Linear Process Research Articles

Forecasting techniques based on the use of time series models for forecasting expenditures on social protection and social security

In the context of a military conflict, it is growing the number of people who are in difficult life circumstances and need state assistance. Therefore, the issue of forecasting spending on social protection and social security is becoming increasingly relevant. The aim of the paper is to consider modern methods of analyzing and forecasting time series and propose their application to determine the need for spending on social protection and social security. The article provides a brief overview of regression models, their advantages and features of use for analyzing and predicting nonlinear and linear processes described by time series of statistical indicators used in the population social protection system. The paper offers a combination of predictions that can be made based on locally linear and nonlinear models, such as threshold autoregression (TAR) and exponential autoregression (ExAR), which have known quality characteristics. This approach primarily concerns time series that contain data on structural changes in the analyzed processes. Using combined predictions, it is possible to estimate the contribution of each component for both different and selected time points using variable weights. To build forecasts, depending on the scenario of distribution of social protection and social security expenditures, it is proposed to use Bayes networks. Their advantages are flexibility, high quality of results, the possibility of structural and parametric optimization and adaptation to new data and conditions, support for quality assessment by appropriate sets of statistical criteria, which makes it possible to analyze thoroughly intermediate and final results. It helps to increase the adequacy of models and the high quality of the final result of their application.

Machine learning-based optimization of photogrammetric JRC accuracy

To improve the accuracy of photogrammetric joint roughness coefficient (JRC) estimation, this study proposes two optimization models based on ground sample distance (GSD), point density, and the root mean square error (RMSE) of checkpoints. First, an algorithm that automatically generates spatial positions for equipment based on the convergence strategy was developed, using principles of Structure from Motion and Multi-View Stereo (SfM-MVS) and the shooting parameter selection algorithm (SPSA). Second, a portable positioning plate containing ground control points and checkpoints was designed based on optical principles, and a moving camera capture strategy guided by SPSA was proposed. Combining SPSA, portable positioning plate, and moving camera capture strategy, a photogrammetric experiment for small-scale rock samples in the field was conducted, collecting 48 datasets with different shooting parameters. Subsequently, a dataset incorporating GSD, point density, RMSE, and three JRC estimation metrics was established, revealing their correlations and sensitivities. Using seven machine learning algorithms, optimization models for photogrammetric JRC accuracy were developed, with Linear Multidimensional Regression and Gaussian Process Regression models improving JRC accuracy by an average of 85.73%. Finally, the applicability and limitations of the newly proposed method were further discussed.

Enhanced Organics Removal Using 3D/GAC/O3 for N-Containing Organic Pharmaceutical Wastewater: Accounting for Improved Biodegradability and Optimization of Operating Parameters by Response Surface Methodology

Pharmaceutical industry effluents often contain high concentrations of refractory organic solvents, chemical oxygen demand (COD), and total dissolved solids (TDSs). These wastewaters, including N-containing organic solvents known for their persistence and toxicity, pose significant environmental challenges. The study evaluated the efficacy of 3D/Granular Activated Carbon (GAC)/O3 treatment compared to linear process additions when treating real pharmaceutical wastewater, and revealed a 2.73-fold enhancement in COD mineralization. The process primarily involves the direct oxidation of monoprotic organic acids found in real pharmaceutical effluents, such as acetic and formic acid, crucially influencing mineralization rates. Optimal conditions determined via the response surface methodology were 125 g/L GAC, 30 mA/cm2, and 75 mg/L O3, achieving high total organic carbon (TOC) and COD removal efficiencies of 87.19 ± 0.19% and 89.67 ± 0.32%, respectively (R2 > 0.9), during verification runs. Current density emerged as the key parameter for organic abatement, aligning with the emphasis on direct oxidation at the anode surface. This integrated approach enhances biodegradability (BOD5/COD) and reduces acute toxicity associated with persistent N-containing solvents, demonstrating promising applications in pharmaceutical wastewater treatment.

