Reviewerly/exHarmony huggingface dataset:
A Study on Error Analysis of Localizer for Korean Learners of Chinese Language: Focusing on Error judgment and Error correction of Teachers

The purpose of this study is to contribute to effective Chinese teaching and learning methods for both teachers and learners by systematically presenting the basis for judging errors and the error correction principle based on the teacher’s pattern of judging errors with regards to error sentences of localizer for Korean learners of Chinese language. The concrete methods of this study are as follows. First of all, recent researches on syntax and preceding researches related to localizer are examined in the study on Chinese error analysis in Korea. Secondly, various sentences are collected and classified according to the error type, which are submitted by Korean learners while actually correcting same error sentences. Next, the patterns of judging errors regarding various learners’ sentences are examined by native language teachers and foreign teachers. Finally, the basis for judging errors is presented based on examples in which the teachers’ error judgments are in disagreement, and furthermore, the educational measures are proposed.
Workshop: Exploring Virtual Reality Learning Environments

Proposed here is a come-and-go demo of the tool used in the classroom as discussed in the paper “Towards an Intelligent Tutoring System for Virtual Reality Learning Environments”. The workshop/demo will introduce participants to the immersive VRLE (Virtual Reality Learning Environment) activity with several VR (Virtual Reality) headsets available for participant engagement in the VR environment. Developers and users will be available for discussion and questions. The workshop team will be discussing findings from the literature related to the tool and exploring participant thoughts and observations relative to their experiences with the immersive VR tool. Participant engagement may be tailored to their appetite for exploration. They may work through all elements of the tools, watch developers/users work through particular areas, or any mix in between. They can participate for the full session or depart as their interest-level is satisfied. Existing literature will be made available and potential for bringing the activity to their classrooms can be discussed.
Content and Skills for Teaching Software Process Improvement in the Computer Science Course: A Mapping of ACM / IEEE, SBC, SWEBOK, CMMI and MR-MPS-SW Assets

This Research to Practice Full Paper seeks to map the assets of ACM / IEEE, SBC and SWEBOK guide specifically in the knowledge area of Software Process Improvement (SPI) to create a set of contents and competences to be addressed in the classroom, aligned with international and Brazilian references using the good practices of CMMI DEV v2.0 and MR-MPS-SW 2023. The teacher is the main gear for conducting teaching, research, and extension, being responsible for selecting the methods to be used to improve the teaching-learning process. SPI is a set of partially ordered steps with the intention of achieving a goal within the context of software development and involves understanding existing processes and changing them to increase product quality and / or reduce costs and development time. Thus, teaching SPI needs to be addressed in computing courses to meet the wishes of the software industry.
Wireless sensor network deployment optimization for a smart farming application: comparison of two Multi-Objective Evolutionary Algorithms

As it is one of the main means of insuring food security, agriculture has employed different technologies such as the Internet of Things and wireless sensor networks (WSN), to improve the quality and quantity of agricultural products, while preserving natural resources. But unfortunately, in agricultural plots where we have large surfaces of interest, the optimization of node deployment in a WSN remains among the major problems to be solved. In this work, we proposed a WSN node deployment optimization model for an agricultural application according to classical constraints of coverage, over-coverage, connectivity and nodes number, in addition to the nodes separating distance constraint which affects the quality of physical parameters models. We have applied two variants of Multi-Objective Genetic Algorithms, the Non Sorting Genetic Algorithm II (NS-GA II) and the Strength Pareto Evolutionary Algorithm II (SPEA II). As a result, for a 100 m2 plot, both algorithms ensured a communication rate of 100% while SPEA 2 presented a lower sensor number and over-coverage rates with a smaller separating distance, and the execution time of NSGA II was shorter with 11 s. Besides, both of them were greedy in terms of computation time with the increase in the size of the plots.
The Effect of the Application of the Make-a-Match Model on the Ability to Understand Mathematical Concepts and Student Learning Activity

This study aims to evaluate the impact of the Make a Match learning model on the ability to understand mathematical concepts, student learning activity, and their response to mathematics learning. The research method used is a quantitative approach with a quasi-experimental design using the nonequivalent group posttest only design method. Data collection techniques involve tests, questionnaires, and documentation. The research sample consisted of class VIII E students as the experimental group and class VIII B as the control group, with a total of 34 students. Research findings show that: 1) the application of the Make a Match learning model has a significant positive impact on the ability to understand mathematical concepts, with an influence of 53.7%, 2) there is a significant influence on student learning activity with the application of the Make a Match learning model, with an influence of 23.4%, and 3) student response to learning using the Make a Match model reaches 87.50%, with good category. These results contribute positively to the understanding of mathematical concepts, learning activity, and student responses to the Make a Match learning model.
A digital Jordan surface theorem with respect to a graph connectedness

