Reviewerly/exHarmony huggingface dataset:
Constructing a Chain Event Graph from a Staged Tree.

Chain Event Graphs (CEGs) are a recent family of probabilistic graphical models - a generalisation of Bayesian Networks - providing an explicit representation of structural zeros and context-specific conditional independences within their graph topology. A CEG is constructed from an event tree through a sequence of transformations beginning with the colouring of the vertices of the event tree to identify one-step transition symmetries. This coloured event tree, also known as a staged tree, is the output of the learning algorithms used for this family. Surprisingly, no general algorithm has yet been devised that automatically transforms any staged tree into a CEG representation. In this paper we provide a simple iterative backward algorithm for this transformation. Additionally, we show that no information is lost from transforming a staged tree into a CEG. Finally, we demonstrate that with an optimal stopping time, our algorithm is more efficient than the generalisation of a special case presented in Silander and Leong (2013). We also provide Python code using this algorithm to obtain a CEG from any staged tree along with the functionality to add edges with sampling zeros.
Semi-supervised Sequence Classification through Change Point Detection

Sequential sensor data is generated in a wide variety of real-world applications. A fundamental machine learning challenge involves learning effective classifiers for such sequential data. While deep learning has led to impressive performance gains in recent years within domains such as speech, this has relied on the availability of large datasets of sequences with high-quality labels. In many applications, however, the associated class labels are often extremely limited, with precise labelling/segmentation being too expensive to perform in a high volume. However, large amounts of unlabelled data may still be available. In this paper we propose a novel framework for semi-supervised learning in such contexts. In an unsupervised manner, change-point detection methods can be used to identify instances where classes change within in a sequence. We show that change points provide examples of similar/dissimilar pairs of sequences which, when coupled with class labels, can be used in a semi-supervised classification setting. Pairs from labels and change points are used by a neural network to learn improved representations for classification. We provide extensive synthetic simulations and show that the learned representations are better than those learned through an autoencoder and obtain improved results on simulations and human activity recognition datasets.
The demographics of power relations

The author of this chapter, Valéria Bankóová, explores the role of Africa in a multilateral world from the perspective of African demographics. She draws on recent data from the UN’s global agenda for Sustainable Development Goals (SDGs) to shed light on two characteristics of Africa today: its younger population and exponential demographic growth. She highlights the geostrategic impact of this shift through three perspectives: African demographic history and the population forecast, the potential effects of this demographic growth, and the African position’s shift in the framework of the relationship between Africa and the EU. She explains that the African population started increasing at the beginning of the 20th century when measures were taken to fight endemic diseases, healthcare provision was increased, female education expanded, and infant mortality fell. At the same time, fertility rates increased, peaking by the 1970s. According to UN data, this process decreased more slowly than expected. Even if African countries undergo this process through different trajectories and rhythms, one thing remains valid for the continent as a whole: Africa is expected to account for roughly 60 per cent of all forecast world population growth by 2050. According to UN forecasting, this continent is viewed as the only region in the world where the population will continue increasing beyond 2050. Bankóová draws on the demographic dividend theory and the theory of youth bulges to explain how Africa can benefit from its demographic trajectory. To reap its demographic growth, Africa must meet various requirements, including the use of advanced technologies, an increase in youth employment, and the promotion of both healthcare and education. The chapter analyses recent improvements in the relationship between the EU and Africa as a case study on the development of Africa’s geostrategic position in the global world.
Towards a Transatlantic Approach to Cultural Engagement in African Design

In recent times, HCI has widens its horizon to a broad range of theoretical perspective and cultural stances that direct design practices. However, there appears to be a continual subjugation of ‘Other’ modes of knowing and theorising in contemporary discourse, which unfortunately finds solace in postcolonial approaches to HCI, and computing more generally. In this position paper, I outline the preliminary ideas about a transatlantic approach to cultural engagement in African design practices. In particular, it focuses on identifying and analysing the integrative aspect of the trinities of African cultures as to bring about an approximate adaptation (to new design context) and translation (to new design conditions) of diverse perspectives in African cultures of design.
Characterizing scalable quantum measures

