Causes Of Such Errors Research Articles

Validity constraints for data analysis workflows

Porting a scientific data analysis workflow (DAW) to a cluster infrastructure, a new software stack, or even only a new dataset with some notably different properties is often challenging. Despite the structured definition of the steps (tasks) and their interdependencies during a complex data analysis in the DAW specification, relevant assumptions may remain unspecified and implicit. Such hidden assumptions often lead to crashing tasks without a reasonable error message, poor performance in general, non-terminating executions, or silent wrong results of the DAW, to name only a few possible consequences. Searching for the causes of such errors and drawbacks in a distributed compute cluster managed by a complex infrastructure stack, where DAWs for large datasets typically are executed, can be tedious and time-consuming.We propose validity constraints (VCs) as a new concept for DAW languages to alleviate this situation. A VC is a constraint specifying logical conditions that must be fulfilled at certain times for DAW executions to be valid. When defined together with a DAW, VCs help to improve the portability, adaptability, and reusability of DAWs by making implicit assumptions explicit. Once specified, VCs can be controlled automatically by the DAW infrastructure, and violations can lead to meaningful error messages and graceful behavior (e.g., termination or invocation of repair mechanisms). We provide a broad list of possible VCs, classify them along multiple dimensions, and compare them to similar concepts one can find in related fields. We also provide a proof-of-concept implementation for the workflow system Nextflow.

An Analysis of Errors in Present Indefinite Tense Sentences: A Case of 6th Grade ESL Learners of Sialkot, Pakistan

Reading the piece of writings in the target language is also suggested to enhance creative ability, while the basic tenets of English Grammar can also be improved through a comparative study of the grammatical concepts. The study aims to identify, discuss, explain, and categorize the grammatical errors, especially errors in present indefinite tense sentences committed by the ESL learners of 6th grade at Cantt Public High School, Sialkot, Pakistan, due to overgeneralization in written exercises. The study gathered data through a worksheet task comprising 10 items of translation sentences from Urdu to English and ten items of English fill-in-the-blanks comprised of grammatical use of present simple tense and agreement morpheme. Corder’s model (1967) of error analysis has opted to analyze the errors in the present indefinite tense. This study pays great attention to overgeneralization in Present Indefinite tense sentences of ESL learners of 6th grade. The learners overgeneralize in the use of rules used for verb forms and auxiliary verbs. The present study also found that a lack of knowledge of the rules of the target language, in addition, to overgeneralization, is the cause of such errors, for instance, the inappropriate use of prepositions. The findings suggest that teachers of English should focus their attention on the troublesome aspect of the present simple tense while also encouraging students to apply the drill practice to the study of the present indefinite tense. This study has a few limitations as it was not feasible for researchers to analyze all kinds of tenses and find all types of errors according to the opted model due to time restraints.

Common Errors of Level Three Students' Writing at the English Department, Faculty of Education, Sana’a University

This research aimed to find out the common errors in third level writing at the English Department, Faculty of Education, Sana’a University during the academic year 2019-2020. It also aimed to highlight the causes of such errors. This research was quantitative research in which its results were calculated quantitatively. For the purpose of achieving the aims of the research, two data collection tools were used (an evaluation sheet for analyzing the test papers and a close ended questionnaire to highlight the errors behind the students' errors in writing. The sample of this research was %29 of the whole population (137 participants) selected randomly to do the questionnaire (40 participants) and 20 essays booklets from the final exam papers of Advanced Writing were chosen also randomly to be as the sample of error analysis. The results showed that errors in capitalization, S-V agreement and spelling were not common because the percentage of errors was not higher than %25 The results also showed that some reasons of making errors in writing as mother tongue interference, lack of vocabulary and the traditional methods of teaching writing.

Abstract Number ‐ 130: Comparison of the Stents Length by Virtual Stent Simulation with the Actual Stent Length

