Reviewerly/exHarmony huggingface dataset:
Multi-Viewpoints Based Visual Method by Latent Dirichlet Allocation for Efficient Tweets Data Clustering

Data clustering methods are popularly used for partitioning the data into clusters based on data objects similarity features. Cluster tendency is a crucial step for the data clustering techniques assessment of a suitable number of clusters of the data. Existing cluster tendency visualization methods, visual assessment tendency (VAT), spectral VAT (SpecVAT), and other methods use the Euclidean and cosine measures for similarity features computation. For text mining domains, cosine-based visual methods assess the clusters more accurately than others; which are recommended for tweet data models for clusters assessment. Such visual methods determine the clusters concerning a single viewpoint. Multi-viewpoints are required for addressing the more informative clusters assessment of tweet documents. In this paper, we proposed a multi-viewpoints based visual method by using Latent Dirichlet Allocation (MVP-VM-LDA) to find the quality of clusters (or topics) and for visualization of cluster tendency. Real-time tweet datasets were extracted for demonstrating the efficiency of the proposed method in the experimental study.
Blockchain Architecture for Securing the IoT

Advancement in technology is a general global need. The technology Internet of Things (IoT) has an additional requirement in large industrial, commercial, and home applications. For providing security to the data generated by various devices, another novel technology can be deployed: blockchain. IoT systems currently use a centralized access control method to control the functioning of IoT systems and have major cost, security, single point of failure (SPoF) and other issues. Decentralizing the control of IoT management can address the drawbacks of this centralized approach, and one such method is blockchain technology. Various architectures of IoT applications can be designed by defining the peer entities in the blockchain, the structure of the block, a digital ledger in the transaction, cryptographic hash function, smart contracts governing the operations by different entities, consensus algorithms and so on. The transactions in the blockchain would be transparent to all the entities and would be tamper-proof, thereby securing them. Hence, we discuss these various possible architectures, their benefits, and the challenges to be met by the application of blockchain to IoT systems.
WASTE MANAGEMENT (TEMAN): MEDIA PENYULUHAN BERBASIS AUGMENTED REALITY SEBAGAI UPAYA EDUKASI PENGELOLAAN SAMPAH DI PIYUNGAN YOGYAKARTA

Waste problem is one of the biggest challenges that must be faced by the community, especially in Indonesia. Garbage is the main problem that causes symptoms that are natural disasters caused by humans such as floods. Special Region of Yogyakarta (DIY) is one of the major cities in Indonesia with a high population density. The high number of residents can cause an increase in the amount of garbage in DIY, causing garbage to accumulate and cause diarrheal diseases and respiratory disorders. One of the efforts of the government of the Special Region of Yogyakarta in overcoming this problem is by establishing a Piyungan Integrated Waste Management Site (TPST). Waste transported to Piyungan TPST comes from Bantul Regency, Sleman Regency and Yogyakarta City. The garbage transported by Piyungan TPST continues to increase every  year. Therefore, it is necessary to deal with the waste so that the Indonesian  people can reduce their waste, both from households, factories and other places, such as organic, non-organic, and B3 waste. One effort to solve the problem is by educating the public about the importance of protecting the environment by reducing waste and not even producing waste (zero waste) through recycling of waste, for example handicraft bags  from household waste.  Through the creation of interactive and interesting Augmented reality-based Waste Management (TEMAN) extension media can facilitate the process of receiving and learning about waste management for the community. The purpose of this paper is: 1) knowing the concept and design, 2) knowing the SWOT analysis, and 3) knowing how to use Waste Management extension media (TEMAN) and predicting the application of TEMAN extension media. Data collection techniques using literature study. Data obtained through library research varies both from journals, news, and the internet from national media. The use of Waste Management extension media (TEMAN) is expected to increase the effectiveness of the  extension process on waste management and be able to attract the attention of the community around the Piyungan area so that the reception process is more active and enjoyable.
Ceremony for the Belt and Road International Scientific and Technological Organisation Cooperation Platform held on 17 November – UIC Communications

The ceremony for the Belt and Road International Scientific and Technological Organisation Cooperation Platform was held on 17 November and was chaired by Mr Song Jun, Chairman of China Science…
NEW PARADIGMATIC RELATIONS BETWEEN FACE TO FACE AND VIRTUAL EDUCATION – FROM ‘HOMO LUDENS’ TO ‘HOMO VIRTUALIS’ IN THE MODERN ACADEMIC PROCESS OF EDUCATION

Information about the paper titled "NEW PARADIGMATIC RELATIONS BETWEEN FACE TO FACE AND VIRTUAL EDUCATION – FROM ‘HOMO LUDENS’ TO ‘HOMO VIRTUALIS’ IN THE MODERN ACADEMIC PROCESS OF EDUCATION" at IATED Digital Library
A New Text Independent Speaker Recognition System with Short Utterances Using SVM

