Reviewerly/exHarmony huggingface dataset:
Perpustakaan Cinet: Wadah Literasi yang Dikenalkan Sejak Dini di Era Digital

Today's reading culture is very rarely found because of the times that continue to this day, let alone entering the era of globalization in which there are various kinds of digitization which in general all work can be done easily and quickly. The program, which was created in Cinet Hamlet, Bulurejo Village, Gondangrejo District, Karanganyar Regency, Central Java Province, is related to restoring reading interest during this very massive digitalization era, namely the Cinet Library. The method that devotees use is environmental observation. From the results of these observations, the devotees have not found one from all sides and corners of the literacy place in Cinet Hamlet, namely the library. The purpose of this service is to make children return to reading books even though the digitalization era has entered their age, which are still in elementary school.
Morphometric Variations of Chalcorana chalconota (Schlegel, 1837) in Four Populations in Jatimulyo Kulon Progo

Jatimulyo is an ecotourism area consisting of several areas, each of which has a different height and abiotic factors. This can affect the morphometric character of frogs including Chalcorana chalconota. Research on specific morphometric variations of Chalcorana chalconota in Jatimulyo ecotourism has never been conducted. The purpose of this study was to analyze the distinguishing character of four frog populations as well as analyze the morphometric variation of the Chalcorana chalconota frog in Jatimulyo ecotourism. The research samples were taken using the visual encounter survey method and direct collection in the field in all four populations. Morphometric measurements use 32 characters. The measurement data obtained were analyzed using the Kruskall-Wallis test followed by UPGMA to see dissimilarity using the MVSP 3.1 program. The results showed that of the 32 characters observed and analyzed, there were nine characters that had a p&lt;0.05 value which means it is significant to distinguish the four populations. The nine characters are (HW), (TD), (MFE), (MBE), (HAL), (LAL), (FOL), (IN), (MTL). LK, DT, JMMD, JMMB, JIN, PMD, PBR, PTJ4, PTM. The frog Chalcorana chalconota population of Kembang Soka has a high morphometric similarity with the population of Kedung Pedut. The Mudal River Population and the Bull Kedung Population have a considerable morphometric similarity with the Soka Flower and Pedut Flower Populations. This study can be concluded that the morphometric variation of Chalcorana chalconota in Jatimulyo ecotourism is influenced by altitude factors.
Features of Monoclausality and Polyclausality in Japanese Benefactives: A Corpus Study

Typological status of complex converb constructions in Japanese is not currently well-defined. Japanese language researchers have no common opinion regarding their syntactic and functional unity. In this article we use corpus data to study such constructions with auxiliary verbs yaru, ageru, kureru, kudasaru, morau and itadaku and reveal features of monoclausality and biclausality with them. In the first part of the article, we overview the preexisting research on this topic, and then we apply the tests of morphological and syntactic independency that can be validated using corpus data. To test morphological independency, we check if focus particles such as mo ‘too’ can be placed between the parts of benefactive construction. For syntactic independency we use such tests as replacing a main verb with soo suru ‘to do so’ and checking the implementation of locality condition for shika ‘except’ when the negation marker is added to a main verb or to an auxiliary. According to our data, parts of all the six types of Japanese benefactive constructions demonstrate morphological independency (except for contracted colloquial forms). As for their syntactic properties, benefactives demonstrate both monoclausality and biclausality features. However, the parallel with direct and indirect passive constructions that exists in preceding research does not find endorsement in our data.
The Students’ Perception of Apprehending, Synthesizing, Analyzing, and Responding (ASAR) Speaking Process-Based Instructional Materials

This study was based on the students’ problems regarding English teaching, especially English materials of speaking skills. The students have poor English speaking ability because the lecturer did not have instructional materials related to their department. The media and method was not attractive and the instructional facilities were not enough to facilitate a good learning process. The objective of the research was to develop Englishspeaking materials by integrating Apprehending, Synthesizing, Analyzing, and Responding (ASAR) based material. The sample of the study was Biological students of Muhammadiyah University of Parepare, Indonesia. The method used in this research was developmental research which attempts to develop English-speaking materials based on the modified ADDIE approach (Analyze, Design, and Development). The result of the study was an authentic English-speaking materials for Biological students of Muhammadiyah University of Parepare. The instructional materials focused on input, process, and output. After the materials were given the student’s perception changed into very good value. It means that English-speaking instructions for the Biology department have good quality in the form of course map, lesson plan, lecturer's manual, topic, video clips, materials, students' worksheets, learning activities, and assessment.
The Influence of Using Gist Strategy Towards Students’ Reading Comprehension at The Eighth Grade Junior High School

