Reviewerly/exHarmony huggingface dataset:
Automatic Extraction Of Handshapes Inventory In Russian Sign Language

The Prosodic model of phonology (Brentari 1998) implies that all signs in any sign language have prosodic and inherent features. This dichotomy (movement feature vs. all other features) occurs to some extent in all phonological theories. The idea derives from Liddell & Johnson’s (1994) Movement-Hold model, where they proposed that movements can be in most cases derived from the knowledge of holds and their relative order, and that it is sufficient to describe in-detail only holds. Therefore, when it comes to describing phonemic inventories of a particular sign language, researchers focus on the building of separate phonemic inventories for each of the inherent features (or for features of holds) (Channon & Hulst 2011), namely handshape, location, and orientation (e.g. van der Kooij (2002) for Sign Language of the Netherlands (NGT) – only handshapes inventory, Nyst (2007) for Adamorobe Sign Language (AdaSL) – handshapes and locations inventories, etc.).This research focuses on handshapes inventory for Russian Sign Language (RSL). First, I automatically extract positions without movement (i.e. holds) using an algorithm developed on the basis of Börstell’s (2018) script. Then I manually annotate holds for the handshapes with respect to Hamburg Notation System (HamNoSys; Hanke 2004) and describe resulting phonetic handshapes inventory for RSL, comparing this data with other sign languages. The last but not the least, the enventory of phonemic hanshapes for RSL is derived from the phonetic one under van der Kooij’s (2002) model of phonology.
A home-based intervention towards preschoolers’ EFL sentence development

Research has shown that the initial few years of children’s lives are the best times for language to develop at a rapid pace, the first language (L1) or a foreign language (FL) may be acquired these times. Researches on preschoolers FL acquisition with home-based intervention (HBI) have not been studied extensively under the L1 environment. This study aims to examine the results of HBI on the development of the acquisition of Indonesian preschoolers’ English as a Foreign Language (EFL) sentences. This research is a case study with naturalistic observation design, where data were obtained from logbooks and interview. The research subjects were 2 preschoolers about 36 months. The study’s duration was 24 months from the 13th until the 36th month with HBI, namely parents-based and authentic/semi authentic-media intervention. The data were the children’s English sentences taken at 24th to 36th months at their own homes. The Owens’ acquisition of sentence forms measured the English sentences’ development of in the respondents’ conversation and self-narration. This research found that at about 36th month, these Indonesian preschoolers were able to communicate in English in various sentences such as declarative, negative, interrogative, imperative, embedded and conjoining.&#x0D; HIGHLIGHTS:&#x0D; &#x0D; Simultaneous foreign language learning and first language acquisition for children is tangible advantage.&#x0D; Authentic input and active interaction act as the language environment substitute in foreign language learning.&#x0D; Intensive learning makes preschoolers speak a foreign language earlier.&#x0D;
OCDL-ACDF: a complex-valued image denoising method based on an adaptive complex domain dictionary

Noise reduction is an essential preprocess in applications of complex-valued images. A method of complex-valued image denoising based on complex-valued dictionary learning and an adaptive complex-valued dictionary filter (OCDL-ACDF) is proposed. Our dictionary is first trained by the online dictionary learning method. Then, to further reduce the noise contained in the dictionary atoms, we design a complex-valued dictionary filter based on the feature similarity between the atoms of redundant dictionaries. By combining the advantages of online dictionary learning and denoising methods of real-valued images, an effective complex-valued dictionary is obtained. The orthogonal matching tracking method, which is a greedy algorithm, is used in the process of sparse coding. The simulation experiments show that the denoising effect of the proposed method is not only better than the current advanced algorithms but also effective at avoiding overfitting. The detail fidelity was also relatively high.
Intellectual property issues in artificial intelligence: specific reference to the service sector

Artificial intelligence (AI) has transformed almost every field of the service sector, such as finance, healthcare logistics, automotive and aviation. The innovative technologies can identify uneven patterns like spam filtering or payment deceit, and make aware businesses in actual time about questionable activities, hence are helpful in the growth of a market. These innovation and creation are protected under different forms of intellectual property (IP). However, the transformation from AI related inventions to AI lead inventions has raised substantial challenges to the existing IP infrastructure. This study aims at looking into different aspects of AI related IP protection with an elaborative analysis of the patenting trends through landscape analysis of AI in the service sector. It is observed that AI is playing a pivotal role in the transformation of the service sector due to its accelerating use. But the issues related to legal and ethical need to be addressed for effective utilisation of AI related invention and creation in the service sector.
Respon Remaja Tentang Kasus Cyberbullying Sulli Dan Goo Hara