Recent advances in the field of speaker recognition have proved to highly outperform algorithms. However this performance degrades when limited data are presented. This paper presents examples on how Support Vector Machines (SVM) can improve speaker recognition for short utterance data duration. The main contribution in this approach is the use of new vectors when training and testing data are limited. We show how different kernels function of SVM can be used to validate the new approach with different speakers from different databases.
An Improved Tracking Algorithm for Occlusion Problem Based on STAPLE

Occlusion is one of the common problems in target tracking, which presents challenges for real-time and robust tracking. In order to solve the problem that the target is lost after being obscured, a STAPLE algorithm combined with SVM is presented in this paper. On this basis, occlusion detection, LBP-based deformation detection and multi-peak repositioning algorithm are added to solve the problem of template contaminated caused by target occlusion and insufficient robustness to distortion. When the target is distorted, the target model is continuously updated to maintain its robustness. When the decrease in confidence level is not caused by deformation, the target detection mechanism is activated and the update of the target model is stopped. The experimental results show that the proposed method is much better than previous algorithms.
Morphological Image Processing of ℓ-HX Group of Vehicles -Traffic Light Control using Bipolar L-fuzzy logic

Controlling and regulating traffic congestion at a four way junction, is one of the major problems in allcities because of ever increasing number of vehicles, overpopulation, poor traffic control system, and others. Thistraffic congestion causes people to lose time, money and good opportunities. In this paper we are going to adopt themorphological image processing technique instead of other electronic sensing devices which are already existing.Morphology image processing technique is based on the algebraic framework of complete lattices. In our proposedmethod we are considering the lattice ordered HX group of vehicles supposed to be at a four way traffic junction.Morphological image processing technique is used to classify the vehicles and detect emergency vehicles, as well,counting the number of vehicles on each of the four roads meeting the junction without any delay. It is also used forthe removal of background noise, leading to the delivery of accurate data instantly. The aim is to control trafficsignal lights using morphological image processing based on bipolar L-fuzzy membership values. The maintendency of this paper is display the green signal first in emergency vehicle road without considered any aspects andclear the traffic congestion immediately without any delay.
INTELLECTUAL DATA ANALYSIS IN PREDICTING STUDENT DROPOUT DURING IN-HOUSE VOCATIONAL TRAINING OF TECHNICAL PERSONNEL

D. Dobrenko1, N. Dobrenko2, A. Aksenova3, M. Ulizko2, A. Gogoberidze3, N. Gusarova2 1Technical School of St. Petersburg Metro (RUSSIAN FEDERATION) 2ITMO University (RUSSIAN FEDERATION) 3The Herzen State Pedagogical University of Russia (RUSSIAN FEDERATION)
A Quantum Concurrent Signature Scheme Based on the Quantum Finite Automata Signature Scheme

When using digital signatures, we need to deal with the problem of fairness of information exchange. To solve this problem, Chen, etc. introduced a new conception which is named concurrent signatures in Eurocrypt'04. Using concurrent signatures scheme, two entities in the scheme can generate two ambiguous signatures until one of the entities releases additional information which is called keystone. After the keystone is released, the two ambiguous signatures will be bound to their real signers at the same time. In order to provide a method to solve the fairness problem of quantum digital signatures, we propose a new quantum concurrent signature scheme. The scheme we proposed does not use a trusted third party in a quantum computing environment, and has such advantages as no need to conduct complex quantum operations and easy to implement by a quantum circuit. Quantum concurrent signature improves the theory of quantum cryptography, and it also provides broad prospects for the specific applications of quantum cryptography.
V.V. Rozanov’s Archive in Rumyantsev Museum

The article presents a general overview of the letters to V.V. Rozanov that he sent to . Rumyantsev Museum. The chronology of the receipt of materials from the epistolary archive to the Department of manuscripts of the Museum is traced. The author refers to the names of the persons who directly handed the materials to the archive, and who accepted and processed them. The bibliophilic priorities of the museum curator . G.P. Georgievsky and V.V. Rozanov became the basis for supplementing the epistolary collection “From the Archive of V.V. Rozanov”. The author mentions the error in dating the letter of V.V. Rozanov to G.P. Georgievsky., written to accompany the last part of the epistolary passed to the Museum inter vivos. The text of the letter is published for the first time. The importance of V.V. Rozanov's review of the book in the «Novoye Vremya» journal at the beginning of the twentieth century is emphasized. The author's approach to the systematization of the correspondents’ letters for their subsequent passing over to Rumyantsev Museum is shown. The author provides concise information on the contents of certain collections of letters from Rozanov’s correspondents. The main themes of V.V. Rozanov's epistolary communication with the authors of the letters are outlined. The author takes note of Rozanov’s special attitude to the selection of letters from the archive of correspondence for further publication. in the “Literary Exiles” series.. In the forefront there are letters from Church leaders and the thinker’s allies in the field of legislation on family relations. The article highlights the problem of correctness of specifying archive code numbers of the Russian State library's manuscript department from the museum part of the archive, which have undergone changes during their stay in the General complex of V.V. Rozanov's manuscript archive.
Applications of robust recognition technology in the foreign language speech assessment system

