Reviewerly/exHarmony huggingface dataset:
Youth Perspective of Middle Students on Disaster Management Using the Simulation Method in Increasing Resiliency

Indonesia is a country that is located between two continents and two oceans, where the volcanic mountain paths meet, namely the Pacific Circum and the Mediterranean Circum, is one of the countries that has a large enough disaster potential. But on the other hand, this condition has a logical consequence that Indonesia is a country that has a high level of vulnerability to natural disasters. West Java itself is one of the areas prone to natural disasters. The National Disaster Management Agency (BNPB) stated that there were 8 provinces that were most frequently hit by disasters during the 2016 period, West Java ranked third after Central Java and East Java.Analyze the level of resilience of disaster management before and after being given the Simulation method and knowing the role of high school students in disaster management using the simulation method. The research method used a quantitative analysis design, with a Quasi Experimental research design with Pre and Post-Experimental measuring the resilience of students who received simulation exercises without a control group. Sampling used the Simple Random Sampling technique with the criteria of Grade 10 and Grade 11 students as many as 30 students at SMA Negeri I Parongpong, Lembang, West Badung Regency. The instrument used in the study used the Connor-Davidson Resilience Scale (CD-RISC) questionnaire. The results of the study showed that there were differences in the perceptions of youth in disaster management and the role of senior high school students in resilience before and after the stimulation method was used. The simulation method is more effective in increasing resilience to disaster management.
Fraud Detection of AD Clicks Using Machine Learning Techniques

Although all businesses face the possibility of fraud, those that rely on internet advertising face an especially high risk of click fraud, which may lead to inaccurate click statistics and unnecessary expenditures. The cost per click for advertising channels might skyrocket if enough people click on the ads. Internet advertising is becoming a significant revenue source for many websites. Under this model, advertisers pay the publisher a flat rate for each click-through from the ad to the advertiser's site. Since spending much on Internet advertising requires significant resources, the term "click fraud" refers to an attack tactic in which the perpetrator repeatedly clicks on a single link for the sole purpose of generating illicit revenue. By clicking on a pay-per-click (PPC) ad many times using a script, fraudsters may trick online advertisers into paying for clicks that never happened. We may use a variety of methods to identify click fraud anytime a human or computer program clicks on a particular link, and then use the click-through rate to ascertain whether the clicker is legitimate. This work provides a machine-learning strategy for predicting user click fraud, which will enable us to distinguish between fraudulent and legitimate clicks and, therefore, identify fraudulent users from legitimate ones. We have used KNN, SVC, and Random Forest models for this purpose.
Cloud ERP Customization using Serverless Runtime

With the advent of cloud computing, it has been proved to be quite useful technology for development and delivery of ERP software.There is often need to customize an ERP software to fit the business process variation of an organization.Many research studies published during 2013 to 2022 acknowledges that deep customization of Cloud ERP System continue to be major challenge especially with public cloud-based edition.There is lack of further study to use server-less architecture to address deep customization needs.This study will present use of open FaaS to call function's client specific implementation via API gateway so to provide deep customization capability in ERPsoftware.This is supported by a proof of concept with reference application of pricing element determination.
Can “Smart Homework” Achieve the Goal of Chinese “Double Reduction” Policy to Reduce Burden and Improve Quality?—The Positive and Negative Effects of “Smart Homework” on Students

The application of information technology provides technical support for achieving the requirements of reducing burden and improving quality in the Chinese “Double Reduction” Policy. Based on the analysis of the mechanism and path of “Smart Homework” (an educational tool that applies artificial intelligence technology) to reduce the burden and improve the quality of Chinese Jiangxi Province by using the literature, this paper investigates 78 counties and cities of this province and finds that this tool can reduce the burden of primary and secondary school students’ homework, improve the completion of homework, reduce the willingness to participate in after-school tutoring, and improve the self-efficacy and learning investment, so as to achieve the goal of the Chinese “Double Reduction” Policy, but at the same time, the lack of convenience in using intelligent products has caused psychological anxiety for a small number of students. The psychological mechanism of reducing burden and improving quality is in line with the principle revealed by the Yerkes–Dodson law; that is, as learning anxiety decreases, the impact of psychological stress on learning efficiency increases. The appropriate psychological stress enhanced the impact of psychological pressure on learning efficacy and engagement, and improved learning efficiency. The article believes that, first, based on the principle of a three-layer structure of homework burden, the use of “Smart Homework” achieves the reduction of homework burden from three aspects: surface layer, inner layer, and core layer. Second, “Smart Homework” reduces the willingness to participate in extracurricular tutoring and, to some extent, reduces the burden of extracurricular tutoring. Third, “Smart Homework” can help students better complete homework and improve learning efficiency.
Using Active Learning to Develop the Problem- Solving Ability of Chinese College Students Majoring in Physical Education

