Reviewerly/exHarmony huggingface dataset:
The Fault Simulation Algorithm Based on Multiple Random Local Stresses Technique - The Tool for Detail Seismic Interpretation

Summary A novel algorithm permits simulation of faults based on analysis of 2D or 3D seismic stratigraphic slices under isotropic or pre-defined boundary stress conditions. The algorithm detects local zones of weakness based on the violation of linear integrity criteria. In addition to detecting fault-related edges in the seismic data, the algorithm produces crisp images of stratigraphic boundaries.
Educación, pandemia y TikTok

This paper examines the problem of how Gen Z students have had to violently migrate from an educational system within the classroom to one that only takes place online, involving such apps as TikTok that are now the main components of the academic processes. This paper also assesses the digital gap between students and teachers, who have had to adapt to these new circumstances in order to continue performing their didactic roles.
Introduction of Information Business Course in the Content of the Computer Science Program

In today’s rapidly changing world of innovative technologies, it is necessary to search for means of modernization of educational process, where along with implementation and constant improvement of new technologies and software it is also important to update the content of education system as well. The modern and developing education institution requires experts in the various related fields. First, it is necessary to know the modern innovative technologies; second, to employ these technologies in various sectors and activities. With regard to the above, the content of education programs with respect to the development of the promising areas should be revised these days. The given article analyses the development of educational content in computer science of Kazakhstan, determines the theoretical basis, development and practical realization of introducing the content of computer science in secondary school. The authors of this article introduced information business in the course of computer science with an aim to develop the content of computer science discipline by introducing elements of information business. The content and structure of training in the fundamentals of information business was introduced in the educational process as a separate elective course and as a fragment of general education computer science course.
SISTEM INFORMASI PAROKI SANTO PIUS X AEK KANOPAN BERBASIS WEB

Information systems are understood as a collection of subsystems that are interconnected, gather together and form a single unit, interact and work together between one part and another in certain ways to perform data processing functions, receive input data, then process it, and produce output in the form of information. The church is an association, association, or fellowship for Christians in one faith that is shaded in a container of organizations or existing religious institutions that have been acknowledged by the government Parish data processing at this time is still manual such as processing data on independent funds, pastor's journey to the station or environment, scheduling Misa is still manual so that people have to come to Parish. To overcome the problems faced by the Aek Kanopan parish at this time, it is expected that with the parish pastoral information system which can later be carried out computerized systems can even be presented in the form of a website. Keywords: Information System, Church
Current Issues and Future Directions of Intelligent Computer-Aided Pronunciation Training for Foreign Language Learning

This article first discusses the significance of intelligent computer-aided pronunciation training for foreign language learning from a developmental neuroscience perspective and illustrates the way to combine linguistics,speech technology,educational psychology,and neuroscience to teach pronunciation more effectively with intelligent software by using visualization.Then the article points out that we need language teachers who are also well informed about the latest technology to lead the design of intelligent systems.Only in this way can we overcome the disadvantage of the technology-driven approach and take full advantage of artificial intelligence in education.It is expected that interdisciplinary experts should work together to promote the innovative development of artificial intelligence in foreign language teaching.
Keefektifan Model Picture and Picture Berbantu Media Gambar Seri Terhadap Ketrampilan Menulis Karangan Narasi Siswa Kelas V SD Negeri Tandang 03 Semarang

The background in this study is that students are less able to develop a writing and are still not careful in writing, ideas and ideas or descriptions that will later be contained in the writing are not fully able to be done by grade V students of Tandang Elementary School 03 Semarang when given the task of making narratives and learning which is still centered on the teacher so that students become passive in participating in learning. This type of research is a quantitative study using a pretest-posttest one-group design. The results of the data analysis of the pre-test and post-test learning outcomes with the t-test were obtained with an average pretest score of 50.14 and an average posttest score of 80.35. With N = 28, obtained tcount = 13.6706 with a significant level of 5% of 2.0484. Because tcount = 13.6706> ttable = 2.0484, then this shows that the t test has a significant effect. This shows that there is an effect of learning the Picture and Picture Model. This research can be concluded that the Picture And Picture Model is effective on the speaking ability of fifth grade students at SD Negeri Tandang 03 Semarang.
Privacy-Preserving and Scalable Authentication based on Network Connection Traces

Since password-based authentication is no longer sufficient for web applications, additional authentication factors are required. Especially in the context of mobile devices and with regard to usability, there is an increasing focus on methods where the user's behavior is used as authentication factor (e.g., touchscreen interactions or sensors). As this typically requires the processing of large amounts of sensitive data, issues related to privacy and scalability arise. Our work addresses the issues by presenting a scalable and privacy-friendly approach for authenticating users of mobile applications based on information about their network connections.
One-shot Learning for Temporal Knowledge Graphs.

