Error Items Research Articles

Enterprise Operating State Evaluation Based on Association Rule Algorithm and Data Set.

In order to further improve the evaluation quality of enterprise operating efficiency, reduce the error items and invalid items of partition, and improve the objectivity of operating condition evaluation, this study takes listed enterprises as an example and proposes an evaluation method of operating efficiency based on association rule algorithm and data set. In this method, the results of operating efficiency are scientifically analyzed from horizontal and vertical dimensions. The operating cost of total assets of listed companies is taken as indicators, and the correlation test is carried out by Kendall's tau_b. From the longitudinal comparison results, it can be seen that only 12 of the 19 enterprises in the study have small-scale changes and increase year by year, accounting for 63.16%. At the same time, there are also 6 enterprises with an overall trend of decline, which objectively reflects the reasonable operation status and operation scale of enterprises in the study.

Prediction of CORS Water Vapor Values Based on the CEEMDAN and ARIMA-LSTM Combination Model

By relying on the advantages of a uniform site distribution and continuous observation of the Continuously Operating Reference Stations (CORS) system, real-time high-precision Global Navigation Satellite System/Precipitable Water Vapor (GNSS/PWV) data interpretation can be carried out to achieve accurate monitoring of regional water vapor changes. The study of the atmospheric water vapor content and distribution changes is the basis for the realization of rainfall forecasting and water vapor circulation research. Such research can provide data support for the effective forecasting of regional precipitation in megacities and the construction of a more sensitive flood prevention and warning system. Nowadays, a single model is often adopted for GNSS/PWV time series. This makes it challenging to match the high randomness characteristic of water vapor change. This study proposes a hybrid model that takes into account the linear and nonlinear aspects of water vapor data by using complete empirical mode decomposition (CEEMDAN) of adaptive noise, differential autoregressive integrated moving average (ARIMA), and the long-short-term memory network (LSTM). The CEEMDAN is used to decompose the water vapor data series. Then, the high- and low-frequency data are modeled separately, reducing the sequence’s complexity and non-stationarity. In selecting the prediction model, we use the ARIMA model for the high-frequency series and the ARIMA–GWO–LSTM ensemble model for the low-frequency sub-series and residual series. The model is verified using GNSS/PWV time series data collected at the Hong Kong CORS station in July 2021. The results show the following: (1) The LSTM model optimized by the grey wolf optimization algorithm (GWO) is comparable with the single LSTM model in the low-frequency sequence prediction process, and the error items are reduced by 30% after calculation. (2) During the process from CEEMDAN decomposition to the use of the combination model for prediction, the accuracy evaluation indexes of the station increase by more than 20%. The interpolation method can accurately determine the regional water vapor spatial variation, which is of practical significance for local rainfall forecasting. High-frequency data obtained by CEEMDAN decomposition demonstrate the dramatic changes in water vapor before and after the rainfall, which can provide ideas for improving the accuracy of rainfall forecasting.

The Impact of Standardized Health Education in Patients with Ischemic Stroke on Patient Management Satisfaction and Quality of Clinical Management Services.

Aim Ischemic stroke is a common brain disease, which seriously affects the quality of life of patients. The purpose of this study was to evaluate the impact of the application of standardized health education in ischemic stroke patients on patient management satisfaction and clinical management service quality. Methods 220 patients with ischemic stroke were chosen for study target. The research objects were randomly divided into control group (n = 110) and education group (n = 110) by odd even number draw lots. The control group conducted conventional treatment; on the basis of the control group, the education group received standardized health education. The impact of the application of standardized health education in patients with ischemic stroke on patient management satisfaction and clinical management service quality was analyzed. Results The number of health error items in the two groups decreased significantly after 2 months and 3 months of treatment, contrast to before admission, and the number of health error items in the education group was lower than that in the control group, and the difference was statistically significant. After 3 months of treatment, the daily activity score increased and the neurological function score decreased in the two groups, and the daily activity score in the education group was higher than that in the control group, and the neurological function score was lower than that in the control group; the difference was statistically significant. The satisfaction scores of patients in the education group in different aspects such as staff working attitude, health management, diet management, and environmental management were higher than those in the control group, and the disparity was obvious. Conclusion The application of standardized health education in patients with ischemic stroke has certain clinical value.

