Reviewerly/exHarmony huggingface dataset:
¿AcaDEmia o acadeMIa? Palabras heterotónicas en el aprendizaje de portugués como lengua extranjera por hablantes de español

espanolDentro del aprendizaje de portugues como lengua extranjera por hispanohablantes (PLE-HE), las palabras heterotonicas se presentan como una interferencia fonologica frecuente. En este articulo, primero, se contrastaran desde un punto de vista sincronico aquellas estructuras que ocasionan una tonicidad divergente en determinadas palabras del espanol y del portugues. Tras ello, se demostrara mediante un estudio empirico realizado con aprendices de portugues que se trata de una interferencia frecuente. Esto llevara a senalar la importancia de considerar un tratamiento mas especifico de este tipo de fenomenos prosodicos en manuales especializados en el aprendizaje de estas dos lenguas. EnglishCognates between Spanish and Portuguese often differ in their stress placement. Hence, they can be expected to be a frequent source of phonological interference for Spanish-speaking learners of Portuguese. In the following article, this interlingual phenomenon shall be examined in two steps: Firstly, a synchronic contrastive analysis of the two languages will shed light on the systematic differences in word stress. Secondly, empirical evidence for the relevance of this error type will be presented based on the results of a study conducted with learners of Portuguese and this type of words. Finally, it will be argued that textbooks should treat the underlying pronunciation patterns more extensively.
Automation of (meta-)data workflows from field to data repository

&amp;lt;p&amp;gt;In Earth and environmental sciences data analyzed from field samples are a significant portion of all research data, oftentimes collected under significant costs and non-reproducibly. If important metadata is not immediately secured and stored in the field, the quality and re-usability of the resulting data will be diminished. &amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;At the Helmholtz Coastal Data Center (HCDC) a metadata and data workflow for biogeochemical data has been developed over the last couple of years to ensure the quality and richness of metadata and enable that the final data product will be FAIR. It automates and standardizes the data transfer from the campaign planning stage, through sample collection in the field, analysis and quality control to the storage into databases and the publication in repositories.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Prior to any sampling campaign, the scientists are equipped with a customized app on a tablet that enables them to record relevant metadata information, such as the date and time of sampling, the involved scientists and the type of sample collected. Each sample and station already receives a unique identifier at this stage. The location is directly retrieved from a high-accuracy GNSS receiver connected to the tablet. This metadata is transmitted via mobile data transfer to the institution&amp;amp;#8217;s cloud storage.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;After the campaign, the metadata is quality checked by the field scientists and the data curator and stored in a relational database. Once the samples are analyzed in the lab, the data is imported into the database and connected to the corresponding metadata using a template. Data DOIs are registered for finalized datasets in close collaboration with the World Data Center PANGAEA. The data sets are discoverable through their DOIs as well as through the HCDC data portal and the API of the metadata catalogue service.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This workflow is well established within the institute, but is still in the process of being refined and becoming more sophisticated and FAIRer. For example, an automated assignment of International Geo Sample Numbers (IGSN) for all samples is currently being planned.&amp;lt;/p&amp;gt;
Sentiment Analysis of Tweets using Machine Learning

The growth of various social networking sites has enabled people to express their opinions, thoughts, and feelings. Social networking platforms such as Twitter, Facebook, etc. are filled with opinions and thoughts. The enormous data gathered using these platforms can help to analyze the sentiment of people. Sentiment analysis is the method to interpret and classify emotions into categories viz positive, and negative.. Data mining is harnessed to uncover relevant information from web pages. The main emphasis of this research is to classify which machine learning algorithm gives better accuracy. Python language is used to implement the proposed system. Machine learning classifiers such as Naive Bayes, SVM, and Decision Tree are applied to categorize the tweets as positive or negative.
Projects using METAL highway graphs with traveler data

The Map-based Educational Tools for Algorithm Learning (METAL) project1 provides graph data representing actual highway systems around the world, along with interactive, map-based algorithm visuali...
LibGuides: How to Make Your Work Open Access: OA Archiving - Deposit AAM

