Reviewerly/exHarmony huggingface dataset:
Exploring school levels of digital readiness in pandemic time

Abstract COVID-19 lockdown measures adopted by governments in March 2020 have impacted our society as never happened before. The school system was not an exception. Interventions to allow students for distance learning through the support of ‘old’ (e.g. TV) or ‘new’ media (e.g. digital platforms) have been promoted, involving millions of students and teachers worldwide. This paper presents a study on school leaders and teachers’ perceptions on the school levels of digital readiness through the comparison of their views before and during the lockdown. The participation in the EU project DETECT provided the context for exploring the school levels of digital readiness. Data were collected belonging to two different phases and allowing to investigate teachers’ perceptions in using technologies for remote teaching. The school is living an unprecedent period where dramatic experiences are also disclosing new opportunities. Our study found that school had a strategy before the COVID-19 emergency, but it was too focused on infrastructures’ acquisition, while the development of competences on the side of both teachers and students requires an investment in long-term training, up to the point of reshaping the current teaching practices and also planning for interdisciplinary educational activities addressed to the students.
A Bearing Weak Fault Diagnosis Method Based on Wavelet-VMD-Teager Energy

针对滚动轴承的单一故障进行诊断,提出了将小波VMD-Teager能量算子相结合和小波CEEMD-Teager能量算子相结合的诊断方法.对于滚动轴承的故障信号首先是进行小波降噪,使用VMD分解得到IMF分量,利用峭度和相关系数的大小选择合适的IMF分量,进行重构.通过对重构的IMF进行Teager能量算子包络解调处理,最后可以得到不同故障程度的轴承故障的特征频率.对比VMD处理和CEEMD处理得到的故障信号包络图,利用实验数据验证表明,VMD处理能更有效提取滚动轴承的单一故障微弱特征.
A Construction of Binary Punctured Linear Codes and A Supporting Method for Best Code Search

Reduction of redundancy and improvement of error-correcting capability are essential research themes in the coding theory. The best known codes constructed in various ways are recorded in a database maintained by Markus Grassl. In this paper, we propose an algorithm to construct the best code using punctured codes and a supporting method for constructing the best codes. First, we define a new evaluation function to determine deletion bits and propose an algorithm for constructing punctured linear codes. 27 new best codes were constructed in the proposed algorithm, and 112 new best codes were constructed by further modifying those best codes. Secondly, we evaluate the possibility of increasing the minimum distance based on the relationship between code length, information length, and minimum distance. We narrowed down the target (n, k) code to try the best code search based on the evaluation and found 28 new best codes. We also propose a method to rapidly derive the minimum weight of the modified cyclic codes. A cyclic code loses its cyclic structure when it is modified, so we extend the k-sparse algorithm to use it for modified cyclic codes as well. The extended k-sparse algorithm is used to verify our newly constructed best code.
Using English Language Learning Mobile Applications among Iraqi EFL University Learners

This study is conducted for the purpose of collecting data, opinions, needs and learning and teaching facts of EFL university students about English Language Learning mobile apps. The study aims to identify the benefits, difficulties, and resolutions of using mobile phone applications. The study was conducted in the English Department at Al-Kitab University at the second semester of the academic years 2019/2020. T The study is based on the descriptive study, since it describes the use of mobile apps in learning and teaching English Language. For this purpose, it employs the observation and structured questionnaire as methods of collecting data. A questionnaire of 13 main items has been lunched to be responded by 133 EFL university students from both genders; 45 (33.8 %) males and 88 (68.2%) females, their ages vary between 19 to 25 years. The results showed that most students responded positively to using mobile applications in teaching and learning processes. In addition, all students had smart phones, and they used varied brands applications in the learning process. Moreover, the results indicated that students understand and learn better through using the applications.
360-Degree Videos, VR Experiences and the Application of Education 4.0 Technologies in Malaysia for Exposure and Immersion