Mist-edge-fog-cloud computing system for geometric and thermal error prediction and compensation of worm gear machine tools based on ONT-GCN spatial–temporal model

The geometric precision of worm gears (WGs) determines the service performance and life of precision machine tools, indexing turntables and other equipment. The machining accuracy of worm gear machine tools (WGMTs) is the core to guarantee the geometric precision of WGs, and is greatly affected by the thermal and geometric errors. To improve the machining accuracy of WGMTs, the thermal and geometric errors should be controlled and compensated. But the control system has a poor real-time performance, and the synchronous control of the geometric and thermal errors cannot be currently achieved, and the thermal error model has a low prediction accuracy and low robustness. To make up for the above gap, a mist-edge-fog-cloud computing system is designed for the error prediction and compensation to relieve the bandwidth pressure of the industrial Internet. Moreover, a sensor network composed of multiple sensors is constructed to obtain the thermal information, and then the ordered neuron temporal-graph convolutional network (ONT-GCN) is proposed based on the ordered neuron-long short term memory network (ON-LSTMN) and graph convolutional network (GCN) for the first time to conduct the spatial and temporal modeling of the thermal error data. The interaction among multiple sensors is explicitly considered, and the dependence of the temporal information of the thermal error data on and spatial information of sensors is taken into account. Besides, to realize the error control, the mapping relationship between the tooth surface error and geometric-thermal errors is established. The error mapping model converts 51 geometric errors and 4 thermal errors into the spatial errors of the hob. Moreover, the sensitivity of errors is analyzed, and then the key error items that affect the geometric precision of the tooth surface are identified and compensated. The results show that the ONT-GCN is superior to traditional time-series modeling methods and that the mist-edge-fog-cloud computing system can effectively shorten the executing time compared with other system frameworks, and can improve the machining accuracy of WGMTs.

An Error Analysis on Past Tense in Recount Text Written by Lower Secondary School Students

Highlighting the importance of accuracy in grammar use, this study is interested to investigate the students’ error in English writing. Based on the preliminary study, the students seemed to have difficulty in conducting the sentences by using simple past. Therefore, this research explored more the errors on using simple past tense in writing recount text. The aim of this thesis was to know the types of error, to find out the dominant error, and to find out the sources of error. The research was a qualitative descriptive research. The subjects of this research were the thirty students of junior high school at eight grade. In collecting data, this research used a writing task about their unforgettable experiences which aimed to identify the errors produced by students in using the simple past in writing recount texts based on the linguistics category taxonomy and sources of error based on Ellis’ theory. The results implied that there were 13 types of errors made by students. The most dominant types of errors were miss-election of V-1 in the past event with the total number of error 56 items. Based on the results of the types of error was found sources of error that there were 96 items of interference errors, 68 items of intralingual errors, and 83 items of developmental errors.

Precision Analysis of Noncircular Gears Based on CNC Machining Technology under Cloud Computing Platform

In order to solve the problem of machining error of noncircular gears, a method based on the analysis and research of the accuracy of noncircular gears based on CNC machining technology under the cloud computing platform is proposed to further improve the technical accuracy of noncircular gears. The error and error items are analyzed mainly, and a model framework based on cloud computing platform is proposed on this basis. The architecture of the system is deeply analyzed, focusing on the dynamic integration method of gear cloud measurement system resources based on cloud platform, building a gear cloud measurement system based on cloud computing platform, and testing needs to use Hadoop to install the software that needs to be prepared: virtual machine version, VMware Workstation-14.0.0 build-6661328, Linux version. The results show that the technical support of the cloud computing platform can effectively improve the accuracy of noncircular gears.