Introduction The selection of the size of a braided stent, such as the flow diverter stent, currently depends on the surgeon’s experience. However, the suitable selection is difficult even for experienced surgeons due to shortening during the deployment. The unsuitable choice of the stent size may result in poor stent apposition or dislodgement of the stent, which may lead to inadequate treatment and increase the risk of complications. To overcome the selection problem, we developed a virtual stent simulation that virtually reproduces the stent geometry preoperatively. However, the lengths of the deployed stents in the virtual stent simulation have not been compared with those in the actual stents. In this study, we evaluated the error between the length of the virtual stent and the actual stent to investigate the clinical usefulness of the virtual stent simulation. Methods We identified 48 internal carotid artery cerebral aneurysms treated with a single flow diverter stent (PipelineTM) between October 2016 and March 2022. The vessel geometries were reconstructed from the preoperative angiographic images, and the virtual stent geometries were reproduced using virtual stent simulation with our in‐house code. The actual stent geometries were reconstructed from the postoperative angiographic images and overlaid on the preoperative vessel geometries using affine transformation. The lengths of the virtual and actual stents were measured, respectively. The differences between the lengths of the virtual and actual stents were calculated by subtracting the actual stent length from the virtual stent length. The errors between the virtual and actual stents were estimated to validate the virtual stent simulation. Results The average maximum diameter in the 48 aneurysms was 16.4±5.91 mm. The average difference in length between the virtual stents and the actual stents was +1.70 ± 4.01 mm, with the average error based on virtual stent length of +3.24 ± 11.3%. The virtual stents of 16 aneurysms were shorter than the actual stents, and the average difference in length was ‐2.97 ± 1.82 mm. On the other hand, the virtual stents of the other 32 aneurysms were longer than the actual stents, with the average difference in length of +4.04 ± 2.47 mm. One possible cause of these differences is that the actual stent may slightly change the geometry of the parent vessel due to the restoring force of the stent. Another reason is that the actual length of the stent may change slightly as the surgeon pushes and pulls the catheter during the procedure. Conclusions Comparing the lengths of virtual and actual stents, it was confirmed that there was some error between the stent length reproduced by the virtual stent simulation and the actual stent length. In particular, the virtual stents tend to be slightly longer than the actual stents. Although our virtual stent may be useful for identifying the appropriate size, it is necessary to investigate the causes of such errors and to realize virtual stent simulations with fewer errors.

The Effects of L1 Transfers on L2 English Intransitive Errors by Japanese Learners

Second language (L2) learners of various native languages frequently overpassivize one type of intransitive verbs, namely, unaccusatives (e.g., disappeared, arrivedn). Previous studies have attempted to address the culprit of this issue without reaching a general consensus on the cause of such errors. This study investigates whether first language (L1) plays a role in L2 English overpassivization errors with intransitive verbs by Japanese-speaking learners. It utilizes the framework of the Unaccusative Trap Hypothesis (UTH, Oshita, 2001) and hypothesizes that learners ungrammatically passivize unaccusative verbs due to L1 lexicon and morphology. It also predicts that learners generate passive errors with unergatives (e.g., cry, smile) in the same manner as passive unaccusatives. The study examined three types of intransitives: English non-alternating/Japanese alternating unaccusatives (e.g., happen in English and okiru/okosu in Japanese); English/Japanese non-alternating unaccusatives (e.g., arrive in English and tuku in Japanese); unergatives. The study analyzed a Japanese learners’ corpus (JEFLL Corpus), consisting of approximately 70,000 words from Japanese junior high and high school students. The findings in this study are that Japanese EFL learners tend to passivize more English non-alternating/Japanese alternating unaccusatives and unergatives than English/Japanese non-alternating unaccusatives. Given the result, it can be suggested that Japanese learners passivize unaccusatives owing to the influence of their L1 lexicon and morphology.

A framework for pronunciation error detection and correction for non-native Arab speakers of English language

This paper examines speakers’ systematic errors while speaking English as a foreign language (EFL) among students in Arab countries with the purpose of automatically recognizing and correcting mispronunciations using speech recognition, phonological features, and machine learning. Accordingly, three main steps are implemented towards this purpose: identifying the most frequently wrongly pronounced phonemes by Arab students, analyzing the systematic errors these students make in doing so, and developing a framework that can aid the detection and correction of these pronunciation errors. The proposed automatic detection and correction framework used the collected and labeled data to construct a customized acoustic model to identify and correct incorrect phonemes. Based on the trained data, the language model is then used to recognize the words. The final step includes construction samples of both correct and incorrect pronunciation in the phonemes model and then using machine learning to identify and correct the errors. The results showed that one of the main causes of such errors was the confusion that leads to wrongly utilizing a given sound in place of another. The automatic framework identified and corrected 98.2% of the errors committed by the students using a decision tree classifier. The decision tree classifier achieved the best recognition results compared to the five classifiers used for this purpose.

