Empirical Method Research Articles

Assessing Helicopter Turbine Engine Health: A Simple Yet Robust Probabilistic Approach

This paper presents a data-driven approach for assessing the health of helicopter turbine engines, developed for the PHM North America 2024 Conference Data Challenge. The task involves both regression and classification to estimate the torque margin and classify engine health as either nominal or faulty. To quantify the reliability of predictions, probabilistic outputs are generated. We employ a two-stage model where the predicted torque margin serves as an input feature for health classification. For probabilistic torque margin estimation, we introduce an empirical error sampling method to generate torque margin samples, followed by a rule-based distribution selection scheme to evaluate the resulting distributions. For fault classification, logistic regression is used to provide confidence estimates, and we incorporate a score-optimized loss function during training to mitigate penalties for false negatives. Our approach demonstrates strong generalization to unseen assets, ranking 2nd in the competition with a score of 0.94, demonstrating its effectiveness in predicting health conditions and uncertainty for more informed helicopter engine management.

Reduced basis method for the elastic scattering by multiple shape-parametric open arcs in two dimensions

We consider the elastic scattering problem by multiple disjoint arcs or cracks in two spatial dimensions. A key aspect of our approach lies in the parametric description of each arc's shape, which is controlled by a potentially high-dimensional, possibly countably infinite, set of parameters. We are interested in the efficient approximation of the parameter-to-solution map employing model order reduction techniques, specifically the reduced basis method. Initially, we utilize boundary potentials to transform the boundary value problem, originally posed in an unbounded domain, into a system of boundary integral equations set on the parametrically defined open arcs. Our aim is to construct a rapid surrogate for solving this problem. To achieve this, we adopt the two-phase paradigm of the reduced basis method. In the offline phase, we compute solutions for this problem under the assumption of complete decoupling among arcs for various shapes. Leveraging these high-fidelity solutions and Proper Orthogonal Decomposition (POD), we construct a reduced-order basis tailored to the single arc problem. Subsequently, in the online phase, when computing solutions for the multiple arc problem with a new parametric input, we utilize the aforementioned basis for each individual arc. To expedite the offline phase, we employ a modified version of the Empirical Interpolation Method (EIM) to compute a precise and cost-effective affine representation of the interaction terms between arcs. Finally, we present a series of numerical experiments demonstrating the advantages of our proposed method in terms of both accuracy and computational efficiency.

Restorative Justice and Agrarian Reform Conflict Resolution

Abstract: The government emasculates agrarian reform. The government no longer interprets agrarian reform as a restructuring of land ownership. Furthermore, the interpretation of agrarian reform now primarily focuses on asset legalization, land redistribution, and social forestry. The issue lies in the emasculation of agrarian reform. Various structural agrarian conflicts remain unresolved after the government's implementation of agrarian reform. Differences in interpretation of agrarian reform trigger the conflict. The government's interpretation is different from the community's interpretation, which considers agrarian reform to be a systematic effort to provide the community with access to land. The author recommends the concept of restorative justice as an effort to resolve this problem. The government should use restorative justice instead of the militaristic approach to resolve the problem. This article employs an empirical legal research method, combining a sociological perspective and a case study approach. This article contains several important findings, one of which is that asset legalization is not an agrarian reform. Asset legalization fails to address the issue of land ownership inequality. The government's implementation of land redistribution fails to address the issue of land ownership inequality. The government's version of land redistribution not only fails to resolve the issue of land ownership inequality, but also seizes land from marginalized communities. The same goes for social forestry. Social forestry leaves behind unresolved agrarian and environmental conflicts. Differences in interpreting agrarian reform actually cause all these problems. Therefore, we can use restorative justice as an alternative to solving the problem. As a problem-solving model involving victims and suspects, this resolution model seeks peace between the two parties. The hope is that there will be no more bloody agrarian conflicts, especially related to agrarian reform in Indonesia. Keywords: Agrarian Conflict, Agrarian Reform, Restorative Justice

Use of PhET to enhance the learning of mechanical energy in high school students of the Fiscomisional Educational Unit “Cinco de Mayo”

