Error Analysis Of Method Research Articles

An investigation into accidents in laboratories in universities in China caused by human error: A study based on improved CREAM and SPAR-H

Although considerable research has been devoted to improving safety in university laboratories, accidents, in that environment, have still occurred frequently at the cost of serious injury or even death of laboratory personnel. Currently, few Human Reliability Analyses (HRA) have been conducted with respect to a university laboratory. The aim of the research was to conduct a reliability study relating to human behaviour in a university laboratory to explore quantitatively the causes and influencing factors relating to the frequency of laboratory accidents. Improved Cognitive Reliability and Error Analysis Method (CREAM) and improved Standardized Plant Analysis Risk HRA (SPAR-H) were employed to assess Human Error Probability (HEP) of 23 subjects. The HEP calculated through improved CREAM proved more accurate than results obtained through improved SPAR-H. Unexpectedly, the results demonstrated that under similar environmental conditions, the HEP of subjects did not decrease with an increase in educational background, including additional experimental time and experience. Moreover, environmental conditions exerted greater impact on personnel reliability than Human Inherent Factors (HIFs) in laboratories. It is anticipated that the study would provide valuable insights, in respect of research methods, and to serve as a practical basis for lowering the accident rate in university laboratories.

A hybrid human reliability analysis approach for a remotely-controlled maritime autonomous surface ship (MASS- degree 3) operation

Maritime autonomous surface ships (MASS) are one of the hot topics in maritime transportation even though they bring many challenges in terms of safety, security, and environment. This paper tackles the safety-related challenges of remotely controlled ships without seafarers on board but controlled at the shore. In this context, the reliability of the operator is of paramount importance for safe and efficient MASS operation. This paper performs systematic human reliability analysis for the operator of MASS (for degree 3) under the Bayesian belief network (BBN) and evidential reasoning (ER)- cognitive reliability and error analysis method (CREAM) approach. In the model, BBN is capable of determining the probability distribution of Contextual Control Modes in CREAM, while ER tackles the uncertainty and subjectivity of expert judgments. The outcome of the paper shows that the human reliability for remote control MASS operation is 8.88E-01. Besides its robust theoretical background, the paper will provide the utmost contributions to operators, managers, safety inspectors, and ship owners of MASS for safer and reliable operations.

Reliability assessment of man‐machine systems subject to probabilistic common cause errors

AbstractThe occurrence of probabilistic common cause errors (PCCEs) in man‐machine systems can lead to multiple human errors being affected by common causes and will contribute greatly to the reliability of the system. In this paper, A reliability modeling method based on event tree (ET)‐fault tree (FT) model for man‐machine systems subjected to PCCEs is proposed. Under the influence of PCCEs, risk factors in the system are not independent, and human errors affected by the same common cause will occur with different probabilities. To describe the dependencies among risk factors, a PCCE gate is proposed to extend FTs in the ET‐FT model. To analyze the impact of common causes on the human error probabilities and quantify the extended FT, an explicit method and an implicit method based on the Cognitive Reliability and Error Analysis Method are proposed. The proposed quantification methods consider the different relationships among multiple common causes in a single model. Finally, the proposed methods are validated in the reliability assessment of the emergency response system under malfunction of the solar wing mechanism.

Optimizing Space Telescopes’ Thermal Performance through Uncertainty Analysis: Identification of Critical Parameters and Shaping Test Strategy Development

The integration of uncertainty analysis methodologies allows for improving design efficiency, particularly in the context of instruments that demand precise pointing accuracy, such as space telescopes. Focusing on the VINIS Earth observation telescope developed by the Instituto de Astrofísica de Canarias (IAC), this paper reports an uncertainty analysis on a thermal model aimed at improving cost savings in the future testing phases. The primary objective was to identify critical parameters impacting thermal performance and reduce overdesign. Employing the Statistical Error Analysis (SEA) method across several operational scenarios, the research identifies key factors, including the Earth’s infrared temperature and albedo, and the spacecraft’s attitude and environmental conditions, as the variables with major influences on the system’s thermal performance. Ultimately, the findings suggest that uncertainty-based analysis is a potent tool for guiding thermal control system design in space platforms, promoting efficiency and reliability. This methodology not only provides a framework for optimizing thermal design and testing in space missions but also ensures that instruments like the VINIS telescope maintain optimal operating temperatures in diverse space environments, thereby increasing mission robustness and enabling precise resource allocation.