This guide provides general information and resources about open access and scholarly publishing to HKUST researchers. You will also find information about the author accepted manuscript requirement by the University.
매체의 확장을 통한 일상성의 탐구 - 본인의 회화, 디지털 프린트, 영상작업을 중심으로

In my works, images that surface through paintings are based on the notion of consciousness, but at the same time they contain the actuality of daily life. Paintings in my exhibition entitled Unfamiliar Maps; Multiple Perspectives are reworked in the forms of digital prints and videos, continuing to produce new meanings not found in the paintings. First, when reworking from painting to digital printing, meaning is expanded in relation to images, concrete objects, subjective spaces and explanations. In the video works, actual objects and virtual images are combined organically, and the real and virtual areas cross each other. The link between the objects is also reinforced by the story. Reworking from a painting to an image led to a formative idea which remained in the painting of actual verifiable objects and escaped from the subjective inner area to move to reality and virtual areas through time. In an actual exhibition, movements between media proceeds in an integrated manner, and the viewer experiences an expansion of meaning through consciousness. This type of work reflects the researchers' view of the world as a state of fragmented images and emphasizes the relationship context of reality by transforming everyday experiences into repetitive play through work.
Wheelchair with solar panels

The 11th International Conference on Information Science and Information Literacy – ICISIL 2021 – will take place in Brașov, Romania, on the 11th and 12th of March, 2021. The conference will be organized by Transilvania University of Brasov, Lucian Blaga University of Sibiu, with the support of The Public Library of Brașov County and MB Think Tank. ICISIL 2021 will focus on: The Role of Information in Services Provided to Innovative Users. ICISIL 2021 will bring together professionals, academic staff, including doctoral students, with a focus on Information Sciences, along with policy-makers and stakeholders. The conference fosters an inter-disciplinary exchange of knowledge. Sessions include contributed papers, keynote presentations and panel discussions. We support PhD students in the field through reduced registration fees. In addition, a PhD workshop will be held in the morning of 12 March 2021, as part of the ICISIL 2021 annual conference, at no extra cost for all registered students. Moreover, ICISIL 2021 will host a workshop on Innovative Technologies, focusing on 3D printing. Please submit your article via Editorial Manager Editorial Manager ABSTRACTING & INDEXING 11th International Conference on Information Science and Information Literacy is covered by the
The Effetiveness Of Using Personal Letter on Students Recount Text Writing (An Experimental Research at the First Grade of SMAN Cijaku)

Ahmad Guntur, 132301507. The Effetiveness Of Using Personal Letter on Students Recount Text Writing (An Experimental Research at the First Grade of SMAN Cijaku). Undergraduate research paper, Faculty Of Education And Teacher Training The State Islamic Uneversity Sultan Maulana Hasanuddin Banten. Advisers: Drs.H.Busthomi Ibrohim M.Ag and Emiliya Sukma Dara Damanik,M.HumThis research conducted based on the statement of problems, 1) How is students’ writing ability on Recount text; 2) How the influence of personal letter Technique on student’s writing recount text. This research oriented to the following aims, 1) To investigate how the student’s writing recount text; 2) To explore influence of personal letter Technique on student’s writing recount text.To answer questions above, the reseacher collected data from 50 students spreading in two classes, each class has 25 students. One class as experimental group, and another one is control group. This research used an experimental research. The population was 50 students of the First grade of SMAN Cijaku. The reseacher took sample from X B class as control group, and X A class as experimental group. The data was gathered through pretest and posttest because the writer used experimental method.Based on the result, the reseacher got mean pretest score 63,16 and posttest 65,44 from control class. While from experimental class the reseacher got mean pretest 63.8 and mean posttest 70.6. The score of experimental class increase on 6.8% it is better than control class students with increase on 2.28%. According to the data, the score of t0 (t observation) 4.91 is higher than tt(t table) from 1% and 5% 2.01 and 2.68 It means that using personal letter Technique gives the significant influence in teaching writing recount text
PELAKSANAAN PROGRAM PERPUSTAKAAN DAERAH DALAM MENUNJANG MINAT BACA ANAK USIA DINI PANDEGLANG – BANTEN

