Results Of Reliability Analysis Research Articles

Slope Stability and Reliability Analysis of Earth Embankment Constructed for the Doubling of Railway Track

Embankments of greater height pose threat to its stability and require geotechnical investigation and intervention. Conventionally, limit equilibrium approach is used to estimate the factor of safety of the slope to assess its stability. Over a period of time, with experience and engineering judgments, a factor of safety of 1.4 is deemed sufficient for Indian practice. In the approach, it is inherently assumed that different sources of uncertainty due to testing errors, model transformation, and inherent variability of the geo-material are taken care of with the use of single value of factor of safety. Still, a question remains, whether the suggested factor of safety is acceptable in a given environment of uncertainty or there is a need to further utilize the probabilistic approach. The present study demonstrates how combination of First Order Reliability Method (FORM), Finite Element Method (FEM) and Response Surface Method (RSM) can be useful in the probabilistic assessment of proposed construction of new earth embankment for the doubling of a railway track. It is further highlighted that conventional factor of safety approach when used in conjunction with probabilistic analysis brings rationality in decision making. Also, based on results of slope stability and reliability analysis, it is proposed to incorporate soil nailing to further improve the stability of the earth embankment.

ДОСЛІДЖЕННЯ ТА ОЦІНКА СТАТИСТИЧНОЇ ОДНОРІДНОСТІ АВТОКОРЕЛЮВАНИХ ВИМІРЮВАНЬ

The presentation is devoted to the study and evaluation of the statistical homogeneity of autocorrelated measurements, which is an important task in the analysis of time series and experimental data. The study will consider how autocorrelation affects statistical conclusions and the quality of parameter estimates. Particular attention is paid to methods of autocorrelation detection and data correction to ensure reliable analysis results. The report covers both theoretical aspects and practical examples of applying various methods for assessing statistical homogeneity in autocorrelated measurements. Autocorrelation can distort statistical conclusions, so the topic of researching such measurements and studying the correction methods that can be used to obtain more reliable results is relevant and not fully covered.

Calculation of Rayleigh Damping Coefficients for a Transient Structural Analysis

Direct numerical integration of differential equations of motion is widely used by engineers to describe the behavior of structures under dynamic loading. The method entails directly integrating the motion equations over time. In the direct method, the damping matrix is formed as a linear combination of mass and stiffness matrices multiplied by the Rayleigh damping coefficients α and β, respectively. The Rayleigh damping coefficients have a significant effect on the response of building structures under dynamic loading. Therefore, the design values of the damping coefficients α and β have crucial importance to ensure accurate and reliable results in a dynamic analysis. The paper presents a time domain analysis for a building subjected to seismic excitations using the modal superposition and direct integration methods. The direct method considers the damping properties of building structures by Rayleigh damping coefficients obtained using various approaches. The building's response to seismic load is compared by response spectra. The authors proposed the least conservative approach for calculating the Rayleigh damping coefficients for analyzing a building in the time domain.

Investigation on the Micro-Grinding Induced Crystallographic Variations of Nine Different Clinkers

Although clinker has been used for many years, complicated mineralogical properties of clinker pose challenges for the precise quantification. In this study, the mineralogical and crystallographic properties of nine different clinkers according to grinding procedures were investigated. With the dry-grinding for 2 h, particle size reduction to 3 μm of median particle size with a substantial phase transition to an amorphous phase observed, to which alite (C3S) mainly contributed to the transition. Meanwhile, the crystallographic properties of the clinker phases were barely changed during the wet-grinding. In the wet-grinding program, the amount of ferrite solid solution (C4AF) with a high linear absorption coefficient was not underestimated. Furthermore, well-corrected preferred orientation effect on C3S was positively contributed to the analysis result of clinkers with the wet-grinding. Hence, it was suggested that the crystallographic effects observed in the wet-grinding program could produce more reliable results in phase analysis for the clinkers.