Nonlinear second order plus time delay model identification and nonlinear PID controller tuning based on extended linearization method

PID control systems based on the first order plus time delay model (FOPTD), which approximate the full system dynamics, are well-accepted for a wide range of linear processes. While such controllers can be applied to overdamped nonlinear processes, they often experience excessive overshoots and oscillations for general nonlinear processes. To overcome this limitation, we propose a novel method to design a nonlinear PID controller based on the second order plus time delay (SOPTD) model. The system nonlinearity requires parameter adjustments of the linearized model across operational ranges. Hence, in this work, it is handled by the extended linearization method (ELM), ensuring local stability under the assumptions of slow and small changes in operating points. Importantly, the model achieves global input-to-output stability even without the above constraints, provided there are no structural and parametric errors. The resulting nonlinear SOPTD model can describe changes in process gain and two time constants as the operation point varies. We demonstrate the applicability of our approach with a polymerization reactor simulation and liquid-level control experiments.

A mechanism-data driven resistance transfer algorithm for lithium-ion batteries and its application to thermal modeling

In this paper, a resistance transfer algorithm (RTA) is proposed to transfer a known battery's resistance data to a new battery, it saves the cost of testing required for thermal modeling. Firstly, the resistance linearization process is derived based on the Arrhenius equation, and a calibration algorithm for the resistance transfer from the reference battery to the target battery is presented. Then, taking the NCM622 battery (50 Ah) as the reference battery, the RTA is performed on an NCM622 battery (51 Ah) to verify the feasibility. Three schemes are compared to explore the appropriate test number of the target battery required for RTA. Subsequently, the RTA is applied to construct the thermal model of the target battery, and the simulation of the NCM622 (51 Ah) battery temperature rise is completed. Finally, RTA is utilized for resistance transfer and temperature rise simulation at different temperatures for four different batteries to further explore the universality. The verification results demonstrate that the proposed RTA can save a significant amount of resistance testing time and the thermal model based on RTA can supply precise temperature rise prediction. In the cost-effective 4-SOC scheme, the number of resistance test points can be reduced by 55 %, the maximum error of the transferred resistance remains within 0.1495 mΩ and the maximum error of the simulated temperature rise at three ambient temperatures stays below 1.727 °C.

Effect of Level and Frequency of Forward Masker on Auditory Brainstem Response.

Forward masking (FM) is characterized by the perception of a signal being reduced or wholly masked due to a preceding sound (masker) of the same or different frequencies that offers a challenge for the auditory system to resolve. Considering that the off-frequency masker is expected to undergo linear processing compared to the on-frequency masker at the signal place, it reflects the peripheral auditory systems' compressive response. Thus, the present study focused on employing FM electrophysiological analogous such as auditory brainstem responses (ABR) to the behavioral masking experiments to objectively measure the frequency and level of processing in the auditory system, from the periphery to the brainstem level. The study was an observational research on 21 female volunteers. ABR was obtained using a tone-on-tone FM paradigm for 1000- and 4000-Hz probe stimuli. An experiment used two forward maskers, on-frequency and off-frequency, with varying levels from 50 to 70 dB SPL. A progressive shift for Vth peak latency and reduction in response amplitude was observed in proportion to the increase of masker level for both the probe stimuli and the masking experiments. However, ABR responses in neither masking condition were observed to differ between 60 and 70 dB SPL. FM ABR experiments are an assessment tool for estimating frequency and level processing in the auditory system, providing good efficiency, reliability, and less subject bias compared to behavioral measures.

Geographic analysis of soil moisture recorded and estimated in Erbil governorate

Calculating of soil moisture and its monitoring is one of the important processes of water balance and sustainable agriculture. The intended goal of this study is to determine soil moisture values in Erbil Governorate and reveal the correlation coefficient and the degree of influence between its values with the elevation and total annual rainfall. The importance of the study lies In its discussion of the accuracy of extracting soil moisture values using satellite images, by comparing its results with the soil moisture values recorded in the governorate’s climate stations, the study reached a set of conclusions, the most important of which is: The results of using satellite images to estimate soil moisture are inaccurate. It is closer than guessing, and the results of applying the linear regression process indicated that there was a significant statistical relationship between the soil moisture values recorded with the two factors of elevation and the total annual rainfall, where the probability values were less than 0.01 and the values of the degree of influence between them reached 0.583 and 0.491 for each of them, respectively.‏