The question of how quantities, like entanglement and coherence, depend onthe number of copies is addressed. We say that ${\cal E}(\rho^{\otimes N})$ is{\it scalable} if it is a physically consistent measure that can be describedas a function of the variables $\{{\cal E}(\rho^{\otimes i_1}), {\calE}(\rho^{\otimes i_2}),\dots,{\cal E}(\rho^{\otimes i_q}); N\}$ for $N>i_j$. Ifanalyticity is assumed, recursive relations can be derived for the Maclaurinseries of ${\cal E}(\rho^{\otimes N})$, which enable us to determine thepossible functional forms. In particular, we find that if ${\calE}(\rho^{\otimes 2^n})$ depends only on ${\cal E}(\rho)$, ${\calE}(\rho^{\otimes 2})$, and $n$, then it is completely determined by Fibonaccipolynomials, to leading order. We show that the one-shot distillable (OSD)entanglement is well described as a scalable measure for several families ofstates. For a particular two-qutrit state $\varrho$, we determine the OSDentanglement for $\varrho^{\otimes 96}$ from smaller tensorings, to leadingorder, with an accuracy of $97 \%$ and no extra computational effort. Finally,we show that superactivation of non-additivity may occur in this context.
Medical diagnosis based on single-valued neutrosophic information

Women with heart disease during pregnancy are at higher risk, which can harm the fetus. This risk can be reduced if wediagnose and treat it early. The decision-making system is very helpful in such situations. Many clinical decision-making systemshave been proposed, but they are too complicated for medical experts to understand and adapt. Here, we develop a new neutrosophicmodel for early diagnosis and explain it using explainable artificial techniques. Our model is taking eight symptoms and signsas inputs and determines the diagnosis, type of treatment, and prognosis. Age, obesity, smoking, family pathological history,personal pathological history, electrocardiogram, ultrasound, and functional class are the inputs of this model. Six diagnoses canbe made- obstruction at existing, obstruction at entry, rhythm disorder, conduction disorders, congenital diseases, genetic diseases.The types of treatments are- pregnancy interruption, diuretic treatment, anti-arrhythmic treatment, treatment with beta-blockersand anticoagulants treatment. The prognosis is- eutectic delivery, dystocic delivery, the child with complications, child withoutcomplications, mother with complications, and mother without complications. The main parts of this system are neutrosophication,knowledge base, inference engine, de-neutrosophication, and explainability. To present the entire execution of the proposed system,we design an algorithm and compute its time complexity to demonstrate the working of the entire system. We compared the resultsof different methods to gain confidence in our model.
Security Analysis of SVD-Based Watermarking Schemes and Possible Solutions

Copyright protection requires a robust image watermarking technique. With robustness, high imperceptibility is a much appreciated trait of a watermarked image. In past years, singular value decomposition (SVD) has emerged as a tool for robust image watermarking. SVD is frequently combined with transforms like discrete wavelet transform (DWT) and discrete cosine transform (DCT) to produce high-quality watermarked images. SVD-based watermarking can withstand large number of image processing attacks, but they are vulnerable to false positive (FP) problem. The false positive problem results in falsely establishing illegal user as the rightful owner of the image. In this paper, security analysis of SVD-based image watermarking techniques is provided. The inherent problems present in such methods are examined, and possible solutions are suggested.
Using maze-like gamification to boost learning skills in Chinese language / Noradila Abd Khalid

Multimedia is a mixture of text, graphics, animation, audio and video that is all we can see and hear in our everyday lives (Vaughan, 2006). Multimedia apps can be used in many fields, such as schools, companies, homes and government spaces. Gamification is a powerful tool for catalysing attention, focus and investment. Gamification transfers the mode, value and incentive of game play to a separate experience like buying groceries, visiting web sites, or even learning. The main problem that lead to this research is people does not know how gamification transfer, works and what makes it effective to students learning. Gamification can be applied to associate fun with learning. In essence, the student is hooked by the idea of the game, pulled forward by curiosity to learn more or win, and ends up enjoying the experience, becoming engaged in the idea or activity and opening themselves up to the possibility of learning. It can help students learn more faster and can remember for long time in learning new language since it required a lot of memories.
f-Aware Conflict Prioritization & Improved Heuristics For Conflict-Based Search

Conflict-Based Search (CBS) is a leading two-level algorithm for optimal Multi-Agent Path Finding (MAPF). The main step of CBS is to expand nodes by resolving conflicts (where two agents collide). Choosing the ‘right’ conflict to resolve can greatly speed up the search. CBS first resolves conflicts where the costs (g-values) of the resulting child nodes are larger than the cost of the node to be split. However, the recent addition of high-level heuristics to CBS and expanding nodes according to f=g+h reduces the relevance of this conflict prioritization method. Therefore, we introduce an expanded categorization of conflicts, which first resolves conflicts where the f-values of the child nodes are larger than the f-value of the node to be split, and present a method for identifying such conflicts. We also enhance all known heuristics for CBS by using information about the cost of resolving certain conflicts, and with only a small computational overhead. Finally, we experimentally demonstrate that both the expanded categorization of conflicts and the improved heuristics contribute to making CBS even more efficient.
An Effective Model of Terminating Phishing Websites and Detection Based On Logistic Regression

