Correct Mistakes Research Articles

TEACh: Task-Driven Embodied Agents That Chat

Robots operating in human spaces must be able to engage in natural language interaction, both understanding and executing instructions, and using conversation to resolve ambiguity and correct mistakes. To study this, we introduce TEACh, a dataset of over 3,000 human-human, interactive dialogues to complete household tasks in simulation. A Commander with access to oracle information about a task communicates in natural language with a Follower. The Follower navigates through and interacts with the environment to complete tasks varying in complexity from "Make Coffee" to "Prepare Breakfast", asking questions and getting additional information from the Commander. We propose three benchmarks using TEACh to study embodied intelligence challenges, and we evaluate initial models' abilities in dialogue understanding, language grounding, and task execution.

Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts

Thanks to their ability to learn flexible data-driven losses, Generative Adversarial Networks (GANs) are an integral part of many semi- and weakly-supervised methods for medical image segmentation. GANs jointly optimise a generator and an adversarial discriminator on a set of training data. After training is complete, the discriminator is usually discarded, and only the generator is used for inference. But should we discard discriminators? In this work, we argue that training stable discriminators produces expressive loss functions that we can re-use at inference to detect and correct segmentation mistakes. First, we identify key challenges and suggest possible solutions to make discriminators re-usable at inference. Then, we show that we can combine discriminators with image reconstruction costs (via decoders) to endow a causal perspective to test-time training and further improve the model. Our method is simple and improves the test-time performance of pre-trained GANs. Moreover, we show that it is compatible with standard post-processing techniques and it has the potential to be used for Online Continual Learning. With our work, we open new research avenues for re-using adversarial discriminators at inference. Our code is available at https://vios-s.github.io/adversarial-test-time-training.

Degraded Rationality and Suboptimal Decision-Making in Old Age: A Silent Epidemic With Major Economic and Public Health Implications.

Sound decision-making is important for success and well-being in all stages of life but is critical in old age, when many complex and influential decisions are made and opportunities to correct mistakes are limited. Decisions related to financial and health matters are of utmost importance for older adults and have far-reaching implications. Older adults control most household wealth in the United States and face a host of difficult financial decisions related to Social Security distributions, asset decumulation, intergenerational transfers of wealth, and more. Older adults also suffer a disproportionate burden of disease and face complex medical decisions related to chronic disease management and end-of-life care. Adding to the complexity of late-life decision-making, many choices older adults face involve novel considerations and inherent uncertainty; for example, effective management of limited retirement funds requires an estimation of one’s own life expectancy. Despite a lifetime of experience with decision-making, accumulating evidence suggests that many older adults struggle with financial and health decision-making. Older adults often take Social Security distributions too early (resulting in a significant long-term financial disadvantage), engage in unsound investments and risky credit/spending behaviors, and fail to take advantage of financial and health-care benefits. Perhaps even more alarming, older adults are highly vulnerable to financial exploitation and lose more than $30 billion annually in the United States alone. Further, recent Federal Trade Commission survey data suggest a disturbing increase in losses, with adults >60 years losing more than younger adults and considerably higher dollar amounts than their peers in prior years. Losses nearly doubled from 2019 to 2020 among individuals >80, the fastest-growing segment of the population. Further compounding the economic challenge is a looming public health crisis. Financial exploitation is associated with a range of adverse health outcomes, including depression, hospitalization, and early mortality. Indeed, the National Council on Aging dubbed scams against the elderly the “crime of the 21st century” and the Centers for Disease Control and Prevention and other federal agencies have called for immediate and intense efforts to address financial exploitation among older adults.

Application of Unsupervised Transfer Technique Based on Deep Learning Model in Physical Training.

