Reviewerly/exHarmony huggingface dataset:
REACTIVE GAMES AS AN EXAMPLE OF EXTENSIVE USE OF EVOCATIVE NARRATIVE ELEMENTS IN DIGITAL GAMES: THE CASES OF DWARF FORTRESS AND RIMWORLD

There are many types of digital games -some focus more on new gameplay mechanics while others focus more on new ways to tell and deliver their stories.Some games, in their goal of creating more engaging narratives, push the environmental storytelling and evocative narrative elements to their limits, allowing for a unique emergent narrative experience for players.Consequently, players now recognize a specific type of game, calling them, "reactive games", in which the events and story of the gameworld occur without the need for the input of the player, who instead must react to the events and problems the game sends their way.This article presents two examples of reactive games which create a unique gameplay experience by exploiting the limits of environmental storytelling, evocative narrative elements, and emergent narrative: Dwarf Fortress and RimWorld.
REFLECTIVE PRACTICE AS A MEANS OF CRITICAL THINKING DEVELOPMENT IN DISTANCE LEARNING WITH UNIVERSITY STUDENTS

Distance learning is getting one of the most popular and inevitable methods of learning and teaching nowadays, which insistently changes the vector in instructions. The education policy, nevertheless, is aimed to achiving the highest level in quality of learning and teaching, as the technologies are changing and requiring relevant level of professional competency, particularly, highly developed 21st-century skills from the graduate students. The teachers, practitioners, and university educators should look for efficient technologies in online learning, saving the students' motivation, and developing the important skills necessary for future professional development. The issue of finding the efficient ways in online learning is becoming one of the leading priorities in organization of the teaching and learning process. This study is sought to analyze the modern research sources about the effective methods teaching online not only develop critical thinking competency as an essential skill of professional portrait, but also enhance students' motivation to study. It also investigates the theoretical background related to reflective practice in university training, after that, it investigates the possible ways of applying reflective practice strategies as a tool for critical thinking skills development. The analysis of recent studies revealed the most sought-after ways of reflective practice strategies which can be widely used online. The result of the analysis provided support in favour of wide-spread methods, which proved their application in various experiments and practical implications, for example, e-portfolios, reflective journals, blogging, MOOCs, which significantly increase students' critical thinking. The implication of this study may be seen in practical development of online courses and assignments for students in todays' university educational process. Keywords: critical thinking; distance learning; reflective practice; university students; critical thinking skills development.
Καταγραφή αναγκών και ευαισθητοποίησης για το φαινόμενο του εκφοβισμού σε σχολεία της πρωτοβάθμιας εκπαίδευσης στην περιοχή της Αθήνας

ABSTRACT IS AVAILABLE IN THE PDF
An Efficient Image Contrast Enhancement Method using Sigmoid Function and Differential Evolution

Image enhancement is an adjusting process to make an image more appropriate for certain applications. The contrast enhancement is one of the most frequently used image enhancement methods. In this study, we introduce a new image contrast enhancement method using a link between sigmoid function and Differential Evolution (DE) algorithm. DE algorithm is performed to identify the parameters in sigmoid function so that they can maximize the measure of contrast. The experimental results show that the proposed method not only retains the original image features but also enhances the contrast effectively. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
Design and Implementation of NLP-based Spell Checker for the Tamil Language

A spell checker is a tool used for analyzing and validating spelling mistakes in the text. Recently, the role of a spell checker has diversified, and it is also used to suggest possible corrections to the detected spelling mistakes. Tamil is one of the oldest surviving and international spoken languages of the world, and it is grammatically very rich. Grammar is vital for effective communication and information transmission. However, learning the language rules and the old teaching methodology becomes a challenge for the researchers. The amalgamation of computer and language using natural language processing (NLP) provides a solution to this problem. In this paper, an advanced NLP technique is used to detect wrongly spelled words in the Tamil language text, and to provide possible correct word suggestions and the probability of occurrence of each word in the corpus. The proposed model recommends correct suggestions for the misspelled words using the minimum edit distance (MED) algorithm, which is customized for the Tamil vocabulary. A distance matrix is created between the misspelled word and all possible permutations of the word. Dynamic programming is used for calculating the least possible changes needed to correct the misspelled words, and suggesting the most appropriate words as the corrections.
In-plane vibration detection using sampling moiré method

