Reviewerly/exHarmony huggingface dataset:
Penggunaan Model Cooperative Integrated and Composition (CIRC) dalam Pembelajaran Meganalisis Unsur Pembangun Cerpen pada Siswa Kelas XI SMA Negeri 2 Subang

The ability of students in reading comprehension is relatively low, especially in analyzing the elements of short story builders, so a breakthrough in learning is needed that can improve students' ability to read comprehension through the use of CIRC learning models. The formulation of the problem in this study are (1) How is the ability to analyze the short story builder elements in class XI students of SMA Negeri 2 Subang? (2) How is the ability to analyze the short story building elements in class XI students of SMA Negeri 2 Subang by using the CIRC learning model? (3) Is the use of the CIRC method effectively used in learning to analyze the short story building elements? The objectives of this study are (1) Describe the ability to analyze short story builder elements in class XI students of SMA Negeri 2 Subang (2) Describe the ability to analyze short story builder elements in class XI students at SMA Negeri 2 Subang using the CIRC learning model. (3) Describe the effectiveness of using the CIRC method in analyzing the elements of the short story builder. This research uses the Pre-Experiment one group pretest-posttest desaign research method. In the initial data the results of this study averaged 63.06 while the average value obtained by students in the final test was 77.94. From both of these results indicate that there is an increase in the average value on the final test compared to the initial test before using the CIRC Learning model, so that the use of the CIRC learning model in analyzing the elements of short story builders can be said to be effective.
Towards a Better Evaluation of Metrics for Machine Translation

An important aspect of machine translation is its evaluation, which can be achieved through the use of a variety of metrics. To compare these metrics, the workshop on statistical machine translation annually evaluates metrics based on their correlation with human judgement. Over the years, methods for measuring correlation with humans have changed, but little research has been performed on what the optimal methods for acquiring human scores are and how human correlation can be measured. In this work, the methods for evaluating metrics at both system- and segment-level are analyzed in detail and their shortcomings are pointed out.
Guide 8: Configuring Content Management Workflow and Permissions

TYPO3’s powerful permission system can allow teams of editors, even thousands of them, to manage content through the backend. Administrators have fine-grained control over who can see and edit what content, determined by a number of factors, including user role, language, location within the page tree, and more.
Jails vs Docker : A performance comparison of different container technologies

Virtualization is used extensively by Enterprise IT architecture and cloud computing, it is used to provide customers a part of their hardware resources as a service. Container technology is the ne ...
The NITS-CNLP System for the Unsupervised MT Task at WMT 2020

We describe NITS-CNLP’s submission to WMT 2020 unsupervised machine translation shared task for German language (de) to Upper Sorbian (hsb) in a constrained setting i.e, using only the data provided by the organizers. We train our unsupervised model using monolingual data from both the languages by jointly pre-training the encoder and decoder and fine-tune using backtranslation loss. The final model uses the source side (de) monolingual data and the target side (hsb) synthetic data as a pseudo-parallel data to train a pseudo-supervised system which is tuned using the provided development set(dev set).
Colaboración especial. Identidad y vínculos educativos: lo que la pandemia trastocó

This article is based on the research I carry out for the National Pedagogical University, which is entitled Identity and constructions of meaning in high school students. The interest of this research is to analyze the processes of construction of subjectivity of adolescents in Mexico City, taking as a central element the conformation of their identities. It should be noted that the studies of youth and adolescence show important and accelerated changes in recent generations of this sector of the population.Unpredictably, when we were about to start the field research through Reflection Groups in two secondary schools, the sanitary confinement measures were decreed, which interrupted the work. Undoubtedly, the pandemic as an event marks radical changes in the current generation of adolescents and young people, whom we can already consider the generation of the pandemic.The text begins with the analysis of the pandemic and its importance due to the disruption of social processes. In particular, the impact it is having on the distance educational process that has been implemented in Mexico as in many countries is examined. One of the central aspects that is being affected is the educational relationship and the links established in it, which are fundamental for the teaching-learning process.
Neural Machine Translation Based on Back-Translation for Multilingual Translation Evaluation Task

This paper presents the systems developed by Beijing Jiaotong University for the CCMT 2020 multilingual translation evaluation task. For this translation task, we need to build a Japanese-English translation system based on only Japanese-Chinese and English-Chinese data. Our method mainly relies on synthetic data generated by back translation. We implemented three different architectures, namely Transformer-big, Transformer-base and Dynamic-Conv. We also implemented multi-model ensemble technique to further boost the final result. Experiments show that our machine translation system achieved high accuracy without relying on any bilingual training data.
Pengaruh Fasilitas, Motivasi, dan Kedisiplinan Terhadap Prestasi Belajar MIPA di SMA Negeri 1 Ceper Kabupaten Klaten

