Reviewerly/exHarmony huggingface dataset:
USING OF INFORMATION TECHNOLOGIES IN DISTANCE LEARNING//Social Sciences: Achievements and Prospects Journal 1(14), 2022 (ISSN 2733-3825)/ Chief Editor Vitalii Vl. Klevtsov /OEAPS OU - Tallinn, Estonia (Open European Academy of Public Sciences): Berlin, Germany, 30.04.2022: OEAPS OU., 2022 - P. 23-26.

Distance learning can expand access to education and training for both general populace and businesses since its flexible scheduling structure lessens the effects of the many time-constraints imposed by personal responsibilities and commitments. The widespread use of computers and the internet have made distance learning easier and faster, and today virtual universities deliver full curricula online. The capacity of Internet to support voice, video, text, and immersion teaching methods made earlier distinct forms of telephone, videoconferencing, radio, television, and text-based education somewhat redundant. However, many of the techniques developed and lessons learned with earlier media are used in Internet delivery.
Cross – Language Information Retrieval

In today‘s growing nation, local database storage and retrieval is crucial for developing countries. A huge amount of information on Internet is available in numerous language that can be access by anybody at any time. Data Retrieval systems are fundamentally linguistic: the content or context of documents must be described, and the inquirers needed for documents must be expressed. These descriptions and expressions are most frequentlyarticulated in free or controlled vocabularies that have some of the same characteristics as natural language. Therefore, the processes of document description or request formulation must be strongly related to the processes of description and inquiry in natural language. Natural language processing is used to (a) preprocess the documents to extract content-carrying terms, (b) discover inter-term dependencies and build a conceptual hierarchy specific to the database domain, and (c) process the user's natural language requests into effective search queries. Since we assume that the information is primarily encoded as text, IR is also a natural language processing problem: to decide if a document is relevant to a given information need, one needs to be able to understand its content. CLIR deals with asking queries in one language and demand for retrieving documents in another language.This paper takes an overview of the new application areas of CLIR and reviews the approaches used in the process of CLIR research for query and document translation.
THE MAIN CHARACTER’S DEPRESSION IN JASMINE WARGA’S MY HEART AND OTHER BLACK HOLES

The topic of this research is the depression experienced by the main character in the Jasmine Warga’s My Heart and Other Black Holes with the formulation problem on how the form of depression in the main character is and the efforts made by the main character to overcome the depression that she is going through. This research uses the descriptive analysis method with data analysis techniques in the form of a literature study using the perspective of literary psychology and a psychological review of depression and intrinsic elements such as character and characterization, plot, conflict, and settings. The results of this study are that the main character experiences a major depression with various physical, psychological, social symptoms, emotional and motivational symptoms, and some triggering factors that are psychological factors with several self-defense mechanisms and the main character's efforts in overcoming her depression.Keywords: Depression; Main Character; Self-defense Mechanism; Overcome Depression.
Intrinsic dimensionality and generalization properties of the $\mathcal{R}$-norm inductive bias

We study the structural and statistical properties of $\mathcal{R}$-norm minimizing interpolants of datasets labeled by specific target functions. The $\mathcal{R}$-norm is the basis of an inductive bias for two-layer neural networks, recently introduced to capture the functional effect of controlling the size of network weights, independently of the network width. We find that these interpolants are intrinsically multivariate functions, even when there are ridge functions that fit the data, and also that the $\mathcal{R}$-norm inductive bias is not sufficient for achieving statistically optimal generalization for certain learning problems. Altogether, these results shed new light on an inductive bias that is connected to practical neural network training.
Clustering coefficients as measures of the complex interactions in a directed weighted multilayer network

In this paper, we provide novel definitions of clustering coefficient for weighted and directed multilayer networks. We extend in the multilayer theoretical context the clustering coefficients proposed in the literature for weighted directed monoplex networks. We quantify how deeply a node is involved in a choesive structure focusing on a single node, on a single layer or on the entire system. The coefficients convey several characteristics inherent to the complex topology of the multilayer network. We test their effectiveness applying them to a particularly complex structure such as the international trade network. The trade data integrate different aspects and they can be described by a directed and weighted multilayer network, where each layer represents import and export relationships between countries for a given sector. The proposed coefficients find successful application in describing the interrelations of the trade network, allowing to disentangle the effects of countries and sectors and jointly consider the interactions between them.
Adsorption Of Metal Lead (Pb) In Batik Industrial Wastewater Using Cellulose-Based Adsorbent: Literature Review