The use of the PhET simulation has proven to be an effective tool to improve the learning of mechanical energy in third-year high school students of the Fiscomisional Educational Unit "Cinco de Mayo". This research aimed to apply said simulator to facilitate the understanding of key concepts such as energy conservation, types of energy and energy transformation. Theoretical methods were used to collect information and empirical methods to evaluate its effectiveness, such as survey, interview and observation sheet. The results obtained showed that the use of the PhET simulation promoted a better understanding of mechanical energy concepts, allowing students to interactively visualize complex phenomena that would otherwise be difficult to illustrate with traditional methods. Furthermore, it was found that this digital tool made the teaching-learning process more attractive and dynamic, significantly improving the participation and motivation of students in the classroom.

G. BERKELEY & F. MATHEWS “LOGOS” ONTOLOGY

The purpose of article’s study is to discover Logos phenomenon which is present in the nature of thinking using an empirical method in the value system of F. Mathews & G. Berkeley from the point of view of modern ethics, historical experience, modern psychology and culture of ecology. “Logos” is considered as a segment of the field of thinking, a certain event in the field of meaning.The meaning of “Logos” as an event in the ontology of F. Mathews is considered from a metaphysical point of view and acquires a special semantic value in the context of G. Berkeley philosophy. In the space-time continuum, “Logos” exists in a moving field of meanings and is opposed to “Nonthought.” In the course of history, the manifestation of “Logos” was absorbed by everyday life and mediocrity, but F. Mathews and G. Berkeley are trying to prevent the disappearance of “Logos” by creating an “Ecological Model of Thinking”, revealing perception from internal semantic structures towards natural phenomena. An ecological model of thinking can prevent the formation of a “perceptual dead zone” where human genius is devalued by self-centered mediocrity. The phenomenon of the integrity of the "Logos" is an ethical expression of intuitive perception.The causes and consequences of "ontological inertia" are also revealed.

An Empirical Line approach for Agrowing Camera Aerial Images of inland waters based on exponential fit and in situ water measurements

Abstract. With the advancement of technology in the area of remote sensing, monitoring the Earth's surface using multispectral cameras attached to unmanned aerial vehicles (UAV) has become promising. However, in many Earth observation applications, it is needed to make compatible the spatial data of images captured by high spatial resolution multispectral sensors with the spectral response of targets on the Earth's surface. This relation is obtained through a radiometric calibration. The empirical line method is commonly used to calibrate the spectral bands of sensors. Thus, applications of this method using linear fit have retrieved negative values in water bodies. So that, attempting different adjustments, as well different reference targets, can solve this issue. In this study, the water quality of small bodies of water was analysed using a Agrowing multispectral camera, which derived negative values when applying linear fit. The aim of this study, therefore, was to fit a radiometric calibration based on empirical line method for Agrowing camera in inland water applications. Besides of standard reference targets, water samples also were attempted because showed a lower radiance response than the darkest (black) calibration target. Two empirical line methods were applied to convert the digital number (DN) from the Agrowing images into remote sensing reflectance (Rrs): linear and exponential. The exponential method showed to be more appropriate, with greater accuracy, unlike the linear method.

The Differential Effects of Augmented Reality and Product Presentation Strategies on Brand Recall: An Embodied Cognition Perspective

As augmented reality (AR) technology becomes more prevalent in marketing, its impact on consumer memory processes, particularly brand recall, remains underexplored. This study primarily employs an empirical research method, using two lab experiments to examine the interaction between product presentation formats (AR vs. non-AR) and presentation strategies (separate vs. collocation) in brand recall. Across two experiments, we showed that AR enhances brand recall only in collocation presentations, where multiple products are displayed together, but not in separate presentations of individual products. In single-product contexts, AR formats do not demonstrate a significant advantage over non-AR formats. These findings suggest that AR’s effectiveness is contingent on presentation strategy, highlighting the contextual boundaries of AR’s utility in influencing consumer memory. By integrating embodied cognition theory with associative network theory, this research advances our understanding of how immersive technologies shape brand recall, offering strategic insights for marketers seeking to leverage AR in diverse product presentation scenarios.