Analyzing human reliability for the operation of cargo oil pump using fuzzy CREAM extended Bayesian Network (BN)

Crude oil cargo discharging operations can be performed by cargo oil pumps in tanker ships. Considering the harmful effects of crude oil, any failure during the cargo oil pump operation may pose acute hazards such as temperature and pressure increase in pipelines, leakage, fire, and following undesired events that lead to marine environmental pollution and toxic effects to humans. The process is managed by the ship's crew, and it requires following the operational steps in order. This paper aims at performing a detailed human reliability analysis (HRA) for the operational process of cargo oil pumps on a tanker ship. In the paper, the Cognitive Reliability and Error Analysis Method (CREAM) is used to calculate human error probability under a fuzzy set which deals with the uncertainty and ambiguity of the CPC (Common Performance Condition). The Bayesian Network (BN) approach is adopted to determine the probability distribution of the control modes in reliability assessment. In view of the findings, the human reliability for the entire process of cargo oil pump operation on tanker ship is found 8.82E-01. The outcomes of the paper provide valuable insight into the improvement of tanker safety in shipboard operation and performance reliability assessment.

A Methodology for Ship Cabin Equipment Layout Considering Human Factor Reliability Optimization

_ The paper proposes an innovative methodology of Human Cognitive Reliability- Cognitive Reliability and Error Analysis Method (HCR-CREAM) coupled with A* search and genetic algorithm (GA) to tackle ship cabin equipment layout considering human factor reliability optimization with the goal of minimizing human error probability (HEP) subjected to practical requirements. After establishing the mathematical model of cabin equipment inspection tasks in ship cabin equipment layout problem through HCR-CREAM and equipment geometric simplification, a method of the horizontal movement based on minimum distance is presented to avoid the equipment overlapping, then A* search is used for planning inspection paths and GA with selection, crossover, and mutation operators is applied to solve equipment layout results. A case of equipment layout in a certain ship engine room has been taken to carry out parameter sampling experiments by Latin Hypercube for GA. The results show the solution effect of GA is less affected by its parameter variation. And through the comparison with the initial equipment layout, the indicators influencing the HEP of the optimized result have been improved, thus significantly reducing HEP. Keywords ship cabin equipment layout; human factor reliability optimization; HCRCREAM; A* search; genetic algorithm

Position and Orientation System Error Analysis and Motion Compensation Method Based on Acceleration Information for Circular Synthetic Aperture Radar

Circular synthetic aperture radar (CSAR) possesses the capability of multi-angle observation, breaking through the geometric observation constraints of traditional strip SAR and holding the potential for three-dimensional imaging. Its sub-wavelength level of planar resolution, resulting from a long synthetic aperture, makes CSAR highly valuable in the field of high-precision mapping. However, the motion geometry of CSAR is more intricate compared to traditional strip SAR, demanding high precision from navigation systems. The accumulation of errors over the long synthetic aperture time cannot be overlooked. CSAR exhibits significant coupling between the range and azimuth directions, making traditional motion compensation methods based on linear SAR unsuitable for direct application in CSAR. The dynamic nature of flight, with its continuous changes in attitude, introduces a significant deformation error between the non-rigidly connected Inertial Measurement Unit (IMU) and the Global Positioning System (GPS). This deformation error makes it difficult to accurately obtain radar position information, resulting in imaging defocus. The research in this article uncovers a correlation between the deformation error and radial acceleration. Leveraging this insight, we propose utilizing radial acceleration to estimate residual motion errors. This paper delves into the analysis of Position and Orientation System (POS) errors, presenting a novel high-resolution CSAR motion compensation method based on airborne platform acceleration information. Once the system deformation parameters are calibrated using point targets, the deformation error can be directly calculated and compensated based on the acceleration information, ultimately resulting in the generation of a high-resolution image. In this paper, the effectiveness of the method is verified with airborne flight test data. This method can compensate for the deformation error and effectively improve the peak sidelobe ratio and integral sidelobe ratio of the target, thus improving image quality. The introduction of acceleration information provides new means and methods for high-resolution CSAR imaging.