&lt;p&gt;This literature review aims to determine the characteristics of the batik industrial wastewater, the type of adsorbent activation method most widely used to adsorb lead (Pb) in the batik industry wastewater, and the correlation between the source of cellulose and parameters on the adsorption ability of lead metal (Pb) with variations in adsorbent mass, pH and contact time in batik industrial wastewater. This literature review was carried out in 7 steps: exploring topics, searching, storing, and organizing information, selecting the required information, expanding the search, analyzing, and evaluating. Information and present the results. This literature review shows that Batik industrial wastewater contains BOD, COD, TSS, and heavy metals. The literature review obtained that the BOD and COD values came from the batik industrial wastewater of Jetis Sidoharjo with a value of 1775.5 mg/L and 16654.80 mg/L, the largest TSS value came from the batik industrial wastewater Gedhog with a value of 449 mg/L. The largest metal content of lead came from the batik industrial wastewater of Wiradesa, with a value of 7.654 mg/L. The most widely used activation method for treating adsorbents is the chemical activation method with strong acids such as HCl, HNO&lt;sub&gt;3&lt;/sub&gt;, and H&lt;sub&gt;2&lt;/sub&gt;SO&lt;sub&gt;4&lt;/sub&gt;. There is a correlation between the source of cellulose and parameters in the adsorption of lead metal in batik industry wastewater. Different sources of cellulose and parameters resulted in different adsorption capacities. Based on the literature review, the highest percentage of cellulose was found in sawn teak (60%), corn cobs (41%), rice straw (37.71%), rice husks (34%), and kapok seeds (21.83%). Maximum adsorption lies in the adsorbent with a mass of 0.1 – 1g, pH 5-7, and 30-45 minutes contact time. &lt;/p&gt;
CoSe-Co: Text Conditioned Generative CommonSense Contextualizer

Pre-trained Language Models (PTLMs) have been shown to perform well on natural language tasks. Many prior works have leveraged structured commonsense present in the form of entities linked through labeled relations in Knowledge Graphs (KGs) to assist PTLMs. Retrieval approaches use KG as a separate static module which limits coverage since KGs contain finite knowledge. Generative methods train PTLMs on KG triples to improve the scale at which knowledge can be obtained. However, training on symbolic KG entities limits their applicability in tasks involving natural language text where they ignore overall context. To mitigate this, we propose a CommonSense Contextualizer (CoSe-Co) conditioned on sentences as input to make it generically usable in tasks for generating knowledge relevant to the overall context of input text. To train CoSe-Co, we propose a novel dataset comprising of sentence and commonsense knowledge pairs. The knowledge inferred by CoSe-Co is diverse and contain novel entities not present in the underlying KG. We augment generated knowledge in Multi-Choice QA and Open-ended CommonSense Reasoning tasks leading to improvements over current best methods on CSQA, ARC, QASC and OBQA datasets. We also demonstrate its applicability in improving performance of a baseline model for paraphrase generation task.
PEMANTAUAN MENTOK RIMBA (ASARCORNIS SCUTULATA) BERBASIS SISTEM INFORMASI GEOGRAFIS DI TAMAN NASIONAL WAY KAMBAS

Forests play a major role in supporting the survival of all living things in the world. A sustainable forest area certainly makes the wildlife live, e.g mentok rimba. A Geographic Information System for Monitoring mentok rimba (Asarcornis scutulata) applying the V-model approach. This research was conducted under programme of Way Kambas National Park and ALeRT (Aliansi Lestari Rimba Terpadu). The purpose of this research is to assist the monitoring team in Way Kambas National Park for updating mentok rimba data. Black Box Testing and User Acceptance Testing were applied. A Geographic Information System (GIS) which contains the distribution of forest stagnation in Way Kambas National Park was built.
ANALISIS SENTIMEN TWEET KASUS KEBOCORAN DATA PENGGUNAAN FACEBOOK OLEH CAMBRIGDE ANALYTICA

The case of the Facebook user data leak by Cambridge Analytica has been spotlight in the public lately. Many of the citizens has participated discussing this case, especially in social media Twitter. Sentiment analysis is a computational research of opinions and emotions sentiment that are expressed textually. This study aims to classify positive and negative sentiment from Twitter data and to determine the accuracy of the classification model using Naïve Bayes Classifier method. Based on experiment conducted by tweet data with the “Zuckerberg” and “Cambridge Analytics” keywords, it has been produced Naïve Bayes Classifier with an accuracy of 83.06%.
Finite-Time Analysis of Fully Decentralized Single-Timescale Actor-Critic