AN ERROR ANALYSIS OF ARABIC WRITING BY ISLAMIC VOCATIONAL HIGH SCHOOL STUDENTS

This research examined different types of writing errors performed by Islamic Vocational High School students undertaking the Arabic course. The current study also discussed the plausible causes of errors committed by the students. A mixed-method approach was used to investigate and analyze a corpus of students’ writing. The data were collected through documentation and obtained from the essays of tenth and eleventh-grade students with 40 respondents. The study employed error analysis steps by Corder as a framework to deal with deviated grammatical rules, including collecting, identifying, classifying, quantifying data, and analyzing sources of errors. The results showed that the most dominant error was spelling, with 35.44%, followed by 28.16% errors in phrases, 22.81% in sentence structures, and 13.59% in agreement. Several possible causes of such errors include overgeneralization, ignorance of rule restrictions, incomplete application of rules, and false concepts hypothesized.

Analysis of the Most Frequent Morphosyntatic Errors in the Italian of Egyptian Students

This research aims to examine from an analytical perspective the most frequent morphosyntactic errors that Egyptian students commit while learning the Italian language. The discussion of this topic is not a mere list of students’ errors, rather it focuses on the problem of error analysis and on the other related problems, such as the typology, the frequency and, finally, the causes of such errors. We started from the fact that in the learning phases of an SL, most students encounter difficulties especially in written production. The correction of the works produced by learners allows us to study the causes of certain errors and to isolate, analyse and correct them.

Imparare dagli errori: apprendenti russofoni di italiano LS/L2

The study deals with written errors in Italian language made by Russian learners and their use in Italian LS/L2 lessons. The cultural-linguistic background of Russian learners of Italian and the differences in the morphosyntax of Italian and Russian are partly accounted for causes of such errors. The paper focuses on the didactic advantages of ranking multiple choice test on the base of the degree of incorrectness of the proposed choice: it supports the importance of using systematic errors as a source to create ad hoc multiple choice, and to trigger students’ conscious second language learning.

Safety climate, nursing organizational culture and the intention to report medication errors: A cross-sectional study of hospital nurses

Background & Aim: Medication errors are the second most common accident after the fall accident in hospitals. Medication errors are a threat to patient safety. It is important to find the cause of such errors so that we can reduce them. However, the rate of medication error reporting is low. This study aimed to explore the factors associated with the intention to report medication errors among general hospital nurses. Methods & Materials: A cross-sectional study design was used. The participants were 171 registered nurses working in 4 general hospitals in South Korea. Convenient random sampling was used to select participants. Data were collected using mobile self-report structured questionnaires that covered general characteristics, medication errors and the intention to report them, the safety climate, and the nursing organizational culture. The data collection period was from March 14 to April 6, 2018. The data were analyzed by descriptive statistics, the Pearson correlation coefficients, and multiple regression analysis. Results: The mean scores of the intention to report medication errors and safety climate were 5.20±1.40 and 3.04±0.47, respectively. Each mean score of nursing organizational culture types was hierarch-oriented culture 3.63±0.51, relation-oriented culture 3.13±0.69, task-oriented-culture2.99±0.56, and innovation-oriented culture 2.85±0.67. Significant factors associated with the intention to report medication errors were the safety climate (β=.26, p=.001), a task-oriented culture (β=.16, p=.023), educational level (β=-.19, p=.006), the experience of medication errors (β=.19, p=.006), and male (β=-.18, p=.011). They accounted for 25% of the intention to report medication errors. Conclusion: This study found that the safety climate of the hospital, task-oriented culture of the nursing organization, education level, experience of medication errors, and gender associated with the intention to report medication errors. It is necessary to find ways to improve the safety climate of the hospital and the task-oriented culture of the nursing organization and establish a strategy for improving the intention to report medication errors for male nurses and nurses with medication errors.

What do experts look at and what do experts find when reading mammograms?

Purpose: Radiologists sometimes fail to report clearly visible, clinically significant findings. Eye tracking can provide insight into the causes of such errors. Approach: We tracked eye movements of 17 radiologists, searching for masses in 80 mammograms (60 with masses). Results: Errors were classified using the Kundel etal. (1978) taxonomy: search errors (target never fixated), recognition errors (fixated ), or decision errors (fixated ). Error proportions replicated Krupinski (1996): search 25%, recognition 25%, and decision 50%. Interestingly, we found few differences between experts and residents in accuracy or eye movement metrics. Error categorization depends on the definition of the useful field of view (UFOV) around fixation. We explored different UFOV definitions, based on targeting saccades and search saccades. Targeting saccades averaged slightly longer than search saccades. Of most interest, we found that the probability that the eyes would move to the target on the next saccade or even on one of the next three saccades was strikingly low ( , even when the eyes were from the target). This makes it clear that observers do not fully process everything within a UFOV. Using a probabilistic UFOV, we find, unsurprisingly, that observers cover more of the image when no target is present than when it is found. Interestingly, we do not find evidence that observers cover too little of the image on trials when they miss the target. Conclusions: These results indicate that many errors in mammography reflect failed deployment of attention; not failure to fixate clinically significant locations.

