Reviewerly/exHarmony huggingface dataset:
Improvement of students’ independent work in learning french during quarantine

The purpose of the article is based on the revealing the effectiveness of the in-dependent work for students in learning a foreign language during quarantine. The article focuses on the analysis of independent work of students, on the domestic experience of finding methods and forms of independent work for students in order to effectively master a foreign language, and also determines the place and role of independent work of students in higher educational institutions. In order to improve the independent work of students in the discipline “Practice of oral and written speech of French” while learning “Contemporary French cinema” there is work with an authentic French feature film “Bienvenue chez les Ch’tis”. A list of colloquial expressions in the language of Shti is also attached after watching the film in order to compare with modern French the semanticization of which is a non-translatable. Also some tasks are offered, such as: tasks for working with modern colloquial vocabulary, tasks for checking the comprehension of the watched film, for compiling a synopsis and discussion on the problems of the film and improving the monologue on the topic, as well as for controlling the acquired communicative competences. The proposed methodological development in the learning of French can be used both in the classroom and remotely by technical means during quarantine. By independent work we understand the students’ learning activities to perform the tasks of the teacher, or at his own request, which is aimed at consolidating, expanding and deepening previously acquired knowledge, as well as the assimilation of new material. Thus, during independent work students have a variety of methods and ways to learn a foreign language in distance learning during quarantine: performing exercises on semanticization and commenting on conversational cliches, conversation and answers to questions to test comprehension drawing up a synopsis according to the proposed plan. All this facilitates the work of students to watch modern authentic French film, organize them to overcome language and speech difficulties, promote the acquisition of colloquial vocabulary, the formation of communicative competence in practical classes in French on “Modern French cinema”. Such work requires a lot of effort and its effectiveness depends on the student’s desire to learn and expand their own “horizons” of competencies. The analysis of the article results provides further coverage of the problem and its latitude, as a university student must not only gain knowledge of the subject of the program, master the skills and abilities to use this knowledge, research methods, but also be able to acquire new scientific knowledge. Key words: independent work, authentic film, French, Ch’ti language, colloquial vocabulary, communicative competence.
Enhancing the Intelligibility of Cleft Lip and Palate Speech using Cycle-consistent Adversarial Networks

Cleft lip and palate (CLP) refer to a congenital craniofacial condition that causes various speech-related disorders. As a result of structural and functional deformities, the affected subjects' speech intelligibility is significantly degraded, limiting the accessibility and usability of speech-controlled devices. Towards addressing this problem, it is desirable to improve the CLP speech intelligibility. Moreover, it would be useful during speech therapy. In this study, the cycle-consistent adversarial network (CycleGAN) method is exploited for improving CLP speech intelligibility. The model is trained on native Kannada-speaking childrens' speech data. The effectiveness of the proposed approach is also measured using automatic speech recognition performance. Further, subjective evaluation is performed, and those results also confirm the intelligibility improvement in the enhanced speech over the original.
Extracting Satisfiability-Preserving Modules From the OWL RL Ontology for Efficient Reasoning

Reasoning on large ontologies has been identified as an important challenge. Concept satisfiability is one of the core reasoning tasks in ontology engineering. To improve the efficiency of concept satisfiability checking for OWL RL ontologies, we propose an approach for extracting modules from the OWL RL ontology. Our approach is based on the idea that for a given concept being checked, not all of the ontology elements are related to the checking process. By transforming the OWL RL axioms into first-order constraints and analyzing the dependencies among the constraints, we give a strategy for deleting the irrelevant elements; thus, a simplified ontology that preserves the original checking result can be obtained. The experimental results obtained for a set of real-world ontologies show that our method can effectively reduce the reasoning time, and the efficiency is increased by 1.15 times to 9.08 times.
Application Development of Inspection of Fire Protection Equipment, First Aid Kit and Incident Reporting Case Study

