Reviewerly/exHarmony huggingface dataset:
READING TEACHING STRATEGIES IN THE SENIOR HIGH SCHOOL

The scholar's capability to understand English the fact veritably low in Indonesia. Not only among newcomers similar as the basic or less high academy degree but the capability to understand introductory reading at the high academy position is inversely worrisome. This has led to a lack of further good mortal resources in recent times. For a long time, we've known that English is a foreign language and unexpectedly indeed introductory reading can not be learned at this position. Not to mention that the after generation of Z has made this language a language that's used every day on every occasion. Not only studying and looking for work, this language and the language used in chatting and it's heartbreaking if the scholars' understanding capability is still veritably low. Several factors greatly impact this disability. The first is the lack of words that they've in interpreting the textbook, the second is the lack of training of the textbook to be read either at home or the academy library and the third is the lack of attention of the subject preceptors in the proper wisdom of each scholar who practices at the academy. There is no revealing provocation to make scholars uncommunicative and assume that reading is boring conditioning. Let alone reading foreign readings, reading textbooks in Indonesian itself, indeed lazy to read because of a lack of mindfulness of the significance of reading conditioning. Reading this is to help scholars get the right understanding of important knowledge, and increase their love of reading, and most importantly how do preceptors realize the most applicable strategies in tutoring and literacy handed the schoolteacher knows the background of each scholar.
Peculiarities of the use of interactive technologies in training future specialists of the agro-industrial complex

The development of all spheres of social life leads to increasing requirements for professionalism and competence of specialists in various industries. In order to meet the requirements of employers and the constantly changing labour market conditions, it is necessary to improve the quality of specialists training by improving the education system in educational institutions. Requirements for specialist training in the Russian Federation are regulated by a number of legislative acts, such as the Federal law "On Education in the Russian Federation", "Strategy of Innovative Development of the Russian Federation until 2020", the Federal State Educational Standard for Higher Professional Education (3rd generations FSES), sample curriculum for the discipline "Foreign Language" for non-linguistic universities and faculties (approved by the Ministry of Education and Science of the Russian Federation, 2011). Based on the above-mentioned regulatory framework, educational institutions develop local regulatory and methodological base, including work programmes, a set of assessment tools and other materials. In particular, such a base was developed at the Don State Technical University for future specialists in the agro-industrial complex. The discipline "Foreign Language" was introduced into the educational program to form students' foreign language communicative competence - the readiness and ability to carry out oral and written communication in social, academic and professional spheres, including using knowledge of the basics of professional terminology in a foreign language.
Business game on the mediation procedure as a way to form conflict - sustainable behavior

The article considers a variant of the business game as one of the effective ways of teaching students to prepare them for a real situation in the event of a labor conflict. Artificial imitation of the proposed model as the main semantic orientation involves the regulation of conflict through mediation. Based on the analysis of an array of domestic and foreign sources, the key points of the mediation approach for including them in the content of the game were identified, and it was also concluded that mediation is not properly widespread in Russia, which is confirmed by the results of a mass survey among domestic youth aged 22-30 years. The sample consisted of 497 respondents, of which 70% may find themselves in a conflict situation in their work at any time. The results of the survey confirmed the hypothesis of the respondents' ignorance of the mediation option of conflict regulation, which determines the relevance and timeliness of the introduction into the educational process of knowledge, skills and abilities on the use of mediation procedures in conflict regulation. It is concluded that the acquired abstract knowledge in the course of the business game tends to turn into real-applicable.
Process virtualization for X-ray images obtaining in industrial radiography during nuclear power plant NDT specialists training

The research aims to highlight the analysis of the virtualization prerequisites in terms of the non-destructive testing training. The peculiarities of radiation control (RC), which significantly affect the organization of practical classes and the profitability of personnel training, are given. The main requirements for specialists in the course of practical training are listed. Methods of processing and visualizing information about the structure of dense three-dimensional bodies are considered and a simplified task-specified alternative is proposed. The results of the research underline the principle of image construction and processing through the use of digital twins of testing samples. This allows the user to get an image that is similar to shooting results of real metal samples in terms of training purposes. In order to deliver a more effective methodology, the main physical principles are taken into account for digital models of radiographs and optical density of films.
Application of artificial intelligence systems for stylometric analysis of texts as factor of sustainable development

