Different Types Of Errors Research Articles

Role of AI in diagnostic imaging error reduction.

The topic of diagnostic imaging error and the tools and strategies for error mitigation are poorly investigated in veterinary medicine. The increasing popularity of diagnostic imaging and the high demand for teleradiology make mitigating diagnostic imaging errors paramount in high-quality services. The different sources of error have been thoroughly investigated in human medicine, and the use of AI-based products is advocated as one of the most promising strategies for error mitigation. At present, AI is still an emerging technology in veterinary medicine and, as such, is raising increasing interest among in board-certified radiologists and general practitioners alike. In this perspective article, the role of AI in mitigating different types of errors, as classified in the human literature, is presented and discussed. Furthermore, some of the weaknesses specific to the veterinary world, such as the absence of a regulatory agency for admitting medical devices to the market, are also discussed.

Teaching the Analysis of Translation Errors through Collaborative Work: The Case of 1st Year Master Students at the University of Mascara – Algeria

Given the gap noted in the Algerian official syllabus of the translation unit, and though both teachers and students are aware of the importance of translation errors, no lecture is dedicated to this concept. Hence, the present investigation attempts to testify the efficiency of collaborative work in teaching translation errors to M.A. students and thereby apply the theoretical background in real situations. It aims to train students to detect and correct errors, improve the final product, and minimise the different types of errors. The paper adopts a qualitative quantitative-mixed method to scrutinise the phenomenon under investigation. Whereas the theoretical part draws on Delisle's (1999) model of translation errors, the practical part relies on data collected via questionnaires, interviews, and document analysis. The paper's data were obtained from M.A. students' documents at Mascara University (Algeria) to examine the efficiency of collaborative work as a method of teaching translation errors. The study finds out that the error rate was reduced by 24% after adopting collaborative work, including the three types of texts (general, medical, and literary). The study also concludes that collaborative work enhances three central competencies competitiveness, autonomy, and motivation; hence, they acquire certain translation maturity and critical thinking.

O ERRO SOBRE PRESSUPOSTOS FÁTICOS DE UMA CAUSA DE JUSTIFICAÇÃO: UMA ANÁLISE À LUZ DA DOGMÁTICA JURÍDICO-PENAL

The article aims to understand the distinction between the legal nature of different types of errors, conduct an analysis regarding the treatment provided by the limited theory of culpability, as adopted by the Penal Code, to putative justifications, examine the hybrid nature of errors concerning the factual assumptions of a justification, and verify the treatment that has been given in light of legal doctrine. Bibliographic research was conducted to assimilate how legal doctrine addresses the topic. The information was analyzed using deductive methodology. The study concludes in favor of the appropriate distinct treatment that should be given to putative justifications, despite the theory adopted by criminal law, ensuring that the dogmatic concepts of the Theory of Crime are not subverted.

Investigating EFL Libyan students problems in translating English Auxiliary verbs in declarative Sentences, Case study: English Department Alasmarya University

This study is an attempt to shed light on the issue of translating English auxiliary verbs in declarative sentences into Arabic. It aims to identify the students’ problems in translating English auxiliary verbs into Arabic. In addition, it aims to examine the extent to which the translation courses taught at the faculty affect students' translations. To achieve these aims, the researchers use a test of translation for data collection. The test includes 20 statements including auxiliary verbs. The sample is 40 English Foreign language (EFL) students at the Faculty of Arts, al-Asmariya Islamic University, Zliten. The results of this research show that the students committed different types of errors in translating English auxiliaries into Arabic such as wrong equivalents in translation and omitting the equivalence. Furthermore, the results of the study reveal that the percentage of the correct and acceptable translations of the group who have not studied any translation courses and the percentage of the other group who have studied one or more translation courses are approximately the same. In words, the translation courses do not affect the student’s proficiency in translation.

Method Comparison for Simulating Non-Gaussian Beams and Diffraction for Precision Interferometry.