Abstract After introducing a graph connectedness induced by a given set of paths of the same length, we focus on the 2-adjacency graph on the digital line <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi mathvariant="double-struck">Z</m:mi> </m:math> {\mathbb{Z}} with a certain set of paths of length <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>n</m:mi> </m:math> n for every positive integer <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>n</m:mi> </m:math> n . The connectedness in the strong product of three copies of the graph is used to define digital Jordan surfaces. These are obtained as polyhedral surfaces bounding the polyhedra that can be face-to-face tiled with digital tetrahedra.
Considerations on Format Protection in Chinese TV Programs

A broadcast format can be thought of as the framework, containing elements that distinguish it from other programs with fixity and identifiability, such as the program name, stage setting, and background music. There is some debate as to whether program formats can be legally protected under traditional copyright principles based on the idea-expression dichotomy.&#x0D; According to China's copyright law, for an intellectual product to be legally protected as a work, the following three conditions must be met: (1) the work must be an intellectual achievement in the field of literature, art, and science; (2) it must have originality; and (3) it must be expressible in a certain form. Given these principles, there are practical limitations to how broadcast program formats can be included in the category of copyrighted works to provide protection under the existing legal order. One way to overcome these limitations is to consider the approach method, which focuses on the substantial similarity of the two broadcast programs at issue.&#x0D; On the other hand, in the broadcast program market, subsequent programs created by copying and plagiarizing an existing successful broadcast format may constitute unfair imitation under the Unfair Competition Law and should be sanctioned under the law. If a format creator trades in format rights or attracts investment based on a format, it is an obvious commercial activity. Therefore, if a broadcast program format is in competition, it is reasonable for the format creator's behavior to be regulated by the Anti-Unfair Competition Law. However, there are certain limitations to the ability of the Unfair Competition Act to regulate infringement of broadcasting formats.&#x0D; In the future, as trade between Korea and China in the cultural content industry expands, it is expected that the number of broadcast program formats produced in China will increase as in the past. In light of this, the discussion on broadcast program formats in China and the study on how to legally protect the rights of authors is also relevant to Korea.
A Study on Child Welfare of Social Security in Japan

The Child Welfare Act aims to ensure the welfare of children so that they can be born healthy and grow up happily and safely. Japan's right to social security has been developed through the reorganization of various social security law-related systems, and the Child Welfare Act has also been institutionalized through various efforts to actively respond to society's demand for child welfare. Therefore, in this study, we would like to examine the Child Welfare Act among Japan's social security rights and find its implications for Korea.&#x0D; In accordance with the Child Welfare Act, Japan operates premature birth facilities, nursing care children's facilities, disabled child detention facilities, and maternal and child support facilities for pregnant women, and also introduces a foster parent system. Public involvement in the operation of facilities is high, and the role and responsibility of the state, metropolitan local governments, and basic local governments are clarified for the installation or operation of facilities and the implementation of child protection policies. In addition, in order to efficiently and integrally promote child welfare-related policies, the Ministry of Health, Labor and Welfare established the Child and Family Office in April 2023 for child abuse and transferred it to the direct agency of the Prime Minister.&#x0D; Child welfare in Korea is similar to Japan, but there is no dedicated department that acts as a control tower to oversee child welfare because ministries are separated from child welfare targets such as the Ministry of Health and Welfare, the Ministry of Gender Equality and Family, and the Ministry of Education. Children's guardians should raise children healthy and safe at home according to the developmental stage, and the state and local governments should take necessary measures to prevent children from being discriminated against, such as religion, property, or disability of their parents. In order to realize such child welfare, it is urgent to establish an integrated dedicated department, expand child protection facilities, and overhaul a careful and balanced system to implement effective policies suitable for changes in social structure. In this respect, the establishment of the Child and Family Agency in Japan has great implications for Korea.
ORGANIZATION AND AUTOMATION OF INCIDENT INVESTIGATION AND RESPONSE PROCESSES USING SIEM

