Reviewerly/exHarmony huggingface dataset:
A Hypergraph Model for Communication Patterns

The article deals with interaction in concurrent systems. A calculus able to express specific communication patterns is defined, together with its abstract control structures. A hypergraph model for these structures is presented. The hypergraphs are able to properly express the communication patterns, providing a fully abstract model for the pattern calculus. It is also proved that the hypergraph model preserves the operational reductions of processes from pattern calculus and of the actions from the control structures.
Psychology of text writing: truths and delusions

Review of the book by E. Peltek "Write - Don't Write: A Psychological Guide for Authors on Working with Text and Oneself". Moscow: Alpina Publisher, 2021
Dynamic attention network for multi-UAV reinforcement learning

Recent methods for multi-agent reinforcement learning problems make use of Deep Neural Networks and provide state-of-the-art performance with dedicated neural network architectures and comprehensive training tricks. However, these deep reinforcement learning methods suffer from reproducibility issues, especially in transfer learning. Since the fixed size of the network input, it is difficult for the existing network structure to transfer the strategies learned from a small scale to a large scale. We argue that proper network architecture design is crucial to the cross-scale reinforcement transfer learning. In this paper, we use transfer training with attention network to solve multi-agent combat problems from aerial unmanned aerial vehicle (UAV) combat scenarios, and extend the small-scale learning to large-scale complex scenarios. We combine the attention neural network with the MADDPG algorithm to process the agent observation. It started training from a small-scale multi-UAV combat scenario and gradually increases the number of UAV. The experimental results show that methods for multi-agent UAV combat problems trained by attention transfer learning can achieve the target performance faster and provide better performance than the method without attention transfer learning.
Impact of Electronic Games on the Increase of School Dropout among Students in the Basic Stage in Jordan from their teachers’ Perspective

The study aims to identify the impact of electronic games on increasing the dropout rate among students in the basic stage in Jordan from their teachers’ point of view. The study adopted a descriptive survey method. Its community consisted of all fe(male) teachers of the basic stage in public and private schools, (First Amman, Irbid, and special education in Zarqa and Amman). The electronic questionnaire was used as a tool for the study. The results have shown that the effect of electronic games on increasing the dropout rate among students in the basic stage in Jordan was high. Besides, there are statistically significant differences due to the gender variable for males. There are statistically significant differences due to the variables of the school sector and private schools. Besides, there are statistically significant differences due to the variable of specialization and in favor of humanities. The study finally recommended to have more stringent controls by the Ministry of Education on dropout students. It has further recommended to activate the role of the educational counselor in educating students about electronic games, and hold workshops for them on how to invest time properly
Penerapan Metode Prototype Pada Sistem Informasi Pengelolaan Data Tamu Hotel

The management of guest data at Hotel Gerbera is currently still by recording books, starting from the check-in process which is done by filling out the registration sheet, then inputting guest data who has checked in in the Guest In The House data table using Microsoft Excel and writing money data. Incoming cash payments, debit / credit and receivables per shift in the Daily Cashier Sheet. This kind of data input process is less effective because it takes a lot of time to enter guest data into each different report form. The research with the title "Gerbera Hotel Guest Data Management Information System Using Prototype Method" has a problem formulation of how to manage the Gerbera Hotel guest database and how to apply the prototype method to the Gerbera Hotel Guest Data Management Information System. The purpose of this research is for the effectiveness of time in the process of managing guest data for the receptionist, storing guest data is well organized by the system, and making it easier for the receptionist to find data on guests who have checked in. This study uses the prototype method. The development of the prototype method starts from the stage of gathering user requirements and analysis, rapid design, building prototypes, evaluating prototypes, changing designs and prototypes, until customers are satisfied, then large-scale development. Based on the research conducted, it is concluded that to manage guest data so that it is stored properly in the database is to develop an information system for managing guest data at Hotel Gerbera. The test results of the Gerbera Hotel guest data management information system are in the very feasible category with a percentage value of 92%.
MCMC for Global-Local Shrinkage Priors in High-Dimensional Settings

In this chapter, we provide a review of MCMC computation with one-group or continuous shrinkage priors expressed as scale mixtures of Gaussians in the high-dimensional regression model. We primarily focus on blocked Gibbs samplers, which are popularly used in hierarchical Gaussian models. For sake of concreteness, we additionally focus on the popular horseshoe prior while pointing out generalizations whenever appropriate. Our discussions span various blocking strategies, computational complexities, numerical issues, and geometric convergence. We conclude with some topics for future research.
Data Preparation

