Reviewerly/exHarmony huggingface dataset:
Shift-rotation absolute measurement method for irregular aperture optical surfaces based on deep learning

Absolute measurement technology has received considerable attention in the field of optical metrology owing to its high accuracy. However, to ensure accuracy of measurement, the traditional method requires the use of expensive high-precision stages and considerable time for the precise adjustment of the measured surface. A shift-rotation absolute measurement method for irregular aperture optical surfaces based on deep learning is presented here. In this method, the measured surface needs to be tested in the original position and two randomly changed positions. Furthermore, a simple and effective shift-rotation prediction convolutional neural network that can learn the mapping relationships between the binarized images of the changed position and shift-rotation is designed. The shape of the measured surface with an irregularly shaped aperture is obtained by fitting orthogonalized Zernike polynomials. Compared with the current absolute measurement method for irregular apertures, this method is highly efficient and cost-effective for adjusting the measured surface. The simulation and experimental results demonstrate the accuracy and validity of this approach.
A Novel Approach to Classify English Handwritten Character Using Convolutional Neural Networks

This paper proposed a methodology for offline Handwritten English Character Recognition (HECR) using a deep learning approach i.e. Convolutional Neural Network (CNN). CNN have capability to extract patterns from image data and then perform classification. Char74k dataset is used for model training and validation. Image pre-processing is applied for cleaning of raw dataset and to remove unwanted features. The proposed HECR system performs quite well yielding higher levels of recognition accuracy compared to the systems employing the traditional methods of feature extraction.
Analisis Usability Sistem Komputerisasi Haji Terpadu Palembang Menggunakan Metode System Usability Scale (SUS)

The Palembang Integrated Hajj Computerized System which is currently used as an information system for Hajj and Umrah pilgrims, because the entire data processing process for the purpose of making Hajj documents such as passports, departure and return flights, banking and biodata of prospective pilgrims refers to the integrated computer system. Both internally and externally there has never been an evaluation, either at the time of design, manufacture or implementation. This research was conducted with the title "Usability Analysis of the Palembang Integrated Hajj Computerized System Using the System Usability Scale (SUS) Method". Aims to measure the level of usefulness of the Palembang Siskohat Application and test the validity and reliability using SPSS 24. System Usability Scale (SUS) With 16 questions as a benchmark for assessing the application. 30 respondents were selected among the administrative staff of the Hajj and Umrah pilgrims in Palembang. The results of the usability test showed the value of Learnibilty 4.68, Efficiency 4.46, Memorabilty 4.64, Error 3.34 Satisfaction 3.74, the average usability value was expressed by Very good reliability and validity on each variable indicate that the questionnaire for each variable has a fairly good level of reliability.
Prediction of Mineralization Prospects Based on Geological Semantic Model and Mobile Computer Machine Learning

Mineral resources are indispensable in the development of human society and are the foundation of national economic development. As the prospecting target shifts from outcrop ore to concealed ore, from shallow to deep, the difficulty of prospecting becomes more and more difficult. Therefore, the prediction of mineralization prospects is of great significance. This paper is aimed at completing the prediction of mineralization prospects by constructing geological semantic models and using mobile computer learning to improve the accuracy of prediction of mineralization prospects and expanding the application of semantic mobile computing. We use five different semantic relations to build a semantic knowledge library, realize semantic retrieval, complete information extraction of geological text data, and study mineral profiles. Through the distributed database of mobile computing, the association rules and random forest algorithm are used to describe the characteristics of minerals and the ore-controlling elements, find the association rules, and finally combine the geological and mineral data of the area and use the random forest algorithm to realize the prospect of mineralization district forecast. The geological semantic model constructed in the article uses the knowledge library for associative search to achieve an accuracy rate of 87.9% and a recall rate of 96.5%. The retrieval effect is much higher than that of traditional keyword retrieval methods. The maximum value of the posterior result of the mineralization prospect is 0.9027, the average value is 0.0421, and the standard deviation is 0.1069. The picture is brighter, and the probability of mineralization is higher.
Traffic4D: Single View Reconstruction of Repetitious Activity Using Longitudinal Self-Supervision.