The research purpose is to study the standardization and scientizing of physical training actions. Stacking denoising auto encoder (SDAE), a BiLSTM deep network model (SDAL-DNM) (a kind of training action model), and an unsupervised transfer model are used to deeply study the action problem of physical training. Initially, the physical training action discrimination model adopted here is a combination of stacked noise reduction self-encoder and bidirectional depth network model. Then, this model can collect data for five actions in physical training and further analyze the importance of action standardization for physical training. Afterward, the SDAL-DNM implemented here fully integrates the advantages of SDAE and BiLSTM. Finally, the unsupervised transfer model adopted here is based on SDAL-DNM deep learning (DL). The movement data of the physical training crowd are collected, and then the unsupervised transfer model is trained. According to the movement characteristics of physical training, the data difference between trainers is calculated so that the actions of each trainer can be continuously adapted according to the model, and finally, the benefits of effectively distinguishing the training actions can be achieved. The research shows that before and after unsupervised learning, the average decline of the model used is 1.69%, while the average decline of extreme learning machine (ELM) is 5.5%. The conclusion is that the unsupervised transfer model can improve the discrimination accuracy of physical training actions and provide theoretical support to effectively correct mistakes in physical training actions.

PENERAPAN REFLEKSI PRIBADI UNTUK MEMBANTU GURU MENJALANKAN PERAN SEBAGAI FASILITATOR PADA PEMBELAJARAN DARING

Teachers as a facilitator is who facilitates students' needs to reflect on learning based on Biblical truth. The fact that happened in one of the Christian schools in Tangerang, there are a problem while teacher facilitating students in online learning. Therefore, teachers need to implement appropriate solutions to improve them. This paper aims to examine whether teacher personal reflection can assist teachers in carrying out their role as facilitators, which aims to find out the importance of personal reflection to help teachers as facilitators carry out their role in online learning. The method of writing uses descriptive qualitative. Personal reflection is a response to our salvation which is part of progressive sanctification to become more like Christ. Biblical truth is the basis for teachers' belief in reflection. As a result, through the implementation of personal reflection, teachers can find out problems then find solutions to correct mistakes when facilitating students in online learning. The conclusion is that the application of teacher personal reflection helps teachers to carry out their role as facilitators in online learning. The next writer is advised to use feedback from students to be the source of reflection

Perception of prosodic cues to correct mistakes, in listeners with normal hearing and with cochlear implants

Prosody is used to mark important information in speech yet is not an integral part of speech recognition testing among people with hearing difficulty. While a listener may correctly perceive words spoken, they may not perceive meaningful emphasis on a certain word, which could be critically important in a variety of everyday situations. This study introduces a new paradigm for assessing perception of prosodic cues in listeners with normal hearing and with cochlear implants, who have notorious difficulty perceiving pitch. Stimuli consisted of spoken sentences where one word (in various sentence positions) was emphasized in a manner that indicated that a prior statement was incorrect in a specific way. Participants used a visual analog scale to mark the timing and degree of emphasis aligned with the target words. Here, the perceptual data are linked with acoustic measures of voice pitch contour, intensity, duration, and vocal quality to characterize how contrastive stress cues are recovered by listeners with and without hearing impairment.

Nonlinear Network Speech Recognition Structure in a Deep Learning Algorithm.

As a result of the fast rise of globalization, people in China are learning English at a rapid pace. However, there is a severe shortage of English teachers in the region, which is a major hindrance. To address these concerns, a deep learning-based algorithm is proposed that can not only check English pronunciation but also help learners distinguish between phonemic and quality phonemic while listening and differentiating, as well as correct phonemic errors, thereby increasing their language learning capacity. In order to study the application of nonlinear network identification technology in English learning, this paper evaluates the English pronunciation quality through the deep learning algorithm of deep learning combined with the related contents of neural network data model, and the experimental results of speech recognition structure are analyzed and discussed in detail. The concordance between machine and manual intonation evaluation is 80%, the concordance rate of adjacent intonation evaluation is 98.33%, and the Pearson correlation coefficient is 0.627 that shows the technique is reliable. The method of English pronunciation and speech identification model is sensible and dependable, which can give beginners a punctual, exact and impartial judgment and response guidance, assist learners to get on the differences between their phonemic and standard phonemic, and correct phonemic mistakes, in order to enhance the ability of oral English learning.

