Reviewerly/exHarmony huggingface dataset:
Large Kernel Convolutional Attention Based U-Net Network for Inpainting Oracle Bone Inscription

Oracle Bone Inscription (OBI) image inpainting is important for inheriting the long history of Chinese culture. The complexity of OBI characters leads to many unique writing characteristics, which increase the difficulty of restoring irregular structures and multiple types of strokes. In this work, we formulate a large kernel convolutional attention based U-Net framework to restore OBI images. The framework consists of two modified U-Nets arranged in a series, which perform an edge inpainting function and an overall image inpainting function, respectively. The implementations of the two U-Nets are identical and each U-Net is composed of an encoder that downsamples input images, followed by eight large kernel convolutional attention blocks, and a decoder that upsamples the image back to its original size. In addition, an adversarial learning algorithm with local and global discriminative networks is used to train the proposed framework to obtain OBI inpainting results. Compared with state-of-the-art image inpainting methods, our experimental results show that the proposed method can achieve the best inpainting results in OBI images; in particular, the method is also suitable to handle the large-area mask tasks.
Reconstruction of Rainfall Patterns with the SpVAR Method: Spatial Analysis in DKI Jakarta

Unexpected rainfall is often a challenge for urban areas such as DKI Jakarta. Therefore, this study aims to establish a Spatial Vector Autoregressive (SpVAR) model to analyze rainfall data in DKI Jakarta from 2017 to 2021. This study used three endogenous variables: the amount of rainfall, air temperature and humidity. The use of the SpVAR method with uniform spatial weighting in the DKI Jakarta area was chosen to provide an initial picture of the potential for spatial interactions between various locations in a complex climate context. This method provides valuable insight into the possibility of spatial dependence during climate change in DKI Jakarta. The SpVAR (1.3) model is based on the VAR (p) model by limiting the spatial orders to one. Parameters of the SpVAR model (1.3) were estimated using the FIML method to identify significant factors in the influence of rainfall in the region. The results showed that the SpVAR model (1.3) shows that rainfall, air temperature and humidity in one location are affected by the same variables in other locations. However, not all of them significantly affect five areas in DKI Jakarta Province. This study confirms the effectiveness of the SpVAR method in analyzing spatial patterns of rainfall, provides essential insights for understanding climate, and supports decision-making that is more responsive to urban disasters in the future.
Mobilization Economy and the Fastest Learning Possible

The current situation in the world and the economy, as well as the goals facing the country, require a rapid in-crease in production efficiency, building new supply chains, and developing new types of activities. Traditional approaches to training and development of specialists, relevant for the “slow” existence of business, are not sufficient to accelerate all processes to achieve set goals. For the current time, new approaches to fast and ef-fective learning are needed, which can be summarized as a methodology for maximally rapid learning (MRL). The aim of the research is to study different methodologies and tools of fast and effective learning, generaliza-tion of which will make it possible to form the author’s methodology for the fastest learning possible. Document analysis and generalization methods were used in this work. The results of the research made it possible to formulate a basic understanding of the methodology for maximally rapid learning, associated with a set of measures and tools for the implementation of educational tasks.
Exploring the GDP-Education Relationship: A Comparative Study of Developing and Developed Nations

This study investigates the relationship between a country's GDP and the advancement of its education system, focusing on the dynamics in developing versus developed countries. In a multivariate linear regression model, this article used years of schooling as a proxy for educational progress and GDP per capita, among other variables. The analysis of the Barro &amp; Lee Dataset, encompassing 88 countries, revealed a positive correlation between GDP and education, particularly strong in developing nations. The findings imply a ceiling effect, indicating that increases in GDP initially result in significant educational gains, which diminish as GDP continues to growobserved particularly in developing countries. These insights underscore that economic prosperity and educational advancement are interconnected, yet the relationship varies depending on a nation's developmental stage. This study offers a nuanced understanding of the interplay between economic performance and education, which can inform economic and educational policies, especially in developing countries. Policymakers can utilize this research to design strategies that align with their country's developmental context, thus fostering economic growth supported by robust educational advancements. The study's novelty lies in its detailed comparison across varying stages of national development and its potential implications for policymaking.
Learn History Using the Rupiah Currency Utilizing Augmented Reality Technology