In the context of simulating precision laser interferometers, we use several examples to compare two wavefront decomposition methods-the Mode Expansion Method (MEM) and the Gaussian Beam Decomposition (GBD) method-for their precision and applicability. To assess the performance of these methods, we define different types of errors and study their properties. We specify how the two methods can be fairly compared and based on that, compare the quality of the MEM and GBD through several examples. Here, we test cases for which analytic results are available, i.e., non-clipped circular and general astigmatic Gaussian beams, as well as clipped circular Gaussian beams, in the near, far, and extremely far fields of millions of kilometers occurring in space-gravitational wave detectors. Additionally, we compare the methods for aberrated wavefronts and their interaction with optical components by testing reflections from differently curved mirrors. We find that both methods can generally be used for decomposing non-Gaussian beams. However, which method is more accurate depends on the optical system and simulation settings. In the given examples, the MEM more accurately describes non-clipped Gaussian beams, whereas for clipped Gaussian beams and the interaction with surfaces, the GBD is more precise.

Characterizing phonemic fluency by transfer learning with deep language models.

Though phonemic fluency tasks are traditionally indexed by the number of correct responses, the underlying disorder may shape the specific choice of words-both correct and erroneous. We report the first comprehensive qualitative analysis of incorrect and correct words generated on the phonemic ('S') fluency test, in a large sample of patients (n = 239) with focal, unilateral frontal or posterior lesions and healthy controls (n = 136). We conducted detailed qualitative analyses of the single words generated in the phonemic fluency task using categorical descriptions for different types of errors, low-frequency words and clustering/switching. We further analysed patients' and healthy controls' entire sequences of words by employing stochastic block modelling of Generative Pretrained Transformer 3-based deep language representations. We conducted predictive modelling to investigate whether deep language representations of word sequences improved the accuracy of detecting the presence of frontal lesions using the phonemic fluency test. Our qualitative analyses of the single words generated revealed several novel findings. For the different types of errors analysed, we found a non-lateralized frontal effect for profanities, left frontal effects for proper nouns and permutations and a left posterior effect for perseverations. For correct words, we found a left frontal effect for low-frequency words. Our novel large language model-based approach found five distinct communities whose varied word selection patterns reflected characteristic demographic and clinical features. Predictive modelling showed that a model based on Generative Pretrained Transformer 3-derived word sequence representations predicted the presence of frontal lesions with greater fidelity than models of native features. Our study reveals a characteristic pattern of phonemic fluency responses produced by patients with frontal lesions. These findings demonstrate the significant inferential and diagnostic value of characterizing qualitative features of phonemic fluency performance with large language models and stochastic block modelling.

Mathematical model for the prediction of high blood pressure through digital dermatoglyphics

Abstract Background Hypertension is considered not only a disease belonging to the large group of cardiovascular conditions, but also a risk factor that impacts at an economic, social, environmental, and cultural level, among others. Worldwide, it is recognized that arterial hypertension is increasing, with projections that estimate a 30% increase in prevalence by the year 2025. Objective. To develop a mathematical model for the prediction of high blood pressure in young people through digital dermatoglyphics. Methods This study was carried out in a sequence of three activities, which included in the first instance the collection and analysis of all the fingerprints of the upper limbs of each study participant with an image recognition device, to later carry out a characterization. in terms of number and type of footprint on each of the participants’ fingers. Subsequently, a multiple linear regression model was carried out for the right and left hand, which includes information on the type of footprint, number of relevant characteristics and other physical characteristics of everyone with which it is possible to determine an expected value of the pressure. diastolic and systolic arterial pressure, a model that was validated through the estimation of different types of error, the correlation coefficient, and the tracking signal, in a contrast between predicted and observed blood pressure in a second control sample with different participants. those used in the formulation of the mathematical model. Results The model had a significant R-square, allowing to establish a relationship of similarity and explanation of the blood pressure values, from the quantification of the characteristics of the fingerprints of the right and left hand with a significance level of 95%. Conclusions An important advance is presented for the prediction of high blood pressure through genetic markers with a non-invasive and low-cost method. Key messages • This type of research allows progress in the establishment of relationships between the subject's genetic conditions and the potential risk for the development of diseases. • Biotechnology is currently presented as a tool that contributes to the challenges that are generated in different areas such as the health sector.