The aim of this study was to undertake research on the building of an active learning physical course that can improve the problem-solving ability of college students majoring in physical education. The study applied a quasi-experimental design, and the participants were 60 Chinese college students. The experimental class consisted of 30 students, who were subjected to active learning methods for 8 weeks, totaling 32 class hours, and the control class without intervention consisted of the other 30 students. The Problem Solving Inventory was applied to the pre- and post-tests. The result showed that problem-solving ability of college students majoring in physical education was significantly improved in the experimental class after the treatment.
Marathi Text Summarization using Extractive Technique

Multilingualism has played a key role in India, where people speak and understand more than one language. Marathi, as one of the official languages inMaharashtra state, is often used in sources such as newspapers or blogs. However, manually summarizing bulky Marathi paragraphs or texts for easy comprehension can be challenging. To address this, text summarization becomes essential to make large documents easily readable and understandable. This research article focuses on single document text summarization using the Natural Language Processing (NLP) approach, a subfield of Artificial Intelligence. Automatic text summarization is employed to extract relevant information in a concise manner. Information Extraction is particularly useful when summarizing documents consisting of multiple sentences into three or four sentences. While extensive research has been conducted on English Text Summarization, the field of Marathi document summarization remains largely unexplored. This research paper explores extractive text summarization techniques specifically for Marathi documents, utilizing the LexRank algorithm along with Genism, a graph-based technique, to generate informative summaries within word limit constraints. The experiment was conducted on the IndicNLP Marathi news article dataset, resulting in 78% precision, 72% recall, and 75% F-measure using the frequency-based method, and 78% precision, 78% recall, and 78% F-measure using the Lex Rank algorithm.
Evaluating the power of a recent method for comparing two circular distributions: an alternative to the Watson U2 test

Abstract Some data are collected on circular (rather than linear) scales. Often researchers are interested in comparing two samples of such circular data to test the hypothesis that they came from the same underlying population. Recently, we compared 18 statistical approaches to testing such a hypothesis, and recommended two as particularly effective. A very recent publication introduced a novel statistical approach that was claimed to outperform the methods that we had indicated were highest performing. However, the evidence base for this claim was limited. Here we perform simulation studies to offer a more detailed comparison of the new “Angular Randomisation Test” (ART) with existing tests. We expand previous evaluations in two ways: exploring small and medium sized samples, and exploring a range of different shapes for the underlying distribution(s). We find that the ART controls type I error rates at the nominal level. The ART had greater power than established methods in detecting a difference in underlying distribution caused by a shift around the circle. Its performance advantage in this case was strongest when samples where small and unbalanced in size. When the difference between underlying unimodal distributions was in shape rather than central tendency, then the ART was at least as good (and sometimes considerably more powerful) than the established methods, except when distributions samples were small and uneven in size, and the smaller sample came from a more concentrated underlying distribution. In such cases its power could be markedly inferior to established alternatives. The ART was also inferior to alternatives in dealing with axially distributed data. We conclude that under widely-encountered circumstances the ART test can be recommended for its simplicity of implementation, but researchers should be aware of situations where it cannot be recommended.
Monitoring and Automation System of Swiftlet House Using Internet Of Things (IoT) Based

This research aims to make a tool in the form of a technological engineering system that is integrated with its operation so that swiftlet farmers can use it. This research is expected to produce a more effective and efficient technology than partial tools and has not yet answered the needs of swallow farmers. The stages in this study used flowcharts consisting of literature studies, program design, making system blocks, system integration, tool testing, and analysis of the results. The system design consists of determining tools and materials and making a block diagram of the work system of the tool with the ESP32 microcontroller. In system settings, it is divided into several system blocks: sound control system block, temperature and humidity control, window opening and closing control, lighting control and streaming video monitoring in swiftlet houses. Based on the results of the study, it was obtained that monitoring and automation system tools for swallow houses use IoT-based Esp32. This tool can automatically regulate and automate sound, temperature, humidity, lighting, and windows in swiftlet houses and can be monitored remotely.
A Robust Joint-Training Graph Neural Networks Model for Event Detection with Symmetry and Asymmetry Noisylabels

