Reviewerly/exHarmony huggingface dataset:
FACTORS AFFECTING SECOND LANGUAGE ACQUISITION AMONG BOARDING SCHOOL STUDENTS

Past study has shown that second language acquisition is equally important as second language learning. Second language acquisition is the subconscious process of absorbing the second language knowledge, and it happens automatically when the students are exposed to the use of the language around them. This study aims to identify the factors affecting second language acquisition among boarding school students and how they acquire the language. The participants were students in one of the boarding schools in Peninsular Malaysia. The data were collected through semi-structured interviews. The findings demonstrate two factors affecting second language acquisition among boarding school students: intellectual process and mother tongue influence. Of the two categories, intellectual processes are the most dominant factors in which are the two major contributing factors affecting second language acquisition among boarding school students. This study implicates the importance of second language acquisition in driving proficiency and enhancing the learning process among boarding school students.
Metaknowledge Enhanced Open Domain Question Answering with Wiki Documents

The commonly-used large-scale knowledge bases have been facing challenges in open domain question answering tasks which are caused by the loose knowledge association and weak structural logic of triplet-based knowledge. To find a way out of this dilemma, this work proposes a novel metaknowledge enhanced approach for open domain question answering. We design an automatic approach to extract metaknowledge and build a metaknowledge network from Wiki documents. For the purpose of representing the directional weighted graph with hierarchical and semantic features, we present an original graph encoder GE4MK to model the metaknowledge network. Then, a metaknowledge enhanced graph reasoning model MEGr-Net is proposed for question answering, which aggregates both relational and neighboring interactions comparing with R-GCN and GAT. Experiments have proved the improvement of metaknowledge over main-stream triplet-based knowledge. We have found that the graph reasoning models and pre-trained language models also have influences on the metaknowledge enhanced question answering approaches.
Structure, metamorphism, and geodynamic significance of the Catalina Schist terrane

ABSTRACT This guide begins with an overview of the internal structure and petrology of the Catalina Schist terrane as exposed on Santa Catalina Island, California, followed by a discussion of the tectonic setting and exhumational history of the terrane, and the Cenozoic tectonic and geological evolution of the Inner Borderland, within which it lies. The guide then presents an itinerary for a three-day field trip from 9–11 May 2020. Next, we present a tectonic model for the formation of the Catalina Schist, followed by a discussion of its relationship to the Pelona, Orocopia, Rand, and related schists in southern California. This field trip generally follows the GSA guide published in GSA Field Guide 59 (available at https://pubs.geoscienceworld.org/gsa): Platt, J.P., Grove, M., Kimbrough, D.L., and Jacobson, C.E., 2020, Structure, metamorphism, and geodynamic significance of the Catalina Schist terrane, in Heermance, R.V., and Schwartz, J.J., eds., From the Islands to the Mountains: A 2020 View of Geologic Excursions in Southern California: Geological Society of America Field Guide 59, p. 165–195, https://doi.org/10.1130/2020.0059(05).
تحلیل سیمیائی لثلاث ترجمات عربیة لروایة جورج أوریل 1984 A Linguistic Analysis of Rats Semiotics in Orwell’s 1984 and its Three Arabic Translations: An SF-MDA

The current study is an attempt to interlink meaning making, through the process of translation from the source text (ST) to the target text (TT), to Systemic Functional Multimodal Discourse Analysis (SF-MDA) (Kress and van Leeuwen, 2006).Given the relevance to SF-MDA through the process of extracting embedded meaning within context, it serves as an approach to textual demonstration via the identification of lexicogrammatical choices which contribute to meaning construction.Based on Halliday's (2004) and Kress and van Leeuwen's (2006) theoretical frameworks, the current study is a comparison between creating the meaning of ironical image through the semiotics analysis of the sign "rats" in Orwell's 1984 in three Arabic translations.The lexicogrammatical choices of the ST are interpreted through transitivity processes using SF-MDA approach.Further, the three translations of "rats" semiotics are compared and examined to investigate how the ironical imagery of "rats" semiotic connotation is renarrated in the Arabic translations.Data of the current study A Linguistic Analysis of Rats Semiotics in...
Initialization and Estimation of Weights and Bias using Bayesian Technique

