Search Results (244)

Thermal control in rolling mills motors is gaining importance as more and more hard-to-deform steel grades are rolled. The capabilities of diagnostics monitoring also expand as digital IIoT-based technologies are adopted. Electrical drives in modern rolling mills are based on synchronous motors with frequency regulation. Such motors are expensive, while their reliability impacts the metallurgical plant output. Hence, developing the on-line temperature monitoring systems for such motors is extremely urgent. This paper presents a solution applying to synchronous motors of the upper and lower rolls in the horizontal roll stand of plate mill 5000. The installed capacity of each motor is 12 MW. According to the digitalization tendency, on-line monitoring systems should be based on digital shadows (coordinate observers) that are similar to digital twins, widely introduced at metallurgical plants. Modern reliability requirements set the continuous temperature monitoring for stator and rotor windings and iron core. This article is the first to describe a method for calculating thermal loads based on the data sets created during rolling. The authors have developed a thermal state observer based on four-mass model of motor heating built using the Simscape Thermal Models library domains that is part of the MATLAB Simulink. Virtual adjustment of the observer and of the thermal model was performed using hardware-in-the-loop (HIL) simulation. The authors have validated the results by comparing the observer’s values with the actual values measured at control points. The discrete masses heating was studied during the rolling cycle. The stator and rotor winding temperature was analysed at different periods. The authors have concluded that the motors of the upper and lower rolls are in a satisfactory condition. The results of the study conducted generally develop the idea of using object-oriented digital shadows for the industrial electrical equipment. The authors have introduced technologies that improve the reliability of the rolling mills electrical drives which accounts for the innovative development in metallurgy. The authors have also provided recommendations on expanded industrial applications of the research results. Full article

Quantization for a Borel probability measure refers to the idea of estimating a given probability by a discrete probability with support containing a finite number of elements. If in the quantization some of the elements in the finite support are preselected, then the quantization is called a conditional quantization. In this paper, we have determined the conditional quantization, first for two different finite discrete distributions with a same conditional set, and for a finite discrete distribution with two different conditional sets. Next, we have determined the conditional and unconditional quantization for an infinite discrete distribution with support $\{{\displaystyle \frac{1}{2^n}}:n\in \mathbb{N}\}$. We have also investigated the conditional quantization for an infinite discrete distribution with support $\{{\displaystyle \frac{1}{n}}:n\in \mathbb{N}\}$. At the end of the paper, we have given a conjecture and discussed about some open problems based on the conjecture. Full article

This paper introduces a novel numerical approach for solving fractional stochastic differential equations (FSDEs) using bilinear time-series models, driven by the Caputo–Katugampola (C-K) fractional derivative. The C-K operator generalizes classical fractional derivatives by incorporating an additional parameter, enabling the enhanced modeling of memory effects and hereditary properties in stochastic systems. The primary contribution of this work is the development of an efficient numerical framework that combines bilinear time-series discretization with the C-K derivative to approximate solutions for FSDEs, which are otherwise analytically intractable due to their nonlinear and memory-dependent nature. We rigorously analyze the impact of fractional-order dynamics on system behavior. The bilinear time-series framework provides a computationally efficient alternative to traditional methods, leveraging multiplicative interactions between past observations and stochastic innovations to model complex dependencies. A key advantage of our approach is its flexibility in handling both stochasticity and fractional-order effects, making it suitable for applications in a famous nuclear physics model. To validate the method, we conduct a comparative analysis between exact solutions and numerical approximations, evaluating convergence properties under varying fractional orders and discretization steps. Our results demonstrate robust convergence, with simulations highlighting the superior accuracy of the C-K operator over classical fractional derivatives in preserving system dynamics. Additionally, we provide theoretical insights into the stability and error bounds of the discretization scheme. Using the changes in the number of simulations and the operator parameters of Caputo–Katugampola, we can extract some properties of the stochastic fractional differential model, and also note the influence of Brownian motion and its formulation on the model, the main idea posed in our contribution based on constructing the fractional solution of a proposed fractional model using known bilinear time series illustrated by application in nuclear physics models. Full article

This article investigates the event-based dissipative filtering problem for nonlinear networked systems with dynamic quantization. The nonlinear plant is represented using a discrete-time Takagi–Sugeno (T–S) fuzzy model. The main idea of this article is that a novel dynamic event-triggered mechanism as well as a dynamic quantization strategy combined with a general online adjustment rule are introduced to comprehensively decrease the amount of data involved in network communication and realize the rational utilization of limited communication resources. This article aims to design an event-based quantized filter such that the asymptotic stability and the specified dissipative filtering performance of the filtering error system can be ensured. The design conditions for the desired filter are provided in the form of linear matrix inequalities. Lastly, the effectiveness of the proposed filter design method is demonstrated through the simulation results of a practical example. Full article

