Reviewerly/exHarmony huggingface dataset:
B4DS @ PRELEARN: Ensemble Method for Prerequisite Learning

In this paper we describe the methodologies we proposed to tackle the EVALITA 2020 shared task PRELEARN. We propose both a methodology based on gated recurrent units as well as one using more classical word embeddings together with ensemble methods. Our goal in choosing these approaches, is twofold, on one side we wish to see how much of the prerequisite information is present within the pages themselves. On the other we would like to compare how much using the information from the rest of Wikipedia can help in identifying this type of relation. This second approach is particularly useful in terms of extension to new entities close to the one in the corpus provided for the task but not actually present in it. With this methodologies we reached second position in the challenge.
Colored Multi-Agent Path Finding: Solving Approaches

Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set of agents moving in a shared environment while each agent has specified its destination. Colored MAPF generalizes MAPF by defining groups of agents that share a set of destination locations. In the paper, we evaluate several approaches to optimally solve the colored MAPF problem, namely, a method based on network flows, an extended version of conflict-based search, and two models using Boolean satisfiability. We also investigate methods for obtaining lower bounds on optimal solutions based on constraint and continuous relaxation techniques.
A Computationally Grounded Logic of Graded Belief

We present a logic of graded beliefs with a formal semantics grounded on the notion of belief base. It has modal operators which represent what an agent would believe if she removed k pieces of information from her belief base. We provide a sound and complete axiomatics for our logic as well as an optimal model checking algorithm. To illustrate its expressive power, we apply it to modeling social influence and epistemic explanation.
Comparison of Explanation-centered Statistical Model and Prediction-centered Machine Learning

This paper compares the results of random forest and logistic regression analysis with empirical data. As the number of cases increased in logistic regression, the type 1 error and verification power were excessively high, leading to problems in predictive power. Although Random Forest showed higher predictive power, since all predictors were included in the analysis without theoretical background, the interpretation of the results were ambiguous or a variables that violate the Basic Law on Employment Policy were used. When analyzing big data, it is necessary to clean data appropriate for the purpose of the study. This paper proposes that we should be careful about model overfitting problem, and by using variable extraction or proxy variables, it can solve inequality while improving predictive power in the HRM.
Usage of eye tracker technology in examining attention distribution of operators of unmanned aerial vehicles

This article proposes yet another approach towards looking into causes for attention distribution of an operator of unmanned aerial vehicle. During examination, the operator is being tested at dedicated flight simulator while data are gathered and visualized through a mobile eye tracker. Two work stages are considered sequentially, i.e. building a geometric 2D transformation of region of interest (homography) within an image, and overlaying a dynamic heatmap as well. In the former stage, spontaneous movements of the operator’s head, recorded by the video, are eliminated thus enabling the operator to use the mobile eye tracker instead of a desktop-based one. During the latter stage, the distribution of operator’s attention over time is displayed. In order to implement the current research, a source code has been developed in C++ for some features readily available in OpenCV library to be used. In addition, data gathered after carrying out flight session are processed and discussed thoroughly.
THE EFFECT OF DUOLINGO USAGE ON STUDENTS’ VOCABULARY MASTERY OF SEVENTH-GRADE STUDENTS AT MTs PAB 1 HELVETIA

Due to Covid-19 pandemic, most of teaching learning process was not conducted at class. The teacher and students had the teaching learning process via online on the internet. This situation occurred serious problem for the students related to the teaching learning goals. Most of students found more difficulties in learning English. Less interactions at class made their vocabulary knowledge and ability became low. They had no chance to explore their vocabulary. In fact, they were difficult to mention some vocabularies around them. They also felt difficult to share their opinion by using English. This research aimed to know the difference, increase or improvement and effect of Duolingo usage on students’ vocabulary mastery. This research was a quantitative approach. The research location was at MTs PAB 1 Helvetia on Jl. Veteran Pasar IV Helvetia with sixty students as the sample. The sample was divided into Experimental and Control group. The Experimental group was taught vocabulary by using Duolingo while the Control group was taught vocabulary by common method. The students’ score result was the primer data and analyzed by using T-Test formula. The calcualtion used SPSS (Statistical Package for Social Science) 20.0 to count the data as valid as it was. The research finding proved that there was a significance difference, increase or improvement and effect of Duolingo usage on students vocabulary mastery. Duolingo usage affected students’ vocabulary mastery of the seventh-grade students at MTs PAB 1 Helvetia. Keywords : Duolingo, Vocabulary Mastery
Towards an Efficient Approach to Manage Graph Data Evolution: Conceptual Modelling and Experimental Assessments