Large-Scale Simulation of Shor’s Quantum Factoring Algorithm

Shor’s factoring algorithm is one of the most anticipated applications of quantum computing. However, the limited capabilities of today’s quantum computers only permit a study of Shor’s algorithm for very small numbers. Here, we show how large GPU-based supercomputers can be used to assess the performance of Shor’s algorithm for numbers that are out of reach for current and near-term quantum hardware. First, we study Shor’s original factoring algorithm. While theoretical bounds suggest success probabilities of only 3–4%, we find average success probabilities above 50%, due to a high frequency of “lucky” cases, defined as successful factorizations despite unmet sufficient conditions. Second, we investigate a powerful post-processing procedure, by which the success probability can be brought arbitrarily close to one, with only a single run of Shor’s quantum algorithm. Finally, we study the effectiveness of this post-processing procedure in the presence of typical errors in quantum processing hardware. We find that the quantum factoring algorithm exhibits a particular form of universality and resilience against the different types of errors. The largest semiprime that we have factored by executing Shor’s algorithm on a GPU-based supercomputer, without exploiting prior knowledge of the solution, is 549,755,813,701 = 712,321 × 771,781. We put forward the challenge of factoring, without oversimplification, a non-trivial semiprime larger than this number on any quantum computing device.

Digital technologies for conducting dictations in Ukrainian

At present, modern information technologies are developing very rapidly. A lot of different software tools are being created to improve and simplify people's lives. This is especially true in the context of distance learning. In the context of online learning, the traditional form of conducting dictations needs to be transformed. Therefore, it is possible to propose automation of the process of conducting and checking dictations using software. The paper analyzes scientific research and publications of the current state of language synthesis technologies and text similarity testing. With the help of C# and the language synthesis libraries of Microsoft, Google, Amazon, software has been developed that allows the user to listen and type text, and then automatically check it with the initial sample. The conducted testing for different types of errors showed the possibility and expediency of development the system for conducting and checking dictations. Follow-up activities will focus on improving the effectiveness of the program. The use of such programs will help improve the organization of conducting and checking dictations during distance learning and self-training of students.

UPAYA MENULIS SURAT LAMARAN KERJA BAHASA INDONESIA MENGGUNAKAN MODEL THINK PAIRE SHARE

This research is a descriptive qualitative research. Data collection was done using observation, essay tests, and documentation methods. This study analyzes student errors based on test results on students' ability to write job application letters. Errors in writing job application letters often occur in the writing stages, such as content, word choice, sentences, paragraphs, and spelling on job application letters. Researchers used the think pair share model. This type of learning model is very suitable for students and helps researchers carry out learning activities in writing application letters. The subjects of this study were students of class XII TBSM and XII TKJ, totaling 60 people. In this study, students were given an essay test in writing a job application letter in the form of a description, then analyzed for errors based on the Indonesian correspondence guide with different types of errors for each category of errors. Obtained from the conclusion, the problem that arises from the background of the problem is in what way the efforts of class XII students of SMK PAB 1 Helvetia in writing essential parts using spelling on job application letters. The results of the data analysis show the control class with an average score of 66 and the experimental results with an average score of 81. Students using the think pair share model are more active in learning, asking questions, and answering questions posed by researchers using the think pair share model.

Navigating the Landscape: A Comprehensive Review of Current Virus Databases.

Viruses are abundant and diverse entities that have important roles in public health, ecology, and agriculture. The identification and surveillance of viruses rely on an understanding of their genome organization, sequences, and replication strategy. Despite technological advancements in sequencing methods, our current understanding of virus diversity remains incomplete, highlighting the need to explore undiscovered viruses. Virus databases play a crucial role in providing access to sequences, annotations and other metadata, and analysis tools for studying viruses. However, there has not been a comprehensive review of virus databases in the last five years. This study aimed to fill this gap by identifying 24 active virus databases and included an extensive evaluation of their content, functionality and compliance with the FAIR principles. In this study, we thoroughly assessed the search capabilities of five database catalogs, which serve as comprehensive repositories housing a diverse array of databases and offering essential metadata. Moreover, we conducted a comprehensive review of different types of errors, encompassing taxonomy, names, missing information, sequences, sequence orientation, and chimeric sequences, with the intention of empowering users to effectively tackle these challenges. We expect this review to aid users in selecting suitable virus databases and other resources, and to help databases in error management and improve their adherence to the FAIR principles. The databases listed here represent the current knowledge of viruses and will help aid users find databases of interest based on content, functionality, and scope. The use of virus databases is integral to gaining new insights into the biology, evolution, and transmission of viruses, and developing new strategies to manage virus outbreaks and preserve global health.

