Reviewerly/exHarmony huggingface dataset:
Simple and precise calibration of the line-structured light vision system using a planar target

When calibrating a line-structured light vision system using a planar target, noise easily affects the solution of the coordinates of light stripe points at the camera coordinate frame. Therefore, the planar target must be placed in the measurement space many times to capture more target images for improving calibration stability and achieving relatively high calibration accuracy. This complicates the calibration process. This paper proposes a calibration method considering the measurement baselines of a planar target. The planar target is placed only two times, and two target images are captured correspondingly. A three-point subset is made up of the two calibration points that form the measurement baseline with the longest 2D projection and any other calibration point. In this way, it is less affected by noise when using the three-point subsets to establish the equations. Then, we use the lengths of the measurement baselines provided by all three-point subsets and their 2D projections to solve the coordinates of light stripe points at the camera coordinate frame more accurately to calibrate the line-structured light vision system. Both the simulation and actual experiment results demonstrate the feasibility of our method. Based on our calibration method, the RMS error is 0.035 mm for length measurement and 0.054 mm for height measurement. Compared with other existing methods, our method needs only two target images. It can also achieve more accurate calibration results than the other methods. In addition, our calibration method increases the applicability of the line-structured light measurement method by reducing the number of target swings.
Tackling the multilingual and heterogeneous documents with the pre-trained language identifiers

The Web has become one of the most important data sources, and the content shared is most often multilingual, as users belong to different cultures and speak different languages. Multilingual content (document) is not suitable for many people who only need content in one language. Furthermore, dividing a multilingual document into monolingual documents helps researchers extract only the text of the desired language to use in different tasks such as training or model testing. Therefore, it is challenging to clean and divide the raw content manually. This paper presents an automatic approach to dividing a multilingual document and reassembling it into monolingual documents by examining three existing state-of-the-art tools for Language Identification (LI). We prepared different corpora with different heterogeneity characteristics for the evaluation and evaluated their code-switching pattern using three different code-switching metrics. The proposed approach reached 99% as the best accuracy result for the long segment (long text) and 90% for the mixed segment. In addition, a good correlation was found between the I-Index and accuracy with Pearson’s r = −0.998.
Majorana's stellar representation of single-particle reduced density matrix for completely symmetric states

The completely symmetric states play an essential role in quantum physics. In this paper, we calculate the reduced density matrix (RDM) for a single particle of the completely symmetric system coupled by $N$ spin-$\frac{1}{2}$ particles, because it helps to investigate the evolution of expectation value for the observable and to calculate the entanglement between the subsystems. Furthermore, we use Majorana's stellar representation (MSR) to represent the results because it provides an intuitive geometric perspective to comprehend the quantum states in the high-dimensional Hilbert space with distributions and trajectories of the Majorana stars on a Bloch sphere. With the operation properties of the generalized many-body anticommutator, we get the general MSR form of a single-qubit RDM. As the application and verification, we calculate the single-qubit RDM for the Dicke states with the results. Similarly, we further solve the RDM of the spin-$\frac{N}{2}$ state in a uniform magnetic field and study the systems with symmetric structures on the Bloch sphere. The results exhibit the relations between the composite systems and the subsystems, and provide a new idea for the numerical solution of multiqubit systems.
Large sets of Strongly Cospectral Vertices in Cayley Graphs

Strong cospectrality is an equivalence relation on the set of vertices of a graph that is of importance in the study of quantum state transfer in graphs. We construct families of abelian Cayley graphs in which the number of mutually strongly cospectral vertices can be arbitrarily large.
Waffster: Hierarchical waffle charts for budget visualization

Understanding and consuming public budget data is a key issue, helping citizens in gaining insight into their democratic and political systems. The goal of this work is to present Waffster, a user-friendly representation supporting the understanding of such data. The proposed representation enables the browsing, searching, comparing, and presenting of the hierarchically arranged components and quantities in budgets. In this paper, we first conduct a thorough survey of online public budget visualizations. Then, in collaboration with Le Devoir, a Canadian daily newspaper, we propose a novel unit-based hierarchical design based on waffle charts. We evaluate this design using a controlled user study to compare it to a tree-map based layout, and a case study conducted with Le Devoir during the provincial election campaign in Québec of 2018.
Corpus stylistic analysis of literary translation using multilevel linguistic measures