Most real-world knowledge graphs are characterized by a long-tail relation frequency distribution where a significant fraction of relations occurs only a handful of times. This observation has given rise to recent interest in low-shot learning methods that are able to generalize from only a few examples. The existing approaches, however, are tailored to static knowledge graphs and not easily generalized to temporal settings, where data scarcity poses even bigger problems, e.g., due to occurrence of new, previously unseen relations. We address this shortcoming by proposing a one-shot learning framework for link prediction in temporal knowledge graphs. Our proposed method employs a self-attention mechanism to effectively encode temporal interactions between entities, and a network to compute a similarity score between a given query and a (one-shot) example. Our experiments show that the proposed algorithm outperforms the state of the art baselines for two well-studied benchmarks while achieving significantly better performance for sparse relations.
Generating Program Identifier Dictionary for Maintaining Legacy Systems

Descriptions of program identifiers improve the maintainability of programs. Modern software projects maintain proper descriptions by following coding conventions. However, software projects maintained for a long time have two problems: (i) descriptions at incorrect locations and (ii) no descriptions. We propose the method of generating a identifier dictionary for managing identifiers and their descriptions, which enables developers to refer to identifier descriptions from anywhere within programs. The method involves two steps: (i) extracting identifiers and descriptions from design documents and programs and (ii) generating descriptions using information-retrieval and machine-learning methods. We applied the proposed method to COBOL programs and design documents of a legacy system that has been maintained for over 20 years as a case study. The proposed method obtained the descriptions of 83% of identifiers and reduced the cost of locating files to be modified by enhancing search keywords using the identifier dictionary. This means that the proposed method can improve the maintainability of systems maintained over many years.
Προκλήσεις ασφάλειας και κυβερνοέγκλημα σε κρίσιμες υποδομές

The digital era affects fundamental rights, social interactions, and economies. Cyberthreats emerge as Information and Communication Technologies (ICT) systems are utilised for the proper operation of Critical Infrastructures. An important and recognised role in achieving cybersecurity is adopted by governments, which develop security by introducing regulations, strategies, and other security measures. In this postgraduate thesis, following the definition of the concept of Critical Infrastructure and how they work with systems that include ICT, various security challenges are described as well as the measures that need to be taken in order to address them. Furthermore, the security standards that apply to the European Union (and therefore Greece), USA, China and Russia are studied, as well as incidents of attacks on critical infrastructure sectors in these countries. Finally, as a result of a comparative assessment of cybercrime incidents in these four study areas, useful conclusions are drawn, and specific proposals are formulated for future research in order to contribute to improvements in the security systems of critical infrastructures.
Similarity Learning for CNN-Based ASL Alphabet Recognition

Sign language is an important communication way to convey information among the deaf community, and it is primarily used by people who have hearing or speech impairments. Besides, sign language represents a direct Human-Computer-Interaction (HCI) similar to voice commands. Therefore, the purpose of this study is to investigate and develop a system for American Sign Language (ASL) alphabet recognition using convolutional neural networks. Our proposal is based on semantic similarity learning using Siamese Convolutional Neural Network to reduce the intra-class variation and inter-class similarity among sign images in a Euclidean space. The results of the siamese architecture applied to the ASL alphabet dataset outperform previous works found in the literature. From these results, using t-SNE visualization, we demonstrate that our hypothesis is correct; the ASL recognition improves when increasing the similarity among encoding of the images belonging to the same class and reducing it otherwise.
한국어교육에서 다중언어능력 및 다중문화능력의 개념과 적용

This study examines the concept of plurilingual and pluricultural competence presented by the CEFR(2018) and proposes application methods in Korean language education. In Korean language education, learners can improve their competence to target language and culture by understanding that learners have various languages and cultural backgrounds and utilizing such resources and experiences. To this end, the understanding and acceptance of culture can be facilitated by establishing a pluricultural repertoire. The target language can be learned by utilizing various language resources through plurilingual understanding of plurilingualism. Furthermore, by building a plurilingual repertoire, it is possible to take advantage of the language resources that learners have to take the initiative in language learning. By applying this concept, a teaching-learning method can be proposed so that learners can utilize each other''s language and cultural resources in professor learning, which used only Korean, the target language in Korean education. (Sogang UniversityㆍSogang UniversityㆍYonsei University)
Temporal–spatial feature compensation combines with multi-feature discriminators for video super-resolution perceptual quality improvement

