Reviewerly/exHarmony huggingface dataset:
Blockchain for baccalaureate examination sheets protection in Iraq

&lt;span lang="EN-US"&gt;Due to their unique qualities, including data integrity, security, decentralization, and dependability, blockchain technologies have drawn a lot of interest from both academia and business. In order to effectively handle the adoption problems of blockchain technologies, it is important to identify what influences their use and adoption. In order to protect the exam sheet (as image format) for the baccalaureate examination in Iraq. This paper article sought to construct a private blockcahin powered by a variety of algorithms, After that, with this concern about privacy and fear of private information leaking, and in order to ensure that that image will only be seen by the specific person you want, the technology is full of many encryption features that achieve this end, we encrypt the image before sending it as a transaction in the Blockchain network. Also, we obtained speed smart contact verifications compared with traditional systems due to the proposed system is private and has simple complexity.&lt;/span&gt;
Web-Based public health center management information system using Codeigneter and Ajax techniques at Public Health Canter

Introduction: The development of science and technology at this time, especially in computerization, has developed rapidly. Computers are beneficial in completing various fields of work because they can save time and money to provide satisfactory results. However, the public health center’s data management process is still manual, and it is ineffective in managing data and time inefficient, resulting in less effective performance. This research aimed to find data and make it easier to create reports or record data, which will be effective in terms of time and management data.
System for Automatic Assignment of Lexical Stress in Croatian

It is very popular today to integrate voice interfaces into IoT devices. The pronunciation and proper prosody of speech play a major role in the intelligibility and naturalness of synthesized voices. Each language has its own prosodic characteristics. In this paper, we present the results of a study aimed at testing the applicability of methods for modelling and predicting the prosodic features of the Croatian language. The extent to which their performance can be improved by incorporating linguistic features and linguistic peculiarities specific to the Croatian language was investigated. In the model learning process, tree classification was used to predict the lexical stress position and the type of stress in a word, and a lexicon of 1,011,785 word forms was used as the model learning set. Separate models were created for predicting the position and type of lexical stress. The results improved significantly after the rules for atonic words (clitics) were applied. A hybrid approach combining a rule-based approach and a modelling approach was also proposed. The final accuracy of assigning lexical stress using the hybrid approach was 95.3%.
A Quantum Machine Learning driven Reliable Resource Allocation Model for Sustainable Cloud Data Center

&lt;p&gt;The exponential growth of cloud computing within the last decade has led to a severe consideration about the power requirement of the cloud data center. However, variations in the computing resource demands and fixed size of virtual machines (VMs) lead to a poor resource utilization, load imbalance, and excessive energy consumption within the data center. Dynamic VM consolidation effectively handles these problems, where VMs are placed on as few physical machines (PMs) as possible. Concurrently, VM allocation must be done strategically by considering various factors of the computing resources for minimal exploitation of them. The high frequency of VM consolidation may lead to the degradation of the system's reliability by assigning VMs to unreliable PMs. A novel Quantum Machine learning driven Reliable Resource Allocation (QM-RRA) model is proposed to address these problems and enhance the data center's reliability. We handle the problem by applying an Evolutionary Quantum C-Not Neural Network (QCNN) unit to forecast future resource usage at the cloud data center. In addition, Quantum Evolutionary Adaptive Algorithm (QEAA) is utilized to optimize qubit network weights. It offers energy saving by minimizing the number of active PMs, maximizing resource utilization, and enhancing the reliability of the overall data center. The QM-RRA model is evaluated by performing experiments on the Google Cluster Data set (GCD). The observed results are compared with the state-of-art methods and shows its supremacy in terms of different performance parameters like resource utilization, power consumption, and the number of active PMs. There is a significant reduction in power consumption and the number of active PMs up to 31.38% and 44.93%, respectively. The enhancement in resource utilization is up to 25.61%, and overall system reliability is 63.35%.&lt;/p&gt;
DEPENDÊNCIA: O CONCEITO E AS GRAMÁTICAS DEPENDENCE: THE CONCEPT AND GRAMMARS

Dependency Grammar has recently gained relevance with the increase of works using its methodology to perform automatic syntactic analysis. They are very productive in terms of syntactic disambiguation, considering the binary arrangement of the trees, and they also have been shown to be much more efficient for automatic parsing (NIVRE, 2005, p.1). With this new demand, Dependency Grammar has become a relevant term in Natural Language Processing works (KÜBLER et al., 2009; DE MARNEFFE and NIVRE; 2019). However, studies related to Dependency Grammars were marginalized compared to the traditional methodology of syntactic analysis, the constituents analysis, which made it difficult to access the theoretical foundation that this type of methodology follows. Considering this, this work intends to make an introductory review of the fundamentals that govern most of the syntactic theories that use the dependency methodology, to make the Dependency Grammar models, as well as the concept of dependency, clearer and more accessible.
Transformer-driven multi-agent deep reinforcement learning based point cloud video transmissions

