Reviewerly/exHarmony huggingface dataset:
The Effectiveness of using Graphic Organizer in Improving Students Performance in Writing Recount Text for Tenth Grade Students

As we know, writing skill is one of the parts of the skill in learning English which must be learned by the learners when they learn English. Nowadays, the problem faced by the students is about the difficulties to understand about the topic that they learn before they write. They have difficulties when they try to understand the structures, grammar, and other language features in recount text. This problem happens in tenth grade r of senior high school. As we know in this technology era, students more interesting to use technology to support their learning activities, even it can make students more creative and active if the media can be used according to the content. In fact, Teach writing is quite hard to be taught in class. Write a text using the correct grammar is very difficult, challenging and sometimes it can be a scary part in learning English that to be faced by the learners. Thus, educators have to find a way to guide them and make them interesting to improve their writing confidence in English, by improving their understanding of how to write recount text. That's why in this study researcher will use Graphic Organizer to solve the student's difficulties in writing recount text. By using GO , students can easy to write recount text using a graphic organizer and improve their performance in writing recount text. Therefore, the purposes of the study are to find out the new strategy that can be applied by the students for learning recount text in the class, the factors that affect the students' choice of learning strategy or learning tools, and how those learning strategies assist and help their learning in writing a recount text. This research is using an experimental method, which to know the result between class using GO and without GO in. T he data will be analyzed by using IBM SPSS 26. Related to the result of the data, GO is proven that effective in improving students performance in writing recount text. It could be seen from the mean score of the pre-test in the treatment class that got 45,94 and the mean score of the post-test was 87,89. The significance level is a positive significant difference as Sig. (2-tailed) the value was .000 which not less than or equal to .05. It could be concluded that there was a great difference in the score after the test. While, Cohen's d value was 1,7 which means the treatments given a strong effect on the treatment class.
Development of the lexico-conceptual knowledge resource for Myanmar NLP applications

The computational lexicons and semantic resources as WordNets of knowledge resources are mostly important for Natural Language Processing (NLP). The importance of computational lexicon is even greater in languages with rich morphology, where the lexicon is expected to provide morphological analyzers with enough information to enable them to correctly process intricately inflected forms. This paper presents for the semiautomatic construction of a multipurpose lexico-conceptual knowledge resources for NLP systems by acquiring the lexical and conceptual knowledge from WordNet and Myanmar English Machine Readable Dictionaries (MRDs). To construct the WordNet like lexicon, to collect the translation links, semantic meaning and synset links, the existing bilingual MRDs and English WordNet are used for building the knowledge resources. The collected of links and their meaning are manually verified. In addition, morphological processors (analyzers and generators) are support to handle cases of inflectional morphology. These resources are very efficient and effected for NLP applications, the building methodology of constructing Myanmar English Computational Lexicon and Myanmar WordNet lexical database reduced the human effort and time consuming.
An Alignment-Based Approach to Semi-Supervised Bilingual Lexicon Induction with Small Parallel Corpora

Aimed at generating a seed lexicon for use in downstream natural language tasks and unsupervised methods for bilingual lexicon induction have received much attention in the academic literature recently. While interesting and fully unsupervised settings are unrealistic; small amounts of bilingual data are usually available due to the existence of massively multilingual parallel corpora and or linguists can create small amounts of parallel data. In this work and we demonstrate an effective bootstrapping approach for semi-supervised bilingual lexicon induction that capitalizes upon the complementary strengths of two disparate methods for inducing bilingual lexicons. Whereas statistical methods are highly effective at inducing correct translation pairs for words frequently occurring in a parallel corpus and monolingual embedding spaces have the advantage of having been trained on large amounts of data and and therefore may induce accurate translations for words absent from the small corpus. By combining these relative strengths and our method achieves state-of-the-art results on 3 of 4 language pairs in the challenging VecMap test set using minimal amounts of parallel data and without the need for a translation dictionary. We release our implementation at www.blind-review.code.
A Hybrid Morphological Active Contour for Natural Images

Morphological active contours for image segmentation have become popular due to their low computational complexity coupled with their accurate approximation of the partial differential equations involved in the energy minimization of the segmentation process. In this paper, a morphological active contour which mimics the energy minimization of the popular Chan-Vese Active Contour without Edges is coupled with a morphological edge-driven segmentation term to accurately segment natural images. By using morphological approximations of the energy minimization steps, the algorithm has a low computational complexity. Additionally, the coupling of the edge-based and region-based segmentation techniques allows the proposed method to be robust and accurate. We will demonstrate the accuracy and robustness of the algorithm using images from the Weizmann Segmentation Evaluation Database and report on the segmentation results using the Sorensen-Dice similarity coefficient.
Preprocessing and Discrimination of Cytopathological Images