This chapter is dedicated to the data preparation step of the data science process. The captured data is typically explored to understand it better. Such exploration may reveal that the captured data is in a form which cannot be directly used to build models – we saw one such case in Chapter 6 where the data captured for predicting the category of an email consisted of just emails and their folders. This data had to go through a lot of preparation before it could be used for building models. In some other cases, it may seem that the data could be given to ML algorithms directly, but preparing the data in various ways might result in more effective models. We saw such a case in one of the examples we discussed in Chapter 1, where the captured data contained the timestamps and sale amounts for transactions at the checkout counter of a store. In this case, we felt that sale amount might have some trends based on what day of the week it is, what month it is, etc. Hence, we transformed the data so that it contains the hour, day, month, etc., along with the corresponding aggregated sale amount hoping that it will enable ML algorithms to find such trends. Hence, preparing the data in such ways might result in better models.
Features of the innovative and creative potential of future education specialists

The current state of economic and social development requires from a professional the ability not only to operate with a certain set of professional knowledge obtained in higher education, but also the formed creative opportunities, the ability to self-realization in further independent activity. Therefore, higher education institutions face an important problem of developing the creative potential of youth, which in turn involves the organization of the educational process taking into account the psychological patterns of development of the entire system of personal qualities in student age. Therefore, the problem of identifying the degree of formation of the creative and innovative potential of future managers and checking the effectiveness of the psychological and pedagogical conditions for their acquisition of professional competencies in this direction in the educational process is urgent. Taking this into account, the main purpose of the study is to find new ways to develop and stimulate the innovative and creative potential of future education managers. For this, the methods of theoretical analysis were used. As a result of the research, the basic principles of development and stimulation of the innovative and creative potential of future education managers were generalized and systematized.
The Institute for Engineering Education at SMU – Answering the Shortage of Tomorrow’s Engineers

To help combat the projected shortage of engineers, the Institute for Engineering Education at SMU was founded in 2002 with funding from the
Review and Analysis on Filtering of Unwanted Multimedia Messages from Online Social Network User Walls

Abstract: When it comes to sharing and exchanging various types of information, online social networks (OSNs) have become an increasingly popular and interactive medium in today's world. People who are connected to blogs and social networks see all of the publicly shared information, and it has a profound effect on the human mind. Messages or comments posted on a wall, a public or private area, may include unnecessary information or sensitive data. Thus, online social networks can benefit from information filtering, which can be used to help users organise messages written in public areas by removing unnecessary words. An information filtering system proposed in this paper may allow OSN users to control the posting and commenting on their walls directly. Every time a user posts a message, the message is intercepted by the filtered wall, which then applies Filtering and Black List Rules to it. The message will appear on the user's wall if it is not filtered or blacklisted. Keywords: Content Based Message Filtering, Demographic Filtering, Collaborative Filtering.
Research on management evaluation of enterprise sales cash flow percentage method based on the application of quadratic linear regression equations

Abstract This article introduces an improved sales percentage method to quantitatively calculate the evaluation process of the corporate sales cash flow percentage method in order to obtain more evidence-based financial data and increase the accuracy of the evaluation results. At the same time, the paper uses SPSS to perform regression analysis on related financial indicators and sales revenue and obtains quadratic regression equations and linear regression equations. The thesis predicts other financial index data based on the predicted future sales revenue, uses the revised linear regression equation to obtain the company's future net cash flow and calculates the company value.
Cluttering Reduction for Interactive Navigation and Visualization of Historical Images

Abstract. Iconographic representations, such as historical photos of geographic spaces, are precious cultural heritage resources capable of describing a particular geographical area’s evolution over time. These photographic collections may vary in size, between hundreds and thousands of items. With the advent of the digital era, many of these documents have been digitized, spatialized, and are available online. Browsing through these digital image collections represents new challenges. This paper examines the topic of historical image exploration in a virtual environment enabling the co-visualization of historical photos into a contemporary 3D scene. We address the topic of user interaction considering the potential volume of the input data. Our methodology is based on design guidelines that rely on visual perception techniques to ease visual complexity and improve saliency on specific cues. The designs are additionally implemented following an image-based rendering approach and evaluated in a group of users. Overall, these propositions may be a notable addition to creating innovative ways to visualize and discover historical images in a virtual geographic environment.
Towards Automatic Deductive Verification of C Programs with Sisal Loops Using the C-lightVer System