Preserving reason: a rationalist defense of the ‘Western telos’ in social science and the humanities

I discuss some of the current challenges to the social sciences/humanities and contend that their impact, marked by epistemological confusion and ill-founded accusatory discourse against the basics of open scientific debate and empirical methods, is damaging and undermining rational exchange. There is notable variety across disciplines, but contestation is rife. I affirm the existence and value of a historical Western telos, as a scientific-epistemological ‘project’ driven both by basic curiosity and (material) interests. In the face of some justified but also some grossly overstated accusations of science, especially during the past two decades, I plead for renewal and recalibration of such a telos (be it Western or other) based on the intrinsic value of sound, evidence-based science and non-justificationist critical rationalism, not the least because the proposed alternatives – slighting evidence-based reasoning and advocating the use of personal experience/bias as authoritative, like in ‘identity politics’– hold little promise.

A Theoretical Model-Based Methodology to the Design of Soft Structures: A Case Study of Pneumatic Mesh Actuators

Soft robots offer significant potential in various fields, including healthcare, education, and rescue operations, where actuators are critical components that influence power, precision, and environmental adaptability. However, the nonlinear properties of hyperelastic materials often necessitate reliance on empirical methods and extensive experimentation for actuator design. This study introduces a methodology for designing soft structures, exemplified by pneumatic mesh actuators. Utilizing numerical simulations to investigate deformation patterns and applying the principle of virtual work within a segmented constant curvature framework, a theoretical model was developed to describe the relationships between input air pressure, bending angle of a single airbag, and wall thickness. To validate the model's accuracy and applicability, bending tests were performed on actuators with varying wall thicknesses. A new pneumatic mesh actuator was designed and fabricated using the proposed method, with the experimental results showing a deviation of only 0.27° from the target bending angle under the specified air pressure. This confirms the effectiveness of the proposed design approach. This methodology has potential applications beyond pneumatic mesh actuators, extending to other areas of soft structure design.

Attitude of adoptive and biological parents to tactile interaction with children

Introduction. The problem of children's adaptation to foster families remains relevant for many years all over the world. However, there is now evidence that humans have two tactile systems, one of which is social and is activated by slow, gentle touch. The idea arose that adoptive parents could be taught such touches using the example of a special massage. But for this you need to know the attitude of parents towards touch in principle. That is why the purpose of this study was to study parents’ attitudes towards tactile interaction with children. Methodology. 277 foster and biological parents (M=39.9; SD=7.6) completed a survey using Google Forms that included 48 statements scored on a psychometric Likert scale. The work used theoretical (analysis, comparison and synthesis), empirical (survey) and statistical (correlation, regression and factor analysis using the SPSS 21 software package) research methods. Results and discussion. Significant inconsistency was found regarding physical sanctions among all groups of respondents. Thus, by unanimously declaring a negative attitude towards punishing the children of other children, respondents allow this to happen to themselves (Ro=-0.603, p<0.001), which affects the personal impact of the child’s development (Ro=-0.508, p<0.001). All mothers reported detecting excessive tactile contact with the child (Ro=0.544, p<0.001). The 4-factor model shows an ambiguous attitude of respondents towards gentle, tactile interaction with both their children and parents in their own childhood (KMO=0.792; p<0.000; 63.1%). Signs of emotional burnout are observed in all parents, but are especially pronounced in adopted ones (p=0.007; R2 =0.056; DW=1.633; r=0.236). Conclusion. Before inviting parents to try massage based on gentle tactile interactions with children, it is necessary to provide training in methods of rewarding and punishing children within the family without violence. A burnout prevention program is needed for all parents.

