Reviewerly/exHarmony huggingface dataset:
Scene Text Recognition with Transformer using Multi-patches

In this paper, we explore the application of Vision transformer (ViT) to the scene text recognition task. As a popular research direction in computer vision, Scene text recognition enables computers to recognize or read the text in natural scenes, such as object labels, text descriptions, and road text signs. At present, the traditional convolutional neural network-based model has better performance. Still, in the face of complex backgrounds and irregular scene text pictures, the performance of the convolutional neural network-based model is challenging to improve in curved text, diverse fonts, distortions, etc. With the application of transformers in computer vision, the model structure based on transformers has also significantly been developed. Although the current transformer-based model can obtain the performance of the model structure similar to CNN, it is currently in the early stage of application, and there is much room for research and improvement. We propose a multi-scale vertical rectangular patch model (MSVSTR) for transformer-based feature extractor to be more suitable for text images. By only arranging the patches in a single direction, when the image is cropped through the patch, it can be more suitable for the distribution form of the text in the text image. At the same time, to be suitable for different numbers of characters in other texts and more robust feature extraction, vertical rectangular patches of different scales are applied to crop the image. Our structure performs better through various ablation experiments than similar transformer-based STR models. At the same time, experiments show that our structure can perform seven benchmarks well.
Lightweight Deep Learning for Room Layout Estimation with a Single Panoramic Image

In this paper, we present a lightweight deep learning model for room layout estimation. We build on the work in HorizonNet, in which a 3D room is restored from a single panoramic picture using three steps (pre-processing, feature extraction, and post-processing) by studying the efficient computation of the feature extraction part. In contrast to the baseline method that uses a combination of a typical residual network (ResNet) and long short-term memory (LSTM) as its principal architecture, we focus on the use of a platform-aware neural architecture search for mobile applications (MnasNet) and a gated recurrent unit (GRU) instead of conventional LSTM. Subsequently, hyperparameters of the suggested architectures are selected using sampling-based optimization. In our qualitative and quantitative experiments, the lightweight model using the combination of MnasNet and GRU required approximately half as many parameters compared to the original method for competitive performance of room layout estimation. Based on the Manhattan world assumption, the proposed architecture was validated using Stanford2D3D, PanoContext, and our real-world panorama dataset collected by off-the-shelf software in RICOH THETA Z1.
Records in Contexts: a Way to Use it

Records in Contexts is a product of ICA, aiming to replace the four standards of archival description. Since, at its core, it is a conceptual model, it is quite abstract and differes from the familiar guideline style of ISADG, for example. The presentation will focus on aspects of practical implementation of RiC: articulation of descriptions (attributes, relations), results, and the benefits of using RiC in comparision with previous standards.
Professional self-development of future domestic science teachers as a relevant problem in the process of their training

The problem of professional self-development of future domestic science teachers in the process of their training is relevant due to the fact that modern educational institutions need teachers who are able to quickly adapt to sweeping changes and are able to develop independently in the professional field. University training of future domestic science teachers is one of the stages of their professional self-development. The objective of the study is to determine to what extent university training of future domestic science teachers is important for their professional self-development. The objective is achieved through the analysis of regulatory documents, the analysis of scientific research and the results of student questionnaires. The presence or absence of aspects affecting the professional self-development of future domestic science teachers were determined while conducting the analysis of the federal regulatory documents that govern the training process of future domestic science teachers at the university. The analysis was carried out in accordance with the Federal State Educational Standard of Higher Education and the “Teacher” Professional Standard. The Federal State Educational Standard for Bachelor’s and Master’s degrees includes a directive to develop a competence closely related to the professional development of future domestic science teachers – Universal Competence-6 (UC-6). The analysis of the professional standard of a teacher allows us to distinguish two fundamental roles teachers perform at work. These roles indicate those actions, skills and knowledge that are collectively associated with the professional self-development of teachers. The empirical research was carried out on a sample of students (N = 52, aged 18 to 30 years, women = 60%), majoring in pedagogy (44.03.01 Pedagogical Education with the major in “Domestic Science”) at Saratov State University (the city of Saratov). A questionnaire (prepared by N. V. Sayapin) was used to determine to what extent professional self-development is significant. The posi tive dynamics of the parameters of time spent on professional self-development for senior courses has been revealed. There is a consensus among respondents that professional self-development is an integral component of professional growth and part of competitiveness in the profession. The presented empirical materials can be used in creating pedagogical conditions for the implementation of effective training aimed at professional self-development of students.
Integration processes in the education system

