Set Of Values Research Articles

On the problem of controlling a second-order nonlinear system by means of discrete control under disturbance

The problem of bringing a trajectory to a neighborhood of zero under disturbance is considered in terms of a differential pursuit game. The dynamics are described by a nonlinear autonomous system of second-order differential equations. The set of values of the pursuer's controls is finite, and that of the evader (disturbance) is compact. The goal of the control, that is, the goal of the pursuer, is to bring, within a finite time, the trajectory to any predetermined neighborhood of zero, regardless of the actions of the disturbance. To construct the control, the pursuer knows only the phase coordinates and the value of the velocity at some discrete moments of time and the choice of the disturbance control is unknown. Conditions are obtained for the existence of a set of initial positions, from each point of which a capture occurs in the specified sense. Moreover, this set contains a certain neighborhood of zero. The winning control is constructed constructively and has an additional property specified in the theorem. In addition, an estimate of the time required to bring the speed from one given point to the neighborhood of another given point under disturbance conditions was obtained.

Видовое разнообразие делинквентных молодежных субкультур в современной России: опыт теоретического исследования

Social disorganization triggers the development of subcultures, both positive and negative. As part of innovative adaptation, a person or a group may update certain sets of values, thus offering an alternative solution to some existing contradictions. Destructive socio-cultural associations, on the contrary, revise and oppose the generally recognized and accepted values, which leads to protest activity and what Peter Berger defined as anti-societies. The article describes the current diversity of delinquent youth subcultures in Russia and their development. The author designed a typology based on sociological interpretation, affiliations, and risks: 1) subcultures with career prospects; 2) subcultures of antisocial leisure activities; 3) subcultures that imitate certain totalitarian organizations; 4) subcultures of escapism; 5) subcultures of gender orientation; 6) street subcultures; 7) school-shooting subcultures. This classification takes into account those aspects of social life that deserve special scientific attention. Each subcultural community requires a special interdisciplinary approach that would consider its socio-cultural and legal adaptation mechanisms, causes, and online and offline functioning.

Interval observers for hybrid continuous-time stationary systems

The problem of interval observer design for hybrid continuous-time stationary systems under external disturbances and measurement noise is studied. It is assumed that continuous-time dynamic of such systems is described by linear or nonlinear differential state equations with linear function of output. System parameters depend on system states and are switched based on the control system with finite set of states. The relations allowing designing hybrid interval observer of minimal dimension estimating the set of admissible values of the prescribed linear vector function of the system states are derived. To solve the problem, algebra of partitions and linear algebra are used. Theoretical results are illustrated by example.

Rapid point-of-care breath test predicts breast cancer and abnormal mammograms in symptomatic women

Previous studies have reported volatile organic compounds (VOCs) in the breath as biomarkers of breast cancer. These biomarkers may be derived from cancer-associated fibroblasts, in which oxidative stress degrades polyunsaturated fatty acids to volatile alkanes and methylated alkane derivatives that are excreted in the breath. We evaluated a rapid point-of-care test for breath VOC biomarkers as predictors of breast cancer and abnormal mammograms.&#xD;Methods: We studied 593 women aged ≥ 18 yr referred to three sites for mammography for a symptomatic breast-related concern (e.g. breast mass, nipple discharge). A rapid point-of-care breath testing system collected and concentrated alveolar breath VOCs on a sorbent trap and analyzed them with gas chromatography and surface acoustic wave detection in < 6 min. Breath VOC chromatograms were randomly assigned to a training set or to a validation set. Monte Carlo analysis identified significant breath VOC biomarkers of breast cancer and abnormal mammograms in the training set, and these biomarkers were incorporated into a multivariate algorithm to predict disease in the validation set. &#xD;Results: Prediction of breast cancer: 50 women had biopsy-proven breast cancer (invasive cancer 41, ductal non-invasive cancer 9)&#xD;Unsplit data set: Breath VOCs identified breast cancer with 83% accuracy (area under curve of receiver operating characteristic), 82% sensitivity and 77.1% specificity.&#xD;Split data sets: Training set breath VOCs identified breast cancer with 80.3% accuracy, 84% sensitivity and 74.3% specificity. Corresponding values in the validation set were 68%% accuracy, 72.4% sensitivity and 61.5% specificity.&#xD;Prediction of BIRADS 4 and 5 mammograms (versus BIRADS 1, 2 and 3): &#xD;Unsplit data set: Breath VOCs identified abnormal mammograms with 76.2% accuracy.&#xD;Split data sets: Breath VOCs identified abnormal mammograms with 74.2% accuracy, 73.3% sensitivity and 60% specificity. Corresponding values in the validation set were 60.5% accuracy, 64.2% sensitivity and 51% specificity.&#xD;Conclusions: A rapid point-of-care test for breath VOC biomarkers predicted risk of breast cancer and abnormal mammograms in women with breast-related symptoms.&#xD;&#xD.