The point cloud videos, a medium for representing natural content in AR/VR with point clouds, have attracted a wide range of attention for its characteristics and have the potential to be the next generation of video technology. Given the high data volume, the point cloud video raises the challenge of intelligent transmission and resource scheduling in multi-user scenarios under time-varying system conditions. In this paper, we propose a multi-agent deep reinforcement learning (DRL) approach to optimize the expected long-term multi-user QoE and adopt a Field of View (FoV) prediction model with Transformer for high-accuracy FoV prediction. Over the time horizon, the proposed approach learns to select the tiles of the corresponding video in accordance with a proposed well-defined QoE model capable of quantifying users' satisfaction for transmissions in an iterative way. Under various settings, extensive numerical experiments based on real throughput data traces and different computation capabilities data demonstrate that the proposed approach is effective for long-term multi-agent point cloud video transmissions.
Online Subjective Answer Verifying System Using Artificial Intelligence

Abstract: Every year educational institutes conduct various examinations, which include institu- tional and non-institutional competitive exams. Now a day’s online tests and examina- tions are becoming popular to reduce the burden of the examination evaluation process. The online exams include either objective or multiple-choice questions. Nevertheless, the exams include only objective or multiple-choice questions. However, subjective- based questions and answers are not involved due to the evaluation process complexity and efficiency of the evaluation process. An automatic answer checker application that checks the written answers and marks the weighted similar to a human being is more helpful in the current modern era is necessary. Hence, the software applications builtto check subjective answers may be more useful for allocating marks to the user after verifying the answers for online examination.
Virtual Reality Tour Sebagai Media Informasi Pengenalan Gedung Kampus 2 Universitas 'Aisyiyah Surakarta

In this era of modernization, technology is a very important aspect, almost every line of life requires the help of technology to make work easier. Through technology, almost every information in the world can be accessed easily and quickly. The information obtained is not only in the form of text, but it can also be in other forms such as images or photos or videos. One type of photo technology, namely 360-degree Virtual Reality (VR) photos, with Virtual Reality can make someone feel as if they are in the real world through this technology. Making a virtual reality tour with the panoramic image method for the ‘Aisyiyah University of Surakarta Campus 2 serves as a form of campus information media that is displayed in the form of a 360-degree panoramic image. The research method used in this study is the Multimedia Development Life Cycle (MDLC) methodology which is the most appropriate method by emphasizing the 6 stages of development, namely concept, design, data collection, installation, testing, and distribution. The need for making this virtual reality tour uses hardware in the form of cellphones, lenses, panoramic gimbals and laptops as well as software such as photoshop, panoweaver, 3sixty, xampp and sublime text.
Pengaruh Modul Elektronik Terhadap Ketrampilan Menulis Puisi Pada Siswa Kelas VIII di SMP Negeri 4 Muncar

Poetry writing skills are one of the materials that require students to be able to present their written work. Based on the results of observations and interviews at SMP Negeri 4 Muncar, it was found that the eighth grade students had difficulties in writing poetry. Students tend not to be able to distinguish the vocabulary used in poetry and descriptive texts, so that students' work tends to lead to descriptive texts. One of them is the use of inappropriate learning media which affects the limited knowledge of students. In the learning process at SMP Negeri 4 Muncar using print media, namely package books. The use of this textbook is considered less effective in delivering the material, because students do not get real examples of the poem. Therefore, researchers use electronic modules as learning media. This research uses quantitative research with a quasi-experimental design. The samples of this study were students of class VIII B as the experimental class and VIII C as the control class. The data in this study were obtained from the results of the pre-test and post-test of the experimental class and the control class. Data analysis in this study used the SPSS 26.0.0 application. This study aims to measure the effect of using electronic modules on poetry writing skills and to determine the differences in poetry writing skills using electronic modules. Based on the value of the pre-test results of the experimental class, the average value was 62.44 and the average value of the post-test results was 84.26. While the results of hypothesis testing are known to be sig.(2tailed) &lt; 0.000 &lt;0.05, there is an effect of using electronic modules on poetry writing skills in class VIII students of SMP Negeri 4 Muncar.
Perancangan Sistem Informasi Penjualan Busana Menggunakan Visual Basic (Studi Kasus Toko Original)

