Reviewerly/exHarmony huggingface dataset:
Steering Witness and Steering Criterion of Gaussian States

Quantum steering is an important quantum resource, which is intermediate between entanglement and Bell nonlocality. In this paper, we study steering witnesses for Gaussian states in continuous-variable systems. We give a definition of steering witnesses by covariance matrices of Gaussian states, and then obtain a steering criterion by steering witnesses to detect steerability of any (m+n)-mode Gaussian states. In addition, the conditions for two steering witnesses to be comparable and the optimality of steering witnesses are also discussed.
FORMATION OF SOFT SKILLS OF FUTURE TEACHERS AS A CONDITION FOR IMPLEMENTATION OF THE TEACHER’S PROFESSIONAL STANDARD

The authors of the article consider the options for organizing the educational activities of future teachers to form soft skills as a condition for implementing the professional standard of a teacher. The professional standard of a teacher is considered and a number of competencies are singled out, the formation of which depends on the development of soft skills. In this regard, the problem of professional training of future teachers is considered in the context of the relationship of goals and objectives with the types of work activities and competencies presented in the professional standard of teachers. As an important result, along with professional competencies, the development of students’ abilities in communication, leadership, cooperation, diplomacy, building relationships is considered; formation of team, public, thinking skills; ability to present their ideas, make decisions, creatively solve professional problems, including social plan and others. The results of the survey of teachers, educators and stakeholders on the problem of soft skills formation are analysed, and difficulties in their formation are revealed. In particular, the analysis of such experience and the results of questionnaires of teachers and students showed, on the one hand, the demand for such skills, but on the other – the lack of readiness of many teachers to form soft skills in the educational process. A map of soft skills development in pedagogy classes is proposed, in particular, the potential of using the “flipped classroom” model as one of the advanced technologies for building the educational process is revealed. Characteristics of the content, forms and technologies of soft skills development at Pavlo Tychyna Uman State Pedagogical University, as well as their own experience in organizing educational activities, allowed us to draw conclusions about the importance of developing soft skills for future teachers to ensure the success of their professional activities.&#x0D; Keywords: formation; soft skills; hard skills; future teachers; professional standard of a teacher; educational process; institution of higher education; modern forms and technologies of education; “flipped classroom”.
TEACHER’S SELF-EDUCATION AS A GUARANTEE OF IMPROVING PROFESSIONAL PEDAGOGICAL SKILLS

The article briefly describes the psychological and pedagogical, socio-economic and scientific-technological prerequisites for improving the professional skills of a teacher of a modern higher education institution.&#x0D; The author touches upon the problems of forming the pedagogical skills of a high school teacher in the context of today, analyzes the dynamics of requirements for him over the past decades and, in particular, during the lockdown period associated with the COVID-19 pandemic. &#x0D; A number of research methods were used: analysis and systematization of scientific sources that reveal the goals and means of improving the pedagogical skills of teachers, in particular, given the problems of teaching in a pandemic COVID-19 and related quarantine facilities; terminological analysis necessary to clarify and differentiate key research definitions; theoretical modeling of processes of increase of professional skill of the scientific and pedagogical worker by means of his self-education; empirical observations - to study current issues of teaching.&#x0D; The author outlines the current factors stimulating the process of increasing the self-educational competence of a teacher of higher education, in particular, the informatization of the educational space, which becomes mandatory in modern conditions. An overview of innovative self-educational tools is made, attention is paid to the role of the administration of higher education institutions in their implementation. The conclusion is made about the need to design and implement tools to increase the self-educational competence of research and teaching staff in modern conditions. The value of the teacher&amp;apos;s self-educational competence is clarified.. The traditional list of principles of self-education (systematic and consistent; focus on practical activities; complexity) and the means of their implementation in the practice of improving the pedagogical skills of a teacher of higher education is analyzed. The inclusion of such principles as interdisciplinarity, innovation, efficiency and mobility, which reflect the proven constant possibility of rapid changes in the educational environment and in the world in general, is justified.
Project Work in Moroccan EFL Classroom: between the Official Guidelines’ Recommendation and the Challenges of Implementation

