Reviewerly/exHarmony huggingface dataset:
PENGARUH MODEL PEMBELAJARAN KOOPERTIF TIPE STAD TERHADAP HASIL BELAJAR IPA SISWA KELAS V SD NEGERI JOMBLANGAN TAHUN AJARAN 2019/2020

The purpose of this study was to determine (1) the extent of the tendency of science learning outcomes with the STAD learning model (Student Teams Achievement Divisions). (2) The extent to which the tendency of science learning outcomes with expository learning models (3) find out the differences in science learning outcomes in class students V Jomblangan Public Elementary School uses the STAD learning model with expository learning model. This research was conducted in class V of SD Negeri Jomblangan, Bantuntapan district, Bantul, academic year 2019/2020 with a population of 64 students consisting of 2 classes. This type of research is quasi-experimental, VA, and VB grade students are taken as research samples. Data collection techniques used were test and documentation techniques. Validity and reliability tests are calculated using Microsoft Excel. The data analysis technique used is the initial ability test, normality test, homogeneity test, and independent-sample t-test. The results showed (1) the tendency of science learning outcomes using the STAD model was in the very high category with an average of 19.96 with a standard deviation of 7.86. (2) the tendency of science learning outcomes by using expository learning models in the high category with an average of 17.88 with a standard deviation of 8.72. (3) independent t-test results obtained t = 4,401 and p = 0,000 shows that there is a very significant difference between STAD learning models and expository learning models because of p &lt;0,000.
Anomaly Detection Algorithms for Streaming Data: Performance Comparison

Today’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming data is important the algorithm used for anomaly detection to be robust with low processing time, eventually at the cost of the accuracy. The aim of this paper is to measure the performance of such algorithms and them to compare with our previously proposed algorithm HW-GA with other existing methods as ARIMA, Moving Average and Holt Winters. The algorithms are implemented in R system and tested on the three Numenta datasets, with known anomalies and own e-dnevnik dataset with unknown anomalies. Evaluation is done by comparing achieved results (the algorithm execution time and CPU usage). As a result of this research we may say that our algorithm HW-GA outperforms others algorithm that we have compared by showing less CPU usage and execution time. Our continues interest is to monitor the streaming log data that are generating in the national educational network (e-dnevnik) that acquires a massive number of online queries and to detect anomalies in order to scale up performance, prevent network downs, alarm on possible attacks and similar.
Effect of Mother Tongue-Based Education (Waray-Waray) in Teaching Mathematics Subjects Among Elementary Grade Pupils

This study evaluated the effect of Mother-Tongue language (Waray-Waray) to the Elementary Grade Pupils (EGP) in Mathematics. An experimental research design using pretest-posttest equivalent group design was utilized in this study. A teacher-made test was utilized to measure the students’ achievement in Mathematics covering the topics Operations of Whole Numbers, Operations of Decimal Numbers, and Laws of Exponent. The results revealed that respondent’s Mathematics achievement rose high for experimental group and very high for control after the posttest, with the control group more homogeneous in term of their scores in the posttest. Teaching Mathematics in English allowed the respondents to perform better than the respondents under the Mother-Tongue (Waray-Waray) mediated Mathematics instruction. Since Mother-Tongue in Samar College is English, pupils may encounter Waray-Waray mediated Mathematics instruction unfamiliar. Therefore, this recommended that English as the Mother-Tongue in Samar College Elementary Department must be utilized in Mathematics enhance the learner’s understanding of the concept and teachers should explain the lessons in the learners’ language, particularly when the teacher notices that the students are having difficulty in understanding the topic.
Gestão, preservação e acesso aos documentos arquivísticos nos Ministérios Brasileiros

This study presents an analysis of the aspects of the management, preservation, and access to the records of the Brazilian ministries, with emphasis on records produced in digital media. A survey of data was carried out in twenty-two Brazilian ministries on the following topics: records management policy; existence of a Standing Document Evaluation Committee; sending of deletion of records to the National Archives; computerized system for the production of digital records; existence of a digital preservation policy; and, application of archival platform of access and diffusion of records. It was found that most ministries do not have a record management policy, and although many have a permanent record evaluation committee, there is no effective deletion of records by sending records deletion of records to the National Archives. The use of computerized systems for the production and processing of digital records has been identified, but, on the other hand, the elements of digital records management are attended by a minimal portion of the ministries, representing a perspective that is not conducive to the management, preservation and access to digital records.
Typology and Grammatical Alignment of Angkola Language