Theoretical Model for Determining the Thickness and Optical Constants of Transparent Conducting Oxide Thin Films From the Measured Reflectance Spectra

ABSTRACTThickness and optical constants of transparent conducting oxide (TCO) of metal oxide thin films have been commonly estimated by invoking theoretical models based on measured optical reflectance or transmittance. One of such widely employed models is reflectance‐based Kushev model. However, the relatively higher value of the absorption coefficient at the absorption edge of TCOs of metal oxide thin films results in a large deviation of their thickness values estimated by this model. To address the underlying problems, in the present work, we have improved the Kushev model. Specifically, for minimizing the error in the estimated thickness values from the proposed model, we have employed t test for discarding outliers of a set of thickness values of a given thin film, which were calculated from nearby extrema of a reflectance curve. Then the thickness calculated from model was validated by comparing the value of ZnO thin transparent films extracted from ellipsometric measurement. Our model shows excellent agreement with the thickness values of ZnO films from ellipsometric measurement with only 1.2% deviation. Furthermore, observed values were also compared with the values from already established Cauchy model. The perfectly matching of the simulated reflectance spectra from the present model with the measured reflectance and excellent agreement of thickness values derived from the ellipsometric measurements with the values extracted from the model may infer us that the present model is suitable for fairly accurately estimating film thicknesses of TCO thin films.

Digital sovereignty: conceptual challenges and constitutional implications

This article examines how national states and integrative unions such as the European Union employ the concept of digital sovereignty in their policy discourse. It begins with the premise that contemporary digital policy of these entities is intricately linked to the idea of digital sovereignty. The study analyzes the factors that have led national states and the European Union to enter a new phase of modern constitutionalism - digital constitutionalism. Modern European constitutionalism has accumulated experience in various social spheres, as evidenced by developments such as economic constitutionalism. In the digital era, it raises and attempts to answer questions about how digital constitutionalism can overcome the limitations of traditional constitutional thinking, particularly its focus on state-legal and political phenomena. The article explores the extent to which the generalization of purely state constitutional principles can advance in the digital age. The paper emphasizes that digital constitutionalism is a convenient concept for explaining the phenomenon of constitutional resistance to challenges created by digital technologies. It notes that existing foreign, and especially Ukrainian, legal scholarship has not yet formed a clear and unified vision of this concept. This article provides a literature review on digital constitutionalism and offers an analysis of the theoretical frameworks surrounding the concept. It posits that digital constitutionalism is an ideology that adapts the values of modern constitutionalism to the demands of the digital age. Currently, digital constitutionalism does not provide normative answers to the challenges of digital technologies, but rather presents a set of principles and values that inform and guide them. The article argues that Internet governance is evolving towards fragmentation, polarization, and hybridization, which contribute to the development of an architecture of freedom and power in the digital environment. The study aims to identify constitutionally significant threats associated with digitalization and allows for the development of constitutional counterstrategies.

The Impact of Organisational Culture on Transportation Behaviours: An Exploratory Analysis

By annually accommodating a growing number of students, higher education institutions contribute significantly to the daily flow of individuals. This flow exerts a significant impact on greenhouse gas emissions caused by transportation. Several studies have addressed promoting sustainable transportation at the individual level, while little attention has been drawn to examining the impact of organisations in this realm. This paper proposes a model of organisational influences on pro-environmental behaviours. Therefore, we thus identify a set of variables within organisations that expect to influence these behaviours. Among these variables, organisational culture appears as a major predictor. Organisational culture is a set of values, norms, beliefs, meanings and behaviours. Based on this definition, we propose to study organisational culture through measurable elements such as the organisation's values, norms and perceived practices. Additionally, we have identified variables directly influenced by organisational culture, such as leadership and organisational trust. Further variables, including personal norms and facilitating conditions, interact with the organisational culture and provide a more precise understanding of pro-environmental behaviours. This framework will be used to investigate student transportation behaviours. The results are expected to provide valuable insights for developing a culture of sustainable transportation at the organisational level.

