Reviewerly/exHarmony huggingface dataset:
Social Media Blueprints: A Study of Self-Representation and Identity Management

The landscape of social dimensions has tremendously changed with the existence of so-cial media as a powerful means to facilitate the process of creating and sharing infor-mation. The navigation, constructions and features of mediated communication fashion on social media have led to the forming of identity blueprints, consisting of narrative strategies in deploying and managing online identity. As a result, fascinating digital stories are formed wherein the content is curated to portray the desired identity. With the aim to examine the extent of gender-based perspective and tendencies in managing mediated identities through social media, this study employed a Mann-Whitney test to measure the variance between male and female responses. The results obtained indicate that statistically, there is a significant difference for both genders in the ways they manage their mediated selves and identities. This study also provides an insight on how social media platforms and specific interfaces like emojis are used as a tool to manage and shape mediated identity, reinforcing the concepts of online self-representation and identity management.
Developing of Learning Media Applications Based on Mobile Android Smartphones in the E-Learning System of PPs UNM

Abstract. This study aims to develop an Android smartphone-based learning media application and to produce a valid, practical, and efficient Android smartphone-based learning media application. This study uses the ADDIE development model which consists of 5 stages, namely Analysis, Design, Development, Implementation, and Evaluation. The testing procedure in this study through three stages, namely peer testing, expert testing and implementation in the form of small group trials and field trials. The informants in this study were experts, peers, and students. Data collection techniques used in this were questionnaires, interviews, and observations. While the data analysis technique used is descriptive data analysis. The results showed that the Android smartphone-based learning media application developed after validation was declared valid. The product in the form of an Android smartphone-based mobile learning media application is stated to be practical and efficient so that it is suitable or use, this is based on the results of small group trials and field trials which are strengthened by the results of interviews which state that this learning media application is practical and efficient, because this application can be installed on any brand Android smartphone, so it can be used and accessed anywhere and anytime and the features and facilities in this application are very complete and very easy to use. Based on the results of the research obtained, it is concluded that the learning media application based on the Android smartphone mobile that has been developed has met the categories of validity, practicality, and efficiency so that it is suitable for use. Keywords: Learning Media, Mobile Learning Android.
COMPARATIVE STUDY OF AGRICULTURAL EXTENSION SYSTEM OF NIGERIA AND THE GAMBIA

This study focuses on the analysis of Nigeria and The Gambia National extension policies and system. The study discussed three main themes (mission and goals, approach and functions, and clienteles). The study found that both two countries does not adopt legislated or formal national extension policy rather implied policies which were garnered, feasible, for the two countries through their government publications and published researched studies from academic and recognized developmental institutions. Generally, the analysis found that the two countries extension missions and goals focused on improving profitability of agricultural business and increasing output volumes; market share in achieving to enhancing quality of life and agricultural development. In terms of approaches and functions, the study observed that public sector extension in the two countries is undergoing transformation including decentralization and outsourcing extension services in the context of adopting a pluralistic system of extension delivery. While up to six models of extension are a commonly applied in the two countries, the dominant context is pluralism around public, private and NGO-based services. The dominant clientele was stated to be women and small- and medium-scale farmers. However, main barriers limiting women’s participation are still insufficiently addressed. The study concludes that it is important for the two countries authorities, perhaps supportively, to develop and establish formal extension policies that will manifest their vision, mission, goals and methods to provide a stable agenda within which targeted clientele and be purposively supported in the pursuit of sustainable agricultural development.&#x0D; Keywords: Extension, Extension Policy, Nigeria, The Gambia, Mission and Goals, Approach and Function, Clientele.
Identification of Factors Affecting Disk Drive’s Performance in Data Server by Use of Decision Tree Learning Method

Abstract To identify factors affecting magnetic disk drive’s data recording performance in data server, decision tree learning method is proposed and validated in this paper. Aiming at improving classification efficiency of various causes of HDD performance degradation, the ID3 algorithm of decision tree was first used showing the training set model would be able to achieve 100% accuracy. The maximum information entropy and information gain theory of ID3 algorithm were then adopted, from which accuracy range of 0.5–0.6 can be further achieved. The proposed method was validated to be effective for leveraging the data sever into Industry 4.0 ready smart machine.
Marathi Text Summarizer using Text rank algorithm