Investment in human capital, along with natural resource management, is an important indicator of sustainable development. One of the areas of such investments is the creation of artificial intelligence systems that allow for the classification of texts. This paper analyzes the use of artificial intelligence systems for stylometric text analysis. On the basis of the algorithm of the convolutional artificial immune system, a system for stylometric analysis of texts was developed and implemented in software. In order to determine the possibility of using this system to determine the authorship of literary works, it was trained and tested. For this, the works of two authors were chosen: Leo Tolstoy and Fyodor Kryukov. This system demonstrated a high quality of text classification and a good speed of work and learning. So, to test the performance of the system, 11 works by Leo Tolstoy and 12 works by Fedor Kryukov were taken that were not used to train the system. All works of these authors were classified correctly. It should be noted that the artificial immune system algorithm can also be successfully used in other tasks requiring text classification.
Updating the professional profile of the modern teacher: the results of a regional study

The article presents the results of expert assessment of the importance of professional competencies for successful educational activity by the teachers of the regional system of secondary education. A theoretical review of the scientific literature on changes in general education and their impact on the professional activities of teachers, as well as the content of the current Russian professional teacher standard provided a methodological basis for the research tools of the current professional profile of the modern teacher. The expert survey and statistical data analysis procedures performed using SPSS software (version 23) allowed us to identify the latent factors that determine new important details of the professional profile of a secondary education teacher. The results of the study are the basis for the development of additional educational resources, professional development courses, internships in the system of supplementary secondary teacher education. Considering the requests of the professional teaching community, which faces staff shortages, it is possible to improve the quality and efficiency of educational organizations of the regional system of secondary education.
Museum Pedagogy in Ukraine: Challenges and Achievements

The article describes the experience of Ukrainian teachers in organizing pedagogical work with preschool children by means of museum pedagogy. Museum pedagogy in Ukraine plays an important role in the process of socializing children by involving them in the historical and cultural heritage of society. It is an effective factor in the cognitive, aesthetic, mental, and creative development of preschoolers. The article reveals the role of museum pedagogy in the educational process of a preschool education establishment. The authors emphasize that in Ukraine today a significant role is given to the creation of appropriate development environments, and the search for new forms and methods of working with children. The article defines the basic principles and tasks of museum pedagogy as an innovative technology and describes the peculiarities of the work of museum staff and the criteria of their pedagogical skills.
Hate-Speech Bans Are Consonant with Liberal Principles - Chapter

Modern liberal-democratic nations are divided over whether the right to freedom of expression should extend to hate speech – expression that abuses, degrades, or promotes violence or discrimination against others based on traits like race, nationality, religion, sex, sexual orientation, and gender identity. Most liberal democracies outlaw certain forms of public hate speech in order to protect the dignity, equality, and security of the targeted groups. By contrast, the United States rejects this position and holds that public hate speech generally should receive constitutional protection, although the law may impose some restrictions on private hate speech, such as epithets hurled in face-to-face confrontations. In this essay, which is a contribution to the forthcoming Oxford Handbook of Hate Speech, I argue that bans on public as well as private hate speech can be consonant with liberal principles. Of course, there are many varieties of liberalism. This essay focuses on the writings of John Locke, which did much to lay the theoretical foundations of the modern liberal state. Moreover, Locke directly addressed the problem of speech that denies the equal status and rights of others. For these reasons, his thought offers one valuable starting point for considering how liberal principles should apply to hate speech.The essay begins by sketching the main outlines of Locke’s political philosophy. I then draw on this discussion, together with our contemporary understanding of rights, to present a general theory of free expression which I call liberal humanism. On this view, free speech is based on respect for human freedom and dignity. But these same values also support other essential rights, ranging from bodily security to personal dignity to equality of citizenship. In general, the right to free speech does not entitle one to infringe the rights of others. I then use this approach to grapple with the problem of hate speech. In cases where that speech targets particular individuals, it may be restricted on the same grounds as other kinds of wrongful speech, such as threats, incitement, and fighting words. Although hate speech that occurs within public discourse poses a more difficult problem, I contend that this speech may be restricted on the ground that it violates the most basic right of all: the right to be recognized and treated as a human being and a member of the community. This position dovetails with the position that Locke took with regard to expression that sought to deny freedom and equality to religious minorities. Expression of this sort, he contended, should not receive legal protection because it invaded the rights of its targets and “undermine[d] the foundations of society,” which was held together by language, reason, and mutual recognition. The essay concludes by responding to two of the leading liberal arguments against hate-speech bans: that they violate individual autonomy and that they undermine democratic legitimacy.
Development of an Interactive Mobile Robot for Playful Learning and Language Teaching