Derivation of a clinical decision rule for termination of resuscitation in non-traumatic pediatric out-of-hospital cardiac arrest

AimPrehospital termination of resuscitation (ToR) rules are used to predict medical futility in adult out-of-hospital cardiac arrest (OHCA), however, the available evidence for pediatric patients is limited. The primary aim of this study is to derive a Pediatric Termination of Resuscitation (PToR) prediction rule for use in pediatric non-traumatic OHCA patients. MethodsWe analyzed a retrospective cohort of pediatric OHCA patients within the CARES database over a 10-year period (2013–2022). We split the dataset into training and test datasets and fit logistic regressions with Least Absolute Shrinkage and Selection Operator (LASSO) to select predictor variables and estimate predictive test characteristics for the primary outcome of death and a secondary composite outcome of death or survival to hospital discharge with unfavorable neurologic status. ResultsWe analyzed a sample of 21,240 children where 2,326 (11.0%) survived to hospital discharge, and 1,894 (8.9%) survived to hospital discharge with favorable neurologic status. We derived a PToR rule for death demonstrating a specificity of 99.1% and a positive predictive value (PPV) of 99.8% and a PToR rule for death or survival with poor neurologic status with a specificity of 99.7% and PPV of 99.9% within the test dataset. ConclusionWe derived a clinical prediction rule with high specificity and positive predictive value in prehospital settings utilizing Advanced Life Support (ALS) providers which may inform termination of resuscitation considerations in pediatric patients. Further prospective and validation studies will be necessary to define the appropriateness and applicability of these PToR criteria for routine use.

Deep-neural-network model for predicting ground motion parameters using earthquake horizontal-to-vertical spectral ratios

This study proposed a deep-neural-network (DNN) model for seismic ground motion prediction by utilizing a unified strong motion database by the National Research Institute for Earth Science and Disaster Resilience, and earthquake horizontal-to-vertical spectral ratio (EHVR) database in Japan. The model aims to enhance the accuracy of predictions by incorporating the EHVRs for complementing site effects, and utilizing existing ground motion prediction equations (GMPE) as the base model for source and propagation path effects. The hybrid approach enables the prediction of peak ground accelerations (PGAs), peak ground velocities (PGVs), and 5% damped absolute acceleration response spectra (SAs). After classifying the training and test sets from the database, the trained DNN models were applied on the test set to evaluate the performance of the predicted results. The accuracy assessment by the residuals, R-squared ( R2), and root mean square error (RMSE) between the predicted and observed values in the test set revealed the superior performance of the proposed model compared with the traditional GMPE with proxy-based site effects such as V S30s especially in predicting both the spectral amplitude and shape of SAs.

Detection of physical hazards from fruit processed products using hyperspectral imaging and prediction based on PLS-DA and logistic regression machine learning models

The current study aims to investigate a prediction model from reflection values and the spectral angle mapper (SAM) obtained from hyperspectral imaging (HSI) technology for the detection of three types of foreign materials – a branch, a knife, and rubber – that are associated with the various fruit-processed products. The study found that the maximum and minimum reflection values in the 900 to 1700 nm range for juices (apple, grape, tomato) and jams (strawberry, peach, tomato) differed depending on the presence or absence of physical hazards. The presence of physical hazards was also confirmed by the color difference in the SAM image. The partial least squares discriminant analysis model (PLS-DA) and logistic regression implemented on the Jupyter Notebook platform through the Anaconda prompt provided accuracy, F1 score, specificity, and sensitivity based on the confusion matrix. The maximum value was 100.0 %, while the minimum value was 97.6 % of the result of the PLS-DA modeling in the testing set. Logistic regression modeling also had a similar result: the maximum value was 100.0 %, while the minimum value was 97.8 % in the testing set. The sensitivity value in the testing set, which is a meaningful result for detecting physical hazards, was a maximum of 100.0 % for both PLS-DA and logistic regression. Results from the current study suggest that the reflection value and SAM data obtained through hyperspectral imaging could build a big data platform for early determination of physical hazards during agricultural product processing.