Events are the core element of information in descriptive corpus. Although many progresses have beenmade in Event Detection (ED), it is still a challenge in Natural Language Processing (NLP) to detect event information from data with unavoidable noisy labels. A robust Joint-training Graph ConvolutionNetworks (JT-GCN) model is proposed to meet the challenge of ED tasks with noisy labels in this paper. Specifically, we first employ two Graph Convolution Networks with Edge Enhancement (EE-GCN) tomake predictions simultaneously. A joint loss combining the detection loss and the contrast loss fromtwonetworks is then calculated for training. Meanwhile, a small-loss selection mechanism is introduced tomitigate the impact of mislabeled samples in networks training process. These two networks gradually reach an agreement on the ED tasks as joint-training progresses. Corrupted data with label noise are generated from the benchmark dataset ACE2005. Experiments on ED tasks has been conducted with bothsymmetry and asymmetry label noise on dif erent level. The experimental results show that the proposedmodel is robust to the impact of label noise and superior to the state-of-the-art models for EDtasks.
Spread and Rainbow Option Pricing Based on ARIMA

Under the regional turbulence, the overall financial market environment is not optimistic.Financial assets are facing risk of decline, especially the index assets which reflect the market direction.Constructing multi-assets option portfolio is an efficient way of risk management and gain profit.This article focuses on the Black-Scholes-Merton(B-S-M) option pricing method of rainbow option and spread option and fits the ARIMA price prediction model.The data for one year is collected as the training set for ARIMA model and the historical volatility estimation.The B-S-M model takes historical and future forecast data into consideration, and find a good estimation for parameters.The Monte Carlo method is utilized for option pricing which contains the measure transform form risk-neutral measure to reality measure.ARIMA models fit subseries well with overall residuals evaluated as normal and the significant model parameters.According to the analysis, investors can forecast the market trend accurately and find the best portfolio.These results offer a guideline for the portfolio design with large net price gap in futures market.In addition, it also provides a way of the risk management under the high volatility condition and region instability nowadays.
DEVELOPMENT OF FLEXIBILITY COMPETENCE IS THE MAIN FORM OF PROFESSIONAL DEVELOPMENT OF A TEACHER OF EDUCATION

In the article the quality of education is the priority, the intellectual potential of personnel, the level of formation of the characteristics of professional responsibility, It is reported that it is difficult for a child to adapt to society without education, that a developing person is necessary for the formation of social attitudes, values, and the position of active activity in society.
Economic Data Analysis Based on Data Mining

With the development of equipment technology, the cost of equipment development is rising too.How to reasonably plan, manage and use the cost of equipment is the concern of equipment management departments and researchers.Data mining technology can find the necessary information from the equipment economic data, which is of great significance to improve the cost-effectiveness.In view of the difficulty in estimating the funds in the project demonstration stage, this paper first uses the correlation analysis method to study the correlation between the normalized eight cost data and the total cost, removes the cost items with weak correlation, and only retains the design person year ratio, material person year ratio, test person year ratio and the total cost person year ratio as the later research object.Next, through cluster analysis, it is found that the aggregation degree of material man year ratio and total cost man year ratio is the best, and the relationship is approximately linear.Then, the 1~5 order regression model is established by using the least square method.Finally, the regression model is verified based on the project data.
Digital Accounting Systems (DIS): Concepts, Components and Roles in Business

Today, with the continuous development of science and technology, the most advanced technology has been applied to the field of human activities, from production and business to monitoring and management. Technology helps people manage work more efficiently and quickly, while providing timely and reliable information. Accounting is a leading important part of the economic and financial management system, playing a great role in controlling, managing and operating the production and business activities of enterprises, especially in the financial sector. current period. That requires businesses to apply technology to the organization that performs accounting work with the aim of creating an effective accounting information system. Such system must be reasonable, rigorous, provide truthful, timely and reliable information with the most advanced processing techniques. That not only contributes to increasing competitiveness but also improves operational efficiency in enterprises. This is an inevitable development trend and is consistent with the renovation process, especially in the current period of economic integration. In this article, Research on the concept of a digital accounting information system and a plan to develop an accounting information system in an enterprise.
Using PRAAT in Teaching the Monophthongs to the EFL Students in Indonesia