Image preparation is one of the most difficult and necessary jobs for image processing applications. This chapter is dedicated to preprocessing techniques and their application to different microscopic cytopathological images. The chapter discusses methods ​​​​​to prepare microscopic images for better analysis. Almost every image processing method involves feature localization and extraction as the fundamental steps for analysis. Image preprocessing makes an image suitable for feature localization so that the feature extraction process can take advantage of it. This chapter discusses these image preprocessing methods along with some enhancement schemes.
AN EVALUATION ON THE EFFECTIVENESS OF ONLINE LEARNING FOR STUDENTS AT GOVERNMENT COLLEGES IN ZIMBABWE: A LECTURER AND STUDENT PERSPECTIVE

The study sought to evaluate the effectiveness of online learning for students in Zimbabwe. A lecturer perspective. A survey of two colleges in the Midlands province was undertaken. A survey of twenty students and ten lecturers (total thirty) from various departments revealed that online learning had its challenges to both students and the lecturers. Results of the study showed that most students were finding it hard to access online learning due to reasons that include lecturer and student attitudes, lack of know-how, poor network and the high costs of purchasing bundles. Most participants did not have access to Wi-Fi. Successful online programmes are influenced by availability of resources. The findings indicated that, in as much as the students and lecturers wanted to use online learning challenges were encountered and these hindered the success of online training programmes. Hence, for effective online learning programmes, assistive technology amongst other resources should be availed to staff and students. Key Words: Online Learning, Assistive Devices Policy Administration CITATION: Watadza, M. L., &amp; Lungu, A. (2021). An evaluation on the effectiveness of online learning for students at government colleges in Zimbabwe: A lecturer and student perspective. T he Strategic Journal of Business &amp; Change Management, 8 (3), 718 – 731.
THE IMPLEMENTATION OF PQ4R STRATEGY IN TEACHING NARRATIVE READING TEXT

PQ4R strategy is a learning strategy which has a good concept to teach the students in comprehending a reading text. Moreover, this study is aimed to find out the implementation of PQ4R strategy in teaching narrative reading text done by the teacher in the classroom. This study is also trying to find out the students’ reading comprehension after practicing the PQ4R strategy in teaching and learning activities. The base of this study is using descriptive qualitative as the research design through an observation. Furthermore, the field notes were used to collect the information regarding teaching and learning process by using the implementation of PQ4R strategy. In one meeting, the teacher implements the stages of PQ4R strategy starting from preview, question, read, reflect, recite, and review sequentially. The implementation of those stages was divided into three reading activities; pre reading, while reading, and post reading. The data from the field notes showed that in pre reading activity, the teacher mostly implemented preview and question stage. In post reading activity, the teacher applied review stage to ensure the students’ understanding about the text by delivering ideas and providing suggestions. The rest of the selected stages read, reflect, and recite applied during while reading activities. Moreover, the students’ reading task was used in order to know the students’ reading comprehension after the implementation and it was analyzed by using ESL Composition Profile considering that the task was in the form of writing a summary towards the reading text. Furthermore, all of those stages of PQ4R strategy and their implementation are useful for the teachers or other educational practitioners when they engaging the students’ reading comprehension in narrative reading text. Keywords: PQ4R strategy, reading comprehension, narrative text.
A study on the use of ‘Geureomyeon’ based on Korean register corpus and Korean textbook corpus

This study aims to qualitatively analyze examples of ‘Geureomyeon’ in two types of corpora, a Korean register corpus and a Korean textbook corpus, by describing the aspects of uses and comparing their uses in a respective corpus. To this end, first, the use of ‘Geureomyeon’ was classified into three categories -conjugated form, conjunctive adverb, and discourse marker- in accordance with their definitions suggested in a Korean dictionary. The next step was to analyze the examples, as a result, it was found that both corpus illustrated the same ordering by frequency. Conjunctive adverbs constituted the most frequent, discourse marker was the second most and conjugated form accounts for the least. In case of the Korean textbook corpus, more than half of the examples of ‘Geureomyeon’ were employed as conjunctive adverbs, showing a certain degree of difference from real language data. Meanwhile, both corpus did not show significant differences in the use of ‘Geureomyeon’ as a purpose of discourse marker. Lastly, the examples classified as conjugated forms accounted for a lower proportion of use, particularly in the Korean textbook corpus, than those of other categories. These results indicated that Korean language text for education should reflect Korean usage more realistically.(Yonsei University)
Exploring the types of teaching-learning activities and teaching strategies to cultivate creativity and aesthetic sensibility in English subject