The objectives to be achieved in this study are to find out the influence of learning facilities at home on the learning achievement, effect of learning motivation, effect of learning discipline, learning achievement of Mathematics and Natural Sciences in Class XI MIPA students of SMA Negeri 1 Ceper, Klaten Regency. The results showed, (1) Effective contribution or the influence of learning facilities at home, MIPA learning motivation and learning discipline towards MIPA learning achievement 63.5% and the remaining 36.5% influenced by other variables not included in the this research. (2) The effective contribution of learning facilities at home to the learning achievement of Mathematics and Natural Sciences students was 12.2% and the relative contribution was 19.2%. (3) The effective contribution of MIPA learning motivation towards the learning achievement was 38.8% and the relative contribution was 61.1%. (4) The effective contribution of learning discipline to the learning achievement of Mathematics and Natural Sciences students was 12.5% and the relative contribution was 19.7%. (5) MIPA learning motivation is an independent variable that has the greatest influence on the learning achievement while learning facilities at home have the least influence on MIPA learning achievement.
Structuring Code-Switched Product Titles in Indonesian e-Commerce Platform

The product title in an e-commerce platform has a significant role in attracting consumers’ attention to the product. Poor quality of a product title needs to be improved, leading to a need for text structuring on the product title. This research proposes an approach to structure e-commerce product titles that are written in code-switched style, i.e. a pipeline method that consists of four modules; chunking, language identification, promotion words identification, and reformation. The model used in the first three modules involves the Conditional Random Field model. The experiment is carried out to test the robustness of the pipeline system. The results showed the 49,14% for the WER and 82,61% for the BLEU score.
LibGuides: CHSS Library: Useful Links

The guide provides user information about library hours and location, services and general links
Pengaruh Strategi Card Sort Pada Pembelajaran Tematik Terhadap Hasil Belajar Pada Siswa Kelas V SDN Sukun 3 Kota Malang

Abstract: The learning strategy used by the teacher in learning activities is not good. The purpose of this study, among others, was to determine the effect of the Card Sort Strategy in thematic learning on learning outcomes in fifth grade students of SDN Sukun 3 Malang. This type of research is quantitative. The research method is a quasi experiment. The instrument test is (1) validity test (2) reliability test (3) difficulty level (4) difference power. The prerequisite tests are (1) normality test (2) homogeneity test (3) hypothesis test. The results showed that the post-test mean score of the card sort experiment class was 85.71 and the conventional control class was 75.64. In addition, the hypothesis test using the independent t-test (mann-whitney) results obtained a significance of 0.002 <0 , 05, which means that Ha is accepted because sig 0.002 <0.05. Based on the results of the study, it can be concluded that there is an effect on learning outcomes using the card sort strategy on thematic learning materials (7 themes of life events, 1 sub-theme of national events during the colonial period).
OCR and Machine Translation

This lesson covers how to convert images of text into text files and translate those text files. The lesson will also cover how to organize and edit images to make the conversion and translation of whole folders of text files easier and more accurate. The lesson concludes with a discussion of the shortcomings of automated translation and how to overcome them.
Development Of Texture Enhancement Manufacturing Text Based On Language Coordination For State Elementary School Students

This study aims to (1) analyze the need for developing enrichment books to produce negotiating text based on politeness according to students and teachers' perceptions, (2) describe the principles of enrichment book development, (3) produce prototype enrichment books, and (4) describe assessment and prototype repair. The research was conducted by the research and development method in five stages, namely a preliminary survey, initial prototype development, product design, product validation, and design improvement. The results of this study indicate that this enrichment book is appropriate to be used as a companion book in learning. This can be seen from the average value of the results of the test of verification by Indonesian language teachers in class of 82.50 which is included in the category of good and expert lecturers at 71.75 which is included in the quite good category
초등 예비교사의 사회과 수업비평문 탐색: 온라인 수업시연을 중심으로

