Balance Method Research Articles

Rational load balancing in collaborated cloud computing environments *

Abstract Optimum efficiency and fault tolerance are the most demanding and challenging issues in the domain of performance and reliability management in cloud computing environments. Optimized resource utilization is a key aspect for yielding efficiency in cloud platforms. Workload balancing through resource sharing is one of the key solutions for attaining performance in cloud environments. In addition, multiple cloud environments join hands to offer performance and fault tolerance through resource sharing. We provide a better and cloud-instances’ priority-based efficient load balancing method for collaborative cloud platforms. The recommended efficient load balancing method shortens the waiting timespan and overcomes the starvation problem of low priority instances in intercloud environments. A functional prototype of the recommended load balancing method was deployed on a physical cloud infrastructure which was setup with the OpenStack cloud software on the Fedora Linux operating system. The pilot project execution findings exhibit a reduction in the timespan borne by instances for executing load balancing. This technique is useful for attaining fault tolerance and efficient resource utilization in intracloud and intercloud environments.

Dynamic balancing method of power distribution and consumption tasks based on state iterative prediction and resource peaking shifting

In the context of the new power system, the widespread access to massive distributed new energy sources has led to the power distribution and consumption tasks characterized by multiple time scales, wide random distribution, and large demand differences, resulting in unpredictable resource peaks in the tasks computing resource demand curve. In view of this situation, a method of forecasting and dynamic balancing of computing resource demand for power distribution and consumption tasks based on state iteration was proposed: firstly, the tasks computing resource demand model was established under the analysis of the attributes and parameter demand of the power distribution and consumption tasks scenario. Secondly, on the basis of the short-term effectiveness prediction of the traditional Markov model, the first-order difference of the state is used for data training to track the state fluctuation, and the historical state and the predicted state are used for state iteration, so as to avoid the convergence of long-term prediction. Finally, a dynamic balancing model is established according to the time-scale characteristics of cyclical and non-cyclical tasks, and the optimal configuration of load imbalance is achieved through the identification and adjustment of historical data and burst data. The simulation results show that the improved Markov model based on first-order difference and state iteration has the short-term accuracy of the traditional model and the long-term traceability of data fluctuations. The dynamic balancing model can combine the characteristics of historical data and burst data to effectively reduce the imbalance of resource demand, and show good ability to cope with resource imbalance deviation.

Quantification of surface layer turbulence using sensible heat values from energy balance versus aerodynamic methods

Surface layer optical turbulence values in the form of the refractive index structure function C n 2 are often calculated from surface layer temperature, moisture, and wind characteristics and compared to measurements from sonic anemometers, differential temperature sensors, and imaging systems. A key derived component needed in the surface layer turbulence calculations is the sensible heat value. Typically, the sensible heat is calculated using the bulk aerodynamic method that assumes a certain surface roughness and a friction velocity that approximates the turbulence drag on temperature and moisture mixing from the change in the average surface layer vertical wind velocity. These assumptions/approximations generally only apply in free convection conditions. To obtain the sensible heat, a more robust method, which applies when free convection conditions are not occurring, is via an energy balance method such as the Bowen ratio method. The use of the Bowen ratio––the ratio of sensible heat flux to latent heat flux––allows a more direct assessment of the optical turbulence-driving surface layer sensible heat flux than do more traditional assessments of surface layer sensible heat flux. This study compares surface layer C n 2 values using sensible heat values from the bulk aerodynamic and energy balance methods to quantifications from sonic anemometers posted at different heights on a sensor tower. The research shows that the sensible heat obtained via the Bowen ratio method provides a simpler, more reliable, and more accurate way to calculate surface layer C n 2 values than what is required to make such calculations from bulk aerodynamic method-obtained sensible heat.

