System Parameters Research Articles

Patient dose and associated exposure parameters in pelvic x-ray examinations: dependence on radiographic system.

Technological differences between computed radiography (CR) and digital radiography (DR) systems can influence patient doses and exposure parameters in pelvic x-ray examinations. The presence of radiosensitive organs in the pelvic region underscores the need to optimize these parameters for both CR and DR systems. This prospective study aimed to compare the patient doses and exposure parameters for adult patients undergoing pelvic x-ray examinations using CR and DR systems, based on data from Sri Lanka. The study included data from 56 x-ray examinations, with 25 using CR and 31 using DR. Patient demographic characteristics and exposure parameters (kVp: kilovoltage peak, mAs: tube current-exposure time product) were recorded, and patient doses were measured in terms of the kerma-area product (PKA) using a PKA meter. Despite similar mean weight and body mass index (BMI), the CR systems showed significantly higher mean kVp (7.4%), mAs (16.4%), and PKA (29.7%) than the DR systems (CR - kVp: 73.2, mAs: 37.8, PKA: 2.29Gy cm2; DR - kVp: 67.8, mAs: 31.6, PKA: 1.61Gy cm2). The Mann-Whitney U test revealed statistically significant differences in PKA and kVp between the CR and DR systems (p < 0.05). Furthermore, even with lower patient weight and BMI, the mean mAs and PKA in this study were substantially higher than those reported in the literature for both CR and DR systems. These results suggest the need to optimize current mAs settings for the studied hospitals and introduce radiographic system-specific exposure parameters and reference dose levels for pelvic x-ray examinations in order to enhance patient protection.

Dynamical analysis and event-triggered adaptive finite-time prescribed performance control of the FO coupled MEMS resonators

This paper explores the dynamic behaviors and control method of weakly coupled micro-electro-mechanical system (MEMS) resonators with fractional-order (FO) dynamics. In the dynamics analysis session, Lyapunov exponents, bifurcation theory, and phase diagrams are used to analyze the effects of system parameters, coupling stiffness, and FO on the complex dynamical behaviors such as periodicity, pseudo-periodicity, and chaos oscillations. To suppress chaotic oscillations, a dynamic event-triggered finite-time prescribed performance controller is proposed. The unknown nonlinear functions are approximated through the interval type-3 fuzzy system (IT3FS) with an adaptive law. A novel finite-time prescribed performance function (finite-time PPF) is constructed to establish constrained boundaries for tracking errors. Compared with the existing PPFs, the proposed approach allows for more flexible setting of the convergence boundary before reaching steady-state. Subsequently, the constrained tracking errors are mapped to an unconstrained form using a nonlinear transformation function, whether the error constraint is symmetric or asymmetric. To circumvent the “explosion of complexity” arising from backstepping design process, a tracking differentiator (TD) is utilized. Additionally, to alleviate strain on communication resources, an event-triggered mechanism is devised to update control signals. The trigger threshold of the control signals can be adaptively adjusted based on the values of the Lyapunov function and the dynamic auxiliary variables. This control method guarantees finite-time convergence for all signals of the system. Finally, extensive simulations are performed to verify the effectiveness of the proposed algorithm.

Radiation shielding competence of SeTeSnIn chalcogenide glassy system: Resistance against gamma irradiation

Abstract This paper reports the study of the high-energy radiation shielding characteristics of the STS glassy system. Further, the work investigates the effect of indium concentration on the high energy radiation shielding characteristics of the STS glassy system. For this purpose, a glassy Se78-xTe20Sn2Inx (x = 0, 2, 4, and 6) system was synthesized using a renowned melt quench technique whose density was measured through the Archimedes method. We have utilized an online platform, i.e., Phy-X/PSD software, to measure the different radiation shielding parameters of the SeTeSnIn glassy system. Several shielding parameters such as linear and mass attenuation coefficient, half value layer (HVL), mean free path (MFP), effective atomic number (Zeff), effective electron density (Neff), effective conductivity (Ceff), equivalent atomic number (Zeq), energy absorption build-up factor (EABF), exposure build-up factor EBF), and fast neutron removal cross-section (FNRCS) have been measured in the energy range of 15 keV to 15 MeV.