This article reviews the literature on both (a) the general theory of public corruption and its evolution over time; and (b) the history of urban public corruption during the modern period into the present. In addition, this article conducts a historical narrative form of representation to structure the historical facts, synthesizing chronologically disparate elements into a synchronic unity, with the focus of the narrative on “urban public corruption”, both empirically (i.e., how its manifestation changed over time in particular times and places) and conceptually (i.e., how the ideas about these manifestations altered with the passage of time). The period considered is mainly from the onset of the Industrial Revolution in the mid-18th century, up to the present time, with a major focus on contemporary developments. This review illustrates that the extraction of rents has always been a key feature of urban corruption. Nonetheless, not all extraction is alike institutionally and historically. The analysis presented here indicates that the modern notion of corruptions has been the product of a long evolution which, no doubt, is not over. The present idea is of corruption as a technocratic one of a “coherent, discrete referent” based on rational choice theory, which can be applied to define acts as corrupt regardless of social context. This is found to be not applicable in all times and places. Defining what constitutes a “corrupt” act varies considerably across cultures, across times, between nations and cities, and sometimes even within them. This article closes with a template about possible behavioral spheres of urban corruption, incorporating overlaps and gaps between “rational”, “maximizing”, and “atomistic” motivations. The conclusion is that the current consensual “rational choice” understandings only apply to those acts which incorporate all three aspects, with variants drawn from “behavioral” economics expanding applicability somewhat, but still leaving out a great deal of city corruption on the ground which is much more social and institutional than present understandings allow for. Full article

Epilepsy is a neurologic condition characterized by recurring seizures resulting from aberrant brain activity. It is crucial to promptly and precisely detect epileptic seizures to ensure efficient treatment. The gold standard electroencephalography (EEG) accurately records the brain’s electrical activity in real time. The intent of this study is to precisely detect epileptic episodes by leveraging machine learning and deep learning algorithms on EEG inputs. The proposed approach aims to evaluate the feasibility of developing a novel technique that utilizes the Hurst exponent to identify EEG signal properties that could be crucial for classification. The idea posits that the prolonged duration of EEG in epileptic patients and those who are not experiencing seizures can differentiate between the two groups. To achieve this, we analyzed the long-term memory characteristics of EEG by employing time-dependent Hurst analysis. Together, the Hurst exponent and the Daubechies 4 discrete wavelet transformation constitute the basis of this unique feature extraction. We utilize the ANOVA test and random forest regression as feature selection techniques. Our approach creates and evaluates support vector machine, random forest classifier, and long short-term memory network machine learning models to classify seizures using EEG inputs. The highlight of our research approach is that it examines the efficacy of the aforementioned models in classifying seizures utilizing single-channel EEG with minimally handcrafted features. The random forest classifier outperforms other options, with an accuracy of 97% and a sensitivity of 97.20%. Additionally, the proposed model’s capacity to generalize unobserved data is evaluated on the CHB-MIT scalp EEG database, showing remarkable outcomes. Since this framework is computationally efficient, it can be implemented on edge hardware. This strategy can redefine epilepsy diagnoses and hence provide individualized regimens and improve patient outcomes. Full article

Quantization for a Borel probability measure refers to the idea of estimating a given probability by a discrete probability with support containing a finite number of elements. If, in the quantization some of the elements in the support are preselected, then the quantization is called a conditional quantization. In this paper, we investigate the conditional quantization for the uniform distributions defined on the unit line segments and m-sided regular polygons, where $m\ge 3$, inscribed in a unit circle. Full article

With the development of Industry 4.0, discrete manufacturing systems are accelerating their transformation toward flexibility and intelligence to meet the market demand for various products and small-batch production. The flexible flow shop (FFS) paradigm enhances production flexibility, but existing studies often address FFS scheduling and automated guided vehicle (AGV) path planning separately, resulting in resource competition conflicts, such as equipment idle time and AGV congestion, which prolong the manufacturing cycle time and reduce system energy efficiency. To solve this problem, this study proposes an integrated production–transportation scheduling framework (FFSP-AGV). By using the adjacent sequence modeling idea, a mixed-integer linear programming (MILP) model is established, which takes into account the constraints of the production process and AGV transportation task conflicts with the aim of minimizing the makespan and improving overall operational efficiency. Systematic evaluations are carried out on multiple test instances of different scales using the CPLEX solver. The results show that, for small-scale instances (job count ≤10), the MILP model can generate optimal scheduling solutions within a practical computation time (several minutes). Moreover, it is found that there is a significant marginal diminishing effect between AGV quantity and makespan reduction. Once the number of AGVs exceeds 60% of the parallel equipment capacity, their incremental contribution to cycle time reduction becomes much smaller. However, the computational complexity of the model increases exponentially with the number of jobs, making it slightly impractical for large-scale problems (job count > 20). This research highlights the importance of integrated production–transportation scheduling for reducing manufacturing cycle time and reveals a threshold effect in AGV resource allocation, providing a theoretical basis for collaborative optimization in smart factories. Full article

