Search Results (603)

Multiple-input multiple-output (MIMO) radars offer significant advantages over conventional standalone radars in terms of target detection and localization capabilities. However, to fully exploit their potential, such systems require excellent time and phase synchronization among the central unit and the radar heads. Only recently, thanks to microwave photonics (MWP) techniques, it has been possible to develop the first coherent MIMO radar demonstrators. In this paper, a simulation tool in MATLAB programming language is proposed to model coherent MIMO radars based on MWP techniques in maritime surveillance applications. Moreover, a novel approach for estimating the radar cross section of extended maritime targets is presented. The system performance in co-located and distributed MIMO configuration, as well as in single- and multi-band operations, is evaluated by means of relevant key performance indicators (KPIs). Simulations are carried out in two close-to-reality scenarios. In the first, a co-located MIMO radar is mounted on top of a patrolling vessel. In the second, a distributed MIMO radar is deployed inside a port. The proposed KPIs are analyzed in terms of both geometric and frequency diversities of the system, laying the foundations for general system optimization criteria valid in any given surveillance application. Full article

This article discusses the topical issues of managing information security vulnerabilities in the life cycle stages of processors and computer equipment. An analysis of the experience of identifying vulnerabilities in the course of the joint design of the processor, computing module and computing complex was carried out. A number of actions have been developed and presented to ensure the control of hardware vulnerabilities in the development stage. The use of the binary translation technology of the Elbrus platform is proposed to prevent the execution of malicious software. A method has been developed to eliminate vulnerabilities in computer equipment for automated systems used for various purposes by using the Lintel binary translation system component. An experiment is described, the purpose of which was to successfully exploit the Meltdown vulnerability on a computer with an Elbrus processor. The experiment showed that, due to the peculiarities of the microarchitecture of Elbrus processors, the exploitation of Meltdown-type vulnerabilities is impossible. Full article

The periodic nature of stream-wise flow occurs in a cooling channel so frequently due to the multiple heat sources in electronic equipment, demanding the creation of an effective technique to improve the heat-cooling convection. This work explores thermal convection enhancement in a heated-block duct for periodic boundary conditions using the element-by-element (EBE) treatment in a semi-implicit projection finite element method (FEM) through a preconditioned conjugate gradient (PCG) solver. The effects of changing the Reynolds numbers (100, 175, and 250) on rectangular cylinders installed in the channel under periodic boundary conditions were studied using time-mean Nusselt number enhancement, friction factor enhancement, and thermal performance coefficient. The results show that the rectangular cylinders installed stream-wise above an upstream block promote thermal convection in the heated-block duct due to modifying the flow of no cylinders. However, increasing the number of rectangular cylinders increases the friction factor enhancement. As a result, the case for periodic boundary conditions with a rectangular cylinder above every two blocks has the best thermal performance coefficient. Full article

This work proposes a procedure for the multi-objective design of a robust forecasting ensemble of data-driven models. Starting with a data-selection algorithm, a multi-objective genetic algorithm is then executed, performing topology and feature selection, as well as parameter estimation. From the set of non-dominated or preferential models, a smaller sub-set is chosen to form the ensemble. Prediction intervals for the ensemble are obtained using the covariance method. This procedure is illustrated in the design of four different models, required for energy management systems. Excellent results were obtained by this methodology, superseding the existing alternatives. Further research will incorporate a robustness criterion in MOGA, and will incorporate the prediction intervals in predictive control techniques. Full article

A mathematical model of the working processes occurring in the gas cap has been developed on the basic fundamental laws of conservation of energy, mass and motion, and the equation of state, both taking into account the change in the mass of the gas due to phase transitions and the solubility of the gas in the liquid, and without taking them into account with a dividing element. In addition, there was developed a mathematical model of the liquid flow from the gas cap through a pipeline of constant cross section. It was found from the results of a numerical experiment that to reduce the feed irregularity, it is necessary to increase the length of the pipeline and the crankshaft revolutions, in addition to the known ratio of the volume of gas in the cap to the working volume of the pump; an increase in discharge pressure and an increase in the diameter of the connecting pipeline increases the feed irregularity. Full article