Least Squares Estimation of Multifactor Uncertain Differential Equations with Applications to the Stock Market

Multifactor uncertain differential equations are powerful tools for studying dynamic systems under multi-source noise. A key challenge in this study is how to accurately estimate unknown parameters based on the framework of uncertainty theory in multi-source noise environments. To address this core problem, this paper innovatively proposes a least-squares estimation method. The essence of this method lies in constructing statistical invariants with a symmetric uncertainty distribution based on observational data and determining specific parameters by minimizing the distance between the population distribution and the empirical distribution of the statistical invariant. Additionally, two numerical examples are provided to help readers better understand the practical operation and effectiveness of this method. In addition, we also provide a case study of JD.com’s stock prices to illustrate the advantages of the method proposed in this paper, which not only provides a new idea and method for addressing the problem of dynamic system parameter estimation but also provides a new perspective and tool for research and application in related fields.

Application of Fractional-Order Multi-Wing Chaotic System to Weak Signal Detection

This work investigates a fractional-order multi-wing chaotic system for detecting weak signals. The influence of the order of fractional calculus on chaotic systems’ dynamical behavior is examined using phase diagrams, bifurcation diagrams, and SE complexity diagrams. Then, the principles and methods for determining the frequencies and amplitudes of weak signals are examined utilizing fractional-order multi-wing chaotic systems. The findings indicate that the lowest order at which this kind of fractional-order multi-wing chaotic system appears chaotic is 2.625 at a=4, b=8, and c=1, and that this value decreases as the driving force increases. The four-wing and double-wing change dynamics phenomenon will manifest in a fractional-order chaotic system when the order exceeds the lowest order. This phenomenon can be utilized to detect weak signal amplitudes and frequencies because the system parameters control it. A detection array is built to determine the amplitude using the noise-resistant properties of both four-wing and double-wing chaotic states. Deep learning images are then used to identify the change in the array’s wing count, which can be used to determine the test signal’s amplitude. When frequencies detection is required, the MUSIC method estimates the frequencies using chaotic synchronization to transform the weak signal’s frequencies to the synchronization error’s frequencies. This solution adds to the contact between fractional-order calculus and chaos theory. It offers suggestions for practically implementing the chaotic weak signal detection theory in conjunction with deep learning.

Advantages of a novel truncated cone DE-air generator in energy conversion

Abstract Harvesting energy from ambient environments such as vibrations is a feasible approach to selfpower low powered electric devices. T- he dielectric elastomer generator (DEG) is a type of novel electrostatic generator with superior vibration energy harvesting (EH) performance. On the basis of traditional DEGs, a new concept of dielectric elastomer (DE)-air generator (DEAG), which contains the air layer and the DE membrane (DEM) as a composite dielectric layer, is proposed in this paper for the first time. Inspired by a classical truncated cone DEG (TC-DEG) concept, the novel truncated cone DEAG (TC-DEAG) is designed and comprehensively studied. Compared with the TC-DEG, the proposed TC-DEAG provides the larger capacitance ratio, leading to superior electrical output. The energy conversion mechanisms of both the TC-DEG and the TC-DEAG under a regular linear reciprocating excitation are analyzed theoretically by deducing the deformation condition of the DEM and the electrical outputs. Through measuring the capacitance of the DEM under deformations and testing the output voltage of the fabricated generators, the proposed theoretical models and predictions are verified. Moreover, numerical simulations based on the verified theoretical model are conducted to reveal the influences of some important system parameters on the EH performances of both generators, providing guidelines for the performance improvement of the generators.

Sodium fluctuation as a parameter in predicting mortality in general hospitalized patients