Obstacles, both imagined and real, continue to hinder the wider adoption of Education 4.0 learning technologies although these technologies are available in the mainstream consumer market. At the same time, the boom in Industry 4.0 manufacturing has brought down the prices of these technological tools making them generally more affordable. A case in point is 360-degree spherical video cameras and software that can record, render and playback immersive ‘real life’ contents. 360-degree spherical video contents can then be rendered and post-processed into VR (virtual reality) experiences that are not just immersive but also allow for limitless exposure time to learners. Both technologies allow for learner-driven learning to happen in the truest sense, for instance for second and foreign language learners. This research paper examines data collected from 560 undergraduates (n = 560) who were immersed and exposed to 360-degree videos and VR experiences for degree level courses on English (as a second language), Mandarin (Chinese) (as a third or foreign language, and Arabic (as a third or foreign language) at four public university campuses in Peninsular Malaysia. The benefits of 360-degree videos and VR experiences in second and foreign languages content delivery were evident to support learner-driven learning: Contents were developed by local lecturers and then uploaded for free online and learners could learn anytime, anywhere; total immersion could be achieved using cheap VR goggles powered by learners’ smartphones; and most beneficially, weaker learners who desperately need more time to understand and practice difficult degree level second or foreign languages now have the freedom to revise and upskill themselves at their own pace.
대학생 핵심역량 진단도구 개발 연구 : S대학 사례를 중심으로

The purpose of this study is to develop and validate the collegiate essential competencies assessment of S university. In order to accomplish this purpose, 1) explore previous research on competencies and cases of developing competencies assessment, 2) development of collegiate essential competencies assessment, 3) conduct internal consistency reliability and exploratory factor analysis of the development assessment on pre-tasted with 118 students was implemented. As a result, the factor structure of each essential competency was classified into 2~3 subfactor, and the reliability coefficient was appropriately between .691 ~ .961. The reliability and validity of the collegiate essential competencies assessment developed in this study were some what satisfactory. This research is meaningful in that can provide practical and useful information to other universities that want to develop or improve diagnostic tools in a similar process in a context of the context of a time when the demand for the development of customized competency diagnosis systems is high.
Learning to Predict Action Based on B-ultrasound Image Information

In the medical field, B-ultrasound is an important way to diagnose diseases. However, due to the lack of professional sonographers, patients have to queue for a long time for examination. Or due to some easily contagious diseases, sonographers cannot directly contact the patient for examination. Therefore, it is necessary to use robotic arms to perform automated B-ultrasound examinations on patients. In our work, the strategy of how to move the probe to detect the kidney is studied. The sonographer is required to hold a special probe instrument to collect the demonstration data, including the B-ultrasound image, as well as the posture and force information of the probe. Then, we leverage the data learning to realize the guidance of the B-ultrasound probe action. In this paper, supervised learning is firstly used to predict actions according image inputs. In other words, the supervised network is input with the B-ultrasound image and output posture and force that the probe should reach at the next moment. Based on the supervised learning, an actor-critic reinforcement learning algorithm that uses asymmetrical data is proposed to improve the utilization of data and enhance the generalization of neural networks.
IMPROVING READING COMPREHENSION USING STORIES AT MTs MIFTAHUL HUDA SILIR WATES

The objective of this research is to improve students’ reading comprehension skills using Stories. The research design used in this study was action research. In this research the reseacher took a test of their improvement in each cycle. Before the reseacher did cycle 1, the reseacher did pre–cycle and found the mean is 64, by percentage of successful is 19% (4 students out of 21) passed the test. In the first cycle the reseacher found the mean of the score of the students reading was 74 by percentage of successful is 57% (12 student out of 21) passed the test. In the second cycle the researcher found the mean of the score of the students reading was 85,7 by percentage of succusful is 86% (18 students out of 21) paased the test.From the observation, the researcher has the criteria of success. they are the average of students’ achievement should be 80, the percentage of successfulness is 80% from the total students, the criteria of minimum passing level (KKM) is 75. The result of the reseach shows that the students improve their ability in reading comprehension by using Stories.
Perancangan dan Penerapan Sistem Penilaian Kinerja Karyawan pada PT. Rofenni Prima Jaya