ERROR ANALYSIS IN WRITING DESCRIPTIVE TEXT

Abstract: The objectives of this research were to figure out and describe the types of grammatical simple present tense errors are found in the one of vocational high school in West Kalimantan 2022/2023. This research used qualitative case study research to analysis the students’ writing ability in descriptive text using present tense based on the four level type of errors: omission, addition, selection and ordering for the one of vocational high school in West Kalimantan. It was conducted on February 2023. The researcher took 12 students as the sample. The subjects of this research was the the one of vocational high school in West Kalimantan 2022/2023 academic year. To collect the data, the researcher used essay writing test with students. After collected the dataafrom the subjects the researcher analysis the dataaby using error analysis method to analyzed qualitative data. The resultaof thisaresearch showedathat the students level of writing skills in descriptive text using present tense is average. The result of this research showed that the students most errors was in error of selection, The most difficult category in writing was in grammatical problem therefore the students should foccus and pay attention on terms of identify reference without ignoring the other aspect of rules of language. Keyword: Error analysis, writing, descriptive text

Operational reliability analysis of remote operated vehicle based on dynamic Bayesian network synthesis method

In this study, we propose a reliability framework that combines the GO method with fault tree analysis and integrates human factor reliability analysis. Taking the application of remotely operated vehicle (ROV) in underwater oil and gas production as an example, a reliability model of ROV operation process is established. The human reliability in the ROV operation process is analyzed on the basis of Cognitive Reliability and Error Analysis Method (CREAM) extension approach. The influence of human factor reliability and equipment reliability on the system is compared and analyzed. The importance of each operation step is also compared and analyzed. A sensitivity analysis of the ROV during operation is performed. This study provides a theoretical basis for the improvement and maintenance of the operational reliability of ROV. The proposed reliability modeling approach solves the reliability analysis problem of large and complex operating systems.

Multipath Branch Model‐Aided Differential Evolution Algorithm Based on Regional Error

This paper introduces a general approach to multiobjective optimization design. In surrogate model‐aided algorithms, the prediction accuracy of the surrogate model plays a key point in determining the optimization results. In order to overcome the defect of a single model in the adaptive antenna optimization problem and improving the efficiency and accuracy of the model, a method called multipath branching model‐aided differential evolution algorithm analysis (MMDEA‐RE) is proposed. The key innovations include: A novel combination model integrating Gaussian process, multilayer perceptron, and radial basis function. Compared with the traditional single model, the combination model can deal with complex and diverse optimization problems more effectively and has stronger robustness and versatility. A method of regional error analysis near the prediction point is proposed, which can select a suitable model with high prediction accuracy after a few iterations. The effectiveness and superiority of MMDEA‐RE are demonstrated by the optimization of two linear array antennas and one 5G antenna. The contribution of this study is to improve the accuracy and generality of surrogate models in antenna design. This proposed method has practical implications and potential applications for improving antenna optimization techniques.

A high-precision modeling and error analysis method for mountainous and canyon areas based on TLS and UAV photogrammetry

A high-precision modeling and error analysis method for mountainous and canyon areas based on TLS and UAV photogrammetry

Analysis of Repetitive Positioning Accuracy of Parallel Mechanisms Based on Monte Carlo Method

Based on the inverse kinematics model of the Stewart parallel mechanism, a motion platform pose error model was constructed through differential transformation. The error model shows that the motion platform pose error comes from the length error of 6 struts and the position error of 12 hinge centers, with a total of 42 error terms. Monte Carlo simulation was used to analyze the effects of struts length error on the pose error of the moving platform. The results show that when the length error of the struts follows a normal distribution, the posture error of the moving platform approximately follows a normal distribution. Monte Carlo simulation is a highly effective error analysis method that can analyze the error distribution pattern of the mechanism before processing and assembly, which provides a method for error analysis of Stewart parallel mechanisms.

Analysis and compensation of stop-and-go approximation in high-resolution spaceborne synthetic aperture radar

ABSTRACT With the advancement of spaceborne synthetic aperture radar (SAR) resolution, the conventional stop-and-go approximation-based motion model is no longer suitable for high-resolution imaging algorithms. This paper conducts a comprehensive analysis of the approximation errors resulting from the stop-and-go approximation and proposes corresponding compensation methods. Firstly, an accurate echo model based on continuous platform motion is derived from the SAR geometry configuration. The impact of these errors on range and azimuth imaging is analysed from a spectral perspective, and the applicable boundary conditions are examined. Subsequently, compensation methods are proposed to eliminate the introduced approximation errors, addressing both”fast time” and”slow time” effects, thus enabling high-resolution imaging through improvements in traditional imaging algorithms. Experimental simulations validate the effectiveness of the error analysis and compensation methods, using X-band low Earth orbit SAR as an illustrative example. The proposed methods are not only compatible with existing mature imaging algorithms, but the analytical approach and compensation methods are also applicable to SAR systems operating on different carrier frequencies, orbits, and platforms.

