Reviewerly/exHarmony huggingface dataset:
PENGARUH PENGGUNAAN MEDIA PEMBELAJARAN TERHADAP MOTIVASI BELAJAR PESERTA DIDIK KELAS VIII-A SMPN 10 CIBINONG

The research I conducted aims to determine the effect of the use of learning media on the learning motivation of class VIII-A students of SMPN 10 Cibinong. This is done because there are still many students who do not understand learning which if only explained by the teacher and do not use equipment or other learning aids. Of course, the media that will be used here is modern learning media. The research method that I use is descriptive qualitative research, the research sample is taken from students of class VIII-A SMPN 10 Cibinong which includes 20 students, the instrument I use is a questionnaire. Method The results of this study indicate that there is a significant effect of the use of instructional media on motivation in class VIII-A students of SMPN 10 Cibinong.
Exploiting Explicit and Inferred Implicit Personas for Multi-turn Dialogue Generation

Learning and utilizing personas in open-domain dialogue have become a hotspot in recent years. The existing methods that only use predefined explicit personas enhance the personality to some extent, however, they cannot easily avoid persona inconsistency and weak diversity responses. To address these problems, this paper proposes an effective model called Exploiting Explicit and Inferred Implicit Personas for Multi-turn Dialogue Generation (EIPD). Specifically, 1) an explicit persona extractor is designed to improve persona consistency; 2) Taking advantage of the von Mises-Fisher (vMF) distribution in modeling directional data (e.g., the different persona state), we introduce the implicit persona inference to increase diversity; 3) during the generation, the persona response generator fuses the explicit and implicit personas in the response. The experimental results on the ConvAI2 persona-chat dataset demonstrate that our model performs better than commonly used baselines. Further analysis of the ablation experiments shows that EIPD can generate more persona-consistent and diverse responses.
Malang Inter Library Loan

The study employed a descriptive-qualitative approach to explore how the MILL are operated in six selected universities in Malang as member of MILL.Three types of data collection techniques were used: interviews, observation, and document analysis.Structured interview was used as the main data collection technique.Findings of the study are presented in four main aspects in the implementation of MILL i.e maximize the use of collections shared by each library so that it can be used by users who need both users from the university itself and outside the university.The stages of cooperation carried out include, identification of the advantages and disadvantages of collections, centralized regional equality, intensive communication, the use of collections together, opportunity, and challenges as main frame of it services.This study is significantly useful for readers and librarian especially in the context of collection development, to know the crucial position of the MILL as medium that frames the resources sharing at universities.Furthermore, MILL has a harmonious integration with the field of scholarly communication, including aspects of dissemination, social networking, and exchange of information sources.
The Use of Media in English Teaching and Learning Vocabulaty at SMP Negeri 1 Luwuk

This research aims to identify and described the application of media used by teachers at SMP Negeri 1 Luwuk in teaching. The type of this research was descriptive qualitative. This research used two instruments to obtain data, namely observation and interviews. The subjects of this research were teachers at SMP Negeri 1 Luwuk. Based on the results, the researcher found the type of media used by teachers in teaching, namely: computer or Laptop, internet, modules, pictures, power points, audio, Zoom and WhatsApp. The description of the application of the Teaching media is: based on the result of observations and interviews, the researcher draws the conclusion that the application of all media used by teachers for online learning is continuous and interconnected between one media and another so that the online learning process runs smoothly.
What’s Emotion Got to Do with It? – An Analysis of Social Media and Student Emotion and the Pandemic (preprint)

This paper explores Student emotion via social media in relationship to the Covid-19 pandemic. With a sample of data pulled from Reddit, we utilized text mining sentiment analysis with the NCR package in R to enhance understanding of student sentiment present in comments surround higher education. Employing text mining, the findings indicate a dramatic shift towards negative in emotional sentiment when the classes shifted from face to face to solely online learning.
Perancangan dan Manajemen Mail Server dengan Menggunakan Exchange Server

In general, a lot of work is done by computerization, be it in the corporate environment or in the world of education. This development can be seen from the software side (software) including the operating system and applications that can be run on it, and so is the hardware (hardware), with this research Knowing the traffic, data capacity when sent by the user: creating high security public folders on this system, building mail servers for multiple users, so that there is high security in public folders development of mail servers followed by an active directory which can be set on the domain controller so that user contact information is easily known, this system can monitor traffic, data capacity, user sending.
Interrogating Community Roles in Funding Security Agencies in Nigeria

