Reviewerly/exHarmony huggingface dataset:
Introduction to the Minitrack on Soft Computing: Theory Innovations and Problem Solving Benefits

The term soft computing is used in reference to a family of preexisting techniques, namely evolutionary computation, fuzzy logic, probabilistic reasoning, neuro-computing, and so on.Taking profit from the main advantages of each individual technique, they can work in a cooperative way to solve lots of complex real-world problems: those for which more conventional methods have not yielded low cost, analytic and complete solutions.Earlier computational approaches could model and precisely analyze only relatively simple systems.However, more complex systems arising in biology, health, economy, digital world, and similar fields, often remained intractable to conventional mathematical and analytical methods.Therefore, the advances in soft computing techniques play an important role in analyzing and modeling more complex systems.Soft computing deals with imprecision, uncertainty, partial truth, and approximation to achieve computability, robustness, and low solution cost, which can better deal with largescale, fast, and unstructured changes that occur as part of the digital world.This minitrack aims to attract researchers with an interest in the research area described above.Specifically, not only contributions on theoretical innovations are welcome, but also those describing different problem-solving benefits by using soft computing-based methodologies in the fields of digital world, digital coaching, digital health, digital economy, and cognitive computing.This minitrack is interested in contributions in which the applied/defined methodologies used are either analysis-or systems-oriented.They may have an experimental or empirical focus.Innovative studies are favored, which combine innovative theoretical results with a careful empirical verification, or good empirical problem solving, planning or decision making with innovative theory building.A common denominator for all studies is the building and use of soft computing-based models.The first paper of this minitrack, "A Rule-Learning Approach for Detecting Faults in Highly Configurable Software Systems from Uniform Random Samples", proposes to address the challenge
Parents and Stakeholders’ Perspectives on Early ‎Reading Intervention Implemented as a Curriculum for ‎Children with Learning Disability

Stakeholder and parent preceptive have an influence on children’s educational performance of early reading stages. The purpose of this study was to understand stakeholders’ perspectives of early reading skills as a curriculum for early readers with learning disabilities. This study used a quantitative method to identify perspectives of stakeholders and parents. Data were collected from 25 public elementary in the metropolitan area of Hail City. Data were analyzed with Exploratory Factor Analysis (EFA), and Multivariate Analysis of Variance (MANOVA) to investigate effects and interactions between variables. The results indicated that 93% of parents and stakeholders strongly agreed on the importance of reading skills as follows: phonological awareness, phonics, and fluency. Also, participants’ role had a significant impact on the variables of perspective while age of participants had non-significant impact. Also, educational levels of participants had no significant affect and impact on the perspective. But, when grouped two variables, participants’ role by Age interaction had a significant effect on the combined dependent variables. Also, participants’ role by education level interaction had significant impact on participant’s perspective. Participants’ role’s by age by educational level interaction had significant impact on the perspective.
THE ROLE OF POLITICAL AND INSTITUTIONAL FACTORS ON ECONOMIC FREEDOM: EMPIRICAL EVIDENCE FROM PMG ARDL MODEL ESTIMATION

This study focuses on investigating the political and institutional factors that impact economic freedom. The factors addressed for the study are those that have resulted in disputed outcomes in prior works— but have not been evaluated holistically. Using annual data collected from 2003 to 2017, a panel ARDL technique was performed for 17 nations to examine both the short-run and long-run impact of political and institutional factors. The results of the study suggest that government effectiveness and political stability have a favorable impact on economic freedom, but government size is not. Furthermore, the study shows that corruption has a detrimental impact on economic freedom. The most likely answer is that corruption is not grease for the economic system’s wheels. Surprisingly, the findings suggest that democracy has a negative influence on economic freedom. Hence, as a policy implication, there is a necessity to improve institutions’ effectiveness, reduce government size and provide political stability to construct economic freedom on economies.
Identifying Chemical Species in a Plasma Using a Neural Network

This paper addresses the problem of identifying the chemical species present in a plasma using optical emission spectra. Two neural networks are initially explored, a multilayer perceptron and a linear associative memory which is trained using the Penrose pseudoinverse matrix. However, examination of the spectra leads to a proposal of a more appropriate architecture in which individual neurons are trained on individual species.
Do Tourist Attraction Objects Implement Health Protocols? Analysis of Tourist Attraction Object in East Java Province Using Google Maps Review