In this study, a novel cantilever piezoelectric energy harvester is constructed by using a quasi-zero stiffness (QZS) structure. The QZS structure consists of a classic piezoelectric cantilever beam combined with some accessories that include two pre-compression springs, rolling bearings, slideways and a cylindrical cam. The purpose of the QZS structure is to reduce the natural frequencies of the harvester, so that it can more efficiently collect low-frequency vibration energy. In this study, firstly, the extended Hamilton variational principle is used to establish the dynamic equations of the continuous system. Secondly, the Galerkin method is used to discretize the partial differential equation, and then the analytical solutions of the output voltage, current, power and vibration response of the harvester are obtained. Finally, the influence of the QZS structure on energy harvesting characteristics is studied. Theoretical research shows that the QZS structure can effectively reduce the fundamental natural frequency of the cantilever beam and improve its energy harvesting efficiency. When the spring stiffness is about half of the bending stiffness of the cantilever beam, the uncoupled fundamental natural frequency of the harvester is quasi-zero. For the experimental device considered here, experiments show that the QZS structure can reduce the fundamental natural frequency from 76.4 Hz to 54.1 Hz, decreasing by 22.3 Hz. The maximum output power is increased from 1.43 mW/g² to 1.95 mW/g², an increase of 36.4%. The experimental results validate the theoretical model. In short, this paper provides a new idea for the design of energy harvesters suitable for low-frequency vibration. Full article

Let $\tau$ be a topology on the finite set $X_n$. We consider the open-set polynomial associated with the topology $\tau$. Its coefficients are the cardinalities of sets $U_j=U_j\left(\tau \right)$ of open sets of size $j=0,\dots ,n.$ We prove that this polynomial has only real zeros only in the trivial case where $\tau$ is the discrete topology. Hence, we answer a question raised by J. Brown. We give a partial answer to the question: for which topology is this polynomial log-concave, or at least unimodal? More specifically, we prove that if the topology has a large number of open sets, its open polynomial is unimodal. The idea of degree of log-concavity is introduced and it is shown to be limited for polynomials of non-trivial topologies. Furthermore, the maximum-sized topologies that omit open sets of given sizes are derived. Moreover, all topologies over n points with at least $(3/8)2^n$ open sets are proved to be unimodal, completing previous results. Full article

The vibration of a ship’s propulsion shaft system directly affects the ship’s lifespan, and many studies have designed vibration absorbers only for one of the natural frequencies of a ship’s propulsion shaft system without considering the influence of multiple low-order resonance frequencies. In this paper, a vibration absorber combined with a magnetorheological elastomer vibration absorber and a rubber vibration absorber in series is designed, and it can cover two torsional natural frequency band ranges to achieve better vibration reduction performances in multiple different torsional natural frequencies. The torsional natural frequency of the propulsion shafting of a 45 m fishing vessel is determined based on a multiple-degrees-of-freedom equivalent discretization model. Two natural frequencies, 22.4 Hz and 131.4 Hz, of a ship propulsion shaft system are selected as the design goal parameters of the combined vibration absorber. The magnetic field is simulated to ensure that the magnetic field generated by an energized coil can meet requirements. Then, a dynamic simulation of the ship propulsion shaft system with a combined vibration absorber is conducted via co-simulation. Afterward, the device is installed on the intermediate shaft of the ship propulsion shaft system for simulation, and the vibration reduction effect of the device is analyzed at different frequencies by controlling the current. When the device is controlled to operate at the optimal frequency point, the results show that the angular acceleration vibration amplitude reduction around the first and third torsional natural frequencies of the propulsion shaft system reaches 90% and 18%, respectively. This study provides new ideas for the intelligent and controllable vibration damping of ship propulsion shaft systems, especially for the development trend of intelligent ship equipment under complex working conditions. Full article

The structural vibration problem in ships and marine structures is one of the core issues in this field. The typical flat plate is a basic structural unit that constitutes the main structures of the hull, such as the cabin, bow and stern, double bottom, superstructure, etc. Typical plate structures and plate frame structures are the basic structures that researchers focus on. This article briefly reviewed the development history of vibration prediction methods for typical flat plate structures and carried out work inspired by different methods and ideas. In order to provide a new tool for predicting the vibration wave energy distribution of typical flat plate structures, a new method for predicting the vibration wave energy distribution of a simple flat plate structure is proposed. This method combines the ideas of ray tracing and the finite element method, discretizes the structure into elements, and represents the transmission of vibration in the structure in the form of energy function mapping between elements and boundaries. After sufficient mapping, the steady-state solution of structural vibration energy density can be obtained. Compared with the finite element method and ray tracing method, this method has better computational efficiency; compared with statistical energy analysis, this method has better spatial resolution. Full article