Background: Occupational Safety and Health (OSH) is an important part of the work environment. Both workers and employers are responsible for maintaining a safe environment in the workplace. However, by comparing and mapping the general situation of occupational safety and health legislation in some countries, we found that the current occupational safety and health standards in the retail industry are seriously insufficient or even absent. This study aimed to examine design an application development of inspection of fire protection equipment, first aid kit and incident reporting case study in the Faculty of Engineering, Diponegoro University. Subjects and Method: Use the Scrum method to develop Android-based occupational safety and health inspection applications. The user of this application is the P2K3 team from each department at the Faculty of Engineering, Diponegoro University. The study phases used in this research are as follows: meeting with customers, creating user stories and product backlogs, application development. Results: The result of this research is a mobile application to record the condition of the fire extinguisher and first aid kit. Conclusion: The application made has been able to handle the records of K3 inspection tools, namely fire extinguishers and first aid kits and can be used to report incidents. Keywords: Information Systems, APAR, First Aid Correspondence: Ike Pertiwi Windasari. Universitas Diponegoro, Semarang, Central Java. Email: ike@ce.undip.ac.id. Mobile: 0856400826 52 DOI: https://doi.org/10.26911/the7thicph.02.25
Taking a Closed-Book Examination: Decoupling KB-Based Inference by Virtual Hypothesis for Answering Real-World Questions

Complex question answering in real world is a comprehensive and challenging task due to its demand for deeper question understanding and deeper inference. Information retrieval is a common solution and easy to implement, but it cannot answer questions which need long-distance dependencies across multiple documents. Knowledge base (KB) organizes information as a graph, and KB-based inference can employ logic formulas or knowledge embeddings to capture such long-distance semantic associations. However, KB-based inference has not been applied to real-world question answering well, because there are gaps among natural language, complex semantic structure, and appropriate hypothesis for inference. We propose decoupling KB-based inference by transforming a question into a high-level triplet in the KB, which makes it possible to apply KB-based inference methods to answer complex questions. In addition, we create a specialized question answering dataset only for inference, and our method is proved to be effective by conducting experiments on both AI2 Science Questions dataset and ours.
Structural Information Preserving for Graph-to-Text Generation

The task of graph-to-text generation aims at producing sentences that preserve the meaning of input graphs. As a crucial defect, the current state-of-the-art models may mess up or even drop the core structural information of input graphs when generating outputs. We propose to tackle this problem by leveraging richer training signals that can guide our model for preserving input information. In particular, we introduce two types of autoencoding losses, each individually focusing on different aspects (a.k.a. views) of input graphs. The losses are then back-propagated to better calibrate our model via multi-task training. Experiments on two benchmarks for graph-to-text generation show the effectiveness of our approach over a state-of-the-art baseline. Our code is available at \url{http://github.com/Soistesimmer/AMR-multiview}.
Team Work Quality

Team Work Quality uses statistical analysis in order to infer how team work quality contributes towards the enhancement of creativity with respect to software organizations.
Language manipulation in ad text

The article analyses the phenomenon of linguistic manipulation, its main areas that are used in advertisement.The given phenomenon is considered from the view point of its presence in all spheres of spiritual and public life of the society.
Automatic Detection of English Pronunciation Errors based on Statistical Pattern Recognition

In the automatic detection of English pronunciation errors, it is easy to be affected by multiple stress problems, resulting in large errors. Therefore, an automatic detection method of English pronunciation errors based on statistical pattern recognition is proposed. In order to solve the problem of noise in the original speech information, the speech signal is preprocessed by adding windows and framing. Statistical pattern recognition technology is used to recognize the acoustic features of speech signals, and the acoustic model is established. At the same time, the phoneme mispronunciation network is constructed based on the wrong pronunciation features. The acoustic model is used to detect English pronunciation errors automatically under the network of phoneme errors. The experimental results show that the Sentence Rhythm detected by the proposed method is basically consistent with the actual pronunciation, and the actual detection level of the method is improved.
Pixel-Based Optimization of Touch Sensing Electrodes for Integration with 5G Antennas

Conventional capacitive touch sensor panels (TSPs) have densely packed sensing electrodes that substantially reflect electromagnetic (EM) waves impinging on them especially in S and C-bands. There is a strong interaction between the antenna element placed underneath and the electrodes, distorting the antenna's radiation pattern. Thus, we propose a systematic strategy that optimizes the shapes of the sensing electrodes to configure transmission pass-bands at will for a normally incident plane wave. Finally, the optimized TSP is integrated with a dipole antenna operating at 4 GHz (5G n77-band) to validate our proposed design methodology.
Learnability and Complexity of Quantum Samples