Abstract Previous studies in corpus-based literary translation have tended to focus on only one or two specific aspects of style. In this study we expand the existing analytical paradigm to show how the style inherent in source texts (STs) is reflected in their translations. We do this using thirty-six multilevel linguistic features. The selected texts are James Joyce’s Dubliners and A Portrait of the Artist as a Young Man and their Korean translations. We find that the general stylistic patterns in the STs are mirrored in the target texts (TTs) in terms of several linguistic measures, but that some aspects of style are not reflected in the TTs. The stylistic discrepancies between the STs and TTs may signify the translator’s strategic decisions to adhere to the target language (TL) norms and translation conventions as well as to preserve the style in the ST.
A Scalable Method to Exploit Screening in Gaussian Process Models with Noise

A common approach to approximating Gaussian log-likelihoods at scale exploits the fact that precision matrices can be well-approximated by sparse matrices in some circumstances. This strategy is motivated by the screening effect, which refers to the phenomenon in which the linear prediction of a process Z at a point x0 depends primarily on measurements nearest to x0. But simple perturbations, such as iid measurement noise, can significantly reduce the degree to which this exploitable phenomenon occurs. While strategies to cope with this issue already exist and are certainly improvements over ignoring the problem, in this work we present a new one based on the EM algorithm that offers several advantages. While in this work we focus on the application to Vecchia’s approximation (Vecchia), a particularly popular and powerful framework in which we can demonstrate true second-order optimization of M steps, the method can also be applied using entirely matrix-vector products, making it applicable to a very wide class of precision matrix-based approximation methods. Supplementary materials for this article are available online.
Optimizing user profile matching: a text-based approach

The rapid expansion of social media platforms has made linking user profiles across various networks an essential aspect of maintaining a consistent identity. With 4.66 billion users reported to be in the Websphere, many are active on multiple social media platforms simultaneously. Identifying users across multiple platforms poses challenges in integrating user profiles from various sources. Different matching schemes have been suggested over the years based on different user profile features, but very little information has been uncovered about user-generated text as a unique attribute for user profile matching, which generally poses real challenges in real-world scenarios. As many users have insufficient text and the use of non-discrete text information makes the comparison operation between the two social networks of quadratic complexity. Our study examines the different existing literature schemes for matching user profile pairs based only on their generated textual content. We suggest and evaluate the effectiveness of a two stage matching approach based on Locality Sensitive Hashing clustering and nearest neighbor search. We also present other matching results of different user representations language models and matching schemes.
Neural axiom network for knowledge graph reasoning

Knowledge graph reasoning (KGR) aims to infer new knowledge or detect noises, which is essential for improving the quality of knowledge graphs. Recently, various KGR techniques, such as symbolic- and embedding-based methods, have been proposed and shown strong reasoning ability. Symbolic-based reasoning methods infer missing triples according to predefined rules or ontologies. Although rules and axioms have proven effective, it is difficult to obtain them. Embedding-based reasoning methods represent entities and relations as vectors, and complete KGs via vector computation. However, they mainly rely on structural information and ignore implicit axiom information not predefined in KGs but can be reflected in data. That is, each correct triple is also a logically consistent triple and satisfies all axioms. In this paper, we propose a novel NeuRal Axiom Network (NeuRAN) framework that combines explicit structural and implicit axiom information without introducing additional ontologies. Specifically, the framework consists of a KG embedding module that preserves the semantics of triples and five axiom modules that encode five kinds of implicit axioms. These axioms correspond to five typical object property expression axioms defined in OWL2, including ObjectPropertyDomain, ObjectPropertyRange, DisjointObjectProperties, IrreflexiveObjectProperty and AsymmetricObjectProperty. The KG embedding module and axiom modules compute the scores that the triple conforms to the semantics and the corresponding axioms, respectively. Compared with KG embedding models and CKRL, our method achieves comparable performance on noise detection and triple classification and achieves significant performance on link prediction. Compared with TransE and TransH, our method improves the link prediction performance on the Hits@1 metric by 22.0% and 20.8% on WN18RR-10% dataset, respectively.
The Beginning of a New Paradigm: From D. Bernouilli to M. Allais

To represent the interaction of the human being with his environment and letting him express it, therefore blending the subject with the object and completing what was missing from Quantum theory. In our polynomial the subjective factor Xo shows up in the numerator and leads to an objective valuation since of a finite degree. Study also revives an approach to elicit human preferences based on the stimuli-response procedure long forgotten. Fifty years ago a new theory, Elementary Catastrophe Theory,(E.C.T.), unfolding a unique Potential in our brain, provided the underlying dynamics needed to fulfill all the desiderata of the so-called school of Psycho-Physics (Weber-Fechner, 1860), seeking to make mathematical sense of the procedure above. The axiomatization of a self-measurement process removes any "a priori" assumptions about human motivation from the explanation of the empirical data. This 5th degree symmetric polynomial exhibits a characteristic (Negative Schwarz' Derivative) that goes a long way to resolve disputes and remove obstacles in the development of Portfolio Theory in addition to meeting the major landmark criteria in the fields of Value and Utility.&nbsp; Given that chaos theory has the divergence of Newton's Method as a paradigm, we have brought order to a potentially chaotic process because our algorithm ensures local and global convergence through the careful selection of initial points. The possibility of expanding the approach to the complex field is encouraged by the expression of the Schwarz derivative's invariance to the Mobius transformation.
IMPROVING PROCEDURE TEXT WRITING ABILITY WITH THE PAIR CHECKS LEARNING MODEL IN CLASS XI CULINARY ART OF VOCATIONAL HIGH SCHOOL WIRA BHAKTI