Studying history may be very boring for students. This is what makes history learning less effective. Education is an effort aimed at developing personality and abilities for life. In education, students are individuals who are different from other people in a class. This explanation can be seen in terms of ability. Every country must have a national identityTraditional dances in Indonesia are very diverse and have their characteristics. This is because the ethnic groups in Indonesia are very numerous and diverse. With advances in technology, it can be used as an alternative learning solution that is more creative and efficient. Therefore, it is the basis for expanding the application of learning about the history of heroes and dances on rupiah banknotes using the Augmented Reality Marker Training method. It is important to have a useful means of displaying and introducing each national hero featured on a particular currency By utilizing these technological Advances we can visualize images more realistically and in real-time, this is what will attract the interest of users, especially students, to use this application as a medium for learning the history of heroes and introducing regional dances found on the rupiah currency
Time Series Prediction Based on LSTM Neural Network for Gold Prices

Metals like gold have been traded around the world for ages. Gold, the yellow shiny metal, can maintain the stability of the market, disperse the risk of transfer price, and stabilize the national economy. Therefore, the research and prediction of gold prices is not only of great significance to the countries but also of great significance to individuals. However, compared with other financial time series, research on gold prices is still relatively few and lacks models integrated with deep learning. The purpose of this paper is to establish a new model for the time series prediction of gold prices and at the same time to provide new ideas for future financial time series prediction problems. In this paper, a prediction model based on LSTM (long-term memory Neural Network) is proposed by using the time series of large amounts of financial data as experimental data for prediction. The RMSE (root mean square error), which acts as a loss function, is selected to evaluate the accuracy of our prediction model. The model proposed has a good prediction effect on financial time series.
Joint Priors-Based Restoration Method for Degraded Images Under Medium Propagation

The deep learning-based methods have shown promising performance in restoring degraded images such as underwater and haze images. However, the majority of existing methods rely on simplified imaging models, which limits their generalization and applicability in real-world scenarios. To address these issues, we incorporate the imaging mechanism in complex underwater environments to redefine the imaging model for degraded images under medium propagation. We then propose a multi-stage restoration framework that combines model-based iterative optimization methods and deep learning methods. At the same time, to tackle the problem of inaccurate parameter estimation in methods relying on a single prior, we introduce a regularization design based on joint priors and develop an attention-based color correction network to correct color distortions in the degraded images. Experimental results on real-world degraded images demonstrate the effectiveness and superiority of our method in both quantitative and subjective evaluations when compared to state-of-the-art methods.
Application of Blockchain Technology for Innovation in the Education Sector

The utilization of blockchain technology holds immense potential to profoundly influence the field of education in the forthcoming years. This technology has the potential to enhance the security, transparency, and affordability of education. Blockchain technology can be employed to securely and permanently maintain student education records. Implementing this can enable students to monitor their academic advancement and receive acknowledgement for their accomplishments. Employing blockchain technology can issue educational certificates that possess a high level of security and are impervious to counterfeiting. This might facilitate students in securing employment or pursuing further education at an advanced level. The implementation of blockchain technology can enhance the security and dependability of online learning platforms. One way to achieve this is by using blockchain technology to store educational resources, evaluations, and communication between students and educators. Blockchain technology can facilitate the creation of adaptive learning systems that have the ability to customize learning materials and procedures according to the individual requirements of each learner. Blockchain technology has the potential to establish a learning environment that is decentralized and characterized by increased democratic participation. A collective or network comprising diverse stakeholders, including students, educators, and parents, typically oversees this educational setting.
DİJİTAL SINIRLAR ÇAĞINDA ÇEVRİMİÇİ TOPLULUĞU ANLAMAK: NETNOGRAFİ NEDİR?

Netnography is a research method that has emerged in the last three decades and has been widely used and recently expanded into different disciplines. After its emergence in the field of marketing, it has been preferred to be used more with the advancement of technology-human interaction. Netnography, which has an ethnography-based starting point, follows the traces of the culture that people build in the online world. The fact that the culture shared in the online environment is very common and simultaneous with the developing social media applications are the advantages that bring Netnography to the fore. This article, however, covers a short history of netnography over time, where it differs from ethnography on philosophical and methodological grounds, how netnography can be applied, and how it has been used and would be used in some fields of business studies
[Review Article] How Blockchain Technology Gives Birth to Digital Currency: A Comprehensive Review

