Reviewerly/exHarmony huggingface dataset:
Estimation of the ages of Devonian and Cretaceous stage boundaries in the Geologic Time Scale.

Estimation of the ages of period and stage boundaries of the Geologic Time Scale (GTS) has a long history that commenced over a century ago with the pioneering work of Arthur Holmes.Frequencies, precision and accuracy of radiogenic isotope age determinations used for time scale construction continue to increase steadily.Later stage boundary age estimates are accompanied by error bars based on 2-sigma age dating errors with incorporation of stratigraphic uncertainty.Most GTS2004 and GTS2012 results involved spline-curve fitting.In GTS2012, Milankovitch-type orbital climate cyclicity was used to tune the Neogene geologic time scale while seafloor spreading was combined with sedimentary cycle scaling to construct the Paleogene time scale, and it also contributed to the construction of the Cretaceous and Jurassic time scales.Geomathematical procedures continue to be refined for the next GTS which is in Gradstein et al. (2020).In this study smoothing splines are used to construct Devonian and Late Jurassic -Early Cretaceous time scales.This methodology and its results are described and some estimates are refined by incorporating Milankovitch cycle durations.
Density-based classification with the DENCLUE algorithm

&lt;p&gt;&lt;span&gt;Classification of information is a vague and difficult to explore area of research, hence the emergence of grouping techniques, often referred to Clustering. It is necessary to differentiate between an unsupervised and a supervised classification. Clustering methods are numerous. Data partitioning and hierarchization push to use them in parametric form or not. Also, their use is influenced by algorithms of a probabilistic nature during the partitioning of data. The choice of a method depends on the result of the Clustering that we want to have. This work focuses on classification using the density-based spatial clustering of applications with noise (DBSCAN) and DENsity-based CLUstEring (DENCLUE) algorithm through an application made in csharp. Through the use of three databases which are the IRIS database, breast cancer wisconsin (diagnostic) data set and bank marketing data set, we show experimentally that the choice of the initial data parameters is important to accelerate the processing and can minimize the number of iterations to reduce the execution time of the application.&lt;/span&gt;&lt;/p&gt;
Opening doors to discovery: Partnerships are key to advancing open science

The evolution of scholarly communications has accelerated in recent years, and 2020 for obvious reasons put even more pressure on the sector to evolve and adapt. By opening up access to research publications, by simplifying or customising the digital experience, or by improving the speed of publishing – the focus is firmly placed on the need for publishers to work more in partnership with each other, with institutions, funders, and new players in the market to develop solutions that meet the evolving needs of researchers and the wider community. Partnerships between different actors in the research process address challenges in practice and help advance open science, publishing, and the research system as a whole.
THE EFFECT OF STORYTELLING AND SOCIAL SKILLS METHODS ON SPEAKING SKILLS AGE 5-6 YEARS AT PAUD RA AL-MAHIR PERCUT SEI TUAN

Research it aims to: (1) MKnowing the difference in the speaking ability of children taught by the storytelling method compared to children taught using the conversation method; (2) Knowing the difference in speaking ability of children with high social skills and children with low social skills; and (3) Knowing the interaction of learning methods and social skills in influencing early childhood speech skills.The sample in this study is children in grades B1 and B2 as many as 32 students. Collecting data in this study used the observation guidelines for social skills and observation guidelines for early childhood speaking skills. Hypothesis testing is done by using the Two Way Anova test. The results showed that: (1)There is a significant difference between the children's speaking skills taught by the storytelling method compared to the conversational method (Fcount = 26.925 and sig. 0.000&gt; 0.05); (2) The speaking skills of children who have high social skills are higher than those who have low social skills (Fcount = 11.867 and sig. 0.043&gt; 0.02); and (3) There is an interaction between learning methods and social skills in influencing children's speaking skills (Fcount = 13.618 and sig. 0.001&gt; 0.05)
Is E-Learning for Primary School Students During the COVID-19 Pandemic a Boon or Bane?

Pandemic due to the deadly virus Covid-19 has put the entire world in complete lock-down, that too, for months together. India has locked-down the entire country for more than two months. Schools, Colleges and Universities were to be closed immediately putting everything in halt. Classes were abruptly suspended and examinations were to be postponed indefinitely. Education at all levels got affected hugely. Higher education institutes (HEIs) of India that are embedded with technology blend teaching-learning system, used electronic mode for teaching and learning, i.e., e-learning, immediately after the announcement of first phase of lock-down. Following the trend, some of the primary Schools of the country also adopted the virtual platform for teaching-learning. On this backdrop, it is necessary to unfold whether the stakeholders of primary education are ready for virtual platform of teaching-learning. Thus, the objective of this paper is to establish on the basis of personal interviews among 50 parents of primary School students and 30 primary School teachers.
Transactional Distance Theory and Compulsory Switching to Remote Teaching due to pandemic in Georgia