A Smartphone Application to Assess Real-Time and Individual-Specific Societal Participation: A Development and Usability Study

ObjectiveTo develop a mobile health app to assess individual-specific meaningful societal participation in real time and to evaluate its usability. DesignDevelopment and usability study. SettingGeneral community. ParticipantsPersons with multiple sclerosis (PwMS) utilized the app for 7 consecutive days. In total, 72 PwMS and smartphone owners were included in the analysis (N=72). InterventionsUsing location tracking, the newly developed Whereabouts app generates an individual-specific timeline of societal participation activities each day, consisting of location and transportation intervals. Subsequently, this timeline is real time enriched by the user with self-reported ratings of meaningfulness and perceived strain of these societal participation activities. The app is based on the International Classification of Functioning, Disability and Health and was developed in an iterative process. Main Outcome Measure(s)Usability of the newly developed Whereabouts app was evaluated by analyzing the effectiveness, efficiency, and user satisfaction. ResultsRegarding effectiveness, the app correctly assessed the type, frequency, and duration of different societal participation activities for 96.1% of the participation activities. The self-reported ratings of societal participation varied for meaningfulness (range, 5-8), perceived strain (range, 2-6), and meaningfulness of the perceived strain (range, 5-8). The latter 2 were highly correlated (r=0.857). With regards to efficiency, 3.9% of the generated participation activities had to be excluded due to inaccuracy or incompleteness. Relating to user satisfaction, 57.3% of PwMS reported that they were satisfied with the usability of the app and 59.7% stated that it gave a realistic overview of their daily activities. However, 54.4% PwMS missed the possibility to specify activities at home, to add activities in more detail, and to correct mistakes. ConclusionsThe Whereabouts app demonstrates usability in assessing real-time, individual-specific meaningful societal participation. Improvements are recommended, such as the possibility to specify participation activities and to generate a graphic overview.

Correction of Speaking Mistakes when Learning a Foreign Language - Analysis of the Most Common Mistakes and their Correction in Learning the German Language

Verbal mistake corrections occur frequently during the process of learning a foreign language and are usually initiated by the teacher. Foreign language teachers have a significant impact on the behavior of verbal correction, thus influencing the organization of in-class discussions and the acquisition of a foreign language. Making mistakes during foreign language learning is no longer seen as a deficiency of language skills. On the contrary, making mistakes is a completely normal part of the process during foreign language acquisition. Fundamentally, mistake correction should be seen as a good opportunity for the students. They show the current acquiring status of the student; teachers understand where it is necessary to replicate knowledge and profoundly acquire it. The main topic of this article is correcting mistakes when speaking in a foreign language. The article addresses issues closely related to the main topic such as: What mistakes do teachers usually correct and how? When do teachers correct mistakes? In what situation do they immediately intervene / not intervene? What do teachers do after the correction? Who corrects during the lesson? How do teachers encourage self-correction? In addition to the theoretical contributions in this field, we have tried to answer these questions through surveys and questionnaires by evaluating the answers we have received from 90 German language teachers. The analyses of the questionnaire as well as the conclusions are presented at the end of this article.
 
 Received: 14 December 2021 / Accepted: 7 February 2022 / Published: 5 March 2022

The Shape of Sex: Nonbinary Gender from Genesis to the Renaissance

The Shape of Sex: Nonbinary Gender from Genesis to the Renaissance

Modification on the convergence results of the Sylvester matrix equation [formula omitted

In this paper, we investigate some convergence results of the gradient based iterative algorithm for solving the Sylvester matrix equation AX+XB=C. We first review the development of the gradient based iterative algorithm and correct mistakes of some convergence results. Then, the idea of ”two iterative factors” is applied to propose some new relaxed gradient iterative algorithms to improve the convergence performance of their previous algorithms. Finally, some numerical examples are taken to illustrate the correctness of the concluded results.

Implemenatasi Metode Talaqqi dalam Pembelajaran Tahfidhul Qur’an di SDIWali Songo Kabupaten Mojokerto

Learning the Qur'an is a virtue for every believer, especially in memorizing it. Based on a preliminary study conducted by the researcher, it is known that the method used in the tahfidhul Qur'an learning at SDI Wali Songo, located in Temon Village, Trowulan District, Mojokerto Regency, is the talaqqi method. This study aims to determine the implementation of the talaqqi method in tahfidhul Qur'an learning at SDI Wali Songo in Mojokerto Regency. This research employs a qualitative research methodology. Data were collected through interviews, observations, and documentation, and then analyzed using Miles and Huberman's analysis techniques. The results of the study indicate that the talaqqi method has been implemented well, starting from the basic volume (juz) to the recitation rules (tajwid) and the uncommon words (ghorib) for students who have not mastered reading and memorizing the Qur'an. Daily and monthly evaluations are conducted to improve students' ability to read the Qur'an and correct mistakes in tajwid and makhraj. The talaqqi method has proven to be effective in enhancing students' memorization skills and is supported by lesson plans (RPP) and syllabi prepared by the school coordinator. In order to improve the quality of learning, it is important to have an adequate number of teachers and facilities. Further research is expected to expand on this study and contribute to educational institutions and the development of knowledge in this field.