BackgroundDysnatremia is the most common electrolyte disorder in hospitalized patients. Sodium fluctuation level may be a better parameter in dysnatremia management. We aimed to examine the association between sodium fluctuation level during hospitalization and mortality and to evaluate its value in predicting poor prognosis among general hospitalized patients.MethodsData were collected from patients admitted to Peking Union Medical College Hospital. The generalized estimated equation (GEE) was used to examine the relationship between sodium fluctuation level and mortality. Receiver-operating characteristic (ROC) curve analysis was performed to calculate the optimal cutoff value and the area under the ROC curve (AUC).ResultsSodium fluctuation level showed a dose-dependent association with increased mortality in general hospitalized patients. After adjusting age, sex, length of hospital stay, and Charlson comorbidity index, the ORs of group G2 to G6 were 5.92 (95% CI 5.16–6.79), 26.45 (95% CI 22.68–30.86), 50.71 (95% CI 41.78–61.55), 104.38 (95% CI 81.57–133.58), and 157.64 (95% CI 112.83–220.24), respectively, p trend &amp;lt;0.001. Both normonatremia and dysnatremia patients on admission had the dose-dependent associations similar to general hospitalized patients. The AUC of sodium fluctuation level was 0.868 (95% CI 0.859–0.877) in general hospitalized patients, with an optimal cutoff point of 7.5 mmol/L, a sensitivity of 76.5% and a specificity of 84.2%.ConclusionWe determined that sodium fluctuation level had a dose-dependent association with increased mortality in general hospitalized patients. Sodium fluctuation level could be used to develop a single parameter system in predicting mortality in general hospitalized patients with acceptable accuracy, sensitivity, and specificity.

Analysis of inter-satellite optical wireless communication systems for enhanced data transmission in satellite constellations

This research focuses on the comprehensive performance analysis of inter-satellite optical wireless communication (IsOWC) systems, specifically tailored for high data rate applications in Earth observation satellites. The research employs OptiSystem 21.0 simulation software to model and analyze the IsOWC systems. The simulation scenario is set in a low Earth orbit (LEO) constellation, typical for Earth observation satellites. Various system parameters are systematically varied to assess their impact on performance. Modulation types, such as non-return-to-zero (NRZ) and return-to-zero (RZ) are analyzed for their influence on the quality (Q) factor. The study further explores the effects of different wavelengths, antenna apertures, transmitter output powers, and link distances on the IsOWC system performance. This research provides valuable insights into optimizing IsOWC systems for Earth observation satellites, contributing to the advancement of communication technologies in satellite networks. The research shows that the NRZ modulation consistently outperforms RZ modulation in terms of maximum Q factor and minimum BER across different antenna apertures and power levels. Additionally, shorter wavelengths exhibit improved performance, while larger antenna apertures contribute to enhanced signal quality. The relationship between transmitter power and data rate is also investigated, demonstrating the potential for achieving higher data rates with increased transmitter power. The findings guide the selection of parameters to achieve optimal performance, ensuring efficient data transfer and meeting the demands of contemporary Earth observation missions. This study provides conclusive evidence that the 1350 nm wavelength outperforms the 1550 nm wavelength in reliable and high-data-rate optical wireless communications, offering higher received power, superior signal quality, and lower bit error rates. This makes it a preferred choice for systems in challenging space environments and could enhance future satellite communication architectures.

Time-bin entanglement in the deterministic generation of linear photonic cluster states

We theoretically investigate strategies for the deterministic creation of trains of time-bin entangled photons using an individual quantum emitter described by a Λ-type electronic system. We explicitly demonstrate the theoretical generation of linear cluster states with substantial numbers of entangled photonic qubits in full microscopic numerical simulations. The underlying scheme is based on the manipulation of ground state coherences through precise optical driving. One important finding is that the most easily accessible quality metrics, the achievable rotation fidelities, fall short in assessing the actual quantum correlations of the emitted photons in the face of losses. To address this, we explicitly calculate stabilizer generator expectation values as a superior gauge for the quantum properties of the generated many-photon state. With widespread applicability in other emitter and excitation–emission schemes also, our work lays the conceptual foundations for an in-depth practical analysis of time-bin entanglement based on full numerical simulations with predictive capabilities for realistic systems and setups, including losses and imperfections. The specific results shown in the present work illustrate that with controlled minimization of losses and realistic system parameters for quantum-dot type systems, useful linear cluster states of significant lengths can be generated in the calculations, discussing the possibility of scalability for quantum information processing endeavors.