This article discussed how to organize and automate incident investigation and response processes using SIEM systems. These days, security operations centers (SOCs) face numerous challenges and problems that can negatively impact their ability to detect, investigate, and respond to security incidents. Some of the major challenges include the increasing volume and complexity of security alerts, the shortage of qualified cybersecurity professionals, the use of disparate security tools and systems, and the need to comply with various regulatory frameworks. In this research, the authors developed detection rules that address the needs for accuracy and specificity to avoid false positives that can lead to unnecessary alerts and undermine the effectiveness of automated response systems. The proposed detection rules have been thoroughly tested on real security incidents to ensure their reliability and effectiveness. The authors of this study, in their work, proposed playbook development methods and SIEM correlation rules, and developed detection rules that enable automatic incident response, thereby facilitating the work of SOC analysts.
Implementation and Utilization of Digital Badges in Domestic Universities: Exploring Perceptions and Requirements of Educational Institutes and Industries

[Objective] This study explored the perceptions and needs for digital badges in education and industry, aiming to devise a feasible plan for their introduction in Korean universities.&#x0D; [Contents] To investigate the perceptions and requirements of digital badges, an online survey was conducted among students at A University in Seoul and employees who serve as university mentors at Korea's top 100 companies.&#x0D; [Conclusions] First, despite low awareness, students and companies expressed high interest in and need for digital badges. Second, digital badges were perceived as useful for managing learners' portfolios or personal histories of skills and experiences, as assessment tools to validate skills and abilities, and for providing information to employers and demonstrating competencies. Third, both students and organizations most wanted badges that reflected educational history, followed by badges that demonstrated qualifications and roles. Finally, when it came to information on digital badges, students prioritized endorsements from industry and professional organizations, whereas businesses emphasized a description of the achieved competencies. Based on the findings of this study, we propose practical implications for the adoption and utilization of digital badges.
Advanced Authentication and Access Control for Encrypted Images in the 3D Cube Domain

Image encryption techniques have been widely employed to protect the privacy of images during transmission and storage. However, the challenge lies in providing secure authentication and access control mechanisms for encrypted images in the 3D cube domain. This research focuses on addressing the issue of authentication and access control for encrypted images within the context of 3D cubes. The 3D cube domain provides a unique and efficient representation for image encryption, allowing for enhanced security and privacy. However, ensuring proper authentication and access control mechanisms while maintaining the encryption's integrity and efficiency poses significant challenges. The proposed methods will aim to provide strong authentication mechanisms to verify the integrity and authenticity of encrypted images, preventing unauthorized access and tampering. By addressing the critical issue of authentication and access control in the 3D cube domain, this research aims to contribute to the development of more secure and reliable image encryption solutions. The outcomes of this research will have implications in various domains, including secure image transmission, cloud storage, and digital rights management, where protecting the confidentiality and access control of encrypted images is of utmost importance.
Translating Hungarian language dialects using natural language processing models

Within the territory of Hungary, there are several dialects that differ from the traditional Hungarian language and have various accents. These differences can influence speech, vocabulary, and text, often leading to misunderstandings. These accents have developed over several centuries and have preserved their regional characteristics. The accent primarily relates to the emphasis and pronunciation of sounds, but there are also written traces that have been preserved over hundreds of years. This intriguing language processing challenge raises the question of whether we can create a translation program using natural language processing models that are capable of translating text or speech between different accents. While we are aware of the similarities between these dialects and the traditional Hungarian language, the research aims to discover further connections between different dialects. Data collection itself poses an interesting challenge since these are only dialects and not distinctly separated from each other. Additionally, there is no comprehensive compilation of the vocabulary or uniqueness of each dialect in Hungarian according to our best knowledge. Even within dialects found in books, there are variations as texts can span several decades or even centuries. Furthermore, territorial changes have also influenced dialects.
From the appearance of “The Computer and the Brain” to the revolution of the infosphere

This Neumann’s last publication marks the beginning of a comparison between artificial and natural information processing machines that has continued ever since, that is, the comparison of “The Computer and the Brain”. With a brief description of the book, we prepare the formulation of the new tasks of the comparison. In doing so, the revolutionary change that took place in the infosphere of humanity with the co-evolution of computing, networking and representing information, and which is still in intensive development, must be taken into account. The book contrasts the stored program architecture based on Neumann’s principle with the neural network architecture of the brain. The numerical comparison is based on differences in the performance, number, and density of the active elements. The comparison cannot be continued in this way, because we are not dealing with individual computers, but with a system of cooperating machines organized in the Internet. The worlds of the two kinds of machines jointly use the latest collection of artificially created information carriers, the Data Sphere, and together they form the active information processing component of the Humanity’s infosphere. The carriers of information provide the common, materially existing object of computation and thinking, which I call formation in the paper. The information event, introduced in the paper, associate formation with information. Formation means information when the observation or creation of the formation in an information event is connected to the meaning for its owner. While the information processing of computers is only the transformation of formations, the assignment of meaning is carried on in an information event both before and after the transformation. In the most important information event, the owner is the human mind. The separating barrier between the two worlds is the information event. Within the computer systems, there are no more information events, only formations are transformed, in which the activation of program formations enables the automatic execution of the computation.
Comparison of scalable distributed algorithms for assessing the kNNG in multi-GPU