This study aimed to analyze the social studies class criticism of elementary school preparatory teachers. To this end, the curriculum and lecture courses of teaching methods of elementary social studies were designed to include a series of courses related to class criticism. Based on this, the online social studies review of prospective teachers who received social studies teacher education in non-face-to-face situations was analyzed under the class criticism observation model. The results of the study are as follows. First, the focus of class criticism mainly converged on class activities and instructional design. This was due to the familiarity with the class reading that was focused on scale-oriented class observation indicators. Second, the class review was freely negotiated regarding what, and how to look at of the class observation elements, and there appeared no specific rules of union between the elements. However, the method of delineation determined the impression of criticism and the tone of the article. Third, the class review revealed science, artistry, and peculiarities in each class. In this process, I could identify my qualifications as a social studies class teacher who judges both the parts and the whole. Fourth, the meaning of social studies recognized by prospective teachers appeared in various categories: the learner's daily life in the source of class content; and the curriculum tradition of the class method that was focused on inquiry and problem-solving; and the role theory of social studies centered on collaboration and social cultivation. Through this, the meaning of writing a class criticism for a prospective teacher was confirmed as a practice of self-directed learning wherein the teachers learn the essence and understanding of the curriculum and classes on their own; and as a process of forming collective intelligence of teacher expertise through various meetings within a homogeneous group.
Teaching Empathy through English Literature and Creative Writing in the Korean Classroom

Low levels of empathy in university students has become an increasing problem worldwide, including in South Korea, triggering an empathy crisis....
A Framework for the Semiotic Quality of User Stories

The use of user stories for expressing software requirements, in agile software projects and beyond, has only increased over the years. However, the results on the quality of user stories have been mixed. This paper proposes a semiotics-based, technology-and-tool-independent, semi-formal framework, comprising interrelated conceptual (meta-)models that provide an understanding to the concept of user story, user story context, user story quality, and violations of user story quality. In doing so, it elicits the unique nature of user story, highlights the challenges in modeling and addressing user story quality, presents the results of a preliminary survey of students and professionals on the use of user story, and, through various real-world examples, illustrates violations of user story quality.
Development of path tracking control of a tracked vehicle for an unmanned ground vehicle

This paper presents the development of path tracking control strategy for a tracked vehicle. A path tracking control strategy is developed using an established Stanley controller. In this study, the controller is integrated with geometric model based on Ackerman steering configuration to provide a relationship between the path tracking controller and tracked vehicle model. The tracked vehicle model consists of several modules such as kinematic model, velocity model, local and global coordinates, turning radius and dynamic model. The main contribution of this paper is the integration of path tracking control between tracked vehicle model and geometric model based on Ackerman steering configuration which is still limited in this research area. The validation of path tracking controller is completed in three various speeds, which are 0.5 m/s, 1 m/s and 3 m/s. All these three tests show that the percentage of error between desired path and the vehicle responses are below than 1% for all tests.
EDMTs: emotion detection on Myanmar texts

At this age, World Wide Web is growing faster. Many companies have built and launch Social Media Networks. People so widely use social media to get the latest news, to express their emotions or moods, to communicate with their friends and so on. Emotions of social media users are needed to analyze in order to apply in many areas. Many researchers do research on emotion detection using different techniques with their languages. Currently, there are no emotion detection systems for Myanmar (Burmese) language. So, this paper describes the emotion detection system for Myanmar language. This system uses our pre-constructed M-Lexicon, a Myanmar word-emotion lexicon, in the detection process. This system detects six basic emotions such as happiness, sadness, anger, fear, surprise, and disgust. In order to determine certain emotion from the text, we also apply rule-based decision making on sentence nature. We use Facebook users’ status, which has been written in Myanmar words. Emotions of user groups are also summarized in this system. Our approach achieves 86% accuracy for emotion detection in Myanmar texts.
PROVISIONING METHOD IN MOBILE CLOUD COMPUTING ENVIRONMENT G RAMAKRISHNA RESEARCH SCHOLAR OF SRI SATYA SAI UNIVERSISTY

The expected responses for grow the limits of mobile devices are: either to improve the hardware of mobile devices or to gadget some product level plan. Notwithstanding the way that hardware technology of mobile devices is advancing anyway the battery technology isn't advancing at a comparable development. In this manner, the elective course of action is to use the product level game plan like Mobile Cloud Computing (MCC). MCC grows the application dealing with limits of mobile devices by offloading computational genuine application/parts to the resource rich coursed application getting ready frameworks. The calculation convey will be as MMSI, TRAM, Adhoc Cloud models with Feedback approach utilizing ns3 test system and clouds to demonstrate that the throughput, network and administration culmination proportion.
Correlation-based heuristics and evaluation of existing greedy heuristics for VM allocations in cloud datacentres

Cloud computing has taken the world in its strides. In cloud datacentres, thousands of physical machines run continuously to execute incoming workload. Virtual machines are provisioned to incoming requests and are allocated to physical machines. Efficient mapping of virtual machines to physical machines has potential impact on the efficiency of datacentres. This paper proposes two greedy heuristics for virtual machines to physical machines mapping. We have empirically evaluated proposed heuristics and existing greedy heuristics for comprehensive datasets including PlanetLab datasets. Thereafter we have considered issue of hotspot, and proposed two heuristics for hotspot mitigation. We have evaluated our proposed hotspot mitigation heuristics for wide varieties of cases and case of SLA violation is also taken into consideration. Extensive simulation shows that our proposed heuristics are substantially faster than their counterparts. As clouds have strong business perspective also, our heuristics can be seen as prime alternate options for virtual machines to physical machines mapping.
Reinforcement learning with one-shot memory