The study found that frequent communication with students, both synchronously and asynchronously, reduces the degree of student autonomy and forces them to engage in dialogue. This in itself is a guarantee of minimizing the transaction distance. One of the interesting strategies for this is to use informal language in written or oral feedback ("Gio, you wrote well, Kochagh!”,“Helen, why didn't you send me an assignment yesterday?”). Personal address to students is important in the asynchronous learning process. It is also important to understand that the student is somehow responsible for publishing his / her assignment in the classroom. Thus, the student becomes accustomed to dialogue with her classmates and feels accountable to them. It is advisable to contact the student's family frequently to find out if they have any problems accessing the Internet or if we can provide the student with a personal device. Sharing personal problems will also reduce the transaction distance and give the student the enthusiasm to engage in dialogue. Moderate use of humor and emotion, hope and encouragement, direct, sincere relationship, will somehow reduce the perception of physical distance, while minimizing the transactional distance.
Determinants of Employee’s Research Productivity in Non-Academic Organizations and Building and Validating a Self-Assessment Tool

Research is a systematic approach to answering evolving inquiries and creating new knowledge critical for organizational development, competitiveness, and innovation. This study aimed to identify the determinants that affect employee individual research productivity. And to create a reliable and valid measurement tool to assist organizations in identifying employees who are ready to produce research. The authors conducted a comprehensive literature review about the topic, illustrated the relationship between the relevant variables in a model, and tested the tool quantitatively on a sample of 161 nurses at a tertiary hospital in the UAE. The analysis revealed that integration of self-efficacy and self-determination plays a critical role in individual research productivity in non-academic organizations. The study also came up with a reliable and valid tool.
Fuzzy C-mean Missing Data Imputation for Analogy-based Effort Estimation

The accuracy of effort estimation in one of the major factors in the success or failure of software projects.Analogy-Based Estimation (ABE) is a widely accepted estimation model since its flow human nature in selecting analogies similar in nature to the target project.The accuracy of prediction in ABE model in strongly associated with the quality of the dataset since it depends on previous completed projects for estimation.Missing Data (MD) is one of major challenges in software engineering datasets.Several missing data imputation techniques have been investigated by researchers in ABE model.Identification of the most similar donor values from the completed software projects dataset for imputation is a challenging issue in existing missing data techniques adopted for ABE model.In this study, Fuzzy C-Mean Imputation (FCMI), Mean Imputation (MI) and K-Nearest Neighbor Imputation (KNNI) are investigated to impute missing values in Desharnais dataset under different missing data percentages (Desh-Miss1, Desh-Miss2) for ABE model.FCMI-ABE technique is proposed in this study.Evaluation comparison among MI, KNNI, and (ABE-FCMI) is conducted for ABE model to identify the suitable MD imputation method.The results suggest that the use of (ABE-FCMI), rather than MI and KNNI, imputes more reliable values to incomplete software projects in the missing datasets.It was also found that the proposed imputation method significantly improves software development effort prediction of ABE model.
O2D2: Out-Of-Distribution Detector to Capture Undecidable Trials in Authorship Verification.

The PAN 2021 authorship verification (AV) challenge is part of a three-year strategy, moving from a cross-topic/closed-set AV task to a cross-topic/open-set AV task over a collection of fanfiction texts. In this work, we present a novel hybrid neural-probabilistic framework that is designed to tackle the challenges of the 2021 task. Our system is based on our 2020 winning submission, with updates to significantly reduce sensitivities to topical variations and to further improve the system's calibration by means of an uncertainty-adaptation layer. Our framework additionally includes an out-of-distribution detector (O2D2) for defining non-responses. Our proposed system outperformed all other systems that participated in the PAN 2021 AV task.
A Comparison of Directed Reading Thinking Activity (DRTA) and Survey, Question, Read, Recite, and Reviews (SQ3R) Strategy to Improve Reading Comprehension Achievement of Indonesian Junior High School Students

The objectives of the research were to investigate whether there was a statistically significant difference of the students’ reading comprehension achievement after the implementation of DRTA strategy and SQ3R strategy. Furthermore, the approach used in this research was quantitative. The subjects were 32 students for DRTA group and 31 students for SQ3R group of Junior High school 9 Bandar Lampung. The reading tests were used as the research instrument. In addition, the data were analyzed by using Repeated Measure t-test. The result showed that there was a statically significant difference of students’ reading comprehension with the significant level 0.05. From the result, it is suggested that SQ3R strategy can facilitate students better to improve their achievement in reading comprehension. Keywords: reading comprehension, DRTA strategy,SQ3R strategy.
The Dynamic Link Between Financial Development, Trade Openness and Foreign Direct Investment: Empirical Evidence from Ethiopia