Energy Metering Integrated Circuit Behavior beyond Standards Requirements

During the last few years, the accuracy of static electricity meters (SEM) has been questioned. Significant metering deviations with respect to a reference meter have been observed at customer premises, and laboratory experimental tests results support such findings. The root cause of such errors remains unknown, as there are multiple elements that could affect the accuracy of electricity meters. Furthermore, standard compliant meters exposed to distorted signals may produce negligible, positive or negative relative error depending on the instrument design. Distorted current signals with fast amplitude transitions have produced the highest error in SEMs reported in the literature. In this paper, the accuracy of an energy metering Integrated Circuit (IC) is evaluated beyond the limits of the standards requirements employing a selection of distorted signals from the standards, real-world captured signals and a set of waveforms designed to test the IC under fast changing currents conditions, which are representative of the waveforms resulting from power electronic devices. The experimental results reveal an accuracy boundary imposed by Gibb’s phenomenon for fast changing current signals and a strong relationship between the IC’s measurement error and two key parameters of the measured waveform: signal slope and phase angle. This paper therefore provides a methodology for the comprehensive analysis of SEMs in future power systems which are dominated with power electronic-controlled electrical demand and contributes to the search for the root cause of error in SEMs exposed to distorted waveforms.

Accuracy in Online Media

Accuracy is at the core of what journalists do and it amounts to journalistic commitment to report without errors. This tenet of journalism is now in danger, because of the influence of digitalization, changes in media landscapes, and the utilization of the assertation model of journalism. In this study, we used a combination of content analysis and visual network analysis to investigate how subjective errors are disseminated through an online environment, how time/speed influences the propagation of errors, and what the error correction procedures/routines are. The results demonstrate that 69% of the analyzed stories contained errors, and the main cause of such errors was the use of secondary sources, instead of primary ones, these errors transcend national borders and, time/speed had only a minor role in the emergence and correction of the errors, etc. Out of the 107 media websites analyzed, only seventeen provide certain modalities of requesting error correction.

The role of decision making in the over-representation of Aboriginal and Torres Strait Islander children in the Australian child protection system

The over-representation of Aboriginal and Torres Strait Islander children in the child protection is a serious concern in Australia. A proportion of this group of children may have been removed from families who are providing an adequately safe and nurturing environment, reflecting false positive errors in decision making. Assuming this to be true, we draw on the decision-making ecology model of judgement and decision making in child protection to speculate on possible causes of such errors. This model suggests that false positive errors would occur if the level of risk children face is estimated to be higher than is actually the case or if the decision threshold applied in making decisions to remove children from their family are too low. We present a discussion of factors that could potentially influence judgements and decision thresholds, which has implications for practice. It is argued that false positive errors are most likely to be avoided through more thorough and accurate assessments families. When assessing Aboriginal and Torres Strait Islander families, we argue that this requires a theoretically grounded, culturally informed framework to improve assessments and decrease the likelihood of false positive errors in decisions involving Aboriginal and Torres Strait Islander children in Australia.

SPECIFIC FEATURES OF IDENTIFICATION AND CORRECTION OF ERRORS IN THE REGISTER MADE IN THE LAND SURVEYING

The article looks at the pressing issue of identification of errors in the Unified State Register of Immovable Property in the territory of the Russian Federation. The objective of this paper is to find out the causes of such errors and the ways of their elimination. Main results: The authors have suggested their own classification of errors in the Unified State Register of Immovable Property based on analysis of forensic examinations conducted by the autonomous nonprofit organization “West-Siberian Expert and Legal Center” over ten years in respect of errors resulting from cadastral works and land surveying. Real-world examples of such errors are provided. Main conclusions: 1. Most of the errors in the Unified State Register of Immovable Property are caused by insufficient professional training of cadastral engineers. 2. Errors in the Unified State Register of Immovable Property can be identified with the help of remote sensing and land surveying. 3. Specialists who conduct cadastral and land surveying works should know the causes of errors in the Unified State Register of Immovable Property and the ways of their identification and correction.