This study uses the theory of language typology by Comrie (1988). This research on grammatical alliance of Angkola language (AL) aims to understand (1) the basic construction of clause, (2) the construction of complex sentence, (3) the pivot system, and (4) the grammatical alliance system. The method used is participant-observation. Pivot test revelas that Angkola language syntactically treats S equals to A, and gives different treatment to P (S` = `A` ≠ P). Angkola language grammatically has an S/A pivot. It can be concluded that AL has a tendency as an accusative language.
Postponement of UIC-KORAIL Training Session on Railway Passenger Service based on IT Technology in Seoul, Korea to 5 – 9 April 2021 – UIC Communications

Due to an unexpected situation, we would like to inform you that the UIC-KORAIL Training Session 2020 on Railway Passenger Service based on IT Technology planned has been postponed to 5 – 9 April…
Toward Developing a Procedure for Automatically Identifying Speech, Writing, and Thought Presentation

The sixth chapter illustrates how the automatic annotation of the different modes of speech, writing, and thought presentation in 19th-century narrative fiction may be performed on the basis of repetitive lexico-grammatical features and by setting up rules based on the manual annotation of the corpus and facilitating it in larger data sets. The chapter proposes a number of formal diagnostic features for the identification of discourse presentation as well as procedures to help their automatic detection. The procedures described serve as basis for a tool for the automatic identification of discourse presentation which can be adopted to programs like <italic>Wmatrix</italic> (Rayson 2018) and <italic>WordSmith Tools</italic> (Scott 2017). The chapter furthermore critically reflects on the limits of automated procedures and the necessity to manually check the annotations and include contextual information for unambiguous identification of different types of discourse presentation.
PENGEMBANGAN APLIKASI KARTU RENCANA STUDI ONLINE PADA JURUSAN PENDIDIKAN LUAR SEKOLAH UNIVERSITAS PALANGKA RAYA

&#x0D; &#x0D; &#x0D; &#x0D; Kartu Rencana Studi is an important activity carried out by students to determine the courses to be taken in the following semester, the process of filling out Kartu Rencana Studi is done one week before the lecture is really active and if students do not fill out in accordance with applicable regulations, the student concerned is considered on college leave.&#x0D; In the Department of Non-School Education, the University of Palangka Raya to fill in Kartu Rencana Studi still uses a manual method where students consult with their academic supervisor to ask for approval of the courses to be programmed in the semester that will take place. In the implementation of this filling process can cause problems, one of which is the delay of students in completing Kartu Rencana Studi, it is difficult to control the courses taken by students, not all courses that want to be programmed in accordance with the courses issued and there are some specific subjects who experience conflicts on the same scheduled day and hour make students have to readjust the schedule and courses to be taken with the available schedule.&#x0D; This research design made up of two stages: (1) data collection and analysis conducted by means of literature study and observation, (2) applying the waterfall method already modified with the stages is system analysis, design, implementation and testing. The implementation uses PHP and Mysql as a database to store data. Furthermore, at this testing stage using the Blackbox method.&#x0D; &#x0D; &#x0D; &#x0D;
On Presuppositions of Machine Learning: A Meta Theory

Machine learning (ML) has been run and applied by premising a series of presuppositions, which contributes both the great success of AI and the bottleneck of further development of ML. These presuppositions include (i) the independence assumption of loss function on dataset (Hypothesis I); (ii) the large capacity assumption on hypothesis space including solution (Hypothesis II); (iii) the completeness assumption of training data with high quality (Hypothesis III); and (iv) the Euclidean assumption on analysis framework and methodology (Hypothesis IV). We report, in this presentation, the effort and advances made by my group on how to break through these presuppositions of ML and drive ML development. For Hypothesis I, we introduce the noise modeling principle to adaptively design the loss function of ML, according to the distribution of data samples, which provides then a general way to robustlize any ML implementation. For Hypothesis II, we propose the model driven deep learning approach to define the smallest hypothesis space of deep neural networks (DNN), which yields not only the very efficient deep learning, but also a novel way of DNN design, interpretation and connection with the traditional optimization based approach. For Hypothesis III, we develop the axiomatic curriculum learning framework to learn the patterns from an incomplete dataset step by step and from easy to difficult, which then provides feasible ways to tackle very complex incomplete data sets. Finally, For Hypothesis IV, we introduce Banach space geometry in general, and XU-Roach theorem in particular, as a possibly useful tool to conduct non-Euclidean analysis of ML problems. In each case, we present the idea, principles, application examples and literatures.
Correction to: A Survey on 3D Visual Tracking of Multicopters

The article A Survey on 3D Visual Tracking of Multicopters, written by Qiang Fu, Xiang-Yang Chen, Wei He, was originally published Online First without Open Access. After publication online first, the author decided to opt for Open Choice and to make the article an Open Access publication. Therefore, the copyright of the article has been changed to © The Author(s) 2019 and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The original article has been corrected.
ROLE OF WHATSAPP® IN MEDICAL EDUCATION: A LITERATURE REVIEW