This study proposes an improved speech assessment algorithm and an improved English (as a foreign language in China) speech assessment system based on robust speech recognition to assess learners' English pronunciation more accurately in noisy environments. In this paper, the traditional assessment framework of English speech recognition system is studied by the literature analysis method and survey research method. At the same time, the principle of speech recognition and robust speech recognition are further studied. Furthermore, the speech assessment algorithm and the system based on the feature compensation algorithm of Vector Taylor Series (VTS) are developed. Finally, the developed system is analysed by perceptual assessment of speech quality (PESQ) and mean opinion score (MOS). The results show that the MOS of the improved English (as the foreign language) speech assessment system is higher and the recognition performance is better than that of the traditional system in the noise conditions.
CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning.

Code retrieval is a common practice for programmers to reuse existing code snippets in the open-source repositories. Given a user query (i.e., a natural language description), code retrieval aims at searching the most relevant ones from a set of code snippets. The main challenge of effective code retrieval lies in mitigating the semantic gap between natural language descriptions and code snippets. With the ever-increasing amount of available open-source code, recent studies resort to neural networks to learn the semantic matching relationships between the two sources. The statement-level dependency information, which highlights the dependency relations among the program statements during the execution, reflects the structural importance of one statement in the code, which is favor-able for accurately capturing the code semantics but has never been explored for the code retrieval task. In this paper, we propose CRaDLe, a novel approach forCodeRtrieval based on statement-levelsemanticDependencyLearning. Specifically, CRaDLe distills code representations through fusing both the dependency and semantic information at the statement level and then learns a unified vector representation for each code and description pair for modeling the matching relationship. Comprehensive experiments and analysis on real-world datasets show that the proposed approach can accurately retrieve code snippets for a given query and significantly outperform the state-of-the-art approaches on the task.
Automatic classification of kinematic flap variants using ultrasound and optical flow

Study of the four covert kinematic variants of North American English flaps can provide insight into questions in speech motor control and articulation-acoustics relations [Derrick and Gick, Can. J. Linguist. 56(3), 307–319 (2011)]. These variants are typically labeled by human annotators from ultrasound video, which is time-consuming and labor-intensive. In this study, we present an automatic classification method, taking as basis data optical flow fields over a series of ultrasound frames flanking the flap; fields are calculated using a method tailored to ultrasound video [Moisik et al., JIPA 44(1), 21–58 (2014)]. Two classifiers are compared: support vector machines, which learn an optimal linear separator between labeled class instances; and simple recurrent neural networks [Elman, Cognit. Sci. 14(2), 179–211], which operate recursively over sequences of data, and whose state at any timepoint is calculated based only on the state at the preceding timepoint and the current input field. We train these classifiers on human-labeled flap tokens and test classification performance against a held-out subset of the labeled tokens. We go on to discuss the general applicability of this method for disambiguating covertly different lingual articulatory events.
CuratorNet: Visually-aware Recommendation of Art Images

Although there are several visually-aware recommendation models in domains like fashion or even movies, the art domain lacks thesame level of research attention, despite the recent growth of the online artwork market. To reduce this gap, in this article we introduceCuratorNet, a neural network architecture for visually-aware recommendation of art images. CuratorNet is designed at the core withthe goal of maximizing generalization: the network has a fixed set of parameters that only need to be trained once, and thereafter themodel is able to generalize to new users or items never seen before, without further training. This is achieved by leveraging visualcontent: items are mapped to item vectors through visual embeddings, and users are mapped to user vectors by aggregating the visualcontent of items they have consumed. Besides the model architecture, we also introduce novel triplet sampling strategies to build atraining set for rank learning in the art domain, resulting in more effective learning than naive random sampling. With an evaluationover a real-world dataset of physical paintings, we show that CuratorNet achieves the best performance among several baselines,including the state-of-the-art model VBPR. CuratorNet is motivated and evaluated in the art domain, but its architecture and trainingscheme could be adapted to recommend images in other areas
Research on classification of spiral galaxies and stars based on convolutional neural network

