Reviewerly/exHarmony huggingface dataset:
Development of Android-based landslide disaster mitigation learning media for disabilities elementary school

The Klaten Regency area is included as a disaster-prone area. One of the disasters that often hit this district are landslides. This increases the risk that human safety is threatened, especially for people with disabilities. This condition will get worse if they do not have education about disaster mitigation. This study aims to develop an Android-based landslide disaster mitigation medium for elementary school disabilities. This media uses three types of software: Kodular to create Android applications, Blender to create 3D animations, construct to make games, and FlipPDF to create e-books. This study used the Research and Development (RD), research method in conjunction with a waterfall process development model. To get the feasibility results, this medium was tested on experts and users, the first being tested on two media experts, with a percentage result of 88.8%, so that it was declared very feasible. The second was tested on two e-book material experts with a percentage of 98.5%, so it was declared very feasible. The third was tested on two video material experts with a percentage of 98.94%, so it was declared very feasible. The fourth was tested on users and got a percentage result of 78.4%, so it was stated that this medium was appropriate.
Deciphering the code of the novel "The Dancing Men"

This study examines a method for deciphering the handwritten dancing men graphic shown in "The Dancing Men." We attempted to reproduce and explain Holmes's reasoning for the graphic cipher by using a mathematical programming approach. Moreover, we studied the validity of Holmes’s reasoning and demonstrated a procedure to decipher the cipher computationally. Herein, we propose a mathematical solution to clarify the ambiguity in Holmes' conjecture. Although the proposed method has not been implemented, its feasibility is confirmed through partial data creation and analysis.
Semantic Enhanced Video Captioning with Multi-feature Fusion

Video captioning aims to automatically describe a video clip with informative sentences. At present, deep learning-based models have become the mainstream for this task and achieved competitive results on public datasets. Usually, these methods leverage different types of features to generate sentences, e.g., semantic information, 2D or 3D features. However, some methods only treat semantic information as a complement of visual representations and cannot fully exploit it; some of them ignore the relationship between different types of features. In addition, most of them select multiple frames of a video with an equally spaced sampling scheme, resulting in much redundant information. To address these issues, we present a novel video-captioning framework, Semantic Enhanced video captioning with Multi-feature Fusion, SEMF for short. It optimizes the use of different types of features from three aspects. First, a semantic encoder is designed to enhance meaningful semantic features through a semantic dictionary to boost performance. Second, a discrete selection module pays attention to important features and obtains different contexts at different steps to reduce feature redundancy. Finally, a multi-feature fusion module uses a novel relation-aware attention mechanism to separate the common and complementary components of different features to provide more effective visual features for the next step. Moreover, the entire framework can be trained in an end-to-end manner. Extensive experiments are conducted on Microsoft Research Video Description Corpus (MSVD) and MSR-Video to Text (MSR-VTT) datasets. The results demonstrate that SEMF is able to achieve state-of-the-art results.
A Deep Learning Approach To Recognizing Emotions Through Facial Expressions

A lot of research has been done over the last few years in the field of facial Emotion recognition (FER) and it is currently a hot topic in both academia and industry. A good way to perceive a user's thoughts and design a good to detect universal facial expressions system. The option to separate different universal facial expressions based on emotional classes makes it feasible to recognize distinct emotions of facial expressions based on the diversity among facial calculations and expressions. Face recognition technology is used extensively today, often in the medical industry, the attendance system, and so on. This work focuses on developing a Facial Expression Recognition (FER) system using CNN. This the model uses Haar cascade classifier for real-time universal facial expressions using a webcam. It was trained using the [FER2013] dataset available on Kaggle to detect facial expressions.
PERANCANGAN APLIKASI REKOMENDASI OBJEK PARIWISATA KOTA PEKANBARU BERBASIS ANDROID MENGGUNAKAN LOCATION BASED SERVICE UNTUK DINAS PARIWISATA KOTA PEKANBARU

Tourists who visit the city of Pekanbaru not only come from within the country, but also from abroad. To provide services to people inside and outside Pekanbaru City, the Pekanbaru City Tourism Office currently has an official website as a medium to convey information about tourist attractions in Pekanbaru City. On the website, there is already a list of tourist attractions in the city of Pekanbaru. This research will develop applications that can be used by tourists who will visit tourist attractions in Pekanbaru City. Applications developed based on Android will provide recommendations for tourist attractions that are around application users by utilizing the Location Based Service feature. The application will also be equipped with a map and use the BellmanFord algorithm to get the shortest route to that location. It is hoped that the application generated from this research can be used as an alternative media that can be used by the Pekanbaru City Tourism Office in order to provide the best service for people inside and outside Pekanbaru City.
Progress in the Application of Mathematical Algorithms in Materials Science

