Reviewerly/exHarmony huggingface dataset:
A NEW DANGER OF BEHAVIORAL ADDICTION: CRYPTOCURRENCY WITH MOBILE INVESTING

Introduction:Cryptocurrencies are a popular investment tool today.However, some studies highlight the investing behavior of cryptocurrencies similar to pathological gambling.Investing behavior becomes risky when it is not based on proper and adequate analysis and carries the possibility of big losses as well as big gains.For this reason, we aimed to determine the potential risky investor profile by age, gender, personality traits and impulsivity levels. Subjects and Methods:Six hundred and fifty-four cryptocurrencies investors (529 was male, 125 was female, their mean age was 35.6 ± 9.0) participated in this study between June 2022 -August 2022.Participants were administered the Sociodemographic Data Form, the South OAKS Gambling Screen Test -revised (SOGS-r), the Big Five Inventory (BFI-10), and Barratt Impulsiveness . Results:We found higher neuroticism and impulsivity in possible problematic crypto investors.In addition, extraversion, agreeableness and conscientiousness scores were lower.Additionally, in our regression analyzes we found that younger age and male gender predicted SOGS-r scores.After controlling for age and gender, extraversion negatively and motor impulsivity positively predicted SOGS-r scores.Discussion: Investing in cryptocurrencies can become a behavioral addiction, similar to pathological gambling.It is important to identify profiles in which investment behavior is risky. Conclusion:Personality traits and impulsivity may have a significant impact on identifying risky crypto investors and in the treatment process.
Pentingnya Penggunaan Model Pembelajaran Project Based Learning Menggunakan Powtoon pada Pembelajaran Sejarah Siswa di MAN 2 Padang

This research aims to analyze the importance of using project-based learning model using powtoon in history learning. This research uses descriptive research using the observation method. This research was conducted at MAN 2 Padang. The population in this study were all X social studies classes from class X social studies 3 which amounted to 35 people. Based on the results of research One of the learning media in history is Powtoon media. The results of this product combine powerpoint displays and comic books. The benefits of learning using powtoon are offering media options to create interesting lesson plans and produce a product that can be applied during learning.
Sistem informasi Inventory Iparepart Motor Pada Bengkel Al Motor

The development of information technology is growing so rapidly, making many people aware of the importance of information. At the AL motorcycle repair shop, the ongoing process is still not effective because the inventory data management is still using the manual method using Microsoft Excel which makes the process of searching for goods take quite a long time. Where sometimes it often happens that the data in the warehouse is wrong with the data in microsoft excel which makes the workshop party have to calculate the stock from the beginning again to match the data in microsoft excel with in the warehouse. The purpose of this research is to assist the workshop in recording stock which has been ineffective in terms of workmanship and the results of this study resulted in the application of this spare parts inventory information system to be a medium to increase accuracy in the suitability of data items with existing physical quantities.
Project Competence of a teacher of the Mari Language and Literature in the Context of Digitalization of Education: Structural and Content Analysis

Today, the formation of project competence is an integral part of the training of a teacher of the Mari language and literature. This characteristic reflects the ability and readiness of the teacher to lead and implement ethnocultural projects in the context of digitalization of education. The purpose of the article is to reveal and justify the concept of “project competence of a teacher of the Mari language and literature”, to determine its structure and content in the context of digitalization of education. Methodology. The methodological base of the study was made up of regulatory documents, modern works of domestic and foreign scientists in the field of digital transformation of education and project management. Theoretical, empirical and mathematical methods used in the study. Research results. The paper substantiates the significant role of project activities in the preparation of a teacher of the Mari language and literature. An overview of the definitions of “project competence” in the studies of domestic and foreign scientists is given, an analysis of their key and structural components is made. The definition of “project competence of a teacher of the Mari language and literature” is given, structural components and content are identified and described. Aspects of the influence of digitalization on the process of forming the project competence of a teacher of the Mari language and literature are displayed. The program of additional professional education “Digital projects on the Mari language and literature” is developed and proposed, its structure and content are described. In conclusion, it is concluded that project competence is an integral part of the training of a teacher of the Mari language and literature and is a complex integrated characteristic consisting of motivational, cognitive, activity, cultural and reflective components. Its formation is greatly influenced by the ongoing processes of digitalization.
Time-optimal universal quantum gates on superconducting circuits

