Insensitive Zone Research Articles

Characterizing Ecological Sensitivity of Yangtze River Delta Urban Agglomeration in China

Ecological sensitivity, as one of the most important indicators to evaluate regional environmental issues, holds significant implications for ecological governance and management in the related area. This study utilized remote sensing imagery of Landsat Thematic Mapper (TM) from the Yangtze River Delta (YRD) in 2014 and 2018, combined with field surveys and socio-economic data. Considering the local ecological and environmental conditions in the region, nine factors related to seven aspects, soil erosion, topography, humidity, habitat, water environment, human interference, and climate, were selected to create an ecological sensitivity evaluation framework for the YRD urban agglomeration. The coefficient of variation method was applied to determine factor weights, while the zonal statistics and spatial overlay methods were used for a comprehensive analysis of ecological sensitivity in a geographic information system (GIS). The YRD urban agglomeration was categorized into five ecological sensitivity levels: extremely sensitive, highly sensitive, moderately sensitive, slightly sensitive, and insensitive. The analysis results revealed spatial variations in the distribution of ecological sensitivity across the YRD urban agglomeration, with the overall ecological sensitivity level being slightly sensitive. The proportions of the total area occupied by extremely sensitive, highly sensitive, moderately sensitive, slightly sensitive, and insensitive zones were 14.30%, 12.02%, 25.29%, 30.34%, and 18.05% in 2014, and 14.30%, 24.01%, 16.33%, 27.32%, and 18.05%, respectively, in 2018. Based on these results, relevant ecological vulnerabilities for the YRD urban agglomeration were discussed.

ANALYSIS OF METHODS OF CHANGING VOLUMES OF ELECTRICITY GENERATION AT SOLAR POWER PLANTS

The article examines the methods of changing electricity generation schedules at solar power plants when operating under the central regulator of the power system. An analysis of the existing regulation methods was carried out, and a new method of controlling the generation of solar power plants under the central regulator of the power system was proposed.
 Background. The increase in the share of solar electricity generation in the energy systems of the countries of the world leads to the need to control and manage the process of electricity production to increase the stability and sustainability of the energy system. A significant price for compensation of imbalances in the energy system is included in the tariffs, which affects the end consumers of electricity.
 Objective: increasing the adequacy of the results of the distribution of deficit frequency containment reserves, frequency restoration reserves to compensate for imbalances that arise when generation is changed at solar power plants. Reducing the cost of compensation for imbalances that occur when changing generation at solar power plants. To solve the goal, it is necessary to analyze the existing methods of compensating power system imbalances that arise as a result of changes in generation at solar power plants and to propose a new technical and mathematical solution for the distribution of deficit reserves of support and frequency restoration.
 Methods: the social engineering approach of forecasting and modeling was used to analyze the processes affecting the method of controlling the generation schedule of the solar power plant.
 Results. A new mathematical and technical solution for compensating the imbalance in the power system in the event of a rapid change in the electricity generation schedule at solar power plants is proposed. For the first time, the given task was solved using a new technical and mathematical solution. Such a technical and mathematical solution can be widely used in the management of the electricity generation schedule at solar power plants in many system operators in different countries of the world, where there is a problem of insufficient for frequency containment and restoration reserves, and the amount of solar electricity generation has a significant share in the total amount of electricity generation energy.
 Conclusions. Existing methods of compensating power system imbalances arising as a result of changes in generation at solar power plants are analyzed and a new technical and mathematical solution for the distribution of deficit reserves of frequency containment reserves and frequency restoration reserves is proposed. The proposed technical and mathematical solution makes it possible to predict an event during which there will be a change in the level of electric energy generation at solar power plants, to transmit information to the central regulator of the energy system, which in turn will give a command to change the schedule of electric energy generation in advance within the insensitivity zone, which will lead to the activation of the frequency restoration reserves and will allow to compensate the existing imbalance at the expense of cheaper reserves and not to activate the frequency containment reserves. Such a mathematical and technical solution will make it possible to significantly increase the stability of the energy system against emerging imbalances and make their compensation cheaper, which in general has a positive effect on the energy security of the state.