As materials are the direct drive for scientific development and social progress, the research on their structure and properties has always been a research hotspot in materials science.At present, the discovery of new materials is mainly carried out by the researcher's intuitive judgment of materials and a large number of "trial and error" experiments, which is inefficient and difficult to effectively discover a large number of possible new material combinations.Materials science has long relied on two major means of experiment and calculation.The machine learning-based mathematical algorithms offers a new research method.This article systematically expounds the common mathematical algorithms and the basic processes of their calculation methods, details the application of mathematical algorithms in material performance prediction and new material design, and gives a summarization and outlook of the challenges and application prospects concerning their application in materials science.
A Study on the Contents of Time Expression Education in Elementary Grammar Education

Objectives This study was conducted to explore issues that should be considered important in realizing the educational content of the elementary school time expression achievement standards newly established in the 2022 Korean language curriculum.. Methods First, in order to clarify the orientation of elementary school time expression education in the 2022 Korean language curriculum, the 2007 and 2015 Korean language curriculum and the 2022 Korean language curriculum were compared. In addition, in order to explore the issues of educational content development, the upper category of time expression, grammar element achievement standards, were analyzed in textbooks that were previously implemented. Finally, elementary school Korean textbooks were also analyzed to illustrate language materials that can be used for time expression education. Results Through curriculum analysis, this study confirmed that the orientation of time expression education in the 2022 Korean language curriculum was significantly different from that in the 2007 Korean language curriculum. In particular, the 2022 Korean language curriculum focused on “language as use, language dynamics, and various aspects of language” and emphasized “discourse and context.” In addition, I argued that time expression education should be implemented with an appropriate hierarchy between height expression and passive expression education through textbook analysis. In addition, the possibility that elementary school time expression education can be linked to literature or reading/writing was confirmed. Specifically, it was exemplified that time expression also contains an expression effect in texts that can be treated at the 5th grade level of elementary school. Conclusions In the 2022 Korean language curriculum, elementary school time expression education should be implemented in delicate consideration of its orientation, hierarchy, and connection. In addition, in order for elementary school time expression education to be implemented as intended, research on learners' use of time expression is necessary.
Research on relay protection inspection method based on operation information

Through data analysis and method research on online detection of relay protection, the decision tree is used to carry out fault diagnosis on the alarm information of secondary equipment, and based on the operation information, the evaluation of relay protection status and auxiliary maintenance decision are realized. For items that cannot be inspected during the inspection cycle and items that are found abnormal, a complete detection system is formed by means of continuous power transmission.
Improved deep convolutional dictionary learning with no noise parameter for low-dose CT image processing

Background: Low-Dose computed tomography (LDCT) reduces radiation damage to patients, however, the reconstructed images contain severe noise, which affects doctors’ diagnosis of the disease. The convolutional dictionary learning has the advantage of the shift-invariant property. The deep convolutional dictionary learning algorithm (DCDicL) combines deep learning and convolutional dictionary learning, which has great suppression effects on Gaussian noise. However, applying DCDicL to LDCT images cannot get satisfactory results. Objective: To address this challenge, this study proposes and tests an improved deep convolutional dictionary learning algorithm for LDCT image processing and denoising. Methods: First, we use a modified DCDicL algorithm to improve the input network and make it do not need to input noise intensity parameter. Second, we use DenseNet121 to replace the shallow convolutional network to learn the prior on the convolutional dictionary, which can obtain more accurate convolutional dictionary. Last, in the loss function, we add MSSIM to enhance the detail retention ability of the model. Results: The experimental results on the Mayo dataset show that the proposed model obtained an average value of 35.2975 dB in PSNR, which is 0.2954 –1.0573 dB higher than the mainstream LDCT algorithm, indicating the excellent denoising performance. Conclusion: The study demonstrates that the proposed new algorithm can effectively improve the quality of LDCT images acquired in the clinical practice.
Privacy protection method for blockchain transaction data based on homomorphic encryption and zero-knowledge proof