Given a quantum circuit, a quantum computer can sample the output distribution exponentially faster in the number of bits than classical computers. A similar exponential separation has yet to be established in generative models through quantum sample learning: given samples from an n-qubit computation, can we learn the underlying quantum distribution using models with training parameters that scale polynomial in n under a fixed training time? We study four kinds of generative models: Deep Boltzmann machine (DBM), Generative Adversarial Networks (GANs), Long Short-Term Memory (LSTM) and Autoregressive GAN, on learning quantum data set generated by deep random circuits. We demonstrate the leading performance of LSTM in learning quantum samples, and thus the autoregressive structure present in the underlying quantum distribution from random quantum circuits. Both numerical experiments and a theoretical proof in the case of the DBM show exponentially growing complexity of learning-agent parameters required for achieving a fixed accuracy as n increases. Finally, we establish a connection between learnability and the complexity of generative models by benchmarking learnability against different sets of samples drawn from probability distributions of variable degrees of complexities in their quantum and classical representations.
Detection of Natural Calamities from Assamese Posts in Social Media

Abstract Social media users and online news portals are rising exponentially in the Northeastern state of India, where every small instance of daily life are posted on social media platforms such as Facebook, Twitter by the users in their native language. Every social media user post about their daily experiences on such kind of social media platform which gives explicit information happening in a particular place. From those posts, extracting of information has been tried regarding natural calamities, a detection system which detects real world happening of natural calamities in a particular place. The objective of this paper is to detect such events from Assamese text posted on social media. Suppose an earthquake has happened, the online news portals, social media users started reporting about the happening in various platforms, just by observing the post an earthquake can be detected easily. A powerful statistical model Conditional Random Field (CRF) is used to detect those natural calamities as events from the posts which are being posted using the Assamese language. This model has the objective to capture the real-world happenings while a goal have been achieved by introducing an event extraction rule. The CRF model is trained with a large dataset NCED20 which is develop manually. The model is trained on a set of features and selecting those features is a significant step in the learning process. In this paper, an algorithm to capture events from the social media post has been proposed.
Research on subliminal visual messages based on EEG signal and convolutional neural network

The visual information that can't be detected by consciousness but can affect individual's behavior and attitude under specific conditions is called subliminal visual messages. In order to better apply subliminal visual messages to commercial advertising, education and other fields, this paper studied the process of subliminal visual messages in the brain. First, this paper designed a experiment to allow the subjects to see a series of pictures stimulation of different durations and collect the EEG signals, then analyzed the impact of stimulation time on classification accuracy. The experimental results showed that when the stimulus time is short, the classification accuracy increases with the increase of time, resulting in subliminal visual effects. However, with the increase of stimulus time, the classification accuracy began to decline. We speculated that the visual information changed from subthreshold to suprathreshold. The subliminal visual effects were disturbed until disappeared.
Property Crimes in the Blockchain Sphere: New Criminal Schemes and Their Criminal Law Assessment

The sphere of blockchain and circulation of cryptocurrency should be recognized as one of the most dynamically developing branches of economy, and this claim is further supported by its unique features, such as the de-centralized character of the net, the anonymity of users and their actions, the inability to recall or reverse the transaction, and a high volatility of virtual currencies. These characteristics made the blockchain technology attractive not only for law-abiding individuals, but also for criminals. For a long time most legal scholars in Russia and abroad viewed the sphere of blockchain as the sphere of criminal actions connected with illegal trade in goods, services or materials, whose circulation is limited or forbidden (narcotic substances, arms, pornography, etc.), and with laundering of illegal gains or financing terrorism. Current global trends in combating cybercrime leave no doubt that the ideas of the invulnerability of the blockchain net to unsanctioned access through the modifications of codes, the use of malware, the invulnerability to thefts or other property crimes against users or the third party are rather utopian. The legislative practice of recent years shows that these trends have not yet been recognized in our country. The research presented in this article consisted in the analysis of property crimes in the sphere of blockchain that are most common in the global virtual space, including in its Russian segment. The author describes the options for the qualification of such criminal actions provided by the current legislation and used in Russian court practice. The author also identifies the cases when the texts of some Articles of the Criminal Code of the Russian Federation do not match the level of public danger and the essence of criminal infringements against property committed with the use of information technologies, including the sphere of blockchain. A number of suggestions on improving the texts of Art. 158, 159.6, 165, 272 and 273 of the CC of the RF are presented.
Quantum programming. Pt.1: Development tools analysis

This article is the first part in a series of articles about quantum programming. The article discusses the tools of developing quantum programs Quantum Developer Kit with the quantum programming language Q # and the Qiskit framework. Superposition, entanglement, and teleportation are implemented using both development tools. The purpose of the work is to select the most suitable tool for the further implementation of solutions to various problems using quantum computing.
Planning a Structure for aMusical Piece: A Composer’s Creative Process