Project work is used in several educational settings, including foreign and second language teaching contexts. In the Moroccan English as a foreign language (EFL) classroom, the Moroccan Ministry of Education recommended implementing project work, and it is a common component of the Moroccan textbooks of English. Yet, there is a scarcity of studies conducted on the use of project work in Moroccan EFL classrooms. The main aim of the study is to investigate students’ and teachers’ attitudes towards project work. The study addresses the question about students’ and teachers’ attitudes towards project work and the factors behind those attitudes. It was conducted with sixty students and eight teachers belonging to two different high schools (Moulay Rachid and Abbas Sebti high schools) in Tangier. To collect data, the researcher made use of two data collection methods, namely the questionnaire and the interview. The results of the study showed that both students and teachers had positive attitudes towards project work. The results also revealed that not all teachers follow the steps of using project work. Based on the results, it was clear that the lack of technology is one of the most severe challenges that hamper the use of project work. The findings of this study could form the basis for further research and contribute to improving the learning and teaching situation in Moroccan high schools.
Handwritten Character Recognition Using Unsupervised Feature Selection and Multi Support Vector Machine Classifier

In recent times, identifying Kannada, Arabic and English handwritten characters is a challenging task in pattern recognition application.The low resolution, complex backgrounds, text orientation, text size, and the variations in the writing styles makes character recognition as a challenging task.To address the above stated issues, a new automated character recognition model is introduced in this paper.Firstly, skewed line segmentation technique is applied to the handwritten character for dissecting the document images into line elements and then split into phrases and single characters.Next, AlexNet model is used for extracting the deep features from the individual characters, where the extracted feature vectors are multi-dimensional in nature that increases the system complexity.So, an unsupervised feature selection algorithm is proposed to select the active feature vectors that are fed to multi support vector machine classifier for individual character classification such as 64 classes in English language, 10 classes in Arabic language, and 657 classes in Kannada language.Experimental analysis showed that the proposed model obtained 85.80%, and 95.55% of accuracy on the chars74K dataset for Kannada, and English characters, respectively.In addition, the proposed model obtained 71.79%, and 99.97% of recognition accuracy in Kannada and Arabic handwritten character recognition on a real time dataset and MADbase digits dataset.The obtained results are better compared to the existing deep learning models; DIGI-Net, feed forward neural network, and context aware model.
A Comparative Analysis of C4.5 Classification Algorithm, Naïve Bayes and Support Vector Machine Based on Particle Swarm Optimization (PSO) for Heart Disease Prediction

Heart disease is a general term for all of types of the disorders which is affects the heart. This research aims to compare several classification algorithms known as the C4.5 algorithm, Naïve Bayes, and Support Vector Machine. The algorithm is about to optimize of the heart disease predicting by applying Particle Swarm Optimization (PSO). Based on the test results, the accuracy value of the C4.5 algorithm is about 74.12% and Naïve Bayes algorithm accuracy value is about 85.26% and the last the Support Vector Machine algorithm is about 85.26%. From the three of algorithms above then continue to do an optimization by using Particle Swarm Optimization. The data is shown that Naïve Bayes algorithm with Particle Swarm Optimization has the highest value based on accuracy value of 86.30%, AUC of 0.895 and precision of 87.01%, while the highest recall value is Support Vector Machine algorithm with Particle Swarm Optimization of 96.00%. Based on the results of the research has been done, the algorithm is expected can be applied as an alternative for problem solving, especially in predicting of the heart disease.
Entropy in Image Analysis III

Image analysis basically refers to any extraction of information from images, which can be as simple as QR codes required in logistics and digital certifications or related to large and complex datasets, such as the collections of images used for biometric identification or the sets of satellite surveys employed in the monitoring of Earth's climate changes [...].
Joined Type Length Encoding for Nested Named Entity Recognition