The COVID-19 pandemic has impacted the tourism sector, particularly the Tourist Attraction Object (TAO) in Indonesia. This research aims: to analyse the implementation of health protocols and facility conditions at TAO, to analyse the change in visitor sentiment and rating towards TAO before and during the COVID-19 pandemic, to analyse the close relationship between ratings and reviews of visitor sentiment on TAO, to analyse the possibility of web scraping data to complement tourism data from BPS Statistics Indonesia. Using Google Maps review, this research uses the Multinomial Naïve Bayes (MNB), Term Frequency-Inverse Document Frequency (TF-IDF), pseudo-labelling, and word association methods. The results show that the health protocol has been implemented in TAO of East Java province, the available facilities are good, and there is no change in reviews during the TAO pandemic. The Stuart-Kendall Tau-c value shows a weak relationship in a positive direction between rating and review sentiment. According to Haversine, Jaro Winkler, and Levenshtein, the data calculation indicates that web scraping data can complement tourism data for BPS-Statistics Indonesia.
Using Fuzzy DEMATEL Method to Evaluate the Success Rate of Higher Education Graduation with Excellent Achievement (SGDHE)

The aim of this paper is the evaluation of the success of graduating with distinction in higher education (SGDHE) using the fuzzy DEMATEL method. The observation has been done using cause and effect criteria. 11 cause and 14 effect clusters have been used in this study. The study result of this work shows that all the effects are connected to the given causes and a cause-effect graph has been generated for each connection. This proposed approach is demonstrated with the empirical case of Dire Dawa University students in Dire Dawa Ethiopia.
Classification of Angle of Eye Movement using Electrooculography with LED testing sphere

This paper proposed the classification of the direction and degree of eye movements using EOG signals 2 channels based on discrete cosine transform and power of discrete signal. The EOG signal collect from the electrode placed on the around of eye in vertical and horizontal and using LED testing sphere to guide the EOG signal from the eye muscles. The k-means Clustering used to identify the posture and degree of eye view. The results show that this method can identify four motion gestures: up sight, down sight, left sight and right sight, with an average accuracy of 98.57% and can distinguish the five degrees of view: 5°, 10°, 15°, 20° and 25° with an average accuracy of 91.94%.
Survey on Context Aware Computing and IoT Environment

Context awareness enables the system to collect the information about the environment at any time and act according to it. It makes use of hardware as well as software to collect and analyze the data automatically. The mobile users particularly the smart phone users are mostly focused by context due to it’s pliability and is often used as a part of ubiquitous and wearable computing. The Internet and upcoming technologies combine to transform every object into smart objects. Where this can be applied to user’s activities on the device or to the physical environment in which the device is being use. Here we survey the context awareness from an IoT perspective to help users by automating the task of selecting the sensors according to the problems/tasks at hand.
Blockchain Based Traceability in Supply Chain Using Smart Contracts

Abstract: A supply chain is defined as all the various points involved in the production and distribution of goods, from the stage of supply to the final customer. While agriculture is the most important industry in rural areas and provides livelihoods for 70% of the world's poor, it is also the industry that creates the greatest disconnect between suppliers and retailers. In addition, due to lack of transparency, buyers and customers cannot be sure of the true value of a product or service. The proposed system is an agricultural supply chain model using the Ethereum platform. Smart contracts are implemented in different stages of the supply chain. These contracts guarantee to meet all predefined conditions before conducting transactions ensuring security, reliability and transparency. This can give consumers greater confidence in the products they buy, and it is also an opportunity to reward producers who use good agricultural practices to develop their products. This will ultimately lead to sustainable farming practices and responsible consumption. Keywords: Supply Chain; Ethereum; Smart Contracts; Transparency; Agriculture;
Soils with seasonal climates have highest potential to stabilize carbon by minerals in sub-Saharan Africa

&amp;lt;p&amp;gt;With climate and land use changes, it is becoming increasingly important to understand not only how much carbon is and will be stored in soils, but also how long this C will remain in soils. Estimates of C age can provide useful information about the timescales on which C will respond to such changes. It is generally accepted that the interaction of climate and soil mineralogy have a strong influence on C age. However, our current understanding is primarily based on findings from temperate regions and from small-scale studies. Large knowledge gaps persist in (sub-)tropical regions where soil processes are often understudied.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Here, we use a systematic continental-scale approach to better understand the processes controlling C age on a larger scale in these understudied soils. In total, 510 samples were analyzed for radiocarbon (&amp;amp;#916;&amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;C), consisting of topsoils (0&amp;amp;#8211;20 cm) and subsoils (20&amp;amp;#8211;50 cm) collected from 30 sites across 14 countries. The sampled soils are part of a comprehensive soil survey (AfSIS) for sub-Saharan Africa, for which soil mineralogy (based on X-ray powder diffraction) and soil chemistry were determined.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Soils with the youngest C ages are generally highly weathered, and are characterized by humid climates, high gross primary productivity (GPP), and a dominance of 1:1 clay minerals. In contrast, older C ages are either found in arid regions characterized by low C inputs and low mineral stabilization, or in seasonal climates, where GPP is high but a portion of the C is stabilized by 2:1 clay minerals and poorly crystalline minerals. Cultivation and erosion appear to play a secondary role at this large scale, but widen the range of C ages.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Our data suggest that soils from seasonal climate zones have the most favorable climatic and pedogenic conditions to stabilize and store C. Yet, they are also the most vulnerable climate zones according to future projections for sub-Saharan Africa. Understanding how the stabilizing minerals will react to climate change is key to understanding short and long-term changes in C storage and stabilization.&amp;lt;/p&amp;gt;
Implementation of Early Literacy Activities during Covid-19: A Parents Involvement Analysis