Generative adversarial network (GAN) for super-resolution (SR) has attracted enormous interest in recent years. It has been widely used to solve the single-image super-resolution (SISR) task and made superior performance. However, GAN is rarely used for video super-resolution (VSR). VSR aims to improve video resolution by exploiting the temporal continuity and spatial similarity of video sequence frames. We design a GAN with multi-feature discriminators and combine it with optical flow estimation compensation to construct an end-to-end VSR framework OFC-MFGAN. Optical flow estimation compensation makes use of temporal continuity and spatial similarity features of adjacent frames to provide rich detailed information for GAN. Multi-feature discriminators based on visual attention mechanism include the pixel discriminator, edge discriminator, gray discriminator, and color discriminator. GAN with multi-feature discriminators makes the data distribution and visually sensitive features (edge, texture, and color) of SR frames similar to high-resolution frames. OFC-MFGAN effectively integrates the time, space, and visually sensitive features of videos. Extensive experiments on public video datasets and surveillance videos show the effectiveness and robustness of the proposed method. Compared with several state-of-the-art VSR methods and SISR methods, the proposed method can not only recover prominent edges, clear textures, and realistic colors but also make a pleasant visual feeling and competitive perceptual index.
Research and Computer Realization of Fault Tree Quantitative Calculation Algorithm

Through the research and understanding of FTA, analysis of its role in reliability engineering and its working principle, for the application of FTA method in the computer to make a reasonable demonstration. From the overview of FTA and the research status at home and abroad, the working principle of reliability engineering and the importance of an important branch -- FTA are analyzed. From the qualitative analysis and quantitative calculation algorithm of FTA, and its quantitative calculation module, FTA is studied separately. Hope to be able to provide help for this professional researchers.
Enhanced classification of crisis related tweets using deep learning models and word embeddings

Social media plays a crucial role during emergency events by preserving intelligence about the current condition, which may save lives. Twitter is one such powerful social media platform where information about the situational awareness is directly posted by victims or bystanders. The objective of the research is to enhance the classification of crisis related tweets by utilising the deep learning models. Our work focuses on evaluating the deep learning models, the vectorisation methods and the effect of data size on them. A multilayer perceptron (MLP), a convolutional neural network (CNN) and a long short term memory (LSTM) are employed along with the vectorisation methods (GloVe and Word2Vec), in different experiments. Based on the results pertaining to the metrics of classification and the learning graphs, the LSTM model is observed to work well. The need for measures, to improve the classification of a large twitter dataset is understood from the analysis.
Specifics of Formation of Professional Skills of Musical Theater Artists in College

Every year in Russia there is a growing number of people who want to devote themselves to stage professions. Pop and academic singer, actor of musical and dramatic theater, ballet dancer – here is an incomplete list of specialties that can be obtained in educational institutions of culture and art. The main task of these educational institutions is the professional formation of future stage masters, the formation of competencies that allow students to carry out further acting activities. The basis for the preparation of the future artist is the formation of stage skills, since this complex concept includes the internal (psychological) and external (physical) data of the actor, the possession of the art of reincarnation in the process of creating a stage image, the possession of stage freedom. The professional training of a musical theater artist in college becomes a multifaceted process, where the combination of vocals, dance, acting is aimed at solving the dramatic problems of a musical performance. The purpose of the article is to theoretically justify and identify empirically the specifics of the formation of professional skills of musical theater artists in college.
SVA Library Research Guides: Online Resources and Services: Library Instruction

The following guide outlines the collections, services, and support available remotely to students, faculty, and staff.
To Improve Speaking Skill of Students with Special Needs by Mentioning The Words Heard using Multisensory Story Telling

This research was conducted to improve speaking skill of students with special needs by mentioning the words heard using the Multisensory Storytelling method. Multisensory Storytelling is an approach uses storytelling while using variety senses of special needs students. There are five main activities in this research : Love Fruits, 'Put Me Right', 'Story Time', 'Wooden Puzzle' and 'Multisensory Storybook'. This research focuses on three objectives namely improving the speech of special needs students through the pronunciation of words uttered, increase the vocabulary and use of variety of senses in helping to improve speaking skill of students with special needs.The participants are two special needs students at one of the primary schools located in Johor, Malaysia. This research is using the design of the action research. The main instruments used are observation and interview. From the observation analysis, teacher found that speaking skills can be improved by increasing the number of words pronounced from none to five out of seven words. Field notes, checklists and video analysis have been used to support this observation findings. Based on the results of the interview, teacher found that the participant's mother also observed the feedback that the speaking skill of the students were improved through the use of the Multisensory Storytelling method as their children can speak up the words in the given situation. The students were able to tell the name of the fruit correctly and the colour of fruit as well. For further research, the researcher proposes this method is widely to help Speech Language Impairment among other categories of learning disabilities.
Where Does Developer Relations Fit?