Dynamic Stability of the Euler Nanobeam Subjected to Inertial Moving Nanoparticles Based on the Nonlocal Strain Gradient Theory

This research studied the dynamic stability of the Euler-Bernoulli nanobeam considering the nonlocal strain gradient theory (NSGT) and surface effects. The nanobeam rests on the Pasternak foundation and a sequence of inertial nanoparticles passes above the nanobeam continuously at a fixed velocity. Surface effects have been utilized using the Gurtin-Murdoch theory. Final governing equations have been gathered implementing the energy method and Hamilton's principle alongside NSGT. Dynamic instability regions (DIRs) are drawn in the plane of mass-velocity coordinates of nanoparticles based on the incremental harmonic balance method (IHBM). A parametric study shows the effects of NSGT parameters and Pasternak foundation constants on the nanobeam’s DIRs. In addition, the results exhibit the importance of 2T-period DIRs in comparison to T-period ones. According to the results, the Winkler spring constant is more effective than the Pasternak shear constant on the DIR movement of nanobeam. So, a 4 times increase of Winkler and Pasternak constants results in 102% and 10% of DIR movement towards higher velocity regions, respectively. Furthermore, the effect of increasing nonlocal and material length scale parameters on the DIR movement are in the same order regarding the magnitude but opposite considering the motion direction. Unlike nonlocal parameter, an increase in material length scale parameter shifts the DIR to the more stable region.

MULTISENSORY METHODS AS TEACHERS' EFFORTS IN DEALING WITH DYSLEXIC CHILDREN IN ELEMENTARY SCHOOL: LITERATURE REVIEW

Dyslexic children of primary school age feel unable to keep up with learning, because they have different ways to learn. Teachers in school need to strategize a method for dyslexic children can follow the lesson well. This study aims to determine the efforts of teachers in dealing the dyslexic children with multisensory methods in elementary school. The research method used is integrative literature review with a five-stage framework, namely problem identification, literature search, data evaluation, data analysis, and presentation of findings. The electronic databases used are Sinta, ResearchGate, Google Scholar, Garuda, and Rama Repository, producing amount 38,649 articles over the past 10 years. Using search keywords, 7 journals were identified as meeting the inclusion criteria using the CASP (Critical Appraisal Skill Program) instrument. The result of this literature review is that multisensory methods are proven to improve the reading ability and learning quality of dyslexic children. Children experience an improvement in their ability to recognize words accurately although not significantly. Teachers need to provide remedial to overcome the difficulties and learning barriers they experience at school, and discuss with parents in order to children get a balanced teaching method between home and school.

Coprime Factor Model Reduction of Multidimensional Systems

    In this work, the right coprime factor for balancing and truncating unstable systems is extended to parameter-varying multidimensional systems employing recent works on coprime factor model reduction of one-dimensional uncertain systems. Since the balanced truncation method cannot be applied directly to unstable systems, state feedback gains should be computed and incorporated in order to stabilize the given system and to be able to apply the balanced truncation technique via defining the so-called stable coprime factor, as coprime factorization overcomes the stability condition required for model reduction. Parameter-dependent state feedback and parameter-dependent Gramians are considered in this work yielding less conservative techniques. In addition, the Gramians are defined as block diagonal matrices, which are partitioned according to the structure of the multidimensional systems. The application to a simulation example demonstrates the applicability and validity of the proposed reduction approach leading to small error bounds between the full and the reduced models.

Cascade Residual Multiscale Convolution and Mamba-Structured UNet for Advanced Brain Tumor Image Segmentation

In brain imaging segmentation, precise tumor delineation is crucial for diagnosis and treatment planning. Traditional approaches include convolutional neural networks (CNNs), which struggle with processing sequential data, and transformer models that face limitations in maintaining computational efficiency with large-scale data. This study introduces MambaBTS: a model that synergizes the strengths of CNNs and transformers, is inspired by the Mamba architecture, and integrates cascade residual multi-scale convolutional kernels. The model employs a mixed loss function that blends dice loss with cross-entropy to refine segmentation accuracy effectively. This novel approach reduces computational complexity, enhances the receptive field, and demonstrates superior performance for accurately segmenting brain tumors in MRI images. Experiments on the MICCAI BraTS 2019 dataset show that MambaBTS achieves dice coefficients of 0.8450 for the whole tumor (WT), 0.8606 for the tumor core (TC), and 0.7796 for the enhancing tumor (ET) and outperforms existing models in terms of accuracy, computational efficiency, and parameter efficiency. These results underscore the model’s potential to offer a balanced, efficient, and effective segmentation method, overcoming the constraints of existing models and promising significant improvements in clinical diagnostics and planning.