Reliability analysis for continuous degrading systems subject to multi-level failure dependence

This article explicitly models multi-level failure dependence existing in continuous degrading systems with multiple degrading components. Dependence within the component level is specified as that arrived shocks increase the vulnerability to inherent degradation. Dependence among components refers to the fact that the degradation of a particular component can be accelerated by others. The Gamma process is employed as a comprehensive framework for modeling the dependence above. A compound Poisson process and normal distribution are both introduced to describe the stochastic characteristics of random shocks. Procedures for obtaining analytical solutions and simulation results of reliability analysis are both presented. At last, an illustrative example of a hydraulic system is studied to demonstrate the effectiveness and advantages of the proposed method.

Reliability and validity estimation of Urdu version of Children Emotion Management Scales (CEMS) in Pakistan.

The present study aimed to translate and validate Children's Emotion Management Scales into Urdu, the national language of Pakistan. The current study comprised three different phases, i.e., phase I: Cross-language validation over a sample of (N = 169) school children, estimated at a 1-week interval. The results indicate a significant correlation (r = 0.846-0.891) at p < 0.01. In phase II, the internal consistency reliability (r = 0.808-0.904) and split-half reliability (r = 0.737-0.898) of the scale were assessed (N = 683) at p < 0.01. Furthermore, significant results for test-retest reliability analysis (N = 168) were obtained (r = 0.736-0.917 at p < 0.01), following the confirmatory factor analysis (CFA) (N = 1,083). Exploratory factor analysis (EFA) was conducted on the same sample chosen for CFA. EFA resulted in the retention of original inhibition (INH), dysregulated expression (DYS), and emotional coping (EMO) factors. CFA findings suggest a good model fit. In phase III, convergent validity and divergent validity were checked (N = 385, 255, and 213). Convergent validity of INH and DYS subscales and divergent validity of EMO subscales were established, with SBI (r = 0.217-0.609; 0.210-0.445; -0.026 to -0.553), SHS (r = 0.417-0.441; 0.480-0.546; -0.338 to -0.582), and suppression subscale of ERQ (r = 0.430-0.480; 0.468-0.522; -0.245 to -0.369) at p < 0.01. For divergent validity of INH and DYS subscales and convergent validity of EMO subscales, their scores were correlated with the SPS (r = -0.204 to -0.350; -0.318 to -0.459; 0.191-0.531), RSE Scale (r = -0.226 to -0.351; -0.279 to -0.352; 0.255-0.507), DTS (-0.290 to -0.617; -0.369 to -0.456; 0.246-0.680), and reappraisal subscale of ERQ (r = -0.456 to -0.541; -0.329 to -0.544; 0.446-0.601) at p < 0.01. It is concluded that the scale is reliable and valid with sound psychometric properties.

Enabling privacy-preserving medication analysis in distributed EHR systems

The digitalization of the medical field has resulted in a vast amount of medical data stored in Electronic Health Record (EHR) systems. Among the various valuable applications of EHRs, medication efficacy analysis stands out as a powerful tool for drug development and enhancing patient treatment. This analysis relies on multi-dimensional medical data, encompassing various factors. Currently, medical research is increasingly inclined towards inter-institutional sharing of medical data to enhance the accuracy and reliability of analysis results. However, due to the sensitivity of personal medical data, privacy and security considerations must be taken into account when conducting medical analyses across institutions. In this paper, we present a novel privacy-preserving scheme for distributed medication efficacy analysis. Our work allows for the analysis of multi-dimensional medical data by leveraging the private set intersection protocol and the Paillier cryptosystem. To validate the feasibility of our scheme, we implement it using some real medical datasets. Experimental results demonstrate that our approach offers enhanced security and lower computational and communication overhead compared to the original approach, which solely processes single-dimensional data at a time.

Analyzing the risk of the ammonia storage facility using extended FMEA model based on probabilistic linguistic GLDS method with consensus reaching