&lt;p&gt;PRAAT can easily and rapidly improve the students’ ability in pronouncing monophthongs in phonetics class. The effectiveness of this software can help the students acquire quality monophthongs sounds. Furthermore, this software could reduce the problem of students learning sounds of monophthongs accurately such as the accuracy of F1 and F2 that is contained in monophthongs. It provided many programs on how to record, analyze, measure, and save in the wave file. This research aimed to investigate to what extent this software affects teaching monophthongs sounds in phonetics class for students. This research was conducted with 40 samples of students. They divided the class into 20 students for the control group and another 20 students for the experimental group. This quasi-experimental was to determine the best treatment before and after giving the treatment by using CALL for the experimental group and NON-CALL for the control group. Before using the software, the students were given the pre-test . Finally, they sat for post- test in the last meeting. The result was exposed through analysis of a t-test. It showed a significant difference in learning through PRAAT software (p&amp;lt;.05). In addition to that, teaching vowels sounds proved to be more successful using PRAAT than the traditional method.&lt;/p&gt;
The Analysis of the Positive Patterns in Education

Each individual is responsible for his or her own actions. Parents should guide their children to be responsible for their own behavior, but also take responsibility for their children actively. Through positive family education, parents engage in growth and reflection. With family education like this, parents get the result twice with half the effort. Parents need to actively seek out and use the positive patterns in the guide of family education. Parents need to find the root of the problem in family education and guide their children to grow up positively and healthily. The positive guide of family education can encourage more parents to take family education seriously and effectively.
Supplementation of synthetic object replicas for increasing precision of microrobot trajectory keypoints

Artificial neural networks are becoming more popular with the development of artificial intelligence. These networks require large amounts of data to function effectively, especially in the field of computer vision. The quality of an object detector is primarily determined by its architecture, but the quality of the data it uses is also important. In this study, we explore the use of novel data set enhancement technique to improve the performance of the YOLOv5 object detector. Overall, we investigate three methods: first, a novel approach using synthetic object replicas to augment the existing real data set without changing the size of the data set; second - rotation augmentation data set propagating technique and their symbiosis, third, only one required class is supplemented. The solution proposed in this article improves the data set with a help of supplementation and augmentation. Lower the influence of the imbalanced data sets by data supplementation with synthetic yeast cell replicas. We also determine the average supplementation values for the data set to determine how many percent of the data set is most effective for the supplementation.
Tweets on migrants during the election campaigns in the Community of Madrid

In this paper we present research into narratives on immigrants and immigration, to identify cases of hate speech on the part of political parties against immigrants on Twitter during the 2019 and 2021 electoral campaigns in the Community of Madrid. Using Critical Discourse Analysis, the results confirm the exponential increase by all parties in discussion on the issue of immigration and that the political agenda and public discourse is increasingly framed by hate speech towards unaccompanied minors and undocumented migrants.
فعالية الطريقة الصوتية لتعليم مهارة القراءة للتلاميذ في المدرسة محمدية 9 الإبتدائية مالانج

Comprehension and mastery of phonology contributes greatly to reading skill. With good understanding and eloquent pronunciation, a person can establish what he is saying to the addressee. If phonology does this skill with eloquence, it will affect the listener, because the information will be obtained by its clear transmission. The task area is to understand phonology influencing reading skill. Reading skill cannot be fully mastered if science understands the sounds a little. As well as learning science, sounds are very important to learn in the Arabic language. Research Objectives In this study, the research is to find out the effectiveness of the phonological method in the reading skill of pupils in the primary school Muhammadiyah 9 Malang. In this study, the researcher used the experimental method with the quantitative approach, and the type of this research is real experimental. It includes two groups, the experimental group and the control group. Research tools including observation, test, and questionnaire. The data collection method is Statistic Descriptif and SPSS. Data analysis using a t-test. The result of this research study is that the use of phonetic method in teaching reading skill in Muhammadiyah 9 Elementary School Malang is effective. Evidence that the statistical result = 15.14 is greater than the result of the significant estimate 5% = 1.67, meaning that Ha is acceptable or that the hypotheses of this research are acceptable.
Challenges and Opportunities in Smart Contract Development on the Ethereum Virtual Machine: A Systematic Literature Review

The development of smart contracts presents significant challenges compared to traditional software development, such as the immutability of the blockchain. This paper presents a systematic literature review (SLR) that aims to understand the limitations and challenges faced by smart contract developers on the Ethereum Virtual Machine (EVM). Among the main challenges identified are language restrictions, infrastructure limitations, and the lack of sufficient information on interface patterns and implementation specifications. Existing proposals are difficult to understand, with complex formal verifications that require advanced technical knowledge. Additionally, the scarcity of accessible educational resources for training new smart contract developers represents a major challenge to be overcome. In this regard, the SLR seeks to identify opportunities for improvement and innovation in the field, as well as validation and evaluation strategies to make the smart contract development process more efficient and secure.