This paper describes a new temporal graph modelling solution to organize and memorize changes in a business application. To do so, we enrich the basic graph by adding the concepts of states and instances. Our model has first the advantage of representing a complete temporal evolution of the graph, at the level of: (i) the graph structure, (ii) the attribute set of entities/relationships and (iii) the attributes’ value of entities/relationships. Then, it has the advantage of memorizing in an optimal manner evolution traces of the graph and retrieving easily temporal information about a graph component. To validate the feasibility of our proposal, we implement our proposal in Neo4j, a data store based on property graph model. We then compare its performance in terms of storage and querying time to the classical modelling approach of temporal graph. Our results show that our model outperforms the classical approach by reducing disk usage by 12 times and saving up to 99% queries’ runtime.
English Teacher’s Questioning Strategy in EFL Classroom Interaction

This study investigated the types of English teacher’s questioning strategy and Students’ perceptions towards the use of teacher questioning strategy in EFL classroom interaction. This study was conducted at SMA Muhammadiyah 1 Palembang with five students as the participants taken from the twelfthgrade nature science students by using purposeful convenience sampling. In collecting data, the researcher used one-on-one interviews through open-ended questions. The interviews conducted in the class XII IPA 1. The result of this study that those were three types of English teacher’s questioning strategy, they were (1) procedural, convergent, and (3) divergent, and the students’ perceptions toward questioning strategy, they were (1) English reading activity, (2) English speaking activity, (3) English writing activity, and (4) English listening activity. This study indicated that those were the students’ perceptions towards the types of teacher’s questioning strategy that used in EFL classroom interaction at SMA Muhammadiyah 1 Palembang.&#x0D;
MICROFINANCE, FINANCIAL DEVELOPMENT, FOREIGN AID, AND INCOME INEQUALITY: EVIDENCE FROM SUB-SAHARAN AFRICA

This paper examines the effects of microfinance, financial development and foreign aid on income inequality for 43 Sub-Saharan African (SSA) countries. Panel data for the period 1995–2015 is examined using fixed effects, pooled ordinary least square and system generalized method of moments (GMM) estimation techniques. Findings suggest that although foreign aid plays a determining role in explaining the dynamics of inequality in SSA, it does not appear to be pro-poor. Moreover, the results reveal that both microfinance and financial development contribute to narrowing the income gap between the poor and the rich and to reducing inequality. This implies that providing access to loans through microfinance institutions or bank-based financial system offer to the poor the potential for income-generating activities. Furthermore, the empirical evidence suggests that GDP per capita growth and government expenditures appear to be pro-poor. While a rapid population growth, high levels of inflation, FDI and trade openness are correlated, positively and significantly, with greater income inequality. These results have important policy implications for SSA. Enhancing the efficiency of social protection, promoting progressive taxation and distributional effectiveness of fiscal are crucial to address income inequalities.Keywords: Income inequality, Microfinance, Financial development, Foreign aid, Sub-Saharan Africa JEL Classifications: C23; D63; F35; O55DOI: https://doi.org/10.32479/ijefi.11277
The Effectiveness of the Android-Based Calistung Digital Game Application to Improve Early Childhood Cognitive Skills

This article aims to determine Android-based digital calistung game application's effectiveness to improve early childhood cognitive skills. The experimental method was carried out on 26 kindergarten students aged 5-6 years. The research design used was pre-experimental. The sampling technique used in this study was purposive sampling. Cognitive skill data collection used observation guidelines consisting of cognitive dimensions (1) symbolic thinking recognizing concepts, (2) learning problem solving and cause and effect, (3) association and classification. The assessment of cognitive skills used a scale of 1 - 4. The study results concluded an increase in the average value of cognitive skills of kindergarten students aged 5-6 years through the Calistung game. This research implies that teachers' competence in using digital calistung media needs to be improved through in-service training kindergarten students' cognitive skills.
Learning adaptive representations for entity recognition in the biomedical domain

Abstract Background Named Entity Recognition is a common task in Natural Language Processing applications, whose purpose is to recognize named entities in textual documents. Several systems exist to solve this task in the biomedical domain, based on Natural Language Processing techniques and Machine Learning algorithms. A crucial step of these applications is the choice of the representation which describes data. Several representations have been proposed in the literature, some of which are based on a strong knowledge of the domain, and they consist of features manually defined by domain experts. Usually, these representations describe the problem well, but they require a lot of human effort and annotated data. On the other hand, general-purpose representations like word-embeddings do not require human domain knowledge, but they could be too general for a specific task. Results This paper investigates methods to learn the best representation from data directly, by combining several knowledge-based representations and word embeddings. Two mechanisms have been considered to perform the combination, which are neural networks and Multiple Kernel Learning. To this end, we use a hybrid architecture for biomedical entity recognition which integrates dictionary look-up (also known as gazetteers) with machine learning techniques. Results on the CRAFT corpus clearly show the benefits of the proposed algorithm in terms of F 1 score. Conclusions Our experiments show that the principled combination of general, domain specific, word-, and character-level representations improves the performance of entity recognition. We also discussed the contribution of each representation in the final solution.
Estimation of Flow Discharge Model at Temef Watershed - East Nusa Tenggara Using TRMM Satellite Data