Foreign direct investment (FDI) is an important source of external financing and an important factor for the economic development of a country. FDI is highly important especially for developing countries as it brings modern technologies and management skills in addition to narrowing the financial gaps. In this sense the knowledge of what determines FDI will have a tremendous significance. With the objective of empirically determining the long-run and short-run relationships between financial development, trade openness and FDI inflows in Ethiopia this study employed the ARDL model. The findings indicated that private sector credit, M2 and trade openness have a positive and significant influence on FDI inflows in the long-run while M2, and trade openness has a positive and significant influence on FDI in the short-run too. Current period private sector credit had no impact on FDI while the one period lag of it has a positive significant effect on FDI. Likewise, the causality test results disclose the presence of bi-directional causal relationships between private sector credit and FDI, and between M2 and trade openness. Furthermore, the findings indicate a one direction Granger cause from M2 to FDI. Policy makers are advised to consider trade openness and financial development measures in their quest for more FDI inflow. Keywords: FDI, trade openness, financial development, ARDL, Ethiopia
Development of an Automated Machine Learning Solution for Educational Data Mining (S)

In the last decade, a large volume of data has emerged from the massive use of Virtual Learning Environments (VLE).The information contained in these data has enabled the evolution of Educational Data Mining (EDM), whose objective is to apply Machine Learning (ML) in educational contexts.However, building accurate and robust ML models requires, in most cases, advanced knowledge in data science.To solve such problems, Automated Machine Learning techniques have been studied, to simplify the repetitive processes of Data Mining.To validate the solution, the database of the Núcleo de Educac ¸ão a Distância da Universidade de Pernambuco was used.In comparison with the classic EDM approaches, the applied technique showed a superior result, obtaining an accuracy of 89% in the student performance classification process.This solution is called the Framework de Minerac ¸ão de Dados Educacionais (FMDEV), whose objective is to allow users to validate and make available ML baselines with greater productivity.The results of the experts' opinions prove that the FMDEV can contribute to the construction of better models of ML.
Animacy, Anaphora and Language Change in Swedish

This paper considers the role of animacy in the overt marking of indirect anaphors, i.e., noun phrases (NP), which introduce new discourse referents, that are grounded in the preceding discourse by means of a grounding element, an anchor. The indirect anaphors are considered in a diachronic perspective with reference to the emergent definite article and the variation between the article and other marking elements, in particular possessive pronouns. The study is based on an annotated corpus of Swedish prosaic texts from 1200–1550, which is a period of time when the definite article undergoes the process of grammaticalization in this language. The material was sorted according to the different combinations of the animacy of the anchor and the anaphor.The indirect anaphors which are anchored by means of expressions referring to animate entities show more variation of expression than those expressions referring to inanimate entities at the onset of definite article grammaticalization, but as the grammaticalization progresses, all indirect anaphors are by default expressed by the definite article. This is connected with the ongoing grammaticalization of the definite article and its extended use in new contexts. Keywords animacy; indirect anaphora; language change; definite article; Swedish
EVALUASI PAMERAN BUKU TAHUN 2017 SAMPAI DENGAN 2019 DISELENGGARAKAN OLEH PERPUSTAKAAN FAKULTAS EKONOMI UNIVERSITAS ISLAM INDONESIA

The book exhibition organized by the Fakultas Ekonomi Universitas Islam Indonesia Library Division is a form of community service especially for the FE UII academic community. This event is regularly held once a year and is part of a series of UII anniversary events. To improve the quality of implementation, evaluation is necessary, according to Bertrand the appropriate model is an assessment model for the media. The evaluation method used is descriptive qualitative. Primary data were obtained through interviews and observations, and secondary data were obtained from literature studies in accordance with the intended topic. The assessment of the exhibition by participants and visitors follows an assessment model of the media which consists of five components, namely attraction, acceptability, comprehension, self involvement and persuation. The collected data about the exhibitions were confirmed by the theory referred to, and also confirmed with the opinions of visitors and exhibitors through direct interviews. The results of the evaluation show that the components of attraction, acceptability, self involvement and persuation are in accordance with expectations, while the components of comprehension are not yet optimal.
Studying the Impact of the User Subscription Times in Different Cloud Configurations

In this paper, we model cloud systems and the user interactions with the cloud provider using the UML2Cloud profile.In general, users request virtual machines according to their needs, but they can also subscribe to the cloud provider and wait to be notified when the requested resources are not available.In this case, users indicate a maximum subscription time, so once this time elapses without being notified, users leave the system unattended.In this paper, then, we present an exhaustive research study to measure how the user subscription times affect the overall system responsiveness.In this study, three different cloud configurations are analyzed.Each cloud processes several workloads, which are generated using two distribution functions for the user arrivals, namely a normal and a cyclic normal distribution.The purpose of this study is to find out the inflection point for the waiting time of the users, from which the cloud responsiveness and its performance do not improve.The obtained information is therefore useful for the cloud provider to improve the configuration of the cloud.
Ensuring License Compliance in Linked Data with Query Relaxation

