Reviewerly/exHarmony huggingface dataset:
The mediating Effects of Cognitive Flexibility on the Relationship between Positive Psychological Capital and School Life Adjustment of High School Student

Objectives The purpose of this study is to investigate the mediating effects of cognitive flexibility on the relationship between positive psychological capital and school life adjustment of high school students.&#x0D; Methods For the research high school students in Busan were surveyed and 227 students’ data were finally analyzed using SPSS. Correlation analysis was conducted to determine the relationship between each variable, and hierarchical multiple regression analysis was conducted to verify the mediating effects of the cognitive flexibility. Sobel Test was used to prove if the indirect effect of mediation variable was significant.&#x0D; Results First the result of this study showed that four components of positive psychological capital (self-efficacy, optimism, hope and resilience), cognitive flexibility, and school life adjustment of high school students had significant positive correlation. Cognitive flexibility on the relationship between four different resources of positive psychological capital and school life adjustment of high school students has been turned out to have partial mediating effects.&#x0D; Conclusions These results suggest the importance of psychological intervention to improve psychological capital (self-efficacy, optimism, hope and resilience) and cognitive flexibility that affect school life adjustment of high school students.
The Development Study of the Drag Coefficient of Solid Cylinder on Inclined Plane in Water

The dynamic resistance of a fluid to a cylinder rolling on an inclined plane in water has been experimentally studied. This creates problems in the form of solid-liquid interactions, which include landslides on the seabed and debris flows on the seabed that cause Tsunamis. The development of flow around a rolling cylinder is described to highlight the implications on the nature of the hydrodynamic force coefficient acting on the cylinder as resistance. The coefficient of drag on the cylinder when rolling on an inclined plane in water is the coefficient of drag that prevents the cylinder from rolling. In addition, other external force coefficients (besides the drag coefficient) also impede the cylinder motion. The equation of motion of the cylinder is solved with experimental data which is used as the most suitable solution to get the drag coefficient value. The movement of the cylinder is also not perfectly linear because there is a force from the side of the track and the cylinder moves slightly zigzag in 1-D motion.&#x0D; HIGHLIGHTS&#x0D; &#x0D; In this study, we present the experimental results of cylindrical drag coefficients of various materials on inclined planes in water as modeling of broader scientific problems, especially the potential for hydrometeorological and sedimentation disasters&#x0D; Fluid dynamics of the cylinder drag force on an inclined plane in water were measured experimentally&#x0D; The motion of the cylinder on an inclined plane in water is recorded, then the recorded video is processed using Logger Pro to obtain experimental time, speed, and position data which is processed using the appropriate mathematical equations&#x0D; &#x0D; GRAPHICAL ABSTRACT
Blockchain analysis of the Bitcoin market. (Part 1) (The article published both in original and Russian translation)

This article presents a detailed analysis of the Bitcoin network (Bitcoin) and its main participants, carried out by authoritative experts - Igor Makarov from the London School of Economics and Antoinette Shoart from the Massachusetts Institute of Technology - on behalf of the National Bureau of Economic Research (NBER) - a private organization in the United States. The Bitcoin network is defined as a new database that includes a large number of public and proprietary sources for linking bitcoin addresses to real objects and an extensive set of algorithms for extracting information about the behavior of major market participants. The analysis of the Bitcoin ecosystem consisted of three main stages. First, the volume of transactions and the network structure of the main participants in the blockchain are analyzed. Secondly, the concentration and regional composition of miners who carry out verification (verification) and ensure the integrity of the blockchain registry (ledger, ledger) are documented. Thirdly, the concentration of ownership of the largest holders of bitcoins is considered.
PENGARUH MOTIVASI BELAJAR DAN DUKUNGAN ORANG TUA TERHADAP HASIL BELAJAR KELISTRIKAN OTOMOTIF

This study aims to analyze the effect of learning motivation and parental support on the learning outcomes of automotive electrical subjects in class XI automotive light vehicles at the Walisongo 2 Gempol Vocational High School. This study uses a descriptive correlational research design. The data from this study were obtained from a questionnaire given to students for the variables of learning motivation and parental support, while the data on student learning outcomes in automotive electrical subjects was obtained by documentation. The method in this research is descriptive quantitative correlation. Based on the results of the research and discussion that have been described, it can be concluded that there is a positive relationship between student learning motivation (X1) and student learning outcomes in the automotive electrical training subject of SMK Walisongo 2 Gempol (Y) students, where the better the student's motivation, the better. Student learning outcomes. There is a positive relationship between parental support (X2) and student learning outcomes in the automotive electrical training subject of Walisongo Walisongo 2 Gempol Vocational High School (Y), where the better the parental support, the better student learning outcomes. There is a positive relationship between learning motivation (X1), parental support (X2) with student learning outcomes in automotive electrical training (Y), these variables together relate to student learning outcomes at Walisongo Walisongo 2 Gempol Vocational High School.
DOCUMENTS ISSUANCE VALIDATION USING 2D BARCODE

