaheuristic rarely outperforms the SRL algorithm, obtaining worse results most of the time, which is counter-intuitive for a metaheuristic. Finally, we test the accuracy of prediction of processing times of jobs. The results indicate high (91.4%) accuracy for predicting processing times of test cases and even higher (98.7%) for prediction of remaining load of test suites. Results also show that schedules obtained through prediction are stable (coefficient of variation is 0.2-3.7%) and do not affect most of the algorithms (around 1% difference in flowtime), proving the considered problem is semi-clairvoyant. For the Largest Remaining Load rule, the predicted values tend to perform better than the actual values. The use of predicted values affects the SRL algorithm the most (up to 15% flowtime increase), but it still outperforms other algorithms. [ABSTRACT FROM AUTHOR]

The dynamic development of science requires constant improvement of approaches to modeling physical processes and phenomena. Practically all scientific problems can be described by systems of differential equations. Many scientific problems are described by systems of differential equations of a special class, which belong to the group of so-called singularly perturbed differential equations. Mathematical models of processes described by such differential equations contain a small parameter near the highest derivatives, and it was the presence of this small factor that led to the creation of a large mathematical theory. The work proposes a developed algorithm for constructing uniform asymptotics of solutions to systems of singularly perturbed differential equations. [ABSTRACT FROM AUTHOR]

The main goal of the paper is to present a logic synthesis strategy dedicated to an LUT-based FPGA. New elements of the proposed synthesis strategy include: an original method of function decomposition, non-disjoint decomposition and technology mapping dedicated to configurability of logic blocks. The aim of all of the proposed synthesis approaches is the sharing of appropriately configured logic blocks. Innovation of the methods is based on the way of searching decomposition, which relies on multiple cutting of an MTBDD diagram describing a multi-output function. The essence of the proposed algorithms rests on the method of unicoding dedicated to sharing resources, searching non-disjoint decomposition on the basis of the partition of root tables and choosing the levels of diagram cutting that will guarantee the best mapping to complex logic blocks. The methods mentioned above were implemented in the MultiDec tool. The efficiency of the analyzed methods was experimentally confirmed by comparing the synthesis results with both academic and commercial tools. [ABSTRACT FROM AUTHOR]

The article proposes an adaptive algorithm that generates all object signals, including those for which measurements are not performed due to the difficulties associated with online measurements. The algorithm is modeled on the idea of the Kalman filter using its equation; however, the selection of gains is optimized differently, i.e. the constant values depend on the adopted ranges of adaptation errors. Moreover, the knowledge of the statistics of all noise signals is not imposed and there is no linearity constraint. This approach allowed us to reduce the complexity of calculations. This algorithm can be used in real-time systems to generate signals of objects described by non-linear differential equations and it is universal, which allows it to be used for various objects. In the conducted research, on the example of a biochemically contaminated river, only easily measurable signals were used to generate the object signals, and in addition, in the case of the absence of some measurements, the functioning of the algorithm did not destabilize. [ABSTRACT FROM AUTHOR]

The article presents the resource-constrained project scheduling problem with the maximisation of discounted cash flows from the contractor's perspective: with cash outflows related to starting individual activities and with cash inflows for completing project stages (milestones). The authors propose algorithms for improving a forward active schedule by iterative one-unit right shifts of activities, taking into account different resource flow networks. To illustrate the algorithms and problem, a numerical example is presented. Finally, the algorithms are tested using standard test problems with additionally defined cash flows and contractual milestones. [ABSTRACT FROM AUTHOR]

The objective of the research was to investigate the efficiency of selected methods of data fusion from visual sensors used on-board satellites for attitude measurements. Data from a sun sensor, an earth sensor, and a star tracker were fused, and selected methods were applied to calculate satellite attitude. First, a direct numerical solution, a numerical and analytical solution of the Wahba problem, and the TRIAD method for attitude calculation were compared used for integrating data produced by a sun sensor and an earth sensor. Next, attitude data from the star tracker and earth/sun sensors were integrated using two methods: weighted average and Kalman filter. All algorithms were coded in the MATLAB environment and tested using simulation models of visual sensors. The results of simulations may be used as an indication for the best data fusion in real satellite systems. The algorithms developed may be extended to incorporate other attitude sensors like inertial and/or GNSS to form a complete satellite attitude system. [ABSTRACT FROM AUTHOR]

The article deals with studying the hydrodynamic characteristics of the fluidized bed in gravitation shelf dryers. The algorithm to calculate hydrodynamic characteristics of the fluidized bed in the dryer's workspace is described. Every block of the algorithm has a primary hydrodynamic characteristics theoretical model of calculation. Principles of disperse phase motion in various areas in the gravitation shelf dryer are established. The software realization of the author's mathematic model to calculate disperse phase motion trajectory in a free and constrained regime, disperse phase residence time in the dryers' workspace, polydisperse systems classification is proposed in the study. Calculations of disperse phase motion hydrodynamic characteristics using the software product ANSYS CFX, based on the author's mathematic model, are presented in the article. The software product enables automating calculation simultaneously by several optimization criteria and visualizing calculation results in the form of 3D images. The disperse phase flow velocity fields are obtained; principles of a wide fraction of the disperse phase distribution in the workspace of the shelf dryer are fixed. The way to define disperse phase residence time91 in the workspace of the shelf dryer in free (without consideration of cooperation with other particles and dryer's elements) and con-strained motion regimes is proposed in the research. The calculation results make a base for the optimal choice of the gravitation shelf dryer working chamber sizes. [ABSTRACT FROM AUTHOR]

Epilepsy is a neurological disorder that causes seizures of many different types. The article presents an analysis of heart rate variability (HRV) for epileptic seizure prediction. Considering that HRV is nonstationary, our research focused on the quantitative analysis of a Poincare plot feature, i.e. cardiac sympathetic index (CSI). It is reported that the CSI value increases before the epileptic seizure. An algorithm using a 1D-convolutional neural network (1D-CNN) was proposed for CSI estimation. The usability of this method was checked for 40 epilepsy patients. Our algorithm was compared with the method proposed by Toichi et al. The mean squared error (MSE) for testing data was 0.046 and the mean absolute percentage error (MAPE) amounted to 0.097. The 1D-CNN algorithm was also compared with regression methods. For this purpose, a classical type of neural network (MLP), as well as linear regression and SVM regression, were tested. In the study, typical artifacts occurring in ECG signals before and during an epileptic seizure were simulated. The proposed 1D-CNN algorithm estimates CSI well and is resistant to noise and artifacts in the ECG signal. [ABSTRACT FROM AUTHOR]

In this study, we propose a novel keyed hash algorithm based on a Boolean function and chaotic attractor. The hash algorithm called BentSign is based on two Signature attractors and XOR function and a bent Boolean function. The provided theoretical and experimental results confirm that the novel scheme can generate output hashes with a good level of security, collision resistance, and protection against most common attacks. [ABSTRACT FROM AUTHOR]

The article presents an algorithm for digital image processing of astronomical objects in order to effectively determine the position of these objects. The proposed method has been optimized due to its effectiveness of removing noise and distortion caused by atmospheric turbulence and imperfections in long exposure photography of astronomical objects. This solution is ready for implementation in a system for automatic identification of stars in the recorded images. Such a system is designed for GoTo circuits at telescope's drives, which can automatically point a telescope to astronomical objects. The method was verified by simulation in MATLAB program on real images of astronomical objects. [ABSTRACT FROM AUTHOR]