Due to the energy crisis, ammonia stands out as an efficient hydrogen energy carrier. However, liquid ammonia's nature of toxicity, corrosiveness, volatility, flammability, etc., make its storage highly risky. It is essential to analyze the risk of the ammonia storage facility for its safety improvement. Failure mode and effect analysis (FMEA) has been a popular risk analysis method due to its ease of implementation. However, traditional FMEA is insufficient to model the uncertainty of risk assessment information, enhance the consensus among experts, aggregate experts' risk evaluation information, and derive reliable risk analysis results. To address these limitations, we introduce a hybrid probabilistic linguistic FMEA framework to analyze failure risk in the ammonia storage facility. First, the probabilistic linguistic terms (PLTs) are introduced to express uncertain risk evaluation information of failure modes. Second, a risk acceptability-based consensus-reaching process is introduced to measure experts' consensus on each failure mode's risk and improve their consensus. Then, a consensus degree-based ordered weighted averaging operator is introduced to fuse experts' risk evaluation information, where experts' weight is determined by their consensus degree. Furthermore, the gained and lost dominance score method is improved on the basis of the expected value of the PLTs to prioritize failure modes' risk. Finally, a case study of the risk analysis for the ammonia storage facility is performed to show the efficiency of the extended FMEA. The case study indicated that condenser cooling water pump failure and failure of level transfer are the top two failure modes and have risk scores of 0.126 and 0.091, respectively.

Development and evaluation of the psychometric properties of a new measure of athlete insomnia: Insomnia in Response to Sports‐related Stress Test questionnaire

AbstractTo develop and validate the Insomnia in Response to Sports‐related Stress Test (IRSST) questionnaire, a new specific instrument with the goal of sensitively measuring vulnerability to sport‐specific stressful situations among elite athletes. Five hundred and thirty‐one competitive elite athletes (mean age = 17.6 ± 4.4 years) completed the Ford Insomnia Response to Stress Test (FIRST) questionnaire and the IRSST, a six‐item questionnaire developed to assess the level of sleep disturbance in response to the commonly experienced sport‐specific stressful situations. A development and validation process including substantive, structural, and external stages was used in the present study. One eigenvalue of the exploratory factor analyses was greater than 1.0 (i.e., 2.91, 48.52% of explained variance) whereas the scree test provided evidence for a one‐factor solution, with all the six items achieving a loading of 0.40 or higher on the factor. Cronbach alpha was 0.77 and provided evidence for the reliability of the IRSST score. The correlation between IRSST and FIRST scores was 0.47 (p &lt; 0.001, moderate effect size). These results provide strong evidence for construct validity, indicating that the IRSST is a promising scale for assessing the likelihood of sleep disruption due to sports‐related stressful situations. The results of reliability and correlational analyses provided further evidence of the promising psychometric properties of the IRSST. We believe that the IRSST could provide to the sport and sleep science communities a sleep screening tool for use in this unique population.

Scale Development Study on the Perception of Responsibility for Providing Professional Value for Prospective Teachers

In this study, it was aimed to develop a measurement tool with validity and reliability to determine the perceptions of academicians working in faculties of education about their responsibility to provide pre-service teachers with professional values. In order to create the necessary item pool for the scale, the literature was reviewed and in this context, a question pool of 44 items was created and expert opinions were taken. After the revisions in the items, Lawshe Technique was used to determine the content validity. 300 faculty members were administered the scale and a data set was obtained, which was analyzed for validity and reliability. Exploratory factor analysis (EFA) was used to reveal the construct validity of the scale, Cronbach's Alpha reliability coefficient, item-total score correlation and two-half test reliability methods were used to ensure the reliability of the scale, and lower 27%-upper 27% independent groups t-test was used for the discrimination of the scale. As a result of EFA, a 26-item, 3-factor structure emerged. This structure explains 59.647% of the total variance of the scale. Cronbach Alpha internal consistency coefficient for the reliability of the scale was found to be 0.952. It was observed that the item total correlation values were high and positive above 0.5 and the correlation values of all items were above 0.30, which is recommended as the lower limit. According to the results of the two-half test reliability analysis, the correlation coefficient between the equivalent halves was found to be 0.942. As a result of the t-test between the scores of the upper 27% and lower 27% groups in order to examine the discrimination of the scale items, it was found that the difference between the groups was significant at α=.000 level.