In modern reinforcement learning to solve problems in virtual environments and realities including games, artificial neural networks are used as approximations. However, since the current artificial neural network is based on statistics, a large amount of data is required, so if there is no simulator, there are difficulties in using and applying it. Besides, making an accurate simulator is often a very expensive and hard problem in most domains we want to solve, and getting appropriate data and rewards from the environment is also not easy task, since they are mostly partially observable and relatively scarce. Due to these difficulties of acquiring sufficient data, there are certain limitations in utilizing artificial neural networks as function approximators in reinforcement learning. Therefore, by using the memory structure, which is case-based learning, a model that can perform fast learning in an environment with little data and sparse rewards. In the experiment, we challenged the Open AI Cartpole problem based on the existing policy gradient and memory. The advantage function that evaluates the gain, was implemented by transforming the one-shot learning memory structure. In subsequent experiments, the model showed poor performance on average due to large variance during training. However, by comparing the learning speed with other algorithms, it was confirmed that the top 10 and 5 scores obtained higher scores than other algorithms compared to the same episode within 100 small episodes. In conclusion, we found possibility that the method of using the memory structure can be effective for small data. And in the future, research on techniques to reduce the deviation of learning is needed. The model is expected to help the decision-making of artificial intelligence NPCs interacting with users.
GRUBERT: A GRU-Based Method to Fuse BERT Hidden Layers for Twitter Sentiment Analysis

In this work, we introduce a GRU-based architecture called GRUBERT that learns to map the different BERT hidden layers to fused embeddings with the aim of achieving high accuracy on the Twitter sentiment analysis task. Tweets are known for their highly diverse language, and by exploiting different linguistic information present across BERT hidden layers, we can capture the full extent of this language at the embedding level. Our method can be easily adapted to other embeddings capturing different linguistic information. We show that our method outperforms well-known heuristics of using BERT (e.g. using only the last layer) and other embeddings such as ELMo. We observe potential label noise resulting from the data acquisition process and employ early stopping as well as a voting classifier to overcome it.
Low-Light Image Enhancement with Color Transfer Based on Local Statistical Feature

The image obtained under the condition of extremely low illumination has the characteristics of high noise, low contrast and the inability to display the detail information in the dark area. These features seriously reduce the visual quality of image and also degrade the performance of other computer vision algorithms that are designed for high quality input. In this paper, we propose a color transfer method based on the local color statistical feature to enhance the low-light image. In this method, an image with clear texture of normal exposure is used as a reference image. Our strategy is to cluster the reference image and the low-light image into several local areas according to the first-order statistical characteristics of color, and then implement color transfer between the locally optimal matching regions to achieve color enhancement of the dark image. In order to obtain an accurate and smooth category area, we propose a new GMM model to fit the color component of the image. In this model the spatial neighborhood relation of pixel coordinates is taken into account and coordinate space smoothing parameters are added. Meanwhile, in the parameter estimation of GMM model, we propose a new method for Gaussian component merging, which can effectively reduce the clustering error. We conducted a number of experiments on real-world low-light image data sets to reveal the effectiveness of our approach, and the results show that our approach is superior over several state-of-the-art methods in both objective and subjective evaluation.
가상현실과 증강현실에 대한 간호대학생의 인식과 관련 교육실태 및 요구도 조사

Purpose: This study aimed to investigate the awareness, current educational status, and educational requirements of the nursing students regarding virtual reality (VR) and augmented reality (AR). Methods: A total 307 nursing students were included in this study using an online survey. Questionnaires were made to investigate the awareness of VR and AR. The final scale consisted of thirteen items and its validity and reliability were verified. Among the 203 nursing institution, 162 institutions were surveyed regarding education for VR and AR. Results: Among the participants, 99.7% knew about VR and AR, 83.7% had direct experiences, and 17.3% had made relative purchases. The awareness of VR and AR was about 4.35±0.73 (maximum scale of 6). Most participants thought that it would be favorable to use VR and AR for educational purposes in classes once or twice a week. Of the 162 nursing institutions, 30 invested in related facilities, and 13 invested in education in the form of cultural studies, lectures, or programs. Conclusion: The awareness of VR and AR among nursing students was positive and showed need for future education adoption. However, the current educational infrastructure is lacking. Therefore, there is a need to develop relevant educational programs in the future.