Reviewerly/exHarmony huggingface dataset:
Designing Learning Media Using Augmented Reality for Engineering Mechanics Course

The development of digital technology for education is continuously conducted to successfully integrate digital technology with people's lives. This study aimed to develop an Augmented Reality learning media application for the Engineering Mechanics course, which is considered challenging by some students. Engineering mechanics, a discipline that analyzes structural analysis in compensating for the loads that work on a particular machine in scalar quantities, motion forces, vectors, and moments that require physical structural forms to analyze them, is considered challenging by some students. The Augmented Reality application was created using the prototyping method, which consists of three steps: 1) listening to the customer, 2) building/ revising mock-up, and 3) customer test-drivers mock-up. The AR-based learning media application includes usage instructions, developer info, learning videos, 3D AR object animation simulations, and exercise and discussion menus, which were tested as expected. The results of the black box testing indicate that the Augmented Reality-based engineering mechanics learning media application ran successfully as expected. However, users suggested improving the navigation speed by streamlining page transitions. The application provides an accessible solution for students as an alternative to traditional distance education, offering anytime, anywhere access to learning materials with longer duration.
The Mechanism of Smart Contract Conclusion in the Italy’s and Iran’s Legal System

The conclusion of smart contracts is placed on the blockchain platform due to the special features of this platform, including the two features of transparency and decriminalization. After being completed on the blockchain network, these contracts' transparency feature enables the public to observe and offer them. In this case, all the people who have access to this platform have the possibility of knowing what was transferred by whom to whom, and this not only prevents the occurrence of many related lawsuits but also many crimes related to property.
Federated Multi-source Domain Adaptive Object Detection with Probabilistic Teacher

In order to reduce data collecting effort as well as increase data diversity in advanced surveillance systems, collaboration among multiple cameras is practical and efficient. However, training a CNN model at a centralized server may violate user privacy and data confidentiality. We propose a novel scenario wherein data providers (clients) can collaboratively train a model without revealing their datasets and map our problem to multi-source domain adaptive object detection under the federated setting. A Mutual Learning Teacher-Student Framework is setup on clients for domain adaptation. To reduce the false pseudo labels, the technique of Probability Teacher is adopted with the weak-strong augmentation for source/target data. Furthermore, the server fuses models from different clients by model aggregation algorithms, so as to generate a global model for the target domain. Experiments on real world dataset show that our approach outperforms other privacy preserving model aggregation methods.
Mask R-CNN Based Segmentation and Classification of Blood Smear Images

Analysis of microscopic images is a reliable laboratory method that provides useful information for disease diagnosis in medical field.Although advanced technological devices can help with blood disease diagnosis, a microscopic blood smear examination is required for a definitive diagnosis.Nowadays, technicians in many laboratories use microscope to detect anomalies in cells (defects in the cell, parasites, low or excess cell count, etc.).Experts' detection of anomalies provides critical information for disease diagnosis.For the expert, analysing microscopic images is a time-consuming and error-prone procedure.As a result, in this study, a method for accelerating expert examination and automatically detecting cells is presented.The importance of basic blood cell segmentation and classification is emphasized.PBC data set blood smear images were used as the data set.The system was built using the Mask R-CNN architecture, which is a region-based convolutional neural network.Mask R-CNN was tested using various spine structures.The sample segmentation feature in the Mask R-CNN algorithm was used to determine the segmentation of blood cells obtained from images, and the error rates were minimized as a result of the tests.The study focused on detecting eight classes but could be improved by enriching it with further classes and using blood cell images from different angles and better segmentation.
Color-encoded M-array Background Oriented Schlieren for measurements of strongly refracting objects

New variant of Background Oriented Schlieren (BOS) technique is proposed for the measurements of strongly refracting objects. The employed pattern presents a rectangular grid of color dots. Special color encoding makes every dot unique provided its nearest neighbors can be identified. This allows robust matching of the dot images for schlieren objects with arbitrary large apparent displacements. Also, possible formation of multiple images of the same dot due to strongly nonlinear variations of the refractive index can be used to improve the accuracy of the refractive index field measurement. Multi-frame approach is employed to improve the spatial resolution. Potential of the proposed technique is demonstrated by measurements of the diffusion layers in aqueous solutions of sodium chloride and ethanol.
Resilient-Based Posyandu for Flood Disaster in Benua Raya Village, South Kalimantan