Researches on artificial neural network models have shown that the method used to initialize and estimate weights and bias always determines the rate at which the network will converge and how efficient the model will perform. Although there are several methods that can be used to initialize and estimate network weights and bias, Bayesian approach is widely considered as a more efficient method for modelling artificial neural networks because it can easily compute the inverses of covariance matrices with high dimension that otherwise are computationally expensive. This study has developed a new filter, the First order Extended Ensemble Filter(FoEEF),that applies numerical solution in solving the inverses of high dimensional covariance matrices from I ^ to ′ s stochastic state-space dynamical models. The research applies the new FoEEF Filter to initializes and estimates the weights and bias of artificial neural network. Comparison on the performance of FoEEF filter in estimating weights and bias are done against the performance of EKF on function estimations by using two different functions, sin(x)+Q function and 3sin(x)3− 3sin(x)2 − sin(x) + 1 function, within 18 and 22 epochs. Emphasis of the performance is placed on the rate at which the models converge. This study gauges the performance by determining the minimum value of the mean square error produced from each epoch and average mean square error minimum value.The outcome from the study showed that FoEEF filter had the lowest value of mean square error and average mean square error which was achieved with the least number of epochs compared to EKF filter. This study concluded that the new FoEEF performed better than EKF and is a more suitable filter for that can be used for initialization and estimation of weights and bias in artificial neural network.
PROGRAM APLIKASI PEMBELAJARAN PADA TAMAN KANAK-KANAK MENGGUNAKAN MACROMEDIA FLASH

Kindergarten (kindergarten) is one of the educational institutions that have an important role in various aspects of development as well as in the learning process. The purpose of this study is to create interactive learning in getting to know numbers and sorting numbers. Learning letters includes: getting to know letters and sorting letters. And learn to know numbers. The methods used in this study are qualitative methods with application program design using Macromedia Flash 8.0 and system design using Unified Modeling Language Introduction (UML). The results showed that the level of effectiveness and interactive learning process in Nurul Huda kindergarten was still lacking. With the application of this computerized child learning application program, learners will be more interactive so that the learning process in Nurul Huda kindergarten is more effective. There is a difference in the level of effectiveness and interactive in learning between the system manually by using computerized program applications in Nurul Huda kindergarten.
RevRec, ASC 606 and IFRS 15: A Briefing on Changes to the Revenue Recognition Regime and their Impact on Technology Agreements

Article RevRec, ASC 606 and IFRS 15: A Briefing on Changes to the Revenue Recognition Regime and their Impact on Technology Agreements was published on April 1, 2022 in the journal Computer Law Review International (volume 23, issue 2).
Pemilihan Kandidat Campaign Volunteer harisenin.com dengan Metode Profile Matching

With the opening of the Harisenin Volunteer program, there are also many registrants who want to join as part of harisenin.com. Due to the large number of registrants, volunteer organizers often have difficulty in selecting candidates, because they do not yet use the Decision Support System. To minimize these obstacles, a decision support system is needed that can analyze several candidates according to predetermined criteria. The Profile Matching process is carried out to determine the most suitable candidate recommendations based on 2 main criteria, namely the suitability of tagging friends in the comments column of Calling for Campaign Volunteer posts and the suitability of uploading twibbon and re-uploading Calling for Campaign Volunteer posts. The result of the selection process is the candidate's final score as a recommendation for decision makers to choose the most suitable candidate for harisenin.com.
Linked open data as a path towards open science

of the CIRCSE Research Centre, which he co-founded in 2009.His main research interests deal with building, using, and disseminating linguistic resources and natural language processing tools for Latin.As a former pupil of one of the pioneers of humanities computing
Implementasi Algoritma K-Medoids dalam Pengelompokan Mahasiswa yang Layak Mendapat Bantuan Uang Kuliah Tunggal

The Single Tuition Assistance Program (UKT) is a program aimed at students whose parents' jobs have been affected by COVID-19. Where this assistance is a program from the government to reduce the number of students who stop continuing their education due to the impact of income during Covid-19, so that universities are appointed by the government to select students who deserve the assistance. However, the problem is, the manual selection system can cause errors or confusion in making the selection so that the term wrong target arises. To narrow this possibility, these problems can be overcome by using data mining to assist universities in determining students who deserve single tuition assistance (UKT). In data mining, a method is needed. In this research, clustering method is used using the K-Medoids Algorithm so that decision making is very effective and fast. Based on this research, it is known that those who deserve to receive tuition assistance in arrears (UKT) are Rohan Purba, Zaza Mutiara, Putri and Alexander.
On Information Hiding in Natural Language Systems