The relevance of studying integration processes in the education system is determined by new requirements for the educational environment, which serve as the basis for the further development of the entire system of education. Optimization of integration processes in the education system is specified by their realization principles, which entail “controlled self-organization” of integrated structures in the interests of “the man, society, state”. The purpose of the study is to search for and to justify the methods and means of optimizing integration processes in the education system. The article defines a set of methodological principles. Implementation of this set of principles makes it possible to optimize the processes of integration of the educational subjects and the educational environment as a whole. It includes the systemic, integration, synergetic and acmeological approaches. The study specifies the content and peculiarities of these approaches, presents research data analysis in the context of the issues under discussion. One of the most important results of integration processes in the system of education is the development of the personality and of the person’s role in the “increase” of educational, and also social capital as a significant resource of social development.
A Study on the Reinforcement of Military Practical Nursing English in the Armed Forces Nursing Academy: Focusing on TOEIC and Military Practical Nursing English Scores

Purpose: The Armed Forces Nursing Academy is a special-purpose university that trains nursing officers and has a unique curriculum. In Particular, regarding the English curriculum, KAFNA has TOEIC-centered general Eng-lish education and offers practical English education for military nursing. This study aimed to improve the effec-tiveness of English education at the Armed Forces Nursing Academy. The researcher identified the relationship between cadets' TOEIC scores and military nursing practical English grades, and this study, based on the rela-tionship, proposed a developmental plan for the English curriculum. Method: In this study, to confirm the relationship between general English proficiency and military nursing English skill, this study analyzed 4years of accumulated TOEIC scores and military nursing practical English grades of 298 cadets, including graduates 60th ~ 63rd year of KAFNA to find a relationship. First, the correlation between TOEIC test scores and military nursing practical English grades was examined, and a T-test was used to determine whether there were differences in military nursing English proficiency according to TOEIC test scores. Results: As a result of examining TOEIC scores and military nursing practical English grades of 298 cadets in four years, the 60th year showed a moderate correlation between the TOEIC score and the military nursing Eng-lish grade, and the 61st~63th year showed a weak correlation. Furthermore, in the case of the 60th~62th year, it was found that there was a difference in the military nursing English score according to the TOEIC score, but there was no difference in the 63rd grade. Conclusion: It seemed that TOEIC scores were only partially related to military nursing practical English grades. Therefore, to communicate in the situation of military nursing practice, which has a specialized purpose, it is necessary to increase the proportion of military nursing practice English learning. In addition, complementary methods like increasing offered credits or motivating cadets should provide so that they can take an interest in learning English for military nursing practice.
Korea Provisional Government Police Organization and Activities

Purpose: The modern police of the Republic of Korea today were established in Shanghai on April 11, 1919 by the Provisional Government of the Republic of Korea, and moved to various areas of China for 27 years until the liberation of the country in 1945 for independence movement. In the face of such hardship, the Provisional Government of the Republic of Korea needs to be aware of the police organization and activities of the Provisional Government of the Republic of Korea, which belongs to the Ministry of Interior as head of administration. Method: The Civil Affairs Bureau of the Ministry of Home Affairs, the head of the administration of the Provisional Government of the Republic of Korea, confirmed through literature evidence that Kim Gu was the apex and tried to change the organization while breaking through the crisis. The police organization of the Provisional Government of the Republic of Korea was active in 1919 with the Police Department and Yeong-Tong-je, 1923 with the Police Department, 1941 with the Guards, and with the 1943 with the Police Department, referring to the Baekbeom Ilji, the National History Compilation Committee, the National Police Agency documents, and the Provisional Government of the Republic of Korea data book. Results: The focus of this study is to give the meaning of finding the issue of Police Day and the legitimacy of the police. The result suggested by this study was an opportunity to overcome the dark period of loss of the country signed by the Eulsa Treaty in 1910 by examining the organizational structure of the Police Department of the Korean Empire and the Police Department of the Provisional Government of the Provisional Government in the Joseon Dynasty. Conclusion: It was judged that it could affect the continuity of the current Korean police, and research was conducted. Also, in response to the common truth that 'as long as there is a state, there is a police', the police organization of the Provisional Government did not change its name even during the Japanese imperialism period. It calls for the existence of a police that is directed towards
Selective Algorithm for Expanded Group Method of Data Handling Applied to Power Amplifier Modeling