Abstract Various methods have been proposed to measure vibration frequency. However, mechanical systems are not efficient as they have to be attached to the object of interest. So, the measurements are not precise when a new mass is introduced to the vibration surface. Besides, obtaining the power and phase distribution on the whole surface of the vibrating object is not possible through using accelerometers or other mechanical vibrometers. Out-of-plane vibration detection was previously proposed by one of the authors, using one pitch phase analysis method. In this paper, a novel accurate in-plane vibration detection technique by using sampling moiré method is proposed. This paper is the first published report on the in-plane vibration distribution of an industrial scale size object. Since noncontact deformation distribution of a deformed body is possible using sampling moiré method, in this study sampling moiré method is applied to vibration analysis of a tuning fork using a high-speed camera. This paper shortly describes the principle of in-plane vibration detection method and compares the experimental in-plane frequency results with those obtained by an accurate laser displacement meter. Moreover, for the first time, power and phase distribution graphs of the whole surface of the tuning fork, in two different frequency modes, are obtained. This technology will be useful for vibration investigation in any movable object on an industrial scale.
Improvement of Scientific Attitudes Through Training of Social Science Scientific Writing in MAN 2 Model Banjarmasin

Scientific works are essays containing scientific ideas that are presented scientifically and use scientific forms and language. Scientific writing brings up scientific problems that are focused on one particular discipline. This article aims to describe the implementation of scientific paper writing training for students in MAN 2 Model Banjarmasin. So that led to the scientific attitude of the writing team. The lecture and assignment methods were carried out during the training from 24 February to 09 March 2020. The results of the service were presented that writing scientific papers, writers must understand the stages of work; first, make ideas in thought. This idea emerged from the reference book, as well as the results of discussions with colleagues. Second, the writer must express his ideas in narrative form (writing). The work process between stages one and two varies greatly for each author. This matter is influenced by experience and habits. However, the second process has an integrated and systemic stage, so that it can provide clarity on the subject of scientific writing for the writer. The next activity is expected to focus on what social themes are relevant to be written in the form of scientific papers.
Research Trend of Causal Machine Learning Method: A Literature Review

Machine learning is commonly used to predict and implement pattern recognition and the relationship between variables. Causal machine learning combines approaches for analyzing the causal impact of intervention on the result, asumming a considerably ambigous variables. The combination technique of causality and machine learning is adequate for predicting and understanding the cause and effect of the results. The aim of this study is a systematic review to identify which causal machine learning approaches are generally used. This paper focuses on what data characteristics are applied to causal machine learning research and how to assess the output of algorithms used in the context of causal machine learning research. The review paper analyzes 20 papers with various approaches. This study categorizes data characteristics based on the type of data, attribute value, and the data dimension. The Bayesian Network (BN) commonly used in the context of causality. Meanwhile, the propensity score is the most extensively used in causality research. The variable value will affect algorithm performance. This review can be as a guide in the selection of a causal machine learning system.
Today’s Usage of Neologisms in Social Media Communication

Referring to a newly formed word that accommodates the usage of a language at a particular time, the term neologism presents a relatively recent or isolated term, word, or phrase that may undergo the process of entering everyday usage, but that has not been fully accepted into language. They appear to be strongly influenced by changes in society, especially in culture and technology, and recently by rapid advancements in internet-based communication. However, due to their significant use, they seem to be widely and quickly accepted in social networking sites around the globe (Facebook, Twitter, Instagram and WhatsApp). These social networking sites have had a significant impact on everyone nowadays as they improve and speed up communication, foster relationships and also boost business ventures. The hypothesis of this paper states that neologisms created by different morphological processes are excessively used in internet-based communication, for which purpose the examples from four most popular social networks have been extracted and compared. The results of the analysis have shown an extremely high percentage of the usage of neologisms in social networking sites.
Training of motor vehicle profile specialists in the conditions of digitalization

The urgency of the digitalization process is directly related to the need for the transition of society around the world to a new level of development, and the catalyst for this process is the formation of general digital literacy as a component of digital competence and readiness to use digital technologies in professional activities. The article analyzes the main trends in the digitalization of vocational (technical) education and highlights the main aspects of modern development of the automotive industry. The system of training of specialists of motor transport profile and innovative pedagogical technologies, which are used for their training in institutions of professional (vocational) education, are investigated. The main competencies that should be possessed by a competitive specialist in the field of motor transport in the digital age are highlighted. Modern learning technologies are considered, with an emphasis on digitalization and features of the modern young generation Z, which are used to form the competencies of specialists in the field of motor transport.
View adaptive learning for pancreas segmentation