Data collection based on satellite TRMM (Tropical Rainfall Measuring Mission) presents one of the good alternatives in estimating rainfall. TRMM technology can minimize manual rainfall recording errors and improve rainfall accuracy for hydrological analysis. The analysis method used in this research is divided into 3 (three) stages, namely Hydrology analysis, Statistical Analysis and Artificial Neural Network Analysis. From the results of TRMM JAXA analysis in the Temef Watershed Area of East Nusa Tenggara Province obtained TRMM JAXA satellite rainfall relationship to observation data shows rainfall patterns between the two data are interconnected but for cases with very high observation rainfall, TRMM rainfall data tends to be low. From statistical method analysis, the relationship between observation rainfall and TRMM JAXA rainfall obtained results with a "Very Strong" interpretation indicated by the results of 9 years calibration and 1 year validation where the selected equation is a polynomial equation (y=-0,0123x2 + 1,5553x + 20,222). Rain data correction results simulated with Debit data to see the relationship between rain and discharge that occurred, this analysis using Artificial Neural Network with Backpropagation method, the results showed a "Strong" interpretation where statistically the value of Nash-Sutcliffe Efficiency (NSE) 0.920, the coefficient value of correlation of field discharge and TRMM rainfall is 0,877 % and the relative error occurred is 2,62%
Autonomous path planning through application of rotated two-parameter overrelaxation 9-point Laplacian iteration technique

Autonomous path navigation is one of the important studies in robotics since a robot’s ability to navigate through an environment brings about many advancements with it. This paper suggests the iteration technique called half-sweep two parameter overrelaxation 9-point laplacian (HSTOR-9P) to be applied on autonomous path navigation and aims to investigate its effectiveness in performing computation for path planning in an indoor static environment. This iteration technique is a harmonic function that solves the Laplace’s equation where the modelling of the environment is based on. The harmonic functions are an appropriate method to be used on autonomous path planning because it satisfies the min-max principle, therefore avoiding the occurrence of local minima which traps robot’s movements, and that it offers complete path planning algorithm. Its performance is tested against its predecessor iteration technique. Results shown that HSTOR-9P iteration technique enables path construction in a lower number of iterations, thus, performs better than its predecessors.
Mobile Augmented Reality: An Alternative Way toward Museum Visitors’ Experience

The research focuses on visitors’ experience via Mobile Augmented Reality (MAR) approach exhibition. Since the museum considered as a complex public institution, it required intellectual involvement from various disciplines in determining design decision at multilayer of design stages. It triggers the research to theorize the complex design development by considering “visitors’ experience” as the backbone of the research. This notion is closely related to the fundamental of the museum context where the research attempts to unfold the factors that constitute them and how its related to each other. The aim is to formalize the factors that constitute the MAR approach exhibition toward visitors’ experience. There are two objectives; to investigate the visitors’ expectation, physical exhibition setting and MAR application that assists various visitors’ activities; to validate the factors that constitute to the MAR approach exhibition toward visitors’ experiences. The research applies mix-mode method which consists of a literature review, interviews and questionnaire to validate the finding. The reflection, the research highlights the “visitors’ experience” as the primary consideration in bridging the gap between curators and designers. Thus, it promises an alternative approach for the museum in harmonizing the visitors’ experience in the exhibition spaces
Blind Extraction of Digital Watermarking Algorithm for Color Images

Digital watermark technology hides copyright information in digital images, effectively protecting the copyright of digital images. At present, the color image digital watermarking algorithm still has defects such as the inability to balance robustness, invisibility and the weak anti-attack ability. Aiming at the above problems, this paper studies the digital watermarking method based on discrete wavelet transform and discrete cosine transform. Then this paper proposes a color image blind digital watermarking algorithm based on QR code. First, convert the color image from RGB space to YCbCr space, extract the Y component and perform the second-level discrete wavelet transform. secondly, block the LL2 subband and perform the discrete cosine transform. finally, use the embedding method to convert the watermark information after the Arnold transform embedded in the block. The experimental results show that the PSNR of the color image embedded with the QR code is 56.7159 without being attacked. After being attacked, its PSNR and NC values are respectively 30dB and 0.95 or more, which proves that the algorithm has good robustness and can achieve watermarking blind extraction.
Smart Brands and Identities: building friendly bridges between Design and Smartness