Reading interest in children must be applied from an early age, the implementation of the regional library program is effective in helping children to foster a desire for children to come to the library, the desire for children to open books, and the desire for children to read books. This study aims to determine what kind of implementation of a mobile library program in supporting early childhood reading interest in the regional library of Pandeglang Regency, Banten, with a total of 3 programs. Data collection procedures were carried out by means of observation, interviews, and documentation. Data analysis using data reduction, data presentation, and drawing conclusions. From the research results, it was found that the implementation of the regional library program in supporting children's reading interest has been carried out well, because the program that has been running has been right on target, namely PAUD Kindergarten children in Pandeglang district and the program is appropriate, because in this program children are already doing activities that encourage children's desire to read.
PENGEMBANGAN SISTEM PENUNJANG KEPEGAWAIAN (FEEDER SIMPEG) MODUL SEKOLAH VOKASI UNTUK HONORARIUM INSTRUKTUR (STUDI KASUS: SEKOLAH VOKASI STT - PLN)

This research aims to develop and build an Employment Support System (FEEDER SIMPEG) Vocational School Module for instructor honorarium, integrating SIKAP and SIMPEG as data needed in the Vocational School Module, calculate the honorarium automatically using a system with data that has been integrated, and monitoring the status of instructors who become vocational school instructors. In this research, system development using the Scrum method which includes activities such as creating a product backlog, determine sprint planning, Daily Scrum, sprint review and sprint retrospective which requires development in a short and effective time. This research is expected to make it easier to collect data on batch data, competency program data, classes & rates, subjects, class schedules, instructor attendance, and teaching recap and instructor honorarium. Tests carried out to determine the functionality of each feature run well or not, this test uses the User Acceptance Testing (UAT) type of black-box testing. Based on this research the results obtained, Vocational School Module that can help manage all data and honorarium instructors properly.
A cluster-based approach to predict serious adverse events in surgery

Managing risks related to the actions and conditions of the various elements that make up an operating room is a major concern during surgery. Determining alert thresholds is one of the main challenges. In this document, we propose to focus on the causes that lead to incidents as well as their prediction, which are essential elements in the determination of alerts. For that purpose, we have designed an architecture that couples a Multi-Agent System (MAS) with Case-Based Reasoning (CBR). The ability to emulate a large number of situations thanks to MAS, combined with analytical data management thanks to CBR is an efficient way of analyzing the state of the system and predicting its evolution. Beyond this architecture, decision support tools have been integrated in order to classify the behavior of entities and predict their evolution. This paper presents and analyzes the performance of our original cluster-based method (similVar) dedicated to the determination of unpredefined alert thresholds and risk prediction in surgery rooms. The obtained results prove the ability of our approach to analyze and predict the evolution of variables as disparate as the constants of a patient (“CAPNIA”, “HYPOTHERMIA”, “FeCO2”, “SpO2” etc.) or human fatigue.
A comparison of multiple-hurdle approach and latent class modeling approach for detecting insufficient effort responding in the survey data