ABSTRACT&#x0D; Background: This review is aimed to find out how WhatsApp® has been integrated into medical education. A systematic review of the current literature was performed, links to prior reviews were drawn and implications for the future were discussed.&#x0D; Methods: Three databases (PubMed, ERIC and Science Direct) were searched after defining the inclusion criteria. Key information from the articles was methodically abstracted and discussed in the categories research type, study design, participants' level of medical education and study content along with the use of WhatsApp® in Medical education and its perceived advantages and disadvantages.&#x0D; Results: Fourteen articles met the inclusion criteria. Results showed that 40-76% of medical students had a WhatsApp® account out of which 30- 60% used WhatsApp® for educational purposes. WhatsApp® was used to communicate with fellow students and faculty, share information online and participate in discussions groups.&#x0D; Conclusion: WhatsApp® influences a myriad of aspects of medical education at the undergraduate and graduate level. Despite an increase in the use of WhatsApp® in medical education, there is a lack of conclusive evidence in terms of its educational effectiveness.
INVESTIGATING THE MEDIATING ROLE OF LEADERSHIP STYLES ON EMPLOYEE SATISFACTION & EMPLOYEE PERFORMANCE:EVIDENCES FROM EDUCATION SECTOR

The objective of this study is to analyse the impact of transformational leadership and transactionalleadership style on satisfaction of their respective employees in education sector. Also identified that if employeesatisfaction has a mediating effect or not. Data were collected from 24 women HODs along with 48 immediateemployees in government colleges and 26 women HODs along with 52 immediate employees in Private colleges.Structural Equation modeling was applied to analyse and interpret the data. Research results revealed that bothtransformational and transactional are significantly positive associated with employee performance howevertransformational leadership were more significant then transactional leadership style. Further, the present studyconfirms that there is a mediating role of employee satisfaction between transactional leadership style andemployees performance. It also mediates the relationship between transformation leadership style and employeeperformance. The study is limited to small sample size and one sector i.e. education sector only. Ethical leadershipmay not only be normatively appropriate but is also instrumental for the effective functioning of organisations. Forenhancing employee satisfaction & performance, academic managers should consider the nature of therelationship they develop with their immediate employees and raise confidence level among them.
New Exploration of Social Practice in Colleges and Universities under the Background of Collaborative Education

Based on the construction of collaborative education platform and the analysis of the significance of collaborative education, this paper explores the functional orientation, management operation, team building and resource sharing of the university-enterprise cooperation platform for social practice activities in colleges and universities, and establishes collaborative innovation practice. Education guarantee mechanism. The aim is to achieve organic integration of production and education, and to form a long-term mechanism for school-enterprise collaborative education and collaborative innovation.
FIGURATIVE LANGUAGE USED BY THE ENGLISH TEACHER IN EFL CLASSROOM AT SMA NEGERI 1 TORAJA UTARA

This research aims at to find out the types of figurative language used by the English teacher in EFL classroom at SMA Negeri 1 Toraja Utara, and the dominant of figurative language used by the English teacher in EFL classroom at SMA Negeri 1 Toraja Utara. The researcher in this study use qualitative research design. The subject of this research is one of English Teacher at SMA Negeri 1 Toraja Utara. The result of the research revealed that there are 8 types of Figurative Language used by the English teacher and some of types of figurative language use more than one, they are: 3 Rhetoric, 9 Repetition, 4 Metonymy, 4 Ellipsis, 2 Irony, 2 Personification, 1 Pleonasm, 1 Simile, the total of all are 26 types of figurative language and the mostdominant of figurative language used by the English teacher is Repetition.            By this result of the research, the researcher suggest that the in teaching process the teacher needs to be more creative expressive in communicating to students, in order that the students be more engaged in studying.
METAPHOR IN STRATEGIC NEWS WRITING ABOUT THE GOVERNMENT TRANSFORMATION PROGRAM (GTP)