Constitutional principles of protection of family rights and interests of the child in civil proceedings

In today's society, paradigms and models of child-rearing, values, and opportunities of parents, competent authorities, and the court to ensure the rights of the child are changing. Most states have identified the protection of family rights and interests of the child, the avoidance of violence against the child, the prohibition of bullying, etc. among the priority areas of state policy. It is important to analyze the constitutional principles of protection of family rights and the concept “the best interests of the child” in civil proceedings, because it is the court that the legislator has the broadest powers in this area, compared to other jurisdictions. The work aims to study the guiding constitutional principles based on which the court can protect the family rights and interests of the child. The research methodology consists of general theoretical and special scientific methods, namely: hermeneutic, system-structural, structural-functional, historical-legal, comparative-legal, and formal-logical. As a result of the study, the mechanisms of the best possible protection of children's rights by the courts were analyzed. An analysis of current case law, including the case-law of the European Court of Human Rights, concluded that today courts and other competent bodies pay considerable attention to analyzing "how a child will be better" and make informed decisions and, if necessary, correct previous mistakes.

Substrate specificity and proposed structure of the proofreading complex of T7 DNA polymerase

Faithful replication of genomic DNA by high-fidelity DNA polymerases is crucial for the survival of most living organisms. While high-fidelity DNA polymerases favor canonical base pairs over mismatches by a factor of ∼1 × 105, fidelity is further enhanced several orders of magnitude by a 3′–5′ proofreading exonuclease that selectively removes mispaired bases in the primer strand. Despite the importance of proofreading to maintaining genome stability, it remains much less studied than the fidelity mechanisms employed at the polymerase active site. Here we characterize the substrate specificity for the proofreading exonuclease of a high-fidelity DNA polymerase by investigating the proofreading kinetics on various DNA substrates. The contribution of the exonuclease to net fidelity is a function of the kinetic partitioning between extension and excision. We show that while proofreading of a terminal mismatch is efficient, proofreading a mismatch buried by one or two correct bases is even more efficient. Because the polymerase stalls after incorporation of a mismatch and after incorporation of one or two correct bases on top of a mismatch, the net contribution of the exonuclease is a function of multiple opportunities to correct mistakes. We also characterize the exonuclease stereospecificity using phosphorothioate-modified DNA, provide a homology model for the DNA primer strand in the exonuclease active site, and propose a dynamic structural model for the transfer of DNA from the polymerase to the exonuclease active site based on MD simulations.

An initial 'snapshot' of sensory information biases the likelihood and speed of subsequent changes of mind.

We often need to rapidly change our mind about perceptual decisions in order to account for new information and correct mistakes. One fundamental, unresolved question is whether information processed prior to a decision being made ('pre-decisional information') has any influence on the likelihood and speed with which that decision is reversed. We investigated this using a luminance discrimination task in which participants indicated which of two flickering greyscale squares was brightest. Following an initial decision, the stimuli briefly remained on screen, and participants could change their response. Using psychophysical reverse correlation, we examined how moment-to-moment fluctuations in stimulus luminance affected participants' decisions. This revealed that the strength of even the very earliest (pre-decisional) evidence was associated with the likelihood and speed of later changes of mind. To account for this effect, we propose an extended diffusion model in which an initial 'snapshot' of sensory information biases ongoing evidence accumulation.