A Hybrid Modelling Approach Coupling Physics-based Simulation and Deep Learning for Battery Electrode Manufacturing Simulations

Lithium-ion battery (LIB) performance is significantly influenced by its manufacturing process. Manufacturing of an optimized electrode can incur high production costs such as high energy consumption, high scrap rates and emissions. This is due to the process that consists of a series of manufacturing steps presenting a complex interrelationship, thus limiting the understanding of performance as a function of manufacturing parameters. While several empirical and computational methods are employed for optimization, they are demanding in terms of resources such as materials or computational effort. By leveraging Deep Learning (DL), we can enhance our understanding of the complex manufacturing processes and accelerate its optimization. We propose a data-driven supervised DL methodology to complement physics-based LIB cathode manufacturing simulations. The trained DL-based predictive model integrates well into the manufacturing simulation framework to forecast cathode slurry microstructures. The DL model demonstrates robust predictive performance for LIB NMC-111 and LiFePO4–based slurries and slurries for a solid-state battery NMC-622/argyrodite composite electrode preparation. While the current work is focused on the cathode slurry process, the proposed methodology has potential for application to drying and calendering steps. This approach will be helpful in streamlining lab-scale electrode manufacturing, and reducing errors, waste and resource consumption.

A Study on the Effectiveness of English Debate Competitions as a Language Learning Aid

English debate competitions have gained widespread attention as an innovative language learning tool in recent years. This study explores the impact of English debate on learners’ listening, speaking, reading, and writing skills, as well as their critical thinking and teamwork abilities. Using empirical research methods such as surveys, interviews, and performance evaluations, this study finds that participation in English debates not only improves students’ English proficiency but also significantly enhances their ability to think critically and collaborate effectively. By integrating recent literature, the research further examines the actual impact of English debate competitions on language learning and their application in educational contexts.

Collocation methods for nonlinear differential equations on low-rank manifolds

We introduce new methods for integrating nonlinear differential equations on low-rank manifolds. These methods rely on interpolatory projections onto the tangent space, enabling low-rank time integration of vector fields that can be evaluated entry-wise. A key advantage of our approach is that it does not require the vector field to exhibit low-rank structure, thereby overcoming significant limitations of traditional dynamical low-rank methods based on orthogonal projection. To construct the interpolatory projectors, we develop a sparse tensor sampling algorithm based on the discrete empirical interpolation method (DEIM) that parameterizes tensor train manifolds and their tangent spaces with cross interpolation. Using these projectors, we propose two time integration schemes on low-rank tensor train manifolds. The first scheme integrates the solution at selected interpolation indices and constructs the solution with cross interpolation. The second scheme generalizes the well-known orthogonal projector-splitting integrator to interpolatory projectors. We demonstrate the proposed methods with applications to several tensor differential equations arising from the discretization of partial differential equations.

Identification of Potential Diagnostic Markers for Depressive Disorders using Urinary Biomarkers of N-Methylnicotinamide and Hippuric Acid

Introduction: The diagnostic methodology for depressive disorders, relying on symptom clusters, has inherent limitations in ensuring heterogeneity levels. Consequently, this presents a notable risk of inevitable diagnostic errors in mental health assessments. Therefore, advocating for objective diagnostic approaches through empirical testing in clinical settings becomes crucial for individuals dealing with depressive disorders. This study aims to identify the effectiveness of urine as a diagnostic support for depressive disorders using the N-Methylnicotinamide and Hippuric Acid biomarkers. Methods: This study used 13 urine samples from patients with depressive disorders and 13 normal urine samples. It used ELISA methods with observational analytic and cross-sectional designs. Results: The results showed that the N-methylnicotinamide biomarker had a relationship with depressive disorders with a correlation value of 0.867, while hippuric acid obtained a correlation value of 0.692. Besides, the N-Methylnicotinamide and Hippuric Acid biomarkers showed differences in the urine of depressive disorder and normal patients with significance values of 0.000 and 0.001 for the N-Methylnicotinamide and Hippuric Acid biomarkers, respectively. In addition, the Relative Operating Characteristics curve analysis showed that these two biomarkers had good sensitivity and specificity values in assisting the diagnosis of depressive disorders. N-methylnicotinamide has a sensitivity of 92.3% and a specificity of 100%, while hippuric acid has a sensitivity of 76.9% and a specificity of 84.6%. Conclusions: Significant differences in the biomarkers of N-methylnicotinamide and hippuric acid in the urine of depressed patients compared to normal patients. Therefore, these biomarkers can be the empirical laboratory methods to support the diagnosis of depressive.

