Reviewerly/exHarmony huggingface dataset:
The Impact of the Pandemic on English Language Development at Elementary School

This research aims to find the impact of the pandemic on language development.This research was conducted at SDS Muhammadiyah Pomalaa, Kolaka.The subjects of this study were 5th grade students, where 15 students were used for the diagnostic test instrument and after that the researcher selected 5 students from 15 students who had done the diagnostic test for interviews.The design of this study used a descriptive qualitative research method.Data obtained by Diagnostic test and interview.The results showed that the pandemic had an impact on the low language development of students seen from the diagnostics scores where the average student got a low score and the interview results showed students were enthusiastic about learning in a pandemic.
Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-Switching

Natural language processing (NLP) models trained on people-generated data can be unreliable because, without any constraints, they can learn from spurious correlations that are not relevant to the task.We hypothesize that enriching models with speaker information in a controlled, educated way can guide them to pick up on relevant inductive biases.For the speakerdriven task of predicting code-switching points in English-Spanish bilingual dialogues, we show that adding sociolinguistically-grounded speaker features as prepended prompts significantly improves accuracy.We find that by adding influential phrases to the input, speakerinformed models learn useful and explainable linguistic information.To our knowledge, we are the first to incorporate speaker characteristics in a neural model for code-switching, and more generally, take a step towards developing transparent, personalized models that use speaker information in a controlled way. Prompt Speaker Description Example ListASH is first speaker, older, female, from Spanish speaking country, between English and Spanish prefers both, rarely switches languages.JAC is second speaker, older, male, from Spanish speaking country, between English and Spanish prefers both, never switches languages.Sentence ASH is a middle-aged woman from a Spanish speaking country.Between English and Spanish she prefers both, and she rarely switches languages.ASH speaks first.JAC is a middle-aged man from a Spanish speaking country.Between English and Spanish he prefers both, and he never switches languages.JAC speaks second.Partner ASH, JAC are all middle-aged from a Spanish speaking country.Between English and Spanish they prefer both.ASH is a woman and rarely switches languages.JAC is a man and never switches languages.ASH speaks first.* About what happened in reality with, this guy, uh, who foresees the future.*… these types of movies confuse me.But … * is a … it was a documentary.Eh eh esa clase de películas me confunden.Pero
Development of Soft Skills of a Modern Specialist in a Higher Education Institution

The article is aimed at studying soft skills that need to be developed by a modern specialist, taking into account trends in their demand both in the domestic and international labor markets and forecasts for their changes in the future, as well as skills that will help a modern specialist to be more confident and competitive in the labor market, will contribute to successful employment, further professional development and career growth. Analyzing, systematizing and summarizing the information of reports and forecasts of the World Economic Forum on the skills in demand in the labor market for the period 2015-2025, as well as information from job search sites, the dynamics of changes taking place as part of the soft skills demanded in the international labor market and the composition of skills that are important for the employment and career of a modern specialist were defined. Based on the generalization of the skills in demand for a modern specialist, the main thematic directions for the formation of the structure of the training course for the development of soft skills are identified, the course itself is focused on mastering specific soft skills in demand both in the current conditions and for the future until 2025, upon which it is necessary to focus more attention in the process of training higher education applicants. Prospects for research in this direction are to determine the dynamics of further changes in the demand for the development of soft skills of future specialists and the development of approaches and technologies for the development of specific soft skills of students in a higher educational institution.
Short Words Signature Verification using Markov Chain and Fisher Linear Discriminant Approach

Writer identification is the domain of documents image analysis which is popularly sound in many applications like banking, academic professional in Optical Character Recognition (OCR) Signature verification remains one of the most important entities to authenticate document in these applications. In view of technical breakthrough, we have focused on short words signatures which are very hard to verify as they raise issues of ambiguities. From the geometrical studies of signature-based images, it is stated that the morphology of directional transformations (MDT) is right to extract the suitable features in case of short words for writer identification. MDT takes the data in the form of Structure Element (SE). The directional morphological structures (DMS) of SE are used as a key factor for performing morphological operations on the signature images. We have adopted Markov chains and Fisher Linear Discriminant (FLD) for computing the gradients from line features corresponding to the word. Neural network is used to evaluate the proposed model. In case of training and testing of the signature, images of short words leave-one-out are followed. Our purposed model is tested on NIST database for extracting the words length with three letters. It is observed that a very simple architecture of neural network achieved 100% satisfactory results using short words.
Non-Parametric Stochastic Autoencoder Model for Anomaly Detection

