Reviewerly/exHarmony huggingface dataset:
TweeNLP: A Twitter Exploration Portal for Natural Language Processing

We present TWEENLP, a one-stop portal that organizes Twitter's natural language processing (NLP) data and builds a visualization and exploration platform.It curates 19,395 tweets (as of April 2021) from various NLP conferences and general NLP discussions.It supports multiple features such as TweetExplorer to explore tweets by topics, visualize insights from Twitter activity throughout the organization cycle of conferences, discover popular research papers and researchers.It also builds a timeline of conference and workshop submission deadlines.We envision TWEENLP to function as a collective memory unit for the NLP community by integrating the tweets pertaining to research papers with the NLPExplorer scientific literature search engine.The current system is hosted at URL.
Blockchain-Based Electronic Health Record Management

The existing electronic health records systems have many challenges like the patients are restricted to access their medical records and providing their essential medical data to the healthcare providers is quite difficult. In addition, the sensitive medical data stored in the existing centralized system isn't secured, as they have a high risk of getting hacked even after spending huge sums of money for security purposes. Blockchain technology is the most efficient solution to this problem. In our project, we successfully showcased that blockchain technology solves multiple problems like a single point of failure, transparency, authenticity and making the system more secure. Moreover, how this technology gives the patient full access to his/her medical data and also how it provides the authorization schemes to provide his/her available medical data to healthcare organizations or biomedical researchers.
Utilization of Unsupervised Anomalies Detector as a Tool for Managing the TDRS Constellation at GSFC

NASA’s Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The mission of the TDRS constellation is to provide relay communications from low-earth orbiting spacecraft to the primary ground station at the White Sands Complex in Las Cruces, New Mexico. Major customers include the International Space Station and Hubble Space Telescope. The NASA Space Network project office at GSFC manages the constellation of spacecraft. The constellation is over 30 years old, and a wide range of technologies and manufacturing techniques are represented on-orbit. Since 1983, the TDRS constellation has recorded thousands of gigabytes of telemetry data. Spacecraft telemetry data has changed throughout the three generations of TDRS spacecraft, however each spacecraft has the same basic functions with some generational enhancements. The constellation includes several spacecraft that have significantly outlived the manufacturer's projected lifetime. This has provided NASA with a significant benefit in terms of return on investment, however it places a burden on efficient management of the assets for maximum life without permitting a TDRS spacecraft to become stranded in its geosynchronous orbital slot. Consequently, the highest level of attention is paid to systems whose failure could strand a TDRS spacecraft in orbit. In this paper, we proposed two stages of analyzing spacecraft anomalies using data mining (DM) to enhance on-going predictions of spacecraft life, subsystem performance, and analysis of subsystem anomalies. The first stage conducts the unsupervised anomaly detector to detect potential anomalies in real-time telemetry data. The second stage introduced telemetry weight (TW) to each telemetry parameter to determine which parameter caused the strongest anomaly. We will present case studies of some of these analyses and how the data can impact decisions on the management of the constellation.
Evaluation Of Machine Learning Classifiers In Breast Cancer Diagnosis

Breast Cancer is one among the most deadly diseases that threaten women. It affects women in general but men are also not exceptions to it. Most breast cancers end up fatal except for a few cases. Early diagnosis of the disease helps in successful treatment and cure. Computer Aided Detection (CADe) or Computer Aided Diagnosis (CADx) System helps physicians to take prompt decisions in the field of medical imaging. CAD systems are aimed at identifying the abnormalities at the earliest in the human body which a human professional may fail to detect. Machine learning techniques in the field of medical imaging are increasingly being used in the accurate diagnosis of breast cancer. Machine learning classifiers such as Support Vector Machine and Neural Network are examined in this paper. Breast mammogram images, both normal and pathological images were used in this experiment. The machine learning classifiers were employed to identify the given image as either Benign ore Malignant. Performance of both the classifiers was recorded and it was observed that the Neural Network classifier excelled in the diagnosis with 98% accuracy than the Support Vector Machine classifier.
A Sequenced Edge Grid Image Technique for Sign Language Recognition

Currently there are many techniques and methods continuously proposed by researchers for Sign language recognition systems based-on machine learning. For data preprocessing for sign language, majority of researchers use single image of hands like static gesture images. Using only static hand images may not be efficient for real-world applications. In this paper, we propose an innovative technique for video processing called Sequenced Edge Grid Images (SEGI) for Sign Language recognition. The proposed SEGI is composed of images that represent the movement of hands within a single image, which can be applied to recognize a word or a sentence. To proof the concept, we have done several experiments with Thai sign language data collected from internet. SEGI was with existing techniques. Data are the Thai sign language learning video clips that are vocabularies to use in daily life. The proposed technique was implemented with convolutional neural network (CNN). For normal CNN, the experiments show that the SEGI with CNN increases of test accuracy rate with approximately 27% when compared to static gesture images.
항공서비스 전공 대학생의 긍정심리자본이 자기주도학습에 미치는 영향 : 학습동기의 매개효과