Online learning chosen to be applied in almost all of schools in Indonesia, but now in condition many school in Indonesia has applied offline learning, this also applied to SMPN 2 Way Jepara East Lampung. GIST strategy to discover important information and idea in a text, and they could schematize descriptive texts in their own language to make them easier to understand. The aims this study was to determine students reading comprehension. This research was conducted with a quantitative method. This subject of this study were 63 students were sampled from 2 courses, VIII1 and VIII 2. The data was collected by using a multiple choice test as an instrument using pre-test and post-test. The independent t-test result was 0.020 with a significance of 0.05, according to the data analysis. The score of t-observed was higher than t-crucial (0.05) in the analysis, so H0 was rejected. It means that the GIST strategy has an influence on students' reading comprehension, especially in descriptive text. So, on there is an influence of employing the GIST strategy on students’ reading comprehension of descriptive text.
Exploring Linguistic Acceptability in Swedish Learners’ Language

We present our initial experiments on binary classification of sentences into linguistically correct versus incorrect ones in Swedish using the DaLAJ dataset (Volodina et al., 2021a). The nature of the task is bordering on linguistic acceptability judgments, on the one hand, and on grammatical error detection task, on the other. The experiments include models trained with different input features and on different variations of the training, validation, and test splits. We also analyze the results focusing on different error types and errors made on different proficiency levels. Apart from insights into which features and approaches work well for this task, we present first benchmark results on this dataset. The implementation is based on a bidirectional LSTM network and pretrained FastText embeddings, BERT embeddings, own word and character embeddings, as well as part-of-speech tags and dependency labels as input features. The best model used BERT embeddings and a training and validation set enriched with additional correct sentences. It reached an accuracy of 73% on one of three test sets used in the evaluation. These promising results illustrate that the data and format of DaLAJ make a valuable new resource for research in acceptability judgements in Swedish.
Towards Trustworthy DeFi Oracles: Past,Present and Future

With the rapid development of blockchain technology in recent years, all kinds of blockchain-based applications have emerged. Among them, the decentralized finance (DeFi) is one of the most successful applications, which is regarded as the future of finance. The great success of DeFi relies on the real-world data which is not directly available on the blockchain. Besides, due to the deterministic nature of blockchain,the blockchain cannot directly obtain in-deterministic data from the outside world (off-chain). Thus, oracles have appeared as a viable solution to feed off-chain data to blockchain applications. In this paper, we carryout a comprehensive study on oracles, especially on DeFi oracles. We first briefly introduce the application scenarios of DeFi oracles, and then we talk about the past of DeFi oracles by categorizing them into several types based on their design features. After that, we introduce five popular DeFi oracles currently in use(such as Chainlink and Band Protocol), with the focus on their system architecture, data validation process,and their incentive mechanisms. We compare these present DeFi oracles from their data trustworthiness,data source trustworthiness and their overall trust models. Finally, we propose a set of metrics for designing trustworthiness DeFi oracles, and propose a potential trust architecture and a few promising techniques for building trustworthiness oracles.
Programmatic Reward Design by Example

Reward design is a fundamental problem in reinforcement learning (RL). A misspecified or poorly designed reward can result in low sample efficiency and undesired behaviors. In this paper, we propose the idea of programmatic reward design, i.e. using programs to specify the reward functions in RL environments. Programs allow human engineers to express sub-goals and complex task scenarios in a structured and interpretable way. The challenge of programmatic reward design, however, is that while humans can provide the high-level structures, properly setting the low-level details, such as the right amount of reward for a specific sub-task, remains difficult. A major contribution of this paper is a probabilistic framework that can infer the best candidate programmatic reward function from expert demonstrations. Inspired by recent generative-adversarial approaches, our framework searches for the most likely programmatic reward function under which the optimally generated trajectories cannot be differentiated from the demonstrated trajectories. Experimental results show that programmatic reward functionslearned using this framework can significantly outperform those learned using existing reward learning algo-rithms, and enable RL agents to achieve state-of-the-artperformance on highly complex tasks.
Recognising diversity of data management approaches towards lifecycle costing through personas