Estimating soil water retention curves over the entire saturation range: A thermal conductivity-based approach

The relationship between soil water content (θ) and suction (h, referring to the absolute value of pressure head), is described by the soil water retention curve (SWRC). Our earlier research (Fu et al. (2021, 2023a) [J. Hydrol.127171]; [J. Hydrol.129898]) recognized underlying correlations between SWRCs and soil thermal conductivity (λ) versus θ curves, and developed methodologies to ascertain the parameters of the van Genuchten (vG) equation using λ(θ) measurements, described by the Ghanbarian & Daigle (GD) equation, and basic soil characteristics. Limitations intrinsic to the van Genuchten equation restrict the GD-vG approach to generate precise estimates only in the wet and medium suction range, specifically h ranging from 0 to 150 mH2O. The validity of these approaches in the dry region remains uncertain. In this study, we associated the Peters-Durner-Iden (PDI) model parameters to those of the GD model. An initial examination was performed on the linearization processes needed to derive the hydraulic continuity water content (θhc) from the capillary water component as characterized by the PDI model and to choose the suction at oven dryness (h0) based on PDI model performance. Subsequently, two piecewise functions and two pedo-transfer functions were formulated to compute the PDI model parameters utilizing soil porosity, particle size distribution, and GD parameters, based on a calibration dataset comprising 25 different soils. The new GD-PDI approach was subsequently assessed with six independent soils and juxtaposed with the previous GD-vG approach. The GD-PDI approach outperformed the GD-vG approach, particularly within the dry range.

Score test for marks in Hawkes processes

AbstractA score statistic for detecting the impact of marks in a linear Hawkes self-exciting point process is proposed, with its asymptotic properties, finite sample performance, power properties using simulation and application to real data presented. A major advantage of the proposed inference procedure is that the Hawkes process can be fitted under the null hypothesis that marks do not impact the intensity process. Hence, for a given record of a point process, the intensity process is estimated once only and then assessed against any number of potential marks without refitting the joint likelihood each time. Marks can be multivariate and serially dependent. The score function for any given set of marks is easily constructed as the covariance of functions of future intensities fits the unmarked process with functions of the marks under assessment. The asymptotic distribution of the score statistic is a Chi-squared distribution, with degrees of freedom equal to the number of parameters required to specify the boost function. Model-based or nonparametric estimation of required features of the mark’s marginal moments and serial dependence can be used. Using sample moments of the marks in the test statistic construction does not impact the size and power properties.

Making of the marginal: gender in a new education city

ABSTRACT Global urban studies are undergoing a paradigm shift recognizing the link between urban and rural studies. In this sense, ‘agrarian urbanism’ has become the research focus, especially in the Global South. This paper analyses the changing social relations in Sonipat (Haryana, India) after it was developed as an ‘Education city’. The focus is gender relations with analysis under two categories: ‘locals’ and ‘outsiders’. While urbanization was thought of as a linear process where surplus production in the rural areas would naturally lead to cities, in the global south capitalist real estate-led development has meant that urbanization is often superimposed on existing rural societies, pushing them towards marginalization in favor of gated enclaved urban infrastructure. Employing qualitative interviews, I hypothesize that the private capital-driven urbanization in Sonipat not only geographically marginalizes the existing villages but also engenders dissonant experiences of local and outsider women. The fault lines between the two mean that interaction between them is defined by exploitation and mutual suspicion. Further, I argue that within this dichotomy, women bear the brunt of social control, restricted movement and potential violence.

Synchronized magnet-induced displacement detection in non-magnetic plates via smart materials near-field sensing

Accurate monitoring of small displacements in non-magnetic thin-walled plates is essential for assessing their manufacturing precision and vibrational characteristics. Optical techniques are limited by environmental disturbances and spatial constraints, while contact methods are compromised by mechanical forces and wear. A synchronized magnet-induced displacement detection method (SMDDM) using heteropolar permanent magnets (HPMs) and smart materials for non-magnetic plates is proposed. Supported by a magnetic-mechanical–electrical coupling model and a joint algorithm with dynamic linear extension and analytic hierarchy process (DLE-AHP), the prototype’s parameters are refined through experimental design, neural networks, and multi-objective optimization. Comprehensive tests show that SMDDM achieves an accuracy of 2 μm and a resolution of 1 μm, with smaller measurement errors observed in low-frequency, small-displacement tests. This validates the method’s effectiveness in multi-scale displacement measurement and vibration testing, highlighting its potential for in-situ monitoring in thin-plate applications.