مشكلات الكتابة العربية وحلولها لطلاب الصف السابع بالمدرسة المتوسطة الاسلامية الأهلية "السلام" بانجيلان طوبان

This research aims to analyze the errors in Arabic writing among 7th-grade students at MTS As-Salam. Arabic language plays a crucial role in understanding and using Islamic religious texts and is one of the key subjects in secondary schools. However, many students face difficulties in learning Arabic, especially in writing.
 The research was conducted using an error analysis method. Data were obtained from the writings of 7th-grade students at MTS As-Salam throughout one semester. The results of this analysis provide an overview of the types of errors commonly made by students in Arabic writing, as well as their contributing factors.
 Based on the research findings, several common types of errors were identified, such as errors in using Arabic letters (huruf hijaiyah), punctuation, affixes, and sentence structures. These errors may hinder the comprehension and interpretation of the texts they write. Contributing factors to these errors include a lack of understanding of Arabic writing rules, insufficient practical writing exercises, and the influence of different native languages.
 Therefore, further efforts are needed to improve the quality of Arabic language teaching at MTS As-Salam. Teachers should provide more practical exercises in Arabic writing and offer a deeper understanding of writing rules. Additionally, collaboration between teachers and parents is essential to help students enhance their Arabic language skills outside the school environment.
 This research is expected to make a positive contribution in understanding and addressing Arabic writing errors among 7th-grade students at MTS As-Salam. By identifying common errors and their causes, it is hoped that the school can implement more effective learning strategies focused on enhancing students' Arabic language proficiency.

Error analysis and correction method of multi-core fiber sensing

To meet the application requirements of accurate shape sensing for biomedical robotics and flexible morphing structure of aircraft etc, the error analysis and correction method for multi-core fiber is proposed. First, the relationship between the central wavelength shift and curvature of the multi-core fiber is analyzed which is based on the principle of multi-core fiber shape sensing, and a temperature decoupling method was researched. Considering the influence of the fiber structural parameters on curvature sensing, which is simulated by using the Monte Carlo method, and the simulation results show a strong influence among them. Next, to reduce the sensing errors introduced by the structural parameters, an error correction method based on regularized multilayer perceptron (MLP) networks is investigated, the proposed method does not require precise structural parameters of the multi-core fiber. Finally, some experiments with different curvatures are carried out, the results showed that the maximum root mean square error (RMSE) decreases from 2.03 m−1 to 0.007 m−1, and the minimum RMSE decreases from 0.01 m−1 to 0.001 m−1. The method this paper proposed has potential applications in shape sensing in the fields of biomedical engineering and aerospace.

Evaluation of Written Expression Skills of Students from Turkish World through Error Analysis

The aim of the research is to evaluate the written expression skills of the students from the Turkish world and communities that are studying at Hoca Ahmet Yesevi International Turkish-Kazakh University by using the error analysis method and to develop a solution proposal for the wrong sources revealed. For this purpose, the composition was printed to evaluate the written expression skills of the students, and negotiations were held so that the wrong sources could be revealed. The results of the research showed that the mistakes most frequently made by Turkish students in written expression studies are spelling and punctuation mistakes and misuse of words. The main causes of these mistakes were determined to be excessive generalizations, not knowing the rule constraints and the main negative transfers. Another category created from student spelling mistakes is mistakes made in word selection. The situation repeated by almost all students in this category is the negative transmission caused by the mother tongue and the incorrect use of words caused by not knowing the rule restrictions. After that, the most repeated mistakes and their causes, respectively, are the unnecessary use of words in sentences due to developing incorrect concepts, excessive generalization and word omissions due to ignorance of rule restrictions, word errors brought from the mother tongue due to negative transmission from the mother tongue, and errors in the use of words that have passed from foreign languages to Turkish.