Decentralized Actor-Critic (AC) algorithms have been widely utilized for multi-agent reinforcement learning (MARL) and have achieved remarkable success. Apart from its empirical success, the theoretical convergence property of decentralized AC algorithms is largely unexplored. Most of the existing finite-time convergence results are derived based on either double-loop update or two-timescale step sizes rule, and this is the case even for centralized AC algorithm under a single-agent setting. In practice, the \emph{single-timescale} update is widely utilized, where actor and critic are updated in an alternating manner with step sizes being of the same order. In this work, we study a decentralized \emph{single-timescale} AC algorithm.Theoretically, using linear approximation for value and reward estimation, we show that the algorithm has sample complexity of $\tilde{\mathcal{O}}(\varepsilon^{-2})$ under Markovian sampling, which matches the optimal complexity with a double-loop implementation (here, $\tilde{\mathcal{O}}$ hides a logarithmic term). When we reduce to the single-agent setting, our result yields new sample complexity for centralized AC using a single-timescale update scheme. The central to establishing our complexity results is \emph{the hidden smoothness of the optimal critic variable} we revealed. We also provide a local action privacy-preserving version of our algorithm and its analysis. Finally, we conduct experiments to show the superiority of our algorithm over the existing decentralized AC algorithms.
SMOOTHED CONTOUR DETECTION METHOD FOR ARBITRARY SHAPE OBJECT OF IMAGES

Description of initial raster image objects by a set of contour vertices coordinates leads to increase efficiency of the retrieval, classification and recognition of graphical data in information systems. In this paper the smoothed contour detection method for objects of raster images is considered. The developed method is based on application of interpolation function for partial differential equation solutions and smoothed function for post-processing of detected contours. The accuracy of contour reproduction for raster image objects is increased on 4.87% by applying the developed method compared to the discrete method of contour detection.
Matching Pursuit Based Scheduling for Over-the-Air Federated Learning

This paper develops a class of low-complexity device scheduling algorithms for over-the-air federated learning via the method of matching pursuit. The proposed scheme tracks closely the close-to-optimal performance achieved by difference-of-convex programming, and outperforms significantly the well-known benchmark algorithms based on convex relaxation. Compared to the state-of-the-art, the proposed scheme poses a drastically lower computational load on the system: For $K$ devices and $N$ antennas at the parameter server, the benchmark complexity scales with $\left(N^2+K\right)^3 + N^6$ while the complexity of the proposed scheme scales with $K^p N^q$ for some $0 < p,q \leq 2$. The efficiency of the proposed scheme is confirmed via numerical experiments on the CIFAR-10 dataset.
MODERN ASPECTS OF STUDYING RUSSIAN TERMINOLOGY BY INTERNATIONAL STUDENTS AT THE PREPARATORY DEPARTMENT IN A TECHNICAL UNIVERSITY

In this study, one of the aspects of teaching Russian as an international language, namely the teaching of mathematical terms in the preparatory department of a technical university in Russia, is considered. The relevance of this subject has arisen due to the growing number of international students in Russian universities and the need for them to master the Russian language as soon as possible to continue their studies at Russian universities. This work aims to describe the learning process of Russian scientific vocabulary and terminology of technical disciplines, especially the language of mathematics, by international students from the countries of the former Soviet Union studying at the Preparatory Department of Tomsk State University of Architecture and Civil Engineering. The complexity of mastering scientific vocabulary in Russian arises from the characteristic differences between Russian and Turkic languages. A linguistic experiment was conducted in which students heard and wrote down scientific terms, words, and phrases in Russian. Students were given a dictation test rich in scientific vocabulary. The results have been gathered, and numerous errors in spelling scientific terms have been pointed out. Studies in Russian universities take place mainly in Russian, with active use of scientific vocabulary, which is extremely difficult for people who are just beginning to learn Russian. After correcting the mistakes and explaining the correct spelling of the words, the dictation is repeated. The results obtained are compared. The features of deviations from the norm are identified, described, and structured, and options for working on the implementation of a program for the development of normative writing skills in international students are suggested. For example, it is quite challenging to determine the boundaries of a word, to identify differences between prefixes and prepositions, the normative spelling of vowels in the endings of nouns, adjectives, and verbs, and the spelling of fricative consonants.
RISKS OF ARCHAIZATION IN THE PROCESS OF REGIONALIZATION OF HIGHER EDUCATION

Objective of the study is to identify the risks of archaization in the process of regionalization of higher education as an integration of the cultural-historical, economic-economic and socio-value component within the framework of the activities of the regional higher education to ensure sustainable development in the Russian regions. &nbsp; Methodological basis of the research constitutes a transdisciplinary approach to the definition of the concept of “archaization”. Research results. Based on the conceptual analysis, it is concluded that the risks of archaization as imitation and reproduction of pre-civilizational forms contain a challenge to the modernization of higher education in the form of replacing values ​​as a cultural and historical heritage with archaisms oriented towards retromodernism, self-isolation, which creates a state of adaptation, but does not contribute to the regionalization of higher education. education. Understanding the risks of archaism in the structural, organizational and activity parameters contributes to the policy of limiting archaisms in higher education and transferring work to ensure continuity in the development of the university system. &nbsp; &nbsp; Prospects of the study are related to the assessment and revision of traditions and innovations in higher education, and in this context, the analysis the relationship between archaic and traditional at the regional level is relevant. &nbsp
The YiTrans End-to-End Speech Translation System for IWSLT 2022 Offline Shared Task

