Reviewerly/exHarmony huggingface dataset:
Sentiment-based Candidate Selection for NMT

The explosion of user-generated content (UGC)—e.g. social media posts and comments and and reviews—has motivated the development of NLP applications tailored to these types of informal texts. Prevalent among these applications have been sentiment analysis and machine translation (MT). Grounded in the observation that UGC features highly idiomatic and sentiment-charged language and we propose a decoder-side approach that incorporates automatic sentiment scoring into the MT candidate selection process. We train monolingual sentiment classifiers in English and Spanish and in addition to a multilingual sentiment model and by fine-tuning BERT and XLM-RoBERTa. Using n-best candidates generated by a baseline MT model with beam search and we select the candidate that minimizes the absolute difference between the sentiment score of the source sentence and that of the translation and and perform two human evaluations to assess the produced translations. Unlike previous work and we select this minimally divergent translation by considering the sentiment scores of the source sentence and translation on a continuous interval and rather than using e.g. binary classification and allowing for more fine-grained selection of translation candidates. The results of human evaluations show that and in comparison to the open-source MT baseline model on top of which our sentiment-based pipeline is built and our pipeline produces more accurate translations of colloquial and sentiment-heavy source texts.
LibGuides: Grade 1 Library Guide, PXES: Small Moments

Materials to help support Grade 1 literacy units, including Small Moments, . . . . .(to be completed as the 2020-21 School Year progresses)
Detection of Consonant Errors in Disordered Speech Based on Consonant-Vowel Segment Embedding

Speech sound disorder (SSD) refers to a type of developmental disorder in young children who encounter persistent difficulties in producing certain speech sounds at the expected age. Consonant errors are the major indicator of SSD in clinical assessment. Previous studies on automatic assessment of SSD revealed that detection of speech errors concerning short and transitory consonants is less satisfactory. This paper investigates a neural network based approach to detecting consonant errors in disordered speech using consonant-vowel (CV) diphone segment in comparison to using consonant monophone segment. The underlying assumption is that the vowel part of a CV segment carries important information of co-articulation from the consonant. Speech embeddings are extracted from CV segments by a recurrent neural network model. The similarity scores between the embeddings of the test segment and the reference segments are computed to determine if the test segment is the expected consonant or not. Experimental results show that using CV segments achieves improved performance on detecting speech errors concerning those difficult consonants reported in the previous studies.
Artifact for "Language-Integrated Updatable Views"

This is the software artifact associated with the IFL'19 paper Language-Integrated Updatable Views by Rudi Horn, Simon Fowler, and James Cheney.The software is packaged as a Docker image and contains the Links implementation and the case study described in the paper.The artifact includes a README.md file which describes how to run the file.
SPATIAL REGRESSION IN THE NUMBER OF COVID-19 CASES IN BANDUNG CITY

ABSTRACTRegression method that pays attention to neighborhood or region is Spatial Regression with Spatial Autoregressive (SAR) and Spatial Error Model (SEM) approaches. This method is used as an approach for cases of the spread of Covid-19 , namely the number of active Covid-19 patients in the city of Bandung with the independent variable in the form of population per hectare. , population age 60 and over, poverty and population not working. The results of the Moran index test show that there is a spatial effect on the spread of positive active Covid-19 patients, and the SAR model is better than the classical linear regression model (OLS; Ordinary Least Square) and SEM with variables/factors having a significant effect, namely population 60 and over, poverty and residents do not work. The AIC value of the SEM model is 262.845 with a coefficient of determination (R-squared) of 0.457302. Keywords: Spatial Regression, OLS, SAR, AIC, Coefficient of Determination.
Sistem Pengelolaan Kegiatan Perusahaan Menggunakan Identifikasi QR Code

Activities in a company or institution are something that is usually done, the forms of these activities are generally training, socialization of new regulations, inauguration, and so on. These activities need to be recorded and the data managed as documentation or reference and consideration in subsequent activities. This activity requires planning starting from preparation, scheduling, distributing invitations via email, to implementing and recording the attendance of invited participants. The case study was conducted at PT Pelni Indonesia as an Indonesian National Shipping company that often carries out internal activities within the company. The problem that occurs in the management of company activities at PT Pelni is that so far it is still using the manual system. The participant registration process, participant data collection, sending invitations, recording participant attendance and so on are carried out in handwriting and stored in an excel file. Of course, this makes it difficult to search and manage data, and allows data loss or document slippage to occur. One solution that can be used to overcome these problems is to build an information system for managing company activity data. The management system can assist the HRD for data management needed in the implementation of activities carried out by the company. QR Code technology is also used to encrypt participant invitation numbers, verify participant data and to record attendance. The result of developing this system is a data management system for company activities by utilizing Quick Response Code (QR Code) technology. The generated QR Code can store various participant data in only 1 code and is used to verify participant data.
LibGuides: McNair Scholars: Research Guides for Your OU Major