Pancreatic segmentation is a fundamental step in computer-aided diagnosis of the pancreatic cancer. Although 3D U-Net has been dominantly used for this task, it still suffers from limited ability to represent the 3D context in volumetric data. In this paper, we propose the view adaptive 3D U-Net (VA-3DUNet) method for pancreas segmentation in contrasted-enhanced abdominal computed tomography (CT) volumes. Adopting the location-to-segmentation strategy, we first train a 3D U-Net for pancreas localization, and then train another 3D U-Net in a view adaptive way to segment the pancreas in the volume of interest (VOI) determined in the localization step. Such view adaptive training enables the 3D U-Net to perceive each volumetric data from the axial, coronal, and sagittal views simultaneously and hence improves its ability to represent the 3D context. We evaluated the proposed VA-3DUNet method against four state-of-the-art methods on the NIH pancreas segmentation dataset and achieved an average Dice similarity coefficient of 86.19%, which is higher than that achieved by those competing methods. Our results demonstrate the effectiveness of the view adaptive training and the satisfactory performance of the proposed VA-3DUNet method in pancreas segmentation.
ADVANCED ENCRYPTION STANDARD USING FPGA OVERNETWORK

The increase number of eavesdropping or cracker to attack the information and hack the privacy of people. So, the essential issue is making system capable of ciphering information with rapid speed. Due to the advance in computer eavesdropping and cracker that made them to analysis the way of ciphering in rapid speed way. The development in the computer especially in the rapid processer in the last decade create the breaching of any system is a matter of time. Owing to most of breaching ways are based on analysis of system that requireы to be breached and to try brute force on that system to crack it. However, the lacking of influential processers that are capable of breaching system since earlier processors are limit to number of instructions. It can be done in second, which was not sufficient trying to break the system using brute force. In addition, the time required is far away from getting valuable messages in the time that needed. So, the research gives the focus on performing rapid system for ciphering the information rapidly and changing the ciphering every few milliseconds. The changing of ciphering in every millisecond helps system form preventing the eavesdropping and cracker from imposing brute force on the system and hacking the messages and images. The system that created is based on Advanced Encryption Standard (AES), which is it very best performing algorithm in ciphering and deciphering since it doesn’t need complex mathematical formula. The research is about designing system that capable of performing AES by using high processer designed on Field programmable gate Area (FPGA). The ciphering of AES using FPGA helps minimize the time required to cipher the information. Also, the research will focus on ciphering and deciphering of images by AES using FPGA
An Overview of the various Smart Contract Platforms in Blockchain

Blockchain is a simple and powerful platform for creating and deploying smart contracts .Its main aim is to remove the barriers in the deployment of blockchain especially for the financial sector. It provides the privacy and control required by them. It is called as smart contract because these are
Digitalisation Practices in South-African State-Owned Enterprises: A Framework for Rapid Adoption of Digital Solutions

The dawn of the 4IR (4 th Industrial Revolution) brought about numerous opportunities for digitisation of South African State-Owned Enterprises (SOEs).Yet, it is uncertain to what extent these SOEs are positioned to embrace 4IR opportunities and address the challenges.In this paper we investigate the value of SOEs in South Africa (SA) as a developing economy as well as important components of the 4IR and SA government initiatives to embrace the 4IR.Amongst others, Blockchain, Advanced Analytics, AI, and the IoT have been identified as important 4IR components.On the strength of a literature review, a number of propositions is defined and these together with existing technology adoption frameworks, notably the Technology-Organisation-Environment (TOE) framework are used to define a digitalisation framework for 4IR adoption by SA SOEs.Key to the framework is collaboration among individuals in the 4IR.The framework is subsequently validated conceptually by linking it to the stated propositions.
An Efficient Algorithm for the Incremental Broad Learning System by Inverse Cholesky Factorization of a Partitioned Matrix