These days phishing is one of the greatest and the quickest developing risk in light of the fact that phishing assailants will get data which was entered by the client and phishing aggressors will utilize that data without the client information.At present personal information is the most important thing compared to money, So phishing website attackers are focusing on the personal information of the user and they taking advantage when the user enters there personal information in the phishing websites. So the main theme of these projects is to avoid misuse of personal information by phishing attackers. To overcome this problem machine learning algorithm such as Logistic regression is used and provided with the massive dataset. From that dataset, it trains the algorithm and helps in detecting the new web links which are fraudulent links. Attackers disguise their website as legitimate and try to get data from the user for which they make users visit a website and get the personal information that is needed. Before trying to enter into those websites it is important to check whether the given link is good or a phishing link. By checking the link we can save ourselves from the attackers and can keep our data safe.Keywords: Phishing, machine learning, Logistic regression, and website links.
THE DESIGN OF AN UNMANNED AERIAL VEHICLE

This paper revolves around the game-plan, appearing, usage and testing of a programmed automated airborne vehicle. The regulator depends on a got together with mechanical assembly to switch control between the RC control and the autopilot control (that is the multiplexer/shield, for the most part called MUX).This control course (following GPS waypoints) and height by controlling the rudder and choke. The structure utilizes flight adjustment structure (co-pilot), a sensor pack, Global Positioning System(GPS) and a RF handset to screen and report tremendous boundaries, for example, rise, speed ,pitch, roll, and position. A shown programming assessment has been made to pull in the aeronautical vehicle achieve the necessary self-affiliation and keep up commendable flight activity.
한국 대학생의 영어 문법 습득 난이도

The purpose of the present study is to investigate the difficulty of English grammar features by Korean EFL learners such as past tense of verbs, passive, 3rd person singular -s, comparative adjectives, yes/no question, auxiliary verbs, many/much, for/since, articles, subjunctive mood, dative alternation, infinitives. gerunds, participles, and relatives. To this end, a fill-in-the-blanks test of English sentences and a set of English proficiency tests were administered for 67 college students in Ulsan, Korea. The results showed significant differences in accuracy for gerunds between high and intermediate levels of learners. In the comparison of accuracy by high and low levels of learners were found significant differences for passive, 3rd person singular -s, yes/no question, auxiliary verbs, many/much, for/since, dative alternation, infinitives, gerunds, participles, and relatives. On the other hand, no significant difference was found for past tense of verbs, comparative adjectives, articles, and subjunctive mood across the groups of learners. Based on these findings, the study suggested that pedagogical priorities should be established to help Korean EFL university learners, particularly with past tense of verbs, subjunctive mood, and 3rd person singular -s, articles, and relatives. Finally, the study discussed difficulty in comparison with those of Rodriguez Silva(2017) and Cheng and Lee(2020).
The influences of Two Stay-Two Stray (TSTS) technique on students’ reading comprehension

The aim of this study is to know the influence of Two Stay-Two Stray (TSTS) technique on students’ reading comprehension. Reading is one of essential ways in building students’ knowledge. The researcher uses experimental research which uses two groups, those are experimental group and control group that consist of 46 students. The researcher elaborated the topics that were suitable for narrative text. Finding shows that the students who are taught by using conventional method, it can be proved from the average of speaking achievement. The students who are taught by using two-stay two-stray (76,43) have higher score than those taught by using direct method (68,21). Furthermore, based on the result of T-test, it is shown that sig.(0,002)<0,05. It means that the study indicated Two-stay Two-stray method is effective.
Phishing attack detection using machine learning method

The development of computer networks today is increased rapidly. This can be shown based on the trend of every computer user around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether they used it for work and assignment purposes, or for the access to social media accounts, such as Instagram, Facebook and Twitter. However, in this wide use of this computer network, the privacy of computer users is in danger. This is because some of the computer users do not install security system in their computer. This problem will allow the hackers to hack and commit the network attacks. This is very dangerous, especially to the important organizations because hackers can disable the online system in the company, steal confidential information and subsequently steal company money through online without being aware of any one. The attacks that can be made includes denial-of-Service attack, DNS spoofing attack and phishing attack. The goal of this study is to apply anti-phishing tools in preventing the network security attack in an organization. In this study, phishing attacks have been studied thoroughly. After a study has been made, machine learning method is used to prevent the phishing attack. Besides, the study also shows that phishing attack is always related to the spam attack, where there might be attached phishing link in the spam message. This spam message includes the email and the SMS message that received by the user. There are several algorithms that can be used in the machine learning method to prevent the both attacks. The Naive Bayes algorithm, Decision Tree algorithm and Support Vector Machine algorithm has been used to prevent the spam attack, as well as the phishing attack. The study of this algorithm is made thoroughly and the methods in implementing this algorithm have been discussed in detail. The experiment is conducted for the datasets that obtained by using machine learning method. The results are obtained, showing the performance of machine learning method on each dataset.
On the implementation of the right to education in the digital environment of the university