Reconstructing 4D vehicular activity (3D space and time) from cameras is useful for autonomous vehicles, commuters and local authorities to plan for smarter and safer cities. Traffic is inherently repetitious over long periods, yet current deep learning-based 3D reconstruction methods have not considered such repetitions and have difficulty generalizing to new intersection-installed cameras. We present a novel approach exploiting longitudinal (long-term) repetitious motion as self-supervision to reconstruct 3D vehicular activity from a video captured by a single fixed camera. Starting from off-the-shelf 2D keypoint detections, our algorithm optimizes 3D vehicle shapes and poses, and then clusters their trajectories in 3D space. The 2D keypoints and trajectory clusters accumulated over long-term are later used to improve the 2D and 3D keypoints via self-supervision without any human annotation. Our method improves reconstruction accuracy over state of the art on scenes with a significant visual difference from the keypoint detector's training data, and has many applications including velocity estimation, anomaly detection and vehicle counting. We demonstrate results on traffic videos captured at multiple city intersections, collected using our smartphones, YouTube, and other public datasets.
Saratov Writers Literary Museum at the Central City Library

The Literary Museum of Saratov Writers established at the Central City Library is the memorial center and, at the same time, it is to reflect current trends in the books of Saratov authors. The concept was conceived within the partnership of the Library and Saratov Regional Union of Russian Writers. The museum provides educational and cultural services, offers tour of its exhibitions and uses information technologies: maintains its e-catalog, provides online services, digitizes and publishes books by Saratov authors on the website of the Central City Library.
Indistinguishable Photons from a Single Molecule under Pulsed Excitation

Quantum light sources are crucial for the future of quantum photonic technologies and, among them, single photons on-demand are key resources in quantum communications and information processing. Ideal quantum emitters providing indistinguishable photons in a clocked manner, negligible decoherence and spectral diffusion, and with potential for scalability are today still a major challenge. We report on photostable and indistinguishable single photon emission from dibenzoterrylene molecules isolated in anthracene nanocrystals (DBT:Ac NCs) at 3K. The visibility of two-photon interference is preserved even when they are separated more than thirty times the excited-state lifetime, or ten fluorescence cycles. One of the advantages of organic molecules is the low-cost mass production of nominally identical emitters, that also allow for on-chip integration. These aspects combined with high spectral stability and coherence make them promising for applications and future quantum technologies.
Semantic matching of State Rubricator of Sci-tech Information and OECD headings

The study was completed to solve the problems of information compatibility and integration of subject subspaces into the single one and information retrieval from heterogeneous resources classified within different classifications of sci-tech information. Based on intellectual analysis and classification synonymity achieved through semantic mapping of hierarchy branches, the tables of SRSTI-OECD headings interreflection were designed. The mapping tables are supplemented with indices comprising Russian-English and English-Russian keywords and word combinations to classify OECD subject domains. The statistics of defined semantic matches distribution of classification numbers in SRSTI thematical classes is included. The SRSTI-OECD «adapter» (semantic links between the classifications and two-language subject indices) makes the component of the single network of interrelated classification systems being developed at the Russian National Public Library for Science and Technology
Efficient Task Scheduling Technique under Batch Mode Heuristic for Cloud Environment

From solving complex computational problems to huge data intensive tasks, Cloud Computing is emerged as one the growing technology. It is not restricted to hand out gigantic problems but also gratifying day to day clients with variable requirements. To accomplish such a variety of users, Cloud always required an efficient task scheduling to cater such dynamism. So, this paper presents a scheduling technique named Efficient Task Scheduling technique under Batch Mode Heuristic for Cloud Environment (ETSBMH) that mapped cloudlets in an efficient way to reduce the makespan along with a new type of metric that depicts variation among heterogeneous virtual machines completion time. We named it Machine Makespan Aware Completion time Variation (MMACV) that considered completion time variation among machines with respect to makespan. Results reveal the effectiveness of proposed technique from on hand approaches in terms of reduced makespan, less MMACV and improved average machine utilization rate.
The Changing Landscape of Government Budget and Treasury Operations with IT as Key Driver

