Reviewerly/exHarmony huggingface dataset:
Educational activities with Arduino to learn about astronomy

There is a need to promote better science, technology, and mathematics (STEM) education at all school levels. Arduino makes it possible by creating the next generation of STEAM programs that empower students on their learning journey through middle school, high school, and university. These kinds of technologies make it possible to make abstract concepts concrete and manipulable, far from the experience of children and young people, increasing the possibilities of learning. Following the constructionist ideas and practices, the National Institute for Astrophysics has developed play.inaf.it, a web platform that collects various coding, educational robotics, making, and tinkering activities, using astronomy and astrophysics as a tool to develop computational thinking and all the skills that are typical of scientific research in the STEM field. In this paper we want to present two projects created by the Play group. The first one aims to create, using an Arduino board, one LED and a photoresistor, an exhibit capable to describe one of the methods most used to identify exoplanets: the transit method, which exploits the fact that the brightness of a star decreases when the planet passes in front of it, with respect to our line of sight. Thanks to this project it is possible both to know Arduino and understand the information that astronomers can obtain from so-called light curves, such as the orbital period, the size of the planet, etc. The second activity aims to create and turn on one or more constellations using Arduino and some LEDs. In this way it will be possible to describe - through an active, cooperative, and operational approach - what are the stars, the constellations and the close relationship that has linked man to the sky since the dawn of time. Thanks to Arduino it is possible to encourage creativity, allowing everyone to give shape and substance to their ideas because the only limit we can set is our imagination
Coupling of Serendipity, Affordance and Taxonomy in Digital Competence: HCI for Illiterates

This research work is the result of multidisciplinary research for the design of a digital learning tool from the basic level.Computer science guarantees the technical concepts of the development of the tool.At the same time, Information and Communication Science discipline describes the concepts of cognitive psychology with digital competence in computerization.The overall goal of this work is to provide an HCI component for basic level learning or HCI for the illiterate.It is about transforming a communication tool from a cognitive system to a digital learning tool adapted to the learner's level of digital competence.The author relies on the UML class diagram to identify the affordance and serendipity of HCI property entities.The mathematical study of the similarity between these two properties allows us to update the learner's profile.Stephanie's approach was used when managing the learner's profile and the digital competency taxonomy to classify the learner's level of digital use.The principle of an expert system was taken up in this work to make the decision on the level of digital competence of the learner and to guide the solution so that the learning continues without interruption.This expert system integrates the data science of digital educational materials, defining its specificity.The algorithm of the realization summarizes the implementation of the whole approach.αβGasy@mobile is an application on Android for Malagasy language literacy.To learn the letter "l" with this application, the initially low-level learner had an intermediate assessment score after 2 hours of con-
AI GENERATED WORKS AND COPYRIGHT PROTECTION

The purpose of the article is to find the most promising and practical way of applying copyright to AI generated works, taking into account the objectives of copyright law and technological progress.Research methods.The methodology of this study includes analytical, comparative and dialectic methods of scientific research.Results.Due to the human-centered approach to authorship, the existing copyright legislation of most countries cannot provide protection for AI generated works.Even the concept of computer-generated works, implemented in the legislation of some countries, cannot fully resolve all complex issues concerning AI generated works, because it confers copyright on those, who design and operate AI systems.At the same time, another concept, proposed for AI generated works, regards such works as public property (public domain), which may be good for the general public, but not good for those who create and operate AI systems.As for the novel concept of electronic persons, providing legal personality for autonomous AI systems, this approach is quite flexible as it allows giving copyright to an AI system itself and enables the owner of such a system to control the exercise of copyright by this system.However, it may still take a while before this concept is finally appreciated and implemented.In fact, it may even require reaching the next stage of AI development, namely Artificial General Intelligence (AGI).Conclusions.At present, copyright law does not protect AI-generated works in most countries.Only a few countries have copyright legislation on computer-generated works applying to the works created by AI systems.According to this legislation, copyright is given to those who have undertaken the necessary arrangements in order for the computer to produce the works.Even though this approach protects the economic interests of those who design and operate AI systems, it cannot always provide a fair allocation of copyrights in situations, involving a large number of stakeholders, due to the complexity of such systems.Another idea is to treat AI generated works as public property (public domain).However, it cannot have a wide application, as it lacks the incentives for those who design and operate AI systems.In theory, it is also possible to give autonomous AI systems their own legal personhood enabling them to become copyright owners.In this case, autonomous AI systems with the legal status of electronic persons could be recognized as authors of the works they generated.This flexible approach also enables the owners of AI systems to control the exercise copyrights belonging to such systems.Although it is unclear if the concept of electronic person can be implemented at this point, it is quite likely to be recognized when the stage of Artificial General Intelligence (AGI) is reached.
Exploiting Language Model for Efficient Linguistic Steganalysis