A single access point for various OU Libraries' research guides and resources for McNair Scholars. Provides links to the research guides for the scholars' major.
THE USE OF RECOMBINATION ACTIVITY TO DEVELOP STUDENTS’ DISCOURSE SKILLS

Discourse analysis cannot be neglected nor separated from our lives. Several experts even claim its importance in language teaching. The need to teach a language in context is something which is unavoidable. Therefore, a lesson plan to develop students’ discourse is needed. This paper reports on a result of teaching practice conducted at a language institution in Yogyakarta. The research was started from lesson plan development to teaching practice in the classroom. The lesson plan followed top-down approach and text-based approach on the model. It focused on the use of recombination activity. At the end of the lesson, three questions were given as a reflection for the students. The results show that half of the students succeeded in arranging the sentences into correct order for the recombination task. it was found that half of them agreed that title provision might help them in doing recombination activity. In addition, all of them also agreed that the knowledge of language features of the text helped them in doing recombination activity. They even mentioned that it was the knowledge of conjunctions that helped them in doing the activities. These results prove that the use of recombination activity may develop students’ discourse skills. Keywords: discourse analysis; recombination activity; lesson plan
Role of the Jordanian TV in Raising Public Awareness of Covid-19 Crisis: A field study from perspective of a sample of the Jordanian public

This paper aims to identify role of the Jordan TV in raising public awareness of Covid-19 crisis. It is a field study conducted on a sample of the Jordanian public. The sample consists of 385 respondents. The descriptive analytics method is used to draw the findings. It is concluded that the Jordan TV has played a role in raising public awareness of Covid-19 crisis and discussing the health aspects related to the crisis. It is noticed that the Jordan TV has contributed to serving the Jordanian community by providing Covid-19 health awareness programs from the perspective of the Jordanian public. This paper recommends that the Jordan TV Administration should realize the importance of educating the Jordanian public about Covid-19 crisis and discussing the health aspects related to it. This is since the Jordan TV plays a key role in guiding the public to follow the good practice in dealing with the Covid-19 crisis.
Kuindzhi: Luminosity of Russian Culture

The article analyzes the work of Arkhip Ivanovich Kuindzhi. According to the author, Kuindzhi’s paintings are not for the mind or distancing thinking, but for the soul. Kuindzhi's way of thinking is contemplation, not conceptualization. The article considers Kuindzhi's works through the prism of P. Florensky's metaphysics of light. According to Florensky, light is not just illumination or the inner principle of things, but the transcendent source of the world. So we have to understand what role the light plays in Kuindzhi's paintings. The author shows that Kuindzhi is not a pantheist who deifies nature and depicts the self-illumination of things, but the artist who sees the world as a symbolic reality. The author explores the work of Kuindzhi in the perspective of the philosophy of modern culture. We look at Kuindzhi today, in the 21st century. The 21st century differs from the 19th or the 20th century. Kuindzhi’s work means light, and the 21st century is the age of darkness. The author brings forth the problem of the collision of modern metaphysics of darkness in the Western tradition and the light-bearing Russian culture.
Using an agent-based approach for robust automated testing of computer games.

Modern computer games typically have a huge interaction spaces and non-deterministic environments. Automation in testing can provide a vital boost in development and it further improves the overall software's reliability and efficiency. Moreover, layout and game logic may regularly change during development or consecutive releases which makes it difficult to test because the usage of the system continuously changes. To deal with the latter, tests also need to be robust. Unfortunately, existing game testing approaches are not capable of maintaining test robustness. To address these challenges, this paper presents an agent-based approach for robust automated testing based on the reasoning type of AI.
Accuracy Assessment of Typical Meteorological Year Data for a Photovoltaic System using a Bootstrap Method

The typical meteorological year (TMY) is a key element in the long-term performance predictions of photovoltaic systems.However, there is a loss of some hourly measured weather data during the formation of the TMY dataset owing to a lack of observations.Therefore, various statistical techniques or satellite observations can be utilized to address this limitation, and these interpolated data may represent some degree of uncertainty that can influence the accuracy of the TMY data.This may in turn affect the long-term planning reliability of the photovoltaic systems.Therefore, a bootstrap method was used in this study to evaluate the accuracy of TMY datasets in the prediction of long-term photovoltaic yields.The electricity production uncertainties obtained through a simulation conducted using this TMY were calculated with a confidence level of 95% for each resulting value as validated based on the long-term average electricity yield.The results show that the bootstrap method provides valid and more useful information than the deterministic approach.Therefore, it is the best method for quantitatively analyzing uncertainty in TMY datasets.The results described herein can serve as a guide for risk management strategies and other business decisions related to solar energy projects.In addition, the results can help planners achieve greater confidence when applying TMY data to feasibility studies.
Rapid scene categorization is not purely feed-forward: An EEG investigation of scene gist facilitation by sequential predictions