Beginning late 1980s, as the winds of liberalization started sweeping the country, the first generation of applications to automate the functions in the finance domain started taking shape. Early efforts were focused on capturing data to create databases and use these for the generation of information systems. As computers started becoming ubiquitous in government offices, the functionalities of these applications were enhanced to automate functions and facilitate users to perform repetitive tasks that were hitherto completed manual. Thus, the automation of key functions such as obtaining estimates from spending units, compiling the budget, distributing funds, processing bills, and monitoring of expenditure to ensure optimal utilization and adherence to budget led to the digital transformation of the sector. This chapter covers some of the key digitalization interventions in the finance domain by the central government. The section on budget computerization highlights the journey of its evolution from stand-alone to a web-based system encompassing all its functionalities, that is, capturing estimates from line ministries/departments, compiling budget documents, preparing detailed demands for grants, and the like. The chapter further details other key initiatives, namely, accounting and expenditure management, non-tax-revenue collection, pension accounting, and employee benefits payments initiatives. The chapter attempts to present a holistic image of the impact that has been delivered by these transformation initiatives and vision for the future by harnessing the data captured over the years by using analytics and leveraging other emerging technologies such as artificial intelligence and blockchain.
Humanism and language pride in learning Indonesian language and literature at school

The essence of education is to humanize humans. For this reason, learning activities must be designed to humanize all parties involved in the learning. The purpose of this study is to describe the learning design that can shape humanism and language pride in Indonesian language learning. The research method and data analysis used descriptive qualitative. The research is literature study with normative studies. Based on the analysis, it can be concluded that learning Indonesian Language and Literature can be designed to instill the values of humanism. With these values of humanism, it is hoped that they will be able to foster a proud attitude towards the Indonesian language. Humanism in Indonesian language learning can be conveyed through cooperative learning activities in the form of interactions that exist between teachers and students. Through these learning activities, it will foster an attitude of pride towards the Indonesian language.
Digitalization of teaching and learning

The Covid-19 pandemic marked a transition in digital teaching. In a short while, higher education had to adopt digital learning processes. This contribution highlights challenges and achievements in a subjective way, based on my own practical insights during the pandemic. Against this background, four major findings can be identified. (1) The rapid transformation toward digital learning leaves a significant amount of students behind, but others benefit from the increase in flexibility and self-organization digital learning provides. (2) Collaboration among students is essential for the learning process but has to be organized. (3) Tools that resemble traditional forms of teaching are well received; new forms of teaching and learning that increase collaboration and interaction but also workload for students are less accepted. (4) Digital teaching fosters the already existing process of work intensification, dissolution of boundaries of work, and an increase in multitasking for the teaching staff.
Research on the Introduction of Multimedia Database in Computer Aided English Courseware Using Information Technology

How to use information technology to introduce Chinese culture into English classrooms, eliminate Chinese cultural aphasia, and make up for the cultural shortcomings of students in international exchanges, is an urgent problem faced by higher vocational English teaching. By expounding the phenomenon of Chinese culture aphasia and analyzing the reasons, with the help of information technology, it explores the implementation path of introducing Chinese culture into higher vocational English teaching from three aspects: curriculum reform, teaching practice, and education evaluation. At the same time, we designed a new design method and implementation result of using multimedia database technology to realize computer-assisted teaching system. The system has enhanced query and interactive performance, good scalability, is conducive to teaching students in accordance with their aptitude, and is easy to popularize and use on the Internet. Teaching practice shows that the English learning atmosphere formed by the integration of rich Chinese cultural elements with the help of information technology is conducive to cultivating students’ cross-cultural communication skills, enhancing cultural literacy, and strengthening cultural self-confidence.
Video Codec IP using Discrete Wavelet Transform

In today’s world, due to the ongoing pandemic, all our interactions have been restricted to occur from behind screens. Thus, our use of online streaming services, e-lectures, and video conferences have increased manifold and there is a strong need for better video and image compression techniques that can compress data while maintaining a good level of image quality. In our paper, we attempted to find the best transform and encoding method to provide a decent compression while retaining the quality. First, we attempted to gain a thorough understanding of current compression algorithms and their flaws, while also considering a new approach to compression in the form of Wavelets. To get better results, we used different versions of compression techniques on different sections of the files. Once a proper working design was established, the design was to be converted to a model which could be easily translated to a machine level language by an Electronic Design and Automation tool like Xilinx Vivado and HLS. We then tried parallelising some of the loops and blocks in our code to achieve a speed up of around 2s. The decoded frame we obtained seemed to resemble the initial frame to a good extent and for comparison with other compression algorithms, various metrics were considered. Finally, the Peak Signal-to-Noise Ratio and Compression Ratio were determined and the results were tabulated and we were able to achieve a CR of 21.85 maintaining a SSIM of 92.17% with PSNR 24.9dB
Proposal of a Low-Cost Refuge Management System using OS Booting by External Storage