The purpose of this study is to verify the effects of positive psychological capital on learning motivation, self-directed learning as well as mediating effects of learning motivation of majoring in aviation service college students. The survey was conducted on 238 students. The results of the study are as follows: First, among the positive psychological capitals of aviation service majors students, self-efficacy, hope, and optimism were found to have a significant positive effect on learning motivation. Second, it was confirmed that the self-efficacy, hope and optimism had significant positive effects on self-directed learning. Third, the learning motivation was found to have a significant positive effect on self-directed learning. Fourth, the mediating effect of learning motivation in positive psychological capital and self-directed learning has a positive effect on self-directed learning. These findings suggest that positive psychological capital influence learning motivation and self-directed learning. There is a need for the development and proper operation of educational programs to improve self-efficacy, hope and optimism.
Estimation and spatio-temporal analysis of soil organic carbon stock in China using machine learning algorithms from 2000 to 2014&amp;#160;

&amp;lt;p&amp;gt;Soil is the largest carbon pool in terrestrial ecosystems, storing up to 2 or 3 times the amount of carbon present in the atmosphere, and a small change in soil carbon stock could have profound effects on atmospheric CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; and climate change. However, an accurate estimate of soil organic carbon (SOC) stock is still challenging. Previous studies on SOC stock prediction across China were mainly from biogeochemical models and national soil inventories, and large uncertainties still remained. In this study, we predicted SOC stock at 0 &amp;amp;#8211; 20 cm and 0 &amp;amp;#8211; 100 cm with 3419 and 2479field observations using artificial neural network (ANN), extreme gradient boosting (XGBoost), random forest (RF), and gradient boosting regression trees (GBRT) across China with the linkage of climate, vegetation and soil variables. Results showed that RF performed best among the four machine learning approaches with model efficiency of 0.61 for 0 &amp;amp;#8211; 20 cm and 0.52 for 0 &amp;amp;#8211; 100 cm. The trained RF model was used to predicted the temporal and spatial patterns of SOC stock at a spatial resolution of 1 km from 2000 to 2014 across China. Temporally, SOC stock at 0 &amp;amp;#8211; 20 cm (p = 0.07) and 0 &amp;amp;#8211; 100 cm (p = 0.3) did not change significantly. However, SOC density showed strong spatial patterns, the mean value of SOC density at 0-20 cm and 0-100 cm increased firstly, then decreased and then increased with the increase of latitude, and the minimum density was 39.83&amp;amp;#176; and 41.59&amp;amp;#176;, respectively. The total SOC stocks across China were 33.68 and 95.01 Pg C for 0 &amp;amp;#8211; 20 cm and 0 &amp;amp;#8211; 100 cm, respectively. The developed SOC stock could serve as an independent dataset that could be used for decision-making and help with baseline assessments for inventory and monitoring SOC stocks for global biogeochemical models in China.&amp;lt;/p&amp;gt;
Research on the Practical Teaching Optimization Mode of "Dual Teacher System" for Applied Undergraduates

The application-oriented undergraduate course was established to train more applied professionals to meet the needs of current social development. In applied subject teaching, practical training has a very important position, but traditional practical teaching is difficult to achieve satisfactory teaching results due to various limitations. In order to further optimize the practical teaching mode, major universities will adopt a “dual teacher system” Incorporated into practical teaching.
Handwritten Signature Verification System Using IoT

The traditional way of gathering information of handwritten signature is manual with the help of a person, the analysis and verification of the signature are done by the person who’s there for verification. In day to day life, the person who’s there for verification of any document can face a problem of signature verification it can be verifying a cheque signature or any document for legal authentication or any types of signing transaction documents which takes too much time if there are lot of documents to analyze and verify. The verification of the signature is divided into parts: signature extraction, and verification respectively. It uses hardware as well as software, out of which hardware include components like Raspberry Pi, camera, flashlight, switch, and software part which use different languages like Python, PHP and different algorithm to recognize and verify the signature. Accuracy of the verification increases with the increased quality of camera and intensity of light by using a flashlight. This paper is based on algorithms which are used in machine learning that uses the CNN and Siamese network for signature verification on the basis of trained dataset and also uses the pre-defined signature dataset that helps in creating a pattern for verification.
Modelagem de metadados multimídia: uma proposta ontológica baseada em reúso: an ontological proposal based on reuse