Recent advances in linguistic steganalysis have successively applied CNN, RNN, GNN and other efficient deep models for detecting secret information in generative texts. These methods tend to seek stronger feature extractors to achieve higher steganalysis effects. However, we have found through experiments that there actually exists significant difference between automatically generated stego texts and carrier texts in terms of the conditional probability distribution of individual words. Such kind of difference can be naturally captured by the language model used for generating stego texts. Through further experiments, we conclude that this ability can be transplanted to a text classifier by pre-training and fine-tuning to improve the detection performance. Motivated by this insight, we propose two methods for efficient linguistic steganalysis. One is to pre-train a language model based on RNN, and the other is to pre-train a sequence autoencoder. The results indicate that the two methods have different degrees of performance gain compared to the randomly initialized RNN, and the convergence speed is significantly accelerated. Moreover, our methods achieved the best performance compared to related works, while providing a solution for real-world scenario where there are more cover texts than stego texts.
Liabilities of Shared System in Forensic Analysis

In today’s connected world, there is a tendency for connectivity even in the sectors which conventionally have been not so connected in the past, such as power systems substations. Substations have seen considerable digitalization of the grid hence, providing much more available insights than before. This has all been possible due to connectivity, digitalization, and automation of the power grids. Interestingly, this also means that anybody can access such critical infrastructures from a remote location, and gone are the days of physical barriers. The power of connectivity and control makes it a much more challenging task to protect critical industrial control systems. This capability comes at a price, in this case, increasing the liabilities and risk of potential cyber threats to substations. (ASIF, FARHAN , &amp; EKSTEDT) Keywords: Digital Evidence Backlog, Digital Forensic Challenges BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security &amp; Forensics. Open Access. Distributed Free Citation: Eric Sowah Badger (2022): Liabilities of Shared System in Forensic Analysis Book Chapter Series on Research Nexus in IT, Law, Cyber Security &amp; Forensics. Pp 191-196 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P31
Comparison of Modern Cryptography Methods

In this paper, different cryptography algorithms were reviewed, and their relative merits were discussed. Symmetric and asymmetric cryptography algorithms were compared for time and space efficiencies. These experiments were run to measure the execution time and the memory footprints of various algorithms to understand the implications of their real-life applications. In the experiment performed, it was observed that elliptic curve cryptography was the most efficient in terms of encryption/decryption time, as well as memory usage.
The Importance of Learning Resources for University Students During Emergency Remote Learning

Although several studies have evaluated online learning tools and resources, few have investigated how useful they are to students. This topic became even more relevant with “emergency remote learning” due to coronavirus disease 2019 (COVID-19). The present study was conducted at a state educational institution in Mexico that offers five university degrees. The objective was to differentiate the importance of online learning resources by degree and by employment status of the students. This quantitative, relational, cross-sectional study included 969 participants. Jamovi, SPSS, and RStudio were used to calculate descriptive statistics and to perform the Scheirer-Ray-Hare and Friedman tests. The results showed that the most important learning resources are lesson recordings, teacher explanations, instructional materials, and online demonstrations, whereas the least important are exams, videos, homework, and projects. These findings were consistent across the five degrees among students who are employed and those who are not. The results suggest that educational resources should be used according to their importance for student learning.
CHMM Object Detection Based on Polygon Contour Features by PSM

Since the conventional split-merge algorithm is sensitive to the object scale variance and splitting starting point, a piecewise split-merge polygon approximation method is proposed to extract the object contour features. Specifically, the contour corner is used as the starting point for the contour piecewise approximation to reduce the sensitivity of the contour segment on the starting point; then, the split-merge algorithm is used to implement the polygon approximation for each contour segments. Both the distance ratio and the arc length ratio instead of the distance error are used as the iterative stop condition to improve the robustness to the object scale variance. Both the angle and length as two features describe the shape of the contour polygon, and affect each other along the contour order relationship. Since they have a strong coupling relationship. To improve the description correction of the contour, these two features are combined to construct a Coupled Hidden Markov Model to detect the object by calculating the probability of the contour feature. The proposed algorithm is validated on ETHZ Shape Classes and INRIA Horses standard datasets. Compared with other contour-based object detection algorithms, the proposed algorithm reduces the complexity of contour description, improves the robustness of contour features to scale variance, and has a higher object detection rate.
Wireless sensor network enabled real-time remote intelligent health monitoring and management system using Internet of Things (IoT) sensing with cloud-based processing during covid-19 situation