An Analysis of Grammatical Errors in Writing Made by English Education Students at IAIN Palopo

Considering the importance of grammatical knowledge in the writing process, this research aims at describing the grammatical errors that are committed by the fifth semester students of English Department at IAIN Palopo. The research study is classified into a descriptive-qualitative study. The data were collected from twenty two English texts written by the English Department students which were done as tasks and contained six familiar topics. Students were supposed to write an essay/paragraph about the given topics. In addition, the researcher had permission from the lecturer to take and analyse the students’ written works. The researcher and students’ written works are the main sources of data collection in this research. To identify the common errors, students’ writings were analysed with the help of checklists in order to classify different types of errors made by the respondents. The results of the study revealed that the most common and frequent errors made by the students are 387 (58.37%) places of omission errors, 213 (32.12%) places of mis formation errors, 131 (19.75%) places of addition errors, 8 (1.20%) places of mis ordering errors. Besides that, the causes of these errors were developmental found in 323 (36.17%) places, 306 (34.26%) of ambiguous, 205 (22.95%) of interlingual, and 59 (6.60%) unique errors. Based on these findings, teachers are suggested to raise students’ awareness on these errors and provide sufficient remedies to prevent students from internalizing such errors.

A Study on Ultrasonic Wireless Power Transfer With Phased Array for Biomedical Implants.

This article presents the design, fabrication, and sensitivity analysis of an ultrasound (US) wireless power transfer (WPT) link using an external phased array. Optimal beam focusing and steering is needed for efficient, safe, and reliable US WPT to biomedical implants with millimeter (mm) dimensions. Therefore, the main contributions of this work include the investigation of the 1) performance of the US WPT link using different mm-sized US receivers, 2) effect of different types of errors in the delay profile of the beamforming system on the delivered power, and 3) implant's localization. In measurements, the fabricated 0.94 MHz, 32-element array (39.48 × 9.6 × 2 mm3) driven by 25 V pulses with beam focusing and steering capability up to 50 mm depth and ±60o angle could deliver power to different mm-sized US receivers within the FDA safety limit of 720 mW/cm2. Specifically, several US transducers with a 1 mm dimension (sphere, cubic, disc shape) and 2 mm dimension (disc shape) received 0.095 mW, 0.25 mW, 0.22 mW, and 0.53 mW, respectively, at a 30 mm depth (0o steering angle). Among these transducers, the sphere shape transducer featured less sensitivity to misalignments. A random error in the phased array delays had a more drastic effect on delivered power reduction. For implant's localization, the measurement results demonstrated comparable power delivery by measuring pulse delays of only 5 elements (out of 32 elements) using 4 different interpolation methods.

Modeling and estimation of solar radiation of Karachi through artificial neural network (ANN) using temperature and dew-point

The most influential source of energy in our lives is solar energy. Solar energy reaches the earth in three different forms, i.e., Global, diffused, and Direct Solar Radiation. The Solar flux at the earth's surface depends on the intensity of these radiations and is a function of the values of latitude and longitude. The earth's temperature and hence dewpoint are greatly affected by solar flux. This idea is used for predicting solar radiation with input parameters, temperature, and dewpoint along with day number and month. The method of prediction of solar radiation used in the study is Artificial Neural Network (ANN). ANN has four variables in the input, ten neurons in the hidden layer, and three output parameters GSR. DSR and BSR. Six different types of errors, namely, Root Mean Square error (RMSE), Mean Absolute Error (MABE), Mean percent error (MAPE), Chi-square, Coefficient of Determination, Kolmogorov Smirnov, have been calculated for training, testing, and validation mode to check the accuracy of estimation. The values of all the errors are low, which indicates the prediction of solar radiation is reliable.