Original store is a store engaged in the sale of clothing. The fashion sales information system that is being used to manage sales data is still using a manual system, where operational activities have not utilized the existing computer. Storage media is still using books so it is less efficient if there is a problem with the book. So the purpose of this study is to determine the design of a clothing sales information system using visual basic at the Original Store. This information system is designed using the Microsoft Visual Studio programming language and MySQL as the database. The method used is the SDLC (Software Development Life Cycle) method which consists of the stages of planning (Planning), analysis (Analysis), design (design), implementation (implementation), testing (testing) and management (maintenance). For system development method using descriptive qualitative method. As for testing using the Blackbox Testing method. Results to launch a better sales information system. So with the information system can provide information about the stock of goods, sales and reports based on a certain period in order to facilitate the owner in managing inventory.
Penerapan Metode Promethee pada Sistem Pendukung Keputusan Penerimaan Beasiswa

A decision support system is a computer-based system that helps users in the decision-making process. In this study, the authors use the promethee method in the decision support system for receiving scholarships at the Information Systems Study Program, University of Flores. The Flores University Foundation Scholarship is a form of appreciation for the Foundation in helping potential students in the form of finances given in the current semester. This research was conducted by building outranking relations through pairwise comparisons by looking for the values ​​of entering flow, leaving flow and net flow. The stages in the promethee method consist of two main parts, namely the stages of preparation and data analysis. The purpose of this study is to apply the promethee method and build a website-based scholarship acceptance decision support system. This decision support system is designed using the PHP programming language and MySQL database. The type of research used is applied research, while the author's research method uses quantitative methods. The application of this decision support system is expected to facilitate the Study Program in the best decision-making process on receiving scholarships at the Fores University Information Systems Study Program.
Algorithms that Get Old: The Case of Generative Deep Neural Networks

Generative deep neural networks used in machine learning, like the Variational Auto-Encoders (VAE), and Generative Adversarial Networks (GANs) produce new objects each time when asked to do so with the constraint that the new objects remain similar to some list of examples given as input. However, this behavior is unlike that of human artists that change their style as time goes by and seldom return to the style of the initial creations. We investigate a situation where VAEs are used to sample from a probability measure described by some empirical dataset. Based on recent works on Radon-Sobolev statistical distances, we propose a numerical paradigm, to be used in conjunction with a generative algorithm, that satisfies the two following requirements: the objects created do not repeat and evolve to fill the entire target probability distribution.
Virtual Reality Maze: Multiplayer Game for Android Smartphone

When thinking of Virtual Reality (VR), people often think of a realistic open scene virtual world where players can do anything their hearts desire. Unfortunately, not all people can afford to buy the best VR equipment such as HTC Vive, Oculus Rift and PlayStation VR. The cheaper option such as Android VR Box tends to give its user a very basic VR experience where there can only look around and have little or no interaction with the VR environment while the expensive option allows players to freely interact with objects in the game. The aim of this project is to develop a VR maze game that can provides a player with better user experience while playing game using a VR headset and a smartphone. This project’s developments processes include study about VR and its implementation integrated with accelerometer and Bluetooth controller to make interactive and more immersive android VR maze game. User testing is also done to evaluate the player’s playing experience on this game. The outcome from this project show that most of the respondents are able to understand how to move their character and interact with objects in the game developed without the needs of further explanation.
Implementation of Design Thinking for Web Based E-Voting Student Organization in Nahdlatul Ulama University of Yogyakarta

Purpose: implement design thinking for web based E-Voting Student Organization in Nahdlatul Ulama University of YogyakartaDesign/methodology/approach:the method which used in this research is design thinking. The steps in this method are emphatize, define, ideate, prototype, and testFindings/result:the development of E-Voting is succesfully made according to user needsOriginality/value/state of the art:E-Voting web-based for student organization in Nahdlatul Ulama University of Yogyakarta
Analisys Mortality Rate of Tuberculosis Patients Seen From Age and Length of Treatment at RSUD Dr. M. Haulussy Ambon Using the K-Means Clustering Algorithm for the Rapidminer Application