The article provides an overview of international documents and Russian normative legal acts that establish the right to education. The rights and obligations of educational organizations to ensure the right to education in the context of digitalization are noted. The possibilities and conditions for the implementation of educational programs with the use of e-learning and distance learning technologies are shown. Attention is drawn to the legalization of educational standards of the latest generation of the implementation of educational programs using digital technologies. In the aspect of local rulemaking, the system of acts regulating distance learning of the Kutafin University (MSLA) is demonstrated. It is concluded that in modern Russia, educational organizations have all the legal grounds to ensure the right of citizens to education through e-learning using distance learning technologies, but this subjective right is limited by the system of legal imperatives. The article presents the data of sociological studies conducted at the MSLA. Based on the analysis of their results, it was stated that the Kutafin University was ready for the digital challenges, providing students with the opportunity to realize the right to a high-quality higher education.
Hawg’s ClanWar Map Builder – Xvm [1.6.0.4]

Is a mod to build Tactical Maps, for Your Clan to Veiw in Battle and to help Prepare for ClanWars .This mod is a must for all Clans Officers. This mod ...
TINJAUAN KEGIATAN PEMUATAN BATU BARA DENGANMENGGUNAKAN FLOATING CRANE DI MUARA BERAU SAMARINDA

To achieve the implementation of the optimal loading coal by using a floating crane. So in writing this paper, the authors describe the theory about the implementation of the preparation and arrangement of the coal charge. Coal cargo has a special character in loads too, resulting in a load of coal must pay attention to the danger that is owned by the cargo when loading the activities carried out by floating crane.The method used by the writer is descriptive method qualitative, while the data collection method used is the method of observation and literature related to cargo handling, especially during unloading.From a review of the implementation of the coal loading by using a floating crane was found constraints in the preparation and execution of loading coal on the ship that is in preparation there are obstacles such as limited materials for treatment of floating crane, floating crane that loads too often stops pengoprasian. Constraints during loading is less skilled crane operators, unavailability loader vehicle, poor communication between the ship and crane operators.In this case it can be concluded that the lack of preparation at the moment before carrying out loading and lack of supervision of the personnel on board at the time of loading the exercise of the loading of coal is not optimal, advice Writer is for the company to pay more attention to the demand for floating crane, in order to improve care floating crane in preparation to load, then each crew to further improve supervision of the work of a floating crane during the loading process progresses.Keywords : Loading, Coal, Floating Crane
Deep Low-Contrast Image Enhancement using Structure Tensor Representation

We present a new deep learning framework for low-contrast image enhancement, which trains the network using the multi-exposure sequences rather than explicit ground-truth images. The purpose of our method is to enhance a low-contrast image so as to contain abundant details in various exposure levels. To realize this, we propose to design the loss function using the structure tensor representation, which has been widely used as high-dimensional image contrast. Our loss function penalizes the difference of the structure tensor between the network output and the multi-exposure images in a multi-scale manner. Eventually, the network trained by the loss function produces a high-quality image approximating the overall contrast of the sequence. We provide in-depth analysis on our method and comparison with conventional loss functions. Quantitative and qualitative evaluations demonstrate that the proposed method outperforms the existing state-of-the-art approaches in various benchmarks.
ECOLOGICAL WORLDVIEW FORMATION OF ENGINEERING STUDENTS IN THE CONTEXT OF FOREIGN LANGUAGE TRAINING

The educational space of a non-linguistic university makes it possible to conduct a purposeful process of forming the ecological worldview and culture of future specialists in the logic of their professional development. According to the authors, the eco-oriented content of teaching a foreign language can make a great contribution to the implementation of this mission due to the great general cultural and educational potential of this discipline. The paper offers a comprehensive theoretical substantiation of the problem under study, reveals the essence, structure and methodology of the ecological worldview formation of engineering students. The authors make an attempt to model the educational process on the basis of interactive pedagogical technologies, the use of which allows students of non-linguistic areas to solve communicative problems on the basis of environmental topics. The totality of data obtained as a result of the experimental work carried out by the authors confirms the effectiveness of students’ ecological worldview formation through the inclusion of environmental-oriented content in the system of language training at the university.