Blockchain technology has revolutionised old financial institutions and changed the way that digital currencies are used today. This paper examines how the invention of digital currency was made possible by blockchain technology, emphasising the underlying ideas and workings of the new phenomenon. This paper offers a comprehensive review of the several ways that blockchain technology has facilitated the invention, advancement, and wide-scale adoption of digital currencies. It looks at the essential characteristics of blockchain technology, such as decentralisation, immutability, and transparency, and discusses how these characteristics help digital currencies succeed and develop. The review also explores how blockchain technology affects conventional financial institutions, as well as the difficulties it presents and the possibilities it holds for a time when digital currencies completely transform the world economy. This review aims to shed light on the revolutionary potential of this technology and its implications for the future of finance through an extensive analysis of blockchain technology's involvement in the creation of digital currencies.
Implementing HIP Reading Activities and the Enhancement of Reading Skills in Malaysian Secondary Schools: A Literature Review

The Highly Immersive Programme (HIP) was introduced by the Ministry of Education in Malaysian language classrooms geared towards mitigating the prevalent lack of English language skills among English language learners. The goal of implementing HIP into the language learning classroom is to provide students with a more engaging, dynamic and interactive learning environment, as the traditional methods of teaching English were proven to be ineffective. This paper aims to provide a comprehensive literature review on implementing the HIP reading activities program to enhance reading skills among secondary school learners. This paper reviewed nine articles related to HIP activities in the language classroom and five papers related to teaching reading skills. This paper includes the benefits and challenges of implementing HIP reading activities, and the integration of the program into the existing curriculum based on past studies. A systematic literature review was employed to select relevant literature for the paper. The selection involved comprehensive database searches overviewing reading skills and the efficacy of the implementation of HIP. This study proposes that future researchers look into a wider perspective of HIP implementation in the language classroom, impact of the implementation on students' proficiency and to explore the adaptability of technological tools to the HIP program.
Simple Ways to improve Discrete Time Evolution

Suzuki-Trotter decompositions of exponential operators like $\exp(Ht)$ are required in almost every branch of numerical physics. Often the exponent under consideration has to be split into more than two operators, for instance as local gates on quantum computers. In this work, we demonstrate how highly optimised schemes originally derived for exactly two operators can be applied to such generic Suzuki-Trotter decompositions. After this first trick, we explain what makes an efficient decomposition and how to choose from the large variety available. Furthermore we demonstrate that many problems for which a Suzuki-Trotter decomposition might appear to be the canonical ansatz, are better approached with different methods like Taylor or Chebyshev expansions. In particular, we derive an efficient and numerically stable method to implement truncated polynomial expansions based on a linear factorisation using their complex zeros.
The Effect of the Individualized Education Program on Early Reading Ability for Special Needs Students Based on Reading Interest in Inclusive Elementary Schools

This study aims to examine the effect of the Individualized Education Program (IEP) on early reading ability of students with special needs in Inclusive Elementary Schools in Magetan Regency based on reading interest. This study used 2 x 2 factorial design with pre-test and post-test control group design. The samples were selected using a cluster random sampling technique; 35 students were selected as experimental group members, while 37 were selected as control group members. Reading interest scale was used to measure the reading interest of students, and early reading ability was measured using early reading ability test. Two-way ANOVA was used to analyse the hypothesis. The test was performed with a multiple comparison test using Scheffe's method. The results show that (1) there are differences in the early reading ability of students with special needs who are taught by applying the IEP and those who are not; (2) there are differences in the early reading ability of students with special needs between groups of students with high reading interest and low reading interest; (3) there is an interaction between the application of IEP and reading interest in improving the early reading ability of students with special needs.
Classification of Japanese Handwritten Characters Using Biometrics Approach

The following paper presents a solution to the problem of offline recognition of Japanese characters. Minutiae and other features extractable from handwriting images have been used to recognize individual characters. The solution presented by the authors uses minutiae to recognise single Japanese characters. Due to the complexity of this typeface, the solution presented can be used to recognise archaic characters, from old documents or also works of art. Neural Networks and hybrid classifiers based on five basic types of classifiers, i.e., k-nearest neighbour method, decision trees, support vector machine, logistic regression and Gaussian Naive Bayes classifier have been developed for classification. The study was conducted on Hiragana, Katakana and Kanji characters (ETL9G Database). The accuracy value obtained was 99.934%. The authors present what is probably the first algorithm using minutiae to recognize Japanese handwriting.
How Artificial Intelligence Affects School Education

The text examines how the integration of technology and artificial intelligence into school education fundamentally alters classical notions of the role and functions of education held by representatives of various scientific disciplines. The literature review is structured around the following research questions: 1) How do technology (including artificial intelligence) reshape the sociologist Emile Durkheim's thesis on the authority of the teacher and their role in the socialization of students?; 2) How does the presence of "superintelligent" technology relate to psychologist Abraham Maslow's theory of motivation and self-actualization?; and 3) How do technology weaken the role of school education in addressing societal inequalities – an idea, advocated by the philosopher John Dewey and his daughter and educator Evelyn Dewey? The report aims to serve as a starting point for future interdisciplinary empirical research in school education, with the goal of finding comprehensive and effective solutions for how technology and artificial intelligence can positively impact school education.
FBi-RRT: a path planning algorithm for manipulators with heuristic node expansion