Security has remained a fundamental need of any society.Sometimes, it requires the multi-stakeholder approach to sustain functional security operatives in most communities.This paper seeks to examine how local communities in Nigeria participate in funding security operatives within their local thereby contributing to national security.Paper shows that communities invest in their own security through volunteer donations and levies aimed at providing certain logistics such as accommodation to security operatives in their community.
Matrix Representation of Graphs in Electronic Circuit

The concept of logical connection between graph theory and analog circuit models of graph are presented in this paper. We formulate an analog electronic circuit network model based on truth table and its various components.
An analysis of the legal framework of cyber related crimes in Uganda

Research report submitted to the school of law in partial fulfillment of the requirement for the award of bachelor’s degree in Laws of Uganda Kampala International University
PERFORMANCE EVALUATION OF ENSEMBLE LEARNING ALGORITHMS FOR VARIOUS CLASSIFIERS

: In the present scenario with the advancement of digital technology extensive amount of data and information are generated. With such extensive amount of data, powerful approaches are required for data interpretation that help the human being for decision making process. Handling, analyzing, processing and finding relevant information from this extensive amount of data is very interesting and fast growing research area. Data mining is the process of extracting or discovering useful information from the large amount of data and then transforms them in to an understandable form for future use. Data mining offers various methods or techniques that are used to predict the accuracy of various classes of object. This research focus on various ensemble learningh techniques like bagging and boosting also enhance the accuracy of various base classifiers like NaiveBayes, DecisionStump, DecisionTable and J48. All the techniques are compared on the basis of four evaluation parameters like accuracy, precision, recall and root mean squared error. The finding are also supported with justification by conducting an experimental survey at the end of research. RapidMiner tool will be used to perform the simulation using 10 fold cross validation
Weightless Neural Networks for text classification using tf-idf

While Weightless Neural Networks (WNN) have been proven effective in Natural Language Processing (NLP) applications, they require the use of highly customized features as they work on binary inputs.However, recent advancements have brought methodologies able to adapt WNN to real numbers showing competitive results on many classification tasks, but they often struggle on sparse data.In this paper, we show that WNN can successfully use sparse linguistic features, like tf-idf, using appropriate transformations.We also show that WNN can be used to improve the performances of existing models for Mixed Language Sentiment Analysis and that it has competitive performances for news categorization. The WiSARD ClassifierThe WiSARD, originally conceived as a pattern recognition device mainly focusing on binary image processing [6], belongs to the class of weightless neu-239
A Range-Domain Measurement Model for Improved Weak-Signal Tracking in Terrestrial Pseudoranging

In this paper we propose a range-domain processing method that improves weak-signal tracking for LDACS. The objective is to improve existing LDACS receiver algorithms towards a more robust computation of navigation observables at no loss in accuracy. Evaluating real flight data from the results of the ALPS project further supports previous claims that LDACS-based navigation will enable RNP 0.3 based on terrestrial ranging. In addition to the improved processing we propose a way of discriminating nominal and faulted measurements. With this screening method we produce the first-ever LDACS-based ranging data set made up of fault-free measurements. Finally, we compute an overbounding Gaussian error model, with a sigma ?? < 30 m, based on 102 million data samples.
Hybrid deep learning framework for human activity recognition

The aim of the recognition in the human activity is to recognize the actions of the individuals using a set of observations and their environmental conditions. Since last two decades, the research on this Human Activity Recognition (HAR) has captured the attention of several computer science communities because of the strength to provide support to different applications and the connection to different fields of study such as, human-computer interaction, healthcare, monitoring, entertainment and education. There are many existing methods like deep learning which have been used to develop to recognize the different activities of the human, but couldn’t identify the sudden change of the activities in the human. This paper presents a method using the deep learning methods which can recognize the specific identities and identify a change from one activity to another for the applications of the healthcare. In this method, a deep convolutional neural network is built using which the features are extracted for the collection of the data from the sensors. After which the Gated Recurrent Unit (GRU) captures the long-tern dependency between the different actions which helps to improve the identification rate of the HAR. From the CNN and GRU, a model of wearable sensor can be proposed which can identify the changes of the activities and can accurately recognize these activities. Experiment have been conducted using open-source University of California (UCI) HAR dataset which composed of six different activity such as lying, standing, sitting, walking downstairs, walking upstairs and walking. The CNN-based model achieves a detection accuracy of 95.99% whereas the CNN-GRU model achieves a detection accuracy of 96.79% which is better than most existing HAR methods.
PENERAPAN MODEL PROBLEM BASED LEARNING UNTUK MENINGKATKAN HASIL BELAJAR MATA PELAJARAN IPS