This paper presents a mobile robot for development of interactive games and language learning purposes based on the Kinect v2. The game uses interface seeks to take advantage of human computer interaction in a playful way through gesture recognition. This work combines robotics and games, games and language learning, and some recent developments about robotics and language learning. The hardware used to build the mobile robot is described as well as the ludic game for language teaching by an interface human-robot. Performance of the platform is assessed by means of real-time experiments by students using a non-linear control based on a trajectory tracking during various practices. The experiment proves the platform potential for supporting ludic game and tested successfully and then discuss the results and mention future perspectives.
Efficient and Accurate Object Detection With Simultaneous Classification and Tracking Under Limited Computing Power

Interacting with the environment, such as object detection and tracking, is a crucial ability of mobile robots. Besides high accuracy, efficiency in terms of processing effort and energy consumption are also desirable. To satisfy both requirements, we propose a detection framework based on simultaneous classification and tracking in the point stream. In this framework, a tracker performs data association in sequences of the point cloud, guiding the detector to avoid redundant processing (i.e. classifying already-known objects). For objects whose classification is not sufficiently certain, a fusion model is designed to fuse selected key observations that provide different perspectives across the tracking span. Therefore, performance (accuracy and efficiency of detection) can be enhanced. This method is particularly suitable for detecting and tracking moving objects, a process which would require expensive computations if solved using conventional procedures. Experiments were conducted on the benchmark dataset, and the results showed that the proposed method outperforms original tracking-by-detection approaches in both efficiency and accuracy.
Structure-Aware Subspace Clustering

Subspace clustering has attracted much attention because of its ability to group unlabeled high-dimensional data into multiple subspaces. Existing graph-based subspace clustering methods focus on either the sparsity of data affinity or the low rank of data affinity. Thus, the quality of data affinity plays an essential role in the performance of subspace clustering. However, the real-world data are generally high-dimensional, complex, and heterogeneous multi-source data, so that the data affinity learned by these methods cannot be completely dependent. Moreover, since these approaches always ignore the intrinsic structure of data, their grouping effect is relatively low. In this paper, we propose a novel unsupervised algorithm, called Structure-Aware Subspace Clustering (SASC), to address the above issues. SASC considers local and global correlation structures simultaneously to capture the intrinsic structure. Further, it integrates the captured structure into representation learning to gain a relatively precise data affinity. It is powerful to promote an all-around grouping effect and enhances the robustness and applicability of subspace clustering. Experiments on various benchmark datasets, including bioinformatics, handwritten digit, object image, and speech signal, demonstrate the effectiveness of the proposed algorithm.
Audio Augmented Reality in Smart Learning Environments

Image processing-based augmented reality (AR) is widely used in several fields. However, audio content is also crucial in certain cases, for example, focusing on appreciating artwork in a museum, rather than a virtually synthesized image. In this study, an attempt was made to provide ubiquitous learning (u-learning) services by using audio AR for smart cities where people do not need smartphones, tablets, or wearable devices for learning. The concept of “unmanned stores” was introduced in the proposed learning environments. A 360° camera was mounted on the ceiling of an exhibition room. An algorithm was used to detect moving objects and locate a visitor, from whose position an information-processing platform searched the showpiece nearest to the visitor and selected the corresponding audio guide. For multiple visitors, infrared (IR) sensors were used to count the visitors inside the room. A loudspeaker array was built to emit directional sounds for eliminating interference between multiple sound sources. Along with the proposed algorithm for increasing the accuracy while sensing multiple movements, the conventional sound field synthesis method was modified to improve the listening experience and learning quality. Image-based sensor technology, IR detection, and an audio signal-processing platform were integrated into a smart environment in which people can conduct u-learning without personal devices. The method can provide immersive audio tours with virtual narrators and peer-helpers in schools, museums, and art galleries. Qualitative and quantitative analyses indicated that effective hands-free and eyes-free learning was achieved.
The Security of Digital Content at University Levels

This research is motivated by the increasing use of information and communication technology (ICT) within the teaching-learning process in universities. This study uses the proposed work methodologies and instruments for identification and evaluation; an instrument proposed by the Institute for Prospective Technological Studies (IPTS) of the European Union was applied to evaluate the digital skills. The results made it possible to identify that there are major deficiencies in the digital skills of the participants, to the point of being placed at the initiation level, especially regarding the protection of personal data and digital identity, and protection of the environment.
Improving UE Energy Efficiency Through Network-Aware Video Streaming Over 5G