Peran Analisis Kesalahan Berbahasa Dalam Meningkatkan Kemampuan Menulis

This article discusses the important role of language error analysis in improving one's writing skills. Language error analysis plays a crucial role in the language learning process, especially in the development of writing skills. By understanding the errors made in writing, one can identify frequently occurring error patterns and address them. The language error analysis method not only helps correct grammatical errors, but also opens up a deeper understanding of better language structure. With a better understanding of mistakes made, one can improve clarity, coherence, and cohesion in one's writing. This article also highlights how the use of language error analysis techniques in the learning process can provide constructive feedback to writers. Thus, this article emphasizes the importance of language error analysis in supporting the improvement of one's writing ability.

Pedestrian crash causation analysis and active safety system calibration

Over 20 % of global crash fatalities involve pedestrians, but pedestrian crash causation and pedestrian protection systems have not been thoroughly developed or reliably tested. To understand the causation characteristics of pedestrian crashes, 398 pedestrian crashes were extracted from the China in-depth accident study (CIDAS), and most of these crashes were aggregated into five scenarios. The two scenarios with the highest proportion of crashes were analyzed by the driving reliability and error analysis method (DREAM) to identify high-risk causation patterns. From these patterns, three main contributing factors were identified: 1) extremely environmental light disturbance; 2) distracted driving caused by drivers’ own thoughts; 3) drivers violating pedestrian yield law. Based on these patterns and factors, a pedestrian protection system was designed. It consists of a forward vision sensor and radar to sense the environment and the three-stage autonomous emergency braking (AEB) algorithm to automatically avoid pedestrian collisions. Crash scenarios from CIDAS data were recreated in MATLAB Simulink to test the pedestrian protection system proposed in this study. This system was found to reduce pedestrian crashes by more than 90 %. The optimal parameters for three AEB stages were obtained, with decelerations of 0.2 g, 0.3 g, and 0.6 g. This study designed an active safety system based on causation analysis of the vehicle–pedestrian crashes and calibrated the AEB algorithm of it, thus providing reference and insight for further development of pedestrian protection systems.

A Study of the Effectiveness of Corpus-Assisted Collocation Teaching on Improving College Students’ English Writing Ability Based on Random Matrix Theory

Abstract This paper presents a semantic analysis of corpus-assisted collocation teaching based on the random matrix theory, taking into account the characteristics of the computer corpus. The construction of a word-document matrix is based on the potential semantic analysis of the corpus and the intrinsic relationships between words and documents. The aggregation and combination relations of collocation, i.e., the lexicon of word meanings, are used to calculate affirmative sentence similarity, incorporating dependent syntactic and semantic analysis. The error analysis method was applied to the teaching of collocations to analyze the common types of errors and the variability of writing errors in English writing and to discuss the correlation between the performance of English composition and the number of collocations used. The correlation coefficient between composition scores and the number of collocations in compositions was 0.924, and the composition scores of college students had a positive linear relationship with the number of collocations.

Enhanced adsorption of toluene using nano silver-modified activated carbon derived from Ricinodendron heudolitii shells: A comparative study"

Considering the risk of toluene exposure in water resources, researchers have been prompted to conduct experiments to remove them from aqueous solutions. This study investigates the use of Ricinodendron Heudolitii shells as a precursor for extracting an adsorbent (activated carbon) through chemical activation with phosphoric acid (H3PO4). The obtained activated carbon was then modified with Quercetagetin stabilized silver nanoparticles (Qtg-Ag/AC), and characterized for thermogravimetric analysis (TGA), Fourier-transformed infrared spectroscopy (FTIR), diffraction light scattering, Powder XRD, and scanning electron microscopy (SEM/EDX). The adsorption characteristics such as kinetics, mechanism and isotherms of toluene were studied. The kinetic data were analyzed using a pseudo-first-order, pseudo-second-order kinetic equation elovick and intraparticle diffusion model. The pseudo-first-order and pseudo-second-order kinetic model describes experimental data better than elovich and intraparticle kinetic model. The results show that Qtg-Ag/AC exhibits superior adsorption capacity (39.352 mg g−1) compared to AC (30.093 mg g−1). Langmuir, Freundlich and Tenkim model for AC and Qtg-Ag/AC described the equilibrium data better. In order to determine the best-fit kinetic model for each system, two error analysis methods, namely, chi-square (χ2) and residual mean squared error (RMSE) were used to evaluate the data. The outcomes of the study demonstrate that our modified (Qtg-Ag/AC) can be a good prototype for the adsorption of toluene from wastewater.