This study aims to determine the increase in the ability to write procedural texts using the pair checks learning model in class XI culinary art of Vocational High School Wira Bhakti. The method used in this research is descriptive method. The descriptive method is related to the explanation of social phenomena to the observed subjects. The techniques used in this research are observation, documentation study, and tests. The results of the ability to write procedural texts using the pair check learning model for class class XI culinary art of Vocational High School Wira Bhakti in cycle I was 72.88% and in cycle II the student score was 80.45%. It can be concluded that the application of the pair check learning model is able to improve the ability to write procedural texts in English for class XI culinary art of Vocational High School Wira Bhakti.
The importance of databases in web programming

Databases are fundamental when working with web applications. The database is a place where the data which is necessary for the operation of a web application is entered, read, deleted and updated on a daily basis. The aim of this paper is to consider the benefits of database’s implementation when it is used for data storage coming from a specific Web application. Hereof, in this paper are shown various advantages: starting from the exchange of data between the web application and the database, the security mechanisms available to the database, how to protect the data from the application stored in the database, how to confirm the identity of the user, data access etc. The subject of research in this paper is to regard more precisely the pros and cons of applying the database when it is used for storage of data coming from a specific Web application.
Cyber Risk Insurance – An Effective Risk Management Tool for SMES in the UK?

This article aims to analyse to what extent small and medium sized businesses (SMEs) in the United Kingdom (England, Scotland, Wales and Northern Ireland) utilise cyber risk insurance as a risk mitigation tool in their cyber security management systems. To this end, the authors, by adopting a systematic qualitative analysis, elaborate the nature and scope of cyber risk insurance products on offer for SMEs (the supply side of the cyber insurance market). They then by utilising the data obtained from SMEs randomly but purposively, attempt to gain an understanding of the attitude of SMEs to cyber security generally and to cyber risk insurance. The main conclusion of the article is that the insurance market should consider developing a new cyber risk insurance product that aligns cyber security closely with the principle of indemnity. It is discussed in the article how such a product will enhance SMEs’ cyber security resilience (hence providing a social benefit for the society) and at the same time afford new opportunities for insurance providers to expand the size of their business and variety of their products.
Literacy Movement in Indonesian and Spanish Context: A Comparative Case Study

&lt;span lang="EN-US"&gt;Literacy movement serves a vital role to support, facilitate, and enhance literacy skills that is crucial to every human being overall development including character, social, and professional development. This comparative study on literacy movement in Indonesia and Spain analyze how these nations promote literacy movement to accelerate students’ literacy skills and how the literacy movement implemented. Likewise, this study adopts a case study in which the data were derieved from observation protocol, document analysis, questionnaies, and interview transcripts. The data analysis revealed that Indonesia through &lt;em&gt;Gerakan Literasi Nasional&lt;/em&gt; (GLN) promotes the literacy by creating literacy culture in educational ecosystem start in family, school, and society as a mean of long-life learning to improve life quality whereas the Ministry of Education Culture and Sport in Spain created a program called Act on The Improvement of the Quality of Education (LOMCE in Spanish) to promote and create a literate environment and improve educational result. As it further investigated, the most noticeable comparison between the practice of literacy movement in Indonesia and Spain is on the equality of literacy movement in every region. In Spain, the literacy movement is equally well-established in every region whereas the equality of literacy movement in Indonesia region is still not equal yet. In this matter, the implementation of literacy movement should be supported by qualified educators, appropriate materials, adequate infrastructure, and effective literacy policies in order to effectively promote the students’ literacy skills and development.&lt;/span&gt;
THE INFLUENCE OF STUDENTS’ GRAMMAR PROFICIENCY ON READING ABILITIES: A STUDY AT AN ISLAMIC BOARDING SCHOOL