Cyberbullying is the act of hurting, embarrassing, or distressing people because all the disgrace is publicized on social media. The victim becomes depressed and commits dangerous things such as suicide. This study aims to explain adolescent responses about Sulli and Goo Hara's cyberbullying that cause death. The author applied descriptive qualitative methods. The results revealed the lack of netizen knowledge and consequences on Sulli and Goo Hara's mental health made them not careful in commenting on social media. Therefore, it is important for netizens to be careful about everything that will be posted on social media in order not to get meanly impact to others.
THE EFFECT OF ECONOMIC GROWTH ON INCOME INEQUALITY:PANEL DATA ANALYSIS FROM FIFTY COUNTRIES

The relationship between economic growth and income inequality is one of the controversial issues in macroeconomics. Many studies have been done to show the relationship between economic growth and income inequality. However, the research about this problem by using panel data is still minimum. Also, there is still no research that differentiates the effect between lower-middle, upper-middle, and high-income countries. This paper examines the effect of economic growth on income inequality by analysing a panel data set of fifty countries from 2000 to 2018. Using the Pooled OLS, Fixed Effect, and Random Effect Model, this paper finds that economic growth has a positive significant impact on income inequality, which means the higher the economic growth, the bigger the gap between the rich and the poor. The empirical evidence suggests that a one-point increase in GDP growth will increase the Gini Index by 0.082 to 0.085 points on average. Moreover, the paper finds that the effect of economic growth on increasing the incidence of income inequality seems to be higher in lower-middle and upper-middle income countries than in high-income countries.
6.2 Expanding Dimensions: A New Source in the Bibliometrician’s Toolbox

Developed by Digital Science in collaboration with over 100 leading research organisations around the world, Dimensions is a unique platform combining data about publications, data sets, grants, patents, clinical trials, and policy documents. This database spans the broader global scientific landscape to enable individual researchers as well as research funders, research organizations, and publishers to discover, analyse, and understand multiple aspects of the research life cycle. This chapter introduces the development and deployment of the Dimensions platform and describes the breadth of available functionality with focus on bibliometric applications and question sets that can be applied to the academic and broader outcomes of research, and gather insights to inform future strategy.
Manajemen Layanan Perpustakaan terhadap Loyalitas Mahasiswa pada Masa Pandemi Covid 19

During the covid-19 pandemic the library stopped all services that were in direct contact with users, so that the library was required to carry out new innovation services so that the information needs of the users were still met. Services that can be done are through online services where users can take advantage of the library's digital collection via the internet. The research on the theme of the effect of library service management on student loyalty was conducted to test the impact of library service management variables (X) on student loyalty (Y). The X variable is developed in 3 dimensions, namely the dimensions of library public policy (X1), loan transactions (X2) and online services (X3). Collecting data through distributing questionnaires to students at 3 private universities in Yogyakarta with the category A accredited university which has a student population of more than 25.000 people. Sampling was not using random sampling but by means of convenience sampling. Analyzing data through descriptive statistical testing and multiple regression. The results of multiple regression analysis partially and simultaneously library service management variables as well as the 3 dimensions X1, X2 and X3 affect student loyalty and from the correlation analysis of the dimensions contained in library service management variables to student loyalty variables it is proven that all hypotheses can be accepted. Conclusion: library service management during the pandemic which is responded to by students is a good (positive) phenomenon, so the respondent's appreciation of student loyalty is also good (superior).
Predicting Time Series of Temperature in Nineveh Using The Conversion Function Models

Prediction of time series is one of the topics that receive significant interest because of its importance in various fields, especially when studying natural phenomena. In this research, the transformation function model was reconciled where it aims to use the genetic algorithm to estimate the parameters of the final transformation function model. Also, it was used to predict future values for the time series of monthly averages of temperatures in Nineveh Governorate for the period (1985-2000) as an output series and wind speed as an input series. In Nineveh Governorate, they are not stable in average and variance; when taking the square root of the data and taking the first seasonal difference as well as the first normal difference, stability was achieved, and then showed a model of the transformation function as shown in the equation (17). This research showed that the model's final parameters were estimated using the genetic algorithm based on the standard error squares average. The best estimate was chosen for the parameters that correspond to the lowest value of the average error squares, and by using this model, monthly temperature rates were predicted. Predictive values were shown to be consistent with the original values of the series. By depending on the transformation function model shown in the above equation, monthly averages of the temperature were predicted for the next four months, and the prediction results were consistent with the original time series values, which indicates the efficiency of the model.
NEW CHALLENGES AND OPPORTUNITIES IN LIBRARY COLLECTIONS, SERVICES, SPACES AND OPERATIONS DURING COVID-19: AN OVERVIEW