The daily procedures in both official and non-official organizations include the printing and archiving of thousands of paper-based documents, either as issued, incoming, or as attachment documents; as well as the verification of the authenticity of the issuance of such documents at the receiving party, this leads to the production of further papers that are referred to as "issuance validation", This procedure costs more time, effort, and money. Furthermore, the process of archiving and storing these documents electronically requires considerable effort and time in terms of manually entering the information or saving them as images, as well as the possibility of data entry mistakes. This paper proposes employing authenticated PDF417 barcodes in paper-based document publication procedures by adding an encrypted barcode (signature) to the issued document and making it simpler to authenticate the information. During the document verification process, neither internet access nor real-time interaction with the document issuer are required. Furthermore, the proposed system offers a way to digitally archive documents using a barcode scanner or smartphones, which enables accuracy and speed in entering the information of documents received or issued by the institution.
NEURAL NETWORK OPTIMIZATION WITH GENETIC ALGORITHM FOR HEART DISEASE PREDICTION

Coronary Heart Disease (CHD) is a contributor to the number 1 cause of death in the world besides cardiovascular disease. The tendency of Indonesian people who do not know and ignore coronary heart disease is a factor that causes Indonesia to be high a contributor to deaths caused by coronary heart disease. This research is expected to produce new predictions of heart disease using genetic optimization of neural networks with better prediction results and can obtain algorithms with new percentage values in predicting coronary heart disease. Genetic optimization of the neural network is used because the algorithm follows the human nervous system which has the characteristics of parallel processing, processing elements in large quantities, and fault tolerance. The results of the research carried out are the accuracy obtained by 82.18% and increased to 83.50% after using genetic algorithm optimization, from these results it can be concluded that the neural network algorithm can be better if it is supported by genetic algorithm optimization
Twin Neural Network Regression

We introduce twin neural network (TNN) regression. This method predicts differences between the target values of two different data points rather than the targets themselves. The solution of a traditional regression problem is then obtained by averaging over an ensemble of all predicted differences between the targets of an unseen data point and all training data points. Whereas ensembles are normally costly to produce, TNN regression intrinsically creates an ensemble of predictions of twice the size of the training set while only training a single neural network. Since ensembles have been shown to be more accurate than single models this property naturally transfers to TNN regression. We show that TNNs are able to compete or yield more accurate predictions for different data sets, compared to other state-of-the-art methods. Furthermore, TNN regression is constrained by self-consistency conditions. We find that the violation of these conditions provides an estimate for the prediction uncertainty.
DAMPAK INFRASTRUKTUR DIGITAL TERHADAP MOBILITAS KOTA BANDARLAMPUNG

Lampung Province, especially in Bandarlampung City, according to the spatial plan (RTRW), Lampung Province has been designated as one of the National Activity Centers (PKN) and as a strategic area for Sumatra Island in the transportation sector. This condition encourages Bandarlampung City to apply the Smart City concept in developing its city, in realizing this concept Bandarlampung City utilizes digital infrastructure platforms in its activities. The digital infrastructure platform is expected to be a solution to push Bandarlampung City towards the realization of the Smart City concept and improve the public's mindset towards technological advances to facilitate and improve the quality of public services. In addition, according to Castells (2010) theory, the existence of this digital platform will reduce mobility in Bandarlampung City because many public service activities are carried out from home without transportation. The digital infrastructure platform of Bandarlampung City that include in this research is a platform for local transportation network infrastructure, government, education, health, trade and commerce, clean water and electricity networks and telephone network utilities. In this research, it was identified that there was a connection between changes in the frequency of use of digital infrastructure platforms which in fact affected the mobility of the citozens of Bandarlampung City.
Rendering Nighttime Image Via Cascaded Color and Brightness Compensation

Image signal processing (ISP) is crucial for camera imaging, and neural networks (NN) solutions are extensively deployed for daytime scenes. The lack of sufficient nighttime image dataset and insights on nighttime illumination characteristics poses a great challenge for high-quality rendering using existing NN ISPs. To tackle it, we first built a high-resolution nighttime RAW-RGB (NR2R) dataset with white balance and tone mapping annotated by expert professionals. Meanwhile, to best capture the characteristics of nighttime illumination light sources, we develop the CBUnet, a two-stage NN ISP to cascade the compensation of color and brightness attributes. Experiments show that our method has better visual quality compared to traditional ISP pipeline, and is ranked at the second place in the NTIRE 2022 Night Photography Rendering Challenge for two tracks by respective People's and Professional Photographer's choices. The code and relevant materials are avaiable on our website: https://njuvision.github.io/CBUnet.
Metaverse Simulation Based on VR, Blockchain, and Reinforcement Learning Model