We investigate classical continuous systems characterized by singular velocity distributions, where the corresponding Radon measures are defined over the entire space with infinite mass. These singular distributions are used to model particle velocities in systems where traditional velocity distributions do not apply. As a result, the particle positions in such systems no longer conform to conventional configurations in physical space. This necessitates the development of novel analytical tools to understand the underlying models. To address this, we introduce a new conceptual framework that redefines particle configurations in phase space, where each particle is represented by its spatial position and a velocity vector. The key idea is the construction of the Plato space, which is designed to represent idealized particle configurations where the total velocity remains bounded within any compact subset of phase space. This space serves as a crucial bridge to the space of vector-valued discrete Radon measures, where each measure captures the velocity distribution over the entire system. Given the inherent complexity of analyzing infinite-dimensional spaces, we tackle the problem by reformulating it onto a finite-dimensional configuration space. This is achieved by decomposing the infinite space into smaller, more manageable components. A central tool in this reformulation is the K-transform, which is pivotal in enabling harmonic analysis of the space. The K-transform allows us to represent the system in terms of components that are more amenable to analysis, thus simplifying the study of the system’s dynamics. Furthermore, we extend previous results in the study of correlation functions by developing correlation measures tailored for these vector-valued Radon measures. These generalized functions provide deeper insights into the correlations between particle positions and velocities, expanding the range of analysis to systems with singular velocity distributions. Through this approach, we develop a robust mathematical framework that sheds light on the structure and dynamics of complex particle systems, especially those characterized by singular velocity distributions. Our results offer a new perspective on systems with non-traditional velocity distributions, advancing the theory and methodology of particle systems in both classical and modern contexts. Full article

The permeability characteristics of tailings directly affect the position of the infiltration line of the tailings dam, which is the most critical factor affecting tailings dam failures. In order to fully analyze the essence of its permeability characteristics, computed tomography (CT) technology is used to analyze the structure of different types of tailings from a microscopic perspective and carry out microscopic seepage simulation. The results showed the following findings: (1) The porosity of viscous tailings ranges from 25 to 35%, the distribution of surface porosity along the height is relatively uniform, and the distribution is shown as having a certain discrete nature with the increase in particle size. (2) Compared with silty and sandy tailings, the surface of viscous tailings is smoother and more round, and the shape factor can reach 0.95; (3) The data gap between the simulation and the measurements by CT scanning technology is less than 10%, and the estimation of the permeability characteristics is feasible, with good applicability in the simulation of tailings seepage. (4) In the microscopic pore throat structure, the permeability characteristics of the tailings are more affected by the radius of the throat than the pore radius, and the exponential function relationship between the permeability coefficient and the porosity satisfies a high correlation. In this paper, the relationship between the microstructure and permeability characteristics of tailings is analyzed by CT technology; the permeability is simulated and calculated, and a permeability coefficient prediction model for tailings is proposed in combination with the experiment, which can provide a new idea and method for the study of the permeability characteristics of tailings. Full article

Background: This retrospective study is the only one in the last 10 years from central Europe and provides a current picture of prevalence, new diagnostic modalities, new methods of surgical treatment, and also offers new insights into post-operative care. Triceps tendon rupture is the least reported among all the tendon injuries in the literature. In general, effective treatments for tendon injuries are lacking because the understanding of tendon biology lags behind that of the other components of the musculoskeletal system. Tendon tissue has a low number of cells and growth hormones and thus a lack of natural healing ability. Understanding the links between the mechanical and biological parameters involved in tendon development, homeostasis, and repair is a prerequisite for the identification of effective treatments for chronic and acute tendon injuries. Methods: The authors statistically evaluated the set of patients with this diagnosis in the largest University Hospital in Slovakia over the last 10 years. Results: Between 2014 and 2023, 23 patients with distal triceps tendon ruptures (DTTR) were treated at University Hospital. In some years not a single patient with this diagnosis underwent surgery, reinforcing the idea that DTTR may be either rare or underdiagnosed. The incidence in our region is 0.46 cases per 100,000 inhabitants. The average age of patients was 57.7 years, with a male predominance of 90%. Less than half of the patients (43.5%) underwent surgical intervention, and the median time from injury to surgery was less than 10 days. This rapid timeline indicates a high standard of medical care, given the semi-elective nature of the surgery and the need for MRI (Magnetic Resonance Imaging) confirmation of tendon rupture exceeding 50% of the fibers before proceeding with surgery. The three standard surgical techniques were employed in approximately equal proportions. Conclusions: This study suggests that none of the methods is currently preferred, and that the choice of the technique was largely determined by perioperative findings and the surgeon’s discretion. Post-operative complications were minimal, with only one patient experiencing any issues after surgery. Full article