The purpose of this study is to find out what types of teaching and learning activities and teaching strategies are used by preliminary English teachers to cultivate creativity and aesthetic sensibility skills. For this purpose, the lesson plans and classroom demonstrations of 29 pre-service English teachers were analyzed to find out the teaching and learning activities and strategies used. The main results and implications of this study are as follows. First, preliminary English teachers didn t seem to have any particular difficulty in giving classes to cultivate creativity or aesthetic sensibility capabilities, but they will need to expand their scope to meet future English education goals. Second, in the case of teaching-learning activities or strategies to cultivate converging thinking or aesthetic sensibility capabilities, diversity was insufficient, so it should be supplemented. In addition to this, this study suggests that preliminary English teachers should be given an opportunity not only to give classes that can cultivate creativity/aesthetic sensibility, but also to demonstrate the ability to engage in teaching activities with creative/aesthetic sensibility.
Experiments for the adaptation of Text2Picto to French

The Dutch Text2Picto system (Sevens, 2018; Vandeghinste et al., 2015) aims to automatically translate text into pictographs for people with an intellectual disability in the context of Augmentative and Alternative Communication (AAC). The AAC technologies are used by disabled people to help them to communicate in daily life and to be more independent in their interactions with others improving the social inclusion (Beukelman and Mirenda, 1998). In the framework of the Able to Include European project, the Text2Picto tool has been designed for three source languages (Dutch, English, Spanish) and two target pictographic languages (Sclera, Beta). In this communication, we propose two main contributions: (1) to adapt th is system to French and (2) to extend it to a third pictograph set, namely Arasaac, that becomes more and more popular within AAC. We describe how we automatically linked the pictographs and their metadata to synsets of two French WordNets (WOLF and WoNeF) so that the translation engine uses the semantic relations between concepts. In order to preprocess the source text in French, we also have adapted the shallow linguistic analysis carried out in Text2Picto to French. Finally, we evaluated our system, whose parameters were optimized using a hill climbing algorithm, on three corpora representing several use cases: social media, books for children, and medical communication between doctors and patients. The results of our experiments are in line with those of the Dutch Text2Picto for social media and of a similar text to picto system for French children’s books (Vaschalde et al., 2018). For medical use case, we also carried out a manual evaluation. As a result of our experiments, we present a fully fledged sy stem easily extensible to other languages and we discuss the challenges we are faced with when evaluating these technologies for adaptation to other use cases.
Inequalities in Africa : Does financial integration matter?

This paper assesses the impact of financial integration on inequality in Africa. Two dimensions of financial integration (regional and international) and three dimensions of inequality (economic, environmental, housing) are considered. Using a sample of 26 countries, we estimate a panel data model using the System Generalized Method of Moments (S-GMM) over the period 1985-2016. Our results show that regardless of the dimension considered, financial integration increases economic, environmental and housing inequalities. The results also show that there is a threshold at which financial integration reduces inequality. Financial integration combined with high financial inclusion is necessary for the mitigation of inequality.
Economic Evaluation of Cryptocurrency Investment

This study proposes a method to enhance cryptocurrency portfolios constructed by forecast models. This study forecasts returns on four liquid cryptocurrencies (Bitcoin, Litecoin, Ripple, and Dash) and determines the weights on the cryptocurrencies based upon a dynamic allocation framework. We assess the performances of the portfolios using the performance fee measure. Our results present that the proposed portfolios outperform the benchmark portfolio with the conventional level of the risk aversion parameter. The economic gain for an investor is equivalent to 12% per week. The economic gain is sensitive to a change in the risk aversion parameter, which contrasts with the studies of exchange rates which is due to the high volatility on the cryptocurrencies. Our predictors are related to the price momentum effects and they outperform widely used network factors.
Mobile Application For Primary School Student Extracurricular Activity

Student attendance is important to an educational institution because better attendance leads to higherretention rates and higher student performance. Presence is most significant in studying environment, work or school activity as this provides insight into attitude. Being late or absent from school activity or class while not always but in most cases, will give a bad impression if done without a valid excuse. Therefore, the ability to record down attendance is crucial. Some school still use traditional method way to record student attendance, such as recording attendance manually through name-calling, collecting signatures student attendance report and student attendance book. This method can causeteacher need to take a long time to finish if there have a larger amount of students. Besides, attendance record book and the attendance report file cannot avoid on many factors such as missing, damage or natural disaster. Since that, this project proposes a mobile application as a solution to solve the manual take attendance method and save time for teacher task to take attendance duringco-curricular activity. This project objective is to develop a prototype mobile application for primaryschool teachers to record student extracurricular attendance. Teacher can save and submit student datato a database through a mobile application in mobile devices. Because people have their own mobiledevices and using mobile applications on mobile devices become custom in people life. Furthermore, mobile applications on mobile devices are convenient, portable and can access anywhere when have internet. This project using an android studio software to develop and design the mobile application prototype. Besides, prototyping model is selected as the methodology to develop the proposed prototype mobile application. Each phase of the model is explained in details.
PENGARUH METODE BERNYANYI TETRHADAP PERKEMBANGAN BAHASA ANAK USIA DINI DI LEMBAGA RA RABBANI ISLAMIC SCHOOL