The public's understanding and knowledge of disasters are lacking, moreover, the territory of the State of Indonesia has a high potential for disasters to occur. South Kalimantan is one of the provinces that often experience disasters, especially floods and land and forest fires. Posyandu is a community group that has great potential in disseminating disaster information, the role of posyandu cadres is important in health activities. This community service activity is carried out to increase the knowledge, attitudes, and skills of Posyandu cadres when a disaster occurs, especially a flood disaster. The method used is to conduct education, outreach, demonstrations, and simulations. The activities carried out were the socialization of the role of posyandu cadres during a disaster, training on making complementary foods during a disaster, disaster simulations, and flood evacuation simulations for posyandu cadres. Posyandu cadres the participants can understand and know the role of cadres in disaster and can practice all the training carried out.
A comparison of perceived image quality between computer display monitors and augmented reality smart glasses

IntroductionAugmented-reality (AR) smart glasses provide an alternative to standard computer display monitors (CDM). AR smart glasses may provide an opportunity to improve visualisation during fluoroscopy and interventional radiology (IR) procedures when there can be difficulty in viewing intra-procedural images on a CDM. The aim of this study was to evaluate radiographer perception of image quality (IQ) when comparing CDM and AR smart glasses.Methods38 radiographers attending an international congress evaluated ten fluoroscopic-guided surgery and IR images on both a CDM (1920 × 1200 pixels) and a set of Epson Moverio BT-40 AR smart glasses (1920 × 1080 pixels). Participants provided oral responses to pre-defined IQ questions generated by study researchers. Summative IQ scores for each participant/image were compared between CDM and AR smart glasses.ResultsOf the 38 participants, the mean age was 39 ± 1 years. 23 (60.5%) participants required corrective glasses. In terms of generalisability, participants were from 12 different countries, the majority (n = 9, 23.7%) from the United Kingdom. For eight out of ten images, the AR smart glasses demonstrated a statistically significant increase in perceived IQ (median [IQR] 2.0 [-1.0 to 7.0] points) when compared to the CDM.ConclusionAR smart glasses appear to show improvements in perceived IQ when compared to a CDM. AR smart glasses could provide an option for improving the experiences of radiographers involved in image-guided procedures and should be subject to further clinical evaluations.Implications for practiceOpportunities exist to improve perceived IQ for radiographers when reviewing fluoroscopy and IR images. AR smart glasses should be further evaluated as a potential opportunity to improve practice when visual attention is split between positioning equipment and image review.
AI Based Content Controlling System using Age Prediction Algorithm and Selenium Tool

Abstract: The internet provides a platform to distribute a vast amount of content to millions of users worldwide. However, the true issue is when users under the age of 18 are denied access to age-restricted content, which over time has a negative impact on the user's physical and mental health. Children are spending more amount of time in surfing the browser and they easily come across all types of content in internet. On the other hand, creating a plan for computing imaginative complexity would ensure children's safety in social networks, which is unmatched among the most important criteria in today's society. This technique will only be used to regulate the website's content. In this proposed work, face detection has been carried out for detecting the age using a Haas cascade classifier and content restriction based on age done by selenium. In general, two sophisticated techniques, such as age estimation and facial recognition, are needed to limit internet access to specified age groups. Then, for a content management system, this proposed work has suggested a new unified framework for face recognition and age detection. This proposed work has developed a system that accurately controls the browser content by combining age recognition and content restriction. In order to regulate the website, selenium is applied after detecting the person’s face and estimating their age.
The Correlation between Students’ Academic Self-Efficacy and Their English Learning Achievement at SMAN 1 Pekanbaru

The research objective was to discover whether or not there is a significant correlation between students’ academic self-efficacy and their English learning achievement at SMAN 1 Pekanbaru. The research applied quantitative approach with correlational research design,. The population of the research was 250 students of tenth grade at SMAN 1 Pekanbaru, meanwhile the samples were 70 students, who were selected using a cluster random sampling technique. The instruments employed in this study were questionnaire to measure students’ academic self-efficacy and secondary data that was taken from the exam results of students’ English achievement. To analyze the data, the researcher applied SPSS 25. The findings proved that the correlation coefficient between the two variables is 0.422 and categorized as ‘moderate’. In addition, the determinant coefficient of students’ academic self-efficacy is 0.1780. It was inferred that there is a moderately significant and positive correlation between two variables.
Integrating mobile assisted language learning (MALL) into EFL classes at a tertiary level