In the past large-scale disasters, it took a considerable amount of time to collect information on victims at an evacuation shelter, and it was difficult to quickly summarize the relief needs of the victims. In order to solve these problems, a refuge management system (RMS) using information and communication technology has been proposed. However, when introducing RMS developed in the past to neighborhood associations and residents' associations in general areas, the introduction cost is considered to be the biggest barrier. In order to solve this problem, we propose a system that can be operated as RMS by connecting an external storage device to a personal computer (PC) that is no longer used and booting an operating system (OS)from the storage device.
MAGNET Architecture Optimization on Multi-Label Text Classification

Text classification is an essential and classic problem in natural language processing. Meanwhile, multi-label text classification categorizes each text into one or several categories, where this problem is in sentiment analysis, information retrieval, news topic classification, and spam detection. MAGNET is a deep learning model architecture that combines Graph Attention Networks, BiLSTM, and BERT embeddings. Label clustering can solve the MAGNET architectural problem in dealing with a large adjacency matrix by splitting the adjacency matrix into several clusters. In addition, XLNet and GRU have been shown to have better performance than BERT and LSTM in other studies. Therefore, XLNet can replace BERT as the embedding layer, and GRU can replace LSTM as the fine-tuning layer. We propose MAGNET C-GAT and MAGNET C-MODEL as model architectures to overcome the shortcomings of MAGNET architecture by clustering the labels and then splitting the Graph Attention Networks or model into several clusters based on the label’s cluster. The results show that both proposed architectures produce the same or better performance than the MAGNET architecture.
THE STUDY OF THE READINESS OF PRIMARY SCHOOL TEACHERS TO PLAN THE CONTENT OF EDUCATION IN THE CONTEXT OF THE TRANSITION FROM INFORMATIZATION TO DIGITALIZATION

The article is devoted to the problem of digitalization, which currently occupies a central place at the global level, since in today's rapidly changing world, accelerated rates and changes in the field of technology can be taken into account not for years, but for months. Today, the main goal of digitalization of education in the republic is to improve the quality of education, the formation of digital competencies of students based on the creation of a unified educational information environment using digital learning technologies. In this regard, the modern education system of the country can be considered as a dynamically developing system aimed at harmonious integration into the world educational space. This, in turn, is accompanied by changes in the content structure of the teaching technology and significant changes in the pedagogical theory and practice of the educational process, which contribute to mastering the constantly dynamically developing didactic capabilities of ICT and the harmonious entry of the child from primary school into the developing information environment. Observation, research of the work of students and teachers and the responses received to the survey prove that the rational use of digital educational resources in everyday practice contributes to improving the efficiency, effectiveness and productivity of the learning process. In addition, digital technologies help to improve relationships, increase the responsibility of students and teachers for learning, achieving success. The authors, analyzing the course of the transition from the period of informatization to the current period of digitalization, by introducing the first computer technologies into the educational process of primary classes, tried to reveal its positive and negative aspects, to determine the readiness of primary school teachers to plan the content of education in the information educational environment. Along with providing the author's position on the basis of an analytical analysis of research works of domestic and foreign scientists on the topic of research, the objective and subjective factors influencing the transition from informatization to digitalization of modern primary schools are revealed.
Remote Usability Testing of Tour Guide Application

Many Indonesian people travel to visit several areas in Indonesia. Most of them require assistance with tourism information and services. Therefore, PT XYZ developed a tour guide application to facilitate travelers to find information from tourism service providers. Usability testing is essential to evaluate the application by assigning several tasks to the user. This paper presents our work in remote usability testing of the application. This test was conducted by involving 15 test participants divided into three groups based on their age ranges. These ranges are age groups of 20–29 years, 30–39 years, and 40–49 years. We measure four usability aspects, which are learnability, efficiency, error, and satisfaction. The first three aspects are performed by giving the test participant several tasks to complete. Meanwhile, the satisfaction aspect is evaluated with System Usability Scale (SUS) questionnaire. The usability testing results indicate that all user in all age range complete the tasks and the defective rate is below the average standard. For the efficiency aspect, our test shows that participants’ efficient time to complete the task is 0.061 goals/sec. From the results of the SUS score, we found that this application is acceptable for all user age in range.