Power amplifiers (PAs) are electronic devices commonly used in telecommunications that need to transmit information with high energetic efficiency. For this, it is necessary to use data manipulation methods that assist in the linearization of the output signal. Our previous conference paper presented two codes constructed based on the Group Method of Data Handling (GMDH) and which differ in their way of selecting the best coefficients to be used in the calculations of the neural network. The first method, called Embracing, assumes greater availability of data, while the second, called Selective, selects information from the beginning of the code. This work extends the previous GMDH models by expanding the PA inputs into Laguerre basis functions with a single real pole. The comparison among the different approaches employs experimental data collected from a GaN HEMT class AB PA and a Si LDMOS class AB. The most selective and computationally more complex structure, when searching for identification since from the first layers, expresses minor errors and the best results in the output for both Conventional and Expanded GMDH models, becoming a reasoned option for use in PAs. A normalized mean square error (NMSE) of -35.44 dB was obtained by Expanded GMDH with Selective algorithm and 5 inputs when using the GaN PA, whereas a NMSE of -40.35 dB was obtained by the Expanded GMDH with Selective algorithm and 4 inputs when calculated with the Si LDMOS PA data.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing Publishing. • Type of peer review: Single Anonymous • Conference submission management system: Morressier • Number of submissions received: 43 • Number of submissions sent for review: 41 • Number of submissions accepted: 37 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 86 • Average number of reviews per paper: 1.33 • Total number of reviewers involved: 10 • Contact person for queries: Name: Ervin Nurhayati Email: ervin@enviro.its.ac.id Affiliation: Institut Teknologi Sepuluh Nopember
Project Enrich Europeana + and the States Archives in Zagreb : Transcribathon Event

This paper will present the project "Enriching Europeana through citizen science and artificial intelligence - unlocking the 19th century" in which the State Archives in Zagreb is included. The project combines citizen science campaigns and artificial intelligence (AI) in facilitating access to 19th-century handwritten documents not only for researchers but also for students, amateur historians, and the general public. This paper will explain the organization of the project, like the divisions into activities as well as the desired outcomes of each of them. It will also explain the role of all the partners who are involved in the project. As for the States Archives in Zagreb, this paper will describe in detail all the tasks that the State Archives is involved in. The main focus will be on representing the organization of the Transcribathon event. The Transcribathon event serves as a crowdsourcing element of the project. The paper will exhibit elements of the Transcribathon event, the main goals of the event, the targeted group, and the materials on which the transcriptions will be done. Also, it will highlight the importance of the visibility of the archive and its materials for educational and scientific purposes.
Diagnostic Testing of Hematology Analyzer Equipped with WPC Channel Scattergram in Determining Strains of Hematological Malignancies

Determination of myeloid and lymphoid strains of hematological malignancies is often difficult when determination is solely based on morphology. ADVIA hematology analyzer and WPC channels are said to have the ability to differentiate acute leukemia strains. There is no data regarding the diagnostic values of WPC channels in determining the strain of both acute and chronic hematological malignancies. This study aims to analyze the diagnostic value of WPC channels in determining myeloid and lymphoid strains in both acute and chronic hematological malignancies in comparison to immunophenotyping, which is considered as the gold standard in strain identification. Peripheral blood and BMA specimens from patients with suspected acute and chronic hematological malignancies were subjected to immunophenotyping and testing using WPC Sysmex XN-1000 simultaneously. The strains of hematological malignancies produced from the two examinations were then statistically analyzed to determine their sensitivity and specificity. There was a total of 86 samples of hematological malignancies used in this research. With WPC channel-based strain interpretation, results showed that 54 samples were in accordance with the results obtained from immunophenotyping, meanwhile 25 samples could not be interpreted/inconclusive. Inconclusive samples were further analyzed by examining the dominant abnormal population contained in the WPC scattergram, which resulted in a lower number of inconclusive samples, namely 5 samples. After further analysis was carried out on the inconclusive samples, the results of the diagnostic test for WPC channel-based strain identification showed sensitivity of 85.71% and specificity of 91.89% in determining hematological malignancies of myeloid and lymphoid strains, with diagnostic accuracy reaching 91.65% in comparison to immunophenotyping. In conclusion, the WPC channels have the ability determine strains of both acute and chronic hematological malignancies with high diagnostic value in comparison to strain identification using immunophenotyping.
A Comprehensive Study on Code Coverage Analysis for effective Test Development/Enhancement Methodology