In creating a musical composition, a music composer often depends on anomalous skills and abilities such as recalling the timbre of a specific musical instrument, reading into an entirely unique language different from any spoken language in the world, and imagining inanimate objects as sound-emitting entities.Because of the possible interactions among these challenging and complex skills and ideas, it is thus important for the composer to have a plan in structuring the composition or a pre-compositional overview before going into the actual creative process of producing a coherent, meaningful piece.The structure or organization assists the composer in examining the interaction of the micro elements within the macro of the composition.It determines the final form of the composition as perceived by the composer.The objective of the paper is to demonstrate the process of planning or structuring a particular piece of composition based on the actual experience of the composer.In this article, the structuring of Taming Sari, a composition for Trumpet, Oboe and String Quintet, is traced through an analysis of the composition process.The emphasis is on the complementary roles of both the technical and non-technical elements in producing and projecting a lived experience of the composition.It is hoped that via sharing of an emic view of the planning process of a composition, it would assist learners in better understanding the process from the perspective of the composer.
Correction to: Scene Understanding in Night-Time Using SSAN Dataset

The original version of this chapter was revised. The names of the authors “Sam Joshuva Paul Jeevan Shapher, Suryakiran Sureshkumar and Nighil Krishna Rajaguru" were corrected.
BENEFITS OF MANAGEMENT GAMES IN DISPLAYS PERFORMANCE STUDENT AT ILEARNING EDUCATION

The development of learning in education has now increased. As time goes on, technology has grown rapidly. With the development of technology today can help the learning process. One example of technological advancement in education is E-Learning. E-Learning provides the convenience of lecturers and students in distance learning so that learning runs effectively and efficiently. In an effort to improve the quality of education in Indonesia, Raharja University has implemented an online learning system called iLearning. But iLearning's online learning system has not been the maximum, there are some students who have not been active in the classroom as the lecture took place and there are still students who are late working on the assignment given. To improve the performance of students while in the classroom and to perform timely assignments lecturers apply a method of gamification. Students will earn points when working on an assignment that has been given by the lecturer. The earning points are listed on the iDu Dashboard in order to provide motivation for students to do other tasks and compete with classmates. The methods used to address these problems include SWOT analysis methods, Literature Review, and Unified Modelling Language (UML) as a modeling design. This research aims to improve student performance in the process of teaching and learning activities.
Text Writing Using Air Gestures for People With Limited Hand Motor Skills

Abstract Mobile devices and laptops are the main ICT tools to exchange information among people in the world. All the applications are designed by following a specific interaction style based either touchscreen or mouse and keyboard, which can be performed only with detailed movements of hands and fingers. Traditional interaction becomes difficult for elderly who have diseases limiting the hand motor skills, such as arthritis and brain stroke. The use of simple air gestures can be adopted as alternative interaction style to interact with smartphones, tablets and laptops. The aim of this research work is the development of an application that allows text writing using air gestures for people with limited hand motor skills. The application embeds several computer vision algorithms and convolutional neural networks software modules to detect and drawn alphanumeric characters and recognizing them using both mobile devices and laptops. The preliminary results obtained show that the approach is robust, and it can easily detect the alphanumeric characters written with the movement of the wrist.
Generalized cell structures

Cell structures were introduced by W. Debski and E. Tymchatyn as a way to study some classes of topological spaces and their continuous functions through discrete approximations. In this work we weaken the notion of cell structure and prove that, the resulting class of topological space admitting such a generalized cell structure includes non-regular spaces.
Factor model of creative leadership potential in the context of the socio-psychological portrait of junior students majoring in humanities

This article explores the creative leadership potential among the junior students majoring in humanities. The relevance of studying creative leadership in the era of transfessionalism is substantiated. Description is given to the current state of studying the concept of creative leadership in global science. The author also delineates the survey results on the creative leadership potential of junior students majoring in humanities, which involved 101 students from different universities of Tomsk. The research employed the method of modeling communicative worlds, method of psycho-semantic graph, method of &amp;ldquo;Myers-Briggs Creative Personality Type&amp;rdquo;, scalogram-based communicability profile, social network analysis (SNA methodology). The scientific novelty is defined by the fact that modern science features a fairly small number of empirical research dedicated to creative leadership. The acquired data was analyzed using the factor analysis. The main result of this research consists in identification of 10 factors that considerably contribute to the creative leadership potential and form its factor structure. At the forefront of the structure of creative leadership potential among the students majoring in humanities is the positive perception of their partners. It is also concluded that the structure of creative leadership potential is quite complex and contradictory. The obtained results would be used in development of psychological support programs for the students to fulfill their creative leadership potential.