Rapid scene categorization is typically argued to be purely feed-forward. Yet, when navigating in our environment, we usually see predictable sequences of scene categories (e.g., offices followed by hallways, parking lots followed by sidewalks, etc.). Previous work showed that scenes were both easier to recognize, and to discriminate from phase-randomized noise, when shown in ecologically valid, predictable sequences than in randomized sequences (Smith & Loschky, 2019). But, when in scene processing do sequential predictions facilitate scene categorization? We examined this question using EEG. Participants saw scenes in either spatiotemporally coherent sequences (first-person viewpoint of navigating, from, say, an office to a classroom) or their randomized versions. Participants saw 288 scene RSVP sequences (each 1 target and 9 primes), while we recorded their event-related potentials (ERPs). Participants had to categorize one randomly selected target image on each trial, in an 8-AFC task. We found reduced ERP amplitudes for targets in coherent sequences roughly 140 milliseconds after image onset--when ERPs typically first index rapid scene categorization--and during the N300 and N400 components, suggesting both reduced identification costs and semantic integration costs in coherent sequences. Interestingly, such ERP amplitude reductions were predicted by low-level visual similarity between sequential prime-target pairs, suggesting that visual similarity might explain the reduced processing costs in coherent sequences. To test this hypothesis, in Experiment 2, we reran Experiment 1 behaviorally, but replaced the targets with noise images, and asked participants to predict the categories of the missing scenes. Target scenes were more predictable in coherent sequences. Importantly, the correlations of Experiment 2 image predictability with Experiment 1 ERP amplitudes (from 140-450 ms) were greater than for image similarity with ERP amplitudes. Thus, contrary to purely feed-forward accounts of rapid scene category recognition, both predictions for an upcoming scene category and visual similarity between successive scenes facilitate scene “gist”.
Apps for developing pronunciation in English as an L2

The goal of pronunciation teaching should be to enable learners to develop intelligible pronunciation and, in order to do this, it is important to teach perception and production of the most relevant segmental and suprasegmental features of pronunciation, considering specific groups of learners (CELCE-MURCIA et al. , 2010). Technology has played an important role in pronunciation teaching, and the applications developed for pronunciation instruction enable learners not only to engage in pronunciation activities, but to have access to a greater variety of input and immediate feedback. Having this in mind, this study aimed at analyzing the content, the pronunciation teaching steps, the features, and usability resources of pronunciation apps. In order to guide the analysis, a framework was developed based on literature related to the areas of pronunciation teaching and of Mobile Assisted Language Learning (MALL). The results showed that there is a tendency for the apps analyzed to focus more on segmentals. All of them offer description and analysis, listening discrimination, and controlled practice of the pronunciation features, as well as feedback. However, they were limited in terms of guided and communicative practice, of Automated Speech Recognition (ASR), and of variety of input.
INVESTIGATING IDEATIONAL MEANINGS OF NARRATIVE TEXTS IN SENIOR HIGH SCHOOL TEXTBOOKS

Penelitian ini bertujuan untuk mengetahui makna ideasional teks naratif dalam buku teks sekolah menengah atas. Penelitian ini menggunakan metode studi kasus kualitatif dan data diambil dari lima teks naratif dari dua buku teks berbeda yang memuat gambar dalam teks. Teks verbal dianalisis dengan menggunakan sistem transitivitas Halliday (1994) dari linguistik fungsional sistemik (SFL) untuk menyelidiki jenis proses yang digunakan dalam teks verbal. Gambar dianalisis dengan menggunakan teori tata bahasa visual Kress dan van Leeweun (2006) untuk menyelidiki jenis proses dalam gambar. Sementara itu, analisis kerangka kerja Royce (2002) digunakan untuk menyelidiki hubungan antara moda verbal dan visual dalam teks naratif. Temuan menunjukkan bahwa proses material sebagai jenis proses yang paling sering digunakan dalam teks verbal dan proses analitis sebagai jenis proses yang paling sering digunakan dalam gambar. Dalam hubungan antara moda verbal dan visual, kedua moda dalam teks naratif dielaborasi dan bekerja sama untuk menyampaikan makna ideasional. Repetisi, sinonim, dan antonim juga ditemukan dalam teks naratif. Berdasarkan temuan tersebut, guru harus memiliki kesadaran lebih untuk memilih bahan teks naratif untuk diberikan kepada siswa.The research aimed to investigate the ideational meanings of narrative texts in senior high school textbooks. The research used a qualitative case study method and the data were taken from five narrative texts from two different textbooks that contain images in the texts. The verbal texts were analyzed by using Halliday’s (1994) transitivity system from systemic functional linguistics (SFL) to investigate the types of processes used in the verbal texts. The images were analyzed by using Kress and van Leeweun’s (2006) theory of visual grammar to investigate the types of processes in the images. Meanwhile, a framework analysis of Royce (2002) was used to investigate the relations between the verbal and visual modes in the narrative texts. The findings show that material process as the most frequently used type of process in the verbal texts and analytical process as the most frequently used type of process in the images. In terms of the relations between the verbal and visual modes, both modes in the narrative texts were elaborated and worked together to convey the ideational meanings. It was also found repetition, synonymy, and antonymy in the narrative texts. Based on the findings, teachers must have more awareness of selecting the narrative text materials to provide to the students.
RESEARCH ON THE TRAINING OF ELECTROMECHANICAL COMPLEX TALENTS IN HIGHER VOCATIONAL COLLEGES UNDER THE BACKGROUND OF ARTIFICIAL INTELLIGENCE