An Automatic Error Correction Method for English Composition Grammar Based on Multilayer Perceptron

In order to improve the timeliness of English grammar error correction and the recall rate of English grammar error correction, this paper proposes an automatic error correction method for English composition grammar based on a multilayer perceptron. On the basis of preprocessing the English composition corpus data, this paper extracts the grammatical features in the English composition corpus and constructs a grammatical feature set. We take the feature set as the input information of the multilayer perceptron and realize feature classification through network learning and training. The grammatical error items in the English composition are detected according to the similarity, and the error correction is completed by setting the penalty parameter and reducing the deviation parameter. The experimental results show that the syntax error detection time of this method is less than 6 minutes, the recall rate is higher than 90%, and the detection error rate is lower than 6%. The method improves the timeliness of grammatical error correction and improves the efficiency of error correction.

Grammatical Errors Found in Articles' Abstracts of Indonesian Scholarly Journals

This study is aimed to know the grammatical errors found in the articles’ abstracts of scholarly journals published by one of Indonesian Islamic State Colleges in 2008-2010. The theory used to analyze the data in this case study is Burt and Kiparsky’s theory, namely Surface Strategy Taxonomy. This theory devides errors into errors of omission,errors of addition, errors of misformation and errors of misordering. This results of the study show that there are 172 items of grammatical errors. The most frequent type of grammatical error is omission with the total number is 72 items or 41.9%. The second is errors of misformation which consist of 57 items or 33.1%. The next is errors of addition (27 items or 15.7%) and finally is errors of misordering as the least number of errors with 16 items or 9.3%.

Evaluation of minimally invasive surgical skills training: comparing a neonatal esophageal atresia/tracheoesophageal fistula model with a dry box.

Pediatric surgeons require highly advanced minimally invasive surgical skills to perform rare and complex surgeries in a very vulnerable population. We developed a neonatal esophageal atresia (EA) model to improve thoracoscopic surgical skills. This study aimed to evaluate the concurrent validity of the model by undertaking pre- and post-training skills assessments in two groups of students with no prior experience performing minimally invasive surgery, using the EA model and a dry box (DB). A pilot study was performed. The participants were randomly divided into two groups: one trained using the DB and one trained using the EA model. Both groups practiced a minimally invasive surgical suture task. The task completion time, 29-point checklist score, modified suturing error sheet score, and three-dimensional forceps movement in both groups were compared pre-and post-training by video analysis. The EA model task was significantly more difficult than that of the DB. Both groups showed significant improvement in the task time, 29-point checklist score, and modified suturing error sheet score; however, the EA model training was more efficient in improving each error item. Regarding forceps movement, the EA model training significantly decreased wasted motion, whereas the DB was limited in this regard. Short-term training on the EA model, which was more technically demanding than the DB, decreased technical error and wasted motion, and allowed learners to acquire surgical skills more efficiently than training with the DB model. These facts revealed the concurrent validity of the EA model.

BIM 품질검토 데이터를 활용한 건설 프로젝트의 설계이슈 항목 간 연관규칙 분석

Design and construction errors that occur in all process of construction project are very important factors that determine productivity, such as cost, schedule and quality. Therefore, identifying the association or causal relationship between these errors and managing potential risks affects all aspects of cost, schedule, and quality. However, most of the existing studies had limitations in analyzing causal or serial relationships between issue factors by analyzing the characteristics of just each error item or using regression analysis to analyze their cause results. In particular, through BIM quality management task, various design and construction quality issues that could not be found in existing 2D-based projects methods can be found and managed. This study aims to analyze the relationship between these errors using these BIM quality management data. To this end, one of the data mining techniques, the association rule analysis method, is to be applied.

Influencing factors of rotary table geometric error measurement using four-station laser tracers

The laser tracer multi-station measurement method has outstanding performance in computerized numerical control (CNC) rotary table geometric error measurement and separation. However, external factors, such as layout, selected distance between the target mirror and measurement coordinate system, uncertainty of the length measurement, selection of measuring radii for the rotary table, and installation deviation from the target mirror center to the rotary table surface, have negative effects on the results. In this research, the position dilution of precision in the global positioning system measurement process is introduced to evaluate the influence of the laser tracers’ positions on measurement errors. The optimal measurement layout of the laser tracer is used to select the distance between the target mirror and XY plane of the laser tracer measurement coordinate system for the simulation. Then, the influence of the length measurement uncertainty on the laser tracer self-calibration and point measurement results used for calibration is examined based on the Monte Carlo simulation method. Different measurement radii in the rotary table are selected, and four-station laser tracers are used to perform the virtual measurement and evaluate the maximum uncertainty in the X, Y, and Z directions to further determine the best measurement radii of the CNC rotary table. Finally, the effects of the deviation of the target mirror installation center on the geometric error items of the CNC rotary table are quantitatively examined through a simulation. The analysis of the influencing factors in the geometric error measurement and separation process of the CNC rotary table can help further understand how the final results are formed, so as to control the influencing factors during the measurement process and finally optimize them in practice.