Abstract Mankind was living quite an ordinary life when Covid 19 pandemic struck. The whole world was in turmoil and was busy trying to make the situation normal again. But it was impossible to regain the old scenario and people had to accept the new normal. The new normal demands people to follow different guidelines out of which maintaining a social distance of 6 feet was a prominent one. Even in this situation occurrence of any disease does not stop and there are always some patients visiting a doctor. Also, a doctor doesn't always have the luxury to visit every place to see patients, especially in rural areas where there is a transportation problem. So we have come up with a cloud-based system that will use the internet of things to diagnose a patient. This device will contain different sensors like temperature sensor, body oxygen level sensor, blood pressure sensor, heart rate sensor, and height and weight measuring gadgets to measure the body parameters of the patient and then store this information in the secured cloud which can then be accessed by the doctor to diagnose the patient. The sensors will be embedded in an Arduino and it will be connected to the cloud wirelessly with the help of a GSM module and node MCU. Also, a laptop will be present to connect the patient and the doctor in video mode for conversations. This system will also generate a prescription provided by the doctor which can be used anywhere. Thus, this device will not only promote social distancing but also it will prohibit the spread of diseases that are communicable. The doctors can work from the comfort of their home without touching a patient and also without traveling long distances to remote locations.
Investigation of Asymptomatic Malaria Transmission through Mass Surveillance Campaign in Gadchiroli, Maharashtra. 1

Gadchiroli district is majorly covered with forest, and most of the population is tribal, living in the vicinity of the forest. The district is located on the eastern side of Maharashtra. As per the 2011 India census, Gadchiroli recorded a total population of 10,71,795. Males constituted 51% of the population and females 49%. Approximately 11% of the population of Gadchiroli was under six years of age, and almost 90% of the child population stays in the rural part of Gadchiroli. Annual rainfall for the Gadchiroli district is approximately 1,000 mm in the monsoon season from June to September. Gadchiroli is a hotspot for malaria disease in Maharashtra. More than 50% of malaria cases in Maharashtra are observed in Gadchiroli. A special malaria campaign of mass survey for identification of active transmission is carried out in 15 malaria-sensitive PHCs in Gadchiroli from mid of February 2021 to the end of March 2021. About 76% population was tested by microscopic, and 11 % population was screened by Rapid Diagnostic Kit. A total of 164 asymptomatic malaria carriers were identified with 25% gametocytes. Identifying these asymptomatic transmissions followed by complete radical treatment towards malaria elimination is suggested.
Maximal complete permutations over $ \mathbb{F}_2^n $

<p style='text-indent:20px;'>We study maximal complete permutations over <inline-formula><tex-math id="M2">\begin{document}$ \mathbb{F}_2^n $\end{document}</tex-math></inline-formula>, i.e., complete permutations have a single fixed point and a cycle of length <inline-formula><tex-math id="M3">\begin{document}$ 2^n-1 $\end{document}</tex-math></inline-formula>. We characterize several classes of Boolean functions with some linear structures. By using some <inline-formula><tex-math id="M4">\begin{document}$ \gamma $\end{document}</tex-math></inline-formula>-cycle permutations, triple-cycle permutations and involutions which are related to Boolean functions having some linear structures, three general constructions of maximal complete permutations are presented from a given maximal linear complete permutation of <inline-formula><tex-math id="M5">\begin{document}$ \mathbb{F}_2^n $\end{document}</tex-math></inline-formula>. Besides, maximal complete permutations are also constructed through composing certain maximal complete permutations with themselves.
Dichotomy between Modernity and Nepalese Education System: A Qualitative Analysis