The Most Frequent Errors in Academic Writing: A Case of EFL Undergraduate Arab Students in Israel

The current study examined the most common types of academic writing errors and the causes of such errors made by 44 tertiary EFL Arab-Israeli students. A methodological triangulation was employed in this research. Results and analyses of errors in the written samples revealed that students made a substantial number of errors in both rating scales. In the generic writing performance scale (the qualitative method), 75% of students’ written samples rated poor, and the error frequency rating scale (the quantitative method) showed that the students made 2965 errors, which is a notably large number in proportion to the essay length. The researchers have also inferred that the principal reason for such errors is the triglossic nature of Arabic in Israel. The novelty of this research is that such triglossic nature of Arab-Israelis’ language has not yet been investigated in the field. To this end, the results drawn will be utilised in future research as a platform for exploring effective teaching approaches that may enhance EFL students’ writing performance.

Concept–based Analysis of Java Programming Errors among Low, Average and High Achieving Novice Programmers

Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However, most of the studies employed omnibus approaches, i.e. without consideration of different programing concepts and ability levels of the trainee programmers. Such concepts and ability specific errors identification and classifications are needed to advance appropriate intervention strategy. Methodology: A sequential exploratory mixed method design was adopted. The sample was an intact class of 124 Computer Science and Engineering undergraduate students grouped into three achievement levels based on first semester performance in a Java programming course. The submitted codes in the course of second semester exercises were analyzed for possible errors, categorized and grouped across achievement level. The resulting data were analyzed using descriptive statistics as well as Pearson product correlation coefficient. Qualitative analyses through interviews and focused group discussion (FGD) were also employed to identify reasons for the committed errors. Contribution:The study provides a useful concept-based and achievement level specific error log for the teaching of Java programming for beginners. Findings: The results identified 598 errors with Missing symbols (33%) and Invalid symbols (12%) constituting the highest and least committed errors respec-tively. Method and Classes concept houses the highest number of errors (36%) followed by Other Object Concepts (34%), Decision Making (29%), and Looping (10%). Similar error types were found across ability levels. A significant relationship was found between missing symbols and each of Invalid symbols and Inappropriate Naming. Errors made in Methods and Classes were also found to significantly predict that of Other Object concepts. Recommendations for Practitioners: To promote better classroom practice in the teaching of Java programming, findings for the study suggests instructions to students should be based on achievement level. In addition to this, learning Java programming should be done with an unintelligent editor. Recommendations for Researchers: Research could examine logic or semantic errors among novice programmers as the errors analyzed in this study focus mainly on syntactic ones. Impact on Society: The digital age is code-driven, thus error analysis in programming instruction will enhance programming ability, which will ultimately transform novice programmers into experts, particularly in developing countries where most of the software in use is imported. Future Research: Researchers could look beyond novice or beginner programmers as codes written by intermediate or even advanced programmers are still not often completely error free.

Bias in Radiology: The How and Why of Misses and Misinterpretations.

Medical errors are a leading cause of morbidity and mortality in the medical field and are substantial contributors to medical costs. Radiologists play an integral role in the diagnosis and care of patients and, given that those in this field interpret millions of examinations annually, may therefore contribute to diagnostic errors. Errors can be categorized as a "miss" when a primary or critical finding is not observed or as a "misinterpretation" when errors in interpretation lead to an incorrect diagnosis. In this article, the authors describe the cognitive causes of such errors in diagnostic medicine, specifically in radiology. Recognizing the cognitive processes that radiologists use while interpreting images should improve one's awareness of the inherent biases that can impact decision making. The authors review the common biases that impact clinical decisions, as well as strategies to counteract or minimize the potential for misdiagnosis. System-level processes that can be implemented to minimize cognitive errors are reviewed, as well as ways to implement personal changes to minimize cognitive errors in daily practice. ©RSNA, 2017.

Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China

A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows.

Identification and quantification of prescription errors

BackgroundPrescription errors are commonly encountered in health care settings. They can lead to inefficient delivery of health care thus jeopardizing patient care. Knowing the quantum and the possible causes of such errors is the first step in trying to prevent them. We conducted a random audit of prescriptions received in service dispensary of a tertiary care hospital and analyzed them for prescription errors. MethodsA total of 1000 prescriptions were randomly selected. These prescriptions were analyzed with the help of three qualified pharmacists and were stratified as per the errors encountered. ResultsOut of the total of 1000 prescriptions, 650 prescriptions (65%) were found to have a total of 1012 errors. Type B errors were found in 22.4% prescriptions, type C errors in 9.7% prescriptions and type D in 69.1% prescriptions. ConclusionPrescription errors require proactive, continuous and meticulous monitoring so as to minimize them. It requires identification of preventable causes, increasing awareness and sensitizing the prescriber towards this important aspect of health care delivery.