Optimum design parameters for double concave friction pendulum system considering ground motion characteristics and friction heating

Optimum design parameters for double concave friction pendulum system considering ground motion characteristics and friction heating

An incentive strategy for the retention of impatient passengers in ride-sourcing markets

A prominent problem plagued the ride-sourcing service providers is the instantaneous real-time demand–supply imbalance. This entails a terrible user experience and causes adverse sustainable results such as customer churn for the platform, which will damage both drivers’ income and the platform revenue. To reduce passenger cancellation caused by extended wait times, we propose an incentive-based queue management strategy —a discount method— to enhance the waiting experience and encourage passengers to stay in a post-peak period . We formulate the waiting process for a ride-sourcing service as an M/M/c+M queue system with impatient passengers, and model passengers’ reneging behaviors by characterizing the impact of discounted trip fare and updated queue information on their travel utilities. Based on such a behavior model, we can analyze the effect of the discount strategy on the queueing process, which allows us to maximize the platform’s profit growth by tailoring the discount strategy. Our result shows that the discount strategy can effectively increase the platform’s profit. Under the specific condition of the discount strategy, the earlier the strategy is implemented in the post-peak period, the higher platform profit can be achieved. Moreover, we explore the impact of queueing system parameters on the performance of the discount strategy and gain some interesting insights.

Load frequency control in power systems with high renewable energy penetration: A strategy employing P[formula omitted](1+PDF) controller, hybrid energy storage, and IPFC-FACTS

The high penetration of Renewable Energy Sources (RESs) in the modern power system poses a challenge to power system stability. This stability is affected by the stochastic, fluctuating output of RESs, which is influenced by weather conditions, and a lack of inertia resulting from reduced rotating mass. To address this issue, a new controller, referred to as Proportional-Fractional Integrator Plus Proportional-Derivative with Filter, PIλ(1+PDF), is designed for Load Frequency Control (LFC) with the support of a Hybrid Energy Storage System (HESS) for power systems with high-RES penetration. The HESS comprises a Superconducting Magnetic Energy Storage System (SMES) and a Vanadium Redox Flow Battery (VRFB) coupled with an Interline Power Flow Controller Flexible AC Transmission Systems (IPFC-FACTs) controller. The HESS, working in conjunction with the proposed LFC, injects virtual inertia and maintains power flow to expedite the frequency stability process. These systems are also integrated with Alternating Current (AC) and High Voltage Direct Current (HVDC) transmission lines to collectively enhance both the system's stability and the capacity of its transmission lines. To optimize the PIλ(1+PDF) controller parameters, Zebra Optimization Algorithm (ZOA) is employed utilizing an Integral Time Absolute Error (ITAE) objective function. The proposed controller is tested on a four-area power system integrated with a wind turbine, photovoltaic (PV) panels, a biodiesel generator, and a hydrogen aqua electrolyzer fuel cell, representing a high penetration of RESs in modern power systems. The results are compared with those obtained using Proportional-Integral-Derivative (PID) and Fractional Order Proportional Integral Derivative (FOPID) controllers. Sensitivity analysis and robustness tests are also performed to verify the stability of the power network by changing system parameters and under randomly chosen loading conditions. The proposed PIλ(1+PDF) controller tuned with ZOA outperforms PID and FOPID controllers by minimizing settling time for frequency changes by 62 %, eliminating overshoot, and reducing undershoots for frequency and tie-line power changes by 73 % and 55 %, respectively. Simulation results demonstrate that the proposed controller outperforms PID and FOPID controllers by effectively damping frequency and tie-line deviations, resulting in reduced frequency overshoots, undershoots, and shorter settling times.

Detection of Demagnetization Faults in Electric Motors by Analyzing Inverter Based Current Data Using Machine Learning Techniques

Demagnetization of the rotor magnets is a significant failure mode that can occur in permanent magnet synchronous machines (PMSMs). Early detection of demagnetization faults can help change system parameters to reduce power output or ensure safety. In this paper, the effects of demagnetization faults were analyzed both in simulation and experiments using the example of drone motors. An approach was investigated to detect even minor demagnetization faults that does not require any additional sensing effort. Machine learning (ML) techniques are used to analyze the phase current data directly received from the inverter to enable anomaly detection. For this purpose, the phase current is transformed by the Fast Fourier Transform (FFT), the spectral data is then reduced in dimensionality, followed by an anomaly detection algorithm using a one-class support vector machine (OC-SVM). To ensure simplified initialization of the ML model without the need for training sets of damaged drives, only data from magnetically undamaged motors was used to train the models for anomaly detection. Different selections of considered harmonics and different metrics were investigated using the experimental data, achieving a precision of up to 99%, a specificity of up to 98%, and an accuracy of up to 90%.

