Under the restriction of ecological and environmental factors, our requirements have improved for the development path of gymnasium construction. According to the previous way to carry out the development path of gymnasium construction will make our construction work encounter a lot of unnecessary troubles, so we can improve the success rate of the development path of gymnasium construction under the constraints of the ecological environment by carrying out relevant evasive operations according to the constraints of ecological environment. The topological path and path algorithm used to improve the efficiency of stadium construction and development path under the constraints of ecological environment, TEG algorithm, Q-TEG model, Q-TEG algorithm, Dtra algorithm, TraD algorithm, ResR algorithm, and Q-TED algorithm used in resource reservation plus time slot plus hosting bring the following advantages: (1) we use topological path and path algorithm to explore topological representation methods suitable for development path. The overview provides a theoretical basis for guidance, for forwarding technology scheduling mechanisms and multi-path forwarding mechanisms to provide higher flexibility. (2) We use the TEG algorithm of resource reservation plus time slot plus trusteeship, Q-TEG model, and Q-TEG algorithm under multi-model model can deal with the capacity and link of queue in each stadium construction development path well. It is more convenient to set the packet loss threshold for the propagation experiment tested in the simulation. Better help gymnasium construction and development path transmission is successful. (3) The use of the Dtra algorithm, TraD algorithm, ResR algorithm, and Q-TED algorithm in our stadium construction development path of a good deal of the transmission link structure between each node, so that the transmission efficiency between nodes becomes higher, making our stadium construction development path operation more efficient and convenient.
This paper proposes an average current mode controller (ACMC) for a single-phase bridgeless power factor correction (PFC) circuit using a single ended primary inductor converter (SEPIC) via second-order model reduction. The superiority of the proposed controller is PFC accomplished at power up to 350 W with high efficiency via the second-order model reduction. The design and implementation of ACMC on the converter operated with continuous conduction mode (CCM) is explained in detail. ACMC forces input current to follow sinusoidal current reference at different power levels and sustain high power factor (PF). The proposed controller is designed based on the theoretical analysis operation of the circuit. For verification, MATLAB/Simulink simulations are carried out and validation through an experiment test rig for 110-220 Vrms input, 100 Vdc/ 350 W output prototype at 20 kHz switching frequency. It is proven that the proposed controller strategy accomplishes high PF, high efficiency and conformity with the simulation.
At present, a photovoltaic (PV) system takes responsibility to reduce the risk of global warming and generate electricity. However, the PV system faces numerous problems to track global maximum peak power (GMPP) owing to the nonlinear nature of the environment especially due to partial shading conditions (PSC). To solve these difficulties, previous researchers have utilized various conventional methods for investigations. Nevertheless, these methods have oscillations around the GMPP. Hence, a new metaheuristic method such as an opposition-based equilibrium optimizer (OBEO) algorithm is used in this work for mitigating the oscillations around GMPP. To find the effectiveness of the proposed method, it can be evaluated with other methods such as SSA, GWO, and P&O. As per the simulation outcome, the proposed OBEO method provides maximum efficiency against all other methods. The efficiency for the proposed method under dynamic PSC is 95.09% in 0.16 s, similarly, 96.17% for uniform PSC and 86.25% for complex PSC.
This study introduces a metasurface (MS) based electrically small resonator for ambient electromagnetic (EM) energy harvesting. It is an array of novel resonators comprising double-elliptical cylinders. The harvester's input impedance is designed to match free space, allowing incident EM power to be efficiently absorbed and then maximally channelled to a single load through optimally positioned vias. Unlike the previous research works where each array resonator was connected to a single load, in this work, the received power by all array resonators is channelled to a single load maximizing the power efficiency. The performance of the MS unit cell, when treated as an infinite structure, is examined concerning its absorption and harvesting efficiency. The numerical results demonstrate that the MS unit cell can absorb EM power, with near-perfect absorption of 90% in the frequency range of 5.14 GHz to 5.5 GHz under normal incidence and with a fractional bandwidth of 21%. The MS unit cell also achieves higher harvesting efficiency at various incident angles up to 60o. The design and analysis of an array of 4x4 double elliptical cylinder MS resonators integrated with a corporate feed network are also presented. The corporate feed network connects all the array elements to a single load, maximizing harvesting efficiency. The simulation and measurement results reveal an overall radiation to AC efficiency of about 90%, making it a prime candidate for energy harvesting applications.