Mobile Assisted Language Learning (MALL) practices have gained increasing popularity thanks to the advancements in mobile technologies. Accordingly, a growing number of initiatives have been taken to integrate it into language learning process. However, a gap in the literature has been observed to measure the effects of MALL on students’ writing competence at a tertiary level in Iraq. To this aim, it was sought to pinpoint the influence of MALL on 60 Language Preparatory School students’ writing competence at TISHK International University by employing snowball sampling technique within 12 weeks in 2021-2022 Academic Year. The study was conducted in an Academic Writing course that required the students to write an essay weekly. The data were collected via exams, a questionnaire, an interview and a survey which were analyzed either by SPSS 23. or MAXQDA software applications in this mixed methods design study. Control group students received a traditional instruction, while experimental group students were trained based on the procedure of MALL. The findings unearthed that MALL practices increased students’ marks dramatically, boosted students’ motivation and increased students’ overall attitudes towards learning English. The findings of this study can have some implications for the educators who consider the implementation of MALL practices at educational institutions.
Models of musical string vibration

Musical string vibration has been the subject of scientific study for centuries. Recent increases in computational power have allowed the exploration of increasingly detailed features of perceptual significance through simulation approaches. The starting point for any simulation is a well-defined model, usually framed as a system of differential equations, with parameters determined by measurement and experiment. This review article is intended to take the reader through models of string vibration progressively, beginning with well-known and well-studied linear models, and then introducing new features that form the basis for the modern study of realistic musical string vibration. These include, first, nonlinear excitation mechanisms, such as the hammer-string and bow-string interaction, and then the collision mechanism, both for pointwise obstructions and over a distributed region. Finally, the linear model of string vibration is generalized to include geometric nonlinear effects, leading to typical nonlinear behaviour such as pitch glides and the appearance of so-called phantom partials due to nonlinear mixing of modes. The article concludes with a general overview of numerical simulation techniques for string vibration.
Staidear Board Game Model Application in Facilitating Vocational School Students Learning

Students need help with learning the basic material of graphic design. It has an impact on low student learning outcomes. This study aims to develop a game-based learning media that can be used to facilitate vocational students' learning in multimedia learning activities. This type of research is research and development using the ADDIE model. The sample in this study was 30 students. Data collection techniques using interviews and questionnaires. Data collection instrument using a questionnaire. Data analysis technique using descriptive analysis. The study's results, namely the material feasibility test, obtained a score of 3.88, while the media feasibility test obtained a score of 3.87. Implementation results 76.6 per cent of respondents are interested in learning multimedia using the Staidear board game, 93.3 per cent of respondents think the Staidear board game is easy to use. It was concluded that board game learning media is appropriate for use in the learning process of graphic design. The application of board game media is effective in learning graphic design. The unique appearance of board games can attract students' interest in learning. Implementing this board game implies an increase in the average student test scores.
Bicomponent sorting algorithms

he possibilities of improving sorting time parameters through preprocessing by stochastic sorting were investigated. The hypothesis that two-component stochastic + classical sorting outperforms classic one-component sorting in terms of time efficiency was experimentally confirmed. Sorting with different computational complexity is accepted as classical sorting algorithms: shaker sort- ing with computational complexity O(n2), insertions O(n2), Shell O(n·(log n)2) ... O(n3/2), fast with optimization of ending sequences O(n·log n). The greatest effect is obtained when performing comparisons using stochastic sorting in the amount of 160 percent of the array’s size. Indicators of the efficiency of the exchange of two elements, as well as series of exchanges, are introduced. This allowed to determine the highest efficiency of stochastic sorting (as the first component of two-component sorting), when one element for comparison is chosen from the first part of the array and the other from the second. For algorithms with a computational complexity of O(n2) the improvement in time efficiency reached 70–80 percent. However, for Shell sort and quick sort, the stochas- tic presort has no positive effect, but instead increases the total sorting time, which is apparently due to the initial high efficiency of these sorting methods. The hypothesis that three-component sorting fast + stochastic + insertions would increase sorting time efficiency was not confirmed. However, during the experiment, the recommended size of the array was determined, at which point the two-component quick + insertion sort must be switched to the second component – insertion sorting. The optimal length of the ending sequences is between 60 and 80 elements. Given that algorithm time efficiency is affected by computer architecture, operat- ing system, software development and execution environment, data types, data sizes, and their values, time efficiency indicators should be specified in each specific case.
An Empirical Study of the University Teachers' Continuance Usage of Online Teaching Platform