Prompted by the increased interest in and strengthened incentives to apply lifecycle costing (LCC) in the Danish AECO industry, this study aims to improve our understanding of how practitioners may apply new technologies and tools in their design practices. By adopting user-centred design methods, this study explores the diversity of current and potential LCC users as users of technology in general with regard to their characteristics, aspirations and work processes towards data management. The research is based on a single case study analysis of a Danish architectural firm. Data are gathered through mixed methods, including quantitative surveys and qualitative observations and interviews. The findings reveal three user personas: the clip-boarder persona, who manually copies and pastes data from one application to another in order to perform calculations; the spreadsheet expert persona, who prefers to work with spreadsheet-based tools for importing and exporting data between tools; the programmer persona, who uses programming language for integrating data from one application to another. This research provides novel insights on users of technology that can advance integration of LCC in design practices and improve design of more useful adequate LCC tools.
Is Political Instability an Obstacle to Economic growth? Evidence from South Asia

The nexus existing between the growth rate of countries and political instability has been subjected to increasing interest among academic scholars and policymakers in different contexts all around the globe. The current study examined the relationship between political instability and economic growth in both short and long-run, employing the Panel Auto Regressive Distributed Lag (PARDL) model. Through the efforts taken via the study to redefine the political instability and growth nexus in South Asia, it could be stated that despite the insignificant impact of political instability on economic growth in the short run, countries gain the capability in elevating the growth level by maintaining stable political regimes in the long run. The results suggested that there is an overall negative and also a significant linkage between political instability and the long-run growth rate. The holistic analysis highlighted that regulatory quality and civil liberties needed to be well ensured to attain economic growth in the long run as they showed a significant positive relationship with the growth of the South Asian region. The short-run analysis of the variables depicted that there is no strong linkage between the growth and instabilities in the political arena, as the majority of the proxies of political instability exhibited an insignificant relationship with economic growth except regulatory quality. &#x0D; Keywords: Economic growth; PARDL model; Political Instability; South Asia
WhatsApp Chat Sentiment Analyzer

Abstract: While being a widely used method of communication in today’s times, WhatsApp is also headed towards being the platform where billions of people share their personal thoughts, emotions and sentiments, most of which is found in the group chats of this application. WhatsApp chat analyzer is a web application which was developed to provide analysis of WhatsApp group chats. Python libraries like matplotlib, re, seaborn, streamlit, pandas and some conceptual knowledge of NLTK are in use here. This is the combination of NLP, NLTK and machine learning. This system makes use of a WhatsApp chat file that is exported from the group chat or an individual user and then analyzes it to give us the analysis.
Computer Science and High Dimensional Data Modelling

Abstract: The need to grasp large database structures is a very important issue in biological and life science. This review paper is aimed toward quantitative medical researchers searching for guidance in modeling large numbers of variables in medical research, how this relates to straightforward linear models and therefore the geometry that underlies their analysis. Issues reviewed include LASSO-related approaches, principal-component based analysis, and problems with model stability and interpretation. Model misspecification issues associated with potential nonlinearities are examined, as is that the Bayesian perspective on these issues.
Comparison of Two Three-dimensional Visualization Systems: A Consecutive Series and Descriptive Analysis of 296 Cases

Other SectionsAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgmentsConflicts of InterestAuthor ContributionTableReference
Academic Presentation in PechaKucha Format is a Professional Component of Bilingual Students in an Online Communication Environment

The article is devoted to the analysis of interactive technologies in Russian as a foreign language classes in the conditions of network communication, which expanded the field of traditional practices and became a new educational environment. This article considers the application of Pechakucha format within the framework of teaching Russian as a foreign language. The application of such modern educational technologies is an effective and appropriate form of organizing the educational process. The relevance of the topic of the study is due to the rapidly developing information technologies that allow successful training of bilingual students in academic skills and contribute to the training of an autonomous student. The following methods were used in the work: general scientific method, comparative analysis method, descriptive method, including the method of observation, interpretation, generalization, as well as experimental methods. The article attempts to show the results of applying the academic presentation in the PechaKucha format as a special format of translating new scientific knowledge on the basis of our own experience. The presented format was used when preparing students for a scientific and practical conference.
Emergency Application for Emergency Services in Critical Condition