In this article, we propose a new encoding scheme for named entity recognition (NER) called Joined Type-Length encoding (JoinedTL). Unlike most existing named entity encoding schemes, which focus on flat entities, JoinedTL can label nested named entities in a single sequence. JoinedTL uses a packed encoding to represent both type and span of a named entity, which not only results in less tagged tokens compared to existing encoding schemes, but also enables it to support nested NER. We evaluate the effectiveness of JoinedTL for nested NER on three nested NER datasets: GENIA in English, GermEval in German, and PerNest, our newly created nested NER dataset in Persian. We apply CharLSTM+WordLSTM+CRF, a three-layer sequence tagging model on three datasets encoded using JoinedTL and two existing nested NE encoding schemes, i.e., JoinedBIO and JoinedBILOU. Our experiment results show that CharLSTM+WordLSTM+CRF trained with JoinedTL encoded datasets can achieve competitive F1 scores as the ones trained with datasets encoded by two other encodings, but with 27%–48% less tagged tokens. To leverage the power of three different encodings, i.e., JoinedTL, JoinedBIO, and JoinedBILOU, we propose an encoding-based ensemble method for nested NER. Evaluation results show that the ensemble method achieves higher F1 scores on all datasets than the three models each trained using one of the three encodings. By using nested NE encodings including JoinedTL with CharLSTM+WordLSTM+CRF, we establish new state-of-the-art performance with an F1 score of 83.7 on PerNest, 74.9 on GENIA, and 70.5 on GermEval, surpassing two recent neural models specially designed for nested NER.
Converting laws to programs

In highly regulated industries, it is critical that laws are translated precisely into code that reflects their intent.
Convolutional Neural Networks for Chagas’ Parasite Detection in Histopathological Images

Chagas disease is a widely spreaded illness caused by the parasite Trypanosoma cruzi (T. cruzi). Most cases go unnoticed until the accumulated myocardial damage affect the patient. The endomyocardium biopsy is a tool to evaluate sustained myocardial damage, but analyzing histopathological images takes a lot of time and its prone to human error, given its subjective nature. The following work presents a deep learning method to detect T. cruzi amastigotes on histopathological images taken from a endomyocardium biopsy during an experimental murine model. A U-Net convolutional neural network architecture was implemented and trained from the ground up. An accuracy of 99.19% and Jaccard index of 49.43% were achieved. The obtained results suggest that the proposed approach can be useful for amastigotes detection in histopathological images.Clinical relevance- The proposed method can be incorporated as automatic detection tool of amastigotes nests, it can be useful for the Chagas disease analysis and diagnosis.
Design and Implementation of an Intelligent Online English Learning System Based on Mobile Internet Technology

A predicament facing education is that the traditional teaching mode could no longer meet the requirements of modern society. The fast development of mobile Internet technology has brought online education platforms into existence, and these newborn things are very helpful to solve the mentioned contradiction. To deepen the research of the application of mobile Internet technology in modern education, this paper designed the functional modules of an intelligent online English teaching (IOET) system and implemented the proposed system. In our study, satisfying students’ learning requirements had been taken as the core principle when building the proposed system, and the database design had followed the principles of standardization, consistency, security, integrity, scalability, and ease of maintenance. The IOET system adopts a three-layer architecture, from top down, the system has a representation layer, a business logic layer, and a data service layer. The main management modules of the system include course notification module, visitor management module, and homework management module, etc. Through this paper, we hope to provide a piece of evidence for the basic research on the upgrade and improvement of intelligent online English teaching platforms.
Generating and evaluating explanations of attended and <scp>error‐inducing</scp> input regions for <scp>VQA</scp> models

Abstract Attention maps, a popular heatmap‐based explanation method for Visual Question Answering, are supposed to help users understand the model by highlighting portions of the image/question used by the model to infer answers. However, we see that users are often misled by current attention map visualizations that point to relevant regions despite the model producing an incorrect answer. Hence, we propose Error Maps that clarify the error by highlighting image regions where the model is prone to err. Error maps can indicate when a correctly attended region may be processed incorrectly leading to an incorrect answer, and hence, improve users' understanding of those cases. To evaluate our new explanations, we further introduce a metric that simulates users' interpretation of explanations to evaluate their potential helpfulness to understand model correctness. We finally conduct user studies to see that our new explanations help users understand model correctness better than baselines by an expected 30% and that our proxy helpfulness metrics correlate strongly () with how well users can predict model correctness.
E-learning moodle

The development of the Intensive Reading learning process with e-learning Moodle is a focus of attention in this study. The main purpose is to find out the effectiveness, practicality, and feasibility of e-learning Moodle that has been designed in the process of learning. The instructional model of ADDIE was the basis for this development research which involves Analysis, Design, Development, Implementation, and Evaluation. Twenty-eight students who joined the intensive reading class and eight validators who were experts in their fields became trial participants in this study. The feasibility of e-learning Moodle was validated by an evaluation sheet that was completed by six validators, who were experts in their field such as learning- media, material, and process. Furthermore, the acquisition of data from students' questionnaires becomes the main data in determining of effectiveness and practicality of the e-learning Moodle. The study indicated that learning model produced can be acceptable and eligible categories, including layout, navigation, function, and pedagogical areas. Based on the students’ answers related to the use of e-learning Moodle of Intensive reading class, it depicts to be effective and practice in all aspects of the evaluation.
Anti-Phishing Awareness Delivery Methods