In this paper, we propose an efficient algorithm to accelerate the existing Broad Learning System (BLS) algorithm for new added nodes.The existing BLS algorithm computes the output weights from the pseudoinverse with the ridge regression approximation, and updates the pseudoinverse iteratively.As a comparison, the proposed BLS algorithm computes the output weights from the inverse Cholesky factor of the Hermitian matrix in the calculation of the pseudoinverse, and updates the inverse Cholesky factor efficiently.Since the Hermitian matrix in the definition of the pseudoinverse is smaller than the pseudoinverse, the proposed BLS algorithm can reduce the computational complexity, and usually requires less than 2 3 of complexities with respect to the existing BLS algorithm.Our experiments on the Modified National Institute of Standards and Technology (MNIST) dataset show that the speedups in accumulative training time and each additional training time of the proposed BLS over the existing BLS are 24.81%∼37.99% and 36.45%∼58.96%, respectively, and the speedup in total training time is 37.99%.In our experiments, the proposed BLS and the existing BLS both achieve the same testing accuracy when the tiny differences (≤ 0.05%) caused by the numerical errors are neglected, and the above-mentioned tiny differences and numerical errors become zeroes and ignorable, respectively, when the ridge parameter is not too small.
Assessing the behavior and performance of a supervised term-weighting technique for topic-based retrieval

Topic-based retrieval is the task of seeking and retrieving material related to a topic of interest. This task involves two subtasks: selecting query terms and ranking the retrieved results. Supervised approaches to assess the importance of a term in a topic or class have demonstrated to be effective for guiding the query-term selection subtask. This article analyzes and evaluates FDDβ, a supervised term-weighting scheme that can be applied for query-term selection in topic-based retrieval. FDDβ weights terms based on two factors representing the descriptive and discriminating power of the terms with respect to the given topic. It then combines these two factor through the use of an adjustable parameter that allows to favor different aspects of retrieval, such as precision, recall or a balance between both. Previous preliminary studies have demonstrated the potential of FDDβ to identify useful query terms. However, preceding studies have limited the analysis to a single domain represented by a single data set with binary categories and have not compared FDDβ to other recently formulated term-weighting techniques. The contributions of this article are the following: (1) it presents an extensive analysis of the behavior of FDDβ as a function of its adjustable parameter; (2) it compares FDDβ against eighteen traditional and state-of-the-art weighting scheme; (3) it evaluates the performance of disjunctive queries built by combining terms selected using the analyzed methods; (4) it makes a full data set and the full code publicly available to replicate the reported analysis and foster future research in the area. The analysis and evaluations are performed on three data sets: two well-known text data sets, namely 20 Newsgroups and Reuters-21578, and the newly released data set. It is possible to conclude that despite its simplicity, FDDβ is competitive with state-of-the-art methods and has the important advantage of offering flexibility at the moment of adapting to specific task goals. The results also demonstrate that FDDβ offers a useful mechanism to explore different approaches to build complex queries.
rl_reach: Reproducible reinforcement learning experiments for robotic reaching tasks

Training reinforcement learning agents at solving a given task is highly dependent on identifying optimal sets of hyperparameters and selecting suitable environment input/output configurations. This tedious process could be eased with a straightforward toolbox allowing its user to quickly compare different training parameter sets. We present rl_reach, a self-contained, open-source and easy-to-use software package designed to run reproducible reinforcement learning experiments for customisable robotic reaching tasks. rl_reach packs together training environments, agents, hyperparameter optimisation tools and policy evaluation scripts, allowing its users to quickly investigate and identify optimal training configurations. rl_reach is publicly available at this URL: https://github.com/PierreExeter/rl_reach.
Media Literacy and Social Responsibility of Educators in the Conditions of Information War: The Problem Statement

The article raises the need to develop theoretical, methodological, and practical principles of media literacy in various target groups traditionally not covered by media education (including adults and older persons). One of the key objectives is to promote the implementation of the Paris Declaration on Media and Information Literacy in the Digital Era (2014): privacy, digital security, and information handling ethics. Methodological research principles of media literacy and social responsibility are based on interdisciplinary and transdisciplinary approaches. The article shows that digital culture, the Internet, and computer algorithms are not morally neutral. There is a close link between media literacy and social responsibility and human rights. Therefore, the focus of this and future research is the question: to what extent do the media contribute to expanding human freedom. After all, there is a real danger – narrowing the sphere of freedom and manipulation of thought. The research also pays special attention to the adult people (who are not seriously involved in the media literacy development projects) and the role of educators’ social responsibility in the face of the hybrid war challenges.
The usage of Vue JS framework for web application creation

The paper concentrates on the positive sides of front-end frameworks. It creates a small webpage that will show some of the basic capabilities of a JavaScript front-end framework called Vue JS and the easiness of its implementation. It shows why is there a need for frameworks in development and how can companies use them for their benefit. Since they can be used and speed up development processes they can be learned in schools for an easier grasp of development concepts.