Anomaly detection is a widely studied field in computer science with applications ranging from intrusion detection, fraud detection, medical diagnosis and quality assurance in manufacturing.The underlying premise is that an anomaly is an observation that does not conform to what is considered to be normal.This study addresses two major problems in the field.First, anomalies are defined in a local context, that is, being able to give quantitative measures as to how anomalies are categorized within its own problem domain and cannot be generalized to other domains.Commonly, anomalies are measured according to statistical probabilities relative to the entire dataset with several assumptions such as type of distribution and volume.Second, the performance of a model is dependent on the problem itself.As a machine learning problem, each model has to have parameters optimized to achieve acceptable performance specifically thresholds that are either defined by domain experts of manually adjusted.This study attempts to address these problems by providing a contextual approach to measuring anomaly detection datasets themselves through a quantitative approach called categorical measures that provides constraints to the problem of anomaly detection and proposes a robust model based on autoencoder neural networks whose parameters are dynamically adjusted in order to avoid parameter tweaking on the inferencing stage.Empirically, the study has conducted a relatively exhaustive experiment against existing and state of the art anomaly detection models in a semi-supervised learning approach where the assumption is that only normal data is available to provide insight as to how well the model performs under certain quantifiable anomaly detection scenarios.
Pedagogical education at the university: from a single standard to methodological diversity

The article discusses the problems of modern higher pedagogical education in the context of the Declaration of the basic principles of the implementation of pedagogical education programs by higher educational institutions, presented at the meeting of the Council of the Russian Union of Rectors in June 2021 at Lomonosov Moscow State University. The article shows the influence of tendencies of standardization associated with the centralization of the higher education system on the development of Russian higher pedagogical education as well as the trend of democratization, reflecting the process of autonomization of universities that train future teachers. The ways of development of pedagogical education internationalization in Russian universities are proposed, taking into account the complication of the geopolitical situation in the modern world. The features of educational work at the university are considered, which, in the conditions of information diversity is aimed at forming information and civic culture among students, which allows reduction of the negative impact of various sources of information placed on the Internet, on the process of personality development of young people, the formation of their civic position. The article presents the results of an empirical study of the influence of standardization of pedagogical education on individual style and creative self-realization of university teachers in their professional activities. It is proved that the unity of requirements for future teachers training at the university should be combined with the creative approach of teachers to the organization of the educational process in higher education, its methodological and technological diversity in the context of academic freedom of scientific and pedagogical staff and the autonomy of universities.
A Novel Code Completion Strategy

Programmers rely on a multitude of techniques to speed up the development process.Among these techniques is code completion, a productivity improvement technique widely used by developers to explore APIs and automatically complete a word being typed by providing a progressively refined list of candidate words (or recommendations).Still called autocompletion, it reduces incorrect calls to APIs.Several techniques have been developed to obtain the list of candidates.Some methods use the history of the code, others neural networks or artificial intelligence; some exploit the program's structure through AST.Often the recommendation list is long, and finding suitable candidates comes at a cost.In this work, we propose a strategy that improves the accuracy of recommendation list offered by code completion.We present a sorting approach based on the popularity and importance of the elements (suggestions) of the list by analyzing the usage data of classes, methods, and variables of projects in the same development environment.We implemented our sorting strategy in Pharo (IDE and language), an immersive modern programming environment to show its applicability.The empirical evaluation results of this strategy show that our approach improves the quality of the suggestions.
Optimization Method and Application in Python and Aviation

Optimization methods have been formed and developed in recent decades and play an important role in many fields.In the aviation sector, it plays a role in everything from the design of air vehicles to the planning of routes, ticketing, etc.Through the method of literature review, this paper introduces optimization methods and their applications in aviation and python.In the theoretical aspect, mathematical methods involved in optimization methods and some python applications of them are included in this paper.In terms of real-world applications, this paper discusses the application of optimization methods in the field of aviation.The paper finds that different optimisation approaches have certain pitfalls in use, such as the gradient descent method used by the authors of this paper, which in some cases may converge to a local minimum rather than a global minimum.Besides, it iterates at a reduced speed near the extremes.
Blockchain Based Redistricting with Public Participation