Many applications, require finding a dataset’s k-Nearest Neighbors Graph (kNNG), crucial for many Machine Learning tasks like clustering and anomaly detection. However, its computation can be costly due to the complexity of finding all kNN for every data point. To address this issue, scalable approximated algorithms have been proposed to speed up the kNNG and maintain its quality. This paper presents an adaption of NNDescent using multi-GPU and an experimental comparison of distributed and parallel approximate kNNG algorithms in GPUs, assessing their scalability, computational cost, and solution quality. Our goal is to identify the most efficient method without significant accuracy loss, enabling faster techniques and handling large datasets.
Processamento e Análise de Big Data e Aplicação de Algoritmos de Machine Learning através da utilização da Plataforma HPCC Systems

In this book are the six mini-courses presented during the XXIV Symposium on High Performance Computing Systems, held from October 17th to 20th, 2023, in Porto Alegre, RS. The first chapter covers essential concepts of processing and analyzing large volumes of data, practicing the use of machine learning algorithms. In the second chapter, readers are introduced to understanding the operation of the OpenMP distributed programming model through the introduction of the OpenMP Cluster. Chapter three explores challenges and solutions associated with complex applications that deal with large volumes of data, aiming to optimize the performance and power consumption of parallel applications. Automated solutions that enable reproducible and shareable installation of packages entirely in user spaces, reducing costs and errors for system administrators, are presented in chapter four. Chapter five aims to present the concepts of an adaptive/evolutionary system, Evolutionary Hardware (EHW), characterized by a high level of parallelism. Finally, chapter six discusses storage systems, covering various connections such as SATA, SCSI, SAS, iSCSI and Fiber Channel, highlighting the advantages and disadvantages of each of these connections.
Breast Cancer Prediction Using Hybrid Machine Learning and Nature-Inspired Adaptive Optimization Algorithms

An early stage of breast cancer occurrence does not have pain as a symptom. This asymptomatic nature of cancer necessitates the need of timely and accurate prediction using other potential indicators. Breast cancers are highly curable if predicted and diagnosed at the earliest. This research explores the capacity of hybridizing intelligent learning models with nature-inspired optimization algorithms for breast cancer prediction. This integration becomes pivotal to optimize internal parameters of the dataset while aiming for augmented accuracy of the proposed predictive models. Each of the four intelligent machine learning models including K-Nearest Neighbor (KNN), Naïve Bayes (NB), Support Vector Machine (SVM), and Artificial Neural Network (ANN) are hybridized with all the three adaptive optimization approaches including Adaptive Particle Swarm Optimization (APSO), Adaptive Genetic Algorithm (AGA) and Adaptive Venus Flytrap Optimization (AVFO). Thus twelve hybridized predictive models were derived namely APSO-KNN, AGA-KNN, AVFO-KNN, APSO-NB, AGA-NB, AVFO-NB, APSO-SVM, AGA-SVM, AVFO-SVM, APSO-ANN, AGA-ANN and AVFO-ANN. These hybridized models were investigated through UCI data repository’s breast cancer dataset namely WBC, WDBC and WPBC. The experimental results were validated against the respective learning models with and without feature selection. Based on the performance measures such as accuracy, F-measure and G-mean, the outperformed learning models with WBC, WPBC and WDBC datasets are AVFO-SVM, AVFO-ANN and APSO-ANN respectively. Conclusively ANN and SVM machine learning algorithms fused with AVFO for feature selection are robust for all the three datasets. The derived hybrid intelligent models trained with tuned datasets optimize the prediction ability of existing breast cancer prediction models.&nbsp;&nbsp
The Report of Standardization for Blockchain-Based Digital Right Management System

Under the threat of digitalization of creations, the traditional digital right management method exposes several problems, including high entering&maintaining costs and low transaction efficiency. Meanwhile, the booming development of blockchain technology shows the potential to harness these issues. Thus, this paper aims to deliver an analysis report of the standardization situation for blockchain-based DRM systems In front, we analyze the current situation of copyright management in both relevant standards and applications. Meanwhile, two general DRM systems based on alliance blockchain and a DRM platform based on public blockchain are demonstrated respectively to satisfy the needs of copyright authentication, judicial safeguards, and digital assets or right transaction.