When two or more licensed datasets participate in evaluating a federated query, to be reusable, the query result must be protected by a license compliant with each license of the involved datasets. Due to incompatibilities or contradictions among licenses, such a license does not always exist, leading to a query result that cannot be licensed nor reused on a legal basis. We propose to deal with this issue during the federated query processing by dynamically discarding datasets of conflicting licenses. However, this solution may generate an empty query result. To face this problem, we use query relaxation techniques. Our problem statement is, given a SPARQL query and a federation of licensed datasets, how to guarantee a relevant and non-empty query result whose license is compliant with each license of involved datasets? To detect and prevent license conflicts, we propose FLiQue, a license-aware query processing strategy for federated query engines. Our challenge is to limit communication costs when the query relaxation process is necessary. Experiments show that FLiQue guarantees license compliance, and if necessary, can find relevant relaxed federated queries with a limited overhead in terms of execution time.
Basic principles and results of comparison of electronic signatures properties of the postquantum period based on algebraic lattices

The paper considers post-quantum projects of the Falcon and Dilithium electronic signature standards (ES), which are finalists of the NIST USA competition. The mathematical apparatus of algebraic lattices and appropriate methods are used in their construction. In further study and comparison of these post-quantum ES draft standards, both from a theoretical and practical standpoint, it is fundamental to substantiate the requirements for parameters and keys and in general to calculate the main indicators according to the accepted conditional and unconditional criteria. In such studies, it is important to determine the sufficiency of ensuring the guarantee of their security against classical, quantum, special and error-based attacks. This can be ensured, inter alia, through a reasonable choice of the sizes of common parameters and keys, and their practical construction in accordance with the adopted security model. However, when choosing the sizes of common parameters and keys, a significant contradiction arises between the properties of the draft of the Falcon and Dilithium ES standards, So increasing the size of the general parameters and keys leads to an increase in the complexity of transformations, and vice versa. The purpose of this article consists in analysis of problematic issues of choosing the size of parameter and keys for post-quantum ES projects based on mathematical methods of Falcon and Dilithium, and features of their implementation, including implementation according to the adopted security model. Comparative analysis of the stability and complexity of the Falcon and Dilithium ES draft standards depending on the size of the parameters and keys, including for 6 and 7 security levels. Development of proposals for decisions on the adoption of national post-quantum ES standards based on the mathematical methods Falcon and Dilithium. Determining the influence of unconditional, conditional and pragmatic criteria on the advantages when deciding on the ES standardization based on Falcon and Dilithium mathematical methods, including taking into account the availability of patents and the need to obtain licenses, etc.
Correlations between learning strategy and the ninth grade students’ reading comprehension in junior high school

This study is limited to the investigation of the correlation between students’ learning strategy, and reading comprehensionof the ninth grade students at State Junior High School 01 Buay Rawan, OKU Selatan. There were 85 students who has been selected as the sample of the research. The writer used correlational study and formula to see the correlation between two variable stated. Correlation about Students’ Learning Strategies (X&lt;sub&gt;2&lt;/sub&gt;) and Reading Comprehension (Y) for 0.028. Sig. Value 0.797 was higher than Alpha value 0.05 (0.797 &amp;gt;0,2146), H&lt;sub&gt;o&lt;/sub&gt; was accepted and H&lt;sub&gt;a&lt;/sub&gt; was rejected. In other words, there was no a positive correlation between Students’ Learning Strategies (X&lt;sub&gt;2&lt;/sub&gt;) and Reading Comprehension(Y). It can be stated that Students Learning Strategies (X) simultaneously have no significant correlated the reading comprehension(Y).
Design and Performance Analysis of a Training Mode for Digital Media Majors

Under the influence of various factors, it is difficult to achieve a good quality in the training of digital media majors. What is worse, the current performance analysis models for the training quality cannot effectively handle uncertain information. To overcome these problems, this paper tries to design a training mode for digital media majors, and evaluates the performance of the model. Firstly, the defects of the current training modes for digital media majors were summarized in the context of the new era, and the implementation strategies and paths were formulated for improving the effect of the training mode. Further, a novel evaluation index system (EIS) was constructed to evaluate the performance of the said training mode, aiming to effectively assess the implementation effect of the mode. Besides, fuzzy system and grey system theories were fully integrated to build an improved performance analysis model for the training effect of digital media majors. The proposed model can effectively process the fuzzy information, and provide a strong support to the smooth implementation of the training mode for digital media majors. The research results boast profound theoretical and engineering values.