Manual summarization of huge documents of texts is tedious and error-prone. Also, the results in such quite summarization may cause different results for a selected document. Thus, Automatic text summarization has become important because of the tremendous growth of knowledge and data. It chooses the foremost informative neighbourhood of text and forms summaries that reveal the foremost purpose of the given document. It yields a summary produced by a summarization system which allows readers to understand the content of the document instead of reading each and every individual document. The aim of Text Summarizer is to supply the meaning of the text in fewer words and sentences. Summarization is often categorized into Abstractive and Extractive. This project is based on an extractive concept implemented on the studied models.Numerous text summarization systems are there today for English or other languages. But when it involves Indian languages, we observe an inadequate number of automatic summarizers. Our efforts during this direction are mainly for developing an automatic text summarizer for the Marathi Language. We glance forward to gauge the obtained summaries using the ROUGE metric.
INTEGRATION OF DIGITAL AND PEDAGOGICAL TECHNOLOGIES IN THE PROCESS OF TEACHING STUDENTS OF SOCIO-ECONOMIC AND PEDAGOGICAL AREAS OF TRAINING

Тhis study examines how to integrate the benefits of role-playing, collaborative and interactive learning, and realistic case studies in a virtual environment. The article describes the experience of implementing an educational model based on the online virtual reality platform Second Life (SL), which provides students with the opportunity to participate in role-playing games, interactive learning, and social interaction in the learning process. The proposed model consists of three modules: the module for the preparation of information, joint modeling, a reflexive module that provides practical skills by participating in a 3D game. Students and teachers who participated in the testing of the model gave a positive assessment. The main goal of developing an educational model that's based on Second Life is to improve the educational process, using the advantages of role-playing games, collaborative and interactive learning, as well as realistic cases in a virtual environment. This can be achieved using three modules: an information preparation module, a joint simulation module for studying the situation, and a reflexive module. Unlike some virtual educational systems, this model is specifically designed to help students understand the causes of problems and how to solve them through data visualization and simple modeling, easy communication, flexible interaction, collaboration, and immersion in the SL environment. By integrating the three modules in the SL environment, the model will provide more opportunities for effective collaborative learning in various fields of knowledge. In the information preparation module, teachers and students use moving avatars to perform all the actions presented in the demo virtual room in SL with the support of the Semantic Wiki Template. This template provides the platform with sections of information on the studied subject. Using it, teachers can easily pass practical tasks to the student, while students can respond and present results without having any deep training in the field of information technology.
On the Unit Instructional Design of the English Subject Based on Big Ideas

Although Curriculum Standards are advocating integrated unit instruction, there are still some problems in English classroom instruction, such as fragmented knowledge teaching, stagnant assessment and so on. Unit instructional design based on big ideas can mediate that challenge and promote in-depth learning. This paper starts with reviewing prior research about big ideas and unit instruction. Based on this, it presents a three-level framework to scaffold unit instructional design around big ideas. Then it explores how to use the framework to design unit instruction. At last, some suggestions are provided on how to design unit instruction more effectively and efficiently.
A Performance Discussion of Web Crawler Using Some Advanced Factors

Research is considering the error rate to enhance the accuracy and reducing space and time during web crawling considering advanced parameters such as TTL, frequency of web page visiting and spam reported by users. The proposed work is supposed to minimize the errors by filtering the urls on the bases of advance parameters. This would increase the accuracy during crawling. More over the time and storage space consumption would be reduced due to elimination of use less links. Accuracy in case of proposed work would be more than previous research because previous research did not considered the advanced parameter to filter the list of URL. The simulation that is representing the accuracy, error rate, time and storage comparison has been made using Matlab. Research is considering the frequency of visiting the page. Another parameter for the crawling is weight age of the page i.e. how much time page gets visited by the end users. The page which is most visited get high weight age. Moreover the research work would consider the TTL value of the page. TTL value shows what the expiry time of the page is. It is considering the pages that are having the less expiry time. The web crawling is capable to filter the web page list during searching considering visiting frequency, weight age and TTL value. The filter has also removed URLs that are reported as spam.
Hawg’s 30 Exit Game Flag Backgrounds V2 [1.3.0.1]

This mod will change the stock background on exiting the game to a customize Exit Background . 30 to pick from Argentina Australia Brazil ...
Using of Human Behavior Manners in the Process of a Film Actor Preparing for a Role