With data privacy becoming more of a necessity than a luxury in today's digital world, research on more robust models of privacy preservation and information security is on the rise. In this paper, we take a look at Natural Language Steganography (NLS) methods, which perform information hiding in natural language systems, as a means to achieve data security as well as confidentiality. We summarize primary challenges regarding the secrecy and imperceptibility requirements of these systems and propose potential directions of improvement, specifically targeting steganographic text quality. We believe that this study will act as an appropriate framework to build more resilient models of Natural Language Steganography, working towards instilling security within natural language-based neural models.
Domain Adaptive Scene Text Localization in Night View Images

Scene text localisation in a night is a challenging problem and a less explored problem in the area of robust reading. The day and night images have a different distribution. Hence, a domain shift exists from day to night images. This paper introduces a domain adaptation network (DAN) to learn the domain shift from day images to night images. The proposed sub-network DAN can be attached to any existing state-of-theart text detector to learn the domain shift from day to night. For the training of the DAN, synthetic data generation has been done by utilising the generative adversarial network. The proposed method has been extensively validated on the public as well as on the synthetic datasets. The proposed DAN improves the performance of the underline text localisation model with a margin of 1.4-4.0%, 0.1-1.0%, and 0.1-3.1% on LP Night Dataset, ICDAR2015, and Total-Text benchmarking datasets.
A Quantitative Study on the Cohesion Problems in English Majors’ Chinese Translation of English Texts

Cohesion is an important means to achieve textual coherence. In translation instruction, it is important to raise students’ awareness of textual cohesion in order to improve their translation competence. However, few studies have been conducted to investigate the problems of cohesion that may exist in students’ translated texts. This article compares the cohesive devices used in the Chinese texts translated from English by 38 junior English majors studying in a major university in China with those in a reference Chinese version, for the purpose of revealing the cohesion problems that may exist in the students’ Chinese translation and providing reference for translation instruction. The results show that the major problems include overuse of personal reference and conjunction, especially additive conjunction, insufficient use of ellipsis and repetition which are common cohesive devices in original Chinese texts. The problems reveal, on the one hand, that students may still be under the influence of the source language negative transfer, and on the other hand, that they may have insufficient understanding of Chinese textual cohesion and the differences between English and Chinese in this regard.
Study on Geochemical Exploration and Processing Studies for Graphite and Tungsten Minerals from Burugubanda-Tapaskonda Areas of East Godavari District, India

Graphite-tungsten mineralization can be found in graphite schists linked with khondalites in the East Godavari district's Burugubanda-Tapaskonda districts, India. Geochemical and geophysical methods of exploration followed by soil and stream sediment sampling clearly demarcated the zones of tungsten mineralization in association with the graphite ore bodies. The fixed carbon and tungsten contents varies from 6.5-10.5% Folin-Ciocalteu reagent and 0.1-0.5% WO3, respectively. The low grade graphite deposits as well as tungsten minerals were subjected to processing studies adopting different techniques to achieve maximum percentage of recovery. The final product of recovery assaying 60-80% Folin-Ciocalteu reagent and 60-65% WO3. The experimental process did not yield satisfactory results but it can be used/applied to obtain an unknown product as pre concentrate which can be subjected to other suitable process to obtain a better concentrate.
Digital forensics: a fast algorithm for a digital sensor identification

We consider the identification of imaging devices by analysing images they produce. The problem is studied in the literature, yet the existing solutions are rather computationally demanding. We propose a high-speed algorithm for the identification of imaging devices. The aim is to provide additional security by identification of legitimate imaging devices or an identification for forensics. The experimental evaluation confirms efficient identification of devices models and brands by the proposed algorithm, compared with the state-of-the-art method. Moreover, our algorithm is approximately two orders of magnitude faster, which is very important in resource-constrained IoT ecosystems or very large databases.
Skills for the European Open Science Commons: Creating a training ecosystem for open and FAIR science

This poster introduces the Skills4EOSC Horizon Europe project (2022-2025) and in particular the legal and ethical working package. The projectâs objectives are the training and up-skilling of data professionals in the field of open science.
High Prevalence of Morphological Abnormality on Peripheral Blood Cells Among Patients in Public Hospitals, Southern Ethiopia