Not all grammar errors are equally noticed: error detection of naturally occurring errors and implications for eye-tracking models of everyday texts.

Grammar errors are a natural part of everyday written communication. They are not a uniform group, but vary from morphological errors to ungrammatical word order and involve different types of word classes. In this study, we examine whether some types of naturally occurring errors attract more attention than others during reading, measured by detection rates. Data from 211 Danish high school students were included in the analysis. They each read texts containing different types of errors: syntactic errors (verb-third word order), morphological agreement errors (verb conjugations; gender mismatches in NPs) and orthographic errors. Participants were asked to underline all errors they detected while reading for comprehension. We examined whether there was a link between the type of errors that participants did not detect, the type of errors which they produce themselves (as measured in a subsequent grammar quiz), and the type of errors that are typical of high school students in general (based on error rates in a corpus). If an error is infrequent in production, it may cause a larger surprisal effect and be more attended to. For the three subtypes of grammar errors (V3 word order, verb errors, NP errors), corpus error rates predicted detection rates for most conditions. Yet, frequency was not the only possible explanation, as phonological similarity to the correct form is entangled with error frequency. Explicit grammatical awareness also played a role. The more correct answers participants had in the grammar tasks in the quiz, the more errors they detected. Finally, we found that the more annoyed with language errors participants reported to be, the more errors they detected. Our study did not measure eye movements, but the differences in error detection patterns point to shortcomings of existing eye-tracking models. Understanding the factors that govern attention and reaction to everyday grammar errors is crucial to developing robust eye-tracking processing models which can accommodate non-standard variation. Based on our results, we give our recommendations for current and future processing models.

CHINESE STUDENTS' WRITING SKILLS: COMMON ENGLISH GRAMMATICAL ERRORS

Writing is a key act in the process of foreign language acquisition. The ability to write properly and accurately is essential for effective communication and critical for human employment. Semantically accurate and grammatically proper writing is of paramount importance especially for students in higher educational institutions. Hence, the present research tends to examine the mistakes made by second language learners in writing essays and proposes recommendations how to improve the English writing skills of the Chinese students. The goal of the research is to reveal common and contrastive features of language errors and help Chinese students to improve their grammatical competences. In order to achieve the above-mentioned goals, the following tasks have been set forth: to discuss and specify the characteristic features of common errors made by Chinese college students; to study different types of errors in writing samples provided by Jiangxi Tellhow Animation Vocational College students; to analyze the possible transformative teaching tendencies and methods that will improve second language learners' writings abilities. The practical significance of the paper is deeply supported by the applicability of its content in education. The methods of inquiry, comparative analysis, component analysis, observation, data collection, etc., have been applied to the research to fulfil the tasks of this research.

Qualitative Analysis of General Aviation Pilots’ Aviation Safety Reporting System Incident Narratives Using the Human Factors Analysis and Classification System

ABSTRACT NASA's Aviation Safety Reporting System (ASRS) gathers data from voluntary aviation safety reports for nonfatal accidents and incidents. These reports are a valuable resource in identifying unsafe occurrences and hazardous situations in the aviation industry. A tool known as the Human Factors Analysis and Classification System (HFACS), initially developed for military use, has proven useful for root cause analysis of human causes in aviation accidents and incidents, including in commercial contexts. This research study utilizes HFACS to classify the ASRS safety reports to identify key indicators in General Aviation (GA) non-fatal accidents and incidents. Qualitative data analysis reveals relationships between incidents and causal factors, indicating 53% of incidents to be perceptual errors, 32% decision errors, and 26% skill-based errors. Prevalent preconditions for these errors include crew resource management (53%), physical environment (32%), and technological environment (16%). The study aligns with previous research findings, suggesting that crew resource management is a common factor in both GA incidents and commercial and military aviation. While GA pilots may make different types of errors, such discrepancies are not prevalent in the voluntarily reported data.