The purpose of the research is to reveal the features of the use of a human behaviour manner in the process of preparing a cinema actor preparing for a role. The research methodology is based on the principles of descriptive, comparative, cultural and artistic methods, the method of observation and experiment, in addition, individualizing and social and psychological approaches are applied during the study of the psycho-physiology of acting through the analysis of the behaviour in the process of individual human capabilities disclosing. The scientific novelty of the research is that the workmanship of the acting game is analyzed through the allocation of a visual demonstration of the manner of behaviour from the inner senses of the character for the first time. Conclusions. The research has shown and analyzed the use of human behaviour in the process of film actor preparing for his/her role. It has been found that the accumulated experience of body movements enriches the repertoire of acting, reduces the risk of the hero emotional state over the inner freedom of a professional actor. Accordingly, with the explored information, the main point here is that impersonation for a character is demonstrating by the simplest properties of human behaviour.
Motives of Foreign Direct Investment (FDI) in Ethiopia: An Empirical Analysis

The central aim of this paper is to investigate the major motives of inward FDI to Ethiopia from 1992-2015. Various economic and financial variables were taken into consideration to assess the relationship between FDI and its motivational factors. Ordinary Least Square method was applied to estimate the association, while Johansen’s co-integration test was employed to examine the combination, and Vector Auto-regressive (VAR) model was used to check whether there is a long run relationship between FDI and explanatory variables. The statistical results show that there is positive and significant relationship between FDI and market size, trade openness, exchange rate and financial freedom whereas inflation had negative and significant association with FDI. However, investment freedom and economic globalization indicated an insignificant relation. Even though all variables jointly affect FDI in the long run, the VAR result didn’t reveal any long term relationship between FDI and its motivational factors individually.
Employee Contact Tracing for a South Florida Hospital System During the COVID-19 Pandemic

with higher odds of accurately identifying CAUTI (Odds Ratio (OR) = 4.92, 95% Confidence Interval (CI): 1.2, 20.5) after adjusting for years of experience and hours spent on surveillance.Similar patterns of association were observed between completion of CLABSI training and correctly identifying CLABSI, but the result was not significant (OR = 2.35, 95% CI: 0.2, 23.8).Compared to those spending less time on NHSN surveillance (< 6 hours/week), those spending more time (>16 hours/week) had lower odds of identifying CAUTI but higher odds of identifying CLABSI.Conclusions: Limited studies demonstrate variability in the accurate application of NHSN surveillance definitions.Possible factors contributing to this variability are also lacking.Our results suggest that recent NHSN training and more years of IP experience may be associated with increased accuracy of HAI identification.However, spending more time with NHSN surveillance every week may not improve one's ability to identify CAUTI.
A Feedback Neural Network Model of Causal Learning and Causal Reasoning

We present a feedback or recurrent, auto-associative model that captures several important aspects of causal learning and causal reasoning that cannot be handled by feedforward models. First, our model learns asymmetric relations between cause and effect, and can reason in both directions between cause and effect. As a result it can represent an important distinction in causal reasoning, that between necessary and sufficient causes. Second, it predicts cue competition among effects and provides a mechanism for them, something which can only be done with feedforward models by assuming that two separate networks are learned, a highly non parsimonious assumption. Finally, we show that contrary to previous claims, a feedforward model cannot handle Discounting and Augmenting in causal reasoning, although a feedback model can. The success of our feedback model argues for a greater focus on such models of causal learning and reasoning.
CSK-ED: CRYPTOGRAPHY SECRET KEY GENERATION FOR EAVESDROPPING DETECTION USING CRYPTO MECHANISM

In Cryptography, the secret key distribution plays a significant role. The distinctive advantage of quantum key distribution is that it determines the presence of eavesdropper. Therefore, error might occur during key sharing because of eavesdropping. This leads to loss of security. To observe such errors, many algorithms were proposed and used. To avoid the bit error due to eavesdropping of the photons, Cryptography Secret Key Generation for Eavesdropping Detection (CSK-ED) that produces a shared secret key. This increases security as eavesdropper has no knowledge of the start and end of key exchange process. Any errors caused by eavesdropping are corrected by the sender and sent over open channel in a secured manner, another encrypted key.
An Intuitive Approach behind Distributed Ledger Technology

Blockchain is an empowering technology with distributed database documents or public ledger of transactions shared amongst organizations or individuals to provide trust and transparency. The decentralized distributed feature on top of cryptography makes blockchain grant higher safety than other systems. The significance of blockchain is to record transactions that are consensually shared and synchronized across multiple nodes of a network. In addition to these facts maintaining the integrity of the data, the fault tolerance of the system, scalability, and security are crucial concerns to be considered in upholding the reliability of a network. To mitigate with the prescribed facts and to make the nodes agree on the authenticity of the transaction, the consensus mechanism plays a significant role. The consensus mechanisms will ensure the correctness of solved transactions among nodes in the network, providing legitimized transactions. However, there are some major limitations and challenges and this chapter will carry out a comprehensive study of each consensus algorithm with its merits, demerits, and applications. Further, this chapter will address a factual study of possible solutions provided by research giants with their adapted innovative protocols thereby helping researchers to draw insights into this field.
Use of r packages “revtools” and “litsearchr” for automated keyword extraction to support building systematic medline searches in covid-19