A novel support vector machine with generalized pinball loss for uncertain data classification

In real‐world problems, data suffer from measurement errors, data staleness, and repeated measurements, which make data uncertain. To consider the uncertainty of data, the concept of giving each data feature as a multidimensional Gaussian distribution has been utilized. In 2021, support vector machines with an insensitive zone pinball loss (UPinSVMs) for uncertain data classification was proposed, where is a positive number. The UPinSVMs bring noise insensitivity, stability for resampling, and increased model sparsity. However, the value of is known to be specified. In order to improve the performance, we combine the generalized pinball loss (( ‐Mod‐Pin‐SVM) into the uncertain classification, term as UGPinSVMs, where are two positive numbers. The generalized pinball loss is an optimal insensitive zone pinball loss and is an extension of existing loss functions that also addresses the issues of noise insensitivity and resampling instability. We solve the primal quadratic programming problems by transforming individuals into unconstrained optimization using an efficient stochastic gradient descent algorithm. More specially, we have introduced verified theorems that are related to our approaches and investigated scatter minimization. The results from several benchmark datasets show that our model outperforms the existing classifier in terms of accuracy and statistical analysis. Furthermore, the application of our framework to the crop recommendation dataset is also examined.

Distributed Strain Measurements Based on Rayleigh Scattering in the Presence of Fiber Bragg Gratings in an Optical Fiber

This paper addresses the challenge of strain measurement using distributed fiber-optic sensors based on Rayleigh scattering in the presence of fiber Bragg gratings (FBGs) with a reflectivity level of 70% within the optical fiber. The reflectivity of such FBGs complicates distributed strain measurements that rely on the cross-correlation algorithm. The cases where the scanning ranges of a backscatter reflectometer include the resonant wavelengths of the FBGs and those beyond their limits, resulting in either a complete absence of a useful signal or the emergence of insensitive zones near the FBGs, are considered. An approach is proposed that employs a windowed Fourier transform with Hann window function for signal processing. This method effectively eliminates insensitive zones in distributed strain measurements based on Rayleigh scattering.

Computer simulation of the microprocessor liquid level automatic control system

Today, automation occupies a leading place in most branches of modern society, in almost all types of industry and economy. One of the main tasks of designing modern automatic control systems is the realization of high indicators in terms of accuracy, control range, and speed, taking into account the features of the control object itself. The purpose of the work –researching the microprocessor system of automatic control of the liquid level by means of computer modeling, taking into account the transport delay, the nonlinearity of the control characteristic of the pump and the presence of an insensitivity zone. To achieve the goal, the following tasks were solved: a computer model of a closed microprocessor system for automatic control of the liquid level wasdeveloped, taking into account the nonlinearity of the characteristics of the pumping unit and transport delay; a number of experiments were conducted to find the values of PI-regulator coefficients that bring the transient process of a real system with a transport delay as close as possible to the transient process of a system in which there is no transport delay; search for optimal values of the coefficients of the PI controller by minimizing the functional of the root mean square deviation of the real from the specified transient processes. As a result of research, it was established that the minimum points of the functional for the control signal and the liquid level do not coincide. At the same time, at the minimum point of the functional for the liquid level, a larger amplitude of oscillations of the control signal is observed, and at the minimum point of the functional for the control signal –an increase in the duration of the transient process. Therefore, the final decision should be based on the selection of priorities or optimal ratios between the speed and wear of the equipment, which is due tothe instability of the control signal.

Negative corona discharge and flow characteristics of a two-stage needle-to-ring configuration ionic wind pump for temperature and relative humidity

