Reviewerly/exHarmony huggingface dataset:
Modern Curriculum Vitae: Wordless Meaning Delivery by Using Symbols

This study was aimed to identify the effectiveness of the Wordless Curriculum Vitae and the perceptions of users in a number of hotels located in Badung, Bali upon the Wordless Curriculum Vitae. The method used was qualitative approach and data were obtained through the distribution of online questionnaires, interviews and documentation studies. The results showed that 90% of Modern Curriculum Vitae’s Human Resource users were able to attract their interest in processing to the next level (interview session) and conveying the meaning of language through icons (symbols) substitution. The CV could convey meaning effectively without changing the meaning. In conclusion, this Wordless CV by the substitution of the icons (symbols) has successfully delivered same meaning compared to the conventional CV.&#x0D; Keywords: Modern Curriculum Vitae, Use of Icon/Symbols, Wordless CV
Uji Signifikansi Pengaruh Kreativitas Belajar pada Keterampilan Membaca Siswa

This study aims to determine the effect of student learning creativity on reading ability. The research method used is an ex-post-facto quantitative approach. The subjects of this study were Buddhist students of class VII in Pagentan District, totaling 22 people. The results showed that the significance value obtained was 0.00. As for the consequences of data analysis, the contribution of learning creativity to reading ability is 59.5%. In conclusion, there is a significant effect between learning creativity and reading the text of Gautama Buddha's biography in English.&#x0D; Keywords: Learning Creativity, Quantitative, Reading
Korelasi Kebiasaan Membaca dengan Membaca Pemahaman

This study aims to determine the relationship between reading habits and students' reading comprehension. The method used is quantitative research through a correlation approach. Sampling was carried out using the theory of Non-Probability Sampling with the Sampling technique. The research instrument used questionnaires and multiple-type objective tests. The study results show that the students' reading habits are categorized as special, with an average score of 80, at the mastery level of 76-85%. Students' reading comprehension results are classified as good, with an average count of 73, which is on a scale of 66-75%. The tcount obtained is 2.36 and ttable 2.056. In conclusion, there is a relationship between reading habits and reading comprehension of students of the Indonesian Language Education study program who take the Reading Skills course at Bung Hatta University.&#x0D; Keywords: Reading Habit, Reading Comprehension
Penggunaan Kalimat Efektif dengan Keterampilan Menulis Teks Deskripsi

This study aims to describe the relationship between effective sentences and the skills of writing descriptive texts for class VII students of SMP N 3 Kec. Payakumbuh. This type of research uses the quantitative correlation method. Sampling was done by random cluster sampling. The results showed that the students' average value of effective sentences was 73.59, with a more than adequate classification. The average descriptive text writing skill is 77.5, with good category. There is a correlation between effective sentences and writing the descriptive text for class VII students of SMP Negeri 3 Payakumbuh District with an r-value of 0.836, after being analyzed by the t-test formula, the value of t count&gt; t table (4.02 &gt; 2.085) with dk n-2 (22-2 = 20) and a significant level of 0.05 or 95%. In conclusion, there is a substantial relationship between effective sentences and the skills of writing descriptive text. The better the students' use of effective sentences, the better their writing skills, especially writing descriptive text.&#x0D; Keywords: Effective Sentences, Writing Skills, Description Text
Relationship of Social Interactions to Learning Outcomes English

This study aims to describe the relationship between social interaction and students' English learning outcomes. This study uses the correlation method. The population in this study amounted to 204 people. The sample is 32 people. Sampling was taken by random cluster sampling. The results showed that the average value of students' social interaction was 64, with sufficient qualifications. The average result of learning English is 79 with suitable qualifications. Therefore, there is a good relationship between student social interaction and Indonesian students' learning outcomes at SMA N 1 Akabiluru District. The test results prove that thitung&gt;t table (3,268&gt;1,697). In conclusion, there is a significant relationship between social interaction and the English learning outcomes of students at SMA N 1 Akabiluru District.&#x0D; Keywords: Learning Outcomes, Relationship, Social Interaction
ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices

Neural Architecture Search (NAS) has shown promising performance in the automatic design of vision transformers (ViT) exceeding 1G FLOPs. However, designing lightweight and low-latency ViT models for diverse mobile devices remains a big challenge. In this work, we propose ElasticViT, a two-stage NAS approach that trains a high-quality ViT supernet over a very large search space that supports a wide range of mobile devices, and then searches an optimal sub-network (subnet) for direct deployment. However, prior supernet training methods that rely on uniform sampling suffer from the gradient conflict issue: the sampled subnets can have vastly different model sizes (e.g., 50M vs. 2G FLOPs), leading to different optimization directions and inferior performance. To address this challenge, we propose two novel sampling techniques: complexity-aware sampling and performance-aware sampling. Complexity-aware sampling limits the FLOPs difference among the subnets sampled across adjacent training steps, while covering different-sized subnets in the search space. Performance-aware sampling further selects subnets that have good accuracy, which can reduce gradient conflicts and improve supernet quality. Our discovered models, ElasticViT models, achieve top-1 accuracy from 67.2% to 80.0% on ImageNet from 60M to 800M FLOPs without extra retraining, outperforming all prior CNNs and ViTs in terms of accuracy and latency. Our tiny and small models are also the first ViT models that surpass state-of-the-art CNNs with significantly lower latency on mobile devices. For instance, ElasticViT-S1 runs 2.62x faster than EfficientNet-B0 with 0.1% higher accuracy.
Mixture of segmentation for heterogeneous functional data

In this paper we consider functional data with heterogeneity in time and in population. We propose a mixture model with segmentation of time to represent this heterogeneity while keeping the functional structure. Maximum likelihood estimator is considered, proved to be identifiable and consistent. In practice, an EM algorithm is used, combined with dynamic programming for the maximization step, to approximate the maximum likelihood estimator. The method is illustrated on a simulated dataset, and used on a real dataset of electricity consumption.
[The techniques of the therapist: a conversation analytic perspective on language in psychotherapy].

During the interactional exchange with their patients, psychotherapists continuously assess the applicability of therapeutic interventions and how to linguistically shape these. Therapists choose on the spot which tools to use for the treatment of the patient.To answer the questions which interactional techniques psychotherapists apply, how these constitute towards the joint construction of meaning and what their consequences are for the role of the therapist.We used the method of conversation analysis in order to investigate the therapist&rsquo;s actions and practices of speaking in a systematic manner.In our analyses, we identified different types of techniques such as mirroring, reformulating, completion proffers and silences. These techniques varied in their openness, directiveness and in the degree to which they were transformative.The spectrum of therapeutic interventions ranges from open and less transformative towards more directive and transformative practices of speaking. During the different interactional phases, therapists strategically vary in the application of these types of interventions and therefore also in their role as interlocutor.
Stand-Alone Inter-Frame Attention in Video Models

Motion, as the uniqueness of a video, has been critical to the development of video understanding models. Modern deep learning models leverage motion by either executing spatio-temporal 3D convolutions, factorizing 3D convolutions into spatial and temporal convolutions separately, or computing self-attention along temporal dimension. The implicit assumption behind such successes is that the feature maps across consecutive frames can be nicely aggregated. Nevertheless, the assumption may not always hold especially for the regions with large deformation. In this paper, we present a new recipe of inter-frame attention block, namely Stand-alone Inter-Frame Attention (SIFA), that novelly delves into the deformation across frames to estimate local self-attention on each spatial location. Technically, SIFA remoulds the deformable design via re-scaling the offset predictions by the difference between two frames. Taking each spatial location in the current frame as the query, the locally deformable neighbors in the next frame are regarded as the keys/values. Then, SIFA measures the similarity between query and keys as stand-alone attention to weighted average the values for temporal aggregation. We further plug SIFA block into ConvNets and Vision Transformer, respectively, to devise SIFA-Net and SIFA-Transformer. Extensive experiments conducted on four video datasets demonstrate the superiority of SIFA-Net and SIFA-Transformer as stronger backbones. More remarkably, SIFA-Transformer achieves an accuracy of 83.1% on Kinetics-400 dataset. Source code is available at \url{https://github.com/FuchenUSTC/SIFA}.
Construction of Knowledge Tracing Model Based on Side Information

Abstract Intelligent Tutoring Systems are becoming more and more important in online education. Knowledge Tracing is a crucial part of ITS and aims to track students' knowledge status according to their historical performance and predict their future performance. Recent research shows that Deep Knowledge Tracing (DKT) models exhibit better performance than traditional models. However, the input of the DKT models depends on the ID and the total number of Students, Knowledge components, and Questions (SKQ), so the DKT models can not quickly be transferred to other datasets. Moreover, the application of the trained models is strictly limited when they are put into use due to data privacy. To solve these problems, this study proposes 14 features as side information (information that does not contain ID) related to SKQ and constructs a Knowledge Tracing model based on Side Information (SIKT). The input of this model neither depends on specific ID and the total number of SKQ nor involves students' private information to apply to all datasets. The results in continual learning with three real-world datasets as independent tasks show that: 1) The SIKT model performs better than the baseline models on three datasets and uses the least number of parameters. The side information of students and questions has a significant impact on the effectiveness of knowledge tracing. 2) In continual learning, the SIKT model has better performance on tasks with wider data distribution and can share knowledge across different tasks. 3)The SIKT model does not have the problem of catastrophic forgetting and learns the knowledge of both the original task and the new task at the same time when learning new tasks. 4) The performance achieved by the SIKT model in continual learning is comparable to that achieved by pooling all tasks at once and the model can generalize better as the number of training tasks increases.
Possessor Extraction in English and Danish