Kornilov Arkady Petrovich (1850-1928), Hofmeister, councillor of state, steward of grand duchess Elizabeth Feodorovna: a newfound face

The article is timed to the 300th anniversary of the city of Perm (1723–2023). From time immemorial to the present, Perm has been a center of attraction for personalities who have left a noticeable mark in the history of the Russian state. We continue the series of publications started by the journal «Vestnik of the Perm Federal Research Center», № 3, 2021, in order to correct mistakes made by the publisher of the book «Memoirs of the Governor, Perm (1911–1915)». Memoirs of Ivan Frantsevich Koshko, the penultimate Perm governor of the pre-revolutionary period, who was directly involved in the reception of the imperial family during their visit to Perm in July 1914. The task of the study is to identify historical figures by analyzing archival documents, memoirs and opinions of historians, comparing photographic materials of the late 19th – early 20th centuries, to determine the genuine appearance of the people depicted in the photograph, thereby restoring historical truth, «the newfound face», and answering the question – who is who.

A study of the quality of Wikidata

Wikidata has been increasingly adopted by many communities for a wide variety of applications, which demand high-quality knowledge to deliver successful results. In this paper, we develop a framework to detect and analyze low-quality statements in Wikidata by shedding light on the current practices exercised by the community. We explore three indicators of data quality in Wikidata, based on: (1) community consensus on the currently recorded knowledge, assuming that statements that have been removed and not added back are implicitly agreed to be of low quality; (2) statements that have been deprecated; and (3) constraint violations in the data. We combine these indicators to detect low-quality statements, revealing challenges with duplicate entities, missing triples, violated type rules, and taxonomic distinctions. Our findings complement ongoing efforts by the Wikidata community to improve data quality, aiming to make it easier for users and editors to find and correct mistakes.

Using Student Created Video Presentations to Build Experiential Learning in the Oral EFL Presentation Classroom

This qualitative study investigates the learning experiences of students in an online oral presentation class where both course delivery, presentation assignments and exams were recorded submissions uploaded to an online classroom. The objective of this study is to understand if the constructivist format of the class encouraged Kolb’s experiential learning environment and to garner any positive or negative takeaways from the experience. Data collected revealed that most students spent 1-2 hours preparing for their presentations and an additional 1-2 hours recording. The additional time spent recording alluded to the idea that recorded submissions directly impacted student motivation to improve. It was also determined that most students preferred recorded submissions because they provided an opportunity to self-reflect and correct mistakes and released them from the anxiety of performing before a live audience thus enhancing the constructivist classroom environment. While many researchers believe that oral presentations are best practiced before a live audience where the skills are normally used, in the post-COVID work environment, more people are expected to work remotely and will require online oral presentation proficiencies. Developing the skills required to deliver asynchronous presentations will make students more competitive in the job market.

Improving Deep Segmentation of Abdominal Organs MRI by Post-Processing

Today Deep Learning (DL) is state-of-the-art in medical imaging segmentation tasks, including accurate localization of abdominal organs in MRI images. But segmentation still exhibits inaccuracies, which may be due to texture similarities, proximity or confusion between organs, morphology variations, acquisition conditions or other parameters. Examples include regions classified as the wrong organ, some noisy regions and inaccuracies near borders. To improve robustness, the DL output can be supplemented by more traditional image postprocessing operations that enforce simple semantic invariants. In this paper we define and apply totally automatic post-processing operations applying semantic invariants to correct segmentation mistakes. Organs are assigned relative spatial location restrictions (atlas fencing), 3D organ continuity requirements (envelop continuity), and smoothness constraints. A reclassification is done within organ envelopes to correct classification mistakes, and noise is removed (fencing, enveloping, noise removal, re-classifying and smoothing). Our experimental evaluation quantifies the improvement and compares the resulting quality with prior work on DL-based organ segmentation. Based on the experiments, we conclude post-processing improved the Jaccard index over independent test MRI sequences by a sum of 12 to 25 percentage points over the four segmented organs. This work has an important impact on research and practical application of DL because it describes how to post-process, quantifies the advantages, and can be applied to any DL approach.

Using Software Applications in Teaching of Slope-Deflection Method in Subject Static Analysis of Constructions

—Static analysis of building structures is an important engineering discipline. The presented paper deals with the teaching process of the slope-deflection method in the subject Static Analysis of Constructions at the Faculty of Civil Engineering of the Technical University in Košice. The slope-deflection method is the method for the analysis of statically indeterminate structures and serves to obtain their inner forces and deformations. For purpose of teaching this subject, teachers prepared programs in the Fortran code and with the help of the output of decisive values obtained from the programs. Teachers know if students have correct solutions of their tasks and can guide students to work to correct mistakes in their work.