Ionic wind pumps have the advantages of a compact structure, no moving parts, and low power consumption. The effects of temperature and humidity on the current–voltage and flow characteristics of ionic wind pumps are still unclear. This study experimentally investigates the effects of temperature and humidity on the breakdown voltage, discharge current, and velocity of a two-stage needle-to-ring type ionic wind pump with a negative corona discharge. It is found that the coupling effects of temperature, humidity, and water vapor condensation determine the current–voltage and flow characteristics of ionic wind pumps. The temperature and vapor condensation effects can enhance the discharge current and outlet velocity and weaken the breakdown voltage. However, the humidity effect can weaken the discharge current and outlet velocity, and improve the breakdown voltage. Moreover, there exists a competition between humidity and vapor condensation effects on breakdown voltage, current, and velocity. The increase in temperature intensifies the humidity effect and weakens the condensation effect; thus, the temperature changes the contribution of humidity and condensation effects in the competition. A working spectrum of ionic wind is provided in the temperature and humidity coupling environment, including a vapor condensation-controlled zone, a sensitive humidity zone for breakdown voltage and velocity, and an insensitive humidity zone for breakdown voltage and velocity. The spectrum can provide theoretical guidance for designing ionic wind pumps at different temperatures and humidity.

EXPERIMENTAL STUDIES OF INFORMATION SIGNAL-TO-RESISTANCE CONVERTER FOR AUTOMATIC CONTROL SYSTEM

Potentiometric sensors are widely used in the construction of automatic and automated process control systems. In potentiometric sensors, resistance is the output signal and its magnitudes depend on the magnitude of the input signal. voltage, current, digital code, angle of rotation, displacement or other signal is usually used as the input signal. In practice, the task of simulating of the signal which coming from the built-in potentiometric sensor is often appeared. An additional potentiometric sensor can be used to simulate the signal of the built-in sensor that allows setting the required resistance magnitude by changing any external parameter.
 The model of the voltage-to-resistance converter is made. This model allows simulating the potentiometric state sensor of the controlled system. The experimental determination of its transfer characteristic at different ambient temperatures is carried out. This model is based on a two-channel conversion circuit, which includes a source of optical radiation and two photoresistors optically connected to it. One of photoresistors is connected to a current stabilizer, while the voltage on it is analyzed by a tracking circuit that changes the brightness of the optical radiation source according to the magnitude of the control voltage. The transfer characteristic of the converter in the initial section has an insensitivity zone, following by a rectilinear section. Within the insensitivity zone, a change in input voltage does not change the output resistance. The magnitude of the insensitivity zone is determined by the maximum voltage on the incandescent lamp that determines its brightness, as well as the minimum possible resistance of the using illuminated photoresistor. Within the rectilinear section, the output resistance of the converter is linearly related to the magnitude of the input voltage. The conversion error does not exceed 0.6 % at an ambient temperature of 20° C. When the temperature decreases to -20° С, the conversion error increases to 7 %, which is due to differences in temperature errors of the photoresistors using in the model.

An investigative sensitivity study of Ovako working posture analyzing system (OWAS)

The purpose of this study is to investigate the sensitivity of the Ovako working posture analyzing system. This paper also focuses on the identification of insensitive and highly sensitive posture zones. The OWAS sensitivity analysis, together with the ordinal regression analysis, offers deeper insights into the methodology for assessing posture. A full factorial design was used to account for all possible combinations of body members. To assess the sensitivity, one parameter of the body part was changed while other parameters were left unchanged to understand its effect on the output score. Combinations of postures in which no change was observed and corresponding ranges were noted. Posture ratings with sudden jumps were also noted. Ordinal regression analysis was performed to identify the body variable with the greatest impact and its weight in estimating the OWAS action category. Ergonomic practitioners can be made aware of insensitive and sensitive zones when assessing posture.

Identification of a nonlinear system with an insensitivity zone of an elastic element, with dry and viscous friction

Identification of a nonlinear system with an insensitivity zone of an elastic element, with dry and viscous friction

On the phase-field modeling of fully coupled chemo-mechanical deterioration and fracture in calcium leached cementitious solids