Redistricting is the process of grouping all census blocks within a region to form larger subdivisions, or districts.The process is typically subject to some hard rules and some (soft) preferences to improve fairness of the solution.Achieving public consensus on the fairness of proposed redistricting plans is highly desirable.Unfortunately, fair redistricting is an NP hard optimization problem.The complexity of the process makes it even more challenging to convince the public of the fairness of the proposed solution.This paper proposes a completely transparent blockchain based strategy to promote public participation in the redistricting process, to increase public confidence in the outcome of the process.The proposed approach is based on the fact that one does not have to worry about how the NP hard problem was solved, as long as it is possible for anyone to compute a "goodness" metric for the proposed plan.In the proposed approach, anyone can submit a plan along with the expected metric.Only the plan with the best claimed metric needs to be evaluated in a blockchain network.
Challenges in including extra-linguistic context in pre-trained language models

To successfully account for language, computational models need to take into account both the linguistic context (the content of the utterances) and the extra-linguistic context (for instance, the participants in a dialogue).We focus on a referential task that asks models to link entity mentions in a TV show to the corresponding characters, and design an architecture that attempts to account for both kinds of context.In particular, our architecture combines a previously proposed specialized module (an "entity library") for character representation with transfer learning from a pre-trained language model.We find that, although the model does improve linguistic contextualization, it fails to successfully integrate extra-linguistic information about the participants in the dialogue.Our work shows that it is very challenging to incorporate extra-linguistic information into pretrained language models.
School-Based Curriculum Development of Handicraft Culture: the Example of Dongyang Wood Carving

With the development and popularization of school-based curriculum, more and more schools have started to develop school-based art curriculum.Dongyang wood carving is a famous national intangible cultural heritage.In order to maximize the use of Dongyang's local cultural resources, it is of great significance to develop school-based curriculum in primary and secondary schools to promote the preservation and transmission of Dongyang wood carvings.After analyzing the cultural characteristics of Dongyang wood carving, this paper provides a theoretical analysis of the feasibility of a school-based curriculum for Dongyang wood carving.
Finding Numbers of Occurrences and Duration of a Particular Face in Video Stream

Face recognition automation had crucially progressed with the introduction of Eigenfaces algorithms. Still, the automation of the face recognition is having several issues with uncertain environments. In this paper, a novel system is proposed to detect and recognize a particular person or object in a video and output the person’s occurrences and duration in the total video stream. The proposed system uses the max-margin object detection method to detect and recognize the human. The system starts counting the occurrences of a particular person if a match is found in the system. The total duration of that specific person and frequency count will be displayed as an output.
The Automatic Search for Sounding Segments of SPPAS: Application to Cheese! Corpus

The development of corpora inevitably involves the need for segmentation. For most of the corpora, the first segmentation to operate consist in determining silences vs Inter-Pausal Units - IPUs, i.e. sounding segments. This paper presents the “Search for IPUs” feature included in SPPAS - the automatic annotation and analysis of speech software tool distributed under the terms of public licenses. Particularly, this paper is focusing on its evaluation on Cheese! corpus, a corpus of reading then conversational speech between two participants. The paper reports the number of manual actions which was performed manually by the annotators in order to obtain the expected segmentation: add new IPUs, ignore irrelevant ones, split an IPU, merge two consecutive ones and move boundaries. The evaluation shows that the proposed fully automatic method is relevant.
“InstaGrammar!” Incorporating Instagram Reel to Enhance English as a Second Language Learners’ Grammatical Accuracy