Tracking and managing the water-food-environment-ecosystem (WFEE) nexus in groundwater irrigation districts using system dynamics modelling

Groundwater irrigation districts, which play a crucial role in the Earth's critical zone, are confronted with numerous challenges, including water scarcity, pollution, and ecological degradation. These issues come from multiple systems and are linked to a groundwater-dominated water-food-environment-ecosystem nexus problem related to agricultural activities (WFEE). There is a pressing need for the scientific characterization and evaluation of the WFEE nexus in groundwater irrigation districts to assure high-quality, sustainable development. Furthermore, it is critical to provide practical and efficient regulations at the farmer level to uphold the health of this nexus. This paper presents a mapping network that focuses on groundwater irrigation districts. The network aims to convert the restriction indicators utilized to maintain the health of the WFEE nexus (at the irrigation district scale) into the targets employed to manage farmers' living and agricultural activities (at the farmer scale). Additionally, a system dynamics model is created to track and manage the interacting relationships between the WFEE nexus and farmers' living and agricultural activities. This proposed model employs a structured parameter system comprising targets, state parameters, regulatory parameters, and evaluation parameters. This system can get insight into the status of the WFEE nexus at the farmer level using state parameters, induce tailored management and regulation measures using regulatory parameters, assess the effectiveness of various measures using the evaluation parameters, and finally provide decision support to enhance the health of the WFEE nexus. The findings from the research conducted in the Yong'an groundwater irrigation district demonstrated that the model accurately described the relationship between the WFEE nexus and farmers' activities in groundwater irrigation districts. Furthermore, the model responded strongly to a variety of improvement strategies, including adjustments in planting area, optimization of planting pattern, improvement of irrigation method, and implementation of agronomic measures. As a result, it provided farmers with decision support for applying agricultural management methods and addressing the WFEE nexus problem in groundwater irrigation areas.

Dynamics, Periodic Orbits of a Novel Four-Dimensional Hyperchaotic System with Hidden Attractors

Abstract In recent years, the investigation of systems featuring hidden attractors and coexisting attractors has garnered significant attention. This paper presents a novel four-dimensional (4D) hyperchaotic system devoid of equilibrium points, achieved by formulating an equation without a solution or constructing a system without fixed points. Due to the complex shape of this attractor, a novel coding method is utilized to establish symbol dynamics using eight letters. The proposed system exhibits highly intricate dynamics, including variations in topological structure with alterations in system parameters, as well as an exploration and discussion of four types of coexisting attractors. Our extensive practice has led us to propose a new conjecture: hyperchaotic systems with parameters close to the bifurcation point frequently display multistable states. Furthermore, the unstable periodic orbits with different topological lengths in the hidden hyperchaotic attractor are calculated systematically using the variational method. Additionally, the DSP circuit implementation is employed to validate the numerical simulation results for this new 4D system. Finally, adaptive synchronization is successfully realized within the system, thereby confirming its feasibility.

Enhancing mobile robot navigation: integrating reactive autonomy through deep learning and fuzzy behavior

Objective: This study aimed to develop a control architecture for reactive autonomous navigation of a mobile robot by integrating Deep Learning techniques and fuzzy behaviors based on traffic signal recognition. Materials: The research utilized transfer learning with the Inception V3 network as a base for training a neural network to identify traffic signals. The experiments were conducted using a Donkey-Car, an Ackermann-steering-type open-source mobile robot, with inherent computational limitations. Results: The implementation of the transfer learning technique yielded a satisfactory result, achieving a high accuracy of 96.2% in identifying traffic signals. However, challenges were encountered due to delays in frames per second (FPS) during testing tracks, attributed to the Raspberry Pi's limited computational capacity. Conclusions: By combining Deep Learning and fuzzy behaviors, the study demonstrated the effectiveness of the control architecture in enhancing the robot's autonomous navigation capabilities. The integration of pre-trained models and fuzzy logic provided adaptability and responsiveness to dynamic traffic scenarios. Future research could focus on optimizing system parameters and exploring applications in more complex environments to further advance autonomous robotics and artificial intelligence technologies.