Simulation-free reliability analysis with importance sampling-based adaptive training physics-informed neural networks: Method and application to chloride penetration

Surrogate model-based reliability analysis aims at building a cheap-to-evaluate mathematical model as a substitute for the original performance function to enhance computational efficiency. Data-driven surrogate models have been popularly studied from a perspective of active learning. On the other hand, Physics-informed Neural Networks, called PINNs, have recently gained much attention as a physics-informed surrogate model to directly solve partial differential equations. Building on the capability of avoiding the simulation of traditional numerical solvers such as the finite element analysis, the PINN-based reliability analysis can achieve highly efficient simulation-free uncertainty quantification. This paper focuses on the development of the PINN-based reliability analysis method and its application in practical engineering applications. Reliability analysis with Importance Sampling-based Adaptive Training Physics-informed Neural Networks (IAT-PINN-RA) is proposed in this work. Compared with the existing PINN-based reliability analysis methods, IAT-PINN-RA introduces a pre-training stage for the establishment of the importance sampling distribution, and therefore achieves better performance when handling rare events. The modeling and reliability analysis of chloride penetration, which can pose serious challenges to the durability of concrete structures, are investigated. A practical example demonstrates the feasibility of using PINNs to model this physical phenomenon and the performance of the proposed method to achieve accurate and efficient reliability analysis results.

A Novel Molecularly Imprinted Quartz Crystal Microbalance Sensor Based on Erbium Molybdate Incorporating Sulfur-Doped Graphitic Carbon Nitride for Dimethoate Determination in Apple Juice Samples.

Dimethoate (DIM) as an organophosphorus pesticide is widely utilized especially in the cultivation of vegetables and fruits due to its killing effect on harmful insects. However, unconscious use of DIM in large amounts can also cause serious health problems. For these reasons, rapid and reliable detection of DIM from food samples is significant. In this study, a novel quartz crystal microbalance (QCM) sensor based on erbium molybdate incorporating sulfur-doped graphitic carbon nitride (EM/S-g-C3N4) and a molecularly imprinting polymer (MIP) was designed for DIM detection in apple juice samples. Firstly, an EM/S-g-C3N4 nanocomposite with high purity was prepared under hydrothermal conditions at high temperatures over a long period of time. After the modification of the EM/S-g-C3N4 nanocomposite on a QCM chip, the polymerization solution including N,N'-azobisisobutyronitrile (AIBN) as an initiator, ethylene glycol dimethacrylate (EGDMA) as a cross-linker, methacryloylamidoglutamic acid (MAGA) as a monomer, and DIM as an analyte was prepared. Then, the polymerization solution was dropped on an EM/S-g-C3N4 nanocomposite modified QCM chip and an ultraviolet polymerization process was applied for the formation of the DIM-imprinted polymers on the EM/S-g-C3N4 nanocomposite modified QCM chip. After the polymerization treatment, some characterization studies, including electrochemical, microscopic, and spectroscopic methods, were performed to illuminate the surface properties of the nanocomposite and the prepared QCM sensor. The values of the limit of quantification (LOQ) and the detection limit (LOD) of the prepared QCM sensor were as 1.0 × 10-9 M and 3.3 × 10-10 M, respectively. In addition, high selectivity, stability, reproducibility, and repeatability of the developed sensor was observed, providing highly reliable analysis results. Finally, thanks to the prepared sensor, it may be possible to detect pesticides from different food and environmental samples in the future.

Finite element analysis of the package structure of HgCdTe infrared focal plane array detector

Reliable material parameters, correct boundary condition settings, and a reasonably simplified numerical model are key to obtain reliable and reasonable analysis results. A new finite element analysis model for the HgCdTe infrared focal plane array detector is presented, which includes the core column. The thermal stress and strain of the new model and current model are analyzed, and their distribution laws are obtained. The results are compared, and the reasons are analyzed, which can provide some references for the simulation of infrared detector package structure.