Abstract: With advancements in virtual reality and the boom of the Metaverse, the technology underlying modern games is progressing rapidly. Virtual reality and current Artificial Intelligence algorithms have resulted in impressive results and immersive user experiences. This proposed work aims to create a first-person blockchain figure VR environment incorporating reinforcement learning and imitation learning methods. Supervised and reinforcement learning work using input-output mapping, but the critical difference is that reinforcement learning uses reward and penalty, which are positive and negative action indicators, respectively. The blockchain-based non-fungible agent, based on this indication, learns which actions are favourable. For a better experience, these profitable actions with imitation learning in the state action format are mapped further. In this environment, reinforcement learning is trained with various parameters such as Sensory complexity, Logic complexity for solving tasks, social complexity, and Physical complexity. This simulation enables users to use NFT guns to shoot enemy agents. These agents have been trained to navigate the map using Reinforcement and Imitation learning and shoot us whenever they sense our presence. The simulation is complete if the user kills every agent before his health level finishes. This proposed work highlights the potential of VR, Blockchain, and reinforcement learning in making Metaverse more interactive and impressive
The Harmonic GBC Function Map is a Bijection if the Target Domain is Convex

Harmonic generalized barycentric coordinates (GBC) functions have been used for cartoon animation since an early work in 2006\cite{JMDGS06}. A computational procedure was further developed in \cite{SH15} for deformation between any two polygons. The bijectivity of the map based on harmonic GBC functions is still murky in the literature. In this paper, we present an elementary proof of the bijection of the harmonic GBC map transforming from one arbitrary polygonal domain $V$ to a convex polygonal domain $W$. This result is further extended to a more general harmonic map from one simply connected domain $V$ to a convex domain $W$ if the harmonic map preserves the orientation of the boundary of the domain $V$. In addition, we shall point out that the harmonic GBC map is also a diffeomorphism over the interior of $V$ to the interior of $W$. Finally, we remark on how to construct a harmonic GBC map from $V$ to $W$ when the number of vertices of $V$ is different from the number of vertices of $W$ and how to construct harmonic GBC functions over a polygonal domain with a hole or holes. We also point out that it is possible to use the harmonic GBC map to deform a nonconvex polygon $V$ to another nonconvex polygon $W$ by a good arrangement of the boundary map between $\partial V$ and $\partial W$. Several numerical deformations based on images are presented to show the effectiveness of the map based on bivariate spline approximation of the harmonic GBC functions.
Discovery Learning Based E-Worksheet Assisted with Google Docs to Grow Higher Order Thinking Skills of Junior High School Students

This study aimed to 1) find out the feasibility of the E-worksheet based on discovery learning with Google Docs product, 2) explain the practicality of the E-worksheet based on discovery learning with Google Docs product, and 3) understand the effectiveness of the E-worksheet based on discovery learning with Google Docs product to grow higher order thinking skills (HOTS) of VIII grade junior high school students on the simple machine topic. The study was a research and development (RD) with the 4D model. The subjects were 32 students of VIIIA class in SMPN 4 Pakem. The instruments were product validation sheet, students’ response questionnaire, pre-test and post-test questions, and learning observation sheet. The feasibility and practicality of the product were analyzed using score conversion. The results of the pre-test and post-test were analyzed using qualitative and quantitative descriptive analysis to find out the effectiveness of the product. The research concluded that 1) the E-worksheet based on discovery learning with Google Docs product was very feasible, both in the material and media aspects, 2) the E-worksheet based on discovery learning with Google Docs was practical based on the teacher and students’ responses, and 3) the E-worksheet based on discovery learning with Google Docs was effective to build the HOTS of the students.
Does an Android-Based Interactive Flipbook Affect the Student’s Science Concept Mastery?