Parameter Sensitivity Analysis for Diesel Spray Penetration Prediction Based on GA-BP Neural Network

Machine learning has started to be used in engine research to optimize combustion and predict fuel spray characteristics. This paper presents the development of a machine learning model using a Genetic Algorithm-Backpropagation (GA-BP) neural network to predict spray penetration. The GA-BP neural network was selected for its ability to optimize neural network weights and biases, thereby improving model convergence and avoiding local minima, which are common challenges in complex, non-linear problems such as spray prediction. The model was trained using experimental data from diesel injector spray tests, and its accuracy was evaluated through parametric sensitivity analysis, examining the influence of various input factors. A comparison between the machine learning model and the traditional empirical formulas of spray penetration revealed that the machine learning model achieved greater accuracy. In terms of the sensitivity to inputs, it is interesting to find that the cognition of machines is different from that of humans. When an input parameter does not have any functional relationship with other input parameters, the absence of this input parameter will lead to a significant decrease in the accuracy of the output result. The results demonstrate that the machine learning approach offers higher accuracy and better generalizability compared to traditional empirical methods. This study recommends the ways to get better results of penetration prediction with BP neural networks, which is efficient in training and utilizing Artificial Neural Networks (ANNs).

Penguatan Kepastian Hukum Kewenangan Kejaksaan Sebagai Penyidik dalam Tindak Pidana Korupsi Sidang Perkara Nomor 28/Puu-Xxi/2023

Corruption cases in Indonesia still really need attention considering that the consequences can be detrimental to the state and society. Handling the eradication of corruption is then carried out by several state institutions which are given direct authority by law, one of which is through the Prosecutor's Office of the Republic of Indonesia. Legal certainty of authority is very necessary to create harmony between government institutions and avoid overlapping authority. Furthermore, in writing this article, we used an approach method, namely an empirical method with descriptive analytical research specifications. The formulation of the problem raised in this article is regarding legal certainty in strengthening the prosecutor's office as an investigator in criminal acts of corruption. Furthermore, the purpose of this article is to analyze legal certainty or the legal standing of the authority of the prosecutor's office as an investigator in criminal acts of corruption. The authority of the Prosecutor's Office is contained in Article 30 paragraph (1) letter d of Law 5 of 1991 concerning the Prosecutor's Office of the Republic of Indonesia which was later declared invalid by Law 16 of 2004 in conjunction with Law Number 11 of 2021 concerning Amendments to Law Number 16 of 2004 concerning the Prosecutor's Office of the Republic of Indonesia. Then in Article 26 of Law no. 19 of 2019 Second amendment to UU No. 31 of 1999 concerning Corruption Crimes.

Manifestations of emotional burnout in rehabilitation centers staff

Introduction. High emotional intensity of professional activities of rehabilitation centers staff, the need to constantly respond to unexpected non-standard pedagogical situations, the requirements for empathy and reflection in conditions of uncertainty, etc. determine the development of emotional burnout. Consequently, an employee suffering from emotional burnout cannot fulfill professional duties efficiently and solve tasks set by the organization. In this regard, it is necessary to understand the emotional sphere manifestations in employees of rehabilitation centers and organize appropriate preventive work. The purpose of this article is to summarize the data on studying the emotional peculiarities, to identify the manifestations of emotional burnout in rehabilitation centers employees. Materials and Methods. The methodological basis of the research includes studying the content of the phenomenon of emotional burnout with the focus on personal and professional self-fulfillment. In order to solve the research tasks the authors used analysis and generalization as theoretical methods and empirical methods, including testing, conversation, and methods of quantitative and qualitative data analysis. The sample consisted of 124 employees of rehabilitation centers in the Krasnodar Territory. Results. The article presents a theoretical overview and summarizes the results of studying the emotional sphere of rehabilitation centers employees. The study reveals the manifestations of emotional burnout, clarifies essential aspects of emotional disorders prevention. Conclusions. Emotional exhaustion, stress resistance disorders, tension, etc. are revealed as basic manifestations of emotional burnout in the research sample. The article concludes that prevention should be comprehensive and take into account the identified characteristics of emotional disorders.