Sensitivity evaluation of machine learning-based calibrated transportation mode choice models: A case study of Alexandria City, Egypt

Intelligent methods including Machine Learning (ML) techniques have been increasingly employed in transportation mode choice modeling, which is more complex than other demand models, since it has to reliably and accurately reflect a wide range of related categorical and continuous variables, concerning the travelers, transportation system, and trip characteristics. ML techniques can capture such complex relationships. So that, they can provide a more nuanced understanding of the travelers’ decision process. Most research studies focused mainly on the evaluation of the model accuracy, where little has been done to evaluate the models’ performance toward transport attributes. This research aims to calibrate the transportation choice models using ML techniques, then conduct a comparison with the Multinomial Logit (MNL) model to identify the impact on the model accuracy and performance and quantify to what extent the ML models are sensitive to transport policies compared to the traditional MNL model. To this end, eight ML classifiers were examined. As a case study, the models were calibrated to reflect the choice behavior of trip makers in Alexandria City, Egypt. The models were successfully calibrated with satisfying accuracy; however, the ML models have better calibration results in terms of predictability, outperforming the MNL model, where the GBDT classifier records the best prediction accuracy. Finally, the sensitivity analysis test was performed to quantify the elasticity of the models to transport policies. The results show the ML models’ structure is more comprehensively and accurately built than the MNL model providing better indicative and reliable sensitivity analysis results.

Point and interval forecasting for wine prices: an approach based on artificial intelligence

Purpose With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to develop a precise and effective wine price point and interval forecasting model. Design/methodology/approach The proposed forecast model uses an improved hybrid kernel extreme learning machine with an attention mechanism and a multi-objective swarm intelligent optimization algorithm to produce more accurate price estimates. To the best of the authors’ knowledge, this is the first attempt at applying artificial intelligence techniques to improve wine price prediction. Additionally, an effective method for predicting price intervals was constructed by leveraging the characteristics of the error distribution. This approach facilitates quantifying the uncertainty of wine price fluctuations, thus rendering decision-making by relevant practitioners more reliable and controllable. Findings The empirical findings indicated that the proposed forecast model provides accurate wine price predictions and reliable uncertainty analysis results. Compared with the benchmark models, the proposed model exhibited superiority in both one-step- and multi-step-ahead forecasts. Meanwhile, the model provides new evidence from artificial intelligence to explain wine prices and understand their driving factors. Originality/value This study is a pioneering attempt to evaluate the applicability and effectiveness of advanced artificial intelligence techniques in wine price forecasts. The proposed forecast model not only provides useful options for wine price forecasting but also introduces an innovative addition to existing forecasting research methods and literature.

THE EXPANDED DIGITAL MEDIA EMPOWERMENT ON SECONDARY EDUCATIONAL SETTING

Background: Digital media empowerment by ensuring equitable access to digital technologies and safeguarding against digital divide issues. Legal measures also ensure that digital platforms are not misused for spreading misinformation or engaging in unlawful activities. This study expanded the digital media empowerment construct for Jakarta's senior high school students to eight dimensions, blending awareness, motivation, technical access, empowerment, and gratification dimension with three dimensions of social contract utilitarianism, egalitarianism, and real equality of opportunity.&#x0D; &#x0D; Method: This study applied an explanatory quantitative approach and conducted a survey. Six hundred respondents were online surveyed and analyzed to confirm the integration of eight dimensions of digital media empowerment. Eight dimensions were validated by Person’s correlation of validity and assessed by Cronbach’s Alpha of reliability. The integrated dimension was tested as a hypothesis by Confirmatory Factor Analysis by showing the value of Kaiser-Meyer-Olkin Measure of Sampling and Barlett’s Test of Sphericity.&#x0D; &#x0D; Results: The result of validity, reliability, and confirmatory factor analysis proved the integration of eight dimensions of digital media empowerment. The results highlighted a significant correlation among all eight dimensions with the digital media empowerment construct. The gratifications dimension is the most dominant dimension of digital media empowerment from students’ perspectives on digital technology usage.&#x0D; &#x0D; Conclusion: The integration offers a more holistic understanding of justice distribution in the secondary educational setting. It underscores the importance of considering both technological and ethical-social factors in shaping students' digital experiences and competencies, paving the way for more targeted and sustainable educational development in the digital era.