Synchronization of the chaotic systems has attracted much attention in recent years due to its vital applications in secured communication systems. In this paper, an implementation and comparative analysis of two different control approaches for synchronization between two identical four-dimensional hyperchaotic systems is presented. The two control approaches are the Adaptive nonlinear controller and the linear optimal quadratic regulator LQR. To demonstrate the effectiveness of each controller, the numerical simulation is presented using Matlab/Simulink and the control law is derived. The performance of the proposed controllers is compared based on four factors; response time, squared error integration, energy applied from the controller, and cost function. To measure the robustness of the control approaches, the performance factors are compared when there is a change in system parameters and a variation in the initial conditions. Then the proposed synchronization methods are implemented on the FPGA platform to demonstrate the utilized resources on Field Programmable Gate Array (FPGA) hardware platform and the operation speed. Finally, to generalize the results of the comparison, the study is implemented for the synchronization of another secured communication system consisting of two identical three-dimensional chaotic. The experimental results show that the LQR method is more effective than the Adaptive controller based on the performance factors we propose. Moreover, the LQR is much simpler to implement on hardware and requires fewer resources on the FPGA.
The controllable intensified process has received immense attention from researchers in order to deliver the benefit of process intensification to be operated in a desired way to provide a more sustainable process toward reduction of environmental impact and improvement of intrinsic safety and process efficiency. Despite numerous studies on gain and phase margin approach on conventional process systems, it is yet to be tested on intensified systems as evidenced by the lack of available literature, to improve the controller performance and robustness. Thus, this paper proposed the exact gain and phase margin (EGPM) through analytical method to develop suitable controller design for intensified system using Proportional-Integral-Derivative (PID) controller formulation, and it was compared to conventional Direct Synthesis methods (DS), Internal Model Control (IMC), and Industrial IMC method in terms of the performance and stability analysis. Simulation results showed that EGPM method provides good setpoint tracking and disturbance rejection as compared to DS, IMC, and Industrial IMC while retaining overall performance stability as time delay increases. The Bode Stability Criterion was used to determine the stability of the open-loop transfer function of each method and the result demonstrated decrease in stability as time delay increases for controllers designed using DS, IMC, and Industrial IMC, and hence control performance degrades. However, the proposed EGPM controller maintains the overall robustness and control performance throughout the increase of time delay and outperform other controller design methods at higher time delay with [Formula: see text] uncertainty test. Additionally, the proposed EGPM controller design method provides overall superior control performance with lower overshoot and shorter rise time compared to other controllers when process time constant is smaller in magnitude ([Formula: see text]) than the instrumentation element, which is one of the major concerns during the design of intensified controllers, resulting overall system with a higher order. The desired selection of gain margin and phase margin were suggested at 2.5 to 4 and 60 °-70 [Formula: see text], respectively, for a wide range of control conditions for intensified processes where higher instrumentation dynamic would be possible to achieve robust control as well. The proposed EGPM method controller is thought to be a more reliable design strategy for maintaining the overall robustness and performance of higher order and complex systems that are highly affected by time delay and high dynamic response of intensified processes.
Background: V2V (Vehicle-to-Vehicle) is a booming research field with a diverse set of services and applications. Most researchers rely on vehicular simulation tools to model traffic and road conditions and evaluate the performance of network protocols. We conducted a scoping review to consider simulators that have been reported in the literature based on successful implementation of V2V systems, tutorials, documentation, examples, and/or discussion groups. Methods: Simulators that have limited information were not included. The selected simulators are described individually and compared based on their requirements and features, i.e., origin, traffic model, scalability, and traffic features. This scoping review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The review considered only research published in English (in journals and conference papers) completed after 2015. Further, three reviewers initiated the data extraction phase to retrieve information from the published papers. Results: Most simulators can simulate system behaviour by modelling the events according to pre-defined scenarios. However, the main challenge faced is integrating the three components to simulate a road environment in either microscopic, macroscopic or mesoscopic models. These components include mobility generators, VANET simulators and network simulators. These simulators require the integration and synchronisation of the transportation domain and the communication domain. Simulation modelling can be run using a different types of simulators that are cost-effective and scalable for evaluating the performance of V2V systems in urban environments. In addition, we also considered the ability of the vehicular simulation tools to support wireless sensors. Conclusions: The outcome of this study may reduce the time required for other researchers to work on other applications involving V2V systems and as a reference for the study and development of new traffic simulators.