Systematic Error Correction for Geo-Location of Airborne Optoelectronic Platforms

In order to improve the geo-location accuracy of the airborne optoelectronic platform and eliminate the influence of assembly systematic error on the accuracy, a systematic geo-location error correction method is proposed. First, based on the kinematic characteristics of the airborne optoelectronic platform, the geo-location model was established. Then, the error items that affect the geo-location accuracy were analyzed. The installation error between the platform and the POS was considered, and the installation error of platform’s pitch and azimuth was introduced. After ignoring higher-order infinitesimals, the least square form of systematic error is obtained. Therefore, the systematic error can be obtained through a series of measurements. Both Monte Carlo simulation analysis and in-flight experiment results show that this method can effectively obtain the systematic error. Through correction, the root-mean-square value of the geo-location error have reduced from 45.65 m to 12.62 m, and the mean error from 16.60 m to 1.24 m. This method can be widely used in systematic error correction of relevant photoelectric equipment.

ADJECTIVE PHRASE CONSTRUCTION INDICATED IN STUDENTS DESCRIPTIVE TEXT: A CROSS SECTIONAL STUDY ON STUDENTS OF SMA NEGERI 1 MATAULI PANDAN TAPANULI TENGAH

This study investigates the types of interlanguage of adjective phrase construction that students made when writing English descriptive text. The errors function as a system and can be used to determine interlanguage. The researcher employed a cross-sectional design and used descriptive qualitative methods. The descriptive texts of the students were collected as primary data at the same time but different levels of proficiency. Thirty tenth-grade students from Matauli Senior High School in Central Tapanuli, North Sumatera, participated in the study. Error Analysis (EA) and Interlanguage theories were central to the data analysis (IL). The findings revealed that students' English production is still interlanguage because their writings contain a wide range of errors regarding adjective phrases. There are 113 errors in total. There are up to 70 items of omission errors (62%), 19 items of misformation errors (17%), 15 items of misordering errors (13%), and 9 items of addition errors (8%). Furthermore, four processes were identified as contributing to students' interlanguage in this study, with the student's native language having the greatest influence on their English production (Language transfer (71%), second language learning strategies (14%), false concepts hypothesized (9.7%), and overgeneralization (5.3%)). The findings also revealed that both interlingual and intralingual sources have caused errors in second language learning. It can be concluded that students' competence at each level is insufficient. Due to their system, they are on the interlanguage continuum, which has a structurally intermediate status between the native and target languages.

Vibration Error Correction for the FOGs-Based Measurement in a Drilling System Using an Extended Kalman Filter

Fiber-optic gyroscopes (FOGs)-based Measurement While Drilling system (MWD) is a newly developed instrument to survey the borehole trajectory continuously and in real time. However, because of the strong vibration while drilling, the measurement accuracy of FOG-based MWD deteriorates. It is urgent to improve the measurement accuracy while drilling. Therefore, this paper proposes an innovative scheme for the vibration error of the FOG-based MWD. Firstly, the nonlinear error models for the FOGs and ACCs are established. Secondly, a 36-order Extended Kalman Filter (EKF) combined with a calibration method based on 24-position is designed to identify the coefficients in the error model. Moreover, in order to obtain a higher accurate error model, an iterative calibration method has been suggested to suppress calibration residuals. Finally, vibration experiments simulating the drilling vibration in the laboratory is implemented. Compared to the original data, compensated the linear error items, the error of 3D borehole trajectory can only be reduced by a ratio from 10% to 34%. While compensating for the nonlinear error items of the FOG-based MWD, the error of 3D borehole trajectory can be reduced by a ratio from 44.13% to 97.22%. In conclusion, compensation of the nonlinear error of FOG-based MWD could improve the trajectory survey accuracy under vibration.