Phishing attacks are increasingly exploited by cybercriminals, they become more sophisticated and evade detection even by advanced technical countermeasures. With cybercriminals resorting to more sophisticated phishing techniques, strategies, and different channels such as social networks, phishing is becoming a hard problem to solve. Therefore, the main objective for any anti-phishing solution is to minimize phishing success and its consequences through complementary means to advanced technical countermeasures. Specifically, phishing threats cannot be controlled by technical controls alone, thus it is imperative to complement cybersecurity programs with cybersecurity awareness programs to successfully fight against phishing attacks. This paper provides a review of the delivery methods of cybersecurity training programs used to enhance personnel security awareness and behavior in terms of phishing threats. Although there are a wide variety of educational intervention methods against phishing, the differences between the cybersecurity awareness delivery methods are not always clear. To this end, we present a review of the most common methods of workforce cybersecurity training methods in order for them to be able to protect themselves from phishing threats.
Knowledge Modelling for Establishment of Common Ground in Dialogue Systems

The establishment and maintenance of common ground, i.e. mutual knowledge, beliefs and assumptions, is important for dialogue systems in order to be seen as valid interlocutors in both task-oriented and open-domain dialogue.It is therefore important to provide these systems with knowledge models, so that their conversations could be grounded in the knowledge about the relevant domain.Additionally, in order to facilitate understanding, dialogue systems should be able to track the knowledge about the beliefs of the user and the level of their knowledgeability, e.g., the assumptions that they hold or the extent to which a piece of knowledge has been accepted by the user and can now be considered shared.This article provides a basic overview of current research on knowledge modelling for the establishment of common ground in dialogue systems.The presented body of research is structured along three types of knowledge that can be integrated into the system: (1) factual knowledge about the world, (2) personalised knowledge about the user, (3) knowledge about user's knowledge and beliefs.Additionally, this article discusses the presented body of research with regards to its relevance for the current state-of-the-art dialogue systems and several ideal application scenarios that future research on knowledge modelling for common ground establishment could aim for.
Content-based Image Retrieval for Map Georeferencing

Abstract. In recent years, libraries have made great progress in digitising troves of historical maps with high-resolution scanners. Providing user-friendly information access for cultural heritage through spatial search and webGIS requires georeferencing of the hundreds of thousands of digitised maps.Georeferencing is usually done manually by finding “ground control points”, locations in the digital map image, whose identity is unambiguous and can easily be found in modern-day reference geodata/mapping data. To decide whether two symbols from different maps describe the same object, their semantic and spatial relations need to be matched. Automating this process is the only feasible way to georeference the immense quantities of maps in conceivable time. However, automated solutions for spatial matching quickly fail when faced with incomplete data – which is the greatest challenge when comparing maps of different ages or scales.These problems can be overcome by computing map similarity in the image domain. Treating maps as a special case of image processing allows efficient and robust matching and thus identification of geographical regions without the need to explicitly model semantics. We propose a method to encode worldwide reference VGI mapping data as image features, allowing the construction of an efficient lookup index. With this index, content-based image retrieval can be used for both geolocating a given map for georeferencing with high accuracy. We demonstrate our approach on hundreds of map sheets of different historical topographical survey map series, successfully georeferencing most of them within mere seconds.
IMPACT OF SIMPLE VIRTUAL TECHNOLOGY APPLICATION IN ARCHITECTURAL EDUCATION

The development of technology cannot be separated from the development of science, including the learning method. There is an elective course named Virtual Reality Architecture in Architecture Department of Petra Chrisitan University. This course focuses on the process of learning architecture at the stage of presenting and communicating ideas. The virtual technology used as a learning method includes three types of technology, animation, augmented reality and virtual reality. The three technologies are elaborated as a simulation method. The simplicity of its application can be seen in the support for hardware, software, and special devices used by students in their daily lives. This study aims to test the achievement of goals at the final level of learning. Students who have attended this lecture are then interviewed and observed, in relation to proving whether this simple virtual technology can be a supporter in the learning process in the architecture study program.