Quantum Entanglement in Nonlinear Coupler with Raman Process

This paper examines the possible quantum entanglement generated in a coupler system consisting of two waveguides, where one waveguide is nonlinear and Raman-active, while the other waveguide only undergoes linear processes. The analytical-perturbative method is employed to investigate the production of entangled states in the given system. The Hillery-Zubairy criterion is employed to examine the possible quantum entanglement between the two fundamental pump modes propagating in both waveguides. We explore the generation of quantum entanglement under different initial conditions and critical design parameters. The simulation results suggest a continuous entanglement that remains until a particular distance of interaction is reached. As the linear coupling parameter increases, the relationship between the maximum reachable distance for entanglement and the degree of entanglement becomes more complex. The study reveals that entanglement experiences significant fluctuations when there is a substantial frequency mismatch between the modes.

Secure smart grid implementation with automatic data integrity attack location prediction and exalted energy theft detection

Smart grid systems use digital communication technology to efficiently monitor and manage electricity distribution. However, there is a need for improve the robustness of smart grid systems. Hence a novel “Secure Smart Grid Implementation with Automatic Data Integrity Attack Location Prediction and Exalted Energy Theft Detection” has been proposed. Current detection methods are not good at identifying data integrity attacks. So a novel Automatic Deterministic Attack Location Prediction Model detects data integrity attacks using a Stacked Watermarking BiGRU-based Deep Deterministic Q network, extracting system matrix and state time series variation. Moreover, Energy theft detection algorithms, which are intended to detect dishonest clients, provide erroneous findings because of linear interpolation processes and randomised near misses, which ignore important data points. Thus a novel Exalted Energy Theft Detector with Secure Encoding is introduced where Amortized Multicode GAN method secures smart grids by detecting energy theft and preventing firmware code modifications, utilising fractional multi-level quantum encoding to identify injection locations. As a result, the proposed model has an accuracy of 97.1%, recall of 96.25%, error rate is 1.36%, F1-score is 96.20%, sensitivity is 96.10%, specificity is 96.10%, MAPE is 0.48%, MSE is 0.0001 and RMSE is 0.017.

An analytic approach for nonlinear collisional fragmentation model arising in bubble column

The phenomenon of coagulation and breakage of particles plays a pivotal role in diverse fields. It aids in tracking the development of aerosols and granules in the pharmaceutical sector, coagulation or breakage of droplets in chemical engineering, understanding blood clotting mechanisms in biology, and facilitating cheese production through the action of enzymes within the dairy industry. A significant portion of research in this direction concentrates on coagulation or linear breakage processes. In the case of linear case, bubble particles break down due to inherent stresses or specific conditions of the breakage event. However, in many practical situations, particle division is primarily due to forces exerted during collisions between particles, necessitating an approach that accounts for nonlinear collisional breakage. Despite its critical role in a wide array of engineering and physical operations, the study of this nonlinear fragmentation phenomenon has not been extensively pursued. This article introduces an innovative semi-analytical method that leverages the beyond linear use of equation superposition function to address the nonlinear integro-partial differential model of collisional breakage population balance. This approach is versatile, allowing for the resolution of both linear/nonlinear equations while sidestepping the complexities associated with discretization of domain. To assess the precision of this method, we conduct a thorough convergence analysis. This process utilizes the principle of contractive mapping in the Banach space, a globally recognized strategy for verifying convergence. We explore a variety of kernel parameters associated with collisional kernels, alongside breakage and initial distribution functions, to derive novel iterative solutions. Comparing our findings with those obtained through the finite volume method regarding number density functions and their integral moments, we demonstrate the reliability and accuracy of our approach. The consistency and correctness of our method are further validated by depicting the errors between the exact and approximated solutions in graphical and tabular formats.