A community health-coaching referral program following discharge from treatment for chronic low back pain – a qualitative study of the patient’s perspective

BackgroundGlobal policy and guidelines for low back pain (LBP) management promote physical activity and self-management yet adherence is poor and a decline in outcomes is common following discharge from treatment. Health coaching is effective at improving exercise adherence, self-efficacy, and social support in individuals with chronic conditions, and may be an acceptable, cost-effective way to support people in the community following discharge from treatment for LBP.AimThis qualitative study aimed to understand which aspects of a community over-the-phone health-coaching program, were liked and disliked by patients as well as their perceived outcomes of the service after being discharged from LBP treatment.MethodsA purposive sampling approach was used to recruit 12 participants with chronic LBP, from a large randomised controlled trial, who were randomly allocated to receive a health coaching program from the Get Healthy Service® in Australia. Semi-structured interviews were conducted, and a general inductive thematic analysis approach was taken.ResultsThe main themes uncovered regarding the intervention included the positive and negative aspects of the health coaching service and the relationship between the participant and health coach. Specifically, the participants spoke of the importance of the health coach, the value of goal setting, the quality of the advice received, the benefits of feeling supported, the format of the coaching service, and LBP-specific knowledge. They also reported the health coach and the coaching relationship to be the primary factors influencing the program outcomes and the qualities of the coaching relationship they valued most were connection, communication, care, and competence. The sub-themes uncovered regarding the outcomes of the intervention included positive impacts (a greater capacity to cope, increased confidence, increased motivation and increased satisfaction) and negative impacts (receiving no personal benefit).Clinical implicationsIn an environment where self-management and self-care are becoming increasingly important, understanding the patient’s experience as part of a coaching program is likely to lead to improved quality of health coaching care, more tailored service delivery and potentially more effective and cost-effective community-based care for individuals with chronic LBP in the community after being discharged from treatment.Trial RegistrationThe GBTH trial was prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12620000889954) on 10/9/2020. Ethical approval was prospectively granted by the Western Sydney Local Health District Human Research and Ethics Committee (2020/ETH00115). Written informed consent was obtained from all participants. The relevant sponsor has reviewed the study protocol and consent form.

Weakly nonlinear hyperbolic differential equation of the second order in Hilbert space

We consider nonlinear perturbations of the hyperbolic equation in the Hilbert space. Necessary and sufficient conditions for the existence of solutions of boundary-value problem for the corresponding equation and iterative procedures for their finding are obtained in the case when the operator in linear part of the problem hasn't inverse and can have nonclosed set of values. As an application we consider boundary-value problem for van der Pol equation in a separable Hilbert space.

Distribution of unit mass on one fractal self-similar web-type curve

In the article, we study structural, spectral, topological, metric and fractal properties of distribution of complex-valued random variable$\tau=\sum\nolimits_{n=1}^{\infty}\frac{2\varepsilon_{\tau}}{3^n}\equiv\Delta^g_{\tau_1...\tau_n...}$, where $(\tau_n)$ is a~sequence of independent random variables taking the values $0,1,\cdots,6$ with the probabilities $p_{0n}$, $p_{1n},\cdots,p_{6n}$; $\varepsilon_{6}=0$, $\varepsilon_0$, $\varepsilon_1,\cdots,\varepsilon_5$ are 6th roots of unity. We prove that the set of values of random variable $\tau$ is self-similar six petal snowflake which is a fractal curve $G$ of spider web type with dimension $\log_37$. Its outline is the Koch snowflake. We establish that $\tau$ has either a discrete or a singularly continuous distribution with respect to two-dimensional Lebesgue measure. The criterion of discreteness for the distribution is found and its point spectrum (set of atoms) is described. It is proved that the point spectrum is a countable everywhere dense set of values of the random variable $\tau$, which is the tail set of the seven-symbol representation of the points of the curve $G$. In the case of identical distribution of the random variables $\tau_n$ (namely: $p_{kn}=p_k$) we establish that the spectrum of distribution $\tau$ is a self-similar fractal and that the essential support of density is the fractal Besicovitch-Eggleston type set. The set is defined by terms digits frequencies and has the fractal dimension $\alpha_0(E)=\frac{\ln {p_0^{p_0}\cdots p_6^{p_6}}}{-\ln 7}$ with respect to the Hausdorff-Billingsley $\alpha$-measure. The measure is a probabilistic generalization of the Hausdorff $\alpha$-measure. In this case, the random variables $\tau=\Delta^g_{\tau_1\cdots\tau_n\cdots}$ and $\tau'=\Delta^g_{\tau_1'...\tau_n'...}$ defined by different probability vectors $(p_0,\cdots,p_6)$ and $(p'_0,\cdots,p'_6)$ have mutually orthogonal distributions.