An unmanned aerial vehicle (UAV)-integrated control system is a set of functionally independent subsystems of the ground and space segments interacting with each other under the conditions of the stochastic nature of the external environment. There is an approach to evaluating its effectiveness based on a generalized multiplicative criterion, which takes into account the features of this system to the maximum extent. It is proposed to single out two particular criteria that characterize the reliability of a UAV and the effectiveness of the control system in relation to it. At the same time, the generalized criterion is a multiplicative convolution based not on the triangular-norm (t-norm) of the particular criterion, but of its correspondence functions, which in a certain way reflect its significance. It is shown that in the particular case of linear dependence of the correspondence functions, the generalized criterion coincides with the classical multiplicative convolution in the form of product of event probabilities. The proposed approach with minimal changes can be adapted to assess the effectiveness of data management systems in heterogeneous networks, process control systems, projects, logistics, etc. Full article

This paper presents a numerical model for simulating melting and solidification driven by natural convection, and validates it against a previous experiment. The experiment involved filling a rectangular aluminum enclosure with RT28HC Phase Change Material (PCM) to 95% of its capacity. To investigate the thermal behavior of the PCM during phase change, the enclosure underwent independent heating and cooling procedures. The simulation was conducted using ANSYS CFX^®, and the additional heat source (AHS) method was implemented in conjunction with the Boussinesq approximation to account for the latent heat during melting and solidification driven by natural convection. This allowed the calculation of temperature fields, the melted fraction, and fluid dynamics during phase change. The momentum equations were modified to include a source term that accounted for a gradual decrease in fluid velocity as the PCM transitions from solid to liquid. To account for density variation, an artificial specific heat curve was implemented based on the assumption that the product of density and specific heat remains constant during phase change. The proposed numerical model achieved good agreement with the experimental data, with an average root mean square error of 2.6% and 3.7% for temperature profiles during charging and discharging simulations, respectively. This model can be easily implemented in ANSYS CFX^® and accurately predicts charging and discharging kinetics, as well as stored/released energy, without any numerical convergence issues. Full article

This study explores the application of computer vision for enhancing the selection of rootstock-graft combinations and detecting diseases in grape seedlings. Computer vision has various applications in viticulture, but publications and research have not reported the use of computer vision in rootstock-graft selection, which defines the novelty of this research. This paper presents elements of the technology for applying computer vision to rootstock-graft combinations and includes an analysis of grape seedling cuttings. This analysis allows for a more accurate determination of the compatibility between rootstock and graft, as well as the detection of potential seedling diseases. The utilization of computer vision to automate the grafting process of grape cuttings offers significant benefits in terms of increased efficiency, improved quality, and reduced costs. This technology can replace manual labor and ensure economic efficiency and reliability, among other advantages. It also facilitates monitoring the development of seedlings to determine the appropriate planting time. Image processing algorithms play a vital role in automatically determining seedling characteristics such as trunk diameter and the presence of any damage. Furthermore, computer vision can aid in the identification of diseases and defects in seedlings, which is crucial for assessing their overall quality. The automation of these processes offers several advantages, including increased efficiency, improved quality, and reduced costs through the reduction of manual labor and waste. To fulfill these objectives, a unique robotic assembly line is planned for the grafting of grape cuttings. This line will be equipped with two conveyor belts, a delta robot, and a computer vision system. The use of computer vision in automating the grafting process for grape cuttings offers significant benefits in terms of efficiency, quality improvement, and cost reduction. By incorporating image processing algorithms and advanced robotics, this technology has the potential to revolutionize the viticulture industry. Thanks to training a computer vision system to analyze data on rootstock and graft grape varieties, it is possible to reduce the number of defects by half. The implementation of a semi-automated computer vision system can improve crossbreeding efficiency by 90%. Reducing the time spent on pairing selection is also a significant advantage. While manual selection takes between 1 and 2 min, reducing the time to 30 s using the semi-automated system, and the prospect of further automation reducing the time to 10–15 s, will significantly increase the productivity and efficiency of the process. In addition to the aforementioned benefits, the integration of computer vision technology in grape grafting processes brings several other advantages. One notable advantage is the increased accuracy and precision in pairing selection. Computer vision algorithms can analyze a wide range of factors, including size, shape, color, and structural characteristics, to make more informed decisions when matching rootstock and graft varieties. This can lead to better compatibility and improved overall grafting success rates. Full article