The study of newly-qualified teachers’ psychological well-being and personal reflection

Introduction. The article examines the peculiarities of psychological well-being and satisfaction with the profession of novice teachers in connection with personal reflection. The purpose of the study is to reveal the specifics of psychological well-being and personal reflection of teachers at the initial stage of professional development. Materials and Methods. The study follows a systematic approach and the concept of psychological well-being (K Riff). In order to achieve the purpose of the research, the authors used theoretical (analysis, comparison, generalization, systematization) and empirical (tests) methods, as well as methods of statistical information processing. To collect relevant data, the methods were presented by means of a Google form via an online resource. The research sample consisted of 162 newly-qualified teachers from Omsk and the Omsk region whose work experience ranged between 6 months and 5 years. Results. The authors of the article obtained the following results: - analyzed and summarized Russian and international research investigations on issues of psychological well-being, the level of development of reflection and novice teachers satisfaction with their profession; - the empirical results of the study are presented, which reflect the priority indicators of psychological well-being, the level and types of personal reflection, the level of satisfaction with the professional development of newly-qualified teachers; the specifics of psychological well-being and personal reflection of teachers are revealed, the types of teachers at the initial stage of professional development are described. Conclusions. The specifics of psychological well-being and personal reflection of novice teachers are determined by difficulties in managing the environment, building interaction with colleagues and self-acceptance, readiness for personal growth and autonomy, and there is also insufficient development of reflection skills, in particular, reflection on communication and real activity, which affects satisfaction with professional activities. The types of novice teachers have been identified depending on the specifics of psychological well-being, the level of development and type of personal reflection, and satisfaction with profession.

Restorative Justice di Tingkat Kepolisian atas Tindak Pidana Balapan Liar yang dilakukan oleh Anak: Studi di Wilayah Kepolisian Resor Kota Sampang

This study is designed to understand how the application and implementation of restorative justice serve as a last resort principle for handling cases of illegal street racing committed by minors in the Sampang City Police jurisdiction. The approach used in this study is the empirical juridical method, involving the Conceptual Approach and the Statute Approach. The research questions addressed in this study are: (1) How is restorative justice implemented at the police level for handling cases of illegal street racing committed by minors (a study in the Sampang City Police area)? (2) What are the challenges and efforts in implementing restorative justice at the police level for cases of illegal street racing committed by minors (a study in the Sampang City Police area)? According to the study’s findings, the conclusions are as follows: The first research question explores the implementation and process of restorative justice carried out by the Sampang City Police for cases of illegal street racing by minors. The second research question reveals various obstacles in the implementation of restorative justice at the police level concerning cases of illegal street racing involving minors. Additionally, efforts are being made by the police to prevent illegal street racing committed by minors.

Analyzing the Influence of Dividend Policy on Corporate Value: A Financial Perspective with Haier as a Case Study

The dividend policy plays a pivotal role in stabilizing stock prices and sustaining investor enthusiasm for listed companies. It not only significantly impacts the interests of management, investors, and creditors but also has long-term implications for the company's development. However, most studies on Chinese enterprises' dividend policies primarily rely on empirical research methods, with limited literature available on individual companies. The utilization of a case analysis methodology in this study has significantly enhanced the research cases related to China's dividend policies, thereby providing valuable insights for the advancement of analogous industries and the formulation of future dividend policies. In this study, Haier Smart Home Co., Ltd. (referred to as "Haier"), a publicly traded company on the Shanghai Stock Exchange, is selected as the case study subject in order to examine the impact of dividend policy on corporate value from a financial perspective. Through an analysis of Haier's dividend allocation data from 2008 to 2022 and an evaluation of various financial indicators during this period, we find that a stable dividend payment level can effectively sustain the enterprise value of the company. Therefore, it is recommended for listed companies to optimize their ownership structure and enhance corporate governance while strategically formulating dividend policies aligned with their financial performance and corporate strategy.