The Corona Virus Disease 2019 (COVID-19) has changed the strategy for learning and teaching. The diverse lockdown were accounted for recalling the fleeting finish of all informational associations for by far most of the countries by the Government. As a result of these cross-country terminations have influenced 90% of the world's graduated class understudy people. To be sure, even the school understudies are furthermore significantly affected to go to the standard classes. Preparing pros from various countries have taken various undertakings to continue with the learning cycle. COVID proposes the difference in guidance and learning into another pathway of virtual learning.
Geological Survey of Western Australia: AusAEM20-WA update

The TEMPEST® component of AusAEM20–WA Stage 1 is complete. Data from the Eastern Goldfields and the East Yilgarn survey blocks (Figure 1) were released on 4 February 2021, followed by the neighbour...
The Design of Application for Accelerating Funding Proposal Selection Using the Object-Oriented Hypermedia Design Method

The Savings and Loans Unit (USP) is an economic business that provides loans in the form of money for village community business activities for individuals or groups considered productive.The process of borrowing funds is carried out by submitting a loan proposal with terms predetermined by the USP.The purpose of this research is to make an application design for accelerated loan proposals using the Object-Oriented Hypermedia Design Method (OOHDM), which can be implemented in the recommendation system for funding loan proposal selection.OOHDM is used in the design of web applications that are oriented towards building large hypermedia.This research produces a web-based application design whose access rights can be used by the USP as an admin as well as a lending decision-maker and a fund user/borrower submitting a loan proposal.
Identification of unexpected decisions in Partially Observable Monte Carlo Planning: a rule-based approach

Partially Observable Monte-Carlo Planning (POMCP) is a powerful online algorithm able to generate approximate policies for large Partially Observable Markov Decision Processes. The online nature of this method supports scalability by avoiding complete policy representation. The lack of an explicit representation however hinders interpretability. In this work, we propose a methodology based on Satisfiability Modulo Theory (SMT) for analyzing POMCP policies by inspecting their traces, namely sequences of belief-action-observation triplets generated by the algorithm. The proposed method explores local properties of policy behavior to identify unexpected decisions. We propose an iterative process of trace analysis consisting of three main steps, i) the definition of a question by means of a parametric logical formula describing (probabilistic) relationships between beliefs and actions, ii) the generation of an answer by computing the parameters of the logical formula that maximize the number of satisfied clauses (solving a MAX-SMT problem), iii) the analysis of the generated logical formula and the related decision boundaries for identifying unexpected decisions made by POMCP with respect to the original question. We evaluate our approach on Tiger, a standard benchmark for POMDPs, and a real-world problem related to mobile robot navigation. Results show that the approach can exploit human knowledge on the domain, outperforming state-of-the-art anomaly detection methods in identifying unexpected decisions. An improvement of the Area Under Curve up to 47\% has been achieved in our tests.
Analysis of Factors Affecting Student Graduation Using the K-Means clustering Method: Analysis of Factors Affecting Student Graduation Using the K-Means clustering Method

This research was conducted because the system was not yet available to analyze the graduates of FTKI students. The purpose of this study was to obtain the results of the analysis of factors affecting the graduation of the National University FTKI students. This study uses the K-means method and uses GPA, income, place of birth, organizational activity, SKPI scores as parameters. Data collection techniques in the form of quantitative data collection. The subjects of this study were alumni of the FTKI National University. From the results of research conducted cluster 3 has the highest average IPK value of 3.57, of the total birth place clusters most are in Jabodetabek, all of the clusters show that organizational inactivity is the highest value, overall income clusters have the most value in class one, in cluster 3 the SKPI score has the highest average value of 3451.
Fuzzy Decision Tree Induction Using Fast Data Partitioning and Incremental Approach

The decision tree is one of the popular methods for learning and reasoning through recursive partitioning of data space. To choose the best attribute in the case on numerical features, partitioning criteria should be calculated for individual values or the value range of each attribute should be divided into two or more intervals using a set of cut points. In partitioning range of attribute, the fuzzy partitioning can be used to reduce the noise sensitivity of data and to increase the stability of decision trees. Since the tree-building algorithms need to keep in main memory the whole training dataset, they have memory restrictions. In this paper, we present an algorithm that builds the fuzzy decision tree on the large dataset. In order to avoid storing the entire training dataset in main memory and overcome the memory limitation, the algorithm builds DTs in an incremental way. In the discretization stage, a fuzzy partition was generated on each continuous attribute based on fuzzy entropy. Then, in order to select the best feature for branches, two criteria, including fuzzy information gain and occurrence matrix are used. Besides, real datasets are used to evaluate the behavior of the algorithm in terms of classification accuracy, decision tree complexity, and execution time as well. The results show that proposed algorithm without a need to store the entire dataset in memory and reduce the complexity of the tree is able to overcome the memory limitation and making balance between accuracy and complexity .
Intelligent Control of Touch Tone of Digital Piano Based on Audio Equalizer