자기보고식 설문자료에서 다양한 양상으로 나타나는 불성실 응답은 분석 결과의 타당성을 저해하거나 연구 결과에 편향을 야기할 수 있는 중요한 요소이므로, 자료 분석 시 불성실 응답을 보인 사례들을 탐지하여 그 영향력을 제외하는 것은 분석 결과의 타당성을 확보하는 데 있어서 매우 중요하다. 이에 본 연구에서는 자료 내의 불성실 응답 탐지를 위한 주요한 두 접근법인 다중허들 접근법과 잠재계층 모형의 불성실 응답 탐지 성능을 비교하였다. 먼저 표본크기, 불성실 응답자의 비율과 불성실 응답 문항 비율 등의 조건 하에서 두 접근법의 정확성을 비교하기 위한 모의실험 연구를 수행하였다. 또한 대학생들을 대상으로 수집된 실제 온라인 설문자료 분석의 맥락에서 두 접근법을 적용하여 불성실 응답을 제외한 자료 분석을 실시한 결과를 비교함으로써 보다 합리적인 불성실 응답 탐지에 대한 방법론적 시사점에 대해 논의하고자 하였다. 본 연구의 주요 결과를 요약하면 다음과 같다. 첫째, 모의실험 분석 결과 다중허들 접근법은 대체로 잠재계층 모형에 비해 자료 내의 불성실 응답을 과도하게 탐지하는 반면, 잠재계층 모형은 어느 정도 불성실 응답을 정확히 탐지하는 동시에 표본의 손실이 비교적 적은 것으로 나타났다. 둘째, 실제자료 분석에서는 두 접근법을 적용하여 각각 수행한 통계 분석의 모형 적합도는 대체로 유사하였으나, 다중허들 접근법을 적용한 경우에는 표본의 손실이 과도한 경향이 있는 것으로 나타났다. 본 연구의 결과를 바탕으로 설문자료 내 불성실 응답의 탐지에서 다중허들 접근법과 잠재계층 모형의 유용성과 한계에 대해 논의하였다.Insufficient effort responding(IER) is commonly observed in self-report survey data. Since the presence of the IER can threaten the validity of the study by leading to potential bias for analysis results, it is an essential procedure to detect and treat the IER before the main statistical analyses are conducted. The purpose of this study is to explore the accuracy of the two most widely used methods for detecting the IER: the multiple-hurdle approach and the latent class modeling approach. The accuracy of the two methods were compared using simulation study considering various factors such as sample size, proportion of the examinees with IER, and the proportion of the IER items. The main results of this study are as follows. First, the findings in the simulation study showed that the multiple-hurdle approach tended to detect the IER excessively, resulting in the loss of sample size. The latent class modeling approach tended to detect the IER with reasonably high level of accuracy and had an advantage to preserve the sample size. Second, the real data analysis with the datasets that removed the IER cases with each of the two approaches showed slightly higher level of model-data fit for the latent class modeling approach and the loss of sample size was more serious in the multiple-hurdle approach. Based on the results, the advantages and limitations of the two approaches were discussed.
보육교사의 전문성 인식과 직무만족도가 영유아 권리존중 보육실행에 미치는 영향

The aim of this study was to examine the effects of child care teachers’ perception of expertise and job satisfaction on their respect for young children’s rights. It provides useful data for researchers seeking to improve the quality of child care practice and respect for young children’s rights. The subjects of this study were 280 child care teachers in Incheon Metropolitan City. Using the SPSS 21.0 Program for data analysis, we conducted frequency analysis, reliability analysis, ANOVA, post-test, Pearson’s product-moment correlation, and multiple regression analysis. We found significant differences in the respect for young children’s rights among child care teachers according to their perception of expertise and job satisfaction. In addition, we found significant correlations among the three variables and that the teachers’ age and some sub-factors of their perception of expertise and job satisfaction had significant effects on their respect for young children’s rights. This study suggests that high levels of perception of expertise and job satisfaction among child care teachers can improve their respect for young children’s rights.
Conception and Appreciation of Convolution Neural Network Using PyTorch for Pattern Recognition

In recent years, deep learning has been used in image classification, object tracking, pose estimation, text detection and recognition, visual saliency detection, action recognition and scene labeling. Auto Encoder, sparse coding, Restricted Boltzmann Machine, Deep Belief Networks (DBN) and Convolutional neural networks (CNN) is commonly used models in deep learning. In present era, machines have successfully achieved 99% accuracy in understanding, identifying the features and objects in the images. This state of the art performance of the machine was possible because of a specific type of neural network called Convolutional Neural Network, also known as convent. CNN is a special type of neural network which works exceptionally well on images. Before Convolutional Neural Networks, multilayer perceptrons have been used in building image classifiers. Image classification refers to the task of extracting information classes from a multiband (Color, Black White) raster image. Modern deep-learning frameworks like Tensorflow and PyTorch make it easy to teach machines about images as how data flows through a neural network and how the Deep layer is able to understand the data and capable of extracting the features from the data. This paper provides a clear idea how an image is passed as an input to the Convolution neural network and how CNN layers are capable of understanding and recognizing the Patterns from the Image using PyTorch.
美 국방부 및 육군의 인공지능(AI) 전략이 한국군에 주는 시사점