Abstract: Emergency calling is fundamental and critical for devices because they must work for Android users while satisfying various carrier and regulatory requirements all over the world. Emergencies can happen anywhere and at any time. The very nature of an emergency is unpredictable and can change in scope and impact. Being prepared and planning ahead is critical to protecting lives, the environment, and property. To overcome problems while facing emergency situations we need a simple and easy application. For this, we create an application that has automatic call and location-sharing services in an emergency situation. This will help us to share the location with our family and nearby hospitals or OPDs and also be useful to the automatic message sending &amp; SOS. For this, we select some famous emergency applications and study them. But some applications are region-based applications And every application has different features. Due to this, it is difficult to use an emergency application in emergency situations. To overcome this problem we develop an application that is not region- based, consists of all features, and is easy to use in any condition.
JARUA: Joint Embedding of Attributes and Relations for User Alignment across Social Networks

User alignment (UA), a central issue for social network analysis, aims to recognize the same natural persons across different social networks. Existing studies mainly focus on the positive effects of incorporating user attributes and network structure on UA. However, there have been few in-depth studies into the existing challenges for the joint integration of different types of text attributes, the imbalance between user attributes and network structure, and the utilization of massive unidentified users. To this end, this paper presents a high-accuracy embedding model named Joint embedding of Attributes and Relations for User Alignment (JARUA), to tackle the UA problem. First, a mechanism that can automatically identify the granularity of user attributes is introduced for handling multi-type user attributes. Second, a graph attention network is employed to extract the structural features and is integrated with user attributes features. Finally, an iterative training algorithm with quality filters is introduced to bootstrap the model performances. We evaluate JARUA on two real-world data sets. Experimental results demonstrate the superiority of the proposed method over several state-of-the-art approaches.
An approach of cervical cancer diagnosis using class weighting and oversampling with Keras

Globally, cervical cancer caused 604,127 new cases and 341,831 deaths in 2020, according to the global cancer observatory. In addition, the number of cervical cancer patients who have no symptoms has grown recently. Therefore, giving patients early notice of the possibility of cervical cancer is a useful task since it would enable them to have a clear understanding of their health state. The use of artificial intelligence (AI), particularly in machine learning, in this work is continually uncovering cervical cancer. With the help of a logit model and a new deep learning technique, we hope to identify cervical cancer using patient-provided data. For better outcomes, we employ Keras deep learning and its technique, which includes class weighting and oversampling. In comparison to the actual diagnostic result, the experimental result with model accuracy is 94.18%, and it also demonstrates a successful logit model cervical cancer prediction.
Supplementary material to "Importance of multiple sources of iron for the upper ocean biogeochemistry over the northern Indian Ocean"

Ocean (STIO) respectively.These regions are used in Figures S2,S3, S6 and S7.
The Relationship between the Digital Literacy Levels of Turkish Language Teacher Candidates and Their Attitudes Towards Digital Writing

The purpose of this study is to explore the levels of digital literacy among Turkish teacher candidates as well as their attitudes about digital writing, and to investigate the relationship between these variables. The survey model is used in this study using a quantitative research approach. The sample of the research consists of 556 Turkish language teacher candidates studying at 18 different public universities in Turkey in the fall of the 2021-2022 academic years. In this study, personal information form, Digital Literacy Scale, and Attitude Scale for Digital Writing (DWS) are employed as data collection tools. The data are analyzed using correlation and regression analysis test. The research findings show that the digital literacy levels of Turkish language teacher candidates and their attitudes towards digital writing are moderate. These findings disclose a necessity to improve both the digital literacy of Turkish teacher candidates and their attitudes towards digital writing. Additionally, the results generally reveal a favorable and significant correlation between the participants’ attitudes regarding digital writing and their degrees of digital literacy. The findings of the present study are examined in the light of the literature, and different recommendations are developed.
A Practical Prediction Methods of Major Earthquakes Using High-frequency Tremor Events

The earthquake prediction, one of the most efficient methods has been tried to develop based on modern scientific method this half century using seismic activity, crustal deformation, chemical anomalies without practical results except only two rare cases with the result of general pessimistic evaluation. The seismic activity has been the field of the most often approached in comparison with other phenomena. Especially foreshocks are investigated enough to provide many useful results but critical defect is unstable occurrence. On the other hands important progress is attained in the laboratory investigation of process of nucleation providing important results. However, those result cannot be confirmed by field observation just before occurrence of major earthquakes. Here we make a special seismic catalog of high frequency tremors deduced anew from continuous seismic data of just before major earthquakes using the extensive network, High-net of Japan. Analyses of catalog for three major and one a little bit smaller earthquakes show that there are three successive precursory phenomena, first at some six weeks, second at some four weeks, and finally immediately before the earthquake. And the three items of prediction, time, location and magnitude can be predicted exactly enough for actual disaster mitigation efforts at each moment of distinguishing of those precursors.