Behaviour and design of duplex stainless steel bolted connections failing in block shear

Duplex stainless steel (DSS) is an emerging construction material for structural engineering, which is featured with high mechanical strength and superior corrosion resistance. Compared with considerable research on DSS structural members, available research is relatively limited for structural joints/connections between these members. In line with this concern, this paper presents a comprehensive experimental and numerical study of duplex stainless steel bolted connections (DSSBCs), focusing on the behaviour and design related to block shear failure. Eleven specimens are tested to investigate the effect of different bolt arrangements on the block shear behaviour. Furthermore, a detailed numerical study was performed as a supplement to the experimental tests, where the anisotropic mechanical properties of DSS are considered in the finite element modelling. Based on the test and analysis results, it is found that the block shear failure mode of DSSBCs resembles that of carbon steel bolted connections, which can be characterised as necking of the tensile section and yielding of the shear sections. Using the experimental and numerical data obtained in this and previous studies, the applicability of various block shear design methods to stainless steel bolted connections is assessed. An updated design method is proposed for predicting the block shear capacity of duplex and austenitic stainless steel bolted connections. A proper partial safety factor/resistance factor is suggested for the proposed method based on the results of reliability analyses.

Kelayakan Media Interaktif Berbasis Nearpod pada Materi Sistem Ekskresi di Kelas XI SMA

The rapid development of information technology in the era of globalization has changed the paradigm of society. Global demands for utilizing technology also influence education, which is always aligned as a form of effort to improve the quality of education. Nearpod is a media in the form of a web application that allows students and educators to interact face-to-face or remotely, and is able to provide innovative, interactive and effective learning experiences. The aim of this research is to develop nearpod-based interactive learning media on excretory system material in class XI. The method used is research and development with the ADDIE development model limited to the development stage. Validation was carried out by five validators with three aspects of media assessment, namely language, material and media aspects. The validator's assessment was tested using validity analysis using Aiken and reliability using ICC, and obtained a validity analysis result of 0.92 which was in the very high validity category, and a reliability analysis result of 0.796 which was in the good category, so it can be concluded that nearpod media is valid and feasible used in learning.

DEVELOPING EUDAIMONIC SELF-REGULATION SCALE (ESRS): VALIDITY AND RELIABILITY STUDY

The purpose of this current study is to develop the Eudaimonic Self-Regulation Scale, which measures the regulation of emotions, cognitions, behaviors and interpersonal relationships in order to reach the eudaimonia explained by ancient Greek philosopher Aristotle. Eudaimonic Self-Regulation Scale, Flourishing Scale, Mindful Attention and Awareness Scale, Personal Growth Initiative Scale, and the General Self-Efficacy Scale were used as measurement instruments. Participants of the study consisted of 1042 adults between the ages of 18 and 65, including 3 different sample groups. As a result of Exploratory Factor Analysis (EFA) of Eudaimonic Self Regulation Scale, a 10-factor structure model with 43 items, which explained % 57.93 of the total variance was obtained. According to the Confirmatory Factor Analysis (CFA) results, the factor loadings ranged from .48 to .88. In addition, model fit indices were satisfactory (χ2=2395.39; df=815, χ2/df=2.93, RMSEA=0.054, CFI=0.97, IFI=0.97, SRMR=0.050). Cronbach’s α values of sub-scales ranged from .75 to .89. In terms of convergent validity, eudaimonic self-regulation indicated significant correlations with psychological well-being, mindfulness, self-efficacy, and personal growth initiative. According to the results of test-retest reliability analysis, the intraclass correlation coefficients ranged from .82 to .94, Pearson's correlation coefficients were between .71 and .88. These results indicated that this scale was a valid and reliable instrument to assess eudaimonic self-regulation in the relevant researches.

Testing and design of cold-formed high strength steel square hollow section columns

An experimental and numerical investigation into the flexural buckling behaviour of cold-formed (CF) high-strength steel (HSS) square hollow section (SHS) members is reported in this paper. A series of 12 flexural buckling tests were conducted on S700 and S900 CF SHS columns. Finite element (FE) models were developed to simulate the experimental observations, which were utilized in a parametric study encompassing a broader range of steel grades and specimen geometries. Subsequently, the current buckling curves in European, North American, and Australian codes was evaluated through reliability analyses. Meanwhile, the effective width method (EWM) and the modified generalized slenderness-based resistance method (GRSM) were compared for slender cross-sections. According to the results of reliability analyses, the modified buckling curves were proposed for CF HSS SHS columns.