Abstract In astronomy, the shape of galaxies can often reflect the course of its evolution, and can further reveal the development law of the universe. With the progress and development of observation technology, image data has grown explosively, and the efficiency of traditional manual astronomical image classification is far from enough. Image classification based on machine learning effectively solves the problem of low efficiency of artificial classification, but in the face of massive data sets, the classification effect of traditional machine learning is often not as good as deep learning. In this paper, relevant concepts based on neural network image classification algorithm are introduced. Then, according to the characteristics of the mainstream CNN (convolutional neural network) model, the design and optimization of the custom RS CNN model are completed. Finally, the custom RS CNN is used to conduct classification experiments on spiral galaxies and stars.
Video Recommendation System in Internet Era

Abstract With the development of Internet technology, mining and analyzing a large number of network data has become a hot issue in the industry. Recommendation system can help solve the problem of information overload and provide accurate and fast recommendation information for users. This paper mainly summarizes the current popular recommendation methods, analyzes and compares the meaning of the popular recommendation algorithms. Finally, the application of recommendation algorithm in video industry is introduced.
Development of Creative Abilities of Students in the Conditions of Technological Education

The article considers the main trends in the development of creative abilities of students in the conditions of technological education. At the same time, the methods of developing students ' creative abilities in technological training are considered from the point of view of integrating the student's personality into the process of creative subject of self-development within the framework of the technology of personal-oriented Technology training. The study involved 263 students and 11 teachers from 10 schools in the Moscow region. The development and adjustment of the pilot program was carried out at the Department of professional education of the center for the development of professional education of the Academy of social management of the Moscow region. The activity approach made it possible to develop a methodology for developing students ' creative abilities in Technology lessons, which is based on the collective project activity of students. Creativity in the framework of the study was defined as the student's activity aimed at removing contradictions, solving a creative technological problem that has objective (social and material) and subjective (abilities and competence) factors, and its (activity) result has novelty, originality and social significance. The results show that the number of students who have a low level of development of creative abilities decreased by 82.3 % (10-12 years), 59.1 % (13-15 years), 71.2 % (16-17 years). The number of students with an average level of development of creative abilities (72.5%, 33.4%, 30.4%, respectively) and a high level of development of creative abilities has significantly increased (7,6 %; 21,4 %; 42,8 %). Developed scientific and methodological support (creation of models of problem situations in the framework of personality-oriented cases; activation of students ' creative activity by including teams of different ages for the implementation of technological projects; presence of a polyvariant creative environment; support for the personal trajectory of creative development of students 'collective creative projects) has proven to be effective in organizing the development of students' creative abilities in Technology lessons.
Municipal Level Teacher Growth System: Improving Pedagogical Design Skills

Innovations in the general education system have significantly changed the content and form of the teacher’s professional activity: pedagogical design has become a dominant feature in its structure. In this regard, there was a contradiction between the need for special training of teachers for the implementation of project activities and the lack of sufficient organizational and methodological conditions for the implementation of such training on the job. The purpose of this article is to justify the possibility of improving the skills of pedagogical design in the conditions of the implementation of the teacher growth system at the municipal level. In the course of theoretical analysis, the author substantiates the role and place of design in the structure of professional pedagogical activity. Based on the theoretical results obtained, the idea of building a subject-oriented process of teacher training, integrated with their immediate professional activity, is put forward. The description of the pedagogical experiment on testing the municipal system of teacher growth and the selected pedagogical conditions for the development of design skills of teachers is given. The results of the experimental work confirmed the hypothesis that the effectiveness of the process of improving teachers’ design skills is achieved by integrating the process of advanced training in labor activity, using a set of special forms and training methods (cases, design sessions, business games, trainings, master classes, tutoring programs, etc.), use of the principles of subject-oriented learning.
Tracelets and Tracelet Analysis Of Compositional Rewriting Systems.

Taking advantage of a recently discovered associativity property of rule compositions, we extend the classical concurrency theory for rewriting systems over adhesive categories. We introduce the notion of tracelets, which are defined as minimal derivation traces that universally encode sequential compositions of rewriting rules. Tracelets are compositional, capture the causality of equivalence classes of traditional derivation traces, and intrinsically suggest a clean mathematical framework for the definition of various notions of abstractions of traces. We illustrate these features by introducing a first prototype for a framework of tracelet analysis, which as a key application permits to formulate a first-of-its-kind algorithm for the static generation of minimal derivation traces with prescribed terminal events.
Multidimensional quantum communication without sharing basis information on the classical channel

We present a multidimensional quantum communication scheme that enables the sharing of information on the basis “non-classically”, encoding it in the same photonic qudits used for carrying the data in the quantum channel.