All users have access to the details of all transactions through the public ledger thanks to the distributed characteristics of the blockchain. However, attackers may infer the identities of the parties through detailed transaction data, and impair the privacy of users. Among these data, the transaction value is one of the most important transaction data. Therefore, for the privacy protection during blockchain transactions, this paper, based on the homomorphic encryption technology, enabled the committer peer to update the ledger during the transaction without knowing the balance of the parties’ accounts and the transaction value. Meanwhile, the zero-knowledge proof scheme was introduced. It was proved by interval range that the committer peer can verify the validity of the transaction without knowing the transaction value.
A practical case of differential equation solution

Differential equation has a wide range of applications in real life, and it is also an important branch of higher athematics. Through the explanation of practical cases, this paper introduces how to solve practical problems through the idea of mathematical modeling. At the same time, the numerical solution of the equation is obtained by combining MATLAB, and the purpose of combining theory with practice is achieved.
Haidilao’s Business Performance Comparison Analysis on Condition of COVID-19

The outbreak and continuation of the pandemic have hit many industries fiercely. In such a situation where the future of enterprise development is not clear in the stage of the global economic downturn, it is crucial to study the root causes and influences, thus summarizing them to find new development opportunities. In this paper, we study the operating conditions of the catering industry before the pandemic and we analyze the impact that COVID-19 brings after 2019. Also, the latest situation has been studied. In addition, we use a case study as our research method and the effort we made reveals that the restaurant industry is still a thriving and flourishing business although it has gone through some ups and downs during the pandemic, it has significantly increased a new way of selling which is online ordering. In addition, there are pieces of advice mentioned in this paper that we hope to contribute to this issue.
Quantum Tant-Fant

Objectives:The Tant-Fant finds its origin in Bengal, India.The original game hereby referred to as the classical game has two players.To develop a basic understanding in the reader's mind, the paper describes the rules and strategies for playing Tant-Fant in detail.The classical game board can be drawn on paper, played on board, or a web reference available.Methods: In the classical version, players ought to have three pieces aligned in a row termed as a three-in-a-row either horizontally, vertically, or diagonally but not on the players' initial position also termed as the home row.Alternatively, the players can make specifically a diagonal three-piece alignment also termed a diagonal three-in-a-row.Findings: QTF uses the counter-intuitive principles of quantum superposition and collapse to design new moves.The players may choose from either of the two quantum moves, QM1 and QM2 which are equivalent to placing a superposition of pieces in different squares.Novelty: The quantization of a given game use fewer steps in comparison to classical computation, bringing out previously non-existing strategies for game playing and for tackling more and more complexities in the game.Quantum computers are finding potential applications in almost every field of life.As the quantization of many classical games has already been achieved, the quantization of a lost traditional game would be an interesting feat to achieve.
Practice of developing the creativity of a future primary school teacher in modern e-learning environment with the help of virtual reality technologies

The research paper is focused on revealing the possibilities of developing the creativity of future primary school teachers in e-learning environment with the help of means and technologies of virtual reality. The notion ‘teacher’s creativity’ has been defined in the article and the basics of vocational training of the creativity of future primary school teachers by VR-means within the digitalization of education have been described. In the modern context of training a creative teacher the VR-means and technologies become to be actual and obligatory for teacher’s professional development. The study is novel in that the authors have practiced the VR-technology for developing the creativity of future primary school teachers within their pedagogical training which allowed to define the features of using modern digital means in the process of pedagogical education of future teachers. As a result, the efficiency of using VR-technology in practical realization for developing the creativity of future primary school teachers have been proven.
Sistem Informasi Raport Online Berbasis Web Pada SMK Negeri 1 Slawi

The work system of teachers and staff of SMKN 1 Slawi still uses a conventional system that has the risk of errors in data input, besides that conventional data input also takes a long time to process. The design of the E-Raport Information System for SMK N 1 Slawi is a web-based information system created to facilitate and speed up teachers and staff in inputting data and assessing and evaluating students' learning from data input to printing report cards. The design of the E-Report Card Information System is expected to change the way teachers work from a conventional work system to a digital work system. In addition, the design of the e-report card information system aims to minimize errors in inputting data and student scores. The web-based E-Report Card Information System is designed using the SDLC (System Developmen Life Cyce) development system which carries out the research process using the waterfall method. Meanwhile, the software model carried out in the preparation of this research uses a programming model. The language used for this research is to discuss CSS programming, PHP, Java Script, HTML, Font Awesome, Data Tables, Boostrap and the databases used are MySQL and MariaDB databases
Analysis of the Furniture Industrial Panorama, in Brazil, in Relation to the Adoption of Industry 4.0 Technologies