Analysis of Indoor Air Quality and Fresh Air Energy Consumption Based on Students’ Learning Efficiency under Different Ventilation Methods by Modelica

This paper aimed to explore a suitable ventilation method at a lower cost of energy to pursue a high learning efficiency based on the characteristics of a Chinese student group and campus building. Firstly, the model was established by Modelica and a good agreement between the numerical simulation and the results by CONTAM 3.4.0.3 was obtained. Secondly, the effects of the fixed window-opening ratio method (FWM), switch control window-opening ratio method (SCM), and automatic control window-opening ratio method (ACM) on CO2 concentration, indoor air temperature, and the heating capacity of air conditioning were investigated. The results showed that, when the FWM with 0% opening or 20% opening was adopted, the indoor CO2 concentration (ICC) was higher than the limit value of the classroom air quality standard, which was 1000 ppm. When the fixed window-opening ratio was greater than 40%, the indoor air temperature could not be controlled at the set value of 18 °C, which presented bad indoor thermal comfort. Meanwhile, when the ACM was adopted, the duration to meet good indoor thermal comfort was 57.17% higher than that of the SCM. However, both of them could maintain the average ICC below the set value in the class. Lastly, the fresh air energy consumption under different ventilation methods was compared. When the design temperature was 13.5 °C, it could be revealed that the fresh air energy consumption under the ACM, SCM, and FWM with 40% opening was 46.58%, 48.38%, and 51.26% lower than those at 18 °C. In summary, it was recommended to set the design temperature of the classroom at 13.5 °C, and the ACM was suggested as a suitable ventilation method to provide fresh air for the classroom.

Analysis of renewable energy resources based on frank power aggregation operators and EDAS method for circular bipolar complex fuzzy uncertainty

The model of circular bipolar complex fuzzy (Cir-BCF) sets computed based on the membership function, non-membership function, and radius among both functions for each value of the universal set. The technique of the Cir-BCF set is the modified or extended form of fuzzy sets, complex fuzzy sets, bipolar fuzzy sets, bipolar complex fuzzy sets, and simple circular bipolar fuzzy sets to cope with uncertain and vague information. In this manuscript, we describe the novel technique of frank operational laws based on Cir-BCF values for frank t-norm and frank t-conorm. Further, we simplify the model of Cir-BCF frank power averaging (Cir-BCFFPA), Cir-BCF frank power weighted averaging (Cir-BCFFPWA), Cir-BCF frank power geometric (Cir-BCFFPG), Cir-BCF frank power weighted geometric (Cir-BCFFPWG) operators, and highlighted their valuable properties, called idempotency, monotonicity, and boundedness. Moreover, analysis of renewable energy resources is very awkward and complicated, but it is natural sources of energy that are refilled constantly or relativeness quickly on a human timescale. Further, solar energy, hydroelectric energy, geothermal energy, biomass energy, and wind energy are five major sources of energy, but it is complex to find which one is the best and which one is worst. For evaluating the above problems, we construct the technique of evaluation based on the distance from the average solution (EDAS) method under the presence of the Cir-BCF numbers (Cir-BCFNs). At the end, we arrange the comparison between proposed and existing techniques based on some numerical examples to describe the validity and proficiency of the initiated information.

The impact of demographic change on value set validity and obsolescence.

To investigate the contribution of demographic trends in countries' age and gender composition to value set validity and obsolescence. Time-trade off (TTO) valuation data from 3 EQ-5D-3L value sets of 20 years or older from the United Kingdom, Japan, and the United States were re-analyzed using Bayesian heteroskedastic Tobit models with sex and age group-specific scale parameters. Original value sets were obtained by weighting the original preference structures with the countries' original demographic composition at the time of the data collection. Updated value sets were created using the original preference structure weighted using the countries' most recent demographic composition. The differences between the original and updated value sets were monitored and compared based on 95% credible intervals. The gender and age composition of the investigated countries changed in all 3 countries over time. The modelled health state preferences also depended on the respondents' gender and age. However, the overall impact of this demographic change on the investigated value sets was negligeable in all 3 countries and this finding was robust to accounting for the impact of ethnicity trends in the United States. Value sets may become redundant and obsolete for various reasons, but demographic change was not identified as a contributing factor.

Chinese utility weights for the EORTC cancer-specific utility instrument QLU-C10D.