Review of chaos in hair-cell dynamics

The remarkable signal-detection capabilities of the auditory and vestibular systems have been studied for decades. Much of the conceptual framework that arose from this research has suggested that these sensory systems rest on the verge of instability, near a Hopf bifurcation, in order to explain the detection specifications. However, this paradigm contains several unresolved issues. Critical systems are not robust to stochastic fluctuations or imprecise tuning of the system parameters. Further, a system poised at criticality exhibits a phenomenon known in dynamical systems theory as critical slowing down, where the response time diverges as the system approaches the critical point. An alternative description of these sensory systems is based on the notion of chaotic dynamics, where the instabilities inherent to the dynamics produce high temporal acuity and sensitivity to weak signals, even in the presence of noise. This alternative description resolves the issues that arise in the criticality picture. We review the conceptual framework and experimental evidence that supports the use of chaos for signal detection by these systems, and propose future validation experiments.

Rat-Tail Models for Studying Hand-Arm Vibration Syndrome: A Comparison between Living and Cadaver Rat Tails

Over-exposure of the hand-arm system to intense vibration and force over time may cause degeneration of the vascular, neurological, and musculoskeletal systems in the fingers. A novel animal model using rat tails has been developed to understand the health effects on human fingers exposed to vibration and force when operating powered hand tools or workpieces. The biodynamic responses, such as vibration stress, strain, and power absorption density, of the rat tails can be used to help evaluate the health effects related to vibration and force and to establish a dose-effect relationship. While the biodynamic responses of cadaver rat tails have been investigated, the objective of the current study was to determine whether the biodynamic responses of living rat tails are different from those of cadaver rat tails, and whether the biodynamic responses of both living and cadaver tails change with exposure duration. To make direct comparisons, the responses of both cadaver and living rat tails were examined on four different testing stations. The transfer function of each tail under a given contact force (2 N) was measured at each frequency in the one-third octave bands from 20 to 1000 Hz, and used to calculate the mechanical system parameters of the tails. The transfer functions were also measured at different exposure durations to determine the time dependency of the response. Differences were observed in the vibration biodynamic responses between living and cadaver tails, but the general trends were similar. The biodynamic responses of both cadaver and living rat tails varied with exposure duration.

Научно-методический подход к разработке проектов опытно-промышленных испытаний открытой разработки месторождений

Methodology of designing pilot tests in open-pit mining is a complex and insufficiently developed issue in the theory and practice of designing mining systems, which, as a rule, fails to take into account the mining and geological features of the deposits. The complex development of mineral deposits requires new methods of open-pit designing. Thus, the theoretical justification and development of the methods to determine the optimal parameters and indicators of open-pits during the design of pilot tests with the establishment of scales, deadlines, tasks and test conditions is an urgent research problem. The authors of the study have systematized the research trends in developing the basis for designing pilot tests in open-pit geotechnology. The level of geological inaccuracies in case of insufficiently reliable prospecting results leads to a decrease in the expected technical and economic indicators of the mining project ranging from 5-20% to several folds. When information on the deposit is insufficient, pilot test projects are prepared. This is done in order to obtain additional input data for preparation of the feasibility study of permanent conditions or at the stage of the field development to verify the created technologies and means of their mechanisation in order to avoid revision of the mining system parameters in the course of the field operations due to discrepancies between the geomechanical and hydrogeological representations given in the detailed exploration materials and the real conditions.

Научно-методический подход к разработке проектов опытно-промышленных испытаний открытой разработки месторождений

Methodology of designing pilot tests in open-pit mining is a complex and insufficiently developed issue in the theory and practice of designing mining systems, which, as a rule, fails to take into account the mining and geological features of the deposits. The complex development of mineral deposits requires new methods of open-pit designing. Thus, the theoretical justification and development of the methods to determine the optimal parameters and indicators of open-pits during the design of pilot tests with the establishment of scales, deadlines, tasks and test conditions is an urgent research problem. The authors of the study have systematized the research trends in developing the basis for designing pilot tests in open-pit geotechnology. The level of geological inaccuracies in case of insufficiently reliable prospecting results leads to a decrease in the expected technical and economic indicators of the mining project ranging from 5-20% to several folds. When information on the deposit is insufficient, pilot test projects are prepared. This is done in order to obtain additional input data for preparation of the feasibility study of permanent conditions or at the stage of the field development to verify the created technologies and means of their mechanisation in order to avoid revision of the mining system parameters in the course of the field operations due to discrepancies between the geomechanical and hydrogeological representations given in the detailed exploration materials and the real conditions.