Tuberculosis (TB) is an infectious disease that causes major health problems in the world by the bacterium Mycobacterium tuberculosis. It spreads through the air when people with TB cough or sneeze. Maluku was in the 10th position with the most TB cases in Indonesia in 2016. Various programs and activities to control TB in Ambon City are carried out, from the process of finding cases, treating patients, health promotions to sputum examination. After that, an evaluation is carried out as an effort to prevent and control to measure the level of success and effectiveness of institutional programs in order to achieve organizational goals. To find out the development of TB cases in Maluku, especially the city of Ambon, the research conducted this time also used the k-means clustering algorithm for the rapidminer application to analyze the death rate of TB patients in terms of age and length of treatment at RSU Dr. M. Haulussy Ambon. The research conducted obtained that the highest number of patients who died were in cluster 1 with an age range of 36-55 years, then followed by the second position in cluster 0 with an age range of 6-33 years, and the last in cluster 2 with a total number of patients. died in the age range of 59-84 years. The length of stay of patients in the hospital varies from half a day to day 21 and is experienced by patients who recover as well as die. The highest patient mortality rate is in the productive age group, rarely does exercise and often engages in active activities and meets many people every day, smoking habits and lack of knowledge about health are the causes of more productive age groups suffering from TB
Pop Up Book Learning Media to Increase Learning Interest of MTsS Alwasliyah Students Bangun Purba

This article aims to increase students' interest in learning mathematics by using pop up book learning media. The research was conducted at MTsS Alwasliyah Bangun Purba class VII. The research method used is a descriptive qualitative method. The instruments in this study are observation sheets and questionnaires of students' interest in learning mathematics. The results of the study obtained that there was an increase in students' interest in learning after the learning process was carried out using pop-up book media.
Data acquisition system of Internet of Things based on Kohonen multi-protocol adaptation

With the development of highway information, according to the actual demand of highway electromechanical equipment management, this paper designs a multi-protocol internet of things data acquisition system to realize instant messaging and data sharing of electromechanical equipment. The Kohonen neural network is used to train the adaptive module of the existing input protocol. According to the eigenvalues of the header, the shaping number of the end bytes and the length of a single packet of the protocol, the function of automatically selecting the appropriate protocol is realized. In the later stage, the ability to learn more protocol adaptation independently can be realized by updating the protocol knowledge base on the internet of things platform. The results show that the average processing time of Kohonen network for each protocol data is about 109ms, and the average recognition rate reaches 95.45%. Kohonen network can be applied in traffic engineering field and realize the conversion of various information data of electromechanical equipment with different protocols into unified information data through protocol conversion rules.
Semi-supervised Multi-graph-attention for Breast Cancer Detection

&lt;p&gt;Mammography is the most widely used breast screening method for early detection and routine monitoring of breast cancer. Most mammogram classification or segmentation techniques are limited to simple binary classifications of the abnormalities in mammograms or classifying specific cropped regions. However, these methods encode merely the texture features of the X-ray-filmed lesions, despite the relationships and patterns. Thus, most of these models have inefficient learning capacities, hindered by supervised learning processes that require extensive annotated data, which is not feasible in the medical domain. To overcome these challenges, we model the deep texture and spatial features of every small segment of the mammogram in a complex multi-graph network.&lt;/p&gt; &lt;p&gt;Moreover, we proposed a semi-supervised mammogram multi-graph attention network (MMGAT) to classify each element into all probabilistic categories. The attention and the dense relationships in the multi-graph network empower the proposed model with significant learning capacities, resulting in a competitive performance outperforming the recent state-of-the-art mammogram classification models. The proposed model can localise every abnormal segment of the mammogram and classify each as a malignant or benign region of a mass or calcification cancerous. The proposed MMGAT requires only 40\% of the data for training to achieve the highest AUC of 0.97 and an F1 score of 0.95 on the publically available DDSM.&lt;/p&gt;
Research on temporal and spatial evolution and influencing factors of children’s programming attention analysis in China: Empirical analysis based on Baidu search index

Children’s programming is widely aroused people’s concern, is a hotspot of research on education, the children’s programming attention to promoting the development of children’s programming education has important significance. Using Baidu index, elastic coefficient, Gini index and geographic concentration coefficient, this paper analyzes the evolution of spatial and temporal distribution and influencing factors of children’s programming attention in China, and establishes the model through panel data model and carries out empirical analysis. The results show that: the public’s attention to children’s programming continues to rise, and is in a gentle stage of development at the present stage. Spatial difference of children’s programming attention is opposite bigger, the eastern region is the most popular children’s programming in the three regions, followed by the, the western region, the internal unbalance in east and west region, the central region in balance, and the central region difference is small, to strengthen the development of the western region to close the gap and balanced development. Regional economic development level and education level have a significant impact on children’s programming attention on the Internet, while educational funds and education level have a significant impact on children’s programming attention in eastern and central China. To improve the development space of children’s programming, we can start from two aspects: strengthening the creation of characteristic learning fields for primary school children’s programming, and improving the wide application of online learning.