Diabetes patients are at risk of having chronic wounds, which would take months to years to resolve naturally. Chronic wounds can be countered using the electrical stimulation technique (EST) by dielectrophoresis (DEP), which is label-free, highly sensitive, and selective for particle trajectory. In this study, we focus on the validation of polystyrene particles of 3.2 and 4.8 μm to predict the behavior of keratinocytes to estimate their crossover frequency (fXO) using the DEP force (FDEP) for particle manipulation. MyDEP is a piece of java-based stand-alone software used to consider the dielectric particle response to AC electric fields and analyzes the electrical properties of biological cells. The prototypic 3.2 and 4.8 μm polystyrene particles have fXO values from MyDEP of 425.02 and 275.37 kHz, respectively. Fibroblast cells were also subjected to numerical analysis because the interaction of keratinocytes and fibroblast cells is essential for wound healing. Consequently, the predicted fXO from the MyDEP plot for keratinocyte and fibroblast cells are 510.53 and 28.10 MHz, respectively. The finite element method (FEM) is utilized to compute the electric field intensity and particle trajectory based on DEP and drag forces. Moreover, the particle trajectories are quantified in a high and low conductive medium. To justify the simulation, further DEP experiments are carried out by applying a non-uniform electric field to a mixture of different sizes of polystyrene particles and keratinocyte cells, and these results are well agreed. The alive keratinocyte cells exhibit NDEP force in a highly conductive medium from 100 kHz to 25 MHz. 2D/3D motion analysis software (DIPP-MotionV) can also perform image analysis of keratinocyte cells and evaluate the average speed, acceleration, and trajectory position. The resultant NDEP force can align the keratinocyte cells in the wound site upon suitable applied frequency. Thus, MyDEP estimates the Clausius-Mossotti factors (CMF), FEM computes the cell trajectory, and the experimental results of prototypic polystyrene particles are well correlated and provide an optimistic response towards keratinocyte cells for rapid wound healing applications.
In this paper, we propose two different control strategies for the position control of the ball of the ball and beam system (BBS). The first control strategy uses the proportional integral derivative-second derivative with a proportional integrator PIDD2-PI. The second control strategy uses the tilt integral derivative with filter (TID-F). The designed controllers employ two distinct metaheuristic computation techniques: grey wolf optimization (GWO) and whale optimization algorithm (WOA) for the parameter tuning. We evaluated the dynamic and steady-state performance of the proposed control strategies using four performance indices. In addition, to analyze the robustness of proposed control strategies, a comprehensive comparison has been performed with a variety of controllers, including tilt integral-derivative (TID), fractional order proportional integral derivative (FOPID), integral-proportional derivative (I-PD), proportional integral-derivative (PI-D), and proportional integral proportional derivative (PI-PD). By comparing different test cases, including the variation in the parameters of the BBS with disturbance, we examine step response, set point tracking, disturbance rejection analysis, and robustness of proposed control strategies. The comprehensive comparison of results shows that WOA-PIDD2-PI-ISE and GWO-TID-F- ISE perform superior. Moreover, the proposed control strategies yield oscillation-free, stable, and quick response, which confirms the robustness of the proposed control strategies to the disturbance, parameter variation of BBS, and tracking performance. The practical implementation of the proposed controllers can be in the field of under actuated mechanical systems (UMS), robotics and industrial automation. The proposed control strategies are successfully tested in MATLAB simulation.