Introduction: Morphologically abnormal blood cells in peripheral blood of a person reflect underlying pathological condition affecting formation, function, and lifespan of these cells. A properly identified morphological defect in peripheral blood cells is important to manage anemia, leukemia and other disorders of blood. This study aimed to assess magnitude and severity of morphological abnormality in blood cells of patients with abnormal complete blood count in public hospitals found in southern Ethiopia. Method: A facility-based cross-sectional study was conducted from January 01 to March 31, 2019 among five public hospitals in Southern Ethiopia. Peripheral blood sample and socio-demographic data were collected from 423 patients with abnormal complete blood count. Thin blood smear was prepared by Wedge method, stained with Wright’s Stain, and examined under microscope by 1000X magnification to detect and characterize abnormality in blood cells’ morphology. Descriptive statistical analysis was done using Statistical Package for Social Sciences version 20.0, and results are presented in tables and figures. Result: Prevalence of blood cell morphological abnormality was 63.8%. From this, 21.8% is marked and 78.2% is moderate abnormality. In 41.9% of the affected patients, the defect involved at least two blood cell types mainly affecting red blood cells. Females (73.8%), children (70.1%) and elderly (82.1%) carried higher prevalence of the abnormality. Conclusion: High prevalence of abnormality in PBS morphology was observed, chiefly among female, children and elderly. Stakeholders should work to alleviate the high prevalence, with particular attention to women, children and old-age people.
Integrating Cognitive Principles From ACT-R Into Probabilistic Conditional Reasoning by Taking the Example of Maximum Entropy Reasoning

Many modern artificial intelligence (AI) systems like human-interacting smart devices or expert systems adapt to specific users' information processes but the underlying AI methods commonly lack a theory of mind. Thus, there is a need to better understand human thinking and to integrate the resulting cognitive models into AI methods. By taking the example of maximum entropy reasoning (MaxEnt), we integrate cognitive principles from the cognitive architecture ACT-R into uncertain reasoning based on probabilistic conditionals. Therewith, we combine two powerful and well-established methodologies from probabilistic reasoning (MaxEnt) and cognitive science (ACT-R) and establish a blueprint for cognitive probabilistic reasoning.
Simple Direct Uncertainty Quantification Technique Based on Machine Learning Regression

Epistemic uncertainty quantification provides useful insight into both deep and shallow neural networks' understanding of the relationships between their training distributions and unseen instances and can serve as an estimate of classification confidence. Bayesian-based approaches have been shown to quantify this relationship better than softmax probabilities. Those approaches to uncertainty quantification, however, require multiple Monte-Carlo samplings of a neural network, augmenting the neural network to learn distributions for its weights, or utilizing an ensemble of neural networks. Current research has yielded several techniques that estimate uncertainty deterministically but tend to struggle in independent evaluation using real-world data and tasks compared to stochastic, or variational, techniques such as Bayesian dropout. In this work, we propose a technique that allows Bayesian dropout uncertainty to be estimated using learned regression models. We find that, once trained, this allows dropout uncertainty to be effectively and efficiently predicted.
Tractable Inference for Hybrid Bayesian Networks with NAT-Modeled Dynamic Discretization

Hybrid BNs (HBNs) extend Bayesian networks (BNs) to both discrete and continuous variables.Among inference methods for HBNs, we focus on dynamic discretization (DD) that converts HBN to discrete BN for inference.Complexity of BN inference is exponential on treewidth, which extends to DD for HBNs.We presents a novel framework where HBN is transformed into NAT-modeled BN (NAT: Non-impeding noisy-AND Tree) for tractable inference.A case-study under the framework is presented on sum of continuous variables.We report significant efficiency gain of approximate inference by NAT-modeled DD over alternative methods.
Peningkatan Hasil Belajar dan Pemahaman Siswa dengan Menggunakan Metode Praktek pada Materi Jenis Bumbu Dasar dan Pengembangannya

The learning process for basic spices and their development in basic culinary lessons in class X Catering at SMK N 3 Karang Baru is still poorly understood, so that student activity in class is still lacking. This has an effect on the low score obtained by students, namely 63.57 with a KKM of 75. The steps taken to overcome this are by using suitable and interesting learning methods so that learning outcomes and students' understanding of learning increase. The application of practical learning methods is one of the researchers' efforts to improve student learning outcomes and understanding of student learning. The research was carried out in 2 cycles. Each cycle consists of stages of planning, implementation, observation, and reflection. The research data includes student learning outcomes taken from giving test questions at the end of the cycle, on the teacher's ability in learning from observation sheets, and data on student reflection on learning from student responses at the end of the cycle. The indicators of research success are: (1) if 80% of the total number of students are categorized as complete, (2) if the teacher's performance ability is at least in good category, (3) if students are categorized as having high interest/interest in the learning provided. The results showed that the understanding of student learning outcomes increased, namely in the first cycle 70.71 and in the second cycle 95.23, the teacher's performance ability was categorized as very good, and students' interest in the learning provided by the teacher was in the high category, students liked the teacher and practical learning methods.