As it is extremely difficult, if not impossible, to carry out fully coupled chemo-mechanical tests lasting several hundreds of years, a reliable modeling approach is thus indispensable in assessing the integrity, durability and safety of infrastructures under aggressive aqueous environments. In this work, we propose a multi-physical phase-field model for fully coupled chemo-mechanical deterioration and fracture in calcium leached cementitious solids, aiming to predict the long-term behavior of concretes structures. The chemical sub-problem is built upon the mass conservation of calcium ions in pore solution, representing the diffusion–dissolution equilibrium of the leached system. Regarding the mechanical process, the length scale insensitive phase-field cohesive zone model is substantially extended with the calcium dissolution induced deterioration of mechanical properties properly accounted for by a porosity-dependent damage variable. Vice versa, during the leaching process both the transport diffusivity of calcium ions and the dissolution rate of the skeleton are promoted with the crack phase-field incorporated into the chemical sub-problem. The resulting inter-field fully coupled model is validated by several representative numerical examples. Both the sequentially and fully coupled chemo-mechanical problems are studied to verify the detrimental effects of simultaneous chemical attack and mechanical loading on the structural behavior. Based on the fully coupled analysis, an extra example is presented to demonstrate the promising prospects of the proposed model in service-life predictions of concrete structures under concurrent mechanical loading and aggressive environmental attacks.

Phase-field modeling of electromechanical fracture in piezoelectric solids: Analytical results and numerical simulations

The optimal design, reliable manufacture and durable utilization of electromechanical systems demand objective modeling of failure under coupled electric field and mechanical actions. This is still a challenging and largely an open issue despite the large volumes of contributions from the discontinuous approach and the phase-field community for brittle fracture. In this work we propose a length scale insensitive phase-field cohesive zone model (PF-CZM) for electromechanical fracture in linear piezoelectric solids, overcoming all the issues of mesh dependence, crack tracking complexity, length scale sensitivity and crack nucleation inconsistency. More specifically, in the electromechanically coupled phase-field constitutive relations, the evolution law for the crack phase-field is established from the geometric regularization of sharp cracks and the energetic criterion in global form. In order to capture the unsymmetric mechanical and electrical fracture behavior, the mechanical energy release rate contributed from the positive cone of the effective stress in energy norm is employed as the crack driving force, resulting in a hybrid formulation. With a set of phase-field characteristic functions optimal for cohesive fracture, the critical stress upon crack nucleation and the post-peak softening regime are derived in close-form for the first time, and the experimentally observed effects of the electric field on the fracture load are predicted qualitatively. The proposed electromechanical PF-CZM is numerically implemented in the multi-field finite element method and applied to several representative examples. In all cases, as those for purely mechanical problems, the predicted crack patterns and fracture loads are insensitive to the phase-field length scale and the experimental results are well reproduced. In particular, the effect of electric field on the deflection of crack paths can be captured. These merits make the proposed PF-CZM promising in the modeling of electromechanical fracture in piezoelectric solids.

Study of association between OWAS, REBA and RULA with perceived exertion rating for establishing applicability

The paper highlights the need to determine applicability of various ergonomic assessment methods. The methods such as Ovako working posture analysing system (OWAS), Rapid entire body assessment (REBA) and Rapid upper limb assessment (RULA) were used for the evaluation. The current research is carried out in three phases. The first phase involves assessing 25 postures at four different load levels (100 postures) to confirm the existence of variation in outcome of assessment. In the second phase, 24 male participants were selected to simulate the selected set of 100 postures-load combination in the laboratory and their perceived exertion rating was noted. Phase three includes the result’s validation. ANOVA was carried out to identify significant factors. It may be concluded from the study that OWAS may be better suited to evaluate risk if the load is less than 5 kg. Similarly, REBA and RULA may be better suited for the load range 5 kg − 10 kg and load greater than 10 kg respectively. It is observed that outcome of assessment methods is insensitive to some posture cases. So, there is a need to identify all the insensitive zones within a method that has a considerable difference in perceived exertion.

Identification of indifferent posture zones in RULA by sensitivity analysis

The paper aims primarily to study the sensitivity of Rapid upper limb assessment (RULA) and identification of insensitive and sensitive posture zones. The sensitivity analysis of RULA along with the ordinal regression analysis offer deeper insights into the methodology used for the assessment of posture. Full factorial design was divided into parts using a forward approach to access the sensitivity. One parameter was changed while keeping other parameters fixed to understand its effect on the output score. Combinations of posture where no change was observed and corresponding ranges were noted. Posture scores were also noted involving sudden jumps. Ordinal regression analysis was performed to identify the most influencing body variable and its weight in estimating the grand RULA score. The justification of the RULA methodology available in the existing literature is very limited. This paper demonstrates the need for understanding of RULA method among the researchers. With this paper, ergonomic practitioners can be made aware of insensitive and sensitive zones in posture assessment.