Система ввода цифровых предыскажений на основе обобщенной полиномиальной модели с памятью для GaN усилителей мощности

Modern power amplifiers based on GaN transistors face a number of problems related to their physical properties and operating conditions. The high output power of such power amplifiers is accompanied by significant nonlinear distortions, especially when operating in saturation mode. Amplifiers based on GaN transistors have pronounced «short» memory effects, which leads to the dependence of current distortions on previous signal states. At the same time, support for broadband signals requires high processing speeds and large computing resources. Classical digital pre-distortion methods do not always cope with the task of effectively compensating for real-time distortion for power amplifiers based on GaN transistors. These problems complicate the process of linearization of power amplifiers based on GaN transistors and require the development of new methods that can effectively compensate for non-linearities and memory effects without significantly increasing the cost and complexity of the system. The purpose of the work is to create and analyze the effectiveness of a digital pre-imaging system based on a generalized polynomial model with memory to improve the linearity and efficiency of power amplifiers based on GaN transistors in wireless communication systems. The paper presents the architecture of the digital preimage input system based on a generalized polynomial model with memory. The use of this model makes it possible to improve the efficiency of suppressing nonlinear distortions at the output of a power amplifier based on GaN transistors. Practical significance – the proposed architecture can be implemented on FPGAs, VLSI or SOC with a minimum amount of computing resources.

Threshold transient growth as a criterion for turbulent mean profiles

Lozano-Duran et al. (J. Fluid Mech., vol. 914, 2021, p. A8) have recently identified the ability of streamwise-averaged turbulent streak fields ${\mathcal {U}}(y,z,t)\hat {\boldsymbol {x}}$ in minimal channels to produce short-term transient growth as the key linear mechanism needed to sustain turbulence at $Re_{\tau }=180$ . Here, in an attempt to extend this result to larger domains and higher $Re_{\tau }$ , we model this streak transient growth as a two-stage linear process by first selecting the dominant streak structure expected to emerge over the eddy turnover time on the turbulent mean profile $U(y)\hat {\boldsymbol {x}}$ , and then examining the secondary growth on this (frozen) streak field ${\mathcal {U}}(y,z)\hat {\boldsymbol {x}}$ . Choosing the mean streak amplitude and eddy turnover time consistent with simulations captures the growth thresholds found by Lozano-Duran et al. (2021) for sustained turbulence. In a larger domain at $Re_{\tau }=180$ , the most energetic near-wall streaks observed in simulations are close to the predicted optimal streaks. This most energetic streak spacing, approaches the optimal streak at $Re_{\tau }=550$ where the secondary growth possible on each also comes together. A key prediction from the model is that the threshold transient growth required to sustain turbulence decreases with increasing $Re_{\tau }$ . More fundamentally, the work of Lozano-Duran et al. (2021) and our results suggest a subtle but significant revision of Malkus's (J. Fluid Mech., vol. 1, 1956, pp. 521–539) classic hypothesis concerning realisable turbulent mean profiles. The key property for a realisable turbulent mean profile could be the ability to generate sufficient short-term transient growth rather than dependence on its (long-term) linear stability characteristics, which was Malkus's original idea.

Multilinearity in ‘reading’: Bridging cultural psychology and autoethnography

Reading is not a linear process. In this commentary on Struppe-Schanda’s autoethnographic work, I explore the multilinear nature of reading from the experience of being able or unable to ‘read’ her work. This commentary attempts an autoethnography that emphasises the subjective feelings of the researcher and resists the traditional modalities of ‘science’. In determining the starting point for this commentary, whether as an autoethnographer or cultural psychologist, I discovered numerous potential directions for further development. Presented as a fictional conversation with my other self, this commentary delves into the implications of deliberative autoethnography, which seeks to explore subjectivity differently from mainstream evocative autoethnography.