An Error Analysis of Descriptive Writing Based on Surface Strategy Taxonomy Made by the Eight Grade Students of SMP N 6 Kebumen in the Academic Year of 2019 / 2020

To support success in the future, the mastery of writing is significant for school students. However, acquiring this ability may take time because students have to learn to minimize errors. This research aims to describe the students’ errors in their writing of descriptive texts and finding out the degree of the errors made by the eight grade students of SMP N 6 Kebumen in the academic year of 2019 / 2020. The writer used descriptive qualitative method in conducting the study. The research involved 32 students of grade VIII in the academic year of 2019 / 2020 at SMP N 6 Kebumen as participants that were selected by purpose. Data in this research were in the forms of words and sentences showing the students’ writing ability of descriptive texts taken from the worksheet documents done by the students. The writer analysed the documents by using the surface strategy taxonomy proposed by Dulay et.all. (1982:152). Data validity was gained by using investigator triangulation. It is how examination of the credibility of the data is done by making use of other observers for checking the degree of trust of the data.The results of the research showed that there had been found 123 items of errors in the descriptive writings made by the students of grade VIII at SMP N 6 Kebumen in the academic year of 2019/2020. These errors consisted of four types. They covered errors of ommision, errors of misformation, errors of addition, and errors of misordering. The sequence of the errors from the most dominant type to the least one was errors of misformation (61%), errors of omission (20%), errors of addition (15%), and errors of misordering (4%). This research was described the students’ errors in writing descriptive texts. Accordingly, this possibly helps students correct their errors to produce better writing later.
 Keywords: Error analysis, descriptive writing, surface strategy taxonomy

Modelling Ghanaian road crash risk using the Manchester driver behaviour Questionnaire

Little is known about how well models of driver crash risks from the developed world apply to motoring in African low and middle income countries. The Manchester Driver Behaviour Questionnaire (DBQ; Reason et al., 1990), which distinguishes deliberate violations of accepted safety practices and unintentional errors in its measurement of risky driving has been demonstrated to measure crash liability across a range of cultures. However, its applicability to Africa is currently unknown. The present study examines the psychometric properties of the DBQ in a sample of 453 Ghanaian drivers. A combination of exploratory and confirmatory factor analyses produced a 24 item 2-factor model of the DBQ with mainly violation items loading onto one factor and error items loading onto the other. Both violations and errors were independently correlated with self-reported crash involvement and violations correlated with self-reported traffic citations. Higher frequencies of violations and errors were reported by the Ghanaian sample than typically observed in the UK. The findings are consistent with the usefulness of the DBQ in characterising behaviours underlying crash risk in Ghana. The extent to which these risky behaviours may be targeted by behavioural, enforcement and engineering interventions is discussed.

Level Detection Equipment for Measuring the Influence of Different Leveling Accuracies on Linear Error

This study developed a level detection equipment which is used in computer numerical control (CNC) machine tool to determine the impact of leveling accuracy on rectilinear motion accuracy. When the CNC precision machine tool has accuracy deterioration under external load or internal stress, mainly caused error is leveling error, this research and development equipment can immediate to analyze and measurement. The allowable error of leveling accuracy can be obtained after experimental validation. The kinematic error relatively increases with leveling error. When the leveling accuracy is within the allowable error, the kinematic error relatively decreases. The main kinematic error items measured in this study include EXX, EBY, EAX, and EYY. The level detection equipment is developed in this study, and the fuzzy regression analysis is used for modeling. The model that has high accuracy in the test of the X‐axis is R2 = 0.9764 and P = 0.0506, and Y‐axis is R2 = 0.9756 and P = 0.0524. In terms of filtering, Kalman filtering is used for signal processing, the measured values and X‐axis and Y‐axis after filtering are improved by 94.1% and 86.2%, respectively, the repeatability of this system is about A grade capability of precision (Cp), resolution is ±0.0001°, and the stability is at least B grade capability of accuracy (Ca). This equipment has the advantages of low cost, high precision, and 2‐axis measurement. This machine tool which has the straightness increases with X and Y axes’ leveling accuracy errors, when the X/Y leveling accuracy is within ±0.01 mm/m, and there is the best straightness and conforms to the ISO230 standard (Lee et al., 2020).