SMART: Spectral energy distributions Markov chain Analysis with Radiative Transfer models

Abstract In this paper we present the publicly available open-source spectral energy distribution (SED) fitting code SMART (Spectral energy distributions Markov chain Analysis with Radiative Transfer models). Implementing a Bayesian Markov chain Monte Carlo (MCMC) method, SMART fits the ultraviolet to millimetre SEDs of galaxies exclusively with radiative transfer models that currently constitute four types of pre-computed libraries, which describe the starburst, active galactic nucleus (AGN) torus, host galaxy and polar dust components. An important novelty of SMART is that, although it fits SEDs exclusively with radiative transfer models, it takes comparable time to popular energy balance methods to run. Here we describe the key features of SMART and test it by fitting the multi-wavelength SEDs of the 42 local ultraluminous infrared galaxies (ULIRGs) that constitute the HERschel Ultraluminous Infrared Galaxy Survey (HERUS) sample. The Spitzer spectroscopy data of the HERUS ULIRGs are included in the fitting at a spectral resolution, which is matched to that of the radiative transfer models. We also present other results that highlight the performance and versatility of SMART. SMART promises to be a useful tool for studying galaxy evolution in the James Webb Space Telescope (JWST) era. SMART is developed in Python and is available at https://github.com/ch-var/SMART.git.

Haque’s approach with mickens’ iteration method to find a modified analytical solution of nonlinear jerk oscillator containing displacement time velocity and time acceleration

AbstractHaque’s approach with Mickens’ iteration method has been used to obtain the modified analytical solutions of the nonlinear jerk oscillator, including displacement time velocity and acceleration. The jerk oscillator represents the features of chaotic behavior in numerous nonlinear phenomena, cosmological analysis, kinematical physics, pendulum analysis, etc., such as electrical circuits, laser physics, mechanical oscillators, damped harmonic oscillators, and biological systems. In this paper, we have used different harmonic terms for different iterative stages using the truncated Fourier series. A comparison is made between the iteration method, the improved harmonic balance method, and the homotopy perturbation method. After comparison, the suggested approach has been shown to be more precise, efficient, simple, and easy to use. Furthermore, there was remarkable accuracy in the comparison between the numerical results and the generated analytical solutions. For the third approximate period, the maximum percentage error is 0.014.

Error measures and solution artifacts of the harmonic balance method on the example of the softening Duffing oscillator

Error measures and solution artifacts of the harmonic balance method on the example of the softening Duffing oscillator

Discrepancy and estimates of groundwater recharge under different land use types on the Loess Plateau

Study regionThe Dongzhi tableland on the loess plateau, China. Study focusThis study investigates how various land use types on the Loess Plateau affect groundwater recharge using the chloride mass balance method (CMB). By integrating data from Cl–, NO3/Cl–, and stable isotopes (δ18O and δ2H), the research develops a new approach to estimate the average ion concentration rates in soil profiles. This methodology provides a nuanced understanding of how precipitation infiltration recharges groundwater under different land use scenarios and the impact of land use changes on these processes. New hydrological insights for the regionThe research findings highlight significant variations in groundwater recharge rates among different land uses. Grasslands show the highest recharge rate at 26 mm/yr, followed by forests at 23 mm/yr, while shrublands have the lowest at 5 mm/yr. Agricultural lands have moderate recharge rates ranging from 14 to 16 mm/yr. Transitioning from agricultural land to other land uses like shrublands and forests results in dramatic changes in recharge rates, with decreases and increases in recharge of 72% and 61%, respectively. These insights are crucial for developing strategic land-use planning to optimize groundwater recharge and enhance water security on the Loess Plateau. The study emphasizes the need for policies that balance hydrological science and land management to sustain both human livelihoods and ecological continuity.