Decoherence is inevitable when manipulating quantum systems. It decreases the quality of quantum manipulations and thus is one of the main obstacles for large-scale quantum computation, where high-fidelity quantum gates are needed. Generally, the longer a gate operation is, the more decoherence-induced gate infidelity will be. Therefore, how to shorten the gate time becomes an urgent problem to be solved. To this end, time-optimal control based on solving the quantum brachistochrone equation is a straightforward solution. Here, based on time-optimal control, we propose a scheme to realize universal quantum gates on superconducting qubits in a two-dimensional square lattice configuration, and the two-qubit gate fidelity approaches $99.9%$. Meanwhile, we can further accelerate the $Z$-axis gate considerably by adjusting the detuning of the external driving. Finally, in order to reduce the influence of the dephasing error, decoherence-free subspace encoding is also incorporated in our physical implementation. Therefore, we present a fast quantum scheme which is promising for large-scale quantum computation.
MyNote: Multiplatform Reactive Integration System with The Clean Architecture Development Concept

The application needs in the current digital era are very broad and varied. In its development, these applications undergo a transformation, thus demanding application developers to create applications that suit their devices. This study applies the concept of the reactive paradigm which is implemented into a multiplatform application system and the concept of clean architecture in the process of creating a simple note management application "MyNote". The concept of reactive programming uses Spring WebFlux on the backend and React.js with RxJs on the frontend. The multiplatform concept on Android is implemented in Webview. Performance analysis is conducted using the load test, and stress test. This research aims to provide information on how to implement the concept of multiplatform applications and reactive programming with the clean architecture development method for the MyNote application. In addition, it also can be used as a consideration in implementing this concept stack in production-ready products. This study succeeded in making the MyNote application using a combination of clean architecture, multiplatform, and reactive programming concepts with a percentage of 93,75% application of the concept, and 80% application development.
The Mechanism of Work of The Mental Lexicon Under the Lights of The Computer System

of The research entitled (The mechanism of work of the mental lexicon under the lights of the computer system) and the research is an attempt to shed light on the mechanism of the work of the mental lexicon in the mini-program and within the framework of the late opinions of (Chomsky), and it must be said that the dictionary enters the data of the morphological level of the language, and realized Chomsky said that the differences between languages ​​lie mainly in the morphological difference, so the level of analysis in this research is morphological. Introduce it into its context specific to the word. In acquiring any language, there are two mechanisms associated with the completion of the language acquisition project. Decreasing any of the two mechanisms misses the acquirer the opportunity to learn the mother language, which lasts until the age of (9-10) years, and if this period is broken, any deficiency destroys the acquisition. As well as within the framework of the research program, we discuss the issue of moving units and merging units after removing them from the mental lexicon. &nbsp
PERBANDINGAN METODE KLASIFIKASI SUPPORT VECTOR MACHINE DAN NAÏVE BAYES PADA ANALISIS SENTIMEN KENDARAAN LISTRIK

Electric vehicles are one of the solutions that can be used to deal with the problem of greenhouse gas emissions. Switching to electric vehicles can be an effective solution because electric vehicles have many advantages. However, the acceptance of electric vehicles in Indonesia depends on the opinions or sentiments given by the community. Sentiment analysis can provide a specific picture of how the sentiment or opinion given by the Indonesian people towards electric vehicles. The sentiment analysis process is carried out using the Python programming language. This research compares SVM and Naïve Bayes methods in sentiment analysis in terms of accuracy and time efficiency. A total of 717 data were used as test data and SVM correctly classified 150 negative data, 152 neutral data, and 277 positive data. Meanwhile, Naïve Bayes correctly classified 166 negative data, 143 neutral data, and 282 positive data. training time required for the SVM method is 37.42 seconds while Naïve Bayes is 0.10 seconds. Naïve Bayes is the best method in this study because of its high accuracy and fast training time.
CPLT: Curriculum Pseudo Label Transformer for Domain Adaptive Object Detection in Foggy Weather

To address the challenge of label-scarce images captured by sensor in foggy weather condition with limited labeled data for autonomous driving, domain adaptation can be applied to transfer information from a label-rich clear-weather dataset to a label-scarce adverse weather dataset. This article proposes a novel approach named curriculum pseudo label transformer (CPLT) for domain adaptive object detection (DAOD). CPLT incorporates two effective techniques to enhance the transformer’s ability to detect objects across domain. First, distribution alignment curriculum (DAC) pseudo label is proposed. The key idea of DAC is to flexibly adjust class-specific thresholds by aligning the class distribution over the course of training. The second technique employed in CPLT is called instance-level feature optimal transport (IFOT), which applies sliced Wasserstein distance to minimize domain discrepancy in instance-level features while preserving the location information. Importantly, neither of these modules introduce additional trainable parameters in the network. Experimental results on five challenging benchmarks demonstrate that CPLT significantly improves domain adaptation object detection performance.
A virtual reality memory scene designed with memory reproduction as the concept