Adaptive Bitrate (ABR) Streaming over cellular networks has been well studied in the literature; however, existing ABR algorithms primarily focus on improving the end-user Quality of Experience (QoE) while ignoring the resource consumption aspect of the underlying device. Consequently, proactive attempts to download video data to maintain the user’s QoE often impact the battery life of the underlying device unless the download attempts are synchronized with the network’s channel condition. In this work, we develop EnDASH-5G – a wrapper over the popular DASH-based ABR streaming algorithm, which establishes this synchronization by utilizing a network-aware video data download mechanism. EnDASH-5G utilizes a novel throughput prediction mechanism for 5G mmWave networks by upgrading the existing throughput prediction models with a transfer learning-based approach, leveraging publicly available 5G datasets. It then exploits deep reinforcement learning to dynamically decide the playback buffer length and the video bitrate using the predicted throughput. This ensures that the data download attempts get synchronized with the underlying network condition, thus saving the device’s battery power. From a thorough evaluation of EnDASH-5G, we observe that it achieves a near 30.5% decrease in the maximum energy consumption than the state-of-the-art Pensieve ABR algorithm while performing almost at par in term of QoE.
History-Guided Hill Exploration for Evolutionary Computation

Although evolutionary computing (EC) methods are stochastic optimization methods, it is usually difficult to find the global optimum by restarting the methods when the population converges to a local optimum. A major reason is that many optimization problems have basins of attraction (BoAs) that differ widely in shape and size, and the population always prefers to converge toward BoAs that are easy to search. Although heuristic restart based on tabu search is a theoretically feasible idea to solve this problem, existing EC methods with heuristic restart are difficult to avoid repetitive search results while maintaining search efficiency. This article tries to overcome the dilemma by online learning the BoAs and proposes a search mode called history-guided hill exploration (HGHE). In the search mode, evaluated solutions are used to help separate the search space into hill regions which correspond to the BoAs, and a classical EC method is used to locate the optimum in each hill region. An instance algorithm for continuous optimization named HGHE differential evolution (HGHE-DE) is proposed to verify the effectiveness of HGHE. Experimental results prove that HGHE-DE can continuously discover unidentified BoAs and locate optima in identified BoAs.
Prototype of Support System for News Summary Video Production

放送局では,ソーシャルメディアなどを利用して番組の要約映像を配信するサービスの必要性が高まっており,映像を自動で要約する技術が求められている.今回我々は,ニュース番組を対象とした映像の自動要約技術を開発し,放送局での実用を想定したニュース要約映像の作成支援システムを試作した.「放送用要約映像に使われやすいシーンの画像特徴」を学習したニューラルネットワークと音声認識技術を利用した自動要約技術により,「放送映像に適した"画作り"」と「アナウンサーの発話内容」の双方を考慮したニュースの要約映像生成を可能にした.また,試作したシステムには,利用者が入力したニュース番組映像を自動で要約するだけでなく,利用者の多様な「こだわり」に応えるための修正機能も実装した.さらに,映像自動要約技術の性能評価と番組制作現場での利用検証により,試作したシステムの有用性を示した.
Wireless Technology Identification Employing Dynamic Mode Decomposition Modeling

Significant growth in broadband wireless services, as well as ever-increasing demand on the spectrum caused by the Internet of Things (IoT) have overstretched limited available spectrum space for wireless services. Heterogeneous wireless networks (HetNets)—wherein multiple wireless technologies (e.g., Wi-Fi, Bluetooth, Zigbee, LTE, and GSM) coexist and share spectrum—are a promising solution for enhancing spectrum sharing. An essential element in developing coexistence protocols is correctly identifying wireless technologies anticipated to share spectrum and to shift users between available wireless technologies in an effort to optimize spectrum usage and minimize interference. For the coexistence research reported in this paper, we analyzed the performance of our developed novel algorithm based on dynamic mode decomposition (DMD) mathematical modeling to identify and differentiate among various wireless technologies. More specifically, our technique identified GSM and LTE signals in the cellular domain, IEEE802.11n, ac, and ax in the Wi-Fi domain, as well as Bluetooth and Zigbee. The proposed DMD-based technique identifies the time domain signature of a signal by capturing embedded periodic features transmitted within the signal. Performance and accuracy were tested and validated using an experimental dataset collected for various time series, and raw-power measurements of the targeted technologies. Results showed that the developed DMD-based algorithm can differentiate and classify individual and coexisting wireless signals with high accuracy —greater than 90% for most cases. Furthermore, only a short time— less than one second—is required for identifying a signal and enabling implementation in real-time practical networks. The advantage of the developed technique over comparable techniques is lower complexity (i.e., shorter processing and training time, no channel estimation, no time/frequency synchronization, and no need for long observation-time intervals).