The new technology in artificial intelligence has a far-reaching impact on the intelligent development of the manufacturing industry. These new skill requirements are bound to promote the reform of vocational education in the field of intelligent control. It is urgent to train a group of highly skilled compound talents who can adapt to the development of artificial intelligence and intelligent manufacturing and can engage in the field of intelligent control technology. In this background, this paper takes Binzhou Polytechnic as an example, which is a high level vocational college with Chinese characteristics. We investigate the current situation and development prospect of artificial intelligence and intelligent manufacturing and analyze the problems and development opportunities of mechatronics technology specialty under the background of artificial intelligence development. We put forward some suggestions on the personnel training system of mechatronics technology from the aspects of specialty orientation and the integration and optimization of training specifications, the development of specialty curriculum system, the reform of teaching mode, and the construction of innovative teacher team.
Impact of resale royalty on primary and secondary sale prices in the non-fungible token marketplace

Startups adopt non-fungible token (NFT) standard on Ethereum network and create marketplaces for collectible assets, trading cards and digital art. NFTs minted on blockchain must be paid a gas fee to miners at delivery. Due to increased traffic on Ethereum blockchain network, the constant upsurge in cost of minting bear hard on monetary security of token creators. As a potential cure for ever-rising minting cost, NFT platform managers adopt resale royalty which is a practice that transfers a fixed percentage of future sale amount to the creator of digital good. The adoption of resale royalty is seemingly beneficial for token creators as it provides a recurrent cash flow. However, it may have unintended consequences on the sale prices, which, in turn, affects the commission revenue for the platforms. In this paper, we develop several hypotheses for the impact of resale royalty on average sale prices on the primary and secondary markets. We leverage a panel dataset from a popular NFT marketplace and test our hypotheses using instrumental variables estimation. We find that the resale royalty leads to a significant decrease in the average primary sale price. We also find evidence that the average secondary sale price significantly increases with resale royalty. Our estimations suggest that token creators benefit from NFTs with resale royalty only after they are sold on the secondary market numerous times. Contrary to the conventional wisdom, re-sellers are better off when they make investments to NFTs with resale royalty even after adjusting for the royalty premium. We argue the managerial implications of the adoption of resale royalty for platform managers, token creators and re-sellers.
LibGuides: Resources for Teachers: Home

A selection of materials and websites for teachers. Includes: Professional development, classroom management, sources for lessons, etc.
F18 The ethics of exploring social cognition in hd using ethnography during a pandemic

<h3>Aim</h3> Using ethnography to study social cognition through social functioning in HD will begin to address the empirical gap in our knowledge of everyday life with HD from the perspective of both people with HD and their companions. As ethnography moves into the messiness of real life in that the researcher is an observer of the participants in their own space and this now needs to include Covid safe strategies (i.e. online observation) risks to all parties may be seen as greater due to the nature of HD alongside exploring the intimacies of interaction remotely. Primacy needs to be given to the principle of ‘do no harm’. <h3>Method</h3> Whilst our fears often do not come to fruition, researchers using this methodology with people with HD and their companions need to consider: Involving a patient participant group Building trust and rapport amongst the community through the life of the project and beyond Family dynamics Tensions which may have been worsened by the pandemic A distress strategy Adjusting the way we as researchers do things and not the other way round Giving more structure, planning and prompting to optimise HD engagement Fluid revisiting of consent Access to technology The limitations of technology in this population <h3>Outcome</h3> Thoughtful preparation although time consuming may enable equitable access to all interested participants but also reduce risks. As Markham notes methods = ethics.