This paper aims to critically assess the impact of modernism upon Nepalese local and indigenous knowledge systems. The paper highlights that modernism is a challenge, as well as an opportunity for the indigenous community and their knowledge systems. This is a challenge because of its potent threats to collapsing the originality and knowledge tradition the local communities have. And, this is an opportunity because of extending and widening its scope and recognition in the global market with a societal or national space. The paper was based on the qualitative research methodology in which numbers of Focus Group Discussion were carried out to generate the data. The paper explores that there is no need for indigenous communities and local knowledge holders to turn back to their tradition by entirely giving up their interests to become a modern one. Nor has there been a compulsion to abandon their oral traditions and wisdom to become an updated modern one. One of the impacts of modernity on Nepali education is privatization which has devalued the local or indigenous knowledge system. The paper, therefore, advises us on an education system that adapts some theoretical concepts that work as a bridge between local/indigenous knowledge system and modern knowledge system enriching local/indigenous knowledge and grasping good ethos of modernity.
A Morphosyntactical Analysis of University Students’ Writing: Indonesian Case

Different grammar between languages often causes confusion to those who learn it. Students often experience such problems when their first language (L1) and the target language (L2) share very limited linguistic aspects. This study aims to focus on the morphosyntactic issues that lead to the grammatical errors which take place in the English writing of Indonesian university students taking writing class and to analyze the potential sources of their mistakes. The data from this study were collected from a writing assignment in three Writing classes. This research followed the steps initiated by James (1998), among others: collecting data, identifying errors, classifying errors, explaining errors, and finding sources of errors. The results revealed that of the 2.218 grammatical errors found, they could be classified into two main error types: morphological errors (81.97%) and syntactic errors (18.03%) which were divided into 32 specific errors. The findings suggest that the Indonesian students are not fully aware how to use the plural marker ‘s’ as well the ‘3rd singular’ in present tense. Moreover, they cannot build a simple sentence due to the different word-order and sentence structure between Indonesian and English in terms of morphology and syntax.With regard to the potential sources of error, both inter-language errors and intralingual errors and developments have an influence on errors made in writing. Errors between languages occur when students try to use their knowledge of the L1 structure to obtain the target language, but the differences between the two languages cause errors. Intralingual and developmental errors are found because of difficulties and problems in the target language itself. The findings in this study are very useful for the process of learning English especially in writing skills.
Intrinsic motivations and open-ended learning

There is a growing interest and literature on intrinsic motivations and open-ended learning in both cognitive robotics and machine learning on one side, and in psychology and neuroscience on the other. This paper aims to review some relevant contributions from the two literature threads and to draw links between them. To this purpose, the paper starts by defining intrinsic motivations and by presenting a computationally-driven theoretical taxonomy of their different types. Then it presents relevant contributions from the psychological and neuroscientific literature related to intrinsic motivations, interpreting them based on the grid, and elucidates the mechanisms and functions they play in animals and humans. Endowed with such concepts and their biological underpinnings, the paper next presents a selection of models from cognitive robotics and machine learning that computationally operationalise the concepts of intrinsic motivations and links them to biology concepts. The contribution finally presents some of the open challenges of the field from both the psychological/neuroscientific and computational perspectives.
Essential Sentences for Navigating Stack Overflow Answers

Stack Overflow (SO) has become an essential resource for software development. Despite its success and prevalence, navigating SO remains a challenge. Ideally, SO users could benefit from highlighted navigational cues that help them decide if an answer is relevant to their task and context. Such navigational cues could be in the form of essential sentences that help the searcher decide whether they want to read the answer or skip over it. In this paper, we compare four potential approaches for identifying essential sentences. We adopt two existing approaches and develop two new approaches based on the idea that contextual information in a sentence (e.g., "if using windows") could help identify essential sentences. We compare the four techniques using a survey of 43 participants. Our participants indicate that it is not always easy to figure out what the best solution for their specific problem is, given the options, and that they would indeed like to easily spot contextual information that may narrow down the search. Our quantitative comparison of the techniques shows that there is no single technique sufficient for identifying essential sentences that can serve as navigational cues, while our qualitative analysis shows that participants valued explanations and specific conditions, and did not value filler sentences or speculations. Our work sheds light on the importance of navigational cues, and our findings can be used to guide future research to find the best combination of techniques to identify such cues.
Definitions and Semantic Simulations Based on Object-Oriented Analysis and Modeling

We have proposed going beyond traditional ontologies to use rich semantics implemented in programming languages for modeling. In this paper, we discuss the application of executable semantic models to two examples, first a structured definition of a waterfall and second the cardiopulmonary system. We examine the components of these models and the way those components interact. Ultimately, such models should provide the basis for direct representation.