The paper describes a tool developed by a team of testing practitioners dealing with a large collection of test suites used for testing Teradata which is large relational database system software. This team has studied the existing database software, available test suites, collected the code coverage data for a large number of available test suites for Teradata and developed an effective Web based Code coverage analysis tool to analyze these Code coverage performance of these test suite while running on Teradata to be able to understand code coverage of these test suites data in various possible dimensions. This activity was undertaken as part of a test engineering initiative to bring in place a set of innovative test engineering practices as potential business value adds.
Research and Implementation of Data Fusion in Obstacle Avoidance Control of Mobile Agent

In complex scenes, the information captured by agents is diverse. How to quickly fuse and analyze data is very important. This paper designs the structural model of mobile agent obstacle avoidance control, and uses the adaptive weighted fusion algorithm to fuse the collected data, so as to lay the foundation for the subsequent mobile agent obstacle avoidance. Finally, the adaptive weighted fusion algorithm used in this paper is compared with the fixed weight weighted fusion algorithm. The simulation results show that the algorithm has better ranging effect and higher accuracy.
EmnDash: A Robust High-Speed Spatial Tracking System Using a Vector-Graphics Laser Display with M-Sequence Dashed Markers

Camera-based wide-area self-posture estimation is an effective method to understand and learn about human motion, especially in sports. However, although rapid spatial tracking typically requires markers, prepositioned markers require extensive preparation in advance, and area projection markers exhibit problems in bright environments. In this study, we propose a system for spatial tracking and graphics display using vector-based laser projection embedded with M-sequence dashed line markers. The proposed approach is fast, wide-area, and can operate in bright environments. The system enables embedding and calibration of M-sequence codes in non-circular vector shapes, as well as rapid image processing recognition. We verified that the accuracy and speed of the proposed approach sufficed through static and dynamic tracking evaluations. We also demonstrate a practical application.
Introduction

Python is versatile language that can be used in many different contexts and for various application development purposes. As such, it is impossible for one to suggest a single setup and development solution that covers all the possible scenarios a developer may encounter. Nevertheless, a number of assumptions and suggestions can be made in this direction, based on some of the most relevant and noteworthy tasks the language may be used for. In this context, the current chapter provides some directions regarding the overall scope and the potential audience of this book, and briefly presents some guidance on setting up a development platform and executing basic tasks that apply to the majority of the subsequent chapters. Finally, it provides a brief overview of the structure of the book and the context of the various chapters, and the organization of the latter into overarching, distinct thematic parts.
Data Analytics and Data Visualization with Python

Python is one of the most popular modern programming languages for data analytics, data visualization, and data science in general. Its power in addressing data analytics problems comes from its numerous built-in libraries, including Pandas, Numpy, Matplotlib, Scipy, and Seaborn, that provide functionality to read data from a variety of sources, clean data, and perform descriptive and inferential statistics operations. In addition, the libraries provide data visualization facilities, supporting the generation of all types of charts. A possible description could be that the term refers to the efficient analysis of data from various sources to produce meaningful results that aid the process of decision-making. The five steps of data analytics and data visualization that are described in detail in this chapter are data acquisition, cleaning data, exploratory analysis, modeling and validation, and visualizing results.
Statistical Analysis with Python

When working with data, one of the main questions one seeks to answer is whether the observed value fluctuations and differences are random or not. If not by chance, what are the key factors that cause such changes, and what are their relationships with the data? Statistical analysis, and in particular inferential statistics, is the key tool for answering these questions. In this chapter, some commonly used statistical functions and the relationship between different types of measurements and statistical tests are introduced, accompanied by demonstrations of how to conduct relevant statistical analysis tasks in Python. The analysis functions follow a linear and incremental order, and build on concepts previously introduced, in order to assist readers with little or no prior experience in this area. For those familiar with the various concepts and functions discussed, this chapter can be used as a refresher or as a practical guide to implementing and executing common statistical functions using the Python platform.
A blockchain based system for multi-level log storage

With the development of the Internet, many log data are generated in the server. How to ensure the security of log data in the server is a problem that needs to be solved. At present, log data storage in most servers relies on a centralized log database or local files. With the increase of running time and scale, there are great challenges in data security and stability. Meanwhile, attackers can tamper with the server's logs to evade tracking. To solve the above problems, this paper proposes a secure multi-level log data storage system based on permissioned blockchain and permission-less blockchain, with high throughput and low cost. In addition, different encryption methods are adopted for different levels of log data to provide higher security