Language is a great tool. With language we can express our thoughts and feelings towards other people. Language can be expressed in various forms, namely speech, writing and gestures. The human organs that play a role are the mouth and throat. Language can also exist without speaking, for example a person is mute - deaf because he cannot hear oral expressions and language so he cannot speak. Seeing the differences in each child, there are three important things that teachers must pay attention to in developing children's language skills to average, namely the number of vocabulary they should master, clarity in speech, and speech disorders. Language is very important to use for socializing, so language needs to be developed from an early age. Learning through the singing method on children's language development may be more effective. Because singing is a fun activity that is loved by children. The singing method is a learning method that uses chanted lyrics. Singing makes the learning atmosphere cheerful and passionate so that children's language development can be stimulated optimally. In addition, singing may increase vocabulary so that children's language development can develop optimally.
펠든크라이스 ATM® (Awareness Through Movement)방식이 무용수의 신체자각 능력에 미치는 영향에 관한 연구 - 대학 3년 현대무용 전공생을 중심으로 -

The objective of this study is to explore the effect of warm-up activities using the Feldenkrais Awareness Through Movement (ATM)® method on the physical awareness of dance major students in a university dance improvisation class. To achieve this, scripts for 12 ATM® classes were selected, based on which warm-up activities were being conducted for the junior year dance major students at University C in Gyeonggi Province, South Korea.Warm-up activities employing the Feldenkrais ATM® Method were reported to be the most effective in Physical Relaxation, among the components of physical awareness. It was followed by “Physical Alignment”, “Sensory Reception”, “Sensory Restoration”, “Sensory Recognition”, “Mind-Body Connectivity”, “Self-image Formation”, “Concentration Control”, “Trust Factor” and “Movement Factor” respectively.The study proved that the warm-up activities using Feldenkrais ATM® method were effective in all of the above mentioned physical awareness factors.
Feature extraction and encoding for video action recognition

Video action recognition, including Third-person Action Recognition (TAR) and Egocentric Action Recognition (EAR), is one of the essential tasks within the realm of computer vision. It can be regarded as the capability of determining whether a given human action occurs in the video or not. Albeit advances made by machine and deep learning techniques significantly improve the performance of action classification, some open questions are far less than comprehensively resolved, such as (1) uncertainty management in feature extraction; (2) estimated attention might not be concordant with the subjective in feature extraction; (3) dimensions may blow up during feature encoding, making visual systems with low practicalities and applicabilities. This PhD project, in the first part, presents a Histogram of Fuzzy Local Saptio-Temporal Descriptors (HFLSTD) to support uncertainty management in extracting a conventional gradient-based local feature descriptor via estimating the contribution of each pixel towards each angular-based bin adaptively controlled by a penalty parameter. The efficiency and efficacy of the HFLSTD have been confirmed by the domain benchmarks of two large scale data sets with competitive performance yielded even in comparison to some recently proposed deep feature descriptors. Then, in order to extract feature descriptors from more informative 3-D attentional regions, the Gaze-Informed Descriptors (GD) are sparsely devised by utilising human eye fixation in conjunction with estimated attention to inform the process of generating a 3-D region of interest, and hence help to extract more informative visual feature descriptors in the context of the EAR. The Saliency Descriptors (SD), ), on which the membership is based, are also developed in a dense manner for the situation where the human eye fixation information is not available. The effectiveness of GD and SD in enhancing the classification performance is demonstrated through not only a collected EAR data set but also a real-time memory aid system for Dementia and Parkinson’s patients to support health care. In addition, in the second part of this work, the Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptor and Fisher Vector (SST-VLAD and SST-FV) are developed to address the inherent redundancy of not only video action data sets but also extracted feature descriptors by mitigating the curse of dimensionality in the super-vector-based encoding schemes. This is contributed to by a tentative proposition of selecting the minimum number of videos from the data set, thereby a small portion of feature descriptors via the ranked video-wise saliency-based spatio-temporal scores, which in turn guide the process of codebook generation. Extensive experimental results identified that SST-VLAD and SST-FV have much lower space- and time-complexity and relative higher action classification performance, in contrast with VLAD and FV, on one TAR and one EAR data set.