Psychometric Properties of the Malay-Language Quality of Life Enjoyment and Satisfaction Scale: A Confirmatory Study on Malaysian Children

The objective of this study was to validate the translated Malay version of the Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-M) scale among Malaysian primary school children using the confirmatory factor analysis (CFA). The Q-LES-Q-M measures the level of enjoyment and satisfaction experienced with relation to physical health, feelings, homework, and leisure. The participants were 607 Malay students, 240 (39.5%) boys and 367 (60.5%) girls, with an age range from 10 to 11 years old. The original version of the Q-LES-Q was translated into the Malay language by forward to backward translation procedures with consideration for the local culture and suitable vocabulary for primary school students. The participants then completed the Q-LES-Q-M. CFA was performed using Mplus 8 software. Using CFA, the initial model did not result in a good data fit. Further analysis of the CFA suggested some changes to the model to improve the fit indices. Model modification included the deletion of three problematic items and co-varying some error items. This resulted in improved fit indices and 40 items remained in the final model. The final model showed good reliability based on two indicators of composite reliability (CR) and Cronbach’s alpha (CA). The factors with their CR and CA were physical activity (CR = 0.857, CA = 0.854), feelings (CR = 0.808, CA = 0.813), homework (CR = 0.837, CA = 0.837) and leisure (CR = 0.742, CA = 0.737). The final measurement consists of 40 items. The retained items were deemed suitable for Malay primary school children. The revised Q-LES-Q-M with 40 items is suitable for measuring the levels of children’s involvement in determining the enjoyment and satisfaction of learning and physical activity.

Hand-eye calibration method with a three-dimensional-vision sensor considering the rotation parameters of the robot pose

Hand-eye calibration is a fundamental step for a robot equipped with vision systems. However, this problem usually interacts with robot calibration because robot geometric parameters are not very precise. In this article, a new calibration method considering the rotation parameters of the robot pose is proposed. First, a constraint least square model is established assuming that each spherical center measurement of standard ball is equal in the robot base frame, which provides an initial solution. To further improve the solution accuracy, a nonlinear calibration model in the sensor frame is established. Since it can reduce one error accumulation process, a more accurate reference point can be used for optimization. Then, the rotation parameters of the robot pose whose slight errors cause large disturbance to the solution are selected by analyzing the coefficient matrices of the error items. Finally, the hand-eye transformation parameters are refined together with the rotation parameters in the nonlinear optimization solution. Some comparative simulations are performed between the modified least square method, constrained least square method, and the proposed method. The experiments are conducted on a 5-axis hybrid robot named TriMule to demonstrate the superior accuracy of the proposed method.

Does speed of recognition predict two-alternative forced-choice performance? Replicating and extending Starns, Dubé, and Frelinger (2018).

Does the speed of single-item recognition errors predict performance in subsequent two-alternative forced-choice (2AFC) trials that include an item with a previous error response? Starns, Dubé, and Frelinger found effects of this kind in two experiments and accounted for them in terms of continuous memory-strength signal guiding recognition decisions. However, the effects of error speed might just as well only reflect an artefact due to an error-correction strategy that uses response latency as a heuristic cue to guide 2AFC responses, elicited through confounding factors in their experimental design such as error-correction instructions and feedback. Using two conditions, a replication condition, replicating the procedure from Starns et al., and an extension condition (each n = 130), controlling for the named shortcomings, we replicated the error speed effect. In both conditions, speed of errors in a single-item recognition task was predictive of subsequent 2AFC performance, including the respective error item. To be more precise, fast errors were associated with decreased 2AFC performance. As there was no interaction with the factor condition, the results support the idea that speed of single-item recognition responses reflects the amount of memory information underlying the respective response rather than being used for a simple error-correction strategy to improve 2AFC performance.