This paper describes the submission of our end-to-end YiTrans speech translation system for the IWSLT 2022 offline task, which translates from English audio to German, Chinese, and Japanese. The YiTrans system is built on large-scale pre-trained encoder-decoder models. More specifically, we first design a multi-stage pre-training strategy to build a multi-modality model with a large amount of labeled and unlabeled data. We then fine-tune the corresponding components of the model for the downstream speech translation tasks. Moreover, we make various efforts to improve performance, such as data filtering, data augmentation, speech segmentation, model ensemble, and so on. Experimental results show that our YiTrans system obtains a significant improvement than the strong baseline on three translation directions, and it achieves +5.2 BLEU improvements over last year's optimal end-to-end system on tst2021 English-German. Our final submissions rank first on English-German and English-Chinese end-to-end systems in terms of the automatic evaluation metric. We make our code and models publicly available.
Correction: Peng et al. A Fast Three-Dimensional Convolutional Neural Network-Based Spatiotemporal Fusion Method (STF3DCNN) Using a Spatial-Temporal-Spectral Dataset. Remote Sens. 2020, 12, 3888

In the original article [...]
The Other Hegemony: Effects of software development culture on music software, and what we can do about it

NIME has recently seen critique emerging around colonisation of music technology, and the need to decolonise digital audio workstations and music software.Â While commercial DAWs tend to sideline musical styles outside of western norms (and even many inside too), viewing this problem through an historical lens of imperialist legacies misses the influence of a more recent - and often invisible - hegemony that bears significant direct responsibility: The culture of technological development. In this paper we focus on the commercial technological development culture that produces these softwares, to better understand the more latent reasons why music production software ends up supporting some music practices while failing others. By using this lens we can more meaningfully separate the influence of historic cultural colonisation and music tech development culture, in order to better advocate for and implement meaningful change. We will discuss why the meaning of the term âdecolonisationâ should be carefully examined when addressing the limitations of DAWs, because while larger imperialist legacies continue to have significant impact on our understanding of culture, this can direct attention away from the techno-cultural subset of this hegemony that is actively engaged in making the decisions that shape the software we use. We discuss how the conventions of this techno-cultural hegemony shape the affordances of major DAWs (and thereby musical creativity). We also examine specific factors that impact decision making in developing and evolving typical music software alongside latent social structures, such as competing commercial demands, how standards are shaped, and the impact of those standards. Lastly, we suggest that, while we must continue to discuss the impact of imperialist legacies on the way we make music, understanding the techno-cultural subset of the colonial hegemony and its motives can create a space to advocate for conventions in music software that are more widely inclusive.
Usability testing with children: History of best practices, comparison of methods and gaps in literature

This paper is a systematized literature review centered on the best practices of usability testing with children, when they are the target end user in product development.The paper begins with a brief history of usability testing with children during the prototyping stage of product development.Following, the methodology guiding this literature review is described.Then, guidelines for usability testing with children provided by past research are outlined in chronological order, documented to show the evolution of changes or improvements in the practices over time.Additionally, most of the approaches to usability (as part of evaluative research) have been identified and compared between one another with a variety of factors.In conclusion, directions for further research are suggested based on current unanswered questions in the field of prototype usability testing with children, such as considerations for longitudinal vs. cross-sectional testing, physical vs. digital product testing, and age range of children.
Pieces Analysis to Improve Performance Cash Sales System: A Case Study on The Darmo Deli Supermarket

Darmo Deli Supermarket is a growing retail company. Cash sales is the main source income for that company. In order to improve its performance, it is deemed necessary to conduct an analysis of the cash sales system at the Darmo Deli supermarket. A qualitative approach with observation, interviews, and documentation was used to obtain information about the cash sales flow and system that had been implemented. PIECES analysis has 6 aspects, performance, information, economic, control, efficiency and service. The results of the study show that the Darmo Deli Supermarket cash sales accounting information system has no warehouse section. Based on PIECES analysis, the control aspect of the cash sales system needs to be improved. So that, the fraudulent sales data reporting can be avoided, velocity and accuracy of financial reports in Darmo Deli Supermarket cash sales system can enhanced.