This research is motivated by the low student learning outcomes in social studies subjects was still in low category. The research objective was to improve the learning outcomes of social studies subjects for class IX-A students of SMP Negeri 2 Sidamulih through the use of the Problem Based Learning (PBL) model. This study used CAR method that was carried out in 2 cycles, each cycle consists of 2 meetings. The research subjects were 27 students of class IX A SMP Negeri 2 Sidamulih in the 2018/2019 academic year, consists of 16 male and 11 female student. The results of the research in cycle I showed that the average learning outcomes Increased 7,41% from 63,33 to 71,11 from the first meeting with a percentage of 25.93% at the second meeting, in Cycle II the average score was 78, 52 with a percentage of 74.07% at meeting 1 to 87.78 with a percentage of 96.30% at meeting 2. The results of skills in the first cycle increased on average from 68.75 with a percentage of 7% at meeting 1 to 76.16 with 33% percentage at meeting 2, in cycle II increased from 79.63 with a percentage of 70% at meeting 1 to 85.65 with a percentage of 93% at meeting 2.Based on the percentage of completeness, it can be concluded that the implementation of the Problem Based Learning model can improve student learning outcomes class IX A subject matter at SMP Negeri 2 Sidamulih.
The Transformation of the Online Teaching Role of University Teachers Under the Embodied Cognition Perspective

With the gradual intervention of the online teaching process of artificial intelligence, the virtual three-dimensional space and the traditional physical space gradually integrate and promote the reshaping of the teaching environment.The teaching needs of the era based on educational big data have put forward new requirements for the classroom role of university teachers.Firstly, from the perspective of teaching environment, teaching subject, cognitive science, then, the teaching enlightenment is summarized to build appropriate learning environment, appropriate learning status, multiple learning experience, technical design, content guidance, activity organization and habit guidance, including environment, experience, subject and activity.
Leveraging Knowledge in Multilingual Commonsense Reasoning

Commonsense reasoning (CSR) requires models to be equipped with general world knowledge.While CSR is a language-agnostic process, most comprehensive knowledge sources are restricted to a small number of languages, especially English.Thus, it remains unclear how to effectively conduct multilingual commonsense reasoning (XCSR) for various languages.In this work, we propose to use English as a pivot language, utilizing English knowledge sources for our our commonsense reasoning framework via a translate-retrievetranslate (TRT) strategy.For multilingual commonsense questions and answer candidates, we collect related knowledge via translation and retrieval from the knowledge in the source language.The retrieved knowledge is then translated into the target language and integrated into a pre-trained multilingual language model via visible knowledge attention.Then we utilize a diverse of four English knowledge sources to provide more comprehensive coverage of knowledge in different formats.Extensive results on the XCSR benchmark demonstrate that TRT with external knowledge can significantly improve multilingual commonsense reasoning in both zero-shot and translatetrain settings, consistently outperforming the state-of-the-art by more than 3% on the multilingual commonsense reasoning benchmark X-CSQA and X-CODAH.
Decibel Imaging for Generating Medical Report using Ultrasonic

Medical imaging is commonly used for diagnosis and care in clinical practice. Report-writing would be prone to mistakes for inexperienced physicians, and experienced physicians would be time consuming and boring. To handle these issues, we study the automated generation of medical imaging reports. This task presents several challenges. First, a complete report contains multiple heterogeneous types of information including findings and tags. Second, abnormal regions in medical images are difficult to spot. Third, usually, the reports are lengthy and contain multiple sentences. To deal with these challenges, we (1) build a multi-task learning framework which jointly performs the prediction of tags and therefore the generation of paragraphs, (2) propose a co-attention mechanism to localize regions containing abnormalities and generate narrations for them, (3) develop a hierarchical LSTM model to get long paragraphs. We show the efficacy of the proposed methods on two datasets which are publicly accessible.
Textual analysis and sentiment analysis in accounting

In spite of the relatively scarce use of textual analysis and sentiment analysis techniques in finance and accounting, they have great potential in accounting, both because of the volume of documents used for the communication of information and due to the growth in the use of digital tools and social media. In that regard, these techniques of analysis may help researchers to analyse hidden clues or look for additional information to that one observed through financial information, increasing the quantity and quality of the information traditionally used, and providing a new perspective of analysis. The aim of this study is to review the use of textual analysis and sentiment analysis in accounting. After presenting the concepts of textual analysis and sentiment analysis and expose their interest in accounting, we perform a review of the previous literature on the use of these techniques in finance and accounting and describe the main techniques of sentiment analysis, as well as the procedure to be followed for the use of this methodology. Finally, we suggest three lines of future research that may benefit from the use of textual and sentiment analysis.
Theoretical Principles of Introducing the Play-Based Methods to Teachers’ Training in the System of Postgraduate Education