In the context of the Malaysian education system, teaching English as a second language is crucial to the factor that the government is accentuating to produce pupils who are well versed in all English language skills.In line with that, schools and teachers together endeavour to approach the difficulties faced by pupils in learning English as a second language.While the world educational system is gradually accepting digital technology, on the other hand social media has gotten the young learners hooked to it around the clock and it has snapped us into an awareness that social media is not only transforming their behaviours but it's also affecting their language learning skills mainly grammar.Presently, besides TikTok, Instagram Reel has been gaining more popularity largely among teenagers.That being the case, it is requisite to make use of the popularity of the exhilarating pertinent feature.Based on the past studies, many Malaysian pupils struggle in writing or speaking English with fewer grammatical errors.Therefore, in this study, researchers aim to analyze lower secondary school pupils' insights in learning grammatical accuracy through Instagram with an intervention, InstaGrammar.An online survey questionnaire was adapted and adopted from the TAM (Technology Acceptance Model).The questionnaire was distributed to 30 Form 2 pupils from a secondary private school based in Selangor, Malaysia.Pupils used one of the current trending Instagram features, Reels to record creative videos about grammar that they've learned in the classroom.This activity was conducted to elevate their motivation and this intervention is intended to balance the acquisition of grammar both in and outside the classroom as well as elevate and inspire the pupils.The outcome of the findings confirmed that ESL pupils' responses towards the intervention were positive.Respondents determined on the incorporation of Instagram's latest feature, reel in learning grammar.Teaching grammar to enhance pupils' language
Instruction Sender Authentication Utilizing Touch Screen Operation Action Fingerprint for UAV Systems

Instruction sender authentication of UAV (Unmanned Aerial Vehicle) control is critical for the secure operation of UAV systems. By exploring user touch action characteristics of the user interaction with the UAV control mobile terminal, this paper proposes a novel instruction sender continuous authentication framework for UAV control systems. In particular, we first obtain the touch screen data in real time from the interaction with the mobile device screen of a user when he controls the UAV. Then we create a polynomial to fit the touch trajectory on the screen of the user, and use the least square method to obtain the optimal estimate of the polynomial coefficients. Finally, we mark the grid area covered by the polynomial to extract the user’s touch screen operation action fingerprint(OAF), and employ the fuzzy extractor method to realize the identity authentication of the sender with certain error tolerance. Extensive experiments are conducted to illustrate the authentication performance of the proposed authentication framework in terms of false acceptance rate, false rejection rate and equal-error rate.
Flexible Visual Grounding

Existing visual grounding datasets are artificially made, where every query regarding an entity must be able to be grounded to a corresponding image region, i.e., answerable.However, in real-world multimedia data such as news articles and social media, many entities in the text cannot be grounded to the image, i.e., unanswerable, due to the fact that the text is unnecessarily directly describing the accompanying image.A robust visual grounding model should be able to flexibly deal with both answerable and unanswerable visual grounding.To study this flexible visual grounding problem, we construct a pseudo dataset and a social media dataset including both answerable and unanswerable queries.In order to handle unanswerable visual grounding, we propose a novel method by adding a pseudo image region corresponding to a query that cannot be grounded.The model is then trained to ground to ground-truth regions for answerable queries and pseudo regions for unanswerable queries.In our experiments, we show that our model can flexibly process both answerable and unanswerable queries with high accuracy on our datasets. 1
Study on the customer oriented modern hotel management system using fuzzy analytic Hierarchical process (FAHP)

The hotel undertaking, as an explanation of the tertiary region, is making at a quick, taking into account fast cash related new turn of events and strong associate for the improvement business experience. In the mean time, it's far up towards strong block each locally and all around. In the records age, a reliably making number of lodgings are picking informationalized control to certifiable strong regions for reflect for them of view through wandered forward liabilities, extra show, and sensible costs. The cutting edge standing control device is all around picked in all pieces of motel control, joining get, behind the scenes cash related making due, and surface gaining errands obviously into an unmarried contraption that basically suits the longings of each and every day hotel control. Standing undertaking information is exploding couple with the improvement of the housing records technique. These information, on the elective hand, have now everything considered unquestionably not an extraordinary clarification for what was in store been progressed and applied to their unwavering potential. This various gives the Warm from an overall perspective based totally Clever Different leveled out Cycle (FAHP), that is used to outline individual thought while generally picking. Hotel control's business undertaking information coordinating is restricted to work with mix, making due, and examinations. The records amassed is brief and timetable, and it falls expedient of the hotel's contemporary-day "support focused" publicizing plan. This subject is by and large settled totally on a standard housing control contraption, and it uses information mining age to take out essential records from present motel undertaking information that grants you to set up a help division mix and guide the decision in with layering in focusing in on information from more than one places and levels across the confirmation making point, that licenses you to thoroughly see the "triviality focused" thought, further help hotel carrier levels, and finish association focus validity.