PT. Rofenni Prima Jaya is a company engaged in land construction services and heavy equipment rental business that has been operating since 1994. The company's problems are insufficient attendance time and lack of employee discipline every month, which can be measured by monthly attendance in the form of employee permits that are delayed resulting in a decrease in productivity and quality. To help the company, an employee performance appraisal system was created. The method used in system development is using the waterfall method and also developing the system using the Hypertext Preprocessor, JavaScript, JQuery, and Bootstrap CSS programming languages, as well as using phpMyAdmin. The results of the system will provide an assessment form by doing one click on the Check List Form button in each period, assessment results reports, and assessment results reports per period. With this assessment system, employees can maintain the performance of employees to achieve the goals that have been targeted, as well as identify deficiencies in carrying out responsibilities.
A Mixed Noise and Constraint-Based Approach to Causal Inference in Time Series

We address, in the context of time series, the problem of learning a summary causal graph from observations through a model with independent and additive noise. The main algorithm we propose is a hybrid method that combines the well-known constraint-based framework for causal graph discovery and the noise-based framework that gained much attention in recent years. Our method is divided into two steps. First, it uses a noise-based procedure to find the potential causes of each time series. Then, it uses a constraint-based approach to prune all unnecessary causes. A major contribution of this study is to extend the standard causation entropy measure to time series to handle lags bigger than one time step, and to rely on a lighter version of the faithfulness hypothesis, namely the adjacency faithfulness. Experiments conducted on both simulated and real-world time series show that our approach is fast and robust wrt to different causal structures and yields good results over all datasets, whereas previously proposed approaches tend to yield good results on only few datasets.
PluGeN: Multi-Label Conditional Generation from Pre-trained Models

Modern generative models achieve excellent quality in a variety of tasks including image or text generation and chemical molecule modeling. However, existing methods often lack the essential ability to generate examples with requested properties, such as the age of the person in the photo or the weight of the generated molecule. Incorporating such additional conditioning factors would require rebuilding the entire architecture and optimizing the parameters from scratch. Moreover, it is difficult to disentangle selected attributes so that to perform edits of only one attribute while leaving the others unchanged. To overcome these limitations we propose PluGeN (Plugin Generative Network), a simple yet effective generative technique that can be used as a plugin to pre-trained generative models. The idea behind our approach is to transform the entangled latent representation using a flow-based module into a multi-dimensional space where the values of each attribute are modeled as an independent one-dimensional distribution. In consequence, PluGeN can generate new samples with desired attributes as well as manipulate labeled attributes of existing examples. Due to the disentangling of the latent representation, we are even able to generate samples with rare or unseen combinations of attributes in the dataset, such as a young person with gray hair, men with make-up, or women with beards. We combined PluGeN with GAN and VAE models and applied it to conditional generation and manipulation of images and chemical molecule modeling. Experiments demonstrate that PluGeN preserves the quality of backbone models while adding the ability to control the values of labeled attributes. Implementation is available at https://github.com/gmum/plugen.
A Study on Interdisciplinary Theories Regarding Maritime Nautical Literature

Maritime or (Nautical literature) was ruling the period during the 18th century which was followed by 19th-century writers. These novels depict the effects on the environment, society and economy of the people. In this study, it is observed that the concept approach towards the Interdisciplinary theory with connection to the people’s thoughts regarding the sea, their religious or holistic approaches, and the gender description given to describe the sea were correlated with some famous nautical novel with notable incidents or theories to prove that the attributes of plots might be different but the themes relating to such sea novels/aquatic novels are more or less similar to each other and they serve some standard settings and motifs on the whole. The study reveals that maritime novels where written in distinctive plots but the themes are more or less focused on masculinity (gender roles) and heroism, social hierarchies and the psychological and holistic transformation during their hard existence in the sea. Ethical approach, the symbolism of sea and the gender roles are used in this regard of research dealing with interdisciplinary theory.
Perancangan Instrumen Evaluasi Pembelajaran Berbasis Website di Sekolah Dasar Negeri 55 Air Pacah Kota Padang