Rationale: COVID-19 has triggered significant research activities worldwide, leading to an immense number of scientific publications in the MEDLINE. Given the high publication volume, proper combinations of structured subject headings (MeSH) and keywords are required to narrow down the search within the COVID-19 literature to the most relevant subtopic. Manual keyword selection is time-consuming and may not always be feasible. The recent text mining algorithms permit automated extraction of keywords from publications identified during pilot reference searches. It is not clear, though, whether automated keyword extraction would be useful if carried out on the pilot reference sample without prior enrichment for the COVID-19 subtopic of interest. This was addressed in the present study. Methods: A non-comprehensive MEDLINE search on the subtopic “Digital telemedicine in COVID-19” was conducted to obtain a pilot reference sample. Without manual enrichment for pertinent publications, keywords from this reference sample were extracted using two R packages, “revtools” (utilizes topic models and weighed keyword ranking) and “litsearchr” (utilizes keyword co-occurrence networks). In parallel, a manual systematic MEDLINE search strategy (MeSH concepts and headings, and manually-selected keywords, the total of 75 terms) was designed on the above topic as per PICO criteria and expert discussions. The automatically extracted keywords were then compared with the terms in manual MEDLINE search strategy. Results: The “revtools” package extracted 150 keywords from the “non-enriched” pilot reference sample. Of those, 12 (8%) keywords (either individual words or phrases) overlapped with the terms already present in the manual MEDLINE search strategy. This extraction also yielded 3 unique keywords useful to augment the manual search strategy. The “litsearchr” package extracted 203 keywords. Of those, 4 (1.97%) overlapped with the terms in the manual MEDLINE search strategy. In addition, 4 unique phrases extracted by this package were found useful for the manual search strategy. The automatically extracted and useful keywords (respectively, 3 and 4) were unique for each package. Conclusions: Automated keyword extraction, despite parallel utilization of different algorithms, cannot yet fully replace an expert-built manual MEDLINE search strategy on COVID-19. Yet this extraction, even if conducted on a non-comprehensive and non-enriched reference sample, can augment the manual search. Automated extraction from the reference sample enriched for the COVID-19 subtopic of interest may further increase the yield of useful keywords.
온라인 한국어 수업에서의 학습실재감과 학습 성과에 대한 연구 - 학습실재감, 만족도, 학습지속의향을 중심으로 -

The health and environmental impact of COVID-19 has caused a significant change in the field of Korean language education. Online classes have been actively implemented as a way to minimize educational gaps in situations in which face-to-face classes cannot be conducted. Following this trend, the learning presence and learning outcomes of 72 undergraduate students at B University in online Korean language classes are investigated. The research shows that cognitive presence is higher than emotional presence in learning presence. However, regarding emotional presence, the degree of awareness of emotional expression and emotion management is lower than other items. Satisfaction and learning persistence that are subdimensions of learning outcomes were measured on a five-point Likert scale. As a result, the mean score of those two subdimensions were found to be over 3.90, allowing students to positively evaluate learning outcomes in online Korean language classes. The results of the multiple regression analysis show that the higher the cognitive presence, the higher the student’s learning persistence, and the higher the emotional presence, the more the students are satisfied with their classes. The current study confirms that a high sense of learning presence is an important factor in achieving successful learning outcomes in online Korean language classes.
Bringing UMAP Closer to the Speed of Light with GPU Acceleration.

The Uniform Manifold Approximation and Projection (UMAP) algorithm has become widely popular for its ease of use, quality of results, and support for exploratory, unsupervised, supervised, and semi-supervised learning. While many algorithms can be ported to a GPU in a simple and direct fashion, such efforts have resulted in inefficent and inaccurate versions of UMAP. We show a number of techniques that can be used to make a faster and more faithful GPU version of UMAP, and obtain speedups of up to 100x in practice. Many of these design choices/lessons are general purpose and may inform the conversion of other graph and manifold learning algorithms to use GPUs. Our implementation has been made publicly available as part of the open source RAPIDS cuML library (https://github.com/rapidsai/cuml).