The C-lightVer system is developed in IIS SB RAS for C-program deductive verification. C-kernel is an intermediate verification language in this system. Cloud parallel programming system (CPPS) is also developed in IIS SB RAS. Cloud Sisal is an input language of CPPS. The main feature of CPPS is implicit parallel execution based on automatic parallelization of Cloud Sisal loops. Cloud-Sisal-kernel is an intermediate verification language in the CPPS system. Our goal is automatic parallelization of such a superset of C that allows implementing automatic verification. Our solution is such a superset of C-kernel as C-Sisal-kernel. The first result presented in this paper is an extension of C-kernel by Cloud-Sisal-kernel loops. We have obtained the C-Sisal-kernel language. The second result is an extension of C-kernel axiomatic semantics by inference rule for Cloud-Sisal-kernel loops. The paper also presents our approach to the problem of deductive verification automation in the case of finite iterations over data structures. This kind of loops is referred to as definite iterations. Our solution is a composition of symbolic method of verification of definite iterations, verification condition metageneration and mixed axiomatic semantics method. Symbolic method of verification of definite iterations allows defining inference rules for these loops without invariants. Symbolic replacement of definite iterations by recursive functions is the base of this method. Obtained verification conditions with applications of recursive functions correspond to logical base of ACL2 prover. We use ACL2 system based on computable recursive functions. Verification condition metageneration allows simplifying implementation of new inference rules in a verification system. The use of mixed axiomatic semantics results to simpler verification conditions in some cases.
An Evidence-Based Approach to Distractor Generation in Multiple-Choice Language Tests

The purpose of this project is to explore the feasibility of a new approach for producing evidence-based distractor sets. We use Common Wrong Answers (CWAs), and the associated performance data, generated by candidate responses to open gap-fill tasks, to produce distractor sets for multiple-choice gap-fill tasks based on the same texts. We then investigate whether these distractor sets are effective for use in language tests, in terms of empirical and qualitative review, and consider potential impacts on the production process for test material. This project explores a new and innovative method of content development, and raises the possibility of a new approach to item production that can semi-autogenerate test items in shorter periods of time without affecting quality or reliability. Although the approach is specific to one task type, it is hoped that further research will expand on the applications of the approach to deliver a version that may be operationalised for use across different task types in the development of language assessments.
From The Training Room to the Classroom: Applying Concepts of Corporate Training and Tertiary Education in Secondary Education

The COVID-19 pandemic has changed the nature of secondary education and encouraged teaching through blended and e-learning. This article explores how the author integrated concepts he previously applied in tertiary education and corporate training, particularly Finks Taxonomy of Significant Learning and P3 Task Taxonomy, through blended and e-Learning to a secondary education context. These ideas developed into a teaching methodology for a business curriculum and were delivered in an international Christian school in Cambodia. The teaching methodology helped streamline curriculum development, adapt to the changing conditions, and improve overall lesson delivery. The study recommends that the teaching methodology be explored further and be developed as a framework to support new and developing teaching staff.
Explaining Deep Neural Networks in medical imaging context.

Deep neural networks are becoming more and more popular due to their revolutionary success in diverse areas, such as computer vision, natural language processing, and speech recognition. However, the decision-making processes of these models are generally not interpretable to users. In various domains, such as healthcare, finance, or law, it is critical to know the reasons behind a decision made by an artificial intelligence system. Therefore, several directions for explaining neural models have recently been explored In this communication, We investigate two major directions for explaining deep neural networks. The first direction consists of feature-based post-hoc explanatory methods, that is, methods that aim to explain an already trained and fixed model (post-hoc), and that provide explanations in terms of input features, such as superpixels for images (feature-based). The second direction consists of self-explanatory neural models that generate medical imaging explanations, that is, models that have a built-in module that generates explanations for the predictions of the model.
Thief Detection with Deep Learning using Yolo Predictive Analysis

Abstract: This paper discusses thief detection, which is one of the important applications of suspicious human activity detections. Individual safety is a major concern in our busy scheduling life. The main reason for this concern is an ever-increasing number of activities that pose a threat. A simple closed-circuit television (CCTV) installation system is not sufficient enough because it usually requires a person to be alert and monitoring the cameras always is inefficient. The necessitates for the development of a fully automated security system detects anomalous activities in real-time, and provides instant assistance to the victim. As a consequence, we proposed a framework that examines and detects suspicious human activity from real-time Surveillance video using deep learning techniques and generates an alert if abnormal activity occurs. The method was tested on a dataset with both normal and abnormal activity and yielded better results. Keywords: Thief detection, deep-learning, surveillance video, predictive analysis, yolo.
Cybersecurity: the backbone of digitalisation