Recently, major developed nations such as the United States and China are considering artificial intelligence as a core technology that will innovate national competitiveness and future warfare. These nations are making national efforts to preoccupy technology. The United States also selected artificial intelligence as a top priority for national R&D in response to the increasing threat of competitors such as China and Russia, and established a national strategy to present its vision. The U.S. Department of Defense and the Army also announced AI strategies in response to national AI agenda, expressing their vision and will for the military application of AI. The U.S. Department of Defense has presented AI's military operation objectives, strategic approaches, and strategic focus areas in the AI strategy, and the U.S. Army describes its AI application goals, means, and methods. These two strategic documents are well-connected to each other and contain various strategic implications. It has many implications for the establishment of our military's AI strategy. In this paper, we tried to derive implications for the Korean military through theoretical considerations on the AI strategy of the U.S. Department of Defense and the Army.
초등예비교사의 프로젝트 학습이 자기주도적 학습능력 및 창의적 인성에 미치는 효과

The purpose of this study is to investigate the effect of the pre-service teacher's maker project learning on self -directed learning ability and creative personality. This study established an eight-week period of experimental treatment from March to April 2019, and the students who participated in the study formed a research group of 75 students in three of their advanced classes who are attending the second semester of B University of Education and taking courses in 'Teaching Research 1'. The experimental treatment of research groups was conducted by the process of producing creative outputs through training of manufacturers. The experimental group of the study group was a process of producing creative output through maker education. The theme was set up to create creative output by group, worked with the main tool, 3D pen, and utilized the recycling material. When the creative output is completed, it is announced by presenting the actual product in each group. The results of the study are as follows. First, project learning by pre-service teachers had an effect on self-directed learning ability. Second, project learning by pre-service teachers had an effect on creative personality. Third, pre-service teachers was interested in learning about the project and responded positively to the students' perception.
Improving Student Learning Outcomes in Social Studies Learning Using Quantum Teaching Model in Elementary School

This research is motivated by teachers who do not prepare lesson plans, are less able to create meaningful experiences for students, rarely provide opportunities for students to name material, do not provide opportunities for students to demonstrate student knowledge, and rarely give acknowledgment of student participation. As a result, the learning outcomes obtained by students were low. The purpose of this study was to describe the increase in student learning outcomes in social studies learning using the quantum teaching model in grade 4 of Bandar Buat Elementary School. The research method used was classroom action research. The results showed that, a) Lesson plan, cycle I was 78.6% with good qualifications and cycle II was 89.3% with very good qualifications, b) the results of the implementation of teacher and student activities, cycle I was 76.6% with good qualifications and cycle II is 87.5% with very good qualifications. c) student learning outcomes, cycle I obtained an average score of 74.4% with sufficient qualifications, and cycle II an average score of 82.7% with good qualifications. Thus, the quantum teaching model can improve student learning outcomes in social studies learning in grade 4 of Bandar Buat Elementary School.
Hardware Acceleration of Deep Neural Networks on Edge Devices with FPGAs

Deep Neural Networks (DNNs) provide excellent performance in the field of machine learning and with the current trend of technology moving towards more mobile and decentralised processing of data, many industries face the challenge of performing DNN inference in constrained edge devices. Field Programmable Gate Arrays (FPGAs) are reconfigurable semiconductor circuits that are well suited for processing DNNs efficiently through hardware acceleration, as developers can adapt and redesign specialized DNN accelerators for new emergent DNNmodels. In this work, we design and implement hardware accelerators within the PYNQ Z1 board. Our designs outperform the CPU only inference of MobileNetV1 by 40% for single thread and 25.4% for dual thread.