Both English and Danish are Germanic languages which are said to require pied-piping of possessive phrases when they are moved, for example in questions like Whose computer do you think this is? If pied-piping is not required in such movements, an alternative way of asking the same question could be Who do you think’s computer this is? (or perhaps, for Danish readers, Hvem er dets computer? [Who is it’s computer?] might be acceptable), where the possessor who/hvem has been extracted from the possessive phrase whose computer/hvis computer, leaving the rest of the possessive DP material -’s/-s computer behind. This type of movement is called possessor extraction (PE), and Davis (2021) provides evidence for the possibility of it in colloquial English for some speakers. This article is a pilot study of Danish PE, suggesting initial generalizations and comparing these to Davis’s (2021) generalizations about English PE.
… And the Computer Plays Along

Software can improvise on the spot to accompany the performance of live musicians.
Flick me once and I know it’s you! Flicking-based Implicit Authentication for Smartwatch

Smartwatch, as a lightweight wearable device, has gained lots of traction recently and is getting deep integration within human life. However, authentication currently employed on smartwatch is still very weak and not user friendly. Inspired by the observation that people flick wrist many times a day to check time, in this work, we propose an implicit authentication approach, FlickAuth, that leverages the common wrist flicking movement to verify smartwatch user identity. FlickAuth works by automatically extracting flick motion, effective features, and classifying users based on one-class SVM. We conducted a user study, using our developed smartwatch app to collect users wrist flicking movement in two scenarios, sitting and standing, which we believe are representative of common situations of users interacting with their smartwatch. Analyses using one-class SVM prove that it is feasible to distinguish different users with this implicit flicking movement and in sitting scenario we can achieve 0% FAR and 100% TPR for majority of the users.
A Netnographic Approach to Investigating Problematic Teenagers' Language Use on Social Media

Social media has become an essential platform for teenagers these days.Social media grew in popularity as a means of communication, entertainment, information, and even education, beginning with simple social activities.Today, social media is also a factor in the development of adolescent behaviour.As a result, the purpose of this research is to explore into the language use by teenagers in social media.Over the course of three months, a netnographic approach was employed to study the language use of nine teenagers.All of the participants' postings, whether text, images, or videos, were evaluated.Instagram stories posted, shared, and reposted on the participant's account are also recorded in Nvivo for thematic analysis and coding.The outcomes of the survey highlighted five important themes of the teens' language use and behaviour: entertainment, popularity, morality and ethics, relationships, and new contacts.This study is concluded with some implications and a detailed discussion of adolescent social media language use and behaviour.The outcome of this study is hoped to help to identify problems faced by problematic students, where early prevention or solution can be proposed.Several other recommendations were also proposed at the end of this paper.
Improving Coronary Artery Disease Prediction

Cardiovascular diseases (CVDs) are the number one cause of death globally. Coronary artery disease (CAD) is the most common form of CVDs. Abundant research works propose decision support systems for CAD early detection. Most of proposed solutions have their origins in the realm of machine learning and datamining. This paper presents two solutions for CAD prediction. The first solution optimizes a random forest model (RFM) through hyperparameters tuning. The second solution uses a case-based reasoning (CBR) methodology. The CBR solution takes advantage of feature importance to improve the execution time of the retrieve step in the CBR cycle. The experimentations show that the RFM outperformed most recent published models for CAD diagnosis. By reducing the number of attributes, the CBR solution improves the execution time and also performs very well in terms of diagnosis accuracy. The performance of the CBR solution is intended to be enhanced because CBR is a learning methodology.
Peer Scaffolding among Primary ESL Learners’ Writing Task: Learners’ Behaviors and Triggering Factors