Mahalanobis balancing: A multivariate perspective on approximate covariate balancing

AbstractIn the past decade, various exact balancing‐based weighting methods were introduced to the causal inference literature. It eliminates covariate imbalance by imposing balancing constraints in a certain optimization problem, which can nevertheless be infeasible when there is bad overlap between the covariate distributions in the treated and control groups or when the covariates are high dimensional. Recently, approximate balancing was proposed as an alternative balancing framework. It resolves the feasibility issue by using inequality moment constraints instead. However, it can be difficult to select the threshold parameters. Moreover, moment constraints may not fully capture the discrepancy of covariate distributions. In this paper, we propose Mahalanobis balancing to approximately balance covariate distributions from a multivariate perspective. We use a quadratic constraint to control overall imbalance with a single threshold parameter, which can be tuned by a simple selection procedure. We show that the dual problem of Mahalanobis balancing is an norm‐based regularized regression problem, and establish interesting connection to propensity score models. We derive asymptotic properties, discuss the high‐dimensional scenario, and make extensive numerical comparisons with existing balancing methods.

Heavy tails and probability density functions to any nonlinear order for the surface elevation in irregular seas

The probability density function (PDF) for the free surface elevation in an irregular sea has an integral formulation when based on the cumulant generating function. To leading order, the result is Gaussian, whereas nonlinear extensions have long been limited to Gram–Charlier series approximations. As shown recently by Fuhrman et al. (J. Fluid Mech., vol. 970, 2023, A38), however, the second-order integral can be represented exactly in closed form. The present work extends this further, enabling determination of this PDF to even higher orders. Towards this end, a new ordinary differential equation (ODE) governing the PDF is first derived. Asymptotic solutions in the limit of large surface elevation are then found, utilizing the method of dominant balance. These provide new analytical forms for the positive tail of the PDF beyond second order. These likewise clarify how high-order cumulants (involving statistical moments such as the kurtosis) govern the tail, which is shown to get heavier with each successive order. The asymptotic solutions are finally utilized to generate boundary conditions, such that the governing ODE may be solved numerically, enabling novel determination of the PDF at third and higher order. Successful comparisons with challenging data sets confirm accuracy. The methodology thus enables the PDF of the surface elevation to be determined numerically, and the asymptotic tail analytically, to any desired order. Results are worked out explicitly up to fifth order. The theoretical probability of extreme surface elevations (typical of rogue waves) may thus be assessed quantitatively for highly nonlinear irregular seas, requiring only relevant statistical quantities as input.

Application of Numerical Bifurcation Tracking Strategy To Blade-Tip/Casing Interactions In Aircraft Engines

Abstract Building on the regularized-Lanczos harmonic balance method, a previously developed frequency method, this paper presents a numerical bifurcation tracking strategy dedicated to high-dimensional nonlinear mechanical systems. In order to demonstrate its applicability to industrial applications, it is here used to obtain original results in the context of blade-tip/casing interactions in aircraft engines. The emphasis is put specifically on the tracking of predicted limit point bifurcations as key parameters-such as the amplitude of the aerodynamic forcing applied on the blade, the friction coefficient or the operating clearances-vary. Overall, presented results underline that the employed frequency method is well-suited to tackle the numerical challenges inherent to such computations on high-dimensional systems. For the mechanical system of interest, the industrial fan blade NASA rotor 67, it is shown that the application of the presented strategy yields an efficient way to identify isolated branches of solutions, which may be of critical importance from a design standpoint.