Abstract This paper is concerned with the problem of collision-free path planning for manipulators in multi-obstacle scenarios. Aiming at overcoming the deficiencies of existing algorithms in excessive time consumption and poor expansion quality, a path planning algorithm named Fast Bi-directional Rapidly-exploring Random Tree (FBi-RRT) with novel heuristic node expansion is proposed, which includes a selective-expansion strategy and a vertical-exploration strategy. The selective-expansion strategy is designed to guide the selection of the nearest-neighbor node to avoid the repeated expansion failure, thereby shortening the overall planning time. Also, the vertical-exploration strategy is developed to regulate the expansion direction of the collision nodes to escape from the obstacle space with less blindness, thus improving the expansion quality and further reducing time cost. Compared with previous planning algorithms, FBi-RRT can generate a feasible path for manipulators in a drastically shorter time. To validate the effectiveness of the proposed heuristic node expansion, FBi-RRT is conducted on a 6-DOF manipulator and tested in five scenarios. The experimental results demonstrate that FBi-RRT outperforms the existing methods in time consumption and expansion quality.
Improving Productivity with New Digital Toolsets

In Chapter 2, we explored the rapid pace of innovation and various digital tool sets that enhance our comprehension of big data, digital principles, and data manipulation. Building a mentality of acquiring new skills and shedding outdated knowledge is fundamental to being effective in this space. Being comfortable with new digital tools and exploring and practicing with new tool sets should be integral to other day-to-day activities to succeed. In the following chapters, we will apply some simple tool sets to develop a mobile app loyalty solution for the Landis Car Hire case example we discussed in Chapter 2. We will harness the sensor data from Landis Car Hire, as provided in the Appendix, to extract valuable insights regarding the showroom and forecourt facility's staff utilization. By using this data we hope to enhance the efficiency of showroom operations and the performance of our staff.
THE DIFFERENCES OF HEMATOCRIT LEVEL IN IMMEDIATE AND DELAYED BLOOD SAMPLES ON MICROHEMATOCRIT METHOD

Background: Hematology specimen examination should be performed at room temperature in less than 2 hours. Recommended specimen storage temperatures are in the range of 2°- 6°C. However, examining laboratory samples with uncertain storage time and temperature is often delayed. Aims: To determine the difference between the hematocrit values of blood samples examined immediately and those that were delayed for more than 2 hours at room temperature. Methods: This study was conducted from April to June 2023 at the Clinical Chemistry Laboratory of Universitas Bali Internasional. A total of 24 venous blood samples were grouped into three treatment groups that were stored for 3 hours (P1), 6 hours (P2), and 12 hours (P3) at room temperature (18-220C), and one control group was examined immediately. Data were analyzed using the Mann-Whitney U test (α=0.05). The results: Statistical tests showed that the comparison of control with P1 was not significantly different (p=0.313), while the comparison of control with P2 (p=0.003) and the control with P3 (p=0.000) was significantly different. Conclusions: There was no significant difference in hematocrit values between blood samples examined immediately and blood samples delayed for 3 hours. Significant differences in hematocrit values were shown in comparing blood samples examined immediately with blood samples delayed for 6 hours and examined immediately with blood samples delayed for 12 hours.
KEMENARIKAN MEDIA PEMBELAJARAN BERBASIS TEACHMINT PADA MATA KULIAH MANAJEMEN PENDIDIKAN MAHASISWA PENDIDIKAN SEKOLAH DASAR

The aim of this research is to evaluate the feasibility, usefulness and efficacy of Teachmint-based learning resources in the Unimed PGSD Department of Educational Materials Management course using classroom management strategies. The ADDIE model—analysis, design, development, implementation, and evaluation—was used in this research and development project. In terms of product validity, the results of data revision and validation from media experts obtained a percentage of 84.35 in the very feasible category, while data validation findings from material experts obtained a percentage of 73.21% which was included in the feasible category. In terms of beauty, 91.60% of the results met the very attractive criteria. In terms of efficacy, students scored an average of 57.6 before the test and an average of 88.8 after the test. The results of the average value show that there are factors that influence the use of Teachmint-based learning resources.