This study is with the purpose of verifying the indirect relationships between variables in the measurement model and confirms all 11 indirect paths of influence. The quantitative design and the empirical analysis have confirmed that service quality, system quality, and IT self-efficacy have indirect impacts on the dependent variable. This finding of this study shows that the system quality and service quality of online teaching platforms have a significant impact on the usage intention and behavior of teacher users. Improving the quality of the system and services can increase the satisfaction and perceived usefulness of teacher users towards the platform, thereby enhancing their continuance intention and continuance usage behavior. Meanwhile, IT self-efficacy plays a crucial role in the continuance intention and behavior of teacher users, and improving their IT self-efficacy can help increase their intention to use online teaching platforms. Enhancing the IT self-efficacy of teacher users: Through training and skill improvement, help teachers improve their IT skills and enhance their confidence in using online teaching platforms. For the research and practical implications, and for the future research, other possible factors that may affect teachers' continuance usage of online teaching platforms, such as organizational support and peer influence, can be further explored. In addition, it is possible to study the differences in the use of online teaching platforms by teachers in different disciplines, educational stages, and regions, to understand the motivations more comprehensively for teachers to continue using online teaching platforms.
Procedural Content Generation pada Game Tower Defense menggunakan Perlin Noise dan Algoritma Floyd Warshall

To distinguish each level, tower defense games require map design, enemy travel routes, and enemy wave designs. Manually designed designs require a lot of effort and time. To overcome this problem, procedural content generation is used to create maps automatically. Not all content can be created automatically, the content designed in this research includes portal design, tower design, enemy design, and tile design. The Map is created automatically using Perlin Noise to determine the type of tiles on the map. To produce a playable map in accordance with the minimum distance requirement of 45 tiles, the position of the player portal and enemy portal need to be checked using the Floyd-Warshall algorithm. The test results show that after 100 attempts, 25 trials need to be repeated because the distance between the portals does not meet the requirements. The average map creation time is 0.99 seconds. The enemy waves on each map also vary from the number of each type and the order in which the enemies come out.
Cryptocurrency Abuse for the Purposes of Money Laundering and Terrorism Financing: Policies and Practical Aspects in the European Union and North Macedonia

The number of countries that express concern for the danger of using cryptocurrencies for illegal activities among which are money laundering and terrorism financing is increasing. Cryptocurrencies are virtual assets created and managed through advanced computer encryption and operate on a decentralized network known as a blockchain. The key issue of concern and attention in the world is the anonymity and pseudonymity of cryptocurrencies, which prevents proper monitoring of transactions by state institutions and allows the completion of suspicious transactions outside the regulated systems. The paper provides an overview and elaborates the existing European legal framework and the measures and activities undertaken by the Republic of North Macedonia, harmonized with the European ones, in the fight against money laundering and terrorist financing in the crypto sector. For that purpose, the legal documents adopted at EU level, as well as those adopted by North Macedonia are analyzed and discussed. At the end, the paper clearly brings out a major way in which the abuse on the use of crypto-currency can be stopped at the international level.
PERANCANGAN APLIKASI PEMBELAJARAN DENGAN KONSEP GAMIFIKASI Systematic Literature Review

The concept of gamification has been considered as one of the innovative methods in learning to increase student motivation and learning outcomes. In this study, researchers analyzed the application of the gamification concept by using a systematic literature review method. Researchers collected several journals about the application of gamification in learning and analyzed the results of these journals. The purpose of this study is to compare which method is best used in applying the concept of gamification in learning
PERANCANGAN SISTEM INFORMASI KAS BERBASIS WEB DENGAN MENGGUNAKAN METODE WATERFALL

The Cirebon City Youth and Sports Service (Dispora) is an autonomous implementing element in the field of sports. This field has a section that manages data on government and non-government activities in Cirebon City. One of them relates to information related to sports in the city of Cirebon. As part of the Cirebon City Youth and Sports Service, they do not yet have an adequate or dynamic financial reporting web, so this agency must develop a dynamic web-based information system to accommodate cash management. System development follows the Waterfall concept, which includes the stages of analysis, design, coding, implementation and maintenance. Data collection procedures were carried out through observation, interviews and documentation studies. The design of this website provides convenience in submitting financial reports to agencies.
Discourse over Discourse: The Need for an Expanded Pragmatic Focus in Conversational AI

The summarization of conversation, that is, discourse over discourse, elevates pragmatic considerations as a pervasive limitation of both summarization and other applications of contemporary conversational AI. Building on impressive progress in both semantics and syntax, pragmatics concerns meaning in the practical sense. In this paper, we discuss several challenges in both summarization of conversations and other conversational AI applications, drawing on relevant theoretical work. We illustrate the importance of pragmatics with so-called star sentences, syntactically acceptable propositions that are pragmatically inappropriate in conversation or its summary. Because the baseline for quality of AI is indistinguishability from human behavior, we draw heavily on the psycho-linguistics literature, and label our complaints as "Turing Test Triggers" (TTTs). We discuss implications for the design and evaluation of conversation summarization methods and conversational AI applications like voice assistants and chatbots