Tracking superharmonic resonances for nonlinear vibration of conservative and hysteretic single degree of freedom systems

Many modern engineering structures exhibit nonlinear vibration. Characterizing such vibrations efficiently is critical to optimizing designs for reliability and performance. For linear systems, steady-state vibration occurs only at the forcing frequencies. However, nonlinearities (e.g., contact, friction, large deformation, etc.) can result in nonlinear vibration behavior including superharmonics — responses at integer multiples of the forcing frequency. When the forcing frequency is near an integer fraction of the natural frequency, superharmonic resonance occurs, and the magnitude of the superharmonics can exceed that of the fundamental harmonic that is externally forced. Characterizing such superharmonic resonances is critical to improving engineering designs. The present work extends the concept of phase resonance nonlinear modes (PRNM) to be applicable to general nonlinearities, and is demonstrated for eight different nonlinear forces. The considered forces include stiffening, softening, contact, damping, and frictional nonlinearities that have not been previously considered with PRNM. The proposed variable phase resonance nonlinear modes (VPRNM) method can accurately track superharmonic resonances for hysteretic nonlinearities that exhibit amplitude dependent phase resonance conditions that cannot be captured by PRNM. The proposed method allows for characterization of superharmonic resonances without constructing a full frequency response curve at every force level with the harmonic balance method. Thus, the present method allows for analysis of potential failures due to large amplitudes near the superharmonic resonance with reduced computational cost. The consideration of single degree of freedom systems in the present paper provides insights into superharmonic resonances and a basis for understanding internal resonances for multiple degree of freedom systems.

Programmable logic controlled lithium-ion battery management system using passive balancing method

Advancements in electric vehicle technologies and the widespread adoption of electric vehicles have brought energy storage systems to the forefront. However, efficient and secure utilization of energy storage systems requires Battery Management Systems (BMS).BMSs are typically designed with power electronics, electronic cards, integrated circuits, and auxiliary hardware components. Nevertheless, BMSs designed with such microcontrollers can only control a limited number of battery cells and constrained current values. Furthermore, employing a separate controller for each battery pack exacerbates these issues.In this study, a Programmable Logic Controller (PLC) - based BMS proposal for lithium-ion batteries has been presented, aiming to address the challenges in existing BMSs. The developed system is a passive balancing BMS comprised of controller PLC modules and auxiliary hardware. The Ladder Diagram (LD) programming language was employed for programming the PLC.In the conducted research, the voltage levels of the cells comprising the battery pack were monitored, and a passive balancing method was employed to equalize the cell voltages. Passive balancing has been applied to cells with voltage values of 2.70 V, 2.40 V, and 2.80 V using the minimum reference voltage cell balancing method to equalize the voltage levels. The output voltage has been balanced according to the maximum reference charge voltage set at 6 V through the maximum reference charge voltage balancing method. Additionally, a cooling circuit was integrated into the system to safeguard the Battery Management System (BMS) against thermal hazards. The developed PLC controller and algorithm can effectively control multiple battery packs with a single controller and operate at higher current values. This advantage allows the PLC-controlled BMS to have a broader control capacity. The presented test results indicate the successful performance of the PLC-based BMS.

Analytical, numerical and experimental observation of isolated branches of periodic orbits in 1DOF mechanical parametric oscillator

The aim of this study is to investigate the dynamic properties of an existing experimental stand of 1DOF mechanical parametric oscillator, with a focus on approximate analytical solutions of the observed isolated branches of periodic orbits. The experimental stand involves a cart moving along a rolling guide, with the stiffness consisting of two components: a time-varying linear element created by a rotating rod with a rectangular cross-section and a nonlinear hardening stiffness caused by magnetic springs. It was demonstrated that a rolling bearing’s nonlinear resistance to motion consists of viscous damping and a second component analytically compared to dry friction. The study utilises multiple scales and harmonic balancing methods to provide analytical solutions. It is then successfully validated using numerical simulations and experimental data. The study investigates how dry friction influences oscillator response and applies the modified Mathieu–Duffing equation to represent the system’s dynamics. Different branches of periodic orbits are researched to determine their function in energy harvesting and mechanical system improvement. This research demonstrates the distinctions across analytical, numerical, and experimental methodologies, providing a comprehensive understanding of investigating intricate nonlinear systems.