This study aims to determine the effect of using android-based interactive flipbook media in increasing the mastery of science concepts for junior high school students. The research was conducted in one experimental class and one control class at SMP Negeri 2 Genteng, Banyuwangi. The instruments used were 10 multiple choice questions and 3 essay question with cognitive levels of C1 – C6. The method used is a Quasy Experiment with a pretest posttest control group design. The experimental class and control class were taken by simple random sampling. The data analysis technique used is the analysis of the independent sample T test with the help of SPSS application and the standard gain value using the gain equation. Sig value. (2-tailed) independent sample T test is 0.000, this indicates that there is a significant didfference between the average concept matery of student in the experimental class and control class. Gain value shows that the average mastery of the concepts of experimental class student has increased from before and after treatment of 0.66 with moderate criteria. The average concept mastery of control class students increased from before and after treatment by 0.24 with low criteria.
Slava Ukraini: Exploring Identity Activism in Support of Ukraine via the Ukraine Flag Emoji on Twitter

Identity Activism, a new phenomenon emerging from the massive popularity of social media, consists of the prominent display of a social movement symbol within space reserved for description of the self. Here we introduce and explore this concept, asking: What is the trajectory of engagement in Identity Activism in response to historical events? As an initial case, we present a timeline of engagement in Identity Activism regarding the 2022 Russian invasion of Ukraine. With user profile data from January - June 2022, we visualize Identity Activism through the prevalence of the Ukraine flag emoji in US Twitter bios. We find that beginning on February 21, Ukraine flag emoji prevalence increased approximately 30-fold over the course of six days, moving from least prevalent out of 121 flags to third most. The prevalence has only declined slightly since, maintaining an average 30 times higher than pre-February 21.
Development of Student Worksheet Based on Discovery Learning to Improve Student’s Concept Understanding

This research aimed to (1) produce student worksheet based on discovery learning to improve students’ conceptual understanding, (2) analyze the practicality of student worksheet based on students’ responses, and (3) test the effectiveness of student worksheet to improve students’ conceptual understanding. The research used research and development (RD) method with a 4D model. The trial design used a one-group pretest-posttest. The instruments were the eligibility validation sheet of student worksheets, student response questionnaires, observation sheets, and instrument tests. The data analysis techniques were a five-scale score conversion, implementation of the lesson plan, the percentage of the practicality of the student worksheet, Wilcoxon signed rank test, and n-Gain. The result showed that (1) student worksheet based on discovery learning was feasible to use with the result of the assessment from material and media experts in the very good category, (2) the practicality of the student worksheet was practical with a practicality percentage of 64% in a practical category, and (3) the student worksheet was effective to improve students’ conceptual understanding as seen by the result of the Wilcoxon signed rank test asymp. Sig (2-tailed) 0.001 0.025. So, there were differences in understanding concepts before and after using the student worksheets. The result was strengthened by the n-Gain analysis of 0.4 with a medium category, and there is a significant increase in conceptual understanding.
Development E-Worksheet Based On Problem Based Learning To Improve Student's Metacognitive Ability

The study aimed to determine the validity, practicality, and effectiveness of electronic student worksheets (e-worksheets) based on problem based learning (PBL) to improve students' metacognitive abilities on stoichiometric material. The research was used a research and development (RD). The sample of the study was 30 students from SMAN 19 Surabaya. The instruments were validation sheets, student observation sheets, cognitive test sheets, and MAI questionnaires. The metacognition ability was tested using MAI questionnaire on the aspects of planning, monitoring, and evaluating. Then, it was strengthened again with a cognitive test consisting of 6 cognitive questions. The results showed that the developed e-worksheet has 89.76%; 86.67%; 83.33%; and 86.67% of content; graphics; presentation; and language validities, respectively. All components were in the very high category. The results of the practicality of the e-worksheet were 94.64%; 99.29%; 95.24%; 97.62%; and 94.05% for the PBL strategy; metacognitive; graphics; presentation; and language components, respectively. All components were in the very practical category. Based on the t-test, the sig.2-tailed of the planning, monitoring, and evaluating aspects were less than 0.05 so Ha is accepted, which means that the e-worksheet can improve students' metacognitive abilities in those aspects. This is supported by the t-test of students' cognitive abilities where the sig.2-tailed is 0.000 so Ha is accepted, which means that the developed e-worksheet can improve students' cognitive abilities
An Empirical Investigation of Learning from Biased Toxicity Labels

Collecting annotations from human raters often results in a trade-off between the quantity of labels one wishes to gather and the quality of these labels. As such, it is often only possible to gather a small amount of high-quality labels. In this paper, we study how different training strategies can leverage a small dataset of human-annotated labels and a large but noisy dataset of synthetically generated labels (which exhibit bias against identity groups) for predicting toxicity of online comments. We evaluate the accuracy and fairness properties of these approaches, and trade-offs between the two. While we find that initial training on all of the data and fine-tuning on clean data produces models with the highest AUC, we find that no single strategy performs best across all fairness metrics.