The aim of this study is to provide Chinese utility weights for the European Organization for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions (EORTC QLU-C10D) which is a preference-based cancer-specific utility instrument derived from the EORTC QLQ-C30. We conducted an online survey of the general population in China, with quota sampling for age and gender. Each respondent was asked to complete a discrete choice experimental survey consisting of 16 randomly selected choice sets. The conditional logit model and mixed logit model were used to analyze respondents' preferences, and the goodness of fit of the model was tested. A total of 2003 respondents were included in the analysis. Utility decrements within dimensions were typically monotonic. Monotonic inconsistency issues in the Fatigue, Sleep, and Nausea dimensions were normalized by monotonicity correction. Physical functioning, Pain, and Role functioning were associated with the greatest utility weights, with the smallest decrements being in Bowel problems and Emotional functioning. The utility value for the worst health state was 0.083, i.e. slightly higher than being dead. This study provides the first China-specific set of value for the QLU-C10D based on societal preferences of the Chinese adult general population. The value set can be used as a cancer-specific scoring system for economic evaluations of new oncology therapies and technologies in China.

Painlevé analysis of the Sasa–Satsuma equation

The Sasa-Satsuma equation is considered. The Painlevé test for partial differential equations with application of the Kruskal variable is used to investigate the necessary condition of integrability of the equation. It is shown that the equation does not pass the Painlevé test in the general case. However, there exist constraints on parameters of the equation, when all Fuchs indices are integers. In these cases the Laurent series expansions of the solution exit and, consequently, there exist analytical solutions of this partial differential equation. We confirm that there are two integrable cases, at which the Sasa–Satsuma equation passes the Painlevé test. We also obtain that there is another set of parameter values at which the equation can be an integrable.

Robust prediction for characteristics of digestion products in an industrial-scale biogas project via typical non-time series and time-series machine learning algorithms

Anaerobic digestion (AD) is a well-established pathway for treating agricultural organic waste, and machine learning has emerged as a novel tool to predict its product performance. In prior research, the majority of studies concentrated on non-time series models for laboratory-scale fermentation data. Consequently, the generalization performance of these models was significantly constrained, particularly in the context of industrial-scale biogas projects. Thus, in this study, typical non-time series models (GBR and RF) and time-series models (LSTM, CNN-LSTM, and DA-LSTM) after hyperparameter optimization were chosen to accurately predict the characteristics of digestion products in a biogas project. The ideal GBR model for CH4 content was obtained, and the R2 values of the test set and training set were 0.93 (RMSE=1.11) and 0.97 (RMSE=0.69), respectively. Temperature was the most important parameter for biogas production according to feature importance and SHAP analysis of the RF model. The DA-LSTM was superior to LSTM and CNN-LSTM for the prediction of biogas production, and the R2 of DA-LSTM was 0.87 (RMSE=1048.14) with a seq_len of 10 d. This study provides direction for high-efficiency biogas production in wet biogas projects with the aid of reliable machine learning models.

Optimizing EDM for titanium alloys: an in-depth comparison of five MCDM techniques

This experimental study investigates the effect of the cutting parameters of the Electrical Discharge Machining (EDM) process of Ti-6Al-4V alloy material on surface roughness (Ra), cutting time (t) and Material Removal Rate (MRR) then solve the Multiple Objective Optimization Problem using separate Multi-Criteria Decision-Making (MCDM) methods namely Entropy-Weighted TOPSIS (E-TOPSIS), MOORA, SAW, VIKOR, and WPM. Focusing on nine 3-levels variants including Operating Voltage (OV), Pulse-On Time (Ton), Pulse-Off Time (Toff), Short-Circuit Off Time (AFF), Secondary Voltage (SV), Feed Rate (WF), Tension (WT), Water Pressure (WL) and Material Cutting Speed (F). Due to the large number of variants studied, the Taguchi L27 experimental design was chosen to reduce the number of experiments while still ensuring reliability in assessing the impact of technological parameters on responses in the study. The optimization results from the different methods indicated two distinct optimal outcomes. According to the E-TOPSIS, MOORA, and SAW, the optimal result is a Ra of 3.27 µm, a t of 7.37 min, and an MRR of 7.45 mm3/min. This result suggests a balanced and harmonious optimization among all criteria. On the other hand, the figures VIKOR and WPM methods are 2.87 µm, 9.57 min, and 5.74 mm3/min, respectively. These results indicate a higher priority for certain criteria, reflected in the lower Ra, longer cutting time, and a smaller MRR in comparison to the figures for the remaining MCDM methods. The different optimal results achieved by various methods highlight that each method is suited to and excels with different sets of values. Therefore, in each specific research or production process, comparing and choosing results calculated by different methods provides a comprehensive view, aiding in making appropriate decisions