Identification of a nonlinear system with an insensitivity zone of an elastic element

The article considers the problem of identifying nonlinear dynamic systems using experimental data obtained by applying test signals to the system. The goal is to determine the unknown parameters of the (frequency) transfer function of a nonlinear dynamical system with a deadband of an elastic element from experimental frequency hodographs. It was assumed that the type of transfer function of the identified system is known. It was assumed that in obtaining the frequency characteristics of a real system hindrances intervenes with the experiment, as a result of which the points of the experimentally obtained hodograph are randomly shifted. The search for a solution to the identification problem was carried out in the class of hodographs specified by the system model. The view of transfer function of the model is the same as the view of transfer function of the identifiable system. The search for unknown parameters of the transfer function of the system model was carried out by minimizing a given criterion (measure) of proximity of the experimentally obtained hodograph of the system and the hodograph of the system model over the entire set of experimental points. The solution of the problem of identifying a nonlinear dynamical system using a frequency hodograph is reduced to solving a system of equations that is linear with respect to unknown parameters of the transfer function of the model of system. For a nonlinear system with an insensitivity zone of an elastic element, a program has been developed for simulating the process of obtaining pseudo-experimental data containing random errors and determining the parameters of this system. A computational experiment was conducted to estimate the error with which the proposed algorithm determines the values of the parameters of this system. An illustrative computational experiment has shown that the error in determining the values of the system parameters is comparable with the measurement error range of the experimental values (counts) of the hodograph of this system.

On pairing Huber support vector regression

In this paper, a novel and efficient pairing support vector regression learning method using ε−insensitive Huber loss function (PHSVR) is proposed where the ε−insensitive zone having flexible shape is determined by tightly fitting the training samples. Our approach leads to solving a pair of unconstrained minimization problems in primal and the solutions are obtained by two algorithms: a functional iterative (FPHSVR) and Newton iterative (NPHSVR) algorithms. The finite termination of the Newton method to its global minimum solution is proved. The significant advantages of the proposed method are the robustness, generalization ability and learning speed. Experiments performed on a series of synthetic data sets, polluted by different types of noise including heteroscedastic noise and outliers, and on real-world benchmark data sets confirm the effectiveness and superiority of the proposed method.

Investigative study and sensitivity analysis of Rapid Entire Body Assessment (REBA)

The paper aims primarily to study the sensitivity of Rapid entire body assessment (REBA) and identification of insensitive and sensitive posture zones. The investigative study, and sensitivity analysis of REBA offer deeper insights into the methodology used for the assessment of posture. Full factorial design is divided into parts using a forward approach to access the sensitivity. One parameter is varied keeping other parameters constant to understand its effect on the output score. Combinations of posture where no change was observed were identified. Posture scores were also noted involving sudden jumps. Regression analysis was performed to identify relative importance or weightage of the body and other variables in estimating the final REBA score. The justification of the REBA methodology available in the existing literature is very limited. This paper also demonstrates the need for understanding of REBA method among the researchers. With this paper, ergonomic practitioners can be made aware of insensitive and sensitive zones in posture assessment. OriginalityThis is the first paper that primarily aims to establish the sensitivity of REBA and identifying insensitive postures or problems in REBA assessment. Few research gaps are identified.

A new asymmetric [formula omitted]-insensitive pinball loss function based support vector quantile regression model

In this paper, we propose a novel asymmetric ϵ-insensitive pinball loss function for quantile estimation. There exists some pinball loss functions which attempt to incorporate the ϵ-insensitive zone approach in it but, they fail to extend the ϵ-insensitive approach for quantile estimation in true sense. The proposed asymmetric ϵ-insensitive pinball loss function can make an asymmetric ϵ- insensitive zone of fixed width around the data and divide it using τ value for the estimation of the τth quantile. The use of the proposed asymmetric ϵ-insensitive pinball loss function in Support Vector Quantile Regression (SVQR) model improves its prediction ability significantly. It also brings the sparsity back in SVQR model. Further, the numerical results obtained by several experiments carried on simulated and real world datasets empirically show the efficacy of the proposed ‘ϵ-Support Vector Quantile Regression’ (ϵ-SVQR) model over other existing SVQR models.