Objective. Gold nanorods (GNRs) have emerged as versatile nanoparticles with unique properties, holding promise in various modalities of cancer treatment through drug delivery and photothermal therapy. In the rapidly evolving field of nanoparticle radiosensitization (NPRS) for cancer therapy, this study assessed the potential of gold nanorods as radiosensitizing agents by quantifying the key features of NPRS, such as secondary electron emission and dose enhancement, using Monte Carlo simulations.Approach. Employing the TOPAS track structure code, we conducted a comprehensive evaluation of the radiosensitization behavior of spherical gold nanoparticles and gold nanorods. We systematically explored the impact of nanorod geometry (in particular size and aspect ratio) and orientation on secondary electron emission and deposited energy ratio, providing validated results against previously published simulations.Main results. Our findings demonstrate that gold nanorods exhibit comparable secondary electron emission to their spherical counterparts. Notably, nanorods with smaller surface-area-to-volume ratios (SA:V) and alignment with the incident photon beam proved to be more efficient radiosensitizing agents, showing superiority in emitted electron fluence. However, in the microscale, the deposited energy ratio (DER) was not markedly influenced by the SA:V of the nanorod. Additionally, our findings revealed that the geometry of gold nanoparticles has a more significant impact on the emission of M-shell Auger electrons (with energies below 3.5 keV) than on higher-energy electrons.Significance. This research investigated the radiosensitization properties of gold nanorods, positioning them as promising alternatives to the more conventionally studied spherical gold nanoparticles in the context of cancer research. With increasing interest in multimodal cancer therapy, our findings have the potential to contribute valuable insights into the perspective of gold nanorods as effective multipurpose agents for synergistic photothermal therapy and radiotherapy. Future directions may involve exploring alternative metallic nanorods as well as further optimizing the geometry and coating materials, opening new possibilities for more effective cancer treatments.
Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services. Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.
Different computational methods have been used for the prediction of X-ray spectra and beam quality in diagnostic radiology. The purpose of this study was to compare X-ray beam qualities based on half-value layers (HVLs) determined through measurements and computational model estimations.
Hyperparameter tuning is an important process to maximize the performance of any neural network model. This present study proposed the factorial design of experiment for screening and response surface methodology to optimize the hyperparameter of two artificial neural network algorithms. Feed-forward neural network (FFNN) and radial basis function neural network (RBFNN) are applied to predict the permeate flux of palm oil mill effluent. Permeate pump and transmembrane pressure of the submerge membrane bioreactor system are the input variables. Six hyperparameters of the FFNN model including four numerical factors (neuron numbers, learning rate, momentum, and epoch numbers) and two categorical factors (training and activation function) are used in hyperparameter optimization. RBFNN includes two numerical factors such as a number of neurons and spreads. The conventional method (one-variable-at-a-time) is compared in terms of optimization processing time and the accuracy of the model. The result indicates that the optimal hyperparameters obtained by the proposed approach produce good accuracy with a smaller generalization error. The simulation results show an improvement of more than 65% of training performance, with less repetition and processing time. This proposed methodology can be utilized for any type of neural network application to find the optimum levels of different parameters.
The present study investigates the response of implantable rotary blood pump (IRBP)-assisted patients to exercise and head-up tilt (HUT), as well as the effect of alterations in the model parameter values on this response, using validated numerical models. Furthermore, we comparatively evaluate the performance of a number of previously proposed physiologically responsive controllers, including constant speed, constant flow pulsatility index (PI), constant average pressure difference between the aorta and the left atrium, constant average differential pump pressure, constant ratio between mean pump flow and pump flow pulsatility (ratioP I or linear Starling-like control), as well as constant left atrial pressure ( P l a ¯ ) control, with regard to their ability to increase cardiac output during exercise while maintaining circulatory stability upon HUT. Although native cardiac output increases automatically during exercise, increasing pump speed was able to further improve total cardiac output and reduce elevated filling pressures. At the same time, reduced venous return associated with upright posture was not shown to induce left ventricular (LV) suction. Although P l a ¯ control outperformed other control modes in its ability to increase cardiac output during exercise, it caused a fall in the mean arterial pressure upon HUT, which may cause postural hypotension or patient discomfort. To the contrary, maintaining constant average pressure difference between the aorta and the left atrium demonstrated superior performance in both exercise and HUT scenarios. Due to their strong dependence on the pump operating point, PI and ratioPI control performed poorly during exercise and HUT. Our simulation results also highlighted the importance of the baroreflex mechanism in determining the response of the IRBP-assisted patients to exercise and postural changes, where desensitized reflex response attenuated the percentage increase in cardiac output during exercise and substantially reduced the arterial pressure upon HUT.