Timbre is the key factor in digital piano performance. In order to effectively control the tone of the digital piano, improve the quality of the digital piano performance, the paper present an intelligent control of touch tone of digital piano based on audio equalizer. The experimental results show that the method is effective, which provides a basis for digital piano players to play more beautiful music works better.
Efektivitas Sistem Temu Kembali Informasi Perpustakaan Digital Institut Seni Indonesia (ISI) Yogyakarta dalam Tinjauan Recall dan Precision

Today's digital library is a necessity. A system that provides all-digital information and services requires that all aspects of it should be accessed effectively. In the context of information retrieval in digital libraries, the information retrieval systems are important instruments. The system becomes a link between relevant information and its users. Evaluation of the information retrieval system to determine its effectiveness is important to ensure that users receive good retrieval services. Recall and precision are approaches to measure the effectiveness of information retrieval systems that are widely used. This study aims to determine the effectiveness of the ISI Yogyakarta digital library retrieval system based on recall and precision approaches. This study will provide benefits for librarians in knowing the effectiveness of the information retrieval system and the extent of their accuracy in indexing. This research uses an experimental method with a quantitative approach. The researcher chose a sample of the searching keywords purposively and then tested them by searching on the portal http://digilib.isi.ac.id/. The data obtained were analyzed using the formula recall and precision. In this study the subjects tested were interior design subjects. The precision measurement of 10 keywords on the subject of interior design gets 92.37% results while the recall measurement gets 80.79% results. The result stated that precision is higher than recall, it showed that the information retrieval system of ISI Yogyakarta’s digital library is quite effective.
Engineering Design Process of Arduino Uno-based Smart Classroom Technology

The important role of higher education in the 21 st century is to participate in educating the public through the development of research results, therefore the Department of Electrical Engineering at the Raja Ali Haji Maritime University emphasizes the importance of implementing an engineering design process to be able to produce technology-based innovations needed by society. This research is a form of higher education contribution in improving student learning outcomes in elementary schools, through the provision of facilities in classrooms. Technology in schools is one of the driving forces for advancing education in schools and is expected to be able to change the mindset of students at Government Primary School (SD Negeri) 011 Tanjungpinang Timur to get to know technology more. It can be said that to realize the perfection of students, in addition to learning activities, supporting facilities are also needed at school according to technological developments. It is hoped that the facilities in technology-based schools will be able to encourage students to be more enthusiastic about learning, have a desire to know developments in the world of technology and change their mindset towards the use of technology in everyday life. From the observations, it was found that the main problem was the minimal use of technology in schools. With these technological problems, this study will design technology-based prototypes, namely smart classrooms based on Arduino Uno, with the aim of making it easier for teachers to turn on electrical equipment in class without direct contact with switches. The intelligent classroom system design uses the Arduino uno as a controller, the HC-06 bluetooth module as a liaison for the user's android with the Arduino Uno, and the boarduino application as a command from the android via bluetooth transmission media
Categorizing Misogynistic Behaviours in Italian, English and Spanish Tweets

espanolLa misoginia es un fenomeno con multiples facetas y puede manifestarse linguisticamente de muchas formas. Las campanas de evaluacion de EVALITA e IberEval en 2018 propusieron una tarea compartida de Identificacion Automatica de Misoginia (AMI) basada en tweets en italiano, ingles y espanol. Dado que los resultados de los equipos participantes fueron bastante bajos en la categorizacion del comportamiento misogino, el objetivo de este estudio es investigar las posibles causas. Medimos el solape y la homogeneidad de los clusteres variando el numero de categorias. Este experimento mostro que los grupos se solapan. Finalmente probamos varios modelos de aprendizaje automatico utilizando los conjuntos de datos originales y fusionando algunas categorias de acuerdo con consideraciones basadas en medidas de similitud y las matrices de confusion de los modelos, obteniendo un aumento de la F1 macro. EnglishMisogyny is a multifaceted phenomenon and can be linguistically manifested in numerous ways. The evaluation campaigns of EVALITA and IberEval in 2018 proposed a shared task of Automatic Misogyny Identification (AMI) based on Italian, English and Spanish tweets. Since the participating teams' results were pretty low in the misogynistic behaviour categorization, the aim of this study is to investigate the possible causes. We measured the overlap and the homogeneity of the clusters by varying the number of categories. This experiment showed that the clusters overlap. Finally, we tested several machine learning models both using the original data sets and merging together some categories according to their overlap, obtaining an increase in terms of macro F1.