In this work, we propose a brain–computer-interface (BCI)-based smart-home interface which leverages motor imagery (MI) signals to operate home devices in real-time. The idea behind MI-BCI is that different types of MI activities will activate various brain regions. Therefore, after recording the user’s electroencephalogram (EEG) data, two approaches, i.e., Regularized Common Spatial Pattern (RCSP) and Linear Discriminant Analysis (LDA), analyze these data to classify users’ imagined tasks. In such a way, the user can perform the intended action. In the proposed framework, EEG signals were recorded by using the EMOTIV helmet and OpenVibe, a free and open-source platform that has been utilized for EEG signal feature extraction and classification. After being classified, such signals are then converted into control commands, and the open communication protocol for building automation KNX (“Konnex”) is proposed for the tasks’ execution, i.e., the regulation of two switching devices. The experimental results from the training and testing stages provide evidence of the effectiveness of the users’ intentions classification, which has subsequently been used to operate the proposed home automation system, allowing users to operate two light bulbs. Full article

Renewable and distributed energy generation includes wind turbines, fuel cells, solar cells, and batteries. These distributed energy sources need special power converters in order to connect them to the grid and make the generated power available for public use. Solar energy is the most readily available energy source; hence, if utilized properly, it can power up both domestic and industrial loads. Solar cells produce DC power, and this should be converted to an AC source with the help of inverters. A multi-level inverter for an application is selected based on a trade-off between cost, complexity, losses, and total harmonic distortion (THD). A packed U-cell (PUC) topology is composed of power switches and voltage sources connected in a series-parallel fashion. This basic unit can be extended to a greater number of output voltage levels. The significance of this design is the reduced use of power switches, gate drivers, protection circuits, and capacitors. The converter presented in this paper is a 31-level topology switched by a variable switching frequency-based model predictive controller that helps in achieving optimal output with reduced harmonics to a great extent. The gate driver circuit is also optimized in terms of power consumption and size complexity. A comparison of the 9-level and the 31-level PUC inverters is carried out to study the impact of the number of levels on the total harmonic distortion. The simulation results depict that the total harmonic distortion (THD) for a nominal modulation index of 0.8 is 11.54% and 3.27% for the 9-level multi-level inverter (MLI) and the 31-level modified packed U-cell multi-level inverter (MPUC-MLI), respectively. The reduction in THD is attributed to the increased number of steps in the output when using the model predictive controller. Full article

Hydrogen powered vehicles use high-pressure reservoirs from which the gas is transferred to the low-pressure fuel-cell via a classical pressure reduction valve. In these systems no expansion work is recovered and the question is addressed of the potential to increase global efficiency by using an expansion machine between the reservoir and the electrochemical reactor. This paper investigates the feasibility of such an expansion machine, and evaluates the mechanical constraints in terms of forces, torques and produced power by numeric simulation. It further evaluates the energetic contribution to the whole conversion chain from the hydrogen reservoir to the common electrical network on board. A low-energy contribution of the expansion system addresses the question of the real benefit of such an investment. Full article

Stirling engines are currently of interest due to their adaptability to a wide range of energy sources. Since simple tools are needed to guide the sizing of prototypes in preliminary studies, this paper proposes two groups of simple models to estimate the maximum power in Stirling engines with a kinematic drive mechanism. The models are based on regression or ANN techniques, using data from 34 engines over a wide range of operating conditions. To facilitate the generalisation and interpretation of results, all models are expressed by dimensionless variables. The first group models use three input variables and 23 data points for correlation construction or training purposes, while another 66 data points are used for testing. Models in the second group use eight inputs and 18 data points for correlation construction or training, while another 36 data points are used for testing. The three-input models provide estimations of the maximum brake power with an acceptable accuracy for feasibility studies. Using three-input models, the predictions of the maximum indicated power are very accurate, while those of the maximum brake power are less accurate, but acceptable for the preliminary design stage. In general, the best results are achieved with ANN models, although they only employ one hidden layer. Full article