The purpose of this research is to discover how early literacy activities are implemented during Covid-19 pandemic in Pekanbaru, Riau, Indonesia.Since the offline meeting at school has been discontinued, the research sample consists of 400 parents in Pekanbaru who were recruited online.This research method is descriptive in quantitative terms and provides an overview of the performance of literacy activities in Pekanbaru Riau.A questionnaire with A Likert Scale Model was used to collect data.The percentage descriptive technique was used for data analysis with IBM SPSS for Windows Version 23.The results showed that the implementation of literacy activities in Pekanbaru kindergarten was carried out through the parent participation in early childhood literacy development.According to the findings, four indicators that children must have in order to develop early literacy well (vocabulary, narrative, print awareness, and print motivation) are in the high category or more than 65%.Meanwhile, the Letter Knowledge and Phonological Awareness skills are sufficient, at around 60%. Overall, the results of this study are in the high category (64.5%), indicating that literacy activities in Pekanbaru, Riau, Indonesia, have involved parents in the advancement of early childhood literacy skills.
Quantifying soil complexity using Fisher Information of 3d X-ray CT scan images

&amp;lt;p&amp;gt;Degradation of soils due to land use change driven by economic factors represents a major concern in many parts of the world. Important questions regarding soil degradation demand further efforts to better understand the effect of land use change on soil functions. With the advent of 3d Computer Tomography techniques and computing power, new methods are becoming available to address these questions. In this work, we investigate how land use change affects soil structure by using information theory to quantify the complexity of soil 3d X-ray CT soil samples in northeastern Brazil. We implement the Fisher-Shannon method, borrowed from information theory, to quantify the complexity of 14 3d CT soil samples from native Atlantic forest sites, and15 samples from nearby sites converted to sugarcane plantation. The distinction found between the samples from the Atlantic forest and the sugarcane plantation is found to be quite pronounced. The discrimination results at the level of 89.6% accuracy were obtained in terms of Fisher information measure (FIM) alone, and 93% level accuracy was attained considering the complexity in the Fisher Shannon plane (FSP). Atlantic forest samples are found to be generally more complex than those from the sugar plantation. The approach introduced in the current work does not use arbitrary parameters, and it provides a rather precise quantitative FSP complexity measure, that may be seen as a quantifier of soil degradation level.&amp;lt;/p&amp;gt;
JPEG Steganalysis Using the Relations Between DCT Coefficients

Increasing attention to steganalysis and steganography due to the need for secure information transfer is one of the most important concerns of communication. Among the several image formats, JPEG is the most widely used compression method today. As a result, various stenographic systems based on disguising messages in jpeg format have been presented. Consequently, steganalysis of JPEG images is very essential. Recently, using neural networks and deep learning has greatly increased both in spatial and JPEG steganalysis. However, in the field of JPEG steganalysis, most of the existing networks still utilized hand-designed components as well. In the proposed JPEG steganalysis method we investigate the relations of the quantized Discrete Cosine Transform (DCT) coefficients and extract the binary vectors as the input of the neural network employing the relations of mid-frequency coefficients. The experimental results illustrate the acceptable detection rate of the simple presented approach.
The Impacts of Online Games on Students’ English Achievement

Focus of the research is to know the analysis of online games on Students English Achievement. Therefore the researcher formulated a research question what are the impact of online game on students English achievement? This research used qualitative method and analysis of Online Games. The researcher used interview and documentation in collecting the data. The objective of the research showed that To investigate the impact of online games on students achievement The research result is the impact of online games on learning English, based on findings in the field, it can be concluded that students have difficulty finding good learning conditions especially during this pandemic because it requires students to learn Via Online, students experience problems in managing independent learning time, doing assignments so you play more often. In terms of learning English, play online games has a huge influence on students' learning patterns and think patterns, how students write, especially in the sentence write section because English has a difference between pronunciation and write, but along with technological developments that make it easier for students to write.
AusGeochem: an Australian AuScope Geochemistry Network data platform for laboratories and their users