Supremacy of suprasegmentals in Arabic phonology: Evidence from malapropisms

Speech errors are an important source of information to understand language processing and production. Earlier research focused on different types of errors including semantic and phonological errors while malapropisms, which refer to slips of the tongue involving whole word substitutions that share phonological similarities but are not related semantically, have not received adequate attention in the Arabic language. Drawing on malapropisms in Jordanian Arabic, we bring evidence on the supremacy of suprasegmental phonological aspects in Arabic phonology. This is unexpected as stress in Arabic is non-phonemic and fully predictable, besides Arabic rhythm is much less stress-timed than that of Germanic languages. Data was collected from spontaneous speech over a period of three years. Results showed that malapropisms share the primary stress position, the number of syllables and the word rhythmic pattern with the target words. To a lesser degree, the target and the error share the same rime and initial segments. Findings suggest that suprasegmental features are very crucial in Arabic phonology, like in Indo-European languages. Evidence suggests that formal similarity that is based on the syllabic and metrical structure of words plays a significant role in language processing and the organization of the mental lexicon in Arabic, which suggests that this is a language universal. Furthermore, our findings do not agree with earlier claims that Arabic has a flat syllabic structure. Rather, evidence suggests that Arabic, like English, has a hierarchical syllable structure, which seems to represent another language universal. More research on other Arabic dialects is recommended to corroborate these findings. Disclosure statement No potential conflict of interest was reported by the authors. * Corresponding author: Mohammed Nour Abu Guba, 0000-0002-5007-6439 mabu-gub@sharjah.ac.ae

Real or Fake Text?: Investigating Human Ability to Detect Boundaries between Human-Written and Machine-Generated Text

As text generated by large language models proliferates, it becomes vital to understand how humans engage with such text, and whether or not they are able to detect when the text they are reading did not originate with a human writer. Prior work on human detection of generated text focuses on the case where an entire passage is either human-written or machine-generated. In this paper, we study a more realistic setting where text begins as human-written and transitions to being generated by state-of-the-art neural language models. We show that, while annotators often struggle at this task, there is substantial variance in annotator skill and that given proper incentives, annotators can improve at this task over time. Furthermore, we conduct a detailed comparison study and analyze how a variety of variables (model size, decoding strategy, fine-tuning, prompt genre, etc.) affect human detection performance. Finally, we collect error annotations from our participants and use them to show that certain textual genres influence models to make different types of errors and that certain sentence-level features correlate highly with annotator selection. We release the RoFT dataset: a collection of over 21,000 human annotations paired with error classifications to encourage future work in human detection and evaluation of generated text.

Analysis of Near-Miss Events and Errors in Handling Thyroid Specimens; A Gross Room Experience from a Pathology Lab

<p>Background and Objective: Thyroid specimens constitute a major bulk of the head and neck surgical specimens received at the Pathology Departments. Careful handling of the specimens in the grossing room will result in an efficient reporting of useful histological parameters required for patient management and prognosis. The objective of this study was to analyze different errors and near-miss events in the grossing of thyroid specimens in the surgical pathology gross room of a Tertiary Care Hospital in Lahore, Pakistan.</p>
 <p>Methods: A cross-sectional analysis was done on different thyroid specimens received at the Pathology reception of Lahore General Hospital, Lahore, Pakistan, from January 2022 to April 2023. Different types of errors involved in standard gross examinations were studied. Data were entered using SPSS version 23.0.</p>
 <p>Results: Errors observed in the preanalytical phase included the use of inappropriate fixative (15.2%), insufficient clinical information (76.5), mislabeled jar/request form (7.6%), and loss of specimen (8%). Grossing errors included insufficient grossing notes (12.2%), cutting thick slices (10.7%), missing lesions on gross examination (9.9%), inappropriate inking (6.9%), overfilling cassette with large tissue sections (6.9%), mislabeled cassettes (93.8%), and incomplete submission of capsule (2.3%).</p>
 <p>Conclusion: This study concludes that errors and near-miss events in handling thyroid specimens can be avoided by effective training of the handling staff and grossing residents. Collaboration between clinical wards and histopathology laboratories can also be helpful in this regard.</p>