The use of VR (virtual reality) in memory recovery has considerable potential, and this is just beginning to materialize. Those exploratory studies conducted so far suggest that VR's participation will help improve the assessment of memory impairment and memory repair using recombinant techniques. Based on the current virtual reality technology is mostly used for game development, the relevant research on memory reproduction is relatively insufficient. In this paper, a memory gallery was built through 3D (three dimensional) modeling, and Metahuman technology was used to achieve character reproduction, combined with unreal5 development to achieve important memory reproduction. This work mainly uses 3D models to make a memory corridor, Metahuman digital virtual human technology and VR Chat VR social combination to bring users immersive precious memories reproduction, and can interact with it. Experiments have shown that recall reproduction is of great help to emotional repair. VR can help by making the presentation more immersive.
Review of image recognition systems for noisy environments

One of the major challenges faced by image recognition systems in practical applications is the presence of noise in the physical world. To address this challenge, this paper proposes two different approaches. The first approach involves constructing a noisy dataset and training the image recognition system to tolerate noise. The second approach utilizes a combination of denoising methods and pre-trained image recognition systems. Experimental tests and analyses are conducted to evaluate the advantages and disadvantages of each approach. Additionally, this paper investigates the relationship between different noise reduction methods and their impact on improving the recognition rate and resource consumption of images containing Gaussian noise, specifically when neural networks are used for recognition.
Natural language processing – relevance to patient outcomes and real-world evidence

KEYWORDS: Clinical informaticsdata scienceelectronic health recordshealthcare datainformation extractionmental healthmental health servicesnatural language processing
Indonesian Sign Language (SIBI) Learning Media Application Based on Deep Learning Technology for Deaf Children

One of the main methods in teaching deaf children effectively is through visualization of learning materials. Previous research has developed augmented reality-based interactive learning media for deaf children. However, these learning media have limitations related to smartphone memory, dependence on certain flashcards, and limited amount of material due to flashcard limitations. Here, researchers innovate to develop SIBI learning media applications based on deep learning technology that material does not depend on a specific flashcard, but the application is able to detect real objects and various images. TensorFlow Lite is considered lighter but still allows the system to run deep learning on mobile devices with low latency. This application is designed to capture a real object or image through the camera, then the object or image will be processed and recognized using TensorFlow Lite. The object recognition process is carried out at the classification layer using switch-case syntax and global class synchronization with the YouTube API. After the image or object is recognized, the system will issue an output in the form of an Indonesian sign language video link from the object.
Visualization of Interest Level using OpenPose with Class Videos

The approach from the teacher's side to improve the classroom is to establish a learning discipline and an improvement method. However, there are various ways to do this, and it is an important part of teachers' work. In this paper, we propose a system for estimating the level of interest from class videos as a means of knowing the learning status of individual students. Using OpenPose, the system detects a person in a class video and extracts feature data of his/her joints. And we measure the concentration level based on the information of posture, facial orientation, and other movements. In addition, assuming that a person's face is facing the direction of the target when he/she is concentrating, we measure the concentration level based on the information of posture, facial direction, and other movements.
Physics Teacher Agency for Physics Education

In the field of middle and high school physics education, teachers must succeed in both “physics education” and “physics as education.” This is because the school classroom is not just a time for learning physics, but also a time for connecting physics to students’ lives “Right here Right now” as an education. Physics teachers are actively interpreting and reconstructing the field with students who change rapidly in society and creating the context of physics education. In this personal and social context, teacher agency is exerted.1) Teacher agency is not just the personal ability of individual teachers to implement policies sincerely or the policies promoted by higher institutions. Teacher agency as a change agent is achieved by creating an environment in which teachers can actively demonstrate their expertise with their own beliefs in a context that encompasses both the personal and social structural dimensions of teachers.2) In order to promote the emergence of physics teacher agency, educational administrative agencies should focus not only on promoting education policies that focus on the individual competencies of teachers, but also on creating a structural context around teachers and teacher networks as important agent in the development and implementation of education policies. The Korean Physical Society, which plays an important role in the development of physics education, needs to expand opportunities for participation in physics education by physics teachers to help expand the network of physics teachers, who are important actors in the network of physics education.
Video-Based Gait Analysis for Assessing Alzheimer’s Disease and Dementia with Lewy Bodies