In recent years, there is a significant growth of semantically related and distributed data on the Web. In this context, metadata standards recommended by the World Wide Web Consortium have been used to describe and represent multimedia resources, making it possible to expand access points and improve the management, organization and recovery of digital resources on the network. A problem commonly found in institutional databases is the integrated treatment of heterogeneous data and the lack of standardization in description formats. The description of numerous items is generally carried out independently, with idiosyncratic standards of description, emphasizing different characteristics to be described and different terminologies to describe them, disregarding interoperability requirements between communities. The present research sought to advance in the forms of representation of multimedia documents with texts, videos, images, 3D models, audios, proposing an Ontological Model of Multimedia Reference capable of semantically organizing types of metadata to describe multimedia content in different contexts and needs. Methodologically, the modeling proposal was based on multimedia ontologies better placed in a ranking obtained from the NeOn Methodology guide, which ensured the selection of adequate knowledge resources in light of functional and non-functional requirements. The Ontological Model of Multimedia Reference proposed fundamental ontological classes and relationships from mappings and semantic alignments between reused ontologies, promoting a comprehensive architecture for the semantic organization of multimedia metadata addressed mainly to applications that deal with information resources on the Web.
Postposition of「Ritual Prayer(のりと)․Order of the King(せんみょう)」

「The Book of Order of the King(せんみょうがき)」including「ritual prayer(のりと)」and「order of the king(せんみょう)」is one of the most common forms of a sentence that is Japanized among Chinese-borrowing transcriptions. The book refers to transcriptions of verb endings, postpositions and an auxiliary verbs. The sentence structure of ritual prayers can be classified into type A, B and C. The order of the king is very similar to typeC which is the most developed type among ritual prayers. In terms of Chinese-borrowing transcriptionss, types A, B and C in ritual prayers contain the following transitional transcriptions for the Book of Order of the king: a turning point, the usage of Chinese characters, verb endings, postpositions, the joint-use of pseudonyms, the pronunciation of Chinese characters in compound verbs and even non-transcription of postpositions and an auxiliary verbs. Types A, B and C have gradually embraced and arranged the transitional transcriptions, and have settled in a regular pseudonym transcription for verb endings, postpositions and an auxiliary verbs. In the same age「Idu」, a Chinese-borrowing transcription, which was similar to the order of the king transcription, existed in Korea. Kono Rokuno(こうのろくろう) described the difference between the two forms as「the difference in the degree of the suitability for Chinese characters」. Through an analysis of the Chinese-borrowing transcription, pseudonyms of postpositions observed in the ritual prayer and the order of the king are unveiled as follows. The ritual prayer covers [ニ(爾/仁)], [ノ(乃/能)], [テ(氐/天/弓)], [ト(止/登)], [ヲ(乎/遠)], [ハ(波)] [ガ(我/可)], [モ(毛/母)] and [ソ曾(1)], while the order of the king contains [ニ(爾/仁)], [ノ(乃/能)], [テ(天/弓/氐)], [ト(止/等/登)], [ヲ(乎/遠)], [ハ(波/方)], [ガ(我/賀)], [モ(毛/母)], [イ(伊)], [ソ曾(11)], [ツ(豆/都/川)], [カ(可/加)], [シ(志/之/自)], [ヤ(夜/耶)], [ユ(由)] and [ヨ(與)].
On Positive Moderation Decisions

A crucial role of moderators is to decide what content is allowed in their community. Though research has advanced its understanding of the content that moderators remove, such as spam and hateful messages, we know little about what moderators approve. This work analyzes moderator-approved content from 49 Reddit communities. It sheds light on the complexity of moderation by giving empirical evidence that the difference between approved and removed content is often subtle. In fact, approved content is more similar to removed content than it is to the remaining content in a community---i.e. content that has never been reviewed by a moderator---along dimensions of topicality, psycholinguistic categories, and toxicity. Building upon this observation, I quantify the implications for NLP systems aimed at supporting moderation decisions, which often conflate moderator-approved content with content that has potentially never been reviewed by a moderator. I show that these systems would remove over half of the content that moderators approved. I conclude with recommendations for building better tools for automated moderation, even when approved content is not available.
The Influence of Scientific Attitude and Emotional Intelligence on Learning Outcomes of Research Methodology for FKIP Unpatti Ambonese Students

This study aims to analyze Effect of Scientific Attitude and Emotional Intelligence on Learning Outcomes of Research Methodology. The method used in this research is a survey method with correlational techniques. This method provides an overview of the research variables as well as investigates the influence between variables, therefore this method reveals factual data based on the information found. The results showed that: 1) The scientific attitude has a positive effect on learning outcomes of research methodology significantly at the significance level alpha = 0.05 with a value of F = 297.624, 2) Emotional intelligence has a positive effect on learning outcomes of research methodology significantly at the significance level alpha = 0.05 with a value of F = 28.165, 3) The scientific attitude and emotional intelligence together or simultaneously have a positive effect on learning outcomes of research methodology significantly at the significance level of alpha = 0.05 with a value of F = 956.777.
Federated Learning and Healthcare

With better and more computer and hardware technology so easily accessible, there is a huge influx of analytical data available from different healthcare stakeholders, from clinical institutions to insurance companies and from patients to pharmaceutical industries. This huge amount of data is a gold mine for uncovering insights that can help design an AI-integrated healthcare system aimed at providing better outcomes and quality at a reasonable cost.
Stylometry: The Royal Book of Oz - Baum or Thompson?