This study explored the relationship between grammar and reading abilities of third-grade junior high school students of an Islamic boarding school in Indonesia. The total number of students sampled in this study was 60 students, with details consisting of 30 female students and 30 male students. The data collection instruments used in this research were grammar tests and reading comprehension tests. The researchers analyzed the data using Pearson Product Moment Correlation and calculated the data using Microsoft Excel 2019 program to test the hypothesis. The result of calculation using Microsoft Excel 2019 program found that the correlation coefficient of grammar mastery and students' reading ability is 0.93 with a significant level of 0.01. With these results, it can be seen that these variables are positively correlated. And there is a significant relationship between grammar mastery and the student's reading ability.
SECONDARY STUDENTS’ REFLECTION TOWARDS MULTIMODAL READING TASKS THROUGH VIRTUAL DIGITAL PLATFORM LEARNING DURING THE COVID-19 PANDEMIC: VOICES FROM INDONESIA

This study reports on secondary students’ reflection towards multimodal reading tasks through virtual digital platform learning. It investigates students’ learning outcomes after studying a multimodal reading involving through five-step learning activities, such as lesson preparation to examine the lesson-planning process, including the use of supplementary materials, and the meaningfulness of activities, scaffolding/modeling to focus on making explicit and direct links between past learning related to the students’ schemata and new concepts, comprehensible input to consider adjusting teacher modeling multimodal reading to enhance comprehension, practice and application and review and assessment to assess students’ learning, and provided feedback to students on their output The data were collected during the 2nd academic term (January-May 2020). The research was conducted in the Senior High School in Indonesia in which thirty five students (20 females and 15 males) participated in this study. The data were analyzed by using Braun &amp;amp; Clark’s (2006) thematic analysis. The findings show that encountered some benefits from this digital platform learning such as the availability of myriad sources online which the students could access at their flexible and convenience time. Additionally, Student teachers’ autonomy, agency, engagement, confidence, skill-set, and the ability to collaborate through online discussion are the important point that they experienced during their learning reading digital texts. Finally, the short time of the studies included in exploration might also indicate the strong need for further longitudinal research on the topic.
THE IMPACT OF USING TEAM GAME TOURNAMENT TO ENHANCE STUDENTS’ VOCABULARY MASTERY

The aim of this study is to reveal the effectiveness of using Team Game Tournament (TGT) to improve the vocabulary mastery of the second-grade students of Islamic Junior High School in Indonesia. Quantitative method design is used in this research. In order to achieve the objective of this research, the researchers designed a quasi-experimental study. The researchers used two classes to take pre-test and post-test, namely experiment and control classes. The teacher teaches vocabulary mastery in two classes. The experiment class used TGT and the control class used existing English textbook in teaching vocabulary mastery. For the data collection method, this study used vocabulary tests with multiple choice questions based on pictures. The final result of this experiment shows the average value of the experimental class was greater than the control class. Based on the findings, it can be concluded that TGT is effective in improving vocabulary mastery.
ROLE PLAY TO IMPROVE STUDENTS’ PARTICIPATION IN LEARNING ENGLISH: A REPORT FROM A HIGH SCHOOL IN EAST JAVA

The study aims to examine to what extent a role-play method can increase students’ participation in English learning. Classroom Action Research (CAR) is conducted to achieve the purpose. Research data are collected through observation to look at students’ participation and questionnaires that are distributed throughout 3 cycles of role-play implementation. The study shows that the role-play method can be enacted to improve students’ participation in learning English. There is also an increase in students’ participation during the three cycles of role-play enactment which proves that this method has a prominent potential in enhancing students’ English learning engagement.
EFL STUDENTS' PERCEPTION ON THE USE OF YOUTUBE AS ONLINE LEARNING MEDIA DURING COVID-19 PANDEMIC

YouTube is a mobile application and social network that are integrated with various platforms and other media such as blogs or presentation materials. Developing a learning community through YouTube makes students experience online learning in an interesting way. The purpose of this study was to find out students' perception in learning English through online learning during Covid-19 pandemic. The participants selected for this research were five students from one of the universities in Bogor, Indonesia. This study uses qualitative research design. The results of this study indicate that YouTube is very helpful in online learning for students and this media can be accessed during online learning because it provides many educational videos to learn English and other skills. However, some difficulties were also found in this study. YouTube is also considered to add education fees in terms of connection. Students, in addition, stated that they had problem with their connection i.e., unstable signals and the ability to understand the video. This activity aims to summarize responses on the use of YouTube as a media of online learning during Covid-19 pandemic.
Educational policy of Heydar Aliyev as a way to inclusive education

Successful education policy – held by Great Leader Heydar Aliyev has played – an important role for the development of inclusive education. In the world, there have been different approaches to the education of people with disabilities, from the period of "isolation" to the period of "inclusion". Currently, inclusive education is regulated by both local and international legislation. Various studies prove that inclusive education leads to positive results for all students both academically and from a socio-psychological point of view, important works are being done in the direction of inclusive education development all over the world, including our country.