Auxotonic training in muscle strength and power performance of professional young volleyball players

Auxotonic training unexplained on isotonic and isometric muscular contraction combination to develop strength and power gain. The study aimed to investigate muscle strength and power changes of professional young volleyball players on the auxotonic training effect. Volleyball players divided in AUT (auxotonic group: 16.32 y, 1.72 m, 63.63 kg) trained over 8 week and per week 2 day performing isotonic + isometric contraction combination periodization and IKT (isokinetic group: 16.23 y, 1.69 m, 60.22 kg) performed only isokinetic contraction periodization. The linear muscle strength and power processes of training periodization preferred for maximize performance. The strength changes of this study resulted on AUT and IKT for 1RM strength test and activforce isometric muscular strength adaptation test were similar, however, AUT obtained high improvement power performance (p < .05). Auxotonic training developed on strength and power for AUT. Additionally, showing of comparison between AUT and IKT concluded CMJ (90°) ES = 1.09 very large, vertical jump ES = 1.31 very large and handgrip right ES = 0.05 small effect size. Based on the results we obtained, current auxotonic contraction was determined on resistance training applied to young volleyball players effective in strength and power development. Auxotonic training performed on young volleyball players will bring a perspective to the coaches and athletes work in this field as a resistance training model. The auxotonic training strategy for long term performance changes on outcomes of using aimed potential muscle isotonic + isometric contraction combination may be effective maximize strength and power performance.

Patient mistreatment, emotional exhaustion and work-family conflict among nurses: a moderated mediation model of social sharing of negative work events and perceived organizational support

BackgroundNursing literature suggested that patient mistreatment has significant impacts on nurses’ emotions and job burnout. Yet, further research is needed to understand the underlying mechanism and the spillover effect on nurses’ families. Leveraging the goal progress theory, this study aimed to examine the association between patient mistreatment, nurses’ emotional exhaustion, and work-family conflict, as well as the mediating role of social sharing of negative work events and the moderating role of perceived organizational support.MethodsDuring the COVID-19 pandemic in China, a cross-sectional study was conducted with a sample of 1627 nurses from the Hematology Specialist Alliance of Chongqing from October to November 2022. Questionnaires were administered to measure patient mistreatment, perceived organizational support, social sharing of negative work events, emotional exhaustion, and work-family conflict. Hierarchical linear regression and conditional processes were used for statistical analyses.ResultsPatient mistreatment was positively associated with emotional exhaustion (β = 0.354, p < 0.001) and work-family conflict (β = 0.314, p < 0.001). Social sharing of negative work events played a partial mediating role in the relationship between patient mistreatment and emotional exhaustion (effect = 0.067, SE = 0.013), and work-family conflict (effect = 0.077, SE = 0.014). Moderated mediation analysis found that the mediation effect was stronger when the perceived organizational support was high.ConclusionOur findings reveal the amplifying effect of social sharing of negative work events on nurses’ emotional exhaustion and work-family conflict. Perceived organizational support strengthens the positive effect of patient mistreatment on the social sharing of negative work events, thus resulting in increased emotional exhaustion and work-family conflict. We also discuss practical implications, limitations, and directions for future research.

Land use transformations in the Brazilian Savanna: A decade of soil erosion and runoff measurements

Changes in land cover and land use (LULC) are one of the main drivers of erosion and runoff. How ever, most research has relied on short-term observations and only focused on one or two land cover types. We investigated the long-term trade-off between common agricultural land covers (sugarcane, pasture, and soybean), runoff, and soil loss rates. We compared these to native forest (wooded Cerrado) and bare soil. The field observations were done in 100 m2 experimental plots in Brazil maintained during the past 10 years. The paper provides three main contributions: (1) long-term runoff and soil loss rates of plots under different LULCs, (2) comparison of runoff, soil loss, and pedological characteristics between plots constructed 10 years apart, and (3) analysis of the trade-off between different LULCs. When ranking land covers based on runoff and soil loss rates, there is a shift in ranking positions, making it difficult to determine which one is more environmentally harmful. However, it is evident that whatever agricultural practice is used, there is a significant impact when compared to native forest. For example, the area converted to pasture resulted in almost 20 times higher runoff, while conversion to sugarcane resulted in 5 times higher soil loss. Not only land cover plays a major influencing factor, but also weathering exposing time. Areas under the same land cover and environmental conditions had different rates of soil loss and runoff due to long-term exposure effects such as soil crusting. Our findings have high relevance for the hydrological and agricultural community by demonstrating (i) the magnitude of trade-off in terms of soil loss and runoff due to land cover changes and (ii) that soil loss should not be assumed to be a linear process over time, as it is commonly assumed.