Main topics. Linguistic stylometry is concerned with the quantitative analysis of language and style. Authors have idiosyncratic styles in the way they build their sentences, which often makes it possible to determine with some probability who has written a particular text. In this chapter the focus is on one particular book from the Wizard of Oz series. Data. Occurrences of 50 frequently used function words were recorded for 21 Wizard of Oz books. The first 14 were written by L. Frank Baum, the last 6 by Ruth Plumly Thompson, and the authorship of one (the 15th in the series) was contested at the time. Research questions. The central question is who of the two authors wrote the 15th book - The Royal Book of Oz, which appeared two years after Baum’s death. Statistical techniques. Principal component analysis, cluster analysis.
Original and effective teaching

Teaching is the constant process in our life. It makes our parents, teachers/pedagogues at school or in the universities, mentors, experts, coaches, well-known academic, preachers and so on. The additional such factor maybe (and do indeed) Internat. Moreover, the common link among people is essentially exchanged as well. Many persons prefer have short conversation using SMS-communications, and it isn’t face-to-face unfortunately. In any transport (metro, bus, trolleybus) a man seeks interesting or useful information but has not noticed persons’ associates. It’s not good. We can see the next negative situation at home in a family. For example: let’s suppose that one student arrived home. Members of his family ask him about his routine business. And they usually here that everything is OK. Even during his eating, he tries to read the information which he sees in his mobile telephone or in the planetable. Besides, he sends different short communications and gives answers. There are not any friendly dialogs with his family (father, mother, grandfather, grandmother, brother or sister). That’s why in this article you can understand the new way how to exchange such negative situation in full.
Estrategia de apoyo estudiantil en tiempos de pandemia

As a result of the main reflections and analyses on the experience that has been carried out after the declaration of the health emergency due to the presence of the coronavirus in Uruguay, this article aims to present the student support strategy designed and promoted in this context by the Learning Support Program of the University of the Republic. A brief introduction is made to the institutional and health context in which this strategy is situated, and some preliminary results arising from the evaluation of its impact are presented, in the first semester of implementation. This strategy is framed in the largest public university in Uruguay, which has undergone a series of transformations during the last decades, involving a growing expansion and diversification of its student enrollment and academic offer, which translates every year into more students coming from the most diverse socioeconomic and cultural contexts. The strategy involves redirecting all its proposals for student support and orientation to a virtual modality, while promoting two new lines: distance entrance support tutorials, and a space for virtual psychological support and containment. It is based on the concept of institutional responsibility supported by the Program, which considers that it is the institution that is responsible for generating the guarantees so that everyone who is in condition and wishes to do so can develop their complete educational career.
Aware and Usage of Information Communication Technology among the MS Ramaiah Institute of Technology, Bangalore: A Study

ICT has grown up as the most popular and effective information tools of present age. In this study, the usage of ICT by the students of MS Ramaiah Institute of Technology, Bangalore is conceded. A total number of 207 respondents were selected and their response was obtained with the help of questionnaires. Most of the students use the ICT for education purposes and for checking E-mails. Slow access speed and over lode information produced by the internetare the two problems faced by the users.
P‐73: Innovative Controller for Touch‐Sensor Panel in Heavy‐Load Parasitic Capacitance

The innovative design of fully differential analog front end is swhich is the parasitic capacitance of a touch sensor is approximately 60% higher than a conventional smartphone. The newly developed touch sensor controller shows approximately 40 % higher SNR than a commercialized flagship smartphone, which is defined with the noise of peak to peak value in the touch signal on the zebra pattern display.
What if ‘eye’ find it too difficult? English L2 users’ response to text simplification

Open Educational Resources (OER) aim to provide equal access to education. Yet, as the language level used in OER presents a barrier to many learners, there is a need to make these resources more comprehensible. This study combined eye-tracking methodology and comprehension assessment to explore the effect of text simplification on English second language (L2) users, while also accounting for text organisational structure, and individual predispositions. A total of 37 adult English L2 users took part in the study. They had to read either an authentic narrative, authentic expository OER, or their linguistically simplified versions. The analysis showed that simplification led to better text comprehension, and text narrativity facilitated text recall, particularly at lower English proficiency levels. Eye-tracking measures revealed that text simplification led to an increase in processing time during the initial reading of the text and a decrease in processing time during text re-inspection. These findings have strong practical applications for online teaching with OER.