Effects of inter-basin transfers on watershed hydrology and vegetation greening in a large inland river basin

The effects of inter-basin transfers (IBTs) on watershed hydrological balances and associated ecosystem processes remain poorly understood in arid regions because of data scarcity and the complexity of ecosystem responses to water management in many parts of the world. To fill this gap, the objective of this study was to quantify the effect of IBTs on watershed hydrological regimes and the associated vegetation dynamics. We conducted a case study on the Shiyang River Basin, a typical mountain-oasis-desert inland river basin in northwestern China, using water balance and wavelet analysis methods. Long-term (1980–2020) monitoring data from river discharge and groundwater tables were used to construct the water balances and quantify the periodicity of the surface water and groundwater. We observed that over 2.90 billion m3 of transferred water during 2003–2020 mitigated the declining trend in groundwater, resulting in a change in water storage trend from –91.9 mm/y to –53.7 mm/y. IBTs contributed approximately 230 % of the increase in observed river runoff, 21 %–60 % (42 % on average) of the increase in total water storage, and 1 %–32 % (12 % on average) of the evapotranspiration deficit (i.e., the portion of actual evapotranspiration beyond climate-driven evapotranspiration). IBTs also significantly altered the seasonal fluctuation and periodicity of river flows and groundwater. Increased water availability promoted vegetation recovery and resulted in multiscale resonance periodicities with vegetation, ranging from monthly to interannual scales. Our results indicate that IBTs markedly modified the water cycle, hydrological regimes, and ecosystem processes in the study basin. Thus, we call for long-term monitoring of the timing, frequency, and magnitude of ecohydrological modifications from IBTs to provide critical information for effective watershed management policies to achieve long-term sustainable development in water-stressed regions.

Vibration mitigation of spar-buoy floating wind turbines using a nonlinear energy sink

This work investigates the possibility of mitigating the wind-wave exerted vibration of floating offshore wind turbines using a nonlinear energy sink (NES). The vibration mitigation of floating wind turbines using passive linear control strategies have been intensively investigated, however, the effectiveness of the linear absorbers only works in a narrow frequency band, resulting in limited vibration suppression performance. The NES comprising a mass, a damper and a cubic stiffness element has the ability to mitigate vibrations in a broadband frequency range, which has been adopted in multiple engineering structures with significant performance benefits identified. In this paper, taking spar-buoy floating wind turbines as prototype structure, a simplified model with a NES mounted in nacelle subjected to wind and wave loads is presented. The harmonic balance method is then employed to analyse its nonlinear responses to the influence of NES parameters, together with the pseudo-arc-length method. The optimum NES parameter values are subsequently identified. Results show that the performance improvement can be up to 74.2% and 14.0%, respectively, comparing to that with no absorber and the TMD. Furthermore, to demonstrate the vibration suppression ability of the optimised NES in more realistic spar-buoy wind turbines, Orcaflex-the world’s leading package for the dynamic analysis of offshore systems, is adopted as the simulation tool. The spar-buoy wind turbine as well as the NES are established in Orcaflex and it is demonstrated that the performance benefits with the NES preserve under various loading conditions.

Theoretical analysis and potential engineering application of an energy harvester

The technique of energy harvesting, which captures the energy from ambient vibrations, has received increasing attention due to its potential to power low-powered wireless sensors. Therefore, it is important to reveal the nonlinear dynamic mechanism to design a high-performance energy harvester. This paper describes an energy harvester with the decoupled bistable potential (DBEH), in which the potential function can be controlled independently by the barrier height or the barrier width. The harmonic balance method (HBM) is used to obtain the theoretical solutions, and the Jacobian matrix is provided to determine their stability. Thirdly, this paper thoroughly discusses the influence of barrier height and width on output responses and the multi-solution range. Finally, numerical simulations observe the stochastic resonance (SR) phenomenon and the inverse SR phenomenon of the DBEH with Gaussian white noise injection. The SR phenomenon of the DBEH is applied to bearing fault diagnosis, effectively enhancing fault characteristics.