Dementia with Lewy Bodies (DLB) and Alzheimer’s Disease (AD) are two common neurodegenerative diseases among elderly people. Gait analysis plays a significant role in clinical assessments to discriminate these neurological disorders from healthy controls, to grade disease severity, and to further differentiate dementia subtypes. In this paper, we propose a deep-learning based model specifically designed to evaluate gait impairment score for assessing the dementia severity using monocular gait videos. Named MAX-GR, our model estimates the sequence of 3D body skeletons, applies corrections based on spatio-temporal gait features extracted from the input video, and performs classification on the corrected 3D pose sequence to determine the MDS-UPDRS gait scores. Experimental results show that our technique outperforms alternative state-of-the-art methods. The code, demo videos, as well as 3D skeleton dataset is available at https://github.com/lisqzqng/Video-based-gait-analysis-for-dementia .
Integration based on Monte Carlo Simulation

In this short article an attempt has been made to model Monte Carlo simulation to solve integration problems. The Monte Carlo method employs random sampling and the theory of big numbers to generate values that are very close to the integral's true solution. Python programming has been used to implement the developed algorithm for integration. The developed Python functions are tested with the help of six different integration examples which are difficult to solve analytically. It has been observed that that the Monte Carlo simulation has given results which are in good agreement with the exact analytical results.
Improving the English Reading Skills and Reading Strategies of Elementary School Students

Students who like reading are more likely to engage with texts, experiment with different genres, and look for opportunities to read on their own. By fostering a love for reading, students are more likely to engage with texts willingly, leading to improved reading skills, a broader vocabulary, increased comprehension, and enhanced critical thinking abilities. This review has focused on the importance, ways and specific measure to improve the English reading skills and reading strategies particularly among the elementary school students.
Analysis of the Amount of Filling and Emptying Time Communal Rainwater Harvesting Tank (RWH)

Abstract Utilization of stagnant water storage tanks in Banjararum Village, Kalibawang District, Kulon Progo Regency with a total of 23 units needs to be optimized by using them as communal rainwater harvesting (RWH). The amount of time for filling and emptying the tank is an important aspect to be able to optimize rainwater used for daily needs. The aims of this research was to determine the effectiveness of the use of Communal PAHs applied in the community. This is analyzed through several stages, including determining the planning location unit, analyzing hydrological characteristics and analyzing the flow rate and duration of filling and emptying the tank using the Prandtl-Colebrook formula and the Bernoulli formula. Researchers took samples in Dusun Kisik by optimizing 2 roofs that can distribute rainwater of 27.09 m 3 /week for roof 1 and 27.19 m 3 /week for roof 2. Assuming 6 people live around the tank who use water storage every day, then the communal PAH can supply 3,000 liters within 52 minutes while the emptying process for distribution to other media takes 69 minutes. This difference is due to the different dimensions of the inlet pipe and outlet pipe. So that the effectiveness of the use of Communal PAHs applied in the community can be one of the recommendations in the provision of sustainable clean water.
A Blockchain-Based Security Model for Cloud Accounting Data

The popularity of cloud accounting is due to its low cost of entry, efficient data processing, and high business efficiency. However, security issues in cloud storage can affect user trust in the service. To address these security issues, a blockchain-based encryption technology model for cloud accounting data security is proposed. Firstly, the feasibility of integrating blockchain technology and cloud accounting is analyzed. Then, an elliptic curve cryptography-based cloud accounting data security solution is proposed. Blockchain and evidence chain technology are used to ensure data security and support data privacy protection for cloud service providers and third-party auditors. The proposed solution has a small computational overhead, as it does not require exponentiation or bilinear pairing. Experimental results show the proposed solution can enhance user control over cloud accounting data, ensure data transmission security, and improve trust between users and cloud accounting service providers. Moreover, it is more efficient.
Blockchain Based Data Steganography

Blockchain based Data Blockchain based Steganography is the system of hiding records which may be text, photo or video Interior a cowl photo. The secret facts are hidden in a way that it not seen to the human eyes. Deep gaining knowledge of era, which has emerged as a powerful tool in diverse programs along with image Blockchain based Steganography, has obtained increased interest lately. The principal purpose of this paper is to explore and talk numerous deep getting to know strategies available in image Blockchain based Steganography area. Deep gaining knowledge of techniques used for photograph Blockchain based Steganography can be broadly divided into 3 classes - traditional strategies, Convolutional Neural community-primarily based and general adverse community-based methods. Along with the technique, A problematic precis on the datasets used, experimentalu. S.A. Taken into consideration and the assessment metrics Normally used are defined in this paper. A table summarizing all of the info also are provided for clean Reference. This paper targets to assist the fellow researchers by means of compiling the current tendencies, challenges and few destinies course on this field