Human interaction and support are key to students’ learning. In English as a second language (ESL) settings, peer scaffolding reinforces the traditional teacher–learner interaction. A lack of peer interaction among students, which is also a product of the COVID-19 pandemic, has resulted in young learners becoming overly reliant on teachers. This concern is a factor in hindering learners’ writing development. Inspired by the sociocultural perspective, this study employed a qualitative research design to explore the types of scaffolding behaviors among young learners. The analysis is based on the Taxonomy of Language Functions and what triggers these behaviors among primary ESL learners during classroom writing tasks. Data from 10 recordings of audiovisual materials and interviews were collected from 30 Year 6 primary school students and were analyzed using thematic analysis. The data analysis showed that scaffolding behaviors occurred continuously throughout each writing stage. The findings revealed that the preferred scaffolding behavior among learners was questioning. Eliciting questions was the most frequent type of inquiry that was applied during peer scaffolding. Results highlight the triggering factors that influenced scaffolding behaviors, which were learners’ level of competency, personalities, and accessibility to L1. This approach can be used as an alternate strategy for teaching writing because of its substantial impact on the writing ability of ESL students. The findings would provide a clear direction for ESL practitioners and learners to acknowledge the significance of learners’ behaviors and factors during peer scaffolding in assisting their development in writing attainment.
Design and Development of Education Management System

While pursuing any graduation Degrees or in school student have difficulty controlling their time and faculty work parallelly. This certainty affects work productivity in offices. With the establishment of the Education Management system application. The purpose of making this application is to assist users in managing their college work or school work all at once in an application. The research method used in data collection is literature study and indirect observation. The application development method uses the system development life cycle method with the waterfall model. This model uses a systematic and sequential approach that starts at the level of requirement to the level of maintenance. This application is based on Android Developed with the Java programming / Kotlin language. The result is an Education Management system application that can be used for remainder or also bring a Digitalization which also reduce a crowd or keeping a store of documents of college students or school students.
Effectiveness of Flipped Classroom Pedagogy in Programming Education: A Meta-Analysis

The flipped classroom has generated considerable interest in programming education in recent years.This meta-analysis aimed to assess the effectiveness of a flipped classroom and traditional methods in teaching programming courses and the impact on students' performance, problem-solving abilities, and behavioural outcomes, and to analyse the specific discipline, students' type, students' level, and publication sources in the relevant studies.Articles published between 2010 and 2021 were searched carefully in six academic databases, comprising Web of Science, IEEE Xplore Digital Library, ScienceDirect, NCBI Databases, and Springer Link.Peer-reviewed articles written in English were selected and screened according to the inclusion criteria.All the vital data were extracted and stored in Microsoft Excel and meta-analysis was performed using the Comprehensive Meta-analysis (CMA) software.A total of 101 articles were retrieved while 27 of them met the inclusion criteria and were subjected to the meta-analysis.Flipped classroom improved students' achievement in programming courses with statistically significant effect size (g = 0.56; p < 0.001, 95% confidence interval; 0.33-0.79)compared to traditional teaching method.The flipped classroom also favoured behavioural outcome (satisfaction) in programming education.Programming subject areas had a significant moderating impact on the effect sizes.Overall, evidence of publication bias was lacking in this study.The findings and implications of implementing flipped classrooms in programming education were highlighted.More studies are needed to elucidate the effect of flipped classroom model on various dimensions of programming students' learning outcomes to support comparative research in future.
Underwater Image Enhancement using Different Techniques

Underwater image enhancement techniques are essential for improving the visual quality of images captured in underwater environments. These techniques can help researchers and scientists extract useful information from underwater images, aid in environmental monitoring, and support various underwater applications such as underwater exploration, oceanography, and marine biology.Underwater image enhancement technique involves two categories-pre-processing techniques and post processing techniques.
Features of the Application of Smart Technologies for the Development of Various Directions of Design Education

The current increase in requirements for designers in various professional fields is due to the challenges posed by globalization and the informatization of modern society as the main trends in its development. The integration of modern technologies into the structure of designers' professional activities requires a revision of approaches to the professional training of both future design professionals and artists in general. The article aims to study the theoretical foundations and certain practical aspects of the application of SMART technologies in the design education of HEIs of technical and humanitarian orientation. Methodology. The study applied analytical and bibliographic, systemic and structural, comparative, logical, and linguistic methods, analysis, synthesis, induction, and deduction in the processing of scientific information on the use of SMART technologies in design education. Moreover, the methods of abstraction and idealization served to study and process statistical and analytical data. Analysis, synthesis, induction, and deduction helped to study the scientific literature and summarize the results of the survey. Results. The study examined the theoretical foundations and results of a survey on the concept and main trends of design education, as well as the prerequisites, patterns, and directions of development of SMART technologies in terms of assessing the experience of their use in the educational process in teaching design specialties.