When adapting an environment toward making it smarter than it is, every user is expected to develop a certain degree of design literacy to effectively contribute with and make use of relevant data. Little research has been done regarding both the expected level of users’ design literacy in smart environments and the developmental tactics for these essential skills to be acquired. Simultaneously, there is little acknowledgement of the relevance of these environments’ brands as important assets in supporting design literacy. This paper speculates on the relevance of investing in “smart visual identities”, which configure as a meaningful and holistic branding resource. Hermeneutics informed the qualitative analysis of content in this research. Two essential dimensions of smart visual identities were identified, and a definition of “smart brand” is proposed, suggesting that highly relatable brand identities allow individuals develop their design literacy while users of a smart learning environment.
STUDENTS’ RESPONSES TOWARD THE IMPLEMENTATION OF BINGO GAME WITH SCIENTIFIC APPROACH IN TEACHING WRITING DESCRIPTIVE TEXT

This study aimed to investigate the implementation of the Bingo game technique in teaching writing and to find out the students’ participation toward the implementation of the Bingo game. The research instruments used interview and observation sheet. This study was conducted at Junior High School in Cimahi. The students of VII F class were selected as the participant of the research. The research used descriptive qualitative method. The data was obtained from classroom observation and students’ interview. The result showed that Bingo game can be used to motivate students in writing skill. It was very helpful in providing the students with more enjoyable activities which made the students involved in the teaching and learning process actively. Keywords: Writing, Bingo Game, Descriptive Text.
Distance Learning Lessons During The Coronavirus Pandemic: Sociological Analysis

The article presents an analysis of the responses of survey participants to the questionnaire "Distance learning: feedback" in order to study the consequences of a post-traumatic situation caused by the sudden introduction of distance learning at a university, among higher education teachers.The situation was ambiguous and exacerbated the stress of teachers and students by the general unhealthy situation around the threat of the coronavirus pandemic, the systematic delay in returning to a normal form of interaction and the unpreparedness of the education sector in general for distance learning.In our study, we focused on the following main blocks of problematic issues: "How effective is it?","Is distance learning ineffective?","In what format can distance learning be implemented based on the experience of springsummer 2020?"The results obtained showed that, in general, teachers are aware of the relevance of distance learning and the need to update the educational methodology.Almost all teachers recognize the value of traditional forms of teaching, in which the first place is the possibility of live dialogue between the teacher and the student, the student and the student.A person has a social being; in the process of adaptation and socialization to the social environment he is formed as a person.The culture of personal development requires a show, an example, live communication.
Interactive e-module using Zoom Cloud Meeting platform to reduce misconceptions on salt hydrolysis material

This study aimed to determine the effectiveness of using an interactive e-module to reduce students’ misconceptions on salt hydrolysis material at grade XI in senior high school. This study implemented a pre-experiment with one group pretest-posttest research design, which utilized one class as the experimental class. Samples were selected by using purposive sampling technique, and it was obtained one class as the experimental class, namely class XI in State Madrasah Aliyah 1 Pekanbaru, Riau, Indonesia. Before giving the treatment, the sample was administered a pretest and after the treatment, they were given a posttest. The pretest and posttest questions occupied three-tier multiple choice questions. The reduction of misconceptions on Salt Hydrolysis material after using the interactive e-module was 16.21%. The study found that interactive e-modules effective to reduce misconceptions on salt hydrolysis material was significant.
Elsevier Title Level Pricing: Dissecting the Bowl of Spaghetti

INTRODUCTION This study will explore the issue of pricing opacity associated with prices paid by academic libraries that have recently unbundled from the Elsevier Big Deal journal package. Additionally, this study will provide metrics for assessing the fair market value (FMV) of unbundled journal packages. The pricing metrics will assist academic libraries in negotiations of subscription and open access agreements. METHODS Pricing information was gathered from five academic libraries. The data was analyzed to arrive at two key metrics (adjustment from list price and the average cost per journal) for establishing comparables, i.e., prices paid by similarly sized institutions, to assess the collective FMVs for unbundled Elsevier journal packages. RESULTS &amp;amp; DISCUSSION The study results show that significant variations existed in the way institutions were charged for content. Additionally, the comparables show wide variations among institutions when measured by the overall adjustment from list price and the average cost per journal. CONCLUSION The pricing metrics developed in this study, adjustment from list price (ALP) and average cost per journal (ACJ), will help libraries assess their final net prices for individual journal subscriptions. The results will be useful to administrators, collection development personnel, and negotiating teams in understanding the prices paid by other institutions for unbundled journal packages to determine FMVs.