The results of observations and interviews conducted at State Elementary School of 55 Air Pacah, during online learning during the covid 19 pandemic there are 2 methods used in learning evaluation. They are (1) using conventional paper-based media that students take home and (2) sending photos of assignments or photos of questions through the WhatsApp application to parents. The use of this method makes it difficult for educators to process values. The use of website-based media in the evaluation of learning is the right solution in the current era. With a website-based evaluation instrument, correction of calculations can be made directly and students immediately get feedback. The training methods are in the form of presentations, demonstrations, hands-on practice with assistance in making evaluation instruments, and assignment methods. As a result of this service activity, educators can understand how to make website-based learning evaluation instruments and be skilled at using them. In addition, since the training was held until now, educators have applied it in online learning.
Virtual education and digital divides in Peru

The objective of the research was to analyze virtual education and the factors existing in the digital divides in Peru. The1research was1applied, with systematic review design.  The population was 20 scientific articles selected in the search engines of Scielo, Google scholar and BASE the same that have been ordered in an Excel matrix to facilitate their quick location. The variables were:  virtual education and digital gaps. The technique used was the documentary review, through the analysis of the results and the conclusions obtained, qualitative, quantitative and descriptive research predominates. Data collection sheets from scientific articles were used. Virtual education is a high-impact strategy in improving coverage, relevance and educational quality at all levels and types of training, due to its multimedia, hypertextual and interactive characteristics. However, in this pandemic crisis, not all students have been able to access this educational modality, generating a considerable dropout due to different factors.
Modeling Human Sentence Processing with Left-Corner Recurrent Neural Network Grammars

In computational linguistics, it has been shown that hierarchical structures make language models (LMs) more human-like. However, the previous literature has been agnostic about a parsing strategy of the hierarchical models. In this paper, we investigated whether hierarchical structures make LMs more human-like, and if so, which parsing strategy is most cognitively plausible. In order to address this question, we evaluated three LMs against human reading times in Japanese with head-final left-branching structures: Long Short-Term Memory (LSTM) as a sequential model and Recurrent Neural Network Grammars (RNNGs) with top-down and left-corner parsing strategies as hierarchical models. Our computational modeling demonstrated that left-corner RNNGs outperformed top-down RNNGs and LSTM, suggesting that hierarchical and left-corner architectures are more cognitively plausible than top-down or sequential architectures. In addition, the relationships between the cognitive plausibility and (i) perplexity, (ii) parsing, and (iii) beam size will also be discussed.
The Special Class Teachers’ Online Learning Operation Status and Their Perceptions on Effective Methods and Effects during COVID-19