The furniture industry is a traditional segment, with a global presence, and as in other markets and segments, globalization has contributed to creating an environment of fierce competition between small, medium and large companies. China, the European Union and the United States are the biggest producers and also the biggest consumers of furniture products. Brazil is also included in this market, but with lower production and consumption volumes. The objective of this study is to analyze panorama of the furniture industry in Brazil and abroad, in relation to the adoption of industry 4.0 technologies to foster new working conditions and productivity. In this work, authors opted for the format of reflective theoretical essay, based on the result of systematic review of literature, performed in Scopus, in February, 2023, employing keywords “Furniture manufacturing” and “Industry 4.0”, with any other restrictions. Only 47 articles were published in this timeline. Analyzing these articles was evidenced that main obstacles to the adoption of technologies I4.0 is related to the insufficient proofs of the advantages and benefits that these technologies may provide for furniture manufacturing process, lack of the awareness of the employees to enable internalization of knowledge about technologies of 4.0 industry. To accomplish this will be necessary to perform actions to establish collaborative networks, both internal and external, to validate the new organizational practices/ routines, and consolidate its adoption in the manufacturing environment. As conclusion of the study is possible to state that the lack of knowledge of I4.0 technologies and their benefits, by workforce and organizational managers also, lack of financing sources and of government policies to foster adoption of technologies I4.0 are among main obstacles to the adoption of the technologies of industry 4.0. Reducing the distance between universities and industries, investing in R&amp;D, using already available and low-cost technologies and adopting proven and established production methods were also highlighted as premises for I4's technologies and that may to succeed in the furniture segment. I4.0 technologies show the potential to maximize productivity and profitability by reducing lead time, operating costs, increasing quality, flexibility of the operational process, in addition to differentiated design.
Redesigning Family Education Media Website Using Design Thinking Method and System Usability Scale

Using educational media today is growing on several platforms, such as websites. Educational media application developers need to pay attention to a good interface so that user interaction with the application runs well and comfortably. One of the website-based family education media is mendadakparenting.com. We evaluate this website to users by paying attention to features and menus that are not yet available. This study aims to improve the design and increase user interest in using family education media as a website. The method we use in this research is the design thinking method. We have considered the choice of this method because it fits the approach to the user. The evaluation technique we use is an usability scale system. In the questionnaire, before the redesign, a score of 65.3 was got, so it was necessary to redesign. Then after we did a redesign with the addition of several features according to user input. The level of convenience based on evaluations to users regarding the design of the family education media website application resulted in a score of 77 with a high acceptance rate, the value scale was B, and it included the adjective rating for the good criteria.
Multi-focus image registration algorithm based on image preprocessing and improved SIFT

Image registration is an important technology in the image processing, which is widely used in computer vision, image fusion, image reconstruction and other fields. To solve the problem of poor image registration due to fuzzy regions in multi-focus images, this paper proposes a multi-focus image registration algorithm based on image preprocessing and improved SIFT. The reference image and the image to be registered are preprocessed by Gaussian smoothing. And then all images are feature extracted and classified. Last, the image is feature matched by bidirectional adaptive threshold algorithm, and finally the registered image is obtained by the registration result. Compared with SIFT algorithm, the number of feature extraction and feature matching of the proposed algorithm increase by 56.57% and 67.43% respectively.
Vulnerability Assessment of Learning Management Systems

This article presents a vulnerability assessment of a class of web applications designed to serve educational coursework to online users. We describe the deployment landscape, the known vulnerabilities institutions must be aware of, and document how nonsupervised deployment puts institutions at risk from cybercriminals.
IBM Attrition Prediction Analysis: Factors That Can Influence the Attrition Rate

This paper aims at solving the high level of attrition rate at IBM. Data scientists would like to measure the relationships between the attrition rate and other descriptive information such as gender, age, working experience and position, to predict the attrition status and look for commons on those who have left or will probably leave the corporation in the future. Based on those predictions, appropriate summaries of their characteristics can be sketched for the manager in IBM to provide better working conditions to lower the rate. The main prediction method in this paper will be tree-based including simple decision tree and other advanced techniques, and the prediction results will be shown as scatter plots. While XGBoost shows the highest performance in this study, it will be selected as the prediction method to predict the attrition status of IBM employees. With such a model, IBM data analysts will be able to do further research on the reasons for attrition and thus lower the attrition rate.