This book provides an overview of the digital tools available in the market as well as the impact of digitalisation on the water sector by sharing Singapore's experiences. PUB, Singapore's National Water Agency, unveiled its SMART PUB Roadmap in 2018 to digitalise Singapore's entire water system to improve the utility's operational excellence and meet the nation's future needs. This book shares PUB's digitalisation drive, highlights the deliberations behind its decisions, showcases its projects, and underlines the infrastructural, cybersecurity and human elements in digitalisation that other water utilities need to consider in crafting their own path forward.To guide the digitalisation efforts, PUB has come up with four major goals: to create value for the utility through new capabilities,more efficient operations,a better work environment, andimproved customer service.With these goals, PUB has been able to focus their research and investments, plan their digitalisation journey in greater detail, and consider more deeply how to collect and use data in innovative ways.ISBN: 9781789061864 (paperback)ISBN: 9781789061871 (eBook)
Publishing management curriculum in Indonesia

One effect of technology development is the dissemination of scientific publications that convert in electronic format. Generally, the basic practice between author, reader, and publisher in offering manuscript, reading, and publishing are not drastically changing. But, it is just changing the flow in digital format. However, in its implementation, many publishers still did not understand the ideal publication process management. This process and management are related to the pre-publishing, production process, and post-publishing. Therefore, this article describes the curriculum design to implement it into formal education, especially in higher education at the magister level. Since there is no formal education in scientific publication management in Indonesia, this curriculum design is the potential to develop. In its development, the curriculum is adopted based on existing related courses from several universities abroad. Those curricula are collected and compared for further development according to the needs. The results extract several courses divided into four semesters with detailed information related to the management of the scientific publication. It is expected that the graduates of this program be able to contribute to the scientific publication business and industry and fulfill the needs of scientific content both in quantity and quality.
VIRTUAL EDUCATIONAL ENVIRONMENT IN THE TRAINING OF A PROFESSIONALLY COMPETENT FOREIGN LANGUAGE TEACHER

The article characterizes the basis of the notion of a virtual educational environment: its interpretations, specific features and criteria. It also provides justification in favor of the importance of this concept in pedagogical training as well as a set of drawbacks. The analysis of scientific works of foreign and domestic researchers within the framework of the topic is carried out. The purpose of this article is to analyze and reveal the foundations of virtual learning environments from the point of view of its significance for a competent and developed teacher of a foreign language.
Data Soup Webinar, December 16, 2021: hosted by the Data Curation Network and the Journal of eScience Librarianship

Data Soup is a collaboration between the Journal of eScience Librarianship (JeSLIB) and the Data Curation Networkto host a series of community focused webinars/discussions to exchange practices for curating research data of different formats or subject areas among data curators. The lineup of the inaugural webinar includes the following speakers and topics from the recent JeSLIB Special Issue: Data Curation in Practice: Creating Guidance for Canadian Dataverse Curators: Portage Network’s Dataverse Curation Guide Alexandra Cooper, Michael Steeleworthy, Ève Paquette-Bigras, Erin Clary, Erin MacPherson, Louise Gillis, and Jason Brodeur, https://escholarship.umassmed.edu/jeslib/vol10/iss3/2; Active Curation of Large Longitudinal Surveys: A Case Study Inna Kouper, Karen L. Tucker, Kevin Tharp, Mary Ellen van Booven, and Ashley Clark, https://doi.org/10.7191/jeslib.2021.1210; Data Curation through Catalogs: A Repository-Independent Model for Data Discovery Helenmary Sheridan, Anthony J. Dellureficio, Melissa A. Ratajeski, Sara Mannheimer, and Terrie R. Wheeler, https://doi.org/10.7191/jeslib.2021.1203.
The AI Promotion Strategy of Korea Defense for the AI Expansion in Defense Domain

Recently, artificial intelligence has spread rapidly and popularized and expanded to the voice recognition personal service sector, and major countries have established artificial intelligence promotion strategies, but in the case of South Korea's defense domain, its influence is low with a geopolitical location with North Korea.This paper presents a total of six strategies for promoting South Korea's defense artificial intelligence, including establishing roadmaps, securing manpower, installing the artificial intelligence base, and strengthening cooperation among stakeholders in order to increase the impact of South Korea's defense artificial intelligence and successfully promote artificial intelligence.These suggestions are expected to establish the foundation for expanding the base of artificial intelligence.