&amp;lt;p&amp;gt;Over the last two years, the Australian AuScope Geochemistry Network (AGN) has developed AusGeochem in collaboration with geoscience-data-solutions company Lithodat Pty Ltd. This open, cloud-based data platform (https://ausgeochem.auscope.org.au) serves as a geo-sample registry, with IGSN minting capability, a geochemical data repository and a data analysis tool. With guidance from experts in the field of geochemistry from a number of Australian institutions, and following international standards and best practices, various sample and geochemistry data models were developed that align with the FAIR data principles. AusGeochem is currently accepting data of SIMS U-Pb as well as of fission track and (U-Th-Sm)/He techniques with LA-ICPS-MS U-Pb and Lu-Hf, &amp;lt;sup&amp;gt;40&amp;lt;/sup&amp;gt;Ar/&amp;lt;sup&amp;gt;39&amp;lt;/sup&amp;gt;Ar data models under development. Special attention is paid to the implementation of streamlined workflows for AGN laboratories to facilitate ease of data upload from analytical sessions. Analytical results can then be shared with users through AusGeochem and where required can be kept fully confidential and under embargo for specified periods of time. Once the analytical data on individual samples are finalized, the data can then be made more widely accessible, and where required can be combined into specific datasets that support publications.&amp;lt;/p&amp;gt;
Real-Time Magnitude Determination and Ground Motion Prediction using Optical Fiber Distributed Acoustic Sensing for Earthquake Early Warning

&amp;lt;p&amp;gt;Distributed Acoustic Sensing (DAS) is ideally suited for the challenges of Earthquake Early Warning (EEW). These distributed measurements allow for robust discrimination between earthquakes and noise, and remote recordings at hard to reach places, such as offshore, close to the hypocenters of most of the largest earthquakes on Earth. In this study, we propose the first application of DAS for EEW. We present a framework for real-time strain-rate to ground accelerations conversion, magnitude estimation and ground shaking prediction. The conversion is applied using the local slant-stack transform, adapted for real-time applications. Since currently, DAS earthquake datasets are limited to low-to-medium magnitudes, an empirical magnitude estimation approach is not feasible. To estimate the magnitude, we derive an Omega-squared-model based theoretical description for acceleration root-mean-squares (rms), a measure that can be calculated in the time-domain. Finally, peak ground motions are predicted via ground motion prediction equation that are derived using the same theoretical model, thus constituting a self-consistent EEW scheme. The method is validated using a composite dataset of earthquakes from different tectonic settings up to a magnitude of 5.7. Being theoretical, the presented approach is readily applicable to any DAS array in any seismic region and allows for continuous updating of magnitude and ground shaking predictions with time. Applying this method to optical fibers deployed near on-land and underwater faults could be decisive in the performance of EEW systems, significantly improving earthquake warning times and allowing for better preparedness for intense shaking.&amp;lt;/p&amp;gt;
UPAYA MENINGKATKAN KETERAMPILAN MENULIS RESENSI DENGAN MODEL STAD MODA DARING PADA PESERTA DIDIK KELAS XI DI SMA N 2 BANTUL

This Classroom Action Research aims to: 1) describe the process of applying the online mode STAD cooperative learning model in the learning process to write reviews, 2) find out the results of learning to write reviews for students in class XI MIPA 2 SMA N 2 Bantul. This Classroom Action Research uses the online mode STAD (Student Team Achievement Division) model using six stages, namely conveying learning objectives, presenting material, forming groups, providing guidance in group learning, evaluation, and providing reinforcement and rewards. The results of this study are 1) the implementation of the STAD model in the act of learning to write reviews for students correctly with the steps of orientation, exploration, re-creation, and posting. 2) There is an increase in the results of student performance on the competence of writing reviews. Improved results can be seen from the results of student performance from cycle I to cycle II. The improvement in cycle II was assisted by the teacher including a review writing format. ABSTRAKPenelitian Tindakan Kelas ini bertujuan untuk: 1) mendeskripsikan proses penerapan model pembelajaran kooperatif STAD moda daring pada proses belajar menulis resensi, 2) mengetahui hasil pembelajaran menulis resensi pada peserta didik kelas XI MIPA 2 SMA N 2 Bantul. Penelitian Tindakan Kelas ini menggunakan model STAD (Student Team Achievement Division) moda daring dengan menggunakan enam tahapan, yaitu menyampaikan tujuan pembelajaran, menyampaikan materi, membentuk kelompok, memberikan bimbingan dalam pembelajaran kelompok, evaluasi, dan memberikan penguatan dan penghargaan. Hasil penelitian ini adalah 1) implemetasi model STAD dalam tindakan pembelajaran menulis resensi pada peserta didik secara tepat dengan langkah-langkah orientasi, eksplorasi, re-kreasi, dan memposting. 2) Adanya peningkatan hasil kinerja peserta didik pada kompetensi menulis resensi. Peningkatan hasil dapat dilihat dari hasil kinerja peserta didik mulai siklus I hingga siklus II. Peningkatan pada siklus II dibantu dengan guru menyertakan format penulisan resensi.