The primary objective of this study is to distinguish between mobile bearing and fixed bearing posterior stabilized knee prostheses in the mechanics performance using the finite element simulation. Quantifying the relative mechanics attributes and survivorship between the mobile bearing and the fixed bearing prosthesis remains in investigation among researchers. In the present study, 3-dimensional computational model of a clinically used mobile bearing PS type knee prosthesis was utilized to develop a finite element and dynamic simulation model. Combination of displacement and force driven knee motion was adapted to simulate a flexion motion from 0° to 135° with neutral, 10°, and 20° internal tibial rotation to represent deep knee bending. Introduction of the secondary moving articulation in the mobile bearing knee prosthesis has been found to maintain relatively low shear stress during deep knee motion with tibial rotation.
Diabetes mellitus is a life threatening disease and scientists are doing their best to find a cost effective and permanent treatment of this malady. The recent trend is to control the disease by target base inhibiting of enzymes or proteins. Secreted frizzled-related protein 4 (SFRP4) is found to cause five times more risk of diabetes when expressed above average levels. This study was therefore designed to analyze the SFRP4 and to find its potential inhibitors. SFRP4 was analyzed by bio-informatics tools of sequence tool and structure tool. A total of three potential inhibitors of SFRP4 were found, namely cyclothiazide, clopamide and perindopril. These inhibitors showed significant interactions with SFRP4 as compared to other inhibitors as well as control (acetohexamide). The findings suggest the possible treatment of diabetes mellitus type 2 by inhibiting the SFRP4 using the inhibitors cyclothiazide, clopamide and perindopril.
The aim of this study was to review the capability of virtual reality simulators in the application of phacoemulsification cataract surgery training. Our review included the scientific publications on cataract surgery simulators that had been developed by different groups of researchers along with commercialized surgical training products, such as EYESI® and PhacoVision®. The review covers the simulation of the main cataract surgery procedures, i.e., corneal incision, capsulorrhexis, phacosculpting, and intraocular lens implantation in various virtual reality surgery simulators. Haptics realism and visual realism of the procedures are the main elements in imitating the actual surgical environment. The involvement of ophthalmology in research on virtual reality since the early 1990s has made a great impact on the development of surgical simulators. Most of the latest cataract surgery training systems are able to offer high fidelity in visual feedback and haptics feedback, but visual realism, such as the rotational movements of an eyeball with response to the force applied by surgical instruments, is still lacking in some of them. The assessment of the surgical tasks carried out on the simulators showed a significant difference in the performance before and after the training.
This paper presents Gene-Expression Programming (GEP), which is an extension to the genetic programming (GP) approach to predict the total bed material load for three Malaysian rivers. The GEP is employed without any restriction to an extensive database compiled from measurements in the Muda, Langat, and Kurau rivers. The GEP approach demonstrated a superior performance compared to other traditional sediment load methods. The coefficient of determination, R(2) (=0.97) and the mean square error, MSE (=0.057) of the GEP method are higher than those of the traditional method. The performance of the GEP method demonstrates its predictive capability and the possibility of the generalization of the model to nonlinear problems for river engineering applications.
Service architectures are necessary for providing value-added services in telecommunications networks, including those in medical institutions. Separation of service logic and control from the actual call switching is the main idea of these service architectures, examples include Intelligent Network (IN), Telecommunications Information Network Architectures (TINA), and Open Service Access (OSA). In the Distributed Service Architectures (DSA), instances of the same object type can be placed on different physical nodes. Hence, the network performance can be enhanced by introducing load balancing algorithms to efficiently distribute the traffic between object instances, such that the overall throughput and network performance can be optimised. In this paper, we propose a new load balancing algorithm called "Node Status Algorithm" for DSA infrastructure applicable to electronic-based medical institutions. The simulation results illustrate that this proposed algorithm is able to outperform the benchmark load balancing algorithms-Random Algorithm and Shortest Queue Algorithm, especially under medium and heavily loaded network conditions, which are typical of the increasing bandwidth utilization and processing requirements at paperless hospitals and in the telemedicine environment.