The article analyzes the theoretical principles of teacher training in the system of postgraduate education for the introduction of play-based methods. It generalizes the scientific approaches of understanding the essence of the individual's readiness for the professional activity in general and pedagogical activity in particular. It is stated, that the readiness of a teacher for the professional activity is an integrative professional and personal phenomenon, the content of which is the integration of value-orientation, cognitive, constructive and reflexive components, and which is the result of long professional training and self-training of a specialist, new stage of his/her development. The peculiarities of the professional activity of elementary school teachers in modern conditions require the possession of play-based teaching methods, which are active in nature. Based on the analysis of the principles of the activity-based approach in education, it is stated, that they put forward their requirements for primary school teachers, including systematic formation of subjectivity as a teacher's ability to be an agent of childhood. The article analyzes the provisions of the integrative “learning through play” approach and the requirements for primary school teachers, which ensure the formation of students' learning experience with the help of the play resource. The work presents an author's understanding of the essence of the primary teacher's readiness to introduce the methods as an integrative personal-professional education, the system characteristics of a specialist, which determines his/hers ability to effectively use play-based teaching methods in the educational process and consists of value, cognitive and constructive components. Preparing a teacher for the introduction of play-based teaching methods is a complex and lengthy process that, in today's context, should take place in the space of postgraduate education.
Research Guides: Group Study Room Reservations: CAB 2030: Leir Data Observatory

This guide provides information on study rooms available for reservation at the Van Houten Library.
The Relationship Among Academic Social Interaction, Academic Behavior and Academic Achievement of Woldia Secondary School Students: Implication for Quality Education and Psychosocial Support

The purpose of this study was to determine the level of students’ academic social interaction, academic behavior and academic achievement: examine the relationship among academic social interaction, academic behavior and academic achievement: do students’ academic social interaction and academic behavior predict students’ academic achievement of grade nine and ten students in Woldia Secondary School. The design used in this study was correlational design. The total number of the target population grade nine students in the study area was 1040. Of the total population, 200 grade nine students were selected as the sample of the study using simple random sampling technique. The instruments used in the study were scale questionnaires that measure students’ social interaction and academic behavior and documents to access student’s academic achievement average score in different school subjects of the first semester of 2011 E.C. One sample t-test, Pearson correlation coefficient and regression analysis were employed as data analysis. The results of one sample t-test demonstrated that the mean value of students’ academic social interaction was significantly higher than the mean test value. The mean value of academic behavior was significantly higher than the mean test value. The mean value of students’ academic achievement was significantly higher than the mean test value. The results of the Pearson correlation coefficient demonstrated that there was a statistically positive significant correlation between students’ academic social interaction and academic achievement. The results of regression analysis revealed that there was statistically significant contribution of academic social interaction and academic behavior to academic achievement. The contribution of academic social interaction found to be positive predictor of academic achievement. Keywords: Social interaction, Academic behavior, Academic achievement DOI: 10.7176/RHSS/10-15-04 Publication date: August 31 st 2020
INTERNET OF NANOTHINGS (IoNT) – A CONCISE REVIEW OF ITS HEALTHCARE APPLICATIONS AND FUTURE SCOPE IN PANDEMICS

Technologies that could allow literally billions of everyday objects to communicate with each other over the internet have enormous potential to change all our lives. The Internet of Things (IoT) is a transformative development, these technologies are a way of boosting productivity, keeping us healthier, making transport more efficient, reducing energy needs and making our homes more comfortable. In recent years, Internet of Things (IoT) and Internet of Nanothings (IoNT) have drawn significant research attention in numerous fields such as Healthcare, Defence, Environmental monitoring, Food and water quality control etc., There are various transformations such as Smart cities, Smart homes, Smart factories, Smart transportation, due to IoT and IoNT. Health care delivery requires the support of new technologies like IoT, IoNT to fight and look against the new pandemic diseases. For the past two years COVID-19 spreaded over worldwide including India, are fighting with pandemic disease and still looking for a practical and cost-effective solution to face the problems arising in several ways. To minimize the person to person, contact and to maintain social distancing various technologies are utilized, among them IoT and IoNT play a major role in healthcare system and allied fields. This review mainly discuss about the IoT, IoNT, its components and various applications in healthcare and allied fields.