이 연구의 목적은 코로나 19 상황에서 특수학급 특수교사의 원격수업 운영실태와 전반적인 인식을 탐색하는 것이다. 이를 위해 G도 소속 초&#8228;중&#8228;고 특수학급 소속 특수교사 101명을 대상으로 설문조사를 실시하였다. 주요 조사 결과 첫째, ‘콘텐츠 활용 수업(외부 자료나 영상 연결)’이 가장 많이 활용하는 방법으로 나타났다. 둘째, 효과적인 방법은 ‘학습 꾸러미 제공(과제 부여하는 등)’이라고 응답하였다. 셋째, 특수교사는 실시간 상호작용을 통한 온라인 학습(예: Zoom 활용)을 미래 원격수업 형태로 가장 적합하다고 인식하였다. 효과적인 원격수업을 위한 필수사항으로는 ‘개별화 수업과 학생별 포트폴리오 구성이 가능한 플랫폼 구축’으로 나타났다. 넷째, 원격수업에서 특수교사는 콘텐츠 개발 및 자료 제작과 교사와 학생 간 관계 형성을 가장 어려워하는 것으로 나타났다. 학생이 겪는 어려움으로는 수업집중도 저하가 가장 심각한 것으로 나타났다. 다섯째, 교사가 인식하는 원격교육의 긍정적 측면으로는 ‘과제해결 기회 제공’이, 부정적 측면으로는 ‘가정 내 돌봄 부족으로 인한 학생 방치’로 나타났다.The purpose of this study was to analyze the status and perceptions of online classes of special education teachers who experienced the non-face-to-face online classes due to COVID-19. This study also explored the ways to implement online classes more effectively for students with disabilities. A total of 101 special education teachers participated in an online survey for this study who enrolled in elementary, middle, and high schools. The key results of this study were as follows. First, the online contents were most widely used during COVID-19. Second, special education teachers perceived the provision of learning packages was the most effective methods in online classes. Third, special education teachers regarded real-time interactive online classes(e.g., using Zoom) as the most appropriate ways of future online classes. In addition, individualizing class and building platforms that could organize portfolios by students were perceived as essential elements for the effective online classes. Fourth, the difficulties that special education teachers experienced during the online classes were content development and data production. The most serious problem that students experienced was class concentration. Fifth, special education teachers perceived that online classes had positive effects on students’ learning. Particularly, they liked various videos and online contents developed during COVID-19. However, the negative effects of the non-face-to-face classes also reported such as ‘lots of students were left alone without enough cares at home’.
An Adaptive Genetic Algorithm-based Background Elimination Model for English Text

Abstract In this paper, an adaptive genetic algorithm is used to conduct an in-depth study and analysis of English text background elimination, and a corresponding model is designed. The curve results after the initial character editorialization are curved and transformed, and the adaptive genetic algorithm is used for the transformation to solve the influence of multiple inflection points of curve images on feature extraction. Then, using the minimum deviation method, the error values of the input characters and the sample set in the spatial coordinate system are calculated, and the deviation values of the angle and the straight line are used to match the characters with the smallest deviation value to match the highest degree. A genetic algorithm is introduced to iterate the feature sets of angles and line segments, and the optimal features are finally derived in the process of cross evolution of generations to improve the recognition accuracy. And the character library is used as input items for average grouping for experiments, and the obtained feature sets are put into the position matrix and compared with the samples in the database one by one. It is found that the improved stroke-structure feature extraction algorithm based on a genetic algorithm can improve the recognition accuracy and better accomplish the recognition task with better results compared to others. Finally, by analyzing the limitations and characteristics of traditional particle swarm optimization algorithm and differential evolution algorithm, and giving full play to the advantages and applicability of different algorithms, a new differential evolution particle swarm algorithm with better performance and more stable performance is proposed. The algorithm is based on the PSO algorithm, and when the population update of the PSO algorithm is stagnant and the search space is limited, the crossover and mutation operations of the DE algorithm are used to perturb the population, increase the diversity of the population, and improve the global optimization ability of the algorithm. The algorithm is tested on a common dataset for text mining to verify the effectiveness and feasibility of the algorithm.
Formalisation of Action with Durations in Answer Set Programming

In this paper, I will discuss the work I am currently doing as a Ph.D. student at the University of Potsdam, under the tutoring of T. Schaub.I'm currently looking into action description in ASP.More precisely, my goal is to explore how to represent actions with durations in ASP, in different contexts.Right now, I'm focused on Multi-Agent Path Finding (MAPF), looking at how to represent speeds for different agents and contexts.Before tackling duration, I wanted to explore and compare different representations of action taking in ASP.For this, I started comparing different simple encodings tackling the MAPF problem.Even in simple code, choices and assumptions have been made in their creations.The objective of my work is to present the consequences of those design decisions in terms of performance and knowledge representation.As far as I know, there is no current research on this topic.Besides that, I'm also exploring different ways to represent duration and to solve related problems.I planed to compare them the same way I described before.I also want this to help me find innovative and effective ways to solve problems with duration.