The research studies hyper-Rayleigh behavior of a wireless communication system functioning in the presence of the generalized multipath fading. Although the initial metric (hyper-Rayleigh mode (HRM)) is quite informative, it is defined only asymptotically (i.e., for the infinitely increasing SNR). In spite of mathematical simplifications brought by such a definition (i.e., in this case most of the performance characteristics defining the HRM can be easily evaluated), it sufficiently limits its applications since, evidently, the real-life systems function in the presence of a finite (and usually not very high) SNR. The study presents a novel approach to the fading channel analysis (i.e., finite signal-to-noise ratio hyper-Rayleigh mode (fHRM)). The proposed metric (fHRM) is studied on the newly presented channel model-fluctuating double-Rayleigh with Line-of-Sight (fdRLoS) fading model. To accomplish this, the novel expressions for two channel-dependent system characteristics (i.e., the Amount of Fading (AoF) and the Outage Probability (OP)) were derived in exact form valid for arbitrary fading parameters. Based on the derived expressions, the finite SNR hyper-Rayleigh map is obtained, which helps to identify the parameters’ values corresponding to the specific propagation scenarios, which were further deployed to analyze the problem of the communication link physical layer security quantified in terms of the probability of strictly positive secrecy capacity (SPSC). Numerical verification of the derived closed-form expressions was performed. Several peculiarities of the system performance are observed and discussed. Full article

Despite the fact that power grids have been planned and utilized using centralized networks for many years, there are now significant changes occurring as a result of the growing number of distributed energy resources, the development of energy storage systems and devices, and the increased use of electric vehicles. In light of this development, it is pertinent to ask what an efficient approach would be to the operation and management of future distribution grids consisting of millions of distributed and even mobile energy elements. Parallel to this evolution in power grids, there has been rapid growth in decentralized management technology due to the development of relevant technologies such as blockchain networks. Blockchain is an advanced technology that enables us to answer the question raised above. This paper introduces a decentralized blockchain network based on the Hyperledger Fabric framework. The proposed framework enables the formation of local energy markets of future citizen energy communities (CECs) through peer-to-peer transactions. In addition, it is designed to ensure adequate load supply and observe the network’s constraints while running an optimal operation point by consensus among all of the players in a CEC. An open-source tool in Python is used to verify the performance of the proposed framework and compare the results. Through its distributed and layered management structure, the proposed blockchain-based framework proves its superior flexibility and proper functioning. Moreover, the results show that the proposed model increases system performance, reduces costs, and reaches an operating point based on consensus among the microgrid elements. Full article

Tremors affect pediatric and adult populations, with roughly 3% of people worldwide experiencing essential tremors. Treatments include medication, deep brain stimulation, occupational/physical therapy, or adaptive equipment. This unblinded experimental pre-test–post-test study was performed (April–September 2021) at Children’s Health of Orange County, evaluating the effectiveness of Move-D, a novel orthotic brace, on pediatric tremors. Ten participants (14–19 years old) experiencing upper extremity tremors (5 essential, 2 dystonic, 1 coarse, 1 postural, and 1 unspecified) were enrolled. Participants completed a usability survey and performance was measured utilizing the Bruininks–Oseretsky Test of Motor Proficiency, second edition, with and without the brace, using one-sided t-tests of mean differences. Move-D improved age-equivalent scores for fine motor precision by 20.5 months and upper limb coordination by 15.1 months. Manual coordination percentile rankings increased by 2.9%. Manual dexterity performance was unaffected. The usability survey revealed that 7/10 participants agreed or strongly agreed that they could move their arm freely while wearing the brace, the brace reduced their tremors, and they felt comfortable wearing the brace at home. Through standardized testing and findings from the usability survey, Move-D showed an improvement of functional abilities in a pediatric population with tremors. Full article