Prediction of the insensitivity zone in the design of the feed drive CNC lathe

The processing on CNC machines of parts of a complex profile with multipass shaping schemes is accompanied by multiple changes in the direction of movement of the working bodies (reverse) during the cutting process and at idle running. When reverse, loss of information is possible due to the presence of gaps in the chain of feed drive and elastic deformations determined by constant loads overcome by the drive. Permanent loads consist of cutting forces and friction in the feed drive chain. Information loss is defined as a position insensitive zone at a position. To determine the insensitive zone, a technique is proposed that takes into account the differential accounting of friction losses in the mechanical feed drive chain. To estimate the elastic deformations in the drive chain, design schemes are proposed and analytical dependencies obtained. Differentiated consideration of friction in determining the insensitive zone allows you to outline the main ways to improve feed drives. It is shown that the magnitude of the preload on the thrust bearings and the tensile forces of the lead screw during assembly do not have a significant effect on the size of the insensitive zone. Even less impact on the dead zone has a preload change in the transfer screw-nut rolling. It was determined that the main ways to reduce the insensitivity zone is to increase the rigidity of the screw-and-nut rolling transmission anchor to the machine carriage and reduce friction in the guides. In addition, an analysis of the layout decisions of the lead screw assembly (one-sided and two-sided termination) according to the insensitive zone criterion showed that the use of one-sided termination of the lead screw is more rational.

Sparse Twin Extreme Learning Machine With $\varepsilon$ -Insensitive Zone Pinball Loss

Twin extreme learning machine (TELM) based on the hinge-loss function shows great potential for pattern classification. However, the hinge loss is related to the shortest distance between sets and the corresponding classifier is hence sensitive to noise and unstable for resampling. In contrast, the $\varepsilon $ -insensitive zone pinball loss is related to the quantile distance therefore is not sensitive to noise, and the resulting solution is sparse. To improve the performance of TELM, we propose a novel TELM learning framework by introducing $\varepsilon $ -insensitive zone pinball loss function into TELM. Compared to TELM with hinge loss, the proposed SPTELM has the same computational complexity and is insensitive to noise, resampling stability and maintaining the sparsity of the solution. Further, we theoretically analyzed the sparsity, noise insensitivity and time complexity of SPTELM. Experimental results on multiple datasets demonstrate the noise insensitive, retains sparsity of the proposed method.

Generalized Pinball Loss SVMs

Abstract Support Vector Machine (SVM) is a well-known efficient classification technique which appropriately trade-offs between the training error and the generalization ability of the classifier. But SVM’s are known to be sensitive towards noise and not stable with respect to re-sampling. Recently, Huang et al. (2014) proposed a novel SVM formulation with pinball loss function (Pin-SVM) model to handle noise sensitivity and instability to re-sampling. The Pin-SVM model in its pure form loses sparsity and therefore Huang et al. (2014) proposed a new pinball SVM model termed as ϵ-insensitive zone Pin-SVM. The ϵ-insensitive zone Pin-SVM formulation requires the value of ϵ to be pre-specified. Taking motivation from these developments, we propose a modified (ϵ1, ϵ2)-insensitive zone Pin-SVM ((ϵ1, ϵ2)-Mod-Pin-SVM) model in which the asymmetric spread of insensitive zone is optimized and therefore it is data-driven. An interesting feature of our proposed (ϵ1, ϵ2)-Mod-Pin-SVM model is that it appropriately trade-offs the generalization ability, the sparsity as well as the noise insensitivity. The (ϵ1, ϵ2)-Mod-Pin-SVM model is very general and subsumes a number of popular SVM type models. Its relation with Minimal Complexity Machine (MCM) introduced by Jayadeva (2015) is interesting and novel. The experimental results on several benchmark datasets prove the effectiveness of our proposed (ϵ1, ϵ2)-Mod-Pin-SVM formulation to that of other state-of-the-art classification algorithms.