Language in news writing is very important because it brings a lot of meaning and understanding when reading to every member of society. The use of correct and meaningful language and having a certain interpretation can shape the thinking of society. Language combinations in news writing have an impact on the development of socio-cultural, informational sources, education, entertainment, key points in the arena of political communication, democratic participation, ideological value communication, norms, nature, and beliefs on an issue. Therefore, this study uses the Critical Discourse Analysis approach (CDA) which emphasizes Critical Metaphor Analysis (CMA) elements to examine the use of language and phrases formed by journalists in writing news on government policy, especially the Government Transformation Program (GTP). The data used in this study were taken from three online newspapers namely Malaysiakini newspaper, Berita Harian, and Utusan Malaysia. The use of metaphorical concepts and metaphors is fully utilized to refine terms in the words, phrases, and sentences written by journalists of these three media organizations. The findings show that journalists are aware and unconscious of writing metaphorical writing and setting the concept metaphor by framing the news they have written. The conceptualized metaphor is clearly displayed in every news writing because they have an agenda set by their respective media organizations to promote or provide understanding on government policies especially in relation to the GTP and the National Key Result Area (NKRA). Their behavior and processes produce stories that have implicit meaning by using metaphors to produce strategic news. The resulting metaphors are different but coherent to confirm the GTP and NKRA as the carriers of positive economic change to the country. Implicitly pointing out that GTP and NKRA need to be implemented if Malaysia wants to become a developed nation. It gives implied meaning because it is not said directly but indirectly through the metaphor.
Case Based Reasoning untuk Diagnosis Penyakit Ikan Kakap Putih

Case Based Reasoning (CBR) is one reasoning from an expert system, namely by reasoning from previous cases that have been stored on a case base to find out the solution of a new case. In case based reasoning there is a retrive process, in the retrieve process there is a similarity process, and to speed up the retrieve process it can use the indexing method. In this research will use the indexing method with Bayesian models and similarity processes using the nearest neighbor method. System testing techniques from this study with two testing techniques namely: the first testing technique using the Bayesian indexing model, the results of the indexing have produced white snapper disease, then proceed with similarity method with the nearest neighbor method used to determine the right solution from the previous case. has been saved on a case base. The second testing technique is without using indexing, the process is only by the nearest neighbor similarity method, the results of similarity in the form of disease and treatment solutions from previous cases that have been stored on a case base. System accuracy for testing with Bayesian model indexing and nearest neighbor similarity with threshold 0,70 is 86% and testing without indexing with Bayesian model with threshold 0,70 is 100%.
Sensitivity of Deep Convolutional Networks to Gabor Noise

Deep Convolutional Networks (DCNs) have been shown to be sensitive to Universal Adversarial Perturbations (UAPs): input-agnostic perturbations that fool a model on large portions of a dataset. These UAPs exhibit interesting visual patterns, but this phenomena is, as yet, poorly understood. Our work shows that visually similar procedural noise patterns also act as UAPs. In particular, we demonstrate that different DCN architectures are sensitive to Gabor noise patterns. This behaviour, its causes, and implications deserve further in-depth study.
Temporal Data Models via Stochastic Process

Author(s): Meng, Rui | Advisor(s): Lee, Herbert | Abstract: Temporal data modeling plays a vital role in various research including finance, environmental science and neuroscience. Understanding and interpreting the evolutionary system behind temporal data is of interest. This work mainly emphasizes efficient statistical models on temporal data via stochastic processes. In particular, we focus on statistical modeling via two flexible random processes: Markov processes and Gaussian processes. The first stage of the research involves a novel hidden Markov model based on Markov jump processes for cervical cancer screening test data. This model is able to model the heterogeneity of both individual and time. We provide an efficient and scalable expectation maximization based inference approach. To the best of our knowledge, our model is the first statistical model that is able to scale to a population-level dataset.Next, we consider an alternative stochastic process that is widely applied in temporal data modeling, the Gaussian process. Motivated by the kernel perspective of inducing-point based sparse Gaussian processes, we propose a general regularization framework of sparse Gaussian processes and extend it into latent variable models. We specifically consider variational inference under our regularization framework in various settings. We theoretically demonstrate that the variational inference under our regularization can be treated by maximizing a log likelihood lower bound on a corresponding empirical Bayesian model. Our framework is illustrated in various settings throughout both synthetic and real datasets. Building on our proposed regularization framework, we develop a hierarchical sparse latent Gaussian process model specifically for categorical data and then we extend our model to temporal data via dynamical priors. In particular, we propose efficient variational inference to make it applicable to large datasets. Moreover, our model provides a visualization way to summarize the dynamics of categorical data into a low-dimension manifold.The fourth project is motivated by electronic health record data and spatially varying coefficient linear coregionalization model. We propose a novel nonstationary multivariate Gaussian process model that allows it to model time dependent smoothness, scale and correlation across different dimensions. One special case of our model is emphasized due to its computational efficiency. It allows an efficient inference via Kronecker algebra. Moreover, we provide both Hamiltonian Monte Carlo inference as a fully Bayesian inference and Maximum a Posteriori based inference as an approximate Bayesian inference. Our posterior inference provides a promising way to understand the relation between cross-correlation of clinical variables and health status, which contributes to early disease detection.