In this chapter, we’ll take a deeper look at the multiple roles Developer Relations plays, where developer relations sits within an organization, and how you can determine its influencers and influences.
Assessment of digital image correlation vibrometry in the presence of thermal flow disturbance

Digital Image Correlation (DIC) is an image-based method for measuring displacement and/or stain on the surface of a structure. When coupled with a stereo pair of highspeed cameras, DIC can also capture three-dimensional dynamic deformation of a structure under vibratory loading. However, high frequency and small amplitude displacement typically associated with structural vibrations mean that extra care is required during measurement and data processing. It becomes more challenging when thermal disturbances are present in the optical path, for example from a heated air flow, which introduces extraneous noise due to disturbances in the refractive index. In the present study, a simple composite plate was vibrated under a shaker excitation and stereo DIC measurements were performed. The obtained vibratory displacement results were compared against accelerometers and a laser Doppler vibrometer. Heated air flow was introduced in front of the plate to observe the effects of thermal disturbances on the DIC measurements. Although the contributions from the thermal disturbances were clearly visible in the DIC displacement data, it was shown that the vibratory deflections of the structure could still be extracted by post processing of the DIC data.
Challenges faced by Academic Libraries due to resource sharing and networking models

Each day millions of books, journals and ephemera are being published and to keep track of these books and literature and to provide them to the information seeking community is a herculean task for Academic Libraries. The difference between good or bad data can be explained as to how accurately the information is dispersed to the academic community. In these circumstances, it becomes significant for libraries to collectively come together and help each other by forming a resource sharing model. Across the globe numerous such models have been formed but most of them struggled to thrive on a long run. The present paper discusses the challenges faced by the resource sharing models and the possible solutions to overcome these problems for the smooth functioning of the consortia.
Impact of Post-Quantum Hybrid Certificates on PKI, Common Libraries, and Protocols

In this work, we assessed the impact of post-quantum (PQ) cryptography on public key infrastructure (PKI). First, we modified a commercially available certification authority (CA) to issue 'hybrid' certificates (X.509 certificates with PQ extensions). Then we assessed the impact of using these certificates on some existing protocols, including TLS, OCSP, CMP, and EST, with open-source libraries OpenSSL and CFSSL, and with a commercially available cryptographic toolkit. We found that most of the protocols and libraries we tested worked with hybrid certificates, and some of the failures could be overcome with minor modifications to the existing software. Our work differentiates from and extends previous work by focusing on the impact of PQ algorithms on certificate issuance, revocation, and management protocols, which are necessary for enterprises to manage PKI in their environments. The impact on TLS is also investigated, allowing consistency with previous results to be evaluated.
HPDM: A Survey Paper

This survey reviews several approaches of HPDM from many research groups world wide. Modern computer hardware supports the development of high-performance applications for data analysis on many different levels. The focus is on modern multi-core processors built into today's commodity computers, which are typically found at university institutes both as small server and workstation computers. So they are deliberately not high-performance computers. Modern multi-core processors consist of several (2 to over 100) computer cores, which work independently of each other according to the principle of instruction multiple data'' (MIMD). They have a common main memory (shared memory). Each of these computer cores has several (2-16) arithmetic-logic units, which can simultaneously carry out the same arithmetic operation on several data in a vector-like manner (single instruction multiple data, SIMD). HPDM algorithms must use both types of parallelism (SIMD and MIMD), with access to the main memory (centralized component) being the main barrier to increased efficiency.
Will Artificial Intelligence Eat the Law? The Rise of Hybrid Social-Ordering Systems

Software has partially or fully displaced many former human activities, such as catching speeders or flying airplanes, and proven itself able to surpass humans in certain contests, like Chess and Jeopardy. What are the prospects for the displacement of human courts as the centerpiece of legal decision-making?Based on the case study of hate speech control on major tech platforms, particularly on Twitter and Facebook, this Essay suggests displacement of human courts remains a distant prospect, but suggests that hybrid machine–human systems are the predictable future of legal adjudication, and that there lies some hope in that combination, if done well.
Preface: Conference on Theoretical Physics and Nonlinear Phenomena (CTPNP) 2019

First Page